Miracle-dz/UniFAR-FTUs huggingface dataset:
Probiotics and vitamins modulate the cecal microbiota of laying hens submitted to induced molting

Induced molting enables laying hens to relax, restore energy and prolong the laying hen cycle, resolving problems such as poor egg quality and minimizing economic losses caused by rising global feeding costs. However, traditional molting methods may disrupt gut microflora and promote potential pathogens infections. This study used a customized additive with a mixture of probiotics and vitamins to induce molting and examine the cecal microbiota post molting. A total of two hundred 377 day-of-ISA Brown laying hens were randomly assigned to four groups: non-molt with basal diet (C), 12-day feeding restriction (FR) in earlier-molting (B), feed again to 27.12% egg production in middle-molting (A) and reach second peak of egg production over 81.36% in post-molting (D). Sequencing 16S rRNA to analyze cecal microbial composition revealed that there is no significant change in bacterial community abundance post-molting. In contrast to group C, the number of potentially harmful bacteria such as E. coli and Enterococcus was not found to increase in groups B, A, or D. This additive keeps cecal microbiota diversity and community richness steady. In cecal contents, hens in group B had lower Lactobacillus, Lachnospiraceae and Prevotellaceae (vsC, A, and D), no significant differences were found between post-molting and the non-molting. Furthermore, cecal microbiota and other chemicals (antibodies, hormones, and enzymes, etc.) strongly affect immunological function and health. Most biochemical indicators are significantly positively correlated with Prevotellaceae, Ruminococcaceae and Subdoligranulum, while negatively with Phascolarctobacterium and Desulfovibrio. In conclusion, the additive of probiotics and vitamins improved the cecal microbiota composition, no increase in the associated pathogenic microbial community due to traditional molting methods, and enhances hepatic lipid metabolism and adaptive immunological function, supporting their application and induced molting technology in the poultry breeding industry.
RNAi-mediated gene silencing of Phlebotomus papatasi defensins favors Leishmania major infection

Introduction: Production of different antimicrobial peptides (AMPs) is one of the insect’s prominent defense strategies, regulated mainly by Toll and immune deficiency (IMD) humoral pathways. Here we focused mainly on two AMPs of Phlebotomus papatasi, vector of Leishmania major parasites, their association with the relish transcription factor and the effective participation on Leishmania infection. Methods and results: We further characterized the role of previously described gut-specific P. papatasi defensin (PpDef1) and identified the second defensin (PpDef2) expressed in various sand fly tissues. Using the RNAi-mediated gene silencing, we report that the silencing of PpDef1 gene or simultaneous silencing of both defensin genes (PpDef1 and PpDef2) resulted in increased parasite levels in the sand fly (detectable by PCR) and higher sand fly mortality. In addition, we knocked down relish, the sole transcription factor of the IMD pathway, to evaluate the association of the IMD pathway with AMPs expression in P. papatasi. We demonstrated that the relish gene knockdown reduced the expression of PpDef2 and attacin, another AMP abundantly expressed in the sand fly body. Conclusions: Altogether, our experiments show the importance of defensins in the sand fly response toward L. major and the role of the IMD pathway in regulating AMPs in P. papatasi.
Influence of game features on attention in adults

Introduction The incorporation of game features into cognitive tasks can inform us about the influence of reward and motivation on attention. Continuous performance tasks (CPTs), designed to assess attention abilities, are examples of cognitive tasks that have been targeted for the addition of game features. However, previous results have been mixed regarding how game elements affect attention abilities and task performance. Methods Here, we studied if there were factors that predict which individuals exhibit changes in attention from game features added to a CPT. Participants (N = 94, aged 21–71) played a traditional CPT and a game CPT with identical mechanics, but featured engaging game elements (aesthetics, storyline, competition, feedback, and reward). Results We first found corroborating evidence that game features have mixed effects on attention performance: most attention metrics of interest exhibited no overall difference between the traditional and game CPT, while game elements reduced performance for a few metrics. Importantly, we also found that specific behavioral and demographic profiles predicted individual differences in performance on the game CPT compared to the traditional CPT. Those with more attention difficulties (ADHD symptoms), more reward responsiveness, and younger adults performed better on the game CPT while, conversely, those with fewer ADHD symptoms, less reward responsiveness, and older adults performed better on the traditional CPT. Discussion These findings provide insights into how game features can influence attention in different individuals and have important implications for the use of game elements in cognitive tasks and training interventions.
Intervention with EMDR on a sample of healthcare workers in the nephrology and dialysis service during the COVID-19 emergency: from immediate treatment effect to long-term maintenance

Background During the COVID-19 pandemic, psychological support was provided to healthcare workers in Nephrology and Dialysis Operative Unit of the Azienda Ospedaliera Bassini using an EMDR group protocol to decrease posttraumatic stress symptoms in the medium and long term. The aim of this study was to demonstrate the effectiveness of EMDR treatment to reduce post-traumatic stress symptoms at the end of the first pandemic wave and its progress over time in the subsequent phases of the health emergency. Methods The sample of study consisted of 43 healthcare workers from the Nephrology and Dialysis Service who spontaneously decided to take part in the Brief EMDR treatment. Statistical analyses were carried out to compare the data collected with the IES-R, the Emotion Thermometer and the Post-Traumatic Growth Scale. The comparisons covered pre-treatment, post-treatment and follow-up. Results The results show a significant clinical improvement in reducing PTSD symptoms following the Brief EMDR group treatment. The comparison between PRE and POST treatment (DELTA1) regarding the scores from IES-R and Emotion Thermometer, highlighted the important statistically change that occurred in terms of symptomatology reduction (p < 0.001). By comparing POST and FU (DELTA2), it was observed that all variables except avoidance show a significant weakening of the effect with time (p < 0.001), but the magnitude of this effect is much smaller than the improvement found in DELTA1. DELTA 3 analysis finally made it possible to highlight how the treatment effect is maintained almost intact at follow-up. In fact, the maintenance of a better situation at follow-up was observed, in the course of re-traumatization linked to the new wave, compared to the initial data (p < 0.001). Conclusion The COVID-19 health emergency has significantly impacted hospital healthcare workers, leading to a high risk of developing PTSD symptoms. A psychological intervention aimed at the operators themselves is therefore of great importance.
Influence of exercise type and duration on cardiorespiratory fitness and muscular strength in post-menopausal women: a systematic review and meta-analysis

Background and aim Both cardiorespiratory fitness (CRF) and muscular strength are reported to decrease with age and menopause, which considered to be risk for cardiovascular diseases (CVDs). Previous relevant meta-analyses are inconclusive on the beneficial effects of exercise, particularly in post-menopausal women. In this systematic review and meta-analysis, we investigated the effects of exercise modalities on CRF and muscular strength in post-menopausal women, and identified the effective exercise type and duration. Methods A comprehensive search was conducted on PubMed, Web of Science, CINAHL, and Medline to identify the randomized controlled trials, which evaluated exercise effect on CRF, lower- and upper-body muscular strength, and/or handgrip strength in post-menopausal women and compared the results with control. Standardized mean differences (SMD), weighted mean differences (WMD), and 95% confidence intervals (95% CIs) were calculated using random effects models. Results A total of 129 studies comprising 7,141 post-menopausal women with mean age and BMI ranging from ∼53 to 90 years and 22 to 35 kg/m2, respectively, were included in the meta-analysis. Overall, exercise training effectively increased CRF (SMD: 1.15; 95% CI: 0.87, 1.42; p = 0.001), lower-body muscular strength (SMD: 1.06; 95% CI: 0.90, 1.22; p = 0.001), upper-body muscular strength (SMD: 1.11; 95% CI: 0.91, 1.31; p = 0.001), and handgrip strength (WMD: 1.78 kg; 95% CI: 1.24, 2.32; p = 0.001) in post-menopausal women. These increments were found to be irrespective of ages and intervention durations. Regarding exercise type, aerobic, resistance, and combined training significantly increased CRF and lower-body muscular strength, while resistance and combined training effectively increased handgrip strength. However, only resistance training increased the upper-body muscular strength in women. Conclusion Our findings suggest that exercise training is effective in increasing CRF and muscular strength in post-menopausal women, which might be cardioprotective. Both aerobic and resistance training alone or in combination increased CRF and lower-body muscular strength, but only resistance training increased upper-body strength in women. Systematic Review Registration https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=283425, identifier: CRD42021283425.
The effects of sucrose and arsenic on muscular insulin signaling pathways differ between the gastrocnemius and quadriceps muscles

Introduction Insulin resistance in muscle can originate from a sedentary lifestyle, hypercaloric diets, or exposure to endocrine-disrupting pollutants such as arsenic. In skeletal muscle, insulin stimulates glucose uptake by translocating GLUT4 to the sarcolemma. This study aimed to evaluate the alterations induced by sucrose and arsenic exposure in vivo on the pathways involved in insulinstimulated GLUT4 translocation in the quadriceps and gastrocnemius muscles. Methods Male Wistar rats were treated with 20% sucrose (S), 50 ppm sodium arsenite (A), or both (A+S) in drinking water for 8 weeks. We conducted an intraperitoneal insulin tolerance (ITT) test on the seventh week of treatment. The quadriceps and gastrocnemius muscles were obtained after overnight fasting or 30 min after intraperitoneal insulin injection. We assessed changes in GLUT4 translocation to the sarcolemma by cell fractionation and abundance of the proteins involved in GLUT4 translocation by Western blot. Results Male rats consuming S and A+S gained more weight than control and Atreated animals. Rats consuming S, A, and A+S developed insulin resistance assessed through ITT. Neither treatments nor insulin stimulation in the quadriceps produced changes in GLUT4 levels in the sarcolemma and Akt phosphorylation. Conversely, A and A+S decreased protein expression of Tether containing UBX domain for GLUT4 (TUG), and A alone increased calpain-10 expression. All treatments reduced this muscle’s protein levels of VAMP2. Conversely, S and A treatment increased basal GLUT4 levels in the sarcolemma of the gastrocnemius, while all treatments inhibited insulin-induced GLUT4 translocation. These effects correlated with lower basal levels of TUG and impaired insulin-stimulated TUG proteolysis. Moreover, animals treated with S had reduced calpain-10 protein levels in this muscle, while A and A+S inhibited insulin-induced Akt phosphorylation. Conclusion Arsenic and sucrose induce systemic insulin resistance due to defects in GLUT4 translocation induced by insulin. These defects depend on which muscle is being analyzed, in the quadriceps there were defects in GLUT4 retention and docking while in the gastrocnemius the Akt pathway was impacted by arsenic and the proteolytic pathway was impaired by arsenic and sucrose. Graphical Abstract Male Wistar rats consuming 20% sucrose and 50 mg/L sodium arsenite for 8 weeks developed systemic insulin resistance. In quadriceps muscles, the main alterations were low expression of TUG after arsenite treatment and low expression of VAMP2 induced by all treatments. In gastrocnemius, all treatments reduced insulin-stimulated GLUT4 translocation by different pathways. Arsenite impaired Akt phosphorylation and TUG proteolysis, while sucrose inhibited TUG proteolysis and capn10 expression. Created with BioRender.com
The role of the anatomical back-projections

IF P HYSICS WAS the science of the first half of the 20th century, biology was certainly the science of the second half. Neuroscience is now often cited as one of the key scientific focuses of the 21st century and has indeed grown rapidly in recent years, spanning a range of approaches, from molecular neurobiology to neuro-informatics and computational neuroscience. Computer science gave biology powerful new dataanalysis tools that yielded bioinformatics and genomics, making possible the sequencing of the human genome. Similarly, computer science techniques are at the heart of brain imaging and other branches of neuroscience. Computers are critical for the neurosciences, though at a much deeper level, representing the best metaphor for the central mystery of how the brain produces intelligent behavior and intelligence itself. They also provide experimental tools for information processing, effectively testing theories of the brain, particularly those involving aspects of intelligence (such as sensory perception). The contribution of computer science to neuroscience happens at multiple levels and is well recognized. Perhaps less obvious is that neuroscience is beginning to contribute powerful new ideas and approaches to artificial intelligence and computer science as well. Modern computational neuroscience models are no longer toy models but quantitatively detailed while beginning to compete with state-of-the-art computervision systems. Here, we explore how computational neuroscience could become a major source of new ideas and approaches in artificial intelligence. Understanding the processing of information in our cortex is a significant part of understanding how the brain works and understanding intelligence itself. For example, vision is one of our most developed senses. Primates easily categorize images or parts of images, as in, say, an office scene or a face within a scene, identifying specific objects. Our visual capabilities are exceptional, and, despite decades of engineering, no computer algorithm is yet able to match the performance of the primate visual system. Our visual cortex may serve as a proxy for the rest of the cortex and thus DOI:10.1145/1831407.1831425
Mathematics and the Understanding of Economic Concepts

This article is prompted by a perplexing finding and its interpretation in an article in the first issue of this Journal by Paden and Moyer, "The Relative Effectiveness of Three Methods of Teaching Principles of Economics" [6]. It does not reflect on the authors' main conclusions regarding differential effects of three teaching methods on economic understandings, but rather comments on a peripheral conclusion about the contribution of mathematics to learning economic concepts. In examining the regression coefficients in their study, Paden and Moyer observe "On both the TEU (Test of Economic Understanding) and the measure of improvement, Table 1 shows that students who completed six or more semesters of college mathematics did less well than students who had either from three to six semesters or zero to three semesters of mathematics. The inference to be drawn from the figures is that the more mathematics a student takes in college the less well he does in economics" [6, p. 38]. The twofold purpose of this article is:
The Influence of Prices, Advertising Attractiveness, Celebrity Endorsers, and Dissatisfaction with Brand Switching on Smartphone Consumers in Mataram City, Indonesia

This research aims to determine the influence of price, advertising attractiveness, celebrity endorsers, and consumer dissatisfaction with brand switching. The population of this study is people who live in the city of Mataram, Indonesia. This research recruits one hundred respondents using the purposive sampling technique. Due to the relatively small number of samples, this study considered analysis using SEM Analysis with the help of the Smart-PLS Program. The results showed a positive and significant influence of all independent variables: price, advertising attractiveness, celebrity endorser, and consumer dissatisfaction on brand switching. The results of this study can be a reference and consideration for companies in determining prices. In marketing smartphone products, companies must also carefully choose the correct public figure to become a brand ambassador because a figure's good image indirectly increases customer trust. The right public figure must also be supported by advertising that is easily remembered and memorable for customers.
Numerical Simulation of Cloud Seeding Experiments in Selected Australian Areas.

Abstract Using actual rainfall records for selected areas, one can by computer simulation apply hypothetical seeding effects and then compare the results obtained and inferences drawn by individual “experimenters” who have superimposed the effects of seeding on the natural variations of rainfall in space and in time. In this way it is possible to infer which kinds of experimental design are preferable and the duration of experiment likely to give meaningful results in a given area for some prescribed increase by seeding. Some results for three different Australian areas are given. These show a marked superiority of the crossover design as compared with target-control or single-area experiments. They also suggest that in more favorable areas a meaningful result could be obtained with a four- to eight-year experiment when the average increase due to seeding was 10%, but in the less favorable (arid) areas even a 16-year experiment would not be long enough. An average 20% increase would, however, be detectabl.
Highspeed laser ablation cutting of metal

In laser ablation cutting, irradiation of high-intense laser beams causes ejection of molten and evaporated material out of the cutting zone as a result of high pressure gradients, induced by expanding plasma plumes. This paper investigates highspeed laser ablation cutting of industrial grade metal sheets using high-brilliant continuous wave fiber lasers with output powers up to 5 kW. The laser beam was deflected with scan speeds up to 2700 m/min utilizing both a fast galvanometer scan system and a polygon scan system. By sharp laser beam focusing using different objectives with focal lengths ranging between 160 mm and 500 mm, small laser spot diameters between 16.5 μm and 60 μm were obtained, respectively. As a result high peak intensities between 3*108 W/cm² and 2.5*109 W/cm² were irradiated on the sample surface, and cutting kerfs with a maximum depth of 1.4 mm have been produced. In this study the impact of the processing parameters laser power, laser spot diameter, cutting speed, and number of scans on both the achievable cutting depth and the cutting edge quality was investigated. The ablation depths, the heights of the cutting burr, as well as the removed material volumes were evaluated by means of optical microscope images and cross section photographs. Finally highspeed laser ablation cutting was studied using an intensified ultra highspeed camera in order to get useful insights into the cutting process.
The Effect of Education on Happiness, Self-Acceptance, and Family Harmony (Empirical Evidence from Indonesia)

Education plays a crucial role in determining the quality of life through economic returns and subjective well-being. However, almost no previous research has examined how education affects subjective well-being indicators beyond happiness. To address this gap, this study used Ordinary Least Squares and the Ordered Probit technique to investigate the effect of education on happiness, self-acceptance, and family harmony. Using the recent microdata from Statistics Indonesia in 2021 the empirical results reveal that education positively affects happiness, self-acceptance, and family harmony. The effect of education remained statistically significant even after incorporating socioeconomic and individual characteristics such as income, gender, age, marital status, home ownership, household size, area classification, health status, and leisure time. The result of this study highlights that individuals with higher levels of education reported higher happiness, greater self-acceptance, and higher satisfaction with family harmony than those with lower levels of education. Although more than half of the magnitude of the education effect decreases after incorporating socioeconomic and individual characteristics variables, the direct effect of education remained significant on happiness, self-acceptance, and family harmony.
Computational Chemistry Programs as a Facilitating Tool in the Teaching and learning Process

1 Laboratory of Chemistry, State University of Amapa, Av. Presidente Vargas, 650, Campus I, 68900070, Macapa, Amapa, Brazil. Laboratory of Modeling and Computational Chemistry, Federal University of Amapa, Rod JK Km 2, 68902-280, Macapa, Amapa, Brazil. Education Center in Science, Engineering and Mathematics, State University of Amapa, Av. Presidente Vargas, 650, Campus I, 68900-070, Macapa, Amapa, Brazil.
Estimating the Local False Discovery Rate via a Bootstrap Solution to the Reference Class Problem: Application to Genetic Association Data

Modern scientific technology such as microarrays, imaging devices, genome-wide association studies or social science surveys provide statisticians with hundreds or even thousands of tests to consider simultaneously. Testing many thousands of null hypotheses may increase the number of Type I errors. In large-scale hypothesis testing, researchers can use different statistical techniques such as family-wise error rates, false discovery rates, permutation methods, local false discovery rate, where all available data usually should be analyzed together. In applications, the thousands of tests are related by a scientifically meaningful structure. Ignoring that structure can be misleading as it may increase the number of false positives and false negatives. As an example, in genome-wide association studies each test corresponds to a specific genetic marker. In such a case, the scientific structure for each genetic marker can be its minor allele frequency. In this research, the local false discovery rate as a relevant statistical approach is considered to analyze the thousands of tests together. We present a model for multiple hypothesis testing when the scientific structure of each test is incorporated as a covariate. The purpose of this model is to incorporate the co-variate to improve the performance of testing procedures. The method we consider has different estimates depending on the tuning parameter. We would like to estimate the optimal value of that parameter by considering observed statistics. Thus, among those estimators, the one which minimizes the estimated errors due to bias and to variance is chosen by