Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Mesh-Based Equivalent Magnetic Network for Performance Analysis and Optimal Design of Permanent Magnet Machines

This paper proposes a novel mesh-based equivalent magnetic network (EMN) model for performance analysis and optimal design of permanent magnet (PM) machines. The key contribution of the EMN model is that a generalized air-gap model solution is proposed by considering the machine motion of PM machines. Meanwhile, a modular modeling method is presented, and then the optimal design of PM machines can be investigated without repetitive programming and modeling. Two kinds of mesh elements are comprehensively utilized in the EMN model, and a hybrid rotor PM (HRPM) machine with interior PM and surface PM configuration is selected as an example to illustrate the development processes of EMN model. Meanwhile, the electromagnetic characteristics of HRPM machine are calculated by the proposed EMN model, such as back electromotive force, air-gap flux density distribution, and average torque. Finally, the accuracy and effectiveness of the proposed EMN model are verified through comparisons with finite element analysis and experimental tests.
Delta neutrophil index as a prognostic marker in emergent abdominal surgery

Delta neutrophil index (DNI) is the fraction of circulating immature granulocytes provided by a routine, complete blood cell analyzer. It is known to be a useful prognostic marker of sepsis. The aim of this study was to evaluate the role of DNI in the diagnosis and prognosis of patients who had undergone emergent surgery for an acute abdomen.
Two incompatible types of invariants in the octonion spaces

The paper aims to study some invariants and conservation laws relevant to electromag- netic and gravitational ﬁelds, by means of the rotational transformations of octonion coordinate systems. The scholars utilize the octonions to analyze the electromagnetic and gravitational ﬁelds simultaneously, including the octonion ﬁeld potential, ﬁeld strength, ﬁeld source, linear momentum, angular momentum, torque and force. When the octo- nion coordinate system transforms rotationally, the vector part of one octonion may alter, while the scalar part of the octonion will remain unchanged. This property allows one to deduce a few invariants, such as the scalar part of octonion radius vector, speed of light, and norm of octonion radius vector. These invariants are the basic postulates for the Galilean transformation and Lorentz transformation. Further, from the rotation transform of octonion coordinate systems, it is capable of deducing several invariants, including the mass, energy and power relevant to gravitational ﬁelds, in one octonion space O . And the term relevant to the electric charge will transform with the rotation of coordinate systems. In another octonion space O u , it is capable of inferring a few invariants, including the electric charge related to electromagnetic ﬁelds. And the terms relevant to the mass and energy will vary with the rotation of octonion coordinate systems. So the invariants are divided into two diﬀerent groups. In particular, the mass conservation law and energy conservation law can be eﬀective simultaneously. But the charge conservation law and mass conservation law are unable to be valid simultaneously, in the strict sense. It is beneﬁcial to further understand the laws of conservation.
Effect of Precipitation Variation on Soil Respiration in Rain-Fed Winter Wheat Systems on the Loess Plateau, China

Global climate change has aggravated the hydrological cycle by changing both the amount and distribution of precipitation, and this is especially notable in the semiarid Loess Plateau. How these precipitation variations have affected soil carbon (C) emission by the agroecosystems is still unclear. Here, to evaluate the effects of precipitation variation on soil respiration (Rs), a field experiment (from 2019 to 2020) was conducted with 3 levels of manipulation, including ambient precipitation (CK), 30% decreased precipitation (P−30), and 30% increased precipitation (P+30) in rain-fed winter wheat (Triticum aestivum L.) agroecosystems on the Loess Plateau, China. The results showed that the average Rs in P−30 treatment was significantly higher than those in the CK and P+30 treatments (p < 0.05), and the cumulative CO2 emissions were 406.37, 372.58 and 383.59 g C m−2, respectively. Seasonal responses of Rs to the soil volumetric moisture content (VWC) were affected by the different precipitation treatments. Rs was quadratically correlated with the VWC in the CK and P+30 treatments, and the threshold of the optimal VWC for Rs was approximately 16.06–17.07%. However, Rs was a piecewise linear function of the VWC in the P−30 treatment. The synergism of soil temperature (Ts) and VWC can better explain the variation in soil respiration in the CK and P−30 treatments. However, an increase in precipitation led to the decoupling of the Rs responses to Ts. The temperature sensitivity of respiration (Q10) varied with precipitation variation. Q10 was positive correlated with seasonal Ts in the CK and P+30 treatments, but exhibited a negative polynomial correlation with seasonal Ts in the P−30 treatment. Rs also exhibited diurnal clockwise hysteresis loops with Ts in the three precipitation treatments, and the seasonal dynamics of the diurnal lag time were significantly negatively correlated with the VWC. Our study highlighted that understanding the synergistic and decoupled responses of Rs and Q10 to Ts and VWC and the threshold of the change in response to the VWC under precipitation variation scenarios can benefit the prediction of future C balances in agroecosystems in semiarid regions under climate change.
CNN Based Wildlife Recognition with Super-Pixel Segmentation for Ecological Surveillance

Recent years, the convolutional neural network have shown to provide excellent results on recognition in different competitions. However, challenges in specific missions still exist. The cluttered backgrounds and rich feature changes of wild environment bring great challenges to the problem of species recognition of wild animals. To address these problems, this paper proposes a novel and effective combination to learn a CNN model. This is achieved by apply simple linear iterative clustering (SLIC)super-pixel segmentation method to unified data dimension during the process of making raw image data (captured by camera-traps)into a dataset. In short, the super-pixel-divided images provides the input of the convolutional neural network. In order to verify the application, we conducted a comprehensive performance comparisons between our SLIC-dataset and generally used Resize-dataset over CNN networks. Results proved that our proposed method performs exceptionally well in low-resolution data when it is crucial to take full advantage of the edge information of original images. In addition, we collected and annotated a standard camera-trap dataset of 14 common wildlife species in China, which contains 16,480 training images and 4,120 testing images.
Application of the gsp_m algorithm for the identification of behavioral patterns of people who shoplift

This work analyzes the results of the use of the algorithm GSP_M (Generalized Sequential Patterns + memory)for processing videos of surveillance in supermarkets, in order to identify the perpetration of thefts. It describes the theoretical framework of concepts used in video surveillance systems, their architecture, and, characteristics. It justified the use of sequential pattern identification algorithms as a tool to analyze human behavior in domains of shoplifting and mathematically define some concepts used by the tool. It describes the objectives of the application of video surveillance systems in supermarkets to minimize shoplifting, explaining that this is based on the fact that, monitored people have a behavior that can be characterized by a set of sequential actions, whose analysis allows obtaining conclusions to consider a person as a suspect, generating an alert or definitely an alarm. The GSP and GSP_M algorithms are described and compared. It details the procedure defined to evaluate the performance of the algorithm GSP_M in the domain of shoplifting, and, the comparison of the results obtained with the results of the GSP application.
Enhanced Memory for Fair-Related Faces and the Role of Trait Anxiety

The current research examined whether fair consideration—a social norm that people inherently prefer to confirm—would modulate face recognition. Each neutral face was associated with fair or unfair offers via an economic decision task, the Ultimatum Game (UG) task. After the UG, participants were asked to identify the faces of proposers who made different offers. Enhanced memory was observed for fair-related compared to unfair-related faces. Furthermore, high trait anxiety was associated with reduced memory for fair-related faces. These results were further confirmed by signal detection theory. The current research provided initial evidence that people showed enhanced memory for faces that made fair offers from the economic decision task, and that high trait anxiety was associated with reduced fair-related memory. Possible neural mechanisms and the implication in economic and social situations have been discussed.
Green Synthesis of Lead Sulphide Nanoparticles for High-Efficiency Perovskite Solar Cell Applications

In this study, lead sulfide (PbS) nanoparticles were synthesized by the chemical precipitation method using Aloe Vera extract with PbCl2 and Thiourea (H2N-CS-NH2). The synthesized nanoparticles have been investigated using x-ray diffraction (XRD), UV-Vis, energy-dispersive x-ray spectroscopy (EDX), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). XRD and TEM results confirm that the films are in the cubic phase. The crystallite size, lattice constant, micro-strain, dislocation density, optical bandgap, etc. have been determined using XRD and UV-Vis for investigating the quality of prepared nanoparticles. The possible application of these synthesized nanoparticles in the solar cells was investigated by fabricating the thin films on an FTO-coated and bare glass substrate. The properties of nanoparticles were found to be nearly retained in the film state as well. The experimentally found properties of thin films have been implemented for perovskite solar cell simulation and current-voltage and capacitance-voltage characteristics have been investigated. The simulation results showed that PbS nanoparticles could be a potential hole transport layer for high-efficiency perovskite solar cell applications.
Elucidating the Lipid Binding Properties of Membrane-Active Peptides Using Cyclised Nanodiscs

The lipid composition of the cellular membrane plays an important role in a number of biological processes including the binding of membrane-active peptides. Characterization of membrane binding remains challenging, due to the technical limitations associated with the use of standard biophysical techniques and available membrane models. Here, we investigate the lipid binding properties of two membrane-active peptides, VSTx1, a well characterized ion-channel inhibitor, identified from spider venom, that preferentially binds to anionic lipid mixtures, and AA139 an antimicrobial β-hairpin peptide with uncharacterised lipid binding properties, currently in pre-clinical development. The lipid binding properties of these peptides are elucidated using nanodiscs formed by both linear and circularized (sortase-mediated) forms of a membrane scaffold protein (MSP1D1ΔH5). We find that nanodiscs formed by circularized MSPs—in contrast to those formed by linear MSPs—are sufficiently stable under sample conditions typically used for biophysical measurements (including lipid composition, a range of buffers, temperatures and concentrations). Using these circularized nanodiscs, we are able to extract detailed thermodynamic data using isothermal titration calorimetry (ITC) as well as atomic resolution mapping of the lipid binding interfaces of our isotope labeled peptides using solution-state, heteronuclear, nuclear magnetic resonance (NMR) spectroscopy. This represents a novel and general approach for elucidating the thermodynamics and molecular interface of membrane-active peptides toward flat lipid bilayers of variable composition. Our approach is validated by first determining the thermodynamic parameters and binding interface of VSTx1 toward the lipid bilayer, which shows good agreement with previous studies using lipid micelles and liposomes. The method is then applied to AA139, where the membrane binding properties are unknown. This characterization, involved solving the high-resolution structure of AA139 in solution using NMR spectroscopy and the development of a suitable expression system for isotope labeling. AA139 was found to bind exclusively to anionic membranes with moderate affinity (Kd~low μM), and was found to have a lipid binding interface involving the termini of the β-hairpin structure. The preference of AA139 for anionic lipids supports a role for membrane binding in the mode-of-action of this peptide, which is also consistent with its higher inhibitory activity against bacterial cells compared to mammalian cells. The described approach is a powerful method for investigation of the membrane binding properties of this important class of molecules.
Preliminary Study: an Efficient Solving Algorithm for Determining the Exact Sampling Condition of Limited-Angle CT Reconstruction

In X-ray computed tomography (CT), it has been widely accepted that reconstruction methods inspired by compressive sensing (CS) can recover the image from an apparent reducing projection number. However, the quantitative study of sufficient sampling number of accurate reconstruction has high computational complexity, and it is limited by the size of the phantom. In this work, sampling condition of limited-angle accurate reconstruction is studied by testing the solution uniqueness in total variation (TV) minimization model. Solution uniqueness is verified by solving the l1 -norm minimization problem. To solve the problem and improve the efficiency, we propose a fast algorithm which is based on the alternating direction method of multipliers (ADMM). In the limited-angle problem, the proposed method quantifies the number of projection acquisitions for accurate reconstruction. The experimental results indicate that the proposed method is more computationally efficient than the existing method. And our method can reduce the limit of phantom size because the computational cost of our algorithm is approximately equivalent to the same size reconstruction problem.
"Who Is Your Neighbor… Like, What Flag Is Hanging off their Porch?": Intersectional Queer Homemaking in North Carolina

abstract:Thirteen semi-structured interviews provided qualitative data regarding residential selection by same-sex couples in North Carolina. Ambivalence about queer enclaves, the intersection of life factors, and the social context of neighborhoods were highlighted. The importance of the intersection of race and sexuality was especially prominent in the data. The social meaning of place is considered, including physical symbols such as yard signs, banners, and flags. There was no one grand narrative vis-à-vis sexuality and residential selection, and intersectional approaches are critically important to telling queer stories.
Effect of Dietary Inclusion of Soybean Hulls in the Diet on Feed Proximate Analysis, Egg Quality Parameters and Economics during Peak Egg Production Stages in Laying Hens

The study was designed to determine the effect of varying levels of soybean hulls inclusion in the diet of brown layer on, feed proximate analysis, egg quality, and economies during peak egg production period with different phases (phase-1=week 29 to 32, phase-2=week 33 to 36, and phase-3=week 37 to 40). One hundred and sixty golden misri (Brown) laying hens of age 28 weeks were sourced and reared for 40 weeks. There were 4 groups with 4 replicates per group containing 10 birds each. Corn-soybean meal diet (Basal Diet) was offered to the control group (A), while groups B, C, and D were fed the basal diet with 3, 6, and 9 % soybean hulls (SH) respectively. Results showed higher( P <0.05)crude fiber, ash, cellulose, and hemicellulose content for diets containing soybean hull (SH) at 3, 6, and 9% compared to the basal diet. Egg weight and egg quality parameters during different phases were not affected among the treatment groups. Total revenue and profit during all phases (phases 1, 2, and 3) while cost-benefit ratio during phase-1 and 2 were recorded significantly higher for the control group than all other treatment groups.It is concluded that the effect of different levels of soy hulls in diet did not affect egg weight and egg quality parameters during different phases but economic parameters were significantly higher ( P <0.05) amount in the control group than all soybean hull treatment groups. Among soybean hulls groups, 3% and 6% SH group showed better results than 9%SH group.
Acidity stress for the systemic elicitation of glyceollin phytoalexins in soybean plants

ABSTRACT Glyceollins are the major pathogen- and stress-inducible natural products (phytoalexins) of soybean that possess broad-spectrum anticancer and neuroprotective properties. Yet like other phytoalexins, glyceollins are difficult to obtain because they are typically biosynthesized only transiently and in low amounts in plant tissues. We recently identified acidity stress (pH 3.0 growth medium) as an elicitor that exerted prolonged (week-long) inductive effects on glyceollin biosynthesis and identified the NAC family TF gene GmNAC42-1 that activates glyceollin biosynthesis in response to acidity stress or WGE from the soybean pathogen Phytophthora sojae. GmNAC42-1 was annotated as an SAR gene and SAR genes were statistically overrepresented in the transcriptomic response to acidity stress suggesting that acidity stress triggers the systemic elicitation of glyceollin biosynthesis. Here, we demonstrate that acidity stress acts as a systemic elicitor when provided to soybean roots. Acidity stress preferentially elicited specific glyceollins in different soybean organs with exceptionally high yields of glyceollin I in root tissues.
Contemporary management of pain in cirrhosis: Toward precision therapy for pain

Chronic pain is highly prevalent in patients with cirrhosis and is associated with poor health‐related quality of life and poor functional status. However, there is limited guidance on appropriate pain management in this population, and pharmacologic treatment can be harmful, leading to adverse outcomes, such as gastrointestinal bleeding, renal injury, falls, and hepatic encephalopathy. Chronic pain can be categorized mechanistically into three pain types: nociceptive, neuropathic, and nociplastic, each responsive to different therapies. By discussing the identification, etiology, and treatment of these three mechanistic pain descriptors with a focus on specific challenges in patients with cirrhosis, we provide a framework for better tailoring treatments, including nonpharmacologic therapies, to patients' needs.
Ten-Year Legacy Effects of Three Eight-Month Exercise Training Programs on Cardiometabolic Health Parameters

Background: STRRIDE (Studies Targeting Risk Reduction Interventions through Defined Exercise) was an eight-month exercise study conducted from 1998–2003. Subjects were randomized to control or one of three exercise groups differing in intensity and amount. To determine if there were legacy effects, we invited 161 individuals who completed the intervention phase to return for a 10-year Reunion study. Methods: Subjects completed medical history and physical activity questionnaires. Height, body weight, blood pressure, waist circumference, and peak VO2 were measured. Fasting blood samples were analyzed for glucose, insulin and lipids. Of 161 original subjects, 153 were within 10 years of STRRIDE completion. Of these, 28 were lost to follow-up and 21 declined to participate in the Reunion study. Overall, 104 subjects (83% eligible) participated. Change over time was computed as the 10-year Reunion value minus the pre-intervention value. Significant within group changes were calculated using two-tailed t-tests. ANCOVA determined differences among groups with pre-intervention values as covariates. Bonferroni corrections were applied to account for multiple comparisons. Results: Ten years after completing STRRIDE, there were a number of group-specific health and fitness legacy effects. Original participation in either the moderate intensity exercise or control group resulted in a 10.5% decrease in peak VO2 over the ensuing 10 years. Conversely, both vigorous intensity groups experienced only a 4.7% decrement in cardiorespiratory fitness over that time period. As compared to controls, all three exercise groups experienced smaller increases in waist circumference. Those who participated in moderate intensity exercise experienced the greatest 10-year reduction in fasting insulin. Compared to all other groups, the moderate intensity subjects had greater reductions in mean arterial pressure at the Reunion timepoint. Summary: Ten years after completing a randomized eight-month exercise training intervention, previously sedentary individuals exhibited group-specific differences consistent with an intervention-based legacy effect on cardiorespiratory fitness and cardiometabolic parameters. These findings highlight the critical need to better understand the sustained legacy health effects of exercise training interventions.
Trapezoidal Pythagorean Fuzzy Linguistic Bonferroni Mean Operator based on the Preference Relation: A Case Study for Targeted Poverty Alleviation

The 19th session of national congress of the communist party of China reaffirmed its determination to win the fight against poverty. Therefore, it is of great importance to determine how to help people in different poverty-stricken areas. Bonferroni mean (BM), which can capture interrelationship among the individual arguments. And the intuitionistic preference relation is a powerful mean to express decision makers' information of intuitionistic preference over criteria in the process of decision making. Hence, in this paper, we present weighted trapezoidal Pythagorean fuzzy linguistic preference relation (TrPFLPR), afterwards, we propose the BM into trapezoidal Pythagorean fuzzy linguistic preference environment, present the trapezoidal Pythagorean fuzzy linguistic Bonferroni mean (TrPFLBM) operator and the weight TrPFLBM operator. In conclusion, a numerical instance about targeted poverty alleviation selection is given to demonstrate the method's effectiveness.