Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Commercial Banks Profitability in Malaysia

The main goal of this study is to identify the factors that influence the profitability of commercial banks in Malaysia by examining recent data from 2010 to 2020. To achieve this objective, the study uses Return on Assets (ROA) as a measure to assess the relationship between capital adequacy, credit risk, management efficiency, and liquidity risk. The research collects data on ROA, capital adequacy, credit risk, management efficiency, and liquidity risk from Bursa Malaysia and company websites. Additionally, secondary data sources are utilized to gather information and provide evidence for the analysis. The aim of the investigation is to assess whether the determinants of commercial bank profitability in Malaysia are capital adequacy, credit risk, management efficiency, and liquidity risk. Multiple Linear Regression is employed to examine the factual relationship and evaluate the hypotheses, and the software used to analyze the results is E-views 2012.
Concurrent validity of VmaxPro, Kinovea, and Speedograph for the assessment of peak barbell velocity during the bench press: A comparison of technological approaches and historical evolutions

Measurement of barbell velocity is a simple and effective way to control strength training. To assess the concurrent validity of different technological approaches measuring barbell velocity, video-analysis (Kinovea), linear velocity transducer (Speedograph), and an inertial measurement unit (V max Pro) were compared. Sixty-eight female and male sport science students lifted two repetitions in the bench press exercise at self-selected barbell loads. Peak vertical barbell velocity (V max ) was parallel measured during the concentric phase of the lift using the aforementioned devices. Concordance correlation coefficient (CCC), Deming regression (DR) and Bland-Altman analysis (BA) were used to assess relative and absolute concurrent validity of V max measured with Kinovea, Speedograph, and V max Pro. Results confirmed high concurrent validity of Speedograph and V max Pro (CCC = 0.99, standard deviation of differences [SDD] = 0.04 m∙s -1 ) without detecting proportional or constant bias. In contrast, V max measured with Kinovea showed poor concurrent validity to Speedograph (CCC = 0.83) and V max Pro (CCC = 0.81) with significant proportional and constant bias. Regression based re-calibration of V max from Kinovea resulted in an SDD = 0.09 m∙s -1 compared to Speedograph and an SDD = 0.08 m∙s -1 compared to V max Pro. Among the three tested devices, V max assessed using Kinovea showed poor concurrent validity. Furthermore, as Kinovea showed proportional bias compared to Speedograph and V max Pro, application-specific re-calibration of Kinovea should be applied when barbell velocity data is compared to Speedograph and V max Pro.
First Report of Rickettsia conorii in Hyalomma kumari Ticks

Simple Summary Ticks are blood-feeding ectoparasites that transmit life-threatening pathogens to humans and animals. Only 10% of all identified tick species have been screened for different tick-borne pathogens. Hyalomma ticks are associated with a wide range of pathogens including Theileria species, Babesia species, Anaplasma species, Ehrlichia species, and Rickettsia species. Moreover, ticks of genus Hyalomma are vectors for the Crimean-Congo hemorrhagic fever (CCHF), a serious threat endemic in Pakistan. In Pakistan, different tick species have been found positive for rickettsial agents; however, Hyalomma kumari ticks have never been investigated for any potential pathogens. In this work, H. kumari ticks were collected from goats and sheep, and morphologically and molecularly identified using different genetic markers. The identified ticks were screened for rickettsial agents using genetic markers that resulted in the detection of Rickettsia conorii for the first time in this tick. A proper surveillance program should be designed to effectively avoid any zoonotic consequences associated with these rickettsial pathogens. Abstract As a vector of wide range of pathogenic agents, ticks pose health threats to wild and domestic animals, and humans. Information is unavailable about the prevalence and spatial survey of Hyalomma kumari ticks and associated Rickettsia spp. in Pakistan. Concerning this knowledge gap, the present study aimed to molecularly detect Rickettsia species associated with H. kumari infesting small ruminants in Khyber Pakhtunkhwa (KP), Pakistan. A total of 409 H. kumari ticks were collected from 163/295 infested hosts with an infestation rate of 55.25%. A total of 204 females, 158 males, and 47 nymphs were collected. Goats were heavily infested by 224 ticks having an infestation rate of 58.33% (98/168), whereas sheep were infested by 185 ticks having a lesser infestation rate of 51.18% (65/127). Genomic DNA extracted from ticks was used for the amplification of tick (cox I, 16S rRNA, ITS-2) species and Rickettsia (gltA, ompA, and ompB) partial genes. Eighty-three ticks were subjected to PCR, and 8/83 (9.6%) were found positive for rickettsial agents. The cox I and 16S rRNA sequences of H. kumari showed 98.90–99.74% identity with H. kumari sequences reported from Pakistan, and phylogenetically clustered to the corresponding species reported from Pakistan and India. The obtained rickettsial gltA, ompA, and ompB sequences showed 100% identity with Rickettsia sp. of the Rickettsia conorii reported from Pakistan. In the phylogenetic trees, rickettsial sequences clustered with uncharacterized Rickettsia sp. from Pakistan and R. conorii from Israel, Russia, South Africa, and India. The present molecular based detection of H. kumari-associated R. conorii will facilitate effective surveillance in the region.
Monitoring Events of Market Competitors: A Text Mining Method for Analyzing Massive Firm-Generated Social Media

Understanding how competitors act in a market is a critical component of strategic decision-making. In this paper, we propose a method to extract firm events from the textual content generated by firms in the market and explore the competitive relationships among firms based on the spatiotemporal homogeneity of events of different firms. To this end, we first introduce experts to define a series of business events based on the content of corporate-generated texts; then, we propose algorithms to extract and enrich the feature words (triggers) of these business events to form better event classifiers. We subsequently use these classifiers to identify the business events recorded in all online texts published by companies. Finally, based on these results, we can obtain a sequence of activities/events for each firm in the market, which can be used to identify the evolutionary patterns of firms’ behavior in the market, as well as their potential competitive relationships. Considering that competition between companies in the market appears to be continuous at the strategic level, but the implementation of competitive behavior is expressed through their “events” in the market, identifying whether companies are “competing” in the market requires timely observation of the information about “events” in the market. However, obtaining accurate market information is complex and costly. Therefore, this study provides a way to bridge the gap between social media data and market competition “events”.
Improved Box-Jenkins estimators

SUMMARY An easily implemented modification of the estimation procedure given by Box & Jenkins (1970) for the autoregressive-moving average time series model is suggested and some new results on covariance determinants are given. The proposed modification provides a closer approximation to the exact maximum likelihood estimators. Simulation experiments which demonstrate the effectiveness of this modification are presented.
Using Boolean Computation to Solve Some Problems from Ramsey Theory

Mathematica’s industrial-strength Boolean computation capability is not used as often as it should be. There probably are several reasons for this lack of use, but it is our view that a primary reason is lack of experience in expressing mathematical problems in the form required for Boolean computation. We look at a typical problem that is susceptible to Boolean analysis and show how to translate it so that it can be tested for satisfiability with Mathematica’s built-in function SatisfiableQ. The problems we investigate come from an area of mathematics called Ramsey theory. Although Ramsey theory has been studied extensively for over 80 years and still provides many challenges, we neglect the theory (for the most part) and instead concentrate on translating the problems so that they are amenable to Boolean computation and then see what can be accomplished by computation alone. Those interested in learning a little more about Ramsey theory can consult [1]; for a standard reference, see [2].
UNIVARIATE SHEPARD-LAGRANGE INTERPOLATION

In this paper we study the univariate Shepard-Lagrange interpolation operator S n,μ (Y ; f ; x) := S L,m n,μ (f ;x) = n ∑ k=0 |x− yn,k|−μ(Lmf)(x; yn,k) n ∑ k=0 |x− yn,k|−μ where (yn,k) are the interpolation nodes and (Lmf)(x; yn,k) is the Lagrange interpolation polynomial with nodes yn,k, yn,k+1, . , yn,k+m. Then we give error estimations for various distribution of interpolation nodes.
Tunneling delays in frustrated total internal reflection

George M. Gehring,1 Andreas C. Liapis,1 and Robert W. Boyd1,2,3 1The Institute of Optics, University of Rochester, Rochester, New York 14627, USA 2Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627, USA 3Department of Physics and School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada K1N 6N5 (Received 6 February 2012; published 22 March 2012)
An Analysis of Oxycodone and Hydrocodone Distribution Trends in Delaware, Maryland, and Virginia Between 2006 and 2014

Objective Opioid medications are widely recognized for their use in analgesia and their addictive properties that have led to the opioid epidemic. Areas with historically high prescribing patterns have been shown to suffer more from the crisis. There is also regional variability in these trends. This study is a county level analysis of oxycodone and hydrocodone use in Delaware, Maryland, and Virginia between 2006 and 2014. Materials and methods A retrospective analysis of oxycodone and hydrocodone distributed as collected by the Drug Enforcement Administration’s (DEA) Washington Post Automation of Reports and Consolidated Orders System (ARCOS) in Delaware, Maryland, and Virginia. Raw drug weights in each county were adjusted to “daily average dose” (grams/county population/365) using publicly available population estimates for all state counties. Purchasing data collected from ARCOS was used to compare distribution trends during this period. This study was limited in that ARCOS report quantity of drug distribution rather than average dose of script written. Results There was a 57.59% increase in the weight of oxycodone and hydrocodone prescribed between 2006 and 2014. Oxycodone prescriptions increased by 75.50% and hydrocodone by 11.05%. Oxycodone increased across all three states between 2006 and 2010 and declined until 2014. Hydrocodone also increased but to a lesser extent than oxycodone. There was substantial variability in daily average dose of both opioids at the county level in all states. Pharmacies accounted for largest portion of oxycodone (69.17%) and hydrocodone (75.27%) purchased in the region. Hospitals accounted for 26.67% of oxycodone and 22.76% of hydrocodone purchased. Practitioners and mid-level providers, including Nurse Practitioners and Physician Assistants, did not significantly contribute to this increase. Conclusion In the states of Maryland, Delaware, and Virginia, the distribution of the prescription opioids oxycodone and hydrocodone increased by 57.59%. Daily average dose increased between 2006 and 2010 in all three states, followed by a decline until 2014. Variability in daily average dose by county highlights the relationship between geography and likelihood of receiving high-dose opioids. Increased monitoring at regional health centers and improving substance abuse treatment infrastructure at the county level may be a more efficient strategy in combating the opioid epidemic. Future research is needed to understand the socioeconomic trends that may influence prescribing trends of opioid medications.
POCUS for Diastolic Dysfunction: A Review of the Literature

Abstract Emergency and critical care physicians frequently encounter patients presenting with dyspnea and normal left ventricular systolic function who may benefit from early diastolic evaluation to determine acute patient management. The current American Society of Echocardiography Guidelines approach to diastolic evaluation is often impractical for point of care ultrasound (POCUS) evaluation, and few studies have evaluated the potential use of a simplified approach. This article reviews the literature on the use of a simplified diastolic evaluation to assist in determining acute patient management.
Imperative and Deontic Logic

Deontic logic has so far been almost exclusively interpreted by a possible worlds semantics and ideality or preference relations between the worlds. In distinguishing itself from attempts at a logic of norms or logic of imperatives, deontic logic has portrayed its formulas as ‘deontic propositions’, true or false statements about what is obligatory, permitted or forbidden according to some unspecified normative system. Based on this idea, the ‘imperatival tradition’ of deontic logic, an unorthodox sidearm of the mainstream, has interpreted the formulas of deontic logic not with respect to ideal or best worlds, but to given sets of norms or imperatives. In a series of papers standing in this tradition, I have shown that by using an explicitly represented set of imperatives and what they command as the logical semantics by which the truth of deontic formulas is defined, all the standard systems of monadic and dyadic deontic logic can be ‘reconstructed’, i.e. they are sound and complete with respect to such semantics. The basic concepts are motivated here from a position of ‘imperativological scepticism’, and the main results are summarized.
Exploring Loneliness, Fear and Depression among Older Adults during the COVID-19 Era: A Cross-Sectional Study in Greek Provincial Towns

Background: With the onset of the COVID-19 pandemic, life changed abruptly for older adults in Greece. Social isolation, lockdowns, the fear of serious illness and death, all contributed to an increased risk of developing depression. Objective: To explore the presence and severity of depression in older adults in Greek provincial towns during the pandemic and to explore any possible relationships with loneliness and fear. Methods: A convenience sample of 200 participants aged >65, completed a socio-demographic form, the Revised UCLA Loneliness Scale, the Geriatric Depression-15 Scale (GDS-15) and the COVID-19 Fear Scale (FCV-19S). Data were collected from April to May 2022. Results: The average age of participants was 76.6 years and 35.5% of the participants presented depressive symptoms (mean prevalenceof depression 5 ± 3.7). A moderate to low level of loneliness (mean value 39 ± 11.3) and a moderate level of COVID-19 fear (mean value 18.9 ± 6.5) were also experienced. Higher levels of loneliness were found among participants with lower perceived health status and among those participants registered in Primary Health and Social Care (PHSC) services. Loneliness was positively correlated with depression (r = 0.7, p < 0.001), and increased loneliness and depression were associated with an increase in fear of COVID-19 (r = 0.2, p = 0.01 for both). Conclusions: During the pandemic, older adults experienced loneliness, fear of COVID-19 and depression which were positively associated with each other. It is imperative to develop PHSC policies that are aimed at addressing the mental health problems of the older population, which have been caused by the COVID-19 pandemic, through developing their resilience, offering psychological support and promoting social connections.
Fringe tracking at longer wavelengths using near- and mid-IR integrated optics devices

Fringe tracking at longer wavelengths is advantageous for its larger Fried parameter (R0) and longer coherence time (τ0). The fringe trackers which are currently available at the VLTi (Finito, FSU, Gravity, etc.) tracks fringes at the near infrared wavelengths (H and K bands). In our work we try to explore the possibilities to track near and mid- infrared fringes using GLS based laser written integrated optics beam combiners. We simulate the atmospheric optical path difference (OPD) using Kolmogorov/Von-Karman atmospheric turbulence statistics. We also include the measured the piston noise generated due to the instrumental vibrations. Using the resulting OPD time series we can estimate the sensitivity of the fringe tracker at the L band.
Tgr5−/− mice are protected from ethanol-induced metabolic alterations through enhanced leptin and Fgf21 signaling

Background: Alcohol-associated liver disease (ALD) is caused by chronic use of alcohol and ranges from hepatic steatosis to fibrosis and cirrhosis. Bile acids are physiological detergents that also regulate hepatic glucose and lipid homeostasis by binding to several receptors. One such receptor, Takeda G protein–coupled receptor 5 (TGR5), may represent a therapeutic target for ALD. Here, we used a chronic 10-day + binge ethanol-feeding model in mice to study the role of TGR5 in alcohol-induced liver injury. Methods: Female C57BL/6J wild-type mice and Tgr5 −/− mice were pair-fed Lieber-DeCarli liquid diet with ethanol (5% v/v) or isocaloric control diet for 10 days followed by a gavage of 5% ethanol or isocaloric maltose control, respectively, to represent a binge-drinking episode. Tissues were harvested 9 hours following the binge, and metabolic phenotypes were characterized through examination of liver, adipose, and brain mechanistic pathways. Results: Tgr5 −/− mice were protected from alcohol-induced accumulation of hepatic triglycerides. Interestingly, liver and serum levels of Fgf21 were significantly increased during ethanol feeding in Tgr5 −/− mice, as was phosphorylation of Stat3. Parallel to Fgf21 levels, increased leptin gene expression in white adipose tissue and increased leptin receptor in liver were detected in Tgr5 −/− mice fed ethanol diet. Adipocyte lipase gene expression was significantly increased in Tgr5 −/− mice regardless of diet, whereas adipose browning markers were also increased in ethanol-fed Tgr5 −/− mice, indicating potential for enhanced white adipose metabolism. Lastly, hypothalamic mRNA targets of leptin, involved in the regulation of food intake, were significantly increased in Tgr5 −/− mice fed ethanol diet. Conclusions: Tgr5 −/− mice are protected from ethanol-induced liver damage and lipid accumulation. Alterations in lipid uptake and Fgf21 signaling, and enhanced metabolic activity of white adipose tissue, may mediate these effects.
Design and analysis of active transtibial prosthesis function using 7-link inverse dynamic model of gait

Abstract In today’s world, in order to increase the movement abilities of amputees, different types of passive prostheses are used according to the level of the person’s disability. Although these types of prostheses increase a person’s mobility; however, they still have a limited ability to help the amputee walk normally on uneven terrain, as there is no net stimulus input power for the target joint. These limitations have led to the growth of the use of active prostheses in recent years, which has led to a variety of prosthetic designs. The purpose of this research is, first of all, to provide a suitable design and control of active transtibial prosthesis close to the performance of lost limb of a healthy person, and second and more importantly, to develop a 7-link inverse dynamic model of human gait and use it to analyze of an amputee gait with the designed prosthesis. Winter’s reference data are used in the entire process of design and simulation of prosthesis performance. Also, it is assumed that the amputation occurred in only one leg of the person. Based on the obtained results, when an amputee with 57 kg weight and 1.55 cm height wears an active prosthesis designed with 0.5 kg extra weight, the amount of metabolic cost of amputee in the swing phase increases by about 20%. By using this obtained model, it will be possible to optimize different prosthesis designs for people with different weight and height conditions.
Fractional-Order Derivative Spectral Transformations Improved Partial Least Squares Regression Estimation of Photosynthetic Capacity From Hyperspectral Reflectance

Hyperspectral spectroscopy based on partial least squares regression (PLSR) is an effective tool for monitoring plant photosynthesis. Despite their wide applications, the robustness of PLSR models on tracing photosynthetic capacity, which varies considerably among different species and at different times, has been far less explored, leading to doubt about whether hyperspectral information can accurately predict the capacity across different species and temporal changes. Ordinary applications of PLSR generally make use of original or integer-order derivative transformed reflected spectra, but recent advances in spectral analysis have revealed that fractional-order derivative (FOD) transformed spectra could provide more details of spectral signals. In this study, PLSR models based on FODs coupled with different wavelength selection methods were developed to evaluate whether photosynthetic parameters (Vcmax and Jmax) could be correctly predicted from reflectance spectra. The result indicated that the best PLSR models for the Vcmax and Jmax were obtained based on the sensitive wavelengths selected by stepwise regression using the fractional orders of 1.25 and 1.60, respectively. The optimal PLSR models were able to capture the temporal variabilities of Vcmax and Jmax with the $\text{R}^{2}$ of 0.62–0.94 and 0.65–0.85, for which the 1605–1845 nm region was consistently used. Meanwhile, these PLSR models have the ability to capture the variations in different species, plant functional types, and biomes. The findings of this study demonstrate that leaf spectra can be successfully used for the timely prediction of variable photosynthetic capacity and provide the fundamentals for monitoring and mapping plant functions from reflected information.
Estimation of the Apparent Source Size of Solar Radio Emission s Using SVD: An Application to Type III Radio Bursts at Long Wavelengths Observed by STEREO and Wind

Type III r adio bursts are intense solar radio emissions. They are frequently observed by the S/Waves instruments on-board the STEREO spacecraft. We describe a wave propagation analysis using the Singular Value Decomposition (SVD) which can be directly applied to spectral matrices measured by the High Frequency Receiver (HFR; a part of the S/Waves experiment). We have found an empirical relation between the decomposed spectral matrices and apparent source sizes for waves with a low degree of polarization. We present a joint observation of a type III radio burst by the STEREO and Wind spacecraft during small separation distances. We obtain consistent results for the apparent source size and k-vector direction using different analysis method for the measurements of the STEREO and Wind spacecraft. We demonstrate that SVD can be an effective tool for the wave analysis of radio emissions with very extended sources.