Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolomics Integrated with HPLC–MS Reveals the Crucial Antioxidant Compounds of Muscadine Wine

Wine is a kind of beverage with a variety of compounds beneficial to human health, which makes it popular all over the world and it contributes importantly to economics. The excessive oxidation of wine has always been a major problem in wine production and storage. Unlike traditional wines which are made from Eurasian grapes, wines made from muscadine grapes (Muscadinia rotundifolia Michx.) can maintain their sensory qualities under natural oxidation conditions for relatively long periods of time despite the insight mechanisms still being unclear. In this study, two muscadine wines, Carlos (CAL) and Noble (NOB), and two traditional wines, Chardonnay (CH) and Marselan (MAS), were chosen for comparison of their compositional alteration during oxidation, in order to analyze the principal components contributing to the antioxidant characteristics of muscadine wines. The DPPH, ORAC, color intensity, and total phenolic content changes during the natural oxidation process were analyzed. Six core significantly changed metabolites (SCMs, avicularin, beta-lactose, delphinidin-3-O-glucoside, ellagic acid, myricetin, and 4-methylcatechol [p < 0.05]) related to the oxidation process were determined. In addition, HPLC–MS was also used to identify pyrogallol which is a unique antioxidant compound in muscadine wine. The present work aims to reveal the crucial antioxidant compounds of muscadine wine and provide valuable information and a new platform for future research on wine oxidation.
Thermodynamic Topological Classifications of Well-Known Black Holes

In this work, we investigate the thermodynamic properties of black holes (BHs) that have non-trivial topological features in their phase diagrams. We consider three different models of BHs: (1) a class of BHs in dRGT massive gravity, which adds a mass term to general relativity; (2) a class of BHs in 5D Yang-Mills massive gravity, which combines dRGT massive gravity with a non-Abelian gauge field; and (3) a D-dimensional RN-AdS BH surrounded by Quintessence and a cloud of strings, which are strange forms of matter that change the thermodynamics of the BH. Our goal is to find the critical points of these BHs, which provide the location of first-order phase transitions and figure out their corresponding topological charges. Topological charges are numbers that show how complicated the BH topology is. Then, we look at these BHs as topological defects in the thermodynamic domain, which is the space of thermodynamic variables like pressure and temperature. We calculate winding numbers to analyze topology on a global and local scale at these defects, which are integers that indicate how many times a curve encircling the defect wraps around the origin. Our analysis reveals that the total topological charge is either equal to 0 or 1 for all models, meaning that the BHs have either a trivial or simple topology. In some cases, we see that the BH's topology belongs to a different thermodynamic topological class. This means that the BHs can go through topological phase transitions.
GreatSplicing: A Semantically Rich Splicing Dataset

In existing splicing forgery datasets, the insufficient semantic varieties of spliced regions cause a problem that trained detection models overfit semantic features rather than splicing traces. Meanwhile, because of the absence of a reasonable dataset, different detection methods proposed cannot reach a consensus on experimental settings. To address these urgent issues, GreatSplicing, a manually created splicing dataset with a considerable amount and high quality, is proposed in this paper. GreatSplicing comprises 5,000 spliced images and covers spliced regions with 335 distinct semantic categories, allowing neural networks to grasp splicing traces better. Extensive experiments demonstrate that models trained on GreatSplicing exhibit minimal misidentification rates and superior cross-dataset detection capabilities compared to existing datasets. Furthermore, GreatSplicing is available for all research purposes and can be downloaded from www.greatsplicing. net.
On robust Hurwitz polynomials

In this note, Kharitonov's theorem on robust Hurwitz polynomials is simplified for low-order polynomials. Specifically, for n = 3, 4 , and 5, the number of polynomials required to check robust stability is one, two, and three, respectively, instead of four. Furthermore, it is shown that for n \geq 6 , the number of polynomials for robust stability checking is necessarily four, thus further simplification is not possible. The same simplifications arise in robust Schur polynomials by using the bilinear transformation. Applications of these simplifications to two-dimensional polynomials as well as to robustness for single parameters are indicated.
Current flow in pulsar magnetospheres

When particle flow is mainly outward through the light cylinder of a rotating pulsar magnetosphere, the resulting current flow leads to very large potential drops along field lines wherever $Omega$xB vanishes (as suggested by Holloway). These occur no matter what the sign of the charge above the magnetic polar cap. For fast pulsars such a gap potential drop is limited by pair production discharge. In such models current flow into and out of the pulsar cap is always carried by particles of the same sign (-$Omega$xB) unless the magnetic polar axis is nearly perpendicular to the spin axis. For the Crab pulsar, the gap potential at breakdown is approx.10$sup 14$ V, and the resulting radiation is mainly hard X-rays and $gamma$-rays up to 10$sup 11$ eV. The latter are expected to be emitted almost perpendicular to the magnetic axis and probably, therefore, should be observed almost 90degree earlier in phase than much lower energy pulsar emission. (AIP)
Magnetoelastic tetragonal-to-orthorhombic distortion in ErNi{sub 2}B{sub 2}C

We have performed synchrotron x-ray scattering experiments on single crystals of ErNi{sub 2}B{sub 2}C. Below 6.3 K, the (2,0,0) Bragg peak splits, indicating a tetragonal-to-orthorhombic distortion. The mismatch between the a and b lattice parameters appears coincident with the onset of long-range antiferromagnetic order and increases continuously with decreasing temperature, reaching a value of a/b{minus}1{approx}0.2{percent} at 3.7 K. {copyright} {ital 1997} {ital The American Physical Society}
Survey Article: Self-adjoint ordinary differential operators and their spectrum

We survey the theory of ordinary selfadjoint differential operators in Hilbert space and their spectrum. Such an operator is generated by a symmetric differential expression and a boundary condition. We discuss the very general modern theory of these symmetric expressions which enlarges the class of these expressions by many dimensions and eliminates the smoothness assumptions required in the classical case as given, e.g., in the celebrated books by Coddington and Levinson and Dunford and Schwartz. The boundary conditions are characterized in terms of squareintegrable solutions for a real value of the spectral parameter, and this characterization is used to obtain information about the spectrum. Many of these characterizations are quite recent and widely scattered in the literature, some are new. A comprehensive review of the deficiency index (which determines the number of independent boundary conditions required in the singular case) is also given for an expression M and for its powers. Using the modern theory mentioned above, these powers can be constructed without any smoothness conditions on the coefficients.
Histopathological Growth Pattern in Colorectal Liver Metastasis and The Tumor Immune Microenvironment

Simple Summary Liver metastases occur in almost half of patients with colorectal cancer, either at the time of presentation (synchronous) or eventually as a metachronous recurrence of the disease. Approximately one quarter of patients with metastasis to the liver receive surgical resection with curative intent but recurrence is frequent and related to tumor biology. Understanding cancer biology is crucial to improve outcomes. In an attempt at unveiling novel targets for treatment, this paper investigates and summarizes current knowledge of the distinct growth patterns of tumor cells at the interface with normal liver tissue, defined as the histopathological growth pattern, and their interaction with immune cells in the microenvironment. Abstract Almost half of all patients with colorectal cancer present with or eventually develop metastasis, most frequently in the liver. Understanding the histopathological growth patterns and tumor immune microenvironment of colorectal liver metastases may help determine treatment strategies and assess prognosis. A literature search was conducted to gather information on cancer biology, histopathological growth patterns, and the tumor immune microenvironment in colorectal liver metastases, including their mechanisms and their impact on clinical outcomes. A first consensus on histopathological growth patterns emerged in 2017, identifying five growth patterns. Later studies found benefits from a two-tier system, desmoplastic and non-desmoplastic, incorporated into the updated 2022 consensus. Furthermore, the tumor immune microenvironment shows additional characteristic features with relevance to cancer biology. This includes density of T-cells (CD8+), expression of claudin-2, presence of vessel co-option versus angiogenesis, as well as several other factors. The relation between histopathological growth patterns and the tumor immune microenvironment delineates distinct subtypes of cancer biology. The distinct subtypes are found to correlate with risk of metastasis or relapse, and hence to clinical outcome and long-term survival in each patient. In order to optimize personalized and precision therapy for patients with colorectal liver metastases, further investigation into the mechanisms of cancer biology and their translational aspects to novel treatment targets is warranted.
Characterization of Bacillus thuringiensis from Cotton Fields and its Effectiveness against Spodoptera litura

Cotton is a cash crop of many countries as it serves as a source of fiber, edible oil, and seedcake. It is grown in a diverse range of environment. Bacillus thuringiensis (Bt) is a gram positive bacterium found in different habitats but mostly found in soil. This bacterium produces endotoxin which is harmful for various insects. Numerous crystal-forming strains of Bt exist in nature, but not all of them are efficient against insect pests. Bt cotton is prevalent internationally because of less insect attack. The key objective of this research was to analyze different Bacillus thuringiensis isolates residing in soil of different cotton fields of Multan and Bahawalpur districts and to identify them on the basis of morphology. To attain this, different soil samples were collected from Multan (Gup wala, Mosey Wala, Taloki Wala, Hafiz Wala, Choudary Wala, Basti Mangla Mari, Sharkha Wala, Lawain Wala, Ghulamo Wala) and Bahawalpur district (Basti Deewan Wali, Check No 8, Basti Tariqabad, Basti Khaji Wala, Basti Khandin, Basti Rammo Wali, Sultanpur, Khurampur, Jahanpur). About 178 colonies of different bacteria from eighteen soil samples appeared on Nutrient Agar plates. The screening of colonies based on morphology yielded 18 colonies of Bt. We performed endo-toxin production experiment and confirmed the presence of parasporal crystals in identified B. thuringiensis colonies. Colony forming units of soil samples collected from Multan and Bahawalpur represented statistically significant results. Based on morphology, eight colonies of B. thuringiensis were confirmed out of eighteen colonies. Results of the current study revealed that out of 18 isolates, 8 bacterial isolates that were grown on the media had an increased elevation, a round, white, slimy morphology, and smooth edges. Toxicity test for resistance to cotton leaf worm second instar larvae revealed that two strains (BtS2, BtS7) of B. thuringiensis were toxic and showed 39.25% mortality. This study will help to identify the local Bt isolates that can be used for the indigenous insect pest control.
Determinants of Muslim Millennials' Intention Towards Savings Sukuk

Savings Sukuk is one of the sharia investment products issued by the Indonesian Government. Investors from the millennials generation always dominate Savings Sukuk sales, although it is a new investment instrument in Indonesia. Therefore, we interest in examining the intention towards Savings Sukuk more deeply. In particular, this study analyzes the effect of religiosity, product knowledge, and pricing on Muslim millennials' intention toward Savings Sukuk in Indonesia. This study used a quantitative approach, and the data collected was analyzed by Partial Least Square – Structural Equation Modeling (PLS-SEM). Purposive sampling was used to get the required sample. Respondents in this study were Muslim millennials in Indonesia and were not limited by region. There are at least 138 respondents who participated in the survey. The results showed that product knowledge and pricing influenced Muslim millennials' intention toward Savings Sukuk. In contrast, religiosity does not affect Muslim millennials' intention toward Savings Sukuk in Indonesia.
Oxidative Stability of Nano-Encapsulated Candlenut Oil

Candlenut has a lot of potential pharmacological benefits including in hair care, in treating skin problems such as psoriasis, and in its use as an emollient. However, the high unsaturated fatty acid content of candlenut oil causes it to be easily degraded by oxidation due to exposure to air, light, and humidity. Nanoencapsulations were found to be an alternative in protecting the materials from degradation. The purpose of this study was to investigate the effect of polymer-based nanoencapsulations on the oxidative stability of candlenut oil. Polyvinyl alcohol (PVA) was used as a polymer wall material. A lower peroxide value indicates better oil stability against oxidation. Results showed that nano-encapsulated candlenut oil has a significantly lower average peroxide value of 0.41 meq/100g over 35 days storage time, compared to 3.8 meq/100g in pure candlenut oil. Furthermore, based on its physical characterization, it was found that the reduction of particle size with the optimal size of 172±12 nm was achieved by increasing the amount of PVA. A well-chosen and well-calculated amount of polymer material, therefore, plays an important role to obtain optimal nano-encapsulated candlenut oil. Keywords: nanoencapsulation, candlenut oil, oxidative stability, polymeric materials
Magnetoelectric effect in crystallographically textured BaTiO3 films deposited on ferromagnetic metallic glass foils

We demonstrate a significant control of the polarization response under an applied magnetic field for a magnetoelectric (ME) heterostructure. This structure was comprised of a 2 μm thick ferroelectric BaTiO3 (BTO) film deposited on flexible ferromagnetic metallic glass foil (25 μm thick). Au was used as a buffer layer to control BTO growth orientation, and to protect the metallic glass from oxidation. x-ray diffraction and scanning electron microscopy demonstrated the successful growth of well-crystallized BTO films with a high degree of (111) orientation on the amorphous metallic glass foils. Well-defined polarization (P-E) and magnetization (M-H) hysteresis loops confirmed the coexistence of ferroelectric and ferromagnetic properties. A ME voltage coefficient of about ∼60 mV/cm Oe was measured.
Refraction effects on the Galileo probe telemetry carrier frequency

As the Galileo probe Relay Radio Link (RRL) signal propagates outward through the Jovian atmosphere, the atmosphere will manifest itself in two ways. First, the geometric path length of the signal is increased, resulting in a small change of the RRL signal departure angle from the probe (transmitter). Secondly, the velocity of the signal is decreased. For a spherical, static atmosphere with a known profile of refractivity versus altitude the effects of refraction on the RRL frequency can be found using a variation of standard ray-tracing techniques, whereby the ray departure angle is found by an iterative process. From the dispersive characteristics of a mixture of hydrogen and helium with trace amounts of methane and ammonia a simple model of the Jovian atmosphere is constructed assuming spherical symmetry and uniform mixing. The contribution to the RRL Doppler frequency arising from refraction is calculated, and its effect on the Doppler wind measurements is discussed.
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising

Although supervised image denoising networks have shown remarkable performance on synthesized noisy images, they often fail in practice due to the difference between real and synthesized noise. Since clean-noisy image pairs from the real world are extremely costly to gather, self-supervised learning, which utilizes noisy input itself as a target, has been studied. To prevent a self-supervised denoising model from learning identical mapping, each output pixel should not be influenced by its corresponding input pixel; This requirement is known as J-invariance. Blind-spot networks (BSNs) have been a prevalent choice to ensure J-invariance in self-supervised image denoising. However, constructing variations of BSNs by injecting additional operations such as downsampling can expose blinded information, thereby violating J-invariance. Consequently, convolutions designed specifically for BSNs have been allowed only, limiting architectural flexibility. To overcome this limitation, we propose PUCA, a novel J-invariant U-Net architecture, for self-supervised denoising. PUCA leverages patch-unshuffle/shuffle to dramatically expand receptive fields while maintaining J-invariance and dilated attention blocks (DABs) for global context incorporation. Experimental results demonstrate that PUCA achieves state-of-the-art performance, outperforming existing methods in self-supervised image denoising.
Banks’ Balance-Sheet Costs, Monetary Policy, and the ON RRP

In June 2022, the Federal Reserve started reducing the size of its balance sheet, which had expanded to just under $9 trillion in response to the COVID-19 pandemic. However, whereas banks’ reserves at the Federal Reserve have decreased, the investment of money market funds (MMFs) at the Federal Reserve’s overnight reverse repo (ON RRP) facility has continued to increase, reaching $2.4 trillion in September 2022. In this paper, we causally identify the drivers of ON RRP take-up through a diff-in-diff approach. By exploiting a temporary change in the computation of banks’ Supplementary Leverage Ratio (SLR) implemented in 2020-21, we show that banks’ balance sheet costs incentivize them to push deposits toward MMFs and to reduce their overnight borrowing from MMFs, leading to an increase in MMF investment at the ON RRP. Furthermore, we show that monetary policy tightening, and Treasury bill scarcity are two additional factors contributing to the recent increase in ON RRP usage.
A new hybrid framework based on deep neural networks and JAYA optimization algorithm for feature selection using SVM applied to classification of acute lymphoblastic Leukaemia

ABSTRACT Identification of Acute lymphoblastic leukemia (ALL) in microscopic images is one of the most challenging tasks in medical image analysis. Despite a wide variety of image processing and deep learning techniques, the task of extracting features from ALL images and selecting the proper features from these redundant and high-dimensional feature space set, and then detecting ALL cells is still a complex issue. In this study, we present a new hybrid two-layer framework to construct an appropriate subset of features. In the first layer of the proposed method, image segmentation is implemented using an improved modified First-Spike-based approach integrated with a Gaussian function. Then a developed deep residual architecture is employed to extract the features. In the second layer, a powerful and reliable meta-heuristic algorithm known as the JAYA optimization algorithm is adopted for feature selection due to its computational efficiency. Finally, a support vector machine (SVM) is used to classify ALL images. To show the effectiveness of the proposed model, it is applied on microscopic images of blood samples from ALL images (ALL-IDB) and ISBI-2019 C-NMC dataset. The results show the superiority of the model to be an appropriate choice for future biomedical imaging tasks.
Identifying suicide ideation in mental health application posts: A random forest algorithm

Abstract The growing use of digitized mental health applications requires new reliable early screening tools to identify user suicide risk. We used a lexicon-based random forest machine learning algorithm to predict suicide ideation scores from 714 online community text posts from December 2019 to April 2020. We validated predicted scores against expert-rated suicide ideation scores. The algorithm-predicted scores offered high validity and a low error rate and correctly identified 95% of expert-rated high-risk suicide ideation posts. Our findings highlight a potential new method to detect suicidal ideation of digital mental health application users.
Synthesis of Data Obtained at Jicamarca, Peru, During the September 11, 1969, Eclipse

Continuous measurements of electron temperatures, electron concentrations, and vertical plasma drift were made at Jicamarca during the September 11, 1969, solar eclipse. Control measurements were made on September 13, 1969. Synthesis of the observed electron concentrations was made, using a model that solved the time-dependent electron-ion continuity equations. Ions O+, NO+, O2+, and N2+ were treated. Physical and chemical processes pertinent to the F region were considered in a realistic way. At noon, 300 km above Jicamarca, we obtained the values q = 290−3 sec−1 for the O+ production rate, β = 1.94 × 10−4 sec−1 for the loss coefficient, and H = 59 km for the atomic oxygen scale height. All large-scale features observed in the F2 region were synthesized by the model. This synthesis was not sensitive to a simultaneous 30% reduction of q and β
A monochromatic and high-power terahertz source tunable in the ranges of 2.7–38.4 and 58.2–3540 μm for variety of potential applications

Based on phase-matched collinear difference-frequency generation in a single GaSe crystal, continuously tunable and coherent radiation in the extremely wide ranges of 2.7–38.4 and 58.2–3540 μm has been achieved. This unique source has the additional advantages of high coherence (narrow linewidth) and simple alignment. The peak output power for the terahertz radiation reaches 209 W at the wavelength of 196 μm (1.53 THz), which corresponds to a power conversion efficiency of 0.055%. Moreover, the terahertz transmission spectra on DNA macromolecules and protein were directly measured, demonstrating some potential and important applications of this terahertz source.
Black holes, the generalized uncertainty principle and higher dimensions

We propose a new way in which black holes connect macrophysics and microphysics. The Generalized Uncertainty Principle suggests corrections to the Uncertainty Principle as the energy increases towards the Planck value. It also provides a natural transition between the expressions for the Compton wavelength below the Planck mass and the black hole event horizon size above it. This suggests corrections to the event horizon size as the black hole mass falls towards the Planck value, leading to the concept of a Generalized Event Horizon. Extrapolating this expression below the Planck mass suggests the existence of a new kind of black hole, whose size is of order its Compton wavelength. Recently it has been found that such a black hole solution is permitted by loop quantum gravity, its unusual properties deriving from the fact that it is hidden behind the throat of a wormhole. This has important implications for the formation and evaporation of black holes in the early Universe, especially if there are extra spatial dimensions.