Mitigation of Triclocarban Inhibition in Microbial Electrolysis Cell-Assisted Anaerobic Digestion.

Triclocarban (TCC), as a widely used antimicrobial agent, is accumulated in waste activated sludge at a high level and inhibits the subsequent anaerobic digestion of sludge. This study, for the first time, investigated the effectiveness of microbial electrolysis cell-assisted anaerobic digestion (MEC-AD) in mitigating the inhibition of TCC to methane production. Experimental results showed that 20 mg/L TCC inhibited sludge disintegration, hydrolysis, acidogenesis, and methanogenesis processes and finally reduced methane production from traditional sludge anaerobic digestion by 19.1%. Molecular docking revealed the potential inactivation of binding of TCC to key enzymes in these processes. However, MEC-AD with 0.6 and 0.8 V external voltages achieved much higher methane production and controlled the TCC inhibition to less than 5.8%. TCC in the MEC-AD systems was adsorbed by humic substances and degraded to dichlorocarbanilide, leading to a certain detoxification effect. Methanogenic activities were increased in MEC-AD systems, accompanied by complete VFA consumption. Moreover, the applied voltage promoted cell apoptosis and sludge disintegration to release biodegradable organics. Metagenomic analysis revealed that the applied voltage increased the resistance of electrode biofilms to TCC by enriching functional microorganisms (syntrophic VFA-oxidizing and electroactive bacteria and hydrogenotrophic methanogens), acidification and methanogenesis pathways, multidrug efflux pumps, and SOS response.

Catalytic degradation of antibiotic sludge to produce formic acid by acidified red mud.

As complex and difficult-to-degrade persistent organic pollutants (POPs), antibiotics have caous damage to the ecological enused serivironment. Because of the difficult degradation of antibiotics, sewage and sludge discharged by hospitals and pharmaceutical enterprises often contain a large number of antibiotic residues. Therefore, the harmless and resourceful treatment of antibiotic sludge is very meaningful. In this paper, amoxicillin was selected as a model compound for antibiotic sludge. Acidified red mud (ARM) was used to degrade antibiotic sludge and produce hydrogen energy carrier formic acid in catalytic wet peroxidation system (CWPO). Based on various characterization analyses, the reaction catalytic mechanism was demonstrated to be the result of the non-homogeneous Fanton reaction interaction between Fe3O4 on the ARM surface and H2O2 in solution. Formic acid is the product of the decarboxylation reaction of amoxicillin and its degradation of various organic acids. The formic acid was produced up to 792.38 mg L-1, under the optimal conditions of reaction temperature of 90 °C, reaction time of 30 min, H2O2 concentration of 20 mL L-1, ARM addition of 0.8 g L-1, pH = 7, and rotor speed of 500 rpm. This research aims to provide some references for promoting red mud utilization in antibiotic sludge degradation.

Roles of red mud in remediation of contaminated soil in mining areas: Mechanisms, advances and perspectives.

Red mud (RM) is a kind of strong alkaline solid waste produced from the aluminum industry, which contributes significantly to environmental pollution and can cause severe health issues.Currently, RM is widely recognized as a potential material for soil remediation because of its rich metal oxide content, such as Fe/Al oxides. However, there is no comprehensive description on the roles of RM in passivation remediation of contaminated soil in mining areas. This review summarizes the mechanisms of passivation of heavy metals (HMs) in contaminated soil by RM, including precipitation, adsorption and ion exchange. Besides the effects of adding RM on soil physicochemical properties, heavy metal forms and ecological environment are further elaborated. Moreover, using the co-hydrothermal carbonization of RM and biomass for enhancing the efficiency of contaminated soil remediation is proposed as the main prospective research. This paper provides technical references for the resource utilization of RM and the treatment of heavy metal-contaminated soil.

Recent advances in organic waste pyrolysis and gasification in a CO2 environment to value-added products.

The persistent combustion of fossil fuels has resulted in a widespread greenhouse effect attributable to the continual elevation of carbon dioxide (CO2) levels in the atmosphere. Recent research indicates that utilizing CO2 as a pyrolysis gasification medium diminishes CO2 emissions and concurrently augments the value of the resultant pyrolysis gasification products. This paper reviews recent advancements in the pyrolysis gasification of organic solid wastes under a CO2 atmosphere. Meanwhile, the mechanisms of CO2 influence in the pyrolysis and gasification processes were also discussed. In comparison to noble gases, CO2 exhibits reactivity with char at≥710 °C, resulting in additional mass loss of the sample. In addition, CO2 was able to increase the specific surface area and stability of biochar and reduce biooil toxicity by lowering the content of cyclic compounds in the biooil, while CO2 was able to react with GPRs with some volatile products (e.g., light hydrocarbons) to increase biogas yield. Finally, CO2 also prevents catalyst deactivation by reducing secondary coke formation. We also recommend directing future attention toward utilizing unpurified CO2 in pyrolysis and gasification. This review aims to expand the utilization of CO2 and advocate for applying pyrolysis gasification products.

A Polyzwitterionic@MOF Hydrogel with Exceptionally High Water Vapor Uptake for Efficient Atmospheric Water Harvesting.

Atmospheric water harvesting (AWH) is considered a promising strategy for sustainable freshwater production in landlocked and arid regions. Hygroscopic salt-based composite sorbents have attracted widespread attention for their water harvesting performance, but suffer from aggregation and leakage issues due to the salting-out effect. In this study, we synthesized a PML hydrogel composite by incorporating zwitterionic hydrogel (PDMAPS) and MIL-101(Cr) as a host for LiCl. The PML hydrogel was characterized using various techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FTIR), and thermogravimetric analysis (TGA). The swelling properties and water vapor adsorption-desorption properties of the PML hydrogel were also assessed. The results demonstrate that the MIL-101(Cr) was uniformly embedded into PDMAP hydrogel, and the PML hydrogel exhibits a swelling ratio of 2.29 due to the salting-in behavior. The PML hydrogel exhibited exceptional water vapor sorption capacity of 0.614 g/g at 298 K, RH = 40% and 1.827 g/g at 298 K, RH = 90%. It reached 80% of its saturated adsorption capacity within 117 and 149 min at 298 K, RH = 30% and 90%, respectively. Additionally, the PML hydrogel showed excellent reversibility in terms of water vapor adsorption after ten consecutive cycles of adsorption-desorption. The remarkable adsorption capacity, favorable adsorption-desorption rate, and regeneration stability make the PML hydrogel a potential candidate for AWH. This polymer-MOF synergistic strategy for immobilization of LiCl in this work offers new insights into designing advanced materials for AWH.

Pyrolytic kinetics, reaction mechanisms and gas emissions of waste automotive paint sludge via TG-FTIR and Py-GC/MS.

The present study experimentally quantified the pyrolysis behaviors of waste solvent-based automotive paint sludge (OAPS) and water-based automotive paint sludge (WAPS) at four different heating rates using thermogravimetric-Fourier transform infrared (TG-FTIR) spectrometry and pyrolysis-gas chromatography-mass (Py-GC/MS) spectrometry analyses. Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods combined with the master-plots method were employed to investigate the pyrolysis kinetics and reaction mechanisms of waste automotive paint sludge. Three reaction stages and three reaction peaks in stage 2 were distinguished for both OAPS and WAPS degradation. The average activation energy (Ea) estimates for OAPS (FWO: 179.09 kJ/mol; KAS: 168.28 kJ/mol) were slightly higher than WAPS (FWO: 175.90 kJ/mol; KAS: 164.80 kJ/mol) according to FWO and KAS methods. The main pyrolysis reaction mechanisms of both OAPS and WAPS closely matched with the order-based model corresponding to 3rd and 2nd order random nucleation on an individual particle. The evolved gas species of CH4, CO2, phenols, NH3, H2O, and CO from OAPS and WAPS pyrolysis were identified by TG-FTIR. According to Py-GC/MS, hydrocarbons (47.2%) and O-components (42.7%) were relatively large after OAPS and WAPS pyrolysis, respectively. Melamine was the most abundant N-component product after pyrolysis of OAPS (5.8%) and WAPS (4.8%).

Development and validation of diffusion-controlled model for predicting polycyclic aromatic hydrocarbons from baking-free brick derived from oil - based drilling cuttings.

Investigating the release of organic pollutants from bricks made from solid waste is essential. Based on Fick's laws of diffusion, the diffusion model and diffusion-degradation model of polycyclic aromatic hydrocarbon (PAH) emission from the bricks were deduced. The degradation and 64-day emission of PAHs in solid bricks made of oil-based drill cuttings were observed experimentally. The emission and degradation characteristics of 14 PAHs were obtained and fitted with the diffusion and diffusion-degradation models. The emission of most of the PAHs from the bricks at the beginning was in good agreement with the diffusion model, except for benzo[a]anthracene, pyrene, benzo[b]fluoranthene, benzo[k]fluoranthene, and benzo[a]pyrene. However, the emission of PAHs after some time was significantly lower than the theoretical value of the diffusion model. Moreover, fitting with the diffusion-degradation model gave better results, indicating that a joint diffusion-degradation mechanism controlled the emission of PAHs. Therefore, the diffusion-degradation model can better predict the long-term emission of PAHs in bricks made of oil-based drill cuttings.

Prediction of Xe/Kr Separation in Metal-Organic Frameworks by a Precursor-Based Neural Network Synergistic with a Polarizable Adsorbate Model.

Adsorption and separation of Xe/Kr are significant for making high-density nuclear energy environmentally friendly and for meeting the requirements of the gas industry. Enhancing the accuracy of the adsorbate model for describing the adsorption behaviors of Xe and Kr in MOFs and the efficiency of the model for predicting the separation potential (SP) value of Xe/Kr separation in MOFs helps in searching for promising MOFs for Xe/Kr adsorption and separation within a short time and at a low cost. In this work, polarizable and transferable models for mimic Xe and Kr adsorption behaviors in MOFs were constructed. Using these models, SP values of 38 MOFs at various temperatures and pressures were calculated. An optimal neural network model called BPNN-SP was designed to predict SP value based on physical parameters of metal center (electronegativity and radius) and organic linker (three-dimensional size and polarizability) combined with temperature and pressure. The regression coefficient value of the BPNN-SP model for each data set is higher than 0.995. MAE, MBE, and RMSE of BPNN-SP are only 0.331, -0.002, and 0.505 mmol/g, respectively. Finally, BPNN-SP was validated by experiment data from six MOFs. The transferable adsorbate model combined with the BPNN-SP model would highly improve the efficiency for designing MOFs with high performance for Xe/Kr adsorption and separation.

A Microporous Zn(bdc)(ted)0.5 with Super High Ethane Uptake for Efficient Selective Adsorption and Separation of Light Hydrocarbons.

Separating light hydrocarbons (C2H6, C3H8, and C4H10) from CH4 is challenging but important for natural gas upgrading. A microporous metal-organic framework, Zn(bdc)(ted)0.5, based on terephthalic acid (bdc) and 1,4-diazabicyclo[2.2.2]octane (ted) ligands, is synthesized and characterized through various techniques, including powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and porosity analysis. The adsorption isotherms of light hydrocarbons on the material are measured and the isosteric adsorption heats of CH4, C2H6, C3H8, and C4H10 are calculated. The prediction of C2-4/C1 adsorption selectivities is accomplished using ideal adsorbed solution theory (IAST). The results indicate that the material exhibits exceptional characteristics, including a Brunauer-Emmett-Teller (BET) surface area of 1904 m2/g and a pore volume of 0.73 cm3/g. Notably, the material demonstrates remarkable C2H6 adsorption capacities (4.9 mmol/g), while CH4 uptake remains minimal at 0.4 mmol/g at 298 K and 100 kPa. These findings surpass those of most reported MOFs, highlighting the material's outstanding performance. The isosteric adsorption heats of C2H6, C3H8, and C4H10 on the Zn(bdc)(ted)0.5 are higher than CH4, suggesting a stronger interaction between C2H6, C3H8, and C4H10 molecules and Zn(bdc)(ted)0.5. The molecular simulation reveals that Zn(bdc)(ted)0.5 prefers to adsorb hydrocarbon molecules with richer C-H bonds and larger polarizability, which results in a stronger dispersion force generated by an adsorbent-adsorbate induced polarization effect. Therefore, the selectivity of C4H10/CH4 is up to 180 at 100 kPa, C3H8/CH4 selectivity is 67, and the selectivity of C2H6/CH4 is 13, showing a great potential for separating C2-4 over methane.

Synthesis of hierarchical porous carbon with high surface area by chemical activation of (NH4)2C2O4 modified hydrochar for chlorobenzene adsorption.

In this work, hydrothermal technique combined with KOH activation were employed to develop a series of porous carbons (NPCK-x) using tobacco stem as a low-cost carbon source and (NH4)2C2O4 as a novel nitrogen-doping agent. Physicochemical properties of NPCK-x were characterized by Brunauer-Emmett-Teller, field emission scanning electron microscopy, X-ray diffraction, Raman microscope, elemental analysis, and X-ray photoelectron spectroscopy. Results showed that the NPCK-x samples possessed large surface areas (maximum: 2875 m2/g), hierarchical porous structures, and high degree of disorder. N-containing functional groups decomposed during activation process, which could be the dominant reason for appearance of abundant mesopores and well-developed pore structure. Dynamic chlorobenzene adsorption experiments demonstrated that carbon materials with (NH4)2C2O4 modification exhibited higher adsorption capacity (maximum: 1053 mg/g) than those without modification (maximum: 723 mg/g). The reusability studies of chlorobenzene indicated that the desorption efficiency of (NH4)2C2O4 modified porous carbon reached 90.40% after thermal desorption at 100°C under N2 atmosphere. Thomas model fitting results exhibited that the existence of mesopores accelerated the diffusion rate of chlorobenzene in porous carbon. Moreover, Grand Canonical Monte Carlo simulation was conducted to verify that micropores with pore sizes of 1.2-2 nm of the optimized porous carbon were the best adsorption sites for chlorobenzene and mesopores with pore sizes of 2-5 nm were also highly active sites for chlorobenzene adsorption.

How to predict emissions of volatile organic compounds from solid building materials? A critical review on mass transfer models.

Volatile organic compounds (VOCs) emitting from solid building materials can cause adverse human health and environmental climate effects. It's more cost effective and powerful for mass-transfer emission models to describe the emission characteristic of VOCs than emission chamber studies. In this review, the existing main physical mechanism-based models for predicting VOCs emissions from dry solid building materials have been discussed, as well as their differences and similarities. Ignoring internal diffusion and porosity of solid materials, single-phase model is generally quite safe for use in actual condition. Conversely, porous media model is good for understanding VOC-transfer principles in porous materials. Additionally, the porous media model and the single-phase model can be transformed mutually because their model parameters are correlative. The availability of emission models is largely determined by the reliable and useful model parameters. Therefore, substantial technologies and novel methods have been developed for parameter estimation, which have also been reviewed in this paper. How to readily and rapidly obtain model parameters is a future development direction. In addition, applying emission models to predict and control VOCs emission from other solid waste materials is another future research prospect.

Emissions of BTEXs, NMHC, PAHs, and PCDD/Fs from Co-processing of Oil-based Drilling Cuttings in Brick Kilns.

Oil-based drilling cuttings (OBDC) produced from shale gas development is a hazardous waste that have high calorific values and should be disposed of properly. Burning bricks with OBDC is a promising co-disposal method; however, organic pollutants emitted during this process have not received sufficient attention. In this study, the composition and combustion characteristics of OBDC were determined, and the emissions of typical organic pollutants when burning bricks with the addition of OBDC were investigated; these included benzene series compounds (BTEXs), non-methane total hydrocarbons (NMHC), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs). The results showed that OBDC comprised large amounts of alkanes and aromatic hydrocarbons, and combusted mainly in the temperature range of 145-450 °C with an ignition temperature of 145 °C. The co-processing 10% OBDC increased the concentrations of toluene, NMHC, and PAHs in the flue gases by ∼1000%, ∼500%, and 200%, respectively, compared to the control experiment; however, their emission concentrations were within the limits set by the Integrated emission standards of air pollutants of Chongqing. It is worth noting that 26.443 ng/Nm3 PCDD/Fs with a total toxicity of 0.709 ng I-TEQ/Nm3 was generated from the co-processing 10% OBDC, which was ascribed to the high content of chlorine and aromatic hydrocarbons in the OBDC-promoted PCDD/Fs formed during the burning and cooling processes. Though PCDD/Fs in flue gas exceeded the 0.5 ng I-TEQ/Nm3 limit prescribed in the Pollution control standard for hazardous wastes incineration of China, the realistic emission of PCDD/Fs is expected to meet with this emission limit after desulfurization treatment as PCDD/Fs can be absorbed by gypsum. It is recommended that a lower amount of OBDC is added to reduce PCDD/F formation at the source and to take more efficient air pollution control system in order to reach a stricter emission limit of 0.1 ng I-TEQ/Nm3 in EU and USA. Cycling flue gas may also be an effective method to reduce other organic pollutants. Under these conditions, co-processing OBDC in brick kilns can be achieved without serious environmental pollution, making it a potential method for disposal and utilization.

Characterizing the emission behaviors of cumulative VOCs from automotive solvent-based paint sludge.

Volatile organic compounds (VOCs) diffused from paint sludge are potential hazard contributing significantly to environmental pollution and exposure to them can cause severe health issues. In this paper, a diffusion-controlled model was firstly developed for characterizing the emission behaviors of cumulative VOCs from automotive solvent-based paint sludge based on the worst field management scenario. The presented model is characterized by two key parameters: the diffusion coefficient (Dm) and the initial emittable concentration (Cm,0), which can be simultaneously obtained by our proposed ER-history method. Four major components were detected including 1-butanol, butyl acetate and 1,2,4-trimethylbenzene and 1-ethyl-4-methylbenzene. In addition, the model was validated by using environmental data in a ventilated test chamber, proving that the model is reliable and convincing. However, relative deviations of 1-butanol and butyl acetate are larger than those of 1,2,4-trimethylbenzene and 1-ethyl-4-methylbenzene, indicating that the model is more accurate for predicting hydrophobic VOCs release than those of hydrophilic VOCs. Besides, an increase in Cm,0 and Dm tends to enhance VOCs cumulation release. Our studies provide new insight into experimental designs for rapid model parameters measurement and a sound basis for estimating VOCs cumulative release from paint sludge as well as for hazardous waste.

Response mechanism of Chlamydomonas reinhardtii to nanoscale bismuth oxyiodide (nano-BiOI): Integrating analysis of mineral nutrient metabolism and metabolomics.

Nanoscale bismuth oxyiodide (nano-BiOI) is widely studied and applied in environmental applications and biomedical fields, with the consequence that it may be deposited into aquatic environments. However, the impact of nano-BiOI on aquatic ecosystems, especially freshwater microalga, remains limited. Herein, the nano-BiOI was synthesized and its response mechanism towards microalga Chlamydomonas reinhardtii was evaluated. Results showed that a low concentration of nano-BiOI (5 mg/L) could stimulate algal growth at the early stage of stress. With the increase in concentration, the growth rate of algal cells was inhibited and showed a dose effect. Intracellular reactive oxygen species (ROS) were significantly induced and accompanied by enhanced lipid peroxidation, decreased nonspecific esterase activity, and significantly upregulated glutathione S-transferase activity (GST) activity. Mineral nutrient metabolism analysis showed that nano-BiOI significantly interfered with the mineral nutrients of the algae. Non-targeted metabolomics identified 35 different metabolites (DEMs, 22 upregulated, and 13 downregulated) under 100 mg/L BiOI stress. Metabolic pathway analysis demonstrated that a high concentration of nano-BiOI significantly induced metabolic pathways related to amino acid biosynthesis, lipid biosynthesis, and glutathione biosynthesis, and significantly inhibited the sterol biosynthesis pathway. This finding will contribute to understanding the toxicological mechanisms of nano-BiOI on C. reinhardtii.

In Situ Fabrication of Hierarchical MTW Zeolite via Nanoparticle Assembly by a Tailored Simple Organic Molecule.

Amphiphilic surfactants are widely used as templates to synthesize hierarchically structured zeolites due to their multiple functions; however, piloting such new dual-functional templates is limited by their time-consuming nature and high cost. Herein, a simple organic molecule, without a long hydrophobic alkyl chain, was tailored from a gemini-type, poly-quaternary ammonium surfactant, and effectively used as a dual-porogenic template to synthesize hierarchical MTW zeolite. Upon a range of synthesis parameter optimizations, our detailed characterization suggested that the hierarchical MTW zeolite would completely crystallize within 36 hours from the surface to the inside of quasi-spherical particles through in situ consumption of amorphous silicon and aluminum species; much faster than most of the hierarchical MTW zeolites generated by conventional methods. Moreover, the as-prepared hierarchical MTW zeolite exhibited 4 times higher catalytic performance and lifetime of benzene-propene alkylation compared to conventional MTW zeolite, while the introduced crystalline mesopores are of benefit to diffuse reactants, products, and coke depositions. Our strategy broadens the design of new templates in more effective ways to facilely synthesize versatile hierarchical zeolites for diverse applications, especially for those in which macromolecules are involved.

Quadrant response model and error analysis of four-quadrant detectors related to the non-uniform spot and blind area.

In the system of tracking and detection based on the four-quadrant detector (4-QD), the energy distribution of the incident spot and the blind area of the photosensitive surface will affect the location accuracy. The current model of the spot is based on the ideal circular Gauss spot, which makes the error caused by the spot shape easily ignored. In this paper, the model of the spot energy distribution is improved, which can adapt to the elliptical Gauss distribution. The width of the blind area is also added to the response models of the detector so that the output of each quadrant and the error of the localization algorithm can be calculated more accurately. The simulation results show that the measurement accuracy of 4-QD decreases with the increase of the blind area, the shape, and the inclination of the light spot. In the experiment, we first verify the correctness and practicability of the improved model of the spot energy distribution, and then the improved model is proved to be able to make the response and error calculation more accurate.

In Situ Assembly of Nanoparticles into Hierarchical Beta Zeolite with Tailored Simple Organic Molecule.

A hierarchically structured beta zeolite with intercrystalline mesopores was successfully synthesized via in situ assembly of nanoparticles by employing a simple organic molecule N2-p-N2, tailored from polyquaternium surfactant, with no hydrophobic long chain. The generated samples were studied by using powder X-ray diffraction (XRD) and nitrogen adsorption/desorption isotherms. Computer simulation, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) technologies were also used. The characterized results show that the tailored template molecule N2-p-N2 without hydrophobic long-chain tail still can direct the zeolite crystallization, while the hydrophobic long-chain tail is not necessary during the mesoporous Beta zeolite formation. The catalytic performances of the sample were studied using alkylation of benzene with propene reaction to evaluate the relationship between the structure and property. The results apparently suggested an overall improved resistance against deactivation as compared to conventional beta zeolite in reactions. Furthermore, this tailored simple organic molecule strategy from dual-functional surfactant for making mesoporous zeolite would offer a new method of synthesizing other hierarchically structured zeolites.

TNF-α Deficiency Prevents Renal Inflammation and Oxidative Stress in Obese Mice.

BACKGROUND/AIMS: Obese patients and experimental animals exhibit high levels of inflammatory cytokines, such as tumor necrosis factor (TNF)-α. However, the role of TNF-α in the pathophysiologic process in obesity induced kidney damage is still unknown. METHODS: We used TNF-α deficient mice and wild-type (WT) C57/BJ6 mice controls to study the effect of TNF-α on inflammation and oxidative stress in kidney by the model of high-fat diet (HFD) and primary isolated mouse renal proximal tubule cells treated with a mixture of free fatty acids (FFA). RESULTS: Compared with the chow diet group, HFD-fed WT mice had higher urinary albumin and increased levels of renal fibrosis, glomerulosclerosis, inflammation, oxidative stress and apoptosis in the kidney. These changes were co-related with increased expression of TNF-α in the kidney and were attenuated by TNF-α deficiency. In vitro, accumulation of intracellular lipids induced TNF-α expression and oxidative stress in FFA treated primary proximal tubule cells. However, TNF-α inhibition with siRNA or TNF-α deficiency decreased the lipid induced oxidative stress in these cells. CONCLUSION: These findings suggest that TNF-α plays an important role in the HFD induced kidney damage, and targeting TNF-α and/or its receptors could be a promising therapeutic regimen for progressive nephropathy.

PMANet: a time series forecasting model for Chinese stock price prediction.

Forecasting stock movements is a crucial research endeavor in finance, aiding traders in making informed decisions for enhanced profitability. Utilizing actual stock prices and correlating factors from the Wind platform presents a potent yet intricate forecasting approach. While previous methodologies have explored this avenue, they encounter challenges including limited comprehension of interrelations among stock data elements, diminished accuracy in extensive series, and struggles with anomaly points. This paper introduces an advanced hybrid model for stock price prediction, termed PMANet. PMANet is founded on Multi-scale Timing Feature Attention, amalgamating Multi-scale Timing Feature Convolution and Ant Particle Swarm Optimization. The model elevates the understanding of dependencies and interrelations within stock data sequences through Probabilistic Positional Attention. Furthermore, the Encoder incorporates Multi-scale Timing Feature Convolution, augmenting the model's capacity to discern multi-scale and significant features while adeptly managing lengthy input sequences. Additionally, the model's proficiency in addressing anomaly points in stock sequences is enhanced by substituting the optimizer with Ant Particle Swarm Optimization. To ascertain the model's efficacy and applicability, we conducted an empirical study using stocks from four pivotal industries in China. The experimental outcomes demonstrate that PMANet is both feasible and versatile in its predictive capability, yielding forecasts closely aligned with actual values, thereby fulfilling application requirements more effectively.

Metabolic regulation mechanism of melatonin for reducing cadmium accumulation and improving quality in rice.

Melatonin acts as a potential regulator of cadmium (Cd) tolerance in rice. However, its practical value in rice production remains unclear. To validate the hypothesis that melatonin affects Cd accumulation and rice quality, a series of experiments were conducted. The results showed that exogenous melatonin application was associated with reduced Cd accumulation (23-43%) in brown rice. Fourier transform infrared spectroscopy (FTIR) analysis showed that exogenous melatonin affected the rice protein secondary structure and starch short-range structure. Metabolomics based on LC-MS/MS revealed that exogenous melatonin altered the brown rice metabolic profile, decreased fatty acid metabolite content, but increased amino acid metabolite, citric acid, melatonin biosynthetic metabolite, and plant hormone contents. These findings indicate that exogenous melatonin can effectively reduced Cd accumulation and improve rice quality through metabolic network regulation, serving as an effective treatment for rice cultivated in Cd-contaminated soil.