In the field of robotics education, introductory courses would ideally utilize heavy industrial arms for hands-on learning. This would provide students with valuable experience in joint programming, which involves direct control of each joint motor in the arm to accomplish desired path planning and differential movements. This practice requires consideration of the physical dynamics of the arm. However, the use of heavy industrial arms has several drawbacks. They are large and expensive, require specialized maintenance, can pose safety risks, and they typically do not allow for direct control of the joint motors. One solution is to use a small, lightweight, toy-like arm. While these are cost-effective and provide direct access to the joint motors without posing safety risks, their lightweight construction means they exhibit minimal dynamic behavior, which limits their educational value. Another solution involves a robotic arm simulator that uses a virtual arm. However, a virtual arm doesn't offer the same level of hands-on engagement and excitement as a physical arm. We propose a hybrid solution that combines a small physical arm with a virtual arm. This approach provides students with the experience of working with an industrial arm, but without the associated difficulties. We demonstrate how this approach successfully improved the completion rate of joint programming assignments, offering a promising solution for practical robotics education.

In this paper, a modular wire-actuated robotic arm was designed to improve the safety and adaptability of service robots during human-robot interaction. To raise the stiffness adjustment range of the robotic arm, a symmetric variable-stiffness unit was designed based on flexure, which had compact and simple structure, and lowly nonlinear stiffness-force relationship. In this paper, we focused on the research of the symmetric 1-DOF joint module. Based on the kinematics and stiffness analysis, the pose of the joint module could be adjusted by controlling the length of the wires, and the stiffness of the joint module could be adjusted by controlling the tension of the wires. Because of the actuation redundancy, the pose and stiffness of the joint module could be controlled synchronously. Furthermore, a directly method was proposed for the stiffness-oriented wire tension distribution problem of the 1-DOF joint module. A simulation was carried out to verify the proposed method.

The article presents several innovative systems developed through student laboratory projects, including two autonomous vehicles, a four-legged walking robot, an active ankle-foot orthosis, a ball on beam balancing mechanism, a ball on plate system, and a manipulator arm—all powered by pneumatic artificial muscles (PAMs). Fluidic muscles offer significant potential in various mechatronic systems, robots, and manipulators due to their flexible, lightweight nature and compliance. Their ability to produce smooth and adaptable motions is particularly beneficial in applications requiring natural and human-like movement, such as rehabilitation and assistive devices. Although PAMs powered control systems face challenges with nonlinear phenomena, their biologically inspired design holds promise for future applications across various industries. These may include innovative applicability in industrial, automotive, and aerospace sectors, as well as use in sports, medical aids, entertainment, and animatronics. Incorporating self-made laboratory systems actuated by PAMs into control systems education offers a comprehensive learning opportunity that combines theoretical concepts with hands-on experience. This approach develops the necessary skills of future engineers, expanding their understanding of technical principles and preparing them for future challenges in engineering practice.

Anonymous communications networks were born to protect the privacy of our communications, preventing censorship and traffic analysis. The most famous anonymous communication network is Tor. This anonymous communication network provides some interesting features, among them, we can mention user’s IP location or Tor Hidden Services (THS) as a mechanism to conceal the location of servers, mainly, web servers. THS is an important research field in Tor. However, there is a lack of reviews that sump up main findings and research challenges. In this article we present a systematic literature review that aims to offer a comprehensive view on the research made on Tor Hidden services presenting the state of the art and the different research challenges to be addressed. This review has been developed from a selection of 57 articles and present main findings and advances regarding Tor Hidden Services, limitations found, and future issues to be investigated.

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state of the art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states which interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological sates, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented adding an exponential cutoff to the interaction term of PPP model. In this way, an adjusted cutoff distance λ = 2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond Hubbard model but not completely unscreened as is the case for the PPP model.

The paper delineates the developed vision system of the UR5 cobot and the operating algorithm of the robotic quality control station. The hardware-software architecture of the developed robotic station was shown, consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system. Image processing and analysis algorithms were described, the method of control and communication between the station components was discussed, and two operating scenarios were presented as a single robotic station and a robotic line. Based on the results obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

Construction and demolition waste (CDW) represents 1/3 of the weight of all-waste produced. Increasing their recycling and reutilization with recycled aggregates (RA) means closing the life cycle of construction materials. Research has been carried out on artificial aggregates from the exclusive crushing of structural concrete waste in selective demolitions (CDWRConc). This study analyses the use of recycled concrete as graded aggregate (GARConc) and in cement soil (CSRConc). The material complies with the requirements as a road base, although due to the low values of resistance to fragmentation these materials are adequate for use in sensitive road systems and other places such as urban roads and car parks. The sensitive road systems are infrastructures in places of great natural wealth and low traffic intensity, with an annual average of heavy vehicle traffic (AADTh) below 50 vhp/d. As soluble salt contents have been detected, additional waterproofing or drainage measures must be adopted to prevent water infiltration into the layers made up of CDWRHorm. Finally, the high initial values of UCS allow the temporary passage of light vehicles over CSRConc after 3 days.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

We have repeated the experiment performed recently by Krasznahorkay et al., (Phys. Rev. Lett. 116, 042501 (2016)), which may indicate a new particle called X17 in the literature. In order to get a reliable, and independent result, we used a different type of electron-positron pair spectrometer which have a more simple acceptance/efficiency as a function of the correlation angle, but the other conditions of the experiment were very similar to the published ones. We could confirm the presence of the anomaly measured at the Ex=18.15 MeV resonance, and also confirm their absence at the Ex=17.6 MeV resonance, and at Ep= 800 keV off resonance energies.

In this paper, we look at how Artificial Swarm Intelligence can evolve using evolutionary algorithms that try to minimize the sensory surprise of the system. We will show how to apply the free-energy principle, borrowed from statistical physics, to quantitatively describe the optimization method (sensory surprise minimization), which can be used to support lifelong learning. We provide our ideas about how to combine this optimization method with evolutionary algorithms in order to boost the development of specialized Artificial Neural Networks, which define the proprioceptive configuration of particular robotic units that are part of a swarm. We consider how optimization of the free-energy can promote the homeostasis of the swarm system, i.e. ensures that the system remains within its sensory boundaries throughout its active lifetime. We will show how complex distributed cognitive systems can be build in the form of hierarchical modular system, which consists of specialized micro-intelligent agents connected through information channels. We will also consider the co-evolution of various robotic swarm units, which can result in development of proprioception and a comprehensive awareness of the properties of the environment. And finally, we will give a brief outline of how this system can be implemented in practice and of our progress in this area.

Particle size can pose a challenge to random embankment compaction control methods, where practical techniques have hardly been developed and procedural control is used instead. In order to develop new quality control procedures for slate random fill, the necessary fieldwork and laboratory tests were carried out. This involved the revision of certain methods such as the wheel-tracking or topographic settlement tests. More than four thousand five hundred in-situ density and moisture content measurements were carried out for this research. In addition, more than five hundred and eighty topographic settlements and nine hundred and sixty wheel-tracking carriage tests were performed. The quality control processes were completed with more than one hundred and thirty plate bearing tests. Possible evidence of statistical correlations between compaction control tests were identified. An analysis of variance (ANOVA) was performed. When testing proved relationships between them, the replacement of one of them by the other was assessed by deduction. Finally, the study suggests new procedures for compaction quality control of random slate fill used in core area.

Robotic Process Automation (RPA) is a fast growing field inside Business Process Automation (BPA). RPA deals with software robots that use human application interface to do some repetitive tasks like starting programs, filling the forms, clicking on buttons etc. Some RPA software tools like Blue Prism, Rapise and UiPath became popular during last years but there are still some problems with them starting with their high price and difficulties to adapt to the real use cases. On the other hand, Optoklik is a relatively small RPA tool developed to be highly adaptable to the real cases and still easy to use. This paper presents the main functions of Optoklik and discusses its usage in automation of different actions that use human application interface.

Robotic surgery is a rapidly developing and evolving surgical technique. This literature review evaluates the advantages and disadvantages in the context of gallbladder disease comparing robotic Cholecystectomy to the well-established laparoscopic Cholecystectomy. Significant advantages are reduced operative blood loss, hospital stays and post operative pain, alongside increased patient satisfaction and improved visualization and precision compared to the laparoscopic approach. Disadvantages include lack of tactile feedback, significant cost attributed to equipment, training requirements and increased procedural time due to the set-up sequences. The implementation of robotic surgery also poses significant changes for the training of future surgeons. Whilst it can standardize training and increases opportunity for simulation, the concern is the loss of traditional skills. Currently the evidence base remains mixed however the use of robotics in the right setting, with suitably trained operatives and appropriate patients can enable improved outcomes for patients with gallbladder disease. There is a lot of scope for development including the implementation of tactile feedback to aid operative technique and artificial intelligence to aid patient safety. Likely broadening the use and potential benefit of robotic surgery not only for cholecystectomy but many surgical specialties.

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analysed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioural and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

Collaborative robots have experienced low acceptance in applications, especially in industry. 1 This fact has attracted the attention of researchers and practitioners, who point to different causes 2 for this low acceptance. One of the main reasons is the difficulty in converging on suitable methods 3 for modeling collaborative interactions between robots and their surrounding context during the 4 requirements phase. These interactions must be elicited and modeled during requirements modeling 5 to maximize value creation through collaboration and must be formally verified, taking into account 6 the risks of human-robot interaction. However, such modeling is often not present in collaborative 7 robot design, and the choice of an appropriate approach remains an open problem. In this paper, 8 this problem is addressed from a requirements engineering perspective, a goal-oriented model and 9 a service-based approach supported by an additional verification method based on Petri nets is 10 proposed. A case study based on collaborative robots used in a hospital environment is presented.

The ethics of invertebrate research have largely been ignored compared to the consideration of higher order animals, but more recent focus has questioned this trend. Using biohybrid robotic jellyfish as a case study, we examine the ethical considerations of invertebrate work and provide recommendations for future guidelines. This paper starts with an overview of philosophical views of animal ethics, the current state of knowledge for invertebrate pain and nociception, and current ethical guidelines. Next, we delve into the case study and analogous precedents. Specifically, in prior studies, we developed biohybrid robotic jellyfish, which modified live moon jellyfish with microelectronic swim controllers for future applications in ocean monitoring. Although jellyfish possess no central nervous system, pain receptors, or nociceptors, we closely monitored their stress responses, using the precautionary and minimization principles in consideration of the 4Rs: reduction, replacement, refinement, and reproducibility. We also discuss ethical considerations related to our studies and suggest that public opinion of invertebrate research relies heavily on repugnance, including fears of ‘playing God’ or limiting the ‘free will’ of animals. These issues are also examined for prior bioethics cases, such as the RoboRoach, cyborg beetle, ‘microslavery’ of microbes, biohybrid robots incorporating tissues from sea slugs (which are known to possess nociceptors), and other tissue cutting experiments involving soft-bodied invertebrates. However, biohybrid robotic jellyfish pose further ethical questions of potential ecological consequences as ocean monitoring tools, such as the impact of electronic waste in the ocean. To conclude these evaluations, we recommend that publishers require brief ethical statements for invertebrate research, which can include the following: a scientific justification for the research, discussion of the 4Rs, and cost-benefit analysis. We also delineate the need for more research on pain and nociception in invertebrates, which can then be used to revise or validate current research standards. These actions provide a stronger basis for the ethical study of invertebrate species, with implications for individual, species-wide, and ecological impacts on animals, as well as for interdisciplinary studies in science, engineering, and philosophy.

Designing and development of agricultural robot is always a challenging issue, because of robot intends to work an unstructured environment and at the same time, it should be safe for the surrounded plants. Therefore, traditional robots cannot meet the high demands of modern challenges, such as working in confined and unstructured workspaces. Based on current issues, we developed a new tomato harvesting wire-driven discrete continuum robot arm with a flexible backbone structure for working in confined and extremely constrained spaces. Moreover, we optimized a tomato detaching process by using newly designed gripper with passive stem cutting function. Moreover, by designing the robot we also developed ripe tomato recognition by using machine learning. This paper explains the proposed continuum robot structure, gripper design, and development of tomato recognition system.

Automated machine classifications of galaxies are necessary because the size of upcoming surveys will overwhelm human volunteers. We improve upon existing machine classification methods by adding the output of SpArcFiRe to the inputs of a machine learning model. We use the human classifications from Galaxy Zoo 1 (GZ1) to train a random forest of decision trees to reproduce the human vote distributions of the Spiral class. We prefer the random forest model over other black box models like neural networks because it allows us to trace post hoc the precise reasoning behind the classification of each galaxy. We find that, across a sample of 470,000 Sloan galaxies that are large enough that details could be seen if they were there, the combination of SpArcFiRe outputs with existing SDSS features provides a better machine classification than either one alone on comparison to Galaxy Zoo 1. We suggest that adding SpArcFiRe outputs as features to any machine learning algorithm will likely improve its performance.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

This paper addresses the effects of electric power quality on robotics operation. A general overview is reported to highlight the main characteristics of electric power quality and their effects on a powered system by considering an end-users viewpoint. Then, authors outline the influence of voltage dip effects by focusing at robotic grasping applications. A specific case of study is reported as referring to LARM Hand IV, a three-fingers robotic hand, which has been designed and built at LARM in Cassino. A dedicated test rig has been settled up for generating predefined voltage dips. Experimental tests are carried out for evaluating the effects of different types of voltage dips on the grasping of objects.

Considering the actual world economical trends, one of the most important questions is now and in the future: how to reduce power consumption of electronic systems. Since the invention of computers, the electrical energy consumption step by step increased. Now when not only computers, but electric vehicles, robots, automation, and unmanned aerial vehicles play a very important role of our life, the main problem of system designers is how to reduce energy consumption in these systems. But also the existing already working systems must be revised in order to decrease their electric power consumption. The importance of this subject (energy control) shows that a huge number of research publications and survey papers deal with it. Just focusing on the last one or two years (2021 and 2022) the search hit 221000 titles (103000 hits only in 2022). Analyzing all the research areas is almost impossible, but focusing on some important research subjects, where one of the main topic is “energy saving methods” can give an overview about the subject. The paper focuses on the area of industrial robotic systems, electric vehicles, and embedded systems.

Background and Objectives: C-arm free MIS techniques can offer significantly reduced rates of postoperative complications such as blood loss and hospitalization time. Another advantageous long-term aspect is the notably diminished exposure to radiation which is known to cause ma-lignant changes. This study emphasizes that, in some cases of spinal conditions which require a procedural intervention, C-arm free MIS techniques hold stronger indications than open surgeries guided by image intensifier. Materials and Methods: In this research, a retrospective analysis and review of various cervical and thoracic spinal procedures, performed in our hospital, by applying C-arm free techniques. The course of the study explains the basic steps of the procedures and demonstrating postoperative or intra-operative results. For anterior cervical surgery, we performed OPLL resection, while for posterior cervical surgery, we performed posterior fossa decompression for Chiari malformation, minimally invasive cervi-cal pedicle screw fixation (MICEPS) and modified Goel technique with C1 lateral mass screw for atlantoaxial subluxation. Re-garding the thoracic spine, we performed anterior correction for Lenke type 5 scoliosis, and transdiscal screw fixation for DISH fractures. Results: C-arm free techniques are safe procedures that offer precise and high-quality postoperative results by offering sufficient spine alignment and adequate decompression depending on the case. Blood loss, postoperative pain and wound infection are other important aspects of spine surgery that must be always taken into consideration. Conclusions: Navigated C-arm free techniques are safe and precise procedures implemented in the treatment of surgically demanding conditions. They can significantly increase accuracy while decreasing the operative time. They represent the advancement in the field spine surgery and are hailed as the future of the same

In contemporary design practices, there is a disconnect between the design techniques used for early-stage design experimentation and performance analysis, and those used for the manufacture and construction. This study addresses the problems in developing an integrated digital design workflow and provides a research framework for integrating environmental performance requirements with robotic manufacturing processes on a construction site. The proposed method enables the user to import a design surface, identify design parameters, set several environmental performance goals, and thereafter simulate and select a robotic building strategy. Based on these inputs, design alternatives are developed and evaluated, considering their robotically simulated constructibility, in terms of their performance criteria. To validate the proposed method, the design is evaluated in an experiment wherein a double-skin facade perforation is generated using the proposed methodology. Initial results suggest a heuristic feature to improve the simulated robotic constructibility. Moreover, the functionality of the prototype is demonstrated.

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an Olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-avoid Navigation, Vision-based Navigation, and Olfaction-based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-based navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms Vision-only and Olfaction-only methods, reducing average search time by 54% and 30%, respectively.

Proposed article deals with analyses on trends of problem-solving robotic applications in manu-facturing, especially in transportations and manipulations. Intelligent agent-based manufacturing systems with robotic agents are observed. Intelligent core of such units must be able to propose the plan of problem-solving in form of strategy. The logical model of adaptive strategies planning for intelligent robotic system is described in form of predicates with presentation of data processing on base of set theory descriptions. Dynamic structure of workspace and possible change of goals are considered as reasons for functional strategies adaptation. Proposed formal descriptions are sup-ported by model of mobile robotic platform, acting in warehouse.

Study design :Technical note. Objectives : To present a new unilateral biportal endoscopic technique for lumbar disc herniation without C-arm . Background : Lumbar disc herniation requires surgical intervention when conservative methods fail. Shifts towards minimally invasive percutaneous endoscopic lumbar discectomy, including uniportal and biportal approaches, have been hindered by challenges such as steep learning curves and reliance on radiation-intensive C-arm guidance. Our study introduces the use of standard intraoperative navigation in unilateral biportal endoscopy (UBE) to reduce radiation exposure and increase surgical acuracy. Materials and Methods : A 24-year-old man with low back and bilateral leg pain with gait disturbance was referred to our hospital. He had have conservative treatment for 12 months in another hospital before admission. However, the conservative treatment did not work for him. He had low back pain (VAS 4/10) and bilateral leg pain (VAS 8/10), muscle waekness of bilateral legs (Manual muscle testing ;MMT of extensor hullusis longs 4 4), and numbness of bilateral lower leg. Preoperative lumbar MRI showed L4/5 large central disc herniation. Results: He underwent C-arm free unilateral biportal endoscopic discectomy under the guidance of O-arm navigation. The patient was successfully treated surgically. Postoperative lumbar MRI showed good decompression of dural sac and bilateral L5 nerve roots. MMT and sensory function of both leg had recovered fully on final follow-up at one year. Conclusions/Level of Evidence: The new unilateral biportal endoscopic technique under navigation guidance is useful technique for lumbar disc herniation. This innovative technique proved to be safe, accurate, and minimized radiation exposure for surgeons for the treatment of lumbar intervertebral disc herniation. Level V.

The paper presents the conceptualization and realization of a novel platform for additive manu-facturing, an industrial robot arm-based system for additive manufacturing applications. Tradi-tional 3D printers, especially those employing fused deposition modelling (FDM) processes, are restricted to depositing material in a single toolpath plane (e.g. x-y plane). The focus of this study was to explore the feasibility of integrating commercial off the shelf (COTS) additive manufac-turing technologies with a six degree of freedom industrial robot arm to yield a 3D additive manufacturing system with the capability to perform free-form six degree of freedom fused deposition modelling. The present paper presents the development of a platform from stage 0, i.e. materials to its use, and finally a printed product with the developed extruder.

Background: In the landscape of thoracic surgery, innovation continually drives progress, offering novel approaches to address complex pathologies while prioritizing patient well-being. Dual-portal robotic-assisted thoracic surgery DRATS represents the next frontier in this evolution. In this report we describe our experience with the DRATS approach for segmentectomy with the indocyanine green intersegmental plane identification. Methods: We presented the case of a patient who underwent a DRATS lingulectomy and lymphadenectomy stations 5, 6, 7, and 10 using the daVinci Surgical System. Results: The patient's postoperative course was uneventful with chest tube was removed in second post operative day. The final pathological analysis confirmed a low-grade malignant potential adenocarcinoma, with main diameter of 1.1 cm, at 3 cm from lung margins. 12 nodes were removed, from station 5,6,7,10,11, all of the free of metastases. Conclusions: Our initial observations suggest that Dual-Portal Robotic-Assisted Tho-racic Surgery (DRATS) demonstrates notable feasibility.

This article examines the evolution of bariatric surgery, with a focus on emerging technologies such as robotics and laparoscopy. In the case of gastric bypass, no significant differences have emerged between the two techniques in terms of hospitalization duration, weight loss, weight regain, or 30-day mortality. Robotic surgery, while requiring more time in the operating room, has been associated with lower rates of bleeding, mortality, transfusions, and infections. In revisional bariatric surgery, the robotic approach has shown fewer complications, shorter hospital stays, and a reduced need for conversion to open surgery. In the case of sleeve gastrectomy, robotic procedures have required more time and longer post-operative stays but have recorded lower rates of transfusions and bleeding compared to laparoscopy. However, robotic surgeries have proven to be more costly and potentially more complex in terms of post-operative complications. The review has also addressed the topic of the single anastomosis duodeno-ileal switch (SADIS), finding comparable results between robotic and laparoscopic techniques, although robotic procedures have required more time in the operating room. Robotic technology has proven to be safe and effective, albeit with slightly longer operating times in some cases.

The evaluation of robotic hands is a subjectively biased, complex process. The fields pertaining to robotic hands are human-centric in nature, making human hands a good standard for benchmark comparisons of robotic hands. To achieve this, we propose a new evaluation index, where we evaluate robotic hands on three fronts: their form, features and performance. An evaluation on how anthropomorphic robotic hands are in basic mobility, and appearance constitutes the ``Form'', while features that can be read, changed and actuated for effective control of robotic hands constitutes the ``Features''. We derived these key features from an extensive analysis of robotic hands in literature. Finally, the robotic hands carry out a series of tasks that evaluate their ``Performance''. An individual score for each category is drawn and we carry out a three-pronged analysis. We also propose an additional feature in the form of price to provide context when analysing multiple hands.

Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with conveyor belt, robot and industry color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of standard uncertainties of type A and B, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e. measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

In order for robots to attain more general-purpose utility, grasping is a necessary skill to master. Such general-purpose robots may use their perception abilities in order to visually identify grasps for a given object. A grasp describes how a robotic end-effector can be arranged on top of an object to securely grab it between the robotic gripper and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task-specific algorithm, but this is an arduous and time-consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods have driven robotics researchers to explore the application of deep learning methods in task generalised robotic applications. This paper reviews the current state-of-the-art in regards to the application of deep learning methods to generalised robotic grasping and discusses how each element of the deep learning approach has improved the overall performance of robotic grasp detection. A number of the most promising approaches are evaluated and the most successful for grasp detection is identified as the one-shot detection method. The availability of suitable volumes of appropriate training data is identified as a major obstacle for effective utilisation of the deep learning approaches, and the use of transfer learning techniques is identified as a potential mechanism to address this. Finally, current trends in the field and future potential research directions are discussed.

This research uses ARM-based FPGA to implement the computation of a virtual-real fusion hardware system. It also evaluates the acceleration effect of virtual-real fusion execution speed after connecting related hardware acceleration and provides a reference for real-time information fusion system design. The hardware uses Xilinx Zynq UltraScale+ MPSoC ZCU102 Evaluation Kit. It also obtains color and depth images with Intel® RealsenseTM D435i depth cameras. This system receives image data through the Linux system built on the ARM and fed to the FPGA for object detection using CNN models. In addition, it develops a module for rapidly performing registration between the color images and the depth images. It can calculate the size and position of the display information on the transparent display according to the pixel coordinates and depth values of the human eye and the object. The fusion took about 47ms on a personal computer with a GPU RTX2060 and 25ms on the ZCU102. The acceleration is nearly 168%. Finally, the results were successfully transplanted into the retail display system for demonstration.

Classifying spinal tumors can be challenging due to nonspecific clinical and radiological qualities, and a precise biopsy is crucial for an accurate diagnosis and treatment planning. This study aimed to enhance the accuracy and efficiency of spinal biopsies integrating Cone Beam Computed Tomography (CBCT) and magnetic resonance imaging (MRI) modalities using an O-arm CT navigation system. Eighteen patients with diverse spinal lesions underwent 18 biopsies following the Stealth Station navigation system Spine 8 protocol. Preoperative MRI scans were merged with intraoperative CT navigation systems for continuous monitoring during the biopsy process. The combined imaging technique accurately identified the diseased lesion type in all biopsies, demonstrating 100% sensitivity and specificity. In conclusion, combining MRI and CT imaging modalities significantly improved spinal biopsy accuracy and efficiency, differentiating between pathological entities. However, large-scale studies are desired to validate these findings and investigate potential benefits in different clinical scenarios. Although this method requires general anesthesia, its potential profits in avoiding misdiagnosed lesions and decreasing the need for further invasive procedures make it a promising approach for improving spinal biopsy accuracy and efficiency.

Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

This study introduces a cybernetic control and architectural framework for a robotic fish avatar operated by a human. The behavior of the robot fish is influenced by the electromyographic (EMG) signals of the human operator, triggered by stimuli from the surrounding objects and scenery. An deep artificial neural network (ANN) with perceptrons classifies EMG signals, discerning the type of muscular stimuli generated. The research unveils a fuzzy-based oscillation patterns generator (OPG) designed to emulate functions akin to a neural central pattern generator, producing coordinated fish undulations. The OPG generates swimming behavior as an oscillation function, decoupled into coordinated step signals, right and left, for a dual electromagnetic oscillator in the fish propulsion system. Furthermore, the research presents an underactuated biorobotic mechanism of the subcarangiform type, comprising a two-solenoid electromagnetic oscillator, an antagonistic musculoskeletal elastic system of tendons, and a multi-link caudal spine composed of helical springs. The biomechanics dynamic model and control for swimming, as well as the ballasting system for submersion and buoyancy, are deduced. Experimental results encompass EMG pattern recognition, OPG, and coordinated fish locomotion, with additional topics illustrated through numerical simulations.

An early hypothesis in robot-assisted stroke therapy was that sensorimotor stimulation through robotic assistance is beneficial for recovery. Despite 25 years of upper-limb rehabilitation robotics research, this hypothesis remains untested barring a few studies with small sample sizes. This review aims to provide a critical summary of the current state of this hypothesis by collating evidence from rehabilitation robotics and other related therapeutic approaches. The review starts with a causal model to expose the various direct and indirect routes through which robotic assistance can aid sensorimotor recovery. The indirect routes include the influence of robotic assistance on therapy intensity, patient motivation, and active participation. The direct route is through changes in cortical networks through Hebbian(-like) learning and changes in peripheral tissue properties. There is currently mixed evidence for the direct causal effect of robotic assistance on recovery from the upper-limb rehabilitation robotics literature. However, evidence from the neuromuscular electrical stimulation literature provides some support for this causal role. Based on the data at hand, we hypothesize that the enhanced movement-related sensory feedback from robotic assistance has a direct, possibly small, causal role in the sensorimotor recovery of the upper-limb, and this effect might be detectable with high-intensity therapy. Large, high-intensity, controlled studies are warranted to support or refute the role of robotic assistance on recovery, which is both scientifically and practically important.

Neuromuscular disorders cause progressive muscular weakness, which limits upper extremity mobility and performance during activities of daily life. A dynamic arm support can improve mobility and quality of life. However, their use is often discontinued over time for unclear reasons. This study aimed to evaluate whether users of dynamic arm supports demonstrate and perceive quantifiable mobility benefits over a period of two months. Nine users of dynamic arm supports were included in this observational study. They had different neuromuscular disorders and collectively used four different arm supports. They were observed for three consecutive weeks during which they were equipped with a multi-sensor network of accelerometers to assess the actual use of the arm support and they were asked to provide self-reports on the perceived benefits of the devices. Benefits were experienced mainly during anti-gravity activities and the measured use did not change over time. The self-reports provided contextual information in domains such as participation to social life, in addition to the sensor system. However self-reports overestimated the actual use by up to three-fold compared to the accelerometer measures. A combination of objective and subjective methods is recommended for meaningful and quantifiable mobility benefits during activities of daily life.

One of the biggest challenges in arm prosthesis design is to resemble normal hand functionality. Some of arm prosthesis try to mimic all hand movement, while other try to produce several main hand grip patterns. We design a Versatile Gripping Technology (VGT) from a basic whippletree mechanism to produce main hand grip patterns in arm prosthesis. VGT development is the result of abstraction, negation, and systemic variation process of existing solution. To validate VGT, we test it to produce six pattern of hand grip from Southampton Hand Assessment Procedure. VGT capable to produce lateral, power, tip, extension, and spherical grip. In other hand, VGT including the thumb movement and it only use one simple shape moving part. Thus, VGT is effective and efficient. With this result, we argue that abstraction, negation, and systemic variation process of existing solution can create a novel solution and it is applicable in another problem or domain.

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man-machine interface and smart environment. In this paper, we use time series analysis method for accurately measuring the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply the dynamic time warping (DTW) method and compare its performance with that of the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and trends of time series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of com- pression strength while two points on the article are pushed towards each otherand include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state-action dynamics as significant obstacles for perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth-shaping, rope manipulation, dressing and bag manip- ulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms, and summarise the future direction for the development of the field.

Background: Locally advanced rectal cancers (10-20%) can present with infiltration into adjacent viscera. R0 resections remain the key factor for better survival. Traditionally these cases have been managed with open surgery. There are some limitations of laparoscopic surgery in these case, which can potentially be overcome by robotic surgery. Objectives: To determine the feasibility and outcome results of robotic multi-visceral resection of stage T4 rectal carcinoma. Methods: Consecutive patients having locally advanced carcinoma of rectum, who undergone robotic multi-visceral resection as the primary treatment between 2015 -2018 were included, through our database which was maintained prospectively. All perioperative and intraoperative parameters were analyzed. Patient demographics, co-morbidities, preoperative imaging, endoscopic findings, operative data, histopathology results, postoperative hospital course and procedure related postoperative adverse events were noted and analyzed. Results: Twenty-one patients with the diagnosis of nonmetastatic locally advanced rectal cancers were operated with Robotic Si/X platform. The median body mass index was 28.5 kg/m2 (range 21-42). The mean blood loss during operation was 20 ml (range 5-200), and the mean duration of surgery was 280 min (range 240-430). The median hospital stay after operation was 6 days (range 4-25 days). On postoperative histopathology, R0 resection rate was 90.5% (19/21). Conclusions: The robotic multi-visceral en-bloc resection of stage T4 rectal carcinoma is technically feasible and oncologically safe. Advanced technical skills, accurate radiological staging and careful patient selection can allow the extension of minimal access surgery to this challenging group of patients.

We introduce a novel hybrid Transformer-CNN architecture for robotic grasp detection, designed to enhance the accuracy of grasping unknown objects. Our proposed architecture has two key designs. Firstly, we develop a hierarchical transformer as the encoder, incorporating the external attention to effectively capture the correlation features across the data. Secondly, the decoder is constructed with cross-layer connections to efficiently fuse multi-scale features. Channel attention is introduced in the decoder to model the correlation between channels and to adaptively recalibrate the channel correlation feature response, thereby increasing the weight of the effective channels. Our method is evaluated on the Cornell and Jacquard public datasets, achieving an image-wise detection accuracy of 98.3% and 95.8% on each dataset, respectively. Additionally, we achieve object-wise detection accuracy of 96.9% and 92.4% on the same datasets. A physical experiment is also performed using the Elite 6Dof robot, with a grasping accuracy rate of 93.3%, demonstrating the proposed method's ability to grasp unknown objects in real-world scenarios. The results of this study show that our proposed method outperforms other state-of-the-art methods.

This paper presents a system that merges computer vision and surface electromyography techniques to carry out grasping tasks. To perform this, the vision-driven system is used to compute pre-grasping poses of the robotic system based on the analysis of tridimensional object features. Then, the human operator can correct the pre-grasping pose of the robot using surface electromyographic signals from the forearm during wrist flexion and extension. Weak wrist flexions and extensions allow a fine adjustment of the robotic system to grasp the object and finally, when the operator considers that the grasping position is optimal, a strong flexion is performed to initiate the grasping of the object. The system has been tested with several subjects to check its performance showing a grasping accuracy of around 95% of the attempted grasps which increases by around a 9% the grasping accuracy of previous experiments in which electromyographic control was not implemented.

Traditional end-effector robots for arm rehabilitation are usually attached a­t the hand, primarily focusing on coordinated multi-joint training. Therapy at an individual joint level of the arm for severely impaired stroke survivors is not always possible with existing end-effector robots. The Arm Rehabilitation Robot (AREBO)—an end-effector robot—was designed to provide both single and multi-joint assisted training while retaining the advantages of traditional end-effector robots, such as ease of use and cost-effectiveness (compared to exoskeletons). This work presents the design, optimization, and characterization of AREBO for training single-joint movements of the arm. The AREBO has three actuated and three unactuated degrees of freedom, allowing it to apply forces in any arbitrary direction at its endpoint and self-align to arbitrary orientations within its workspace. The AREBO’s link lengths were optimized to maximize its workspace and manipulability. The AREBO provides single-joint training in both unassisted and adaptive weight support modes using a human arm model to estimate the human arm's kinematics and dynamics without using additional sensors. The characterization of the robot’s controller and the algorithm for estimating the human arm parameters were performed using a two degrees of freedom mechatronic model of the human shoulder joint. The results demonstrate that: (a) the movements of the human arm can be estimated using a model of the human arm and robot’s kinematics, (b) the AREBO has similar transparency to that of existing arm therapy robots in the literature, and (c) the adaptive weight support mode control can adapt to different levels of impairment in the arm. This work demonstrates how an appropriately designed end-effector robot can be used for single-joint training, which can be easily extended to multi-joint training. Future work will focus on the evaluation of the system on patients with any neurological condition requiring arm training.

About 70% of children and adolescents with cerebral palsy experience gait impairments which affect their autonomy and well-being. Robotic-assisted gait training using the Lokomat is particu-larly promising for rehabilitation as it provides a standardized environment favoring the massive repetition of the movement, in which physical demands are low on the therapist and high training loads can be achieved. As no guidelines exist regarding training protocols and Lokomat settings, the goal of this study was to review the literature on Lokomat-assisted gait therapy and possibly make training recommendations. The twelve studies reviewed reported both positive and null effects of Lokomat training on gait. Half of the studies combined Lokomat with other types of training and only five used a control intervention to assess its benefit. Overall, training was administered 1-5 times per week for 20-60 minutes, over 1-12 weeks. Although Lokomat settings were not always described, progressively decreasing body-weight support and guidance, while increasing treadmill speed appear to be prioritized. The variety of training protocols and settings used did not allow pooling of the studies to assess effects of interventions on gait parameters in children and adoles-cents with cerebral palsy. This review highlights the need for homogenization of interventions so that clear guidelines can emerge and be applied in rehabilitation centers.

Robot-assisted rehabilitation has emerged as a promising approach for enhancing motor function in stroke survivors. However, the feasibility and effectiveness of home-based robotic training in this population are underexplored, especially in low/middle-income countries. This feasibility study aimed to address this gap by examining the feasibility and effectiveness of independent home-based training using PLUTO, a robotic device for hand training. A total of 7 chronic stroke survivors were recruited, with 5 completing the study. The results revealed high engagement and adherence to the home-based training program, with participants averaging 1659.8 minutes of training over 24.8 days. The PLUTO system demonstrated excellent usability and elicited positive user perceptions. Significant improvements were observed in functional outcomes, as evidenced by a noteworthy increase in Fugl-Meyer Assessment scores (mean increase of 6.2 points, exceeding the minimal clinically important difference (MCID) of 5.35 points). Furthermore, participants showed improvements in the ABILHAND measure (mean improvement of 1.24 logits, surpassing the MCID of 0.2 logits) and the Barthel Index (mean increase of 8.8 points). These findings demonstrate the feasibility and effectiveness of home-based robotic rehabilitation for chronic stroke survivors. This has implications for expanding access to rehabilitation services in low- and middle-income countries, enhancing patient engagement and adherence, and improving functional outcomes. Larger controlled studies are warranted to evaluate the effectiveness of home-based robotic rehabilitation programs.

The vibrations of a Cartesian cutting machine caused by the pneumatic tool are studied with a sub-system approach. The cutting head is modeled as an equivalent robot arm which is able to mimic the measured resonances, The Cartesian structure is modeled according to the mode superposition approach. The full model is able to predict the variations in the response of the machine to tool excitation that are caused by the motion of the head along the rails of the Cartesian structure. Comparisons with experimental results are made. Finally, the mathematical model is used for assessing the effectiveness of a vibration absorber tuned to main resonance frequency of the cutting head.

Spinal metastatic tumors are common and often cause debilitating symptoms. Image-guided percutaneous thermal ablation (IPTA) has gained significant recognition in managing spinal column tumors due to its exceptional precision and effectiveness. Conventional guidance modalities, including computed tomography, fluoroscopy, and ultrasound, have been important in targeting spinal column tumors while minimizing harm to adjacent critical structures. This study presents a novel approach utilizing a fusion of Cone Beam Computed Tomography with Magnetic Resonance Imaging to guide percutaneous thermal ablation for four patients with secondary spinal column tumors. The visual analog scale (VAS) evaluated procedure effectiveness during an 18-month follow-up. Percutaneous vertebroplasty was performed in two cases, and a thermostat was used during all procedures. Imaging was performed using the Stealth Station navigation system Spine 8 (SSS8) and a 1.5T MRI machine. The fusion of CBCT with MRI allowed precise tumor localization and guidance for thermal ablation. Initial results indicate successful tumor ablation and symptom reduction, emphasizing the potential of CBCT-MRI fusion in spinal column tumor management. This innovative approach is promising in optimizing therapy for secondary spinal column tumors. Further studies are necessary to validate its efficacy and applicability.

This paper provides a structured and practical roadmap for practitioners to integrate Learning from Demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an easy-to-follow roadmap for practitioners with moderate expertise, to transform existing robotic processes to customizable LfD-based solutions. To realize this transformation, we devise the key questions of "What to Demonstrate", "How to Demonstrate", "How to Learn", and "How to Refine". To follow through these questions, our comprehensive guide offers a questionnaire-style approach, highlighting key steps from problem definition to solution refinement. The paper equips both researchers and industry professionals with actionable insights to deploy LfD-based solutions effectively. By tailoring the refinement criteria to manufacturing settings, the paper addresses related challenges and strategies for enhancing LfD performance in manufacturing contexts.

Cloud robotics is becoming an alternative to support advanced services of robots with low computing power as network technology advances. Recently, fog robotics has gained attention since the approach has merit relieving latency and security issues over the conventional cloud robotics. In this paper, a Function-as-a-Service based Fog Robotic (FaaS-FR) for cognitive robots is proposed. The model distributes the cognitive functions according to the computational power, latency and security with a public robot cloud and fog robot server. During the experiment with a Raspberry Pi as an edge, the proposed FaaS-FR model shows efficient and practical performance in the proper distribution of the computational work of the cognitive system.

We report on an exploratory study conducted at a graduate school in Sweden with a humanoid robot, Baxter. First, we describe a list of potentially useful capabilities for a robot teaching assistant derived from brainstorming and interviews with faculty members, teachers, and students. These selected capabilities consist of reading, greeting, alerting, remote operation, clarification, and motion. Second, we present feedback on how the robot's capabilities, demonstrated in part with the Wizard of Oz approach, were perceived, and iteratively adapted over the course of several lectures, using the \EP tool. Third, we discuss observations and findings regarding the capabilities and the development process. Our findings suggest that using a social robot as a teaching assistant is promising using the chosen capabilities. We find that personalizing the capabilities and the role of embodiment are important topics to be considered in future work.

The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to sprouting of a relatively new yet extremely rewarding sphere of technology. The fusion of current deep reinforcement algorithms with physical advantages of a soft bio-inspired structure certainly directs us to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment to achieve a task they have been assigned. For soft robotics structure possessing countless degrees of freedom, it is often not easy (something not even possible) to formulate mathematical constraints necessary for training a deep reinforcement learning (DRL) agent for the task in hand, hence, we resolve to imitation learning techniques due to ease of manually performing such tasks like manipulation that could be comfortably mimicked by our agent. Deploying current imitation learning algorithms on soft robotic systems have been observed to provide satisfactory results but there are still challenges in doing so. This review article thus posits an overview of various such algorithms along with instances of them being applied to real world scenarios and yielding state-of-the-art results followed by brief descriptions on various pristine branches of DRL research that may be centers of future research in this field of interest.

This paper presents the robotic platform, PiBot, that has been developed and that is aimed at improving the teaching of Robotics with vision to secondary students. Its computational core is the Raspberry Pi 3 controller board, and the greatest novelty of this prototype is the support developed for the powerful camera mounted on board, the PiCamera. An open software infrastructure written in Python language was implemented so that the student may use this camera, or even a WebCam, as the main sensor of this robotic platform. Also, higher level commands have been provided to enhance the learning outcome for beginners. In addition, a PiBot 3D printable model and the counterpart for the Gazebo simulator were also developed and fully supported. They are publicly available so that students and educational centers that do not have the physical robot or can not afford the costs of these, can nevertheless practice and learn or teach Robotics using these open platforms: DIY-PiBot and/or simulated-PiBot.

Service robots operating in indoor environments should recognize dynamic changes from sensors, such as RGB-D camera, and recall the past context. Therefore, we propose a context query-processing framework, comprising spatio-temporal robotic context query language (ST-RCQL) and spatio-temporal robotic context query-processing system (ST-RCQP), for service robots. We designed them based on the spatio-temporal context ontology. ST-RCQL can query not only the current context knowledge but also the past. In addition, ST-RCQL includes a variety of time operators and time constants, and thus queries can be written very efficiently. The ST-RCQP is a query-processing system equipped with a perception handler, working memory, and backward reasoner for real-time query-processing. Moreover, ST-RCQP accelerates query-processing speed by building a spatio-temporal index in the working memory, where percepts are stored. Through various qualitative and quantitative experiments, we demonstrate the high efficiency and performance of the proposed context query-processing framework.

(1) Background: The lateral arm flap has been the very useful choice in the reconstruction of small- to medium-sized defects like hand, extremity, oral head and neck area reconstructions. Its versatile characteristics and surgical feasibility allow this flap to be widely applied, but the reconstructive potential in facial subunit after tumor ablative procedures has never been reported. In this study, we aimed to utilize the advantages of the flap to treat facial temple subunit defect reconstruction. (2) Methods: Between 2020 and 2023, 12 patients underwent temple reconstruction with lateral arm free flaps after malignant tumor wide excision. There were 7 women and 5 men, and the mean patient age was 60.6 years old. Among the patients with cancer, 6 had squamous cell carcinoma, 5 had basal cell carcinoma and 1 had myxofibrosarcoma. All the flaps were elevated under general anesthesia. Aloprostadil(PGE1, Eglandin®) were administered postoperatively. (3) Results: All the flap types were fasciocutaneous type with varied sizes from 3 × 4 to 5 × 7 cm (Average size of flap 22.7cm2) were utilized. The average pedicle length was 6.1cm. The versatility of the lateral arm flap enabled successful coverage of all cases with no specific complications. Good functional outcome and range of motion in the recipient arm were obtained after surgery. (4) Conclusion: The authors successfully verified the advantages of lateral arm flaps in the treatment of medium sized facial subunt temple defect reconstruction.

Burning mouth syndrome (BMS) is a chronic oral pain disorder. There is a theory that BMS is nociplastic pain. Standard treatment for BMS has not yet been established. Kampo medicine is a traditional oriental medicine. The purpose of this study is to evaluate the effectiveness of rikkosan—a traditional Japanese herbal medicine (Kampo)—in the treatment of BMS. A single-center retrospective study was conducted in 20 patients who were diagnosed with BMS and treated with rikkosan alone (7.5 g) three times daily for approximately 4 weeks. They were treated with rikkosan alone approximately 4 weeks (29.5 ± 6.5 days) for the initial treatment. They had an average age of 63 years and 90% were being treated for other illnesses, but their medication status was the same during this study period, except for rikkosan. No side effects were observed in patients. Numerical rating scale (NRS) or visual analogue scale (VAS)/10 scores decreased significantly between the time of the initiation of rikkosan and the one-month after (-2.1 ± 1.2, p < 0.05). Rikkosan has a short-term effect of reducing NRS by two levels in BMS patients.

In the last decade, robotic-mediated rehabilitation has emerged as a potential solution to improve repetitive task training. Each device in this field has a unique development history shaped by engineers’ expertise in specific programming languages or platforms. In this work we adopt an approach that tries to abstract from the final implementation with the aim to make control logic more shareable and understandable. The authors will present the outcomes of the application of a Rapid Control Prototyping strategy to an upper-limb robotic exoskeleton. A model-based design approach implemented on a real-time target machine is presented. This modern design approach was explored with several control strategies and was used to test the exoskeleton’s performances. The proposed method highlights how it is possible to develop the entire control architecture in a single programming environment.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

Obesity represents a worldwide epidemic disorder, increasing the overall morbidity and mortality rate. In this study we investigated the impact of obesity on peri-operative and long-term functional outcomes of Robotic assisted simple prostatectomy (RASP). Baseline flowmetry parameters and validated questionnaires’ scores were prospectively recorded. Follow-up assessments included Flowmetry and validated questionnaires. Composite outcomes (Trifecta) was defined as combination of: post-operative Q-max>15 ml/sec, IPSS score<8 and absence of complications. Pentafecta included also post-operative ejaculation persistence (MSHQ score>0) and the Erectile function maintenance (∆IEEF<6). Data were stratified by BMI (<30 or ≥30). 81 patients underwent RASP in our Institution. Baseline demographics and clinical features, questionnaires score and baseline flowmetry results were comparable between obese and non-obese cohorts. At follow-up, obese patients reported lower subjective improvement in IPSS (p=0.02) and OABQ scores (p<0.001) and higher incidence of stress incontinence requiring Duloxetin (p<0.001). Flowmetry outcomes, were also worse in this cohort (p=0.02 and p=0.03, respectively). At comprehensive outcomes assessment, obese patients had comparable Trifecta (67% vs 54%, p=0.39) and pentafecta achievement rate (p=0.76). Our prelimirary results proved that obesity is associated with worse functional outcomes (storage LUTS and incontinence rate) after RASP, but doesn’t affect trifecta and pentafecta achievement rate.

Endoscopy has made a significant and noteworthy contribution to the field of medical science and technology. Nevertheless, its potential remains constrained due to the limited availability of rigid or flexible endoscopes. This paper introduces a novel hydraulic actuator based on electrorheological fluid (ERF) as a pivotal advancement in bridging the existing gap within the realm of endoscopy. Following a comprehensive introduction that briefly outlines the electrorheological effect, the subsequent section is dedicated to the elucidation of the actuator’s development process. Challenges arise, particularly in terms of miniaturization and the realization of a hydraulically sealed system with integrated valve electrodes. An internal electrorheological valve system consisting of four valves that are controlled using a pulse-width modulated high voltage was suitable for position control of the antagonistic hydraulic actuators. High-precision stereolithography (SLA) printing has proven practical for manufacturing the actuator components. For functional testing, a test bench was set up in which the actuator follows a setpoint through a PI control loop. The control deviation ranged from 0.6 to 1 degree, with a response time between 6 and 8 seconds. The experiments have demonstrated that, through the use of ERF and integrated valve electrodes, a miniaturized functional actuator can be constructed.

In large industrial plants, the trend is to move the position of the human to the area of service and diagnostics, in medium and smaller plants the trend is different and is mainly directed to the sphere of close cooperation between the human and the robotic system. This paper deals with the implementation of human-cooperating robots in manufacturing processes. The analytical part of the paper deals with theoretical knowledge, taking into account the latest trends in the subject area. To achieve a successful implementation of cobots based on the above-mentioned operating systems in manufacturing systems, it is necessary to pay attention specifically to the interfacing of the robotic operating system with the control systems of the manufacturing systems at the process level of the enterprise. Within the practical part, an algorithm with well-defined steps towards the successful implementation of cobots in holonic manufacturing processes is proposed. By setting up an experimental workstation in the laboratory, the proposed procedures are verified at the end of the paper. In the context of the implementation of collaborative robots in enterprises, the paper also discusses cloud computing. The creation of a design for the implementation of a collaborative robot with a human represents the missing link in the whole chain of commercial applications of the latest trends from the field of robotic systems in the industrial sphere.

We describe and analyze the Local Charged Particle Swarm Optimization (LCPSO) algorithm, that we designed to solve the problem of tracking a moving target releasing scalar information in a constrained environment using a swarm of agents. This method is inspired by flocking algorithms and the PSO algorithm for function optimization. Four parameters drive LCPSO: the number of agents; the inertia weight; the attraction/repulsion weight; and the inter-agent distance. Using APF, we provide a mathematical analysis of the LCPSO algorithm under some simplifying assumptions. First, the swarm will aggregate and attain a stable formation, whatever the initial conditions. Second, the swarm moves thanks to an attractor in the swarm, which serves as a guide for the other agents to head for the target. By focusing on a simple application of target tracking with communication constraints, we then remove those assumptions one by one. We show the algorithm is resilient to constraints on the communication range, and the behavior of the target. Results on simulation confirm our theoretical analysis. This provides useful guidelines to understand and control the LCPSO algorithm as a function of swarm characteristics as well as the nature of the target.

The purpose of this study was to quantify characteristics of bimanual movement intensity during 30-hour Hand Arm Bimanual Intensive Therapy (HABIT) and bimanual performance (activities and participation) in real-world using accelerometers in children with unilateral cerebral palsy (UCP). Twenty-five children with UCP participated in a 30-hour HABIT program. Data was collected from bilateral wrist-worn accelerometers during 30-hours HABIT to quantify the movement intensity, and three days pre- and post-HABIT to assess real-world performance gains. Movement intensity and performance gains were measured using six standard accelerometer-derived variables. Bimanual capacity (body function and activities) was assessed using standardized hand function tests. We found that accelerometer variables increased significantly during HABIT, indicating increased bimanual symmetry and intensity. Post-HABIT, children demonstrated significant improvements in all accelerometer metrics, reflecting real-world performance gains. Children also achieved significant and clinically relevant changes in the hand capacity following HABIT. Therefore, our findings suggest that accelerometers can objectively quantify bimanual movement intensity during HABIT. Moreover, HABIT enhances hand function as well as activities and participation in real-world situation in children with UCP.

Modelling errors, robust stabilization/tracking problems under parameter and model uncertainties complicate the control of the flexible underactuated systems. Chattering-free sliding-mode based input-output control law realizes robustness against the structured and unstructured uncertainties in the system dynamics and avoids excitation of unmodeled dynamics. The main purpose is to propose a robust adaptive solution for stabilizing and tracking direct-drive (DD) flexible robot arms under parameter and model uncertainties, as well as external disturbances. A lightweight robot arm subject to external and internal dynamic effects was taken into consideration. The challenges are compensating actuator dynamics with the inverter switching effects and torque ripples, stabilizing the zero dynamics under parameter/model uncertainties and disturbances while precisely track the predefined reference position. The precise control of this kind of system demands an accurate system model and knowledge of all sources that excite unmodeled dynamics. For this purpose, equations of motion for a flexible robot arm were derived and formulated for the large motion via Lagrange’s method. The goals were determined to achieve high-speed, precise position control, and satisfied accuracy by compensating the unwanted torque ripple and friction that degrades performance through an adaptive robust control approach. The actuator dynamics and their effect on the torque output were investigated due to the transmitted torque to the load side. The high-performance goals, precision&robustness issues, and stability concerns were satisfied by using robust-adaptive input-output linearization-based control law combining chattering-free sliding mode control (SMC) while avoiding the excitation of unmodeled dynamics.

Plantar flexors (PF) spasticity is known to poorly correlate with active dorsiflexion (DF) impairment throughout the swing phase of hemiparetic gait. Spastic Cocontraction, instead, stemming from descending pathways, potentially misdirect antagonist PF activity opposing DF during swing. Electromyographic (EMG) recordings, while unable to differentiate between reflex-based and descending origins, may offer valuable insights into this distinction by exploring PF EMG activity after tibial nerve neurotomy (which eliminates PF spasticity). Eleven subjects with hemiparesis walking at comfortable velocity and 11 controls walking at comfortable and slow velocity, underwent kinematic and PF/DF EMG analysis. Five of the hemiparetic subjects underwent tibial neurotomy &gt;1 year prior. We evaluated spasticity at rest (Tardieu scale), maximal ankle dorsiflexion, tibialis anterior agonist recruitment and gastrocnemius medialis and soleus cocontraction coefficients during swing. At slow velocity, controls (0.80±0.12 m/s) moved at a similar pace as hemiparetic subjects (0.73±0.37 m/s, NS). Hemiparetic subjects showed: (i) reduced ankle DF across swing (ii) increased PF cocontraction, including before any DF (iii) higher cocontraction despite absent spasticity in tibial neurotomy subjects (iv) higher tibialis anterior recruitment. Increased PF cocontraction occurs in the absence of spasticity or ankle DF despite higher agonist recruitment. Spastic cocontraction is a major factor limiting active DF at swing, unlike spasticity.

Within environmental perception, automatic navigation and object detection, computer vision is a crucial and demanding field with many applications in modern industries, such as multi-target long-term visual tracking in automated production, defect detection, and driverless robotic vehicles with sensing ability. The performance of computer vision has greatly improved recently thanks to developments in deep learning algorithms and hardware computing capabilities, which has spawned the creation of a large number of related applications. This paper presents the results of a detailed review of over 50 papers published over the course of two decades (1999–2024), with a primary focus on the technical advancement of computer vision. To elucidate the foundational principles, an examination of typical visual algorithms based on traditional correlation filtering was initially conducted. Subsequently, a comprehensive overview of the most recent advancements in deep learning-based computer vision techniques was compiled. Furthermore, a comparative analysis between conventional and novel algorithms was undertaken to discuss the future trends and directions of computer vision. Lastly, the feasibility of employing visual SLAM (Simultaneous Localization and Mapping) algorithms in the context of autonomous vehicles with sensing capability was explored. Furthermore, we explored a thorough and efficient architecture for utilizing these techniques in autonomous robotic vehicles into unmanned green and low-carbon smart factories, underlining novel advances as well as potential prospects for future research.

Background Robotic-assisted thoracic surgery (RATS) has become the standard procedure for treating lung malignancy, offering numerous advantages over traditional methods. However, the minimally invasive nature of RATS presents unique challenges, notably a limited field of view and reduced tactile feedback for the surgeon. These limitations can significantly impact the surgeon's ability to navigate complex anatomical structures during surgery. To address these challenges, we recognized the need for enhanced preoperative familiarization with each patient’s specific anatomy. In response, we developed an innovative virtual reality (VR) surgical navigation system, utilizing head-mounted displays (HMDs), designed to provide surgeons with a more comprehensive and interactive understanding of the patient's anatomy before the actual surgery. This VR system aims to extend the surgeon's capabilities in both preoperative sumilation and intraoperative navigation, potentially mitigating the inherent limitations of RATS. Methods Three-dimensional (3D) volumized data, meticulously extracted from preoperative computed tomography (CT) scans, were seamlessly integrated into the Perspectus VR Education software. These data were then displayed on an HMD, facilitating an interactive 3D reconstruction of pulmonary structures. This reconstruction allowed for each structure to be visualized individually, enabling detailed preoperative resection simulations tailored to each patient's unique anatomy. During RATS, these specific 3D reconstructed images were made accessible within the surgeon's console through the TilePro™ multi-display input, providing real-time, intraoperative guidance. Results During the preoperative simulations, the 3D anatomic structure of the pulmonary vessels, as well as the spatial relationship between the lesion and adjacent tissues, were successfully visualized. This enhanced visualization enabled surgeons to thoroughly evaluate a patient's anatomy, significantly improving the safety and accuracy of the subsequent procedure. The integration of VR software with the HMD provided surgeons with a true 3D interaction with real patient data. This setup not only offered a unique perspective through the surgical console but also allowed for easy manipulation of the data on a mobile laptop, thereby enhancing the overall surgical planning process. Conclusions VR simulation using HMDs offers a viewing experience akin to that of a robotic 3D viewer, potentially providing an innovative avenue for surgeons to develop specific robotic surgical skills without the need for practicing on live patients. This technology, when integrated with routine imaging modalities, can significantly enhance preoperative planning. Such integration not only contributes to the safety but also improves the accuracy of anatomical resections. Our findings suggest that VR simulation with HMDs is particularly effective in assisting surgeons to accurately identify lesion locations in RATS, thereby optimizing surgical outcomes.

The upper extremities limitation represents one of the essential functional impairments in patients with cervical spinal cord injury. Electromechanics assisted devices and robots are increasingly used in neurorehabilitation to help functional improvement in patients with neurological diseases. This review aimed to systematically report the evidence-based, state-of-art on clinical applications and robotic-assisted arm training (RAT) in motor and functional recovery in subjects affected by cervical spinal cord injury. The present study has been carried out within the framework of the Italian Consensus Conference on "Rehabilitation assisted by robotic and electromechanical devices for persons with disability of neurological origin" (CICERONE). PubMed/MEDLINE, Cochrane Library, and Physiotherapy Evidence Database (PEDro) databases were systematically searched from inception to September 2021. The 10-item PEDro scale assessed the study quality for the RCT and the AMSTAR-2 for the systematic review. Two different authors rated the studies included in this review. If consensus was not achieved after discussion, a third reviewer was interrogated. The 5-item Oxford CEBM scale was used to rate the level of evidence. A total of 11 studies were included. The selected studies were: two systematic reviews, two RCTs, one parallel-group controlled trial, one longitudinal intervention study and five case series. One RCT was scored as a high-quality study, while the systematic review was of low quality. RAT was reported as feasible and safe. Initial positive effects of RAT were found for arm function and quality of movement in addition to conventional therapy. The high clinical heterogeneity of treatment programs and the variety of robot devices could severely affect the generalizability of the study results; therefore, future studies are warranted to standardize the type of intervention and evaluate the role of robotic-assisted training in subjects affected by cervical spinal cord injury.

Worldwide, millions of kilometres of sewers are constructed from concrete pipes. Unfortunately, concrete sewers are susceptible to corrosion from biogenic hydrogen sulphide, and though they may pass visual inspection, their ability to hold together under load may be degraded. This paper presents the design of a teleoperated robot with a protractible probe, that allows an operator to apply a localised load to selected points within a concrete sewer pipe. We report findings from laboratory and field trials of our prototype, with initial results suggesting that this approach has the potential to contribute useful information to sewer maintenance planning.

RISC-V offers a modular technical approach combined with an open, royalty-free instruction set architecture (ISA). This openness allows various researches to incorporate RISC-V into both open and proprietary solutions or services. However, despite its advantages as a fundamental building block for many embedded systems, the escalating complexity and functional demands of real-time applications have made adhering to response time deadlines challenging. This has led to an increased demand for comprehensive development insights for real-time systems based on RISC-V. To improve development efficiency, we offer a detailed performance analysis of RISC-V in comparison to various ISAs. In this paper, we analyze the real-time performance of RISC-V through two real-time approaches based on processor architectures. For RTOS applications, we adopted FreeRTOS and evaluated its performance on HiFive1 Rev B (RISC-V) and STM3240G-EVAL (ARM M) to evaluate real-time performance. For Real-time Linux, we utilized Linux with the Preempt-RT patch and tested its performance on VisionFive 2 (RISC-V), MIO5272 (x86-64), and Raspberry Pi 4 B (ARM A). Through these experiments, we examined the real-time mechanism of each operating system. Additionally, in the Preempt-RT experiments, scheduling latencies were evaluated using cyclictest. Finally, in order to practically show the real-time capabilities of RISC-V, we implemented motion control of a six-axis collaborative robot, which was performed on the VisionFive 2 platform. This implementation provided a comparative result of RISC-V’s performance against the x86-64 architecture of MIO-5272. Ultimately, the results indicated that the real-time performance of RISC-V for real-time applications was slightly inferior to that of the x86-64 architecture. A noticeable achievement of this research was the first implementation of an EtherCAT Master on RISC-V designed for real-time applications featuring a multi-tasking structure. The research offers valuable insights into the real-time capabilities of RISC-V compared to established architectures like x86-64. While RISC-V might not surpass these architectures in real-time performance, its flexibility, modularity, and open nature make it a compelling choice for a wide range of real-time applications. The successful implementation of the EtherCAT Master on RISC-V further expands its potential in the domain of real-time embedded control systems.

(1) Background. Intracavitary hyperthermic chemotherapy (HITHOC) remains a part of the complex mosaic which is the multimodal approach in advanced stage thymomas and pleural malignancies, and its role is still widely debated. In recent years, several studies have demonstrated the feasibility and the efficacy of HITHOC combined with cytoreductive surgery in the treatment of thymoma relapses and malignant pleural mesothelioma (MPM). However, there are currently no studies available on pleurectomy/removal of pleural lesions using the robotic technique, in association with intrathoracic chemotherapy. The aim of this narrative review is to evaluate the feasibility and safety of robotic pleurectomy/removal of relapses and HITHOC in patients with pleural recurrence of thymoma or MPM, after having analyzed the literature concerning this controversial topic, and to report our experience with robotic surgery. (2) Methods: A review of papers published on this topic, from 1980, was conducted. Later, the data of consecutive patients affected by thymoma relapses or MPM who underwent robotic surgery in combination with HITHOC will be collected and analyzed. The surgery performed, prior to intrathoracic infusion of the high-temperature chemotherapy, consisted of the removal of the recurrences or pleurectomy, depending on the pathology. All surgeries were performed with a 4-port-fully robotic technique. (3) Results: Between 2017 and 2022, nine patients underwent robotic cytoreductive surgery in combination with HITHOC. No intraoperative complications occurred. One patient had a grade II Clavien-Dindo postoperative complication. Oncological follow-up showed results in line with the literature. (4) Conclusion: With the limitation of the small number of patients, considering the results, robotic surgery may represent the surgical approach of choice, in combination with HITHOC, in patients with pleural relapses of thymoma and early-stage MPM.

This paper illustrates that the ROTASE model proposed by the author for the formation of spiral arms of galaxies is nicely demonstrated by the spirals generated by rockets venting fuel during free fall. The patterns of spirals by the falling rockets strongly support that the spiral galaxies with perfect central symmetry have to be originated from the galactic centers, and the spiral arms and the galactic bars are bound together as “rigid” body. The exclusive presence of a rear side trail effect in galaxies indicates the absence of co-rotation, and the rotation of spiral arms is faster than the galactic matters. The exact nature of X-matter remains an open question.

Background and Objectives: Light therapy (LT) is used as an adjunctive treatment for sleep problems. This study evaluates the impact of LT on sleep quality and sleep-related parameters in patients with sleep disorders. Materials and Methods: We performed a pilot randomized, open-label clinical trial. Fourteen patients aged 20–60 years with sleep disorders for more than three months were randomized into the control and LT groups (1:1 ratio). The LT group was instructed to use a device that provides bright LT (6000 K, 380 lux, wavelength 480 nm) for at least 25 minutes before 09:00 am for two weeks. A self-reported questionnaire was used to evaluate circadian preference, mood, and sleep-related parameters. We analyzed serum cortisol levels and clock genes expression. Results: The Epworth Sleepiness Scale (ESS), insomnia severity index, and Pittsburgh Sleep Quality index were significantly improved within the LT group only after the two-week period. When comparing the two groups, only the change in ESS significant was significant (mean difference; control: -0.14 vs LT: -1.43, p=0.021) after adjusting for baseline characteristics. There were no significant differences in serum cortisol or clock genes expression. Conclusions: LT can improve daytime sleepiness in patients with sleep disorders; however, further well-designed studies are warranted to confirm its efficacy.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

The corrosion behavior of Fe-containing directionally solidified (DS) and centrifugally cast (CC) Al-Si-Cu-Zn alloys with either Co or Ni additions has been investigated. Electrochemical and immersion corrosion methods were used to investigate the corrosion behavior in 0.6 M NaCl after short (1-hour) and long (30-day) exposure periods. The employed solidification methods allowed the production of samples with a wide range of secondary dendrite arm spacing (SDAS) while preserving Si and Fe-containing phases. The 0.5 wt.% Ni and Co additions led to the growth of the AlFeSi(Ni) and AlFeSi(Co) phases, but no binary AlNi nor AlCo intermetallic par-ticles have been generated. Potentiodynamic polarization studies at early exposure revealed an increase in the corrosion potential as the Ni was added for either fast or slow solidified samples. The electrochemical impedance spectroscopy at early exposure demonstrated that the Ni-modified alloy, on the other hand, was associated to smaller charge transfer resistances, in-dicating a reduction in corrosion resistance after short elapsed time into the electrolyte. Howev-er, 30-day immersion tests revealed much lower corrosion rate of the Ni-modified alloy than the other alloys, while the corrosion rates of the Co-modified and non-modified alloys were simi-lar. In the Ni-containing alloy, decreased corrosion rate under long-term corrosion process was attributed to the formation of a thick and dense alumina layer, effectively protecting the surface under such conditions. This work contributes to a better knowledge of the corrosion behavior of Ni- and Co-corrected Al industrial scrap compositions.

While researchers have made notable progress in bio-inspired swimming robot development, a persistent challenge lies in creating propulsive gaits tailored to these robotic systems. The California sea lion achieves its robust swimming abilities through a careful coordination of foreflippers and body segments. In this paper, reinforcement learning (RL) was used to develop a novel sea lion foreflipper gait for a bio-robotic swimmer using a numerically modelled computational representation of the robot. This model integration enabled reinforcement learning to develop desired swimming gaits in the challenging underwater domain. The novel RL gait outperformed the characteristic sea lion foreflipper gait in the simulated underwater domain. When applied to the real-world robot, the RL constructed novel gait performed as well or better than the characteristic sea lion gait in many factors. This work shows the potential for using complimentary bio-robotic and numerical models with reinforcement learning to enable the development of effective gaits and maneuvers for underwater swimming vehicles.

Background DaVinci Single-Port (SP) robotic surgery offers several benefits compared to traditional multiport laparoscopic or robotic surgeries. One of the main advantages is that it allows for a minimally invasive approach, resulting in a single, smaller incision and reduced trauma to the patient’s body leading to less postoperative pain, faster recovery, and reduced risk of complications. The cosmesis of a single port with minimal visible scarring is also an attractive aspect to the patients; however, many surgeons use an additional port for energy device, stapler use, and drain insertion. Pure single port surgery with one incision is still rare. Here we share our experience of first 10 cases using SP robotic platform in colorectal surgery. Methods From May 2023 to December 2023, colorectal patients who underwent SP-robotic surgery were analyzed. Placement of the incision was umbilicus for 8 patients, and right lower quadrant for 2 patients through which ileostomy maturation was performed. Data including perioperative parameters and postoperative outcomes were analyzed with a median follow-up of 4.6months (range 0.6-7.4months). Results A total number of 10 colorectal patients underwent DaVinci Single-Port robotic colorectal surgery at our institution during this period. Demographics of the patients showed 4 males (40%) and 6 females (60%) with a median age of 63.5years (range 50-75years). Median body mass index (BMI) was 22.89kg/m2 (range 19.92-26.84kg/m2), and 9 patients were diagnosed with colorectal cancer and 1 patient was diagnosed with rectal gastrointestinal tumor. One patient underwent anterior resection and cholecystectomy simultaneously. Mean operation time was 222min (range 142-316min), and mean wound size was 3.25cm (range 2.5-4.5cm). Nine patients underwent surgery with single incision through which single port trocar was inserted, and one patient had one additional port for drain insertion. Mean hospital stay was 6 days (range 4-8 days) with 1 postoperative complication of bleeding requiring transfusion, but there was no re-admission within 30 days. Conclusion Overall, our experience with single-port robotic colorectal surgery has been promising. With only one patient with additional port for drain insertion, all nine patients underwent SP-robotic surgery with single incision for colon as well as rectal surgeries. Compared to an average postoperative length of stay of 6.5-8 days in laparoscopic colorectal surgeries reported in literature, SP-robotic surgery showed faster recovery of 6 days highlighting its benefits in patient recovery and satisfaction.

Diagnosing cervical foraminal stenosis with intermittent arm radiculopathy is chal-lenging due to discrepancies between MRI findings and symptoms. This can be attributed to the fact that MRI images are often obtained in a relaxed supine position. This study aims to evaluate the feasibility of the Dynamic MRI Compression System (DMRICS) and to assess possible changes in cervical foramina, with both quantitative measurements and qualitative grading systems, with MRI during a simulated Spurling test. Ten patients (5 women and 5 men, ages 29-45) with previously confirmed cervical foraminal stenosis underwent MRI scans using DMRICS. MRIs were acquired in both relaxed and provoked states. A radiologist assessed 30 foramina (C4-C7) on the symptomatic side in both patient positions. Quantitative and qualitative measures were performed including the Numeric Rating Scale (NRS) and the Park and Kim grading systems. The provoked state induced concordant neck and arm pain in 9 of 10 patients. Significant shifts in Park and Kim fo-raminal gradings were noted: 13 of 27 Park gradings and 9 of 27 Kim gradings escalated post-provocation. No quantitative changes were observed. This pilot study indicates that the DMRICS device has potential to improve diagnostic accuracy for cervical radicu-lopathy, demonstrating induced cervical foraminal changes during a simulated Spurling test while performing MRI.

A three-arm, randomized, placebo controlled clinical study has been performed to evaluate the effects of a lyophilized pineapple extract titrated in bromelain (Brome-Inf®), and purified bro-melain on pain, swelling, trismus and quality of life (QoL) after the surgical removal of the lower third molars. Moreover, the need for non-steroidal anti-inflammatory drugs (NSAIDs) has also been evaluated and compared with a placebo group. The study included 42 people that required the extraction of a single mandibular third molar under local anesthesia. The patients were ran-domized and distributed to receive Brome-Inf®, purified bromelain or placebo and started the treatment the day of surgery and continued it for the next 7 days. The primary outcome was the requirement of NSAIDs in the three groups. The outcome variables were pain, swelling and trismus, which were measured postoperatively at 1, 3, and 7 days. The differences in the efficacy of the freeze-dried pineapple extract and single-component bromelain were also evaluated. At the end of the study, the assumption of ibuprofen (from days 1-7) was statistically higher in the placebo group (p

Efficient processing of end-of-life lithium-ion batteries of electric vehicles is important and a pressing challenge for a circular economy. Regardless of whether the processing strategy is recycling, repurposing or remanufacturing, the first processing step would usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. The work was conducted as a case study to demonstrate the concept of autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported and future research directions are suggested.

While shoulder injuries represent the musculoskeletal disorders (MSDs) most encountered in physical therapy, there is no consensus on their management. As attempts to provide standardized and personalized treatment, a robot-ic-assisted device combined with EMG biofeedback specifically dedicated to shoulder MSDs has been developed. The aim of this study was to determine the efficacy of an 8-week rehabilitation program (≈3 sessions a week) using a ro-botic-assisted device combined with EMG biofeedback (RA-EMG group) in comparison with a conventional program (CONV group) in patients presenting with shoulder MSDs. This study is a retrospective cohort study including data from 2010 to 2013 on patients initially involved in a physical rehabilitation program in a private clinic of Chicoutimi (Canada) for shoulder MSDs. Shoul-der flexion strength and range of motion were collected before and after the rehabilitation program. Forty-four patients participated in a conventional pro-gram using dumbbell (CONV group) while 72 of them completed a program on robot-assisted device with EMG and visual biofeedback (RA-EMG group), whereby both programs consisted in 2 sets of 20 repetitions at 60% of maximal capacity. Results showed that the RA-EMG had significantly greater benefits than the Conv group for shoulder flexion strength (+103.1% vs 67%, p = 0.016) and range of motion (+14.4% vs 6.1%, p = 0.046). The current retrospective co-hort study showed that a specific and tailored rehabilitation program with constant effort by automatic adjustment of the level of resistance was able to potentiate strength and range of motion shoulder flexion after an 8-week reha-bilitation period in comparison with a conventional approach in patients with shoulder MSDs. This study provides new insight on shoulder MSD rehabilita-tion and future research should be pursued to determine the added potential of this approach for abduction and external rotation with a randomized controlled design.

Inland waters pose a unique challenge for water quality monitoring by remote sensing techniques due to their complicated spectral features and small-scale variability. At the same time, collecting the high-quality reference data needed to calibrate remote sensing data products is both time consuming and expensive. In this study, we present the further development of a robotic team composed of an uncrewed surface vessel (USV) providing in situ reference measurements and an unmanned aerial vehicle (UAV) equipped with a hyperspectral imager. Together, this team is able to address the limitations of existing approaches by enabling the simultaneous collection of comprehensive in situ data together with high-resolution hyperspectral imagery. We showcase the capabilities of this team using data collected in a north Texas pond during three collections in the fall of 2020. Machine learning models for 13 variables are trained using the data set of paired in situ measurements and coincident reflectance spectra. These models can successfully estimate physical variables, including temperature, conductivity, pH, and turbidity, as well as the concentrations of blue-green algae, colored dissolved organic matter (CDOM), chlorophyll-a, crude oil, optical brighteners and the ions Ca2+, Cl−, and Na+. We extend the training procedure to utilize conformal prediction to estimate 90% confidence intervals for the output of each trained model. The maps generated by applying each trained model to the collected images reveal the small-scale spatial variability within the pond. Additionally, the permutation importance computed for each feature of the trained models highlights the spectral features relevant to each water quality variable.

Abstract. Leiomyoma is a benign tumour of smooth muscle cells classified into three groups: solid leiomyoma, angioleiomyoma and leiomyoblastoma. Angioleiomyoma arises from the tunica media of veins and arteries of vascular smooth muscle.Nasal cavity, paranasal sinus and oral cavity are the most frequent locations in Head and Neck region. Here we present the case of a tongue base angioleiomyoma with an emphasis on clinical data, pathologic findings and surgical approach. The patient complained about a one-month of globus sensation, dysphagia and hemoptysis without other systemic symptoms. Laryngoscopy revealed the presence of a 2 cm solitary submucosal mass located on the left tongue base covered with normal mucosa. The patient underwent direct laryngoscopy to perform a biopsy for the purpose of achieving the conclusive diagnosis. Treatment options were discussed, included surgical resection. Transoral robot-assisted resection was performed without complications. Clearly the description of our case does not want to have a purpose in terms of indications but wants to describe the possibility of considering TORS in the case of benign tumours of the tongue base, especially in cases like this where a standard technique can difficulty be achieved. Current literature review was provided and discussed.

Background: Wilms tumor (WT) is the main renal tumor in children. SIOP-UMBRELLA Guidelines admit Nephron sparing surgery (NSS) in syndromic patients, and in small (&lt;300 ml) nonsyndromic unilateral WTs, without lymph node involvement, and with a substantial expected remnant renal function, after neoadjuvant chemotherapy. We report our prechemotherapy transperitoneal robot-assisted partial nephrectomy (RAPN) in a unilateral non-syndromic Wilms tumor. Methods: A 6-year-old-child showed an exophytic 3.6 cm diameter solid rounding mass involving the upper right renal pole at an incidental abdominal echotomography. CT-scan and abdominal MRI proved no local infiltration neither lymph node involvement was appreciated, suggesting an exophytic mass easily resectable through a NSS robotic approach, with a low risk of rupture and no subverted renal anatomy. The preoperative imaging was not suggestive for WT. A virtual 3D reconstruction of the tumor was performed. Results: the oncologic board approved a robot-assisted partial nephrectomy with the intraperitoneal approach. The histopathologic analysis displayed a WT. The patient underwent 10 vincristine-doses adjuvant chemotherapy. 28-months follow-up showed no tumor recurrence. Conclusions: Intraperitoneal RAPN can represent an opportunity for WT and needs to be assessed as a challenging possibility. This case suggests a potential role of prechemotherapy RAPN in the near future for highly selected patients.

Background: Mood disorders, especially depression, and emotional difficulties such as anxiety are very common problems among patients with spinal cord injury (SCI). The loss of physical training may deteriorate their mental state, which in turn has a significant impact on the improvement of functioning. The aim of the present study was to examine the influence of innovative rehabilitation approaches involving robotic assisted gait therapy (RAGT) on mood and anxiety symptoms in pa-tients with SCI. Methods: To this single-centre, single-blinded, single-arm, prospective study, 110 participants with subacute SCI were enrolled; patients were divided into experimental (robotic assisted gait therapy -RAGT) and control (conventional gait therapy with dynamic parapodium - DPT) groups. They received five training sessions per week over 7- weeks. The severity of de-pression was assessed by Depression Assessment Questionnaire (KPD) and anxiety symptoms by State - Trait Anxiety Inventory (STAI X-1) on the beginning and end of therapy. Results: SCI patients experienced significantly lower levels of anxiety and depression-related symptoms after completing the seven-week rehabilitation program (KPD: Z=6.35; p<0.001; r=0.43; STAI X-1: Z=-6.20; p<0.001; r=0.42) in both group of patients. In the RAGT group, post-rehabilitation measurements also indicated an improvement in psychological functioning, i.e., a decrease in depression and anxiety, and an increase in self-regulation. Significant results were noted for each variable (STAI X-1: Z = -4.93; KPD: Z = -5.26; SR: Z = -3.21). In the control group, there was also a decrease in the effect on the depression, anxiety-state and an increase in self-regulation ability (STAI X-1: Z=-4.01; KPD: Z=-3.65; SR: Z=-2.83). Rehabilitation modality did not appear to have a statistically significant relationship with the magnitude of improvement in KPD (including SR) and STAI scores. However, there were some significant differences when comparing the groups by extent and depth of injury and type of paralysis. The study also did not find a significant rela-tionship between improvements in physical aspects and changes in psychological factors. Conclusion: Subjects in RAGD and DPT groups experienced a decrease in anxiety and depres-sion after a 7-week rehabilitation program. However, the rehabilitation modality (DPT vs. RAGT) did not differentiate patients with SCI in terms of the magnitude of this change. Our results may suggest that individuals with severe neurological condition and complete spinal cord injury (AIS A) may experience more benefit in terms of change in psychological parameters after rehabilitation with RAGT.

This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and is relevant to satellite calibration/validation and the creation of new remote sensing data products. A case study is described for the rapid characterisation of the aquatic environment, over a period of just a few minutes we acquired thousands of training data points. This training data allowed our machine learning algorithms to rapidly learn by example and provide wide area maps of the composition of the environment. Along side these larger autonomous robots two smaller robots that can be deployed by a single individual were also deployed (a walking robot and a robotic hover-board), observing significant small scale spatial variability.

Background: The present study compared corticospinal excitability to the biceps brachii muscle during arm cycling at a self-selected and a fixed cadence (SSC and FC, respectively). We hypothesized that corticospinal excitability would not be different between the two conditions. Methods: The SSC was initially performed and the cycling cadence was recorded every 5 seconds for one minute. The average cadence of the SSC cycling trial was then used as a target for FC of cycling that the participants were instructed to maintain. Motor evoked potentials (MEPs) elicited via transcranial magnetic stimulation (TMS) of the motor cortex were recorded from the biceps brachii during each trial of SSC and FC arm cycling. Results: Corticospinal excitability as assessed via normalized MEP amplitudes (MEPs were made relative to a maximal compound muscle action potential) were not different between groups. Conclusions: Focusing on maintaining a FC cadence during arm cycling does not influence corticospinal excitability as assessed via TMS-evoked MEPs.

STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a flexible robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. It consists of three cable-driven systems, one endoscope serving as guide and two inserted instruments. The flexible and bendable instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this research, a pair of specific sensor gloves, which ergonomically fit to the master handles of the system was designed and the forces applied by one expert and one novice user during system-specific task execution in a simulator task (4-step-pick-and-drop) were compared. The results show that user expertise is not only reflected by shorter task execution times but also, more importantly, by specific differences in handgrip force profiles for specific sensor locations on anatomically relevant parts of the fingers and hand controlling the surgical instruments of the robotic master/slave system.

Sexual issues and treatment side effects are not routinely discussed with men receiving treatment for prostate cancer and support to address these concerns is not consistent across settings. This study evaluates a brief e-learning resource designed to improve sexual wellbeing support and examine its effects on healthcare professionals’ sexual attitudes and beliefs. Healthcare professionals (n=44) completed an online questionnaire at baseline which included a modified 12-item sexual attitudes and beliefs survey (SABS). Follow-up questionnaires were completed immediately after the e-learning and at 4 weeks. Data were analysed using one-way, repeat measures ANOVAs to assess change in attitudes and beliefs over time. Significant improvements were observed at follow-up for a number of survey statements including ‘knowledge and understanding’, ‘confidence in discussing sexual wellbeing’ and the extent to which participants felt ‘equipped with the language to initiate conversations’. The resource was seen as concise, relevant to practice, and as providing useful information on potential side effects of treatment. Brief, e-learning has potential to address barriers to sexual wellbeing communication and promote delivery of support for prostate cancer survivors. Practical methods and resources should be included with these interventions to support implementation of learning and long-term changes in clinical behaviour.

This study evaluates the R3THA™ technology-supported assessment protocol for home-based rehabilitation in children with cerebral palsy (CP). It focuses on the reliability and validity of R3THA™ in assessing hand and arm function, comparing kinematic assessments with standard clinical assessments. Conducted during a 4-week summer camp, the study involved children with CP aged 3-18, assessing their functional and impairment levels. The findings suggest that R3THA™ is more reliable for children aged 8 and older, indicating that age significantly influences the protocol's effectiveness. Results also showed that R3THA-AP's kinematic measurements of hand and wrist movements were positively correlated with the Box and Blocks Test Index (BBTI), reflecting hand function and dexterity. Additionally, R3THA-AP's accuracy metrics for hand and wrist activities aligned with the Melbourne Assessment 2's Range of Motion (MA2-ROM) scores, suggesting a meaningful relationship between R3THA-AP data and clinical assessments of motor skills. However, no significant correlations were observed between R3THA-AP and MA2's accuracy and dexterity measures, indicating areas for further research. These findings validate R3THA-AP's utility in assessing motor abilities in CP, supporting its integration into clinical practice.

Dry eye syndrome (DES) has become increasingly prevalent due to the prolonged use of digital devices in modern society. Individual supplementation with lutein or docosahexaenoic acid (DHA) demonstrated potential benefits for eye health. This study aimed to investigate the effects of lutein plus DHA complex supplementation on DES, visual function, and memory in healthy individuals. Thirty-four participants, aged 40~60 years, received lutein/DHA complex supplements (containing 10 mg free-form lutein, 200 mg DHA, 30 mg red algae extract (astaxanthin), phosphatidylserine, and vitamin A) for 12 weeks. Ophthalmological examinations and memory tests were carried out, and a questionnaire was administered at weeks 0, 6, and 12 of the study. After 12 weeks of the intervention, the tear break-up time had significantly increased, and intraocular pressure (IOP) had significantly decreased. This suggests that lutein/DHA complex supplementation may reduce the IOP and offer potential benefits for DES, as indicated by improved tear stability.

This study examines the practicality and limitations of using a FANUC CRX-10 iA/l collaborative robot to assemble a product component, highlighting the trade-offs between increased roboisation and reduced manual intervention. Through a detailed case study in the i-Labs laboratory, critical factors affecting precision assembly such as station layout, tooling design and robot programming are discussed. The findings highlight the benefits of robots for non-stop operation, freeing up human operators for higher value tasks despite longer cycle times. In addition, the paper advocates further research into reliable gripping of small components, a current challenge for robotics. The work contributes to open science by sharing partial results and methods that could inform future problem solving in robotic assembly.

Nerve-sparing vs. non nerve sparing surgery (NSS vs. non-NSS) is associated with improved functional outcomes in prostatectomy patients. The aim of the present study is to compare the oncological outcomes of patients with high-risk localized prostate cancer undergoing nerve-sparing and non nerve-sparing robot-assisted radical prostatectomy (RARP). Between November 2002 and December 2018, we prospectively recorded data of patients undergoing RARP for high-risk localized prostate cancer (PCa). NSS (nerve-sparing surgery) was offered based on preoperative clinical characteristics of patients and intraoperative assessment. Patients were stratified into 2 groups according to NSS. The primary outcome was biochemical recurrence (BCR), while positive surgical margin (PSM) and cancer-specific survival (CSS) were secondary outcomes. Logistic regression was used to investigate predictive factors. A total of 779 patients were included in the study, 429 (55.1%) underwent NSS while 350 (44.9%) underwent a non-NSS. After a mean (±SD) follow-up of 192 (±14) months, 328 (42.1%) patients developed BCR, no significant difference was found between NSS and non-NSS group (156 vs. 172; p=0.09). Both univariable and multivariable analysis found that nerve-sparing approach was not a predictor of BCR (p>0.05). NSS vs. non-NSS was not associated with worse oncological outcomes in patients with high-risk PCa

Obstructive sleep apnea (OSA) is a common sleep disorder, and continuous positive airways pressure (CPAP) is the most effective treatment. Poor adherence is one of the major challenges in CPAP therapy. The recent boom of wearable optical sensors measuring oxygen saturation makes the at-home multiple-night CPAP titrations possible, which may essentially improve the adherence of CPAP therapy by optimizing its pressure in a real-life setting economically. We tested whether the oxygen desaturations (OD) measured in the arm muscle (arm_OD) by gold-standard frequency-domain multi-distance near-infrared spectroscopy (FDMD-NIRS) changes with titrated CPAP pressures in OSA patients together with polysomnography. We found that the arm_OD (2.08 ± 1.23%, mean ± standard deviation) was significantly smaller (P-value &lt;0.0001) than the fingertip OD (finger_OD) (4.46 ± 2.37%) measured by polysomnography pulse oximeter. Linear mixed-effects models suggested that CPAP pressure was a significant predictor for finger_OD but not for arm_OD. Since FDMD-NIRS measures a mixture of arterial and venous OD, whereas fingertip pulse oximeter measures arterial OD, our results of no association between arm_OD and finger_OD indicate that the arm_OD mainly represented venous desaturation. Arm_OD measured by near-infrared optical sensors may be not a suitable indicator of the effectiveness of CPAP titration.

Objectives: Robotic bilateral axillary breast approach (BABA) thyroid surgery began in 2008 and is now one of the most widely used remote-access thyroid surgeries worldwide. This study aimed to analyze the results of 500 robotic BABA thyroid surgeries performed in a single institution in Korea compared with open thyroid surgery. Methods: From December 2018 to March 2020, 502 robotic BABA thyroidectomies (RTs) and 531 conventional open thyroidectomies (OTs) were performed in our institution by a single endocrine surgeon. We retrospectively reviewed patient medical records and performed a comparative analysis of OT and RT. Results: The RT group was younger (43.41±11.41 versus 54.28±13.41 years, p<0.001) and had a higher proportion of females (84.3% versus 69.3%, p<0.001), a lower BMI (24.66±3.97 versus 25.83±4.07 kg/m2), a higher proportion of lobectomies (52.6% versus 45.2%) and a lower proportion of lateral neck dissections (3.4% versus 10.0%, p<0.001). The RT group had a lnger operation time (145.33±40.80 versus 93.39±43.55 minutes, p<0.001) and higher surgical cost. Although the OT group had a larger tumor size and higher proportion of extrathyroidal extension, the numbers of retrieved lymph nodes were not significantly different between the two groups. Additionally, there was no difference in the stimulated thyroglobulin level before radioactive iodine therapy (7.01±35.73 versus 8.39±58.77, p=0.782). The rates of transient vocal cord palsy and transient hypoparathyroidism were significantly lower in the RT group, and those of scar-related complications were higher in the OT group. Conclusion: Robotic BABA thyroid surgery has advantages not only in better cosmetic outcomes but also in lower rates of vocal cord palsy and hypoparathyroidism, with comparable lymph node retrieval and serum thyroglobulin levels.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.