bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dissolution of Bioactive Glass S53P4 in Continuous Flows of Tris Buffer and Lactic Acid
Authors: Siekkinen Minna , Engblom Markus , Karlström Oskar , Hupa Leena 
Published: November 2023

AbstractIn vitro dynamic dissolution of bioactive glass S53P4 particles was studied in a cascade of three reactors. Tris buffer (pH 7.40) and lactic acid (pH 2.00) with flow rates of 0.2 and 0.04 ml/min were fed through the reactors for 24 h. The increased ion concentrations in Tris inflows to the second and third reactors decreased the dissolution of the particles. However, the normalised surface-specific mass loss rate decreased from the first to the third reactor and with decreasing flow rate. No distinct differences were observed in the reaction layers on the particles in the three consecutive reactors. This implied that the ions released in the previous reactors contributed to the reaction layers formed in the following reactors. Highly incongruent dissolution with similar dissolution rates of sodium, calcium, and phosphorus occurred with the two flow rates in lactic acid. Although a thick silica-rich layer formed on the particles, the low pH prevented calcium phosphate layer precipitation. The results imply that S53P4 particles in an implant react at different rates depending on their location but form similar reaction layer morphologies independent of their location in physiological solutions (pH 7.4). On the other hand, S53P4 particles exposed to acidic solutions with a pH < 5 likely dissolve incongruently, leaving a slowly dissolving Si-rich layer. In such an environment, the dissolution rates of Na, Ca, and P are independent of the location of the S53P4 particle in the implant. Thus, the pH and fluid flow are critical factors for the dissolution of S53P4 bioactive glass particles.
APT Attack Detection Based on Graph Convolutional Neural Networks
Authors: Ren Weiwu , Song Xintong , Hong Yu , Lei Ying , Yao Jinyu , Du Yazhou , Li Wenjuan 
Published: November 2023

AbstractAdvanced persistent threat (APT) attacks are malicious and targeted forms of cyberattacks that pose significant challenges to the information security of governments and enterprises. Traditional detection methods struggle to extract long-term relationships within these attacks effectively. This paper proposes an APT attack detection model based on graph convolutional neural networks (GCNs) to address this issue. The aim is to detect known attacks based on vulnerabilities and attack contexts. We extract organization-vulnerability relationships from publicly available APT threat intelligence, along with the names and relationships of software security entities from CVE, CWE, and CAPEC, to generate triple data and construct a knowledge graph of APT attack behaviors. This knowledge graph is transformed into a homogeneous graph, and GCNs are employed to process graph features, enabling effective APT attack detection. We evaluate the proposed method on the dataset constructed in this paper. The results show that the detection accuracy of the GCN method reaches 95.9%, improving by approximately 2.1% compared to the GraphSage method. This approach proves to be effective in real-world APT attack detection scenarios.
Machine learning for activity-based road transportation emissions estimation
Authors: Rollend Derek , Foster Kevin , Kott Tomek M. , Mocharla Rohita , Muñoz Rai , Fendley Neil , Ashcraft Chace , Willard Frank , Reilly Elizabeth P. , Hughes Marisa 
Published: November 2023

Abstract
Measuring and attributing greenhouse gas (GHG) emissions remains a challenging problem as the world strives toward meeting emissions reductions targets. As a significant portion of total global emissions, the road transportation sector represents an enormous challenge for estimating and tracking emissions at a global scale. To meet this challenge, we have developed a hybrid approach for estimating road transportation emissions that combines the strengths of machine learning and satellite imagery with localized emissions factors data to create an accurate, globally scalable, and easily configurable GHG monitoring framework.
Leveraging Bluetooth low-energy technology to improve contact tracing among healthcare personnel in hospital setting during the coronavirus disease 2019 (COVID-19) pandemic
Authors: Vazquez Guillamet M. Cristina , Rjob Ashraf , Zhang Jingwen , Dai Ruixuan , Wang Ruiqi , Damulira Christopher , Hamauon Reshad , Candell Jeff , Kwon Jennie H. , Babcock Hilary , Bailey Thomas C. , Lu Chenyang , Fraser Victoria 
Published: November 2023

AbstractTo improve contact tracing for healthcare workers, we built and configured a Bluetooth low-energy system. We predicted close contacts with great accuracy and provided an additional contact yield of 14.8%. This system would decrease the effective reproduction number by 56% and would unnecessarily quarantine 0.74% of employees weekly.
Physician perceptions of barriers to infection prevention and control in labor and delivery
Authors: Barnes Laura E.A. , White Katelyn A. , Young Marisa R. , Ramsey Patrick S. , Cochran Ronda L. , Perkins Kiran M. 
Published: November 2023

AbstractObjective:To learn about the perceptions of healthcare personnel (HCP) on the barriers they encounter when performing infection prevention and control (IPC) practices in labor and delivery to help inform future IPC resources tailored to this setting.Design:Qualitative focus groups.Setting:Labor and delivery units in acute-care settings.Participants:A convenience sample of labor and delivery HCP attending the Infectious Diseases Society for Obstetrics and Gynecology 2022 Annual Meeting.Methods:Two focus groups, each lasting 45 minutes, were conducted by a team from the Centers for Disease Control and Prevention. A standardized script facilitated discussion around performing IPC practices during labor and delivery. Coding was performed by 3 reviewers using an immersion-crystallization technique.Results:In total, 18 conference attendees participated in the focus groups: 67% obstetrician-gynecologists, 17% infectious disease physicians, 11% medical students, and 6% an obstetric anesthesiologist. Participants described the difficulty of consistently performing IPC practices in this setting because they often respond to emergencies, are an entry point to the hospital, and frequently encounter bodily fluids. They also described that IPC training and education is not specific to labor and delivery, and personal protective equipment is difficult to locate when needed. Participants observed a lack of standardization of IPC protocols in their setting and felt that healthcare for women and pregnant people is not prioritized on a larger scale and within their hospitals.Conclusions:This study identified barriers to consistently implementing IPC practices in the labor and delivery setting. These barriers should be addressed through targeted interventions and the development of obstetric-specific IPC resources.
Precision therapy in dilated cardiomyopathy: Pipedream or paradigm shift?
Authors: Javed Saad , Halliday Brian P. 
Published: November 2023

Abstract
Precision medicine for cardiomyopathies holds great promise to improve patient outcomes costs by shifting the focus to patient-specific treatment decisions, maximising the use of therapies most likely to lead to benefit and minimising unnecessary intervention. Dilated cardiomyopathy (DCM), characterised by left ventricular dilatation and impairment, is a major cause of heart failure globally. Advances in genomic medicine have increased our understanding of the genetic architecture of DCM. Understanding the functional implications of genetic variation to reveal genotype-specific disease mechanisms is the subject of intense investigation, with advanced cardiac imaging and mutliomics approaches playing important roles. This may lead to increasing use of novel, targeted therapy. Individualised treatment and risk stratification is however made more complex by the modifying effects of common genetic variation and acquired environmental factors that help explain the variable expressivity of rare genetic variants and gene elusive disease. The next frontier must be expanding work into early disease to understand the mechanisms that drive disease expression, so that the focus can be placed on disease prevention rather than management of later symptomatic disease. Overcoming these challenges holds the key to enabling a paradigm shift in care from the management of symptomatic heart failure to prevention of disease.
Revisiting the predisposing, enabling, and need factors of unsafe abortion in India using the Heckman Probit model
Authors: Rahaman Margubur , Roy Avijit , Chouhan Pradip , Das Kailash Chandra , Rana Md Juel 
Published: November 2023

AbstractUnsafe abortion refers to induced abortions performed without trained medical assistance. While previous studies have investigated predictors of unsafe abortion in India, none have addressed these factors with accounting sample selection bias. This study aims to evaluate the contributors to unsafe abortion in India by using the latest National Family Health Survey data conducted during 2019–2021, incorporating the adjustment of sample selection bias. The study included women aged 15 to 49 who had terminated their most recent pregnancy within five years prior to the survey (total weighted sample (N) = 4,810). Descriptive and bivariate statistics and the Heckman Probit model were employed. The prevalence of unsafe abortion in India was 31%. Key predictors of unsafe abortion included women’s age, the gender composition of their living children, gestation stage, family planning status, and geographical region. Unsafe abortions were typically performed in the early stages of gestation, often involving self-administered medication. The primary reasons cited were unintended pregnancies and health complications. This study underscores the urgent need for targeted interventions that take into account regional, demographic, and social dynamics influencing abortion practices in India.
Medico-legal liability of injuries arising from laryngoscopy
Authors: Fritz Christian G , Monos Stylianos D , Romeo Dominic , Lowery Anne , Xu Katherine , Atkins Joshua , Rajasekaran Karthik 
Published: November 2023

AbstractObjectiveDental and mucosal injuries from laryngoscopy in the peri-operative period are common medico-legal complaints. This study investigated lawsuits arising from laryngoscopy.MethodsWestlaw, a legal database containing trial records from across the USA, was retrospectively reviewed. Plaintiff and/or defendant characteristics, claimed injuries, legal outcomes and awards were extracted.ResultsOf all laryngoscopy-related dental or mucosal injuries brought before a state or federal court, none (0 per cent) resulted in a defence verdict against the provider or monetary gain for the patient. Rulings in the patient's favour were observed only when laryngoscopy was found to be the proximate cause of multiple compounding complications that culminated in severe medical outcomes such as exsanguination, septic shock or cardiopulmonary arrest.ConclusionProper laryngoscopy technique and a robust informed-consent process that accurately sets patients' expectations reduces litigation risk. Future litigation pursuits should consider the low likelihood of malpractice allegation success at trial.
The road to recovery: conservation management for the Critically Endangered Bali myna shows signs of success
Authors: Squires Thomas M. , Kepakisan Agus N.K. , Kusumanegara Hery , Collar Nigel J. , Yuni Luh P.E.K. , Owen Andrew , Nugroho Andri , Sarmawi Mas U. , Nelson S. Sunny , Winarni Nurul L. , Marsden Stuart J. 
Published: November 2023

AbstractThe Bali mynaLeucopsar rothschildihas long suffered heavy trapping, leading to its near extinction in the wild and categorization as Critically Endangered on the IUCN Red List. Decades of conservation breeding, release of birds and post-release management at Bali Barat National Park have, until recently, failed to secure a viable wild population. However, over the past decade, population increases, expansion into new areas of the National Park and beyond, and successful breeding in both artificial and natural nest sites have occurred. These recent successes are associated with a change in approach by the National Park authority from concentrating efforts on the last refugium of the species (an area protected from trapping but with potentially suboptimal habitat) and towards the human-dominated landscapes around the main road through the National Park. Bali mynas tended to favour areas with extensive shorter grass cover and open canopies and to shun denser woodland. Anthropogenic landscapes such as farmland and plantations presumably mimic the original savannah habitat of the species, but nestbox provision has probably been crucial in these areas in the absence of natural cavities. A potential further factor in the increases in myna numbers and range has been a scheme involving local people in commercial breeding of the species, thereby reducing its market price, and working with communities to reduce trapping pressure. We encourage continuing operation of this management strategy inside the National Park and its further extension into adjacent tourist areas, which appear to have myna-friendly socio-ecological conditions.
The risk and development of work disability among individuals with gambling disorder: a longitudinal case–cohort study in Sweden
Authors: Månsson Viktor , Pettersson Emma , Mittendorfer-Rutz Ellenor , Guterstam Joar , Berman Anne H. , Jayaram-Lindström Nitya , Molero Yasmina 
Published: November 2023

AbstractBackgroundThis longitudinal register study aimed to investigate the association between gambling disorder (GD) and work disability and to map work disability in subgroups of individuals with GD, three years before and three years after diagnosis.MethodsWe included individuals aged 19–62 with GD between 2005 and 2018 (n = 2830; 71.1% men, mean age: 35.1) and a matched comparison cohort (n = 28 300). Work disability was operationalized as the aggregated net days of sickness absence and disability pension. Generalized estimating equation models were used to calculate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for the risk of long-term work disability (>90 days of work disability/year). Secondly, we conducted Group-based Trajectory Models on days of work disability.ResultsIndividuals with GD showed a four-year increased risk of long-term work disability compared to the matched cohort, peaking at the time of diagnosis (AOR = 1.89; CI 1.67–2.13). Four trajectory groups of work disability days were identified: constant low (60.3%, 5.6–11.2 days), low and increasing (11.4%, 11.8–152.5 days), medium–high and decreasing (11.1%, 65.1–110 days), and constant high (17.1%, 264–331 days). Individuals who were females, older, with prior psychiatric diagnosis, and had been dispensed a psychotropic medication, particularly antidepressants, were more likely to be assigned to groups other than the constant low.ConclusionIndividuals with GD have an increased risk of work disability which may add financial and social pressure and is an additional incentive for earlier detection and prevention of GD.
Interpretable long-term gait trajectory prediction based on Interpretable-Concatenation former
Authors: Yin Jie , Chen Meng , Zhang Chongfeng , Xue Tao , Zhang Ming , Zhang Tao 
Published: November 2023

AbstractHuman gait trajectory prediction is a long-standing research topic in human–machine interaction. However, there are two shortcomings in the current gait trajectory prediction technology. The first shortcoming is that the neural network model of gait prediction only predicts dozens of future time frames of gait trajectory. The second shortcoming is that the gait prediction neural network model is uninterpretable. We propose the Interpretable-Concatenation former (IC-former) model, which can predict long-term gait trajectories and explain the prediction results by quantifying the importance of data at different positions in the input sequence. Experiments prove that the IC-former model we proposed not only makes a breakthrough in prediction accuracy but also successfully explains the data basis of the prediction.
Differential activation of programmed cell death in patients with severe SARS-CoV-2 infection
Authors: Riegler Ashleigh N. , Benson Paul , Long Kenneth , Leal Sixto M. 
Published: November 2023

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes severe lower airway disease and death in a subset of patients. Knowledge on the relative contribution of programmed cell death (PCD) to lung pathology is limited to few human autopsy studies with small sample size/scope, in vitro cell culture, and experimental model systems. In this study, we sought to identify, localize, and quantify activation of apoptosis, ferroptosis, pyroptosis, and necroptosis in FFPE lung tissues from patients that died from severe SARS-CoV-2 infection (n = 28) relative to uninfected controls (n = 13). Immunofluorescence (IF) staining, whole-slide imaging, and Image J software was used to localize and quantify expression of SARS-CoV-2 nucleoprotein and the following PCD protein markers: cleaved Caspase-3, pMLKL, cleaved Gasdermin D, and CD71, respectively. IF showed differential activation of each PCD pathway in infected lungs and dichotomous staining for SARS-CoV-2 nucleoprotein enabling distinction between high (n = 9) vs low viral burden (n = 19). No differences were observed in apoptosis and ferroptosis in SARS-CoV-2 infected lungs relative to uninfected controls. However, both pyroptosis and necroptosis were significantly increased in SARS-CoV-2-infected lungs. Increased pyroptosis was observed in SARS-CoV-2 infected lungs, irrespective of viral burden, suggesting an inflammation-driven mechanism. In contrast, necroptosis exhibited a very strong positive correlation with viral burden (R2 = 0.9925), suggesting a direct SARS-CoV-2 mediated effect. These data indicate a possible novel mechanism for viral-mediated necroptosis and a potential role for both lytic programmed cell death pathways, necroptosis and pyroptosis, in mediating infection outcome.
Slower clozapine titration is associated with delayed onset of clozapine-induced fever among Japanese patients with schizophrenia
Authors: Kikuchi Yuki , Yada Yuji , Otsuka Yuji , Ito Fumiaki , Tanifuji Hiroaki , Komatsu Hiroshi , Tomita Hiroaki 
Published: November 2023

AbstractClozapine-induced fever marks the beginning of its inflammatory and potentially life-threatening adverse effects, such as myocarditis. We retrospectively analyzed the correlation between clozapine titration rate and fever onset date in 254 Japanese patients, including 55 with treatment-resistant schizophrenia who developed clozapine-induced fever. Pearson’s product-moment correlation indicated a significant delay in the fever onset date with slower titration. Most fever onset cases occurred within 4 weeks, even with slow titration. Therefore, clinicians should remain vigilant in monitoring clozapine-induced fever within 4 weeks of clozapine initiation, regardless of the titration rate.
Functional convergence of genomic and transcriptomic architecture underlies schooling behaviour in a live-bearing fish
Authors: Corral-Lopez Alberto , Bloch Natasha I. , van der Bijl Wouter , Cortazar-Chinarro Maria , Szorkovszky Alexander , Kotrschal Alexander , Darolti Iulia , Buechel Severine D. , Romenskyy Maksym , Kolm Niclas , Mank Judith E. 
Published: November 2023

AbstractThe organization and coordination of fish schools provide a valuable model to investigate the genetic architecture of affiliative behaviours and dissect the mechanisms underlying social behaviours and personalities. Here we used replicate guppy selection lines that vary in schooling propensity and combine quantitative genetics with genomic and transcriptomic analyses to investigate the genetic basis of sociability phenotypes. We show that consistent with findings in collective motion patterns, experimental evolution of schooling propensity increased the sociability of female, but not male, guppies when swimming with unfamiliar conspecifics. This finding highlights a relevant link between coordinated motion and sociability for species forming fission–fusion societies in which both group size and the type of social interactions are dynamic across space and time. We further show that alignment and attraction, the two major traits forming the sociability personality axis in this species, showed heritability estimates at the upper end of the range previously described for social behaviours, with important variation across sexes. The results from both Pool-seq and RNA-seq data indicated that genes involved in neuron migration and synaptic function were instrumental in the evolution of sociability, highlighting a crucial role of glutamatergic synaptic function and calcium-dependent signalling processes in the evolution of schooling.
Facemap: a framework for modeling neural activity based on orofacial tracking
Authors: Syeda Atika , Zhong Lin , Tung Renee , Long Will , Pachitariu Marius , Stringer Carsen 
Published: November 2023

AbstractRecent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracker and a deep neural network encoder for predicting neural activity. Our algorithm for tracking mouse orofacial behaviors was more accurate than existing pose estimation tools, while the processing speed was several times faster, making it a powerful tool for real-time experimental interventions. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used the keypoints as inputs to a deep neural network which predicts the activity of ~50,000 simultaneously-recorded neurons and, in visual cortex, we doubled the amount of explained variance compared to previous methods. Using this model, we found that the neuronal activity clusters that were well predicted from behavior were more spatially spread out across cortex. We also found that the deep behavioral features from the model had stereotypical, sequential dynamics that were not reversible in time. In summary, Facemap provides a stepping stone toward understanding the function of the brain-wide neural signals and their relation to behavior.
Electromyography and kinematics data of the hand in activities of daily living with special interest for ergonomics
Authors: Roda-Sales Alba , Jarque-Bou Néstor J. , Bayarri-Porcar Vicent , Gracia-Ibáñez Verónica , Sancho-Bru Joaquín L. , Vergara Margarita 
Published: November 2023

AbstractThis work presents a dataset of human hand kinematics and forearm muscle activation collected during the performance of a wide variety of activities of daily living (ADLs), with tagged characteristics of products and tasks. A total of 26 participants performed 161 ADLs selected to be representative of common elementary tasks, grasp types, product orientations and performance heights. 105 products were used, being varied regarding shape, dimensions, weight and type (common products and assistive devices). The data were recorded using CyberGlove instrumented gloves on both hands measuring 18 degrees of freedom on each and seven surface EMG sensors per arm recording muscle activity. Data of more than 4100 ADLs is presented in this dataset as MATLAB structures with full continuous recordings, which may be used in applications such as machine learning or to characterize healthy human hand behaviour. The dataset is accompanied with a custom data visualization application (ERGOMOVMUS) as a tool for ergonomics applications, allowing visualization and calculation of aggregated data from specific task, product and/or participants’ characteristics.