Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyclical Dynamics of Shopping: Aggregate Implications on Labor and Product Markets

I propose a theory of price hunting over the business cycle with empirical evidence. In the U.S. data, not only is aggregate shopping time lower in recession but also it is more pronounced for unemployed individuals than employed ones. However, the standard price search models based on the income effect predict opposites. In this paper, I build a model of endogenous price hunting in decentralized labor and product markets. The model predicts that the joint effect of a procyclical return to shopping, which this paper newly finds, and the standard income effect explains the data. Empirical evidence based on the consumer panel data supports the arguments. Lastly, I identify that while search frictions amplify business cycle fluctuations, endogenous shopping effort consistent with the data does not. JEL Classification: E31, E32, J64
FACTORS AFFECTING TRUST IN SUPPLY CHAIN COMMITMENT

Trust is one of the most important aspects in successful supply chain relationship that encourages commitment in the relationship. A supply chain relationship which lacks of trust and commitment may affect the performance of partners which in turn results in high-cost or even loss of current suppliers or customers. This research's objective is to measure the factors that affect level of trust and the impact of trust on supply chain commitment in Electronic Distribution business in Bangladesh. To measure the factors affecting trust and the impact of trust on commitment, items were adapted from the study conducted by Kwon and Suh (2004). Data were collected from 54 managers, branch managers and managing directors of electronic distribution business in Chattogram. Convenience sampling technique was used to select respondents. The results indicate that a firm’s trust in its supply chain partner is highly associated partner’s specific asset investments (positively) and behavioral uncertainty (negatively). It is also found that information sharing reduces the level of behavioral uncertainty, which, in turn, improves the level of trust. A partner’s reputation in the market has a positive impact on the trust-building process, whereas a partner’s perceived conflict creates a negative impact on trust. Finally, the level of commitment is strongly related to the level of trust. Managerial implications, limitations and further research directions are also discussed.
Sporthesia: Augmenting Sports Videos Using Natural Language

Augmented sports videos, which combine visualizations and video effects to present data in actual scenes, can communicate insights engagingly and thus have been increasingly popular for sports enthusiasts around the world. Yet, creating augmented sports videos remains a challenging task, requiring considerable time and video editing skills. On the other hand, sports insights are often communicated using natural language, such as in commentaries, oral presentations, and articles, but usually lack visual cues. Thus, this work aims to facilitate the creation of augmented sports videos by enabling analysts to directly create visualizations embedded in videos using insights expressed in natural language. To achieve this goal, we propose a three-step approach – 1) detecting visualizable entities in the text, 2) mapping these entities into visualizations, and 3) scheduling these visualizations to play with the video – and analyzed 155 sports video clips and the accompanying commentaries for accomplishing these steps. Informed by our analysis, we have designed and implemented Sporthesia, a proof-of-concept system that takes racket-based sports videos and textual commentaries as the input and outputs augmented videos. We demonstrate Sporthesia's applicability in two exemplar scenarios, i.e., authoring augmented sports videos using text and augmenting historical sports videos based on auditory comments. A technical evaluation shows that Sporthesia achieves high accuracy (F1-score of 0.9) in detecting visualizable entities in the text. An expert evaluation with eight sports analysts suggests high utility, effectiveness, and satisfaction with our language-driven authoring method and provides insights for future improvement and opportunities.
Green Factor Influence on the Yield of Stocks and Bonds in the Russian Financial Market

In this paper we test whether environmental characteristics of assets influence their returns for the case of Russian financial market. Our main hypothesis based on the relevant literature is that if a spread between “green” and “brown” assets’ yield exists, it should be in favour of the brown assets. We employ relevant econometric models separately for stocks and for bonds. For the stock market we used realized returns and estimated the role of the green factor in the yield using the three-factor Fama–French model. While the resulting coefficient was not significant, on the whole we have observed that the realized return of the climate-risk hedge portfolio had a negative value over a nearly ten-year observation period. We have also demonstrated the applicability of the green factor calculations for estimating the degree of climate risk exposure for individual companies. Using data on a number of green bonds and their chosen “twin” bonds, we calculate the difference in the premium in the yield to maturity over that of a similar government bond for all pairs of “twin” bonds and proceed to check if this difference is significant, and if it can be attributed to the Greenium factor. We find that over the stable period in Russian financial markets (allowing for the most stable results) “green” bonds have lower yield to maturity a result that is in line with previous results for other markets and suggests that green financing might be cheaper for companies. On the whole our results suggest that environmental considerations might be relevant in the Russian financial market during stable macroeconomic periods.
An observational study of the surgical site infection rate in a General Surgery Department at a General Hospital in Malaysia

Background: Surgical site infection (SSI) is one of the most common healthcare-associated infections globally. A consequence of infection is wound dehiscence with an associated high mortality rate. Method: A surveillance study of SSI was undertaken in a Surgical Department of a General Hospital in East Malaysia to determine the SSI incidence and to identify the risk factors and outcomes associated with SSI. This was a prospective cohort study of 222 patients, who were admitted for either elective or emergency operations. Results: The SSI incidence was 11.7% (n=26) and the risk factors associated with an SSI were male gender (OR 3.47, 95% CI 1.40–8.64; AOR 2.54, 95% CI 0.98–6.55, p =0.054) and surgical wounds classified as contaminated or dirty (OR 5.49, 95% CI 2.26–13.34; AOR 4.53, 95% CI 1.82–11.23, p =0.001). The re-admission rate was 19.2% and the mean length of stay was 20.5 days (SD=12.4). Additional microbiological data identified that Escherichia coli was the most common isolated pathogen. This study was the first prospective study on SSI incidence in the hospital where the corresponding author works and has helped to establish a baseline SSI rate to inform subsequent audits.
Assessment of genetic advance and correlation coefficient for yield and yield attributed traits of RIL population in basmati rice ( Oryza sativa L.)

During kharif 2018, one hundred thirty ( Oryza sativa L.) RILs derived from a cross between Basmati 370 and Pusa basmati1121 were evaluated for fifteen quantitative traits related to grain quality and yield to examine the nature and magnitude of genetic variability, correlation coefficient analysis and genetic advance. Estimates of correlation coefficient, genetic variability, heritability and genetic advance in per cent of mean were also obtained for the above fifteen traits. Analysis of variance revealed that significant amount of genetic variability was present in the entire characters studied. The highest positive correlation was observed between PL and PH (r=0.33), ET and PH (r=0.21) followed by GW and GPP (r=0.20). Some of the traits showed then significant negative correlation with each other like YPP and PL (r=-0.25), KE and GW(r=-0.02) and KE and YPP (r=-0.11). High phenotypic variation was observed for yield per plant (40.25%), effective tillers per plant (42.28%) and amylose content (37.41%), Moderate phenotypic variations was recorded in plant height (12.23%), panicle length (11.99%) and so many other traits. Therefore, the present study was undertaken to find the genetic variability, correlation coefficient analysis, genetic advance through RIL population for the Selection criteria of fine rice lines.
Using machine learning to detect non-triviality of knots via colorability of knot diagrams

We apply machine learning to combinatorial knot theory, specifically, we consider a classical problem of deciding if a knot diagram represents the trivial knot as a classification problem. As a part of this process, we use a reformulation of this problem expressed via so-called Fox coloring of knot diagrams or, more generally, coloring knot diagrams with elements of algebraic structures called quandles
The Relationship between Management Accounting Systems and Quality of Accounting Information in the Jordanian Industrial Sectors

: The purpose of this paper is to investigate the effect of the management accounting systems on quality of accounting information in the Jordanian companies. The data were collected by distributing 144 mailed questionnaires to management accountants, senior accounting executives, and senior or executive-level managers. In addition, model was used PLS-SEM to analysis. The study found that just in time, target costing, and balanced scorecard significant effect to quality of accounting information. According to the research findings, the management accounting systems have a meaningful and positive impact on the quality of accounting information. The results contribute to a better understanding concerning the benefit of management accounting systems and quality of accounting information in Jordanian industrial sectors.
The Role of Experiential Knowledge and Innovation in International Creative Industry’s Performance

: Creative industries from emerging markets are increasingly engaging in internationalization. Nevertheless, there is limited research on how these firms achieved international performance. The purpose of this paper was to verify the connection between experiential knowledge and innovation and their impacts on the international performance of creative industries. Based on 247 Indonesian SMEs data conducted in creative industries, they were analyzed by a structural equation model. Results showed that an innovation mediates the relation between experiential knowledge and international performance. Yet, the influence of experiential knowledge is lower when mediated by innovation. This research has scant contributed but it increased the number of empirical studies which investigate the link between knowledge and internationalization of SME performance in emerging market contexts. international performance. Knowledge may generate appropriate organizational capabilities embedded into the firms’ cultures through ongoing replication of routines and produces a unique configuration of resources. Limited empirical research in the field of internationalization in creative industries has motivated the author to analyze this case by using the theory of SMEs internationalization. The results showed that the experiential knowledge that consist of internationalization knowledge, institutional knowledge, business knowledge, technological knowledge and innovation have significant influences on the international performance of firms in creative industry sector. Moreover, this study confirms that experiential knowledge of the entrepreneur or manager encourage innovation and offer a description of the international performance in the creative industry scope.
Validating the Theoretical Foundations of Residual Networks through Experimental Testing

Convolutional neural networks traditionally initialize their learning parameters randomly and symmetrically about zero. This initialization makes it difﬁcult for convolutional layers to ”learn” the identity mapping, which in theory forces layers to alter intermediate mappings which may offer better performance than the overall network. The residual network architecture aims to address this problem, however the foundational theory behind their performance has yet to be established. (Hardt & Ma, 2016) explores the theoretical foundations of residual networks while also providing experimental results. We aim to validate and replicate their ﬁndings through our own practical experiments.
Exact Unbiased Inverse of the Anscombe Transformation and its Poisson-Gaussian Generalization

Digital image acquisition is an intricate process, which is subject to various errors. Some of these errors are signal-dependent, whereas others are signal-independent. In particular, photon emission and sensing are inherently random physical processes, which in turn substantially contribute to the randomness in the output of the imaging sensor. This signal-dependent noise can be approximated through a Poisson distribution. On the other hand, there are various signal-independent noise sources involved in the image capturing chain, arising from the physical properties and imperfections of the imaging hardware. The noise attributed to these sources is typically modelled collectively as additive white Gaussian noise. Hence, we have three common ways of modelling the noise present in a digital image: Gaussian, Poisson, or Poisson-Gaussian. Image denoising aims at removing or attenuating this noise from the captured image, in order to provide an estimate of the underlying ideal noise-free image. For simplicity, denoising algorithms often assume the noise to be Gaussian, and ignore the signal-dependency. However, in an image corrupted by signal-dependent noise, the noise variance is typically not constant and varies with the expectation of the pixel value. Thus, for the removal of signal-dependent noise, we can either design an algorithm specifically for the particular noise model, or use an indirect three-step variance-stabilization approach. In the indirect approach, the noisy image is first processed with a variance-stabilizing transformation (VST), which renders the noise approximately Gaussian with a known constant variance. Then the transformed image is denoised with a Gaussian denoising algorithm, and finally an inverse VST is applied to the denoised data, providing us with the final estimate of the noise-free image. For the Poisson and Poisson-Gaussian cases, the most well-known VSTs are the Anscombe transformation and the generalized Anscombe transformation, respectively. The former of these was introduced in the late 1940s, and has been in wide use ever since in all areas of applied statistics where the Poisson distribution is relevant. In addition to a suitable VST, the above indirect denoising process requires a properly designed inverse VST. Unfortunately, the importance of the inverse VST is often neglected. The simple inverse VST obtained by taking the direct algebraic inverse of the VST generally leads to a biased estimate. Usually the issue of bias is addressed by using an asymptotically unbiased inverse, but also this inverse remains highly inadequate, especially for low-intensity data (e.g., for an image captured in a dark environment or with a very short exposure time).
Estimate of genetic variability and correlation coefficients for some quantitative characters in bread wheat (Triticum aestivum L.)

To improve wheat in terms of yield and other agronomic characters, twenty-five (25) varieties of bread wheat were selected to test the amount phenotypic and genotypic variability present and phenotypic correlation coefficients in relation to yield. High genetic coefficient of variation was obtained for weight of main spike and awn length. Heritability was found to be high for awn length, spike length, weight of the main spike and plant height. Total tillers per plant, spike length and number of grains per spike had moderate heritability with high genetic advance. Grain yield per plant was high and positively correlated with effective tiller per plant. A positive significant correlation of yield was observed with length of spike, spike lets per spike, weight of main spike and plant height. Effective number of tiller and weight of the main spike had high heritability with high genetic advance and significant positive correlation with yield. L. ).
Critical exponent for the quantum Hall plateau transition (Spectra of Random Operators and Related Topics)

In this article we will briefly review our work on estimating the critical exponent of the Anderson transition at the centre of a Landau level. We review some basic facts about the quantum Hall effect and briefly describe how the critical exponent is measured. We explain why physicists think critical exponents are important. We also explain how the exponent can be estimated numerically and to what extent our current estimate is in agreement with experiments.
Low-frequency asymptotic form of the self-energy parts of a superfluid Bose system at T=0

A functional integration method is used to obtain the first two terms of the asymptotic form of the Green's functions at (.omega.,k) =p.-->. 0 and the principal asymptotic terms of the self-energy parts of three-dimensional and two-dimensional superfluid Bose systems at T=0. It is shown that the anomalous self-energy part tends to zero like (ln Rp)/sup -1/ for three-dimensional system and like p for the two-dimensional system.
EFFORT TO ACHIEVE QUALITY JOB THROUGH INCREASING NURSE PERFORMANCE MOTIVATION

Abstract Objective : The era of globalization is a challenge for health companies to keep abreast of trends and issues in the health sector. The challenges of health companies are not only external factors, Human Resources is one of the challenges that must be solved by health companies, especially the motivation of nurses. Method: The method in this research is Literature Review. The purpose of this research is to improve company performance through employee motivation. The search method uses the Prisma 2020 chart, the literature search for the authenticity of this research is carried out with a literature review using the keywords "Performance Motivation" AND "Quality Jobs"" from 2020 to 2022. The search results obtained 8,430 articles but only 25 articles that match the criteria study. Articles obtained from Scopus, ScienceDirect, ProQuest and PubMed, google scholar Findings: The results of 15 journal articles related to Performance Motivation, show that motivation affects employee performance, both motivation as an independent variable, dependent variable or intermediary variable, all show that there is a very strong relationship between motivation and employee performance in general. Based on previous research, there is a positive and significant influence between work motivation and employee performance Conclusion: Based on the results of the Literature Review, it was found that there is a positive and strong relationship between Performance Motivation and Work Quality. As an effort to improve the quality of work, it is necessary to meet the variables that affect work motivation such as psychological motivation, safety motivation, social motivation, reward motivation, and actualization motivation, leadership, etc. Keyword : Quality Job, Nurse Performance Motivation
Interpreting the Observed Positive Correlation between the Event-integrated Fluence and the Rollover Energy of Solar Energetic Particle Events by the PAMELA Mission with Coupled Hydromagnetic Wave Excitation and Proton Acceleration at Shocks in the Low Corona

An analytical model for diffusive shock acceleration (DSA) at one-dimensional stationary planar shocks in the lower corona is presented. The model introduces an upstream escape boundary through which a constant flux of protons streaming upstream out of the system is allowed. The nonvanishing flux of streaming protons out of the system limits the maximum attainable energy of DSA and produces a rollover in the high-energy spectra of the shock-accelerated protons. The condition for the rollover energy derived from the model can account for the approximately linear relation between the natural logarithm of event-integrated fluences and the natural logarithm of rollover energies as demonstrated in Bruno et al. Solar energetic particle (SEP) events with higher integrated fluences in principle exhibit higher rollover energies since proton-excited hydromagnetic waves in the turbulent sheath reduce the proton diffusion coefficient and throttle the upstream streaming of protons. The consistency between the observation and the theory of DSA at shocks in the lower corona serves as evidence for the shock origin of protons of the highest energies in large SEP events.
HgGa2Se4 under high pressure: An optical absorption study

High‐pressure optical absorption measurements have been performed in defect chalcopyrite HgGa2Se4 to investigate the influence of pressure on the bandgap energy and its relation with the pressure‐induced order–disorder processes that occur in this ordered‐vacancy compound. Two different experiments have been carried out in which the sample undergoes either a partial or a total pressure‐induced disorder process at 15.4 and 30.8 GPa, respectively. It has been found that the direct bandgap energies of the recovered samples at 1 GPa were around 0.15 and 0.23 eV smaller than that of the original sample, respectively, and that both recovered samples have different pressure coefficients of the direct bandgap than the original sample. A comprehensive explanation for these results on the basis of pressure‐induced order–disorder processes is provided.
Differences in maternally inherited and age-related de novo mitochondrial DNA variants between ART and spontaneously conceived individuals associate with low birth weight

Background Children born using assisted reproductive technologies (ART) have an increased risk of a lower birth weight, the cause of which remains unclear. As a causative factor, we hypothesized that variants in the mitochondrial DNA (mtDNA) that are not associated with disease, may explain changes in birth weight. Methods We deep-sequenced the mtDNA of 451 ART and spontaneously conceived (SC) individuals, 157 mother-child pairs and 113 individual oocytes from either natural menstrual cycles or cycles with ovarian stimulation (OS). The mtDNA genotypes were compared across groups and logistic regression and discriminant analysis were used to study the impact of the different factors on birth weight percentile. Results ART individuals more frequently carried variants with higher heteroplasmic loads in protein and rRNA-coding regions. These differences in the mitochondrial genome were also predictive of the risk of a lower birth weight percentile, irrespective of the mode of conception but with a sex-dependent culture medium effect. The higher incidence of these variants in ART individuals results both from maternal transmission and de novo mutagenesis, which we found not to be caused by OS but to be associated to maternal ageing. Conclusions MtDNA variants in protein and rRNA coding regions are associated with a lower birth weight and are more frequently observed in ART children. We propose that these non-disease associated variants can result in a suboptimal mitochondrial function that impacts birth weight. Future research will establish the long-term health consequences of these changes and how these findings will impact the clinical practice and patient counselling in the future.