Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty

In this paper, a method to review the role of renewable energy as an energy producer in scheduling a problem unit commitment is presented. Today, renewable energy sources, due to the lack of environmental pollution, and consequently a very low marginal cost, have been receiving considerable attention in power systems. The correct management of the unit commitment (UC) is a controversial and important issue in the power production unit, which requires suitable scheduled hours to obtain a minimum cost. This study was conducted to investigate the presence of electric vehicles and photovoltaic sources in UC and their impact to reduce production costs and improve load profiles. To achieve the optimum solution, a meta-heuristic Cuckoo search algorithm with high convergence speed is used to solve the UC problem. An IEEE 10-unit test system is employed to investigate the impacts of PEVs and PV on generation scheduling. Since the PV system is associated with uncertainty, in this study, the Uncertainty problem has been modeled using an iterative algorithm randomly with the allocation of density functions that fits the solar radiation. So, the used stochastic Monte Carlo optimization algorithm is capable of handling uncertain outputs of solar power. The simulation results show the effectiveness of the proposed method in reducing production costs and improving load profiles.In this paper, a method to review the role of renewable energy as an energy producer in scheduling a problem unit commitment is presented. Today, renewable energy sources, due to the lack of environmental pollution, and consequently a very low marginal cost, have been receiving considerable attention in power systems. The correct management of the unit commitment (UC) is a controversial and important issue in the power production unit, which requires suitable scheduled hours to obtain a minimum cost. This study was conducted to investigate the presence of electric vehicles and photovoltaic sources in UC and their impact to reduce production costs and improve load profiles. To achieve the optimum solution, a meta-heuristic Cuckoo search algorithm with high convergence speed is used to solve the UC problem. An IEEE 10-unit test system is employed to investigate the impacts of PEVs and PV on generation scheduling. Since the PV system is associated with uncertainty, in this study, the Uncertainty problem has .
Predicting \tau-lepton polarization at the LHC

This is a master's thesis and it is written in Lithuanian language. The goal of this thesis is to predict the polarization of a \tau-particle produced at the LHC and coming from a real W boson. This is achieved by calculating the projection of the expectation value of the polarization vector of the \tau-particle. Calculations are done in the frame of the Standard Model. In this model only left-chiral currents couple to W bosons. The mass of the \tau-particle is left non-zero, therefore one can see the influence of helicity mixing on polarization. The initial colliding particles at the LHC are protons and the most important channels for W production are quark fusion: $q\bar{q} -> W^+ -> \tau^+ \nu_{\tau}$. Calculation for \tau-lepton production from Z bosons and photons, $q\bar{q} -> Z^0, A^\gamma -> \tau^+ \tau^-$, are also included for investigation of possible background events. Because quarks are confined in a proton, this thesis presents a thorough treatment on discribing proton's inner structure with Parton distribution functions. The results section shows plots of differential cross sections for \tau-lepton production from different quark flavours and different energy intervals of the \tau-particle. A projection of the expectation value of the polarization vector depends on the chosen energy intervals. The vector on which it is projected is chosed to be the direction of the \tau-particle's motion. The influence of the mass is best seen for low energy particles, because then the helicity mixing is higher. PACS numbers: 13.88. +e, 14.60. Fg
Embedded Intelligence in Urban Transportation Networks

 Energy is inefficiently used in today’s society.  One of the main sources of energy waste is transportation. According to Figure [1], road transportation is the main contributor to energy waste with 93.4% of all transportation energy waste.  Road systems require advancements in order to enhance road safety.  The safety of humans on roads is at risk as traffic congestion increases; this is due to various causes as shown in Figure [2] with accidents being the second highest cause. Situation
Characterization of the Basal and mTOR-Dependent Acute Pulmonary and Systemic Immune Response in a Murine Model of Combined Burn and Inhalation Injury

Severe burn injury leads to a cascade of local and systemic immune responses that trigger an extreme state of immune dysfunction, leaving the patient highly susceptible to acute and chronic infection. When combined with inhalation injury, burn patients have higher mortality and a greater chance of developing secondary respiratory complications including infection. No animal model of combined burn and inhalation injury (B+I) exists that accurately mirrors the human clinical picture, nor are there any effective immunotherapies or predictive models of the risk of immune dysfunction. Our earlier work showed that the mechanistic/mammalian target of rapamycin (mTOR) pathway is activated early after burn injury, and its chemical blockade at injury reduced subsequent chronic bacterial susceptibility. It is unclear if mTOR plays a role in the exacerbated immune dysfunction seen after B+I injury. We aimed to: (1) characterize a novel murine model of B+I injury, and (2) investigate the role of mTOR in the immune response after B+I injury. Pulmonary and systemic immune responses to B+I were characterized in the absence or presence of mTOR inhibition at the time of injury. Data describe a murine model of B+I with inhalation-specific immune phenotypes and implicate mTOR in the acute immune dysfunction observed.
Efficient Monte Carlo Calculations of the One-Body Density

An alternative Monte Carlo estimator for the one-body density rho(r) is presented. This estimator has a simple form and can be readily used in any type of Monte Carlo simulation. Comparisons with the usual regularization of the delta-function on a grid show that the statistical errors are greatly reduced. Furthermore, our expression allows accurate calculations of the density at any point in space, even in the regions never visited during the Monte Carlo simulation. The method is illustrated with the computation of accurate Variational Monte Carlo electronic densities for the Helium atom (1D curve) and for the water dimer (3D grid containing up to 51x51x51=132651 points).
An Integrated Approach of Machine Learning, Remote Sensing, and GIS Data for the Landslide Susceptibility Mapping

Landslides triggered in mountainous areas can have catastrophic consequences, threaten human life, and cause billions of dollars in economic losses. Hence, it is imperative to map the areas susceptible to landslides to minimize their risk. Around Abbottabad, a large city in northern Pakistan, a large number of landslides can be found. This study aimed to map the landslide susceptibility over these regions in Pakistan by using three Machine Learning (ML) techniques, specifically Linear Regression (LiR), Logistic Regression (LoR), and Support Vector Machine (SVM). Several influencing factors were used to identify the potential landslide areas, including elevation, slope degree, slope aspect, general curvature, plan curvature, profile curvature, landcover classification system, Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), soil, lithology, fault density, topographic roughness index, and road density. The weights of these factors were calculated using ML techniques. The weightage overlay tool is adopted to map the final output. According to three ML models, lithology, NDWI, slope, and LCCS significantly impact landslide occurrence. The area under the ROC curve (AUC) is applied to validate the performance of models, and the results show the AUC value of LiR (88%) is better than SVM (86%) and LoR (85%) models. ML models and final susceptibility map gives good accuracy, which can be reliable for the results. The study’s outcome provides baselines for policymakers to propose adequate protection and mitigation measures against the landslides in the region, and any other researcher can adopt this methodology to map the landslide susceptibility in another area having similar characteristics.
Apresentando Inteligência Artificial para jovens do ensino médio: um relato de experiência

Neste artigo é relatada a experiência de planejamento e execução de um curso de introdução a inteligência artificial para alunos do ensino médio da rede pública estadual de Alagoas. Durante 6 semanas de curso os alunos aprenderam sobre a história da IA, suas aplicações e conceitos de aprendizagem de máquina. Foram realizadas atividades práticas para todos os conceitos aprendidos. Além disso, o curso foi finalizado com aulas de empreendedorismo voltadas para IA, onde os alunos descreveram problemas que encontram no cotidiano e propuseram soluções usando IA para resolvê-los. Foram utilizadas metodologias ativas com o intuito de deixar o curso mais motivador e atrativo.
Vienna VLBI Software - Current release and plans for the future

The Vienna VLBI Software (VieVS) is a geodetic Very Long Baseline Interferometry (VLBI) data analysis software which has been developed at the Vienna University of Technology since 2008. This paper gives an overview about its capabilities, including scheduling and simulation of VLBI observations. The latest release, version 2.1 includes a a graphical user interface. A few results and planned future developments are presented as well.
3D Printed Active Origami Dielectrics for Frequency Tunable Antennas Through Mechanical Actuation

We investigate using a reconfigurable metamaterial structure based on high permittivity dielectric elements in a flexible origami framework to control the electromagnetic response of a suspended patch antenna. Origami-inspired dielectric structures are fabricated by additive manufacturing of origami elements using an ABS-30 vol% BaTiO3 filament (permittivity <inline-formula> <tex-math notation="LaTeX">${\sim }11$ </tex-math></inline-formula>). The printed millimeter-scale elements are then assembled into an origami structure using flexible polymer hinges. Alternatively, dielectric origami structures are also achieved using a flexible, polymer-only origami lattice pre-fabricated by stereolithography into which shaped high dielectric elements (permittivity <inline-formula> <tex-math notation="LaTeX">${\sim }18$ </tex-math></inline-formula>) of ABS-60 vol% CaTiO3, manufactured by field assisted sintering, are inserted. The various dielectric origami designs are inserted into the air gap between a suspended patch antenna and a ground plane, designed to operate at a resonant frequency of 1 GHz. The presence of the dielectric origami modifies the antenna resonant frequency and tunablity is then achieved through different configurations of the dielectric origami, actuated by hand or mechanically. Tunability arises because varying the configuration, and overall density, of the dielectric origami varies its effective permittivity and thus the patch resonant frequency. The dielectric origami structures provide a tunable range up to <inline-formula> <tex-math notation="LaTeX">${\sim }14\%$ </tex-math></inline-formula>, in good agreement with numerical simulations. Simulations are also used to show how broader tunability could be achieved easily, for example, by optimizing the size of the dielectric elements. Overall, the results using these preliminary dielectric origami structures, enabled by combining advanced manufacturing techniques, suggest that the approach offers a wide design space with the potential to realise novel antenna functionality and flexibility.
Are we any closer to understanding why fish can die after severe exercise?

Post- exercise mortality (PEM) may occur when fish exercise to exhaustion and are pushed so far beyond their physiological limits that they can no longer sustain life. Although fish exercise to overcome a variety of natural challenges, the phenomenon of PEM is most often observed as the result of interactions between fish and humans. The seminal work of Black (Can J Fish Aquat Sci, 15:573, 1958) and Wood et al. (J Fish Biol, 22:189, 1983) provided a foundation for exploring the potential causes of PEM in fish. With no “silver bullet” explaining PEM being apparent, contemporary research has continued to focus on physiological mechanisms of exhaustion in fish, including factors such as oxygen delivery, ion regulation, hormone signalling, and cardiac function. This paper provides an overview of these studies, and reviews the continuous improvement in data collection methods, tools, and experimental protocols used to examine the PEM phenomenon. These studies of exhaustion have played an important role in informing management actions for activities such as bycatch revival and fish passage. Since the contribution of Wood et al. (Journal of Fish Biology, 22(2):189– 201, 1983), the combined efforts of fundamental and applied research have yielded a greater understanding of why fish die after severe exercise, yet much remains to be explored through future work.
Metacognition in Teaching: Using A “Rapid Responses to Learning” Process to Reflect on and Improve Pedagogy

In this paper, we critically evaluate the use of a weekly “rapid responses (RR) to learning” process in the context of teaching a graduate course on research methods over a three-year period. The RR process involves use of a short set of open-ended questions about key moments in learning that students complete, in writing, during the last five minutes of each class. The questions ask students to identify salient take-away messages, note when they felt the most and least engaged, name actions taken by anyone that were affirming or confusing, and consider specific “aha” moments. Our specific aim was to assess the following questions: What was the pedagogic value of the RR process? How did it inform our teaching and to what extent were there direct benefits of the process for students as well as for us as teachers? We found that the systematic feedback we obtained in this way supports weekly monitoring of student learning, facilitates response to trouble spots, and assists in assessment of student engagement and classroom climate. It also provides insight into the efficacy of pedagogic strategies, invites students to engage in metacognitive learning about their own learning, and models a process of instructors receiving feedback and being flexible to change. For instructors, the process enhances motivation and professional development and can be used to document instructor leadership and development. Finally, it facilitates deeper appreciation of the need to better integrate student self-assessment and the development of metacognitive skills as core components of the course.
Mini-Review on the Enzymatic Lipophilization of Phenolics Present in Plant Extracts with the Special Emphasis on Anthocyanins

Different plant extracts have the potential to be important sources of phenolic compounds. Their antibacterial, antifungal and antioxidant properties are of interest to researchers due to various possibilities for use in the pharmacy, cosmetic and food industries. Unfortunately, the direct application of phenolics in food is limited because of their hydrophilic nature and low solubility. The review is devoted to the recent advances in the methods of lipophilization of phenolic extracts along with the use of enzymes. The concept of extract modification instead of single compound modification is based on the expected synergistic effect of many phenolic compounds. The main focus is on the phenolic compounds found in fruits, flowers and leaves of different common and underutilized as well as medicinal, folk-medicinal or endemic plants. The compiled papers point to the great interest in the modification of anthocyanins, highly active but often unstable phenolics. Some examples of other flavonoids are also outlined. The possible applications of the lipophilized plant extracts are presented for improving the stability of edible oils, decreasing the content of acrylamide, exhibiting higher color stability in thermal processing and increasing the nutritional value.
Green Nano-Biotechnology: A New Sustainable Paradigm to Control Dengue Infection

Dengue is a growing mosquito-borne viral disease prevalent in 128 countries, while 3.9 billion people are at high risk of acquiring the infection. With no specific treatment available, the only way to mitigate the risk of dengue infection is through controlling of vector, i.e., Aedes aegypti. Nanotechnology-based prevention strategies like biopesticides with nanoformulation are now getting popular for preventing dengue fever. Metal nanoparticles (NPs) synthesized by an eco-friendly process, through extracts of medicinal plants have indicated potential anti-dengue applications. Green synthesis of metal NPs is simple, cost-effective, and devoid of hazardous wastes. The recent progress in the phyto-synthesized multifunctional metal NPs for anti-dengue applications has encouraged us to review the available literature and mechanistic aspects of the dengue control using green-synthesized NPs. Furthermore, the molecular bases of the viral inhibition through NPs and the nontarget impacts or hazards with reference to the environmental integrity are discussed in depth. Till date, major focus has been on green synthesis of silver and gold NPs, which need further extension to other innovative composite nanomaterials. Further detailed mechanistic studies are required to critically evaluate the mechanistic insights during the synthesis of the biogenic NPs. Likewise, detailed analysis of the toxicological aspects of NPs and their long-term impact in the environment should be critically assessed.
The Effect of the Use of Information Technology, Social Media and Work Discipline on Employee Productivity at PT Kencana Sawit Indonesia Solok Selatan

The aim of this study is to analyze the influence of Information Technology, Social Media, and Work Discipline on Employee Productivity at PT Kencana Sawit Indonesia South Solok. Data collection methods used are questionnaires and literature review. The questionnaire is using Agree-Disagree Scale with a scale of 10 points and the sample collection method used is total sampling with a sample of 50 employees at PT Kencana Sawit Indonesia. The analysis technique is using validity test, reliability test, normality test, heteroscedasticity test, multicollinearity test, multiple linear regression analysis, T test, F test and coefficient of determination. Based on the calculations, regression equation obtained is Y = 0.602X1 + 0.364X2 + 0.562X3 + e, with a coefficient of determination is 68.4%. These results indicate that Information Technology (X1), Social Media (X2) and Work Discipline (X3) variables have a significant and positive effect on Employee Productivity (Y). This study only examines the influence of Information Technology, Social Media, and Work Discipline on Employee Productivity in industrial companies, to further research of the effect of Information Technology, Social Media, and Work Discipline on Employee Performance, besides that it can use research objects in other industries and can use samples of more than 50
Investigation of Six-Phase Surface Permanent Magnet Machine With Typical Slot/Pole Combinations for Integrated Onboard Chargers Through Methodical Design Optimization

This article presents an analytical magnetic equivalent circuit (MEC) modeling approach for a six-phase surface-mounted permanent magnet (SPM) machine equipped with fractional slot concentrated winding (FSCW) for integrated onboard chargers. For the sake of comparison, the selected asymmetrical six-phase slot/pole combinations with the same design specifications and constraints are first designed based on the parametric MEC model and then optimized using a multiobjective genetic algorithm (MOGA). The commercial BMW i3 design specifications are adopted in this article. The main focus of this study is to achieve optimal design of the SPM machine considering both the propulsion and charging performances. Thus, a comparative study of the optimization cost functions, including the peak-to-peak torque ripple and core losses under both motoring and charging modes and electromagnetic forces (EMFs) under charging, is conducted. In addition, the demagnetization capability in the charging mode and the overall cost of the employed machines are optimized. Since the average propulsion torque is crucial in electric vehicle (EV) applications, it is maintained through the design optimization process. Furthermore, finite element (FE) simulations have been carried out to verify the results obtained from the analytical MEC model. Eventually, the effectiveness of the proposed design optimization process is corroborated by experimental tests on a 2-kW prototype system.
The Critical Role and Application of Microbes towards Sustainable Development and Human Wellbeing

Microorganisms (also called microbes) make up a large portion (1 trillion (1012) species or 60%) of the Earth’s living as they are abundant and diversified in nature. Though they are vital for ecosystems and human welfare, their roles are often ignored or underrated. While most studies are underway in the global north to figure out how to utilise microbes in agriculture, industries, medical, space mission, and many other sectors, this kind of research is limited in the global south, particularly in Sub–Saharan Africa. Also, there has been scarce knowledge regarding the importance of microorganisms. The present paper aims to highlight and discuss current knowledge on the roles and/ or applications of microorganisms and their contribution toward sustainable development and human welfare in the global south. It also aims to help the scientists and/ or researchers in sub–Saharan Africa comprehends the use of microbial communities. We reviewed 84 published original research and review articles to explore microbial roles and their applications. We establish that many microbes play critical roles, which include but are not limited to ecological, pharmaceuticals, food source, biofuel or energy production, drugs or medicine development, nitrogen and carbon fixation, biocontrol agents, bioremediation, decomposition of organic matters, and soil formation. Since microbes potentially ensure the functioning of the Earth’s ecosystem and support human welfare, research on this subject should be prioritised in the global south to improve human development and well-being.
Inpatient pulmonary rehabilitation followed by Tele-Rehabilitation in a patient with Post Tubercular sequelae: A case study

A 52-year-old known case of pleural effusion caused by tuberculosis presented with complaints of breathlessness, right-sided chest pain, and weakness. History revealed that this was her second episode as a post tuberculosis sequel. She was treated with a multidisciplinary approach i.e. pharmacological as well as physiotherapeutic management. Necessary radiological imaging included chest x-ray and HRCT thorax which gave a better understanding of the lung condition of the patient. Pharmacological treatment included oxygen therapy and Inj. Augmentin, Inj. Aminophylline, Inj. Hydrocort, Tab. Mucinac 600mg and Tab. Montair; whereas physiotherapeutic management included airway clearance techniques, chest expansion techniques, early graded mobilization, strengthening, and stretching through telerehabilitation. The progression of the patient was recorded on outcome measures taken such as Dyspnea (MMRC score), 6-minute walk test, and HADS (Hospital Anxiety and Depression Scale).