This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational ...This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.展开更多
Thermoelectric generators(TEGs)play a critical role in collecting renewable energy fromthe sun and deep space to generate clean electricity.With their environmentally friendly,reliable,and noise-free operation,TEGs of...Thermoelectric generators(TEGs)play a critical role in collecting renewable energy fromthe sun and deep space to generate clean electricity.With their environmentally friendly,reliable,and noise-free operation,TEGs offer diverse applications,including areas with limited power infrastructure,microelectronic devices,and wearable technology.The review thoroughly analyses TEG system configurations,performance,and applications driven by solar and/or radiative cooling,covering non-concentrating,concentrating,radiative cooling-driven,and dual-mode TEGs.Materials for solar absorbers and radiative coolers,simulation techniques,energy storage management,and thermal management strategies are explored.The integration of TEGs with combined heat and power systems is identified as a promising application.Additionally,TEGs hold potential as charging sources for electronic devices.This comprehensive review provides valuable insights into this energy collection approach,facilitating improved efficiency,reduced costs,and expanded applications.It also highlights current limitations and knowledge gaps,emphasizing the importance of further research and development in unlocking the full potential of TEGs for a sustainable and efficient energy future.展开更多
A relatively high aerodynamic drag is an important factor that hinders the further acceleration of high-speed trains.Using the shear stress transport(SST)k-ωturbulence model,the effect of various vortex generator typ...A relatively high aerodynamic drag is an important factor that hinders the further acceleration of high-speed trains.Using the shear stress transport(SST)k-ωturbulence model,the effect of various vortex generator types on the aerodynamic characteristics of an ICE2(Inter-city Electricity)train has been investigated.The results indi-cate that the vortex generators with wider triangle,trapezoid,and micro-ramp arranged on the surface of the tail car can significantly change the distribution of surface pressure and affect the vorticity intensity in the wake.This alteration effectively reduces the resistance of the tail car.Meanwhile,the micro-ramp vortex generator with its convergent structure at the rear exhibits enhancedflow-guiding capabilities,resulting in a 15.4%reduction in the drag of the tail car.展开更多
In the quantum Monte Carlo(QMC)method,the pseudo-random number generator(PRNG)plays a crucial role in determining the computation time.However,the hidden structure of the PRNG may lead to serious issues such as the br...In the quantum Monte Carlo(QMC)method,the pseudo-random number generator(PRNG)plays a crucial role in determining the computation time.However,the hidden structure of the PRNG may lead to serious issues such as the breakdown of the Markov process.Here,we systematically analyze the performance of different PRNGs on the widely used QMC method known as the stochastic series expansion(SSE)algorithm.To quantitatively compare them,we introduce a quantity called QMC efficiency that can effectively reflect the efficiency of the algorithms.After testing several representative observables of the Heisenberg model in one and two dimensions,we recommend the linear congruential generator as the best choice of PRNG.Our work not only helps improve the performance of the SSE method but also sheds light on the other Markov-chain-based numerical algorithms.展开更多
A Solid Oxide Fuel Cell(SOFC)is an electrochemical device that converts the chemical energy of a substance into electrical energy through an oxidation-reduction mechanism.The electrochemical reaction of a solid oxide ...A Solid Oxide Fuel Cell(SOFC)is an electrochemical device that converts the chemical energy of a substance into electrical energy through an oxidation-reduction mechanism.The electrochemical reaction of a solid oxide fuel cell(SOFC)generates heat,and this heat can be recovered and put to use in a waste heat recovery system.In addition to preheating the fuel and oxidant,producing steam for industrial use,and heating and cooling enclosed rooms,this waste heat can be used for many more productive uses.The large waste heat produced by SOFCs is a worry that must be managed if they are to be adopted as a viable option in the power generation business.In light of these findings,a novel approach to SOFC waste heat recovery is proposed.The SOFC is combined with a“Thermoelectric Generator and an Alkali Metal Thermoelectric Converter(TG-AMTC)”to transform the excess heat generated by both the SOFC and the TG-AMTC.The proposed TG-AMTC is evaluated using a number of performance indicators including power density,operating temperature,heat recovery rate,exergetic efficiency,energy efficiency,and recovery time.The experimental results state that TG-AMTC has provided an exergetic efficiency,energetic efficiency,and recovery time of 97%,98%,and 23%,respectively.The study proves that the proposed TG-AMTC for SOFC is an efficient method of recovering waste heat.展开更多
This paper aims to treat a study of generators of the cyclic group of higher even, odd, and prime order for composition being multiplication. In fact we developed order of a group, order of element of a group and gene...This paper aims to treat a study of generators of the cyclic group of higher even, odd, and prime order for composition being multiplication. In fact we developed order of a group, order of element of a group and generators of the cyclic group in real numbers. Also we express cyclic and generators of the group for composition in real numbers. Here we discuss the higher order of groups in different types of order, and generators of the cyclic group which will give us practical knowledge to see the applications of the composition. In order to find out the order of an element am∈Gin which an=e= identity element, then find Highest Common Factor i.e. (H.C.F) of mand n. When Gis a finite group, every element must have finite order but the converse is false. There are infinite groups where each element has a finite order. There may be more than one generator of a cyclic group. Also every cyclic group is necessarily abelian. But show that every infinite cyclic group contains only two generators. Finally, we find out the generators of the cyclic group of higher even, odd and prime order in different types of the group for composition being multiplication.展开更多
Neuroinflammation is associated with Parkinson’s disease:Reactive gliosis and neuroinflammation are hallmarks of Parkinson’s disease(PD),a multisystem neurodegenerative disorder characterized by a progressive loss o...Neuroinflammation is associated with Parkinson’s disease:Reactive gliosis and neuroinflammation are hallmarks of Parkinson’s disease(PD),a multisystem neurodegenerative disorder characterized by a progressive loss of dopaminergic neurons.Neuroinflammation has long been considered a mere consequence of neuronal loss,but whether it promotes PD or is a key player in disease progression remains to be determined.Human leukocyte antigen.展开更多
The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by...The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.展开更多
This study presents a comparative analysis of a complex SQL benchmark, TPC-DS, with two existing text-to-SQL benchmarks, BIRD and Spider. Our findings reveal that TPC-DS queries exhibit a significantly higher level of...This study presents a comparative analysis of a complex SQL benchmark, TPC-DS, with two existing text-to-SQL benchmarks, BIRD and Spider. Our findings reveal that TPC-DS queries exhibit a significantly higher level of structural complexity compared to the other two benchmarks. This underscores the need for more intricate benchmarks to simulate realistic scenarios effectively. To facilitate this comparison, we devised several measures of structural complexity and applied them across all three benchmarks. The results of this study can guide future research in the development of more sophisticated text-to-SQL benchmarks. We utilized 11 distinct Language Models (LLMs) to generate SQL queries based on the query descriptions provided by the TPC-DS benchmark. The prompt engineering process incorporated both the query description as outlined in the TPC-DS specification and the database schema of TPC-DS. Our findings indicate that the current state-of-the-art generative AI models fall short in generating accurate decision-making queries. We conducted a comparison of the generated queries with the TPC-DS gold standard queries using a series of fuzzy structure matching techniques based on query features. The results demonstrated that the accuracy of the generated queries is insufficient for practical real-world application.展开更多
Graph burning is a model for describing the spread of influence in social networks and the generalized burning number br(G)of graph Gis a parameter to measure the speed of information spread on network G. In this pape...Graph burning is a model for describing the spread of influence in social networks and the generalized burning number br(G)of graph Gis a parameter to measure the speed of information spread on network G. In this paper, we determined the generalized burning number of gear graph, which is useful model of social network. We also provided properties of the generalized burning number of sun graphs, including characterizations and bounds.展开更多
ChatGPT is a natural language processing tool that creates human-like conversations,responds to questions,and creates wrtten content when prompted by the end-user.As ChatGPT is trained on published material,allowing i...ChatGPT is a natural language processing tool that creates human-like conversations,responds to questions,and creates wrtten content when prompted by the end-user.As ChatGPT is trained on published material,allowing it to find and parse relevant literature about prompted targets,it in theory is an ideal way to make literature reviews more efficient.As more academics use the tool,gauging the accuracy of the information gathered by this automation becomes important.Our research aims to assess the accuracy of literature found by ChatGPT when performing a systematic review.We searched PubMed for recent systematic reviews on chronic diseases(e.g.,diabetes and hypertension)published before November 2022.Two researchers extracted aims and inclusion/exclusion criteria from each review.Using these criteria,we prompted ChatGPT to find 10 relevant articles.Researchers then cross-referenced ChatGPT's results with Google Scholar,PubMed,and Tulane Library's database.We categorized ChatGPT's results as fake,real but not in the review,or matched with the review.If ChatGPT provided 10 real articles,we prompted it for another set.We calculated the rates of each outcome.Nine systematic reviews were selected to assess ChatGPT's ability to conduct literature reviews.In total,ChatGPT found 90 articles after 9 sets of 10 articles each of 90 articles,58%of articles were real but 38(42%)of citations were for articles that did not exist.Additionally,of the 90 articles,only 16(18%)matched articles in the systematic reviews.38(42%)were fake,16(18%)were real articles that matched the target review,and 36(40%)were real articles but did not match the reviews.Furthermore,we never achieved 10/10 real articles in a single query.ChatGPT is a tool that can demonstrably make healthcare research tasks more efficient.However,healthcare decision and policy makers cannot yet rely on pure generative AI output without knowing whether humans were involved in the entire research process.And so,there appears to exist an ability ceiling above which the current ChatGPT algorithms cannot reach.展开更多
With the rapid development of generative artificial intelligence(AI)technology in the field of education,global educational systems are facing unprecedented opportunities and challenges,urgently requiring the establis...With the rapid development of generative artificial intelligence(AI)technology in the field of education,global educational systems are facing unprecedented opportunities and challenges,urgently requiring the establishment of comprehensive,flexible,and forward-looking governance solutions.The“Australian Framework for Generative AI in Schools”builds a multi-dimensional governance system covering aspects such as teaching and humanistic care,fairness and transparency,and accountability and security.Based on 22 specific principles and six core elements,it emphasizes a human-centered design concept,adopts a principle-based flexible structure,focuses on fairness and transparency,and stresses accountability and security.The framework provides valuable references for the use of generative AI in China’s education system and holds significant importance for promoting educational modernization and cultivating innovative talents adapted to the era of artificial intelligence.展开更多
In 1694,Gregory and Newton proposed the problem to determine the kissing number of a rigid material ball.This problem and its higher dimensional generalization have been studied by many mathematicians,including Minkow...In 1694,Gregory and Newton proposed the problem to determine the kissing number of a rigid material ball.This problem and its higher dimensional generalization have been studied by many mathematicians,including Minkowski,van der Waerden,Hadwiger,Swinnerton-Dyer,Watson,Levenshtein,Odlyzko,Sloane and Musin.In this paper,we introduce and study a further generalization of the kissing numbers for convex bodies and obtain some exact results,in particular for balls in dimensions three,four and eight.展开更多
Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for conse...Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of equidistant sub-sequences,we investigate the ratio of the sum of numbers along main-diagonal and sub-diagonal of odd-order grids containing generalized Fibonacci sequences.We show that this ratio is solely dependent on the order of the grid,providing a concise and splendid identity.展开更多
Driven by the dual forces of China’s financial powerhouse strategy and advancements in artificial intelligence,digital finance has experienced rapid growth,rendering traditional financial legal regulations inadequate...Driven by the dual forces of China’s financial powerhouse strategy and advancements in artificial intelligence,digital finance has experienced rapid growth,rendering traditional financial legal regulations inadequate to meet its regulatory demands.Key challenges include lagging legislative regulation,limited applicability of the standard regulations,and diminished effectiveness of the supervisory regulations.These challenges stem from the“single-entity”regulatory approach which is inadequate to meet its regulatory needs of mixed operations of digital finance,the misalignment between“static”administrative regulations and the dynamic evolution of financial technology(fintech),and the uneven allocation of regulatory resources,which constrain regulatory precision.To achieve a dynamic balance between the development of digital finance and its regulation,the adoption of inclusive legal regulation is imperative.The technological empowerment theory integrates the principles of finance with the“people-centered”concept and the social good,which thereby safeguards the rights and interests of digital finance consumers.As a pivotal standard for shaping inclusive legal regulation,digital justice should not only uphold fairness in the regulation of processes but also advance the organic integration of scenario-based justice and the principles of Law 3.0.In the future,China should foster multi-stakeholder collaborative governance to ensure the orderly allocation of the regulators’power.This effort should be supported by a comprehensive toolkit of technological regulations,which can dynamically balance incentive regulation with binding regulation while simultaneously enabling the efficient flow of regulatory resources within specific application scenarios.Such strategies would provide a viable pathway toward the goal of achieving inclusive legal regulation in digital finance.展开更多
BACKGROUND Patients with chronic obstructive pulmonary disease(COPD)frequently experience exacerbations requiring multiple hospitalizations over prolonged disease courses,which predispose them to generalized anxiety d...BACKGROUND Patients with chronic obstructive pulmonary disease(COPD)frequently experience exacerbations requiring multiple hospitalizations over prolonged disease courses,which predispose them to generalized anxiety disorder(GAD).This comorbidity exacerbates breathing difficulties,activity limitations,and social isolation.While previous studies predominantly employed the GAD 7-item scale for screening,this approach is somewhat subjective.The current literature on predictive models for GAD risk in patients with COPD is limited.AIM To construct and validate a GAD risk prediction model to aid healthcare professionals in preventing the onset of GAD.METHODS This retrospective analysis encompassed patients with COPD treated at our institution from July 2021 to February 2024.The patients were categorized into a modeling(MO)group and a validation(VA)group in a 7:3 ratio on the basis of the occurrence of GAD.Univariate and multivariate logistic regression analyses were utilized to construct the risk prediction model,which was visualized using forest plots.The model’s performance was evaluated using Hosmer-Lemeshow(H-L)goodness-of-fit test and receiver operating characteristic(ROC)curve analysis.RESULTS A total of 271 subjects were included,with 190 in the MO group and 81 in the VA group.GAD was identified in 67 patients with COPD,resulting in a prevalence rate of 24.72%(67/271),with 49 cases(18.08%)in the MO group and 18 cases(22.22%)in the VA group.Significant differences were observed between patients with and without GAD in terms of educational level,average household income,smoking history,smoking index,number of exacerbations in the past year,cardiovascular comorbidities,disease knowledge,and personality traits(P<0.05).Multivariate logistic regression analysis revealed that lower education levels,household income<3000 China yuan,smoking history,smoking index≥400 cigarettes/year,≥two exacerbations in the past year,cardiovascular comorbidities,complete lack of disease information,and introverted personality were significant risk factors for GAD in the MO group(P<0.05).ROC analysis indicated that the area under the curve for predicting GAD in the MO and VA groups was 0.978 and 0.960.The H-L test yieldedχ^(2) values of 6.511 and 5.179,with P=0.275 and 0.274.Calibration curves demonstrated good agreement between predicted and actual GAD occurrence risks.CONCLUSION The developed predictive model includes eight independent risk factors:Educational level,household income,smoking history,smoking index,number of exacerbations in the past year,presence of cardiovascular comorbidities,level of disease knowledge,and personality traits.This model effectively predicts the onset of GAD in patients with COPD,enabling early identification of high-risk individuals and providing a basis for early preventive interventions by nursing staff.展开更多
The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the cont...The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the continuum. In application to the Newton gravitation theory, the analysis consists of three stages. First, we assume that the gravitational force is determined by the initial sphere radius and constant density and does not change in the process of the sphere collapse. The obtained analytical solution allows us to find the collapse time in the first approximation. Second, we construct the step-by-step process in which the gravitational force at a given time moment depends on the current sphere radius and density. The obtained numerical solution specifies the collapse time depending on the number of steps. Third, we find the exact value of the collapse time which is the limit of the step-by-step solutions and study the collapse and the expansion processes in the Newton theory. In application to general relativity, we use the space model corresponding to the special four-dimensional space which is Euclidean with respect to space coordinates and Riemannian with respect to the time coordinate only. The obtained solution specifies two possible scenarios. First, sphere contraction results in the infinitely high density with the finite collapse time, which does not coincide with the conventional result corresponding to the Schwarzschild geometry. Second, sphere expansion with the velocity which increases with a distance from the sphere center and decreases with time.展开更多
Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to capture the complex structural ...Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to capture the complex structural and relational information inherent in molecular graphs. Despite their effectiveness, the “black-box” nature of GNNs remains a significant obstacle to their widespread adoption in chemistry, as it hinders interpretability and trust. In this context, several explanation methods based on factual reasoning have emerged. These methods aim to interpret the predictions made by GNNs by analyzing the key features contributing to the prediction. However, these approaches fail to answer critical questions: “How to ensure that the structure-property mapping learned by GNNs is consistent with established domain knowledge”. In this paper, we propose MMGCF, a novel counterfactual explanation framework designed specifically for the prediction of GNN-based molecular properties. MMGCF constructs a hierarchical tree structure on molecular motifs, enabling the systematic generation of counterfactuals through motif perturbations. This framework identifies causally significant motifs and elucidates their impact on model predictions, offering insights into the relationship between structural modifications and predicted properties. Our method demonstrates its effectiveness through comprehensive quantitative and qualitative evaluations of four real-world molecular datasets.展开更多
Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivor...Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivorous livestock animals. Also, other Taeniid tapeworms could infect domestic dogs and they pose significant veterinary and public health concerns worldwide. This study aimed to develop a sensitive molecular method for detecting Echinococcus spp. DNA in dog fecal samples using next-generation sequencing (NGS). A set of PCR primers targeting conserved regions of Taeniid tapeworms’ 18s rRNA genes was designed and tested for amplifying genomic DNA from various tapeworm species. The PCR system demonstrated high sensitivity, amplifying DNA from all tested tapeworm species, with differences observed in amplified band sizes. The primers were adapted for NGS analysis by adding forward and reverse adapters, enabling the sequencing of amplified DNA fragments. Application of the developed PCR system to dog fecal samples collected from Yatta town, Palestine, revealed the presence of E. granulosus DNA in five out of 50 samples. NGS analysis confirmed the specificity of the amplified DNA fragments, showing 98% - 99% similarity with the 18s rDNA gene of E. granulosus. This study demonstrates the utility of NGS-based molecular methods for accurate and sensitive detection of Echinococcus spp. in dog fecal samples, providing valuable insights for epidemiological surveillance and control programs of echinococcosis in endemic regions.展开更多
In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use ...In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use the Z1transformation to get the general solutions of some nonlinear partial differential equations for the first time, and use the general solutions to obtain the exact solutions of some typical definite solution problems.展开更多
文摘This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.
基金supported by the Hong Kong Polytechnic University through Projects of RCRE(Project No.1-BBEG)sponsored by the Research Grants Council of HongKong and the NationalNatural Science Foundation of China(Project No.N_PolyU513/18).
文摘Thermoelectric generators(TEGs)play a critical role in collecting renewable energy fromthe sun and deep space to generate clean electricity.With their environmentally friendly,reliable,and noise-free operation,TEGs offer diverse applications,including areas with limited power infrastructure,microelectronic devices,and wearable technology.The review thoroughly analyses TEG system configurations,performance,and applications driven by solar and/or radiative cooling,covering non-concentrating,concentrating,radiative cooling-driven,and dual-mode TEGs.Materials for solar absorbers and radiative coolers,simulation techniques,energy storage management,and thermal management strategies are explored.The integration of TEGs with combined heat and power systems is identified as a promising application.Additionally,TEGs hold potential as charging sources for electronic devices.This comprehensive review provides valuable insights into this energy collection approach,facilitating improved efficiency,reduced costs,and expanded applications.It also highlights current limitations and knowledge gaps,emphasizing the importance of further research and development in unlocking the full potential of TEGs for a sustainable and efficient energy future.
基金supported by the National Natural Science Foundation of China(12372049)Sichuan Science and Technology Program(2023JDRC0062)+1 种基金Science and Technology Program of China National Accreditation Service for Conformity Assessment(2022CNAS15)the Independent Project of State Key Laboratory of Rail Transit Vehicle System(2023TPL-T06).
文摘A relatively high aerodynamic drag is an important factor that hinders the further acceleration of high-speed trains.Using the shear stress transport(SST)k-ωturbulence model,the effect of various vortex generator types on the aerodynamic characteristics of an ICE2(Inter-city Electricity)train has been investigated.The results indi-cate that the vortex generators with wider triangle,trapezoid,and micro-ramp arranged on the surface of the tail car can significantly change the distribution of surface pressure and affect the vorticity intensity in the wake.This alteration effectively reduces the resistance of the tail car.Meanwhile,the micro-ramp vortex generator with its convergent structure at the rear exhibits enhancedflow-guiding capabilities,resulting in a 15.4%reduction in the drag of the tail car.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12274046,11874094,and 12147102)Chongqing Natural Science Foundation(Grant No.CSTB2022NSCQ-JQX0018)Fundamental Research Funds for the Central Universities(Grant No.2021CDJZYJH-003).
文摘In the quantum Monte Carlo(QMC)method,the pseudo-random number generator(PRNG)plays a crucial role in determining the computation time.However,the hidden structure of the PRNG may lead to serious issues such as the breakdown of the Markov process.Here,we systematically analyze the performance of different PRNGs on the widely used QMC method known as the stochastic series expansion(SSE)algorithm.To quantitatively compare them,we introduce a quantity called QMC efficiency that can effectively reflect the efficiency of the algorithms.After testing several representative observables of the Heisenberg model in one and two dimensions,we recommend the linear congruential generator as the best choice of PRNG.Our work not only helps improve the performance of the SSE method but also sheds light on the other Markov-chain-based numerical algorithms.
基金Foundation of Heilongjiang Bayi Agricultural University(Grant Nos.ZRCPY201916ZRCPY201817).
文摘A Solid Oxide Fuel Cell(SOFC)is an electrochemical device that converts the chemical energy of a substance into electrical energy through an oxidation-reduction mechanism.The electrochemical reaction of a solid oxide fuel cell(SOFC)generates heat,and this heat can be recovered and put to use in a waste heat recovery system.In addition to preheating the fuel and oxidant,producing steam for industrial use,and heating and cooling enclosed rooms,this waste heat can be used for many more productive uses.The large waste heat produced by SOFCs is a worry that must be managed if they are to be adopted as a viable option in the power generation business.In light of these findings,a novel approach to SOFC waste heat recovery is proposed.The SOFC is combined with a“Thermoelectric Generator and an Alkali Metal Thermoelectric Converter(TG-AMTC)”to transform the excess heat generated by both the SOFC and the TG-AMTC.The proposed TG-AMTC is evaluated using a number of performance indicators including power density,operating temperature,heat recovery rate,exergetic efficiency,energy efficiency,and recovery time.The experimental results state that TG-AMTC has provided an exergetic efficiency,energetic efficiency,and recovery time of 97%,98%,and 23%,respectively.The study proves that the proposed TG-AMTC for SOFC is an efficient method of recovering waste heat.
文摘This paper aims to treat a study of generators of the cyclic group of higher even, odd, and prime order for composition being multiplication. In fact we developed order of a group, order of element of a group and generators of the cyclic group in real numbers. Also we express cyclic and generators of the group for composition in real numbers. Here we discuss the higher order of groups in different types of order, and generators of the cyclic group which will give us practical knowledge to see the applications of the composition. In order to find out the order of an element am∈Gin which an=e= identity element, then find Highest Common Factor i.e. (H.C.F) of mand n. When Gis a finite group, every element must have finite order but the converse is false. There are infinite groups where each element has a finite order. There may be more than one generator of a cyclic group. Also every cyclic group is necessarily abelian. But show that every infinite cyclic group contains only two generators. Finally, we find out the generators of the cyclic group of higher even, odd and prime order in different types of the group for composition being multiplication.
基金supported by the Spanish Government(ISCIII-FEDER)PI20/01063by Navarra Government(PC 060-061 and PC 192-193)Fundación Gangoiti(to MSA).LA was funded by FPU19/03255.
文摘Neuroinflammation is associated with Parkinson’s disease:Reactive gliosis and neuroinflammation are hallmarks of Parkinson’s disease(PD),a multisystem neurodegenerative disorder characterized by a progressive loss of dopaminergic neurons.Neuroinflammation has long been considered a mere consequence of neuronal loss,but whether it promotes PD or is a key player in disease progression remains to be determined.Human leukocyte antigen.
基金described in this paper has been developed with in the project PRESECREL(PID2021-124502OB-C43)。
文摘The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.
文摘This study presents a comparative analysis of a complex SQL benchmark, TPC-DS, with two existing text-to-SQL benchmarks, BIRD and Spider. Our findings reveal that TPC-DS queries exhibit a significantly higher level of structural complexity compared to the other two benchmarks. This underscores the need for more intricate benchmarks to simulate realistic scenarios effectively. To facilitate this comparison, we devised several measures of structural complexity and applied them across all three benchmarks. The results of this study can guide future research in the development of more sophisticated text-to-SQL benchmarks. We utilized 11 distinct Language Models (LLMs) to generate SQL queries based on the query descriptions provided by the TPC-DS benchmark. The prompt engineering process incorporated both the query description as outlined in the TPC-DS specification and the database schema of TPC-DS. Our findings indicate that the current state-of-the-art generative AI models fall short in generating accurate decision-making queries. We conducted a comparison of the generated queries with the TPC-DS gold standard queries using a series of fuzzy structure matching techniques based on query features. The results demonstrated that the accuracy of the generated queries is insufficient for practical real-world application.
文摘Graph burning is a model for describing the spread of influence in social networks and the generalized burning number br(G)of graph Gis a parameter to measure the speed of information spread on network G. In this paper, we determined the generalized burning number of gear graph, which is useful model of social network. We also provided properties of the generalized burning number of sun graphs, including characterizations and bounds.
文摘ChatGPT is a natural language processing tool that creates human-like conversations,responds to questions,and creates wrtten content when prompted by the end-user.As ChatGPT is trained on published material,allowing it to find and parse relevant literature about prompted targets,it in theory is an ideal way to make literature reviews more efficient.As more academics use the tool,gauging the accuracy of the information gathered by this automation becomes important.Our research aims to assess the accuracy of literature found by ChatGPT when performing a systematic review.We searched PubMed for recent systematic reviews on chronic diseases(e.g.,diabetes and hypertension)published before November 2022.Two researchers extracted aims and inclusion/exclusion criteria from each review.Using these criteria,we prompted ChatGPT to find 10 relevant articles.Researchers then cross-referenced ChatGPT's results with Google Scholar,PubMed,and Tulane Library's database.We categorized ChatGPT's results as fake,real but not in the review,or matched with the review.If ChatGPT provided 10 real articles,we prompted it for another set.We calculated the rates of each outcome.Nine systematic reviews were selected to assess ChatGPT's ability to conduct literature reviews.In total,ChatGPT found 90 articles after 9 sets of 10 articles each of 90 articles,58%of articles were real but 38(42%)of citations were for articles that did not exist.Additionally,of the 90 articles,only 16(18%)matched articles in the systematic reviews.38(42%)were fake,16(18%)were real articles that matched the target review,and 36(40%)were real articles but did not match the reviews.Furthermore,we never achieved 10/10 real articles in a single query.ChatGPT is a tool that can demonstrably make healthcare research tasks more efficient.However,healthcare decision and policy makers cannot yet rely on pure generative AI output without knowing whether humans were involved in the entire research process.And so,there appears to exist an ability ceiling above which the current ChatGPT algorithms cannot reach.
基金2024 Undergraduate Innovation Training Program Project“Research on the Current Situation,Impact and Management Countermeasures of Generative AI in College Students’Learning”(202410065153)。
文摘With the rapid development of generative artificial intelligence(AI)technology in the field of education,global educational systems are facing unprecedented opportunities and challenges,urgently requiring the establishment of comprehensive,flexible,and forward-looking governance solutions.The“Australian Framework for Generative AI in Schools”builds a multi-dimensional governance system covering aspects such as teaching and humanistic care,fairness and transparency,and accountability and security.Based on 22 specific principles and six core elements,it emphasizes a human-centered design concept,adopts a principle-based flexible structure,focuses on fairness and transparency,and stresses accountability and security.The framework provides valuable references for the use of generative AI in China’s education system and holds significant importance for promoting educational modernization and cultivating innovative talents adapted to the era of artificial intelligence.
基金supported by the National Natural Science Foundation of China(12226006,11921001)the Natural Key Research and Development Program of China(2018YFA0704701).
文摘In 1694,Gregory and Newton proposed the problem to determine the kissing number of a rigid material ball.This problem and its higher dimensional generalization have been studied by many mathematicians,including Minkowski,van der Waerden,Hadwiger,Swinnerton-Dyer,Watson,Levenshtein,Odlyzko,Sloane and Musin.In this paper,we introduce and study a further generalization of the kissing numbers for convex bodies and obtain some exact results,in particular for balls in dimensions three,four and eight.
基金Supported by the National Natural Science Foundation of China(Grant No.12471298)the Shaanxi Fundamental Science Research Project for Mathematics and Physics(Grant No.23JSQ031)the Shaanxi Province College Student Innovation and Entrepreneurship Training Program(Grant Nos.S202210699481 and S202310699324X).
文摘Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of equidistant sub-sequences,we investigate the ratio of the sum of numbers along main-diagonal and sub-diagonal of odd-order grids containing generalized Fibonacci sequences.We show that this ratio is solely dependent on the order of the grid,providing a concise and splendid identity.
基金funded by a general project of the National Social Science Fund of China“Research on the Construction of the Implementation Mechanism of the Paris Agreement under the Concept of a Community with a Shared Future for Mankind(Project No.:20BFX210)”a Humanities and Social Sciences Special Project of the Fundamental Research Funds for the Central Universities“Research on Legal Issues and Countermeasures for Promoting High-Quality Green Development in the Belt and Road Region”(Project No.:2022CD-JSKPY28).
文摘Driven by the dual forces of China’s financial powerhouse strategy and advancements in artificial intelligence,digital finance has experienced rapid growth,rendering traditional financial legal regulations inadequate to meet its regulatory demands.Key challenges include lagging legislative regulation,limited applicability of the standard regulations,and diminished effectiveness of the supervisory regulations.These challenges stem from the“single-entity”regulatory approach which is inadequate to meet its regulatory needs of mixed operations of digital finance,the misalignment between“static”administrative regulations and the dynamic evolution of financial technology(fintech),and the uneven allocation of regulatory resources,which constrain regulatory precision.To achieve a dynamic balance between the development of digital finance and its regulation,the adoption of inclusive legal regulation is imperative.The technological empowerment theory integrates the principles of finance with the“people-centered”concept and the social good,which thereby safeguards the rights and interests of digital finance consumers.As a pivotal standard for shaping inclusive legal regulation,digital justice should not only uphold fairness in the regulation of processes but also advance the organic integration of scenario-based justice and the principles of Law 3.0.In the future,China should foster multi-stakeholder collaborative governance to ensure the orderly allocation of the regulators’power.This effort should be supported by a comprehensive toolkit of technological regulations,which can dynamically balance incentive regulation with binding regulation while simultaneously enabling the efficient flow of regulatory resources within specific application scenarios.Such strategies would provide a viable pathway toward the goal of achieving inclusive legal regulation in digital finance.
基金Supported by the Henan Provincial Health Commission,No.232102310145.
文摘BACKGROUND Patients with chronic obstructive pulmonary disease(COPD)frequently experience exacerbations requiring multiple hospitalizations over prolonged disease courses,which predispose them to generalized anxiety disorder(GAD).This comorbidity exacerbates breathing difficulties,activity limitations,and social isolation.While previous studies predominantly employed the GAD 7-item scale for screening,this approach is somewhat subjective.The current literature on predictive models for GAD risk in patients with COPD is limited.AIM To construct and validate a GAD risk prediction model to aid healthcare professionals in preventing the onset of GAD.METHODS This retrospective analysis encompassed patients with COPD treated at our institution from July 2021 to February 2024.The patients were categorized into a modeling(MO)group and a validation(VA)group in a 7:3 ratio on the basis of the occurrence of GAD.Univariate and multivariate logistic regression analyses were utilized to construct the risk prediction model,which was visualized using forest plots.The model’s performance was evaluated using Hosmer-Lemeshow(H-L)goodness-of-fit test and receiver operating characteristic(ROC)curve analysis.RESULTS A total of 271 subjects were included,with 190 in the MO group and 81 in the VA group.GAD was identified in 67 patients with COPD,resulting in a prevalence rate of 24.72%(67/271),with 49 cases(18.08%)in the MO group and 18 cases(22.22%)in the VA group.Significant differences were observed between patients with and without GAD in terms of educational level,average household income,smoking history,smoking index,number of exacerbations in the past year,cardiovascular comorbidities,disease knowledge,and personality traits(P<0.05).Multivariate logistic regression analysis revealed that lower education levels,household income<3000 China yuan,smoking history,smoking index≥400 cigarettes/year,≥two exacerbations in the past year,cardiovascular comorbidities,complete lack of disease information,and introverted personality were significant risk factors for GAD in the MO group(P<0.05).ROC analysis indicated that the area under the curve for predicting GAD in the MO and VA groups was 0.978 and 0.960.The H-L test yieldedχ^(2) values of 6.511 and 5.179,with P=0.275 and 0.274.Calibration curves demonstrated good agreement between predicted and actual GAD occurrence risks.CONCLUSION The developed predictive model includes eight independent risk factors:Educational level,household income,smoking history,smoking index,number of exacerbations in the past year,presence of cardiovascular comorbidities,level of disease knowledge,and personality traits.This model effectively predicts the onset of GAD in patients with COPD,enabling early identification of high-risk individuals and providing a basis for early preventive interventions by nursing staff.
文摘The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the continuum. In application to the Newton gravitation theory, the analysis consists of three stages. First, we assume that the gravitational force is determined by the initial sphere radius and constant density and does not change in the process of the sphere collapse. The obtained analytical solution allows us to find the collapse time in the first approximation. Second, we construct the step-by-step process in which the gravitational force at a given time moment depends on the current sphere radius and density. The obtained numerical solution specifies the collapse time depending on the number of steps. Third, we find the exact value of the collapse time which is the limit of the step-by-step solutions and study the collapse and the expansion processes in the Newton theory. In application to general relativity, we use the space model corresponding to the special four-dimensional space which is Euclidean with respect to space coordinates and Riemannian with respect to the time coordinate only. The obtained solution specifies two possible scenarios. First, sphere contraction results in the infinitely high density with the finite collapse time, which does not coincide with the conventional result corresponding to the Schwarzschild geometry. Second, sphere expansion with the velocity which increases with a distance from the sphere center and decreases with time.
文摘Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to capture the complex structural and relational information inherent in molecular graphs. Despite their effectiveness, the “black-box” nature of GNNs remains a significant obstacle to their widespread adoption in chemistry, as it hinders interpretability and trust. In this context, several explanation methods based on factual reasoning have emerged. These methods aim to interpret the predictions made by GNNs by analyzing the key features contributing to the prediction. However, these approaches fail to answer critical questions: “How to ensure that the structure-property mapping learned by GNNs is consistent with established domain knowledge”. In this paper, we propose MMGCF, a novel counterfactual explanation framework designed specifically for the prediction of GNN-based molecular properties. MMGCF constructs a hierarchical tree structure on molecular motifs, enabling the systematic generation of counterfactuals through motif perturbations. This framework identifies causally significant motifs and elucidates their impact on model predictions, offering insights into the relationship between structural modifications and predicted properties. Our method demonstrates its effectiveness through comprehensive quantitative and qualitative evaluations of four real-world molecular datasets.
文摘Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivorous livestock animals. Also, other Taeniid tapeworms could infect domestic dogs and they pose significant veterinary and public health concerns worldwide. This study aimed to develop a sensitive molecular method for detecting Echinococcus spp. DNA in dog fecal samples using next-generation sequencing (NGS). A set of PCR primers targeting conserved regions of Taeniid tapeworms’ 18s rRNA genes was designed and tested for amplifying genomic DNA from various tapeworm species. The PCR system demonstrated high sensitivity, amplifying DNA from all tested tapeworm species, with differences observed in amplified band sizes. The primers were adapted for NGS analysis by adding forward and reverse adapters, enabling the sequencing of amplified DNA fragments. Application of the developed PCR system to dog fecal samples collected from Yatta town, Palestine, revealed the presence of E. granulosus DNA in five out of 50 samples. NGS analysis confirmed the specificity of the amplified DNA fragments, showing 98% - 99% similarity with the 18s rDNA gene of E. granulosus. This study demonstrates the utility of NGS-based molecular methods for accurate and sensitive detection of Echinococcus spp. in dog fecal samples, providing valuable insights for epidemiological surveillance and control programs of echinococcosis in endemic regions.
文摘In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use the Z1transformation to get the general solutions of some nonlinear partial differential equations for the first time, and use the general solutions to obtain the exact solutions of some typical definite solution problems.
