A longitudinal analysis of the impact of the local tobacco retail availability and neighbourhood deprivation on male smoking behaviours in Shanghai, China

Some evidence from Western high-income countries suggests local tobacco retail availability and neighbourhood deprivation may influence smoking behaviours. However, this assertion has not been considered in China, where 44% of males continue to smoke. Data were analysed from Chinese males (n = 2054) who participated in Waves 3–5 (2009–2015) of the International Tobacco Control (ITC) China Survey by linking information on tobacco retail availability (estimated through population weighted Kernel Density of tobacco retailers in 2019) and neighbourhood deprivation (calculated as a composite score derived from the 2010 Chinese census) across Shanghai. Generalised Estimating Equation models were fitted to examine the impacts of local tobacco availability and neighbourhood deprivation on smoking behaviours (current smoking versus current non-smoking, quitting versus current smoking, longer durations of smoking abstinence versus current smoking) using the longitudinal data. Examining the impacts separately, participants living in neighbourhoods with greater availability and higher levels of deprivation were less likely to maintain longer durations of smoking abstinence in both unadjusted and adjusted models. Neighbourhood deprivation, but not availability, was found to be associated with higher odds of being a current smoker. Examining the impacts jointly, neighbourhood deprivation was still positively associated with current smoking and negatively associated with longer durations of smoking abstinence, but the negative association between availability and longer durations of smoking abstinence disappeared. The findings offer some evidence that greater tobacco retail availability and deprivation are obstacles on prolonged smoking cessation among males in Shanghai, China. Policymakers should consider small-area level place-based restrictions in China, such as reducing the availability of tobacco, as part of a comprehensive tobacco control strategy aimed at addressing the high prevalence of smoking

A cross-sectional analysis of socio-spatial patterning of tobacco retail in Shanghai, China

INTRODUCTION: International evidence from high-income countries demonstrates that the availability of tobacco tends to be greater in more urban and more deprived neighborhoods. However, little is known about the socio-spatial disparities in other settings, including megacities in China. This study investigated the patterning of tobacco retailers across Shanghai by types of tobacco retailers, including the relationship with levels of urbanity and neighborhood deprivation. AIMS AND METHODS: Tobacco retailer data (n = 19 413) was extracted from a web-scraped Points-of-Interest database. For all communities (n = 5432) across Shanghai, neighborhood tobacco retail availability was calculated using population-weighted kernel density estimation and grouped by quintiles of neighborhood deprivation and a 3-level urban classification. Associations were analyzed using the Kruskal–Wallis tests and epsilon squared. RESULTS: Across Shanghai, tobacco retail availability decreased from more urbanized areas to less urbanized areas. There was a statistical difference (p < .001) in the availability of tobacco retail across quintiles of deprivation, with the highest availability in the less deprived neighborhoods, and the lowest availability in the most deprived neighborhoods. However, this trend was reversed in the urban center, where retail availability was greatest in the most deprived areas. Convenience stores were the most common type of tobacco retailer across the city, while tobacco-only outlets were most strongly associated with levels of neighborhood deprivation. CONCLUSIONS: The results show an association between tobacco retail availability and neighborhood deprivation, which varied with levels of urbanity and types of tobacco retailers. These findings provide supportive evidence for further interventions that target reducing inequalities in exposure to tobacco retail. IMPLICATIONS: This is the first study to examine the relationship between tobacco retail availability and neighborhood deprivation in the context of Chinese megacities. Using data from Shanghai, China, we found a significant non-linear association between tobacco retail availability and neighborhood deprivation across the city. It is plausible that the socio-spatial disparities in tobacco retail availability at the neighborhood level may be a key factor explaining differences in smoking behaviors between sociodemographic groups. The findings emphasize the need for greater efforts in regulating neighborhood-level tobacco retailing in China

A partner-matching framework for social activity communities

A lot of daily activities require more than one person to participate and collaborate with each other; however, for many people, it is not easy to find good partners to engage in activities with one another. With the rapid growth of social network applications, more and more people get used to creating connections with people on the social network. Therefore, designing social network framework for partner-matching is significant in helping people to easily find good partners. In this paper, we proposed a framework which can match partners for an active community. In order to improve the matching performance, all users are divided into groups based on a specific classification tree that is built for a specific activity. The optimization goal of the partner-matching is to maintain as many stable partnerships as possible in the community. To achieve the goal, various factors are considered to design matching functions. The simulation results show that the proposed framework can help most people find stable partners quickly

In-Situ Radar Observation of Shallow Lunar Regolith at the Chang’E-5 Landing Site : Research Progress and Perspectives

Funding Information: This work is supported by the National Natural Science Foundation of China (Grant No. 42241139 and 42004099), the Opening Fund of the Key Laboratory of Lunar and Deep Space Exploration, Chinese Academy of Sciences (No. LDSE202005), the National Innovation and Entrepreneurship Training Program for College Students (No. 202310590016), the Fund of Shanghai Institute of Aerospace System Engineering (No. PZ_YY_SYF_JY200275), and the Shenzhen Municipal Government Investment Project (No. 2106_440300_04_03_901272).Peer reviewedPublisher PD

GEospatial aNalysis of ExtRacorporeal membrane oxygenATion in Europe (GENERATE)

Introduction: A cross-sectional survey GENERATE (GEospatial aNalysis of ExtRacorporeal membrane oxygenATion in Europe) initiated on behalf of the European chapter of the Extracorporeal Life Support Organization (EuroELSO), aims to provide a systematic, detailed description of contemporary Extracorporeal Life Support (ECLS) provision in Europe, map the spatial distribution of ECLS centers, and the accessibility of ECLS. Methods: Structured data collection forms were used to create a narrative description of ECLS provision in EuroELSO affiliated countries. This consisted of both center-specific data and relevant national infrastructure. Data was provided by a network of local and national representatives. Spatial accessibility analysis was conducted where appropriate geographical data were available.Results: 281 centers from 37 countries affiliated to EuroELSO were included in the geospatial analysis and demonstrate heterogeneous patterns of ECLS provision. Accessibility of ECLS services within 1 hour of drive-time is available for 50% of the adult population in 8 of 37 countries (21.6%). This proportion is reached within 2 hours in 21 of 37 countries (56.8%) and within 3 hours in 24 of 37 countries (64.9%). For pediatric centers, accessibility is similar with 9 of 37 countries (24.3%) reached the covering of 50% of the population aged 0-14 within 1 hour and 23 of 37 countries (62.2%) within 2 hours and 3 hours.Conclusions: ECLS services are accessible in most of the European countries, but their provision differs across the continent. There is still no solid evidence given regarding the optimal ECLS provision model. The spatial disparity in ECLS provision demonstrated in our analysis requires governments, healthcare professionals and policy makers to consider how to develop existing provision to accommodate the anticipated increase in need for time critical access to this advanced support modality

Engineering medium-range order and polyamorphism in a nanostructured amorphous alloy

Like crystalline materials, the properties of amorphous materials can be tailored by tuning the local atomic-to-nanoscale structural configurations. Polyamorphism is evident by the coexistence of kinetically stabilized amorphous structures with tailorable short-to-medium-range orders, providing a viable means to engineer the degree of local order and heterogeneity. Here, we report experimental evidence of the coexistence of liquid-like and solid-like amorphous phases in a Ni$_{82}$P$_{18}$ amorphous alloy with enhanced thermal stability and plasticity prepared by pulsed electrodeposition. The two amorphous phases, of comparable volume fraction of ~50% each, have similar short-range order but are distinguished by packing at the medium-range length scale (>6 Å). Upon heating, a structure crossover at ~450 K was observed, where the liquid-like structure transforms to the solid-like structure, as evidenced by the enthalpy release and an anomalous contraction of atomic structure over the medium-range length scale, due to the metastable nature of the liquid-like structure

ART⋅\boldsymbol{\cdot}V: Auto-Regressive Text-to-Video Generation with Diffusion Models

We present ART$\boldsymbol{\cdot}$V, an efficient framework for auto-regressive video generation with diffusion models. Unlike existing methods that generate entire videos in one-shot, ART$\boldsymbol{\cdot}$V generates a single frame at a time, conditioned on the previous ones. The framework offers three distinct advantages. First, it only learns simple continual motions between adjacent frames, therefore avoiding modeling complex long-range motions that require huge training data. Second, it preserves the high-fidelity generation ability of the pre-trained image diffusion models by making only minimal network modifications. Third, it can generate arbitrarily long videos conditioned on a variety of prompts such as text, image or their combinations, making it highly versatile and flexible. To combat the common drifting issue in AR models, we propose masked diffusion model which implicitly learns which information can be drawn from reference images rather than network predictions, in order to reduce the risk of generating inconsistent appearances that cause drifting. Moreover, we further enhance generation coherence by conditioning it on the initial frame, which typically contains minimal noise. This is particularly useful for long video generation. When trained for only two weeks on four GPUs, ART$\boldsymbol{\cdot}$V already can generate videos with natural motions, rich details and a high level of aesthetic quality. Besides, it enables various appealing applications, e.g., composing a long video from multiple text prompts.Comment: 24 pages, 21 figures. Project page at https://warranweng.github.io/art.

Multi-view radiomics and deep learning modeling for prostate cancer detection based on multi-parametric MRI

IntroductionThis study aims to develop an imaging model based on multi-parametric MR images for distinguishing between prostate cancer (PCa) and prostate hyperplasia.MethodsA total of 236 subjects were enrolled and divided into training and test sets for model construction. Firstly, a multi-view radiomics modeling strategy was designed in which different combinations of radiomics feature categories (original, LoG, and wavelet) were compared to obtain the optimal input feature sets. Minimum-redundancy maximum-relevance (mRMR) selection and least absolute shrinkage selection operator (LASSO) were used for feature reduction, and the next logistic regression method was used for model construction. Then, a Swin Transformer architecture was designed and trained using transfer learning techniques to construct the deep learning models (DL). Finally, the constructed multi-view radiomics and DL models were combined and compared for model selection and nomogram construction. The prediction accuracy, consistency, and clinical benefit were comprehensively evaluated in the model comparison.ResultsThe optimal input feature set was found when LoG and wavelet features were combined, while 22 and 17 radiomic features in this set were selected to construct the ADC and T2 multi-view radiomic models, respectively. ADC and T2 DL models were built by transferring learning from a large number of natural images to a relatively small sample of prostate images. All individual and combined models showed good predictive accuracy, consistency, and clinical benefit. Compared with using only an ADC-based model, adding a T2-based model to the combined model would reduce the model’s predictive performance. The ADCCombinedScore model showed the best predictive performance among all and was transformed into a nomogram for better use in clinics.DiscussionThe constructed models in our study can be used as a predictor in differentiating PCa and BPH, thus helping clinicians make better clinical treatment decisions and reducing unnecessary prostate biopsies