bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-classical Correlations of Accelerated Observers Interacting with a Classical Stochastic Noise
Authors: Abd-Rabbou M. Y. , Shamirzaie M. , Khan Salman 
Published: January 2023

Abstract
The influence of a classical environment on the behaviour of the Wigner function and the concurrence of an accelerated two-qubit system interacting is discussed. The negative values of the Wigner function verify the non-classicality, while the concurrence shows the entanglement degree of the quantum system. We assume one or both observers are accelerated (s) and interact with a common or independent environment. Suppression of the coherence rises due to acceleration effect, noise strength, and noise frequency are pointed. The amount of quantum entanglement is investigated by using the quantum concurrence, where its positive values are consistent with what the negative Wigner function shows. We found that the degradation of coherence of the initial system reduces when observers interact with their environments independently more than when it interacts with a common one. It is also sensitive to the acceleration status of both observers. Additionally, the correlation and entanglement pertinent to the situation with common or independent noise agents behave contrarily for the two regimes of Markovian and non-Markovian noises.
A Case of Tofacitinib for the Treatment of Resistant Vitiligo and Sustained Repigmentation After Discontinuation
Authors: Shah Rohan , McMichael Amy 
Published: January 2023

Abstract
Vitiligo is an acquired skin disorder clinically characterized by depigmented macules and patches caused by the autoimmune destruction of melanocytes. Tofacitinib, an oral Janus Kinase (JAK) 1/3 inhibitor approved for the treatment of rheumatoid arthritis has been used off-label for alopecia areata, and more recently, vitiligo. With advancements in understanding vitiligo pathogenesis, JAK inhibitors like tofacitinib have emerged as a promising treatment modality especially when traditional therapies including topical steroids and calcineurin inhibitors have had minimal efficacy. As with other targeted therapies, tofacitinib is associated with certain adverse effects, the most dangerous being malignancy. We report a 61-year-old woman with a history of progressive vitiligo, refractory to multiple topical therapies, who was initiated on tofacitinib and showed significant improvement in disease. However, she subsequently developed a primary lung adenocarcinoma within 20 months of treatment and was forced to discontinue treatment. Although definitive causation cannot be established in this case without additional studies, it is important to note that tofacitinib, and other targeted therapies, have the ability to increase susceptibility to cancer. Unlike previous studies which report a relapse in vitiligo after treatment discontinuation, our case was noteworthy in that even after 5 months of discontinuing tofacitinib the patient maintained pigmentation. This finding offers a foundation for exploring new treatment protocols for patients whose vitiligo has clinically improved and who may not need continued usage of tofacitinib.
Safety helmet detection method based on semantic guidance and feature selection fusion
Authors: Xu Zhigang , Li Yugen , Zhu Honglei 
Published: January 2023

Abstract
Safety helmet detection is a hot topic of research in the field of industrial safety for object detection technology. Existing object detection methods still face great challenges for the detection of small-scale safety helmet object. In this paper, we propose a safety helmet detection method based on the fusion of semantic guidance and feature selection. The method is able to consider the balance between detection performance and efficiency. First, a multi scale non-local module is proposed to establish internal correlations between different scales of deep image features as well as to aggregate semantic context information to guide the information recovery of decoder network features. Then the feature selection fusion structure is proposed to adaptively select deep features and underlying key features for fusion to make up for the missing semantic and spatial detail information of the decoding network and improve the spatial location expression capability of the decoding network. Experimental analysis shows that the method in this paper has good detection performance on the expanded safety helmet wearing dataset with 5.12% improvement in mAP compared to the baseline method CenterNet, and 6.11% improvement in AP for the safety helmet object.
Effects of high energy laser peening followed by pre-hot corrosion on stress relaxation, microhardness and fatigue life and strength of single crystal nickel CMSX-4® superalloy
Authors: Morar Nicolau Iralal , Holtham Noah , Hackel Lloyd , Davami Keivan , Sharma Montu , DeWald Adrian , Roy Rajkumar 
Published: January 2023

Abstract

This study investigated the stress relaxation and fatigue life and strength of laser peened single crystal nickel superalloy specimens compared to un-peened and shot peened specimens following hot corrosion exposure and then fatigue testing. The specimens were treated by conventional laser peening and a new cyclic laser peening plus thermal microstructure engineering process. The latter treatment supports the benefit of a unique process involving application of layers of laser peening using high energy with large footprint spots combined with interspersed cyclic annealing. Stress measurements by slitting showed the plastic penetration depth of laser peening exceeded shot peening by a factor of 24. Un-peened and peened specimens were exposed to sulphate corrosives at 700°C for 300 hours and then fatigue tested. Tests of five non-laser peened specimens all failed in low cycle fatigue regime whereas three identically tested laser peened specimens all achieved multi-million-cycle runout without failure, indicating fully consistent large benefit for life by laser peening. Additional tests also showed fatigue strength improvement of 2:1 by laser peening. Residual stress measurements post hot-corrosion exposure and fatigue testing showed notable 5 mm depth retention of residual eigenstress in a laser peened specimen.
Differentiation of acute graft-versus-host disease from drug reaction in skin by a novel tissue-based biomarker assay
Authors: Lehman Julia S. , Dasari Surendra , Damodaran Sindhuja Sominidi , Li Ming , Hashmi Shahrukh K. , el-Azhary Rokea A. , Gibson Lawrence E. , Lazarus Hillard M. , Hogan William J. , Kenderian Saad S. , Patnaik Mrinal M. , Litzow Mark R. , Meves Alexander 
Published: January 2023

Abstract
Acute graft-versus-host disease (GVHD), a serious complication of allogeneic hematopoietic cell transplantation (HCT), frequently involves the skin. Since clinicopathologic features of GVHD can mimic those of certain drug eruptions, accurate diagnosis can be challenging. We aimed to develop a tissue-based molecular assay to improve differentiation of GVHD from vacuolar interface drug eruption in the post-HCT period. After identifying 62 putative tissue-based biomarkers using unbiased molecular methods, we incorporated 26 into a quantitative RT-PCR assay. We tested skin biopsy specimens showing vacuolar interface changes attributable to either acute GVHD (n=67) or drug reaction (n=17), as classified by meticulous review of clinical features and course. Data were incorporated into clinical-molecular fusion diagnostic models. Significant differences in the expression of several genes, including MX1, MNDA, OAS, LIMA1, GSTM5, and SPP1, were detected between the two diagnostic groups (p<0.05). The optimal fusion model, which incorporated quantitative expression of MX1, MNDA, OAS, and GSTM5, as well as the clinical feature of diarrhea, imparted high diagnostic accuracy (receiver operating characteristic area-under-curve: 0.89). This novel tissue-based diagnostic molecular assay and fusion model demonstrates potential to improve distinction of GVHD from drug eruptions in the post-HCT setting. Multicenter validation studies are required.
Differential response to Donepezil in MRI subtypes of mild cognitive impairment
Authors: Diaz-Galvan Patricia , Lorenzon Giulia , Mohanty Rosaleena , Mårtensson Gustav , Cavedo Enrica , Lista Simone , Vergallo Andrea , Kantarci Kejal , Hampel Harald , Dubois Bruno , Grothe Michel , Ferreira Daniel , Westman Eric 
Published: January 2023

Abstract
Background
Donepezil is an approved therapy for the treatment of Alzheimer’s disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to Donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes.
Methods
From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical-AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We compared two subtyping approaches: the conventional categorical approach and an approach based on continuous dimensions.
Results
Donepezil treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response.
Conclusions
Our data suggest that individuals with MCI, with hippocampal sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment.
Trial registration:
Clinical Trial.gov Number: NCT00403520, Submission Date: November 21, 2006.
Evolution of Chilean Higher Education From the Governance Equalizer Perspective
Authors: Brunner José Joaquin , Alarcón Mario 
Published: January 2023

Abstract
This article examines how Chile's higher education system governance has evolved over the past 50 years. The New Public Management (NPM) narrative is used as our conceptual framework and the governance equalizer as our analytical model to study changes in different periods characterized by different political contexts. The results show that over the past 50 years, governance of the Chilean higher education system has transitioned from an academic self-governance regime to a hybrid scheme coordinated predominantly by means of state regulation, competition and managerial governance. The results of previous studies that used the governance equalizer lens applied to the higher education systems of Italy, Hungary, Ukraine, Poland, and Ethiopia are reviewed. We find there is a common trend towards hybrid governance models, and we note the limitations of the ideal governance regimes to represent the current complexity of national systems of higher education.
Five decades of infectious diseases outbreaks in the African region (1970-2018) A geographic snapshot
Authors: Ngom Roland , Gueye Abdou Salam , Lassieur Stephanie , Oloo Stephen , Shahid Rizwan , Mize Valerie , Lukoya Charles okot , Waogodo Joseph Cabore , Fall Ibrahima Soce 
Published: January 2023

Abstract

This paper is being written at a time when the recent pandemic, namely COVID-19 has shaken the entire world in a manner that has never been seen in modern history. The ecology, socio-economy and weak health systems make Africa an area favorable to the occurrence of various diseases and disease outbreaks. This paper explores forty-eight (48) years of disease outbreaks in the WHO African region of the World Health Organization (WHO). Twenty-five (25) Integrated Disease Surveillance and Response priority diseases were selected, and their outbreaks described and analyzed. Using inferential spatial statistics, spatial clusters at the health district level, specifically hot spots of those outbreaks were produced and analyzed. Population at risk those hot spots were estimated. Results show a consistent report of outbreaks during the selected period with 52 outbreaks on average per year. Poliomyelitis, cholera, yellow fever, meningococcal disease and measles were the most reported epidemics. Democratic Republic of the Congo (DRC) and Nigeria were the countries reporting the highest number of outbreaks (5 on average per year) with the latter country having the highest population at risk (39M people). Despite efforts to limit their number, some disease outbreaks such as malaria, cholera, and measles continue to have a burden in terms of morbidity and mortality, while others such as poliomyelitis, yellow fever and diarrhoeal disease have shown a declining trend and the wild polio virus transmission has been eliminated in the region. Results suggest that concerted public health action may help reduce the occurrences of outbreaks in the region. Results can be used to inform preparedness and prevention activities. Priority public health actions should target DRC and Nigeria, but also identified hot spots and areas with existing risk factors within other countries.
Two years of COVID restrictions: A lesson from water demand data
Authors: Balacco Gabriella , Martellotta Audrey Maria Noemi , Iacobellis Vito , Piccinni Alberto Ferruccio 
Published: January 2023

Abstract
The long period of great fragility experienced by the lockdown has strained entire countries. In response to COVID-19, Italy performed stay-at-home orders to attenuate disease spread, provoking drastic changes in all aspects of users' behaviour, particularly affecting water demand. A dataset of hourly water demand for 2019, 2020, and 2021, related to five Italian towns permitted to observe water consumption changes. Trends highlight a general decrease in water consumption, linked to the strict restrictions imposed and a morning peak shift. At the end of the strict quarantine regulations, water consumption did not return to pre-pandemic values because COVID-19 has led to a change in lifestyle.
Manejo do Nitrogênio Químico e Orgânico em Dois Ciclos de Alface Irrigado com Água Residuária
Authors: Lobo Thomaz Figueiredo , Siqueira Marcos Vinicius Bohrer Monteiro , Oliveira Sebastião de , Grassi Filho Hélio 
Published: January 2023

O aumento do custo de fertilizantes minerais e a crescente poluição ambiental fazem do uso de resíduos orgânicos na agricultura uma opção atrativa do ponto de vista econômico, em razão da ciclagem de C e nutrientes. O objetivo deste trabalho foi avaliar a produtividade e a nutrição do alface em diferentes manejos de nitrogênio químico e orgânico irrigado com água residuária proveniente da Estação de Tratamento de Esgoto (ETE) em dois ciclos de alface. O experimento foi realizado em vaso com capacidade para 5 litros, em casa de vegetação, o delineamento experimental foi composto por 6 tratamentos e 5 blocos casualizados da seguinte maneira: T0 – sem N; T1 – 0,54 gramas por planta de N mineral proveniente da ureia esta adubação foi dividida em três vezes (7, 14 e 28 dias de transplante); T2 – 0,27 gramas de N proveninete do composto organico (esterco de galinha e casca de eucalipto) e 0,27 gramas de N proveniente de ureia dividido em três vezes por planta (7, 14 e 28 dias de transplante); T3 – 0,54 gramas de N (composto orgânico) por planta; T4 – 0,81 gramas de N (composto orgânico) por planta; T5 – 1,08 gramas de N (composto orgânico) por planta. As adubaçoes com composto organico foi realizada antes do plantio e misturado ao solo. As alfaces que foram adubadas com composto orgânico obtiveram maiores produtividades de massa fresca e acúmulo de nutrientes tanto no primeiro quanto no segundo ciclo.
Telemedical Interventions for Chronic Obstructive Pulmonary Disease Management: Umbrella Review
Authors: Koh Jin Hean , Chong Lydia Ching Yee , Koh Gerald Choon Huat , Tyagi Shilpa 
Published: January 2023

Background
Chronic obstructive pulmonary disease (COPD) is a growing epidemic, with a heavy associated economic burden. Education, physical activity, and pulmonary rehabilitation programs are important aspects of the management of COPD. These interventions are commonly delivered remotely as part of telemedicine interventions. Several systematic reviews and meta-analyses have been conducted to assess the effectiveness of these interventions. However, these reviews often have conflicting conclusions.

Objective
We aim to conduct an umbrella review to critically appraise and summarize the available evidence on telemedicine interventions for the management of COPD.

Methods
In this umbrella review, the MEDLINE, Embase, PsycINFO, and Cochrane databases were searched from inception to May 2022 for systematic reviews and meta-analyses relating to telemedicine interventions for the management of COPD. We compared odds ratios, measures of quality, and heterogeneity across different outcomes.

Results
We identified 7 systematic reviews that met the inclusion criteria. Telemedicine interventions used in these reviews were teletreatment, telemonitoring, and telesupport. Telesupport interventions significantly reduced the number of inpatient days and quality of life. Telemonitoring interventions were associated with significant reductions in respiratory exacerbations and hospitalization rates. Teletreatment showed significant effectiveness in reducing respiratory exacerbations, hospitalization rate, compliance (acceptance and dropout rate), and physical activity. Among studies that used integrated telemedicine interventions, there was a significant improvement in physical activity.

Conclusions
Telemedicine interventions showed noninferiority or superiority over the standard of care for the management of COPD. Telemedicine interventions should be considered as a supplement to usual methods of care for the outpatient management of COPD, with the aim of reducing the burden on health care systems.
A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis
Authors: Coelho Flávio , Câmara Daniel Cardoso Portela , Araújo Eduardo Correa , Bianchi Lucas Monteiro , Ogasawara Ivan , Dalal Jyoti , James Ananthu , Abbate Jessica L , Merzouki Aziza , dos Reis Izabel Cristina , Nwosu Kene David , Keiser Olivia 
Published: January 2023

Background
Guaranteeing durability, provenance, accessibility, and trust in open data sets can be challenging for researchers and organizations that rely on public repositories of data critical for epidemiology and other health analytics. The required data repositories are often difficult to locate and may require conversion to a standard data format. Data-hosting websites may also change or become unavailable without warning. A single change to the rules in one repository can hinder updating a public dashboard reliant on data pulled from external sources. These concerns are particularly challenging at the international level, because policies on systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs.

Objective
In this paper, we introduce a comprehensive public health data platform, EpiGraphHub, that aims to provide a single interoperable repository for open health and related data.

Methods
The platform, curated by the international research community, allows secure local integration of sensitive data while facilitating the development of data-driven applications and reports for decision-makers. Its main components include centrally managed databases with fine-grained access control to data, fully automated and documented data collection and transformation, and a powerful web-based data exploration and visualization tool.

Results
EpiGraphHub is already being used for hosting a growing collection of open data sets and for automating epidemiological analyses based on them. The project has also released an open-source software library with the analytical methods used in the platform.

Conclusions
The platform is fully open source and open to external users. It is in active development with the goal of maximizing its value for large-scale public health studies.
Understanding Why Many People Experiencing Homelessness Reported Migrating to a Small Canadian City: Machine Learning Approach With Augmented Data
Authors: Liyanage Chandreen Ravihari , Mago Vijay , Schiff Rebecca , Ranta Ken , Park Aaron , Lovato-Day Kristyn , Agnor Elise , Gokani Ravi 
Published: January 2023

Background
Over the past years, homelessness has become a substantial issue around the globe. The largest social services organization in Thunder Bay, Ontario, Canada, has observed that a majority of the people experiencing homelessness in the city were from outside of the city or province. Thus, to improve programming and resource allocation for people experiencing homelessness in the city, including shelter use, it was important to investigate the trends associated with homelessness and migration.

Objective
This study aimed to address 3 research questions related to homelessness and migration in Thunder Bay: What factors predict whether a person who migrated to the city and is experiencing homelessness stays or leaves shelters? If an individual stays, how long are they likely to stay? What factors predict stay duration?

Methods
We collected the required data from 2 sources: a survey conducted with people experiencing homelessness at 3 homeless shelters in Thunder Bay and the database of a homeless information management system. The records of 110 migrants were used for the analysis. Two feature selection techniques were used to address the first and third research questions, and 8 machine learning models were used to address the second research question. In addition, data augmentation was performed to improve the size of the data set and to resolve the class imbalance problem. The area under the receiver operating characteristic curve value and cross-validation accuracy were used to measure the models’ performances while avoiding possible model overfitting.

Results
Factors predicting an individual’s stay duration included home or previous district, highest educational qualification, recent receipt of mental health support, migrating to visit family or friends, and finding employment upon arrival. For research question 2, among the classification models developed for predicting the stay duration of migrants, the random forest and gradient boosting tree models presented better results with area under the receiver operating characteristic curve values of 0.91 and 0.93, respectively. Finally, home district, band membership, status card, previous district, and recent support for drug and/or alcohol use were recognized as the factors predicting stay duration.

Conclusions
Applying machine learning enables researchers to make predictions related to migrants’ homelessness and investigate how various factors become determinants of the predictions. We hope that the findings of this study will aid future policy making and resource allocation to better serve people experiencing homelessness. However, further improvements in the data set size and interpretation of the identified factors in decision-making are required.