As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,t...As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,traceability and tamper-proof features,is an importantway to achieve efficient consumption andmulti-party supply of new energy.In this article,we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’revenue,consider the degree of microgrid users’preference for electricity thus increasing users’reliance on the blockchainmarket,and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue.The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.展开更多
Chromium released during municipal solid waste incineration(MSWI)is toxic and carcinogenic.The removal of chromium from simulated MSWI flue gas by four sorbents(CaO,bamboo charcoal(BC),powdered activated carbon(PAC),a...Chromium released during municipal solid waste incineration(MSWI)is toxic and carcinogenic.The removal of chromium from simulated MSWI flue gas by four sorbents(CaO,bamboo charcoal(BC),powdered activated carbon(PAC),and Al_(2)O_(3))and the effects of four oxides(SiO_(2),Al_(2)O_(3),Fe_(2)O_(3),and CaO)on chromium speciation transformationwere investigated.The results showed that the removal rates of total Cr by the four sorbents were Al_(2)O_(3)<CaO<PAC<BC,while the removal rates of Cr(Ⅵ)by the four sorbents were Al_(2)O_(3)<PAC<BC<CaO.CaO had a strong oxidizing effect on Cr(Ⅲ),while BC and PAC had a better-reducing effect on Cr(Ⅵ).SiO_(2)was better for the reduction of Na_(2)CrO_(4)and K_(2)CrO_(4)above 1000℃due to its strong acidity,and the addition of CaO significantly inhibited the reduction of Cr(Ⅵ).MgCrO_(4)decomposed above 700℃to form MgCr_(2)O_(4),and the reaction between MgCrO_(4)and oxides also existed in the form of a more stable trivalent spinel.Furthermore,when investigating the effect of oxides on the oxidation of Cr(Ⅲ)in CrC_(l3),it was discovered that CaO promoted the conversion of Cr(Ⅲ)to Cr(Ⅵ),while the presence of chlorine caused chromium to exist in the form of Cr(V),and increasing the content of CaO and extending the heating time facilitated the oxidation of Cr(Ⅲ).In addition,silicate,aluminate,and ferrite were generated after the addition of SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),which reduced the alkalinity of CaO and had an important role in inhibiting the oxidation of Cr(Ⅲ).The acidic oxides can not only promote the reduction of Cr(Ⅵ)but also have an inhibitory effect on the oxidation of Cr(Ⅲ)ascribed to alkali metals/alkaline earth metals,and the proportion of acidic oxides can be increased moderately to reduce the generation of harmful substances in the hazardous solid waste heat treatment.展开更多
Proteins secreted by Gram-negative bacteria are tightly linked to the virulence and adaptability of these microbes to environmental changes.Accurate identification of such secreted proteins can facilitate the investig...Proteins secreted by Gram-negative bacteria are tightly linked to the virulence and adaptability of these microbes to environmental changes.Accurate identification of such secreted proteins can facilitate the investigations of infections and diseases caused by these bacterial pathogens.However,current bioinformatic methods for predicting bacterial secreted substrate proteins have limited computational efficiency and application scope on a genome-wide scale.Here,we propose a novel deep-learning-based framework—DeepSecE—for the simultaneous inference of multiple distinct groups of secreted proteins produced by Gram-negative bacteria.DeepSecE remarkably improves their classification from nonsecreted proteins using a pretrained protein language model and transformer,achieving a macro-average accuracy of 0.883 on 5-fold cross-validation.Performance benchmarking suggests that DeepSecE achieves competitive performance with the state-of-the-art binary predictors specialized for individual types of secreted substrates.The attention mechanism corroborates salient patterns and motifs at the N or C termini of the protein sequences.Using this pipeline,we further investigate the genome-wide prediction of novel secreted proteins and their taxonomic distribution across~1,000 Gram-negative bacterial genomes.The present analysis demonstrates that DeepSecE has major potential for the discovery of disease-associated secreted proteins in a diverse range of Gram-negative bacteria.An online web server of DeepSecE is also publicly available to predict and explore various secreted substrate proteins via the input of bacterial genome sequences.展开更多
基金This research was funded by the NSFC under Grant No.61803279in part by the Qing Lan Project of Jiangsu,in part by the China Postdoctoral Science Foundation under Grant Nos.2020M671596 and 2021M692369+3 种基金in part by the Suzhou Science and Technology Development Plan Project(Key Industry Technology Innovation)under Grant No.SYG202114in part by the Open Project Funding from Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving,Anhui Jianzhu University,under Grant No.IBES2021KF08in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.KYCX23_3320in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.SJCX22_1585.
文摘As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,traceability and tamper-proof features,is an importantway to achieve efficient consumption andmulti-party supply of new energy.In this article,we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’revenue,consider the degree of microgrid users’preference for electricity thus increasing users’reliance on the blockchainmarket,and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue.The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.
基金supported by the National R&D Program Project of China(No.2019YFC1907000)the Key Research and Development Program of Hubei Province(No.2020BCA076)+1 种基金the Natural Sciences Foundation of China(No.52176127)Natural Science Foundation of Hubei Province(No.2022CFB045)。
文摘Chromium released during municipal solid waste incineration(MSWI)is toxic and carcinogenic.The removal of chromium from simulated MSWI flue gas by four sorbents(CaO,bamboo charcoal(BC),powdered activated carbon(PAC),and Al_(2)O_(3))and the effects of four oxides(SiO_(2),Al_(2)O_(3),Fe_(2)O_(3),and CaO)on chromium speciation transformationwere investigated.The results showed that the removal rates of total Cr by the four sorbents were Al_(2)O_(3)<CaO<PAC<BC,while the removal rates of Cr(Ⅵ)by the four sorbents were Al_(2)O_(3)<PAC<BC<CaO.CaO had a strong oxidizing effect on Cr(Ⅲ),while BC and PAC had a better-reducing effect on Cr(Ⅵ).SiO_(2)was better for the reduction of Na_(2)CrO_(4)and K_(2)CrO_(4)above 1000℃due to its strong acidity,and the addition of CaO significantly inhibited the reduction of Cr(Ⅵ).MgCrO_(4)decomposed above 700℃to form MgCr_(2)O_(4),and the reaction between MgCrO_(4)and oxides also existed in the form of a more stable trivalent spinel.Furthermore,when investigating the effect of oxides on the oxidation of Cr(Ⅲ)in CrC_(l3),it was discovered that CaO promoted the conversion of Cr(Ⅲ)to Cr(Ⅵ),while the presence of chlorine caused chromium to exist in the form of Cr(V),and increasing the content of CaO and extending the heating time facilitated the oxidation of Cr(Ⅲ).In addition,silicate,aluminate,and ferrite were generated after the addition of SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),which reduced the alkalinity of CaO and had an important role in inhibiting the oxidation of Cr(Ⅲ).The acidic oxides can not only promote the reduction of Cr(Ⅵ)but also have an inhibitory effect on the oxidation of Cr(Ⅲ)ascribed to alkali metals/alkaline earth metals,and the proportion of acidic oxides can be increased moderately to reduce the generation of harmful substances in the hazardous solid waste heat treatment.
基金the National Natural Science Foundation of China(32070572)the Foundation of Key Laboratory of Veterinary Biotechnology(shklab202005)+1 种基金Shanghai,China,and the Science and Technology Commission of Shanghai Municipality(19JC1413000)R.B.G.and J.S.were supported by grants from the Australian Research Council(ARC)(LP220200614).
文摘Proteins secreted by Gram-negative bacteria are tightly linked to the virulence and adaptability of these microbes to environmental changes.Accurate identification of such secreted proteins can facilitate the investigations of infections and diseases caused by these bacterial pathogens.However,current bioinformatic methods for predicting bacterial secreted substrate proteins have limited computational efficiency and application scope on a genome-wide scale.Here,we propose a novel deep-learning-based framework—DeepSecE—for the simultaneous inference of multiple distinct groups of secreted proteins produced by Gram-negative bacteria.DeepSecE remarkably improves their classification from nonsecreted proteins using a pretrained protein language model and transformer,achieving a macro-average accuracy of 0.883 on 5-fold cross-validation.Performance benchmarking suggests that DeepSecE achieves competitive performance with the state-of-the-art binary predictors specialized for individual types of secreted substrates.The attention mechanism corroborates salient patterns and motifs at the N or C termini of the protein sequences.Using this pipeline,we further investigate the genome-wide prediction of novel secreted proteins and their taxonomic distribution across~1,000 Gram-negative bacterial genomes.The present analysis demonstrates that DeepSecE has major potential for the discovery of disease-associated secreted proteins in a diverse range of Gram-negative bacteria.An online web server of DeepSecE is also publicly available to predict and explore various secreted substrate proteins via the input of bacterial genome sequences.
