Assessment of the elevation-dependent warming in the Qinling-Daba Mountains and its relationship with land surface albedo and aerosol optical depth from 2001 to 2021.

In this paper, we examined the elevation-dependent warming (EDW) patterns of MODIS LST across different seasons in the Qinling-Daba Mountains, further investigate the connections between the EDW patterns of Land surface temperature (LST) and land surface albedo (ALB) as well as aerosol optical depth (AOD). The key findings include: (1) Our study reveals a robust correlation between LST and air temperature in the Qinling-Daba Mountains, suggesting the feasibility of using MODIS LST to predict the temperature trends (2) During the period from 2001 to 2010, MODIS LST shows a significant EDW trend, primarily in the spring season. In contrast, a negative EDW is observed in the period during 2011-2021, which is contrary to the earlier decade, particularly during the autumn and winter seasons.

The impact of varying EDTA dosage on the flower-like morphology and thermoelectric properties of Ce-doped BiTe₃.

Thermoelectric materials have significant applications in energy utilization and environmental protection. The effect of different EDTA (ethylenediaminetetraacetic acid) dosages on the flower-like morphology and thermoelectric properties of Ce-doped BiTe nanoparticles were investigated. The Ce-doped BiTe nanoparticles were sucessfully prepared via the hydrothermal method, and the influence of EDTA dosage on the morphology, structure, and thermoelectric properties of the materials was analyzed.

Nanoparticles constructed from natural polyphenols are used in acute kidney injury.

Acute kidney injury (AKI) is a severe clinical syndrome characterized by rapid deterioration of renal function caused by a variety of pathogeneses. Natural polyphenols have been considered to have potential in the treatment of AKI due to their powerful antioxidant and anti-inflammatory activities, but their low bioavailability limits their efficacy. Polyphenol nanoparticles based on a nano-delivery system show good effects in reducing kidney injury, improving renal function and promoting renal tissue repair, and brings new hope and possibility for the treatment of AKI.

Alleviative effects of C fullerene nanoparticles on arsenate transformation and toxicity to Danio rerio.

Widely-used C fullerene nanoparticles (C) result in their release into the aquatic environment, which may affect the distribution and toxicity of pollutants such as arsenic (As), to aquatic organism. In this study, arsenate (As(V)) accumulation, speciation and subcellular distribution was determined in Danio rerio (zebrafish) intestine, head and muscle tissues in the presence of C. Meanwhile we compared how single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), graphene oxide (GO) and graphene (GN) nanoparticles alter the behaviors of As(V).

Rational design of an AIEgen for imaging lipid droplets polarity change during ferroptosis.

Ferroptosis can regulate cell death by accumulating lipid peroxides, affecting the structure and polarity of lipid droplets (LDs), but clear evidence is still lacking. Fluorescence imaging is the most powerful technique for studying LDs' function. However, developing AIE fluorescent probes with high selectivity and sensitivity for targeting LDs remains challenging.

Eco-friendly revenues for healthcare: assessing the relationship between green taxation, public health expenditures, and life expectancy in China.

Introduction: The synergy of green taxation, public health expenditures, and life expectancy emerges as a compelling narrative in the intricate symphony of environmental responsibility and public well-being. Therefore, this study examine the impact of green taxation on life expectancy and the moderating role of public health expenditure on the said nexus, particularly in the context of China, an emerging economy.

Methods: Statistical data is collected from the National Bureau of Statistics of China to empirically examine the proposed relationships.

A first-principles study on the promising thermoelectric properties of SnX (X = S, Se, Te) compounds.

SnSe has emerged as an outstanding thermoelectric material due to its exceptional performance. In this study, first-principles calculations are employed to investigate the thermoelectric properties of materials within the SnX family, where X can be either S, Se, or Te. Initially, we assessed the stability of SnX (X = S, Se, Te).

Enhancing the energetic and magnetic stability of atomic hydrogen chemisorbed on graphene using (non)compensated B-N pairs.

In this pioneering study for identifying atomic scale magnetic moment, a single hydrogen atom chemisorbed on pristine graphene exhibits distinct spin polarization. Using first-principles calculations and analyses, we demonstrate that the binding between a H adsorbate and a C substrate is substantially enhanced compensated B-N pairs embedded into graphene. Surprisingly, the interaction can be further enhanced non-compensated B-N pair doping.

Function analysis of transcription factor OSR1 regulating osmotic stress resistance in maize.

Background: Maize is a major cereal crop world widely, however, the yield of maize is frequently limited by dehydration and even death of plants, which resulted from osmotic stress such as drought and salinity. Dissection of molecular mechanisms controlling stress tolerance will enable plant scientists and breeders to increase crops yield by manipulating key regulatory components.

Methods: The candidate OSR1 gene was identified by map-based cloning.

Interlayer sp Bonds and Chirality at Bilayer Graphene Oxide/Calcium Silicate Hydrate Abnormally Enhance Its Interlayer Stress Transfer.

Graphene oxide (GO) is an ideal reinforcing material with super design capability, which can achieve the combination of strength and toughness. However, the actual effect of GO is far below the theoretical prediction. This is mainly due to the weak interface between the nanofiller and the matrix.

Fault-tolerant Hamiltonian cycle strategy for fast node fault diagnosis based on PMC in data center networks.

System-level fault diagnosis model, namely, the PMC model, detects fault nodes only through the mutual testing of nodes in the system without physical equipment. In order to achieve server nodes fault diagnosis in large-scale data center networks (DCNs), the traditional algorithm based on the PMC model cannot meet the characteristics of high diagnosability, high accuracy and high efficiency due to its inability to ensure that the test nodes are fault-free. This paper first proposed a fault-tolerant Hamiltonian cycle fault diagnosis (FHFD) algorithm, which tests nodes in the order of the Hamiltonian cycle to ensure that the test nodes are faultless.

Breaking barriers to climate finance: Asymmetric nexus between green investment and energy innovation in Europe.

Growing concerns regarding climate change and the necessity to shift towards a low-carbon economy have resulted in a significant rise in the worth of green finance for developing energy technology. This growing emphasis on green finance underscores the urgency for a nuanced exploration of the asymmetric nexus between green investment and energy innovation in Europe. The present article investigates the asymmetric relationship between green investment and energy innovation in the top ten European nations with the highest green investment (France, Netherlands, Germany, Italy, Spain, Denmark, Austria, Finland, the UK, and Sweden).

Attention-enhanced gated recurrent unit for action recognition in tennis.

Human Action Recognition (HAR) is an essential topic in computer vision and artificial intelligence, focused on the automatic identification and categorization of human actions or activities from video sequences or sensor data. The goal of HAR is to teach machines to comprehend and interpret human movements, gestures, and behaviors, allowing for a wide range of applications in areas such as surveillance, healthcare, sports analysis, and human-computer interaction. HAR systems utilize a variety of techniques, including deep learning, motion analysis, and feature extraction, to capture and analyze the spatiotemporal characteristics of human actions.

A KD-tree and random sample consensus-based 3D reconstruction model for 2D sports stadium images.

The application of 3D reconstruction technology in building images has been a novel research direction. In such scenes, the reconstruction with proper building details remains challenging. To deal with this issue, I propose a KD-tree and random sample consensus-based 3D reconstruction model for 2D building images.

Exploring positive teacher-student relationships: the synergy of teacher mindfulness and emotional intelligence.

Introduction: This study delves into the intricate synergy between teacher mindfulness and the quality of teacher-student relationships, with a specific and deliberate focus on the mediating influence of emotional intelligence. The way teachers engage with their students not only impacts the learning outcomes but also contributes significantly to the overall classroom atmosphere. Understanding the underlying mechanisms that drive these relationships is crucial for educators and policymakers alike.

Synergistic modulation of electrical and thermal transport toward promising n-type MgOCuSbSe thermoelectric performance by MO-intercalated CuSbSe.

The layered ternary CuSbSe semiconductor with ultralow thermal conductivity is particularly suitable for thermoelectric applications. Nevertheless, its poor electrical conductivity greatly lowers the dimensionless figure of merit and accordingly limits its thermoelectric applications. Here, we use first-principles calculations combined with semi-classical Boltzmann transport theory to evaluate the thermoelectric properties of MO-intercalated (M = Mg, Ca, Sr, and Ba) CuSbSe.

Image denoising and segmentation model construction based on IWOA-PCNN.

The research suggests a method to improve the present pulse coupled neural network (PCNN), which has a complex structure and unsatisfactory performance in image denoising and image segmentation. Then, a multi strategy collaborative improvement whale optimization algorithm (WOA) is proposed, and an improved whale optimization algorithm (IWOA) is constructed. IWOA is used to find the optimal parameter values of PCNN to optimize PCNN.

A novel colorimetric fluorescent probe for sensing bisulfite detection in plant and zebrafish.

Sulfur dioxide (SO) and its derivatives (SO and HSO), are important active sulfur species that play significant roles in physiological processes. Fluorescence probe imaging technology, due to its high temporal and spatial resolution, real-time non-invasive and non-destructive detection, has emerged as a valuable tool for studying SO in biological systems. In this study, we presented a colorimetric fluorescent probe for the detection of HSO.

Regional impact of aging population on carbon dioxide emissions in China: Evidence from panel threshold regression (PTR).

Carbon dioxide emission is a high-profile issue that can affect both the human economy and human existence, but few scholars have studied the relationship between these two. Therefore, this study constructs the panel threshold regression (PTR) based on the National Bureau of Statistics of China's panel data from 2002 to 2019 in 19 regions. One of the advantages of PTR is to leverage segmented functions, allowing for a more detailed analysis of the data.

China's economic development quality grows faster than economic quantity.

It is known that the rapid progress of the Chinese economy is perceived to be aligned more towards increasing the economic quantity (GDP) rather than its quality primarily owing to a large amount of carbon emission, increased environmental pollution, and high resource consumption. However, such perception comes with no single evidence or study that compares growth rates between the quantity and quality of China's economic development. Such a comparative study could provide useful information to the Chinese government and concerned agencies to manage and promote sustainable economic development in China.

Occurrence of super-diffusion in two-layer networks.

Super-diffusion is a phenomenon that can be observed in multilayer networks, which describes that the diffusion in a multilayer network is faster than that in the fastest individual layer. In most studies of super-diffusion on two-layer networks, many researchers have focused on the overlap of edges in the two layers and the mode of interlayer connectivity. We discover that the occurrence of super-diffusion in two-layer networks is not necessarily related to the overlap degree.

The Relationship between Corporate Social Responsibility and Firm Value of Chinese Firms: Exploring from Degree of Internationalization.

The purpose of this paper is to explore the relationship between corporate social responsibility (CSR) and firm value in the Chinese market and identify factors that may influence it. We discuss the relationship between CSR engagement in Chinese firms and firm value from a nonlinear perspective. In addition, we examine how the degree of internationalization in a firm may affect the relationship between CSR and firm value.

Disease- and Drug-Related Knowledge Extraction for Health Management from Online Health Communities Based on BERT-BiGRU-ATT.

Knowledge extraction from rich text in online health communities can supplement and improve the existing knowledge base, supporting evidence-based medicine and clinical decision making. The extracted time series health management data of users can help users with similar conditions when managing their health. By annotating four relationships, this study constructed a deep learning model, BERT-BiGRU-ATT, to extract disease-medication relationships.