Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Learning Approach to Forecasting Monthly Demand for Residential–Sector Electricity

Forecasting electricity demand at the regional or national level is a key procedural element of power-system planning. However, achieving such objectives in the residential sector, the primary driver of peak demand, is challenging given this sector’s pattern of constantly fluctuating and gradually increasing energy usage. Although deep learning algorithms have recently yielded promising results in various time series analyses, their potential applicability to forecasting monthly residential electricity demand has yet to be fully explored. As such, this study proposed a forecasting model with social and weather-related variables by introducing long short-term memory (LSTM), which has been known to be powerful among deep learning-based approaches for time series forecasting. The validation of the proposed model was performed using a set of data spanning 22 years in South Korea. The resulting forecasting performance was evaluated on the basis of six performance measures. Further, this model’s performance was subjected to a comparison with the performance of four benchmark models. The performance of the proposed model was exceptional according to all of the measures employed. This model can facilitate improved decision-making regarding power-system planning by accurately forecasting the electricity demands of the residential sector, thereby contributing to the efficient production and use of resources.
STUDY OF RATIONAL PRESCRIBING AND DISPENSING OF PRESCRIPTIONS WITH NONSTEROIDAL ANTI-INFLAMMATORY DRUGS IN ORTHOPEDIC OUTPATIENT DEPARTMENT

ABSTRACT Objective: To study the prescribing pattern of non-steroidal anti-inflammatory drugs (NSAIDs) in outpatient orthopedic hospitals from a rural area of Maharashtra, India. Methods: A total of 237 prescriptions containing NSAIDs evaluated for their distribution according to the classification of NSAIDs and World Health Organization core indicators for prescribing practices and patient care. Results: The average number of drugs per prescription was 3.5. The average number of NSAIDs per prescription found to be 1.12. The incidence of generic prescribing was very low. The overall average consultation time and dispensing time found to be 4.5 and 1.9 minutes respectively. The percentage of drugs adequately labeled was 61.44%. Out of the 843 drugs, 267 were systemic NSAIDs, of which 50.56% and 49.43% used as monotherapy and fixed dose combinations respectively. The prescriptions are containing either one or two NSAIDs. Non-selective NSAIDs most commonly prescribed than selective cyclooxygenase-2 (COX2) inhibitors and highly selective COX2 inhibitors. The ratio of non-selective to selective NSAID usage pattern was 1:1.28. Conclusion: The study shows more use of traditional NSAIDs and underutilization of COX2 inhibitors. The study suggests that there is the immense scope of improvement for prescribing in the hospitals. Keywords: Prescribing pattern of non-steroidal anti-inflammatory drugs, Rational use of non-steroidal anti-inflammatory drugs, World Health Organization core drug use indicators.
Analysis and generalization of competitive activity results of handball clubs in the game development aspect

Purpose: an analysis of the competitive activity of men's club handball teams in the final tournament of the European Champions and Champions League Cup gives you the opportunity to determine the rating of the teams on the continent and the development tendencies of the game. Material: the best men's handball clubs from 52 national federations in Europe which competed in the qualifying tournament and the group stages of the draw and were the winners and prize winners of the European Champions and Champions League Cup of 1956/1957-2017/2018. A systematic review of the available qualitative literature was conducted according to Preferred Reporting Items for Systematic reviews. The “Web of Science”, “Physical Education Index (ProQuest)”, “Google Scholar” and “Scientific Periodicals Ukraine” databases were used in order to ensure, from an early stage, the scientific quality of the revised studies. The research was conducted based on ‘any field’ (e.g. title, abstract, text) and no restrictions were made regarding the language of publication. The terms used in the research were “teams scoring performance”, “elite handball”, “game location”, “players exclusions”, “home advantage”, “quality”, “opposition”, and “indicators”. The quality of the articles was assessed by a set of criteria developed by members of the Evidence for Policy and Practice Information and other specialists. The initial search found 132 journal articles; for a final list of 52 publications. Results: The article covers the organizational aspects of the competitive activity of men's handball clubs in Europe at the European Champions and Champions League tournaments from 1956 to 2018. The given analysis of the highest achievements of the leading handball clubs which are not only winners and prize winners, but also the countries that they represented. The winners and prize winners are marked both between teams of different countries and teams of one country. Conclusions: Achievements and rankings of the leading handball clubs in the international arena are the main components of preparing them for official competitions: new approaches to planning the preparation of players and teams for higher sports achievements and maximum realization of individual opportunities; the integration of the individual readiness of highly skilled handball players into leading handball clubs; to the important aspects of the new rules of the game, which are developed in the theory and implemented in practice; the main tendencies in the international and European handball that systematically develop and apply to a core of players as well as the next reserve.
Controller design for MTDC grid to enhance power sharing and stability

Voltage droop control is considered as a reliable control approach for multi-terminal DC (MTDC) grid system. A low value of droop constant may result in a high dynamic variation associated with oscillations for power and DC voltage deviation. Thus, the stability of the MTDC grid is at risk. This study presents a linear quadratic regulator (LQR) control design with an adaptive droop to achieve appropriate power sharing among the converter terminals. A control strategy with the combination of adaptive droop and LQR is designed in this study. The weights of LQR are tuned using the Gramian analysis. The closed-loop stability analysis is carried out using Lyapunov's stability approach. The proposed control scheme improves the closed-loop system dynamics by reducing the overshoots/undershoots and time to reach steady-state condition. In addition, power sharing according to converter rating is appropriately achieved. The performance of the proposed control scheme is validated on five terminal MTDC grid system simulated in MATLAB®.
School-Based Practices for the 21st Century: Noncognitive Factors in Student Learning and Psychosocial Outcomes

Noncognitive skills—such as motivation, perseverance, social abilities, and self-control—drive long-term student success in school and in life. Although recognized as an important causal factor in student success, these skills show considerable variability in how much time and financial resources schools invest developing them. The Every Student Succeeds Act (ESSA) now requires states to include at least one nonacademic measure in their student accountability system and funding the implementation of new models to support student learning. We review the evidence for several malleable noncognitive skills that benefit student learning and long-term psychosocial outcomes. We recommend educational stakeholders take advantage of the increased flexibility ESSA provides to cultivate noncognitive skills that yield meaningful long-term educational, economic, and social benefits for students.
Global climate change and Indian agriculture: impacts, adaptation and mitigation

Inter-Governmental Panel on Climate Change has shown that the earth temperature has increased by 0.74 degree C between 1906 and 2005 due to increase in anthropogenic emissions of greenhouse gases. By the end of this century, temperature increase is likely to be 1.8-4.0 degreee C. This would lead to more frequent hot extremes, floods, droughts, cyclones and gradual recession of glaciers, which in turn would result in greater instability in food production. It is estimated that crop production loss in India by 2100 AD could be 10-40% despite the beneficial effects of higher C02 on crop growth. We could lose 4-5 million tonnes of wheat (Triticum aestivum L. emend. Fiori & Paol.) with every rise of 1 degree C temperature. Dynamics of pests and diseases will be significantly altered. Agriculture contributes 28% of the Indian greenhouse gases emissions, primarily due to methane emission from rice (Oryza sativa L.), enteric fermentation in ruminant animals, and nitrous oxides from application of manures and fertilizers to the soils. Potential approaches to reduce these emissions include mid-season drainage or alternate drying in rice, approaches to increase N-use efficiency and soil carbon, and improvement in livestock diet. Simple adaptation strategies, such as change in planting dates and varieties could help in reducing impacts of climate change to some extent. Additional strategies for increasing our adaptive capacity include development of adverse climate-tolerant genotypes and land-use systems, providing value-added climatic risk management services to farmers, and improved land-use policies and risk management though early warning system and crop-weather insurance.
Composition and Diversity of Fungal Decomposers of Submerged Wood in Two Lakes in the Brazilian Amazon State of Pará

Aquatic ecosystems in tropical forests have a high diversity of microorganisms, including fungi, which are important decomposers of submerged wood. Despite the importance of their role in decomposition, research concerning the diversity of freshwater fungi from Brazilian Amazonian environments is scarce. The aim of this work was to describe the composition and diversity of fungi present on submerged wood in two lakes of the Brazilian Amazon (State of Para). Fragments of decaying wood (30 samples per lake) were collected from the Lakes Jua and Maica. The wood samples were inspected for 6 months in the presence of fungal reproductive structures. Fungi observed in the wood were identified morphologically. Twenty-three taxa were identified in the Lake Jua (10 sexual and 13 asexual) and 26 taxa in the Lake Maica (17 sexual, 9 asexual). ITS sequences were obtained for 14 taxa to aid in identification. In the Lakes Jua and Maica, the diversity indices were H': 2.6514 and H': 2.8174, respectively. The Sorensen index of the fungal communities in the studied lakes was 0.3673. This study is the first to describe the fungal biodiversity of two important aquatic environments in Para, Brazil.
Ameliorating effects of some trematode antigens on arthritis induced in Wistar rats

Introduction: Rheumatoid Arthritis (RA) is an autoimmune disease mediated by T helper 1 immune cells (Th1). Aim: Given that parasitic antigens are capable of polarizing the immune response towards T helper 2 immune cells (Th2), this study aimed to assess the potential effect of Schistosoma mansoni soluble egg antigen (Sm) and fasciola hepatica adult worm antigen (Fh) which are known to induce Th2 type response. Materials and Methods: RA was induced in female Wistar rats by intradermal injection (i.d) of 0.1ml complete Freund’s adjuvant (CFA). After 12 days of CFA injection, rats were treated with i.d injection of 0.1 mL saline, 0.2 mg/mL methotrexate (MXT via intraperitoneal injection, i.p)) once a week four 3 consecutive weeks as a reference drug, 100 μg Sm (i.p) or (i.d), 100 μg Fh (i.p) and (i.d). Rats were treated with antigens daily for two weeks. Results: Compared to control RA rats, treatment with Sm orFh antigens resulted in significant amelioration in the symptoms of the disease, including paw thickness and deformity measured by X-ray. These effects were further confirmed by significant alteration in histopathological changes in the hind paw. Analysis of Th1 and Th2 cytokines axis revealed high serum levels of IL-6 and TNF-a and lower serum levels of IL-4 and IL-10. Analysis of liver function showed that treatment with Sm or Fh antigens resulted in significant amelioration in hepatic enzymes including ALT, AST, and ALP. Treatment with Fh orSm also induced significant amelioration in the increased number of white blood cells and the absolute numbers of neutrophils. Conclusion: Overall, our data indicate that Sm possesses higher anti-arthritic effect than Fh, suggesting that trematode antigens can be used as a potential therapeutic approach to ameliorate arthritis.
A compact wideband circularly polarized quadrifilar antenna with PIFA elements for UHF RFID readers

Abstract In this paper, a compact circularly polarized quadrifilar antenna with planar inverted-F antenna (PIFA) elements is presented. The proposed antenna consists of four PIFA elements and a Wilkinson divider-based feed network fabricated on FR-4 substrate (ɛr = 4.4, loss tangent = 0.02, thickness = 1.6 mm). The total size of the antenna is 120 × 120 × 13.2 mm3. Impedance matching with a reflection coefficient <−15 dB and an axial ratio (AR) <3 dB are achieved over the global ultra-high frequency (UHF) radio frequency identification (RFID) frequency band and beyond. The realized gain ranges from 2.25 to 3.75 dBic within the frequency band of interest from 860 to 960 MHz with a directional radiation pattern. The proposed antenna is compact, low-cost and extremely wideband in terms of matching and AR compared to state-of-the-art UHF RFID reader antennas.
Diagnostics of laser induced plasmas at late delay times

The study of the diagnostics of plasmas produced by a laser is not always possible without enough data; usually a precise record of several lines meeting certain spectroscopic conditions is needed. In this work, a method for diagnosing plasmas was implemented at sufficiently late postbreakdown times, where it is no longer possible to apply known methods (e.g. Boltzmann plot for the estimation of kT), through an iterative algorithm that uses the parameters obtained by traditional methods at early times (LIBS typical delay time) and a minimum number of lines visible at the late times. Using the late times that are typical to the plasma's final life stage, evolution of the temperature and electronic density of the plasma is studied. The LTE condition was also verified by McWhirter's criterion.
Voices from the Language Classroom

Find loads of the voices from the language classroom book catalogues in this site as the choice of you visiting this page. You can also join to the website book library that will show you numerous books from any types. Literature, science, politics, and many more catalogues are presented to offer you the best book to find. The book that really makes you feels satisfied. Or that's the book that will save you from your job deadline.
Sensor-based Detection and Classification of Soccer Goalkeeper Training Exercises

Many goalkeeper trainees cannot afford a personal human coach. Hence, they could benefit from a virtual coach that provides personalized feedback about the execution of their training exercises. As a first step towards this goal, we developed an algorithm to detect and classify goalkeeper training exercises using a wearable inertial sensor attached to a goalkeeper glove. We collected data from 14 goalkeeper trainees while performing a series of training exercises (e.g., dives, catches, throws). Our approach first detects the exercises using an event detection algorithm based on a high-pass filter, a peak detector, and Dynamic Time Warping to detect and eliminate irrelevant motion instances. Then, it extracts a set of statistical and heuristic features to describe the different exercises and train a machine learning classifier. Our exercise detection approach retrieves 93.8% of the relevant exercises with 90.6% precision and classifies the detected exercises with an accuracy of 96.5%. The exercises recognized by our algorithm can be used to compute further qualitative metrics about individual exercise executions to provide goalkeepers with relevant feedback about their training.
Meeting the requirements of IEC TS 60904-1-2 for single light source bifacial photovoltaic characterisation: evaluation of different back panel materials

The International Electrotechnical Commission (IEC) published a technical specification, TS60904-1-2 in 2019 to standardize both indoor and outdoor characterisation ofbifacial PV cells and modules. The indoor electrical characterisation can be performed with a single or double light source. Given the linear relationship between irradiance and short-circuit current, the effect of stray light on the non-irradiated side could generate measurement artefacts in the single light source characterisation. Hence, the technical specification mentions several procedures to carefully control the unwanted irradiance below 3 W m−2. This paper describes an approach for systematic analysis of the back panel materials through experiment and simulation to meet IEC TS 60904-1-2 requirements. First, optical properties (specular and diffuse reflection) of four different backpanel materials are evaluated. Next, using different back panel materials, the irradiance on the non-irradiated side of a bifacial module is spatially mapped out using low-noise response silicon photodiode. The average irradiance on the non-irradiated side for the existing solar simulator configuration is measured to be 5.7 W/m2, failing to meet the standard requirements. The low-reflection coating (LRC) material with mask achieves the lowest average irradiance of 0.9 W m−2 on the non-irradiated side and reduces the irradiance from existing configuration by 84 %. Lastly, ray-tracing simulation is used to plot the irradiance profile on the non-irradiated side, to compensate for the low-resolution irradiance map constructed using experimental measurements with the photodiode. The simulation results also show that when a flash chamber is long, similar to a black tunnel of rectangular tube, the back panel is not required to fulfil the requirements of technical specification for single light source characterisation.
Abnormal Behavior Detection Based on the Potential Field Forces in Surveillance Scenarios

In a social environment, there is a natural mutual force between people. This paper proposes a method for detecting group abnormal behavior based on the potential field method. The movement of a pedestrian is described as the movement towards the target under the combined action of several forces. Forces on pedestrians include the attractive force for themselves and the repulsive force between pedestrians. By calculating the resultant force between them, the behavior of pedestrians is judged according to a set threshold. It is verified through experiments on public data sets that our method has high accuracy and robustness.
The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model

We develop a framework for localizing an unknown point w using paired comparisons of the form "w is closer to point xi than to xj" when the points lie in a union of known subspaces. This model, which extends a broad class of existing methods to exploit union of subspaces structure, provides a powerful framework for using the types of structure found in many practical applications. We divide the problem into two phases: (1) determining which subspace w lies in, and (2) localizing w within the identified subspace using existing techniques. We introduce two algorithms for determining the subspace in which an unknown point lies: the first admits a sample complexity guarantee demonstrating the advantage of the union of subspaces model, and the second improves performance in practice using an adaptive Bayesian strategy. We demonstrate the efficacy of our method with experiments on synthetic data and in an image search application.
The Origins of Trust Asymmetry in International Relationships: An Institutional View

Trust is key to relationship marketing. Although trust is bilateral, studies on the dispersion of trust among exchange parties remain limited, leaving the antecedents and outcomes of trust asymmetry largely underexplored. To fill the gaps, this study empirically examines the effects of different types of trust asymmetry on exchange performance and then investigates the institutional origins of trust asymmetry in international interfirm exchanges. Drawing on a survey of 134 international buyer–supplier relationships in China, the study finds that both calculative trust asymmetry and relational trust asymmetry have negative influences on exchange performance. The study also finds that formal institutional distance constrains calculative trust asymmetry and informal institutional distance increases relational trust asymmetry. Moreover, prior interactions and expectations of continuity significantly moderate the effects of formal and informal institutional distance. This study advances trust studies in cross-border settings.
Fake colorized and morphed image detection using convolutional neural network

As the technology develops, utilization of the phony pictures is at highest, So, as per an overview most of the pictures stored on the server or in the cloud are being transformed or counterfeit. As a result, it is difficult to identify whether the images stored are real or not. So not many systems are existing today which are equipped to tell whether pictures are fake or not. Earlier Histogram based and feature extraction-based methods were used to identify fake images. The neural network is being the most advanced technology distinguishes the phony pictures by studying various features of the image and learning the procedure of faking an image. So as a minor advance towards this, proposed system uses features like dark channel, bright channel, RGB channel and alpha channel. Using Gaussian distribution, we can anlayze the edges of the images to identify phony images. Deep layer analysis is performed using convolutional neural system along with the fuzzy classification procedure to improve the likelihood of recognizing phony pictures. Through this research it is concluded that convolutional neural networks (CNN) based fake colorized image detection showcases a better result than histogram based and feature extraction based fake colorized image detection.
Testing for Quantile Sample Selection

This paper provides distribution free tests for detecting sample selection in conditional quantile functions. The first test is an omitted predictor test with the propensity score as the omitted variable. In the case of rejection we cannot distinguish between rejection due to genuine selection or to misspecification. Thus, we suggest a second test using only individuals with propensity score close to one. The latter relies on an ‘identification at infinity’ argument, but accommodates cases of irregular identification, and neither of the two tests requires a continuous exclusion restriction. We apply our procedure to test for selection in log hourly wages using UK survey data and derive an extension of the tests to the conditional mean.