Development and validation of a risk score nomogram model to predict the risk of 5-year all-cause mortality in diabetic patients with hypertension: A study based on NHANES data.

Background: The present study aimed to develop and validate a prediction nomogram model for 5-year all-cause mortality in diabetic patients with hypertension. Methods: Data were extracted from the National Health and Nutrition Examination Survey (NHANES). A total of 3291 diabetic patients with hypertension in the NHANES cycles for 1999-2014 were selected and randomly assigned at a ratio of 8:2 to the training cohort (n = 2633) and validation cohort (n = 658). Multivariable Cox regression was conducted to establish a visual nomogram model for predicting the risk of 5-year all-cause mortality. Receiver operating characteristic curves and C-indexes were used to evaluate the discriminant ability of the prediction nomogram model for all-cause mortality. Survival curves were created using the Kaplan-Meier method and compared by the log-rank test. Results: The nomogram model included eight independent predictors: age, sex, education status, marital status, smoking, serum albumin, blood urea nitrogen, and previous cardiovascular disease. The C-indexes for the model in the training and validation cohorts were 0.76 (95% confidence interval: 0.73-0.79, p < 0.001) and 0.75 (95% confidence interval: 0.69-0.81, p < 0.001), respectively. The calibration curves indicated that the model had satisfactory consistency in the two cohorts. The risk of all-cause mortality gradually increased as the tertiles of the nomogram model score increased (log-rank test, p < 0.001). Conclusion: The newly developed nomogram model, a readily useable and efficient tool to predict the risk of 5-year all-cause mortality in diabetic patients with hypertension, provides a novel risk stratification method for individualized intervention.

SEB-YOLO: An Improved YOLOv5 Model for Remote Sensing Small Target Detection.

Due to the limited semantic information extraction with small objects and difficulty in distinguishing similar targets, it brings great challenges to target detection in remote sensing scenarios, which results in poor detection performance. This paper proposes an improved YOLOv5 remote sensing image target detection algorithm, SEB-YOLO (SPD-Conv + ECSPP + Bi-FPN + YOLOv5). Firstly, the space-to-depth (SPD) layer followed by a non-strided convolution (Conv) layer module (SPD-Conv) was used to reconstruct the backbone network, which retained the global features and reduced the feature loss. Meanwhile, the pooling module with the attention mechanism of the final layer of the backbone network was designed to help the network better identify and locate the target. Furthermore, a bidirectional feature pyramid network (Bi-FPN) with bilinear interpolation upsampling was added to improve bidirectional cross-scale connection and weighted feature fusion. Finally, the decoupled head is introduced to enhance the model convergence and solve the contradiction between the classification task and the regression task. Experimental results on NWPU VHR-10 and RSOD datasets show that the mAP of the proposed algorithm reaches 93.5% and 93.9%respectively, which is 4.0% and 5.3% higher than that of the original YOLOv5l algorithm. The proposed algorithm achieves better detection results for complex remote sensing images.

Mechanistic insight into the aggregation ability of anammox microorganisms: Roles of polarity, composition and molecular structure of extracellular polymeric substances.

The chemical characteristics of extracellular polymeric substances (EPS) of anammox bacteria (AnAOB) play a crucial role in the rapid enrichment of AnAOB and the stable operation of wastewater anammox processes. To clarify the influential mechanisms of sludge EPS on AnAOB aggregation, multiple parameters, including the polarity distribution, composition, and molecular structure of EPS, were selected, and their quantitative relationship with AnAOB aggregation was analyzed. Compared to typical anaerobic sludge (anaerobic floc and granular sludge), the anammox sludge EPS exhibited higher levels of tryptophan-like substances (44.82-56.52 % vs. 2.57-39.81 %), polysaccharides (40.02-53.49 mg/g VSS vs. 30.22-41.69 mg/g VSS), and protein structural units including α-helices (20.70-23.98 % vs. 16.48-19.32 %), ß-sheets (37.43-42.98 % vs. 25.78-36.72 %), and protonated nitrogen (Npr) (0.065-0.122 vs. 0.017-0.061). In contrast, it had lower contents of ß-turns (20.95-27.39 % vs. 28.17-39.04 %). These biopolymers were found to originate from different genera of AnAOB. Specifically, the α-helix-rich proteins were mainly derived from Candidatus Kuenenia, whereas the extracellular proteins related to tryptophan and Npr were closely associated with Candidatus Brocadia. Critically, these EPS components could drive anammox aggregation through interactions. Substantial amounts of tryptophan-like substances facilitated the formation of ß-sheet structures and the exposure of internal hydrophobic clusters, which benefited the anammox aggregation. Meanwhile, extracellular proteins with high Npr content played a pivotal role in the formation of mixed protein-polysaccharide gel networks with the electronegative regions of polysaccharides, which could be regarded as the key component in the maintenance of anammox sludge stability. These findings provide a comprehensive understanding of the multifaceted roles of EPS in driving anammox aggregation and offer valuable insights into the development of EPS regulation strategies aimed at optimizing the anammox process.

Selective Nitrate Electroreduction to Ammonia on CNT Electrodes with Controllable Interfacial Wettability.

The development of electrocatalysts that can efficiently reduce nitrate (NO3-) to ammonia (NH3) has garnered increasing attention due to their potential to reduce carbon emissions and promote environmental protection. Intensive efforts have focused on catalyst development, but a thorough understanding of the effect of the microenvironment around the reactive sites of the catalyst is also crucial to maximize the performance of the electrocatalysts. This study explored an electrocatalytic system that utilized quaternary ammonium surfactants with a range of alkyl chain lengths to modify an electrode made of carbon nanotubes (CNT), with the goal of regulating interfacial wettability toward NO3- reduction. Trimethyltetradecylammonium bromide with a moderate alkyl chain length created a very hydrophobic interface, which led to a high selectivity in the production of NH3 (∼87%). Detailed mechanistic investigations that used operando Fourier-transform infrared (FTIR) spectroscopy and online differential electrochemical mass spectrometry (DEMS) revealed that the construction of a hydrophobic modified CNT played a synergistic role in suppressing a side reaction involving the generation of hydrogen, which would compete with the reduction of NO3-. This electrocatalytic system led to a favorable process for the reduction of NO3- to NH3 through a direct electron transfer pathway. Our findings underscore the significance of controlling the hydrophobic surface of electrocatalysts as an effective means to enhance electrochemical performance in aqueous media.

Hepatotoxic effects of chronic exposure to environmentally relevant concentrations of Di-(2-ethylhexyl) phthalate (DEHP) on crucian carp: Insights from multi-omics analyses.

Di-(2-ethylhexyl) phthalate (DEHP) is an extensively used phthalate esters (PAEs) that raise growing ecotoxicological concerns due to detrimental effects on living organisms and ecosystems. This study performed hepatotoxic investigations on crucian carp under chronic low-dosage (CLD) exposure to DEHP at environmentally relevant concentrations (20-500 µg/L). The results demonstrated that the CLD exposure induced irreversible damage to the liver tissue. Multi-omics (transcriptomics and metabolomics) analyses revealed the predominant toxicological mechanisms underlying DEHP-induced hepatotoxicity by inhibiting energy production pathways and the up-regulation of the purine metabolism. Disruption of metabolic pathways led to excessive reactive oxygen species (ROS) production and subsequent oxidative stress. The adverse metabolic effects were exacerbated by an interplay between oxidative stress and endoplasmic reticulum stress. This study not only provides new mechanistic insights into the ecotoxicological effects of DEHP under chronic low-dosage exposure, but also suggests a potential strategy for further ecological risk assessment of PAEs.

USP36-mediated PARP1 deubiquitination in doxorubicin-induced cardiomyopathy.

Doxorubicin (Dox) is a potent antineoplastic agent, but its use is curtailed by severe cardiotoxicity, known as Dox-induced cardiomyopathy (DIC). The molecular mechanism underlying this cardiotoxicity remains unclear. Our current study investigates the role of Ubiquitin-Specific Protease 36 (USP36), a nucleolar deubiquitinating enzyme (DUB), in the progression of DIC and its mechanism. We found increased USP36 expression in neonatal rat cardiomyocytes and H9C2 cells exposed to Dox. Silencing USP36 significantly mitigated Dox-induced oxidative stress injury and apoptosis in vitro. Mechanistically, USP36 upregulation positively correlated with Poly (ADP-ribose) polymerase 1 (PARP1) expression, and its knockdown led to a reduction in PARP1 levels. Further investigation revealed that USP36 could bind to and mediate the deubiquitination of PARP1, thereby increasing its protein stability in cardiomyocytes upon Dox exposure. Moreover, overexpression of wild-type (WT) USP36 plasmid, but not its catalytically inactive mutant (C131A), stabilized PARP1 in HEK293T cells. We also established a DIC model in mice and observed significant upregulation of USP36 in the heart. Cardiac knockdown of USP36 in mice using a type 9 recombinant adeno-associated virus (rAAV9)-shUSP36 significantly preserved cardiac function after Dox treatment and protected against Dox-induced structural changes within the myocardium. In conclusion, these findings suggest that Dox promotes DIC progression by activating USP36-mediated PARP1 deubiquitination. This novel USP36/PARP1 axis may play a significant regulatory role in the pathogenesis of DIC.

Bioinspired Tandem Electrode for Selective Electrocatalytic Synthesis of Ammonia from Aqueous Nitrate.

The electrocatalytic nitrate reduction reaction (NO3RR) has recently emerged as a promising technique for readily converting aqueous nitrate (NO3-) pollutants into valuable ammonia (NH3). It is vital to thoroughly understand the mechanism of the reaction to rationally design and construct advanced electrocatalytic systems that can effectively and selectively drive the NO3RR. There are several natural enzymes that incorporate molybdenum (Mo) and that can activate NO3-. Based on this, a cadmium (Cd) single-atom anchored Mo2TiC2Tx electrocatalyst (referred to as CdSA-Mo2TiC2Tx) through the NO3RR to generate NH3 was rationally designed and demonstrated. In an H-type electrolysis cell and at a current density of 42.5 mA cm-2, the electrocatalyst had a Faradaic efficiency of >95% and an impressive NH3 yield rate of 48.5 mg h-1 cm-2. Moreover, the conversion of NO3- to NH3 on the CdSA-Mo2TiC2Tx surface was further revealed by operando attenuated total reflection Fourier-transform infrared spectroscopy and an electrochemical differential mass spectrometer. The electrocatalyst significantly outperformed Mo2TiC2Tx as well as reported state-of-the-art catalysts. Density functional theory calculations revealed that CdSA-Mo2TiC2Tx decreased the ability of the d-p orbital to hybridize with NH3* intermediates, thereby decreasing the activation energy of the potential-determining step. This work not only highlights the application prospects of heavy metal single-atom catalysts in the NO3RR but also provides examples of bio-inspired electrocatalysts for the synthesis of NH3.

To Assess the Role of microRNA-451 in the Progression and Metastasis of Colorectal Cancer.

The study aimed to determine the expression of miR451 in colorectal cancer (CRC) subjects with CRC cells, and the role of miR451 in colorectal cancer cells. In October 2020, ATC purchased CRC and normal mucosal cell lines of CRC and implanted them in DMEM with 10% fetal serum. The suitability of the HT29 cell line is verified using the STR profile. In an incubator with 5% CO2, enlarged cells were placed at 37 °C. TCGA data was used to select the top 120 patients with a high voice and the lowest 120 patients with a low voice. Cells were collected and coated with Annexin V and PE according to the manufacturer's instructions after 24.0 h. After that, the cells were separated. Cells were also tested using flow cytometry. HCT-120 cells were transplanted into a concentration of 5×105/ml cells in 6-source plates. HCT120 cells in the experimental group were combined with miR451 mimics, miR451 inhibitors, or miR451 miR + SMAD4B for 12 h at 37 °C, and cells were collected 24 h later at 37 °C. The sample was injected with 5 ml of Annexin VFITC and PE. Compared with normal colorectal mucosal cells, CRC cell lines decreased miR451 expression levels (fetal human cells (FHC) and HCoEpiC). Then, the HCT120 cells were transfected with miR451 inhibitors, and 72 h after transfection, say of miR451 was normal. There was a significant decrease in cell function in the miR451mimic groups, but an increase when the miR451 was blocked. The proliferation of cancer cells was prevented and chemotherapy was effective when miR451 was overexpressed. The SMAD4 gene provides instructions for making a protein involved in transmitting chemical signals from the cell surface to the nucleus. The SMAD4B expression was tested by RT-qPCR and Western blotting after 72.0 h of transmission. The mRNA and protein expression of SMAD4B decreased significantly when miR451 was significantly higher than when inhibited, as revealed in the results of this study. Seventy-two hours after transplantation, mRNA levels and SMAD4B proteins were measured in HCT120 cells. In addition, the researchers in this study investigated whether miR451 was associated with SMAD4B-directed control of CRC growth and migration. It was found that SMAD4B is highly expressed in both CRC and para-cancer tissues while using the TCGA database to detect SMAD4B expression. Patients with CRC with SMAD4B have a severe prognosis. MiR451 is sensitive to depressive disorders by targeting SMAD4B, according to these studies. We found that miR451 inhibited cell growth and migration, made CRC cells more readily available in chemotherapy, and did so by targeting SMAD4B. The findings suggest that miR451 and its genetic predisposition, SMAD4B, may help predict the prognosis and course of cancer patients. Treatments that target the miR451/SMAD4B axis may be helpful to people with CRC.

Electro-oxidation and UV irradiation coupled method for in-site removing pollutants from human body fluids in swimming pool.

A comprehensive study was conducted to investigate how ultraviolet (UV) irradiation combined with electrochemistry (EC) can efficiently remove human body fluids (HBFs) related pollutants, such as urea/creatinine/hippuric acid, from swimming pool water (SPW). In comparison with the chlorination, UV, EC, and UV/chlorine treatments, the EC/UV treatment exhibited the highest removal rates for these typical pollutants (TPs) from HBFs in synthetic SPW. Specifically, increasing the operating current of the EC/UV process from 20 to 60 mA, as well as NaCl content from 0.5 to 3.0 g/L, improved urea and creatinine degradation while having no influence on hippuric acid. In contrast, EC/UV process was resilient to changes in water parameters (pH, HCO3-, and actual water matrix). Urea removal was primarily attributable to reactive chlorine species (RCS), whereas creatinine and hippuric acid removal were primarily related to hydroxyl radical, UV photolysis, and RCS. In addition, the EC/UV procedure can lessen the propensity for creatinine and hippuric acid to generate disinfection by-products. We can therefore draw the conclusion that the EC/UV process is a green and efficient in-situ technology for removing HBFs related TPs from SPW with the benefits of needless chlorine-based chemical additive, easy operation, continuous disinfection efficiency, and fewer byproducts production.

SiamHSFT: A Siamese Network-Based Tracker with Hierarchical Sparse Fusion and Transformer for UAV Tracking.

Due to high maneuverability as well as hardware limitations of Unmanned Aerial Vehicle (UAV) platforms, tracking targets in UAV views often encounter challenges such as low resolution, fast motion, and background interference, which make it difficult to strike a compatibility between performance and efficiency. Based on the Siamese network framework, this paper proposes a novel UAV tracking algorithm, SiamHSFT, aiming to achieve a balance between tracking robustness and real-time computation. Firstly, by combining CBAM attention and downward information interaction in the feature enhancement module, the provided method merges high-level and low-level feature maps to prevent the loss of information when dealing with small targets. Secondly, it focuses on both long and short spatial intervals within the affinity in the interlaced sparse attention module, thereby enhancing the utilization of global context and prioritizing crucial information in feature extraction. Lastly, the Transformer's encoder is optimized with a modulation enhancement layer, which integrates triplet attention to enhance inter-layer dependencies and improve target discrimination. Experimental results demonstrate SiamHSFT's excellent performance across diverse datasets, including UAV123, UAV20L, UAV123@10fps, and DTB70. Notably, it performs better in fast motion and dynamic blurring scenarios. Meanwhile, it maintains an average tracking speed of 126.7 fps across all datasets, meeting real-time tracking requirements.

Water Flow-Driven Coupling Process of Anodic Oxygen Evolution and Cathodic Oxygen Activation for Water Decontamination and Prevention of Chlorinated Byproducts.

Electrochemical advanced oxidation process (EAOP) is a promising technology for decentralized water decontamination but is subject to parasitic anodic oxygen evolution and formation of toxic chlorinated byproducts in the presence of Cl-. To address this issue, we developed a novel electrolytic process by water flow-driven coupling of anodic oxygen evolution reaction (OER) and cathodic molecular oxygen activation (MOA). When water flows from anode to cathode, O2 produced from OER is carried by water through convection, followed by being activated by atomic hydrogen (H*) on Pd cathode to produce •OH. The water flow-driven OER/MOA process enables the anode to be polarized at low potential (1.7 V vs SHE) that is lower than that of conventional EAOP whose •OH is produced from direct water oxidation (>2.3 V vs SHE). At a flow rate of 30 mL min-1, the process could achieve 94.8% removal of 2,4-dichlorophenol (2,4-DCP) and 71.5% removal of chemical oxygen demand (COD) within 45 min at an anode potential of 1.7 V vs SHE and cathode potential of -0.5 V vs SHE. To achieve the comparable 2,4-DCP removal performance, 4.3-fold higher energy consumption was needed for the conventional EAOP with titanium suboxide anode (anode potential of 2.9 V vs SHE), but current efficiency declined by 3.5 folds. Unlike conventional EAOP, chlorate and perchlorate were not detected in the OER/MOA process, because low anode potential <2.0 V vs SHE was thermodynamically unfavorable for the formation of chlorinated byproducts by anodic oxidation, indicated by theoretical calculations and experimental data. This study provides a proof-in-concept demonstration of water flow-driven OER/MOA process, representing a paradigm shift of electrochemical technology for water decontamination and prevention of chlorinated byproducts, making electrochemical water decontamination more efficient, more economic, and more sustainable.

Copper Nanowire Networks: An Effective Electrochemical Peroxymonosulfate Activator toward Nitrogenous Pollutant Abatement.

Herein, we developed an electrochemical filtration system for effective and selective abatement of nitrogenous organic pollutants via peroxymonosulfate (PMS) activation. Highly conductive and porous copper nanowire (CuNW) networks were constructed to serve simultaneously as catalyst, electrode, and filtration media. In one demonstration of the CuNW network's capability, a single pass through a CuNW filter (τ < 2 s) degraded 94.8% of sulfamethoxazole (SMX) at an applied potential of -0.4 V vs SHE. The exposed {111} crystal plane of CuNW triggered atomic hydrogen (H*) generation on sites, which contributed to effective PMS reduction. Meanwhile, with the involvement of SMX, a Cu-N bond was formed by the interactions between the -NH2 group of SMX and the Cu sites of CuNW, accompanied by the redox cycling of Cu2+/Cu+, which was facilitated by the applied potential. The different charges of the active Cu sites made it easier to withdraw electrons and promote PMS oxidation. Theoretical calculations and experimental results were combined to suggest a mechanism for pollution abatement with CuNW networks. The results showed that system efficacy for the degradation of a wide array of nitrogenous pollutants was robust across a broad range of solution pH and complex aqueous matrices. The flow-through operation of the CuNW filter outperformed conventional batch electrochemistry due to convection-enhanced mass transport. This study provides a new strategy for environmental remediation by integrating state-of-the-art material science, advanced oxidation processes, and microfiltration technology.

Fluidic MXene Electrode Functionalized with Iron Single Atoms for Selective Electrocatalytic Nitrate Transformation to Ammonia.

The growth of renewable energy industries and the ongoing need for fertilizer in agriculture have created a need for sustainable production of ammonia (NH3) using low-cost, environment-friendly techniques. The electrocatalytic nitrate (NO3-) reduction reaction (NO3RR) has the potential to improve both the management of environmental nitrogen and the recycling of synthetic nutrients. However, NO3RR is frequently hindered by the incomplete NO3- conversion, sluggish reaction kinetics, and suppression of the hydrogen evolution reaction (HER). Inspired by specific local electronic structures that are adjustable for single-atom catalysts, this work presents a nanohybrid electrocatalytic filter with iron single atoms (FeSA) immobilized on MXene. The fabricated FeSA/MXene filter exhibited maximum NH3 Faradaic efficiency and selectivity (82.9 and 99.2%, respectively) that were higher than those for filters made of Fe nanoparticles anchored on MXene (FeNP/MXene) (69.2 and 81.3%, respectively) and MXene alone (32.8 and 52.4%, respectively), measured at an initial pH of 7 and an applied potential of -1.4 V vs Ag/AgCl. Density functional theory calculations revealed that, compared to the FeNP/MXene filter, the FeSA/MXene filter prevented the competition from the HER and reduced the activation energy of the potential-limiting step (*NO to *NHO) that made the NH3 synthesis thermodynamically favorable . This work highlights an alternative strategy for achieving a synergistic NO3- removal and nutrient recovery with durable catalytic activity and stability.

Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification.

In this study, a machine learning (ML) framework is developed toward target-oriented inverse design of the electrochemical oxidation (EO) process for water purification. The XGBoost model exhibited the best performances for prediction of reaction rate (k) based on training the data set relevant to pollutant characteristics and reaction conditions, indicated by Rext2 of 0.84 and RMSEext of 0.79. Based on 315 data points collected from the literature, the current density, pollutant concentration, and gap energy (Egap) were identified to be the most impactful parameters available for the inverse design of the EO process. In particular, adding reaction conditions as model input features allowed provision of more available information and an increase in the sample size of the data set to improve the model accuracy. The feature importance analysis was performed for revealing the data pattern and feature interpretation by using Shapley additive explanations (SHAP). The ML-based inverse design for the EO process was generalized to a random case for tailoring the optimum conditions with phenol and 2,4-dichlorophenol (2,4-DCP) serving as model pollutants. The resulting predicted k values were close to the experimental k values by experimental verification, accounting for the relative error lower than 5%. This study provides a paradigm shift from conventional trial-and-error mode to data-driven mode for advancing research and development of the EO process by a time-saving, labor-effective, and environmentally friendly target-oriented strategy, which makes electrochemical water purification more efficient, more economic, and more sustainable in the context of global carbon peaking and carbon neutrality.

Distribution and transmission of ß-lactamase resistance genes in meal-to-milk chain on dairy farm.

Antibiotics have been widely used in animal husbandry, which leads to high risk of food-borne transfer of antibiotic resistance genes (ARGs). The present study investigated the distribution of ß-lactamase resistance genes (ß-RGs) on dairy farm in the Songnen Plain of western Heilongjiang Province, China, to provide mechanistic insights into food-borne transmission of ß-RGs through "meal-to-milk" chain under practically relevant circumstances. The results demonstrated that the abundance of ß-RGs (91%) was much higher than that of other ARGs in the livestock farms. The blaTEM exhibited the content as high as 94.55% among all ARGs, and higher than 98% blaTEM was detected in meal, water and milk sample. The metagenomic taxonomy analysis indicated that the blaTEM should be carried by tnpA-04 (7.04%) and tnpA-03 (1.48%) hosted in Pseudomonas genus (15.36%) and Pantoea (29.02%) genus. Both tnpA-04 and tnpA-03 in the milk sample were identified to be the key mobile genetic elements (MGEs) responsible for transferring blaTEM along the "meal-manure-soil-surface water-milk" chain. The ARGs transfer across ecological boundaries underscored the need to evaluate potential dissemination of high-risk Proteobacteria and Bacteroidetes carried by humans and animals. They were capable of producing expanded-spectrum ß-lactamases (ESBLs) and destroying commonly used antibiotics, leading to possible risk of food-borne horizontal transmission of ARGs. This study not only has important environmental implications for identifying the pathway for ARGs transfer, but also highlights the demand for appropriate policy toward safe regulation of dairy farm and husbandry products.

Deciphering the fate of osmotic stress priming on enhanced microorganism acclimation for purified terephthalic acid wastewater treatment with high salinity and organic load.

Osmotic stress priming (OSP) was an effective management strategy for improving microbial acclimation to salt stress. In this study, the interaction between pollutants and microbiota, and microbial osmoregulation were investigated triggered by OSP (alternately increasing salinity and organic loading). Results showed that OSP significantly improved COD removal from 31.53 % to 67.99 % and mitigated the terephthalate inhibition produced by toluate, decreasing from 1908.08 mg/L to 837.16 mg/L compared with direct priming. Due to an increase in salinity, Pelotomaculum and Mesotoga were enriched to facilitate terephthalate degradation and syntrophic acetate oxidation (SAO). And organic load promoted acetate formation through syntrophic metabolism of Syntrophorhabdus/Pelotomaculum and SAO-dependent hydrogenotrophic methanogenesis. K+ absorbing, proline and trehalose synthesis participated in osmoregulation at 0.5 % salinity, while only ectoine alleviated intracellular osmolarity under 1.0 % salinity with OLR of 0.44 kg COD /m3. This study provided in-depth insight for microbial acclimation process of anaerobic priming of saline wastewater.

Highly-dispersed NiFe alloys in-situ anchored on outer surface of Co, N co­doped carbon nanotubes with enhanced stability for oxygen electrocatalysis.

Transition metal alloys have emerged as promising catalysts for oxygen reduction/evolution reactions (ORR/OER) because of their intermetallic synergy and tunable redox properties. However, for alloy nanoparticles, it is quite challenging to suppress the self-aggregation and promote the bifunctional activity. Anchoring alloys in heteroatoms-doped carbon matrix with excellent electro-conductibility is a powerful strategy to form strongly-coupled alloy-carbon nanohybrids. Here, highly-dispersed NiFe alloys are evenly in-situ anchored on the surface of Co, N co-doped carbon nanotubes (NiFe/Co-N@CNTs) via a gravity-guided chemical vapor deposition and self-assembly strategy. Stably-structured NiFe/Co-N@CNTs possesses a tubular skeleton with diameters of 80-100 nm and a hydrophilic surface. For ORR, half-wave potential of NiFe/Co-N@CNTs (0.87 V vs RHE) is higher than that of Pt/C (0.85 V). Strong synergies between NiFe alloys and Co-Nx species facilitate the charge transfer on one-dimensional conductive structure to boost the 4e- ORR kinetics. For OER, NiFe/Co-N@CNTs has a lower overpotential (300 mV) than RuO2 (400 mV) at 10 mA cm-2 due to in-situ formation of highly-active NiOOH/FeOOH species (as indicated by in-situ X-ray diffraction) at the catalytic sites on NiFe alloy. Rechargeable Zn-air battery (ZAB) with NiFe/Co-N@CNTs-based air-cathode exhibits promising open-circuit potential (1.52 V) and charge-discharge cycling stability (350 h). This alloy-carbon integrating strategy is meaningful for promoting dispersion, activity and stability of non-noble metal alloys for oxygen electrocatalysis.

Prospective Life Cycle Assessment for the Electrochemical Oxidation Wastewater Treatment Process: From Laboratory to Industrial Scale.

Electrochemical oxidation (EO) is a promising technology for water purification, but indirect environmental burdens may arise in association with consumption of materials and energy during electrode preparation and process operation. This study evaluated the life cycle environmental impacts of emerging EO technology from laboratory scale to industrial scale using prospective life cycle assessment (LCA) on a quantitative basis. Environmental impacts of EO technology were assessed at laboratory scale by comparing three representative anode materials (SnO2, PbO2, and boron-doped diamond) and other two typical processes (adsorption and Fenton method), which verified the competitiveness of the EO process and identified the key factors to environmental hotspots. Thereafter, LCA of scale-up EO was performed to offer guidance for practical application, and the life cycle inventory was compiled upon thermodynamic and kinetic simulations, empirical calculation rules, and similar technical information. Results demonstrated EO to be effective for destructing recalcitrant organic pollutants, but visible direct benefits might be outweighed by increased indirect environmental burdens associated with the preparation of anode materials, use of electrolytes, and energy consumption during the operation stage at both laboratory scale and larger scale. This necessitated attention to overall life cycle profiles by taking into account reactor design, anode materials, electrolyte and flow pattern, and decentralized location with a large share of renewable power station and rigorous contamination control strategies for wastewater treatment plants.

Enhanced visible light photo-Fenton catalysis by lanthanum-doping BiFeO3 for norfloxacin degradation.

Efficient photo-Fenton removal of antibiotic effluent is a widely followed and significant attempt to deal with the growing environmental pollution. In this study, BiFeO3 and lanthanum doped BiFeO3 catalysts were synthesized via one-step hydrothermal method as hydrogen peroxide activator for mineralization of norfloxacin (NOR). Various characterization measurements were used to verify La was successfully doped into the lattice of perovskite and investigated the effect of La doping molar ratio on BiFeO3 through the characterization of the morphology and physicochemical properties. The degradation experiment and reaction rate constants showed that the La-doped BiFeO3 particle exhibited superior photo-Fenton catalytic performance to undoped BiFeO3. Especially, the degradation efficiency of 15% La-doped BiFeO3 could reach up to 84.94%. And the first order kinetic constant of optimized conditions was 0.01638 min-1, which was about 6.9 times than that of undoped BiFeO3.The influence of pH, oxidizer content and catalyst dosage in photo-Fenton reaction were investigated detailedly. Besides, the synthetic catalyst possessed favorable stability and reusability with little metal leaching after many cycles of use. Radical scavenger experiments and electron spin resonance tests were carried out to conclude that the ·OH and holes were regarded as the dominate active species in the catalytic process. The narrow band gap and excellent electron transfer efficiency were the key factors for La-doped BiFeO3 to have high catalytic efficiency in the photo-Fenton system. Current works demonstrated the great promise of La-doped BiFeO3 in the elimination of antibiotic organics.

Improved Machine Learning Models by Data Processing for Predicting Life-Cycle Environmental Impacts of Chemicals.

Machine learning (ML) provides an efficient manner for rapid prediction of the life-cycle environmental impacts of chemicals, but challenges remain due to low prediction accuracy and poor interpretability of the models. To address these issues, we focused on data processing by using a mutual information-permutation importance (MI-PI) feature selection method to filter out irrelevant molecular descriptors from the input data, which improved the model interpretability by preserving the physicochemical meanings of original molecular descriptors without generation of new variables. We also applied a weighted Euclidean distance method to mine the data most relevant to the predicted targets by quantifying the contribution of each feature, thereby the prediction accuracy was improved. On the basis of above data processing, we developed artificial neural network (ANN) models for predicting the life-cycle environmental impacts of chemicals with R2 values of 0.81, 0.81, 0.84, 0.75, 0.73, and 0.86 for global warming, human health, metal depletion, freshwater ecotoxicity, particulate matter formation, and terrestrial acidification, respectively. The ML models were interpreted using the Shapley additive explanation method by quantifying the contribution of each input molecular descriptor to environmental impact categories. This work suggests that the combination of feature selection by MI-PI and source data selection based on weighted Euclidean distance has a promising potential to improve the accuracy and interpretability of the models for predicting the life-cycle environmental impacts of chemicals.