Interfacial SbOC bond and structural confinement synergistically boosting the reaction kinetics and reversibility of Sb2Se3/NC nanorods anode for sodium storage.

Antimony selenide (Sb2Se3) has been considered as a prospective material for sodium-ion batteries (SIBs) because of its large theoretical capacity. Whereas, grievous volume expansion caused by the conversion-alloying reaction leads to fast capacity decay and inferior cycle stability. Herein, the confined Sb2Se3 nanorods in nitrogen-doped carbon (Sb2Se3/NC) with interfacial chemical bond is designed to further enhance sodium storage properties of Sb2Se3. The robust enhancing effect of interfacial SbOC bonds can significantly promote electron transfer, Na+ ions diffusion kinetics and alloying reaction reversibility, combining the synergistic effect of the unique confinement structure of N-doped carbon shells can efficiently alleviate the volume change to ensure the structural integrity. Moreover, in-situ X-ray diffraction reveals intercalation/de-intercalation, conversion/reversed conversion reaction and alloying/de-alloying reaction mechanisms, and the kinetics analysis demonstrates the diffusion-controlled to contribute high capacity. As a result, Sb2Se3/NC anode delivers a high reversible capacity of 612.6 mAh/g at 0.1 A/g with a retentive specific capacity of 471.4 mAh/g after 1000 cycles, and long-cycle durability of over 2000 cycle with the reversible capacities of 371.1 and 297.3 mAh/g at 1 and 2 A/g are achieved, respectively, and an good rate capability. This distinctive interfacial chemical bonds and confinement effect design shows potential applications in the improved conversion/alloying-type materials for SIBs.

Effects of dietary glycerol monolaurate on growth and digestive performance, lipid metabolism, immune defense and gut microbiota of shrimp (Penaeus vannamei).

The advancement of the Penaeus vannamei industry in a sustainable manner necessitates the creation of eco-friendly and exceptionally effective feed additives. To achieve this, 720 similarly-sized juvenile shrimp (0.88 ± 0.02 g) were randomly divided into four groups in this study, with each group consisting of three replicates, each tank (400 L) containing 60 shrimp. Four experimental diets were formulated by adding 0, 500, 1000, and 1500 mg kg-1 glycerol monolaurate (GML) to the basal diet, and the feeding trial lasted for 42 days. Subsequently, a 72-h White Spot Syndrome Virus (WSSV) challenge test was conducted. Polynomial orthogonal contrasts analysis revealed that with the increase in the concentration of GML, those indicators related to growth, metabolism and immunity, exhibit linear or quadratic correlations (P < 0.05). The results indicate that the GML groups exhibited a significant improvement in the shrimp weight gain rate, specific growth rate, and a reduction in the feed conversion ratio (P < 0.05). Furthermore, the GML groups promoted the lipase activity and reduced lipid content of the shrimp, augmented the expression of triglyceride and fatty acid decomposition-related genes and lowered the levels of plasma triglycerides (P < 0.05). GML can also enhanced the humoral immunity of the shrimp by activating the Toll-like receptor and Immune deficiency immune pathways, improved the phagocytic capacity and antibacterial ability of shrimp hemocytes. The challenge test revealed that GML significantly reduced the mortality of the shrimp compared to control group. The 16S rRNA sequencing indicates that the GML group can increases the abundance of beneficial bacteria. However, 1500 mg kg-1 GML adversely affected the stability of the intestinal microbiota, significantly upregulating intestinal antimicrobial peptide-related genes and tumor necrosis factor-alpha levels (P < 0.05). In summary, 1000 mg kg-1 GML was proven to enhance the growth performance, lipid absorption and metabolism, humoral immune response, and gut microbiota condition of P. vannamei, with no negative physiological effects.

Effects of dietary dihydromyricetin on growth performance, antioxidant capacity, immune response and intestinal microbiota of shrimp (Litopenaeus vannamei).

A 56-day culture trial was conducted to evaluate the effects of dietary dihydromyricetin (DMY) on growth performance, antioxidant capacity, immune response and intestinal microbiota of shrimp (Litopenaeus vannamei). 840 healthy shrimp (1.60 ± 0.21 g) in total were fed with four different levels of DMY diets at 0 (Control), 100 (D1), 200 (D2), and 300 (D3) mg/kg, respectively. Samples were collected after the culture trial, and then, a 7-day challenge experiment against Vibrio parahaemolyticus was conducted. The results demonstrated that DMY significantly enhanced the activity of protease, amylase and lipase as well as the expression of lipid and protein transport-related genes (P < 0.05). The results of plasma lipid parameters indicated that DMY reduced lipid deposition, manifested by significantly (P < 0.05) decreased plasma total cholesterol (T-CHO), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C). The expression of genes involved in fatty acid ß-oxidation and triglyceride catabolism was significantly up-regulated (P < 0.05), and genes involved in triglyceride synthesis were significantly down-regulated in DMY groups when compared to control group (P < 0.05). Moreover, dietary DMY also significantly (P < 0.05) increased the total antioxidant capacity (T-AOC), antioxidant enzymes activity and glutathione (GSH) content of shrimp, and a significant increase of total hemocytes count (THC), phagocytic rate (PR), antibacterial activity (AA) and bacteriolytic activity (BA) was observed in DMY groups (P < 0.05). The addition of DMY to the diet significantly augmented immune response by up-regulating the expression of genes related to toll-like receptors (Toll) signaling pathway, immune deficiency (IMD) signaling pathway and intestinal mucin. Furthermore, dietary DMY could modulate the composition and abundance of intestinal microbiota. In conclusion, DMY showed promising potential as a functional feed additive for shrimp to improve the growth performance and physiological health.

A Bayesian network-GIS probabilistic model for addressing human disturbance risk to ecological conservation redline areas.

Population growth and associated ecological space occupation are posing great risks to regional ecological security and social stability. In China, "Ecological Conservation Redline" (ECR) that prohibited urbanization and industrial construction has been proposed as a national policy to resolve spatial mismatches and management contradictions. However, unfriendly human disturbance activities (e.g., cultivation, mining, and infrastructure construction) still exist within the ECR, posing a great threat to ecological stability and safety. In this article, a Bayesian network (BN)-GIS probabilistic model is proposed to spatially and quantitatively address the human disturbance risk to the ECR at the regional scale. The Bayesian models integrate multiple human activities, ecological receptors of the ECR, and their exposure relationships for calculating the human disturbance risk. The case learning method geographic information systems (GIS) is then introduced to train BN models based on the spatial attribute of variables to evaluate the spatial distribution and correlation of risks. This approach was applied to the human disturbance risk assessment for the ECR that was delineated in 2018 in Jiangsu Province, China. The results indicated that most of the ECRs were at a low or medium human disturbance risk level, while some drinking water sources and forest parks in Lianyungang City possessed the highest risk. The sensitivity analysis result showed the ECR vulnerability, especially for cropland, that contributed most to the human disturbance risk. This spatially probabilistic method can not only enhance model's prediction precision, but also help decision-makers to determine how to establish priorities for policy design and conservation interventions. Overall, it presents a foundation for later ECR adjustments as well as for human disturbance risk supervision and management at the regional scale.

A novel regional-scale human health risk assessment model for soil heavy metal(loid) pollution based on empirical Bayesian kriging.

Soil heavy metal(loid)s contamination caused by rapid urbanization and industrialization seriously affects human health and hinders the global sustainable development goals (SDGs). Currently, there is a lack of comprehensive human health risk assessment (HHRA) studies for multiple land use types at the regional scale. We propose a practical risk assessment framework that integrates empirical Bayesian kriging (EBK), pollution level analyses, and modified HHRA modeling. The concentrations of copper industry-related metals (Cu, Ni, Cd, As, and Hg) in 332 topsoil samples from the south bank of the Yangtze River in Tongling were investigated. Obvious enrichment of Cu, Cd, As, and Hg was detected, and the average concentration of Cu was 5.24 times higher than the background values. The distribution of heavy metal(loid) pollution was typically high in the south and east, and low in the north and west. The mean errors of interpolation for Cu, Ni, and Hg were 0.84, 1.29, and 0, respectively, and the root mean square errors of interpolation for Cd and As were 1.29 and 0.86, respectively. Non-carcinogenic risks of soil heavy metal(loid)s were assessed as acceptable throughout the studied area. The hazard index decreased in the order As (0.448) > Ni (0.0729) > Cd (0.0136) > Hg (9.04 ×10-4) > Cu (6.41 ×10-4). Nevertheless, the carcinogenic risks of Ni, Cd, and As in 70-80% of the administrative units (AUs) were between 10-6 to 10-4, considered an unacceptable level. Exposure through the oral ingestion route accounted for 88.0-99.2% of the total three exposure routes. It is worth noting that four AUs were considered to be the priority control units, and Ni and As were identified as the priority control soil heavy metal(loid)s. This case demonstrates the feasibility and scientific validity of the new EBK-HHRA framework, which confirms that EBK can effectively predict the spatial distribution patterns of soil heavy metal(loid)s and that modified HHRA models are conducive to risk integration at the regional scale. The EBK-HHRA approach is generic and provides substantial support for risk source identification and risk management of soil heavy metal(loid)s contamination at the regional scale.

A three-dimensional interconnected molybdenum disulfide/multi-walled carbon nanotubes cathode with enlarged interlayer spacing for aqueous zinc-ion storage.

Layered molybdenum disulfide (MoS2) shows tremendous prospect as cathode material for aqueous zinc-ion batteries (AZIBs) due to the two-dimensional zinc ions (Zn2+) diffusion channels and tunable interlayer spacing. However, it is subjected to sluggish insertion/extraction kinetics, inferior electronic conductivity and inadequate active capacities. Herein, a three-dimensional (3D) interconnected MoS2/multi-walled carbon nanotubes (MWCNTs) framework is proposed to address these issues. Importantly, the MWCNTs cores offer interconnection routes for fast electrons and zinc ions transport, the expanded spacing of MoS2 interlayer with 1.05 nm can facilitate rapid Zn2+ intercalation/extraction, and the confined MoS2 layers in inner MWCNTs can mitigate the agglomeration and restacking of MoS2 nanosheets. Benefitting from the confined structural configuration, sufficient active surface and 3D structural stability, the MoS2/MWCNTs as AZIBs cathode delivers a large initial reversible capacity of 218.3 mAh/g and high coulombic efficiency of 78.2 % at 0.1 A/g. Additionally, the 3D interconnected cathode maintains nearly intact structure after a fierce galvanostatic charge/discharge process, resulting in large retained capacities of 126.3 mAh/g at 1 A/g after 650 cycles and 101.1 mAh/g at 3 A/g after 1000 cycles. This work offers a novel strategy for the structure design of two-dimensional materials to develop high-performance cathodes for AZIBs.

A Comparative Study of Various Land Use and Land Cover Change Models to Predict Ecosystem Service Value.

Ecosystem services are closely related to human well-being and are vulnerable to high-intensity human land-use activities. Understanding the evolution of land use and land cover (LULC) changes and quantifying ecosystem service value (ESV) are significant for sustainable development. In this study, we used land use and land cover data and other data from 2000 to 2020 to analyze the evolution of land use and land cover and ESV in Tongliao, China. With the goal of exploring the characteristics of different cellular automata (CA)-based models, CA-Markov, Future Land Use Simulation (FLUS), and Patch-generating Land Use Simulation (PLUS) models were used to simulate future land use and land cover, and the results were verified and compared. Considering the impacts of policies for capital farmland (CF) and ecological protection red line (EPRL) in the context of territorial spatial planning, four scenarios (inertial development, S1; CF, S2; EPRL, S3; EPRL and CF, S4) were set. The results showed that from 2000 to 2020, farmland and built-up land increased the most (341.18 km2 and 220.56 km2), while grassland had the largest decrease (380.08 km2). The main mutual transitions were from grassland and farmland. The total ESV showed a decreasing trend (from 52,364.56 million yuan to 51,620.62 million yuan). The simulation results for 2035 under four scenarios were similar, where farmland would decrease the most (96.81 km2). The ESV in 2035 would decrease from 51,620.62 million yuan to 51,541.12 million. In addition, under scenarios for the impact of policy, the land showed a trend of scattered expansion. This study provides a scientific basis for making regional sustainable development policy decisions and implementing ecological environmental protection measures.

Prioritizing risk mitigation measures for binary heavy metal contamination emergencies at the watershed scale using bayesian decision networks.

Water pollution accidents have the characteristics of high uncertainty, rapid evolution and are difficult to control, thus posing great threats to human health, ecological security, and social stability. During the last 10 years, China has faced the occurrence of six extraordinarily serious heavy metal contamination pollution events at the watershed scale. This has alerted governments and enterprises of the significance of emergency decision-making. To quantitatively prioritize risk mitigation strategies for heavy metal emergencies, a Bayesian Decision Network-based probabilistic model is proposed under the Drivers-Pressures-States-Impacts-Responses (DPSIR) framework. A Copula-based exposure risk model is embedded to simulate the fate of heavy metal ions for each risk reduction option, whose joint probability distributions can then be used as input parameters in the Bayesian Decision Network. This method was applied to the emergency response prioritization for acute Cr(VI)-Hg(II) contamination accidents in the Danshui River watershed. The results indicated that comprehensive measure (M5) was the best option for decreasing ecological and human health risks. As for a single risk mitigation strategy, risk source prevention (M1) was the best alternative compared to exposure pathway interruption (M2) and human/ecological receptor protection (M3-M4). This probabilistic method can not only address the uncertainties between certain risk sources and receptors in the BDN structure, but also realize the risk system optimization in a satisfactory/preferred mode under the DPSIR framework. Overall, it provides the probabilistic risk estimates for watershed-scale risk management and policy making for local risk managers and stakeholders.

Copula-based exposure risk dynamic simulation of dual heavy metal mixed pollution accidents at the watershed scale.

Most heavy metal exposure and pollution results from multiple industrial activities, including metal processing in refineries, and microelectronics. These issues pose a great threat to human health, ecological balance, and even societal stability. During 2012-2017, China, in particular, faced the challenge of 23 heavy metals accidents, six of which were extraordinarily serious accidents. Accidental environmental pollution is rarely caused by a single heavy metal, but rather by heavy metal mixtures. To address the need for a joint exposure risk assessment for heavy metal mixed pollution accidents at the watershed scale, a Copula-based exposure risk dynamic simulation model was proposed. A coupled hydrodynamic and accidental heavy metal exposure model is constructed for an hourly simulation of the exposure fate of heavy metals from each risk source once accidental leakage has occurred. The Copula analysis was introduced to calculate the dual heavy metal joint exposure probability in real time. This method was applied to an acute Cr6+-Hg2+ joint exposure risk assessment for 43 electroplating plants in nine sub-watersheds within the Dongjiang River downstream basin. The results indicated seven risk sources (i.e., S1, S4, H18, H23, H27-H28, and H34) that presented relatively high exposure risk to their surrounding sub-watersheds. Spatially, the acute exposure risk level was highest in the tributary basin (sub-watershed XW) than in the mainstream (sub-watershed DW2) and the river network (sub-watershed RW) of the lower reaches of the Dongjiang River. This research highlights an effective probabilistic approach for performing a joint exposure risk analysis of heavy metal mixed pollution accidents at the watershed scale.