Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also th...Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.展开更多
A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linea...A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.展开更多
Protein aggregation has been linked with many neurodegenerative diseases,such as Alzheimer’s disease(AD)or Parkinson’s disease.AD belongs to a group of heterogeneous and incurable neurodegenerative disorders collect...Protein aggregation has been linked with many neurodegenerative diseases,such as Alzheimer’s disease(AD)or Parkinson’s disease.AD belongs to a group of heterogeneous and incurable neurodegenerative disorders collectively known as tauopathies.They comprise frontotemporal dementia,Pick’s disease,or corticobasal degeneration,among others.The symptomatology varies with the specific tau protein variant involved and the affected brain region or cell type.However,they share a common neuropathological hallmark-the formation of proteinaceous deposits named neurofibrillary tangles.Neurofibrillary tangles,primarily composed of aggregated tau(Zhang et al.,2022),disrupt normal neuronal functions,leading to cell death and cognitive decline.展开更多
Parkinson's disease(PD),a prevalent neurodegenerative disorder,is chara cterized by the loss of dopaminergic neurons and the aggregation ofα-synuclein protein into Lewy bodies.While the current standards of thera...Parkinson's disease(PD),a prevalent neurodegenerative disorder,is chara cterized by the loss of dopaminergic neurons and the aggregation ofα-synuclein protein into Lewy bodies.While the current standards of therapy have been successful in providing some symptom relief,they fail to address the underlying pathophysiology of PD and as a result,they have no effect on disease progression.展开更多
With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals.Support vector machine(SVM)is one of the most...With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals.Support vector machine(SVM)is one of the most elementary learning models of machine learning.Privacy issues surrounding SVM classifier training have attracted increasing attention.In this paper,we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction,called FedDPDR-DPML,which greatly improves data utility while providing strong privacy guarantees.Considering in distributed learning scenarios,multiple participants usually hold unbalanced or small amounts of data.Therefore,FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted model averaging and knowledge aggregation and then the server distributes the global model to each participant to improve local data utility.Aiming at high-dimensional data,we adopt differential privacy in both the principal component analysis(PCA)-based dimensionality reduction phase and SVM classifiers training phase,which improves model accuracy while achieving strict differential privacy protection.Besides,we train Differential privacy(DP)-compliant SVM classifiers by adding noise to the objective function itself,thus leading to better data utility.Extensive experiments on three high-dimensional datasets demonstrate that FedDPDR-DPML can achieve high accuracy while ensuring strong privacy protection.展开更多
Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cott...Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.展开更多
Occurrence of neurofibrillary tangles of the tau protein is a hallmark of tau-related neurodegenerative diseases, i.e. Alzheimer's disease(AD) and frontotemporal dementia. The pathological mechanism underlying AD ...Occurrence of neurofibrillary tangles of the tau protein is a hallmark of tau-related neurodegenerative diseases, i.e. Alzheimer's disease(AD) and frontotemporal dementia. The pathological mechanism underlying AD remains poorly understood, and effective treatments are still unavailable to mitigate the disease.Inhibiting of tau aggregation and disrupting the existing fibrils are key targets in drug discovery towards preventing or curing AD. In this study, grape seed proanthocyanidins(GSPs) was found to effectively inhibit the repeat domain of tau(tau-RD) aggregation and disaggregate tau-RD fibrils in a concentrationdependent manner by inhibiting β-sheet formation of tau-RD. In cells, GSPs relieved cytotoxicity induced by tau-RD aggregates. Molecular dynamics simulations indicated that strong hydrogen bonding,hydrophobic interaction and π-π stacking between GSPs and tau-RD protein were major reasons why GSPs had high inhibitory activity on tau-RD fibrillogenesis. These results provide preliminary data to develop GSPs into medicines, foodstuffs or nutritional supplements for AD patients, suggesting that GSPs could be a candidate molecule in the drug design for AD therapeutics.展开更多
Deposition of β-amyloid protein(Aβ) is the main hallmark of Alzheimer's disease(AD), and it has been well recognized that Cu^(2+)-mediated Aβ aggregation plays a crucial role in AD pathological processes.Cu^(2+...Deposition of β-amyloid protein(Aβ) is the main hallmark of Alzheimer's disease(AD), and it has been well recognized that Cu^(2+)-mediated Aβ aggregation plays a crucial role in AD pathological processes.Cu^(2+)binding to Aβ can promote the production of reactive oxygen species(ROS) through Fenton-like reactions and produce more toxic Aβ-Cu^(2+)species under Cu^(2+)stimulation. Thus, the development of nanomaterials that can inhibit Cu^(2+)-mediated Aβ aggregation and degrade Aβ-Cu^(2+)complexes is considered an effective strategy for the prevention and treatment of AD. In this study, polydopamine nanoparticles(PDA NPs) were prepared and the results reveal that PDA NPs potently inhibit Cu^(2+)-mediated Aβaggregation and effectively reduce the formation of Aβ-Cu^(2+)complexes. In vitro experiments show that PDA NPs efficiently eliminate ROS generation catalyzed by Cu^(2+)or Aβ-Cu^(2+)complexes, thus rescuing cultured cells by reducing intracellular ROS levels. More importantly, PDA NPs can depolymerize Aβ-Cu^(2+)complexes, and the degradation of Aβ-Cu^(2+)complexes is promoted by near-infrared light irradiation due to their high photothermal conversion ability. In vivo studies reveal that PDA NPs significantly reduce the deposition of Aβ plaques in the presence of Cu^(2+)and extend the lifespan of AD nematodes from 11 to 14 d. Thus, the PDA NPs developed herein are multifunctional against Cu^(2+)-mediated Aβ aggregation for the potential prevention and treatment of AD.展开更多
As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when ...As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when learning agents are deployed on the edge side,the data aggregation from the end side to the designated edge devices is an important research topic.Considering the various importance of end devices,this paper studies the weighted data aggregation problem in a single hop end-to-edge communication network.Firstly,to make sure all the end devices with various weights are fairly treated in data aggregation,a distributed end-to-edge cooperative scheme is proposed.Then,to handle the massive contention on the wireless channel caused by end devices,a multi-armed bandit(MAB)algorithm is designed to help the end devices find their most appropriate update rates.Diffe-rent from the traditional data aggregation works,combining the MAB enables our algorithm a higher efficiency in data aggregation.With a theoretical analysis,we show that the efficiency of our algorithm is asymptotically optimal.Comparative experiments with previous works are also conducted to show the strength of our algorithm.展开更多
In this paper,a decision-making problem with a q-rung orthopair fuzzy hypersoft environment is developed,and two operators of ordered weighted average and induced ordered weighted average are developed.Several fundame...In this paper,a decision-making problem with a q-rung orthopair fuzzy hypersoft environment is developed,and two operators of ordered weighted average and induced ordered weighted average are developed.Several fundamental features are also derived.The induced ordered weighted average operator is essential in a q-ROFH environment as the induced ordered aggregation operators are special cases of the existing aggregation operators that already exist in q-ROFH environments.The main function of these operators is to help decision-makers gain a complete understanding of uncertain facts.The proposed aggregation operator is applied to a decision-making problem,with the aim of selecting the most promising real estate project for investment.展开更多
Copolymerization of an electron-rich donor(D)unit with an electron-deficient acceptor(A)unit to construct efficient D-π-A-πtype donors is an effective strategy for organic solar cell applications.The electron-defici...Copolymerization of an electron-rich donor(D)unit with an electron-deficient acceptor(A)unit to construct efficient D-π-A-πtype donors is an effective strategy for organic solar cell applications.The electron-deficient unit fusion,endows extendedπ-conjugation plane and insures excellent photoelectronic property,has great advantages to build A moiety and gradually receives considerable attention.In this work,we adopt benzo[2,1-b:3,4-b’]dithiophene and benzopyrazine(BP),benzothiadiazole(BT)and benzoselenadiazole(BS)to cleverly construct a series of fused A units with different electrondeficient ability,and further synthesize three polymer donors PBDP-BP,PBDP-BT,and PBDP-BS,respectively.The relationships between structure and performance were systematically investigated.PBDPBT shows a moderate aggregation behavior in both solution and film,and the highest hole mobility among the three polymers.After blending with Y6,the PBDP-BT:Y6-based film has the strongest absorption,favorable compatibility,superior crystallinity,and uniform phase separation morphology compared with PBDP-BP or PBDP-BS based blend films.Thus,the device based on PBDP-BT:Y6 has the highest and balanced charge mobility,suppressive recombination,reduced energy loss and achieves an outstanding PCE of 15.14%,which is superior to PBDP-BP:Y6(8.55%)and PBDP-BS:Y6(6.85%).These results provide learnable guidelines for future fused electron-deficient unit-based donor design for photovoltaic application.展开更多
Turing patterns are typical spatiotemporal ordered structures in various systems driven far from thermodynamic equilibrium.Turing’s reaction-diffusion theory,containing a long-range inhibiting agent and a local catal...Turing patterns are typical spatiotemporal ordered structures in various systems driven far from thermodynamic equilibrium.Turing’s reaction-diffusion theory,containing a long-range inhibiting agent and a local catalytic agent,has provided an explanation for the formation of some patterns in nature.Numerical,experimental and theoretical studies about Turing/Turing-like patterns have been generally focused on systems driven far from thermodynamic equilibrium.The local dynamics of these systems are commonly very complex,which brings great difficulties to understanding of formation of patterns.Here,we investigate a type of Turing-like patterns in a near-equilibrium thermodynamic system experimentally and theoretically,and put forward a new formation mechanism and a quantitative method for Turing/Turing-like patterns.Specifically,we observe a type of Turing-like patterns in starch solutions,and study the effect of concentration on the structure of patterns.The experimental results show that,with the increase of concentration,patterns change from spots to inverse spots,and labyrinthine stripe patterns appear in the region of intermediate concentration.We analyze and model the formation mechanism of these patterns observed in experiments,and the simulation results agree with the experimental results.Our conclusion indicates that the random aggregation of spatial components leads to formation of these patterns,and the proportion of spatial components determines the structures.Our findings shed light on the formation mechanism for Turing/Turing-like patterns.展开更多
Dolichospermum,a typical model filamentous of cyanobacteria,has the potential to cause severely bloom.Extracellular polymeric substances(EPSs)are considered to influence the aggregation of the algae,and temperature is...Dolichospermum,a typical model filamentous of cyanobacteria,has the potential to cause severely bloom.Extracellular polymeric substances(EPSs)are considered to influence the aggregation of the algae,and temperature is a significant factor affecting EPSs secretion.However,the mechanism of how EPSs affects the aggregation of Dolichospermum is still unclear because the structure and composition of EPSs are complex.In this study,the effects of EPSs on the aggregation of Dolichospermum during the rise of temperature(7-37℃)were determined.The results showed that the concentration of extracellular polysaccharides and proteins changed significantly with increasing temperature(P<0.01).Firstly,during the increasing temperature,the polysaccharide content of EPSs increased from 20.34 to 54.64 mg/L,and the polysaccharides in the soluble EPS(S-EPS)layer changed significantly.The protein content reached maximum value at 21℃(14.52 mg/L)and varied significantly in S-EPS and loosely bound EPS(LB-EPS).In the EPSs matrix,humus substances and protein were main components of S-EPS and LB-EPS,and protein was the main component of tightly bound EPS(TB-EPS).Secondly,the cell density of Dolichospermum increased during the temperature rise while the aggregation ratio decreased.Moreover,zeta potential and surface thermodynamic analysis of Dolichospermum revealed that the interfacial free energy and electrostatic repulsion increased gradually with increasing temperature,which further reduced the aggregation of Dolichospermum.Finally,principal component analysis(PCA)analysis showed the aggregation of Dolichospermum was directly related to the changes of protein in EPSs(especially S-EPS and LB-EPS)and zeta potential,and polysaccharides in EPSs inhibited the aggregation of Dolichospermum.Based on these results,it was illustrated that the composition and concentration of EPSs affected the cell surface properties of Dolichospermum with the change of temperature and thus affected the aggregation of Dolichospermum.展开更多
The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disin...The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks(RAEEC),which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges.We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.展开更多
Quantum multi-signature has attracted extensive attention since it was put forward.Beside its own improvement,related research is often combined with other quantum signature.However,this type of quantum signature has ...Quantum multi-signature has attracted extensive attention since it was put forward.Beside its own improvement,related research is often combined with other quantum signature.However,this type of quantum signature has one thing in common,that is,the generation and verification of signature depend heavily on the shared classical secret key.In order to increase the reliability of signature,the homomorphic aggregation technique is applied to quantum multi-signature,and then we propose a quantum homomorphic multi-signature protocol.Unlike previous quantum multi-signature protocols,this protocol utilizes homomorphic properties to complete signature generation and verification.In the signature generation phase,entanglement swapping is introduced,so that the individual signatures of multiple users are aggregated into a new multi-signature.The original quantum state is signed by the shared secret key to realize the verification of the signature in the verification phase.The signature process satisfies the homomorphic property,which can improve the reliability of the signature.展开更多
To reduce mucosal damage in the gastrointestinal tract caused by aspirin,we developed a dissolvable polymeric microneedle(MN)patch loaded with aspirin.Biodegradable polymers provide mechanical strength to the MNs.The ...To reduce mucosal damage in the gastrointestinal tract caused by aspirin,we developed a dissolvable polymeric microneedle(MN)patch loaded with aspirin.Biodegradable polymers provide mechanical strength to the MNs.The MN tips punctured the cuticle of the skin and dissolved when in contact with the subcutaneous tissue.The aspirin in the MN patch is delivered continuously through an array of micropores created by the punctures,providing a stable plasma concentration of aspirin.The factors affecting the stability of aspirin during MNs fabrication were comprehensively analyzed,and the hydrolysis rate of aspirin in the MNs was less than 2%.Compared to oral administration,MN administration not only had a smoother plasma concentration curve but also resulted in a lower effective dose of antiplatelet aggregation.Aspirin-loaded MNs were mildly irritating to the skin,causing only slight erythema on the skin and recovery within 24 h.In summary,aspirin-loaded MNs provide a new method to reduce gastrointestinal adverse effects in patients requiring aspirin regularly.展开更多
Multi-stream carrier aggregation is a key technology to expand bandwidth and improve the throughput of the fifth-generation wireless communication systems.However,due to the diversified propagation properties of diffe...Multi-stream carrier aggregation is a key technology to expand bandwidth and improve the throughput of the fifth-generation wireless communication systems.However,due to the diversified propagation properties of different frequency bands,the traffic migration task is much more challenging,especially in hybrid sub-6 GHz and millimeter wave bands scenario.Existing schemes either neglected to consider the transmission rate difference between multistream carrier,or only consider simple low mobility scenario.In this paper,we propose a low-complexity traffic splitting algorithm based on fuzzy proportional integral derivative control mechanism.The proposed algorithm only relies on the local radio link control buffer information of sub-6 GHz and mmWave bands,while frequent feedback from user equipment(UE)side is minimized.As shown in the numerical examples,the proposed traffic splitting mechanism can achieve more than 90%link resource utilization ratio for different UE transmission requirements with different mobilities,which corresponds to 10%improvement if compared with conventional baselines.展开更多
Aggregation-induced thermally activated delayed fluorescence(TADF)phenomena have attracted extensive attention recently.In this paper,several theoretical models including monomer,dimer,and complex are used for the exp...Aggregation-induced thermally activated delayed fluorescence(TADF)phenomena have attracted extensive attention recently.In this paper,several theoretical models including monomer,dimer,and complex are used for the explanation of the luminescent properties of(R)-5-(9H-carbazol-9-yl)-2-(1,2,3,4-tetrahydronaphthalen-1-yl)isoindoline-1,3-dione((R)-ImNCz),which was recently reported[Chemical Engineering Journal 418129167(2021)].The polarizable continuum model(PCM)and the combined quantum mechanics and molecular mechanics(QM/MM)method are adopted in simulation of the property of the molecule in the gas phase,solvated in acetonitrile and in aggregation states.It is found that large spin–orbit coupling(SOC)constants and a smaller energy gap between the first singlet excited state and the first triplet excited state(△E_(st))in prism-like single crystals(SC_(p)-form)are responsible for the TADF of(R)-lmNCz,while no TADF is found in block-like single crystals(SC_(b)-form)with a larger △E_(st).The multiple ultralong phosphorescence(UOP)peaks in the spectrum are of complex origins,and they are related not only to ImNCz but also to a minor amount of impurities(ImNBd)in the crystal prepared in the laboratory.The dimer has similar phosphorescence emission wavelengths to the(R)-lmNCz-SC_(p) monomers.The complex composed of(R)-lmNCz and(R)-lmNBd contributes to the phosphorescent emission peak at about 600 nm,and the phosphorescent emission peak at about 650 nm is generated by(R)-lmNBd.This indicates that the impurity could also contribute to emission in molecular crystals.The present calculations clarify the relationship between the molecular aggregation and the light-emitting properties of the TADF emitters and will therefore be helpful for the design of potentially more useful TADF emitters.展开更多
Affinity propagation(AP)is a widely used exemplar-based clustering approach with superior efficiency and clustering quality.Nevertheless,a common issue with AP clustering is the presence of excessive exemplars,which l...Affinity propagation(AP)is a widely used exemplar-based clustering approach with superior efficiency and clustering quality.Nevertheless,a common issue with AP clustering is the presence of excessive exemplars,which limits its ability to perform effective aggregation.This research aims to enable AP to automatically aggregate to produce fewer and more compact clusters,without changing the similarity matrix or customizing preference parameters,as done in existing enhanced approaches.An automatic aggregation enhanced affinity propagation(AAEAP)clustering algorithm is proposed,which combines a dependable partitioning clustering approach with AP to achieve this purpose.The partitioning clustering approach generates an additional set of findings with an equivalent number of clusters whenever the clustering stabilizes and the exemplars emerge.Based on these findings,mutually exclusive exemplar detection was conducted on the current AP exemplars,and a pair of unsuitable exemplars for coexistence is recommended.The recommendation is then mapped as a novel constraint,designated mutual exclusion and aggregation.To address this limitation,a modified AP clustering model is derived and the clustering is restarted,which can result in exemplar number reduction,exemplar selection adjustment,and other data point redistribution.The clustering is ultimately completed and a smaller number of clusters are obtained by repeatedly performing automatic detection and clustering until no mutually exclusive exemplars are detected.Some standard classification data sets are adopted for experiments on AAEAP and other clustering algorithms for comparison,and many internal and external clustering evaluation indexes are used to measure the clustering performance.The findings demonstrate that the AAEAP clustering algorithm demonstrates a substantial automatic aggregation impact while maintaining good clustering quality.展开更多
The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies.Early diagnosis of many diseases will improve the patient ...The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies.Early diagnosis of many diseases will improve the patient life.The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things(IoT),Wireless Sensor Networks(WSN),Embedded systems,Deep learning approaches and Optimization and aggregation methods.The data generated through these technologies will demand the bandwidth,data rate,latency of the network.In this proposed work,efficient discrete grey wolf optimization(DGWO)based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code(ECEMAC)has been used to aggregate the parameters generated from the wearable sensor devices of the patient.The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO.Aggregation scheme will reduce the number of transmissions over the network.The aggregated data are preprocessed at edge node to remove the noise for better diagnosis.Edge node will reduce the overhead of cloud server.The aggregated data are forward to cloud server for central storage and diagnosis.This proposed smart diagnosis will reduce the transmission cost through aggrega-tion scheme which will reduce the energy of the system.Energy cost for proposed system for 300 nodes is 0.34μJ.Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme(SPPDA),concealed data aggregation scheme for multiple application(CDAMA)and secure aggregation scheme(ASAS)are 1.3μJ,0.81μJ and 0.51μJ respectively.The optimization approaches and encryption method will ensure the data privacy.展开更多
基金supported by the National Key R&D Program of China(Nos.2019YFD0901204,2019YFD 0901205).
文摘Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.
基金Project supported by the National Natural Science Foundation of China (Nos.12072007,12072006,12132001,and 52192632)the Ningbo Natural Science Foundation of Zhejiang Province of China (No.202003N4018)the Defense Industrial Technology Development Program of China (Nos.JCKY2019205A006,JCKY2019203A003,and JCKY2021204A002)。
文摘A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.
基金funded by European Union Horizon 2020 research and innovation programme under GA 952334(PhasAGE)the Spanish Ministry of Science and Innovation(PID2019-105017RB-I00)by ICREA,ICREA Academia 2015,and 2020(to SV).
文摘Protein aggregation has been linked with many neurodegenerative diseases,such as Alzheimer’s disease(AD)or Parkinson’s disease.AD belongs to a group of heterogeneous and incurable neurodegenerative disorders collectively known as tauopathies.They comprise frontotemporal dementia,Pick’s disease,or corticobasal degeneration,among others.The symptomatology varies with the specific tau protein variant involved and the affected brain region or cell type.However,they share a common neuropathological hallmark-the formation of proteinaceous deposits named neurofibrillary tangles.Neurofibrillary tangles,primarily composed of aggregated tau(Zhang et al.,2022),disrupt normal neuronal functions,leading to cell death and cognitive decline.
基金the financial support received from the Michael J.Fox Foundation through the Target Advancement Program Grant Award (Grant No.MJFF-000649) (to HK)。
文摘Parkinson's disease(PD),a prevalent neurodegenerative disorder,is chara cterized by the loss of dopaminergic neurons and the aggregation ofα-synuclein protein into Lewy bodies.While the current standards of therapy have been successful in providing some symptom relief,they fail to address the underlying pathophysiology of PD and as a result,they have no effect on disease progression.
基金supported in part by National Natural Science Foundation of China(Nos.62102311,62202377,62272385)in part by Natural Science Basic Research Program of Shaanxi(Nos.2022JQ-600,2022JM-353,2023-JC-QN-0327)+2 种基金in part by Shaanxi Distinguished Youth Project(No.2022JC-47)in part by Scientific Research Program Funded by Shaanxi Provincial Education Department(No.22JK0560)in part by Distinguished Youth Talents of Shaanxi Universities,and in part by Youth Innovation Team of Shaanxi Universities.
文摘With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals.Support vector machine(SVM)is one of the most elementary learning models of machine learning.Privacy issues surrounding SVM classifier training have attracted increasing attention.In this paper,we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction,called FedDPDR-DPML,which greatly improves data utility while providing strong privacy guarantees.Considering in distributed learning scenarios,multiple participants usually hold unbalanced or small amounts of data.Therefore,FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted model averaging and knowledge aggregation and then the server distributes the global model to each participant to improve local data utility.Aiming at high-dimensional data,we adopt differential privacy in both the principal component analysis(PCA)-based dimensionality reduction phase and SVM classifiers training phase,which improves model accuracy while achieving strict differential privacy protection.Besides,we train Differential privacy(DP)-compliant SVM classifiers by adding noise to the objective function itself,thus leading to better data utility.Extensive experiments on three high-dimensional datasets demonstrate that FedDPDR-DPML can achieve high accuracy while ensuring strong privacy protection.
基金supported by the National Natural Science Foundation of China(32071968)the Jiangsu Agricultural Science and Technology Innovation Fund,China(CX(22)2015))the Jiangsu Collaborative Innovation Center for Modern Crop Production,China。
文摘Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.
基金supported by the National Natural Science Foundation of China (21878262)。
文摘Occurrence of neurofibrillary tangles of the tau protein is a hallmark of tau-related neurodegenerative diseases, i.e. Alzheimer's disease(AD) and frontotemporal dementia. The pathological mechanism underlying AD remains poorly understood, and effective treatments are still unavailable to mitigate the disease.Inhibiting of tau aggregation and disrupting the existing fibrils are key targets in drug discovery towards preventing or curing AD. In this study, grape seed proanthocyanidins(GSPs) was found to effectively inhibit the repeat domain of tau(tau-RD) aggregation and disaggregate tau-RD fibrils in a concentrationdependent manner by inhibiting β-sheet formation of tau-RD. In cells, GSPs relieved cytotoxicity induced by tau-RD aggregates. Molecular dynamics simulations indicated that strong hydrogen bonding,hydrophobic interaction and π-π stacking between GSPs and tau-RD protein were major reasons why GSPs had high inhibitory activity on tau-RD fibrillogenesis. These results provide preliminary data to develop GSPs into medicines, foodstuffs or nutritional supplements for AD patients, suggesting that GSPs could be a candidate molecule in the drug design for AD therapeutics.
基金funded by the National Natural Science Foundation of China (21978207 and 21621004)the Natural Science Foundation of Tianjin from Tianjin Municipal Science and Technology Commission (19JCZDJC36800)。
文摘Deposition of β-amyloid protein(Aβ) is the main hallmark of Alzheimer's disease(AD), and it has been well recognized that Cu^(2+)-mediated Aβ aggregation plays a crucial role in AD pathological processes.Cu^(2+)binding to Aβ can promote the production of reactive oxygen species(ROS) through Fenton-like reactions and produce more toxic Aβ-Cu^(2+)species under Cu^(2+)stimulation. Thus, the development of nanomaterials that can inhibit Cu^(2+)-mediated Aβ aggregation and degrade Aβ-Cu^(2+)complexes is considered an effective strategy for the prevention and treatment of AD. In this study, polydopamine nanoparticles(PDA NPs) were prepared and the results reveal that PDA NPs potently inhibit Cu^(2+)-mediated Aβaggregation and effectively reduce the formation of Aβ-Cu^(2+)complexes. In vitro experiments show that PDA NPs efficiently eliminate ROS generation catalyzed by Cu^(2+)or Aβ-Cu^(2+)complexes, thus rescuing cultured cells by reducing intracellular ROS levels. More importantly, PDA NPs can depolymerize Aβ-Cu^(2+)complexes, and the degradation of Aβ-Cu^(2+)complexes is promoted by near-infrared light irradiation due to their high photothermal conversion ability. In vivo studies reveal that PDA NPs significantly reduce the deposition of Aβ plaques in the presence of Cu^(2+)and extend the lifespan of AD nematodes from 11 to 14 d. Thus, the PDA NPs developed herein are multifunctional against Cu^(2+)-mediated Aβ aggregation for the potential prevention and treatment of AD.
基金supported by the National Natural Science Foundation of China(NSFC)(62102232,62122042,61971269)Natural Science Foundation of Shandong Province Under(ZR2021QF064)。
文摘As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when learning agents are deployed on the edge side,the data aggregation from the end side to the designated edge devices is an important research topic.Considering the various importance of end devices,this paper studies the weighted data aggregation problem in a single hop end-to-edge communication network.Firstly,to make sure all the end devices with various weights are fairly treated in data aggregation,a distributed end-to-edge cooperative scheme is proposed.Then,to handle the massive contention on the wireless channel caused by end devices,a multi-armed bandit(MAB)algorithm is designed to help the end devices find their most appropriate update rates.Diffe-rent from the traditional data aggregation works,combining the MAB enables our algorithm a higher efficiency in data aggregation.With a theoretical analysis,we show that the efficiency of our algorithm is asymptotically optimal.Comparative experiments with previous works are also conducted to show the strength of our algorithm.
文摘In this paper,a decision-making problem with a q-rung orthopair fuzzy hypersoft environment is developed,and two operators of ordered weighted average and induced ordered weighted average are developed.Several fundamental features are also derived.The induced ordered weighted average operator is essential in a q-ROFH environment as the induced ordered aggregation operators are special cases of the existing aggregation operators that already exist in q-ROFH environments.The main function of these operators is to help decision-makers gain a complete understanding of uncertain facts.The proposed aggregation operator is applied to a decision-making problem,with the aim of selecting the most promising real estate project for investment.
基金financially supported by the National Natural Science Foundation of China(21733005,21975115 and 51903116)the Shenzhen Fundamental Research Program(JCYJ20200109140801751,JCYJ20190809163011543 and JCYJ20190809161413310)+2 种基金the Guangdong Provincial Key Laboratory of Catalysis(2020B121201002)the Guangdong Innovative and Entrepreneurial Research Team Program(2016ZT06G587)the Shenzhen Sci-Tech Fund(KYTDPT 20181011104007)。
文摘Copolymerization of an electron-rich donor(D)unit with an electron-deficient acceptor(A)unit to construct efficient D-π-A-πtype donors is an effective strategy for organic solar cell applications.The electron-deficient unit fusion,endows extendedπ-conjugation plane and insures excellent photoelectronic property,has great advantages to build A moiety and gradually receives considerable attention.In this work,we adopt benzo[2,1-b:3,4-b’]dithiophene and benzopyrazine(BP),benzothiadiazole(BT)and benzoselenadiazole(BS)to cleverly construct a series of fused A units with different electrondeficient ability,and further synthesize three polymer donors PBDP-BP,PBDP-BT,and PBDP-BS,respectively.The relationships between structure and performance were systematically investigated.PBDPBT shows a moderate aggregation behavior in both solution and film,and the highest hole mobility among the three polymers.After blending with Y6,the PBDP-BT:Y6-based film has the strongest absorption,favorable compatibility,superior crystallinity,and uniform phase separation morphology compared with PBDP-BP or PBDP-BS based blend films.Thus,the device based on PBDP-BT:Y6 has the highest and balanced charge mobility,suppressive recombination,reduced energy loss and achieves an outstanding PCE of 15.14%,which is superior to PBDP-BP:Y6(8.55%)and PBDP-BS:Y6(6.85%).These results provide learnable guidelines for future fused electron-deficient unit-based donor design for photovoltaic application.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12205006 and 11975025)the Excellent Youth Scientific Research Project of Anhui Province(Grant No.2022AH030107)+1 种基金the Natural Science Foundation of Anhui Higher Education Institutions of China(Grant No.KJ2020A0504)the International Joint Research Center of Simulation and Control for Population Ecology of Yangtze River in Anhui(Grant No.12011530158).
文摘Turing patterns are typical spatiotemporal ordered structures in various systems driven far from thermodynamic equilibrium.Turing’s reaction-diffusion theory,containing a long-range inhibiting agent and a local catalytic agent,has provided an explanation for the formation of some patterns in nature.Numerical,experimental and theoretical studies about Turing/Turing-like patterns have been generally focused on systems driven far from thermodynamic equilibrium.The local dynamics of these systems are commonly very complex,which brings great difficulties to understanding of formation of patterns.Here,we investigate a type of Turing-like patterns in a near-equilibrium thermodynamic system experimentally and theoretically,and put forward a new formation mechanism and a quantitative method for Turing/Turing-like patterns.Specifically,we observe a type of Turing-like patterns in starch solutions,and study the effect of concentration on the structure of patterns.The experimental results show that,with the increase of concentration,patterns change from spots to inverse spots,and labyrinthine stripe patterns appear in the region of intermediate concentration.We analyze and model the formation mechanism of these patterns observed in experiments,and the simulation results agree with the experimental results.Our conclusion indicates that the random aggregation of spatial components leads to formation of these patterns,and the proportion of spatial components determines the structures.Our findings shed light on the formation mechanism for Turing/Turing-like patterns.
基金Supported by the National Natural Science Foundation of China(Nos.41877336,41907202,91951112,41773077)the China Postdoctoral Science Foundation(No.2019M651877)+2 种基金the Natural Science Foundation of Jiangsu Province(No.SBK2019043965)the Yancheng Fishery High Quality Development Project(No.YCSCYJ2021030)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_1581)。
文摘Dolichospermum,a typical model filamentous of cyanobacteria,has the potential to cause severely bloom.Extracellular polymeric substances(EPSs)are considered to influence the aggregation of the algae,and temperature is a significant factor affecting EPSs secretion.However,the mechanism of how EPSs affects the aggregation of Dolichospermum is still unclear because the structure and composition of EPSs are complex.In this study,the effects of EPSs on the aggregation of Dolichospermum during the rise of temperature(7-37℃)were determined.The results showed that the concentration of extracellular polysaccharides and proteins changed significantly with increasing temperature(P<0.01).Firstly,during the increasing temperature,the polysaccharide content of EPSs increased from 20.34 to 54.64 mg/L,and the polysaccharides in the soluble EPS(S-EPS)layer changed significantly.The protein content reached maximum value at 21℃(14.52 mg/L)and varied significantly in S-EPS and loosely bound EPS(LB-EPS).In the EPSs matrix,humus substances and protein were main components of S-EPS and LB-EPS,and protein was the main component of tightly bound EPS(TB-EPS).Secondly,the cell density of Dolichospermum increased during the temperature rise while the aggregation ratio decreased.Moreover,zeta potential and surface thermodynamic analysis of Dolichospermum revealed that the interfacial free energy and electrostatic repulsion increased gradually with increasing temperature,which further reduced the aggregation of Dolichospermum.Finally,principal component analysis(PCA)analysis showed the aggregation of Dolichospermum was directly related to the changes of protein in EPSs(especially S-EPS and LB-EPS)and zeta potential,and polysaccharides in EPSs inhibited the aggregation of Dolichospermum.Based on these results,it was illustrated that the composition and concentration of EPSs affected the cell surface properties of Dolichospermum with the change of temperature and thus affected the aggregation of Dolichospermum.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61877046, 12271419, and 62106186)the Natural Science Basic Research Program of Shaanxi (Program No. 2022JQ-620)the Fundamental Research Funds for the Central Universities (Grant Nos. XJS220709, JB210701, and QTZX23002)。
文摘The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks(RAEEC),which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges.We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.
基金Project supported by the National Natural Science Foundation of China(Grant No.61762039).
文摘Quantum multi-signature has attracted extensive attention since it was put forward.Beside its own improvement,related research is often combined with other quantum signature.However,this type of quantum signature has one thing in common,that is,the generation and verification of signature depend heavily on the shared classical secret key.In order to increase the reliability of signature,the homomorphic aggregation technique is applied to quantum multi-signature,and then we propose a quantum homomorphic multi-signature protocol.Unlike previous quantum multi-signature protocols,this protocol utilizes homomorphic properties to complete signature generation and verification.In the signature generation phase,entanglement swapping is introduced,so that the individual signatures of multiple users are aggregated into a new multi-signature.The original quantum state is signed by the shared secret key to realize the verification of the signature in the verification phase.The signature process satisfies the homomorphic property,which can improve the reliability of the signature.
基金by the National Key Research and Development Plan of China[No.2016YFC1000902].
文摘To reduce mucosal damage in the gastrointestinal tract caused by aspirin,we developed a dissolvable polymeric microneedle(MN)patch loaded with aspirin.Biodegradable polymers provide mechanical strength to the MNs.The MN tips punctured the cuticle of the skin and dissolved when in contact with the subcutaneous tissue.The aspirin in the MN patch is delivered continuously through an array of micropores created by the punctures,providing a stable plasma concentration of aspirin.The factors affecting the stability of aspirin during MNs fabrication were comprehensively analyzed,and the hydrolysis rate of aspirin in the MNs was less than 2%.Compared to oral administration,MN administration not only had a smoother plasma concentration curve but also resulted in a lower effective dose of antiplatelet aggregation.Aspirin-loaded MNs were mildly irritating to the skin,causing only slight erythema on the skin and recovery within 24 h.In summary,aspirin-loaded MNs provide a new method to reduce gastrointestinal adverse effects in patients requiring aspirin regularly.
基金supported by the National Natural Science Foundation of China (NSFC) under Grants 62071284, 61871262, 61901251 and 61904101the National Key Research and Development Program of China under Grants 2019YFE0196600+2 种基金the Innovation Program of Shanghai Municipal Science and Technology Commission under Grant 20JC1416400Pudong New Area Science & Technology Development Fundresearch funds from Shanghai Institute for Advanced Communication and Data Science (SICS)
文摘Multi-stream carrier aggregation is a key technology to expand bandwidth and improve the throughput of the fifth-generation wireless communication systems.However,due to the diversified propagation properties of different frequency bands,the traffic migration task is much more challenging,especially in hybrid sub-6 GHz and millimeter wave bands scenario.Existing schemes either neglected to consider the transmission rate difference between multistream carrier,or only consider simple low mobility scenario.In this paper,we propose a low-complexity traffic splitting algorithm based on fuzzy proportional integral derivative control mechanism.The proposed algorithm only relies on the local radio link control buffer information of sub-6 GHz and mmWave bands,while frequent feedback from user equipment(UE)side is minimized.As shown in the numerical examples,the proposed traffic splitting mechanism can achieve more than 90%link resource utilization ratio for different UE transmission requirements with different mobilities,which corresponds to 10%improvement if compared with conventional baselines.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11974216,11874242,21933002 and 11904210)Shandong Provincial Natural Science Foundation,China(Grant No.ZR2019MA056)+1 种基金the support of the Taishan Scholar Project of Shandong Provincethe project funded by China Postdoctoral Science Foundation(Grant No.2018M642689)。
文摘Aggregation-induced thermally activated delayed fluorescence(TADF)phenomena have attracted extensive attention recently.In this paper,several theoretical models including monomer,dimer,and complex are used for the explanation of the luminescent properties of(R)-5-(9H-carbazol-9-yl)-2-(1,2,3,4-tetrahydronaphthalen-1-yl)isoindoline-1,3-dione((R)-ImNCz),which was recently reported[Chemical Engineering Journal 418129167(2021)].The polarizable continuum model(PCM)and the combined quantum mechanics and molecular mechanics(QM/MM)method are adopted in simulation of the property of the molecule in the gas phase,solvated in acetonitrile and in aggregation states.It is found that large spin–orbit coupling(SOC)constants and a smaller energy gap between the first singlet excited state and the first triplet excited state(△E_(st))in prism-like single crystals(SC_(p)-form)are responsible for the TADF of(R)-lmNCz,while no TADF is found in block-like single crystals(SC_(b)-form)with a larger △E_(st).The multiple ultralong phosphorescence(UOP)peaks in the spectrum are of complex origins,and they are related not only to ImNCz but also to a minor amount of impurities(ImNBd)in the crystal prepared in the laboratory.The dimer has similar phosphorescence emission wavelengths to the(R)-lmNCz-SC_(p) monomers.The complex composed of(R)-lmNCz and(R)-lmNBd contributes to the phosphorescent emission peak at about 600 nm,and the phosphorescent emission peak at about 650 nm is generated by(R)-lmNBd.This indicates that the impurity could also contribute to emission in molecular crystals.The present calculations clarify the relationship between the molecular aggregation and the light-emitting properties of the TADF emitters and will therefore be helpful for the design of potentially more useful TADF emitters.
基金supported by Research Team Development Funds of L.Xue and Z.H.Ouyang,Electronic Countermeasure Institute,National University of Defense Technology。
文摘Affinity propagation(AP)is a widely used exemplar-based clustering approach with superior efficiency and clustering quality.Nevertheless,a common issue with AP clustering is the presence of excessive exemplars,which limits its ability to perform effective aggregation.This research aims to enable AP to automatically aggregate to produce fewer and more compact clusters,without changing the similarity matrix or customizing preference parameters,as done in existing enhanced approaches.An automatic aggregation enhanced affinity propagation(AAEAP)clustering algorithm is proposed,which combines a dependable partitioning clustering approach with AP to achieve this purpose.The partitioning clustering approach generates an additional set of findings with an equivalent number of clusters whenever the clustering stabilizes and the exemplars emerge.Based on these findings,mutually exclusive exemplar detection was conducted on the current AP exemplars,and a pair of unsuitable exemplars for coexistence is recommended.The recommendation is then mapped as a novel constraint,designated mutual exclusion and aggregation.To address this limitation,a modified AP clustering model is derived and the clustering is restarted,which can result in exemplar number reduction,exemplar selection adjustment,and other data point redistribution.The clustering is ultimately completed and a smaller number of clusters are obtained by repeatedly performing automatic detection and clustering until no mutually exclusive exemplars are detected.Some standard classification data sets are adopted for experiments on AAEAP and other clustering algorithms for comparison,and many internal and external clustering evaluation indexes are used to measure the clustering performance.The findings demonstrate that the AAEAP clustering algorithm demonstrates a substantial automatic aggregation impact while maintaining good clustering quality.
基金This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI)funded by the Ministry of Health&Welfare,Republic of Korea(grant number:HI21C1831)the Soonchunhyang University Research Fund.
文摘The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies.Early diagnosis of many diseases will improve the patient life.The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things(IoT),Wireless Sensor Networks(WSN),Embedded systems,Deep learning approaches and Optimization and aggregation methods.The data generated through these technologies will demand the bandwidth,data rate,latency of the network.In this proposed work,efficient discrete grey wolf optimization(DGWO)based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code(ECEMAC)has been used to aggregate the parameters generated from the wearable sensor devices of the patient.The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO.Aggregation scheme will reduce the number of transmissions over the network.The aggregated data are preprocessed at edge node to remove the noise for better diagnosis.Edge node will reduce the overhead of cloud server.The aggregated data are forward to cloud server for central storage and diagnosis.This proposed smart diagnosis will reduce the transmission cost through aggrega-tion scheme which will reduce the energy of the system.Energy cost for proposed system for 300 nodes is 0.34μJ.Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme(SPPDA),concealed data aggregation scheme for multiple application(CDAMA)and secure aggregation scheme(ASAS)are 1.3μJ,0.81μJ and 0.51μJ respectively.The optimization approaches and encryption method will ensure the data privacy.
