bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between iKaluk/Arctic charr (Salvelinus alpinus) and estuarine benthic diatom habitats in nearshore Nunatsiavut waters
Authors: MacMillan-Kenny Zachary , Denniston Mary , Edinger Evan , Templeton Adam , Côté David , Limoges Audrey , Robert Katleen 
Published: January 2025

Abstract
iKaluk, Inuttitut for Arctic charr (Salvelinus alpinus), holds significant commercial and cultural value for Inuit communities throughout Nunatsiavut. Studies evaluating iKaluk habitat associations in freshwater are plentiful; however, there is limited information on the ecological makeup and sediment characteristics of anadromous charr habitats in marine environments. This study investigated the benthic associations of Arctic charr during their marine residency period in Nain, Nunatsiavut, using underwater videos, harvester-identified fishing locations, and acoustic telemetry. Drop-camera surveys were deployed on previously placed hydrophone acoustic receivers and within harvester-identified fishing locations to describe and quantify available benthic habitats in the study area. Telemetry information was used to identify charr occupancy hotspots, and calculate habitat suitability indices. A total of 248,056 benthic organisms belonging to 63 morphotaxa were identified within the 125 video drops used for benthic community characterization and these represented five faunal assemblages. Marine phase charr occupied estuaries to a greater degree than other fjord or coastal headland environments and these habitats were typically characterized by fine sediments covered by high densities of brittle stars (Ophiuroidea spp.) and benthic diatom mats. The consistent presence of diatomaceous sediments is indicative of abundant foraging opportunities. The importance of these habitats to iKaluk, need to be considered in future marine planning given the cultural and ecological value of this species to many northern communities that face growing threats from environmental change.
Change in kidney volume growth rate and renal outcomes of tolvaptan treatment in autosomal dominant polycystic kidney disease: post-hoc analysis of TEMPO 3:4 trial
Authors: Higashihara Eiji , Matsukawa Miyuki , Jiang Huan 
Published: January 2025

Abstract
Background
Despite of long-lasting tolvaptan treatment, individual renal outcomes are unclear in autosomal dominant polycystic kidney disease (ADPKD). This post-hoc analysis of the TEMPO 3:4 trial aimed to evaluate the predictability of estimated height-adjusted total kidney volume growth rate (eHTKV-α) on renal outcomes.

Methods
In TEMPO 3:4, 1445 patients with ADPKD were randomised to tolvaptan or placebo for 3 years. The present analysis included patients with total kidney volume (TKV) data available at baseline and month 12 (tolvaptan, n = 812; placebo, n = 453); tolvaptan-assigned patients were grouped into quartiles based on percent change in eHTKV-α from baseline at 1 year. Clinical parameters were compared between quartiles, and regression analyses evaluated the predictive value of 1-year percent change in eHTKV-α and other factors on annual changes in TKV and estimated GFR (eGFR) over 3 years.

Results
Trend tests identified significant differences between quartiles for several baseline parameters. Multivariate regression models confirmed that 1-year percent change in eHTKV-α was a significant predictor of annual changes in both TKV and eGFR over 3 years. Other significant predictors of annual changes in TKV and eGFR over 3 years were sex, age and body mass index, and first-year change in eGFR, race and baseline eGFR, respectively. Predicting factors using urine osmolality and plasma copeptin levels were not significant by backward stepwise selection analysis.

Conclusions
1-year percent change in eHTKV-α is useful biomarker to identify treatment good responders and may be utilized for early estimate of trial outcomes of new drugs in ADPKD.
Deciphering Necroptosis-Associated Molecular Subtypes in Acute Ischemic Stroke Through Bioinformatics and Machine Learning Analysis
Authors: Wu Zongkai , Fan Hongzhen , Qin Lu , Niu Xiaoli , Chu Bao , Zhang Kaihua , Gao Yaran , Wang Hebo 
Published: January 2025

AbstractAcute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investigate their potential as diagnostic and therapeutic targets for AIS. Expression profiling data were acquired from the Gene Expression Omnibus database, and necroptosis-associated genes were retrieved from GeneCards. The differentially expressed genes (DEGs) and necroptosis-related genes were intersected to obtain the necroptosis-related DEGs (NRDEGs) in AIS. In AIS, a total of 76 genes associated with necroptosis (referred to as NRDEGs) were identified. Enrichment analysis of these genes revealed that they were primarily enriched in pathways known to induce necroptosis. Using weighted gene co-expression network analysis (WGCNA), five co-expression modules consisting of NRDEGs were identified, along with two modules that exhibited a strong correlation with AIS. Protein–protein interaction (PPI) analysis resulted in the identification of 20 hub genes. The Least absolute shrinkage and selection operator (LASSO) regression model demonstrated promising potential for diagnostic prediction. The receiver operating characteristic (ROC) curve validated the diagnostic model and selected nine characteristic genes that exhibited statistically significant differences (p < 0.05). By employing consensus clustering, distinct patterns of necroptosis were identified using these nine signature genes. The results were validated by quantitative PCR (qPCR) in venous blood from patients with AIS and healthy controls and HT22 cells, as well as external datasets. Furthermore, the analyzed ceRNA network included nine lncRNAs, six miRNAs, and three mRNAs. Overall, this study offers novel insights into the molecular mechanisms underlying NRDEGs in AIS. The findings provide valuable evidence and contribute to our understanding of the disease.
Role of sludge biochar immobilized multifunctional microbiome in phytoremediation of lead-zinc composite pollution
Authors: Yang Zihao , Jiang Lijuan , Li Xuejun , Ji Qiaoling , Wang Mengyuan , Zhang Yi , Cheng Yuanlin , Zhang Xuan , Li Hui , Feng Chongling 
Published: January 2025

AbstractSludge biochar, as a soil amendment, has demonstrated its capacity to remediate heavy metal-contaminated soil. It is frequently utilized to facilitate phytoremediation or as a microbial carrier in remediation strategies, aiming to enhance overall remediation efficiency. Nonetheless, there exists a knowledge gap regarding the influence of biochar on the migration and accumulation of Pb and Zn within soil-microbe-plant systems, as well as its effects on plant growth conditions and microbial community composition. This study constructed a multifunctional microbiome and evaluated the role of microbiome and biochar in phytoremediation under Pb and Zn stress. Biochar immobilized microbiome (MB) significantly enhanced phytoremediation and showed synergistic effects by improving root phenotypes up to 2.4 times compared to the untreated group (CK). Meanwhile, the MB increased Pb root absorption by 56.9% and Zn aboveground transfer by 30%, and reduced the acid-extractable content of Pb and Zn under high concentrations. In addition, microbial community composition and diversity analyses showed that the bacterial and fungal communities of MB were more stable while multifunctional microbiome reshaped microbial community with boosted abundance of plant growth promoting microorganisms, and fungi of saprotroph and symbiotroph nutritional categories. This study provided a novel phytoremediation approach of castor with the combination of multifunctional microbiome and biochar.
Graphical Abstract
Creating Time and Space for the Intersection of Climatological Disasters and Racial Inequalities Curricula in the Classroom
Authors: DeVincenzo Joshua L. , Ahmadi Tina , Buena Lea , Zapata Daisy , Han Sori , Tingley Christopher , Panwar Himanshu , Gan Linfan 
Published: January 2025

Abstract
Racial disparities and climatological disasters are complex topics rarely addressed in K-12 curricula. Each topic has long been neglected vis-à-vis a pedagogy that has either lagged behind contemporary issues or has intentionally sidestepped the importance of addressing these themes through legal and policy mechanisms that limit educators’ ability to discuss each topic. When it comes to students and communities of color in the U.S. who are unequally vulnerable to and affected by the impacts of climate change, it is a significant disservice not to provide fundamental learning opportunities that allow students to engage and contribute to the discourse surrounding these pressing issues. This project was intended to support educators and administrators in implementing pedagogy around these topics conducive to curriculum standards and explicitly developed content for students in grades 8-12. The research question was, “How can the racial inequalities of disaster vulnerability and recovery be addressed in the classroom effectively to build a comprehensive knowledge base, to educate and empower a generation of students who will experience considerably more climatological disasters in the future?"
Community Involvement in COVID-19 Management: A Central Component of Comprehensive Public Health Responses to COVID-19 and Future Health Crises
Authors: Aghakhani Nader , Ewalds-Kvist Béatrice Marianne , Azami Mehdi , Amini Rarani Saeid 
Published: January 2025

Abstract
The COVID-19 pandemic is highly contagious, with symptoms such as myalgia, cough, fever, and weakness, posing a greater risk to older adults and individuals with chronic conditions. Effective management requires meaningful community involvement to reduce health inequalities and ensure people-centered health care. Engaging local voices, including leaders, health care professionals, and vulnerable populations, enhances decision-making, transparent communication, and resource mobilization. A whole-community approach, involving collaboration across various sectors, strengthens prevention, testing, and recovery efforts. By prioritizing vulnerable groups and adapting interventions to local contexts, community engagement plays a vital role in addressing the pandemic’s challenges and building a resilient health care system. This strategy not only aids in managing the current crisis but also prepares public health systems for future emergencies, emphasizing equity and comprehensive public health responses.
Post-Traumatic Symptoms and Sleep Problems in Children and Adolescents after Twin Earthquakes in Turkey
Authors: Koçak Hatice Serap , Kiliç Fedli Emre , Kaplan Serin Emine 
Published: January 2025

Abstract

Objectives
Earthquakes cause great destruction due to their suddenness and intensity. Although all people are affected by earthquakes, children are among those most affected. Every year, millions of children and young people are exposed to many natural disasters and are affected differently. Earthquakes can cause physical, mental, and sleep disorders in children. The aim of this study is to investigate the post-traumatic response and its effects on sleep on child and adolescent earthquake survivors living in the earthquake zone in Turkey.

Methods
This research was carried out between June and August 2023 as a descriptive and cross-sectional study. A total of 230 earthquake survivor children from Adıyaman were included in the study. Personal information forms, the Child Posttraumatic Stress Reaction Index (CPTS-RI), and the Sleep Disturbance Scale for Children (SDSC) were used to collect data.

Results
It was determined that the scale scores of the children who were financially affected by the earthquake, who were injured, and who were under the rubble were higher (P < 0.05).

Conclusions
It was observed that more than half of the children had severe trauma and had sleep disorders. Children who experience trauma from an earthquake have more sleep disorders. For this reason, in addition to emergency aid and interventions in earthquakes, arrangements should be made for the mental health of children and social and psychological support should be provided.
Temporal Trends in Treatment Interruption among the Victims of Heavy Rain Disasters in Japan: Findings from Emergency Medical Team Data
Authors: Nakamura Yuichi , Fukunaga Ami , Nagata Tatsuhiro , Chimed-Ochir Odgerel , Yumiya Yui , Taji Akihiro , Akahoshi Kouki , Toyokuni Yoshiki , Chishima Kayako , Mimura Seiji , Wakai Akinori , Kondo Hisayoshi , Koido Yuichi , Kubo Tatsuhiko 
Published: January 2025

Abstract

Objectives
Treatment interruptions in disaster victims are concerning, owing to an increase in natural disasters and the growing elderly population with chronic conditions. This study examined the temporal trends in treatment interruptions among victims of 2 recent major heavy rain disasters in Japan: West Japan heavy rain in 2018 and Kumamoto heavy rain in 2020.

Methods
Data for this study were derived from the national standardized medical data collection system called the “Japan Surveillance in Post-Extreme Emergencies and Disasters.” Joinpoint regression analysis was performed to examine the daily trends in treatment interruptions reported soon after each disaster onset.

Results
A total of 144 and 87 treatment interruption cases were observed in the heavily affected areas of the West Japan heavy rain in 2018 and Kumamoto heavy rain in 2020, respectively. In both disasters, a high number of treatment interruption cases were observed on the first day after the disaster. Joinpoint regression analysis showed that trends in the percentage of treatment interruptions differed between the 2 disasters at different disaster scales.

Conclusions
The findings suggest the importance of a prompt response to treatment interruptions in the immediate aftermath of a disaster and consideration of the specific characteristics of the disaster when planning for disaster preparedness and response.
Skip-WaveNet: a wavelet based multi-scale architecture to trace snow layers in radar echograms
Authors: Varshney Debvrat , Yari Masoud , Ibikunle Oluwanisola , Li Jilu , Paden John , Gangopadhyay Aryya , Rahnemoonfar Maryam 
Published: January 2025

Abstract
Airborne radar sensors capture the profile of snow layers present on top of an ice sheet. Accurate tracking of these layers is essential to calculate their thicknesses, which are required to investigate the contribution of polar ice cap melt to sea-level rise. However, automatically processing the radar echograms to detect the underlying snow layers is a challenging problem. In our work, we develop wavelet-based multi-scale deep learning architectures for these radar echograms to improve snow layer detection. These architectures estimate the layer depths with a mean absolute error of 3.31 pixels and 94.3% average precision, achieving higher generalizability as compared to state-of-the-art snow layer detection networks. These depth estimates also agree well with physically drilled stake measurements. Such robust architectures can be used on echograms from future missions to efficiently trace snow layers, estimate their individual thicknesses, and thus support sea-level rise projection models.
Knowledge-driven neural models for extraction and analysis of sustainability events from the web
Authors: Naskar Abir , Goel Tushar , Chauhan Vipul , Verma Ishan , Dasgupta Tirthankar , Dey Lipika 
Published: January 2025

Abstract
Sustainability practices of a company reflect its commitments to the environment, societal good, and good governance. Institutional investors take these into account for decision-making purposes, since these factors are known to affect public opinion and thereby the stock indices of companies. Though sustainability score is usually derived from information available in self-published reports, News articles published by regulatory agencies and social media posts also contain critical information that may affect the image of a company. Language technologies have a critical role to play in the analytics process. In this paper, we present an event detection model for detecting sustainability-related incidents and violations from reports published by various monitoring and regulatory agencies. The proposed model uses a multi-tasking sequence labeling architecture that works with transformer-based document embeddings. We have created a large annotated corpus containing relevant articles published over three years (2015–2018) for training and evaluating the model. Knowledge about sustainability practices and reporting incidents using the Global Reporting Initiative (GRI) standards have been used for the above task. The proposed event detection model achieves high accuracy in detecting sustainability incidents and violations reported about an organization, as measured using cross-validation techniques. The model is thereafter applied to articles published from 2019 to 2022, and insights obtained through aggregated analysis of incidents identified from them are also presented in the paper. The proposed model is envisaged to play a significant role in sustainability monitoring by detecting organizational violations as soon as they are reported by regulatory agencies and thereby supplement the Environmental, Social, and Governance (ESG) scores issued by third-party agencies.
The promise of neuromorphic edge AI for rural environmental monitoring
Authors: Aral Atakan 
Published: January 2025

Abstract
Edge AI is the fusion of edge computing and artificial intelligence (AI). It promises responsiveness, privacy preservation, and fault tolerance by moving parts of the AI workflow from centralized cloud data centers to geographically dispersed edge servers, which are located at the source of the data. The scale of edge AI can vary from simple data preprocessing tasks to the whole machine learning stack. However, most edge AI implementations so far are limited to urban areas, where the infrastructure is highly dependable. This work instead focuses on a class of applications involved in environmental monitoring in remote, rural areas such as forests and rivers. Such applications have additional challenges, including failure proneness and access to the electricity grid and communication networks. We propose neuromorphic computing as a promising solution to the energy, communication, and computation constraints in such scenarios and identify directions for future research in neuromorphic edge AI for rural environmental monitoring. Proposed directions are distributed model synchronization, edge-only learning, aerial networks, spiking neural networks, and sensor integration.
The Pre-Removal Detention of Immigrants: A Return to Ordinary Meaning
Authors: Schotel Bas , Venzke Ingo 
Published: January 2025

Abstract
The EU Return Directive demands that immigrant detention be as short as possible, but, by logical implication, this also means that detention can be as long as necessary. What concerns the maximum length of detention, the Return Directive is remarkably generous: Immigrants can be detained for a period of up to eighteen months—a deprivation of liberty that is otherwise justified only as punishment for serious crimes. The practice of such long-term detention, now burgeoning, is highly questionable for moral, practical, and—our focus—legal reasons.
The European Convention of Human Rights (ECHR) provides the relevant yardstick. While discussions on the legality of immigrant detention have focused on requirements of necessity, we shift attention towards the surprisingly absent question of maximum duration. Our analysis delves into the drafting context of the ECHR to reveal that it only authorizes the pre-removal detention of immigrants for markedly short periods. Picking up the interpretative canon of the regime, we note that meanings can of course change, but we argue that it is a legal mistake to consider that long-term detention is now sanctioned by the Convention.
Multi-parametric characterization of proton bunches above 50 MeV generated by helical coil targets
Authors: Martin P. , Ahmed H. , Cavanagh O. , Ferguson S. , Green J. S. , Greenwood B. , Odlozilik B. , Borghesi M. , Kar S. 
Published: January 2025

Abstract
Tightly focused proton beams generated from helical coil targets have been shown to be highly collimated across small distances, and display characteristic spectral bunching. We show, for the first time, proton spectra from such targets at high resolution via a Thomson parabola spectrometer. The proton spectral peaks reach energies above 50 MeV, with cutoffs approaching 70 MeV and particle numbers greater than 10

${}^{10}$

. The spectral bunch width has also been measured as low as approximately 8.5 MeV (17% energy spread). The proton beam pointing and divergence measured at metre-scale distances are found to be stable with the average pointing stability below 10 mrad, and average half-angle beam divergences of approximately 6 mrad. Evidence of the influence of the final turn of the coil on beam pointing over long distances is also presented, corroborated by particle tracing simulations, indicating the scope for further improvement and control of the beam pointing with modifying target parameters.
Modernization of Ukrainian Trademark Law: A New Generation of Protection
Authors: Mykhailiuk Galyna , DiMatteo Larry A. 
Published: January 2025

AbstractThis article examines the current state of Ukrainian trademark law to enhance further Ukrainian integration into the European and global intellectual property law systems. Ukraine must be seen as a jurisdiction with a high level of trademark protection, as the momentum has swung in favor of Ukraine's admission to the European Union (EU). It also serves as a case study of a country transitioning from an older, obsolete trademark system to a modern one. The article explores the facets of trademark law, both substantive and procedural, that make up a modern, progressive trademark protection law system. The article uses United States (US) and EU trademark laws as benchmarks to compare the development of Ukraine's law on the subject. It explores recent legislative reforms and existing proposals to enhance trademark protection. Particular attention is paid to the 2020 and 2023 Amendments that recognize trademark dilution as a separate cause of action and provide a more precise delineation of the fair use of a trademark, as well as the modernization of the registration process and actions related to trademark opposition and infringement. Additionally, issues related to the revocation, invalidity, and enforcement of trademarks are analyzed. The article concludes that, when fully implemented, the existing intellectual property reform legislation will improve the efficiency of trademark protection in Ukraine.