Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation of intragranular plastic deformation localization in FCC polycrystals by Discrete Dislocation Dynamics

Strain localization mechanisms taking place in polycrystal grains are investigated using Discrete Dislocation Dynamics (DDDs) simulations. First, elastic Finite Element Method simulations are used to calculate the intragranular stress distribution linked to strain incompatibilities between grains. Many configurations are tested to evaluate the stress heterogeneity and constitute a database for DDD simulations. From the analysis of these microstructures, a criterion is proposed to identify the grains where the emergence of the localization of the deformation is the most likely. Then, DDD simulations are used to explore the plastic strain localization phenomenon at the grain scale. Those simulations show that stress concentrations close to a polycrystal quadruple node can play a fundamental role in plastic strain localization. This work paves the way for future investigations to be made thanks to DDD simulations regarding slip band initiation and strain relaxation phenomena.
Hydrodynamics of Mount Simon Sandstone, Ohio and Adjoining Areas: ABSTRACT

The Mount Simon Sandstone (Cambrian), the most favorable stratum for waste injection in Ohio, presently accepts about 250 × 106 gal of industrial waste per year. Concern has been expressed about the transport of these fluids by natural hydrodynamic flow. The potentiometric surface map of the Mount Simon reservoir of Ohio has a form which mirrors the structural configuration--highest values are in the deeper part of the Appalachian basin and lowest on the Indiana-Ohio platform. Flow direction in central Ohio is indicated to be west or northwest. Head difference is 2-7 ft. Porosity and permeability data combined with this information (Darcy's law) yield velocities of less than 6 in. /year. Because the assumptions involved in determining velocity in this manner are questionable, the resulting values should be considered rough approximations. Nevertheless, the calculations generally show that transport of injected fluids by hydrodynamic flow is not presently a serious hazard in Ohio. End_of_Article - Last_Page 1593------------
ReverseDock: a web server for blind docking of a single ligand to multiple protein targets using AutoDock Vina

Several platforms exist to perform molecular docking to computationally predict binders to a specific protein target from a library of ligands. The reverse, that is, docking a single ligand to various protein targets, can currently be done by very few web servers, which limits the search to a small set of pre-selected human proteins. However, the possibility to in silico predict which targets a compound identified in a high-throughput drug screen bind would help optimize and reduce the costs of the experimental workflow needed to reveal the molecular mechanism of action of a ligand. Here, we present ReverseDock, a blind docking web server based on AutoDock Vina specifically designed to allow users with no computational expertise to dock a ligand to 100 protein structures of their choice. ReverseDock increases the number and type of proteins a ligand can be docked to, making the task of in silico docking of a ligand to entire families of proteins straightforward. We envision ReverseDock will support researchers by providing the possibility to apply inverse docking computations using web browser. ReverseDock is available at: https://reversedock.biologie. uni-freiburg.de/
Growth of molten zone as a mechanism of slip weakening of simulated faults in gabbro during frictional melting

[1] To understand how frictional melting affects fault instability, we performed a series of high-velocity friction experiments on gabbro at slip rates of 0.85-1.49 m s -1 , at normal stresses of 1.2-2.4 MPa and with displacements up to 124 m. Experiments have revealed two stages of slip weakening; one following the initial slip and the other immediately after the second peak friction. The first weakening is associated with flash heating, and the second weakening is due to the formation and growth of a molten layer along a simulated fault. The two stages of weakening are separated by a marked strengthening regime in which melt patches grow into a thin, continuous molten layer at the second peak friction. The frictional coefficient decays exponentially from 0.8-1.1 to 0.6 during the second weakening. The host rocks are separated completely by a molten layer during this weakening so that the shear resistance is determined by the gross viscosity and shear strain rate of the molten layer. Melt viscosity increases notably soon after a molten layer forms. However, a fault weakens despite the increase in melt viscosity, and the second weakening is caused by the growth of molten layer resulting in the reduction in shear strain rate of the molten layer. Very thin melt cannot be squeezed out easily from a fault zone so that the rate of melting would be the most critical factor in controlling the slip-weakening distance. Effect of frictional melting on fault motion can be predicted by solving a Stefan problem dealing with moving host rock/molten zone boundaries.
The contribution of Fe(III) and humic acid reduction to ecosystem respiration in drained thaw lake basins of the Arctic Coastal Plain

Previous research showed that anaerobic respiration using iron (Fe) oxides as terminal electron acceptor contributed substantially to ecosystem respiration (ER) in a drained thaw lake basin (DTLB) on the Arctic coastal plain. As DTLBs age, the surface organic layer thickens, progressively burying the Fe‐rich mineral layers. We therefore hypothesized that Fe(III) availability and Fe reduction would decline with basin age. We studied four DTLBs across an age gradient, comparing seasonal changes in the oxidation state of dissolved and extractable Fe pools and the estimated contribution of Fe reduction to ER. The organic layer thickness did not strictly increase with age for these four sites, though soil Fe levels decreased with increasing organic layer thickness. However, there were surprisingly high levels of Fe minerals in organic layers, especially in the ancient basin where cryoturbation may have transported Fe upward through the profile. Net reduction of Fe oxides occurred in the latter half of the summer and contributed an estimated 40–45% to ecosystem respiration in the sites with the thickest organic layers and 61–63% in the sites with the thinnest organic layers. All sites had high concentrations of soluble Fe(II) and Fe(III), explained by the presence of siderophores, and this pool became progressively more reduced during the first half of the summer. Redox titrations with humic acid (HA) extracts and chelated Fe support our view that this pattern indicates the reduction of HA during this interval. We conclude that Fe(III) and HA reductions contribute broadly to ER in the Arctic coastal plain.
Study on the Financial Capacity of Securities Companies Listed on the Hanoi Stock Exchange

Research solutions to improve the financial capacity of securities companies listed on the Hanoi Stock Exchange. The data are audit reports of stock companies listed on the Hanoi Stock Exchange in the period 2020 - 2022. Using a combination of quantitative and qualitative methods. Based on the research results, the author proposes (i) The author has systematized the basic theory of quality management of listed securities companies. (ii) Based on the theoretical basis of financial capacity developed by the author, it is used to evaluate the current situation of financial capacity of stock companies listed on the Hanoi Stock Exchange. (iii) From there, the author proposes some solutions to improve the financial capacity of securities companies listed on the Hanoi Stock Exchange.
The natural thermoluminescence of meteorites 4. Ordinary chondrites at the Lewis Cliff Ice Field

Natural thermoluminescence (TL) measurements have been made on 302 meteorites from the vicinity of the Lewis Cliff in the Beardmore region of Antarctica. The data provide information on terrestrial age and unusual radiation and thermal histories, which, in turn, are helpful in identifying fragments of a single fall and in understanding ice sheet movements and the mechanisms by which meteorite concentration occurs at this site. The present data with data for induced TL, class, find location, hand-specimen descriptions and mineral composition have enabled 70 of the present samples to be assigned to 27 groups of “paired” meteorites, with between 5 and 2 meteorites in each group. The distribution of meteorites on the ice, the shape of the fields of “paired” meteorites, and trends in the natural TL data indicate that there is a western component to the movement of the ice at this location, as well as the previously supposed movement to the north. This western vector probably explains the concentration of meteorites along the western edge of the ice tongue. Meteorites at the northern end of the tongue (the Lower Ice Tongue), and Meteorite Moraine to the east, have relatively high natural TL, and therefore young terrestrial ages, while those on the upper tongue show a broad range of ages including a great many large ages. Details of the meteorite concentration are different on the Upper and Lower Tongue and it might be that these two parts of the ice sheet are unrelated. These new natural TL data identify several recent falls and several meteorites which probably had unusually small perihelia immediately prior to capture by the earth.
An Artificial Intelligence (AI) workflow for catalyst design and optimization

In the pursuit of novel catalyst development to address pressing environmental concerns and energy demand, conventional design and optimization methods often fall short due to the complexity and vastness of the catalyst parameter space. The advent of Machine Learning (ML) has ushered in a new era in the field of catalyst optimization, offering potential solutions to the shortcomings of traditional techniques. However, existing methods fail to effectively harness the wealth of information contained within the burgeoning body of scientific literature on catalyst synthesis. To address this gap, this study proposes an innovative Artificial Intelligence (AI) workflow that integrates Large Language Models (LLMs), Bayesian optimization, and an active learning loop to expedite and enhance catalyst optimization. Our methodology combines advanced language understanding with robust optimization strategies, effectively translating knowledge extracted from diverse literature into actionable parameters for practical experimentation and optimization. In this article, we demonstrate the application of this AI workflow in the optimization of catalyst synthesis for ammonia production. The results underscore the workflow's ability to streamline the catalyst development process, offering a swift, resource-efficient, and high-precision alternative to conventional methods.
Advances in dendritic cell targeting nano-delivery systems for induction of immune tolerance

Dendritic cells (DCs) are the major specialized antigen-presenting cells (APCs), play a key role in initiating the body’s immune response, maintain the balance of immunity. DCs can also induce immune tolerance by rendering effector T cells absent and anergy, and promoting the expansion of regulatory T cells. Induction of tolerogenic DCs has been proved to be a promising strategy for the treatment of autoimmune diseases, organ transplantation, and allergic diseases by various laboratory researches and clinical trials. The development of nano-delivery systems has led to advances in situ modulation of the tolerance phenotype of DCs. By changing the material composition, particle size, zeta-potential, and surface modification of nanoparticles, nanoparticles can be used for the therapeutic payloads targeted delivery to DCs, endowing them with great potential in the induction of immune tolerance. This paper reviews how nano-delivery systems can be modulated for targeted delivery to DCs and induce immune tolerance and reviews their potential in the treatment of autoimmune diseases, organ transplantation, and allergic diseases.
An Attribution Deep Learning Interpretation Model for Landslide Susceptibility Mapping in the Three Gorges Reservoir Area

Deep learning (DL) models are increasingly used for landslide susceptibility mapping (LSM) due to their higher accuracy. However, due to the lack of explanations of the influence of input contributing factors by current DL models, accurately identifying the cause of each landslide remains challenging. This study proposes a novel interpretable DL model named Deep-Attention-LSF, which assigns significance scores to contributing factors at local levels for attributing landslide susceptibility. This model considers the significance scores of input factors to more accurately predict landslide occurrence. DeepLIFT is used as an attribution branching network for interpreting the relationship between input factors and each landslide event. Subsequently, a landslide classification network formed by combining convolutional neural network and long short-term memory is used to predict the landslide occurrence in the entire study area. The performance of Deep-Attention-LSF is tested using the landslide inventory map of Three Gorges Reservoir Area and the associated maps of 18 landslide-related factors. The accuracy, recall, precision, and F1-score of our model were 0.9645, 0.9583, 0.9676, and 0.9522, respectively. These suggest that our model outperformed the compared models, including self-attention LSM, frequency-ratio-attention LSM, bagging and random subspace naive Bayes tree, gradient boosting decision tree, random forest, information value model, and enhanced C5.0 decision tree model. Deep-Attention-LSF provided reasonable explanations for landslide attributions by comparison with field investigation reports for four specific landslide cases. Combining the interpretation of Deep-Attention-LSF with field investigations can provide more comprehensive information for evaluating specific landslides, providing a useful tool for landslide prevention and management.
A Hybrid Intelligence-Based Integrated Smart Evaluation Model for Vocal Music Teaching

The smart evaluation for teaching effect has received much attention, especially in field of vocal music. Currently, such evaluation mainly relies on expert rating, which costs much human labors. Fortunately, the machine learning and deep learning-based techniques have been applied to evaluation affairs in a number of areas. This work takes the vocal music teaching as the main object, and introduces several typical intelligent algorithms to construct a smart evaluation workflow. Thus in this paper, a hybrid intelligence-based integrated smart evaluation model for vocal music teaching is proposed. First of all, a comprehensive evaluation system is formulated from mechanism as the main feature space. Then, convolutional neural network, long short-term memory network and multi-layer perceptrons are employed to establish a novel integrated structure as the main evaluation model. To assess the proposed technical framework in this paper, a case study is conducted and some simulation experiments are carried out for this purpose. The experimental results show that the proposal can well realize automatic evaluation for vocal music teaching.
COMPARISON OF BLOOD PRESSURE AND HEART RATE AMONG ACTIVE AND PASSIVE CIGARETTE SMOKERS

OBJECTIVE:To compare the effects of passive and active cigarette smokers on blood pressure and heart rate. METHODS: It was a cross sectional study based in Physiology department of Khyber Medical College, Peshawar. It was conducted from January 2022 to June 2022. Using non probability convenient sampling, MBBS students and college employees were divided into three groups. Each group had a sample size of 50. Group 1 comprised of passive smokers, group 2 consisted of active smokers and group 3 of nonsmokers. Heart rate and blood pressure, including Systolic Blood Pressure, Diastolic Blood Pressure, Mean Arterial Pressure and Pulse Pressure, were measured. Data was analysed using SPSS 26. RESULTS: In Group-1, all smokers were males. In Group-2 (nonsmokers), 42 were males (32.6%) and 8 (34.8%) were females and in Group-3 (passive smokers), 37 were males (28.7%) and 15 were females (65.2%). Using Anova test, the difference in the mean values of systolic blood pressure (SBP) among the three groups was found to be highly significant (0.001), while that of diastolic blood pressure (DBP) non-significant (0.291). The mean values of Heart Rate (HR) among the three groups was also significant (0.049). CONCLUSION:Smoking effects blood pressure and heart rate, as the systolic blood pressure and heart rate of smokers in our study was raised. KEY WORDS: Hypertension, smokers, powerlab,
Effects of prenatal bisphenol S and bisphenol F exposure on behavior of offspring mice

ABSTRACT Bisphenol A (BPA) is a representative endocrine-disrupting chemical that exhibits hormonal disturbance reactions. Various alternatives, such as Bisphenol S (BPS) and Bisphenol F (BPF), are being developed. BPS and BPF (which are representative alternatives to BPA) are used in consumer products such as polycarbonate plastics and epoxy resins. They have structures similar to those of BPA and have also been proven to be exogenous endocrine disruptors. However, although there are many studies on BPA, there are few studies on the neurodevelopmental effects of BPS and BPF. Therefore, in this study, we analyzed neurobehavioral changes in offspring mice exposed to BPS and BPF during brain development by administering BPS and BPF to pregnant mice. We found that prenatal exposure to BPS and BPF did not affect anxiety-and depression-like behaviors, locomotion, sociability, memory, or cognition functions in offspring mice. However, exposure to BPS and BPF decreased the preference for social novelty in the offspring mice. Taken together, these findings suggest that perinatal exposure to BPS and BPF affects changes in social behaviors, but not other behavioral changes such as emotion, memory, or cognition in the offspring mice.
Prognostic Value of Mitral Regurgitation in Patients with Primary Hypertrophic Cardiomyopathy

Background and Objectives: Mitral valve pathology and mitral regurgitation (MR) are very common in patients with hypertrophic cardiomyopathy (HCM), and the evaluation of mitral valve anatomy and degree of MR is important in patients with HCM. The aim of our study was to examine the potential influence of moderate or moderately severe MR on the prognosis, clinical presentation, and structural characteristics of HCM patients. Materials and Methods: A prospective study examined 176 patients diagnosed with primary asymmetric HCM. According to the severity of the MR, the patients were divided into two groups: Group 1 (n = 116) with no/trace or mild MR and Group 2 (n = 60) with moderate or moderately severe MR. All patients had clinical and echocardiographic examinations, as well as a 24 h Holter ECG. Results: Group 2 had significantly more often the presence of the obstructive type of HCM (p < 0.001), syncope (p = 0.030), NYHA II class (p < 0.001), and atrial fibrillation (p = 0.023). Also, Group 2 had an enlarged left atrial dimension (p < 0.001), left atrial volume index (p < 0.001), and indirectly measured systolic pressure in the right ventricle (p < 0.001). Patients with a higher grade of MR had a significantly higher E/e′ (p < 0.001) and, as a result, higher values of Nt pro BNP values (p < 0.001) compared to Group 1. Kaplan–Meier analysis demonstrated that the event-free survival rate during a median follow-up of 88 (IQR 40–112) months was significantly higher in Group 1 compared to Group 2 (84% vs. 45% at 8 years; log-rank 20.4, p < 0.001). After adjustment for relevant confounders, the presence of moderate or moderately severe MR remained as an independent predictor of adverse outcomes (HR 2.788; 95% CI 1.221–6.364, p = 0.015). Conclusions: The presence of moderate or moderately severe MR was associated with unfavorable long-term outcomes in HCM patients.
Causes and development of repeated Arctic Ocean warming events

A model hindcast for 1948–2002 shows several warming events in the Atlantic layer of the Arctic Ocean. The most recent warming event in the 1990s spread from Fram Strait to the Lomonosov Ridge and into the Canadian Basin. Only a warming event in the 1960s can also be followed into the eastern Eurasian Basin. These two warming events are reinforced by anomalously warm flow from the Barents Sea while warming events in the 1970s and 1980s encounter average or below normal temperatures in the Barents Sea branch of the Atlantic Water. The warm Barents Sea outflow in the 1960s is caused by extensive ice cover and a melt water induced halocline in the Barents Sea that reduced heat loss from the Atlantic water. In the 1990s, however, the warm inflow from the Nordic Seas was responsible for warmer than normal flow from the Barents Sea into the Arctic Ocean.
A Preliminary Study on Crustal Velocity Structures of Maqin‐Lanzhou‐Jingbian Deep Seismic Sounding Profile

The 1 000 km-long Marqin-Lanzhou-Jingbian comprehensive geophysical profile was deployed for the purpose of studying the interaction between the Qinghai-Xizang Plateau block and the Ordos block as well as for studying the deep driving mechanism of tectonic deformation. This paper presents only the preliminary results obtained with deep seismic sounding (DSS) observation data. The crust is clearly stratified. On the whole, it can be divided into two parts, i.e., the upper crust and the lower crust, with interface C as the boundary surface. Each of the two parts contains a number of secondary interfaces. The general trend of lateral variation is that the crust becomes gradually thicker from northeast to southwest, which is mainly due to the variation in the thickness of the lower crust. The average crustal velocity tends to become gradually lower from northeast to southwest–the velocity is obviously low west of Zeku and in Haiyuan region. A number of crustal low velocity layers exist west of Zeku and another low velocity layer exists near Haiyuan. The number of reflecting horizons increases gradually from northeast to southwest. As seen in seismic reflection waveforms, Pc wave is very strong at Haiyuan and it also lasts long. Besides, the complexity coefficients of Pm wave in Haiyuan and west of Zeku are extremely large, much larger than those in other parts. The above results clearly show that anomalous structure exists in the crust and upper mantle west of Zeku and in Haiyuan region, which reflects the interactions between Bayankar block and Chaidamu block, and between Qilian block and Ordos block.