Miracle-dz/UniFAR-FTUs huggingface dataset:
“Efficacy–Nature–Structure” Relationship of Traditional Chinese Medicine Based on Chemical Structural Data and Bioinformatics Analysis

Traditional Chinese medicines (TCMs) have wide pharmacological activities, and the ingredients in individual TCMs determine their efficacies. To understand the “efficacy–nature–structure” relationship of TCM, compounds from 2444 kinds of herbs were collected, and the associations between family, structure, nature, and biological activities were mined and analyzed. Bernoulli Naïve Bayes profiling and a data analysis method were used to predict the targets of compounds. The results show that genetic material determined the representation of ingredients from herbs and the nature of TCMs and that the superior scaffolds of compounds of cold nature were 2-phenylochrotinone, anthraquinone, and coumarin, while the compounds of hot nature were cyclohexene. The results of the similarity analysis and distribution for molecular descriptors of compounds show that compounds associated with the same nature were similar and compounds associated with different natures occurred as a transition in part. As for integral compounds from 2-phenylochrotinone, anthraquinone, coumarin, and cyclohexene, the value of the shape index increased, indicating the transition of scaffolds from a spherical structure to a linear structure, with various molecular descriptors decreasing. Three medicines and three recipes prescribed based on “efficacy–nature–structure” had a higher survival rate in the clinic and provided powerful evidence for TCM principles. The research improves the understanding of the “efficacy–nature–structure” relationship and extends TCM applications.
Metagenomic Analysis for Evaluating Change in Bacterial Diversity in TPH-Contaminated Soil after Soil Remediation

Soil washing and landfarming processes are widely used to remediate total petroleum hydrocarbon (TPH)-contaminated soil, but the impact of these processes on soil bacteria is not well understood. Four different states of soil (uncontaminated soil (control), TPH-contaminated soil (CS), after soil washing (SW), and landfarming (LF)) were collected from a soil remediation facility to investigate the impact of TPH and soil remediation processes on soil bacterial populations by metagenomic analysis. Results showed that TPH contamination reduced the operational taxonomic unit (OTU) number and alpha diversity of soil bacteria. Compared to SW and LF remediation techniques, LF increased more bacterial richness and diversity than SW, indicating that LF is a more effective technique for TPH remediation in terms of microbial recovery. Among different bacterial species, Proteobacteria were the most abundant in all soil groups followed by Actinobacteria, Acidobacteria, and Firmicutes. For each soil group, the distribution pattern of the Proteobacteria class was different. The most abundant classed were Alphaproteobacteria (16.56%) in uncontaminated soils, Deltaproteobacteria (34%) in TPH-contaminated soils, Betaproteobacteria (24%) in soil washing, and Gammaproteobacteria (24%) in landfarming, respectively. TPH-degrading bacteria were detected from soil washing (23%) and TPH-contaminated soils (21%) and decreased to 12% in landfarming soil. These results suggest that soil pollution can change the diversity of microbial groups and different remediation techniques have varied effective ranges for recovering bacterial communities and diversity. In conclusion, the landfarming process of TPH remediation is more advantageous than soil washing from the perspective of bacterial ecology.
Community-wide epigenetics provides novel perspectives on the ecology and evolution of marine microbiome

DNA methylation in prokaryotes is involved in many different cellular processes including cell cycle regulation and defense against viruses. To date, most prokaryotic methylation systems have been studied in culturable microorganisms, resulting in a limited understanding of DNA methylation from a microbial ecology perspective. Here, we analyze the distribution patterns of several microbial epigenetics marks in the ocean microbiome through genome-centric metagenomics across all domains of life. We show that overall, DNA methylation can readily be detected across dominant oceanic bacterial, archaeal, and viral populations, and microbial epigenetic changes correlate with population differentiation. Furthermore, our genome-wide epigenetic analysis of Pelagibacter suggests that GANTC, a DNA methyltransferase target motif, is related to the cell cycle and is affected by environmental conditions. Yet, the presence of this motif also partitions the phylogeny of the Pelagibacter phages, possibly hinting at a competitive co-evolutionary history and multiple effects of a single methylation mark. One-Sentence Summary DNA methylation patterns are associated with ecological changes and virus-host dynamics in the marine microbiome.
Data Management for Experimental Watersheds

A data management system (DMS) was developed for use with hydrologic databases collected on Little River Experimental Watersheds (LRW) for the 25-year period, 1968 to 1992. The system consists of data management protocols and computer programs that edit field records, detect and correct erroneous data, and provide initial levels of summarization. The system provides logic for filling of missing records, as well as provisions for storage, retrieval, and backup of data. This DMS has produced quality hydrologic databases for use in water resource and environmental quality research, and has resulted in timely availability and summarization of data with low percentages of missing or estimated records.
Face Detection with Occlusions

We describe a new framework, based on boosting algorithms and cascade structures, to efficiently detect faces with occlusions. While our approach is motivated by the work of Viola and Jones, several techniques have been developed for establishing a more general system, including (i) a robust boosting scheme, to select useful weak learners and to avoid overfitting; (ii) reinforcement training, to reduce false-positive rates via a more effective training procedure for boosted cascades; and (iii) cascading with evidence, to extend the system to handle occlusions, without compromising in detection speed. Experimental results on detecting faces under various situations are provided to demonstrate the performances of the proposed method.
Are There Different Kinds of Rogue Waves

There is clearly no immediate answer to the question posted by the title of this paper. Inasmuch as that there are not much definitively known about rogue waves and that there is still no universally accepted definition for rogue waves in the ocean, we think there might just be even more than one kind of rogue waves to contend with. While the conventional approach has generally designated waves with H max /H s greater than 2.2 as possible rogue waves, based on Rayleigh distribution considerations, there is conspicuously no provision as to how high the ratio of H max /H s can be and thus not known how high can a rogue wave be. In our analysis of wave measurements made from a gas-drilling platform in South Indian Ocean, offshore from Mossel Bay, South Africa, we found a number of cases that indicated H max /H s could be valued in the range between 4 and 10. If this were to be the case, then these records could be considered to be "uncommon" rogue waves, whereas a record of H max /H s in the range between 2 and 4 could be considered to comprise "typical" rogue waves. On the other hand, the spikes in the H max data could have been caused by equipment malfunction or some other phenomenon. Clearly, the question of whether or not there are different kinds of rogue waves cannot be readily answered by theoretical considerations alone and there is a crucial need for long-term wave time-series measurements for studying rogue waves.
MicroRNA Cues from Nature: A Roadmap to Decipher and Combat Challenges in Human Health and Disease?

MicroRNAs are small non-coding RNA (18–24 nt long) that fine-tune gene expression at the post-transcriptional level. With the advent of “multi-omics” analysis and sequencing approaches, they have now been implicated in every facet of basic molecular networks, including metabolism, homeostasis, and cell survival to aid cellular machinery in adapting to changing environmental cues. Many animals must endure harsh environmental conditions in nature, including cold/freezing temperatures, oxygen limitation (anoxia/hypoxia), and food or water scarcity, often requiring them to revamp their metabolic organization, frequently on a seasonal or life stage basis. MicroRNAs are important regulatory molecules in such processes, just as they are now well-known to be involved in many human responses to stress or disease. The present review outlines the role of miRNAs in natural animal models of environmental stress and adaptation including torpor/hibernation, anoxia/hypoxia tolerance, and freeze tolerance. We also discuss putative medical applications of advances in miRNA biology including organ preservation for transplant, inflammation, ageing, metabolic disorders (e.g., obesity), mitochondrial dysfunction (mitoMirs) as well as specialized miRNA subgroups respective to low temperature (CryomiRs) and low oxygen (OxymiRs). The review also covers differential regulation of conserved and novel miRNAs involved at cell, tissue, and stress specific levels across multiple species and their roles in survival. Ultimately, the species-specific comparison and conserved miRNA responses seen in evolutionarily disparate animal species can help us to understand the complex miRNA network involved in regulating and reorganizing metabolism to achieve diverse outcomes, not just in nature, but in human health and disease.
Comparison of the Methods for LS Factor Calculation when Evaluating the Erosion Risk in a Small Agricultural Area Using the USLE Tool

In the projects of anti-erosion protection in the Czech Republic, USLE was used as a standard tool for evaluating the risk of water erosion. The precision of the resulting USLE values is defined by the quality of input data and algorithms used. Two methods for LS factor calculation are recommended for use in the planning practice in the Czech Republic: the computing method based on the USLE 2D software and the other computing methods. Various methods can assess the LS factor; however, their results differ. On the example of the Starovice – Hustopeče study area (Czech Republic), strongly threatened by erosion, this report aimed to show the differences brought using these differing methods of LS factor assessment, all in two variants before and after application of antierosion measures (retention grass belts, grassed thalweg). Changes in the calculation of the LS factor were directly reflected in the calculation of the long-term average soil loss by water erosion.
Single Fault Isolation of a Hydrostatic Transmission System: Simulation and Experimentation

In this article, different methodologies in the area of system identification, parametric fault isolation, robustness in fault diagnosis have been surveyed and applied to a pedagogical HydroStatic Transmission (HST) system. A Bond Graph (BG) model for the system has been developed and then nonlinear regression analysis was done on the state equations, obtained from that model, to estimate the unknown parameters as a part of system identification. The test bench was designed to introduce faults in different components for the purpose of experimental validation of Fault Detection and Isolation (FDI). The model based single fault isolation was done by using structural analysis of some constraint relations, called Analytical Redundancy Relations (ARR), the numerical evaluation of which are called residuals. The robustness in fault isolation was addressed through Linear Fractional Transformation (LFT) approach to make residuals insensitive to uncertainty of system parameters, but sensitive to fault.
Screening of Severe Acute Respiratory Syndrome Coronavirus 2 RNA-Dependent RNA Polymerase Inhibitors Using Computational Approach

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.
Branched Chain Amino Acid Supplementation to a Hypocaloric Diet Does Not Affect Resting Metabolic Rate but Increases Postprandial Fat Oxidation Response in Overweight and Obese Adults after Weight Loss Intervention

Background: Branched chain amino acids (BCAA) supplementation is reported to aid in lean mass preservation, which may in turn minimize the reduction in resting metabolic rate (RMR) during weight loss. Our study aimed to examine the effect of BCAA supplementation to a hypocaloric diet on RMR and substrate utilization during a weight loss intervention. Methods: A total of 111 Chinese subjects comprising 55 males and 56 females aged 21 to 45 years old with BMI between 25 and 36 kg/m2 were randomized into three hypocaloric diet groups: (1) standard-protein (14%) with placebo (CT), (2) standard-protein with BCAA, and (3) high-protein (27%) with placebo. Indirect calorimetry was used to measure RMR, carbohydrate, and fat oxidation before and after 16 weeks of dietary intervention. Results: RMR was reduced from 1600 ± 270 kcal/day to 1500 ± 264 kcal/day (p < 0.0005) after weight loss, but no significant differences in the change of RMR, respiratory quotient, and percentage of fat and carbohydrate oxidation were observed among the three diet groups. Subjects with BCAA supplementation had an increased postprandial fat (p = 0.021) and decreased postprandial carbohydrate (p = 0.044) oxidation responses compared to the CT group after dietary intervention. Conclusions: BCAA-supplemented standard-protein diet did not significantly attenuate reduction of RMR compared to standard-protein and high-protein diets. However, the postprandial fat oxidation response increased after BCAA-supplemented weight loss intervention.
High-accuracy white-light optical piston sensor for segmented optics

A novel piston sensing concept is described for measuring piston over the +/- 0.5 wave range. The image of a white light point source is optically processed using a half-wave phase plate to enhance the presence of piston in the incident wavefront. The resultant point spread function is recorded on a CCD camera and analyzed using a simple intensity balance algorithm. Theoretical derivation and experimental results are provided, with emphasis on piston values below 0.25 waves. Piston values are measured to +/- 1/200 wave accuracy or better with a repeatability on the order of +/- 1/1000 wave.
Quality-Aware Multimodal Biometric Recognition

We present a quality-aware multimodal recognition framework that combines representations from multiple biometric traits with varying quality and number of samples to achieve increased recognition accuracy by extracting complimentary identification information based on the quality of the samples. We develop a quality-aware framework for fusing representations of input modalities by weighting their importance using quality scores estimated in a weakly-supervised fashion. This framework utilizes two fusion blocks, each represented by a set of quality-aware and aggregation networks. In addition to architecture modifications, we propose two task-specific loss functions: multimodal separability loss and multimodal compactness loss. The first loss assures that the representations of modalities for a class have comparable magnitudes to provide a better quality estimation, while the multimodal representations of different classes are distributed to achieve maximum discrimination in the embedding space. The second loss, which is considered to regularize the network weights, improves the generalization performance by regularizing the framework. We evaluate the performance by considering three multimodal datasets consisting of face, iris, and fingerprint modalities. The efficacy of the framework is demonstrated through comparison with the state-of-the-art algorithms. In particular, our framework outperforms the rank- and score-level fusion of modalities of BIOMDATA by more than 30% for true acceptance rate at false acceptance rate of 10−4.
Training and development methods and organizational performance: A case of the local government organization in Central Region, Ghana

Abstract Purpose: Is to investigate the relationship between training and development (T&D) methods and organizational performance in the local government sector, as well as contribute to knowledge. Research Methodology: The study employed a quantitative approach and correlation design, a census sampling method to sample 215 employees, a structured questionnaire to collect data, multiple linear regression to test hypotheses, and the Statistical Package for Social Science (SPSS) version 20 to input, transform and analyze the data. Result: The result shows that training and development (T & D) methods (job orientation, job rotation, workshop & conference, and classroom lectures) had a significant relationship with organizational performance. The findings also revealed that training and development (T & D) methods (job orientation, workshop & conference, and classroom lectures) have a significant relationship with the quality of service delivery. However, job rotation has no relationship with quality service delivery. Limitation: The study's main weakness is that it only looked at four different training and development methods and their impact on organizational performance and service quality. Another flaw in the study is that it only looked at one metropolitan assembly. Contribution: In this regard, metropolitan and municipal assembly executives and managers should consider employing training and development methods that provide stronger predictions to boost the organization’s performance and delivery of quality services to communities. They should train and develop employees within the organization as soon as political power changes hands to enhance organization performance because policy adherence is critical to the organization's performance.
Oxandrastins: Antibacterial Meroterpenes from an Australian Mud Dauber Wasp Nest-Associated Fungus, Penicillium sp. CMB-MD14

The ethyl acetate extract of an ISP-2 agar cultivation of the wasp nest-associated fungus Penicillium sp. CMB-MD14 exhibited promising antibacterial activity against vancomycin-resistant enterococci (VRE), with a bioassay guided chemical investigation yielding the new meroterpene, oxandrastin A (1), the first andrastin-like metabolite with an extra oxygenation at C-2. A culture media optimisation strategy informed a scaled-up rice cultivation that yielded 1, together with three new oxandrastins B–D (2–4), two known andrastins C (5) and F (6), and a new meroterpene of the austalide family, isoaustalide F (7). Structures of 1–7 were assigned based on detailed spectroscopic analysis and chemical interconversion. A GNPS molecular networking analysis of the rice cultivation extract detected the known austalides B (8), H (9), and H acid (10), tentatively identified based on molecular formulae and co-clustering with 7. That the anti-VRE properties of the CMB-MD14 extract were exclusively attributed to 1 (IC50 6.0 µM, MIC99 13.9 µM), highlights the importance of the 2-OAc and 3-OAc moieties to the oxandrastin anti-VRE pharmacophore.
Analyzing Infant Mortality in Rural Bangladesh: A Frailty Modeling Approach

In practice, it may happen that data may arise from a hierarchical structure i.e., a cluster is nested within another cluster. In this case, nested frailty model is appropriate to analyze survival data to obtain optimal estimates of the parameters of interest. To identify significant determinants of infant mortality in rural Bangladesh, survival data have been extracted from Bangladesh Demographic and Health Survey (BDHS), 2014. Because of the presence of two-level clustering in data, nested frailty model has been employed for the purpose of analysis. Recommendations have been suggested based on the results obtained from the survival model to reduce the infant mortality in rural Bangladesh to a great extent. Dhaka Univ. J. Sci. 69(2): 63-69, 2021 (July)
Double resurf technology for HVICs

A double resurf high voltage IC technology using a linearly varying doped (LVD) p- layer at the surface of a lateral power device is proposed. Detailed numerical simulations indicate enhancement in the performance of a lateral double diffused MOSFET (LDMOS) incorporating an LVD p- layer in comparison to a uniform p- layer. Moreover, this technique is found to be very effective as an interconnection technology.
Case study of inbreeding within Japanese Black cattle using resources of the American Wagyu Association, National Animal Germplasm Program, and a cooperator breeding program in Wyoming

© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Transl. Anim. Sci. 2021.5:S170–S174 https://doi.org/10.1093/tas/txab181
Recent progress of transparent conductive electrodes in the construction of efficient flexible organic solar cells

Flexible transparent conducting electrodes (F‐TCEs) are an important part of a flexible solar cell. The performance of the F‐TCEs is very important for the transmission of light and charge. Therefore, the selection of appropriate characteristics of F‐TCES, especially electrical conductivity, light transmittance, and mechanical flexibility, is essential for fabricating solar cells with high performance. This article reviewed the latest development of F‐TCEs and the structural design of flexible solar cells, compared and analyzed the preparation methods, advantages, and disadvantages of several different F‐TCEs, such as metal oxides, metals, carbon materials, polymers, and their composites. Based on different solar cell structures and flexible substrate types, the measures to obtain high transmittance, low resistance, etc., were emphatically discussed to obtain F‐TCEs with excellent performance. In order to make up for the shortcomings of single electrode materials, the current development of composite F‐TCEs electrodes was discussed and analyzed. Finally, the challenges faced by F‐TCEs and future development direction were prospected, providing a reference for the design of future intelligent photovoltaic systems.