In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test r...In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test rig is used as a prototype of a rotor system to validate a novel parameter identification technique based on an FE model. Rotor shaft vibration at varying operating speeds is measured and correlated with the FE results. Firstly, the theories of the FE modelling and identification technique are introduced. Then disk unbalance parameter, stiffness and damping coefficients of the bearing supports on the test rig are identified. The calculated responses of the FE model with identified parameters are studied in comparison with the experimental results.展开更多
Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting t...Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting these advantages of IR-UWB technology at the physical-layer design, this paper proposes that a cross layer architecture platform can be considered as a good integrator for different wireless short-ranges indoor protocols into a universal smart wireless-tagged architecture with new promising applications in cognitive radio for future applications. Adaptive transmission algorithms have been studied to show the trade-off between different specific QoS requirements, transmission rates and distances at the physical layer level and this type of dynamic optimization and reconfiguration leads to the cross-layer design proposal in the paper. Studies from both theoretical simulation and statistical indoor environments experiments are considered as a proof of concept for the proposed architecture.展开更多
[Objective] The research aimed to initially study degradation effect of the CODc, in sewage by two psychrotrophs. [Method] Two psychrotrophs were isolated from the activated sludge of wastewater treatment plant in Tia...[Objective] The research aimed to initially study degradation effect of the CODc, in sewage by two psychrotrophs. [Method] Two psychrotrophs were isolated from the activated sludge of wastewater treatment plant in Tianjin Konggang Economic Area. CODc, degradation ability of the screened psychrotroph was analyzed in simulated domestic wastewater at 6℃. [Result] K 36 was identified as Comamonas testosterone, and K 38 was identified as Serratia fonticola. CODcr degradation abilities of the two strains were different in test. COOcr removal rates of the K 36 and K 38 respectively reached up to 23% and 53%. The measured result of growth rate suggested that two psychrotrophs both had high activities at low temperature. [ Conclusion] K 36 and K 38 had potentials in wastewater treatment application.展开更多
Despite a plethora of studies on how corporate social responsibility(CSR)generates favorable consumer outcomes,the existing literature provides limited insights about how CSR may affect inter-consumer connection and b...Despite a plethora of studies on how corporate social responsibility(CSR)generates favorable consumer outcomes,the existing literature provides limited insights about how CSR may affect inter-consumer connection and brand community engagement.Enhancing consumer engagement in the brand community is one of the key marketing objectives for strengthening the brand-consumer relationship.This study aims to explore the role of corporate social responsibility in enhancing brand community engagement and examines the dual mediating role of brand identification and community identification.Quantitative research was conducted and an adapted questionnaire was used.Survey data were collected from 405 Chinese consumers,and structural equational modeling was used to test the hypothesis.Results demonstrated that CSR motivates consumers to engage with the brand community.Further,brand identification and community identification perform the role of partial mediators.展开更多
The illicit trafficking of special nuclear materials(SNMs)poses a grave threat to global security and necessitates the development of effective nuclear material identification methods.This study investigated a method ...The illicit trafficking of special nuclear materials(SNMs)poses a grave threat to global security and necessitates the development of effective nuclear material identification methods.This study investigated a method to isotopically identify the SNMs,including^(233,235,238)U,^(239-242)Pu,and^(232)Th,based on the detection of delayedγ-rays from photofission fragments.The delayedγ-ray spectra resulting from the photofission of SNMs irradiated by a 14 MeVγbeam with a total of 10~9 were simulated using Geant4.Three high-yield fission fragments,namely^(138)Cs,^(89)Rb,and^(94)Y,were selected as candidate fragments for SNM identification.The yield ratios of these three fragments were calculated,and the results from the different SNMs were compared.The yield ratio of^(138)Cs/^(89)Rb was used to identify most SNMs,including^(233,235,238)U,^(242)Pu,and^(232)Th,with a confidence level above 95%.To identify^(239-241)Pu with the same confidence,a higher total number of 10^(11)γbeams is required.However,although the^(94)Y/^(89)Rb ratio is suitable for elementally identifying SNMs,isotopic identification is difficult.In addition,the count rate of the delayedγabove 3 MeV can be used to rapidly detect the presence of nuclear materials.展开更多
Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent bioc...Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.展开更多
Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the ...Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the present study,an innovative natural product virtual screening-interaction-phenotype(NP-VIP)strategy that integrates virtual screening,chemical proteomics,and metabolomics to identify and validate the bioactive targets of NPs.This approach reduces false positive results and enhances the efficiency of target identification.Salvia miltiorrhiza(SM),a herb with recognized therapeutic potential against ischemic stroke(IS),was used to illustrate the workflow.Utilizing virtual screening,chemical proteomics,and metabolomics,potential therapeutic targets for SM in the IS treatment were identified,totaling 29,100,and 78,respectively.Further analysis via the NP-VIP strategy highlighted five high-confidence targets,including poly[ADP-ribose]polymerase 1(PARP1),signal transducer and activator of transcription 3(STAT3),amyloid precursor protein(APP),glutamate-ammonia ligase(GLUL),and glutamate decarboxylase 67(GAD67).These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM.The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research,proposing a comprehensive approach that could be adapted for broader pharmacological explorations.展开更多
To better understand the migration behavior of plastic fragments in the environment,development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary.Howeve...To better understand the migration behavior of plastic fragments in the environment,development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary.However,most of the studies had focused only on colored plastic fragments,ignoring colorless plastic fragments and the effects of different environmental media(backgrounds),thus underestimating their abundance.To address this issue,the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis(PLS-DA),extreme gradient boost,support vector machine and random forest classifier.The effects of polymer color,type,thickness,and background on the plastic fragments classification were evaluated.PLS-DA presented the best and most stable outcome,with higher robustness and lower misclassification rate.All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm.A two-stage modeling method,which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background,was proposed.The method presented an accuracy higher than 99%in different backgrounds.In summary,this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.展开更多
As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and...As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.展开更多
Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from b...Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.展开更多
Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on ...Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on machine learning of rock visible and near-infrared spectral data.First,the rock spectral data are preprocessed using Savitzky-Golay(SG)smoothing to remove the noise of the spectral data;then,the preprocessed rock spectral data are downscaled using Principal Component Analysis(PCA)to reduce the redundancy of the data,optimize the effective discriminative information,and obtain the rock spectral features;finally,a Bayesian-optimized lithology identification model is established based on rock spectral features,optimize the model hyperparameters using Bayesian optimization(BO)algorithm to avoid the combination of hyperparameters falling into the local optimal solution,and output the predicted type of rock,so as to realize the Bayesian-optimized lithology identification.In addition,this paper conducts comparative analysis on models based on Artificial Neural Network(ANN)/Random Forest(RF),dimensionality reduction/full band,and optimization algorithms.It uses the confusion matrix,accuracy,Precison(P),Recall(R)and F_(1)values(F_(1))as the evaluation indexes of model accuracy.The results indicate that the lithology identification model optimized by the BO-ANN after dimensionality reduction achieves an accuracy of up to 99.80%,up to 99.79%and up to 99.79%.Compared with the BO-RF model,it has higher identification accuracy and better stability for each type of rock identification.The experiments and reliability analysis show that the Bayesian-optimized lithology identification method proposed in this paper has good robustness and generalization performance,which is of great significance for realizing fast,accurate and Bayesian-optimized lithology identification in tunnel site.展开更多
It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in...It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.展开更多
In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant ...In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical fluctuations.These issues can lead to potential failures in peak-searching-based identification methods.To address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification model.Comparative experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma spectra.With only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain samples.The proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(...Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(ΣOPEs)in soil ranged from 1.33 to 96.5 ng/g dry weight(dw),with an average value of 17.1 ng/g dw.Especially,halogenated-OPEs were the predominant group with amean level of 9.75 ng/g dw,and tris(1-chloro-2-propyl)phosphate(TCIPP)was the most abundant OPEs,accounting for 51.1%ofΣOPEs.The concentrations of TCIPP andΣOPEs were found to be significantly higher(P<0.05)in soils of urban areas than those in suburban areas.In addition,the use of agricultural plastic films and total organic carbon had a positive effect on the occurrence of OPE in this study.The positive matrix factorization model suggested complex sources of OPEs in agricultural soils from Fuzhou.The ecological risk assessment demonstrated that tricresyl phosphate presented a medium risk to land-based organisms(0.1≤risk quotient<1.0).Nevertheless,the carcinogenic and noncarcinogenic risks for human exposure to OPEs through soil ingestion and dermal absorption were negligible.These findings would facilitate further investigations into the pollution management and risk control of OPEs.展开更多
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stre...Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.展开更多
In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has...In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.展开更多
In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the...In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.展开更多
As climate change,international trade,and human activities increasingly disrupt traditional geographic barriers in the oceans,non-indigenous species(NIS)have successfully established themselves outside their native ra...As climate change,international trade,and human activities increasingly disrupt traditional geographic barriers in the oceans,non-indigenous species(NIS)have successfully established themselves outside their native ranges.Outbreaks of NIS can pose significant threats to local ecosystems and economies,making them a critical issue for marine biodiversity and biosecurity.Biological invasions in marine habitats differ significantly from those on land or in freshwater.Detection and identification of NIS in marine habitats is particularly challenging due to difficulties in sampling,morphological identification,and visualization in the early stages of outbreaks.Environmental DNA(eDNA)approaches have emerged as reliable and cost-effective methods for both qualitative and quantitative detection of marine NIS,particularly in the introductory phase.In this review,we summarize recent applications and advances in eDNA-based detection of marine NIS.We emphasize that innovations in eDNA sampling equipment,improvements in detection methods,and further refinement of the reference genomic database for marine species are crucial for the future development of this field.展开更多
基金supported by the National Natural Science Foundation of China(50775028)the Ministry of Science and Technology of China for the 863 High-Tech Scheme(2007AA04Z418)
文摘In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test rig is used as a prototype of a rotor system to validate a novel parameter identification technique based on an FE model. Rotor shaft vibration at varying operating speeds is measured and correlated with the FE results. Firstly, the theories of the FE modelling and identification technique are introduced. Then disk unbalance parameter, stiffness and damping coefficients of the bearing supports on the test rig are identified. The calculated responses of the FE model with identified parameters are studied in comparison with the experimental results.
文摘Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting these advantages of IR-UWB technology at the physical-layer design, this paper proposes that a cross layer architecture platform can be considered as a good integrator for different wireless short-ranges indoor protocols into a universal smart wireless-tagged architecture with new promising applications in cognitive radio for future applications. Adaptive transmission algorithms have been studied to show the trade-off between different specific QoS requirements, transmission rates and distances at the physical layer level and this type of dynamic optimization and reconfiguration leads to the cross-layer design proposal in the paper. Studies from both theoretical simulation and statistical indoor environments experiments are considered as a proof of concept for the proposed architecture.
基金Supported by Excellent Talent Support Plan Project in New Century, Ministry of Education,China(NCET-09-0586)Special Project of the Science Research in Public Welfare Industry,Ministry of Water Resources,China (201101018,201201114)Special Item of the National International Science and Technology Cooperation(S2013BGR0244)
文摘[Objective] The research aimed to initially study degradation effect of the CODc, in sewage by two psychrotrophs. [Method] Two psychrotrophs were isolated from the activated sludge of wastewater treatment plant in Tianjin Konggang Economic Area. CODc, degradation ability of the screened psychrotroph was analyzed in simulated domestic wastewater at 6℃. [Result] K 36 was identified as Comamonas testosterone, and K 38 was identified as Serratia fonticola. CODcr degradation abilities of the two strains were different in test. COOcr removal rates of the K 36 and K 38 respectively reached up to 23% and 53%. The measured result of growth rate suggested that two psychrotrophs both had high activities at low temperature. [ Conclusion] K 36 and K 38 had potentials in wastewater treatment application.
文摘Despite a plethora of studies on how corporate social responsibility(CSR)generates favorable consumer outcomes,the existing literature provides limited insights about how CSR may affect inter-consumer connection and brand community engagement.Enhancing consumer engagement in the brand community is one of the key marketing objectives for strengthening the brand-consumer relationship.This study aims to explore the role of corporate social responsibility in enhancing brand community engagement and examines the dual mediating role of brand identification and community identification.Quantitative research was conducted and an adapted questionnaire was used.Survey data were collected from 405 Chinese consumers,and structural equational modeling was used to test the hypothesis.Results demonstrated that CSR motivates consumers to engage with the brand community.Further,brand identification and community identification perform the role of partial mediators.
基金supported by the National Key Research and Development Program(No.2022YFA1603300)the National Natural Science Foundation of China(Nos.U2230133,12305266,11921006,12405282)National Grand Instrument Project(No.2019YFF01014400)。
文摘The illicit trafficking of special nuclear materials(SNMs)poses a grave threat to global security and necessitates the development of effective nuclear material identification methods.This study investigated a method to isotopically identify the SNMs,including^(233,235,238)U,^(239-242)Pu,and^(232)Th,based on the detection of delayedγ-rays from photofission fragments.The delayedγ-ray spectra resulting from the photofission of SNMs irradiated by a 14 MeVγbeam with a total of 10~9 were simulated using Geant4.Three high-yield fission fragments,namely^(138)Cs,^(89)Rb,and^(94)Y,were selected as candidate fragments for SNM identification.The yield ratios of these three fragments were calculated,and the results from the different SNMs were compared.The yield ratio of^(138)Cs/^(89)Rb was used to identify most SNMs,including^(233,235,238)U,^(242)Pu,and^(232)Th,with a confidence level above 95%.To identify^(239-241)Pu with the same confidence,a higher total number of 10^(11)γbeams is required.However,although the^(94)Y/^(89)Rb ratio is suitable for elementally identifying SNMs,isotopic identification is difficult.In addition,the count rate of the delayedγabove 3 MeV can be used to rapidly detect the presence of nuclear materials.
基金supported by the grants from University of Macao,China,Nos.MYRG2022-00221-ICMS(to YZ)and MYRG-CRG2022-00011-ICMS(to RW)the Natural Science Foundation of Guangdong Province,No.2023A1515010034(to YZ)。
文摘Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.
基金supported by the National Natural Science Foundations of China(Grant No.:82204584)Liaoning Provincial Science and Technology Projects,China(Project No.:2021JH1/10400055).
文摘Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the present study,an innovative natural product virtual screening-interaction-phenotype(NP-VIP)strategy that integrates virtual screening,chemical proteomics,and metabolomics to identify and validate the bioactive targets of NPs.This approach reduces false positive results and enhances the efficiency of target identification.Salvia miltiorrhiza(SM),a herb with recognized therapeutic potential against ischemic stroke(IS),was used to illustrate the workflow.Utilizing virtual screening,chemical proteomics,and metabolomics,potential therapeutic targets for SM in the IS treatment were identified,totaling 29,100,and 78,respectively.Further analysis via the NP-VIP strategy highlighted five high-confidence targets,including poly[ADP-ribose]polymerase 1(PARP1),signal transducer and activator of transcription 3(STAT3),amyloid precursor protein(APP),glutamate-ammonia ligase(GLUL),and glutamate decarboxylase 67(GAD67).These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM.The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research,proposing a comprehensive approach that could be adapted for broader pharmacological explorations.
基金supported by the National Natural Science Foundation of China(No.22276139)the Shanghai’s Municipal State-owned Assets Supervision and Administration Commission(No.2022028).
文摘To better understand the migration behavior of plastic fragments in the environment,development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary.However,most of the studies had focused only on colored plastic fragments,ignoring colorless plastic fragments and the effects of different environmental media(backgrounds),thus underestimating their abundance.To address this issue,the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis(PLS-DA),extreme gradient boost,support vector machine and random forest classifier.The effects of polymer color,type,thickness,and background on the plastic fragments classification were evaluated.PLS-DA presented the best and most stable outcome,with higher robustness and lower misclassification rate.All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm.A two-stage modeling method,which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background,was proposed.The method presented an accuracy higher than 99%in different backgrounds.In summary,this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.
基金support by the National Natural Science Foundation of China(Grant No.52402520)。
文摘Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.
基金support from the National Natural Science Foundation of China(Grant Nos:52379103 and 52279103)the Natural Science Foundation of Shandong Province(Grant No:ZR2023YQ049).
文摘Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on machine learning of rock visible and near-infrared spectral data.First,the rock spectral data are preprocessed using Savitzky-Golay(SG)smoothing to remove the noise of the spectral data;then,the preprocessed rock spectral data are downscaled using Principal Component Analysis(PCA)to reduce the redundancy of the data,optimize the effective discriminative information,and obtain the rock spectral features;finally,a Bayesian-optimized lithology identification model is established based on rock spectral features,optimize the model hyperparameters using Bayesian optimization(BO)algorithm to avoid the combination of hyperparameters falling into the local optimal solution,and output the predicted type of rock,so as to realize the Bayesian-optimized lithology identification.In addition,this paper conducts comparative analysis on models based on Artificial Neural Network(ANN)/Random Forest(RF),dimensionality reduction/full band,and optimization algorithms.It uses the confusion matrix,accuracy,Precison(P),Recall(R)and F_(1)values(F_(1))as the evaluation indexes of model accuracy.The results indicate that the lithology identification model optimized by the BO-ANN after dimensionality reduction achieves an accuracy of up to 99.80%,up to 99.79%and up to 99.79%.Compared with the BO-RF model,it has higher identification accuracy and better stability for each type of rock identification.The experiments and reliability analysis show that the Bayesian-optimized lithology identification method proposed in this paper has good robustness and generalization performance,which is of great significance for realizing fast,accurate and Bayesian-optimized lithology identification in tunnel site.
基金supported by the National Natural Science Foundation of China(42122017,41821002)the Independent Innovation Research Program of China University of Petroleum(East China)(21CX06001A).
文摘It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.
基金supported by the National Defense Fundamental Research Project(No.JCKY2022404C005)the Nuclear Energy Development Project(No.23ZG6106)+1 种基金the Sichuan Scientific and Technological Achievements Transfer and Transformation Demonstration Project(No.2023ZHCG0026)the Mianyang Applied Technology Research and Development Project(No.2021ZYZF1005)。
文摘In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical fluctuations.These issues can lead to potential failures in peak-searching-based identification methods.To address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification model.Comparative experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma spectra.With only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain samples.The proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
基金supported by the Open Fund of the Laboratory for Earth Surface Processes,Ministry of Education,Peking University,Beijing,China,and the Cultivation Fund Program for Excellent Dissertation in Fujian Normal University,China(No.LWPYS202315)the Research Start-up Fund of Fujian Normal University,China(No.Y0720304X13).
文摘Fifty agricultural soil samples collected from Fuzhou,southeast China,were first investigated for the occurrence,distribution,and potential risks of twelve organophosphate esters(OPEs).The total concentration of OPEs(ΣOPEs)in soil ranged from 1.33 to 96.5 ng/g dry weight(dw),with an average value of 17.1 ng/g dw.Especially,halogenated-OPEs were the predominant group with amean level of 9.75 ng/g dw,and tris(1-chloro-2-propyl)phosphate(TCIPP)was the most abundant OPEs,accounting for 51.1%ofΣOPEs.The concentrations of TCIPP andΣOPEs were found to be significantly higher(P<0.05)in soils of urban areas than those in suburban areas.In addition,the use of agricultural plastic films and total organic carbon had a positive effect on the occurrence of OPE in this study.The positive matrix factorization model suggested complex sources of OPEs in agricultural soils from Fuzhou.The ecological risk assessment demonstrated that tricresyl phosphate presented a medium risk to land-based organisms(0.1≤risk quotient<1.0).Nevertheless,the carcinogenic and noncarcinogenic risks for human exposure to OPEs through soil ingestion and dermal absorption were negligible.These findings would facilitate further investigations into the pollution management and risk control of OPEs.
基金financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金financially supported by the National Natural Science Foundation of China(No.52204084)the Open Research Fund of the State Key Laboratory of Coal Resources and safe Mining,CUMT,China(No.SKLCRSM 23KF004)+3 种基金the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities),China(No.FRF-IDRY-GD22-002)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange and Growth Program,China(No.QNXM20220009)the National Key R&D Program of China(Nos.2022YFC2905600 and 2022 YFC3004601)the Science,Technology&Innovation Project of Xiongan New Area,China(No.2023XAGG0061)。
文摘Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.
文摘In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.
文摘In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.
文摘As climate change,international trade,and human activities increasingly disrupt traditional geographic barriers in the oceans,non-indigenous species(NIS)have successfully established themselves outside their native ranges.Outbreaks of NIS can pose significant threats to local ecosystems and economies,making them a critical issue for marine biodiversity and biosecurity.Biological invasions in marine habitats differ significantly from those on land or in freshwater.Detection and identification of NIS in marine habitats is particularly challenging due to difficulties in sampling,morphological identification,and visualization in the early stages of outbreaks.Environmental DNA(eDNA)approaches have emerged as reliable and cost-effective methods for both qualitative and quantitative detection of marine NIS,particularly in the introductory phase.In this review,we summarize recent applications and advances in eDNA-based detection of marine NIS.We emphasize that innovations in eDNA sampling equipment,improvements in detection methods,and further refinement of the reference genomic database for marine species are crucial for the future development of this field.
