Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of quantitative trait loci for milk protein percentage in Murrah buffaloes

Milk protein is an important constituent of milk in buffaloes and is moderately heritable. The milk protein percentage varies significantly between breeds/herds/species. Buffaloes can be selected for higher milk protein percentage and this paper provides QTLs for marker assisted selection in buffaloes. The milk protein percentage records on 2,028 daughters belonging to 12 half sib families were analyzed for the identification of QTLs on 8 chromosomes in buffaloes using chromosome scans. The single marker analysis revealed 74 markers to be associated with milk protein percentage in 12 sire families. When common markers were removed from the analysis, 51 markers remained. The Interval mapping using R/qtl identified 69 QTLs in 12 half sib families on 8 chromosomes of buffalo. The meta QTL analysis defined 25 consensus QTL regions in buffaloes for milk protein percentage. Most of the QTLs identified have been reported for cattle however few new chromosomal locations were also identified to be associated with milk protein percentage in buffaloes. Comparative genomics revealed 1117 genes underlying the QTL regions associated with milk protein percentage. Among these, 109 genes were directly associated with protein metabolism. The protein-protein interaction among the genes and gene ontology analysis and pathways have been identified. These 109 genes have potential to be candidate genes for milk protein percentage in buffaloes.
Magnon gas and deviation from the Bloch law in a nanoscale Heisenberg ferromagnet

It is known that saturation magnetization of ferromagnetic nanoparticles and nanoclusters deviates strongly from the Bloch T 3/2 law. To describe the deviation one usually uses a modified power law T α with a size dependent exponent α, which is motivated simply by its flexibility in fitting the observed behavior. By considering the Heisenberg spin model we derive an explicit expression in terms of a magnon gas which generalizes the Bloch formula to a finite size system. Comparison to the experimental data shows good agreement with the observed behavior and gives a better understanding of its physics.
Parameter Estimation of Different Photovoltaic Models Using Hybrid Particle Swarm Optimization and Gravitational Search Algorithm

The performance of a typical solar energy-based system can be improved by accurately modeling the current versus voltage characteristics of the involved solar cells. However, estimating the exact value of parameters related to solar cells is quite challenging. The optimization function, considering the current–voltage characteristics of solar cells, requires the solution of sophisticated non-linear and multi-modal optimization methods. So far, various optimization approaches have been reported. This paper proposes the application of a new hybrid algorithm, i.e., Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA), which is a combination of two algorithms, i.e., Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) method. The hybrid PSOGSA algorithm is superior to other algorithms in terms of higher accuracy in searching for optimal solutions and better explorative capability. Moreover, the developed hybrid algorithm is benchmarked using ten standard test functions to verify its efficiency. In this manuscript, monocrystalline and polycrystalline solar cells are considered. The parameter optimization results are obtained using PSOGSA and further compared with those obtained using other algorithms presented in the literature, such as PSO, GSA, MVO, HBO, PO and SCA. The complete error analysis is carried out for the modified single-diode model (MSDM), the modified double-diode model (MDDM), and the modified three-diode model (MTDM) of photovoltaic (PV) cells to prove the superiority of the PSOGSA. Moreover, statistical results are carried out based on Friedman’s ranking and Wilcoxon’s rank sum test. The comparison results show that the proposed PSOGSA is better than other algorithms in estimating the unknown PV model parameters.
Machine Learning Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor

The walkability of a neighborhood impacts public health and leads to economic and environmental benefits. The condition of sidewalks is a significant indicator of a walkable neighborhood as it supports and encourages pedestrian travel and physical activity. However, common sidewalk assessment practices are subjective, inefficient, and ineffective. Current alternate methods for objective and automated assessment of sidewalk surfaces do not consider pedestrians’ physiological responses. We developed a novel classification framework for the detection of irregular walking surfaces that uses a machine learning approach to analyze gait parameters extracted from a single wearable accelerometer. We also identified the most suitable location for sensor placement. Experiments were conducted on 12 subjects walking on good and irregular walking surfaces with sensors attached at three different locations: right ankle, lower back, and back of the head. The most suitable location for sensor placement was at the ankle. Among the five classifiers trained with gait features from the ankle sensor, Support Vector Machine (SVM) was found to be the most effective model since it was the most robust to subject differences. The model’s performance was improved with post-processing. This demonstrates that the SVM model trained with accelerometer-based gait features can be used as an objective tool for the assessment of sidewalk walking surface conditions.
Choice of treatment evaluated after trial periods with bone conduction devices and contralateral routing of sound systems in patients with single‐sided deafness

Patients with single‐sided deafness (SSD) may experience difficulties with speech perception in noise, sound localization, have tinnitus and experience a reduced quality of life (QoL). contralateral routing of sound hearing aids (CROS) or bone conduction devices (BCD) may partly improve subjective speech communication and QoL in SSD patients. A trial period with these devices can help in making a well‐informed choice of treatment. Our aim was to evaluate factors influencing the choice of treatment made after a BCD and CROS trial period in adult SSD patients.
Opportunities for Recycling PV Glass and Coal Fly Ash into Zeolite Materials Used for Removal of Heavy Metals (Cd, Cu, Pb) from Wastewater

This work shows the development and characterization of two zeolite structures by recycling PV glass and coal fly ash for the removal of cadmium, copper, and lead from synthetic solutions containing one or three cations. The materials were characterized in terms of crystalline structure (XRD), morphology (SEM, AFM), and specific surface. For increasing the heavy-metals removal efficiency, the adsorption conditions, such as substrate dosage, preliminary concentration, and contact time, were optimized. The pseudo-second-order kinetic model adsorption kinetics fit well to describe the activity of the zeolites ZFAGPV-A and ZFAGPV-S. The zeolite adsorption equilibrium data were expressed using Langmuir and Freundlich models. The highest adsorption capacities of the ZFAGPV-A zeolite are qmaxCd = 55.56 mg/g, qmaxCu = 60.11 mg/g, qmaxPb = 175.44 mg/g, and of ZFAGPV-S, are qmaxCd = 33.45 mg/g, qmaxCu = 54.95 mg/g, qmaxPb = 158.73 mg/g, respectively. This study demonstrated a new opportunity for waste recycling for applications in removing toxic heavy metals from wastewater.
SHAKEDOWN OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMED STRUCTURES

Structures subjected to variable repeated loads can undergo the shakedown or adaptation phenomenon,-which prevents them from collapse but may cause lack of serviceability, for the plastic deformations developed, although finite, as shakedown occurrence postulates, may exceed some maximum values imposed by external ductility criteria. This paper is devoted to the optimal design of reinforced concrete structures, subjected to variable and repeated loads. For such structures the knowledge of the actual values taken by the plastic deformations, at shakedown occurrence, is a crucial issue. An approximate assessment of such plastic deformations is needed, which is herein provided in the shape of quadratic constraints, by the so-called perturbation method. By suitable finite element discretization, the optimal shakedown problem is formulated as a convex nonlinear mathematical programming one. The M-N (bending moment-axial force) interaction is accounted for in the aim to provide the optimal shakedown design. The.
Blind image restoration based on parzen-window estimate and regularization method

To investigate blind image restoration problem, we propose to combine Parzen-window estimate with regularization technique (PWERT) in this paper. Parzen-window estimate method is engaged to obtain point spread function. And regularization technique is utilized to control the noise deterioration and ill-posed case during image restoration. Experiment results show that PWERT is able to deblur degraded image effectively and is robust to noise.
Effect of inflammation on cytochrome P450-mediated arachidonic acid metabolism and the consequences on cardiac hypertrophy

Abstract The incidence of heart failure (HF) is generally preceded by cardiac hypertrophy (CH), which is the enlargement of cardiac myocytes in response to stress. During CH, the metabolism of arachidonic acid (AA), which is present in the cell membrane phospholipids, is modulated. Metabolism of AA gives rise to hydroxyeicosatetraenoic acids (HETEs) and epoxyeicosatrienoic acids (EETs) via cytochrome P450 (CYP) ω-hydroxylases and CYP epoxygenases, respectively. A plethora of studies demonstrated the involvement of CYP-mediated AA metabolites in the pathogenesis of CH. Also, inflammation is known to be a characteristic hallmark of CH. In this review, our aim is to highlight the impact of inflammation on CYP-derived AA metabolites and CH. Inflammation is shown to modulate the expression of various CYP ω-hydroxylases and CYP epoxygenases and their respective metabolites in the heart. In general, HETEs such as 20-HETE and mid-chain HETEs are pro-inflammatory, while EETs are characterized by their anti-inflammatory and cardioprotective properties. Several mechanisms are implicated in inflammation-induced CH, including the modulation of NF-κB and MAPK. This review demonstrated the inflammatory modulation of cardiac CYPs and their metabolites in the context of CH and the anti-inflammatory strategies that can be employed in the treatment of CH and HF.
Phenolic Profile and the Antioxidant, Anti-Inflammatory, and Antimicrobial Properties of Açaí (Euterpe oleracea) Meal: A Prospective Study

The mechanical extraction of oils from Brazilian açaí (Euterpe oleracea Mart) produces significant amounts of a byproduct known as “meal”, which is frequently discarded in the environment as waste material. Nevertheless, plant byproducts, especially those from oil extraction, may contain residual polyphenols in their composition and be a rich source of natural bioactive compounds. In this study, the phenolic composition and in vitro biological properties of a hydroethanolic açaí meal extract were elucidated. The major compounds tentatively identified in the extract by high-resolution mass spectrometry were anthocyanins, flavones, and flavonoids. Furthermore, rhamnocitrin is reported in an açaí byproduct for the first time. The extract showed reducing power and was effective in scavenging the ABTS radical cation (820.0 µmol Trolox equivalent∙g−1) and peroxyl radical (975.7 µmol Trolox equivalent∙g−1). NF-κB activation was inhibited at 10 or 100 µg∙mL−1 and TNF-α levels were reduced at 100 µg∙mL−1. However, the antibacterial effects against ESKAPE pathogens was not promising due to the high concentration needed (1250 or 2500 µg∙mL−1). These findings can be related to the diverse polyphenol-rich extract composition. To conclude, the polyphenol-rich extract obtained from açaí meal showed relevant biological activities that may have great applicability in the food and nutraceutical industries.
Thymus musilii Velen. Methanolic Extract: In Vitro and In Silico Screening of Its Antimicrobial, Antioxidant, Anti-Quorum Sensing, Antibiofilm, and Anticancer Activities

Thymus musilii Velen. is a rare plant species cultivated in the Ha’il region (Saudi Arabia) under greenhouse conditions. In this work, we described, for the first time, the phytochemical composition, antimicrobial, antioxidant, anti-quorum sensing, and anticancer activities of T. musilii methanolic extract using both experimental and computational approaches. The obtained results showed the identification of eight small-like peptides and eighteen phyto-compounds by using high-resolution liquid chromatography–mass spectrometry (HR-LCMS) dominated mainly by compounds belonging to isoprenoid, fatty acyl, flavonoid, and alkaloid classes. The tested extracts exhibited high antifungal and antibacterial activity with the mean diameter of growth inhibition zones ranging from 12.33 ± 0.57 mm (Pseudomonas aeruginosa ATCC 27853) to 29.33 ± 1.15 mm (Candida albicans ATCC 10231). Low minimal inhibitory concentrations were recorded for the tested micro-organisms ranging from 0.781 mg/mL to 12.5 mg/mL. While higher doses were necessary to completely kill all tested bacterial and fungal strains. Thyme extract was able to scavenge DPPH•, ABTS•+, β-carotene, and FRAP free radicals, and the IC50 values were 0.077 ± 0.0015 mg/mL, 0.040 ± 0.011 mg/mL, 0.287 ± 0.012 mg/mL, and 0.106 ± 0.007 mg/mL, respectively. The highest percentage of swarming and swimming inhibition was recorded at 100 µg/mL with 39.73 ± 1.5% and 25.18 ± 1%, respectively. The highest percentage of biofilm inhibition was recorded at 10 mg/mL for S. typhimurium ATCC 14028 (53.96 ± 4.21%) and L. monocytogenes ATCC 7644 (49.54 ± 4.5 mg/mL). The in silico docking study revealed that the observed antimicrobial, antioxidant, and anticancer activities of the constituent compounds of T. musilii are thermodynamically feasible, notably, such as those of the tripeptides (Asn-Met-His, His-Cys-Asn, and Phe-His-Gln), isoprenoids (10-Hydroxyloganin), and diterpene glycosides (4-Ketoretinoic acid glucuronide).
Dieting Behavior Characterized by Caloric Restriction and Relation to Sleep: A Brief Contemporary Review

There is sufficient evidence showing that greater sleep quality improves weight loss outcomes achieved through dietary modifications; however, the effects of dietary modifications such as caloric restriction on sleep outcomes is less established. Caloric restriction is a commonly recommended weight-loss method, yet it may result in short-term weight loss and subsequent weight regain, known as “weight cycling”, which has recently been shown to be associated with both poor sleep and worse cardiovascular health. The purpose of this brief narrative review was to summarize the evidence from recent studies of the effects of caloric restriction on sleep. Six articles were identified that specifically measured effects of a caloric restriction-based intervention on aspects of sleep as primary or secondary outcomes. Most research to date indicates that caloric restriction improves sleep outcomes including sleep quality and sleep onset latency. However, the relation between caloric restriction and sleep duration is less clear. Given the mixed results and the potential for severe caloric restriction to lead to weight cycling, future studies are needed to clarify how caloric restriction affects sleep and the potential implications for weight-management efforts.
Transient receptor potential melastatin 7 aggravates necrotizing enterocolitis by promoting an inflammatory response in children

Background As a rare disease in children, necrotizing enterocolitis (NEC) leads to high morbidity and mortality. However, its pathophysiology is largely unclear. Transient receptor potential melastatin 7 (TRPM7) is a membrane protein, which plays key roles in the inflammatory response. This study sought to examine the promoting effect of TRPM7 on NEC in children and explore the therapeutic effect of a TRPM7 inhibitor NS8593. Methods First, we detected TRPM7 and NLR family pyrin domain containing 3 (NLRP3) expression and the state of inflammation in children with NEC through quantitative real-time polymerase chain reaction (RT-PCR), Western blot, and enzyme-linked immunosorbent assays. Next, Human intestinal epithelial cell lines were induced to NEC by lipopolysaccharides (LPSs). The level of cytokines and reactive oxygen species (ROS) were tested by RT-PCR and flow cytometry. The TRPM7 mediated calcium flux were determined by fluorescence. In addition, we used the TRPM7 inhibitor NS8593 to treat the in vivo rat model. The mRNA and protein expression were determined by real-time PCR and Elisa analysis, respectively. Results TRPM7 and NLRP3 expression was more increased in the samples from children with NEC compared to the control samples. Additionally, the elevated secretion of interleukin-1β, interleukin-6, and tumor necrosis factor alpha was also detected in the serum of children with NEC. These results showed that TRPM7 had a promoting effect on NEC development, possibly via the activation of NLRP3. To test our hypothesis, the TRPM7 inhibitor NS8593 was used to treat the LPS-stimulated IEC-6 cells. We found that the TRPM7 inhibitor NS8593 inhibited LPS-induced cytokine production and exhibited an anti-inflammatory effect by alleviating TRPM7-mediated NLRP3 inflammasome activation. Through in-vivo experiments, we found that TRPM7 was involved in the occurrence of NEC, and its inhibitor NS8593 played a certain therapeutic role in the rat model. Conclusions Our study revealed TRPM7 inhibitors attenuated LPS-induced ROS and reduced the release of pro-inflammatory cytokines. It also exhibited protective effects on the NEC model.
On the along-track acceleration of the LAGEOS satellite

The Earth-induced Yarkovsky thermal drag is known to be the principal drag mechanism for LAGEOS. In combination with charged and neutral particle drag this thermal drag can account for all of the observed average along-track acceleration as well as its long periodic variation, if we allow for an alignment of the satellite's spin axis with the Earth's polar axis, decreasing the colatitude of the spin axis by 50% every 6 years. This motion is probably due to the interaction of eddy currents in the satellite and the Earth's magnetic field. The spin axis appears not to precess in longitudinal direction, indicating that gravitational torques hardly affect the satellite. Calculations confirm that the related principal moments of inertia of the spacecraft differ much less than generally assumed. A combination of two other force models, operating only during the partly eclipsed orbital periods, is likely to explain most of the anomalous residual fluctuations in the along-track acceleration. The first model is the Yarkovsky-Schach effect, a variant of the aforementioned thermal drag, involving heating by the Sun. The second embodies anisotropic reflection of sunlight by LAGEOS' surface; one hemisphere of the satellite probably has a specular albedo, which is about 5% larger than the other. By applying these two models, in addition to particle and Yarkovsky thermal drag, the standard deviation of the residual acceleration could be reduced by 61%.
Optimal Scheduling of Battery-Swapping Station Loads for Capacity Enhancement of a Distribution System

A battery-swapping station (BSS) can serve as a flexible source in distribution systems, since electric vehicle (EV) batteries can be charged at different time periods prior to their swapping at a BSS. This paper presents an EV battery service transformation from charging to swapping batteries for EVs for the capacity enhancement of a distribution system. A novel mathematical model is proposed to optimally quantify and maximize the flexibility of BSS loads in providing demand response for the utility operator while considering technical operations in the distribution grid. Case studies and numerical findings that consider data from the National Household Travel Survey and a 32-bus distribution system are reported and discussed to demonstrate the effectiveness of the proposed model. Offering battery-swapping services helps reduce not only the peak load, but also the station operation cost.
Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.
Fabrication of Woven Jute Fiber Epoxy Bio-Composites through the Epoxy/Thiol-Ene Photopolymerization Technique

An eco-friendly epoxy/thiol-ene photopolymerization (ETEP) process was employed to prepare epoxy bio-composites using a commercial biobased epoxy resin and a woven jute fabric as reinforcement. In this process the components of the thiol-ene system, an allyl-functionalized ditertiary amine curing agent, a multifunctional thiol and a radical photoinitiator, were added to the epoxy resin to produce a polyether–polythioether crosslinked co-network. Moreover, the jute fibers were functionalized with thiol groups using the 3-mercaptopropyl (trimethoxysilane) with the purpose of creating a chemically bonded polymeric matrix/fiber system. The obtained bio-composites prepared with the thiol-functionalized cellulose fibers exhibited an increase up to 52% and 40% in flexural modulus and strength with respect to the non-functionalized counterparts. Under the three-point bending loadings, the composites displayed higher deformation at break and toughness due to the presence of polythioethers in the co-network. The prepared bio-composites developed in this work are excellent candidates to extend the use of cellulose fibers for structural applications.