Miracle-dz/UniFAR-FTUs huggingface dataset:
Crime amount prediction based on 2D convolution and long short‐term memory neural network

Crime amount prediction is crucial for optimizing the police patrols' arrangement in each region of a city. First, we analyzed spatiotemporal correlations of the crime data and the relationships between crime and related auxiliary data, including points‐of‐interest (POI), public service complaints, and demographics. Then, we proposed a crime amount prediction model based on 2D convolution and long short‐term memory neural network (2DCONV‐LSTM). The proposed model captures the spatiotemporal correlations in the crime data, and the crime‐related auxiliary data are used to enhance the regional spatial features. Extensive experiments on real‐world datasets are conducted. Results demonstrated that capturing both temporal and spatial correlations in crime data and using auxiliary data to extract regional spatial features improve the prediction performance. In the best case scenario, the proposed model reduces the prediction error by at least 17.8% and 8.2% compared with support vector regression (SVR) and LSTM, respectively. Moreover, excessive auxiliary data reduce model performance because of the presence of redundant information.
Early metabolic impairment as a contributor to neurodegenerative disease: Mechanisms and potential pharmacological intervention

The metabolic syndrome comprises a family of clinical and laboratory findings, including insulin resistance, hyperglycemia, hypertriglyceridemia, low high‐density lipoprotein cholesterol levels, and hypertension, in addition to central obesity. The syndrome confers a high risk of cardiovascular mortality. Indeed, metabolic dysfunction has been shown to cause a direct insult to smooth muscle and endothelial components of the vasculature, which leads to vascular dysfunction and hyperreactivity. This, in turn, causes cerebral vasoconstriction and hypoperfusion, eventually contributing to cognitive deficits. Moreover, the metabolic syndrome disrupts key homeostatic processes in the brain, including apoptosis, autophagy, and neurogenesis. Impairment of such processes in the context of metabolic dysfunction has been implicated in the pathogenesis of neurodegenerative diseases, including Alzheimer, Parkinson, and Huntington diseases.
Comparing Asynchronous Distributed Averaging Gossip Algorithms Over Scale-free Graphs

Gossip algorithms are an approach for data dissemination within networks that can compute data aggregates efﬁciently. Gossip protocol is fascinating due to its capability of powering the classical protocols, its parallel to larger social structures and its feature of full decentralization. We deem computing the distributed average in a network a critical and fundamental procedure for distributed machine learning study. Thus, we are interested in exploring the three well-known gossip algorithms solving this problem, namely Push-pull, Push-sum, and Sum-weight gossip, particularly in asynchronous mode. This paper ﬁrst attempts to connect the theoretical and the practical work, by proposing modiﬁcations to the general algorithms which make them more applicable in practice. Since no thorough empirical comparison of these gossip algorithms has been conducted, we compare three algorithms on two synthetic dataset and one real-world dataset, by the scale-free graph (Barab´asi-Albert graph). We show that all three algorithms have an extremely high accuracy for approximating the distributed mean although Push-sum would obtain bad result on few occasions. Also, Push-sum is the most efﬁcient algorithm when the mean degree in the graph is small, and Push-sum and Push-pull are both efﬁcient when the graph or the mean degree is large. On the other hand, the experimental results demonstrate that the performance (accuracy and efﬁciency) of each algorithm could be affected by variously distinct graph properties. Furthermore, we discuss the time complexity of three asynchronous gossip algorithms and prove that they are all bounded by a logarithmic function of the graph size and other properties.
Equivalent Lumped Circuit Study for the Field Stabilization of a Long Four-Vanes RFQ

The possibility to design an RFQ long respect to the RF wavelength is very important for the feasibility of linacs with different applications, from the high power CW linacs for neutron production to the low power high frequency linacs proposed for hadrotherapy. In particular INFN has been funded for the study of the critical parts of a waste transmutation linac. In this framework the field stabilization of a 352 MHz RFQ has been studied, using the LANL resonant coupling technique; an equivalent lumped circuit approach has been used, and compared with MAFIA simulations. Based on the results of these studies an aluminum model (1:1 scale, 0.04 mm tolerances) has been built and we are now ready for the test of the tuning procedure.
Nonlinear robust control of marine diesel engine

ABSTRACT Diesel engines are widely used for the propulsion of marine vehicles and are exposed to uncertain working environment. In this paper, a robust nonlinear controller is proposed for a marine diesel engine that employees sliding mode control theory. The robust controller aims to maintain the desired diesel engine speed performance under harsh sea environment. The sliding surface has been carefully chosen that minimises the error in both angular velocity and acceleration. Robust control algorithm development and its tuning are also discussed. The performance of the proposed nonlinear robust controller is investigated thoroughly and is compared with a classical Proportional–Integral–Differentiation controller with integral windup scheme. Simulation results show that the proposed super-twisting-algorithm-based sliding mode controller can effectively improve the speed performance of the marine diesel engine in transient and steady operating conditions.
Intelligent Temperature Control System of Greenhouse Based on STM32 Single Chip Microcomputer

With the development of automatic control technology and the popularization of agricultural science and technology, people are more and more aware of the intelligence convenience. In this study, a set of intelligent greenhouse temperature control system is established based on single chip microcomputer STM32F103. PID algorithm is used to realize stepless adjustment of greenhouse temperature, and complete the temperature automatic monitoring and control. It solves the greenhouse problems of low automation degree, large amount of manual work and low control accuracy of crop growth environment. The system simulation and practice show that it can improve the temperature and humidity control accuracy of greenhouse by 10.8%, and reduce the amount of manual work, and provide a good natural environment for plant growth and development, and have high economic benefits.
Investigation of phase and temperature perturbations induced by a candle using Hilbert optics methods

The method of multiwave RGB-optical Hilbert diagnostics of the phase and temperature spatial structure of the flame (in an air flow heated by a candle flame) at a fixed moment of time is discussed. The object of study satisfies the model of axial symmetry of the torch associated with the vertical orientation of the candle. The reliability of the received results is confirmed by comparing the reconstructed radial temperature by experimental hilbertogram with data measured by a thermocouple. The flickering effect of the flame was not taken into account in the work, this is the subject of further research.
Fan Pages On The Customer-Brand Relationship and Its Motivation To Participate: A Conceptual Paper

The purpose of this conceptual paper is to review the relationship between customers and their motivations to participate in Facebook fan pages. It defines and presents the effects of fan pages in a manner that shed light on the constructs and sets the stage for future research. This article also explores its factors that contribute to the participation in fan pages of social network as well as a thorough understanding of why an attraction of fan pages among customers exists and whether customer integration and engagement effects on their brand loyalty. This will further determine whether companies do benefit from their brands’ Facebook fans. This paper provides a conceptual framework for considering predictors of participation in fan pages of social network. It indicates factors that contribute to the consequence as well as practical insights for managers.
Determination of the ignition temperature of mechanically activated carbon of various degrees of metamorphism and type of grinding

The experiments carried out using two methods of TGA (thermogravimetric analysis) made it possible to determine the ignition temperatures for brown coal, hard coal and anthracite treated both with activator mills (VCM, disintegrator) and with a standard hammer mill (initial coal). Practically all the results of coal ignition obtained by different methods correlate with each other. They show a decrease in the ignition temperature of micromilled coals during mechanically activated grinding. The analysis of the results of experimental studies made it possible to calculate kinetic parameters such as the ignition index, the maximum burning rate, the burnout index, and the comprehensive index. The data obtained are new and prove the effectiveness of mechanical activation treatment of coal fuel.
Stochastic Battery SOC Model of EV Community for V2G Operations Using CTA-2045 Standards

An electric vehicle (EV) battery has large energy storage capacity in the context of residential total usage, and the potential to provide large energy reserves for Home energy Management (HEM) systems. In an electric distribution system, groups of EVs could provide vehicle-to-grid (V2G) service in response to control signals and enable virtual power plant (VPP) operation of the car batteries. The CTA-2045 standards were considered for integration of the EV controls into the HEM system for maximal interoperability with other appliances, such as residential battery, electric water heater, and heating, ventilation, and air conditioning (HVAC) system. The power distribution system under study was modeled based on a modified IEEE 123-bus feeder test case in OpenDSS software. The availability and state of charge (SOC) of EVs were calculated based on the national household travel survey (NHTS) data following a new procedure to create synthetic communities following experimental probability density functions (PDFs). Example case studies for long and short term V2G services were completed in this paper from the perspective of the distribution system. The power flow for the distribution system, the voltages on the buses, as well as the SOCs and available energies of the EVs were calculated following the control signals on an example day.
2′-O-Methylperlatolic Acid Enhances Insulin-Regulated Blood Glucose-Lowering Effect through Insulin Receptor Signaling Pathway

Purpose Insulin receptor (InsR) sensitizers represent a new type of therapeutic agent for the treatment of diabetes, with 2′-O-methylperlatolic acid (2-O-M) being a potential InsR targeting drug. The purpose of this study was to determine whether 2-O-M functions as an activator of the insulin signaling pathway, regulating glucose hemostasis through the InsR and exerting a glucose-lowering effect in an animal model of diabetes. Methods SPR-based analyses were used to detect the binding of different concentrations of 2-O-M to the InsR. The protein levels of IR-β, p-IR, AKT, and p-AKT in Hepa and C2C12 cell lines and liver and muscle tissues were determined by western blotting. Glucose uptake capacity was determined in C2C12 cells. Streptozotocin-induced diabetic mice were randomly divided into four groups: the control, insulin treated, 2-O-M treated, and combined insulin and 2-O-M treated. Mice were injected with 2-O-M or normal saline and the average blood glucose concentration after 120 min, and the serum levels of insulin, glucagon, and C-peptide were measured. Next, qRT-PCR was performed to detect the mRNA expression of genes involved in lipid and glucose metabolism in the liver and muscle tissues. Results 2-O-M binds to the extracellular domain of the InsR. Moreover, combination treatment with 2-O-M and insulin resulted in significant activation of the insulin signaling pathway in vitro and significant stimulation of the glucose uptake capacity of C2C12 myotubes. In mice with streptozotocin-induced diabetes, 2-O-M significantly prolonged the blood glucose-lowering effect of insulin, significantly reduced the secretion of exogenous insulin, and reduced the blood glucose concentration in vivo. In addition, treatment with 2-O-M alone significantly enhanced the phosphorylation of AKT in muscle tissue, which enhanced glucose uptake in C2C12 myotubes. Further, 2-O-M significantly increased glucagon secretion and enhanced liver gluconeogenesis to prevent hypoglycemia. Conclusion 2-O-M enhances the hypoglycemic effect of insulin through the insulin signaling pathway and can be used as a complement to insulin. This synergetic effect may lower the required dose of insulin and protect β cells.
The Impact of Organizational Culture on Employee Engagement and Organizational Citizenship Behavior

Organizational Citizenship Behavior (OCB) is defined as positive behavior that goes beyond the formal role as defined even though it is not mentioned in the job description. It can be influenced by employee engagement and Organizational culture. Meanwhile, according to Gallup Survey, 80% of workers in Indonesia are categorized as not engaged in the workplace. Besides, according to Quantum Workplace survey, manufacturing company is on rank 15 of 17 of the kind of company that focus on employee engagement. This is a quantitative research and the population is all permanent employees of PT XYZ. By using the Slovin formula, there are 268 respondents. The sampling technique is stratified proportional random sampling. The results are organizational culture has siginificant effect on employee engagement and OCB partially.
HOW TO PREDICT THE VIBRATION EFFECT DUE TO THE MACHINE OPERATION ON ITS VICINITY

The satisfactory performance of a machine is concerned with its installation, i.e., with a well-designed foundation and soil investigation. The vibration amplitude of the machine-foundation system must be kept under permissible values generally specified by the machine's manufacturers and natural frequencies must be determined to avoid resonance. There may be situations when amplitudes of the machine may be within the acceptable limits for satisfactory machine operation but the vibrations may affect other machines around, be harmful to adjacent structures and precision equipment and annoying to persons. Here in will be shown how to predict in a simple way the effect of the vibration due to the machine operation on its vicinity considering the foundation as a vibration source on the surface of an elastic medium. All machines generated unbalanced dynamic loads (forces and moments) that induce vibrations. These dynamic loads are caused by machine operation condition such as wear, imbalance, misalignment, etc, and must be kept under a safety limit by the maintenance personal for the satisfactory operation of the entire plant. Another machine's vibration problem is caused by resonance. The resonance condition is reached when one or more frequencies of the exciting loads are near or equal to any of the natural frequencies of the machine-foundation-soil system. Unfortunately the resonance problem can't be readily solved because a structural modification will be necessary to bring the vibration level to accepted values. The vibration generated by the machine operation condition is then transmits through the soil by the block foundation what may affect the vicinity in a bad way. A vibrating footing is then a source of wave generation in the soil. Herein the response of a block foundation embedded in the soil and excited by a vertical harmonic load will be outlined and used to predict vibration response of the foundation. Also the problem of the vibration propagation through the soil due to concentrated dynamic load acting on the soil surface will be treated to estimated the decrease in amplitude of the vibration with distance from the source and to evaluated the effects of the vibration on the performance of other equipments in the vicinity and structures around. 2. Vibration Propagation Through the Soil Due to Periodic Concentrated Load The problem of the surface wave propagation in an elastic medium (elastic half-space) was first studied by Lord Rayleigh (1885) and is known as the Rayleigh wave. Later Lamb (1904) studies the response of the medium as it was excited by oscillating vertical force or pulse loading acting at a point or along a line on the surface and within the body. See fig. (1). Lamb's solutions for calculation of vertical surface displacement at a distance r from the concentrated dynamic load on the surface of the medium may be written as following,
Automated Emboss Of Mobile (Android) Phishing APPS via Graphical User Interface-DoS ATTACK

- -Phishing is a plan of attack to gain personal information for the intention of identity theft, usually by means of fraudulent E-mail. Attackers use emails, social media to trick victims into providing sensitive information/data or visiting malicious URL (Uniform Resource Locator) in the attempt to compromise their systems. Mobile phishing attacks, such as mimic mobile browser pages, masquerade as permissible applications by leveraging repackaging or clone techniques, have caused varied yet symbolic security concerns. Therefore, detection methods have been receiving increasing attention. In this paper, we propose a new attacking technique, called GUI-DoS (Squatting) attack, which can generate phishing apps automatically and effectively on the Android platform. This method embraces image processing and deep learning algorithms, to enable significant and large-scale attacks. We detect that a successful phishing attack requires two situations, page confusion and logic deception during attacks synthesis. Our experimental calculation reveal that existing phishing securities are less effective against such emergent attacks and may therefore stimulate more efficient detection techniques. To further reveal that our generated phishing apps can not only bypass existing detection techniques, but also deceive real users.
Saving PAM4 Bus Energy with SMOREs: Sparse Multi-level Opportunistic Restricted Encodings

Pulse Amplitude Modulation (PAM) uses multiple voltage levels as different data symbols, transferring multiple bits of data simultaneously, thereby enabling higher communication bandwidth without increased operating frequencies. However, dividing the voltage into more symbols leads to a smaller voltage difference between adjacent symbols, making the interface more vulnerable to crosstalk and power noise. GDDR6X adopts four-level symbols (PAM4) with Maximum Transition Avoidance (MTA) coding, which reduces the effects of crosstalk. However, current coding approaches can consume excess energy and produce excess power noise. This paper introduces novel energy reduction techniques for PAM interfaces, specifically demonstrating them for GDDR6X PAM4. Inspired by prior work on conventional single-ended I/O interfaces, we leverage the unused idle periods in DRAM channels between data transmissions to apply longer but more energy-efficient codes. To maximize the energy savings, we build multiple sparse encoding schemes to fit different sized gaps in the DRAM traffic. These sparse encodings can provide energy reductions of up to 52% when transferring 4-bit data using a 3-symbol sequence. We evaluate these coding techniques using an NVIDIA RTX 3090 baseline, a recent GPU which uses GDDR6X with PAM4 signaling. Our evaluation shows the opportunity for large energy savings at the DRAM I/O interface (28.2% on average) over many HPC/DL applications with minimal performance degradation.
Incentivized and non-incentivized liking ratings outperform willingness-to-pay in predicting choice

A core principle in decision science is that people choose according to their subjective values. These values are often measured using unincentivized scales with arbitrary units (e.g., from 0 to 10) or using incentivized willingness-to-pay (WTP) with dollars and cents. What is unclear is whether using WTP actually improves choice predictions. In two experiments, we compare the effects of three different subjective valuation procedures: an unincentivized rating scale, the same scale with incentives, and incentivized WTP. We use these subjective values to predict behavior in a subsequent binary food-choice task. The unincentivized rating task performed better than the incentivized WTP task and no worse than the incentivized rating task. These findings challenge the view that subjective valuation tasks need to be incentivized. At least for low-stakes decisions, commonly used measures such as WTP may reduce predictive power.
[14]. Robot-assisted Relaxation Training for Children with Autism Spectrum

 Abstract — Cognitive Behavioral Therapy (CBT) has been proven an effective tool to address anger and anxiety issues in children and adolescents with Autism Spectrum Disorders (ASD). Robot-enhanced therapy has been used in psychosocial and educational interventions for children with ASD with promising results. Whenever CBT-based techniques were incorporated in robot-based interventions, they were mainly performed in group sessions. Objectives: The study’s main objective was the implementation and evaluation of the effectiveness of a relaxation training intervention for children with ASD, delivered by the social robot NAO. Methods: 20 children (aged 7–12 years) were randomly assigned to 16 sessions of relaxation training implemented twice a week. Two groups were formed: the NAO group (children participated in individual sessions with the support of NAO) and the control group (children participated in individual sessions with the support of the therapist only). Participants received three different relaxation scenarios of increasing difficulty (a breathing scenario, a progressive muscle relaxation scenario and a body scan medication scenario), as well as related homework sheets for practicing. Pre- and post-intervention assessments were conducted using the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire for parents (SDQ-P). Participants were also asked to complete an open-ended questionnaire to evaluate the effectiveness of the training. Parents’ satisfaction was evaluated via a questionnaire and children satisfaction was assessed by a thermometer scale. Results: The study supports the use of relaxation training with the NAO robot as instructor for children with ASD. Parents of enrolled children reported high levels of satisfaction and provided positive ratings of the training acceptability. Children in the NAO group presented greater motivation to complete homework and adopt the learned techniques at home. Conclusions: Relaxation training could be effectively integrated in robot-assisted protocols to help children with ASD regulate emotions and develop