In the realm of video understanding,the demand for accurate and contextually rich video captioning has surged with the increasing volume and complexity of multimedia content.This research introduces an innovative solu...In the realm of video understanding,the demand for accurate and contextually rich video captioning has surged with the increasing volume and complexity of multimedia content.This research introduces an innovative solution for video captioning by integrating a Convolutional BiLSTM Convolutional Bidirectional Long Short-Term Memory(BiLSTM)constructed Variational Sequence-to-Sequence(CBVSS)approach.The proposed framework is adept at capturing intricate temporal dependencies within video sequences,enabling a more nuanced and contextually relevant description of dynamic scenes.However,optimizing its parameters for improved performance remains a crucial challenge.In response,in this research Golden Eagle Optimization(GEO)a metaheuristic optimization technique is used to fine-tune the Convolutional BiLSTM variational sequence-to-sequence model parameters.The application of GEO aims to enhancing the CBVSS ability to produce more exact and contextually rich video captions.The proposed attains an overall higher Recall of 59.75%and Precision of 63.78%for both datasets.Additionally,the proposed CBVSS method demonstrated superior performance across both datasets,achieving the highest METEOR(25.67)and CIDER(39.87)scores on the ActivityNet dataset,and further outperforming all compared models on the YouCook2 dataset with METEOR(28.67)and CIDER(43.02),highlighting its effectiveness in generating semantically rich and contextually accurate video captions.展开更多
Objective:Large-scale CRISPR screens have identified essential genes across cancer cell lines,but links between tumor functional properties and specific dependencies require investigation to reveal the mechanisms unde...Objective:Large-scale CRISPR screens have identified essential genes across cancer cell lines,but links between tumor functional properties and specific dependencies require investigation to reveal the mechanisms underlying dependencies and broaden understanding of targeted therapy.Methods:We selected 47 breast cancer cell lines from the Cancer Cell Line Encyclopedia(CCLE)with multi-omics data including gene dependency;somatic mutations;copy number alterations;and transcriptomic,proteomic,metabolomic,and methylation data.We established a dependency marker association(DMA)analytic pipeline by using linear regression modeling to assess associations between 3,874 representative gene dependencies and multi-omics markers.Additionally,we conducted non-negative matrix factorization clustering,to stratify breast cancer cell lines according to gene dependency features,and investigated cluster-specific DMAs.Results:We interpreted valuable DMAs according to two primary aspects.First,dependencies associated with gain-of-function alterations revealed addiction to lactate transporter SLC16A3,thus suggesting a promising therapeutic target.Second,dependencies associated with loss-of-function alterations included synthetic lethality(SL),collateral SL,and prioritized metabolic SL,encompassing paralog SL(e.g.,IMPDH1 and IMPDH2),single pathway SL(e.g.,GFPT1 and UAP1),and alternative pathway SL(e.g.,GPI and PGD).DMA analysis of the two clusters with divergent dependency signatures demonstrated that cluster1 cell lines exhibited extensive metabolism with mitochondrial protein dependencies,whereas cluster2 displays enhanced cell signaling,and reliance on DNA replication and membrane organelle regulators.Conclusions:We established a DMA analysis pipeline linking the gene dependencies of breast cancer cell lines to multi-omics characteristics,thus elucidating the underpinnings of tumor dependencies and offering a valuable resource for developing novel precision treatment strategies incorporating relevant markers.展开更多
In this paper, the definition of approximate XFDs based on value equality is proposed. Two metrics, sup port and strength, are presented for measuring the degree of approximate XFD. A basic algorithm is designed for e...In this paper, the definition of approximate XFDs based on value equality is proposed. Two metrics, sup port and strength, are presented for measuring the degree of approximate XFD. A basic algorithm is designed for extracting minimal set of approximate XFDs, and then two optimized strategies are proposed to improve the performance. Finally, the experimental results show that the optimized algorithms are correct and effective.展开更多
Today, the quantity of data continues to increase, furthermore, the data are heterogeneous, from multiple sources (structured, semi-structured and unstructured) and with different levels of quality. Therefore, it is v...Today, the quantity of data continues to increase, furthermore, the data are heterogeneous, from multiple sources (structured, semi-structured and unstructured) and with different levels of quality. Therefore, it is very likely to manipulate data without knowledge about their structures and their semantics. In fact, the meta-data may be insufficient or totally absent. Data Anomalies may be due to the poverty of their semantic descriptions, or even the absence of their description. In this paper, we propose an approach to better understand the semantics and the structure of the data. Our approach helps to correct automatically the intra-column anomalies and the inter-col- umns ones. We aim to improve the quality of data by processing the null values and the semantic dependencies between columns.展开更多
According to the analysis of existing complicated functional dependencies constraint, we conclude the conditions of defining functional dependency in XML, and then we introduce the concept of the node value equality. ...According to the analysis of existing complicated functional dependencies constraint, we conclude the conditions of defining functional dependency in XML, and then we introduce the concept of the node value equality. A new path language and a new definition of functional dependencies in XML （XFD） are proposed XFD includes the relative XFD and the absolute XFD, in which absolute key and relative key are the particular cases. We focus on the logical implication and the closure problems, and propose a group of inference rules. Finally, some proofs of the correctness and completeness are given. XFD is powerful on expressing functional dependencies in XML causing data redundancy, and has a complete axiom system.展开更多
N6-methyladenosine(m6A)is an important RNA methylation modification involved in regulating diverse biological processes across multiple species.Hence,the identification of m6A modification sites provides valuable insi...N6-methyladenosine(m6A)is an important RNA methylation modification involved in regulating diverse biological processes across multiple species.Hence,the identification of m6A modification sites provides valuable insight into the biological mechanisms of complex diseases at the post-transcriptional level.Although a variety of identification algorithms have been proposed recently,most of them capture the features of m6A modification sites by focusing on the sequential dependencies of nucleotides at different positions in RNA sequences,while ignoring the structural dependencies of nucleotides in their threedimensional structures.To overcome this issue,we propose a cross-species end-to-end deep learning model,namely CR-NSSD,which conduct a cross-domain representation learning process integrating nucleotide structural and sequential dependencies for RNA m6A site identification.Specifically,CR-NSSD first obtains the pre-coded representations of RNA sequences by incorporating the position information into single-nucleotide states with chaos game representation theory.It then constructs a crossdomain reconstruction encoder to learn the sequential and structural dependencies between nucleotides.By minimizing the reconstruction and binary cross-entropy losses,CR-NSSD is trained to complete the task of m6A site identification.Extensive experiments have demonstrated the promising performance of CR-NSSD by comparing it with several state-of-the-art m6A identification algorithms.Moreover,the results of cross-species prediction indicate that the integration of sequential and structural dependencies allows CR-NSSD to capture general features of m6A modification sites among different species,thus improving the accuracy of cross-species identification.展开更多
Thucydides asserts that the occupation of Decelea by the Spartans in 413 BC made the grain supply for Athens costly by forcing the transport from land onto the sea.This calls into question the well-established consens...Thucydides asserts that the occupation of Decelea by the Spartans in 413 BC made the grain supply for Athens costly by forcing the transport from land onto the sea.This calls into question the well-established consensus that sea transport was far cheaper than land transport.This paper contends that the cost of protecting supply lines-specifically the expenses associated with the warships which escorted the supply ships-rendered the grain transported on the new route exceptionally costly.In this paper,the benefits and drawbacks of a maritime economy,including transaction costs,trade dependencies,and the capabilities of warships and supply ships are discussed.展开更多
Theory of rough sets, proposed by Zdzislaw Pawlak in 1982, is a model of approximate reasoning. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads t...Theory of rough sets, proposed by Zdzislaw Pawlak in 1982, is a model of approximate reasoning. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to significant results in many areas including, for example, finance, industry, multimedia, medicine, and most recently bioinformatics.展开更多
In the field of data-driven bearing fault diagnosis,convolutional neural network(CNN)has been widely researched and applied due to its superior feature extraction and classification ability.However,the convolutional o...In the field of data-driven bearing fault diagnosis,convolutional neural network(CNN)has been widely researched and applied due to its superior feature extraction and classification ability.However,the convolutional operation could only process a local neighborhood at a time and thus lack the ability of capturing long-range dependencies.Therefore,building an efficient learning method for long-range dependencies is crucial to comprehend and express signal features considering that the vibration signals obtained in a real industrial environment always have strong instability,periodicity,and temporal correlation.This paper introduces nonlocal mean to the CNN and presents a 1D nonlocal block(1D-NLB)to extract long-range dependencies.The 1D-NLB computes the response at a position as a weighted average value of the features at all positions.Based on it,we propose a nonlocal 1D convolutional neural network(NL-1DCNN)aiming at rolling bearing fault diagnosis.Furthermore,the 1D-NLB could be simply plugged into most existing deep learning architecture to improve their fault diagnosis ability.Under multiple noise conditions,the 1D-NLB improves the performance of the CNN on the wheelset bearing data set of high-speed train and the Case Western Reserve University bearing data set.The experiment results show that the NL-1DCNN exhibits superior results compared with six state-of-the-art fault diagnosis methods.展开更多
This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optiflml perturbation （CNOP） method for forecasts of two typhoons. Typhoon Meari （2004） was weakly no...This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optiflml perturbation （CNOP） method for forecasts of two typhoons. Typhoon Meari （2004） was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa （2005） was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.展开更多
This paper summarizes the main instrumental and methodological points of the tidal research which was performed in the framework of the National Scientific Research Fund Project K101603. Since the project is still run...This paper summarizes the main instrumental and methodological points of the tidal research which was performed in the framework of the National Scientific Research Fund Project K101603. Since the project is still running the tidal analysis results published here are only preliminary. Unmodelled tidal effects have been highlighted in some recent absolute gravity measurements carried out in the Pannonian basin resulting in a periodic modulation exceeding the typical standard deviations （±1microGal） of the drop sets. Since the most dominant source of the daily gravity variation is the bulk tidal effect, the goal of the project is to check its location dependency at BGal level. Unfortunately Hungary has had no dedicated instrumentation, so an effort was made to make the available LaCoste- Romberg spring G meters capable for continuous recording. As a reference instrument the GWR SG025 operated in the Conrad Observatory, Austria was also used and in the mean time of the project, a Scintrex CG-5 became also available, Eventually 6 instruments at 5 different locations were operated for 3 9 months mainly in co-located configuration. Although many experiments （moving mass calibrations） were done to determine the scale factors and scale functions of the instruments, the direct comparison of the tidal parameters obtained from the observations is still questionable. Therefore the ratio of the delta factors of O1 and M2 tidal constituents was investigated supposing that M2 is much more influenced by the ocean loading effect than O1. The slight detected increase of δ（O1 ）/δ（M2） （≈0.2%） toward east does not contradict to theory. This result has to be validated in the near future by analyzing available ocean loading models.展开更多
With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependenc...With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic(LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on j BPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.展开更多
This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets...This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.展开更多
In uncertain data management, lineages are often used for probability computation of result tuples. However, most of existing works focus on tuple level lineage, which results in imprecise data derivation. Besides, co...In uncertain data management, lineages are often used for probability computation of result tuples. However, most of existing works focus on tuple level lineage, which results in imprecise data derivation. Besides, correlations among attributes cannot be captured. In this paper, for base tuples with multiple uncertain attributes, we define attribute level annotation to annotate each attribute. Utilizing these annotations to generate lineages of result tuples can realize more precise derivation. Simultaneously,they can be used for dependency graph construction. Utilizing dependency graph, we can represent not only constraints on schemas but also correlations among attributes. Combining the dependency graph and attribute level lineage, we can correctly compute probabilities of result tuples and precisely derivate data. In experiments, comparing lineage on tuple level and attribute level, it shows that our method has advantages on derivation precision and storage cost.展开更多
Temperature and doping dependencies of the transport properties have been calculated using an ensemble Monte Carlo simulation. We consider the polar optical phonon, acoustic phonons, piezoelectric, intervalley scatter...Temperature and doping dependencies of the transport properties have been calculated using an ensemble Monte Carlo simulation. We consider the polar optical phonon, acoustic phonons, piezoelectric, intervalley scatterings and Charged impurity scattering model of Ridley;furthermore, a non nonparabolic three-valley model is used. Our simulation results have shown that the electron velocity in GaN is less sensitive to changes in temperature than that associated with GaAs. Also it is found that GaN exhibits high peak drift velocity at room temperature, 2.8 × 105m/s, at doping concentration of 1 × 1020 m–3and the electron drift velocity relaxes to the saturation value of 1.3 × 105 m/s which is much larger than that of GaAs. The weakening of the phonon emission rate at low temperature explains the extremely high low field mobility. Our results suggest that the transport characteristics of GaN are superior to that of GaAs, over a wide range of temperatures, from 100 K to 700 K, and doping concentrations, up to 1 × 1025展开更多
The escalation of compound extreme events has resulted in noteworthy economic and property losses.Recognizing the intricate interconnections among these events has become imperative.To tackle this challenge,we have fo...The escalation of compound extreme events has resulted in noteworthy economic and property losses.Recognizing the intricate interconnections among these events has become imperative.To tackle this challenge,we have formulated a comprehensive framework for the systematic analysis of their dependencies.This framework consists of three steps.(1)Define extreme events using Mahalanobis distance thresholds.(2)Represent dependencies among multiple extreme events through a point process-based method.(3)Verify dependencies with residual tail coefficients,determining thefinal dependency structure.Applying this framework to assess the extreme dependence of precipitation on wind speed and temperature in China,revealed four distinct dependency structures.In northern,Jianghuai,and southern China,precipitation heavily relies on wind speed,while tempera-tures maintain relative independence.In northeastern and northwestern China,precipitation exhibits relative independence,yet a notable dependence exists between temperatures and wind speed.In southwestern China,precipitation strongly depends on temperature,while wind speed remains relatively indepen-dent.The Qinghai–Tibet Plateau region displays a significant dependence relationship among precipitation,wind speed,and temperature,with weaker dependence between extreme wind speed and temperature.This framework is instrumental for analyzing dependencies among extreme values in compound events.展开更多
Conspecific negative density dependencies(CNDDs)foster biodiversity through reducing the chances of competitive exclusion in plant communities and have therefore fascinated ecologists.A major driver of CNDDs is plant-...Conspecific negative density dependencies(CNDDs)foster biodiversity through reducing the chances of competitive exclusion in plant communities and have therefore fascinated ecologists.A major driver of CNDDs is plant-soil feedback,and a lot of the literature assumes that the triggers of CNDDs concur with those for plant-soil feedback.Here,we suggest that a core assumption of a lot of the literature on CNDDs,that CNDDs are stronger in AM-associated than ECM-associated trees,is not quite as well supported as widely claimed.We think that dismissing this very important consideration prevents us from identifying a major gap in the literature on CNDDs.The vast majority of the literature on mycorrhiza-induced CNDDs originates from temperate systems,but the findings are extrapolated across divergent ecosystems.We then develop the argument that likely propagule limitations for arbuscular mycorrhizal trees in temperate forests might be inducing stronger CNDDs than they do at propagule sufficiency,which arbuscular mycorrhizal trees usually experience in other systems.We are thus contributing a new hypothesis in the field of mycorrhizal ecology with the potential to unify observations across scales and biomes.展开更多
Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,o...Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,only loose constraints have been established to date.Current constraints are based on the assumption that the cross section is a quadratic function of the trilinear Higgs self-coupling within the framework.Incorporating higher-order quantum corrections from virtual Higgs bosons would significantly alter this functional form,introducing new quartic and cubic power dependencies on the trilinear Higgs self-coupling.To derive this new functional form,we propose a specialized renormalization procedure that tracks all Higgs self-couplings at each calculation step.Additionally,we introduce renormalization constants for coupling modifiers within the framework to ensure the cancellation of all ultraviolet divergences.With new functional forms of the cross sections in both the gluon-gluon fusion and vector boson fusion channels,the upper limit of kλ_(3H)=λ_(3H)^(SM)set by the ATLAS(CMS)collaboration is reduced from 6.6(6.49)to 5.4(5.37).However,extracting a meaningful constraint on the quartic Higgs self-coupling from Higgs boson pair production data remains challenging.We also present the invariant mass distributions of the Higgs boson pair at different values of the self-couplings,which could assist in setting optimal cuts for experimental analysis.展开更多
Background:“Gateway Drugs Theory”indicates the assumption that the use of an illicit drug or psychoactive substance may be associated with a greater likelihood of switching to using more harmful substances.Materials...Background:“Gateway Drugs Theory”indicates the assumption that the use of an illicit drug or psychoactive substance may be associated with a greater likelihood of switching to using more harmful substances.Materials and Methods:With reference to this theory,the objective of this study is to understand how many of the subjects that referred to the Service for Pathological Dependencies(SerDP)of Parma,from 2016 to 2019,and who kicked off their addiction to cannabis,have then switched to the use of different drugs,by analysing all the information obtained from the patients and their health life archive.Results:The total number of patients considered was 160(142 males and 18 females).35 out of 160 subjects(21.9%)manifested the switch,i.e.a substance"escalation"that induced the subject to being using cannabis as another drug.60%of the patients(21/35),after an average of 2 years of cannabis use,started abusing cocaine too.Among them,moreover,few particular cases arose,namely 4,in which simultaneous positivity also resulted for other substances.It turns out that 17 patients(48.6%)out of 35 experienced the switch towards cocaine,while 4 patients(11.4%)manifested a switch to more than one substance.Considering the passage to opiates,9 patients were identified(25.7%).5 patients all switched to amphetamine(14.3%).Conclusions:The theory of cannabis as a gateway drug should be associated with the theory of vulnerability according to which some people,due to genetic,individual and environmental characteristics,are more exposed at the risk of developing addiction if placed in contact with drugs.展开更多
Traditional attack descriptions and threat modeling are discussed directly from the perspective of attacking infrastructure,i.e.,platforms,using malicious code.For example,it is believed that exploiting vulnerabilitie...Traditional attack descriptions and threat modeling are discussed directly from the perspective of attacking infrastructure,i.e.,platforms,using malicious code.For example,it is believed that exploiting vulnerabilities to access the system,and then invading the target platform that support the specified business through lateral movement can achieve the purpose of attacking the business.The most classic Cyber Kill Chain model expresses the attack process almost directly as a life cycle of malicious code execution,but in fact there are many ways can be utilized by adversary,such as the dependencies among businesses.In this paper,we discuss threat transmission from a business perspective.In a business dependency sequence,if any of the businesses prior to the specified business is abnormal,it is unlikely that the business will operate normally either.This leads adversary to target various business support platforms of the business dependent sequence in order to disrupt the normal operation of the target business,rather than attacking through lateral movement.For adversary organizations whose goal is to paralyze the architecture which includes many systems,they will utilize the interrelationships of businesses in the architecture to make the effects of the attack transmit from business to business,this attack pattern cannot be described by traditional threat models.This paper constructs an architecture model that integrates the platform and business,and also constructs a threat model that reflects the ripple effect of threats utilizing the dependency among businesses.The threat model is able to characterize the logic of the transmission of the threat in the architecture after it encounters an attack.By using our architecture model and threat model to characterize real attack event and to model the financial scenario,this paper indicates that our threat modeling approach can be used for threat event assessment and threat effect inference.展开更多
文摘In the realm of video understanding,the demand for accurate and contextually rich video captioning has surged with the increasing volume and complexity of multimedia content.This research introduces an innovative solution for video captioning by integrating a Convolutional BiLSTM Convolutional Bidirectional Long Short-Term Memory(BiLSTM)constructed Variational Sequence-to-Sequence(CBVSS)approach.The proposed framework is adept at capturing intricate temporal dependencies within video sequences,enabling a more nuanced and contextually relevant description of dynamic scenes.However,optimizing its parameters for improved performance remains a crucial challenge.In response,in this research Golden Eagle Optimization(GEO)a metaheuristic optimization technique is used to fine-tune the Convolutional BiLSTM variational sequence-to-sequence model parameters.The application of GEO aims to enhancing the CBVSS ability to produce more exact and contextually rich video captions.The proposed attains an overall higher Recall of 59.75%and Precision of 63.78%for both datasets.Additionally,the proposed CBVSS method demonstrated superior performance across both datasets,achieving the highest METEOR(25.67)and CIDER(39.87)scores on the ActivityNet dataset,and further outperforming all compared models on the YouCook2 dataset with METEOR(28.67)and CIDER(43.02),highlighting its effectiveness in generating semantically rich and contextually accurate video captions.
基金supported by grants from the National Key Research and Development Project of China(Grant No.2020YFA0112304)the National Natural Science Foundation of China(Grant Nos.91959207 and 82202883).
文摘Objective:Large-scale CRISPR screens have identified essential genes across cancer cell lines,but links between tumor functional properties and specific dependencies require investigation to reveal the mechanisms underlying dependencies and broaden understanding of targeted therapy.Methods:We selected 47 breast cancer cell lines from the Cancer Cell Line Encyclopedia(CCLE)with multi-omics data including gene dependency;somatic mutations;copy number alterations;and transcriptomic,proteomic,metabolomic,and methylation data.We established a dependency marker association(DMA)analytic pipeline by using linear regression modeling to assess associations between 3,874 representative gene dependencies and multi-omics markers.Additionally,we conducted non-negative matrix factorization clustering,to stratify breast cancer cell lines according to gene dependency features,and investigated cluster-specific DMAs.Results:We interpreted valuable DMAs according to two primary aspects.First,dependencies associated with gain-of-function alterations revealed addiction to lactate transporter SLC16A3,thus suggesting a promising therapeutic target.Second,dependencies associated with loss-of-function alterations included synthetic lethality(SL),collateral SL,and prioritized metabolic SL,encompassing paralog SL(e.g.,IMPDH1 and IMPDH2),single pathway SL(e.g.,GFPT1 and UAP1),and alternative pathway SL(e.g.,GPI and PGD).DMA analysis of the two clusters with divergent dependency signatures demonstrated that cluster1 cell lines exhibited extensive metabolism with mitochondrial protein dependencies,whereas cluster2 displays enhanced cell signaling,and reliance on DNA replication and membrane organelle regulators.Conclusions:We established a DMA analysis pipeline linking the gene dependencies of breast cancer cell lines to multi-omics characteristics,thus elucidating the underpinnings of tumor dependencies and offering a valuable resource for developing novel precision treatment strategies incorporating relevant markers.
基金Supported by the National Natural Science Foun-dation of China (60173051) , Teaching and Research Award Programfor Outstanding Young Teachers in Higher Education Institution ofthe Ministry of Education,the National Research Foundation for theDoctoral Programof Higher Education of China(20030145029) ,andthe Natural Science Foundationfor Doctoral Career Award of LiaoningProvince(20041016)
文摘In this paper, the definition of approximate XFDs based on value equality is proposed. Two metrics, sup port and strength, are presented for measuring the degree of approximate XFD. A basic algorithm is designed for extracting minimal set of approximate XFDs, and then two optimized strategies are proposed to improve the performance. Finally, the experimental results show that the optimized algorithms are correct and effective.
文摘Today, the quantity of data continues to increase, furthermore, the data are heterogeneous, from multiple sources (structured, semi-structured and unstructured) and with different levels of quality. Therefore, it is very likely to manipulate data without knowledge about their structures and their semantics. In fact, the meta-data may be insufficient or totally absent. Data Anomalies may be due to the poverty of their semantic descriptions, or even the absence of their description. In this paper, we propose an approach to better understand the semantics and the structure of the data. Our approach helps to correct automatically the intra-column anomalies and the inter-col- umns ones. We aim to improve the quality of data by processing the null values and the semantic dependencies between columns.
基金Supported by the National Natural Science Foundation of China (60573089)the National High Technology Research and Development Program of China (2006AA09Z139)
文摘According to the analysis of existing complicated functional dependencies constraint, we conclude the conditions of defining functional dependency in XML, and then we introduce the concept of the node value equality. A new path language and a new definition of functional dependencies in XML （XFD） are proposed XFD includes the relative XFD and the absolute XFD, in which absolute key and relative key are the particular cases. We focus on the logical implication and the closure problems, and propose a group of inference rules. Finally, some proofs of the correctness and completeness are given. XFD is powerful on expressing functional dependencies in XML causing data redundancy, and has a complete axiom system.
基金supported in part by the National Natural Science Foundation of China(62373348)the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01D05)+1 种基金the Tianshan Talent Training Program(2023TSYCLJ0021)the Pioneer Hundred Talents Program of Chinese Academy of Sciences.
文摘N6-methyladenosine(m6A)is an important RNA methylation modification involved in regulating diverse biological processes across multiple species.Hence,the identification of m6A modification sites provides valuable insight into the biological mechanisms of complex diseases at the post-transcriptional level.Although a variety of identification algorithms have been proposed recently,most of them capture the features of m6A modification sites by focusing on the sequential dependencies of nucleotides at different positions in RNA sequences,while ignoring the structural dependencies of nucleotides in their threedimensional structures.To overcome this issue,we propose a cross-species end-to-end deep learning model,namely CR-NSSD,which conduct a cross-domain representation learning process integrating nucleotide structural and sequential dependencies for RNA m6A site identification.Specifically,CR-NSSD first obtains the pre-coded representations of RNA sequences by incorporating the position information into single-nucleotide states with chaos game representation theory.It then constructs a crossdomain reconstruction encoder to learn the sequential and structural dependencies between nucleotides.By minimizing the reconstruction and binary cross-entropy losses,CR-NSSD is trained to complete the task of m6A site identification.Extensive experiments have demonstrated the promising performance of CR-NSSD by comparing it with several state-of-the-art m6A identification algorithms.Moreover,the results of cross-species prediction indicate that the integration of sequential and structural dependencies allows CR-NSSD to capture general features of m6A modification sites among different species,thus improving the accuracy of cross-species identification.
文摘Thucydides asserts that the occupation of Decelea by the Spartans in 413 BC made the grain supply for Athens costly by forcing the transport from land onto the sea.This calls into question the well-established consensus that sea transport was far cheaper than land transport.This paper contends that the cost of protecting supply lines-specifically the expenses associated with the warships which escorted the supply ships-rendered the grain transported on the new route exceptionally costly.In this paper,the benefits and drawbacks of a maritime economy,including transaction costs,trade dependencies,and the capabilities of warships and supply ships are discussed.
文摘Theory of rough sets, proposed by Zdzislaw Pawlak in 1982, is a model of approximate reasoning. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to significant results in many areas including, for example, finance, industry, multimedia, medicine, and most recently bioinformatics.
基金supported by the State Key Laboratory of Traction Power,Southwest Jiaotong University (TPL2104)the National Natural Science Foundation of China (61833002).
文摘In the field of data-driven bearing fault diagnosis,convolutional neural network(CNN)has been widely researched and applied due to its superior feature extraction and classification ability.However,the convolutional operation could only process a local neighborhood at a time and thus lack the ability of capturing long-range dependencies.Therefore,building an efficient learning method for long-range dependencies is crucial to comprehend and express signal features considering that the vibration signals obtained in a real industrial environment always have strong instability,periodicity,and temporal correlation.This paper introduces nonlocal mean to the CNN and presents a 1D nonlocal block(1D-NLB)to extract long-range dependencies.The 1D-NLB computes the response at a position as a weighted average value of the features at all positions.Based on it,we propose a nonlocal 1D convolutional neural network(NL-1DCNN)aiming at rolling bearing fault diagnosis.Furthermore,the 1D-NLB could be simply plugged into most existing deep learning architecture to improve their fault diagnosis ability.Under multiple noise conditions,the 1D-NLB improves the performance of the CNN on the wheelset bearing data set of high-speed train and the Case Western Reserve University bearing data set.The experiment results show that the NL-1DCNN exhibits superior results compared with six state-of-the-art fault diagnosis methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.41105038and40830955)the NationalKey Technology R&D Program(Grant No.2012BAC22B03)
文摘This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optiflml perturbation （CNOP） method for forecasts of two typhoons. Typhoon Meari （2004） was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa （2005） was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.
基金the financial support of NKFIH-OTKA in the framework of contract K101603
文摘This paper summarizes the main instrumental and methodological points of the tidal research which was performed in the framework of the National Scientific Research Fund Project K101603. Since the project is still running the tidal analysis results published here are only preliminary. Unmodelled tidal effects have been highlighted in some recent absolute gravity measurements carried out in the Pannonian basin resulting in a periodic modulation exceeding the typical standard deviations （±1microGal） of the drop sets. Since the most dominant source of the daily gravity variation is the bulk tidal effect, the goal of the project is to check its location dependency at BGal level. Unfortunately Hungary has had no dedicated instrumentation, so an effort was made to make the available LaCoste- Romberg spring G meters capable for continuous recording. As a reference instrument the GWR SG025 operated in the Conrad Observatory, Austria was also used and in the mean time of the project, a Scintrex CG-5 became also available, Eventually 6 instruments at 5 different locations were operated for 3 9 months mainly in co-located configuration. Although many experiments （moving mass calibrations） were done to determine the scale factors and scale functions of the instruments, the direct comparison of the tidal parameters obtained from the observations is still questionable. Therefore the ratio of the delta factors of O1 and M2 tidal constituents was investigated supposing that M2 is much more influenced by the ocean loading effect than O1. The slight detected increase of δ（O1 ）/δ（M2） （≈0.2%） toward east does not contradict to theory. This result has to be validated in the near future by analyzing available ocean loading models.
基金supported by the National Natural Science Foundation of China (No. 61502043, No. 61132001)Beijing Natural Science Foundation (No. 4162042)BeiJing Talents Fund (No. 2015000020124G082)
文摘With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic(LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on j BPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.
文摘This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.
基金Supported by the Key Program of National Natural Science Foundation of China(61232002)The National Natural Science Foundation of China(61202033)+2 种基金The Program for Innovative Research Team of Wuhan(2014070504020237)The Ph.D.Seed Foundation of Wuhan University(2012211020207)The Science and Technology Support Program of Hubei Province(2015BAA127)
文摘In uncertain data management, lineages are often used for probability computation of result tuples. However, most of existing works focus on tuple level lineage, which results in imprecise data derivation. Besides, correlations among attributes cannot be captured. In this paper, for base tuples with multiple uncertain attributes, we define attribute level annotation to annotate each attribute. Utilizing these annotations to generate lineages of result tuples can realize more precise derivation. Simultaneously,they can be used for dependency graph construction. Utilizing dependency graph, we can represent not only constraints on schemas but also correlations among attributes. Combining the dependency graph and attribute level lineage, we can correctly compute probabilities of result tuples and precisely derivate data. In experiments, comparing lineage on tuple level and attribute level, it shows that our method has advantages on derivation precision and storage cost.
文摘Temperature and doping dependencies of the transport properties have been calculated using an ensemble Monte Carlo simulation. We consider the polar optical phonon, acoustic phonons, piezoelectric, intervalley scatterings and Charged impurity scattering model of Ridley;furthermore, a non nonparabolic three-valley model is used. Our simulation results have shown that the electron velocity in GaN is less sensitive to changes in temperature than that associated with GaAs. Also it is found that GaN exhibits high peak drift velocity at room temperature, 2.8 × 105m/s, at doping concentration of 1 × 1020 m–3and the electron drift velocity relaxes to the saturation value of 1.3 × 105 m/s which is much larger than that of GaAs. The weakening of the phonon emission rate at low temperature explains the extremely high low field mobility. Our results suggest that the transport characteristics of GaN are superior to that of GaAs, over a wide range of temperatures, from 100 K to 700 K, and doping concentrations, up to 1 × 1025
基金National Key R&D Program of China,Grant/Award Number:2022YFC3002705National Natural Science Foundation of China,Grant/Award Number:5220904China Institute of Water Resources and Hydropower Research,Grant/Award Number:SKL2022TS11。
文摘The escalation of compound extreme events has resulted in noteworthy economic and property losses.Recognizing the intricate interconnections among these events has become imperative.To tackle this challenge,we have formulated a comprehensive framework for the systematic analysis of their dependencies.This framework consists of three steps.(1)Define extreme events using Mahalanobis distance thresholds.(2)Represent dependencies among multiple extreme events through a point process-based method.(3)Verify dependencies with residual tail coefficients,determining thefinal dependency structure.Applying this framework to assess the extreme dependence of precipitation on wind speed and temperature in China,revealed four distinct dependency structures.In northern,Jianghuai,and southern China,precipitation heavily relies on wind speed,while tempera-tures maintain relative independence.In northeastern and northwestern China,precipitation exhibits relative independence,yet a notable dependence exists between temperatures and wind speed.In southwestern China,precipitation strongly depends on temperature,while wind speed remains relatively indepen-dent.The Qinghai–Tibet Plateau region displays a significant dependence relationship among precipitation,wind speed,and temperature,with weaker dependence between extreme wind speed and temperature.This framework is instrumental for analyzing dependencies among extreme values in compound events.
基金the National Natural Science Foundation of China(Grant:“MycoDisp:Implications of connectance of mycorrhizal habitats for the functioning of ecosystems”,with the grant agreement number C0311-32371721).
文摘Conspecific negative density dependencies(CNDDs)foster biodiversity through reducing the chances of competitive exclusion in plant communities and have therefore fascinated ecologists.A major driver of CNDDs is plant-soil feedback,and a lot of the literature assumes that the triggers of CNDDs concur with those for plant-soil feedback.Here,we suggest that a core assumption of a lot of the literature on CNDDs,that CNDDs are stronger in AM-associated than ECM-associated trees,is not quite as well supported as widely claimed.We think that dismissing this very important consideration prevents us from identifying a major gap in the literature on CNDDs.The vast majority of the literature on mycorrhiza-induced CNDDs originates from temperate systems,but the findings are extrapolated across divergent ecosystems.We then develop the argument that likely propagule limitations for arbuscular mycorrhizal trees in temperate forests might be inducing stronger CNDDs than they do at propagule sufficiency,which arbuscular mycorrhizal trees usually experience in other systems.We are thus contributing a new hypothesis in the field of mycorrhizal ecology with the potential to unify observations across scales and biomes.
基金Supported in part by the National Natural Science Foundation of China(12275156,12321005,12375076)and the Taishan Scholar Foundation of Shandong province(tsqn201909011)。
文摘Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,only loose constraints have been established to date.Current constraints are based on the assumption that the cross section is a quadratic function of the trilinear Higgs self-coupling within the framework.Incorporating higher-order quantum corrections from virtual Higgs bosons would significantly alter this functional form,introducing new quartic and cubic power dependencies on the trilinear Higgs self-coupling.To derive this new functional form,we propose a specialized renormalization procedure that tracks all Higgs self-couplings at each calculation step.Additionally,we introduce renormalization constants for coupling modifiers within the framework to ensure the cancellation of all ultraviolet divergences.With new functional forms of the cross sections in both the gluon-gluon fusion and vector boson fusion channels,the upper limit of kλ_(3H)=λ_(3H)^(SM)set by the ATLAS(CMS)collaboration is reduced from 6.6(6.49)to 5.4(5.37).However,extracting a meaningful constraint on the quartic Higgs self-coupling from Higgs boson pair production data remains challenging.We also present the invariant mass distributions of the Higgs boson pair at different values of the self-couplings,which could assist in setting optimal cuts for experimental analysis.
文摘Background:“Gateway Drugs Theory”indicates the assumption that the use of an illicit drug or psychoactive substance may be associated with a greater likelihood of switching to using more harmful substances.Materials and Methods:With reference to this theory,the objective of this study is to understand how many of the subjects that referred to the Service for Pathological Dependencies(SerDP)of Parma,from 2016 to 2019,and who kicked off their addiction to cannabis,have then switched to the use of different drugs,by analysing all the information obtained from the patients and their health life archive.Results:The total number of patients considered was 160(142 males and 18 females).35 out of 160 subjects(21.9%)manifested the switch,i.e.a substance"escalation"that induced the subject to being using cannabis as another drug.60%of the patients(21/35),after an average of 2 years of cannabis use,started abusing cocaine too.Among them,moreover,few particular cases arose,namely 4,in which simultaneous positivity also resulted for other substances.It turns out that 17 patients(48.6%)out of 35 experienced the switch towards cocaine,while 4 patients(11.4%)manifested a switch to more than one substance.Considering the passage to opiates,9 patients were identified(25.7%).5 patients all switched to amphetamine(14.3%).Conclusions:The theory of cannabis as a gateway drug should be associated with the theory of vulnerability according to which some people,due to genetic,individual and environmental characteristics,are more exposed at the risk of developing addiction if placed in contact with drugs.
基金supported by the National Natural Science Foundation of China under Grants No.62302122the Key R&D Program of Heilongjiang Province of China under Grants No.JD2023SJ07
文摘Traditional attack descriptions and threat modeling are discussed directly from the perspective of attacking infrastructure,i.e.,platforms,using malicious code.For example,it is believed that exploiting vulnerabilities to access the system,and then invading the target platform that support the specified business through lateral movement can achieve the purpose of attacking the business.The most classic Cyber Kill Chain model expresses the attack process almost directly as a life cycle of malicious code execution,but in fact there are many ways can be utilized by adversary,such as the dependencies among businesses.In this paper,we discuss threat transmission from a business perspective.In a business dependency sequence,if any of the businesses prior to the specified business is abnormal,it is unlikely that the business will operate normally either.This leads adversary to target various business support platforms of the business dependent sequence in order to disrupt the normal operation of the target business,rather than attacking through lateral movement.For adversary organizations whose goal is to paralyze the architecture which includes many systems,they will utilize the interrelationships of businesses in the architecture to make the effects of the attack transmit from business to business,this attack pattern cannot be described by traditional threat models.This paper constructs an architecture model that integrates the platform and business,and also constructs a threat model that reflects the ripple effect of threats utilizing the dependency among businesses.The threat model is able to characterize the logic of the transmission of the threat in the architecture after it encounters an attack.By using our architecture model and threat model to characterize real attack event and to model the financial scenario,this paper indicates that our threat modeling approach can be used for threat event assessment and threat effect inference.
