Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Dual-Energy X-ray Absorptiometry in Children with Inflammatory Bowel Disease: A Large Single Centre Study

Purpose Low bone mineral density (BMD) is a complication in children with inflammatory bowel disease (IBD). There are limited data evaluating dual-energy x-ray absorptiometry (DXA) as a screening tool for low BMD in children with IBD. We performed a single site retrospective analysis of DXA use. Methods Children aged 5–18 years with IBD diagnosed between 2013 to 2017 at the Royal Children’s Hospital, Australia, were included. Patient demographics, measures of disease activity, DXA scores, and factors related to BMD were collected. Results Over a median follow up of 5.1 (4–6.4) years, 72/239 (30.1%) children underwent DXA, and 28/239 (11.7%) children had a second DXA. Our DXA practice differed to consensus guidelines regarding initial screening based on height and/or body mass index (BMI) z-score (8/17 [47.1%]), and repeat surveillance (13/42 [31.0%]). Children had a median lumbar spine (LS) z-score −0.80 (−1.65–0.075). Children with LS z-score≤−2.0 (n=14) had lower weight (6.57 [1.78–23.7] vs. 51.1 [26.5–68.7], p=0.0002) and height centiles (3.62 [1.17–17.1] vs. 42 [16.9–67.1], p=0.0001), and higher faecal calprotectin (FCP) (3041 [1182–4192] vs. 585 [139–2419], p=0.009) compared to children with LS z-score>−2.0. No fractures were reported. Of 28 children who underwent a second DXA 1.6 (1.1–2.2) years following initial DXA, no significant change in z-scores occurred. Conclusion Children with IBD had low BMD. In addition to height centile and weight centile, FCP was associated with lower BMD, and should be considered in DXA screening guidelines. Greater clinician awareness of DXA consensus guidelines is required. Future prospective studies are required.
Limit theorems for a moderately subcritical branching process in a random environment

Let {ξ,,} be a moderately subcritical branching process in a random environment with linear-fractional generating functions, m„ be the conditional expectation of ξ,, with respect to the random environment. We prove theorems on convergence of the sequence of random processes {δ,,,ΐ/m,,,,,, / e (0,1) | ξ,, >0} as η -> °° in distribution, and of the initial and final segments of the random sequence ξο/mo, ξ ι /mi , . , ξ,,/m,, considered under the condition that {ξ,, > 0}. 1. Let sequences of random variables /=0 be identically distributed and independent for different n. We introduce the generating functions A sequence of non-negative integer-valued random variables {ξη, η Ε Ν0} is called a branching process in the random environment {πη, η E N0}, if E(/"' |§, , ξ , , . . .Λ.Λο,πΙ , . . . ,7ζΙ) = (^(^, η Ε No (for simplicity we assume that ξο = 1). In [1], the classification of branching processes in a random environment depending on the sign of Eln/0 '(l) is given: if Eln/0(l) > 0, then the process is supercritical, if Ε ln/0'(l) = 0, the process is critical, and if Ε ln/0'(l) < 0, the process is subcritical. In its turn, in [2] it is shown that the asymptotical behaviour of the extinction probability of a subcritical branching process in a random environment essentially depends on the sign of E(/Q'(l)ln/0'(l)). In [3], a subcritical branching process in a random environment is called strictly subcritical, if *UDC 519.2. Originally published in Diskretnaya Matematika (1998) 10, No. 1, 141-157 (in Russian). Received March 10, 1997. Translated by V. F. Kolchin.
The Chow ring of the moduli space of abelian threefolds

In this paper we determine the structure of the Chow ring of the Delaunay-Voronoi compactification $\tilde{\cal A}_3$ of the moduli space of principally polarized abelian threefolds. This compactification was introduced by Namikawa and studied by Tsushima. We use equivariant classes on level coverings of $\tilde{\cal A}_3$. We also compare this ring with the Chow ring of the moduli space of stable genus 3 curves as determined by Faber.
Food Insufficiency among Job-Loss Households during the Pandemic: The Role of Food Assistance Programs

During the early stages of the pandemic, many households experienced a loss of employment income, which worsened food insecurity and food insufficiency across the United States. This study aimed to examine whether food assistance programs (FAPs) significantly alleviated food insufficiency (FI) among job-loss households during the pandemic. The analysis was conducted with nationally representative survey data (n = 229,668) collected across 50 states and D.C. in 2020. Spatial analysis and logistic regression were applied to analyze the patterns of FI and to assess the Supplemental Nutrition Assistance Program (SNAP), FAPs for children, and community FAPs. Approximately 18.6% of participants faced FI, 41% of whom experienced FI for the first time. SNAP significantly lowered the odds of being food insufficient by 24.5% among households who were already food insufficient before the pandemic and by 11.9% for households with children. FAPs for children slightly reduced FI among households with children, but those who participated in these programs still had higher prevalence of food insufficiency than those who did not. Community FAPs were not effective. The findings suggest increasing the benefit level of SNAP for households with lowest income, strengthening their partnership with community FAPs, and distributing more emergent assistance to the most vulnerable households.
New effective pressure and existence of global strong solution for compressible Navier–Stokes equations with general viscosity coefficient in one dimension

In this paper we prove the existence of a unique global strong solution for the Cauchy problem associated to the one dimensional Navier–Stokes equations with general degenerate viscosity coefficients. The cornerstone of the proof is the introduction of a new effective pressure which allows to obtain an Oleinik-type estimate for the so called effective velocity. In our proof we make use of additional regularizing effects on the velocity which requires to extend the techniques developed by Hoff for the constant viscosity case.
A Hybrid ADMM for Six-Degree-of-Freedom Entry Trajectory Optimization Based on Dual Quaternions

This article investigates the six-degree-of-freedom (6-DoF) entry trajectory optimization problem in a Human-Mars entry, powered descent, and landing mission. During the entry phase, aerodynamic forces are employed to decelerate the vehicle. Instead of being treated as a point mass, both translational and rotational motions of the entry vehicle are considered. Specifically, the 6-DoF rigid body motion of the entry vehicle is modeled using the unit dual quaternion representations to avoid highly nonlinear terms in the flight dynamics expression originally based on the flight-path coordinates. Then, the entry trajectory optimization problem is to minimize the terminal speed subject to dynamical, operational, and mission constraints modeled by the new representation scheme. By applying the discretization technique and polynomial approximation, the entry trajectory optimization problem is reformulated as a nonconvex quadratically constrained quadratic programming problem, which is solved via a hybrid alternating direction method of multipliers (ADMM). The accuracy of the dual-quaternion-based model and the computational efficiency of the hybrid ADMM are validated via numerical simulations.
Tawhid-Based Green Learning in Islamic Higher Education: An Insan Kamil Character Building

This study aims to integrate green learning into the curriculum and proposes a holistic conceptual framework for Islamic higher education. This study used a qualitative-thematic approach and collected data through structured interviews with four informants from Islamic higher education institutions with green campus programs who were selected through snowball sampling. The results revealed that the green campus had been implemented in several ways, including the vision and governance of the campus environment, the appropriate waste management, research, and community service, and the learning process in several courses, either explicitly regulated in the written curriculum or implicitly taught in the hidden curriculum. One of the goals of implementing a green campus is to provide insight to students, lecturers, and other higher education communities about the importance of a sustainable environment through the learning process as a provision when living in a society. In addition, Islamic higher education has budgeted funds for green campus development, although it is limited because it strictly competes with funds allocations for other required campus development. For this reason, the researchers propose Tawhid-Based Green Learning, a conceptual framework for developing Islamic higher education responsive to the natural environment, which is reflected in the vision, mission, goals, learning materials, quality assurance, and outcomes. The concern for the environment based on tawhid (monotheism) integrated into the curriculum is also a form of human piety, and Islamic higher education has the task of producing graduates who have insan kamil personalities. As an implication, Islamic higher education must contribute to reducing the impact of global warming through tawhid-based green learning included in curriculum and lecture materials.
Discovery, Genomic Sequence Characterization and Phylogenetic Analysis of Novel RNA Viruses in the Turfgrass Pathogenic Colletotrichum spp. in Japan

Turfgrass used in various areas of the golf course has been found to present anthracnose disease, which is caused by Colletotrichum spp. To obtain potential biological agents, we identified four novel RNA viruses and obtained full-length viral genomes from turfgrass pathogenic Colletotrichum spp. in Japan. We characterized two novel dsRNA partitiviruses: Colletotrichum associated partitivirus 1 (CaPV1) and Colletotrichum associated partitivirus 2 (CaPV2), as well as two negative single-stranded (ss) RNA viruses: Colletotrichum associated negative-stranded RNA virus 1 (CaNSRV1) and Colletotrichum associated negative-stranded RNA virus 2 (CaNSRV2). Using specific RT-PCR assays, we confirmed the presence of CaPV1, CaPV2 and CaNSRV1 in dsRNAs from original and sub-isolates of Colletotrichum sp. MBCT-264, as well as CaNSRV2 in dsRNAs from original and sub-isolates of Colletotrichum sp. MBCT-288. This is the first time mycoviruses have been discovered in turfgrass pathogenic Colletotrichum spp. in Japan. CaPV1 and CaPV2 are new members of the newly proposed genus “Zetapartitivirus” and genus Alphapartitivirus, respectively, in the family Partitiviridae, according to genomic characterization and phylogenetic analysis. Negative sense ssRNA viruses CaNSRV1 and CaNSRV2, on the other hand, are new members of the family Phenuiviridae and the proposed family “Mycoaspirividae”, respectively. These findings reveal previously unknown RNA virus diversity and evolution in turfgrass pathogenic Colletotrichum spp.
Can TikTok be a good way to extend the adoption of green control techniques? Evidence from rural China

ABSTRACT In the context of agricultural digitalisation in China, TikTok is becoming widely popular in rural areas and a novel way for agricultural technology extension. Based on survey data on 770 rice and wheat farmers in Hubei and Henan provinces in China, the endogenous switching probit model was used to verify the influence of TikTok usage on the adoption of Green Control Techniques (GCT). We found that farmers’ adoption probability of GCT will be significantly increased by 9.3–11.8% with their use of TikTok to browse GCT content. This shows that TikTok is an effective way to extend GCT. Furthermore, TikTok can complement traditional offline training as a digital agriculture extension for small-scale, older, and non-plain-area farmers, who are often of unequal status and are unable to obtain government agricultural extension services. These findings evaluate the effectiveness of short video software as a digital agriculture extension platform, which contributes to the rapid and effective extension of GCT. It is suggested that more GCT online promotion platforms should be built and applied in China.
Fano-Ricci limit spaces and spectral convergence

We study the behavior under Gromov-Hausdorff convergence of the spectrum of weighted $\barpartial$-Laplacian on compact K\"ahler manifolds. This situation typically occurs for a sequence of Fano manifolds with anticanonical K\"ahler class. We apply it to show that, if an almost smooth Fano-Ricci limit space admits a K\"ahler-Ricci limit soliton and the space of all $L^2$ holomorphic vector fields with smooth potentials is a Lie algebra with respect to the Lie bracket, then the Lie algebra has the same structure as smooth K\"ahler-Ricci solitons. In particular if a $\Q$-Fano variety admits a K\"ahler-Ricci limit soliton and all holomorphic vector fields are $L^2$ with smooth potentials then the Lie algebra has the same structure as smooth K\"ahler-Ricci solitons. If the sequence consists of K\"ahler-Ricci solitons then the Ricci limit space is a weak K\"ahler-Ricci soliton on a $\mathbb{Q}$-Fano variety and the space of limits of $1$ eigenfunctions for the weighted $\barpartial$-Laplacian forms a Lie algebra with respect to the Poisson bracket and admits a similar decomposition as smooth K\"ahler-Ricci solitons.
Thermal nonlinear effects in hybrid optical microresonators

The inherent material properties of silica reduce the susceptibility of silica optical microcavities to many nonlinear phenomena, enabling the development of devices with improved stability. However, large nonlinear coefficients can be leveraged to create microcavities with additional functionality. Therefore, devices with controllable nonlinear behavior are of interest. In the present research, silica microcavities are coated with polystyrene or polymethylmethacrylate to form hybrid microresonators. Using these devices, the thermally induced nonlinear optical behavior is investigated. By precisely controlling the optical field overlap with the polymer film, an environmentally stable device, in which the resonant frequency is independent of the input power, is demonstrated.
Dynamic Choice Theory and Dynamic Programming

Finite horizon sequential decision problems with a "temporal von NeumannMorgenstern utility" criterion are analyzed. This criterion, as developed in [7], is a generalization of von Neumann-Morgenstern (expected) utility of the vector of rewards, wherein an individual's preferences concerning the timing of the resolution of uncertainty are taken into account. The preference theory underlying this criterion is reviewed and then extended in natural fashion to yield preferences for strategies in sequential decision problems. The main result is that value functions for sequential decision problems can be defined by a dynamic programming recursion using the functions which represent the original preferences, and these value functions represent the preferences defined on strategies. This permits citation of standard results from the dynamic programming literature, concerning the existence of (memoryless) strategies which are optimal with respect to the given preference relation.
The Relationships Between Psychological Capital and Psychological Well-being of MSME Owners in Tempursari Village

Because the pandemic caused a decrease in turnover and economic instability, MSME owners required psychological well-being in order to develop and create innovations. Psychological capital is thought to be capable of improving psychological well-being through its dimensions. This study aimed to determine the relationship between psychological capital and the psychological well-being of MSME owners in Tempursari Village. This study included 79 MSME owners from different businesses in Tempursari Village. The data collection method used a questionnaire consisting of two scales, the Psychological Capital Scale-24 (reliability = .883) and the Psychological Well-Being Scale (reliability = .884). The hypothesis was tested using Spearman’s Rank Correlation, which yielded a significant positive correlation coefficient (p=.274, p≤.05) between psychological capital and psychological well-being of MSME owners in Tempursari Village. Keywords: MSME owners, psychological capital, psychological well-being
The Incidence of the Agenesis of Fetal Ductus Venosus at the 11–13 Weeks’ Ultrasound Examination

Objective: The objective is to examine the incidence of agenesis of fetal ductus venosus (DV) at the routine ultrasound examination at 11-13 weeks. Materials and methods: This is a retrospective study on women presenting for screening for chromosomal abnormalities. The fetal DV was routinely examined by color Doppler in the sagittal view. Results: Out of 8,304 fetuses examined, there were 13 cases of DV agenesis (0.15%). The umbilical vein drainage was intra-hepatic in two-thirds of the cases, and all resulted in normal live births. In the remaining one-third of cases, the umbilical vein drained to the inferior vena cava and all had a poor outcome because of aneuploidies, cardiac defects, and Noonan syndrome. Conclusion: Fetal DV agenesis occurs in about one in 650 fetuses and the majority of cases have a benign course and a favorable outcome. Failure to identify the DV should prompt a detailed ultrasound examination, identification of the drainage site of the umbilical vein, and genetic testing.
Automated Detection of Surgical Implants on Plain Knee Radiographs Using a Deep Learning Algorithm

Background and Objectives: The number of patients who undergo multiple operations on a knee is increasing. The objective of this study was to develop a deep learning algorithm that could detect 17 different surgical implants on plain knee radiographs. Materials and Methods: An internal dataset consisted of 5206 plain knee antero-posterior X-rays from a single, tertiary institute for model development. An external set contained 238 X-rays from another tertiary institute. A total of 17 different types of implants including total knee arthroplasty, unicompartmental knee arthroplasty, plate, and screw were labeled. The internal dataset was approximately split into a train set, a validation set, and an internal test set at a ratio of 7:1:2. You Only look Once (YOLO) was selected as the detection network. Model performances with the validation set, internal test set, and external test set were compared. Results: Total accuracy, total sensitivity, total specificity value of the validation set, internal test set, and external test set were (0.978, 0.768, 0.999), (0.953, 0.810, 0.990), and (0.956, 0.493, 0.975), respectively. Means ± standard deviations (SDs) of diagonal components of confusion matrix for these three subsets were 0.858 ± 0.242, 0.852 ± 0.182, and 0.576 ± 0.312, respectively. True positive rate of total knee arthroplasty, the most dominant class of the dataset, was higher than 0.99 with internal subsets and 0.96 with an external test set. Conclusion: Implant identification on plain knee radiographs could be automated using a deep learning technique. The detection algorithm dealt with overlapping cases while maintaining high accuracy on total knee arthroplasty. This could be applied in future research that analyzes X-ray images with deep learning, which would help prompt decision-making in clinics.
Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm

Few studies classified and predicted hypertension using blood pressure (BP)-related determinants in a deep learning algorithm. The objective of this study is to develop a deep learning algorithm for the classification and prediction of hypertension with BP-related factors based on the Korean Genome and Epidemiology Study-Ansan and Ansung baseline survey. We also investigated whether energy intake adjustment is adequate for deep learning algorithms. We constructed a deep neural network (DNN) in which the number of hidden layers and the number of nodes in each hidden layer are experimentally selected, and we trained the DNN to diagnose hypertension using the dataset while varying the energy intake adjustment method in four ways. For comparison, we trained a decision tree in the same way. Experimental results showed that the DNN performs better than the decision tree in all aspects, such as having higher sensitivity, specificity, F1-score, and accuracy. In addition, we found that unlike general machine learning algorithms, including the decision tree, the DNNs perform best when energy intake is not adjusted. The result indicates that energy intake adjustment is not required when using a deep learning algorithm to classify and predict hypertension with BP-related factors.
Knowledge, Attitude and Practice Survey on Body Posture Among Undergraduate Physiotherapy Students

Background: Posture is the alignment or orientation of body segments by maintaining an upright position. The postural deviations associated with change in young people’s behavior have increased. Incorrect posture refers to an irregular state of the body in which the body does not sustain a steady state and tissues and organs function normally in an erect position. Objective: The objectives of this study were to check the knowledge about body posture, attitude towards good and bad posture and practice for correcting the wrong posture to prevent complications in physiotherapy students. Methodology: An observational cross sectional study was conducted among the physiotherapy students from University Institute of Physical Therapy (UIPT), The University of Lahore Chenab Campus; Pakistan. For knowledge section Questionnaire on level of awareness of body use in young people was used, for attitude section a self-structured questionnaire and for practice section (Q-BAPHYP) was used. Data were analyzed by using SPSS (version 21.0). Results: Out of 202 physiotherapy students, 21(10.4%) were males and 181(89.6%) were females. 12.4% students were from 2nd year, 37.1% from 3rd year, 28.2% from 4th year and 22.3% from 5th year. Average age was 21.43 years. Among the total 36(17.8%) student’s had knowledge of good posture, 143(70.8%) often good posture. 168(83.2%) students responded of having a positive attitude towards good posture and only 11(5.4%) always practices good posture in their daily life. There is a positive but a weak correlation between knowledge and attitude (Spearman Correlation value=0.138) Conclusion: It was found that the physiotherapy students had knowledge of good posture and showed a positive attitude towards good posture but they are not well practicing it in their daily routine. Key words: Bad posture, Ergonomics, Good posture, Kinematics, Posture, Scoliosis
Student engagement with modeling in multiweek student-designed lab projects

Modeling, which is the process of constructing, testing, and refining models, is an important skill in experimental physics, and thus a learning goal of many physics laboratory classes. One promising approach to help students develop modeling skills is to incorporate multiweek student-designed projects into lab courses. In order to assess the potential benefits of these projects in enhancing students ’ modeling abilities, we analyzed projects from three upper-division lab courses at different institutions. By looking at written student coursework and student interviews, we investigated which parts of the modeling process the students from each project undertook, and how this engagement in modeling differed depending on features of the projects. The projects in our dataset varied widely, showing evidence of different ways students engaged with model construction and revisions. We observed that the features of the projects, such as the goal of the project and the complexity of the required apparatus, were associated with the ways in which the students constructed models and enacted revisions. This has implications for how instructors may choose to frame and structure courses with student-designed lab projects. iterative nature of the modeling process.