bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploration of Urban Ecological Recreation Space——Taking Nanjing Commercial Buildings as an Example
Authors: jiang xintong 
Published: June 2023

Abstract
As urbanization accelerates and the built-up area continues to expand, people's opportunities for outdoor activities are decreasing. In addition, the pressure of survival brought on by epidemic prevention and control is forcing more and more people to choose outdoor recreational facilities to get close to nature and relax. Most people believe that low density should correspond to comfortable space, while high density corresponds to oppression and compactness. However, high-density space often brings a stronger sense of vitality, convenient living conditions, efficient and resourceful centralization, and rich living levels. I am also transforming the existing urban passive space into active space, starting with the physical and psychological needs of residents and intervening new forces into the existing urban space or architectural space to find a super-density symbiotic recreation space between people and buildings and buildings and architecture. The main content of this design is as follows: first, review the existing literature and related urban open space planning; synthesize and analyze the existing urban open space structure and typical open space functional area research results; and make an objective analysis. Secondly, to explore the recreation demand of urban commercial buildings, to explore the ideal urban recreation space structure pattern and composition elements, and to reflect on their own design. Then, we analyze the hierarchical structure of ecological open space in commercial buildings through the distribution of open space in Nanjing and propose the overall design idea of ecological open space. Finally, we summarize the shortcomings and outlook.
The friction-reduction and anti-wear mechanism of AISI321 stainless steel treated by surface nanocrystallization assisted sulfurization
Authors: ding lifen , Li You 
Published: June 2023

Abstract
Through compound treatment of surface nanocrystallization and low-temperature ion sulfurization, the compound-modified layer (nanocrystalline/FeS film) with excellent friction-reduction and anti-wear properties was fabricated on the surface of AISI321 stainless steel. A comparative study is conducted on the element distribution, microstructure, and vacuum tribology properties (1 × 10‒4 Pa) of compound-treated samples, single-related samples (surface nanocrystallization or low-temperature ion sulfurization), and original substrate samples. The nanocrystallization treatment formed the high hardness, high activity nanocrystalline structure on the surface of AISI321, which results in significantly refined microstructure, increased thickness and concentration of S element in the compound-sulfurized layer compared to the single-sulfurized layer on the substrate. Tribological tests reveal that both the original AISI321 substrate and the single-sulfurizing treated samples are subject to severe abrasion. Single nanocrystallization treatment can improve the wear resistance of AISI321, while the compound treatment can obviously improve the comprehensive tribological properties with milder wear and lower friction of coefficient. The good tribological properties of the compound-modified layer are related to the enhancement of substrate hardness and the increase of the thickness, density, and homogeneity of the sulfurized layer. Furthermore, a physical model is developed for the vacuum tribological behavior of the samples after different treatments. This model provides a reference for revealing the tribological mechanism of the compound-modified layer treated by surface nanocrystallization assisted chemical heat treatment.
Behavioral and metabolic and effects of ABCG4 KO in the APPswe,Ind (J9) mouse model of Alzheimer’s disease
Authors: Fong Vincent , Kanuri Babunageswararao , Traubert Owen , Lui Min , Patel Shailendra B. 
Published: June 2023

Abstract

The pathogenesis of Alzheimer’s disease (AD) is complex and involves an imbalance between production and clearance of amyloid-ß peptides (Aß), resulting in accumulation of Aß in senile plaques. Hypercholesterolemia is a major risk factor for developing AD, with cholesterol shown to accumulate in senile plaques and increase production of Aß. ABCG4 is a member of the ATP-binding cassette transporters predominantly expressed in the CNS, and has been suggested to play a role in cholesterol and Aß efflux from the brain. In this study, we bred Abcg4 knockout (KO) with the APPSwe,Ind (J9) mouse model of AD to test the hypothesis that loss of Abcg4 would exacerbate the AD phenotype. Unexpectedly, no differences were observed in Novel object recognition (NOR) and Novel object placement (NOP) behavioral tests, or on histologic examinations of brain tissues for senile plaque numbers. Furthermore, clearance of radiolabeled Aß from the brains did not differ between Abcg4 KO and control mice. Metabolic testing by indirect calorimetry, glucose tolerance test (GTT) and insulin tolerance test (ITT), were also mostly similar between groups with only a few mild metabolic differences noted. Overall these data suggest that the loss of ABCG4 did not exacerbate the AD phenotype.
A Smart IDS in IoT System to Detect Zero-Day Intrusions Using Automated Signature Update
Authors: Mahmood Mutahher , Shafi Qaisar 
Published: June 2023

Abstract
Protecting industry infrastructure from cyber-attacks is the necessity of time. We heard of zero-day attacks, and now every industry is facing them. The death of the Perimeter term in cybersecurity defines that we can't make our infrastructure 100\% secure. We are using Firewalls, Anti-viruses, IPS (Intrusion Prevention Systems) and IDS (Intrusion Detection Systems), etc., to make industry perimeter secure. But we are still facing zero-day attacks, and we can't prevent them. There is a need for smart IDS that can detect intrusion in networks and systems, and prevent them as well. Some previous work is already been done to detect zero-day attacks in networks, and they are using different approaches based on anomaly detection using Machine Learning algorithms. Machine Learning provides many benefits including and not limited to zero-day attacks by analyzing previously learned and trained datasets. But the only problem that remains is the accuracy of ML algorithms. Our approach is using old-fashioned signature-based detection, which guarantees 100\% accuracy but is limited to zero-day attacks. To deal with zero-day attacks, we're using our approach with the ML algorithms and a multi-classifier to detect zero-day intrusion in a network and update their signatures automatically. Our approach will guarantee prevention from known threats using signatures and more accuracy in the detection of zero-day attacks by using ML algorithms with a multi-classifier.
Unveiling Spatial Associations Between COVID-19 Severe Health Index, Racial/Ethnic Composition, And Community Factors
Authors: juboori Ruaa Al , Subramaniam Divya S. , Hinyard Leslie , Sandoval Ness 
Published: June 2023

Abstract

Limited efforts have been made to incorporate various predisposing factors, including racial/ethnic composition, into prediction models exploring the spatial distribution of COVID-19 Severe Health Risk Index (SHRI). This study examines county-level data from 3,107 US counties, utilizing publicly available datasets. Spatial and non-spatial regression models were constructed, adjusting for rurality, socio-demographic factors, physical health, smoking, sleep, health insurance, healthcare providers, hospitalizations, and environmental risks. Findings reveal spatial models effectively explain geospatial disparities of COVID-19 SHRI. White, Hispanic, and other racial/ethnic majority counties exhibit lower burdens compared to majority Black counties. Older population, lower income, smoking, insufficient sleep, and preventable hospitalizations are associated with higher burdens. Counties with better health access and internet coverage experience lower burdens. This study provides insights into at-risk populations, guiding resource allocation. Racial/ethnic inequalities play a significant role in driving disparities. Addressing these factors reduces health outcome disparities. This work establishes a baseline typology for exploring social, health, economic, and political factors contributing to different health outcomes.
Clinical characteristics and prediction of neurodevelopmental outcomes of infants with ventriculomegaly in utero: A prospective observational study
Authors: Zhou Faliang , Li Chen , Huo Yixuan , Sun Guoyu , Lin Yan , Chen Junya , Hou Xinlin , Liu Lili 
Published: June 2023

Abstract
Background: To evaluate the clinical features and neurodevelopmental outcomes of infants with fetal ventriculomegaly (VM) and determine prognostic factors.
Methods: We studied 167 VM fetuses, assessed the perinatal outcome and the neurodevelopmental outcome at age of 18 months by Bayley Scales of Infant Development. We assessed the association of clinical features and characteristics of VM with Mental Development Index (MDI) and Psychomotor Development Index (PDI).
Results: Among the 167 VM fetuses, 23 underwent induced abortion or were stillborn, and 130 completed a thorough VM evaluation and postnatal follow-up. Of 130 cases, 47% (61/130) showed isolated VM and 53% (69/130) non-isolated VM. Non-isolated VM cases had a higher rate of bilateral (52% vs.25%), severe (12% vs.2%), and progressive (16% vs.10%) VM compared with isolated VM. Neurodevelopmental outcome differed between the isolated and non-isolated VM groups, and the mild and severe VM groups. Progressive VM cases had lower PDI (p=0.006). Anomalies in the CNS, urogenital system, and gastrointestinal tract were associated with lower MDI (ORCNS 4.19,95%CI 1.56-11.28;ORUrogenity 7.00,95%CI 1.81-27.07) or PDI (ORCNS 4.61,95%CI 1.79-11.85;ORGastrointestine 7.88,95%CI 1.24-50.18). Cases with lower MDI or PDI were more likely to have multiple anomalies (both CNS and non-CNS anomalies) (MDI: OR 5.78,95%CI 1.57-21.30,p=0.004, PDI: OR 7.20,95%CI 1.98-26.24,p=0.001).
Conclusions: The neurodevelopmental outcomes in a fetus with VM were poor when VM was severe or progressive VM, or accompanied by structural anomalies. Cerebral, urogenital, and gastrointestinal structural anomalies contribute to poor neurodevelopmental outcomes.
Mental Health and the Youth Athlete: An Analysis of the HeartBytes Database
Authors: Vyas Arthraj J. , Sun Mengyi , Farber Jason , Dikdan Sean J. , Ruge Max , Corgan Sondra , Johnson Drew , Shipon David 
Published: June 2023

Abstract
Background
There is a high rate of mental health conditions among the youth athlete population; however, there is limited information about the impact mental health disorders can have on their overall health and athletic performance.
Methods
Data was collected by Simon’s Heart, a nonprofit organization that coordinates pre-participation examinations (PPE) for adolescents. Multivariable logistic regression adjusting for age, gender, race, BMI, asthma, anemia, and participation in sports was performed to assess the relationship between mental health disorders and each outcome.
Results
The HeartBytes dataset is composed of screening data from 7425 patients ranging from 12 to 20 years old. We identified 565 patients (7.6%) diagnosed with ADHD and 370 patients (5.0%) diagnosed with anxiety/depression. Screened participants without a diagnosis of ADHD, anxiety, or depression were significantly more likely to play sports compared to those with these conditions (75.4% vs 59.4%, P < 0.001 for ADHD; 89.4% vs 72.4%, P < 0.001 for anxiety/depression). Those with anxiety/depression not on an antidepressant (OR: 2.09, CI: 1.31–3.19, P < 0.01), but not those on an antidepressant (OR: 1.87, CI: 0.96–3.33, P = 0.05), were more likely to report chest pain or dyspnea with exercise. Those with ADHD not on a stimulant (aOR 1.91, CI 1.22–2.89, p < 0.01), but not those on a stimulant (aOR 1.40, CI 0.82–2.24, p = 0.19) were more likely to report palpitations. ECG abnormalities were not more prevalent regardless of anxiety/depression, ADHD, or medical therapy with an antidepressant or a stimulant.
Conclusion
Young athletes with anxiety/depression were less likely to participate in sports than healthy individuals. This may be due to deterrence as a result of the symptoms, such as dyspnea or chest pain, they experience during exercise. However, those taking antidepressants had fewer symptoms during exercise. Given that exercise has been shown to improve depression/anxiety, increasing the rate of antidepressant use may lead to less symptoms, more exercise, and an overall improvement in the mental health conditions in this population.
UAV based smart grazing：A prototype and test bed for space-air- ground integrated IoT networks in Qinghai-Tibet plateau
Authors: Li Ji , Ling Min , Huang Shijie , Dong Yugang , Fu Bin , Wang Kun , Gou Biao , Wu Yanshuang 
Published: June 2023

Abstract
Smart grazing is a relatively difficult field of digital agriculture. Restricted by the geographical conditions of pastures, poor network infrastructure and low economic output, relevant applications have been difficult to achieve. In this paper, we propose the SAG-GIoT system based on the background of yak grazing production in the Qinghai Tibet Plateau, and define three intelligent grazing management application scenarios: daily grazing supervision, UAV grazing and searching for yaks. To this end, we have designed the three-tier technical architecture of SAG-GIoT, and developed collar, base station and grazing management system. We designed the all-terrain network service scheme with BDS-BSS and SBSs, and verified the daily grazing supervision test in long-term. UAV grazing test was carried out in pasture, and a flexible communication networking was realized through the UAV-BS. With the guidance of UAV searching and APP positioning, taking HBSs in hand, we quickly and accurately find the lost yaks. SAG-GIoT system is characterized as low cost, flexible deployment and global service, and has broad application prospects.
Using physiological and morphological methods for comparison: is mixed Phyllostachys edulis and Carya illinoinensis a reasonable mixed forest model?
Authors: Lu Qifan , Zhang Xu , Yu Qunfen , Liu Shenghui , Zhou Zhou , Wang Anke , Du Xuhua , Wang Zijie , Zhong Hao , Ning Yilin , Lan Lan , Bi Yufang 
Published: June 2023

Abstract

The purpose of this study was to investigate whether thePhyllostachys edulis-Carya illinoinensisco-plantation is a feasible forest model. Two treatments and one control were evaluated. The control was a low-densityC. illinoinensisforest (CK), and the treatments were a high-densityC. illinoinensis forest(DF), and aC. illinoinensis-P. edulisco-plantation forest (MF). Gas exchange and chlorophyll fluorescence parameters, leaf physiology, macromorphology, and anatomical structure ofC. illinoinensiswere measured and principal component analysis (PCA) was used to evaluate treatment effects. The highest net photosynthetic rate (Pn), which was 13.72 .µmol CO2·m-2·s-1, was recorded forC. illinoinensisunder the CK treatment, while the corresponding values for MF and DF treatments were 8.98 and 5.25 µmol CO2·m-2·s-1, respectively. The JIP test revealed that plastoquinone libraries were inhibited under both MF and DF, particularly in the latter. Compared with CK, antioxidant substances in MF and DF leaves increased to a certain extent, again, particularly in the latter. Leaf macromorphology and anatomical structures under the different treatments also changed to acclimated to different environments. The leaf area of MF became lower, and the vascular tissue of DF petiole became larger. Finally, based on the main data, the order of the PCA scores was CK > MF > DF. The results indicated that both co-plantation and high-density planting caused both interspecific and intraspecific competition. Photosynthesis was inhibited inC. illinoinensisto varying degrees under both cultivation models. Nonetheless, the stress levels inC. illinoinensiswere significantly lower under the co-plantation forest than under high-density planting. These findings indicate thatC. illinoinensisgrowth was not severely inhibited by co-plantation withP. edulis, as it still developed well. Hence, co-plantation ofP. edulisandC. illinoinensisis a promising mixed-forest model.
Characterization of Dropouts in Crowdsourcing Markets
Authors: Bhattacharya Bijoly Saha , Biswas Arindam , Bhattacharyya Malay 
Published: June 2023

Abstract
There have been limited attempts toward the characterization of dropouts in crowdsourcing markets arguably due to the disagreement in defining a dropout. In this paper, we evaluate three different approaches of designating a crowd dropout and demonstrate that a prolonged interruption is enough to characterize a dropout. Our analyses on the crowdsourcing platform Flightfox reflect that the persistence of crowd workers depends on the remuneration and nature of task in addition to the previously reported success rate. Based on this, we show that it is possible to predict the dropouts in a crowdsourcing market with a very high (more than 90%) accuracy, as demonstrated both on cross-validation and independent test sets, with appropriate selection of features. A comprehensive analysis across different machine learning algorithms and feature selection approaches demonstrate that a graph-based robust feature selection performs the best with a boot-strap aggregation approach. It also highlights the importance of having effective communication among the crowd workers who tend to be dropout, a hitherto untold fact. The overall investigation not only provides new perspectives toward designating a dropout but also ensures their effective recognition. Moreover, it highlights the significance of incorporating feedback mechanism in crowdsourcing environments.
The tyrosine kinase inhibitor Dasatinib reduces cardiac steatosis and fibrosis in obese, type 2 diabetic mice
Authors: Gu Yue , Avolio Elisa , Alvino Valeria V , Thomas Anita C , Herman Andrew , Miller Poppy J , Sullivan Niall , Faulkner Ashton , Madeddu Paolo 
Published: June 2023

Abstract
Background Cardiac steatosis is an early yet overlooked feature of diabetic cardiomyopathy. There is no available therapy to treat this condition. Tyrosine kinase inhibitors (TKIs), clinically used as an anti-cancer treatment, influence glucose and lipid metabolism, leading to improved glycemic control and allowing insulin discontinuation in cancer patients with diabetes mellitus. The present study aimed to determine the therapeutic effect of the second-generation TKI Dasatinib on lipid accumulation and cardiac function in obese, type 2 diabetic mice. We also assessed if the drug impacts extra-cardiac fat tissue depots.Methods Two studies on 21-week-old male obese leptin receptor mutant BKS.Cg-+Leprdb/+Leprdb/OlaHsd (db/db) mice compared the effect of Dasatinib (5 mg/kg) and vehicle (10% DMSO + 90% PEG-300) given via gavage once every three days for a week or once every week for four weeks. Functional and volumetric indices were studied using echocardiography. Post-mortem analyses included the assessment of fat deposits and fibrosis using histology, and senescence using immunohistochemistry and flow cytometry. The anti-adipogenic action of Dasatinib was investigated on human bone marrow (BM)-derived mesenchymal stem cells (MSCs). Two-tailed independent samples t-tests and one-way analysis of variance were used as appropriate.Results Dasatinib reduced steatosis and fibrosis in the heart of diabetic mice. The drug also reduced BM adiposity but did not affect other fat depots. These structural changes were associated with an improvement in the diastolic index E/A. Moreover, Dasatinib-treated mice had lower levels of p16 in the heart and BM, and lower circulating PAI-1, compared with vehicle-treated controls, suggesting an inhibitory impact of the drug on the senescence signalling pathway. In vitro, Dasatinib inhibited human BM-MSC viability and adipogenesis commitment.Conclusions Our findings suggest that Dasatinib opposes heart and BM adiposity and cardiac fibrosis. In the heart, this was associated with favourable functional consequences, namely improvement in an index of diastolic function. Repurposing TKI for cardiac benefit could address the unmet need of diabetic cardiac steatosis.
Machine Learning in Heart Failure Research: A Bibliometric Analysis from 2003 to 2023
Authors: Yu Deshuai , Yang Shuangjie , Wang Ruiting , Wang Kai , Han Wenbo , Wu Huanlin , Wang Wei , Wang Xian 
Published: June 2023

Abstract
Background
Heart failure (HF) is a global public health problem with high morbidity and mortality. While machine learning (ML) has been perceived as a promising tool for HF research, a bibliometric analysis of this application is still lacking. This study aims to analyze the relevant papers from 2003 to 2023 and provide a comprehensive overview of this field in a visual way.
Methods
We systematically searched Web of Science Core Collection, PubMed, and preprint servers (arXiv, BioRxiv, and MedRxiv) to identify records from 2003 to 2023 on ML in HF research. After manual data cleansing, a Python approach based on the regular expression matching algorithm was used to automate text annotations, while three bibliometric analysis tools (CiteSpace, VOSviewer, and Bibliometrix) were used for the visualization of research trends, collaboration networks, and research hotspots.
Results
We analyzed 6,115 records (including 1,797 published papers) and observed a steady increase in annual publication rates since 2015, with a significant uptick after 2020. We identified 23 core journals in the field according to Bradford's law, and presented the top 10 journals with the highest citations, h-index, g-index, or m-index. The United States was the most productive country, followed by China and the United Kingdom. The most prolific institutions were Harvard Medical School and Mayo Clinic. Using text annotations, we identified 1,257 ML-related original HF research. In these studies, the main data modalities were ultrasound, electronic health records, and electrocardiograms. The most frequently applied ML methods were neural networks, followed by linear models and ensembles. The most common clinical goals were diagnosis, prediction, and classification. The main research topics included the classification of HF, AI-assisted medical diagnostic technologies, HF-related clinical prediction models, and HF-related bioinformatics research.
Conclusions
This bibliometric analysis revealed a significant growth in the application of ML in HF research over the past two decades. The current research landscape encompasses a wide range of ML techniques and applications, focusing on improving diagnosis, prognosis, classification, and precision treatment for HF patients.