This year marks the 50th anniversary of the normalization of diplomatic relations between China and Japan.Looking back on the past and forward to the future,we realize modernity has become a critical issue that not on...This year marks the 50th anniversary of the normalization of diplomatic relations between China and Japan.Looking back on the past and forward to the future,we realize modernity has become a critical issue that not only China and Japan,but the whole East Asian region should pay attention to.China and Japan are both within the“Circle of Confucius Culture”and are both modern latecomer countries.As they were coerced by western countries to enter the modern age,they shared multiple common features.An exploration of the two countries’respective rising of modern women’s education is an important path to discuss the reconstruction of gender and an important method of the course of the embodiment of east-Asian women into modernization drives.With regards to conclusion,entering the modern age,Chinese and Japanese intellectuals reshaped the female gender in terms of interpersonal relationship,value system,and knowledge structure by advocating the idea of“virtuous wives and worthy mothers”education.In the concept of virtuous wives and worthy mothers in East Asia,the Confucian ethics of“docility and virtue”is the soul,and modern scientific knowledge serves this core value.On the other hand,in the course of localization in China and Japan,this imported concept from the West has encountered a completely different historical fate.展开更多
Following the discovery of bone as an endocrine organ with systemic influence,bone-brain interaction has emerged as a research hotspot,unveiling complex bidirectional communication between bone and brain.Studies indic...Following the discovery of bone as an endocrine organ with systemic influence,bone-brain interaction has emerged as a research hotspot,unveiling complex bidirectional communication between bone and brain.Studies indicate that bone and brain can influence each other’s homeostasis via multiple pathways,yet there is a dearth of systematic reviews in this area.This review comprehensively examines interactions across three key areas:the influence of bone-derived factors on brain function,the effects of brain-related diseases or injuries(BRDI)on bone health,and the concept of skeletal interoception.Additionally,the review discusses innovative approaches in biomaterial design inspired by bone-brain interaction mechanisms,aiming to facilitate bonebrain interactions through materiobiological effects to aid in the treatment of neurodegenerative and bone-related diseases.Notably,the integration of artificial intelligence(AI)in biomaterial design is highlighted,showcasing AI’s role in expediting the formulation of effective and targeted treatment strategies.In conclusion,this review offers vital insights into the mechanisms of bone-brain interaction and suggests advanced approaches to harness these interactions in clinical practice.These insights offer promising avenues for preventing and treating complex diseases impacting the skeleton and brain,underscoring the potential of interdisciplinary approaches in enhancing human health.展开更多
Opposed multi-burner(OMB)gasification technology is the first large-scale gasification technology developed in China with completely independent intellectual property rights.It has been widely used around the world,in...Opposed multi-burner(OMB)gasification technology is the first large-scale gasification technology developed in China with completely independent intellectual property rights.It has been widely used around the world,involving synthetic ammonia,methanol,ethylene glycol,coal liquefaction,hydrogen production and other fields.This paper summarizes the research and development process of OMB gasification technology from the perspective of the cold model experiment and process simulation,pilotscale study and industrial demonstration.The latest progress of fundamental research in nozzle atomization and dispersion,mixing enhancement of impinging flow,multiscale reaction of different carbonaceous feedstocks,spectral characteristic of impinging flame and particle characteristics inside gasifier,and comprehensive gasification model are reviewed.The latest industrial application progress of ultralarge-scale OMB gasifier and radiant syngas cooler(RSC)combined with quenching chamber OMB gasifier are introduced,and the prospects for the future technical development are proposed as well.展开更多
Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI pre...Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features.In this study,we proposed KG-CNNDTI,a novel knowledge graph-enhanced framework for DTI prediction,which integrates heterogeneous biological information to improve model generalizability and predictive performance.The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm,which were further enriched with contextualized sequence representations obtained from ProteinBERT.For compound representation,multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated.The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor.Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods,particularly in terms of Precision,Recall,F1-Score and area under the precision-recall curve(AUPR).Ablation analysis highlighted the substantial contribution of knowledge graph-derived features.Moreover,KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease,resulting in 40 candidate compounds.5 were supported by literature evidence,among which 3 were further validated in vitro assays.展开更多
The rheological properties of South China Sea （SCS） crude oil were studied. A group of synthetic long-chain polymers, including octadecyl acrylate-maleic anhydride bidodecyl amide copolymer （VR-D）, octadecyl acryl...The rheological properties of South China Sea （SCS） crude oil were studied. A group of synthetic long-chain polymers, including octadecyl acrylate-maleic anhydride bidodecyl amide copolymer （VR-D）, octadecyl acrylate-maleic anhydride bioctadecyl amide copolymer （VR-O） and octadecyl acrylate-maleic anhydride phenly amide copolymer （VR-A）, were employed to serve as viscosity reducers （VRs）. Their performance was evaluated by both experimental and computational methodologies. The results suggest that the SCS crude oil has low wax content yet high resin and asphaltene contents, which lead to high viscosity through formation of association structures. Additionally, the SCS crude oil appears to be a pseudoplastic fluid showing linear shear stress-shear rate dependence at low temperature. Interestingly, it gradually evolves into a Newtonian fluid with exponential relationship between shear stress and shear rate at higher temperature. Synthetic VRs demonstrate desirable and effective performance on improvement of the rheological properties of SCS crude oil. Upon the introduction of 1000ppm VR-O, which is synthesized by using octadecylamine in the aminolysis reaction, the viscosity of SCS crude oil is decreased by 44.2% at 15 ℃ and 40.2% at 40℃. The computational study suggests significant energy level increase and shear stress decrease for VR-containing crude oil systems.展开更多
The rising prevalence of drug-resistant Gram-positive pathogens,particularly methicillin-resistant Staphy-lococcus aureus(MRSA)and vancomycin-resistant Enterococci(VRE),poses a substantial clinical challenge.Biofilm-a...The rising prevalence of drug-resistant Gram-positive pathogens,particularly methicillin-resistant Staphy-lococcus aureus(MRSA)and vancomycin-resistant Enterococci(VRE),poses a substantial clinical challenge.Biofilm-associated infections exacerbate this problem due to their inherent antibiotic resistance and complex structure.Current antibiotic treatments struggle to penetrate biofilms and eradicate persister cells,leading to prolonged antibiotic use and increased resistance.Host defense peptides(HDPs)have shown promise,but their clinical application is limited by factors such as enzymatic degradation and difficulty in largescale preparation.Synthetic HDP mimics,such as poly(2-oxazoline),have emerged as effective alter-natives.Herein,we found that the poly(2-oxazoline),Gly-POX_(20),demonstrated rapid and potent activity against clinically isolated multidrug-resistant Gram-positive strains.Gly-POX_(20) showed greater stability under physiological conditions compared to natural peptides,including resistance to protease degradation.Importantly,Gly-POX_(20) inhibited biofilm formation and eradicated mature biofilm and demonstrated superior in vivo therapeutic efficacy to vancomycin in a MRSA biofilm-associated mouse keratitis model,suggesting its potential as a novel antimicrobial agent against drug-resistant Gram-positive bacteria,especially biofilm-associated infections.展开更多
The treatment of wastewater from pulp-paper plants in China by horseradish peroxidase was investigated in this study. The effects of horseradish peroxidase and coagulants were discussed in detail. The results indica...The treatment of wastewater from pulp-paper plants in China by horseradish peroxidase was investigated in this study. The effects of horseradish peroxidase and coagulants were discussed in detail. The results indicated that enzymes might improve the removal of AOX, TOC and colour for pulp\|paper wastewater and modified chitosan is far more effective than Al\-2(SO\-4)\-3 to remove AOX, TOC and colour.展开更多
The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La a...The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.展开更多
The difficulty in fabricating a multifaceted composite heterojunction system based on Cd_(x) Zn_(1-x) S limits the enhancement of photocatalytic performance.In the present scrutiny,novel ZnO/Cd_(x) Zn_(1-x) S/CdS com-...The difficulty in fabricating a multifaceted composite heterojunction system based on Cd_(x) Zn_(1-x) S limits the enhancement of photocatalytic performance.In the present scrutiny,novel ZnO/Cd_(x) Zn_(1-x) S/CdS com-posite heterojunctions are successfully prepared by the alkaline dissolution etching method.The internal electric field at the interface of I-type and Z-scheme heterojunction improved the effective charge sepa-ration.The ZC 8 sample exhibits excellent photocatalytic performance and the H2 production efficiency is 15.67 mmol g^(−1) h^(−1) with good stability up to 82.9%in 24-hour cycles.The performance of CH_(4) and CO capacity in the CO_(2) RR process is 3.47μmol g^(−1) h^(−1) and 23.5μmol g^(−1) h^(−1),respectively.The photogener-ated accelerated charge transport is then examined in detail by in situ X-ray photoelectron spectroscopy(ISXPS)and density functional theory(DFT)calculations.This work presents a new idea for the synthe-sis of Cd_(x) Zn_(1-x) S solid-solution-based materials and provides a solid reference for the detailed mechanism regarding the electric field at the heterojunction interface.展开更多
1.Introduction In recent years,China has carried out an extensive preventative battle against air,water,and soil pollution,and the nation’s environmental quality-as reflected by conventional pollutant indicators—has...1.Introduction In recent years,China has carried out an extensive preventative battle against air,water,and soil pollution,and the nation’s environmental quality-as reflected by conventional pollutant indicators—has significantly improved.At the same time,the issue of emerging contaminants(ECs)is beginning to receive increasing attention.ECs generally refer to newly discovered or noticeable pollutants that pose risks to the ecological environment or human health.Either they have not been included in environmental management,or existing management measures are insufficient to effectively prevent and control their risks.The ECs of greatest concern generally include persistent organic pollutants(POPs),endocrine-disrupting chemicals(EDCs),pharmaceuticals and personal care products(PPCPs),and microplastics.These four categories of ECs are not entirely separate,as they interrelate with each other(Fig.1).Chemical production and product usage are the main sources of ECs.China is the world’s largest producer and consumer of bulk chemicals,and the production value of China’s chemical industry is predicted to reach 50%of the global total by 2030[1].Scientific control of ECs based on their environmental risk assessment is a necessary way to support the prevention and legal governance of ECs.展开更多
Many strategies have been proposed to produce arenes from lignin as liquid fuel additives.However,the development of these methods is limited by the low yield of products,low atom utilization,and inefficient lignin de...Many strategies have been proposed to produce arenes from lignin as liquid fuel additives.However,the development of these methods is limited by the low yield of products,low atom utilization,and inefficient lignin depolymerization.Herein,we develop an energy-efficient synthetic method for the production of high-carbon-number arenes from sustainable lignin with a total yield of 23.1 wt%.Particularly,high carbon number arenes are obtained by fully utilizing the formaldehyde stabilizing additive and the methoxy group in lignin.The process begins with the reductive depolymerization of formaldehyde-stabilized lignin,followed by transmethylation between lignin monomers over Au/Nb_(2)O_(5) catalyst,and the Ru/Nb2O5-catalyzed hydrodeoxygenation.This work demonstrates the potential of value-added arenes production directly from lignin.展开更多
Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear...Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear programming(MINLP)problem.Considering the large scale of the MINLP model,in order to improve the efficiency of the solution,the mixed integer linear programming-nonlinear programming(MILP-NLP)strategy is used to solve the problem.This paper uses the linear blending rules plus the blending effect correction to build the gasoline blending model,and a relaxed MILP model is constructed on this basis.The particle swarm optimization algorithm with niche technology(NPSO)is proposed to optimize the solution,and the high-precision soft-sensor method is used to calculate the deviation of gasoline attributes,the blending effect is dynamically corrected to ensure the accuracy of the blending effect and optimization results,thus forming a prediction-verification-reprediction closed-loop scheduling optimization strategy suitable for engineering applications.The optimization result of the MILP model provides a good initial point.By fixing the integer variables to the MILPoptimal value,the approximate MINLP optimal solution can be obtained through a NLP solution.The above solution strategy has been successfully applied to the actual gasoline production case of a refinery(3.5 million tons per year),and the results show that the strategy is effective and feasible.The optimization results based on the closed-loop scheduling optimization strategy have higher reliability.Compared with the standard particle swarm optimization algorithm,NPSO algorithm improves the optimization ability and efficiency to a certain extent,effectively reduces the blending cost while ensuring the convergence speed.展开更多
The environmentally friendly and resourceful utilization of organic waste liquid is one of the frontiers of environmental engineering. With the increasing demand for chemicals, the problem of organic waste liq- uid wi...The environmentally friendly and resourceful utilization of organic waste liquid is one of the frontiers of environmental engineering. With the increasing demand for chemicals, the problem of organic waste liq- uid with a high concentration of inorganic pollutants in the processing of petroleum, coal, and natural gas is becoming more serious. In this study, the high-speed self-rotation and flipping of particles in a three- dimensional cyclonic turbulent field was examined using a synchronous high-speed camera technique; the self-rotation speed was found to reach 2000-6000 rad.s 1. Based on these findings, a cyclonic gas- stripping method for the removal of organic matter from the pores of particles was invented. A techno- logical process was developed to recover organic matter from waste liquid by cyclonic gas stripping and classifying inorganic particles by means of airflow acceleration classification. A demonstration device was built in Sinopec＇s first ebullated-bed hydro-treatment unit for residual oil. Compared with the T-STAR fixed-bed gas-stripping technology designed in the United States, the maximum liquid-removal effi- ciency of the catalyst particles in this new process is 44.9% greater at the same temperature, and the time required to realize 95% liquid-removal efficiency is decreased from 1956.5 to 8.4 s. In addition, we achieved the classification and reuse of the catalyst particles contained in waste liquid according to their activity. A proposal to use this new technology was put forward regarding the control of organic waste liquid and the classification recovery of inorganic particles in an ebullated-bed hydro-treatment process for residual oil with a processing capacity of 2×106 t.a^1. It is estimated that the use of this new tech- nology will lead to the recovery of 3100 t.a 1 of diesel fuel and 647 t.a^1 of high-activity catalyst; in addi- tion, it will reduce the consumption of fresh catalyst by 518 t.a^1. The direct economic benefits of this process will be as high as 37.28 million CNY per year.展开更多
The influence of nitrogen-containing polycyclic aromatic hydrocarbons(NC-PAH)on the formation of carbonaceous mesophase remains enigmatic,despite extensive research on the production of carbonaceous materials from aro...The influence of nitrogen-containing polycyclic aromatic hydrocarbons(NC-PAH)on the formation of carbonaceous mesophase remains enigmatic,despite extensive research on the production of carbonaceous materials from aromatic-rich oils.Molecular dynamics simulation was used to investigate the variations in pyrolysis behavior between PAH and NC-PAH based on the composition analysis.Through adjusting the content of NC-PAH,the influence of NC-PAH on the thermal stability of slurry oils(SOs)was evaluated by thermogravimetry,viscosity,coke value,and quinoline insoluble(QI).The morphology and structure of mesocarbon microbeads(MCMBs)prepared with SOs were measured by a polarized-light microscope,SEM,XRD,and Raman.Simulation results indicate that NC-PAH possesses much higher reactivity and tends to produce highly condensed solid and coke products.It corresponds to the QI and high viscosity in thermal stability experiments.Therefore,high concentrations of NC-PAH result in nonuniform morphology and disordered structures.In a system with low viscosity and few QIs,SO,which has a low nitrogen content(475 ppm),reacts gently to produce MCMBs with a uniform particle size(10-40μm)and an excellent spherical shape.As NC-PAH content decreases,the crystalline size of graphitization elevates,as evidenced by parallel layers(10.472-11.764)and stack height(3.269-3.701 nm).The graphitization degree becomes worse and nonuniform with the increase of the content of NC-PAH,and the best is 20.58%evaluated by Raman spectra area ratio(AG/Aall).Overall,this work suggests a nitrogen content reference and a controlling technology of nitrogen for the preparation of superior MCMB.展开更多
Deep Learning has been widely used to model soft sensors in modern industrial processes with nonlinear variables and uncertainty.Due to the outstanding ability for high-level feature extraction,stacked autoencoder(SAE...Deep Learning has been widely used to model soft sensors in modern industrial processes with nonlinear variables and uncertainty.Due to the outstanding ability for high-level feature extraction,stacked autoencoder(SAE)has been widely used to improve the model accuracy of soft sensors.However,with the increase of network layers,SAE may encounter serious information loss issues,which affect the modeling performance of soft sensors.Besides,there are typically very few labeled samples in the data set,which brings challenges to traditional neural networks to solve.In this paper,a multi-scale feature fused stacked autoencoder(MFF-SAE)is suggested for feature representation related to hierarchical output,where stacked autoencoder,mutual information(MI)and multi-scale feature fusion(MFF)strategies are integrated.Based on correlation analysis between output and input variables,critical hidden variables are extracted from the original variables in each autoencoder's input layer,which are correspondingly given varying weights.Besides,an integration strategy based on multi-scale feature fusion is adopted to mitigate the impact of information loss with the deepening of the network layers.Then,the MFF-SAE method is designed and stacked to form deep networks.Two practical industrial processes are utilized to evaluate the performance of MFF-SAE.Results from simulations indicate that in comparison to other cutting-edge techniques,the proposed method may considerably enhance the accuracy of soft sensor modeling,where the suggested method reduces the root mean square error(RMSE)by 71.8%,17.1%and 64.7%,15.1%,respectively.展开更多
Erythroid cells, the predominant circulating blood cells, are essential for oxygen and carbon dioxide transport (Obeagu, 2024).Their production, erythropoiesis, involves the coordinated synthesis of globin chains and ...Erythroid cells, the predominant circulating blood cells, are essential for oxygen and carbon dioxide transport (Obeagu, 2024).Their production, erythropoiesis, involves the coordinated synthesis of globin chains and heme molecules to assemble hemoglobin(Zhang et al., 2021). The erythroid-specific enzyme δ-aminolevulinate synthase 2 (ALAS2) is a key rate-limiting factor in heme biosynthesis,with its expression increasing in late-stage erythropoiesis to meet heme demands (Sadlon et al., 1999). Zebrafish (Danio rerio) is a well-established model for studying erythropoiesis due to its genetic tractability and optical transparency (Zhang and Hamza, 2019;Zhang et al., 2021). The Tol2-mediated Gal4-UAS system has been widely applied for gene and enhancer trapping in zebrafish (Asakawa and Kawakami, 2009). However, reliable Gal4 enhancer-trap lines for erythropoiesis remain limited. Here, we report a transgenic zebrafish line with erythroid-specific Gal4FF expression under the control of the endogenous alas2 promoter, offering a more precise erythroblast labeling than the gata1a reporter line. This model provides a valuable tool for erythroid-specific investigations of blood flow dynamics and gene function.展开更多
Accurate state of health(SOH)estimation is a cornerstone for ensuring the safety,performance and longevity of lithium-ion batteries,especially in electric vehicle(EV)applications.While numerous studies have demonstrat...Accurate state of health(SOH)estimation is a cornerstone for ensuring the safety,performance and longevity of lithium-ion batteries,especially in electric vehicle(EV)applications.While numerous studies have demonstrated the significant advantages of data-driven methods in SOH estimation,most rely on laboratory-standardized test data.This raises concerns about the generalization and robustness of the models under real-world operating conditions,where batteries undergo irregular driving patterns,incomplete charging cycles,and unpredictable environments.Notably,real-world EV data reflects the coupling between battery aging characteristics and actual operating conditions,providing an unprecedented perspective for developing SOH estimation models.This review provides a comprehensive and systematic overview of data-driven SOH estimation using real-world data,a topic that has received increasing attention but lacks a consolidated research framework.The paper begins by reviewing the established SOH estimation methodologies and points out the specific challenges arising from the transition to real-world data.It then probes practical issues across the pipeline:data pre-processing for anomalies,solutions for the lack of labels,feature extraction from complex operating data,machine learning model construction,and performance evaluation across various system deployments.Key insights are presented on how to handle noisy,unlabeled,and heterogeneous data using robust modeling strategies.Moreover,a valuable extension focusing on applying the advancements to battery reuse and recycling is discussed,with the goal of developing a whole lifecycle health diagnosis framework.The paper concludes with promising prospects,encompassing open-source standardized dataset establishment,weakly supervised learning,physics-reinforced modeling,real-world deployment,and advanced sensing technology,emphasizing that real-world data makes the transition of data-driven methods from theoretical validation to industrial deployment promising.This paper aims to assist researchers and practitioners in navigating the complexities of real-world SOH estimation,accelerating the collaborative innovation and industrial adoption in battery health management.展开更多
[2+2]-Type cyclobutane derivatives comprise a large family of natural products with diverse molecular architectures.However,the structure elucidation of the cyclobutane ring,including its connection mode and stereoche...[2+2]-Type cyclobutane derivatives comprise a large family of natural products with diverse molecular architectures.However,the structure elucidation of the cyclobutane ring,including its connection mode and stereochemistry,presents a significant challenge.Plumerubradins A-C(1-3),three novel iridoid glycoside[2+2]dimers featuring a highly functionalized cyclobutane core and multiple stereogenic centers,were isolated from the flowers of Plumeria rubra.Through biomimetic semisynthesis and chemical degradation of compounds 1-3,synthesis of phenylpropanoid-derived[2+2]dimers 7-10,combined with extensive spectroscopic analysis,single-crystal X-ray crystallography,and microcrystal electron diffraction experiments,the structures with absolute configurations of 1-3 were unequivocally elucidated.Furthermore,quantum mechanics-based^(1)H NMR iterative full spin analysis successfully established the correlations between the signal patterns of cyclobutane protons and the structural information of the cyclobutane ring in phenylpropanoid-derived[2+2]dimers,providing a diagnostic tool for the rapid structural elucidation of[2+2]-type cyclobutane derivatives.展开更多
Drying operations are of grave importance to realize the reduction and utilization of sewage sludge resources,but the conventional thermal evaporation drying(TED)technology presents challenges due to the need for a la...Drying operations are of grave importance to realize the reduction and utilization of sewage sludge resources,but the conventional thermal evaporation drying(TED)technology presents challenges due to the need for a large amount of thermal energy to conquer the phase-change latent heat of moisture.Herein,we report a non-phase change technology based on particle high-speed self-rotation in a cyclone for fast,low-temperature drying of viscous sludge with high-moisture contents.Dispersed phase medium(DPM)is introduced into the cyclone self-rotation drying(CSRD)reactor to enhance the dispersion of the viscous sludge.The effects of carrier gas temperature,feeding rate,size,and proportion of DPM particles in the drying process are systematically examined.Under optimal operating conditions,the weighted content of moisture in the viscous sludge could be reduced from 80%to 15.01%in less than 5 s,achieving a high drying efficiency of 95.79%.Theoretical calculations also reveal that 89.26%of the moisture is removed through non-phase change pathway,contributing to a 522-fold increase in the drying rate of CSRD compared to TED technology.This investigation presents a sustainable effective approach for high moisture viscous sludge treatment with low energy consumption and carbon emissions.展开更多
Drug research and development(R&D)plays a crucial role in supporting public health.However,the traditional drug-discovery paradigm is hindered by significant drawbacks,including high costs,lengthy development time...Drug research and development(R&D)plays a crucial role in supporting public health.However,the traditional drug-discovery paradigm is hindered by significant drawbacks,including high costs,lengthy development timelines,high failure rates,and limited output of new drugs.Recent advances in micro/nanotechnology,along with progress in computer science,have positioned microfluidics and artificial intelligence(AI)as promising transformative tools for drug development.Microfluidics offers miniaturized,multiplexed,and versatile platforms for high-dimensional data acquisition,while AI enables the rapid processing of complex,large-scale microfluidic data;together,they are accelerating a paradigm shift in the drug-discovery process.This paper first outlines the mainstream microfluidic strategies and AI models used in drug R&D.It then summarizes and discusses real-world applications of the integrated use of these technologies across various stages of drug discovery,including early drug discovery,drug screening,drug evaluation,drug manufacturing,and drug delivery systems.Finally,the paper examines the main limitations of microfluidics and AI in drug R&D and offers an outlook on the future convergence of these technologies.展开更多
文摘This year marks the 50th anniversary of the normalization of diplomatic relations between China and Japan.Looking back on the past and forward to the future,we realize modernity has become a critical issue that not only China and Japan,but the whole East Asian region should pay attention to.China and Japan are both within the“Circle of Confucius Culture”and are both modern latecomer countries.As they were coerced by western countries to enter the modern age,they shared multiple common features.An exploration of the two countries’respective rising of modern women’s education is an important path to discuss the reconstruction of gender and an important method of the course of the embodiment of east-Asian women into modernization drives.With regards to conclusion,entering the modern age,Chinese and Japanese intellectuals reshaped the female gender in terms of interpersonal relationship,value system,and knowledge structure by advocating the idea of“virtuous wives and worthy mothers”education.In the concept of virtuous wives and worthy mothers in East Asia,the Confucian ethics of“docility and virtue”is the soul,and modern scientific knowledge serves this core value.On the other hand,in the course of localization in China and Japan,this imported concept from the West has encountered a completely different historical fate.
基金financially supported by the Basic Science Center Program(T2288102)the Key Program of the National Natural Science Foundation of China(32230059)+3 种基金the Foundation of Frontiers Science Center for Materiobiology and Dynamic Chemistry(JKVD1211002)the Project supported by the Young Scientists Fund of the National Natural Science Foundation of China(32401128)Postdoctoral Fellowship Program of CPSF(GZC20230793)Shanghai Post-doctoral Excellence Program(2023251).
文摘Following the discovery of bone as an endocrine organ with systemic influence,bone-brain interaction has emerged as a research hotspot,unveiling complex bidirectional communication between bone and brain.Studies indicate that bone and brain can influence each other’s homeostasis via multiple pathways,yet there is a dearth of systematic reviews in this area.This review comprehensively examines interactions across three key areas:the influence of bone-derived factors on brain function,the effects of brain-related diseases or injuries(BRDI)on bone health,and the concept of skeletal interoception.Additionally,the review discusses innovative approaches in biomaterial design inspired by bone-brain interaction mechanisms,aiming to facilitate bonebrain interactions through materiobiological effects to aid in the treatment of neurodegenerative and bone-related diseases.Notably,the integration of artificial intelligence(AI)in biomaterial design is highlighted,showcasing AI’s role in expediting the formulation of effective and targeted treatment strategies.In conclusion,this review offers vital insights into the mechanisms of bone-brain interaction and suggests advanced approaches to harness these interactions in clinical practice.These insights offer promising avenues for preventing and treating complex diseases impacting the skeleton and brain,underscoring the potential of interdisciplinary approaches in enhancing human health.
基金supported by the National Natural Science Foundation of China(21776086,21761132034)。
文摘Opposed multi-burner(OMB)gasification technology is the first large-scale gasification technology developed in China with completely independent intellectual property rights.It has been widely used around the world,involving synthetic ammonia,methanol,ethylene glycol,coal liquefaction,hydrogen production and other fields.This paper summarizes the research and development process of OMB gasification technology from the perspective of the cold model experiment and process simulation,pilotscale study and industrial demonstration.The latest progress of fundamental research in nozzle atomization and dispersion,mixing enhancement of impinging flow,multiscale reaction of different carbonaceous feedstocks,spectral characteristic of impinging flame and particle characteristics inside gasifier,and comprehensive gasification model are reviewed.The latest industrial application progress of ultralarge-scale OMB gasifier and radiant syngas cooler(RSC)combined with quenching chamber OMB gasifier are introduced,and the prospects for the future technical development are proposed as well.
基金supported by the National Natural Science Foundation of China(Nos.82173746 and U23A20530)Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism(Shanghai Municipal Education Commission)。
文摘Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features.In this study,we proposed KG-CNNDTI,a novel knowledge graph-enhanced framework for DTI prediction,which integrates heterogeneous biological information to improve model generalizability and predictive performance.The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm,which were further enriched with contextualized sequence representations obtained from ProteinBERT.For compound representation,multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated.The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor.Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods,particularly in terms of Precision,Recall,F1-Score and area under the precision-recall curve(AUPR).Ablation analysis highlighted the substantial contribution of knowledge graph-derived features.Moreover,KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease,resulting in 40 candidate compounds.5 were supported by literature evidence,among which 3 were further validated in vitro assays.
基金financially supported by the Training Program of the Major Research Plan of the National Natural Science Foundation of China(grant no.91634112)the Natural Science Foundation of Shanghai(grant no.16ZR1408100)+2 种基金the Fundamental Research Funds for the Central Universities of China(grant no.22A201514010)the Open Project of State Key Laboratory of Chemical Engineering(SKL-Ch E-16C01)the institutional funds from the Gene and Linda Voiland School of Chemical Engineering and Bioengineering at Washington State University
文摘The rheological properties of South China Sea （SCS） crude oil were studied. A group of synthetic long-chain polymers, including octadecyl acrylate-maleic anhydride bidodecyl amide copolymer （VR-D）, octadecyl acrylate-maleic anhydride bioctadecyl amide copolymer （VR-O） and octadecyl acrylate-maleic anhydride phenly amide copolymer （VR-A）, were employed to serve as viscosity reducers （VRs）. Their performance was evaluated by both experimental and computational methodologies. The results suggest that the SCS crude oil has low wax content yet high resin and asphaltene contents, which lead to high viscosity through formation of association structures. Additionally, the SCS crude oil appears to be a pseudoplastic fluid showing linear shear stress-shear rate dependence at low temperature. Interestingly, it gradually evolves into a Newtonian fluid with exponential relationship between shear stress and shear rate at higher temperature. Synthetic VRs demonstrate desirable and effective performance on improvement of the rheological properties of SCS crude oil. Upon the introduction of 1000ppm VR-O, which is synthesized by using octadecylamine in the aminolysis reaction, the viscosity of SCS crude oil is decreased by 44.2% at 15 ℃ and 40.2% at 40℃. The computational study suggests significant energy level increase and shear stress decrease for VR-containing crude oil systems.
基金financially supported by the National Key Research and Development Program of China(no.2022YFC2303100)National Natural Science Foundation of China(nos.T2325010,22305082,52203162,and 22075078)+1 种基金Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism(Shanghai Municipal Education Commission),the Fundamental Research Funds for the Central Universities(nos.JKVD1241029 and JKD01241701)Open Research Fund of State Key Laboratory of Polymer Physics and Chemistry(Changchun Institute of Applied Chemistry,Chinese Academy of Sciences),the Open Project of Engineering Research Center of Dairy Quality and Safety Control Technology(Ministry of Education,no.R202201).
文摘The rising prevalence of drug-resistant Gram-positive pathogens,particularly methicillin-resistant Staphy-lococcus aureus(MRSA)and vancomycin-resistant Enterococci(VRE),poses a substantial clinical challenge.Biofilm-associated infections exacerbate this problem due to their inherent antibiotic resistance and complex structure.Current antibiotic treatments struggle to penetrate biofilms and eradicate persister cells,leading to prolonged antibiotic use and increased resistance.Host defense peptides(HDPs)have shown promise,but their clinical application is limited by factors such as enzymatic degradation and difficulty in largescale preparation.Synthetic HDP mimics,such as poly(2-oxazoline),have emerged as effective alter-natives.Herein,we found that the poly(2-oxazoline),Gly-POX_(20),demonstrated rapid and potent activity against clinically isolated multidrug-resistant Gram-positive strains.Gly-POX_(20) showed greater stability under physiological conditions compared to natural peptides,including resistance to protease degradation.Importantly,Gly-POX_(20) inhibited biofilm formation and eradicated mature biofilm and demonstrated superior in vivo therapeutic efficacy to vancomycin in a MRSA biofilm-associated mouse keratitis model,suggesting its potential as a novel antimicrobial agent against drug-resistant Gram-positive bacteria,especially biofilm-associated infections.
文摘The treatment of wastewater from pulp-paper plants in China by horseradish peroxidase was investigated in this study. The effects of horseradish peroxidase and coagulants were discussed in detail. The results indicated that enzymes might improve the removal of AOX, TOC and colour for pulp\|paper wastewater and modified chitosan is far more effective than Al\-2(SO\-4)\-3 to remove AOX, TOC and colour.
基金financially supported by the National Key R &D Program of China (No.2022YFB3709300)。
文摘The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.
基金financially supported by the National Key Re-search and Development Program of China[No.2022YFF1202500,2022YFF1202502]the National Natural Science Foundation of China[62071459]+1 种基金the Subject arrangement Foundation of Shen-zhen[No.JCYJ20180507182057026]the International Science and Technology Cooperation Project of Bingtuan[No.2022BC008]。
文摘The difficulty in fabricating a multifaceted composite heterojunction system based on Cd_(x) Zn_(1-x) S limits the enhancement of photocatalytic performance.In the present scrutiny,novel ZnO/Cd_(x) Zn_(1-x) S/CdS com-posite heterojunctions are successfully prepared by the alkaline dissolution etching method.The internal electric field at the interface of I-type and Z-scheme heterojunction improved the effective charge sepa-ration.The ZC 8 sample exhibits excellent photocatalytic performance and the H2 production efficiency is 15.67 mmol g^(−1) h^(−1) with good stability up to 82.9%in 24-hour cycles.The performance of CH_(4) and CO capacity in the CO_(2) RR process is 3.47μmol g^(−1) h^(−1) and 23.5μmol g^(−1) h^(−1),respectively.The photogener-ated accelerated charge transport is then examined in detail by in situ X-ray photoelectron spectroscopy(ISXPS)and density functional theory(DFT)calculations.This work presents a new idea for the synthe-sis of Cd_(x) Zn_(1-x) S solid-solution-based materials and provides a solid reference for the detailed mechanism regarding the electric field at the heterojunction interface.
基金supported by the Major Project of National Natural Science Foundation of China(52091544).
文摘1.Introduction In recent years,China has carried out an extensive preventative battle against air,water,and soil pollution,and the nation’s environmental quality-as reflected by conventional pollutant indicators—has significantly improved.At the same time,the issue of emerging contaminants(ECs)is beginning to receive increasing attention.ECs generally refer to newly discovered or noticeable pollutants that pose risks to the ecological environment or human health.Either they have not been included in environmental management,or existing management measures are insufficient to effectively prevent and control their risks.The ECs of greatest concern generally include persistent organic pollutants(POPs),endocrine-disrupting chemicals(EDCs),pharmaceuticals and personal care products(PPCPs),and microplastics.These four categories of ECs are not entirely separate,as they interrelate with each other(Fig.1).Chemical production and product usage are the main sources of ECs.China is the world’s largest producer and consumer of bulk chemicals,and the production value of China’s chemical industry is predicted to reach 50%of the global total by 2030[1].Scientific control of ECs based on their environmental risk assessment is a necessary way to support the prevention and legal governance of ECs.
文摘Many strategies have been proposed to produce arenes from lignin as liquid fuel additives.However,the development of these methods is limited by the low yield of products,low atom utilization,and inefficient lignin depolymerization.Herein,we develop an energy-efficient synthetic method for the production of high-carbon-number arenes from sustainable lignin with a total yield of 23.1 wt%.Particularly,high carbon number arenes are obtained by fully utilizing the formaldehyde stabilizing additive and the methoxy group in lignin.The process begins with the reductive depolymerization of formaldehyde-stabilized lignin,followed by transmethylation between lignin monomers over Au/Nb_(2)O_(5) catalyst,and the Ru/Nb2O5-catalyzed hydrodeoxygenation.This work demonstrates the potential of value-added arenes production directly from lignin.
基金supported by National Natural Science Foundation of China(Basic Science Center Program:61988101)Shanghai Committee of Science and Technology(22DZ1101500)+1 种基金the National Natural Science Foundation of China(61973124,62073142)Fundamental Research Funds for the Central Universities。
文摘Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear programming(MINLP)problem.Considering the large scale of the MINLP model,in order to improve the efficiency of the solution,the mixed integer linear programming-nonlinear programming(MILP-NLP)strategy is used to solve the problem.This paper uses the linear blending rules plus the blending effect correction to build the gasoline blending model,and a relaxed MILP model is constructed on this basis.The particle swarm optimization algorithm with niche technology(NPSO)is proposed to optimize the solution,and the high-precision soft-sensor method is used to calculate the deviation of gasoline attributes,the blending effect is dynamically corrected to ensure the accuracy of the blending effect and optimization results,thus forming a prediction-verification-reprediction closed-loop scheduling optimization strategy suitable for engineering applications.The optimization result of the MILP model provides a good initial point.By fixing the integer variables to the MILPoptimal value,the approximate MINLP optimal solution can be obtained through a NLP solution.The above solution strategy has been successfully applied to the actual gasoline production case of a refinery(3.5 million tons per year),and the results show that the strategy is effective and feasible.The optimization results based on the closed-loop scheduling optimization strategy have higher reliability.Compared with the standard particle swarm optimization algorithm,NPSO algorithm improves the optimization ability and efficiency to a certain extent,effectively reduces the blending cost while ensuring the convergence speed.
基金This work was supported by the sponsorship of the National Science Foundation for Distinguished Young Scholars of China （51125032）, the sponsorship of the National Key Research and Development Program of China （2016YFC0204500）, and the National Natural Science Foundation of China （51608203）.
文摘The environmentally friendly and resourceful utilization of organic waste liquid is one of the frontiers of environmental engineering. With the increasing demand for chemicals, the problem of organic waste liq- uid with a high concentration of inorganic pollutants in the processing of petroleum, coal, and natural gas is becoming more serious. In this study, the high-speed self-rotation and flipping of particles in a three- dimensional cyclonic turbulent field was examined using a synchronous high-speed camera technique; the self-rotation speed was found to reach 2000-6000 rad.s 1. Based on these findings, a cyclonic gas- stripping method for the removal of organic matter from the pores of particles was invented. A techno- logical process was developed to recover organic matter from waste liquid by cyclonic gas stripping and classifying inorganic particles by means of airflow acceleration classification. A demonstration device was built in Sinopec＇s first ebullated-bed hydro-treatment unit for residual oil. Compared with the T-STAR fixed-bed gas-stripping technology designed in the United States, the maximum liquid-removal effi- ciency of the catalyst particles in this new process is 44.9% greater at the same temperature, and the time required to realize 95% liquid-removal efficiency is decreased from 1956.5 to 8.4 s. In addition, we achieved the classification and reuse of the catalyst particles contained in waste liquid according to their activity. A proposal to use this new technology was put forward regarding the control of organic waste liquid and the classification recovery of inorganic particles in an ebullated-bed hydro-treatment process for residual oil with a processing capacity of 2×106 t.a^1. It is estimated that the use of this new tech- nology will lead to the recovery of 3100 t.a 1 of diesel fuel and 647 t.a^1 of high-activity catalyst; in addi- tion, it will reduce the consumption of fresh catalyst by 518 t.a^1. The direct economic benefits of this process will be as high as 37.28 million CNY per year.
基金support of National Natural Science Foundation of P.R.China(22308104).
文摘The influence of nitrogen-containing polycyclic aromatic hydrocarbons(NC-PAH)on the formation of carbonaceous mesophase remains enigmatic,despite extensive research on the production of carbonaceous materials from aromatic-rich oils.Molecular dynamics simulation was used to investigate the variations in pyrolysis behavior between PAH and NC-PAH based on the composition analysis.Through adjusting the content of NC-PAH,the influence of NC-PAH on the thermal stability of slurry oils(SOs)was evaluated by thermogravimetry,viscosity,coke value,and quinoline insoluble(QI).The morphology and structure of mesocarbon microbeads(MCMBs)prepared with SOs were measured by a polarized-light microscope,SEM,XRD,and Raman.Simulation results indicate that NC-PAH possesses much higher reactivity and tends to produce highly condensed solid and coke products.It corresponds to the QI and high viscosity in thermal stability experiments.Therefore,high concentrations of NC-PAH result in nonuniform morphology and disordered structures.In a system with low viscosity and few QIs,SO,which has a low nitrogen content(475 ppm),reacts gently to produce MCMBs with a uniform particle size(10-40μm)and an excellent spherical shape.As NC-PAH content decreases,the crystalline size of graphitization elevates,as evidenced by parallel layers(10.472-11.764)and stack height(3.269-3.701 nm).The graphitization degree becomes worse and nonuniform with the increase of the content of NC-PAH,and the best is 20.58%evaluated by Raman spectra area ratio(AG/Aall).Overall,this work suggests a nitrogen content reference and a controlling technology of nitrogen for the preparation of superior MCMB.
基金supported by the National Key Research and Development Program of China(2023YFB3307800)National Natural Science Foundation of China(62394343,62373155)+2 种基金Major Science and Technology Project of Xinjiang(No.2022A01006-4)State Key Laboratory of Industrial Control Technology,China(Grant No.ICT2024A26)Fundamental Research Funds for the Central Universities.
文摘Deep Learning has been widely used to model soft sensors in modern industrial processes with nonlinear variables and uncertainty.Due to the outstanding ability for high-level feature extraction,stacked autoencoder(SAE)has been widely used to improve the model accuracy of soft sensors.However,with the increase of network layers,SAE may encounter serious information loss issues,which affect the modeling performance of soft sensors.Besides,there are typically very few labeled samples in the data set,which brings challenges to traditional neural networks to solve.In this paper,a multi-scale feature fused stacked autoencoder(MFF-SAE)is suggested for feature representation related to hierarchical output,where stacked autoencoder,mutual information(MI)and multi-scale feature fusion(MFF)strategies are integrated.Based on correlation analysis between output and input variables,critical hidden variables are extracted from the original variables in each autoencoder's input layer,which are correspondingly given varying weights.Besides,an integration strategy based on multi-scale feature fusion is adopted to mitigate the impact of information loss with the deepening of the network layers.Then,the MFF-SAE method is designed and stacked to form deep networks.Two practical industrial processes are utilized to evaluate the performance of MFF-SAE.Results from simulations indicate that in comparison to other cutting-edge techniques,the proposed method may considerably enhance the accuracy of soft sensor modeling,where the suggested method reduces the root mean square error(RMSE)by 71.8%,17.1%and 64.7%,15.1%,respectively.
基金supported by the National Key Research and Development Plan of China (2023YFA1802000)the National Natural Science Foundation of China for Distinguished Young Scholars (31925014),the National Natural Science Foundation of China Key Program (32130033),the National Natural Science Foundation of Original Exploratory Program (32350006)+5 种基金the Key Research Program of Frontier Sciences,Chinese Academy of Sciences (ZDBS-LY-SM010)Shanghai Pilot Program for Basic Research-Chinese Academy of Sciences,Shanghai Branch (JCYJ-SHFY-2022-006)Shanghai Science Technology Innovation Action Plan for Basic Research Program (21JC1406300)Haihe laboratory of Cell Ecosystem Innovation Fund (24HHXBSS00011)CAS project for Young Scientists in Basic Research (YSBR-077)supported by Science and Technology Commission of Shanghai Municipality (Shanghai Rising-Star Program,23QA1411300)
文摘Erythroid cells, the predominant circulating blood cells, are essential for oxygen and carbon dioxide transport (Obeagu, 2024).Their production, erythropoiesis, involves the coordinated synthesis of globin chains and heme molecules to assemble hemoglobin(Zhang et al., 2021). The erythroid-specific enzyme δ-aminolevulinate synthase 2 (ALAS2) is a key rate-limiting factor in heme biosynthesis,with its expression increasing in late-stage erythropoiesis to meet heme demands (Sadlon et al., 1999). Zebrafish (Danio rerio) is a well-established model for studying erythropoiesis due to its genetic tractability and optical transparency (Zhang and Hamza, 2019;Zhang et al., 2021). The Tol2-mediated Gal4-UAS system has been widely applied for gene and enhancer trapping in zebrafish (Asakawa and Kawakami, 2009). However, reliable Gal4 enhancer-trap lines for erythropoiesis remain limited. Here, we report a transgenic zebrafish line with erythroid-specific Gal4FF expression under the control of the endogenous alas2 promoter, offering a more precise erythroblast labeling than the gata1a reporter line. This model provides a valuable tool for erythroid-specific investigations of blood flow dynamics and gene function.
基金supported by the National Natural Science Foundation of China(52375144 and 52205153)the Shanghai Pujiang Programme(23PJD019)the Shanghai Gaofeng Project for University Academic Program Development。
文摘Accurate state of health(SOH)estimation is a cornerstone for ensuring the safety,performance and longevity of lithium-ion batteries,especially in electric vehicle(EV)applications.While numerous studies have demonstrated the significant advantages of data-driven methods in SOH estimation,most rely on laboratory-standardized test data.This raises concerns about the generalization and robustness of the models under real-world operating conditions,where batteries undergo irregular driving patterns,incomplete charging cycles,and unpredictable environments.Notably,real-world EV data reflects the coupling between battery aging characteristics and actual operating conditions,providing an unprecedented perspective for developing SOH estimation models.This review provides a comprehensive and systematic overview of data-driven SOH estimation using real-world data,a topic that has received increasing attention but lacks a consolidated research framework.The paper begins by reviewing the established SOH estimation methodologies and points out the specific challenges arising from the transition to real-world data.It then probes practical issues across the pipeline:data pre-processing for anomalies,solutions for the lack of labels,feature extraction from complex operating data,machine learning model construction,and performance evaluation across various system deployments.Key insights are presented on how to handle noisy,unlabeled,and heterogeneous data using robust modeling strategies.Moreover,a valuable extension focusing on applying the advancements to battery reuse and recycling is discussed,with the goal of developing a whole lifecycle health diagnosis framework.The paper concludes with promising prospects,encompassing open-source standardized dataset establishment,weakly supervised learning,physics-reinforced modeling,real-world deployment,and advanced sensing technology,emphasizing that real-world data makes the transition of data-driven methods from theoretical validation to industrial deployment promising.This paper aims to assist researchers and practitioners in navigating the complexities of real-world SOH estimation,accelerating the collaborative innovation and industrial adoption in battery health management.
基金supported by the National Key R&D Program of China(No.2023YFC3503902)the National Natural Science Foundation of China(Nos.82293681(82293680)and 82321004)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(Nos.2022B1515120015 and 2021A1515111021)the Guangdong Major Project of Basic and Applied Basic Research(No.2023B0303000026)the Science and Technology Projects in Guangzhou(No.202102070001).
文摘[2+2]-Type cyclobutane derivatives comprise a large family of natural products with diverse molecular architectures.However,the structure elucidation of the cyclobutane ring,including its connection mode and stereochemistry,presents a significant challenge.Plumerubradins A-C(1-3),three novel iridoid glycoside[2+2]dimers featuring a highly functionalized cyclobutane core and multiple stereogenic centers,were isolated from the flowers of Plumeria rubra.Through biomimetic semisynthesis and chemical degradation of compounds 1-3,synthesis of phenylpropanoid-derived[2+2]dimers 7-10,combined with extensive spectroscopic analysis,single-crystal X-ray crystallography,and microcrystal electron diffraction experiments,the structures with absolute configurations of 1-3 were unequivocally elucidated.Furthermore,quantum mechanics-based^(1)H NMR iterative full spin analysis successfully established the correlations between the signal patterns of cyclobutane protons and the structural information of the cyclobutane ring in phenylpropanoid-derived[2+2]dimers,providing a diagnostic tool for the rapid structural elucidation of[2+2]-type cyclobutane derivatives.
基金supported by the National Key Research and Development Program of China(2019YFA0705800)the National Natural Science Foundation of China(52030001)the Science&Technology Commission of Shanghai Municipality(20dz1207600).
文摘Drying operations are of grave importance to realize the reduction and utilization of sewage sludge resources,but the conventional thermal evaporation drying(TED)technology presents challenges due to the need for a large amount of thermal energy to conquer the phase-change latent heat of moisture.Herein,we report a non-phase change technology based on particle high-speed self-rotation in a cyclone for fast,low-temperature drying of viscous sludge with high-moisture contents.Dispersed phase medium(DPM)is introduced into the cyclone self-rotation drying(CSRD)reactor to enhance the dispersion of the viscous sludge.The effects of carrier gas temperature,feeding rate,size,and proportion of DPM particles in the drying process are systematically examined.Under optimal operating conditions,the weighted content of moisture in the viscous sludge could be reduced from 80%to 15.01%in less than 5 s,achieving a high drying efficiency of 95.79%.Theoretical calculations also reveal that 89.26%of the moisture is removed through non-phase change pathway,contributing to a 522-fold increase in the drying rate of CSRD compared to TED technology.This investigation presents a sustainable effective approach for high moisture viscous sludge treatment with low energy consumption and carbon emissions.
基金s supported by the National Natural Science Foundation of China(82425104)the National Key Research and Development Program of China(2022YFC3400501).
文摘Drug research and development(R&D)plays a crucial role in supporting public health.However,the traditional drug-discovery paradigm is hindered by significant drawbacks,including high costs,lengthy development timelines,high failure rates,and limited output of new drugs.Recent advances in micro/nanotechnology,along with progress in computer science,have positioned microfluidics and artificial intelligence(AI)as promising transformative tools for drug development.Microfluidics offers miniaturized,multiplexed,and versatile platforms for high-dimensional data acquisition,while AI enables the rapid processing of complex,large-scale microfluidic data;together,they are accelerating a paradigm shift in the drug-discovery process.This paper first outlines the mainstream microfluidic strategies and AI models used in drug R&D.It then summarizes and discusses real-world applications of the integrated use of these technologies across various stages of drug discovery,including early drug discovery,drug screening,drug evaluation,drug manufacturing,and drug delivery systems.Finally,the paper examines the main limitations of microfluidics and AI in drug R&D and offers an outlook on the future convergence of these technologies.
