Miracle-dz/UniFAR-FTUs huggingface dataset:
An empirical investigation of Tobin’s-Q augmented various Asset Pricing Models: Evidence from Pakistan

Despite the strong growing popularity of Asset Pricing Models, it is difficult to estimate which factor contributes significantly in explaining average excess portfolio returns particularly in emerging equity market. Using an extensive sample over Jan-1994-Dec-2020 period, this paper aims to extend the literature by augmenting Tobin-Q adjusted risk premium with various unconditional standard asset pricing models which seeks to postulate the nexus between expected portfolios stock returns and risk-factors using monthly data of 521 enlisted financial and non-financial firms from Pakistan Stock Exchange. The multiple time-series OLS regression analysis models are employed to analyze Tobin-q risk-factor augmented with various factors models. Fama and French (2015) five-factor model excessively explains average equity returns however, our results reveal that size, value, profitability and particularly Tobin-q factor are significant while market and investment factor are redundant in Pakistan Stock Exchange. The momentum factor shows weak results in describing average equity returns in the market. Based on Gibbons, Ross and Shanken (1989) test, our findings support Tobin-Q augmented Fama and French (2015) five-factor model as appropriate for pricing stocks returns in emerging market of Pakistan. The investors, portfolio managers and policy-makers should assume the Tobin-q factor while constructing diversified portfolios for investments in Pakistan Stock Exchange
X-ray image enhancement based on the dyadic wavelet transform

X-ray images are often of low contrast due to the subtle distinction of attenuation coefficients and scatter effect, which makes it difficult to distinguish signals from background. This paper proposes an image enhancement algorithm using the multi-scale dyadic wavelet transform. The algorithm includes two steps: 1) In order to enhance contrast, a non-linear mapping is performed on wavelet coefficients at different scales. Inhibition factors are then applied to reduce the impact of scatter; 2) In order to reduce the negative impact of noise amplification from the first step, wavelet coefficients are classified into two categories: irregular coefficients and edge-related and regular coefficients, and then filtered with different schemes for each category. Experimental results demonstrate that this algorithm effectively enhance the contrast of x-ray images. Examination is also done on CT reconstructions from multi-view projection data processed by the proposed method and significant improvement of image quality is observed. Our results are expected to offer great help to follow-up detection and recognition tasks.
A Survey of Indicators of Fat Content and Body Mass Index on the Physical Condition of Martial Arts Athletes in Kota Batu Ahead of the East Java Porprov VII

Physical conditions as a reference for athletes' abilities can be used as a supporting process for evaluation materials for coaches and athletes in assessing the abilities of their athletes after the training process is carried out. Some things that support the physical condition of athletes include anthropometry, fat content, body mass index (BMI), nutrition, psychology, environment, and the training process in each sport. In this case, BMI and fat content are part of this study to identify the relationship between physical condition and BMI and body fat levels of Kota Batu martial arts athletes with a total of 45 athletes. T a tool to measure BMI and body fat levels in this study using the Body Composition Analyzer, Tanita DC-360Phe method used in this study is a survey with descriptive data presentation that correlates indicators of fat content, and body mass index with the physical condition of martial athletes which include: (1) arm muscle strength, (2) abdominal muscle strength, (3) leg muscle strength, (4) back muscle strength, (5) balance, (6) leg muscle power, (7) arm muscle power, (8) agility and (9) cardiovascular endurance. The physical fitness level of Kota Batu martial arts athletes has a fairly good percentage with an average score of 76% for male athletes and 77% for female athletes. Athletes have a fairly ideal body condition because the fat mass of all athletes is at normal levels and 33 athletes are at the ideal BMI.
Back-Reaction of Classical Fields on Black Hole Area Law

(This is the unpublished manuscript while parts are corrected and included in version III of arXiv:1602.00964 which is submitted to the journal.) We study the back-reaction of classical Maxwell field and massive scalar field on the BTZ black hole entropy. The exact values of the modification which correct the black hole area law are found. We discuss the similar properties between the scalar and Maxwell fields which are investigated in both of Coulomb gauge and Lorentz gauge. The dependences of mass and mode number on the black hole entropy are illustrated. We also study the back-reaction by D branes, which are described by DBI action, and explicitly check that the classical solution which gives the black hole entropy precisely corrects the black hole area law. Our results extend the calculations of the generalized gravitational entropy proposed in recent by Lewkowycz and Maldacena [1].
Vegetation Productivity and Precipitation Use Efficiency across the Yellow River Basin: Spatial Patterns and Controls

In arid and semi-arid climate zones, understanding the spatial patterns and biogeographical mechanisms of net primary production (NPP) and precipitation use efficiency (PUE) is crucial for assessing the function and stability of ecosystem services, as well as directing ecological restoration. Although the vegetation coverage has changed dramatically after the construction of several ecological restoration projects, due to limited observation data, fewer studies have provided a thorough understanding of NPP and PUE’s recent spatial patterns and the controlling factors of different vegetation types in the Yellow River Basin (YRB). To narrow this gap, we integrated remote-sensing land-cover maps with long-term MODIS NPP and meteorological datasets to comprehend NPP and PUE spatial patterns in YRB. Furthermore, we applied structural equation models (SEM) to estimate the effect intensity of NPP and PUE controlling factors. The results showed that along geographical coordinates NPP and PUE decreased from southeast to northwest and trends were roughly consistent along latitude, longitude, and elevation gradients with segmented patterns of increasing and decreasing trends. As for climate gradients, NPP showed significant linear positive and negative trends across the mean annual precipitation (MAP) and the arid index (AI), while segmented changes for PUE. However, the mean annual average temperature (MAT) showed a positive slope for below zero temperature and no change above zero temperature for both NPP and PUE. SEM results suggested that AI determined the spatial pattern of NPP, whereas PUE was controlled by MAP and NPP. As the AI becomes higher in the further, vegetation tends to have decreased NPP with higher sensitivity to water availability. While artificial vegetation had a substantially lower NPP than original vegetation but increased water competition between the ecosystem and human society. Hence further optimization of artificial vegetation is needed to satisfy both ecological and economic needs. This study advanced our understanding of spatial patterns and biogeographic mechanisms of NPP and PUE at YRB, therefore giving theoretical guidance for ecological restoration and ecosystem function evaluation in the face of further climate change.
Spacelike translating solitons of the mean curvature flow in Lorentzian product spaces with density

By applying suitable Liouville-type results, an appropriate parabolicity criterion, and a version of the Omori-Yau's maximum principle for the drift Laplacian, we infer the uniqueness and nonexistence of complete spacelike translating solitons of the mean curvature flow in a Lorentzian product space $ \mathbb R_1\times\mathbb P^n_f $ endowed with a weight function $ f $ and whose Riemannian base $ \mathbb P^n $ is supposed to be complete and with nonnegative Bakry-Émery-Ricci tensor. When the ambient space is either $ \mathbb R_1\times\mathbb G^n $, where $ \mathbb G^n $ stands for the so-called $ n $-dimensional Gaussian space (which is the Euclidean space $ \mathbb R^n $ endowed with the Gaussian probability measure) or $ \mathbb R_1\times\mathbb H_f^n $, where $ \mathbb H^n $ denotes the standard $ n $-dimensional hyperbolic space and $ f $ is the square of the distance function to a fixed point of $ \mathbb H^n $, we derive some interesting consequences of our uniqueness and nonexistence results. In particular, we obtain nonexistence results concerning entire spacelike translating graphs constructed over $ \mathbb P^n $.
Which stresses affect the glide of screw dislocations in bcc metals?

By direct application of stress in molecular statics calculations we identify the stress components that affect the glide of 1/2〈111〉 screw dislocations in bcc tungsten. These results prove that the hydrostatic stress and the normal stress parallel to the dislocation line do not play any role in the dislocation glide. Therefore, the Peierls stress of the dislocation cannot depend directly on the remaining two normal stresses that are perpendicular to the dislocation, as proposed by Koester A, Ma A, Hartmaier A. Acta Mater 2012;60:3894 but, instead, on their combination that causes an equibiaxial tension-compression (and thus shear) in the plane perpendicular to the dislocation line. The Peierls stress of 1/2〈111〉 screw dislocations then depends only on the orientation of the plane in which the shear stress parallel to the Burgers vector is applied and on the magnitude and orientation of the shear stress perpendicular to the slip direction.
Wetland use by Greater White-fronted Geese and spatial overlap with waterfowl conservation priority areas in Mexico

Greater White-fronted Geese ( Anser albifrons frontalis ) use both agricultural and wetland habitats throughout winter with changes in use exhibited temporally and in relation to environmental and landscape factors. Currently, an unknown proportion of Greater White-fronted Geese winter in Mexico, largely along the Gulf Coast and in the Central Highlands, where information regarding wintering ecology is largely unknown. Because conservation efforts for waterfowl typically focus on wetland habitats, understanding factors influencing wetland use is imperative to developing informed conservation strategies. During winters, 2016– 2018, we used remote sensing to measure characteristics of 91 wetlands used by GPS-tagged Greater White-fronted Geese, and modeled how wetland and landscape variables influenced wetland use and selection. Our top model of wetland use indicated that larger wetlands and wetlands that were closer to other used wetlands were related to increased use. There was an interaction between wetland type and distance to agriculture, indicating that Greater White-fronted Geese exhibited increased use of emergent herbaceous/grass and woody wetland types that were in closer proximity to agriculture. Our wetland-selection model indicated that woody and emergent wetlands that were larger in size were selected at greater rates than available wetlands on the landscape. Additionally, we conducted a spatial comparison of used wetlands in this study with wetlands previously identified as important for waterfowl conservation in Mexico in the literature. Of 91 wetlands used by geese, only 7.7% fell within wetland complexes identified as priority for waterfowl conservation or specific wetlands important to Greater White-fronted Geese by previous research, and all were within the Laguna Madre de Mexico and Rio Grande Delta regions in Tamaulipas. Wetlands in Mexico are being degraded at a rapid rate, and information such as this is important for future management and conservation-planning efforts throughout Mexico for wetland-dependent species such as the Greater White-fronted Goose. la conservation dans tout le Mexique pour les espèces qui dépendent de milieux humides comme l’Oie rieuse.
Why Not Blow the Whistle on Health Care Insurance Fraud? Evidence from Jiangsu Province, China

Purpose To identify the factors that influence whistleblowing behavior as it relates to health care insurance fraud in Jiangsu Province, China. Methods To construct a factor model and formulate research hypotheses using the Motivation–Opportunity–Ability framework. We designed a questionnaire containing 24 items and distributed it on-site to 2081 respondents in Jiangsu Province, China. Afterward, we applied structural equation modeling to validate the research hypotheses. Results Policy awareness negatively contributes to whistleblowing behavior, risk perception does not reduce the incentive to blow the whistle, and an inability to recognize fraud is another critical barrier to converting whistleblowing intentions into behavior. Conclusion Practices that are likely to promote citizen whistleblowing on insurance fraud may focus on the constraints identified by the comprehensive Motivation–Opportunity–Ability framework.
The Therapeutic Potential of Targeted Nanoparticulate Systems to Treat Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a widespread autoimmune inflammatory disease. It implicates damage to bones, cartilage, and joints with uncertain pathogenesis. It is coupled with an elevated risk of cardiovascular complications and human disability. The conventional dosage forms for RA treatment pose numerous problems including poor efficacy, large dosages, frequent administration, limited responsiveness, greater expenses, and severe side effects. The nanoparticulate systems are emerging as a new thought for the diagnosis and treatment of RA. Anti-inflammatory drug-loaded nanoparticulate systems aid in the active and passive targeting of the inflamed region. Improved bioavailability and targetability are achieved by using these systems. In this review, the pathophysiology of RA and its conventional treatment has been discussed. The role of various nanoparticulate systems for passive and active targeting of RA has been reviewed. The authors have summarized the current practices in the typical and novel nanosystems to improve the quality of life in RA patients.
Comprehensive Analysis and Evaluation of DC-Link Voltage and Current Ripples in Symmetric and Asymmetric Two-Level Six-Phase Voltage Source Inverters

Multiphase drives (MPD) in general and six-phase in particular have been gaining popularity in many industries, which calls for a proper multiphase inverter (MPI) design. For voltage source inverter (VSI)-fed drives, the knowledge of voltage and current stresses on the dc-link are imperative for input capacitor sizing. To this end, the voltage and current stresses on the dc-link capacitor in two-level six-phase VSIs are examined thoroughly in this article for two configurations of load/winding spatial distribution: symmetric and asymmetric. First, the harmonic spectrum of the input dc current of each inverter is analyzed in detail by benchmarking them against the conventional three-phase VSI, to precisely establish the dc-capacitor requirement reduction in six-phase counterparts. Second, analytical formulae for the dc-link capacitor voltage ripples are derived for both configurations. Third, simple formulae for dc-capacitor sizing for six-phase VSIs with different load configurations are provided. The accuracy of the derived formulae is verified by simulation and experimental testing at various power factors and modulation depth. It is found that six-phase VSI supplying symmetric and asymmetric loads reaps 10% and 7% lower dc-link current ripples, respectively. Hence, six-phase symmetric loads yield the smallest capacitor size.
Spin-liquid and magnetic phases in the anisotropic triangular lattice: The case of κ − ( ET ) 2 X

The two-dimensional Hubbard model on the anisotropic triangular lattice, with two different hopping amplitudes $t$ and ${t}^{\ensuremath{'}}$, is relevant to describe the low-energy physics of $\ensuremath{\kappa}\text{\ensuremath{-}}{(\text{ET})}_{2}\text{X}$, a family of organic salts. The ground-state properties of this model are studied by using Monte Carlo techniques, on the basis of a recent definition of backflow correlations for strongly correlated lattice systems. The results show that there is no magnetic order for reasonably large values of the electron-electron interaction $U$ and frustrating ratio ${t}^{\ensuremath{'}}/t=0.85$, suitable to describe the nonmagnetic compound with $\text{X}={\text{Cu}}_{2}{(\text{CN})}_{3}$. On the contrary, N\'eel order takes place for weaker frustrations, i.e., ${t}^{\ensuremath{'}}/t\ensuremath{\sim}0.4\text{--}0.6$, suitable for materials with $\text{X}={\text{Cu}}_{2}{(\text{SCN})}_{2}$, $\text{Cu}[\text{N}{(\text{CN})}_{2}]\text{Cl}$, or $\text{Cu}[\text{N}{(\text{CN})}_{2}]\text{Br}$.
A BGK approximation to nonlinear parabolic initial‐boundary value problems

We present a relaxation semilinear system of conservation laws with source which approximates nonlinear parabolic equations with initial and boundary conditions. The system can be interpreted as a BGK (Bhatnagar, Gross, Krook) model with a finite number of velocities. We prove the well-posedness of the model, a priori estimates and we obtain the convergence towards the solution of the parabolic problem. Moreover we prove a similar result for a weakly degenerate problem.
On the technique for the recovery of the spectrum of turbulence in astrophysical discs

We present a method that can be used to recover the spectrum of turbulence from observations of optically thin emission lines formed in astrophysical disks. Within this method we analyze how line intensity fluctuations depend on the angular resolution of the instrument, used for the observations. The method allows us to restore the slope of the power spectrum of velocity turbulent pulsations and estimate the upper boundary of the turbulence scale.
A System for Orchestrating Multiple Procedurally Generated Content for Different Player Profiles

We propose a system able to orchestrate the procedural generation of three creative facets (levels, narrative, and rules), using quality-diversity algorithms to promote diversity while converging to the desired solutions and able to satisfy different player's profiles. We aim to facilitate the project's reproducibility and extension by presenting the system's architecture and high-level design decisions and showcasing how we decoupled it enough to change algorithms. Our generation starts with a grammar-based quest generator that works as a frame for two quality-diversity algorithms: a level generator, which also creates locked-door puzzles, and an enemy generator, which selects their visuals based on their weapons. A rule-based profile analysis uses a pretest questionnaire to classify the player into four profiles, and the quest generator creates different content for each of them. We use a game prototype to test our system with over 83 players, playing over 204 levels and answering a posttest questionnaire after each. Results show the game and contents were well received, and there was a difference in perception between profiles. Players who played content based on their profile enjoyed it more than those playing content from another profile.
Conceptualization of Psychotherapy Incorporating Equine Interactions in the United States

While several systematic and mapping reviews have been published in the last decade on the psychological effects of interacting with horses in therapy services, little has been written about how licensed mental health therapists in the United States should best understand, describe, and conceptually position interactions with horses within their clinical practice. To this end, a healthcare-aligned conceptualization of equine interactions in psychotherapy and counseling is presented. Drawing from competencies and statements published by the American Counseling Association and the Human-Animal Interaction section of the American Psychological Association, the proposed conceptualization describes interactions with horses during psychotherapy as a technique and enhancement to existing treatment approaches, not as a standalone intervention or therapy. Additionally, the conceptualization aligns with legal and ethical responsibilities, and the professional identity of the licensed mental health therapist. The proposed conceptualization emphasizes the importance of using science-based information about horses so that their role and function in psychotherapy sessions can be more accurately understood. The conceptualization is proposed to have positive effects on the day-to-day practice of licensed mental health therapists in areas such as professional communication, treatment planning and provision, and engagement with healthcare processes such as service coding, reimbursement and insurance. The conceptualization could also be of use in research efforts as it clarifies how horse interactions should be understood in the context of treatment, which, in turn, affects research design. Use of the proposed conceptualization may help safeguard clients, other stakeholders, horses, and the licensed mental health therapists who incorporate interactions with horses in the provision of psychotherapy.
Classification System of National Music Rhythm Spectrogram Based on Biological Neural Network

National music is a treasure of Chinese traditional culture. It contains the cultural characteristics of various regions and reflects the core value of Chinese traditional culture. Classification technology classifies a large number of unorganized drama documents, which are not labeled, and to some extent, it helps folk music better enter the lives of ordinary people. Simulate folk music of different spectrum and record corresponding music audio under laboratory conditions Through Fourier transform and other methods, music audio is converted into spectrogram, and a total of 2608 two-dimensional spectrogram images are obtained as datasets. The sonogram dataset is imported into the deep convolution neural network GoogLeNet for music type recognition, and the test accuracy is 99.6%. In addition, the parallel GoogLeNet technology based on inverse autoregressive flow is used. The unique improvement is that acoustic features can be quickly converted into corresponding speech time-domain waveforms, reaching the real-time level, improving the efficiency of model training and loading, and outputting speech with higher naturalness. In order to further prove the reliability of the experimental results, the spectrogram datasets are imported into Resnet18 and Shufflenet for training, and the test accuracy of 99.2% is obtained. The results show that this method can effectively classify and recognize music. The experimental results show that this scheme can achieve more accurate classification. The research realizes the recognition of national music through deep learning spectrogram classification for the first time, which is an intelligent and fast new method of classification and recognition.