Leukoaraiosis is associated with clinical symptom severity,poor neurological function prognosis and stroke recurrence in mild intracerebral hemorrhage:a prospective multi-center cohort study

Leukoaraiosis(LA)results from ischemic injury in small cerebral vessels,which may be attributable to decreased vascular density,reduced cerebrovascular angiogenesis,decreased cerebral blood flow,or microcirculatory dysfunction in the brain.In this study,we enrolled 357 patients with mild intracerebral hemorrhage(ICH)from five hospitals in China and analyzed the relationships between LA and clinical symptom severity at admission,neurological function prognosis at 3 months,and 1-year stroke recurrence.Patients were divided into groups based on Fazekas scale scores:no LA(n=83),mild LA(n=64),moderate LA(n=98)and severe LA(n=112).More severe LA,larger hematoma volume,and higher blood glucose level at admission were associated with more severe neurological deficit.More severe LA,older age and larger hematoma volume were associated with worse neurological function prognosis at 3 months.In addition,moderate-to-severe LA,admission glucose and symptom-free cerebral infarction were associated with 1-year stroke recurrence.These findings suggest that LA severity may be a potential marker of individual ICH vulnerability,which can be characterized by poor tolerance to intracerebral attack or poor recovery ability after ICH.Evaluating LA severity in patients with mild ICH may help neurologists to optimize treatment protocols.This study was approved by the Ethics Committee of Ruijin Hospital Affiliated to Shanghai Jiao Tong University(approval No.12)on March 10,2011.

Fast Computation of Sparse Data Cubes with Constraints

For a data cube there are always constraints between dimensions or among attributes in a dimension, such as functional dependencies. We introduce the problem that when there are functional dependencies, how to use them to speed up the computation of sparse data cubes. A new algorithm CFD (Computation by Functional Dependencies) is presented to satisfy this demand. CFD determines the order of dimensions by considering cardinalities of dimensions and functional dependencies between dimensions together, thus reduce the number of partitions for such dimensions. CFD also combines partitioning from bottom to up and aggregate computation from top to bottom to speed up the computation further. CFD can efficiently compute a data cube with hierarchies in a dimension from the smallest granularity to the coarsest one. Key words sparse data cube - functional dependency - dimension - partition - CFD CLC number TP 311 Foundation item: Supported by the E-Government Project of the Ministry of Science and Technology of China (2001BA110B01)Biography: Feng Yu-cai (1945-), male, Professor, research direction: database system.

Application of extension method to fault diagnosis of transformer

A novel extension diagnosis method was proposed for enhancing the diagnosis ability of the conventional dissolved gas analysis. Based on the extension theory a matter-element model was established for qualitatively and quantitatively describing the fault diagnosis problem of power transformers. The degree of relation based on the dependent functions was employed to determine the nature and the grade of the faults in a transformer system. And the proposed method was verified with the experimental data. The results show that accuracy rate of the diagnosis method exceeds 90% and two kinds of faults can be detected at the same time.

Multimodality magnetic resonance imaging in hepatic encephalopathy: An update

Hepatic encephalopathy(HE) is a neuropsychiatric complication of cirrhosis or acute liver failure. Currently, HE is regarded as a continuous cognitive impairment ranging from the mildest stage, minimal HE to overt HE. Hyperammonaemia and neuroinflammation are two main underlying factors which contribute to the neurological alterations in HE. Both structural and functional impairments are found in the white mater and grey mater involved in HE. Although the investigations into HE pathophysiological mechanism are enormous, the exact pathophysiological causes underlying HE remain controversial. Multimodality magnetic resonance imaging(MRI) plays an important role in helping to understand the pathological process of HE. This paper reviews the up-to-date multimodality MRI methods and predominant findings in HE patients with a highlight ofthe increasingly important role of blood oxygen level dependent functional MRI.

A Systematic Study of the Relationship between RRDB and FRDB

In this paper, based on rough set theory and relational database, the relationship between rough relational database (RRDB) and fuzzy relational database (FRDB) is analyzed systematically from functional dependency, normal form and Armstrong axiom. The results show that both fuzzy functional dependency and rough functional dependency are the generalizations of classical functional dependency.Fuzzy normal form is the expansion of classical normal form while rough normal form is an independent system.RRDB and FRDB obey Armstrong axiom to some extent from the point of view of inference rule.

The Cox-Aalen Models as Framework for Construction of Bivariate Probability Distributions, Universal Representation

Starting with the Aalen （1989） version of Cox （1972） ＇regression model＇ we show the method for construction of ＂any＂ joint survival function given marginal survival functions. Basically, however, we restrict ourselves to model positive stochastic dependences only with the general assumption that the underlying two marginal random variables are centered on the set of nonnegative real values. With only these assumptions we obtain nice general characterization of bivariate probability distributions that may play similar role as the copula methodology. Examples of reliability and biomedical applications are given.

DPIF:A Framework for Distinguishing Unintentional Quality Problems From Potential Shilling Attacks

Maliciously manufactured user profiles are often generated in batch for shilling attacks.These profiles may bring in a lot of quality problems but not worthy to be repaired.Since repairing data always be expensive,we need to scrutinize the data and pick out the data that really deserves to be repaired.In this paper,we focus on how to distinguish the unintentional data quality problems from the batch generated fake users for shilling attacks.A two-steps framework named DPIF is proposed for the distinguishment.Based on the framework,the metrics of homology and suspicious degree are proposed.The homology can be used to represent both the similarities of text and the data quality problems contained by different profiles.The suspicious degree can be used to identify potential attacks.The experiments on real-life data verified that the proposed framework and the corresponding metrics are effective.

An Optimized Approach for Extracting Approximate Functional Dependencies in XML Documents

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.

Functional Dependencies and Its Axiom System in XML

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.

Stability analysis of nonlinear Roesser-type two-dimensional systems via a homogenous polynomial technique

This paper is concerned with the problem of stability analysis of nonlinear Roesser-type two-dimensional （2D） systems. Firstly, the fuzzy modeling method for the usual one-dimensional （1D） systems is extended to the 2D ease so that the underlying nonlinear 2D system can be represented by the 2D Takagi Sugeno （TS） fuzzy model, which is convenient for implementing the stability analysis. Secondly, a new kind of fuzzy Lyapunov function, which is a homogeneous polynomially parameter dependent on fuzzy membership functions, is developed to conceive less conser- vative stability conditions for the TS Roesser-type 2D system. In the process of stability analysis, the obtained stability conditions approach exactness in the sense of convergence by applying some novel relaxed techniques. Moreover, the obtained result is formulated in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, a numerical example is also given to demonstrate the effectiveness of the proposed approach.

Developmental dependence for functional eye regrowth in Xenopus laevis

Introduction：A key challenge in designing tissue repair strategies is knowing whether and how developmental mechanisms are used for successful repair of mature/adult tissues.Although it is known that developmental components are used in repair,it remains mostly unclear which ones are required and whether they act similarly as during development.This issue is further complicated by the fact that it is difficult.

Improve Data Quality by Processing Null Values and Semantic Dependencies

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.

The Effects of Oxidation States and Spin States of Chromium Interaction with <i>Sargassum Sp</i>.: A Spectroscopic and Density Functional Theoretical Study

The study of various oxidation states of chromium with Sargassum sp. is of particular interest since hexavalent chromium is reduced to trivalent chromium in an aqueous solution. In this study, a systematic density functional theory (DFT) calculations were performed to study the interactions of transition metal chromium ion with different oxidation states and spin states with the Sargassum sp. decorated with carboxylate (acetate) at the wB97XD/6-311++ G(d,p) level of theory. The structures and binding energies of chromium metal-carboxylate complexes at various oxidation states and spin states in gas phase were examined. The coordination strength of Cr(VI) with the acetate ligand was predominantly the strongest compared to the other oxidation states. Vibrational frequency analysis, for the homoleptic monomers of tris [CrIII(AC)3]0 and [CrVI(AC)3]3+ complexes, illustrate good harmony with the experimental and theoretical calculated frequencies. Using the time-dependent DFT (TD-DFT) at the level of CAM-B3LYP/6-311++G(d,p), the vertical excitation energies were obtained. The stabilization energies derived using the second order perturbation theory, Eij(2), of NBO analysis confirmed the greater charge transfer for the observed trends in the metal binding. The calculated binding energies (ΔE) and interactions energies SEij(2) favor the formation of [CrVI(AC)3]3+ complexes. The findings of this study identify efficient electronic factors as major contributors to the metal binding affinities, with promising possibilities for the design of metal-ligand complexes and sensing of the metal ions.

THE INTEGRAL AS A FUNCTlON OF THE UPPER LIMIT AND DEPENDING ON A PARAMETER TO SOLVE DRAWING THROUGH IDLING ROLLS

The relocity and sirain-rate .field which are different from Avilzur's have beenestablished in Caitesian coordinates. Using the integral as a function of the upper limitand integration depending on a parameler, an analylical upper-bound solution todrawing stress through idling rolls has been obtained in this paper.

Rheological Behaviour for Polymer Melts and Concentrated Solutions Part Ⅲ: A New Multiple Entanglement Model to Predict the Dependence of Linear Viscoelastic Function (η_0, Ψ_(10)~0,η_(ext)~0) on the Ranges of Primary Molecular Weights and the Species of Polymers

It is shown theoretically that the viscoelasticity of polymer melts is determined by three combining factorst they are the primary molecular weight and its distribution, the number of entanglement sites on polymer chain and the sequence distribution of constituent chains in entanglement spacings. A unified quantity for the three combing factors is the average constrained dimensional number of constituent chains in the long entanglement spacings (v). A new relation of v to the primary molecular weight and the number of testing polymers were derived from the multiple entanglement and reptation model, and a new method for determining v was proposed. The dependences of linear viscoelastic functions on the primary molecular weight and its distribution were derived by the statistical method. When Mn=6Me to 18 Me, the values of (v) can range from 3.33 to 3.70. Their values are in a good agreement with the experiment data, and it can slightjy vary with the different species of polymers and the different ranges of molecular weight of polymers

Fast Algorithms of Mining Probability Functional Dependency Rules in Relational Database

This paper defines a new kind of rule, probability functional dependency rule. The functional dependency degree can be depicted by this kind of rule. Five algorithms, from the simple to the complex, are presefited to mine this kind of rule in different condition. The related theorems are proved to ensure the high efficiency and the correctness of the above algorithms.

Discovering context-aware conditional functional dependencies

Conditional functional dependencies（CFDs） are important techniques for data consistency. However, CFDs are limited to 1） provide the reasonable values for consistency repairing and 2） detect potential errors. This paper presents context-aware conditional functional dependencies（CCFDs） which contribute to provide reasonable values and detect po- tential errors. Especially, we focus on automatically discov- ering minimal CCFDs. In this paper, we present context rela- tivity to measure the relationship of CFDs. The overlap of the related CFDs can provide reasonable values which result in more accuracy consistency repairing, and some related CFDs are combined into CCFDs. Moreover, we prove that discover- ing minimal CCFDs is NP-complete and we design the pre- cise method and the heuristic method. We also present the dominating value to facilitate the process in both the precise method and the heuristic method. Additionally, the context relativity of the CFDs affects the cleaning results. We will give an approximate threshold of context relativity accord- ing to data distribution for suggestion. The repairing results are approved more accuracy, even evidenced by our empirical evaluation.

Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

A min-max model predictive control strategy is proposed for a class of constrained nonlinear system whose trajectories can be embedded within those of a bank of linear parameter varying （LPV） models. The embedding LPV models can yield much better approximation of the nonlinear system dynamics than a single LTV model. For each LPV model, a parameter-dependent Lyapunov function is introduced to obtain poly-quadratically stable control law and to guarantee the feasibility and stability of the origi- nal nonlinear system. This approach can greatly reduce computational burden in traditional nonlinear predictive control strategy. Finally a simulation example illustrating the strategy is presented.

Determining the Real Data Completeness of a Relational Dataset

Low quality of data is a serious problem in the new era of big data, which can severely reduce the usability of data, mislead or bias the querying, analyzing and mining, and leads to huge loss. Incomplete data is common in low quality data, and it is necessary to determine the data completeness of a dataset to provide hints for follow-up operations on it.Little existing work focuses on the completeness of a dataset, and such work views all missing values as unknown values. In this paper, we study how to determine real data completeness of a relational dataset. By taking advantage of given functional dependencies, we aim to determine some missing attribute values by other tuples and capture the really missing attribute cells. We propose a data completeness model, formalize the problem of determining the real data completeness of a relational dataset, and give a lower bound of the time complexity of this problem. Two optimal algorithms to determine the data completeness of a dataset for different cases are proposed. We empirically show the effectiveness and the scalability of our algorithms on both real-world data and synthetic data.

Reliability evaluation of PMS considering coupling effect of functional and physical dependency

Aviation and aerospace system are typical Phased-Mission Systems(PMSs)featured with varying configuration,phased load condition and cross phase failure correlation.The coupling effect of Functional Dependency(FDEP)and Physical Dependency(PDEP)has a unique influence on the failure behavior of PMS.In this article,the coupling effect is analyzed,and the degradation of components is modeled with the positive drift wiener process,in which the drift coefficient is related to environmental conditions and operation stress.Finally,failure behavior and system reliability are simulated.An avionics controller is studied as a case,with the degradation time distribution model and simulation algorithm,the coupling effect and dynamical system reliability can be achieved.Results show that this modeling method can describe the coupling effects of FDEP and PDEP and their influence on the failure behavior and reliability of the PMS system.