Mitigation of heat island effect by green stormwater infrastructure: a comparative study between two diverse green spaces in Nanjing

IntroductionStudies have shown that green spaces and water bodies can alleviate heat island effects. However, uncertainty remains regarding the characteristics and influence of Green Stormwater Infrastructures (GSIs) on the cooling effects under different weather conditions. To address this issue, a comparative study was conducted between the green spaces in a wetland park with GSIs and a general green space without GSIs. MethodsIn this study, atmospheric temperatures were collected from both green spaces using mobile measurements to compare the cold island effect. In addition, the precise characteristics of the surface temperatures of the underlying surfaces in the wetland park were explored using an Unmanned Aerial Vehicle (UAV). ResultsThe results revealed that green spaces with GSIs had a stronger cooling effect on the surrounding thermal environment than green spaces without GSIs, in most cases. The heat fluxes of different types of underlying surfaces in green spaces with different GSIs varied at different time periods. During the daytime, permeable pavement and some grasslands had a warming effect. The cooling effect of the other underlying surfaces was in the order of water bodies>arbors>shrubs>grasslands. At night, the changes in heat flux were lower, and only the arbors showed cooling due to evapotranspiration.DiscussionThese findings may provide innovative ideas and methods for planning GSIs to mitigate the urban heat island effects

Deciphering the spatiotemporal trade-offs and synergies between ecosystem services and their socio-ecological drivers in the plain river network area

Understanding changes in ecosystem services (ESs) and quantitatively identifying the drivers that influence these changes are essential for achieving sustainable ecosystem development. In this study, multiple data sources and techniques, including meteorological data, land use/cover data, soil data, the InVEST model, and ArcGIS, were used to analyze the spatiotemporal variation characteristics of carbon storage, habitat quality, soil retention, water yield, and crop product supply in Xinghua City from 2000 to 2015. Additionally, we explored the causes of these changes and the interrelationships among these ESs. The results showed that: (1) During the study period, carbon storage and habitat quality declined, water yield fluctuated and increased, and soil retention had small interannual variations. The supply capacity of crop products first increased rapidly and then stabilized. (2) ESs were influenced by multiple drivers, with altitude having the strongest explanatory power for habitat quality and soil retention, and food production having the strongest explanatory power for crop product supply. (3) Relationships between different ESs were variable and changed over time. This study could enrich the understanding of spatial and temporal changes and drivers of ESs in the plain river network area, which has important implications for future land use planning and sustainable development of ESs

LUCIDENIC ACID A INHIBITS THE BINDING OF HACE2 RECEPTOR WITH SPIKE PROTEIN TO PREVENT SARS-COV-2 INVASION

High infection caused by mutations of SARS-CoV-2 calls for new prevention strategy. Ganoderma lucidum known as a superior immunoenhancer exhibits various antiviral effects, whether it can resist SARS-CoV-2 remains unclear. Herein, virtual screening combined with in vitro hACE2 inhibition assays were used to investigate its anti SARS-CoV-2 effect. Potential 54 active components, 80 core targets and 20 crucial pathways were identified by the component-target-pathway network. The binding characters of these components to hACE2 and its complexes with spike protein including omicron variant was analyzed by molecular docking. Lucidenic acid A was selected as the top molecule with high affinity to all receptors by forming hydrogen bonds. Molecular dynamics simulation showed it had good binding stability with the receptor proteins. Finally, in vitro FRET test demonstrated it inhibited the hACE2 activity with IC50 2 μmol/mL. Therefore, lucidenic acid A can prevent the virus invasion by blocking hACE2 binding with SARS-CoV-2

Data Efficient and Stability Indicated Sampling for Developing Reactive Machine Learning Potential to Achieve Ultra-long Simulation in Lithium Metal Batteries

Modelling the formation of solid-liquid interphase (SEI) is challenging as its strict requirement with both simulation accuracy and length. Machine learning potential (MLP) based molecular dynamics (MD) simulation is expected to play a role in this field while currently its use is hindered by sampling efficiency and simulation stability. In this work, we tackle the two challenges together. We propose the stability-indicated sampling (SIS) algorithm for efficiently sampling training data using physical infor mation (temperature). Unlike previous strategies, our method does not need prior knowledge of reaction networks or training multiple MLPs for uncertainty estimation. Compared with the recent proposed methods HAIR and DP-GEN, our approach gives significant improvement of sampling efficiency with less requirements with the initial training data, to realize > 10 ns MLPMD simulation using ab initio MD (AIMD) trajectory of just a few ps. We introduce the concept underlying instability consis tency by showing the accuracy of reaction mechanisms and radial distribution function (RDF) can be improved by SIS-MLPMD, although their information is not explicitly used in our sampling decision. Furthermore, we show that long-time MLPMD simu lation of Lithium metal battery (LMB) can not only reproduce some well-known SEI components including LiF, Li2O, LiOH, LiS and the incomplete N-S breaking in high concentration systems, but also ionic aggregation structures of LiF, which is not shown in our AIMD training data but matches previous results of electrochemical impedance spectroscopy. Our work is expected to help accelerate future investigations, especially for studying long-time (≥ ns scale) reaction dynamics in interfacial problems

A multiple-fidelity Method for Accurate Simulation of MoS 2 Properties Using JAX-ReaxFF and Neural Network Potentials

Reactive force field (ReaxFF) is one of the most commonly used force field to model the chemical reactions on atomic level. Recently, JAX-ReaxFF, combined with auto- matic differentiation, has been used to efficiently parameterize ReaxFF. However, pre- dicted properties using parameterized ReaxFF may be inaccurate due to the inductive bias of its analytical formula. While neural network-based potentials (NNPs) trained on density functional theory (DFT)-labeled data offer a more accurate method, it re- quires a large amount of training data to be trained from scratch. To overcome these issues, we present a multiple-fidelity method that combines JAX-ReaxFF and NNP, and apply the method on MoS 2 , a promising two-dimensional (2D) semiconductor for flexible electronics due to its excellent mechanical, optical, and electronic properties. By optimizing ReaxFF for MoS 2 and incorporating implicit prior physical information in the functional forms, we show that ReaxFF can serve as a cost-effective way to generate pretraining data, facilitating more accurate simulations of MoS 2 properties, such as the convex hull diagram, sulfur vacancy formation, and interaction with S 8 using SchNet. Moreover, in the Mo-S-H multi-element system, the pretraining strat- egy can reduce root-mean-square errors(RMSE) of energy by 20%. This approach can be extended to a wide variety of material systems, accelerating their computational research

Cooperated control strategy of generator re-dispatching and multi-HVDC modulation after ultra HVDC block

With the increase of DC project voltage level and transmission capacity, the security and stability risk caused by DC blocking is gradually increasing. Aiming at reserve dispatch after ultra-high voltage direct current (UHVDC) block, scenarios of DC power modulation participating in dispatching are presented. Mathematical models of generator re-dispatching incorporated control of DC in AC/DC hybrid grid in three situations in terms of enough reserve capacity in the disturbed province, regional reserve capacity sufficient and insufficient to make up for the power deficiency are presented. Then, a decision-aid system for optimal reserve dispatch after UHVDC block is proposed. Simulation results of Central China power grid indicate that the proposed scheduling scheme can reduce the operation risks of security and load loss if necessary

Identifying CTH and MAP1LC3B as ferroptosis biomarkers for prognostic indication in gastric cancer decoding

Abstract Gastric cancer (GC), known for its high incidence and poor prognosis, urgently necessitates the identification of reliable prognostic biomarkers to enhance patient outcomes. We scrutinized data from 375 GC patients alongside 32 non-cancer controls, sourced from the TCGA database. A univariate Cox Proportional Hazards Model (COX) regression was employed to evaluate expressions of ferroptosis-related genes. This was followed by the application of Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate COX regression for the development of prognostic models. The composition of immune cell subtypes was quantified utilizing CIBERSORT, with their distribution in GC versus control samples being comparatively analyzed. Furthermore, the correlation between the expressions of Cystathionine Gamma-Lyase (CTH) and Microtubule Associated Protein 1 Light Chain 3 Beta (MAP1LC3B) and the abundance of immune cell subtypes was explored. Our bioinformatics findings underwent validation through immunohistochemical analysis. Our prognostic models integrated CTH and MAP1LC3B. Survival analysis indicated that patients categorized as high-risk, as defined by the model, exhibited significantly lower survival rates compared to their low-risk counterparts. Notably, CTH expression inversely correlated with monocyte levels, while MAP1LC3B expression showed an inverse relationship with the abundance of M2 macrophages. Immunohistochemical validation corroborated lower expressions of CTH and MAP1LC3B in GC tissues relative to control samples, in concordance with our bioinformatics predictions. Our study suggests that the dysregulation of CTH, MAP1LC3B, and the accompanying monocyte-macrophage dynamics could be pivotal in the prognosis of GC. These elements present potential targets for prognostic assessment and therapeutic intervention

Spontaneous Emulsification via Once Bottom-Up Cycle for the Crude Oil in Low-Permeability Reservoirs

The formulation and mechanism of a hybrid ultralow interfacial tension spontaneous emulsification (SE) system consisting of alkyl polyglucoside surfactant and low-concentration alkali were investigated to enhance oil recovery for low-permeability reservoirs. Multiple-light scattering was used to characterize the stability and demulsification process of oil-in-water (O/W) emulsions. The emulsions were evaluated in terms of droplet size distribution, ζ potential, and three-phase rheological property. The average droplet size of the optimum SE O/W emulsion is about 0.2 µm, which is smaller than the average diameter of the low-permeability throats (0.2-4.0 µm). The coalescence and floatation of emulsion droplets are well-deferred. The oscillation-shear-oscillation rheological property could be further improved with the presence of the optimum system. This can be attributed to the synergistic effect of surfactants and alkali, which enables the formation of a more tight arrangement film of surfactants at the oil-water interface. Subsequently, diffusion of the surfactant from the interface to the bulk phase is inhibited by enhancing the interfacial viscosity. Moreover, the flooding results from the visual micromodel experiments demonstrate that the small residual oil droplets could be displaced easily in the porous media. The newly formulated SE system can be applied to enhance oil recovery for low-permeability reservoirs