Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by devising three heuristic solvers aimed at efficiently scheduling tasks in robotic swarms, which collaborate together to accomplish a mission, and by presenting experimental results obtained over realistic scenarios in the underwater environment. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks and the relative execution order of such tasks within the schedule of certain robots. The obtained results reveal interesting differences in terms of Pareto optimality and spread between the algorithms considered in the benchmark, which are insightful for the selection of a proper task scheduler in real underwater campaigns. Scheduling problems can be widely conceived as the family of optimization paradigms focused on allocating jobs or tasks over time subject to mutually affecting constraints such as the restricted availability of resources needed to complete the work or a maximum commit time beyond which all tasks should be completed. Scheduling lies at the very core of production processes and operational logistics of many different fields of knowledge, within which the interest in new algorithmic perspectives capable of efficiently dealing with scheduling problems of high dimensionality has become specially notable during the last few years, e.g., manufacturing and service industry ,2,3, robincrementally with respect to) the current schedule. In this application domain the main sources of uncertainty encountered in a real setup can be enumerated as: (1) robot or underwater vehicle malfunctions, including uncertain repair times; (2) increased priority of tasks; and (3) change in due dates, plan, and/or order cancellations, among others. Whenever any of such unexpected event occurs, a new scheduling decision must be made on the reordering of tasks (or new plan with different tasks) in real time. This process is often referred to as “rescheduling”, whose main objective is “to find immediate solutions to problems resulting from disturbances in the system” 14], HarmIn this paper the focus is placed on underwater collaborative task scheduling, in which a group of underwater vehicles  together with other support vehicles (USVs) collaborate with each other to accomplish a set of tasks. In off-shore and maritime missions there are several scenarios such as the monitoring of chemical pollution, the detection/inspection/tracking of plumes or ocean surveying, where a collaboration among underwater vehicles is required in order to accomplish the scanning of a set of areas. In this proposal, the main idea gravitates on the intuition that, given certain areas to be scanned, an algorithm should be able to calculate which the optimal set of vehicles is and which path they should follow to fulfill the mission tasks optimally in terms of time and cost , taking into account restrictions such as the distance to the starting point or underwater currents. Examples of tasks involved in the scanning of an area are “move to waypoint”, “follow row”, “measure” or “take samples”  and m (robot) is made explicit.In reference to j is an integer number denoting the relative position of task m.Differences among robots to complete the tasks come along with a higher operational price (cost) when robots with short completion times are assigned to any task within the mission. This cost collects and represents penalties arising from a more extensive allocation of high-performing robots in favor of shorter completion times of the overall mission. Such penalties can be exemplified by a higher expected energy consumption of the robot when moving quicker through the underwater medium due to the higher dynamic resistance of the water. Cost, furthermore, is also roughly determined by the order in which the task is performed along the scheduling of each robot. The cost incurred by a robot m to task m along time   2) we wiWe start by delving into the first solver considered in this study, the Harmony Search (HS) optimization algorithm, which was coined by Geem et al. in  and subsharmony, whereas note denotes any of its compounding N entries. In our optimization framework each note is encoded based on a Random-Keys (RK) strategy [In this paper we focus on deriving a multi-objective version of the HS algorithm that attempts at simultaneously minimizing the aforementioned fitness functions: total time and cost. Due to its population-based search procedure, HS operates on a set of candidate solutions strategy , by whicTo decode a RK-encoded individual all notes sharing the same value for their integer part are grouped and sorted in increasing order of the value of their fractional part. This process results in the planning of tasks for every robot. For instance, the solution vector In the literature RK has been utilized to represent solutions of evolutionary solvers that handle task plans, often improved further by means of local search procedures  or otherHarmony Memory Considering Rate   2) are eBased on such metric values, a rank and a crowding distance value are assigned at each solution. As explained in  candidatIf the number of iterations is less than Once new harmonies have been improvised, they are evaluated in terms of the two objective functions (mission completion time and cost) for every improvised melody, and the best  Algorithm 1: Multi-objective Harmony Search Algorithm (MOHS).Originally contributed by Deb et al. in , the NSGNSGA-II has been widely utilized in scheduling. For example, in  an hybriPAES  is a mulAlgorithm 2: Non-Dominated Sorting Genetic Algorithm-II (NSGA-II)Algorithm 3: Pareto-Archived Evolution Strategy (PAES)In order to assess the performance of the above multi-objective solvers when applied to the underwater collaborative scenario described in preceding sections several computer simulations have been carried out over different hypothesis posed over the operational circumstances under which the deployed robots operate. Such simulation scenarios are described next.The aim of the real simulation setup presented in this paper is to handle several robots and plan their actions so as to optimize the whole mission costs.A and record video to detect objects). For this demonstrator, the focus is put on “area” tasks related to a “seabed mapping” scenario, in which the mission comprises scanning the area, taking measurements, navigating and providing information to the operator. The exchanged information includes diverse actions such as the acquisition of images and/or videos, the delivery of measurements from different sensors onboard or even additional parameters acquired by equipment that is switched on or off on demand. That being so, to define a seabed mapping scenario, apart from defining the tasks that comprise the mission, the first step is to define the set of available robots and the areas of interest, as shown in The site used for the trials is the open sea waters of the Melenara Bay located on the East coast of Gran Canaria , but also to their price and incurred cost when undertaking a certain task; each robot may require different time and battery cost to carry out a certain task. Moreover, it is important to note that by means of dividing the global area into subareas and enabling AUVs cooperation, the whole area could be covered performing a faster real-time mapping and inspection of the area.As mentioned in Mission definition: the operator draws on a map in the GUI the set of areas to be mapped. The system informs the operator which robots are available and their configurations.Multi-objective scheduling algorithm: to optimize the whole mission and coordinate the robots, the system needs a planning model describing the available objects and their possible tasks. Given this model, the proposed heuristic algorithms compute the best sequence of actions performed by the robots, i.e., the plan.Gantt chart view of the task plans for each robot: the mission plan consists of a list of tasks assigned to each robot. Plans are shown as paths on the map and Gantt charts, showing the duration of the tasks and the order of execution for each robot.Once the algorithm has optimized the task schedule for each member of the entire robotic swarm, the operator selects the best candidates among the proposed solutions. The output of the solver, now integrated into the human-machine interface, has revealed that they are capable of planning the mission of up to four robots, covering diverse areas to be scanned with computation time in the order of a few minutes’ computation time. In summary, the GUI entails the following steps:Since this study is focused on the multi-objective scheduling algorithms themselves, the results provided in the next subsection describes quantitatively the task schedules produced by each of the algorithms.In order to assess the performance rendered by all multi-objective approaches proposed in this paper, namely MOHS, NSGA-II and PAES, a comparison study in a real scenario in Gran Canarias (Spain) will be presented and discussed. In this real scenario a total of Simulation results consider: (1) a baseline scenario in which robots are located relatively close to each other and without battery limitations; (2) a battery-limited scenario in which robot There are different complementary multi-objective performance metrics that can be employed in order to evaluate the quality of the approximated Pareto fronts obtained by multi-objective approaches. On one hand, cardinality metrics refers to the number of solutions that exists in the resultant Pareto Front; intuitively, a high number of solutions—and hence a high value of such metrics—is preferred. In this context, In terms of diversity metrics, Finally, the coverage rate metric (%) presented in This work has formulated a joint task assignment and scheduling problem framed within monitoring and inspection underwater missions performed collaboratively by robot swarms. Optimality in this problem is defined by the minimization of two conflicting criteria: the completion time of the mission and its cost, the latter defined as a numerical score of the impact that the assignment and scheduling of tasks imprints on certain parameters of interests of the deployed robots . To efficiently deal with this multi-objective paradigm, a set of different multi-objective meta-heuristics, namely NSGA-II, PAES and MOHS, have been designed by using a RK encoding strategy, by which solutions simultaneously represent both the mapping from tasks to robots and the scheduling of tasks within every robot commit.The performance of such heuristics has been assessed over three realistic scenarios deployed in Gran Canarias (Spain) in terms of different multi-objective performance indicators, which quantify the cardinality, distribution and spread of the obtained non-dominated solutions. The obtained results highlight the importance of achieving a wide Pareto front and diversity of results. In this context, both NSGA-II and MOHS attain a higher explorative behavior than PAES. Nevertheless, in terms of hypervolume MOHS renders the best performance metrics in the majority of scenarios, especially in those under operational constraints in which PAES clearly fails to explore the search space efficiently and consequently yields the worst results.Future research will be devoted towards spanning the portfolio of algorithms in the benchmark . Furthermore, the real scenario inspiring this work calls for further constraints in the posed optimization problem, such as the inclusion of relationships of dependence between tasks, the availability of charging depots in the mission area or the transfer of unfinished tasks between robots. All these ingredients will be formulated and added to the problem statement in the near future.


Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node– continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches. WMSNs are capable of capturing audio-video information by using low-cost cameras embedded with sensor nodes. The multimedia sensors provide substantial information related to a particular area of interest ,3,4,5,6.The connectivity is a severe problem subject to the mobility change when the network has been set up. The sensors nodes try to identify new neighbors to address mobility problems, but a hidden node problem is a hurdle. Initial neighbor node discovery is typically performed when the sensor node has no proof about the configuration of its immediate neighbors. In this situation, the sensor node is unable to communicate with either the base station or the sink station. Thus, immediate neighboring nodes should be detected as soon as possible to set a path to the base station and contribute to the operation of the network ,12. HencIn order to handle the hidden node and coverage problem, our approach contributes the Obstacle-driven Negative Effect Strategy (ONES) method that handles the negative effect of the obstacles. The proposed method is designed for those scenarios where the number of the relays are less than those of relays required for building steady links. In addition, it is particularly suitable for those multimedia sensor networks that suffer due to several disconnected subdivisions of the network that are experiencing the issue of obstacles among the subdivisions. The method is validated by applying several assumptions and definitions. This helps reduce energy consumption and maintaining the QoS.Furthermore, our paradigm contributes the Optimized Hidden Node Paradigm that involves the hidden node detection, message exchange phase, and location detection. Our paradigm is different from existing hidden node approaches, as we focus on the multiple discoveries of nodes rather than a single discovery of node. The approach is particularly designed for a distributed network as most of the existing approaches follow the central-based network in the node discovery process, which is also expensive for location-updating. We focus on improving the QoS and extending the network life. Thus, a network is divided into different subdivisions and is controlled by a coordinator node, as the subdivision process helps multimedia sensor nodes cover the entire area efficiently. The network life extension is justified with the proper selection of a controlling node using metrics such as residual energy, data forwarding capacity of the node, distance of the node from the base station, and memory allocation. These metrics are assigned the specific weightage that provides enough chance for each node to be a coordinator and balance the network. Handling the problem of overlapped subdivisions in the network particularly when a new joining node attempts to be a part of either subdivision is a critical issue that has also been handled by a priority-based synchronization.The random wake-up procedure is applied to reduce the option of repeating collision amongst the nodes in the same subdivision. The beauty of our random wake-up process that it provides an opportunity for each node to coordinate with its neighborhood nodes to avoid the collision and initiate a faster discovery process for the new joining hidden node. In addition, each node applies an active discovery process to detect its coordinator node, whereas in the existing approaches, the coordinator (head node) is responsible for detecting its nodes in its subdivision, which puts an extra burden on the coordinator node. However, our approach handles this issue by assigning responsibility to each node to detect its coordinator node in each subdivision. Unlike existing approaches, our paper also contributes the novel location detection procedure that helps detect the maximum view, node boundary and viewpoint of multimedia sensor node; existing approaches either apply a node boundary or node view to detect the location. The remainder of the paper is organized as follows: In this section, related WMSN approaches are discussed. Previous works discuss maximizing the coverage area and detecting the hidden nodes in the fields of wireless sensor networking, ad-hoc networks, and robotics. However, little research has been done in wireless multimedia sensor networking. Some addresses an omnidirectional coverage problem in wireless sensor networks ,14, but R: sensing radius of sensors). The neighbor discovery node process is proposed in  to regulIn , virtualHere, we consider the wireless sensor network that is divided into several subdivisions and suffered because of disconnected subdivisions; it also experiences the issue of the obstacles among the subdivisions. In the network, each subdivision is controlled by the coordinator node. The coordinator node has a communication range Assumption 1: All the relay nodes are mobile sensor and responsible for on-demand delivery as depicted in Assumption 2: There is at least one edge that interconnects the obstacles. Each obstacle is not overlapped with subdivisions.Assumption 3: Letbe the count of subdivision. The number of available mobile relay nodes responsible for dealing with on-demand multimedia service should satisfy the following condition:where: Total relay nodes.Definition 1: Given an undirected graphwith subdivisions (segments)and edgescan be written as. Thus, the set of subdivisions areand edges.. Let obstacle-driven negative effect strategy ‘Ψ’ be Ψ = , wheredenotes the set of edges of (ONES). Letand, where: Euclidean distance of subdivision,: deleted edges.Definition 2: The number of relay sensor nodes between subdivisionscan be denoted byThus,can be obtained by:Definition 3: Letrepresents the total number of the relay needed to generate the steady network topology. Thus,can be obtained by:Hence, obstacle-driven negative effect strategy can be simplified asthat is the set of subdivisions and set of obstacles are. wherecannot be overlapped with subdivision. Thus,denotes the total relay nodes to create the steady network topology. Letbe the available relays for on-demand multimedia contents, wheresatisfies following condition:Hidden Node DetectionMessage Exchange PhaseLocation DetectionAn optimized hidden node detection paradigm is introduced for distributed wireless multimedia sensor networks because the sensor nodes are deployed in a disseminated manner within a realistic environment. On the other hand, centralized location deployment is not appropriate for WMSNs because these networks encompass a large number of multimedia nodes. Furthermore, updating the location is expensive within a centralized approach when compared to a distributed approach. Our approach consists of three phases:Detecting a hidden node in WMSNs is the critical problem that affects the network performance. Hence, the efficient neighbor discovery process helps in hidden node detection. In this phase, we focus on a continuous neighbor discovery process to determine the hidden nodes. Each sensor node uses a coordination-driven approach, and we chose the 1-hop multiple neighborhood discovery process rather than the particular node-discovery in the network that helps detect all hidden nodes at the1-hop neighborhood. As a result, the network consumes a minimum amount of energy and has a collision-free process. In this approach, the nodes share the schedule as discussed in . The netThe hidden node detection process applies a random wake-up procedure to reduce the option of repeating collisions amongst the nodes in the same subdivision. In this phase, each node coordinates with its neighborhood nodes during the wake-up period to avoid collisions and make a faster discovery process of any new joining hidden node. The wake up time period is very small, and the time of forwarding the HELLO message is even smaller. In this case, there is a possibility that two nodes can be active at same time and initiate the neighbor node discovery process. Therefore, we use a scheduling method to control the wake up process of two nodes at the same time. During the scheduling, the nodes are required to be synchronized with each other and report to the coordination node. During the scheduling, each receiving node chooses time slots and obtains the data during those time slots. The time slot process is performed without contradicting the schedule of the other node. This is the reason that the neighbor nodes are subdivided into different subdivisions, where each node chooses its slot assigned to that subdivision. Each sensor node decides randomly when to initiate the transmission of a HELLO message. If its message does not strike with another HELLO message, the node is referred to as a discovered node. We can also determine residual energy and the load of each node after the node discovery process occurs.Let us assume that each sensor node communicates at the distance of the single-hop node to detect the hidden nodes. Each sensor node sends the HELLO message ‘Hm’ at the distance ‘d’ within the subdivision ‘Sd’ and is located at the N × N area of WMSN. The residual energy of the two types of multimedia sensor nodes, the coordinator node ‘C’ and the non-coordinator node ‘Cn’, can be determined as follows.The coordinator node performs four types of jobs that include the synchronization with newly joined nodes, broadcasting the information of newly joined nodes inside the subdivision, scheduling the transmission of subdivision, and data collection from non-coordinator nodes of the subdivision. The synchronization process between the newly joined node and the coordinator is explained in Algorithm 1. Algorithm 1: Priority-based synchronization process between coordinator and newly joined nodesInitialization:  shows the consumed energy by coordinator node for synchronization:Equation (4) shows the consumed energy for broadcasting the message (disclosing the information of newly joined nodes to the subdivision nodes):Equation (5) shows the consumed energy by coordinator node for scheduling with subdivision nodes:Equation (6) shows the consumed energy by coordinator node for collecting and forwarding the data.We can determine the residual energy of the coordinator node and non-coordinator nodes based on the energy consumption for four tasks given by Equations (7) and (8), respectively:Determining the node’s load is significant for hidden node discovery. The load factor When the nodes that are available at the distance of a one hop neighborhood node of coordinator node receive the messages they start calculating distance from the coordinator node to detect the hidden nodes depicted in Hence, the straight distance is at the possible values  used in  is appliIn this phase, the multimedia sensor nodes exist at a 1-hop neighborhood node that initiates the message exchange process to gather the information about the neighboring nodes. All sensor nodes use unicast addressing methodology that refers to the neighbor handshake indication (NHI) process. The NHI contains the identity of the nodes and the current location of the multimedia sensor node. Let us assume that the mobile multimedia sensor node comprises an identical standpoint and a list of overlapped neighbor nodes that are accessible in the same sensing position that yields the NHI. This aims to guarantee that each multimedia sensor node should detect their neighbor’s hidden nodes and their location:In Equation (10), the total neighbor nodes In Equation (11), multimedia sensor node unicasts the neighbor handshake indication process that contains node identity In Equation (12), each neighbor node returns the message The location detection of the sensor node is of paramount significance for continuous communication. Thus, there are several events that can be implicitly adjusted and responded to only if the correct location of the event is detected. The location detection plays a key role for understanding the multimedia- application- contents. There are three advantages of detecting the location of the multimedia sensor node. First, location detection is required to determine the event of the interest. For example, the location of a fire, location of an intruder, or the location of the opponent’s tank in the arena are critical for deploying the relief troops and rescue squads. Second, location detection enables several application services, such as helping doctors to gain the information of medical gears and personnel in smart hospitals. Third, the location detection helps in several system functionalities, such as network coverage checking, geographical routing, and location-based information querying. This phase helps to detect a sensor’s maximum view. The location detection involves the node boundary and viewpoint. In the node boundary, we detect the area in which the node is capable of broadcasting the message. The viewpoint covers the degree of the node from 0 to 360 in which the node can be located at any degree. First, the node attempts to determine the location of the neighbor node within the boundary by broadcasting the message. If a node fails to locate the node within the boundary, then it initiates the neighbor distance search process by checking the distance of the node viewpoint of the neighbor node. Last, if the previous process fails, then an obstacle-distance process is used . If the The average location detection time is an important factor that helps determine the detection capacity of the multimedia sensor nodes. As such, this feature has an impact on the performance and extensibility of the network. Thus, Equation (14) provides an average location detection time for each multimedia sensor node as follows:In To validate the effectiveness of our proposed optimized hidden node detection paradigm for wireless multimedia sensor networks, we performed the simulation by using network simulator-NS2. The network is constructed to cover 1200 × 1200 square meters. The 270 multimedia enabled nodes are randomly distributed with homogenous capabilities. The initial energy of each node is set at 7 joules. The simulation aims to identify the coverage and network efficiency in the presence of hidden nodes. Furthermore, the performance of OHND is compared with other known mechanisms handling the issue of hidden nodes: Line Of Sight Method (LOSM) , EfficieWe designed three scenarios that include both hidden nodes and without hidden nodes. In the first scenario, each multimedia sensor node hears 20 out of 30 of the other multimedia sensor nodes. This gives a 66.666% probability of detecting the hidden nodes without wasting additional energy. In the second scenario, 10 out of 30 multimedia sensor nodes can hear other nodes that give a 33.33% probability to detect the hidden nodes. In the third scenario, all end nodes that contribute in the network can listen to each other. The distance between each multimedia sensor node is set at 40 meters. These three scenarios demonstrate expected, worst, and ideal scenarios, respectively. All nodes are completely constructed using the angle Multimedia Throughput EfficiencySuccessful Packet Delivery RatioNetwork AccuracyEnergy Consumption with Hidden NodesBased on simulation, we obtained these results:To confirm the multimedia throughput-efficiency of our proposed optimized hidden node detection, we created three scenarios: the worst case, the expected case, and the ideal case. In the worst case scenario, we used 18–27 maximum obstacles depicted in One of the drawbacks of the hidden node in WMSNs is to drop the packets due to collisions. As a result, the quality of service is highly affected. Successful packet delivery ratio can be shown in Equation (15):Network accuracy is highly affected due to the presence of hidden nodes. Thus, end- to- end delay including processing, propagation delay, and time synchronization between the two end-to-end-points are extended. As a result, the network does not perform as expected and throughput performance is greatly degraded. In The reason for better network accuracy in our case is the use of a random wake-up procedure that reduces the option of repeating collision amongst the nodes in the same subdivision. The beauty of our random wake-up process is to provide a chance for each node of coordination with its neighborhood nodes in avoiding a collision and initiating a faster discovery process for a new joining hidden node.The performance of the OHND approach was evaluated by using 500 rounds with a constant frame size of 512 data frames (including payload and data frame format). We performed several runs to determine the energy consumption of our proposed approach. The hidden node problem creates a real threat to any type of multimedia wireless sensor network application. This paper introduces an optimized hidden node detection paradigm to improve the quality of service of the wireless multimedia sensor networks. Our paradigm consists of three phases: hidden node detection, message exchange phase, and location detection. These three phases resolve the hidden node problem and improve the network performance and QoS provision. The message exchange phase is responsible for detecting overlapped and non-overlapped areas of multimedia sensor nodes. The location detection phase determines the correct location of each multimedia node which helps improve the coverage efficiency of multimedia sensor nodes. Furthermore, the hidden node detection phase identifies the load and residual energy of the nodes when performing the discovery process. To determine the strength of our proposed OHND, we used NS2 and also compared the performance with other competing approaches: LOSM, EBSAHN, HNP, and CMDHN. The results demonstrate that our OHND improved multimedia coverage, energy consumption, and the packet delivery ratio when compared to other approaches. Furthermore, OHND has a hidden node detection capacity that is 0.8%–4.1% higher than the other the approaches. The simulation results confirm that our proposed paradigm is capable of determining hidden nodes for WMSNs application. In future research, we will implement our proposed OHND in a hardware-based environment.


We assume that for keeping their BCR responsive, B cells must maintain partial BCR saturation, which is a narrow region defined by [Ag]≈KD. To remain in this region, B cells respond to changes in [Ag] by proliferation or apoptosis and modulate KD by changing BCR structure. We apply this framework to various niches of B-cell development such as the bone marrow, blood, lymphoid follicles and germinal centers. We propose that clustered B cells in the bone marrow and in follicles present antigen to surrounding B cells by exposing antigen captured on complement and Fc receptors. The model suggests that antigen-dependent selection in the bone marrow results in (1) effector BI cells, which develop in blood as a consequence of the inexhaustible nature of soluble antigens, (2) memory cells that survive in antigen rich niches, identified as marginal zone B cells. Finally, the model implies that memory B cells could derive survival signals from abundant non-cognate antigens.In a pair of articles, we present a generalized quantitative model for the homeostatic function of clonal humoral immune system. In this first paper, we describe the cycles of B-cell expansion and differentiation driven by B-cell receptor engagement. The fate of a B cell is determined by the signals it receives via its antigen receptor at any point of its lifetime. We express BCR engagement as a function of apparent affinity and free antigen concentration, using the range of 10 The enormous progress of bioinformatics, computation and mathematical modelling of biological phenomena is currently transforming all fields of biology, including immunology. The main intention of development of the model presented here is to provide a general quantitative framework for describing antibody–antigen interactions. General because we attempt to insert all key developmental and differentiation events of B cells into the model in our first article and all key soluble antibody-mediated antigen recognition phenomena in our second article. Quantitative because we insert these events into a coordinate system clearly defined by concentration and affinity. While we try to address some questions about molecular mechanisms within the cells, effects of cytokines and chemokines, adhesion molecules, interactions with T cells, it is beyond the scope of the paper to answer those questions. Rather, we focus strictly on interactions of surface or soluble immunoglobulins and antigens, yet being aware that B cells have several functions other than antibody production. The assumptions required for the development of the model place the known phenomena in new perspectives and may also provide unexpected answers to existing questions.1 and are found throughout the body, reaching various tissues and organs via the blood and the lymphatics. B cells are defined by their ability to rearrange the genetic loci coding the surface immunoglobulin (sIg) of the B-cell antigen receptor (BCR) complex and by their ability to secrete antibodies in later stages of their development.2 Surface or membrane Ig is composed of a heavy and a light chain that are linked by disulfide bonds in a L-H-H-L stoichiometry. The BCR complex contains in addition to the sIg various transmembrane and intracellular molecules that modulate signaling via the BCR.3 This signaling is vital for all B cells from the moment of their commitment, since these signals drive survival, differentiation or death of the cell. Starting with the expression of the surrogate light chain, B cells go through several cycles of activation, proliferation, survival and antibody production, all governed by BCR engagement.B cells are lymphocytes, ‘cells of the lymph', which are present in the blood as part of the mononuclear cell fraction of white blood cells. They are produced in the bone marrowM to pM concentration range in the blood.4 External antigens may reach high concentrations at the site of entry and become diluted out by degradation or elimination. Complete absence of BCR engagement as well as the complete saturation of BCR would lead to inability to respond to changes  apparent affinities. Thus, by apparent affinity, we refer to the global strength of BCR engagement, determined by affinity and the aforementioned factors. The upper value of antigen concentration was chosen because the upper limit of concentration for macromolecules is in the millimolar range in molecularly crowded environments. In fact, the apparent affinity of interactions under conditions of molecular crowding, like an immunological synapse, may be higher than that observed in dilute conditions.6 The lower value shown represents 10 antigen molecules in 10 nanoliters, which we arbitrarily chose as a volume potentially sampled by a single B cell.The generalized quantitative model (GQM) assumes that, in order to deliver functional signals to the B cells, the saturation of the BCR by antigen is regulated by adjusting the number of available cells and the apparent affinity of the interaction . Saturat changes . Theoret changes . We shal antigen . It is iKD:By substituting BCR for Ab in the general equation defining equilibrium dissociation constant We deriveKD=[Ag] when [BCR]=[BCRAg]. For the moment, we neglect questions of avidity and shall regard [BCR] as the concentration of paratope and [Ag] as the concentration of epitope.showing that KD, enclosing the line representing 50% saturation of the BCR  and a heavy chain. The SLC has been shown to bind to glycans11 or glycan-binding lectins12 and thereby guide the recognition properties of the newly born pre-BCR. It is not known whether a ligand is required for the preBCR signaling but our GQM assumes so. Glycans abundantly present in the glycocalyx and membrane glycoproteins of cells are good candidate ligands. The glycocalyx displays self-identity beyond the genetic and proteomic information and can be considered the ultimate phenotype of the cell13 and is therefore a prime candidate for laying the foundations of the B-cell repertoire. Of note, analysis of serum IgM binding to different types of glycans revealed that blood group determines reactivity against glycans other than the blood group antigens,14 pointing towards a genetically determined, glycan-mediated selection of precursor B cells. Selection requires the pairing of the rearranged heavy chain to SLC and potentially the ability to promote binding of the pre-BCR to its ligand. The SLC will thereby guide the pre-BCR by binding to molecules generally present on the cell surface. Successful binding translates to increased apparent affinity in our map  until they reach their comfort zone or will die otherwise , cells may further proliferate and thus require adjustment of BCR engagement by changes to apparent affinity. A solution for improving BCR apparent affinity is the switching of the isotype of the surface immunoglobulin molecule, since class-switched BCR show increased sensitivity to engagement. antigen .5 Here the antigen is enzymatically degraded, and peptides and lipids may bind to molecules of the major histocompatibility complex, MHC class II or CD1. Presentation of peptides and lipids to cognate helper CD4 T cells or NKT cells, respectively, provides a special signal for differentiation and gene expression. These responses are called TD-1 and TD-2, referring to the dependence of T-cell help.29 TD-2 responses lead to the formation of small germinal centers and minimal mutations. TD-1 responses are characterized by the development of germinal centers and extensive mutations that change not just the apparent but the true affinity of the BCR.Here we have to make a note on another function of the BCR, namely antigen uptake. High affinity and long-lasting interactions with antigen trigger the internalization of the BCR complex, leading to the transport of the antigen to the endolysosomal compartment.1 becoming able to present complexes containing cleaved complement C3 products. Transitional B cells express BCR at high density, rendering them sensitive to cell death but downregulate BCR expression upon becoming follicular BII cells. IgD expression is upregulated in follicular BII cells but disappears upon activation. Even though the exact role of surface IgD is not known, its characteristic and limited appearance in BII cells suggests it may have to do with providing survival signals for keeping these cells in the quiescent G0 state.Newly formed B cells, which based on their phenotype and are subdivided into transitional 1 and 2 cells (T1 and T2), enter the spleen. Transitional B cells acquire a different set of receptors capable of binding immune complexes: they lose C1qR and express CR2 instead,muR on the follicular B cells ensures that a set of antigens similar to those in the bone marrow will be displayed in the spleen at least, an organ that captures blood-borne antigens just as the bone marrow. This is expected to provide a comfort zone of BCR signaling to the newly arriving T1 cells. The spleen is a likely place for the differentiation of transitional B cells into mature follicular BII cells. Surviving transitional B cells will become follicular BII cells at the end of the differentiation phase, having found their comfort zone of BCR engagement and circulate in the body homing from follicle to follicle. Elsewhere, such as the lymph nodes and mucosa-associated follicles, self-antigens will be mostly supplemented by foreign, previously not encountered antigens.The diversity and concentration of antigens presented in the periphery, in addition to the presenting set of molecules, will largely depend on the environment of the host. Expression of FcWe can compare the diversity of the molecules displayed in the follicle to that displayed in the bone marrow. Apart from the fact that the capture molecules themselves are different here, the principle is the same: feedback about the sampled anatomical region is provided by the molecules produced by activated cells of the repertoire. In the splenic follicles blood-borne antigen is displayed, so the diversity of antigens may be similar to that in the bone marrow. In case a systemic antigen concentration becomes sufficiently high, a more focused response may arise. Particulate antigens captured in the marginal zone may be transferred to the follicle, again favoring focused responses. Elsewhere in the periphery, such as the lymph nodes, Peyer's patches and other mucosal sites, particular antigens may become dominant, in the case of an injury or infection. Competing B cells will therefore have to increase their survival signals via the BCR in the presence of limited antigen. Thus, selection pressures in the microenvironment of follicular B cells favor monospecificity, cells acquiring optimal BCR signaling by changing the composition and/or the affinity of the BCR complex.30 The result of the process is the accumulation of mutations during repeated cell divisions and a diversified protein sequence coding for the BCR. Most mutations decrease the affinity of the interaction with antigen, these cells die during the selection process that follows. Because of the repeated divisions availability of antigen, as expressed by [Ag], will decrease, forcing the progeny of cells to compete. Cells with the highest affinity are therefore selected for cycling and longevity in the process (32 An increased usage of amino acids conferring rigidity (proline) and filling space  is observed at the antibody–antigen interface in matured human antibody sequences.33 Increased affinity is endowed by a lock-and-key binding mechanism, which will allow slow dissociation from the target resulting in high-affinity interactions.New non-self antigens entering a lymphoid follicle may react with BII cells with an unprecedented high affinity . This in process . High-af34 which corresponds to BCR engagement in our model. Higher-affinity clones returning for antigen will capture more antigen in the same microenvironment with a given antigen concentration, triggering more rounds of division  is still incompletely understood. These cells are transcriptionally and metabolically distinct from B cells and even from short-lived plasma cells or plasmablasts, even though they bear no unique surface markers to our current knowledge. LLPC are terminally differentiated, fully devoting themselves to antibody production.38 It is important to note that the same extent of BCR engagement by low- and high-affinity antigens differs with respect to the exact BCR molecules involved in antigen binding. High-affinity binding will engage the same BCR complexes for extended periods of time, while low-affinity interactions will involve the same number of molecules at a given point of time but different BCR over time. High-affinity interactions can lead to qualitatively different signaling events, this probably being one of the factors determining subsequent longevity of plasma cells. Cells with the highest affinity would be able to capture the last antigen molecules, gaining a survival advantage over cells with lower BCR affinity for the antigen. Upon finding a suitable niche in the bone marrow, these cells would become terminally differentiated instead of becoming quiescent, being in the G0 state but with a very high metabolic activity. Such terminally differentiated cells are no longer controlled by antigen availability. They lose several surface proteins characteristic of B cells, including the BCR.Our GQM states that when B cells reach a comfort zone of BCR engagement they exit cell cycle and enter a G0 state. We hypothesize that following extensive proliferation  and the gradual disappearance of antigen, some cells would reach this optimal BCR engagement. As antigen concentrations decrease towards the end of response the likelihood of optimally engaging BCR increases first, then drops again. A recent study in mice showed that LLPC appearance in the bone marrow peaks following a GC reaction and follows the development of memory B cells.How circulating antibodies fit into the GQM is described in our accompanying article.We approached the sequence of events leading to humoral immune response with the assumption that availability of antigen and affinity of the surface antibody–antigen interaction together define BCR engagement and B-cell fate. In order to remain responsive to changes of antigen concentration in the microenvironment, B cells proliferate, die and modulate BCR signaling properties. This assumption led to the proposal that B-cell selection in the bone marrow is antigen dependent. Antigen is transported to the bone marrow by immune complexes and displayed there on the developing B cells themselves. Obviously, such a process needs to be initiated by antibody production, otherwise there would be no immune complex formation. So B cells are raised to identify self, perhaps first identified by C1q and other innate molecules, later expanding the range of recognized molecules in a recursive process where novel targets are brought for recognition with a continuously growing and changing antibody repertoire. Similar events take place in the secondary lymphoid organ follicles, where IgM-mediated antigen display is extended to antibodies with switched isotypes. The combination of cell expansion and differentiation events in the bone marrow, in the blood, in the follicles and germinal centers can be visualized in our map in a quantitative manner and confirm previous observations on antigen-driven responses.The overall picture that emerges from the GQM is that there is an antigen-dependent, bone marrow-mediated and bone marrow-regulated homeostatic immune response to the immunological self, mediated mainly by B1 cells and MZ B cells. This is a dynamic, fluctuating immunity empowered by the supply of immature B cells selected for low-affinity self-reactivity in the bone marrow. Selection events in the bone marrow in turn are modulated by antigens transported to the bone marrow via blood by antibodies secreted into the blood. Along the immunological exploration of our molecular environment, the generation of long-lived cells with increased affinity for their cognate antigen lends rigidity to this system: antibodies displayed or secreted by these long-lived cells are highly efficient in binding to their target antigens but not to other molecules. This is a focused, slowly eroding immunity, generated mainly via GC-dependent selection and affinity maturation of B cells. Immune responses mediated by secreted antibodies are discussed in our accompanying paper on circulating antibodies and their network interactions.


The Theory of Mind (ToM) paradigm was born almost 40 years ago with the study “Does the chimpanzee have a theory of mind?” by Premack and Woodruff . SeveralShatz directly addresses the issue raised in by Premack and Woodruff .It is possible to cluster the manuscripts that compose the RT around a few principal axes. Some papers offer general considerations about ToM construct. The contribution by Woodruff . She argAirenti broached this matter by analysing the difference between the implicit and explicit comprehension of others and the related issue regarding the comparability of verbal and non-verbal tests. Furthermore, Ghrear et al. examine, also from a methodological point of view, the twist between the understanding of false belief and the curse of knowledge. This twist changes along the life-span, and for this reason, new tools are required to evaluate its nature and subsequently the evolution of ToM beyond the “litmus test” of false belief. Finally, Bellagamba et al. investigate the link between the understanding of false belief and the cognitive and affective inhibitory control mechanisms among pre-schoolers. Their findings argue for a specific connection concerning the cold component of inhibitory control. Results are discussed with regard to the link between delayed gratification and mental time travel  based on a set of cognitive skills which includes ToM.The central concept of belief and false belief has been discussed in many studies as the most debated and utilized ToM measurement. Dore et al. jointly analyse ToM and social pretend play and subsequently overturn the widely accepted hypothesis of “Play first.” The hypothesis “ToM first” can be supported by naturalistic longitudinal studies. As opposed to the more commonly used training studies, they could investigate both causal directions while monitoring all of the variables potentially involved, with a particular focus on linguistic skills. Through Aesop's Fables, Pelletier and Beatty investigate the bond between the understanding of stories and ToM. Age is positively associated with the ability to infer moral meanings from such stories based on the mental contents of the protagonists rather than on their concrete actions. From an educational perspective, this is important given the role played by the explicit conversation regarding the mental states in the school context. Gilli et al. explore the impact of an interpretative ToM with respect to various issues linked with the representational understanding of the arts. The developmental steps highlight interesting changes in the conceptions about the intentions of both the artists and the art-users, which are progressively included in a more comprehensive view of the respective agency. The understanding of esthetic experience requires critical elements of judgment as well as the recognition of a particular concept of “truth” (artistic artifact vs. fake). Brizio et al. address the social cognition characteristics in adolescence, a period in the life-span which has been scarcely investigated in literature. The classic ToM tasks, suitable for infancy and childhood, are inadequate in this case as they fail to account for the great cultural valence of adolescent social competencies. The latter would be more properly investigated incorporating the narrative tools used by adolescents to cope with challenges and risks of this developmental phase.Other contributions explore the relation between ToM and some specific abilities deriving from mental representation: pretense, understanding of stories and artistic artifact and the narrative attitude. Schurz and Perner analyse, on the basis of a previous meta-analysis, nine domain-specific, and domain-general neurocognitive theories and the respective predictions regarding the neural activations while subjects are engaged in six categories of ToM tasks. The failures of the theories in predicting the results are discussed in the context of four critical issues: (1) lack of a clear and shared definition of what is a ToM task, (2) the need for more appropriate knowledge concerning the cognitive processes involved, (3) the need for a more precise anatomical brain mapping, (4) a better understanding of the differences between ToM tasks and Control tasks, which is an emerging topic in this field. Cabinio et al. analyse age-related structural brain changes in relation to a widely used affective ToM task. The negative relation between age and ToM performance is explained by both gray and white matter structural modifications. However, the decline remains within a normal range. The most likely hypothesis is that compensatory mechanisms of brain plasticity aid in maintaining this ToM ability. The study by Marchetti et al. provides both behavioral and neural evidences about Mind Wandering (MW). This study includes the Italian validation of a questionnaire designed to explore the contents of the resting mind. Moreover, the relationship between the ToM contents of the questionnaire and the brain functional connectivity during MW are explored. These evidences show the involvement of areas involved in both affective and cognitive ToM tasks.Further evidences about the topic are provided by the studies regarding the neural correlates of ToM. Marraffa et al. examine the nativist/modularist theory and the cognitive constructivist theory. They argue that the intersubjectivity promoted by mentalization (named respectively “Mindreading” and “Introspection”) comes from a first-person perspective, connected to mindreading; only at a later point does this scheme tie into a socio-cultural frame, in which the attachment elements are included. Rollo and Sulla analyse through a Vygotskian perspective the influence of maternal mental language on cognitive and socio-cognitive skills in pre-schoolers. Also maternal empathy and child's temperament are proposed as variables that need to be investigated. Rosso et al. examine pre-adolescent and mother dyads in order to characterize the link between the maternal reflective function and pre-adolescents' mentalization process. They observe a lack of connection between the maternal security of attachment and the pre-adolescents' mentalistic abilities, in contrast to the one found with the maternal reflective function. This aspect is especially true regarding negative or ambivalent mental states. These evidences are particularly relevant for focused therapeutic interventions. Similarly, other studies deal with therapeutic and psychoeducational applications. Baimel et al. propose a strategy to understand the other's mind based on behavioral synchrony. The social rituals, which support behavioral synchrony by reducing the psychological distance, can be efficient tools to promote cooperation. The promotion of this mechanism is an implicit way to support ToM as an alternative to overcome the limits of explicit strategies. Bak et al. propose the theoretical basis and application of a Resilience Program. It is an intervention to promote ToM in different contexts for various targets, such as, parents, teachers, and pediatric health care providers. The main characteristic of this program is its flexibility and the possibility to divide it into separate blocks on a case-by-case basis depending on the requirements. Cavallini et al. discuss the results of a ToM training proposed to elderly people. The effectiveness of the training is based on the three fundamental criteria highlighted in the literature for the transfer of acquisitions: (1) repetition, (2) variability of tasks, (3) a learner-oriented approach. From the clinical perspective, Muller and Midgley show the features of the time-limited Mentalization-Based Treatment for Children (MBT-C). It is an adjustment of mentalization-based psychotherapy for borderline patients. Considering mentalization as a set of developing multifaceted abilities allows for a more precise formulation of the various cases. The idea that the development of mentalization is a relational process implies the involvement of parents in different steps of the treatment. This aspect stems from the hypothesis that improved mentalization in parents can strongly produce a similar improvement in that of the child.The inter-subjective understanding of the subjectivity and the role of attachment process within this dynamic are also addressed in another cluster of papers. Fadda et al. explore the role of ToM in the promotion of moral reasoning in a sample of children with autism spectrum disorder. In these children ToM impairments seem to be connected to a higher proclivity to evaluate actions on the basis of their outcomes. Moreover, they seem more inclined to rigidly comply with moral norms, as in the Piagetian stage of heteronomous morality. Bender et al. investigate the emotive component of ToM with respect to attachment and emotional dysregulation in clinically anxious children. They demonstrate a relationship between the understanding of emotion as mental states and some aspects of anxiety. Ayesa-Arriola et al. analyse whether first episode psychosis patients show a stable ToM impairment over time. In their study, ToM deficits are associated with the neurocognitive status but not with the clinical symptoms. Furthermore, they observe that trait-related mentalizing impairments are found in even in remitted patients.Finally, some studies regard ToM in a clinical sample involving participants from school-age to adulthood. All contributions presented above elicit some considerations and comments. Developmental researchers appear to remain mostly interested in the quantitative aspect ToM abilities. They study the evolution of these competencies depending on age and specific trainings. Nowadays the qualitative aspect of ToM is more addressed in the clinical field as effects of treatments are also evaluated with respect to the contents of mentalization. In the developmental field the relevance of the ToM quality emerges only in the assessment and training studies where language  is the core of the investigations. Since the beginning of this research paradigm, additional life epochs have been added to both before the original pre-school phase as well as going forward all the way to the elderly one. In the meantime various tasks have been devised to meet these new research requirements as well as to investigate the nascent field concerning ToM's neural correlates. However, there is still a lack of authentic life-span studies performed with cross-sectional methods. On the other hand, longitudinal research is generally performed regarding follow up of clinical and training studies as well as researches on the effects of social relational variables (e.g. security of attachment) on mentalistic abilities in different developmental phases. A relevant future topic of research could concern the long-term developmental patterns of ToM skills in different typical and atypical situations.All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Current research largely relies on hand-traced, single B-Scan segmentations because commercially available programs require high quality images, and the existing implementations are closed, scarce and not freely available. We developed and implemented a robust algorithm for segmenting and quantifying the choroidal layer from 3-dimensional OCT reconstructions. Here, we describe the algorithm, validate and benchmark the results, and provide an open-source implementation under the General Public License for any researcher to use ( The vessels of the choroid are the exclusive source of oxygen and nutrients to the outer retina and its anatomy plays an important role in the symptoms and pathogenesis of several eye conditions26710These OCT studies require particularly high signal-to-noise ratio (SNR) images of the deepest layers of the ocular fundus to be able to visualize the choroid clearly. Two technologies have recently enabled this: Enhanced Depth Imaging (EDI) OCT410141516et al. have developed an algorithm based on the segmentation of individual blood vesselset al. have proposed a two stage statistical model based on texture and shape analysis to segment the choroid2017et al. have developed a graph-cut method to segment the choroid layerSome modern OCT devices provide automatic segmentation software for the choroid. However, the results depend strongly on the quality of the images, and the software lacks sufficient versatility to adapt to abnormal tissue profiles encountered in many ocular pathologies. A limited group of studies have developed automatic or semiautomatic segmentation algorithms. Zhang We have recently developed a novel algorithm to automatically detect the choroidal boundaries on OCT time series at a single location in the retinaThe proposed software segments the anterior and posterior interfaces of the choroid from an OCT volume centered at the macula, and automatically builds a 2D thickness map (3D topology). In this article we describe every step of the algorithm in detail, we assess the software performance, we compare against manual and commercial segmentations, and we demonstrate the use of the algorithm for analyzing the choroid layer in 3D using several surface descriptors.https://www.mathworks.com/matlabcentral/fileexchange/61275-choroidsegmentationFinally, in an effort to overcome the shortfall in open-source analysis resources and thereby increase the pace of OCT-based research into ocular pathology, we release the full multiplatform Matlab source code under version 3 of the General Public License The program uses as input a set of OCT images of the retina around the macula and detects the position of 3 layers: the retinal-vitreous interface (RVI), the Bruch’s membrane (BM), and the choroid-sclera interface (CSI). The OCT images consist of a series of B-scans that the algorithm segments individually. The segmentation output of all B-scans is analyzed, combined and finally interpolated to build graphic representations as 2D maps, and allow computation of the thickness of the whole retina as well as that of the choroid.First, we standardize tomography volume data by representing it as a sorted series of adjacent B-scans and a table describing their positions in the volume. To increase the SNR, images are smoothed using information from adjacent B-scans, retinal interfaces are segmented in each B-scan individually, and finally the 2D retinal and choroidal thickness maps are generated.Different OCT devices have different image storage formats, hence the first step of the algorithm is to convert the tomography into a sorted series of contiguous B-scans and extract their location information with respect to the fundus coordinates. Here we provide the implementation for the Heidelberg-Spectralis format. For other devices, the user needs to extract the B-scans from the device and store them in individual image files which are named to facilitate contiguous sorting, and run a small Matlab script (that we provide) to input basic size and location information.The Bruch’s membrane is commonly used to define the anterior limit of the choroid. This membrane, however, is often difficult to distinguish from the RPE in OCT images, particularly for retinas affected by drusen, edema and epithelial dystrophies. Since the RPE is usually easy to segment, we estimate the location of the BM as the convex hull of the RPE. In other words, the convex hull may be interpreted as the shape of a rubber band stretched around the RPE from the posterior side .th degree polynomial and discarding the points that differ from the fit by more than five times the median deviation. The discarded values are replaced using linear interpolation. Next, the center of the RPE in the anterior-posterior direction is localized more precisely and robustly with a graph search algorithm using all pixels between the anterior and posterior interfaces as nodes, and their corresponding pixel intensities as weights  throughout the whole volume using neighboring B-scans . The candidate nodes of the graph are defined as the pixels where the derivative of the intensity with respect to z is greater than a predefined positive threshold and the absolute value of the second derivative is near zero . In other words, the nodes are defined as the inflexion points of the intensity in the z direction, which localize to the posterior walls of blood vessels where intensity transitions from dark to bright  to the connections between nodes a and b, defined as:For the graph-search we assign weights wEuclid favors connecting nodes close to each other. The jump penalties wz and wx are defined asThe Euclidean distance between nodes z and x directions respectively, where Ax, Az, Tx, Tz, and α are parameters and H(x) is the Heaviside step function. Finally, wAffin favors bonds going through regions of high edge probability P. This probability is computed using the Gabor transform θ and at scale s. It is defined as the correlation between a Gabor function I, whereto discourage large leaps in xθ, zθ) are coordinates in a system rotated by an angle θ with respect to  according toand  along pixels in a straight line L connecting nodes a and b aswhere the maximum is taken from a set of Gabor transforms at angles in a range  . The weiTz in z and 5Tx in x were allowed to connect.Only nodes spaced less than 5For the start and end nodes, we added two virtual nodes before the first and after the last columns respectively. The minimum weight path through the graph is found using the Dijkstra’s algorithmx axis where some segments overlap, and discarding unlikely segments to avoid superposition.Sometimes, however, only a few vessels are clearly visible in the B-Scan, and the number of candidate nodes found is not enough to produce a whole trace across the B-scan. In order to profit from those nodes detected, and when a full-length trace fails, we subdivide the graph into connected fragments and search for the shortest path within each fragment. We use Tarjan’s algorithm for the subdivisionTo make this choice, we assign weights to each segment based on their edge likelihood, computed as follows:Wsum is the sum of the edge probability P  subjects; these 30 raw B-Scans were presented sequentially and twice over (once for tracing the BM and once for the CSI) to a group of 5 independent evaluators who were asked to delineate the layers manually. The evaluators manually segmented the BM and the CSI directly on the touch screen of a tablet computer , using a stylus pen. The two traces were drawn using pre-set colors and analyzed to extract the manual segmentations.xc, zc). At each column xc we compute the mean xs, zs) by interpolating the remaining In order to compensate for inter-subject variability, we defined the ground truth for a particular layer as the mean trace among the five evaluators , and all splines .The traces produced by the five subjects were averaged at each column to render the ground truth trace The distribution of deviations for the commercial software and our method is largely equivalent to manual evaluators regarding segmentation of the BM, where all distributions medians are smaller than 6 μm. For the CSI, the performance of our method is similar to manual segmentation , whereas the commercial software produces larger deviations  approximately centered at the macula , spanning a range of ocular disease . The average age of the cohort is 68 years old with a standard deviation of 11. The image dataset consists of OCT scans over square regions  within the circular region indicating choroidal thickness (Δzk), and a weight (Wk) calculated as the edge probability P defined by Maps consist of a set of scattered points , and decreases approximately 23 μm per decade, similar to what has been previously reported using manual measurements on single-scan OCT images  suggesting that this measurement is not biased by age related pathologies.We observe that the average thickness correlates negatively with age (θ (polar) and ϕ  describing the direction of the vector normal to such plane. These values indicate the tilt and orientation of choroidal thickness. et al. have reported results consistent with this observation using manual segmentation of OCT volumes. They report that the nasal quadrant has the lowest choroidal volume, and the superior quadrant presents the highestWe have also fit a plane  to the thickness map, as illustrated in The vast majority of studies based on choroidal thickness maps published so far, which will become seminal for the determination of therapeutic decisions, are based on software black boxes. Due to the variety of eye pathology, the diversity of tissue shapes, and the limitations on image quality (particularly in elderly patients), it is rare that a single piece of software performs optimally in all cases. Open-source algorithms, such as the one we present here, provide the necessary flexibility and freedom as well as long term public support, whereas proprietary software packaged exclusively with new hardware hinders progress in a field in which manual measurements of large cohorts is not a feasible segmentation alternative.The segmentation strategy we present also possesses some compelling characteristics. Although the CSI segmentation is based on graph theory, it does not require a fully connected path across an entire B-scan to be successful. Given the tortuosity and variable reflectivity of blood vessels in the choroid, sometimes only a few of them are visible in the images; it is therefore beneficial to make use of all available information to reconstruct the topography. The approach also benefits from averaging adjacent B-Scans to obtain higher signal-to-noise-ratio images for improved segmentation results.Additionally, although a 2D scattered interpolation is used to build the visual representation of the maps, quantifications are based solely on detected graph nodes weighted by the edge probability, preventing interpolation artifacts from interfering with results.The method is also highly robust, overcoming to a large extent the segmentation challenges posed by tissue anomalies such as drusen and RPE discontinuities, and by low quality images. This is reflected in the high number of correctly segmented maps , and it The software we provide is coded in Matlab, which is multiplatform and is widely used for quantitative analysis of biomedical studies. The code has been tested on Matlab R2014b for OSX El Capitan 64bits, Matlab R2014a for Linux 64 bits, and Matlab 2013b for Windows 10 64 bits.The systematic analysis of the role of the deepest layers of the eye in the pathogenesis of disease is becoming the focus of an impressive number of studies. Beyond average choroidal thickness, the analysis of 3-dimensional surfaces opens the door to a panoply of local and global descriptors that may correlate with ocular physiology, and which are presently unexplored. Accurate and flexible tools for delineation of the choroid are essential to find these anatomical and functional biomarkers of the progression and outcome of blinding disorders.How to cite this article: Mazzaferri, J. et al. Open-source algorithm for automatic choroid segmentation of OCT volume reconstructions. Sci. Rep.7, 42112; doi: 10.1038/srep42112 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this.Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a  RNA silencing is known to play a key role in the fine-tuning of gene expression in eukaryotes .The procFor most molecular biology experiments, an important question is how the observed phenotype or inherent differences  are reflected in the variation in expression of sRNAs, commonly referred to as differential expression analysis or DE analysis . IdentifBioinformatics methods developed for DE analysis have thus far largely focused on analyzing messenger RNA (mRNA) data, first from microarray experiments and now, more commonly, from RNA-seq (mRNA-seq) data sets . Many ofA common approach for HTS data analysis is to group several tools into a pipeline. As well as providing the ability to tailor pipelines to individual experiments, this enables researchers to configure the distinct stages of the analysis as required . After tH. sapiens data set, described in the main text, we demonstrate how this can be extended to multiple comparisons that can be used to group sequences with similar patterns across the whole experiment.Here we present a comprehensive, interactive processing pipeline for the analysis of sRNA-seq data sets included as part of the UEA small RNA Workbench . The pipH. sapiens, GSE47532  and in Supplemental Information 3 . The impact of the number of samples or available memory (RAM) on the runtime is discussed in Supplemental Information 2.In this section, we illustrate the features of our pipeline on a publically available data set in GSE47532  to highlThe pipeline is part of the existing UEA small RNA Workbench package , which pA standard pipeline takes as input sequence data in FASTA format with the adapters trimmed. The files can be generated using the adapter removal tool  which alAfter configuring the sample files, users can choose to begin the workflow immediately or enter each stage of the workflow and change the configurable parameters, as necessary. In addition, during the workflow, users can mark problematic replicates  or individual size classes for removal, then select up to six normalization methods to be investigated. The quality check reports are then recreated on the normalized data and can be inspected. Next, the user can select the method that best corrects the data artifacts based on the nuanced characteristics of the data set's expression distributions.The quality check, normalization, and DE steps are computationally intensive and pose significant demands on both processor and in particular memory (RAM). To counteract this issue, we developed a series of back end improvements, which enable users with a wide range of computing hardware to use the pipeline. More specifically, we used disk solutions based on relational database management interfaced with a Java front end and interacted via a JavaScript GUI . However, as the use of disk for runtime storage and calculations can have significant impacts on processing time, a RAM-only version of the software is also available for users with access to high-end computing hardware.H. sapiens data set (H data) were conducted both before and after aligning reads to the reference genome. The first step of the pipeline is to evaluate the overall features of the data being analyzed. The sequencing quality of individual sRNA-seq samples is initially assessed based on the positional nucleotide composition. Next, the total library size (redundant count) and the total number of unique sequences (non-redundant) count are compared across libraries to assess the variation in sequencing depth. The size class distributions for both redundant and non-redundant reads . Other options are rank-based quantile normalization adapted for sRNA-seq data  and subsThe analysis of the H data set highlights a common issue with normalization where two replicates are sequenced with different overall depths (mainly due to the characteristics of the sequencing platform used). To evaluate which method(s) are suitable for this data set, we tested all six normalization techniques described in Materials and Methods. We exemplify the DE analysis on the H data set for two comparisons: N00/H32 and H32/H48; the left-hand side is considered the reference sample.2 scale (LOFC) and confidence interval (CI) pattern approach—described in Materials and Methods, with two of the most widely used tools for detecting DE reads, DESeq2  we encourage the user to investigate their using the revised quality check plots.P-value threshold to assess DE genes, which often reports large numbers of significant genes often with a low difference in expression, we used a cut-off of 1 LOFC to filter the reported sequences. The cut-off can, however, be user defined in order to reduce or increase the number of reported sequences. Importantly, the ranking of sequences by LOFC is not populated with high but insignificant fold changes.When identifying DE transcripts in HTS data it is important to take into account the level of noise, a quantity that increases with the depth of sequencing. To account for this, we have implemented a user-friendly tool for the identification of a suitable offset, which estimates the abundance range of the reads lacking sRNA characteristics , taking into account the sequencing depth and the characteristics of the sRNA population present in the samples. We compared the results of our DE analysis (LOFC) to that of DESeq2 and edgeR DE packages to determine the level of overlap between other methods and our own. In lieu of a To further accommodate the variability between replicates we use CIs created over normalized replicate expression levels which produce more stringent lists of DE sequences between treatments. The method is also extended to multiple conditions by using pattern-based grouping of the sequences . The metDuring our analyses we observed that problematic data sets arise when whole size classes are affected by a condition, causing a high rate of DE for a large proportion of the sRNAs, e.g., RNAi mutants which cause the exclusion of a whole class of sRNAs or virus infections which produce a large set of viral siRNAs in the infected samples . To our In conclusion, we have described a user-friendly pipeline for sRNA DE analysis that allows the evaluation of a variety of techniques to identify the most suitable approach for a given data set. The workbench includes both established approaches and tools that we have specifically developed for sRNA sequence analysis and facilitates a coherent and informed analysis through linking the different aspects into a workflow. The UEA sRNA Workbench and the pipeline design devised for the data analysis may prove to be a valuable resource facilitating the expansion of our knowledge of sRNAs, especially for the study of new or less well characterized classes of sRNAs.H. sapiens data set referred to as “H” data (publicly available on Gene Expression Omnibus [GEO] under accession number GSE47532). This is an experiment on the effects of hypoxic conditions on MCF7 cells  consisting of two samples, with four biological replicates each  consisting of two samples, with three biological replicates each -based approach . For eac2 offset fold change (LOFC) method previously described in The amplitude of the difference in expression between conditions is considered on proximate extremes (the closest ends of the neighboring CI) of the reference and observed CIs and is only calculated on sequences that have been assigned a U or D descriptor. The amplitude is calculated using the logTo determine an appropriate offset for a data set, the pipeline can be used to estimate the abundance level around which the majority of noise-related reads lie. Previous studies have observed that low abundance regions/loci have a high strand bias (derived from the reduced number of reads), but loci within the noise-to-signal range have no preferred strand bias . Based ohttp://srna-workbench.cmp.uea.ac.uk. The license is a custom license written for the UEA sRNA Workbench and can be found in the Workbench installation directory or by visiting http://srna-workbench.cmp.uea.ac.uk/wp-content/uploads/2016/11/sRNA-WorkbenchEULA.pdf. There are no restrictions on use other than requiring citations to specific papers when conducting research with the software; specific details can be found on the website.The workbench and all the supporting data and tutorials are freely available from Supplemental material is available for this article.


Packaging represents an important part in the microintegration of sensors based on microelectromechanical system (MEMS). Besides miniaturization and integration density, functionality and reliability in combination with flexibility in packaging design at moderate costs and consequently high-mix, low-volume production are the main requirements for future solutions in packaging. This study investigates possibilities employing printed circuit board (PCB-)based assemblies to provide high flexibility for circuit designs together with film-assisted transfer molding (FAM) to package sensors. The feasibility of FAM in combination with PCB and MEMS as a packaging technology for highly sensitive inertia sensors is being demonstrated. The results prove the technology to be a viable method for damage-free packaging of stress- and pressure-sensitive MEMS. The production of smart packaging solutions presents a major challenge in microassembly technology ,2. PolymFilm assisted transfer molding (FAM) is based on standard transfer molding (TM) technology and presents a new, advanced industrial manufacturing technology . The majMEMS are typically packaged in hard shell ceramic or metal encapsulation because of the mechanical component of the sensor, which could become dysfunctional after packaging by an encapsulation technology with direct contact to the sensor elements. Thus the cost for producing such a MEMS package is commonly high due to the complexity of the encapsulation and its assembly steps. Combining the PCB and FAM technology, low cost MEMS packaging is possible. With the developments of the IGF (Industrielle Gemeinschaftsforschung) project ‘FlexPacFAM’, founded by the German state , a new sThe advantage of PCBs in comparison to lead frames is that they can be easily designed using available software tools and produced in a cost-efficient manner by employing multilayer technology for complex routed electrical circuits. Thereby, a much higher integration density and complexity can be achieved in comparison to lead frames. This allows the integration of a smart system in the package. In particular, leadless packages like QFN are in high demand due to the trend to use less space for an assembly. Providing an even further miniaturization, more complex circuitry can be embedded into the QFN . On the downside of the combinatory technology, PCBs show higher tolerances than lead frames. For this reason, alignment methods for FAM processes are not trivial . The chaWith the new developments, the FAM process, in combination with MEMS and PCB, was enabled to be employed for scalable, flexible production and low-cost MEMS sensor encapsulation, whereas the requirements of MEMS remained unknown regarding a damage-free encapsulation. In order to evaluate the combination of technologies regarding its reliability for highly sensitive sensors, the electrical measurement signal of MEMS was analyzed after encapsulation with EMC, proving the applicability of this new technology for flexible, functional packages.For the FAM process, a Unistar Boschman FAM machine with the ability to process EMC pellets was used for the development of the flexible, PCB-based packaging concept. The material EME-G770H Type CD from Sumitomo Bakelite was selected in order to provide a good CTE match for die packaging on PCB. The process temperature was set to 180 °C, at which the ETFE foil remained stable during the FAM process while becoming flexible for a form adaptation into the mold cavity. At the end of the FAM process cycle, the used foil was coiled onto a roll for disposal, and at the same time new foil was placed into the process area.Due to the properties of the PCB technology, the adhesion mechanisms of EMC on the PCB surface are of utmost importance in relation to the reliability of the molded system. Thus, adhesions tests were carried out with defined EMC buttons molded onto the substrate’s different surfaces and subsequent shear testing with a DAGE Series 4000. The tests were designed according to the SEMI standard G69-0996 . The tes2-plasma) and conventional atmospheric plasma (N2/O2-plasma) were also tested to characterize the influence of these methods regarding the adhesion properties.An insert for the molding tool was designed and manufactured by precision tool making to mold the EMC buttons on the test panel by means of the FAM process a. For eaFor the investigation of packaging MEMS on PCB using FAM, an inertia sensor with a thin aluminum (Al) layer for the electrical conductivity of the silicon ridge structure was used. This type of sensor is typically used in applications such as construction machinery to measure inclination. The sensor is based on silicon technology (MEMS) and a glass lid acts as a protection mounted on top of the sensor to cover the MEMS structures b. NormalThe investigation was divided into two parts. Throughout the first part, the aim was to show how low the cure pressure within the FAM process needs to be to achieve complete, flawless molding without any damage of the inertia sensors. The cure pressure is the parameter, which takes the most stress onto the sensor. After the virtually pressure-free transfer of the EMC melt into the cavity by simple displacement of the air with material, both at atmospheric pressure, the cure pressure starts to compress the EMC and drives out the remaining air out of the cavity. Subsequently, the cure pressure values increase to 30 bar to 60 bar in typical applications, which can damage the Al layer by deforming the glass lid of the sensor and consequently the sensor itself. For the first approach, five PCB panels with nine sensors each were mounted. Each PCB was equipped with four partly malfunctioning inertia sensors, where the x-axis was working unobtrusively but the y-axis was malfunctioning. Five dummy sensors were bonded at the empty slots in order to provide thermal stability and material distribution equally to the final constellation in a later production cycle. After the transfer process of the EMC melt, four different cure pressures were applied, namely 10 bar, 20 bar, 30 bar and 40 bar. One of the PCB panels underwent the FAM process without encapsulation with EMC to verify the effect of process temperature on the inertia sensor. After FAM, an electrical test by means of CVC2 (capacity-to-voltage converter with two channels) circuit was carried out to measure the static and dynamic behavior of the packaged inertia sensor. The results were compared to evaluate the best cure pressure for production. Applying X-ray using computer tomography , the cured EMC was inspected to analyze the density and identify voids within the material.The second approach employed fully functional inertia sensors in a stack configuration with an ASIC mounted on the glass lid. Five PCB panels with five stacks were bonded on each panel. The sensor stack was programmed using the CVC2 circuit of the ASIC in order to get the sensor into a calibrated condition. The cure pressure of the FAM process was set to the smallest pressure that could be used to fill the whole cavity as evaluated in the first approach. An electrical measurement was carried out at four different stages: At first, after die and wire bonding and before the FAM process in order to record the electrical properties of each sensor after calibration. Secondly, after the FAM process to verify the signal changes caused by the encapsulation. Thirdly, after a post-mold cure process for EMC residual curing at 180 °C for 4 h. Finally, after a dicing process, which separates the inertia sensor-FlexPacs from the PCB panel. pF in the x- and y-axis of the sensor was determined for an angle of 0° and 20°. Therefore, the offset capacity was measured to detect the influence of each process step by FAM.For each case, the electrical measurement was the same. The sensor capacity in To determine the warpage within the package due to internal stresses as a reason for increased offset capacity of the inertia sensor, a white light interferometry measurement from was carried out using a Veeco interferometer. 2-plasma significantly increased the adhesive strength effect on polymeric surfaces but it exerted only a weak effect on metallic ENEPIG surfaces. This stronger effect of oxygen plasma on polymeric surfaces was probably based on a better continuance of ionic oxygen on a polymeric surface compared to a metallic surface, leading to an improved wetting of the EMC on the polarized polymer surface. The Pd content of ENEPIG is typically a barrier for oxidation of Ni, preventing oxidation in order to improve the Au wire bonding on this surface. Solely a cleaning effect can be achieved using oxygen plasma on metal surfaces, whereas the ions react with organic contamination and evaporate. The FR4 showed the strongest and the ENEPIG the lowest adhesive strength a. Treatm2/O2-plasma treatment resulted in no significant change of the adhesive strength of EMC on ENEPIG. However, the PCB-base material showed a decreasing effect for the adhesion value in comparing to EMC on PCB without any pretreatment. This could be due to the fact that treatment of FR4 by means of N2/O2-plasma leads to a degeneration process of the FR4, whereas organic material evaporates out of the surface. Furthermore, some additives of the polymeric component may react with the nitrogen ions in the plasma, and the surface becomes more nonpolar in contrast. The effect of N2/O2-plasma treatment on solder resist showed an increased adhesion value, leading to the general conclusion that it is also possible to increase the adhesion values on polymeric surfaces.N2-plasma had a greater effect on increasing the adhesion on polymeric surfaces than the N2/O2-plasma treatment. For ENEPIG, no differences between the treatments could be observed.By comparing both treatments, it could be recognized that the OSince the adhesion of EMC to FR4 without pretreatment provided sufficient strength , the process of plasma treatment is only recommended if increased reliability is required. Nonetheless, the plasma treatment presents also a method to remove surface contamination, thereby providing a safer process regarding the quality of differently produced PCBs. Furthermore, less statistical variations in terms of adhesion occur if plasma treatment is employed. Visual inspection of the fracture surfaces of each kind of surface showed cohesive failure for both solder resist and FR4. Adhesive fracture was observed for the ENEPIG surface b. AdhesiSince the fractured surface of the FR4 base material showing the glass fiber mat, which is located below the top surface of the PCB-base material, it can be concluded that the adhesion between EMC and the FR4 is higher than the adhesion between the different core layers of the PCB.For the FR4 surfaces without plasma pretreatment, a cohesive fracture between EMC buttons to the FR4 was observed, indicated by the mixed adhesive and cohesive fracture between EMC button, FR4 and the glass fiber mat. The reason for the mixed adhesive/cohesive fracture might be that the EMC button lifts off the FR4 at the beginning of the shear process until a critical strength is reached. After exceeding a critical strength, the influence of tensile stress on FR4 epoxy generates a fracture path vertical to the shear direction that the EMC button pulls out the FR4 epoxy by braking from the surface. The atmospheric plasma reduces the adhesion of EMC on FR4 compared to non-treatment. In this case the fracture surface shows predominant an adhesive fracture. Consequently, solder resist, if possible, should be avoided if possible as it presents a weak point in terms of reliability. Thus, the following investigations were performed without solder resist on the top surface of the PCBs and without plasma pretreatment. However, if the area of exposed ENEPIG lines is significantly higher than FR4, solder resist on top of this surface is preferable to improve adhesion.Four partly functional inertia sensors were attached on three corners as well as in the middle of the PCB panel. In order to track the positions, the sensor positions were numbered from one to four see a. Empty Even though a common cure pressure above 20 bar is recommended for FAM, the visual inspection after FAM showed that all used cure pressure were able to fill the whole cavity. Therefore, 10 bar could be qualified for use as cure pressure for the main investigation. However, using X-ray, voids could be observed on the end of the cured flow front for cure pressure 10 bar a. That m, showed random results. All inertia sensors with a fail showed no or less sensitivity (The results for the static electrical function test showed no discrepancies, meaning the electrical conductivity was checked successfully for each inertia sensor. However, the dynamic electrical test, at which the sensitivity of each inertia sensor was determined by an inclination of 30°sitivity .The reference showed one fail and three functional inertia sensors. According to the manufacturer’s experience, such failures can result from die attachment processes, where handling can lead to damages of the glass lid and thus non-hermeticity, which in return causes the silicon ridge structure to lose its sensitivity. Also, thermal stresses based on the temperature cycle of the FAM process are a possible cause for the failure. Comparing the electrical test results, the test panel processed at a cure pressure of 30 bar had three functional inertia sensors after encapsulation. The other test panels showed more failed sensors after encapsulation. Hence, no connection between the cure pressure and the failure of the inertia sensors could be established, excluding the cure pressure as the main reason for failure. However, due to the complexity of the hybrid assembly of MEMS, die attach and FAM process, interactions of thermal and mechanical stresses cannot be excluded. Consequently, the dynamic electrical test demonstrates that by means of FAM, packaging with the tested curing pressures can be successful in terms of the MEMS sensors remaining functional. The yield needs to be evaluated and a detailed failure mode evaluation analysis with larger sample sets remains to be conducted.In the second investigation, five test panels were assembled with five fully functional inertia sensors, each with a stacked ASIC a. The wiThe first electrical tests after assembly and prior to encapsulation showed that three stacks were dysfunctional after the assembly process and one channel of stack at one of the panels was also dysfunctional. Some of the stacks had an offset signal, leading to reduced sensitivity or a signal that exceeds the calibrate range in maximum positions, but were tolerable according to the specifications. This offset is due to pre-damaging caused during the production of the MEMS or during the assembly procedure. Subsequent to a parameter screening for FAM process for a complete filling without voids, the set cure pressure could be minimized to 21 bar, thereby generating as little stress as possible to the sensor by the EMC melt. Subsequent electrical testing showed that for most of the stacks, the offset increased after encapsulation by the FAM process . These sAfter the post-mold cure, the warpage of test panels 2 and 5 was determined by means of white light interferometry . The difElectrical testing was performed after a post-mold cure, presented in Test panels 2 and 5 were diced using a wafer saw to separate the inertia sensor-FlexPacs in order to determine the influence of the dicing process on the stacks . The dicThe results demonstrate that by means of FAM, inertia sensors on PCB can be functionally packaged. Furthermore, the stress on the MEMS can be reduced by a post-mold cure and dicing to separate the package from the panel. This investigation successfully demonstrated that a PCB-based inertia sensor packaging solution can be realized by means of the film-assisted transfer molding technology. A button shear test for PCB was described, and two kinds of plasma were examined to determine design rules for the PCB and to quantify the best surface composition and pre-treatments. The adhesion of EMC on polymeric surfaces showed excellent adhesion strength and ENEPIG as the gold finish was in adhesion of EMC unaffected by plasma treatment. Furthermore, it was discussed that FAM is a functional solution to encapsulate pressure- and stress-sensitive MEMS as demonstrated by an inertia sensor-FlexPac. The process chain to assemble and package the inertia sensor-FlexPac was shown and validated by electrical function testing to determine the influence of each step. With cure pressure values above 10 bar in order to achieve void-free packaging, a certain degree of damage to the pressure-sensitive MEMS sensors was expected. However, it was recognized that mechanical, electrical and thermal failures are the dominant cause for malfunctions in the inertia sensor, not the cure pressure.