bluuebunny/crossref_metadata_2025_split huggingface dataset:
Finding answers in lipid profile in COVID-19 patients
Authors: Sampedro-Nuñez M. , Aguirre-Moreno N. , García-Fraile Fraile L. , Jiménez-Blanco S. , Knott-Torcal C. , Sanz-Martin P. , Fernández-Jiménez G. , Marazuela M. 
Published: October 2021

Abstract
Introduction
A small percentage of patients will develop a severe form of COVID-19 caused by SARS-CoV-2 infection. Thus, it is important to predict the potential outcomes identifying early markers of poor prognosis. In this context, we evaluated the association of SARS-CoV-2 infection with lipid abnormalities and their role in prognosis.

Methods
Single-center, retrospective, observational study of COVID-19 patients admitted from March to October 2020. Clinical and laboratory data, comorbidities, and treatments for COVID-19 were evaluated. Main outcomes including intensive care unit (ICU) admission and mortality were analyzed with a multivariable Cox proportional hazards regression model.

Results
We selected 1489 from a total of 2038 consecutive patients with confirmed COVID-19, who had a complete lipid profile before ICU admission. During the follow-up performed in 1109 patients, we observed a decrease in T-c, HDL-c, and LDL-c in 28.6%, 42.9%, and 30.4% of patients, respectively, and an increase in TG in 76.8%. The decrease of both T-c and HDL- c was correlated with a decrease in albumin levels (r = 0.39 and r = 0.37, respectively). Kaplan–Meier survival curves found an increased ICU admission in patients with lower T-c (HR 0.55, CI 0.36–0.86), HDL-c (HR 0.61, CI 0.45–0.84), and LDL-c (HR 0.85, CI 0.74–0.97). Higher values of T-c (HR 0.45, CI 0.36–0.57), HDL-c (HR 0.66, CI 0.54–0.81), and LDL-c (HR 0.86, CI 0.78–0.94) showed a protective effect on mortality.

Conclusions
Abnormalities in lipid profile are a frequent complication of SARS-CoV-2 infection and might be related to morbidity and mortality.

Funding
Proyectos de Investigación en Salud (FIS) and cofinanced by FEDER.
Aplysia Neurons as a Model of Alzheimer’s Disease: Shared Genes and Differential Expression
Authors: Kron Nicholas S. , Fieber Lynne A. 
Published: October 2021

AbstractAlthough Alzheimer’s disease (AD) is the most common form of dementia in the United States, development of therapeutics has proven difficult. Invertebrate alternatives to current mammalian AD models have been successfully employed to study the etiology of the molecular hallmarks of AD. The marine snailAplysia californicaoffers a unique and underutilized system in which to study the physiological, behavioral, and molecular impacts of AD. Mapping of theAplysiaproteome to humans and cross-referencing with two databases of genes of interest in AD research identified 898 potential orthologs of interest inAplysia. Included among these orthologs were alpha, beta and gamma secretases, amyloid-beta, and tau. Comparison of age-associated differential expression inAplysiasensory neurons with that of late-onset AD in the frontal lobe identified 59 ortholog with concordant differential expression across data sets. The 21 concordantly upregulated genes suggested increased cellular stress and protein dyshomeostasis. The 47 concordantly downregulated genes included important components of diverse neuronal processes, including energy metabolism, mitochondrial homeostasis, synaptic signaling, Ca++regulation, and cellular cargo transport. Compromised functions in these processes are known hallmarks of both human aging and AD, the ramifications of which are suggested to underpin cognitive declines in aging and neurodegenerative disease.
The origins of paraffinic oils collected from oilfields in the western Siberian Basin, Russia: implications from geochemical and physical characteristics
Authors: Hakimi Mohammed Hail , Saeed Shadi A. , Al-Muntaser Ameen A. , Varfolomeev Mikhail A. , Djimasbe Richard , Lashin Aref , Yelwa Nura Abdulmumini , Suwaid Muneer A. 
Published: October 2021

AbstractFour oil samples were collected from oilfields in the western Siberian Basin, and analyzed using conventional geochemical and physical methods. The results of this study were used to evaluate the oil samples, focusing on the characteristics of their source rocks, including the origin of organic matter input; redox depositional conditions and degree of thermal maturity of their probable source rock were studied. The obtained SARA results show that the examined oils are paraffinic oils owing to their high saturated hydrocarbon fraction values of greater than 70% volume. The observed API gravity values (23.55° to 32.57°) and low sulfur content of less than 0.25% wt indicate that the examined oils are sweet oils and were generated from source rock containing Type-II, with low sulfur content. The low sulfur content combined with the vanadium (V) and nickel (Ni) ratios indicates that the examined oils were scoured from a mixture of aquatic and terrestrial organic matter, depositing under generally suboxic environmental conditions. The n-alkane and isoprenoid distributions, with their ratios and parameters further suggest that the examined oil samples were generated from source rock containing a mixed organic matter input and deposited under suboxic to relatively oxic environmental conditions. Bulk compositions and distributions of n-alkane and isoprenoid indicate that the oil samples were generated from mature source rock.
Safety evaluation of a vehicle–bridge interaction system using the pseudo-excitation method
Authors: Zhang Nan , Zhou Ziji , Wu Zhaozhi 
Published: October 2021

AbstractA method for analysing the vehicle–bridge interaction system with enhanced objectivity is proposed in the paper, which considers the time-variant and random characteristics and allows finding the power spectral densities (PSDs) of the system responses directly from the PSD of track irregularity. The pseudo-excitation method is adopted in the proposed framework, where the vehicle is modelled as a rigid body and the bridge is modelled using the finite element method. The vertical and lateral wheel–rail pseudo-excitations are established assuming the wheel and rail have the same displacement and using the simplified Kalker creep theory, respectively. The power spectrum function of vehicle and bridge responses is calculated by history integral. Based on the dynamic responses from the deterministic and random analyses of the interaction system, and the probability density functions for three safety factors (derailment coefficient, wheel unloading rate, and lateral wheel axle force) are obtained, and the probabilities of the safety factors exceeding the given limits are calculated. The proposed method is validated by Monte Carlo simulations using a case study of a high-speed train running over a bridge with five simply supported spans and four piers.
Change Detection of Urban Trees in MLS Point Clouds Using Occupancy Grids
Authors: Hirt Philipp-Roman , Xu Yusheng , Hoegner Ludwig , Stilla Uwe 
Published: October 2021

AbstractTrees play an important role in the complex system of urban environments. Their benefits to environment and health are manifold. Yet, especially near streets, the traffic can be impaired by a limited clearance. Even injuries could be caused by breaking tree parts. Hence, it is important to capture the trees in the frame of a tree cadastre and to ensure regular monitoring. Mobile laser scanning (MLS) can be used for data acquisition, followed by an automated analysis of the point clouds acquired over time. The presented approach uses occupancy grids with a grid size of 10 cm, which enable the comparison of several epochs in three-dimensional space. Prior to that, a segmentation of single tree objects is conducted. After cylinder-based trunk localisation, closely neighboured tree crowns are separated using weights derived from local point densities. Therefore, changes for every single tree can be derived with regard to its parameters and its point cloud. The testing area is set along an urban street in Munich, Germany, using the publicly available benchmark data sets TUM-MLS-2016/2018. In the frame of the evaluation, tree objects are geo-referenced and mapped in 2D. The tree parameters height and diameter at breast height are derived. The geometric evaluation of the change analysis facilitates not only the acquisition of stock changes, but also the detection of shape changes for the tree objects.
Tying the Delivery of Activity Step Instructions to Step Performance: Evaluating a Basic Technology System with People with Special Needs
Authors: Lancioni Giulio E. , O’Reilly Mark F. , Sigafoos Jeff , Alberti Gloria , Tenerelli Giovanna , Ricci Carlo , Marschik Peter B. , Desideri Lorenzo 
Published: October 2021

Abstract

Objectives

This study assessed a new technology system that automatically presented instructions for multistep activities to people with intellectual and sensory disabilities. The instructions were presented one at a time, and tied to the participants’ performance of the activity steps. That is, a new instruction occurred only after the participant had carried out the previous step.

Methods
The new system involved a Samsung Galaxy A10 with Android 10.0 operating system equipped with Amazon Alexa, MacroDroid, and Philips Hue applications and a Philips Hue indoor motion sensor. The assessment of the new system was carried out with seven participants who were exposed to two or three pairs of activities. They performed one activity of each pair with the new system and the other with a system presenting instructions at preset time intervals according to an alternating treatments design that included a cross-over phase.

Results
The mean percentage of correct responses tended to be higher with the new system than with the control system. Paired t-tests carried out to compare the sessions with the new system with the sessions with the control system of each participant showed that the differences in correct responses between the two sets of sessions were statistically significant for all participants.

Conclusions
The new system may represent a useful (advantageous) tool for supporting people like those involved in this study in the performance of multistep activities.
Contemporary Transformations in the Brazilian Popular Catholic Festivals: the Case of the Holy Divine Spirit Festival (Festa do Divino)
Authors: Siuda-Ambroziak Renata , Mariano Fabiene Passamani 
Published: October 2021

AbstractThe Azorean families, wherever they migrated, brought their cultural background in which there clearly stood out celebrations of the annual festival of the Divine Holy Spirit. The Festa do Divino, as it is called in Brazil, has turned, in places where they originally settled down, into one of the most famous religious festivals of the Brazilian Popular Catholicism. However, due to some contemporary sociocultural factors, mostly linked to the more and more frequent application of the laws of market economy to the sphere of religion and also to the visible liberalization of the religious festivals’ “rules of conduct,” it has been recently suffering from some important modifications. In this article, we present and analyze such changes, basing on the study of celebrations of this popular religious tradition in four different municipalities of four different states of Brazil.
Methodology for integrating artificial intelligence in healthcare systems: learning from COVID-19 to prepare for Disease X
Authors: Radanliev Petar , De Roure David , Maple Carsten , Ani Uchenna 
Published: October 2021

AbstractArtificial intelligence and edge devices have been used at an increased rate in managing the COVID-19 pandemic. In this article we review the lessons learned from COVID-19 to postulate possible solutions for a Disease X event. The overall purpose of the study and the research problems investigated is the integration of artificial intelligence function in digital healthcare systems. The basic design of the study includes a systematic state-of-the-art review, followed by an evaluation of different approaches to managing global pandemics. The study design then engages with constructing a new methodology for integrating algorithms in healthcare systems, followed by analysis of the new methodology and a discussion. Action research is applied to review existing state of the art, and a qualitative case study method is used to analyse the knowledge acquired from the COVID-19 pandemic. Major trends found as a result of the study derive from the synthesis of COVID-19 knowledge, presenting new insights in the form of a conceptual methodology—that includes six phases for managing a future Disease X event, resulting with a summary map of various problems, solutions and expected results from integrating functional AI in healthcare systems.
The Structural Violence Trap: Disparities in Homicide, Chronic Disease Death, and Social Factors Across San Francisco Neighborhoods
Authors: Boeck Marissa A , Wei Waverly , Robles Anamaria J , Nwabuo Adaobi I , Plevin Rebecca E , Juillard Catherine J , Bibbins-Domingo Kirsten , Hubbard Alan , Dicker Rochelle A 
Published: October 2021

BACKGROUND:
On average, a person living in San Francisco can expect to live 83 years. This number conceals significant variation by sex, race, and place of residence. We examined deaths and area-based social factors by San Francisco neighborhood, hypothesizing that socially disadvantaged neighborhoods shoulder a disproportionate mortality burden across generations, especially deaths attributable to violence and chronic disease. These data will inform targeted interventions and guide further research into effective solutions for San Francisco’s marginalized communities.

STUDY DESIGN:
The San Francisco Department of Public Health provided data for the 2010–2014 top 20 causes of premature death by San Francisco neighborhood. Population-level demographic data were obtained from the US American Community Survey 2015 5-year estimate (2011–2015). The primary outcome was the association between years of life loss (YLL) and adjusted years of life lost (AYLL) for the top 20 causes of death in San Francisco and select social factors by neighborhood via linear regression analysis and heatmaps.

RESULTS:
The top 20 causes accounted for N = 15,687 San Francisco resident deaths from 2010–2014. Eight neighborhoods (21.0%) accounted for 47.9% of city-wide YLLs, with 6 falling below the city-wide median household income and many having a higher percent population Black, and lower education and higher unemployment levels. For chronic diseases and homicides, AYLLs increased as a neighborhood’s percent Black, below poverty level, unemployment, and below high school education increased.

CONCLUSIONS:
Our study highlights the mortality inequity burdening socially disadvantaged San Francisco neighborhoods, which align with areas subjected to historical discriminatory policies like redlining. These data emphasize the need to address past injustices and move toward equal access to wealth and health for all San Franciscans.
Recurrent neural network for end-to-end modeling of laminar-turbulent transition
Authors: Zafar Muhammad I. , Choudhari Meelan M. , Paredes Pedro , Xiao Heng 
Published: October 2021

Abstract
Accurate prediction of laminar-turbulent transition is a critical element of computational fluid dynamics simulations for aerodynamic design across multiple flow regimes. Traditional methods of transition prediction cannot be easily extended to flow configurations where the transition process depends on a large set of parameters. In comparison, neural network methods allow higher dimensional input features to be considered without compromising the efficiency and accuracy of the traditional data-driven models. Neural network methods proposed earlier follow a cumbersome methodology of predicting instability growth rates over a broad range of frequencies, which are then processed to obtain the N-factor envelope, and then, the transition location based on the correlating N-factor. This paper presents an end-to-end transition model based on a recurrent neural network, which sequentially processes the mean boundary-layer profiles along the surface of the aerodynamic body to directly predict the N-factor envelope and the transition locations over a two-dimensional airfoil. The proposed transition model has been developed and assessed using a large database of 53 airfoils over a wide range of chord Reynolds numbers and angles of attack. The large universe of airfoils encountered in various applications causes additional difficulties. As such, we provide further insights on selecting training datasets from large amounts of available data. Although the proposed model has been analyzed for two-dimensional boundary layers in this paper, it can be easily generalized to other flows due to embedded feature extraction capability of convolutional neural network in the model.
The Swedish Covid-19 strategy and voluntary compliance: Failed securitisation or constitutional security management?
Authors: Larsson Oscar Leonard 
Published: October 2021

AbstractThe Covid-19 pandemic that emerged in the spring of 2020 caused severe political, social, and economic turmoil throughout the world. In spite of early warning signals from the World Health Organization, countries struggled to shape their policy responses and countermeasures for curtailing the spread of the virus while also minimising the damage that any restrictions would inflict on the health and well-being of society at large. While some countries have adopted strict regulations and extraordinary measures after declaring ‘states of exception’ and ‘national emergencies’, others have relied upon expert recommendations and individual responsibility. Sweden is viewed as having adopted one of the latter type of approaches in that it places the responsibility for social distancing upon the individual. Is this an instance of a failed ‘securitisation’ process, or rather a sensible constitutional and political response to a severe security event? This article presents an in-depth analysis of the Swedish strategy for coping with Covid-19, arguing that this case illustrates that security management in a democratic state should direct greater attention to rule following in accordance with a logic of appropriateness rather than the rule breaking envisaged by securitisation theory.
Attempted suicide rates before and during the COVID-19 pandemic: interrupted time series analysis of a nationally representative sample
Authors: Travis-Lumer Yael , Kodesh Arad , Goldberg Yair , Frangou Sophia , Levine Stephen Z. 
Published: October 2021

AbstractBackgroundTo characterize the association between the protracted biopsychosocial coronavirus disease 2019 (COVID-19) pandemic exposures and incident suicide attempt rates.MethodsData were from a nationally representative cohort based on electronic health records from January 2013 to February 2021 (N = 852 233), with an interrupted time series study design. For the primary analysis, the effect of COVID-19 pandemic on incident suicide attempts warranting in-patient hospital treatment was quantified by fitting a Poisson regression and modeling the relative risk (RR) and the corresponding 95% confidence intervals (CIs). Scenarios were forecast to predict attempted suicide rates at 10 months after social mitigation strategies. Fourteen sensitivity analyses were performed to test the robustness of the results.ResultsDespite the increasing trend in the unexposed interval, the interval exposed to the COVID-19 pandemic was statistically significant (p < 0.001) associated with a reduced RR of incident attempted suicide (RR = 0.63, 95% CI 0.52–0.78). Consistent with the primary analysis, sensitivity analysis of sociodemographic groups and methodological factors were statistically significant (p < 0.05). No effect modification was identified for COVID-19 lockdown intervals or COVID-19 illness status. All three forecast scenarios at 10 months projected a suicide attempt rate increase from 12.49 (7.42–21.01) to 21.38 (12.71–35.99).ConclusionsThe interval exposed to the protracted mass social trauma of the COVID-19 pandemic was associated with a lower suicide attempt rate compared to the unexposed interval. However, this trend is likely to reverse 10 months after lifting social mitigation policies, underscoring the need for enhanced implementation of public health policy for suicide prevention.
Intelligent cooperative collision avoidance via fuzzy potential fields
Authors: Choi Daegyun , Chhabra Anirudh , Kim Donghoon 
Published: October 2021

SummaryThis paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.
A type- and scope-safe universe of syntaxes with binding: their semantics and proofs
Authors: ALLAIS GUILLAUME , ATKEY ROBERT , CHAPMAN JAMES , MCBRIDE CONOR , MCKINNA JAMES 
Published: October 2021

Abstract
The syntax of almost every programming language includes a notion of binder and corresponding bound occurrences, along with the accompanying notions of α-equivalence, capture-avoiding substitution, typing contexts, runtime environments, and so on. In the past, implementing and reasoning about programming languages required careful handling to maintain the correct behaviour of bound variables. Modern programming languages include features that enable constraints like scope safety to be expressed in types. Nevertheless, the programmer is still forced to write the same boilerplate over again for each new implementation of a scope-safe operation (e.g., renaming, substitution, desugaring, printing), and then again for correctness proofs. We present an expressive universe of syntaxes with binding and demonstrate how to (1) implement scope-safe traversals once and for all by generic programming; and (2) how to derive properties of these traversals by generic proving. Our universe description, generic traversals and proofs, and our examples have all been formalised in Agda and are available in the accompanying material available online at https://github.com/gallais/generic-syntax.