Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effectiveness of e-Learning, Learning Styles, Prior Knowledge, and Internet Self Efficacy in Business Mathematics Courses

The purpose of this study is to analyze the effectiveness of e-learning associated with learning style variables, prior knowledge, and internet self-efficacy (ISE) in the Business Mathematics course. The research method uses descriptive statistics and correlations, where the learning styles studied are visual, auditory, reading, and kinesthetic. The results and conclusions of this study are (1) the majority of respondents have a visual learning style, (2) simultaneously learning styles, prior knowledge, and internet selfefficacy affect learning outcomes in e-learning strategies, (3) partially initial knowledge and internet self-efficacy does not affect learning outcomes, and (4) The effectiveness of e-learning Business Mathematics is achieved in respondents with visual learning styles, because respondents with this learning style tend to have high internet selfefficacy, even though respondents have low prior knowledge of Mathematics Abstrak Tujuan dari penelitian ini adalah untuk menganalisis efektivitas e-learning dikaitkan dengan variabel gaya belajar, pengetahuan awal, dan internet self efficacy (ISE) pada mata kuliah Matematika Bisnis. Metode penelitian menggunakan statitika deskriptif dan korelasi, dimana gaya belajar yang diteliti adalah visual, auditory, reading, dan kinestetik. Hasil dan kesimpulan penelitian ini adalah (1) mayoritas responden mempunyai gaya belajar visual, (2) secara simultan gaya belajar, pengetahuan awal, dan internet self efficacy mempengaruhi hasil belajar dalam strategi e-learning, (3) secara parsial pengetahuan awal dan internet self efficacy tidak mempengaruhi hasil belajar, dan (4) Efektivitas e-learning Matematika Bisnis tercapai pada responden dengan gaya belajar visual, karena responden dengan gaya belajar tersebut cenderung mempunyai internet self efficacy yang tinggi, walaupun responden memiliki pengetahuan awal Matematika yang rendah.
Towards Deep Radar Perception for Autonomous Driving: Datasets, Methods, and Challenges

With recent developments, the performance of automotive radar has improved significantly. The next generation of 4D radar can achieve imaging capability in the form of high-resolution point clouds. In this context, we believe that the era of deep learning for radar perception has arrived. However, studies on radar deep learning are spread across different tasks, and a holistic overview is lacking. This review paper attempts to provide a big picture of the deep radar perception stack, including signal processing, datasets, labelling, data augmentation, and downstream tasks such as depth and velocity estimation, object detection, and sensor fusion. For these tasks, we focus on explaining how the network structure is adapted to radar domain knowledge. In particular, we summarise three overlooked challenges in deep radar perception, including multi-path effects, uncertainty problems, and adverse weather effects, and present some attempts to solve them.
Design of L + U‐band Erbium‐doped fiber amplifier based on a single S‐band forward pump source

The multi‐band transmission (MBT) technique is one of the most cutting‐edge approaches to increase the capacity of fiber‐optic transmission systems and meeting the growing bandwidth demand. MBT technique considers the transmission in C + L‐ and U‐bands based on Erbium‐doped fiber amplifiers (EDFAs). Therefore, we propose a high gain and low noise figure EDFA for L + U‐band amplification having gain bandwidth of more than 82 nm in the spectral range of 1578–1660 nm, based on a single standard S‐band forward pump source. The L + U‐band amplification is obtained by pumping the gain medium which is heavily doped with Er3+. The results based on numerical simulations show that an efficient amplification is obtained over L + U‐band with an average small signal gain of around 39 dB covering 1578–1660 nm wavelength range while incorporating a short 12 m length of Erbium‐doped fiber (EDF) at an optimized pump power of 300 mW. A maximum noise figure of 4.46 dB is observed at 1593 nm. In addition, power conversion efficiency (PCE) of different C‐band pump wavelengths has also been evaluated, and the findings show that the PCE of 1560 nm pump wavelength is 70% higher than standard 1480 nm pump wavelength at the expense of cost efficiency. Finally, the system level performance of the designed L + U‐band EDFA is investigated in a five channel wavelength division multiplexed (WDM) link.
Key Drivers of Customer Satisfaction on the E-Commerce Business

To survive in the e-retail business, current online retailers should compete with others to retain their customers. Tremendous efforts are required to meet the expectations of demanding online customers. This means that online businesses should understand what key factors determine customer satisfaction to survive in the current e-commerce business. The aim of this paper is to analyze the key factors of customer satisfaction for e-commerce companies. The methodology of this study is based on the work of (Yoon, 2007), which consists of customer service, fulfilment/reliability, ease of use, product/service offering, and security and privacy. The world's two leading e-commerce companies - Amazon and eBay - were selected as best practice examples for this case.
Soaking Soybean Seeds with Abeliophyllum distichum Nakai Extract Increased the Yield and Nutritional Value of Soybean Sprouts

Abeliophyllum distichum Nakai, an ornamental plant, contains a wide range of phytochemicals having pharmaceutical properties. The use of dif - ferent plant-based extracts for the enhancement of yield and/or quality of soybean sprouts, one of the most inexpensive but nutritious food products, is common. The objective of this study was to examine the effect of A. distichum flower extract (ADE) on the yield and nutritional value of soybean sprouts. Soybean seeds were soaked in ADE solutions with concentrations ( w/v ) of 0.5% (ADE-0.5), 1% (ADE-1), 3% (ADE-3), and 5% (ADE-5). The effect of ADE concentration on the yield and different nutrient components varied. The highest soybean sprout yield and vitamin C content were found with ADE-3. The most abundant essential amino acid content was detected in ADE-1, whereas the greatest amounts of total isoflavones and to tal minerals were determined in ADE-5 and the ADE-untreated control, respectively. Overall results of yield, color, and contents of vitamin C, amino acids, and isoflavones suggest that 1% or 3% of A. distichum extract could be an optimum concentration to soak the soybean seeds for higher sprout yield and nutrient content.
A New Continuous Input Current Nonisolated Bidirectional Interleaved Buck-Boost DC-DC Converter

In this paper, a new interleaved bidirectional buck-boost DC-DC converter is proposed. The input current of this converter is continuous and has a low ripple, that cause reduction in the size of the input filter of the converter. Because of these features, this converter is appropriate for renewable applications such as fuel cells and photovoltaic (PV) panels for obtaining maximum power in which the continuity of the input current is essential. The operation principle of this converter is detailed, and its power losses calculation shows the positive effects of the low input current ripple on its efficiency. The input current ripple of the proposed converter and conventional interleaved buck-boost converter has been calculated in detail. In addition, the comparison results of this converter with conventional interleaved buck-boost converters and other similar structures confirm that the proposed converter without utilizing extra components achieves continuous input current with low ripple. Compared with other buck-boost structures, the low input current ripple in the presented converter causes an improvement in its efficiency. An experimental prototype is implemented in the laboratory to confirm the correctness of theoretical analyses.
Investigating the DSM-5 and the ICD-11 PTSD symptoms using network analysis across two distinct samples.

OBJECTIVE Posttraumatic stress disorder (PTSD) has long been debated with a recent focus on the consequences of having two different diagnostic descriptions of PTSD (i.e., the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition [DSM-5] and the International Classification of Diseases-11th Edition [ICD-11]). Research has modeled PTSD as a network of interacting symptoms according to both diagnostic systems, but the relations between the two systems remain unclear regarding which symptoms are more central or interconnected. To answer this question, the present study is the first study to investigate the combined network structure of PTSD symptoms according to both systems using validated measurements (i.e., the International Trauma Questionnaire [ITQ] and the Posttraumatic Stress Disorder Checklist 5 [PCL-5] across two distinct trauma samples [a community sample, N = 2,367], and a military sample, N = 657). METHOD We estimated two Gaussian Graphical Models of the combined ICD-11 and DSM-5 PTSD symptoms across the two samples. RESULTS Five of the six most central symptoms were the same across both samples. CONCLUSIONS The results underline that a combination of five symptoms representing both diagnostic systems may hold central positions and potentially be important for treatment. However, the implications depend on if the different diagnostic descriptions can be reconciled in an indexical rather than constitutive perspective. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
functional analysis of Ghanaian presidential debates

Scholars of the functional theory of campaign discourse have explored the nature of political campaign discourse, particularly presidential campaign discourse. This paper adds to the exploration and the data by analysing Ghanaian presidential debates using Benoit’s functional theory. The analysis reveals that the presidential candidates acclaimed more than they attacked and defended. Two additional functional categories – appeal and recommendation – are identified. Contrary to the assumptions of the functional theory that incumbents acclaim more than challengers, the paper finds that challengers acclaimed more than the incumbent, and that the candidates discussed more future plans/deliberative rhetoric. The study concludes that even though most of the assumptions of the theory were confirmed, there are additional persuasive strategies of presidential candidates in Ghanaian political debates such as appeal and recommendation. Thus, the study recommends that further studies extend the theory to accommodate the discourse strategies in multi-candidate campaigns since the theory emerged from several studies of two-candidate campaigns in the United States.
The Impact of Fiscal Rules on the Fiscal Deficit for Ten Countries of the European Union -Empirical Analysis for the Period 1995-2020

This paper analyzes whether fiscal rules impact improved budget performance and fiscal discipline in the ten EU nations with the largest average fiscal deficit from 1995 to 2020. Fiscal performance will be reflected through the fiscal deficit adjusted for cyclical economic periods. The independent variables are real long-term interest rates, fiscal rules, public debt (expressed as a percentage of GDP), government effectiveness, and government spending (expressed as a percentage of GDP). The methodology used consists of empirical panel data through the OLS econometric model. With this model we have analyzed the responsiveness of the fiscal deficit, which have applied fiscal rules, by incorporating in the model other factors as well. The empirical results shows that fiscal rules, public debt, government effectiveness, and government spending statistically significantly impact the fiscal deficit. At the same time, the real long-term interest rate did not reach the level of statistical significance based on the model results.
Investigation of Global Trends of Pollutants in Marine Ecosystems around Barrang Caddi Island, Spermonde Archipelago Cluster: An Ecological Approach

High-quality marine ecosystems are free from global trending pollutants’ (GTP) contaminants. Accuracy and caution are needed during the exploitation of marine resources during marine tourism to prevent future ecological hazards that cause chain effects on aquatic ecosystems and humans. This article identifies exposure to GTP: microplastic (MP); polycyclic aromatic hydrocarbons (PAH); pesticide residue (PR); heavy metal (HM); and medical waste (MW), in marine ecosystems in the marine tourism area (MTA) area and Barrang Caddi Island (BCI) waters. A combination of qualitative and quantitative analysis methods were used with analytical instruments and mathematical formulas. The search results show the average total abundance of MPs in seawater (5.47 units/m3) and fish samples (7.03 units/m3), as well as in the sediment and sponge samples (8.18 units/m3) and (8.32 units/m3). Based on an analysis of the polymer structure, it was identified that the dominant light group was MPs: polyethylene (PE); polypropylene (PP); polystyrene (PS); followed by polyamide-nylon (PA); and polycarbonate (PC). Several PAH pollutants were identified in the samples. In particular, naphthalene (NL) types were the most common pollutants in all of the samples, followed by pyrene (PN), and azulene (AZ). Pb+2 and Cu+2 pollutants around BCI were successfully calculated, showing average concentrations in seawater of 0.164 ± 0.0002 mg/L and 0.293 ± 0.0007 mg/L, respectively, while in fish, the concentrations were 1.811 ± 0.0002 µg/g and 4.372 ± 0.0003 µg/g, respectively. Based on these findings, the BCI area is not recommended as a marine tourism destination.
NeuroGrasp: Multimodal Neural Network With Euler Region Regression for Neuromorphic Vision-Based Grasp Pose Estimation

Grasp pose estimation is a crucial procedure in robotic manipulation. Most of the current robot grasp manipulation systems are built on frame-based cameras like RGB-D cameras. However, the traditional frame-based grasp pose estimation methods have encountered challenges in scenarios such as low dynamic range and low power consumption. In this work, a neuromorphic vision sensor—dynamic and active-pixel vision sensor (DAVIS)—is introduced to the field of robotic grasp. DAVIS is an event-based bio-inspired vision sensor that records asynchronous streams of local pixel-level light intensity changes, called events. The strengths of DAVIS are it can provide high temporal resolution, high dynamic range, low power consumption, and no motion blur. We construct a neuromorphic vision-based robotic grasp dataset with 154 moving objects, named NeuroGrasp, which is the first RGB-Event multimodality grasp dataset (to the best of our knowledge). This dataset records both RGB frames and the corresponding event streams, providing frame data with rich color and texture information and event streams with high temporal resolution and high dynamic range. Based on the NeuroGrasp dataset, we further develop a multimodal neural network with a specific Euler region regression sub-network (ERRN) to perform grasp pose estimation. Combined with frame-based and event-based vision, the proposed method achieves better performance than the method that only takes RGB frames or event streams as input on the NeuroGrasp dataset.
Stability of insurance efficiency during the Covid-19 pandemic: A comparative study between Islamic and conventional insurance in Indonesia

Purpose – The purpose of this study is to measure and compare The Stability of the efficiency of insurance companies, particularly during the COVID-19 pandemic, at 70 insurance institutions (both sharia and conventional) in Indonesia over Five years, from 2016 to 2020.Methodology – Non-parametric approach, Data Envelopment Analysis (DEA), then extended by Window DEA analysis was employed as the research method.Findings – This study found that COVID-19 has little effect on Insurance efficiency. COVID-19 has a detrimental impact on the efficiency of conventional insurance but does not affect Sharia insurance. This study also found that most Indonesian Insurances are considered the worst performers in terms of efficiency and efficiency stability during the study period. Most of the insurances are included in quadrant IV (low efficiency and high stability). Furthermore, according to the window DEA analysis, the most relatively stable value of Indonesian Insurances is Sinarmas Conventional InsuranceOriginality – The study that focuses on measuring the efficiency of sharia insurances compared to the efficiency of conventional insurances in Indonesia during the COVID-19 outbreak has never been conducted. This study was the first to measure and compare the efficiency of Indonesian Insurances using the Window DEA analysis.
New Wave of COVID-19 Vaccine Opinions in the Month the 3rd Booster Dose Arrived

Vaccination has been proposed as one of the most effective methods to combat the COVID-19 pandemic. Since the day the first vaccine, with an efficiency of more than 90%, was announced, the entire vaccination process and its possible consequences in large populations have generated a series of discussions on social media. Whereas the opinions triggered by the administration of the initial COVID-19 vaccine doses have been discussed in depth in the scientific literature, the approval of the so-called 3rd booster dose has only been analyzed in country-specific studies, primarily using questionnaires. In this context, the present paper conducts a stance analysis using a transformer-based deep learning model on a dataset containing 3,841,594 tweets in English collected between 12 July 2021 and 11 August 2021 (the month in which the 3rd dose arrived) and compares the opinions (in favor, neutral and against) with the ones extracted at the beginning of the vaccination process. In terms of COVID-19 vaccination hesitance, an analysis based on hashtags, n-grams and latent Dirichlet allocation is performed that highlights the main reasons behind the reluctance to vaccinate. The proposed approach can be useful in the context of the campaigns related to COVID-19 vaccination as it provides insights related to the public opinion and can be useful in creating communication messages to support the vaccination campaign.
Growth Patterns and Developmental Changes of Backfat Thickness in Okinawa Agu Gilts

: This study clarified the growth patterns and developmental changes of the backfat thickness (BF) of Okinawa Agu gilts regarding their management. Five nonlinear growth models (Logistic, Gompertz, von Bertalanffy, Richards, and Janoschek) were used to describe growth patterns. Weekly, body weight (BW) data from birth to 34 weeks of age were collected. BF at the P2 position from 4 to 34 weeks of age was recorded every 4–5 weeks. Among 23 gilts pigs, 14 were Agu pigs, and nine were Landrace pigs. Animals were allowed fed ad libitum to 16 weeks of age and then reared under restricted feeding (1.3 kg/day for Agu gilts : 2.5 kg/day for Landrace gilts) to 34 weeks of age. Comparison among the five models revealed that the Richards model was the best fit for the growth data based on adjusted R-square (AdjR 2 ) and Akaikeʼs information criterion (AIC) for both breeds. The Agu gilts showed smaller mature BW, early maturing rate, and earlier weeks of age at the inflection point than Landrace gilts. BF development in Agu gilts was rapid during 4–16 weeks of age under ad libitum feeding but was suppressed after 16 weeks of age under restricted feeding. The breed differences of BF were observed from 8 weeks of age, and Agu gilts had thicker BF than Landrace gilts.
Wow, this chilli is hot! Interjections in student grammars of English: a lexical category that is not there.

The paper examines how interjections have been treated in linguistic literature; on what grounds they have been separated from pure response cries; and what their relation is to iconic (onomatopoeic) vocabulary items. Second, the paper examines various English grammars intended for university level students, especially in second language contexts, to see how their treatment of interjections reflects what is said in linguistic literature. It will be shown that most such grammars ignore interjections almost entirely, which means student learners have very little change of learning about such vocabulary items only based on their grammar books.
Emerging technologies in the field of thermometry

The past decade saw the emergence of new temperature sensors that have the potential to disrupt a century-old measurement infrastructure based on resistance thermometry. In this review we present an overview of emerging technologies that are either in the earliest stages of metrological assessment or in the earliest stages of commercial development and thus merit further consideration by the measurement community. The following emerging technologies are reviewed: Johnson noise thermometry, optical refractive-index gas thermometry, Doppler line broadening thermometry, optomechanical thermometry, fiber-coupled phosphor thermometry, fiber-optic thermometry based on Rayleigh, Brillouin and Raman scattering, fiber-Bragg-grating thermometry, Bragg-waveguide-grating thermometry, ring-resonator thermometry, and photonic-crystal-cavity thermometry. For each emerging technology, we explain the working principle, highlight the best known performance, list advantages and drawbacks of the new temperature sensor and present possibilities for future developments.
Rapid Determination of RNA Modifications in Consensus Motifs by Nuclease Protection with Ion-Tagged Oligonucleotide Probes and Matrix-Assisted Laser Desorption Ionization Mass Spectrometry

The reversible and substoichiometric modification of RNA has recently emerged as an additional layer of translational regulation in normal biological function and disease. Modifications are often enzymatically deposited in and removed from short (~5 nt) consensus motif sequences to carefully control the translational output of the cell. Although characterization of modification occupancy at consensus motifs can be accomplished using RNA sequencing methods, these approaches are generally time-consuming and do not directly detect post-transcriptional modifications. Here, we present a nuclease protection assay coupled with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) to rapidly characterize modifications in consensus motifs, such as GGACU, which frequently harbor N6-methyladenosine (m6A). While conventional nuclease protection methods rely on long (~30 nt) oligonucleotide probes that preclude the global assessment of consensus motif modification stoichiometry, we investigated a series of ion-tagged oligonucleotide (ITO) probes and found that a benzylimidazolium-functionalized ITO (ABzIM-ITO) conferred significantly improved nuclease resistance for GGACU targets. After optimizing the conditions of the nuclease protection assay, we applied the ITO and MALDI-MS-based method for determining the stoichiometry of GG(m6A)CU and GGACU in RNA mixtures. Overall, the ITO-based nuclease protection and MALDI-MS method constitutes a rapid and promising approach for determining modification stoichiometries of consensus motifs.