Miracle-dz/UniFAR-FTUs huggingface dataset:
Antidiabetic (α-amylase and α-glucosidase) and anti-obesity (lipase) inhibitory activities of edible cassava (Manihot esculenta Crantz) as measured by in vitro gastrointestinal digestion: effects of phenolics and harvested time

ABSTRACT Edible cassava leaves (Manihot esculenta) were consumed as vegetables for their bioactive compounds, however the effect of harvesting time on these bioactive compounds and their antidiabetic and anti-obesity inhibitory activities were scarcely reported in the literature. Phenolics from edible leaves harvested at different times were assessed using HPLC-DAD, and their antidiabetic and anti-obesity inhibitory activities were investigated before and after in vitro gastrointestinal digestion. The results showed a significant (P < .05) effect of harvesting time on phenolic contents. Bound phenolics showed higher lipase inhibitory activity than their free fractions. However, phenolic contents decreased after in vitro digestion, while they showed high antidiabetic and anti-obesity inhibitory activities. The present study demonstrated that edible leaves harvested at different times are rich in flavonoids, stilbenes, tannins and saponins. These bioactive compounds are highly potent against α-amylase, α-glucosidase and lipase before and after in vitro gastrointestinal digestion. Therefore, we recommend edible cassava leaves for important biological active compounds for the prevention of obesity and type 2 diabetes.
MEASURING THE STORE IMAGE AS A HIGHER ORDER FACTOR IN UDON THANI PROVINCE

The objective of the research was to examine the store image in Udon Thani province. Given the literature review, a model proposed the store image which was identified as a one-dimensional construct consisting of five components such as brand name, product quality, service quality, atmosphere, and perceived value. Using a survey design, data were collected via questionnaires interviewing 443 household samples. They included the customers of stores in Udon Thani province. The author argued the second-order factor structure for the store image significantly supported. This suggested that customers evaluated the store image on five basic dimensions but they also viewed overall store image as a higher order factor that captured a meaning common to all dimensions.
Ensemble Deep-Learning-Enabled Clinical Decision Support System for Breast Cancer Diagnosis and Classification on Ultrasound Images

Simple Summary In the literature, there exist plenty of research works focused on the detection and classification of breast cancer. However, only a few works have focused on the classification of breast cancer using ultrasound scan images. Although deep transfer learning models are useful in breast cancer classification, owing to their outstanding performance in a number of applications, image pre-processing and segmentation techniques are essential. In this context, the current study developed a new Ensemble Deep-Learning-Enabled Clinical Decision Support System for the diagnosis and classification of breast cancer using ultrasound images. In the study, an optimal multi-level thresholding-based image segmentation technique was designed to identify the tumor-affected regions. The study also developed an ensemble of three deep learning models for feature extraction and an optimal machine learning classifier for breast cancer detection. The study offers a means of assisting radiologists and healthcare professionals in the breast cancer classification process. Abstract Clinical Decision Support Systems (CDSS) provide an efficient way to diagnose the presence of diseases such as breast cancer using ultrasound images (USIs). Globally, breast cancer is one of the major causes of increased mortality rates among women. Computer-Aided Diagnosis (CAD) models are widely employed in the detection and classification of tumors in USIs. The CAD systems are designed in such a way that they provide recommendations to help radiologists in diagnosing breast tumors and, furthermore, in disease prognosis. The accuracy of the classification process is decided by the quality of images and the radiologist’s experience. The design of Deep Learning (DL) models is found to be effective in the classification of breast cancer. In the current study, an Ensemble Deep-Learning-Enabled Clinical Decision Support System for Breast Cancer Diagnosis and Classification (EDLCDS-BCDC) technique was developed using USIs. The proposed EDLCDS-BCDC technique was intended to identify the existence of breast cancer using USIs. In this technique, USIs initially undergo pre-processing through two stages, namely wiener filtering and contrast enhancement. Furthermore, Chaotic Krill Herd Algorithm (CKHA) is applied with Kapur’s entropy (KE) for the image segmentation process. In addition, an ensemble of three deep learning models, VGG-16, VGG-19, and SqueezeNet, is used for feature extraction. Finally, Cat Swarm Optimization (CSO) with the Multilayer Perceptron (MLP) model is utilized to classify the images based on whether breast cancer exists or not. A wide range of simulations were carried out on benchmark databases and the extensive results highlight the better outcomes of the proposed EDLCDS-BCDC technique over recent methods.
The Relationship of Metacognitive Reading Strategies Used by Saudi EFL Learners and their Emotional Intelligence

Reading comprehension is a complex process that is based on several factors such as emotion, intelligence, cognition, metacognition and like. It has been proved that there is a strong correlation between the use of metacognitive strategies and reading comprehension. This study investigated the relationship between Saudi EFL learners’ emotional intelligence and using metacognitive reading strategies. The sample of the study consisted of 100 Saudi EFL learners across the age range of 18-35 who were selected randomly from different Saudi universities. The participants were homogenized through administering a reading comprehension test. The main instruments included Emotional Intelligence Questionnaire (Petrides, 2009) and Mokhtari and Sheorey (2002) Survey of Reading Strategies (SORS) that measured the use of metacognitive reading strategies. The results revealed a highly positive connection between the Saudi EFL students’ emotional intelligence and the use of metacognitive reading strategies. Furthermore, practical implications were provided for EFL learners, teachers, and curriculum and program designers and developers.
High-dimensional sufficient dimension reduction through principal projections

: We develop in this work a new dimension reduction method for high-dimensional settings. The proposed procedure is based on a principal support vector machine framework where principal projections are used in order to overcome the non-invertibility of the covariance matrix. Using a series of equivalences we show that one can accurately recover the central subspace using a projection on a lower dimensional subspace and then applying an (cid:2) 1 penalization strategy to obtain sparse estimators of the suﬃcient directions. Based next on a desparsiﬁed estimator, we provide an inferential procedure for high-dimensional models that allows testing for the importance of variables in determining the suﬃcient direction. Theoretical properties of the methodology are illustrated and computational advantages are demonstrated with simulated and real data experiments.
Multielemental Inductively Coupled Plasma – Optical Emission Spectrometric (ICP-OES) Method for the Determination of Nutrient and Toxic Elements in Wild Mushrooms Coupled to Unsupervised and Supervised Chemometric Tools for Their Classification by Species

Abstract An inductively coupled plasma – optical emission spectrometric (ICP-OES) method was employed to assess the elemental composition of the wild mushrooms belonging to the species of Craterellus cornucopioides, Boletus aereus, and Cantharellus cibarius. The ICP-OES method was validated in terms of linearity, accuracy, precision, limits of detection (LODs), and limits of quantification (LOQs). The relative recoveries of the proposed method were between 80.9% and 119.7%, while the relative standard deviation values were less than 8.8%. The limits of detection and quantification of the ICP-OES method were between 0.02 mg/kg (Mn) − 1.37 mg/kg (Αl), and between 0.08 mg/kg (Mn) − 4.57 mg/kg (Al), respectively. Al, B, Ca, Cr, Cu, Fe, Mg, Ni, and Zn were determined, and the results were analyzed by principal component analysis (PCA). One-way ANOVA was used to identify statistically significant differences based on the metal content and the mushroom species. Finally, a partial least square discriminant analysis (PLS-DA) model was developed to classify the samples based on their elemental profile according to their species.
Spatial Panel Data Approach on Environmental Quality in Indonesia

Indonesia adopted a strategic long-term development plan (2005-2025) targeting to achieve a green and everlasting Indonesia through implementing various environmental policies. One of the mandatory matters for governments is to continue environmental control by constructing Environmental Quality Indexes (EQI). This study focuses on the relationship between regional output or real Regional GDP, level of population density, and the government expenditure on environment quality on EQI in 34 provinces in Indonesia by the time period 2015 to 2019 using a spatial panel data approach. Within the context of spatial modeling, the interaction between provinces depends on their geographical location and condition. Using the geographic information system (GIS) and stata attributes, the coordinates and distances can be mapped and then defined for observation units in space via the spatial weight matrix used. From the perspective of spatial geography, this paper verifies the spatial dependence of Indonesia’s Environmental Quality Index (EQI). Pesaran's CD test indicates the spatial effect on the model and SAR with random effect can be considered a better-fitting spatial panel regression model. The results of the econometric spatial panel using SAR panel with random effect analysis show that Indonesia’s EQI in the provinces was dependent on the spatial. It was also found that regional GDP has a significant and negative effect on EQI and population density has a negative and significant effect on EQI. While fiscal policy on the environmental area on improving environmental quality did not pass a significance test. Thus, it is recommended to look for ways to promote green growth in the country.
Comprehensive Analyses of Four PtoNF-YC Genes from Populus tomentosa and Impacts on Flowering Timing

Flowering is an important link in the life process of angiosperms, and it is also an important sign of the transformation of plants from vegetative to reproductive growth. Although the flowering regulation network of Arabidopsis is well-understood, there has been little research on the molecular mechanisms of perennial woody plant flower development regulation. Populus tomentosa is a unique Chinese poplar species with fast growth, strong ecological adaptability, and a long lifecycle. However, it has a long juvenile phase, which seriously affects its breeding process. Nuclear factor-Y (NF-Y) is an important type of transcription factor involved in the regulation of plant flowering. However, there are few reports on PtoNF-Y gene flowering regulation, and the members of the PtNF-YC subfamily are unknown. In this study, four key genes were cloned and analyzed for sequence characteristics, gene structure, genetic evolution, expression patterns, and subcellular localization. The plant expression vector was further constructed, and transgenic Arabidopsis and P. tomentosa plants were obtained through genetic transformation and a series of molecular tests. The flowering time and other growth characteristics were analyzed. Finally, the expression level of flowering genes was detected by quantitative PCR, the interaction between PtoNF-YC and PtoCOL proteins was measured using the yeast two-hybrid system to further explain the flowering regulation mechanism, and the molecular mechanisms by which PtNF-YC6 and PtNF-YC8 regulate poplar flowering were discussed. These results lay the foundation for elucidating the molecular regulation mechanism of PtoNF-YC in flowering and furthering the molecular design and breeding of poplar, while providing a reference for other flowering woody plants.
The impact of supply chain specific investments on firms’ market performance: the mediating role of innovation

Purpose Manufacturers’ specific investments (SIs) in a specific partner that are of lower value when used in an alternative relationship, such as training employees and tailoring systems to achieve better cooperation, can help improve market performance. However, previous studies lack a simultaneous focus on a manufacturer’s SIs in its upstream and downstream partners. The purpose of this study is to address the effects of manufacturers’ SIs in their suppliers and customers on the two types of innovation and market performance individually and jointly and the mediating effects of radical and incremental innovation on relationships between SIs and market performance. Design/methodology/approach This study tests proposed relationships based on data collected from 206 manufacturers in China using regression methods. Findings Results show that SIs in customers directly and indirectly affect market performance through radical and incremental innovation. However, SIs in suppliers cannot directly improve market performance but indirectly enhance market performance through radical innovation. Furthermore, results also show the interaction of SIs in suppliers and customers is positively related to market performance and radical innovation. Originality/value This study contributes to the literature on SIs by identifying supply chain SIs (SCSIs) through simultaneously focusing on SIs in suppliers and customers and exploring the direct and indirect effects of SCSIs on market performance. This study also contributes to the innovation literature by empirically verifying incremental and radical innovation as effective intermediaries that help convert SIs into the actual performance improvement.
Malaria prevention practices and malaria prevalence among children living in a rural community in Southwest Nigeria.

INTRODUCTION Living conditions in most rural African communities favour malaria transmission and threaten global eradication. Prevention strategies and interventions such as the use of bed nets have reduced the prevalence of malaria. This study described the various methods employed to prevent malaria and their effects on malaria parasite prevalence among children living in a rural community in Nigeria. METHODOLOGY A community-based cross-sectional study conducted among 357 children aged 1-15 years, in a Nigerian rural community. Data was analyzed using SPSS version 25. Chi-squared test of association with a level of significance of p < 0.050 was used. RESULTS Only 110 (30.8%) participants owned mosquito nets. Mostly those from the high social class (45; 40.9%) used the nets, and these were mostly 'under-five' children. Thirty-six (10.1%) were routinely given antimalarial drugs for malaria prophylaxis. Also, 102 (28.6%), 151 (42.3%), 278 (77.9%), 99 (27.7%) and 15 (5.0%) children used insecticides, local herbs, window nets, outlet door nets and mosquito repellent creams respectively. None of the methods employed to prevent malaria had statistically significant effect on malaria parasite prevalence among participants (p > 0.050). CONCLUSIONS Malaria prevention methods were mostly practiced by participants of the high social class while children under-five considerably used mosquito nets. This study highlights the need to address the socio-demographic imbalance regarding malaria preventive measures in the community where the study was conducted. There is also a need to regulate the use of antimalarial drugs for malaria prophylaxis in the rural community. These suggest that the current malaria prevention methods in the community be reviewed.
Antiviral Effects of Probiotic Metabolites

Presently, viral diseases are incrementing all over the world, for which the definitive solutions are difficult since there are no effective drugs. In the 1990s, antiviral probiotics first appeared when they acted as drugs for protecting the intestinal epithelium against viral infection and reducing diarrhea. Thus, further studies have been performed to define the mechanisms behind this antiviral impact. Over 100 years ago, lactic acid bacteria (LAB) were accidentally utilized naturally exist in fermented products, against viral infections. Producing several active ingredients like active ribosomal proteins, acids, hydrogen peroxide, non-ribosomal synthetase peptides (NRPS), and other metabolites is an important feature of lactic acid bacteria. Numerous studies have recently assessed the significance of these active ingredients in both nutrition and medicine. LAB was utilized in food fermentation to present a good taste for food while protecting it from pathogenic microorganisms and spoilage. In this article, the LAB metabolites’ antiviral activity was assessed.
Frequentist test in Bayesian two-stage designs applied in experimental trials

Prediction provides discipline and pragmatic importance to empirical research. The design with the predictive probability approach provides an excellent alternative for conducting multi-stage phase II trials; it is efficient and flexible and possesses desirable statistical properties. In this paper we consider the Bayesian predictive procedures within the experimental design, for this, we define indices of satisfaction related to a test as a decreasing function of the p-value and satisfaction is higher than the null hypothesis is rejected wider. This design possesses good frequentist properties and allows early termination of the trial. We treated our applications by simulation and real data in experimental planning and sequential designs with binary outcomes.
Evaluation of the Diagnostic Accuracy of Nasal Cavity and Nasopharyngeal Swab Specimens for SARS-CoV-2 Detection via Rapid Antigen Test According to Specimen Collection Timing and Viral Load

The rapid diagnosis of SARS-CoV-2 is an essential aspect in the detection and control of the spread of COVID-19. We evaluated the accuracy of the rapid antigen test (RAT) using samples from the nasal cavity and nasopharynx based on sample collection timing and viral load. We enrolled 175 patients, of which 71 patients and 104 patients had tested positive and negative, respectively, based on real time-PCR. Nasal cavity and nasopharyngeal swab samples were tested using STANDARD Q COVID-19 Ag tests (Q Ag, SD Biosensor, Korea). The sensitivity of the Q Ag test was 77.5% (95% confidence interval [CI], 67.8–87.2%) for the nasal cavity and 81.7% (95% [CI, 72.7–90.7%) for the nasopharyngeal specimens. The RAT results showed a substantial agreement between the nasal cavity and nasopharyngeal specimens (Cohen’s kappa index = 0.78). The sensitivity of the RAT for nasal cavity specimens exceeded 89% for <5 days after symptom onset (DSO) and 86% for Ct of E and RdRp < 25. The Q Ag test performed fairly well, especially in the early DSO when a high viral load was present, and the nasal cavity swab can be considered an alternative site for the rapid diagnosis of COVID-19.
Novel Crab Cavity RF Design

A 20-50 MV integrated transverse voltage is required for the Electron-Ion Collider. The most promising of the crab cavity designs that have been proposed in the last five years are the TEM type crab cavities because of the higher transverse impedance. The TEM design approach is extended here to a hybrid crab cavity that includes the input power coupler as an integral part of the design. A prototype was built with Phase I monies and tested at JLAB. The results reported on, and a system for achieving 20-50 MV is proposed.
Impact of Transmission Distortion of Line-outage-state Information on Cascading Failures

The impact of failures in the information network on a power system is seldom,if ever,considered in the conventional research on cascading failures in power systems.Therefore,the information network is integrated with the hidden failure model to investigate the impact of node failures in the information network on the cascading failures in power systems.Take the New England 39-bus system as an example.A new index is used to identify the key-buses causing large blackouts.The index is very effective in identifying the key-buses which exert vital influence on blackouts in power systems operating in various states.Simulation results show that the failures of the information network may make the situation even worse and lead to large blackouts.Moreover,high-degree and,in fact,high-betweenness nodes in the information network,are not the key information nodes that generate important influence in the spread of cascading failures.Rather,compared with the topological characteristics of information nodes in their own network,the physical characteristics of the information nodes corresponding transmission lines are better able to characterize the importance of information nodes in the cascading failures of the power system.
Impaired Cardiovascular Response to Exercise in Patients with Severe Asthma: A Case-Control Study

Background: Although asthmatics may present reduced exercise capacity, data on their cardiovascular responses during exercise testing have been scarcely investigated. The aim of this pilot case-control study is to test: a) whether double product (DP), an index of cardiovascular reserve, differs among patients with severe and mild-moderate asthma, and b) whether DP is associated with asthma control level, physical activity (PA) and exercise capacity, in asthmatics population. Materials and Methods: A group of patients with severe asthma (group S) and a matched group of patients with mild-moderate asthma (group M) was studied. All participants completed asthma control and physical activity (IPAC) questionnaires, lung function measurements and six-minute walk test. The exercise capacity (as 6-minute walk distance (6MWD) and corresponding work), the Borg Dyspnea, the rating of perceived excursion and the average PA METS were recorded. Results: A total of 18 patients were studied. DP at exercise end was significantly lower in group S, compared to group M (16412.2±4732.1 vs. 18594.8±3984.4 mmHgXbpm; p=0.041) and was moderately associated with % predicted 6MWD (r=0.592; p=0.001). Group S patients were also presented with lower moderate intensity PA, compared to group M, while exercise capacity was similar between the groups. Asthma control level had no impact on exercise capacity nor PA parameters. Conclusion: Patients with severe asthma may have impaired cardiovascular reserve as established by DP, even when exercise capacity is indifferent from patients with milder disease. As an easy-to-assess parameter, DP may offer further information in the functional evaluation of these patients.