An Energy-conscious Transport Protocol for Multi-hop Wireless Networks

We present a transport protocol whose goal is to reduce power consumption without compromising delivery requirements of applications. To meet its goal of energy efficiency, our transport protocol (1) contains mechanisms to balance end-to-end vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgements and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within a recently developed ultra low-power multi-hop wireless network system, extensive simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network.Defense Advanced Research Projects Agency (NBCHC050053

A Two-step Statistical Approach for Inferring Network Traffic Demands (Revises Technical Report BUCS-2003-003)

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study a two-step approach for inferring network traffic demands. First we elaborate and evaluate a modeling approach for generating good starting points to be fed to iterative statistical inference techniques. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we evaluate and compare alternative mechanisms for generating starting points and the convergence characteristics of our EM algorithm against a recently proposed Weighted Least Squares approach.National Science Foundation (ANI-0095988, EIA-0202067, ITR ANI-0205294

Kaposi's sarcoma-associated herpesvirus oncoprotein K13 protects against B cell receptor induced growth arrest and apoptosis through NF-κB activation

Kaposi's sarcoma-associated herpesvirus (KSHV) has been linked to the development of Kaposi's sarcoma, primary effusion lymphoma and multicentric Castleman's disease (MCD). We have characterized the role of KSHV-encoded viral FLICE inhibitory protein K13 in the modulation of anti-IgM induced growth arrest and apoptosis in B cells. We demonstrate that K13 protects WEHI 231, an immature B cell line, against anti-IgM induced growth arrest and apoptosis. The protective effect of K13 was associated with the activation of the NF-κB pathway and was deficient in its mutant, K13-58AAA, and a structural homolog, vFLIP E8, which lack NF-κB activity. K13 upregulated the expression of NF-κB subunit RelB and blocked the anti-IgM induced decline in c-Myc and rise in p27(Kip1) that have been associated with growth arrest and apoptosis. K13 also upregulated the expression of Mcl-1, an anti-apoptotic member of the Bcl2 family. Finally, K13 protected the mature B cell line Ramos against anti-IgM induced apoptosis through NF-κB activation. Inhibition of anti-IgM induced apoptosis by K13 may contribute to the development of KSHV-associated lymphoproliferative disorders

What do resident physicians know about nutrition? A survey at a university hospital

info:eu-repo/semantics/publishedVersio

Reinforcement learning for energy-efficient control of multi-stage production lines with parallel machine workstations

An effective approach to enhancing the sustainability of production systems is to use energy-efficient control (EEC) policies for optimal balancing of production rate and energy demand. Reinforcement learning (RL) algorithms can be employed to successfully control production systems, even when there is a lack of prior knowledge about system parameters. Furthermore, recent research demonstrated that RL can be also applied for the optimal EEC of a single manufacturing workstation with parallel machines. The purpose of this study is to apply an RL for EEC approach to more workstations belonging to the same industrial production system from the automotive sector, without relying on full knowledge of system dynamics. This work aims to show how the RL for EEC of more workstations affects the overall production system in terms of throughput and energy consumption. Numerical results demonstrate the benefits of the proposed model

Mathematical Models for Minimizing Total Tardiness on Parallel Additive Manufacturing Machines

In this research we tackle the scheduling problem in additive manufacturing for unrelated parallel machines. Both the nesting and scheduling aspects are considered. Parts have several alternative build orientations. The goal is to minimize the total tardiness of parts. We propose a mixed-integer linear programming model which considers the nesting subproblem as a 2D bin-packing problem, as well as a model which simplifies the nesting subproblem to a 1D bin-packing problem. The computational efficiency and properties of the proposed models are investigated by numerical experiments. Results show that the total tardiness optimization significantly increases the complexity of the problem, only the simple instances are solved optimally, whereas the makespan variant is able to solve all testing instances. Using the 1D bin-packing simplification allows for solving more instances to optimality, but with a risk of obtaining nesting-infeasibility. We also observed the compromise between the total tardiness and makespan objectives, which originates from the dilemma of “packing more parts to benefit from the common machine setup/recoating time” or “packing less parts to maintain the flexibility for handling distributed duedates”

Analysis of clusterin expression changes as a biomarker of osteoarthritis

Purpose: The discovery and validation of arthritis-related biomarkers and establishment of methodology for proteomic studies in osteoarthritis (OA) are needed. Proteomics strategies have identified many proteins that may relate to pathological mechanisms of OA, however targeted approaches are required to validate the roles of these proteins. This study aimed to use mass spectrometry and western blotting to identify peptides from several proteins in the secretome of chondrocytes, cartilage explants and osteochondral biopsies treated with inflammatory cytokines over a 2-week period, to evaluate their potential as biomarkers of OA progression. Methods: Healthy cartilage was obtained from fetlock joints of skeletally mature horses, euthanized for unrelated veterinary reasons. Cartilage explants were isolated using a 6 mm biopsy, with discs placed into wells (3 discs per 1 ml DMEM + 1% Pen/Strep) before incubation for 24 hours (37 °C, 5% CO2). After this equilibration period, the media was removed and replaced with either fresh DMEM + 1% Pen/Strep or DMEM supplemented with 1% Pen/Strep containing TNFα and IL-1β both at 10ng/ml. Explants were culture for 7–14 days with the cytokines replaced every 4th day. For cell based assays chondrocytes were isolated from tissue using 70U pronase for 1hr at 37 °C and overnight digestion at 37°C using a 0.2% collagenase II solution. The cell suspension was filtered and washed before being seeded into culture flasks and cultured until confluence was reached (37°C, 5% CO2). Once cultures were established cells were split into two groups: healthy control (DMEM supplemented with 1% Pen/Strep and 10% foetal calf serum) or stimulated cells (DMEM as above plus TNFα and IL-1β both at 10ng/ml). Chondroyctes were cytokine-stimulated for up to one week. Cells were used in experiments up to the 2nd passage. Results: Mass spectrometry data showed that peptides representative of clusterin were found to decrease following 7 days of inflammatory stimulation. Western blotting of secreted proteins in media of cartilage explants or chondrocyte showed that clusterin expression was reduced following 7 days of cytokine treatment. Catabolic matrix metalloproteinase enzymes MMP1, MMP3 and MMP13, as well the matrix component cartilage oligomeric protein (COMP) were all found to have an increased abundance in the media of the cytokine treated samples. This data was supported by qPCR for clusterin gene expression which showed initially mRNA levels increased 3 day after inflammatory stimulation but expression was lost after 7 days. Western blotting of media from the osteochondral biopsies showed an increase in clusterin expression after 7 days of inflammatory stimulation however clusterin protein expression could not be detected after 14 days of treatment, indicating a delayed response compared to cartilage tissue alone. Conclusions: The equine chondrocytes, cartilage explant and osteochondral biopsy models exhibited highest clusterin secretion in untreated cultures. IL-1β and TNFα treatment caused a reduction in clusterin secretion. Clusterin acts as a chaperone to aid protein refolding in situations of stress and is constitutively secreted by mammalian cells. IL-1β and TNFα appear to interrupt clusterin secretion and therefore the protection it may offer healthy functioning cells. Previous studies have reported variable data, with some studies indicating a decrease in clusterin in OA, while others indicate an increase in clusterin expression. Our results suggest the clusterin increases immediately after inflammatory stimulation but is lost after prolonged exposure. Therefore, levels of secreted clusterin may be a candidate biomarker for OA progression

Extraction of bioactive compounds from a juçara byproduct.

31st EFFoST. 13 a 16 novembro. Sitges, Spain