Miracle-dz/UniFAR-FTUs huggingface dataset:
Agaricus Mushroom-Enriched Diets Modulate the Microbiota-Gut-Brain Axis and Reduce Brain Oxidative Stress in Mice

Neurodegenerative diseases pose a major problem for developed countries, and stress has been identified as one of the main risk factors in the development of these disorders. Here, we have examined the protective properties against brain oxidative stress of two diets supplemented with 5% (w/w) of Agaricus bisporus (white button mushroom) or Agaricus bisporus brunnescens (Portobello mushroom) in mice. These diets did not modify the weight gain of the animals when compared to those fed with a regular diet, even after feeding on them for 15 weeks. The long-term modification of the microbiota after 12 weeks on the diets was investigated. At the phylum level, there was a large increase of Verrucomicrobia and a reduction of Cyanobacteria associated with the mushroom diets. No changes were observed in the Firmicutes/Bacteroidetes ratio, whose stability is a marker for a healthy diet. At the family level, three groups presented significant variations. These included Akkermansiaceae and Tannerellaceae, which significantly increased with both diets; and Prevotellaceae, which significantly decreased with both diets. These bacteria participate in the generation of microbiota-derived short-chain fatty acids (SCFAs) and provide a link between the microbiota and the brain. Mice subjected to restraint stress showed an upregulation of Il-6, Nox-2, and Hmox-1 expression; a reduction in the enzymatic activities of catalase and superoxide dismutase; and an increase in lipid peroxidation in their brains. All these parameters were significantly prevented by feeding for 3 weeks on the Agaricus-supplemented diets. In summary, the supplementation of a healthy diet with Agaricus mushrooms may significantly contribute to prevent neurodegenerative diseases in the general population.
An Efficient Hybrid Evolutionary Optimization Method Coupling Cultural Algorithm with Genetic Algorithms and Its Application to Aerodynamic Shape Design

Evolutionary algorithms have been widely used to solve complex engineering optimization problems with large search spaces and nonlinearity. Both cultural algorithm (CA) and genetic algorithms (GAs) have a broad prospect in the optimization field. The traditional CA has poor precision in solving complex engineering optimization problems and easily falls into local optima. An efficient hybrid evolutionary optimization method coupling CA with GAs (HCGA) is proposed in this paper. HCGA reconstructs the cultural framework, which uses three kinds of knowledge to build the belief space, and the GAs are used as an evolutionary model for the population space. In addition, a knowledge-guided t-mutation operator is developed to dynamically adjust the mutation step and introduced into the influence function. HCGA achieves a balance between exploitation and exploration through the above strategies, and thus effectively avoids falling into local optima and improves the optimization efficiency. Numerical experiments and comparisons with several benchmark functions show that the proposed HCGA significantly outperforms the other compared algorithms in terms of comprehensive performance, especially for high-dimensional problems. HCGA is further applied to aerodynamic optimization design, with the wing cruise factor being improved by 23.21%, demonstrating that HCGA is an efficient optimization algorithm with potential applications in aerodynamic optimization design.
The complete mitochondrial genome of Pomadasys kaakan (Perciformes: Haemulidae)

Abstract Pomadasys kaakan (Cuvier 1830) is a fish found in coastal waters that is widely distributed in the Western Indo-Pacific Ocean and plays an important role in commercial fisheries. The complete mitochondrial genome of P. kaakan was determined for the first time in this study. The genome was 16,808 bp in length and consisted of 13 protein coding genes, 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, and one noncoding control region. The overall base composition was estimated to be A: 27.1%; T: 24.7%; C: 31.7%; and G: 16.5%, with an AT bias of 51.8%. Molecular phylogenetic analysis suggested that P. kaakan was clustered with species of genera Plectorhinchus, Diagramma, and Parapristipoma, which also belonged to the Haemulidae family. Furthermore, the Haemulidae family was closely related to the group containing Oplegnathidae, Kyphosidae, Teraponidae, and Lutjanidae. These results may provide molecular information for the species evolution and phylogenetic status of P. kaakan in the suborder Percoidei.
Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study

Background Social media platforms are widely used by people suffering from mental illnesses to cope with their conditions. One modality of coping with these conditions is navigating online communities where people can receive emotional support and informational advice. Benefits have been documented in terms of impact on health outcomes. However, the pitfalls are still unknown, as not all content is necessarily helpful or correct. Furthermore, the advent of the COVID-19 pandemic and related problems, such as worsening mental health symptoms, the dissemination of conspiracy narratives, and medical distrust, may have impacted these online communities. The situation in Italy is of particular interest, being the first Western country to experience a nationwide lockdown. Particularly during this challenging time, the beneficial role of community moderators with professional mental health expertise needs to be investigated in terms of uncovering misleading information and regulating communities. Objective The aim of the proposed study is to investigate the potentially harmful content found in online communities for mental health symptoms in the Italian language. Besides descriptive information about the content that posts and comments address, this study aims to analyze the content from two viewpoints. The first one compares expert-led and peer-led communities, focusing on differences in misinformation. The second one unravels the impact of the COVID-19 pandemic, not by merely investigating differences in topics but also by investigating the needs expressed by community members. Methods A codebook for the content analysis of Facebook communities has been developed, and a content analysis will be conducted on bundles of posts. Among 14 Facebook groups that were interested in participating in this study, two groups were selected for analysis: one was being moderated by a health professional (n=12,058 members) and one was led by peers (n=5598 members). Utterances from 3 consecutive calendar years will be studied by comparing the months from before the pandemic, the months during the height of the pandemic, and the months during the postpandemic phase (2019-2021). This method permits the identification of different types of misinformation and the context in which they emerge. Ethical approval was obtained by the Università della Svizzera italiana ethics committee. Results The usability of the codebook was demonstrated with a pretest. Subsequently, 144 threads (1534 utterances) were coded by the two coders. Intercoder reliability was calculated on 293 units (19.10% of the total sample; Krippendorff α=.94, range .72-1). Aside from a few analyses comparing bundles, individual utterances will constitute the unit of analysis in most cases. Conclusions This content analysis will identify deleterious content found in online mental health support groups, the potential role of moderators in uncovering misleading information, and the impact of COVID-19 on the content. International Registered Report Identifier (IRRID) PRR1-10.2196/35347
ACE2 Receptor and Its Isoform Short-ACE2 Are Expressed on Human Spermatozoa

Angiotensin-converting enzyme 2 (ACE2) is a protein widely expressed in numerous cell types, with different biological roles mainly related to the renin-angiotensin system. Recently, ACE2 has been in the spotlight due to its involvement in the SARS-CoV-2 entry into cells. There are no data available regarding the expression of ACE2 and its short-ACE2 isoform at the protein level on human spermatozoa. Here, protein expression was demonstrated by western blot and the percentage of sperm displaying surface ACE2 was assessed by flow cytometry. Immunocytochemistry assays showed that full-length ACE2 was mainly expressed in sperm midpiece, while short ACE2 was preferentially distributed on the equatorial and post-acrosomal region of the sperm head. To our knowledge, this is the first study demonstrating the expression of protein ACE2 on spermatozoa. Further studies are warranted to determine the role of ACE2 isoforms in male reproduction.
Joint Traffic Routing and Scheduling Algorithm Eliminating the Nondeterministic Interruption for TSN Networks Used in IIoT

Recently, time-sensitive networking (TSN) has been developed to incorporate real-time capabilities to the standard Ethernet for the incompatible issue in existing industrial communication solutions and is considered a promising solution to satisfy the requirements of the Industrial Internet of Things (IIoT). However, the routing and scheduling methods are left out of the TSN standard. This study developed a novel joint traffic routing and scheduling algorithm to compute routes for time-critical flows and construct the schedules. The validity of the proposed algorithm was verified using a random synthetic test scenario. The simulation results demonstrated that the real-time requirements of time-critical traffic could be satisfied with the proposed algorithm. Subsequently, we evaluated the scalability of the proposed algorithm from the perspective of the number of flows that can be scheduled and the network size. The results showed that the computational times for 4000 flows in the realistic industrial network topology and random network topologies (with up to 21 switches and 105 end stations) are at the subsecond level, which indicated the perfect scalability of the proposed algorithm. In addition, compared with the well-known integer linear programming (ILP)-based approach, Degree of Conflict (DoC)-aware iterative routing and scheduling (DA/IRS) approach, and hybrid genetic algorithm (HGA)-based approach, the proposed algorithm is faster than the three approaches by at least an order of magnitude.
Quantitative and qualitative analysis of biosurfactant by oil spreading method

There are three methods to detect biosurfactant production, drop collapse, oil spreading, and blood agar. The method of oil spreading is popular, there is a every strong linear correlation between the diameter of clear zone obtained with the oil spreading, the concentration of biosurfactant and the surface tension of culture, according to one data, the other two data can be calculated from the chart. Using drop spreading method to detect whether the bacterium isolated from high temperature Dagang Oil Field is a biosurfactant producer and to determinate the concentration of the biosurfactant, which provide the oil spreading method is a easy and reliable method of quantitative and qualitative analysis of biosurfactant.
Comparative study between sliding mode control and the vector control of a brushless doubly fed reluctance generator based on wind energy conversion systems

Introduction. Nowadays, global investment in renewable energy sources has been growing intensely. In particular, we mention here that wind source of energy has grown recently. Purpose. Comparative study between sliding mode control and vector control of a brushless doubly fed reluctance generator based on wind energy conversion systems. Methods. This paper deals with conceptual analysis and comparative study of two control techniques of a promising low-cost brushless doubly-fed reluctance generator for variable-speed wind turbine considering maximum power point tracking. This machine's growing interest because of the partially rated power electronics and the high reliability of the brushless design while offering performance competitive to its famous spring counterpart, the doubly-fed induction generator. We are particularly interested in comparing two kinds of control methods. We indicate here the direct vector control based on Proportional-Integral controller and sliding mode controller. Results. Simulation results show the optimized performances of the vector control strategy based on a sliding mode controller. We observe high performances in terms of response time and reference tracking without overshoots through the response characteristics. The decoupling, the stability, and the convergence towards the equilibrium are assured.
Partial Purification of Cholinesterase from Pangasius pangasius using Affinity Chromatography

An affinity chromatography column to purify AChE was developed using procainamide as the ligand coupled with the epoxy activated Sephacryl-S1000 as the modified matrix. From this study, the procainamide matrix was found to be capable of binding acetylcholinesterase (AChE) from the brain of Pangasius pangasius efficiently, with percentage of yield of approximately 51.97% and a purification fold of 7.52. The value for Michaelis-Menten (Km app) was 0.1265 mM and maximal velocity (Vmax app) of the partially purified enzyme was 0.6981 Âµmol/min/mg, with a substrate specificity in the sequence ofâ€” acetylthiocholine iodide (ATC) > propinylcholine iodide (PTC) > butyrylcholine iodide (BTC). This strongly suggest that using this column, AChE can be purified successfully and efficiently. SDS-PAGE indicated a reduced band intensity, indicating that the procainamide-based affinity chromatography column produces acceptable partially purified enzyme adequate for the application in the rapid detection of carbamate and organophosphate (OP) at the large scale.
Red Blood Cell Distribution Width in Heart Failure: Pathophysiology, Prognostic Role, Controversies and Dilemmas

Red blood cell distribution width (RDW), an integral parameter of the complete blood count (CBC), has been traditionally used for the classification of several types of anemia. However, over the last decade RDW has been associated with outcome in patients with several cardiovascular diseases including heart failure. The role of RDW in acute, chronic and advanced heart failure is the focus of the present work. Several pathophysiological mechanisms of RDW’s increase in heart failure have been proposed (i.e., inflammation, oxidative stress, adrenergic stimulation, undernutrition, ineffective erythropoiesis, reduced iron mobilization, etc.); however, the exact mechanism remains unknown. Although high RDW values at admission and discharge have been associated with adverse prognosis in hospitalized heart failure patients, the prognostic role of in-hospital RDW changes (ΔRDW) remains debatable. RDW has been incorporated in recent heart failure prognostic models. Utilizing RDW as a treatment target in heart failure may be a promising area of research.
Understanding Consumers’ Food Waste Reduction Behavior—A Study Based on Extended Norm Activation Theory

Based on norm activation theory, a research framework was built to explore the food waste reduction behavior when consumers eat out. The framework included behavior intentions and four psychological factors: awareness of consequence (persons understanding that actions have consequences), ascription of responsibility (duty to respond), self-efficacy (belief in own skills and capacity), personal norm (individuals’ values to act by socially accepted rules and reduce food waste as a code of conduct and moral obligation). A total of 514 samples from different regions of China were collected through an online survey platform, and the research framework was tested by applying structural equation modeling (SEM). This study found that ascription of responsibility and self-efficacy can effectively activate personal norm to reduce food waste. Personal norm and self-efficacy had a significant positive effect on behavior intentions to reduce food waste. Specifically, self-efficacy had the greatest effect on personal norm, followed by ascription of responsibility, and on behavior intentions to reduce food waste, followed by personal norm. Interestingly, while ascription of responsibility and self-efficacy had an impact on personal norm, awareness of consequence did not significantly influence personal norm to reduce food waste, suggesting that emotional factors are more likely to trigger personal norms that motivate consumers to take action to reduce food waste than cognitive factors. Based on the findings, several suggestions are provided for more effective interventions by restaurants to promote food waste reduction behavior, such as information intervention strategies, displaying information related to food consumption, and reducing the size of plates for some meals.
An evaluation of the psychometric properties of the Fear of COVID-19 Scale in a sample of help-seeking men

Aim: The Fear of COVID-19 Scale is a widely used measurement tool for related anxieties, however previous studies validating the scale report varying fit indices, often below accepted cut-off points. This suggests re-specification of the scale may be required. The present study aimed to examine the psychometric properties of the English-version of the Fear of COVID-19 Scale in a population of help-seeking males using exploratory (EFA) and confirmatory factor analysis (CFA). Material and methods: Data from 621 males aged 18-80 years (mean=38.23, SD=13.59) was collected via a cross-sectional open online survey. Along with the 7-item Fear of COVID-19 Scale, the PHQ-4 and PROMIS Anger Short Form were used to measure probable anxiety, depression and anger. Data were randomly partitioned into two subsamples and separate factor analyses were conducted with robust CFA corrections applied for non-normality. Results: A 4-item single-factor version of the scale was identified reporting excellent model fit (R-RMSEA=.033, R-CFI=.998, R-TFI=.997, SRMR=.012) and good internal consistency (α=.86). Age and probable anxiety effects were observed. Discussion: Relative to existing validation studies of the Fear of COVID-19 Scale, the present study provides improved psychometrics of the 4-item version of the scale, while scale means observed were comparable to other studies. Conclusion: This study validates a 4-item version of the Fear of COVID-19 Scale to assess related anxieties in a help seeking male population. Future research should seek to validate the 4-item version in other subpopulations. © 2022 Polish Psychiatric Association. All rights reserved.
Factors Affecting Vehicle Purchase in Major Cities

Nowadays, personal vehicles have become synonymous with the modern city market. The development and splendor of the city can also portray by the use of such vehicles. The purpose of this study was to analyze the factors affecting vehicle buying in major cities. This research used descriptive and causal research design. Primary data were collected. Survey research was administered and 2000 responses were collected. A PLS-SEM tool was used to test validity, reliability and path of advance modeling. This research confirmed expected features, price, dealer/showroom influence has significant influence on car buying. After sales service has no effect on car buying. Marketers should identify target group who showed interest on cars and marketing programs should be directed to them.
The importance of e-service quality in the livestreaming music concert business

Abstract The live music concert business was one of the economic sectors most affected by mandatory quarantine and social restrictions due to COVID-19. The quarantine forced this industry to reinvent itself through digital communication, to be able to continue offering this type of shows, but in a completely virtual way. Taking this into account, this research analyses the adaptation of the live music concert business through e-service quality management in digital communication, and how the consumer of this type of shows responded to this new commercial strategy. Through the PLS a sample of 294 consumers was processed in the city of Bogota, (Colombia), who, once the mandatory quarantine ended, attended some kind of live music concert, but completely in a virtual way. The results allow us to show the positive relationships between study variables, thus demonstrating the emergence of a digital consumer in this sector.
Development of an Automatic Interpretation Algorithm for Uroflowmetry Results: Application of Artificial Intelligence

Purpose To develop an automatic interpretation system for uroflowmetry (UFM) results using machine learning (ML), a form of artificial intelligence (AI). Methods A prospectively collected 1,574 UFM results (1,031 males, 543 females) with voided volume>150 mL was labelled as normal, borderline, or abnormal by 3 urologists. If the 3 experts disagreed, the majority decision was accepted. Abnormality was defined as a condition in which a urologist judges from the UFM results that further evaluation is required and that the patient should visit a urology clinic. To develop the optimal automatic interpretation system, we applied 4 ML algorithms and 2 deep learning (DL) algorithms. ML models were trained with all UFM parameters. DL models were trained to digitally analyze 2-dimensional images of UFM curves. Results The automatic interpretation algorithm achieved a maximum accuracy of 88.9% in males and 90.8% in females when using 6 parameters: voided volume, maximum flow rate, time to maximal flow rate, average flow rate, flow time, and voiding time. In females, the DL models showed a dramatic improvement in accuracy over the other models, reaching 95.4% accuracy in the convolutional neural network model. The performance of the DL models in clinical discrimination was outstanding in both genders, with an area under the curve of up to 0.957 in males and 0.974 in females. Conclusions We developed an automatic interpretation algorithm for UFM results by training AI models using 6 key parameters and the shape of the curve; this algorithm agreed closely with the decisions of urology specialists.
Student Experiences on Emergency Synchronous Online Teaching in Higher Education

This research aims to reveal university students’ experiences, expectations, and suggestions regarding synchronous online teaching. For this purpose, the study was conducted in a qualitative research case study design. The study group of the research consists of 24 university students. The research data were collected using a semi-structured interview form and document review technique. The data obtained through the semi-structured interview form were analysed using the descriptive analysis technique through the MAXQDA qualitative data analysis program. Research findings show that students have problems accessing devices and the internet. Students and instructors are not competent in using technology and do not have pedagogical content knowledge. The findings reveal that students do not open their webcams and are unwilling to attend and participate in classes because the strategies used in the learning-teaching process are not suitable for classroom interaction. Additionally, students could easily cheat in online exams and had some problems about self-regulation skills. In line with these findings, it has been proposed self-regulated learning framework, formative and authentic assessments and the “community of inquiry” framework.