Towards an Applied Urban Form Approach: Temporal Dynamics and Context-Dependent Effects of Urban Form on Air Quality in China

Over the last several decades, air pollution has posed a tremendous socio-economic challenge to the sustainable development of cities. Many studies suggest that managing urban forms, including spatial composition and configuration of urban landscapes and populations, can sustainably mitigate urban air quality deterioration. Particularly, urban form influences air quality through immediate pathways and time-delayed socio-ecological processes. Understanding the dynamic temporal impacts of urban form on air quality is critical to estimating air quality changes and making policy decisions. Yet, the temporal effects of urban form may be understudied. Moreover, evidence indicates the effects of urban form on air quality vary by urban size, density and other dependent conditions. The relationship between urban form and air quality can be influenced by contextual urban forms, while most research concentrates on the independent effect of a single dimension of urban form. These gaps present challenges in applying the statistical findings of academic studies to urban planning practice, given that real-world cities are dynamic and cannot be characterised by a single dimension of urban form. This research may be the first empirical investigation that attempts to synthesise the scientific results to inform planning practice in consideration of the time-lag effect and the context-dependent effect. The research contributed to advancing the recent discussions on the applied urban ecology approach that is still not fully developed in bringing the urban ecology theory to the field of urban sustainability with practical considerations. This research selects China as a case study to address the research gaps in a real-life context. In the past 20 years, China has seen rapid urbanisation, leading to air pollution issues and notable variations in air quality and urban form. The study aims to deepen our understanding of the temporal dynamics and context-dependent effects of urban form on air quality, which can contribute to the establishment of applicable guidelines for the urban form approach to mitigate air pollution in Chinese cities. Specifically, for the temporal dynamics, the results indicated urban forms related to mobility and energy consumption have a more significant immediate effect. Other urban forms concerning infrastructure development and land use changes exert a greater influence on air quality after a period exceeding five years. For the context-dependent effect, the study found that population-related urban forms serve as contextual factors that influence the relationship between other urban forms and air quality. Landscape-related urban forms interact in ways that either reinforce or lessen the positive or negative impacts on air quality. The study categorised sample cities into six clusters, exhibiting distinct urban form typologies and air quality attributes. It is hoped that tailored planning guidelines for each cluster sharing similar urban form and air quality characteristics can assist China’s planning practice in applying the urban form approach to address the air pollution issue

Towards Effective Multi-Moving-Camera Tracking: A New Dataset and Lightweight Link Model

Ensuring driving safety for autonomous vehicles has become increasingly crucial, highlighting the need for systematic tracking of on-road pedestrians. Most vehicles are equipped with visual sensors, however, the large-scale visual data has not been well studied yet. Multi-target multi-camera (MTMC) tracking systems are composed of two modules: single-camera tracking (SCT) and inter-camera tracking (ICT). To reliably coordinate between them, MTMC tracking has been a very complicated task, while tracking across multiple moving cameras makes it even more challenging. In this paper, we focus on multi-target multi-moving-camera (MTMMC) tracking, which is attracting increasing attention from the research community. Observing there are few datasets for MTMMC tracking, we collect a new dataset, called Multi-Moving-Camera Track (MMCT), which contains sequences under various driving scenarios. To address the common problems of identity switch easily faced by most existing SCT trackers, especially for moving cameras due to ego-motion between the camera and targets, a lightweight appearance-free global link model, called Linker, is proposed to mitigate the identity switch by associating two disjoint tracklets of the same target into a complete trajectory within the same camera. Incorporated with Linker, existing SCT trackers generally obtain a significant improvement. Moreover, to alleviate the impact of the image style variations caused by different cameras, a color transfer module is effectively incorporated to extract cross-camera consistent appearance features for pedestrian association across moving cameras for ICT, resulting in a much improved MTMMC tracking system, which can constitute a step further towards coordinated mining of multiple moving cameras. The project page is available at https://dhu-mmct.github.io/

Embracing integrated watershed revitalization in Suzhou, China: learning from global case studies

AbstractSuzhou is China’s historic water town, and a sustainable approach to watershed revitalization is firmly on the agenda. The practice of integrated watershed management requires collaborative planning involving a significant number of stakeholders; no single organization can solve the problems of ecosystem management unilaterally. The changing social–political environment in China has led to the development of a new form of governance. China is in transition from the traditional government image of a regulator and a controller towards an enabler that facilitates provision and action by, and through, others. Global case studies show that sustainability issues are essential to tackling watershed ecosystem management by creating a win–win strategy for wider stakeholders. Viewed from an institutional perspective, the emergence of a new collaborative partnership model requires a different implementation process to tackle practical problems in the face of complex watershed agendas. Drawing upon global and China’s experiences, the paper concludes that some planning processes require government leadership continuity, while others need bottom–up approaches.</jats:p

Is ignorance bliss? Evaluating information awareness and life satisfaction through the lens of perceived air pollution: The case of Beijing, China.

Our study presents fresh insight into the impacts of air-related information accessibility and policy awareness on citizen's life satisfaction, through the lens of perceived air pollution sources. It is widely accepted that disclosing information about air pollution adversely affects an individual's life satisfaction. However, the impact of information accessibility and public policy awareness on life satisfaction remains poorly understood in real-life contexts and their interrelationship warrants exploration. Earlier studies suggested that public scrutiny via information disclosure is a means to lower air pollution levels, potentially enhancing life satisfaction through improved air quality perception and reduced health risks. However, much of that research was based on the flawed presumption that all individuals can access and understand this officially disclosed information. They overlooked the actual availability of information and public reflections on relevant policies that were influenced by their perception of air pollution. This research gap highlights the need for in-depth evidence of the impacts of information accessibility and policy awareness on life satisfaction. Employing a covariance-based Structural Equation Modelling, our study analyses the views of 1867 Beijing residents in 2022. We assessed information accessibility, policy awareness, perceived air pollution sources, life satisfaction, and socio-demographic characteristics covering two time periods: a) before the COVID-19 pandemic and b) during its normalisation phase. Our findings reveal that both information accessibility and policy awareness significantly and positively affect life satisfaction in both periods. Moreover, the indirect parameter analysis underscores the presence of significant heterogeneity when considering the mediating role of impacts of perceived air pollutants. The results of this study offer a novel contribution regarding the relationship between air pollution information accessibility, policy awareness, and life satisfaction

The impact of positive activities on mental health: the mediating role of positive emotion

ObjectiveMental health has become a widely concerned topic worldwide. However, the impact and mechanism of positive activities on mental health still needed to be explored. This study aimed to apply the positive-activity model to investigate the effect of participation in positive activities on mental health and the mediating role of positive emotion.MethodsThis study used data from the 2021 China Comprehensive Social Survey (CGSS) and included 2,581 individuals. Ordinary Least Squares (OLS) and a three-step method was used for analysis.ResultsThe average of positive activities was 15.83. The positive activities affected positively mental health (β = 0.0132, p &lt; 0.001). The positive emotion played a mediating role (β =0.2281, p &lt; 0.001). The effect of positive activities on mental health was significant in older adults group (β = 0.024, p &lt; 0.001), female (β = 0.015, p &lt; 0.01) and male group (β = 0.01, p &lt; 0.01), unmarried/divorced/widowed group (β = 0.024, p &lt; 0.01), cohabitation/first marriage with spouse/remarriage with spouse/separation without divorce group (β = 0.010, p &lt; 0.001), middle(β = 0.013, p &lt; 0.05), and upper-middle-level SES group (β = 0.054, p &lt; 0.001).ConclusionsWe concluded that the participation level of positive activities still needs to be improved and positive activities improve mental health through positive emotion, which implied that positive activities, as an easily implementable measure, should be greatly encouraged in mental health policies. And older adults, female, people without spouse, middle and upper-middle-income individuals need to be paid more attention

m6A Regulator-Based Exosomal Gene Methylation Modification Patterns Identify Distinct Microenvironment Characterization and Predict Immunotherapeutic Responses in Colon Cancer.

peer reviewedRecent studies have highlighted the biological significance of exosomes and m6A modifications in immunity. Nonetheless, it remains unclear whether the m6A modification gene in exosomes of body fluid has potential roles in the tumor microenvironment (TME). Herein, we identified three different m6A-related exosomal gene modification patterns based on 59 m6A-related exosomal genes, which instructed distinguishing characteristics of TME in colon cancer (CC). We demonstrated that these patterns could predict the stage of tumor inflammation, subtypes, genetic variation, and patient prognosis. Furthermore, we developed a scoring mode-m6A-related exosomal gene score (MREGS)-by detecting the level of m6A modification in exosomes to classify immune phenotypes. Low MREGS, characterized by prominent survival and immune activation, was linked to a better response to anti-PDL1 immunotherapy. In contrast, the higher MREGS group displayed remarkable stromal activation, high activity of innate immunocytes, and a lower survival rate. Hence, this work provides a novel approach for evaluating TME cell infiltration in colon cancer and guiding more effective immunotherapy strategies

Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples

BACKGROUNDLIBS technology is a non-destructive, high sensitivity, high resolution spectroscopy technology that can be used to analyze the composition and structure of chemical substances and materials. It has extensive application in fields such as chemistry, materials science, life science, and geological exploration, and its emergence has provided new methods and technologies for the development of these fields. LIBS technology can be used to non-destructively analyze the chemical composition of underground rocks and minerals, helping geologists to better understand the composition and properties of underground resources, thus providing better guidance for geological exploration and development. In recent years, scholars at home and abroad have been exploring LIBS technology constantly, and through improving the detection system and optimizing laser pulse parameters, high sensitivity LIBS analysis at extremely low concentration has been achieved. By using finer spectral lines, higher sampling rate, and more precise laser pulse control, high resolution LIBS analysis at nanoscale has been achieved. The combination of LIBS technology with multi-spectral image processing technology can integrate information from multiple spectral channels to achieve a more comprehensive analysis of samples. However, the existence of matrix effects and spectral fluctuations always affects the accuracy of LIBS quantitative analysis, and poor reproducibility and high detection limits also need to be solved.OBJECTIVESTo improve the accuracy of quantitative analysis of complex matrix samples.METHODSA multi-layer classification model based on k-nearest neighbors (kNN) and support vector machine (SVM) algorithms was constructed to identify the rock type of samples. The samples were divided into two major categories of felsic rocks and mafic rocks using the kNN algorithm, and then six categories were formed by the SVM algorithm. Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. Then, appropriate pre-processing methods were adopted to improve the stability of spectral data for different elements in different rock types. Compared to the traditional standard curve quantitative method, using the pre-classification method can reduce the influence of different rock matrices on each other, thus reducing errors caused by the non-uniform matrix of samples.RESULTSDue to the influence of matrix effects, a single pre-processing method is not suitable for all elements in quantitative analysis. Therefore, in order to improve the accuracy and stability of quantitative analysis, different methods are used to pre-process the data. For different pre-processing methods, the R2 values of four elements in six types of rock samples are mostly greater than 0.90, as shown in Table 2. After pre-processing, the correlation coefficients of the four elements are significantly improved, and they are all higher than 0.99. The correlation coefficients of Si, Ca, Mg, and K elements in the test set after quantitative analysis are increased from 0.664, 0.638, 0.461, and 0.231 to 0.999, 0.994, 0.999, and 0.996, respectively. In addition, it can be seen from the analysis of the data that the traditional quantitative analysis model has poor stability. The average relative standard deviation (RSD) of Si, Ca, Mg, and K elements in the test set are 3.4%, 10.7%, 48.2%, and 90.8%, respectively, while the RSD of four elements in the multi-layer model are 1.5%, 5.2%, 10.3%, and 17.4%, which shows a significant improvement in stability compared to traditional quantitative analysis models. At the same time, it can be more intuitively evaluated by comparing the average relative error between the predicted value and the target value of each element in the test set. As shown in Table 3, the prediction performance of Si element in the multi-layer model is the best, with an average relative error of only 4.65%. Although the average relative error of the other three elements is over 10%, it is significantly improved compared to the traditional standard curve model.CONCLUSIONSBy utilizing a multi-layer classification model for preliminary categorization, standard rock samples that match the matrix are obtained. Subsequently, quantitative analysis models are developed for samples with similar matrices. Employing distinct preprocessing methods for different elemental compositions within various rock types helps mitigate spectral discrepancies caused by matrix effects, reduces spectral fluctuations and data noise, and enhances the accuracy and stability of quantitative analysis. Standard curve models are then established for each element, enabling quantitative analysis of Si, Ca, Mg, and K elements in six categories of rock samples. Results demonstrate a notable improvement in the accuracy of quantitative analysis compared to traditional standard curve models. This model not only diminishes the impact of matrix effects on quantitative analysis but also corrects instabilities arising from hardware, environmental conditions, and sample variations. Furthermore, it alleviates the workload of data analysis, simplifying the analytical process and thereby boosting efficiency. However, the current multi-layer quantitative analysis model still exhibits some deviations in regard to different elements. In the future, a potential avenue is to consider integrating various algorithms to establish preliminary classification models, aiming for even better quantitative analysis outcomes

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages