A Pilot Study of Development and Validation of Treatment Fidelity Checklist for Intervention Research in K-12 School Physical Education

No conceptual framework and valid and reliable measurement of treatment fidelity are available for intervention research in K-12 school physical education. The purposes of this study were to propose a conceptual framework and then develop and validate a checklist to assess treatment fidelity in K-12 school physical education. A literature search was conducted on journal article titles using key words through EBSCO Discovery Service. A conceptual framework and Treatment Fidelity Checklist were developed. The conceptual framework and Treatment Fidelity Checklist were validated by four experts and an intercoder reliability coefficient. All experts validated the conceptual framework and Treatment Fidelity Checklist. The overall IOA was 88%. The Treatment Fidelity Checklist is valid and reliable. The conceptual framework and Checklist of Treatment Fidelity provide a very useful document to guide future intervention research in physical education and what to be reported in publications

A Review on the Dose Response Effect of Regular Physical Activity on Cognitive Function Among Children and Adolescents

Purpose: Positive effects of physical activity on cognitive function among children and adolescents have been observed in previous studies. However, little is known about whether there is a dose-response effect of physical activity on cognitive functioning. Especially, the curvilinear relationship between regular physical activity and cognitive functioning remained unexplored. The purpose of this paper was to review the literature on the dose response effect of physical activity on cognitive function among children and adolescents. Methods: A literature search on key words, title, and abstract with the phrases “physical activity and executive function”, “physical activity and cognition”, and “physical activity and cognitive function” was conducted by the authors on five databases: (a) Academic Search Complete; (b) ERIC; (c) Medline; (d) Pubmed; and (e) SportDiscus. Articles that met the inclusive and exclusive criteria were included in this review. Data including eight variables were extracted by the first author and validated by the second author independently. Results: Only four studies examined the dose-response effects of regular physical activities on cognitive functions. Little evidence is available to support the dose response effect. There is no evidence to support a curvilinear relationship between physical activity and cognitive function. Discussion and Conclusion: Research on the dose response effect of physical activity on cognitive function is still in its infancy. More research is warranted to further advance this line of research. Especially, future research should focus on what constitutes the minimal physical activity for cognitive benefits and what constitutes the optimal PA required to achieve maximal cognitive benefits. Findings from this line of research are critical to guiding future interventions and policies on increasing physical activity and cognitive function among children and adolescents in the United States

Noisy Knowledge Graph Representation Learning: a Rule-Enhanced Method

Knowledge graphs are used to store structured facts, which are presented in the form of triples, i.e., (head entity, relation, tail entity). Current large-scale knowledge graphs are usually constructed with (semi-) automated methods for knowledge extraction and the process inevitably introduces noise, which may affect the effectiveness of the knowledge representation. However, most traditional representation learning methods assume that the triples in knowledge graphs are correct and represent knowledge in a distributed manner accordingly. Therefore, noise detection on knowledge graphs is a crucial task. In addition, the incompleteness of knowledge graphs has also attracted people’s attention. The above problems are studied and a knowledge representation learning framework combining logical rules and relation path information is proposed, which accomplishes knowledge representation learning and achieves a mutual enhancement effect while detecting possible noise. Specifically, the framework is divided into a triple embedding part and a triple trustworthiness estimation part. In the triple embedding part, relation path information and logical rule information are introduced to construct a better knowledge representation based on the triple structure information, the latter of which is used to enhance the ability of relation path reasoning and the interpretability of the representation learning. In the triple trustworthiness estimation part, three types of information are further utilized to detect possible noise. Experiments are conducted on three public evaluated datasets and the results show that the model achieves significant performance improvement in tasks such as knowledge graph noise detection and knowledge complementation compared with all baseline methods

In-painting Radiography Images for Unsupervised Anomaly Detection

We propose space-aware memory queues for in-painting and detecting anomalies from radiography images (abbreviated as SQUID). Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. To exploit this structured information, our SQUID consists of a new Memory Queue and a novel in-painting block in the feature space. We show that SQUID can taxonomize the ingrained anatomical structures into recurrent patterns; and in the inference, SQUID can identify anomalies (unseen/modified patterns) in the image. SQUID surpasses the state of the art in unsupervised anomaly detection by over 5 points on two chest X-ray benchmark datasets. Additionally, we have created a new dataset (DigitAnatomy), which synthesizes the spatial correlation and consistent shape in chest anatomy. We hope DigitAnatomy can prompt the development, evaluation, and interpretability of anomaly detection methods, particularly for radiography imaging.Comment: Main paper with appendi

Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images

Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. Exploiting this structured information could potentially ease the detection of anomalies from radiography images. To this end, we propose a Simple Space-Aware Memory Matrix for In-painting and Detecting anomalies from radiography images (abbreviated as SimSID). We formulate anomaly detection as an image reconstruction task, consisting of a space-aware memory matrix and an in-painting block in the feature space. During the training, SimSID can taxonomize the ingrained anatomical structures into recurrent visual patterns, and in the inference, it can identify anomalies (unseen/modified visual patterns) from the test image. Our SimSID surpasses the state of the arts in unsupervised anomaly detection by +8.0%, +5.0%, and +9.9% AUC scores on ZhangLab, COVIDx, and CheXpert benchmark datasets, respectively. Code: https://github.com/MrGiovanni/SimSIDComment: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). arXiv admin note: substantial text overlap with arXiv:2111.1349

Decreased lung function with mediation of blood parameters linked to e-waste lead and cadmium exposure in preschool children

Blood lead (Pb) and cadmium (Cd) levels have been associated with lower lung function in adults and smokers, but whether this also holds for children from electronic waste (e-waste) recycling areas is still unknown. To investigate the contribution of blood heavy metals and lung function levels, and the relationship among living area, the blood parameter levels, and the lung function levels, a total of 206 preschool children from Guiyu (exposed area), and Haojiang and Xiashan (reference areas) were recruited and required to undergo blood tests and lung function tests during the study period. Preschool children living in e-waste exposed areas were found to have a 1.37 mu g/dL increase in blood Pb, 1.18 mu g/L. increase in blood Cd, and a 41.00 x 10(9)/L increase in platelet counts, while having a 2.82 decrease in hemoglobin, 92 mL decrease in FVC and 86 mL decrease in FEV1. Each unit of hemoglobin (1 g/L) decline was associated with 5 mL decrease in FVC and 4 mL decrease in FEV1. We conclude that children living in e-waste exposed area have higher levels of blood Pb, Cd and platelets, and lower levels of hemoglobin and lung function. Hemoglobin can be a good predictor for lung function levels. (C) 2017 Elsevier Ltd. All rights reserved.</p