Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication.

Autonomous systems are becoming increasingly relevant in our everyday life. The transportation field is no exception and the smart cities concept raises new tasks and challenges for the development of autonomous systems development which has been progressively researched in literature. One of the main challenges is communication between different traffic objects. For instance, a mobile robot system can work as a standalone autonomous system reacting to a static environment and avoiding obstacles to reach a target. Nevertheless, more intensive communication and decision making is needed when additional dynamic objects and other autonomous systems are present in the same working environment. Traffic is a complicated environment consisting of vehicles, pedestrians, and various infrastructure elements. To apply autonomous systems in this kind of environment it is important to integrate object localization and to guarantee functional and trustworthy communication between each element. To achieve this, various sensors, communication standards, and equipment are integrated via the application of sensor fusion and AI machine learning methods. In this work review of vehicular communication systems is presented. The main focus is the researched sensors, communication standards, devices, machine learning methods, and vehicular-related data to find existing gaps for future vehicular communication system development. In the end, discussion and conclusions are presented.

Fast detection of micro-objects using scanning electrochemical microscopy based on visual recognition and machine learning.

Scanning electrochemical microscopy (SECM) is a scanning probe microscope with an ultramicroelectrode (UME) as a probe. The technique is advantageous in the characterization of the electrochemical properties of surfaces. However, the limitations, such as slow imaging and many functions depending on the user, only allow us to use some of the possibilities. Therefore, we applied visual recognition and machine learning to detect micro-objects from the image and determine their electrochemical activity. The reconstruction of the image from several approach curves allows it to scan faster and detect active areas of the sample. Therefore, the scanning time and presence of the user is diminished. An automated scanning electrochemical microscope with visual recognition has been developed using commercially available modules, relatively low-cost components, design, software solutions proven in other fields, and an original control and data fusion algorithm.

Stretch Sensor: Development of Biodegradable Film.

This article presents research on biodegradable stretch sensors produced using biological material. This sensor uses a piezoresistive effect to indicate stretch, which can be used for force measurement. In this work, an attempt was made to develop the composition of a sensitive material and to design a sensor. The biodegradable base was made from a κ-carrageenan compound mixed with Fe2O3 microparticles and glycerol. The influence of the weight fraction and iron oxide microparticles on the tensile strength and Young's modulus was experimentally investigated. Tensile test specimens consisted of 10-25% iron oxide microparticles of various sizes. The results showed that increasing the mass fraction of the reinforcement improved the Young's modulus compared to the pure sample and decreased the elongation percentage. The GF of the developed films varies from 0.67 to 10.47 depending on composition. In this paper, it was shown that the incorporation of appropriate amounts of Fe2O3 microparticles into κ-carrageenan can achieve dramatic improvements in mechanical properties, resulting in elongation of up to 10%. The developed sensors were experimentally tested, and their sensitivity, stability, and range were determined. Finally, conclusions were drawn on the results obtained.

Biodegradable Carrageenan-Based Force Sensor: An Experimental Approach.

The development of low-cost biodegradable pressure or force sensors based on a carrageenan and iron (III) oxide mix is a promising way to foster the spread of green technologies in sensing applications. The proposed materials are inexpensive and abundant and are available in large quantities in nature. This paper presents the development and experimental study of carrageenan and iron (III)-oxide-based piezoresistive sensor prototypes and provides their main characteristics. The results show that glycerol is required to ensure the elasticity of the material and preserve the material from environmental impact. The composition of the carrageenan-based material containing 1.8% Fe2O3 and 18% glycerol is suitable for measuring the load in the range from 0 N to 500 N with a sensitivity of 0.355 kΩ/N when the active surface area of the sensor is 100 mm2. Developed sensors in the form of flexible film have square resistance dependence to the force/pressure, and due to the soft original material, they face the hysteresis effect and some plastic deformation effect in the initial use stages. This paper contains extensive reference analysis and found a firm background for a new sensor request. The research covers the electric and mechanical properties of the developed sensor and possible future applications.

Characteristics and Functionality of Cantilevers and Scanners in Atomic Force Microscopy.

In this paper, we provide a systematic review of atomic force microscopy (AFM), a fast-developing technique that embraces scanners, controllers, and cantilevers. The main objectives of this review are to analyze the available technical solutions of AFM, including the limitations and problems. The main questions the review addresses are the problems of working in contact, noncontact, and tapping AFM modes. We do not include applications of AFM but rather the design of different parts and operation modes. Since the main part of AFM is the cantilever, we focused on its operation and design. Information from scientific articles published over the last 5 years is provided. Many articles in this period disclose minor amendments in the mechanical system but suggest innovative AFM control and imaging algorithms. Some of them are based on artificial intelligence. During operation, control of cantilever dynamic characteristics can be achieved by magnetic field, electrostatic, or aerodynamic forces.

Yeast cell detection using fuzzy automatic contrast enhancement (FACE) and you only look once (YOLO).

In contemporary biomedical research, the accurate automatic detection of cells within intricate microscopic imagery stands as a cornerstone for scientific advancement. Leveraging state-of-the-art deep learning techniques, this study introduces a novel amalgamation of Fuzzy Automatic Contrast Enhancement (FACE) and the You Only Look Once (YOLO) framework to address this critical challenge of automatic cell detection. Yeast cells, representing a vital component of the fungi family, hold profound significance in elucidating the intricacies of eukaryotic cells and human biology. The proposed methodology introduces a paradigm shift in cell detection by optimizing image contrast through optimal fuzzy clustering within the FACE approach. This advancement mitigates the shortcomings of conventional contrast enhancement techniques, minimizing artifacts and suboptimal outcomes. Further enhancing contrast, a universal contrast enhancement variable is ingeniously introduced, enriching image clarity with automatic precision. Experimental validation encompasses a diverse range of yeast cell images subjected to rigorous quantitative assessment via Root-Mean-Square Contrast and Root-Mean-Square Deviation (RMSD). Comparative analyses against conventional enhancement methods showcase the superior performance of the FACE-enhanced images. Notably, the integration of the innovative You Only Look Once (YOLOv5) facilitates automatic cell detection within a finely partitioned grid system. This leads to the development of two models-one operating on pristine raw images, the other harnessing the enriched landscape of FACE-enhanced imagery. Strikingly, the FACE enhancement achieves exceptional accuracy in automatic yeast cell detection by YOLOv5 across both raw and enhanced images. Comprehensive performance evaluations encompassing tenfold accuracy assessments and confidence scoring substantiate the robustness of the FACE-YOLO model. Notably, the integration of FACE-enhanced images serves as a catalyst, significantly elevating the performance of YOLOv5 detection. Complementing these efforts, OpenCV lends computational acumen to delineate precise yeast cell contours and coordinates, augmenting the precision of cell detection.

Development of Electrostatic Microactuators: 5-Year Progress in Modeling, Design, and Applications.

The implementation of electrostatic microactuators is one of the most popular technical solutions in the field of micropositioning due to their versatility and variety of possible operation modes and methods. Nevertheless, such uncertainty in existing possibilities creates the problem of choosing suitable methods. This paper provides an effort to classify electrostatic actuators and create a system in the variety of existing devices. Here is overviewed and classified a wide spectrum of electrostatic actuators developed in the last 5 years, including modeling of different designs, and their application in various devices. The paper provides examples of possible implementations, conclusions, and an extensive list of references.

Conducting Polymers for the Design of Tactile Sensors.

This paper provides an overview of the application of conducting polymers (CPs) used in the design of tactile sensors. While conducting polymers can be used as a base in a variety of forms, such as films, particles, matrices, and fillers, the CPs generally remain the same. This paper, first, discusses the chemical and physical properties of conducting polymers. Next, it discusses how these polymers might be involved in the conversion of mechanical effects (such as pressure, force, tension, mass, displacement, deformation, torque, crack, creep, and others) into a change in electrical resistance through a charge transfer mechanism for tactile sensing. Polypyrrole, polyaniline, poly(3,4-ethylenedioxythiophene), polydimethylsiloxane, and polyacetylene, as well as application examples of conducting polymers in tactile sensors, are overviewed. Attention is paid to the additives used in tactile sensor development, together with conducting polymers. There is a long list of additives and composites, used for different purposes, namely: cotton, polyurethane, PDMS, fabric, Ecoflex, Velostat, MXenes, and different forms of carbon such as graphene, MWCNT, etc. Some design aspects of the tactile sensor are highlighted. The charge transfer and operation principles of tactile sensors are discussed. Finally, some methods which have been applied for the design of sensors based on conductive polymers, are reviewed and discussed.

Deep Q-Learning in Robotics: Improvement of Accuracy and Repeatability.

Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot positioning errors are complex due to the extensive combination of their sources and cannot be compensated for using conventional methods. Some robot positioning errors can be compensated for only using machine learning (ML) procedures. Reinforced machine learning increases the robot's positioning accuracy and expands its implementation capabilities. The provided methodology presents an easy and focused approach for industrial in situ robot position adjustment in real-time during production setup or readjustment cases. The scientific value of this approach is a methodology using an ML procedure without huge external datasets for the procedure and extensive computing facilities. This paper presents a deep q-learning algorithm applied to improve the positioning accuracy of an articulated KUKA youBot robot during operation. A significant improvement of the positioning accuracy was achieved approximately after 260 iterations in the online mode and initial simulation of the ML procedure.

An Automotive Ferrofluidic Electromagnetic System for Energy Harvesting and Adaptive Damping.

Vibration energy harvesting is receiving significant interest due to the possibility of using extra power in various machines and constructions. This paper presents an energy-harvesting system that has a structure similar to that of a linear generator but uses permanent magnets and magnetorheological fluid insets. The application of a standard vehicle example with low frequencies and amplitudes of the excitations was used for the optimization and experimental runs. The optimization for low excitation amplitudes shows that the best magnetic field change along the slider is obtained using differentially orientated radial magnets of 5 mm in width. This configuration was used for the experimental research, resulting in 1.2-3.28 W of power generated in the coils. The power conditioning system in the experimental research was replaced by loading resistors. Nevertheless, the initial idea of energy harvesting and a damping effect was confirmed by the circuit voltage output.

Assessment of Rhizobium anhuiense Bacteria as a Potential Biocatalyst for Microbial Biofuel Cell Design.

The development of microbial fuel cells based on electro-catalytic processes is among the novel topics, which are recently emerging in the sustainable development of energetic systems. Microbial fuel cells have emerged as unique biocatalytic systems, which transform the chemical energy accumulated in renewable organic fuels and at the same time reduce pollution from hazardous organic compounds. However, not all microorganisms involved in metabolic/catalytic processes generate sufficient redox potential. In this research, we have assessed the applicability of the microorganism Rhizobium anhuiense as a catalyst suitable for the design of microbial fuel cells. To improve the charge transfer, several redox mediators were tested, namely menadione, riboflavin, and 9,10-phenanthrenequinone (PQ). The best performance was determined for a Rhizobium anhuiense-based bio-anode mediated by menadione with a 0.385 mV open circuit potential and 5.5 µW/cm2 maximal power density at 0.35 mV, which generated 50 µA/cm2 anode current at the same potential.

Wearable Feet Pressure Sensor for Human Gait and Falling Diagnosis.

Human falls pose a serious threat to the person's health, especially for the elderly and disease-impacted people. Early detection of involuntary human gait change can indicate a forthcoming fall. Therefore, human body fall warning can help avoid falls and their caused injuries for the skeleton and joints. A simple and easy-to-use fall detection system based on gait analysis can be very helpful, especially if sensors of this system are implemented inside the shoes without causing a sensible discomfort for the user. We created a methodology for the fall prediction using three specially designed Velostat®-based wearable feet sensors installed in the shoe lining. Measured pressure distribution of the feet allows the analysis of the gait by evaluating the main parameters: stepping rhythm, size of the step, weight distribution between heel and foot, and timing of the gait phases. The proposed method was evaluated by recording normal gait and simulated abnormal gait of subjects. The obtained results show the efficiency of the proposed method: the accuracy of abnormal gait detection reached up to 94%. In this way, it becomes possible to predict the fall in the early stage or avoid gait discoordination and warn the subject or helping companion person.

Polyethylene-Carbon Composite (Velostat®) Based Tactile Sensor.

The progress observed in 'soft robotics' brought some promising research in flexible tactile, pressure and force sensors, which can be based on polymeric composite materials. Therefore, in this paper, we intend to evaluate the characteristics of a force-sensitive material-polyethylene-carbon composite (Velostat®) by implementing this material into the design of the flexible tactile sensor. We have explored several possibilities to measure the electrical signal and assessed the mechanical and time-dependent properties of this tactile sensor. The response of the sensor was evaluated by performing tests in static, long-term load and cyclic modes. Experimental results of loading cycle measurements revealed the hysteresis and nonlinear properties of the sensor. The transverse resolution of the sensor was defined by measuring the response of the sensor at different distances from the loaded point. Obtained dependencies of the sensor's sensitivity, hysteresis, response time, transversal resolution and deformation on applied compressive force promise a practical possibility to use the polyethylene-carbon composite as a sensitive material for sensors with a single electrode pair or its matrix. The results received from experimental research have defined the area of the possible implementation of the sensor based on a composite material-Velostat®.

Human Emotion Recognition: Review of Sensors and Methods.

Automated emotion recognition (AEE) is an important issue in various fields of activities which use human emotional reactions as a signal for marketing, technical equipment, or human-robot interaction. This paper analyzes scientific research and technical papers for sensor use analysis, among various methods implemented or researched. This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity. The results of the analysis performed in this paper present applicable methods for each type of emotion and their intensity and propose their classification. The classification of emotion sensors is presented to reveal area of application and expected outcomes from each method, as well as their limitations. This paper should be relevant for researchers using human emotion evaluation and analysis, when there is a need to choose a proper method for their purposes or to find alternative decisions. Based on the analyzed human emotion recognition sensors and methods, we developed some practical applications for humanizing the Internet of Things (IoT) and affective computing systems.

Scanning electrochemical microscopy in the development of enzymatic sensors and immunosensors.

Scanning electrochemical microscopy (SECM) is very useful, non-invasive tool for the analysis of surfaces pre-modified with biomolecules or by whole cells. This review focuses on the application of SECM technique for the analysis of surfaces pre-modified with enzymes (horseradish peroxidase, alkaline phosphatase and glucose oxidase) or labelled with antibody-enzyme conjugates. The working principles and operating modes of SECM are outlined. The applicability of feedback, generation-collection and redox competition modes of SECM on surfaces modified by enzymes or labelled with antibody-enzyme conjugates is discussed. SECM is important in the development of miniaturized bioanalytical systems with enzymes, since it can provide information about the local enzyme activity. Technical challenges and advantages of SECM, experimental parameters, used enzymes and redox mediators, immunoassay formats and analytical parameters of enzymatic SECM sensors and immunosensors are reviewed.

Modification of the AFM Sensor by a Precisely Regulated Air Stream to Increase Imaging Speed and Accuracy in the Contact Mode.

Increasing the imaging rate of atomic force microscopy (AFM) without impairing of the imaging quality is a challenging task, since the increase in the scanning speed leads to a number of artifacts related to the limited mechanical bandwidth of the AFM components. One of these artifacts is the loss of contact between the probe tip and the sample. We propose to apply an additional nonlinear force on the upper surface of a cantilever, which will help to keep the tip and surface in contact. In practice, this force can be produced by the precisely regulated airflow. Such an improvement affects the AFM system dynamics, which were evaluated using a mathematical model that is presented in this paper. The model defines the relationships between the additional nonlinear force, the pressure of the applied air stream, and the initial air gap between the upper surface of the cantilever and the end of the air duct. It was found that the nonlinear force created by the stream of compressed air (aerodynamic force) prevents the contact loss caused by the high scanning speed or the higher surface roughness, thus maintaining stable contact between the probe and the surface. This improvement allows us to effectively increase the scanning speed by at least 10 times using a soft (spring constant of 0.2 N/m) cantilever by applying the air pressure of 40 Pa. If a stiff cantilever (spring constant of 40 N/m) is used, the potential of vertical deviation improvement is twice is large. This method is suitable for use with different types of AFM sensors and it can be implemented practically without essential changes in AFM sensor design.

Biomechanical evaluation of native acromioclavicular joint ligaments and two reconstruction techniques in the presence of the sternoclavicular joint: A cadaver study.

BACKGROUND: Where is over 100 reconstruction techniques described for acromioclavicular (AC) joint reconstruction. Although, it is not clear whether the presence of the sternoclavicular (SC) joint influences the biomechanical properties of native AC ligaments and reconstruction techniques. The purpose of the present study was to investigate the biomechanical properties of native AC joint ligaments and two reconstruction techniques in cadavers with the SC joint still present. MATERIALS AND METHODS: We tested eight fresh-frozen cadaver hemithoraces for superior translation (70 N load) and translation increment after 1000 cycles (loading from 20 to 70 N) in a controlled laboratory study. There were three testing groups created: native ligaments, the single coracoclavicular loop (SCL) technique, and the two coracoclavicular loops (TCL) technique. Superior translation was measured after static loading. Translation increment was calculated as the difference between superior translation after cyclic and static loading. RESULTS: Native AC ligaments showed significantly lower translation than the SCL ( p = 0.023) and TCL ( p = 0.046) groups. The SCL had a significantly lower translation increment than native AC ligaments ( p = 0.028). There was no significant difference between reconstruction techniques in terms of translation ( p = 0.865) and translation increment ( p = 0.113). CONCLUSIONS: Native AC joint ligaments had better static properties than both reconstruction techniques and worse dynamic biomechanical properties than the SCL technique. The SCL technique appeared to be more secure than the TCL technique. The presence of the SC joint did not have an observable influence on test results.

Different Stabilization Techniques for Type 62B3 Acetabular Fractures in Combination With Primary Total Hip Arthroplasty in Elderly Patients: A Biomechanical Comparison.

INTRODUCTION: The total hip arthroplasty (THA) as part of acute fracture management is used for acetabular fractures in elderly patients. Our objective was to assess the stability of osteosynthesis performed using 2 different techniques in combination with THA in an experimental model. MATERIALS AND METHODS: We conducted 20 experiments using the left-side hemipelves composite bone models. There were 2 testing groups: 1- and 2-stage osteosynthesis. The acetabular fractures of the anterior column and posterior hemitransverse were simulated. The same THA technique was used in both groups. The stability of osteosynthesis was explored and compared between the groups by measuring the fracture displacement of anterior and posterior columns under the standardized test load (1187 N) protocol. Load distance diagrams were generated. RESULTS: The 0.680-mm gap (0.518; 1.548) of the posterior column in the 1-stage group (n = 10) was higher than the 0.370-mm gap (0.255; 0.428) in the 2-stage group (n = 10; P = .002). There was no significant difference between the gap of the anterior column in the 1- and 2-stage groups (0.135 [0.078; 0.290] mm vs 0.160 [0.120; 0.210] mm; P = .579). CONCLUSION: The 2-stage osteosynthesis of the anterior and posterior columns in combination with THA provides better stability of posterior column when compared to 1-stage method in composite bone models.