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Mountain town ecosystems are fragile and highly susceptible to the impacts of human activities and ecological imbalances. This study aimed to improve the traditional ecological footprint (EF) model by incorporating expanded land functions, localised factors, and temporal continuity. Using Lushan County in Sichuan Province as a case study, we calculated spatial and temporal changes from 2009 to 2022 and evaluated sustainable development through four indicators: ecological pressure, ecological sustainability, ecological occupation, and ecological–economic coordination. The results show that from 2009 to 2022, the per capita ecological carbon footprint in Lushan County decreased by 48%, and the ecological carrying capacity declined by 9%. Despite a more than 73% reduction in the ecological surplus, indicating gradual ecological recovery, Lushan County remains in an ecological deficit state with increasing ecological unsustainability. Only forest land is in an ecological surplus state among the six land use categories, while all other categories are in ecological deficit states. Regarding ecological sustainability assessment, Lushan County's overall land use is in a strong sustainability state, with the sustainable development index gradually improving. However, ecological–economic coordination remains poor, with a high ecological occupation index and significant ecological pressure, indicating an imbalance between economic development and ecosystem protection. For future sustainable development in mountainous areas, Lushan County should focus on reducing the ecological carbon footprint and enhancing the ecological carrying capacity. These research findings provide valuable insights and methodological references for the sustainable development of mountain towns. [ABSTRACT FROM AUTHOR]

The study of Features and Characteristics of Mountainous Rural Settlements (RFCMRS) is a key factor in the development of rural settlements during the urbanization process. Mountainous rural settlements, due to their unique mountainous conditions, climate, living environments, and regional culture, are among the important subjects of research for governments and the academic community worldwide. This paper, utilizing the knowledge mapping software CiteSpace (6.2.R3) for co-citation and collaboration analysis, keyword clustering, keyword time zoning, and keyword emergence, analyzes the research trajectory, key issues, and future trends of RFCMRSs. The study finds that current RFCMRS research can be categorized into the following three key issues: "implications of climate change: risks and adaptive responses", "regional cultural heritage and economic development", and "ecological conservation and fostering harmonious symbiosis". Future research will focus on the following three development trends: "risk response based on climate resilience and ecological protection", "factors of features and characteristics based on regional culture and landscape configurations", and "human settlements based on low-carbon objectives and sustainable development principles". Lastly, the paper proposes the following three future research suggestions: "improving the evaluation system for features and characteristics of mountainous rural settlements", "deepening the study on the evolutionary phenomenon and mechanism for features and characteristics of mountainous rural settlements", and "exploring the design methods for features and characteristics of mountainous rural settlements based on the concept of sustainable development". [ABSTRACT FROM AUTHOR]

The carbon-to-nitrogen (C/N) ratio in the cultivation medium significantly influences the growth rate, vigor of mycelium, yield of fruiting bodies, and their nutritional composition. Recently, agricultural and forestry wastes have been increasingly used in cultivating Flammulina velutipes. However, systematic research on how these materials affect the nutritional and functional properties of the fruiting bodies is lacking. This study investigated the effects of different C/N ratios on F. velutipes cultivation. We evaluated the agronomic traits, nutritional composition, and flavor compounds of the fruiting bodies. Our findings reveal that an optimal C/N ratio of 27:1 in the composted substrates enhances the total yield of fruiting bodies, with 25.1% soybean straw as the primary raw material. This ratio also significantly increases the levels of crude protein, total amino acids, and essential amino acids in the fruiting bodies (p < 0.05). Fruiting bodies from the high-nitrogen (HN) treatment showed the highest content of umami amino acids and equivalent umami concentration value. Additionally, we employed an untargeted liquid chromatography–mass spectrometry (LC-MS)-based metabolomics approach to analyze the metabolite profiles of fruiting bodies cultivated in high-nitrogen (HN), medium-nitrogen (MN), and low-nitrogen (LN) substrates. We found that the carbon–nitrogen ratio can affect the flavor and quality of fruiting bodies by regulating amino acid biosynthesis and metabolism and other related pathways. Our results suggest that a C/N ratio of 27:1 offers numerous benefits for the cultivation of F. velutipes with comprehensive analyses and has promising application prospects. [ABSTRACT FROM AUTHOR]

Ecological networks in mountainous regions are vital for enhancing ecosystem functionality and ensuring regional ecological stability, alleviating the contradiction between land use and ecological development in rapid urbanization. However, the complexity of mountains and the need to establish a connection between ecosystem services and human well-being present significant challenges in constructing ecological networks. This study proposes an idea that identifies and derives an optimal scenario for ecological networks, integrating insights from ecosystem services and network analysis. The aim of the ecological network is to improve and protect the ecosystem's stability while better guiding sustainable development in mountainous regions' urban and rural areas. This study uses qualitative evaluation methods and a graph theory model to obtain the ecological network's sources and links. The results indicate that (1) 58 important ecological source areas were identified, with a total area of 5746 km2, mainly covered by woodland and water bodies. (2) An optimal and feasible scenario comprising 5 horizontal and 14 longitudinal corridors was established. Corridors rely primarily on the river system and mountains. (3) A total of 5 key ecological function areas and some ecological zones in important urban development areas were identified. Control measures for these ecological lands were proposed to enhance the effectiveness of ecosystem service construction. It can be concluded that identifying and deriving an optimal scenario of ecological networks in mountainous regions from the perspectives of ecosystem services and network analysis is feasible. [ABSTRACT FROM AUTHOR]

Climate change and urbanization intersect with escalating danger. Urban areas significantly contribute to climate change, which, in turn, poses severe threats to urban settings. The frequency and intensity of extreme events, like flooding and heat, are rising, with the need to enhance urban climate resilience (UCR) becoming more immediate. Scholarship tends to underrepresent general climate resilience in favor of specific hazards. This research seeks to contribute to the literature by exploring the case of Shanghai, China, discovering the mechanisms and characteristics of UCR governance, and examining how these outcomes are formed from a comparative gesture. The findings indicate that in Shanghai, 36.8% and 26.8% of climate resilience governance strategies are reflected in regional management and infrastructure construction led by the Water Affairs Bureau and the Meteorological Bureau. Furthermore, 30.6% of the strategies relate to the Water Affairs Bureau, showcasing a robust and integrated flood response. Meanwhile, 15.7% involve the Meteorological Bureau, boosting responses to high temperatures with better monitoring and early warning for increased flexibility and efficiency. Distinct governance processes for floods and extreme heat mirror these hazards' inherent characteristics and societal perceptions. With strong government willingness and support, Shanghai has rapidly enhanced its flood resilience capabilities within a brief timeframe. Conversely, addressing the emerging risk of extreme heat is still in the early stages of evaluation, due to the lack of a clear disaster-bearing system and identified responsible agents. This research suggests that the future of climate resilience governance in Shanghai may emphasize identifying the characteristics of critical climate-related risks, expanding social autonomy through grassroots self-governance, procuring economic backing from the central government, and applying the tool of urban spatial planning. [ABSTRACT FROM AUTHOR]

Hybrid aluminum dialkylphosphinates were synthesized from mixed diethyl-, ethylisobutyl-, and diisobutylphosphinates and Al3+ in water. The XRD, DSC, and TGA results of these Al phosphinates established that phosphinate ligands are randomly distributed in the species. The thermal and thermoxidative stabilities of the hybrid phosphinates were easily adjustable by varying the ratio of phosphinate ligands, a desirable feature for efficient flame retardants. The hybrid aluminum dialkylphosphinates with a relatively low ratio of diethylphosphinate demonstrated higher efficiency than Al diethylphosphinate and Al diisobutylphosphinate in flame-retarding polyamide 66. Detailed investigations on the thermal and thermoxidative stabilities of Al dialkylphosphinates and the morphologies of char obtained in UL-94 tests revealed that timely vaporization of degradation products of hybrid dialkylphosphinates at a temperature which closely matches the degradation temperature of polyamides and their ability to promote char formation of polyamides are two key factors which contribute to the excellent performance of hybrid aluminum dialkylphosphinates. [ABSTRACT FROM AUTHOR]

The hard-healing chronic wounds of diabetics are still one of the most intractable problems in clinical skin injury repair. Wound microenvironments directly affect wound healing speed, but conventional dressings exhibit limited efficacy in regulating the wound microenvironment and facilitating healing. To address this serious issue, we designed a thermo-sensitive drug-controlled hydrogel with wound self-adjusting effects, consisting of a sodium alginate (SA), Antheraeapernyi silk gland protein (ASGP) and poly(N-isopropylacrylamide) (PNIPAM) for a self-adjusting microenvironment, resulting in an intelligent releasing drug which promotes skin regeneration. PNIPAM has a benign temperature-sensitive effect. The contraction, drugs and water molecules expulsion of hydrogel were generated upon surpassing lower critical solution temperatures, which made the hydrogel system have smart drug release properties. The addition of ASGP further improves the biocompatibility and endows the thermo-sensitive drug-controlled hydrogel with adhesion. Additionally, in vitro assays demonstrate that the thermo-sensitive drug-controlled hydrogels have good biocompatibility, including the ability to promote the adhesion and proliferation of human skin fibroblast cells. This work proposes an approach for smart drug-controlled hydrogels with a thermo response to promote wound healing by self-adjusting the wound microenvironment. [ABSTRACT FROM AUTHOR]

During the development of rural settlements, the loss of distinctive rural characteristics, caused by the contradiction between urban expansion and the ideal of pastoralism, has attracted widespread attention from researchers worldwide. To effectively understand the development and trends of the Research of Features and Characteristics of Rural Settlements (abbreviated as RFCRS), this paper uses the knowledge mapping software CiteSpace to conduct co-citation analysis, research collaboration analysis, keyword clustering, and keyword co-occurrence. The study analyzes the basic concepts, the literature distribution characteristics, research clusters, key issues, and development trends of RFCRS. The research found that the current key issues in RFCRS include "Eco-logical services and environmental protection of rural settlements", "Sustainable planning and architectural design issues of rural settlements", and "Human settlement environment and service facility construction of rural settlements". This paper predicts that future RFCRS research trends will focus on the study of landscape features and characteristics based on ecology, climate, and aesthetics; study of architectural features and characteristics based on characteristic factors and hierarchical structure; and research on rural revitalization based on sustainable development principles. The paper also offers four priority research suggestions for researchers from different disciplines. [ABSTRACT FROM AUTHOR]

C5F10O is a promising insulating medium in the manufacturing of environmentally friendly gas-insulated switchgears (GISs). The fact that it is not known whether it is compatible with sealing materials used in GISs limits its application. In this paper, the deterioration behaviors and mechanism of nitrile butadiene rubber (NBR) after prolonged exposure to C5F10O are studied. The influence of C5F10O/N2 mixture on the deterioration process of NBR is analyzed through a thermal accelerated ageing experiment. The interaction mechanism between C5F10O and NBR is considered based on microscopic detection and density functional theory. Subsequently, the effect of this interaction on the elasticity of NBR is calculated through molecular dynamics simulations. According to the results, the polymer chain of NBR can slowly react with C5F10O, leading to deterioration of its surface elasticity and loss of inside additives, mainly ZnO and CaCO3. This consequently reduces the compression modulus of NBR. The interaction is related to CF3 radicals formed by the primary decomposition of C5F10O. The molecular structure of NBR will be changed in the molecular dynamics simulations due to the addition reaction with CF3 on NBR's backbone or branched chains, resulting in changes in Lame constants and a decrease in elastic parameters. [ABSTRACT FROM AUTHOR]

The spindle is the key working part of the horizontal cotton picker, and the wear resistance of its surface directly affects the service life of the spindle. Improving the surface performance of the spindle is fundamental for improving the performance of cotton pickers. To enhance the wear resistance of the spindle surface, this study used the physical vapor deposition (PVD) technique to prepare TiN coating on the spindle substrate surface of the cotton-picking machine to improve the spindle surface rather than the original electroplated chromium coating. The microscopic morphology of the spindle was analyzed by scanning electron microscope (SEM), the mechanical and frictional properties of the spindle were tested by a nanoindentation tester and a friction wear tester, and the morphology of the worn spindle was observed by a portable microscope and a 3D surface profiler. The test results indicated that after the PVD treatment, the surface hardness of the spindle was about 2.5 times that of the electroplated chromium spindle, and the H/E value was 2.2 times that of the electroplated chromium spindle. PVD-TiN spindle showed better mechanical properties. In the friction test, under the same conditions, the wear rate of the PVD-TiN spindle was less than that of the chrome plating spindle. In a field test of 100 hm2, the average wear area of the second tooth tip surface of the electroplated chromium spindle was about 2.17 times that of the PVD-TiN spindle. It was verified that the PVD-TiN spindle surface had better wear resistance than the electroplated chromium spindle. This study has certain research significance for the performance optimization of cotton pickers. Also, it is indicated that PVD-TiN coating can effectively improve the wear resistance of the spindle surface and provides a new method for enhancing the service life of the spindle. [ABSTRACT FROM AUTHOR]

This paper presents a method for the automatic detection of sorbite content in high-carbon steel wire rods. A semantic segmentation model of sorbite based on DeepLabv3+ is established. The sorbite structure is segmented, and the prediction results are analyzed and counted based on the metallographic images of high-carbon steel wire rods marked manually. For the problem of sample imbalance, the loss function of Dice loss + focal loss is used, and the perturbation processing of training data is added. The results show that this method can realize the automatic statistics of sorbite content. The average pixel prediction accuracy is as high as 94.28%, and the average absolute error is only 4.17%. The composite application of the loss function and the enhancement of the data perturbation significantly improve the prediction accuracy and robust performance of the model. In this method, the detection of sorbite content in a single image only takes 10 s, which is 99% faster than that of 10 min using the manual cut-off method. On the premise of ensuring detection accuracy, the detection efficiency is significantly improved and the labor intensity is reduced. [ABSTRACT FROM AUTHOR]

Since the 20th century, the escalating impact of climate risks has led to a heightened global focus on climate-change-oriented human settlement research (hereafter referred to as CCHSR). This paper presents an econometric analysis of 6830 research papers published from 1975 to 2023 (first two months) to investigate the characteristics, key issues, and research trends in CCHSR, to provide valuable insights and recommendations for future research. We used CiteSpace, bibliometric software that constructs a knowledge-mapping analysis of annual publication volume, source publications, and country distribution; this study examines the characteristics of the literature sources in CCHSR. It also explores the literature distribution through an analysis of co-citation and collaboration. The study identifies the key topics of current research through a keyword clustering analysis, including extreme climate risk response, environmental safety and sustainability enhancement, and machine learning technology application. The study identifies three research trends for future investigations by analysing keyword emergence, including climate risk governance implementation, artificial intelligence technology application, and settlement security and resilience enhancement. Finally, the study presents recommendations for priority CCHSR in three areas: theoretical system development, mechanism strategy design, and technology implementation. [ABSTRACT FROM AUTHOR]

Grain size has a significant effect on the mechanical properties of metals. It is very important to accurately rate the grain size number of steels. This paper presents a model for automatic detection and quantitative analysis of the grain size of ferrite–pearlite two-phase microstructure to segment ferrite grain boundaries. In view of the challenging problem of hidden grain boundaries in pearlite microstructure, the number of hidden grain boundaries is inferred by detecting them with the confidence of average grain size. The grain size number is then rated using the three-circle intercept procedure. The results show that grain boundaries can be accurately segmented by using this procedure. According to the rating results of grain size number of four types of ferrite–pearlite two-phase microstructure samples, the accuracy of this procedure is greater than 90%. The grain size rating results deviate from those calculated by experts using the manual intercept procedure by less than Grade 0.5—the allowable detection error specified in the standard. In addition, the detection time is shortened from 30 min of the manual intercept procedure to 2 s. The procedure presented in this paper allows automatic rating of grain size number of ferrite–pearlite microstructure, thereby effectively improving the detection efficiency and reducing the labor intensity. [ABSTRACT FROM AUTHOR]

Non-metallic inclusions are unavoidable defects in steel, and their type, quantity, size, and distribution have a great impact on the quality of steel. At present, non-metallic inclusions are mainly detected manually, which features high work intensity, low efficiency, proneness to misjudgment, and low consistency of results. In this paper, based on deep neural network algorithm, a small number of manually labeled, low-resolution metallographic images collected by optical microscopes are used as the dataset for intelligent boundary extraction, classification, and rating of non-metallic inclusions. The training datasets are cropped into those containing only a single non-metallic inclusion to reduce the interference of background information and improve the accuracy. To deal with the unbalanced distribution of each category of inclusions, the reweighting cross entropy loss and focal loss are respectively used as the category prediction loss and boundary prediction loss of the DeepLabv3+ semantic segmentation model. Finally, the length and width of the minimum enclosing rectangle of the segmented inclusions are measured to calculate the grade of inclusions. The resulting accuracy is 90.34% in segmentation and 90.35% in classification. As is verified, the model-based rating results are consistent with those of manual labeling. For a single sample, the detection time is reduced from 30 min to 15 s, significantly improving the detection efficiency. [ABSTRACT FROM AUTHOR]

In recent years, as the frequency of debris flow outbreak in strong earthquake areas has increased and the scale has been expanding, in order to explore the erosion characteristics of debris flow, a lateral erosion flume model experimental device has been designed, and 18 groups of incomplete orthogonal experiments have been carried out, with a unit weight of debris flow of 1.6~2.0 g/cm3, a content of fine particles in the accumulation of 0~28.82%, and a longitudinal slope gradient of the gully of 8°~20° as variables. The results show that the erosion width, erosion depth, and erosion volume decrease with the increase in fluid bulk density and increase with the increase in gully slope. When the longitudinal slope of the gully was 16°, the sediment with 11.40% fine particles had the strongest erosion effect, indicating that more or less fine particles are not conducive to the occurrence of lateral erosion of the gully. Finally, through multi-factor variance analysis, it was found that the order of the three factors on the gully lateral erosion degree from strong to weak is: debris flow unit weight, gully slope, and accumulation grading. The analysis results further showed that the unit weight of debris flow has the greatest impact on the erosion degree of the side slope, which is consistent with the experimental results. The research results have important reference significance for revealing the mechanism of lateral erosion and improving the level of debris flow disaster prevention in strong earthquake areas. [ABSTRACT FROM AUTHOR]

To improve the versatility of the sodium alginate-loaded bio-hydrogels, Antheraea pernyi silk gland protein/sodium alginate drug-loaded hydrogels were prepared by using an eco-friendly multiple network cross-link technology. Fourier transform infrared (FT-IR) spectroscopy and UV-Vis spectrophotometer were used separately to evaluate the chemical structure and drug release behavior of drug-loaded hydrogels. The antibacterial drug carrier gels were evaluated by using inhibition zone test against the S. aureus and E. coli. The CCK-8 assay was used to assess the biocompatibility of drug loaded hydrogels. The FT-IR results showed that there was a strong interaction within the drug loaded hydrogels, and the ASGP was beneficial to enhance the interaction within the drug loaded hydrogels. UV-Vis spectrophotometer results indicated the cumulative release reached 80% within 400 min. Antibacterial bio-hydrogels had a good antibacterial property, especially the antibacterial bio-hydrogels with bacitracin exhibits superior to other antibacterial agents. The drug-loaded bio-hydrogels exhibited the adhesion and proliferation of RSC96 cells and perfected biocompatibility. This provides a new idea for further research and development of tissue-friendly drug-loaded biomaterials. [ABSTRACT FROM AUTHOR]

Barley leaf stripe, caused by Pyrenophora graminea, is an essential systemic seed-borne disease in barley worldwide. Barley is a major cereal crop in the Qinghai–Tibet Plateau, and barley production has been threatened by leaf stripe in this region, particularly in organic farming regions. Detecting the pathogen in infected barley seeds is crucial for managing barley leaf stripe. In this study, a loop-mediated isothermal amplification (LAMP) assay was developed to detect the pathogen based on primers designed based on the sequence of the pig 14 gene (GenBank: AJ277800) of P. graminea. The optimal concentrations of MgSO4, dNTPs, and enzymes in the LAMP reaction system were established as 10.0 mM, 1.0 mM, and 8 U in a 25 μL reaction volume, respectively. The established LAMP methods for detecting P. graminea were optimally performed at 63 °C for 70 min with high reliability. The minimum detection limit was 1 × 10−2 ng·μL−1 in the 25 μL reaction system. The specificity of LAMP for P. graminea was validated with eight fungal species. All DNA extracts from P. graminea-infected barley seeds with incubation, intact, and smashed treatments were applied in LAMP and confirmed to enable the detection of the pathogen. The LAMP assay in this study could facilitate the detection of P. graminea in barley seeds onsite, provide information for seed health certificates, and help decide on seed treatment in leaf stripe management. [ABSTRACT FROM AUTHOR]

With the significant increase in global ageing and its derivative risks, governments and academic communities have been widely concerned with research on facilities of combined medical and nursing care for the elderly (FCMNCE). Using Citespace and VOSviewer bibliometric software, in this paper, we explore the evolutionary phases, hotspots, and trends in research on FCMNCE. First, the concept and connotation of FCMNCE are clarified. Secondly, based on a bibliometric analysis of the number of annual publications, disciplinary distribution, publication sources, and country distribution, we classify research on FCMNCE into four phases: the exploratory phase of influencing factors, the constructive phase of combined medical and nursing care patterns, the improvement phase of life quality, and the synergistic development phase of science and technology. Thirdly, based on a bibliometric analysis of keyword clustering, annual overlap, and burst keywords, the research hotspots of FCMNCE are identified. Finally, we predicts that future research on FCMNCE will be characterized by the trends of smart elderly facilities, smart medical services, and public health risks. Our conclusion can help researchers to understand the research status and development trends of FCMNCE and select future research directions based on their disciplinary background. [ABSTRACT FROM AUTHOR]

Wheat stripe rust-damaged leaves present challenges to automatic disease index calculation, including high similarity between spores and spots, and difficulty in distinguishing edge contours. In actual field applications, investigators rely on the naked eye to judge the disease extent, which is subjective, of low accuracy, and essentially qualitative. To address the above issues, this study undertook a task of semantic segmentation of wheat stripe rust damage images using deep learning. To address the problem of small available datasets, the first large-scale open dataset of wheat stripe rust images from Qinghai province was constructed through field and greenhouse image acquisition, screening, filtering, and manual annotation. There were 33,238 images in our dataset with a size of 512 × 512 pixels. A new segmentation paradigm was defined. Dividing indistinguishable spores and spots into different classes, the task of accurate segmentation of the background, leaf (containing spots), and spores was investigated. To assign different weights to high- and low-frequency features, we used the Octave-UNet model that replaces the original convolutional operation with the octave convolution in the U-Net model. The Octave-UNet model obtained the best benchmark results among four models (PSPNet, DeepLabv3, U-Net, Octave-UNet), the mean intersection over a union of the Octave-UNet model was 83.44%, the mean pixel accuracy was 94.58%, and the accuracy was 96.06%, respectively. The results showed that the state-of-art Octave-UNet model can better represent and discern the semantic information over a small region and improve the segmentation accuracy of spores, leaves, and backgrounds in our constructed dataset. [ABSTRACT FROM AUTHOR]

A Ni-Cr alloyed layer was prepared on the surface of Q235 steel using double-glow plasma surface alloying (DGPSA) technology and the alloyed layer was cold-rolled with different deformation rates. The microstructure, composition distribution and phase composition of the alloyed layer were characterized using a scanning electron microscope (SEM), an energy dispersive spectrometer (EDS), X-ray diffraction (XRD) and an electrochemical workstation. On this basis, the corrosion resistance of the alloyed layer was analyzed. The results showed that a Ni-Cr alloyed layer formed on the surface of Q235 steel following double-glow plasma nickel–chromium alloying. The alloy elements of Ni and Cr were distributed in a gradient from the outside to the inside and the main phases were FeCr0.29Ni0.16C0.06, Cr23C6 and γ solid solution. The alloyed layer, once cold-rolled with different deformation rates, underwent synchronous plastic deformation with the substrate, with no fracturing and spalling. The self-corrosion potential of the cold-rolled specimens in 5% H2SO4 and 3.5% NaCl solution is close to that of 304L stainless steel, and the corrosion currents are much lower. The corrosion resistance of the cold-rolled specimens is comparable to the original specimens, with no significant changes. [ABSTRACT FROM AUTHOR]

Climate issues have affected the sustainable development of global human settlements, and carbon, an essential factor affecting climate change, has become a hotspot of academic concern. This paper analyzes the research characteristics, stages and planning of carbon-oriented climate change response research in human settlements based on the literature related to research on carbon-oriented human settlements for climate change, hereinafter referred to as RCHSCC, included in the Web of Science core database since 1991, using CiteSpace and VOSviewer bibliometric software. Based on the analysis of the literature and discipline distribution, research hotspots and priorities, this paper classifies the RCHSCC into four stages: early exploration, relationship building, integrated development and deepening collaboration. Based on keyword clustering, annual overlap and keyword emergence analysis, this paper predicts that future research will have three major trends regarding climate risk management, carbon technology enhancement and urban safety and resilience research. The study aims to analyze the distribution characteristics and evolution of research on carbon-oriented human settlements for climate change from 1991 to 2022. The RCHSCC predicts three major trends in the future—climate risk management, carbon technology upgrading and urban security and resilience—and offers three recommendations for governments and planners in terms of climate change adaptation and low-carbon and efficient development in human settlements. [ABSTRACT FROM AUTHOR]

The SF6/N2 gas mixture is an alternative gas to SF6. SF6/N2 will decompose and generate nitrogenous characteristic gases, such as NO, NO2, N2O, and NF3, when exposed to long-term partial discharge. The adsorption models of Ti3C2Tx (T=O, F, OH) and NO, NO2, N2O, NF3 were constructed, and the most stable adsorption structure was selected in this paper. The electron density and density of states of the adsorption system were further analyzed to study the adsorption behavior, and the sensing performance was evaluated in the end. The results are as follows: four gases could be spontaneously adsorbed on Ti3C2Tx, and strong adsorption occurred when surface terminal groups were OH, forming hydrogen or chemical bonds with significant charge transfer. Results show that Ti3C2(OH)2 had a stronger sensing ability than Ti3C2F2 and Ti3C2O2. The conductivity of the Ti3C2Tx with different terminal groups was improved after the adsorption of NO and NO2, showing Ti3C2Tx had a good sensing ability for NO and NO2. It was difficult for the four gases to desorb from the Ti3C2(OH)2 surface, but the adsorption on the Ti3C2F2, Ti3C2O2 surface had a short recovery time at room temperature. [ABSTRACT FROM AUTHOR]

Hurricanes are one of the most devastating earth surface processes. In 2020 and 2021, Hurricanes Zeta and Ida pounded the Mississippi River Delta in two consecutive years, devastated South Louisiana, and raised tremendous concerns for scientists and stakeholders around the world. This study presents a high-resolution spatial-temporal analysis incorporating planialtimetric data acquired via LIDAR, drone, and satellite to investigate the shoreline dynamics near Port Fourchon, Louisiana, the eye of Ida at landfall, before and after the beach nourishment project and recent hurricane landfalls. The remote sensing analysis shows that the volume of the ~2 km studied beachfront was reduced by 240,858 m3 after consecutive landfalls of Hurricanes Zeta and Ida in 2020 and 2021, while 82,915 m3 of overwash fans were transported to the backbarrier areas. Overall, the studied beach front lost almost 40% of its volume in 2019, while the average dune crest height was reduced by over 1 m and the shoreline retreated ~60 m after the two hurricane strikes. Our spatial-temporal dataset suggests that the Louisiana Coastal Protection and Restoration Authority's (CPRA's) beach nourishment effort successfully stabilized the beach barrier at Port Fourchon during the hurricane-quiescent years but was not adequate to protect the shoreline at the Mississippi River Delta from intense hurricane landfalls. Our study supports the conclusion that, in the absence of further human intervention, Bay Champagne will likely disappear completely into the Gulf of Mexico within the next 40 years. [ABSTRACT FROM AUTHOR]

Selenium (Se) is essential for the basic functions of life, but the low daily intake of Se urges us to find reliable ways to increase food Se content. Plant-growth-promoting bacteria (PGPB) have shown potential in enhancing plant growth and Se accumulation. In this study, the soils collected from a Se tailing were used to isolate Se-tolerant PGPB. The results showed that a total of three strains were identified. Strain LWS1, belonging to Priestia sp., grew well in M9 medium and exhibited typical PGP characteristics by an IAA-production ability of 24.3 ± 1.37 mg·L−1, siderophore-production ability of 0.23 ± 0.04 and phosphate-solubilizing ability of 87.5 ± 0.21 mg·L−1. Moreover, LWS1 strain tolerated selenite (SeIV) up to 90 mM by a LC50 of 270.4 mg·L–1. Further investigations demonstrated that the inoculation of strain LWS1 resulted in up to 19% higher biomass and 75% higher Se concentration in rice (Oryza sativa L.) than uninoculated treatments. Our study has provided evidence that microbial Se biofortification through inoculating with Priestia sp. strain LWS1 is an alternative way to improve Se uptake in crops and maintain human health. [ABSTRACT FROM AUTHOR]

Increasing extreme rainfall events caused by global climate change have had a significant impact on urban drainage systems. As a critical component of a pumping station, a large-scale slanted axial-flow pump (SAFP) featuring high specific speed plays a critical role in mitigating urban flooding and waterlogging. In this study, to reveal the transient characteristics of a SAFP at shut-off conditions, a computational fluid dynamics (CFD) based approach with dynamic mesh was proposed. Multiple shut-off conditions with various shut-down speeds of the sluice gate (SG) were modeled. Our analysis demonstrated that both the shut-off conditions and the slanted structure have conspicuous impacts on the hydrodynamic performance of a SAFP. Reducing the shut-down speed leads to a greater reverse flow rate and higher runner speed. The water hammer effect was simulated with different shut-down speeds, increasing the water head by 5.07–10.42 m, the axial force by 163.46–297.06 kN∙m, and the axial moment by 116.05–224.01 kN∙m. Compared with the axial direction, moments in the radial directions were found with more obvious oscillation as a result of stronger rotor–stator interaction. Due to the gravitational effect of the slanted structure, the fluctuation of the runner in vertical direction presented an off-axis characteristic compared with the horizontal one. As the SG speed increased, pressure fluctuations gradually decreased at various locations across the SAFP. [ABSTRACT FROM AUTHOR]