Active Database Research Articles

Characterization of a Thermobifida fusca β-1,3-Glucanase (Lam81A) with a Potential Role in Plant Biomass Degradation

Thermobifida fusca is a filamentous soil bacterium that plays a major role in the breakdown of plant biomass. In this paper, we report the cloning, expression, purification, and characterization of the T. fusca enzyme, Lam81A. The Carbohydrate Active Enzymes Database (http://afmb.cnrs-mrs.fr/CAZY/) indicates that Lam81A belongs to a relatively uncharacterized family of beta-1,3-glucanases, family GH-81 [Coutinho, P. M., and Henrissat, B. (1999) in Recent Advances in Carbohydrate Bioengineering (Gilbert, H. J., Davies, G., Henrissat, B., and Svensson, B., Eds.) pp 3-12, The Royal Society of Chemistry, Cambridge, U.K.]. Microarray analysis suggests that Lam81A plays a role in biomass degradation, where its natural substrate may be the plant cell wall polysaccharide, callose, which is a polymer of beta-1,3-linked glucose. Characterization of Lam81A has shown that the enzyme is specific for beta-1,3-linked glucose polysaccharides, is endohydrolytic, and utilizes an inverting mechanism for substrate hydrolysis. In addition, the enzyme has a broad pH optimum from 5.5 to 10, a temperature optimum of 50 degrees C, and demonstrates substrate inhibition, as well as showing a high basal level of expression.

Extending the OBJECTIVE Benchmark for Evaluation of Active Rules in a Distributed Component Integration Environment

This research presents a benchmark for the evaluation of active rules within a distributed component integration environment. The benchmark is based on the OBJECTIVE active database benchmark. Our work was specifically performed in the context of the Integration Rules (IRules) project that uses active rules for the integration of distributed software components, which are based on the Enterprise JavaBeans component model. In addition to mapping the test rules of the OBJECTIVE benchmark to the integration rules of the IRules system, we have extended the OBJECTIVE benchmark to test additional features of a component-based active rule system, such as the event detection time, the rule execution time related to the invocation of methods on components, asynchronous coupling modes, and the rule processor execution time under a heavy event load. Although the research presents specific performance evaluation results for the IRules project, the approach more generally demonstrates the manner in which an existing rule processing benchmark for a centralized environment can be adapted and extended for use in a rule-based approach to distributed component integration.

Meta-Analysis of Aggression or Hostility Events in Randomized, Controlled Clinical Trials of Atomoxetine for ADHD

We systematically examined potential aggression/hostility-related events in a meta-analysis of acute clinical trials of atomoxetine for attention-deficit/hyperactivity disorder (ADHD). Pediatric patients from 14 trials of atomoxetine were subdivided into a placebo-controlled (atomoxetine n = 1308, placebo n = 806) or active comparator databases (atomoxetine n = 566, methylphenidate n = 472). A third database comprised adult patients from placebo-controlled studies (atomoxetine n = 541, placebo n = 405). A computerized search of adverse events and comments identified patients with potential aggression/hostility events. Mantel-Haenszel incidence differences (MHID) were calculated. In the placebo-controlled database, we observed 21 atomoxetine and 9 placebo patients with reported aggression/hostility events, MHID of .6% (95% confidence interval [CI]: -.4, 1.7). In the active comparator database, there were seven events in atomoxetine and four in methylphenidate patients, MHID = .2% (95% CI: -1.0,1.3). In the adult database, there were no events in 0 atomoxetine and one placebo patient, MHID = -.3% (95% CI: -.8, .2). Aggression/hostility-related events occurred in less than 2% of patients and were more frequent in pediatric patients treated with atomoxetine versus placebo (risk ratio of 1.33; not statistically significant). The risk of aggression/hostility events was similar in patients treated with atomoxetine or methylphenidate.

Predicting Hospitalization and Mortality in End-Stage Renal Disease (ESRD) Patients Using an Index of Coexisting Disease (ICED)–Based Risk Stratification Model

We evaluated the use of an additive Index of Coexisting Diseases (ICED)-based stratification schema to determine subsequent hospitalization and mortality in a hemodialysis population. Patients from five commercial health plans were stratified into low-, medium-, and high-risk groups and followed for up to 1 year. Patients were reassessed and restratified at 90-day intervals and censored when disease management ceased. Outcome measures collected through selfreports and health plan records were captured in an active database. Survival to first hospitalization/ mortality was compared by Kaplan Meier curves, survivor function differences by the Wilcoxon test, and group comparisons by ANOVA and chi square. Population characteristics included mean age of 63.0, 57.7% male, and 58.8% diabetic. Mortality was 13.0% per patient year (standardized mortality ratio 0.43) and the hospitalization rate was 0.59 per patient year (standardized hospitalization ratio 0.24). Survival curves demonstrated differences in mortality and hospitalization between the patients in different initial risk categories (p < 0.01). Mean hospitalizations were 0.81 +/- 1.53 per patient year (high risk), 0.45 +/- 0.99 (medium risk), and 0.15 +/- 0.51 for the low-risk group (p < 0.001). Stratification was dynamic; 47.3% decreased and 4.7% increased risk level between the first and second assessment. These changes were associated with survival differences for initial low (p = 0.06) or medium patients (p < 0.01), and hospital-free survival for initial medium (p = 0.08) or high patients (p < 0.05). In conclusion, this ICED-based stratification schema predicted mortality and hospitalization for hemodialysis patients participating in our disease management program.

Information fusion for simulation based decision support in manufacturing

Robust and informed decisions are important for the efficient and effective operation of installed production facilities. The paper discusses Information fusion (IF) including a generic model for IF, and situations for decision-making. The paper also discusses current and future use of manufacturing resource simulation for design/configuration, operational planning and scheduling, and service and maintenance of manufacturing systems. Many of these applications use IF in some way, as is explained in more detail for simulation based service and maintenance. An extension of the generic model for IF is presented which incorporates modeling and simulation, and active databases as used in a simulation based service and maintenance system at the authors’ laboratory.

Weight, Dietary and Physical Activity Behaviors Two Years after Gastric Bypass

This cross-sectional survey was designed to determine the self-reported weight management, dietary and physical activity behaviors of Roux-en-Y gastric bypass (RYGBP) patients who were 1 to 4 years after the RYGBP operation, and to identify gaps in follow-up nutrition-related chronic disease prevention. Questionnaires including behavioral items from the 2003 and 2004 Behavioral Risk Factor Surveillance System (BRFSS) were mailed to all RYGBP patients in a clinically active outpatient database. Of 212 patients, 140 (66%) returned completed questionnaires. Responders were 24.2 +/- 7.9 months postoperatively. They were older than nonresponders (45.2 +/- 9.9 vs 38.5 +/- 8.9 years, P<.001). Responders had an average weight loss of 55.8 +/- 15.2 kg, and most (81%) reported that they were still trying to lose weight. The most frequently reported dietary behavior for weight loss was decreasing calorie and fat intakes. However, in addition to avoiding sodas and sweet desserts, responders were also excluding nutrient-dense foods high in vitamins and minerals such as milk and dairy products, red meats, breads, cereals and nuts. Remarkably, only 25 (17.9%) engaged in regular exercise activities before surgery, while 116 (82.9%) indicated a moderate level of current physical activity averaging 54.7 +/- 38.5 minutes per episode. Multivariable linear regression analyses identified age, weight at age 21, pre-surgery BMI and time in regular physical activities as the four significant predictors of BMI after weight loss stabilization. Postoperative RYGBP patients engage in various weight management behaviors, some of which could offer greater health benefits with follow-up intervention from dietitians and exercise specialists to prevent adverse outcomes such as weight regain and micronutrient deficiencies.

능동 데이터베이스를 이용한 직접부하제어

본 연구에서는 우선순위기반의 동적 프로그래밍 기법을 이용하여 제안된 기존의 직접부하제어 알고리즘과 본 연구에서 제시되는 능동 데이터베이스를 연동시킨 직접부하제어시스템을 제안하였다. 능동 데이터베이스 구축을 위해, 데이터베이스의 요구 사항을 분석하여 E-R Diagram을 이용한 개념을 도입하여 데이터베이스를 설계 후 이를 시스템으로 구현하였다. 그 후 현재 부하량 또는 15분 후의 부하량이 목적 부하량을 초과하는 경우에 사용자의 개입 없이 직접부하제어가 이루어지도록 하기 위해 기존의 직접부하제어 알고리즘을 능동 규칙으로 모델링 하여 데이터베이스에 부과하였다. 그 결과, 직접부하제어 시스템의 데이터 관리에서 빈번한 부하의 ON/OFF에 따른 이들 데이터의 갱신 등이 발생할 경우 반드시 지켜져야 되는 무결성 검증과 현재 전력량 또는 15분 후의 전력량이 갑작스럽게 증가할 경우, 이를 해결하기 위해 사용자의 개입 없는 시스템이 자동적으로 대처할 수 있도록 하였다

A concurrent rule scheduling algorithm for active rules

The use of rules in a distributed environment creates new challenges for the development of active rule execution models. In particular, since a single event can trigger multiple rules that execute over distributed sources of data, it is important to make use of concurrent rule execution whenever possible. This paper presents the details of the integration rule scheduling (IRS) algorithm. Integration rules are active database rules that are used for component integration in a distributed environment. The IRS algorithm identifies rule conflicts for multiple rules triggered by the same event through static, compile-time analysis of the read and write sets of each rule. A unique aspect of the algorithm is that the conflict analysis includes the effects of nested rule execution that occurs as a result of using an execution model with an immediate coupling mode. The algorithm therefore identifies conflicts that may occur as a result of the concurrent execution of different rule triggering sequences. The rules are then formed into a priority graph before execution, defining the order in which rules triggered by the same event should be processed. Rules with the same priority can be executed concurrently. The IRS algorithm guarantees confluence in the final state of the rule execution. The IRS algorithm is applicable for rule scheduling in both distributed and centralized rule execution environments.

PressBase : a presentation synchronization database for distributed multimedia systems

Multimedia presentations are the basic objects of multimedia databases. Since a multimedia presentation is not an instant display of a query result, the control knowledge (or synchronization requirements) has to be incorporated into the database and necessary precautions have to be taken for a lengthy presentation. Active databases provide a mechanism for incorporation of control knowledge by using event-condition-action (ECA) rules. In this paper, we describe how multimedia synchronization can be handled within a database using ECA rules. We present a prototype presentation synchronization database, named as PressBase, for distributed multimedia systems. We have adopted one of the synchronization models, SynchRuler, and then incorporated into a relational database system.

An algebraic framework for temporal attribute characteristics

Most real-world database applications manage temporal data, i.e., data with associated time references that capture a temporal aspect of the data, typically either when the data is valid or when the data is known. Such applications abound in, e.g., the financial, medical, and scientific domains. In contrast to this, current database management systems offer preciously little built-in query language support for temporal data management. This situation persists although an active temporal database research community has demonstrated that application development can be simplified substantially by built-in temporal support. This paper's contribution is motivated by the observation that existing temporal data models and query languages generally make the same rigid assumption about the semantics of the association of data and time, namely that if a subset of the time domain is associated with some data then this implies the association of any further subset with the data. This paper offers a comprehensive, general framework where alternative semantics may co-exist. It supports so-called malleable and atomic temporal associations, in addition to the conventional ones mentioned above, which are termed constant. To demonstrate the utility of the framework, the paper defines a characteristics-enabled temporal algebra, termed CETA, which defines the traditional relational operators in the new framework. This contribution demonstrates that it is possible to provide built-in temporal support while making less rigid assumptions about the data and without jeopardizing the degree of the support. This moves temporal support closer to practical applications.

Model Checking Active Database Rules under Various Rule Processing Strategies

An active database is a database system that can react to internal, as well as external, database events. The reactive behavior of an active database is determined by a predefined set of active database rules, along with a rule processing strategy. A common problem associated with active database systems is the possible non-termination of the active database rules. Previous work on the analysis of the conditions required for the termination of active database rules has only considered limited rule processing strategies. This paper proposes an approach for automatically detecting the non-termination of active database rules using a model checking technique. With this approach, a general framework for modeling active database systems is first proposed. This framework is useful for analyzing the behavior of rules with different rule processing strategies and for allowing the adoption of different contexts and different execution coupling modes for the active database rules. Based on the proposed modeling framework, the termination property of active database rules with various rule processing strategies is next checked using SPIN, a model checking tool. Through experimental results, we demonstrated the feasibility of using this method.

Improving clinical care and elucidating the pathophysiology of Diamond Blackfan anemia: An update from the Diamond Blackfan Anemia Registry

Diamond Blackfan anemia (DBA) is a heterogeneous genetic disorder characterized by red cell aplasia, congenital anomalies, and a predisposition to cancer. Although incompletely understood, the erythroid failure in DBA appears to result from the accelerated apoptosis of affected erythroid progenitors/precursors. One of what appears to be multiple DBA genes, coding for a ribosomal protein RPS 19, has been cloned. Even within multiplex families individuals may vary dramatically as to the degree of anemia, response to treatment and the presence of congenital anomalies. The Diamond Blackfan Anemia Registry (DBAR), a comprehensive database of pediatric and adult patients with DBA who are enrolled after informed consent, was designed to overcome two significant obstacles encountered in the study of a rare disease; the reporting bias inherent in the literature and the lack of an active patient database. To enroll, patients, their families and their physicians complete a detailed questionnaire. A review of medical records and telephone interviews are performed to complete and clarify the information provided. As of May 1, 2005, 420 patients have been enrolled in the DBAR. Epidemiological, clinical, and laboratory data have been collected and analyzed. The DBAR has provided new information on the clinical presentation, outcome and genetics of DBA as well as a better description of congenital malformations and cancer predisposition. This has resulted both in improved clinical care of patients with DBA as well as providing new insights into the pathophysiology of this complex disorder.

Distribution and synchronisation of engineering information using active database technology

Today, work collaboration is normal practice in developing modern products. Engineering collaborative work involves a number of team members that need to share and exchange design ideas while working with engineering analysis tools such as mechanical computer aided engineering systems. This work presents the M-Sync prototype system that uses an active database approach to enable exchange of engineering information among distributed team members in a timely manner. The distributed data is fully accessible by the local member and is automatically synchronised between different places using a database management system that support event-condition-action (ECA) database rules. Only updates introduced at one location are distributed to other locations, thereby minimizing information transfer and enhancing performance. Members working at different locations can therefore work in a peer-to-peer (P2P) manner and interactively manipulate the same set of information at the same time.

SnoopIB: Interval-based event specification and detection for active databases

Detection-based semantics does not differentiate between event detection and event occurrence and has been used for detecting events in most of the active systems that support Event–Condition–Action rules. However, this is a limitation for many applications that require interval-based semantics. In this article, we formalize the detection of Snoop (an event specification language) event operators using interval-based semantics (termed SnoopIB) in various event consumption modes. We show how events are detected using event detection graphs, and present a few representative algorithms to detect SnoopIB operators and comment on their implementation in the context of Sentinel—an active object-oriented DBMS.

Prompting conceptual understanding with computer‐mediated peer discourse and knowledge acquisition techniques

AbstractNumerous computer‐mediated communication (CMC) tools have been designed to facilitate group discourses on the Web. However, previous studies noted that participants did not value online conferencing as a method for conducting in‐depth discussions, and instead considered this method as merely scratching the surface of the issues involved. Therefore, the teachers must moderate the online discourse to add value to the success of CMC. This study presents a methodology that uses knowledge acquisition techniques during online discourses to increase student conceptual understanding and evaluation skills. The methodology explains the conceptual frameworks of individuals and the conceptual relationships between student peers. Active database triggers then are applied to automatically monitor the conceptual relationships and to moderate online discourses between student peers. Student reactions demonstrated that discourses mediated by the repertory grid analysis technique helped group members not only promote common conceptual understandings but also to approach the level of conceptual understanding of the teacher.

Noncompliance with Behavioral Recommendations Following Bariatric Surgery

Bariatric surgery has been increasingly utilized for treatment of severe obesity. Although initial weight loss following surgery is almost completely assured, little is known about long-term out-come and patient compliance with post-surgical behavioral recommendations for diet and exercise that would improve outcome. The purpose of this study was to examine the rate of noncompliance with behavioral recommendations and to identify the incidence of psychological concerns following bariatric surgery. Subjects were identified from an active clinical data-base of prospective clinical follow-up of all bariatric surgery patients. 100 consecutive patients who underwent Roux-en-Y gastric bypass were identified, and a chart review was conducted at 6 and 12 months postoperatively to gather demographic data and identify the prevalence of noncompliance identified in monthly follow-up visits. Also, patients were asked about depression, relationship/sexual concerns, and medical complications. 81 women and 19 men were followed for 1 year. The majority of patients reported noncompliance in at least one area, with lack of exercise and snacking being most frequently cited (41%, 37% respectively overall). Most patients were compliant with eating protein first and avoiding sodas. At 12 months follow-up, 12% reported depression, 4% reported sexual concerns and 2% reported relationship problems. Also, 9% reported having experienced some medical complication related to their surgery. Noncompliance with behavioral recommendations is pervasive following bariatric surgery, with lack of exercise being the most likely area of noncompliance. Because of the importance of compliance with behavioral recommendations for the successful outcome of bariatric surgery, further research is warranted to further clarify the factors that impact long-term outcome and to design interventions to improve compliance.

Release of Active Fault Database in Japan

Release of Active Fault Database in Japan

MODULAR FINITE STATE MACHINES IMPLEMENTED AS EVENT-CONDITION-ACTION SYSTEMS

This paper presents a method to design a logic controller as an Event-Condition-Action (ECA) system, where the Modular Finite State Machine (MFSM) framework has been used to build the model for the controller. The resulting model, called an ECA MFSM, is in essence a MFSM model with a special structure that enables the processing of logic to follow the ECA paradigm. The ECA rule based method has a solid theoretical root and has been the paradigm followed to design active database systems.

Designing Triggers with Trigger-By-Example

One of the obstacles that hinder database trigger systems from their wide deployment is the lack of tools that aid users in creating trigger rules. Similar to understanding and specifying database queries in SQL3, it is difficult to visualize the meaning of trigger rules. Furthermore, it is even more difficult to write trigger rules using such text-based trigger rule languages as SQL3. In this paper, we propose TBE (Trigger-By-Example) to remedy such problems in writing trigger rules visually by using QBE (Query-By-Example) ideas. TBE is a visual trigger rule composition system that helps the users understand and specify active database triggers. TBE retains benefits of QBE while extending features to support triggers. Hence, TBE is a useful tool for novice users to create simple triggers in a visual and intuitive manner. Further, since TBE is designed to hide the details of underlying trigger systems from users, it can be used as a universal trigger interface.

Business rules systems modelling with UML and rules enforcing in active relational databases

Business rules, control system of business rules, modelling of business rules by using UML diagrams and possibility to apply these systems of rules in the RDBVS are analysed in the article. Analysis showed that systems of rules could be modelled by UML and active rules of DBVS could be generated using model of rules. Possibility to describe priorities for rules, to determine conflicts between rules and recursions using UML diagrams was researched.