Miracle-dz/UniFAR-FTUs huggingface dataset:
Volatility Asymmetry and Spillover Effects in Crude Oil Futures Market: Evidence from China

In order to study the international influence and function of domestic crude oil futures prices in depth, based on the daily data of 2018-2022, this paper uses Granger causality test, cointegration test, ECM model and several forms of GARCH model to make empirical research on the price correlation, volatility, asymmetry and risk spillover effects of domestic crude oil, Brent crude oil, WTI crude oil and Oman crude oil futures in the three major foreign crude oil markets. The study found that there is a Granger causal relationship and a cointegration relationship between domestic and foreign crude oil futures prices. There are interactions in the crude oil futures markets at home and abroad, and there are different fluctuation patterns in the short-term fluctuation process. There are asymmetries, leverage effects and spillover effects in the volatility of the four crude oil futures markets at home and abroad with different intensities. The bearish news of the three foreign markets is greater than the impact of the bullish news than that of the domestic one. There are risk spillover effects and volatility effects between domestic and the three foreign crude oil futures markets, and the domestic spillover effect on foreign crude oil is greater than the spillover effect on domestic crude oil from abroad. The conclusion is that the international influence of domestic crude oil futures prices is stronger than that of Omani crude oil, and weaker than Brent and WTI crude oil. The leverage effect of the three foreign markets is greater than that of China, and the leverage effect of the Oman crude oil futures market is the strongest. The asymmetry and spillover effect of fluctuations in the domestic and foreign crude oil futures markets lead to the risk and speculation of the three foreign markets being greater than that of the domestic one, and the speculative arbitrage through the domestic and foreign crude oil markets may cause huge market risks, and it is suggested that the internationalization of the domestic futures market needs more systems and mechanisms to support the construction.
Magnetic Shell Structure of 2D-Trapped Fermi Gases in the Flat-Band Lieb Lattices

We investigate the magnetic shell structure of repulsively interacting two-component Fermi gases trapped in a two-dimensional harmonic potential and loaded on the optical Lieb lattices. We employ the real-space dynamical mean-field theory (R-DMFT) to explicitly consider the trap potential in a self-consistent way. Computing the profiles of particle density and local magnetization across the lattice sites in the trap, we find that the incompressible core with ferrimagnetic ordering appears with the density plateau at the trap center, which is surrounded by the shell of the normal metallic phase. We examine the incompressibility of the core by adding more particles and creating the higher spin-population imbalance. While the core area expands from the outer shell with added particles and increased polarization, the excess particles are prohibited from going inside the core, and thus the density plateau is unchanged at the half-filling with the same magnetic ordering. In addition, we find that the feature of the phase separation differs with the sublattices, where the interstitial sites causing the flat band dispersion shows the signature of the abrupt transition in the density and magnetization at the boundary between the core and surrounding shells.
C10Pred: A First Machine Learning Based Tool to Predict C10 Family Cysteine Peptidases Using Sequence-Derived Features

Streptococcus pyogenes, or group A Streptococcus (GAS), a gram-positive bacterium, is implicated in a wide range of clinical manifestations and life-threatening diseases. One of the key virulence factors of GAS is streptopain, a C10 family cysteine peptidase. Since its discovery, various homologs of streptopain have been reported from other bacterial species. With the increased affordability of sequencing, a significant increase in the number of potential C10 family-like sequences in the public databases is anticipated, posing a challenge in classifying such sequences. Sequence-similarity-based tools are the methods of choice to identify such streptopain-like sequences. However, these methods depend on some level of sequence similarity between the existing C10 family and the target sequences. Therefore, in this work, we propose a novel predictor, C10Pred, for the prediction of C10 peptidases using sequence-derived optimal features. C10Pred is a support vector machine (SVM) based model which is efficient in predicting C10 enzymes with an overall accuracy of 92.7% and Matthews’ correlation coefficient (MCC) value of 0.855 when tested on an independent dataset. We anticipate that C10Pred will serve as a handy tool to classify novel streptopain-like proteins belonging to the C10 family and offer essential information.
Three-dimensional imaging characteristics of laser scan fluorescence microscopy--Two-photon excitation vs.single-photon excitation

The three-dimensional spatila-frequency bands of a laser scanning fluorescence microscope for both single-photon and two-photon excitations are theoretically derived. An approximate expression giving the lateral and longitudinal resolving power of the microscope is introduced. The parameters of the expression are the wavelenghts of the excitation laser and of the fluorescence; the number of the photons in the induced-fluorescence process; the size of the detection pinhole and the numerical aperture of the microscope objectives. A comparison between the three-dimensional spatial-frequency bands of a single-photon excitation lase-scanning microscope and a two-photon excitation one shows that the two methods have almost the same three-dimensional resolution
Polymorphism analysis of myosin 1H (G/A) and P561T (C/A) genes on class I, class II, and class III malocclusion

CONTEXT: Besides environmental factors, genetic factors play an important role in the etiology of malocclusion. Polymorphisms of the Myosin 1H gene in orofacial muscle fibers are thought to influence the growth and development of the mandible. Growth hormone receptors are present on the growth of cartilage, especially the condyle of the mandible. The polymorphisms of the growth hormone receptor have an effect on the growth and development of the mandible. The potential of the Myosin 1H and P561T genes as bioindicators in aiding diagnosis of malocclusion is quite good based on the available literature. However, until now there has been no research that has observed genetic analysis on polymorphism-based malocclusion of the Myosin 1H and P561T genes in the Indonesian population. AIMS: To determine the relationship between polymorphisms of Myosin 1H and P561T genes, towards the growth and development of the mandible in malocclusion cases. SETTINGS AND DESIGN: Subjects were patients aged 17--45 years old with skeletal malocclusions who were undergoing or were about to undergo orthodontic treatment at RSGM-FKG UI (Universitas Indonesia's Dental Hospital), with 50 people in each group. METHODS AND MATERIAL: Malocclusions were determined based on radiographic analysis of the initial cephalometry using the Stainer method. DNA samples were extracted from buccal swabs and blood cells in Class I and II malocclusion while nail clippings and hair follicles extracts were used in Class III malocclusion. DNA sequence amplification was carried out using Polymerase Chain Reaction, while Genetic Polymorphism Analysis of Myosin 1H and P561T genes was performed with Restriction Fragment Length Polymorphism. STATISTICAL ANALYSIS USED: Pearson Chi-Square was used to analyze the Myosin 1H gene, while the Fisher Exact Test was used to analyze the P561T gene. RESULTS: A relationship between Myosin 1H gene polymorphism and Class I, II, and III skeletal malocclusion was found. There was no correlation between P561T gene polymorphism and Class I, II, and III skeletal malocclusion. CONCLUSIONS: Myosin 1H gene polymorphism is one of the risk factors for Class I, II, and III malocclusion. Extraction of DNA from hair follicles gave good results in terms of DNA quality and was a relatively easier sampling method compared to blood cell purification and buccal swabs.
Adherence to Anti-tubercular Agents in DOTS Center in Western Nepal

INTRODUCTION: Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis and is one of the major public health problems in developing countries like Nepal. Despite the availability of effective tuberculosis treatment regimens, patients must take a combination of anti-tubercular drugs for at least six months and may endure numerous side effects, making treatment compliance exceedingly difficult to maintain. The primary objective of the study was to assess the adherence rate to anti-tubercular agents and to find the prevalence of adverse drug reactions to the anti-tubercular therapy. MATERIALS AND METHODS: This study was an observational study conducted in the DOTS centers of UCMS-TH, Bhairahawa, and Lumbini Provincial Hospital Butwal. A semi-structured questionnaire was used to collect data from 170 participants to determine the adherence rate to anti-tubercular therapy and the incidence of associated adverse drug reactions. Statistical Package for Social Sciences (SPSS Version 20) program was used to enter and analyze the data. The association between adherence and other variables was established using the Chisquare test. RESULTS: The adherence rate to anti-tubercular therapy was found to be 159 (93.5%). The major reasons for non-adherence include forgetfulness 8 (72.72%) followed by adverse effects 2 (18.18%) and transport difficulty in reaching the health facility 1 (9.1%). The prevalence of adverse drug reactions was 58 (34.12%) (27.1 - 41.2 at 95% Confidence Interval). Adherence was significantly associated with the experience of adverse effects, literacy, marital status, area of residence, and age of the participants. CONCLUSIONS: The adherence rate to anti-tubercular therapy was very high, which can be the primary determinant of tuberculosis treatment success.
Perceptions and Motivating Factors Regarding COVID-19 Vaccination in Latinx Older Adults in Chicago: A Local, Qualitative Perspective

Purpose Historically marginalized communities disproportionately impacted by the pandemic are demonstrating lower uptake of COVID-19 vaccines. To facilitate the development of culturally tailored, language concordant educational materials promoting COVID-19 vaccination, we first explored older Latinx adults’ awareness, attitudes, and beliefs about COVID-19 vaccines and factors involved in vaccination decisions within their communities. Patients and Methods Individual, semi-structured interviews were conducted with 15 participants who self-identified as Latinx/Hispanic, aged 50 and older, and living in Chicago. Eight interviews were conducted in English and seven in Spanish. Thematic analysis was used to analyze participants’ responses. Results Participants revealed four key factors influencing vaccination decisions: 1. protecting oneself and loved ones (against COVID-19 (n=14), or from perceived dangers of the vaccine (n=9)); 2. trust in authorities (trusting information (n=9), or worrying the vaccine is being manipulated (n=5)); 3. access and availability (gratitude to live in a country where vaccines are available (n=5), or fear of going to vaccination sites due to immigration and insurance status (n=4)); and 4. Employment and semblance of normalcy (vaccination to create opportunities (n=6), or concern about missing out due to side effects (n=9)). Conclusion Our findings illuminate key factors influencing decisions for COVID-19 vaccination among Latinx older adults in Chicago. Vaccination information aiming to increase vaccination rates among this important population may benefit from leveraging collective pronouns and spirituality, language concordance, low-tech options, building trust, and addressing insurance and immigration doubts. Next steps include developing educational materials based on these themes, followed by dissemination and evaluation. Lessons learned may be of interest to public health experts responding to the ongoing pandemic and other public health crises experienced by historically marginalized communities.
Study on the Influence of Borehole Water Content on Bolt Anchoring Force in Soft Surrounding Rock

In order to further reveal the influence mechanism of borehole water content on anchoring force in soft surrounding rock, three different research methods are used. Firstly, through theoretical analysis, it reveals that borehole water content will affect the cohesion of anchoring agent and then leads to the decrease of anchoring force. Secondly, through experimental analysis and numerical simulation of the influence of different boreholes water content on the anchoring force, it indicates that the borehole water content has a weakening effect on the mechanics characteristics of bolts significantly. When the borehole water content is less than 15mL, the influence of borehole water content on anchoring force is weak for a given borehole length. When the borehole water content is greater than 15mL, the anchoring force decreases greatly with the increase of borehole water content for a given borehole length and the decline of anchorage force is more than 30%. At the same time, through the experimental analysis, it reveals that the failure type of bolt in weak surrounding rock is the typical failure of anchorage force where the fracture goes far into the surrounding rock. )us, in practical operation, reasonably controlling the borehole water content (rate) within the critical value can improve the bolt support effect and reduce the support cost.
Advanced Computational Modeling Methods for Floating Offshore Wind Systems

approved: Bryony L. DuPont Floating offshore wind energy is anticipated to become a competitive source of renewable energy by the late 2020s, but the industry must reduce costs and uncertainties associated with the technology to do so. Identifying solutions to these problems frequently relies on computational modeling, which presents technical shortcomings limiting the versatility of the modeling results. This work presents two improvements that augment existing computational tools, allowing researchers to more accurately model floating offshore wind systems and reduce uncertainty. The first study presents a custom optimization algorithm to identify the relationship between cost and reliability for floating offshore wind farms using shared anchoring. The algorithm minimizes the added costs associated with failure by optimizing the strength of anchors for a case study of a large wind farm under simulated survival load conditions. The optimization algorithm merges a genetic algorithm with elements of Bayesian optimization to account for uncertainty from the probability of failure and the resulting repair costs. The second study presents a numerical model created by modifying the OpenFAST floating wind turbine simulation software. This numerical model solves for aerodynamic loading in a real-time hybrid simulation, allowing for integration with physical wave basin experiments with proper scaling and higher fidelity than computer simulations. Validation shows that the model accurately generates aerodynamic loads efficiently enough to be used in a real-time hybrid simulation setup. The study also identifies modifications that will allow for modeling of tower top elasto-servo dynamics in future work. ©Copyright by Michael C. Devin May 27, 2021 All Rights Reserved Advanced Computational Modeling Methods for Floating Offshore Wind Systems
INTINERANT MAGNETISM AND ITS CHARACTERIZATION IN HETEROGENEOUS SYSTEMS

This thesis describes calculations for the magnetic and electronic properties of a variety of systems that display itinerant magnetism. An early chapter considers the exact solution of a Hubbard Hamiltonian within the context of periodic boundary conditions; remaining calculations treat various heterogeneous transition-metal systems by means of a realistic tight-binding scheme, with single site, full orbital interactions treated self consistently. The latter method is shown to be consistently reliable: In each case where comparison with experiment or with state-of-the-art calculations could be made, there is agreement in the integrated properties, such as spin polarization, to within a few percent. Comparison of calculated density of states with photoemission data, although complicated by various many-body processes, again shows excellent 'agreement. This relatively inexpensive computational method is used to calculate the properties of complex systems which 1
Matrix Quantum Mechanics for Supermembrane on AdS_{7} x S^{4}

We explore the light-cone gauge formulation of a closed supermembrane on AdS_{7} x S^{4}. We obtain the action of matrix quantum mechanics with large N U(N) gauge symmetry for the light-cone supermembrane. We show that this action reproduces leading order terms in \alpha'-expansion of the non-abelian Born-Infeld action of N D0-branes propagating near the horizon of D4-branes. The matrix quantum mechanics obtained in this paper, therefore, has an interpretation as Matrix theory in the near-horizon of D4-branes.
A new method to analyze species abundances in space using gener- 1 alized dimensions 2

1 • Species-area relationships (SAR) and species abundance distributions (SAD) are among the most 2 studied patterns in ecology, due to their application in both theoretical and conservation issues. One 3 problem with these general patterns is that different theories can generate the same predictions, and for 4 this reason they can not be used to detect different mechanisms. 5 • A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to 6 the whole species abundance distribution. A generalized dimension (Dq) approach has been proposed 7 to study the scaling of SAD, but there has been no evaluation of the ability of this pattern to detect 8 different mechanisms. 9 • An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new 10 way to study scaling of SAD using a spatial version of RAD: the species-rank surface (SRS), which can 11 be analyzed using Dq. Thus there is an old Dq based on SAR (D q ), and a new one based on SRS 12 (D q ). I perform spatial simulations to relate both Dq with SAD, spatial patterns and number of 13 species. Finally I compare the power of both Dq, SAD, SAR exponent, and the fractal information 14 dimension to detect different community patterns using a continuum of hierarchical and neutral spatially 15 explicit models. 16 • The SAD, D q and D q all had good performance in detecting models with contrasting mechanisms. 17 D q had a better fit to data and a strong ability to compare between hierarchical communities where 18 the other methods failed. The SAR exponent and information dimension had low power and should not 19 be used. 20 • SRS and D q could be an interesting addition to study community or macroecological patterns. 21
DETECTION OF FEMUR FRACTURES IN X-RAY IMAGES

Many people suffer from hip fractures, especially people suffering from osteoporosis. Doctors rely on radiographs, i.e., x-ray images, to establish the precise nature of a fracture. An automated fracture detection system can assist the doctor by performing the first examination to screen out the easier cases, leaving a small number of difficult cases and the second confirmation to the doctors. This thesis outlines a fracture detection system and focus on measuring the neck-shaft angle of the femur. The accuracy of using the neck-shaft angle for determining femur fractures is also tested.
GRAPHICAL ANALYSIS AND EXPERIMENTAL EVALUATION OF SACCHAROMYCES CEREVISIAE PTRK1I2 AND PBMH'12 PROMOTER REGION

We designed a simple graphical presentation for the results of a transcription factor (TF) pattern matching analysis. The TF analysis algorithm utilized known sequence signature motifs from several databases. The graphical presentation enabled a quick overview of potential TF binding sites, their frequency and spacing on both DNA strands and thus straight forward identification of promising candidates for further experimental investigations. The developed tool was applied on in total four Saccharomyces cerevisiae gene promoter regions. The selected differentially expressed genes belong to functionally different families and encode duplicate functions, TRKI and TRK2 as ion transporters and BMHI and BMH2 as multiple regulators. Output evaluation revealed a number of TFs with promising differences in the promoter regions of each gene pair. Experimental investigations were performed by using corresponding TF yeast mutants for either phenotypic analysis of ion transport mediated growth or expression analysis of BMHl,2 genes. Upon phenotypic testing one TF mutant exhibited severely impaired growth under non-permissive conditions. This TF, Mot3p was identified as of most abundant potential binding sites and distinctive patterns among the TRK promoter regions.
A Bimodal Gaussian Inhomogeneous Poisson Algorithm for Bike Number Prediction in a Bike-Sharing System

Due to the rapid development of the sharing economy, shared bikes have become one of the most popular and convenient traveling tools in intelligent transport systems. Aiming to save the time spent on waiting for or searching bikes at bike stations, the operators of bike-sharing systems need to dynamically dispatch bikes. Predicting the number of bikes for each station can help to optimize the repository of bikes. The usage of bikes is affected by several uncertain factors, so bike number prediction becomes a challenging and difficult problem. To manage this problem, we propose an algorithm called bimodal Gaussian inhomogeneous Poisson (BGIP) to predict the number of bikes. The BGIP includes three steps. First, the inhomogeneous Poisson process is adopted to describe the process that people arrive at a bike station to pick up or return bikes. Second, the bimodal Gaussian function is used to describe the intensity function of inhomogeneous Poisson process. In order to dynamically uncover the changing trend in the usage state of bikes, we propose a method to measure the influences of external factors on the usage of bikes. Third, the number of bikes is predicted by calculating the mean usage of bikes on the basis of checking-out and checking-in sequences. Experiments demonstrated that our algorithm outperformed the baseline algorithms in solving the bike prediction problem: accurately predicting the number of bikes and determining whether there is at least one bike available at a bike station.
chain controls CD70 transport in dendritic cells and thereby regulates CD8+ T cell priming

CD70 is a Tumor Necrosis Factor family member that is expressed by mature dendritic cells and provides T cell costimulatory signals. Strict regulation of CD70 cell surface expression is essential to maintain T cell homeostasis and immunological tolerance. We report here that the Invariant chain (Ii, CD74), a well-known chaperone for major histocompatibility complex (MHC) class II molecules, regulates transport and function of CD70. In cells lacking the MHC class II presentation pathway, CD70 was transported to the plasma membrane, but co-expression of Ii directed CD70 towards late endosomes/lysosomes. In cells with features of professional antigen presenting cells, CD70 and endogenous Ii were co-transported to the late endosomal/lysosomal MHC class II compartment. Fluorescence resonance energy transfer studies documented a physical interaction between the two molecules. In activated dendritic cells, Ii controlled the kinetics and level of CD70 cell surface expression and thereby dictated the extent of CD8+ T cell clonal expansion. We propose that directional and temporal control of CD70 cell surface expression by Ii serves to set the threshold for CD8+ T cell priming.