Complexity and entropy of natural patterns.

Complexity and entropy play crucial roles in understanding dynamic systems across various disciplines. Many intuitively perceive them as distinct measures and assume that they have a concave-down relationship. In everyday life, there is a common consensus that while entropy never decreases, complexity does decrease after an initial increase during the process of blending coffee and milk.

Coupled analysis of arable land input intensity and output intensity based on sliding windows.

Sustainable intensification (SI) of agriculture can produce more food to meet the demand of a growing population while considering ecosystem health. The current SI estimation framework ignores the complex coupling between input and output intensity of arable land. A method for coupled analysis of arable land input intensity and output intensity based on sliding windows is proposed.

A raster-based spatial clustering method with robustness to spatial outliers.

Spatial clustering is an essential method for the comprehensive understanding of a region. Spatial clustering divides all spatial units into different clusters. The attributes of each cluster of the spatial units are similar, and simultaneously, they are as continuous as spatially possible.

Analyzing spatial patterns and driving factors of cropland change in China's National Protected Areas for sustainable management.

Farming in protected areas frequently challenges ecological conservation goals while supporting local livelihoods. To balance protection and agriculture, a comprehensive understanding of cropland dynamics in protected areas is of paramount importance. However, studies addressing this trade-off are relatively scarce, especially considering explicit Chinese government regulations on population relocation and cropland retirement in National Protected Areas (NPAs).

Exploring Relationships between Boltzmann Entropy of Images and Building Classification Accuracy in Land Cover Mapping.

Remote sensing images are important data sources for land cover mapping. As one of the most important artificial features in remote sensing images, buildings play a critical role in many applications, such as population estimation and urban planning. Classifying buildings quickly and accurately ensures the reliability of the above applications.

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas.

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFS) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFS through transboundary transport is currently not well known.

CLUMondo-BNU for simulating land system changes based on many-to-many demand-supply relationships with adaptive conversion orders.

Land resources are fundamentally important to human society, and their transition from one macroscopic state to another is a vital driving force of environment and climate change locally and globally. Thus, many efforts have been devoted to the simulations of land changes. Among all spatially explicit simulation models, CLUMondo is the only one that simulates land changes by incorporating the multifunctionality of a land system and allows the establishment of many-to-many demand-supply relationships.

Fulfilling global climate pledges can lead to major increase in forest land on Tibetan Plateau.

The UN Climate Change Conference in Glasgow spawned the enhancement and updating of many nations' climate pledges. Previous research has investigated the effects of these pledges on limiting planetary warming, but their spatially explicit effects on land use/cover are unknown. Here, we linked the Glasgow pledges and the spatially explicit responses of the Tibetan Plateau's land systems.

Selenium alleviates endoplasmic reticulum calcium depletion-induced endoplasmic reticulum stress and apoptosis in chicken myocardium after mercuric chloride exposure.

Mercury is a highly toxic heavy metal with definite cardiotoxic properties and can affect the health of humans and animals through diet. Selenium (Se) is a heart-healthy trace element and dietary Se has the potential to attenuate heavy metal-induced myocardial damage in humans and animals. This study was designed to explore antagonistic effect of Se on the cardiotoxicity of mercuric chloride (HgCl) in chickens.

Mercuric chloride induces sequential activation of ferroptosis and necroptosis in chicken embryo kidney cells by triggering ferritinophagy.

Mercuric chloride (HgCl) is an environmental pollutant with serious nephrotoxic effects, but the underlying mechanism of HgCl nephrotoxicity is not well understood. Ferroptosis and necroptosis are two programmed cell death (PCD) modalities that have been reported singly in heavy metal-induced kidney injury. However, the interaction between ferroptosis and necroptosis in HgCl-induced kidney injury is unclear.

Protective mechanism of selenium on mercuric chloride-induced testis injury in chicken via p38 MAPK/ATF2/iNOS signaling pathway.

Mercuric chloride (HgCl) is a well-known toxic heavy metal contaminant, which causes male reproductive function defects. Selenium (Se) has been recognized as an effective antioxidant against heavy metals-induced male reproductive toxicity. The aim of present study was to explore the potentially protective mechanism of Se on HgCl-induced testis injury in chicken.

Selenium ameliorates mercuric chloride-induced brain damage through activating BDNF/TrKB/PI3K/AKT and inhibiting NF-κB signaling pathways.

Mercuric chloride (HgCl), a heavy metal compound, causes neurotoxicity of animals and humans. Selenium (Se) antagonizes heavy metal-induced organ damage with the properties of anti-oxidation and anti-inflammation. Nevertheless, the molecular mechanism underlying the protective effects of sodium selenite (NaSeO) against HgCl-induced neurotoxicity remains obscure.

Antagonistic effect of selenium on mercuric chloride in the central immune organs of chickens: The role of microRNA-183/135b-FOXO1/TXNIP/NLRP3 inflammasome axis.

Mercury (Hg) is a persistent environmental and industrial pollutant that accumulated in the body and induces oxidative stress and inflammation damage. Selenium (Se) has been reported to antagonize immune organs damage caused by heavy metals. Here, we aimed to investigate the prevent effect of Se on mercuric chloride (HgCl )-induced thymus and bursa of Fabricius (BF) damage in chickens.

Selenium alleviates mercury chloride-induced liver injury by regulating mitochondrial dynamics to inhibit the crosstalk between energy metabolism disorder and NF-κB/NLRP3 inflammasome-mediated inflammation.

Mercury (Hg) is a persistent heavy metal contaminant with definite hepatotoxicity. Selenium (Se) has been shown to alleviate liver damage induced by heavy metals. Therefore, the present study aimed to explore the mechanism of the antagonistic effect of Se on mercury chloride (HgCl)-induced hepatotoxicity in chickens.

The spatiotemporal variation in heavy metals in China's farmland soil over the past 20 years: A meta-analysis.

Accurate information on farmland soil heavy metal elements is needed for pollution management and strategic decision making at the national level. In this paper, we review the Chinese literature on soil heavy metal elements (i.e.

Aberrant Gene Expression of Selenoproteins in Chicken Spleen Lymphocytes Induced by Mercuric Chloride.

Mercury (Hg) is a heavy metal widely distributed in ecological environment, poisoning the immune system of humans and animals. Selenium (Se) is an essential microelement and selenoproteins involved in the procedure of Se antagonizing organ toxicity induced by heavy metals. The aim of this research was to investigate the changes of gene expression profile of selenoproteins induced by mercuric chloride (HgCl) in chicken spleen lymphocytes.

belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients.

Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. However, in the last several years, a number of methods for calculating Boltzmann entropy for landscape mosaics and gradients were proposed.

Use of Entropy in Developing SDG-based Indices for Assessing Regional Sustainable Development: A Provincial Case Study of China.

Sustainable development appears to be the theme of our time. To assess the progress of sustainable development, a simple but comprehensive index is of great use. To this end, a multivariate index of sustainable development was developed in this study based on indicators of the United Nations Sustainable Development Goals (SDGs).

Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic.

Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder. In addition, it has been recently criticized to be thermodynamically irrelevant.

Response of selenoproteins gene expression profile to mercuric chloride exposure in chicken kidney.

Kidney is a primary target organ for mercuric chloride (HgCl) toxicity. Selenium (Se) can exert antagonistic effect on heavy metals-induced organ toxicity by regulating the expression of selenoproteins. The objective of this study was to investigate the effect of HgCl on the gene expression of selenoproteins in chicken kidney.

An Urban Scaling Estimation Method in a Heterogeneity Variance Perspective.

Urban scaling laws describe powerful universalities of the scaling relationships between urban attributes and the city size across different countries and times. There are still challenges in precise statistical estimation of the scaling exponent; the properties of variance require further study. In this paper, a statistical regression method based on the maximum likelihood estimation considering the lower bound constraints and the heterogeneous variance of error structure, termed as CHVR, is proposed for urban scaling estimation.

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images.

The quality of an image affects its utility and image quality assessment has been a hot research topic for many years. One widely used measure for image quality assessment is Shannon entropy, which has a well-established information-theoretic basis. The value of this entropy can be interpreted as the amount of information.

GIS-based analysis of population exposure to PM air pollution-A case study of Beijing.

PM, formally defined as particulate matter with diameter less than 2.5μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM are strongly linked with respiratory diseases.