A new attempt to remove toluene using nickel-iron bimetallic particle electrode reactor.

A new attempt of removing toluene waste gas using a three-dimensional electrode reaction device with nickel-iron bimetallic particle electrode is presented in this paper. The particle electrode was prepared by a simple liquid phase reduction method. Through bimetal modification, the particle electrode mass transfer rate is increased to 1.29 times, and the degradation efficiency of the reactor is increased by nearly 40%, which makes it possible to remove toluene waste gas by other electrochemical methods in addition to plasma method. The removal efficiency of the particle electrode can be stabilized at more than 80% after 5 cycles (50 h). At the same time, the relationship between independent working parameters and dependent variables is analyzed using the central composite design, and the operating parameters are optimized. Based on this study, the removal mechanism and possible degradation pathway of toluene were investigated. This study provides a supplement to the possibility and theoretical basis of new technology application for electrocatalytic oxidation removal of VOCs.

Pollutant removal in an experimental bioretention cell situated in a northern Chinese sponge city.

To assess the viability and effectiveness of bioretention cell in enhancing rainwater resource utilization within sponge cities, this study employs field monitoring, laboratory testing, and statistical analysis to evaluate the water purification capabilities of bioretention cell. Findings indicate a marked purification impact on surface runoff, with removal efficiencies of 59.81% for suspended solids (SS), 39.01% for chemical oxygen demand (COD), 37.53% for ammonia nitrogen (NH3-N), and 30.49% for total phosphorus (TP). The treated water largely complies with rainwater reuse guidelines and tertiary sewage discharge standards. Notably, while previous research in China has emphasized water volume control in sponge city infrastructures, less attention has been given to the qualitative aspects and field-based evaluations. This research not only fills that gap but also offers valuable insights and practical implications for bioretention cell integration into sponge city development. Moreover, the methodology and outcomes of this study serve as a benchmark for future sponge city project assessments, offering guidance to relevant authorities.

Bidirectional machine learning-assisted sensitivity-based stochastic searching approach for groundwater DNAPL source characterization.

In this study, we designed a machine learning-based parallel global searching method using the Bayesian inversion framework for efficient identification of dense non-aqueous phase liquid (DNAPL) source characteristics and contaminant transport parameters in groundwater. Swarm intelligence organized hybrid-kernel extreme learning machine (SIO-HKELM) was proposed to approximate the forward and inverse input-output correlation with a high accuracy using the DNAPL transport numerical simulation model. An adaptive inverse-HKELM was established for preliminary estimation of the source characteristics and contaminant transport parameters to correct prior information and generate high-quality initial starting points of parallel searching. A local accurate forward-HKELM surrogate of the numerical model was embedded in the searching system for avoiding repetitive CPU-demanding likelihood evaluations. A sensitivity-based Metropolis criterion (MC), incorporating the dynamic particle swarm optimization (SD-PSO) algorithm, was developed for improving the search ergodicity and realizing precise inversion of all the unknown variables with drastic variations in sensitivity to the likelihood function. Results showed that the generalization capability and robustness of SIO-HKELM were superior to those of the traditional machine learning methods, including KELM and support vector regression (SVR), and it sufficiently approximated the forward and inverse input-output mapping of the numerical model with testing determination coefficients of 0.9944 and 0.6440, respectively. With high-quality prior information and initial starting points generated by the adaptive inverse-HKELM feed approach, the uncertainty in the inversion outputs was reduced, and the searching process rapidly converged to reasonable posterior distributions in around 60 iterations. Compared with the widely used multichain Markov chain Monte Carlo (MCMC) approach, the parallel searching lines generated by SD-PSO-MC adequately covered the searching space, and the "equifinality" effect was more effectively restrained by reducing the relative errors of all the point estimations to less than 8%. Therefore, the real source information reflected by the statistical characteristics of the SD-PSO-MC inversion outputs was more precise than that obtained using the multichain MCMC approach.

Spectroscopic studies of the role of dissolved organic matter in acenaphthene photodegradation in liquid water and ice.

The effect of concentration and origin of dissolved organic matter (DOM) on acenaphthene (Ace) photodegradation in liquid water and ice was investigated, and the components in DOM which were involved in Ace photodegradation were identified. The DOM samples included Suwannee River fulvic acid (SRFA), Elliott soil humic acid (ESHA), and an effluent organic matter (EfOM) sample. Due to the production of hydroxyl radical (•OH) and triplet excited-state DOM (3DOM*) which react with Ace, DOM had promotion effects on Ace photodegradation. However, the promotion effects of DOM were prevailed over by their suppressing effect of DOM including screening light effect, intermediates reducing effect and RS quenching effect, and thus, the photodegradation rates of Ace decreased in the presence of the three DOM with concentrations of 0.5-7.5 mg C/L in liquid water and ice. ESHA had higher light absorption and thus had higher screening light effect on Ace photodegradation in liquid water than SRFA and EfOM. At each DOM concentration, ESHA exhibited higher promotion effect on Ace photodegradation than SRFA and EfOM, in liquid water and ice. The binding of Ace with DOM was indicated by decreases in fluorescence intensity of Ace when coexisted with DOM. However, the binding of Ace to DOM played an unimportant role in suppressing Ace photodegradation. The photodegradation behavior of fluorophores in Ace with DOM present in ice was not similar to that in liquid water. C-O, C═O, carboxyl groups O-H and aliphatic C-H functional groups in DOM were involved in the interaction of DOM with Ace. The presence of Ace seemed to have no influence on the photodegradation behavior of functional groups in DOM.

Recent progress of particle electrode materials in three-dimensional electrode reactor: synthesis strategy and electrocatalytic applications.

With the complete promotion of a green, low-carbon, safe, and efficient economic system as well as energy system, the promotion of clean governance technology in the field of environmental governance becomes increasingly vital. Because of its low energy consumption, great efficiency, and lack of secondary pollutants, three-dimensional (3D) electrode technology is acknowledged as an environmentally beneficial and sustainable way to managing clean surroundings. The particle electrode is an essential feature of the 3D electrode reactor. This study provides an in-depth examination of the most current advancements in 3D electrode technology. The significance of 3D electrode technology is emphasized, with an emphasis on its use in a variety of sectors. Furthermore, the particle electrode synthesis approach and mechanism are summarized, providing vital insights into the actual implementation of this technology. Furthermore, by a metrological examination of the research literature in this sector, the paper expounds on the potential and obstacles in the development and popularization of future technology.

The improved resistance of germinated spores to ultraviolet irradiation: Comparison with chlorine.

Fungi outbreaks in water will include a series of processes, including spore aggregation, germination, biofilm, and finally present in a mixed state in the aquatic environment. More attention is paid to the control of dispersed fungal spores, however, there was little knowledge of the control of germinated spores. This study investigated the inactivation kinetics and mechanism of ultraviolet (UV) treatment for fungal spores with different germination percentages compared with dormant spores. The results indicated that the inactivation rate constants (k) of spores with 5%-45% germination were 0.0278-0.0299 cm2/mJ for Aspergillus niger and 0.0588-0.0647 cm2/mJ for Penicillium polonicum, which were lower than those of dormant spores. It suggested that germinated spores were more tolerant to UV irradiation than dormant spores, and it may be due to the defensive barrier (upregulated pigments) and some reductive substance (upregulated enoyl reductase) by absorbing UV or reacting with reactive oxygen species according to transcriptome analysis. Compared to dormant spores, the k-UV of germinated spores decreased by 18.17%-26.56% for Aspergillus niger, which was less than k-chlorine (62.33%-69.74%). A slighter decrease in k-UV showed UV irradiation can efficiently control fungi contamination, especially when dormant spores and germinated spores coexisted in actual water systems. This study indicates that more attention should be paid to germinated spores.

Effect of dissolved organic matter on sulfachloropyridazine photolysis in liquid water and ice.

Dissolved organic matter (DOM) is an ubiquitous component of environmental snow and ice, which can absorb light and produce reactive species (RS) and thus is of importance in ice photochemistry. The photodegradation of sulfachloropyridazine (SCP) without and with DOM present in liquid water and ice were investigated in this study. The photodegradation rate constants for SCP without DOM present was enhanced by 52.5 % in ice relative to liquid water, likely due to the enhanced role of SCP self-sensitized RS in ice. DOM significantly promoted SCP photolysis in both liquid water and ice, which was mainly attributed to roles of singlet oxygen (1O2) and triplet excited-state DOM (3DOM*) generated from DOM. 1O2 production from DOM was significantly enhanced in ice relative to liquid water. Hydroxyl radical (•OH) production from DOM in ice was similar to those in liquid water. Enhancement in 3DOM* production in ice was observed at low DOM concentrations. Suwannee River Fulvic Acid (SRFA) and Elliott Soil Humic Acid (ESHA) exhibited differences in RS production in liquid water and ice, as well as in enhancement of 1O2 and 3DOM* produced in ice relative to liquid water. DOM induced reaction pathways of SCP different from those without DOM present, and therefore affected toxicity of SCP photoproducts. There were differences in photodegradation pathways of SCP as well as in toxicity of SCP photoproducts between liquid water and ice.

How to promote the sustainable development of virtual reality technology for training in construction filed: A tripartite evolutionary game analysis.

In recent years, virtual reality training technology (VRTT) has been considered by many scholars as a new training method instead of traditional training (TT) to reduce unsafe behaviors ascribed to construction workers (CWs) and corporate accident rates. However, in this process, a conflict of interest arises among the government, construction enterprises (CEs), and CWs. Therefore, this study introduces a quantitative research method, the three-party evolutionary game and creatively combining them with the product life cycle (PLC) to solve this problem by analyzing the equilibrium and evolutionarily stable strategies of the system. Finally, collaborative players' decision-making behaviors and their sensitivity to critical factors are examined. This paper will illustrate these in each stage through numerical simulations. The results of the study indicate that the government plays a dominant role in the VRTT introduction stage. When the government gives CEs appropriate subsidies, CEs will eventually realize the importance of VRTT for CWs. Then the government will gradually reduce the amount of the subsidies in this process. In addition, we also find that the continually high cost will lead to negative policies by the government, which requires the active cooperation and attitude change from CEs and CWs. Ultimately, the government, CEs and CWs adopt the best strategy in the evolutionary process to facilitate the promotion, application and sustainability of VRTT in the construction industry.

Attention-Driven Memory Network for Online Visual Tracking.

A memory mechanism has attracted growing popularity in tracking tasks due to the ability of learning long-term-dependent information. However, it is very challenging for existing memory modules to provide the intrinsic attribute information of the target to the tracker in complex scenes. In this article, by considering the biological visual memory mechanisms, we propose the novel online tracking method via an attention-driven memory network, which can mine discriminative memory information and enhance the robustness and reliability of the tracker. First, to reinforce effectiveness of memory content, we design a novel attention-driven memory network. In the network, the long memory module gains property-level memory information by focusing on the state of the target at both the channel and spatial levels. Meanwhile, in reciprocity, we add a short-term memory module to maintain good adaptability when confronting drastic deformation of the target. The attention-driven memory network can adaptively adjust the contribution of short-term and long-term memories to tracking results under the weighted gradient harmonized loss. On this basis, to avoid model performance degradation, an online memory updater (MU) is further proposed. It is designed to mining for target information in tracking results through the Mixer layer and the online head network together. By evaluating the confidence of the tracking results, the memory updater can accurately judge the time of updating the model, which guarantees the effectiveness of online memory updates. Finally, the proposed method performs favorably and has been extensively validated on several benchmark datasets, including object tracking benchmark-50/100 (OTB-50/100), temple color-128 (TC-128), unmanned aerial vehicles-123 (UAV-123), generic object tracking -10k (GOT-10k), visual object tracking-2016 (VOT-2016), and VOT-2018 against several advanced methods.

Degradation of ciprofloxacin by persulfate activated by Fe(III)-doped BiOCl composite photocatalyst.

Fe-BOC-X photocatalyst was successfully prepared by solvothermal method. The photocatalytic activity of Fe-BOC-X was determined by ciprofloxacin (CIP), a typical fluoroquinolone antibiotic. Under sunlight irradiation, all Fe-BOC-X showed better CIP removal performance than original BiOCl. In comparison, the photocatalyst with iron content of 50 wt% (Fe-BOC-3) has excellent structural stability and the best adsorption photodegradation efficiency. The removal rate of CIP (10 mg/L) by Fe-BOC-3 (0.6 g/L) reached 81.4% within 90 min. At the same time, the effects of photocatalyst dosage, pH, persulfate, persulfate concentration, and combinations of different systems (PS, Fe-BOC-3, Vis/PS, Vis/Fe-BOC-3, Fe-BOC-3/PS, and Vis/Fe-BOC-3/PS) on the reaction were systematically discussed. In reactive species trapping experiments, electron spin resonance (ESR) signals revealed that the photogenerated holes (h+), hydroxyl radical (•OH), sulfate radical (•SO4-), and superoxide radical (•O2-) played an important role in CIP degradation; hydroxyl radicals (•OH) and sulfate radicals (•SO4-) play a major role. Various characterization methods have demonstrated that Fe-BOC-X has larger specific surface area and pore volume than original BiOCl. UV-vis DRS indicate that Fe-BOC-X has wider visible light absorption and faster photocarrier transfer and provides abundant surface oxygen absorption sites for effective molecular oxygen activation. Accordingly, a large number of active species were produced and participated in the photocatalytic process, thus effectively promoting the degradation of ciprofloxacin. Based on HPLC-MS analysis, two possible decomposition pathways of CIP were finally proposed. The main degradation pathways of CIP are mainly due to the high electron density of piperazine ring in CIP molecule, which is mainly attacked by various free radicals. The main reactions include piperazine ring opening, decarbonylation, decarboxylation, and fluorine substitution. This study can better open up a new way for the design of visible light driven photocatalyst and provide more ideas for the removal of CIP in water environment.

Progress in Research and Application of Metal-Organic Gels: A Review.

In recent years, metal-organic gels (MOGs) have attracted much attention due to their hierarchical porous structure, large specific surface area, and good surface modifiability. Compared with MOFs, the synthesis conditions of MOGs are gentler and more stable. At present, MOGs are widely used in the fields of catalysis, adsorption, energy storage, electrochromic devices, sensing, analysis, and detection. In this paper, literature metrology and knowledge graph visualization analysis are adopted to analyze and summarize the literature data in the field of MOGs. The visualization maps of the temporal distribution, spatial distribution, authors and institutions' distribution, influence of highly cited literature and journals, keyword clustering, and research trends are helpful to clearly grasp the content and development trend of MOG materials research, point out the future research direction for scholars, and promote the practical application of MOGs. At the same time, the paper reviews the research and application progress of MOGs in recent years by combining keyword clustering, time lines, and emergence maps, and looks forward to their challenges, future development trend, and application prospects.

Enhanced degradation of emerging contaminants by percarbonate/Fe(II)-ZVI process: case study with nizatidine.

Pharmaceuticals have recently emerged as a significant environmental concern due to the growth of population, expansion of industry, and the shift in modern lifestyles. Herein, we present a Fe(II)/percarbonate (SPC) process with dramatically enhanced efficiency by the introduction of zerovalent iron (ZVI). After the addition of ZVI, the removal rate of nizatidine (NZTD) went up from 71.7 to 84.2%. The removal rate of NZTD decreases with rising pH and speeds up with increasing temperature. It was found that under the condition of pH = 7 and T = 25 °C, the molar ratio of the optimal concentration of NZTD degradation in the system was [NZTD]0:[SPC]0:[Fe(II)]0:[ZVI]0 = 1:8:24:16, with a degradation rate of 99.8%. At the same time, target pollutants can also be successfully eliminated from actual water bodies. Moreover, we test for toxicity using luminescent bacteria, and the results demonstrate that the system is capable of effectively decreasing the toxicity of NZTD. The research findings can contribute to the clarification of the migration and transformation law of NZTD in the oxidation process, thereby providing a scientific basis and technical support for the removal of NZTD in the tertiary water treatment for a water source.

Research status of volatile organic compound (VOC) removal technology and prospect of new strategies: a review.

As an important component of air pollution, the efficient removal of volatile organic compounds (VOCs) is one of the most important challenges in the world. VOCs are harmful to the environment and human health. This review systematically introduced the main VOC control technologies and research hotspots in recent years, and expanded the description of electrocatalytic oxidation technology and bimetallic catalytic removal technology. Based on a three-dimensional electrode reactor, the theoretical design of a VOC removal control technology using bimetallic three-dimensional particle electrode electrocatalytic oxidation was proposed for the first time. The future research focus of this method was analyzed, and the importance of in-depth exploration of the catalytic performance of particle electrodes and the system reaction mechanism was emphasized. This review provides a new idea for using clean and efficient methods to remove VOCs.

Degradation of ciprofloxacin by a constitutive g-C3N4/BiOCl heterojunction under a persulfate system.

Ciprofloxacin (CIP) is a third-generation quinolone antimicrobial with broad-spectrum antimicrobial activity, and is not fully metabolized in the human body, resulting in more than 70% of CIP being excreted into water as a prodrug. In this study, g-C3N4/BiOCl heterojunction structure composites were prepared to study the degradation effect of ciprofloxacin (CIP) under photocatalytic conditions. The results showed that CIP at 10 mg L-1 was best degraded after 90 min at 0.3 g L-1 g-C3N4/BiOCl-2, pH of 5.8 and PS dosing of 1 mM. The quenching experiments and electron spin resonance spectroscopy (ESR) confirmed that ˙OH, ˙SO4 - and h+ played a major role. After the photocatalytic degradation of this reaction system, the biological toxicity of CIP was effectively controlled. This material is stable and the CIP removal rate remained above 80% after four cycles of experiments.

Synergistic and efficient degradation of acid red 73 by UV/O3/PDS: Kinetic studies, free radical contributions and degradation pathways.

Acid red 73 (AR73) is a representative dye pollutant that poses a threat to the environment and human health. Effectively removing this type of pollutant by conventional processes is difficult. However, this study found that compared with UV/PDS, UV/O3, and PDS/O3, UV/O3/PDS composite system had the highest degradation effect on AR73. The degradation efficiency in the composite system reached 97.61% within 30 min, and the synergistic coefficients in the composite system were all greater than 1. In the UV/O3/PDS system, ·OH was the main free radical that mainly degrades AR73. The increase of PDS dosage promoted the degradation of AR73, but the increase of O3 dosage was difficult to greatly improve the degradation of AR73 effect. The kinetic model of the apparent reaction rate was determined. The UV/O3/PDS system can efficiently degrade AR73 in a wide range of substrate concentrations and pH levels, and at the same time showed good adaptability to various concentrations of anions (Cl-, CO32-, SO32-, and C2O42-). Under raw water quality, the degradation effect of AR73 was still as high as approximately 90%. The theoretical attack site was obtained by DFT calculation, and the possible degradation pathway of AR73 was proposed based on the GC-MS spectrum and UV-Vis absorption spectrum. The attack of -NN- by ·OH, SO4-, and O3 was proposed to be the main possible degradation pathway for AR73. Therefore, this study further improves the understanding of the UV/O3/PDS system and shows the potential applicability of this system in the treatment of dye wastewater.

The obesity paradox in ST-segment elevation myocardial infarction patients: A meta-analysis.

OBJECTIVE: The aim of this study was to investigate whether there was a difference in survival after initial percutaneous coronary intervention (PCI) among ST-segment elevation myocardial infarction (STEMI) patients with different body mass index (BMI). METHODS: Literature retrieval was conducted on PubMed, Web of Science, Embase, CNKI, and Wanfang databases to obtain the published studies on the survival of STEMI patients with different BMI after initial PCI from the establishment of the database to 2022. All statistical analyses were performed using STATA16.0. RESULTS: Two hundred thirty-nine studies were retrieved, and 12 studies were eventually included. Meta-analysis showed that overweight patients [OR = 0.66, 95% CI (0.58, 0.76), p < .001] and obese patients [OR = 0.60, 95% CI (0.51, 0.72), p < .001] had lower in-hospital mortality than healthy-weight patients. Overweight patients [OR = 0.66, 95% CI (0.58, 0.74), p < .001] and obese patients [OR = 0.62, 95% CI (0.53, 0.72), p < .001] had lower short-term mortality than healthy-weight patients. In addition, overweight patients [OR = 0.63, 95% CI (0.58, 0.69), p < .001] and obese patients [OR = 0.59, 95% CI (0.52, 0.66), p < .001] also had lower long-term mortality than healthy-weight patients. There was no significant difference in in-hospital mortality [OR = 1.06, 95% CI (0.89, 1.27), p > .05], short-term mortality [OR = 1.04, 95% CI (0.89, 1.22), p > .05], and long-term mortality [OR = 1.07, 95% CI (0.95, 1.20), p > .05] between overweight and obese patients. CONCLUSION: This meta-analysis confirmed an obesity paradox in STEMI patients following PCI. The obesity paradox exists in in-hospital, short-term, and long-term conditions.

Mechanism and efficiency of photocatalytic triclosan degradation by TiO2/BiFeO3 nanomaterials.

Hierarchical porous TiO2 photocatalytic nanomaterials were fabricated by impregnation and calcination using a peanut shell biotemplate, and TiO2/BiFeO3 composite nanomaterials with different doping amounts were fabricated using hydrothermal synthesis. The micromorphology, structure, element composition and valence state of the photocatalyst were analyzed using a series of characterization methods, including X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), BET surface area (BET), X-ray photoelectron spectroscopy (XPS), UV-visible diffuse reflectance (UV-vis), fluorescence spectroscopy (PL) and other technological means. Finally, the degradation mechanism and efficiency of BiFeO3 composite photocatalyst on the target pollutant triclosan were analyzed using a xenon lamp to simulate sunlight. The results showed that TiO2/BiFeO3 catalyst fabricated using a peanut shell biotemplate has a specific surface area of 153.64 m2/g, a band gap of 1.92 eV, and forms heterostructures. The optimum doping amount of TiO2/BiFeO3 catalyst was 1 mol/mol, and the degradation rate was 81.2%. The main active substances degraded were ·O2-and ·OH. The degradation process measured is consistent with the pseudo-first-order kinetic model.

Chronic non-communicable diseases: Hainan prospective cohort study.

PURPOSE: The Hainan Cohort was established to investigate the incidence, morbidity and mortality of non-communicable diseases and their risk factors in the community population. PARTICIPANTS: The baseline investigation of the Hainan Cohort study was initiated in five main areas of Hainan, China, from June 2018 to October 2020. A multistage cluster random-sampling method was used to obtain samples from the general population. Baseline assessments included a questionnaire survey, physical examination, blood and urine sample collection, and laboratory measurements, and outdoor environmental data were obtained. FINDINGS TO DATA: A total of 14 443 participants aged 35-74 years were recruited at baseline, with a participation rate of 90.1%. The mean age of the participants was 48.8 years; 51.8% were men, and 83.7% had a secondary school or higher education. The crude prevalence of diabetes, coronary heart disease, stroke, hypertension, hyperuricaemia, chronic bronchitis, pulmonary tuberculosis, asthma, cancer, chronic hepatitis and metabolic syndrome were 8.6%, 9.2%, 2.0%, 37.1%, 7.1%, 2.3%, 1.4%, 2.1%, 4.1%, 2.2% and 14.5%, respectively. FUTURE PLANS: The Hainan Cohort is a dynamic cohort with no end date. All participants will be monitored annually for cause-specific mortality and morbidity until death. Long-term follow-up will be conducted every 5 years. The baseline population is considered to expand in the next wave of follow-up, depending on the availability of funding support.

Personalized Deep Bi-LSTM RNN Based Model for Pain Intensity Classification Using EDA Signal.

Automatic pain intensity assessment from physiological signals has become an appealing approach, but it remains a largely unexplored research topic. Most studies have used machine learning approaches built on carefully designed features based on the domain knowledge available in the literature on the time series of physiological signals. However, a deep learning framework can automate the feature engineering step, enabling the model to directly deal with the raw input signals for real-time pain monitoring. We investigated a personalized Bidirectional Long short-term memory Recurrent Neural Networks (BiLSTM RNN), and an ensemble of BiLSTM RNN and Extreme Gradient Boosting Decision Trees (XGB) for four-category pain intensity classification. We recorded Electrodermal Activity (EDA) signals from 29 subjects during the cold pressor test. We decomposed EDA signals into tonic and phasic components and augmented them to original signals. The BiLSTM-XGB model outperformed the BiLSTM classification performance and achieved an average F1-score of 0.81 and an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.93 over four pain states: no pain, low pain, medium pain, and high pain. We also explored a concatenation of the deep-learning feature representations and a set of fourteen knowledge-based features extracted from EDA signals. The XGB model trained on this fused feature set showed better performance than when it was trained on component feature sets individually. This study showed that deep learning could let us go beyond expert knowledge and benefit from the generated deep representations of physiological signals for pain assessment.