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With the fast-growing accumulation of electronic waste and rising demand for rare metals, it is compelling to develop technologies that can promotionally recover targeted metals, like gold, from waste, a process referred to as urban mining. Thus, there is increasing interest in the design of materials to achieve rapid, selective gold capture while maintaining high adsorption capacity, especially in complex aqueous-based matrices. Here, a highly porous metal-organic framework (MOF)–polymer composite, BUT-33–poly( para -phenylenediamine) (PpPD), is assessed for gold extraction from several matrices including river water, seawater, and leaching solutions from CPUs. BUT-33–PpPD exhibits a record-breaking extraction rate, with high Au 3+ removal efficiency (>99%) within seconds (less than 45 s), a competitive capacity (1600 mg/g), high selectivity, long-term stability, and recycling ability. Furthermore, the high porosity and redox adsorption mechanism were shown to be underlying reasons for the material’s excellent performance. Given the accumulation of recovered metallic gold nanoparticles inside, the material was also efficiently applied as a catalyst.

Biomimic nanozymes coassembled by peptides or proteins and small active molecules provide an effective strategy to design attractive nanozymes. Although some promising nanozymes have been reported, rational regulation for higher catalytic activity of biomimic nanozymes remains challenging. Hence, we proposed a novel biomimic nanozyme by encapsulating the coassembly of hemin/bovine serum albumin (BSA) in zeolite imidazolate frameworks (ZIF-8) to achieve controllable tailoring of peroxidase-like activity via the confinement effect. The assembly of Hemin@BSA was inspired by the structure of horseradish peroxidase (HRP), in which hemin served as the active cofactor surrounded by BSA as a blocking pocket to construct a favorable hydrophobic space for substrate enrichment. Benefiting from the confinement effect, ZIF-8 with a porous intracavity was identified as the ideal outer layer for Hemin@BSA to accelerate substrate transport and achieve internal circulation of peroxidase-like catalysis, significantly enhancing its peroxidase-like activity. Especially, the precise encapsulation of Hemin@BSA in ZIF-8 could also prevent it from decomposition in harsh environments by rapid crystallization around Hemin@BSA to form a protective shell. Based on the improved peroxidase-like activity of Hemin@BSA@ZIF-8, several applications were successfully performed for the sensitive detection of small molecules including H

Biomass-derived nanocarbons with natural intramolecular N,S frameworks are impressively used to fabricate DACs with pairwise-dual-atoms on a gram-scale for highly efficient oxygen reduction reaction.

Psychosocial combined with methadone maintenance treatment aimed at opioid use disorder is effective, but the efficacy of the psychosocial intervention in such treatment is questionable.This study aims to evaluate the effectiveness of psychosocial plus methadone maintenance treatment versus methadone maintenance treatment alone for opioid use disorder in improving treatment retention and reducing drug use.An exhaustive literature search was conducted in PubMed, EMBASE, Cochrane Library, Web of Science, PsycINFO, CINAHL, China National Knowledge Infrastructure database, "the Wan Fang database, the VIP database, and the Chinese Biomedical Literature Database", and randomized controlled trials were identified from their inception to February 2021.Twenty-four studies were included. The results of this meta-analysis showed that adding any psychosocial treatment to standard methadone maintenance treatment significantly improved the illicit drug use during the treatment relative risk (RR) 0.62 (95% CI 0.48 to 0.79), and retention in treatment RR 1.18 (95% CI 1.11 to 1.25). No statistically significant additional benefit was detected in terms of retention at follow-up RR 1.08 (95% CI 0.95 to 1.22).The present evidence suggests that adding psychosocial intervention to methadone maintenance treatment significantly improves the nonuse of opioids and retention in treatment. It should be noted that psychosocial treatment is only beneficial for methadone treatment when methadone is provided in subtherapeutic doses. Additionally, the finding about the improvement effect of retention at follow-up did not achieve statistical significance. Due to the diversity of outcome indicators in relevant original studies, the included studies are limited.

Acute myocardial infarction (AMI)-related microRNAs (miRNAs) in circulating blood have been proved as promising biomarkers for AMI diagnosis. The detection of these miRNAs at ultralow levels usually requires nucleic acid amplification strategies to improve the sensitivity at the cost of time. Given that the first hour after an AMI attack is the golden time for saving AMI patients' lives, shortening the time of ultrasensitive miRNA analysis is of great significance for clinical AMI diagnosis. Toward this goal, here we present a direct electrochemiluminescence (ECL) sensing strategy for fast and ultrasensitive miRNA detection, circumventing the time-consuming signal amplification steps. Target miRNAs are directly hybridized with two probe strands that are attached to a covalently hemin-modified spherical nucleic acid enzyme (SNAzyme) and a truncated triangular pyramid DNA nanoplatform on the electrode, respectively. Both of them improve the ECL signal and meanwhile reduce the background, thereby remarkably promoting the detection sensitivity of target miRNAs. It enables the rapid detection of an AMI-related miRNA (miR-499) at 10 aM in human serum within 30 min using the SNAzyme-catalyzed luminol-H

Children are more likely to experience maltreatment and parental conflict in a pandemic context, which can exacerbate their vulnerability to psychological disorders. The purpose of the present study was to examine mental health symptoms in children aged 0 to 10 years and consider related factors from the perspectives of maltreatment and parental conflict during the COVID-19 lockdown. Participants were 1286 parents aged 18 years and over with children aged 0 to 10 years were included. Several multivariable linear regressions were used to analyze the data. The largest variance in child mental health was explained by child maltreatment, as more maltreatment predicted higher reported psychological problems (standardized beta = 0.49, P 0.001). Comparatively, parental conflict predicted less variance in mental health problems than maltreatment (standardized beta = 0.18, P 0.001). Children who experienced more maltreatment experience and exposure to COVID-19 showed elevated levels of mental health symptoms (standardized beta = 0.06, p 0.05), as did those who experienced parental conflict and pandemic exposure (standardized beta = 0.06, p 0.05). The findings highlight that tailored programs that focus on a healthy family environment and strategic parental support services may be particularly effective in reducing children's mental health problems due to COVID-19 exposure.

Removing non-biodegradable Pb

Antibiotic residues cause increasing concern in environmental ecology and public health, which needs efficient analysis strategy for monitoring and control. In this study, a fast, specific, and ultrasensitive sensor based on field-effect transistor (FET) has been proposed for the detection of ampicillin (AMP). The sensor involves monolayer tungsten disulfide (WS

Under complex seismic forces, the failure characteristics of the plastic hinge region at the bottom of the pier column and the methods improving the ductility have attracted extensive attention. In this study, steel fiber-reinforced concrete with fine aggregate (SFRC-FA) was applied to locally replace the conventional concrete in the potential plastic hinge region at the bottom of the pier column. Five SFRC-FA pier column specimens with different stirrup ratios and different replacement lengths and one conventional reinforced concrete pier column specimen were produced. Using the seismic behavior tests under the combined bending-shear-torsion-axial force, the failure mode, torsional bearing capacity, energy dissipation, and the torsional plastic hinges of the pier columns were investigated. In addition, an equation for calculating the torsional bearing capacity of the new composite pier columns was proposed. The results showed that (1) compared with the reinforced concrete pier column, the plastic hinge was shifted from the bottom of the pier column to the middle of the height of the pier column due to the application of SFRC-FA at the bottom of the pier column, which improved the torsional bearing capacity; (2) the effect of reducing the stirrup ratio of the SFRC-FA replacement region on the torsional bearing capacity, cracking mode, energy dissipation, and ductility was not obvious; (3) the accuracy of the new equation based on the space truss model proposed in this article was verified by comparison with the experiments of this study and other researches.

Silver (Ag) is a widely used heavy metal, and its oxidation state (Ag+) causes serious harm to organisms after bioaccumulation and biomagnification, posing urgent demand for the rapid, efficient, and simply operated Ag+ detection techniques. In this work, a fast, portable, and label-free Ag+ detection sensor based on a Ti3C2Tx MXene field-effect transistor (FET) is reported. The Ti3C2Tx MXene works as the sensing element in the FET sensor, which shows excellent sensing performance, i.e., fast response (few seconds) and good sensitivity and selectivity to Ag+ without any detection label or probe. Utilizing the visual photograph, transmission electron microscopy image, and Ag elemental mapping analysis, the sensing mechanism of the label-free Ti3C2Tx MXene FET sensor is demonstrated to be the in situ reduction of Ag+ and the formation of Ag nanoparticles (AgNPs). Moreover, Ag+ detection in real samples shows that the proposed FET devices have satisfactory sensing capability for Ag+ in tap water and river water. This study puts forward a novel FET strategy for Ag+ detection in aqueous systems, which is of essential and inspiring meaning for motivating the potential applications of MXene-based sensor devices in analytical applications and the realization of on-site environmental monitoring.

Objectives The coronavirus (COVID-19) global pandemic has increased psychological distress among the general population. The objective of this study is to evaluate a mindfulness-based intervention for psychological distress among Chinese residents during COVID-19. Methods This study used a switching replications design to test the feasibility and efficacy of a brief online mindfulness-based intervention for Chinese residents’ psychological distress. Fifty-one residents in the Hubei province were randomly allocated to two groups (experimental group and waitlist control group) with three waves of measurement at time 1, time 2, and time 3 for changes in mindfulness and psychological distress. Results In addition to significant within-group improvements over time for both groups, OLS linear regression with full information likelihood estimation revealed statistically significant between-group treatment effects across outcome domains, including mindfulness awareness, b = 2.84, p < 0.001, g = 6.92, psychological distress, b = −21.33, p < 0.001, g = 6.62, somatic symptoms, b = −6.22, p < 0.001, g = 4.42, depressive symptoms, b = −7.16, p < 0.001, g = 5.07, and anxiety symptoms, b = −8.09, p < 0.001, g = 6.84. Conclusions Results suggest that a brief online mindfulness-based intervention can be a feasible and promising intervention for improving mindfulness and decreasing psychological distress among Chinese residents staying at home during the COVID-19 outbreak. The study used a small convenience sample which led to a concern of external generalizability and with limited evaluation of long-term change.

A simple, efficient, and environmentally friendly electro-Fenton (EF) process is highly demanded for EF practical application. Herein, a highly practical double-cathode EF system has been developed...

Field-effect transistors (FETs) receive growing attention for gas detection owing to their superior sensing performance over traditional techniques. The sensitivity and selectivity of FET sensors can be enhanced by tuning the structure of channel materials via doping, surface functionalization, hybridization, etc. However, the intrinsic semiconductor characteristics of the channel material and its gas adsorption capacity largely determine the sensing performance. In this work, we compared the room-temperature sensing performance of FET sensors with few-layer graphene, black phosphorous (BP), and MoS2 with mixed polymorphic phases (metallic 1T phase and semiconducting 2H phase), and 2H-MoS2 as a channel material for formaldehyde. The sensing results indicate that 1T/2H-MoS2 exhibits the best sensitivity, response time as well as selectivity for formaldehyde detection. The theoretical calculation demonstrates that 1T/2H-MoS2 yields the optimum semiconducting properties and gas adsorption capability for formaldehyde over other 2D channels. Moreover, by investigating the sensing performance under humid conditions, it was discovered that high humidity enhances the sensing response. This study demonstrates that the regulation of the intrinsic electronic structures of the 2D semiconducting channel directly affects the gas detection performance.

Eleven metabolites, six echinosporins (1-6), four dibenzoyls (7-10), and an aromatic compound (11), were isolated from the fermentation broth of lichen-associated Amycolatopsis hippodromi. The structures of the new compounds (1-5, 8-11) were elucidated by comprehensive spectroscopic analysis including data from experimental and calculated ECD spectra. Amycolasporins A-C (1-3) demonstrated antibacterial activities against Bacillus subtilis, Staphylococcus aureus, and Escherichia coli with MIC values of 25 or 100 μg/mL. Amycolasporin C (3) and the known dibenzoyl (7) attenuated the production of NO due to the suppression of the expression of nitric oxide synthase (iNOS) in LPS-induced RAW 264.7 cells in a dose-dependent manner.

Monolayer MoS2 (ML-MoS2) with various polymorphic phases attracts growing interests for device applications in recent years. Herein, a field-effect transistor (FET) gas sensor is developed on the basis of monolayer MoS2 with a heterophase of a 1T metallic phase and a 2H semiconducting phase. Lithium-exfoliated MoS2 nanosheets own a monolayer structure with rich active sites for gas adsorption. With thermal annealing from 50 to 300 °C, the initial lithium-exfoliated 1T-phase MoS2 gradually transforms into the 2H phase, during which the 1T and 2H heterophases can be modulated. The 1T/2H heterophase MoS2 shows p-type semiconducting properties and prominent adsorption capability for NO2 molecules. The highest response is observed for 100 °C annealed MoS2 of a 40% 1T phase and a 60% 2H phase, which shows a sensitivity up to 25% toward 2 ppm NO2 at room temperature in a very short time (10 s) and a lower limit of detection down to 25 ppb. This study demonstrates that the gas detection capability of ML-MoS2 could be boosted with the heterophase construction, which brings new insights into transition-metal dichalcogenide gas sensors.

Two-dimensional (2D) Ti3C2Tx MXene has shown great potential in the energy storage field, and its performance strongly depends on the intercalation of cations. Therefore, engineering its interlayer...

Besides excellent adsorption performance of adsorbents, the disposal of spent adsorbents should be considered for environmental concern. In this study, a new all-biomass double network Jute/sodium alginate (Jute/SA) gel is prepared via the simple dripping technique. 80 wt% water of Jute/SA hydrogel endows the adsorbent with high permeability for heavy metal ions diffusion onto internal adsorption sites. The Jute/SA gel adsorbent can efficiently remove heavy metals from melting wastewater, especially Pb2+ and Cd2+. The adsorbent shows high adsorption capacities of 291.3 mg g−1 for Pb2+ and 149.9 mg g−1 for Cd2+ at 298 K. The adsorption equilibrium reaches within 45 min for 45 mg L−1 Cd2+ and Pb2+ using 1 g L−1 adsorbent, showing 98% removal efficiency of Pb2+ and Cd2+. Moreover, the removal efficiencies in 45 min reach up to 99.1% for Pb2+ (7.539 mg L−1) and 89.9% for Cd2+ (4.743 mg L−1) in actual melting effluent containing Zn (43.95 mg L−1), Cu (16.50 mg L−1), Mn (19.24 mg L−1), Ni (4.90 mg L−1) and Fe (33.75 mg L−1) using 1 g L−1 adsorbent. The concentrations of Pb and Cd decrease below 0.001 mg L−1 using 4 g L−1 adsorbent. Furthermore, the adsorption efficiencies for Pb2+ and Cd2+ remain above 95% in the tenth cycle, and the desorption efficiency is up to 99%. In addition, the spent Jute/SA gel was a good organic fertilizer for plant growth. This work develops an efficient and eco-friendly biomass adsorbent for the removal of heavy metals in actual wastewater.

MXenes, a group of emerging two-dimensional (2D) transition metal carbides or nitrides, have attracted wide interest due to their unique structures and properties. Their stability and applicability in different media especially in an alkaline environment are directly associated with their potential applications and are not yet explored. Herein, a field-effect transistor (FET) is fabricated with single/double-layer Ti3C2Tx MXene. The Ti3C2Tx FET indicator shows a fast (∼1 s), sensitive, and selective response to alkali. Moreover, the device can work even in a high-salinity (2 M NaCl) environment, suggesting its high anti-interference ability for alkali in a high-ionic-strength environment. Using an in situ morphological image evolution study, it is demonstrated that the response signal results from alkali-induced denaturation of Ti3C2Tx nanosheets. The Ti3C2Tx-based alkali FET indicator and systematic evaluation on alkali-induced structure evolution of Ti3C2Tx provide essential insights into MXene-based FETs and future applications of MXene in alkaline environments.

Although graphitic carbon nitride (g-C3N4) has been identified as a promising photocatalyst, pristine g-C3N4 has a limited light absorption, insolubility, small specific surface area, and rapid ele...

The Coronavirus Disease 2019 (COVID-19) pandemic has caused numerous unexpected changes for families and societies, which have likely contributed to higher amounts of stress for most parents. This study aimed to examine the relationship between burnout and mental health among parents during the COVID-19. Pandemic exposure and household factors (e.g., family structure, family function) were examined as moderators. An online cross-sectional survey recruiting 1,209 adults was conducted from April 21st to April 28th, 2020 during the COVID-19 lockdown in China. The multivariable linear regression analysis was employed to test the association between burnout, household factors, and mental health among parents. Findings suggested that for parents with a young child, poorer mental health was related to a higher level of burnout (β = 0.220, P < 0.001) and greater exposure to the pandemic. Mothers of a single and/or young child had considerably poorer mental health. Moreover, the relationship between mental health and burnout among parents was significantly moderated by epidemic exposure (β = 2.561, P < 0.001), family structure (number of children: β = −1.257, P < 0.001; first child age: β=-1.116, P < 0.001) and family function (β = −0.574, P < 0.05). This study indicated that burnout symptoms were significantly associated with worse mental health among parents in China. Besides, exposure to the pandemic, family structure, and family function was found to moderate the association between burnout and mental health among parents. Therefore, the present study stressed enhanced access to mental health resources and emotional supports for parents during a public crisis to reduce the deleterious effects of burnout.

Electrochemical reduction of nitrate (NO3-) to ammonia (NH3) provides a promising route for recycling nitrate from wastewater to balance the nitrogen cycle and sustainable production of ammonia. Among various catalytic materials for NO3- electroreduction, Cu shows a favorable selectivity to NH3. However, Cu can be easily oxidized, while the effect of the Cu oxidation state on NO3- reduction remains to be elucidated. Here, we report that oxidic Cu formed on a Cu electrode can enhance its activity and selectivity for NO3- reduction to NH3. We first used a polished Cu foil as a model catalyst for NO3- reduction and found that a brief exposure of the Cu electrode to air could increase its yield rate and Faradaic efficiency for NH3 production. The improved catalytic performance was attributed to the formed Cu+ sites that can reduce the energy barrier for NO3- reduction to NH3 and suppress the competing HER reaction. Based on this finding, an oxide-derived Cu (OD-Cu) electrode was prepared by annealing a Cu foil in O2 gas followed by electroreduction, which exhibited superior performance for NO3- reduction to NH3, with a Faradaic efficiency of 92% and a yield rate of 1.1 mmol h-1 cm-2 for NH3 production at -0.15 V versus reversible hydrogen electrode. Moreover, an OD-Cu foam electrode was similarly developed to demonstrate NO3- recycling from a low-concentration NO3- solution, which showed a nearly 100% conversion of NO3- to NH3 using a circulating flow cell.

The oxygen evolution reaction has become the bottleneck of electrochemical water splitting for its sluggish kinetics. Developing high-efficiency and low-cost non-noble-metal oxide electrocatalysts is crucial but challenging for industrial application. Herein, superhydrophilic/superaerophobic hierarchical nanoneedle/microflower arrays of Ce-substituted Co

Objective: The study aimed to review evidence on the efficacy of submucosal (SM) administration vs. intravenous (IV) or intramuscular (IM) route of injections of dexamethasone for improving outcomes after mandibular third molar surgery.Methods: PubMed, Embase, CENTRAL, and Google Scholar were searched for randomized controlled trials (RCTs) up to 20th May 2021. Early (2–3 days) and late (7 days) outcomes were compared between SM vs. IV or IM dexamethasone. Quality of evidence was assessed based on GRADE.Results: Thirteen trials were included in the systematic review and 10 in the meta-analysis. Meta-analysis indicated a significant reduction in early pain with IV dexamethasone but no such difference for late pain compared to the SM group. There was no difference in early and late swelling scores between the SM and IV groups. Pooled analysis indicated no significant difference in early and late trismus between SM and IV groups. Comparing SM with IM dexamethasone, there was no significant difference in early and late pain scores. Swelling in the early and late postoperative periods was not significantly different between the two groups. There was no significant difference in early and late trismus between SM and IM groups. The quality of evidence was low for all outcomes.Conclusion: Low-quality evidence suggests that SM infiltration of dexamethasone results in similar outcomes as compared to IV or IM administration of the drug after third molar surgeries. Further high-quality RCTs are needed to corroborate the current conclusions.

Aiming at the problem of grammar and semantic information understanding of the network structure of software system, this paper proposes a method of software defect prediction, which is based on Transformer model, which is completely dependent on self-attention mechanism, it can embed key information in the code semantics of the end-to-end learning software modules. Firstly, the software module is converted into an abstract syntax tree, and later it is traversed to extract word sequence of the software module. Then, thinking of the word sequence as input, acts on the self-attention layer to perform semantic feature embedding of the software module. Finally, the Softmax neural network is used to predict the software defect. The experimental results show that the software defect prediction method based on Transformer model has better defect prediction effects in the three open source software, and it has an average increase of 3.2% than the optimal model based on the Convolutional Neural Network (CNN).