Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

Reconfigurable SiC Embedded Photonic Structures with Self Optical Bias Control

Multilayered heterostructures based on embedded a-Si:H and a-SiC:H p-i-n filters are analyzed from differential voltage design perspective using short- and long-pass filters. The transfer functions characteristics are presented. A numerical simulation is presented to explain the filtering properties of the photonic devices. Several monochromatic pulsed lights, separately (input channels) or in a polychromatic mixture (multiplexed signal) at different bit rates, illuminated the device. Steady-state optical bias is superimposed from the front and the back side. Results show that depending on the wavelength of the external background and impinging side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. Particular attention is given to the amplification coefficient weights, which allow to take into account the wavelength background effects when a band or frequency needs to be filtered or the gate switch, in which optical active filter gates are used to select and filter input signals to specific output ports in wavelength division multiplexing (WDM) communication systems. This nonlinearity provides the possibility for selective removal or addition of wavelengths. A truth table of an encoder that performs 8-to-1 MUX function exemplifies the optoelectronic conversion.

Differential expression of the eukaryotic release factor 3 (eRF3/GSPT1) according to gastric cancer histological types

Background: There are now several lines of evidence to suggest that protein synthesis and translation factors are involved in the regulation of cell proliferation and cancer development. Aims: To investigate gene expression patterns of eukaryotic releasing factor 3 (eRF3) in gastric cancer. Methods: RNA was prepared from 25 gastric tumour biopsies and adjacent non-neoplastic mucosa. Real time TaqMan reverse transcription polymerase chain reaction (RT-PCR) was performed to measure the relative gene expression levels. DNA was isolated from tumour and normal tissues and gene dosage was determined by a quantitative real time PCR using SYBR Green dye. Results: Different histological types of gastric tumours were analysed and nine of the 25 tumours revealed eRF3/GSPT1 overexpression; moreover, eight of the 12 intestinal type carcinomas analysed overexpressed the gene, whereas eRF3/GSPT1 was overexpressed in only one of the 10 diffuse type carcinomas (Kruskal-Wallis Test; p , 0.05). No correlation was found between ploidy and transcript expression levels of eRF3/GSPT1. Overexpression of eRF3/GSPT1 was not associated with increased translation rates because the upregulation of eRF3/GSPT1 did not correlate with increased eRF1 levels. Conclusions: Overexpression of eRF3/GSPT1 in intestinal type gastric tumours may lead to an increase in the translation efficiency of specific oncogenic transcripts. Alternatively, eRF3/GSPT1 may be involved in tumorigenesis as a result of its non-translational roles, namely (dis)regulating the cell cycle, apoptosis, or transcription.

Differential expression of CDC25 phosphatases splice variants in human breast cancer cells

Background: CDC25 phosphatases control cell cycle progression by activating cyclin dependent kinases. The three CDC25 isoforms encoding genes are submitted to alternative splicing events which generate at least two variants for CDC25A and five for both CDC25B and CDC25C. An over-expression of CDC25 was reported in several types of cancer, including breast cancer, and is often associated with a poor prognosis. Nevertheless, most of the previous studies did not address the expression of CDC25 splice variants. Here, we evaluated CDC25 spliced transcripts expression in anti-cancerous drug-sensitive and resistant breast cancer cell lines in order to identify potential breast cancer biomarkers. Methods: CDC25 splice variants mRNA levels were evaluated by semi-quantitative RT-PCR and by an original real-time RT-PCR assay. Results: CDC25 spliced transcripts are differentially expres-sed in the breast cancer cell lines studied. An up-regulation of CDC25A2 variant and an increase of the CDC25C5/C1 ratio are associated to the multidrug-resistance in VCREMS and DOXOR breast cancer cells, compared to their sensitive counterpart cell line MCF-7. Additionally, CDC25B2 tran-script is exclusively over-expressed in VCREMS resistant cells and could therefore be involved in the development of certain type of drug resistance. Conclusions: CDC25 splice variants could represent interesting potential breast cancer prognostic biomarkers.

Differential expression of GSPT1 GGCn alleles in cancer

The human eukaryotic release factor 3a (eRF3a), encoded by the G1 to S phase transition 1 gene (GSPT1; alias eRF3a), is upregulated in various human cancers. GSPT1 contains a GGCn polymorphism in exon 1, encoding a polyglycine expansion in the N-terminal of the protein. The longer allele, GGC12, was previously shown to be associated to cancer. The GGC12 allele was present in 2.2% of colorectal cancer patients but was absent in Crohn disease patients and in the control group. Real-time quantitative RT-PCR analysis showed that the GGC12 allele was present at up to 10-fold higher transcription levels than the GGC10 allele (P < 0.001). No GSPT1 amplifications were detected, and there was no correlation between the length of the alleles and methylation levels of the CpG sites inside the GGC expansion. Using flow cytometry, we compared the levels of apoptosis and proliferation rates between cell lines with different genotypes, but detected no significant differences. Finally, we used a cytokinesis-block micronucleus assay to evaluate the frequency of micronuclei in the same cell lines. Cell lines with the longer alleles had higher frequencies of micronuclei in binucleated cells, which is probably a result of defects in mitotic spindle formation. Altogether, these findings indicate that GSPT1 should be considered a potential proto-oncogene.

Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Comparing the schedulers and power saving strategies with SPARTS

We have developed SPARTS, a simulator of a generic embedded real-time device. It is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the wide variety of applications. SPARTS was developed to help the community investigate the behaviour of the real-time embedded systems and to quantify the associated constraints/overheads.

Energy efficient scheduling for cluster-tree wireless sensor networks with time-bounded data flows: application to IEEE 802.15.4/ZigBee

Cluster scheduling and collision avoidance are crucial issues in large-scale cluster-tree Wireless Sensor Networks (WSNs). The paper presents a methodology that provides a Time Division Cluster Scheduling (TDCS) mechanism based on the cyclic extension of RCPS/TC (Resource Constrained Project Scheduling with Temporal Constraints) problem for a cluster-tree WSN, assuming bounded communication errors. The objective is to meet all end-to-end deadlines of a predefined set of time-bounded data flows while minimizing the energy consumption of the nodes by setting the TDCS period as long as possible. Sinceeach cluster is active only once during the period, the end-to-end delay of a given flow may span over several periods when there are the flows with opposite direction. The scheduling tool enables system designers to efficiently configure all required parameters of the IEEE 802.15.4/ZigBee beaconenabled cluster-tree WSNs in the network design time. The performance evaluation of thescheduling tool shows that the problems with dozens of nodes can be solved while using optimal solvers.

Handling shared resources and precedence constraints in open systems

There is an increasing demand for highly dynamic realtime systems where several independently developed applications with different timing requirements can coexist. This paper proposes a protocol to integrate shared resources and precedence constraints among tasks in such systems assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a capacity sharing and stealing mechanism to efficiently exchange bandwidth among needed tasks, minimising the cost of blocking.

HIV/AIDS knowledge among men who have sex with men: applying the item response theory

OBJECTIVE To evaluate the level of HIV/AIDS knowledge among men who have sex with men in Brazil using the latent trait model estimated by Item Response Theory. METHODS Multicenter, cross-sectional study, carried out in ten Brazilian cities between 2008 and 2009. Adult men who have sex with men were recruited (n = 3,746) through Respondent Driven Sampling. HIV/AIDS knowledge was ascertained through ten statements by face-to-face interview and latent scores were obtained through two-parameter logistic modeling (difficulty and discrimination) using Item Response Theory. Differential item functioning was used to examine each item characteristic curve by age and schooling. RESULTS Overall, the HIV/AIDS knowledge scores using Item Response Theory did not exceed 6.0 (scale 0-10), with mean and median values of 5.0 (SD = 0.9) and 5.3, respectively, with 40.7% of the sample with knowledge levels below the average. Some beliefs still exist in this population regarding the transmission of the virus by insect bites, by using public restrooms, and by sharing utensils during meals. With regard to the difficulty and discrimination parameters, eight items were located below the mean of the scale and were considered very easy, and four items presented very low discrimination parameter (< 0.34). The absence of difficult items contributed to the inaccuracy of the measurement of knowledge among those with median level and above. CONCLUSIONS Item Response Theory analysis, which focuses on the individual properties of each item, allows measures to be obtained that do not vary or depend on the questionnaire, which provides better ascertainment and accuracy of knowledge scores. Valid and reliable scales are essential for monitoring HIV/AIDS knowledge among the men who have sex with men population over time and in different geographic regions, and this psychometric model brings this advantage.

Direct search optimization application programming interface with remote access

Search Optimization methods are needed to solve optimization problems where the objective function and/or constraints functions might be non differentiable, non convex or might not be possible to determine its analytical expressions either due to its complexity or its cost (monetary, computational, time,...). Many optimization problems in engineering and other fields have these characteristics, because functions values can result from experimental or simulation processes, can be modelled by functions with complex expressions or by noise functions and it is impossible or very difficult to calculate their derivatives. Direct Search Optimization methods only use function values and do not need any derivatives or approximations of them. In this work we present a Java API that including several methods and algorithms, that do not use derivatives, to solve constrained and unconstrained optimization problems. Traditional API access, by installing it on the developer and/or user computer, and remote API access to it, using Web Services, are also presented. Remote access to the API has the advantage of always allow the access to the latest version of the API. For users that simply want to have a tool to solve Nonlinear Optimization Problems and do not want to integrate these methods in applications, also two applications were developed. One is a standalone Java application and the other a Web-based application, both using the developed API.

Enabling Global Experiments With Interactive Reconfiguration And Steering By Multiple Users

In global scientific experiments with collaborative scenarios involving multinational teams there are big challenges related to data access, namely data movements are precluded to other regions or Clouds due to the constraints on latency costs, data privacy and data ownership. Furthermore, each site is processing local data sets using specialized algorithms and producing intermediate results that are helpful as inputs to applications running on remote sites. This paper shows how to model such collaborative scenarios as a scientific workflow implemented with AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic), a decentralized framework offering a feasible solution to run the workflow activities on distributed data centers in different regions without the need of large data movements. The AWARD workflow activities are independently monitored and dynamically reconfigured and steering by different users, namely by hot-swapping the algorithms to enhance the computation results or by changing the workflow structure to support feedback dependencies where an activity receives feedback output from a successor activity. A real implementation of one practical scenario and its execution on multiple data centers of the Amazon Cloud is presented including experimental results with steering by multiple users.

Optimization of magneto-electro-elastic composite structures using differential evolution

Magneto-electro-elastic structures are built from materials that provide them the ability to convert in an interchangeable way, magnetic, electric and mechanical forms of energy. This characteristic can therefore provide an adaptive behaviour to a general configuration elastic structure, being commonly used in association with any type of composite material in an embedded or surface mounted mode, or by considering the usage of multiphase materials that enable achieving different magneto-electro-elastic properties. In a first stage of this work, a few cases studies will be considered to enable the validation of the model considered and the influence of the coupling characteristics of this type of adaptive structures. After that we consider the application of a recent computational intelligence technique, the differential evolution, in a deflection profile minimization problem. Studies on the influence of optimization parameters associated to the problem considered will be performed as well as the adoption of an adaptive scheme for the perturbation factor. Results are also compared with those obtained using an enhanced particle swarm optimization technique. (C) 2013 Elsevier Ltd. All rights reserved.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.