bluuebunny/crossref_metadata_2025 huggingface dataset:
Transdisciplinary Innovations in Athlete Health: 3D Printable- Wearable Sensors for Health Monitoring and Sports Psychology
Authors: Sekeroglu Mustafa Onder , Pekgor Metin , Algin Aydolu , Toros Turhan , Serin Emre , Uzun Meliha , Cerit Gunay , Onat Tugba , Ermis Sermin Agrali
Published: January 2025

The integration of 3D printing technology into sensor development holds transformative potential for sports psychology, offering innovative solutions for monitoring athlete health and enhancing performance. Various theories have been established to explain how different levels and types of arousal impact athletic performance, providing valuable frameworks for optimizing athletes’ well-being and performance. By incorporating wearable sensors into sports psychology, professionals can gain deeper insights into athletes’ arousal and emotional states, enabling more precise assessments and interventions that lead to improved outcomes. This article explores the application of wearable sensors in sports, with a particular focus on 3D printable sensors that measure both physiological and psychological parameters in real time. These advanced sensors provide coaches and sports psychologists with critical data, allowing them to tailor interventions and strategies more effectively to each athlete’s unique needs. The real-time data collection enabled by these sensors offers a dynamic approach to managing athlete performance and well-being. Furthermore, the article outlines future directions for sports psychology, emphasizing the importance of interdisciplinary collaboration and the integration of technological advancements, such as artificial intelligence. By harnessing these innovative tools, sports psychology can significantly enhance athlete resilience and performance, paving the way for a more comprehensive understanding of the complex relationship between mental states and athletic achievement. This approach not only advances the field but also contributes to the overall well-being and success of athletes in a highly competitive environment.
Age-Related Dynamics in Endometrial Vascularity: A Comprehensive 3D Ultrasound Evaluation During Follicular and Luteal Phases
Authors: Ahmed Badreldeen , Justin Justin Chi
Published: January 2025

Objective: Transvaginal ultrasonography plays a crucial role in contemporary fertility management, offering insights into uterine and endometrial blood flow. Three-dimensional ultrasonography utilizing power Doppler angiography (3D-CPA) allows precise measurement of endometrial volume and vascular parameters, including the vascularization index (VI), blood flow index (FI), and vascularization flow index (VFI); variables which indirectly assess endometrial receptivity and integrity. Doppler technology allows for the captures of changes in the uterus induced by hormonal-related fluctuations during the menstrual cycle, revealing a significant correlation between endometrial receptivity and vascularity. Age-related changes in endometrial function are implicated in declining fertility, with limited research exploring this aspect. The aim of this study was to investigate the impact of aging on various ultrasound parameters of the uterus including endometrial vascularity.
Methods: A retrospective cross-sectional study of women who attended the Feto-Maternal Centre from January 2022 to December 2023. Each woman whose menstrual cycle was regular underwent 3D ultrasound with power Doppler as part of the routine assessment of the pelvis. Parameters assessed include the VI, FIand VFI as well as uterine volume, endometrial volume, and endometrial thickness. The women were grouped based on age and the variables measured in the follicular and luteal phases were compared between the age groups using SPSS.
Results: A total of 907 women (427 follicular and 480 luteal phase) were studied. 297 (131 follicular and 166 luteal) were 20-29 years; 471 (240 follicular and 231 luteal) were aged 30-39 and 139 (56 follicular and 83 luteal) were aged 40-49. Uterine volume, endometrial volume and thickness increased significantly and steadily with age. VI, VFI and FI decreased significantly with age in the follicular phase but in the luteal phase there was no statistically significant difference in any of these indices with age.
Conclusion: Uterine volume, endometrial thickness, and endometrial volume increased with age, but the vascular indices decreased with age in the follicular but not in the luteal phase. These age-related changes in endometrial vascularity may partly explain the decrease in age-related fertility. Further research is needed to comprehensively explore the complexities of uterine aging and its implications for female fertility.
LncRNAs Regulate Vasculogenic Mimicry in Human Cancers
Authors: Ibarra-Sierra Eloísa , Bermúdez Mercedes , Villegas-Mercado Carlos Esteban , Silva-Cázares Macrina B. , López-Camarillo César
Published: January 2025

: Vasculogenic mimicry (VM) has been recently discovered as an alternative mechanism to nourish cancer cells in vivo. During VM, tumor cells align and organize in three-dimensional (3D) channel-like structures to transport nutrients and oxygen to the internal layers of tumors. This mechanism occurs mainly in aggressive solid tumors and has been associated with poor prognosis in oncologic patients. Long non-coding RNAs (lncRNAs) are essential regulators of protein-encoding genes involved in cancer development and progression. These single-stranded RNA molecules regulate critical cellular functions in cancer cells, including cell proliferation, apoptosis, angiogenesis, VM, therapy response, migration, invasion, and metastasis. Recently, high-throughput RNA sequencing technologies have identified thousands of lncRNAs, but only a tiny percentage have been functionally characterized in human cancers. The vast amount of data about its genomic expression in tumors can allow us to dissect their functions in cancer biology and make them suitable biomarkers for cancer diagnosis and prognosis. Here, we have reviewed the current knowledge about the role of lncRNAs in VM in human cancers, with a special emphasis on their potential to be used as novel therapeutic targets in RNA-based molecular interventions.
The Impact of Syphilis on HIV Acquisition and Progression in Sub-Saharan Africa
Authors: Gandla Sindhuri , Nakka Raja , Khan Ruhul Ali , Salboukh Fatemeh , Ghebremichael Musie
Published: January 2025

Most people living with HIV (PLWH) are co-infected with syphilis or other sexually transmitted infections (STIs) and experience frequent reactivations of syphilis. Thus, syphilis or other STIs are highly prevalent in most regions experiencing severe HIV epidemics. In sub-Saharan Africa, the region most heavily affected by HIV, the prevalence of syphilis among PLWH is approximately 7.3%. This region accounts for 40% of global STIs and 70% of HIV cases, highlighting the need for targeted research. Despite the high prevalence of syphilis among PLWH in the region, the impact of syphilis on HIV transmission and HIV disease progression has not been well-studied. In this manuscript, we evaluated if syphilis facilitates HIV acquisition and HIV disease progression in the region. We used retrospective data from 53,915 adult participants enrolled through Population-based HIV Impact Assessment (PHIA) surveys conducted in Zambia and Tanzania. Logistic regression models were used to assess the impact of syphilis on HIV acquisition and disease progression. Our findings indicated that syphilis infection was associated with higher odds of HIV acquisition. Moreover, co-infection with syphilis was associated with higher odds of HIV disease progression among PLWH treated with antiretroviral therapy (ART). Our findings suggested that the recognition, treatment, and prevention of syphilis to reduce the risk of HIV transmission and HIV disease progression should be a public health priority in sub-Saharan Africa, where ART may not be readily available.
Surgeon Training in the Era of Computer Enhanced Simulation Robotics and Emerging Technologies: A Narrative Review
Authors: Keelan Simon , Guirgis Mina , Julien Benji , Hewett Peter , Talbot Michael
Published: January 2025

Background:
Teaching methodology has recently undergone significant evolution from traditional apprenticeship models as we adapt to ever increasing rates of technological advancement. Big data, artificial intelligence and machine learning are on the precipice of revolutionizing all aspects of surgical practice with far reaching implications. Robotic platforms will increase in autonomy as machine learning rapidly becomes more sophisticated and therefore training requirements will no longer slow innovation.

Materials and Methods:
Search of published studies discussing surgeon training and computer enhanced simulation robotics and emerging technologies using MEDLINE, PubMed, EMBASE, Scopus, CRANE, CINAHL and Web of Science was performed January 2024. Online resources associated with proprietary technologies related to the subject matter were also utilised.

Results:
Following review of 3209 articles, 91 published, relevant articles on aspects of robotics-based computer enhanced simulation, technologies and education were included. Publications ranged from RCTs, cohort studies, meta-analysis and systematic reviews. Eight medical technology-based website content were analysed and included in this review to ensure the most up-to-date information was analysed.

Discussion:
Surgeons should aim to be at the forefront of this revolution for the ultimate benefit of patients. Surgical exposure will no longer be due to incidental experiences. Rather, surgeons and trainees will have access to a complete database of simulated minimally invasive procedures and procedural simulation certification will likely become a requisite from graduation to live operating to maintain rigorous patient safety standards. This review provides a comprehensive outline of the current and future status of surgical training in the robotic and digital era.
Electrochemical Synthesis and Characterization of Ag-Re Coatings
Authors: Bersirova Oksana , Kublanovsky Valeriy , Kochetova Svetlana , Bondar Olena
Published: January 2025

Silver-white, matte, smooth, and durable deposits of silver-rhenium, with thicknesses ranging from 2.0 to 13.7 μm and containing 0.15 to 13.5 wt.% Re, were obtained with a current efficiency of 66-98% from a developed dicyanoargentate-perrhenate bath based on a borate-phosphate-carbonate silver-plating electrolyte. The study was focused on the influence of bath composition, the [Ag(I)]:[ReO4-] ratio, surfactant additives, applied current density, temperature, and stirring, on the alloys composition, structure, morphology, microhardness, adhesion, and porosity. A voltammetric analysis was conducted, considering the influence of ethanolamines on electrode processes. In baths with TEA, coatings similar to a silver matrix with rhenium doped in mass fractions are likely achievable. MEA is recommended due to its process-activating properties. All coatings were nanocrystalline (τ = 28.5 - 35 nm). For deposits containing less than 10 wt.% Re, characteristic silver XRD peaks were observed, while other deposits, additional peaks attributed probably to Re(VII) and Re(VI) oxides. A linear relationship, typical for Hall-Petch plots, was obtained, confirming that grain boundaries play a crucial role in mechanical properties of coatings. The conditions for stable electrochemical synthesis of promising functional Ag-Re coatings of predetermined composition (0.7-1.5 wt.% Re) were proposed for practical use in power electronics and energy sectors, for manufacturing electrical contacts operating across a wide temperature range. This was realized by deposition from an Ag-rich bath in the area of mixed electrochemical kinetics, at potential values corresponding to the region of half the limiting current: j = 2.5 ‒ 6 mA cm-2, t = 19 - 33°C.
Machine Learning Algorithms and Nondestructive Methods for Estimating Wood Density in Planted Forest Trees
Authors: Mansini Lorensani Rafael Gustavo , Gonçalves Raquel
Published: January 2025

Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees, aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, Extreme Gradient Boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R²) of 89% and a root mean square error (RMSE) of 10.6 kg·m⁻³. In contrast, the conventional statistical model, using the same parameters, yielded an R² of 33% and an RMSE of 26.4 kg·m⁻³. These findings highlight the superior performance of machine learning in nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry.
Determinants of Cleaner Cooking Fuel Choice: A Study of Two Riparian Communities in Ghana
Authors: Codjoe Ann Bretaah , Quansah Reginald , Boateng Godfred O.
Published: January 2025

Background: Transitioning to clean energy at the household level has been challenging for most households in Low—and Middle-Income Countries. However, there is a dearth of research on what informs the choice of cleaner fuel for cooking. Therefore, this study examined the predictors of cleaner household cooking fuel in rural and peri-urban set-tings among primary cooks in Ghana.
Methodology. Data for this study were drawn from the Briquette for Cooking Fuel Project (B4CcokingF) launched in 2018 by the Volta River Authority and the University of Ghana School of Public Health to manage invasive aquatic weeds. Data were collected on the primary, secondary and tertiary fuel used, sociodemographic characteristics, and waste management measures from two riparian communities. With an analytical sample of 420, we used multinomial logistic regression to assess the determinants of clean fuel choices.
Results: Of the 420 primary cooks interviewed, 59.2% were below 40 yrs, 79% had primary school education, and 78.8% lived in peri-urban settings. Most households used charcoal as their primary fuel (64.49%), wood fuel (44.29%) as secondary fuel, and liquefied petroleum gas (LPG) as the primary tertiary fuel (48.84%). Using bivariate and multivariable models, household heads with tertiary education, waste collection by waste management companies, and increased household wealth were identified as significant predictors of cleaner cooking fuel choice.
Conclusion: Policies that focus on advancing higher education, increasing environmental consciousness, and transitioning people out of poverty are necessary to reduce the use of solid fuels and transition most households to using cleaner and sustainable cooking en-ergy sources.
Mating Increases CHST10 Activity in the Oviductal Mucosa to Induce the Synthesis of HNK-1 Glycoproteins: The Possible Role of HNK-1-ALDH9A1 in Sperm–Oviduct Interactions
Authors: Fábrega-Guerén Francisca , Andrade JC , Zúñiga-Cóndor Marlene , Morales Patricio , Gómez-Silva Benito , Zúñiga Lidia M
Published: January 2025

Previously, we reported that mating induces an early transcriptional response in the oviductal mucosa of rats. The functional category ‘cell-to-cell signaling and interaction’ was overrepresented in this gene list. Therefore, in the present study, we describe the role of one of these genes, carbohydrate sulfotransferase 10 (Chst10), in the oviductal mucosa. CHST10 participates in the synthesis of the carbohydrate moiety HNK-1, which mediates cell-to-cell interactions. Using 1D western blot and sulfotransferase assays, we showed that mating increased the protein level and activity of CHST10 in the oviductal mucosa at 3 h after stimulation. A 2D western blot assay and mass spectrometry were used to identify the novel HNK-1 glycoproteins ALDH9A1, ALDOA and FHL1 in the oviductal mucosa, and we showed that mating induces the synthesis of their acidic variants. Interestingly, in the utero-tubal junction (UTJ), acrosome-reacted sperm are in close contact with HNK-1-ALDH9A1 regions, and acrosome-intact sperm are in close contact with other regions in which HNK-1 and ALDH9A1 do not colocalize. Furthermore, vaginocervical stimulation applied to unmated rats increases the mRNA level of Chst10 in the oviductal mucosa. In conclusion, mating increases the activity of CHST10 in the oviductal mucosa, which in turn induces the synthesis of acidic variants of ALDH9A1 and FHL1 via HNK-1 glycosylation. In the UTJ, HNK-1-ALDH9A1 can control the quality of the sperm arriving at the fertilization site, since we detected acrosome-reacted sperm in close contact with this glycoprotein, a finding that merits further research to propose the use of HNK-1-ALDH9A1 in the selection of sperm in procedures of assisted reproduction. Finally, the sensorial component of mating could regulate events occurring in the oviductal mucosa early after mating.
Calculation of α Decay Half-Lives for Tl, Bi and at Isotopes
Authors: Mun Myeong-Hwan , Heo Kyoungsu , Cheoun Myung-Ki
Published: January 2025

We investigated the reaction Q-value (Qα) for the α decay of Tl, Bi, and At isotopes using the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) with the covariant density functional PC-PK1. The α decay half-lives of Tl, Bi, and At isotopes are evaluated using various empirical formulas, based on both experimental Qα and those obtained from DRHBc calculations. The calculated Qα and α decay half-lives are compared with experimental data. On the basis of these results, we also predicted the α decay half-lives of isotopes for which experimental data are unavailable.
The Effect of the Ideal Food Pyramid on Gut Microbiota in Rheumatoid Arthritis Patients
Authors: Kaçar Mutlutürk Ülger , Çiçek Betül , Cengiz Gizem
Published: January 2025

Background: Rheumatoid arthritis (RA) is a dysbiosis of the gut microbiota, and diet is one of the powerful environmental factors that can alter the microbiota. The aim of the clinical study was to determine the effect of the Ideal Food Pyramid on gut microbiota in RA patients; as well as its effect on disease activity, biochemical findings and anthropometric measurements.
Methods: Thirty patients diagnosed with RA who met the inclusion criteria were randomly divided into diet and control groups and followed for 12 weeks. Gut microbiota composition was determined by 16S rRNA gene sequencing.
Results: At the end of the study, Simpson, Shannon and Chao-1 indices were higher in the diet group (16) than in the control group (14), although not significantly (p>0.05). At the phylum level, the relative abundance of Firmicutes increased and the abundance of Bacteroidetes decreased in the diet group at the end of the trial. At species level, Prevotella Copri, Bacteroides fragilis, Prevotella stercorea, Bacteroides uniformis decreased while Faecalibacterium prausnitzii, Roseburia faecis, Bacteroides ovatus, Akkermansia muciniphila, Coprococcus eutactus, Gemmiger formicilis, Ruminococcus bromii, Bifidobacterium longum species increased in the diet group.
Conclusion: The Ideal Food Pyramid has been determined to have many clinical benefits for RA patients, especially for the gut microbiota.
EEGDataAugmentation Method Based on the Gaussian Mixture Model
Authors: Liao Chuncheng , Zhao Shiyu , Wang Xiangcun , Zhang Jiacai , Liao Yongzhong , Wu Xia
Published: January 2025

Traditional methods of electroencephalograms(EEG) data augmentation, such as segmentation-reassembly and noise mixing, suffer from data distortion that can alter the original temporal and spatial feature distributions of the brain signals. Deep learning-based methods for generating augmentation EEG data, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have shown promising performance but require a large number of comparative learning samples for model training. To address these issues, this paper introduces an EEG data augmentation method based on Gaussian Mixture Model microstates, which retains the spatiotemporal dynamic features of the EEG signals in the generated data. The method first performs Gaussian mixture clustering on data samples of the same class, using the product of the probability coefficients and weight matrices of each Gaussian model as corresponding microstate features. Next, it randomly selects two EEG data samples of the same type, analyzes the similarity of the main components of the microstate features, and swaps the similar main components to form new Gaussian mixture model features. Finally, new data is generated according to the Gaussian mixture model using the respective model probabilities, weights, means, and variances. Experimental results on publicly available datasets demonstrate that the proposed method effectively characterizes the original data's spatiotemporal and microstate features, improving the accuracy of subject task classification.
The Impact of CO2 Emissions in Indonesia's Construction Industry: A Human Development Perspective
Authors: Tampubolon Manotar
Published: January 2025

The construction industry in Indonesia plays a crucial role in the country's economic growth, but it is also one of the top contributors to CO2 emissions, raising important concerns about its effects on environmental sustainability and human development. This study explores the relationship between the carbon footprint of the construction sector and its effects on Indonesia’s human development indicators, including health, education, and income. By employing a mixed-methods approach that combines an analysis of CO2 emission data from major construction activities with a review of government policies and frameworks, this research identifies trends and assesses mitigation strategies. The findings indicate that the construction sector is responsible for a significant portion of national greenhouse gas emissions, primarily due to energy-intensive processes and a slow uptake of green technologies. However, the evidence suggests that strategic interventions, such as encouraging green construction practices and implementing regulatory measures, can effectively reduce emissions while also providing socioeconomic benefits. The study concludes that it is essential to incorporate sustainable practices within the construction industry to align environmental objectives with human development goals. These insights provide practical recommendations for policymakers and stakeholders to achieve a balance between growth and sustainability.
Anaerobic Fermentation of Integral Cassava Ensiling as an Alternative Food Product: Nutritional, Microbiological, and Paste Properties
Authors: Lopes Pedro Faria , Ferreira Tânia Aparecida Pinto de Castro , Ribeiro Alline Emanuele Chaves , Rezende Cíntia Silva Minafra , Cavalcante Rodrigo Barbosa Monteiro , Ascheri Diego Palmiro Ramirez
Published: January 2025

The present work studied a modified processing technique of a traditional aerobic fermented cassava product called "Puba". Puba is a food process developed by Native Americans in South America but made in microbiological hazard conditions. The process modification was designed in an anaerobic environment obtained by pressing Puba in a glass jar and sealing then. Changes in the nutritional composition and antioxidant capacity as vitamin C contents were evaluated in the food products produced with cassava peels, cassava from conventional and cassava from organic farming systems as raw materials. In addition, were researched microbiological safety, the pres-ence of lacteal bacteria, and paste properties of the products, named Puba 2.0. One-way variance analysis, Student, and Tukey post hoc tests, with p ≤ 0.05, evaluated the data. Results: The organic cassava had a significantly higher vitamin C content and more beneficial bacterial growth than that grown conventionally (t-test, p ≤ 0.05). The Puba 2 made with cassava peels showed protein and insoluble and total dietary fiber contents significantly increased. Puba 2.0 fermentation promoted the growth of bacteria with probiotic potential and resulted in good qualities for bakery products, compared with Puba. Conclusions: Puba 2.0 fermentation is a simple and inexpensive technique with nutritional, technological, and probiotic potential. This procedure showed the potential of cassava peels use and the nutritional superiority of organic cassava as raw material. The cassava processing made in an environmental temperature and no refrigeration, can be safely applied for human consumption.
Atypical Manifestations of Rett Syndrome: Macrocephaly and Hyperostosis Frontalis Interna in a Female Patient
Authors: Imataka George , Koyama Satomi , Kuwashima Shigeko , Shiraishi Hideaki
Published: January 2025

Rett syndrome is a rare neurodevelopmental disorder caused by mutations in the MECP2 gene on the X chromosome, primarily affecting females. It is characterized by developmental regression, stereotypic hand movements, seizures, and microcephaly due to decelerated head growth. However, atypical presentations, such as macrocephaly and hyperostosis frontalis interna (HFI), are rarely reported. HFI, defined as abnormal thickening of the frontal bone, is uncommon in pediatric populations and is often linked to metabolic disturbances, hormonal imbalances, or prolonged anti-seizure medication (ASM) use. We report the case of a 16-year-old girl with genetically confirmed Rett syndrome who presented with macrocephaly (+2.5 SD) and HFI. Genetic testing identified a pathogenic MECP2 mutation (c.882C>T, Arg270Stop), confirming the diagnosis. The patient’s early development was normal until 18 months, when developmental regression occurred, including loss of speech, impaired social interactions, and stereotypic hand movements. She was also diagnosed with central precocious puberty at age 9, treated with leuprorelin acetate for three years, during which her growth in height ceased. By age 16, her height was -2.6 SD. Brain MRI revealed thickening of the frontal bone and enlarged frontal sinuses, consistent with HFI. She experienced intractable epilepsy managed with multiple ASMs. Reduction in ASM doses improved dystonia but led to seizure recurrence. Additional evaluations revealed mild osteopenia and altered hormonal profiles, suggesting systemic effects of MECP2 dysfunction. This case highlights the expanded phenotypic spectrum of Rett syndrome, emphasizing the impact of MECP2 mutations on cranial growth and bone metabolism. Hormonal dysregulation and ASM use may contribute to these anomalies. Comprehensive evaluation and genetic testing are critical for differentiating Rett syndrome from overlapping conditions. A multidisciplinary approach is essential to manage rare manifestations and improve personalized care strategies.
Optimizing Defect Detection on Curvy and Reflective Surfaces Using Deep Learning and Advanced Imaging Systems
Authors: Yoon Joung-Hwan , Okwuosa Chibuzo Nwabufo , Aronwora Nnamdi Chukwunweike , Hur Jang-Wook
Published: January 2025

The industrial application of artificial intelligence (AI) has witnessed outstanding adoption due to its robust efficiency in recent times. Image fault detection and classification have also been implemented industrially for product defect detection, as well as for maintaining standards and optimizing processes using AI. However, there are deep concerns regarding the latency in the performance of AI for fault detection in curvy and glossy products, due to their nature and reflective surfaces, which hinder the adequate capturing of defective areas using traditional cameras. Consequently, this study presents an enhanced method forcurvy and glossy surface image data collection using a Basler vision camera with specialized lighting and KEYENCE displacement sensors, which are used to train deep learning models. Our approach employed image data generated from normal and two defect conditions to train eight deep learning algorithms: four custom Convolutional Neural Networks (CNNs), two variations of VGG-16, and two variations of ResNet-50. The objective was to develop a computationally robust and efficient model by deploying global assessment metrics as evaluation criteria. Our results indicate that a variation of ResNet-50, ResNet-50224, demonstrated the best overall efficiency, achieving an accuracy of 97.79%, a loss of 0.1030, and an average training step time of 839 milliseconds. However, in terms of computational efficiency, it was outperformed by one of the custom CNN models, CNN6-240, which achieved an accuracy of 95.08%, a loss of 0.2753, and an average step time of 94 milliseconds, making CNN6-240 a viable option for resource-sensitive environments.
Computational Complexity of Radix-2, Radix-4 and Bluestein Algorithms Implementation of the Discrete Fourier Transform (DFT)
Authors: Giannakopoulos Georgios , Shaikh Khushbu Mehboob , Perez Maria Antonnette
Published: January 2025

The computational complexity of Discrete Fourier Transform (DFT) algorithms plays a pivotal role in signal processing, influencing their applicability in various domains. This paper investigates three prominent Fast Fourier Transform (FFT) algorithms: Radix-2, Radix-4, and Bluestein, with a focus on their computational efficiency and suitability for different sequence lengths. MATLAB implementations were developed to optimize these algorithms, reducing the number of multiplications and additions required during runtime. A comparative analysis reveals that Radix-2 and Radix-4 algorithms are highly efficient for power-of-two and power-offour data lengths, respectively, while the Bluestein algorithm provides unparalleled flexibility for arbitrary sequence lengths, including primes. The study demonstrates the trade-offs associated with each algorithm, highlighting their strengths and limitations. Radix-4 achieves greater efficiency over Radix-2 for longer sequences, while Bluestein eliminates the need for zero-padding at the cost of increased computational complexity. This research offers valuable insights into the selection of FFT algorithms based on application-specific requirements and data characteristics, laying the groundwork for further optimization and hybrid algorithm development. The findings underscore the enduring importance of FFTs in addressing the computational demands of modern signal processing tasks.
Can Testing 7000 Seeds Help to Understand the Dormancy Type of a Taxon? A Case Study of Linum Mulleri, an Endemic and Endangered Species of Sardinia (Italy)
Authors: Dessì Ludovica , Porceddu Marco , Podda Lina , Cuena Lombraña Alba , Bacchetta Gianluigi
Published: January 2025

Linum mulleri is an endemic taxon of southwestern Sardinia (Italy), categorised as Endangered (EN) on the IUCN Red List and included in Annexes II and IV of the Habitats Directive (92/43/EEC) as priority species for conservation. This study investigated the germination ecophysiology of L. mulleri and the possible presence of dormancy by using 7000 seeds, providing useful information for conservation strategies. The germination response of fresh seeds was evaluated under different temperatures, photoperiods, pre-treatments [cold stratification (C); warm stratification (W); W+C; C+W+C; dry after ripening (DAR)], and different gibberellic acid (GA3) concentrations. L. mulleri germinates under controlled conditions, particularly at 15 and 20°C, while germination percentages (FGP) never exceeded 5% at 5 and 30°C. C and C+W+C induced secondary dormancy, delaying germination, whereas W, DAR and GA3 stimulate it. Light and dark incubation showed no significant differences in FGP. W, DAR and 250 mg/L GA3 effectively overcame physiological dormancy (PD), expanding the germination temperature range to below 10 and above 25°C. These responses suggested type 3 non-deep PD, as germination temperatures extended from moderate to both low and high temperatures. Analyzing 7000 seeds provided crucial information into dormancy and germination strategies, supporting both ex situ and in situ conservation efforts.
Current Progress in Bacillus by Bibliographic Analysis
Authors: Ding Yuanzhao
Published: January 2025

Bacillus, a versatile microorganism, has widespread industrial applications, particularly in the fields of biotechnology and environmental sustainability. This study uses bibliographic analysis through VOSviewer to explore key trends in Bacillus research, identifying significant keywords, organizations, and countries or regions leading the field. One notable discovery is the potential use of Bacillus in cement production, where its incorporation can enable self-healing of cracks in cement. This self-healing property can significantly reduce maintenance and labor costs in construction. Furthermore, the study highlights future opportunities for Bacillus research, particularly the integration of big data and machine learning. By leveraging large-scale data and advanced algorithms, Bacillus applications can be optimized for various industries, offering more efficient and sustainable solutions. This study provides insights into both current applications and future research directions for Bacillus in industrial settings.
Experimental Study of the Hydrodynamic Forces of Pontoon Raft Aquaculture Facilities Around a Wind Farm Monopile Under Wave Conditions
Authors: Chen Deming , Lin Mingchen , Zhou Jinxin , Tang Yanli , Zhao Fenfang , Wang Xinxin , Yu Mengjie , Li Qiao , Kitazawa Daisuke
Published: January 2025

The integrated development of offshore wind power and marine aquaculture represents a promising approach to the sustainable utilization of ocean resources. The present study investigates the hydrodynamic response of an integrated wind energy-aquaculture structure. Physical water tank experiments were conducted on pontoon raft aquaculture facilities (PRAF) deployed around a wind farm monopile using the following three configurations: single-row PRAF (1) with and (2) without a monopile, and (3) three-row PRAF without a monopile. The interaction between the aquaculture structure and the wind farm monopile was examined, with a particular focus on the mooring line tensions and bridle line tensions under different wave conditions. The findings indicate that, among all configurations, both the maximum mooring line tension and bridle line tension decrease with increasing wave period and increase with increasing wave height. Utilizing the wind farm monopile foundation as an anchor, the mooring line tension was reduced significantly with the highest reduction of 66% in the single-row PRAF. The multi-row arrangement PRAF experienced lower mooring line tension in comparison to the single-row arrangement PRAF. However, for the bridle line tension, the upstream component enhanced while the downstream one weakened with a monopile, and they both decreased in multi-row arrangement. Finally, the numerical simulation results confirmed the dampening effects of the monopile on wave propagation. These findings provide insights into the hydrodynamic performance of integrated wind-aquaculture systems, offering scientific guidance for the optimal deployment of aquaculture structures within offshore wind farms.
Forever Chemicals PFAS Global Impact and Activities, Cascading Consequences of Colossal Systems Failure: Long-Term Health Effects, Food-Systems, Eco-Systems
Authors: Lee Jocelyn C. , Smaoui Slim , Duffill John , Marandi Ben , Varzakas Theodoros
Published: January 2025

Per- and polyfluoroalkyl substances (PFAS) are found everywhere including food, cosmetics, and pharmaceuticals. This review introduces PFAS comprehensively, discussing their nature, identifying the interconnection with microplastics, and their impacts on public health and the environment. The Human cost of decades of delay, cover-ups, and mismanagement of PFAS and plastic waste has been outlined and briefly explained. Following that PFAS and long-term health effects have been criti-cally assessed. Risk assessment has then been critically reviewed mentioning different tools and models. Scientific Research and Health Impacts in the United States of America have been critically analyzed tak-ing into consideration the Center for Disease Control (CDC) PFAS Medical Studies and Guidelines. PFAS impact, activities, and studies around the world have focused on PFAS Levels in Food Products and Dietary Intake in Different Countries such as China, European countries, USA and Australia. Moreover, PFAS in Drinking Water and Food have been outlined with regard to risks, mitigation, and reg-ulatory needs taking into account chemical contaminants in food and their Impact on health and safety. Finally, PFAS impact and activities briefings specific to regions around the world refer to Australia, Vi-etnam, Canada, Europe, and the United States of America. Crisis Multi-Faceted Issue, exacerbated by mismanagement has been discussed in the context of applying problem-solving analytical tools: the Domino Effect Model of accident causation, the Swiss Cheese Theory Model, and the Ishikawa Fish Bone Root Cause Analyses. Last but not least, the PFAS impact on the Sustainable Development Goals (SDGs) of 2030 has been rigorously discussed.
Syntactic Complexity and Proficiency: A Study of Objective Measures in the TEEP Speaking Test
Authors: Akilova Munis
Published: January 2025

Syntactic complexity plays a critical role in assessing language proficiency, yet identifying measures that effectively distinguish proficiency levels remains challenging. This study investigates the relationship between objective measures of syntactic complexity and subjective ratings in the Test of English for Educational Purposes speaking assessment. Focusing on three metrics Mean Length of AS-Unit, Mean Length of Clause, and Subordinate Clauses per AS-Unit the research evaluates their ability to correlate with subjective ratings of grammatical range and accuracy and differentiate proficiency levels. Using a quantitative approach, the study analyzed 89 TEEP speaking test transcriptions paired with proficiency scores ranging from 5.0 to 7.5. Statistical analyses revealed weak but significant positive correlations between MLAS and MLC with subjective ratings, suggesting that these measures contribute modestly to evaluative outcomes. However, SCP-AS showed no significant correlation. ANOVA results highlighted that while MLAS distinguished between lower and higher proficiency levels, it struggled to differentiate adjacent levels. MLC and SCP-AS showed limited variation across levels, indicating low sensitivity. The findings suggest refining TEEP rating scales to assess complexity and accuracy separately and incorporating diverse syntactic, lexical, and morphological measures to enhance assessment validity. Future research should expand metrics and task types to deepen understanding of syntactic complexity in language assessment contexts.
How Should We Understand That a Map of Information Concept Is Created?
Authors: Enomoto Takuto
Published: January 2025

The definition of information concepts has been approached in various ways. Previous studies have classified these definitions into three categories: (1) reductionism, (2) antireductionism, and (3) non-reductionism. The map of information concepts developed by Luciano Floridi organizes information concepts in terms of (3) non-reductionism. However, the map is often criticized due to misunderstandings, since neither the specific method for constructing the map nor its structure is described in detail. The purpose of this paper is to reconstruct the map using the method of levels of abstraction (LoA) and to make its structure explicit. First, Section 2 reviews previous studies and organizes the definitions of information concepts based on the above classification scheme. Next, Section 3 explains the method of LoA and applies it to information concepts. As a result, it becomes clear that the map differs from the well-known DIKW pyramid in that each element is arranged by adding observables in order from higher to lower degrees of abstraction. This work allows us to demonstrate the relationship between the map and the method of LoA, and to re-evaluate Floridi’s achievement.
The Interprofessional Education Matrix: Sessions to Incorporate Higher Education Institutes within Pre-registration Nursing and Allied Health Professionals
Authors: Davies Michaela , Knight Kate H. , Chaplin Catherine , Dillon Anya Mitford , Pollitt Catherine , Hay Jonathan
Published: January 2025

This study examines the Outreach Skills Clinic for Assessment (OSCA), a collaborative Interprofessional Education (IPE) initiative led by the University of Chester. Designed to enhance the competencies of pre-registration health and social care learners, OSCA integrates multi-disciplinary teaching across Higher Education Institutions. Data from student and practitioner feedback highlight the program’s success in fostering a supportive learning environment, promoting clinical skills development, and improving peer collaboration. By collating and structuring diverse healthcare professional expertise, OSCA bridges theory and practice, equipping learners with practice skills geared towards adaptability across varied care settings. Data illustrates that this integrated approach enhances healthcare education and contributes to the delivery of safe, high-quality patient care.
Comparison of Three Autoencoder-Based Models Using Molecular Dynamics (MD) Simulations Data
Authors: Ojeda-May Pedro
Published: January 2025

Molecular dynamics Molecular dynamics (MD) simulations have proven useful in studying the dynamics of Biomolecules, for instance proteins. However, the computational cost for conducting such simulations is high as reflected in the number of core-hours consumed in high performance computing (HPC) clusters. Although some techniques are available for enhancing the sampling of the conformational space, they usually make assumptions about the system by introducing empirical parameters. Machine learning (ML) models can overcome this issue because here, important features of the landscape can be inferred from the data themselves. In this work, we use an autoencoder ML model with three different flavors: Variational, Wasserstein, and Denoising to generate new protein conformations using MD trajectories as the training data. These generated structures can potentially enhance the ensemble of the original MD data.
Non-hydrostatic Galerkin Model with Weighted Average Pressure Profile
Authors: Calvo Lucas , De Padova Diana , Mossa Michele
Published: January 2025

This work develops a new two-dimensional depth-integrated non-hydrostatic model for wave propagation simulation using a weighted average linear/quadratic non-hydrostatic pressure profile. The model is constructed by modifying an existing non-hydrostatic discontinuous/continuous Galerkin finite element model with a linear vertical non-hydrostatic pressure profile. A series of analytical solutions and laboratory experiments verify and validate the model. The results show that using a weighted average linear/quadratic non-hydrostatic pressure profile improved the performance of previous depth-integrated models with linear or quadratic non-hydrostatic pressure profiles.
Reflections on COVID-19 Adaptive Responses as a Template for Climate Intervention-Geoengineering Engagement
Authors: Patrick Hosea Olayiwola
Published: January 2025

The discourse on geoengineering applications as a climate intervention strategy has been met with opposing views across many quarters. The central argument underlined the need for more research as solar geoengineering applications' implications are widely unknown. While the discourse raises justice, equity, and governance issues, an underlining debate is how geoengineering engagement should be tailored going forward. Using a systematic desktop review methodology, the paper provides a descriptive overview of Covid-19 responses and possible points to consider for climate interventions. The rationale is to examine the extent to which vertical and horizontal reactions and public opinions influence policy response and actions for Covid-19 adaptation and coping mechanisms as a lesson for Solar geoengineering engagement. It concludes that as a lesson for effective climate intervention, there is a need to develop strategic partnerships among various stakeholders, create an alignment between research objectives and the community's needs and peculiarities, consider the ethics of practice and develop a monitoring and governance framework to avoid possible stakeholders' excesses.
Digitalization and Gamification in ELT. A Pathway to Successful Teaching
Authors: Padurean Alina Nicoleta
Published: January 2025

In recent years, the digitalization of education has reshaped the way we teach English (ELT). As technology continues to permeate classrooms around the globe, educators focus on digital tools to enhance both teaching practices and student engagement. From interactive online platforms to language learning apps, digital resources are making English instruction more accessible, flexible, and efficient. Among the most innovative approaches to emerge in this digital transformation is gamification. Gamification is to be understood as a technique that applies game-like elements to non-game contexts. Gamification has proven to be particularly effective in ELT, helping to motivate learners, engage the in classroom activities and improve language retention. By merging digitalization with game-based learning strategies, educators can create dynamic, enjoyable, and interactive learning environments that support the diverse needs of modern language learners. This article explores the role of digitalization in ELT and examines how gamification is revolutionizing the way students acquire language skills.
Immune Responses Against West Nile Virus and Mosquito Salivary Proteins in Wild Birds from St. Tammany Parish, Louisiana
Authors: Schwinn Alyssa R. , Harris Sara , Jacobs Zoe , De Verges Jane , Jameson Samuel B. , Wesson Dawn M. , Michaels Sarah R. , Caillouët Kevin A. , Londoño-Renteria Berlin
Published: January 2025

Though a variety of methods are used to conduct West Nile virus (WNV) surveillance, accurate prediction and prevention of outbreaks remains a global challenge. Previous studies have established that the concentration of antibodies to mosquito saliva is directly related to the intensity of exposure to mosquito bites and can be a good proxy to determine risk of infection in human populations. To assess exposure characteristics and transmission dynamics among avian communities, we tested the levels of IgY antibodies against whole salivary glands of Aedes albopictus and Culex quinquefasciatus, as well as WNV antigen, in 300 Northern cardinals sampled from April 2019 to October 2019 in St. Tammany Parish, Louisiana. Though there were no significant differences in antibody responses among sex or age groups, exposure to Ae. albopictus bites was more positively associated with exposure to WNV compared with Cx. quinquefasciatus exposure (ρ = 0.2525, p <0.001; ρ = 0.1752, p = 0.02437). This association was more pronounced among female birds (ρ = 0.3004, p = 0.0075), while no significant relationship existed between exposure to either mosquito vector and WNV among male birds in the study. In general, two seasonal trends in exposure were found, noting that exposure to Ae. albopictus becomes less intense throughout the season (ρ = -0.1529, p = 0.04984), while recaptured birds in the study were found to have increased exposure to Cx. quinquefasciatus by the end of the season (ρ = 0.277, p = 0.0468). Additionally, we report the identification of several immunogenic salivary proteins, including D7 family proteins, from both mosquito vectors among the birds. Our results suggest the role of Ae. albopictus as an early season enzootic vector of WNV, facilitated by Northern cardinal breeding behaviors, enhancing the potential to increase infections among Cx. quinquefasciatus mosquitoes in the late season contributing to human disease incidence and epizootic spillover in the environment.