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To further improve the sensitivity of porous silicon-assembled microcavity biosensors, the detection of porous silicon assembled microcavity by angle spectrum method is also researched. This contribution uses CdSe/ZnS quantum dot-labelled probe DNA to amplify the refractive index and detect it by the angle spectrum method. The first layer is a microcavity layer, and the next is porous silicon with a Bragg structure. After functionalization, different concentrations of target DNA were coupled to construct quantum dot-labelled probe DNA to bind specifically to the target DNA. With the Bragg device based on quartz glass forming an assembled microcavity structure, using a He-Ne laser as the detection light and collimation beam, the angle spectrum method is used to detect different concentrations of target DNA before and after biological reaction with quantum dot-labelled probe DNA and reflect the angle of minimum light intensity. The experimental results show that with increasing target DNA concentration, probe DNA concentration and angle, the detection limit is 13.25 pM. The angle-spectrum method has been successfully used to detect the assembled porous silicon microcavity. The angle-spectrum method has the advantages of spectrometer free and low cost.

Mechanical testing and gait measurement for ankle-foot orthosis (AFO) are crucial for determining the AFO stiffness magnitude in an individual. However, information on the effect of the stiffness magnitude on the muscle force during gait is limited. This study aimed to investigate the relationship between the AFO stiffness and ankle muscle force during gait. The AFO stiffness was mechanically tested using a six-axis robot arm. The stiffness magnitude was adjusted using different spring constants. Five stiffness conditions were set for each plantarflexion resistive (PFR) and dorsiflexion resistive (DFR) function. The effect of the PFR and DFR on the ankle muscle force during gait were determined using musculoskeletal and AFO models. Tibialis anterior (TA) and triceps surae (TS) muscle forces were calculated through gait simulation. The angle-moment relationships display hysteresis loops for each condition. One of the PFR and DFR conditions differed significantly from the others (for all, p < 0.05). In order of lower stiffness, the each PFR contribution ratio to the peak TA muscle force normalized in the no-stiffness condition was 8.4%, 10.8%, 11.3%, 13.5%, and 15.3%; while the each DFR contribution ratio to the peak TS muscle force was 16.2%, 20.9%, 25.3%, 29.8%, and 30.5%, respectively. Through mechanical testing as well as gait simulation, it was demonstrated that the magnitude of the AFO stiffness decreased the required ankle muscle force during gait. This study can contribute to more effective gait rehabilitation using AFO as well as AFO fabrication with customized stiffness for individual gait function.

Recently, the development of agile-legged robots that mimic the structures and functions of biological muscles and tendons of quadruped mammals has attracted significant attention. The driving force of muscles and the elastic force of muscles and tendons can help improve the performances of these robots. Thus far, most of these robots have been developed based on the muscle-tendon complex of the lower legs. However, some mammals have a larger muscle-tendon complex on the upper legs, which contributes significantly to agile movements. In this study, a legged robot that mimics the functions of the bi-articular muscle-tendon complex of the thigh was developed, and its effects on static and dynamic movements were verified through simulations and experiments. While maintaining a static posture, the transfer of torque between two joints in the thigh mechanism reduced the power consumption by the robot’s motors by half, used for balancing the gravity of the robot. For a dynamic vertical jump, the motion trajectory generation for the robot was performed using non-linear optimization to maximize the jump height. As a result, the jump height was significantly enhanced by the effect of the thigh mechanism, and the height was more than twice the leg length.

A kind of wearable exoskeleton soft rehabilitation glove is proposed for the dementia in Parkinson's disease (PD) patients with loss of hand function, limited range of motion, and insufficient finger muscle strength to carry out rehabilitation exercise training in a passive or auxiliary way. A novel soft joint structure based on composite fabric material is introduced for the design of the soft glove with bionic method, and experiments are conducted to verify the effeteness of the proposed soft rehabilitation glove. The test results showed that when the fluid pressure was 0.42 MPa, the joint angle of MCP, PIP and DIP could be up to 81°, 98°, 72°, and produce output torque of 1.18Nm, 1.44Nm and 1.82Nm respectively, which meets the requirements of the hand rehabilitation. A dynamic rehabilitation-training test of the rehabilitation glove was also carried out, and the results showed that the movement frequency of soft fingers could reach 30 times/min, which is sufficient for repetitive flexion/extension exercise. In order to verify the grasping characteristics of the soft glove for irregular objects, experiments were carried out. The experimental results showed that the bionic soft glove was dexterous in grasping, which conforms to the universal grasping characteristics of human hands, has the function of assisting daily life (ADL), and meets the requirements of rehabilitation.

Water-in-oil droplet generation for object encapsulation is of increasing importance in biochemical reaction, drug diagnostics, and environmental science. Optofluidic technique is a powerful tool for manipulating mesoscopic particles and droplets within a continuous liquid phase. Here, we report a flexible and miniaturized droplet generator based on a microvortex chip by light-heat energy conversion to fuse, trap, and release picoliter aqueous droplets in the immiscible carrier oil. The droplet sizes in the generators can be tuned by the flow rate of the vortices. Further, it is demonstrated that the generated droplet can realize size-selective encapsulation of micro-matters with tunable rotating trajectories. The results showed that the microvortex-based droplet generator propose a method for the stable fusion and encapsulation of droplet with controllable positions and volumes. This system will provide a controllable microfluidic environment for droplet tweezers, micro-reactors, micro-mixers, and object encapsulation in practical applications.

Rescue work after a coal mine accident is fraught with challenges and dangers. Considering the safety of rescue workers and the urgency of a rescue mission, it is necessary to use coal mine rescue robots to perform the tasks of environmental detection and rescue. As a key part of the robot sensing system, a visual sensor can provide much information about a scene. Among vision sensor types, binocular vision has the advantages of being noncontact and passive, and it is the key technology for a robot to acquire obstacle information and reconstruct a three-dimensional scene. Therefore, coal mine rescue robots based on binocular vision have become a popular research topic in the field of mine safety. First, the research status of camera calibration and stereo vision matching for binocular vision is systematically introduced in this paper. Second, the latest research progress on coal mine rescue robots based on binocular vision is reviewed from the perspective of technological applications and development. Finally, the technical challenges and future development trends of binocular vision in coal mine rescue robots are described.

Coal mills have a significant influence on the reliability, efficiency, and safe operation of a coal-fired power plant. Coal blockage is one of the main reasons for coal mill malfunction. It is highly essential to accurately detect the critical blockage in coal mills to ensure a safe and stable operation of the unit. Taking advantage of unsupervised learning methods and historical process data from distributed control systems (DCS), a stacked denoising autoencoder (SDAE) network–based approach for monitoring critical blockage in a coal mill is proposed in this work. The SDAE model with optimized parameters is applied to reconstruct the operating data during normal operating conditions. The intrinsic relationship between all input variables was captured by training a multilayer network model. The monitoring indicator was obtained from the reconstruction errors, and the threshold for monitoring indicators was obtained using kernel density estimation (KDE) during normal operation. The proposed network is independent of fault data, requires a reduced on-line calculation, and demonstrates a better real-time performance compared to conventional methods. The abnormal variables analysis may provide a theoretical evidence for critical blockage. The effectiveness of the proposed method is validated using operating data collected from an actual coal-fired power plant in China. The results demonstrated that the proposed method can effectively detect critical blockage in a coal mill and issue a timely warning, which allows operators to detect potential faults.

In this paper, we propose a novel strategy for human-robot impedance mapping to realize an effective execution of human-robot collaboration. The endpoint stiffness of the human arm impedance is estimated according to the configurations of the human arm and the muscle activation levels of the upper arm. Inspired by the human adaptability in collaboration, a smooth stiffness mapping between the human arm endpoint and the robot arm joint is developed to inherit the human arm characteristics. The estimation of stiffness term is generalized to full impedance by additionally considering the damping and mass terms. Once the human arm impedance estimation is completed, a Linear Quadratic Regulator is employed for the calculation of the corresponding robot arm admittance model to match the estimated impedance parameters of the human arm. Under the variable admittance control, robot arm is governed to be complaint to the human arm impedance and the interaction force exerted by the human arm endpoint, thus the relatively optimal collaboration can be achieved. The radial basis function neural network is employed to compensate for the unknown dynamics to guarantee the performance of the controller. Comparative experiments have been conducted to verify the validity of the proposed technique.

In order to study the effect of stress/plastic deformation on electrical conductivity of various magnetic materials, the electrical conductivity of silicon steel, carbon steel and aluminum alloy of different resistance coefficients at the stage of elasticity deformation and plastic deformation were studied by measuring the resistance, fitting-models were established through theorization and measuring data, and corresponding parameters are given. The results show that: 1 At the stage of elasticity deformation, the electrical conductivity of the material increases rapidly first, and then slowly increases with the increase of stress. 2 At the stage of plastic deformation under stress unloading conditions, the electronic conductivity decreases approximately linearly with the increase of plastic deformation. 3 At the stage of plastic deformation under stress loading conditions, the electronic conductivity decreases approximately linearly with the increase of plastic deformation. As the result of stress, electrical conductivity in the superposition state is higher than that in the corresponding plastic deformation state.

Microwave directional heating can rapidly increase the temperature of coal and promote the desorption of coalbed methane. The temperature field of coal subjected to microwave directional heating was simulated by using COMSOL software. By coupling the energy conservation equation for an electromagnetic field with the heat conduction equation for solids, a heat conduction equation for the microwave directional heating of coal was established. The effects of the microwave heating time, power, frequency, incident distance and cross-sectional area of the waveguide on the temperature field of coal were studied via simulation. The results revealed that the increasing rate of temperature was high in the early stages of microwave heating. Moreover, higher microwave power corresponded to a higher coal sample temperature, a larger temperature gradient for the coal sample, and less energy being required to achieve the desired coal sample temperature. Additionally, it was found that there is an optimal microwave frequency that maximises the temperature of the coal sample. A larger microwave incident distance resulted in a lower average coal sample temperature. The waveguide was also found to have an optimal cross-sectional area that maximises the maximum temperature of the coal sample.

Due to manufacturing errors and material deteriorations in the metal rubber of clamps, the clamp stiffness of the pipeline is uncertain. This paper presents a non-intrusive multi-dimensional Chebyshev polynomial approximation method (M-CPAM) to evaluate uncertain characteristics of the frequency response function (FRF) of the clamp-pipeline system (CPS), where the clamp stiffness parameters are taken as unknown but bounded interval variables. Firstly, a finite element model of the clamp-pipeline system is established. Secondly, the variance-based global sensitivity analysis is implemented to determine significant stiffness parameters. Then, the uncertain intervals of the clamp stiffness are measured by experiments and the dispersion of the clamp stiffness is described. Finally, based on the measured stiffness interval, the uncertain frequency responses of the CPS under different tightening torques are analyzed by the proposed M-CPAM, and the effectiveness of simulation results is verified by experiments. Compared with the results obtained from the Monte Carlo simulation, the experimental measurements, and the polynomial chaos expansion, the proposed M-CPAM provides a more accurate, time-saving and practical method for solving the uncertain frequency responses of the CPS with interval stiffness variables. The results show that the clamp stiffness has great dispersion under the same tightening torque. A frequency shift phenomenon will be observed when the clamp stiffness is uncertain. Moreover, the dispersion of the frequency response of the CPS tends to be concentrated with the increase of the tightening torques.

Nuclear Magnetic Resonance (NMR) detection is a non-destructive testing method that can be used to detect the aging state of organic materials. A unilateral NMR sensor is used in this study to detect the aging state of the corona aging samples of silicone rubber materials after 100-hour's corona aging under different humidity. At the same time, a comparative analysis is made between the NMR results and the conventional methods results such as Fourier Transform Infrared Spectroscopy (FTIR) and static contact angle test. The results show that with the effect of corona discharge, the polymer structure of the silicone rubber materials change to a certain extent. These changes are shown as the effective transverse relaxation time $T_{\mathrm {2eff}}$ of aged sample decreases in the NMR detection. The results of NMR and FTIR both show that the molecular crosslinking density of silicon rubber materials increases, and the activity of the H-containing group decreases. With the increase of relative ambient humidity, $\Delta T_{\mathrm {2eff}}$ gradually increase, and it means the corona aging state is becoming much severer. The results of NMR are consistent with the results of FTIR and contact angle tests. The $T_{\mathrm {2eff}}$ of the same sample tested at different time does not have significantly changes. This indicates that the NMR characteristic of silicon rubber materials after corona are irreversible. The NMR method can test the permanent damage of silicon rubber materials caused by corona. Compared with the static contact angle test, the NMR method can analyze silicon rubber materials from the molecular structure level, and it has good portability and orientation. Meantime, NMR method can achieve a non-destructive aging state detection. Hence the NMR method will provide reference for the operation and maintenance of the silicone rubber composite insulator.

When a dual-arm robot clamps a rigid object in an environment for human beings, the environment or the collaborating human will impose incidental disturbance on the operated object or the robot arm, leading to clamping failure, damaging the robot even hurting the human. This research proposes a prioritized hierarchical compliance control to simultaneously deal with the two types of disturbances in the dual-arm robot clamping. First, we use hierarchical quadratic programming (HQP) to solve the robot inverse kinematics under the joint constraints and prioritize the compliance for the disturbance on the object over that on the robot arm. Second, we estimate the disturbance forces throughout the momentum observer with the F/T sensors and adopt admittance control to realize the compliances. Finally, we perform the verify experiments on a 14-DOF position-controlled dual-arm robot WalkerX, clamping a rigid object stably while realizing the compliance against the disturbances., 7 pages, 7 figures, accepted by IEEE ROBIO 2021

This paper investigates the influence of nano sized alumina trihydrate and fumed silica fillers on suppressing the DC erosion of hybrid silicone rubber composites containing micron-sized alumina trihydrate filler. Fumed silica was found to be more influential on enhancing the thermal conductivity of the composites compared to nano alumina trihydrate, which is possibly a result of the better filler dispersion of the former. Thermogravimetric analysis suggests the effectiveness of fumed silica in suppressing depolymerization of silicone rubber as a result of silica's favourable interaction with the silicone polymer. Furthermore, the thermal analyses outcomes indicate a significant absorbed moisture content in nano alumina trihydrate which could have adversely impacting the residue characteristics and poorly suppressed silicone rubber depolymerization. In addition, a high temperature endotherm for micro sized alumina trihydrate filler was found indicating the possible decomposition of boehmite to release water molecules promoting the internal oxidation of silicone rubber at high temperature. Outcomes of the +DC inclined plane tracking erosion test correlate with those of the thermal analyses indicating a more influential role for fumed silica's interface in enhancing the DC erosion performance of silicone rubber despite the silica hybrid composite having a lower thermal conductivity than micro alumina trihydrate filled silicone rubber., 2021 IEEE Electrical Insulation Conference (EIC), June 7-28, 2021, Denver, Colorado [Virtual Event]

Magnetorheological fluid is a type of smart material whose viscosity changes quickly when exposed to an external magnetic field. This paper focuses on the optimized design of a miniature magnetorheological valve integrated into a novel smart shoe-sole that can dynamically redistribute plantar pressure on the foot of diabetic patients by leveraging this specific characteristic. The primary design goals are to maximize pressure drop (>= 400 kPa) while reducing volume. Analytical equations and finite element analysis are used to calculate the results. To evaluate the trade-off between distinct physical responses, a response surface method-based multi-objective optimization is used. To prepare for future validation, a test bench has been created.

Crimes committed against women are continuously increasing. Most of the crimes are committed when the woman is outside her residence and alone. In this paper an attempt has been made to develop a smart shoe to stop these atrocities against women. The Smart shoe consists of a force sensor placed in each shoe. On tapping the backside of the left shoe together with the left side of the right shoe, if the threshold is crossed by both the force sensors, an SOS message will be sent to the pre-saved contacts with the location coordinates every 30 seconds. To decrease the scope of error two sensors instead of one is used. The device will only be triggered if the threshold is crossed by both the sensors. Due to the position of the sensors the device gives accurate results in all the terrains. Thus resulting in no false alarm. Shoes were tested on level ground and on inclined ascent by two volunteers. Efficiency of the shoes designed is validated with the experimental results. The result obtained clearly shows that the device is highly accurate and only activated under certain parameters. If a woman is accompanied by a device which will alert her contacts if she is in distress, she will certainly feel safer and more confident.

In this study we present a microfluidic device as an electrochemical biosensor with a role for detecting fungal skin/tissue infections. This biosensor, made by colloidal aqueous solution of rhodamine Rh6G - gold nanoparticles (AuNP) functionalized with bovine serum albumin (BSA) with applications in selective detection and identification of infections in the human body.The interaction between the prepared Rh6G-Au NPs and BSA samples were characterized morphologically with Scanning Electron Microscopy-SEM, electrically and by optical florescence microscopy. Gold nanoparticles (AuNPs) have been used as carriers of Rh6G and BSA in order to obtain an amplification of the electrical signal in the biosensor with the role of detecting tissue infections and also in transporting drugs to the affected tissues in the body. Furthermore, we used also COMSOL software to enables the simulation of realized designs for the associated fluidic microchannel, an important component part of the biosensor. We hope by improving and developing the propsed model to progress in the area of clinical diagnostics and to answer some challenges about protein with high binding affinity and highest energy acceptance efficiency

We show the design, fabrication, and characterization of a wedge-shape Au thin film for integrating multiple surface plasmon resonance transducers in a single chip, which enhances the figure-of-merit by the reflectivity change with an attenuated-total-reflection setup upon modulating the wavenumber of surface plasmon polariton with the thickness of Au.

We fabricated a planar lightwave circuit consisting of non-doped silica and fluorine-doped silica and demonstrated that a waveguide with a non-doped silica core is effective to suppress the photoinduced degradation which increases the propagation loss and changes the refractive index due to the high-power blue light incident.

This study ascertains the emotion perception of different gender consumers towards service robots with different degrees of anthropomorphic appearance in spaces for consumption. Differences between male and female consumers with regard to pleasure are examined through an experiment using robots with different degrees of anthropomorphic appearance in spaces for consumption. Results will provide a basis for the design of service robots. The 161 subjects between the ages of 20 and 50 first read a short passage on consumption behavior, and then they view pictures of robots with different degrees of anthropomorphic appearance. They then fill out a questionnaire on their perception of the role played by the robot in the scenario. Research results indicate that robots with higher degree of anthropomorphic appearance generated more pleasure among male subjects than female subjects, i.e. men prefer more human-like robots compared with women in spaces for consumption. Based on the results of this study, in spaces mainly for male consumers, robots should be designed with higher degree of anthropomorphic appearance; in spaces mainly for female consumers, robots can be designed with either high or low degree of anthropomorphic appearance.

In this study, three kinds of underfill materials were used to investigate the enhancement of silane coupling agents on the adhesive strength of the underfill and the silicon substrate undergoing boiling water soaking. Adhesion properties between the underfill and the silicon were evaluated by shearing test. The fracture interfaces of the shearing tests are observed by SEM. The results show that the adhesive strength between the silicon and the underfill decreases significantly without silanes, and the bonding between the resin and the filler becomes loose by hydrothermal aging. Underfill containing aminosilane has higher water resistance, which can improve the adhesive strength of underfill, and can help to strengthen the bonding between underfill and filler after hydrothermal aging.

Ensuring that there is no oxidation on the surface of the nano-copper particles is an important task to make sure the subsequent sintering performance. In order to reduce the surface oxidation of nano-copper particles, this research mainly studies the benzotriazole (BTAH) coating. Corresponding XRD, TEM and XPS test results show that after BTAH treatment, the oxidation degree of copper particles decreases. At the same time, organics related to BTAH is detected on the surface of the treated copper particles. This fully shows that the BTAH coating can effectively prevent the surface oxidation of copper nanoparticles, which lays a good foundation for further sintering experiments.

Light-Emitting Diode (LED) has been widely used in various fields owing to their outstanding properties, such as high efficiency, long service life, diverse colors and environmental friendliness. With the rapid development of LED, the requirements of materials for LED encapsulation are getting higher and higher. Currently, silicone resins are widely used for LED encapsulation because of their unique performance. However, in the process of application, silicone resins suffer from aging due to the thermal produced by LED. In this paper, through analyzing the characteristics in aging based on a failure case, the aging mechanism of silicone materials for LED encapsulation is studied. After thermal aging, silicone packaging materials become hard and brittle, leading to the cracking. Furthermore, the proportion of silicon near the crack increases obviously. In the FT-IR spectra, there is an obvious carbonyl absorption peak near 1720cm-1. In TGA, silicone packaging materials degrade in advance, and the residual mass increase eventually. In DSC, there is an obvious endothermic peak during the first heating process. The fundamental causes of above characteristics can be attributed to the degradation of main chain and the oxidation of side chain.

Traditional planar microelectrode arrays (MEAs) have contributed significantly to broaden our knowledge on neuronal electrophysiological signaling by enabling simultaneous recording and stimulation of intracellular activities. However, planar MEAs are not suitable for investigating the electrophysiological behavior of complex 3D neuronal cultures. To exploit the potential of these 3D cultures, more advanced tools are needed which can assess the network-wide electrophysiological activity of neurons in 3D space. In this work, we propose a novel approach to develop a multi-level 3D microstructured array built on a well-established planer MEA setup. Initially, a planer MEA is realized using standard photolithography and physical vapor deposition (PVD) technique. During fabrication of the planer MEA, circuitry is added to connect the planar microelectrodes separately into individual groups. In addition to it, an electroplating process is utilized to grow gold micro-pillars on the planar electrode pads using a chemically amplified negative photoresist (KMPR 1050) from Kayaku Microchem as the mold. The circuitry allows independent control of the heights of the individual groups of 3D multi-level gold microelectrodes on the array. The mold is then stripped off. The microelectrodes can be insulated with Parylene-C and crowned with spherical gold beads using the ball bonding technique. The spherical gold beads could act as the interface between the device and the neuronal culture. The spherical shape of the bead would allow omnidirectional growth of neuronal networks, better mimicking the in vivo growth patterns. Experiment work to record and stimulate the electrophysiological activities of neuronal networks is ongoing. All fabrication techniques utilized in this approach are well established, allowing the fabricated devices to be reproducible, cost-effective, and scalable.

The main parameters of glow discharge burning mode that affect the heating process of welded parts during diffusion welding are described in this work. The main control actions and their influence on the thermal energy characteristics of thenormal DC glow discharge are determined. It was established that the main control actions that characterize the mode of the heating and welding processess by the glow discharge are the discharge current (I d ), which determines the total power released in the discharge gap, and the gas pressure (P), which changes the specific energy characteristics of the discharge. The technical means of control of the glow discharge main parameters (I d , P) during diffusion welding have been developed, which provide the regulation of the discharge current within 1…10 A and gas pressures in the discharge chamber from 1.33 to 13.3 kPa.

Cold Atmospheric pressure Plasma (CAP) has the ability to both inactivate and remove bacterial biofilms from wounds and surfaces. Planar CAP arrays 1 (2.4 x 2 cm) have been developed using linear discharge elements (2.4 cm long), operating with a 0.75 mm gap at 0.5-2 kV, 20 kHz AC. The elements are fabricated using Low Temperature Co-fired Ceramic (LTCC). Hydrated argon gas flows (1-5 slm) between two plates to create the discharge element. Each discharge element draws 0.5 – 1.5 mA depending upon operating conditions. The elements are stacked together to form the arrays. Measurements of reactive oxygen species have shown generation of peroxide and hydroxyl radicals which increase linearly with plasma exposure times from the arrays. Measurements of the Colony Forming Units (CFUs) shown >99% reduction in

Capacitively-coupled plasmas (CCP's) are widely used at low pressures for thin film etching on silicon substrates and, at higher pressures, for film deposition on silicon and very large glass substrates. These applications require extreme processing uniformity. At higher driving frequency and/or larger area, the radial wavelengths of the propagating surface waves in the plasma can become comparable to the substrate or reactor size, leading to standing wave effects and center-high plasma non-uniformities.

Epoxy resin is widely used in insulating mediums in power system for their excellent electrical and mechanical properties. The improvement of the surface hydrophobicity of epoxy resin is key important to further enhance the insulating performance of epoxy resin. In this paper, the super-hydrophobic film is deposited on the surface of epoxy resin by a one dimensional Ar jet array driven by nanosecond pulse with hexamethyldisiloxane (HMDSO) addition. The influences of the plasma treatment time and the HMDSO content ratio on discharge characteristic and surface hydrophobicity of the deposited film are investigated by electrical and optical diagnoses, and surface physical and chemical measurements. With the optimized experimental conditions (60 s plasma treatment with 0.04 % HMDSO), the surface of the treated epoxy is found to be covered with dense coral like nano-particles with the scanning electron microscope (SEM) measurement. The Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analyze the chemical changes of the surface of epoxy resin. And it is found that the original C=O, C-H and other organic functional groups were replaced by Si-O-Si, Si-(CH 3 ) and other Silicon-containing functional groups and the element ratio of Si was increased from 0.4% to 28.0%. The water contact angle increased from 60.3° of the untreated surface to 150.0° after plasma treated.

Breast anatomical structures are distributed layer by layer in breast ultrasound (BUS) images. Breast anatomy decomposition (BRAND) has several clinical potentials in providing localization constraints for breast lesion detection and supporting multimodal registration. To take advantage of convolutional neural network (CNN) and reduce the requirements of manual labels, we propose a semi-supervised deep learning method for BRAND. A CNN is first trained on labeled training data. Pseudo labels for unlabeled training data are generated by smoothing the network's predictions with simple linear iterative clustering (SLIC) super-pixel algorithm. The proposed approach achieves Dice similarity coefficient (DSC) of 89.6 ± 9.3%, 88.2 ± 9.7%, 84.6 ± 17.7% and 89.5 ± 21.6% for subcutaneous fat, mammary gland, muscles and thorax layers, respectively, which outperforms the reported results. The proposed approach is demonstrated to be sufficient for BRAND in BUS images both with and without breast lesions.

Social robots are widely applied in various contexts to provide human-like assistance and facilitate service experience. Prior research considered a variety of design features to explore the influences in human-robot relationships, while a robot’s manner of assisting in interaction and its consequent effects are rarely discussed. This study aims to investigate the relationship between a robot’s communication design and a human’s perceived intimacy in the human-humanoid robot interaction. Different levels of service proactivity (proactive vs. reactive) and types of expressive behaviors (neutral vs. intimate) are developed and empirically validated through an online survey. The findings indicate that the manipulations designed for each experimental condition can be recognized by the participants. In addition, the perception of intimacy is significantly affected when interacting with different robots accompanying different types of behaviors.

We demonstrate the impact of the intermediate hydrogen plasma treatment of intrinsic amorphous silicon layer in silicon heterojunction solar cells (SHJ). After deposition of the first layer of intrinsic amorphous hydrogenated silicon with a thickness of 5–6 nm hydrogen plasma treatment allows passivation of defects in the layer and, due to surface hydrogenation, creates conditions for defect-free growth of the next layer to a total thickness of 10 nm. The lifetime of minority charge carriers increases from 2 to 5 ms in comparison with base process. The parameters of hydrogen plasma treatment are determined, which makes it possible to increase the surface passivation quality by the layers of intrinsic hydrogenated amorphous silicon in the production of high-efficiency solar cells. The process is useful for fabrication of high performance SHJ solar cells.

The blast furnace is a metallurgical reactor that works at high temperature and pressure to obtain cast iron. The process it done by reactions and heat transfer between the solids, presents on the descendent burden (Iron ore, pellets, fluxes and coke) and ascendant reducing gases, generated by the burn of fuels (coke and pulverized coal) in the low part of the reactor. These reactions result in hot metal, slag, blast furnace gas and other by products. The motivation for this role is the successful application of artificial neural networks in blast furnaces. The mathematical modeling accomplished in MATLAB R2020b used 17 input variables and 8 output variables, to develop a neural network to predict the production and quality control of hot metal in a blast furnace using a layer of 25 neurons.

This work presents a comparative analysis of the chemical and phase composition, current efficiency, and microhardness of binary and ternary electrolytic CoRe and CoWRe alloys, deposited from two types of electrolytes: acidic citrate and alkaline citrate-pyrophosphate ones. It has been shown that the use of electrolytes of various complexes compositions makes it possible to vary the amount of rhenium in the coatings over a wide range (12 – 59 at.%). Ternary CoWRe alloys contain 4 – 9 at.% of tungsten, and they are deposited with higher current efficiency (up to 86%) than binary alloys. By selecting the composition of the electrolyte and the electrolysis mode, it is possible to regulate not only the chemical composition but also the structure of the coatings and to obtain X-ray amorphous or crystalline alloys, depending on the task.

The article considers the effect of modification of commercial material P25-TiO 2 with yttrium oxide and the effect of the modifier nature on the photocatalytic activity towards ciprofloxacin. TiO 2 modification with yttrium oxide enhances the degree of antibiotic degradation. Increase in modifier content affects the photoactivity of TiO 2 ambiguously: when yttrium chloride is used as a precursor, photoactivity increases; when yttrium nitrate is used – photoactivity decreases. Additional use of an oxidant (H 2 O 2 ) significantly increases (more than 2 times) efficiency of the photocatalytic process. It has been found that at low concentrations of antibiotic aqueous solution (up to $10\ \mathrm{mg/dm^{3}}$), its photodegradation over TiO 2 modified with yttrium oxide reaches 100%. However, in case of high concentrations of ciprofloxacin (up to $50\ \mathrm{mg/dm^{3}}$), complete degradation of the antibiotic is observed only when the combination of TiO 2 modified with yttrium oxide and oxidant H 2 O 2 is utilized in the photocatalytic process.

Oral interventional surgery robots can assist doctors to remotely control mobile phones to perform surgery, reduce radiation hazards, improve surgery accuracy, and shorten surgery time. It has become a research focus of medical robots. This article introduces the positioning system of dental implant interventional surgery robot designed by domestic and foreign research institutions in recent years. Analyze key positioning technologies such as mobile phone equipment, electromagnetic navigation, mechanical navigation, ultrasonic navigation, and optical navigation in the oral interventional surgery robot, clarify the significance of this technology in the oral interventional surgery robot system, and discuss the development trend of key technologies Finally, it lists the future research directions of the oral intervention surgery robot positioning system. This article can enable researchers to understand the structure of the positioning system of the oral interventional surgery robot, grasp the development status of key technologies, and provide references for future research directions.

Hollowing disease is one of the most common diseases of open stone relics. It is very important to timely evaluate and monitor the hollowing disease to prevent further deterioration. The hollowing disease of Yungang Grottoes were detected and studied using terahertz and infrared technology, combined with spectral processing methods in this paper. The results showed that the method can not only effectively detect and locate the hollowing disease, but also quantitative evaluate the degree of the hollowing disease with high precision. This technology can provide effective data support for the restoration and protection of stone relics.

Terahertz nondestructive testing is carried out for the inclusion defects of rubber materials, and the waveform features of the inclusion defects are extracted. Different wave features are used to image the inclusion defects of rubber materials, and the imaging quality is compared. The best imaging method of different inclusion defects is analyzed from the perspective of defect recognition rate.

Cord reinforcement framework can effectively improve the rubber performance. The absence of cord may lead to potential safety hazard. In this paper, we successfully demonstrate the detection of cord reinforcement framework absence in rubber through comparison analysis the terahertz (THz) images with and without rubber inner cord. This work provides a solution for the rapid nondestructive detection of the missing of rubber inner cord reinforcement framework. Future work assisted by artificial intelligence enabled technology, we believe the intelligent THz imaging will provide better solution for rapid and nondestructive detection of rubber internal defects and other disruptive applications.

With the aim of serving the shipping transportation enterprise, the crew training institution and the government administration department, the Chinese vessel crew boom index model is developed to monitor the daily transportation, crew teaching and management, study the vessel crew market, evaluate the shipping policy. The vessel crew index system consists of the vessel crew index itself and five sub-index: the vessel crew requirement, the vessel crew examination, the vessel crew certificate issue, the vessel crew valid certificate, the vessel crew serving time. With the data experiment, the Chinese vessel crew boom index model is proved to be able to reflect the running status and developing trend of Chinese vessel crew market efficiently. And the model can also be an important tool for decision making for the maritime department and other vessel crew market related subjects.

Coronavirus caused pandemics as many viruses did through human history. The current pandemic causes overwhelmed healthcare system, locked down cities, and massive fatality among humans. Thus, different robots have been used since the COVID outbreak worldwide to reduce spreading infectious diseases and support frontline healthcare workers. This paper sets out the different robots implemented for hospital, non-hospital use, and possible use that can be deployed amidst the pandemic. A literature survey of versatile robots during COVID-19 is introduced. Roboticists contributed with wheeled and drone robots with various applications to assist medical care systems and society during the ongoing crisis. Pandemics are common throughout human history and difficult to avoid or prevent; thus, we intend to encourage societies, academia, engineers and innovators to invest more in robots that cannot catch the virus and consequently introduce beneficial solutions to fight such pandemic in the future.

International audience; In the manufacturing of hot water tanks, welding quality evaluation and fault detection is a critical operation that is still frequently conducted visually or with the help of none destructive tests, which can generate a high consumption of time and resources. To overcome this problem, many methods have been proposed for defect detection based on the classification of the welding signals. However, most of the proposed methods do not consider the problems of defect localization and the generalization from small sample size. Moreover, studies on the interactions between welding signals seem to be absent in the literature despite its importance in the formulation of the defect detection problem. In this paper, we aim to address these gaps by presenting a study on the causalities between welding signals in the circular welding of hot water tanks. Based on the findings from the causality study, we propose a method that detects and localize welding defect with high accuracy and handles the problem of small sample size. Furthermore, we present a study on the defects root cause and show the possibility of early defect prediction.

In the era of Industry 4.0, the vast development of Smart Factory is always followed by the advancement of Deep Learning technology. To avoid the smart factory system from unwanted losses because of defects in its output production in the steel factory, defect classification on steel sheets based on Deep Learning should be developed precisely. This paper explains how the Deep Learning technique was used to implement defect detection in a smart factory. For this study, we used an open dataset of steel defects. The result of the Deep Learning method for the defect detection system generates 96% accuracy, 0.95 recall, and a precision of 0.97 on the training process. This research goal may contribute to enhancing efficiency and cost reduction in the smart steel factory environment.

The constant stiffness of the soft medical robots imposes a cap on their force transmission capacity. To address this limitation, the objective of this study was to investigate the effects of chamber pressure on the stiffness of pneumatic soft robots. To this end, a single-chamber pneumatic soft robot was designed and fabricated. Afterward, a mechanistic model of the robot under external force and chamber pressure was developed. The model was solved as an initial value problem with homogeneous Neumann and Dirichlet boundary conditions. Comparison of the theoretical findings with experimental results for tip displacement and stiffness showed similar trends with a maximum error of 8.7%. The findings confirmed the feasibility of stiffness adaptation through chamber pressure regulation.

In this paper, we propose a method for automatically detecting sweat droplets from images taken by replicas of the silicone skin surface created by the Impression Mold Technique (IMT) to evaluate sweating responses to thermal stimulus in atopic dermatitis. The proposed method is a U-Net based image segmentation using deep learning. From experimental results, we succeeded in obtaining a result close to the expert’s manual identification result of sweat droplets.

Due to the recent lifestyle changes, instances of people eating alone have been increasing. We think robots can be good meal partners without having to risk disease transmission. Furthermore, people are able to eat with robots without worrying about mealtimes. In this study, we determine who are more likely to accept robots as eating partners and compare eating with a single robot to eating with multiple robots. The results revealed that people who have vast experience in interacting with robots and those who have relatively few opportunities to eat alone felt better about eating with robots, whereas those who have numerous opportunities to eat alone enjoyed eating with multiple robots.

In this paper, an intravascular robotic teleoperation system (IRTS) has proposed to reduce the physical stress and xray exposure to surgeons during vascular interventional surgery (VIS), reducing the probability of occupational diseases. The system, through its ergonomic design, allows the surgeon to bring the experience to robot-assisted VIS. For this reason, a master haptic module based on magnetorheological (MR) fluid technology was designed to provide fast and accurate haptic feedback while capturing the surgeon's hand movements (radial and axial direction) in operating the catheter. In the slave side, the catheter manipulator is designed to mimic the surgeon's action at the main end, with a novel grasper designed to provide sufficient clamping force while protecting the catheter surface from damage. At the same time, the contact force between the catheter and the patient's vessels can be measured by the motor current loss-speed-resistance model, which has less impact on surgery and a more accurate way to measure force. Compared with traditional VIS, the IRTS not only achieves the same results, but also reduces the cognitive workload of the operation and further improves the transparency and safety of the VIS.

In this paper, we report that how much the presence of a robot increases the rate of valid responses in a questionnaire survey. We conducted a field trial in a university campus based on a single-case design method that is used in applied behavior analysis. We made two conditions: One was a condition that a robot interacting with people was installed (robot condition), and another was a condition that the robot was not installed (no-robot condition). We measured once a day for eight days, each day lasting 125 minutes from 11:25 to 13:30. The robot condition and the no-robot condition were assigned alternately to each day. The robot was controlled by an operator. The results showed that the valid response rates of the robot condition were 8.9%, 3.8%, 6.1%, and 1.9%, and those of the no-robot condition were 4.9%, 3.7%, 3.1%, and 1.8%. Considering both these results and complete answer rates, we found that although a robot can attract people’s attention and increase the response rates a little and short-term, the valid response rates do not increase so much as we expect because people who are attracted by the robot are likely to quit answering the questionnaire halfway. In order to increase the valid response rates, we will need to consider a new interaction design for preventing people from quitting their answer.

For post-stroke patient, the interaction force between the impaired limb and the rehabilitation robotic system is an important issue for patient safety in clinical treatment. The compliance control scheme can be achieved by the rehabilitation robotics with variable stiffness actuator (VSA) for the safe physical human robot interaction. The output stiffness would be adjusted independently via variable stiffness actuator during the rehabilitation training processing. In addition, when the stiffness changing, the different impedance characteristic can be realized according to the environmental applied force. The compliance control of VSA can be utilized into the rehabilitation application scenario for improving the training safety. In this paper, a performance-based stiffness control strategy for maximum the rehabilitation effect and increasing the patient participant was proposed utilizing the compliance characteristic of VSA. The elbow joint output stiffness would be regulated according the patient's training performance which will be determined using the real-time position tracking error. It is noted that the training performance should be different to adapt the patient individual-specific. Therefore, an acceptable position tracking error range should be set in advance for the suitable training plan. The experimental results show that the proposed method can adjust the elbow joint stiffness for patients according to the real-time training performance.

This paper proposes a modeling method for a robotic fish with elastic tail, which is driven by a motor in head and uses a spring steel sheet as a passive flexible joint, followed by a rigid caudal fin. The pseudo-rigid-body model (PRBM) is firstly used to analyze the flexible joint, then the fluid force acting on the robotic fish is divided into the pressure on links and cross-sectional resistance. Further, a dynamic model is established by the Lagrangian dynamic method to solve the movement of the robotic fish. And the model is utilized to investigate the influence of joint stiffness on propulsion performance. For different frequencies, the optimal joint stiffness is calculated to maximize the swimming speed. These optimized speeds are all higher than using rigid joints, and a maximum speed increase of 0.33 body length per second is reached at the largest simulation frequency 10Hz. In addition, the swimming speed can be maximized at the same input power by adjusting the stiffness of the joint. These findings prove the effectiveness of passive flexible joints in optimizing the performance of the robot fish.

Aircraft servicing or Maintenance is a critical environment that must be given due consideration because it is directly related to passenger safety. As a consequence, maintenance operations are crucial in assessing the aircraft’s fitness. Since any aircraft’s structural failure can result in fatalities, vehicle health management is critical in the aviation industry to prevent and detect structural damage at an early stage. This study examines the literature on how prognostics have been used to improve the Maintenance of aircraft and discusses the study limitations for improving aircraft maintenance in the commercial aviation industry. Moreover, it highlights the state of the art in the application of prognostics to enhance maintenance of aircraft is then double-checked, possible opportunities and issues are explained and investigated. Additionally, it shad alight on the big prospect of the Methodologies and Techniques for Predicting Remaining Useful Life and future directions for further research.