Miracle-dz/UniFAR-FTUs huggingface dataset:
The Implications in Meat Quality and Nutrition by Comparing the Metabolites of Pectoral Muscle between Adult Indigenous Chickens and Commercial Laying Hens

Aged chickens are often a secondary dietary choice, owing to the poor organoleptic qualities of their meat. With regard to the meat quality of chickens, the metabolic profiles of pectoral muscle in Guangyuan grey chickens (group G) and Hy-Line grey hens (group H) aged 55 weeks were compared via ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). A total of 74 metabolites were identified with differential changes in the ion model. Lipids and lipid-like molecules comprised the largest proportion among the different metabolites. The content of myristic acid and palmitic acid were found to be higher in the pectoral muscle of group G, while group H showed significantly higher levels of glycerophospholipid molecules, such as LPC(18:2/0:0), Pi(38:5), Pc(16:0/16:0), and Pe(16:1e/14-hdohe). KEGG pathway analysis indicated that the abundant metabolites in group G were mainly involved in energy metabolism and fatty acid biosynthesis and metabolism, whereas those of group H were mainly attributed to the metabolism of unsaturated fatty acids and amino acids. Overall, the differences in lipid and amino acid metabolism in pectoral muscle appear to be responsible for the difference in meat quality between indigenous chickens and commercial laying hens.
Trends in child and adolescent psychiatric diagnoses in a Romanian Inpatient Unit between 1990 and 2014

Objective. This paper aims to describe trends in diagnostic data in discharged patients from a regional child and adolescent psychiatric inpatient unit in Romania, over a 25-year period (1990-2014). Method. Data on discharge diagnosis of the 30854 patients from the study timeframe were analyzed. Diagnostic formulations in the years prior to ICD implementation were converted into ICD-10 specific disorders/ class of disorders. Results. Results showed a significant increase in proportion of autism spectrum disorders and hyperkinetic disorders over time and a significant decrease of stress related, dissociative and somatoform disorders. The number of psychotic disorders was constant over time, mood disorders had peak frequencies in 2003 and 2014 and anxiety disorders has a twofold increase from 2007 to 2014. Conclusions. This study demonstrates a major shift in the patterns of mental health disorders diagnosed among children and adolescents at our clinic over the last 25 years. Defining the current mental health needs of young people and adjusting service delivery in child and adolescent psychiatric settings have become of great importance in recent years.
Corrigendum: Calculating lattice thermal conductivity: a synopsis (2018 Phys. Scr. 93 043002)

visually comparing the bottom panel of the published version of ﬁ gure 13 with the corresponding bottom panel of the same ﬁ gure in the present corrigendum it is apparent that a graphical error occurred, whereby only the present version of the ﬁ gure correctly reports the temperature pro ﬁ le ( corresponding to the blue line in ( c )) found in the stationary state of thermal conduction consistent with the assigned boundary conditions. We remark that ﬁ gure 13 ( c ) is not the output of any calculation, but just represents the graphical conceptualization of a given ther-modynamical situation. We ﬁ nally state that the scien-ti ﬁ c content discussed in the paper is not affected by this graphical error.
A spotlight on bias in the growth mindset intervention literature: A reply to commentaries that contextualize the discussion (Oyserman, 2023; Yan & Schuetze, 2023) and illustrate the conclusion (Tipton et al., 2023).

Two meta-analyses examined the effects of growth mindset interventions. Burnette et al. (2023) tested two moderators and found that effects ranged from negative to positive. We (Macnamara & Burgoyne, 2023) tested 11 preregistered moderators and examined the evidence according to a well-de ﬁ ned set of best practices. We found major areas of concern in the growth mindset intervention literature. For instance, 94% of growth mindsetinterventionsincludedconfounds, authorswith aknown ﬁ nancialincentivewere twoand a half times as likely to report positive effects, and higher quality studies were less likely to demonstrate a bene ﬁ t. Yan and Schuetze (2023) contextualized these ﬁ ndings by describing problems with mindset theory and its measurement. Likewise, Oyserman (2023) discussed how growth mindset is a culturally ﬂ uent idea; papers supportive of growth mindset are widely embraced, whereas papers taking a skeptical approach are challenged.Inanothercommentary, Tiptonetal. (2023)challengedourresults,claimingtoproducepositive effects byreanalyzingourdata setusingBurnetteet al. ’ s (2023)approach.However,inadditiontochanging the approach, Tipton et al. changed effect sizes, how moderators were coded, and which studies were included, often without explanation. Though we appreciate the discussion of multiple meta-analytic approaches, we contend that meta-analytic decisions should be a priori, transparently reported, and consistently applied. Tipton et al. ’ s analysis illustrated our (Macnamara & Burgoyne ’ s, 2023) conclusion: Apparent effects of growth mindset interventions on academic achievement may be attributable to inadequate study design, reporting ﬂ aws, and bias.
MicroRNAs in Juvenile Idiopathic Arthritis: State of the Art and Future Perspectives

Simple Summary Juvenile Idiopathic Arthritis (JIA) is a chronic pediatric arthritis and an important cause of children’s disabilities. Despite major therapeutic advancements achieved in the last decades, the lack of diagnostic and predictive biomarkers still hinders JIA patients’ clinical management. MicroRNAs (miRNAs) are small nucleic acids whose role in many pathologies has been demonstrated. In particular, miRNAs circulating in patient body fluids represent potential new disease biomarkers. Although more extensively investigated in adult arthritis, the expression and roles of miRNAs have also been studied in JIA. Here, we review the most relevant studies analyzing the expression of miRNAs in patients affected by JIA and evaluate their potential as biomarkers, highlighting the limitations currently affecting miRNA investigation. Abstract Juvenile Idiopathic Arthritis (JIA) represents the most common chronic pediatric arthritis in Western countries and a leading cause of disability in children. Despite recent clinical achievements, patient management is still hindered by a lack of diagnostic/prognostic biomarkers and targeted treatment protocols. MicroRNAs (miRNAs) are short non-coding RNAs playing a key role in gene regulation, and their involvement in many pathologies has been widely reported in the literature. In recent decades, miRNA’s contribution to the regulation of the immune system and the pathogenesis of autoimmune diseases has been demonstrated. Furthermore, miRNAs isolated from patients’ biological samples are currently under investigation for their potential as novel biomarkers. This review aims to provide an overview of the state of the art on miRNA investigation in JIA. The literature addressing the expression of miRNAs in different types of biological samples isolated from JIA patients was reviewed, focusing in particular on their potential application as diagnostic/prognostic biomarkers. The role of miRNAs in the regulation of immune responses in affected joints will also be discussed along with their potential utility as markers of patients’ responses to therapeutic approaches. This information will be of value to investigators in the field of pediatric rheumatology, encouraging further research to increase our knowledge of miRNAs’ potential for future clinical applications in JIA.
Regional Ionospheric VTEC Estimation Applied by Spherical Cap Harmonic Analysis and Kalman Filter

In this paper, the regional ionospheric VTEC models for GNSS (Global Navigation Satellite System) positioning in the local area like as Japan are investigated. The ionosphere is modeled based on VTEC (Vertical Total Electron Content) estimation methods. In order to model regional VTEC distribution from regional data, GEONET (Gnss Earth Observation NETwork) data are used and obtained from the GSI (Geospatial Information Authority of Japan). In our previous research, Least Squares method has been applied. In this paper, we propose the method by applying Kalman Filter. In the experiments, the ionospheric VTEC is modeled by the previous and proposed methods.
Fast imbalanced binary classification: a moment-based approach

In this paper, we consider the problem of imbalanced binary classification in which the number of negative examples is much larger than the number of positive examples. The two mainstream methods to deal with such problems are to assign different weights to negative and positive points or to subsample points from the negative class. In this paper, we propose a different approach: we represent the negative class by the two first moments of its probability distribution (the mean and the covariance), while still modeling the positive class by individual examples. Therefore, our formulation does not depend on the number of negative examples, making it suitable to highly imbalanced problems and scalable to large datasets. We demonstrate empirically, on a protein classification task and a text classification task, that our approach achieves similar statistical performance than the two mainstream approaches to imbalanced classification problems, while being more computationally efficient.
Effect of e-banking practices in the banking sector of Bangladesh-customers' perception

In the present study, the quality of E-Banking is reviewed with short- and long-term effect on the perception of bank consumers. The Opinion of 400 banker and customer was collected by survey questionnaire method in the month of June-July, 2022 on a five-point Likert scale. The response variables are classified as E-Banking quality, E-Banking short term effect, and E-Banking long term effect by factor analysis and reliability test. Based on the above classification structural equation model (SEM) is developed with demographic variables. The findings indicate that as the quality of electronic banking rises, potential short-term effects may also rise noticeably. Also, with the increase of E-Banking quality long term effect may increases significantly. The bankers observed that the quality of E-Banking is good, but the customer identifies the quality of E-Banking is not sufficient. E-banking is still in its infancy and is being expanded in new directions. In order to ensure optimum customer satisfaction, it must be addressed and new options for the consumer must be created, which calls for ongoing research. The banking authority may take the required steps to improve the quality of e-banking, which will have an impact on both the short- and long-term consequences of e-banking and will therefore continue in Bangladesh.
Design of FSS radome using binary particle swarm algorithm combined with pixel-overlap technique

Abstract An optimization method for designing frequency selective surface (FSS) radome using binary particle swarm optimization (BPSO) algorithm combined with pixel-overlap technique is proposed, in this paper. The proposed method takes the connectivity condition of adjacent conductors within FSS element into consideration. With the help of pixel-overlap technique, lattice points in FSS element are avoided by overlapping adjacent conductors, which improves the manufacturability of the FSS layers. Also, structure parameters of the FSS radome can be obtained according to the desired frequency selective property using the BPSO algorithm. To verify the validity of the proposed method, a sandwich-structured FSS radome is designed, fabricated, and measured. Good agreements between the simulation and measurement results can be observed, which demonstrate that the proposed method can be applied to design FSS radome.
The effects of hesperidin supplementation on cardiovascular risk factors in adults: a systematic review and dose–response meta-analysis

Hesperidin is a naturally occurring bioactive compound that may have an impact on cardiovascular disease risks, but the evidence is not conclusive. To investigate further, this study aimed to explore the effects of hesperidin supplementation on cardiovascular risk factors in adults. A comprehensive search was conducted up to August 2022 using relevant keywords in databases such as Scopus, PubMed, Embase, Cochrane Library, and ISI Web of Science for all randomized controlled trials (RCTs). The results showed that hesperidin supplementation had a significant effect on reducing serum triglyceride (TG), total cholesterol (TC), low-density cholesterol (LDL), tumor necrosis factor-alpha (TNF-α), and systolic blood pressure (SBP), whereas weight was increased. However, no significant effect was observed on high-density cholesterol (HDL), waist circumference (WC), fasting blood glucose (FBG), insulin, homeostatic model assessment for insulin resistance (HOMA-IR), C-reactive protein (CRP), interleukin-6 (IL-6), body mass index (BMI), and diastolic blood pressure (DBP). The study also found that an effective dosage of hesperidin supplementation was around 1,000 mg/d, and a more effective duration of supplementation was more than eight weeks to decrease insulin levels. Furthermore, the duration of intervention of more than six weeks was effective in decreasing FBG levels.
The Extent of Medication Errors During Hajj in the Kingdom of Saudi Arabia

Background Medication errors are frequently identified in healthcare institutions and pose a risk to patients. The mass gathering during Hajj may expose the pilgrims to numerous health risks. No study has reported the extent of medication errors during Hajj in Saudi Arabia. We investigated the rate, nature, reporting, severity, and causes of medication errors in Hajj pilgrims. Methodology A retrospective analysis of medication errors reported by healthcare professionals was conducted from July 5, 2022, to July 15, 2022, at Mina Al Wadi Hospital, Saudi Arabia. This study included all medication error report forms collected during the Hajj season. The National Coordinating Council for Medication Error Reporting and Prevention Index was used to classify the severity of medication errors. Results There were reports of 43 medication errors in 3,210 prescriptions. The medication error incidence rate was 1.5% (43/3,210). The highest proportion of medication errors (83.72%, 95% confidence interval (CI) = 72.69-94.75) occurred during the prescribing phase, and 97% (95% CI = 93.16-100.0) of medication errors were classified as near misses. Wrong drugs (23.25%) and frequency (18.60%) were responsible for nearly half of the medication errors. Lack of drug information was the leading cause of reported medication errors (58.14%), followed by environmental, personnel, and workload issues (23.25%), and look-alike/sound-alike medication issues (18.60%). Conclusions This study found that the incidence of medication errors was consistent with the global standard, and many of them did not reach pilgrims and were preventable. This highlights the importance of targeted interventions. Incorrect medication was the common type of medication error, highlighting a crucial area for intervention and improvement. Lack of drug information was the primary underlying factor in the occurrence of medication errors. Pharmacists were more likely than other healthcare professionals to report medication errors, highlighting the importance of their involvement in improving medication safety among pilgrims. Future research needs to focus on examining the effectiveness of interventions (e.g., provision of education regarding medicines and medication review) in reducing medicine-related events during Hajj.
Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data

In a traditional Gaussian graphical model, data homogeneity is routinely assumed with no extra variables affecting the conditional independence. In modern genomic datasets, there is an abundance of auxiliary information, which often gets under-utilized in determining the joint dependency structure. In this article, we consider a Bayesian approach to model undirected graphs underlying heterogeneous multivariate observations with additional assistance from covariates. Building on product partition models, we propose a novel covariate-dependent Gaussian graphical model that allows graphs to vary with covariates so that observations whose covariates are similar share a similar undirected graph. To efficiently embed Gaussian graphical models into our proposed framework, we explore both Gaussian likelihood and pseudo-likelihood functions. For Gaussian likelihood, a G-Wishart distribution is used as a natural conjugate prior, and for the pseudo-likelihood, a product of Gaussian-conditionals is used. Moreover, the proposed model has large prior support and is flexible to approximate any $\nu$-H\"{o}lder conditional variance-covariance matrices with $\nu\in(0,1]$. We further show that based on the theory of fractional likelihood, the rate of posterior contraction is minimax optimal assuming the true density to be a Gaussian mixture with a known number of components. The efficacy of the approach is demonstrated via simulation studies and an analysis of a protein network for a breast cancer dataset assisted by mRNA gene expression as covariates.
Thiol–Disulfide Exchange Coordinates the Release of Nitric Oxide and Dexamethasone for Synergistic Regulation of Intestinal Microenvironment in Colitis

The cell-specific functions of nitric oxide (NO) in the intestinal microenvironment orchestrate its therapeutic effects in ulcerative colitis. While most biomaterials show promise by eliciting the characteristics of NO, the insufficient storage, burst release, and pro-inflammatory side effects of NO remain as challenges. Herein, we report the development of thiol–disulfide hybrid mesoporous organosilica nanoparticles (MONs) that improve the storage and sustained release of NO, broadening the therapeutic window of NO-based therapy against colitis. The tailored NO-storing nanomaterials coordinated the release of NO and the immunoregulator dexamethasone (Dex) in the intestinal microenvironment, specifically integrating the alleviation of oxidative stress in enterocytes and the reversal of NO-exacerbated macrophage activation. Mechanistically, such a synchronous operation was achieved by a self-motivated process wherein the thiyl radicals produced by NO release cleaved the disulfide bonds to degrade the matrix and release Dex via thiol–disulfide exchange. Specifically, the MON-mediated combination of NO and Dex greatly ameliorated intractable colitis compared with 5-aminosalicylic acid, even after delayed treatment. Together, our results reveal a key contribution of synergistic modulation of the intestinal microenvironment in NO-based colitis therapy and introduce thiol–disulfide hybrid nanotherapeutics for the management of inflammatory diseases and cancer.
Intrinsic difficulties in using the doubly-infinite time axis for input-output systems theory

We point out that the natural definitions of stability and causality in input-output control theory lead to certain inconsistencies when inputs and outputs are allowed to have support on the doubly-infinite time-axis. In particular, systems with right half plane poles cannot be considered to be both causal and stabilizable. In contrast, there is no such conflict when the semi-infinite time axis is used. <<ETX>>
A systematic exploratory review investigating the relationship between working memory and emotion regulation: implications for working memory training

Working memory training (WM-T), as an intervention strategy to improve emotion regulation (ER), has become popular in cognitive psychology. However, it poses many different challenges for researchers, and far-transfer effects on subsequent ER have been debated. This systematic exploratory review investigates how the WM-ER dyad is implicated in WM-T as an intervention strategy for improving ER. Systematic review protocols were followed for the selection of studies investigating the relationship between WM and ER, and WM-T to improve ER. An electronic database search following the PRISMA statement was conducted in which 15 studies were considered eligible. The studies were assessed for quality control using an adapted Critical Appraisal Skills Programme (CASP) tool for quantitative studies. Studies were analysed using the population, variables, and outcomes (PVO) strategy for systematic exploratory reviews. Five studies included psychological disorders and one study used brain imaging. From a neural perspective, the coupling of the prefrontal cortex and the anterior cingulate cortex over the amygdala was involved in the WM-ER dyad. Although there was a lack of evidence of far-transfer effects of WM-T to improve ER, the mechanisms of reward-enhancing effects in WM-T, as well as dopamine release (involved in brain-reward circuitry), should be explored further. This will allow researchers to re-evaluate the direction that the investigation is taking. More concerningly, there is a need for quality control in WM-T studies due to several studies acking sufficient attention to ethical considerations standardisation. Future WM-T studies must ensure that research is founded on quality evidence.
Asset Structure, Dividend Policy, and Sales Growth Influence on Stock Prices

Purpose: This research aims to identify asset structure, dividend policy, and partial sales of stock prices. Theoretical framework: Asset Structure, Dividend Management, and Sales Growth to Improve Stock Prices. This topic has already been the site of several debates in literary circles. Design/methodology/approach: This method involves using a classical assumption, a regressive analysis, and a partial hypothesis. Illustration of the rise of seven automotive industries on the IDX from 2015 to 2019 using the purposive sampling method. Findings: businesses with a growing active structure continue to have higher-than-average stock prices, and dividends have no effect on stock prices. High total dividends distributed by the company do not reflect high or rising stock prices, sales growth reflects the embodiment of investment success in high and rising stock success. Research, Practical & Social implications: We suggest a future research agenda related to being able to suggest a research period and sample so that it is hoped that maximum results will be obtained. To achieve more accurate data processing, you can also use different processes and data learning methods. Originality/value: Previously, researchers discovered fakor that lowered the value of stocks. However, there is a lack of comprehensive information about the impact of this on the price of gold in Indonesia. This strengthens the importance of our research.