In this study, we assessed the performance characteristics of five different magnetorheological micropump designs, two of which were our proposed designs, while others were from the existing designs in the literature. Comparisons have been performed based on physics-based simulations, and the fully coupled magneto-solid-fluid interaction simulations were carried out in COMSOL Multiphysics software. For a fair and meaningful comparison, both the material and geometric properties were kept the same, and the simulations were run for one complete pumping cycle. The results showed that the proposed flap and duckbill valve models could pump 1.09 µL and 1.16 µL respectively in 1 s, which was more than the rest of the existing micropump models. Moreover, at 0.5 s, when the magnetic flux density was maximum, the flap and duckbill valve models could pump almost twice as fluid as some of the existing valve models did. The results also demonstrated that the flap and duckbill valve models were nearly five times faster than some of existing models. In conclusion, the proposed two micropump models could propel more net fluid volume than the existing micropump designs, experienced low leakage during the contraction and expansion phase, and had faster response times. We believe that the present study provides valuable insights for future micropump designs, which have an extensive range of application areas, ranging from insulin dosing systems for T1D patients to artificial organs to transport blood and from organ-on-chip applications to micro-cooling systems. With the recent advancements in manufacturing technologies, researchers have begun to explore novel designs at the micro and nano levels. Various micropump designs have been proposed and studied in the literature, including AC magnetohydrodynamic, piezoelectric, electroosmotic, acoustic, shape memory, thermo-pneumatic and so on. These designs have their advantages and disadvantages over one another in terms of scalability, biocompatibility, complexity, accuracy, cost and reliability. In this study, we focus on the magnetorheological micropumps. Magnetorheological elastomer (MRE) is a type of semi-active material, consisting of a rubber-like matrix with micron-sized iron particles embedded in it. MREs change their mechanical behavior under the influence of magnetic field. Their stiffness and damping properties alter with the intensity of the magnetic field. Due to this unique feature, they were utilized in various applications, ranging from vibration isolation systems in buildings and bridges to sensors for structural health monitoring applications and actuation systems such as micropumps ,2,3,4. THowever, all of these designs were studied individually, and they are not compared against one another in terms of their pumping performances. In this study, we assessed the performance characteristics of five different MR micropump designs, two of which were our proposed designs, while others were from the existing designs in the literature. The models from the literature included the Behrooz, Ehsani and Xufeng ,16,17,18The other two models are the ones that are proposed in this study, namely the duckbill valve and flap valve models. Comparisons have been performed based on physics-based simulations, and the fully coupled magneto-solid-fluid interaction (MFSI) simulations were carried out in COMSOL Multiphysics software. For a fair and meaningful comparison, both the material and geometric properties were kept the same, and the simulations were run for one complete pumping cycle. The details of the design will be discussed in Among the proposed designs, the flap valve model consists of a pump chamber, two one-way flap valves and an electromagnet, while the duckbill valve model is composed of a pump chamber, two one-way duckbill valves and an electromagnet . The topThe proposed design involves coupled magneto-solid-fluid interaction physics. Thus, the performance of the pump could best be predicted with the help of computer simulations rather than simplified 1D analytical models. In this study, simulations were carried out using COMSOL Multiphysics software . The geometric and material properties of the 2D models are given in The dimensions of the five 2D valve models are shown in the In this study, MRE is assumed as a ferromagnetic material that has constant structural and magnetic properties. The wall at the bottom does not deform in the presence of the magnetic field. It is assumed to be sitting on a flat rigid surface so the deformation on the top wall can activate the fluid flow. The magnetic field analysis was conducted in an AC/DC module, whereas the structural deformation of the pump chamber, including the top wall and one-way valves and fluid flow through pump chamber and valves were carried out in Solid Mechanics and Laminar Flow modules, respectively .The simulation procedure is illustrated with the flowchart shown in As for the boundary conditions, a current excitation was added to the coil in the AC/DC module, and the force calculation interface was selected for the top edge of the upper wall of the pump chamber. This was to ensure that the Maxwell forces were transferred to the top edge for the desired deformation, and thus the resulting pumping effect. A sinusoidal time function and an external current density with a specific amplitude were applied to the core of the electromagnet. In the solid mechanics module, fixed support was added at the bottom wall of the pump chamber and the Maxwell surface stress tensor (magnetic interaction force between the pump chamber and magnetic field) was selected in the boundary load interface. In the laminar flow module, the pressures at the left and right outlets were set to 0 Pa (gage). This was to allow the fluid freely to pass in and out from two terminals. In addition, a no-slip condition was applied to the walls surrounding the flow chamber.Next, we discuss the governing equations for each physics involved. The following equations were solved for the magnetic domainMoreover, Equation (5) shows the final equation of a and b are the cross-sectional dimensions of the core. The magnetic field density In Equations (6) and (7), The Maxwell stress is shown in Equations (9) and (10) the total stress, which is the result of magnetic stress and fluid pressure, is shownIn the fluid domain, the flow is set to laminar incompressible flow appropriately. The following equations were solved in the fluid domain:Steady continuity:Navier-Stokes equations for stationary approach:Navier-Stokes equation for the time-dependent approachFor the solid mechanics, the following equations were solved:For stationary approach:For the time-dependent approach:l is the unit tensor and FS (F is the deformation gradient) is the first Piola-Kirchhoff stress tensor.In Equations (15) and (16), As is commonplace procedure for conducting simulations in both Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), a mesh independency analysis was conducted. To begin this process, a course mesh was applied to an initial simulation. Then, the mesh size was reduced continually, and the net pumped volume was monitored after each run. The mesh size reduction continued until there was no significant change between two sequential cases. This process is shown in Although COMSOL Multiphysics is a proven simulation tool and has been employed by thousands of scientific studies in the literature, it is always wise and scientifically required to validate the simulation approaches with the existing studies in literature when experimental data is not readily available. To this end, we selected the model presented in . All parThe simulations were carried out by following the procedure outlined in In this section, the pumping process is analyzed for one pumping cycle for the five micropump models. Comparisons are made in terms of volume flow rate and MRE wall response time. A full pumping cycle consists of a contraction phase, followed by an expansion phase. When the electromagnet is activated, the magnetic particles inside the MRE actuates and deforms the MRE wall downwards. The first phase of pumping is contraction. In this phase, the magnetic field over the MRE wall increase. When the upper wall begins to deform downwards it pushes the fluid inside the microchannel towards the two outlets. At this time, the fluid enclosed between the two valves deflects the left and right valves in a way that prevents the backflow, and propels the fluid to the right unidirectionally. This phenomenon is the same for all the five models.From t = 0.5 s), but the Ehsani valve model has the highest backflow compared to the other four models. Hence, the Ehsani model is the least advantageous among the five models. As seen from The material and the design of the chamber needed to be tuned to ensure the optimum deformation due to the electromagnetic force could be achieved, as stiff sidewalls would be a challenge for electromagnetic forces to be able to deform the chamber and increase the pressure to open the outlet valve. On the other hand, the return cycle needed to be as quick as possible to bring the chamber back to the initial shape ready for the next cycle, while generating enough suction to open the inlet valve and suck fluid into the chamber for the next pumping cycle. Both pressure and cycle time for pumping and suction cycles are directly related to the mechanical property of the elastic material and the design of the chamber. The thickness and design of the side walls has been tuned to optimize these pumping and suction performance of the pump. FEA analysis has been used to simulate the deformation and return of the chamber, to optimize the thickness and design of the chamber. While mechanical property of the chamber could be tuned by adjusting the UV-power density (power x exposure time) during the 3D printing process, a constant UV-power density  has been used throughout all initial fabrication experiments.The advantage of this fabrication is that geometry design and mechanical properties of the chamber could be easily modified and fine-tuned, with minimum limitation imposed from fabrication technique. The elastic resin used in this study is a new type of resin for 3D printing that has been developed by “Adaptive3D”.In this work, we presented a comparative evaluation of several magnetorheological micropump designs. All designs were positive displacement pumps, pushing the fluid in one direction via two flexible valves. The Behrooz, Ehsani and Xufeng valves were existing in the literature, while the flap and duckbill valve models were proposed in this study. The performances of the pumps were evaluated through physics-based multiphysics computer simulations. The comparisons of the performance characteristics of the five pumps were presented and discussed.○the proposed duckbill and flap valve micropumps were five times faster than the Ehsani and Xufeng valve micropumps;○the backflow was comparatively less for the duckbill and flap valve micropumps, while the Ehsani models showed the maximum backflow;○the proposed flap and duckbill valve model could pump 1.09 µL and 1.16 µL in 1 s of pumping cycle, respectively, which is more than each of the three existing micropump models.The comparison study revealed that:After examining the MRE wall deformation, velocity magnitude and volume flow rate, it is concluded that the proposed duckbill and flap valve models can propel the largest amount fluid in the same time interval, and both of them have short response time to apply the magnetic field. Thus, in terms of the performance measures, it can be concluded that the proposed two models provide better results.The proposed study could be used for future MR micropump design considerations.The major takeaways from this study can be listed as follows:


One of the most challenging issues in the routing protocols for underwater wireless sensor networks (UWSNs) is the occurrence of void areas (communication void). That is, when void areas are present, the data packets could be trapped in a sensor node and cannot be sent further to reach the sink(s) due to the features of the UWSNs environment and/or the configuration of the network itself. Opportunistic routing (OR) is an innovative prototype in routing for UWSNs. In routing protocols employing the OR technique, the most suitable sensor node according to the criteria adopted by the protocol rules will be elected as a next-hop forwarder node to forward the data packets first. This routing method takes advantage of the broadcast nature of wireless sensor networks. OR has made a noticeable improvement in the sensor networks’ performance in terms of efficiency, throughput, and reliability. Several routing protocols that utilize OR in UWSNs have been proposed to extend the lifetime of the network and maintain its connectivity by addressing void areas. In addition, a number of survey papers were presented in routing protocols with different points of approach. Our paper focuses on reviewing void avoiding OR protocols. In this paper, we briefly present the basic concept of OR and its building blocks. We also indicate the concept of the void area and list the reasons that could lead to its occurrence, as well as reviewing the state-of-the-art OR protocols proposed for this challenging area and presenting their strengths and weaknesses. With a large area of the earth (more than 2/3) covered by water ,2, invesOne of the main tasks that faces researchers in the networks is determining how to route the information collected by sensor nodes to reach the sink(s) while minimizing routing costs  and ensuring network connectivity (void area problem). That is, to assure the network continues to function for as long as possible. OR is one of the routing techniques used to transmit data in UWSNs. It is an emerging routing technology that was proposed to overcome the drawback of unreliable transmission, especially in UWSNs. OR uses the broadcast nature of wireless communication to forward data packets to reach the sink(s) through one-hop or multi-hops. It addresses the major challenges of UWSNs, such as energy efficiency, void avoidance, reliability, and network stability. This OR approach takes into consideration the limited resources (battery and memory) of the underwater sensor nodes, and over the years, many forwarder methods in OR were proposed to prolong the network lifetime and increase the chance that every node has a direct or indirect link to the sink(s). Therefore, OR extends the lifetime of the UWSNs. However, based on previous research, it has been determined that there is still space for development in this area .Many survey papers for UWSNs have been published, such as ,24,25,26We explain how the void area problem in UWSNs can be addressed by utilizing the OR technique, and we review up-to-date OR protocols. To the best of our knowledge, our survey paper is the first one that reviews up-to-date void-avoidance OR protocols for UWSNs.We classify up-to-date void avoiding OR protocols for UWSNs based on their most important characteristics and features.We identify some of the open issues and challenges in UWSNs, which can assist the designers of OR protocols for UWSNs.The main contributions of this survey paper are:The rest of this paper is structured as follows: In general, the underwater sensor nodes are deployed in the area of interest following one of the underwater network architectures  and low data rate . The limited accessible acoustic bandwidth depends on the communication range and acoustic frequency.High propagation delay: The UWSNs use an acoustic channel for communication between the underwater sensor nodes themselves and with the sink(s). In the acoustic channel, the propagation speed is five orders of magnitude lower than in the radio channel. This high propagation delay (0.67 s/km) can significantly decrease the throughput of the network.High noise and interference: Basically, there are two kinds of noises, man-made and natural. These noises are caused by water currents, machines, marine mammals, and shipping. The noise under water is much more serious than in the terrestrial environment. The interference is essentially caused by the surface, the bottom, or animals and contamination reflections.High bit error: Due to the shadow zones caused by animals, water currents, and human-made noise, the acoustic channel suffers from a high bit error rate and temporary losses of connectivity.Limited resources: In UWSNs, sensor nodes are constricted resource devices . Therefore, after deploying the sensors in an underwater environment, it becomes difficult and costly to replace or recharge the node batteries due to the harsh underwater environment. Moreover, underwater sensor nodes are vulnerable to deterioration and damage due to corrosion and pollution.Topology changes: Due to the flow of water, the underwater sensor nodes cannot stay in one location; instead, they move randomly, which gives UWSNs a mobile or changeable topology.In this context, to better design an OR routing protocol for UWSN, a number of challenges that UWSN routing protocol designers encounter are listed and briefly discussed below, as in :Limited Sensor nodes drift at different depths in the commonly deployed three-dimensional UWSN architecture to make it easier to identify or monitor a certain phenomenon. Multi-hop routing protocols depend on the relay nodes with positive advancement to transmit the data collected from the phenomenon from the source node to reach the target location on the water surface (sink(s)), as illustrated in Therefore, a communication void or void area between underwater nodes exists when the area has an absence of nodes. The void area is one of the essential problems to investigate in the UWSN field. It can prevent communication between two or more network sensor nodes, which in turn can lead to a topological partition that results in decreased network connectivity and increased packet loss, which lowers the performance of the entire network.Sparse topology deployment: Because underwater sensor nodes are expensive, it may not be possible to deploy enough of them to cover the area of interest. These sparse networks are prone to empty areas.Underwater sensors failure: Owing to the harshness and peculiarities of the underwater environment, it is more likely that the sensors would malfunction due to corrosion and fouling, which could result in a void area issue.Movement of the underwater sensor nodes: Water currents cause the underwater sensor nodes to move in both horizontal and vertical directions. Both node placements and the network topology will change because of this relocation, and a void area might be created.Temporary obstacles: Many living organisms are found in the underwater environment. The movement of organisms could interfere with the underwater sensor nodes’ ability to communicate. In addition, ships, boats, and other water-surface machinery might block the communication link between the network devices. As a result, void areas could be created.The acoustic channel characteristics: The underwater environment characteristics have an impact on the acoustic communication channel, changing the signal’s quality and strength at different water depths due to disturbed pressure, temperature, and salinity at varying water levels.Through our research and review of the literature, we have come to conclude that any network architecture can experience the void area phenomenon due to one or more of the following causes :Sparse tAt the beginning of this section, we will give the definitions of some terminologies that are used in this paper to make it simple and clear.Neighbor nodes/neighboring nodes of node (i): are a set of nodes, which are in the transmission range of the node (i).The qualified set: is a subset of the node’s neighbor, which meet the rules adopted by the author(s) to design an efficient routing protocol.Next-hop forwarder of node (i): the nodes within the transmission range of the node (i) and at the same time have depths less than the depth of node (i).Beacon messages: Status messages that contain the status information of the nodes, which are used to exchange this information between the neighbors.holder: is the node carrying the data packet in the current round. It could be the source node, which originally generated the data pocket, or a relay node.PRelay nodes (i): any node located between source node and sink(s) that carries on forwarding the data packet starting from the source hop by hop until it reaches the sink(s).OR is a promising technique that was proposed for overcoming acoustic signal fading, high bit errors and losses due to shadow zones, limited bandwidth, high power consumption, and signal spreading . The maiIn OR protocols, a subset of a node’s neighbors will be selected as next-hop forwarder set candidates. These nodes collaborate in a coordinated manner to continue forwarding the packet along toward the destination (sink) by using a prioritized technique according to the rules implemented by the protocol ,14,39. Tp and (0< p ≤ 1).Let us assume that the delivery probability of each link , the delivery probability is 0.4096 for the traditional routing, while by using Equation (2), we get a delivery probability of 0.9684 for the OR routing. Consider the following numerical example: assume Hence, by taking into account the advantage of the broadcast nature of the wireless transmission medium  and usinThe OR protocol technique is essentially constructed on two important building blocks, as illustrated with their classifications in Sender-side-based candidate set selection: in this category, beacon messages between the nodes in the networks are used to exchange the information of the sensor nodes and make it available within their neighborhood. The current forwarder node, which has a data packet to transmit, will use this information to facilitate its mission to determine its next-hop forwarder candidate set.Receiver-side-based candidate set selection: in contrast to the first category, this one requires the neighbors to check the data packet’s header when they receive a data packet from the sender in order to identify which received nodes are eligible to be candidate nodes and which ones are not. In this category, each neighboring node is responsible for determining whether it will be included in the list of the potential next-hop forwarder candidate set or not.Hybrid candidate set selection: In this category, the next-hop forwarder candidate set is determined cooperatively by the current forwarder node, which has the data packet to transmit, and its neighbor nodes by exchanging their information.The first building block in OR protocol design is the candidate forwarding set selection process. Selecting a subset of nodes from the source’s neighboring nodes to be the qualified set to carry on the packet and continue the forwarding procedure is the responsibility of this process. More generally, based on the next-hop forwarder node-selecting technique, the candidate forwarding set selection procedures can be classified into the three following categories ,25:SendeThe coordination phase is the second and most significant building block in constructing an OR protocol. In order to continue forwarding the data packet until it reaches its destination, the nodes in the next-hop forwarder candidate set must cooperate in a coordinated manner. According to the protocol’s regulations, the node with the highest priority  will transmit the packet in this case, deferring transmission to other candidates with lesser priorities. If the node with the higher priority cannot finish its transmission, the node with the next higher priority will begin its transmission, and so on, until the packet reaches its destination.By functioning in a coordinated manner, this building process supports enhancing the network’s throughput and the routing protocol’s accuracy by preventing packet duplication. Packet duplication causes unnecessary and redundant transmissions, wasting the node’s energy. Additionally, the overall collision rate can be decreased.Timer-based candidate set coordination: Each candidate node in this process has a holding time based on its priority. As a result, the candidate keeps the source’s received data packet in their possession for a while (the holding period). The remaining candidates will suppress their transmission if the highest-priority node successfully transmits the packet and if they get an indication during the waiting period. If not, the packet will begin to be forwarded by the node with the next highest priority when its holding time expires, and so on.Control packet-based candidate set coordination: The candidate nodes in this approach communicate with one another by exchanging control packets. Therefore, a candidate node responds to a packet with a brief control message. This control packet transmission is used to notify the currently active forwarder node that the packet has been successfully received. It also notifies the other low priority candidate nodes to pause their transmissions.The coordination procedures between the candidate nodes can be divided into the two following categories ,25:TimerThe existing OR protocols in UWSNs can be classified based on their positioning information into two main classifications: geography-based and pressure-based. In the first category (geographic-based), selecting the forwarding set candidates and making the forwarding packet decisions in OR requires information about the geographic location of sensor nodes. While in the pressure-based category the depth information of nodes is needed to select the next forwarding set candidates and make the forwarding packets decisions. This classification with the state-of-the-art reviewed protocols can be seen in Only a few protocols have been proposed to deal with the void communication area problem in UWSNs using the opportunistic routing technique. In this section, we will give a quick review of all the existing protocols.HydroCastAuthors in  presenteLocal Lower-Depth-First Recovery approach and 2-D Void Floor Surface Flooding for Recovery Path Search for a recovery mode. Where each void node  seeks out its neighbors to find a node with a lesser depth than itself, this lesser depth node could be another void node with a new recovery path or a sensor node in a position that helps to resume the greedy forwarding techniques. HydroCast also proposes a In the 3D network topology, nodes experiencing a void area employ a costly flooding technique to learn which nodes are best suited to resume greedy forwarding or identify alternative routes to better forwarding channels. However, it is difficult to estimate the limited 3D flooding probability value because the flooding could involve every sensor node and affect the entire network topology. They suggest 2D flooding on the surface of the void floor to get around this restriction and increase the effectiveness of the procedure. This flood will include the best possible collection of nodes. As a result, nodes on the surface will monitor their void floor surface status using their local connectivity information and forward packets accordingly, whereas nodes that are not on the surface but are controlled by surface neighbors will not forward packets.HydroCast addresses the void area issue using an OR approach, which also successfully enables increasing the packet delivery ratio with small end-to-end delays since a subset of the neighboring nodes simultaneously receive the data packet appropriately. However, at the same time, as a result of using opportunistic routing, the HydroCast protocol suffers from redundant packet transmission, where a data packet may be delivered to the sink multiple times, causing the depletion of network resources. In addition, in terms of energy efficiency, implementing the recovery mode results in additional energy costs. Moreover, there is no evidence provided about the energy consumed by the pressure sensor in order to find its depth.VAPRVoid-Aware Pressure Routing (VAPR)  is an anIn VAPR, any node that receives a beaconing message from a neighbor updates its neighboring table and examines its depth with the received depth information. The node then makes its own routing decision by removing void nodes  from its forwarding sets and chooses the overall best route to the destination as shown in GEDAR1D to 2D) to adjust its depth. Then it bypasses the void area to be able to communicate with other nodes trying to resume the greedy forwarding. Therefore, the void node first discontinues sending the gathered packets and starts calculating a new depth that will allow it to continue its OR greedy forwarding to deliver the data packet to the next hop.In , the proThe recovery technique used by GEDAR helps by bypassing the void area, which as a result, improves the networks connectivity and increases the packet delivery ratio. On the other hand, in energy consumption terms, this Depth Adjustment technique implemented by GEDAR exhausts a very high amount of energy in physical movement to adjust the network topology, and this will make nodes exhaust their energy rapidly and reduce the network lifetime.IVARAn Inherently Void Avoidance Routing Protocol for Underwater Sensor Networks (IVAR)  is a recChoosing a route with a lower hop count manages the energy consumption and reduces the packet delivery time. Besides, using the node’s depth assists in preventing packet duplication. On the other hand, because of the broadcast nature of the protocol and because the qualified forwarding nodes may be distributed around the forwarding node in various directions, the protocol cannot completely suppress route and transmission duplication. This limitation will cause the hidden terminal problem and, consequently, extra energy consumption. IVAR uses a periodic beacon by the sink to update the underwater nodes with their current position in the network. Therefore, all the routes from the sink to the sensor nodes will be established in advance, and all the routes directing the packets to void areas will be excluded. However, the beacon interval has to be chosen cleverly because it has a great effect on node information and communication efficiency, which consequently will impact network performance.OVARThe opportunistic void avoidance routing (OVAR) protocol  is a senVHGORConvex void handling: If the packet is stuck at the NCD node, VHGOR attempts to identify a different path to forward the same packet to the destination by removing the present forwarder and re-establishing the convex structure with remaining neighbors founded in the neighbor table (NT).Concave void handling or recovery mode: The void becomes concave when a packet gets trapped in a node without any neighbors with lower pressure levels, which means that its NT entry is empty. In order to reroute the packet along a different path to the destination, VHGOR manages the concave void by rerouting it down the recovery path, which runs from downward to upward. The previous sender chooses the subsequent NCD node from its NT to continue sending the same packet after receiving the packet from the concave empty node.Void handling using geo-opportunistic routing in underwater wireless sensor networks (VHGOR)  adopts g1 chooses node n2 to be the next forwarding node, since node n2 has the highest Expected Packet Progress (EPP) value in its neighbor table (direction number 1 in the figure). In the same manner, node n2 chooses node n3 as the next forwarding node and transmits the packet to it (direction number 2 in the figure). However, since node n3 is a void node and has no nodes to forward to, node n3 returns the message back to node n2 (direction number 3 in the figure). The next node in Node n2′s neighbor table is subsequently chosen as the next forwarder (direction number 4 in the figure). Since D is inside the transmission range of node n10, node n10 finally delivers the packet to D. In order to create the best forwarder from FCS, VHGOR takes into account residual energy, which helps cut down on energy consumption.VHGOR considers the residual energy in forming the optimal forwarder from the forwarding candidate set (FCS), which assists in reducing the energy consumption. Besides, employing opportunistic forwarding works in improving the delivery ratio at the same time introduces end-to-end delay to some extent .WDFAD-DBRIn , anotherIn WDFAD-DBR, the void nodes can remove themselves from the data packet routing to increase the opportunity for the other candidates in the forwarding set to forward the packet. In addition, to control the number of forwarding nodes, WDFAD-DBR divides the forwarding area into a constant primary forwarding area (the Reuleaux triangle) and two auxiliary forwarding areas, which might be extended or shrunk depending on node density and the quality of the channel. In terms of energy consumption, on one one hand, to help reduce the energy expenditure due to the duplicated packet transmission, the auxiliary forwarding area is divided into a number of smaller sub-areas, which helps save some energy. On the other hand, the periodic neighbor requests and the corresponding ACKs in a reply to each control packet exhaust the energy of the nodes and waste network resources. In order to bypass the void area, WDFAD-DBR successfully detects the void nodes and excludes them from the forwarding procedure. However, the protocol fails to detect the trapped nodes in advance. Moreover, when a fixed primary forwarding area is implemented by the protocol, the flexibility of the routing might be restricted in its ability to choose and adjust the forwarding nodes under various conditions.EVA-DBR and SORPIn ,51, the In terms of energy consumption, since the nodes do not need to send an ACK to the node’s neighbors as a reply to their control packets, the energy consumed per node will be somewhat reduced. In contrast, both protocols may allow the duplicated transmissions to increase the packet delivery probability in a sparse network in addition to periodic broadcasted information exhausting the node’s battery and, as a result, decreasing the network lifetime as well as the node’s life. And in terms of void avoidance, the state of excluded nodes from the forwarding set that announced themselves as void or trapped nodes may change during the transmission data packet or before the period of broadcasting information expires, which may effect the energy consumption and reliability of the network. Moreover, maintaining the neighboring table and the two-hop information will adversely affect the limited resources of the nodes .EDOVEThis section reviews the energy and depth variance-based opportunistic void avoidance (EDOVE) protocol that was presented in . EDOVE wFinally, to choose the best forwarder node, EDOVE makes the decision by calculating the holding time and selecting the receiving node with the largest residual energy, the greatest depth difference to the source, the greatest depth difference to its neighbor, and many neighbors with a large variance in their depth differences. More factors are taken into account by the protocol, which increases energy efficiency, prevents packet collisions, and extends network lifetime. However, in dense networks or when the size of the network is increased, there are increases in the probability of duplicated packet transmission because the number of nodes with the same depth will increase, making their estimated holding times almost the same. This results in an increase in data packet traffic, which in turn increases energy consumption. Additionally, the protocol views the void area only as a series of energy holes, despite the fact that it serves a variety of purposes, as stated above.TORAThe totally opportunistic routing algorithm (TORA) is proposed for UWSNs in . TORA isAt the water surface, the multi-sink network architecture is installed, and ordinary nodes drift in different levels underwater, as shown in To locate nodes in the network, the time of arrival (TOA) and range are used. Sinks periodically send hello messages to help collect node information that will be used to determine ordinary node location in the localization phase. Next, based on the nodes’ geographic coordinates and remaining energy, the best forwarding node that has a higher residual energy and is closer to one of the sinks will get a higher priority to relay the packet in the candidate forwarder selection phase. After that, the data transmission phase starts once a node has a data packet ready to send. This data packet should be delivered to one of the sinks in a multi-hop fashion through selected forwarding relay nodes. TORA utilizes 2-hop Ack to make sure that the packet has traveled for two hops and zero Acks to reduce end-to-end delay and retransmissions. As a conclusion, data is transmitted to the sink node using a combination of several short, active links.2EBER2) has been proposed to address the void areas. EBER2 adopts the potential forwarding nodes (PFN) concept to tackle WDFAD-DBR shortcomings. Since WDFAD-DBR experiences void area problems in some cases because it ignores taking into account the PFNs for the second hop, it suffers from high duplicate packets and collisions, which reduce protocol performance and efficiency. In EBER2, the network architecture consists of three types of sensor nodes , as demonstrated in In , an ener2 take into account three factors as primary parameters for choosing the next forwarder in order to address the WDFAD-DBR weaknesses. The first parameter is the weighting depth difference of two hops; by choosing the next forwarder node based on the depths of the first two hops, the likelihood of a network void area problem is reduced. The second factor is the number of PFNs, which are nodes that are within the source node’s upper hemisphere of its transmission range. A void node is one that has no PFNs; as a result, it is excluded from the upcoming forwarding set, which improves network stability. The residual energy is the third parameter, and it is used to provide PFNs with the same depth but varying holding durations in order to prevent duplicate packets. In addition to forming the next forwarder set and preventing void nodes from being chosen as candidates for the next forwarder, these three parameters also support energy efficiency, boost packet delivery ratio, and lengthen network lifetime by preventing duplicate packets and the ensuing collisions.The authors of EBER2 protocol deploys two additional embedded sinks in the underwater area of interest that have high traffic density, as can be seen from 2 employs a transmission energy adaptation mechanism that enables nodes that are closer to sinks to reduce their transmission power level in accordance with their distance from that sink. This minimizes the void area created by the death of these nodes by preventing the nodes close to the sinks from rapidly exhausting their energy due to being involved in the majority of forwarding procedures.To further assist these nodes in communicating with the embedded sinks and delivering data packets to them rather than travelling through a long path to reach the sinks on the surface, the EBEREDORQThe authors of  proposed(d) and void-flag information of the current node from the packet header after receiving the data packet and then compared d with its own depth. In order to ensure that the data packets are quickly sent in the sink’s direction, the greedy mode helps locate a collection of candidate nodes closer to the water’s surface. In order to achieve this, the void-flag field in the packet header is set to “0,” indicating that only nodes whose depth is less than the current forwarder are eligible to be chosen as candidates. However, the protocol switches to void recovery mode when the packet is stuck in the void node as, illustrated in EDORQ starts the forwarding process using greedy mode, where the current forwarding node broadcasts the data packet to its neighbors. Each candidate neighbor extracted the depth The current node will retransmit the data packet in a void recovery mode, where the value “1” is entered in the void-flag field, allowing the neighbor nodes with the greatest depth to be chosen as candidate nodes. A node should only forward packets with the same ID once for a predetermined period of time in order to reduce duplicate transmissions, comparable to the DBR. As a result, the new candidate set of current nodes would continue the forwarding process. The next best packet forwarder from the current node will then transmit packets in a greedy manner toward the sink if no other the void node is reached.RPSORIn , anotherIn RPSOR, two sinks are mobile, as can be seen in At the beginning of each simulation round, the network uses hello messages to assess the node density at various hops, and it then permits the sink to travel to any hops with a high node density. The nodes located at the following hop must transmit a large amount of load created by denser network locations. The majority of the packets are lost when this high traffic enters the network’s sparse area since the network cannot handle such high traffic levels. Utilizing the position data of the denser hop, which was acquired by the greeting message, the sink determines the vertical trajectory.PCRRecently, a novel power control-based opportunistic (PCR) routing protocol for the Internet of Underwater Things (IoUTs) was proposed in . They deBy changing the transmission power level at each hop, the PCR packet delivery ratio was enhanced in order to select the most suitable candidate nodes from the sender neighbors to continue passing data packets to the sink(s) on the water’s surface. In dense networks, PCR also lowers the node’s transmission power level to lessen the need for retransmissions, which lowers energy usage in some cases. The energy consumption is still higher than the related works, as we can see from their data, and this will shorten the lifespan of the network.SEEORVAA secure and energy-efficient opportunistic routing protocol with void avoidance for underwater acoustic sensor networks, (SEEORVA) was presented in . This prIn SEEORVA, the best forwarder selection was performed as follows: when a source node has packets to transmit, it creates a virtual vector pipe to the sink  results, it is also easy to implement with less overhead and delay. In addition, the encryption method ensures secure data packet transmission and avoids any leakage in data packets that can be harmful in any way.EEDOR-VAholder can easily construct its forwarding set. That is, sensor nodes use the information from the hop-count discovery algorithm to update their hop count from the sink(s) and exclude void and trapped nodes in the Pholder nodes’ transmission range from being included in the forwarding set. Periodic beaconing and its related costs is eliminated by the hop count discovery mechanism proposed in EEDOR-VA. The main goal of EEDOR-VA is to find as many loop-free paths as possible between a source node and a single or multiple sinks on the sea surface. The protocol can easily change the chosen route from one path to another by electing the next relay nodes from a different path if this relay node is the best choice in the next hop forwarding range. As a result, this technique prevents having to start the hop-count discovery process all over again. If all routes to all of the sinks fail, then a hop-count discovery is initiated. EEDOR-VA updates relay node information using route information and ensures that nodes responding to the Pholder have a path to one of the sink(s) in order to avoid the void nodes. The EEDOR-VA protocol’s process is depicted in In , the mosThe EEDOR-VA protocol uses rounds; every round is comprised of three phases: a hop-count discovery phase, a forwarding set creation phase, and a data packet forwarding phase.holder forms its next-hop forwarder set based on the extracted candidate information, and only a candidate with a hop count less than the Pholder hop count, no matter if it has less or more depth than the Pholder, will be added to that Pholder next-hop forwarder set. Finally, Pholder integrates the data packet with the sorted list of the selected forwarding candidate IDs and transmits it to its neighbors. Each neighbor checks the packet header and simply drops the packet if it cannot find its ID in the attached list or starts computing its holding time otherwise.The hop-count discovery phase is in charge of determining the hop count of any source and/or relay nodes in the network to the sinks, whether the sink(s) are directly reachable within the transmission range of the source or reachable via one or more hops through relay nodes. Once the hop count of each of the route nodes is defined, the forwarding set formation phase is started. In each hop, the PThe EEDOR-VA protocol uses the node’s hop count as the first metric to identify the best forwarding node and the node’s depth as a secondary metric in the event of a tie. The best forwarding node will transmit the data packet immediately after receiving it to continue the forwarding process. Other forwarding candidates will drop the packet if they successfully hear the transmission from the most appropriate node. If not, the data packet will be transmitted by the following node in the sorted list, and so forth. These processes will be repeated hop by hop until the data packet reaches the sink or all the candidate nodes in the forwarding set fail to do so.In the previous section, the literature review of the state-of-the-art of the OR protocols that are proposed for UWSNs to address the void area problem is presented. The main challenge in the protocols was to handle the void area problem by using different approaches. The occurrence of the void area in the routing path can significantly reduce network performance. In this section, the general comparison of these reviewed protocols based on their characteristics and features is summarized below in In The reviewed protocols are divided into sender-side and receiver-side categories based on which node will decide if the candidate node can be added to the next hop forwarder set or not. A higher communication overhead is needed on the sender-side because the sensors frequently need to exchange node information in order to update their neighbors’ tables. As a result, the limited resources of the node  are used up. On the receiver-side, the sender is unaware of its neighbors and is unaware of its forwarding set. This may result in a significant number of redundant broadcasts and raise the possibility of transmission collisions requiring reiterate transmissions. The entire network stability period may be shortened as a result of packet loss and sensor node energy consumption. A number of these protocols take advantage of the multi-sink architecture and consider the data packet as delivered if it reaches one of the deployed sinks on the water surface. This improves the network reliability.These state-of-the-art protocols employ various void area handling techniques to address the void area problem in order to increase network performance and deliver data packets properly.Moreover, Energy efficiency: Due to the harsh underwater environment restrictions and limitations on recharging or replacing the deployed sensor node, energy efficiency is a major constraint that can restrict many applications from achieving their goals. The current focus of study is on energy conservation and routing process energy optimization. Future studies will continue to focus heavily on this topic.Channel utilization: effective and efficient channel usage is a significant area of investigation in UWSNs that has attracted a lot of attention; it has an effect on energy consumption and void areas that form easily in UWSNs. The channel must be used to its full potential to overcome its limitations, like interference, high error rates, continual sensor node mobility, and propagation latency.Void areas: Due to the reasons listed in Security: A significant area of concern is the security of data exchanged between sensor nodes. The security of data is the most crucial issue in many UWSN applications, especially the military ones. In such applications, any information leak could lead to harmful effects and severe repercussions. To secure the connection between the sensor nodes in UWSNs as attacks and threats grow, investigations that consider security and privacy will be a continuing and extremely difficult effort.These are some of the most significant and active fields of research for UWSNs that need more investigation, and they will remain so in the upcoming years.These days, opportunistic routing in UWSNs has drawn a lot of attention from researchers. OR has been shown to be more effective than the conventional routing strategy for wireless networks because it makes use of the broadcast nature of wireless networks. A number of factors have an impact on the performance and effectiveness of the UWSNs, including a shortage of resources (restricted battery power and memory), the harsh underwater environment, and a weak communication channel. The void area problem employing an OR approach is one of the significant concerns and research challenges in UWSNs. We have investigated in this paper the existing OR protocols proposed to address this problem.First, we discussed the aspects of routing protocols for UWSNs covering the main challenges facing researchers when designing routing protocols, the concept of the void area problem in UWSNs, and reasons for this problem. OR and its key elements, including OR construction blocks and OR classification have been introduced. Second, the state-of-the-art void avoiding protocols that use the OR technique were investigated in depth. The reviewed protocols have then been compared in many aspects, including the type of protocol, number of sinks, network topology requirements, and the special information required or needed to be maintained during the data packet routing. Their advantages and limitations were listed in the last two columns of


Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks). Various types of optical fiber sensors have been widely applied to structural health monitoring thanks to the intrinsic advantages of the optical fiber, such as small size, chemical inertness, immunity to electromagnetic interference, and so on . RecentlDistributed fiber sensors (DFSs) rely on various backscattering mechanisms in the fiber and perform the spatially resolved measurement over the whole fiber length. The Raman-based DFS exploits the optical power change of the anti-Stokes component of the spontaneous Raman scattering to retrieve the temperature information. The DFS based on Brillouin scattering usually uses the Brillouin frequency shift to measure temperature and strain with a typical sensitivity of 1 MHz/K and 0.05 MHz/με, respectively, and at an operating wavelength of 1550 nm . Since sA distributed acoustic sensor (DAS), also known as coherent optical time domain reflectometry (COTDR), retrieves the environmental information based on the interference result of the Rayleigh backscattered light . It fulfThe COTDR system is meant to find many applications in structural health monitoring. Particularly, it can be used to determine the vibration frequency of a bridge and provide a warning if the bridge vibrates close to its natural frequency. Such a sensor has the potential to measure the acoustic emission, allowing the cracks in the bridge to be detected . The senIn this paper, we report the measurement results using an intensity-based COTDR system during a destructive testing of a bridge in Germany. More information about this bridge can be found in . This isRayleigh scattering originates from the density variation of the medium that is formed during the fiber drawing process, and it accounts for most of the fiber loss at 1550 nm. A COTDR system sends narrow and highly coherent optical pulses into the sensing fiber and collects the interference result of the Rayleigh backscattered light. Due to the stochastic distribution of the fiber density, the interference process is totally random and changes with the fiber position, thus the obtained COTDR trace exhibits a noise-like shape along the fiber . AlthougThe intensity-based COTDR system fails to quantify the measurand because the signal change has not even a monotonic relationship with the environmental variations . Hence, The configuration of the sensing system used for bridge monitoring is depicted in The pulse width was set as 10 ns during the measurement, corresponding to 1 m spatial resolution. The bandwidth of the photodetector was 125 MHz, which could guarantee the spatial resolution ,24. The The superstructure of the concrete bridge was ~37 m wide and over 150 m long. There were several box girders in the main beam with a height of ~1.5 m. Detailed information is provided in . A standFor each measurement, the sawing process lasted several minutes; however, the sensing system continued to acquire data over tens of minutes. Hence, many results were obtained during the three-day test, and only a few exemplary results are presented here.S is actually a 3D matrix in time, distance, and frequency domain. The raw data presented in The figure exhibits significant signals at ~10 ms due to the sawing process. For the fibers installed below and above the bridge, most of the signal was below 10 kHz, as shown in Although the measured frequency spectra vary from case to case, the last fiber section always experiences the most intense vibration, as demonstrated by The frequency analysis also helps identify the vibration events. The STFT results within the frequency range between 0 Hz and 20 kHz are summed up at each position and time point. The obtained results for each fiber section are plotted in Another usage of the frequency result is to detect the effective sawing during the whole measurement. In this case, the STFT result over each sensing section and the whole frequency range is summed, so the obtained data changes only with time. The summation results for all three sensing sections are plotted in The inset in The STFT result as shown in One of the unexpected acoustic events, as signified by the arrow in the inset, was thoroughly investigated. The raw data and the data change are plotted in The signal from the fiber section inside the girder was further analyzed in frequency domain. The STFT result of the signal at the starting point (203.5 m) is shown in This paper reports the results of an intensity-based COTDR system measured during destructive testing of a bridge. The sawing-induced vibration was thoroughly investigated in time and frequency domains, and a handful of valuable results were obtained which can aid in bridge health analysis. In practice, the sensing fiber will be deployed as a net to cover most of the bridge. Thus, many fiber sections can measure the same vibration at slightly different times. The propagation speed and the location of the vibration can be determined by the position of the fiber section and the difference in the detection time. In addition, the COTDR system acquired unexpected signals which exhibited different characteristics from the sawing-induced signal. The job of the COTDR system is to detect and locate any vibration events, which may be related to damages inside the bridge. This system can also provide meaningful signals in time and frequency domains so that civil engineers can identify the events based on the detected signal, making the structural health monitoring of the bridge possible.The COTDR system has also been demonstrated as an effective tool for traffic monitoring in our previous publication , and the


Surgical care, which is performed by intensely interacting multidisciplinary teams of surgeons, anesthetists, and nurses, remains associated with significant morbidity and mortality. Intraoperative communication has been shown to be associated with surgical outcomes, but tools ensuring efficient intraoperative communication are lacking. In a previous study, we developed the StOP?-protocol that fosters structured intraoperative communication. Before the critical phases of the operation, the responsible surgeon initiates and leads one or several StOP?s. During a StOP?, the surgeon informs about the progress of the operation (status), next steps and proximal goals (objectives), and possible problems (problems) and encourages all team members to voice their observations and ask questions (?). In a before-after study performed mainly in visceral surgery, we found effects of the StOP?-protocol on mortality, length of hospital stay, and reoperation. We intend to assess the impact of the StOP?-protocol in a cluster randomized trial, in a wider variety of surgical specialties . The primary hypothesis is that the consistent use of the StOP?-protocol by the main surgeon reduces patient mortality within 30 days after the operation. The secondary hypothesis is that the consistent use of the StOP?-protocol by the main surgeon reduces unplanned reoperations, length of hospital stay, and unplanned hospital readmissions.This study is designed as a multicenter, cluster-randomized parallel-group trial. Board-certified surgeons of participating clinical departments will be randomized 1:1 to the StOP? intervention group or to the standard of care (control) group. The intervention group will undergo a training to use the StOP?-protocol and receive regular feedback on their compliance with the protocol. The surgeons in the control group will communicate as usual during their operations. The unit of observation will be operations performed by cluster surgeons. Consecutive patients will be enrolled over 4 months per cluster. A total of 400 surgeons will be recruited, and we expect to collect patient outcome data for 14,000 surgical procedures.The StOP?-protocol was designed as a tool to structure communication during surgical procedures. Testing its effects on patient outcomes will contribute to implementing evidenced-based interventions to reduce surgical complications.ClinicalTrials.gov NCT05356962. Registered on May 2, 2022The online version contains supplementary material available at 10.1186/s13063-022-06775-y. Each year, about 4.2 million people die within 30 days following a surgical procedure . FurtherOutcomes of operations depend on many factors. Patient factors are pivotal; additional factors include structural as well as procedural aspects . Regardipatient outcomes, our own observational study [intraoperative information sharing and patient outcomes.There is mounting evidence, however, that communication and teamwork within the surgical team are important for patient outcomes, and studies are needed that aim at improving teamwork and assessing clinical patient outcomes . Researcal study  demonstral study  showing Core aspects of effective communication are creating and maintaining high levels of situation awareness in surgical teams—this is a (shared) perception and knowledge regarding important elements and the development of the situation that indicate  a need for action , 15. Sitchecklists and briefings [general teamwork and communication training, typically conducted in a specific training setting. Although such training settings may be realistic  [Common methods to improve communication in the OR are based on riefings , typicalriefings , regard riefings . A seconlations) , they calations) , and tralations) . Furtherlations) . Successlations)  and for lations) –28. Howelations) , 28, 29.lations) , 25, 30.Status of the operation , then states the Objectives , the potential Problems they may encounter, and, finally, asks if the team members have contributions or questions (?). The briefing is very short (30–90 s) and requires the attention of the entire OR team (including anesthesia and circulators), who is asked to stop working during the briefing. The StOP?s are used in a flexible way at times when they do not interrupt the flow of the operation or actions that require full attention of the surgeon. The surgeons thus choose when they perform the StOP?-protocol and are asked to announce during the pre-operative team timeout when they intend to perform the StOP?-protocol(s).In an attempt to encourage structured information exchanges during surgical procedures, we developed an intervention aimed to assure structured information exchange during operations, the StOP?-protocol . The StOIn a before-and-after design, the StOP?-protocols were introduced in four surgical departments of four different hospitals  in 8256 operations   and the operation level.Study sites, i.e., departments employing surgeons specialized in general, visceral, thoracic, vascular surgery; surgical urology; or gynecology, will be eligible to participate in the study. This choice was guided by the mortality rates of about 1% in these specialties –39, whicBoard-certified surgeons in one of the specialties of interest will be recruited. Surgeons who are already performing StOP?-protocols  will be excluded. Resident surgeons will not be recruited as clusters, since they either assist or perform surgical procedures under supervision, and since they are still in training, an additional task may interfere with their technical performance.Elective and emergency operations performed by a cluster (surgeon) during the cluster-specific time period will be considered for inclusion. We expect an operation volume of 30 eligible operations per surgeon within 4 months. This number is the target per cluster but the actual number will vary among surgeons.Patient age below 18 yearsPrevious operation at the same site up to 30 days prior to the index operationProcedures not done in operating rooms but in outpatient clinics, onwards, etc.Mainly diagnostic endoscopic procedures Percutaneous interventions Documented refusal of the patient for the use of healthcare-related dataExclusion criteria for operations include the following:On the participating study sites, board-certificated surgeons will receive detailed information on the study to decide on participating. Each participating surgeon will sign an informed consent defining tasks, responsibilities, potential risks, and benefits. The investigators will explain to each surgeon the nature of the study, its purpose, the procedures involved, and the expected duration. Each surgeon will be informed that the participation in the study is voluntary and that he or she may withdraw from the study at any time.On the consent form, participants will be asked if they agree to the use of their data should they choose to withdraw from the trial. Participants will also be asked for permission for the research team to share relevant data with people from the universities taking part in the research or from regulatory authorities, where relevant.The StOP?-protocol is an intraoperative briefing addressing communication within the surgical team. The study has no impact on the medical treatment of the patient. Therefore, this study is performed based on a general consent from the patients, where they agree with the use of healthcare-related data that are the result of the patient’s treatment.The surgeons in the intervention group will undergo a multi-module training on how to use the StOP?-protocol . The traSurgeons in the control group will not be trained. They represent the standard of care, using local practices, and are asked to communicate as usual during their operations. Given the nature of the study, these surgeons will not be blinded to the intervention.In each participating site, the anesthesiology and OR nurses team will be informed about the study. The information will consist of a presentation of the study by the research team and flyers will be available to inform about the StOP?-protocol and the study goals.The following data will be collected.Basic characteristics of the study sites will be recorded, such as the language region, hospital type, number of beds, number of employees, number of operating rooms, yearly operating volume, hospital teaching category, number of staff in training, current practices of the WHO timeout and signouts, and previous team training history.Data collected about all participating surgeons include age, gender, nationality, native language, year of primary medical degree, year of general and specialized surgery degrees, tenure at the current hospital, tenure in current position; hierarchy level, job title, study arm, and time frame of participation in the study. For surgeons in the intervention group, additional information collected are adherence rates and whether the initial training, and retrainings took place.We will collect data about the type of operation, date of admission, date of operation, time of incision, time of last stich, duration, surgical access, level of urgency, and IDs of the surgeons and residents present during the operation. Patient characteristics include gender, age at the time of operation, height, weight, previous laparotomies at the same site 30 days prior the operation, ASA score, and wound contamination class.The intervention is a behavioral intervention that requires the surgeon to remember and implement a new behavior pattern; thus, adherence needs to be assessed. Adherence to the StOP?-protocol will be measured for each operation. Adherence is assessed using a standardized reporting form filled in by each scrub technician present during the operation before they leave the operating room. They report if and how many StOP?s were performed during their presence and provide a simple quality rating of the StOP?s on a Likert scale from 1 (very bad) to 5 (very good); a definition of the characteristics of a good StOP? is provided , engaged, the complete team stopped working and paid attention). Adherence of reporting by the scrub technicians will be calculated by comparing the number of operations performed with the number of reports submitted. Adherence to the StOP?-protocol will be calculated by comparing the adherence reports of the scrub technicians for surgeons in the intervention group with the number of operations performed by these surgeons.The primary endpoint is death up to 30 days after the start of the index operation. This information will be provided by the hospital. The hospital obtains the information from patient records and, if not available, via the patients directly, the family, or the general practitioner.Unplanned reoperation within 30 days is defined as any operation after the end of the index operation for up to 30 days. Only reoperations within the same hospital of the index operation will be considered. The definition of type IIIb  of the Clavien-Dindo Classification will be used to define this variable . Data wiLength of index hospital stay is defined as days between the index operation to discharge or transfer to another hospital. In-hospital deaths will be recorded and considered as censoring events. Data will be obtained from medical records.Unplanned readmission within 30 days is defined as any unplanned readmission at the same hospital as the index hospital within 30 days after the operation. Readmissions that are mentioned already in the discharge letter of the index hospital stay are considered planned if the reason for the readmission matches to the one described in the discharge letter. Data will be obtained from medical records.We plan to conduct additional analyses on surgical site infections as an endpoint. Data on surgical site infections are collected according to international standards defined by the Centers for Disease Control and Prevention (CDC) by the surveillance system of Swissnoso—the national center for the prevention of infections in Switzerland. Type 1 , type 2 , and type 3 (organ/space) infections are distinguished (91). Swissnoso collects data only in Switzerland and only for a subset of operations. The data will be obtained from Swissnoso and form a pragmatic subsample of data that is available.The following secondary endpoints will be assessed:Based on the previous study (StOP? I) , retentiEnrolled clusters will be randomized in a 1:1 fashion to either the StOP? or the standard arm. Randomization will be stratified by surgical department and seniority (Chef-/Leitende Ärztin/Arzt versus other).Allocation will be done using a web-based system, which also contains the electronic case report form (eCRF): REDCap. The system reveals the allocation only after a cluster is definitely enrolled in the trial, i.e., eligibility criteria confirmed.Dedicated study personnel will establish a list of eligible surgeons. After obtaining informed consent from the surgeons, the responsible study personnel will transfer the list of enrolled clusters to CTU Bern. There, an independent data manager will allocate these clusters to the two trial groups (batch randomization) and will create a new cluster record within the web-based system. The system will disclose the assignment only after the completion of this registration.z-test with standard error adjusted by the intracluster correlation and varying cluster size. With 400 clusters overall , an average size of 24 patients per cluster, and a coefficient of variation of 0.5, we will achieve 84% power at a significance level of 0.05 (two-sided).Sample size calculations were based on the primary objective, i.e., whether patients in the StOP? intervention group have a lower risk of mortality compared to patients in the standard of care group. The primary effect measure will be odds ratio as the primary analysis will be based on a logistic regression (see below). Based on the data from the first StOP? study, we calculated an intracluster correlation coefficient (ICC) of 0.024 from a mixed-effects logistic model. Also, we estimated 30-day mortality from the before phase of the StOP? study and use this number (1.8%) for the event rate in the control group. The target treatment effect that we do not want to miss is an odds ratio of 0.5, i.e., we aim to reduce mortality in the StOP? intervention group to 0.9%. Sample size calculations were done in Stata (release 16.1) using the power twoproportions command with the cluster option. The command calculates power based on a We assume that some patients will be operated by two disparate surgeons . To accommodate this, we fixed the target average cluster size at 30 patients. This sample size allows for varying cluster sizes to accommodate differences in operation volume across clusters . A minimum of 12,000 patients will be required. Based on the experience of the StOP? I study, we expect that some surgeons perform many more operations than the assumed upper cluster size. Therefore, we expect that 14,000 patients will be enrolled overall. Given the relatively low number of events, we performed simulation studies to check the robustness of the assumption of an asymptotically normally distributed test statistic. Using a random-effects logistic regression in 1000 simulated trials with the same assumptions as described above, we calculated a power of more than 90%.We also performed several sensitivity analyses to account for the uncertainty of our assumptions, e.g., (1) allowing for a larger variation in cluster size (coefficient of variation of 0.7) results in 82% power; (2) allowing for the unlikely case of higher intracluster correlation (ICC of 0.03) results in 80% power; and (3) allowing for enrolment problems i.e., 370 clusters but similar cluster size results in 80.9% power or a similar number of clusters but smaller average cluster size (21 patients) results in 80.6% power.p-value. The primary null hypothesis of no difference in mortality between the two groups will be rejected if the two-tailed p-value is < 0.05.The primary analysis will follow the intention-to-treat (ITT) principle. We will assess outcomes at the patient level, accounting for the correlated nature of data within surgeon and hospital by using multilevel mixed-effects models. The primary outcome  will be presented as a number and proportion for each group. We will incorporate random intercepts for surgeons and units in the multilevel models and adjust for variables related to the site, surgeon characteristics, and type of operation. The odds ratio of death for the intervention vs. the control group will be presented with a two-tailed 95% confidence interval (CI) and accompanying Binary secondary outcomes (unplanned reoperation and readmission) will be analyzed with the same model approach as used for the primary outcome. For the time-to-event outcome length of stay, we will use a multilevel mixed-effects parametric survival model parameterized as an accelerated failure time model. Random and fixed factors will be used as described above. The results will be presented as the difference in days with 95% CIs. Length of stay will be censored at the time of death or transfer to another hospital. Depending on the number of in-hospital deaths, we will consider a competing risk regression as the primary analysis approach for this outcome. Differences between the groups will be evaluated using multilevel mixed-effects linear regression, adjusting for random and fixed factors as described above. The results will be presented as the mean difference with 95% CI.We will report results in accordance with the 2010 Consolidated Standards of Reporting Trials (CONSORT) statement extension to cluster-randomized trials .As a secondary analysis, we will perform a per-protocol analysis, excluding operations where the surgeon in the intervention group did not adhere to the protocol and where surgeons in the control group actually performed a StOP?. However, it is now well known that a naïve per-protocol analysis is problematic as it does not properly take confounding/selection bias into account . Direct Because cluster randomization may lack the optimal balancing in characteristics between the groups seen in individual-level randomization, we will adjust each model for additional pre-defined patient-level, surgeon-level, and hospital-level variables to account for case-mix differences between the groups in a sensitivity analysis. Moreover, we will qualitatively assess the imbalances of hospital, surgeon, and patient characteristics between the groups. If we observe relevant imbalances in covariates not considered in the primary and sensitivity analyses, we will perform additional adjustments and consider propensity score-based approaches to assess the robustness of our results.In exploratory analyses, we will assess the adherence and study the influence of the number of StOP?-protocols on outcomes. Such analyses include the assessment of the impact of surgeons’ gender or patients’ gender on primary or secondary endpoints.We plan exploratory analyses based on the collected data. One such analysis concerns predictors of adherence to the protocol, based on adherence data. We also plan to investigate the changes in outcomes based on surgeon experience with the StOP?-protocol  both surgeons are from the intervention group (25% of interactions), (ii) both surgeons are from the control group (25% of interactions), and (iii) one surgeon is from the intervention group and the other from the control group (50% of interactions). The observations from the StOP? I study showed that collaborations between board-certified surgeons are much more common in university (90% of the procedures) and large teaching (30% of procedures) hospitals, and less frequent in rural hospitals (5% of the procedures). We take this into account for the sample size calculation and the data analyses.We will conduct exploratory analyses for operations jointly performed by surgeons that are assigned to different treatment groups with a special emphasis on the influence of hierarchical status on adherence to the StOP?-protocol.The main analysis will be based on the intention-to-treat analysis set where all operations of a randomized surgeon done during the enrolment period are analyzed in the randomized arm, regardless of adherence. The per-protocol analysis set consists of all operations where the surgeon was adherent, i.e., if a surgeon in the control group performs a StOP?-protocol during an operation, such operations will be excluded and, if a surgeon in the intervention group does not perform a StOP?-protocol, such operations will be excluded.We do expect only few missing data with respect to the primary outcome . We will impute missing outcome data based on all available baseline characteristics of hospitals, surgeons, and patients using chained equations. Analyses will be conducted as described above using Rubin’s rules to combine measures across multiple data sets . This wimedRxiv.org) and submit it to a peer-reviewed journal. At publication of the primary results, the full protocol, the data management plan including the codebook of the trial database, and information on how to get access to the primary trial data will be published in the repository of the University of Bern which fulfills the FAIR criteria (Bern Open Repository and Information System (boris.unibe.ch)). A 12-month grace period after publication of the primary results is currently foreseen to allow all collaborators to complete additional, pre-planned analyses and projects.We will deposit the final protocol in a preprint repository  is established, and possible sample size adaptations or trial termination for futility will be decided by the Steering Committee.This is an open-label trial as the intervention cannot be blinded. Given the nature of the primary endpoint, the risk for ascertainment bias is considered negligible. Follow-up data collection is centralized and will be done by blinded personnel.The schedule and timelines are presented in Tables Figure This study is conducted in compliance with the protocol, the current version of the Declaration of Helsinki, ICH-GCP in analogy, and applicable national regulations, i.e., the Human Research Act in Switzerland as well as other locally relevant legal and regulatory requirements.Requires inpatient treatment not envisaged in the protocol or extends a current hospital stayResults in permanent or significant incapacity or disabilityIs life-threatening or results in deathCauses a congenital anomaly or birth defectStOP? II is regulated by chapter 4 of the Clinical Trial Ordinance. Chapter 4 describes the safety documentation and notification requirements for serious adverse events (SAEs). It defines (Art. 63) SAEs that have to be documented (and reported) as any event which:And it cannot be excluded that the event is attributable to the intervention.Given the nature of the intervention, we submit that Article 63 is not directly applicable to this trial. Unless there are specific reasons to assume an involvement of the StOP?-protocol, we will not routinely record serious adverse events and therefore also not foresee this in the case report forms and standard operating procedures. We base this decision on the following reasons: (1) the intervention is not directly applied to patients; (2) the nature of the intervention and the perceived mechanism practically exclude any direct effects; rather, the intervention entails its effects (if any) indirectly see ; consequInstead, we record relevant data with regard to safety as primary and secondary endpoints. Not applicable as described aboveNot applicable as described aboveIf immediate safety and protective measures have to be taken during the conduct of the study, the investigator notifies the responsible ethics committee of these measures, and of the circumstances necessitating them, within 7 days.An annual safety report (ASR/DSUR) containing relevant safety information from all sites is provided by the sponsor. Relevant safety information in this case means descriptive statistics of accumulating primary and secondary endpoint events pooled across trial arms. Pooling of trial arms is necessary to avoid multiple testing. The sponsor distributes the ASR/DSUR to all the participating Investigators. It is submitted once a year to the local ethics committee by the investigator.Substantial changes to the study setup and study organization, the protocol, and relevant study documents are submitted to the Ethics Committee for approval before implementation. Under emergency circumstances, deviations from the protocol to protect the rights, safety, and well-being of human subjects may proceed without prior approval of the Ethics Committee. Such deviations shall be documented and reported to the Ethics Committee as soon as possible.Substantial amendments are changes that affect the safety, health, rights, and obligations of participants, changes in the protocol that affect the study objective(s) or central research topic, changes of study site(s), or of study leader and sponsor.www.swissethics.ch.A list of substantial changes is also available on A list of all non-substantial amendments will be submitted once a year to the responsible Ethics Committee together with the ASR.○ Ethical concerns○ Insufficient participant recruitment○ Alterations in accepted clinical practice that make the continuation of the study unwise○ Early evidence of harm of the experimental interventionThe sponsor may terminate the study prematurely according to certain circumstances, e.g.:Upon regular study termination, the Ethics Committee is notified within 90 days.Upon premature study termination or study interruption, the Ethics Committee is notified within 15 days.To compensate trial participants for study-related damage or injuries, liability is provided per local regulations.Trial and participant data will be handled with utmost discretion and is only accessible to authorized personnel who require the data to fulfill their duties within the scope of the study. On the CRFs and other study-specific documents, participants are only identified by a unique participant number.Characteristics of participating hospitals Characteristics of participating clinical departments (department data)Characteristics of participating surgeons including allocated trial arm and training details (surgeon data)Patient keyCharacteristics, operation, and outcome data of the patient (patient data)Adherence to the StOP?-protocolThe following data will be centrally stored:Linkage of data will be ensured via unique keys. Data 1–4 will be stored in a GCP-compliant trial management system on the same server. Data 1, 2, and 4 do not contain directly identifying person data. The surgeon data (#3) contains the name of the surgeon. This will be mentioned explicitly in the informed consent. The identifying data of the surgeon will only be visible for data entry personnel. The system prohibits to generate lists of names or to export the names. Given the data that must be collected for each surgeon and the limited number of surgeons per clinical department, we consider it identifying whether or not it contains the name.Identifiable data of patients will be stored in a physically separated GCP-compliant database. Access to the database will be restricted to data entry personnel. After the closure of the database containing participant data, each site will receive a list of their patients (participant log) for archiving. After all sites confirmed receipt of their list, the database will be (completely) erased. A codebook describing the set-up of the database will be stored in the Trial Master File. The data on adherence to the StOP?-protocol will be collected via questionnaires filled out by the scrub technicians after each operation (#6). To identify the operation, the scrub technicians will put the patient sticker on the paper questionnaire and deposit the questionnaire in a sealed box within the operation room ward. The paper questionnaires will at no point leave the hospital. The research team will enter the questionnaires into the system, and the data will be coded at this point, so that no identifying information will remain with the electronically stored adherence data.All study data are archived for at least 15 years after study termination or premature termination of the study.The expected results may reveal if clinical outcomes can be improved by addressing team behavior during the performance of complex surgical procedures. In particular, the study has the potential to provide evidence that a short  and inexpensive intraoperative briefing may reduce mortality and morbidity. The results of the study will be of interest not only to surgical specialists but also to a wide public, and therefore, progression and findings will be communicated to healthcare workers of other specialties.As benefits, we expect that this simple, cost-efficient behavioral intervention will improve the quality of peri-operative communication and consequently reduce the risk of errors associated with the intervention and peri-operative care, eventually reducing post-operative patient mortality, unplanned reoperations, readmissions, and reduce the length of hospital stay. If the study reveals a positive effect not only on mortality, it is likely that the StOP?-protocol has importance for even more types of operations including operations of the head and neck and orthopedic procedures, and it may be extended to disciplines that mainly perform percutaneous interventions such as cardiology, angiology, and neuroradiology that typically are associated with other complications than mortality.From a clinical perspective, the risks of the study seem minimal. In the StOP? I trial, we did not observe adverse events or risks associated with the intervention itself. The primary treatment is not affected at any time by these interventions. Distraction or irritation of the personnel or prolongation of the surgical procedures because of the briefings has not been observed between the two groups. Surgeons in the intervention group perform the StOP?-protocol according to the manuals and training. We will not define the criteria for modifying the intervention, as the surgeon is allowed to adapt the timing and execution of the protocol according to the procedure. This flexibility of the StOP?-protocol is a central part of the concept. Overall risks of StOP? seem comparable to the risk of conducting preoperative time-out that is now standard worldwide.However, from a scientific perspective, there are some risks inherent to this study:Threat of bias of contamination: Given that the study aims to change the behavior of surgeons in the treatment group, potential bias or contamination of the surgeons enrolled in the control group needs to be addressed:○ First, surgeons in the control group will not undergo the StOP? training, but they will not be blind to the intervention as surgeons within a department work closely together. This could be a source of contamination, because surgeons in the comparator group may observe StOP?s performed while they operate with a surgeon in the intervention group. If surgeons in the comparator group observe communication behavior that they judge as promising, they may be motivated to copy this behavior. However, sporadic observations of others’ behaviors are not sufficient to sustainably change a behavior. Active strategies are needed to improve adherence to and ensure the sustainability of behavioral interventions, such as audits and feedbacks .○ Second, different hospitals will be included in the study and some may already have implemented a sign-out. Surgeons in the intervention group will explicitly be asked to reflect what extent the StOP?-protocol may be associated to the sign-outs, so that both can be combined during the operation in the case they already work with sign-outs. We will record the communication practices of each hospital (including sign-outs) and statistically control for these practices in the analysis.Threat of potential interaction between the treatment and the control group: An important aspect is that surgeons in the comparator group may be operating together with surgeons in the treatment group within a surgical department. Thus, a not trained surgeon may participate in operations where a StOP?-protocol is done; this could lead to direct interactions. As discussed in the section on statistical methods for additional analyses, we expect different interactions (i.e. (i) both surgeons are from the intervention group, (ii) both surgeons are from the control group, and (iii) one surgeon is from the intervention group and the other from the control group). These different interactions were taken into account in the sample size calculation and will also be taken into account in the data analysis and allow for interesting future analyses. If a surgeon from the intervention group collaborates with a control group surgeon, we define that during the collaborative phase, the surgeon with a higher hierarchical status acts according to his or her study condition. Thus, an intervention group surgeon with lower hierarchical status will not have to initiate StOP?s in the presence of a control-group surgeon with a higher hierarchical status.○ Dr. Sandra Keller, post-doctoral fellow, work psychologist, project managerThe entire study is coordinated by a steering committee. The steering committee consists of○ Prof. Guido Beldi, principal investigator, staff surgeon, Department for Visceral Surgery and Medicine, University of Bern, SwitzerlandThe project manager will be responsible for organizing the information about the StOP?-protocol at the participating hospitals; for overseeing the recruitment of the surgeons on-site; for collecting the data related to the participating surgeons and hospitals; for organizing the StOP? training—including individual instruction-interviews with the surgeons in the interventional group; and for the implementation of the StOP?-protocol—including on-site observations and monthly feedbacks to each surgeon in the interventional group.○ Prof. Tanja Manser, co-principal investigator, Director School of Applied Psychology, University of Applied Sciences and Arts Northwestern Switzerland FHNWThe principal investigator is responsible for the management and integrity of the design, conduct, and reporting of the research project and for managing, monitoring, and ensuring the integrity of any collaborative relationships. The PI ensures contact to the participating centers and ensures inclusion of sufficient participating centers.○ PD Dr. med. Sven Trelle, director, Clinical Trial Unit (CTU) Bern, University of BernThe co-PI is responsible for the management and integrity of the design, conduct, and reporting of the research project and for managing, monitoring, and ensuring the integrity of any collaborative relationships. The co-PI ensures the scientific integrity of questions related to work psychology.○ Prof. em. Franziska Tschan, professor emeritus for work psychology, University of Neuchâtel○ Prof. em. Norbert Semmer, professor emeritus for work psychology, University of BernCoordinates the study team of the CTU Bern and guarantees the statistical and analytical integrity of the trial. The CTU will be responsible for collecting patient data and will collaborate closely with the team of psychologists with regard to the different tasks listed above. The CTU is responsible for data analyses.Prof. Tschan and Prof. Semmer were deeply involved in the StOP? I study as well as in the design of the current study and thereby add to the psychological expertise on communication and coordination in surgical teams, and they assure continuity between the first project and the current one.The steering committee meets at least biweekly via videoconferencing. An agenda is sent at least a day beforehand and a protocol is written and distributed for each meeting by an administrator (Franka Theile). The steering committee is also responsible for the study in the coordinating center.An advisory board has been established including representatives of patients, public, patient organizations, and medical faculties. Throughout the study, the advisory board shares findings of important research and raises the awareness among the public that the study is taking place. At later stages, the advisory board will analyze and comment on research findings from a patient perspective and support the dissemination of the findings. A meeting via videoconferencing is performed at least twice per year.Representing patient safety○ Prof. David Schwappach ○ Prof. Matthias Weigl ○ Prof. Siri Wiig, PhD Representing patients and the public○ Prof. Stefan Weber Representing academic surgical units○ PD Dr. Marco Von Strauss ○ Prof. Martin Hübner The advisory board consists of the following:Problems of adherence to a protocol have been reported for the introduction of checklists  as well We invested quite some effort in ensuring adherence during the previous study . This inGiven that the study aims to change the behavior of surgeons in the treatment group, potential bias or contamination of the surgeons enrolled in the control group needs to be addressed: First, although surgeons in the control group do not receive training, they will not be blind to the intervention, as surgeons within a department work closely together. This could be a source of contamination, because surgeons in the control group may observe StOP?s performed while they operate with a surgeon in the intervention group. If control group surgeons observe communication behavior that they judge as promising, they may be motivated to copy this behavior. However, sporadic observations of others’ behaviors are not sufficient to sustainably change a behavior. Training and feedbacks would be necessary for sustainable behavioral changes.Second, some participating hospitals may have implemented a sign-out, which partially overlaps with a StOP?. For surgeons in the intervention group, the training interview will address this and ask the surgeons to reflect to what extent a StOP? may be associated to the sign-out, so that both can be combined during the operation.The protocol version V1.2, 4.2.2022 was approved by the Lead Ethics Committee 14.3.2022. Recruitment of surgeons in the first participating center is planned for August 2022. Date of recruitment completed: October 2025.The results of this study will be important for four key audiences, namely:A:Healthcare professionalsB:AcademiaC:Patients and the publicD:Policy makers and medical societiesIf the study shows the expected results, the findings are of high importance and will be broadly received. Research is most effectively disseminated using multiple channels, adapted to the audiences.During the study, we will build and maintain a network between participating study centers in order to exchange information, but also to provide regular feedback on the progress of the study. This will mostly be done using electronic means, but also regular videoconferencing and meetings. This network will also be used for the discussion and interpretation of the results .A webpage will be set up that allows communication with the study centers but also allows regular dissemination of information to an interested audience of healthcare professionals, media, and lay people . Via this webpage, webinars will be performed at least annually .The results of the study will be published in peer-reviewed medical scientific journals and presented at national and international conferences . Newsletters will be sent by email . Mailing lists will be made available by the participating surgical societies and the two included patient organizations. After the study, toolkits of training materials will be offered free of charge (A). We will work closely with the media to inform the general public about the results of the study . Differences in outcome dependent on the gender of the surgeon as well as of the patient will be analyzed. The results of this analysis will be published medRxiv.org) and submit it to a peer-reviewed journal. At publication of the primary results, the full protocol, the data management plan including the codebook of the trial database, and information on how to get access to the primary trial data will be published in the repository of the University of Bern which fulfills the FAIR criteria (Bern Open Repository and Information System (boris.unibe.ch)). A 12-month grace period after publication of the primary results is currently foreseen to allow all collaborators to complete additional, pre-planned analyses and projects.We will deposit the final protocol in a preprint repository (Additional file 1.