The aim of this work is to propose an angular positioning solution for the round cutting insert of an indexable insert torus milling cutter, dedicated to the multi-axis milling process under HSM conditions. The solution was based on the development of a wear model using a nonlinear estimation method with an eigenfunction, the development of a tool life model taking into account parameter of the cutter blade working angle and the method of reference marking and insert mounting, as well as the measurement methodology. The own function adopted to approximate the wear of the tool over its useful life is adequate and provides a prediction accuracy of 90%. The developed procedure for angular positioning and measurement enables the entire cutting edge of the cutting blade to be fully used, so that the total lifespan of the tool as an indexable insert tool is significantly extended. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the insert indicate the location of “notching” type wear.

In wheeled vehicles, there exists a challenge concerning the alignment of the front wheels during turns. When both wheels are turned to the same extent, the inner wheel experiences lateral slippage on the road surface, resulting in reduced steering efficiency. Such problems can be solved by using the Ackermann principle. There are two approaches: through the steering mechanism or by employing autonomous wheel control. From a technical standpoint, it is achievable to synthesize a steering mechanism that fulfills the Ackermann condition, ensuring as accurately as possible for any given turning radius. This research paper focuses on synthesizing a steering mechanism, specifically a two-circuit linkage that links the left and right wheels. The structure and kinematics of this mechanism are being investigated. Following the principles of Ackermann, an objective function for the kinematic synthesis of the mechanism has been formulated. The synthesis process of the mechanism is conducted using the analytical method of interpolation in four parameters. A dedicated method has been developed, and kinematic analysis of the mechanism using the synthesized parameters has been performed. The simulation results have demonstrated high accuracy in achieving the desired implementation of the Ackermann condition.

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are significant lightweight metal matrix composites extensively utilized in precision instruments and aerospace sectors. Nevertheless, the inclusion of rigid SiC particles exacerbates tool wear in mechanical machining, resulting in a decline in the quality of surface finish. This work undertakes a comprehensive investigation into the problem of tool wear in SiCp/Al composite materials throughout the machining process. Initially, a comprehensive investigation was conducted to analyze the effects of cutting velocity vc, feed per tooth fz, milling depth ap, and milling width ae on tool wear during high-speed milling under SCCO2-MQL (Supercritical Carbon Dioxide Minimum Quantity Lubrication) ultrasonic vibration conditions. Furthermore, a prediction model for tool wear was developed by employing the orthogonal test method and multiple linear regression. The model's relevance and accuracy were confirmed using F-tests and t-tests. Ultimately, through the utilization of a genetic algorithm, the milling parameters were optimized, resulting in the identification of the most optimal combination of parameters. Empirical findings suggest that the careful selection of milling parameters can significantly mitigate tool wear, extend the lifespan of the tool, and enhance the quality of the surface. This work serves as a significant point of reference for the processing of SiCp/Al composite materials.

This paper presents three approaches to estimating battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS); these approaches are referred to as (a) least squares (LS), (b) exhaustive search (ES), and (c) nonlinear least squares (NLS). The ES approach is assisted with the LS method for the rough determination of the lower and upper bound of the ECM parameters, and the NLS approach is incorporated with the Monte Carlo run such that different initial guesses can be assigned to improve the goodness of EIS fitting. The proposed approaches are validated using both simulated and real EIS data. Compared to LS approach, the ES and NLS approaches show better fitting accuracy at various noise levels; whereas both in the validation using simulated EIS data and actual EIS data collected from LG 18650 and Molicel 21700 batteries, the NLS approach shows better fitting accuracy than that of LS and ES approaches. In all cases, compared with the ES approach, the computational time of the NLS approach is significantly faster, and compared with the LS approach, the NLS approach shows a minimal difference in computational time and considerably better fitting performance.

Nowadays, when milling complex parts or curved surfaces, we encounter several problems that must be taken into account in the production process. There are various factors that affect the quality and accuracy of production. The main objective of this paper was to analyze the size of the effective tool diameter when machining a shaped surface with respect to the selected position, namely at the perpendicular position of the tool. At the same time, the distribution of the engagement area on the tool surface was evaluated by extracting the area content and volume data at the point of contact. The experiment was also intended to highlight the importance of the choice of finishing strategy in a CAM system. The results showed that the tool engagement size corresponded to the extracted data describing the area and volume size for each tool position with respect to the curvature of the surface. The negative deviations obtained by the scanning method were due to machining close to the tool centre, which was affected by the changing effective tool diameter.

Coded aperture 3D imaging techniques have been rapidly evolving in the recent years. The two main directions of evolution are in aperture engineering to generate the optimal optical field and in development of computational reconstruction to reconstruct the object’s image from the intensity distribution with a minimal noise. The goal is to find the ideal aperture-reconstruction method pair and if not, to optimize one to match the other for designing an imaging system with required 3D imaging characteristics. Lucy-Richardson-Rosen algorithm (LR²A), a recently developed computational reconstruction method was found to perform better than its predecessors such as matched filter, Weiner filter, phase-only filter, Lucy-Richardson algorithm and non-linear reconstruction (NLR) for certain apertures when the point spread function (PSF) is a real and symmetric function. For other cases of PSF, NLR performed better than the rest of the methods. In this tutorial, LR²A has been presented as a generalized approach for any optical field along with MATLAB codes for reconstruction of any image when the PSF is known. The common problems and pitfalls in using LR²A has been discussed. Simulation and experimental studies for common optical fields such as spherical, Bessel, vortex beams and exotic optical fields such as Airy, scattered and self-rotating beams have been presented. From this study, it can be seen that it is possible to transfer the 3D imaging characteristics from non-imaging type exotic fields to indirect imaging systems faithfully using LR²A. The application of LR²A to medical images such as colonoscopy images and cone beam computed tomography images with synthetic PSF has been demonstrated. We believe that the tutorial will provide a deeper understanding of computational reconstruction using LR²A.

While traditional AC mechanical circuit breakers have been competent for protecting AC circuits, high penetration of DC power distribution technologies like DC microgrids (MGs) obligate better disruption performance features such as quick and reliable switch-ing speeds. However, a DC circuit breaker (DCCB) novel design is challenging due to the need to quickly break high currents within milliseconds, caused by the high fault current rise in DC grids compared to AC grids. In DC grids, the circuit breaker must provide zero current crossing and be designed for absorbing surges since the arc is not naturally extinguished by the system. Additionally, the DC breaker must mitigate the magnetic energy stored in the system inductance and withstand residual over-voltages after current interruption. These challenges require a fundamentally different topology for DCCBs, which are typically made using solid-state semiconductor technology, metal oxide varistors (MOV), and ultra-fast switches. This study aims to provide a comprehensive review on development, design, and performance description of DCCBs in parallel with a specific concentration on analysis of internal topology, energy absorption path and sub-circuits in Solid-State (SS)-based DCCBs. The research explores various novel designs that introduce different structures for energy dissipation solution. The classification of these designs is based on the fundamental principles of surge mitigation and a detailed analysis of the techniques employed in DCCBs. In addition, our framework offers an advantageous reference point for the future evolution of SS-circuit breakers in numerous developing power delivery systems.

Fused deposition modeling (FDM) is widely applied in various fields due to its affordability and ease of use. However, it faces challenges such as achieving high surface quality, precise dimensional tolerance and overcoming anisotropic mechanical properties. This paper analyzes and compare the machinability of 3D printed PLA, PETG and carbon fiber reinforced PETG focusing on surface roughness and burr formation. A design of experiments (DoE) with a full factorial design was used, considering three factors: rotation speed, feed rate and depth of cut. Each factor had different levels: rotational speed at 3000, 5500 and 8000 rpm; feed rate at 400, 600 and 800 mm/min; and depth of cut at 0.2, 0.4, 0.6, and 0.8 mm. Machinability was evaluated by roughness and burr height using a profilometer for all the materials under the same milling conditions. To evaluate the statistical significance of the influence of various processing parameters on surface roughness and burr formation in 3D printed components made of three different materials PLA, PETG and carbon fiber reinforced PETG, an analysis of variance (ANOVA) test was conducted. This analysis investigated whether variations in rotational speed, feed rate and depth of cut resulted in measurable and significant differences in machinability results. Results showed that milling parameters significantly affect roughness and burr formation, with optimal conditions for minimizing any misalignment highlighting the trade-offs in parameter selection. These results provide insights into the post-processing of FDM-printed materials with milling, indicating the need for a balanced approach to parameter selection based on application-specific requirements.

Recently in various theoretical works, path-breaking progress has been made in recovering the well-known Page Curve of an evaporating black hole with Quantum Extremal Islands, proposed to solve the long-standing black hole information loss problem related to the unitarity issue. Motivated by this concept, in this paper, we study cosmological circuit complexity in the presence (or absence) of Quantum Extremal Islands in negative (or positive) Cosmological Constant with radiation in the background of Friedmann-Lemaî tre-Robertson-Walker (FLRW) space-time. Without using any explicit details of any gravity model, we study the behaviour of the circuit complexity function with respect to the dynamical cosmological solution for the scale factors for the above mentioned two situations in FLRW space-time using squeezed state formalism. By studying the cosmological circuit complexity, Out-of-Time Ordered Correlators, and entanglement entropy of the modes of the squeezed state, in different parameter space, we conclude the non-universality of these measures. Their remarkably different features in the different parameter space suggests their dependence on the parameters of the model under consideration.

Drosophila circadian circuit is one of the best described neural circuits but is complex enough to obscure our understanding of how it actually works. Animals’ rhythmic behavior, the seemingly simple outcome of their internal clocks, relies on the interaction of heterogeneous clock neurons that are spread across the brain. Direct observations of their coordinated network interactions can bring us forward in understanding the circuit. The current challenge is to observe activity of each of these neurons over a long span of time –hours to days– in live animals. Here we review the progress in circadian circuit interrogation powered by in vivo calcium imaging.

Force reduction is one of the most important benefit of applying ultrasonic vibration on milling. However, most of studies so far are limited to experimental investigation. In the current study, an analytical predictive model on cutting forces in ultrasonic vibration-assisted milling is proposed. The three types of tool-workpiece criteria are considered based on the instantaneous position and velocity of tool center. Type I criterion indicates that there is no contact if the instantaneous velocity is opposite to tool rotation direction. Type II criterion checks whether the vibration displacement is larger than the instantaneous uncut chip thickness. Type III criterion considers the overlaps between current and previous tool paths due to vibration. If none of these criteria is satisfied, milling forces are nonzero. Then the calculation is performed by transforming milling and tool geometry configuration to orthogonal cutting at each instant. The orthogonal cutting forces are predicted through the exhaustive search of shear angle and calculation of shear flow stress on tool-chip interface. The axial force is then calculated based on tool geometry, and the milling forces in feed, cutting, and axial directions are calculated after coordinate transformation. The proposed predictive force model in ultrasonic vibration-assisted milling is validated through comparison to experimental measurements on Aluminum alloy 2A12. The predicted values are able to match the measured milling forces with high accuracy of average difference of 13.6% in feed direction and 13.8% in cutting direction.

Nickel-based Superalloy Inconel 718 is widely used in the aerospace industry for its excellent high-temperature strength and thermal stability. However, milling Inconel 718 presents challenges due to significantly increased cutting force and vibration, which is a typical difficult-to-machine material. This paper focuses on the milling process of Inconel 718, establishing a milling force model to analyze the force trends under various processing parameters. Finite element analysis is employed to study the stress and temperature fields during milling. Dynamic equations for milling Inconel 718 are developed, and stability lobe diagrams are generated based on modal experiments. Milling experiments on Inconel 718 validate the milling force model and finite element analysis results. The fmincon optimization algorithm is utilized to identify the optimal machining parameters for Inconel 718. Through this research, valuable insights into enhancing the efficiency and quality of Inconel 718 machining are provided. This study contributes to a deeper understanding of Inconel 718 milling behavior, offering crucial guidance for more efficient machining processes.

Memristor has attracted a lot of interest due to its high processing speed, low power consumption and high integration ability, which is critical for electronic systems and memory-centric computing. However, the memristor programming circuit and strategy are still inflexible and complex, since the signal generator/collector and stimulate pulse must be carefully matched and designed based on memristor intrinsic characteristics without reconfigurable. Here, a simple and effective circuit only consists a parallel reference-resistor-and-NMOS is designed to program memristor with a more than 99% memristance precision. And the amplitude and width of stimulate pulse are fixed to ±4V and 5ms, respectively. In order to cope with the device variation, such as ±10% tolerance of transition voltage, an optimized programming strategy was proposed and demonstrated great robustness. Additionally, a set of reference resistors and NMOSs have been added to facilitate multi-level memristance operation without requiring any changes to the circuit structure. This program circuit was also employed to program memristor crossbar remains 99% precision. In the end, a memristor-based convolutional neural network which controlled by our optimized programming circuit was used for image recognition, and 89.36% accuracy can be achieved even under 15.8% memristance tolerance. This novel circuit demonstrates a simple and flexible strategy in memristor programming, providing a new way to control memristor crossbar for practical application.

Huntington's disease (HD) is an inherited neurodegenerative disorder that usually starts during midlife with progressive alterations of motor and cognitive functions. The disease is caused by a CAG repeat expansion within the huntingtin gene leading to severe striatal neurodegeneration. Recent studies conducted on pre-HD children highlight early striatal developmental alterations starting as soon as 6 years old, the earliest age assessed. These findings, in line with data from mouse models of HD, raise the question of when during development do the first disease-related striatal alterations emerge or whether they contribute to the later appearance of the neurodegenerative features of the disease. In this review we will describe the different stages of striatal network development and then discuss recent evidence for its alterations in rodent models of the disease. We argue that a better understanding of the striatum’s development should help in assessing aberrant neurodevelopmental processes linked to the HD mutation.

Several studies have highlighted the importance and evolution of process safety leadership and culture in various industries. However, none has focused on the palm oil milling industry yet. This paper critically reviews the latest developments in the palm oil milling process and unit operations leading to process safety concerns. It also discusses the Principle of 3C that is applied to explain repeat accidents and the four-level safety culture in the palm oil milling industry. For this purpose, the author presents case studies of two key palm oil companies in Malaysia. Overall, this paper offers guidelines to leaders in the palm oil milling industry about the required process safety leadership and culture to be understood in order to improve their safety outcomes.

The implementation of Boolean functions using Nano crossbar- based switching lattices has been suggested as a substitute for conventional CMOS-based approaches in digital circuits . This alternative may satisfy the needs of future electronic designs, con- sidering the expected end of Moore’s law. This study introduces CVM, a Crossbar-based circuit Verification through Modeling tech- nique

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

The described data set contains features from the machine control of a five-axis milling machine. The features were recorded during thirteen series productions. Each series production includes a changeover process in which the machine was set up for the production of a different product. In addition to the timestamps and the twenty recorded features derived from Numerical Control (NC) control variables, the data set also contains labels for the different production phases. For this purpose, up to 23 phases were assigned, which are based on a generalized milling process. The data set consists of thirteen .csv files, each representing a series production. The data set was recorded in a production company in the contract manufacturing sector for components with real series orders in ongoing industrial production.

Nickel base superalloy GH4169 is a material with strong mechanical properties and is difficult to process. In order to reduce tool wear during material processing and improve workpiece surface processing quality, based on the finite element simulation software DEFORM, the influence of n, ap, and fz parameters on tool wear during carbide tool milling GH4169 was studied, and a simulation orthogonal experimental model was established, The prediction model of tool wear is obtained; The ultrasonic vibration milling is compared with ordinary milling, and the improvement degree of different coating materials on carbide tool wear is explored. The results show that the ultrasonic vibration signal is helpful to reduce tool wear, improve the surface quality of the workpiece, and improve the stability of the milling process. TIALN/TIN (WC) composite coated tools have good cutting performance, help to reduce tool temperature, reduce tool wear, and improve tool life.

Background: Aflatoxins (AFs) as toxic compounds are widely spread. They are frequent contaminants of crops that are produced by fungi species. Corn is of crops that widely used in the corn dry milling process; a four-step procedure comprises grain handling and milling, liquefaction and saccharification, fermentation, and co-product recovery that produces ethanol and animal feed. However, it is possible that corn as a feed for dry milling process might be contaminated with AFs. Therefore, monitoring AFs in during widespread this process results having a better understanding of the fate of AFs. Methods: In this study, a sample of corn kernel was contaminated with a high level of AFs using Aspergillus parasiticus. Then, the corn flour comprising 23400.5 µg/kg of the total level of aflatoxins (AFT), was hydrolyzed by enzymes and acid for ethanol fermentation with Saccharomyces cerevisiae. Also, the level of AFs was monitored during ethanol fermentation process. Results: The results showed that AFs did not detect in the ethanol produced through fermentation and it was safe. Also, during the experiments, the AFT level reduced by 58.5 and 95.7% for the ethanol fermentation with simultaneous saccharification and fermentation and ethanol production with acidic hydrolysis, respectively. Conclusion: The results of this study showed that highly contaminated corn with AFs can be used for ethanol fermentation through dry milling process and the produced ethanol was safe.

Neural circuits that enable an organism to protect itself by promoting escape from immediate threat and avoidance of future injury are conceptualized to carry an “aversive” signal. One of the key molecular elements of these circuits is the kappa opioid receptor (KOR) and its endogenous peptide agonist, dynorphin. In many cases, the aversive response to an experimental manipulation can be eliminated by selective blockade of KOR function, indicating its necessity in transmitting this signal. The dopamine system, through its contributions to reinforcement learning, is also involved in processing of aversive stimuli, and KOR control of dopamine in the context of aversive behavioral states has been intensely studied. In this review, we have discussed the multiple ways in which the KORs regulate dopamine dynamics with a central focus on dopamine neurons and projections from the ventral tegmental area. At the neuronal level, KOR agonists inhibit dopamine neurons both in the somatodendritic region as well as at terminal release sites, through various signaling pathways and ion channels, and these effects are specific to different synaptic sites. While the dominant hypotheses are that aversive states are driven by decreases in dopamine and increases in dynorphin, reported exceptions to these patterns indicate these ideas require refinement. This is critical given that KOR is being considered as a target for development of new therapeutics for anxiety, depression, pain, and other psychiatric disorders.

In this study, a new methodology based on the circuit approach is employed to obtain renewable electric energy. Although a voltage source and a current source generate voltage and current, respectively, they work only when they receive electric power, which is the product of voltage and current. However, this paper proposes a circuit with a voltage source, a current source and a super-condenser connected in series, in which the voltage source provides voltage for the current source and the current source provides current for the voltage source. Resultantly, electric power is generated both at the voltage and current sources, and the energy (i.e., the electric power) from the current source is converted to the charging energy in the super-condenser. Herein, we describe the method for charging the super-condenser using a voltage source and a current source. To confirm the abovementioned concept, we conducted experiments, and the energy was successfully produced, with high reproducibility. Finally, the brief mechanism for the energy conversion, a schematic method for reducing the capacitances of stored batteries, and the significance of this study are described.

The system design for Sustainable manufacturing is to consider both ecological and financial constraints. Manufacturing industry demands to advance in sustainable manufacturing by accounting in environment factors in it. All the factors that affect the environment need to be analyzed so that proper amendments or suggestions can be provided. To favour this, Computer aided life cycle inventory model has been presented for CNC milling and turning processes. Based on utilization of resources and stages, whole machining operation time can be divided into three phases named as process (milling or turning), idle and basic times. As parameters are different for evaluating the process times i.e. depth and width of cut in case of milling and initial and final diameters for turning, two different case studies has been presented one for each milling and turning process. Effect of material choice has been studied for different processes. Highly dense and hard materials takes more time in finishing the job due to low cutting speed and feed rates as compared to that of sot materials. In addition, face milling takes more time and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in peripheral retraction process.

The microstructural evolution, thermodynamics and kinetics of Mo-21%Tm₂O₃ (mass fraction, %) powder mixtures during ball milling were investigated using X-ray diffraction and transmission electron microscopy. Ball milling induced Tm₂O₃ to be decomposed and then dissolved into Mo crystal. The supersaturated nanocrystalline solid solution of Mo (Tm, O) was obtained after 96 h of ball milling. The elements of Mo, Tm and O were distributed uniformly in the ball-milled particles. Based on the semi-experimental theory of Miedema, a thermodynamic model was developed to calculate the driving force of phase evolution. There was no chemical driving force to form a crystal solid solution of Tm atoms in Mo crystal or an amorphous phase because the Gibbs free energy for both processes was higher than zero. For Mo-21%Tm₂O₃, it was mechanical work, not negative heat of mixing, that provided the driving force to form supersaturated nanocrystalline Mo (Tm, O) solid solution.

Machine learning methods have widely been applied to detect anomalies in machine and cutting tool behavior during lathe or milling. However, detecting anomalies in the workpiece itself did not get the same attention by researchers. That is why in this article, the authors present a pub-licly available multivariate time series dataset which was recorded during milling of 16MnCr5. Due to artificially introduced, though realistic anomalies in the workpiece the dataset can be ap-plied for anomaly detection. By using a convolutional autoencoder as a first model good results in detecting the location of the anomalies in the workpiece were achieved. Furthermore, milling tools with two different diameters where used which led to a dataset eligible for transfer learn-ing. The objective of this article is to provide researchers with a real-world time series dataset of the milling process which is suitable for modern machine learning research topics like anomaly detection and transfer learning.

In laser-assisted milling, higher temperature in shear zone softens the material potentially resulting in a shift of mean residual stress, which significantly affects the damage tolerance and fatigue performance of product. In order to guide the selection of laser and cutting parameters based on the preferred mean residual stress, inverse analysis is conducted by predicting residual stress based on guessed process parameters, which is defined as the forward problem, and applying iterative gradient search to find process parameters for next iteration, which is defined as the inverse problem. An analytical inverse analysis is therefore proposed for the mean residual stress in laser-assisted milling. The forward problem is solved by analytical prediction of mean residual stress after laser-assisted milling. The residual stress profile is predicted through the calculation of thermal stress, by treating laser beam as heat source, and plastic stress by first assuming pure elastic stress in loading process, then obtaining true stress with kinematic hardening followed by the stress relaxation. The variance-based recursive method is applied to solve inverse problem by updating process parameters to match the measured mean residual stress. Three cutting parameters including depth of cut, feed per tooth, and cutting speed, and two laser parameters including laser-tool distance and laser power, are updated with respected to the minimization of resulting residual stress and measurement in each iteration. Experimental measurements are referred on the laser-assisted milling of Ti-6Al-4V grade 5 and ELI. The percentage difference between experiments and predictions is less than 5% for both materials, and the selection is completed within 50 loops.

Tungsten and its alloys are considered as a key component in high temperature environment. Self-passivating W-Si-xY alloys with different Y contents made from the powders milled for different times were prepared by mechanical alloying (MA) and spark plasma sintering (SPS). Their microstructures and oxidation resistance were investigated. It is found that the oxidation resistance of the alloys with low Y contents (0Y and 2Y) made from 20 h-milled powders is worse than that of the alloys made from 4 h-milled powders. It is because the protective WO3/SiO2 composite layer is discontinuous. While the alloys with high Y contents (4Y and 6Y) made from 4 h and 20 h-milled powders show good oxidation resistance. Even, the thickness of the oxide layer of the alloys with 4Y and 6Y made from 20 h-milled powders after oxidation at 1000 ℃ for 2 h is 84.0 μm and 70.7 μm, less than that made from 4 h-milled powders. This is due to the size and distribution of W5Si3, Y2Si2O7 aggregates and W-Y-O melt. The synergistic effects of Y contents and milling time on the microstructures and oxidation resistance of the alloys are revealed.

Plastic contamination is a burning issue costing the global cotton and textile industries billions of dollars annually. Any time plastics from different sources end up in a cotton lint bale, the value to the textile mills plummets significantly. Various industry players have therefore made a concerted effort to find lasting solutions to the menace posed by plastic to cotton profitability and sustainability. Nevertheless, until now, there have been no up-to-date comprehensive documents detailing the numerous and ever-growing efforts committed to solving this challenge. Therefore, this article provides a detailed yet compact review of this highly dynamic subject matter. First, it puts into perspective plastic contamination in the cotton and textile industries. Then, the cotton value chain is subdivided into phases from pre-cultivation to textile mills. The root causes of plastic contamination are discussed in each stage, followed by discussions of some already developed and emerging solutions in response to the challenge by the affected industries and researchers. Concluding from the author’s perspective, the paper makes projections for the future directions of plastic mitigation efforts within the cotton and textile industries. This article also infers from the reviewed literature that research on finding alternative materials to plastic as module wrap, the development of new, effective, and all-condition plastic sensing techniques for ginning and spinning equipment, and standardized protocols for UAV in-field surveys of plastic trash are some of the areas that will be beneficial to finding a permanent solution to the challenge.

This study explores the intriguing phenomenon of action potentials reverberating and propagating in high-resistance tissues, such as gliosis, leading to the emergence of short circuits within the brain. Gliosis, characterized by increased tissue resistance, presents a unique environment for electrical signals. My research investigates the possible mechanisms behind these reverberations and their role in the creation of self-empowering short circuits that can potentially affect the entire brain's functionality. Understanding these processes may have significant implications for the treatment and management of neurological disorders associated with gliosis and abnormal electrical activity in the brain.

Based on the analysis of the working principle, circuit design and working loss of the common charger DC/DC converter, this paper designs a ZVS half-bridge three-level DC/DC converter based on non-phase-shift control mode, and proposes a multi-stage constant current and voltage limiting charging control strategy based on modulation wave selection control. The simulation results show that the proposed method and control strategy have faster voltage regulation ability and wider stability margin, and can achieve stable current sharing control in the charging process.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

Emerging semiconductor devices often lack accurate analytical models. The same is usually true of any devices working under extreme conditions like cryogenic temperatures. The usual workaround involves the use of approximation models, usually based on lookup tables or neural networks individually fitted to measurement data. In the case of experimental devices or ones working under extreme conditions, the number of units available for measurement is limited. As a result, the number of approximation-model instances is too small to enable a statistical simulation of even middle-sized circuits, which is a necessary step in integrated-circuit design since it provides the realistic picture of the circuit’s behavior in the presence of manufacturing process variations. Approximation models using structure parameters as inputs do exist in the literature, but are only useful if the end user knows the statistical distributions of those parameters, which is not usually the case. We propose a technique based on generative machine learning, namely the variational autoencoder, that uses only a small sample of devices to capture the essential features of their I–V curves under process variations and subsequently generates an arbitrary number of similarly disturbed curves. The model trained on as few as 20 instances per device type is shown to precisely reproduce the distributions of period and power consumption of a ring oscillator.

Recently, the demand for electric vehicle is increasing worldwide due to eco-friendly policies and stricter emission regulations. As a traction motor for electric vehicle, interior permanent magnet synchronous motors are mainly used. For the design of the interior permanent magnet synchronous motor, the magnetic equivalent circuit method, which is a method of lumped constant circuit, and the finite element method, which is a method of distributed constant circuit, mainly are used. Magnetic equivalent circuit method is useful for simple design through fast and intuitive parameters, but it cannot derive the distribution of magnetic field. The finite element method can derive an accurate magnetic field distribution, but it takes a long time to analyze and it is difficult to analyze intuitive design parameters. In this paper, magnetic equivalent circuit method and Carter coefficient are mixed for rotor structure design. This design method will be called the hybrid magnetic equivalent circuit method. Intuitive design parameters are derived through this hybrid magnetic equivalent circuit method. We will derive the Air gap flux density distribution according to rotor shape, no-load induced voltage, and cogging torque, and compare and verify it with the finite element method.

In this study, a mixed rule of degree of precision nine has been developed and implemented in the field of electrical sciences to obtain the instantaneous current in the RLC- circuit for particular value .The linearity has been performed with the Volterra’s integral equation of second kind with particular kernel . Then the definite integral has been evaluated through the mixed quadrature to obtain the numerical result which is very effective. A polynomial has been used to evaluate Volterra’s integral equation in the place of unknown functions. The accuracy of the proposed method has been tested taking different electromotive force in the circuit and absolute error has been estimated.

Due to the high specific surface area of titanium aluminide powders, significant and unavoidable surface oxidation takes place during processing. The resulting oxides disrupt the conventional powder metallurgical process route (pressing and sintering) by reducing green strength and sintered properties. Oxide-free particle surfaces offer the potential to significantly increase particle bond strength and enable the processing of difficult-to-press material powders. In this work, the effect of milling titanium aluminide powder in a silane-doped atmosphere on the component properties after pressing and subsequent sintering was investigated. Ball milling was used to break up the oxide layers and create bare metal surfaces on the particles. With the help of silane-doped inert gas, the oxygen partial pressure was greatly reduced during machining. It was investigated whether oxide-free surfaces could be produced and maintained by milling in silane-doped at-mospheres. Furthermore, the resulting material properties after pressing and sintering were an-alyzed using density measurements, hardness tests, EDX-measurements and micrographs. It was concluded, that ball milling in a silane-doped atmosphere produces and maintains oxide-free particle surfaces. These oxide-free surfaces and smaller particle sizes improve the component properties after pressing and sintering.

In the world industry plant, solid and solid metals are always in contact even their motions not independent. Modeling of rolling die contact with slab primarily needs to describe the Tribology of contact phenomena. Consideration of continuum theory of rolling contact how a contact region is formed between rolling die and slab, and how the tangential force is distributed over the contact area with coefficient of friction is important. The central concern of numerical model is used in this work to indicate a set of equations, derived from the contact principle, that transfer the physical event into the mathematical equations including the laws of nature, such as newton’s laws, boundary conditions, state of stresses and their derivatives at particular time and locations. In this paper the elasticity stress behavior of rolling die contact with slab for number of cyclic loads is modeled. The model is including new proposed constitutive equations for discontinuity of the velocity, pressure distribution in rolling contact from the enter side to exit side of the neutral point. To verify the model, finite element simulation and experimental data from the literature are considered. The results show good agreement with finite element simulation and experimental data.

This work presents a methodology for the generation and classification of phase resolved partial discharges (PRPD) patterns based on the use of a printed UHF monopole antenna and signal con-ditioning circuit to reduce hardware requirements. For this purpose, envelope detection technique was applied. In addition, test objects such as a hydrogenerator bar, dielectric disks with internal cavities in an oil cell, potential transformer, and tip-tip electrodes immersed in oil were used to generate partial discharge (PD) signals. To detect and classify partial discharges, the standard IEC 60270 (2000) method was used as reference. After acquisition of conditioned UHF signals, digital signal filtering threshold technique was used, and peaks of partial discharges envelopes pulses were extracted. Feature selection techniques were used to classify the discharges and choose the best features to train machine learning algorithms, such as multilayer perceptron, support vector ma-chine and decision tree. Accuracies greater than 84% were met, revealing the classification potential of the methodology proposed in this work.

Previously, we described that Adenine, Thymine, Cytosine, and Guanine nucleobases were superconductors in a quantum superposition of phases on each side of the central Hydrogen bond acting as a Josephson Junction. Genomic DNA has two strands wrapped helically around one another, but during transcription, they are separated by the RNA polymerase II to form a molecular condensate called the transcription bubble. Successive steps involve the bubble translocation along the gene body. This work discusses how quantum information transfer and entanglement can be achieved by modeling DNA as a combination of

Abstract: The traditional model of closed circuit ball milling systems has been used for several decades, however, if the classifier of the closed circuit ball mill system performs the duties of both pre-classification and check-classification, the characterization error of the traditional model is large. To address this problem, a new model is obtained by modifying and supplementing the traditional one. The most important feature of the new model compared to the traditional model is that the circulating load is considered to be the fresh feed for the entire system rather than the ball mill. The error between the slurry level height calculated using the traditional model and the actual is 52.31%, which is 13.77 times higher than that of the new model. When the relative capacity varies greatly, that of the ball mill calculated by the traditional model fluctuates between 0.95 and 1.15, while the new model is 0.6 to 1.4. The new model has a higher accuracy than the traditional model in characterizing the production status of the grinding system, which is of some significance for industrial production.

In this research paper, a novel high step up dc-dc converter with a coupled inductor and voltage doubler circuits is proposed. The converter achieves a high step up voltage gain with an appropriate duty ratio and low voltage stress on the power switches. Also, the energy which is stored in the leakage inductor of the coupled inductor can be recycled to the output. The operating principles and the steady state analysis of the proposed converter are discussed in detail. Finally, a prototype circuit of the proposed converter is implemented in the laboratory in order to verify the performance of the proposed converter.

In the current study nanocellulose was isolated from walnut shell using mechanical and chemical methods. This study highlights the particle size, morphology and these methods’ efficiency in nano structure extraction. The difference between morphology and size of the particles (of the both extracted methods) were investigated by field emission scanning electron microscopy (FESEM). Walnut shell is an agro-waste material with source of lignin and cellulose. Ball mill-ing with different times, in the presence and absence of additive and acid hydrolysis were used as mechanical and chemical methods, respectively. The result showed mechanical method is unable to extract nanoparticle and just reshape the walnut shell. Milling time were also found important in morphology of fiber extracted. FE-SEM images represented that structure mean diameter of using ball mill was 1± 5 μm while hydrolysis acid method extract nano particle with mean diameter of 40± 20 nm.

This study was aimed at investigating the effects of roasting and cryogenic milling on particle size, water solubility, and amount of bioactive components in ginseng root. Samples were pulverized by cryogenic milling, and one treatment condition was selected for each size range (10-50 μm, and >50 μm). The selected samples were roasted at different temperatures (160-200 °C) followed by cryogenic milling. Powdered samples were analyzed for their physicochemical characteristics. Results revealed that roasted samples exhibited significantly smaller particle size than controls (not roasted, p<0.05), and the particle size of roasted samples decreased with increase in roasting temperature until flocculation occurred around 180-190 °C. With decrease in particle size of ginseng; water solubility index, antioxidant activity, total polyphenol content, and total polysaccharide content were observed to increase. Ginseng samples showed an increasing trend in antioxidant activity with decreasing particle size (p>0.05) with significantly higher values for all roasted samples compared to the controls (p<0.05). Non-polar ginsenosides such as Rg2(S), Rg2(R), Rg3(S), Rg3(R), and Rh1(S) showed an increase in temperature-dependent manner. This study revealed that roasting at certain temperature range with cryogenic milling has positive effects on ginseng by reducing its particle size, and increasing water solubility and bioactive components.

This study aimed to decrease the particle size of ginseng by roasting and cryogenic milling to increase its water solubility and physiological activity. The samples were roasted for different times (9–21 min) and generated in different sizes (10–50, and > 50 μm). All roasted samples revealed significantly smaller particle sizes than did non-roasted samples based on Sauter mean diameter (D [3,2], p < 0.05). Further, the particle sizes of roasted samples decreased till roasting up to 15 min. In terms of the water solubility index (WSI), antioxidant activity, total polyphenol content (TPC), and total polysaccharides according to particle size, 10-20 μm-sized samples showed the highest values when compared with >50 μm-sized samples. Based on roasting time, WSI values of all samples roasted for up to 15 min were higher than those of the control (not roasted) (p < 0.05). Antioxidant activity and TPC also increased with increasing roasting time. Total polysaccharide content was the highest upon roasting for 15 min except for the 10-20 μm sample. Ginsenoside content of roasted samples >20 μm size was higher than that of the control (not roasted) except after 15 min of roasting. Therefore, roasting and cryogenic milling are effective in producing ginseng root powder.

The world is currently facing an energy crisis. To solve the problem, many countries have been exploring renewable energy sources. However, the existing renewable energy sources are highly dependent on weather changes, necessitating the utilization of significantly expensive and large storage batteries.As a solution, we propose a system for generating renewable energy. The proposed system comprises a current source and a voltage source connected in series. With appropriate adjustments, the current source supplies current without voltage and the voltage source provides voltage without current. Considering that electric power is a product of current and voltage, electric power is generated from the interaction between the current source and voltage source. In our previous study, the same result was obtained; however, the output voltage was low, which resulted in a low amount of generated energy. In this study, by introducing some ingenuities, we successfully increased the output voltage. Consequently, we succeeded in powering a light-emitting diode and charging a super-condenser to the standard voltage. Using this system, we generated a relatively large amount of energy in the right place and at the right time, validating our systems’ robustness to changes in weather. The large-scale adoption of our system could contribute to solving the global energy crisis.

In this article, we propose a circuit to imitate the behavior of a Reward-Modulated Spike-Timing-Dependent Plasticity synapse. When two neurons in adjacent layers produce spikes, each spike modifies the thickness of the common synapse. As a result, the synapse’s ability to conduct impulses is controlled, leading to an unsupervised learning rule. By introducing a reward signal, reinforcement learning is enabled by redirecting the growth and shrinkage of synapses based on signal feedback from the environment. The proposed synapse manages the convolution of the emitted spike signals to promote either the strengthening or weakening of the synapse, which is represented as the resistance value of a memristor device. As memristors have a conductance range that may differ from the available current input range of typical CMOS neuron designs, the synapse circuit can be adjusted to regulate the spike’s amplitude current to comply with the neuron. The circuit described in this work allows for the implementation of fully interconnected layers of neuron analog circuits. This is achieved by having each synapse reconform the spike signal, thus removing the burden of providing enough power from the neurons to each memristor. The synapse circuit was tested using a CMOS analog neuron described in the literature. Additionally, the article provides insight into how to properly describe the hysteresis behavior of the memristor in Verilog-A code. The testing and learning capabilities of the synapse circuit are demonstrated in simulation using the Skywater-130nm process. The article’s main goal is to provide the basic building blocks for Deep Neural Neural Networks relying on spiking neurons and memristors as the basic processing elements to handle spike generation, propagation, and synaptic plasticity.

The Chen circuit system, a three-dimensional autonomous system with intriguing dynamics, has gained considerable attention due to its potential applications in diverse scientific fields. In this article, a Chen circuit-like system is defined and a comprehensive dynamics has been studied. The system exhibits chaotic dynamics, limit cycles, and bifurcations, making it a captivating subject of study. By employing numerical simulations and analytical techniques, we explore the system's stability and identify critical parameter values leading to qualitative changes. Notably, we delve Hopf bifurcations, which give rise to stability changes and the emergence of limit cycles. Furthermore, we analyze the fractal dimension of the system's attractor, providing insights into its complexity and self-similarity. Through a systematic examination of the Chen circuit-like system, we deepen our understanding of its intricate dynamics and offer valuable insights into the underlying mechanisms. The findings contribute to the field of dynamical systems and hold potential implications in areas such as chaos-based secure communications, signal processing, and nonlinear control. This work serves as a valuable reference for researchers and practitioners interested in the dynamics and bifurcation analysis of nonlinear systems.

This study aims to develop novel automated computer vision algorithms and systems for component replacement inspection for Printed Circuit Boards (PCBs). The proposed algorithms are able to identify locations as well as sizes of different components. They are object detection algorithms based on keypoints of the target components. The algorithms can be implemented as neural networks consisting of two portions: frontend networks and backend networks. The frontend networks are used for the feature extractions of input images. The backend networks are adopted for producing component inspection results. Each component class can has its own frontend and backend networks. In this way, the neural model for the component class can be effectively reused for different PCBs. To reduce the computation time for the inference of the networks, different component classes can share the same frontend networks. A two-stage training process is proposed for effectively exploring features of different components for accurate component inspection. The proposed algorithm has the advantages of the simplicity for training data collection, high accuracy for defect detection, and high reusability and flexibility for online inspection. The algorithm is an effective alternative for the automated inspection in smart factory with growing demand for product quality and diversification.

As the PCIe 6.0 specification places higher requirements on signal integrity and transmission la-tency, it becomes especially important to improve signal transmission performance at the physical layer of the transceiver interface. Retimer circuit as a key component of high-speed serial interface, its delay and jitter size directly affect the overall performance of PCIe. For the conventional Retimer circuit with large latency and low jitter performance, this paper proposes a low latency and low jitter Retimer circuit based on CDR+PLL architecture for PCIe 6.0, using a jitter canceling filter circuit to eliminate the frequency difference between the retiming clock and data, reduce the retiming clock jitter, and improve the quality of Retimer output data; The data is sampled using the retiming clock and then output, avoiding the problem of large penetration latency of con-ventional Retimer circuits. The circuit is designed using CMOS 28nm process. Simulation results show that when 112Gbps PAM4 data is input to the Retimer circuit, the Retimer penetration la-tency is 27.3 ps, which is 83.5% lower than the conventional Retimer structure; the output data jitter is 741 fs, a 31.4% reduction compared to the conventional Retimer structure.

Computation of circuit complexity has gained much attention in the Theoretical Physics community in recent times to gain insights about the chaotic features and random fluctuations of fields in the quantum regime. Recent studies of circuit complexity take inspiration from the geometric approach of Nielsen, which itself is based on the idea of optimal quantum control in which a cost function is introduced for the various possible path to determine the optimum circuit. In this paper, we study the relationship between the circuit complexity and Morse theory within the framework of algebraic topology using which we study circuit complexity in supersymmetric quantum field theory describing both simple and inverted harmonic oscillators up to higher orders of quantum corrections. The expression of circuit complexity in quantum regime would then be given by the Hessian of the Morse function in supersymmetric quantum field theory, and try to draw conclusion from their graphical behaviour. We also provide a technical proof of the well known universal connecting relation between quantum chaos and circuit complexity of the supersymmetric quantum field theories, using the general description of Morse theory.

Rail impedance directly affects the transmission performance of track circuit . Considering the condition of earth stratification, for the difficult to calculate the rail impedance due to the semi-infinite integration interval and the oscillation of the integrand by using the Carson formula, The truncation method is proposed to divide the impedance formula is divided into definite integral and tail integral. The integral is approximated by the spline function, and the tail integral is calculated by using the exponential integral and Euler formula. Based on it, the rail impedance calculation formula of track circuit is obtained. The electromagnetic field model of track circuit with earth stratification is simulated by finite element method, and the correctness of the method is verified. Based on the formula, the influence of current frequency, soil depth and conductivity on rail impedance is studied. The relative error between the calculated results of rail impedance and the simulation results of finite element is within 5%. It can be seen that the formula has high accuracy and correctly reflects the law of rail impedance variation with current frequency, soil depth and resistivity. It provides a reliable reference for the theoretical calculation of rail impedance of track circuit.

The aim of this document is to present how the interpretation of the RVM (Recovery Voltage Measurement) test can be improved through the use of a Debye equivalent circuit. As it is described in the literature the interpretation of the RVM test requires expertise and if the transformer presents a high interfacial polarization it is not possible to diagnose it in detail. Debye model is proposed in this work for enhancing RVM interpretation. This model is based on an electrical circuit that includes basic R-L-C components, that allows two interesting features: on one hand, isolation physical effects can be separately represented and, on the other, the values of the R-C components can be calculated from the RVM response (L components are not used in this work as long as no magnetic field effects are taken into account). Thus, the different isolation effects that are indistinguishable merged in the RVM transient response can be split into different R-C branches, each one corresponding with a single (not merged) isolation effect. Finally, several case studies are presented, in which it is correlated a dielectric oil treatment carried out and the equivalent circuit changes.

Blisks subjected to rough machining for channel creation must undergo finishing processes, and such processes must achieve the required tolerance limits. A high-quality surface finish and predictable long tool life are critical for the finish milling of blisks. Accordingly, the aim of this study was to optimize parameters for the finish machining of an Inconel 718 alloy monolithic blisk. Ball-cone mills were used to machine the blade surface at a constant depth. A sensory tool holder was used to collect cutting force signals during machining, and a digital microscope was used to examine tool wear. The surface texture measuring instrument was used to measure blisk blade surface roughness to evaluate processing quality. This study manipulated two cutting parameters, namely cutting speed and feed per tooth, and investigated their effects. The relationship between cutting conditions and machining efficiency was analyzed. According to the experimental results, we identified a set of optimal parameters for marginal tool wear and fast cutting speeds and then estimated the corresponding tool life by using the derived parameters.

In the manufacturing industry, cutting tool failure is a probable fault which causes damage to the cutting tools, workpiece quality and unscheduled downtime. It is very important to develop a reliable and inexpensive intelligent tool wear monitoring system for use in cutting processes. A successful monitoring system can effectively maintain machine tools, cutting tool and workpiece. In the present study, the tool condition monitoring system has been developed for Die steel (H13) milling process. Effective design of experiment and robust data acquisition system ensured the machining forces impact in the milling operation. Also, ANFIS based model has been developed based on cutting force-tool wear relationship in this research which has been implemented in the tool wear monitoring system. Prediction model shows that the developed system is accurate enough to perform an online tool wear monitoring system in the milling process.

This paper presents a study of the 2D roughness profiles on a flat surface generated on a steel work piece, by ball nose end milling, with linear equidistant tool paths (pick-intervals). The milled surface exploration with a surface roughness tester (on pick and feed directions) produces usually 2D roughness profiles having periodical evolutions. These evolutions can be seen as time-dependent signals, describable as a sum of sinusoidal components (the wavelength of each component being regarded as a period). In order to detect a well approximated description of these components, two appropriate signal processing techniques are used in this work: first technique provides a direct mathematical (analytical) description and is based on computer aided curve (signal) fitting (more accurate), the second technique (providing an indirect and incomplete description) is based on the spectrum generated by fast Fourier transform (less accurate). This study can be seen as a way for a better understanding the interaction between the tool and the work piece or to achieve a mathematical description of the machined surface microgeometry in terms of roughness (e. g. its description being a collection of closely spaced 2D roughness profiles).

The total ionizing dose (TID) effect significantly impacts the electrical parameters of fully depleted silicon on insulator (FDSOI) devices and even invalidates the on-off function of devices. At present, most of the irradiation research on the circuit level is focused on the single event effect, and the research on the total ionizing dose effect is very little. Therefore, this study mainly analyzes the influence of TID effects on a CMOS inverter circuit based on 22 nm FDSOI transistors. First, we constructed and calibrated an N-type FDSOI metal-oxide semiconductor (NMOS) structure and P-type FDSOI metal-oxide semiconductor (PMOS) structure. The transfer characteristics and trapped charge distribution of these devices were studied under different irradiation doses. Next, we studied the TID effect on an inverter circuit composed of these two MOS transistors. The simulation results show that when the radiation dose is 400 krad (Si), the logic threshold drift of the inverter is approximately 0.052 V. These results help further investigate the impact on integrated circuits in the irradiation environment.

Cocoyam is a highly nutritious root crop and very promising with vast industrial potentials. The effect of some processing methods on the proximate composition of cocoyam (Xanthosoma sagittifolium) flour was investigated by subjecting the cormels to three pre-treatment methods (soaking, fermentation and steaming) and subsequently, to two different milling methods (wet and dry-milling methods). The proximate composition namely moisture content, crude protein, crude fat, fibre, ash and carbohydrate contents of the flours obtained was carried out. The fermented samples of the wet- and dry-milled flours retained the highest nutrients compared with the soaked and steamed samples. However, the fermented dry-milled flour had the highest crude protein (5.83-6.98 %), crude fat (0.55-2.21%), ash (3.75-4.29%), and carbohydrate (83.75-87.62%), which made it the most acceptable of the samples. The milling methods (wet and dry) had significant effects (p≤0.05) on the proximate composition of the flour for the selected pretreatment methods (soaking, fermentation and steaming). Fermentation as a pretreatment method was therefore, recommended for better nutrient retention for cocoyam flour.

Shaped surfaces are increasingly used in the field of mould making for casting or injection moulding, where future products include shapes with different curvatures. These are surfaces that form convex curves, concave curves, or a combination thereof. Given these machined surfaces, it is important to know the impact of the finishing strategies on these surfaces. This paper deals with the comparison of finishing milling strategies in the production of shaped surfaces and the analysis of different methods for the evaluation of surface topography, surface roughness and the evaluation of deviations. The material used for the experiments was AlCu4Mg aluminium alloy, and Constant Z, Spiral and Spiral circle strategies were chosen for the finishing strategies. The evaluation of surface topography and surface roughness was carried out at three different sample heights with respect to the tool contact with the machined surface. The results showed changes in the toolpaths due to the variation of the effective diameter of the tool cutter to the machined surface as well as the choice of strategy. To produce specimens with corresponding shapes in terms of topography, the Constant Z strategy was the most suitable, in which uniform toolpaths were obtained over the whole height of the sample.

Various metals and semiconductors containing Printed Circuit Boards (PCBs) are abundant in any electronic device equipped with controlling and computing features. These devices inevitably constitute E-waste after the end of service life. The typical construction of PCBs includes mechanically and chemically resistive materials, which significantly reduce the reaction rate or even avoid accessing chemical reagents (dissolvents) to target metals. Additionally, the presence of relatively reactive polymers and compounds from PCBs requires high energy consumption and reactive supply due to the formation of undesirable and sometimes environmentally hazardous reaction products. Preliminarily milling PCBs into powder is a promising method for increasing the reaction rate and avoiding liquid and gaseous emissions. Unfortunately, current state-of-the-art milling methods also lead to the presence of significantly more reactive polymers still adhered to milled target metal particles. This paper aims to find a novel single and two-stage disintegration-milling approach that can provide the formation of metal-rich particle size fractions. The morphology, particle fraction sizes, bulk density, and metal content in produced particles were measured and compared. Research results show the highest bulk density (up to 6.8 g·cm-3) and total metal content (up to 95.2 wt. %) in finest sieved fractions after the single-step milling of PCBs. Therefore, the concentrations of about half tested metallic elements are higher in the single milled specimen and with lower adhered plastics concentrations, as compared to double milled specimens.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

In the process of metal cutting, the anti-wear performance of the tool determines the life of the tool and affects the surface quality of the workpiece. The finite element simulation method can directly show the tool wear state and morphology, but due to the limitations of the simulation time and complex boundary conditions, it has not been commonly used in tool life prediction. Based on this, a tool wear model was established on the platform of a finite element simulation software for the cutting process of titanium alloy TC4 by end milling. The key technique is to embed different types of tool wear models into the finite element model in combination with the consequent development technology. The effectiveness of the tool wear model is validated by comparing the experimental results with the simulation results. At the same time, in order to quickly predict the tool life, an empirical prediction formula of tool wear was established, and the change course of tool wear under time change was obtained.

Boost-derived converters are most popular in Power Factor Correction AC-DC conversion applications and alternative energy generation systems. The proper operation of such converters relies on housekeeping power supplies providing auxiliary power for their control circuitry. The purpose of this study is to present a design-oriented analysis of a simple, passive, isolated, self-bias circuit that can provide a stabilized voltage for the control circuits of boost-derived converters. The circuit’s output voltage inherently follows the main regulated output and therefore, does not require an additional active control. The paper presents a detailed analysis of the circuit and offers design guidelines. Following the presentation of the basic idea several variations of the circuit, that can be used in special applications, are presented. The feasibility of the proposed bias circuits was verified by simulation and experiment on a laboratory prototype.

This paper presents a Modified Gate Diffusion Input (MGDI) design with four inputs for Quantum-dot Cellular Automata (QCA) technology. QCA is a promising nanotechnology that offers benefits such as low power consumption, and high density, making it a potential alternative to CMOS technology. The proposed planar cell design has advantages over previous designs, including a 19% reduction in the number of cells, a 29% reduction in total energy consumption, and a 44% reduction in average energy loss at the same occupancy level. The proposed block is capable of implementing 21 basic combinational functions and various sequential functions. The simulation of functions in 18nm technology and energy consumption calculation indicates that the resulting circuits have improvements of 41%, 27%, 27%, and 20% compared to multiplexers, comparators, four-bit parity circuits, and single-bit memory, respectively. Additionally, the number of cells in the proposed circuits has improved by 10%, 7%, 22%, and 19%, respectively.

Energy efficiency considerations in terms of reduced power dissipation is a significant issue in the design of digital circuits for very large-scale integration (VLSI) systems. Quantum-dot cellular automata (QCA) is an emerging ultra-low power dissipation approach, distinct from the traditional complementary metal-oxide semiconductor (CMOS) technology, for building digital computing circuits. Developing fully reversible QCA circuits has the potential to significantly reduce energy dissipation. The multiplexer is a fundamental element in the construction of useful digital circuits. In this paper, a novel, multilayer, fully reversible QCA 8:1 multiplexer circuit, with ultralow energy dissipation, is introduced. The proposed multiplexer power dissipation is simulated using the QCADesigner-E version 2.2 tool, describing the microscopic physical mechanisms underlying the QCA operation. The results showed that the proposed reversible QCA 8:1 multiplexer consumes 89% less energy than the most energy-efficient 8:1 multiplexer circuit presented previously in the scientific literature.

Abstract: For the problem of small target of printed circuit board surface defects and low detection accuracy, the printed circuit board surface defect detection network DCR-YOLO is designed to meet the premise of real-time detection speed and effectively improve the detection accuracy. Firstly, the backbone feature extraction network DCR-backbone, consisting of two CR residual blocks and one common residual block, is used for small target defect extraction on printed circuit boards. Secondly, the SDDT-FPN feature fusion module is responsible for the fusion of high level features to low level features, while enhancing feature fusion for the feature fusion layer where the small target prediction head YOLO Head-P3 is located to further enhance the low level feature representation. the PCR module enhances the feature fusion mechanism between the backbone feature extraction network and the SDDT-FPN feature fusion module at different scales of feature layers. the C5ECA module is responsible for adaptive adjustment of feature weights and adaptive attention to the requirements of small target defect information, further enhancing the adaptive feature extraction capability of the feature fusion module. Finally, three YOLO-Heads are responsible for predicting small target defects for different scales. Experiments show that the DCR-YOLO network model detection Map reaches 98.58%, the model size is 7.73MB, which meets the lightweight requirement, and the detection speed reaches 103.15fps, which meets the application requirements for real-time detection of small target defects.

This paper considers the principles of building a circuit model of film resistor cutting. The conductive resistive medium is defined with the component equations and the topology of the circuit model. A method of estimating the electric parameters of a resistor operating in the system with a measuring voltage source is shown. An equation system for the node voltages is defined, and the resistive layer parameters are analyzed as the circuit model structure changes during the cutting process.

With the development of designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system becomes a key point to determine their internal performances. Nevertheless, phase delay of electron components may result in some serious hazards. This paper describes a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis is provided to clarify the influences of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and zero rate output (ZRO) utilizing force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between amplitude-frequency, phase-frequency of MEMS gyroscope and the phase relationship of the whole control loop, a real-time correction system is proposed to automatically adjust the phase reference value of phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results show that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO is decreased by 755% to 0.095°/s. This correction system realizes a small angle random walk of 0.978°/√h, and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. Besides, the thermal drift of ZRO is reduced to 0.0034°/s/°C at a temperature range from -20°C to 70°C.

This article focuses on the variation of how the U.S. Circuit Court of Appeals uses the language of trauma in gender-based asylum claims. Gender-based asylum claims include female genital mu-tilation (FGM), domestic violence, forced marriage, coercive population control (CPC) in the form of forced abortions and forced sterilizations, and rape. The Circuit Courts have reviewed appeals from petitioners with asylum claims since 1946, yet the language of trauma did not appear in the Court’s decisions until 1983. From 1983-2023 only 385, 3.85% or less, of the over 10,000 asylum cases before the Circuit Courts used the language of trauma in its legal interpretation of persecution. I have identified 101 gender-based asylum cases that were reviewed by one of the eleven U.S. Circuit Court of Appeals that apply the language of trauma in its legal interpretation of persecution for this analysis. This study found that U.S. Circuit Courts use the language of trauma in four ways: precedent cases, psychological trauma, physical trauma, and policies and reports when reviewing gender-based asylum claims.

The intravenous cocaine self-administration model is widely used to characterize the neurobiology of cocaine seeking. When studies are aimed at understanding relapse to cocaine-seeking, a post-cocaine abstinence period is imposed, followed by “relapse” tests to assess the ability of drug-related stimuli (“primes”) to evoke the resumption of the instrumental response previously made to obtain cocaine. Here we review this literature on the impact of post-cocaine abstinence procedures on neurobiology, finding that the prelimbic and infralimbic regions of the prefrontal cortex are recruited by extinction training, and are not part of the relapse circuitry when extinction training does not occur. Pairing cocaine infusions with discrete cues recruits the involvement of the NA which, together with the dorsal striatum, is a key part of the relapse circuit regardless of abstinence procedures. Differences in molecular adaptations in the NA core include increased expression of GluN1 and glutamate receptor signaling partners after extinction training. AMPA receptors and glutamate transporters are similarly affected by abstinence and extinction. Glutamate receptor antagonists show efficacy at reducing relapse following extinction and abstinence, with a modest increase in efficacy of compounds which restore glutamate homeostasis after extinction training. Imaging studies in humans reveal cocaine-induced adaptations that are similar to those produced after extinction training. Thus, while instrumental extinction training does not have face validity, its use does not produce adaptations distinct from human cocaine users.

Durum wheat is an important staple food used to obtain several products. At first the wheat is milled to obtain different products: bran, semolina and flour. These products are the base of several artifacts with varying properties both from a nutritional point of view and flavoring characteristics. It is known that most elements concentrate in the outer layers of the wheat seed (pericarp and aleurone) so that the content of the elements vary a lot in the ground products. The present study investigates the characterizing elements of the milled products and the effect of cultivation protocol applied. We measured, by ICP-OES, the concentration of 28 elements in the whole seed and in any grinding products; the results show that only few elements characterize each product. Few elements, but different for each product, permit to disclose the kind of agri-cultural method used: organic or conventional protocol. Five elements: B, Cd, Cu, K, Se, are the most important to distinguish between organic and conventional agriculture by PCA and PLS analysis; these elements also permit some differentiation of products.

For better understanding the corrosion and corrosion products behavior in the primary circuit of lead-bismuth eutectic (LBE) coolant reactor, the concentration distribution of soluble impurities and the transport of solid particles are investigated through finite-element method. An axisymmetric model of the primary circuit of LBE reactor was constructed to accelerate the calculation the thermal hydraulic filed of circuit. The saturation concentration of solute Fe, Cr and Ni in LBE coolant are identified through the equilibrium of their oxides and PbO. And the very different saturation concentrations of Fe/Cr/Ni in LBE will lead to significant element selective corrosion. The migration of solid oxides particles in the primary circuit is also investigated by the Euler-Lagrange tracing model. The simulation shows that driving force for the movement of particles &gt;100 μm is buoyancy, which lets particles float on a free surface, while particles &lt;10 μm tend to suspend in coolant. However, the behavior of particles also depends on the formation position, the particles formed above the core have the high possibility of re-entering in the core.

Face milling is a well known commercial process highly used in heavy industries that consumes high amount of power. Besides power issue, modern manufacturing industries are aiming for per part cost reduction keeping the product quality unimpaired. Unexpectedly if the part is rejected in any stage of manufacturing, the cost of manufacturing dramatically increases. Major cause of part rejection is excessive tool wear that imparts poor surface profile or catastrophic tool failure that causes adherence of broken tool debris onto machined surface. Furthermore, the tool wear is associated with sliding distance (frictional distance) and the tool life quantifies the cost of tools. As such, from the perspective of manufacturing industries it is imperative to optimize the surface quality parameter, cost of part, power consumption, and material removal – this is exactly what is accomplished here. By this work, it is possible to conserve power consumption, produce parts with lower cost, manufacture with uncompromising surface quality and enhanced material removal rate. Moreover, as intermediate factors of interest, the influences of sliding distance, tool life and tool flank wear on the overall machining performance are evaluated. The multi-objective optimization by Grey Relational Analysis (GRA) revealed that for improved product performance and fast manufacturing (case 1) optimum results are: feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min and cutting length l = 0.5 mm; for resource conservation (case 2) the optimum results are: feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, cutting length l = 0.5 mm.

Hot stamping dies include cooling channels to treat the formed sheet. The optimum cooling channels of dies & molds should adapt to the shape and surface of the dies, so that a homogeneous temperature distribution and cooling are guaranteed. Nevertheless, cooling ducts are conventionally manufactured by deep drilling, attaining straight channels unable to follow the geometry of the tool. Laser Metal Deposition (LMD) is an additive manufacturing technique capable to fabricate nearly free-form integrated cooling channels and therefore shape the so-called conformal cooling. The present work investigates the design and manufacturing of conformal cooling ducts, which are additively built up on hot work steel and then milled in order to attain the final part. Their mechanical performance and heat transfer capability has been evaluated, both experimentally and by means of thermal simulation. Finally, conformal cooling conduits are evaluated and compared to traditional straight channels. The results show that LMD is a proper technology for the generation of cooling ducts, opening the possibility to produce new geometries on dies & molds and, therefore, new products.

Modeling and assessing the sustainability of machining systems has been considered to be a crucial approach to improving the environmental performance of the machining processes. As the most common machining system, the computer numerical control (CNC) milling system is a typical man-machine cooperative system where the activities of the machine tool and operator generate material and energy consumption. However, the energy consumption of the operator in the CNC milling system has often been ignored in most existing research. Therefore, existing methods fail to provide a comprehensive understanding of the sustainability of the CNC milling system. To fill this gap, an exergy loss assessment method is proposed to investigate the sustainability of the CNC milling system, where the energy consumption of the operator, the energy consumption of the machine tool, and material consumption are taken into consideration. The key performance indexes of the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss, and the specific exergy loss (SEL) are analyzed and modeled. To demonstrate the feasibility of the proposed method, a case study was carried out on a three-axis machining center (XH714D), in which SEL was found to be 88.04J/mm3. The proposed method is effective to assess the sustainability of the CNC milling system, and the established exergy loss models build a good basis for exergy efficiency optimization.

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong com-pound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the Electromagnetic Interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, common mode rejection ratio , gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain Computer Interfaces and neurofeedback training systems.

In general, a superconductor has zero resistance, although it requires significant refrigeration or high pressures with high manufacturing costs, which prevents it into practical applications. In other words, solving these issues implies main superconducting researches. To solve these problems, this paper describes a new type of superconductivity, which is independent for temperatures and which operates without pressures. The principles of the presented system are as follows:First a voltage source, a current source and a load are connected in series. Then, the voltage of the voltage source is adjusted to balance the voltage of the load. Under this condition, the balance of the two voltages provides a zero voltage between the taps of the current source and the generated current from the voltage source becomes zero because of the internal infinite resistance of the current source. As a result, the electric powers generated by the two sources are zero, and therefore, the load cannot generate Joule heating because of energy conservation. However, the current from the current source (not the voltage source) is not zero; therefore, we can predict that the resistance of the load must be zero. As a theory, we derived a new electric field and transient attractive force, which result in a very short coherence of an electron pair because there is not the Coulomb repulsive force due to the existence of the above transient attractive force. Note that both the forces are derived by the Poisson equation, which implies that they cannot be compatible. Therefore, the pair combination energy from spins becomes extremely strong, which is not destroyed by the normal heat energy. Moreover, every center-of-mass motion of electron pair results in the Bose-Einstein condensation and the macroscopic wave function, which produces the London equation (i.e., the Meissner effect). Moreover, by introducing the equivalent circuit, this paper conducted numerical calculations. As a result, we could derive numerically zero resistance and responses for additional static magnetic fields as a discharged current, which implies the Meissner effect. Note that this paper has prepared Appendix section, which provides a guide to reproduce actual experiments and preliminary experimental results. These results in the Appendix indicate the zero resistances and Meissner effects.

In this paper, we have shown the electronic circuit equivalence of a mechanical system consists of two oscillators coupled with each other. The mechanical design has the effects of the magnetic, resistance forces and the spring constant of the system is periodically varying. We have shown that the system’s state variables, such as the displacements and the velocities, under the effects of different forces, lead to some nonlinear behaviors, like a transition from the fixed point attractor to the chaotic attractor through the periodic and quasi-periodic attractors. We have constructed the equivalent electronic circuit of this mechanical system and have verified the numerically obtained behaviors using the electronic circuit.

Barriers to inventing electronic devices involve challenges of iterating electronic designs due to long lead times for professional circuit board milling or high-costs of commercial milling machines. To overcome these barriers this study provides open source (OS) designs for a low-cost circuit milling machine. First, design modifications for mechanical and electrical sub-systems of the OS D3D Robotics prototyping system are provided. Next, Copper Carve, an OS custom graphical user interface, is developed to enable circuit board milling by implementing backlash and substrate distortion compensation. The performance of the OS D3D circuit mill is then quantified and validated for: positional accuracy, cut quality, feature accuracy and distortion compensation. Finally, the return on investment is calculated for inventors using it. The results show by properly compensating for motion inaccuracies with Copper Carve, the machine achieves a motion resolution of 10 microns, which is more than adequate for most circuit designs. The mill is at least five times less expensive than all commercial alternatives and the material costs of the D3D mill are repaid from fabricating 20-43 boards. The results show that the OS circuit mill is of high-enough quality to enable rapid invention and distributed manufacturing of complex products containing custom electronics.

The article is focused mainly on verifying the suitability of data from experimental milling heat-treated beech wood and on investigation of the effect of technical and technological parameters of milling on the energy consumption of this process. The independent parameters of machining process are cutting speed, feed speed, rake angle, and hydrothermal modification of experimental wood material. Based on analysis of variance it can be argued that the greatest statistically significant effect on energy consumption have cutting speed and rake angle of the tool while the feed speed had the least influence. The measured data of cutting power during milling were used to build a regression model and validate it, while the most suitable type of model with correlation of 87 % is Classification and Regression Tree followed by model created by Random Forests method.

Form deviation generated during the milling profile process poses challenges to the precision and functionality of industrial fixtures and product manufacturing across various sectors. The inspection of contour profile quality often relies on commonly employed contact methods for measuring form deviation, but these methods frequently face limitations that can impact the reliability and overall accuracy of the inspection process. This paper introduces a novel approach, the novel intelligent inspection method (NIIM), developed to accurately inspect and categorize contour profiles in machined parts manufactured through the milling process by computer numerical control (CNC) machines. The NIIM integrates a calibration piece, a vision system (RAM−StarliteTM), and machine learning techniques to analyze the line profile and classify the quality of contour profile deformation generated during CNC milling. The calibration piece is specifically designed to identify form deviations in the contour profile during the milling process. The RAM−StarliteTM vision system captures contour profile images corresponding to curves, lines, and slopes. An algorithm generates a profile signature, extracting Fourier descriptor features from the contour profile to analyze form deviations when compared to an image reference. A feed-forward neural network is employed to classify contour profiles based on quality properties. Experimental evaluations involving 60 machined calibration pieces, resulting in 356 images for training and testing, demonstrate the accuracy and computational efficiency of the proposed NIIM for profile line tolerance inspection. Results demonstrate that the NIIM offers 96.99% accuracy, low computational requirements, 100% inspection capability, quality classification.

The present work was aimed at the investigation of effect of High Energy Ball Milling (HEBM) time on the sintering kinetics, structure, and properties of heavy tungsten alloy (HTA) W-7%Ni-3%Fe. The HTA samples were obtained from the nanopowders (20-80 nm) by conventional liquid phase sintering (LPS) in hydrogen and by Spark Plasma Sintering (SPS) in vacuum. The HTA density was shown to depend on the HEBM time non-monotonously that originates from the formation of non-equilibrium solid solutions in the W-Ni-Fe systems during HEBM. The SPS kinetics of the HTA nanopowders was shown to have a two-stage character, the intensity of which depends on the Coble diffusion creep rate and on the intensity of diffusion of the tungsten atoms in the crystal lattice of the -phase. The kinetics of sintering of the initial submicron powders have a single-stage character originating from the intensity of the grain boundary diffusion in the -phase. The dependencies of the hardness and of the yield strength on the grain sizes were found to obey the Hall-Petch relation. The hardness, strength, and dynamic strength in the compression tests of the fine-grained tungsten alloys obtained by SPS and LPS were studied.

This paper aims to study the surface homogenization and integrity of Ti-6Al-4V alloy by longitudinal-torsional coupled ultrasonic vibration assisted ball-end milling. A method of continuous processing between the flat surface and freeform surface connection is proposed by using ultrasonic vibration assisted ball-end precision milling, during this process, it is not necessary to exchange the cutting tool. The way has been explored for changing the homogenization of surface on Ti-6Al-4V by ultrasonic vibration-assisted milling (UVAM). Cutting experiments employing three parameters, cutting speed, feed rate and depth of cut and two types of machining forms using ball-end milling with UVAM and conventional milling (CM) respectively. The high frequency cutting force, finished surface roughness, topography and residual stresses on the surface and tool wear have been measured by advanced instruments. Particularly, adopting the high frequency cutting force measurement system, it is concluded cutting force in ball-end milling decreased significantly using UVAM as against CM. Moreover, the surface roughness by UVAM with ball-end milling is much better than the CM at a high cutting speed. However, an opposite trend is observed at a low cutting speed. Especially, there is a steep decrease from Ra 0.828 μm average value at 4000 rpm to Ra 0.129 μm average value at 5000 rpm. At the same time, the homogenization of surface roughness and residual stresses decrease significantly in UVAM as compared to which in CM when taking the transversal-longitudinal ratio into consideration. Cutting experiments and measuring results are demonstrated the validity and feasibility of UVAM with ball-end milling, and this method enjoys significant advantages compared to CM process.

South Africa (SA) is grappling with a severe food insecurity crisis exacerbated by socioeconomic challenges. This resulted in the Department of Basic Education (DBE) advocating for the establishment of vegetable gardens at schools. However, information on the suitability of the soils in SA for sustainably growing Beetroot is unavailable. This study aimed to assess the suitability of soils for sustainable Beetroot production at various schools in the Kgakotlou circuit. Four Secondary Schools were selected: Mothimako, Madipoane, Klaas Mothapo and Phomolong. A detailed soil survey was carried out to study soils in vegetable gardens. Soil samples were collected for laboratory analysis of physicochemical properties. The soil suitability was evaluated using the physicochemical properties of the soils and optimal soil requirements for Beetroot production. We found various soils in the schools, including Cambisols (Hutton and Nkonkoni), Leptosol (Glenrosa), Plinthosol (Westleigh), and Acrisols (Tshiombo and Tubatse). Portions of the gardens on Hutton and Westleigh soil were moderately suitable (S2), limited by electrical conductivity (EC). Meanwhile, portions of Tshiombo, Tubatse, and Nkonkoni were marginally suitable (S3), limited by pH and EC. Portions on Glenrosa soil at Klaas Mothapo and Phomolong were not suitable (NS) and were limited by shallow depth, soil pH and EC. The results reveal the importance of considering soil suitability before establishing vegetable gardens in school settings. Indexing soil suitability using the physicochemical properties of soil resources for sustainable beetroot production is proposed for schools in the Kgakatlou circuit and other parts of SA.

Electrical rotating machines like Induction Motors (IMs) are widely used in several industrial applications since their robust elements, provide high efficiency and give versatility in industrial applications. Nevertheless, the occurrence of faults in IMs is inherent to their operating conditions, hence, Inter-turn short-circuit (ITSC) is one of the most common failures that affect IMs and its appearance is due to electrical stresses leads to the degradation of the stator winding insulation. In this regard, this work proposes a diagnosis methodology for the assessment and detection of incipient ITSC in IMs, the proposed method is based on the processing of vibration, stator currents and magnetic stray-flux signals. Certainly, the novelty and contribution include the characterization of different physical magnitudes by estimating a set of statistical time domain features, as well as, their fusion and reduction through the Linear discriminant Analysis technique within a feature-level fusion approach. Furthermore, the fusion and reduction of information from different physical magnitudes leads to perform the automatic fault detection and identification by a simple Neural-Network (NN) structure. The proposed method is evaluated under a complete set of experimental data and the obtained results demonstrate that the fusion of information from different sources (physical magnitudes) allows to improve the accuracy during the detection of ITSC in IMs , the results make this proposal feasible to be incorporated as a part of condition-based maintenance programs in the industry.

Modern technologies for recycling electronic waste (e-waste) impose high economic efficiency and environmental safety requirements. Among existing technologies, hydrometallurgy is considered the most promising technology for e-waste recycling. Increasing attention to the chlorination method is associated with the complex recycling of low-grade ores containing noble metals and secondary polymetallic raw materials. In this paper, we propose a new scheme for leaching metals from computer printed circuits (PCBs) pre-crushed in a disintegrator: the processes of chlorine production and hydrochlorination are implemented in one reactor under the action of alternating current (AC) of industrial frequency (50 Hz). It was found that complete leaching of gold is achieved from fine fractions of raw materials containing 0.03% and 0.01% of the gold at an experiment duration of 2 hours, a current density of 0.66 A·cm-2, and a solid/liquid ratio of 8.6 g·L-1. Under the same conditions of the electrochemical leaching process from the fraction of raw material with a gold content of 0.08%, the degree of metal leaching is 80.5%. At the same time, with an increase in the copper content in the raw material from 1.40% to 6.13%, an increase in the degree of its leaching from 84.6% to 95.2%, respectively, is observed. These results will serve as a foundation for developing a complex technology for recovering valuable metals from PCBs.

Nano Silicon carbide reinforced aluminum (Al/nanoSiC) metal matrix composites are attractive because of their superior properties such as high strength and stiffness, Application of aluminum in technological and structural application is growing steadily. The major limitation for metal matrix nano composites, however, is their propensity to brittle fracture. The new technologies and new materials are two basic aims for companies. In this research, the effect of addition Al/SiC nano particles on microstructure and mechanical properties of pure aluminum has been investigated. Pure aluminum powder and various fractions of SiC particles with an average diameter of 50 nm were milled by a high-energy planetary ball mill to produce nanocrystalline Al–SiC nanocomposite powders. Pressing and sintering applied to consolidate powders to tablet shape. Then the samples were rolled to cylindrical shape. The nano SiC Percentage were 0%, 2.5%, 5%, 7.5%, 10% , 12,5% and 15%. Mechanical tests such as tensile, hardness, fracture toughness and young’s modules measurement carried out to study the mechanical behavior of each alloy. Scanning electron microscopy was used to study the morphology and microstructure of nanocomposite powders and bulk samples. The role of wt% fraction of SiC nanoparticles was investigated. The results shows that the addition of SiC nano particles has significant influence on the microstructure and mechanical properties of composites and usually the optimum properties depends on wt% SiC.

The rising world population has made it imperative to get rid of time-consuming and non-economical agricultural practices. Thus, advances in Internet of Things (IoT) technology have recently propelled significant advancements in agriculture, similar to several other sectors. Through the combination of IoT and Farm Management Information Systems (FMIS), field data can be automatically collected, stored, analysed and accessed by farmers in real-time. In this paper, we present Proof-of-Concept (PoC) IoT circuit and FMIS web app for precision agriculture. The IoT circuit incorporates sensors, microcontroller and Wi-Fi module, which acquire and transfer field data to the FMIS web app. We designed and simulated the IoT circuit using Proteus, Arduino Uno, and Arduino Integrated Development Environment (IDE). The FMIS PoC web app was modelled with relevant Unified Modeling Language (UML) diagrams and Django (a Python framework) was employed to implement the app. Our simulation result illustrates how essentila field parameters can be monitored remotely and seamlessly by agriculture practitioners. It further provides a blueprint for real-time precision agriculture at scale and could serve as a learning aid for students in engineering and agricultural science.

Abstract: Circuit breakers are affected by multiple lightning strikes after the breaker has been tripped and can break down again, which will reduce the life of the circuit breaker and threaten the stable operation of the power system. Aiming at this problem, the paper obtained the temperature diffusion process of the inrush current process of circuit breaker opening and breaking through the schlieren technique, and combined with the existing image recognition technology to obtain the temperature characteristics of the airflow in the air gap of the contact, and the characteristics of the airflow flow. The results of the study show that the circuit breaker breakdown process generates a shock wave with a velocity approximately equal to the speed of sound under the same conditions. The maximum velocity of the airflow boundary diffusion is about 1/4 of the speed of sound under the same condition, and it decays very fast, reducing to the airflow drift velocity within 10ms after breakdown. The maximum temperature of the thermals is concentrated between 6000 and 8000 K and the temperature change is approximately inversely proportional to the square of time. The research provides the basis for the design of circuit breaker contact structure, opening speed optimization method, interrupter chamber and insulation design optimization.

The role of fractional calculus in circuit systems has received increased attention in recent years. In order to evaluate the effectiveness of time-domain calculation methods in the analysis of fractional-order piecewise smooth circuit systems, an experimental prototype is developed and the effects of three typical calculation methods in different test scenarios are compared and studied in this paper. It is proved that Oustaloup’s rational approximation method usually overestimates the peak-to-peak current and brings in pulse-voltage phenomenon in piecewise smooth test scenarios, while the results of two iterative recurrence-form numerical methods are in good agreement with the experimental results. The study results are dedicated to provide a reference for efficiently deploying calculation methods in fractional-order piecewise smooth circuit systems. Some quantitative analysis results are concluded in this paper.

Ensuring a protection scheme in DC distribution is more difficult to achieve against pole-to-ground fault than in AC distribution system because of the absence of zero crossing points and low line impedance. To complement the major obstacle of limiting the fault current, several compositions have been proposed related to mechanical switching and solid-state switching. Among them, solid-state circuit breakers(SSCBs) are considered a possible solution to limit fast fault current. However, they may cause problems in circuit complexity, reliability and cost-related troubles due to the use of multiple power semiconductor devices and additional circuit configuration to commutate current. This paper proposes the SSCB with a coupled inductor(SSCB-CI) which has symmetrical configuration. The circuit is comprised of passive components like commutation capacitors, a CI and damping resistors. Thus, proposed SSCB-CI offers the advantages of simple circuit configuration and fewer utilized power semiconductor devices than another typical SSCBs in LVDC microgrid. For analysis, six operation states are described for the voltage across main switches and fault current. The effectiveness of the SSCB-CI against a short-circuit fault is proved via simulation and experimental results in a lab-scale prototype.

The power converter is the significant device in a wind power system. Wind turbine will be shut down and off grid immediately with the occurrence of the IGBT module open-circuit fault of power converter, which will seriously impact the stability of grid and even threaten personal safety. However, in the existing diagnosis strategies of power converter, there are few single and double IGBT modules open-circuit fault diagnosis methods producing negative results including erroneous judgment, omissive judgment and low accuracy. In this paper, a novel method to diagnose the single and double IGBT modules open-circuit faults of the permanent magnet synchronous generator (PMSG) wind turbine grid-side converter (GSC) is proposed. Above all, collecting the three-phase current varying with wind speed of 22 failure states including a normal state of PMSG wind turbine GSC as the original signal data. Afterward, the original signal data are decomposed by using variational mode decomposition (VMD) to obtain the mode coefficient series, which are analyzed by the proposed method base on fault trend feature for extracting the trend feature vectors. Finally, the trend feature vectors are used as the input of deep belief network (DBN) for decision-making and obtaining the classification results. The simulation and experimental results show that the proposed method can diagnose the single and double IGBT modules open-circuit faults of GSC, and the accuracy is higher than the benchmark models.

Milling machines have made denture fabrication possible with high accuracy in a short time. However, the relationship between the milling conditions, accuracy, and milling duration has not been clarified. This study aimed to clarify the effects of milling conditions on surface roughness and milling duration. The specimen was designed using a CAD software, and milled using PMMA disks. In milling, the parameters of finishing the specimen surface were adjusted. Three different spindle speeds and four different feed rates were set. Twelve combinations of each parameter were used for milling, and the surface roughness and milling duration were measured. Results showed that the surface roughness significantly increased with the feed rate on the slopes of the specimen. The surface roughness differed with the spindle speed on the left and right slopes. The spindle speed and feed rate did not affect the surface roughness on the flat surface. The milling duration was not affected by spindle speed but decreased as the feed rate increased. In conclusion, by increasing both the spindle speed and feed rate, the milling duration could be shortened while maintaining a constant surface quality. The optimum milling conditions were a spindle speed of 40,000 rpm and feed rate of 3,500 mm/min.

Repeated cocaine produces an enhanced locomotor response (sensitization) paralleled by biological adaptations in the brain. Previous studies demonstrated region-specific responsiv-ity of adenosine monophosphate-activated protein kinase (AMPK) to repeated cocaine. AMPK maintains cellular energy homeostasis at the organismal and cellular level. Here we first quanti-fied changes in phosphorylated (active) and total AMPK in the cytosol and synaptosome of the medial prefrontal cortex, nucleus accumbens, and dorsal striatum following acute or sensitizing cocaine injections. Rats were given cocaine (15 mg/kg, IP) or saline for six days with a challenge injection on day seven resulting in four groups: saline-saline, saline-cocaine, cocaine-saline, and cocaine-cocaine. Brain region and cellular compartment selective changes in AMPK and pAMPK were found with some differences associated with acute withdrawal versus ongoing cocaine treatment. Other rats were pretreated with the indirect AMPK activator metformin. Metformin potentiated the locomotor activating effects of acute cocaine but blocked the development of sensi-tization. Sex differences largely obscured protein level treatment group effects, although pAMPK in the NAc shell cytosol was surprisingly reduced by metformin in rats receiving repeated co-caine. These data inform our understanding of AMPK activation dynamics in subcellular com-partments and provide additional support for repurposing metformin for cocaine use disorder.

Surface Plasmon Resonance (SPR) based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still limited and almost confined to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic circuit to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30 to 50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration.

The purpose of this study was to investigate the effect of circuit training on β-amyloid, BDNF, and cognitive function in untrained obese elderly Korean women. The subjects for the study were aged 65–70 years, composed of the circuit training group(n=12) and control group(n=11). The 60-minute combined exercise was performed 3 times per week for 16 weeks. Exercise intensity was progressively increased from 40% HRR to 70% HRR. The test data were analyzed by paired t-test, independent t-test, and two-way repeated measures ANOVA, and the alpha level of .05 was set for all tests of significance. The findings of this study were as follows: β-amyloid significantly decreased after the exercise group had compared to before the exercise and BDNF and cognitive function significantly increased after the exercise group had compared to before the exercise. However, there were no significant changes in β-amyloid, BDNF, and cognitive function in the control group Therefore, it is suggested that the circuit training used in this study could be an effective exercise method for improving the risk factors of cognitive impairment in obese elderly Korean women.

Reliable motor control design is a critical part of the electric vehicle application. Control techniques and motor control devices play an important role in achieving system reliability. In this study, motor control devices have been proposed to implement control techniques in sensorless PMSM. Motor control devices including PWM signal generation by FPGA, gate driver circuit (GDC), and power inverter were developed to be integrated into single-stage motor control devices for sensorless motor control applications. Improvements in GDC design have been the focus to increase the performance of the motor control devices used. Switching losses due to the parasitic elements caused ringing switching behavior of the power inverter circuit, which reduces the performance when the system is integrated. Moreover, in the implementation of sensorless motor control using observer techniques, these conditions affect the accuracy of rotor position estimation, which uses the current or voltage information of the power converter as a variable in the observer design model. Therefore, a GDC design using IR2110 with additional ringing suppression circuit configuration was proposed for the application of motor device control topology to improve the performance of sensorless motor control system. Furthermore, the reduction of switching losses, reduction of current distortion, and accuracy of rotor position information were confirmed by experimental results.

To address the limitations of the current anodes of Li+-ion batteries (LIBs), a Ge/GeO2/Carbon (Ge@GeO2-C) composite was designed by introducing a high-energy ball-milling process for advanced LIBs. Ge@GeO2-C is prepared and characterized by XPS, XRD, SEM, and TEM, which facilitate synthesis and provide controllability with respect to milling time. Interestingly, as the ball-milling time increased, the proportion of metallic Ge increased during the carbon thermal reduction reaction. The electrochemical characteristics of Ge@GeO2-C are assessed using differential capacity analysis (dQ/dV) and galvanostatic charge-discharge techniques to confirm its viability as an anode material in LIBs. The results demonstrated decent initial and secondary capacities of approximately 1800 mAh g-1 (for the first cycle) and 838 mAh g-1 (for the second cycle) at a rate of C/60 by the reaction between Ge and the Li-Ge complex. Furthermore, postmortem characterization was performed to gain an understanding of the material, suggesting future prospects for advanced LIBs.

In this paper, existence and stability results of non-local integro-differential equation with Hilfer derivative of order ω∈(1,2) have been investigated. In this derivative is applied in RLC circuit equation of various fractional order. To proposed problem the existence solutions are derived using Schaefer’s fixed point theorem and the Banach contraction principle is using for uniqueness results. To demonstrate the effectiveness and applicability of our theoretical conclusions and two-step Lagrange polynomial interpolation were used to solve four numerical results.

Two region asymmetric polymers PR2F and PR1F with three repeat units of A-D-A, π-D-A, and π-D-π along the polymer backbone were attained by polymerizing different fluorinated benzothiadiazole-thiophene units, FBT-T and 2FBT-T units (A–π), with benzodithiophene unit (D), respectively. Here, the new region asymmetric polymers were in contrast to the traditional polymers featuring a D–A or D–π–A–π backbone. Both the region asymmetric polymers showed a low lying of HOMO energy level in relation to that of the PC61BM acceptor and then obtained the high open-circuit voltage of ~1 V in both PR2F and PR1F devices. Bulk-heterojunction devices based on PR2F with difluorinated BT exhibited an appreciable power conversion efficiency (PCE) of 4.73% due to the relatively high and balanced charge carrier mobilities, while the mono-fluorinated BT polymer PR1F-based devices gave a lower PCE of 2.92%. These results indicate that the region asymmetric conjugated polymer is a promising class of materials for polymer solar cell applications, and it is significant to further understand the influence of polymer structure on optoelectronic properties.

Short-circuit blowing is an important technical means to ensure the rapid surfacing of submersible. In order to study the impact of seven multiple manipulation factors of three levels on blowing, a proportional short-circuit blowing model test bench had been built and L18(37) orthogonal experiments were carried out; then, using Back propagation neural network and Pearson correlation analysis, the experimental data were trained and predicted, correlation between individual factor and blowing was further studied as supplement of orthogonal experiments. It had been proved that both multi-factor combination and individual including blowing duration, sea tank back pressure, the gas blowing pressure of the cylinder group, and sea valve flowing area had larger influence, whose correlation coefficients were 0.6535, 0.8105, 0.5569, 0.5373, of which the F-ratio of blowing duration is over critical value 3.24. And statistical evaluation indicators of Back propagation neural network were between 10e-2 and 10e-13, relative error was less than 3%, and prediction error accuracy was 100%. Based on the results above, a reasonable prediction method for submersible short-circuit blowing had been formed and suggestions on engineering design and operations were proposed, including advantage of short-circuit blowing method, initial condition settings and manipulation strategy.

The thermoelectric generator (TEG) stands out in many energy harvesters due to its simple structure, small size, etc. However, previous studies rarely probe into the influence of TEG internal resistances on extracting maximum power from TEG, and tracking efficiency is limited. By analyzing the relationship between the tracking efficiency and the TEG internal resistances, a time exponential rate perturbation and observation (P&amp;O) technology is proposed to achieve maximum power point tracking (MPPT) for a wide resistance range of TEG. Using the time exponential rate P&amp;O, the MPPT circuit observes the power change by comparing PMOS on-time and perturbs the power by adjusting NMOS on-time exponentially. The MPPT circuit is implemented in a 110nm CMOS process. The tracking efficiency keeps a high level from 98.9 to 99.5%. The applicable range of the TEG resistance is from 1 to 12Ω, which is enhanced at least 2.2 times.