Miracle-dz/UniFAR-FTUs huggingface dataset:
Boundary Layer between a Plasma and a Magnetic Field

The problem of a steady boundary layer or sheath between a plasma and a magnetic field is considered. A self‐consistent transition layer is found which joins a uniform magnetic field at plus infinity with a collisionless field‐free plasma region with arbitrary velocity distribution at minus infinity; i.e., a magnetic field profile is found such that the exact particle orbits in this field produce a current which gives rise to the field. An interesting mathematical feature of the ``thinnest'' such solution is that, with any nonsingular velocity distribution at minus infinity, the magnetic field penetrates only a finite distance into the plasma although the plasma extends to infinity, exponentially attenuated, into the magnetic field region. The scale of length is the ratio of the speed of light to the plasma frequency or, equivalently, the Larmor radius of a representative particle. Electric fields arising from charge separation in the case of particles of different mass are ignored.
Review of Navigation Methods for UAV-Based Parcel Delivery

This paper presents a comprehensive review of state-of-the-art navigation methods available for unmanned aerial vehicles (UAVs) used in parcel delivery. Particularly, the paper focuses on state-of-the-art sensor configurations, multi-sensor data fusion architectures, and their performance when employed for UAV navigation. Additionally, this paper presents the associated safety regulations for UAV navigation currently imposed by regulatory bodies in US and Canada. The existing navigation solutions sometimes produce degenerative results due to GPS loss, multipath signals, spoofing events, and other sensor degradation scenarios. Therefore, this article investigates the suitability of integrating visual lidar odometry and mapping (VLOAM) with GPS to overcome the limitations of existing navigation solutions. A comparative study of the multi-sensory combined solutions is presented with numerical simulations, validating the regulatory compliance of VLOAM and GPS integrated system under common GPS failure cases. Note to Practitioners—This work was motivated by the need for a survey on existing UAV navigation methods for parcel delivery applications. Different UAV navigation methods exist, depending on the sensors used and the sensor fusion architectures, with varying degrees of localization accuracy. It can be challenging for researchers and practitioners to decide which method to adopt for their application while complying with the existing safety regulations. Therefore, this paper presents an overview of the current safety regulation for UAV navigation and evaluates the state-of-the-art navigation methods against regulatory safety compliance. Additionally, a numerically validated safe navigation method is suggested for UAV-based parcel delivery. This paper provides researchers and practitioners with comprehensive reference sources in the UAV navigation field, which can help them develop suitable solutions to ensure safe navigation.
A Novel Data-Driven Self-Tuning SVC Additional Fractional-Order Sliding Mode Controller for Transient Voltage Stability With Wind Generations

This paper proposes a novel data-driven self-tuning additional sliding mode controller for power system transient voltage stability enhancement considering wind integration. We first develop a new additional fractional-order sliding mode controller (FOSMC) for the static var compensator (SVC). The tuning of FOSMC parameter settings is then reformulated as a Markov decision process (MDP) and solved by the deep reinforcement learning (DRL) algorithm. In addition, a data-driven estimation method is proposed for the identification of an equivalent transfer function that is further used to calculate reward during the training process, yielding the model-free training. After that, the well-trained agent allows us to tune the controller parameters considering system uncertainties and achieve robustness against various operating conditions. Comparative results with other state-of-art methods demonstrate that the proposed method can effectively suppress the chattering issue of the sliding mode controller and ensure transient voltage stability under different operating conditions.
Antioxidant, Cytotoxic, and DNA Damage Protection Activities of Endophytic Fungus Pestalotiopsis neglecta Isolated from Ziziphus spina-christi Medicinal Plant

Fungal endophytes are friendly microorganisms that colonize plants and are important in the interactions between plants and their environment. They generate valuable secondary metabolites that are valuable to both plants and humans. Endophytic fungi with bioactivities were isolated from the leaves of the medicinal plant Ziziphus spina-christi. An efficient isolate was selected and identified as Pestalotiopsis neglecta based on nucleotide sequencing of the internal transcribed spacer region (ITS 1-5.8S-ITS 2) of the 18S rRNA gene (NCBI accession number OP529850); the 564 bp had 99 to 100% similarity with P. neglecta MH860161.1, AY682935.1, KP689121.1, and MG572407.1, according to the BLASTn analysis, following preliminary phytochemical and antifungal screening. The biological activities of this fungus’ crude ethyl acetate (EtOAc) extract were assessed. With an efficient radical scavenging activity against 2,2′-diphenyl-1-picrylhydrazyl and an IC50 value of 36.6 µg mL−1, P. neglecta extract has shown its potential as an antioxidant. Moreover, it displayed notable cytotoxic effects against MCF-7 (breast carcinoma, IC50 = 22.4 µg mL−1), HeLa (cervical carcinoma, IC50 = 28.9 µg mL−1) and HepG-2 (liver carcinoma, IC50 = 28.9 µg mL−1). At 10 µg mL−1, EtOAc demonstrated significant DNA protection against hydroxyl radical-induced damage. Based on FT-IR and GC-MS spectral analysis, it was detected that the EtOAc of P. neglecta product contains multiple bioactive functional groups. Subsequently, this validated the features of major different potent compounds; tolycaine, 1H-pyrazol, 1,3,5-trimethyl-, eugenol, 2,5-cyclohexadiene-1,4-dione, 2,6-bis(1,1-dimethyl), and bis(2-ethylhexyl) phthalate. Since these compounds are biologically relevant in various aspects, and distinct biological activities of fungal extract were acceptable in vitro, this suggests that endophytic fungus P. neglecta may be a viable source of bioactive natural products. This could be a good starting point for pharmaceutical applications.
Integrating Home and International Students in HE: Academic and Social Effects of Pair Work PBL Assignments Online

Integration is vital to student well-being in higher education but integrating new students from different countries can be challenging. To ascertain students’ integration into their new environment, this mixed method study combined the data collected from weekly diary entries of home and international students at the start of one engineering program, with follow-up interviews. These students studied primarily online due to the pandemic. The diary entries focused on their adjustment to the program from an academic, social and pair work perspective. Results show that the students reacted slightly negatively to the academic experience but very positively to their pair work. It seems that the teacher-formed pair work helped to bridge the academic and social gap and not only alleviate some of the stress caused by assignments, but in some cases, provided new social contacts. The article concludes that structural factors within the course can facilitate interaction and thus support integration.
Microdosing Sprint Distribution as an Alternative to Achieve Better Sprint Performance in Field Hockey Players

Abstract Introduction: The implementation of optimal sprint training volume is a relevant component of team sport performance. This study aimed to compare the efficiency and effectiveness of two different configurations of within-season training load distribution on sprint performance over 6 weeks. Methods: Twenty male professional FH players participated in the study. Players were conveniently assigned to two groups: the experimental group (MG; n = 11; applying the microdosing training methodology) and the control group (TG; n = 9; traditional training, with players being selected by the national team). Sprint performance was evaluated through 20 m sprint time (T20) m and horizontal force–velocity profile (HFVP) tests before (Pre) and after (Post) intervention. Both measurements were separated by a period of 6 weeks. The specific sprint training program was performed for each group (for vs. two weekly sessions for MG and TG, respectively) attempting to influence the full spectrum of the F-V relationship. Results: Conditional demands analysis (matches and training sessions) showed no significant differences between the groups during the intervention period (p > 0.05). No significant between-group differences were found at Pre or Post for any sprint-related performance (p > 0.05). Nevertheless, intra-group analysis revealed significant differences in F0, Pmax, RFmean at 10 m and every achieved time for distances ranging from 5 to 25 m for MG (p < 0.05). Such changes in mechanical capabilities and sprint performance were characterized by an increase in stride length and a decrease in stride frequency during the maximal velocity phase (p < 0.05). Conclusion: Implementing strategies such as microdosed training load distribution appears to be an effective and efficient alternative for sprint training in team sports such as hockey.
Development and Initial Validation of Scores on the Inner Wealth Inventory: Implications for Human Service Management and Practice

ABSTRACT Human services professionals who work in child welfare face notable risks for burnout, which is associated with higher levels of job stress, job dissatisfaction, and turnover. The authors of this study developed and validated scores on the Inner Wealth Inventory (IWI), a screening tool for appraising Inner Wealth (IW), a strengths-based construct with implications for reducing burnout. The collective results of exploratory factor analysis, confirmatory factor analysis, convergent validity testing, and internal consistency reliability analyses supported the psychometric properties of the IWI with two independent samples of child welfare professionals. Implications for human service managers, researchers, and practitioners are discussed.
Higher Dimensional Kerr-Schild Spacetimes with (A)dS Background

Geometric properties of higher dimensional Kerr-Schild (KS) spacetimes with (A)dS background are summarised. For Einstein spaces algebraic types of the Weyl tensor compatible with the KS ansatz are established, optical properties of the KS vector are given. Important examples of exact solutions belonging to this class, such as Kerr-de Sitter metrics in arbitrary dimension are also briefly discussed.
Model functions in the modified L-curve method—case study: the heat flux reconstruction in pool boiling

The L-curve method is known as one of the most popular heuristic regularization parameter choice rules in solving discrete ill-posed problems: A modification of the L-curve method proposed by Regińska (1996 SIAM J. Sci. Comput. 17 740–9) consists in finding the minimizer of the functional where −1/μ is the slope at the corner of the L-curve. In this paper we propose a model function approach in the modified L-curve method for the choice of the regularization parameter. The idea is to replace the residual norm and the regularized solution norm with appropriate model functions. With such an approach, the computational cost of the minimization procedure can be essentially reduced. This approach is applied to pool boiling data to reconstruct unknown heat fluxes at the boiling surface.
The context signals of mitochondrial miRNAs (mitomiRs) of mammals

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level in the cytoplasm and play an important role in a wide range of biological processes. Recent studies have found that the miRNA sequences are presented not only in the cytoplasm, but also in the mitochondria. These miRNAs (the so-called mitomiRs) may be the sequences of nuclear or mitochondrial origin; some of them are involved in regulation of the mitochondrial gene functions, while the role of others is still unknown. The identification of nucleotide signals, which are unique to mitomiRs, may help to determine this role. We formed a dataset that combined the experimentally discovered mitomiRs in human, rat and mouse. To isolate signals that may be responsible for the mitomiRs’ functions or for their translocation from or into mitochondria a context analysis was carried out for the sequences. For three species in the group mitomiRs/non-mitomiRs and the group of all miRNAs from the miRBase database statistically overrepresented 8-letter motifs were identified (p-value < 0.01 with Bonferroni correction for multiple comparisons), for these motifs the patterns of the localization in functionally important regions for different types of miRNAs were found. Also, for the group mitomiRs/non-mitomiRs we found the statistically significant features of the miRNA nucleotide context near the Dicer and Drosha cleavage sites (Pearson’s χ2 test of independence for the first three positions of the miRNA, p-value < 0.05). The observed nucleotide frequencies may indicate a more homogeneous pri-miRNA cleavage by the Drosha complex during the formation of the 5’ end of mitomiRs. The obtained results can help to determine the role of the nucleotide signals in the origin, processing, and functions of the mitomiRs.
Exponential stability and stabilizability in mean square of large-scale stochastic systems

This paper deals with decomposition techniques for nonlinear large ndash scale stochastic systems which have the feature that the interactions between the various subsystems are nonadditive. We consider the system differential equations into a hierarchical form (see Vidyasagar §). We prove that the overall system is exponentially stable (respectively stabilizable) in mean square if and only if each of the subsystems is exponentially stable (respectively stabilizable) in mean square. Several examples are presented to illustrate the various theorems
Polarimetric Radar Observation Operator for a Cloud Model with Spectral Microphysics

AbstractThe radar observation operator for computation of polarimetric radar variables from the output of numerical cloud models is described in its most generic form. This operator is combined with the Hebrew University of Jerusalem cloud model with spectral microphysics. The model contains 7 classes of hydrometeors and each class is represented by size distribution functions in 43 size bins. The performance of the cloud model and radar observation operator has been evaluated for the case of a hailstorm in Oklahoma on 2 February 2009. It is shown that the retrieved fields of polarimetric radar variables at C and S microwave bands are generally consistent with results of observations. The relationship between microphysical and polarimetric signatures is illustrated.
Using Single-Cell RNA Sequencing and MicroRNA Targeting Data to Improve Colorectal Cancer Survival Prediction

Colorectal cancer has proven to be difficult to treat as it is the second leading cause of cancer death for both men and women worldwide. Recent work has shown the importance of microRNA (miRNA) in the progression and metastasis of colorectal cancer. Here, we develop a metric based on miRNA-gene target interactions, previously validated to be associated with colorectal cancer. We use this metric with a regularized Cox model to produce a small set of top-performing genes related to colon cancer. We show that using the miRNA metric and a Cox model led to a meaningful improvement in colon cancer survival prediction and correct patient risk stratification. We show that our approach outperforms existing methods and that the top genes identified by our process are implicated in NOTCH3 signaling and general metabolism pathways, which are essential to colon cancer progression.
On estimation of distribution temperature

Distribution temperature is a concept that assigns a temperature to radiation from an incandescent lamp, which has a relative spectral power distribution reasonably close to that of a blackbody radiator. Different least square estimation methods for determination of distribution temperature are compared. Their applicability is discussed with regard to uncertainties of the spectral irradiance data of incandescent lamps. Simulation results are analysed to support theoretical conclusions. Experimental results indicate that the estimation method currently recommended by CIE will lead to feasible results only if the relative uncertainties of spectral irradiance data over the chosen wavelength region can be presumed constant. Otherwise, the use of this estimation method weighted with the relative uncertainties is suggested.
The fundamental plane of cluster ellipticals.

It is shown that, for the Coma cluster ellipticals of normal surface brightness, there is a highly significant correlation between the residual from the D n -σ relation and effective surface brightness μ. The higher surface brightness ellipticals give systematically larger D n -σ distances. New, independent V-band photometry, when combined with the published velocity dispersion data, also show the same, highly significant correlation. This correlation arises because, for the Coma ellipticals, D n does not give a precise edge-on view of the fundamental plane. The Coma ellipticals with μ < 22.0 define a fundamental plane with no intrinsic scatter, indicating a remarkable degree of homogeneity
The Dietary Inflammatory Index Is Positively Associated with Colorectal Cancer Risk in a Chinese Case-Control Study

Diet may modulate chronic inflammation. The aim of this study is to investigate whether the dietary inflammatory index (DII®) was associated with the risk of colorectal cancer in a Chinese population. A case-control study was conducted from July 2010 to April 2019, in Guangzhou, China. A total of 2502 eligible cases were recruited along with 2538 age- (5-year interval) and sex-matched controls. Dietary data derived from a validated food frequency questionnaire were used to calculate the energy-adjusted DII (E-DII) scores. Odds ratios (ORs) and 95% confidence intervals (CIs) for colorectal cancer risk were estimated using unconditional logistic regression models. In this study, E-DII scores ranged from −5.96 (the most anti-inflammatory score) to +6.01 (the most pro-inflammatory score). A positive association was found between the E-DII and colorectal cancer risk, with the OR = 1.40 (95% CI 1.16, 1.68; Ptrend < 0.01) for the highest E-DII quartile compared with the lowest quartile after adjusting for potential confounders. When stratified based on cancer subsite, sex, body mass index, and smoking status, significant associations were not observed in women or underweight individuals. Results from this study confirmed that a higher E-DII score was associated with an increased risk of colorectal cancer in a Chinese population.
Galaxy morphology in rich clusters: Implications for the formation and evolution of galaxies

A study of the galaxy populations in 55 rich clusters is presented together with a discussion of the implications for the formation and/or evolution of different morphological types. A well-defined relationship is found between local galaxy density and galaxy type, which, in agreement with previous studies, indicates an increasing elliptical and SO population and a corresponding decrease in spirals with increasing density.
Weak shock structure on the basis of modified hydrodynamical equations

The structure of a normal shock wave is calculated on the basis of the hydrodynamics of fast processes [A. D. Khonkin, Fluid Mech. Sov. Res. 9, 93 (1980)] to investigate the validity of the theory for this classical problem. The analysis shows that the theory predicts the continuous shock profile to exist only for M≤1.27. The shock thicknesses and the asymmetry factors resulting from the Mott‐Smith method, the Navier–Stokes and the Burnett equations, and also from the experiments and simulations are compared to the present results for a gas of Maxwell molecules.
Analytic preconditioners for the electric field integral equation

Since the advent of the fast multipole method, large‐scale electromagnetic scattering problems based on the electric field integral equation (EFIE) formulation are generally solved by a Krylov iterative solver. A well‐known fact is that the dense complex non‐hermitian linear system associated to the EFIE becomes ill‐conditioned especially in the high‐frequency regime. As a consequence, this slows down the convergence rate of Krylov subspace iterative solvers. In this work, a new analytic preconditioner based on the combination of a finite element method with a local absorbing boundary condition is proposed to improve the convergence of the iterative solver for an open boundary. Some numerical tests precise the behaviour of the new preconditioner. Moreover, comparisons are performed with the analytic preconditioner based on the Calderòn's relations for integral equations for several kinds of scatterers. Copyright © 2004 John Wiley & Sons, Ltd.
The Singular Case in the Stability of Additive Functions

for some e > 0 and all x y ∈ Z. Those who do not know why this is called the singular case are invited to peruse the book [7]. Suffice it to recall here that, putting together theorems 1.1, 2.1, and 2.2 therein, one has the following starting result. Theorem 1 (Hyers–Rassias–Gajda). Let p = 1 be a fixed real number. Suppose ω Z → Y is a mapping (acting between Banach spaces) satisfying an estimate
Source image Target image Training Evaluation Trainable model Aligned image Sampled image Synthetic image

We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine, homography or thin-plate spline transformation, and estimating its parameters. The contributions of this work are three-fold. First, we propose a convolutional neural network architecture for geometric matching. The architecture is based on three main components that mimic the standard steps of feature extraction, matching and simultaneous inlier detection and model parameter estimation, while being trainable end-to-end. Second, we demonstrate that the network parameters can be trained from synthetically generated imagery without the need for manual annotation and that our matching layer significantly increases generalization capabilities to never seen before images. Finally, we show that the same model can perform both instance-level and category-level matching giving state-of-the-art results on the challenging PF, TSS and Caltech-101 datasets.
The Development of AgriVerse: Past, Present, and Future

Agricultural metaverse (AgriVerse) aims to optimize the production chain by saving costs, increasing efficiencies, and breaking information silos, in order to achieve sustainable agriculture. While AgriVerse is featured by the virtual-real interaction of the agriculture-related processes based on heterogeneous data, knowledge, and models, the link between AgriVerse and the intensively studied plant modeling is vague. This article presents briefly the research contents of plant modeling, analyzes the ongoing transition at the age of artificial intelligence (AI), and envisions future AgriVerse with the support of the agricultural foundation model, the decentralized agricultural organization (DAO) and the decentralized science (DeSci) of the plant model. Three AgriVerse application scenarios are presented. The opportunities and challenges of AgriVerse are discussed. This work is expected to identify the key research issues of AgriVerse and bring practitioners of diverse backgrounds together into the AgriVerse community.