Multi-component Application Research Articles

Efficient Algorithms for Multi-Component Application Placement in Mobile Edge Computing

In this article, we address the Multi-Component Application Placement Problem ( <inline-formula><tex-math notation="LaTeX">${\sf MCAPP}$</tex-math></inline-formula> ) in Mobile Edge Computing (MEC) systems. We formulate this problem as a Mixed Integer Non-Linear Program (MINLP) with the objective of minimizing the total cost of running the applications. In our formulation, we take into account two important and challenging characteristics of MEC systems, the mobility of users and the network capabilities. We analyze the complexity of <inline-formula><tex-math notation="LaTeX">${\sf MCAPP}$</tex-math></inline-formula> and prove that it is <inline-formula><tex-math notation="LaTeX">$NP$</tex-math></inline-formula> -hard, that is, finding the optimal solution in reasonable amount of time is infeasible. We design two algorithms, one based on matching and local search and one based on a greedy approach, and evaluate their performance by conducting an extensive experimental analysis driven by two types of user mobility models, real-life mobility traces and random-walk. The results show that the proposed algorithms obtain near-optimal solutions and require small execution times for reasonably large problem instances.

Inspection and evaluation of a network of concrete bridges based on multiple NDT techniques

Bridge condition rating is a crucial variable used for prioritisation of bridge needs in bridge management systems (BMSs). At present, bridge rating is predominantly based on visual inspections. A practical method incorporating non-destructive testing (NDT) results for rating bridges in a BMS is not available. In this study, an integrated rating method for reinforced concrete bridges based on both visual inspection and multiple NDT techniques with the ultimate goal of incorporating it into BMSs was developed. The method uses a multi-component and multi-modal NDT application at network-level with improved testing speed. The application results of four non-destructive techniques including visual inspection, polarisation resistance, penetration resistance, and pulse velocity on a reinforced concrete bridge network of 100 bridges are presented. At bridge level, a multi-component approach was used, including decks, girders, cap beams, piers, and abutments. A novel method for NDT-based reinforcement corrosion rating was developed. Correlation among NDT variables was also investigated and the results are presented. Multiple linear regression models were developed using ANOVA analyses. Only the statistically significant regressors with the largest partial F-statistic were included in the model formulas. The expected weights of the four evaluation criteria in the formula were obtained by combining the results of two techniques: statistical data available in literature on the frequency of use of NDT techniques for bridge inspection, and a three-level analytical hierarchy process (AHP) based on expert survey. Application of three NDT techniques to inspections of concrete bridges, determination of NDT ratings using the integrated rating formula, and incorporation of the resulting ratings into a BMS for bridge ranking can be performed using the proposed methodology.

Prediction of the mechanisms of Xiaoai Jiedu Recipe in the treatment of breast cancer: A comprehensive approach study with experimental validation

Ethnopharmacological relevanceTraditional Chinese medicine (TCM) holds a great promise for preventing complex chronic diseases through a holistic way. Certain Chinese medicine formulae from TCM are effective for treating and preventing cancer in clinical practice. Xiaoai Jiedu Recipe (XJR) is a Chinese medicine formula that has been used to treat breast cancer (BC). However, its active ingredients and therapeutic mechanisms on tumor are unclear. Therefore, further investigation is necessary. Aim of the studyThis study aims to elucidate the active compounds of XJR and its molecular mechanisms for the treatment of BC. Materials and methodsA comprehensive approach was used to clarify the pharmacodynamic basis of XJR and its pharmacological mechanism, including the acquisition of differentially expressed genes of BC, screening of active ingredients and their targets, construction of complex internetwork between drugs and diseases, and analysis of the key subnetwork. Finally, these results were validated by in vitro experiments and comparison with literature reviews. ResultsBy using bioinformatics, 5211 differentially expressed genes of BC were identified, more than half of them had been reported in previous studies. By using network analysis, 113 potential bioactive compounds in the ten component herbs of XJR and 157 BC-related targets were identified, which were significantly enriched in 85 pathways and 1321 GO terms. The in vitro studies showed that quercetin and ursolic acid, the active components of XJR, could effectively inhibit the proliferation of breast cancer cells, and the combination of the two components could significantly decrease the mitochondrial membrane potential and suppress the activation of PI3K-Akt signaling pathway, thus inducing apoptosis of cancer cells. ConclusionsXJR played an important role in anti-BC through multi-component, multi-target and multi-pathway mechanisms, in which quercetin and ursolic acid may be the key active components. The anticancer effect of multi-component application was better than that of a single component. This study not only deepened our understanding of the role of TCM in the prevention and treatment of diseases, but also provided a reference for the in-depth research, development and application of the ancient medicine.

Estimating costs of multi-component enterprise applications

AbstractEstimating the cost of a multi-component application (e.g., its resource or energy consumption) is fundamental in nowadays enterprise IT, especially if we consider that current pricing models are mainly pay per-use. While this is still manageable on small applications, it is really hard to manually estimate the cost of large-scale enterprise applications involving hundreds of interdependent application components. In this article, we formalise the problem of estimating costs of multi-component applications, by representing the structure of an application as a typed directed graph, and by allowing to associate different types of costs with different application components. We show that costs can be fully customised, and that associating different costs with the same application leads to different cost estimation problems defined on that application.We then present an approach for solving cost estimation problems on multi-component applications, which is based on terminating and confluent graph transformations. We also present a prototype implemenation of our approach, which we use to run a case study based on a third-party application.

Extending access to a web-based mental health intervention: who wants more, what happens to use over time, and is it helpful? Results of a concealed, randomized controlled extension study

BackgroundWeb-based mental health applications may be beneficial, but adoption is often low leaving optimal implementation and payment models unclear. This study examined which users were interested in extended access to a web-based application beyond an initial 3-month trial period and evaluated if an additional 3 months of access was beneficial.MethodsThis study was a concealed extension of a multi-center, pragmatic randomized controlled trial that assessed the benefit of 3 months of access to the Big White Wall (BWW), an anonymous web-based moderated, multi-component mental health application offering self-directed activities and peer support. Trial participants were 16 years of age or older, recruited from hospital-affiliated mental health programs. Participants who received access to the intervention in the main trial and completed 3-month outcome assessments were offered participation. We compared those who were and were not interested in an extension of the intervention, and re-randomized consenting participants 1:1 to receive extended access or not over the subsequent 3 months. Use of the intervention was monitored in the extension group and outcomes were measured at 3 months after re-randomization in both groups. The primary outcome was mental health recovery as assessed by total score on the Recovery Assessment Scale (RAS-r), as in the main trial. Linear mixed models were used to examine the time by group interaction to assess for differences in responses over the 3-month extension study.ResultsOf 233 main trial participants who responded, 119 (51.1%) indicated an interest in receiving extended BWW access. Those who were interested had significantly higher baseline anxiety symptoms compared to those who were not interested. Of the 119, 112 were re-randomized (55 to extended access, 57 to discontinuation). Only 21 of the 55 extended access participants (38.2%) used the intervention during the extension period. Change in RAS-r scores over time was not significantly different between groups (time by group, F(1,77) = 1.02; P = .31).ConclusionsOnly half of eligible participants were interested in extended access to the intervention with decreasing use over time, and no evidence of added benefit. These findings have implications for implementation and payment models for this type of web-based mental health intervention.Trial registrationClinicaltrials.govNCT02896894. Registered retrospectively on September 12, 2016.

Development of a multicomponent psychological mobile application (app) for patients with acute myeloid leukemia (AML).

166 Background: Patients newly diagnosed with AML experience substantial psychological distress as they confront a life-threatening diagnosis requiring an urgent 4-6 week hospitalization to initiate chemotherapy. Interventions to address psychological distress in this population are lacking. Methods: We used a five-step app development process to create a psychological intervention app targeting patients’ needs during the initial hospitalization following a new diagnosis of AML. Patients, caregivers, oncologists, psychologists, and nurses served as stakeholders and were involved in 1) developing a conceptual framework for the intervention; 2) creating an intervention manual that incorporates medical information, psychoeducation, and psychosocial skill-building corresponding to the illness trajectory; 3) translating the intervention manual into a storyline with gamification to enhance patient engagement; 4) creating initial wireframes of the app modules; and 5) refining the app through iterative testing. Results: The app consists of five 20-minute modules which the patient will complete weekly over a 5-week period. The modules consist of 1) supportive psychotherapy to address the initial shock of diagnosis; 2) psychoeducation to manage expectations and mobilize social supports; 3) psychosocial skill-building to promote effective coping; 4) self-care to promote positive health behaviors; and 4) a summary module to reinforce learning points from prior modules. Two bonus modules are available for patients who wish to engage in additional cognitive-based restructuring strategies. We utilized gamification strategies to enhance patient engagement including a) creating an app storyline focused on the patient’s journey during hospitalization; 2) creating a guide character doctor that accompanies the patient through their journey; 3) incorporating videos of AML survivors; and 4) developing a point reward system for completing the modules. Conclusions: We developed a novel psychological intervention app for patients with AML using an iterative development process. Future studies should assess the efficacy of the app in improving outcomes for patients with AML.

Fault-aware management protocols for multi-component applications

Nowadays, applications are composed by multiple heterogeneous components, whose management must be suitably coordinated by taking into account inter-component dependencies and potential failures. In this paper, we first present fault-aware management protocols, which allow to model the management behaviour of application components, and we then illustrate how such protocols can be composed to analyse and automate the overall management of a multi-component application. We also show how to recover applications that got stuck because a fault was not handled properly, or because a component is behaving differently than expected. To illustrate the feasibility of our approach, we present Barrel, a proof-of-concept application that permits editing and analysing fault-aware management protocols in multi-component applications. We also discuss the usefulness of Barrel by showing how it was fruitfully exploited it in a concrete case study and in a controlled experiment.

Adaptive Executions of Multi-Physics Coupled Applications on Batch Grids

Long running multi-physics coupled parallel applications have gained prominence in recent years. The high computational requirements and long durations of simulations of these applications necessitate the use of multiple systems of a Grid for execution. In this paper, we have built an adaptive middleware framework for execution of long running multi-physics coupled applications across multiple batch systems of a Grid. Our framework, apart from coordinating the executions of the component jobs of an application on different batch systems, also automatically resubmits the jobs multiple times to the batch queues to continue and sustain long running executions. As the set of active batch systems available for execution changes, our framework performs migration and rescheduling of components using a robust rescheduling decision algorithm. We have used our framework for improving the application throughput of a foremost long running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our real multi-site experiments with CCSM indicate that Grid executions can lead to improved application throughput for climate models.

ChemInform Abstract: Hydrazinophosphonates and Hydrazinobisphosphonates: Novel Mitsunobu and Arbuzov‐Type Multicomponent Application of the Morrison—Brunn—Huisgen Betaine.

AbstractThe reaction of the zwitterion, generated from DIAD and trialkylphosphite, with aroyl, phosphoryl, and sulfonyl chlorides produces the expected fully substituted hydrazines in good to excellent yields.

Grids with multiple batch systems for performance enhancement of multi-component and parameter sweep parallel applications

In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies (FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

Combining digital elevation data (SRTM/ASTER), high resolution satellite imagery (Quickbird) and GIS for geomorphological mapping: A multi-component case study on Mediterranean karst in Central Crete

Remote sensing data have become more and more popular for geomorphological investigations because their steadily increasing level of detail and accessibility opens up new potentials. In this context, this paper examines the application and quality of digital elevation models (SRTM and ASTER DEMs), high resolution satellite imagery (Quickbird) and GIS techniques for the detection and mapping of karst landforms (mainly enclosed depressions) at different scales in the Ida Mountains of Central Crete. Besides discussing methodological issues and evaluating suitability potentials, we conducted an exemplary case study based on spatial analysis of the regional karst morphology. Different input datasets and processing methods are applied (GIS-based analysis, land cover classification, raster calculations, etc.) in order to carry out an area-wide surveying and mapping of karst depressions. The findings are supported and validated by auxiliary field studies. Due to the level of detail and occasional data errors, an exclusive use of satellite imagery or digital elevation models for automatic karst landform detection performs insufficiently. Our results demonstrate that mapping karst features through remote sensing is significantly dependent on scale of interest, existing environmental conditions and data quality. A semi-automatic data integration approach on the basis of digital datasets generated by combined satellite image processing and DEM analysis yields the best results, especially when indirect karst-indicating variables like iron oxide-rich sediments are included as detection criteria. The multi-component application presented in this paper provides a time-saving and effective tool for meso- to macro-scale object detection and extensive study areas. However, the potential of fully automated karst feature mapping still needs to be explored in future work. Concerning the spatial dimension of karstification in Central Crete, the GIS-based results allow differentiating further geomorphological characteristics, e.g. by indicating a significant altitudinal change of karst forms within the study area. Size and shape of depressions (dolines, uvalas, and poljes) vary considerably due to the geological setting, climatic impacts, neotectonics and elevation.

Dynamic Component Extension: a Strategy for Performance Improvement in Multicomponent Applications

Multicomponent application paradigms have gained prominence in many significant multidisciplinary scientific applications. In this work, we propose a software strategy called dynamic component extension for multicomponent applications to improve application performance by minimizing processor idling. In this strategy, the processor space of a component is dynamically extended to include the processors of other components during certain computationally intensive phases of the component. We demonstrate its use in improving the performance of one of the most prominent multicomponent applications, the community climate system model (CCSM). In this application, we dynamically extend the atmosphere component to minimize the idling in other components caused by large periodic temporal load imbalances in the atmosphere component. By means of experiments on different parallel platforms with different numbers of processors, we show that using our strategy can lead to about 15% reduction and savings of several days in execution times of CCSM for 1000-year simulation runs.

Visualisation as a Tool to Help Multicomponent Non-Ideal System Characterisation and Application to Complex Distillation Processes

Visualisation as a Tool to Help Multicomponent Non-Ideal System Characterisation and Application to Complex Distillation Processes

Ligature: Component Architecture for High Performance Applications

The increasing feasibility of developing applications spanning nationwide supercomputing resources makes possible the creation of simulations composed of multiple interdisciplinary components and capable of modeling natural and social phenomena of national importance with unprecedented speed and accuracy. However, the potential offered by hardware technology often fails to be fully realized due to the lack of software environments supporting such efforts. Furthermore, the complexity of combining within one application components with different performance characteristics often prevents such applications from achieving required performance levels. The Ligature project at Los Alamos National Laboratory addresses the issue of designing a software infrastructure enabling fast and efficient development of multicomponent applications and that of providing performance guidance to the programmer using this infrastructure. Ligature allows the programmer to define component interfaces specifying how heterogeneous, distributed components can interact within a larger system and provides a reusable infrastructure capable of connecting these components. These interfaces, as well as information about component performance, are accessible through a database. Within this framework, we are trying to understand how information about the performance of individual components and information about performance of the framework can be combined to develop a performance-aware multicomponent application.

Post-marketing surveillance: drug epidemiology.

A description of the need for and appropriateness of a multi-component application of epidemiological methods to the post-marketing evaluation of drugs is presented. There is a need for the development of the art and science of Drug Epidemiology. The large number of drugs introduced over the last 40 years and the number of interventions constitute an issue of public health interest. It is appropriate that scientifically sound information be collected about medications. There has been considerable discussion about the methods to be used in any such systematic approach. The choice of method is obviously dependent upon the questions to be addressed and the functions to be satisfied. The proposal is presented for the appropriate content functions of post-marketing drug evaluation, and a description of some and currently employed approaches show how they differentially satisfy the functions. It is concluded that there is a need for the development and application of multiple complementary methods to satisfy the requirements of a meaningful system for post-marketing drug evaluation.

Xps Valence State Determination of Np And Pu in Multicomponent Borosilicate Glass and Application to Leached 76–68 Waste Glass Surfaces

Current plans for high-level radioactive waste disposal call for long term emplacement of canisters of a suitably leach resistant waste form in deep underground repositories. Proposed regulations [11] call for canisters with a designed lifetime of 1000 years. After this initial period, most of the remaining activity in the waste will be associated with the actinide elements. Thus, the leach behavior of the actinides takes on special importance. In particular, the leaching mechanisms must be understood if we are to attach any confidence to long term predictive extrapolation of short term leach tests. The actinides, unlike the rare earths, are not particularly similar in chemical behavior nor is their behavior reliably modeled by that of other elements. Thus, more studies directed toward the behavior of the actinides in candidate waste forms are important.