Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Impact of Ampelopsis Grossedentata Flavonoids on Growth Performance, Ruminal Microbiota, and Plasma Physiology and Biochemistry of Kids

Simple Summary In the face of the challenge posed by antibiotic prohibition, the identification of sustainable, eco-friendly alternatives to antibiotics is important. Ampelopsis grossedentata flavonoids, a plant-based extract, have high antioxidant and anti-inflammatory activities provide a non-toxic and innocuous option for the extended application of additives. This study examined the viability of Ampelopsis grossedentata flavonoids as a potential substitute for antibiotics. The results showed that supplementation of Ampelopsis grossedentata flavonoids in the diet exhibited the capacity to enhance rumen microbial diversity and immune competence, thereby fostering improved growth performance among weaned kids. Consequently, this study provides an important reference for the future development of Ampelopsis grossedentata flavonoids as a new environmentally friendly additive. Abstract This study was conducted to evaluate the influences of supplementing Ampelopsis grossedentata flavonoids (AGF) on the rumen bacterial microbiome, plasma physiology and biochemistry, and growth performance of goats. Twenty-four Nubian kids were randomly allocated to three dietary treatments: the control (CON, basal diet), the 1.0 g/kg AGF treatment (AGF), and the 12.5 mg/kg monensin treatment (MN). This trial consisted of 10 days for adaptation and 90 days for data and sample collection. The results reveal that Bacteroidetes, Firmicutes, and Proteobacteria are the dominant phyla in kids’ rumen. Compared with the CON group, the alpha diversity in the MN and AGF groups significantly increased (p < 0.01). Beta-diversity shows that rumen microbial composition is more similar in the MN and AGF groups. LEfSe analysis shows that Prevotella_1 in the AGF group were significantly higher than those in the MN and CON group. The high-density lipoprotein cholesterol and glucose levels in the AGF group were significantly higher than those in the CON group (p < 0.05), whereas the low-density lipoprotein cholesterol, glutamic-pyruvic transaminase, and alkaline phosphatase levels exhibited the opposite trend. The average daily gains in the AGF and MN groups significantly increased, while the feed-to-gain ratios were significantly decreased (p < 0.05). The results suggest that adding AGF to the diet improves microbial composition and has important implications for studying juvenile livestock growth and improving economic benefits.
Biochemical Alterations in Triticale Seedlings Pretreated with Selective Herbicide and Subjected to Drought or Waterlogging Stress

Waterlogging and drought disrupt crop development and productivity. Triticale is known to be relatively tolerant to different stress factors. In natural conditions, plants are rather subjected to multiple environmental factors. Serrate® (Syngenta) is a systemic selective herbicide suitable for cereal crops such as triticale and wheat to restrain annual grass and broadleaf weeds. Triticale (×Triticosecale Wittm., cv. Rozhen) was grown as soil culture under controlled conditions. Seventeen-day-old plantlets were leaf sprayed with Serrate®. The water stress (drought or waterlogging) was applied after 72 h for 7 days, and then the seedlings were left for recovery. The herbicide does not provoke sharp alterations in the antioxidant state (stress markers level, and antioxidant and xenobiotic-detoxifying enzymes activity). The water stresses and combined treatments enhanced significantly the content of stress markers (malondialdehyde, proline, hydrogen peroxide), non-enzymatic (total phenolics and thiol groups-containing compounds), and enzymatic (activities of superoxide dismutase, catalase, guaiacol peroxidase, glutathione reductase) antioxidants, and xenobiotic-detoxifying enzymes (activities of glutathione S-transferase, NADPH:cytochrome P450 reductase, NADH:cytochrome b5 reductase). These effects were more severely expressed after the drought stress, suggesting that this cultivar is more tolerant to waterlogging than to drought stress.
Accruals, real earnings management, and CEO demographic attributes in emerging markets: Does concentration of family ownership count?

Abstract The present study utilizes agency theory and the upper echelons theory (UET) to investigate whether there is a moderating effect of family ownership concentration (FOWC) on the association between CEO demographic attributes and two forms of earnings management (EM), specifically accruals earnings management (AEM) and real earnings management (REM). Additionally, this study investigates whether CEO demographic attributes affect EM (AEM and REM) in Jordanian companies. The study sample includes 137 companies listed on the Amman Stock Exchange (ASE) from 2017 to 2021, with the banking and insurance sectors excluded, resulting in 685 company-year observations. To accomplish the study’s goals, feasible generalized least squares estimation (FGLS) regressions were applied. The findings indicate that CEO non-duality and age decrease REM and improve the quality of financial reporting (QFR). However, they indicate that CEO age increases AEM, and family ownership concentration enhances the power of older CEOs to engage in AEM and affects QFR. The study finds that a CEO with high education does not affect EM but that the presence of family ownership increases a CEO’s capacity with high education to reduce EM (AEM and REM) and generate trustworthy financial reports. However, we don’t find any relationship between CEO gender and EM (AEM &REM), but family ownership increases male CEOs’ power to engage in AEM. In addition, the outcome shows that family ownership concentration interacts with CEO non-duality and leads to restricting REM and engagement in AEM practices. This study is among the earliest attempts to examine how family ownership concentration affects the connection between CEO demographic attributes and EM, using both types of EM (AEM and REM). Thus, the results of this study are significant in providing meaningful insights for various stakeholders, such as management, investors, and owners, about the QFR and EM practices in emerging markets. Also, the outcomes of this study can contribute significantly to the existing literature on CEO characteristics, family ownership concentration, and EM practices. The findings can be used by the board of directors, policymakers, and regulators to re-evaluate the selection criteria for CEOs based on specific characteristics that can affect QFR. However, the results may not be applicable to markets that are characterized by dispersed ownership structures, where family ownership is not a dominant factor.
Evaluation of Online Learning in Vocational High School Major in Accounting and Financial Institution: Kirkpatrick’s Model

Online learning during the pandemic of COVID-19 in accounting and financial institution major of Public Vocational High School 1 of Boyolangu has not been evaluated as yet, which makes the effect and result of the learning still unknown; therefore, this research aimed to evaluate the online learning established at the school. The model of evaluation adopted in this research was Kirkpatrick’s two levels of evaluation: reaction and learning. The purposes are to measure students’ satisfaction with the online learning and understanding of subject materials given during the online learning. The data in this research were collected through questionnaires. The research found that students on the whole felt satisfied with the establishment of online learning during the pandemic for at least two reasons: students began to feel comfort and used to online learning and the information technology skills of both teachers and students improved by virtue of online learning. However, there were some problems which impaired the effectiveness of online learning, including limited internet quota and poor internet connection. Additionally, students had difficulty completing practical assignments because some of them did not possess laptops, and sometimes teachers had not given them any explanation of the subject materials before
Current State and Advanced Architectures of Doherty Power Amplifiers

Power amplifiers are critical components of wireless communication systems, providing the necessary power to transmit signals over long distances. Among various power amplifier solutions, the Dougherty power amplifier (DPA) remains a popular choice due to its high efficiency, speed, and power combination. However, conventional DPAs suffer from limited bandwidth and linearity, which have been major challenges in contemporary DPA design. This paper discusses the status, challenges, and potential solutions for improving the bandwidth and linearity of the DPAs. The limited bandwidth of conventional DPAs has been a challenge for their use in wireless data communication. Furthermore, concerning DPA linearity, this paper discusses the importance of linearity for modern wireless communication and potential DPA linearization techniques. The paper proposes several emerging DPA architectures, namely the Asymmetric Dougherty Power Amplifier, Multi-Stage Dougherty Power Amplifier, and Digital Dougherty Power Amplifier. The findings of this paper provide insights into the current status and future development of DPA technology, particularly in terms of bandwidth and linearity.
Clinical and Molecular Characterization of Neural Tube Defects with Special Emphasis on MTHFR Gene

Background: Studies have highlighted that MTHFR plays a crucial and essential role in formation of neural tube in early fetal life, and thus occurrence of any mutation to this gene will eventually affected the normal process of neural tube formation leading to defects and the severity of it depends on type of mutation and its impact on clinical picture of patient having this congenital anomalies. Objectives of the study: To describe demographic data and clinical presentation of Sudanese patients with neural tube defect. To characterize MTHFR gene in Sudanese patients with neural tube defects. To correlate clinical presentation with molecular findings of MEHFR gene. Material and methods: This is a cross - sectional study that had been performed at National Center of Neurological Sciences (NCNS) during June 2016 to October 2019. The study included clinical data and peripheral blood sample taken from all neural tube defects patients diagnosed at NCNS, during the above mention period. The study was conducted in accordance with the guidelines of the local ethical committee. Blood samples were obtained from 50 neural tube defect patients. Blood samples were taken in sterile containers that contained EDTA and processed for DNA extraction. The extracted DNA was amplified by PCR for detection of MTHFR gene
Toward a Common Ground for Gravity and Optics

A long enough period of observation of the Sun’s gravitational dragging effects by using a modified Cavendish’s balance output of experimental evidence shows new patterns. Those patterns can be explained assuming that the Sun has a torus with rotation, precession, and nutation. This purpose of this paper is to introduce the frequencies of all those movements. The torus’s rotational period can be used to explain the Sun’s magnetic pole reversal. Utilizing a modified Cavendish’s balance showed an output of dragging forces stronger than the attraction between the gravitational masses. This tool afforded this research a new experimental possibility to a more precise determination of the Universal Gravitational Constant Big G. Moreover, the dragging forces directly affect any volume of mass, which includes the atmosphere. This paper shows a correlation between the Sun’s dragging peaks and density of the air squared. The aforementioned correlation and the inverse cubic relation with the distance to the Sun are common for the dragging and tide forces providing the possibility that tidal forces are also a gravitational dragging consequence. The last 2017 total Solar eclipse created a new temporal reaction on the modified Cavendish’s balance. That temporal pattern looks as the spatial pattern created by an opaque disk. This similarity allows the researcher to calculate that the dragging forces are transmitted by photons with spatial periodicity of value λ = 6.1 km.
Pengenalan Jalan Berlubang Berbasis Vision Menggunakan Pyramid Histogram Of Oriented Gradients

Lubang, sejenis kerusakan jalan, dapat merusak kendaraan dan berdampak negatif pada keamanan mengemudi dari pengemudi. Bahkan, dalam kasus yang parah dapat menyebabkan kecelakaan lalu lintas. Manajemen jalan berlubang yang efisien dan preventif di lingkungan jalan yang kompleks memainkan peran penting dalam mengamankan keselamatan pengemudi. Hal ini juga diharapkan dapat memberikan kontribusi terhadap pencegahan kecelakaan lalu lintas dan kelancaran arus lalu lintas. Di masa lalu, deteksi lubang terutama dilakukan melalui inspeksi visual oleh ahli manusia. Baru-baru ini, metode deteksi lubang otomatis menerapkan berbagai teknologi yang menyatukan teknologi dasar seperti sensor dan pemrosesan sinyal. Pada artikel ini, metode berbasis pengolahan citra dan pembelajaran mesin diaplikasikan untuk mengenali lubang di jalan. Penelitian ini menghasilkan model dari bentuk lubang dengan memanfaatkan ciri bentuk yang diekstraksi dari Pyramid Histogram of Oriented Gradients (PHOG). Untuk metode klasifikasi, peneliti menggunakan Support Vector Machine (SVM) dengan hasil terbaik diperoleh pada penggunaan kernel polynomial. Sistem pengenalan jalan berlubang yang diusulkan mampu menunjukkan hasil performa yang sangat baik, yaitu akurasi sebesar 94,45%, precision sebesar 96,13% recall sebesar 95,77%, dan F1-score sebesar 95,95%. AbstractPotholes on roads can damage vehicles and endanger drivers, potentially leading to accidents. Preventative management of potholes is crucial for driver safety and efficient traffic flow. Traditional methods of pothole detection relied on visual inspection, but automatic methods have been developed using sensors and signal processing. This article presents a new approach using image processing and machine learning to identify potholes on roads. The proposed system uses shape features extracted from Pyramid Histogram of Oriented Gradients (PHOG) and a Support Vector Machine (SVM) with polynomial kernels for classification. The system achieves high accuracy, precision, recall, and F1-Score, with an accuracy of 94.45%, precision of 96.130%, recall of 95.77%, and F1-Score of 95.950%.
Explicit uniform bounds on integrals of Bessel functions and trace theorems for Fourier transforms

Explicit and partly sharp estimates are given of integrals over the square of Bessel functions with an integrable weight which can be singular at the origin. They are uniform with respect to the order of the Bessel functions and provide explicit bounds for some smoothing estimates as well as for the L2 restrictions of Fourier transforms onto spheres in Rn which are independent of the radius of the sphere. For more special weights these restrictions are shown to be Hölder continuous with a Hölder constant having this independence as well. To illustrate the use of these results a uniform resolvent estimate of the free Dirac operator with mass m≥0 in dimensions n≥2 is derived.
Strategies for parameter extraction of the time constant distribution of time-dependent variability models for nanometer-scale devices

Time-dependent variability phenomena are stochastic and discrete for nanometer-scale technologies, and, hence, must be statistically characterized. These phenomena are attributed to the emission and capture of charges in device defects. This paper explores two different strategies to extract, from experimental data, the distribution parameters of the time constants of the defects. It delves into the accuracy of each strategy, showing how the extraction strategy can have a huge impact on the accuracy and the amount of characterization data required, and, therefore, on the amount of (expensive) characterization time in the lab.
A 23.5–32.5GHz, 17dBm PSAT and 37.5% PAE Power Amplifier Synthesized Using an Automated Design Methodology

The design of power amplifiers (PAs) in the millimeter-wave (mm-Wave) regime is remarkably complex. In order to meet the linearity and efficiency requirements for 5G or 6G operation, designers have been struggling to efficiently design such PAs in a reasonable time. Hence, in the past few years, a growing interest has emerged in developing optimization-based methodologies which can automatize the design of mm-Wave circuits. In this paper, a fully-automated, process, voltage and temperature (PVT), and layout-aware optimization-based design strategy is applied to the design of a mm-Wave PA. It accurately models the transformers in the PA using machine-learning techniques and exploits a multi-objective optimization algorithm, achieving a Pareto optimal front (POF) containing hundreds of PAs over the landscape of the performance trade-offs. By leveraging the layout in the loop, it outputs a set of design solutions that have their GDSII readily available and ready to fabricate without the need for further designer intervention.
Compact Optical Add-Drop De-Multiplexers with Cascaded Micro-Ring Resonators on SOI

A four-channel integrated optical wavelength de-multiplexer is experimentally illustrated on a silicon-on-insulator (SOI) substrate. With the aid of cascaded micro-ring resonators, the whole performance of the wavelength de-multiplexer is improved, such as 3 dB bandwidth and channel crosstalk. Based on the transform matrix theory, a four-channel wavelength de-multiplexer with average channel spacing 4.5±0.5 nm (3 dB bandwidth ~ 2 ± 0.5 nm) is demonstrated at telecommunication bands. For each channel, the extinction at the adjacent channel is below −39 dB and the out-of-band rejection ratio is up to 40 dB. The channel dropping loss is below 5 dB in the five FSR spectral response periods (near 100 nm).
The Bacterial Microbiota of Artisanal Cheeses from the Northern Caucasus

In this study, we used culture-independent analysis based on 16S rRNA gene amplicons and metagenomics to explore in depth the microbial communities and their metabolic capabilities of artisanal brine cheeses made in the North Caucasus. Additionally, analysis of organic acid profiles was carried out for cheese characterization. Twelve cheese samples (designated as 05SR–16SR) from various artisanal producers were taken from five different villages located in Northern Ossetia–Alania (Russia). These cheeses were made using methods based on cultural traditions inherited from previous generations and prepared using a relatively uncontrolled fermentation process. The microbial diversity of Caucasus artisanal cheeses was studied for the first time. The results showed a diverse composition in all cheeses, with Bacillota (synonym Firmicutes) (9.1–99.3%) or Pseudomonadota (synonym Proteobacteria) (0.2–89.2%) prevalence. The microbial communities of the majority of the studied cheeses were dominated by lactic acid bacteria (LAB) genera, like Lactococcus (10.3–77.1% in 07SR, 09SR, 10SR, 11SR, 13SR, 15SR, 16SR), Lactobacillus (54.6% in 09SR), Streptococcus (13.9–93.9% in 11SR, 13SR, 14SR, 15SR), Lactiplantibacillus (13.4–30.6% in 16SR and 07SR) and Lentilactobacillus (5.9–14.2% in 09SR, 10SR and 13SR). Halophilic lactic acid bacteria belonging to the Tetragenococcus genus accounted for 7.9–18.6% in 05SR and 06SR microbiomes. A distinctive feature of Ossetia cheese microbiomes was the large variety of halophilic proteobacteria, and in some cheeses they prevailed, e.g., Chromohalobacter (63–76.5% in 05SR and 06SR), Psychrobacter (10–47.1% in 08SR, 11SR, 12SR), Halomonas (2.9–33.5% in 06SR, 08SR, 11SR and 12SR), Marinobacter (41.9% in 12SR) or Idiomarina (2.9–14.4% in 06SR, 08SR and 11SR samples). Analysis of the genomes assembled from metagenomes of three cheeses with different bacterial composition revealed the presence of genes encoding a variety of enzymes, involved in milk sugar, proteins and lipid metabolism in genomes affiliated with LAB, as well as genes responsible for beneficial bioamine and bacteriocin synthesis. Also, most of the LAB did not contain antibiotic resistance genes, which makes them potential probiotics, so highly demanded nowadays. Analysis of the genomes related to halophilic proteobacteria revealed that they are not involved in milk fermentation; however, the search for “useful” genes responsible for the synthesis of beneficial products/metabolites was partially positive. In addition, it has been shown that some halophiles may be involved in the synthesis of inappropriate bioactive components. The results obtained by culture-independent analyses confirm the importance of using such techniques both to clarify the quality and health-promoting properties of the product, and to look for probiotic strains with specified unique properties. This study has shown that traditional dairy foods may be a source of such beneficial strains.
Robust Laplace Periodogram and Its Asymptotic Properties for Frequency Estimation of 2-Dimensional Superimposed Sinusoidal Model

In this paper, we consider the problem of robust estimation of frequencies of a 2-dimensional superimposed sinusoidal model. We propose a 2-dimensional sequential Laplace periodogram for the frequency estimation problem and derive it’s asymptotic distribution. The proposed approach and the derived asymptotic results extend the Laplace periodogram approach of Li [1,2] to 2-dimensional sinusoidal models. Empirical studies illustrate the usefulness and advantages of the proposed approach as compared to usual periodogram approach. Introduction Estimation of the frequencies of superimposed sinusoidal models is a fundamental problem in statistical signal processing. Periodogram based approach for estimation of frequencies associated with 1-dimensional and 2-dimensional models is widely used in the literature of signal processing. The formulation of robust periodograms necessitates from the fact that sinusoids combined with heavy tailed noises or data combined with extreme outliers cannot be accurately modeled by ordinary periodogram. It is a well known fact that least absolute deviation (LAD) estimators give more robust estimates than the least squares estimators (LSE) by taking into account the presence of outliers present in the data or heavy tailed nature of noise. Recently, Li [1,2] introduced the concept of Laplace Periodogram for frequency estimation of 1-dimensional sinusoidal model and studied it’s asymptotic statistical properties. The purpose of the present paper is to extend the Laplace periodogram concept to the 2-dimensional frequency estimation problem and establish it’s theoretical asymptotic properties. In this paper, we consider the problem of robust frequency estimation of the following 2-dimensional superimposed sinusoidal model: (1) A and B are unknown conditionally linear amplitude parameters. ( , ) (0, ) (0, ) λ μ π π ∈ × are unknown frequencies. { } ts ε is a sequence of additive noise random variables. Given 11 21 { , ,. , } mn y y y , the problem is to estimate the unknown parameters. For a given 11 21 { , ,. , } mn y y y and frequency parameters ( , ) (0, ) (0, ) λ μ π π ∈ × the ordinary periodogram is defined by 2 =1 =1 1 ( , ) = ( ( )) n m mn ts s t I y exp i t s mn λ μ λ μ + ∑ ∑ If 2 = k m π λ and 2 = l n π μ for some integers k and l , then it can be shown that 2 ( , ) = 4 mn mn mn I λ μ β where mn β is the LSE solution i.e. 2 2 =1 =1 = ( , ) min n m T R mn ts ts s t arg y x β β λ μ β ∈ − ∑ ∑ . The ordinary periodogram however fails to resolve 2-d frequencies in case of heavy tailed noise (Figure 1 and Figure2).