Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Active Sites of the Water-Gas Shift Reaction over Titania Supported Platinum Catalysts under Uncertainty

A comprehensive uncertainty quantification framework has been developed for integrating computational and experimental kinetic data and to identify active sites and reaction mechanisms in catalysis. Three hypotheses regarding the active site for the water-gas shift reaction on Pt/TiO2 catalysts are tested - Pt(111), an edge interface site, and a corner interface site. Uncertainties associated with DFT calculations and model errors of microkinetic models of the active sites are informed and verified using Bayesian inference and predictive validation. Significant evidence is found for the role of the oxide support in the mechanism. Positive evidence is found in support of the edge interface active site over the corner interface site. For the edge interface site, the CO-promoted redox mechanism is found to be the dominant pathway and only at temperatures above 573 K does the classical redox mechanism contribute significantly to the overall rate. At all reaction conditions, water and surface O-H bond dissociation steps at the Pt/TiO2 interface are the main rate controlling steps.
Coverage Analysis of mmWave and THz-Enabled Aerial and Terrestrial Heterogeneous Networks

Heterogeneous networks (HetNets) are becoming a promising solution for future wireless systems to satisfy the high data rate requirements. This paper introduces a stochastic geometry framework for the analysis of the downlink coverage probability in a multi-tier HetNet consisting of a macro-base station (MBS) operating at sub-6 GHz, millimeter wave (mmWave)-enabled unmanned aerial vehicles (UAVs) operating at 28 GHz, and small BSs operating both at mmWave and THz frequencies. The analytical expressions for the coverage probability for each tier have been derived in the paper. Monte Carlo simulations are then performed to validate the analytical expressions. The effectiveness of the HetNet is analyzed on various performance metrics including association and coverage probabilities for different network parameters. We show that the mmWave and THz-enabled cells provide significant improvement in the achievable data rates because of their high available bandwidths, however, they have a degrading effect on the coverage probability due to their high propagation losses.
EVALUATION OF IN VITRO ANTIDIABETIC AND ANTIOXIDANT POTENTIAL OF BARLERIA CRISTATA LEAVES EXTRACTS

Â Objectives: The objectives of the study were to study the in vitro antidiabetic and antioxidant activity of Barleria cristata leaves extracts.Methods: Ethanol extract and petroleum ether extract of leaf and root of B. cristata were tested for their antidiabetic activity. The in vitro antidiabetic activity from I±-amylase, I±-glucosidase, and antioxidant activity was used to assess the potential activity of the fractions.Results: Our attempt results suggest that ethanol and the petroleum ether leaf extract from B. cristata show signs of dose-dependent increases to inhibitory activity on I±-amylase, I±-glucosidase enzymes, and antioxidant activity when compared with control. Ethanolic leaves to extract produced maximum in vitro antidiabetic effect and antioxidant activity when compared to petroleum ether extract.Conclusion: The ethanol leaf extract from B. cristata may be used in managing of blood glucose in a medical condition like diabetes.
Visual Analysis of Deep Q-network

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.
Functional feeding groups of Protist Ciliates (Protist: Ciliophora) on a neotropical flood plain

Functional diversity approaches have been an efficient tool in gaining a better understanding of how environmental conditions selected species in a given environment and how they share resources, linking ecological processes to biodiversity patterns. Although most of the protist ciliates are not highly specialized, functional feeding groups with species which ingest similar food can be identified. Thus, this study aimed to compare the abundance of different Functional Feeding Groups (FFG) of ciliates in environments with different hydrodynamic conditions (lotic and lentic) in different hydrological periods (high and low water) in a neotropical flood plain. The samples for analysis of the community of ciliates were taken in March and September of 2010 and 2011, at the subsurface of 12 different hydrodynamic environments. The results of an RDA showed a spatial and temporal segregation of the sampling units, based on the abundance and occurrence of the FFG. In addition, a clear influence of food resources on the structuring of functional ciliate guilds was evidenced. Thus, there were both temporal (hydrological periods) and spatial (different hydrodynamic environments) differences in the distribution of the FFG, with a clear separation of the FFGs between the years studied. In summary, the results of the categorization of species of ciliates in FFG responded satisfactorily suggesting fluctuations in different food resources, which reinforces the idea that the grouping of species by functional characteristics can be a good indicator of the responses of organisms to environmental fluctuations.
Resilience in the Face of Disaster: Psychosocial Effects of the 2017 Northern California Wildfires in Caregivers and Persons with Cognitive Impairment Participating in an Integrative Group Movement Program at an Adult Day Center

ABSTRACT Natural disasters are often stressful for persons with cognitive impairment (PWCI) and caregivers. We investigated the impact of the Northern California 2017 wildfires on PWCI and caregivers who were participating in a research study of an integrative group movement program at an adult day center affected by the fires. One month and 7 months after the fires, we sent caregivers a survey that included the 10-item Perceived Stress Scale (PSS, range: 0–40) and open-ended questions to assess the psychosocial impact of the fires on PWCI and caregivers. We used paired t-tests to analyze PSS responses and qualitative content analysis for open-ended responses. Thirteen of the 17 caregivers returned at least one survey. Caregivers reported moderate levels of perceived stress at both time points, with no change over time (PSS mean: 20.4 vs. 21.3, p = .31). We identified three psychosocial domains impacted by the fires. First, both PWCI and caregivers experienced emotional distress. Second, PWCI exhibited a range of cognitive responses, including confusion and disorientation, no impact, hyperawareness, and improved cognitive function and adaptability. Third, despite emotional distress, some caregivers reported increased self-efficacy. Our results provide evidence of resilience in some PWCI and caregivers in response to the fires, despite emotional distress. This resilience may have been due to the sense of community that sometimes occurs following natural disasters, or it may have been a result of participating in the study, which was designed to promote social/emotional connectedness and may have provided a source of continuity and support during a time of tragedy.
A new tripodal-3-hydroxy-4-pyridinone for iron and aluminium sequestration: synthesis, complexation and in vivo studies

Elevated levels of iron and aluminium in the body can lead to tissue damage, organ failure and eventually death. To reduce complications of metal overload, specific chelating agents have been used. Following our recent developments in a series of hexadentate 3-hydroxy-4-pyridinones (3,4-HP) with high M3+ sequestering capacity, we herein present a novel tripodal homologue, whose design involves one methylene truncation on the linkers. This truncation aimed to reduce the ligand molecular weight and concomitant improvement in the membrane crossing ability and accessibility to cytoplasmic iron pools, but still retaining the capacity for the formation of a 1 : 1 (M3+ : L) complex with high thermodynamic stability and kinetic inertness. Besides the synthesis of a new ligand, solution studies have been performed to evaluate the acid–base properties and complexation capacity towards Fe(III) and Al(III) using potentiometry and a panoply of spectrometric techniques. The pFe and pAl values show some decrease, as compared with the non-truncated homologues, but still represent an improvement of, respectively, 7- and 4-orders of magnitude, as compared to the marketed drug deferiprone. The ability of this new ligand to facilitate metal-mobilization from the body was investigated using a mice model injected with 67Ga. The new chelator possessing high pM3+ values shows promising ability to remove Fe and Al under in vivo conditions.
Safety and Quality Evaluation of Various Grades of Egyptian Beef Luncheon Sausage and Burger Patties: A Comparative Study

| The current study was carried out to compare the safety and quality between the high price (premium) and low price (economic) meat products that are commonly distributed in the Egyptian markets. To achieve this goal, 200 samples from the various grades of Egyptian beef luncheon sausage and burger patties were collected randomly from different Egyptian markets and subjected to physicochemical, microbiological, and histological examinations. Results revealed that both grades of examined luncheon samples had higher moisture content than its permissible limits. However, the protein contents were lower than the established limit in both grades of all examined products. Results also showed that all examined samples showed fatty acids profile was nearly similar to that of chicken and buffalo meat than that of beef. Moreover, the results revealed that the samples that exceeded the permissible limits of TBARS and TVBN values were higher in premium than those of economic products for both luncheon and burger patties. Conversely, the economic luncheon showed a higher percentage of samples that exceeded the permissible limit of residual nitrite when compared to the premium one. Both grades of all examined products contained higher levels of monosodium glutamate (MSG) than that of the established level, moreover; all examined bacterial groups exceeded their stated limits in most examined samples. Histological examination revealed that all examined products contained a low percentage of muscular tissue and higher amounts of fat, heart muscle, connective tissue, skin, bone, cartilage, and carbohydrates. This study proved that both chemical and histological examinations provide an effective tool to detect the various methods of adulteration in meat products.
Simulations of the Soil Evaporation and Crop Transpiration Beneath a Maize Crop Canopy in a Humid Area

Soil evaporation (Es) and crop transpiration (Tc) are important components of water balance in cropping systems. Comparing the accurate calculation by crop models of Es and Tc to the measured evaporation and transpiration has significant advances to the optimal configuration of water resource and evaluation of the accuracy of crop models in estimating water consumption. To evaluate the adaptation of APSIM (Agricultural Production Systems simulator) in calculating the Es and Tc in Nanjing, APSIM model parameters, including the meteorological and soil parameters, were measured from a two-year field experiment. The results showed that: (1) The simulated evaporation was basically consistent with the measured Es, and the regulated model can effectively present the field evaporation in the whole maize growth period (R2 = 0.85, D = 0.96, p < 0.001); and (2) The trend of the simulated Tc can present the actual Tc variation, but the accuracy was not as high as the evaporation (R2 = 0.74, D = 0.87, p < 0.001), therefore, the simulation of water balance process by APSIM will be helpful in calculating Es and Tc in a humid area of Nanjing, and its application also could predict the production of maize fields in Nanjing.
Optimization of Rock Phosphate Solubilization in Submerged Cultures Containing Some Agro-Industrial Residues

Aims: To solubilize rock phosphate in presence of agriculture wastes by microorganisms and produce fermented solution rich with soluble phosphate. Study Design: The effect of agriculture wastes, rock phosphate concentrations and culture conditions on rock phosphate solubilization. Identification of the potential isolate. Place and Duration of Study: Microbiology Dept., Fac. of Agriculture, Ain Shams Univ., Cairo, Egypt, 2015/ 2016. Methodology: Four isolates were tested on 7 agriculture wastes for rock phosphate solubilization. Optimization of some environmental factors. Identification of fungal isolate by 18S rRNA sequence analysis. Results: Some agro-industrial residues (bagasse, corn cobs, black sugar cane molasses, olive cake wastes, rice straw, sugar beet waste and whey) were used as a carbon source at different treatments for highest rock phosphate solubilization (RPS) by Serratia sp. Rs7 and Rs22, and Original Research Article Abou-Taleb et al.; JAMB, 11(2): 1-18, 2018; Article no.JAMB. 41624 2 Aspergillus sp. Bf6 and RPf10 isolates. The maximum RPS was obtained by the tested bacteria and fungi when both were grown on whey and sugar beet waste as a whole medium which increased the fermentation period to 10 and 12 days. All treatments of sugar beet wastes, bagasse, rice straw and corncobs failed to support RPS by bacterial isolates. Also corn cobs showed negative effect on RPS in all treatments for fungal isolates. In serial experiments, the maximum RPS was obtained by the tested bacteria and fungi in media supplemented with 7.0 and 10.0 gL RP at pH 7.0 and 5.5 inoculated with 3% standard inoculum and incubated at 30°C respectively. The fermented solution produced by Aspergillus sp. RPf10 containing higher amounts of citric acid (543.39 μgP ml) and indole-3-acetic acid (11.96 mgL) as well as higher phosphatase activity than that produced by other tested isolates. This isolate was identified as Aspergillus tubingensis RPf10. Conclusion: the ability of Aspergillus tubingensis to convert sugar beet waste and insoluble rock phosphate into fermented solution containing maximum level of soluble phosphate, growth promoting and organic acids which can be apply this solution in future in microbial nutrient and agriculture field.
WIND-TUNNEL EXPERIMENTS AND CFD SIMULATIONS TO STUDY THE INCREASE IN SHIP RESISTANCE COMPONENTS DUE TO ROUGHNESS

: This is a study on the effect of hull roughness on ship resistance components (especially full viscous resistance), which is tested using wind-tunnel experiments and Computational Fluid Dynamics (CFD) simulations. With the wind-tunnel experiment, a full viscous resistance analysis can be carried out to further explore changes in the friction and pressure resistance only without the wave resistance. In the experiments, the roughness model used sandpaper with an average roughness height ( k a ) = 162 µ m, that then it was predicted equal with k s = 1475 µ m. In the CFD simulations, the roughness parameter was represented by an equivalent sand grain roughness height ( k s ), and this was varied by several levels. The results indicated that there was a significant increase in ∆ C t (up to 73.7%) and ∆ C f (up to 106.96%), but only a slight increase in ∆ C p (up to 10.57%). The trend of the increase in resistance due to k s and Reynolds numbers were also discussed. The parameter k s were very influential on ∆ C f , but had only a slight effect on ∆ C p . With the significant results about the increase in ship resistance due to the roughness, both the friction and the pressure resistance component will lead to an increase in fuel consumption on a ship then it will increase levels of carbon emissions in the air.
Relation-Aware Facial Expression Recognition

Research on facial expression recognition has been moving from the constrained lab scenarios to the in-the-wild situations and has made progress in recent years. However, it is still very challenging to deal with facial expression in the wild due to large poses and occlusion as well as illumination and intensity variations. Generally, existing methods mainly take the whole face as a uniform source of features for facial expression analysis. Actually, physiology and psychology research shows that some crucial regions, such as the eye and mouth, reflect the differences of different facial expressions, which have close relationships with emotion expression. Inspired by this observation, a novel relation-aware facial expression recognition method called relation convolutional neural network (ReCNN) is proposed in this article, which can adaptively capture the relationship between crucial regions and facial expressions leading to the focus on the most discriminative regions for recognition. We have evaluated the proposed ReCNN on two large in-the-wild databases: 1) AffectNet and 2) RAF-DB. Extensive experiments on these databases show that our method has superior recognition accuracy compared with state-of-the-art methods and the relationship between crucial regions and facial expressions is beneficial to improve the performance of facial expression recognition.
Differential retention contributes to racial/ethnic disparity in U.S. academia

Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world’s largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios.
A Comparative Study of Additively Manufactured Low-Power-Loss Windings for PM Machines

This theoretical study explores concepts of electrical windings in application to low-voltage permanent magnet (PM) machines. The research focus has been placed on low-power-loss winding designs, with the use of modern additive manufacturing (AM) techniques in mind. A case study PM machine with concentrated winding topology has been used to demonstrate how the AM enabled winding concepts compare with the more conventional constructions. To make the comparison more relevant, the theoretical body of work has been supported with the existing know-how in electrical machines construction and latest developments in AM. The research findings suggest that the AM winding concepts offer similar power losses with simpler winding fabrication and assembly, subject to further advancement in AM.
Distributed Online Dispatch for Microgrids Using Hierarchical Reinforcement Learning Embedded With Operation Knowledge

This paper considers the problem of distributed online economic dispatch (DOED) from sequential data using reinforcement learning. Learning operation behavior in high-dimension environments with constraints is a major challenge for the DOED of networked microgrids (MGs), where insufficient exploration prevents agents from building complex policies. Therefore, this paper develops a hierarchical reinforcement learning (HRL) to handle the DOED problem, where radial basis function (RBF) approximation is incorporated to make policies in continuous space. Based on the hierarchical framework, the HRL algorithm improves learning efficiency and reduces computational cost. The online HRL achieves distributed self-adaption and better performance of real-time dispatch by a modest number of interacting variables. In addition, guided by domain knowledge, the HRL algorithm avoids baseline violation and additional learning beyond feasible action space. In the case of an actual networked MG cluster in Qingdao with real operation data, simulation is conducted to verify that the proposed hierarchical learning can reduce long-term operation costs and enhance operation stability. To explore the learning process, we also provide its convergence condition and analyze the sensitivity of the learning parameters.
Screening potential inhibitors for cancer target LSD1 from natural products by steered molecular dynamics

Abstract LSD1 is one of the important proteins which help transcriptional machine to access to DNA though open or close DNA around histone. It can also demethylate p53 at specific lysines altering the p53-mediated transcriptional process which could lead to the inhibition of the role of p53 in promoting apoptosis. Thus, inhibition of LSD1 activity by small compounds becomes a promising cancer therapy. Combining the Lipinski’s rule with docking and steered molecular dynamics simulation we have found from the traditional Chinese medicine database four compounds that are good candidates for inhibiting LSD1 activity.
Sono-transformation of tannic acid into biofunctional ellagic acid micro/nanocrystals with distinct morphologies

A sustainable, reagent-less and one-pot ultrasonic methodology has been developed to transform amorphous tannic acid into regularly shaped crystalline ellagic acid particles. Multiple and consecutive reactions have been performed on tannic acid, in aqueous solution without the addition of any external reagent. The size, morphology and bio-activity of ellagic acid micro-nanocrystals can be finely tuned by choosing appropriate ultrasonic parameters.