The National Health Service (NHS) Digital Diabetes Prevention Programme (DDPP) is a behaviour change programme for adults in England who are at high risk of developing type 2 diabetes. Four independent providers deliver the NHS-DDPP following a competitive tendering process. Although providers work to a single service specification, there is potential for some variation in the service across providers. This study (1) assesses fidelity of the structural features of the design of the NHS-DDPP compared to the service specification, (2) describes the structural features of delivery of the NHS-DDPP as implemented (3) reports developers’ views on how the structural components of the NHS-DDPP were developed and why changes were made following implementation.Using mixed methods, we conducted a document review of providers’ NHS-DDPP design and delivery documentation, and extracted information using the Template for Intervention Description and Replication checklist, which was adapted to capture features of digital delivery. Documentation was supplemented by content analysis of interviews with 12 health coaches involved in delivering the NHS-DDPP. Semi-structured interviews were also conducted with 6 programme developers employed by the digital providers.Provider plans for the NHS-DDPP show relatively high fidelity to the NHS service specification. Despite this, there was wide variation in structural features of delivery of the NHS-DDPP across providers, particularly for delivery of ‘support’ . Interviews with developers of the programmes showed that much of this variation is likely to be attributable to the origin of each provider’s programme, which was usually a pre-existing programme that was adapted to conform to the NHS-DDPP service specification. The NHS-DDPP is continually improved and developed based on user experience feedback and research conducted by the providers.Indirect evidence suggests that variation in delivery of support could affect effectiveness of the NHS-DDPP. A priority for future research is ascertaining whether the variation in delivery of the NHS-DDPP across providers is related to any differences in health outcomes. It is recommended that future rounds of commissioning the NHS-DDPP pre-specify the type of support participants should receive, including expected dose and scheduling.The online version contains supplementary material available at 10.1186/s12913-023-09210-3. Type 2 diabetes mellitus (T2DM) is a major public health concern that is largely preventable by weight loss and improved diet and physical activity. Following the success of diabetes prevention trials –3, severIn 2016, the National Health Service (NHS) in England implemented the Healthier You: NHS Diabetes Prevention Programme (NHS-DPP) for adults at risk of developing T2DM. The NHS-DPP is a behaviour change programme delivered in groups which aimed to support participants improve dietary and physical activity behaviours, and prevent progression to T2DM. It has been rolled out in waves, gradually reaching universal national coverage .Early favourable health outcomes from the NHS-DPP have been reported , 8, but The NHS-DPP was then re-procured in 2019, when a number of enhancements were made to the service specification, including the introduction of a digital DPP service as an adjunct to the face-to-face service (Framework 2). At this point, five providers were selected to deliver the face-to-face group service by NHSE to provide NHS DPP across England: four of the previous providers plus one new provider . Four ofNHSE produced a Framework 2 service specification  detailinIn the present study we assess the fidelity of the structural features  of the design of the NHS-DDPP compared to the NHS service specification, and describe the delivery of the NHS-DDPP using the Template for Intervention Description and Replications (TIDieR) checklist . The TIDIn addition to an assessment of fidelity to the service specification, it is also important to fully document the reasons for changes in key structural features of delivery of the NHS-DDPP as it is implemented. Although the programme is commissioned centrally by NHSE and each provider is working to a single service specification, because the programme is delivered by multiple providers, there is potential for some variation in the service across providers. It is important to understand what (if any) variation occurs as the programme is implemented. Further, it is informative to explore the journey by which the provider programmes were developed, to explain how and why the programmes were structured as they are. Such findings can provide important context for further evaluative work on the NHS-DDPP and further inform implementation of the NHS-DPP and other similar programmes.A mixed methods approach has been chosen to document the structural features of the NHS-DDPP (quantitative) and the evolution of the provider programmes throughout the journey of development and implementation . Specifically, the objectives of the present study are firstly to: (1) compare the structural features of the NHS-DDPP design to the NHS service specification for the programme (fidelity); (2) describe the structural features of the delivery of the NHS-DDPP using TIDieR (highlighting variation across providers and any modifications introduced following implementation). Secondly, a series of interviews with NHS-DDPP programme developers has allowed a qualitative assessment of (3) how the structural components of the NHS-DDPP were developed and why changes were made to the programme following implementation.This study used a mixed-methods design. Components of the NHS-DDPP were content-analysed for structural features of design (objective 1) and delivery (objective 2). Semi-structured interviews investigated how the NHS-DDPP was developed and any rationale for any changes made to the NHS-DDPP once implemented (objective 3).The programme specification documents for the NHS-DDPP indicate the key content that should be included in the programme, and comprise of the NHS service specification  and NICEThe design documentation supplied by each digital provider to the research team has been described previously . In brieThe design of each provider version of the NHS-DDPP was described using the TIDieR checklist . TIDieR The delivery documentation provided by each digital provider to the research team has been described previously  and is dGuest access to smartphone and web applications for three out of the four providers. The other provider supplied an app user guide.All educational materials, including learning platforms, online articles, PDF articles, videos, online workbooks and additional workbooks posted to service users.Standard text/script sent to service users via email and text messages.Further, a series of semi-structured interviews were conducted with health coaches who are actively involved in delivering the NHS-DDPP. A total of two, four, two and four interviews (n = 12) were conducted with health coaches from providers 1, 2, 3 and 4 respectively between July and November 2021. Recruitment and informed consent procedures for health coaches taking part in the interviews are described elsewhere  experience surveys so how patients find the app, what things they find useful, what they find not so useful. Or how they found the coaching, how was their relationship. So we’re constantly developing the app based on user feedback (Provider 2).” Further, in some instances a periodic review of scientific recommendations and guidelines is conducted to ensure that the programme is routinely “up-to-date and evidence-based (Provider 3)”.These changes are largely driven by user experiences of the programme. Some providers described their own research methods to gain insights on user experiences: Overall, the NHS-DDPP is a complex multi-faceted intervention, that requires substantial commitment from providers and participants. Our fidelity analysis of the NHS-DDPP shows provider plans for the programmes are generally in line with the NHS service specification. Important variation in programme features has been identified across the four digital providers, as well as modifications to the programmes since implementation. Important differences were identified in terms of support offered to participants  and the delivery channels/methods and dose and scheduling by which such support was offered to participants. This results in substantial variation in intensity or support offered to participants across the four digital provider programmes.Interviews with programme developers provided rationale and background to why such variation is apparent. For at least 3 out of 4 provider programmes, the origin was a pre-existing programme that was adapted to become in line with the NHS service specification for the DDPP, and much of the ethos of the original programme remained intact. Therefore, features of the programmes related to ‘support’ were more a reflection of the original programmes than what was required in the NHS service specification. As subcontractors of face-to-face providers of the DPP, these original pre-existing programmes were usually consumer-facing digital programmes and not specifically related to the face-to-face version of the DPP. Uniquely for provider 3, its programme was described as developed specifically for the pilot DDPP, based on experience of other digital health interventions; such experience highlighted the need for intensive support in the early stages of the programme.Interviews also identified that the digital programmes are continually improved and developed based on user experience feedback and research conducted by providers. Interviews with developers from provider 3 indicated that the option for group support was introduced after the provider had run its own research to explore user experience of group support.All documentation supplied by providers  has been reviewed systematically using a standardised TIDieR checklist. Our decision to adapt the TIDieR checklist for describing the delivery of the digital programme is in line with previous research  that sugHowever, it should be noted that participants who were interviewed for this study were not always necessarily directly involved in the development of the provider programmes. It is possible that some people involved in the early stages of design and development had since moved on to other roles. Nonetheless, the research team tried to identify at least one relevant individual from each digital provider and aimed to interview professionals from different backgrounds to gather a range of views and provide a comprehensive understanding of the processes involved in the design and development of each NHS-DDPP intervention. Every effort was made by the research team to obtain access to all relevant documentation for the study but it is possible that we were not given access to all relevant design and delivery documentation by providers (for example we were not provided with the app for provider 3). Content analysis of interviews with health coaches (as key deliverers of the programme) was included in this study to help to fill any potential gaps in information on provider programmes. By conducting triangulation across multiple sources of information in this way, we can be more confident of the overall picture in results.Our finding that provider programmes were designed with relatively high fidelity to the NHS service specification is comparable to outputs from an evaluation of the face-to-face version of the NHS-DPP. The NHS-DPP programme design demonstrated good fidelity to the structural features itemised in the programme specification . A similThe resulting variation in service delivery across providers that is highlighted in this study is significant, particularly because a substantial component of the variation is around features of the programme that provide support to participants. Programmes did have fidelity to the service specification because the NHS specification documentation simply refers to ‘consider social and psychological support needed to support people to implement behaviour changes and to provide individual 1–1 support’  and is nTo the authors’ knowledge, the concept of repurposing or adapting a pre-existing intervention to meet a service specification, has not been previously evaluated in the literature. Accordingly, there is some degree of uncertainty regarding the implications of this. Knowledge of this route of programme development could, to some extent, explain the lack of theoretical underpinning for the programme demonstrated previously . In a siOur finding that shows the NHS-DDPP is continually updated and reviewed by providers, based on user feedback, is positive. An expert consensus  has highThe current study is part of a research programme that provides a thorough fidelity investigation of the NHS-DDPP, and we are not aware of similar work on any other nationally-implemented diabetes prevention programmes (DPPs). It is therefore impossible to directly compare our findings to fidelity assessments of DPPs in other high-income countries. However, fidelity of nationally implemented DPPs is likely to be an issue because large-scale programmes sometimes commission several different providers  to deliver the programme on their behalf, following central guidance, with some room for interpretation . These iAn immediate question for future research is understanding whether the variation in delivery of the NHS-DDPP across providers is related to any differences in health outcomes (HbA1C and/or weight loss). It would be helpful to know whether participants who receive more support through the programme are more likely to achieve behaviour change and prevention of T2DM, and whether there are particular population groups that benefit most from this support. To date, we are not aware of any analyses of the effectiveness of the implemented NHS-DDPP that report health outcomes according to providers, but would urge investigators and research funders to consider this as a next step. Experiences from an analysis of the face-to-face DPP lend support to this premise, as large differences in health outcomes were reported across providers, and such variation was found to be a more important factor on outcomes than variation in patient characteristics .This work has potential implications for the NHS-DDPP and the way in which the service is commissioned. NHSE appear to have used a pragmatic approach to implement the NHS-DDPP at pace and at scale, using multiple independent providers to deliver the service. Providers’ approach of adapting pre-existing programmes to meet the NHS-DDPP specification has advantages in terms of meeting a service need efficiently. Recent findings suggest that the face-to-face version of the programme achieves a reduction in population incidence of T2DM  and thatProvider plans for the NHS-DDPP show relatively high fidelity to the NHS service specification. Despite this, there was wide variation in structural features of delivery of the NHS-DDPP across providers. This was most evident for delivery of ‘support’, in terms of use of health coaching and/or group support, with further variation across delivery channel and method, and dose and scheduling. Interviews with developers of the provider programmes showed that much of this variation is likely to be attributable to the ways in which the provider programmes were developed. The origin of each provider’s programme was usually a pre-existing programme that was adapted to become in line with the NHS service specification for the DDPP, and much of the ethos of the original programmes remained intact. Each provider version of the NHS-DDPP is continually improved and developed based on user experience feedback and research conducted by the providers.Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4


Cosmic ray muons tomography is a non-destructive imaging technique that uses the natural radiation of cosmic ray muons to create tomographic images of objects. This article presents a novel imaging algorithm that effectively utilizes experimental measurement data to achieve rapid and clear imaging of cosmic ray muons. A clear image can be obtained with only 20 min of measurement time and approximately 200 effective muons. However, the current detection flux is only about 0.044 cm Cosmic muons strike the sea level at a rate of about 10000 2. However, the detection efficiency of practical detection systems is far from this ideal value due to the multiple layers of detectors required for MST, as well as the limited detection area of the detectors and other factors. Therefore, the key to achieving fast imaging of cosmic muons lies in achieving imaging with low event counts.The universe is full of cosmic rays, including cosmic muons, which are high-energy particles that constantly bombard the Earth’s atmosphere. Muons are similar to electrons, but they are significantly heavier. This reduces their Bremsstrahlung and allows them to penetrate much deeper into matter. This unique property makes them an ideal probe for imaging the structures of dense materials. Muon scattering tomography (MST) is a technique that utilizes the scattering behavior of cosmic ray muons to estimate the material composition of a given volume, demonstrating significant potential for enhancing homeland security. The pioneering work on MST was conducted by the Los Alamos team in 20033. For small-angle scattering, scattering angle is distributed near the mean value zero, which can be described by Gaussian distribution. The root-mean-square (RMS) width is related to the scattering material through its radiation length pc is the muon momentum in MeV/c, L is the path length of the muon through the material. The radiation length i of muon events in the data, and N the total number of events. Large angle scattering from muons colliding with nuclei is similar to Rutherford scattering in that the distribution has a high tail (compared to Gaussian distribution). It is obvious that these large angle data have a great impact on the RMS value obtained in experiment. To reduce this impact of these large angle data, the so-called ratio algorithm was proposed in reference4. This algorithm focuses on small angle events, thereby improving the utilization efficiency of experimental data and effectively enhancing the final imaging quality. This paper further improves the efficiency of data utilization based on the algorithm, aiming to achieve high-quality imaging with fewer events.Cosmis muons pass through the material, they are scattered by the coulomb potential of nuclei and eletrons. Each scattering will slightly affect the motion of the particles. The result of a large scattering process is that the charged particles will slightly deviate from the original direction of incidence. The scattering angle distribution of Coulomb scattering is described by Moliere theory8. This method only uses the data passing through each voxel to calculate the corresponding value for that voxel. Therefore, in cases with small amounts of data, the size of the voxel needs to be relatively large to obtain sufficient statistical data. To maximize the utilization of experimental data, a ratio algorithm without voxel imaging has been proposed here, taking into account the characteristic of the ratio algorithm that focuses on small-angle data. In this method, each center position of the multiple voxels divided in the reconstruction region is called a reconstructed data point. Voxel-free means that the size of the voxel is infinitely large. Therefore, the ratio value calculation for each reconstructed data point will use all experimental data. The specific approach is as follows:Each reconstructed data point corresponds to a ratio value.a with a scattering angle A, we obtain the angle for the reconstructed data point as A and a, k is a parameter calibrated based on actual data, and in this paper, we set k to be 1.6 cm.To calculate the ratio value for a reconstructed data point, an attenuating function that is distance-dependent must be used to convert the experimental scattering angle to the reconstructed data point scattering angle based on the distance between the two points. For instance, if the scattering point of the experimental data point is located at position Using the ratio algorithm, we can obtain a corresponding ratio value for each reconstructed data point based on all of its reconstructed scattering angles. By visualizing all reconstructed data points and their corresponding ratio values within the measurement area, an image can be generated.A prototype of muon tomography, called the muon Scattering and Transmission imaging facility , a general data acquisition (DAQ) board, a server, two scintillators for trigger generation, and several high-voltage (HV) modules. Each Micromegas detector achieved a spatial resolution better than 200 To achieve experimental scattering-muon imaging, a set of muon detectors must be established above and below the object to be imaged. Each detector set includes two or more planes of position-sensitive muon detectors. The top set detects incoming muons while the bottom set detects outgoing muons. By analyzing the tracks of incoming and outgoing muons, one can obtain information on the scattering points and scattering angles of muons passing through the object. A tomographic reconstruction of the volume of interest is performed based on the data provided by multiple muons. The reconstruction area is divided into multiple voxels, and each voxel is assigned a value using a certain algorithmi, A letter “mentclass2pt{minimSupplementary Information.


Cardiopulmonary bypass (CPB) is an indispensable technique in cardiac surgery, providing the ability to temporarily replace cardiopulmonary function and create a bloodless surgical field. Traditionally, the operation of CPB systems has depended on the expertise and experience of skilled perfusionists. In particular, simultaneously controlling the arterial and venous occluders is difficult because the blood flow rate and reservoir level both change, and failure may put the patient’s life at risk. This study proposes an automatic control system with a two-degree-of-freedom model matching controller nested in an I-PD feedback controller to simultaneously regulate the blood flow rate and reservoir level. CPB operations were performed using glycerin and bovine blood as perfusate to simulate flow-up and flow-down phases. The results confirmed that the arterial blood flow rate followed the manually adjusted target venous blood flow rate, with an error of less than 5.32%, and the reservoir level was maintained, with an error of less than 3.44% from the target reservoir level. Then, we assessed the robustness of the control system against disturbances caused by venting/suction of blood. The resulting flow rate error was 5.95%, and the reservoir level error 2.02%. The accuracy of the proposed system is clinically satisfactory and within the allowable error range of 10% or less, meeting the standards set for perfusionists. Moreover, because of the system’s simple configuration, consisting of a camera and notebook PC, the system can easily be integrated with general CPB equipment. This practical design enables seamless adoption in clinical settings. With these advancements, the proposed system represents a significant step towards the automation of CPB. I.The cardiopulmonary bypass (CPB) system is used to replace cardiac and pulmonary functions during cardiac surgery. It was first developed by Gibbon In the CPB circuit, a patient is connected to a blood pump and reservoir via vinyl tubing attached to the arterial and venous sides, with occluders on both the arterial and venous circuits to control the blood flow rate. The amount of blood flowing into and out of the reservoir is determined by the flow rate difference between the arterial and venous sides. Because the reservoir level is correlated with the volume of blood in the patient’s heart and lungs, an unstable reservoir level can lead to unintended blood pressure fluctuations in the patient, putting the patient’s life at risk. In addition, an extreme drop in the reservoir level can lead to air embolus and cause severe damage to the patient Most studies aimed at automating blood flow rate operations have focused on CPB systems using roller pumps to control the blood flow rate Therefore, in this paper, we propose an automatic system that simultaneous controls the arterial flow rate and the reservoir level, as shown in II.A.The proposed system, as shown on the right side of B.The proposed system for automatically controlling ent} see  and is nent} see . More deIn addition, the controllers ensured robustness against surgical disturbances induced by suction of blood from the operative field, which increases venous flow. The final value theorem can be used to prove that the effect of the disturbance on the suction flow approaches zero over time .C.The first experiment (perfusion process experiment) aimed to examine the accuracy of controlling the reservoir level and arterial blood flow rate. We performed experiments simulating the perfusion process from the CPB flow-up phase to the flow-down phase for two system configurations with and without reservoir level control units. The system without the reservoir control unit was configured by removing The second experiment (disturbance experiment) was performed to examine the robustness of the system against disturbances caused by venting/suction. The experimental system and experimental protocol are presented in Supplementary Material A4 and A5, respectively. The configurations used in these experiments were designed based on those applied in previous studies on automated CPB systems The efficacy of the proposed system was assessed based on two aspects, the tracking accuracy of the arterial flow rate III.IV.The aim of this study was to automate the control of the arterial occluder in the CPB circuit to reduce the operational burden of perfusionists, and we proposed an automatic reservoir level and arterial flow rate control system with a nested structure. Experiments were conducted to examine the control accuracy and robustness of the proposed system by simulating the perfusion process from the CPB flow-up phase to the flow-down phase and simulating venting/suction disturbances. Through these experiments, we assessed the control accuracy and robustness of the proposed system under realistic conditions encountered during clinical perfusion.The experiment simulating the perfusion process demonstrated control accuracies of In the experiment with venting/suction disturbances, the control accuracies were In the perfusion process using a centrifugal pump, backflow occurs at low flow rates V.First, while we designed the experimental conditions based on those used in previous studies VI.This paper proposed a system to automatically control the arterial flow rate and reservoir level in CPB systems, with accuracies comparable to those of qualified perfusionists. Therefore, the proposed system has a high potential for clinical application to reduce errors during operation and reduce burdens on perfusionists, who are required to work long hours


This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human–Robot Collaboration (HRC) tasks requiring high-level interaction forces on a real-world scale. The proposed multimodal framework is capable of combining physical interaction, Ultra Wide-Band (UWB) radio sensing, a Graphical User Interface (GUI), verbal control, and gesture interfaces, combining the benefits of all these different modalities and allowing humans to accurately and efficiently command the RELAX mobile cobot and collaborate with it. The effectiveness of the multimodal interface is evaluated in scenarios where the operator guides RELAX to reach designated locations in the environment while avoiding obstacles and performing high-payload transportation tasks, again in a collaborative fashion. The results demonstrate that a human co-worker can productively complete complex missions and command the RELAX mobile cobot using the proposed multimodal interaction framework. The use of collaborative robots in industrial settings has recently gathered great attention as a means of transitioning from traditional industrial robotic systems that operate in separated and enclosed workspaces to robots that can provide flexibility while operating safely alongside their human coworkers. This has led to the development of various collaborative robots, known as cobots , which aVarious research laboratories and companies have expended effort on integrating cobots and mobile robots to realize mobile cobots, allowing the execution of tasks that require both mobility and manipulation functionalities. A distinctive feature of this kind of robot is that they provide physical assistance in terms of force in collaborative tasks while simultaneously allowing safety when working with their human counterparts in the whole industrial/warehouse environment . ApplicaOne of the main motivations for using a multimodal interface to control a mobile cobot is to improve the ease of use and user experience for the operator. By providing multiple input modalities, the operator can choose the one that is most comfortable or appropriate for the task at hand. This can help to reduce the cognitive load on the operator, as they do not have to remember complex commands or manipulate small buttons and controls. Additionally, multimodal interfaces can improve the safety of the cobot, as they allow the operator to retain their attention and stay focused on their tasks. This can be especially important in industrial or hazardous environments where the operator needs to be able to quickly and easily control the cobot to avoid potential accidents or collisions. Finally, by providing multiple input modalities, multimodal interfaces can improve the flexibility and adaptability of the cobot, as it can be used in a wider range of applications and environments.In the work presented herein, we propose a novel unified multimodal and multisensor interface framework for a new mobile co-worker platform called RELAX (Robot Enabler for Load Assistive relaXation). RELAX allows for the control of both mobility and manipulation by integrating a physical interaction interface, an Ultra Wide-Band Real-Time Location System (UWB RTLS), a mobile GUI, and finally verbal and gesture recognition interfaces. Specifically, physical interaction is achieved without the need for any additional mechanical/electronic interface by utilizing the compliance and force/torque sensing capabilities of the RELAX cobot. In addition, UWB technology is used for mobility control; a set of anchors is placed on the robot and a tag device is worn by the user, as described in We have validated the proposed framework on a set of navigation/transportation collaborative tasks using the recently developed RELAX mobile cobot, showing the effectiveness of our multimodal interface and demonstrating its advantages compared to a single-channel control interface.The rest of the paper is organized as follows: https://new.abb.com/products/robotics/collaborative-robots/yumi/irb-14000-yumi), which consists of two 7-DOF arm systems designed for small-part assembly side-by-side with human workers. Even though YuMi can detect contacts, it is position-controlled [https://www.kuka.com/en-gb/products/robotics-systems/industrial-robots/lbr-iiwa) is the new generation of the LBR (7-DOFs arm), which has been widely used in robotics research [https://www.franka.de/production/) and Research 3 (https://www.franka.de/research/) designed for assembly and component testing side-by-side with human workers. Both models are fully torque-controlled and have a moderate payload (3 kg), a small footprint, and high repeatability. Universal Robots has developed a set of collaborative robots  called UR3e, UR5e, UR10e, UR16e, and UR20 for use in manufacturing and assembly environments. They feature lightweight designs and 6-axis arms that can be programmed to perform a wide range of tasks while working with payloads of 3 kg, 5 kg, 10 kg, 16 kg, and 20 kg, respectively. The Japanese company Fanuc has several collaborative robot solutions on the market; for example, the CR-14iA/L cobot  has a payload of 14 kg and a medium footprint. It can be used for loading and unloading machines as well as for other factory automation tasks. In the research community, the Fetch Robotics Fetch mobile manipulator (https://fetchrobotics.com/fetch-mobile-manipulator/) was designed for use in manufacturing, logistics, and research environments. It features an autonomous navigation system, can be programmed to move around a facility and to pick up and transport items as directed, and has an arm payload of 6 kg.In the field of colborative robotics, ABB introduced the dual-arm YuMi cobot , into which a custom collaborative robotic arm has been integrated.The RELAX mobile manipulation collaborative robot represents a customized system composed of a commercial mobile industrial platform, the non-holonomic MIR250 . A torque sensor is based on a custom load cell structure sized appropriately for the two sizes of the actuator to measure the torque generated at the output. The actuation unit includes a brake module. Finally, the actuator incorporates two temperature sensors, which are installed to monitor the motor windings and motor electronics temperatures. The main specifications of the two actuator sizes of the RELAX robot are displayed in The fabrication of the RELAX custom collaborative robot arm was also performed starting from the manufacturing, assembly, and calibration of its actuators followed up by the realization of the 2-DOF body modules  and the The final integration of the RELAX robot arm on top of the MIR250 is reported in To render the RELAX arm capable of grasping and holding objects and tools of various shapes and sizes with low to moderate payload and interaction force requirements, a robust and easily reconfigurable end-effector module was fabricated. It consists of a generic 1-DoF jaw-type gripper shown in  in whichhttp://wiki.ros.org/rosbridge_suite) that translates the Web API provided by the MIR250 to the ROS communication language. On the arm side, the XBotCore [http://wiki.ros.org/navigation) package on the mobile base for 2D planning. Using the odometry and sensors data retrieved from the MIR250 ROS Bridge as input, the mobile cobot can be driven to a certain goal pose on the map using the velocity commands generated by the navigation stack.As shown in XBotCore ,20 real-XBotCore , with buThe RELAX software stack includes simulation support for fast prototyping and transparent code porting to the real robot; built-in support is provided for the Gazebo dynamic simulator, as shown in The diagram in The proposed physical interface permits control of the mobile base velocities interacting physically with the robot arm. By rendering low joint impedance settings on the cobot, the Cartesian displacement of the end-effector in the X and Y directions with respect to its starting pose generated by the interaction of the operator with the cobot is used to compute velocity references for the RELAX mobile platform. Moreover, the low impedance settings assure user safety during the physical contact between the operator and the cobot.It is worth noticing that the physical interaction of the user can happen in every part of the robot body, making it very intuitive and straightforward to use. This perturbation generates translational and rotational velocity references for the mobile base following the linear controller described in Equation .(1)vx(tUltra Wide-Band (UWB) is a type of Radio Frequency (RF) technology characterized by a large bandwidth and low energy level transmission protocol, features that make this technology suitable for ranging and positioning systems. As highlighted in yellow in The implemented controller for the mobile base is reported in Equation . The posROS-Mobile Android application [The joypad interface realizes a velocity controller for the mobile base, and is capable of commanding both its linear and angular velocities. It is implemented using a standard twist command for the base, which is generated by a virtual joystick implemented as a built-in feature in the lication .As in the previously described joypad interface, the ROS-Mobile Android app was used to integrate a speech recognition module as a verbal interface inside the proposed multimodal framework, as reported in https://developer.android.com/reference/android/speech/SpeechRecognizer) to provide a particular command associated with a word to the cobot as an open/close primitive for the end-effector or a Cartesian reference pose for the arm.In particular, we implemented the “Speech” widget inside the app using the native Android Java API in order to have access to the microphone of the mobile device (or a paired Bluetooth device), and used the Android speech recognition engine  and a final goal location B placed at  with respect to the arm base, resulting in a line segment trajectory of 0.8m along the Y direction of the arm workspace.ResultsThe top plot in Experimental SetupThe second set of tests sought to validate the proposed unified multimodal interface in the experimental scenario illustrated in ResultsIn close, fist, half-open, and full-open gestures with the related estimated hand aperture percentages. Safe thresholds are employed to differentiate the four gestures, which are then coupled with specific manipulation primitives for the robot.The gesture interface is employed for manipulation tasks; in its current state it supports four different hand gestures, which are shown in Finally, the unified multimodal–multisensor interface framework results are illustrated in The effectiveness of the proposed multimodal interface framework is highlighted in The multimodal approach was compared with the standalone physical and UWB approaches, repeating the experiment five times for each interface. Three main metrics were used: the average completion time of the task, calculated as the total time to move from A to B to C; the average precision, calculated using the MIR250 odometry and markers placed on the ground; and the time spent by the human operator in contact with the RELAX mobile cobot body, which was used to quantify the required effort and attention on the part of the operator during the collaborative task. It is clear that the proposed multimodal interface framework has comparable precision to the physical approach, as when greater accuracy is required , the human operator moved closer to the cobot and activated this modality while at the same time keeping the flexibility of the UWB interface for the rest of the navigation. This resulted in the time spent in contact with the cobot being reduced by around 44%. It is worth noting that the average completion times with the physical interface and the multimodal framework are very similar, as the operator avoids spending time on the precise positioning of the cobot using the UWB signal, which is the main drawback of this standalone interface.Experimental SetupIn the last set of experiments, the RELAX cobot with its end-effector was employed to grasp a long payload of about 2 m in length and 3.5 kg in weight during a collaborative transportation task with a human coworker. The mission, as reported in In this case, the verbal interface is employed to send the RELAX cobot the command to open or close the end-effector. The physical interface is used during the transportation phase to move the RELAX cobot’s base, and the joypad interface is used to return it from the unloading point to the loading one. It is worth noting that the physical interface is exploited when the operator needs to place the RELAX end-effector precisely below the payload for grasping and transport. The same set of parameters used in the second group of experiments was employed in this last validation scenario.ResultsLoading Zone to the Unloading Zone twice, i.e., once for each of the long payloads to be transported. Moreover, the center image shows the linear (in the X direction) and angular reference velocities for the mobile base generated by the physical and the joypad interfaces, with the latter used only on the way back to the loading zone from the unloading zone. The torques sensed by the RELAX end-effector are visualized in the bottom image, clearly showing the grasping and release phases during transportation from the loading zone to the unloading zone.https://youtu.be/yUaOi5VZhUM).A video of the last two experimental trials is available (In this work, we introduce a novel multimodal–multisensor interface framework for a mobile cobot that combines physical interaction, UWB distance measurements, joypad control, verbal interaction, and gesture recognition to create a safe, intuitive, and accurate method for controlling the mobility and manipulation of the robot. The developed multimodal interface was tested on the new RELAX cobot, which represents another contribution of this work. The hardware design and software implementation of the RELAX cobot are described in depth. The motivation for realizing a custom-designed cobot was the need for a robot that could handle high-payload tasks while remaining adaptable and safe for physical interaction, as the cobots available on the market are not able to provide high payload-to-weight ratio performance. Another essential feature of the RELAX mobile cobot is its ease of integration into existing industrial workstations due to its limited mass and dimensions. In the experimental section, we demonstrate the performance of the custom-designed RELAX cobot arm in terms of payload and repeatability, the effectiveness of the proposed unified multimodal interface in terms of execution time and precision in a partially cluttered navigation/mobility scenario for high-payload transportation, and a task involving transportation of a long payload in collaboration with a human co-worker. The scenarios for which the multimodal interface for mobile cobots is intended can be represented by a constrained workspace with static obstacles; to this end, a future direction of our work will focus on carrying out collaborative transportation tasks autonomously while taking into account possible obstacles in the environment. Moreover, a richer GUI and an easier-to-handle device, such as a smartwatch with wireless earbuds, could be provided for human coworkers. Another research topic of interest regards the control of a mobile cobot fleet with one or more humans to extend the current approach to a multi-robot /multi-human use case. Finally, in terms of evaluation, a set of usability trials will be conducted with a representative sample of users to provide insight into their thought processes and decision-making. After these trials, user feedback will be collected through questionnaires and surveys and analyzed in order to identify any usability or acceptability issues. These might include confusion about performing certain tasks, difficulty in finding certain features or information, frustration with the provided human–robot interface, etc.A patent proposal for the methodology presented in this paper has been filed with application ID IT 102023000016302.


Sudden shocks, disturbances, and changes in today’s and the future’s operating environment call for a more resilient food system. COVID-19 and Russia’s latest war in Ukraine have revealed that rapid shocks and disturbances in global social-ecological systems can affect societies and pose various risks to food security. The discussion of food security and especially food supply security under uncertain changes has therefore been highlighted. In this study, food system resilience and the driving forces and current trends affecting it were evaluated in an expert panel study. We used the Delphi technique for the data collection, which included several rounds of iterative evaluation of future food system development up to 2030. We analysed the results using cluster analysis. Based on the results, three clusters were identified which weigh different points within the development foci of food system resilience, namely: (1) the lack of efficient and consensual global crisis preparedness, (2) looking after domestic food production, and (3) trusting the current good efforts in resilience building. The key resilience determinants in each cluster and their importance analysis are presented. We also present enablers and barriers from techno-economic, politico-institutional, and socio-cognitive perspectives that hinder or support resilience building.The online version contains supplementary material available at 10.1186/s40309-023-00215-z. • The weakest point in terms of food system resilience is primary production and its poor profitability.• Consensus topics increased protein crop and domestic RE production and the backup power systems.• Collaboration between actors increases trust and systemic understanding of food system development.• Clear targets and criteria for food system resilience should be created.• Resilience should be included in the strategies that guide food system development.The online version contains supplementary material available at 10.1186/s40309-023-00215-z. The food system faces various social, economic, and ecological driving forces, changes, trends, and disruptions. The need for holistic management has been acknowledged among actors and society. COVID-19 has revealed how vulnerable the global food systems are to disruptions, highlighting the importance of resilience for food security . In FinlFood systems are under pressure to transform into operating within planetary boundaries, adapting to climate change and dietary changes, and cutting emissions. The projected increase in food and nutrition insecurity on a global scale has been driven by different shocks and stressors that often overlap or interact. They can be categorised into the following four clusters  with somThe coronavirus pandemic has increased uncertainty, disrupted production chains, caused a labour shortage threat, and led to drastic measures in several countries to limit the spread of the virus while securing economic recovery after the crisis . The corDuring the 2 years of the pandemic, security of supply and self-sufficiency have been much discussed in Finland. Finland is almost self-sufficient in basic foodstuffs. The production volume of pork and poultry meat has covered domestic demand in recent years, while beef production accounts for around 80% of its consumption. Moreover, the self-sufficiency rate of Finnish milk production, calculated according to milk protein, still significantly exceeds 100% . Yields Changes in food consumption patterns change slowly. However, the discussion of change in diets of a more plant-based and fish-based diet has received much attention in Finland. The dietary change will probably revolutionise the agricultural and food sector in the long run. That said, the total output of agriculture is anticipated to be the same as today only if production still contains at least some meat production . BetweenIt is argued that a controlled change to a sustainable food system requires new value chains and investments to produce plant-based products . This caWhat are the key priorities for the development of a resilient food system for the Finnish food system expert community?How do key priorities and weights vary among food system expert community?What are the enablers promoting and barriers hampering the resilience of the Finnish food system?In this paper, based on food system expert views, we analyse the key determinants of a resilient food system. Identifying and developing the key determinants can prevent situations of sudden food shortages caused by different shocks like COVID-19. The study forms a practice-oriented view of the food system actors’ roles in making food systems’ foresight more efficient when confronting changes. The paper has three research questions:The paper is constructed as follows: first, the background of the study is presented from the perspective of resilience and the future scenarios of food systems; second, the method and data, namely the Delphi method, are presented; third, the results from the Delphi study are analysed, and special attention is paid to the differences and emerging topics within the questions and future views; and finally, the results are discussed, and conclusions are drawn, in the light of the literature from food systems’ resilience and future scenarios.We use an expert-based Delphi method in this study. The Delphi method consists of the judgement of experts by means of successive iterations of given topics to show a possible convergence of opinions and identify dissent or non-convergence . The DelA random sample of respondents was not used in this study. Instead, the Delphi expert panel included experts from all major food system actors, from primary production to the input and processing industry, retail, and support systems such as research, governance, policymaking, and advisory as the target group of this work. The participants and their background for the future evaluation of the determinants of a resilient food system can be seen in Fig. According to Kuusi , the metThe anonymity principle was followed during the Delphi round questionnaires. Anonymity provides an equal chance for each panel member to present and react to ideas unbiased by the identities of other participants . HoweverKeeney et al.  states tThe Delphi survey data were analysed using the IBM SPSS statistical program. The cluster analysis was used to categorise the varying expert views on asked resilience statements. Initially, the run of descriptive statistics was conducted to obtain an overview of the valid and missing values. The missing values were then recoded in the same variables, and these values were then replaced with the series mean. Cluster analysis is an exploratory method . It has The cluster validation was done by 1) comparing the results of two different sets of cluster solutions (three- and four-cluster solutions) to determine which is better and (2) proximity matrix that can evaluate the ‘goodness’ of the clustering by looking at the correlations between observation pairs. This also helped in determining the interpreted ‘correct’ number of clusters. The proximity matrix is presented in Additional file  comparinEach of the sections in the survey also included open-ended questions. The responses were used to deepen the content of the cluster analysis. The categorisation of the open-ended responses did not follow the clusters. Instead, we sought the most illustrative arguments to enrich each cluster-based narrative.The results consist of three sections from the Delphi survey process: (1) the statements of the determinants, drivers, and changes of a resilient food system; (2) the stated importance of the disruptions, drivers, and changes the food system faces; and (3) open-ended answers that were asked after “Introduction” and “Material and methods” sections (the respondent could make further arguments based on his/her view of the questions).K-means and hierarchical clustering algorithms and which number of chosen clusters provided a relevant basis for interpretations of the Delphi data. K-means clustering was abandoned because it does not allow clusters to form freely. Instead, you must select how many clusters there are. In hierarchical cluster analysis, you can either decide beforehand the number of clusters or let them form freely. As such, cluster analysis is an iterative process where researcher’s subjective evaluation of the identified clusters has a major role until a desired or appropriate interpretation of the result is achieved. Also, as the size of Delphi data was rather small (n = 38) and the methodological approach more qualitative, the hierarchical cluster analysis was selected over K-means clustering. Varho and Tapio [Several runs with the dataset were conducted to test how the data reacted to nd Tapio  suggest nd Tapio  too, fewAfter testing from a single solution to a range of three to eight solutions, it was noticed that taking the five-cluster solution or more would form one cluster with just one respondent. Therefore, we abandoned the solutions starting from five clusters and concentrated on the solutions of three and four clusters. Also, the four-cluster solution forms one cluster of three respondents on stage 12 . The cluster 2 mean value is more neutral . Cluster 3 separates itself clearly having a mean value of 0.43. Therefore, it stands out as more positive stance on resilience determinants, drivers, and changes. As the clusters are not similar in size, the differences in clusters focus more on interpreting intra-cluster variation than on cross-cluster variation. Cluster 3 is by far the largest in terms of internal standard deviation  but on the other hand contains smallest number of respondents (five). The mean of standard deviation in cluster 1 is lowest (0.77) and in cluster 2 0.85.This cluster includes those expert respondents who are concerned about overall resilience within the food system. They consider system-level understanding and management in the food chain to be currently inadequate, and this does not enable rapid responses, decision-making, and process changes if required. They see that the threats to the global operating environment are extensive. Dependence on imports of inputs especially jeopardises food security in crisis situations.They also consider that a lack of sufficient backup systems remains. Part of this is that employees’ well-being is currently inadequate in terms of resilience. Furthermore, current reserve stocks do not ensure the adequacy of inputs and products in crisis situations. Insufficient attention is paid to the protection of information systems. Overall, the enterprise structure  is insufficiently decentralised and diverse. This cluster also considers that cooperation between food system operators is currently insufficiently open, and trust building and effort sharing in the food chain are unevenly distributed between the actors.Cluster 2 can be described as a milder version of the former cluster. It includes those expert respondents who are reasonably satisfied with the current domestic system but are concerned about the profitability and independence of primary production and its development nationally. Indeed, the poor economic viability of primary production hinders the implementation of preparatory measures for resilience. This cluster also emphasises independence from imported inputs; it is currently insufficient from a resilience perspective, and dependence on imports jeopardises food security in crisis situations. This cluster also pinpoints the importance of independence in the energy system and considers that increasing domestic renewable energy production from current levels would improve resilience. Simultaneously, backup power systems should be increased in electricity production in different parts of the food system.This cluster is the most positive in the current situation. The expert respondents attached to this cluster rely on the current networks and cooperation and believe that the costs of promoting resilience are evenly distributed between the actors. They trust the current market and policy environment. They consider that the cooperation between food system operators is currently sufficiently open and trust building in terms of resilience. Furthermore, the food system actor network is sufficiently extensive and versatile in its resilience. Awareness and control are also adequate to prevent disturbances .In contrast with the other two clusters, this cluster considers that the poor economic viability of primary production does not hinder the implementation of preparatory measures for resilience. The enterprise structure  is also sufficiently decentralised and diverse in terms of food system resilience. They also consider that employees’ mental well-being is currently adequate level in its resilience.It should be noted that of the 23 statements, three were close to each other in the calculated values of these three cluster centres—namely, statements 7, 9, and 10. These can be considered consensus topics among the food system expert community, and they are the following: (1) increasing the protein crop production area from the current level would improve resilience, (2) increasing domestic renewable energy production from current levels would improve resilience, and (3) the backup power systems should be increased in electricity production in different parts of the food system.Questions were also asked about the experts’ background questions, and they were utilised in analysing whether educational background or the respondent’s actor and stakeholder status within the food system explained the formed clusters . Table As Table Cluster 3 has ‘the cooperation between food system operators’ as the most important determinant, followed by ‘the extensive and versatile food system actor network’, which that is not in the top 5 list of the other clusters. ‘Protection of information systems’ is also a different determinant than in the former two clusters. ‘Dependence on imports’ can also be found in cluster 3, and the fifth determinant is ‘backup systems for crisis situations’.When examining the Delphi expert panellists’ views of the overall importance Table , the meaDuring the Delphi survey, a respondent could argue with open-ended answers what kind of solutions, enablers, challenges, or barriers there were concerning their numerical evaluation. From these open-ended answers, Table The open answers Table  providedTo tackle these issues, the respondents proposed a more systematic framework for food system resilience. A common framework would highlight the variety of actors and policy dimensions involved when reinforcing food system resilience, creating a more cohesive set of means to address it. Additionally, clear targets and criteria for resilience should be created for food system actors and policymakers alike to track progress in the matter. Better communication and collaboration between actors in the food system could generate added trust between the actors and a broader understanding of food system resilience. In turn, this could reduce reluctance to act and create a motivation to participate in building a more resilient food system from the bottom up. Tangible functional examples would create willingness and lower the threshold for participation. At the political level, additional subsidies and other policy means were found important drivers to accelerate the development of a more resilient food system. The profitability of agricultural production should especially be emphasised, and costs related to increasing resilience compensated either through producer prices or by taxation. Domestic decentralised solutions in both agricultural production and energy production were found to support resilience in Finnish conditions.In this paper, we have analysed the key determinants of a resilient food system using an expert method. The study therefore forms a practice-oriented view of the food system actors’ views and argumentation in making food systems more resilient to confront changes. An analysis of the expert process result showed the different weights of the key priorities for the development of a resilient food system. The three experts’ opinion polls formed by cluster analysis pinpointed the following: (1) the lack of efficient and consensual global crisis preparedness; (2) concerns of the domestic food system, especially the poor profitability and its effect on resilience building; and (3) a more optimistic view and trust in current resilience-building efforts, especially pinpointing the importance of tight cooperation between food system actors.According to the results, the weakest point in the food system is primary production and its poor profitability in the eyes of resilience building. The current structural development of primary production, resulting in a concentration of production sectors in different areas of Finland, accelerated by the subsidy system, fails to provide reasonable incentives for resilience development (e.g. nutrient cycling). It was argued that a lack of systematic resilience thinking, combined with the political system’s stiffness and inertia, gave mixed signals for food system actors, yielding at best sluggish progress in building resilience. A tangible example is the structural development of farms so far. The development in the last 25 years has meant that there has been little variation in size, production branch, specialisation, and diversification on farms than was the situation, e.g. in 1995, when Finland joined the EU [Clear targets and criteria for resilience were considered important, and these should be created for food system actors and policymakers alike to focus on the right things and track progress in the matter. Improving communication and collaboration between actors in the food system could generate added trust between them and a broader and systemic understanding of food system resilience. There was a strong consensus among the food system expert community on the three main areas of resilience building. First, increasing the protein crop production area from the current level would improve resilience. Second, increasing domestic renewable energy production from current levels would also improve resilience. Third, the backup power systems should be increased in electricity production in different parts of the food system.The three clusters formed reflect the differences in weighting the resilience factors rather than being completely disconnected and exclusive from each other. They therefore differ in their framing of food system resilience and in the trends and forces that contribute to a more resilient system. Cluster 1 appears to strongly emphasise the structure of Finnish food production as part of the global food system and calls for strong public policy to steer resilience development. It approaches the food system from a structural perspective and seems more cautious about the structural developments in the system compared to other clusters. This cluster also seems the most concerned about the actors within the food system, calling for attention to the poor developments in actors’ mental well-being, cooperation between actors, and the equal distribution of the burden between food system actors. Cluster 2 appears more concerned about the functionality of the domestic food system and especially the continuity and independence of domestic food supply. This cluster especially focuses on the poor economic conditions in primary production and advocates solutions targeted mostly at improving the operating conditions and self-sufficiency of inputs in production to enhance the overall food system’s resilience. Finally, cluster 3 seems to emphasise the role of undisturbed market forces and a clear continuous political framework as the optimal way to ensure resilience in the food system. In this view, resilience could be promoted through market selection, in which competitive and capable enterprises would recognise the importance of resilience in their operations and organically seek to reduce the impact of potential disturbances through planning and increased cooperation with other food system actors. The answers in this cluster portray the current state of food system resilience significantly more positively and seem to accept creative destruction and market orientation in the food system more willingly than the other clusters.To build society’s resilience and adaptive capacity for change, anticipation of future challenges can provide a common insight, both in confronting short-term distortions and building long-term adaptation strategies. This can be improved by defining and sharpening the foci of current food system foresight. The public discussion of the COVID-19 pandemic may lead to a sudden food crisis if the pandemic is prolonged . A food One possibility from the resilience perspective is to generate an indicator setup for the use of follow-up, anticipation, and evaluation. As resilience calls for a holistic framework to identify the main vulnerabilities and determinants, i.e. weak and strong points within the food system, a well-balanced indicator setup could be a practical tool to monitor and anticipate the big picture development. Engle et al.  propose For some time now, especially with the COVID-19 pandemic, system resilience has received more attention. Engle et al.  define rIn this study, we analysed through the Delphi method three key questions about food system resilience. Firstly, we analysed what are the key priorities for the development of a resilient food system. According to the Delphi study results, the weakest point from the food system resilience perspective is primary production and its poor profitability. The structural development of farms has been rapid in the last 25 years, and the aim has been to invest in growth and specialisation among farms. At the same time, a regional concentration of agricultural production has occurred. To maintain and develop resilience, agricultural and other policies that guide food production should consider and evaluate the vulnerabilities of such a rapid structural development. The Delphi panel agreed on three key issues: resilience can be developed by increasing the protein crop production in agriculture, by increasing domestic renewable energy production, and by increasing the backup power systems in electricity production in different parts of the food system.Secondly, we also analysed how do key priorities and weights vary among the food system expert community. According to the results, there are various means to sustain and increase resilience in which the expert community weights are more diverse, e.g. the dependence on import of inputs and increasing domestic renewable energy production. The self-sufficiency and security of supply of agricultural production should therefore play a strong role in agricultural policy measures during the 2020s. The efficient implementation of the EU’s Green Deal  and the Thirdly, we analysed what are the enablers promoting and barriers hampering the resilience of the Finnish food system. The results indicate that collaboration between food system actors increases trust and the systemic understanding of food system development. Based on the sudden shocks and disruptions, clear targets and criteria for food system resilience should be created, and resilience should be included in the strategies that guide food system development throughout the different parts of the food chain. As a main barrier, the experts considered the lack of systematic resilience thinking, combined with the political system’s stiffness and inertia as the main barrier can give mixed signals for the food system actors, yielding sluggish progress at best. The public authorities and key food system operators should continue their tight collaboration, especially in the current organisation for the security of supply. Through this, trust in and systemic understanding of food system development will increase.Additional file 1: Proximity matrix.


Echinoderms are a phylum of marine deterostomes with a range of interesting biological features. One remarkable ability is their impressive capacity to regenerate most of their adult tissues, including the central nervous system (CNS). The research community has accumulated data that demonstrates that, in spite of the pentaradial adult body plan, echinoderms share deep similarities with their bilateral sister taxa such as hemichordates and chordates. Some of the new data reveal the complexity of the nervous system in echinoderms. In terms of the cellular architecture, one of the traits that is shared between the CNS of echinoderms and chordates is the presence of radial glia. In chordates, these cells act as the main progenitor population in CNS development. In mammals, radial glia are spent in embryogenesis and are no longer present in adults, being replaced with other neural cell types. In non-mammalian chordates, they are still detected in the mature CNS along with other types of glia. In echinoderms, radial glia also persist into the adulthood, but unlike in chordates, it is the only known glial cell type that is present in the fully developed CNS. The echinoderm radial glia is a multifunctional cell type. Radial glia forms the supporting scaffold of the neuroepithelium, exhibits secretory activity, clears up dying or damaged cells by phagocytosis, and, most importantly, acts as a major progenitor cell population. The latter function is critical for the outstanding developmental plasticity of the adult echinoderm CNS, including physiological cell turnover, indeterminate growth, and a remarkable capacity to regenerate major parts following autotomy or traumatic injury. In this review we summarize the current knowledge on the organization and function of the echinoderm radial glia, with a focus on the role of this cell type in adult neurogenesis. Echinoderms are a phylum of exclusively marine invertebrates, whose biology is fascinating at many levels. Phylogenetically, echinoderms are placed, together with hemichordates, as a sister taxon (Ambulacraria) to chordates within the monophyletic group Deuterostomia . This deThere are about 7,000 extant echinoderm species Satoh,  that areradial nerve cord (RNC), which is accompanied by other radial organs, including the hemal canal, the water-vascular canal, and muscle(s)  , 3A–C. Irve ring . Becauserve ring , with unrve ring . What maCtenoimbricata and ctenocystoids) were bilateral, with a clearly defined anterior-posterior body axis  within the POU family of transcription factors  of the ectoneural epithelium of the radial nerve cord. This is the region where most of the radial glial cell bodies are located. At the cellular level, however, not all radial glial cells express Myc. Instead, Myc-positive glial cells are interspersed among Myc-negative cells  neurogenesis in the uninjured adult nervous tissue under “normal” conditions and (b) post-traumatic neurogenesis triggered by an injury or autotomy. Neurogenesis of the first type is a continuous long-term (lifelong) process that results in the replacement of the dead/worn out cells and/or adult growth . Neurogenesis of the second type is a relatively short-term event triggered by a CNS injury and aimed at the restoration of the anatomical, histological and functional integrity of the damaged CNS region. Both types of neurogenesis rely on the same source, the radial glial cells, that undergo cell division and give rise to new neuronal and glial cells.Echinoderms are well-known for their ability to rapidly and fully regrow most of their adult tissues and organs, including the central nervous system . Both early events, the glial activation and the surge in apoptosis, are controlled by the transcription factor Myc  increase of the expression of the long terminal repeat (LTR) retrotransposon Gypsy1 (Mashanov et al., H. glaberrima were surgically excised and kept in vitro. The radial glial cells in the explants started exhibiting signs of dedifferentiation as early as on day three in culture, while the relative abundance of apoptotic cells remained at the basal level. These results indicate that dedifferentiation of surviving glial cells does not necessarily require apoptosis of adjacent cells in the neuroepithelium.Even though the increase in cell death and glial dedifferentiation both take place simultaneously during the early post-injury phase and both are regulated by Myc, these two cell events are not necessarily coupled. In a recent study (Quesada-Díaz et al., Once dedifferentiated, glial cells become highly proliferative and will give rise to new glial cells and neurons. After radial nerve cord transection in sea cucumbers (Mashanov et al., It is interesting to note the similarities between the neurogenesis in the uninjured CNS and post-traumatic neural regeneration in echinoderms. The most interesting parallel is that both phenomena rely on radial glial cells as the progenitor population. This observation is in line with the growing body of evidence that suggest that the capacity for post-traumatic adult regeneration strongly correlates with indeterminate growth and that the mechanisms underlying the normal growth can be co-opted in regeneration Vogt, . Better The echinoderm radial glia shares a number of key characteristics with the radial glia of chordates, including:- the orthogonal orientation relative to the surface of the neuroepithelium;- the slender elongated shape spanning the height of the neuroepithelium;- the epithelial nature with clear apicobasal cell polarity and apical cilia;- the well-developed cytoskeleton composed of bundles of intermediate filaments in the cytoplasm;- the ability to produce and secrete SCO-spondin;- the requirement of Myc expression for the activation of the neural progenitor function.The neurogenic progenitor population in echinoderm neurogenesis is a subset of radial glial cells. The neurogenic activity in these cells is known to be defined by the differential activity of two transcription factors: the expression of Myc and the absence of Brn1/2/4. Myc is required for the glia activation in response to injury. Brn1/2/4 needs to be absent in order for the glia to be able to function as the progenitor cell population.The morphological, molecular, and functional similarities between the echinoderm radial glia and their counterparts in chordates reveals that radial glia is a phylogenetically ancient cell type that would have emerged at least in the last common ancestor of ambulacrarians and chordates. The stereotypical role of the radial glia in neurogenesis raises the possibility that the fundamental mechanisms of neurogenesis are conserved in deuterosomes. Further research into the neurogenesis of highly regenerative echinoderms will help us understand how the latent phylogenetically conserved cellular and molecular mechanisms can be harnessed to develop new efficient treatment options for human CNS injuries.VM: Conceptualization, Writing—original draft. SA: Writing—review and editing. DJM: Writing—review and editing. RR: Writing—review and editing. DJ: Writing—review and editing.


Engraulis ringens, Merluccius gayi, and Strangomera bentincki and non-targeted Normanichthtys crockeri and Stromateus stellatus fish species. This proof-of-concept method is composed of two channels of a convolutional neural network (CNN) architecture that processes the Red–Green–Blue (RGB) images and the visible and near-infrared (VIS-NIR) reflectance spectra of each species. The classification results of the CNN model achieved over 94% in all performance metrics, outperforming other state-of-the-art techniques. These results support the potential use of the proposed method to automatically monitor fish landings and, therefore, ensure compliance with the established fishing quotas.Fishing has provided mankind with a protein-rich source of food and labor, allowing for the development of an important industry, which has led to the overexploitation of most targeted fish species. The sustainable management of these natural resources requires effective control of fish landings and, therefore, an accurate calculation of fishing quotas. This work proposes a deep learning-based spatial-spectral method to classify five pelagic species of interest for the Chilean fishing industry, including the targeted  Fish have long been a crucial source of protein for human consumption. Unfortunately, poor management has led to the overexploitation of most targeted fish species and endangered the remaining ones . The lasThe sustainable management of fishing stocks has proved to be challenging, and it is a multivariate problem . ResearcOne of the underlying problems of controlling catch quotas is the accurate identification of the fish landed . WithoutBecause the control process of pelagic fish species in Chile uses no digital technology at all, SERNAPESCA states in its strategic roadmap that introducing digital technology would greatly assist their efforts for the recovery and management of threatened and endangered fish stocks ,10.Engraulis ringens, Merluccius gayi, Normanichthtys crockeri, Stromateus stellatus, and Strangomera bentincki  using a SpectralonThe calibrated hypercubes are then further processed to isolate every fish in the image via the 2-step segmentation procedure depicted in The reflectance curve describes the percentage of light that the fish skin reflects at each wavelength. The reflectance curves represent the so-called spectral features or optical fingerprints specific to an object of interest.K be the total number of samples of a single fish species; then, the spatial average reflectance of the k-th fish sample is computed as:Let R RoIs, with each one of them containing P pixels. Let p-th pixel in the r-th RoI. Then, the average spectral signature of the r-th RoI is computed as:R spectral signatures associated with the sample, and the spectral dimensions are reduced to To develop our classification models, we defined the spectral signatures for each species as the spatial average of the hyperspectral images over an RoI. Some pixels are randomly selected to define one or more RoIs in the segmented image, as depicted in RGB images were generated from the hyperspectral images by applying a method based on emulating the spectral sensitivity of an RGB camera, as illustrated in RGB image extraction method, the relationship between the spectral sensitivity of the RGB camera and the RGB channels can be represented as a matrix with the dimensions RGB channels and RGB images as follows. First, the hyperspectral image of the dimensions RGB camera spectral sensitivity. This projection matrix averages the hyperspectral system output at all wavelengths RGB camera. In this manner, the projection matrix averages the hyperspectral channels RGB camera model. Finally, the RGB image is formed by (i) performing a matrix multiplication between the reordered hyperspectral image, the projection matrix, and the matrix of spectral sensitivity vs. RGB; and (ii) reordering the result. At the end of this stage, RGB images of Color RGB images and spectral signatures extracted from the hyperspectral images were input into a CNN. Three models of this network were evaluated, considering the following inputs: (i) RGB images; (ii) spectral signatures; and (iii) both RGB images and spectral signatures. In all cases, the network can automatically extract relevant features from the input data using convolution operations on the different input data. These features are used to classify the different fish species, as schematically shown in RGB images, obtaining a vector of 65,536 features. In this sense, the initial CNN layers automatically allow for extraction of simple features  from the RGB images, while the later layers learn complex features [A DL-based classification method was designed to automatically discriminate five different species of Chilean pelagic fishes. The features . On the RGB images as described below. Note that the original RGB images, i.e., the result directly obtained by imaging the fish, have a dimension of The training of a CNN requires many samples, which is difficult to achieve in practice. To overcome this limitation, we augmented the spectral data of each fish hypercube by extracting the reflectance curves of various random RoIs as described in ling see a.Before augmenting the spatial data, the images are all rescaled to a size of ssifiers ,34,35,36ssifiers ,38. Addissifiers .Engraulis ringens, As mentioned above, the spectral signatures are augmented by generating different RoIs over an image to spatially average the reflectance associated with different zones of the fish. In this way, the resulting spectral signature is a good representation of the whole sample. Finally, at the end of this stage, a total number of 1000 images per class were obtained, as shown in RGB images) and the spectral channel  independently, then concatenates these relevant features into a single feature vector that is used as an input to the classification stage, which is shown in The proposed CNN automatically extracts key features from both the spatial  metric between the predictions  :(8)L, pixels per cell = , and cells per block =  [The performance of the proposed classification method was assessed by analyzing the impact that spectral and spatial features have on it and by comparing its performance against an SVM classification method. A linear kernel is considered to keep the rest of the parameters by default . The per =  ,52.RGB images and spectral signatures outperformed the others, obtaining values of over 94% in all performance metrics. In the case of SVM, using spectral information improved the performance of this classifier, especially when combined with HOG features.Merluccius gayi. This result could be attributed to its distinctive reflectance signature , we included the VIS-NIR reflectance signatures of the species for more accurate classification. Thus, we demonstrated the feasibility of using spectral information on fish species of comparable size and morphology.A spatial-spectral method based on Deep Learning (DL) was developed and tested for the classification of five different pelagic fish species that are common and intensively fished by the Chilean fishing industry: Although we only used a total of 1000 images per species to generate the training and testing datasets in this work, the proposed method achieved accuracy rates of over 94%, outperforming the classifiers described as state of the art refer to  with no Future work from our research team will focus on refining our classifiers by acquiring more images of the pelagic species included in this study and other fish species  along the Chilean coast. Designing a model to estimate the size and weight of the landed fish is also desired, as it would contribute to better fish management; however, it is heavily conditioned to solid fish size–mass curves. The results show that developing a fully automated method capable of controlling fish landings in a real scenario is undoubtedly feasible and much needed under our current global over-fishing scenario.