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Background: Inositol is a potential new therapeutic agent for gestational diabetes mellitus (GDM), but its effectiveness is still controversial. The aim of the report was to evaluate the effectiveness of inositol to preventing or reducing the severity of GDM. Methods: We searched PubMed, EmBase, Web of science, Cochrane library databases, Clinicaltrials.gov, and International Clinical Trials Registry Platform for randomized controlled trials (RCTs) assessing the effectiveness of inositol supplementation to prevent and treat GDM. This meta-analysis was performed using the random-effects model. Results: A total of 7 RCTs (1319 pregnant women at high risk of GDM) were included in the meta-analysis. The meta-analysis found that inositol supplementation resulted in a significantly lower incidence of GDM in the inositol versus the control group (odds ratio [OR] 0.40; 95% confidence interval [CI] 0.24–0.67; P = 0.0005). The inositol group had improved fasting glucose oral glucose tolerance test (FG OGTT; mean difference [MD] = − 3.20; 95% CI − 4.45 to − 1.95; P < 0.00001), 1-h OGTT (MD = − 7.24; 95% CI − 12.23 to − 2.25; P = 0.004), and 2-h OGTT (MD = − 7.15; 95% CI − 12.86 to − 1.44; P = 0.01) results. Inositol also reduced the risk of pregnancy-induced hypertension (OR 0.37; 95% CI 0.18–0.75; P = 0.006) and preterm birth (OR 0.35; 95% CI 0.18–0.69; P = 0.003). A meta-analysis of 4 RCTs including 320 GDM patients showed that the patients' insulin resistance (P < 0.05) and neonatal hypoglycemia risk (OR 0.10, 95% CI 0.01–0.88; P = 0.04) were lower in the inositol than in the control group. Conclusions: Inositol supplementation during pregnancy has the potential to prevent GDM, improve glycemic control, and reduce preterm birth rates. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) have attracted much attention for decades as they are the precursors of photochemical smog and are harmful to the environment and human health. Vacuum ultraviolet (VUV) photodegradation is a simple and effective method to decompose VOCs (ranging from tens to hundreds of ppmV) without additional oxidants or catalysts in the air at atmospheric pressure. In this paper, we review the research progress of VOCs removal via VUV photodegradation. The fundamentals are outlined and the key operation factors for VOCs degradation, such as humidity, oxygen content, VOCs initial concentration, light intensity, and flow rate, are discussed. VUV photodegradation of VOCs mixture is elucidated. The application of VUV photodegradation in combination with ozone-assisted catalytic oxidation (OZCO) and photocatalytic oxidation (PCO) systems, and as the pre-treatment technique for biological purification are illustrated. Based on the summary, we propose the challenges of VUV photodegradation and perspectives for its future development. [Display omitted] [ABSTRACT FROM AUTHOR]

The sludge dewaterability is essential for waste activated sludge (WAS) treatment and disposal in wastewater treatment plants (WWTPs). The biological enzyme conditioning process is a promising method to enhance the dewaterability of WAS. In this study, the optimal conditions in terms of pH, temperature, bio-enzyme dosage, and treatment time for five kinds of biological enzymes (α-amylase, cellulase, acidic protease, neutral protease, and alkaline protease) were investigated. Among them, α-amylase and neutral protease showed good performance in conditional optimization experiments. After biological enzyme conditioning, the sludge supernatant of proteins, polysaccharides, and SCOD contents increased. The sludge water content (Wc) decreased, while the capillary suction time (CST) increased. The optimal conditions for α-amylase were pH 6, 45 ℃ of temperature, 30 mg/g TSS of dosage, and 3 h of treatment time, under which the lowest Wc can reach 68.67%. The optimal conditions for neutral protease were pH 6.5, 40 ℃ of temperature, 30 mg/g TSS of dosage, and 2 h of treatment time, under which the lowest Wc can reach 69.82%. Using biological enzymes is an environmentally friendly conditioning process for efficient WAS dewatering. The optimization of operating conditions in the biological enzymes conditioning process may be beneficial to WAS dewatering and further disposal in actual WWTPs. [ABSTRACT FROM AUTHOR]

Background: The detection of amyloid-β (Aβ) deposition in the brain provides crucial evidence in the clinical diagnosis of Alzheimer's disease (AD). However, the current positron emission tomography (PET)-based brain Aβ examination suffers from the problems of coarse visual inspection (in many cases, with 2-class stratification) and high scanning cost.Objective: 1) To characterize the non-binary Aβ deposition levels in the AD continuum based on clustering of PET data, and 2) to explore the feasibility of predicting individual Aβ deposition grades with non-invasive functional magnetic resonance imaging (fMRI).Methods: 1) Individual whole-brain Aβ-PET images from the OASIS-3 dataset (N = 258) were grouped into three clusters (grades) with t-SNE and k-means. The demographical data as well as global and regional standard uptake value ratios (SUVRs) were compared among the three clusters with Chi-square tests or ANOVA tests. 2) From resting-state fMRI, both conventional functional connectivity (FC) and high-order FC networks were constructed and the topological architectures of the two networks were jointly learned with graph convolutional networks (GCNs) to predict the Aβ-PET grades for each individual.Results: We found three clearly separated clusters, indicating three Aβ-PET grades. There were significant differences in gender, age, cognitive ability, APOE type, as well as global and regional SUVRs among the three grades we found. The prediction of Aβ-PET grades with GCNs on FC for the 258 samples in the AD continuum reached a satisfactory averaged accuracy (78.8%) in the two-class classification tasks.Conclusion: The results demonstrated the feasibility of using deep learning on a non-invasive brain functional imaging technique to approximate PET-based Aβ deposition grading. [ABSTRACT FROM AUTHOR]

Oral hypoglycemic drugs for the treatment of gestational diabetes mellitus (GDM) are still controversial because they can pass through the placenta. The purpose of this meta-analysis is to evaluate the safety and effectiveness of oral hypoglycemic drugs. PubMed, Ovid Embase, Web of Science, and Cochrane databases were systematically searched (inception to 20 April 2021). Rev Man 5.0 was used to analyze the data. A random-effects model was used to compute the summary risk estimates. There were 26 randomized controlled trials (RCTs) involving 4921 GDM patients which were included in this meta-analysis. Compared with metformin, insulin had a significant increase in the risk of preeclampsia (odds ratio [OR], 1.61; 95% confidence interval [CI], 1.06 to 2.45; I2=40%; p <.05), hypertension (OR, 1.42; 95% CI, 1.02 to 1.99; I2=0%; p <.05), hypoglycemia (OR, 3.93; 95% CI, 1.27 to 12.19; I2=0%; p <.05), neonatal hypoglycemia (OR, 1.92; 95% CI, 1.34 to 2.76; I2=41%; p <.0001), neonatal jaundice (OR, 2.70; 95% CI, 1.12 to 6.52; I2=0%; p <.05), and Neonatal Intensive Care Unit Admission (OR, 1.46; 95% CI, 1.09 to 1.95; I2=39%; p <.05), but the risk of neonatal macrosomia (OR, 1.67; 95% CI, 1.12 to 2.40; I2=0%; p <.05) and neonatal injury (OR, 0.70; 95% CI, 0.55 to 0.89; I2=0%; p <.01) is lower. Metformin is comparable with insulin in glycemic control and neonatal outcomes and has the potential to replace insulin therapy in clinical practice. Glyburide is behind metformin and insulin, and more RCTs are needed to verify its safety. [ABSTRACT FROM AUTHOR]

Sulfate radical based photocatalysis is recognized as an effective approach for the photodegradation of organic pollutants in wastewater. To overcome the defects of weak visible light absorptivity and low catalytic efficiency of ZSM-5 based catalysts, MXene (Ti3C2) and a dopant were introduced to develop the multifunctional photocatalyst Metal/MXene/ZSM-5 by a modified in situ hydrothermal method, which was applied to phenol degradation under simulated solar light. The crystal growth, morphology, and structure of the prepared catalysts were systematically characterized by X-ray diffraction, scanning electron microscopy, surface area measurements, and various spectroscopy methods (UV-Raman, X-ray photoelectron, and UV-visible diffuse reflectance spectroscopies). The heterostructure of Fe(II)/Fe(III)/TiO2 in 5%Fe/5%MXene/ZSM-5 reduces the band gap and improves the visible light absorptivity, leading consequently to improved phenol photocatalytic degradation efficiency. The effects of pH, reaction temperature, initial phenol concentration, and peroxymonosulfate dosage on the catalytic performance of 5%Fe/5%MXene/ZSM-5 and the production of free active radicals in the 5%Fe/5%MXene/ZSM-5/PMS system were then investigated. 5%Fe/5%MXene/ZSM-5 achieves an efficient catalytic activity with over 98% removal of phenol within 25 min and 1O2 and ˙O2− radicals are the dominant reactive radicals in the 5%Fe/5%MXene/ZSM-5/PMS system for phenol degradation. This investigation improves the photocatalytic efficiency of the ZSM-5 zeolite-based catalyst under simulated sunlight. [ABSTRACT FROM AUTHOR]

Although digestive resistance of Kunitz protease inhibitors has been reported extensively, the molecular mechanism is not well established. In the present study, the first X-ray structure of Cassia obtusifolia trypsin inhibitor (COTI), a member of Kunitz protease inhibitors, was solved at a resolution of 1.9 Å. The structure adopted a classic β -trefoil fold with the inhibitory loop protruding from the hydrophobic core. The role of Phe139, a unique residue in Kunitz protease inhibitors, and Arg63 in the COTI structure was verified by F139A and R63E mutants. COTI was a specific inhibitor of bovine trypsin and the result was also verified by COTI-trypsin complex formation. Meanwhile, COTI showed equivalent inhibitory activity with that of soybean trypsin inhibitor against bovine trypsin and midgut trypsin from Pieris rapae. The F139 and R63E mutants further indicated that inhibitory specificity and efficiency of COTI were closely related to the global framework, the conformation and the amino acid composition of reactive loop. Finally, a midgut trypsin from P. rapae (PrSP40), which might be involve in the food digestion, was proposed to be a potential target of COTI and might be a promising target for future crop-protection strategy. The results supported the digestive resistance of COTI. [ABSTRACT FROM AUTHOR]

• The FeOCl/PMS/Vis system could efficiently remove and mineralize aquatic organic pollutants. • It was significantly enhancing the activation and utilization efficiency of PMS. • Operation across a broad range of environmental conditions. • The synergistic mechanism between photocatalysis and PMS activation in FeOCl/PMS/Vis system was revealed. Inspired by the photosensitivity and self-heal properties of iron oxychloride (FeOCl), we used photocatalysis coupling peroxymonosulfate (PMS) activation for effective aquatic decontamination in a cost-efficient and environmentally friendly method. Synthesized FeOCl was appointed to activate PMS to degrade bisphenol A (BPA, 2,2-bis(4-hydroxydiphenyl) propane) persistently under visible light. The best performance of FeOCl/PMS/Vis system was ∼100% BPA degradation efficiency which achieved in 20 min. The BPA removal efficiency had a positive correlation with the dosages of FeOCl and PMS, but negatively related to BPA concentration. The FeOCl/PMS/Vis system also presented impressive degradation performance at a wide pH range (pH = 3–11) and showed well excellent stability and reusability. The addition of either bicarbonate or chloride had impressive promotion effect on BPA removal. The reaction mechanism of FeOCl/PMS/Vis system was studied deeply. PMS was activated to generate active radicals (SO 4 − and HO) by Fe(II) of FeOCl for BPA degradation. Then the as-formed Fe(III) was reduced to Fe(II) via trapping photoexcited electrons in conduction band (CB) of FeOCl, which effectively inhibited the recombination of photo-generate charges and the pollutants oxidation would recur via facilitating the Fe(II)/Fe(III) redox recycle. Thus, the activation and utilization efficiency of PMS was effectively improved. This work indicated the FeOCl/PMS/Vis system was a promising application in wastewater treatment. [ABSTRACT FROM AUTHOR]

A laboratory scale closed-loop cycle system for the complete regeneration of sodium persulfate/sulfuric acid etching solution (SPS) has been developed by anode oxidation of sulfate paired to cathode reduction of copper. A current-efficient (110%), zero-chemical dosage and zero-emission strategy for complete regeneration of SPS and recovery of copper was achieved. The micro-etching rate of the recycled SPS has no significant difference compared with that of the fresh SPS. On average, the cost of etching in this recycling system is decreased by 100%, compared with that in the current printed circuit boards used in industries. The full utilization of spent SPS realizes waste to wealth conversion in the true sense. The developed recycling system is a techno-economically feasible, environmentally friendly, sustainable, clean and green process for the reuse of SPS and recovery of valuable metal Cu through electrooxidation of sulfate paired to electroreduction of copper. [ABSTRACT FROM AUTHOR]

[Display omitted] • Propose deep learning-based detection method of time-delayed water quality indicator. • Contribution of each input indicator is quantified based on SHAP value. • NH 3 -H, DO, turbidity contribute significantly to detecting time-delayed WQIs. • Sensitivity analysis provides insight for higher accuracy and cost performance. Rapid and accurate detection of time-delayed water quality indicators (WQIs) is the key to achieving fast feedback regulation of wastewater treatment plants (WWTPs) that enables its energy-efficient operation and high tolerance towards shock sewage loads. However, advanced oxidation methods are costly, and data-driven modeling methods based on traditional machine learning algorithms for detecting time-delayed WQIs have limited detection accuracy. This work develops deep learning models based on long short-term memory (LSTM) neural networks to detect time-delayed WQIs in WWTPs intake accurately. The lack of interpretability of the deep learning models hampers the optimization of the developed LSTM models in applications. Therefore, a global sensitivity analysis (GSA) based on Shapley additive explanations (SHAP) is performed to quantify the contribution of the input indicators to detection results of the developed LSTM models. The direct contributions provide the basis for optimizing the input indicators to achieve more cost-effective modeling detection. In the case study, the developed LSTM models achieved good accuracy (R2 of 0.9141, 0.9239, and 0.9040, respectively) in detecting chemical oxygen demand, total nitrogen, and total phosphorus in the influent of a WWTP, outperforming the four types of baseline models. According to the SHAP values, the contributions of dissolved oxygen, turbidity, and ammonia nitrogen to the above detection targets are always in the top third of all input indicators, which are more outstanding than meteorological indicators. Removing the indicator with the smallest SHAP value reduces the build and run costs of the models with minimal loss of detection accuracy. Combining deep learning and GSA to detect WWTPs influent is a novel and effective attempt. This attempt provides a more sustainable solution for rapid and accurate detection of time-delayed WQIs, which drives WWTPs' operation in an intelligent, clean, and safe direction. [ABSTRACT FROM AUTHOR]

[Display omitted] • VUV/PMS system was firstly proposed as an effective technique for MPs degradation. • VUV/PMS system removes 51.5% of polyethylene after 48 h treatment under mild conditions. • The synergistic effect between VUV and PMS-based AOPs is the key to degrading MPs. • The direct photolysis of VUV enhances the adsorption of ROS for MPs degradation. Microplastics (MPs) pose a severe threat to the environment and human health, and effective treatment techniques are urgently desired to prevent the global spread of MPs pollution. However, efficient degradation of MPs remains difficult. Herein, vacuum ultraviolet (VUV) activated peroxymonosulfate (PMS) was firstly proposed as a promising technique for the degradation of polyethylene MPs. The weight loss of MPs reaches as high as 51.5% under mild conditions ([PMS] = 32 mmol/L, initial pH = 7, [MPs] = 1 g/L, [Time] = 48 h), which is the record performance achieved at room temperature and ambient pressure for MPs degradation. The excellent degradation performance is uncovered to originate from the synergistic effect of VUV and activated PMS. Direct photolysis of VUV can rapidly oxidize the surface of MPs to reduce its hydrophobicity and thus enhance the adsorption of reactive oxidation species (i.e., SO 4 ⋅− and HO⋅) rooted from the VUV activated PMS, which was further confirmed by DFT calculations. The degradation of MPs repeatedly undergoes the process of VUV photolysis oxidation of the surface, degradation via VUV/UV/PMS-derived reactive oxidation species, shedding, and re-exposure of the new surface via VUV photolysis oxidation. This study highlights the unique role of the VUV photolysis in MPs degradation, paving a new route for designing practical MPs pollution remediation techniques. [ABSTRACT FROM AUTHOR]

A power law relation between the filtration coefficients of straining and flux through small pores has been reported. The effluent concentrations of the colloidal particles and the exponents derived from the experiment are inconsistent with those obtained from 2D network models simulation in their researches. In this study, a straining-dominant deep bed filtration (DBF) model is proposed based on 3D network simulation. The effects of simulation parameters such as lattice type, lattice coordination number z , pore size distribution (PSD), and particle capture scheme on DBF were investigated. Consistent with the power law formula and the normalized effluent concentrations ( C e/ C 0 ), simulation results indicate that the exponents increase with increasing coordination number z. The change in the PSD parameters alters the flux and weight of path type linked to node, thereby influencing the numerical simulation of staining-dominate DBF on 3D networks. The effects of capture scheme and coordination number on the simulated normalized effluent concentration could be due to variations in the total capture probability for different lattices with the same PSD. The results were obtained from simulation on hexagonal close packing (HCP) and 2D triangular lattices under the optimal conditions. The simulated C e/ C 0 and exponents of the HCP lattice are similar to those of 2D triangular lattice and consistent with the experimental data. [ABSTRACT FROM AUTHOR]

Hydroxyl radicals (·OH) electrogenerated at anode surface can efficiently eliminate organic pollutants. However, these radicals are rapidly consumed and its action occurs only in the region where it is produced, thus only a portion of ·OH that are generated can be utilized and the degradation efficiency will eventually drop upon extended electrolysis. This paper proposed an alternative electro-oxidation process to avoid the mass transfer limitation and ·OH loss. This approach consists of two parts: (i) in situ electrogeneration of persulfate and (ii) subsequent UV activation. Efficient electro-generation of persulfate and degradation of phenol were obtained simultaneously when the anolyte contains sulfate ion and potassium sulfocyanide. Compared with ·OH mediated oxidation, persulfate mediated oxidation process has a small negative effect initially on the degradation rate of phenol, but then the persulfate effect became positive gradually. Phenol could be rapid eliminated once UV irradiation was added to activate the co-produced persulfate. A two-step mediated oxidation method was employed to further reduce consumed energy and sulfate dosage. Results show that the two-step method could completely eliminate the phenol in the wastewater which volume was ten times as much as that of the anolyte. An analysis of the whole reaction schemes governing this process was also presented. In summary, the persulfate mediated anodic oxidation process can be considered as a suitable and attractive method for maximizing the utilization of the electrochemical technology. [ABSTRACT FROM AUTHOR]

• A model combining two-stage decomposition and LSTM for TP detection in sewer networks. • Two-stage decomposition reduces the instability and complexity of TP time series. • Mode decomposition procedure setting significant impact modeling efficiency, accuracy. • Proposed hybrid model achieves excellent accuracy of average R2 = 0.946. • Proposed hybrid model has the advantage of being energy-efficient and cost-effective. Timely and accurately grasping total phosphorus (TP) concentration in sewer networks is crucial for urban phosphorus flow management and shock load early warning of sewage treatment facilities. Modeling-based methods are cleaner and more energy-saving than traditional methods requiring digestion procedures. However, the TP time series' strong nonlinearity and complexity result in unsatisfactory accuracy in these methods. This work proposes a hybrid model named CEEMDAN-SE-VMD-LSTM that combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), sample entropy (SE), variational mode decomposition (VMD), and long short-term memory (LSTM) neural network to improve the accuracies of modeling-based methods. In proposed hybrid model, the two-stage decomposition procedure can decompose the TP time series into several lower-complexity modes, and the powerful nonlinear mapping ability of the LSTM neural network enables accurate prediction of these modes. In case study, the proposed hybrid model achieves excellent detection accuracy with an average R2 of 0.9460 ± 0.0243. Compared with the hybrid models formed by combining other decomposition procedures (i.e., CEEMDAN, VMD, singular spectrum analysis (SSA), CEEMDAN-SE-SSA) and LSTM neural network, the proposed hybrid model has the highest detection accuracy (1.36–3.94 % higher Nash-Sutcliffe efficiency, 1.28–4.58 % higher R2, 12.14–24.86 % lower RMSE). The strategy of setting the mode decomposition procedure based on a comprehensive analysis of the decomposition algorithms and the obtained modes ensures high detection accuracy of the proposed hybrid model while avoiding costly computational burdens. This work is enlightening for improving the accuracy and modeling efficiency of soft detection methods, which are expected to reduce energy consumption and pollution caused by water quality detection. [ABSTRACT FROM AUTHOR]

Simultaneous electrosynthesis of H 2 O 2 and persulfate was performed in a paired electrolysis system separated by a cationic membrane. To maximize the current efficiency, H 2 O 2 reacted in-situ with the added ferrous ion to form Fenton's reagent, while persulfate was used for commercial production. In the processing of electrolytic procedure, sulfate ion consumed constantly became the limiting factor for producing persulfate, while H 2 SO 4 and KSCN did not. Cyclic voltammetry test and radical quenching experiments were carried out to validate the electrosynthetic route of persulfate. During the electro-Fenton process, H 2 O 2 was decomposed into hydroxyl radical by either the added ferric ion or electron transfer reaction which resulted in a rapid degradation of phenol. The area ratio of anthode surface to anode surface was optimized to be 10:1. During the coupling process, various catholyte conditions had negligible effect on anodic electro-generation of persulfate. However, in the anode compartment the pattern was different. Hydrogen ion (H 2 SO 4 ) both in the anolyte and in the catholyte had an extensively negative effect on cathodic electrosynthesis of H 2 O 2 . Eventually, optimum conditions for the cathodic indirect oxidation of organic pollutant paired to anodic persulfate production were optimized. The coupling process can be considered as an alternative and efficient method for maximizing the utilization of the electrochemical technology. [ABSTRACT FROM AUTHOR]

The synthesized Bi 2 Fe 4 O 9 nanosheets exhibit excellent piezocatalytic activity for molecular oxygen activation. The Fe2+ sites in Bi 2 Fe 4 O 9 nanosheets as active centers preferentially adsorb molecular oxygen and donate electrons to molecular oxygen to generate O 2 ∙ - for degrading organic pollutants, which is then regenerated by accepting the piezo-electrons, resulting in outstanding piezocatalytic performance. [Display omitted] • Bi 2 Fe 4 O 9 nanosheets exhibit outstanding piezocatalytic activity for molecular oxygen activation. • The O 2 ∙ - and piezo-holes are the major active species for piezocatalytic degradation of sulfamethoxazole. • Fe2+ in Bi 2 Fe 4 O 9 nanosheets as active sites activate molecular oxygen into O 2 ∙ - via donating electrons. • The Fe2+ can be regenerated by accepting the piezo-electrons. Piezocatalytic molecular oxygen activation has been regarded as a promising and low energy-cost strategy for environment remediation, yet the piezocatalytic activity is still far from satisfactory and little is known on its activation mechanism, which greatly hinders its further development. Herein, the piezocatalyst Bi 2 Fe 4 O 9 nanosheets (BFO NSs) are synthesized via a facile hydrothermal method, which exhibit excellent piezocatalytic performance for sulfamethoxazole degradation. O 2 ∙ - generated via the molecular oxygen reduction reaction by piezo-electrons and the piezo-holes were confirmed as major active species for organic pollutants degradation. Further theoretical calculations and XPS analyses confirm the Fe2+ sites as active centers activate molecular oxygen into O 2 ∙ - via donating the electrons to molecular oxygen and the piezo-electrons reduce Fe3+ to Fe2+. This work provides atomic-scale insights into the active sites of piezocatalytic molecular oxygen activation, which can inspire the development of more efficient piezocatalysts for environment application. [ABSTRACT FROM AUTHOR]

Electro-Fenton process represents an attractive and effective technology in destroying hazardous and organic pollutants. However, the low H 2 O 2 productivity and the narrow working pH range have been limiting its further industrial application. In this study, an improved gas diffusion electrode constructed by carbon black and PTFE was designed to improve H 2 O 2 productivity. The diaphragm electrolytic device was then used to degrade phenol without adding any catalyst. Results showed that the maximum concentration of H 2 O 2 was 275.5 mM, which was roughly eight times higher than the value obtained by traditional reference cathode. The effects of the operation parameters, such as current density, supporting electrolyte, pH, air flow rate, and phenol concentration, on phenol removal were systematically optimized. Under the optimum conditions, phenol removal reached almost 100% after 40 min and the mineralization efficiency in terms of TOC exceeded 85% after 120 min. Experiments indicated that the degradation of phenol in the electrochemical process was dominated by radical based mechanisms, which was obtained by the electro-generation and the subsequent electro-activation of H 2 O 2 at the cathode interface. It is suggested that the electro-activated H 2 O 2 process with less influence of pH and ferrous is a potential method for the electrochemical degradation process. [ABSTRACT FROM AUTHOR]

Quickly and accurately grasping the water quality in the drainage network is essential for the management and early warning of the urban water environment. Modeling-based detection methods enable fast and reagent-free water quality detection based on inexpensive multi-source data, which is cleaner and more sustainable than traditional chemical-reaction-based detection methods. But the unsatisfactory accuracy limits their practical application. This study proposes an integrated EMD-LSTM model that combines the data preprocessing module centered on empirical mode decomposition (EMD) and the long short-term memory (LSTM) neural network prediction module to improve the accuracy of the modeling-based detection methods. In the integrated EMD-LSTM model, EMD allows retaining outliers and utilizing data on non-aligned moments, which contributes to capturing data patterns, while powerful nonlinear mapping and learning ability of LSTM neural network enables the time series prediction of water quality. As a result, the EMD-LSTM has achieved the highest R2 values (0.961, 0.9384, 0.9575, 0.9441, 0.9502) and the lowest RMSE values (8.3112, 6.7795, 0.2691, 2.6239, 1.4894) in the prediction of COD, BOD 5 , TP, TN, NH 3 –N when compared with the integrated models formed by combining other preprocessing procedures (i.e., traditional operation, short-time Fourier transform) and data-driven forecasting algorithms (i.e., partial least squares regression, gradient boosting regression, deep neural network). This study provides enlightenment for improving the accuracy of modeling-based detection methods, which has driven the development of water quality detection technology towards cleaner and more sustainable. [Display omitted] • Propose an integrated EMD-LSTM model for high-cost water quality indicator prediction. • Preprocessing procedure with EMD improves the efficiency of data utilization. • EMD based LSTM prediction achieves 1.6–2.8% higher R2 than traditional pretreatment. • EMD enables outliers and non-aligned moments data play positive roles. [ABSTRACT FROM AUTHOR]

The high concentrations of heavy metals in municipal industrial sewer networks will seriously impact the microorganisms of the activated sludge in the wastewater treatment plant (WWTP), thus deteriorating the effluent quality and destroying the stability of sewage treatment. Therefore, timely prediction and early warning of heavy metal concentrations in industrial sewer networks is crucial. However, due to the complex sources of heavy metals in industrial sewer networks, traditional physical modeling and linear methods cannot establish an accurate prediction model. Herein, we developed a Gated Recurrent Unit (GRU) neural network model based on a deep learning algorithm for predicting the concentrations of heavy metals in industrial sewer networks. To train the GRU model, we used low-cost and easy-to-obtain urban multi-source data, including socio-environmental indicator data, air environmental indicator data, water quantity indicator data, and easily measurable water quality indicator data. The model was applied to predict the concentrations of heavy metals (Cu, Zn, Ni, and Cr) in the sewer networks of an industrial area in southern China. The results are compared with the commonly used Artificial Neural Network (ANN) model. In this study, it was shown that the GRU had better prediction performance for Cu, Zn, Ni, and Cr concentrations, with the average R2 significantly increased by 12.35%, 11.94%, 9.21%, and 8.13%, respectively, compared to ANN predictions. The sensitivity analysis based on Shapley (SHAP) values revealed that conductivity (σ), temperature (T), pH, and sewage flow (Flow) contributed significantly to the prediction results of the model. Furthermore, the three input variables including air pressure (AP), land area (A), and population (Pop.) were removed without affecting the prediction performance of the model, which maximized the modeling efficiency and reduced the operational cost. This study provides an economical and feasible technical method for early warning of abnormal heavy metal concentrations in urban industrial sewer networks. [Display omitted] • This study reveals the variation of Cu, Zn, Ni, and Cr concentrations in industrial sewer networks. • Deep learning method based on multi-source data can predict heavy metal concentrations in sewers. • The Gated Recurrent Unit model has superior prediction performance with more than 93% accuracy. • The Shapely value method identifies the key indicators for predicting heavy metals. [ABSTRACT FROM AUTHOR]

The thesis aims to investigate the aspirations of Chinese educators and the use of innovations in education in the Chinese classroom due to the contradiction between the widespread encouragement of technological use in teaching and the latest research on educator software. Eight parameters such as presumed usage (PU), presumed ease of use (PEU), behavioral interpretation (BI), machine self-efficacy (MSE), software complexity (SC), ease of glass wall), and social constructivism educational values (CEVs) were introduced. Into the innovation diffusion model to investigate connections between these factors. Those would be the foundation of the technology acceptance framework. Digital teaching in the Chinese university's (DT-CU) framework is proposed in this research. Information was obtained from a Personality survey and evaluated with a conceptual model from 185 educators at five educational institutions. The findings show that the method suggested fits well. There were four values – PU, SC, and CEVs, while PEU and SC aren't the most robust determinants. In comparison, PU, CEV, and MSEs are important backgrounds for the technology usage of educator BIs. This research helped explain entrepreneurial intention hypotheses by putting the present study within the education system framework. It offered essential references for the decision formulation and personal success of educators related to technical. [ABSTRACT FROM AUTHOR]

A straining-dominant filtration model based on directed bond percolation is proposed. The infinite cluster structure of this model is relevant to filtration properties. Thus, a direct electrifying algorithm is modified for infinite cluster backbone identification, and the geometrical characteristic of the infinite cluster is analyzed. In addition, the relationship between the normalized effluent concentration and infinite cluster is established. The model is validated by comparing the particle concentrations estimated from analyzing the property of filtration cluster of network model with the normalized effluent concentration obtained from filtration process simulation and the experimental data. The results show that normalized effluent concentrations estimated from cluster analysis are consistent with the experimental data and filtration simulated result. Finally, the sensitivity of pore size distribution (PSD) parameters to normalized effluent concentrations estimation is analyzed. Assuming that the PSD is lognormal, the normalized effluent concentrations increase as the location parameter μ increases and scale parameter σ decreases. [ABSTRACT FROM AUTHOR]

A power law relation between the filtration coefficients for straining and flux through small pores is reported. This relation can well explain the large penetration depths of particles. However, the normalized effluent concentrations in the experiment and the exponents estimated from the laboratory tests are inconsistent with those from the 2D network model simulation. This study discusses the effects of pore size distribution, capture scheme, and coordination number on the straining-dominant filtration simulation. The findings are compared with experimental data. The sensitivity studies indicate that the two parameters in pore size distribution particularly scale parameter σ , significantly influence the experimental and simulation power law exponent estimation. Three methods are used to estimate the pore size distribution of packing glass granules to obtain a highly accurate pore size distribution. Two capture schemes are applied to 2D pore network models with periodical boundaries and random walk of particles. The normalized effluent concentrations and exponents increase as the coordination number z increases. This trend is more significant in the minimum capture scheme under the same pore size distribution parameters. The simulated normalized effluent concentrations and exponents are consistent with the experimental data under the appropriate simulated conditions. Highly accurate pore size distribution parameters of the porous medium can be inversely determined from laboratory tests with the use of the power law function. [ABSTRACT FROM AUTHOR]

Highlights: [•] The photolysis of low concentration of H2S malodorous gas. [•] Self-made high frequency discharge electrodeless lamp. [•] Effects of relative humidity and gas environments. [•] Mechanisms for direct and indirect photolysis (ozone and radical generation). [Copyright &y& Elsevier]

Highlights: [•] Zeolite/cellulose acetate blend (ZCAB) fiber possessed highly porous structures. [•] The removal of Cu(II) by ZCAB fiber was studied in a packed bed up-flow column. [•] The leakage of zeolite particles was overcome in the dynamic adsorption process. [•] The column was applied for the removal of Cu(II) from electroplating wastewater. [Copyright &y& Elsevier]

Highlights: [•] Fe2O3 was used as heterogeneous catalyst to activate PMS for oxidation of dye. [•] The as-prepared sample presented bread crumb-like and porous morphology. [•] The porous Fe2O3/PMS system exhibited high activity in decolorization of dye. [•] The porous structure and the great surface area enhanced the catalytic activity. [•] The catalyst had good stability and reusability. [ABSTRACT FROM AUTHOR]

• Data-driven method based on deep learning can predict FOG content in sewers. • The FOG prediction model based on GRU has good generalization ability. • GRU network structure adjustment achieves the optimal model performance. • The key indicators are identified based on GSA for rapid FOG content monitoring. The content of fat, oil and grease (FOG) in the sewer network sediments is the key indicator for diagnosing sewer blockage and overflow. However, the traditional FOG detection is time-consuming and costly, and the establishment of mathematical models based on statistical methods to predict the content of FOG fail to provide satisfactory accuracy. Herein, a deep learning algorithm used a data-driven FOG content prediction model is proposed to achieve a more accurate prediction of FOG content. Meanwhile, global sensitivity analysis (GSA) is exploited to evaluate the contribution of input indicators to the output indicator (FOG) in the model, so that some input indicators that have less impact on the prediction performance can be screened out, the best combination of input indicators can be determined, and the operation cost of the model can be reduced. To evaluate the effectiveness of the proposed model, a case study was conducted in a city in southern China. The experimental results indicate that the prediction model obtains good FOG estimations and performs well from a single site to multiple sites with a mean R2 of 0.922, showing a good generalization performance. Through GSA, the key input indicators in the model were identified as pH, water temperature (T), relative humidity (RH), sewage flow (Flow), drinking water supply (DWS), velocity (V) and conductivity (σ), and the input indicators such as air pressure (AP), population (Pop.), and liquid level (LV) can be reduced without affecting the prediction accuracy of the model. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: UV/TiO2/H2O2 decolorization of methylene blue (MB) was studied under high UV photon flux irradiation; the UV photon flux in this work was ranging from 3.13×10−8 to 3.13×10−6 einsteincm−2 s−1. It was shown that photodegradation using UV/TiO2/H2O2 process was much more effective than UV/TiO2 process. Under the optimal conditions of UV/TiO2/H2O2 process, 98% decolorization of 20mgL−1 MB could be achieved in 10 s. Kinetics of UV/TiO2/H2O2 decolorization follows pseudo-first order with respect to the dye concentration. In UV/TiO2 process, the photocatalytic rate constant increased with the square root of photon flux under high photon flux UV irradiation, and addition of H2O2 could turned the square root relationship closed to linear relationship. The apparent photonic efficiency under various experimental conditions have been calculated and the results also clarified that H2O2 could improve the light utilization efficiency of photocatalytic process. The electrical energy per order (EEO ) values showed that adding H2O2 could reduce energy consumption remarkably. Besides, effect of H2O2 concentration, effect of MB initial concentration and TOC removal were also studied. [Copyright &y& Elsevier]

Abstract: Cellulose acetate (CA)/zeolite (Z) composite fiber was prepared by wet spinning method and studied for the removal of copper and nickel ions from aqueous solutions. Scanning electron microscopy (SEM) showed that the CA/Z fiber possessed highly porous and sponge-like structures. The influence of several variables such as initial pH value of the solution, contact time, initial metal ion concentration and temperature on the adsorption capacity of the fiber was investigated in a batch adsorption mode. The kinetic data were analyzed by the pseudo-first-order, pseudo-second-order and intra-particle diffusion models, and the experimental data were well described by the pseudo-second-order model. The equilibrium data were discussed by the Langmuir, Freundlich and Dubinin–Radushkevich isotherm models, and the adsorption isotherms were better fitted by the Langmuir equation. Thermodynamic parameters were evaluated to understand the nature of adsorption process. Desorption of metal ions was accomplished with hydrochloric acid solution, and the result showed that the adsorbent could be reused without significant loss in adsorption performance. [Copyright &y& Elsevier]

Abstract: Compared with pollution transfer, cleaner production (CP) is more effective to reduce heavy metal pollution in many less developed countries. However, it’s more difficult to develop an efficient policy to make enterprises to completely invest in CP. This paper analyses the effects of CP policies on investment decisions of firms using a dynamic systems model and by simulating a typical electroplating enterprise in Shenzhen, China. Results show that water price could be effective only when it is increased by a sufficient amount. For instance, only when it is increased directly from 2 to 8 CNY/m3 (0.3–1.2 USD/m3), or from 8 to 16 CNY/m3 (1.2–2.5 USD/m3), will an enterprise gradually increase CP investment from process modification to recovery technology. Increasing the metal utilization rate of CP standard-plating and surface finishing industry from its current value of 75%–85% would encourage an enterprise to add recovery technology. Uniform preferential tax rate and penalties for the three parts of CP do not affect investment decisions on CP. Using the same investment subsidy rate for the three parts of CP could be effective in promoting CP only if it is above 60%. The current emission standard of metal has played a role in promoting CP. A comparison of three possible strategies indicates that a distinct policy for the different parts of CP is the optimal policy combination. An overall investigation of typical enterprises based on the abovementioned framework is suggested to make more practical policies, which than can promote CP instead of pollution transfer. [Copyright &y& Elsevier]

Abstract: CuO particles were synthesized by a hydrothermal method and used to activate Oxone for advanced oxidation of phenol in aqueous solution. The effects of several parameters on the degradation efficiency of the process were investigated. The as-prepared catalyst exhibited high activity in degradation of phenol and 100% decomposition and 86% TOC removal could be achieved in 60min at the optimum conditions. Moreover, the catalyst was demonstrated to have good stability and reusability. Radical quenching studies were conducted to classify the type of active radicals present in the reaction and X-ray photoelectron spectroscopy (XPS) was applied to investigate the transformation of the chemical state of copper. According to the experimental results, a reasonable mechanism was proposed to interpret the catalytic process. [Copyright &y& Elsevier]

novel UV apparatus based on Dean vortex technology is designed for inactivating bacteria in milk. In this apparatus, the milk flows through a helical quartz tube coiling around an electrodeless UV lamp (EUL) with a radio frequency of 2.65 MHz. Flow rate, inner diameter of quartz tube, different UV sources, and different types of bacteria have been found as the key factors for the valuable effects on bacterial inactivation. The EUL apparatus worked more efficiently in the UV inactivation of the predetermined populations of milk-related bacteria than the conventional low-pressure high-intensity mercury lamp. When the UV dose of 21.3 mJ/cm was applied, the numbers of all the bacteria were reduced by more than 6 log with a flow rate of 28.8 L/h and a tube's inner diameter of 1.5 mm. Dean vortices were formed in the milk flow during the UV processing and played an important role in the UV inactivation of the bacteria. Another inactivation test with the apparatus applying the UV dose of 21.3 mJ/cm was also done with raw cow's milk containing indigenous microorganisms, including Salmonella and Shigella spp., Listeria monocytogenes, Staphylococcus spp., Enterobacteriaceae, lactic acid bacteria, pseudomonads, and the total aerobic bacteria were reduced by approximately 3-4 log. In short, the EUL apparatus requires smaller energy, occupies less space, and has simpler operating procedures than thermal pasteurization. Thus, the novel method provides a viable alternative to thermal pasteurization of milk for improving the microbial safety of milk and extending its shelf life. [ABSTRACT FROM AUTHOR]

Abstract: LiFe(WO4)2 particles were synthesized successfully and used as a Fenton-like catalyst. The structure and morphology were characterized using scanning electron microscopy (SEM) and X-ray powder diffraction (XRD). The degradation of methylene blue (MB) under atmospheric pressure was studied as a model experiment to evaluate the catalytic activity of these particles. The results showed that the catalyst had catalytic activity in the treatment of solution containing MB and 99.7% decolorization efficiency of MB (500mgL−1) was achieved within 60min under the optimum conditions. Moreover, LiFe(WO4)2 was demonstrated to have good stability and reusability, indicating it could be a suitable heterogeneous Fenton-like catalyst. Based on the results, a reasonable mechanism was investigated to interpret the degradation process of MB. [Copyright &y& Elsevier]

Abstract: Heterogeneous photo-Fenton process using LiFe(WO4)2 as catalyst was studied to degrade Methylene blue (MB) dye in aqueous solution. The results indicated that LiFe(WO4)2 could effectively catalyze the decolorization of MB in the presence of UV light and H2O2. The effects of different parameters such as amounts of catalyst, H2O2 concentration, initial pH of the dye solution, initial dye concentration and UV light intensity on the decolorization efficiency of the process were investigated. It was found that LiFe(WO4)2 possessed a wide applicable pH range. X-ray photoelectron spectroscopy (XPS) was applied to investigate the transformation between Fe(III) and Fe(II). It was also observed that catalytic behavior could be reproduced in consecutive experiments without a considerable drop in the process efficiency. [Copyright &y& Elsevier]

Abstract: A novel thin-film apparatus with quartz optical fibers for UV-light delivery was tested for its potential to inactivate bacteria in beer. Its suitability for application could be shown in experiments with Escherichia coli, Lactobacillus brevis, Saccharomyces cerevisiae and naturally contaminating microorganisms as test microorganisms. We have optimized the optical-fiber distribution density (ODD) and thin-film thickness for treating beer. The apparatus could reduce counts of inoculated E. coli and L. brevis in beer from approximately 106 CFU/ml to below 1×101 CFU/ml and from approximately 104 CFU/ml to non-detectable limits at UV doses of 16.1 and 9.7mJ/cm2 by the thin-film apparatus respectively. The reduction of S. cerevisiae was not so efficient. Naturally contaminating lactic acid bacteria and Enterobacteriaceae in draft beer could be effectively inactivated. Furthermore, the beneficial yeasts in the draft beer were scarcely inactivated. These results implicate that application of this novel apparatus provides a promising approach to improving microbial safety and extending shelf-life of draft beer. [Copyright &y& Elsevier]

Abstract: Most juices are opaque to ultraviolet (UV) due to the high-suspended solids in them and therefore the conventional UV treatment, generally used for water treatment, cannot be used for treating juices. In order to achieve a high germicidal efficiency of UV processing, an optical device with silica optical fibers for UV light delivery was designed. Its suitability for application could be shown in experiments with Escherichia coli, Lactobacillus brevis, Saccharomyces cerevisiae and naturally contaminating microorganisms as test microorganisms. The thin-film thickness for treating apple juice was optimized. At 2.0-mm film thickness, E. coli and L. brevis were reduced by up to 6 log orders with the UV dose of 23.7mJ/cm2 and the optical-fiber distribution density of 15fibers/cm2, while only about 4-log reduction of S. cerevisiae was achieved under the same condition. Naturally contaminating lactic acid bacteria, Enterobacteriaceae and yeasts and moulds in freshly extracted apple juice were reduced to below 10CFU/ml. These results indicate that this optical device could be used to improve microbial safety and extend shelf-life of apple juice. [ABSTRACT FROM AUTHOR]

Abstract: Soil protection from heavy metal contamination requires scientific assessment on the linkage between site-specific pollutant discharge and environmental effects. However, this kind of linkage is usually disregarded due to the lack of assessment tools in environmental policies, e.g., some developed coastal cities in China have forced their highly polluting industries out to less developed interior areas without consideration of the impacts from pollution transfer. This paper developed a soil adsorption fraction (SAF) model to characterize the emissions-to-adsorption relationship between heavy metal emission and the adsorption by soil. Case studies were carried out for two adjacent southern cities in China, i.e., Guangzhou and Shaoguan. The results indicated that the average SAF of cadmium was 5.38×10−3 for Shaoguan and 1.28×10−3 for Guangzhou, i.e., cadmium released from Shaoguan threatened the soil environment 4.2 times of that from Guangzhou. Further analysis showed the polluting pathway and abundance of water resources were the main influencing factors on SAF. Soil contamination will be exaggerated by relocating heavy metal polluting industries from coastal areas to interior areas. The results should be useful to prompt site-specific policies on heavy metal pollution control. [Copyright &y& Elsevier]

Abstract: Polyacrylonitrile fiber (PANF) was modified by alcoholysis reaction and the efficiencies of the PANF and the modified polyacrylonitrile fiber (MPANF) for oil removal were investigated. Fourier transform infrared (FTIR) spectroscopy revealed that new organophilic functional groups were grafted on the fiber surface. Scanning electron microscopy (SEM) showed that the alcoholysis process made the surface of the MPANF rougher than that of the PANF. Oil sorption tests of the PANF and the MPANF for motor oil SAE 30, motor oil SAE 50, and multigrade engine oil (MEO) were carried out in batch tank (in water and in oil without water), and the MPANF showed higher oil sorption capacity compared to the PANF. Dynamic sorption of diesel oil-in-water emulsion (initial oil concentration of 630mg/dm3) was investigated in coalescing bed. The experiments in the coalescing bed indicated that the MPANF could resist higher interstitial velocity, as compared to the PANF. More than 97% of oil content in the influent stream could be removed by the MPANF bed under the optimum condition. The results indicated that reuse of the PANF as oil sorbent was quite feasible. [Copyright &y& Elsevier]

Point source pollution in urban drainage networks, which is difficult to monitor and control, has been regarded as an intractable problem. To solve the problem, key water quality indicators must be tracked in the evaluation and prediction of sewer water quality. However, some of these important chemical indicators (e.g. biological oxygen demand (BOD 5), chemical oxygen demand (COD), ammonia nitrogen (NH 4 +-N), total nitrogen (TN), and total phosphorus (TP)) require a great deal of time and effort to measure, which will adversely affect the prediction in a sewage network. Existing statistical methods and machine learning algorithms cannot effectively solve the detection time problem or provide limited accuracy. Moreover, the lack of various factors taken into account in these methods results in unsatisfactory predictive performance. Few studies consider the impact of urban multi-source data on water quality prediction of sewer networks while developing statistical methods or machine learning algorithms. To address this problem, we propose a deep learning approach based on multi-source data fusion. This approach takes into account the following indicators to comprehensively analyze and predict drainage water quality: environmental indicators (such as area and diameter); social indicators (such as population); water quantity indicators (such as drinking water supply, sewage flow, water velocity, and liquid level); and easily monitored water quality criteria indicators (such as pH, temperature, and conductivity). To test the effectiveness of this method, we conducted a case study in a city in southern China. By comparing this new method with the linear method (multiple linear regression, MLR) and traditional learning algorithm (multilayer perception, MLP), it is found that the deep learning algorithm—which includes recurrent neural network (RNN), long-short term memory (LSTM), and gated recurrent unit (GRU)—has good predictive performance, in which GRU shows superior ability in predicting the chemical index of water quality and the learning curve is faster. The results showed that the GRU achieved 0.82%–5.07% higher R2 than RNN and LSTM, 9.13%–15.03% higher R2 than traditional machine learning algorithms, and 37.26%–43.38% higher R2 than linear methods. [Display omitted] • Deep learning model based on multi-source data can predict sewer water quality. • RNN-based models have better predictive performance than MLR and MLP models. • In deep learning models, the GRU has fast learning curve and simple architecture. • GRU model prediction performance outperformed RNN and LSTM model. [ABSTRACT FROM AUTHOR]

Abstract: Since there are several problems in traditional UV disinfection techniques, a highly efficient, reliable and economical method, using quartz optical fibers to deliver UV light is proposed. The principle of the experimental setup is that ultraviolet rays are gathered by a reflector and converge on a light point, the diameter of approximately 5mm. In this way UV light can be transferred into water to kill the bacteria in the water. This paper presents preliminary results on water disinfection using this new UV disinfection setup. Its suitability for application could be shown in experiments with E. coli (ATCC8099) as test microorganisms. We have optimized the distribution of the optical fibers in the water in bench-scale study. This result can provide guidance for pilot-scale and field-scale study of this new technique. The results show that the new technique had a good performance under different conditions as follows: (a) turbidity level=10.2NTU, (b) ferric ion concentration=0.3mg/L, and (c) humic acid concentration=5mg/L. The new technique provides a promising approach to disinfection treatment of drinking water. [Copyright &y& Elsevier]

Nowadays, it is a great challenge to minimize the negative impact of hazardous organic compounds in the environment. Highly efficient hydrogen peroxide (H 2 O 2) production through electrochemical methods with gas diffusion electrodes (GDEs) is greatly demand for degradation of organic pollutants that present in drinking water and industrial wastewater. The GDEs as cathodic electrocatalyst manifest more cost-effective, lower energy consumption and higher oxygen utilization efficiency for H 2 O 2 production as compared to other carbonaceous cathodes due to its worthy chemical and physical characteristics. In recent years, the crucial research and practical application of GDE for degradation of organic pollutants have been well developed. In this review, we focus on the novel design, fundamental aspects, influence factors, and electrochemical properties of GDEs. Furthermore, we investigate the generation of H 2 O 2 through electrocatalytic processes and degradation mechanisms of refractory organic pollutants on GDEs. We describe the advanced methodologies towards electrochemical kinetics, which include the enhancement of GDEs electrochemical catalytic activity and mass transfer process. More importantly, we also highlight the other technologies assisted electrochemical process with GDEs to enlarge the practical application for water treatment. In addition, the developmental prospective and the existing research challenges of GDE-based electrocatalytic materials for real applications in H 2 O 2 production and wastewater treatment are forecasted. According to our best knowledge, only few review articles have discussed GDEs in detail for H 2 O 2 production and their applications for degradation of organic pollutants in water. Unlabelled Image • Efficient GDE cathodes for electrogeneration of H 2 O 2 and water treatment • Fundamentals aspects, influence factors, and electrochemical properties of GDEs are discussed. • Applications of GDEs in electrochemical advanced oxidation processes are described. • The degradation mechanisms of refractory organic pollutants by GDEs are explained. • Research challenges and future perspectives of GDEs are proposed. [ABSTRACT FROM AUTHOR]

Background. Protein-L-isoaspartate (D-aspartate) O-methyltransferase (PCMT1) is involved in the occurrence and development of a variety of malignant tumors. However, the prognostic value of PCMT1 in breast cancer remains unclear. Methods. Based on the Cancer Genome Atlas database, we assessed the correlation between the expression of PCMT1 and prognosis, immune invasion, and tumor mutation burden in a variety of cancers. The expression level, mutation, immune correlation, and coexpression of PCMT1 in breast cancer were studied using the following databases: UALCAN database, Human Protein Atlas database, cBioPortal database, TIMER database, and LinkedOmics database. Kaplan–Meier Plotter was used for survival analysis. Receiver operating characteristic (ROC) curves and nomograms were drawn using the R software package. P < 0.05 was considered statistically significant. Results. Pancancer analysis showed that PCMT1 is highly expressed in a variety of cancers and is significantly related to the prognosis of a variety of cancers. PCMT1 is significantly related to the tumor mutation burden of a variety of cancers. PCMT1 is significantly high in breast cancer, and it is significantly related to the abundance of immune infiltration. Survival analysis revealed that high PCMT1 expression is significantly associated with shorter overall survival (OS), relapse-free survival (RFS), and postprogression survival (PPS) in breast cancer patients. ROC curves and nomograms verify the effectiveness of PCMT1 as a prognostic biomarker for breast cancer. Conclusions. PCMT1 can be used as a potential prognostic biomarker of breast cancer, and it is significantly related to the abundance of breast cancer immune infiltration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mn dopant-reinforced NaTi 2 (PO 4) 3 possesses superior structural stability and conductivity. • The optimal NT 1.5 M 0.5 P exhibits ultrahigh salt removal capacity of 128.5 mg/g and cycle stability. • The ultrahigh durability is rooted from the solid-solution reaction induced by Mn-ions pillar. • NT 1.5 M 0.5 P||NaFeHCF rocking-chair desalination battery owns stable, rapid and low energy consumption desalination. Battery deionization (BDI) technique has attracted great attention as a potential candidate to tackle the freshwater crisis, but its application is plagued by the lack of electrode materials with large desalination capacity and excellent durability. Herein, Mn dopant-reinforced NaTi 2 (PO 4) 3 (NT 2–x M x P) composites with significantly enhanced structural stability and electronic/ionic conductivity were fabricated toward seawater desalination. Especially, the NT 1.5 M 0.5 P exhibits excellent desalination performance, affording a salt removal capacity (SRC) of 128.5 mg/g with a salt removal rate (SRR) of 18.4 mg g−1 min−1 and almost no capacity attenuation after 500 cycles. Furthermore, the NT 1.5 M 0.5 P further possesses favorable technical feasibility in different aqueous media, including desalination at various NaCl concentrations, temperature, solution pH, and natural seawater. Mechanism studies reveal that the NT 1.5 M 0.5 P undergoes a solid-solution reaction based on the reversible electrochemical reaction of the Ti4+/Ti3+ redox pair during the desalination/salination process. A rocking-chair desalination battery consisting of NT 1.5 M 0.5 P and NaFeHCF demonstrates a favorable desalination ability (average SRC of 49.4 mg/g and SRR of 1.73 mg g−1 min−1), outstanding cycling stability (92 % of capacity retention in 100 cycles), low energy consumption (0.288 kWh/kg-NaCl) and high average charging efficiency (86.9 %). This work sheds light on the rational design of advanced NASICON-type electrodes for seawater desalination with remarkable desalination capacity and long serving life. [ABSTRACT FROM AUTHOR]

The application of promising persulfate-based advanced oxidation processes (AOPs) for environment remediation is limited by the poor charge separation and the sluggish kinetic for active centers regeneration of the catalysts. Piezocatalytic activation has been proposed to solve the above concern recently, but little is known on its mechanism. Herein, novel piezocatalyst Bi 2 Fe 4 O 9 nanosheets (BFO NSs) are demonstrated to significantly improve peroxydisulfate (PDS) activation efficiency via piezocatalysis, resulting SO 4 •− and •OH as the dominant active species for organic pollutants degradation. Further DFT calculations and experimental investigations confirm that the Fe2+ in BFO NSs as active sites donate electrons for PDS to generate SO 4 •−, and simultaneously that the piezo-electrons can accelerate the regeneration of Fe2+, thus leading to the superior catalytic activity. This work provides atomic-scale insights of catalytic sites and mechanisms of piezocatalytic PDS activation and may inspire the development of more efficient piezocatalysts and AOPs. Highly efficient piezocatalytic activation of peroxydisulfate over Bi 2 Fe 4 O 9 nanosheets was demonstrated. Fe2+ in Bi 2 Fe 4 O 9 as active centers can activate S 2 O 8 2– into SO 4 •− through donation electrons for organic pollutants degradation, meanwhile the piezo-electrons can accelerate the regeneration of Fe2+, thus resulting in excellent catalytic activity. [Display omitted] • The novel piezocatalyst Bi 2 Fe 4 O 9 nanosheets are synthesized through a facile hydrothermal approach. • The piezocatalysis of Bi 2 Fe 4 O 9 can significantly improve peroxydisulfate activation efficiency. • The piezo-electrons can accelerate the regeneration of Fe2+ active sites. [ABSTRACT FROM AUTHOR]

Background: Glucagon-like peptide-1 (GLP-1) is an incretin hormone that facilitates insulin secretion and preserves β cell function. hypertriglyceridemia plays an important role in the pathogenesis of insulin resistance and T2DM. The purpose of this study was to measure fasting active GLP-1 levels in hypertriglyceridemia subjects and analyse the relationship between GLP-1 and insulin resistance. Methods: We recruited 146 subjects including 38 diabetes patients with hypertriglyceridemia, 33 diabetes patients without hypertriglyceridemia, 35 hypertriglyceridemia subjects, and 40 healthy subjects as the normal control group. Serum fasting active GLP-1 was tested with ELISA in the four groups, and associations with insulin resistance were analysed. Results: Serum fasting active GLP-1 levels were significantly increased in hypertriglyceridemia subjects with or without T2DM compared with healthy controls, particularly hypertriglyceridemia patients with T2DM (p < 0.01). GLP-1 levels positively correlated with triglyceride (TG) levels, fasting insulin (FINS) levels, and HOMA-IR (p < 0.01). Furthermore, multiple stepwise regression showed that TG levels and HOMA-IR were independently associated with fasting active GLP-1 levels (p < 0.01). Conclusions: Hypertriglyceridemia was associated with elevated fasting active GLP-1 levels, and a significant association was noted between GLP-1 and HOMA-IR. This finding provides evidence that the increase in GLP-1 may play a compensatory role in the pathogenesis of insulin resistance induced by hypertriglyceridemia. [ABSTRACT FROM AUTHOR]

Operation performances of phosphorus removal sludge with different electron acceptors in three parallel SBRs were firstly compared in the present study, and the effect of post-aeration on denitrifying phosphorus removal was also studied. Moreover, community dynamics of different phosphorus removal sludge was systematically investigated with high-throughput sequencing for the first time. TP removal rates for nitrate-, nitrite-, and oxygen-based phosphorus removal sludge were 84.8, 78.5, and 87.4 %, with an average effluent TP concentration of 0.758, 0.931, and 0.632 mg/l. The average specific phosphorus release and uptake rates were 20.3, 10.8, and 21.5, and 9.43, 8.68, and 10.8 mgP/(gVSS h), respectively. Moreover, electron utilization efficiency of denitrifying phosphorus removal sludge with nitrate as electron acceptor was higher than nitrite, with P/e were 2.21 and 1.51 mol-P/mol-e, respectively. With the assistance of post-aeration for nitrate-based denitrifying phosphorus removal sludge, settling ability could be improved, with SVI decreased from 120 to 80 and 72 ml/g when post-aeration time was 0, 10, and 30 min, respectively. Moreover, further phosphorus removal could be achieved during post-aeration with increased aeration time. However, the anoxic phosphorus uptake was deteriorated, which was likely a result of shifted microbial community structure. Post-aeration of approximately 10 min was proposed for denitrifying phosphorus removal. Nitrate- and nitrite-based denitrifying phosphorus removal sludge exhibited similar community structure. More phosphorus accumulating organisms were enriched under anaerobic-aerobic conditions, while anaerobic-anoxic conditions were favorable for suppressing glycogen-accumulating organisms. Significant differences in pathogenic bacterial community profiles revealed in the current study indicated the potential public health hazards of non-aeration activated sludge system. [ABSTRACT FROM AUTHOR]

Developing electrolytes qualified for high-voltage (>4 V vs Li/Li+) conditions is of great significance for high-energy density Li-metal batteries (LMBs). Carbonate-based electrolytes possess high oxidation stability, whereas the uneven Li deposition, low Coulombic efficiency (CE) and poor anodic stability of such electrolytes severely impede the practical application in high-voltage LMBs. Herein, a 1.8 M lithium bis(trifluoromethanesulphonyl)imide (LiTFSI)-carbonate electrolyte with high compatibility with both Li anode and high-voltage cathode is designed. LiNO 3 is introduced into the electrolyte as an additive with the assistance of CuF 2 cosolvent, which efficiently enables robust and conductive interfaces at both anode and cathode sides. As a consequence, an average CE of 98.0% is achieved for Li||Cu half-cell at 1 mA cm−2. Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 full cell fabricated with cathode areal capacity of 2.4 mAh cm−2 and 5× excess Li achieves a high capacity retention of 80.7% after 200 cycles with cut-off voltage of 4.3 V. This work provides a facile and effective approach to improve the application of carbonate-based electrolytes in high-voltage LMBs. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Nickel catalyzed Suzuki-type alkylation utilizing combined ligand systems. • Selective activation of one C–Cl bond of inert 1,2-dichloroethane (DCE). • Circumvent undesirable Ni-mediated β-chloride or β-hydride eliminations. • Facile access to homobenzylic chlorides in step-simplicities. Abstract The selective conversion of one inactive C(sp3)-Cl bond of 1,2-dichloroethane (DCE) into C(sp3)-C(sp2) linkages for access to β-chloroethylarenes is presented here. The key to achieve the required reactivity and chemoselectivity in this synthetic method was the utilization of nickel and combinatorial nitrogen ligands as catalytic system. Synthetic advantages of this coupling chemistry included the step-simplicities to β-chloroethylarenes, the mildness and effectiveness of coupling conditions, together with the convenience for allowing further functional group transformations of the retained homobenzylic C–Cl bonds. [ABSTRACT FROM AUTHOR]

[Display omitted] • A highly active 2e-WOR electrocatalyst was prepared by modifying CFP with SAMs. • SAMs modified CFP achieves a high H 2 O 2 yield of 79.8 μmol min−1 cm−2 at 2.1 V. • SAMs modification enriches the 2e-WOR active site and reduces the OER active site by modulating the ΔG*OH. • Carbon atoms adjacent to O=C-M are active sites for efficient 2e-WOR. • O=C-M are rooted from the reaction between the functional group on CFP and SAMs. Two-electron water oxidation (2e-WOR) is an attractive method for the electrosynthesis of hydrogen peroxide (H 2 O 2). However, its practical application is limited by the viable 2e-WOR catalysts that can ensure high selectivity and high H 2 O 2 yield. In this paper, a highly active 2e-WOR electrocatalyst was prepared by modifying carbon fiber paper (CFP) with a self-assembled membrane (SAMs). The SAMs modified CFP can achieve an H 2 O 2 yield of 79.8 μmol min−1 cm−2 and an H 2 O 2 selectivity of 82.5% at a low potential (2.1 V vs. RHE). The DFT calculation reveals that SAMs modification can modulate the *OH binding energy of the active site on CFP, thus leading to a significantly improved selectivity and production rate of H 2 O 2. Moreover, the 2e-WOR performance is found to be independent of the functional tail groups of SAMs because the electron transfer during the 2e-WOR occurs through direct electron transfer via the carbon atoms adjacent to the O=C-M on carbon fiber rather than the well-known electron tunneling through SAMs. This study provides a new strategy for surface modification of 2e-WOR carbon-based catalysts and opens a new way for efficient electrosynthesis of H 2 O 2. [ABSTRACT FROM AUTHOR]

Mesoporous In/Hβ-X series catalysts were prepared by desilication method with tetrapropylammonium hydroxide (TPAOH) and indium incorporation for selective catalytic reduction of NO with methane (CH 4 -SCR). The post desilication treatment conditions for preparing In/Hβ-X were optimized. Etching time is the most important desilication parameter influencing the resulting CH 4 -SCR performance of the catalyst. The In/Hβ-3 sample which was etched for 3 h presents the highest NO x conversion, 22% higher than In/H-Beta counterparts using commercial microporous beta. Obvious analysis reveals that besides generating mesopores, controlled desilication can modulate the proportion of InO+ active sites and surface oxygen species, allowing more active sites to be exposed. • Mesoporous beta zeolite was fast synthesized by desilication with TPAOH. • Portion of InO+ greatly contributed to the high catalytic efficiency. • Controlled etching modulated the proportion of InO+ active sites and surface oxygen. [ABSTRACT FROM AUTHOR]

In this paper, the NO x conversion reduced enormously after the water vapor and sulfur test. Then, the poisoning mechanism of SO 2 /H 2 O on In/H-Beta for CH 4 -SCR was investigated using various characterization techniques such as TPSR, XRD, XPS, and in-situ DRIFTS to elucidate the CH 4 -SCR process over In/H-Beta catalyst. The results showed that SO 2 , NO and CH 4 had competitive adsorption on the (InO)+ active sites of the catalyst to form sulfate species. H 2 O adsorbed on the Si-OH (i) and (InO)+ active sites, reduced the adsorption of NO and CH 4 and ultimately blocked the catalyst for the CH 4 -SCR reaction. This study provided insights into the H 2 O/SO 2 poisoning mechanism of the In/H-Beta catalyst, which guide the design of novel catalysts for CH 4 -SCR. [Display omitted] • SO 2 competed with NO for adsorption on the surface by interacting with (InO)+. • H 2 O adsorbed on Si-OH (i) , further affecting NO's adsorption. • H 2 O was preferentially adsorbed on the InO+ active sites compared to SO 2 , CH 4 and NO. • SO 2 and H 2 O appeared to exhibit synergistic toxicity in the poisoning of the catalyst. [ABSTRACT FROM AUTHOR]