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• The impact of digital economy on green total factor productivity in China is investigated. • The evidence on digital economy from a policy perspective is further supplied. • The ordinary least squares model and fixed effects model are used to research simultaneously. • Technological innovation, industrial structure optimization and resource misallocation as the transmission channels are considered in mechanism test. Digital economy has become a major driver of the green transformation of the economy. The "National Big Data Comprehensive Pilot Zone" policy is taken as a quasi-natural experiment. The Difference-in-Differences model is employed to explore the impact of digital economy on green total factor productivity, and the heterogeneity of this impact is further explored. The mechanism test model is applied to investigate its indirect transmission mechanism. It is found that digital economy significantly enhances green total factor productivity. Further, the impact is larger and more significant in the mid-western, non-resource-based, and large cities, whereas it is smaller or insignificant in the eastern, resource-based, and small and medium-sized cities. Results of mechanism analysis show that digital economy enhances green total factor productivity through the transmission channels of technological innovation, industrial structure optimization, and resource misallocation. Policy recommendations are provided on the basis of these results to establish the environment and digital economy that are mutually beneficial. [ABSTRACT FROM AUTHOR]

At the end of 2022, the FIFA Men's World Cup took place in Qatar, and Argentina won its third title. Among thr worldwide supporters, India, a nation that had never played at the event, caught my attention. This study focuses on the state of Kerala, a mainly rural zone in Southwest India, and its massive support for Brazil and Argentina. After a literature review on football in India, the globalization of football, and team rivalries, the study analyzes a few English-written news articles to understand such manifestation of fandom in Kerala, and focuses on the giant cut-outs to find the answer as to why Brazil and Argentina are the teams who received the biggest support. It concludes that the said support has social, political, mediatic, identitarian, and religious roots. The article ends with the question as to how these manifestations differ in different countries, states, championships, and religions. [ABSTRACT FROM AUTHOR]

Green development is an important component of China's new development concept. Pilot Free Trade Zones (PFTZs), as "experimental fields" for promoting reform, deepening opening-up, and raising the level of an open economy, are important open areas for China to promote green development. However, existing related research is not extensive. This article takes PFTZs as quasi-natural experiments, with the Yangtze River Economic Belt (YREB) as the research area. Based on urban panel data from 2006 to 2020, using multi-period differences-in-differences and spatial differences-in-differences models, it explores the impact effects of PFTZs on urban green development and their potential mechanisms. The research findings indicate: (1) Overall, PFTZs significantly promote urban green development, with variations in impact effects due to different batches and locations of establishment. (2) Mechanism tests show that PFTZs mainly promote urban green development by stimulating technological innovation, industrial upgrading, and reducing government intervention. (3) From the perspective of spatial spillover effects, the establishment of PFTZs not only promotes the green development process in the host cities but also has a promoting effect on the green development of surrounding cities. [ABSTRACT FROM AUTHOR]

Context: The productivity of crops is influenced by the available net water balance, which relies on a complex interplay of edaphic and climatic factors. In this sense, rainfall is the leading water input for crop growth and yield, especially in water-scarce regions under semi-arid climates worldwide. Aims: This study aimed to define the optimum cropping calendar and the agroclimatic and agroecological zones for rainfed maize in the state of Ceará, which is predominantly located within the Brazilian semi-arid region, assuming different rainfall scenarios. Methods: We considered the subdivision of the study area into eight homogeneous precipitation regions according to the regional rainfall pattern. The climatic water balance for each region over two decades was calculated from historical weather data series, assuming three rainy scenarios: dry, regular, and rainy. The agroclimatic zoning was defined through the crop water balance results, soil classification, land use and occupation, slope and temperature, weighted through a multi-criteria decision analysis based on the Analytic Hierarchy Process. Key results: The recommended planting period was broader in rainy conditions. However, there may be some dry spells between two 10-day intervals of the calendar, which impair plant growth depending on their intensity. For the dry scenario, the agroclimatic zoning showed that the marginal water deficiency covered 96.55% of the study area. Conclusions: Rainfed maize cultivated under the semi-arid climate of Ceará state is viable in rainy conditions, partially restricted in regular years, and not recommended in dry years. Implications: This study emphasises the importance of climate monitoring in effective planning for rainfed maize cultivation in semi-arid regions. This study aimed to define the optimum cropping calendar and the agroclimatic and agroecological zones for rainfed maize (Zea mays L.) across Ceará state, situated within the Brazilian semi-arid region, assuming different rainfall scenarios: dry, regular, and rainy. The agroclimatic zoning was defined trough the crop water balance results. Our findings demonstrated that rainfed maize cultivated under the semi-arid climate of Ceará state is viable in rainy conditions, partially restricted in regular years, and not recommended in dry years. [ABSTRACT FROM AUTHOR]

The construction of well-facilitated farmland plays a vital role in ensuring national food security. Therefore, our study sought to facilitate the evaluation of farmland constructions and site selection. To achieve this, we conducted a case study in the Fengxiang District of Baoji City and developed a suitability evaluation model based on the ecological niche theory. This model considered four key factors: soil conditions, infrastructure construction, landscape patterns, and ecological constraints. Through a comparison of realistic and ideal ecological niches for various factors, we established a diagnostic model that identifies obstacle factors along with their respective obstacle degrees and ecological niches. By combining suitability, obstacle level, and transformation difficulty, we categorized different well-facilitated farmland construction priority zones, ranging from the most suitable and easiest to implement to the least suitable and more challenging. A total of 20,669 farmland patches were quantitatively evaluated and our findings indicated that the overall suitability of farmland construction in Fengxiang District is good. Cultivated land in the priority construction areas accounts for 47.49%, demonstrating high suitability for construction and the potential to reach optimal regional levels with minor adjustments. Our analysis revealed that the main obstacle factors in the landscape pattern dimension were mainly at the field scale, whereas the key obstacle factors in the ecological constraints dimension were related to irrigation water sources and slope gradients. Importantly, the evaluation results were generally consistent with the real situation, thus validating the scientific robustness and realistic nature of the ecological niche model for assessing construction suitability. Overall, our proposed approach can be used to effectively evaluate the suitability of regional well-facilitated farmland construction. These findings can serve as a solid basis for making scientifically informed decisions when selecting sites for well-facilitated farmland construction, contributing to its successful, efficient, and cost-effective implementation. [ABSTRACT FROM AUTHOR]

We examined dam-induced land use and land cover change (LULCC) detection in the Amerti-Nashe hydroelectric power reservoirs. These dams were constructed for a variety of purposes, primarily for irrigation in the lower reaches and hydropower generation in the upper reaches. The main objective of the study was to investigate dam-induced LULCC in the study area over the last 41 years. Satellite images were downloaded from the United States Geological Survey (USGS). The data from remote sensing satellite images were used to reflect the spatial variation in LULCC, and land surface temperature (LST) in the study areas near hydropower plants in the years 1985, 2003, and 2021. The supervised classification method is adopted, and the maximum likelihood rule is used as the parameter rule for image classification. The land use classification results show that grazing land, woody grassland, and cultivated land gradually decreased, which could be associated with the establishment of dams. But commercial farming, waterbodies, and built-up areas increased during these study periods. LST variations based on its relationship with Land Use Land Cover (LULC) in the area decreased after the dam was constructed, particularly in the irrigated lowland and places inundated by water from the reservoir in the upper stream. Generally, the construction of the Amerti-Nashe hydroelectric dam projects in the study area has changed land use type and LST both at a lower and upper stream. Therefore, hydropower development in the area needs strategic planning on how to minimize land use land cover change impacts on the environment and the local community. [ABSTRACT FROM AUTHOR]

As legal marijuana is emerging as an important component of cities across the United States, it is important to understand the factors that contribute to legal marijuana facility siting. Although land use and zoning are expected to determine where commercial marijuana facilities are located, if residential characteristics also enter siting considerations, some neighbourhoods may either bear the burden of undesired facilities or reap the benefits of legal marijuana, underscoring equitable considerations in marijuana facility siting. Thus, this study examines how neighbourhood change associated with locally unwanted land uses and gentrification influences the amount of retail marijuana facilities across three US cities: Denver, Colorado; Portland, Oregon; and Seattle, Washington. Using a series of Poisson-related regressions, this study finds that neighbourhood residential characteristics influence retail marijuana facilities in ways exceeding siting restrictions alone, like zoning. Notably, quantitative results suggest that there are fewer retail marijuana facilities in neighbourhoods experiencing locally unwanted land use-related change than non-locally unwanted land use neighbourhoods in Denver and Seattle; and more retail marijuana facilities in gentrified compared to non-gentrified neighbourhoods in Denver. Overall, these findings advance understanding of the connection between legal marijuana and neighbourhood changes and aim to influence guidelines for integrating legal marijuana facilities into communities. [ABSTRACT FROM AUTHOR]

Integrated crop–livestock systems (ICLS) are among the main viable strategies for sustainable agricultural production. Mapping these systems is crucial for monitoring land use changes in Brazil, playing a significant role in promoting sustainable agricultural production. Due to the highly dynamic nature of ICLS management, mapping them is a challenging task. The main objective of this research was to develop a method for mapping ICLS using deep learning algorithms applied on Satellite Image Time Series (SITS) data cubes, which consist of Sentinel-2 (S2) and PlanetScope (PS) satellite images, as well as data fused (DF) from both sensors. This study focused on two Brazilian states with varying landscapes and field sizes. Targeting ICLS, field data were combined with S2 and PS data to build land use and land cover classification models for three sequential agricultural years (2018/2019, 2019/2020, and 2020/2021). We tested three experimental settings to assess the classification performance using S2, PS, and DF data cubes. The test classification algorithms included Random Forest (RF), Temporal Convolutional Neural Network (TempCNN), Residual Network (ResNet), and a Lightweight Temporal Attention Encoder (L-TAE), with the latter incorporating an attention-based model, fusing S2 and PS within the temporal encoders. Experimental results did not show statistically significant differences between the three data sources for both study areas. Nevertheless, the TempCNN outperformed the other classifiers with an overall accuracy above 90% and an F1-Score of 86.6% for the ICLS class. By selecting the best models, we generated annual ICLS maps, including their surrounding landscapes. This study demonstrated the potential of deep learning algorithms and SITS to successfully map dynamic agricultural systems. [ABSTRACT FROM AUTHOR]

In this paper, the design and research of a sensor-based personal air-quality monitoring device are presented, which is retrofitted into different personal protective face masks. Due to its small size and low power consumption, the device can be integrated into and applied in practical urban usage. We present our research and the development of the sensor node based on a BME680-type environmental sensor cluster with a wireless IoT (Internet of Things)-capable central unit and overall low power consumption. The integration of the sensor node was investigated with traditional medical masks and a professional FFP2-type mask. The filtering efficiency after embedding was validated with a head model and a particle counter. We found that the professional mask withstood the embedding without losing the protective filtering aspect. We compared the inner and outer sensor data and investigated the temperature, pressure, humidity, and AQI (Air Quality Index) relations with possible sensor data-fusion options. The novelty is increased with the dual-sensor layout (inward and outward). It was found that efficient respiration monitoring is achievable with the device. With the analysis of the recorded data, characteristic signals were identified in an urban environment, enabling urban altimetry and urban zone detection. The results promote smart city concepts and help in endeavors related to SDGs (Sustainable Development Goals) 3 and 11. [ABSTRACT FROM AUTHOR]

The use of land use regulations to enhance a city's sustainability portfolio is not well understood by public administration and policy scholars. Given the positive impact higher-density, environmentally conscious zoning instruments can have on a city's overall progress toward increased sustainability, we seek to determine why some cities use these sustainability-focused land use regulations and others do not. After developing an explanatory framework emphasizing a city's population growth and environmental stress, as well as its political institutions and economic conditions, we use an enhanced ICMA's (International City/County Management Association) Local Government Sustainability Practices survey to test our predictions. We find that cities experiencing greater population growth and environmental stress will be more likely to include land use regulations in their sustainability portfolios. We also find that cities operating under council-manager forms of government and those with greater fiscal resources are more likely to have sustainability-focused zoning regulations in place. [ABSTRACT FROM AUTHOR]

Mountain is the most traditional tourism destination in China. On the basis of analyzing the particularity and its spatial differentiation of human-environment relationship in mountain tourism destination, this paper conducts empirical analysis in Yulong Snow Mountain by land use type classification. Firstly, ENVI is used to preprocess the Landsat-8 images of the research area. Then the visual interpretation is performed by ArcGIS to classify land use types. Based on the above, the differentiation status of human-environment relationship is analyzed. It concluded that: (1) Under the influence of natural factors such as piedmont, climate, altitude, gradient, slope, geological environment, and geomorphic characteristics, the uneven spatial distribution of human-environment relationship in mountain tourism destination is greatly affected by vegetation, rainfall, heat distribution, wind direction, suitability for human activities, and especially the topography; (2) The Yulong Snow Mountain forms three distinct levels of spatial differentiation in human-environment relationships between the east and west slopes, between high, medium and low elevations, and between different gradients. [ABSTRACT FROM AUTHOR]

Urban transformation strategies should be included in zoning plans to take precautions against disasters caused by natural events such as floods and landslides and to identify building stocks that are not earthquake resistant. This study was conducted to determine the level of consideration of the need for urban transformation in development planning processes. Environment, Urbanization and Climate Change, and AFAD Provincial Directorates, all municipalities and universities in Adana province were determined as the population of this study. In this context, questions were asked to public personnel who urban transformation law enforcers and researchers through the expert opinion form are. Participant responses were analysed with frequency and percentage values, and responses regarding importance levels were analysed on a 5-point Likert scale. The data indicated that the issue of urban transformation is not sufficiently included in development planning practices and that the actions on this issue should be carried out. We suppose that making the necessary revisions in the relevant legislation, which is the basis of urban transformation, will ensure that urban transformation takes an important place in development planning studies. [ABSTRACT FROM AUTHOR]

Studying driving factors of the urban heat island phenomenon is vital for enhancing urban ecological environments. Urban functional zones (UFZs), key for planning and management, have a substantial impact on the urban thermal environment through their two-dimensional (2D)/three-dimensional (3D) morphology. Despite prior research on land use and landscape patterns, understanding the effects of 2D/3D urban morphology in different UFZs is lacking. This study employs Landsat-8 remote sensing data to retrieve the land surface temperature (LST). A method combining supervised and unsupervised classification is proposed for UFZ mapping, utilizing multi-source geospatial data. Subsequently, parameters defining the 2D/3D urban morphology of UFZs are established. Finally, the Pearson correlation analysis and GeoDetector are used to analyze the driving factors. The results indicate the following: (1) In the Fifth Ring Road area of Beijing, the residential zones exhibit the highest LST, followed by the industrial zones. (2) In 2D urban morphology, the percentage of built-up landscape (built-PLAND) and Shannon's diversity index (SHDI) are the main factors influencing LST. In 3D urban morphology, building density, the sky view factor (SVF), and the area-weighted mean shape index (shape index) are the main factors influencing LST. Therefore, low-density buildings with simple and dispersed shapes contribute to mitigating LST, while fragmented distributions of trees, grasslands, and water bodies also play important roles in alleviating LST. (3) In the interactive detection results, all UFZs show the highest interaction detection results with the built-PLAND. (4) Spatial variations are observed in the impact of different UFZs on LST. For instance, in the residential zones, industrial zones, green space zones, and public service zones, the SVF is negatively correlated with LST, while in the commercial zones, the SVF exhibits a positive correlation with LST. [ABSTRACT FROM AUTHOR]

The productivity and quality of grapes and wine are significantly influenced by changing climate conditions in vineyard regions worldwide. This study assesses changes in temperature, precipitation, and viticultural indices between the periods of 1971–1990 and 2000–2019 in Trebinje, a vineyard area located in the Herzegovina region of Bosnia and Herzegovina. Between the two periods, mean annual temperature increased by 2 °C and mean vegetational temperature by 2.4 °C, while mean precipitation remained within the range of climatological variability, with annual values increasing by 6% and vegetational values decreasing by 4.6%. Warming resulted in a longer duration of the vegetation season by 23.7 days, a reduced risk of late spring frosts, and an increased risk of very high temperatures during summer. These changes led to the reclassification of Trebinje vineyards' climate from Region III to Region V, based on the Winkler index values, from a "temperate warm" to a "warm" category, based on the Huglin heliothermic index, and from "cool nights" to "temperate nights" based on the cool nights index. The category of the dryness index remained unchanged between the two periods. The findings emphasize the necessity for a renewal of the viticultural zoning and the development of climate change-adaptation plans for this region. [ABSTRACT FROM AUTHOR]

Whether or not a streetscape skeleton (defined as the 3D street space) is harmonious depends on the degree of difference between heights and setbacks of adjacent buildings, which is called the relative variability in the streetscape skeleton, but this has generally been overlooked. Because streetscape skeletons are ambiguous, evaluating whether or not they are harmonious is thus conceptually and technically challenging. This article, therefore, considers the relative variability in streetscape skeletons and their spatial associations and answers the following question: where are harmonious or inharmonious streetscape skeletons locally clustered? The relative variability in the streetscape skeletons in the districts of the Tokyo metropolitan region was computed, where building heights and setbacks are directly controlled through streetscape promotion district planning stipulated in the City Planning Act. The spatial association of the relative variability in streetscape skeletons was then visualized to identify where streetscape skeletons are harmonious and inharmonious. The results showed that although harmonious streetscape skeletons are spatially clustered inside the domain bounded by wider streets, such clusters are small and spatially scattered. We, therefore, concluded that the effectiveness of direct controls through streetscape‐promoting district planning to maintain and create harmonious streetscape skeletons is spatially limited and thus insufficient. [ABSTRACT FROM AUTHOR]

Transit-oriented development (TOD) has been widely encouraged as a strategy to limit urban sprawl, increase urban density, and enhance neighborhood diversity. Federal and regional governments have been increasingly promoting such TOD in parallel with light rail transit (LRT) projects to foster sustainable transitions. Little is known, however, about the processes through which municipalities have made changes to existing land use regulations to achieve TOD goals. In this article we trace changes in municipal plans and bylaws surrounding a CA$7 billion LRT in Montréal (Canada) that opened in summer 2023, 7 years after its announcement. Specifically, we analyzed whether changes in municipal bylaws conformed to TOD plans recommended by the metropolitan government while exploring local barriers to zoning reform. Through policy and spatial analysis, we found that only a limited number of municipalities made sufficient bylaw changes between 2016 and 2022 to support TOD plans aimed at implementing mixed-use zoning, increasing urban density, and reducing parking ratios. Through an analysis of rezoning processes, we see an opportunity for improved multilevel cooperation, public engagement activities, and positive communication strategies in the process of building integrated transport and land use systems. These findings can aid planners and policymakers in understanding the importance of reforming municipal zoning bylaws and regional approaches to TOD, strengthening collaboration between different levels of government, and engaging in meaningful public consultation practices to foster an integrated transport and land use approach. If LRT projects are to be successful in meeting sustainability goals, greater engagement with land use regulations across multiple scales is needed to facilitate TOD. [ABSTRACT FROM AUTHOR]

An instrument of wealth accumulation and racial segregation in housing markets, the intersections between zoning and labor are often overlooked. Extending theories of space, race, and class, and drawing on historical and archival evidence, I elaborate three ways that American land-use zoning emerged to shape labor markets in the early 20th century: (1) zoning constrained households from engaging in subsistence and direct market activity, acting as a regulatory source of labor commodification; (2) zoning first emerged as a xenophobic tool for regulating labor competition; and (3) zoning introduced racialized boundaries distinguishing formal work from a sphere of economic informality. I illustrate these theoretical-historical propositions with a study of the frontier origins of American land-use zoning laws in late-19th -century Los Angeles. This first and influential approach to residential zoning emerged amid racial dynamics of western settlement and the class politics of a national "free" labor market. I demonstrate how efforts to regulate the settlement and labor practices of poor urban households and Chinese immigrants on in Los Angeles became the direct legal basis for the dichotomous categories of "residential" and "industrial" districts that the city first defended before the U.S. Supreme Court in 1915. By theorizing the intersections of land-use zoning and labor markets, this paper provides a theoretical framework and historical genealogy for future work to consider entanglements of housing and labor politics amid the concurrent flexibilization of work and land use in the present. [ABSTRACT FROM AUTHOR]

In a pre-service mathematics methods class I taught, in which we mathematized political districting (first horizontally, then vertically), student questions led to engaging mathematics, in particular, the development of a new number sequence. [ABSTRACT FROM AUTHOR]

Is it possible to persuade voters to support more housing in their communities and affordable housing policies at the state and local levels? Generally, residents living close to proposed developments are more likely to oppose them, giving rise to the 'NIMBY' ('Not in My Back Yard') label. Previous research suggests institutional context rather than attitudes explains most of the geographic variation in regulatory barriers to new housing. This study investigates the possibility of changing voter attitudes towards housing and housing policies with a pair of preregistered survey experiments conducted on adult residents of New Hampshire, one of the most tightly regulated states for new housing. We discover two forms of messaging that move public opinion on state and local housing policy and find typical, anti-development attitudes among homeowners, but not renters, when it comes to proposed developments in respondents' own neighbourhoods. [ABSTRACT FROM AUTHOR]

Landsliding and slope instability pose significant risks to human settlements and infrastructure. This study aims to develop a landslide susceptibility map for the mountainous regions of Tehran province, Iran. The rock engineering approach was employed at a regional scale, utilizing a database of regional landslides. The semi‐quantitative Rock Engineering System method was applied, considering 10 conditioning factors. The model was validated using historical landslide data, showing strong correlation. The majority of landslides occurred within medium and high susceptibility zones. Geological units, particularly the Karaj Formation's claystone layers, displayed a clear association with landslide susceptibility. The rock engineering approach yielded a highly accurate susceptibility map. Findings can inform future territorial planning in the area. [ABSTRACT FROM AUTHOR]

The complementary characteristics of SAR and optical images are beneficial in improving the accuracy of land cover classification. Deep learning-based models have achieved some notable results. However, how to effectively extract and fuse the unique features of multi-modal images for pixel-level classification remains challenging. In this article, a two-branch supervised semantic segmentation framework without any pretrained backbone is proposed. Specifically, a novel symmetric attention module is designed with improved strip pooling. The multiple long receptive fields can better perceive irregular objects and obtain more anisotropic contextual information. Meanwhile, to solve the semantic absence and inconsistency of different modalities, we construct a multi-scale fusion module, which is composed of atrous spatial pyramid pooling, varisized convolutions and skip connections. A joint loss function is introduced to constrain the backpropagation and reduce the impact of class imbalance. Validation experiments were implemented on the DFC2020 and WHU-OPT-SAR datasets. The proposed model achieved the best quantitative values on the metrics of OA, Kappa and mIoU, and its class accuracy was also excellent. It is worth mentioning that the number of parameters and the computational complexity of the method are relatively low. The adaptability of the model was verified on RGB–thermal segmentation task. [ABSTRACT FROM AUTHOR]

As valued members of forest ecosystems, fast-growing tree species are of great importance for protecting natural forests, fulfilling the demand for raw wood material, and preserving biodiversity and ecosystem services. In this regard, multi-temporal monitoring and evaluation of poplar planted areas are essential for decision makers and planners to keep the inventory maps of planted areas up-to-date and track the temporal changes accurately. Using a spectral library, available spectral knowledge can be incorporated into inventory mapping and image classification processes. In this study, in situ spectral measurements of five Populus (four clones and one species) planted sites in Türkiye were collected at three phenological stages (early, mid, and late vegetation) and a novel spectral library was created after completing strict processing stages. Analysis of the spectral reflectances of the Populus species revealed that their spectral properties in the visible region are similar, whereas the discrimination in the near-infrared and shortwave infrared (SWIR) regions was noticeably higher. Two types of applications were conducted to effectively use the spectral library. First, the spectral library was used to validate the poplar class labels of the sites visited during the field campaign. The effectiveness of Worldview-3 imagery with eight SWIR bands was evaluated by pairwise comparison of the spectral curves of the sample fields with those of the spectral library. Second, the spectral library facilitated the extraction of poplar samples from Sentinel-2 imagery in an unvisited region, and a supervised classification process was conducted using the random forest algorithm. The results revealed that the Populus species (Samsun and I-214) could be delineated with high accuracy (>70%) using 10-band Sentinel-2 imagery, and object-based classification outperformed pixel-based classification by approximately 5% for the poplar types. The developed spectral library stands as a valuable asset for studies focused on identifying and classifying Populus species using high-resolution imagery. [ABSTRACT FROM AUTHOR]

Good city management is essential in mitigating the impact of various crisis events and thus enhances urban resilience. The current zoning system that underlies China’s city management system, however, hardly meets the resilient requirements in failing to appropriately and flexibly allocate patrol personnel under normal and various crisis scenarios. We propose an optimization method that gives rise to a resilient city management zoning system by introducing spatial interaction. We realize this through community detection in a spatially embedded patrol passage cost network. Illustrated by a case in Jiangbei District, Ningbo, China, we show that the optimized zoning system has significant advantages in terms of event coverage, response efficiency, and workload balance in the normal scenario as compared to the status quo with up to 3.6 percent, 5.9 percent, and 34.0 percent performance improvement, respectively. Moreover, the method also achieves similar performance improvement in three typical shock scenarios in city management: epidemic, typhoon, and crowd gathering. We conclude the article with discussions on the findings’ significance in urban resilience building and their methodological and theoretical implications in applied urban sciences. [ABSTRACT FROM AUTHOR]

Urban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of "dual carbon". [ABSTRACT FROM AUTHOR]

Air quality dispersion models are typically driven by meteorology preprocessors (e.g. CALMET, AERMET, GRAMM), for which a key input is land use classification data. Land use classification will determine for the model domain (or grid square) geophysical properties such as surface roughness, surface albedo, heat flux, and leaf area index. Variation of these variables results in differing predictions of both meteorological data used to drive the dispersion model and potentially also pollutant dispersion. As such, land use classification data can be a critical data input that can significantly affect final predicted results. Several land use classification datasets exist that are commonly adopted for air quality modelling applications in Australia and New Zealand. Some examples of these datasets include - the USGS Global Land Cover Characterisation (GLCC) at 1km resolution for 1992-1993, the USGS Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type at 500m resolution annually for 2001-2018, and the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) Australian Collaborative Land Use and Management Program (ACLUMP). Each of these datasets exists at different spatial resolution and has been collated for differing time periods. Consequently, a potential issue that arises from use of these prepared datasets is whether land use dataset resolution is sufficient and current enough to predict accurately the represented modelling scenario. One potential solution is to utilise GIS machine learning algorithms that can be taught to recognise and classify land use categories from current satellite imagery. This paper investigates using these machine learning techniques to classify land use data from current satellite imagery and provides comparisons with other conventionally used datasets. [ABSTRACT FROM AUTHOR]

The aim of the study is to provide a comprehensive understanding of the complex relationship between African urban peripheries and informal development that also aligns with the broader goal of creating inclusive and sustainable urban environments. The authors employed a literature review approach and examined the complexities of informal settlements. In the presentation of their findings, the authors focus on conceptualizing of informality beyond slum areas, unravelling urbanization complexities in African urban peripheries, analysing the emergence of informal development in urban peripheral zones, and addressing informal settlements in the context of SDG 11. The findings reveal the embeddedness of informal practices in African urban peripheries, and the emphasis on adaptability, hybridity, and the role of informal entities in shaping complex urban fabrics. Additionally, inclusivity, safety, resilience, and sustainability are emphasized within the context of SDG 11. The authors conclude that a holistic and collaborative approach is important for shaping inclusive and sustainable urban futures in African urban peripheries. Additionally, they propose strategies for upgrading and formalizing informal settlements, the provision of essential social services, creation of economic opportunities, enhancement of safety, and to foster resilience through adaptive strategies. [ABSTRACT FROM AUTHOR]

Proponents of fair districting reforms continue to face challenges in seeking to address the problem of partisan gerrymandering. Even in states that have successfully enacted redistricting reforms, state actors have been able to evade compliance, and state courts have been unable to guarantee fair districts. In addition, the Supreme Court's decision in Moore v. Harper could also limit state court efforts to guarantee fair districts. This Article argues that state evasion and Moore threaten to undermine the efficacy of fair districting norms recognized by state courts or enacted through either state political processes. Moore could create a one-way ratchet by weakening state courts' role in policing partisan gerrymandering, while allowing state courts to dismantle fair districts and fail to address the problem of evasion. This Article analyzes these dynamics by examining recent examples of evasion of anti-partisan gerrymandering norms by legislatures, redistricting commissions, and other political actors in the post-2020 redistricting cycle in Ohio, New York, and Florida. The Article begins by situating Moore and state evasion dynamics within theories of federalism, democracy, and election law. It then provides a descriptive account of state partisan gerrymandering regimes, by analyzing variation in the pathways through which states have entrenched norms against partisan gerrymandering, and variation in evasion strategies employed by political actors. Finally, the Article assesses the broader implications of Moore and state evasion dynamics for state court decision-making and the efficacy of state reforms. [ABSTRACT FROM AUTHOR]

The article titled "Cultural Zoning as Reparations: Providing Power to Asian American Communities" explores the concept of reparations for Asian American communities. It discusses the historical injustices faced by Asian Americans, including violence and discrimination, and argues that reparations are necessary to address these harms. The article proposes the idea of cultural zoning as a form of reparations, which would grant Asian American communities the power to create cultural zones to protect their interests and preserve their unique identity. It also examines a case study of the Two Bridges neighborhood in New York City to illustrate the potential benefits of cultural zoning. The article discusses the potential benefits of granting Asian American enclaves the power to implement cultural zoning as a form of reparations. The article focuses on the case study of the Two Bridges area in Manhattan, where luxury high-rise apartments are being constructed despite opposition from advocacy groups and residents. The Chinatown Working Group has proposed the Two Bridges Community Plan as an alternative zoning plan that prioritizes affordable housing and protects the neighborhood's character. The article argues that granting cultural zoning power to minority communities would empower them to protect their neighborhoods and counteract the harms of gentrification and cultural appropriation. [Extracted from the article]

The classification of urban functional areas is important for understanding the characteristics of urban areas and optimizing the utilization of urban land resources. Existing related methods have improved accuracy. However, they neglect cognitive differences amongst humans in the different scales of regional functions. Moreover, how to build the correlations of cross-scale characteristics is still unresolved when realizing the classification of multiscale urban functional zones. To resolve these problems, a transportation analysis zone involving urban buildings as research units is created and these units are described by geometric and functional characteristics using multiple data sources. Then, a hierarchical clustering model is built for the recognition of urban functional areas at varying scales with landmark semantic constraints. In the experiments, Shanghai served as the study area, and multiscale zones were created using different levels of road networks considering the constraint correlation of the significance between cross-scale maps. The experiential results show the proposed method has excellent performance and optimizes the functional zone classification at different scales. This study not only enriches the multiscale urban functional area-recognition methods but also can be used in other aspects, like cartographic generalization or spatial analysis. [ABSTRACT FROM AUTHOR]

The European Commission requested the EFSA Panel on Plant Health to prepare and deliver risk assessments for commodities listed in Commission Implementing Regulation (EU) 2018/2019 as 'High‐risk plants, plant products and other objects'. This Scientific Opinion covers plant health risks posed by defoliated 1‐ or 2‐year old bare root plants for planting (grafted or not) of 12 Prunus species (Prunus armeniaca, P. avium, P. canescens, P. cerasifera, P. cerasus, P. davidiana, P. domestica, P. dulcis, P. fontanesiana, P. persica, P. salicina, P. tomentosa) imported from Moldova, taking into account the available scientific information, including the technical information provided by the applicant country. The evaluation identified three EU‐quarantine pests, Erwinia amylovora (protected zone quarantine pest), Xiphinema rivesi non‐EU populations and Xanthomonas arboricola pv. pruni (protected zone quarantine pest), which were selected for further evaluation, based on defined criteria, including their presence in the applicant country. It should be noted that there is uncertainty regarding whether all relevant pests have been identified due to a limited number of scientific publications and pest surveys in Moldova. For the three selected pests, the risk mitigation measures proposed in the technical dossier from Moldova were evaluated taking into account the possible limiting factors. For these pests, an expert judgement is given on the likelihood of pest freedom taking into consideration the risk mitigation measures acting on it, including uncertainties associated with the assessment. The degree of pest freedom varies among the pests evaluated, with Erwinia amylovora being the pest most frequently expected on the imported plants. The Expert Knowledge Elicitation indicated, with 95% certainty, that between 9823 and 10,000 bundles (comprising 10–20 plants per bundle) out of 10,000 bundles would be free from E. amylovora. [ABSTRACT FROM AUTHOR]

Classification with a few samples of training set has been a longstanding issue in the field of polarimetric synthetic aperture radar (PolSAR) image analysis and processing. Aiming at the small number of training samples of the PolSAR image classification task, a novel Self‐Supervised Ensemble Learning Framework (SSELF) is designed. The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. In addition, it can significantly decrease the dependence of neural network algorithms on large labelled samples of training set. First, utilise the spatial–polarimetric features of PolSAR data perfectly, the EfficientNet‐B0 is presented and utilised as the main section of the Deep Learning (DL) model to extract DL features of PolSAR data. Then, using an optimisation function that constrains the cross‐correlation matrix of various distortions of each sample to the identity matrix, the designed DL model can obtain the effective features of homogeneous samples gathering and heterogeneous samples separating from each other in a self‐supervised manner. Moreover, following the great success of curriculum learning in the area of machine learning, a novel deep curriculum‐learning model is proposed, entitled Deep Curriculum Learning (DCL), to train the DL network in our self‐supervised model. The proposed DCL utilises the entropy‐alpha target decomposition to estimate the degree of complexity of each PolSAR image patch before applying it to the EfficientNet‐B0. Also, an accumulative mini‐batch pacing function is used to introduce more difficult patches to EfficientNet‐B0 in the training process of the designed self‐supervised model. Furthermore, two EL models, feature‐level and view‐level ensemble, are proposed to increase the feature extraction capability and classification result of PolSAR data by jointly using spatial features at different scales and polarimetric information at different bands. In fact, in the proposed feature‐level ensemble strategy, to improve the classification result, the extracted features of the different scales are used as the input of the designed feature fusion algorithm. Therefore, the extracted features are mapped to the new space with lower dimension. In general, in the proposed view‐level ensemble strategy, first, the Mutual Information (MI) between each feature and the other features calculates, and then based‐on the calculated MI, different group of features are selected as various views. Next, the final classification result of the PolSAR image classification is obtained by using the designed majority vote of the result in each view. It should be noted that unlike existing traditional methods, both amplitude and phase information of SAR images to devolve the training process of the proposed model are used. In addition, all of the parameters of the proposed network are developed to a complex domain. In addition, a complex backpropagation algorithm by using the gradient‐based model is used for training the network. Finally, experimental results on three well‐known PolSAR data sets illustrate that the designed SSELF can extract more discriminant features using the designed DL model and can achieve better classification results than the other six novel DL models in terms of small training samples and adequate labelled samples. [ABSTRACT FROM AUTHOR]

Thedistribution of products stands out as one of the pivotal activities for logistics companies in recent years, particularly in the aftermath of the COVID-19 pandemic and other geopolitical events. Intense competition compels companies to efficiently execute their logistical processes, with cross-docking emerging as a frequently applied solution. However, the location of cross-dock terminals in urban areas remains a problem insufficiently addressed in the literature, with a dearth of studies and models tackling this issue. This paper introduces a novel and innovative model for locating cross-dock terminals based on the CI-DEA–IDOCRIW–MABAC (Composite Indicators–Data Envelopment Analysis-Integrated Determination of Objective Criteria Weights–Multi-Attributive Border Approximation Area Comparison) methods. In the process of defining input indicators, the following three sources were utilized: relevant literature, practical insights from logistics experts, and the knowledge and experience of the authors. Eight inputs and three outputs were considered (the number of users in the observed channel; the area served by the channel; the average distance a vehicle travels in one delivery; the required number of vehicles; labor availability; competition; construction, and expansion possibilities; proximity to the main infrastructure and traffic facilities; the average number of deliveries; average delivered quantity; and service level). The model underwent testing in a case study analyzing nine distribution channels (areas within the observed urban zone). The results indicated that alternative A4 (in the southwest area) ranked the highest since it was the best-ranked in accordance with the most important criteria, suggesting that the terminal is best located in the southwest zone. The accuracy of the results was confirmed by company management. By developing a completely new model and addressing the identified gap in the literature, this paper provides unequivocal scientific contributions. [ABSTRACT FROM AUTHOR]

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global (all seven scenes) and regional (arid, tropics, and temperate) adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class (68.4% vs. 73.1%), six-class (79.8% vs. 82.8%), and five-class (80.1% vs. 85.1%) schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies (five classes: Esri 80.0 ± 3.4%, region corrected 85.1 ± 2.9%). The results highlight not only performance in line with an intensive deep learning approach, but also that reasonably accurate models can be created without a full annual time series of imagery. [ABSTRACT FROM AUTHOR]

This study analyzed radiation dose data to observe the annual decline in ambient radiation doses and assess the factors contributing to fluctuations in reconstructed areas of the Fukushima prefecture. Utilizing a novel mobile monitoring system installed on a community minibus, the study employed a cost-effective sensor, namely, Pocket Geiger which was integrated with a microcontroller and telecommunication system for data transfer, access, visualization, and accumulation. The study area included the region between Okuma and Tomioka towns. The ambient dose rate recorded along the minibus route was depicted on a map, averaged within a 1 × 1 km mesh created with the Quantum Geographic Information System. To ensure accuracy, the shielding factor of the minibus material is determined to adjust the dose readings. A significant decrease (p < 0.001) in the radiation dose ranges from 2022 to 2023 was observed. The land use classification by the Advanced Land Observation Satellite revealed an ecological half-life ranging from 2.41 years to 1 year, suggesting a rapid radiation decay across all land types. This underscores the close connection between radiation attenuation and environmental factors, as well as decontamination efforts across diverse land categories. [ABSTRACT FROM AUTHOR]

This paper studies the effect of craft breweries on residential property values. Using a hedonic Difference‐in‐Differences (DID) approach and about 250 thousand housing transactions in Denver, Colorado from 1990 to 2016, we investigate the impact of proximity to a craft brewery on residential property values. We consider three types of residence (single‐family home, row house, and condominiums), three types of brewery (all craft breweries, microbreweries, and brewpubs/taprooms), and two measurements of distance (Euclidian and walk‐time). Our most robust results are found for single‐family homes, whose values enjoy a premium of up to 20.4% for being in proximity to a brewpub/taproom several years after, with the average annual maximum premium around 3%. As expected, premiums decline as distance from breweries increase. Beyond a distance of 0.5 km or a 10‐min walk‐time, the premium for a regional/microbrewery is greater than that for a brewpub/taproom. For single family homes within 4 km or 40‐min walk‐time, the annualized premium ranges between 0.41% and 3.01%. These findings support the narrative that craft breweries are a neighborhood asset. [ABSTRACT FROM AUTHOR]

Electrofacies analysis conducted the distribution effects throughout the reservoir despite the difficulty of characterizing stratigraphic relationships. Clustering methods quantitatively define the reservoir zone from non-reservoir considering electrofacies. Asmari Formation is the most significant reservoir of the Mansouri oilfield in SW Iran, generally composed of carbonate and sandstone layers. The stratigraphical study is determined by employing 250 core samples from one exploratory well in the studied field. Five zones with the best reservoir quality in zones 3 and 5 containing sandstone/shale are determined. Moreover, multi-resolution graph-based and artificial neural network clustering involving six logs are employed. Utilizing Geolog software, an optimal model with eight clusters with better rock separation is obtained. Eventually, five electrofacies with different lithological compositions and reservoir conditions are identified and based on lithofacies describing thin sections, sandstone, and shale in zones 3 and 5 show high reservoir quality. According to the depth related to these zones, most of the facies that exist in these depths include sandstone and dolomite facies, and this is affected by the two factors of the primary sedimentary texture and the effect of the diagenesis process on them. Results can compared to the clustering zone determination in other nearby sandstone reservoirs without cores. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has had severe economic consequences across the globe. The crisis emanating from the pandemic has caused demand and supply side shocks, more far reaching than any crisis in living memory. We use a new data set from the 2020/21 Egyptian Industrial Firm Behavior Survey to examine determinants of firms' resilience during the pandemic. Crisis present the opportunity for what Schumpeter (In Economics of the Recovery Program, McGraw-Hill, 1934) calls creative destruction. Have manufacturing firms been all hit by the crisis equally, or were less efficient firms more likely to exit or downsize their activities thereby 'cleansing' the market? Two sets of factors affect firm dynamics and survival: (1) firms' innate characteristics and; (2) firm behavior, which captures the extent to which good management, innovation, the adoption of advanced technologies and worker training, have provided an opportunity for firms to adapt their business models and show greater resilience in coping with the crisis. We illustrate the vulnerability of private, smaller, informal firms and those that are not located in industrial zones. Second, pre-COVID behavioral characteristics matter for firm dynamics. The food sector and sectors identified as 'COVID sectors' show more resilience. Some behavioral traits vary by sector and are more influential depending on firm size. [ABSTRACT FROM AUTHOR]

Historic injustices due to racial discrimination, redlining, and inequitable zoning practices have contributed to urban inequalities in the United States. These inequalities have been compounded by a lack of consideration for how infrastructure, industrial projects, and zoning impact nearby low-income and minority populations. To promote an equitable future, this paper investigates whether there are spatial patterns based on zoning variance data in the city of Pittsburgh. The authors used principal component analysis and regression analysis to study statistical correlations between socioeconomic and demographic characteristics and zoning variance application data. Several relationships reflect statistical significance, such as the average income of the residents and the percentage over the age of 25 who are college-educated, while the overall results highlight potential future research areas. Our work combining data sets with spatially explicit statistical analysis has the potential to equip decision makers with future tools necessary to account for inequalities and assess communities that may be unaware of the opportunities that variances present. [ABSTRACT FROM AUTHOR]

Membranes are protein and lipid structures that surround cells and other biological compartments. We present a conceptual model wherein all membranes are organized into structural and functional zones. The assembly of zones such as receptor clusters, protein-coated pits, lamellipodia, cell junctions, and membrane fusion sites is explained to occur through a protein-lipid code. This challenges the theory that lipids sort proteins after forming stable membrane subregions independently of proteins. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau, recognized as Earth's third pole and among the most responsive regions to climate shifts, profoundly influences regional and even global hydrological processes. Here, we discerned a significant weakening in the influence of temperature on the initiation of surface freeze-thaw cycle (the Start of Thawing, SOT), which can be ascribed to a multitude of climatic variables, with radiation emerging as the most pivotal factor. Additionally, we showed that the diminishing impact of warming on SOT yields amplified soil moisture within the root zone. This, in turn, fosters a greening third pole with increased leaf area index and solar-induced chlorophyll fluorescence. We further showed that current Earth system models failed to reproduce the linkage between weakened sensitivity and productivity under various shared socioeconomic pathways. Our findings highlight the dynamic shifts characterizing the influence of climate warming on spring freeze-thaw process and underscore the profound ecological implications of these changes in the context of future climate scenarios. [ABSTRACT FROM AUTHOR]

The common channel attention mechanism maps feature statistics to feature weights. However, the effectiveness of this mechanism may not be assured in remotely sensing images due to statistical differences across multiple bands. This paper proposes a novel channel attention mechanism based on feature information called the feature information entropy attention mechanism (FEM). The FEM constructs a relationship between features based on feature information entropy and then maps this relationship to their importance. The Vaihingen dataset and OpenEarthMap dataset are selected for experiments. The proposed method was compared with the squeeze-and-excitation mechanism (SEM), the convolutional block attention mechanism (CBAM), and the frequency channel attention mechanism (FCA). Compared with these three channel attention mechanisms, the mIoU of the FEM in the Vaihingen dataset is improved by 0.90%, 1.10%, and 0.40%, and in the OpenEarthMap dataset, it is improved by 2.30%, 2.20%, and 2.10%, respectively. The proposed channel attention mechanism in this paper shows better performance in remote sensing land use classification. [ABSTRACT FROM AUTHOR]

The fast rise of rural tourism in China has necessitated an assessment of the ecological circumstances in rural areas. But because rural landscapes are complicated and there are many different characteristics to consider, this can be challenging. With an emphasis on Pingchang County, Bazhong City, Sichuan Province, in particular, this study aims to provide a technique for the comprehensive assessment of the ecological environment quality in rural tourism zones. Analyzing the variables influencing these tourist destinations' ecological environments is one of the multiple-criterion decision-making procedures known as the Analytic Hierarchy Process (AHP). The fuzzy synthesis method was used after the hierarchical model was constructed and weight calculations were completed. To complete the assessment, a judgment matrix was created, and the weights of each indicator were determined. The assessment was then carried out through detailed review and consistency testing. The proposed approach works well for managing complex decision-making circumstances, including multiple criteria, and agreeing with professional opinions. The results of this study show consistent criteria ranking, high stability across iterations, minimal sensitivity to changes in criteria, and strong alignment with expert judgments. The results obtained using the proposed AHP method were numerically consistent, with a consistency ratio (CR) of 0.08, meaning that the criteria ranking remained constant across the iterations. In addition, the approach demonstrated a 0.95 alignment score with expert opinions, confirming its strength and reliability in providing evaluations in accordance with professional insights to direct rural tourism development plans. [ABSTRACT FROM AUTHOR]

Cultivated land has been one of the most important resources in agricultural production. Dynamically stable areas and the quality of cultivated land can greatly contribute to national food security and sustainable development. However, the cultivated land resources have been gradually fragmented and dispersed, with the rapid development of urbanization and industrialization. The cultivated land has been under serious threat in recent years. Therefore, this study aims to assess the suitability and necessity of cultivated land fragmentation for better cultivation zoning, in order to efficiently utilize the cultivated land resources and spatial layout. Accordingly, the background and progress were first combed to improve the research theory and logic fundamentals. The study area was selected as the typical mountainous county in the resource-oriented Dexing City in Jiangxi Province of China. 105 villages with cultivated land were taken as the evaluation unit. Secondly, a binding model was established for control and management. The "three zones and three lines" delineation was used as the reference. 20 indicators were also selected to construct an evaluation system for the suitability of cultivated land fragmentation, according to the three evaluation dimensions of production suitability, spatial agglomeration, and management control binding. The multi-factor integrated superposition was also evaluated for the appropriateness of cultivated land in the fragmentation management. Again, the three-dimensional Rubik's Cube spatial classification was used to construct the zoning guidelines. Production suitability, spatial agglomeration, and management control constraints were set as the X-, Y-, and Z-axis of the Rubik's Cube. The evaluation and grading results of each dimension were the nodes of the axes on the remediation and zoning. The results show that: 1) The better suitability of arable land resources production was 0.558, where 58 villages were more than the average value. The higher value was concentrated in the southwestern part of Dexing City; There was a uniform spatial agglomeration of arable land, with a citywide average of only 0.350. Less than half of the villages had a higher spatial agglomeration than the average, where the maximum of 0.577 was located in Jietian Village; The average value of the management control constraints was 0.075. There was a great variation in the villages, where the high values were concentrated mainly in the villages around towns and ecological red lines; The average value of the appropriateness in the management of cultivated land fragmentation was 0.711, and the appropriateness in the management of 53 villages was higher than the average, indicating the fine-fragmentation of cultivated land resources. 2) The comprehensive assessment showed that the 105 villages were divided into five zones, including the high-quality security, comprehensive improvement, facility optimization, intensive integration, and status quo maintenance zone, where the proportions of the cultivated land area were 38.36%, 12.01%, 19.11%, 17.84%, and 12.68%, respectively, according to the three-dimensional Rubik's Cube spatial classification. Differential remediation measures and strategies were also formulated to consider the different production suitability, spatial agglomeration, management and control constraints in each district. The finding can provide the theoretical basis and technical support to implement the diversified management and control measures in the different types of arable land resources, particularly in the cultivated land fragmentation remediation project. [ABSTRACT FROM AUTHOR]

By systematically reviewing the practical experience of management of urban parks at home and abroad, the advanced experience in organization, management system, operation mechanism and social participation were summarized, and the optimization and improvement measures for the construction and management of urban parks in Chengdu were proposed to provide reference for the high-level construction, high-quality experience and efficient management of urban parks in the construction of park city demonstration zone in Chengdu. [ABSTRACT FROM AUTHOR]

Ecotoxicity of dust was assessed for different functional zones in three Moscow districts. Ecotoxicity was estimated by the reaction of higher plants using a new approach to the implementation of biotesting method and by changes in the biomass and respiration of microorganisms in residential and transport zones as compared to recreational zones. The proposed method of assessing urban dust toxicity upon modeling dust transfer to soil-like substrates allowed us to solve the main methodological problem, i.e., the choice of control. By the example of perennial ryegrass (Lollium perenne L.), it was found out that annual volume of dust deposition upon a high load within a one-meter zone from the road surface does not manifest toxicity, whereas a three-year volume suppresses plants up to 27% relative to the control. No significant differences were found between the phytotoxicity of dust in different functional zones; and phytotoxicity did not correlate with any of the studied properties of dust (organic carbon content (Corg), pH, electrical conductivity, moisture capacity, particle-size composition). Basal respiration and carbon content in microbial biomass (Cmic) of dust were maximal in the recreational zones of the city (3.1–7.2 μg C–CO2 g–1 h–1 and 314–435 μg g–1, respectively) decreasing by 27–71% in residential and by 76–81% in the transport zones. Significant correlations of basal respiration and Cmic with Corg were observed (rS = 0.57 and 0.61, respectively, p < 0.05, n = 49). High values of microbial metabolic quotient qCO2 of dust and a small share of Cmic in Corg indicate unfavorable conditions for microorganisms. [ABSTRACT FROM AUTHOR]

The overcrowding of cities has led to the depopulation of rural areas, which has made them a testing ground for the location, in many cases without measure, of renewable energy installations. Something that should have a positive character, runs the risk of ending up irreparably affecting the areas where they are located, which is also unacceptable. Beyond the approach to the problem, the present work, by means of the figure of the social licence, brings possible solutions closer, with verifiable and effective examples. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) change is one of the primary contributors to hydrological change in urban watersheds and can potentially influence stream flow and flood volume. Understanding the impacts of LULC change on urban hydrological processes is critical to effective urban water management and minimizing flood risks. In this context, this study aims to determine the impacts of LULC change on hydrological response in a fast transitioning watershed for the predicted years of 2050 and 2080. This research employs the hybrid land use classification technique, Cellular Automata–Markov (CA–Markov) model to predict land use changes, utilizing land use data from 2001, 2013, and 2021. Additionally, it incorporates a calibrated, event-specific hydrologic model known as the Personal Computer Storm Water Management Model (PCSWMM) to assess alterations in hydrological responses for storm events of various magnitudes. The findings indicate a transition of the watershed into an urbanized landscape, replacing the previous dominance of agriculture and forested areas. The initial urban area, constituting 11.6% of the total area in 2021, expands to cover 34.1% and 44.2% of the total area by 2050 and 2080, respectively. Due to the LULC changes, there are increases in peak discharge of 5% and 6.8% and in runoff volume of 8% and 13.3% for the years 2050 and 2080 for a 100-year return period storm event. Yet, the extent of these changes intensifies notably during storm events with lower return periods. This heightened impact is directly attributed to the swift urbanization of the watershed. These results underscore the pressing necessity to regulate LULC change to preserve the hydrological equilibrium. [ABSTRACT FROM AUTHOR]

Autophagy is a highly conserved intracellular degradation mechanism. The most distinctive feature of autophagy is the formation of double-membrane structures called autophagosomes, which compartmentalize portions of the cytoplasm. The outer membrane of the autophagosome fuses with the vacuolar/lysosomal membrane, leading to the degradation of the contents of the autophagosome. Approximately 30 years have passed since the identification of autophagy-related (ATG) genes and Atg proteins essential for autophagosome formation, and the primary functions of these Atg proteins have been elucidated. These achievements have significantly advanced our understanding of the mechanism of autophagosome formation. This article summarizes our current knowledge on how the autophagosome precursor is generated, and how the membrane expands and seals to complete the autophagosome. [ABSTRACT FROM AUTHOR]

Biological membranes, including plasma membrane (PM) and organelle membranes, restrict the flux of ions, molecules and organelles. However, the barrier function of biological membranes is frequently compromised by various perturbations, including physical membrane damage and protein- or chemical-induced pore formation. Recent evidence suggests that, upon PM damage, protein gelation and solid condensation are utilized to restrict ion/molecule/organelle flux across the damaged membranes by zoning the cytoplasm. In addition, membrane permeabilization dramatically alters intramembrane and extramembrane ion/molecule concentrations via the flux across the permeabilized membrane. The changes in ion/molecule concentration and their downstream pathways induce protein phase transition to form zones for biological processes or protein sequestration. Here, we review the mechanisms and functions of protein phase transition after biological membrane permeabilization. [ABSTRACT FROM AUTHOR]