Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary Inflammatory Index and Associations with Sarcopenia Symptomology in Community-Dwelling Older Adults

Low-grade systemic inflammation is a key driver of muscle degeneration in older adults, and diets with pro-inflammatory properties may further contribute to loss of muscle mass, strength and function. Therefore, this research aimed to explore the associations between the inflammatory potential of the diet and measures of sarcopenia symptomology in community-dwelling older adults. Upper (handgrip strength, HGS) and lower extremity (sit-to-stand) muscle strength, physical performance (timed-up-and-go, TUG) and appendicular skeletal muscle mass (ASM) was assessed according to the European Working Group on Sarcopenia in Older People version 2 (EWGSOP2) criteria. Multiple 24-hr dietary recalls were used to calculate the Dietary Inflammatory Index (DII), which was then used to group participants into anti- and pro-inflammatory dietary groups. Multiple linear regression investigated associations between DII, muscle strength, physical performance, and muscle quantity adjusted for age, gender, comorbidities, waist circumference and physical activity. Adults 65–85 years (n = 110, 72.1 ± 4.7 years, 76.4% female) were recruited. One participant was identified with sarcopenia, 35.2% were pre-frail, or frail. More participants with a pro-inflammatory DII score had low muscle quantity than those with anti-inflammatory DII (3.4% vs. 6.4%, x2 = 4.537, p = 0.043) and DII was negatively associated with HGS (β = −0.157, p = 0.016) and ASM (β = −0.176, p = 0.002) which remained significant after adjusting for covariates. In this population, DII was associated with less favorable muscle strength, physical performance, and muscle quantity.
Describing the Morphology of 2 H Martensite Using Group Theory Part I: Theory

ABSTRACT This paper is devoted to a clear and simple group theory description of the morphology and microstructure (including the orientation relationships among lattice correspondence variants, habit plane variants and the self-accommodation diamond) of 2H martensite in shape memory alloys (SMAs). There are 24 elements in point group 𝒫24 of DO 3 austenite, and they correspond to 24 habit plane variants. These 24 habit plane variants form a cubic group. Martensite point group 𝒫4 is a subgroup of 𝒫24 and 4 habit plane variants that correspond to 𝒫4 and form a correspondence variant dominant group. A cubic group can be divided into six correspondence variant dominant groups that correspond to six elements of 6 —the left co-set of 𝒫4 in 𝒫24. The point group 𝒮4 is also a subgroup of 𝒫24 and is a self-accommodation group in 2H martensite. 4 normal directions of habit plane variants in self-accommodation group 𝒮4 cluster together along one [110] direction. A cubic group can be divided into six self-accommodation equivalent classes, which correspond to six self-accommodation martensite diamonds. There are 4 different cubic groups in 2H martensite. Thus, there are 96 martensite habit plane variants that correspond to 192 normal habit plane directions and 48 phase transformation eigenstrains.
Performance analysis of unbiased and classical measurement conversion techniques

Conventional tracking with range-bearing measurements often requires the measurement to be converted to Cartesian coordinates before a tracker is invoked. Theoretical limits are derived for the performance of classical and unbiased conversion techniques using the expected normalized error squared as a function of bearing uncertainty and the ratio of range to range uncertainty. The unbiased measurement conversion is shown to be more consistent than the classical measurement conversion with respect to range and bearing uncertainty.
Improved log‐linear model estimators of abundance in capture‐recapture experiments

The authors review log‐linear models for estimating the size of a closed population and propose a new log‐linear estimator for experiments having between animal heterogeneity and a behavioral response. They give a general formula for evaluating the asymptotic biases of estimators of abundance derived from log‐linear models. They propose simple frequency modifications for reducing these asymptotic biases and investigate the modifications in a Monte Carlo experiment which reveals that they reduce both the bias and the mean squared error of abundance estimators.
Parkin regulates neuronal lipid homeostasis through SREBP2-lipoprotein lipase pathway—implications for Parkinson’s disease

Abstract Abnormal lipid homeostasis has been observed in the brain of Parkinson’s disease (PD) patients and experimental models, although the mechanism underlying this phenomenon is unclear. Notably, previous studies have reported that the PD-linked protein Parkin functionally interacts with important lipid regulators, including Sterol Regulatory Element-Binding Proteins (SREBPs) and cluster of differentiation 36 (CD36). Here, we demonstrate a functional relationship between Parkin and lipoprotein lipase (LPL), a triglyceride lipase that is widely expressed in the brain. Using a human neuroblastoma cell line and a Parkin knockout mouse model, we demonstrate that Parkin expression level positively correlates with neuronal LPL protein level and activity. Importantly, our study identified SREBP2, a major regulator of sterol and fatty acid synthesis, as a potential mediator between Parkin and LPL. Supporting this, SREBP2 genetic ablation abolished Parkin effect on LPL expression. We further demonstrate that Parkin-LPL pathway regulates the formation of intracellular lipid droplets, and that this pathway is upregulated upon exposure to PD-linked oxidative stress induced by rotenone. Finally, we show that inhibition of either LPL or SREBP2 exacerbates rotenone-induced cell death. Taken together, our findings reveal a novel pathway linking Parkin, SREBP2 and LPL in neuronal lipid homeostasis that may be relevant to the pathogenesis of PD.
A Comparison of Deep Neural Networks for Monocular Depth Map Estimation in Natural Environments Flying at Low Altitude

Currently, the use of Unmanned Aerial Vehicles (UAVs) in natural and complex environments has been increasing, because they are appropriate and affordable solutions to support different tasks such as rescue, forestry, and agriculture by collecting and analyzing high-resolution monocular images. Autonomous navigation at low altitudes is an important area of research, as it would allow monitoring parts of the crop that are occluded by their foliage or by other plants. This task is difficult due to the large number of obstacles that might be encountered in the drone’s path. The generation of high-quality depth maps is an alternative for providing real-time obstacle detection and collision avoidance for autonomous UAVs. In this paper, we present a comparative analysis of four supervised learning deep neural networks and a combination of two for monocular depth map estimation considering images captured at low altitudes in simulated natural environments. Our results show that the Boosting Monocular network is the best performing in terms of depth map accuracy because of its capability to process the same image at different scales to avoid loss of fine details.
Frequency–temperature compensated sapphire loaded cavity for compact hydrogen masers

We report some theoretical and experimental results about a frequency–temperature compensated sapphire loaded cavity for compact hydrogen maser atomic clocks. Based on theoretical calculations, the frequency–temperature coefficients in the TE0 1 1 mode of a sapphire cavity associated with two small rings of SrTiO3 can be reduced. For instance, at 50 °C, when the thickness of the SrTiO3 ring is 5 mm, the frequency–temperature coefficient can be reduced by about five times, and in the meantime, the quality factor can be kept at above 40 000 synchronously. A sapphire loaded cavity and eight small compensated chips of SrTiO3 were prepared and a combined cavity of sapphire with SrTiO3 chips was simulated by the finite element method and measured by experiments. The simulation and the related experimental results agree well. In addition, the frequency–temperature coefficients in two different configurations of eight SrTiO3 chips were also measured and compared.
The Mediating Effect of Caregiving Relationship Quality on the Association Between Caregiving Stressors and Mental Health Problems Among Older Spousal Caregivers

Providing care to a spouse can be especially challenging for older adults given their compounding stressors resulting from aging and caregiving. This cross-sectional study examines the relationships between caregiving stressors and caregiver mental health problems and the potential mediator (i.e., caregiving relationship quality) of these associations. A total of 431 Americans (≥65 years) were selected from the National Study of Caregiving. Path analysis shows that care assistance was positively associated with caregiver mental health problems, and this association was mediated by negative relationship quality (Indirect effect = .14, p = .016). Moreover, role overload was positively associated with caregiver mental health problems, which was mediated by negative relationship quality (indirect effect = .13, p = .002). Findings suggest that caregiving stressors can adversely affect mental health by exacerbating negative relationship quality. Interventions that limit negative exchanges and increase compassionate communications between older spousal caregivers and their care-receiving partners are needed.
Coherent magnetic field fluctuations and locked modes in a reversed-field pinch

Magnetic field fluctuations have been measured in the TPE‐1RM20 reversed‐field pinch [in Plasma Physics and Controlled Nuclear Fusion Research, Proceedings of the 14th International Conference, 1992, Wurzburg (International Atomic Energy Agency, Vienna, 1992) Paper IAEA‐CN‐56/C‐4‐3]. The dominant modes are m=1/n=7–9, resonant near the axis. The fluctuations are coherent, corresponding to nearly continuous rigid body rotation with poloidal and toroidal frequencies of fθ=130–170 kHz and fφ=11–14 kHz, respectively. Discrete dynamo events (in which toroidal magnetic flux is generated) of two different types are observed at high values of pinch parameter (Θ≳1.6). The first type is triggered by a single, wall‐locked m=1/n=7 mode. The slowing down of the mode rotation is in rough agreement with a simulation which assumes the effect of induced eddy current in the vacuum liner. In the subsequent relaxation event, the locked mode decays and the m=1 spectrum cascades to higher‐n modes. However, in some cases the sat.
Inpatient forensic psychiatry in the time of COVID-19: a survey study of perceived mental health implications on people with schizophrenia spectrum disorder

ABSTRACT Background The aim of our study was to assess the perceived mental health impact of the COVID-19 pandemic on people with schizophrenia spectrum disorder (SSD) in an inpatient forensic psychiatric institution and to identify personal networks most crucial for the patient during the pandemic. Methods In this cross-sectional survey study, 44 patients with SSD took part in a COVID-19-specific interview. The data was correlated with the Positive and Negative Syndrome Scale (PANSS) to evaluate the patients’ psychopathology. In addition, we investigated subgroups of vaccinated and unvaccinated patients to analyze possible differences in psychopathology. Results Less contact with family members was associated with significantly higher PANSS scores (p < 0.05). Patients who reported to feel less relaxed and more stressed during the pandemic than they had been before the outbreak of the virus showed significantly higher PANSS scores (p < 0.05). Unvaccinated patients demonstrated significantly higher PANSS scores than their vaccinated controls (p < 0.05). Conclusions Social support from family members played an important role for people with SSD in inpatient forensic psychiatric institutions during the pandemic. Moreover, individuals with SSD seemed to be more emotionally vulnerable during the pandemic. A more pronounced symptomatology in patients with SSD might be a potential barrier to immunization against COVID-19.
Spin-Disorder Scattering and Magnetoresistance of Magnetic Semiconductors

The consequences of a simple type of exchange interaction between free charge carriers in a broad energy band and localized magnetic moments are discussed. The interaction causes a splitting of the energy bands into bands for the two spin directions. It also leads to spin-disorder scattering of the charge carriers. The temperature dependence of the mobility is calculated for ferromagnetic and antiferromagnetic semiconductors. Expressions are given for the magnetoresistance of ferromagnetic semiconductors.
Automatic Lag Selection in Covariance Matrix Estimation

We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix. For a given kernel for weighting the autocovariances, we prove that our procedure is asymptotically equivalent to one that is optimal under a mean squared error loss function. Monte Carlo simulations suggest that our procedure performs tolerably well, although it does result in size distortions.
Optimization of duct acoustic liners of finite length

Lining design procedures generally ignore the effects of discontinuous impedance changes on reflection and modal redistribution of incident energy. The present study, spurred by preliminary work of Lansing and Zorumski [J. Sound Vib. 27, 85–100 (1973)], involves identification of the mechanisms of optimal suppression by segmented liners, including impedance discontinuity effects. The mathematical model involves rectangular ducts in the absence of mean flow. Segmented acoustic fields are represented by duct eigenfunction expansions, and mode‐matching is used to ensure continuity of the total field. Extensive parameter studies were used to identify attenuation mechanisms and to define preliminary liner configurations. These are used as starting values in conjugate‐gradient optimization studies. Optimal segmented liners are presented and it is shown that, if the sound source is sufficiently well‐defined, conventional infinite duct optimum attenuation rates can be improved upon by taking advantage of wall imp.
A Novel Few-Mode Multi-core Fiber with Large Effective Mode Area and Low Inter-Core Crosstalk

This Paper proposes a novel 7-core 5-mode fiber with large mode area and low inter-core crosstalk(XT). The proposed optical fiber, by adopting a combination of air-trench structure and high-index ring, realizes large mode area and low XT. The numerical analyses reveal that the proposed fiber can stably transmit 5 LP modes in the C+L band; the effective mode area of each of the 5 LP modes is larger than 110μm2; the XT of in each of the 5 LP modes is smaller than –79 dB/km; each mode has an effective refractive index difference bigger than 1.1 × 10-3. Therefore, a low XT result can still be achieved when the mode area is large. The proposed optical fiber may be well utilized to construct a high-capacity fiber optic transmission system.
Energy and structure of the ground state of liquid He4

We present the results of a calculation of the energy- and liquid-structure function of the ground state of liquid $^{4}\mathrm{He}$ in the density range 0.0180-0.0257 ${\mathrm{\AA{}}}^{\ensuremath{-}3}$, using both the Lennard-Jones 6-12 potential and the second Morse-dipole-dipole potential of Bruch and McGee. The method is to determine the optimum Jastrow trial wave function by multiple iteration of the paired-phonon analysis, and then calculate the contributions of three-body factors in the wave function. Tables of values are given at several densities for the radial distribution function, Jastrow function, and liquid-structure function. We also present a variational formulation of the paired phonon analysis and numerical examples of its convergence and self-consistency.
Numerical simulation of conical diffraction of tapered electromagnetic waves from random rough surfaces and applications to passive remote sensing

A new tapered wave integral equation method was derived to simulate the conical diffraction of electromagnetic waves from rough surfaces. Both the full matrix inversion and the banded matrix iterative approaches are developed. By using the principle of reciprocity and energy conservation, all four Stokes parameters are calculated for polarimetric passive remote sensing of rough surfaces. We show in this paper that for a moderately rough surface, the third Stokes parameter can be as high as ±20°K. The tapered wave integral equation approach can deal with a rough surface with a large slope. The new method presented in this paper is compared with the previously published plane wave integral equation method and the extended boundary condition method. Very good agreement is obtained. Unlike the plane wave integral equation method and the extended boundary condition method, the tapered wave integral equation method does not have the kinks imposed by Floquet models and it requires a shorter surface length in most applications.
Cloud Motion and Rainfall Statistics

Abstract This paper presents some of the results obtained from a new analysis of the data collected during 1968 and 1970 by EML in the Florida cumulus modification experiment (the “single cloud” experiment). The most important new element in this analysis is the stratification of the data into categories based on cloud motion. Category 1 days are those displaying significant, relatively uniform cloud motion throughout the day. Category 2 days are those displaying no such motion. First the rainfall data are analyzed without regard to motion categories, the log-normal model is introduced, and evidence for multiplicative seeding factor is adduced and its value estimated. The data are also analyzed on a pairwise basis. Next the data are stratified by motion categories and the analysis repeated with categories. It is shown that although a log-normal model can still be applied within categories, there is no basis for assuming a multiplicative seeding factor within categories. It is shown that category 1 clouds .
Heights of projective varieties and positive Green forms

Using arithmetic intersection theory, a theory of heights for projective varieties over rings of algebraic integers is developed. These heights are generalizations of those considered by Weil, Schmidt, Nesterenko, Philippon, and Faltings. Several of their properties are proved, including lower bounds and an arithmetic Bezout theorem for the height of the intersection of two projective varieties. New estimates for the size of (generalized) resultants are derived. Among the analytic tools used in the paper are "Green forms" for analytic subvarieties, and the existence of poSitive Green forms is discussed. (J.-B.Bost and C. Soule) INSTITUT DES HAUTES ETUDES ScIENTIFIQUES,35,RoUTE DE CHARTRES, 91440, BURES-SUR-YvETTES, FRANCE (H. Gillet) DEPARTMENT OF MATHEMATICS, STATISTICS, AND COMPUTER SCIENCE, (M/c249), UNIVERSITY OF ILLINOIS AT CHICAGO, 851 S. MORGAN STREET, CHICAGO, ILLINOIS 60607 E-mail address: henriGmath. uic . edu License or copyright restrictions may apply to redistribution; see http://www.ams. org/journal-terms-of-use
Genetic diversity evaluation of Sojat goat population of India

Sojat goat forms the part and parcel of the lives of the farmers in the Barmer region of Rajasthan. These are large-sized goats, white in colour, and have dual utility. These goats fetch premium price during the Eid festival. Assessment of diversity is essential for germplasm characterization and management. Genomic microsatellite markers being a valuable tool for estimating genetic diversity were selected for exploring existing genetic variability in the Sojat goat population. The standard metrics of genomic diversity detected moderate variability with a total of 162 alleles across 22 loci in this lesser-known population. The expected number of alleles had a mean value of 3.40±0.39. Similarly, a moderate magnitude of diversity was recorded in the Sojat population as the mean observed heterozygosity was 0.54±0.05. Expected heterozygosity was higher than the observed (0.60±0.06), indicating a deviation from Hardy-Weinberg Equilibrium (HWE) and the possibility of inbreeding due to the non-random mating in the population. Accordingly, significant heterozygote deficiency was noticed (F=0.08±0.03). The population did not suffer a reduction in effective population size in the last few generations. Mutation drift equilibrium did not reveal significant heterozygosity excess under different models of microsatellite evolution and no shift was recorded in the frequency distribution of alleles. To conclude, the results provided the first insights into the genetic diversity of Sojat goats. A moderate genetic variability with heterozygote deficiency within the population warrants immediate attention for scientific management of this unique goat population to conserve the existing genetic variation and to avoid any escalation of inbreeding.
Mach Number Dependence of Near Wall Structure in Compressible Channel Flows

A newly developed statistical correlation structure is used to analyze compressible channel flows up to M = 3.0. Using velocity‐vorticity correlation structure (VVCS), the Mach number dependence of the characteristic scales of near wall structure are analyzed. The detailed results show that the length scale and the spanwise spacing of VVCS exponentially increase with Mach number in the near wall region. For example, for VVCSuωx, the length scale of the statistical streamwise structure is Lxuωx = e6.5 + M/2.8 + (M/4.1)2, and spacing between the structure is Dxuωx = 60eM/2.2 + 13.3, where the parameters 2.8, 4.1 and 2.2 are characteristic Mach numbers to be explained further. The geometrical features of the statistical structure are consistent with the observations of Coleman et al., and it is also argued that the quantitative relationship between the characteristic scales of VVCS and Mach number is important to consider in performing numerical computation of compressible flows. This study also suggests tha.
Multiscale Convolutional Transformer for EEG Classification of Mental Imagery in Different Modalities

A new kind of sequence–to–sequence model called a transformer has been applied to electroencephalogram (EEG) systems. However, the majority of EEG–based transformer models have applied attention mechanisms to the temporal domain, while the connectivity between brain regions and the relationship between different frequencies have been neglected. In addition, many related studies on imagery–based brain–computer interface (BCI) have been limited to classifying EEG signals within one type of imagery. Therefore, it is important to develop a general model to learn various types of neural representations. In this study, we designed an experimental paradigm based on motor imagery, visual imagery, and speech imagery tasks to interpret the neural representations during mental imagery in different modalities. We conducted EEG source localization to investigate the brain networks. In addition, we propose the multiscale convolutional transformer for decoding mental imagery, which applies multi–head attention over the spatial, spectral, and temporal domains. The proposed network shows promising performance with 0.62, 0.70, and 0.72 mental imagery accuracy with the private EEG dataset, BCI competition IV 2a dataset, and Arizona State University dataset, respectively, as compared to the conventional deep learning models. Hence, we believe that it will contribute significantly to overcoming the limited number of classes and low classification performances in the BCI system.