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Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi'an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi'an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions. [ABSTRACT FROM AUTHOR]

The trajectory tracking control problem for wheeled mobile robot (WMR) subject to generalized torque constraints is studied in this paper. First, a more general model is obtained by taking the displacement between the centre of mass of the WMR and the midpoint of the driving wheels into consideration. Then, a virtual velocity controller and a generalized torque controller are designed based on a new Lyapunov function. Due to the advantages of the new Lyapunov function, the stability of the trajectory tracking error system can be derived directly and the constraint of the initial tracking errors is removed. Less conservative conditions for tuning the controller parameters to satisfy the saturation constraints are also derived. Finally, some numerical examples are given to show the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

In order to improve the operational efficiency of medical institutions and build a more complete and efficient medical system, the Chinese government is vigorously promoting the reform of hierarchical diagnosis and treatment. We constructed a multi-factor composite selection weight to characterize the residents' medical treatment behavior in the context of hierarchical diagnosis and treatment. By combining the weight with the two-step floating catchment area method, we analyzed the spatial variation characteristics of residents' accessibility to medical care under different scenarios. Results show that the referral rate between medical institutions increases gradually along with the occurrence of public health events. When there is a major public health event, the proportion of the population transferred from the primary medical institutions to the county hospitals and the county hospitals to the municipal hospitals exceeded 65%. In three scenarios, the spatial pattern of accessibility shows obvious consistency and local differences. Among the three-tier medical institutions in China, the service capacity of county hospitals is poor, and the contribution rate of accessibility is less than 20%. The results clearly show the spatial differences in the accessibility of Chinese residents in different scenarios and the impact of public health events on accessibility. This research can provide a reference for the layout optimization of medical resources in the future. [ABSTRACT FROM AUTHOR]

Background: As the emerging economies, the BRICS (Brazil, Russia, India, China, and South Africa) shared 61.58% of the global chronic respiratory diseases (CRD) deaths in 2017. This study aimed to assess the secular trends in CRD mortality and explore the effects of age, period, and cohort across main BRICS countries. Methods: Data were obtained from the Global Burden of Disease Study (GBD) 2019 and analyzed using the age-period-cohort (APC) model to estimate period and cohort effects between 1990 and 2019. The net drifts, local drifts, longitudinal age curves, period/cohort rate ratios (RRs) were obtained through the APC model. Results: In 2019, the CRD deaths across the BRICS were 2.39 (95%UI 1.95 to 2.84) million, accounting for 60.07% of global CRD deaths. Chronic obstructive pulmonary disease (COPD) and asthma remained the leading causes of CRD deaths. The age-standardized mortality rates (ASMR) have declined across the BRICS since 1990, with the most apparent decline in China. Meanwhile, the downward trends in CRD death counts were observed in China and Russia. The overall net drifts per year were obvious in China (-5.89%; -6.06% to -5.71%), and the local drift values were all below zero in all age groups for both sexes. The age effect of CRD presented increase with age, and the period and cohort RRs were following downward trends over time across countries. Similar trends were observed in COPD and asthma. The improvement of CRD mortality was the most obvious in China, especially in period and cohort effects. While South Africa showed the most rapid increase with age across all CRD categories, and the period and cohort effects were flat. Conclusions: BRICS accounted for a large proportion of CRD deaths, with China and India alone contributing more than half of the global CRD deaths. However, the declines in ASMR and improvements of period and cohort effects have been observed in both sexes and all age groups across main BRICS countries. China stands out for its remarkable reduction in CRD mortality and its experience may help reduce the burden of CRD in developing countries. [ABSTRACT FROM AUTHOR]

The recursive secure state estimator design issue is investigated in this article for a class of dynamic coupled networks (DCNs) through the encoding-decoding scheme. The random variables distributed over specified intervals are utilized to depict the stochastically varying coupling strengths. For the sake of facilitating the data transmission, saving network resources and cutting down security risks, the two-description coding scheme (TDCS) is employed in the communication channels. Based on the TDCS, the encoders are installed at two independent communication channels, and the packet loss phenomena are considered in two encoder-to-decoder channels. The random denial of service (DoS) attack is taken into account when the decoded data are transmitted to the estimator through the shared communication networks. By recursively dealing with two coupled backward Riccati difference equations (CBRDEs), the desired finite-horizon H ∞ state estimator gain matrix (EGM) can be determined. Finally, a numerical example is exhibited to illustrate the efficiency of the designed finite-horizon secure state estimator. [ABSTRACT FROM AUTHOR]

Background: Emergency department crowding is an obstacle in the process of obtaining emergency care services, which will lead to the increase of time cost. Most studies focused on the direct access to emergency medical resources, and few studies took the crowding of hospital emergency department as an evaluation index to reflect the convenience of obtaining emergency medical resources. It is a significance for the identification of areas with insufficient access to emergency service resources with this method. Methods: This paper utilizes the improved potential model and the inverted Two-Step Floating Catchment Area method, combined with network map API service data to evaluate response time, delivery time and waiting time (for emergency department crowding) spent in different residential areas of Xi'an City in the process of emergency. Meanwhile, the vulnerable regions of gaining emergency medical resources are identified through the comprehensive analysis of the three stages of emergency. Results: The studies show that the residents in built-up area are more convenient to get ambulance service and arrive at care hospitals than those in suburban areas, but they may face greater hospital crowdedness. Although suburban residents are faced with low hospital crowdedness, they spend more time on getting ambulances and going to care hospitals. The accessibility of emergency medical resources varies greatly among residents in different regions, with 5.38% of the residents were identified in the high-risk area distributing in suburban residential areas in the south of the city center, 21.92% in the medium risk area in the southern mountainous areas and the periphery of the core suburban areas of the city, and 46.11% in the low-risk area which are mainly distributed in built-up areas in gaining emergency medical services. Conclusions: Obviously, getting an ambulance and arriving at the nearest hospital quickly shows that it is conducive to access to emergency resources. However, the impact of hospital emergency crowding can not be ignored, especially in the area surrounded by high-grade hospitals in the central area of the city. In considering the spatial layout of emergency stations and emergency hospitals, the dislocation distribution of hospitals at different levels should be reasonably adjusted to balance the equity of residents in obtaining emergency medical resources. [ABSTRACT FROM AUTHOR]

With global warming, the great changes in the patterns of plant growth have occurred. The conditions in early spring and late autumn have changed the process of vegetation photosynthesis, which are expected to have a significant impact on net primary productivity (NPP) and affect the global carbon cycle. Currently, the seasonal response characteristics of NPP to phenological changes in dryland ecosystems are still not well defined. This article calibrated and analyzed the normalized difference vegetation index (NDVI) time series of Advanced Very-High-Resolution Radiometer (AVHRR) data from 1982 to 2015 in the Loess Plateau, China. The spatial and temporal distributions of vegetation phenology and NPP in the Loess Plateau under semihumid and semiarid conditions were investigated. The seasonal variation in the NPP response to vegetation phenology under the climate change was also analyzed. The results showed that, different from the northern forest, there was distinct spatial heterogeneity in the effect of climate change on the dynamic change in vegetation growth in the Loess Plateau: 1) an advance of the start of the growing season (SOS) and a delay of the end of the growing season (EOS) significantly increased the NPP in spring and autumn, respectively, in the humid southeast; 2) in the arid northwest, the NPP did not significantly increase in spring and autumn but significantly decreased in summer. [ABSTRACT FROM AUTHOR]

Background: As the emerging economies, the BRICS (Brazil, Russia, India, China, and South Africa) shared 61.58% of the global chronic respiratory diseases (CRD) deaths in 2017. This study aimed to assess the secular trends in CRD mortality and explore the effects of age, period, and cohort across main BRICS countries.Methods: Data were obtained from the Global Burden of Disease Study (GBD) 2019 and analyzed using the age-period-cohort (APC) model to estimate period and cohort effects between 1990 and 2019. The net drifts, local drifts, longitudinal age curves, period/cohort rate ratios (RRs) were obtained through the APC model.Results: In 2019, the CRD deaths across the BRICS were 2.39 (95%UI 1.95 to 2.84) million, accounting for 60.07% of global CRD deaths. Chronic obstructive pulmonary disease (COPD) and asthma remained the leading causes of CRD deaths. The age-standardized mortality rates (ASMR) have declined across the BRICS since 1990, with the most apparent decline in China. Meanwhile, the downward trends in CRD death counts were observed in China and Russia. The overall net drifts per year were obvious in China (-5.89%; -6.06% to -5.71%), and the local drift values were all below zero in all age groups for both sexes. The age effect of CRD presented increase with age, and the period and cohort RRs were following downward trends over time across countries. Similar trends were observed in COPD and asthma. The improvement of CRD mortality was the most obvious in China, especially in period and cohort effects. While South Africa showed the most rapid increase with age across all CRD categories, and the period and cohort effects were flat.Conclusions: BRICS accounted for a large proportion of CRD deaths, with China and India alone contributing more than half of the global CRD deaths. However, the declines in ASMR and improvements of period and cohort effects have been observed in both sexes and all age groups across main BRICS countries. China stands out for its remarkable reduction in CRD mortality and its experience may help reduce the burden of CRD in developing countries. [ABSTRACT FROM AUTHOR]

The occurrence of drought is related to complicated interactions between many factors, such as precipitation, temperature, evapotranspiration and vegetation. In this study, the relationships between drought and precipitation, temperature, vegetation and evapotranspiration were investigated with a random forest (RF), and a new combined drought monitoring index (CDMI) was constructed. The effectiveness of the CDMI in monitoring drought in Shaanxi Province was verified by the in situ 1 ∼ 12-month standardized precipitation index (SPI); relative soil moisture (RSM) and four other commonly used remote sensing drought monitoring indices. The results show that CDMI is more correlated with the SPI and RSM than the four indices. Moreover, the spatial distributions of drought for the CDMI and RSM are similar. Therefore, the CDMI can be used to monitor droughts in Shaanxi Province, and machine learning can explore the relationships between various factors and establish a drought index without knowledge of the causal mechanisms of these factors. [ABSTRACT FROM AUTHOR]

Although conventional two-dimensional model predictive iterative learning control (2D-MPILC) based on an extended non-minimum state space (ENMSS) model can avoid designing an observer, it only relies on feedback to passively deal with time delay. This passive treatment for time delay hinders the further improvement of control performance. To address this shortcoming, a two-dimensional model predictive iterative learning control strategy based on the set point learning (2D-SPL-MPILC) is proposed. Firstly, a set point learning strategy is developed to improve the ability to deal with time delay. Based on the error of the previous batch, the set point learning strategy perceives the system dynamics in advance, and then outputs this advance perception in the form of the predictive set point. Secondly, a novel ENMSS model is constructed on the basis of the predictive tracking error between the predictive set point and the actual output. Since the predictive tracking error integrates the predictive set point, this novel ENMSS model has certain predictive ability. Finally, based on this novel ENMSS model, a novel two-dimensional model predictive iterative learning control (2D-MPILC) method, which is called 2D-SPL-MPILC method, is designed. Because this controller contains the perception of future process dynamics, it can reduce the impact of time delay and improve the control performance. The case studies on the packing pressure control in injection molding process and batch reactors demonstrate the effectiveness of the presented 2D-SPL-MPILC strategy. • a set point learning strategy is developed. • a novel extended non-minimum state space (ENMSS) model is developed. • a two-dimensional model predictive iterative learning control (2D-MPILC) method is designed. [ABSTRACT FROM AUTHOR]

Net primary production (NPP) can regulate global climate change and carbon balance. Although scholars have qualitatively studied the influencing factors of NPP, few have quantified the contribution of different degrees of drought aggravation or mitigation and major land-use changes to NPP changes. Based on the temporal and spatial characteristics of NPP for 2000–2015 in the Chinese Loess Plateau, we quantified the contribution of drought, land use and land cover change (LUCC), and hydrothermal conditions to changes in NPP. Particularly, we analyzed the contribution of major land-use change and different drought levels to NPP. Our results showed that the 15-years average NPP was approximately 227 gC/m2 and decreased from southeast to northwest. Overall, NPP showed a linear increasing trend over the 15-years period. The results suggested that changes in hydrothermal conditions had the strongest impact on NPP (~61%), followed by drought (~33%), and land use and land cover change had the weakest impact (~1.4%). In particular, ~13% of the NPP decreases was affected by light drought aggravation, ~10% of the NPP decreases was affected by moderate drought aggravation, and ~0.3% was affected by the conversion of cropland to grassland or non-NPP main production land. Moreover, ~12.7% of the NPP increase was affected by light drought alleviation, ~9.4% was affected by moderate drought alleviation, and ~1.1% was affected by the conversion of grassland to cropland or forestland. The mechanisms underlying the effect of drought and land-use change on NPP were clarified and provide an important reference value for future research on the carbon cycle and regional ecological environmental restoration. [ABSTRACT FROM AUTHOR]

This article proposes an improved two-degree-of-freedom Smith predictive control method for typical industrial control systems. Smith predictive control is a classic control strategy designed for systems with pure lag. As an extension of Smith predictive control, internal model control can solve the time-delay problem effectively and make the controller design simple. Based on the two control algorithms, an enhanced control method with modified control structure is developed in this paper. In the design scheme, the set-point tracking and the disturbance rejection characteristics are decoupled, such that the set-point tracking and disturbance rejection controllers can be designed independently to achieve better control performance. The obtained control strategy possesses simple and convenient parameter tuning procedures. The validity of the proposed scheme is verified through theoretical analysis and simulation comparison with other control methods, and the results indicate that the proposed strategy shows better performance on set-point tracking and disturbance rejection. [ABSTRACT FROM AUTHOR]

This article concentrates on the finite-time nonfragile distributed dissipative filtering issue for time-varying switched stochastic systems (SSSs) with state saturations over wireless sensor networks based on FlexRay communication protocol. To effectively deal with the resource restriction problem of the public communication network and energy consumption of the sensor nodes, the FlexRay communication protocol, including the Round-Robin protocol (RRP) and weighted try-once-discard protocol (WTODP), is introduced to schedule the data transmission of each sensor node. In addition, the phenomenon of randomly occurring gain variations (ROGVs) of filter parameters, characterised by the Bernoulli distributed random variables, is taken into consideration for the implementation of desired filter. A sufficient condition under the average dwell time (ADT) restriction is presented to guarantee the mean-square exponential stability and stochastically dissipative property of the augmented filtering error system (AFES) in a finite horizon. Moreover, the gains of the dissipativity-based filters are achieved by solving recursive linear matrix inequalities (RLMIs). Finally, an illustrative example is provided to exhibit the effectiveness of the designed filter. [ABSTRACT FROM AUTHOR]

This study investigated the impact of epidemiologic and sociodemographic changes in tracheal, bronchus, and lung cancer associated with residential radon, solid fuels, and particulate matter. What are the influencing factors of tracheal, bronchus, and lung cancer disease burden attributable to the three pollutants? Data were obtained from the Global Burden of Disease 2019. Age-standardized mortality rate (ASMR) and sociodemographic index (SDI) values were collected from 21 regions, and restricted cubic splines and quantile regression were used to investigate the relationship between ASMR or age-standardized disability-adjusted life years rate (ASDR), and SDI. Additionally, five countries with different SDIs were selected, and the Bayesian age-period-cohort model was used to predict the ASMR trends from 2020 to 2030. High SDI quintiles were associated with increased residential radon pollution. The disease burden attributed to these three pollutants was particularly severe in the middle SDI quintiles. Older adults aged 80 to 89 years had the highest age-specific mortality, and the disease burden was greater in male patients than in female patients with these cancers attributed to the pollutants. The highest ASMR attributable to particulate matter when the SDI was 0.7. As the SDI increased, the disease burden caused by radon increased, whereas the burden caused by solid fuels decreased. Projections have indicated a rise in the death burden in patients with this cancer from particulate pollution in China, India, and Uganda over the next decade. The disease burden of tracheal, bronchus, and lung cancer attributed to the three pollutants was influenced by SDI, sex, and age. Older men are more susceptible to be affected. More preventive interventions may be required for men at younger ages to reduce the high death burden of older men. However, it is necessary to give due attention to women in specific countries in the future. [ABSTRACT FROM AUTHOR]

Purpose: Assessing the mortality rates associated with tobacco-related oral cancer (OC) is crucial for effective allocation of resources within healthcare and economic systems. Methods: In this study, data from the Global Burden of Disease Study (GBD) 2019 were utilized to analyze the burden of tobacco-attributable OC in China, the United States (US), and India from 1990 to 2019. Descriptive statistics and an age-period-cohort model were employed to examine and compare the effects on OC mortality. Results: 1. Attributable to tobacco, the deaths remained stable in the US, but increased in China and India. The trend of age-standardized mortality rate of OC increased in China, and decreased in the US and India, whereas the rate in India was the highest. 2. According to the APC model, the risk of death increased with age in all three countries. The period and later birth cohort effects were identified as risk factors in China and India, while in the US, the previous cohorts were identified as a risk factor. Except for India, males faced higher death risk than females in China and the US. Conclusions: The burden of OC attributable to tobacco remains substantial in China and India. Public health officials in these countries should implement prevention and treatment strategies for OC, and interventions aimed at regulating the tobacco industry. The elderly is at an elevated risk for OC, and medical resources and policies should be directed toward this population. The successes experience in tobacco control and OC prevention in the US may serve as a model for other countries. [ABSTRACT FROM AUTHOR]

The hierarchical diagnosis and treatment reform of China can guide residents to seek medical treatment in an orderly manner and improve access to medical treatment. Most existing studies on hierarchical diagnosis and treatment used accessibility as the evaluation index to determine the referral rate between hospitals. However, the blind pursuit of accessibility will cause the problem of uneven utilization efficiency of hospitals at different levels. In response to this, we constructed a bi-objective optimization model based on the perspective of residents and medical institutions. This model can give the optimal referral rate for each province considering the accessibility of residents and the utilization efficiency of hospitals, to improve the utilization efficiency and equality of access for hospitals. The results showed that the applicability of bi-objective optimization model is good, and the optimal referral rate based on the model can ensure the maximum benefit of the two optimization goals. In the optimal referral rate model, residents' medical accessibility is relatively balanced overall. In terms of obtaining high-grade medical resources, the accessibility is better in the eastern and central regions, but poorer in the western China. According to the current allocation of medical resources in China, the medical tasks undertaken by high-grade hospitals account for 60%–78%, which are still the main force of medical services. In this way, there is a big gap in realizing the "serious diseases do not leave the county" goal of hierarchical diagnosis and treatment reform. • We constructed a bi-objective optimization model to give the optimal referral rate. • The model considered the accessibility and the utilization efficiency of hospitals. • A method is proposed to calculate utilization efficiency of hospitals. • High-grade hospitals are still the main force of medical services under the HDTS. [ABSTRACT FROM AUTHOR]

A novel design of robust constrained model predictive tracking control is proposed for systems with polytopic description. Unlike the conventional robust model predictive tracking control, the proposed method adopts an improved state space model in which the process state variables and tracking error are combined such that they can be tuned in the cost function optimization separately. Based on the proposed new model, more degrees of freedom are provided for the subsequent controller design, which leads to improved control performance. The relevant feasibility and robust stability issues are further discussed, and the effectiveness of the proposed approach is tested on the control of a system which is open-loop unstable with dead time and reverse responses. [ABSTRACT FROM AUTHOR]

The assessment of the accessibility for medical resources is of great significance for understanding the distribution characteristics and optimizing the space allocation of medical resources. This paper incorporated the probability statistical data of actual medical treatment choice behavior of residents into the formulation of accessibility. We constructed a health facility accessibility index combined the travel time with waiting time and an improved three-step floating catchment area method to evaluate the accessibility of outpatient and inpatient treatment for residents. Results showed the accessibility of outpatient and inpatient treatment has significant geographical differentiation characteristics and presents a distribution pattern of high in the eastern and central China and low in the western. The outpatient medical service was available for residents, which there are more than 85% of the population having access to medical services within 30min.The accessibility of inpatient treatment presents a radiological distribution model with provincial capital city as the core, in which the spatial allocation of high-quality medical resources is not balanced and the regional difference is obvious. This study demonstrated the geographical differentiation characteristics of spatial distribution for the accessibility of medical resources in China, which can provide targeted proposals according to medical institutions level. • Evaluating the spatial accessibility from outpatient and inpatient medical treatment. • A health facility accessibility index and the improved three-step floating catchment area method were employed. • The policy-oriented matrix of medical services was constructed to provide policy recommendations for the provinces in China. [ABSTRACT FROM AUTHOR]

This paper studies the regional pole placement problem for a class of T–S fuzzy systems. Firstly, a definition for the fuzzy systems to be D stable is given from the viewpoint of Lyapunov functions. Then a new sufficient condition is proposed to guarantee all the poles of the fuzzy systems located within a prescribed LMI region by using the fuzzy Lyapunov functions method and introducing some free matrices. And then the controller design approach is given by solving a set of LMIs. Finally, numerical examples are given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The finite-time stability analysis of discrete-time fuzzy Hopfield neural networks is studied in this paper. Firstly, the concept of finite-time stability is generalized to the fuzzy neural networks. And then by the Lyapunov approach and linear matrix inequality technique, a sufficient condition for the system to be finite-time stable is proposed, based on which, the finite-time stability condition for the system with norm bounded uncertainties is also given. Finally a numerical example is given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The geometric registration of mountainous remote sensing images is always a challenging project, as terrain fluctuations increase the complexity. Deep learning, with its superior computing power and data-driven nature, promises to solve this problem. However, the lack of an appropriate dataset limits the development of deep learning technology for mountainous remote sensing image registration, which it still an unsolved problem in photogrammetry and remote sensing. To remedy this problem, this paper presents a manually constructed imagery dataset of mountainous regions, called the MID (mountainous imagery dataset). To create the MID, we use 38 images from the Gaofen-2 satellite developed by China and generated 4093 pairs of reference and sensed image patches, making this the first real mountainous dataset to our knowledge. Simultaneously, we propose a fully unsupervised, convolutional-network-based iterative registration scheme for the MID. First, the large and global deformation of the reference and sensed images is reduced using an affine registration module, generating the coarse alignment. Then, the local and varied distortions are learned and eliminated progressively using a hybrid dilated convolution (HDC)-based encoder–decoder module with multistep iterations, achieving fine registration results. The HDC aims to increase the receptive field without blocking the artifacts, allowing for the continuous characteristics of the mountainous images of a local region to be represented. We provide a performance analysis of some typical registration algorithms and the developed approach for the MID. The proposed scheme gives the highest registration precision, achieving the subpixel alignment of mountainous remote sensing images. Additionally, the experimental results demonstrate the usability of the MID, which can lay a foundation for the development of deep learning technology in large mountainous remote sensing image registration tasks. [ABSTRACT FROM AUTHOR]

• The fruit color changes of different varieties in different periods were measured. • The contents of three main pigments were determined, and their accumulation with the change of fruit color was clarified. • The expression patterns of genes in carotenoid synthesis pathway was analyzed and several important genes were screened. • The correlation analysis of fruit color, pigment and related genes of ornamental pepper was carried out. To understand better the mechanisms of the pigment accumulation in ornamental pepper, the fruit color, pigment and expression of carotenoid biosynthetic genes were investigated. The test materials were divided into three categories. The first category included cultivars B3, J1, J2 and Q3, the second were M3, M3′, W8 and WU, C2, S1, W3 and W4 belonged to the third category. The pigment changes during ripening were characterized by loss of chlorophyll and anthocyanin, and a rapid accumulation of carotenoids. It was found that GGPS, PSY, CRTZ -2 and CCS genes have abundant transcription during the accumulation of carotenoids in ornamental pepper, which have a more important regulatory function. Correlation analysis were conducted between fruit color, pigment and expression of genes, it showed that there were significant correlation between key genes of carotenoid biosynthetic pathway, among which PSY was highly correlated with CCS and CRTZ- 2 , CCS was highly correlated with CRTZ- 2. Chromaticity values were negatively correlated with anthocyanin content in fruits, and the correlation between a* and carotenoid content was significantly higher. The information will be benefit for exploring the carotenoid regulation mechanism of ornamental pepper, and providing theoretical for fruit color breeding of ornamental pepper. [ABSTRACT FROM AUTHOR]

The variation of soil moisture (SM) is a complex and synthetic process, which is impacted by numerous factors. The effects of these factors on soil moisture are dynamic. As a result, the relationship between soil moisture and explanatory variables varies with time and season. This kind of change should be considered in obtaining fine spatial resolution soil moisture products. We chose a study area with four distinct seasons in the temperate monsoon region. In this research, we established seasonal downscaling models to avoid the influence of seasonal differences. Precipitation, land surface temperature, evapotranspiration, vegetation index, land cover, elevation, slope, aspect and soil texture were taken as explanatory variables to produce fine spatial resolution SM. SM products derived from Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) were downscaled with the help of machine learning algorithms. We compared three machine learning algorithms of random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN) to determine the most suitable algorithm for this study. The results show that season-based downscaling is even better than continuous time series. In the analysis of seasonal differences, precipitation plays a dominant role, but its contribution rate is different in each season. Moreover, the influence of vegetation is more prominent in winter, while the influence of terrain is more important in the other three seasons. It could be noted that the accuracy of the RF model is the best among three machine learning algorithms, and the RF-downscaled products have superior matching performance to both AMSR (AMSR-E and AMSR2) SM products and in-situ measurements. The analysis indicates considering seasonal difference and the application of machine learning has high potential for spatial downscaling in remote sensing applications. [ABSTRACT FROM AUTHOR]

Vegetation phenology is highly sensitive to climate change, and the phenological responses of vegetation to climate factors vary over time and space. Research on the vegetation phenology in different climatic regimes will help clarify the key factors affecting vegetation changes. In this paper, based on a time-series reconstruction of Moderate-Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data using the Savitzky–Golay filtering method, the phenology parameters of vegetation were extracted, and the Spatio-temporal changes from 2001 to 2016 were analyzed. Moreover, the response characteristics of the vegetation phenology to climate changes, such as changes in temperature, precipitation, and sunshine hours, were discussed. The results showed that the responses of vegetation phenology to climatic factors varied within different climatic regimes and that the Spatio-temporal responses were primarily controlled by the local climatic and topographic conditions. The following were the three key findings. (1) The start of the growing season (SOS) has a regular variation with the latitude, and that in the north is later than that in the south. (2) In arid areas in the north, the SOS is mainly affected by the temperature, and the end of the growing season (EOS) is affected by precipitation, while in humid areas in the south, the SOS is mainly affected by precipitation, and the EOS is affected by the temperature. (3) Human activities play an important role in vegetation phenology changes. These findings would help predict and evaluate the stability of different ecosystems. [ABSTRACT FROM AUTHOR]

To achieve the goal of worldwide sustainable protection and utilization of terrestrial ecosystems, it is necessary to quantitatively assess the implementation of Sustainable Development Goal 15 (SDG 15) at all administrative levels, especially at the grass-roots level, using the indicator framework of the UN SDGs. However, in the SDG 15 indicator system, the relationship between goal and indicators is ambiguous, and the results of the indicators cannot be visualized to show the differences within regions. Moreover, its design scale is country-oriented, which suggests that the indicator system cannot be applied directly to the county levels. In light of these issues, this paper used four modalities of localization to form an indicator system of localization, and applied it in the quantitative evaluation of meeting the objectives of SDG 15 in Deqing County, China. The localized indicator system for county level based on geospatial information included six indicators, which were clustered into three categories: sustainable forest management, halt and reverse land degradation, and conservation of biodiversity. By comparing and evaluating the quantitative results of SDG 15 in Deqing, 70% of the comparable indicators in the localization indicator system were at the forefront of those in China or the world. The results showed that grouped analysis of the targets and indicators could clarify the relationship between the implications of the goal and indicators, and the indicator system based on the geographic information was conducive to displaying the spatial distribution of the results of the indicators and clarifying the internal differences. [ABSTRACT FROM AUTHOR]

Efficient utilization of land resources is fundamental for achieving sustainable urban development. Utilizing the urban land use efficiency (ULUE) framework for production-living-ecological (PLE) functions, this study establishes three key indicators to evaluate the sustainable development status of each dimension. The indicator system was applied to 433 Chinese cities to analyze the temporal and spatial changes in urban sustainable development from 2000 to 2020. Research findings reveal significant disparities in sustainable urban development levels across Chinese regions from 2000 to 2020, following a consistent trend: Eastern > Western > Central > Northeast. The ULUE for living and production functions in Chinese cities experienced an obvious decline from 2015 to 2020. This indicates that urban land expansion in most Chinese cities surpassed population growth, accompanied by a noticeable reduction in economic growth rates. Since 2010, the ULUE for ecological function has improved significantly in Eastern region, reflecting a shift in development priorities towards a green approach rooted in ecological conservation principles. However, the ULUE in Northeastern cities has declined, placing this region at a competitive disadvantage due to the dual challenges of declining population and economic recession. Since 2015, urban land expansion in Central Chinese cities has significantly outpaced other regions, resulting in extensive land use, posing challenges to resource planning and management. Smaller cities, in contrast to their larger counterparts, face a lower overall sustainability level and encounter more acute challenges related to population migration and economic transition. The analysis offers valuable insights and policy recommendations to enhance sustainability in developing regions. • Efficient urban land use contributes to sustainable urban development. • Introduce an assessment indicator system for Urban Land Use Efficiency (ULUE). • Uncover spatial and temporal disparities in sustainable urban development. • Examine regional disparities in sustainable development among various Chinese cities. [ABSTRACT FROM AUTHOR]

Cerebrovascular segmentation based on phase-contrast magnetic resonance angiography (PC-MRA) provides patient-specific intracranial vascular structures for neurosurgery planning. However, the vascular complex topology and spatial sparsity make the task challenging. Inspired by the computed tomography reconstruction, this paper proposes a Radon Projection Composition Network (RPC-Net) for cerebrovascular segmentation in PC-MRA, aiming to enhance distribution probability of vessels and fully obtain the vascular topological information. Multi-directional Radon projections of the images are introduced and a two-stream network is used to learn the features of the 3D images and projections. The projection domain features are remapped to the 3D image domain by filtered back-projection transform to obtain the image-projection joint features for predicting vessel voxels. A four-fold cross-validation experiment was performed on a local dataset containing 128 PC-MRA scans. The average Dice similarity coefficient, precision and recall of the RPC-Net achieved 86.12%, 85.91% and 86.50%, respectively, while the average completeness and validity of the vessel structure were 85.50% and 92.38%, respectively. The proposed method outperformed the existing methods, especially with significant improvement on the extraction of small and low-intensity vessels. Moreover, the applicability of the segmentation for electrode trajectory planning was also validated. The results demonstrate that the RPC-Net realizes an accurate and complete cerebrovascular segmentation and has potential applications in assisting neurosurgery preoperative planning. • A Radon Projection Composition Network for cerebrovascular segmentation in phase-contrast magnetic resonance angiography. • Multi-directional projections are introduced to strengthen the sparse 3D vascular representation and topological connectivity. • The mutual conversion between the 3D image and projection domains is realized by Radon transform and its inverse transform. • A two-stream network is utilized to extract and fuse the features of the 3D image and projection domains. [ABSTRACT FROM AUTHOR]

This paper investigates the sliding mode control problem for networked control systems, which are influenced by the non-ideal network environment, such as network-induced delays, packet dropouts and quantization errors. The states of the system are assumed to be unavailable, and an observer is designed to estimate the state of the system, based on which a sliding mode controller is given to guarantee the closed-loop system to be stable. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space. Finally, a numerical example is given to illustrated the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper considers linear quadratic (LQ) optimal control problems based on state observer for a class of discrete-time system over lossy data network. Both sensor data and control commands are transmitted by the same network. And the packets may be randomly lost according to the Bernoulli distribution. In the infinite horizon expected total cost we derive expressions for computing the corresponding controller gain. And the hold-input compensation strategy is applied to the closed system in which the previous control signal is used when packet dropped. Moreover, illustrative example is presented to demonstrate the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Background: Micromobility sharing platforms have involved skyrocketing numbers of users in multiple countries since 2010. However, few studies have examined the overall impact of the growing micromobility market on road injuries. Method: We use road injury data from the Global Burden of Disease Study database to examine the effect of age, period, and cohort on micromobility injury-related deaths and incidence. We compared four countries that vary in demographic background and road infrastructure. By comparing the countries, we analyzed the relationship between the trends in road injuries and these factors. Results: We found an overall upward trend in micromobility injuries. A higher risk of micromobility-related injuries was witnessed in China and the US in 2015-2019, and people older than 45 showed a growing micromobility-related mortality and incidence rate in China, India, and the US. Cohorts after 1960 showed higher micromobility injury incidence risks in China and India, but the population born after 1990 in India showed a slightly lower risk compared to those before it. Conclusions: The boosted usage of micromobility devices explains these increasing trends. Road infrastructure and separated traffic ease the collisions from micromobility devices. The overall situation calls for improvement in legislation as well as road infrastructure. [ABSTRACT FROM AUTHOR]

Background: Micromobility sharing platforms have involved skyrocketing numbers of users in multiple countries since 2010. However, few studies have examined the overall impact of the growing micromobility market on road injuries.Method: We use road injury data from the Global Burden of Disease Study database to examine the effect of age, period, and cohort on micromobility injury-related deaths and incidence. We compared four countries that vary in demographic background and road infrastructure. By comparing the countries, we analyzed the relationship between the trends in road injuries and these factors.Results: We found an overall upward trend in micromobility injuries. A higher risk of micromobility-related injuries was witnessed in China and the US in 2015-2019, and people older than 45 showed a growing micromobility-related mortality and incidence rate in China, India, and the US. Cohorts after 1960 showed higher micromobility injury incidence risks in China and India, but the population born after 1990 in India showed a slightly lower risk compared to those before it.Conclusions: The boosted usage of micromobility devices explains these increasing trends. Road infrastructure and separated traffic ease the collisions from micromobility devices. The overall situation calls for improvement in legislation as well as road infrastructure. [ABSTRACT FROM AUTHOR]

This paper focuses on distributed filter design for Markov jump one-sided Lipschitz nonlinear systems over a sensor network by applying Round-Robin scheduling scheme. The nonlinear perturbations occur randomly and satisfy the so-called one-sided Lipschitz constraint that is more general than the conventional Lipschitz restraint. Two categories of exogenous noises, i.e., the persistent bounded noise and square additive noise in l 2 space, are taken into investigation, respectively. Meanwhile, the well-known Round-Robin scheduling protocol is employed to regulate the data transmission through the shared communication media. The exponential mean-square ultimate boundedness and stochastic bounded real lemma (BRL) are obtained for the filtering error dynamics, and then two distributed filters are correspondingly designed. Finally, an illustrative example shows the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Background The new coronavirus (COVID-19) rapidly resulted in a pandemic. We report the characteristics of patients with severe or critical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Wuhan city, China, and the risk factors related to infection severity and death. Methods We extracted the demographic and clinical data of 7283 patients with severe COVID-19 infection from designated Wuhan hospitals as of 25 February 2020. Factors associated with COVID-19 critical illness and mortality were analysed using logistic- and Cox-regression analyses. Results We studied 6269 patients with severe COVID-19 illness and 1014 critically ill patients. The median (IQR) age was 64 (53–71) years; 51.2% were male, 38.9% were retirees and 7.4% had self-reported histories of chronic disease. Up to the end of the study, 1180 patients (16.2%) recovered and were discharged, 649 (8.9%) died and the remainder were still receiving treatment. The number of daily confirmed critical cases peaked between 23 January and 1 February 2020. Patients with advanced age [odds ratio (OR), 1.03; 95% confidence intervals (CIs), 1.03–1.04], male sex (OR, 1.57; 95% CI, 1.33–1.86) and pre-existing diabetes (OR, 2.11), hypertension (OR, 2.72), cardiovascular disease (OR, 2.15) or respiratory disease (OR, 3.50) were more likely to be critically ill. Compared with those who recovered and were discharged, patients who died were older [hazard ratio (HR), 1.04; 95% CI, 1.03–1.05], more likely to be male (HR, 1.74; 95% CI, 1.44–2.11) and more likely to have hypertension (HR, 5.58), cardiovascular disease (HR, 1.83) or diabetes (HR, 1.67). Conclusion Advanced age, male sex and a history of chronic disease were associated with COVID-19 critical illness and death. Identifying these risk factors could help in the clinical monitoring of susceptible populations. [ABSTRACT FROM AUTHOR]

Abstract Objective The present study investigated the electroclinical features and epileptogenic networks of parietal operculum seizures (POS) by using stereoelectroencephalography (SEEG) intracerebral recordings. Methods Comprehensive presurgical evaluation data of seven patients with drug-resistant epilepsy with POS were analyzed retrospectively. Stereoelectroencephalography-recorded seizures were processed visually and quantitatively by using epileptogenicity mapping (EM), which has been proposed to ergonomically quantify the epileptogenicity of brain structures with a neuroimaging approach. Results Six patients reported initial somatosensory or viscerosensitive symptoms. Ictal clinical signs comprised frequently nocturnal hypermotor seizures and contralateral focal motor seizures, including tonic, tonic–clonic, or dystonic seizures of the face and limbs. Interictal and ictal scalp EEG provided information regarding lateralization in the majority of patients, but the discharges were widely distributed over perisylvian or "rolandic-like" regions and the vertex. Furthermore, two subgroups of epileptogenic network organization were identified within POS by SEEG, visually and quantitatively, using an EM approach: group 1 (mesial frontal/cingulate networks) was observed in three patients who mainly exhibited hypermotor seizures; group 2 (perisylvian networks) was observed in four patients who mainly exhibited contralateral focal motor seizures. Conclusion This study indicated that POS could be characterized by initial specific somatosensory sensations, followed by either frequently nocturnal hypermotor seizures or contralateral focal motor seizures. The distinctive seizure semiology depended on the organization of two primary epileptogenic networks. This article is part of the Special Issue "Individualized Epilepsy Management: Medicines, Surgery and Beyond. Highlights • Parietal operculum seizures were characterized by initial specific somatosensory sensations, followed by either frequently nocturnal hypermotor seizures or contralateral focal motor seizures. • Two subgroups of epileptogenic networks could be identified within parietal operculum seizures: mesial frontal/cingulate networks and perisylvian networks. [ABSTRACT FROM AUTHOR]

Highlights • Considerable differences were detected in drought trend during crop growing seasons. • A clear evolution of drought from summer and autumn to winter and spring is revealed. • The variations in SPEI could explain well the fluctuations of both crop yields. • Large differences exist in the responses of the crops to different lags of the SPEI. • Agricultural drought risk increased for wheat but decreased for maize over the NCP. Abstract The understanding of the impact of drought on the agricultural ecosystem is key to minimize drought-related yield losses. In this study, we analyzed the spatiotemporal characteristics of drought events in the North China Plain (NCP) based on the Standard Precipitation Evapotranspiration Index (SPEI) and investigated the impact of drought on winter wheat and summer maize yields. The results indicate an overall drought and wetting trend during the winter wheat growing season in the Henan and Shandong provinces, respectively. A significant wetting trend was detected in the NCP during the summer maize growing season at the 1-, 3-, 6-, and 12-month scales. Moreover, the drought episodes clearly reveal that the drought pattern has changed from summer and autumn droughts in the 1980s, to autumn and winter droughts in the 1990s, and to winter and spring droughts in the recent decade. Our results also show that the annual variations in the detrended SPEI can explain extensive fluctuations associated with both winter wheat and summer maize yields in the NCP. Furthermore, considerable differences in the relationship between agricultural crop yields and the SPEI time series with different lags were observed; the most correlated time scale increases with the advancement of the winter wheat growth stage. The correlations between the winter wheat standardized yield residuals series (SYRS) and detrended SPEI in three subperiods are consistently high and stable, whereas a substantial decrease of the correlation was observed at all time scales for summer maize, except for the 1-month lag. Our findings can help to better understand the drought evolution in the NCP in recent decades and hence provide stakeholders with references for the design of future drought mitigation plans. [ABSTRACT FROM AUTHOR]

There are rare researches on the correlations between metals exposure and serum uric acid (SUA), and existing research has only investigated the single metal effect. This study aimed to investigate the combined effects of metal mixtures on SUA and hyperuricemia using three statistical models. In this study, the data were extracted from three cycle years of the National Health and Nutrition Examination Survey (NHANES). Subsequently, generalized linear regression, weighted quantile regression (WQS) and Bayesian kernel machine regression (BKMR) models were fitted to evaluate the correlations between metal mixtures and both SUA and hyperuricemia. Of 3926 participants included, 19.13% participants had hyperuricemia. It was found using multi-metals generalized linear regression models that there were positive correlations of arsenic and cadmium with both outcomes. The negative correlations were identified in cobalt, iodine, and manganese with SUA concentration, whereas only cobalt was negatively correlated with hyperuricemia. Based on the WQS regression model fitted in positive direction, it was suggested that the WQS indices were significantly correlated with SUA (β = 6.64, 95% CI: 3.14–10.13) and hyperuricemia (OR = 1.25, 95% CI: 1.08–1.44); however, the result achieved by using the model fitted in negative direction indicated that the WQS indices were only significantly correlated with SUA (β = -5.29, 95%CI: 8.02 ∼ −2.56). With the use of the BKMR model, a significant increasing trend between metal mixtures and hyperuricemia was found, while no significant overall effect of metal mixtures on SUA was identified. The predominant roles of arsenic, cadmium, and cobalt in the change of SUA and hyperuricemia risk were found using all three models. The finding of this study revealed that metal mixtures might have a positive combined effect on hyperuricemia. The mutual verification of two outcomes using the three different models provided strong public health implications for protecting people from heavy metal pollution and preventing hyperuricemia. [Display omitted] • The effects of exposure to a variety of metals on serum uric acid were examined and studied. • Novel methods were adopted to deal with high-dimensional exposures and verify each other. • The single and combined effects of different metals were explored. [ABSTRACT FROM AUTHOR]

Mobile robots tracking a reference trajectory are constrained by the motion limits of their actuators, which impose the requirement for high autonomy driving capabilities in robots. This paper presents a model predictive control (MPC) scheme incorporating neural-dynamic optimization to achieve trajectory tracking of nonholonomic mobile robots (NMRs). By using the derived tracking-error kinematics of nonholonomic robots, the proposed MPC approach is iteratively transformed as a constrained quadratic programming (QP) problem, and then a primal–dual neural network is used to solve this QP problem over a finite receding horizon. The applied neural-dynamic optimization can make the cost function of MPC converge to the exact optimal values of the formulated constrained QP. Compared with the existing fast MPC, which requires repeatedly calculating the Hessian matrix of the Langragian and then solves a quadratic program. The computation complexity reaches O(n^3) , while the proposed neural-dynamic optimization contains O(n^2) operations. Finally, extensive experiments are provided to illustrate that the MPC scheme has an effective performance on a real mobile robot system. [ABSTRACT FROM PUBLISHER]

In view of the geographic annotation evaluation problem under the network map service environment, this paper extended the content of traditional geography annotation with the unstructured text form, and defined a broad geographic annotation. Using the putting process to model the annotation behavior, first of all, need confirm the geographic annotation text classification according to the frequency class, and establish a quantitative convergence description about the spatial correlation in the putting neighborhood according to the Voronoi k order adjacency relationship, proceed to the next step, build a putting model based on the geographical annotation types and type transformation combined with the geographic annotation text and the existing geographical annotation neighborhood. Through experimental verification, in the actual case of already known two typological geographic annotation sets, putting model can effectively evaluate the newly increased geographic annotation in a reasonable way. [ABSTRACT FROM AUTHOR]

B Correct funding b This work was funded by the National Natural Science Foundation of China (Grant No. 82173626, 81773552) and the National Key Research and Development Program of China (Grant No. 2018YFC1315302). Reference 1 Zhao Y. Demographics of road injuries and micromobility injuries among China, India, Japan, and the United States population: evidence from an age-period-cohort analysis. [Extracted from the article]