Conjugated Porous Organic Polymers Featuring Both Soft-Hard Combined Coordination Sites and Photoelectrochemical Properties for Palladium Capture and Subsequent Photocatalysis.

Palladium (Pd) capture from high-level liquid waste for subsequent photocatalytic applications is desirable for the development of nuclear energy and the reutilization of valuable resources. Herein, we approach our design with a unique porous organic polymer containing thiazolo[5,4-d]thiazole units (denoted as TzPOP-OH). It possesses two potential soft-hard (N-O and S-O) combined coordination sites for Pd(II) coordination and features strong donor-acceptor repeating units and high planarity of linkage enforced by hydrogen bonds for subsequent photocatalysis. Accordingly, TzPOP-OH with three hydroxyl groups on the linkage exhibits a high Pd(II) capacity of 369 mg g-1 at 3 M HNO3, considerably surpassing those of the controlled polymer TzPOP without hydroxyl groups and most other reported materials. Additionally, TzPOP-OH boasts other merits, including outstanding acid tolerance, extraordinary radiation stability, good reusability, and remarkable selectivity. After palladium adsorption, Pd@TzPOP-OH demonstrates impressive photodegradation efficiency to reduce the concentration of rhodamine B in contaminated urban water from 10 to less than 0.1 ppm. This work provides a feasible approach to designing materials with both suitable coordination microenvironments and semiconductor properties for metal separation and photocatalysis.

Micropollutant rejection by nanofiltration membranes: A mini review dedicated to the critical factors and modelling prediction.

Nanofiltration (NF) membranes, extensively used in advanced wastewater treatment, have broad application prospects for the removal of emerging trace organic micropollutants (MPs). The treatment performance is affected by several factors, such as the properties of NF membranes, characteristics of target MPs, and operating conditions of the NF system concerning MP rejection. However, quantitative studies on different contributors in this context are limited. To fill the knowledge gap, this study aims to assess critical impact factors controlling MP rejection and develop a feasible model for MP removal prediction. The mini-review firstly summarized membrane pore size, membrane zeta potential, and the normalized molecular size (λ = rs/rp), showeing better individual relationships with MP rejection by NF membranes. The Lindeman-Merenda-Gold model was used to quantitatively assess the relative importance of all summarized impact factors. The results showed that membrane pore size and operating pressure were the high impact factors with the highest relative contribution rates to MP rejection of 32.11% and 25.57%, respectively. Moderate impact factors included membrane zeta potential, solution pH, and molecular radius with relative contribution rates of 10.15%, 8.17%, and 7.83%, respectively. The remaining low impact factors, including MP charge, molecular weight, logKow, pKa and crossflow rate, comprised all the remaining contribution rates of 16.19% through the model calculation. Furthermore, based on the results and data availabilities from references, the machine learning-based random forest regression model was trained with a relatively low root mean squared error and mean absolute error of 12.22% and 6.92%, respectively. The developed model was then successfully applied to predict MPs' rejections by NF membranes. These findings provide valuable insights that can be applied in the future to optimize NF membrane designs, operation, and prediction in terms of removing micropollutants.

Synergistic effects of peracetic acid and free ammonia pretreatment on anaerobic fermentation of waste activated sludge to promote short-chain fatty acid production for polyhydroxyalkanoate biosynthesis: Mechanisms and optimization.

Peracetic acid (PAA) combined with free ammonia (FA) pretreatment can be utilized to promote anaerobic fermentation (AF) of waste activated sludge (WAS) to produce short-chain fatty acids (SCFAs), and the resulting SCFAs are desirable carbon sources (C-sources) for polyhydroxyalkanoate (PHA) biosynthesis. This work aimed to determine the optimum conditions for PAA + FA pretreatment of sludge AF and the feasibility of using anaerobic fermentation liquor (AFL) for PHA production. To reveal the mechanisms of integrated pretreatment, the impacts of PAA + FA pretreatment on different stages of sludge AF and changes in the microbial community structure were explored. The experimental results showed that the maximum SCFA yield reached 491.35 ± 6.02 mg COD/g VSS on day 5 after pretreatment with 0.1 g PAA/g VSS +70 mg FA/L, which was significantly greater than that resulting from PAA or FA pretreatment alone. The mechanism analysis showed that PAA + FA pretreatment promoted sludge solubilization but strongly inhibited methanogenesis. According to the analysis of the microbial community, PAA + FA pretreatment changed the microbial community structure and promoted the enrichment of bacteria related to hydrolysis and acidification, and Proteiniclasticum, Macellibacteroides and Petrimonas became the dominant hydrolytic and acidifying bacteria. Finally, after alkali treatment, the AFL was utilized for batch-mode PHA production, and a maximum PHA yield of 55.05 wt% was achieved after five operation periods.

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways.

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective.

The proliferation of unverified or false information by irresponsible users can significantly amplify the spread of misinformation or fake news. Despite growing research on unverified information sharing, a comprehensive understanding of the varying influences of different factors and strategies to mitigate this issue remains under investigation. To address this research gap, this study, rooted in the theory of herd behavior, develops, and tests a model theorizing the reasons behind social media users' unverified information sharing. Data was collected from 510 respondents across six regions of China using a convenience sampling method. The collected data was analyzed using Mplus. The results from this study indicated that perceived severity, state uncertainty, and herding have a significant positive influence on unverified information sharing. These results enrich the understanding of unverified information-sharing behavior among Chinese social media users. Drawing from these results, we suggest platform administrators and policymakers mitigate herd behavior tendencies and stem the spread of misinformation by disseminating timely, accurate, and authoritative information. Since this action will reduce users' perceptions of severity and uncertainty. Social media users are also advised to stay vigilant over the implications of herd behavior and foster a more critical attitude towards information sharing.

A new perspective on anthropogenic nitrogen loss mitigation strategies: Integrated control via sustainable regional integration.

Unregulated regional integrated development disrupts the reactive nitrogen (Nr) cycle, adding complexity to anthropogenic Nr environmental losses. The objective of this study was to establish a framework for mitigating anthropogenic Nr loss through a new regional integration perspective by analyzing anthropogenic Nr loss and integrated control strategies in the Yangtze River Delta (YRD) region from 2011 to 2020. The results revealed that the total Nr loss in the YRD ranged from 1780.7 to 1972.0 Gg N yr-1. Re-linking cropland and livestock is crucial for reducing Nr loss, as they act as the main sources of Nr loss. Spatial analysis at the regional scale revealed that regional integration has led to a dispersion of Nr loss, while uneven development among cities has resulted in a westward shift of 8.6 km in the Nr loss centroid, suggesting the need for the implementation of collaborative governance and integrated environmental regulation in the YRD. At the city scale, 27 cities were clustered into six types based on the similarity of Nr loss structural characteristics, allowing for the development of targeted reduction policies based on the specific Nr structural characteristics of each city. The results of driver and mitigation potential analysis indicated the feasibility of achieving the shared goal of sustainable regional integration and the application of optimal mitigation strategies in different cities and the YRD. Overall, the new-perspective framework established in this study provides valuable references for sustainable Nr management in the context of regional integration.

The microstrain-accompanied structural phase transition from h-MoO3 to α-MoO3 investigated by in situ X-ray diffraction.

In situ X-ray diffraction indicates that the structural phase transition from h-MoO3 to α-MoO3 is a first-order transition with a phase transition temperature range of 378.5-443.1 °C. The linear coefficients of thermal expansion of h-MoO3 are strongly anisotropic, that is, αa=b = 72.87 × 10-6 K-1 and αc = -19.44 × 10-6 K-1. In the h-MoO3 phase, water molecules are located at the (0 0 0.25) site inside the MoO6 octahedra tunnel that is formed by six MoO6 corner-sharing octahedron zigzag chains. With increasing temperature, the release of water molecules from the octahedra tunnel causes the octahedra chains to shrink and the octahedra tunnel to expand. When the phase transition occurs, the anomalous expansion of the MoO6 octahedra tunnel ruptures the Mo-O2 bonds, forming individual MoO6 octahedron zigzag chains that then share corners to generate octahedron layers in the ⟨100⟩α direction. The octahedron layers are bonded by van der Waals interactions in the ⟨010⟩α direction, crystalizing into the α-MoO3 structure.

Evaluating the anthropogenic nitrogen emissions to water using a hybrid approach in a city cluster: Insights into historical evolution, attribution, and mitigation potential.

Anthropogenic reactive nitrogen (Nr) emissions from agricultural production and food consumption in city clusters have caused water quality degradation and scarcity. In this study, anthropogenic Nr emissions to the water environment were quantitatively evaluated in the Yangtze River Delta city cluster from 2011 to 2020 using coupling nitrogen (N) flow analysis and the grey water footprint (GWF) method. The spatiotemporal characteristics of the GWF and the relative contributions of natural and human factors to the water pollution level (WPL) were analyzed. The results showed that from 2011 to 2020, the total N-related GWF decreased by 12.1 %, mainly driven by reduced fertilizer application and livestock numbers. In 2020, the primary pollution source changed from livestock to humans; however, non-point sources still dominated the GWF. The spatial clustering trend of the GWF was significant: high and low GWF were mainly concentrated in the northeast and southwest regions, respectively. From 2011 to 2020, the mean center of the GWF moved west due to the decrease and increase in the eastern and western regions, respectively, supporting the pollution haven hypothesis. The WPL ranged from 2.67 to 5.03 and fluctuated due to variations in precipitation. The relative contributions of natural and human factors to the WPL evolution were 72.9 % and 27.1 %, respectively. According to the scenario analysis, increasing the N use efficiency to 50 %, manure recycling rate to 80 %, and sewage treatment rate in urban and rural regions to 98 % and 40 %, respectively, could decrease GWF by 39.6 %. The present study establishes an open framework to evaluate anthropogenic N emissions to water, and the outcomes provide valuable references for sustainable N management in city clusters.

Sodium doping in brookite TiO2 enhances its photocatalytic activity.

We report in this work that sodium doping of brookite TiO2 effectively enhances its photocatalytic activity, which becomes three times higher than that of the quasi-spherical brookite TiO2. The results demonstrated that the sodium-doped brookite Na x Ti1- x O2 can be stable up to 500 °C. At 600°C, the sodium in the brookite precipitates in the form of Na2CO3, and above 700 °C, the brookite Na x Ti1- x O2 transforms into Na2Ti6O13 by a twinning process with the orientation relationship of [1-2-3]Matrix//[1-23]Twins and (-2-10)Matrix//(1-1-1)Twins. The differences in the ionic radius and the electronegativity between Na and Ti destroy the local atomic arrangement of the brookite structure and produce microstructures such as the core-shell structure, local lattice distortion, interstitial atoms, and atomic vacancies, which are critical to its excellent photocatalytic activity.

Formation mechanism of contributors' self-identity based on social identity in online knowledge communities.

Introduction: Contributors' self-identity is a critical element in the sustainable development of online knowledge communities (OKCs). However, research concerning the formation mechanism of contributors' self-identity remains scarce. This research posits information support, novel posting and sense of self-worth as mediating variables between social identity and self-identity to construct a path model, aiming to explore the way in which self-identity is formed on the basis of social identity in OKCs. Methods: To examine this mode, an online survey was administered to many different OKCs, and 515 usable questionnaire responses were collected. Structural equation modeling was then employed to examine the model. Results: The R2 value of self-identity was 0.627, thus indicating that the model was able to explain 62.7% of the variance in self-identity. We find that self-identity emerges through the mediating effects of information support, novel posting and sense of self-worth. In addition, social identity can elicit novel posting and information support, which are all beneficial for enhancing the dynamics of OKCs and further generate sense of self-worth. We also observe that although social identity and individualized behavior (novel posting) are generally incompatible, they can be compatible in the context of OKCs. Discussion: Self-identity as a contributor can be formed on the basis of social identity via the social path and the psychological path in OKCs, while the two paths for fostering self-identity are not independent of each other, and there is also a very strong link between behavioral and psychological mechanisms.

Nitrogen flow in the food production and consumption system within the Yangtze River Delta city cluster: Influences of cropland and urbanization.

Intensive anthropogenic activities associated with the food production and consumption system (FPC) drive massive reactive nitrogen inputs to city clusters resulting in serious nitrogen (N) pollution. We conducted a substance flow analysis to examine N flows in the FPC within the Yangtze River Delta city cluster from 2011 to 2019. The total N input and output showed parabolic downward trends, with decreases from 4008.27 to 3472.57 Gg N yr-1 and 3518.65 to 3061.29 Gg N yr-1, respectively; chemical fertilizer (54.7%-57.3%) and N loss (87.1%-90.9%) were the primary components of N input and output, respectively. The decreased total N input was related to reductions in chemical fertilizers and livestock numbers. However, a notable increase in N input to the human subsystem was observed, and urbanization was associated with increased N inputs within the human subsystem via higher amounts of food N consumed per capita and proportions of animal-based food N consumed. Total N loss initially increased then decreased; Nantong, Jiaxing, Shanghai, Yancheng, Taizhou, and Yangzhou were the top six cities in N loss intensity. The proportion of cultivated land area, livestock numbers per unit area, and population density were important factors influencing the spatial heterogeneity of N loss intensity. Twenty-six cities were divided into six groups based on their N loss composition, and various N management strategies were proposed. This study highlights the strong influences of cropland and urbanization on N flows within the FPC, which can be used as a reference for N management at a city cluster scale.

Cognitive behavior therapy for insomnia in cancer patients: a systematic review and network meta-analysis.

OBJECTIVE: The aim of this study was to examine the most effective delivery format of cognitive behavioral therapy for insomnia (CBT-I) on insomnia in cancer patients. METHODS: We searched five databases up to February 2021 for randomized clinical trials that compared CBT-I with inactive or active controls for insomnia in cancer patients. Outcomes were insomnia severity, sleep efficiency, sleep onset latency (SOL), wake after sleep onset (WASO), and total sleep time (TST). Pairwise meta-analyses and frequentist network meta-analyses with the random-effects model were applied for data analyses. RESULTS: Sixteen unique trials including 1523 participants met inclusion criteria. Compared with inactive control, CBT-I could significantly reduce insomnia severity (mean differences [MD] = -4.98 points, 95% confidence interval [CI]: -5.82 to -4.14), SOL (MD = -12.29 min, 95%CI: -16.48 to -8.09), and WASO (MD = -16.58 min, 95%CI: -22.00 to -11.15), while increasing sleep efficiency (MD = 7.62%, 95%CI: 5.82% to 9.41%) at postintervention. Compared with active control, CBT-I could significantly reduce insomnia severity (MD = -2.75 points, 95%CI: -4.28 to -1.21), SOL (MD = -13.56 min, 95%CI: -18.93 to -8.18), and WASO (MD = -6.99 min, 95%CI: -11.65 to -2.32) at postintervention. These effects diminished in short-term follow-up and almost disappeared in long-term follow-up. Most of the results were rated as "moderate" to "low" certainty of evidence. Network meta-analysis showed that group CBT-I had an increase in sleep efficiency of 10.61%, an increase in TST of 21.98 min, a reduction in SOL of 14.65 min, and a reduction in WASO of 24.30 min, compared with inactive control at postintervention, with effects sustained at short-term follow-up. CONCLUSIONS: CBT-I is effective for the management of insomnia in cancer patients postintervention, with diminished effects in short-term follow-up. Group CBT-I is the preferred choice based on postintervention and short-term effects. The low quality of evidence and limited sample size demonstrate the need for robust evidence from high-quality, large-scale trials providing long-term follow-up data.

Microplastic pollution in the Yangtze River Basin: Heterogeneity of abundances and characteristics in different environments.

Microplastic pollution in the Yangtze River Basin has become a major concern; however, the variations in different environmental compartments are unknown. Here, we compiled published information including detection methods, occurrence, and characterization of microplastics from 624 sampling sites in river water, river sediment, lake and reservoir water, and lake and reservoir sediment in the Yangtze River Basin. The spatial distribution of sampling sites shows fractal pattern and was uniformly concentrated around the main stream of the Yangtze River and the lake geographical zone. Collection, pretreatment, identification, and quantification processes varied among different studies. Non-parametric tests were performed to compare the different microplastic indices. A Pearson correlation analysis was used to study the relationship between microplastic pollution and local socioeconomic conditions. We found that the microplastic size and abundance distribution in river water and lake and reservoir water showed different patterns for different sampling methods, indicating that different methods influenced the results. Population density and urbanization rate are suggested to be important factors influencing the spatial heterogeneity of microplastic abundances in water, rather than in sediment. The microplastic abundances in lake and reservoir water were higher than that in river water in bulk samples. However, microplastic abundances among different sediment environments shows no significant difference. For bulk water samples and sediment samples overall, the proportion of small microplastics (<1 mm, i.e. SMP), fibers, transparent debris, and polypropylene (PP) were 65.1%, 67.8%, 31.8%, and 29.7%, respectively. The microplastic characteristics of lake and reservoir water and sediment were similar, differing from those of river water and sediment. This study provides the first basin scale insight into microplastic occurrence and characteristics in different environments in the Yangtze River Basin.

A data-driven framework for spatiotemporal characteristics, complexity dynamics, and environmental risk evaluation of river water quality.

To evaluate the evolution of river water quality in a changing environment, measuring the objective water quality is critical for understanding the rules of river water pollution. Based on the sample entropy theory and a nonlinear statistical method, this study aims to identify the spatiotemporal dynamics of water quality and its complexity in the Yangtze River basin using time series data, to separate the contributions of human activity and climate change to water quality, and to establish a data-driven risk assessment framework for the spatial (potential risk) and temporal (direct risk) aspects of water pollution. The results demonstrate that the spatiotemporal dynamics of water quality and sample entropy in each monitoring section are closely related to the characteristics of the corresponding location. The water quality of the main stream is superior, and its complexity is less than that of the tributaries. Cascade reservoir operation and vegetation status, agricultural production, and rainfall patterns exert great influences in the upper, middle, and lower reaches, respectively. Dam construction, urban agglomeration development, and interactions between river and lake are also influencing factors. An attributional analysis found that climate change and human activities negatively contributed to the evolution of NH3-N concentration in most of the monitored sections, and the average relative contribution rates of human activities to changes in water quality in the main and tributary streams were -55.46% and -48.49%, respectively. In addition, the construction of data-driven risk assessment framework can efficiently and accurately assess the potential and direct water pollution risks of rivers.

Full nitration-denitration versus partial nitration-denitration-anammox for treating high-strength ammonium-rich organic wastewater.

This study investigated the performance of full nitration-denitration (FND) and partial nitration-denitration-anammox (PNDA) in treating a synthetic wastewater with 300 mg/L NH4+-N and 600 mg/L COD. It was found that approximately 40% higher total nitrogen removal was achieved via PNDA than via FND. Meanwhile, high-throughput sequencing also revealed that aerobic heterotrophic bacteria were predominant in the FND process, while facultative and even anaerobic bacteria including anammox bacteria were dominant in PNDA process. Furthermore, the mass balance on nitrogen showed that 44% of nitrogen was removed by partial nitration-denitration, while 36% via nitritation-anammox pathway in the PNDA process, with the significant saving in aeration and demand of organic carbon source. Compared to the FND process, it is obvious that the PNDA process will offer a more cost-effective alternative with easy operation for treating ammonium-rich organic wastewater.

A novel single-stage process integrating simultaneous COD oxidation, partial nitritation-denitritation and anammox (SCONDA) for treating ammonia-rich organic wastewater.

In this study, simultaneous carbon oxidation, partial nitritation, denitritation and anammox (SCONDA) was successfully integrated into a one-stage sequencing biofilm batch reactor for treating ammonia-rich organic wastewater with carbon to nitrogen (C/N) ratio of 3. The results showed that 94.3% of COD removal together with 92.6% NH4+-N and 88% TN removal were achieved via SCONDA. High-throughout sequencing analysis further revealed that the microbial community developed in the proposed system was primarily dominated by heterotrophic bacteria (e.g. Thauera, Azovibrio, Ohtaekwangia, Azospira), autotrophic bacteria (e.g. Nitrosomona) and unclassified genus of anammox bacterium, which were all essential for COD and N removal via SCONDA. The observed spatial distributions of the functional species in stratified biofilms were found to be crucial for successful SCONDA at the low dissolved oxygen of 1.3 mg/L. The integrated SCONDA system is expected to offer a promising alternative for advanced nitrogen and organic removal from high-ammonia organic wastewater.