Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on end-to-end animal behavior speech classification based on Wav2Vec2.0

There are many fields involved in human research on animal vocal behavior, such as biomedical science, ecology, and behavioral science. Understanding animal language and behavior remains a major focus of scientific research, and many efforts are being made in this direction. With the development of artificial intelligence technology, deep learning has gradually become a major method for humans to understand animal behavior sound. This article aims to develop an end-to-end animal behavior sound classification model using Wav2Vec2.0 (W2VCM). By combining the Wav2Vec2.0 model with the CatMeows dataset, a pre-trained model is obtained for extracting speech features and performing animal behavior sound classification tasks. Experimental results demonstrate that W2VCM achieves higher accuracy than six other deep learning models tested, both on the original and re-divided datasets. The accuracy of W2VCM reached 97.97%, 2.03% higher than the best result of other models on the original dataset, and 3.13% higher on the re-divided dataset.
Study on the types of abuse in young couples as a function of sex

This study analyses the types of violence that can occur in intimate partner relationships among young people and their self-perception of abuse. For this purpose, we have used a survey-type methodology, with a quantitative approach. Participants were selected by means of non-probabilistic convenience and consisted of students enrolled in different degree and postgraduate courses in the Faculty of Education Sciences of the University of Granada (Spain). The sample consisted of 323 students, with a mean age of 23.8 years (SD = 5.2). Statistical and inferential tests were carried out with the data obtained using the SPSS V26 data analysis programme. The results show that the type of maltreatment most suffered, at some time by the sample participants, is emotional maltreatment, physical maltreatment, and psychological maltreatment. By comparing the means obtained, we can conclude that sex did not influence the violence suffered by young couples, which gives it a bidirectional character.
Antihyperglycemic, Neuropharmacological, Cytotoxic, Anticoagulant, and Anti-inflammatory Pharmacological Evaluations of Vernonia elaeagnifolia DC Leaves Secondary Bioactive Metabolites

The current investigation was carried out to confirm the antihyperglycemic, cytotoxic, neuropharmacological, anticoagulant, and anti-inflammatory effects of the ethanolic extract of Vernonia elaeagnifolia leaves in different experimental models. In the oral glucose tolerance test, the plant extract demonstrated significant (p < 0.05) antihyperglycemic activity by reducing the elevated blood glucose level in mice at both doses (250 mg/kg and 500 mg/kg) when compared to the control groups. The crude ethanolic leaf extract, however, didn’t afford to block the α-glucosidase enzyme up to 0.5 mg/mL. The experimental mice showed a noticeable (p <0.001) decrease in locomotor and exploratory activities in the hole cross and open field tests, as well as head dipping in the hole-board test model in the neuropharmacological activity assay at both doses (250 mg/kg and 500 mg/kg). The extracts also showed cytotoxic activity in a brine shrimp lethality bioassay with an LC50 of 91.929 μg/mL and showed significant concentration-dependent anticoagulant activity (p<0.001). Moreover, the extract (10–500 mg/kg) caused a significant (P<0.01 – 0.001) dose-dependent reduction of inflammation induced in rats by using two different models: formalin-induced paw edema and egg-albumin-induced paw edema. From the above results, the crude extract of V. elaeagnifolia DC leaves have significant pharmacological potential in different in vitro and in vivo study model. So, it could be a source of a substance for isolating lead that could be used to treat several diseases.
Iron Deficiency Might Impair the Recovery of Left Ventricular Function after Surgical Revascularization in Diabetic Patients: A Retrospective Study

Background : Iron deficiency (ID) is one of the most common micronutrient deficiencies affecting public health. Studies show that ID affects the prognosis of patients with heart disease, including heart failure, coronary artery disease and myocardial infarction. However, there is limited information regarding the impact of ID on patients undergoing cardiac surgery. This study aimed to evaluate the influence of preoperative ID on the prognosis of type 2 diabetes mellitus (T2DM) patients undergoing coronary artery bypass grafting (CABG). Methods : In the Glycemic control using mobile-based intervention in patients with diabetes undergoing coronary artery bypass to promote self-management (GUIDEME) study, patients with T2DM undergoing CABG were prospectively recruited. In this study, only those patients with preoperative iron metabolism results were enrolled. Patients were grouped based on the presence of preoperative ID. The primary endpoint was defined as the significant improvement of follow-up ejection fraction (EF) compared to postoperative levels (classified according to the 75th percentile of the change, and defined as an improvement of greater than or equal to 5%). Univariable logistic regression was performed to explore the potential confounders, followed by multiple adjustment. Results : A total of 302 patients were enrolled. No deaths were observed during the study period. A higher incidence of the primary endpoint was observed in the ID group (25.4% vs 12.9%, p = 0.015). The postoperative and follow-up EF were similar beween the two groups. In the regression analysis, ID was noticed to be a strong predictor against the significant improvement of EF in both univariable (odds ratio [OR]: 0.44, 95% confidence interval [CI]: 0.22–0.86, p = 0.017) and multivariable (OR: 0.43, 95% CI: 0.24–0.98, p = 0.043) logistic regression. In the subgroup analysis, ID was a predictor of significant improvement of EF in age ≤ 60 years, male, EF ≤ 60%, and on-pump CABG patients. Conclusions : In T2DM patients undergoing CABG, ID might negatively affect the early recovery of left ventricular systolic function in terms of recovery of EF 3–6 months after surgery, especially in patients age ≤ 60 years, males, EF ≤ 60% and in those undergoing on-pump CABG.
Dynamics and Control of a Tensegrity System in Low-Earth Orbit

Low-Earth orbit (LEO) is an environment where the effects of the Earth’s gravitational field are still strong enough to produce potentially detrimental distortions of large flexible structures. One such example is a tensegrity system, which is held in balance by an assortment of interconnected bars and cables to form a self-standing but ultimately flexible structure. This thesis derives the dynamics of such a structure in the gravity field of LEO, including the distortion of the structure due to the motions of the individual bars and the changes in attitude of the spacecraft. Methods of linear control are discussed for minimizing or controlling these gravity-induced distortions. Funding for this research was provided by the Aerospace Department at Virginia Tech, the College of Engineering, the Multicultural Academic Opportunities Program, and the Virginia Space Grant Consortium. This work was also supported by the National Science Foundation under the grant CMMI-0952558. Dynamics and Control of Tensegrity Systems in Low-Earth Orbit Maria del Carmen Rye GENERAL AUDIENCE ABSTRACT Tensegrity is the name given to a system of interconnected bars and tendons that can form a flexible self-standing structure. Its flexibility is due to the ability of the bars to move nearindependent to each other, movement that can be caused by controlled tension forces in the tendons or external forces such as gravity. However, a balance of sorts must be maintained if a tendon were to go slack, the entire structure could become unstable and collapse on itself. This thesis looks at placing a tensegrity structure in orbit around the Earth. As a spacecraft’s orbit is moved further away from the Earth, the strength of the Earth’s gravity field lessens. Ideally, such a flexible structure would be placed far enough away from the Earth so that the gravity field would have too weak an impact on its individual elements to cause major distortions. However, the author recognizes that altitudes below 2,000 km, where the Earth’s gravity field is still very prevalent, are the most common altitudes used by orbiting spacecraft today. The goal of this thesis is to analyze the distortions of the tensegrity structure at these lower altitudes, and also look at methods for controlling these distortions. Funding for this research was provided by the Aerospace Department at Virginia Tech, the College of Engineering, the Multicultural Academic Opportunities Program, and the Virginia Space Grant Consortium. This work was also supported by the National Science Foundation under the grant CMMI-0952558. iv
A Simplified Dynamic Strength Analysis of Cardboard Packaging Subjected to Transport Loads

The article presents a simplified method for determining the strength of corrugated board packaging subjected to dynamic transport loads. The proposed algorithm consists of several calculation steps: (1) a static analysis of the compressive strength of the package, (2) an analysis of random vibrations in the frequency domain used to determine the resonance frequencies and (3) a dynamic analysis of the package loaded with computed resonant frequencies. For this purpose, numerical models of the static compression test of the packaging before and after the dynamic analysis of the package subjected to general transport loads were developed. In order to validate the model, laboratory packaging compression tests were also performed for samples of boxes using three-layer cardboard. Due to this, it was possible to verify the numerical simulation results of the compression tests for several box geometries. This, in turn, allowed for the development of a method based on dynamic and post-dynamic (static) numerical analyses, permitting a high-accuracy determination of the resistance of the selected packaging to vibrations and dynamic loads. The results of the (experimentally validated) numerical analysis proved the usefulness of the simplified method presented herein for precise estimation of the load capacity of various packages dynamically loaded during transport.
TOPOLOGICAL ASYMPTOTIC ANALYSIS FOR A CLASS OF QUASILINEAR ELLIPTIC EQUATIONS

Topological asymptotic expansions for quasilinear elliptic equations have not been studied yet. Such questions arise from the need to apply topological asymptotic methods in shape optimization to nonlinear elasticity equations as in imaging to detect sets with codimensions ≥ 2 (e.g. points in 2D or segments in 3D). Our main contribution is to provide topological asymptotic expansions for a class of quasilinear elliptic equations, perturbed in non-empty subdomains. The obtained topological gradient can be split into a classical linear term and a new term which accounts for the non linearity of the equation. With respect to topological asymptotic analysis, moving from linear equations onto quasilinear ones requires to heavily revise the implemented methods and tools. By comparison with the steps carried out to obtain such expansions with the Laplace equation, the core issue for a quasilinear equation lies in the ability to defi ne the variation of the direct state at scale 1 in R^N . Accordingly we build dedicated weighted quotient Sobolev spaces, which semi-norms encompass both the L^p norm and the L^2 norm of the gradient in R^N. Then we consider an appropriate class of quasilinear elliptic equations, to ensure that the problem de ning the direct state at scale 1 enjoys a combined p and 2 ellipticity property. The needed asymptotic behavior of the solution of the nonlinear interface problem in R^N is then proven. An appropriate duality scheme is set up between the direct and adjoint states at each stage of approximation.
Serologic Response and Safety after a Third Dose of the COVID-19 BNT162b2 Vaccine in Patients with Inflammatory Bowel Diseases

Vaccines are pivotal for control of the coronavirus disease (COVID-19) pandemic. Patients with inflammatory bowel diseases (IBDs) treated with antitumor necrosis factor (TNF)-α have lower serologic response after two COVID-19 vaccine doses. Data regarding a third vaccine dose are scarce. An Israeli multicenter prospective observational study recruited 319 subjects: 220 with IBD (79 treated with anti-TNFα) and 99 healthy control (HC) participants. All patients received two mRNA-BNT162b2 vaccines (Pfizer/BioNTech), 80% of whom received a third vaccine dose. Evaluation included disease activity, anti-spike (S) and nucleocapsid (N) antibody levels, anti-TNFα drug levels, and adverse events (AEs). All participants showed significant serologic response one month after receiving a third dose. However, three months later, the anti-S levels decreased significantly in patients treated with anti-TNFα compared with the non-anti-TNFα and HC groups. A correlation between serologic response to the third vaccine dose and anti-TNF drug levels was not found. No significant AE or IBD exacerbation was observed. Importantly, lower serologic response after the third vaccine dose predicted infection. A third dose of BNT162b2 is effective and safe in patients with IBD. Lower serologic response predicted infection, even in seropositive subjects. Lower serologic responses and their rapid decline suggest a fourth vaccine dose in this patient population.
Characteristics of Lightning Channel in Thunderclouds Determined by Thunder

Lightning channels in thunderclouds are investigated with the thunder technique, and the relationship between the channel direction and the storm characteristics is discussed. It is confirmed that the channels of ground flashes horizontally extend in clouds and the channel directions tilt to the downstream of the wind in the upper atmosphere. It is found that the distribution on a horizontal plane, of the directions of horizontal channel projections inside the clouds relates with the speed of storm motion, and channel directions tend to tilt to the downstream with increasing speed of storm motion. The distribution of the channel inclinations in clouds seems to relate with the flash frequency of the storm, which is controlled by the updraft in the clouds.
“Why Can’t We Be Friends”? An Examination of Academic and Industry Alignment in Sport Sponsorship

The purpose of this study is to produce an analysis of content published in both academic literature and industry related publications that specifically examines the theme of sport sponsorship. Scholars suggest a gap between academia and industry, yet it is undetermined how published articles about sponsorship are aligned and why certain topics may overlap in interest where others are independent topics. While a number of other studies have examined content in academic publications, no study has yet been applied comparing industry publications. Our intention is to compare the published academic articles and what is written in industry publications to better understand the content that is being discussed across the various channels, and to see if there is a gap between industry and academia. Findings show academics focused on certain categories while industry focused on others. Within some categories there was a clear distinction in how differently they discussed certain topics. However, some categories did demonstrate balance.
Distinct Classes of Statistical Anxiety: Latent Profile and Network Psychometrics Analysis of University Students

Purpose Many university students will experience statistical anxiety. Consequentially, the relationship between such anxiety and learning performance has been of concern to various educational researchers. To date, however, there has been no consistent resolution to this problem. Because previous studies have mainly used the perspective of variant-centered analysis rather than taking into account individual differences, this study argues that the different classes of statistical anxiety among university students may be an important influencing factor. Participants and Methods In this study, 1607 Chinese university students who had just completed a statistics course were assessed using the Statistical Anxiety Scale, Statistics Learning Self-Efficacy Scale, and Learning Engagement Scale, and an exploratory study was conducted to determine whether university students’ statistical anxiety could be divided into different classes. Latent profile and network psychometrics analyses were then used to analyze the data. Results (1) The latent profile analysis found that university students’ statistical anxiety could be divided into three different latent classes: mild test anxiety, moderate text anxiety, and severe statistical anxiety. (2) The correlation analysis showed that the relationships among the three latent classes of statistical anxiety and learning performance were not entirely consistent, indicating that there was heterogeneity in the statistical anxiety of these university students. (3) Further network psychometrics analysis showed that the statistical anxiety network structure of the three latent classes has different core nodes that reflected the most important symptoms of statistical anxiety. Conclusion There is heterogeneity in university students’ statistical anxiety that can be divided into three latent classes. These core nodes in the statistical anxiety networks of the three latent classes were different, helping statistics instructors to better understand the nature of these latent classes, take different intervention measures for different latent classes of university students.
Examining Factors That Influence BIPOC Students’ Enrollment in STEM Postsecondary Majors

Existing research has studied the underrepresentation of Black, Indigenous and People of Color (BIPOC) students enrolling in and graduating from science, technology, engineering, and mathematics (STEM) fields in college (e.g., Okahana et al., 2018; Rincón & Lane, 2017). However, there is a dearth of research that examines the precollegiate factors that impact whether a student majors in a STEM field (Moakler & Kim, 2014). This study uses binary logistic regression and moderated binary logistic regression to examine the influences that gender, mathematics (math) identity, science identity, career expectations at age 30, and high school STEM credit completion have on BIPOC students’ postsecondary major (STEM or non-STEM). Based on the logistic regression results, our study indicates that gender, science identity, career expectations at age 30, and high school STEM credit completion significantly predict the odds of postsecondary enrollment in a STEM major. In addition, our ad hoc analysis confirms that gender moderates the relationship between science identity and the likelihood of a STEM collegiate major. These results can aid researchers and practitioners in investigating opportunities to improve STEM participation for BIPOC students.
Effect of printing parameters on mechanical properties and processing time of additively manufactured parts

Fused deposition modeling (FDM) has gained popularity recently due to its versatility and low cost. Considering that the quality of printed parts depends on many variables, a 3^3 factorial design of experiments was conducted, where three influential parameters in the process were studied: layer height (0.15, 0.2, and 0.25 mm), infill per - centage (30%, 60%, and 90%), and shell count (2, 3, and 4), using polylactic acid as the material. Their effects on tensile strength, flexural strength, printing time, and interactions were measured. The maximum tensile and flexural stress obtained were 33.5 MPa and 87.3 MPa, respectively, at a 90% infill percentage. It was found that layer height does not significantly affect mechanical strength, while infill percentage has the most significant influence, followed by the number of shells. The latter two factors show a meaningful interaction. Furthermore, all the studied parameters have a significant impact on printing time.
A high-throughput phenotyping assay for precisely determining stalk crushing strength in large-scale sugarcane germplasm

Sugarcane is a major industrial crop around the world. Lodging due to weak mechanical strength is one of the main problems leading to huge yield losses in sugarcane. However, due to the lack of high efficiency phenotyping methods for stalk mechanical strength characterization, genetic approaches for lodging-resistant improvement are severely restricted. This study attempted to apply near-infrared spectroscopy high-throughput assays for the first time to estimate the crushing strength of sugarcane stalks. A total of 335 sugarcane samples with huge variation in stalk crushing strength were collected for online NIRS modeling. A comprehensive analysis demonstrated that the calibration and validation sets were comparable. By applying a modified partial least squares method, we obtained high-performance equations that had large coefficients of determination (R2 > 0.80) and high ratio performance deviations (RPD > 2.4). Particularly, when the calibration and external validation sets combined for an integrative modeling, we obtained the final equation with a coefficient of determination (R2 ) and ratio performance deviation (RPD) above 0.9 and 3.0, respectively, demonstrating excellent prediction capacity. Additionally, the obtained model was applied for characterization of stalk crushing strength in large-scale sugarcane germplasm. In a three-year study, the genetic characteristics of stalk crushing strength were found to remain stable, and the optimal sugarcane genotypes were screened out consistently. In conclusion, this study offers a feasible option for a high-throughput analysis of sugarcane mechanical strength, which can be used for the breeding of lodging resistant sugarcane and beyond.
A Duality Result for Robust Optimization with Expectation Constraints

This paper demonstrates a practical method for computing the solution of an expectation-constrained robust maximization problem with immediate applications to model-free no-arbitrage bounds and super-replication values for many financial derivatives. While the previous literature has connected super-replication values to a convex minimization problem whose objective function is related to a sequence of iterated concave envelopes, we show how this whole process can be encoded in a single convex minimization problem. The natural finite-dimensional approximation of this minimization problem results in an easily-implementable sparse linear program. We highlight this technique by obtaining no-arbitrage bounds on the prices of forward-starting options, continuously-monitored variance swaps, and discretely-monitored gamma swaps, each subject to observed bid-ask spreads of finitely-many vanilla options.