Digital Commons Network^™

Experimental Study On Effects Of Physical Exercise Function Training On Physical Health Of Primary School Students, Mingzhuo Yan, Zhihua Yin

International Journal of Physical Activity and Health

Recently, the physical health problems of children in China have attracted extensive attention. The education department has issued a notice on further strengthening the physical health management of primary and secondary schools. Many studies have shown that physical exercise function training has unique advantages in promoting the healthy development of students' physique and is unaffected by venues or weather. This study aims to explore and verify the intervention effect of physical exercise function training on students’ physical health indicators, including physical shape, function, and quality. It also intends to practically explore the improvement of students' physical health status and expand …

Quality Of Community Sports Service Distribution And Behavior Intention Of The Elderly, Yani Cui, Hongying Wang

International Journal of Physical Activity and Health

The purpose of this study was to explore the quality of community sports distribution service through the evaluation and satisfaction of the elderly in Yangpu District of Shanghai on the quality of community sports service and explore the relationship between the quality of community sports distribution service, satisfaction, and behavioral intention. Data were collected by using surveys and analyzed using mathematical statistics. The survey refers to SERVPERF model to design a six-dimension, intermediary variable satisfaction and behavioral intention five-point scale for the service quality of community sports distribution. The sample size was 261. SPSS25.0 was used to conduct data analysis. …

Influence Of Physical Activity On Heart Rate Variability In Physically Inactive Adults: A Meta-Analysis, Lingsong Kong, Qin Yang

International Journal of Physical Activity and Health

This meta-analysis aimed to examine the influences of physical activity (PA) interventions on heart rate variability (HRV) among healthy but physically inactive adults aged 18 to 65 years old. PubMed, SPORTDiscus and Web of Science online databases were searched in September 2021. The eligibility criteria were: (1) peer-reviewed articles in English; (2) randomized controlled trials; (3) healthy but physically inactive adults aged 18 to 65 years; (4) at least two-week PA intervention; (5) available frequency domain result. The data were extracted to a pre-designed form. The primary outcome of this study was the frequency domain of HRV, which included natural …

Developing Sustainable Snow Sports Education Programs For Adolescent Participation, Zhaofei Chen, Wei Zuo, Hongwei Guan

International Journal of Physical Activity and Health

Following Beijing’s winning bid to host the 2022 Winter Olympic Games, winter sports have ushered in a great development opportunity for adolescents in China. Beijing initiated the Ice and Snow Sports on Campus Program in 2016, however, one of the challenges is that the lack of quality snow sports instructors and access to ski resorts is limiting sustainable programs. Greek Peak Ski Resort, located in upstate NY, has a successful history of running snow sport educational programs that Beijing may be able to learn from. The purpose of this study was to assess and compare the Ice and Snow Sports …

The Relationship Between Fundamental Motor Skills And Physical Fitness In Children Aged 7-12 Years, Caifang Wu, Xiaozan Wang, Qinping Xu, Lingsong Kong

International Journal of Physical Activity and Health

The purpose of this study was to examine the relationship between fundamental motor skills (FMS) and physical fitness (PF) in children aged 7-12 years. The participants were 217 children (50.7% female) from a primary school in Shanghai. The FMS was assessed using Chinese version Test of Gross Motor Development–3 edition (CTGMD-3), which includes 6 locomotor skills and 7 ball skills. PF was measured following China’s national physical health standards for students, which includes BMI, vital capacity, sit and reach, 50m sprint, one-minute rope jumping, one-minute sit-ups and 50m * 8 shuttle run. The weighted score of the 7 tests was …

An Analysis Of Machine Learning Based Cybersecurity Breaches Handling Frameworks, Young B. Choi

KAUPA Letters

As diverse groups of security breaches are occurring in business enterprises, corresponding measures to protect them are necessary. In this paper, AI Machine Learning based security breaches handling concept is surveyed and an XAI(Explainable Artificial Intelligence) oriented Machine Learning based security breaches handling framework is explained.

Kaupa Letters: Volume 10, Issue 3, Korean American University Professors Association

KAUPA Letters

No abstract provided.

2023 February 1 - From My Notepads Newsletter, Office Of The President, East Tennessee State University, Brian Noland

From My Notepads: A Newsletter from President Brian Noland

No abstract provided.

Attitudes, Clinical Practices, And Perceived Advocacy Needs Of Professionals With Interests In Personality Disorders, William D. Ellison, S. Huprich, A. Behn, M. Goodman, S. Kerr, K. N. Levy, S. M. Nelson, C. Sharp, The Board Of Directors Of The International Society For The Study Of Personality Disorders

Psychology Faculty Research

Experts in personality disorders (PDs) generally prefer dimensional diagnostic systems to categorical ones, but less is known about experts’ attitudes toward personality pathology diagnoses in adolescents, and little is known about public health shortfalls and advocacy needs and how these might differ geographically. To fill these gaps, the International Society for the Study of Personality Disorders surveyed 248 professionals with interests in PDs about their attitudes toward different diagnostic systems for adults and adolescents, their PD-related clinical practices, and perceived advocacy needs in their area. Results suggested that dimensional diagnostic systems are preferable to categorical and that skepticism about personality …

Direct Air Capture, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about direct air capture (DAC), a carbon capture technology that will reduce and remove carbon dioxide from the atmosphere. DAC supports environmental sustainability, North Dakota’s economy, and boosts the energy industry.

Seismic Azimuthal Anisotropy Beneath A Fast Moving Ancient Continent: Constraints From Shear Wave Splitting Analysis In Australia, Kailun Ba, Stephen S. Gao, Jianguo Song, Kelly H. Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Seismic Azimuthal Anisotropy Beneath Australia is Investigated using Splitting of the Teleseismic PKS, SKKS, and SKS Phases to Delineate Asthenospheric Flow and Lithospheric Deformation Beneath One of the Oldest and Fast-Moving Continents on Earth. in Total 511 Pairs of High-Quality Splitting Parameters Were Observed at 116 Seismic Stations. Unlike Other Stable Continental Areas in Africa, East Asia, and North America, Where Spatially Consistent Splitting Parameters Dominate, the Fast Orientations and Splitting Times Observed in Australia Show a Complex Pattern, with a Slightly Smaller Than Normal Average Splitting Time of 0.85 ± 0.33 S. on the North Australian Craton, the Fast …

Sex Differences In Stress-Induced (Takotsubo) Cardiomyopathy, Waddah Maskoun, Bilal Alqam, Fuad Habash, Zaid Gheith, Stephen G. Sawada, Srikanth Vallurupalli

Cardiology Articles

Background: Takotsubo cardiomyopathy (TC) affects predominantly women. Prior studies have suggested that men might have worse short-term outcomes, but limited data are available regarding long-term outcomes. We hypothesized that men, compared to women, with TC have worse short- and long-term outcomes.

Methods: A retrospective study of patients diagnosed with TC between 2005 and 2018 in the Veteran Affairs system was performed. Primary outcomes were in-hospital death, 30-day risk of stroke, death, and long-term mortality.

Results: A total of 641 patients were included (444 men [69%]; 197 women [31%]). Men had a higher median age (65 vs 60 years; P < 0.001), and women were more likely to present with chest pain (68.7% vs 44.1%; P < 0.001). Physical triggers were more common in men (68.7% vs 44.1%, P < 0.001). Men had a higher in-hospital mortality rate (8.1% vs 1%; P < 0.001). On multivariable regression analysis, female sex was an independent predictor for improved in-hospital mortality, compared to men (odds ratio 0.25, 95% confidence interval 0.06-1.10; P = 0.04). On 30-day follow-up, no difference occurred in a combined outcome of stroke and death (3.9% vs 1.5%; P = 0.12). On long-term follow-up (3.7 ± 3.1 years), female sex was identified as an independent predictor of lower mortality (hazard ratio 0.71, 95% CI 0.51-0.97; P = 0.032). Women were more likely to have TC recurrence (3.6% vs 1.1%; P = 0.04).

Conclusions: …

Sex Differences In Stress-Induced (Takotsubo) Cardiomyopathy, Waddah Maskoun, Bilal Alqam, Fuad Habash, Zaid Gheith, Stephen G. Sawada, Srikanth Vallurupalli

Cardiology Articles

BACKGROUND: Takotsubo cardiomyopathy (TC) affects predominantly women. Prior studies have suggested that men might have worse short-term outcomes, but limited data are available regarding long-term outcomes. We hypothesized that men, compared to women, with TC have worse short- and long-term outcomes.

METHODS: A retrospective study of patients diagnosed with TC between 2005 and 2018 in the Veteran Affairs system was performed. Primary outcomes were in-hospital death, 30-day risk of stroke, death, and long-term mortality.

RESULTS: A total of 641 patients were included (444 men [69%]; 197 women [31%]). Men had a higher median age (65 vs 60 years; P < 0.001), and women were more likely to present with chest pain (68.7% vs 44.1%; P < 0.001). Physical triggers were more common in men (68.7% vs 44.1%, P < 0.001). Men had a higher in-hospital mortality rate (8.1% vs 1%; P < 0.001). On multivariable regression analysis, female sex was an independent predictor for improved in-hospital mortality, compared to men (odds ratio 0.25, 95% confidence interval 0.06-1.10; P = 0.04). On 30-day follow-up, no difference occurred in a combined outcome of stroke and death (3.9% vs 1.5%; P = 0.12). On long-term follow-up (3.7 ± 3.1 years), female sex was identified as an independent predictor of lower mortality (hazard ratio 0.71, 95% CI 0.51-0.97; P = 0.032). Women were more likely to have TC recurrence (3.6% vs 1.1%; P = 0.04).

CONCLUSIONS: …

Quantization-Aware Interval Bound Propagation For Training Certifiably Robust Quantized Neural Networks, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, A. Thomas Henzinger, Daniela Rus

Research Collection School Of Computing and Information Systems

We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization, and certification of the quantized representation is necessary to guarantee robustness. In this work, we present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs. Inspired by advances in robust learning of non-quantized networks, our training …

Generalizing Math Word Problem Solvers Via Solution Diversification, Zhenwen Liang, Jipeng Zhang, Lei Wang, Yan Wang, Jie Shao, Xiangliang Zhang

Research Collection School Of Computing and Information Systems

Current math word problem (MWP) solvers are usually Seq2Seq models trained by the (one-problem; one-solution) pairs, each of which is made of a problem description and a solution showing reasoning flow to get the correct answer. However, one MWP problem naturally has multiple solution equations. The training of an MWP solver with (one-problem; one-solution) pairs excludes other correct solutions, and thus limits the generalizability of the MWP solver. One feasible solution to this limitation is to augment multiple solutions to a given problem. However, it is difficult to collect diverse and accurate augment solutions through human efforts. In this paper, …

Scalable And Globally Optimal Generalized L1 K-Center Clustering Via Constraint Generation In Mixed Integer Linear Programming, Aravinth Chembu, Scott Sanner, Hassan Khurran, Akshat Kumar

Research Collection School Of Computing and Information Systems

The k-center clustering algorithm, introduced over 35 years ago, is known to be robust to class imbalance prevalent in many clustering problems and has various applications such as data summarization, document clustering, and facility location determination. Unfortunately, existing k-center algorithms provide highly suboptimal solutions that can limit their practical application, reproducibility, and clustering quality. In this paper, we provide a novel scalable and globally optimal solution to a popular variant of the k-center problem known as generalized L_1 k-center clustering that uses L_1 distance and allows the selection of arbitrary vectors as cluster centers. We show that this clustering objective …

Learning Relation Prototype From Unlabeled Texts For Long-Tail Relation Extraction, Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting entity relations from texts. However, it usually suffers from the long-tail issue. The training data mainly concentrates on a few types of relations, leading to the lack of sufficient annotations for the remaining types of relations. In this paper, we propose a general approach to learn relation prototypes from unlabeled texts, to facilitate the long-tail relation extraction by transferring knowledge from the relation types with sufficient training data. We learn relation prototypes as an implicit factor between entities, which reflects the meanings of relations as well …

Learning Comprehensive Global Features In Person Re-Identification: Ensuring Discriminativeness Of More Local Regions, Jiali Xia, Jianqiang Huang, Shibao Zheng, Qin Zhou, Bernt Schiele, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Computing and Information Systems

Person re-identification (Re-ID) aims to retrieve person images from a large gallery given a query image of a person of interest. Global information and fine-grained local features are both essential for the representation. However, global embedding learned by naive classification model tends to be trapped in the most discriminative local region, leading to poor evaluation performance. To address the issue, we propose a novel baseline network that learns strong global feature termed as Comprehensive Global Embedding (CGE), ensuring more local regions of global feature maps to be discriminative. In this work, two key modules are proposed including Non-parameterized Local Classifier …

Real-Time Hierarchical Map Segmentation For Coordinating Multi-Robot Exploration, Tianze Luo, Zichen Chen, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Coordinating a team of autonomous agents to explore an environment can be done by partitioning the map of the environment into segments and allocating the segments as targets for the individual agents to visit. However, given an unknown environment, map segmentation must be conducted in a continuous and incremental manner. In this paper, we propose a novel real-time hierarchical map segmentation method for supporting multi-agent exploration of indoor environments, wherein clusters of regions of segments are formed hierarchically from randomly sampled points in the environment. Each cluster is then assigned with a cost-utility value based on the minimum cost possible …

Lightweight And Non-Invasive User Authentication On Earables, Changshuo Hu, Xiao Ma, Dong Ma, Ting Dang

Research Collection School Of Computing and Information Systems

The widespread adoption of wireless earbuds has advanced the developments in earable-based sensing in various domains like entertainment, human-computer interaction, and health monitoring. Recently, researchers have shown an increased interest in user authentication using earables. Despite the successes witnessed in acoustic probing and speech based authentication systems, this paper proposed a lightweight and non-invasive ambient sound based user authentication scheme. It employs the difference between the in-ear and out-ear sounds to estimate the individual-specific occluded ear canal transfer function (OECTF). Specifically, the {out-ear, in-ear} scaling factors at different frequency bands are captured via linear regression and treated as the OECTF …

Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

Research Collection School Of Computing and Information Systems

The graph kernel of the functional brain network is an effective method in the field of neuropsychiatric disease diagnosis like Alzheimer's Disease (AD). The traditional static brain networks cannot reflect dynamic changes of brain activities, but evolving brain networks, which are a series of brain networks over time, are able to seize such dynamic changes. As far as we know, the graph kernel method is effective for calculating the differences among networks. Therefore, it has a great potential to understand the dynamic changes of evolving brain networks, which are a series of chronological differences. However, if the conventional graph kernel …

Mirror: Mining Implicit Relationships Via Structure-Enhanced Graph Convolutional Networks, Jiaying Liu, Feng Xia, Jing Ren, Bo Xu, Guansong Pang, Lianhua Chi

Research Collection School Of Computing and Information Systems

Data explosion in the information society drives people to develop more effective ways to extract meaningful information. Extracting semantic information and relational information has emerged as a key mining primitive in a wide variety of practical applications. Existing research on relation mining has primarily focused on explicit connections and ignored underlying information, e.g., the latent entity relations. Exploring such information (defined as implicit relationships in this article) provides an opportunity to reveal connotative knowledge and potential rules. In this article, we propose a novel research topic, i.e., how to identify implicit relationships across heterogeneous networks. Specially, we first give a …

Cross-Domain Graph Anomaly Detection Via Anomaly-Aware Contrastive Alignment, Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie

Research Collection School Of Computing and Information Systems

Cross-domain graph anomaly detection (CD-GAD) describes the problem of detecting anomalous nodes in an unlabelled target graph using auxiliary, related source graphs with labelled anomalous and normal nodes. Although it presents a promising approach to address the notoriously high false positive issue in anomaly detection, little work has been done in this line of research. There are numerous domain adaptation methods in the literature, but it is difficult to adapt them for GAD due to the unknown distributions of the anomalies and the complex node relations embedded in graph data. To this end, we introduce a novel domain adaptation approach, …

Improving Automatic Melanoma Diagnosis Using Deep Learning-Based Segmentation Of Irregular Networks, Anand K. Nambisan, Akanksha Maurya, Norsang Lama, Thanh Phan, Gehana Patel, Keith Miller, Binita Lama, Jason Hagerty, Ronald Stanley, William V. Stoecker

Chemistry Faculty Research & Creative Works

Deep Learning Has Achieved Significant Success in Malignant Melanoma Diagnosis. These Diagnostic Models Are Undergoing a Transition into Clinical Use. However, with Melanoma Diagnostic Accuracy in the Range of Ninety Percent, a Significant Minority of Melanomas Are Missed by Deep Learning. Many of the Melanomas Missed Have Irregular Pigment Networks Visible using Dermoscopy. This Research Presents an Annotated Irregular Network Database and Develops a Classification Pipeline that Fuses Deep Learning Image-Level Results with Conventional Hand-Crafted Features from Irregular Pigment Networks. We Identified and Annotated 487 Unique Dermoscopic Melanoma Lesions from Images in the ISIC 2019 Dermoscopic Dataset to Create a …

Salt Doping Of Hyaluronic Acid Glycopolymer Biocondensates, James D. Sterling, Lu Fu, Kenisha Pudun, Shenda Baker, Megan Lord, Henry E. Riggs

Business and Information Technology Faculty Research & Creative Works

Biocondensates are largely studied with regard to intracellular components, while recognition of the formation of extracellular biocondensates are emerging, such as for cell surface heparan sulfate binding with basic fibroblast growth factor. This study analyzed the formation of biocondensates in vitro between the ubiquitous extracellular component, hyaluronan an anionic glycosaminoglycan, and cationic derivitized polyglucosamines known to bind to mucosal interfaces. The effect of molecular weight and net charge ratio was studied using a combination of microscopy, turbidity, laser diffraction particle sizing and zeta potential measurements. These analyses revealed that molecular weight affected the ability to form biocondensates while the surface …

Biostimulation Of Petroleum-Contaminated Soil Using Organic And Inorganic Amendments, Ogochukwu A. Udume, Gideon O. Abu, Herbert O. Stanley, Ijeoma F. Vincent-Akpu, Yusuf Momoh, Michael O. Eze

Chemistry Faculty Research & Creative Works

The most common approaches for the in-situ bioremediation of contaminated sites worldwide are bioaugmentation and bio stimulation. Bio stimulation has often proved more effective for chronically contaminated sites. This study examined the effectiveness of optimized water hyacinth compost in comparison with other organic and inorganic amendments for the remediation of crude oil-polluted soils. Water hyacinth was found to be rich in nutrients necessary to stimulate microbial growth and activity. an organic geochemical analysis revealed that all amendments in this study increased total petroleum hydrocarbon (TPH) biodegradation by ≥75% within 56 days, with the greatest biodegradation (93%) occurring in sterilized soil …

Wayne E. Sabbe Arkansas Soil Fertility Studies 2022, Nathan A. Slaton, Mike Daniels

Arkansas Agricultural Experiment Station Research Series

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas.

Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid

All Works

The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root …

Augmenting Ccam Infrastructure For Creating Smart Roads And Enabling Autonomous Driving, M. Jalal Khan, Manzoor Ahmed Khan, Obaid Ullah, Sumbal Malik, Farkhund Iqbal, Hesham El-Sayed, Sherzod Turaev

All Works

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the …

Disentangling Effects Of Mating, Nuptial Gifts And Accessory Gland Proteins On Reproduction In Female Crickets, Ian G. Rines, Audrey E. Harrod, John Hunt, Ben M. Sadd, Scott K. Sakaluk

Faculty Publications – Biological Sciences

Accessory gland proteins contained within male ejaculates influence female reproduction and survival in insects. Nuptial food gifts offered by male crickets and katydids, the consumption of which may also alter female behaviour and physiology after mating, also contain accessory gland proteins. However, because nuptial feeding promotes the transfer of sperm and ejaculatory substances, it is unclear whether it is accessory gland proteins in the ejaculate, nuptial gifts or both that mediate these effects. Here we evaluate the effects of mating, nuptial gifts and accessory gland proteins on female reproduction in a gift-giving cricket (Gryllodes sigillatus) using a …