Miracle-dz/UniFAR-FTUs huggingface dataset:
The investigation of approximate solutions of Deformed Schrödinger Equations for the Hydrogenic Atoms, Heavy Quarkonium Systems 𝑸𝑸𝑸𝑸 ( 𝑸𝑸 = 𝒃𝒃 , 𝒄𝒄 ) and Diatomic molecule Bound-State Problem under Improved Exponential, Generalized, Anharmonic Cornell potential Model in NCPS symmetries

Recently Ibekwe et al . (Ref [16]) have treated the bound state solution of the radial Schrödinger equation for the exponential generalized Cornell anharmonic potential (EGACp, in short, see Eq. (1)) model within the framework of quantum mechanics known in the literature. According to the generalized Bopp's shift method and standard perturbation theory, we generalize this process by adding multi-variable coupling potentials 𝑑𝑑𝑒𝑒𝑒𝑒𝑒𝑒 ( −𝛼𝛼𝛼𝛼 ) 𝑓𝑓+𝑙𝑙 ( 𝑙𝑙+1 ) 𝛼𝛼 4 , and �−𝑎𝑎𝐋𝐋𝚯𝚯 + 𝐋𝐋𝛉𝛉 2𝜇𝜇 � together with the EGACp model in three-dimensional nonrelativistic quantum mechanics noncommutative phase space (3DNRQm-NCPS) including the effect of the centrifugal term. The multi-variable coupling potentials appear as a result of the effects of NC properties of space and phase on the EGACp model. We called this newly proposed potential the improved generalized Cornell anharmonic potential (IEGACp, in short, see Eq. (2)) model. We were able to discover a new application of this potential to hydrogen atoms He + , Li +2, and Be + , in addition to other applications the heavy quarkonium systems ( 𝑐𝑐𝑐𝑐 and 𝑏𝑏𝑏𝑏 ) and some selected diatomic molecules (CO, NO, CH and N 2 ) known in the literature within the framework of (3DNRQm-NCPS). The obtained energy is sensitive to discreet atomic quantum numbers ( 𝑗𝑗 , 𝑛𝑛 , 𝑙𝑙 , 𝑠𝑠 and 𝑚𝑚 ), the noncommutativity parameter ( 𝛩𝛩 , 𝜎𝜎 , 𝜒𝜒 ) due to the topological properties of the self-quantum influence of space-space and phase-phase, in (3DNRQm-NCPS) symmetries, in addition to the discreet atomic quantum numbers ( 𝑛𝑛 , 𝑙𝑙 ) and the parameters ( 𝑎𝑎 , 𝑏𝑏 , 𝑐𝑐 , 𝑑𝑑 , 𝑒𝑒 , 𝑓𝑓 , 𝛼𝛼 ) or ( 𝑟𝑟 𝑒𝑒 , 𝐷𝐷 𝑒𝑒 , 𝛼𝛼 ) of the EGACp model that appeared in the literature. Furthermore, we have shown that the corresponding Hamiltonian operator in (3DNRQm-NCPS) symmetry is the sum of the Hamiltonian operator of EGACp and three operators, the first one is the perturbed spin-orbit interaction, the second is the modified Zeeman operator while the last part corresponds to the induced rotational Fermi Hamiltonian. The new mass spectrum of the heavy quarkonium systems is carried out by introducing the IEGACp model in (3DNRQm-NCPS) symmetries. The comparison with other special cases of potentials in the literature is motivating. The limiting cases are analyzed for ( 𝛩𝛩 , 𝜎𝜎 , 𝜒𝜒 ) and ( 𝛩𝛩 𝑐𝑐 , 𝜎𝜎 𝑐𝑐 , 𝜒𝜒 𝑐𝑐 ) → (0,0,0) and are compared with those of literature.
Impact of climate change on vegetation period of basic species of vegetables in Slovakia

The aim of the paper is to provide climatic data from the basic elements and characteristics of the energy balance in terms of the current state and in terms of trends and assumptions of their future changes in Slovakia. Climate change affect agriculture and its procedures. Changes in vegetation period in Slovakia of selected vegetables are presented in this study. We used for agro-climatic analysis one hundred climatological stations, which were selected to cover all agricultural regions up to 800 m a.s. l. Actual data and predictions were compared with time period 1961–2010. Due to homogeneity in data measurements, was chosen this period. We obtained climate trends and assumed map outputs of future climate changes by mathematical-statistical methods for horizons of years 2011–2020, 2041–2050, 2071–2080 and 2091–2100. We analysed vegetation period changes of selected fruit vegetables, Brassica vegetables and root vegetable in field conditions with prediction to year 2100. In our results is shown the earlier beginning of vegetation period in a spring and later end in an autumn in last 30 years. The vegetation period is getting longer about 15–20 days for Capsicum annuum ; 15–20 days for Brassica oleracea var. capitate ; 10–15 days for Beta vulgaris subsp. vulgaris with comparation of nowadays situation and period 2091–2100.
Evaluation of certain insecticides to control shoot and fruit borer, Leucinodes orbonalis Guenee on brinjal ( Solanum melongena L)

The present investigation entitled was carried out at Mahewa, Prayagraj, Uttar Pradesh, India. The experiment was conducted during kharif season of 2021-22 in Randomized Block Design (RBD) on three replications. Two applications of eight treatments viz., Spinosad 45SC (T1), Flubendiamide 480SC (T2), Neem oil 0.2% (T3), Indoxacarb 14.5SC (T4), Emamectin benzoate 5SG (T5), Cartap Hydrochloride 25SG (T6), Chlorantraniliprole 18.5SC (T7) and untreated Control (T8). Among all the treatments minimum percent shoot infestation, percent fruit infestation and B:C ratio were observed in Spinosad 45SC (10.756%, 11.581% and 1:5.64). Flubendiamide 480SC (15.756%, 17.143% and 1:5.31) is found to be the next best treatment followed by Emamectin Benzoate 5SG (16.86%, 18.348% and 1:4.74), Chlorantraniliprole 18.5SC (18.493%, 18.406% and 1:4.54) and Indoxacarb 14.5SC (19.821%, 20.547% and 1:4.16), Cartap Hydrochloride 25SG (21.501%, 20.622% and 1:3.73) and Neem oil 0.2% (23.892%, 23.467% and 1:3.55) is found to be least effective but comparatively superior over the control (27.534%, 34.725% and 1:2.59) respectively.
A deep learning based framework for badminton rally outcome prediction

Badminton is a fast-paced net-based sport in which players' actions and strategies in-game determine their chances of winning. With sports analytics gaining popularity due to its capability in providing valuable information for players and coaches to counter opponents with tactics, some recent research works attempted to perform stroke recognition. However, there has been little research into using stroke sequences for sports analytics. In this paper, we propose a player-independent framework to investigate the relationship between strokes and rally outcome in badminton games. To classify the rally outcome, strokes are represented by deep features extracted using CNN and fitted into LSTM. Experiments with various variants of GRU and LSTM models demonstrate that Bidirectional LSTM gives the best prediction performance, with ResNet-18 as the feature extractor. Additional experiments were performed to study different features that represent the stroke as plain text and player's pose, as well as methods to augment a small sequential dataset.
TWO-DIMENSIONAL WAVE RUN-UP INUNDATION ANALYSIS

Due to the complex nature of wave run-up (wind-generated waves approaching a shoreline), characterization of run-up inundation can be difficult. For example, if waves during a storm surge event inundate around a complex network of structures, it is difficult (if not impossible) to evaluate inundation extents/depths and associated loadings on structures using existing empirical run-up equations. A method was developed to combine the application of empirical run-up equations with two-dimensional hydrodynamic modelling to characterize inundation of waves. A synthetic wave field is developed for input to the hydrodynamic model. The height of the synthetic wave field is calibrated to ensure that the run-up height in the model matches the run-up height indicated by an empirical run-up equation for specified design incident wave conditions. The calibrated synthetic wave field is used as the input to a detailed model that simulates inundation around structures. The model output can provide information about inundation depths and velocities, which support a detailed evaluation of loadings exerted on inundated structures. A validation of this method is provided by comparing the results to a more computationally intensive numerical model. This methodology provides a way to estimate the extent of wave run-up inundation in circumstances where some other two-dimensional run-up simulation techniques are too computationally intensive, empirical run-up equations are not sufficient, and physical modelling is not feasible.
Growing Up in a Union Household: Impacts of Adult Union Status on Children’s Life Course*

Labor unions might have various effects beyond the workplace. We link data on mothers from the National Longitudinal Survey of Youth (NLSY79) to data on their children from the NLSY79 Child Survey to analyze whether a mother’s unionization history while a child is growing up affects two childhood outcomes–cognitive skill and behavior–and two adult outcomes–educational attainment and earnings. We similarly use the Panel Study of Income Dynamics (PSID) to analyze the effect of the unionization history of the household heads on similar childhood and adult outcomes. As these outcomes are likely the product of cumulative childhood experiences, we emphasize the use of unique, cumulative measures of mother or household head union status. We do not find a strong pattern of results indicative of a significant union influence on these measures of the quality of a child’s life course. JEL codes: J51, J13, J62, J31 * We are extremely grateful to Jianxuan Lei for his tireless, expert work cleaning the PSID data. We recognize and appreciate the staff at our respective institutions who supported us as researchers while we conducted this research. The NLSY79 and Children of the NLSY79 surveys are sponsored and directed by the U.S. Bureau of Labor Statistics and the National Institute for Child Health and Human Development. The survey is managed by the Center for Human Resource Research (CHRR) at The Ohio State University and interviews are conducted by the National Opinion Research Center (NORC) at the University of Chicago. The collection of the Panel Study of Income Dynamics data by the Institute for Social Research, University of Michigan, was partly supported by the National Institutes of Health under grant number R01 HD069609 and R01 AG040213, and the National Science Foundation under award numbers SES 1157698 and 1623684.
A Review of Board Level IT Governance: A Taxonomy to Inform the Quality of Financial Reports

Financial reports are important documents that stakeholders never ignore, and Information Technology (IT) is utilized throughout firms to increase operation efficiency. However, prior researches studies Information Technology Governance (ITG) that relates to cybersecurity risks, thus, this paper takes step further to reviews board level ITG literature that is relevant to Corporate Governance (CG) and discuss how it impacts on the quality of financial reports. This paper systematically presents a taxonomy of research encompassing the focus areas: performance, cybersecurity losses, more accurate earnings forecasts, lower audit fees based upon prior studies in ITG over the period 2010-2020. The main finding is that results reveal a lack of board level ITG under CG research and a lack of the relation between board level ITG and financial results. Therefore, this paper discusses research perspectives and identify avenues for future research in last part, research perspectives and future research could focus on how to improve CG based on IT and the financial consequences of CG with IT.
Rural implementation of Girls' Programming Network (GPN)

A small-scale pilot study was conducted in north-west Tasmania to investigate adolescent girls’ willingness to participate in informal STEM education, through exploring their perceptions and experiences of computer science (CS), and their future aspirations. This pilot study was funded by an Inspiring Australia Public Science Event Grant, enabling the delivery of two local Girls’ Programming Network (GPN) workshops by the two Sydney-based GPN co-founders. The aim of this case study was to determine the viability of establishing an ongoing and sustainable northwest Tasmanian GPN, which would provide rural adolescent girls with opportunities to explore programming, connect them with mentors and role models, and show them what potential career opportunities exist beyond family and local contexts. Qualitative methods of data collection comprised focus group interviews and artefact elicitation with the participants, and individual interviews with the program co-founders. The results indicate that single-sex informal CS education opportunities are valued by adolescent girls, and that typical gender stereotypes can be changed due to the experience of engaging in them. The success of the pilot study indicates that establishing the GPN in a rural area to provide adolescent girls with free and fun CS experiences is worthwhile and viable.
V2492 Cygni: THE EARLY EVOLUTION OF THE 2010 OUTBURST

We present Gemini-North optical and near-IR observations of a young eruptive star in Cygnus, designated as V2492 Cygni in the General Catalog of Variable Stars. This object is one of two young stars, located within 2 deg of each other, that recently brightened by around 5 mag and were reported as possible new FU Orionis-type variables. The outburst spectrum of V2492 Cygni shows atomic emission features throughout the optical and near-infrared. In the optical, Hα is in emission and has an associated blueshifted absorption component. The far-red Ca ii triplet lines are also in emission and, as with Hα, possess significant blueshifted absorption. The optical TiO molecular bands are also in emission. In the near-infrared, Paβ, Brγ, and the CO overtone bandheads are strongly in emission. Such spectral characteristics are very similar to those exhibited by both EX Lupi, the progenitor of the EXor class of eruptive variables, during its 2008 extreme outburst, and V1647 Ori during its elevated phase in 2003. Additionally, we consider archival data on V2492 Cygni and investigate the pre-outburst nature of this young star. We construct a quiescent-phase spectral energy distribution which, via model fitting, gives insight into the circumstellar environment of the object prior to the current eruption. Our investigation strongly suggests that the V2492 Cygni outburst appears to be more consistent with an EXor event, a fact supported by its recent 2 mag fading and stochastic variability.
The Global Navigation Satellite System (GNSS): Positioning, Velocities, and Reﬂections

Since the inception and realization of the Global Positioning System (GPS) in the 1970-1980s, the Global Satellite Navigation System (GNSS) has become a ubiquous tool in civil, business, and scientiﬁc life. Major breakthroughs in our understanding of dynamic Earth processes were only achievable through this precise positioning technology. While positioning is the chief objective of the system, the nature of its design requires satellite signals to traverse the ionosphere and the troposphere, and results in signal reﬂections oﬀ the ground. In addition to crustal dynamics, this enables the study of the atmosphere and local environmental sensing, impacting ﬁelds far beyond solid earth research, including space physics, atmospheric science, glaciology, hydrology, and natural hazards. In this paper I review some of the history of this technology and its impact on the Earth sciences. Using the example of GPS, I introduce how satellite positioning systems work and how we can infer precise positions from the signals broadcast by the satellites. For this, I give an overview on reference systems, diﬀerent observation models, the predominant precise positioning strategies and how the various error terms can be corrected. Once a solid understanding of precise positioning is developed, I present some of the complications that arise in high-rate (1 or more sample per second observations) sub-daily and real-time kinematic positioning, which is of great utility in the characterization and monitoring of many natural hazards. GNSS enables observations beyond precise positioning. I provide background and observation models for instantaneous velocity estimations, useful in real-time applications particularly where precise orbits and intial positions are not available, and GNSS reﬂectometry, which allows to perform local environmental sensing around GNSS monuments, including the inference of snow depth or tidal heights. Throughout the paper, each method is illustrated by a number of applications either from the literature or novel work. The focus is on some highlights from the last decade of geodetic work, with a clear slant towards examples from solid Earth and hydrologic research.
Optimizing productivity on high capacity protein A affinity medium

Intellectual Property Notice: The Biopharma business of GE Healthcare was acquired by Danaher on 31 March 2020 and now operates under the CytivaTM brand. Certain collateral materials (such as application notes, scientific posters, and white papers) were created prior to the Danaher acquisition and contain various GE owned trademarks and font designs. In order to maintain the familiarity of those materials for long-serving customers and to preserve the integrity of those scientific documents, those GE owned trademarks and font designs remain in place, it being specifically acknowledged by Danaher and the Cytiva business that GE owns such GE trademarks and font designs.
The Effect of Problem-Based Learning Strategies and Direct Learning Strategies on Students' Fiqh Learning Outcomes

This study aims to determine whether there is a positive influence on the use of problem-based learning strategies and the use of direct learning strategies on Fiqh learning outcomes for MA Palapa Nusantara students. The type of research used in this research is quantitative research with an experimental research approach with Quasi-Experimental Design research methods. Data collection techniques in the study used tests, observations, and documentation. In the Experiment class, teachers' teaching activities are in the Good and Very Good categories, and the value of student learning activities is 90.2%. While in the Control class, the value of teacher teaching activities is in the Good and Very Good category, and the importance of student learning activities is 80.8%. The prerequisite test shows that the data is typi-cally distributed and homogeneous. It is concluded that using Problem Based Learning strategies can significantly improve achievement or learning outcomes. In contrast, direct learning strategies cannot substantially improve learning achievement or outcomes.
Influence of Ecap Process on Mechanical, Corrosion and Bacterial Properties of Zn-2ag Alloy for Wound Closure Devices

Actual polymeric wound closure devices are not optimal for load-bearing applications due to the low mechanical properties and the risk of inflammation and bacterial infection mainly produced by multifilament and braided configurations. Biodegradable metallic Zn alloys are promising materials candidates; however, mechanical performance, corrosion behaviour, and biological response should be controlled in order to inhibit the risk of inflammation and bacterial infection. To this end, a Zn-2Ag (2 wt.% Ag) alloy was processed by ECAP to evaluate the concurrent combined effect of grain refinement and Ag alloying on biodegradation and antibacterial activity. Two ECAP cycles were successfully applied to a Zn-2Ag alloy obtaining a homogeneous ultra-fine-grained structure in which nanoindentation maps suggested isotropic mechanical properties. Lower UTS and YS with higher elongation was reported after ECAP with similar corrosion rates as before processing. ECAP processed samples showed a homogeneous Ag + release below the minimum inhibitory concentration for S. Aureus and no antibacterial effect was observed by diffusion. As expected, the presence of Ag in Zn-Ag alloys reduced bacterial attachment. Nevertheless, ECAP processed Zn-2Ag provided an excellent antibacterial activity after 3 h probably caused by the uniformly degraded and thus, non-stable, surface observed after bacterial adhesion.
A new rare type of supernovae: hypervelocity stellar collisions at galactic centers

When a binary star system is tidally disrupted by a supermassive black hole at a galactic nucleus, one star is ejected at a high speed while the other remains in a tightly bound orbit around the black hole. The cluster of tightly bound stars builds over time, eventually creating a steady state in which the rate of collisions between these stars is similar to the rate of capturing new stars. A large fraction of the collisions occur near the periapsis of the orbits around the black hole, where the kinetic energies are sufficient to generate an explosive disruption of the two stars involved. The typical flare brightens for several days, with a peak luminosity that is comparable to the lower-luminosity end of known supernovae. The explosion lightcurve is followed by a longer flare due to accretion of ejected matter onto the black hole. Dedicated searches in the near universe could observe several such "collisional-supernovae" per year.
Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data

ABSTRACT The all-wave net radiation (Rn) at the land surface represents surface radiation budget and plays an important role in the Earth's energy and water cycles. Many studies have been conducted to estimate from satellite top-of-atmosphere (TOA) data using various methods, particularly the application of machine learning (ML) and deep learning (DL). However, few studies have been conducted to provide a comprehensive evaluation about various ML and DL methods in retrieving. Based on extensive in situ measurements distributed at mid-low latitudes, the corresponding Moderate Resolution Imaging Spectroradiometer (MODIS) TOA observations, and the daily from the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) used as a priori knowledge, this study assessed nine models for daily estimation, including six classic ML methods (random forest -RF, adaptive boosting - Adaboost, extreme gradient boosting -XGBoost, multilayer perceptron -MLP, radial basis function neural network -RBF, and support vector machine -SVM) and three DL methods (multilayer perceptron neural network with stacked autoencoders -SAE, deep belief network -DBN and residual neural network -ResNet). The validation results showed that the three DL methods were generally better than the six ML methods except XGBoost, although they all performed poorly in certain conditions such as winter days, rugged terrain, and high elevation. ResNet had the most robust performance across different land cover types, elevations, seasons, and latitude zones, but it has disadvantages in practice because of its highly configurable implementation environment and low computational efficiency. The estimated daily values from all nine models were more accurate than the corresponding Global LAnd Surface Satellite (GLASS) product.