bluuebunny/crossref_metadata_2025 huggingface dataset:
Zihinsel Engelli Çocuk Sahibi Annelerin ve Toplumun Engelliliğe Bakışı
Authors: Aksakal Erol
Published: May 2024

Zihinsel engelli çocuk sahibi ebeveynlerin engelliliği dışlanma, damgalanma, ayrımcılık, ve eşitlik bağlamında nasıl düşündüğü, nasıl inşa ettiği bu araştırmanın nihai hedefini oluşturmaktadır. Araştırmanın özgünlüğü açısından, zihin engelli çocuğu bulunan ebeveynlerin, engellilere yönelik gerek kullanılan dil, gerekse davranışlar açısından, damgalayıcı, dışlayıcı ve ayrımcı eğilimleri kabullenip, bu durumu günlük yaşamlarında yeniden üretip üretmediğinin tespit edilmesi, doldurulması gereken önemli bir boşluğu oluşturmaktadır. Bu hedefle bu araştırma, İzmir ilinin Kemalpaşa ilçesinde 1 erkek, 39 kadın olmak üzere toplam 40 zihinsel engelli çocuk sahibi ebeveyn ile yarı yapılandırılmış görüşme formu dahilinde yapılan yüz yüze derinlemesine görüşmelerden oluşmuştur. Araştırma bulguları göstermektedir ki; zihinsel engelli çocuk sahibi ebeveynler (özellikle anneler) zihinsel engelli çocuğun her şeyi ile ilgilenmekte, bunun için büyük fedakarlıklara katlanmakta, kendi kariyer, sosyal kültürel gelişmelerine zaman ayıramamakta ve çocukların maruz kalmış olduğu dışlanma ve damgalanma sorunlarını kendileri de yaşamaktadır. Diğer taraftan engellilere bakış açısı olarak, ebeveynlerin neredeyse tamamının tıbbi temelli hakim engellilik tanımını içselleştirdiği, yeniden ürettiği, ve engelliliği tanımlarken dışlayıcı ve damgalayıcı bir dil kullandığı tespit edilmiştir. Ayrıca toplum tarafından çeşitli damgalama, dışlanma ve ayrımcılığa maruz kalan ebeveynler özellikle engelliliğe yönelik cinsiyetleştirilmiş ve ırksallaştırılmış damgalayıcı ve dışlayıcı dilin etkisinden kaçamamaktadırlar.
Türkiye’de İslami Kadın Moda Algısına Eleştirel Bir Katkı
Authors: Aytepe Ozan
Published: May 2024

Türkiye'de tarihsel bir perspektiften incelendiğinde, İslamcı olarak nitelendirilen veya inançları doğrultusunda yaşamayı tercih eden Müslüman kadınların toplumsal katılımı ve görünürlüğü üzerine yapılan tartışmalar önemli bir evrim süreci göstermiştir. Geçmişte, ev ortamı ve bireysel habituslarında daha kapalı ve sınırlı bir alana mahkûm edilen Müslüman kadınların toplumsal katılımı günümüzde önemli ölçüde artmış, bu kadınlar artık toplumun göz önünde olan, vitrindeki yerlerini almış bireyler haline gelmişlerdir. Bu dönüşümün arka planında yatan çeşitli faktörler arasında İslami moda ve bu modaya dair algılar dikkate değer bir inceleme konusudur. İslami modanın popülerleşmesi, Müslüman kadınların hem dini inançlarını ifade etme biçimlerini hem de toplumsal ve kültürel katılımlarını şekillendiren önemli bir faktör olmuştur. Bu süreç, moda dergileri, sosyal medya fenomenleri ve çevrimiçi oyunlar gibi çeşitli medya araçları aracılığıyla incelenmiş ve değerlendirilmiştir. Bu platformlar, İslami moda anlayışının yaygınlaşmasında ve çeşitlenmesinde kilit rol oynamış, Müslüman kadınların kendilerini ifade etme ve toplum içinde görünür olma yollarını çeşitlendirmiştir. Moda dergileri, trendleri ve yeni stil önerilerini sunarken, sosyal medya fenomenleri kişisel deneyimlerini ve giyim tarzlarını takipçileriyle paylaşarak İslami modanın daha geniş kitlelere ulaşmasını sağlamıştır. Çevrimiçi oyunlar ise, sanal dünyada Müslüman kadın karakterlerin modaya dair tercihlerini yansıtarak, genç nesiller arasında farkındalık yaratmış ve İslami moda anlayışını daha geniş bir perspektifle ele almayı mümkün kılmıştır.
Evaluation of the cooling flow rate of the cooled steam turbine for a novel H2/O2 cycle
Authors: Ma Bangyan , Shi Lei , Li Yan , Zhu Xiaocheng , Du Zhaohui
Published: May 2024

In recent years, with the global low-carbon development, hydrogen as a clean fuel for the industry has attracted the interest of many research institutions all over the world. The potential of hydrogen energy in energy transformation has been paid attention to again. In the power generation industry, using hydrogen as gas turbine fuel is likely to play an important role in achieving carbon neutrality. At design stage, it is necessary to perform a preliminary evaluation of the performance of the novel hydrogen-fueled cycle with a few (or even without) experimental data. It is sure that secondary cooling systems have a significant impact on it. In this paper, a methodology is adopted for the cooling of hydrogen-fueled gas turbine. It is based on mass/energy balances and heat transfer correlations. The aim is to evaluate the turbine efficiency and cooling flow requirements of the novel hydrogen-fueled cycle. When both the working fluid and coolant are steam, the cooling flow rate is less. Preliminary results for the novel H2/O2 cycle turbine show that part of the stages need to be cooled and the film cooling effectiveness is less.
BIBLIOMETRIC INSIGHTS INTO ASSESSMENT PRACTICES IN THE MERDEKA CURRICULUM: IDENTIFYING OPPORTUNITIES FOR NEW ASSESSMENT DEVELOPMENT
Authors: Hadiastriani Yasmine , Djarot Prasetyorini , Chemistry Valerie Indiana
Published: May 2024

The Merdeka Curriculum in Indonesia represents a transformative educational reform emphasizing holistic student development. However, conventional assessment methods have proven inadequate in comprehensively evaluating these desired learning outcomes. This study employs bibliometric analysis to systematically examine the research landscape surrounding the multiple assessment in the context of Merdeka Curriculum. Through data mining from the Google Scholar database spanning 2018 to 2023, the findings reveal a significant gap between the substantial academic interest in multiple assessments, as evidenced by 2,727 citations from 660 publications, and the limited number of studies (92 articles with 187 citations) explicitly focused on developing new assessment instruments. Keyword analysis further highlighted the under representation of terms like "assessment instrument" and "development," signaling a need for intensified research efforts in this domain. The study's findings underscore the urgent necessity for developing innovative assessment tools that transcend traditional knowledge-based testing methods. These new assessments hold the potential to elevate the quality of education in Indonesia, better preparing students to navigate the complexities of the 21st century global landscape.
The Effect of Five-Finger Relaxation Technique on Anxiety and Stress in Non-Hemorrhagic Stroke Patients at the Inpatient Installation of RSUD Cimacan Cianjur District
Authors: Dewi Rosliana , Fatmala Syiva Dwi , Yulianti Maria , Arsyi Dila Nurul
Published: May 2024

Aims: The purpose of this study was to examine the effect of five-finger relaxation technique on anxiety and stress in hemorrhagic stroke patients at Cimacan Hospital.
Methods: This study used quasi-experiment with nonequivalent control group design. Sample collection using purposive sampling. The sample was 40 people and divided into two groups with 20 people each for the intervention group and control group. Data analysis using Paired Sample T-Test and Independent Sample T-Test.
Results: The results showed that after the five-finger relaxation technique was performed on the intervention group, there was a decrease in anxiety levels (p = 0.000) and stress (p = 0.000) in stroke patients, while in the control group there was a decrease in anxiety (p = 0.000) and stress (p = 0.000), and there was a difference between anxiety levels (p = 0.000) and stress (p = 0.000) in the intervention and control groups.
Conclusion: There is an effect of five-finger relaxation technique on anxiety and stress in non-hemorrhagic stroke patients, and there are differences in anxiety and stress in the control and intervention groups. It is hoped that this five-finger relaxation technique can be used as an evidence base nursing on non-pharmacological treatment as a form of independent nursing intervention by a nurse in providing nursing care to help in the process of reducing anxiety and stress in stroke patients.
Belief in Divine (Versus Human) Control of Earth Affects Perceived Threat of Climate Change
Authors: Kane John , Perry Samuel
Published: May 2024

Religious conservatism is associated with Americans’ skepticism toward climate-related science and policy. Yet the specific religious beliefs that are causally responsible for this dynamic, if any, remain unclear. In this study, we theorize that belief in divine (versus human) control over Earth’s future climate reduces belief in humans’ responsibility for climate change as well as concern about its severity. Regression analyses with national survey data (n=5,321) demonstrate that believing “God would not allow humans to destroy the Earth” is associated with lower concern about climate change. Next, a pre-registered survey experiment (n=3,333) finds that manipulating belief in God’s—vis-à-vis humans’—control of Earth’s climate affects the perceived severity of climate change and need for policy intervention. Our manipulation also reduced demand for climate- related information from the National Oceanic and Atmospheric Association. Our results establish an important causal link between a religious belief and climate change attitudes in the U.S. public.
Ensaios de uma transintervenção psi com mulheres em uma clínica de Nutrição
Authors: Santos Áshlyn Lima dos , Brunini Bárbara Cossettin Costa Beber
Published: May 2024

O presente trabalho debruça-se do resultado do encontro de corpos mulheres com uma Psicologia Feminista no espaço de uma clínica escola de Nutrição, trazendo, através de ensaios nos próprios corpos, o modelo de transintervenção. No primeiro ensaio desta escrita/experimentação, a genealogia e a etimologia da palavra “trans”, referenciam nosso estar em corpo e formação e seus atravessamentos no estar estagiária, de uma transintervenção que reflete sobre a produção de saúde mental e mulheridades. O segundo ensaio discorre sobre o método cartográfico que foi o elencado para o desenvolvimento do estágio com a intenção de vivenciar uma pesquisa-intervenção ética e política na transformação de territórios subjetivos. Para o terceiro ensaio, faz-se uma recuperação histórica do(s) feminismo(s) no Brasil, estudos sobre gênero, corpo e mulheridades. Por fim, no quarto ensaio e considerações finais reflete-se sobre o compromisso psicossocial da Psicologia com a temática desenvolvida ao longo do estágio.
Identification of circulatory microRNA based biomarkers for early pregnancy diagnosis in buffalo
Authors: Batra Kanisht , Sehrawat Anju , Kumar Aman , Singh Man , Kaur Ramandeep , Yadav Dipin Chander , Singh Neha , Maan Sushila
Published: May 2024

Introduction: The most crucial factor in improving animal reproduction efficiency is early pregnancy diagnosis. Early diagnosis not only reduces the time interval between two calvings but also aids farmers in identifying open animals, thereby preventing significant milk production losses. Therefore, the objective of this study was to discover circulatory miRNAs that would be useful for early pregnancy diagnosis in buffalo.

Material and methods: Blood samples were taken on 0, 6th, 12th, and 18th day after artificial insemination from pregnant animals (n = 30) and non-pregnant animals (n = 20). During these stages of pregnancy, total RNA was extracted, and a small RNA library was subsequently generated and sequenced on the Illumina platform. Subsequently, Real-time PCR was used to validate the findings.

Results and discussion: There were 4,022 miRNAs found during the pregnancy, with 15 of those lacking sequences and 4,007 having sequences already in the database. From the beginning of pregnancy until the 18th day, 25 of these miRNAs showed a substantial shift in expression levels in the maternal blood, with a change more than two logs. Furthermore, based on qPCR results, 19 miRNAs were found to be more abundant in pregnant animals than in non-pregnant animals. We used target prediction analysis to learn how maternally expressed miRNAs relate to fetal-maternal communication. In conclusion, miRNA based biomarkers that could be associated with the diagnosis of pregnancy were identified including miR-181a and miR-486 highly upregulated on the 18th day of pregnancy. This study also provides a comprehensive profile of the entire miRNA population in maternal buffalo blood during the early stages of pregnancy.
Assessment of causal associations between obesity and peripheral artery disease: a bidirectional Mendelian randomization study
Authors: Huang Xi-wei , Pang Shu-wen , Zhang Tao , Huang Chuang-wei
Published: May 2024

Background

Several observational studies have documented a potential link between obesity and peripheral artery disease (PAD), although conflicting findings exist. The causal relationship between obesity and PAD continues to be a subject of ongoing debate in the medical community.

Objectives

In this study, we employed a bidirectional Mendelian randomization (MR) analysis to explore the potential causal relationship between obesity and the risk of PAD.

Methods

To investigate these causal relationships, we conducted bidirectional MR analysis using publicly available genome-wide association study (GWAS) data. Effect estimates were calculated using the random-effects inverse variance-weighted (IVW) method.

Results

We identified eight independent single nucleotide polymorphisms (SNPs) associated with obesity in 218,735 samples involving 16,380,465 SNPs, all of which met the genome-wide significance threshold (p < 5 × 10−⁸). The IVW analysis indicates a significant positive association between genetic obesity and multiple datasets with PAD as the outcome: Queue-1 (GWAS ID: finn-b-I9_PAD) (OR = 1.138, 95% CI: 1.027–1.261, p = 0.013), Queue-2 (GWAS ID: bbj-a-144) (OR = 1.190, 95% CI: 1.019–1.390, p = 0.028), Queue-3 (GWAS ID: ebi-a-GCST90018670) (OR = 1.174, 95% CI: 1.014–1.360, p = 0.032), and Queue-4 (GWAS ID: ebi-a-GCST90018890) (OR = 1.194, 95% CI: 1.099–1.296, p < 0.001). However, we did not observe a significant genetic-level association between obesity and PAD for Queue-5 (GWAS ID: ukb-d-I9_PAD) (OR = 1.001, 95% CI: 1.000–1.002, p = 0.071). Furthermore, we conducted a reverse causal MR analysis to explore the potential reverse causal relationship between obesity and PAD. This comprehensive analysis did not provide evidence of a reverse causal association between these two factors.

Conclusions

In summary, our study offers genetic evidence suggesting a possible causal link between obesity and PAD. While we did not find evidence supporting the “obesity paradox”, prudent weight management remains crucial, as lower weight does not necessarily guarantee better outcomes. As with any study, caution is required in interpreting the findings. Further research is essential to assess the clinical relevance of weight in preventing PAD, which could inform the development of more precise intervention strategies.
Comparative investigations on hull line optimization based on traditional and fully parametric methods for saving energy
Authors: Cheng Xuankai , Wang Dong , Huang Xinhui , Yan Xu , Dou Peng , Ji Renwei
Published: May 2024

The new regulations on ship energy efficiency proposed by the International Maritime Organization have had a significant impact on the shipping and shipbuilding industries. Improving the speed performance of ships was an effective approach to meet the requirements of energy conservation and emission reduction, reduce ship energy consumption and operating costs, and strengthen the market competitiveness of the ship enterprises. One method to improve ship speed performance was by mainly reducing the ship’s resistance. The main aim was to optimize the principal dimensions and hull lines of ships. Taking the research and development of a ship as an example, the application of the fully parametric optimization method in the optimization of ship hull lines was described in detail. The parent ship was selected from the ship database, which has excellent speed performance. The parent ship was simply transformed to meet the requirements of the target ship. The traditional optimization method was used to optimize the hull lines to reduce the hull resistance as much as possible, and a hull line with the best resistance performance was obtained. Based on the initial hull lines that met the requirements, the fully parametric model of the hull was established, and the fully parametric optimization method was used to optimize the hull with the best resistance performance. Experiments were carried out in the towing tank, and the resistance results of the two types of ships were found. The simulation of computational fluid dynamics (CFD) and model test had good consistency, and it was found that the hull lines optimized by the fully parameterization method had better performance than those optimized by the traditional method. The fully parametric hull line optimization method was effective in optimizing hull lines, and it could also reduce the excessive dependence of research personnel on the parent ship and design experience.
Cost-effective high-gain DC-DC converter for elevator drives using photovoltaic power and switched reluctance motors
Authors: Baskaran J. , Naghapushanam Manimaran , Ganapathy Mahalakshmi , Meena P. , Meena V. P. , Azar Ahmad Taher , Hameed Ibrahim A.
Published: May 2024

Low-cost photovoltaic-powered elevators (PVPEs) have gained ever-increasing attention in the last few years for their advantages in terms of renewable energy and low maintenance costs after installation. In this paper, four high-step-up DC-DC converters for low-voltage sources such as solar photovoltaic, fuel cells, and battery banks are proposed. Their performances are evaluated in terms of optimal capability and high reliability. Among the four proposed architectures, the bootstrap converter is selected for its ability to restrict losses and other redundant parameters. The proposed converter drives the inverter-driven switched reluctance motor (SRM) assembly through a directly coupled method, which eliminates the need for battery banks while aiding in cost reduction. The prototype model is implemented, and results are validated, showing promising performance and thus being very efficacious for application to low-cost PVPEs.
Effects of different dietary energy levels on growth performance, meat quality and nutritional composition, rumen fermentation parameters, and rumen microbiota of fattening Angus steers
Authors: Chen Kaihao , Shui Yanghaoer , Deng Ming , Guo Yongqing , Sun Baoli , Liu Guangbin , Liu Dewu , Li Yaokun
Published: May 2024

This study investigates the effects of varying energy levels in diets on Black Angus steers, focusing on growth performance, muscle composition, rumen microbial community, and their interrelationships. Twenty-seven Black Angus steers, aged approximately 22 months and weighing 520 ± 40 kilograms, were randomly divided into three groups: low-energy (LE), medium-energy (ME), and high-energy (HE). Each group consisted of nine individuals. The steers were fed diets with energy levels of 6.657 MJ/kg (LE), 7.323 MJ/kg (ME), and 7.990 MJ/kg (HE) following a 14-day pre-feeding period, with a subsequent 90-day main experimental phase. After the 90-day feeding period, both the HE and ME groups exhibited significantly higher average daily weight gain (ADG) compared to the LE group (p < 0.05). The feed-to-weight ratios were lower in the HE and ME groups compared to the LE group (p < 0.05). The HE group showed significantly higher crude fat content in the longissimus dorsi muscle compared to the LE group (p < 0.05), with total fatty acid content in the muscle surpassing that in the ME and LE groups (p < 0.05). As dietary energy levels increased, the diversity of the rumen microbial community decreased (p < 0.05), and significant differences in bacterial community structure were observed between the LE and HE groups (p < 0.05). The results suggest that higher dietary energy levels enhance growth performance and alter muscle composition in Black Angus steers, while also influencing the rumen microbial community. This study contributes to understanding optimal dietary strategies for finishing Angus cattle to improve beef quality, economic returns, and the development of standardized production procedures.
Vendors' handling practices of edible long-horned grasshoppers (Ruspolia differens) products and implications on microbial safety
Authors: Mugo-Kamiri Loretta , Imungi Jasper K. , Njue Lucy , Diiro Gracious , Ombura Fidelis Levi O. , Akutse Komivi S. , Chrysantus Tanga M. , Khamis Fathiya M. , Subramanian Sevgan
Published: May 2024

Edible grasshopper, Ruspolia ruspolia, has nutritional and cherished cultural and economic importance to people from diverse cultures, particularly in over 20 African countries. It is consumed at home or commercially traded as sautéed, deep-fried, or boiled products. However, there is limited information on the hygiene practices of the vendors and the implications on the microbial safety of the final product. This research aimed at assessing the food safety knowledge, handling practices and shelf life of edible long-horned grasshopper products among vendors and the microbial safety of ready-to-eat products sold in 12 different markets in Uganda. Samples of raw, deep-fried and boiled grasshoppers were randomly collected from 74 vendors (62% street and 38% market vendors) and subjected to microbial analysis. Over 85% of the vendors surveyed had no public health food handler's certificate and >95% had limited post-harvest handling knowledge. Total aerobic bacteria (7.30–10.49 Log10 cfu/g), Enterobacteriaceae (5.53–8.56 Log10 cfu/g), yeasts and molds (4.96–6.01 Log10 cfu/g) total counts were significantly high and above the acceptable Codex Alimentarius Commission and Food Safety Authority of Ireland (FSAI) limits for ready-to-eat food products. Eight key pathogenic bacteria responsible for foodborne diseases were detected and these isolates were characterized as Bacillus cereus, Hafnia alvei, Serratia marcescens, Staphylococcus aureus, S. xylosus, S. scuiri, S. haemolyticus, and Pseudomonas aeruginosa. Findings from this study highlight the urgent need to create local and national food safety policies for the edible grasshopper “nsenene” subsector to regulate and guide street and market vending along the value chain, to prevent the transmission of foodborne diseases to consumers.
Rippling life on a dormant planet: hibernation of ribosomes, RNA polymerases, and other essential enzymes
Authors: Helena-Bueno Karla , Chan Lewis I. , Melnikov Sergey V.
Published: May 2024

Throughout the tree of life, cells and organisms enter states of dormancy or hibernation as a key feature of their biology: from a bacterium arresting its growth in response to starvation, to a plant seed anticipating placement in fertile ground, to a human oocyte poised for fertilization to create a new life. Recent research shows that when cells hibernate, many of their essential enzymes hibernate too: they disengage from their substrates and associate with a specialized group of proteins known as hibernation factors. Here, we summarize how hibernation factors protect essential cellular enzymes from undesired activity or irreparable damage in hibernating cells. We show how molecular hibernation, once viewed as rare and exclusive to certain molecules like ribosomes, is in fact a widespread property of biological molecules that is required for the sustained persistence of life on Earth.
Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study
Authors: Russo Samuele , Tibermacine Imad Eddine , Tibermacine Ahmed , Chebana Dounia , Nahili Abdelhakim , Starczewscki Janusz , Napoli Christian
Published: May 2024

Introduction

The primary objective of this research is to examine acrophobia, a widely prevalent and highly severe phobia characterized by an overwhelming dread of heights, which has a substantial impact on a significant proportion of individuals worldwide. The objective of our study was to develop a real-time and precise instrument for evaluating levels of acrophobia by utilizing electroencephalogram (EEG) signals.

Methods

EEG data was gathered from a sample of 18 individuals diagnosed with acrophobia. Subsequently, a range of classifiers, namely Support Vector Classifier (SVC), K-nearest Neighbors (KNN), Random Forest (RF), Decision Tree (DT), Adaboost, Linear Discriminant Analysis (LDA), Convolutional Neural Network (CNN), and Artificial Neural Network (ANN), were employed in the analysis. These methodologies encompass both machine learning (ML) and deep learning (DL) techniques.

Results

The Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) models demonstrated notable efficacy. The Convolutional Neural Network (CNN) model demonstrated a training accuracy of 96% and a testing accuracy of 99%, whereas the Artificial Neural Network (ANN) model attained a training accuracy of 96% and a testing accuracy of 97%. The findings of this study highlight the effectiveness of the proposed methodology in accurately categorizing real-time degrees of acrophobia using EEG data. Further investigation using correlation matrices for each level of acrophobia showed substantial EEG frequency band connections. Beta and Gamma mean values correlated strongly, suggesting cognitive arousal and acrophobic involvement could synchronize activity. Beta and Gamma activity correlated strongly with acrophobia, especially at higher levels.

Discussion

The results underscore the promise of this innovative approach as a dependable and sophisticated method for evaluating acrophobia. This methodology has the potential to make a substantial contribution toward the comprehension and assessment of acrophobia, hence facilitating the development of more individualized and efficacious therapeutic interventions.
Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders
Authors: Ramos-Triguero Anna , Navarro-Tapia Elisabet , Vieiros Melina , Mirahi Afrooz , Astals Vizcaino Marta , Almela Lucas , Martínez Leopoldo , García-Algar Óscar , Andreu-Fernández Vicente
Published: May 2024

Introduction

Fetal alcohol spectrum disorders include a variety of physical and neurocognitive disorders caused by prenatal alcohol exposure. Although their overall prevalence is around 0.77%, FASD remains underdiagnosed and little known, partly due to the complexity of their diagnosis, which shares some symptoms with other pathologies such as autism spectrum, depression or hyperactivity disorders.

Methods

This study included 73 control and 158 patients diagnosed with FASD. Variables selected were based on IOM classification from 2016, including sociodemographic, clinical, and psychological characteristics. Statistical analysis included Kruskal-Wallis test for quantitative factors, Chi-square test for qualitative variables, and Machine Learning (ML) algorithms for predictions.

Results

This study explores the application ML in diagnosing FASD and its subtypes: Fetal Alcohol Syndrome (FAS), partial FAS (pFAS), and Alcohol-Related Neurodevelopmental Disorder (ARND). ML constructed a profile for FASD based on socio-demographic, clinical, and psychological data from children with FASD compared to a control group. Random Forest (RF) model was the most efficient for predicting FASD, achieving the highest metrics in accuracy (0.92), precision (0.96), sensitivity (0.92), F1 Score (0.94), specificity (0.92), and AUC (0.92). For FAS, XGBoost model obtained the highest accuracy (0.94), precision (0.91), sensitivity (0.91), F1 Score (0.91), specificity (0.96), and AUC (0.93). In the case of pFAS, RF model showed its effectiveness, with high levels of accuracy (0.90), precision (0.86), sensitivity (0.96), F1 Score (0.91), specificity (0.83), and AUC (0.90). For ARND, RF model obtained the best levels of accuracy (0.87), precision (0.76), sensitivity (0.93), F1 Score (0.84), specificity (0.83), and AUC (0.88). Our study identified key variables for efficient FASD screening, including traditional clinical characteristics like maternal alcohol consumption, lip-philtrum, microcephaly, height and weight impairment, as well as neuropsychological variables such as the Working Memory Index (WMI), aggressive behavior, IQ, somatic complaints, and depressive problems.

Discussion

Our findings emphasize the importance of ML analyses for early diagnoses of FASD, allowing a better understanding of FASD subtypes to potentially improve clinical practice and avoid misdiagnosis.
Legumes and common beans in sustainable diets: nutritional quality, environmental benefits, spread and use in food preparations
Authors: Lisciani Silvia , Marconi Stefania , Le Donne Cinzia , Camilli Emanuela , Aguzzi Altero , Gabrielli Paolo , Gambelli Loretta , Kunert Karl , Marais Diana , Vorster Barend Juan , Alvarado-Ramos Katherine , Reboul Emmanuelle , Cominelli Eleonora , Preite Chiara , Sparvoli Francesca , Losa Alessia , Sala Tea , Botha Anna-Maria , Ferrari Marika
Published: May 2024

In recent decades, scarcity of available resources, population growth and the widening in the consumption of processed foods and of animal origin have made the current food system unsustainable. High-income countries have shifted towards food consumption patterns which is causing an increasingly process of environmental degradation and depletion of natural resources, with the increased incidence of malnutrition due to excess (obesity and non-communicable disease) and due to chronic food deprivation. An urgent challenge is, therefore, to move towards more healthy and sustainable eating choices and reorientating food production and distribution to obtain a human and planetary health benefit. In this regard, legumes represent a less expensive source of nutrients for low-income countries, and a sustainable healthier option than animal-based proteins in developed countries. Although legumes are the basis of many traditional dishes worldwide, and in recent years they have also been used in the formulation of new food products, their consumption is still scarce. Common beans, which are among the most consumed pulses worldwide, have been the focus of many studies to boost their nutritional properties, to find strategies to facilitate cultivation under biotic/abiotic stress, to increase yield, reduce antinutrients contents and rise the micronutrient level. The versatility of beans could be the key for the increase of their consumption, as it allows to include them in a vast range of food preparations, to create new formulations and to reinvent traditional legume-based recipes with optimal nutritional healthy characteristics.
Dimensionality assessment in ordinal data: a comparison between parallel analysis and exploratory graph analysis
Authors: Markos Angelos , Tsigilis Nikolaos
Published: May 2024

In the social sciences, accurately identifying the dimensionality of measurement scales is crucial for understanding latent constructs such as anxiety, happiness, and self-efficacy. This study presents a rigorous comparison between Parallel Analysis (PA) and Exploratory Graph Analysis (EGA) for assessing the dimensionality of scales, particularly focusing on ordinal data. Through an extensive simulation study, we evaluated the effectiveness of these methods under various conditions, including varying sample size, number of factors and their association, patterns of loading magnitudes, and symmetrical or skewed item distributions with assumed underlying normality or non-normality. Results show that the performance of each method varies across different scenarios, depending on the context. EGA consistently outperforms PA in correctly identifying the number of factors, particularly in complex scenarios characterized by more than a single factor, high inter-factor correlations and low to medium primary loadings. However, for datasets with simpler and stronger factor structures, specifically those with a single factor, high primary loadings, low cross-loadings, and low to moderate interfactor correlations, PA is suggested as the method of choice. Skewed item distributions with assumed underlying normality or non-normality were found to noticeably impact the performance of both methods, particularly in complex scenarios. The results provide valuable insights for researchers utilizing these methods in scale development and validation, ensuring that measurement instruments accurately reflect theoretical constructs.
invariant Natural Killer T cell therapy as a novel therapeutic approach in hematological malignancies
Authors: Boonchalermvichian Chaiyaporn , Yan Hao , Gupta Biki , Rubin Anabel , Baker Jeanette , Negrin Robert S.
Published: May 2024

Invariant Natural Killer T cell therapy is an emerging platform of immunotherapy for cancer treatment. This unique cell population is a promising candidate for cell therapy for cancer treatment because of its inherent cytotoxicity against CD1d positive cancers as well as its ability to induce host CD8 T cell cross priming. Substantial evidence supports that iNKT cells can modulate myelomonocytic populations in the tumor microenvironment to ameliorate immune dysregulation to antagonize tumor progression. iNKT cells can also protect from graft-versus-host disease (GVHD) through several mechanisms, including the expansion of regulatory T cells (Treg). Ultimately, iNKT cell-based therapy can retain antitumor activity while providing protection against GVHD simultaneously. Therefore, these biological properties render iNKT cells as a promising “off-the-shelf” therapy for diverse hematological malignancies and possible solid tumors. Further the introduction of a chimeric antigen recetor (CAR) can further target iNKT cells and enhance function. We foresee that improved vector design and other strategies such as combinatorial treatments with small molecules or immune checkpoint inhibitors could improve CAR iNKT in vivo persistence, functionality and leverage anti-tumor activity along with the abatement of iNKT cell dysfunction or exhaustion.
Optimizing image processing for modern wide field surveys: enhanced data management based on the LSST science pipelines
Authors: Hong Yuanyu , Yang Chao , Zhang Miaomiao , Chen Yanpeng , Liu Binyang
Published: May 2024

Introduction:In recent decades, numerous large survey projects have been initiated to enhance our understanding of the cosmos. Among these, the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) stands out as a flagship project of the Stage IV cosmology imaging surveys, offering an open-source framework for data management and processing adaptable to various instruments.

Methods:In this paper, we introduce the ‘obs_mccd’ software package, designed to serve as a bridge linking raw data from generic mosaic-CCD instruments to the LSST data management framework. The package also facilitates the deployment of tailored configurations to the pipeline middleware. To validate our data processing pipeline, we processed a batch of realistic data from a commissioning wide-field telescope.

Results:We established a prototype of the quality control (QC) system capable of assessing image quality parameters such as PSF size, ellipticity, and astrometric calibration. Our findings indicate that using a fifth-order polynomial for astrometric calibration effectively characterizes geometric distortion, achieving a median average geometric distortion residual of 0.011 pixel.

Discussion:When comparing the performance of our pipeline to our in-house pipeline applied to the same dataset, we observed that our new ‘obs_mccd’ pipeline offers improved precision, reducing the median average geometric distortion residual from 0.016 pixel to 0.011 pixel. This enhancement in performance underscores the benefits of the obs_mccd package in managing and processing data from wide-field surveys, and it opens up new avenues for scientific exploration with smaller, flexible survey systems complementing the LSST.
Is neoadjuvant chemotherapy followed by surgery the appropriate treatment for esophagogastric signet ring cell carcinomas? A systematic review and meta-analysis
Authors: Schiefer Sabine , Crnovrsanin Nerma , Kalkum Eva , Vey Johannes A. , Nienhüser Henrik , Rompen Ingmar F. , Haag Georg M. , Müller-Stich Beat , Billmann Franck , Schmidt Thomas , Probst Pascal , Klotz Rosa , Sisic Leila
Published: May 2024

Background

The impact of neoadjuvant chemotherapy (nCTX) on survival and tumor response in patients with esophagogastric signet ring cell carcinoma (SRCC) is still controversial.

Methods

Two independent reviewers performed a systematic literature search in Medline, CENTRAL, and Web of Science including prospective and retrospective two-arm non-randomized and randomized controlled studies (RCTs). Data was extracted on overall survival (OS) and tumor regression in resected esophagogastric SRCC patients with or without nCTX. Survival data was analyzed using published hazard ratios (HR) if available or determined it from other survival data or survival curves. OS and histopathological response rates by type of tumor (SRCC vs. non-SRCC) were also investigated.

Results

Out of 559 studies, ten (1 RCT, 9 non-RCTs) were included in this meta-analysis (PROSPERO CRD42022298743) investigating 3,653 patients in total. The four studies investigating survival in SRCC patients treated with nCTX + surgery vs. surgery alone showed no survival benefit for neither intervention, but heterogeneity was considerable (HR, 1.01; 95% CI, 0.61–1.67; p = 0.98; I2 = 89%). In patients treated by nCTX + surgery SRCC patients showed worse survival (HR, 1.45; 95% CI, 1.21–1.74; p < 0.01) and lower rate of major histopathological response than non-SRCC patients (OR, 2.47; 95% CI, 1.78–3.44; p < 0.01).

Conclusion

The current meta-analysis could not demonstrate beneficial effects of nCTX for SRCC patients. Histopathological response to and survival benefits of non-taxane-based nCTX seem to be lower in comparison to non-SRC esophagogastric cancer. However, certainty of evidence is low due to the scarcity of high-quality trials. Further research is necessary to determine optimal treatment for SRCC patients.

Systematic Review Registration

https://www.crd.york.ac.uk/, PROSPERO (CRD42022298743).
The Weighted Least-Squares Approach to State Estimation in Linear State Space Models: The Case of Correlated Noise Terms
Authors: Galka Andreas
Published: May 2024

In this article, a particular approach to deriving recursive state estimators for linear state space models is generalised, namely the weighted least-squares approach introduced by Duncan and Horn in 1972, for the case of the two noise processes arising in such models being cross-correlated; in this context, the fact that in the available literature two different non-equivalent recursive algorithms are presented for the task of state estimation in the aforementioned case is discussed. Although the origin of the difference between these two algorithms can easily be identified, the issue has only rarely been discussed so far. Then the situations in which each of the two algorithms apply are explored, and a generalised Kalman filter which represents a merger of the two original algorithms is proposed. While, strictly speaking, optimal state estimates can be obtained only through the non-recursive weighted least-squares approach, in examples of modelling simulated and real-world data, the recursive generalised Kalman filter shows almost as good performance as the optimal non-recursive filter.
Identification Algorithm for Stability Improvement of Welding Robot End-Effector
Authors: Liu Lijian , Zhang Yongkang , Wei Bin , Yang Guang
Published: May 2024

Aiming to solve the problem that the significant error between the actual joint torque and the calculated joint torque of a welding robot leads to the vibration of the end-effector, which in turn affects the stability of the end-effector, this paper proposes a identification algorithm based on the Weighted Least Squares Genetic Algorithm (WLS-GA) to construct and solve the dynamical model to obtain the accurate dynamical parameters. Firstly, a linear model of welding robot dynamics is derived. The fifth-order optimal Fourier series excitation trajectory is designed to collect experimental data such as joint torque. Then, a rough solution of the parameters to be recognized is obtained by solving the dynamics model through the Weighted Least Squares (WLS) method, the search space is determined based on the rough solution, and the optimal solution is obtained by using the Genetic Algorithm (GA) to perform a quadratic search in the search space. Finally, the identification data obtained from the algorithm is analyzed and compared with the experimental data. The results show that the error between the identification data obtained using the WLS-GA identification algorithm and the experimental data is relatively small. The results show that the identification data obtained using the WLS-GA identification algorithm have less error than the experimental data, taking the Root Mean Square (RMS) value of the joint torque error obtained using the weighted least squares algorithm as a criterion. The accuracy of the WLS-GA identification algorithm can be improved by up to 66.85% compared with that of the weighted least squares algorithm and by up to 78.0% compared with that of the Ordinary Least Squares (OLS) algorithm. In summary, the WLS-GA identification algorithm can accurately identify the dynamic parameters of the welding robot and more accurately construct a dynamic model to solve the effect of joint torque error on the control characteristics of the welding robot. It can improve the stability of the end-effector of the welding robot to ensure the quality of the automobile body and beam welding and welding speed.
Defining Terminal Airspace Air Traffic Complexity Indicators Based on Air Traffic Controller Tasks
Authors: Jurinić Tea , Juričić Biljana , Antulov-Fantulin Bruno , Samardžić Kristina
Published: May 2024

This paper focuses on terminal air traffic complexity indicators. By thorough analysis of previous research, the benefits and limitations of the existing terminal complexity models are identified. According to these findings, a new approach for determining terminal air traffic complexity indicators is proposed which assumes that terminal complexity could be determined based on approach air traffic controller (ATCO) tasks. The comprehensive list of general approach ATCO tasks was defined using a literature review and observation of training exercises, forming the basis for subsequent expert group workshops which enabled the acquisition of ATCOs’ knowledge data. Through these workshops, new approach ATCO tasks were additionally identified, and terminal complexity indicators were defined with airspace and traffic parameters. These new tasks and indicators present a novelty in this field of research since they incorporate ATCOs’ knowledge as the data input and consider various traffic scenarios, all types of traffic, weather conditions, and off-nominal situations.
Crop HTP Technologies: Applications and Prospects
Authors: He Shuyuan , Li Xiuni , Chen Menggen , Xu Xiangyao , Tang Fenda , Gong Tao , Xu Mei , Yang Wenyu , Liu Weiguo
Published: May 2024

In order to rapidly breed high-quality varieties, an increasing number of plant researchers have identified the functions of a large number of genes, but there is a serious lack of research on plants’ phenotypic traits. This severely hampers the breeding process and exacerbates the dual challenges of scarce resources and resource development and utilization. Currently, research on crop phenotyping has gradually transitioned from traditional methods to HTP technologies, highlighting the high regard scientists have for these technologies. It is well known that different crops’ phenotypic traits exhibit certain differences. Therefore, in rapidly acquiring phenotypic data and efficiently extracting key information from massive datasets is precisely where HTP technologies play a crucial role in agricultural development. The core content of this article, starting from the perspective of crop phenomics, summarizes the current research status of HTP technology, both domestically and internationally; the application of HTP technology in above-ground and underground parts of crops; and its integration with precision agriculture implementation and multi-omics research. Finally, the bottleneck and countermeasures of HTP technology in the current agricultural context are proposed in order to provide a new method for phenotype research. HTP technologies dynamically monitor plant growth conditions with multi-scale, comprehensive, and automated assessments. This enables a more effective exploration of the intrinsic “genotype-phenotype-environment” relationships, unveiling the mechanisms behind specific biological traits. In doing so, these technologies support the improvement and evolution of superior varieties.
Applying Paraconsistent Annotated Logic Eτ for Optimizing Broiler Housing Conditions
Authors: Martinez Angel Antonio Gonzalez , de Alencar Nääs Irenilza , de Carvalho-Curi Thayla Morandi Ridolfi , Abe Jair Minoro
Published: May 2024

Broilers are particularly sensitive to heat stress, which can impair growth, and lower conversion efficiency and survival rates. Under a climate change scenario, maintaining optimal thermal conditions within broiler houses becomes more complex and energy-intensive. Climate change can worsen air quality issues inside broiler houses by increasing the concentration of harmful gases, and proper mechanical ventilation systems are essential for diluting and removing these gases. The present study aimed to develop and validate a model for the ideal broiler housing strategy by applying the Paraconsistent Annotated Evidential Logic Eτ. A database from four broiler houses in a commercial farm, rearing 157,700 birds from the 1st to the 42nd day of growth, was used in the research. All environmental data were recorded weekly inside the houses, and on day 42, flock mortality, overall feed-to-gain ratio, and body weight were calculated and registered. The Cohen’s Kappa statistics for each environmental parameter classification compared to the paraconsistent classification. Results indicated that temperature shows good agreement, relative humidity shows slight agreement, air velocity presents a good agreement, CO2 concentration has a slight agreement, and NH3 concentration is classified by slight agreement. The environmental and productivity variables as a function of the broiler age using the extreme True paraconsistent state indicate the model validation. The paraconsistent analysis presented the ideal scenario for broilers’ growth, maintaining the environmental variables level within a particular threshold and providing greater profit to broiler farmers.