Miracle-dz/UniFAR-FTUs huggingface dataset:
Using network pharmacology and molecular docking to explore the underlying anti-inflammatory mechanism of Wuyao-Danshen to treat endometriosis

Background This study sought to explore the anti-inflammatory mechanism of Wuyao (radix linderae)–Danshen (salviae miltiorrhiza) in endometriosis (EMS) based on network pharmacology and molecular docking. Methods The active constituents of Wuyao-Danshen were collected and identified using the Traditional Chinese Medicine Systems Pharmacology Database, and used to predict and identify the protein targets. The EMS targets and anti-inflammatory targets were obtained from Genecards, Online Mendelian Inheritance in Man, and Drugbank. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used to analyze the protein interactions (PPIs) and core targets, and a target PPI network was constructed by importing the software of Cytoscape. The Metascape database was used to conduct enrichment analyses of the Gene Ontology (GO) functions and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways for the key anti-inflammatory targets of EMS. Finally, Autodock Vina software was used to verify the results of the active ingredients and key anti-inflammatory targets. Results There were 8 active components in Wuyao, 65 in Danshen, and 591 corresponding protein targets in Danshen, and 375 in Wuyao, including luteolin, quercetin, vancomyl alcohol, and salvianol. One thousand and six hundred eighty-nine disease targets, 1,216 anti-inflammatory targets, and 144 key anti-inflammatory targets were identified, including the (signal transduction and transcriptional activator 3) STAT3, phosphatidyl inositol-3 kinase regulates subunit 1 (PIK3R1) and mitogen-activated protein kinase 1 (MAPK1) protein kinase B. Three hundred and fifty-three biological processes (BPs), 21 cellular components, and 25 molecular functions (MFs) were enriched with GO functions, and 108 KEGG pathways were enriched and analyzed, including the MAPK and PI3K-Akt signaling pathways. Molecular docking confirmed that luteolin, coumarin, and quercetin could bind to the key target proteins (i.e., STAT3, PIK3R1, and MAPK1). Conclusions Based on network pharmacology and molecular docking, Wuyao-Danshen was found to act on EMS through anti-inflammatory targets and related signaling pathways. Our findings provide a basis for further research.
Nanoindentation study on helium-irradiated graphene–aluminum composite: Indentation size effect, creep behavior, and their implications for coating–substrate systems

We carried out systematic nanoindentation measurements on nanolaminated graphene (reduced graphene oxide, RGO)–aluminum (Al) composite irradiated with high-energy helium ions at room and elevated temperatures. We revealed a clear transition in the deformation mechanism with the increase in indentation depth, within the micron-sized irradiation damage layer. At shallow indentations, the deformation of the irradiated layer was dominated by the indentation size effect, while the substrate effect started to interfere when the indentation depth exceeded a critical depth. Subsequent room temperature creep tests were conducted at maximum indentation depths that were meticulously chosen to avoid the interference of the substrate effect. The fitted creep stress exponents and the extracted apparent activation volumes reflected different operating deformation mechanisms among various sample sets. Our study provides a practical approach to deconvolute the indentation size effect and the substrate effect, which may lead to an improved accuracy in the interpretation of indentation data.
Detection of grassland mowing frequency using time series of vegetation indices from Sentinel-2 imagery

ABSTRACT Management intensity deeply influences meadow structure and functioning, therefore affecting grassland ecosystem services. Conservation and management measures, including European Common Agricultural Policy subsidies, should therefore be based on updated and publicly available data about management intensity. The mowing frequency is a crucial trait to describe meadows management intensity, but the potential of using vegetation indices from Sentinel-2 imagery for its retrieval has not been fully exploited. In this work we developed on the Google Earth Engine platform a four-phases algorithm to identify mowing frequency, including i) vegetation index time-series computing, ii) smoothing and resampling, iii) mowing detection, and iv) majority analysis. Mowing frequency during 2020 of 240 ha of grassland fields in the Italian Alps was used for algorithm optimization and evaluation. Six vegetation indexes (EVI, GVMI, MTCI, NDII, NDVI, RENDVI783.740) were tested as input to the proposed algorithm. The Normalized Difference Infrared Index (NDII) showed the best performance, resulting in mean absolute error of 0.07 and 93% overall accuracy on average at the four sites used for optimization, at pixel resolution. A slightly lower accuracy (mean absolute error = 0.10, overall accuracy = 90%) was obtained aggregating the maps to management parcels. The algorithm showed a good generalization ability, with a similar performance between global and local optimization and an average mean absolute error of 0.12 and an overall accuracy of 89% on average on the sites not used for parameters optimization. The lowest accuracies occurred in intensively managed grasslands surveyed by one satellite orbit only. This study demonstrates the suitability of the proposed algorithm to monitor very fragmented grasslands in complex mountain ecosystems. Google Earth Engine was used to develop the model and will enable researchers, agencies and practitioners to easily and quickly apply the code to map grassland mowing frequency for extensive grasslands protection and conservation, for mowing event verification, or for forage system characterization.
Multi Neural Network Method for Soft Sensing and Its Application

A Multi Neural Network method is proposed for soft sensing in a complex non-linear biochemical process. Low dimensional sample data are achieved by way of original data compression through principal component analysis, and a kind of modified sorting indices are used for these data to accomplish data hierarchy of the biochemical process model. Then, a soft sensing model is developed using multi neural network to fit the different hierarchical property of the process. The method has been applied to a glutamic acid fermentation process, and the testing results showed its effectiveness.
Negative E-cadherin expression on bone marrow myeloma cell membranes is associated with extramedullary disease

Background: The loss of E-cadherin expression and the induction of N-cadherin are known as hallmarks of the epithelial-to-mesenchymal transition, an essential initial step in the process of metastasis in solid tumors. Although several studies have reported expressions of these cadherins in patients with multiple myeloma (MM), their clinical significance is unknown as MM cells are non-epithelial. Methods: In this study, we examined the expression of E- and N-cadherins by immunohistochemistry using bone marrow (BM) biopsy specimens from 31 newly diagnosed MM patients and in subsequent biopsy specimens from six of these. Results: Negative E-cadherin expression on BM myeloma cell membranes was significantly associated with the presence of soft-tissue masses arising from bone lesions and breaking through the cortical bone, referred to as extramedullary disease (EMD). Conclusions: Given the aggressive nature of EMD, our study suggests that screening for E-cadherin using BM immunohistochemistry is one measure that could predict the development of EMD in patients with MM.
Concurrent Heat Waves and Extreme Ozone (O3) Episodes: Combined Atmospheric Patterns and Impact on Human Health

More recurrent heat waves and extreme ozone (O3) episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance, and their joint effect on human health. In this work, we use surface maximum temperature and O3 observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indices (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Saharan Oscillation (SaO)). We then identify concurrent heat waves and O3 episodes, the weather type behind this concurrence, and the combined health risks. Our findings show that the concurrence of heat waves and O3 episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step toward the establishment of an alert system. It will help to provide recommendations for coping with concurrent heat waves and air pollution episodes.
Joint management of marine mammals and a fish species: The case of cod and grey seals in the Nordic‐Baltic Sea countries

In this paper, we present a simple theoretical, steady‐state equilibrium, predator‐prey model for the joint management of marine mammals and a fish species. As an empirical case, we choose cod and grey seals in the Nordic‐Baltic Sea countries, and several benefits and costs related to the latter are considered. We show that the optimal grey seal population is much lower than the actual population, and this result is robust to variations in relevant parameter values. This result can be explained by the fact that the profit from harvesting cod is much higher than the net benefits from grey seals.
Identifying entrepreneurial discovery processes with weak and strong technology signals: a text mining approach

This study aims to propose methods for identifying entrepreneurial discovery processes with weak/strong signals of technological changes and incorporating technology foresight in the design and planning of the Smart Specialization Strategy (S3). For this purpose, we first analyse patent abstracts from 2000 to 2009, obtained from the European Patent Office and use a keyword-based text mining approach to collect weak and strong technology signals; the word2vec algorithm is also employed to group weak signal keywords. We then utilize Correlation Explanation (CorEx) topic modelling to link technology weak/strong signals to invention activities for the period 2010-2018 and use the ANOVA statistical method to examine the relationship between technology weak/strong signals and patent values. The results suggest that patents related to weak rather than strong signals are more likely to be high-impact innovations and to serve as a basis for future technological developments. Furthermore, we use latent Dirichlet allocation (LDA) topic modelling to analyse patent activities related to weak/strong technology signals and compute regional topic weights. Finally, we present implications of the research.
Response of bacterial community structure to different ecological niches and their functions in Korean pine forests

A healthy plant microbiome is diverse, taxonomically-structured, and gives its plant host moderate advantages in growth, development, stress tolerance, and disease resistance. The plant microbiome varies with ecological niches and is influenced by variables that are complex and difficult to separate from each other, such as the plant species, soil, and environmental factors. To explore the composition, diversity, and functions of the bacterial community of Korean pine forests, we used high-throughput sequencing to study five areas with different forest ages from June to October 2017 in northeast China. We obtained 3,247 operational taxonomic units (OTUs) based on 16S rRNA gene sequencing via an Illumina Hi-seq platform. A total of 36 phyla and 159 known genera were classified. The Shannon index of the bacterial community from the rhizospheric soil was significantly higher (p < 0.01, n = 10) than that of the root tips. Beta-diversity analysis confirmed that the bacterial community of the rhizospheric soil was significantly different (p < 0.001) from the root tips. Nine bacterial phyla were dominant (relative richness > 1%) in the rhizospheric soil, but there were six dominant phyla in the root tips. Proteobacteria was the core flora in the root tips with a relative abundance of more than 50%. It is known that the formation of bacterial communities in the rhizospheric soil or the root is mainly caused by the processes of selection, and we found a relatively high abundance of a few dominant species. We further analyzed the correlations between the bacterial community from the rhizospheric soil with that of the root tips, as well as the correlations of the bacterial community with soil physicochemical properties and climate factors. We used Functional Annotation of the Prokaryotic Tax (FAPROTAX) to predict the functions of the bacterial community in the rhizospheric soil and root tips. Five related phototrophic functions, nine nitrogen cycle functions, two related chemoheterotrophic functions, and two others were predicted. The abundance of the bacteria phyla performing relevant functions was different in the rhizospheric soil than in the root tips. These functions were significantly influenced by the contents of nitrogen, phosphorus, and potassium in the soil habitat. The bacterial composition and functions in the rhizospheric soil and root tips of Korean pine were analyzed, and the results demonstrated the importance of soil and plant species on the bacterial community in the below ground plant microbiome.
Automated Quality and Process Control for Additive Manufacturing using Deep Convolutional Neural Networks

Additive Manufacturing (AM) is a crucial component of the smart manufacturing industry. In this paper, we propose an automated quality grading system for the fused deposition modeling (FDM) process as one of the major AM processes using a developed real-time deep convolutional neural network (CNN) model. The CNN model is trained offline using the images of the internal and surface defects in the layer-by-layer deposition of materials and tested online by studying the performance of detecting and grading the failure in AM process at different extruder speeds and temperatures. The model demonstrates an accuracy of 94% and specificity of 96%, as well as above 75% in measures of the F-score, the sensitivity, and the precision for classifying the quality of the AM process in five grades in real-time. The high-performance of the model could not be achieved with the values usually used for printing temperature and printing speed, only in addition with much higher values. The proposed online model adds an automated, consistent, and non-contact quality control signal to the AM process. The quality monitoring signal can also be used by the AM machine to stop the AM process and eliminate the sophisticated inspection of the printed parts for internal defects. The proposed quality control model ensures reliable parts with fewer quality hiccups while improving performance in time and material consumption.
Prognostic Impact of In-Hospital Use of Mechanical Cardiopulmonary Resuscitation Devices Compared with Manual Cardiopulmonary Resuscitation: A Nationwide Population-Based Observational Study in South Korea

Background and Objectives: This study analyzed the prognostic impact of mechanical cardiopulmonary resuscitation (CPR) devices in out-of-hospital cardiac arrest (OHCA) patients, in comparison to manual CPR. Materials and Methods: This study was a nationwide population-based observational study in South Korea. Data were retrospectively collected from 142,905 OHCA patients using the South Korean Out-of-Hospital Cardiac Arrest Surveillance database. We included adult OHCA patients who received manual or mechanical CPR in the emergency room. The primary outcome was survival at discharge and the secondary outcome was sustained return of spontaneous circulation (ROSC). Statistical analysis included propensity score matching and multivariate logistic regression. Results: A total of 19,045 manual CPR and 1125 mechanical CPR cases (671 AutoPulseTM vs. 305 ThumperTM vs. 149 LUCASTM) were included. In the matched multivariate analyses, all mechanical CPR devices were associated with a lower ROSC than that of manual CPR. AutoPulseTM was associated with lower survival in the multivariate analysis after matching (aOR with 95% CI: 0.57 (0.33–0.96)), but the other mechanical CPR devices were associated with similar survival to discharge as that of manual CPR. Witnessed arrest was commonly associated with high ROSC, but the use of mechanical CPR devices and cardiac origin arrest were associated with low ROSC. Only target temperature management was the common predictor for high survival. Conclusions: The mechanical CPR devices largely led to similar survival to discharge as that of manual CPR in OHCA patients; however, the in-hospital use of the AutoPulseTM device for mechanical CPR may significantly lower survival compared to manual CPR.
Social Globalisation and Efficiency of Microfinance Institutions Nexus: Empirical Evidence on Financial and Social Efficiency

The main objective of this paper is to identify the impacts of social globalisation comprised of personal contacts, information flows and cultural proximity to the financial and social efficiency of Microfinance Institutions (MFIs). This study had conducted two stages of analysis, in which the first stage is Data Envelopment Analysis (DEA) approach and the second stage is multiple panel regression analysis under Generalized Least Square estimation method. The results exhibit that the overall MFIs operated in a relatively optimal scale during the period of the study. However, these MFIs were managerially inefficient in utilising their resources to achieve both social and financial efficiency. The results from panel regression analysis showed that only personal contacts exhibit a significant positive relationship with the financial efficiency of MFIs. This study could contribute new insights and implications to various parties, such as MFIs, policy makers, investors and researchers to improve the efficiency of MFIs.
Inactivation of Opportunistic Pathogens Acinetobacter baumannii and Stenotrophomonas maltophilia by Antimicrobial Photodynamic Therapy

Acinetobacter baumannii and Stenotrophomonas maltophilia are opportunistic pathogens causing hospital infections with limited treatment options due to bacterial multidrug resistance. Here, we report that antimicrobial photodynamic therapy (aPDT) based on the natural photosensitizers riboflavin and chlorophyllin inactivates A. baumannii and S. maltophilia. The riboflavin and chlorophyllin photostability experiments assessed the photomodifications of photosensitizers under the conditions subsequently used to inactivate A. baumannii and S. maltophilia. A. baumannii planktonic cells were more sensitive to riboflavin-aPDT, while biofilm bacteria were more efficiently inactivated by chlorophyllin-aPDT. S. maltophilia planktonic and biofilm cells were more susceptible to chlorophyllin-aPDT compared to riboflavin-aPDT. The results suggest that riboflavin- and chlorophyllin-aPDT can be considered as a potential antimicrobial treatment for A. baumannii and S. maltophilia inactivation.
Vardenafil Oral Dispersible Films (ODFs) with Advanced Dissolution, Palatability, and Bioavailability

Oral, quick response, and on demand, also known as a spontaneous oral treatment for erectile dysfunction, is highly needed by both patients and physicians. Vardenafil is selective (fewer side effects) and more effective in difficult-to-treat conditions than sildenafil. This study aims at fostering the dual objectives of using biomolecules such as artificial sweetening agents to solubilize and mask the bitterness of vardenafil loaded on biodegradable polymeric materials (PVA, MC, SA, and PVP K30) to fabricate oral, fast-dissolving films (vardenafil ODFs) in the mouth without the need for water to ingest the dosage form. Furthermore, coprecipitated-dispersed mixtures of vardenafil and three sweeteners (sorbitol, acesulfame K, and sucralose) were prepared and characterized using FTIR, DSC, and solubility studies. Moreover, eight different vardenafil ODFs were prepared using the solvent-casting method. Modified gustatory sensation test, in vitro disintegration, and release studies were performed. In addition, the optimized ODF (F8) was compared with the commercial film-coated tablets pharmacokinetically (relative bioavailability, onset, and duration of actions were estimated). The results indicated that the three sweetening agents had comparable solubilizing capacity. However, both sucralose- and acesulfame K-based ODFs have a more enhanced sweet and palatable taste than sorbitol-sweetened ODF. The SA- and PVP K30-based ODFs showed significantly faster disintegration times and release rates than MC. In conclusion, PVA has good film-forming properties, but a higher ratio of PVA adversely affected the disintegration and release characteristics. The % relative bioavailability for ODF was 126.5%, with a superior absorption rate constant (Ka) of 1.2-fold. The Cmax and estimated Tmax were compared to conventional film-coated tablets.
Risk Assessment Matrices for Workplace Hazards: Design for Usability

In occupational safety and health (OSH), the process of assessing risks of identified hazards considers both the (i) foreseeable events and exposures that can cause harm and (ii) the likelihood or probability of occurrence. To account for both, a table format known as a risk assessment matrix uses rows and columns for ordered categories of the foreseeable severity of harm and likelihood/probability of that occurrence. The cells within the table indicate level of risk. Each category has a text description separate from the matrix as well as a word or phrase heading each row and column. Ideally, these header terms will help the risk assessment team distinguish among the categories. A previous project provided recommended sets of header terms for common matrices based on findings from a survey of undergraduate OSH students. This paper provides background on risk assessment matrices, discusses usability issues, and presents findings from a survey of people with OSH-related experience. The aim of the survey was to confirm or improve the prior recommended sets of terms. The prior recommendations for severity, likelihood, and extent of exposure were confirmed with minor modifications. Improvements in the probability terms were recommended.