Scientific Research Research Articles

Effectiveness of an Inquiry-Based Science Program on Enhancing Science Process Skills and Knowledge Among Moroccan Preschool Children

<p style="text-align:justify">This study evaluates the effectiveness of a twelve-week Inquiry-Based Science (IBS) program on enhancing science process skills and scientific knowledge among preschool children in Morocco. Conducted in a quasi-experimental setting, it involved 105 children (M = 60.46 months, SD = 4.32), with 37 in the IBS group and 68 in the control group. The program utilized the 5Es instructional model and the Engineering Design Process (EDP) to engage children in active, hands-on learning experiences. Statistical analysis demonstrated that the IBS group achieved substantial improvements in both science process skills and scientific knowledge relative to the control group, with between-group effect sizes (Cohen’s d) ranging from 1.02 and 2.31. These findings highlight the significant impact of structured inquiry-based approaches in early childhood education. The study underscores the need for integrating such methods into the preschool curriculum to foster scientific understanding and skills from a young age, thereby better preparing Moroccan children for future academic and professional challenges. The results advocate for educational stakeholders to consider adopting inquiry-based learning frameworks to enhance the overall quality of early childhood education in Morocco.</p>

Epigenetics Embedding of Oral Feeding Skill Development in Preterm Infants

Background: Preterm infants face challenges to feed orally, which may lead to failure to thrive. Oral feeding skill development requires intact neurobehaviors. Early life stress results in DNA methylation of NR3C1 and HSD11B2, which may disrupt neurobehaviors. Yet, the extent to which early life stress impairs oral feeding skill development and the biomechanism whereby this occurs remains unknown. Our team is conducting an NIH funded study (K23NR019847, 2022-2024) to address this knowledge gap. Purpose: To describe an ongoing study protocol to determine the extent to which early life stress, reflected by DNA methylation of NR3C1 and HSD11B2 promoter regions, compromises oral feeding skill development. Methods: This protocol employs a longitudinal prospective cohort study. Preterm infants born between 26 and 34 weeks gestational age have been enrolled. We evaluate early life stress, DNA methylation, cortisol reactivity, neurobehaviors, and oral feeding skill development during neonatal intensive care unit hospitalization and at 2-week post-discharge. Results: To date, we have enrolled 70 infants. We have completed the data collection. Currently, we are in the data analysis phase of the study, and expect to disseminate the findings in 2025. Implications for Practice and Research: The findings from this study will serve as a foundation for future clinical and scientific inquiries that support oral feeding and nutrition, reduce post-discharge feeding difficulties and lifelong risk of maladaptive feeding behaviors and poor health outcomes. Findings from this study will also provide further support for the implementation of interventions to minimize stress in the vulnerable preterm infant population.

The Motility Ratio method as a novel approach to qualify semen assessment

AbstractMany scientific studies often assumed that the most reliable methods for assessing sperm motility are those that give the highest values, and this leads to misinterpretation of the results. This study aims to propose an objective method to validate sperm motility reliability. Bovine and porcine semen samples were split into two equal fractions. Fraction A was kept alive with a motile population considered at maximum proportion, while fraction B was killed with 0% motile population. A range of motile/non motile sperm was performed by mixing both fractions. The Motility Ratio method, comparing measured and theoretical motility, was validated using LEJA slide and IVOS II and applied to other slides. All slides showed strong Concordance Correlation Coefficient between measured and theoretical motility. However, with IVOS II, LEJA slide showed the lowest bias (< 1) while MAKLER or coverslip showed higher bias (> 2 and > 7 respectively) between measured and theoretical motility. This study shows that the best sperm motility is not always the true motility and highlights the importance of implementing a gold standard methodology for motility reliability such as The Motility Ratio method.

Artificial intelligence, emotional labor, and the quest for sociological and political imagination among low-skilled workers

Abstract This study examines how generative AI impacts low-skilled workers in their daily professional lives, how it changes the nature of their work, and what, if any, strategies they develop to cope with this new reality. Emphasis is placed on call center agents—an occupational group facing a particularly high automation risk. Drawing on Constructivist Grounded Theory and semistructured interviews in an Austrian call center, we uncover how flawed generative AI tools have increased emotional labor among these workers. This increase is hypothesized to result in agents’ inability to embed their own problems in the larger social context of generative AI’s impact on the labor market, let alone to politicize these problems. They were thus said to lack sociological and political imagination. Our study is the first to link emotional labor with these forms of imagination among low-skilled workers, offering new analytical tools for future research on generative AI’s nuanced effects on the labor market. To empower low-skilled workers, foster their imaginations and address their concerns, we propose several policy recommendations, including targeted education campaigns, enhanced social dialogue, co-determination rights, and tailored upskilling programs. This study thus offers a valuable contribution to scientific research while providing practical implications for policymakers.

Beyond Lux: methods for species and photoreceptor-specific quantification of ambient light for mammals

Abstract Background Light is a key environmental regulator of physiology and behaviour. Mistimed or insufficient light disrupts circadian rhythms and is associated with impaired health and well-being across mammals. Appropriate lighting is therefore crucial for indoor housed mammals. Light is commonly measured in lux. However, this employs a spectral weighting function for human luminance and is not suitable for ‘non-visual’ effects of light or use across species. In humans, a photoreceptor-specific (α-opic) metrology system has been proposed as a more appropriate way of measuring light. Results Here we establish technology to allow this α-opic measurement approach to be readily extended across mammalian species, accounting for differences in photoreceptor types, photopigment spectral sensitivities, and eye anatomy. We develop a high-throughput method to derive spectral sensitivities for recombinantly expressed mammalian opsins and use it to establish the spectral sensitivity of melanopsin from 13 non-human mammals. We further address the need for simple measurement strategies for species-specific α-opic measures by developing an accessible online toolbox for calculating these units and validating an open hardware multichannel light sensor for ‘point and click’ measurement. We finally demonstrate that species-specific α-opic measurements are superior to photopic lux as predictors of physiological responses to light in mice and allow ecologically relevant comparisons of photosensitivity between species. Conclusions Our study presents methods for measuring light in species-specific α-opic units that are superior to the existing unit of photopic lux and holds the promise of improvements to the health and welfare of animals, scientific research reproducibility, agricultural productivity, and energy usage.

Systematic Review of Deep Learning Techniques in Skin Cancer Detection

Skin cancer is a serious health condition, as it can locally evolve into disfiguring states or metastasize to different tissues. Early detection of this disease is critical because it increases the effectiveness of treatment, which contributes to improved patient prognosis and reduced healthcare costs. Visual assessment and histopathological examination are the gold standards for diagnosing these types of lesions. Nevertheless, these processes are strongly dependent on dermatologists’ experience, with excision advised only when cancer is suspected by a physician. Multiple approaches have surfed over the last few years, particularly those based on deep learning (DL) strategies, with the goal of assisting medical professionals in the diagnosis process and ultimately diminishing diagnostic uncertainty. This systematic review focused on the analysis of relevant studies based on DL applications for skin cancer diagnosis. The qualitative assessment included 164 records relevant to the topic. The AlexNet, ResNet-50, VGG-16, and GoogLeNet architectures are considered the top choices for obtaining the best classification results, and multiclassification approaches are the current trend. Public databases are considered key elements in this area and should be maintained and improved to facilitate scientific research.

The next generation of physician-researchers: undergraduate medical students’ and residents’ attitudes, challenges, and approaches towards addressing them

Abstract Background Undergraduate medical education and residency training are critical periods for conducting research. Medical diagnoses and therapies are direct results of successful research efforts that have advanced several scientific fields. This review highlights the importance of incorporating scientific research training into the curricula of undergraduate medical education and residency programs. Methods We utilized key databases such as PubMed, Web of Science, and Google Scholar to conduct a narrative review of English-language articles published between 2002 and 2024. Ultimately, we selected 49 studies that examined the attitudes of undergraduate medical students and residents toward research, the common challenges they encounter while participating in research activities, and the strategies that support and encourage their involvement, all in alignment with our study objectives and keywords. In addition, we identified several relevant themes, including the value of research experience in shaping well-rounded medical professionals; the integrity of research practices in residency selection, which addresses concerns such as the arms race and misrepresentation, as well as the balance between quality and quantity; striking a balance between research and clinical training while promoting equity and inclusion; and effective programs and mentorship strategies to enhance research engagement. Results Translating the positive attitudes of undergraduate medical students and residents into improved knowledge and practice necessitates the development of structured mentoring programs and advanced training systems. Institutions must provide the necessary tools, guidance, and support to overcome research barriers. This will help establish an environment in undergraduate medical education and residency training that values research, facilitates access to it, and integrates it into the curriculum. Conclusions To address the critical shortage of physician-researchers and improve evidence-based medical practice, it is crucial for medical schools to focus on research education and create avenues for student involvement. By tackling research challenges and implementing supportive strategies, these efforts empower the next generation of physician-researchers to embrace research, contribute to medical progress, and uphold the highest standards of patient care.

How Are The Science Process Skills of Prospective Science Teacher Students: Studies in Inorganic Chemistry and Gender

Prospective teacher students must be able to design practicums so that the learning process is meaningful. The skills that students develop in carrying out scientific discoveries, namely applying concepts, rules, and characteristics that exist in science, are called science process skills (SPS). Therefore, in building students' knowledge, students must have process skills in teaching so they can teach effectively and must have a good understanding of concepts and strong process skills. This research aims to describe the SPS of prospective science education teacher students through inorganic chemistry courses after going through learning with the discovery learning model. This research uses a quantitative approach with a pre-experimental design one-shot case study research method. The research results show that student SPS as a whole is in the high category with an average percentage of 59.71%. SPS analysis in classes A, B, and C, respectively, has an average percentage of 58.23%, 62.66%, and 58.24% in the high category. SPS analysis based on gender shows that the respective percentage of male students is 53.89% with the medium category for women and 59.81% for the high category.

Lessons from the SARS-CoV-2 Pandemic: Perspectives in the Medico-Legal Field

Background: The SARS-CoV-2 pandemic led to an enormous global health, social and economic crisis. The pandemic caused considerable upheaval and considerable difficulties due to an unforeseen and devastating health condition. Materials and Methods: We discuss the numerous challenges encountered in the fields of forensic medicine and public health during the COVID-19 pandemic. Particularly during the first wave of the pandemic, forensic pathologists faced significant difficulties due to the lack of safe autopsy protocols and insufficient personal protective equipment. Mainly in Europe, they had to manage a substantial number of potential cases of medical liability related to COVID-19. The widespread outbreak of the virus in residential care homes and prisons posed another significant challenge. Furthermore, forensic pathologists had to address the issue of complications arising from vaccination campaigns. Conclusions: This article underscores the need for continued efforts in scientific research and healthcare preparedness to effectively manage such complex crises. Forensic pathologists must be equipped with the necessary resources and training to address unpredictable, complex situations with far-reaching social implications.

Factors Influencing Hotel Revenue Management in Times of Crisis: Towards Financial Sustainability

(1) Background: Facing the challenges of a post-pandemic period and the Ukraine War and recognising the gap in scientific research on the application of revenue management (RM) in the Portuguese hotel industry, the main objective of this study is to identify the most effective and least appropriate RM practices for use in periods of low demand and crises, reflecting the financial sustainability perspective. The theoretical framework of this study focuses on the main RM practices, grouping them into price and non-price strategies. (2) Methods: A quantitative methodology was employed, collecting information from Portuguese hotels through an online questionnaire, and statistical analysis using Mann–Whitney and Chi-square tests was conducted. (3) Results: Hotels offered discounts during the pandemic, but room rates were reduced during the recovery period. These findings also revealed that commonly used techniques were the best available rate (BAR) and rate fences, particularly during the pandemic. Quality, brand image, strategic partnerships, and marketing actions are recognised as essential. However, loyalty programs, length of stay (LOS) control, rate parity, and bundled services are not commonly implemented despite their importance during periods of low demand. Larger hotels, five-star hotels, and members of international chains applied more RM practices than smaller four-star independent hotels. (4) Originality: This study provides original and valuable insights into increasing hotel revenues and occupancy rates during future periods of low demand, which benefit financial sustainability.

Do scientific attitude and intelligence affect motivation towards STEM? Structural equation modelling

IntroductionThe aim of this study is to reveal the effect of scientific attitude and intelligence on STEM (science, technology, engineering and mathematics) motivation using Structural Equation Modelling (SEM). It is possible to say that there is a reciprocal relationship between attitudes towards science, intelligence and motivation towards STEM. Motivation is closely and positively related to STEM, scientific attitude, intelligence and organizational development. When female students are supported and motivated positively, it is possible for them to be successful in STEM. It is possible to say that female students are the female leadership candidates of the future. Female leader candidates can play a role in future organizational development. Female leader candidates who are supported and motivated by their environment can take their place in organizational development. There is a gap in the research literature on this subject in Türkiye. This study fills an important gap in terms of sampling, research method and data analysis.MethodIn the study, personal information form, Attitude Towards Scientific Research Scale, Multiple Intelligences Self-Perception Scale and STEM Value-Expectation Rating Scale were applied to 159 female undergraduate students who are disadvantaged in STEM field and studying at Ege University Ödemiş Faculty of Health Sciences.ResultsIt is possible to say that most female students have positive attitudes towards scientific research. According to the research results, as the reluctance to help researchers and negative attitudes towards research increase, motivation towards STEM decreases. As positive attitudes towards research and researchers increase, motivation towards STEM increases. In addition, increases in verbal–linguistic intelligence, logical-mathematical intelligence, spatial intelligence, interpersonal intelligence, intrapersonal intelligence and natural intelligence lead to an increase in positive attitudes towards research and thus STEM motivation.ConclusionWhen the value expectations of future female leadership candidates for the STEM field were evaluated, it was found that 81.13% of the students had a medium level of value expectation evaluation level for the STEM field. This situation suggests that female students are not positively motivated for STEM in the family, school and peer environment.

Early scientific research training links to the innovation ability of medical undergraduates and postgraduates

Scientific research training (SRT) is crucial for fostering skills and innovation in college students. However, the status of SRT in medical undergraduates and postgraduates, as well as the impact of early SRT on students’ innovation abilities, remain largely unknown. This study assessed the role of SRT in culturing innovation abilities among medical students. The results revealed that undergraduates exhibited a greater understanding of scientific research compared to postgraduates. Notably, undergraduates demonstrated a higher level of understanding of SRT in contrast to postgraduates (81.26% vs. 56.97%). A significant proportion (>70%) of undergraduates had engaged in research activities early in their academic journey, with an average participation duration exceeding 1 year. Moreover, undergraduates initiated their involvement in SRT during the first- and second- year of undergraduates, which was earlier than postgraduates. Personal interest emerged as a primary motivator for engaging in SRT, with postgraduates exhibiting higher research aspirations and achieving greater research outcomes. Postgraduates also received more substantial guidance from advisors, leading to enhanced academic performance compared to undergraduates (90.7% vs. 67.59%). Interestingly, students expressed satisfaction with laboratory conditions and attributed their academic success to personal efforts. These findings underscore the importance of early SRT in cultivating the innovation abilities of medical students.

Investigation of the Effective Numerical Model for Seismic Response Analysis of Concrete-Faced Rockfill Dam on Deep Overburden

The construction of high rockfill dams on deep overburden in seismically active regions poses significant challenges. Currently, there are no standardized guidelines for defining the computational domain range in seismic analysis, necessitating the establishment of a universally applicable computational domain range that optimizes the balance between computational accuracy and efficiency. This has critical engineering implications for the seismic analysis of rockfill dams on deep overburden. This study employed the seismic wave input method to consider the dynamic interaction between the dam, overburden, and infinite domain. A systematic investigation was conducted on a concrete-faced rockfill dam (CFRD) constructed on deep overburden, considering the influences of overburden thickness, dam height, overburden properties, soil layer configuration, ground motion intensity, and the frequency content of the seismic waves. The acceleration response and seismic deformation of the dam were analyzed. Subsequently, the computational domain range corresponding to various levels of acceptable engineering precision was established. The results indicated that the lateral boundary length should extend a minimum distance equal to the sum of 3 times the overburden depth and 1.2 times the maximum dam height. Additionally, the depth below the overburden–bedrock interface should extend at least 1.2 times the maximum dam height. This study provides a crucial foundation for determining the optimal computational domain range in the seismic analysis of rockfill dams constructed on deep overburden.

Review of the book title: recommendations for increasing physical activity after the Covid-19 pandemic

Recommendations for Increasing Physical Activity after the COVID-19 Pandemic focuses on the importance of physical activity, especially after the pandemic, which significantly impacted the lifestyle of many people. The book starts with an analysis of the pandemic's effects on people's physical habits, highlighting a decline in physical activity and an increase in sedentary behaviour. It is followed by recommendations and practical exercises aimed at helping individuals improve their physical fitness and overall health. The book provides a detailed examination of how lockdowns and other restrictions led to decreased physical activity. This section is well-supported by data and scientific studies. The author includes practical guidelines for various types of exercises that are accessible to the general public. Detailed descriptions and step-by-step instructions on how to perform these exercises are included.

Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol

Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. Notably, abnormal cholesterol levels are a well-established indicator of various pathological conditions; yet, the quantitative detection of the free form of cholesterol is complicated by its small molecular size, pronounced hydrophobicity, and the necessity for mediator molecules to achieve efficient sensing. In the present study, a novel strategy for cholesterol quantification was developed, leveraging a plasmonic optical readout in conjunction with a highly specific cholesterol-binding peptide (C-pept) as a biorecognition element, anchored on a functionalized silica substrate. The resulting biosensor exhibited an exceptionally low detection limit of 21.95 µM and demonstrated a linear response in the 10–200 µM range. This peptide-integrated plasmonic sensor introduces a novel one-step competitive method for cholesterol quantification, positioning itself as a highly sensitive biosensing modality for implementation within the AVAC platform, which operates using reflective dark-field microscopy.

A comprehensive study of common and rare genetic variants in spermatogenesis-related loci identifies new risk factors for idiopathic severe spermatogenic failure

Abstract STUDY QUESTION Can genome-wide genotyping data be analysed using a hypothesis-driven approach to enhance the understanding of the genetic basis of severe spermatogenic failure (SPGF) in male infertility? SUMMARY ANSWER Our findings revealed a significant association between SPGF and the SHOC1 gene, and identified three novel genes (PCSK4, AP3B1, and DLK1) along with 32 potentially pathogenic rare variants in 30 genes that contribute to this condition. WHAT IS KNOWN ALREADY SPGF is a major cause of male infertility, often with an unknown aetiology. SPGF can be due to either multifactorial causes, including both common genetic variants in multiple genes and environmental factors, or highly damaging rare variants. Next-generation sequencing (NGS) methods are useful for identifying rare mutations that explain monogenic forms of SPGF. Genome-wide association studies (GWAS) have become essential approaches for deciphering the intricate genetic landscape of complex diseases, offering a cost-effective and rapid means to genotype millions of genetic variants. Novel methods have demonstrated that GWAS datasets can be used to infer rare coding variants that are causal for male infertility phenotypes. However, this approach has not been previously applied to characterize the genetic component of a whole case-control cohort. STUDY DESIGN, SIZE, DURATION We employed a hypothesis-driven approach focusing on all genetic variation identified, using a GWAS platform and subsequent genotype imputation, encompassing over 6 million polymorphisms and a total of 1571 SPGF patients and 2431 controls. Both common (minor allele frequency, MAF > 0.01) and rare (MAF < 0.01) variants were investigated within a total of 1797 loci with a reported role in spermatogenesis. This gene panel was meticulously assembled through comprehensive searches in the literature and various databases focused on male infertility genetics. PARTICIPANTS/MATERIALS, SETTING, METHODS This study involved a European cohort using previously and newly generated data. Our analysis consisted of three independent methods: (1) variant-wise association analyses using logistic regression models, (2) gene-wise association analyses using combined multivariate and collapsing (CMC) burden tests, and (3) identification and characterisation of highly damaging rare coding variants showing homozygosity only in SPGF patients. MAIN RESULTS AND THE ROLE OF CHANCE The variant-wise analyses revealed an association between SPGF and SHOC1-rs12347237 (p = 4.15E-06, OR = 2.66), which was likely explained by an altered binding affinity of key transcription factors in regulatory regions and the disruptive effect of coding variants within the gene. Three additional genes (PCSK4, AP3B1, and DLK1) were identified as novel relevant players in human male infertility using the gene-wise burden test approach (p < 5.56E-04). Furthermore, we linked a total of 32 potentially pathogenic and recessive coding variants of the selected genes to 35 different cases. LARGE SCALE DATA Publicly available via GWAS catalog (Accession number: GCST90239721). LIMITATIONS, REASONS FOR CAUTION The analysis of low-frequency variants presents challenges in achieving sufficient statistical power to detect genetic associations. Consequently, independent studies with larger sample sizes are essential to replicate our results. Additionally, the specific roles of the identified variants in the pathogenic mechanisms of SPGF should be assessed through functional experiments. WIDER IMPLICATIONS OF THE FINDINGS Our findings highlight the benefit of using GWAS genotyping to screen for both common and rare variants potentially implicated in idiopathic cases of SPGF, whether due to complex or monogenic causes. The discovery of novel genetic risk factors for SPGF and the elucidation of the underlying genetic causes provide new perspectives for personalized medicine and reproductive counselling. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by the Spanish Ministry of Science and Innovation through the Spanish National Plan for Scientific and Technical Research and Innovation (PID2020-120157RB-I00) and the Andalusian Government through the research projects of “Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI 2020)” (ref. PY20_00212) and “Proyectos de Investigación aplicada FEDER-UGR 2023” (ref. C-CTS-273-UGR23). SGM was funded by the previously mentioned projects (ref. PY20_00212 and PID2020-120157RB-I00). AGJ was funded by MCIN/AEI/10.13039/501100011033 and FSE “El FSE invierte en tu futuro” (grant ref. FPU20/02926). IPATIMUP integrates the i3S Research Unit, which is partially supported by the Portuguese Foundation for Science and Technology (FCT), financed by the European Social Funds (COMPETE-FEDER) and National Funds (projects PEstC/SAU/LA0003/2013 and POCI-01-0145-FEDER-007274). SS is supported by FCT funds (10.54499/DL57/2016/CP1363/CT0019), ToxOmics-Centre for Toxicogenomics and Human Health, Genetics, Oncology and Human Toxicology, and is also partially supported by the Portuguese Foundation for Science and Technology (UIDP/00009/2020 and UIDB/00009/2020). SLarriba received support from Instituto de Salud Carlos III (grant: DTS18/00101], co-funded by FEDER funds/European Regional Development Fund (ERDF)-a way to build Europe-), and from “Generalitat de Catalunya” (grant 2021SGR052). SLarriba is also sponsored by the “Researchers Consolidation Program” from the SNS-Dpt. Salut Generalitat de Catalunya (Exp. CES09/020). All authors declare no conflict of interest related to this study.

Hybrid Oversampling and Undersampling Method (HOUM) via Safe-Level SMOTE and Support Vector Machine

The improvements in collecting and processing data using machine learning algorithms have increased the interest in data mining. This trend has led to the development of real-life decision support systems (DSSs) in diverse areas such as biomedical informatics, fraud detection, natural language processing, face recognition, autonomous vehicles, image processing, and each part of the real production environment. The imbalanced datasets in some of these studies, which result in low performance measures, have highlighted the need for additional efforts to address this issue. The proposed method (HOUM) is used to address the issue of imbalanced datasets for classification problems in this study. The aim of the model is to prevent the overfitting problem caused by oversampling and valuable data loss caused by undersampling in imbalanced data and obtain successful classification results. The HOUM is a hybrid approach that tackles imbalanced class distribution challenges, refines datasets, and improves model robustness. In the first step, majority-class data points that are distant from the decision boundary obtained via SVM are reduced. If the data are not balanced, SLS is employed to augment the minority-class data. This loop continues until the dataset becomes balanced. The main contribution of the proposed method is reproducing informative minority data using SLS and diminishing non-informative majority data using the SVM before applying classification techniques. Firstly, the efficiency of the proposed method, the HOUM, is verified by comparison with the SMOTE, SMOTEENN, and SMOTETomek techniques using eight datasets. Then, the results of the W-SIMO and RusAda algorithms, which were developed for imbalanced datasets, are compared with those of the HOUM. The strength of the HOUM is revealed through this comparison. The proposed HOUM algorithm utilizes a real dataset obtained from a project endorsed by The Scientific and Technical Research Council of Turkey. The collected data include quality control and processing parameters of yarn data. The aim of this project is to prevent yarn breakage errors during the weaving process on looms. This study introduces a decision support system (DSS) designed to prevent yarn breakage during fabric weaving. The high performance of the algorithm may encourage producers to manage yarn flow and enhance the HOUM’s efficiency as a DSS.

Inverse Cherenkov dielectric laser accelerator with alternating phase focusing for subrelativistic particles

In this paper, we propose a dielectric laser acceleration scheme based on the inverse Cherenkov effect, which uses the principle of alternating phase focusing to accelerate, confine, and bunch the subrelativistic electron beam over an extended distance. In this scheme, the reference electron is always synchronized with the acceleration wave and is thus continuously accelerated. Electrons around it are alternately subjected to focusing and defocusing forces by alternately jumping its phase. Optimizing the focusing period can achieve stable beam confinement. Simulations show that a 100 keV electron bunch can be coherently accelerated with the average acceleration gradient of 220.8 MV/m, and it can travel nearly 200 μm without loss in a channel only 500 nm wide. This approach is scalable, potentially enabling the development of millimeter-scale MeV particle accelerators for ground-breaking use in medical, scientific, and materials research. Published by the American Physical Society 2024

Participatory science and course-based undergraduate research experience to improve research-informed teaching of evolution and palaeontology

AbstractThis study introduces a participatory science-inspired approach to teaching and curriculum design, involving undergraduate students directly in active research. Using a case study on dinosaur eye size, integrated into a first-year undergraduate course in Geology and Palaeontology at a UK university, this study presents the advantages and disadvantages of this approach for both teachers and learners. As part of the study, 22 undergraduate students were involved in data collection, analysis, and the subsequent publication processes, emphasizing active student participation in research. A subsequent survey demonstrated high student engagement and perceived relevance of this participatory science-style teaching approach. Results indicate that students found the approach appealing, engaging, and beneficial for understanding scientific concepts and methods. The case study shows that a participatory science approach through a course-based research experience can enhance student engagement and learning by providing meaningful, hands-on research experiences. This approach allowed students to apply theoretical knowledge in a realistic context, fostering their understanding of evolutionary theory through active data collection and analysis. However, care should be taken concerning data accuracy and ethical aspects, such as exploitation of labour and the recognition of knowledge creators and participants. Despite these challenges, the benefits of integrating such approaches into higher education curricula can be substantial, offering a valuable model for teaching evolutionary theory and related topics.

Does the COVID-19 Vaccines Effect on the Menstrual Cycle, Cross-Sectional Study Among Adult Females at King Saud University

COVID-19 vaccinations have been associated with irregularities in the menstrual cycle and symptoms occurring pre and post-menstruation, affecting women’s reproductive health. This study aimed to demonstrate the impact of COVID-19 vaccines on women’s reproductive health by examining the association between COVID-19 vaccines and disturbed menstrual cycles. This cross-sectional survey-based study was conducted among adult females at King Saud University, Saudi Arabia, from April 2022 to August 2022. A total of 380 participants were selected through a stratified random sampling technique. Ethical approval was obtained from the Deanship of Scientific Research at King Saud University. The data were analysed using descriptive statistics and appropriate statistical tests. The results revealed that 53.9% of the participants experienced disturbances in the menstrual cycle after receiving the COVID-19 vaccination. Adult females aged 18-25 showed the highest rate of disorders. Menstrual disruptions were substantially correlated with marital status (p = 0.05), with a significant association between the number of COVID-19 vaccine doses and the occurrence of menstrual disturbances (p = 0.001). The administration of the vaccination during menstruation was linked to a notable occurrence of menstrual disturbances, although the p-value showed no statistical significance. A significant correlation was examined (p < 0.05) between pre-existing menstrual problems and the occurrence of disorders after receiving the COVID-19 vaccine (p < 0.05). The study emphasised the importance of tailored healthcare treatments for women following COVID-19 vaccination and the need for regular evaluation of reproductive health outcomes post-COVID-19 vaccination.