Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Evolutionary Analyses of the Spike Protein Gene and Spike Protein in the SARS-CoV-2 Omicron Subvariants

To better understand the evolution of the SARS-CoV-2 Omicron subvariants, we performed molecular evolutionary analyses of the spike (S) protein gene/S protein using advanced bioinformatics technologies. First, time-scaled phylogenetic analysis estimated that a common ancestor of the Wuhan, Alpha, Beta, Delta variants, and Omicron variants/subvariants diverged in May 2020. After that, a common ancestor of the Omicron variant generated various Omicron subvariants over one year. Furthermore, a chimeric virus between the BM.1.1.1 and BJ.1 subvariants, known as XBB, diverged in July 2021, leading to the emergence of the prevalent subvariants XBB.1. 5 and XBB.1.16. Next, similarity plot (SimPlot) data estimated that the recombination point (breakpoint) corresponded to nucleotide position 1373. As a result, XBB.1. 5 subvariants had the 5′ nucleotide side from the breakpoint as a strain with a BJ.1 sequence and the 3′ nucleotide side as a strain with a BM.1.1.1 sequence. Genome network data showed that Omicron subvariants were genetically linked with the common ancestors of the Wuhan and Delta variants, resulting in many amino acid mutations. Selective pressure analysis estimated that the prevalent subvariants, XBB.1. 5 and XBB.1.16, had specific amino acid mutations, such as V445P, G446S, N460K, and F486P, located in the RBD when compared with the BA.4 and BA.5 subvariants. Moreover, some representative immunogenicity-associated amino acid mutations, including L452R, F486V, R493Q, and V490S, were also found in these subvariants. These substitutions were involved in the conformational epitopes, implying that these mutations affect immunogenicity and vaccine evasion. Furthermore, these mutations were identified as positive selection sites. These results suggest that the S gene/S protein Omicron subvariants rapidly evolved, and mutations observed in the conformational epitopes may reduce the effectiveness of the current vaccine, including bivalent vaccines such as mRNA vaccines containing the BA.4/BA.5 subvariants.
Potential impact of all‐sky assimilation of visible and infrared satellite observations compared with radar reflectivity for convective‐scale numerical weather prediction

Although cloud‐affected satellite observations are heavily used for nowcasting applications, their use in regional data assimilation is very limited despite possible benefits for convective‐scale forecasts. In this article, we estimate the potential impact of assimilating cloud‐affected satellite observations of visible (0.6 μ$$ \upmu $$ m) and near thermal infrared wavelengths (6.2 and 7.3 μ$$ \upmu $$ m) relative to the impact of assimilating radar reflectivity observations. We employed observing‐system simulation experiments with a perfect‐model forecast for two cases of strong convective summertime precipitation. Observations are simulated using the radiative transfer model RTTOV/MFASIS and assimilated by the ensemble adjustment Kalman filter in the Data Assimilation Research Testbed. The Weather Research and Forecasting model at 2‐km grid resolution was used for forecasts. Results show that satellite observations can be nearly as beneficial as three‐dimensional radar reflectivity observations. Under favorable conditions, where the prior contains no error in the stage of storm development but only in horizontal position and strength, the assimilation of visible observations leads to 88% of the radar impact. Under more difficult conditions, the impact of visible and infrared observations still reached 50 and 79%, respectively.
Associated primes and primary right ideals of generalized triangular matrix rings

Abstract Let be an (S, R)-bimodule of the rings R and S. We determine the associated primes of a formal triangular matrix ring Indeed, we show that We then obtain necessary and sufficient conditions for the tertiary decomposition theory to exist on a module over an arbitrary ring. Consequently, we classify all the tertiary right ideals of the formal triangular matrix rings.
Mechanisms of Herba Epimedii in Lung Cancer Treatment: A Combination of Molecular Docking and Network Pharmacology Analyses

Introduction Lung cancer (LC) ranks among the most prevalent malignant neoplasms globally. As a Traditional Chinese medicine (TCM), Herba Epimedii has been commonly used for treating LC. However, the specific mechanism of LC remains to be elucidated. Objectives This research aimed to explore the mechanisms of Herba Epimedii in treating LC according to molecular docking and network pharmacology. Materials and Methods The active components (ACs) and targets of Herba Epimedii were screened through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. LC targets were retrieved from GeneCards and DisGeNET databases. Cytoscape v3.9. 0 was employed to construct a “drug-component-disease-target” network. The STRING database and Cytoscape 3.9. 0 software were utilized to establish a PPI network. The DAVID database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The AutoDock software was employed for molecular docking verification, and the Pymol software was applied for visual processing. Results Herba Epimedii acted on 108 LC treatment targets through 22 ACs. Five core components were screened, including quercetin, luteolin, kaempferol, anhydroicaritin, and 8-isopentenyl-kaempferol, while 12 core targets were screened, including TP53, AKT1, MYC, CASP3, ESR1, JUN, HIF1A, VEGFA, TNF, CCND1, EGFR, and IL-6. GO enrichment analysis mainly involved positive regulation of gene expression, positive regulation of the apoptotic process, enzyme binding, identical protein binding, macromolecular complex, nucleoplasm, etc. KEGG enrichment analysis mainly involved p53, interleukin-17, PI3K-Akt, and other signaling pathways. Five core components all demonstrated excellent binding activities with the core targets. Conclusion The mechanisms of Herba Epimedii in LC treatment may involve multiple components, targets, and pathways, inducing apoptosis, and inhibiting proliferation, invasion, metastasis, and drug resistance of LC cells.
Airborne observation with a low-cost hyperspectral instrument: Retrieval of NO 2 VCD and the satellite sub-grid variability over industrial point sources

The high spatial resolution NO 2 vertical column densities (VCDs) were measured from the airborne observations using the low-cost Hyperspectral Imaging Sensor (HIS) at three industrial areas (i.e., Chungnam, Jecheon, and Pohang) in Korea, where point sources (i.e., power plant, petrochemical complex, steel yard, and cement Kiln) with significant NO 2 emissions are located. An innovative and versatile approach for NO 2 VCD retrieval, hereafter referred to as the Modified 15 Wavelength Pair (MWP) method, was developed to overcome the excessively variable radiometric and spectral characteristics of the HIS attributed to the absence of temperature control during the flight. The newly developed MWP method was designed to be insensitive to broadband spectral features, including the spectral dependency of surface and aerosol reflectivity, and can be applied to observations with relatively low spectral resolutions. Moreover, the MWP method can be implemented without requiring precise radiometric calibration of the instrument (i.e., HIS) by utilizing clean pixel 20 data for non-uniformity corrections and is also less sensitive to the optical properties of the instrument and offers computational cost competitiveness. In the experimental flights using the HIS, NO 2 plumes emitted from steel yards were particularly conspicuous among the various NO 2 point sources, with peak NO 2 VCD of 2.0 DU at Chungnam and 1.8 DU at Pohang. The typical NO 2 VCD uncertainties ranged between 0.025–0.075 DU over the land surface and 0.10–0.15 DU over the ocean surface, and the discrepancy can be attributable to the lower signal-to-noise ratio over the ocean and higher 25 sensitivity of the MWP method to surface reflectance uncertainties under low-albedo conditions. The NO 2 VCDs retrieved from the HIS with the MWP method showed a good correlation with the collocated TROPOMI data (R=0.73, mean absolute error=0.106 DU). However, the temporal disparities between the HIS frames and the TROPOMI overpass, as well as the different observation geometries under complex vertical wind fields, limited the correlation. The comparison of TROPOMI and HIS NO 2 VCD further demonstrated that the satellite sub-grid variability could be intensified near the point sources, 30 with more than a threefold increase in HIS NO 2 VCD variability (e. g., difference between 25 th and 75 th quantiles) over the TROPOMI footprints with NO 2 VCD values exceeding 0.8 DU compared to footprints with NO 2 VCD values below 0.6 DU.
The Effects of Product Type, Product Involvement and Technology Fluidity on Flow and Newsfeed Advertising

ABSTRACT Existing research explaining product and technology factors influencing the effectiveness of newsfeed ads embedded in social media platforms remains scarce. Applying the flow concept and technology fluidity theory, this experiment explored how product and technological factors influenced consumers’ interaction with and evaluation of newsfeed ads on Facebook. Results showed that product type (think vs. feel) but not product involvement level (high vs. low), influenced immersion (a flow dimension) with the ad. While technology fluidity predicted users’ sense of control (a second flow dimension) of the ad, the two flow dimensions were positively related to attitude toward the newsfeed ad.
Cross-spectra over the sea from observations and 1 mesoscale modelling 2

Co-spectra and quadrature spectra are calculated for six pairs of 7 tall oﬀshore measurement masts near the Horns Rev I wind farm in the Danish 8 North Sea and the Nysted wind farm in the Baltic sea. The mast-pairs are 9 separated from one another by horizontal distances of 2.13 km to 12.4 km. 10 Co-spectra and quadrature spectra for the two sites are classiﬁed in terms 11 of the angle between the mean wind direction and the line connecting each 12 pair of masts. The frequency axes of the spectra are normalized to remove the 13 eﬀect of mean wind speed and separation distance. Results indicate a larger 14 contribution to the quadrature spectrum for ﬂow from the sea than for ﬂow 15 from the land, and the patterns in the spectra are clearer and better deﬁned
Licensed and Unlicensed Bands Allocation for Cellular Users: A Matching-Based Approach

Long term evolution-unlicensed (LTE-U) technologies allow cellular users (CUs) to be served in unlicensed bands. However, how a CU properly chooses between licensed and unlicensed bands and how a CU can utilize the unlicensed bands without jeopardizing other unlicensed-band users, e.g., Wi-Fi users (WUs), remain as open problems. In this letter, we aim to optimize the allocation of radio resources in both licensed and unlicensed bands in an LTE-U and Wi-Fi coexisting scenario, where a CU can be allocated either a licensed or unlicensed band. We formulate a multi-objective optimization problem to maximize every CU’s utility, while guaranteeing the throughput requirements of both CUs and WUs. We propose an algorithm based on one-to-one and many-to-one matching algorithms to solve it. The stability, Pareto optimality, and convergence of the proposed matching-based algorithm are proven. Simulation results show that the proposed algorithm can achieve near-optimal performance but with a low computational complexity.
Efficacy and safety of monoclonal antibodies targeting interleukin-17 pathway for inflammatory arthritis: a meta-analysis of randomized controlled clinical trials

: T-helper 17 (Th17) pathway plays an important and distinct role in autoimmunity and inflammation. A growing body of evidence demonstrates that interleukin-17 (IL-17) is also synthesized in inflammatory arthritis tissues and exerts potent proinflammatory and joint-destructive activities. Clinical studies have been performed to evaluate the therapeutic efficacy of antibodies blocking the IL-17 signaling pathway in patients with rheumatoid arthritis (RA). In this study, we performed a meta-analysis to systematically evaluate the clinical effects of IL-17 antibodies in RA patients. By searching PubMed, five randomized, placebo-controlled randomized controlled clinical trials that tested three antibodies against IL-17A (LY2439821 and secukinumab/AIN457) and the IL-17A receptor (brodalumab) were identified. The primary outcomes that were analyzed include American College of Rheumatology (ACR) Improvement Criteria and Disease Activity Score in 28 joints (DAS28). Meanwhile, the safety and adverse effects were also systematically analyzed. The results of the meta-analysis demonstrated that IL-17 antibody is effective in ameliorating the RA symptoms. Specifically, IL-17-blocking antibody significantly reduced ACR20 and ACR50. It also dramatically reduced DAS28, an index that measures tenderness and swelling severity of joints. The side effects of and intol-erance to the antibody treatment were higher than those in the placebo control. The analysis result provides evidence-based information for clinical use of these agents in the treatment of inflammatory arthritis.
Mandarin Chinese

Adpositions, though belonging to a closed functional category, can contribute significantly to meaning. Schneider et al. (2018b) proposed an annotation scheme called Semantic Network of Adposition and Case Supersenses (SNACS), which includes 50 supersense labels (LOCUS, TOPIC, etc.). Unlike other approaches to semantic tagging/role labeling, SNACS incorporates the construal analysis (Hwang et al., 2017) wherein the lexical semantic contribution of an adposition token (its function) is distinguished and may diverge from the underlying relation in the surrounding context or scene. For instance, (1) blends the domains of emotion (principally reflected in care, which licenses a STIMULUS), and cognition (principally reflected in about, which often marks nonemotional TOPICs). The token is therefore annotated with both supersenses; we use the notation SCENEROLE FUNCTION:
Fuzzy SLIC: Fuzzy Simple Linear Iterative Clustering

Most superpixel methods are sensitive to noise and cannot control the superpixel number precisely. To solve these problems, in this article, we propose a robust superpixel method called fuzzy simple linear iterative clustering (Fuzzy SLIC), which adopts a local spatial fuzzy C-means clustering and dynamic fuzzy superpixels. We develop a fast and precise superpixel number control algorithm called onion peeling (OP) algorithm. Fuzzy SLIC is insensitive to most types of noise, including Gaussian, salt and pepper, and multiplicative noise. The OP algorithm can control the superpixel number accurately without reducing much computational efficiency. In the validation experiments, we tested the Fuzzy SLIC and OP algorithm and compared them with state-of-the-art methods on the BSD500 and Pascal VOC2007 benchmarks. The experiment results show that our methods outperform state-of-the-art techniques in both noise-free and noisy environments.
Women's Critical Responses to Sexually Explicit Material: The Role of Hyperfemininity and Processing Style

Previous research on women's responses to male-targeted sexually explicit material (SEM) suggests that women may be critical toward such content. However, women's critical responses to SEM have not been explained empirically. The present study had two goals: (1) to investigate whether women's critical responses to male-targeted SEM depend on individual differences in gender role orientation (i.e., hyperfemininity) and (2) to explain the effect of hyperfemininity on critical responses to SEM by looking at the way sexual material is processed. In an online experiment among women aged 18 to 30 (N = 195), both the type of SEM (a male- versus female-targeted erotic story) and processing style (stimulus- versus response-focused) were manipulated. In addition, participants were divided into three groups based on low, moderate, or high hyperfemininity. When using stimulus-focused processing (i.e., attending to the characters and situational context of the story), women were more critical toward male-targeted SEM (relative to female-targeted material), but only when they had low and moderate degrees of hyperfemininity.
The Future of Chinese Management Research: A Theory of Chinese Management versus A Chinese Theory of Management

Two approaches to the evolution of Chinese scholarship are possible. The first – developing a theory of Chinese management – focuses on applying and refining theories developed elsewhere in a Chinese context. In this sense, the emergence of the Chinese economy represents an important natural experiment for the test and refinement of general management theories. The second – developing a Chinese theory of management – focuses on creating explanations for the existence of Chinese management phenomena that are uniquely Chinese. This approach rejects a research agenda created by Western scholars in favour of a research agenda created by Chinese scholars in order to understand Chinese phenomena. The implications of choosing either of these approaches for the future of Chinese management research and possible relationships between them are discussed.
Minimally important differences for interpreting European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 scores in patients with head and neck cancer

Background: We aimed to estimate minimally important difference (MID) for interpreting group-level change over time for European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ-C30) scores in head and neck cancer. Methods: Data were derived retrospectively from two published EORTC trials. Clinical anchors were selected using correlation strength and clinical plausibility of the given anchor/QLQ-C30 scale pair. MIDs for within-group and
MACHINE LEARNING TECHNIQUES APPLIED IN SURFACE EMG DETECTION- A SYSTEMATIC REVIEW

Surface electromyography (EMG) has emerged as a promising clisnical decision support system, enabling the extraction of muscles' electrical activity through non-invasive devices placed on the body. This study focuses on the application of machine learning (ML) techniques to preprocess and analyze EMG signals for the detection of muscle abnormalities. Notably, state-of-the-art ML algorithms, including Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Random Forests (RF), and Naive Bayes (NB), have been harnessed by researchers in the biomedical sciences to achieve accurate surface EMG signal detection. Within this paper, we present a meticulously conducted systematic review, employing the PRISMA method to select relevant research papers. Various databases were thoroughly searched, and multiple pertinent studies were identified for detailed examination, weighing their respective merits and drawbacks. Our survey comprehensively elucidates the latest ML techniques used in surface EMG detection, offering valuable insights for researchers in this domain. Additionally
Electromagnetic and Thermal Analysis of a 6/4 Induction Switched Reluctance Machine for Electric Vehicle Application

In this paper, an oil-cooling induction switched reluctance machine (ISRM) is offered. The stator and rotor of the electric machine are non-segmental. However, by placing coils on the rotor, a short magnetic flux path is achieved in the rotor and stator cores. As a result, a higher torque with lower losses is generated. This configuration can be used in high-power electric motors for electric and hybrid vehicles. ISRM is a novel machine and there is a lack of access to its operation and data characteristics. ISRM can be designed in different configurations with various stator and rotor pole numbers and winding strategies. In this study, an oil-cooling three-phase ISRM with 6 stator poles and 4 rotor poles was considered. Firstly, a 2D finite element model of it is created, and its magnetic properties extracted, the flux path, torque and efficiency of the ISRM are calculated, and the results are presented. Secondly, the thermal performance of the motor is analyzed using ANSYS Motor-Cad software. Finally, a prototype of the ISRM and its appropriate drive with the oil cooling system is built and tested. The experimental results and conclusions which prove the ability of the presented machine are presented in the last parts of the paper.
HPV vaccination to prevent recurrence of Anal Intraepithelial Neoplasia in HIV+ MSM: a randomised, placebo-controlled multicentre trial

Objective Anal cancer precursor lesions high-grade anal intraepithelial neoplasia (HGAIN) are highly prevalent among HIV+ men-who-have-sex-with-men (MSM). Treatment of HGAIN is frustrated by high recurrence rates. We investigated the efficacy of the quadrivalent human papillomavirus (qHPV) vaccine as post-treatment adjuvant in preventing HGAIN recurrence in HIV+MSM.
Exterior-point Optimization for Nonconvex Learning

In this paper we present the nonconvex exterior-point optimization solver (NExOS) — a novel first-order algorithm tailored to constrained nonconvex learning problems. We consider the problem of minimizing a convex function over nonconvex constraints, where the projection onto the constraint set is single-valued around local minima. A wide range of nonconvex learning problems have this structure including (but not limited to) sparse and low-rank optimization problems. By exploiting the underlying geometry of the constraint set, NExOS finds a locally optimal point by solving a sequence of penalized problems with strictly decreasing penalty parameters. NExOS solves each penalized problem by applying a first-order algorithm, which converges linearly to a local minimum of the corresponding penalized formulation under regularity conditions. Furthermore, the local minima of the penalized problems converge to a local minimum of the original problem as the penalty parameter goes to zero. We implement NExOS in the open-source Julia package NExOS.jl , which has been extensively tested on many instances from a wide variety of learning problems. We demonstrate that our algorithm, in spite of being general purpose, outperforms specialized methods on several examples of well-known nonconvex learning problems involving sparse and low-rank optimization.
Optimal Monetary Policy and the Sources of Local-Currency Price Stability 1

We analyze the policy trade-o s generated by local currency price stability of imports in economies where upstream producers strategically interact with downstream rms selling the nal goods to consumers. We study the e ects of staggered price setting at the downstream level on the optimal price (and markup) chosen by upstream producers and show that downstream price movements a ect the desired markup of upstream producers, magnifying their price response to shocks. We revisit the international dimensions of optimal monetary policy, unveiling an argument in favor of consumer price stability as the main prescription for monetary policy. Since stable consumer prices feed back into a low volatility of markups among upstream producers, this contains ine cient deviations from the law of one price at the border. However, e cient stabilization of di erent CPI components will not generally result into perfect stabilization of headline in ation. National policies optimally respond to the same shocks in a similar way, thus containing volatility of the terms of trade, but not necessarily of the real exchange rate. The latter will be more volatile, among other things, the larger the home bias in expenditure and the content of local inputs in consumer goods. JEL Classi cation Codes.F31, F33, F41.