Miracle-dz/UniFAR-FTUs huggingface dataset:
Peculiarities of the psychological well-being and social adaptation of young students and cadets in wartime conditions

Background and Aim of Study: The mental health and social adaptation of young students and cadets in wartime conditions is a new and understudied problem. The aim of the study: to identify the particularities of psychological well-being and social adaptation of students and cadets in wartime conditions. Materials and Methods: Our study was conducted among the students and cadets of two Ukrainian universities (KNUIA, UzhNU) in 2023, February. 327 participants were divided into 3 groups: 1) 112 cadets whose permanent disposition was changed in Ukraine; 2) 108 students who were displaced and who are in Ukraine and EU countries; 3) 107 students who did not change their place of permanent residence and who are in Ukraine in the combat zone or near it. The 28-item General Health Questionnaire (GHQ-28) to assess psychological well-being and emotional stability, and the Social Support Questionnaire (F-SozU K-22) to determine the particularities of emotional support, practical support, and social integration were used in the study. Appropriate internal consistency values (Cronbach α between 0.817 and 0.903) were found for both scales. Results: Group 1 has the best general health indicator: 1.65 times better than Group 3. The levels of somatic symptoms, anxiety and insomnia are lower in Group 1 (practically the same in women and men), and higher in Group 3. The highest rates of social dysfunction are found in Group 3. Men in all groups have more pronounced social dysfunction; women in all groups have more pronounced severe depression. Group 1 total perceived social support is 1.89 times better than Group 3. Emotional support, social integration are highest in Group 1, practical support is highest in Group 2. Conclusions: The lowest levels of psychological well-being and social adaptation were found in Group 3. This is probably due to uncertainty about the future, constant instability and insecurity. Teachers and psychologists are urged to consider the identified psychological and social peculiarities in the educational and clinical process when dealing with young students.
Urban Thermal Influence on the Background Environment of Convective Precipitation

Does the presence of cities enhance precipitation? It is an issue that needs to be addressed. This study focuses on the thermal excess in cities and attempts to determine the influence of this parameter on atmospheric instability, which constitutes the background condition for convective precipitation. A simple analytical approach involving the calculation of the daytime evolution of the mixed layer over a homogeneous ground surface was developed. The calculations were based on the data from the ensemble average of observations. Using these calculations, the convective available potential energy (CAPE) was obtained for two idealized geographic areas: one with urban land cover and the other with rural land cover. Urban heat excess, which was 200 W m greater than rural area, increased CAPE value by 75 % comparing to the rural CAPE value of 513 J kg. Cities can produce stratification in the atmosphere that is favorable for convective precipitation.
The Development and Validation of A Questionnaire on The Relationship between Religious Life and Life Satisfaction among Secondary School Students in The Manjung District

Living religiously is the main factor that leads to life satisfaction. Life satisfaction is important because it determines a person’s level of happiness in life. Every aspect of life has its satisfaction and enjoyment. Happiness, according to Imam Al Ghazali, cannot be acquired only by knowing the happiness formula without continuous efforts and reliance on knowledge and charity. The purpose of this writing is to build and validate the study questionnaire on the Relationship between Religious Life with Life Satisfaction Among Secondary School in Manjung District. The constructs and items in the study instrument are built on the exploration of the literature and the analysis of existing instruments identified as contributing to both variables in the study. The validity and reliability of the instrument were checked by analyzing the items of the questionnaire using the Statistical Package for Social Science (SPSS) software. These validity and reliability results show the instrument is suitable for the actual study. The findings of this research clearly show that this instrument has high validity and reliability and can be used in actual studies.
A revalidation of the school participant empowerment scale amongst science and mathematics teachers

ABSTRACT The purpose of this study is to explore the validity and reliability of the School Participant Empowerment Scale amongst science and mathematics teachers. Using a sample of 257 elementary and secondary teachers, the study used exploratory and confirmatory factor analysis to examine the validity of the instrument. We began by trying to confirm the hypothesised structure using confirmatory factor analysis, but were unable to do so. A subsequent exploratory factor analysis produced a structure that differed somewhat from the original structure. A six-factor solution emerged, but the items loaded differently than the original structure. We have named the emergent factors: “Self-efficacy”, “Decision-making autonomy”, “Professionalism”, “Scheduling autonomy”, “Influence” and “Authority”. The results raise questions about the scale for measuring empowerment amongst science and mathematics teachers. Future work should seek to replicate our findings with a larger sample and consider developing items relating to professional knowledge.
Minimizing Nonconvex Population Risk from Rough Empirical Risk

Population risk—the expectation of the loss over the sampling mechanism—is always of primary interest in machine learning. However, learning algorithms only have access to empirical risk, which is the average loss over training examples. Although the two risks are typically guaranteed to be pointwise close, for applications with nonconvex nonsmooth losses (such as modern deep networks), the effects of sampling can transform a well-behaved population risk into an empirical risk with a landscape that is problematic for optimization. The empirical risk can be nonsmooth, and it may have many additional local minima. This paper considers a general optimization framework which aims to find approximate local minima of a smooth nonconvex function F (population risk) given only access to the function value of another function f (empirical risk), which is pointwise close to F (i.e., ‖F − f‖∞ ≤ ν). We propose a simple algorithm based on stochastic gradient descent (SGD) on a smoothed version of f which is guaranteed to find an -second-order stationary point if ν ≤ O( /d), thus escaping all saddle points of F and all the additional local minima introduced by f . We also provide an almost matching lower bound showing that our SGD-based approach achieves the optimal trade-off between ν and , as well as the optimal dependence on problem dimension d, among all algorithms making a polynomial number of queries. As a concrete example, we show that our results can be directly used to give sample complexities for learning a ReLU unit, whose empirical risk is nonsmooth.
Assessing the Impact of Bank Liquidity on the Performance of Banks in Ghana

The ability of banks to perform their core role effectively depends largely on liquidity. In this study, the main objective is to examine the impact of bank liquidity on the performance of banks in Ghana. The study used both regression (pooled regression) and descriptive methods. The main findings indicate that liquidity has a positive impact on the performance of the bank. Further, interest income, efficiency of management staff as bank-specific factors promote liquidity of the banks. For macroeconomic variables, exchange rate volatility showed a significant inverse effect on the liquidity. As policy implication, management should adopt best liquidity management practices and a more efficient and advanced approaches to improve efficiency. This can be achieved by taking advantage of the revolution in Information Telecommunication (IT) and the mobile telecommunication industry. Also, the banks should reduce their concentration of loans and diversified to other less risky but attractive areas such as investment into government securities.
The 'Computational Unified Field Theory' (CUFT): A New 'A-Causal Computation' Physics

Introduction Twenty-first century Physics finds itself at a “theoretical crisis” akin to Einstein’s pre-1905 Relativity Theory Paradigmatic Shift: the two primary pillars of modern Physics, namely: Relativity Theory (RT) and Quantum Mechanics (QM) [1-4] seem contradictory of each other and there exist a series of unresolved Physical Conundrums which cannot be explained (in a satisfactory manner) by either QM or RT, i.e., the most prominent conundrum being “dark-matter” and “dark-energy” (e.g., up to 90% of all mass and energy in the universe cannot be accounted for by these QM and RT theoretical models! Based on Thomas Kuhn’s well known analysis of the evolution of Science (1962), which highlighted the fact that scientific progress is characterized through alternating phases of ‘Standard Science’ in which scientific inquiry is based upon an established Scientific Paradigm, which then leads to critical junctures in which this Standard Paradigm can no longer account for a series of phenomena and there
The Steady Global Corona and Solar Wind: A Three-dimensional MHD Simulation with Turbulence Transport and Heating

We present a fully three-dimensional magnetohydrodynamic model of the solar corona and solar wind with turbulence transport and heating. The model is based on Reynolds-averaged solar wind equations coupled with transport equations for turbulence energy, cross helicity, and correlation scale. The model includes separate energy equations for protons and electrons and accounts for the effects of electron heat conduction, radiative cooling, Coulomb collisions, Reynolds stresses, eddy viscosity, and turbulent heating of protons and electrons. The computational domain extends from the coronal base to 5 au and is divided into two regions: the inner (coronal) region, 1–30 R☉, and the outer (solar wind) region, 30 R☉–5 au. Numerical steady-state solutions in both regions are constructed by time relaxation in the frame of reference corotating with the Sun. Inner boundary conditions are specified using either a tilted-dipole approximation or synoptic solar magnetograms. The strength of solar dipole is adjusted, and a scaling factor for magnetograms is estimated by comparison with Ulysses observations. Except for electron temperature, the model shows reasonable agreement with Ulysses data during its first and third fast latitude transits. We also derive a formula for the loss of angular momentum caused by the outflowing plasma. The formula takes into account the effects of turbulence. The simulation results show that turbulence can notably affect the Sun’s loss of angular momentum.
THE INFLUENCE OF MINIMAL NPK FERTILISATION ON THE QUANTITY AND QUALITY OF APPLE YIELDS

During an annual cycle, fruit trees go through developmental stages, characterised by a higher demand for some mineral elements, called critical periods, which coincide with the phenophases of bud opening and shoot initiation. Research on mineral nutrition in fruit growing has highlighted that the maximum consumption of nutrients is during the period of shoot growth, fruit development and differentiation of fruit buds. In apple, flowering is influenced more by the time of fertiliser application and the form of nitrogen than by the amount applied, as apple has high requirements for the element phosphorus in the phenophases of intense shoot growth and wood maturation. Fertilisation with NPK increased apple yield for both fertilisation treatments compared to the unfertilised control treatments. After applying 270 kg·ha⁻¹ NPK in the first year of the experiment, very significant production increases were obtained, 4.46t·ha⁻¹, with a content of 16% dry matter, 13.13°Brix soluble matter and a titratable acidity of 0.465 mg malic acid/100 g.
Realizing a Mental Revolution through Astabratha Belief as a Fraud-Neutral Detector

This study aims to realize a mental revolution in the individual through astabratha belief as an effort to achieve fraud-neutral character. The belief is based that the initial occurrence of fraud comes from the mental self. This mentality is formed by teaching the human self-character through the local wisdom genius astabratha which is broken down into eight (asta) character traits. This research uses a qualitative approach with ethnographic studies to reveal the implementing culture of metal astabratha characteristics. The results of study show that fraud comes from self-character which can be prevented by growing eight characters, namely earth, fire, water, wind, sky, sun, moon and stars. These eight characters are manifested through mental self (pangawikan pribadi) to understand actions. This achievement is the result of a movement (response) to persistently reject fraudulent activities through creative, non-authoritarianism, thinking about difficulties and self-afflictions, self-safety and freeing people from suffering and worries, and finally achieving the noble goals of human life. As a result of an embodiment of self-awareness, there is no longer any desire to commit fraud, as well as awareness and behavior culture to feel peaceful in dealing with other people. This mental consistency leads to fraud neutrality as a form of moral integrity for pride, honor and self-esteem.
CFD-based Methodology for Wind Farm Layout Optimization

CFD-based Methodology for Wind Farm Layout Optimization Enrico Giuseppe Agostino Antonini Doctor of Philosophy Department of Mechanical and Industrial Engineering University of Toronto 2018 Driven by concerns on climate change and global warming, increasing oil prices, government support and public receptiveness, wind energy harvesting is emerging as one of the fastest growing renewable energy technologies. Most wind energy is nowadays produced by wind farms, which consist of hundreds of turbines to take advantage of economies of scale. Wind farm performance is however affected by the wakes generated by the turbines which can significantly diminish their annual energy production. Accurate wake effect predictions and reliable wind farm layout design become therefore critical aspects to the economic success of a wind farm project. The present research project aims therefore to define an innovative design framework that integrates accurate wake effect predictions for the development of the next generation wind farms as part of the strategy for promoting the transition to a renewable energy generation. Computational fluid dynamics (CFD) provides a unique tool to simulate wind turbine wakes because of its capability to provide a complete solution for the flow field in complex configurations. Nevertheless, CFD simulations are strongly influenced by the choice of the turbulence model used to close the Reynoldsaveraged Navier-Stokes (RANS) equations. We therefore conducted an analysis of different turbulence models and their influence on the results of CFD wind turbine simulations to suggest the most suitable for such applications. Even though proper turbulence modeling is adopted, several studies showed however that the effectiveness of RANS models in wind farm simulations has not always been consistent. We therefore hypothesized this limitation to arise from uncertainties generated by the wind direction variability and proposed a modeling framework that, by accounting for such uncertainties, consistently improved the agreement of the CFD predictions with the experimental observations. To integrate the CFD models in a design methodology, we developed an innovative continuous adjoint formulation for gradient calculations within the framework of a gradient-based wind farm layout optimization. By testing this optimization methodology under different wind farm configurations, wind resource distributions and terrain topography, we showed that this unique CFD-based design framework effectively improved the annual energy production of a proposed wind farm by optimally siting its turbines.
A New Quantum Operator for Distance and its use in Studying the Weak Equivalence Principle

We introduce a new non-relativistic quantum operator for the distance traveled by a particle in a given interval of time. The purpose of this operator is to investigate the Weak Equivalence Principle (WEP) in the quantum regime. In particular, our operator measures the integrated expected trajectory of the particle. If its expectation value depends on the particle's mass we can infer that the particle's motion is also dependent on its mass and thus violates the WEP. In this article the new operator is derived and some of its elementary properties are explored. As a proof of concept we use it to analyze the expected distance traveled by a free Gaussian wavepacket with some initial momentum. It is shown in this case that the distance such a particle travels becomes close to light-like as its mass vanishes and agrees with the classical result for macroscopic masses. This calculation begs a number of questions which are presented as topics for future research.
Numerical investigation of stand-still characteristics of a bio-inspired vertical axis wind turbine rotor

This paper reports the preliminary findings of a numerical study of a 500 W bio-inspired Vertical Axis Wind Turbine (VAWT) rotor for an urban environment. The rotor shapes are inspired by seed pods of two trees found commonly in India viz. Mimosa and Bauhinia Variegata. 15 samples of seed pods were collected from each of these trees and their diameter-to-height ratio (d/h) & helix pitch-to-height ratio (p/h) were measured. Baseline rotor shapes were based on these measurements. Subsequently, d/h and p/h ratios were varied and a 3D parametric CFD analysis was carried out using an open-source CFD solver, OpenFOAM. 3D CAD models of the rotors were created using SOLIDWORKS. Grids were generated by blockMesh and snappyHexMesh tools of OpenFOAM. Numerical simulations revealed that for a d/h of 0.27 and p/h of 0.7, the single bladed helical shaped rotor produced a stand-still aerodynamic torque of about 0.26 Nm at a wind speed of 2 m/s. This was higher than the typical cogging torque of a 500 W permanent magnet generator. Hence, the bio-inspired single bladed helical shaped rotor with d/h of 0.27 and p/h of 0.7 would exhibit early start-up at wind speeds as low as 2 m/s and would be suitable for optimally operating in an urban environment.
Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship

Abstract The main objective of this paper is to non-parametrically estimate the quantiles of a conditional distribution in the censorship model when the sample is considered as an -mixing sequence. First of all, a kernel type estimator for the conditional cumulative distribution function (cond-cdf) is introduced. Afterwards, we estimate the quantiles by inverting this estimated cond-cdf and state the asymptotic properties when the observations are linked with a single-index structure. The pointwise almost complete convergence and the uniform almost complete convergence (with rate) of the kernel estimate of this model are established. This approach can be applied in time series analysis.
A comprehensive review of demand response strategies and the role of emergent technologies for sustainable home energy management systems

Growing electricity demand shoots the challenge of maintaining a supply-demand balance, especially during peak hours. Failure of this stimulates the system’s stability problems and may lead to a blackout. This raised the need for new power generation installations associated with huge costs. Instead, the Demand-side Management (DSM) techniques were adopted to balance the existing infrastructure for a sustainable energy supply. They motivate optimal, reliable and efficient ways of energy utilisation. This paper presents an overview of DSM and its subcategories, benefits and potential challenges in its implementation with a focus on the residential sector. This also highlights rebound peaks caused by Demand Response and the need for renewable power resources at consumer premises for better load management. Moreover, DR techniques can be best implemented with emerging networking and communication technologies, such as the Internet of Things, Artificial Intelligence and Blockchain. Hence the paper highlights their future scope and importance in residential DR under the smart grid paradigm.
2D lateral heterostructures of group-III monochalcogenide: Potential photovoltaic applications

Solar photovoltaics provides a practical and sustainable solution to the increasing global energy demand. Using first-principles calculations, we investigate the energetics and electronic properties of two-dimensional lateral heterostructures by group-III monochalcogenides and explore their potential applications in photovoltaics. The band structures and formation energies from supercell calculations demonstrate that these heterostructures retain semiconducting behavior and might be synthesized in laboratory using the chemical vapor deposition technique. According to the computed band offsets, most of the heterojunctions belong to type II band alignment, which can prevent the recombination of electron-hole pairs. Besides, the electronic properties of these lateral heterostructures can be effectively tailored by the number of layers, leading to a high theoretical power conversion efficiency over 20%.
Search for pair production of second-generation leptoquarks at √s = 13 TeV

A search for pair production of second-generation leptoquarks is performed using proton-proton collision data collected at $\sqrt {s} = 13$ TeV in 2016 with the CMS detector at the CERN LHC, corresponding to an integrated luminosity of 35.9 $fb^{−1}$. Final states with two muons and two jets, or with one muon, two jets, and missing transverse momentum are considered. Second-generation scalar leptoquarks with masses less than 1530(1285) GeV are excluded for β=1.0(0.5), where β is the branching fraction for the decay of a leptoquark to a charged lepton and a quark. The results of the search are also interpreted as limits on the pair production of long-lived top squarks in an R-parity violating supersymmetry model that has a final state with two muons and two jets. These limits represent the most stringent limits to date on these models.
Integer points unusually close to elliptic curves

We consider an elliptic curve Eα,β given by the equation Y 2 = X + αX + β, where α, β are real numbers, and look for integer points close to the curve. In case the diophantine type of α is larger than 4 we find infinitely many integer points unusually close to Eα,β or to the curve E−α,β .
Interleaved Training Scheme for Multi-User Massive MIMO Downlink With User SINR Constraint

We propose an interleaved training design for multi-user massive MIMO downlink and study the performance thereof with the maximum-ratio transmission (MRT) precoding. In our proposed design, the channels are trained one BS antenna at a time and each training step is interleaved with the channel state information (CSI) feedback. The decision to continue training depends on whether or not the signal-to-interference-plus-noise (SINR) requirements of all users are satisfied with currently available instantaneous CSI. For the MRT precoding, we analyze the system performance in terms of the training length and the transmission success rate. Our simulation results show that the proposed training scheme has a significant performance advantage over existing full training scheme and fixed-length partial training scheme.