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• This study presents a systematically downscaling framework for GRACE-derived data. • Machine learning and remote sensing tools are used to present drought maps. • The efficiency of using ConvLSTM model is explored over previous methods. • The significant reasons for the water crisis and drought in Iran are investigated. • The results indicate that Iran has experienced water resource overexploitation. The current study proposes a new method to downscale the monthly GRACE-derived Terrestrial Water Storage Anomaly (TWSA) to 10 km spatial resolution over Iran using deep learning methods. First, the growing neural gas (GNG) method is utilized to cluster the TWSA data to find similar patterns. The Silhouette Chou Davies (SCD) validity measure, a combination of three robust cluster validity measures, is used to evaluate the performance of the GNG method. Then, the feasibility of deep learning Convolutional Long Short-Term Memory (ConvLSTM), shallow learning Feed Forward Neural Networks (FFNN), and Random Forest (RF) are examined in downscaling GRACE-derived TWSA using only remote sensing images. The results indicate that the deep learning method outperforms the RF and FFNN models by 7 % and 18 %, respectively. Then, the Ground Water Storage (GWS) data are isolated from TWSA, showing an agreement between the GRACE-derived GWS and ground-based measurements with R2 = 0.76. Additionally, the downscaled TWSA is used to generate annual drought frequency and change detection maps for the GWS from 2002 to 2016. Annual standardized precipitation index (SPI) drought frequency maps are also produced to gain deeper insight into the water resource scarcity of Iran. The results indicate that Iran has experienced water resource overexploitation since 2011 for agricultural activities, while meteorological drought is a trigger and intensifier for the water crisis in Iran. According to the results, Iran experienced exceptional drought in some regions, and the GWS has decreased all over the country. In addition, further analysis of Iran's water resources is provided until 2022. The current study calls for integrated sustainable water resources management in Iran; otherwise, irreversible water and environmental problems with higher frequencies will be expected in the near future. [ABSTRACT FROM AUTHOR]

The accurate estimation of coastal water quality parameters (WQPs) is crucial for decision-makers to manage water resources. Although various machine learning (ML) models have been developed for coastal water quality estimation using remote sensing data, the performance of these models has significant uncertainties when applied to regional scales. To address this issue, an ensemble ML-based model was developed in this study. The ensemble ML model was applied to estimate chlorophyll-a (Chla), turbidity, and dissolved oxygen (DO) based on Sentinel-2 satellite images in Shenzhen Bay, China. The optimal input features for each WQP were selected from eight spectral bands and seven spectral indices. A local explanation strategy termed Shapley Additive Explanations (SHAP) was employed to quantify contributions of each feature to model outputs. In addition, the impacts of three climate factors on the variation of each WQP were analyzed. The results suggested that the ensemble ML models have satisfied performance for Chla (errors = 1.7%), turbidity (errors = 1.5%) and DO estimation (errors = 0.02%). Band 3 (B3) has the highest positive contribution to Chla estimation, while Band Ration Index2 (BR2) has the highest negative contribution to turbidity estimation, and Band 7 (B7) has the highest positive contribution to DO estimation. The spatial patterns of the three WQPs revealed that the water quality deterioration in Shenzhen Bay was mainly influenced by input of terrestrial pollutants from the estuary. Correlation analysis demonstrated that air temperature (Temp) and average air pressure (AAP) exhibited the closest relationship with Chla. DO showed the strongest negative correlation with Temp, while turbidity was not sensitive to Temp, average wind speed (AWS), and AAP. Overall, the ensemble ML model proposed in this study provides an accurate and practical method for long-term Chla, turbidity, and DO estimation in coastal waters. • A machine learning (ML) based ensemble model was proposed for the estimation of water quality parameters. • The feature selection was conducted for the ML-based ensemble model. • The ML-based ensemble model improved the estimation accuracy of non-optical active constituent. • SHAP method was employed to quantify the contribution of the input features. • Climate factors driving mechanism was considered on interannunal dynamics of water quality. [ABSTRACT FROM AUTHOR]

This paper proposed a dynamic current-enhancement technique based on AC coupling network and feedforward compensation capacitor for current-feedback low-dropout regulators (LDOs). Compared with traditional reported current-feedback LDOs, this design exhibits wider input voltage range, greater load capacity and fast transient response, yet no extra power consumption is introduced. Moreover, a complete stability analysis under full load range is given in this paper. The proposed LDO is fabricated in SMIC 0. 18 μ m CMOS process. The input voltage range is 0.8–2.2 V and the maximum load current is 50 mA. The experiment results indicate that the overshoot and undershoot are 76 mV and 141 mV respectively when the load current is varied from 0 to 50 mA within 300 ns under the load of 100 pF load capacitor. • This paper proposed a dynamic current-enhancement technique for current-feedback lowdropout regulators. It significantly reduces the overshoot and undershoot and improves large signal transient response. More importantly, it is not implemented at the expense of more quiescent current. [ABSTRACT FROM AUTHOR]

Hydrogen is widely believed to be a promising fuel to solve the global energy crisis and environmental issues. The catalytic system represented by metal‐supported catalysts is an important process of upgrading the hydrogen source in industry. Single‐atom catalysts (SACs), which inherit the advantages of homogeneous and heterogeneous catalysts, provide a broad prospect for low‐cost H2 production technology. This review focuses on the potential mechanisms in the rational design of SACs, including active sites, coordination configuration, mass loading, heteroatom‐doping, and metal−support interaction. The design strategies of single metal atoms on different supports are reviewed to give a proposal on how to immobilize the atomic active sites and modulate the geometric/electronic structures of SACs. Subsequently, the synergistic effect in SACs and the dynamic evolution of the atomically dispersed heterometal catalysts are introduced, aiming to provide further guidelines for H2 evolution SACs. H2 generation from the water−gas shift reaction and electro‐/photocatalytic water splitting are the main research directions at present. The latest progress of SACs employed in these applications is thoroughly reviewed. At the end of this review, personal perspectives on the prospects and challenges of H2 evolution SACs are put forward, hoping to promote the rapid development of SACs toward superior H2 evolution performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • NO 3 -N and TN are removed by 95% and 84% without NO 2 -N detected. • CS isolates Fe0 from NO 3 -N to alleviate biological and chemical competition. • Fe0@C shows high electron selectivity in wide range of pH, temp. and NO 3 -N. • H 2 is the main electron donor and dominates the autotrophic denitrification. • The sustained electrons released from Fe0@C promote TN removal capacity by Fe0@C. Iron-carbon micro-electrolysis (IC-ME) can promote Fe0 corrosion to provide H 2 or e− as electron donors for autotrophic denitrifier under organic-limited wastewater, but also stimulate the chemical reduction of NO 3 -N to undesired NH 4 -N. Therefore, it is still a challenge to optimize the eletron pathways provided by Fe0 to improve its eletron selectivity for biodenitrification. Herein, a Carbon-coated Iron (Fe0@C) Autotrophic Denitrification (CCIAD) system was first established to achieve higher removal efficiency of NO 3 -N (95%) and TN (84%) without NO 2 -N accumulation, and the role of carbon shell (CS) in Fe0@C was systematically evaluated. Hydrophobic CS could prevent iron oxidation from oxygen and isolate Fe0 from NO 3 -N to alleviate the competition of biological and chemical processes for reducing nitrate. In addition, the CS promoted e− generation, while inhibited the adsorption of NO 3 -N, thereby increasing the H 2 production. Therefore, the assembly of carbon coated Fe0 regulated the electron pathway so that H 2 became the main electron donor and dominated the autotrophic denitrification, thereby improving the electron efficiency of Fe0 (82.7%). The sustained electron release of Fe0@C improved its TN removal capacity (78 mg N/g Fe). This study shed light on the electronic pathways provided by Fe0@C and advanced our understanding of Fe0@C-based bio-denitrification for the purpose of next-generation Fe0 design. [ABSTRACT FROM AUTHOR]

• The deep learning method is used to simulate the canopy stomatal resistance (r sc);. • A two-objective monte Carlo-based bayesian framework is proposed to estimate soil surface resistance (r ss);. • Bayesian model evidence (BME) is used to evaluate model performance;. • Evapotranspiration (ET) simulation and partition are evaluated in urban forest lands;. • The enhanced shuttleworth-wallace model has the ability to simulate regional scale ET. The Shuttleworth-Wallace two-source (S-W) model has been widely applied to estimate evapotranspiration (ET) and its components in a variety of vegetation-covered surface conditions. However, significant uncertainties occur in calculation of vegetation canopy resistance (r sc) and soil surface resistance (r ss). In this study, an enhanced version of the S-W model is proposed to simulate and partition ET. The deep learning (DL) approach which combined soil, vegetation, and meteorological observation data, is employed to simulate r sc. A two-objective Monte Carlo-based Bayesian parameter optimization (TOMCBP) is developed to determine the empirical parameters for the r ss calculation. The enhanced S-W model was verified based on the three years of eddy correlation (EC) and stable water isotope observations in an urban forest land located in Tianjin, China. Results suggest the machine learning-based r sc parametric scheme effectively improved the performance of the S-W model for the ET simulation. The TOMCBP-based r ss parameterization scheme can improve the performance of the S-W model for ET partition. Furthermore, this study used the Bayesian model evidence (BME) to evaluate the performance of different models. BME is shown to balance the model complexity and fitting accuracy when compared with traditional statistical parameters, thus showing superiority in model evaluation and selection. This study improves the physical mechanism and performance of the S-W model and proposes a new method for r sc and ET components simulation based on machine learning. The enhanced S-W model is more precise and provides guidance for irrigation measures in urban woodland areas. [ABSTRACT FROM AUTHOR]

Aims. Ulcerative colitis (UC) is a type of chronic idiopathic inflammatory bowel disease with a multifactorial pathogenesis and limited treatment options. The aim of the present study is to investigate the hydrogen deuterium exchange mass spectrometry (HDX-MS) behaviors of fermented deoxyanthocyanidins and their molecular mechanisms to alleviate UC by using quantum chemistry and network pharmacology. Methods. Tandem MS indicated at least two fragmentation pathways through which deuterated vinylphenol-deoxyanthocyanidins could generate different product ions. Quantum calculations were conducted to determine the transition states of the relevant molecules and analyze their optimized configuration, vibrational characteristics, intrinsic reaction coordinates, and corresponding energies. The potential targets of deoxyanthocyanidins in UC were screened from a public database. The R package was used for Gene Ontology (GO) and KEGG pathway analyses, and the protein–protein interactions (PPIs) of the targets were assessed using Search Tool for the Retrieval of Interacting Genes (STRING). Finally, molecular docking was implemented to analyze the binding energies and action modes of the target compounds through the online tool CB-Dock. Results. Quantum calculations indicated two potential fragmentation pathways involving the six-membered ring and dihydrogen cooperative transfer reactions of the vinylphenol-deoxyanthocyanidins. A total of 146 and 57 intersecting targets of natural and fermented deoxyanthocyanidins were separately screened out from the UC database and significant overlaps in GO terms and KEGG pathways were noted. Three shared hub targets (i.e., PTGS2, ESR1, and EGFR) were selected from the two PPI networks by STRING. Molecular docking results showed that all deoxyanthocyanidins have a good binding potential with the hub target proteins and that fermented deoxyanthocyanidins have lower binding energies and more stable conformations compared with natural ones. Conclusions. Deoxyanthocyanidins may provide anti-inflammatory, antioxidative, and immune system regulatory effects to suppress UC progression. It is proposed for the first time that fermentation of deoxyanthocyanidins can help adjust the structure of the intestinal microbiota and increase the biological activity of the natural compounds against UC. Furthermore, HDX-MS is a helpful strategy to analyze deoxyanthocyanidin metabolites with unknown structures. [ABSTRACT FROM AUTHOR]

The reactive oxygen species (ROS) generated by photoinduced molecular oxygen (O 2) activation has attracted great attention in environmental remediation and pollution control. Herein, we establish a facile sulfur doping strategy that promotes the activation of molecular oxygen over BiOCl for rapid and continuous degradation of organic pollutants. In this work, we demonstrate that the significantly enhanced built-in electric field (BIEF) induced by the heterogeneous introduction of S atoms not only multiplies the electron concentration in the BiOCl matrix, but also accelerates the rapid separation/transfer of charge carriers and inhibits recombination. Driven by this, the exciton behavior in the BOC undergoes a transformation. The electrons generated through exciton dissociation activate the adsorbed O 2 on the surface into superoxide radicals (•O 2 –). Benefited from the superior O 2 activation efficiency, the degradation rate constant of ciprofloxacin (CIP) the fabricated S-doped BiOCl increased by 8.8 times, under visible light. This work proposes a strategy to promote the photocatalytic O 2 activation via tuning BIEF and manipulating excitonic effects, which affords new perspective for understanding the reaction mechanisms related to charge transfer in photocatalytic systems. [Display omitted] • S doping dramatically alter morphology and physicochemical characteristics of BiOCl. • Enhanced built-in electric field induced by S doping promotes separation and migration of charge carriers in bulk BiOCl. • Remarkable efficiency of O 2 activation is achieved over S-doped BiOCl with abundant O vacancies. • Boosted dissociation of excitons into charge carriers transforms O 2 activation behavior. • S-doped BiOCl exhibits remarkable performance toward photocatalytic degradation of CIP and various antibiotics in water. [ABSTRACT FROM AUTHOR]

PCM Trombe walls have been an effective passive technology to achieve energy efficiency. However, the majority of previous research investigated the PCM Trombe walls primarily focused on structural improvement, and very few studies have focused on mixed-dry climate Therefore, in this study, ten scenarios were created and simulated by the validated CFD model under a mixed dry climate. The findings indicate that in summer, an external PCM layer with a melting point of 38 °C could reduce the maximum peak load by 48.9 %, decrease the fluctuation amplitude by 76 %, reduce the cooling load by 14.4 %, compared to the reference case, and yields time lags of 4.5 h and 6.1 h for the maximum and minimum indoor temperatures, respectively. In winter, an external PCM layer with a melting point of 30 °C can reduce the thermal load by 38.2 %, decrease the fluctuation amplitude by 28.5 %, compared to the reference case, and achieve time lags of 4.0 h and 1.7 h for the minimal and maximum indoor temperatures, respectively. Overall, the PCM layer should be placed adjacent to the air channel, and the appropriate PCM melting points in summer and winter are different. [ABSTRACT FROM AUTHOR]

• GALDIT inspired, z-number based modeling applied for GW quality assessment. • Method applied for aquifers around Urmia Lake where is facing environmental problems. • Classic GALDIT, Fuzzy logic (FL) and proposed Z-number based methods were compared. • GALDIT parameters and EC considered as inputs and output for FL and Z-number models. • Z-number outperformed GALDIT, FL methods by 85% and 35%, respectively based on HSS. Groundwater (GW) quality assessment is an essential issue, especially in arid and semi-arid regions, due to its critical role in obtaining requirements for freshwater. The GALDIT method is widely recognized as a practical approach for assessing GW susceptibility, which considers six key factors, including the occurrence of groundwater (G), hydraulic conductivity of the aquifer (A), elevation of groundwater above sea level (L), distance from the shoreline (D), impact of existing seawater intrusion (I), and thickness of the aquifer (T). The GALDIT method, being an unsupervised model, has a drawback in that it depends on expert opinion for parameter ranking, leading to an increase in uncertainty. To address this uncertainty and evaluate the susceptibility of the aquifers of Urmia lake basin to saltwater intrusion, this study employed the Z-number which is a novel adaptation of Fuzzy Logic (FL). In contrast to classic FL that does not account for data reliability, the Z-number approach considers both constraints and data reliability, making it a more effective method to manage data uncertainty compared to classic fuzzy models. To illustrate this methodology, the GALDIT parameters (inputs) and Electrical Conductivity (EC) values (outputs) were employed to determine the vulnerability of aquifers. Additionally, the GALDIT method was utilized as a benchmark model to evaluate the inherent vulnerability of aquifers, and its outcomes were compared with those of the proposed model. Upon analyzing the results, it was found that the Z-number Based Modeling (ZBM) not only outperformed the GALDIT method but also enhanced the quality of outcomes by 85% and 35% based on Heidke Skill Score (HSS) and Total Accuracy (TA) criteria compared to the classic FL. [ABSTRACT FROM AUTHOR]

Vibration signals from elevators contain critical information pertinent to condition monitoring and fault diagnosis. However, the presence of noise in real-world data acquisition environments invariably contaminates these signals, thus compromising the effectiveness of condition monitoring and fault diagnosis. This study proposes a novel denoising method based on deep residual U-Net to mitigate noise in the vertical vibration signals of elevator cabins. The proposed network is a convolutional neural network with skip connection and multi-scale convolution structure, which can automatically learn the potential mapping between noisy and clean signals. The robustness and effectiveness are verified through experiments using real-world vibration signals compared with three conventional denoising methods in both linear and non-linear systematic indicators. Moreover, the proposed method exhibits higher accuracy and promising prospects in practical applications when applied to elevator travel distance monitoring. • The feasibility of elevator vibration signal denoising based on deep learning is investigated. • A novel method based on deep residual U-Net for elevator vibration signal denoising is proposed. • The effectiveness and superiority in both linear and nonlinear systematic indicators are verified. • The robustness under unknown intensities and types of noise is conducted. • The engineering prospect in the application of elevator condition monitoring is explored. [ABSTRACT FROM AUTHOR]

A data-driven model is commonly employed for partitioning eddy covariance (EC) CO 2 fluxes (NEE) into ecosystem respiration (ER) and gross primary productivity (GPP) fluxes. However, current data-driven solely utilizing one sub-neural network to estimate above-ground respiration (ER a) and below-ground respiration (ER b), leading to substantial uncertainty. To address this issue, this research introduces a hybrid four-sub-deep neural network (HFSD) for partitioning NEE into GPP and ER. The HFSD employs dual sub-deep neural networks (DNNs) to independently estimate ER a and ER b. Additionally, the HFSD incorporates GPP and various environmental variables to predict vegetation transpiration (T). The GPP and ER partitioned by the HFSD model are constrained by EC-derived T and NEE. Comparison between the partitioned GPP and ER by the HFSD model and the nighttime (NT) and daytime (DT) temperature-driven methods is conducted across three EC towers. The results indicate that the dual sub-DNNs architecture enhances the accuracy of ER simulations, while integrating EC-derived T as a constraint improves the accuracy of GPP simulations. Furthermore, the HFSD model exhibits the capability to simulate GPP and ER under extreme scenarios and demonstrates strong generalization potential. Correlation analyses suggest that seasonal variations in GPP and ER are primarily influenced by solar radiation (R a) and air temperature (T a) during wet seasons, while GPP and ER are highly sensitive to soil moisture (SM) during dry seasons. This study advances the biophysical description of data-driven models for NEE partitioning and enhances the accuracy of GPP and ER estimates. • We propose a hybrid four-sub-deep neural network to partition NEE into GPP and ER. • Above-ground and below-ground respiration are estimated using dual sub-DNNs. • The predicted GPP and ER are constrained by vegetation transpiration and NEE. • HFSD demonstrates excellent generalization potential, even under extreme events. • The variations in GPP and ER are controlled by multiple environmental variables. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new quorum quenching strain LZX01 was isolated and produce intracellular lactonase. • LZX01 can rapidly degrade AHL and effectively mitigated membrane biofouling. • LZX01 decreased activated sludge TB-EPS and enhances its hydrophilicity. • LZX01 affected the growth of biofilm-associated bacteria but not MBR performance. • LZX01 still has high QQ activity in the environment rich in some toxic substances. Significant progress has been made in mitigating membrane biofouling by microbial quorum quenching (QQ). More efficient and survivable QQ strains need to be discovered. A new strain named Bacillus thuringiensis LZX01 was isolated in this study using a low carbon source concentration "starving" method from a membrane bioreactor (MBR). LZX01 secreted intracellular lactonase to enable QQ behavior and was capable of degrading 90 % of C8-HSL (200 ng/mL) within 30 min, which effectively delayed biofouling by inhibiting the growth of bacteria associated with biofouling and improving the hydrophilicity of bound extracellular polymeric substances. As a result, the membrane biofouling rate of MBR adding LZX01 was four times slower than that of the control MBR. Importantly, LZX01 maintains its QQ activity even in environments contaminated with typical toxic pollutants. Therefore, with high efficiency, toxicity resistance, and easy culture, LZX01 holds great potential and significant promise for biofouling control applications. [ABSTRACT FROM AUTHOR]

• An innovative continuous-flow miniaturized MFC-based biosensor was developed. • Substrate diffusion, degradation, and concentration was simulated by CFD method. • Optimal MFC dimension and detection range was established. • The detection range of MFC-based biosensor was influenced by the channel width. • The stability and sensitivity was significantly influenced by channel length. An innovative continuous-flow miniaturized MFC-based biosensor was developed in this work. The substrate distribution inside sensor channels has important influence in the biofilm uniformity, and consequently in the sensor performance. However, such miniaturized device is too small in dimension to be directly measured. In this work, computational fluid dynamics (CFD) was chosen to simulate the diffusion of substrate and its concentration distribution in sensors, with different channel dimensions and various flow rates. CFD results were in good agreement with the experimental data. Results demonstrated that channel length has a significant influence on the stability and sensitivity of MFC-based biosensor whilst the detection range was mostly influenced by the channel width. It found that MFC sensor with 10 mm × 10 mm dimension and 50 μL/min flow rate could have the most uniform substrate distribution for 0–492 mg/L BOD. The CFD method developed in this research could also be utilized in the calibration of MFC-based sensor. [ABSTRACT FROM AUTHOR]

• The phase equilibria of the Zn-Mn system in the Zn-rich side Zn-rich at 400 °C was obtained. • The space group of the δ 1 -MnZn 9 phase was determined to be P 6 3 /mmc. • A set of self-consistent thermodynamic parameters for the Zn-Mn system was obtained by the CALPHAD approach. • The reliability of the thermodynamic parameters was verified by the Scheil solidification simulation. The phase relationship of the Zn-Mn system in the range of 0–12 at% Mn at 400 °C was experimentally investigated. Four phases, viz, ε, δ 1 -MnZn 9 , ζ-MnZn 13 and (Zn) were observed in the present work. The δ 1 -MnZn 9 phase was determined to be a hexagonal structure (space group P 6 3 /mmc , No. 194, lattice parameters: а = b = 1.2771 Å, c = 5.7069 Å) based on the single-phase X-ray diffraction data and confirmed by the analysis of the high-resolution image and selected area electron diffraction. Presently obtained experimental results, combined with the reliable literature data, were used to develop a refined thermodynamic description of the Zn-Mn system utilizing the CALPHAD (CALculation of PHAse Diagram) method. The present calculated results can reproduce the experimental data well. The reliability of the presently obtained thermodynamic parameters was also verified by the Scheil solidification simulation and phase analysis of the as-cast alloys. [ABSTRACT FROM AUTHOR]

In this paper, sediment microbial fuel cell (SMFC) with nano‐Fe2O3 modified anode was investigated to enhance in‐situ remediation. Results showed that the modification led to higher removal of total organic matter (TOC) after 50 days. Anodic microbial community was further analyzed. It was found that the decrease of relative abundance of exoelectrogens and the suppression of methanogens led to the reduction of the power generation in SMFC with modified anode. Longilinea was one of key bacteria regarding TOC degradation. Besides, potential environmental effects resulting from SMFC and nano‐Fe2O3 modification were also discussed. The competition of exoelectrogens with methanogens for nutrient potentially resulted in the reduction of methane emission. The SMFC system could inhibit the growth of fecal bacteria and the nano‐Fe2O3 modified anode had stronger inhibitory effect, which further reduce the risks induced by fecal bacteria to human health. The modification could further maintain the biodiversity of eucaryon and achieve higher ecosystem stability. [ABSTRACT FROM AUTHOR]

• A surface energy balance constrained deep learning (DL-SEB) model was proposed. • The DL-SEB model improved ET simulations under extreme events. • Global land surface ET increased 3.8% during 2000–2019. • The long-term annual average global land surface ET was 613 mm/yr. • El Niño events altered short-term global ET variation. Estimating global land surface evapotranspiration (ET) is of great significance for assessing the impact of climate change on the global hydrological cycle and energy balance. In this study, we propose a surface energy balance constrained deep learning (DL-SEB) model for simulating global land surface evapotranspiration (ET). The accuracy of the DL-SEB model in estimating ET was tested using FLUXNET observations. The results suggested that the proposed DL-SEB model significantly enhanced the simulation capability of extreme ET events compared with the original deep learning model (without being coupled with the energy balance equation). The DL-SEB model was further applied to reconstruct global ET changes during 2000–2019 based on meteorological, soil, vegetation, and flux data sets. The annual average global land surface ET was 613 mm/yr during the period 2000–2019 (exclude Antarctica and deserts). The global land surface ET exhibited a significant upward trend with average increase rate of 1.16 mm/yr during the past two decades, which corresponds to approximately 3.8% increase above the mean global ET during 2000–2019. The positive trend of global land surface ET was driven by the combined effect of air temperature (T a), soil moisture (SM), net radiation flux (R n) and leaf area index (LAI). The natural climatic events such as El Niño events significantly altered short-term global ET variation, but did not changed the long-term increase trend of global ET. This study enhanced the understanding of the impact of climate change on the global land surface ET. The proposed DL-SEB model achieved a physics-based, smart and reliable ET simulation at global and regional scales. [ABSTRACT FROM AUTHOR]

[Display omitted] • The best-performing micron-scale Fe0 relieved Cr(VI) inhibition on anammox by over 195%. • Hydroxyl-containing proteins in EPS were improved with mFe0 addition. • mFe 3 O 4 stimulated more production of EPS and cytochrome c than Fe0. • Cytochrome c was the most critical indicator in the anammox recovery. Hexavalent chromium Cr(VI) is widely present in industrial wastewater, which can inhibit anammox performance significantly. Iron is a critical element of anammox metabolism and also has the capacity to remove Cr(VI). In this study, batch experiments were conducted to investigate the effects of commercial zero-valent iron (Fe0) and ferroferric oxide (Fe 3 O 4) in the nano-(n) and micron-(m) scales (mFe0, nFe0, mFe 3 O 4 , and nFe 3 O 4 , respectively) on recovering anammox activity with inhibition of Cr(VI). Their recovery efficiencies on the anammox process were in the order of mFe0, mFe 3 O 4 , nFe0, and nFe 3 O 4 at their minimum effective dosages, with specific anammox activities being promoted by 95.2%, 57.0%, 45.0%, and 15.8%, respectively, in comparison to the control. More hydroxyl groups in extracellular polymeric substances (EPS) were observed with mFe0, and the electron transport performances of soluble and loosely-bound EPS were particularly enhanced. By contrast, Fe 3 O 4 stimulated more production of EPS than mFe0, which helped remove Cr(VI) outside the cell membrane. Moreover, the contents of heme c and cytochrome c were improved most with mFe 3 O 4 by 10.9% and 41.3%, respectively, and hydrazine dehydrogenase activity was enhanced by 47.7% with mFe0, at their optimal dosages. In addition, cytochrome c showed a significant positive correlation with recovery performance for all four materials (R2 > 0.82, P < 0.05), indicating its pivotal role in alleviation effectiveness. More FeOOH was found on the two micron-scale materials detected by X-ray diffractometry and Fourier transform infrared spectroscopy, which would help electron transfer between materials and anammox bacteria. In contrast, the fast corrosion and adsorption processes and biological toxicity of nanoscale materials may lead to their poor performance. [ABSTRACT FROM AUTHOR]

The development of visible light-responsive photocatalytic membranes (vis-PMs) has opened a promising direction in water purification field. Herein, supramolecular aggregates from cyanuric acid (C), melamine (M), and urea (U) in dimethyl sulfoxide (DMSO) were used to prepare the porous carbon nitride nanosheet (MCU-C 3 N 4) with excellent photocatalytic performance. A sort of 3D heterostructure PMs consisting of MCU-C 3 N 4 and carbon nanotube (CNTs) interposed into graphene oxide (GO) on the PVDF membrane was firstly fabricated by the layer-by-layer (LbL) assembly method, in which CNTs/MCU-C 3 N 4 /GO material was immobilized on the polyelectrolytes (PE) modified PVDF based on their electrostatic attractions. Such PMs with abundant nano-channels had excellent mechanical strength, satisfactory water permeability (14.35 L m−2 h−1 bar−1) and synergetic removal efficiency of rhodamine B (RhB, 98.31%) in long -term operation, relative to the pristine GO membrane and MCU-C 3 N 4 /GO membrane fabricated by the same method. In addition, such PMs also exhibited the satisfactory tetracycline hydrochloride (TC) removal rate (84.81%) under visible light irradiation. Construction and performance of such carbon-based PMs might provide guidance for development of vis-PMs in terms of bonding strength, multidimensional morphology and water purification application. • LbL self-assembly strategy for carbon-based PMs with 3D heterostructure is proposed. • Such PMs are equipped with satisfactory water permeability (14.35 L m−2 h−1 bar−1). • Such PMs exhibit high performance for RhB removal (98.31%) in the integrated system. • RhB removal mechanism on such PMs under photocatalytic filtration process is given. [ABSTRACT FROM AUTHOR]

• Plasma increased hydrophilicity, encouraging bacterial growth and diversity. • CNT changed anode surface morphology, encouraging electroactive bacteria growth. • Both plasma and CNT treatment do not increase the sensitivity of the biosensor. • The conditions optimal for power generation may not be optimal for MFC sensors. The anode surface is known to play an important role in the microbial growth and in mediating electron transfer between electroactive bacteria and the electrodes in power generating microbial fuel cells (MFCs). However, the effect of the anode surface and its modification on MFC-based biosensor performance has not been studied previously. In this study, our results show that the surface modification influences certain aspect of the biosensor performance. Plasma treatment makes the carbon cloth electrode hydrophilic with contact angle of 82 ± 5° from that of 139 ± 3° without treatment which consequently increases the amount of biofilm and produces higher current generation. Carbon nanotube (CNT) treatment doesn't increase the amount of biofilm but significantly changes its electroactive microorganism composition from 2.3% to 17.3% that improves current generation. Interestingly, the sensitivity of the MFC sensor was not improved by either of these treatments. These findings would be important for the optimized design and manufacturing of biosensing MFCs. [ABSTRACT FROM AUTHOR]

• Microbial community dynamics are analyzed under the condition of exogenous QQ. • The change of sludge's biofouling propensity is investigated when adding exogenous QQ. • Exogenous QQ can reduce the species diversities of MBRs, especially in the short term. • Exogenous QQ can enhance biofouling propensity of sludge itself in the short term. • The enhancing of biofouling propensity of sludge depends on the dynamics of situ QS and QQ bacteria. Recently, bacterial quorum quenching (QQ) has been proven as a novel approach for biofouling mitigation in membrane bioreactors (MBRs). The information about microbial community is vital for the development of QQ strategies. Also, the change of microbial community may affect the biofouling propensity of sludge. In this study, the effects of exogenous QQ on microbial community dynamics in MBRs were investigated, along with biofouling propensity of activated sludge. QQ MBR dosed with exogenous QQ bacteria exhibited a better anti-biofouling, whereas the wastewater treatment performance was almost no difference compared with control MBR. As for the microbial community, exogenous QQ had an impact on both the bacterial diversities and community composition, especially for the quorum sensing (QS) and QQ bacteria in situ. The addition of exogenous QQ could reduce the QQ ability of sludge itself in the short term, and enhance its biofouling propensity. These findings provided new insights for the development of QQ strategies. [ABSTRACT FROM AUTHOR]

Membrane distillation (MD) has attracted increasing attention for seawater and brackish water desalination, wastewater treatment, and concentration of juices and pharmaceutical solutions due to its feasibility of using low-grade energy and achieving high solute rejection. However, the successful implementation of MD technology is still impeded by membrane wetting resulted from membrane scaling by inorganic crystals and membrane fouling by organic matters in the feed solutions, especially when dealing with challenging wastewaters. Herein, this study describes a novel strategy to develop a robust and superhydrophobic membrane via electrospinning followed by electrospray to enhance membrane anti-wetting properties caused by scaling and fouling. The robust superhydrophobic membrane PDMS-3 comprised a superhydrophobic surface layer fabricated by electrospraying a PVDF/PDMS/silica fume blended solution and an electrospun nanofibrous PVDF support. The newly developed membrane PDMS-3 not only exhibited an outstanding superhydrophobicity with a water contact angle of 170⁰ ± 1⁰, but also showed a unique anti-abrasive feature, which still possessed a slippery superhydrophobic property after 40 abrasion cycles. Moreover, the DCMD tests revealed that this rigid superhydrophobic surface rendered PDMS-3 with the best anti-scaling and anti-fouling properties compared to the nanofibrous and commercial PVDF membranes. It could achieve a superior MD flux of 28 kg m−2 h−1and a stable salt rejection above 99.99% during a continuous 160-h DCMD operation when the feed and permeation solutions were 3.5 wt% NaCl solution at 333K and distillate water at 293 K, respectively. These results underline the importance of anti-abrasive superhydrophobic membrane development to deal with wastewaters containing diverse inorganic and organic matters via MD. • The robust and superhydrophobic composite membranes were fabricated by electrospinning and electrospray. • The abrasive resistance of as-developed superhydrophobic membranes were examined. • PDMS-3 with the highest silica content exhibits the best anti-abrasive property. • Compared to nanofibrous PVDF membrane, PDMS-3 exhibits better anti-scaling and anti-fouling properties. • The surface property of PDMS-3 is significant in determining its long-term stability in MD. [ABSTRACT FROM AUTHOR]

• First application of xurographic fabrication technology to construct micro-MFC. • The cost of fabricating the sensor is lower than 0.5 USD. • The response time of the BOD sensor could be as short as 1.1 min. • The sensor can cover a wide range of BOD between 20−490 mg/L. The rapid quantification of biological oxygen demand (BOD) plays an important role in environmental management, for instance, wastewater treatment. This study used xurographic fabrication technology to rapidly fabricate a low cost miniaturized microbial fuel cell (MFC) and demonstrated its suitability to measure BOD. The miniaturized sensor could be fabricated in 10 min with low cost of $0.5 U.S. per device. The reaction volume was designed to be 1.8 μL to obtain faster response time. The sensor was tested using sodium acetate (NaAc) as a model BOD analyte. It could response to a wide range of BOD concentration between 20 and 490 mg/L which would cover the majority range of wastewater BOD concentration in a wastewater treatment plant. The response time of this microsensor was 1.1 min which was significantly shorter than other conventional methods for BOD measurements (5 days). This study demonstrated that the use of xurographic methods to fabricate MFCs could enable rapid fabrication of microsensors to measure BOD in a rapid manner. This study also identified the potential of the sensor for application in wastewater treatment plants to monitor BOD and provide guidance for controlling treatment processes. [ABSTRACT FROM AUTHOR]

Surfactants widely exist in oil-in-water (O/W) emulsions, and they may exert significant influence on membrane performance during ultrafiltration (UF) of O/W emulsions using ceramic membrane. In this paper, we investigated UF of O/W emulsions stabilized by three surfactants (SDBS, CTAB and Tween-80 as anionic, cationic and nonionic surfactant) at different concentrations (0.25–2 CMC) using silicon carbide (SiC) ceramic membranes. SiC ceramic membrane showed satisfactory separation ability for O/W emulsions with oil rejection higher than 90%. Influence of surfactant on properties of O/W emulsions, oil rejection and permeate flux were studied. The main fouling types for all O/W emulsions were cake filtration and standard pore blocking based on analysis of flux data using Hermia's blocking model, and highest fouling degree occurred in CTAB prepared emulsions which has a opposite charge to ceramic membrane. Generation of fouling is not only related to blocking and adsorption of oil droplets on membrane, but also referred to surfactant adsorption on membrane. Surfactant adsorption on ceramic membrane during UF of O/W emulsions was further investigated based on Zhu and Gu's model. Surfactant was found to deposited in hemimicelle form on membrane surface and in membrane pores which have an important influence on membrane fouling. [ABSTRACT FROM AUTHOR]

• Methanosaeta outcompeted Methanosarcina at elevated levels of acetate up to 66 mM. • At an initial pH of 3.5 in the reactor, methanogens were able to degrade 60% COD. • At pH 4.5, after acclimatization, the performance was comparable to neutral pH. • Initial low pH was neutralized without any buffering agents. • pH of the reactor and CH 4 in biogas showed a positive correlation. Anaerobic digestion (AD) reactors often encounter low pH inhibition during startup and high organic loading periods. The use of a large amount of NaOH in order to raise and buffer the low pH, is reported to be inhibitory to methanogens. In order to address this problem, we acclimatized aceticlastic methanogens to low pH. Methanogens were successfully acclimatized to initial low pH down to 3.5 in a lengthy, five months, acclimatization period. The aceticlastic methanogen, Methanothrix soehngenii which was 96.3% of the total methanogenic population at pH 4.5 and 86.75% at pH 3.5, demonstrated that they were the most tolerant aceticlastic methanogens to low pH. After acclimatization, methane yield at pH 4.5 was comparable to neutral pH. Methanosaeta maintained its dominance over Methanosarcina at an elevated level of acetate (66 mM), and a negative correlation was observed between them. There was a positive correlation between the CH 4 content and pH. [ABSTRACT FROM AUTHOR]

Low dimensional accuracy and high surface roughness induced by the inherent powder adhesion and staircase effect are the critical challenges for the application of parts fabricated by laser powder bed fusion (LPBF). In this study, an innovative hybrid additive manufacturing process by adding the ultrafast laser machining to the LPBF process was proposed. After LPBF process, the additively manufactured samples were micromachined using a picosecond laser. The effects of parameters (i.e. , laser frequency, and scanning speed) of the ultrafast laser machining on the surface morphology were investigated by the single-pass ablation experiments. The impact of the scan counts on the cutting depth was analyzed by the large-area cutting experiments. Subsequently, samples with different tilt angles were fabricated by a hybrid additive manufacturing process with alternating processing of LPBF and the ultrafast laser machining. The side surface roughness (4.98 ± 0.44 µm) of the samples fabricated by hybrid additive manufacturing process was lower than that of as-built LPBF samples. The processing characteristics and the ablation morphology of the picosecond laser were investigated. The factors affecting the quality of hybrid manufacturing were systematically discussed. This work may provide a new way to manufacture parts with high dimensional accuracy and low surface roughness by LPBF. • A new hybrid additive manufacturing combining LPBF and picosecond laser processing was realized. • The picosecond laser processing characteristics and process parameters of AM stainless steel samples were investigated. • The side surface roughness was reduced by the hybrid additive manufacturing process. • The main factors affecting the surface quality in hybrid additive manufacturing process were discussed. [ABSTRACT FROM AUTHOR]

• A novel photocatalyst constructed by BNQDs and UPCN was prepared. • Intensified exciton dissociation and charge transfer across BNQDs/UPCN heterostructure. • Higher photocatalytic efficiency toward molecular oxygen activation under visible light. • Mechanisms of enhanced photocatalytic activities were proposed. Graphitic carbon nitride (g-C 3 N 4) has enormous potential for photocatalysis, but only possesses moderate activity because of excitonic effects and sluggish charge transfer. Herein, metal-free heterostructure photocatalyst constructed by boron nitride quantum dots (BNQDs) and ultrathin porous g-C 3 N 4 (UPCN) was successfully developed for overcoming these defects. Results showed that the BNQDs loaded UPCN can simultaneously promote the dissociation of excitons and accelerate the transfer of charges owing to the negatively charged functional groups on the surface of BNQDs as well as the ultrathin and porous nanostructure of g-C 3 N 4. Benefiting from the intensified exciton dissociation and charge transfer, the BNQDs/UPCN (BU) photocatalyst presented superior visible-light-driven molecular oxygen activation ability, such as superoxide radical (O 2 −) generation and hydrogen peroxide (H 2 O 2) production. The average O 2 − generation rate of the optimal sample (BU-3) was estimated to be 0.25 μmol L−1 min−1, which was about 2.3 and 1.6 times than that of bulk g-C 3 N 4 and UPCN. Moreover, the H 2 O 2 production by BU-3 was also higher than that of bulk g-C 3 N 4 (22.77 μmol L−1) and UPCN (36.13 μmol L−1), and reached 72.30 μmol L−1 over 60 min. This work reveals how rational combination of g-C 3 N 4 with BNQDs can endow it with improved photocatalytic activity for molecular oxygen activation, and provides a novel metal-free and highly efficient photocatalyst for environmental remediation and energy conversion. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A new magnetic Cu-Fe oxide (CuFeO) was developed as the photo-Fenton catalyst. • CuFeO/H 2 O 2 /Vis system can work efficiently at slightly basic pH conditions. • The completely removal of 50 mg L−1 of SMZ has been achieved in 30 min. • HO and photoinduced e− are mainly responsible for the degradation of SMZ. Abstract The presence of antibiotics in aquatic environments has attracted global concern. Heterogeneous photo-Fenton process is an attractive yet challenging method for antibiotics degradation, especially when such a process can be operated at neutral pH values. In this work, a new magnetic Cu-Fe oxide (CuFeO) was developed as the heterogeneous photo-Fenton catalyst through a facile two-step method. The obtained CuFeO particles were found to be more efficient to activate H 2 O 2 into radicals (OH and O 2 −) than Cu-Fe Prussian blue analogue (Cu-Fe PBA, the precursor) at near neutral conditions. The removal rate of sulfamethazine (SMZ) in CuFeO/H 2 O 2 /Vis system was much higher than those in CuO/H 2 O 2 /Vis and Fe 3 O 4 /H 2 O 2 /Vis systems. It was observed that nearly complete removal of SMZ from ultrapure water, river water and tap water can be achieved in 30 min in CuFeO/H 2 O 2 /Vis system. The influence of different process parameters on the SMZ degradation efficiency was then examined and the catalytic stability of CuFeO was also tested. The SMZ degradation intermediates during the process were analyzed and the degradation pathway was proposed based on LC–MS results. The mechanisms for H 2 O 2 activation were studied by X-ray photoelectron spectrum analysis, radical scavenging and electron spin-trapping experiments. It is suggested that the synergistic effect among photo-induced electrons, Cu and Fe in CuFeO exhibits excellent performance in the catalytic activation of H 2 O 2. This work is expected to provide useful information for the design and synthesis of bimetallic oxide for heterogeneous photo-Fenton reactions. [ABSTRACT FROM AUTHOR]

Abstract The bulk polycrystalline samples of La 0.67 Ca 0.13 Ba 0.2 Mn 1-x Co x O 3 (x = 0, 0.02, 0.04, 0.06, 0.08, 0.1) have been prepared by conventional solid-state reaction method. X-ray powder diffraction shows that all samples crystallize in the rhombohedral structure with R 3 ¯ c space group symmetry. The ratio of Co3+/Co4+ gradually increases with increasing Co doping composition, which was determined by XPS analysis. The temperature and applied magnetic field dependence of magnetization were carried out. All samples exhibit a FM-PM transition at the Curie temperature T C , which decreases from 312 K to 223 K with increasing Co composition. Critical analysis shows that the estimated critical exponents β, γ and δ are in between the theoretically predicted values for 3D-Heisenberg and mean-field theory models for all samples. The magnetocaloric effect has been calculated from isothermal magnetization curve at various temperatures near T C. The maximum magnetic entropy changes -ΔS max under applied magnetic field of 1.6 T were found to be 3.18 J kg−1 K−1, 2.47 J kg−1 K−1 and 2.68 J kg−1 K−1 respectively for x = 0, 0.02 and 0.04 composition, which will be an interesting compound for application materials working as magnetic refrigerants near room temperature. Highlights • All samples crystallize in the rhombohedral structure with R 3 ¯ c space group symmetry. • The Curie temperature T C decreases from 312 K to 223 K with increasing Co composition. • The estimated critical exponents β, γ and δ are in between the theoretical values for 3D-Heisenberg and mean-field theory models. • The maximum magnetic entropy change -ΔS max under applied magnetic field of 1.6 T was found to be 3.18 J kg−1 K−1 for x = 0. [ABSTRACT FROM AUTHOR]

In this study, nano-hydroxyapatite/polyamide66 composite scaffold was prepared by combining thermally induced phase separation and particulate leaching. The morphological structure and compositional phases of the scaffold were analyzed, while the in vitro and in vivo biological behaviors were assessed by comparing with the control of the commercial porous polyethylene (MEDPOR®). Results indicate that nano-hydroxyapatite/polyamide66 scaffold showed excellent biocompatibility and the ability to accelerate bone marrow mesenchymal stem cells differentiation in vitro and bone marrow mesenchymal stem cells/nano-hydroxyapatite/polyamide66–engineered constructs exhibited much better in vivo biocompatibility and osteoconductivity with the surrounding host bone than bone marrow mesenchymal stem cells/MEDPOR constructs. The porous nano-hydroxyapatite/polyamide66 scaffold demonstrates a potential to be applied in the orthopedic or maxillofacial surgery. [ABSTRACT FROM AUTHOR]

Abstract An integrated stochastic-fuzzy pollution assessment method (ISFPAM) for soil heavy metal was established based on geo-accumulation index (I geo), stochastic-fuzzy theory and double weight system under synthetical consideration of metal ecotoxicity and bioaccessibility. The pollution characteristics of the topsoil heavy metals (Cu, Zn, Cd, Pb and Cr) in Xiangjiang New District were evaluated by the widely-used Single factor index (SF), Nemerow index (NI), I geo , Potential ecological index (PERI), Risk assessment code (RAC) and the ISFPAM. The results of SF , NI , I geo , RI and RAC of the studied metals revealed the following orders: Cd > Zn > Cr > Cu > Pb, Cd > Zn > Pb > Cr > Cu, Cd > Cr > Cu > Zn > Pb, Cd > Cu > Pb > Cr > Zn, and Cd > Pb > Cr > Zn > Cu, respectively. The different pollution assessment methods outputted the differentiated conclusions to some extent except the judgment for Cd. Results based on ISFPAM indicated that metal pollution degrees decreased in the order of Cd (5.91, Grade 6) > Cu (2.81, Grade 3) > Pb (2.66, Grade 3) > Cr (1.58, Grade 2) > Zn (0.69, Grade 1). By detailed comparison analysis, the double weight system and stochastic-fuzzy theory made ISFPAM better resolving ability to find out priority heavy metals and areas with relatively higher enrichment, ecotoxicity and bioaccessibility under efficient parameter uncertainty control. Cd, Cu and Pb were regarded as the priority control metals, especially Cd. Simultaneously, the reliabilities of heavy metal pollution corresponding to adjacent pollution grades were quite close in some sites, which recommend recheck for avoid misleading the decision-makers. Graphical abstract Unlabelled Image Highlights • Soil metal enrichment, ecotoxicity and bioaccessibility need integrated evaluation. • Integrated stochastic-fuzzy pollution assessment method (ISFPAM) was established. • ISFPAM integrated I geo , stochastic-fuzzy theory and double weight system. • Cd, Cu and Pb was identified to be priority pollutants in topsoil from XND. • ISFPAM show better resolving ability compared with SF , NI , I geo , RI and RAC. [ABSTRACT FROM AUTHOR]

Abstract Mitigating membrane fouling extensively occurred in membrane-based water treatment techniques in an efficient and durable way is a pressing challenge. The novel electro-assisted membrane coupling technology showed great potentials for tackling the problem. Foulants like charged natural organic matter, colloids and bacteria can be successfully repelled from membrane surface in the presence of electric field, contributing to less adoption, accumulation, and blocking. More importantly, the inactivation of microorganisms induced by electric field played a significant role in inhibiting the formation of the stubborn biofilm, which showed distinct and excellent advantages over other membrane fouling control approaches like surface hydrophilic modification, chemical cleaning, and pretreatment optimization. This thorough and long-term effective coupling means will actually open a new sight for membrane fouling mitigation fields. Herein, we reviewed the configuration of direct current (DC) membrane coupling technology to control membrane fouling, fouling alleviating mechanisms, and membrane filtration performances of DC electric field membrane coupling process. Additionally, some potential drawbacks and corresponding strategies were also discussed; hopefully to supply some viewpoints for prospective developments in membrane fouling mitigation fields. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

In order to improve the antifouling properties of quorum quenching (QQ) bacteria immobilized beads, the mechanical strength and permeability of QQ beads were modified by adding powdered activated carbon (PAC) based on traditional polyvinyl alcohol (PVA)-boric acid method. Optimal PAC concentration was investigated through measuring the mechanical strength, permeability and N -octanoyl-DLhomoserine lactone (C8-HSL) removal ratio of the PAC-PVA beads. Particularly, the enhanced antifouling effects of the optimal PAC-PVA beads were compared with those of original QQ beads through a membrane filtration experiment under constant pressure. The optimal concentration of PAC was 1% (w/v), under that PAC concentration, the mechanical strength, permeability and removal ratio of C8-HSL increased by 11.3%, 29.3% and 12.4% respectively. Synergistic effect between adsorption and biodegradation of 1% PAC-PVA beads was also observed. In membrane filtration experiment, membrane permeability with the 1% PAC-QQ beads decreased to 55.4% after 14 days, while the membrane permeability with 0% PAC-QQ beads decreased to 39.9%. The addition of PAC (1%) increased the antifouling efficiency of the QQ beads 15.5%. This paper demonstrated PAC-PVA bead as a QQ bacteria immobilized method had a great potential for biofouling control in membrane bioreactors (MBRs). [ABSTRACT FROM AUTHOR]

The laser-induced method to prepare three-dimensional (3D) porous graphene has been widely used in many fields owing to its low-cost, easy operation, maskless patterning and ease of mass production. Metal nanoparticles are further introduced on the surface of 3D graphene to enhance its property. The existing methods, however, such as laser irradiation and electrodeposition of metal precursor solution, suffer from many shortcomings, including complicated procedure of metal precursor solution preparation, strict experimental control, and poor adhesion of metal nanoparticles. Herein, a solid-state, reagent-free, and one-step laser-induced strategy has been developed for the fabrication of metal nanoparticle modified-3D porous graphene nanocomposites. Commercial transfer metal leaves were covered on a polyimide film followed by direct laser irradiation to produce 3D graphene nanocomposites modified with metal nanoparticles. The proposed method is versatile and applicable to incorporate various metal nanoparticles including gold silver, platinum, palladium, and copper. Furthermore, the 3D graphene nanocomposites modified with AuAg alloy nanoparticles were successfully synthesized in both 21 Karat (K) and 18K gold leaves. Its electrochemical characterization demonstrated that the synthesized 3D graphene-AuAg alloy nanocomposites exhibited excellent electrocatalytic properties. Finally, we fabricated LIG-AuAg alloy nanocomposites as enzyme-free flexible sensors for glucose detection. The LIG-18K electrodes exhibited the superior glucose sensitivity of 1194 μA mM−1 cm−2 and low detection limits of 0.21 μM. The LIG-21K nanocomposite sensors showed two linear ranges from 1 μM to 1 mM and 2 mM–20 mM with good sensitivity. Furthermore, the flexible glucose sensor showed good stability, sensitivity, and ability to sense in blood plasma samples. The proposed one-step fabrication of reagent-free and metal alloy nanoparticles on LIG with excellent electrochemical performance opens up possibilities for diversifying potential applications of sensing, water treatment and electrocatalysis. [Display omitted] • A solid-state, reagent-free and one-step method for the synthesis of LIG-metal nanocomposites was proposed. • The one-step LIG method demonstrated the universality for monometallics and alloys. • Metal nanoparticles and alloys were uniformly and densely introduced to the 3D graphene. • The fabricated flexible LIG-AuAg alloy glucose sensors exhibited low detection limit and high sensitivity. [ABSTRACT FROM AUTHOR]

To evaluate the long-term climate change impacts on groundwater fluctuations of the Ardabil plain, Iran, a groundwater level (GWL) modeling was proposed in this study. Accordingly, the outputs of Global Climate Models (GCMs) under the sixth report of Coupled Model Intercomparison Project (CMIP6) and future scenario of the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5), were used as climate change forcing to the Machine learning (ML) models. The GCM data were first downscaled and projected for the future via Artificial Neural Networks (ANNs). Based on the results, compared to 2014 (the last year of the base period), the mean annual temperature may increase by 0.8 °C per decade until 2100. On the other hand, the mean precipitation may decrease by about 8% compared to the base period. Then, the centroid wells of clusters were modeled by Feedforward Neural Network (FFNN), examining different input combination sets to simulate both autoregressive and non-autoregressive models. Since each of the ML models can extract different kinds of information from a dataset, after finding the dominant input set via FFNN, GWL time series were modeled via various ML methods. The modeling results indicated that the ensemble of shallow ML models could lead to a 6% more accurate outcome than the individual shallow ML models, and 4% than the deep learning models. Also, the simulation results for future GWLs illustrated that temperature can impact groundwater oscillations directly, whereas precipitation may not have uniform impacts on the GWLs. The uncertainty evolving in the modeling process was quantified and observed to be in acceptable range. Modeling results showed that the main reason for the declining GWL in the Ardabil plain could be primarily linked to the excessive exploitation of the water table, while climate change impact could be also notable. • The average temperature will increase at different rates in different seasons. • The average precipitation will change variously in different months. • Ensemble model is more accurate than other ML models. • Temperature has a direct impact on groundwater fluctuations. • Precipitation impacts the groundwater in complex ways. [ABSTRACT FROM AUTHOR]

Some agronomic practices not only promote the development of crop roots and increase overall plant performance but also affect colonisation by rhizosphere microorganisms. However, the composition and temporal dynamics of the tobacco rhizosphere microbiota under different root-promoting practices are poorly understood. Here, we characterised the tobacco rhizosphere microbiota at the knee-high, vigorous growing, and maturity stages under the application of potassium fulvic acid (PFA), γ-Polyglutamic acid (PGA), soymilk root irrigation (SRI), and conventional fertilization (CK) and its correlation with root characteristics and soil nutrients. The results showed that three root-promoting practices notably improved the dry and fresh root weights. Total nitrogen and phosphorus, available phosphorus and potassium, and organic matter contents in the rhizosphere markedly increased at the vigorous growing stage. The rhizosphere microbiota was changed through root-promoting practices. However, with tobacco growth, the change of rhizosphere microbiota showed a pattern of slow first and then fast and the microbiota of different treatments gradually approached. SRI reduced plant-pathogenic fungi but increased chemoheterotrophic and phototrophic bacteria, and arbuscular mycorrhizal fungi. PFA and PGA markedly increased arbuscular mycorrhizal and ectomycorrhizal fungi at the knee-high stage, which benefitted tobacco nutrient absorption. The correlation between rhizosphere microorganisms and environmental factors varied at different growth stages. Notably, the rhizosphere microbiota was more sensitive to environmental factors at the vigorous growing stage, and the interactions were more complex than in other stages. Furthermore, a variance partitioning analysis showed that the influence of root–soil interaction on the rhizosphere microbiota increased with tobacco growth. Overall, all three root-promoting practices could improve root characteristics, rhizosphere nutrient, and rhizosphere microbiota to varying degrees and increase the tobacco biomass, among which PGA had the most obvious effect and most suitable for tobacco cultivation. Our findings revealed the role of root-promoting practices in shaping the rhizosphere microbiota during plant growth and elucidated the assembly patterns and environmental drivers of crop rhizosphere microbiota driven by the application of root-promoting practices in agricultural production. • Tobacco rhizosphere microbiota under root-promoting practices was characterized. • Root-promoting practices can enrich beneficial microorganisms in tobacco rhizosphere. • Root-soil interactions affect the rhizosphere microbiota during tobacco growth. • The microbial community is more sensitive during the vigorous growing stage. [ABSTRACT FROM AUTHOR]

The junction temperature of LED (light emitting diode) has a significant impact on its performance and lifetime. In this paper, a simplified model based on the finite element analysis is developed to simulate the temperature distribution of the 200 W LED module using software ANSYS. The model contains LED package, the heat pipe radiator, as well as TIM (thermal interface material) between the LED package and radiator. The temperature distribution of the simulation agrees with that of the experimental measurement. Thickness of TIM affects the heat dissipation significantly, the chips temperature and the maximum temperature difference of chips increases sharply with TIM thickness increasing. Substituting aluminum fins with copper fins cannot improve the heat dissipation performance of heat pipe radiator, and the air velocity of heat pipe radiator plays a key role in the heat dissipation. Thermal conductivity of package submount directly affects the chip temperature and the uniformity of temperature distribution of package submount. [ABSTRACT FROM AUTHOR]

The structural, elastic, thermodynamic and electronic properties of the Ti 15−x Mo x Sn compounds were systematically investigated by means of first-principles calculations based on the density functional theory (DFT). The calculated results demonstrate the Ti 15−x Mo x Sn compounds still remain the stable β phase structure. The calculation of cohesive energy shows that the structural stability of the Ti 15−x Mo x Sn compounds increases apparently with the increase of Mo content. According to Hooke's law, the single crystal elastic constants were obtained and show that all the calculated compounds keep mechanical stability. Then the bulk modulus B , shear modulus G , Young's modulus E and Poisson's ratio ν of polycrystalline aggregates were calculated at zero pressure. The calculated results show that among these Ti 15−x Mo x Sn compounds, Ti 4 Mo 11 Sn exhibits the largest stiffness while Ti 12 Mo 3 Sn shows the greatest ductility. The compounds Ti 12 Mo 3 Sn and Ti 11 Mo 4 Sn with the two lowest elastic Young's modulus of 61.01 GPa and 65.59 GPa are expected to be promising metallic biomaterials for implant applications. Besides, the Debye temperature Θ D and the electronic density of states (DOS) are also investigated and discussed. [ABSTRACT FROM AUTHOR]

Paralytic shellfish toxins (PSTs) producing algae are widely distributed in the global coastal aquatic environment, posing a threat to coastal ecosystem health and mariculture safety. However, the levels and potential environmental risks of PSTs frequently detected in shellfish remain largely unexplored in seawater of mariculture zones. In this study, a new method for trace detection of 13 common PSTs (<1.0 ng/L) in seawater was established based on off-line solid phase extraction (SPE) and on-line SPE-liquid chromatography-tandem mass spectrometry (on-line SPE-LC-MS/MS), and a systematic investigation of PSTs in seawater of the Laizhou Bay, a typical aquaculture bay in China, was conducted to understand their pollution status, environmental impact factors and ecological risks for the first time. Eleven PSTs were detected in the seawater of Laizhou Bay with total concentrations ranging from 0.75 to 349.47 ng/L (mean, 176.27 ng/L), which indicates the rich diversity of PSTs in the mariculture bay and demonstrates the reliability of the proposed analytical method. C1, C2, GTX2, GTX3, dc GTX2, and dc GTX3 were found to be the predominant PSTs, which refreshed the knowledge of PST contamination in the coastal aquatic environment. PST levels in seawater exhibited the highest levels in the southeastern mouth of Laizhou Bay and decreased toward the inner bay. Correlation analyses showed that climatic factors, nutrient status and hydrological conditions had significant effects on the distribution of PST in mariculture bay. Preliminary environmental risk assessments revealed that aquatic organisms throughout the waters of Laizhou Bay are at risk of chronic PST toxicity. These findings imply that the risk of PST in seawater of mariculture bay has previously been grossly underestimated, and that the coastal aquatic environment in North China and even the world may be at more serious risk of PST pollution, which should be taken seriously. [Display omitted] • A new analytical method was developed for 13 trace PSTs in seawater (<1.0 ng/L). • Various PSTs widely distributed in nearshore water was reported for the fist time. • GTXs, dc GTXs, and C-toxins are the predominant PSTs in mariculture seawater. • Aquatic organisms in the Laizhou Bay are generally at risk of chronic PST toxicity. • Nutrient and hydrological conditions affect the distribution of PST in Laizhou Bay. [ABSTRACT FROM AUTHOR]

• The peak current and sensitivity are strongly affected by Temp. • The biosensor achieved most sensitive and accurate test at 35 °C. • The relative abundance of dominant exoelectrogens varied with temperature. • Low biomass (18.3 µm of thickness) still enables precise detection. • MFC sensor is sensitive to the content of acid and alcohol in wastewater. Miniaturized MFC-based BOD biosensors have attracted attention due to their fast response and low cost. However, the influence of ambient temperature and poor response to actual wastewater restrict their practical application. To clarify the influence mechanism of temperature on the biosensor performance, the anodic biofilm was analyzed in-depth. The biosensor performances increased between 5 and 35 °C, while decreased at higher temperature (45 °C) due to a significant reduction in bacterial viability. Further, the variation of dominant exoelectrogen with different electrical production capacity with temperature is the main mechanism of temperature influence. In addition, the factors affecting the accuracy of actual wastewater detection were discussed. Although the microorganisms in the actual wastewater interfered with the metabolism of exoelectrogen, the deviation between the sensing results and the real BOD value was mainly due to the fact that the exoelectrogen only metabolize the acid and alcohol components in the wastewater. In general, our research will provide some suggestions for the practical application of MFC sensors. [ABSTRACT FROM AUTHOR]

The current study developed a new perspective whether crystalline structures influence the adsorption of heavy metals on magnetic iron oxides synthesized by applying surfactant sodium dodecyl sulfate (SDS)-templated strategy. The products were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive analysis of X-ray (EDAX), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transformed infrared spectroscopy (FT-IR), and ζ-potential analyzer. Most SDS were removed after calcination and the phase of iron oxide transformed from amorphous Fe 3 O 4 to (α + γ)-Fe 2 O 3 and finally to highly crystalline α-Fe 2 O 3 , followed by decreasing surface area and pore volume with increasing calcining temperatures. Amorphous Fe 3 O 4 exhibited a better adsorption capacity towards Pb (II) and Cd (II) than that of (α + γ)-Fe 2 O 3 and α-Fe 2 O 3 , suggesting that metals adsorption by amorphous iron oxide was superior to that owns high degree of crystallization. The removal performances containing ion exchange, hydrolysis of heavy metals, electrostatic attraction and chemical binding or specific interaction were consistent with XPS and other measurements. After five adsorption–desorption cycles, all synthesized iron oxides still maintained above 79% removal efficiency for both Pb (II) and Cd (II). This study provides a promising potential for the application of iron oxides as adsorbents for heavy metals treatment in wastewater. [ABSTRACT FROM AUTHOR]

Recently, persulfate-based advanced oxidation processes (persulfate-AOPs) are booming rapidly due to their promising potential in treating refractory contaminants. As a type of popular two-dimensional material, layered double hydroxides (LDHs) are widely used in energy conversion, medicine, environment remediation and other fields for the advantages of high specific surface area (SSA), good tunability, biocompatibility and facile fabrication. These excellent physicochemical characteristics may enable LDH-based materials to be promising catalysts in persulfate-AOPs. In this work, we make a summary of LDHs and their composites in persulfate-AOPs from different aspects. Firstly, we introduce different structure and important properties of LDH-based materials briefly. Secondly, various LDH-based materials are classified according to the type of foreign materials (metal or carbonaceous materials, mainly). Latterly, we discuss the mechanisms of persulfate activation (including radical pathway and nonradical pathway) by these catalysts in detail, which involve (i) bimetallic synergism for radical generation, (ii) the role of carbonaceous materials in radical generation, (iii) singlet oxygen (1O 2) production and several special nonradical mechanisms. In addition, the catalytic performance of LDH-based catalysts for contaminants are also summarized. Finally, challenges and future prospects of LDH-based composites in environmental remediation are proposed. We expect this review could bring new insights for the development of LDH-based catalyst and exploration of reaction mechanism. [Display omitted] • Systematic introduction of different persulfate activation mechanisms by LDH-based catalysts. • Unique "intercalation effect" of LDH-based catalysts have been discussed. • Discussion on the effect of tailoring the morphology of LDHs for improving catalytic performance. [ABSTRACT FROM AUTHOR]

Cimabanshuo deposit is a newly discovered porphyry copper (Cu) deposit with giant metallogenic potential, found in the western segment of the Gangdese metallogenic belt, Tibet. The average elevation of the deposit is greater than 5500 m and the terrain on which it is found is steep and complex. Therefore, it is untraversed, and the existing exploration works on it are weak. We used 59 AMT sites belonging to an array covering the main, proven mineralization zone and ore bodies of this deposit for an analysis of its underground electrical structure. Dimensionality and strike analysis revealed the apparent three-dimensional (3D) features near the Cu ore bodies. 3D inversion with topography was conducted for the AMT array data. A large range of high-resistivity anomaly (~500–2000 Ωm) appears beneath the proven Cu mineralization zone and ore bodies, which is interpreted as intrusive rocks with potassic alteration. Although containing chalcopyrite, it is characterized by middle–high resistivity due to a low sulfide content and poor connectivity. Moreover, a series of scattered conductors (~10–300 Ωm) around the Cu ore bodies are distributed in the shallow layer from near the surface to ~200 m, possibly indicating phyllic alteration containing pyritization and connected metal sulfides. The proven ore bodies of Cimabanshuo are mainly located at the junction regions between high-resistivity intrusive rocks and high-conductivity sericitization alteration zones. According to this research, the 3D inversion with topography of AMT data can visually display the 3D distribution of intrusive rocks and alteration zones beneath porphyry Cu deposits in high-elevation regions, and provides a reference for further exploration works. [ABSTRACT FROM AUTHOR]

An ultrasensitive photoelectrochemical (PEC) immunosensor based on gold nanoclusters (AuNCs) with 11-mercaptoundecanoic acid (MUA) ligands was fabricated for determination of microcystin-LR (MC-LR). The PEC immunosensor was developed by loading the monoclonal MC-LR antibody (Ab) to the MUA-AuNCs modified gold electrodes. After different measurement conditions being optimized, silver nanoparticles (AgNPs), gold nanorods (AuNRs), graphene oxide (GO) and carboxyl-functionalized graphene oxide (cGO) were introduced into MUA-AuNCs to enhance the sensing properties. The experimental result revealed that the sensitivity of PEC immunosensors was enhanced by both their photoelectrochemical properties and antibody loading properties with dependent relationship, which was different from the enhancement strategy of PEC sensors based on redox reactions. Among different hybrid nanocomposites, MUA-AuNCs/cGO not only improved the photoelectrochemical properties, but also loaded more antibodies for sensing, which resulted in best sensing performance. Thus, a universal method was proposed to enhance the sensing performance of PEC immunosensors based on impedance changes. Finally, MUA-AuNCs/cGO based PEC immunosensors exhibited a wide linear range of 0.001 nM–1000 nM with low detection limit of 0.011 pM (S/N = 3) for MC-LR determination. Meanwhile, the designed PEC immunosensors showed high selectivity, reproducibility and specificity, which provided the promising applications in aquatic environment. [Display omitted] • AuNCs with MUA ligands-based PEC immunosensors were first developed for ultrasensitive MC-LR detection. • AgNPs, AuNRs, GO and cGO were introduced into MUA-AuNCs as hybrid nanocomposites to enhance PEC sensing properties. • MUA-AuNCs/cGO based PEC immunosensors exhibited best sensitivity, LOD and specificity. • PEC immunosensors can be enhanced by photoelectric properties and antibody loading properties with dependent relationship. • A universal method to enhance the sensing properties of PEC immunosensors based on impendence changes was proposed. [ABSTRACT FROM AUTHOR]