bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved deep semantic dictionary learning for multi-label image classification
Authors: Zhang Shihan 
Published: November 2023

Abstract
Multi-label image classification is a practical and challenging task in the field of machine learning. It is a fundamental but essential task used in auto driving, internet image classification, and other fields. Many researchers have done various researches on relevant aspects. Deep Semantic Dictionary Learning (DSDL) is a multi-label image classification method brought out by previous researchers which combines the semantic meaning information into the classification task. However, it only uses one kind of feature extraction network as the feature map generator without considering other alternatives. In this paper, six types of pretrained networks are applied as alternative choices to validate the performance of DSDL on different neural networks. Experiments are conducted on the VOC2007 dataset and the result shows the inner relation of different series of neural networks and demonstrates that different feature extraction networks perform variously on different tasks. The ResNet-152 achieves the mean average precision (mAP) of 94.5% and outperforms the original DSDL method of 0.3% mAP.
Research on electronic stethoscope system and signal processing algorithm
Authors: Li Xiao , Shang Yujing , Wei Jiaqi , Zhou Yiheng 
Published: November 2023

Abstract
Stethoscopes have an important role in non-invasive diagnosis of cardiovascular and respiratory diseases, digestive diseases, and other kinds of diseases. The emergence of high-end diagnostic devices and new diagnostic methods have caused the status of the stethoscope to decline. However, stethoscope has the advantages of simple operation, mature auscultation theory and low cost, and thus is still widely used in medical diagnosis. This paper first introduces the design and application of electronic stethoscope solutions based on contact sensors and air coupling sensors, and then introduces advanced algorithms for digital signal processing for the diagnosis and treatment of different diseases, including heart sound noise reduction algorithm, heart sound segmentation algorithm and heart sound feature extraction and recognition algorithm. Finally, this paper summarizes the application of the electronic stethoscope system in medical testing, and its future development direction. In summary, the electronic stethoscope system is a reliable medical testing tool, which can convert sound signals into digital signals through complex signal processing algorithms for more accurate detection of human physiological parameters. The research of this paper will be of great value to the research and application of electronic stethoscopes.
CNN combined with data augmentation for face recognition on small dataset
Authors: Chen Siru 
Published: November 2023

Abstract
Faces have universal structures yet contain distinct features among individuals. Recognizing individuals based on their faces has always been a popular topic in pattern recognition, and computer vision and many traditional approaches have yielded satisfying results. In recent years, rapid growth in deep learning has encouraged researchers to use deep learning methods to solve authentication problems. Convolutional neural networks are one of the most popular deep neural networks with multiple layers and the ability to reduce parameters by using kernels to capture features from input. It has outstanding performance in pattern recognition due to its ability to extract features and take images as inputs. In machine learning, data augmentation is a technique to seemingly enlarge a dataset to avoid underfitting or overfitting problems caused by insufficient data. This paper uses convolutional neural networks to solve face recognition problems on a small dataset. It compares performance with traditional face recognition methods such as Principal Component Analysis and examines the impact on performance using data augmentation. Overall, data augmentation boosts the accuracy of the network but also results in an unsteady learning curve. The convolutional neural network performs well on pattern recognition and obtains an accuracy of 94% in an augmented dataset with only two convolutional layers.
Face image generation and feature visualization using deep convolutional generative adversarial networks
Authors: Wu Han 
Published: November 2023

Abstract
Generative Neural Networks (GAN) aims to generate realistic and recognizable images, including portraits, cartoons and other modalities. Image generation has broad application prospects and important research value in the fields of public security and digital entertainment, and has become one of the current research hotspots. This article will introduce and apply an important image generation model called GAN, which stands for Generative Adversarial Network. Unlike recent image processing models such as Variational Autoencoders (VAE), The discriminative network evaluates potential candidates while the GAN generates candidates. As a result, the discriminative network distinguishes created and real candidates, while the generative network learns to map from a latent space to an interest data distribution. In this article, the GAN model and some of its extensions will be thoroughly applied and implemented based on the dataset of CelebA, and details will be discussed through the images and graphs generated by the model. Specific training methods for various models and optimization algorithms can be produced by the GAN framework. The experiment’s findings in this article will show how the framework’s potential may be quantified and qualitatively assessed using the samples that were produced.
Review of ansatz designing techniques for variational quantum algorithms
Authors: Qin Junhan 
Published: November 2023

Abstract
For a large number of tasks, quantum computing demonstrates the potential for exponential acceleration over classical computing. In the NISQ era, variable-component subcircuits enable applications of quantum computing. To reduce the inherent noise and qubit size limitations of quantum computers, existing research has improved the accuracy and efficiency of Variational Quantum Algorithm (VQA). In this paper, we explore the various ansatz improvement methods for VQAs at the gate level and pulse level, and classify, evaluate and summarize them.
Theoretical framework and advanced applications of spiking neural networks
Authors: Zhu Shurui 
Published: November 2023

Abstract
Developed from traditional Artificial neural networks (ANN), the Spiking neural network (SNN) faithfully mimics the biological behaviours of natural neurons. SNNs transmit information through firing of spiking neurons only when the membrane potential reaches a certain threshold. Because of this property, SNNs are referred to as the most biologically plausible neural model. They are also evaluated as time-efficient and low power-consuming when dealing with complex computational tasks. In this paper, the differences between SNNs and ANNs are first identified. The theoretical framework of the SNN, including the biomedical background, classical spiking neuron models, neural coding mechanisms as well as the learning algorithm are then thoroughly introduced. From the theories, the SNN’s biological plausibility, working principles, strengths and limitations are discussed. Additionally, two applications in the medical & robotics field using the SNN’s pattern recognition and classification are described in detail, indicating its potential in more innovative studies. More imaginative uses of SNNs are in demand for its dominant role in future computational fields.
Social Ecological Influences on Nicotine/Tobacco Use Among Gender-Varying and Gender-Stable Adolescents and Adults in the USA
Authors: Kcomt Luisa , Evans-Polce Rebecca J , Engstrom Curtiss W , Takahashi Jodene , Matthews Phoenix A , Veliz Phil T , West Brady T , McCabe Sean Esteban 
Published: November 2023

AbstractBackground and PurposeOur study examined individual-, interpersonal-, community-, and policy-level associations with nicotine/tobacco use among gender-varying and gender-stable U.S. individuals.MethodsData from Waves 2–4 (2014/15–2016/18) of the Population Assessment of Tobacco and Health (n = 33,197 U.S. adolescents and adults aged ≥14 years) and state-level gender minority policy data were used. Using multivariable logistic regression, the odds of past-30-day nicotine/tobacco use at W4 were estimated as a function of gender stability/variability, psychological distress, number of tobacco products used by family/friends, anti-tobacco marketing exposure, and change in gender minority-related policies from 2015 to 2017.ResultsGender-varying individuals had higher odds of nicotine/tobacco use compared with gender-stable individuals (AOR range = 1.7–2.3, p &lt; .01). In the overall sample, positive change in gender minority policy protections (tallied from medium to high) was associated with lower odds of any nicotine/tobacco, other tobacco, and poly-tobacco use (AOR = 0.8, p &lt; .05) compared to states with no change in their negative policies. Anti-tobacco marketing exposure was associated with lower odds of any tobacco, cigarette, e-cigarette, and poly-tobacco use compared with those who had no anti-tobacco marketing exposure (AOR = 0.9, p &lt; .05). Higher psychological distress (AOR range = 1.7–2.4, p &lt; .001) and an increasing number of tobacco products used by family/friends (AOR range = 1.1–1.3, p &lt; .001) were associated with increased odds of nicotine/tobacco use.ConclusionsMultilevel prevention and intervention strategies are needed to reduce the risk of nicotine/tobacco use among gender-varying and gender-stable individuals.
Postacute symptoms 4 months after SARS-CoV-2 infection during the Omicron period: a nationwide Danish questionnaire study
Authors: Spiliopoulos Lampros , Sørensen Anna Irene Vedel , Bager Peter , Nielsen Nete Munk , Hansen Jørgen Vinsløv , Koch Anders , Meder Inger Kristine , Videbech Poul , Ethelberg Steen , Hviid Anders 
Published: November 2023

Abstract
Postacute symptoms are not uncommon after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with pre-Omicron variants. How the Omicron variant and coronavirus disease 2019 (COVID-19) booster vaccination influence the risk of postacute symptoms is less clear. We analyzed data from a nationwide Danish questionnaire study, EFTER-COVID, comprising 36 109 individuals aged ≥15 years who were tested between July 2021 and January 2022, to evaluate the associations of the Omicron variant and COVID-19 booster vaccination with postacute symptoms and new-onset general health problems 4 months after infection with SARS-CoV-2. Risk differences (RDs) were estimated by comparing Omicron cases with controls, comparing Omicron cases with Delta cases, and comparing Omicron cases vaccinated with 3 doses with those vaccinated with 2 doses, adjusting for age, sex, body mass index, self-reported chronic diseases, Charlson comorbidity index, health-care occupation, and vaccination status. Four months after testing for SARS-CoV-2 during the Omicron period, cases experienced substantial postacute symptoms and new-onset health problems in comparison with controls; the largest RD was observed for memory issues (RD = 7.4%; 95% CI, 6.4-8.3). However, risks were generally lower than those in the Delta period, particularly for dysosmia (RD = –15.0%; 95% CI, −17.0 to −13.2) and dysgeusia (RD = –11.2%; 95% CI, −13.2 to −9.5). Booster vaccination was associated with fewer postacute symptoms and new-onset health problems 4 months after Omicron infection as compared with 2 doses of COVID-19 vaccine.
Inconsistency in UK Biobank Event Definitions From Different Data Sources and Its Impact on Bias and Generalizability: A Case Study of Venous Thromboembolism
Authors: Bassett Emily , Broadbent James , Gill Dipender , Burgess Stephen , Mason Amy M 
Published: November 2023

Abstract
The UK Biobank study contains several sources of diagnostic data, including hospital inpatient data and data on self-reported conditions for approximately 500,000 participants and primary-care data for approximately 177,000 participants (35%). Epidemiologic investigations require a primary disease definition, but whether to combine data sources to maximize statistical power or focus on only 1 source to ensure a consistent outcome is not clear. The consistency of disease definitions was investigated for venous thromboembolism (VTE) by evaluating overlap when defining cases from 3 sources: hospital inpatient data, primary-care reports, and self-reported questionnaires. VTE cases showed little overlap between data sources, with only 6% of reported events for persons with primary-care data being identified by all 3 sources (hospital, primary-care, and self-reports), while 71% appeared in only 1 source. Deep vein thrombosis–only events represented 68% of self-reported VTE cases and 36% of hospital-reported VTE cases, while pulmonary embolism–only events represented 20% of self-reported VTE cases and 50% of hospital-reported VTE cases. Additionally, different distributions of sociodemographic characteristics were observed; for example, patients in 46% of hospital-reported VTE cases were female, compared with 58% of self-reported VTE cases. These results illustrate how seemingly neutral decisions taken to improve data quality can affect the representativeness of a data set.
Reduction of alcohol use and increase in psychological flexibility after a naturalistic psychedelic experience: a retrospective survey
Authors: Kervadec Ewen , Fauvel Baptiste , Strika-Bruneau Lana , Amirouche Ammar , Verroust Vincent , Piolino Pascale , Romeo Bruno , Benyamina Amine 
Published: November 2023

Abstract

Introduction
Alcohol use can be significantly associated with negative social, professional, and health outcomes. Even more so, alcohol use disorder (AUD) is a critical public health issue and major avoidable risk factor. This study aimed to examine the effect of a naturalistic psychedelic experience on alcohol use and related measures.

Methods
A retrospective online survey was conducted on 160 individuals who reported a psychedelic experience and a concomitant drinking habit but did not necessarily have an AUD. Demographic data, characteristics of the psychedelic experience, and changes in alcohol consumption and psychological flexibility were surveyed. Results: The mean number of drinking days per week and AUDIT scores significantly decreased after the psychedelic experience (P &lt; .001). Subjects who quit or reduced drinking had a more severe AUD (P &lt; .01) and lower psychological flexibility (P = .003) before the psychedelic session. Alcohol use reduction was significantly associated with the intensity of the mystical experience (P = .03). Psychological flexibility increased more in participants who reduced their alcohol use (P &lt; .001), and the change in psychological flexibility was one of the predictors of alcohol use improvement (P = .003). Conclusion: Our findings suggest that a naturalistic psychedelic experience could be associated with a reduction in alcohol use and dependency. Such positive health outcomes can be associated with the intensity of the mystical experience as well as an increase in psychological flexibility.
Effect of a moderate alcohol dose on physiological responses during rest and prolonged cycling
Authors: Marley Andrew , Bakali Marianna , Simpson Charlie 
Published: November 2023

Abstract
Aim: We examined the acute effects of a moderate alcohol dose (48 g) ingested before prolonged cycling on acute physiological responses in eight healthy males (mean ± SD; 23 ± 2 years; 1.77 ± 0.04 m; 75.8 ± 4.1 kg). Methods: In a randomized order, euhydrated participants completed two experimental sessions with the sequence of 150-min seated at rest, 90-min of cycling at 50% of the maximal rate of oxygen consumption ($\dot{\textrm V}\textrm O$2max), 120-min seated at rest. Participants drank 250 mL of flavored squash with or without alcohol (vodka; ~16 g) at 10, 40, and 70 min of the initial resting phase, giving a cumulative fluid intake of 750 mL with 48 g of alcohol. Heart rate, blood glucose, breath alcohol concentration, and respiratory gasses were recorded throughout the entire trial with cumulative urine volume recorded during both rest phases. Results: Total carbohydrate (control = 115 ± 19 g: alcohol = 119 ± 21 g; P = 0.303) and lipid (control = 17 ± 4 g: alcohol = 20 ± 7 g; P = 0.169) oxidation was similar between conditions. Average heart rate was 7% higher in the alcohol condition (control = 111 ± 12 bpm; alcohol = 119 ± 11 bpm; P = 0.003). Blood glucose concentrations were similar between conditions during (P = 0.782) and after exercise (P = 0.247). Urine output was initially increased between conditions following alcohol ingestion before diminishing (P &lt; 0.001) with no difference in total cumulative urine output (P = 0.331). Conclusion: Consuming an alcoholic drink containing 48 g of alcohol in the hour before moderate intensity sub-maximal aerobic exercise led to detectable increases in heart rate and rate of urine production with no effect on substrate use.
link-ancestors: fast simulation of local ancestry with tree sequence software
Authors: Tsambos Georgia , Kelleher Jerome , Ralph Peter , Leslie Stephen , Vukcevic Damjan 
Published: November 2023

Abstract

Summary
It is challenging to simulate realistic tracts of genetic ancestry on a scale suitable for simulation-based inference. We present an algorithm that enables this information to be extracted efficiently from tree sequences produced by simulations run with msprime and SLiM.

Availability and implementation
A C-based implementation of the link-ancestors algorithm is in tskit (https://tskit.dev/tskit/docs/stable/). We also provide a user-friendly wrapper for link-ancestors in tspop, a Python-based utility package.
The interaction effects of age, APOE and common environmental risk factors on human brain structure
Authors: Chen Jie , Li Tengfei , Zhao Bingxin , Chen Hui , Yuan Changzheng , Garden Gwenn A , Wu Guorong , Zhu Hongtu 
Published: November 2023

Abstract
Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44–81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.
Relationship between false lumen morphology and entry tear in acute type A aortic dissection
Authors: Furui Masato , Uesugi Noriko , Matsumura Hitoshi , Hayashida Yoshio , Kuwahara Go , Fujii Mitsuru , Shimizu Masayuki , Morita Yuichi , Ito Chihaya , Hayama Masato , Wada Hideichi 
Published: November 2023

Abstract

OBJECTIVES
This study aimed to investigate the relationship between false lumen morphology and the size, aortic segment and position of the entry tear for acute type A aortic dissection.

METHODS
The records of patients who underwent emergency operation for acute type A aortic dissection in our institution between April 2011 and May 2022 were examined. Data regarding size, location and position of the entry tear and preoperative computed tomography findings were reviewed. The relationship of these variables with false lumen morphology was examined and retrospectively compared according to tear size.

RESULTS
Of 243 cases, characteristics of the entry tear, visualized during surgery, were confirmed in 134 cases (age = 70.9 ± 12.6 years, male = 45.5%). Tear sizes at different aortic segments were not significantly different (P = 0.376). Tears posterior to the lesser curvature were significantly smaller than those anterior to the greater curvature (P = 0.004). A thrombosed false lumen was associated with a significantly smaller tear size and position on the posterior to the lesser curvature side in aortic cross-section (all P &lt; 0.001). Multivariate analysis showed that tear size, the presence of re-entry and tear position anterior to the greater curvature were independent predictors of a patent false lumen.

CONCLUSIONS
In acute type A aortic dissection, larger tear size, the presence of re-entry and tear position anterior to the greater curvature are risk factors for a patent false lumen. Although the results of this study are valid only for patients in whom intimal tears were detected during aortic surgery, this trend may provide information for pathophysiology of the disease.
Proteomic Analysis of the Senescence-Associated Secretory Phenotype: GDF-15, IGFBP-2, and Cystatin-C Are Associated With Multiple Aging Traits
Authors: Evans Daniel S , Young Danielle , Tanaka Toshiko , Basisty Nathan , Bandinelli Stefania , Ferrucci Luigi , Campisi Judith , Schilling Birgit 
Published: November 2023

Abstract
Cellular senescence, a hallmark of aging, results in a senescence-associated secretory phenotype (SASP) with an increased production of proinflammatory cytokines, growth factors, and proteases. Evidence from nonhuman models demonstrates that SASP contributes to tissue dysfunction and pathological effects of aging. However, there are relatively few human studies on the relationship between SASP and aging-related health outcomes. Proteins from the SASP Atlas were measured in plasma using aptamer-based proteomics (SomaLogic). Regression models were used to identify SASP protein associations with aging-related traits representing multiple aspects of physiology in 1 201 participants from 2 human cohort studies (BLSA/GESTALT and InCHIANTI). Traits examined were fasting glucose, C-reactive protein, interleukin-6, alkaline phosphatase, blood urea nitrogen, albumin, red blood cell distribution width, waist circumference, systolic and diastolic blood pressure, gait speed, and grip strength. Study results were combined with a fixed-effect inverse-variance weighted meta-analysis. In the meta-analysis, 28 of 77 SASP proteins were significantly associated with age. Of the 28 age-associated SASP proteins, 18 were significantly associated with 1 or more clinical traits, and 7 SASP proteins were significantly associated with 3 or more traits. Growth/differentiation factor 15, Insulin-like growth factor-binding protein 2, and Cystatin-C showed significant associations with inflammatory markers and measures of physical function (grip strength or gait speed). These results support the relevance of SASP proteins to human aging, identify specific traits that are potentially affected by SASP, and prioritize specific SASP proteins for their utility as biomarkers of human aging.