bluuebunny/crossref_metadata_2025 huggingface dataset:
The Value of GDF-15 and Conventional Markers in Combination for Clinical Diagnosis of Lung Cancer
Authors: Ni Jingru , Wu Yongkang , Niu Limin , Liu Heng , Lin Qinghai , Hao Xiaohe , Mao Cuiping
Published: November 2024

Lung cancer is a leading cause of morbidity and mortality worldwide, and effective biomarkers for its screening and monitoring are still lacking. This study aims to assess the diagnostic value of Growth Differentiation Factor 15 (GDF15) in lung cancer and its subtypes, compared to conventional biomarkers, to evaluate its potential as a predictive biomarker for lung cancer screening and monitoring. GDF15 levels were measured and analyzed in different subtypes of lung cancer and non-tumor controls. The correlation between GDF15 and the expression of eight conventional biomarkers was assessed by analyzing serum GDF15 levels in the markersnormal groups and the markershigh groups. The superiority of GDF15 in screening and monitoring of lung cancer was confirmed using ROC curve analysis of GDF15, alongside conventional biomarkers. Serum GDF15 levels were significantly higher in all subtypes of lung cancer compared with non-tumor controls, showing significant correlations with the levels of conventional biomarkers. ROC curve analysis demonstrated that GDF15 has superior sensitivity and specificity over conventional biomarkers, highlighting its potential as a promising diagnostic biomarker for lung cancer. GDF15 shows strong potential as a diagnostic tool for lung cancer, outperforming conventional markers. It presents a promising new biomarker for lung cancer monitoring and diagnosis.
Electrochemically-Induced Partial Cation Disorder Eliminates Lattice Collapse in Compositionally-Simple LiNi0.9Mn0.1O2
Authors: Chueh William , Lee Junghwa , Jiang Zhelong , Liang Nicolas , Nguyen Howie , Busse Grace , Kwak Jin Hwan , Yoo Yiseul , Ramachandran Hari , Lim Kipil , Csernica Peter , Li Tianyi , Xu Xin , Chung Kyung Yoon , Michel Kathrin , Frerichs Joop , Gent William , Clément Raphaële , Park Jungjin
Published: November 2024

Virtually all layered oxide positive electrodes (cathodes) for lithium-ion batteries exhibit abrupt shrinkage along the c lattice (c-collapse) at high states-of-charge, limiting cycle life. In this work, we suppress c-collapse by electrochemically inducing partial disorder permanently throughout the bulk of compositionally-simple LiNi0.9Mn0.1O2. Our approach leverages irreversible oxygen oxidation in the as-synthesized Li-excess Ni-rich oxides to activate partial disordering of the cation sublattice, while preserving the long-range layered structure. Using this method, Li-stoichiometric transition metal oxides with variable extents of cation disorder are readily fabricated by adjusting the starting Li-excess in the as-synthesized materials. Surprisingly, at a TMLi concentration of ≥12%, the c lattice parameter remains nearly invariant during (de)lithiation, leading to decreased chemical strain, enhanced microstructural integrity, and improved battery cycle life. We demonstrate a combination of high specific capacity and long cycle life, along with negligible voltage hysteresis and decay. This concept opens the opportunity for designing materials by inducing persistent intrinsic disorder electrochemically.
The impact of labeling automotive AI as “trustworthy” or “reliable” on user evaluation and technology acceptance
Authors: Dorsch John , Deroy Ophelia
Published: November 2024

This study explores whether labeling AI as either “trustworthy” or “reliable” influences user perceptions and acceptance of automotive AI technologies. Utilizing a one-way between-subjects design, the research presented online participants (N=478) with a text presenting guidelines for either trustworthy or reliable AI, before asking them to evaluate 3 vignette scenarios and fill in a modified version of the Technology Acceptance Model which covers different variables, such as perceived ease of use, human-like trust, and overall attitude. While labeling AI as “trustworthy” did not significantly influence people’s judgements on specific scenarios, it increased perceived ease of use and human-like trust, namely benevolence, suggesting a facilitating influence on usability and an anthropomorphic effect on user perceptions. The study provides insights into how specific labels affect adopting certain perceptions of AI technology.
Multi-Angle Assessment of Leather Strength and Elasticity: Beyond Standard Parallel and Perpendicular Measurement
Authors: Efendioglu Nilay Ork
Published: November 2024

Tensile strength and elongation are key mechanical properties of leather that reveal important aspects of its performance. Traditionally, these properties are measured using samples taken in two directions - parallel and perpendicular to the leather’s backbone line - and averaged. However, collagen fibers in leather are oriented in various directions and proportions throughout the material. Unlike fabrics, where shear behaviors are considered, leather’s shear strength is often overlooked in property evaluations. Considering leather as a fabric, shear strength becomes significant because garments are subjected to forces in multiple directions during use. No prior studies have investigated leather strength by considering all directions beyond the standard parallel and perpendicular measurements. This study examines whether tensile strength and elongation vary with sampling direction. Data were collected at 15° intervals around a 360° circle from garment sheep leather samples. Results reveal that tensile strength was generally higher in samples taken parallel to the backbone line, while elongation was lower in this direction. This study helps leather apparel companies optimize cutting techniques by revealing how tensile strength and elongation vary with sampling direction. Improved cutting decisions lead to better garment performance, fit, and durability, while also enhancing customer satisfaction.
Evolution of the social-economic profile of a Polish Paralympian from Heidelberg to Tokyo: A Study Protocol for a Prospective Longitudinal Study
Authors: Sobiecka Joanna , Zwierzchowski Jakub B. , Zwierzchowska Anna
Published: November 2024

The observation of sociodemographic characteristics is important for the characterization of Paralympic athletes and the identification of determinants of their athletic performance. The aim of this study was to present the changes that have occurred in the profile of the Polish Paralympian in the period from Heidelberg to Tokyo Paralympic Games based on basic demographic characteristics and selected social and sport-related features. The study included 652 Polish Paralympic athletes, accounting for 96.6% of the population from the 1972- 2021 Games. The research was conducted with the direct participant observation method using a diagnostic survey. Analysis of the data showed that gender was not a differentiating factor among Polish Paralympic athletes, and the proportion of women was lower than men. Still, age was a significant differentiating factor at (p<0.05). Furthermore, a significant differentiation of athletes in terms of the structure of education was observed, with a tendency to a steady increase in its level in subsequent years (chi2=68.83; df=8; p<0.01). However, this did not have a significant effect on their professional fulfillment. The proportion of multiple participants of the Paralympic Games increased significantly (chi2=21.43; df=8; p<0.01), while the proportion of athletes who won a Paralympic medal decreased (chi2=59.11; df=8; p<0.01).
Exploring the establishment of the long-spined sea urchin Centrostephanus sylviae in the Juan Fernández Archipelago, Chile: ecosystem threats and future conservation efforts in a biosphere reserve
Authors: Vera-Duarte Javier , Carrasco Sergio A. , Mettifogo Bianca , Gaymer Carlos F. , Friedlander Alan M. , Wahle Richard A. , Palma Álvaro , Hinojosa Iván A.
Published: November 2024

The Juan Fernández Archipelago (JFA) is a unique ecosystem due to its diversity and high endemism. In recent years there has been an increase in the populations of the endemic sea urchin Centrostephanus sylviae, generating negative impacts to the ecological and socio-economic systems of the archipelago. Here we describe the establishment of C. sylviae and the consequences of its overabundance on the subtidal communities, specifically around Robinson Crusoe and Santa Clara islands. The increase in abundance of C. sylviae and its community-level impacts (i.e., sessile benthic, macroinvertebrates, and fishes) were documented by visual surveys using scuba diving at various sites during January 2014 (12 sites), March 2017 (12 sites), March 2020 (4 sites), and January 2024 (7 sites). Over this time period the increase of C. sylviae abundance (~ 40-50%) was associated with a significant decrease in sessile biotic benthic cover and an increase in the percentage of barren grounds (40-95%). Additionally, a significant decrease in the abundance of the sea star Patiriella calcarata (100%) and the sea cucumber Mertensiothuria platei (80%) was observed, together with a decrease in the biomass of the endemic Juan Fernández wrasse Malapterus reticulatus (95%) and the endemic Juan Fernández trevally, Pseudocaranx chilensis (65%). Although the increase in urchin abundance has resulted in serious problems for the main economic activities of the archipelago (i.e., lobster fishery and recreational diving), it could also be considered an opportunity to diversify economic activity through the commercialization of the species, whose biological attributes make it an attractive gastronomic product. However, to create sustainable commercial exploitation, the ecological characteristics of the species and socioecological traits need to be understood to generate effective management and enforcement strategies. The results of the present study could serve as a baseline for exploring ongoing community changes in subtidal environments.
On the Performance of Large Language Models on Introductory Programming Assignments
Authors: Raihan Nishat , Goswami Dhiman , Puspo Sadiya Sayara Chowdhury , Siddiq Mohammed Latif , Newman Christian , Ranasinghe Tharindu , Santos Joanna C.S. , Zampieri Marcos
Published: November 2024

Recent advances in artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) have led to the development of a new generation of Large Language Models (LLMs) trained on massive amounts of data. Commercial applications (e.g., ChatGPT) have made this available to the general public, enabling the use of LLMs to produce high-quality texts for academic and professional purposes. Educational institutions are increasingly aware of stu-dents’ use of AI-generated content and are researching its impact and potential misuse. Computer Science (CS) and related fields are particularly affected, as LLMs can also generate programming code in various languages. To understand the potential impact of publicly available LLMs in CS education, we extend our previously introduced CSEPrompts [1], a framework comprising hundreds of programming exercise prompts and multiple-choice questions from introductory CS and programming courses. We provide experimental results on CSEPrompts, evaluating the performance of several LLMs in generating Python code and answering basic computer science and programming questions, offering insights into the implications of this technology for CS education.
Full-body rotation measurements of micro-sized curved fibers in turbulence
Authors: Caridi Giuseppe C. A. , Giurgiu Vlad , De Paoli Marco , Soldati Alfredo
Published: November 2024

This study introduces a novel technique to measure full-body rotation rate in combination with Lagrangian tracking of anisotropic micro-sized fibers. By exploiting the geometric anisotropy of these fibers — specifically, their tapered shape for tumbling measurement and curvature for spinning quantification — we address a significant gap in the literature concerning gyro-tracking along fiber trajectories. Our analysis investigates how fiber geometry and imaging parameters impact the accuracy of full-body rotation measurements. By integrating synthetic data with experimental results, we assess the influence of magnification, sampling frequency and curvature of the fiber on the uncertainty of these measurements. Experimental results obtained in a channel flow environment demonstrate the method’s potential to accurately detect rotations of micro-fibers with lengths approaching the Kolmogorov scale.
The climatology of the ionospheric electron density peak parameters retrieved from the two COSMIC missions between 2007-2023
Authors: Farid A. I. Saad , Elshoukrofy A. Sh. M. , Aly Ayman A. , Fathy Adel
Published: November 2024

With the accumulation of the ionospheric Radio Occultation (RO) measurements provided by Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), it becomes accessible to use the long-term observations provided by their two COSMIC missions, namely COSMIC-1 and COSMIC-2, to exploit the ionospheric climatology research. As such, the spatial and temporal of diurnal, seasonal and annual variations of the electron density peak (NmF2 and hmF2) are investigated. The dataset used encompasses COSMIC observations spanning 16 consecutive years from Jan 2007 to Dec 2023, corresponding to the minimum phase of solar cycle 23 (2007–2008), complete solar cycle 24 (2009–2019) and the ascending phase of the solar cycle 25 (2020–2023). The present study emphasizes some of the preceding features that prescribed the morphology of the ionosphere. It showed that the NmF2 generally becomes fully developed in the afternoon time and enhanced to higher values in the dusktime hours, while the lowest levels are observed around post-sunset until the early morning. Further, the NmF2 variations exhibit semiannual pattern, with peak NmF2 values occurring during equinoxes. Whereas the hmF2 variations exhibit annual pattern peaks around summer in the northern hemisphere but around winter in the southern hemisphere. Results additionally verify that the long-term fluctuations in ionospheric electron density parameters are closely aligned with changes in the solar activity cycle. They also demonstrate that, irrespective of the season, the NmF2 saturates as the solar activity approaches higher levels. Besides, this dusktime NmF2 is always much higher and more pronounced in the northern hemisphere than the southern hemisphere irrespective season. The mechanism of the dusk side hemispheric asymmetry and saturation to be investigated in further studies. Consequently, our study extends previous research studies by identifying the long-term patterns of ionospheric parameters, which would be beneficial for constructing and developing well-defined ionospheric modeling.
Characterizing Motion States in the Restricted Five-Body Problem with Perturbing Forces.
Authors: Kumar A.K. Awasthi Sanjeev Sanjeev
Published: November 2024

The n-body problem, a cornerstone of celestial mechanics, has been the subject of extensive research for centuries, with particular emphasis on the complexities of the three-body problem under various perturbations. These perturbations include oblateness, triaxiality, radiation pressure, and the effects of Coriolis and centrifugal forces. Recent advancements have shifted focus to systems involving more than three bodies, with notable work in the four-body problem. In this study, we extend the analysis to the five-body problem, examining its chaotic behavior and identifying regions of libration points. By varying the masses of the bodies across distinct surface points, we analyze the system’s dynamics, uncovering fractal zones within the problem. Additionally, we perform a stability analysis of the libration points, offering new insights into the behavior and stability of the five-body system. This research contributes to a deeper understanding of multi-body interactions and their implications in theoretical and applied contexts.
The influence of native shrub density on bird communities in the Central Drylands of California, USA
Authors: Hillier-Weltman Zoë , Lortie CJ , Zuliani Mario
Published: November 2024

Interactions between key landscape features in desert ecosystems such as shrubs and other foundation plants can influence avian community assembly. Bird species often use resources and microhabitats provided by these shrubs for food, perching sites, and as thermal refuges. Citizen science data, such as eBird, are broadly accessible and can be used to examine fine-scale avian distribution. Coupling this accessible data with key factors, such as native shrubs, can be used for conservation practices. eBird data offers the opportunity to examine avian communities across regional ecological gradients. Using eBird, we tested the hypothesis that shrub density and relative differences in aridity among sites within this region shape the structure of bird communities throughout Central California drylands. Shrub density positively influenced the observation rates of avian communities sampled. Decreasing aridity increased the positive associations of birds with shrubs. Citizen science data such as eBird offers promise for testing predictions at fine spatial scales, and further research can explore availability and reporting of data for other regions - particularly in drylands subject to substantial pressures from climate change globally. Simple landscape features in drylands, such as native shrub density and cover, offer a viable path forward for avian community conservation and potential habitat restoration in drylands in the face of a changing climate and increasing desertification.
Genetics of faba bean yield and yield stability
Authors: Bornhofen Elesandro , Mouritzen Troels , Alves Sheila , Robertson-Shersby-Harvie Thomas Ramsay , Skovbjerg Cathrine , Windhorst Alex , Zhang Hailin , Jayakody Thilani , Magnin-Robert Jean-Bernard , Aubert Grégoire , Floriot Matthieu , Guiziou Camille , Sass Olaf , Welna Gregor , Solís Ignacio , Nielsen Linda , Gutiérrez Natalia , Jayakodi Murukarthick , Stoddard Frederick , O'Sullivan Donal , Torres Ana , Link Wolfgang , TAYEH Nadim , Janss Luc , Andersen Stig
Published: November 2024

Faba bean is a globally adapted legume protein crop with a high yield potential. Currently, yield variation across environments limits more widespread cultivation and the underlying genetics remain unknown. Here, we identify major QTL for faba bean yield and yield stability. We genotype the ProFaba diversity panel with high resolution and carry out coordinated multi-year/location trials across Europe. Based on these data, we identify more than one hundred loci associated with mean performance and stability for 14 complex traits, including yield. Furthermore, we introduce a method for integrating environmental data in the analysis of trait stability, which enables prediction of performance in untested environments. Our work offers insights into the genetics underlying traits and trait stability in faba bean and provides the approaches and resources needed to drive future protein crop improvement.
Keep your tree above the water: competition and flooding drive the decline of Carya illinoinensis in the Upper Mississippi River
Authors: Férriz Macarena , Maxwell Justin T. , Harley Grant L. , King Daniel J. , King Karen E. , Au Tsun Fung , Vandermyde Benjamin J. , Stoff Brian , Luitel Beda
Published: November 2024

Context Floodplain forests along the Upper Mississippi River System (UMRS) are highly influenced by the human-altered river flow regime. More intense and frequent floods are inducing decline in less flood-tolerant tree species. Of special concern is the situation of northern pecan tree (Carya illinoinensis (Wangenh. K.Koch)), which shows clear symptoms of decline (i.e. defoliation, mortality) and a lack of regeneration. Objective We attempt to investigate changes in C. illinoinensis decline and health and determine the biometric factors that lead to these differences. Methods We established 15 plots along the UMRS floodplain and within each plot, we recorded species composition, health status, diameter at breast height and tree location. Additionally, we collected increment cores to study the disturbance regime, and the effects of climate and river flow on radial growth. We applied a principal component analysis and a mixed effect regression model to determine the factors related to pecan health at site and individual level, respectively. Results Two major disturbance events occurred during the 20th century: in 1965 and 1993. Both events are related to extraordinary flow discharges in the river that led to significant tree mortality in the overstory. Pecans exhibited growth release after the disturbances, however, the incidence of recruitment for this species was very scarce during the 20th century. Our analysis revealed that plots with a higher proportion of healthy pecans are located in the southmost area, which is characterized by less frequent extraordinary floods and less stand competition. Conclusions We conclude that without oriented management efforts, pecans will eventually disappear from the northern extent of the species range soon, leading to a loss in tree diversity in the UMRS.
Effectiveness of low temperature storage on lipid nutritional quality of fish: A meta-analysis
Authors: Tan Karsoon , Huang Leiheng , Luo Cong , Choong KhaiHang , Cheong Kit-Leong
Published: November 2024

Fish are rich in n-3 long-chain polyunsaturated fatty acids, which have many health benefits for the human body. Food storage methods, especially low temperature storage, are key components in maintaining the lipid nutritional quality of seafood. Although many studies have been conducted on the effects of low temperature storage on fish lipids, the information is still poorly organized, and many useful detail (such as various lipid nutritional quality indices) were not extracted in most studies. Therefore, this study conducted a meta-analysis to evaluate the effects of short-term and long-term low temperature storage on the lipid nutritional quality of fish. The results of this study are very important as they provide guidance for consumers to select appropriate low temperature storing methods to better preserve the quality of fish lipids.
Unmasking Faces: Hybrid Attention Mechanisms for Robust Masked and Unmasked Face Recognition
Authors: Shahriari Babak , Yazdian-Dehkordi Mahdi , Ahmadi Ehsan
Published: November 2024

Face recognition, an important technology in biometric identification, encounters significant difficulties when facial features are partially occluded, especially by face masks that hide essential facial details. These challenges are addressed by proposing a novel hybrid approach designed to effectively manage both masked and unmasked face recognition. The approach incorporates fixed and adaptive prior attention mechanisms within a deep learning framework to enhance recognition accuracy. The fixed prior attention mechanism uses segmentation to filter out non-informative areas like backgrounds or masks, ensuring that the model concentrates only on the essential facial regions. At the same time, the adaptive prior attention mechanism employs the Convolutional Block Attention Module (CBAM) to dynamically highlight critical facial features necessary for accurate recognition, while minimizing attention to less relevant areas. This innovative approach is integrated with a customized ResNet architecture which enables the model to produce robust face embeddings crucial for accurate classification. Evaluations on benchmark datasets, including both masked and unmasked scenarios, demonstrate the effectiveness of the proposed method.Additionally, an ablation study proves the contribution of each component within the system, showing valuable insights into their specific roles and effectiveness. The findings suggest that the proposed method has significant potential to enhance the reliability and accuracy of face recognition systems in real-world applications.
From Classroom to Action Training of New Staff in a New Specialty Hospital of a Non-Profit Organization
Authors: Camputaro Luis Alberto , Bórtoli Romina Georgina , Ortiz Jose Luis Tamayo , Torrez Alfonso Quispe , Rosales Luis Mario Campos , Garcia Mirian del Carmen Avalos
Published: November 2024

For the proper functioning of any health institution, it is necessary to unify and/or standardize the knowledge of its staff to achieve smooth teamwork, sharing the same language and criteria. This is even more necessary in health care work to provide the best patient care through an organized interdisciplinary team. Training in competencies, prioritizing the acquisition of practical skills while fostering theoretical self-education, has proven effective for health staff training, improving patient care. Acquiring the skills to detect life-threatening health conditions and their correct treatment and understanding the risk factors for unfavorable evolution are essential to provide timely treatment and avoid complications. Proper training is particularly relevant when a non-governmental hospital institution opens its doors and inaugurates its services to a specific community in the country's interior. To prepare staff for this new Non-Profit Organization (NPO) initiative, a hybrid training course that includes online theoretical classes and hands-on practical workshops was planned to train all the medical and paramedical staff of a new Specialty Hospital.
Patients’ perspectives: Factors affecting the provision of integrated care for patients with pulmonary tuberculosis and type 2 diabetes mellitus multi-morbidity in Addis Ababa, Ethiopia
Authors: Salato Sisay , Setswe Geoffrey
Published: November 2024

Background
Tuberculosis (TB) and type 2 diabetes mellitus (T2DM) represent growing public health challenges globally. Integrated care is important for effective management of this multi-morbidity. However, health systems face challenges in providing such services, particularly in resource-limited settings. This study aimed to assess patients’ perspectives on factors affecting the provision of integrated care for patients with TB and T2DM in Addis Ababa, Ethiopia.
Methods
A health facility based cross-sectional study was conducted. A structured questionnaire was employed to conduct face-to-face interviews with randomly selected sample of 370 patients presenting with both pulmonary tuberculosis and diabetes mellitus multi-morbid patients. Information on patient socio-demographic characteristics and health system factors was collected. Data collection was conducted in accordance with ethical standards and with approval from the relevant ethics committees. Data analysis was conducted using the Statistical Package for Social Sciences (SPSS) software version 27. Logistic regression was employed to identify factors associated with service integration, with a p value of less than 0.05 deemed statistically significant.
Results
A total of 357 respondents participated in this study, giving a response rate of 96.5%. The mean age of the respondents was 49.87 ± 14.046 years. A mere 13.4% (95% CI of 10.1–17.4%) of the respondents received integrated TB-T2DM services across 25% of the assessed facilities. Insufficient counseling on the proper use of medication (AOR = 2.6, CI: 1.1–6.6, p = 0.035) and the risk of TB for DM patients (AOR = 10, CI: 3.7–27, p < 0.001), unorganized TB-DM care (AOR = 4.1, CI: 1.7–10, p < 0.001), the absence of an integrated care policy (AOR = 6.9, CI: 2.7–17, p < 0.001), and a lack of continuity of care (AOR = 3, CI: 1.3–7.5, p = 0.016) were identified as health system factors affecting the integration of services.
Conclusion
The study revealed that the majority of patients in Addis Ababa had limited access to integrated tuberculosis-diabetes services. The identified health system factors pertaining to integration included insufficient counseling on medication and TB risk, unorganized care for TB and T2DM care, and a lack of continuity and policy integration. To improve integration, policymakers must prioritize integrating TB and diabetes strategies, ongoing evaluations to detect gaps, and broader qualitative research exploring patient perspectives across care settings.
Heat transfer using Robin conditions in chemically reactive dual diffusive Casson nanofluid flow: An intelligent computing paradigm
Authors: Butt Zeeshan Ikram , Ahmad Iftikhar , Raja Muhammad Asif Zahoor , Shoaib Muhammad
Published: November 2024

In this research-oriented study, dual diffusive Casson nanofluid stretching flow embedded in a Darcy-Forchheimer type porous medium is scrutinized using a quite new computerized neuro-heuristic optimization technique based on Ricker wavelet neural networks fabricated through global and local solvers namely genetic algorithms and sequential quadratic programming respectively. The flow of the suggested fluid model is characterized by thermal radiation, chemical reaction and Robin conditions for the analysis of heat and mass transfer effects. The similarity approach simplifies the governing partial differential equations of currently discussed flow model into a dimensionless nonlinear system of ordinary differential equations which are solved using the crafted solver and the obtained numerical outcomes are successfully compared with the reference solution compiled through Adam’s numerical technique. A detailed form convergence analysis of the novel design created solver is accomplished using various statistical performance operators.
Dietary Patterns Affecting Oral and Oropharyngeal Cancer: a Mendelian Randomization Analysis
Authors: He Yun , Wang Siyuan , Zhang Jiali
Published: November 2024

Introduction and Aims:
Oral cancer (OC) and oropharyngeal cancer (OPC) are significant global health concerns. Numerous studies have investigated the influence of dietary patterns on these cancers, but the results have been controversial. Therefore, we aim to explore the causal relationship between dietary patterns and OC/OPC.
Methods
Mendalian randomization (MR) analysis was conducted using 85 principal component-derived dietary patterns (exposures) and genetic association data from the Integrative Epidemiology Unit Open Genome-Wide Association Study Database. MR associations were assessed using the inverse-variance weighted method, and horizontal pleiotropy was determined by the MR-Egger intercept method. Heterogeneity, result robustness, and false discovery rate were determined using the Cochran’s Q test, sensitivity analysis, and the Benjamini-Hochberg method, respectively.
Results
A total of 8 and 209 single nucleotide polymorphisms were identified for each dietary pattern. There was a positive association of the consumption of milk and refined breads with increased OC/OPC risk, while the consumption of whole grains, tub margarine spreads, oat cereals, and oily fish were linked to a reduced risk. Additionally, consumption of full cream milk resulted in higher risks of OC and OPC than other types of milk. Alcohol consumption was also associated with an increased risk, but having meals with alcohol mitigated that risk. Sensitivity analysis confirmed that the results were robust without horizontal pleiotropy or heterogeneity.
Conclusion
This study confirms the causal relationships between specific dietary patterns and the risks of oral and oropharyngeal cancers. Adjusting dietary habits, such as reducing full cream milk and alcohol intake while increasing whole grains and oily fish consumption, may help lower cancer risks.
Clinical Relevance:
The findings provide actionable insights for dietary guidelines aimed at cancer prevention. Incorporating these dietary recommendations into public health strategies could reduce the incidence of oral and oropharyngeal cancers.
Identification of NRPS and type II PKS biosynthetic gene cluster (s) encoding decaplanin and kigamicin from Amycolatopsis regifaucium DSM 45072T
Authors: Bisht Niyati , Mayilraj Shanmugam , Kumar Shailesh , Kaur Navjot
Published: November 2024

Amycolatopsis regifaucium is a Gram-positive actinomycete that produces polyphenol antibiotics such as kigamicins. As a member of the order Actinomycetales which represents a prolific source of biologically active compounds, the genome of this organism was sequenced to explore its biosynthetic potential. Here, we report a draft genome of Amycolatopsis regifaucium DSM 45072T, comprising 8.28 Mb in genome size with 62 contigs, 312 subsystems, 7,966 coding genes, and 52 RNAs with the G+C content of 68.5 mol%. Genome mining studies revealed the presence of an unidentified glycopeptide antibiotic and a type II polyketide synthases (PKS) gene cluster in its genome. Further in-silico analysis, combined with wet lab experiments such as HPLC and LCMS, confirmed the production of decaplanin, previously reported from Amycolatopsis decaplanina DSM 44594T, where its gene cluster was also identified. For the first time, a putative type II PKS gene cluster has been predicted within the glycopeptide antibiotic-producing clade (cluster A) of the genus Amycolatopsis, which is known for producing aromatic polyketide antibiotics, such as kigamicins.
Automated identification of the origin of energy loss in non-oriented electrical steel by feature-extended Ginzburg–Landau free-energy framework
Authors: Taniwaki Michiki , Nagaoka Ryunosuke , Masuzawa Ken , Sato Shunsuke , Foggiatto Alexandre Lira , Mitsumata Chiharu , Yamazaki Takahiro , Obayashi Ippei , Hiraoka Yasuaki , Igarashi Yasuhiko , Mizutori Yuta , Sepehri-Amin Hossein , Ohkubo Tadakatsu , Mogi Hisashi , Kotsugi Masato
Published: November 2024

This study presents the automated identification of the complex magnetization reversal process in non-oriented electrical steel (NOES) using the feature-extended-Ginzburg–Landau (eX-GL) free-energy framework. eX-GL provides a robust connection between microscopic magnetic domains and macroscopic magnetic hysteresis using a data science perspective. This method employs physically meaningful features to analyze the energy landscape, providing insights into the mechanisms behind function. We obtained features representing both the microstructure and energy of the domain wall. The causes of iron loss were traced to the original domain structure, through which we could successfully distinguish and visualize the role of pinning as a promoting and resisting factor. We found that the reversal process was governed not only by general grain boundary pinning but also by segmented magnetic domains within the grain. This method revealed the complex interplay between magnetism and metallography and introduced a new means for transformative material design, bridging structures and functions.
On Feature-based Metric Visual Servoing
Authors: Silveira Geraldo
Published: November 2024

This paper investigates various feature-based metric visual servoing techniques in the teach-by-showing scheme. Metric techniques include all classical 3D and 2D control approaches because they estimate or require some me\-tric (3D) information, such as the camera pose or the scene depth. Unlike standard solutions, this work defines the 3D estimation problem as a 2D-to-2D feature nonlinear registration task, and also exploits the observability issues associated to monocular systems. Such framework allows the development of a family of new feature-based 3D visual servoing strategies with varying degrees of computational complexity and prior knowledge. Three new techniques are then proposed and, as a key contribution, strong connections are found between them and the classical 2D visual servoing methods. These connections lead to a unifying formulation that may open up new research directions, such as on the role of the latter methods and on smooth switching controllers.
Women’s fertility intentions and households’ vulnerability to climate change: responses to cyclones and floods in Bangladesh
Authors: Ahmed Khandaker , Tan Yan , Rudd Dianne
Published: November 2024

This study examines how extreme climatic events and household vulnerability affect such intentions in two Bangladeshi villages: one prone to cyclones and one prone to flooding. Primary data, collected via surveys of 544 married women with at least one child aged 18–49 in 2019–2020, were analysed using a two-stage binary probit regression model. The findings show that household vulnerability to climatic extremes directly and indirectly affects women’s childbearing intentions. Household well-being (livelihood sources, housing, food security, and health status) significantly influenced vulnerability. Women in increasingly vulnerable situations and those wanting two or more children were likely to delay their successive births. In households that had previously experienced flooding, women were more inclined to desire additional children sooner if their well-being was adversely affected. Conversely, those residing in cyclone-prone areas were more likely to postpone their birth plans.
Unaccounted impacts of diterpene emissions on atmospheric aerosol loadings
Authors: Yañez-Serrano Ana , Penuelas Josep , Jorba Oriol , Graeffe Frans , Meder Melissa , Garmash Olga , Zhang Yanjun , Li Haiyan , Luo Yuanyuan , Praplan Arnaud , Hellen Heidi , Schobesberger Siegfried , Vettikkat Lejish , Thomas Steven , Kurtén Theo , Taipale Ditte , Bourtsoukidis Efstratios , Guenther Alex , Ehn Mikael
Published: November 2024

Diterpenes (C20H32) are commonly found in trees, but their emissions into the atmosphere were previously considered unlikely due to their low volatility. Consequently, they have been disregarded in atmospheric chemistry processes. Recent improvements in sampling and analytical instrumentation have enabled the detection and quantification of diterpenes in the gas phase. However, the atmospheric implications of these emissions, including their potential to form secondary organic aerosol (SOA), are not well understood. This study provides the first quantification of kaurene emissions and their potential contribution to secondary organic aerosol (SOA) formation. Here, we incorporate all available emission measurements of kaurene (the most measured diterpene species) and findings from laboratory investigations of SOA formation into a global chemistry transport model to quantify the importance of diterpenes on SOA loads in the atmosphere. Chamber experiments revealed an SOA yield of 4% to 7%, demonstrating the rapid gas-to-particle phase transition, while global kaurene emissions, estimated at 5.1 Tg yr⁻¹, contribute to an SOA burden of 0.005 Tg. Our findings suggest that diterpenes contribute to SOA formation, establishing new links to the biosphere-atmosphere interactions that are increasingly important due to climate warming.
Enhancing consensus on introducing national healthcare workforce metrics in Luxembourg: a hybrid multi-stakeholder consultation protocol
Authors: Goetzinger Catherine , d'Hérouël Aymeric , Berthet Françoise , Dima Alexandra
Published: November 2024

Background
The effectiveness of healthcare delivery depends on the availability of adequately skilled healthcare workforce (HWF) to respond to the current and future needs of healthcare users. Obtaining accurate and timely HWF data is essential for health policy. This article reports on the conceptualization of definitions and a methodology to estimate the active HWF in Luxembourg and presents the protocol for a real-time online Delphi (RT-Delphi) study to consult stakeholders on the methodology proposed.
Methods
Definitions and methods for assessing an active HWF were established through a scoping review and discussions within the project’s steering committee. RT-Delphi study and online multistakeholder meeting are conducted to explore the level of agreement among stakeholders on the proposed definitions and methods determining the active HWF in Luxembourg and collect stakeholder feedback to improve the method. Stakeholders evaluate the proposed definition and methods. They can reconsider their evaluations, multiple times, based on aggregated feedback in real-time and during a final multistakeholder meeting planned for clarification and further debate on open topics, if applicable. We will quantify agreement on the whole sample and per stakeholder group and perform analyses of process to examine variation in responses. Open-text comments and workshop discussions will be analyzed qualitatively via content analysis, and results used to improve the methodology and its implementation in practice.
Results
The scoping review retained seven studies on defining and measuring active healthcare workforce (HWF), revealing a lack of standardized methods and definitions. Workshops recommended adopting the JQNMHC’s definition for Luxembourg due to its alignment with national data reporting needs. Three activity level measurement methods for self-employed HWF were retained. Additionally, a new definition for primary care in Luxembourg was proposed based on recent WHO guidelines, outlining essential functions such as accessibility, comprehensiveness, and coordination.
Conclusion
Involving stakeholders allows for a transparent and structured way to inform conceptualization of indicators to assess HWF activity and better prepare for their adoption and implementation on a national level.
Cardiovascular Disease Prediction Using Machine Learning: An XGBoost Approach with
Hyperparameter Tuning
Authors: Santos Dheiver Francisco
Published: November 2024

Cardiovascular diseases (CVDs) are one of the leading causes of mortality worldwide. Early diagnosis and intervention are crucial to reducing the risk associated with these diseases. In this study, we propose a machine learning-based system for predicting cardiovascular disease using the Extreme Gradient Boosting (XGBoost) technique. We employ feature selection and hyperparameter optimization using random search to enhance the model’s accuracy. The model’s performance is evaluated through cross-validation and compared with other algorithms, including K-Nearest Neighbors (KNN), Na¨ıve Bayes, Support Vector Machine (SVM), and Random Forest. Experimental results show that our XGBoost-based model outperforms the other algorithms with an accuracy of 98% and an area under the ROC curve of 0.98.
Predicting Surgical Complications Using Deep Learning Techniques
Authors: Santos Dheiver Francisco
Published: November 2024

ccurate prediction of surgical complications is crucial for optimizing treatment plans and improving patient outcomes. This paper investigates the application of deep learning models, particularly Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for predicting the likelihood of complications based on patient and surgical data. Using a novel dataset with 1,500 instances and 20 features, we explore the performance of these models compared to traditional machine learning algorithms. Our results show that deep learning models provide superior accuracy, achieving 96
Parametric Study of a Ternary Batch Distillation Column
Authors: bendjaouahdou Chaouki
Published: November 2024

The objective of this research is to study the influence of various parameters on the efficiency of a batch distillation column. The column is loaded with a ternary liquid mixture. The study is carried out by simulation. The parametric study of the ternary batch distillation is carried out in order to highlight the influence functioning parameters on the quality of separation of the three components at the exit of the column. The studied parameters are: withdrawn distillate molar flow rate (D), Number of trays (NT) and the steam molar flow rate through the trays (V). The results obtained by numerical simulation show the possibility of separation of the three components and an optimal case was evidenced in which the parameters values were well determined.
Epidemiology of Helicobacter Pylori Infection Among School Going Children (6-15years) in Jalalabad Afghanistan
Authors: Shinwari Abdullah Jan , Azamee Ahmad Gul
Published: November 2024

Background: Helicobacter pylori infection continues to pose a major global health concern, particularly in low-income countries. It has been linked to growth delays in children, persistent iron deficiency anemia, and chronic antral gastritis, which can lead to duodenal ulcers, gastric ulcers, and possibly gastric adenocarcinoma. This study aims to assess the prevalence of H. pylori infection and investigate the potential risk factors among asymptomatic school-aged children.
Methods: A cross-sectional study was conducted among 460 asymptomatic children aged 6 to 15 years in Jalalabad. Stool samples were collected and tested for H. pylori antigens using the RapiCard test. Socio-demographic, economic, and hygiene-related factors were analyzed using logistic regression to identify potential risk factors.
Results:Among 460 participants, 49.3% tested positive for H. pylori infection, with no gender difference. Older children (13–15 years) had almost double the odds of infection compared to younger children (5–9 years) (AOR = 1.92, p = 0.004). Children from larger families (6–12 or more than 12 members) demonstrated significantly higher odds of infection (AOR = 3.20, p = 0.002; AOR = 4.11, p = 0.001). Parental university education (AOR = 0.28, p = 0.02) and higher family income (AOR = 0.20, p = 0.03) were protective. Occasional consumption of raw vegetables reduced infection risk (AOR = 0.45, p = 0.037), while poor handwashing habits increased it (AOR = 2.03, p = 0.001).
Conclusion: The prevalence of H. pylori infection among school-going children is high, suggesting the need for targeted public health interventions. Parental education appears to be a critical determinant of infection, emphasizing the importance of educational programs to reduce H. pylori transmission.
The Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience
Authors: SALISU Temitope Quadri
Published: November 2024

The study examines the impact of trade openness on economic growth and development in Nigeria from 1980 to 2021. The variables used in the study include the proxy of capital and labour, trade openness, exchange rate, and import and foreign reserves. A different diagnostic test was carried out which included correlation, unit root test and Autoregressive Distributed Lag. Descriptive statistics was used to examine if the explanatory variables and the dependent variable exhibit time-varying volatility and leptokurtosis characteristics. The Augmented Dickey-Fuller (ADF) unit root test was also carried out to check the long-run and short-run relationship of the variables while Аutоrеgrеssіvе dіstrіbutеd lаg (АRDL) bоunds tеstіng рrосеdurе and standardised beta was used to achieve the two specific objectives that were set. The АRDL bоunds tеstіng рrосеdurе revealed that the proxy of capital and labour is the only variables that determine economic growth and development in Nigeria, but trade openness has a positive insignificant effect on economic growth and development in Nigeria. Also, in the short run, the variables that significantly determine economic growth and development are the proxy of capital and labour, exchange rate and import.