Magnetic Biochar Derived from Fenton Sludge/CMC for High-Efficiency Removal of Pb(II): Synthesis, Application, and Mechanism.

Magnetic biochar composites (MBC) were developed by a simple one-step pyrolysis method using Fenton sludge waste solid and carboxymethyl cellulose sodium. Detailed morphological, chemical, and magnetic characterizations corroborate the successful fabrication of MBC. Batch adsorption experiments show that the synthesized MBC owns high-efficiency removal of Pb(II), accompanied by ease-of-separation from aqueous solution using magnetic field. The experiment shows that the equilibrium adsorption capacity of MBC for Pb(II) can reach 199.9 mg g-1, corresponding to a removal rate of 99.9%, and the maximum adsorption capacity (qm) reaches 570.7 mg g-1, which is significantly better than that of the recently reported magnetic similar materials. The adsorption of Pb(II) by MBC complies with the pseudo second-order equation and Langmuir isotherm model, and the adsorption is a spontaneous, endothermic chemical process. Investigations on the adsorption mechanism show that the combination of Pb(II) with the oxygen-containing functional groups (carboxyl, hydroxyl, etc.) on biochar with a higher specific surface area are the decisive factors. The merits of reusing solid waste resource, namely excellent selectivity, easy separation, and simple preparation make the MBC a promising candidate of Pb(II) purifier.

Novel insights into impacts of the "7.20" extreme rainstorm event on water supply security of Henan Province, China: Levels and health risks of tap water disinfection by-products.

Spatial distributions, levels, and comprehensive assessments of post-flood tap water disinfection by-products (DBPs) were first studied in Henan Province after the "7.20" Extreme Rainstorm Event in 2021. DBPs levels and health risks in tap water were higher in areas flooded (waterlogged) by storm or upstream flood discharge (WA) and rainstorm-affected areas (RA) compared with other areas (OA), suggesting that extreme rainstorm and flooding events may somehow exacerbate DBPs contamination of tap water through disinfection. WA sites were characterized as contamination hotspots. The results revealed high haloacetic acids (HAAs) levels in WA (Avg: 57.79 µg·L-1) and RA (Avg: 32.63 µg·L-1) sites. Compared with normal period, DBPs-caused cancer risk increased by 3 times, exceeding the negligible risk level. Cancer risk came primarily from the ingestion of trihalomethanes (THMs) (>80%), children were the sensitive group. Those between 30 and 69 showed approximately 1.7 times higher disability-adjusted life yearsper person-yearthan other age groups. Apart from regulated DBPs, bromochloracetic acid (BCAA) and dibromoacetonitrile (DBAN) appear to be the main toxicity contributors in these samples. Our results provide a scientific basis for preventing and controlling health risks from tap water DBPs and for assessing the social benefits and burdens of emergency disinfection.

SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training.

Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven neuromorphic hardware due to their spatio-temporal information processing capability and high biological plausibility. Although SNNs are currently more efficient than artificial neural networks (ANNs), they are not as accurate as ANNs. Error backpropagation is the most common method for directly training neural networks, promoting the prosperity of ANNs in various deep learning fields. However, since the signals transmitted in the SNN are non-differentiable discrete binary spike events, the activation function in the form of spikes presents difficulties for the gradient-based optimization algorithms to be directly applied in SNNs, leading to a performance gap (i.e., accuracy and latency) between SNNs and ANNs. This paper introduces a new learning algorithm, called SSTDP, which bridges the gap between backpropagation (BP)-based learning and spike-time-dependent plasticity (STDP)-based learning to train SNNs efficiently. The scheme incorporates the global optimization process from BP and the efficient weight update derived from STDP. It not only avoids the non-differentiable derivation in the BP process but also utilizes the local feature extraction property of STDP. Consequently, our method can lower the possibility of vanishing spikes in BP training and reduce the number of time steps to reduce network latency. In SSTDP, we employ temporal-based coding and use Integrate-and-Fire (IF) neuron as the neuron model to provide considerable computational benefits. Our experiments show the effectiveness of the proposed SSTDP learning algorithm on the SNN by achieving the best classification accuracy 99.3% on the Caltech 101 dataset, 98.1% on the MNIST dataset, and 91.3% on the CIFAR-10 dataset compared to other SNNs trained with other learning methods. It also surpasses the best inference accuracy of the directly trained SNN with 25~32× less inference latency. Moreover, we analyze event-based computations to demonstrate the efficacy of the SNN for inference operation in the spiking domain, and SSTDP methods can achieve 1.3~37.7× fewer addition operations per inference. The code is available at: https://github.com/MXHX7199/SNN-SSTDP.

Cost-utility analysis of newborn hepatitis B immunization in Beijing.

OBJECTIVES: To evaluate cost-utility of universal Hepatitis B vaccination program in the Beijing city (Beijing). METHODS: A decision-Markov model was constructed to determine the cost-utility of the universal immunization program for infants (universal vaccination program) by comparing with a hypothetic nonvaccination strategy in Beijing. Parameters in models were extracted from Beijing Center for Disease Control and Prevention (CDC) annual work report, Beijing health statistical yearbook, National Health Survey report, Beijing 1% population sample survey report, Beijing Health and Medical Price Monitoring Data Platform, and public literatures. The incremental cost­utility ratio (ICUR) was used to compare alternative scenarios. One-way sensitivity analysis and probabilistic sensitivity analysis were used to assess parameter uncertainties. RESULTS: The universal vaccination program had increased the utility and reduced cost among infants born in 2016 in Beijing. The ICUR was CNY -24,576.61 (US$ -3779.16) per QALY for universal vaccination program comparing with non-vaccination scenario from healthcare perspective. It was estimated that the universal vaccination would save direct medical treatment cost of CNY 2,262,869,173.50 (US$ 347,962,414.43) and prevent loss of 18322.25 QALYs within lifetime of target cohort. Discount rate accounted for the most remarkable influence on ICUR in one-way sensitivity analysis. The result of probabilistic sensitivity analysis illustrated that all of the ICURs were located in the fourth quadrant of the cost-utility incremental plot undergone 5000 times of Monte Carlo simulation. CONCLUSIONS: Current universal hepatitis B vaccination program in Beijing was highly cost utility. The investment was reasonable for current universal vaccination program in Beijing.

Dynamic evolution of electrochemical and biological features in microbial fuel cells upon chronic exposure to increasing oxytetracycline dosage.

Dynamic changes in power generation and electrochemical properties were compared between the control microbial fuel cells (C-MFC) and an oxytetracycline (OTC)-treated MFC (O-MFC) on days 84, 139, 174, 224, 295, 307 and 353. The results showed that a high concentration of OTC (>5 mg·L-1) could inhibit microbial activity and result in a decline of voltage output and power density compared with the same C-MFC. However, with the prolongation of incubation time, the inhibitory effect was gradually weakened. Electrochemical analyses demonstrated that long-term OTC acclimation reduced the ohmic and polarisation resistance of the anode, which was conducive to the recovery of electrochemical performance. More than 99% of 10 mg·L-1 OTC could be removed within 48 h, and the antibacterial activity of the MFC effluent on Escherichia coli DH5α was conclusively eliminated. High-throughput sequencing analysis revealed that the diversity and richness of the microbial community decreased significantly after long-term OTC enrichment. Acinetobacter, Petrimonas, Spirochaetaceae and Delftia were enriched and played a dominant role in C-MFC stability and power generation. The promotion by Cupriavidus, Geobacter and Stenotrophomonas in simultaneous OTC degradation and bioelectricity generation in the O-MFC was demonstrated.

Magnetic supramolecular polymer: Ultrahigh and highly selective Pb(II) capture from aqueous solution and battery wastewater.

For the practical capture of heavy metal ions from wastewater, fabricating environmental friendly adsorbents with high stability and super adsorption capacity are pursuing issue. In this work, we develop magnetic supramolecular polymer composites (M-SMP) by using a simple two-step hydrothermal method. Systematical characterizations of morphological, chemical and magnetic properties were conducted to confirm the formation of M-SMP composites. The resulting M-SMP composites were applied to remove Pb(II) from aqueous solution and from real battery wastewater, and easy separation was achieved using a permanent magnet. By investigating the effects of various parameters, we optimized their operating condition for Pb(II) adsorption by the M-SMP. The uptake of Pb(II) onto M-SMP fitted well the pseudo-second-order and Langmuir isotherm models, and favourable thermodynamics showed a spontaneous endothermic process. The SMP endowed M-SMP with ultrahigh adsorption capacity for Pb(II) (946.9 mg g-1 at pH = 4.0, T = 298 K), remarkable selectivity, satisfactory stability and desirable recyclability. In Pb-contaminated lead-acid battery industrial wastewater, the concentration of Pb(II) declined from 18.070 mg L-1 to 0.091 mg L-1, which meets the current emission standard for the battery industry. These merits, combined with simple synthesis and convenient separation, make M-SMP an outstanding scavenger for the elimination of industrial Pb(II) wastewater.

Highly effective remediation of Pb(II) and Hg(II) contaminated wastewater and soil by flower-like magnetic MoS2 nanohybrid.

The efficient enrichment and remediation of heavy metals from realistic wastewater and contaminated soil containing large excess of competitive ions remains a daunting challenge by far. In the present study, flower-like molybdenum disulfide decorated with iron oxide nanoparticles (MoS2/Fe3O4) is designed via a two-step hydrothermal method and mainly applied in the removal of Hg(II) and Pb(II) ions in aqueous environment. Exhaustive morphological, chemical and magnetic characterizations verify the successful formation of magnetic MoS2/Fe3O4. Batch adsorption experiments show that the obtained MoS2/Fe3O4 nanohybrid enables efficient capture of Hg(II) and Pb(II) ions, accompanied by ease-of-separation from solution by simply applying a magnet. In this respect, high adsorption capacities (263.6 mg g-1 for Pb(II) and 428.9 mg g-1 for Hg(II)) can be gained under optimized conditions (pH = 5.0; 298 K; nanohybrid dosage: 0.8 g L-1 and the contact time: 180 min). In addition, the effects of different parameters such as initial Pb(II)/Hg(II) concentration (50-500 mg L-1), temperature (298, 308 and 318 K) and co-existing ions (Zn(II), Cu(II), Cd(II) and Mg(II)) were systematically probed. The favorable adsorption capacity, selectivity and recyclability mainly originates from the strong Hg2+/Pb2+···S2- bonding interactions. Practical application potential of magnetic MoS2/Fe3O4 nanohybrid in realistic lead-acid battery industry wastewater and Pb(II)-contaminated soil is further explored, achieving promising results with high Pb(II) removal efficiency of 99.63% for wastewater and 57.15% for soil. Simple preparation, easy separation and high adsorption capacity would foster thus-designed sulfide-based nanohybrid a promising adsorbent for heavy metal removal from wastewater and contaminated soil.

In situ polymerization of magnetic graphene oxide-diaminopyridine composite for the effective adsorption of Pb(II) and application in battery industry wastewater treatment.

The efficient removal of heavy metals from aqueous environment is imperative and challenging. A novel ternary composite constructed of diaminopyridine polymers, graphene oxide, and ferrite magnetic nanoparticles was designed by a facile in situ polymerization strategy for the removal of Pb(II) from aqueous solution. Detailed characterization of morphological, chemical, and magnetic properties was employed systematically to confirm the formation of the composite material. Batch adsorption experiment studies suggested that the composite was an excellent adsorbent for Pb(II) which was easily collected after use via exposure to an external magnetic field for 30 s. The effects of different parameters such as solution pH, adsorbent dosage, contact time, initial Pb(II) concentration, temperature, and co-existing ions were examined. The maximum adsorption capacity at pH = 5 was estimated to be 387.2 mg g-1 at 298 K by the Langmuir isotherm model, accompanied by favorable adsorption recyclability according to the investigation of regeneration experiments. Thermodynamic studies revealed that the Pb(II) adsorption via our ternary composite was endothermic and spontaneous. The corresponding removal performance for effluent containing Pb(II) from the battery industry was successfully examined. The present results indicated that our designed adsorbent is beneficial to the practical Pb(II) removal in wastewater purification.