Miracle-dz/UniFAR-FTUs huggingface dataset:
Altered Purinergic Signaling in Neurodevelopmental Disorders: Focus on P2 Receptors

With the umbrella term ‘neurodevelopmental disorders’ (NDDs) we refer to a plethora of congenital pathological conditions generally connected with cognitive, social behavior, and sensory/motor alterations. Among the possible causes, gestational and perinatal insults have been demonstrated to interfere with the physiological processes necessary for the proper development of fetal brain cytoarchitecture and functionality. In recent years, several genetic disorders caused by mutations in key enzymes involved in purine metabolism have been associated with autism-like behavioral outcomes. Further analysis revealed dysregulated purine and pyrimidine levels in the biofluids of subjects with other NDDs. Moreover, the pharmacological blockade of specific purinergic pathways reversed the cognitive and behavioral defects caused by maternal immune activation, a validated and now extensively used rodent model for NDDs. Furthermore, Fragile X and Rett syndrome transgenic animal models as well as models of premature birth, have been successfully utilized to investigate purinergic signaling as a potential pharmacological target for these diseases. In this review, we examine results on the role of the P2 receptor signaling in the etiopathogenesis of NDDs. On this basis, we discuss how this evidence could be exploited to develop more receptor-specific ligands for future therapeutic interventions and novel prognostic markers for the early detection of these conditions.
Different Crystallization Behavior of Amorphous ITO Film by Rapid Infrared Annealing and Conventional Furnace Annealing Technology

An amorphous indium tin oxide (ITO) film (Ar/O2 = 80:0.5) was heated to 400 °C and maintained for 1–9 min using rapid infrared annealing (RIA) technology and conventional furnace annealing (CFA) technology. The effect of holding time on the structure, optical and electrical properties, and crystallization kinetics of ITO films, and on the mechanical properties of the chemically strengthened glass substrates, were revealed. The results show that the nucleation rate of ITO films produced by RIA is higher and the grain size is smaller than for CFA. When the RIA holding time exceeds 5 min, the sheet resistance of the ITO film is basically stable (8.75 Ω/sq). The effect of holding time on the mechanical properties of chemically strengthened glass substrates annealed using RIA technology is less than that of CFA technology. The percentage of compressive-stress decline of the strengthened glass after annealing using RIA technology is only 12–15% of that using CFA technology. For improving the optical and electrical properties of the amorphous ITO thin films, and the mechanical properties of the chemically strengthened glass substrates, RIA technology is more efficient than CFA technology.
Significant Impact of Big Data Analytics on the Organizations

The researcher provides an overview of one of the most significant technologies in the current era which is "Big data analytics". Also describe the definition of big data, the types of big data, the importance of this technology, the application of this technology, and the difficulties that can be faced during its implementation. Also, how the new generation of organizations depends on this big data for its several features.
On the finite termination of the Douglas-Rachford method for the convex feasibility problem

In this paper we apply the Douglas–Rachford (DR) method to solve the problem of finding a point in the intersection of the interior of a closed convex cone and a closed convex set in an infinite-dimensional Hilbert space. For this purpose, we propose two variants of the DR method which can find a point in the intersection in a finite number of iterations. In order to analyse the finite termination of the methods, we use some properties of the metric projection and a result regarding the rate of convergence of fixed point iterations. As applications of the results, we propose the methods for solving the conic and semidefinite feasibility problems, which terminate at a solution in a finite number of iterations.
The Immunohistochemical Staining of Vimentin and E-Cadherin in Bladder Cancer Patients Infected with Hepatitis C Virus

The invasion and spread of cancer cells are two of the most notable characteristics of malignant tumors. Recent studies suggest that the epithelial-mesenchymal transition (EMT) has been linked to this significant occurrence. It is linked to the absence of the epithelial brow and the presence of mesenchymal facial hair. The aims of the present study were to explore the immunohistochemical staining of vimentin and E-cadherin ex vivo as EMT markers and assess their potential as predictive biomarkers for transitional cell cancer (TCC). In this study, 55 paraffin-embedded biopsies from TCC patients and 10 autopsies that appeared to be normal were included. Immunohistochemistry was used to produce patterns of vimentin and E-cadherin expression. When compared to female patients, the expression of E-cadherin and vimentin significantly increased with increasing age in male patients (> 50 years). In contrast to the considerable rise in vimentin expression in higher grades and stages of the tumor, E-cadherin expression was significantly reduced with tumor stage and grade. The findings of this study reveal that elevated vimentin and reduced E-cadherin are important indicators associated with a poor prognosis for TCC.
Efficient simulation of a slow-fast dynamical system using multirate finite difference schemes

Abstract We consider a system of ordinary differential equations describing a slow-fast dynamical system, in particular, a predator-prey system that is highly susceptible to local time variations. This model exhibits coexistence of predatorprey dynamics in the case when the prey population grows much faster than that of the predators with a quite diversified time response. For particular parametric values their interactions show a stable relaxation oscillation in the positive octant. Such characteristics are diﬃcult to mimic using conventional time integrators that are used to solve systems of ordinary diﬀerential equations. To resolve this, we design and analyze multirate time integration methods to solve a mathematical model for a slow-fast dynamical system. Proposed methods are based on using extrapolation multirate discretisation algorithms. Through these methods, we reduce the integration time by integrating the slow sub-system with a larger step length than the fast sub-system. This allows us to efficiently solve multiscale ordinary differential equations. Besides theoretical results, we provide thorough numerical experiments which confirm that these multirate schemes outperform corresponding single-rate schemes substantially both in terms of computational work and CPU times.
DIT Measurement Model of Website's Ease of Use Based on User's Appraoch

Through reviewing the research of Website's Ease of Use(WEU),the paper analyzes and points out the problem existed in quantitative measurement of WEU.To solve the direct quantitative measurement problem,the paper introduces the theory of Distance of Information-State Transition(DIT),and build a direct quantitative measurement model of WEU.Finally the paper uses this model to calculate the DIT of two examples.This paper presents a new study approach of direct quantitative measurement of WEU.
Screening of Suitable Reference Genes for Immune Gene Expression Analysis Stimulated by Vibrio anguillarum and Copper Ions in Chinese Mitten Crab (Eriocheir sinensis)

The reference gene expression is not always stable under different experimental conditions, and screening of suitable reference genes is a prerequisite in quantitative real-time polymerase chain reaction (qRT-PCR). In this study, we investigated gene selection, and the most stable reference gene for the Chinese mitten crab (Eriocheir sinensis) was screened under the stimulation of Vibrio anguillarum and copper ions, respectively. Ten candidate reference genes were selected, including arginine kinase (AK), ubiquitin-conjugating enzyme E2b (UBE), glutathione S-transferase (GST), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1α (EF-1α), α-tubulin (α-TUB), heat shock protein 90 (HSP90), β-actin (β-ACTIN), elongation factor 2 (EF-2) and phosphoglucomutase 2 (PGM2). Expression levels of these reference genes were detected under the stimulation of V. anguillarum at different times (0 h, 6 h, 12 h, 24 h, 48 h and 72 h) and copper ions in different concentrations (11.08 mg/L, 2.77 mg/L, 0.69 mg/L and 0.17 mg/L). Four types of analytical software, namely geNorm, BestKeeper, NormFinder and Ref-Finder, were applied to evaluate the reference gene stability. The results showed that the stability of the 10 candidate reference genes was in the following order: AK > EF-1α > α-TUB > GAPDH > UBE > β-ACTIN > EF-2 > PGM2 > GST > HSP90 under V. anguillarum stimulation. It was GAPDH > β-ACTIN > α-TUB > PGM2 > EF-1α > EF-2 > AK > GST > UBE > HSP90 under copper ion stimulation. The expression of E. sinensis Peroxiredoxin4 (EsPrx4) was detected when the most stable and least stable internal reference genes were selected, respectively. The results showed that reference genes with different stability had great influence on the accurate results of the target gene expression. In the Chinese mitten crab (E. sinensis), AK and EF-1α were the most suitable reference genes under the stimulation of V. anguillarum. Under the stimulation of copper ions, GAPDH and β-ACTIN were the most suitable reference genes. This study provided important information for further research on immune genes in V. anguillarum or copper ion stimulation.
Embedded System Vehicle Based on Multi-Sensor Fusion

As intelligent driving vehicles came out of concept into people’s life, the combination of safe driving and artificial intelligence becomes the new direction of future transportation development. Autonomous driving technology is developing based on control algorithms and model recognitions. In this paper, a cloud-based interconnected multi-sensor fusion autonomous vehicle system is proposed that uses deep learning (YOLOv4) and improved ORB algorithms to identify pedestrians, vehicles, and various traffic signs. A cloud-based interactive system is built to enable vehicle owners to master the situation of their vehicles at any time. In order to meet multiple application of automatic driving vehicles, the environment perception technology of multi-sensor fusion processing has broadened the uses of automatic driving vehicles by being equipped with automatic speech recognition (ASR), vehicle following mode and road patrol mode. These functions enable automatic driving to be used in applications such as agricultural irrigation, road firefighting and contactless delivery under new coronavirus outbreaks. Finally, using the embedded system equipment, an intelligent car was built for experimental verification, and the overall recognition accuracy of the system was over 96%.
A Galerkin approximation for integro-differential equations in electromagnetic scattering from a chiral medium

We consider the scattering of time-harmonic electromagnetic waves from a chiral medium. It is known for the Drude–Born–Fedorov model that the forward scattering problem can be described by an integro-differential equation. In this paper we study a Galerkin finite element approximation for this integro-differential equation. Our Galerkin scheme, which relies on a suitable periodization of the integral equation, enables the use of the fast Fourier transform and a simple numerical implementation. We establish a quasi-optimal convergence analysis for the Galerkin method. Explicit formulas for the discrete scheme are also provided.
Deep Reinforcement Learning-Based Scheduling for NR-U/WiGig Coexistence in Unlicensed mmWave Bands

This paper investigates the coexistence of the New Radio-based access to Unlicensed spectrum (NR-U) network and the Wireless Gigabit (WiGig) network in unlicensed millimeter-wave (mmWave) bands. To enable the NR-U network to achieve equitable and harmonious spectrum sharing with WiGig systems, we develop two new classes of user equipment (UE) scheduling schemes by exploiting the deep reinforcement learning (DRL) technique. Specifically, we first propose the distributed deep reinforcement learning scheduling (DeepDS) scheme, wherein multiple deep neural networks (DNNs) are used to make decisions for different panels in an independent fashion. Thereafter, to reduce the computational cost of adopting multiple DNNs, we design the centralized deep reinforcement learning scheduling (DeepCS) scheme that introduces the shared DNN framework to perform decisions for all panels in parallel at one time. The objective of both DeepDS and DeepCS is to maximize the total data rate of the NR-U network with as little interference to WiGig systems as possible, while satisfying the quality of service (QoS) requirement for each UE. We first formulate this problem into the constrained Markov decision process framework. To address the multi-constraint issue, we put forth a new DRL algorithm that incorporates the Lagrangian primal-dual optimization into the deep Q-network framework, referred to as adaptive multi-constraint deep Q-network (AMC-DQN). With AMC-DQN, both DeepDS and DeepCS can achieve their goals even without acquiring prior operations about the WiGig network. Simulation results show that compared with the state-of-the-art omniLBT and dirLBT, both DeepDS and DeepCS yield significant performance benefits in terms of the total network data rate. We also demonstrate the ability of DeepDS and DeepCS to satisfy the QoS requirements of different UEs and their robustness against various simulation setups. Furthermore, compared with DeepDS, DeepCS can save a large amount of computational cost although at the expense of a slightly lower data rate.
XUV spectral analysis of ns- and ps-laser produced platinum plasmas

XUV spectra of ns- and ps-laser produced platinum (Pt) plasmas in the 1–7 nm wavelength region, where Δn = 1 n = 4–5 and Δn = 0 n = 4-4 transitions dominate the observed emission, were investigated experimentally and theoretically. Ab initio calculations using the Hartree–Fock with configuration interaction (HFCI) Cowan suite of codes and the unresolved transition array (UTA) formalism, as well as consideration of previous predictions of isoelectronic trends, together with spectra obtained under different laser power densities are all employed to identify lines and a number of new features in spectra from Pt XX to Pt XLII. The possible reasons for the main differences between the ns- and ps-laser plasmas spectra are also demonstrated. This work extends previous analyses of the XUV spectra of laser produced gold, tungsten, tantalum, hafnium and rhenium plasmas in the 1–7 nm wavelength range.
Self-Standing, Ultrasonic Spray-Deposited Membranes for Fuel Cells

The polymer electrolyte membrane and its contact with electrodes has a significant effect on the performance of fuel and electrolysis cells but the choice of commercially available membranes is limited. In this study, membranes for direct methanol fuel cells (DMFCs) were made by ultrasonic spray deposition from commercial Nafion solution; the effect of the drying temperature and presence of high boiling solvents on the membrane properties was then analyzed. When choosing suitable conditions, membranes with similar conductivity, water uptake, and higher crystallinity than comparable commercial membranes can be obtained. These show similar or superior performance in DMFC operation compared to commercial Nafion 115. Furthermore, they exhibit low permeability for hydrogen, which makes them attractive for electrolysis or hydrogen fuel cells. The findings from our work will allow for the adjustment of membrane properties to the specific requirements of fuel cells or water electrolysis, as well as the inclusion of additional functional components for composite membranes.
Rare Oral Crohn’s Disease: A Case Report

Crohn's disease is an inflammatory granulomatous and chronic disease characterized by inflammation of the gastrointestinal mucosa with extra-intestinal manifestations. Oral lesions seem to occur as specific lesions like lip swelling, cobblestone or tag lesions, or nonspecific lesions like ulcers. The present case report describes an orofacial Crohn’s disease case, a rare presentation of Crohn’s disease, managed with infliximab. Oral Crohn's disease refers to the spread of manifestations of Crohn’s disease and could precede other signs. Physicians have to be aware of oral mucosal changes. The treatment options are based on the use of corticosteroids, immune-modulators and biologics. The best plan and therapy to control oral Crohn's disease requires early and precise diagnosis.
Potential of Synthetic and Natural Compounds as Novel Histone Deacetylase Inhibitors for the Treatment of Hematological Malignancies

Simple Summary Histone deacetylases (HDACs) are epigenetic regulators that influence chromatin structure and gene transcription, but also the function of non-histone targets like chaperones and proteins participating in the DNA damage response. Histone modifications are implicated in cancer and HDAC inhibitors (HDACis) can be useful to treat hematological malignancies, including leukemia, B-cell lymphoma, virus-associated tumors, and multiple myeloma. Several HDACis were approved for clinical use and others are showing promising results, especially as adjuvants to conventional treatments. In addition to synthetic inhibitors, this work discusses the potential of phytocompounds, such as chrysin and oleacein as well as marine-derived agents, such as halenaquinone and xestoquinone, as therapeutic agents against hematological cancers. Abstract Histone deacetylases (HDACs) and histone acetyltransferases (HATs) are enzymes that remove or add acetyl groups to lysine residues of histones, respectively. Histone deacetylation causes DNA to more snugly encircle histones and decreases gene expression, whereas acetylation has the opposite effect. Through these small alterations in chemical structure, HATs and HDACs regulate DNA expression. Recent research indicates histone deacetylase inhibitors (HDACis) may be used to treat malignancies, including leukemia, B-cell lymphoma, virus-associated tumors, and multiple myeloma. These data suggest that HDACis may boost the production of immune-related molecules, resulting in the growth of CD8-positive T-cells and the recognition of nonreactive tumor cells by the immune system, thereby diminishing tumor immunity. The argument for employing epigenetic drugs in the treatment of acute myeloid leukemia (AML) patients is supported by evidence that both epigenetic changes and mutations in the epigenetic machinery contribute to AML etiology. Although hypomethylating drugs have been licensed for use in AML, additional epigenetic inhibitors, such as HDACis, are now being tested in humans. Preclinical studies evaluating the efficacy of HDACis against AML have shown the ability of specific agents, such as anobinostat, vorinostat, and tricostatin A, to induce growth arrest, apoptosis, autophagy and cell death. However, these inhibitors do not seem to be successful as monotherapies, but instead achieve results when used in conjunction with other medications. In this article, we discuss the mounting evidence that HDACis promote extensive histone acetylation, as well as substantial increases in reactive oxygen species and DNA damage in hematological malignant cells. We also evaluate the potential of various natural product-based HDACis as therapeutic agents to combat hematological malignancies.
An Application of Logistic Regression on Correlated Data

It is common to find data in the form of proportions have more variability than the variance based on the binomial distribution. The phenomenon is called extra-binomial variation or overdispersion and commonly caused by the occurrence of correlation within response variable. Models for correlated outcome produces unbiased estimate, but its standard error is underestimated. Hence, confidence interval becomes too narrow and statistical test tends to reject the null hypothesis. Williams has proposed to simple method correct the effect of extra-binomial variation by taking inflation factor into consideration. In this paper, the Williams approach is implemented to analyze the poverty data in Indonesia, which exhibit extra-variation. The result shows that the method adjusts the standard error of estimates and then provides more reliable conclusion than the naive approach. Public policy of government certainly requires adequate recommendations to allocate limited resources appropriately following defined objectives. Regional data usually depends on many factors causing non-independent outcome making the data are overdispersed. Models which ignore the extra-variation will lead to a wrong conclusion. Therefore, applying regression analysis in public policy with accommodating overdispersion is important to obtain meaningful and reliable recommendations. Keywords: Logistic Regression; Extra-binomial Variation; Overdispersion; Williams Method; Poverty Analysis. 2010 Mathematics Subject Classification: 62J05
Antibacterial and Analgesic Properties of Beta-Caryophyllene in a Murine Urinary Tract Infection Model

Beta-caryophyllene has demonstrated anti-inflammatory effects in a variety of conditions, including interstitial cystitis. These effects are mediated primarily via the activation of the cannabinoid type 2 receptor. Additional antibacterial properties have recently been suggested, leading to our investigation of the effects of beta-caryophyllene in a murine model of urinary tract infection (UTI). Female BALB/c mice were intravesically inoculated with uropathogenic Escherichia coli CFT073. The mice received either beta-caryophyllene, antibiotic treatment using fosfomycin, or combination therapy. After 6, 24, or 72 h, the mice were evaluated for bacterial burden in the bladder and changes in pain and behavioral responses using von Frey esthesiometry. In the 24 h model, the anti-inflammatory effects of beta-caryophyllene were also assessed using intravital microscopy. The mice established a robust UTI by 24 h. Altered behavioral responses persisted 72 h post infection. Treatment with beta-caryophyllene resulted in a significant reduction in the bacterial burden in urine and bladder tissues 24 h post UTI induction and significant improvements in behavioral responses and intravital microscopy parameters, representing reduced inflammation in the bladder. This study demonstrates the utility of beta-caryophyllene as a new adjunct therapy for the management of UTI.
On Importance Sampling for State Space Models

We consider likelihood inference and state estimation by means of importance sampling for state space models with a nonlinear non-Gaussian observation y ~ p(y|alpha) and a linear Gaussian state alpha ~ p(alpha). The importance density is chosen to be the Laplace approximation of the smoothing density p(alpha|y). We show that computationally efficient state space methods can be used to perform all necessary computations in all situations. It requires new derivations of the Kalman filter and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results are presented that lead to a more effective implementation of importance sampling for state space models. An illustration is given for the stochastic volatility model with leverage.