Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accuracy, and consistency in machining operations. However, robot implementation faces some limitations, such as a huge variety of materials and tools, low adaptability to environmental changes, flexibility issues, a complicated tool path preparation process, and challenges in quality control. Industrial robotics applications include cutting, milling, drilling, and grinding procedures on various materials, including metal, plastics, and wood. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. Some publications propose approaches for planning the robot’s posture or tool orientation. In contrast, others focus on optimizing machining parameters through the utilization of advanced control and computation, including machine learning methods with the integration of collected sensor data.

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.

Electrically conductive polymers are promising materials for charge transfer from living cells to the anodes of electrochemical biosensors and biofuel cells. The modification of living cells by polypyrrole (PPy) causes shortened cell lifespan, burdens the replication process, and diminishes renewability in the long term. In this paper, the viability and morphology non-modified, inactivated, and PPy-modified yeasts were evaluated. The results displayed a reduction in cell size, an incremental increase in roughness parameters, and the formation of small structural clusters of polymers on the yeast cells with the increase in the pyrrole concentration used for modification. Yeast modified with the lowest pyrrole concentration showed minimal change; thus, a microbial fuel cell (MFC) was designed using yeast modified by a solution containing 0.05 M pyrrole and compared with the characteristics of an MFC based on non-modified yeast. The maximal generated power of the modified system was 47.12 mW/m², which is 8.32 mW/m² higher than that of the system based on non-modified yeast. The open-circuit potentials of the non-modified and PPy-modified yeast-based cells were 335 mV and 390 mV, respectively. Even though applying a PPy layer to yeast increases the charge-transfer efficiency towards the electrode, the damage done to the cells due to modification with a higher concentration of PPy diminishes the amount of charge transferred, as the current density drops by 846 μA/cm². This decrease suggests that modification by PPy may have a cytotoxic effect that greatly hinders the metabolic activity of yeast.

Microbial fuel cell (MFC) efficiency depends on charge transfer capability from microbe to anode, and the application of suitable redox mediators is important in this area. In this study, yeast viability experiments were performed to determine the 2-methyl-1,4-naphthoquinone (menadione (MD)) influence on different yeast cell species (baker’s yeast and Saccharomyces cerevisiae yeast cells). In addition, electrochemical measurements to investigate MFC performance and efficiency were carried out. This research revealed that baker’s yeast cells were more resistant to dissolved MD, but the current density decreased when yeast solution concentration was incrementally increased in the same cell. The maximal calculated power of a designed baker’s yeast-based MFC cell anode was 0.408 mW/m² and this power output was registered at 24 mV. Simultaneously, the cell generated a 62-mV open circuit potential in the presence of 23 mM potassium ferricyanide and the absence of glucose and immobilized MD. The results only confirm that MD has strong potential to be applied to microbial fuel cells and that a two-redox-mediator-based system is suitable for application in microbial fuel cells.

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.

Scanning electrochemical microscopy enhanced by electrochemical impedance spectroscopy (SEIM) was applied to detect immobilized antibodies labelled with horseradish peroxidase (Ab-HRP). The localized HRP activity was investigated by the SEIM redox competition (RC-SEIM) mode using hydrogen peroxide as a substrate and hexacyanoferrate as a redox mediator. Electrochemical impedance shows to be related to the consumption of hydrogen peroxide at the ultramicroelectrode. For the evaluation of impedimetric results, an equivalent electric circuit was applied with solution resistance, double-layer capacitance, and charge-transfer resistance. These equivalent circuit characteristics depend on the distance between the sample and ultramicroelectrode, and the concentration of substrate. From the gathered data, the charge-transfer resistance appeared to be the parameter describing the behavior of HRP catalyzed reaction as it showed a linear dependence on H₂O₂ concentration. The RC-SEIM mode suitability for the studying of HRP catalyzed reactions and for the evaluation of Ab-HRP bound to the surface was demonstrated. Additionally, the applicability of RC-SEIM mode for the determination of Ab-HRP affinity bound to the target analyte was discussed.