Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluid-Triggered Aftershocks in an Anisotropic Hydraulic Conductivity Geological Complex: The Case of the 2016 Amatrice Sequence, Italy

The mechanism by which faults interact each other is still a debated matter. One of the main issues is the role of pore-pressure diffusion in the delayed triggering of successive events. The 2016 Amatrice–Visso–Norcia seismic sequence (Central Apennines, Italy) provides a suitable dataset to test different physical mechanisms leading to delayed events. The sequence started on August 24, 2016, with the Amatrice mainshock (MW = 6), and was followed after more than 60 days by events in Visso (MW = 5.4) and Norcia (MW = 5.9). We analyzed the contribution of the static stress change and the role of fluids in the delayed triggering. Through 3D poroelastic modeling, we show that the Amatrice mainshock induced a pore-pressure diffusion and a normal stress reduction in the hypocentral area of the two aftershocks, favoring the rupture. Our parametric study employs a simple two-layered conductivity model with anisotropy in the seismogenic layer, characterized by larger conductivity values (K > 10–5 m/s) along the NNW-SSE direction. The one-way coupled pore-pressure 3-D diffusion modeling predicts the maximum increase of the pore pressure at the location of the two Visso earthquakes 60 days after the mainshock. The occurrence of anisotropic diffusivity is supported by the pattern of active faults and the strong crustal anisotropy documented by S-wave splitting analysis. We conclude that the temporal evolution of the sequence was controlled by the anisotropic diffusion of pore-pressure perturbations through pre-existing NNW-trending fracture systems.
Diagnosis for Latent Tuberculosis Infection: New Alternatives

Latent tuberculosis infection (LTBI) is a subclinical mycobacterial infection defined on the basis of cellular immune response to mycobacterial antigens. The tuberculin skin test (TST) and the interferon gamma release assay (IGRA) are currently used to establish the diagnosis of LTB. However, neither TST nor IGRA is useful to discriminate between active and latent tuberculosis. Moreover, these tests cannot be used to predict whether an individual with LTBI will develop active tuberculosis (TB) or whether therapy for LTBI could be effective to decrease the risk of developing active TB. Therefore, in this article, we review current approaches and some efforts to identify an immunological marker that could be useful in distinguishing LTBI from TB and in evaluating the effectiveness of treatment of LTB on the risk of progression to active TB.
Molecular Weight Impact of Poly(2,5-Benzimidazole) Polymer on Film Conductivity, Ion Exchange Capacity, Acid Retention Capability, and Oxidative Stability

In order to show the impact of the molecular weight (MW) of poly(2,5-benzimidazole) (ABPBI) on its physicochemical properties, a series of ABPBI polymers with different MWs ranging from 20 to 113 kDa were synthesized and fabricated into conductive films. The ABPBI films are characterized by different spectroscopic methods measuring the acid loading level, acid retention capability, ion exchange capacity (IEC), and the proton conductivity. Notably, the phosphoric acid (PA) loading ratio increased with the increase of ABPBI MW. The acid retention capability increased by 11% when the ABPBI MW reached 113 kDa. The fabricated ABPBI films exhibited good oxidative stability. A weight loss of only 9 wt% was observed for the high-MW ABPBI film compared to 19 wt% for the low-MW ABPBI film after 7 days in Fenton’s reagent at 65°C. The IEC increased with an order of magnitude when the ABPBI MW changed from 20 to 113 kDa. A maximum proton conductivity of 8.0 mS/cm was recorded for the high-MW film at 140°C, which was 45% higher than that for the low-MW ABPBI film. The proton conduction process followed the Grotthuss mechanism with a low activation energy (9.3 kJ mol) at the high-MW ABPBI film. These results indicated how important the ABPBI MW is in obtaining conductive films with remarkable properties for fuel cell (FC) applications. Prospectively, the findings of the current study can be implemented for other conductive polymers. Graphical Abstract Molecular weight control of ABPBI polymer to improve PEM conductivity.
Mechanics of Advanced Composite Structures

Active vibration control Classical shell theory Modified Galerkin method Magnetostrictive layers Rotating laminated composite cylindrical shell In this study, active control of free and forced vibration of rotating thin laminated composite cylindrical shells embedded with two magnetostrictive layers is investigated by means of classical shell theory. The shell is subjected to harmonic load exerted to inner surface of the shell in thickness direction. The velocity feedback control method is used in order to obtain the control law. The vibration equations of the rotating cylindrical shell are extracted by means of Hamilton principle while the effects of initial hoop tension, centrifugal and Coriolis accelerations are considered. The partial differential equations of the rotating cylindrical shell are converted to ordinary differential equations by means of modified Galerkin method. The displacement of the shell is obtained using modal analysis. The free vibration results of this study are validated by comparison with the results of published literature. Also, the forced vibration result is compared with the result of fourth order Runge-Kutta method to prove its correctness. Finally, the effects of several parameters including circumferential wave number, rotational velocity, the whole thickness of orthotropic layers, the whole thickness of orthotropic layers, length, the amplitude and exciting frequency of the load on the vibration characteristics of the rotating cylindrical shell are investigated. * Corresponding author. Tel. : +98-21-84063215; Fax: +98-21-88674748 E-mail address: sh.mrezazadeh@gmail.com DOI: 10.22075/MACS.2020. 16921.1191 Received 2019-01-06; Received in revised form 2019-11-14; Accepted 2020-06-19 © 2020 Published by Semnan University Press. All rights reserved.
Prevalence, Distribution, and Diversity of Salmonella Strains Isolated From a Subtropical Lake

This study investigated the prevalence, serovar distribution, antimicrobial resistance, and pulsed field gel electrophoresis (PFGE) typing of Salmonella enterica isolated from Lake Zapotlán, Jalisco, Mexico. Additionally, the association of the presence of Salmonella with physicochemical and environmental parameters was analyzed using Pearson correlation analysis and principal component analysis (PCA). Salmonella spp. were identified in 19 of 63 (30.15%) samples. The prevalence of Salmonella was positively correlated with air temperature, electrical conductivity, pH, and dissolved oxygen and negatively correlated with relative humidity, water temperature, turbidity, and precipitation. The predominant serotype identified was Agona (68.48%), followed by Weltevreden (5.26%), Typhimurium (5.26%), and serogroup B (21.05%). Overall, the highest detected antimicrobial resistance was toward colistin (73.68%), followed by sulfamethoxazole (63.15%), tetracycline (57.89%), nalidixic acid (52.63%), and trimethoprim (52.63%). All Salmonella strains were genetically diverse, with a total of 11 XbaI and four BlnI profiles on PFGE. The use of these two enzymes allowed differentiate strains of Salmonella of the same serotype. The results obtained in this study contribute to a better understanding of the Salmonella spp. ecology in an endorheic subtropical lake and provide information for decision makers to propose and implement effective strategies to control point and non-point sources of pathogen contamination.
Enhancing Internal Learning in Teams: The Role of Network Centrality and Psychological Capital of Undergraduate Students

This study aims to analyze the mediating role of psychological capital (PsyCap) in the relationship between network centrality and internal learning in teams. A questionnaire was administered to 480 undergraduate students to test this relationship. The results confirmed the positive relationship between network centrality and internal learning in teams, and a mediating role of PsyCap in the relationship between student network centrality and internal learning in teams. This study suggests that it is important to promote centrality in advice networks among undergraduate students. In addition, this study might raise awareness among students, teachers, and public policymakers about the need to promote a socially responsible environment in higher education institutions.
Early-Occurring Dendritic Spines Alterations in Mouse Models of Alzheimer’s Disease Inform on Primary Causes of Neurodegeneration

The consensus that synaptic failure is the earliest cause of cognitive deterioration in Alzheimer’s disease (AD) has initially led to investigate structural (dendritic spines) and physiological (LTP) synaptic dysfunctions in mouse models of AD with established cognitive alterations. The challenge is now to track down ultra-early alterations in spines to uncover causes rather than disease’s symptoms. This review article pinpoints dysregulations of the postsynaptic density (PSD) protein network which alter the morphology and function of spines in pre- and early- symptomatic hAPP mouse models of AD, and, hence, inform on primary causes of neurodegeneration.
Next-Generation Digital Ecosystem for Climate Data Mining and Knowledge Discovery: A Review of Digital Data Collection Technologies

Climate change has been called “the defining challenge of our age” and yet the global community lacks adequate information to understand whether actions to address it are succeeding or failing to mitigate it. The emergence of technologies such as earth observation (EO) and Internet-of-Things (IoT) promises to provide new advances in data collection for monitoring climate change mitigation, particularly where traditional means of data exploration and analysis, such as government-led statistical census efforts, are costly and time consuming. In this review article, we examine the extent to which digital data technologies, such as EO (e.g., remote sensing satellites, unmanned aerial vehicles or UAVs, generally from space) and IoT (e.g., smart meters, sensors, and actuators, generally from the ground) can address existing gaps that impede efforts to evaluate progress toward global climate change mitigation. We argue that there is underexplored potential for EO and IoT to advance large-scale data generation that can be translated to improve climate change data collection. Finally, we discuss how a system employing digital data collection technologies could leverage advances in distributed ledger technologies to address concerns of transparency, privacy, and data governance.
Patients With Rheumatoid Arthritis Increased Risk of Developing Osteoarthritis: A Nationwide Population-Based Cohort Study in Taiwan

Objective: To investigate the risk of developing OA in patients diagnosed with RA. Methods: In this study, we presented gender, age, urbanization, occupation and, comorbidities in a RA cohort and a non-RA cohort based on number and percentage. We investigated the OA risk in patients with RA. We conducted a retrospective cohort study with a 13-year longitudinal follow-up in Taiwan. Patients who received RA diagnoses between 2000 and 2012 were enrolled in the study cohort. The non-RA cohort were 1:1 propensity score matched with the RA cohort by age, gender, index year, urbanization, occupation, and comorbidities. The hazard ratios (HRs) and adjusted HRs (aHRs) were estimated after confounders were adjusted. Sensitivity analysis utilizing the Longitudinal Health Insurance Database (LHID) was conducted. Results: We totally enrolled 63,626 cases in RA patients (study cohort) and matched controls. In the RA cohort, the crude HR for OA was 2.86 (95% confidence interval (CI), 2.63–3.11, p < 0.001), and the aHR was 2.75 (95% CI, 2.52–2.99, p < 0.001). (The study demonstrated that patients with RA had a higher risk for developing OA compared with the non-RA controls. Conclusion: Developing effective OA prevention strategies are necessary in patients with RA. This finding may be extended to evaluate the risk of OA among other kinds of inflammatory autoimmune diseases. Identifying the key pathogenesis mechanisms are necessary in the future study.
Do agrochemicals used during soybean flowering affect the visits of Apis mellifera L.

In the Pampa region of Argentina, most beehives are situated near to soybean [ Glycine max (L.) Merr. ] crop and honey bees ( Apis mellifera L.) use its floral resources. Soybean is often sprayed with pesticides but very little is known about their repellent action against bees. This study evaluates the visit of honey bees to crop after the application of agrochemicals aiming to check for repellency of them and estimate the possible impact on crop pollination . For this, six treatments were used (glyphosate + cypermethrin; glyphosate; cypermethrin; lambda-cyhalothrin; methoxyfenocide; Bacillus thuringiensis ) and developed on plots of 625 m 2 , located in Oro Verde (Argentina), applying two sprays during the crop flowering. The bees were captured using entomological net every 4 days in three different times from the day after the first spraying and up the end of crop flowering. The results showed very little or no repellent action of pesticides on A. mellifera , noting that it foraged on soybean flowers regardless of the temporal proximity and the type of product used in sprays. Possible causes are discussed and the need for larger studies is evident in field conditions related to pesticides repellency and mixtures. Also, further evaluation of the effects of the different chemical formulations available on the market and used regionally where the subspecies A . mellifera can be found. Simultaneously some management practices that could help minimize the risk of contamination are mentioned; the use of defensive crop products of biological origin is encouraged as well as further research in this topic.
Distinguishing Intermediate and Novice Surgeons by Eye Movements

Surgical skill-level assessment is key to collecting the required feedback and adapting the educational programs accordingly. Currently, these assessments for the minimal invasive surgery programs are primarily based on subjective methods, and there is no consensus on skill level classifications. One of the most detailed of these classifications categorize skill levels as beginner, novice, intermediate, sub-expert, and expert. To properly integrate skill assessment into minimal invasive surgical education programs and provide skill-based training alternatives, it is necessary to classify the skill levels in as detailed a way as possible and identify the differences between all skill levels in an objective manner. Yet, despite the existence of very encouraging results in the literature, most of the studies have been conducted to better understand the differences between novice and expert surgical skill levels leaving out the other crucial skill levels between them. Additionally, there are very limited studies by considering the eye-movement behaviors of surgical residents. To this end, the present study attempted to distinguish novice- and intermediate-level surgical residents based on their eye movements. The eye-movement data was recorded from 23 volunteer surgical residents while they were performing four computer-based simulated surgical tasks under different hand conditions. The data was analyzed using logistic regression to estimate the skill levels of both groups. The best results of the estimation revealing a 91.3% recognition rate of predicting novice and intermediate surgical residents on one scenario were selected from four under the dominant hand condition. These results show that the eye-movements can be potentially used to identify surgeons with intermediate and novice skills. However, the results also indicate that the order in which the scenarios are provided, and the design of the scenario, the tasks, and their appropriateness with the skill levels of the participants are all critical factors to be considered in improving the estimation ratio, and hence require thorough assessment for future research.
Individual Response Variation in the Effects of Weight Loss and Exercise on Insulin Sensitivity and Cardiometabolic Risk in Older Adults

Weight loss induced by decreased energy intake (diet) or exercise generally has favorable effects on insulin sensitivity and cardiometabolic risk. The variation in these responses to diet-induced weight loss with or without exercise, particularly in older obese adults, is less clear. The objectives of our study were to (1) examine the effect of weight loss with or without exercise on the variability of responses in insulin sensitivity and cardiometabolic risk factors and (2) to explore whether baseline phenotypic characteristics are associated with response. Sedentary older obese (BMI 36.3 ± 5.0 kg/m2) adults (68.6 ± 4.7 years) were randomized to one of 3 groups: health education control (HED); diet-induced weight loss (WL); or weight loss and exercise (WL + EX) for 6 months. Composite Z-scores were calculated for changes in insulin sensitivity (C_IS: rate of glucose disposal/insulin at steady state during hyperinsulinemic euglycemic clamp, HOMA-IR, and HbA1C) and cardiometabolic risk (C_CMR: waist circumference, triglycerides, and fasting glucose). Baseline measures included body composition (MRI), cardiorespiratory fitness, in vivo mitochondrial function (ATPmax; P-MRS), and muscle fiber type. WL + EX groups had a greater proportion of High Responders in both C_IS and C_CMR compared to HED and WL only (all p < 0.05). Pre-intervention measures of insulin (r = 0.60) and HOMA-IR (r = 0.56) were associated with change in insulin sensitivity (C_IS) in the WL group (p < 0.05). Pre-intervention measures of glucose (r = 0.55), triglycerides (r = 0.53), and VLDL (r = 0.53) were associated with change in cardiometabolic risk (C_CMR) in the WL group (p < 0.05), whereas triglycerides (r = 0.59) and VLDL (r = 0.59) were associated with C_CMR (all p < 0.05) in WL + EX. Thus, the addition of exercise to diet-induced weight loss increases the proportion of older obese adults who improve insulin sensitivity and cardiometabolic risk. Additionally, individuals with poorer metabolic status are more likely to experience greater improvements in cardiometabolic risk during weight loss with or without exercise.
Contamination of aqueous glycerol solution by Cladosporium cladosporioides

trees to pathogenic fungi. Kentucky Ag. Exp. Station Rep. 1977. Pp. 132-133. , and P. L. Cornelius. 1979. Quantitative inoculation of eastern cottonwood leaf tissue with Melampsora medusae under controlled conditions. Phytopathology 69: 301-304. , and U. Jirlfors. 1987. Ultrastructure of eastern cottonwood clones susceptible or resistant to leaf rust. Canad. J. Bot. 65: 1586-1598. i i. e tucky g. Exp. StaWidin, K. D. , and A. L. Schipper, Jr. 1981. Effect of Melampsora medusae leaf rust infection on yield of hybrid poplars in the north-central United States. Eur. J. Forest Pathol. 11: 438-448. Willing, R. R. , and L. D. Pryor. 1976. Interspecific hybridisation in poplar. Theoret. Appl. Genetics 47: 141-151. Ziller, W. G. 1974. The tree rusts of western Canada. Canad. For. Service Publ. 1329. 272 p. i , K. D. , and A. L. Schipper, Jr. 981. Effect of la psora medusae leaf rust infecti on yield brid poplars in the north-central United States.
COVID-19 Likely Launches Multipronged Attack on Kidneys

Sault Ste. Marie, Michigan, had only two confirmed COVID-19 cases by early May, but the pandemic was still hitting its healthcare system hard. With the small city’s War Memorial Hospital mostly shut down and elective procedures postponed, the hospital was on shaky financial ground. “My biggest concern is how all of this will impact the overall financial viability of our hospital,” said David Jahn, War Memorial president and CEO. In early May, the hospital was projecting revenues would be down for the year by 40%, or $35 million, if the coronavirus shutdown continued. The loss is not sustainable, Jahn said. Eighty percent of the hospital’s revenue is from outpatient services, which declined by 53% in April. That tracks with the national average—79% of rural hospital revenue is from outpatient care, according to the Chartis Center for Rural Health. The center is part of the Chartis Group, a healthcare advisory and analytics services firm. As states shut down across the country, elective proceRural Health Hit Hard by COVID-19 Shutdown COVID-19 Likely Launches Multipronged Attack on Kidneys
Dynamic Functional Connectivity of Resting-State Spinal Cord fMRI Reveals Fine-Grained Intrinsic Architecture

The neuroimaging community has shown tremendous interest in exploring the brain's spontaneous activity using functional magnetic resonance imaging (fMRI). On the contrary, the spinal cord has been largely overlooked despite its pivotal role in processing sensorimotor signals. Only a handful of studies have probed the organization of spinal resting-state fluctuations, always using static measures of connectivity. Many innovative approaches have emerged for analyzing dynamics of brain fMRI, but they have not yet been applied to the spinal cord, although they could help disentangle its functional architecture. Here, we leverage a dynamic connectivity method based on the clustering of hemodynamic-informed transients to unravel the rich dynamic organization of spinal resting-state signals. We test this approach in 19 healthy subjects, uncovering fine-grained spinal components and highlighting their neuroanatomical and physiological nature. We provide a versatile tool, the spinal innovation-driven co-activation patterns (SpiCiCAP) framework, to characterize spinal circuits during rest and task, as well as their disruption in neurological disorders.
Reliability-Oriented Automated Design of Double-Sided Cooling Power Module: A Thermo-Mechanical-Coordinated and Multi-Objective-Oriented Optimization Methodology

Compared with the traditional single-sided cooling (SSC) power module, owing to the decreased thermal resistance and packaging parasitics, the double-sided cooling (DSC) power module is a promising solution of the motor drive for electric vehicle (EV) implementation. However, the lack of the model to characterize the thermo-mechanical interaction mechanism in the DSC power module challenges the co-design methodology of the power module from the respective of multi-physics. In this paper, aiming at reliability improvement, to balance the tradeoff between thermal resistance and mechanical stress, a multi-objective-coordinated automated design methodology is proposed for the DSC power module. To characterize the influences of material properties and structure sizes, the mathematical models for the thermal and mechanical features of the DSC power module are proposed. These models are also examined by using the finite element analysis (FEA) tool. Besides, to promote the specifications of DSC power module, a multi-objective optimization model is proposed to coordinate thermo-mechanical metrics in multi-physics. The non-dominated sorting genetic algorithm II (NSGA-II) is implemented to automatically achieve the Pareto solutions of the proposed multi-objective optimization model with respect to thermal resistance and mechanical stress. Considering the influences of material properties, optimal structure sizes of the DSC power module are comprehensively presented. The proposed multi-objective-oriented optimization methodology provides a new routine to reshape the thermo-mechanical performance of the next-generation DSC power module toward more reliable EV implementation.