Land use classification in mine-agriculture compound area based on multi-feature random forest: a case study of Peixian

IntroductionLand use classification plays a critical role in analyzing land use/cover change (LUCC). Remote sensing land use classification based on machine learning algorithm is one of the hot spots in current remote sensing technology research. The diversity of surface objects and the complexity of their distribution in mixed mining and agricultural areas have brought challenges to the classification of traditional remote sensing images, and the rich information contained in remote sensing images has not been fully utilized.MethodsA quantitative difference index was proposed quantify and select the texture features of easily confused land types, and a random forest (RF) classification method with multi-feature combination classification schemes for remote sensing images was developed, and land use information of the mine-agriculture compound area of Peixian in Xuzhou, China was extracted.ResultsThe quantitative difference index proved effective in reducing the dimensionality of feature parameters and resulted in a reduction of the optimal feature scheme dimension from 57 to 22. Among the four classification methods based on the optimal feature classification scheme, the RF algorithm emerged as the most efficient with a classification accuracy of 92.38% and a Kappa coefficient of 0.90, which outperformed the support vector machine (SVM), classification and regression tree (CART), and neural network (NN) algorithm.ConclusionThe findings indicate that the quantitative differential index is a novel and effective approach for discerning distinct texture features among various land types. It plays a crucial role in the selection and optimization of texture features in multispectral remote sensing imagery. Random forest (RF) classification method, leveraging a multi-feature combination, provides a fresh method support for the precise classification of intricate ground objects within the mine-agriculture compound area

HyFish: hydrological factor fusion for prediction of fishing effort distribution with VMS dataset

Predicting fishing effort distribution is crucial for guiding fisheries management in developing effective strategies and protecting marine ecosystems. This task requires a deep understanding of how various hydrological factors, such as water temperature, surface height, salinity, and currents influence fishing activities. However, there are significant challenges in designing the prediction model. Firstly, how hydrological factors affect fishing effort distributions remains unquantified. Secondly, the prediction model must effectively integrate the spatial and temporal dynamics of fishing behaviors, a task that shows analytical difficulties. In this study, we first quantify the correlation between hydrological factor fields and fishing effort distributions through spatiotemporal analysis. Building on the insights from this analysis, we develop a deep-learning model designed to forecast the daily distribution of fishing effort for the upcoming week. The proposed model incorporates residual networks to extract features from both the fishing effort distribution and the hydrological factor fields, thus addressing the spatial limits of fishing activity. It also employs Long Short-Term Memory (LSTM) networks to manage the temporal dynamics of fishing activity. Furthermore, an attention mechanism is included to capture the importance of various hydrological factors. We apply the approach to the VMS dataset from 1,899 trawling fishing vessels in the East China Sea from September 2015 to May 2017. The dataset from September 2015 to May 2016 is used for correlation analysis and training the prediction model, while the dataset from September 2016 to May 2017 is employed to evaluate the prediction accuracy. The prediction error ratio for each day of the upcoming week range is only 5.6% across all weeks from September 2016 to May 2017. HyFish, notable for its low prediction error ratio, will serve as a versatile tool in fisheries management for developing sustainable practices and in fisheries research for providing quantitative insights into fishing resource dynamics and assessing ecological risks related to fishing activities

Serum 25-hydroxyvitamin D3 is associated with advanced glycation end products (AGEs) measured as skin autofluorescence: The Rotterdam Study

Advanced glycation end products (AGEs) accumulate in tissues with aging and may influence age-related diseases. They can be estimated non-invasively by skin autofluorescence (SAF) using the AGE Reader™. Serum 25-hydroxyvitamin D3 (25(OH)D3) may inhibit AGEs accumulation through anti-oxidative and anti-inflammatory properties but evidence in humans is scarce. The objective was to investigate the association between serum 25(OH)D3 and SAF in the population-based cohort study. Serum 25(OH)D3 and other covariates were measured at baseline. SAF was measured on average 11.5 years later. Known risk factors for AGE accumulation such as higher age, BMI, and coffee intake, male sex, smoking, diabetes, and decreased renal function were measured at baseline. Linear regression models were adopted to explore the association between 25(OH)D3 and SAF with adjustment for confounders. Interaction terms were tested to identify effect modification. The study was conducted in the general community. 2746 community-dwelling participants (age ≥ 45 years) from the Rotterdam Study were included. Serum 25(OH)D3 inversely associated with SAF and explained 1.5% of the variance (unstandardized B = − 0.002 (95% CI[− 0.003, − 0.002]), standardized β = − 0.125), independently of known risk factors and medication intake. The association was present in both diabetics (B = − 0.004 (95% CI[− 0.008, − 0.001]), β = − 0.192) and non-diabetics (B = − 0.002 (95% CI[− 0.003, − 0.002]), β = − 0.122), both sexes, both smokers and non-smokers and in each RS subcohort. Serum 25(OH)D3 concentration was significantly and inversely associated with SAF measured prospectively, also after adjustment for known risk factors for high SAF and the number of medication used, but the causal chain is yet to be explored in future studies. Clinical Trial Registry (1) Netherlands National Trial Register: Trial ID: NTR6831 (http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=6831). (2) WHO International Clinical Trials Registry Platform: under shared catalogue number NTR6831 (www.who.int/ictrp/network/primary/en/)

What Drives the Rise of Metro Developments in China? Evidence from Nantong

This paper addresses to the rapid rise of metro developments in Chinese cities to reconsider the official justifications of such mega-projects and the underlying driving forces behind proposal and approval processes. Qualitative approaches were undertaken in this in-depth case study of Nantong’s metro project, through insights into planning documents and evidences gathered from interviews, together with relevant socioeconomic data. Our research findings reveal four major motivations to develop metro projects in China: the city’s expected improvements through the metro system, the local economic power as the essential requirement and source of confidence for project development, the inter-city competition as an invisible factor driving project proposals, and the changing domestic political economy as the direct cause of its approval. As a topic that is frequently studied in the relevant literature and often advocated by metro projects promoters, the local expected achievements in terms of modal shift to public transport, transit-oriented development, economic growth, and tax maximisation are highlighted in this case study. Additionally, in China, inter-city competition and economic-political reasons involved in initiating, promoting, and approving urban mega-projects are also vital to the whole process

Current Approach in Surface Plasmons for Thin Film and Wire Array Solar Cell Applications

Surface plasmons, which exist along the interface of a metal and a dielectric, have been proposed as an efficient alternative method for light trapping in solar cells during the past ten years. With unique properties such as superior light scattering, optical trapping, guide mode coupling, near field concentration, and hot-electron generation, metallic nanoparticles or nanostructures can be tailored to a certain geometric design to enhance solar cell conversion efficiency and to reduce the material costs. In this article, we review current approaches on different kinds of solar cells, such as crystalline silicon (c-Si) and amorphous silicon (a-Si) thin film solar cells, organic solar cells, nanowire array solar cells, and single nanowire solar cells

A Comprehensive Assessment and Spatial Analysis of Vulnerability of China’s Provincial Economies

Vulnerability theory is a fundamental scientific knowledge system in sustainable development, and vulnerability assessment is important in vulnerability studies. Economic vulnerability affects economic growth sustainability. Comprehensive assessment of economic vulnerability in the process of economic growth under the theoretical framework of vulnerability will provide a new perspective for vulnerability studies. Based on a vulnerability scoping diagram assessment model, this study selected 22 economic sensitivity indexes and 25 economic adaptability indexes from the economic, social, and nature–resource–environmental subsystems to comprehensively assess and spatially analyse the vulnerability of China’s provincial economies since the year 2000, while applying the entropy method, multilevel extension assessment, spatial measurement method, and geographic information system technology. The results showed the following: (1) There are great differences in the vulnerability of China’s provincial economies. Western China’s vulnerability is higher and the fluctuation range of economic vulnerability is larger. The vulnerability increased significantly based on spatial differential features; (2) Regional differences in economic vulnerability, mainly caused by differences within a region, increased gradually. Eastern and Western China showed the spatial pattern characteristics of prominent and reinforcing regional imbalance, while Central and Northeast China showed declining regional imbalance. The spatial structure evolution of economic vulnerability is characterized by a volatility curve, and regional separation and divergence are strengthened; (3) Growth of China’s provincial economies and economic vulnerability are related negatively. In Eastern, Central, and Northeast China, vulnerability of the provincial economies has a negative spillover effect on neighbouring provinces’ economic growth, while in Western China it has a slight positive spillover effect

Topological phase transitions and Weyl semimetal phases in chiral photonic metamaterials

Recently, topologically nontrivial phases in chiral metamaterials have been proposed. However, a comprehensive description of topological phase diagrams and transitions in chiral metamaterials has not been presented. In this work, we demonstrate several forms of topological phase transitions and study the existence of edge states in different phases. In the local/lossless chiral media system, the topological phase transitions are associated with Weyl points. Along with the transitions, the edge state and Fermi arc exhibit a series of changes. When the nonlocal effect is introduced, the system shows phase transition between type-I/II Weyl semimetal phase and trivial phase. Moreover, the dissipative system also undergoes topological phase transitions owing to the annihilation of the topological charges. Our work could be helpful for the application of topological concepts and rich the topological wave physics in metamaterials

Study of the Distribution Characteristics of the Airflow Field in Tree Canopies Based on the CFD Model

Air-assisted sprayers are the mainstream orchard plant protection machinery in China. During the usage of sprayers, the pesticide droplets carried by strong air jets from sprayers enter into the target canopy. Therefore, the distribution of airflow field in the canopy has significant influence on the spatial movement of the droplets and the adhesion and penetration of the droplets inside the canopy. To enhance the working performance of sprayers, it is imperative to study their use in tree canopies. Based on computational fluid dynamics (CFD), the k-ε turbulence model, and the SIMPLE algorithm, a 3D simulated model of the spatial distribution of the airflow field in and around the tree canopy was established based on the porous model in this paper. The model was used to simulate and calculate the air field distribution of an air-assisted orchard sprayer under different operating parameters. The results showed that the optimal operation effect was achieved when the driving speed and the air speed of the fan outlet were 1 m/s and 20 m/s, respectively, while the air speed in the canopy was not less than 2 m/s. The 36 points measured in the canopy were compared with the simulated results through field experiments. It showed that average relative error between the measured and simulated values was 13.85%, and the overall goodness-of-fit was 0.97656. The model accurately simulated the airflow distribution in the canopy and provided a basis for optimizing the operating parameters of the air-assisted sprayers in orchards

Image Reconstruction Using Autofocus in Single-Lens System

To reconstruct the wavefront in a single-lens coherent diffraction imaging (CDI) system, we propose a closed-loop cascaded iterative engine (CIE) algorithm based on the known information of the imaging planes. The precision of diffraction distance is an important prerequisite for a perfect reconstruction of samples. For coherent diffraction imaging with a lens, autofocus is investigated to accurately determine the object distance and image distance. For the case of only the object distance being unknown, a diffuser is used to scatter the coherent beam for speckle illumination to improve the performance of autofocus. The optimal object distance is obtained stably and robustly by combing speckle imaging with clarity evaluation functions. SSIM and MSE, using the average pixel value of the reconstructed data set as a reference, are applied on two-unknown-distance autofocus. Simulation and experiment results are presented to prove the feasibility of the CIE and proposed auto-focusing method