bluuebunny/crossref_metadata_2025_split huggingface dataset:
Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking
Authors: Gwynne Steve M. V. , Ronchi Enrico , Wahlqvist Jonathan , Cuesta Arturo , Gonzalez Villa Javier , Kuligowski Erica D. , Kimball Amanda , Rein Guillermo , Kinateder Max , Benichou Noureddine , Xie Hui 
Published: February 2023

AbstractWildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland–urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts.
Type I Interferonopathy due to a Homozygous Loss-of-Inhibitory Function Mutation in STAT2
Authors: Zhu Gaofeng , Badonyi Mihaly , Franklin Lina , Seabra Luis , Rice Gillian I. , Anne-Boland-Auge  , Deleuze Jean-François , El-Chehadeh Salima , Anheim Mathieu , de Saint-Martin Anne , Pellegrini Sandra , Marsh Joseph A. , Crow Yanick J. , El-Daher Marie-Therese 
Published: February 2023

Abstract

Purpose
STAT2 is both an effector and negative regulator of type I interferon (IFN-I) signalling. We describe the characterization of a novel homozygous missense STAT2 substitution in a patient with a type I interferonopathy.

Methods
Whole-genome sequencing (WGS) was used to identify the genetic basis of disease in a patient with features of enhanced IFN-I signalling. After stable lentiviral reconstitution of STAT2-null human fibrosarcoma U6A cells with STAT2 wild type or p.(A219V), we performed quantitative polymerase chain reaction, western blotting, immunofluorescence, and co-immunoprecipitation to functionally characterize the p.(A219V) variant.

Results
WGS identified a rare homozygous single nucleotide transition in STAT2 (c.656C > T), resulting in a p.(A219V) substitution, in a patient displaying developmental delay, intracranial calcification, and up-regulation of interferon-stimulated gene (ISG) expression in blood. In vitro studies revealed that the STAT2 p.(A219V) variant retained the ability to transduce an IFN-I stimulus. Notably, STAT2 p.(A219V) failed to support receptor desensitization, resulting in sustained STAT2 phosphorylation and ISG up-regulation. Mechanistically, STAT2 p.(A219V) showed defective binding to ubiquitin specific protease 18 (USP18), providing a possible explanation for the chronic IFN-I pathway activation seen in the patient.

Conclusion
Our data indicate an impaired negative regulatory role of STAT2 p.(A219V) in IFN-I signalling and that mutations in STAT2 resulting in a type I interferonopathy state are not limited to the previously reported R148 residue. Indeed, structural modelling highlights at least 3 further residues critical to mediating a STAT2-USP18 interaction, in which mutations might be expected to result in defective negative feedback regulation of IFN-I signalling.
The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis
Authors: Heinzel Alexander , Mottaghy Felix M. , Filss Christian , Stoffels Gabriele , Lohmann Philipp , Friedrich Michel , Shah Nadim J. , Caspers Svenja , Lucas Carolin Weiss , Ruge Maximilian I. , Galldiks Norbert , Fink Gereon R. , Langen Karl-Josef , Kocher Martin 
Published: February 2023

Abstract
Purpose
In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL.

Methods
In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores.

Results
Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits.

Conclusion
In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.
Pedagogical challenges in integrating refugee students in the Global North: A literature review
Authors: Radhouane Myriam 
Published: February 2023

AbstractFor several years now, military conflict, climate change, lack of food, and other forces have compelled many people around the globe to leave their countries and live in exile. As shown by exponentially increasing statistics, children are leaving their homes, sometimes their families, and their schools. Once they arrive in a country of resettlement, they face the challenge of new schooling. To understand how best to support these exile communities and those who work with them—students, their parents, teachers, schools—I searched the international literature for the main challenges of schooling refugee students in resettlement countries in the Global North. This literature review identifies the variety of their profiles, the challenges related to pre- and post-migration experiences, as well as all the intertwined issues taking place within the school: language learning, relationships with the teacher and with other students, teacher training, etc. These challenges are numerous and their intertwining only makes them more complex. Understanding them therefore seems to be the basis of any action in support of refugee education.
Decolonizing AI Ethics: Relational Autonomy as a Means to Counter AI Harms
Authors: Mhlambi Sábëlo , Tiribelli Simona 
Published: February 2023

AbstractMany popular artificial intelligence (AI) ethics frameworks center the principle of autonomy as necessary in order to mitigate the harms that might result from the use of AI within society. These harms often disproportionately affect the most marginalized within society. In this paper, we argue that the principle of autonomy, as currently formalized in AI ethics, is itself flawed, as it expresses only a mainstream mainly liberal notion of autonomy as rational self-determination, derived from Western traditional philosophy. In particular, we claim that the adherence to such principle, as currently formalized, does not only fail to address many ways in which people’s autonomy can be violated, but also to grasp a broader range of AI-empowered harms profoundly tied to the legacy of colonization, and which particularly affect the already marginalized and most vulnerable on a global scale. To counter such a phenomenon, we advocate for the need of a relational turn in AI ethics, starting from a relational rethinking of the AI ethics principle of autonomy that we propose by drawing on theories on relational autonomy developed both in moral philosophy and Ubuntu ethics.
Fluxes of settling sediment particles and associated mercury in a coastal environment contaminated by past mining (Gulf of Trieste, northern Adriatic Sea)
Authors: Pavoni Elena , Petranich Elisa , Signore Sergio , Fontolan Giorgio , Bezzi Annelore , Covelli Stefano 
Published: February 2023

Abstract
Purpose
As the result of historical mining at Idrija (Slovenia), mercury (Hg) contamination in the Gulf of Trieste (northern Adriatic Sea) is still an issue of environmental concern. The element has been conveyed into the coastal area by the Isonzo/Soča River inputs of freshwater and suspended particles for centuries. This research aims to investigate the occurrence of Hg bound to the settling sediment particles (SSP) in the coastal water and to assess the sedimentary Hg fluxes.

Methods
Settling sediment particles were collected at four sites located in the innermost sector of the Gulf, a shallow and sheltered embayment where the accumulation of fine sediments is promoted. Six sampling campaigns were performed under different environmental conditions in terms of discharge from the Isonzo River and 12 sediment traps were installed in the upper and bottom water column for SSP collection. Settling sediment particles (SSP) were collected approximately every 2 weeks and analysed for grain size and total Hg.

Results
Settling sediment particles (SSP) consisted predominantly of silt (77.7 ± 10.1%), showing a concentration of Hg ranging overall between 0.61 and 6.87 µg g−1. Regarding the daily SSP fluxes, the minimum (7.05 ± 3.26 g m−2 day−1) and the maximum (92.4 ± 69.0 g m−2 day−1) values were observed under conditions of low and high river discharge, respectively. The daily Hg fluxes displayed a notable variability, up to an order of magnitude, both in the surface water layer (3.07–94.6 µg m−2 day−1) and at the bottom (11.3–245 µg m−2 day−1), reaching the maximum values following periods of high river flow.

Conclusions
The Isonzo River inputs of suspended particulate matter continue to convey Hg into the Gulf of Trieste, especially following river flood events, which represent one of the most relevant natural factors affecting the variations of the Hg flux in the investigated area.
An end-to-end deep learning approach for real-time single image dehazing
Authors: Jeong Chi Yoon , Moon KyeongDeok , Kim Mooseop 
Published: February 2023

AbstractImage dehazing methods can restore clean images from hazy images and are popularly used as a preprocessing step to improve performance in various image analysis tasks. In recent times, deep learning-based methods have been used to sharply increase the visual quality of restored images, but they require a long computation time. The processing time of image-dehazing methods is one of the important factors to be considered in order not to affect the latency of the main image analysis tasks such as detection and segmentation. We propose an end-to-end network model for real-time image dehazing. We devised a zoomed convolution group that processes computation-intensive operations with low resolution to decrease the processing time of the network model without performance degradation. Additionally, the zoomed convolution group adopts an efficient channel attention module to improve the performance of the network model. Thus, we designed a network model using a zoomed convolution group to progressively recover haze-free images using a coarse-to-fine strategy. By adjusting the sampling ratio and the number of convolution blocks that make up the convolution group, we distributed small and large computational complexities respectively in the early and later operational stages. The experimental results with the proposed method on a public dataset showed a real-time performance comparable to that of another state-of-the-art (SOTA) method. The proposed network’s peak-signal-to-noise ratio was 0.8 dB lower than that of the SOTA method, but the processing speed was 10.4 times faster.
Diagnosis and Management of Posterior Cortical Atrophy
Authors: Yong Keir X. X. , Graff-Radford Jonathan , Ahmed Samrah , Chapleau Marianne , Ossenkoppele Rik , Putcha Deepti , Rabinovici Gil D. , Suarez-Gonzalez Aida , Schott Jonathan M. , Crutch Sebastian , Harding Emma 
Published: February 2023

Abstract
Purpose of review
The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps.

Recent findings
Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer’s disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies.

Summary
PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic — pharmacological and non-pharmacological — and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile — visual-spatial — rather than memory-led, predominantly young onset — and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.
Personality trait estimation in group discussions using multimodal analysis and speaker embedding
Authors: Mawalim Candy Olivia , Okada Shogo , Nakano Yukiko I. , Unoki Masashi 
Published: February 2023

AbstractThe automatic estimation of personality traits is essential for many human–computer interface (HCI) applications. This paper focused on improving Big Five personality trait estimation in group discussions via multimodal analysis and transfer learning with the state-of-the-art speaker individuality feature, namely, the identity vector (i-vector) speaker embedding. The experiments were carried out by investigating the effective and robust multimodal features for estimation with two group discussion datasets, i.e., the Multimodal Task-Oriented Group Discussion (MATRICS) (in Japanese) and Emergent Leadership (ELEA) (in European languages) corpora. Subsequently, the evaluation was conducted by using leave-one-person-out cross-validation (LOPCV) and ablation tests to compare the effectiveness of each modality. The overall results showed that the speaker-dependent features, e.g., the i-vector, effectively improved the prediction accuracy of Big Five personality trait estimation. In addition, the experimental results showed that audio-related features were the most prominent features in both corpora.
A Reinforcement Learning approach for bus network design and frequency setting optimisation
Authors: Yoo Sunhyung , Lee Jinwoo Brian , Han Hoon 
Published: February 2023

AbstractThis paper proposes a new approach to solve the problem of bus network design and frequency setting (BNDFS). Transit network design must satisfy the needs of both service users and transit operators. Numerous optimisation techniques have been proposed for BNDFS in the literature. Previous approaches tend to adopt a sequential optimisation strategy that conducts network routing and service frequency setting in two separate steps. To address the limitation of sequential optimisation, our new algorithm uses Reinforcement Learning for a simultaneous optimisation of three key components of BNDFS: the number of bus routes, the route design and service frequencies. The algorithm can design the best set of bus routes without defining the total number of bus routes in advance, which can reduce the overall computational time. The proposed algorithm was tested on the benchmark Mandl Swiss network. The algorithm is further extended to the routing of express services. The validation includes additional test scenarios which modify the transit demand level on the Mandl network. The new algorithm can be useful to assist transit agencies and planners in improving existing routing and service frequency to cope with changing demand conditions.
A small assemblage of early Oligocene rodents and insectivores from the Sivas basin, Turkey
Authors: van de Weerd Andrew A. , de Bruijn Hans , Wessels Wilma 
Published: February 2023

AbstractThe assemblage of small mammals from a site near Yeniköy (Anatolia) is described. The assemblage was collected by screen-washing a sample from a locality in the Selimye Formation (Sivas basin). The site has a magneto-stratigraphic calibrated age of 29 Ma (younger part of the early Oligocene). The murids dominate in this relatively small collection with Eucricetodon and Pseudocricetodon. In addition, a dipodid, an unidentified erinaceide and the new baluchimyin hystricognath genus and species Zorania milosi nov. gen. et nov. sp. are present. The study of Eucricetodon, Pseudocricetodon and Zorania nov. sp. includes an analysis of incisor enamel microstructure. The incisor microstructure of Eucricetodon shows that there are several parallel long-living lineages within the genus. The Anatolia-Balkans biogeography of the late Eocene-Oligocene is reviewed. Its rodent assemblages are characterised by dominance of murids and presence of taxa that are known from low-latitude Asia. The Paleogene Anatolia-Balkans biogeographic province, is therefore rather different from those of western European and the Indian subcontinent.
Intersecting Inequalities in Access to Justice for Trans and Non-binary Sex Workers in Canada
Authors: Scheim Ayden I. , Santos Heather , Ciavarella Sophia , Vermilion Jelena , Arps Freddie S. E. , Adams Noah , Nation Kelendria , Bauer Greta R. 
Published: February 2023

Abstract
Introduction
In the context of renewed debate about Canada’s “end demand” sex work laws, we took an intersectional approach to characterize experiences with the criminal legal system and perceived access to justice among transgender (trans) and nonbinary sex workers in Canada.

Methods
The Trans PULSE Canada community-based study collected multimode survey data in fall 2019. Data were cross-stratified by lifetime sex work and sex assigned at birth, ethnoracial group, or household income. Age adjustment did not meaningfully impact results.

Results
Of 2012 included participants (median age = 30, 66.5% assigned female at birth, 48.9% non-binary), 280 (16.1%) had ever done sex work. While access to justice was limited for trans and non-binary people overall, sex workers were more likely to anticipate (72.1% vs. 50.5%) and experience (43.2% vs. 15.7%) police mistreatment. In the previous 5 years, sex workers were more likely to experience violence for any reason (61.4% vs. 27.4% of other participants) or due to being trans or non-binary (41.4% vs. 14.0%), and to have avoided calling 911 for police (51.4% vs. 18.1%). Few sex workers trusted that they would be treated fairly by police if they experienced physical (10.8% vs. 34.9%) or sexual (4.7% vs. 20.6%) violence. Intersectional inequalities included that sex workers assigned male at birth and street-based workers were most likely to have experienced gender-based violence, and that Indigenous and racialized sex workers reported higher levels of police mistreatment and 911 avoidance.

Conclusions
Overall, trans and non-binary people in Canada reported high levels of violence and limited access to justice. Sex workers faced large inequities in these outcomes, which were exacerbated for transfeminine, Indigenous, racialized, and street-based workers.

Policy Implications
These findings challenge the notion that Canadian sex work laws protect sex workers and highlight the limitations of formal legal protections for trans people. These inequities must be addressed in sex work legal reform efforts.
Personal GHG emissions accounting and the driving forces decomposition in the past 10 years
Authors: Zhou Yuxiao , Li Jiyang , Cui Jicui , Wang Hui , Wang Chuan , Zhang Ruina , Zhu Ying , Zhu Nanwen , Lou Ziyang 
Published: February 2023

AbstractPersonal greenhouse gas (PGHG) emissions were crucial for achieving carbon peak and neutrality targets. The accounting methodology and driving forces identification of PGHG emissions were helpful for the quantification and the reduction of the PGHG emissions. In this study, the methodology of PGHG emissions was developed from resource obtaining to waste disposal, and the variations of Shanghainese PGHG emissions from 2010 to 2020 were evaluated, with the driving forces analysis based on Logarithmic Mean Divisia Index (LMDI) model. It showed that the emissions decreased from 3796.05 (2010) to 3046.87 kg carbon dioxides (CO2) (2014) and then increased to 3411.35 kg CO2 (2018). The emissions from consumptions accounted for around 62.1% of the total emissions, and that from waste disposal were around 3.1%, which were neglected in most previous studies. The PGHG emissions decreased by around 0.53 kg CO2 (2019) and 405.86 kg CO2 (2020) compared to 2018 and 2019, respectively, which were mainly affected by the waste forced source separation policy and the COVID-19 pandemic. The income level and consumption GHG intensity were two key factors influencing the contractively of GHG emissions from consumption, with the contributing rate of 169.3% and − 188.1%, respectively. Energy consumption was the main factor contributing to the growth of the direct GHG emissions (296.4%), and the energy GHG emission factor was the main factor in suppressing it (− 92.2%). Green consumption, low carbon lifestyles, green levy programs, and energy structure optimization were suggested to reduce the PGHG emissions.
Multi-step semi-analytical solutions for a chikungunya virus system
Authors: Chamekh Mourad , Latrach Mohamed Ali , Jday Fadel 
Published: February 2023

AbstractIn this paper, we propose a semi-analytical solution for a dynamical system of differential equations describing Chikungunya virus propagation within the human population. For this, we propose an efficient method based on a modified differential method which can be useful for dynamical systems. At the numerical level, we compared the obtained solutions with Runge–Kutta 4 solutions, and we propose a study on the effect of this disease during an epidemic.