bluuebunny/crossref_metadata_2025_split huggingface dataset:
Power efficient MoS2 synaptic devices based on Maxwell–Wagner interfacial charging in binary oxides
Authors: Zou Jingyi , Lin Sen , Huang Tianyi , Liu Hefei , Liu Yushuang , Zhong Yibai , Lin Yuxuan Cosmi , Wang Han , Shen Sheng , Xu Min , Zhang Xu 
Published: October 2023

Abstract
Synaptic devices with tunable weight hold great promise in enabling non-von Neumann architecture for energy efficient computing. However, conventional metal-insulator-metal based two-terminal memristors share the same physical channel for both programming and reading, therefore the programming power consumption is dependent on the synaptic resistance states and can be particularly high when the memristor is in the low resistance states. Three terminal synaptic transistors, on the other hand, allow synchronous programming and reading and have been shown to possess excellent reliability. Here we present a binary oxide based three-terminal MoS2 synaptic device, in which the channel conductance can be modulated by interfacial charges generated at the oxide interface driven by Maxwell-Wagner instability. The binary oxide stack serves both as an interfacial charge host and gate dielectrics. Both excitatory and inhibitory behaviors are experimentally realized, and the presynaptic potential polarity can be effectively controlled by engineering the oxide stacking sequence, which is a unique feature compared with existing charge-trap based synaptic devices and provides a new tuning knob for controlling synaptic device characteristics. By adopting a three-terminal transistor structure, the programming channel and reading channel are physically separated and the programming power consumption can be kept constantly low (∼50 pW) across a wide dynamic range of 105. This work demonstrates a complementary metal oxide semiconductor compatible approach to build power efficient synaptic devices for artificial intelligence applications.
Stress relaxation behavior of low carbon steel at different temperatures
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Authors: Zuo Shanchao , Wang Danchen , Yang Changqi , Hu Peipei , Bi Ran , Du Bing , Wang Decheng 
Published: October 2023

Abstract
In this paper, the stress relaxation behavior of Q235 with the initial tensile stress of 70, 85 and 100 MPa were investigated at different temperature. Based on the thermal activation theory, the stress relaxation model of Q235 steel was established, and the physical mechanism and deformation process in the stress relaxation process were revealed. The results shows that with the increase of temperature or initial stress, the nominal activation volume decreases, but the strain rate and the strain rate sensitivity coefficient increase. The repeated stress relaxation test shows that the stress release amount decreases with the increase of the number of cycles, and the higher the temperature, the smaller the effect of the number of cycles. Under the action of temperature and stress, the dislocation starts to move from the disordered bending shape in the original sample to the flat shape gradually. Moreover, the dislocation density decreases to less than 47.8% of the initial sample as the temperature increases and the initial stress decreases. It can be concluded that the dislocation motion is the core mechanism of stress relaxation of Q235 steel.
Quantum eigenvector continuation for chemistry applications
Authors: Mejuto-Zaera Carlos , Kemper Alexander F 
Published: October 2023

Abstract
A typical task for classical and quantum computing in chemistry is finding a potential energy surface (PES) along a reaction coordinate, which involves solving the quantum chemistry problem for many points along the reaction path. Developing algorithms to accomplish this task on quantum computers has been an active area of development, yet finding all the relevant eigenstates along the reaction coordinate remains a difficult problem, and determining PESs is thus a costly proposal. In this paper, we demonstrate the use of a eigenvector continuation—a subspace expansion that uses a few eigenstates as a basis—as a tool for rapidly exploring PESs. We apply this to determining the binding PES or torsion PES for several molecules of varying complexity. In all cases, we show that the PES can be captured using relatively few basis states; suggesting that a significant amount of (quantum) computational effort can be saved by making use of already calculated ground states in this manner.
Unrecorded alcohol consumption in Lithuania: a modelling study for 2000–2021
Authors: Štelemėkas Mindaugas , Goštautaitė Midttun Nijolė , Lange Shannon , Liutkutė-Gumarov Vaida , Manthey Jakob , Miščikienė Laura , Petkevičienė Janina , Radišauskas Ričardas , Rehm Jürgen , Trišauskė Justina , Telksnys Tadas , Thompson Mark James 
Published: October 2023

Abstract
The aim of the study was to estimate unrecorded alcohol consumption in Lithuania for the period 2000–2021 using an indirect method for modelling consumption based on official consumption data and indicators of alcohol-related harm. Methodology employed for estimating the unrecorded alcohol consumption was proposed by Norström and was based on the country’s 2019 European Health Interview Survey and indicators of fully alcohol-attributable mortality. The proportion of unrecorded alcohol consumption was estimated as 8.30% (95% CI 7.7–8.9%) for 2019 in Lithuania. The estimated total (recorded and unrecorded) alcohol per capita consumption among individuals 15 years of age and older in 2019 was 12.2 L of pure alcohol, 1.01 (95% CI 0.94–1.09%) L of which is likely unrecorded. The lowest unrecorded alcohol level was estimated for 2009 and 2014, while 2018 had the highest level (i.e. 9.33% of total alcohol per capita consumption). Unrecorded alcohol consumption in Lithuania is likely to be modest when compared to recorded alcohol consumption, the latter of which still remains a major challenge to public health.
A - 25 The Role of Prospective Memory in Instrumental Activities of Daily Living and the Use of Compensatory Aids in Mild Cognitive Impairment
Authors: Kozuki Jordan T , Hickman Angela , Sidhu Jasman , Chapp Andrew , Lent David , Wright Matthew , Schmitter-Edgecombe Maureen , Woo Ellen 
Published: October 2023

Abstract

Objective
Prospective memory (PM), which involves remembering to execute a future action, is impacted by Alzheimer’s disease. This study examined the role of PM in instrumental activities of daily living (IADLs) and the use of compensatory aids in mild cognitive impairment (MCI) and healthy aging.

Methods
Participants included 44 healthy older controls and 49 persons with MCI. Simple PM was measured by asking participants to remember to execute a single action- to request a pill after completing each of a series of neuropsychological tests. Complex PM was then measured by asking participants to request a specific number of pills depending on whether a memory test was just completed or a non-memory test was completed. The Instrumental Activities of Daily Living- Compensation (IADL-C) scale was used to assess IADLs and the use of compensatory aids for completing these activities.

Results
Regression analyses revealed that both types of PM together predicted the IADLs of money/self-management skills and home/daily living skills in healthy older controls. Both types of PM also predicted total IADLs in controls. PM did not predict IADLs in MCI or the use of compensatory aids in either group.

Conclusion
Results indicated that PM was predictive of IADLs in healthy older adults. When PM skills are poorer, as in MCI, they are not predictive of IADLs.
A - 138 Using the Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System to Understand Complex Associations between Traumatic Brain Injury and Alcohol or Substance Use
Authors: Shirley Kate , Clauss Kate , Cameron David , Krushnic Danielle , Baker-Robinson William , Hannon Sara , O'Neil Maya 
Published: October 2023

Abstract

Objective
Associations between traumatic brain injury (TBI) and alcohol or substance use are complex and likely bidirectional. The purpose of this project was to conduct a proof-of-concept study demonstrating our ability to compile patient-level TBI data from shared studies in the Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System to improve our understanding of key TBI outcomes.

Method
We searched the FITBIR database for shared studies reporting alcohol or substance use among participants with TBI. We merged and harmonized data across the relevant studies to determine rates of alcohol or substance use by TBI severity.

Results
In the alcohol use sample (N = 1539), 82% of participants had a history of mild TBI and 46% met criteria for alcohol use disorder (AUD). Participants with a history of mild TBI had 1.34 greater odds of screening positive for AUD (95% CI: 0.98, 1.82) and males had 2.48 increased odds of screening positive for AUD (95% CI: 1.67, 3.68). Unfortunately, due to limited data on substance use we were unable to conduct the intended analyses for this outcome.

Conclusions
Data support research and theory suggesting that rates of AUD are higher among individuals with mild TBI versus those without, particularly among males. Additionally, this proof-of-concept study established methods, created data harmonization and analysis code, and provided the TBI-SUD meta dataset back to FITBIR for dissemination. Further, numerous additional datasets have been shared with the FITBIR platform since the time of these analyses, which will allow our team and others to extend these analyses over time.
Optimization of drug–target affinity prediction methods through feature processing schemes
Authors: Ru Xiaoqing , Zou Quan , Lin Chen 
Published: October 2023

AbstractMotivationNumerous high-accuracy drug–target affinity (DTA) prediction models, whose performance is heavily reliant on the drug and target feature information, are developed at the expense of complexity and interpretability. Feature extraction and optimization constitute a critical step that significantly influences the enhancement of model performance, robustness, and interpretability. Many existing studies aim to comprehensively characterize drugs and targets by extracting features from multiple perspectives; however, this approach has drawbacks: (i) an abundance of redundant or noisy features; and (ii) the feature sets often suffer from high dimensionality.ResultsIn this study, to obtain a model with high accuracy and strong interpretability, we utilize various traditional and cutting-edge feature selection and dimensionality reduction techniques to process self-associated features and adjacent associated features. These optimized features are then fed into learning to rank to achieve efficient DTA prediction. Extensive experimental results on two commonly used datasets indicate that, among various feature optimization methods, the regression tree-based feature selection method is most beneficial for constructing models with good performance and strong robustness. Then, by utilizing Shapley Additive Explanations values and the incremental feature selection approach, we obtain that the high-quality feature subset consists of the top 150D features and the top 20D features have a breakthrough impact on the DTA prediction. In conclusion, our study thoroughly validates the importance of feature optimization in DTA prediction and serves as inspiration for constructing high-performance and high-interpretable models.Availability and implementationhttps://github.com/RUXIAOQING964914140/FS_DTA.
A Bayesian nonparametric approach to correct for underreporting in count data
Authors: Arima Serena , Polettini Silvia , Pasculli Giuseppe , Gesualdo Loreto , Pesce Francesco , Procaccini Deni-Aldo 
Published: October 2023

Summary
We propose a nonparametric compound Poisson model for underreported count data that introduces a latent clustering structure for the reporting probabilities. The latter are estimated with the model’s parameters based on experts’ opinion and exploiting a proxy for the reporting process. The proposed model is used to estimate the prevalence of chronic kidney disease in Apulia, Italy, based on a unique statistical database covering information on m = 258 municipalities obtained by integrating multisource register information. Accurate prevalence estimates are needed for monitoring, surveillance, and management purposes; yet, counts are deemed to be considerably underreported, especially in some areas of Apulia, one of the most deprived and heterogeneous regions in Italy. Our results agree with previous findings and highlight interesting geographical patterns of the disease. We compare our model to existing approaches in the literature using simulated as well as real data on early neonatal mortality risk in Brazil, described in previous research: the proposed approach proves to be accurate and particularly suitable when partial information about data quality is available.
COVID-19 Impact on Children’s Social Work Practice and Social Worker Well-being: A Mixed Methods Study from Northern Ireland and Great Britain during 2020–2022
Authors: McFadden Paula , Ross Jana , MacLochlainn Justin , Mallett John , McGrory Susan , Currie Denise , Schroder Heike , Nicholl Patricia , Ravalier Jermaine , Manthorpe Jill 
Published: October 2023

Abstract
Social workers were heavily impacted by the COVID-19 pandemic. In this study, we examined the well-being, burnout and work conditions of UK children’s social workers at five time points of the COVID-19 pandemic. This was a cross-sectional mixed methods study analysing data from 1,621 social workers who worked in children’s services in the UK in 2020–2022. Data were collected using anonymous online surveys which included both quantitative and qualitative questions. The mental well-being of participants decreased as the pandemic progressed and work-related burnout increased. In the later stages of the pandemic, children’s social workers in Northern Ireland fared better than their Great Britain counterparts in relation to their well-being and levels of burnout. Thematic analysis of qualitative data revealed four major themes: Changes in service demand and referrals, Adapted ways of working, Staff shortages and Emotional impact. The findings highlight the challenges that the children’s social workers encountered during the COVID-19 pandemic and have implications for policy, practice and research.
Cardiac resynchronization therapy from an iliac approach in a patient without superior access: a case report
Authors: Xu Lei , Su Yangang , Qin Shengmei , Ge Junbo 
Published: October 2023

Abstract

Background
Cardiac resynchronization therapy (CRT) has been shown to benefit patients with heart failure and left bundle branch block (LBBB). However, CRT implantation is challenging when the superior venous access is not feasible.

Case summary
A 50-year-old man with a history of dilated cardiomyopathy and complete LBBB was referred to our hospital for CRT management. Angiography showed that the left and right brachiocephalic veins were occluded. Cardiac resynchronization therapy was finally implanted via the iliac vein. Follow-up echocardiography showed improved cardiac function, and the pacing system was functioning properly.

Discussion
The iliac vein access is feasible for CRT implantation with good stability, which can be a viable alternative to avoid unnecessary risk associated with thoracotomy and epicardial lead placement.
Subacute right coronary artery thrombosis treated by using Excimer Laser Coronary Angioplasty: a case report
Authors: Faria Daniel , Jeronimo Adrián , Escaned Javier , Nuñez-Gil Ivan J 
Published: October 2023

Abstract

Background
Managing high thrombotic burden in the context of myocardial infarction remains a challenging scenario.

Case summary
A 51-year-old male was admitted for a subacute inferior myocardial infarction with persistent chest pain. Emergent coronary angiography showed an ostial–proximal thrombotic occlusion of a large ectatic right coronary artery. Several balloon inflations were performed that were not able to improve distal TIMI flow beyond II. With the intent of vaporizing the remaining thrombus, Excimer Laser Coronary Angioplasty was performed with a favourable outcome.

Discussion
The present case constitutes an opportunity to revisit percutaneous and non-percutaneous strategies to tackle persistent coronary thrombus showing a contemporary approach to niche technologies such as laser angioplasty.
Practice makes perfect? Institutional coronary artery bypass case volumes and outcomes
Authors: Schwann Thomas A , Engoren Milo , Gaudino Mario F , Mentz Graciela , Saadat Siavash , Engelman Daniel , Lobdell Kevin W , Vekstein Andrew M , Habib Robert H 
Published: October 2023

Abstract

OBJECTIVES
Older studies of coronary artery bypass grafting (CABG) institutional case volumes and outcomes reported conflicting results. We explored this association in the rapidly changing contemporary practice of American surgeons using the Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database.

METHODS
The 2018–2019 isolated primary CABG experience in the STS Adult Cardiac Surgery Database was analysed (241 902 patients; 1014 hospitals; 2718 surgeons). Generalized Estimating Equations were used to estimate coefficients between CABG institutional case volumes and outcomes. The observed-to-expected ratios based on STS risk models were used to assess risk-adjusted operative mortality (OM), mortality/major morbidity (MM) and deep sternal wound infections (DSWI) as a function of institutional case volumes.

RESULTS
The mean (standard deviation) OM, MM and DSWI rates were 2.1% (2.7), 11.1% (9.2) and 0.6% (0.5), respectively. The mean (standard deviation) institutional case volumes per study period was 239 (192); 23% and 9% of institutions performed &lt;100 and &gt;500 cases/study period, respectively. There was a weak negative correlation between expected mortality (R2 –0.0014), OM (R2 –0.0272), MM (R2 –0.1213) and DSWI (R2 –0.003) and institutional case volumes.

CONCLUSIONS
CABG outcomes generally improve with increasing institutional case volumes. Given the large number of CABG cases performed nationally, even the documented weak correlation has the potential to appreciably decrease OM, MM and DSWI if cases are performed at higher volume institutions. Studies focusing on additional hospital and surgeon factors are warranted to further define quality improvement opportunities.
Oxidative Stress Factors Mediate the Association Between Life’s Essential 8 and Accelerated Phenotypic Aging: NHANES 2005–2018
Authors: Liu Wen , Wang Jia , Wang Miao , Hou Huimin , Ding Xin , Ma Lingzhi , Liu Ming 
Published: October 2023

Abstract
Cardiovascular health (CVH) is a well-known predictor of morbidity and mortality, while phenotypic age (PhenoAge) is a promising biomarker of aging. This study aimed to explore the association between Life’s Essential 8 (LE8), a novel CVH measure, and PhenoAge acceleration (PhenoAgeAccel), as well as the potential mediating role of oxidative stress biomarkers in this relationship. A total of 23 896 individuals were included in the National Health and Nutrition Examination Survey database (2005–2018). Life’s Essential 8 scores were categorized into low, moderate, and high groups. PhenoAge, measured through clinical laboratory blood chemistries, served as a marker of biological aging. Weighted linear regression analyses were performed to assess the association between LE8 scores and PhenoAgeAceel. In the multivariable linear regression, LE8 scores were significantly and inversely associated with PhenoAgeAccel, showing a decreased risk in the moderate CVH group (β −2.98; 95% CI −3.29, −2.66) and high CVH group (β −4.72; 95% CI −5.08, −4.35) compared to the low CVH group. When treated as a continuous variable, each 10-point increase in LE8 scores corresponded to a 1.14-year decrease in PhenoAge (β −1.14; 95% CI −1.21, −1.06). Among the 8 individual components in LE8, 7 exhibited a significant negative correlation with PhenoAgeAccel, except for blood lipids. Additionally, mediation analysis revealed that oxidative stress biomarkers, including γ-glutamyltransferase, bilirubin, and uric acid, collectively mediated 17.1% of the associations between LE8 scores and PhenoAgeAccel (p &lt; .001). Higher LE8 scores, representing ideal CVH, are significantly related to a deceleration in PhenoAge, and oxidative stress biomarkers may play a mediating role in this relationship.
Combining uncertainty-aware predictive modeling and a bedtimeSmart Snackintervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections
Authors: Mosquera-Lopez Clara , Roquemen-Echeverri Valentina , Tyler Nichole S , Patton Susana R , Clements Mark A , Martin Corby K , Riddell Michael C , Gal Robin L , Gillingham Melanie , Wilson Leah M , Castle Jessica R , Jacobs Peter G 
Published: October 2023

AbstractObjectiveNocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose metrics and physical activity patterns. We utilized these predictions in silico to prescribe bedtime carbohydrates with a Smart Snack intervention specific to the predicted minimum nocturnal glucose and timing of nocturnal hypoglycemia.Materials and methodsWe leveraged free-living datasets collected from 366 individuals from the T1DEXI Study and Glooko. Inputs to the ENN used to model nocturnal hypoglycemia were derived from demographic information, continuous glucose monitoring, and physical activity data. We assessed the accuracy of the ENN using area under the receiver operating curve, and the clinical impact of the Smart Snack intervention through simulations.ResultsThe ENN achieved an area under the receiver operating curve of 0.80 and 0.71 to predict nocturnal hypoglycemic events during 0-4 and 4-8 h after bedtime, respectively, outperforming all evaluated baseline methods. Use of the Smart Snack intervention reduced probability of nocturnal hypoglycemia from 23.9 ± 14.1% to 14.0 ± 13.3% and duration from 7.4 ± 7.0% to 2.4 ± 3.3% in silico.DiscussionOur findings indicate that the ENN-based Smart Snack intervention has the potential to significantly reduce the frequency and duration of nocturnal hypoglycemic events.ConclusionA decision support system that combines prediction of minimum nocturnal glucose and proactive recommendations for bedtime carbohydrate intake might effectively prevent nocturnal hypoglycemia and reduce the burden of glycemic self-management.