(Main Section: Community Planning)

Shenzhen is a Chinese city with a very fast-paced work and life environment. Because people there are often under high pressure, fitness and sports have great benefits for their health. In order to study the correlation between inhabitants’fitness and sports activities and the community environment, a questionnaire is designed based upon a review of the literature on fitness behavior and the community environment, and then 595 inhabitants of Shenzhen are surveyed in 2016. The survey involved the demographic information of the subjects, their fitness and sports activities, and the satisfaction of spaces for sports in urban communities. Through analysis of the questionnaire data by cross tabulation, patterns of how and where people like to do exercise have been found. Jogging and walking are the most popular individual activities, where the preferred places are neighborhood gardens, urban squares and parks. The most popular team sports are badminton, table tennis and tennis, where the preferred places are professional fitness clubs, urban squares or parks. Gender differences significantly determine the choice of sport. Males tend to cycle or run individually, and to play ball games as a team. Females prefer to do yoga or eight section brocade individually, and square dance as a team. The factors influencing the satisfaction of places for exercise are ordered as follows: accessibility, fresh air and a clean environment, and low cost. The main requests from locals for the improvement of the recreation environment are the supply of more kinds of sports facilities and fields and better maintenance and management of sports facilities. Some urban design strategies for enhancing the community’s sports environment are recommended

Privacy-preserving inpainting for outsourced image

In this article, a framework of privacy-preserving inpainting for outsourced image and an encrypted-image inpainting scheme are proposed. Different with conventional image inpainting in plaintext domain, there are two entities, that is, content owner and image restorer, in our framework. Content owner first encrypts his or her damaged image for privacy protection and outsources the encrypted, damaged image to image restorer, who may be a cloud server with powerful computation capability. Image restorer performs inpainting in encrypted domain and sends the inpainted and encrypted image back to content owner or authorized receiver, who can acquire final inpainted result in plaintext domain through decryption. In our encrypted-image inpainting scheme, with the assist of Johnson–Lindenstrauss transform that can preserve Euclidean distance between two vectors before and after encryption, the best-matching block with the smallest distance to current block can be found and utilized for patch filling in Paillier-encrypted image. To eliminate mosaic effect after decryption, weighted mean filtering in encrypted domain is conducted with Paillier homomorphic properties. Experimental results show that our privacy-preserving inpainting framework can be effectively applied in secure cloud computing, and the proposed encrypted-image inpainting scheme achieves comparable visual quality of inpainted results with some typical inpainting schemes in plaintext domain

Changes in Physicochemical Properties and Flavor Characteristics of Rosa roxburghii Tratt. Fruit Vinegar during Fermentation

This paper investigated the compositional changes of Rosa roxburghii Tratt. fruit vinegar during fermentation. By using Rosa roxburghii Tratt. as raw material and using the whole liquid fermentation technique, fruit vinegar was prepared by fermenting alcoholic and acetic acids simultaneously. The physicochemical properties of the fermentation process were dynamically monitored. Headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and the odor activity value (OAV) were utilized to analyze volatile flavor components. As fermentation proceeded, soluble solids, pH, total sugars, and reduced sugars decreased, while total acid and VC contents increased. From the original juice to the end of acetic acid fermentation, the total acid and VC contents ranged from 1.86 g/100 mL and 956.82 mg/100 mL to 6.79 g/100 mL and 1275.88 mg/100 mL. Oxalic acid, quinic acid, pyruvic acid, ascorbic acid, lactic acid, acetic acid, and fumaric acid showed varying degrees of increasing (P<0.05). By contrast, formic acid, citric acid, maleic acid, and succinic acid exhibited little variation. A total of 92 volatile compounds were detected in the Rosa roxburghii Tratt. fruit vinegar, and with the addition of OAV analysis, ten volatile compounds were identified as key aroma compounds, which included nonanal, acetaldehyde, ethyl isobutyrate, ethyl butyrate, ethyl 2-methylbutyrate, ethanol, isoamyl alcohol, leaf alcohol, linalool, and phenyl ethanol. Among these components, ethyl butyrate and leaf alcohol contributed most to the aroma of Rosa roxburghii Tratt. fruit vinegar. Green grass and green apples were characteristic aromas of this vinegar. The results of the study would provide a theoretical basis and practical guidance for the effective control of fermentation conditions, revealing the physicochemical characteristics and flavor features of fermented Rosa roxburghii Tratt. fruit vinegar, forming a method for quality evaluation of Rosa roxburghii Tratt. fruit vinegar, and formulating quality standards

Robust elbow angle prediction with aging soft sensors via output-level domain adaptation

Wearable devices equipped with soft sensors provide a promising solution for body movement monitoring. Specifically, body movements like elbow flexion can be captured by monitoring the stretched soft sensors’ resistance changes. However, in addition to stretching, the resistance of a soft sensor is also influenced by its aging, which makes the resistance a less stable indicator of the elbow angle. In this paper, we leverage the recent progress in Deep Learning and address the aforementioned issue by formulating the aging-invariant prediction of elbow angles as a domain adaption problem. Specifically, we define the soft sensor data (i.e., resistance values) collected at different aging levels as different domains and adapt a regression neural network among them to learn domain-invariant features. However, unlike the popular pairwise domain adaptation problem that only involves one source and one target domain, ours is more challenging as it has “infinite” target domains due to the non-stop aging. To address this challenge, we novelly propose an output-level domain adaptation approach which builds on the fact that the elbow angles are in a fixed range regardless of aging. Experimental results show that our method enables robust and accurate prediction of elbow angles with aging soft sensors, which significantly outperforms supervised learning ones that fail to generalize to aged sensor data

Predicting progression of white matter hyperintensity using coronary artery calcium score based on coronary CT angiography—feasibility and accuracy

ObjectiveCoronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions.MethodsWe evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to &lt;100, 100 to 400, and &gt; 400) to compare their WMH changes in nine brain regions.ResultsAlcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (p &lt; 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p &lt; 0.05).ConclusionThis study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD

Enhancing reliability and efficiency for real-time robust adaptive steganography using cyclic redundancy check codes

The development of multimedia and deep learning technology bring new challenges to steganography and steganalysis techniques. Meanwhile, robust steganography, as a class of new techniques aiming to solve the problem of covert communication under lossy channels, has become a new research hotspot in the field of information hiding. To improve the communication reliability and efficiency for current real-time robust steganography methods, a concatenated code, composed of Syndrome–Trellis codes (STC) and cyclic redundancy check (CRC) codes, is proposed in this paper. The enhanced robust adaptive steganography framework proposed is this paper is characterized by a strong error detection capability, high coding efficiency, and low embedding costs. On this basis, three adaptive steganographic methods resisting JPEG compression and detection are proposed. Then, the fault tolerance of the proposed steganography methods is analyzed using the residual model of JPEG compression, thus obtaining the appropriate coding parameters. Experimental results show that the proposed methods have a significantly stronger robustness against compression, and are more difficult to be detected by statistical based steganalytic methods

Association Study Reveals Genetic Loci Responsible for Arsenic, Cadmium and Lead Accumulation in Rice Grain in Contaminated Farmlands

Accumulation of toxic heavy metals and metalloids (THMMs) in crop grain remarkably affects food safety and human health. Reducing the content of THMMs in grain requires the identification and manipulation of the genes regulating their accumulation. This study aimed to determine the genetic variations affecting grain THMM accumulation in rice by using association mapping. We used 276 accessions with 416 K single nucleotide polymorphisms (SNPs) and performed genome-wide association analysis of grain THMM concentrations in rice grown in heavily multi-contaminated farmlands. We detected 22, 17, and 21 quantitative trait loci (QTLs) for grain arsenic, cadmium, and lead concentrations, respectively. Both inter- and intra-subpopulation variants accounted for these QTLs. Most QTLs contained no known THMM-related genes and represented unidentified novel genes. We examined the candidate genes in qGAS1, a QTL for grain arsenic concentration with the best P-value detected for the entire population. We speculated that a transport protein of the multidrug and toxin extrusion family could be the candidate gene for this QTL. Our study suggested that the genetic regulation of grain THMM accumulation is very complex and largely unknown. The QTLs and SNPs identified in this study might help in the identification of new genes regulating THMM accumulation and aid in marker-assisted breeding of rice with low grain THMM content

Suppression of Estrogen Receptor Transcriptional Activity by Connective Tissue Growth Factor

Secreted growth factors have been shown to stimulate the transcriptional activity of estrogen receptors (ER) that are responsible for many biological processes. However, whether these growth factors physically interact with ER remains unclear. Here, we show for the first time that connective tissue growth factor (CTGF) physically and functionally associates with ER. CTGF interacted with ER both in vitro and in vivo. CTGF interacted with ER DNA-binding domain. ER interaction region in CTGF was mapped to the thrombospondin type I repeat, a cell attachment motif. Overexpression of CTGF inhibited ER transcriptional activity as well as the expression of estrogen-responsive genes, including pS2 and cathepsin D. Reduction of endogenous CTGF with CTGF small interfering RNA enhanced ER transcriptional activity. The interaction between CTGF and ER is required for the repression of estrogen-responsive transcription by CTGF. Moreover, CTGF reduced ER protein expression, whereas the CTGF mutant that did not repress ER transcriptional activity also did not alter ER protein levels. The results suggested the transcriptional regulation of estrogen signaling through interaction between CTGF and ER, and thus may provide a novel mechanism by which cross-talk between secreted growth factor and ER signaling pathways occurs