Identification of Showers with Cores Outside the ARGO-YBJ Detector

In any EAS array, the rejection of events with shower cores outside the detector boundaries is of great importance. A large difference between the true and the reconstructed shower core positions may lead to a systematic miscalculation of some shower characteristics. Moreover, an accurate determination of the shower core position for selected internal events is important to reconstruct the primary direction using conical fits to the shower front, improving the detector angular resolution, or to performe an efficient gamma/hadron discrimination. In this paper we present a procedure able to identify and reject showers with cores outside the ARGO-YBJ carpet boundaries. A comparison of the results for gamma and proton induced showers is reported.Comment: 4 pages, to be published in the Proceedings of the 28th International Cosmic Ray Conference (Tsukuba, Japan 2003

The Networked Common Goods Game

We introduce a new class of games called the networked common goods game (NCGG), which generalizes the well-known common goods game. We focus on a fairly general subclass of the game where each agent's utility functions are the same across all goods the agent is entitled to and satisfy certain natural properties (diminishing return and smoothness). We give a comprehensive set of technical results listed as follows. * We show the optimization problem faced by a single agent can be solved efficiently in this subclass. The discrete version of the problem is however NP-hard but admits an fully polynomial time approximation scheme (FPTAS). * We show uniqueness results of pure strategy Nash equilibrium of NCGG, and that the equilibrium is fully characterized by the structure of the network and independent of the choices and combinations of agent utility functions. * We show NCGG is a potential game, and give an implementation of best/better response Nash dynamics that lead to fast convergence to an $\epsilon$-approximate pure strategy Nash equilibrium. * Lastly, we show the price of anarchy of NCGG can be as large as $\Omega(n^{1-\epsilon})$ (for any $\epsilon>0$), which means selfish behavior in NCGG can lead to extremely inefficient social outcomes

Ant colony optimisation and local search for bin-packing and cutting stock problems

The Bin Packing Problem and the Cutting Stock Problem are two related classes of NP-hard combinatorial optimization problems. Exact solution methods can only be used for very small instances, so for real-world problems, we have to rely on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to these problems, including Genetic Algorithms and Evolutionary Programming. In the work presented here, we used an ant colony optimization (ACO) approach to solve both Bin Packing and Cutting Stock Problems. We present a pure ACO approach, as well as an ACO approach augmented with a simple but very effective local search algorithm. It is shown that the pure ACO approach can compete with existing evolutionary methods, whereas the hybrid approach can outperform the best-known hybrid evolutionary solution methods for certain problem classes. The hybrid ACO approach is also shown to require different parameter values from the pure ACO approach and to give a more robust performance across different problems with a single set of parameter values. The local search algorithm is also run with random restarts and shown to perform significantly worse than when combined with ACO

The synergistic effect of prebiotics, probiotics and antioxidants on dogs with chronic kidney disease

The use of probiotics, prebiotics and antioxidants could be found beneficial for dogs with chronic kidney disease (CKD). The aim of our case-control study is to evaluate the synergistic effect of a diet integrated with a supplement containing probiotics (Lactobacillus acidophilus), prebiotics (fructoligosaccharides) and antioxidants (Olea Europaea extract) on the nutritional status and on serum and urinary parameters of dogs with CKD. A total of 30 dogs classified with IRIS CKD stage 3 were enrolled and randomly assigned to a control (CG, n = 15) and a treated (TG n = 15) group. The trial consisted in a 7-days adaptation period, followed by 90 days where animals in the TR group received the supplement, while in the CG group the placebo. No significant changes in body weight and body condition score were recorded. We recorded a significant improvement of the protein plasmatic level and a decrease in blood phosphorus, systolic pressure, BUN, proteinuria and urine protein-to-creatinine ratio throughout the trial in the TG compared to the CG group. Furthermore, the parameters related to inflammation and oxidative stress (C-reactive protein and Reactive Oxygen Metabolite- derived compound, respectively) were lower in the TG than in the CG group throughout the study. Our results showed that the supplement allows to maintain the correct nutritional status and to improve blood and kidney parameters in dogs with advance stage of CKD. This supplement could be considered as a new nutritional approach for treating this condition.HIGHLIGHTS Diet supplemented with prebiotics, probiotics and antioxidants is safe for dogs with CKD. The synergic effect of prebiotics, probiotics and antioxidants included in the supplement under study shows the maintenance of a good nutritional status and the improvement of blood and urinary parameters in dogs with CKD

Next-Generation Sequencing for Clinical Management of Multiple Myeloma : Ready for Prime Time?

Personalized treatment is an attractive strategy that promises increased efficacy with reduced side effects in cancer. The feasibility of such an approach has been greatly boosted by next-generation sequencing (NGS) techniques, which can return detailed information on the genome and on the transcriptome of each patient's tumor, thus highlighting biomarkers of response or druggable targets that may differ from case to case. However, while the number of cancers sequenced is growing exponentially, much fewer cases are amenable to a molecularly-guided treatment outside of clinical trials to date. In multiple myeloma, genomic analysis shows a variety of gene mutations, aneuploidies, segmental copy-number changes, translocations that are extremely heterogeneous, and more numerous than other hematological malignancies. Currently, in routine clinical practice we employ reduced FISH panels that only capture three high-risk features as part of the R-ISS. On the contrary, recent advances have suggested that extending genomic analysis to the full spectrum of recurrent mutations and structural abnormalities in multiple myeloma may have biological and clinical implications. Furthermore, increased efficacy of novel treatments can now produce deeper responses, and standard methods do not have enough sensitivity to stratify patients in complete biochemical remission. Consequently, NGS techniques have been developed to monitor the size of the clone to a sensitivity of up to a cell in a million after treatment. However, even these techniques are not within reach of standard laboratories. In this review we will recapitulate recent advances in multiple myeloma genomics, with special focus on the ones that may have immediate translational impact. We will analyze the benefits and pitfalls of NGS-based diagnostics, highlighting crucial aspects that will need to be taken into account before this can be implemented in most laboratories. We will make the point that a new era in myeloma diagnostics and minimal residual disease monitoring is close and conventional genetic testing will not be able to return the required information. This will mandate that even in routine practice NGS should soon be adopted owing to a higher informative potential with increasing clinical benefits

Stat3 promotes mitochondrial transcription and oxidative respiration during maintenance and induction of naive pluripotency.

Transcription factor Stat3 directs self-renewal of pluripotent mouse embryonic stem (ES) cells downstream of the cytokine leukemia inhibitory factor (LIF). Stat3 upregulates pivotal transcription factors in the ES cell gene regulatory network to sustain naïve identity. Stat3 also contributes to the rapid proliferation of ES cells. Here, we show that Stat3 increases the expression of mitochondrial-encoded transcripts and enhances oxidative metabolism. Chromatin immunoprecipitation reveals that Stat3 binds to the mitochondrial genome, consistent with direct transcriptional regulation. An engineered form of Stat3 that localizes predominantly to mitochondria is sufficient to support enhanced proliferation of ES cells, but not to maintain their undifferentiated phenotype. Furthermore, during reprogramming from primed to naïve states of pluripotency, Stat3 similarly upregulates mitochondrial transcripts and facilitates metabolic resetting. These findings suggest that the potent stimulation of naïve pluripotency by LIF/Stat3 is attributable to parallel and synergistic induction of both mitochondrial respiration and nuclear transcription factors.GM’s laboratory is supported by grants from Armenise-Harvard Foundation and Telethon Foundation (TCP13013). The Cambridge Stem Cell Institute receives core funding from the Wellcome Trust and Medical Research Council. GM was supported by a Human Frontier Science Program Fellowship. AS is a Medical Research Professor.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.15252/embj.20159262

Solving Medium-Density Subset Sum Problems in Expected Polynomial Time: An Enumeration Approach

The subset sum problem (SSP) can be briefly stated as: given a target integer $E$ and a set $A$ containing $n$ positive integer $a_j$, find a subset of $A$ summing to $E$. The \textit{density} $d$ of an SSP instance is defined by the ratio of $n$ to $m$, where $m$ is the logarithm of the largest integer within $A$. Based on the structural and statistical properties of subset sums, we present an improved enumeration scheme for SSP, and implement it as a complete and exact algorithm (EnumPlus). The algorithm always equivalently reduces an instance to be low-density, and then solve it by enumeration. Through this approach, we show the possibility to design a sole algorithm that can efficiently solve arbitrary density instance in a uniform way. Furthermore, our algorithm has considerable performance advantage over previous algorithms. Firstly, it extends the density scope, in which SSP can be solved in expected polynomial time. Specifically, It solves SSP in expected $O(n\log{n})$ time when density $d \geq c\cdot \sqrt{n}/\log{n}$, while the previously best density scope is $d \geq c\cdot n/(\log{n})^{2}$. In addition, the overall expected time and space requirement in the average case are proven to be $O(n^5\log n)$ and $O(n^5)$ respectively. Secondly, in the worst case, it slightly improves the previously best time complexity of exact algorithms for SSP. Specifically, the worst-case time complexity of our algorithm is proved to be $O((n-6)2^{n/2}+n)$, while the previously best result is $O(n2^{n/2})$.Comment: 11 pages, 1 figur