Miracle-dz/UniFAR-FTUs huggingface dataset:
Confluent Kampé de Fériet Series Arising in the Solutions of Cauchy Problem for the Degenerate Hyperbolic Equation of the Second Kind with the Spectral Parameter

We define the order of the double hypergeometric series, investigate the properties of the new confluent Kampé de Fériet series, and build systems of partial differential equations that satisfy the new Kampé de Fériet series. We solve the Cauchy problem for a degenerate hyperbolic equation of the second kind with a spectral parameter using the high-order Kampé de Fériet series. Thanks to the properties of the introduced Kampé de Fériet series, it is possible to obtain a solution to the problem in explicit forms.
DETERMINATION OF THE BEST METHODOLOGY FOR BATHYMETRY MAPPING USING SPOT 6 IMAGERY: A STUDY OF 12 EMPIRICAL ALGORITHMS

For the past four decades, many researchers have published a novel empirical methodology for bathymetry extraction using remote sensing data. However, a comparative analysis of each method has not yet been done. Which is important to determine the best method that gives a good accuracy prediction. This study focuses on empirical bathymetry extraction methodology for multispectral data with three visible band, specifically SPOT 6 Image. Twelve algorithms have been chosen intentionally, namely, 1) Ratio transform (RT); 2) Multiple linear regression (MLR); 3) Multiple nonlinear regression (RF); 4) Second-order polynomial of ratio transform (SPR); 5) Principle component (PC); 6) Multiple linear regression using relaxing uniformity assumption on water and atmosphere (KNW); 7) Semiparametric regression using depth-independent variables (SMP); 8) Semiparametric regression using spatial coordinates (STR); 9) Semiparametric regression using depth-independent variables and spatial coordinates (TNP), 10) bagging fitting ensemble (BAG); 11) least squares boosting fitting ensemble (LSB); and 12) support vector regression (SVR). This study assesses the performance of 12 empirical models for bathymetry calculations in two different areas: Gili Mantra Islands, West Nusa Tenggara and Menjangan Island, Bali. The estimated depth from each method was compared with echosounder data; RF, STR, and TNP results demonstrate higher accuracy ranges from 0.02 to 0.63 m more than other nine methods. The TNP algorithm, producing the most accurate results (Gili Mantra Island RMSE = 1.01 m and R 2 =0.82, Menjangan Island RMSE = 1.09 m and R 2 =0.45), proved to be the preferred algorithm for bathymetry mapping.
High Performance GaN-Based Ultraviolet Photodetector via Te/Metal Electrodes

Photodetectors (PDs) based on two-dimensional (2D) materials have promising applications in modern electronics and optoelectronics. However, due to the intralayer recombination of the photogenerated carriers and the inevitable surface trapping stages of the constituent layers, the PDs based on 2D materials usually suffer from low responsivity and poor response speed. In this work, a distinguished GaN-based photodetector is constructed on a sapphire substrate with Te/metal electrodes. Due to the metal-like properties of tellurium, the band bending at the interface between Te and GaN generates an inherent electric field, which greatly reduces the carrier transport barrier and promotes the photoresponse of GaN. This Te-enhanced GaN-based PD show a promising responsivity of 4951 mA/W, detectivity of 1.79 × 1014 Jones, and an external quantum efficiency of 169%. In addition, owing to the collection efficiency of carriers by this Te–GaN interface, the response time is greatly decreased compared with pure GaN PDs. This high performance can be attributed to the fact that Te reduces the contact resistance of the metal electrode Au/Ti to GaN, forming an ohmic-like contact and promoting the photoresponse of GaN. This work greatly extends the application potential of GaN in the field of high-performance photodetectors and puts forward a new way of developing high performance photodetectors.
Environmental cost of financial development within the framework of the load capacity curve hypothesis in the BRICS economies: Do renewable energy consumption and natural resources mitigate some burden?

Ecological changes and deformations put nations around the world under socioeconomic pressure and are thus an important topic of discourse. In this framework, this study explores the effect of economic progress, natural resources, renewable energy and financial development on load capacity factor (proxy of ecological quality) utilizing the second‐generation approach for the case of the BRICS economies. Moreover, the paper explores the validity of the load capacity curve (LCC) hypothesis that has been recently introduced in the energy economics literature for the period between 1990 and 2018. The research results disprove the validity of the LCC hypothesis for the BRICS nations. Moreover, economic progress, financial development and natural resources cause ecological quality to decline, while renewable energy improves ecological quality. The panel causality results also support these results. Among several recommendations, the research advises that governments and policymakers advocate for reforms to promote renewable energy sources. The BRICS countries can go green and maintain ecological sustainability through this transition towards renewable energies, which is also a top priority of the UN's SDG 7.
Safety and efficacy of vedolizumab in pediatric inflammatory bowel disease with emphasis on the very-early-onset group

Introduction: Vedolizumab (VDZ) is effective in the induction and maintenance of remission in adults with inflammatory bowel disease (IBD). Pediatric data are still limited. This retrospective cohort study aimed to assess the safety and efficacy of VDZ in pediatric IBD including very-early-onset IBD (VEO-IBD). Material and methods: A review of pediatric IBD patients receiving VDZ was conducted. Laboratory parameters, nutritional status, and disease activity scores were compared between each follow-up visit and between two groups divided by age of disease onset – VEO-IBD (age of onset < 6-years-old) and non-VEO-IBD (age of onset ≥ 6 years < 17 years). The primary outcome was clinical response after induction therapy (at 4 th dose visit). The secondary outcome was clinical remission after induction (at 4th dose visit) and maintenance phase (at 10th dose visit). Statistical considerations were included. Results: Seventy-two patients with pediatric IBD were included: 12 with Crohn disease (CD), 60 with ulcerative colitis (UC). The definition of VEO-IBD was met by 21 patients. After the induction phase, a clinical response was observed in 60/72 (83.3%) patients (51/60 with UC and 9/12 with CD) and clinical remission in 44/72 (61.1%) patients (40/60 with UC and 4/12 with CD). Clinical remission after the maintenance phase was achieved by 22/72 (30.6%) patients (16/60 with UC and 6/12 with CD). Improvement in the patients’ laboratory parameters and nutritional status was observed. No significant differences were observed in VDZ response between VEO-IBD and non-VEO-IBD. Conclusions: Vedolizumab was safe and effective in the treatment of pediatric IBD irrespective of age of disease onset.
A Reliable Method to Estimate the Bispectral Index Value Using a Single Frontal EEG Channel for Intra and Inter Subject Variability

Objective: Monitoring the depth of anesthesia (DoA) plays an important role for administering the drug injection during a surgery, i.e., preventing undesired awareness and inordinate anesthetic depth. Although the bispectral index (BIS) monitor is the golden standard system for the DoA monitoring, it is still not affordable for the developing countries. Alternatively, a low-cost electroencephalogram (EEG) headband can be used. The objective of this paper is to present a new algorithm for estimating the BIS values using a single frontal EEG channel. Method: In the first step, the EEG signal is filtered for the elimination of artifacts and is split into its sub-bands. In the second step, several linear and nonlinear features are extracted from each sub-band and fed to a random forest regression model in order to estimate the BIS. The performance of the proposed algorithm is assessed using EEG data recorded from twenty-four subjects during the general anesthesia and is validated in terms of correlation coefficient (CC) and absolute error (AE) between the reference and estimated BIS values. Results: The proposed algorithm achieved the mean CC of 0.83 and AE of 6.5 for intra subject variability and mean CC of 0.87 and AE of 5.5 for inter subject variability. Significance: Given the similar results for both intra and inter subject variability, the proposed algorithm has the potential to be used in the real-world scenario.
Free convection enhancement in an annulus between horizontal confocal elliptical cylinders using hybrid nanofluids

ABSTRACT In the present paper, natural convection in an annulus between two confocal elliptic cylinders filled with a Cu-Al2O3/water hybrid nanofluid is investigated numerically. The inner cylinder is heated at a constant surface temperature while the outer wall is isothermally cooled. The basic equations are formulated in elliptic coordinates and developed in terms of the vorticity-stream function formulation using the dimensionless form for 2D, laminar and incompressible flow under steady-state condition. The governing equations are discretized using the finite volume method and solved by an in-house FORTRAN code. Numerical simulations are performed for various volume fractions of nanoparticles (0 ≤ ϕ ≤ 0.12) and Rayleigh numbers (103 ≤ Ra ≤ 3 × 105). The eccentricity of the inner and outer ellipses and the angle of orientation are fixed at e1 = 0.9, e2 = 0.6 and γ = 0° respectively. It is found that employing a Cu-Al2O3/water hybrid nanofluid is more efficient in heat transfer rate compared to the similar Al2O3/water nanofluid.
Multipretext-Task Prototypes Guided Dynamic Contrastive Learning Network for Few-Shot Remote Sensing Scene Classification

As a content management technique, remote sensing (RS) scene classification (RSSC) always attracts researchers’ attention. In the past decades, many successful methods have been proposed. Nevertheless, their prerequisite is that there are large labeled datasets, which is a strict demand in practice. To resolve this contradiction, developing RSSC models with the help of few-shot learning (FSL) has become popular. Due to lacking prior knowledge, most of the existing few-shot RSSC models pay attention to the learning algorithm. However, they do not attach importance to the complex contents within RS scenes and the intricate interclass/intraclass relations between RS scenes. This would influence their performance negatively. In this article, we propose a new few-shot RSSC model named multipretext-task prototypes guided dynamic contrastive learning network (MPCL-Net). MPCL-Net consists of a multipretext tasks generation submodule, a deep feature learning submodule, and a joint optimization submodule. First, two RS-oriented pretext tasks are constructed under the self-supervised learning (SSL) framework in the multipretext tasks generation submodule, which aims to explore multiscale and rotation-invariant information from RS scenes. Second, a simple convolutional neural network (CNN) is developed in the deep feature learning submodule to transform the RS scenes into visual features. Third, three loss functions are formulated and integrated into the joint optimization submodule. Their goals are to fully capture the diverse land covers within RS scenes and compact/separate the intraclass/interclass samples with limited supervision. Finally, our MPCL-Net can be trained in a meta way. The positive results counted on the three public RS scene datasets confirm that our MPCL-Net is helpful to RSSC tasks under the few-shot scenario. Our source codes are available at https://github.com/TangXu-Group/Remote-Sensing-Images-Classification/tree/main/MPCL.
Association between Gut Microbiota and Digestive System Cancers: A Bidirectional Two-Sample Mendelian Randomization Study

Accumulating evidence indicates that gut microbiota closely correlates with the tumorigenesis of digestive system cancers (DSCs). However, whether the causality between gut microbiota and DSCs exists is unknown. Genome-wide association study (GWAS) summary statistics for gut microbiota and DSCs and the bidirectional two-sample Mendelian randomization (MR) analysis were utilized to assess the causality between gut microbiota and DSCs. Sensitivity analyses were performed to evaluate the robustness of our results. We found that the genus Eggerthella (OR = 0.464, 95%CI: 0.27 to 0.796, p = 0.005) was negatively associated with the risk of gastric cancer. The genetically predicted genus Lachnospiraceae FCS020 group (OR = 0.607, 95%CI: 0.439 to 0.84, p = 0.003) correlated with a lower risk of colorectal cancer, and genus Turicibacter (OR = 0.271, 95%CI: 0.109 to 0.676, p = 0.005) was a protective factor for liver cancer. In the reverse MR, DSCs regulated the relative abundance of specific strains of gut microbiota. We comprehensively screened the association between gut microbiota and DSCs using a bidirectional two-sample MR analysis and identified the causality between several microbial taxa and DSCs. Our discoveries are beneficial for the development of novel microbial markers and microbiota-modifying therapeutics for DSC patients.
Perceived job insecurity and sickness presenteeism among public service employees: Moderated mediation model of organisational culture and gender

Previous research efforts have concentrated on the link between personal factors and sickness presenteeism, with few attempts to research the roles of contextual factors such as organisational culture and perceived job insecurity. Also, the mechanism through which the link exists has not been examined across the gender divide. Therefore, this paper examined the moderated mediation effects of gender on the relationship between perceived job insecurity and sickness presenteeism through organisational culture. A total of 244 (F=140; M=104) respondents participated in the study. The Stanford Presenteeism Scale and Job Insecurity and Organisational Culture scales were used for data collection. Results of the correlation analysis revealed that perceived job insecurity is negatively associated with organisational culture and sickness presenteeism. It also revealed that organisational culture is positively related to sickness presenteeism. The Hayes PROCESS macro analysis showed that organisational culture mediated the relationship between perceived job insecurity and sickness presenteeism. Furthermore, the results of the moderated mediation analysis showed that gender moderated the mediating role of organisational culture in the relationship between perceived job insecurity and sickness presenteeism. The study concluded that the indirect effect of perceived job insecurity on sickness presenteeism through organisational culture was higher among female respondents than their male counterparts.
Artificial neural network applicability in studying hot deformation behaviour of high-entropy alloys

The potentials of artificial neural network (ANN) modelling as a potent machine learning approach for investigating the hot deformation behaviour of high-entropy alloys (HEAs) and multi-principal element alloys during thermomechanical processing are assessed and reviewed. Flow stress of CoCrFeNiMn (FCC Cantor alloy), HfNbTaTiZr (BCC refractory alloy), AlCoCuFeNi, and Al x CoCrFeNi alloys is accurately predicted based on the deformation temperature, strain rate, and strain. Moreover, in comparison with the limited experimental dataset, a significantly larger output dataset can be generated by ANN to gain valuable insights such as prediction of flow stress (and whole dynamic recovery/recrystallisation flow curves), elucidating the microstructural mechanisms such as dynamic precipitation reactions, and obtaining hot working parameters (e.g. deformation activation energy) for different ranges of deformation conditions.
NMR spectra of chiral smectic liquid crystals differing in helical parameters

ABSTRACT Chiral liquid crystals with three-ring rigid core were examined. The method based on the selectively reflected light was used to determine the helical pitch. The helical twist sense was worked out using the polarimetry method. 1H and 13C NMR measurements were performed. The influence of three molecular structure parameters: the type of chiral centre, the length of non-chiral chain and substitution of benzene ring by fluorine atoms, on helical pitch, handedness of helical structure and values of chemical shift in proton and carbon spectra was determined. The change of the length of non-chiral terminal chain has the most significant influence on the temperature dependence of helical pitch. All tested parameters have the biggest influence on the values of chemical shift of atoms in the chiral centre. Graphical Abstract
An Efficient Scaling-Free Folded Hyperbolic CORDIC Design Using a Novel Low-Complexity Power-of-2 Taylor Series Approximation

Hyperbolic trigonometric functions are widely used in several engineering and scientific applications, including digital signal processing (DSP), communication systems, and many others. In this article, we propose a scaling-free hyperbolic coordinate rotation digital computer (CORDIC) algorithm and its architecture based on a novel power-of-2 coefficient low-complexity Taylor series approximation to implement sinh and cosh functions. CORDIC architectures are generally slow due to their high latency of computation. The proposed architecture reduces the latency and achieves the desired precision with only four iterations where an optimized angle set comprised of six CORDIC microrotations are mapped into a four-stage folded-pipeline structure leveraging mutually exclusive behavior of two pairs of microrotations. The proposed design is implemented on field-programmable gate arrays (FPGAs) Xilinx Zedboard using 65.38% less registers with ~63.63% less latency and 48.97% less power consumption compared with the best of the existing designs. The proposed design is synthesized by Synopsys Design Compiler and place and route (PnR) tool using Taiwan Semiconductor Manufacturing Company (TSMC) 65-nm CMOS process. It consumes ~76.31% less area, 68.75% less computational delay, and 68.92% less power consumption compared with the best of the existing designs. Moreover, the proposed architecture involves 46.89% less energy per output (EPO) than the best of the existing designs. The error–energy performance (EEP) and the error–area performance (EAP) of the proposed design are, respectively, ~1.25 times and ~2.8 times better than that of the best of the existing designs. Besides, the proposed architecture is also implemented and verified on a silicon chip in the TSMC 180-nm CMOS process for the validation of the algorithm and architecture.
Semi-Analytical AC Resistance Prediction Model for Litz Wire Winding in High-Frequency Transformer

The importance of the high-frequency transformer in power electronics devices cannot be overstated. Its compact design is made possible by operating in a high-frequency range, although winding losses increase due to eddy current effects. One solution to this problem is using litz wire, which has a small cross-sectional area and is less affected by eddy current effects at high frequencies. However, accurately predicting winding loss in litz wire is challenging due to efficiency and accuracy concerns as well as the impact of influencing factors. Prior articles have focused on the strand structure of litz wire conductors, often ignoring the impact of operating conditions and geometrical parameters on leakage field distribution and ac resistance. To address this gap, this article introduces a simple semi-analytical model with revised coefficient to enhance the accuracy of conventional ac resistance prediction models. The model considers the interplay between winding structure and core as well as the influence of operating conditions on the conductor. The article examines the winding loss of litz wire in a high-power transformer using this model. Experimental prototypes based on the resulting formulas confirm improved matching between calculation results and measurements.
Access to Credit and the Expansion of Broadband Internet in Peru

We exploit the staggered expansion of the internet broadband network to firms and bank branches locations in Peru during the last decade to study non-financial firm performance and bank credit dynamics. Access to broadband unleashes firm growth, increases the chances of entry of firms and reduces the probability of exit in benefited locations. For those firms that had a borrowing relation with a bank before the expansion of broadband, the increase in sales serves as a signal to banks about their profitability, which in turn respond by providing more credit. Entry and exit from the credit market follows a similar pattern as in the case of firms, but the results take longer to materialize after the shock. We can disentangle supply and demand effects, since there is a group of firms and bank branches with different locations and asymmetrical timing for the availability of the technology. Our analysis highlights the importance of the demand channel in the reduction of the observed interest rates, which is consistent with the fact that our credit market results are concentrated among micro and small firms, and firms with thin credit files, which are often perceived as riskier.
Association of Low Serum Bilirubin Concentrations and Promoter Variations in the UGT1A1 and HMOX1 Genes with Type 2 Diabetes Mellitus in the Czech Population

Bilirubin has potent biological beneficial effects, protecting against atherosclerosis, obesity, and metabolic syndrome. The aim of this study was to assess serum bilirubin concentrations and (TA)n and (GT)n microsatellite variations in the promoter regions of the UGT1A1 and HMOX1 genes, respectively, in patients with type 2 diabetes mellitus (T2DM). The study was carried out in 220 patients with T2DM and 231 healthy control subjects, in whom standard biochemical tests were performed. The (TA)n and (GT)n dinucleotide variations were determined by means of fragment (size-based) analysis using an automated capillary DNA sequencer. Compared to controls, both male and female patients with T2DM had lower serum bilirubin concentrations (9.9 vs. 12.9 μmol/L, and 9.0 vs. 10.6 μmol/L, in men and women, respectively, p < 0.001). Phenotypic Gilbert syndrome was much less prevalent in T2DM patients, as was the frequency of the (TA)7/7 UGT1A1 genotype in male T2DM patients. (GT)n HMOX1 genetic variations did not differ between diabetic patients and controls. Our results demonstrate that the manifestation of T2DM is associated with lower serum bilirubin concentrations. Consumption of bilirubin due to increased oxidative stress associated with T2DM seems to be the main explanation, although (TA)n repeat variations in UGT1A1 partially contribute to this phenomenon.
Turbulence-induced viscous dissipation in a quantum-mechanical piston shock

The piston shock problem is a prototypical example of strongly nonlinear fluid flow that enables the experimental exploration of fluid dynamics in extreme regimes. We investigate this problem for the case of a nominally inviscid, superfluid Bose-Einstein condensate and observe rich dynamics including the formation of a plateau region, a sharp shock front, and rarefaction waves. Interestingly, many aspects of the observed dynamics follow the predictions of classical viscous, rather than superfluid dispersive, shock theory. The emergence of viscous dissipation in the fluid is attributed to turbulent vortex dynamics. Our experimental observations are accompanied by numerical simulations revealing a turbulent energy spectrum $E$ that develops into the critical balance regime $E \sim k^{-2}$, typical of wavebreaking scenarios in other systems. This work provides a new avenue for the investigation of quantum shock waves and turbulence in channel geometries, both of which are currently the focus of intense research efforts.