Spatial distribution of mountainous regions and classifications of economic development in China

China is a mountainous country with a great diversity of landform and geomorphology.This diversity underlines the need for regionalization and classification.This study defines the mountain terrains and regions with three criteria-elevation,relative height,and slope,and examines the extent of mountainous regions by using county as the basic administrative unit.According to the three parameters of economic base,resident income and development potential,we classified the economic development level in mountainous regions of China.The findings reveal that the extent of the mountainous region accounts for 74.9% of the China's Mainland's total area.The economic development of mountainous regions in China is classified into 4 main types and 23 subtypes.

Classification and Development Laws of Karst Landform in Suzhou Area, North Anhui Province of China

Suzhou area in north Anhui Province is a low hilly area on the Huaibei Plain where carbonate rocks and karstification are widely distributed, and karst landscapes form major physical contours of the bedrock outcrops. Through field investigation, karst landscapes of Suzhou area were divided into two categories based on their morphological characteristics: macro-geomorphologic landscapes including normal hills, dry valleys, karst springs and caves, and micro-corrosion landscapes including corrosion pits, dissolved pores, dissolution traces, corrosion cracks, clints and karrens. Distribution, development and scale of karst landscapes in this region are controlled by climate, rock type, structure, topography and other factors. It was suggested that karst landscapes in the study area could be used as a representative of karst landforms in North China.

Spatiotemporal Differences and Classification Regulation of Urbanization Impact on Agricultural Development in Shrinking Areas:A Case Study of 15 Shrinking Cities in Three Provinces of Northeast China

Studying the impact of urbanization on agricultural development in shrinking areas is important for maintaining food security and promoted agricultural development in China.Based on the measurement results of the shrinking cities in the three provinces of Northeast China,this paper selects 15 shrinking cities as the research object,and constructs a multi-dimensional index system to explore the impact of the urbanization level of the shrinking areas on the agricultural development in the region since 2007–2019,analyzes the influencing factors and their differences by using the geographically-weighted regression model and Geodetector,and proposes a targeted regulation strategy.The results show that:1)overall,there is a negative correlation between the urbanization level and the agricultural development level in the contracted areas of the three northeastern provinces.The urbanization level in these areas has a certain negative impact on the overall level of agricultural development;2)regarding the time dimension,the impact of urbanization level on the agricultural development level in the contracted areas of the three northeastern provinces gradually increases over time;3)regarding the spatial pattern,the overall impact of shrinking urbanization levels in the three provinces of Northeast China on the agricultural development shows a significant distribution pattern of high in the east and low in the west;4)the total population and natural population growth rate at the end of the year were the main factors influencing a certain level of urbanization on agricultural development in the shrinking cities while population density and the urban fixed asset investment rate were the secondary factors;and 5)the main reasons why the level of agricultural development in different cities was affected by the level of urbanization were different.However,they can be categorized into areas of population loss and spatial construction,which can be further divided into area of population loss in the northeast,areas of negative population growth in the west,and areas of urban spatial change in the south.According to the causes of the impact,this paper adopted targeted regulation strategies and formulated relevant policies and solutions that cater to local conditions.

Construction of the Classification and Grading Index System of Cultivated Land Based on the Viewpoint of Sustainable Development

In order to objectively and reasonably evaluate the actual and potential value of cultivated land, both social and ecological values are introduced into the classification and grading index system of cultivated land based on the viewpoint of sustainable development, after considering the natural and economic values of cultivated land. Index system construction of the sustainable utilization of cultivated land should follow the principles of economic viability, social acceptability, and ecological protection. Classification of cultivated land should take into account the soil fertility of cultivated land. Then, grading of cultivated land is carried out from the practical productivity (or potential productivity) of cultivated land. According to the existing classification index system of cultivated land, the soil, natural and environmental factors in plains, mountains and hills are mainly modified in the classification index system of cultivated land. And index systems for the cultivated land classification in plains, mountains and hills are set up. The grading index system of cultivated land is established based on the economic viability (economic value), social acceptability (social value) and protection of cultivated land (ecological value). Quantitative expression of cultivated land grading index is also carried out.

Geographical Space Development Zone Classification:An Essential Guide for Transformation of Mountain Resource Cities

Sustainable development of mountain areas and resource cities has been a significant issue worldwide. Transformation of mountain resource cities is facing tremendous difficulties. In the context of National Major Function-oriented Zone Planning raised to a national strategic level in China, it is important to effectively implement the planning by studying geographical space development zone classification of prefecture- and county-level cities based on their major function orientation. This research is even more critical for the transformation of mountain resource cities. In this study, we evaluated geographical space development suitability, and classified geographical space development zones for Dongchuan Distric in Kunming City of Yunan Province, China, a typical mountain resource city. A quantitative grid-based evaluation was conducted using key-factor identification and restrictive-supportive comprehensive index determinati based on a geographic information system framework with different source data. The results included a classification of geographical space of Dongchuan into five types: the prohibited development zone, the inappropriate development zone, the controlled development zone, the moderate development zone and the preferential development zone. The distribution characteristics of geographical space development zones showed that the proportion of the prohibited development zone is the highest, while that of the other four development zones is comparatively lower and significantly fragmented. The geographical space development suitability is greatly controlled by the geomorphic pattern. Although Dongchuan is extremely restrained in terms of suitable geographical space for industrialization and urbanization, it still has the certain preferential and moderate development zones with an area of 207.81 km2 with large parts being concentrated and contiguous, which makes these areas the most favorable for development. Only by adapting to this reality and implementing centralized development strategy in the regions with higher suitability may Dongchuan achieve smooth transformation from expansion mode to compact mode and its sustainable development capacity may be improved. Suggestions with an angle of industrial and spatial development pattern were put forward for the transformation of the city in future.

Classification and Spatial Pattern of Township Development in Liaoning Province, China

The classification of township development types is an urgent problem that requires solution to enable the township to choose an appropriate development path.Using a township development classification method,we determine the township development types and their spatial patterns in Liaoning Province,China.The results showed that the patterns of township development types based on their general advantages had significant spatial differentiations.The planting,and livestock and poultry breeding township development types based on general advantages were mainly distributed across the central plain of Liaoning Province,China,and also concentrated in Dandong City−Dalian City along Yellow Sea coast,and in the northwest of Chaoyang City.The business and tourism,industry and mining,and residence township development types based on general advantages were distributed mainly along the Shenyang–Dalian Economic Belt in the central and southern Liaoning Province.The ecology township development type based on general advantages was mainly distributed in the eastern and western Liaoning Province to maintain regional ecological security.Township development types based on non-advantages were sporadically distributed in the middle and western Liaoning Province.Based on the classification and spatial patterns,the differences between the distribution of twonship development types and the plan for the major functional areas of Liaoning Province were proposed which could provide the basis for the optimization of the major functional areas.

New Thinking of Traditional Industry Development under the New Economic Condition——Classification of the Industry by the Management Mode of Nike

This paper has announced the arrival of new economic era through an analysis of Nike＇s management mode. The traditional industry classification can＇t meet demands of industry development. We should inherit and improve traditional economy in order to adapt to the development demand of new economy.

Studies on Classification of Recreational Fishery Resources and Evaluation on its Development

Recreational fishery is the combination of traditional fishery and modern leisure activities.Development of recreational fishery resources must be based on related resources,but the present research on recreational fishery is mainly confined to the development of leisure projects,the definition of connotation and scope of recreational fishery resources is rather vague,and there is no precise classification and evaluation system.According to the resources attributes,resources functions,and tourism resources classification,investigation and evaluation standard,recreational fishery resources include a number of different types.Expert Scoring Method and Analytic Hierarchy Process can be used to determine the evaluation factors of recreational fishery resources and their weights,and then make comprehensive evaluation on recreational fishery resources of different regions and types,so as to improve the scientific nature of recreational fishery development.

Development of a novel staging classification for Siewert Ⅱ adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND Stage classification for Siewert Ⅱ adenocarcinoma of the esophagogastric junction(AEG)treated with neoadjuvant chemotherapy(NAC)has not been established.AIM To investigate the optimal stage classification for Siewert Ⅱ AEG with NAC.METHODS A nomogram was established based on Cox regression model that analyzed variables associated with overall survival(OS)and disease-specific survival(DSS).The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test,Akaike information criterion,Harrell concordance index,time-receiver operating characteristic curve,and decision curve analysis.RESULTS Data from 725 patients with Siewert type Ⅱ AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance,Epidemiology,and End Results database.Univariate and multivariate analyses revealed that sex,marital status,race,ypT stage,and ypN stage were independent prognostic factors of OS,whereas sex,race,ypT stage,and ypN stage were independent prognostic factors for DSS.These factors were incorporated into the OS and DSS nomograms.Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer.Finally,a user-friendly web application was developed for clinical use.CONCLUSION The nomogram established specifically for patients with Siewert type Ⅱ AEG receiving NAC demonstrated good prognostic performance.Validation using external data is warranted before its widespread clinical application.

New aspects of a small GTPase RAB35 in brain development and function

In eukaryotic cells,organelles in the secretory,lysosomal,and endocytic pathways actively exchange biological materials with each other through intracellular membrane trafficking,which is the process of transporting the cargo of proteins,lipids,and other molecules to appropriate compartments via transport vesicles or intermediates.These processes are strictly regulated by various small GTPases such as the RAS-like in rat brain(RAB)protein family,which is the largest subfamily of the RAS superfamily.Dysfunction of membrane trafficking affects tissue homeostasis and leads to a wide range of diseases,including neurological disorders and neurodegenerative diseases.Therefore,it is important to understand the physiological and pathological roles of RAB proteins in brain function.RAB35,a member of the RAB family,is an evolutionarily conserved protein in metazoans.A wide range of studies using cultured mammalian cells and model organisms have revealed that RAB35 mediates various processes such as cytokinesis,endocytic recycling,actin bundling,and cell migration.RAB35 is also involved in neurite outgrowth and turnover of synaptic vesicles.We generated brain-specific Rab35 knockout mice to study the physiological roles of RAB35 in brain development and function.These mice exhibited defects in anxiety-related behaviors and spatial memory.Strikingly,RAB35 is required for the precise positioning of pyramidal neurons during hippocampal development,and thereby for normal hippocampal lamination.In contrast,layer formation in the cerebral cortex occurred superficially,even in the absence of RAB35,suggesting a predominant role for RAB35 in hippocampal development rather than in cerebral cortex development.Recent studies have suggested an association between RAB35 and neurodegenerative diseases,including Parkinson's disease and Alzheimer's disease.In this review,we provide an overview of the current understanding of subcellular functions of RAB35.We also provide insights into the physiological role of RAB35 in mammalian brain development and function,and discuss the involvement of RAB35 dysfunction in neurodegenerative diseases.

A novel method for clustering cellular data to improve classification

Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.

Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.

Postnatal development of rat retina:a continuous observation and comparison between the organotypic retinal explant model and in vivo development

The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies.Thus,we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina.In this study,we showed that postnatal retinal explants undergo normal development,and exhibit a consistent structure and timeline with retinas in vivo.Initially,we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells.We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin,respectively.Ki-67-and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis,and exhibited a high degree of similarity in abundance and distribution between groups.Additionally,we used Ceh-10 homeodomain-containing homolog,glutamate-ammonia ligase(glutamine synthetase),neuronal nuclei,and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells,Müller glia,mature neurons,and microglia,respectively.The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas.Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development.The findings confirm the accuracy and credibility of this model and support its use for long-term,systematic,and continuous observation.

Performance evaluation of seven multi-label classification methods on real-world patent and publication datasets

Purpose:Many science,technology and innovation(STI)resources are attached with several different labels.To assign automatically the resulting labels to an interested instance,many approaches with good performance on the benchmark datasets have been proposed for multi-label classification task in the literature.Furthermore,several open-source tools implementing these approaches have also been developed.However,the characteristics of real-world multi-label patent and publication datasets are not completely in line with those of benchmark ones.Therefore,the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world datasets.Research limitations:Three real-world datasets differ in the following aspects:statement,data quality,and purposes.Additionally,open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection,which in turn impacts the performance of a multi-label classification approach.In the near future,we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter settings.Practical implications:The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets,underscoring the complexity of real-world multi-label classification tasks.Approaches leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among labels.With ongoing enhancements in deep learning algorithms and large-scale models,it is expected that the efficacy of multi-label classification tasks will be significantly improved,reaching a level of practical utility in the foreseeable future.Originality/value:(1)Seven multi-label classification methods are comprehensively compared on three real-world datasets.(2)The TextCNN and TextRCNN models perform better on small-scale datasets with more complex hierarchical structure of labels and more balanced document-label distribution.(3)The MLkNN method works better on the larger-scale dataset with more unbalanced document-label distribution.

Constructing a standard system of city sustainable development assessment technology based on the SDGs

Given the rapid development of China’s new urbanization,cities with different locations and varying functional positioning,resource endowments,and development stages have insufficient scientific and applicable technical tools for implementing the United Nations Sustainable Development Goals(SDGs).City managers and policymakers must urgently establish SDG benchmarks to diagnose city development.Moreover,successful experiences from similar cities regarding sustainable development and self-improvement must be learned from to promote diversified,sustainable development across the country.Furthermore,emerging technologies such as artificial intelligence,the Internet of Things,big data and 5G are widely used in smart cities.Therefore,there is a growing need for“knowledge-based,personalized and intelligent”technologies to support monitoring,evaluation,and decision-making processes facilitating sustainable development in cities.This paper uses standardization as the theoretical support and technical basis.This approach can help clarify the sustainable development processes in China and clarify the evaluation results of and provide data on horizontal city comparisons,which can be used to develop evaluation technology for sustainable development in cities and construct a standardized system.The results provide a standard framework for intelligent assessment and decision-making regarding cities’sustainable development capabilities in China.Evaluating major international standardization institutions reveals that the practices of Chinese national standards should be fully absorbed and integrated to guide the evaluation of smart,resilient,and low-carbon cities.To this end,an indicator library of city sustainable development is proposed to provide standard evaluation technology methods.Finally,analyzing the response relationship of the indicator library to SDGs reveals the need for a standardized knowledge map of sustainable development assessment techniques and methods from the perspective of integrated management for sustainable development in cities.

Spatial Differentiation and Convergence Trend of High-quality Development Level of China’s Tourism Economy

This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.

Classification and rating of disintegrated dolomite strata for slope stability analysis

Although disintegrated dolomite,widely distributed across the globe,has conventionally been a focus of research in underground engineering,the issue of slope stability issues in disintegrated dolomite strata is gaining increasing prominence.This is primarily due to their unique properties,including low strength and loose structure.Current methods for evaluating slope stability,such as basic quality(BQ)and slope stability probability classification(SSPC),do not adequately account for the poor integrity and structural fragmentation characteristic of disintegrated dolomite.To address this challenge,an analysis of the applicability of the limit equilibrium method(LEM),BQ,and SSPC methods was conducted on eight disintegrated dolomite slopes located in Baoshan,Southwest China.However,conflicting results were obtained.Therefore,this paper introduces a novel method,SMRDDS,to provide rapid and accurate assessment of disintegrated dolomite slope stability.This method incorporates parameters such as disintegrated grade,joint state,groundwater conditions,and excavation methods.The findings reveal that six slopes exhibit stability,while two are considered partially unstable.Notably,the proposed method demonstrates a closer match with the actual conditions and is more time-efficient compared with the BQ and SSPC methods.However,due to the limited research on disintegrated dolomite slopes,the results of the SMRDDS method tend to be conservative as a safety precaution.In conclusion,the SMRDDS method can quickly evaluate the current situation of disintegrated dolomite slopes in the field.This contributes significantly to disaster risk reduction for disintegrated dolomite slopes.

Embryonic and Larval Development of Reciprocal Crosses between Clarias gariepinus (Burchell, 1822) and Clarias jaensis (Boulenger, 1909) in West Cameroon

Establishing intraspecific breeding and hybridization programs and determining genetic variability are two important issues for aquaculture. However, interspecific hybridization to improve growth and feeding efficiency is limited. For this purpose, the embryonic and larval development of reciprocal crosses of Clarias gariepinus (Burchell, 1822) and Clarias jaensis (Boulenger, 1909) were studied under laboratory conditions. The fertilization rate varied from 63.33% to 92%, while the hatching rate ranged from 55.68% to 76% with the highest value in hybrids ♀Cg × ♂Cj. Crosses between ♀Cj × ♂Cj, ♀Cg × ♂Cj and ♀Cj × ♂Cg had embryonic stages similar to those of the pure sib ♀Cg x ♂Cg. All crosses, however, had different timing for the various embryological stages. Hatching occurred at 32 h 15 min and 38 h for ♀Cj × ♂Cj and ♀Cj × ♂Cg, and 23 h and 23 h 30 min, respectively, for ♀Cg × ♂Cg and ♀Cg × ♂Cj. However, both crosses produced viable larvae until the first external feeding. The external morphological features of the larvae were completely formed by the 10th day after hatching. The body forms of the crosses at this time were indistinguishable from the pure sib. This study thus laid the groundwork for further comparative studies on hybrid performance and characterization.

Assessment of rural sustainable development and analysis and prediction of obstacles and coupled coordinated development:A case study of Zaozhuang City

In China,the Innovation Demonstration Zone for the National Sustainable Development Agenda is a key initiative for executing the United Nations(UN)2030 Agenda for Sustainable Development.The Zone also plays critical roles in addressing the developmental bottlenecks that China faces and sharing Chinese insights into global sustainable development efforts.On July 15,2022,the State Council endorsed the Zone’s establishment in Zaozhuang City,Shandong Province,where it focuses on innovation-led sustainable development in rural areas.Research into the levels,impediments,interdependencies,and evolutionary trends of rural sustainable development is crucial.Therefore,this research aimed to assist in comprehensively assessing developmental challenges and facilitating the harmonious advancement of social,economic,and environmental aspects in rural areas.In pursuit of the three fundamental dimensions of the UN’s Sustainable Development Goals(SDGs),namely development’s drivers,quality,and equity,this study was grounded in China’s national Rural Revitalization Strategy and the demands of sustainable development strategies.It also aligns with the UN 2030 Agenda for Sustainable Development and the associated SDG indicators.Focusing on four key areas,namely production elements,natural elements,social elements,and rural governance,this study developed an evaluation index system for assessing the level of rural sustainable development.It employed a range of analytical models,including the game theory-based combination empowerment method,barrier degree model,coupling degree model,coupling coordination degree model,and gray prediction GM(1,1)model,to analyze the status and evolving trends of rural sustainable development in Zaozhuang City from 2015 to 2022.The key findings were as follows:①Relative to the baseline year 2015,the sustainable development level in Zaozhuang’s rural areas has shifted toward an improved state overall.②The primary barrier to achieving rural sustainable development in Zaozhuang is the city’s rural governance system.③While the components of rural sustainable development in Zaozhuang are in the early stages of both basic and moderate coordination,an overall enhancement has occurred in their integrative coordination.④Between 2023 and 2025,the level of integrative coordination in Zaozhuang is expected to rise steadily.However,reaching a state of advanced coordination will require additional time for development.

Critical Success Factors for Citizen Development

The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) projects: 1) Strategy;2) Infrastructure;3) Technology;4) Processes & Procedures;5) Governance;6) Culture;7) People;8) Goals & Metrics and selected six critical success factors from these categories: 1) Operational Efficiency;2) Time Savings;3) Timeframe to Realize Value;4) Employee Engagement;5) Participation;6) Number of Sponsored Ideas. End users of the digital transformation efforts through Citizen Development were asked to assess the six critical success measures in terms of performance and importance criteria. The research results identified that focus should be applied to improving “Timeframe to Realize Value”, on “Operational Efficiency”, and on “Time Savings” to deliver success.