Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlling electrical circuit of electric motor on igbt transistors

Purpose. Development and analysis of the operation of an electrical circuit for controlling a 700 W direct current electric motor using a contactor on IGBT transistors for operation in diesel locomotives. Methodology. Analytical and computational methods for developing and analyzing the operation of an electrical circuit using a contactor on IGBT transistors. Findings. An electrical circuit for controlling a 700 W DC motor using IGBT transistors was developed. The circuit allows you to replace electromagnetic contactors with IGBT transistors to improve the technical characteristics and performance of the electric motor. The use of IGBT transistors allows you to avoid burning of contact groups in comparison with an electromagnetic contactor. A graphical analysis of the transient processes during switching on and off of the electric motor using a circuit based on IGBT transistors was carried out. The analysis of the load characteristic of the electric motor at start-up shows that in the initial section the voltage increases according to a linear law. After the initial increase in voltage, it reaches the set value and the electric motor operates in the operating mode. The analysis of the load characteristics of the electric motor when it is turned off shows, that when the power is turned off, the motor can’t stop immediately, as the phenomenon of self-induction occurs. When the external voltage is turned off, its change on the electric motor occurs according to the exponential law. It is shown that for controlling the operation of the electric motor, it is more appropriate to use an electric circuit based on IGBT transistors, which provides conditions for more stable and safe operation of the electric motor. Using the electrical circuit allows you to find quickly malfunctions for their further elimination. The electrical circuit allows you to avoid physical wear of its electrical elements. Originality. An electrical circuit for controlling an electric motor based on modern electronic components has been developed, which allows the use of IGBT transistors instead of electromagnetic contactors. On the basis of the analytical and calculation method and graphical analysis, the expediency of using IGBT transistors instead of electromagnetic contactors has been proven. Practical value. The developed electrical circuit can be applied to control a 700 W direct current electric motor for operation in diesel locomotives. The proposed electrical circuit allows to increase the mobility of repairs in the event of a malfunction by replacing the corresponding unit.
Radiation of a pulsating portion of a sphere: application to horn radiation

This paper introduces the modelling of the radiation of a sphere, part of which, S0, is pulsating with an uniform velocity while the other remains motionless. Velocity and pressure can be expressed analytically in the space outside the sphere using spherical harmonic decomposition. The radiation impedance can then be deduced, providing a model approximating the radiation of horns, accounting for the curvature of the wavefront. The angular dependence of the radiation impedance is eliminated by averaging on S0 to remain compatible with most of simplified models of horns whose equations depend on a unique space variable. This averaging provides an analytical expression representing the optimal approximation, minimizing the mean square error. Three simple parametric models, which are inexpensive to simulate and approximate this model of impedance with various precisions, are proposed. They are well adapted to real-time applications, such as the simulation of wind instruments. Their parameters are given according to the geometrical characteristics of S0 and the stability is checked. The error introduced by these models is negligible compared to the original due to averaging on S0.
YOLOV5-based traffic sign detection algorithm

For the problems of low recognition accuracy and slow detection speed in traffic sign recognition tasks, an improved YOLOv5-based traffic sign recognition model is proposed. The first step is to replace Shufflenetv2 with a lightweight network. Firstly, Shufflenetv2, a lightweight network, is used to replace the YOLOv5 backbone network to improve the detection speed of the model; then, BiFPN is used as the feature fusion structure in the Neck layer to achieve multi-scale fusion; finally, K-means algorithm is used to reacquire the initial anchor frame value of the model. The experimental results show that the recognition accuracy of the improved network model is better than that of the original YOLOv5, and the recognition of traffic signs is improved.
The universal optimal relations of the allocation and effectiveness of the heat exchangers for power plants with n Carnot-like cycles

espanolSe optimiza un modelo de planta de potencia irreversible con n ciclos tipo Carnot. Las irreversibilidades de cada uno de los ciclos son: transferencia finita de calor entre el fluido de trabajo y los depositos de temperatura, disipacion del fluido de trabajo y fuga de calor entre ambos depositos; es extendido a dos o mas de este ciclo combinado. Aplicando el Principio de Bellman, encontramos las relaciones de recurrencia optimas para la dimension y efectividad de los intercambiadores de calor para modelo combinado. La optima dimension y efectividad se determina mediante dos reglas de diseno, aplicadas alternativamente: conductancias termicas restringidas o area total constante. Las relaciones optimas para la dimension o efectividad obtenidas para este modelo combinado son invariantes a la potencia y eficiencia y a la ley de transferencia de calor. EnglishA model of irreversible Carnot-like power plant with n Carnot-like cycles is optimized. The irreversibilities of each cycle are: finite rate heat transfer between the working fluid and the external heat sources, internal dissipation of the working fluid, and heat leak between reservoirs; is extended to two or more of this combined model. Applying the Bellman’ Principle, we find the optimal recurrence relations for the allocation of the heat exchangers for thes power plants. The optimal allocation or effectiveness is determined by two design rules, applied alternatively: internal thermal conductance fixed or areas fixed. The optimal recurrence relations obtained for this combined model are invariant to the power and efficiency and to the heat transfer law.
GAMIFICANDO O ENSINO QUÍMICA: UM RELATO DE EXPERIÊNCIA DURANTE O ENSINO REMOTO

O distanciamento social imposto pela pandemia da Covid-19 trouxe profundas mudanças sociais, e para a educação não foi diferente. A retomada das aulas nesse novo contexto exigiu uma rápida adaptação e apropriação, por parte dos professores, de metodologias e tecnologias digitais até então pouco ou nunca exploradas. Neste contexto, o presente trabalho visa apresentar e discutir os resultados da implementação de atividades gamificadas como elemento de mediação pedagógica em uma disciplina de Química para um curso da área de Ciências Rurais. Sustentados na metodologia da pesquisa baseada em Design-Based Research, a partir do contexto pandêmico, as atividades foram desenvolvidas, com auxílio da ferramenta Google Forms, com o objetivo de revisar os conteúdos de Preparo de Soluções, Hidrólise Salina e Equilíbrio Químico. Os resultados apontam acerca da potencialidade da ferramenta para mediação pedagógica e desenvolvimento da autonomia discente.
Application of potassium nitrate and salicylic acid improves grain yield and related traits by delaying leaf senescence in Gpc-B1 carrying advanced wheat genotypes

Grain protein content (GPC) is an important quality trait that effectively modulates end-use quality and nutritional characteristics of wheat flour-based food products. The Gpc-B1 gene is responsible for the higher protein content in wheat grain. In addition to higher GPC, the Gpc-B1 is also generally associated with reduced grain filling period which eventually causes the yield penalty in wheat. The main aim of the present study was to evaluate the effect of foliar application of potassium nitrate (PN) and salicylic acid (SA) on the physiological characteristics of a set of twelve genotypes, including nine isogenic wheat lines carrying the Gpc-B1 gene and three elite wheat varieties with no Gpc-B1 gene, grown at wheat experimental area of the Department of Plant Breeding and Genetics, PAU, Punjab, India. The PN application significantly increased the number of grains per spike (GPS) by 6.42 grains, number of days to maturity (DTM) by 1.03 days, 1000-grain weight (TGW) by 1.97 g and yield per plot (YPP) by 0.2 kg/plot. As a result of PN spray, the flag leaf chlorophyll content was significantly enhanced by 2.35 CCI at anthesis stage and by 1.96 CCI at 10 days after anthesis in all the tested genotypes. Furthermore, the PN application also significantly increased the flag leaf nitrogen content by an average of 0.52% at booting stage and by 0.35% at both anthesis and 10 days after anthesis in all the evaluated genotypes. In addition, the yellow peduncle colour at 30 days after anthesis was also increased by 19.08% while the straw nitrogen content was improved by 0.17% in all the genotypes. The preliminary experiment conducted using SA demonstrated a significant increase in DTM and other yield component traits. The DTM increased by an average of 2.31 days, GPS enhanced by approximately 3.17 grains, TGW improved by 1.13g, and YPP increased by 0.21 kg/plot. The foliar application of PN and SA had no significant effect on GPC itself. The findings of the present study suggests that applications of PN and SA can effectively mitigate the yield penalty associated with Gpc-B1 gene by extending grain filling period in the wheat.
Secure Traffic Monitoring With Spatio-Temporal Metadata Protection Using Oblivious RAM

In a traffic monitoring system, users report their driving data (e.g., routes and timestamps) to a server, aggregating them to acquire the information of interest and provide services, e.g., traffic flow prediction. Such systems have considerable promise for improving the quality of life and decreasing environmental pollution and economic losses. However, the threat to individual privacy is a critical problem that hinders the further development of such systems; e.g., the server can abuse the spatio-temporal metadata in the reports to infer sensitive user information, such as the home address. In this paper, we propose a privacy-preserving aggregation framework called secure Publish Aggregate Subscribe Data ( $s$ PASD) for traffic monitoring that can protect spatio-temporal metadata during driving data aggregation. The framework is built upon a trusted execution environment and two cryptographic tools: additive homomorphic encryption and oblivious RAM. It takes a hierarchical structure that boosts batch processing efficiency, making it more appropriate for traffic monitoring scenarios. Furthermore, we provide a cost model to derive the optimal settings from the efficiency perspective. Security analysis demonstrates that $s$ PASD can protect individual privacy by hiding spatio-temporal information during aggregation. Moreover, we implement the proposed framework in Python and evaluate it together with other competitive methods over a real-world dataset. The experiment results verify the accuracy of the proposed cost model and show that the proposed framework can gain a 51.39% saving on computation cost.
Predictive Neural Networks

Recurrent neural networks are a powerful means to cope with time series. We show that already linearly activated recurrent neural networks can approximate any time-dependent function f(t) given by a number of function values. The approximation can effectively be learned by simply solving a linear equation system; no backpropagation or similar methods are needed. Furthermore the network size can be reduced by taking only the most relevant components of the network. Thus, in contrast to others, our approach not only learns network weights but also the network architecture. The networks have interesting properties: In the stationary case they end up in ellipse trajectories in the long run, and they allow the prediction of further values and compact representations of functions. We demonstrate this by several experiments, among them multiple superimposed oscillators (MSO) and robotic soccer. Predictive neural networks outperform the previous state-of-the-art for the MSO task with a minimal number of units.
Evaluation of Chemical Compositions and the Antioxidant and Cytotoxic Properties of the Aqueous Extract of Tri-Yannarose Recipe (Areca catechu, Azadirachta indica, and Tinospora crispa)

Tri-Yannarose is a Thai traditional herbal medicine formula composed of Areca catechu, Azadirachta indica, and Tinospora crispa. It possesses antipyretic, diuretic, expectorant, and appetite-stimulating effects. This study aimed to evaluate the antioxidant activities, cytotoxicity, and chemical constituents of an aqueous extract following a Tri-Yannarose recipe and its plant ingredients. The phytochemical analysis was performed using LC-QTOF-MS. Antioxidant activities were determined using DPPH, ABTS, TPC, TFC, FRAP, NBT, MCA, and ORAC assays. Cytotoxicity was investigated using a methyl thiazol tetrazolium (MTT) assay. In addition, the relationship between the chemical composition of Tri-Yannarose and antioxidant activities was investigated by examining the structure–activity relationship (SAR). The results of the LC-QTOF-MS analysis revealed trigonelline, succinic acid, citric acid, and other chemical constituents. The aqueous extract of the recipe showed significant scavenging effects against ABTS and DPPH radicals, with IC50 values of 1054.843 ± 151.330 and 747.210 ± 44.173 µg/mL, respectively. The TPC of the recipe was 92.685 mg of gallic acid equivalent/g of extract and the TFC was 14.160 mg of catechin equivalent/g of extract. All extracts demonstrated lower toxicity in the Vero cell line according to the MTT assay. In addition, the SAR analysis indicated that prenyl arabinosyl-(1–6)-glucoside and quinic acid were the primary antioxidant compounds in the Tri-Yannarose extract. In conclusion, this study demonstrates that Tri-Yannarose and its plant ingredients have potent antioxidant activities with low toxicity. These results support the application of the Tri-Yannarose recipe for the management of a range of disorders related to oxidative stress.
Design and Implementation of Smart Agriculture System Based on Wireless Sensors Networks

: The development of information and communication technology has provided the conditions for the advancement of smart agriculture. This article focuses on designing a smart agriculture system based on wireless sensor network technology for large-scale outdoor cultivation of grain crops, aiming to provide scientific guidance for increasing crop yield and applying scientific and technological advancements to modern agricultural production. The design of the smart agriculture system in this article is divided into two parts: the perception layer and the network layer. The perception layer includes data collection terminals and control terminals. The data collection terminals are used for acquiring and transmitting environmental parameters of crops, while the control terminals are used to regulate the environmental parameters of agricultural equipment. Both the data collection terminals and control terminals employ LoRa wireless communication technology to achieve long-range data transmission. The network layer consists of LoRa gateways, which connect to the network server via Ethernet and are responsible for uploading data from the data collection terminals and control terminals, as well as issuing control commands. Finally, the article conducted functional tests on the smart agriculture system, and the results indicated that all functions and performance of the system met the expected requirements. The system is capable of long-range data collection and transmission, meeting the demands of smart agriculture, and has promising application prospects.
Winning Ways for Your Mathematical Plays

In the quarter of a century since three mathematicians and game theorists collaborated to create Winning Ways for Your Mathematical Plays, the book has become the definitive work on the subject of mathematical games. Now carefully revised and broken down into four volumes to accommodate new developments, the Second Edition retains the original's wealth of wit and wisdom. The authors' insightful strategies, blended with their witty and irreverent style, make reading a profitable pleasure. In Volume 4, the authors present a Diamond of a find, covering one-player games such as Solitaire.
Clinical value of ultrasound in the evaluation of vascular function after carotid plaque formation

: The purpose of this study is to explore the value of vascular intima-media measurement (QIMT) and vascular function assessment system (QAS) in evaluating the structure and function of carotid artery in patients with carotid plaque. 30 patients with carotid artery plaque confirmed by ultrasound were randomly selected into the plaque group, and 31 healthy volunteers were enrolled in control group. Parameters of carotid artery were collected by QIMT and QAS, respectively. The parameters included intima-media thickness (IMT), dilatation coefficient (DC), α elastic coefficient (α), β elastic coefficient (β), pulse wave velocity (PWV) and augmented index of reflected wave (AIx). The results showed that IMT, α, β and PWV in plaque group were significantly hi gher than those in control group, while DC was significantly lower than that in control group, and the difference was statistically significant (P < 0.05). There was no significant difference in AIx between plaque group and control group. In conclusion, the carotid IMT is thickened, the elasticity is reduced and the stiffness is significantly increased in the plaque group; QIMT and QAS technology can detect the early changes of carotid structure and function, and provide a reference for early intervention and treatment of clinical cardiovascular and cerebrovascular events.
Social capital and health micro-insurance uptake by the informal sector workers in Kenya

This paper focuses on social capital as a determinant of health micro insurance uptake by informalsector workers in eight regions (Lake, North Rift, Central, Pwani, South Eastern, Frontier counties,Narok-Kajiado and Nairobi) in Kenya. Further moderating effects of mobile telephone technology wasexplored to find out its influence on the health micro insurance uptake. The study target populationcomprised 7,399,347 micro and small enterprises while sample size of 1,387 was selected out of thepopulation using stratified sampling technique. Social capital was found positive and significant (pvalue<0.05) in relation to health micro insurance uptake. The mobile telephone technology was found positiveand significant (p-value< 0.05) in seven regions while Nairobi region, it was found to benegative and insignificant (p- value=0.123). The study found that social capital is an important factorto consider when selling micro insurance products.
A Swin Transformer-Based Approach for Motorcycle Helmet Detection

Video surveillance-based automated detection of helmet use among motorcyclists has the potential to improve road safety by aiding in the implementation of enforcement initiatives. Despite that, the current detection approaches have many limitations. For instance, they are unable to detect multiple passengers or to function effectively in complex conditions. In this paper, we address the challenging problem of automated monitoring of helmet use using computer vision and machine learning. We propose a method based on deep neural network models known as transformers. We apply the base version of the Swin transformer as a backbone for feature extraction, and then combine a Feature Pyramid Network (FPN) neck with the Cascade Region-based Convolutional Neural Networks (RCNN) framework for final detection. The effectiveness of our proposed method is demonstrated through extensive experiments and is compared to existing approaches. Our method achieves a mean Average Precision (mAP) of 30.4, thus outperforming state-of-the-art detection methods.
Linearly Constrained Weights: Resolving the Vanishing Gradient Problem by Reducing Angle Bias

In this paper, we first identify \textit{angle bias}, a simple but remarkable phenomenon that causes the vanishing gradient problem in a multilayer perceptron (MLP) with sigmoid activation functions. We then propose \textit{linearly constrained weights (LCW)} to reduce the angle bias in a neural network, so as to train the network under the constraints that the sum of the elements of each weight vector is zero. A reparameterization technique is presented to efficiently train a model with LCW by embedding the constraints on weight vectors into the structure of the network. Interestingly, batch normalization (Ioffe & Szegedy, 2015) can be viewed as a mechanism to correct angle bias. Preliminary experiments show that LCW helps train a 100-layered MLP more efficiently than does batch normalization.
Coherent Energy Transfer and the Potential Implications for Consciousness

The argument that biological systems are too “warm and wet” to support quantum effects is becoming increasingly antiquated as research in the field of quantum biology progresses. In fact, not only is it becoming apparent that quantum processes may regularly take place in biological systems, but these processes may underlie the mechanisms of consciousness and propel our models of conceptualizing the human brain into the next era of scientific understanding. The phenomena of consciousness have allured scientists and philosophers for thousands of years, while a precise technical understanding has remained elusive. If possible, developing this understanding will likely be one of humanity’s greatest achievements. Knowing the fundamental processes that create conscious experience has far-reaching implications, from the potential birth of true artificial intelligence to a better Journal of Cognitive Science 19-2:115-124, 2018 c2018 Institute for Cognitive Science, Seoul National University 116 J. Tory Toole, P. Kurian, T. J. A. Craddock understanding of mental health disorder etiologies and treatments. One major challenge in the mental health professions, and, ultimately, in empathy of any kind, is being able to see from and appreciate another person’s unique, subjective experience. Discoveries in the field of consciousness could help bridge this gap.
Bubble-Based Drug Delivery Systems: Next-Generation Diagnosis to Therapy

Current radiologic and medication administration is systematic and has widespread side effects; however, the administration of microbubbles and nanobubbles (MNBs) has the possibility to provide therapeutic and diagnostic information without the same ramifications. Microbubbles (MBs), for instance, have been used for ultrasound (US) imaging due to their ability to remain in vessels when exposed to ultrasonic waves. On the other hand, nanobubbles (NBs) can be used for further therapeutic benefits, including chronic treatments for osteoporosis and cancer, gene delivery, and treatment for acute conditions, such as brain infections and urinary tract infections (UTIs). Clinical trials are also being conducted for different administrations and utilizations of MNBs. Overall, there are large horizons for the benefits of MNBs in radiology, general medicine, surgery, and many more medical applications. As such, this review aims to evaluate the most recent publications from 2016 to 2022 to report the current uses and innovations for MNBs.