A Schedulability Analysis Framework for Real-time Infrastructure Systems Managing Heterogeneous Resources

REACTION 2012. 1st International workshop on Real-time and distributed computing in emerging applications. December 4th, 2012, San Juan, Puerto Rico.Electricity generating systems, such as smart grid systems, and water management systems are infrastructure systems that manage resources critical to human life. In the systems, resources are produced and managed to supply them to various consumers, such as building, car, factory, and household, according to their needs and priorities. Reliable supply of resources depends not only on sufficient production of resources but also on reliable sharing of resource supply facilities. This paper presents a schedulability analysis framework. A prominent characteristic of the framework is that it considers at once the two types of resources, i.e. consumable resources, such as electricity, energy, and water, and sharable resources, such as pipelines, storages, and processors, are considered. To apply a formal approach to schedulability analysis of infrastructure system, this paper classifies the types of resources and real-time jobs for infrastructure systems. Then based on the classification , it presents an architectural model and a schedulability analysis framework.This research was supported by the KAIST High Risk High Return Project (HRHRP)

A Formal Modeling and Analysis Framework for Software Product Line of Preemptive Real-Time Systems

International audienceThis paper presents a formal analysis framework to analyze a family of platform products w.r.t. real-time properties. First, we propose an extension of the widely-used feature model, called Property Feature Model (PFM), that distinguishes features and properties explicitly Second, we present formal behavioral models of components of a real-time scheduling unit such that all real-time scheduling units implied by a PFM are automatically composed to be analyzed against the properties given by the PFM. We apply our approach to the verification of the schedulability of a family of scheduling units using the symbolic and statistical model checkers of Uppaal

Resting State Brain Network Function in Elderly: The Formation of Social Ties

Background: The purpose of this study is to determine the relevance of the relationship between brain network and the social ties management.Methods: Participants are based on 52 Korean seniors aged 65 and older who live in Ganghwa-gun, Incheon. We used a closed-triad index (CTI), which is the most basic unit of analysis in the study of group phenomena. This index is a social networking variable that has been shown to have a different implication depending on the subject’s condition and role. After two questionnaire surveys were conducted at three years intervals, participants were classified into an increased group and a decreased group according to the change of CTI. Resting-state fMRI analysis were followed to investigate the difference of brain networks between groups. Results: According to the analysis of the study, the whole participants who had increased in number of CTI has higher local efficiency than the group of the participants who had no effect or decreased in CTI. Conclusions: Our study suggests that social relationship, which is substantially related to brain network, is a major factor in successful aging. Lastly, since there is a restriction that the study cannot explain the causal aspect of the brain network and the triad-relationship, there is a need for further investigation

Load-Adaptive Practical Multi-Channel Communications in Wireless Sensor Networks

In recent years, a significant number of sensor node prototypes have been designed that provide communications in multiple channels. This multi-channel feature can be effectively exploited to increase the overall capacity and performance of wireless sensor networks (WSNs). In this paper, we present a multi-channel communications system for WSNs that is referred to as load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink since it has a more comprehensive view of the network behavior, and dynamically adds or removes channels based on the estimated load. LPMC updates the routing path to balance the loads of the channels. The nodes in a path use the same channel; therefore, they do not need to switch channels to receive or forward packets. LPMC has been evaluated through extensive simulations, and the results demonstrate that it can effectively increase the delivery ratio, network throughput, and channel utilization, and that it can decrease the end-to-end delay and energy consumption

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

Increased Transforming Growth Factor-beta1 in Alcohol Dependence

Ethanol and its metabolite acetaldehyde increase transforming growth factor beta1 (TGF-β1) expression in animal studies. TGF-β1 is related with the hepatic stellate cell (the key element of hepatic fibrogenesis) and the radial glia (the key element of neuronal migration). Blood samples were collected from 41 patients with alcohol dependence, TGF-β1 levels measured by ELISA were compared with 41 normal subjects. Plasma TGF-β1 levels in the patients with alcohol dependence (1,653.11±532.45 pg/mL) were significantly higher than those of healthy subjects (669.87±366.53 pg/mL) (P=0.000). Patients with or without liver pathology showed no difference in TGF-β1 (P=0.36). Increased TGF-β1 may mediate deleterious effect of alcohol such as hepatic fibrosis and suppressed neuronal developments in alcohol dependence patients

Stretchable and transparent electrodes based on in-plane structures

Stretchable electronics has attracted great interest with compelling potential applications that require reliable operation under mechanical deformation. Achieving stretchability in devices, however, requires a deeper understanding of nanoscale materials and mechanics beyond the success of flexible electronics. In this regard, tremendous research efforts have been dedicated toward developing stretchable electrodes, which are one of the most important building blocks for stretchable electronics. Stretchable transparent thin-film electrodes, which retain their electrical conductivity and optical transparency under mechanical deformation, are particularly important for the favourable application of stretchable devices. This minireview summarizes recent advances in stretchable transparent thin-film electrodes, especially employing strategies based on in-plane structures. Various approaches using metal nanomaterials, carbon nanomaterials, and their hybrids are described in terms of preparation processes and their optoelectronic/mechanical properties. Some challenges and perspectives for further advances in stretchable transparent electrodes are also discussed. © 2015 The Royal Society of Chemistry.open0

Polygenic risk score validation using Korean genomes of 265 early-onset acute myocardial infarction patients and 636 healthy controls

Background The polygenic risk score (PRS) developed for coronary artery disease (CAD) is known to be effective for classifying patients with CAD and predicting subsequent events. However, the PRS was developed mainly based on the analysis of Caucasian genomes and has not been validated for East Asians. We aimed to evaluate the PRS in the genomes of Korean early-onset AMI patients (n = 265, age <= 50 years) following PCI and controls (n = 636) to examine whether the PRS improves risk prediction beyond conventional risk factors. Results The odds ratio of the PRS was 1.83 (95% confidence interval [CI]: 1.69-1.99) for early-onset AMI patients compared with the controls. For the classification of patients, the area under the curve (AUC) for the combined model with the six conventional risk factors (diabetes mellitus, family history of CAD, hypertension, body mass index, hypercholesterolemia, and current smoking) and PRS was 0.92 (95% CI: 0.90-0.94) while that for the six conventional risk factors was 0.91 (95% CI: 0.85-0.93). Although the AUC for PRS alone was 0.65 (95% CI: 0.61-0.69), adding the PRS to the six conventional risk factors significantly improved the accuracy of the prediction model (P = 0.015). Patients with the upper 50% of PRS showed a higher frequency of repeat revascularization (hazard ratio = 2.19, 95% CI: 1.47-3.26) than the others. Conclusions The PRS using 265 early-onset AMI genomes showed improvement in the identification of patients in the Korean population and showed potential for genomic screening in early life to complement conventional risk prediction

Myotis rufoniger genome sequence and analyses: M-rufoniger's genomic feature and the decreasing effective population size of Myotis bats

Myotis rufoniger is a vesper bat in the genus Myotis. Here we report the whole genome sequence and analyses of the M. rufoniger. We generated 124 Gb of short-read DNA sequences with an estimated genome size of 1.88 Gb at a sequencing depth of 66x fold. The sequences were aligned to M. brandtii bat reference genome at a mapping rate of 96.50% covering 95.71% coding sequence region at 10x coverage. The divergence time of Myotis bat family is estimated to be 11.5 million years, and the divergence time between M. rufoniger and its closest species M. davidii is estimated to be 10.4 million years. We found 1,239 function-altering M. rufoniger specific amino acid sequences from 929 genes compared to other Myotis bat and mammalian genomes. The functional enrichment test of the 929 genes detected amino acid changes in melanin associated DCT, SLC45A2, TYRP1, and OCA2 genes possibly responsible for the M. rufoniger's red fur color and a general coloration in Myotis. N6AMT1 gene, associated with arsenic resistance, showed a high degree of function alteration in M. rufoniger. We further confirmed that the M. rufoniger also has batspecific sequences within FSHB, GHR, IGF1R, TP53, MDM2, SLC45A2, RGS7BP, RHO, OPN1SW, and CNGB3 genes that have already been published to be related to bat's reproduction, lifespan, flight, low vision, and echolocation. Additionally, our demographic history analysis found that the effective population size of Myotis clade has been consistently decreasing since similar to 30k years ago. M. rufoniger's effective population size was the lowest in Myotis bats, confirming its relatively low genetic diversity