Learning Model-Based Sparsity via Projected Gradient Descent

Several convex formulation methods have been proposed previously for statistical estimation with structured sparsity as the prior. These methods often require a carefully tuned regularization parameter, often a cumbersome or heuristic exercise. Furthermore, the estimate that these methods produce might not belong to the desired sparsity model, albeit accurately approximating the true parameter. Therefore, greedy-type algorithms could often be more desirable in estimating structured-sparse parameters. So far, these greedy methods have mostly focused on linear statistical models. In this paper we study the projected gradient descent with non-convex structured-sparse parameter model as the constraint set. Should the cost function have a Stable Model-Restricted Hessian the algorithm produces an approximation for the desired minimizer. As an example we elaborate on application of the main results to estimation in Generalized Linear Model

TimeTrader: Exploiting Latency Tail to Save Datacenter Energy for On-line Data-Intensive Applications

Datacenters running on-line, data-intensive applications (OLDIs) consume significant amounts of energy. However, reducing their energy is challenging due to their tight response time requirements. A key aspect of OLDIs is that each user query goes to all or many of the nodes in the cluster, so that the overall time budget is dictated by the tail of the replies' latency distribution; replies see latency variations both in the network and compute. Previous work proposes to achieve load-proportional energy by slowing down the computation at lower datacenter loads based directly on response times (i.e., at lower loads, the proposal exploits the average slack in the time budget provisioned for the peak load). In contrast, we propose TimeTrader to reduce energy by exploiting the latency slack in the sub- critical replies which arrive before the deadline (e.g., 80% of replies are 3-4x faster than the tail). This slack is present at all loads and subsumes the previous work's load-related slack. While the previous work shifts the leaves' response time distribution to consume the slack at lower loads, TimeTrader reshapes the distribution at all loads by slowing down individual sub-critical nodes without increasing missed deadlines. TimeTrader exploits slack in both the network and compute budgets. Further, TimeTrader leverages Earliest Deadline First scheduling to largely decouple critical requests from the queuing delays of sub- critical requests which can then be slowed down without hurting critical requests. A combination of real-system measurements and at-scale simulations shows that without adding to missed deadlines, TimeTrader saves 15-19% and 41-49% energy at 90% and 30% loading, respectively, in a datacenter with 512 nodes, whereas previous work saves 0% and 31-37%.Comment: 13 page

Material Induced Anisotropic Damage

The anisotropy in damage can be driven by two different phenomena; anisotropic defor-mation state named Load Induced Anisotropic Damage (LIAD) and anisotropic (shape and/or distribution) second phase particles named Material Induced Anisotropic Damage (MIAD). Most anisotropic damage models are based on LIAD. This work puts emphasis on the presence of MIAD in DP600 steel. Scanning Electron Microscopic (SEM) analysis was carried out on undeformed and deformed tensile specimens. The martensite morphology showed anisotropy in size and orientation. Consequently, significant MIAD was observed in the deformed tensile specimens. A through thickness shear failure is observed in the tensile specimen, which is pulled along the rolling direction (RD), whereas a dominant ductile fracture is observed when pulled perpendicular to RD. The Modified Lemaitre’s (ML) anisotropic damage model is improved to account for MIAD in a phenomenological manner. The MIAD parameters are determined from tensile tests carried out in 0o, 45o and 90o to the RD. The formability of DP600 is lower in the RD compared to that in 90o to the RD, due to the phenomenon of MIAD

Making regulatory mechanisms work : lessons from cases of Private Sector Participation

This paper is about the regulation of private sector participation (PSP) in public water utilities. Using case studies from Argentina, Chile and the United Kingdom, it identifies and discusses the regulatory mechanisms that have been introduced and the issues surrounding information access, price and service quality regulation. The paper also analyses what measures have been implemented in these three cases in order to achieve regulatory accountability, independence and an adequate level of financial and human resources. The method adopted was case survey including the analysis of official regulatory documents and other relevant material and validation by an expert panel. It investigates the conditions that are necessary for regulatory mechanisms to be implemented and operated effectively in each context, and draws out some general conclusions for areas of improvement

Antimicrobial Activity of Varthemia iphinoides and Majorana syriaca Essential Oils from Jordan and Their Potential Use as Natural Food Preservatives

The aim of this study was to evaluate the efficiency of Varthemia iphinoides and Majorana syriaca essential oils as natural food preservative in four different food model media (cheese, meat, milk, and tomato) against two gram-positive and two gram-negative bacteria (Bacillus cereus, Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa) and three different food spoilage fungi using agar well diffusion method. The results showed that the maximum activity of V. iphinoides essential oil was against S.aureus in tomato media with relative inhibition zone diameter (RIZD) 186 ± 9 %, the most sensitive food spoilage fungi was penicillium sp. in tomato media with RIZD 149 ± 10 %. The results showed that there was inhibitory effect of M. syriaca and V. iphinoides essential oils. against most of the tested species in different food model media which will lead to control food pathogen organisms by using essential oils as food preservative and flavoring agents. Key words: Varthemia iphinoides , Majorana syriaca, Essential oils, Antimicrobial, Food preservative

Validation of Modified Lemaitre's Anisotropic Damage Model with the Cross Die Drawing Test

Dual Phase (DP) steels are widely replacing the traditional forming steels in automotive industry. Advanced damage models are required to accurately predict the formability of DP steels. In this work, Lemaitre’s anisotropic damage model has been slightly modified for sheet metal forming applications and for strain rate dependent materials. The damage evolution law is adapted to take into account the strain rate dependency and negative triaxialities. The damage parameters for pre-production DP600 steel were determined. The modified damage models (isotropic and anisotropic) were validated using the cross die drawing test. The anisotropic damage model predicts the crack direction more accurately

MicroRNA-203 predicts human survival after resection of colorectal liver metastasis.

BackgroundResection of colorectal liver metastasis (CRLM) can be curative. Predicting which patients may benefit from resection, however, remains challenging. Some microRNAs (miRNAs) become deregulated in cancers and contribute to cancer progression. We hypothesized that miRNA expression can serve as a prognostic marker of survival after CRLM resection.ResultsMiR-203 was significantly overexpressed in tumors of short-term survivors compared to long-term survivors. R1/R2 margin status and high clinical risk score (CRS) were also significantly associated with short-term survival (both p = 0.001). After adjusting for these variables, higher miR-203 expression remained an independent predictor of shorter survival (p = 0.010). In the serum cohort, high CRS and KRAS mutation were significantly associated with short-term survival (p = 0.005 and p = 0.026, respectively). After adjusting for CRS and KRAS status, short-term survivors were found to have significantly higher miR-203 levels (p = 0.016 and p = 0.033, respectively).Materials and methodsWe employed next-generation sequencing of small-RNAs to profile miRNAs in solid tumors obtained from 38 patients who underwent hepatectomy for CRLM. To validate, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed on 91 tumor samples and 46 preoperative serum samples.ConclusionsAfter CRLM resection, short-term survivors exhibited significantly higher miR-203 levels relative to long-term survivors. MiR-203 may serve as a prognostic biomarker and its prognostic capacity warrants further investigation