Miracle-dz/UniFAR-FTUs huggingface dataset:
Nominal and Real Convergence of European Union and Western Balkan Countries: A Panel Data Analysis

: Purpose: In view of the fact that the economic future of the region is the European Union, this research paper studies the economic progress of the Western Balkan countries towards the EU, based on the performance of macroeconomic indicators. The purpose of the research paper is to analyse the macroeconomic indicators of the Western Balkan countries, the assessment of the economic growth per capita during the period 2000-2020, the expectations for the future, and the measurement of the economic progress of such countries towards the European path. Design/Methodology/Approach: Through panel data using several econometric models, the consideration of the Maastricht criteria in achieving convergence between the Western Balkan countries and the European Union countries, is examined. Using the indicator of economic growth and the GDP per capita in purchasing power parity, the direct significance of the Maastricht criteria in the real convergence between these countries is measured. Findings: Empirical results showed that there is a relationship between real and nominal convergence, with the nominal convergence being considered a prerequisite for achieving real convergence. Practical Implications: The agenda for the idea of European expansion should become a genuine economic policy based on economic parameters measured and analyzed with research and scientific methods. As the study highlights different aspects of economic growth promoters, the quality of institutions is one of the critical indicators that mobilize macroeconomic factors to ensure economic growth in WB countries. Originality/Value: This paper provides a fine scientific and research example in analyzing the convergence process. The results can serve as a good guide for policymakers in navigating the right path to EU membership.
Prevalence of mastitis in dairy animals in Indonesia: A systematic review and meta-analysis

Background and Aim: Mastitis is an important disease that can reduce milk production and farmer income as well as negatively affect human health. This study aimed to summarize dairy mastitis in Indonesia, both subclinical mastitis (SCM) and clinical mastitis (CM), and its prevalence in different provinces, the diagnostic methods, and the animal species. Materials and Methods: Relevant studies on mastitis in dairy animals in Indonesia were obtained from PubMed, Scopus, ProQuest, Google Scholar, and Garuda. The title and abstract were screened for the eligibility of the studies. The full text of the selected studies was assessed and the data were extracted for analysis. To determine the pooled estimate of the prevalence of mastitis, a random-effects model was performed using the “Meta” and “Metaphor” packages in the R software version 4.2. 2. The heterogeneity of several characteristics (mastitis type, provinces, animal species, and diagnostic methods) was evaluated through subgroup meta-analysis. Meta-regression analysis was conducted to assess the trend of mastitis prevalence reports over time. Publication bias was evaluated using Egger’s test and a funnel plot. Results: A total of 735 studies were retrieved for the title and abstract screening, which resulted in the final selection of 37 studies with a total of 6050 samples for meta-analysis. The pooled estimate of mastitis prevalence in dairy animals in Indonesia was 59.44% (95% confidence interval [CI], 52.39%–66.49%). Based on mastitis type, SCM had a significantly higher prevalence than CM (58.24% [95% CI, 51.26%–65.23%] vs. 3.31% [95% CI, 1.42%–5.19%]). No significant difference was observed in the analysis of other subgroups. Among provinces, Central Java had the highest prevalence (66.62% [95% CI, 49.37%–83.87%]), whereas Yogyakarta had the lowest (41.77% [95% CI, 14.96%–68.58%]). Based on animal species, cow and goat had a prevalence of 63.42% (95% CI, 55.97%–70.86%) and 44.96% (95% CI, 28.26%–61.66%), respectively. Based on the diagnostic method, the California mastitis test resulted in 60.08% (95% CI, 52.11%–68.06%) and the Institut Pertanian Bogor test, 56.00% (95% CI, 41.20%–70.81%). No significant change in the prevalence of mastitis in Indonesia was observed from 2003 to 2022. Conclusion: This study demonstrates that the pooled estimate of mastitis prevalence in dairy animals in Indonesia is >50%. Based on subgroup analysis, SCM had a higher prevalence than CM; however, the prevalence between provinces, detection methods, and animal species in the 2003–2022 periods was not significantly different. A mastitis control strategy needs to be developed to reduce the prevalence of mastitis and further loss in milk production.
Pictorial-Based Learning Model for Remote Vocabulary Learning: A Systematic Review

This systematic review was conducted to provide inspiration on the development of a learning model for vocabulary learning via the use of pictorials, as well as the omissions and gaps in the synthesized literature on the topic, especially with regards to the use of such a model for remote learning. The significance of this particular study lies in the affirmation of whether this pictorial-based vocabulary learning model is a viable solution for the necessity of remote learning. There are a total of three research questions, which are (1) What are the benefits of developing a pictorial-based vocabulary model for learning vocabulary? (2) What are the challenges in the integration and application of digital technology for remote learning and learning enhancement? and (3) How effective is using pictorial elements in enhancing students’ learning of vocabulary? Two main databases – ResearchGate and Scopus – were explored for data collection. A total of 16 studies of relevance to the topic of investigation were retained for further analysis out of more than 50 studies after the strict process of removing duplicates and scrutinizing the abstracts for a suitable level of relevance. To account for the derivation of the various themes under this review, the method of a thematic analysis was preferred. The emerging themes being analyzed are: (1) The Development of a Pictorial-Based Learning Model for Vocabulary Learning (2) The Integration and Application of Digital Technology for Remote Learning and Learning Enhancement (3) The Effectiveness of Using Pictorial Elements on Enhancing Students’ Learning of Vocabulary.
Evolution of planar defects during homoepitaxial growth of β-Ga2O3 layers on (100) substrates—A quantitative model

We study the homoepitaxial growth of β-Ga2O3 (100) grown by metal-organic vapour phase as dependent on miscut-angle vs. the c direction. Atomic force microscopy of layers grown on substrates with miscut-angles smaller than 2° reveals the growth proceeding through nucleation and growth of two-dimensional islands. With increasing miscut-angle, step meandering and finally step flow growth take place. While step-flow growth results in layers with high crystalline perfection, independent nucleation of two-dimensional islands causes double positioning on the (100) plane, resulting in twin lamellae and stacking mismatch boundaries. Applying nucleation theory in the mean field approach for vicinal surfaces, we can fit experimentally found values for the density of twin lamellae in epitaxial layers as dependent on the miscut-angle. The model yields a diffusion coefficient for Ga adatoms of D = 7 × 10−9 cm2 s−1 at a growth temperature of 850 °C, two orders of magnitude lower than the values published for GaAs.
Research on temperature measurement by spontaneous Rayleigh-Brillouin scattering profile

Rayleigh-Brillouin scattering is a promising remote diagnostic technique for the measurement of gas temperature in high pressure environments, such as the Space Shuttle Main Engine Pre-burner. In order to study the accuracy in temperature measurement of three theoretical models (Tenti S6 model, V3 model and G3 model), spontaneous Rayleigh-Brillouin scattering experiments in nitrogen (N2) have been conducted at a wavelength of 532nm in the pressure range from 4 atm to 7atm with a temperature of 298K and a 93° scattering angle. The spontaneous Rayleigh-Brillouin scattering profile with high signal-to-noise ratio (SNR) is measured by scanning Fabry-Perot interferometer (FPI). By comparing the root-mean-square error of fitting residuals respectively for Tenti S6 model, V3 model and G3 model, it is found that V3 and G3 model have good fitting performance, while as for the processing data ability, the G3 model yield a fastest speed at only 0.09s. As for the measurement accuracy of the temperature retrieved from fitted data, it is found that the maximum absolute error for Tenti S6 model is at around 4K and those for V3 and G3 models are more than 10K, which means Tenti S6 model is most accurate in retrieving temperature. However, although there is a large error in measuring temperature with V3 and G3 models, this margin of error is allowed in the temperature measurement of the high-temperature tail flame of a pulsed detonation engine.
An obstacle problem arising in large exponent limit of power mean curvature flow equation

We study limit behavior for the level-set power mean curvature flow equation as the exponent tends to infinity. Under Lipschitz continuity, quasiconvexity, and coercivity of the initial condition, we show that the limit of the viscosity solutions can be characterized as the minimal supersolution of an obstacle problem involving the 1-Laplacian. Such behavior is closely related to applications of power mean curvature flow in image denoising. We also discuss analogous behavior for other evolution equations with related applications.
Spin and Charge Qubits in Si/SiGe Quantum dots

In this thesis, we study the spin and charge properties of Si/SiGe double dot system and demonstrate coherent quantum control of few-electron qubits. First, we use a pulsed magneto-spectroscopy method to measure the excited-state spectrum of a Si/SiGe quantum dot. The application of this technique in a two-electron quantum dot allows us to identify the spin of the lowest three eigenstates, which are S, T− and T0, in different field values. We extract the singlet-triplet energy splitting, an essential parameter for spin qubits, from the magneto-spectroscopy data and find it tunable by lateral displacement of the dot, which is realized by changing two gate voltages on opposite sides of the device. We present calculations showing the data are consistent with a spectrum in which the first excited state of the dot is a valley-orbit state. Next, making use of the two-electron singlet and triplet states we measure above, as well as a one-electron state in the adjacent dot, we propose a quantum dot qubit architecture that has an attractive combination of speed and fabrication simplicity. The proposed hybrid qubit consists of a double quantum dot with two electrons in one dot and one electron in the other. The qubit itself is a set of two states with total spin quantum numbers S2 = 3/4 (S = 1/2) and Sz = −1/2, with the two different states being singlet and triplet in the doubly occupied dot. Gate operations can be implemented electrically, and the qubit is highly tunable, enabling fast implementation of oneand two-qubit gates in a simpler geometry and with fewer operations than in other proposed quantum dot qubit architectures with fast operations. Moreover, the system has potentially long coherence times. These are all extremely attractive properties for use in quantum information processing devices. The hybrid qubit formed from three electrons in a double quantum dot has the potential for great speed due to presence of level crossings where the qubit becomes charge-like. Therefore, to implement a pulse-gated hybrid qubit, we first demonstrate coherent manipulations in a three-electron charge qubit. Fast quantum oscillations of a charge qubit in a double quantum dot are demonstrated and characterized experimentally. The measured inhomogeneous dephasing time T ∗ 2 ranges
Emergence of altruistic behavior in heterogeneous populations of artificial agents by evolution of kin discrimination mechanism

The emergence of altruistic behaviors in heterogeneous populations of autonomous robots, especially in signaling tasks, has proven to be a difficult problem to solve. However signaling and altruistic behaviors are present throughout the tree of life. Specially giving that, signaling behaviors seem to have evolved multiple times whenever there is a channel to emit a signal and one to receive it. In this work, this problem is addressed, using evolutionary algorithms, and modeling phenomena such as kin selection and kin discrimination in a biologically plausible way. We also used self-organizing maps to analyze the behavior of these populations during the evolutionary process, within the solution space. We believe that this approach can shed light on the predictive power of the Hamilton rule, the importance of kin selection in the evolution of altruistic behaviors, and how self-organizing maps can allow us to observe the different solutions in which the evolutionary algorithm converges through time.
Turbulent boundary layer investigations with conventional and stereoscopic PIV

In order to obtain detailed information about coherent structures, instantaneous velocity fields were measured in two flat plate boundary layer flows applying high resolution Particle Image Velocimetry. The experiments were performed in two wind tunnels with different PIV technique.The plane normal to the wall was investigated using the conventional PIV technique. Planes parallel to the wall were measured with a digital stereo system which provided all three velocity components simultaneously. The statistical properties of the velocity obtained by ensemble averaging of the PIV recordings are in reasonable agreement with results obtained by other measurement techniques. Two dimensional correlations yielded the average dimensions of the vortical structures in different planes parallel to the wall. The observed dimensions are in agreement with hot wire results of other investigations.
The effect of human capital and structural capital on leverage: Evidence from Jordan

This study investigates the effect of human capital and structural capital on leverage for Jordanian industrial firms from 2006 to 2020. The relevance of this topic lies in the importance of capital structure decisions for firm value and the limited research conducted on the topic in Jordan. The aim is to examine whether human capital efficiency and structural capital efficiency significantly affect leverage. The sample includes 77 industrial firms. The study employs multiple regression analysis to test the hypotheses, controlling for variables such as return on equity and firm size. The findings show that structural capital efficiency does not significantly affect leverage, but human capital efficiency and ROE have significant effects. Furthermore, the study finds that the relationship between these variables differs between large and small companies. This implies that firms with more efficient human capital tend to use less debt financing. The study concludes that human and structural capital efficiency should be considered when making capital structure decisions, as they can affect the optimal level of debt financing. The practical value is the insights for firms in Jordan and other emerging markets on optimizing their capital structure decisions by considering their human and structural capital efficiency. These results contribute to the literature on firm performance determinants in emerging economies and offer valuable information for practitioners and policymakers. AcknowledgmentI want to thank Amman Arab University for funding this study.
Identifikasi Pemberdayaan dan Sertifikasi Halal Pada UMKM oleh Lembaga Zakat di Bangkalan Madura

Indonesia Law Number 33 of 2014 concerning Halal Product Guarantee emphasizes that food, medicine, cosmetics and other products must be halal certified, which not only applies to products of large companies, but also targets MSME. Apart from going through a special self-declaration route for simple products for free, most MSMEs such as processed products from slaughter, pentol sellers, meatballs need to get service facilitation, which can be taken from social institution posts, such as zakat, infaq and shodaqaoh. Zakat management institutions are one of the institutions that collect, manage and distribute social religious funds, which are intended to improve economic levels, either consumptively or productively. With approximately 166,000 MSMEs in Bangkalan Regency, the participation of social religious institutions is needed to support the halal certification policy. This research used qualitative method, descriptive analytical with empirical approach. Data collection through interviews, observations and documentation studies at zakat management institutions in Bangkalan. The results showed that zakat management institutions in Bangkalan have not facilitated the halal certification process for MSME, apart from the fact that there has been no socialization from zakat institutions at the central level to play an active role in the program, also concerns about the h}add al-kifayah standard for mustahiq need to be emphasized so that the limits of zakat distribution for empowerment and acceleration of halal certification programs are right on target and right based on sharia provisions, it is necessary to identify the income of MSMEs so that the mustahiq category can still be accommodated.
Structural change detection via penalized regression

This dissertation research addresses how to detect structural changes in stochastic linear models. By introducing a special structure to the design matrix, we convert the structural change detection problem to a variable selection problem. There are many existing variable selection strategies, however, they do not fully cope with structural change detection. We design two penalized regression algorithms specifically for the structural change detection purpose. We also propose two methods involving these two algorithms to accomplish a bi-level structural change detection: they locate the change points and also recognize which predictors contribute to the variation of the model structure. Extensive simulation studies are shown to demonstrate the effectiveness of the proposed methods in a variety of settings. Furthermore, we establish asymptotic theoretical properties to justify the bi-level detection consistency for one of the proposed methods. In addition, we write an R package with computationally efficient algorithms for detecting structural changes. Comparing to traditional methods, the proposed algorithms showcase enhanced detection power and more estimation precision, with added capacity of specifying the model structures at all regimes.
Exploring the Enhanced Antiproliferative Activity of Turmeric Oil and 6-Mercaptopurine in a Combined Nano-Particulate System Formulation

6-Mercaptopurine (6-MP) is a chemotherapeutic agent with inadequate efficacy due to its poor aqueous solubility and limited bioavailability. Turmeric oil is a naturally occurring bioactive substance obtained from the rhizomes of Curcuma longa Linn that has well-known antiproliferative activities. The aim of this study was to develop a 6-MP-loaded turmeric oil-based self-nanoemulsifying drug delivery system (SNEDDS) to improve the anticancer activity of 6-MP. Turmeric oil was extracted and used in a range of 15–25% to develop SNEDDS formulations utilizing tween 80 and dimethyl sulfoxide as the surfactant and cosurfactant, respectively. The size, charge, and effect of the formulations on the viability against HepG2 and MCF-7 cell models, as well as the apoptosis and cell cycle, were analyzed. The prepared SNEDDS formulations were in the size range of 425.7 ± 7.4–303.6 ± 19.3 nm, using a polydispersity index of 0.429–0.692 and electronegative surface charges. Moreover, 6-MP-loaded SNEDDS with 15% turmeric oil content (F1) showed smaller particle sizes and a noticeable antiproliferative activity against both cell line models. Also, F1 showed a higher rate of late apoptosis than the pure drug and the corresponding non-medicated formulation. A morphological study revealed significant changes in the HepG2 cells compared to untreated cells. More cells halted in the S phase, and a marked decrease in the proportions of cells in the G1/G0 phase was observed when using SNEDDS formulation compared to pure drug. Thus, SNEDDS formulation is a promising drug delivery system for improving the antiproliferative activity of 6-MP, especially when turmeric oil is incorporated.
The non‐local character of turbulence asymmetry in the convective atmospheric boundary layer

The inadequacy of conventional gradient diffusion in closure modelling of turbulent heat fluxes within the convective atmospheric boundary layer is often alleviated by accounting for non‐local transport effects, such as Deardorff's counter‐gradient models, Wyngaard's transport asymmetry closures or mass‐flux parametrization. This concept of large‐eddy flux transport is examined here with the principal aim of unifying these seemingly different models. Using large‐eddy simulation (LES) runs for the atmospheric boundary layer, spanning weakly to strongly convective conditions, a generic diagnostic framework that encodes the role of third‐order moments in non‐local transport is developed and tested. The premise is that these non‐local effects are responsible for the inherent asymmetry in vertical transport and hence the necessary non‐Gaussian nature of the joint probability density function (JPDF) of vertical velocity and potential temperature must account for these effects. Conditional sampling (quadrant analysis) of this JPDF and the imbalance between the flow mechanisms of ejections and sweeps are used to characterize this asymmetry, which is then linked to the third‐order moments using a cumulant‐discard method for the Gram–Charlier expansion of the JPDF. While the concept of ejection‐sweep events used here is not a simple extension of that commonly used in the surface layer, their connection to third‐order moments shows that the concepts of bottom‐up/top‐down diffusion or updraught/downdraught models are accounted for by various quadrants of the JPDF. An analogy between mass‐flux models and the relaxed eddy accumulation method reveals that there is a seemingly implicit assumption of a Gaussian JPDF in the former.
Causal Effects between Gut Microbiome and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Two-Sample Mendelian Randomization Study

Background Evidence from previous studies have implicated an important association between gut microbiota (GM) and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), but whether there is a definite causal relationship between GM and ME/CFS has not been elucidated. Method This study obtained instrumental variables of 211 GM taxa from the Genome Wide Association Study (GWAS), and mendelian randomization (MR) study was carried out to assess the effect of gut microbiota on ME/CFS risk from UK Biobank GWAS (2076 ME/CFS cases and 460,857 controls). Inverse variance weighted (IVW) was the primary method to analyze causality in this study, and a series of sensitivity analyses was performed to validate the robustness of the results. Results The inverse variance weighted (IVW) method indicated that genus Paraprevotella (OR:1.001, 95%CI:1.000–1.003, value of p < 0.05) and Ruminococca- ceae_UCG_014 (OR 1.003, 95% CI 1.000 to 1.005, value of p < 0.05) were positively associated with ME/CFS risk. Results from the weighted median method supported genus Paraprevotella (OR 1.003, 95% CI 1.000 to 1.005, value of p < 0.05) as a risk factor for ME/CFS. Conclusion This study reveals a causal relationship between genus paraprevotella, genus Ruminococcaceae_UCG_014 and ME/CFS, and our findings provide novel insights for further elucidating the developmental mechanisms mediated by the gut microbiota of ME/CFS.