Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensitivity of WRF Forecasts for South Florida to Initial Conditions

Abstract This study presents results from an experiment conducted to measure the impact of locally initializing a numerical weather prediction model on that model’s ability to predict precipitation and other surface parameters. The study consisted of quantifying the impact of initializing the Weather and Research Forecast (WRF) model with the Advanced Weather Interactive Processing System (AWIPS) Local Analysis and Prediction System (LAPS) diagnostic analyses. In the experiment, WRF was run for two different initial times: 0600 and 1800 UTC. For each initial time, the model was run twice, once using LAPS for the initial conditions, and once using the North American Mesoscale model (NAM; also known as the Eta Model at the time of the experiment). The impact of the local LAPS initialization on the model forecast of surface parameters is presented. Additionally, the model’s quantitative precipitation forecast (QPF) skill is compared for three different model configurations: 1) WRF initialized with LAPS, 2) W.
The Role of Gender in Moderating The Effect of Teachers Empathy, Reputation and System Quality on Student Satisfaction Online Learning Program

Over the past few years, technology adoption in education has increased significantly. Most universities like to invest in modern forms of learning, therefore it can be seen for the rapid growth of e-learning. This study aims to determine a comprehensive model in determining online learning student satisfaction during the Covid-19 pandemic with the role of gender as moderation. The sample in this study was 239 Binus Online Learning students. The data analysis technique in this study used a structural equation model (Structural Equation Modeling, SEM) with SmartPLS 3 software. The results of this study found that instructor empathy, higher education reputation, and system quality had a significant influence on student satisfaction, especially in the context of online learning on Binus Online Learning which simply used high technology to support the Learning Management System. Gender has no role in moderating exogenous to endogenous constructs in this research model, so it can be said that the technology used in Binus Online Learning has high student satisfaction because the system is good enough to carry out online learning.
The Lattice Molecular Automaton(LMA): A Simulation System for Constructive Molecular Dynamics

Molecular self-assembly is frequently encountered in biochemical systems generating higher order structures with well-defined functionalities. However, the driving forces underlying these processes are not well understood. The Lattice Molecular Automaton (LMA) is a deterministic computational tool suitable for simulation of self-organization processes in large scale, molecular systems. This paper introduces the basic computational concepts needed to formulate molecular dynamics and self-assembly in a discrete field, cellular automaton environment: Molecular objects are encoded as data structures on a 2D triangular lattice. Propagating force particles together with kinetic and potential energy terms define simulation objects that specify molecular dynamics and force field properties. As an example, the simulation of polymer dynamics in an aqueous environment is shown. In this paper we focus on the mathematical and algorithmic formulation of a variety of intra- and intermolecular interactions. Thermodynamical characteristics together with a variety of other physico-chemical properties of the LMA are discussed in detail in Ref. 1.
Triglyceride-glucose index levels in patients with Klinefelter syndrome and its relationship with endothelial dysfunction and insulin resistance: a cross-sectional observational study

ABSTRACT Objectives: This study aimed to investigate the triglyceride-glucose (TyG) index, which is a simple surrogate marker of insulin resistance that is associated with various cardiometabolic diseases, in patients with Klinefelter syndrome (KS). Subjects and methods: A total of 30 patients with KS (mean age: 21.53 ± 1.66 years) and 32 healthy controls (mean age: 22.07 ± 1.01 years) were included in the study.The clinical and laboratory parameters,TyG index, asymmetric dimethylarginine (ADMA) level, homeostatic model assessment of insulin resistance (HOMA-IR) score, and high-sensitivity C-reactive protein level were measured in patients with KS and healthy subjects. Results: Patients with KS had higher HOMA-IR score (p = 0.043), ADMA levels (p < 0.001), and TyG index (p = 0.031) and lower high-density lipoprotein cholesterol levels (p < 0.001) than healthy subjects. TyG index was positively correlated with plasma ADMA (r = 0.48, p < 0.001) and HOMA-IR (r = 0.36, p = 0.011). Multivariate analyses showed that total testosterone level (β = −0.44, p = 0.001) and TyG index (β = 0.29, p = 0.045) were independent determinants of plasma ADMA levels. Conclusion: Patients with KS had higher TyG indices than healthy subjects. Moreover, TyG index was independently associated with endothelial dysfunction in patients. TyG index may be a practical and useful measure to show the increased endothelial dysfunction in patients with KS.
Antiviral RNAi Response in Culex quinquefasciatus-Derived HSU Cells

Culex spp. mosquitoes are important vectors of viruses, such as West Nile virus, Eastern equine encephalitis virus and Rift valley fever virus. However, their interactions with innate antiviral immunity, especially RNA interference (RNAi), are not well known. Most research on RNAi pathways in mosquitoes is focused on the tropical vector mosquito Aedes aegypti. Here, we investigated the production of arbovirus-specific small RNAs in Cx. quinquefasciatus-derived HSU cells. Furthermore, by silencing RNAi-related proteins, we investigated the antiviral role of these proteins for two different arboviruses: Semliki Forest virus (SFV) and Bunyamwera orthobunyavirus (BUNV). Our results showed an expansion of Ago2 and Piwi6 in Cx. quinquefasciatus compared to Ae. aegypti. While silencing Ago2a and Ago2b increased BUNV replication, only Ago2b showed antiviral activity against SFV. Our results suggest differences in the function of Cx. quinquefasciatus and Ae. aegypti RNAi proteins and highlight the virus-specific function of these proteins in Cx. quinquefasciatus.
The Integrated spectra of nearby galaxies: General properties and emission line spectra

This paper presents the first results from a survey of the integrated spectra of 90 nearby galaxies. Intermediate- and low-resolution spectrophotometry over the 3650-7000 A range has been used to compile a spectral atlas of galaxies (published in a companion paper) and to investigate the systematic behavior of the emission-line spectra in normal and peculiar galaxies. The data are especially useful as a comparison sample for spectroscopic survey of more distant galaxies.
UAS-Based Real-Time Detection of Red-Cockaded Woodpecker Cavities in Heterogeneous Landscapes Using YOLO Object Detection Algorithms

In recent years, deep learning-based approaches have proliferated across a variety of ecological studies. Inspired by deep learning’s emerging prominence as the preferred tool for analyzing wildlife image datasets, this study employed You Only Look Once (YOLO), a single-shot, real-time object detection algorithm, to effectively detect cavity trees of Red-cockaded Woodpeckers or RCW (Dryobates borealis). In spring 2022, using an unmanned aircraft system (UAS), we conducted presence surveys for RCW cavity trees within a 1264-hectare area in the Sam Houston National Forest (SHNF). Additionally, known occurrences of RCW cavity trees outside the surveyed area were aerially photographed, manually annotated, and used as a training dataset. Both YOLOv4-tiny and YOLOv5n architectures were selected as target models for training and later used for inferencing separate aerial photos from the study area. A traditional survey using the pedestrian methods was also conducted concurrently and used as a baseline survey to compare our new methods. Our best-performing model generated an mAP (mean Average Precision) of 95% and an F1 score of 85% while maintaining an inference speed of 2.5 frames per second (fps). Additionally, five unique cavity trees were detected using our model and UAS approach, compared with one unique detection using traditional survey methods. Model development techniques, such as preprocessing images with tiling and Sliced Aided Hyper Inferencing (SAHI), proved to be critical components of improved detection performance. Our results demonstrated the two YOLO architectures with tiling and SAHI strategies were able to successfully detect RCW cavities in heavily forested, heterogenous environments using semi-automated review. Furthermore, this case study represents progress towards eventual real-time detection where wildlife managers are targeting small objects. These results have implications for more achievable conservation goals, less costly operations, a safer work environment for personnel, and potentially more accurate survey results in environments that are difficult using traditional methods.
Understanding Mentors’ Engagement in OSS Communities via Google Summer of Code

A constant influx of newcomers is essential for the sustainability and success of open source software (OSS) projects. However, successful onboarding is always challenging because newcomers face various initial contributing barriers. To support newcomer onboarding, OSS communities widely adopt the mentoring approach. Despite its significance, previous mentoring studies tend to focus on the newcomer's perspective, leaving the mentor's perspective relatively under-studied. To better support mentoring, we study the popular Google Summer of Code (GSoC). It is a well-established global program that offers stipends and mentors to students aiming to bring more student developers into OSS development. We combine online data analysis, an email survey, and semi-structured interviews with the GSoC mentors to understand their motivations, challenges, strategies, and gains. We propose a taxonomy of GSoC mentors’ engagement with four themes, ten categories, 34 sub-categories, and 118 codes, as well as the mentors’ attitudes toward the codes. In particular, we find that mentors participating in GSoC are primarily intrinsically motivated, and some new motivators emerge adapting to the contemporary challenges, e.g., sustainability and advertisement of projects. Forty-one challenges and 52 strategies associated with the program timeline are identified, most of which are first time revealed. Although almost all the challenges are agreed upon by specific mentors, some mentors believe that several challenges are reasonable and even have a positive effect. For example, the cognitive differences between mentors and mentees can stimulate new perspectives. Most of the mentors agreed that they had adopted these strategies during the mentoring process, but a few strategies recommended by the GSoC administration were not agreed upon. Self-satisfaction, different skills, and peer recognition are the main gains of mentors to participate in GSoC. Eventually, we discuss practical implications for mentors, students, OSS communities, GSoC programs, and researchers.
Design of modulo 2n-1 multiplier Based on Radix-8 Booth Algorithm using Residue Number System

Modular arithmetic operations (inversion, multiplication and exponentiation) are used in several cryptography applications. A special moduli set of forms {2 n -1, 2 n , 2 n +1} are preferred over the generic moduli due to the ease of hardware implementation of modulo arithmetic functions as well as system-level inter-modulo operations, such as RNS-to-binary conversion and sign detections. With this precept, a family of radix-8 Booth encoded modulo 2 n -1 multipliers, with delay adaptable to the RNS multiplier delay, is proposed. The first-ever family of low-area and low-power radix-8 Booth encoded modulo 2 n - 1 multiplier whose delay can be tuned to match the RNS delay closely has been proposed in this paper. A CSA tree with end-around-carry addition for accumulation of redundant partial products and a Sklansky parallel-prefix structure has also been implemented.
The acquisition of verbal morphology in Cochlear Implanted and Specific Language Impaired children

The cochlear implant (CI) gives severely hearing impaired to profoundly deaf children access to auditory speech input and consequently stimulates their oral language development. However, speech perception with a CI is still not optimal. Therefore, these children develop oral language based on reduced auditory speech input. This dissertation aims at enhancing our knowledge of whether a CI provides sufficient access to auditory speech input to acquire verbal morphology. It takes a new perspective regarding the research on morphology acquisition in CI children. The outcomes of the children under investigation are not only compared to those of their normal hearing peers, but also to those of their specific language impaired (SLI) peers. The latter group is known to be particularly delayed in their acquisition of verbal morphology. One of the major findings of this dissertation is that CI children outperform their SLI peers in the production of verbal morphology. Remarkably, they are even able to catch up with their normal hearing peers. Nevertheless, their spontaneous speech samples contain more verb inflection errors as compared to similar samples from normal hearing peers. In this respect CI children compare to their SLI peers. The results of the CI children are further analyzed as a function of their age at implantation and hearing age. Additional emphasis is given to the role of perceptual salience in the acquisition of morphology.
Repurposing β-Lactams for the Treatment of Mycobacterium kansasii Infections: An In Vitro Study

Mycobacterium kansasii (Mkn) causes tuberculosis-like lung infection in both immunocompetent and immunocompromised patients. Current standard therapy against Mkn infection is lengthy and difficult to adhere to. Although β-lactams are the most important class of antibiotics, representing 65% of the global antibiotic market, they have been traditionally dismissed for the treatment of mycobacterial infections, as they were considered inactive against mycobacteria. A renewed interest in β-lactams as antimycobacterial agents has shown their activity against several mycobacterial species, including M. tuberculosis, M. ulcerans or M. abscessus; however, information against Mkn is lacking. In this study, we determined the in vitro activity of several β-lactams against Mkn. A selection of 32 agents including all β-lactam chemical classes (penicillins, cephalosporins, carbapenems and monobactams) with three β-lactamase inhibitors (clavulanate, tazobactam and avibactam) were evaluated against 22 Mkn strains by MIC assays. Penicillins plus clavulanate and first- and third-generation cephalosporins were the most active β-lactams against Mkn. Combinatorial time-kill assays revealed favorable interactions of amoxicillin–clavulanate and cefadroxil with first-line Mkn treatment. Amoxicillin–clavulanate and cefadroxil are oral medications that are readily available, and well tolerated with an excellent safety and pharmacokinetic profile that could constitute a promising alternative option for Mkn therapy.
Heterogeneous Nucleation in Protein Crystallization

Protein crystallization was first discovered in the nineteenth century and has been studied for nearly 200 years. Protein crystallization technology has recently been widely used in many fields, such as drug purification and protein structure analysis. The key to successful crystallization of proteins is the nucleation in the protein solution, which can be influenced by many factors, such as the precipitating agent, temperature, solution concentration, pH, etc., among which the role of the precipitating agent is extremely important. In this regard, we summarize the nucleation theory of protein crystallization, including classical nucleation theory, two-step nucleation theory, and heterogeneous nucleation theory. We focus on a variety of efficient heterogeneous nucleating agents and crystallization methods as well. The application of protein crystals in crystallography and biopharmaceutical fields is further discussed. Finally, the bottleneck of protein crystallization and the prospect of future technology development are reviewed.
Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning

Digital twins have revolutionized manufacturing and maintenance, allowing us to interact with virtual yet realistic representations of the physical world in simulations to identify potential problems or opportunities for improvement. However, traditional digital twins do not have the ability to communicate with humans using natural language, which limits their potential usefulness. Although conventional natural language processing methods have proven to be effective in solving certain tasks, neuro-symbolic AI offers a new approach that leads to more robust and versatile solutions. In this paper, we propose neuro-symbolic reasoning (NSR)—a fundamental method for interacting with 3D digital twins using natural language. The method understands user requests and contexts to manipulate 3D components of digital twins and is able to read maintenance manuals and implement installations and removal procedures autonomously. A practical neuro-symbolic dataset of machine-understandable manuals, 3D models, and user queries is collected to train the neuro-symbolic reasoning interaction mechanism. The evaluation demonstrates that NSR can execute user commands accurately, achieving 96.2% accuracy on test data. The proposed method has industrial importance since it provides the technology to perform maintenance procedures, request information from manuals, and serve as a tool to interact with complex virtual machinery using natural language.
Four New Species of Russula Subsection Sardoninae from China

Four new species of Russula subsection Sardoninae from northern and southwestern China under coniferous and deciduous trees are proposed as R. begonia, R. photinia, R. rhodochroa, and R. rufa. Illustrations and descriptions of R. gracillima, R. leucomarginata, R. roseola, and the above four new species are provided based on evidence of morphological characters and phylogenetic analyses of the internal transcribed spacer (ITS), as well as the multi-locus of mtSSU, nLSU, rpb1, rpb2 and tef1-α. The relationships between these new species and allied taxa are discussed.
Plasma Troponins Identify Patients with Very Low-Risk Acute Pulmonary Embolism

Introduction: Although in the non-vitamin K oral anticoagulants (NOAC) era majority of low-risk acute pulmonary embolism (APE) patients can be treated at home, identifying those at very low risk of clinical deterioration may be challenging. We aimed to propose the risk stratification algorithm in sPESI 0 point APE patients, allowing them to select candidates for safe outpatient treatment. Materials and methods: Post hoc analysis of a prospective study of 1151 normotensive patients with at least segmental APE. In the final analysis, we included 409 sPESI 0 point patients. Cardiac troponin assessment and echocardiographic examination were performed immediately after admission. Right ventricular dysfunction was defined as the right ventricle/left ventricle ratio (RV/LV) > 1.0. The clinical endpoint (CE) included APE-related mortality and/or rescue thrombolysis and/or immediate surgical embolectomy in patients with clinical deterioration. Results: CE occurred in four patients who had higher serum troponin levels than subjects with a favorable clinical course (troponin/ULN: 7.8 (6.4–9.4) vs. 0.2 (0–1.36) p = 0.000). Receiver operating characteristic (ROC) analysis showed that the area under the curve for troponin in the prediction of CE was 0.908 (95% CI 0.831–0.984; p < 0.001). We defined the cut-off value of troponin at >1.7 ULN with 100% PPV for CE. In univariate and multivariate analysis, elevated serum troponin level was associated with an increased risk of CE, whereas RV/LV > 1.0 was not. Conclusions: Solely clinical risk assessment in APE is insufficient, and patients with sPESI 0 points require further assessment based on myocardial damage biomarkers. Patients with troponin levels not exceeding 1.7 ULN constitute the group of “very low risk” with a good prognosis.
Cessation of Face Mask Use after COVID-19 Vaccination in Patients with Diabetes: Prevalence and Determinants

Studies on the cessation of face mask use after a COVID-19 vaccine in patients with diabetes are not available, despite their greater predisposition to complications. We estimated the prevalence of cessation of face mask use after receiving the COVID-19 vaccine in patients with diabetes and identified which factor was most strongly associated with non-use. This was a cross-sectional study in patients with diabetes 18–70 years with at least one dose of vaccine against COVID-19 (n = 288). Participants were asked to respond face-to-face to a questionnaire in a primary care center. Descriptive statistics, chi-square tests, and multivariate binary logistic regression were used for analyzing the association between vulnerability, benefits, barriers, self-efficacy, vaccine expectations (independent variables), and cessation of use (dependent variable), controlling for sociodemographic, smoking, medical, vaccine, and COVID-19 history. The prevalence of cessation of face masks was 25.3% (95% CI 20.2, 30.5). Not feeling vulnerable to hospitalization increased the odds of non-use (adjusted OR = 3.3, 95% CI 1.2, 8.6), while perceiving benefits did the opposite (adjusted OR = 0.4, 95% CI 0.2, 0.9). The prevalence was low, and only two factors were associated with the cessation of face mask use after COVID-19 vaccination in patients with type 2 diabetes.
On Uncertainty Principle for the Morse - Sard Theorem

We prove a bridge theorem that includes the classical Morse--Sard Theorem on critical values and its previous elegant extensions obtained by Dubovitskii and Federer as particular cases. Intuitively, the sense of this bridge theorem is very close to the~uncertainty principle in theoretical physics: the more precise is the information we receive on measure of the image of the critical set, the less precisely the preimages are described, and vice versa. The result is new even for the classical C^k-case; similar results are established for the Holder and Sobolev classes of mappings with minimal integrability assumptions that guarantee in general only the continuity (not everywhere differentiability) of a~mapping. The proofs of the most results are based on our previous joint papers with J.~Bourgain and J.Kristensen (2013, 2015). We also crucially use very deep Y. ~Yomdin's entropy estimates of near critical values for polynomials (based on algebraic geometry tools). These results were useful for the solution of the so-called Leray's problem in mathematical fluid mechanics (see, e.g., Korobov et al., Ann. of Math., vol.181, (2015), no.2, 769-807 )