bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring New and Promising Genetic Biomarkers for Evaluating Traumatic Brain Injuries: A Case-Control Study
Authors: Rabou Yasmin Kamal Abd , Zayed Abeer Ahmed , Fahim Sally A. , Abdelgwad Marwa , Fiki Ahmed El , Fayed Nermin Nabil 
Published: December 2024

Abstract
Traumatic brain injury (TBI) is a common cause of morbidity and death in all age groups, with an estimated 50 million people having brain injury due to trauma each year. Accurate blood-based biomarkers are needed to assist with diagnosis of patients across the spectrum of time and severity. Our objectives were to explore the diagnostic precision of time- and severity- related four blood-based biomarkers: AKT3, GSK-3β, hsa-miR-16-5p, and MALAT-1 for TBI for the purpose of diagnosis, prognosis, and follow-up. 40 samples were recruited as the following: 30 TBI patients and 10 healthy volunteers as controls with matched age and sex. They were divided according to the Glasgow Coma Scale into mild (mTBI), moderate (modTBI), and severe(sTBI) TBI. Blood samples were withdrawn at entry, and after 5 and 30 days, RT-PCR was used for measuring the expression level. The results showed upregulated expression levels of AKT3, hsa-miR-16-5p and significantly downregulated expression levels of GSK-3β in TBI patients compared to controls at all timings measured. mTBI patients showed a higher expression level of hsa-miR-16-5p compared with modTBI, and sTBI patients. MALAT-1 level showed a significant increase in severe cases only. We concluded that AKT3, hsa-miR-16-5p, and GSK-3β are excellent diagnostic biomarkers in TBI patients at initial assessment, as well as at 5 and 30 days following the injury. Moreover, MALAT-1 had good diagnostic value in sTBI patients, and its prognostic value extends to 30 days. GSK-3β was an excellent biomarker for detecting mTBI.
How to be happy from east to west: social and flexible pursuit of happiness is associated with positive effects of valuing happiness on well-being
Authors: Zhang Hanxin , Kahriz Bahram Mahmoodi , McCabe Ciara , Vogt Julia 
Published: December 2024

Abstract
Recent evidence has suggested that valuing happiness to an extreme degree has a potential downside in Western but not in East Asian countries. We tested how valuing happiness relates to well-being in mainland China (N = 721) and Western countries (UK, US, and Canada) (N = 349) in two online survey studies. We predicted that pursuing happiness in a socially engaged yet flexible (i.e., feasible and achievable) way underlies a positive association between valuing happiness and well-being. Indeed, in study 1, a socially engaged definition of happiness mediated the relationship between valuing happiness and well-being in a Chinese sample. Specifically, increased valuing happiness was associated with a higher socially engaged definition of happiness, which in turn was related to higher well-being. Demonstrating the role of flexibility in pursuing happiness, Chinese participants reported more items overall and more feasible items to achieve happiness, though not more social items than participants in the Western sample). In study 2, we repeated the study during the Covid-19 lockdown in Chinese (N = 308) and Western (N = 185) samples and also tested if participants were able to adopt a mindset of flexibly pursuing happiness by adding a survey with social actions that were still feasible (e.g., a call instead of meeting in-person). We found the association holds in times of emotional stress and social restrictions in both samples, suggesting that people flexibly pursue social activities that relate to happiness. We propose that a socially engaged but also feasible and flexible way to pursue happiness is associated with higher well-being.
Nonparametric Analysis of Multivariate Data in Factorial Designs with Nondetects: A Case Study with Microbiome Data
Authors: Kiefel Maximilian , Freidl Johanna 
Published: December 2024

AbstractThe term “nondetects” describes observations that are not fully observed because the true value is below a detection threshold—and can therefore not be precisely detected. One may also consider them a special case of left-censored data. Nondetects occur frequently, for instance, in life sciences research in medicine or microbiology. This article examines the use of nonparametric inference methods for multivariate data in factorial designs in situations where nondetects are present, and it evaluates their performance. The focus is on testing hypotheses regarding interaction and main factor effects. The nonparametric centerpiece of the methodology is assuming the nonparametric relative effect (probabilistic index) and its generalizations as the functional on which inference is built, along with the respective invariance properties of the resulting tests. On this basis, we apply and evaluate recently proposed nonparametric analogs to the following types of multivariate test statistics: (1) Wald-type statistic (WTS), (2) ANOVA-type statistic (ATS), (3) Lawley–Hotelling trace, (4) Wilks Lambda (Likelihood ratio), (5) Bartlett–Nanda–Pillai trace. Except for the WTS, all the mentioned methods are available through the R-package nparmd. Extensive simulations and a case study from the field of microbiology demonstrate that the proposed methods can handle commonly occurring rates of nondetects without substantial impairment of specificity and sensitivity.
Normalising inhomogeneities in geo-social media data – a comparison of different measures
Authors: Hauthal Eva , Mukherjee Sagnik , Burghardt Dirk 
Published: December 2024

Abstract
Geo-social media data involve various kinds of inhomogeneities. These can concern, amongst others, the users, but also spatial distributions or the fact that the most frequently used hashtags, keywords or emojis often have little relevance in the context under investigation. In order to properly tackle and reduce these inhomogeneities and to strive for a less distorted analysis, normalisation of geo-social media data is expedient. Various measures exist that are frequently used in research for this purpose. This paper presents four of these measures and compares them with each other, both theoretically as well as practically in the form of a demonstration through three exemplary case studies highlighting potentials and limitations of each measure. This comparison involves the relatively new typicality measure, which was developed specifically for this type of data following the dimensions commonly used to describe geo-social media data (temporal, spatial, social and thematic dimension).
Effects of the COVID-19 Lockdown on HbA1c Levels of Ethnic Minorities and Low-income Groups with Type 2 Diabetes in Israel
Authors: Riklin Galia , Friger Michael , Shoham-Vardi Ilana , Golan Rachel , Wainstock Tamar 
Published: December 2024

Abstract
Aims
To investigate the impact of low socioeconomic status (SES) and/or membership in ethnic minority has on HbA1c before and during the COVID-19 lockdown.

Methods
A retrospective cohort study was conducted between March 2019 and March 2021, based on data from electronic medical records of 17,072 patients with type-2 diabetes, collected by Clalit (Israel’s largest health maintenance organization). Low SES was compared to high and ethnic minorities (Arabs and ultra-Orthodox Jews) were compared to the general Israeli population of mostly Jewish, but not ultra-Orthodox, Israeli citizens. Quantile regressions were used to examine the impact of SES and ethnic minority membership on HbA1c levels in the 0.10, 0.25, 0.50, 0.75, 0.90 quantiles before and during the lockdown.

Results
In the pre-lockdown period, patients with type-2 diabetes of low versus high SES, and Arabs versus the general population, had higher HbA1c. During the lockdown HbA1c levels of low versus high SES rose significantly in the 0.10 and 0.90 quantiles, and among Arabs HbA1c levels rose significantly across all quantiles, with a remarkable increment in the 0.90 quantile (from 0.316% in the pre-lockdown period to 0.730% in the lockdown period). Ultra-Orthodox Jewish diabetic patients had a marginally higher mean HbA1C level regardless of the period. Quantile regressions did not reveal a significant difference between the ultra-Orthodox Jewish and the general population.

Conclusion
The lockdown exacerbated disparities in glycemic control between low and high SES individuals and between Arab minority and the general population.
Voting Restrictions and Increased Odds of Adverse Birth Outcomes in the US
Authors: Liu Sze Yan , Grinshteyn Erin , Cook Daniel , Pabayo Roman 
Published: December 2024

Abstract
Background
Disparities persist in adverse birth outcomes — preterm birth and small-for-gestational age (SGA) among racialized populations. Previous studies have indicated that voting restrictions are associated with health outcomes, such as access to health insurance and teenage birth rates. This paper examines whether the association between voting restrictions and adverse birth outcomes varies according to birthing individuals’ race/ethnicity.

Methods
These analyses merged individual-level 2019–2020 Pregnancy Risk Assessment Monitoring System (PRAMS, 8th edition) data with state-level exposure information. The exposure, the Cost of Voting Index (COVI), is a 2020 state-level measure of voting restrictions, and the outcomes were preterm birth and SGA. Multilevel logistic regression, survey-weighted models adjusted for sociodemographic and geographically-based characteristics. Subanalyses examined if the association differed by race (non-Hispanic White, non-Hispanic Black, Hispanic, API, Other).

Results
In the unadjusted model, a standard deviation increase in COVI was associated with increased odds of preterm birth (OR = 1.11, 95% CI = 0.98, 1.25) and SGA (OR = 1.12, 95% CI = 1.02, 1.22). The association for SGA was still significant in the fully adjusted models. Results differed by race/ethnicity with the largest effects among API (OR = 1.20, 95% CI = 0.95, 1.52) for preterm birth and OR = 1.27, 95% CI = 1.01, 1.59) for SGA respectively).

Conclusion
Our results suggest structural voting barriers disproportionately increase the odds of adverse birth outcomes, especially for API-birthing individuals. Increasing voting restrictions may amplify existing birth inequities.
Assessing how Grazing Intensity Affects the Spatial Distribution of Soil Properties
Authors: Barrena-González Jesús , Antoneli Valdemir , Contador J Francisco Lavado , Fernández Manuel Pulido 
Published: December 2024

AbstractGrazing activities occupy the largest land surface, making their management crucial for addressing key issues related to the sustainability of agroecosystems. This study seeks to identify the influence of grazing intensity and vegetation cover on the spatial distribution of soil properties in a farm located in a dehesa ecosystem (SW, Spain). To achieve this, 144 soil samples were collected at 0–5 and 5–10 cm depths across six grazing intensity classes (GIC) defined by the current spatial distribution of vegetation canopy. Leveraging 25 environmental covariates, five individual machine learning algorithms (MLAs) and an ensemble model were employed, to predict soil property values. Metrics such as R2, RMSE (root mean square error), and CCC (Lin’s concordance correlation coefficient) were used to determine the best-performing model. The results revealed that high-intensity grazing classes showed higher values of soil nutrients, and SOC (soil organic carbon)than low-intensity grazing classes. Nevertheless, there no significant differencesin areas with shrub and tree canopy cover. Also, the results reveld that different between depth interval were higher in high-intensity class than in low-intensity classes. The study highlights the importance of selecting environmental variables for accurate soil property prediction. The best model depend on soil property selected and depth interval. In conclusion, this studyoffers valuable insights into grazing intensity and vegetation’s influence on soil properties in dehesa ecosystems, guiding future studies in this field.
Comprehensive Monitoring System for High-Risk Pregnancies
Authors: Gonzalez Santiago Paeres , Montoya Germán A. , Lozano-Garzón Carlos 
Published: December 2024

AbstractPrenatal care protects the Health of both mother and baby, influencing the development and well-being of the mother-child duo. Risks during pregnancy, such as preeclampsia or gestational diabetes, can have long-term effects on the mother’s Health. Effective monitoring of pregnancy risks is essential for improving health outcomes. Therefore, we propose the development of an integrated high-risk pregnancy monitoring mobile application incorporating IoT sensors (smartwatches) to monitor critical biomedical variables. This allows healthcare professionals to collect and analyze data, reducing prenatal risks and improving maternal and fetal health outcomes. Functional and non-functional requirements were gathered and refined through continuous support and iterative meetings with an experienced gynecologist. We identified multiple functional requirements through user stories. Non-functional requirements were also collected to design the proposed architecture and comply with current legislation, prioritizing the security and privacy of biomedical data. We conducted Load tests on the proposed architecture, verifying the system’s quality attributes. Additionally, we carried out usability tests through interviews with a sample of ten pregnant women. Participants found the application intuitive and essential for monitoring their Health, and it could provide a constant source of confidence throughout their pregnancy. The proposed system could be a valuable tool for high-risk pregnancy monitoring. However, large and intensive clinical trials are essential to validate its effectiveness in real-life scenarios.
Circular Commons: Exploring Innate Spatial Tactics as Pathways toward a Circular Built Environment
Authors: Egger Tamara , van Dorst Machiel , Ioannou Olga , den Heijer Alexandra 
Published: December 2024

AbstractThe built environment significantly contributes to current socioenvironmental crises, necessitating systemic change. Circularity and the commons are re-emerging as potential pathways for such transition. A circular built environment (CBE) aims to close resource loops, but its implementation is often slow and neglects social and local aspects. The commons framework emphasizes local involvement and sustainable self-management of shared resources. However, the intersection of circularity and the commons in spatial production is underexplored. This paper explores their relationship as “innate spatial tactics,” referring to the ways ordinary people interact with the built environment to meet their daily needs. Through a literature review, we developed a conceptual framework of “circular commoning,” encompassing three dimensions: resources, people, and governance. We applied this framework to analyze 16 empirical examples of circular commoning in contemporary urban settings. Our research shows that circularity and the commons are closely linked and mutually beneficial. Circular commoning involves diverse resources, changing social roles, and innovative governance. We identified three forms of circular commoning as innate spatial tactics: building circular, circular use of space, and creating spaces for circular activities. The framework developed here provides a basis for further action research. The practice review demonstrates that circular commoning is not only a distant utopian ideal but is enacted daily in diverse urban contexts. Such often-overlooked innate spatial tactics can offer valuable lessons for pathways toward a CBE involving principles of a circular society. Additionally, they can help shape new narratives and channel hope for practical progress towards circular futures.
Bio-nanopore technology for biomolecules detection
Authors: Li Peizhi , Liang Dan , Yang En , Zeb Mustafa , Huang Huiqi , Sun Haihui , Zhang Wenhan , Peng Chifang , Zhao Yuan , Ma Wei 
Published: December 2024

AbstractBio-nanopore technology holds great promise in biomacromolecule detection, with its high throughput and low cost positioning it as an ideal detection tool. This technology employs a unique detection mechanism that utilizes nanoscale pores to rapidly and sensitively convert biological molecules interactions into electrical signals, enabling real-time, single-molecule detection with exceptional sensitivity. This review focuses on the latest advancements in this technology across various domains, including DNA and RNA sequencing, protein detection, and small molecule identification. Additionally, future trends are explored, providing a comprehensive and in-depth perspective on the role of bio-nanopore technology in biomolecule detection.
Research on multiple quadrotor UAV formation obstacle avoidance based on finite-time consensus
Authors: Zhang L. , Liu R. , Qu B. , Wei T. , Chai X. , Yan L. 
Published: December 2024

Abstract
Aiming at the problem of fast and consensus obstacle avoidance of multiple unmanned aerial systems in undirected network, a multi-quadrotor unmanned aerial vehicles UAVs (QUAVs) finite-time consensus obstacle avoidance algorithm is proposed. In this paper, multi-QUAVs establish communication through the leader-following method, and the formation is led by the leader to fly to the target position automatically and avoid obstacles autonomously through the improved artificial potential field method. The finite-time consensus protocol controls multi-QUAVs to form a desired formation quickly, considering the existence of communication and input delay, and rigorously proves the convergence of the proposed protocol. A trajectory segmentation strategy is added to the improved artificial potential field method to reduce trajectory loss and improve the task execution efficiency. The simulation results show that multi-QUAVs can be assembled to form the desired formation quickly, and the QUAV formation can avoid obstacles and maintain the formation unchanged while avoiding obstacles.
Fragments of Thought: Considering Sophie Germain’s Process Epistemology
Authors: Tamboukou Maria 
Published: December 2024

Abstract
In this paper I look at the philosophical work of Sophie Germain, a woman mathematician and philosopher in nineteenth-century France. Although forgotten after her death, Germain’s contribution to mathematical sciences has been revisited and reappraised in recent years, but with very few notable exceptions, her philosophical work is still in the margins. In addressing this gap in the literature, I revisit Germain’s contribution to the history of ideas, particularly focusing on her contribution to process epistemologies. I argue that Germain was a truly transdisciplinary thinker avant la lettre and that her philosophical work should be mapped in the wider field of process philosophies. In doing so I make connections between Sophie Germain and Alfred Whitehead’s philosophy of the organism, particularly focusing on their take on feelings, prehensions, happy ideas, and events.
Genetic diversity within a tree and alternative indexes for different evolutionary effects
Authors: Iwasa Yoh , Tomimoto Sou , Satake Akiko 
Published: December 2024

Abstract
Trees, living for centuries, accumulate somatic mutations in their growing trunks and branches, causing genetic divergence within a single tree. Stem cell lineages in a shoot apical meristem accumulate mutations independently and diverge from each other. In plants, somatic mutations can alter the genetic composition of reproductive organs and gametes, impacting future generations. To evaluate the genetic variation among a tree’s reproductive organs, we consider three indexes: mean pairwise phylogenetic distance (

$\overline{D}$

), phylogenetic diversity (

$PD$

; sum of branch lengths in molecular phylogeny) and parent-offspring phylogenetic distance (

${D}_{PO}$

). The tissue architecture of trees facilitated the accumulation of somatic mutations, which have various evolutionary effects, including enhancing fitness under strong sib competition and intense host-pathogen interactions, efficiently eliminating deleterious mutations through epistasis and increasing genetic variance in the population. Choosing appropriate indexes for the genetic diversity of somatic mutations depends on the specific aspect of evolutionary influence being assessed.
Openness, Phenomenology, Politics: Luciano Berio and the Neoavanguardia in the Early 1960s
Authors: DAVIS JAMES 
Published: December 2024

AbstractLuciano Berio’s modernism, which has fallen off the critical radar since the composer’s death, is not typically tied to extroverted political statements, and so does not easily allow for the fashionable (liberal) equation of aesthetic radicalism with political radicalism. On the contrary, Berio’s musical output is perhaps instructive precisely as a negative case study of the link between political and aesthetic radicalisms. Such will be the gambit of this article, which will consider the engagement with contemporary ideas of ‘openness’ and practices of phenomenology in works from the early 1960s, like Passaggio (1962) and Epifanie (1963), to illuminate Berio’s relationship to the so-called neoavanguardia, a cultural movement which emerged in the 1950s and 1960s as part of a withdrawal from the cultural–political activism associated within Italy’s leftist intelligentsia.
Comorbidity of problematic substance use and other addictive behaviors and anxiety, depression, and post-traumatic stress disorder: a network analysis
Authors: Shmulewitz Dvora , Levitin Maor Daniel , Skvirsky Vera , Vider Merav , Eliashar Roi , Mikulincer Mario , Lev-Ran Shaul 
Published: December 2024

AbstractBackgroundAmong those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used.MethodsIn a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model.ResultsStrongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use.ConclusionsNetwork analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.