Miracle-dz/UniFAR-FTUs huggingface dataset:
Six sigma for gamma-distributed processes: a case study in oil and gas

Purpose The purpose of this paper is to study the relationship between reported sigma levels and actual failure rates (FRs) of gamma-distributed processes. The added complexity of the non-normality behavior of the gamma distribution is analyzed for the case of the cycle time (CT) of a real procurement process from the oil and gas industry. Then, recommendations and guidelines for the application of Six Sigma methodology for the case study are proposed. Design/methodology/approach Sensitivity analysis is conducted to study the relationship between gamma distribution parameters and FRs considering different quality levels. Then, adjustments for implementing Six Sigma programs for gamma processes are proposed. These adjustments consist of first determining the appropriate probability distribution, the standard CT and the due date, followed by setting performance zones and improvement strategies on target gamma parameters that yield the minimal FR. Findings For gamma-distributed processes, simply reporting the sigma level is not sufficient to capture the main characteristics of the process. These characteristics include process FR, mean setting, shape, spread and amount of variation reduction (i.e. improvement effort) required. That is why caution must be exercised when dealing with one-sided non-normal quality characteristics such as CT. Originality/value To the authors’ knowledge, this is the first time that the Six Sigma performance has been evaluated for gamma processes to analyze the link between Six Sigma FRs and gamma distribution parameters leading to the development of a modified Six Sigma methodology for non-normal processes.
Effects of socio-demographic factors on leadership style in Serbian banking industry

The main aim of this paper is to investigate the effects that gender, age, and educational level have on leadership styles, based on the Multifactor Leadership Questionnaire (MLQ) methodology. The sample used in the research comprises 140 managers from the banking sector in Serbia. The research was performed in 2019. The research methodology includes a literature review in the area of leadership and a statistical analysis of the data collected. The regression models were created to investigate the relations between leadership styles and demographic factors of age and educational level of managers. The results of the research pointed that there are positive statistically significant relations between the transformational and transactional leadership styles and level of education, while in the case of age, there are negative relations observed. The authors presented practical and theoretical implications and limitations of the study.
Developing new statistical content knowledge with secondary school mathematics teachers

This paper describes a pilot study exploring the acquisition of new statistical content knowledge by teachers, which is now needed as a result of curriculum change. The teachers involved in the study formed a professional learning community where their learning needs with respect to changes in the statistics curriculum were identified and workshops presented to help meet these needs. In this paper teachers’ understanding of new statistical content knowledge and learning experiences are reported. Initial findings support previous research into how teachers learn and show that new content knowledge is not automatically gained through their participation in professional development.
Twitter Sentiment Analysis and Influence on Stock Performance Using Transfer Entropy and EGARCH Methods

Financial economic research has extensively documented the fact that the impact of the arrival of negative news on stock prices is more intense than that of the arrival of positive news. The authors of the present study followed an innovative approach based on the utilization of two artificial intelligence algorithms to test that asymmetric response effect. Methods: The first algorithm was used to web-scrape the social network Twitter to download the top tweets of the 24 largest market-capitalized publicly traded companies in the world during the last decade. A second algorithm was then used to analyze the contents of the tweets, converting that information into social sentiment indexes and building a time series for each considered company. After comparing the social sentiment indexes’ movements with the daily closing stock price of individual companies using transfer entropy, our estimations confirmed that the intensity of the impact of negative and positive news on the daily stock prices is statistically different, as well as that the intensity with which negative news affects stock prices is greater than that of positive news. The results support the idea of the asymmetric effect that negative sentiment has a greater effect than positive sentiment, and these results were confirmed with the EGARCH model.
Surgical Outcome of Distally Based Peroneus Brevis Flap: A Retrospective Study

Background: This study aimed to evaluate the surgical outcomes of distally based peroneus brevis muscle flap in post-traumatic lower leg defects. Methods: This is a retrospective analysis conducted from February 2017 to May 2019 including six patients who had sustained post-traumatic lower leg critical soft tissue defects and were treated with distally based peroneus brevis muscle flap and primary skin grafting. Results: In five cases, the flap was successful in providing excellent soft tissue cover to the defects addressed. Partial flap loss was seen in one patient. Skin graft partial loss was seen in three of the six patients. There was no significant donor site morbidity. Conclusions: The distally based peroneus brevis muscle flap is a safe, easy, and reliable flap option for coverage of lower leg defects. The muscle flap also thins with time to provide a good aesthetic outcome.
Identification of Key Biomarkers and Immune Infiltration in Liver Tissue after Bariatric Surgery

Background Few drugs are clearly available for nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH); nevertheless, mounting studies have provided sufficient evidence that bariatric surgery is efficient for multiple metabolic diseases, including NAFLD and NASH, while the molecular mechanisms are still poorly understood. Methods The mRNA expression profiling of GSE48452 and GSE83452 were retrieved and obtained from the Gene Expression Omnibus (GEO) database. The limma package was employed for identifying differentially expressed genes (DEGs), followed by clusterProfiler for performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and GSEA software for performing GSEA analyses. The PPI network analyses were constructed using Metascape online analyses. WGCNA was also utilized to identify and verify the hub genes. CIBERSORT tools contributed to the analysis of immune cell infiltration of liver diseases. Results We identify coexpressed differential genes including 10 upregulated and 55 downregulated genes in liver tissue after bariatric surgery. GO and KEGG enrichment analyses indicated that DEGs were remarkably involved in the immune response. GSEA demonstrated that DEGs were markedly enriched in the immune response before surgery, while most were enriched in metabolism after surgery. Seven genes were screened through the MCC algorithm and KME values, including SRGN, CD53, EVI2B, MPEG1, NCKAP1L, LCP1, and TYROBP. The mRNA levels of these genes were verified in the Attie Lab Diabetes Database, and only LCP1 was found to have significant differences and correlation with certain immune cells. Conclusion Our knowledge of the mechanisms by which bariatric surgery benefits the liver and the discovery of LCP1 is expected to serve as potential biomarkers or therapeutic targets for NAFLD and NASH.
Alternative Molecular Tools for the Fight against Infectious Diseases of Small Ruminants: Native Sicilian Sheep Breeds and Maedi-Visna Genetic Susceptibility

Simple Summary Local breeds represent a precious reservoir of genetic diversity, crucial to adapting to environmental and climate changes and reacting to evolving diseases. In Sicily, four native dairy breeds, namely Valle del Belìce, Comisana, Barbaresca, and Pinzirita, have adapted to low-input farming systems and semiarid environments, having an essential role in producing high-quality milk and typical dairy products. Maedi-visna (MV) is one of the most important chronic diseases affecting the sheep sector worldwide, causing production losses. Different target genes play an important role in immunity and in genetic resilience to MV, such as TMEM154, TLR9, MYD88, and CCR5. A major host genetic component to sheep MV susceptibility was identified in the ovine TMEM154 gene. Animals with either of TMEM154 haplotypes that encode glutamate at position 35 (E35) of the protein are at higher risk of MV infection than those homozygous with lysine at position 35 (K35). In the tested Sicilian breeds, animals carrying the allele E35 showed a greater risk of being serologically positive. Comisana, Barbaresca, and Pinzirita breeds showed a good frequency of the protective allele K35, whilst a high frequency of risk allele was found in the Valle del Belìce breed, related to the selection strategies addressed to obtain a productive dairy sheep. Our results highlight the importance of the preservation of autochthonous breeds as a reservoir of natural resistance against infectious disease. Abstract Maedi-visna (MV) is a disease caused by small ruminant lentiviruses. It is included in the list of notifiable terrestrial animal diseases due to economic losses and animal welfare harm in the sheep sector. To date, control programs remain the onliest approach to avoiding infection. The allelic variant p.Glu35Lys (E35K) of the TMEM154 gene has been strongly associated with host vulnerability to MV illness. The present study aimed to investigate the association of TMEM154 E35K allele frequencies with MV susceptibility in native Sicilian sheep breeds. More than 400 animals from 14 local sheep were serologically tested and genotyped for the TMEM154 E35K polymorphism. The local breeds displayed different values of MV seroprevalence, with the lowest antibody prevalence in Barbaresca and Pinzirita breeds. TMEM154 protective allele (K35) was less frequent than the risk allele (E35) in Valle del Belìce breed, whereas the other three breeds showed a more balanced alleles distribution. A positive association between seroprevalence and genotype was found in the entire sample set. The risk of infection resulted in more than 3-fold times as high in sheep with EK and EE genotype compared to the KK genotype. Our data could be helpful in establishing selection breeding programs aimed at reducing MV infection in Sicilian sheep farming and encouraging the breeding of native breeds.
A Novel Mathematical Method to Diagnose the Transverse Growth Deficit of the Nasomaxillary Complex

The diagnosis of transverse growth deficit of the maxilla in daily clinical practice is carried out mainly through the experience of a well-trained clinician, which implies a lack of objective criteria applicable in a protocolized manner. The objective of this study was to establish a mathematical method to diagnose maxillary compression in relation to the dimensions of the skull and mandible. Methods: Records of 97 cases with an overall mean age of 9.8 ± 2.6 years were analyzed by three experienced orthodontists. The group of transverse compression was comprised of 62 cases and the control group of 35 cases. The main measurements of the widths were made on a frontal teleradiography of the skull (cranial, zygomatic, orbital, maxillary, bigonial and biantegonial width) and a lateral teleradiography of the skull (facial axis, mandibular plane, SNA, SNB, ANB and Wits). It was established that from the cranial width it is possible to predict the group to which each subject studied belongs—the compression group or the control group. A mathematical formula was obtained in the form of logistic regression that allows for the diagnosis of the presence of maxillary compression based on the cranial, maxillary and orbital widths with a sensitivity of 88.7% and a specificity of 77.1%.
Relationship between Premature Birth and Asphyxia in Newborn Babies

This study is to see whether relationship between babies born prematurely with the incidence of asphyxia. Premature birth refers to a newborn born alive before the third trimester of pregnancy and weighing less than 2500 grams. Asphyxia can occur immediately after birth because the placenta in the fetus is very important for oxygenation, nutrition, and waste disposal so that disturbances in umbilical and placental blood flow almost always cause asphyxia. Asphyxia is a condition in which newborns cannot breathe regularly and spontaneously. Asphyxia occurs due to the inability of the baby’s respiratory organs to carry out their functions. The data were collected through questionnaire distributed to 20 respondents in Surabaya, Indonesia. The results of this study showed that there is a relationship between babies born prematurely with the incidence of asphyxia. Babies born with a gestational age of less than 37 weeks will experience organ immaturity, especially in the lungs which causes spontaneous breathing failure in the early minutes of birth. The lungs are formed and undergo a gradual maturation process.
Women’s Pathways: Replication and Generalizability Across State Prison Systems

This study demonstrates the replication and validation of a prior model of women’s pathways to prison that was initially developed in California Women’s prisons and subsequently implemented in the Massachusetts Department of Correction (MADOC) women’s prison in 2013. The following four main pathways were identified: (1) Quasi-normal, least disturbed, drug and situational offending; (2) lifelong abused and depressed drug abusing women; (3) socialized subcultural women, with chronic crimes and drug abuse; and (4) abused and aggressive, early onset and multi-need women with severe drugs, crime, and mental health issues. Since 2013, this model has routinely functioned in MADOC women’s prison as an internal classification (IC) for women detainees. Using a newly extracted sample of approximately 1,800 cases from MADOC, several forms of replication and validation were conducted; these demonstrated cross-sample stability, cross-method stability, and stability across time and region. Implications for theory, treatment planning, and implementation are discussed.
On Solutions of Hybrid–Sturm-Liouville–Langevin Equations with Generalized Versions of Caputo Fractional Derivatives

The main intention of this research article is to introduce a new class of generalized fractional differential equations that fall into the categories of Sturm-Liouville’s, Langevin’s, and hybrid’s problems involving Y -Caputo fractional derivatives. The existence of the solutions of the proposed equations is discussed by using the technique of the measure of noncompactness related to the fixed point theorem, which is a generalization of Darbo’s fixed point theorem. Additionally, pertinent examples are provided along with the different values of the function Y to confirm the validity of the reported results.
Tiny‐Crack‐Net: A multiscale feature fusion network with attention mechanisms for segmentation of tiny cracks

Convolutional neural networks (CNNs) have gained growing interest in recent years for their advantages in detecting cracks on concrete bridge components. Class imbalance is a fundamental problem in crack segmentation, resulting in unsatisfactory segmentation for tiny cracks. Besides, limited by the local receptive field, CNNs often cannot integrate local features with global dependencies, thus significantly affecting the detection accuracy of tiny cracks across the entire image. To solve those problems in segmenting tiny cracks, a multiscale feature fusion network with attention mechanisms named “Tiny‐Crack‐Net” (TCN) is proposed. The modified residual network was used to capture the local features of tiny cracks. The dual attention module was then incorporated into the architecture to better separate the tiny cracks from the background. Also, a multiscale fusion operation was implemented to preserve the edge details of tiny cracks. Finally, a joint learning loss of the cross‐entropy and similarity was proposed to alleviate the poor convergence induced by the severe class imbalance of the pixels representing tiny cracks. The capability of the network in segmenting tiny cracks was remarkably enhanced by the aforementioned arrangements, and the “Tiny‐Crack‐Net” achieved a Dice similarity coefficient of 87.96% on an open‐source data set, which was at least 5.84% higher than those of the six cutting‐edge networks. The effectiveness and robustness of the “Tiny‐Crack‐Net” were validated with field test results, which showed that the intersection over union (IOU) for cracks with a width of 0.05 mm or wider reaches 91.44%.
Investigations on the Performance of a New Grounding Device with Spike Rods under High Magnitude Current Conditions

In many publications, the characteristics of practical earthing systems were investigated under conditions involving fast-impulse currents of different magnitudes by field measurements. However, as generally known, in practice the transient current can normally reach several tens of kiloamperes. This paper therefore aimed to investigate the characteristics of a new electrode for grounding systems under high current magnitude conditions, and compare it with steady-state test results. The earth electrodes were installed in low resistivity test media, so that high impulse current magnitudes can be achieved. The effects of impulse polarity and earth electrode’s geometry of a new earth electrode were also quantified under high impulse conditions, at high currents (up to 16 kA).
Development of the Mental Health Support Scale: A New Measure of Mental Health First Aid Behaviors

Mental health first aid (MHFA) courses teach community members the knowledge and skills needed to recognize and respond to mental health problems until professional help is received or the crisis resolves. This study aimed to develop a reliable and valid measure of MHFA behaviors. A pool of actions that were recommended and not recommended were selected from MHFA guidelines and developed into two scales measuring either intended or provided support. Items were tested with a sample of 697 adults. Item response theory guided the selection of final items. The Mental Health Support Scale (MHSS) Intended version has 23 items across two subscales and the MHSS–Provided has 12 items across two subscales. These scales demonstrated convergent validity, discrimination between respondents with and without MHFA expertise, and acceptable measurement precision across a range of skill levels. Overall, findings suggest that the MHSS is a valid and useful measure of MHFA behaviors.
Prediction Model of Dissolved Gas in Transformer Oil Based on VMD‐SMA‐LSSVM

Dissolved gas analysis in oil is an effective method for early fault diagnosis of transformers. Predicting the concentration of future characteristic gases in the transformer can assist operation and maintenance personnel in judging the operation trend of the transformer and ensure stable operation. In order to improve the prediction accuracy of dissolved gas in transformer oil based on a small number of samples, this paper proposes a VMD‐SMA‐LSSVM combined prediction model by using variational modal decomposition and least square support vector machine optimized by slime mold algorithm. First, use variational modal decomposition to decompose the gas signal. For each subsequence, a combined algorithm based on slime mold optimization and least square support vector machine is used to predict separately. Then the prediction results of each sub‐sequence are superimposed and reconstructed to obtain the final prediction value. The research results show that the prediction results obtained based on this method have better prediction effects than other models of machine learning models, other decomposition methods and optimization methods. The proposed method has good fitting characteristics when predicting seven characteristic gases, which verifies the effectiveness. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
High‐Performance p‐type 2D FET Based on Monolayer GeC with High Hole Mobility: A DFT‐NEGF Study

2D materials are identified as Si alternatives for channels in next‐generation electronic devices. However, lack of high‐performance (HP) p‐type field‐effect transistors (FETs) acts as a block to the development of efficient complementary circuits. Here, p‐type monolayer GeC with planar structure is evaluated as a promising channel material to resolve the corresponding problems. The monolayer GeC possesses a direct bandgap of 2.07 eV with high hole mobility up to 6600 cm2 V–1 s–1. Coupling with ballistic quantum transport simulations, the results show that both n‐ and p‐FETs can hold the on‐currents exceeding 1200 µA µm–1 for HP devices. Particularly, for p‐type, the on‐currents with the channel shrinking from 10 to 3 nm can reach as high as 2991—1660 µA µm–1, which is of great value for the design of complementary circuits in 2D electronics. In addition, the figures of merits for GeC FETs, such as delay time, power dissipation, and energy‐delay product, are also assessed, fulfilling the demands of the International Technology Roadmap for Semiconductors (ITRS) and the International Roadmap for Devices and Systems (IRDS) for HP applications. Hence, this study demonstrates great potential of 2D GeC for future competitive electronic devices.
Gastrointestinal Symptoms and Hepatopancreatic Involvement in COVID-19 Children: A Narrative Review

Background: To the best of our knowledge, limited studies explored gastrointestinal (GI) symptoms and hepatopancreatic involvement in children with coronavirus disease 2019 (COVID- 19) infection. Objectives: This review study aimed to evaluate the GI symptoms and abnormal liver and pancreas function in children with COVID-19 infection. Methods: In this review study, databases of Scopus, PubMed, Google Scholar, and Web of Science were searched using the relevant keywords of “COVID-19,” “children,” “gastrointestinal,” “liver,” and “pancreas. ” Descriptive and cross-sectional studies were reviewed in the current study, with the main focus on GI symptoms and elevated liver enzymes in children with COVID-19 infection. Results: Overall, 27 studies from countries of Iran, Spain, Turkey, Italy, and the United States were selected. Although the prevalence of GI symptoms varied in different studies, our review showed that most children with COVID-19 infection experienced GI symptoms. In addition to GI symptoms, there is the possibility of elevated liver enzymes, such as alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and creatine phosphokinase in children with COVID-19 infection. Conclusions: COVID-19 infection may present various GI, hepatic, and pancreatic manifestations in children. The difference in the prevalence of these symptoms can probably be attributed to the geographical region of the study and the history of the disease.