bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sizing of an On-site Hydrogen Refueling System for a Fleet of Fuel Cell Buses in Dhulikhel-Kathmandu Route
Authors: Kafle Nawaraj , Phuyal Tej Prasad , Dhrubabar Singh K.C , Niroula Sagar , Sakhya Nashla , Singh Thapa Biraj 
Published: September 2024

Abstract
Nepal’s heavy-duty vehicle fleet relies entirely on imported fossil fuels, posing significant environmental risks due to high particulate matter (PM) emissions. Battery-powered alternatives are unsuitable for large fleets due to trade-offs between range and vehicle weight, which is not an issue for hydrogen-powered fuel cell electric vehicles (FCVs). Shifting to hydrogen fuel offers a promising solution for sustainable, emission-free heavy-duty vehicle operation. Fuel cell buses (FCBs) represent a transformative step in transportation, prioritizing environmental protection, decarbonization, and achieving net-zero carbon emissions by 2045. This paper reviews the critical components for developing an on-site hydrogen refueling station (OHRS). It analyzes the power requirements of vehicles operating on inclined roads based on vehicle modeling. By studying existing diesel buses on the route, the specifications needed for FCBs are determined. It involves Excel-based calculations of fuel demand, vehicle drive cycle modeling, infrastructure assessment, and capacity determination for a fleet of ten hydrogen buses. The analysis reveals that the maximum tractive power required is 119.85 kW, with buses averaging a velocity of 6.8 m/s, reaching a maximum of 20.75 m/s, and achieving a maximum acceleration of 0.96 m/s2. The average motor power required is 13.09 kW, with a maximum of 151.48 kW. Each bus requires 8 kg of hydrogen per day, necessitating an OHRS capable of producing 80 kg per day for a fleet of 10 buses. Consequently, the sizing of components such as the electrolyzer, compressor, storage, and dispenser is dictated by a hydrogen production flow rate of 4 kg per hour. This study provides a comprehensive framework for implementing and operationalizing OHRS to support the deployment of FCBs in heavy-duty transportation.
Design of Force Sensitive Resistor (FSR) embedded insole for phase detection during human gait and its classification
Authors: Pant U , Baral S , Gupta A , Shrestha P L 
Published: September 2024

Abstract
Gait analysis is the study of human motion during walking or running. It is often used to evaluate and treat individuals with movement disorders or to assist in the design of prosthetics and other assistive devices. The phase detection aspect of gait allows for the quantification of gait characteristics, assessment of effectiveness of interventions and monitoring the changes in gait over time. The objective of the paper is the design and development of a Force Sensing Resistor (FSR) embedded insole that can be placed in shoes for detection of phases during the human gait and its classification. The classification using FSR is achieved by placing sensors at strategic locations on the foot, to detect the forces applied during walking. The data collected by these sensors are used to identify specific phases of the gait cycle—particularly heel strike, midstance, toe-off and swing, by analysing the patterns of data during movement. The layout and number of FSRs is determined through literature review and is followed by the insole fabrication. The wireless transmission of gait data through the FSRs is actuated for ten healthy adults. Machine Learning (ML) program is consequently developed based on all available classification algorithms of supervised learning namely—Logistic Regression, Naïve Bayes, Decision Tree, Random Forest and Support Vector Machine (SVM). The algorithm is trained and tested on separate FSR data sets from which the predictive decision in each gait cycle is attained. In the phase classification aspect, SVM, Naïve Bayes, and Random Forest achieved the highest accuracy of 91.54%, followed by Decision Tree at 90.77% and Logistic Regression at 89.23%. In conclusion, the optimal number of FSRs and their location in smart insole for gait phase detection is resolved. Gait phase classification is also attained. FSR embedded insole thus, provides a promising solution in accurately identifying and categorizing gait phases.
Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia
Authors: Le Priol Clément , Monteiro Joy Merwin , Bouchet Freddy 
Published: September 2024

Abstract
Computing the return times of extreme events and assessing the impact of climate change on such return times is fundamental to extreme event attribution studies. However, the rarity of such events in the observational record makes this task a challenging one, even more so for ‘record-shattering’ events that have not been previously observed at all. While climate models could be used to simulate such extremely rare events, such an approach entails a huge computational cost: gathering robust statistics for events with return time of centuries would require a few thousand years of simulation. In this study, we use an innovative tool, rare event algorithm, that allows us to sample numerous extremely rare events at a much lower cost than direct simulations. We employ the algorithm to sample extreme heatwave seasons, corresponding to large anomalies of the seasonal average temperature, in a heatwave hotspot of South Asia using the global climate model Plasim. We show that the algorithm estimates the return levels of extremely rare events with much greater precision than traditional statistical fits. It also enables the computation of various composite statistics, whose accuracy is demonstrated through comparison with a very long control run. In particular, our results reveal that extreme heatwave seasons are associated with an anticyclonic anomaly embedded within a large-scale hemispheric quasi-stationary wave-pattern. Additionally, the algorithm accurately represents the intensity-duration-frequency statistics of sub-seasonal heatwaves, offering insights into both seasonal and sub-seasonal aspects of extreme heatwave seasons. This innovative approach could be used in extreme event attribution studies to better constrain the changes in an event’s probability and intensity with global warming, particularly for events with return times spanning centuries or millennia.
A rapid response process for evaluating causes of extreme temperature events in the United States: The 2023 Texas/Louisiana heat wave as a prototype
Authors: Schreck III Carl J , Easterling David R , Barsugli Joseph J , Coates David A , Hoell Andrew , Johnson Nathaniel C , Kunkel Kenneth E , Labe Zachary M , Uehling John , Vose Russell S , Zhang Xiangdong 
Published: September 2024

Abstract
As climate attribution studies have become more common, routine processes are now being established for attribution analysis following extreme events. This study describes the prototype process being developed through a collaboration across National Oceanic and Atmospheric Administration (NOAA), including monitoring tools as well as observational and model-based analysis of causal factors. The prolonged period of extreme heat in summer 2023 over Texas, Louisiana and adjacent areas provided a proving ground for this emerging capability. This event posed unique challenges to the initial process. The extreme heat lasted for most of the summer while most heat wave metrics have been designed for 3–7 d events. The eastern portion of the affected area also occurred within the so-called summer-time daytime warming hole where the warming trend in maximum temperatures has been mitigated wholly or in part by increased precipitation. The extreme temperature coincided with a strong—but not record—precipitation deficit over the region. Both observations and climate model simulations illustrate that the temperatures for a given precipitation deficit have warmed in recent decades. In other words, meteorological droughts today are hotter than their historical analogs providing a stronger attribution to anthropogenic forcing than for temperature alone. These findings were summarized in a prototype plain language report that was distributed to key stakeholders. Based on their feedback, the monitoring and assessment tools will continue to be refined, and the project is exploring other climate model large ensembles to increase the robustness of attribution for future events.
Setting the Stage
Authors: Talisse Robert B 
Published: September 2024

Abstract
This chapter clarifies the book’s central thesis that responsible citizenship calls for occasions of solitary reflection, moments when citizens can be alone with their thoughts. In addition, it explains that the book is a work of prescriptive and normative democratic theory-it seeks to provide an account of what we must do to improve democracy. It then sketches the core argument that the polarization dynamic undermines our democratic capacities from within. The idea of the “curative fallacy” is introduced. This is the error of mistaking a preventative measure for a curative one. Accordingly, the task of repairing democracy is not simply that of figuring out how current dysfunctions could have been averted.
Reading Tolkien
Authors: Townend Matthew 
Published: September 2024

Abstract
This brief chapter introduces J. R. R. Tolkien’s two major works, The Hobbit (1937) and The Lord of the Rings (1954-5), and explores how an encounter with these works has been life-changing for millions of readers. It also discusses how Tolkien’s works have changed the common culture, in the development of the fantasy genre in his wake (in a variety of forms and flavours) and the prominence of many of his names and motifs in modern discourse.
Sources
Authors: Townend Matthew 
Published: September 2024

Abstract
This chapter considers some of the main sources and inspirations for J. R. R. Tolkien’s writings. It discusses the emergence of modern ‘medievalism’ as a cultural phenomenon, following the rediscovery in the nineteenth century of medieval language and literature as a creative resource. For Tolkien, Old English, Middle English, and Old Norse (his areas of professional expertise) were especially productive as a source of inspiration, and the chapter supplies examples of the many ways in which Tolkien adapted and re-deployed elements from these medieval languages and literatures. The chapter also explores more modern and contemporary forms of writing that left their mark on Tolkien’s works, such as folklore and fairy tales, early fantasy literature, children’s literature of the so-called Golden Age, and modern adventure stories.
Seeding the rule of law
Authors: Huq Aziz Z. 
Published: September 2024

Abstract
The idea of the rule of law distills ideas that developed earlier under different rubrics and varying verbal formulations in both ancient and early modern theorizing about the state. This chapter focuses on the three most canonical figures—the ancient Greek thinker Aristotle, the French aristocrat and proto-sociologist Charles-Louis de Secondat (known too as the Baron de La Brède et de Montesquieu, or just Montesquieu), and the English Whig thinker, political activist, and imperial administrator John Locke. These thinkers did not use the phrase “rule of law,” but nevertheless are commonly perceived as its forebearers. It then takes on the peculiar, persistent myth that the Magna Carta lies at the root of the rule of law—and rejects that idea as anything more than a fable.
Important antimicrobial dosing considerations for transitions of care: Focus on thrice-weekly dosing in hemodialysis
Authors: Tsai Y Vivian , Soto Caitlin , Crawford Garrett , Dzintars Kathryn 
Published: September 2024

Abstract

Purpose
The objective of this clinical review is to evaluate current literature and propose optimal dosing strategies for thrice-weekly postdialytic administration of select antimicrobial agents in individuals receiving chronic intermittent hemodialysis (iHD).

Summary
The optimization of outpatient parenteral antimicrobial therapy (OPAT) for patients receiving chronic iHD presents a prime opportunity for stewardship intervention. By utilizing the existing vascular hemodialysis access instead of inserting an additional peripheral catheter for antimicrobial administration, the risk for potential clinical complications (e.g. vein thrombosis, catheter-associated infections) can be minimized. In addition to vancomycin and aminoglycosides, literature evidence also supports the use of thrice-weekly cefazolin, ceftazidime, cefepime, ertapenem, and daptomycin given after dialysis sessions.

Conclusion
Optimal dosing strategies of antimicrobials during transitions-of-care are imperative, especially in those receiving OPAT with iHD. While different dosing strategies may exist for each antimicrobial agent, other factors such as the modality of hemodialysis and site/severity of infection should be considered when choosing the optimal dosing regimen.
Management of obesity
Authors: Cross Lourdes 
Published: September 2024

Abstract

Purpose
This review summarizes the comprehensive management of obesity with a focus on the pharmacology, efficacy, and safety of anti-obesity medications.

Summary
Obesity is a highly prevalent chronic disease with significant health risks, requiring a multifaceted approach to treatment. While most approved weight loss medications have modest effects, newer medications such as semaglutide and tirzepatide have shown greater than 15% reduction in baseline weight. Optimal selection of therapy requires taking into consideration patient factors, such as comorbidities and goals, and medication-related factors, including weight loss efficacy, contraindications, and improvements in cardiovascular risk. As the availability of anti-obesity medications increases, multidisciplinary care teams will play an important role in selecting optimal strategies for long-term health benefits in individuals with obesity.

Conclusion
The expanding array of anti-obesity medications provides valuable treatment options alongside lifestyle interventions and surgical approaches for managing obesity and reducing weight-related health risks. As this therapeutic area continues to grow, selecting optimal agents and educating patients on administration, monitoring, and potential adverse effects will be critical for improving overall outcomes.
Comparison of a radiofrequency electric and magnetic field source-based job-exposure matrix with personal radiofrequency exposure measurements
Authors: Turuban Maxime , Kromhout Hans , Vila Javier , de Vocht Frank , Vallbona-Vistós Miquel , Baldi Isabelle , Cardis Elisabeth , Turner Michelle C 
Published: September 2024

Abstract

Objectives
Assessing occupational exposure to radiofrequency electromagnetic fields (RF-EMF) presents significant challenges due to the considerable variability in exposure levels within and between occupations. This spatial and temporal variability complicates the reliable evaluation of potential health risks associated with RF-EMF exposure in the workplace. Accurate assessment methods are crucial to understand the extent of exposure and to evaluate potential health risks, especially given the potential for higher exposures in occupational settings compared to the general population. This study compares the historical RF-EMF exposure estimates in the INTEROCC RF-EMF job-exposure matrix (RF-JEM) with recent personal measurement data collected in 2 countries as part of the OccRF-Health study, to assess the broader applicability of the RF-JEM.

Methods
Weighted kappa (kw) coefficients and Spearman rank correlation tests were performed to assess the alignment between RF-JEM estimates and measurements for 8 h time-weighted average exposure intensity and prevalence estimates across various occupations. The comparisons were mainly based on 22 jobs having ≥5 measured workers in the OccRF-Health study.

Results
Poor agreement was found for both exposure prevalence and intensity between both methods (kw &lt; 0.1). RF-JEM values likely overestimated exposure levels for both electric (E) and magnetic (H) fields (mean percentage difference &gt;194%) compared to current personal measurements.

Conclusions
Findings suggest that the INTEROCC-JEM likely overestimates current exposure intensity levels in the measured jobs. Adopting a semiquantitative JEM could also mitigate misclassification errors due to exposure variability, improving accuracy in exposure assessment. These findings indicate the need for more targeted personal measurements, including among highly exposed workers, and for potentially considering new exposure metrics to more accurately assess occupational RF-EMF exposures in occupational epidemiological research.
Knowledge Graphs for drug repurposing: a review of databases and methods
Authors: Perdomo-Quinteiro Pablo , Belmonte-Hernández Alberto 
Published: September 2024

AbstractDrug repurposing has emerged as a effective and efficient strategy to identify new treatments for a variety of diseases. One of the most effective approaches for discovering potential new drug candidates involves the utilization of Knowledge Graphs (KGs). This review comprehensively explores some of the most prominent KGs, detailing their structure, data sources, and how they facilitate the repurposing of drugs. In addition to KGs, this paper delves into various artificial intelligence techniques that enhance the process of drug repurposing. These methods not only accelerate the identification of viable drug candidates but also improve the precision of predictions by leveraging complex datasets and advanced algorithms. Furthermore, the importance of explainability in drug repurposing is emphasized. Explainability methods are crucial as they provide insights into the reasoning behind AI-generated predictions, thereby increasing the trustworthiness and transparency of the repurposing process. We will discuss several techniques that can be employed to validate these predictions, ensuring that they are both reliable and understandable.
Algorithm-agnostic significance testing in supervised learning with multimodal data
Authors: Kook Lucas , Lundborg Anton Rask 
Published: September 2024

Abstract

Motivation
Valid statistical inference is crucial for decision-making but difficult to obtain in supervised learning with multimodal data, e.g. combinations of clinical features, genomic data, and medical images. Multimodal data often warrants the use of black-box algorithms, for instance, random forests or neural networks, which impede the use of traditional variable significance tests.

Results
We address this problem by proposing the use of COvariance MEasure Tests (COMETs), which are calibrated and powerful tests that can be combined with any sufficiently predictive supervised learning algorithm. We apply COMETs to several high-dimensional, multimodal data sets to illustrate (i) variable significance testing for finding relevant mutations modulating drug-activity, (ii) modality selection for predicting survival in liver cancer patients with multiomics data, and (iii) modality selection with clinical features and medical imaging data. In all applications, COMETs yield results consistent with domain knowledge without requiring data-driven pre-processing, which may invalidate type I error control. These novel applications with high-dimensional multimodal data corroborate prior results on the power and robustness of COMETs for significance testing.

Availability and implementation
COMETs are implemented in the cometsR package available on CRAN and pycometsPython library available on GitHub. Source code for reproducing all results is available at https://github.com/LucasKook/comets. All data sets used in this work are openly available.
Cancer Characteristics, Prognoses, and Mortality of Colorectal Cancer in Patients With Crohn’s Disease—A Danish Nationwide Cohort Study, 2009-2019
Authors: Johansen Martha Pollen , Wewer Mads Damsgaard , Krarup Peter-Martin , Burisch Johan , Nordholm-Carstensen Andreas 
Published: September 2024

Abstract

Background and Aims
The aim of this study was to investigate the impact of Crohn’s disease (CD) on patient and cancer characteristics and mortality in patients with colorectal cancer (CRC).

Methods
This was a nationwide cohort study of patients diagnosed with CRC in Denmark from 1 January, 2009 to 31 December, 2019. Cancer characteristics were retrieved from the Danish Colorectal Cancer Group registry and merged with a nationwide cohort for inflammatory bowel disease. The main outcome was all-cause mortality in CRC patients with and without CD, comparing CD patients with CRC with those in the general CRC population (non-CD CRC), evaluated by adjusted Cox regression analysis and propensity score matching.

Results
Of 38 077 CRC patients, 245 (0.6%) had CD. The median age at cancer diagnosis was 69 years (interquartile range [IQR]: 60-76) for CD-CRC and 71 years (IQR: 64-78) for non-CD CRC (p &lt; 0.001). Most cancers were located in the right colon in the CD-CRC group. CD was not associated with increased all-cause mortality in the cohort overall. CD patients with colon and rectal cancers and UICC Stage III tumors had a higher mortality rate in both multivariate {hazard ratio (HR) 1.60 (95% confidence interval [95% CI], 1.13-2.27), p = 0.008} and univariate analyses (HR 1.57 [95% CI, 1.11-2.22], p = 0.011). In the propensity score-matched analysis, CD was not associated with increased mortality for colon cancer (HR 1.06 [0.82-1.36], p = 0.7) or rectal cancer (HR 1.25 [0.79-1.98], p = 0.3).

Conclusions
This nationwide study identified distinct features of colon and rectal cancers in patients with CD that have implications for the timing of diagnoses, disease course, and mortality specifically in UICC Stage III disease.
Impact of whole-body and skeletal muscle composition on peak oxygen uptake in heart failure: a systematic review and meta-analysis
Authors: Schmid Veronika , Foulkes Stephen J , Walesiak Devyn , Wang Jing , Tomczak Corey R , Tucker Wesley J , Angadi Siddhartha S , Halle Martin , Haykowsky Mark J 
Published: September 2024

Abstract

Aims
Heart failure (HF) has a major impact on exercise tolerance that may (in part) be due to abnormalities in body and skeletal muscle composition. This systematic review and meta-analysis aims to assess how differences in whole-body and skeletal muscle composition between patients with HF and non-HF controls (CON) contribute to reduced peak oxygen uptake (VO2peak).

Methods and results
The PubMed database was searched from 1975 to May 2024 for eligible studies. Cross-sectional studies with measures of VO2peak, body composition, or muscle biopsies in HF and CON were considered. Out of 709 articles, 27 studies were included in this analysis. Compared with CON, VO2peak [weighted mean difference (WMD): −9.96 mL/kg/min, 95% confidence interval (CI): −11.71 to −8.21), total body lean mass (WMD: −1.63 kg, 95% CI: −3.05 to −0.21), leg lean mass (WMD: −1.38 kg, 95% CI: −2.18 to −0.59), thigh skeletal muscle area (WMD: −10.88 cm2 , 95% CI: −21.40 to −0.37), Type I fibres (WMD: −7.76%, 95% CI: −14.81 to −0.71), and capillary-to-fibre ratio (WMD: −0.27, 95% CI: −0.50 to −0.03) were significantly lower in HF. Total body fat mass (WMD: 3.34 kg, 95% CI: 0.35–6.34), leg fat mass (WMD: 1.37 kg, 95% CI: 0.37–2.37), and Type IIx fibres (WMD: 7.72%, 95% CI: 1.52–13.91) were significantly higher in HF compared with CON. Absolute VO2peak was significantly associated with total body and leg lean mass, thigh skeletal muscle area, and capillary-to-fibre ratio.

Conclusion
Individuals with HF display abnormalities in body and skeletal muscle composition including reduced lean mass, oxidative Type I fibres, and capillary-to-fibre ratio that negatively impact VO2peak.