bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic pricing strategy for efficient electric vehicle charging and discharging in microgrids using multi-objective jaya algorithm
Authors: Sharma Swati , Ali Ikbal 
Published: July 2024

Abstract
The rising demand for electric vehicle (EV) charging is spurring their increased integration into microgrids. With significant advancements, EVs have become widely adopted and integrated into various settings for charging/discharging. EVs integrated with the microgrids possess the capability to serve as variable loads and the various energy suppliers present it as a dual opportunity. However, a primary challenge in EV deployment lies in efficiently managing charging stations (CSs) to minimize waiting times for users and reduce charging costs for EV owners. In addressing these challenges require consideration of dynamic pricing mechanisms and the diverse characteristics of EVs to achieve optimal scheduling. A novel approach that combines dynamic pricing strategies with optimized scheduling for effective EV charging operations using multi-objective Jaya algorithm. To evaluate its performance, we conducted a numerical experiment using real-time data and the Nissan Leaf model EV. The results demonstrate that our multi-objective Jaya-based approach outperforms existing methods by achieving a remarkable cost saving rate of 16.013% and an average profit of ₹ 243.6331 per kilowatt-hour with a network convergence time of 112 s. Also, our proposed algorithm provides a correlation between minimized EV charging costs and maximized EV aggregator profits. These findings validate the effectiveness and practical applicability of our proposed EV scheduling algorithm in real-world scenarios.
Comparison of Si and SiC MOSFETs responses to electrical stress and the observation of parameter recovery in SiC MOSFET by stress superposition
Authors: Wang Xinyu , Awadelkarim Osama O 
Published: July 2024

Abstract
In this study we examined the effects of room temperature DC and AC electrical stress on Si and SiC n-channel metal-oxide-semiconductor field effect transistors (MOSFETs). Measurement of threshold voltage, transconductance, subthreshold swing, charge pumping, and gate oxide breakdown are used to compare the impact of stress on Si MOSFETs and SiC MOSFETS, as well as to understand the processes of carrier injection and trapping at oxide and interface defects. DC stress is observed to promote negative charge buildup in the gate oxide and interface in Si MOSFETs. However, in SiC MOSFETs the net charge buildup sign alternates between negative and positive as the DC stress polarity is changed from positive to negative, respectively. For the same stress level, relative degradation in parameters of SiC MOSFETs are significantly smaller than those in Si MOSFETs, where in the latter interface state density, conductance, and subthreshold swing have degraded by up to 400%.The change of charge buildup sign explains our observation that degradation in SiC MOSFETs subjected to AC bipolar stress is insignificantly small, whereas AC stressing of Si MOSFETs is observed to be much more severe. Also, the superposition of alternating DC stress polarity eliminates the stress induced degradation in SiC MOSFETs thus enabling a straightforward process for parameter reconfiguration and recovery.
Towards robust data-driven automated recovery of symbolic conservation laws from limited data
Authors: Oellerich Tracey , Emelianenko Maria 
Published: July 2024

Abstract
Conservation laws are an inherent feature in many systems modeling real world phenomena, in particular, those modeling biological and chemical systems. If the form of the underlying dynamical system is known, linear algebra and algebraic geometry methods can be used to identify the conservation laws. Our work focuses on using data-driven methods to identify the conservation law(s) in the absence of the knowledge of system dynamics. We develop a robust data-driven computational framework that automates the process of identifying the number and type of the conservation law(s) while keeping the amount of required data to a minimum. We demonstrate that due to relative stability of singular vectors to noise we are able to reconstruct correct conservation laws without the need for excessive parameter tuning. While we focus primarily on biological examples, the framework proposed herein is suitable for a variety of data science applications and can be coupled with other machine learning approaches.
Enhancing the rationale of convolutional neural networks for glitch classification in gravitational wave detectors: a visual explanation
Authors: Koyama Naoki , Sakai Yusuke , Sasaoka Seiya , Dominguez Diego , Somiya Kentaro , Omae Yuto , Terada Yoshikazu , Meyer-Conde Marco , Takahashi Hirotaka 
Published: July 2024

Abstract
In the pursuit of detecting gravitational waves, ground-based interferometers (e.g. LIGO, Virgo, and KAGRA) face a significant challenge: achieving the extremely high sensitivity required to detect fluctuations at distances significantly smaller than the diameter of an atomic nucleus. Cutting-edge materials and innovative engineering techniques have been employed to enhance the stability and precision of the interferometer apparatus over the years. These efforts are crucial for reducing the noise that masks the subtle gravitational wave signals. Various sources of interference, such as seismic activity, thermal fluctuations, and other environmental factors, contribute to the total noise spectra characteristic of the detector. Therefore, addressing these sources is essential to enhance the interferometer apparatus’s stability and precision. Recent research has emphasised the importance of classifying non-stationary and non-Gaussian glitches, employing sophisticated algorithms and machine learning methods to distinguish genuine gravitational wave signals from instrumental artefacts. The time-frequency-amplitude representation of these transient disturbances exhibits a wide range of new shapes, variability, and features, reflecting the evolution of interferometer technology. In this study, we developed a convolutional neural network model to classify glitches using spectrogram images from the Gravity Spy O1 dataset. We employed score-class activation mapping and the uniform manifold approximation and projection algorithm to visualise and understand the classification decisions made by our model. We assessed the model’s validity and investigated the causes of misclassification from these results.
Capturing the ghost in the machine: a process for development and validation of measures of phenomenal consciousness in delirium
Authors: Eeles Eamonn , Tran David Duc , Ward Sarah , Teodorczuk Andrew , Ray Julian , Miller Tim , Dissanayaka Nadeeka N 
Published: July 2024

Abstract

Background
Delirium has conventionally been considered a disorder of consciousness. Alertness and arousal are used as surrogates in clinical practice but are insufficient for the purposes of a more dimensional assessment of consciousness. We present a process of development and validation of candidate measures of phenomenal consciousness that could be applied to the diagnosis of delirium.

Methods
First, a narrative review of available instruments in the fields of phenomenal consciousness, including prereflective consciousness, the phenomenal-sensed experience and reflective thought, was undertaken. Eligibility of tools in the context of applicability to delirium was based upon objectivity in test interpretation and the requirement for tester administration. Second, where there was a gap in suitable cognitive tools, new items were derived using the silent generation technique. A process of face and construct validity using a diverse panel of experts was performed, and readability was evaluated.

Results
814 articles were screened from the literature review. Fourteen candidate tools were reported from the three domains of phenomenal consciousness. One of these met the eligibility criteria for a delirium assessment. Fifty-seven new tests of phenomenal consciousness were identified. After a process of item reduction, a total of 26 individual tests were identified. After content validity, 22 of the 26 items were retained. The scale average content validity index was 0.89. The agreement between raters was between 80% and 97%. 100% of responses for face validity were rated as positive. Flesch Reading Ease Score was 91.6 (very easy to read).

Conclusions
Candidate measures of phenomenal consciousness are described, and early validity studies are promising.
Spatiotemporal patterns of excess mortality from non-COVID causes of death in the United States, March to December 2020
Authors: Zalla Lauren C , Lesko Catherine R 
Published: July 2024

Abstract
To estimate the burden of excess mortality from 17 underlying causes of death between March and December 2020 in the United States and to compare trends in excess deaths from non-COVID causes vs from COVID-19. Using time-series models, we estimated monthly counts of all-cause and cause-specific excess deaths. We stratified by geographic region and compared temporal trends in excess deaths from non-COVID causes to trends in deaths attributed to COVID-19. Of approximately 500 000 excess deaths, 70% were attributed to COVID-19. We observed increases in several underlying causes of death, ranging from a 3% increase in kidney disease deaths to a 24% increase in homicides, as well as decreases in deaths from cancer (–0.3%), influenza and pneumonia (–2%), chronic lower respiratory disease (–3%), and suicide (–7%). Trends in excess deaths from cardiovascular disease, diabetes, and Alzheimer disease closely mirrored trends in deaths from COVID-19. Trends in excess liver disease, homicide, suicide, and motor vehicle accident deaths were negatively correlated with trends in deaths from COVID-19. There was wide regional variation in excess death rates for some causes of death, including a disproportionate increase in homicide and motor vehicle accident deaths in the Great Lakes and a sustained reduction in cancer deaths in the Mideast and New England. Increases in cardiovascular disease, diabetes, and Alzheimer disease deaths from March to December 2020 likely reflect health care system disruptions or acute complications of COVID-19. Excess deaths from homicide and liver disease are more likely to reflect social and economic effects of the emerging pandemic or other separate causes.
Preconception and first trimester exposure to pesticides and associations with stillbirth
Authors: Furlong Melissa A , Paul Kimberly C , Parra Kimberly L , Fournier Alfred J , Ellsworth Peter C , Cockburn Myles G , Arellano Avelino F , Bedrick Edward J , Beamer Paloma I , Ritz Beate 
Published: July 2024

Abstract
Associations of pesticide exposures during preconception with stillbirth have not been well explored. We linked Arizona pesticide use records with birth certificates from 2006 to 2020 and estimated associations of living within 500 m of any pyrethroid, organophosphate (OP), or carbamate pesticide applications during a 90-day preconception window or the first trimester, with stillbirth. We considered a binary measure of exposure (any exposure), as well as log-pounds and log-acres applied within 500 m, in a negative control exposure framework with log-binomial regression. We included 1 237 750 births, 2290 stillbirths, and 27 pesticides. During preconception, any exposure to pesticides was associated with stillbirth, including cyfluthrin (risk ratio [RR] = 1.97; 95% CI, 1.17-3.32); zeta-cypermethrin (RR = 1.81; 95% CI, 1.20-2.74); OPs as a class (RR = 1.60; 95% CI, 1.16-2.19); malathion (RR = 2.02; 95% CI, 1.26-3.24); carbaryl (RR = 6.39; 95% CI, 2.07-19.74); and propamocarb hydrochloride (RR = 7.72; 95% CI, 1.10-54.20). During the first trimester, fenpropathrin (RR = 4.36; 95% CI, 1.09-17.50); permethrin (RR = 1.57; 95% CI, 1.02-2.42); OPs as a class (RR = 1.50; 95% CI, 1.11-2.01); acephate (RR = 2.31; 95% CI, 1.22-4.40); and formetanate hydrochloride (RR = 7.22; 95% CI, 1.03-50.58) were associated with stillbirth. Interpretations were consistent when using continuous measures of pounds or acres of exposure. Pesticide exposures during preconception and first trimester may be associated with stillbirth.
This article is part of a Special Collection on Environmental Epidemiology.
Feasibility of respirable crystalline silica exposure reduction in small-scale tanzanite mining in Tanzania
Authors: Nota Manti Michael , Mbuligwe Stephen E , Kassenga Gabriel R , Gottesfeld Perry 
Published: July 2024

Abstract

Introduction
Respirable crystalline silica (RCS) exposures in tanzanite gem mining have been linked to tuberculosis and silicosis among miners. We conducted a plot study to assess RCS exposures and to introduce safer mining practices in one small-scale underground tanzanite mine.

Materials and methods
Personal and area air samples for RCS were collected during tanzanite mining operations before and after improved work practices employed to reduce exposures and analyzed using X-ray diffraction. Area samples were collected at the rest area, located approximately 300 m underground and 100 m from other work activities. Improved practices included the use of wet drilling methods and drilling with new bits.

Results
A total of 33 personal and 4 area air samples were collected. Pre-intervention, mean exposures for all operations, drilling operations, non-drilling activities, and area samples were 122 mg/m3, 247 mg/m3, 34.3 mg/m3, and 1.95 mg/m3, respectively which exceeded the U.S. OSHA Permissible Exposure Limit (PEL) by 2,440 times for all operations, by 4,946 times for drilling operations, by 686 times for non-drilling activities and 39 times for area samples collected at an underground rest area. The post-intervention results showed a 99% reduction of RCS exposures for wet drilling operations, 98.5% reduction for non-drilling activities, and 36% reduction for area samples. Despite improvements, post-intervention RCS exposures during drilling had a mean of 2.08 mg/m3 or more than 41 times the OSHA PEL.

Conclusions
We successfully piloted a program to work with small-scale tanzanite miners to reduce RCS exposures and raise awareness about the occupational health risks of RCS, though additional measures are recommended to further reduce RCS exposures. Similar programs should be taken to scale throughout underground mining sites in Tanzania and other countries.
Customized antisense oligonucleotide-based therapy for neurofilament-associated Charcot–Marie–Tooth disease
Authors: Medina Jessica , Rebelo Adriana , Danzi Matt C , Jacobs Elizabeth H , Xu Isaac R L , Ahrens Kathleen P , Chen Sitong , Raposo Jacquelyn , Yanick Christopher , Zuchner Stephan , Saporta Mario A 
Published: July 2024

Abstract
DNA-based therapeutics have emerged as a revolutionary approach for addressing the treatment gap in rare inherited conditions by targeting the fundamental genetic causes of disease. Charcot–Marie–Tooth (CMT) disease, a group of inherited neuropathies, represents one of the most prevalent Mendelian disease groups in neurology and is characterized by diverse genetic aetiology. Axonal forms of CMT, known as CMT2, are caused by dominant mutations in &gt;30 different genes that lead to degeneration of lower motor neuron axons. Recent advances in antisense oligonucleotide therapeutics have shown promise in targeting neurodegenerative disorders.
Here, we elucidate pathomechanistic changes contributing to variant specific molecular phenotypes in CMT2E, caused by a single nucleotide substitution (p.N98S) in the neurofilament light chain gene (NEFL). We used a patient-derived induced pluripotent stem cell-induced motor neuron model that recapitulates several cellular and biomarker phenotypes associated with CMT2E. Using an antisense oligonucleotide treatment strategy targeting a heterozygous gain-of-function variant, we aimed to resolve molecular phenotypic changes observed in the CMT2E p.N98S subtype. To determine the therapeutic potential of antisense oligonucleotide, we applied our treatment strategy in induced pluripotent stem cell-derived motor neurons and used both established and new biomarkers of peripheral nervous system axonal degeneration.
Our findings demonstrated a significant decrease in clinically relevant biomarkers of axonal degeneration, presenting the first clinically viable genetic therapeutic for CMT2E. Similar strategies could be used to develop precision medicine approaches for otherwise untreatable gain-of-function inherited disorders.
Task and stimulus coding in the multiple-demand network
Authors: Shashidhara Sneha , Assem Moataz , Glasser Matthew F , Duncan John 
Published: July 2024

Abstract
In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala et al, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns. In each parcel, we compared multivertex patterns for every combination of three tasks (working memory, task-switching, and stop-signal) and two stimulus classes (faces and buildings). Though both task and stimulus category were discriminated in every cortical parcel, the strength of discrimination varied strongly across parcels. The different cognitive operations of the three tasks were strongly discriminated in MD regions. Stimulus categories, in contrast, were most strongly discriminated in a large region of primary and higher visual cortex, and intriguingly, in both parietal and frontal lobe regions adjacent to core MD regions. In the monkey, frontal neurons show a strong pattern of nonlinear mixed selectivity, with activity reflecting specific conjunctions of task events. In our data, however, there was limited evidence for mixed selectivity; throughout the brain, discriminations of task and stimulus combined largely linearly, with a small nonlinear component. In MD regions, human fMRI data recapitulate some but not all aspects of electrophysiological data from nonhuman primates.
The integration of migrants in the German labour market: evidence over 50 years
Authors: Berbée Paul , Stuhler Jan 
Published: July 2024

SUMMARY
Germany has become the second-most important destination for migrants worldwide. Using all waves from the microcensus, we study their labour market integration over the last 50 years and highlight differences to the US case. Although the employment gaps between immigrant and native men decline after arrival, they remain large for most cohorts; the average gap after one decade is 10 percentage points. Conversely, income gaps tend to widen post-arrival. Compositional differences explain how those gaps vary across groups, and why they worsened over time; after accounting for composition, integration outcomes show no systematic trend. Still, economic conditions do matter, and employment collapsed in some cohorts after structural shocks hit the German labour market in the early 1990s. Lastly, we examine the integration of recent arrivals during the European refugee ‘crisis’ and the Russo-Ukrainian war.
Pan-Genome Provides Insights into Vibrio Evolution and Adaptation to Deep-Sea Hydrothermal Vents
Authors: Bosi Emanuele , Taviani Elisa , Avesani Alessia , Doni Lapo , Auguste Manon , Oliveri Caterina , Leonessi Martina , Martinez-Urtaza Jaime , Vetriani Costantino , Vezzulli Luigi 
Published: July 2024

Abstract
This study delves into the genomic features of 10 Vibrio strains collected from deep-sea hydrothermal vents in the Pacific Ocean, providing insights into their evolutionary history and ecological adaptations. Through sequencing and pan-genome analysis involving 141 Vibrio species, we found that deep-sea strains exhibit larger genomes with unique gene distributions, suggesting adaptation to the vent environment. The phylogenomic reconstruction of the investigated isolates revealed the presence of 2 main clades: The first is monophyletic, consisting exclusively of Vibrio alginolyticus, while the second forms a monophyletic clade comprising both Vibrio antiquarius and Vibrio diabolicus species, which were previously isolated from deep-sea vents. All strains carry virulence and antibiotic resistance genes related to those found in human pathogenic Vibrio species which may play a wider ecological role other than host infection in these environments. In addition, functional genomic analysis identified genes potentially related to deep-sea survival and stress response, alongside candidate genes encoding for novel antimicrobial agents. Ultimately, the pan-genome we generated represents a valuable resource for future studies investigating the taxonomy, evolution, and ecology of Vibrio species.
Regional variation in length of stay for stroke inpatient rehabilitation in traditional Medicare and Medicare Advantage
Authors: Luo Dian , Ouayogodé Mariétou H , Mullahy John , Cao Ying (Jessica) 
Published: July 2024

Abstract
Regional variation in health care use threatens efficient and equitable resource allocation. Within the Medicare program, variation in care delivery may differ between centrally administered traditional Medicare (TM) and privately managed Medicare Advantage (MA) plans, which rely on different strategies to control care utilization. As MA enrollment grows, it is particularly important for program design and long-term health care equity to understand regional variation between TM and MA plans. This study examined regional variation in length of stay (LOS) for stroke inpatient rehabilitation between TM and MA plans in 2019 and how that changed in 2020, the first year of the COVID-19 pandemic. Results showed that MA plans had larger across-region variations than TM (SD = 0.26 vs 0.24 days; 11% relative difference). In 2020, across-region variation for MA further increased, but the trend for TM stayed relatively stable. Market competition among all inpatient rehabilitation facilities (IRFs) within a region was associated with a moderate increase in within-region variation of LOS (elasticity = 0.46). Policies reducing administrative variation across MA plans or increasing regional market competition among IRFs can mitigate regional variation in health care use.