Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic Accident Prediction Based on LSTM-GBRT Model

Road traffic accidents are a concrete manifestation of road traffic safety levels. The current traffic accident prediction has a problem of low accuracy. In order to provide traffic management departments with more accurate forecast data, it can be applied in the traffic management system to help make scientific decisions. This paper establishes a traffic accident prediction model based on LSTM-GBRT (long short-term memory, gradient boosted regression trees) and predicts traffic accident safety level indicators by training traffic accident-related data. Compared with various regression models and neural network models, the experimental results show that the LSTM-GBRT model has a good fitting effect and robustness. The LSTM-GBRT model can accurately predict the safety level of traffic accidents, so that the traffic management department can better grasp the situation of traffic safety levels.
Effekte einer sportlichen[5_TD$DIFF] Intervention auf die Haltungsentwicklung vom Jugend- zum Erwachsenenalter

Hintergrund: Haltungsschw€achen im Kindesund Jugendalter werden mit einer Pr€avalenz von bis zu 65% angegeben. Zusammenh€ange zu Beschwerden im R€uckenund Nackenbereich sind bekannt. In der vorliegenden Langzeitstudie sollte €uberpr€uft werden, wie sich ein zielgerichtetes Haltungstraining auf die K€orperhaltung auswirkt und inwieweit m€ogliche positive Effekte vom Adoleszenzins Erwachsenenalter €ubertragen werden k€onnen. Material und Methoden: Bei 57 haltungsschwachen Jugendlichen wurden €uber 6 Jahre j€ahrlich mehrere Haltungsparameter erhoben. 20 Jugendliche trainierten ab dem Alter von 14 Jahren durchg€angig bis zum Alter von 20 Jahren, 24 Jugendliche beendeten das Training mit 18 Jahren, 13 Jugendliche dienten als Kontrollgruppe. Das Haltungstraining fand zweimal w€ochentlich statt und beinhaltete Kraftausdauer-, Dehnungsund K€orperwahrnehmungs€ubungen. Die Auswertung erfolgte mittels ANOVA mit Messwertwiederholung, der post hocPaarvergleich mittels Scheff e-Test und Bonferroni-Korrektur. Als Signifikanzniveau wurde 0,05 festgelegt. Ergebnisse: Die durchgehend trainierende Gruppe zeigte eine signifikante Verbesserung der Haltungsparameter in allen Haltesituationen und zu allen Zeitpunkten. Die ab dem Erwachsenenalter nicht mehr trainierende Gruppe konnte einzelne Verbesserungen, wie die bewusste Aufrichtung der K€orperhaltung, beibehalten; in anderen Haltesituationen (habituell, geschlossene Augen) kam es wieder zu einer Verschlechterung der Haltung. Die ermittelten Effektst€arken lagen zwischen n [1_TD$DIFF] = 0,25 und n = 0,49 und kennzeichnen starke Effekte. Die Kontrollgruppe zeigte keine Ver€anderung. Schlussfolgerungen: Ein zielgerichtetes Haltungstraining sollte daher aus medizinisch-pr€aventiver Sicht bereits im Jugendalter begonnen und lebensbegleitend kontinuierlich fortgesetzt werden. Evidenzebene: II
SAMA Working Paper: Promoting Industrial and Export Diversification in Resource-Dependent Countries The Case of Saudi Arabia

This paper studies the Saudi industrial development, and evaluates major opportunities and challenges that faces Saudi Arabia in its industrial diversification plans. It begins by reviewing the resource curse theory, and then highlights the role of economic policies in mitigating the Dutch Disease. It then reviews two major industrial diversification approaches for resource-dependent countries: the product space strategy (Hidalgo and Hausmann 2009) and resource-based industrialization (RBI) (e.g. Perez 2015). These frameworks are used in two ways; firstly, to assess the current industrial and export structures; and secondly, to discuss possible diversification opportunities for Saudi Arabia. Finally, the paper provides policy recommendations.
Compensation of Current Harmonic Components of Nonlinear Loads in Presence of Distributed Generation Resources Using Multi-Criteria Vector Control

Filtering the harmonics produced by nonlinear loads in power systems is an important issue for the engineers to follow. In most cases, to this end, active filters have been used. In this paper, however, it is shown that this task can be accomplished using a Multi-Criteria algorithm and distributed generations (DGs) resources. In the proposed algorithm, when the DGs are connected to the main network, compensations of active and reactive powers as well as harmonic components are possible. To do so, first, the dynamical model of the systems will be shown in details in the static three-phase system, and then, they are transferred to a rotating orthogonal set using the necessary conversion equations. Therefore, the transferred variables are used to control the voltage source converters in order to achieve improvements in DGs’ behavior when they are connected to the network. In this control method, the active and reactive powers transmitted to the load as well as the current harmonics are compensated using samples of voltages and currents taken at the connection points; thus capabilities for sinusoidal current and maximum active power transmissions are provided. Besides, the control proposed method has a fast dynamical response in active and reactive power compensations. Therefore, using this control approach, the transmitted power of DGs to the network are maximized, the power coefficient factor is improved and current harmonics of the load are decreased significantly.
An efficient numerical solution for time switching optimal control problems

In this paper, an efficient computational algorithm for the solution of Hamiltonian boundary value problems arising from bang-bang optimal control problems is presented. For this purpose, at first, based on the Pontryagin’s minimum principle, the first order necessary conditions of optimality are derived. Then, an indirect shooting method with control parameterization, in which the control function is replaced with piecewise constant function with values and switching points taken as unknown parameters, is presented. Thereby, the problem is converted to the solution of the shooting equation, in which the values of the control function and the switching points as well the initial values of the costate variables are unknown parameters. The important advantages of this method is that, the obtained solution satisfies the first order optimality conditions, further the switching points can be captured accurately which is led to an accurate solution of the bang-bang problem. However, solving the shooting equation is nearly impossible without a very good initial guess. So, in order to cope with the difficulty of the initial guess, a homotopic approach is combined with the presented method. Consequently, no assumptions are made on the optimal control structure and number of the switching points, and sensitivity to the initial guess for the unknown parameters is resolved too. Illustrative examples are included at the end and efficiency of the method is reported.
Size-resolved aerosol pH over Europe during summer

Abstract. The dependence of aerosol acidity on particle size, location, and altitude over Europe during a summertime period is investigated using the hybrid version of aerosol dynamics in the chemical transport model PMCAMx. The pH changes more with particle size in northern and southern Europe owing to the enhanced presence of non-volatile cations (Na, Ca, K, Mg) in the larger particles. Differences of up to 1–4 pH units are predicted between sub- and supermicron particles, while the average pH of PM1−2.5 can be as much as 1 unit higher than that of PM1. Most aerosol water over continental Europe is associated with PM1, while coarse particles dominate the water content in the marine and coastal areas due to the relatively higher levels of hygroscopic sea salt. Particles of all sizes become increasingly acidic with altitude (0.5–2.5 units pH decrease over 2.5 km) primarily because of the decrease in aerosol liquid water content (driven by humidity changes) with height. Inorganic nitrate is strongly affected by aerosol pH with the highest average nitrate levels predicted for the PM1−5 range and over locations where the pH exceeds 3. Dust tends to increase aerosol pH for all particle sizes and nitrate concentrations for supermicron range particles. This effect of dust is quite sensitive to its calcium content. The size-dependent pH differences carry important implications for pH-sensitive processes in the aerosol.
THE DISTANCE COVERED BY WINNING AND LOSING PLAYERS IN ELITE SQUASH MATCHES RAZLIKE V OBSEGU GIBANJA MED ZMAGOVALCI IN PORAŽENCI AKTIVNIH

Namen raziskave je bil preučiti gibanje najboljših svetovnih igralcev squasha in ugotoviti ali obstajajo razlike v poti gibanja zmagovalcev in poražencev posameznih aktivnih faz. S pomočjo avtomatičnega sledilnega sistema in nadzorom operaterja je potekalo sledenje igralcev, ki so nastopili na Svetovnem ekipnem prvenstvu (N=11). V raziskavi so bile zajete vse aktivne faze (n = 1429), razen tistih pri katerih se je aktivna faza končala s sodniško odločitvijo ‘let’ (n = 307). Vse aktivne faze so bile razdeljene v štiri časovne kategorije in sicer v zelo kratke, kratke, srednje in dolge aktivne faze. V povprečju so zmagovalci opravili za 0.71 m krajšo pot gibanja kot poraženci. Vendar so v 41.4% primerih poraženci opravili krajšo pot gibanja od zmagovalcev. Ti rezultati kažejo, da igralec, ki prisili nasprotnika opraviti daljšo pot gibanja, ni nujno tudi zmagovalec aktivne faze. Do tega lahko pride, ko dominanten igralec v posamezni fazi stori napako oziroma igralec v podrejenem položaju izvede zmagoviti udarec. Zaradi tega je v nadaljnjih raziskavah smiselno preučiti interakcijo med posameznimi udarci in njihovo učinkovitostjo ter potjo gibanja obeh igralcev. Ključne besede: squash, analiza gibanja, aktivna faza, zmagovalci, poraženci, razlike Abstract
Efficiency of vanillin in impeding metabolic adaptability and virulence of Candida albicans by inhibiting glyoxylate cycle, morphogenesis, and biofilm formation

Background and Purpose: Candida albicans is the fourth most common cause of nosocomial fungal infections across the world. The current drug regimens are suffering from such drawbacks as drug resistance, toxicity, and costliness; accordingly, they highlight the need for the discovery of novel drug agents. The metabolic adaptability under low-carbon conditions and expression of functional virulence traits mark the success of pathogens to cause infection. The metabolic pathways, such as glyoxylate cycle (GC), enable C. albicans to survive under glucose-deficient conditions prevalent in the hostile niche. Therefore, the key enzymes, namely isocitrate lyase (ICL) and malate synthase (MLS), represent attractive agents against C. albicans. Similarly, virulence traits, such as morphogenesis and biofilm formation, are the crucial determinants of C. albicans pathogenicity. Regarding this, the present study was conducted to uncover the role of vanillin (Van), a natural food flavoring agent, in inhibiting GC, yeast-to-hyphal transition, and biofilm formation in human fungal pathogen C. albicans. Materials and Methods: For the determination of hypersensitivity under low-glucose conditions, phenotypic susceptibility assay was utilized. In addition, enzyme activities were estimated based on crude extracts while in-silico binding was confirmed by molecular docking. The assessment of morphogenesis was accomplished using hyphal-inducing media, and biofilm formation was estimated using calcofluor staining, MTT assay, and biomass measurement. Additionally, the in vivo efficacy of Van was demonstrated using Caenorhabditis elegans nematode model. Results: Based on the results, Van was found to be a potent GC inhibitor that phenocopied ICL1 deletion mutant and displayed hypersensitivity under low-carbon conditions. Accordingly, Van facilitated the inhibition of ICL and MLS activities in vitro. Molecular docking analyses revealed the in-silico binding affinity of Van with Icl1p and Mls1p. Those analyses were also confirmative of the binding of Van to the active sites of both proteins with better binding energy in comparison to their known inhibitors. Furthermore, Van led to the attenuation of such virulence traits as morphogenesis, biofilm formation, and cell adherence. Finally, the antifungal efficacy of Van was demonstrated by the enhanced survival of C. elegans with Candida infection. The results also confirmed negligible hemolytic activity on erythrocytes. Conclusion: As the findings of the present study indicated, Van is a persuasive natural compound that warrants further attention to exploit its anticandidal potential.
IMPACTS OF PHYTOESTROGENS ON LIVESTOCK PRODUCTION: A REVIEW

Phytoestrogens, polyphenolic compounds, are one of the major plant secondary metabolites found abundantly in animal diets. However, these phytochemicals play initial important roles in plant growth, development and maintenance. They also have many biological roles in animal body, affecting their productivity. The richest sources of phytoestrogens in animal diets are legumes, particularly, soybeans and clover. These plants often comprise substantial part of animal feed, thus presenting a potential source of phytoestrogens.The interest in these compounds was started earlier, over 50 years ago, when they have been known to affect fertility of an Australian sheep herd, resulting in an economic loss. The putative effects of phytoestrogens are based on their structural similarity to the mammalian estrogen 17β-estradiol (E2) and thus their potency to bind with mammalian estrogen receptors. More attention has been paid to these metabolites since they can act as estrogen agonists or antagonists which make their effects are not expected. The estrogenic activity of phytoestrogens depends on many factors such as chemical structure of the compound, bioavailability, animal specie, responsive tissue and its estrogen receptor (ER) sub-type (ERα or ERβ) and metabolites resulting from their fermentation and digestion. Reports showed that phytoestrogens could affect animal fertility and growth, quality of animal products and human health. This review illustrates the impacts of phytoestrogens on the livestock production system, focusing on physiology of reproduction, as well as the knowledge obtained from research in laboratory and field scales.
Evaluation of Power Generation Potential of Cellulose Microfibrils and Onion Skin-based Bio-Piezoelectric Nanogenerators

It is highly desirable for new nanosystems and nanodevices to be self-powered for applications in biomedical science, sensing, robotics and personal electronics. As new trends require these devices to be downsized and incorporated in remote and hard to reach locations the challenge to develop new technologies that allow autonomous, maintenance-free and continuous supply of energy is great. Over the last decade researchers have found ways to harness ambient energy from mechanical vibrations to develop self-powered devices. The present research reports the fabrication of two bio-piezoelectric generators using cellulose as biomaterial in two distinct configurations, as well as commonly used materials in a simple manufacturing process. Cellulose microfibrils, a disoriented structure, obtained from cotton wads was mixed with silicone to obtain an CMFPNG, while onion skin, a more oriented cellulose structure, was left untreated or naked to fabricate a NOSBPNG. The chemical and physical differences where evaluated using Fourier-transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM), the abundance of H-boding groups available in the onion skin structure present an interesting proposition for a high performance piezoelectric material, while the simpler an disoriented fashion on CMFs is less likely to perform equally. The self-orientation of PNG using onion skin without chemical treatment and no sputtering for the formation of the electrode generate an output voltage up until 3.26 V and store 0.395 V in a 4.7 μF capacitor, resulting in a power storage of 1.25 μJ, making it a viable material for the construction of smart devices such as PNG. CMFPNG results were not conclusive, hence it is suggested the present methods are not the adequate for this material. However important factors to consider are presented for future research. Nevertheless the results of NOSBPNG support the use of onion skin as a self-oriented waste material for the construction of new smart bio-materials.
Investigating the relationship between seasonal temperature changes and the referrals of patients with acute coronary syndrome

Introduction: Due to the relationship between climate and human health, scientists are interested in evaluating seasonal and daily changes in air temperature and risk for cardiovascular diseases. Objective: The aim of this study was to investigate the relationship between seasonal temperature changes and the rates of referring patients with acute coronary syndrome. Patients and Methods: The present case-control study was performed on all consecutive patients suffering acute coronary syndrome that were hospitalized in a great referral hospital in Tehran between 2011 and 2015. The meteorological and mortality data were first matched with each other. Then the number of patients with acute coronary syndrome was determined by region and gender. Results: Assessing the frequency of patients referred from 2011 to 2015 indicated the upward trend of referral to the hospital. Regarding the frequency of referrals in different months of the year (regardless of the year of assessment), the highest rate of referral for patients with unstable angina was in the month of October and then in November and the lowest referral was in August. The number of referees was significantly associated with the increase in minimum and maximum temperature, average air pressure, as well as with the decrease in air humidity during the years studied. Conclusion: The risk of acute coronary syndrome attacks is highest in the cold months of the year, especially in the autumn and early winter, and is the lowest in the middle of summer. Over the years, increasing air temperature with increasing air pressure and reducing humidity can increase the risk of acute coronary syndrome.
Acoustic detection of apple mealiness based on support vector machine

Mealiness degrades the quality of apples and plays an important role in fruit market. Therefore, the use of reliable and rapid sensing techniques for nondestructive measurement and sorting of fruits is necessary. In this study, the potential of acoustic signals of rolling apples on an inclined plate as a new technique for nondestructive detection of Red Delicious apple mealiness was investigated. According to destructive confined compression tests, the mealiness of apples was evaluated by the hardness and juiciness measurements. In addition, support vector machine (SVM) models were developed to classify apples. The radial basis function (RBF) as the kernel was used in SVM models. According to exhaustive search method, the model with nine features combination was found to be the best model. Results indicated overall accuracy of 85.5 % to classify apples in mealy and healthy groups. The results indicated that this method is potentially useful for apple mealiness detection.
Parkinson’s disease: A review article

Parkinson’s is one of the most horrendous disease affecting 1% of the adult population above the age of 60 and 4% over the age 85 . This disease is chronic and progressive in neurodegeneration causing dopaminergic neurons in Substantia nigra region of the mid brain to die which ultimately leads to decrease in dopamine production in our brain. Though any direct cause of this disease has not been identified yet, but many genetic mutations and environmental factors are found to be related to it. The diagnosis depends on family genetic history and disease symptoms. Dopamine is a neurotransmitter which controls certain notable functions of body including movement, memory, sleep, attention and learning. Due to plummeted production of dopamine, a Parkinson’s patient encounters several symptoms like tremor, bradykinesia, rigidity, postural instability.
A Socially Adaptable Framework for Human-Robot Interaction

In our everyday lives we regularly engage in complex, personalized, and adaptive interactions with our peers. To recreate the same kind of rich, human-like interactions, a social robot should be aware of our needs and affective states and continuously adapt its behavior to them. Our proposed solution is to have the robot learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers. To make the robot autonomous in its decision making, this process could be guided by an internal motivation system. We wish to investigate how an adaptive robotic framework of this kind would function and personalize to different users. We also wish to explore whether the adaptability and personalization would bring any additional richness to the human-robot interaction (HRI), or whether it would instead bring uncertainty and unpredictability that would not be accepted by the robot's human peers. To this end, we designed a socially adaptive framework for the humanoid robot iCub. As a result, the robot perceives and reuses the affective and interactive signals from the person as input for the adaptation based on internal social motivation. We strive to investigate the value of the generated adaptation in our framework in the context of HRI. In particular, we compare how users will experience interaction with an adaptive versus a non-adaptive social robot. To address these questions, we propose a comparative interaction study with iCub whereby users act as the robot's caretaker, and iCub's social adaptation is guided by an internal comfort level that varies with the stimuli that iCub receives from its caretaker. We investigate and compare how iCub's internal dynamics would be perceived by people, both in a condition when iCub does not personalize its behavior to the person, and in a condition where it is instead adaptive. Finally, we establish the potential benefits that an adaptive framework could bring to the context of repeated interactions with a humanoid robot.
Multi-Agent Deep Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks With Imperfect Channels

This paper investigates a futuristic spectrum sharing paradigm for heterogeneous wireless networks with imperfect channels. In the heterogeneous networks, multiple wireless networks adopt different medium access control (MAC) protocols to share a common wireless spectrum and each network is unaware of the MACs of others. This paper aims to design a distributed deep reinforcement learning (DRL) based MAC protocol for a particular network, and the objective of this network is to achieve a global $\alpha$α-fairness objective. In the conventional DRL framework, feedback/reward given to the agent is always correctly received, so that the agent can optimize its strategy based on the received reward. In our wireless application where the channels are noisy, the feedback/reward (i.e., the ACK packet) may be lost due to channel noise and interference. Without correct feedback, the agent (i.e., the network user) may fail to find a good solution. Moreover, in the distributed protocol, each agent makes decisions on its own. It is a challenge to guarantee that the multiple agents will make coherent decisions and work together to achieve the same objective, particularly in the face of imperfect feedback channels. To tackle the challenge, we put forth (i) a feedback recovery mechanism to recover missing feedback information, and (ii) a two-stage action selection mechanism to aid coherent decision making to reduce transmission collisions among the agents. Extensive simulation results demonstrate the effectiveness of these two mechanisms. Last but not least, we believe that the feedback recovery mechanism and the two-stage action selection mechanism can also be used in general distributed multi-agent reinforcement learning problems in which feedback information on rewards can be corrupted.