Determinants of Air Quality in Building Environments: A Multi-Regression Analysis and Implications for Open Teaching Practices

In the ever-evolving educational milieu, the integration of innovative teaching methodologies is increasingly crucial to meet the changing needs of modern learners. This research meticulously explores the application of open teaching practices in the fields of building environment and energy application engineering. Through an in-depth examination of multi-regression data pertaining to various environmental factors, this study reveals significant correlations and patterns that are relevant to both educators and environmental specialists. Emphasis is placed on the student-centric ethos of this approach, combining the dual concepts of environmental science and pedagogical progression. The relationship between environmental variables, such as PM2.5, PM10, temperature, and humidity, and the air quality index (AQI) is rigorously analyzed. Such analysis underscores the educational improvements brought about by open teaching strategies. The presented findings not only offer nuanced insights into how the aforementioned variables influence air quality but also highlight the benefits and potential of open teaching methodologies in creating a more interactive and enlightening academic environment

Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently

Existing hand detection methods usually follow the pipeline of multiple stages with high computation cost, i.e., feature extraction, region proposal, bounding box regression, and additional layers for rotated region detection. In this paper, we propose a new Scale Invariant Fully Convolutional Network (SIFCN) trained in an end-to-end fashion to detect hands efficiently. Specifically, we merge the feature maps from high to low layers in an iterative way, which handles different scales of hands better with less time overhead comparing to concatenating them simply. Moreover, we develop the Complementary Weighted Fusion (CWF) block to make full use of the distinctive features among multiple layers to achieve scale invariance. To deal with rotated hand detection, we present the rotation map to get rid of complex rotation and derotation layers. Besides, we design the multi-scale loss scheme to accelerate the training process significantly by adding supervision to the intermediate layers of the network. Compared with the state-of-the-art methods, our algorithm shows comparable accuracy and runs a 4.23 times faster speed on the VIVA dataset and achieves better average precision on Oxford hand detection dataset at a speed of 62.5 fps.Comment: Accepted to AAAI201

Psychometric assessment of HIV/STI sexual risk scale among MSM: A Rasch model approach

<p>Abstract</p> <p>Background</p> <p>Little research has assessed the degree of severity and ordering of different types of sexual behaviors for HIV/STI infection in a measurement scale. The purpose of this study was to apply the Rasch model on psychometric assessment of an HIV/STI sexual risk scale among men who have sex with men (MSM).</p> <p>Methods</p> <p>A cross-sectional study using respondent driven sampling was conducted among 351 MSM in Shenzhen, China. The Rasch model was used to examine the psychometric properties of an HIV/STI sexual risk scale including nine types of sexual behaviors.</p> <p>Results</p> <p>The Rasch analysis of the nine items met the unidimensionality and local independence assumption. Although the person reliability was low at 0.35, the item reliability was high at 0.99. The fit statistics provided acceptable infit and outfit values. Item difficulty invariance analysis showed that the item estimates of the risk behavior items were invariant (within error).</p> <p>Conclusions</p> <p>The findings suggest that the Rasch model can be utilized for measuring the level of sexual risk for HIV/STI infection as a single latent construct and for establishing the relative degree of severity of each type of sexual behavior in HIV/STI transmission and acquisition among MSM. The measurement scale provides a useful measurement tool to inform, design and evaluate behavioral interventions for HIV/STI infection among MSM.</p

A global assessment of the impact of school closure in reducing COVID-19 spread.

Prolonged school closure has been adopted worldwide to control COVID-19. Indeed, UN Educational, Scientific and Cultural Organization figures show that two-thirds of an academic year was lost on average worldwide due to COVID-19 school closures. Such pre-emptive implementation was predicated on the premise that school children are a core group for COVID-19 transmission. Using surveillance data from the Chinese cities of Shenzhen and Anqing together, we inferred that compared with the elderly aged 60 and over, children aged 18 and under and adults aged 19-59 were 75% and 32% less susceptible to infection, respectively. Using transmission models parametrized with synthetic contact matrices for 177 jurisdictions around the world, we showed that the lower susceptibility of school children substantially limited the effectiveness of school closure in reducing COVID-19 transmissibility. Our results, together with recent findings that clinical severity of COVID-19 in children is lower, suggest that school closure may not be ideal as a sustained, primary intervention for controlling COVID-19. This article is part of the theme issue 'Data science approach to infectious disease surveillance'

Multilevel and spatial analysis of syphilis in Shenzhen, China, to inform spatially targeted control measures

The present study investigates the varied spatial distribution of syphilis cases in Shenzhen, China, and explores the individual-, neighbourhood- and district-level factors affecting the distribution

Identification of miRs-143 and -145 that Is Associated with Bone Metastasis of Prostate Cancer and Involved in the Regulation of EMT

The principal problem arising from prostate cancer (PCa) is its propensity to metastasize to bone. MicroRNAs (miRNAs) play a crucial role in many tumor metastases. The importance of miRNAs in bone metastasis of PCa has not been elucidated to date. We investigated whether the expression of certain miRNAs was associated with bone metastasis of PCa. We examined the miRNA expression profiles of 6 primary and 7 bone metastatic PCa samples by miRNA microarray analysis. The expression of 5 miRNAs significantly decreased in bone metastasis compared with primary PCa, including miRs-508-5p, -145, -143, -33a and -100. We further examined other samples of 16 primary PCa and 13 bone metastases using real-time PCR analysis. The expressions of miRs-143 and -145 were verified to down-regulate significantly in metastasis samples. By investigating relationship of the levels of miRs-143 and -145 with clinicopathological features of PCa patients, we found down-regulations of miRs-143 and -145 were negatively correlated to bone metastasis, the Gleason score and level of free PSA in primary PCa. Over-expression miR-143 and -145 by retrovirus transfection reduced the ability of migration and invasion in vitro, and tumor development and bone invasion in vivo of PC-3 cells, a human PCa cell line originated from a bone metastatic PCa specimen. Their upregulation also increased E-cadherin expression and reduced fibronectin expression of PC-3 cells which revealed a less invasive morphologic phenotype. These findings indicate that miRs-143 and -145 are associated with bone metastasis of PCa and suggest that they may play important roles in the bone metastasis and be involved in the regulation of EMT Both of them may also be clinically used as novel biomarkers in discriminating different stages of human PCa and predicting bone metastasis

Influence Mechanism of Structural Characteristics of Interdisciplinary Knowledge Network on College Students’ Innovation Ability

Interdisciplinary scientific research method plays a significant role in promoting technological innovation. As the principal subject in scientific research activities, college students need to improve their innovation ability using interdisciplinary knowledge resources and knowledge network. Existing researches are mostly carried out from a single perspective of knowledge network, and ignore systematical analysis for interdisciplinary multilayer network. For that reason, the influence mechanism of structural characteristics of interdisciplinary knowledge network on college students’ innovation ability is established in this article. An interdisciplinary-dependent multilayer network is built and network nodes are divided into interdisciplinary knowledge elements, scientific research theme, and discipline and specialty. Structure attribute of interdisciplinary knowledge network and relationship attribute of interdisciplinary knowledge elements are also used to calculate indicators at different knowledge dimensions, and specific indicator measurement modes are proposed. The regression model is built to explore direct influence mechanism of dynamic and static characteristics of interdisciplinary knowledge network on college students’ innovation ability. A regression model is also built to further verify the regulating effect of disciplinary knowledge’s network location attribute of college students’ specialty in influence relationship between interdisciplinary knowledge network and college students’ innovation ability. Last, corresponding analysis result is given based on experiment result

Examination of the Relationships Between Environmental Exposures to Volatile Organic Compounds and Biochemical Liver Tests: Application of Canonical Correlation Analysis

This study was to explore the relationships between personal exposure to 10 volatile organic compounds (VOCs) and biochemical liver tests with the application of canonical correlation analysis. Data from a subsample of the 1999-2000 National Health and Nutrition Examination Survey were used. Serum albumin, total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and γ-glutamyl transferase (GGT) served as the outcome variables. Personal exposures to benzene, chloroform, ethylbenzene, tetrachloroethene, toluene, trichloroethene, o-xylene, m-,p-xylene, 1,4-dichlorobenzene, and methyl tert-butyl ether (MTBE) were assessed through the use of passive exposure monitors worn by study participants. The first two canonical correlations were 0.3218 and 0.2575, suggesting a positive correlation mainly between the six VOCs (benzene, ethylbenzene, toluene, o-xylene, m-,p-xylene, and MTBE) and the three biochemical liver tests (albumin, ALP, and GGT) and a positive correlation mainly between the two VOCs (1,4-dichlorobenzene and tetrachloroethene) and the two biochemical liver tests (LDH and TB). Subsequent multiple linear regressions show that exposure to benzene, toluene, or MTBE was associated with serum albumin, while exposure to tetrachloroethene was associated with LDH and total bilirubin. In conclusion, exposure to certain VOCs as a group or individually may influence certain biochemical liver test results in the general population