Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Positive Emotions on the Willingness to Communicate in Second Language

Globally, second language (L2) education aims to empower the learners with skills and motivation necessary for effective communication. The current study investigated the association between ten positive emotions and the Willingness to Communicate (WTC) in L2. The emotions studied were joy, gratitude, interest, serenity, amusement, hope, pride, awe, inspiration, and love. While previous research conducted on this topic was largely confined to the Western context, this study incorporated the Pakistani context as well to establish a more comprehensive picture. Three hundred (300) undergraduate and postgraduate students enrolled in higher education institutions (HEIs) in Islamabad, Pakistan took part in the research. The findings revealed that gratitude, pride, hope, inspiration, and amusement tend to impact students’ WTC in L2. The results offer many practical insights for policymakers, teachers, and higher education students. HEIs may develop/conduct a variety of policies, strategies, initiatives, trainings, and workshops to address L2 communication based on the findings of this research.
Exploring the potential of social media to study environmental topics and natural disasters

ABSTRACT Social media has become an important means of communication and new insights can be gained from processing this data on a large scale. Our goal is to develop and implement a pipeline to automatically extract and analyse Twitter data on natural disasters and environmental topics. We aim to provide an additional layer of spatiotemporal data that can be used to study the immediate and lasting impacts of natural disasters, climate change, and environmental topics on the global population. An initial analysis of forest fires was conducted in four different languages confirming the need for multilingual support for global analysis. We found a positive correlation between wildfire occurrence and tweeting behaviour, as well as the geographic spread of fires. We found that simple sentiment predictions add little value when aggregating data on a large scale. A subsequent test using a fine-tuned stance detection model proved promising in determining the stance of tweets towards nuclear energy. We intend to expand our dataset and develop customised models in the future that can be used to analyse the global impact of natural disasters and environmental topics.
Capital Optical Character Recognition Using Neural Network Based on Gaussian Filter

Purpose: As digital technology advances, society needs to convert physical text into digital text. There are now many methods available for doing this. One of them is OCR (Optical Character Recognition), which can scan images [1]–[4] containing writing and turn them into digital text, making it easier to copy written text from an image. Text recognition in images is complex due to variations in text size, color, font, orientation, background, and lighting conditions.Methods: The technique of text recognition or optical character recognition (OCR) in images can be done using several methods, one of which is a neural network or artificial neural network. The artificial neural network method can help a computer make intelligent decisions with limited human assistance. Intelligent decisions can be made because the neural network can learn and model the relationship between nonlinear and complex input and output data. In this research, the scaled conjugated gradient is applied for optimization. SCG is very effective in finding the minimum value of a complex function, but it takes longer than some other optimization algorithms.Result/Findings: The dataset used is an image with a size of 28 x 28 which is changed in dimension to 784 x 1. This research uses 4000 epochs and obtained the best validation result at epoch 3506 with a value of 0.0087446. Results: From the statistical test results, the effect of perceived usefulness on ease of use has the highest level of influence, obtaining a test value of 3.6. Furthermore, the effect of the attitude towards using on the behavioral intention to use has the lowest level of influence, which obtained a test value of 1.2. Novelty: In this article, Gaussian filter is used as feature extraction to improve yield. Character detection results using a Gaussian filter are known to be almost 10% higher than those using only a neural network. The result with the Neural Network alone is 82.2%, while the Neural Network-Gaussian Filter produces 92.1%.
Endothelial TAZ inhibits capillarization of liver sinusoidal endothelium and damage-induced liver fibrosis via nitric oxide production

Background: Endothelial dysfunction is a systemic disorder and is involved in the pathogenesis of several human diseases. Hemodynamic shear stress plays an important role in vascular homeostasis including nitric oxide (NO) production. Impairment of NO production in endothelial cells stimulates the capillarization of liver sinusoidal endothelial cells, followed by hepatic stellate cell activation, inducing liver fibrosis. However, the detailed mechanism underlying NO production is not well understood. In hepatocytes, transcriptional co-activator with PDZ-binding motif (TAZ) has been reported to be involved in liver fibrosis. However, the role of endothelial TAZ in liver fibrosis has not been investigated. In this study, we uncovered the role TAZ in endothelial cell NO production, and its subsequent effects on liver fibrosis. Methods: TAZ-floxed mice were crossed with Tie2-cre transgenic mice, to generate endothelium-specific TAZ-knockout (eKO) mice. To induce liver damage, a 3,5-diethoxycarboncyl-1,4-dihydrocollidine, methionine-choline-deficient diet, or partial hepatectomy was applied. Liver fibrosis and endothelial dysfunction were analyzed in wild-type and eKO mice after liver damage. In addition, liver sinusoidal endothelial cell (LSEC) was used for in vitro assays of protein and mRNA levels. To study transcriptional regulation, chromatin immunoprecipitation and luciferase reporter assays were performed. Results: In liver of eKO mice, LSEC capillarization was observed, evidenced by loss of fenestrae and decreased LSEC-specific marker gene expression. LSEC capillarization of eKO mouse is caused by downregulation of endothelial nitric oxide synthase expression and subsequent decrease in NO concentration, which is transcriptionally regulated by TAZ-KLF2 binding to Nos3 promoter. Diminished NO concentration by TAZ knockout in endothelium accelerates liver fibrosis induced by liver damages. Conclusions: Endothelial TAZ inhibits damage-induced liver fibrosis via NO production. This highlights an unappreciated role of TAZ in vascular health and liver diseases.
Surgical and Quality of Life Outcomes Following Robotic-Assisted (da Vinci) Laparoscopic Repair of Vesicovaginal Fistula: A Case Report and Video Demonstration

This report presents the case of a 63-year-old woman who developed a vesicovaginal fistula as a complication of a previous total hysterectomy. The fistula was treated with the use of the da Vinci X surgical system by a multi-disciplinary operating team, including senior Robotic Urological and Gynecological Surgeons at St. Luke’s Hospital in Thessaloniki, Greece. The patient was monitored up to 12 months post-op at the time of writing and she was asked to evaluate post-op quality of life using the SF-36 and ICIQ-SF-UI questionnaires. The robotic surgical procedure was completed successfully. The total operation duration was 105 minutes, without any intra-operative complications. The patient was hospitalized for two days and made a swift, uneventful recovery. Regarding the quality of life, the patient reported satisfactory improvement in almost every domain assessed compared to her pre-op assessment; an improvement that was maintained throughout the reported follow-up period. At the time of writing, the patient reports no long-term complications and satisfactory urinary continence. Robotic-assisted laparoscopic vesicovaginal fistula repair is an effective and safe treatment option for this rare complication, as indicated by both post-operative data and the patient’s own self-evaluation in this report. Further research is warranted, focusing on refining the surgical technique and comparing this to other alternative methods aiming to further improve patient outcomes.
Derivation of Stochastic Equations for Computational Uncertainties in Petro-Physical Properties Using a Simplified Algorithm

This paper presents a simple mathematical algorithm or procedure for computing the uncertainties at the various percent of data input, using the stochastic approach of simulating the input variables to compute the output variables. A simple algorithm was used to derive stochastic equations for some selected petrophysical parameters using the relative standard deviations techniques (σ). These equations also known as reference work equations were found to produce reasonably accepted magnitude of uncertainties in the different parameters associated with cores. Equations were derived for the percent uncertainties in the values of the pore volume of the core - V p , the fluid saturation – S w , S or , the porosity of the core – Φ, formation factor - F, bulk density – ρB, the derived porosity - Φ L and the derived permeability – K BU , Kro, Krw. The uncertainty equations can also be used to define the maximum level of uncertainty that can be tolerated in any independent variable if the maximum uncertainty to be tolerated in the dependent variable is known Keywords : Stochastic equations, petrophysical parameters, percent uncertainties, Mathematical algorithm, standard deviations, partial derivatives, degree of accuracy, empirical models.
Exploring the Key Drivers of User Continuance Intention to Use Digital Museums: Evidence From China’s Sanxingdui Museum

With the rapid development and wide application of digital information technology, digital museums are gradually replacing traditional museums and being transformed from “object-centric” to “experience-centric” paradigms. However, studies on the continuance intention of digital museums from the perspective of user experience are still scarce. It is essential to study what variables affect user experience and behavior and what variables can improve user continuance intention. Therefore, this study constructs a theoretical model and fourteen hypotheses that affect user continuance intention toward digital museums by expanding the technology acceptance model (TAM) with the addition of interaction quality, information quality, information richness and other variables and uses a structural equation model to verify the hypotheses. The empirical results indicate that 1) interaction quality (IQ) has a positive impact on information quality (IQU) and information richness (IR); 2) information richness (IR) has a positive impact on perceived usefulness (PU), information quality (IQU), and perceived ease of use (PEOU); 3) information quality (IQU) has a positive impact on satisfaction (SAT), perceived ease of use (PEOU), and perceived playfulness (PP); 4) compared with perceived playfulness (PP), perceived ease of use (PEOU) has a greater impact on perceived usefulness (PU); 5) perceived usefulness (PU) and perceived ease of use (PEOU) are significant indicators for predicting satisfaction (SAT); and 6) satisfaction (SAT) and perceived playfulness (PP) are critical factors influencing continuance intention. The findings of this study will enrich relevant academic theories and provide references for professionals to enhance user experience services in digital museums.
Approximation methods for lognormal characteristic functions

ABSTRACT The characteristic function of the lognormal distribution is of interest in a number of scientific fields yet an analytic solution remains elusive, making reliable and efficient approximations necessary. In this article, we build on the results of N. C. Beaulieu and A. Saberali in ‘New approximations to the lognormal characteristic function’, by introducing a Taylor- and Bessel function-based partial expansion of the integrand and a Chebyshev quadrature approach. Through computer simulations we show that the Taylor expansion remains accurate and efficient for all commonly computed values, and specify the range of values for which the other two approaches show a significantly stronger performance.
Space-time study of energy deposition with intense infrared laser pulses for controlled modification inside silicon

La modification du silicium dans son volume est possible aujourd’hui avec des lasers infrarouges nanosecondes. Neanmoins, le regime d’interet pour la modification controlee en volume des materiaux transparents correspond aux impulsions femtosecondes. Cependant, aujourd’hui aucune demonstration de modification permanente du volume du Si n’a ete realisee avec une impulsion ultra-breve (100 fs). Pour infirmer ce resultat, nous avons developpe des methodes de microscopie infrarouge ultra-rapides. Tout d’abord, nous etudions le microplasma confine dans le volume, caracterise par la generation de porteurs libres par ionisation nonlineaire du silicium, suivie de la relaxation totale du materiau. Ces observations, couplees a la reconstruction de la propagation du faisceau dans le materiau, demontrent un depot d’energie d’amplitude fortement limitee par des effets nonlineaires d’absorption et de propagation. Cette analyse a ete confirmee par un modele numerique simulant la propagation nonlineaire du faisceau femtoseconde. La comprehension de cette limitation a permis de developper de nouvelles configurations experimentales grâce auxquelles l’endommagement local et permanent du volume du silicium a pu etre initie en regime d’impulsions courtes.
CAVIN2/SDPR Functioned as a Tumor Suppressor in Lung Adenocarcinoma from Systematic Analysis of Caveolae-Related Genes and Experimental Validation

Background: Caveolae-Related Genes include caveolins and cavins, which are the main component of the fossa and, play important roles in a variety of physiological and pathological processes. Although increasing evidence indicated that caveolins (CAVs) and cavins (CAVINs) are involved in carcinogenesis and progression, their clinical significance and biological function in lung cancer are still limited. Methods: We investigated the expression of CAVs and CAVINs at transcriptional levels using Oncomine and Gene Expression Profiling Interactive Analysis. The protein and mRNA expression levels of CAVs and CAVINs were determined by the human protein atlas website and our surgically resected samples, respectively. The clinical value of prognostic prediction based on the expression of CAVs and CAVINs was also assessed. cBioPortal, GeneMANIA and STRING were used to analyze the molecular characteristics of CAVs and CAVINs in lung adenocarcinoma (LUAD) comprehensively. Finally, we investigated the effect of CAVIN2/SDPR (serum deprivation protein response) on LUAD cells with biological experiments in vitro. Results: The expression of CAV1/2 and CAVIN1/2/3 were significantly downregulated in LUAD and lung squamous cell carcinoma (LUSC). The patients with high expression of CAV1, CAV2, CAV3, CAVIN1 and CAVIN2/SDPR were tightly correlated with a better prognosis in LUAD, while no statistical significances in LUSC. Further, our results found that CAVIN2/SDPR can be identified as a prognostic biomarker independent of other CAVINs in patients with LUAD. Mechanically, the overexpression of CAVIN2/SDPR inhibited cell proliferation and migration owing to the cell apoptosis induction and cell cycle arrest at S phase in LUAD cells. Conclusions: CAVIN2/SDPR functioned as a tumor suppressor, and was able to serve as prognostic biomarkers in precision medicine of LUAD. Mechanically, overexpression of CAVIN2/SDPR inhibited cell proliferation by inducing cell apoptosis and S phase arrest in LUAD cells.
Fluid Properties Extraction in Confined Nanochannels with Molecular Dynamics and Symbolic Regression Methods

In this paper, we propose an alternative road to calculate the transport coefficients of fluids and the slip length inside nano-conduits in a Poiseuille-like geometry. These are all computationally demanding properties that depend on dynamic, thermal, and geometrical characteristics of the implied fluid and the wall material. By introducing the genetic programming-based method of symbolic regression, we are able to derive interpretable data-based mathematical expressions based on previous molecular dynamics simulation data. Emphasis is placed on the physical interpretability of the symbolic expressions. The outcome is a set of mathematical equations, with reduced complexity and increased accuracy, that adhere to existing domain knowledge and can be exploited in fluid property interpolation and extrapolation, bypassing timely simulations when possible.
Tales told by Galaxies: Clues to chemical enrichment and the Epoch of Reionization

We use integrated-light spectroscopic observations to measure metallicities and chemical abundances for two extragalactic young massive star clusters (NGC1313-379 and NGC1705-1). The spectra were obtained with the X-Shooter spectrograph on the ESO Very Large Telescope. We compute synthetic integrated-light spectra, based on colour-magnitude diagrams for the brightest stars in the clusters from Hubble Space Telescope photometry and theoretical isochrones. Furthermore, we test the uncertainties arising from the use of Colour Magnitude Diagram (CMD) +Isochrone method compared to an Isochrone-Only method. The abundances of the model spectra are iteratively adjusted until the best fit to the observations is obtained. In this work we mainly focus on the optical part of the spectra. We find metallicities of [Fe/H] = ≠0.84 ± 0.07 and [Fe/H] = ≠0.78 ± 0.10 for NGC1313-379 and NGC1705-1, respectively. We measure [–/Fe]=+0.06 ± 0.11 for NGC1313-379 and a super-solar [–/Fe]=+0.32 ± 0.12 for NGC1705-1. The roughly solar [–/Fe] ratio in NGC1313379 resembles those for young stellar populations in the Milky Way (MW) and the Magellanic Clouds, whereas the enhanced [–/Fe] ratio in NGC1705-1 is similar to that found for the cluster NGC1569-B by previous studies. Such super-solar [–/Fe] ratios are also predicted by chemical evolution models that incorporate the bursty star formation histories of these dwarf galaxies. Furthermore, our –-element abundances agree with abundance measurements from H II regions in both galaxies. In
The Effect of Artificial Intelligence (AI) on Human Capital Management in Indonesia

Human resources in an organization is the capital for the organization and its performance is the main indicator for the organization to achieve its goals. In the current digital era, the shift in human resources is demonstrated by the application of Artificial Intelligence (AI) to organizations in Indonesia, both in companies and in several government organizations. A company has a responsibility to its stakeholders to do the job and get the desired profit. However, no research specifically discusses the analysis of the influence of AI (Machine Learning Algorithm, Deep Learning and Big Data) on Human Capital Management in Indonesia. This study aims to determine the effect of artificial Intelligence (AI) on Human Capital Management in Indonesia. This sample of this study is 85 respondents of organizational leaders and human resource managers (HR) in Indonesia. It can be concluded that adoption of Deep Learning and Big Data has a significant positive impact on Human Capital Management.
Self-organisation in currents: complex plasmas vs. humans

Complex plasmas ‐ low temperature plasmas with micron sized particles ‐ exhibit various effects of self-organisation. This can be used to simulate the behaviour of matter in nearly any state from solid (crystalline) to liquid ‐ even super-critical states have been realised so far ‐ on the kinetic level of individual particles (‘atoms’). To avoid gravitational effects experiments have been performed under microgravity conditions on parabolic flights and onboard the International Space Station ISS. [1] The ‘Plasmakristall (PK-) 4’ setup uses a HV DC discharge in a glass tube to create a complex plasma for studying mainly fluids on the particle level [2,3]. During parabolic flights we observed another self-organisation effect, so-called ‘lane formation’. This effect occurs under certain conditions [4] when two types of particles pass through each other. It is known from two-component fluids, granular media and even people moving in a crowd [5]. A comparison of these cases with the PK-4 experiment (fig. 1a, b) is given here.
INFLUENCE OF TREASURY SINGLE ACCOUNT (TSA) POLICY ON MONITORING FRADULENTS PRACTICES AND BLOCKING FINANCIAL LEAKAGES ON THE ADMINISTRATION OF PUBLIC UNIVERSITIES IN NORTH EASTERN NIGERIA

The study investigated the influence of Treasury Single Account (TSA) policy on monitoring fraudulent practices and blocking financial leakages on the administration of public universities in North Eastern Nigeria. two specific objectives with corresponding research questions guided the study and two hypotheses were formulated and tested at 0.05 level of significance. The study adopted a survey research design, and was carried out in North Eastern Nigeria. The population of the study comprised 547 Bursary staff of Federal Universities in North Eastern Nigeria. The sample size for the study comprised 231 Bursary staff obtained from the use of Taro Yamane formula for sample size determination. The instrument for data collection was a structured questionnaire. The reliability of the instrument was estimated using Cronbach Alpha statistic and an overall reliability coefficient of 0.84 was obtained. The data was analyzed using Means and Standard Deviation to answer the research questions. Chi-Square Statistic to test the null hypotheses at 0.05level of significance. Findings of the study revealed that the implementation of TSA has made inflation of contract difficult and has also made fabrication of accounts to disclose false position in public sector difficult to perpetuate in the administration of public universities. It further revealed that maintenance of Treasury Single Account helps to eliminate idle funds usually left with different commercial banks in the administration of public universities and Treasury Single Account enhances e-payment collection and this influences the administration of public universities. Based on these findings, it was recommended that; Federal government should ensure all contracts in within the university is solely monitored using TSA, as this would make inflation of contract difficult and also make fabrication of accounts to disclose false position in public universities difficult to perpetuate, therefore enhancing speedy execution of projects for efficient administration of public universities. Federal government should sensitize Vice Chancellors on the constant need of institutionalizing Treasury Single Account in their respective schools, as it would help to eliminate idle funds usually left with different commercial banks via e-payment as this would make more cash available to the government to address other needs in public universities.
Functional Central Limit Theorem for the Interface of the Symmetric Multitype Contact Process

We study the interface of the symmetric multitype contact process on Z. In this process, each site of Z is either empty or occupied by an individual of one of two species. Each individual dies with rate 1 and attempts to give birth with rate 2R lambda; the position for the possible new individual is chosen uniformly at random within distance R of the parent, and the birth is suppressed if this position is already occupied. We consider the process started from the configuration in which all sites to the left of the origin are occupied by one of the species and all sites to the right of the origin by the other species, and study the evolution of the region of interface between the two species. We prove that, under diffusive scaling, the position of the interface converges to Brownian motion.