Optimal configuration of Energy-Efficient Ethernet

The IEEE 802.3az standard provides a new low power mode that Ethernet network interfaces can use to save energy when there is no traffic to transmit. Simultaneously with the final standard approval, several algorithms were proposed to govern the physical interface state transition between the normal active mode and the new low power mode. In fact, the standard leaves this sleeping algorithm unspecified to spur competition among different vendors and achieve the greatest energy savings. In this paper, we try to bring some light to the most well known sleeping algorithms, providing mathematical models for the expected energy savings and the average packet delay inflicted on outgoing traffic. We will then use the models to derive optimum configuration parameters for them under given efficiency constraints.     

Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection

Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoothly reproduce different RBFs by changing a real parameter τ. In addition, the mixed use of different RBF shapes in only one RBFNN is allowed. Generalized Radial Basis Function (GRBF) is based on Generalized Gaussian Distribution (GGD), which adds a shape parameter, τ, to standard Gaussian Distribution. Moreover, this paper describes a hybrid approach, Hybrid Algorithm (HA), which combines evolutionary and gradient-based learning methods to estimate the architecture, weights and node topology of GRBFNN classifiers. The feasibility and benefits of the approach are demonstrated by means of six gene microarray classification problems taken from bioinformatic and biomedical domains. Three filters were applied: Fast Correlation-Based Filter (FCBF), Best Incremental Ranked Subset (BIRS), and Best Agglomerative Ranked Subset (BARS); this was done in order to identify salient expression genes from among the thousands of genes in microarray data that can directly contribute to determining the class membership of each pattern. After different gene subsets were obtained, the proposed methodology was performed using the selected gene subsets as new input variables. The results confirm that the GRBFNN classifier leads to a promising improvement in accuracy.     

Validation of a Gas Chromatography-Mass Spectrometry Method for the Measurement of the Redox State Metabolic Ratios Lactate/Pyruvate and β-Hydroxybutyrate/Acetoacetate in Biological Samples

The metabolic ratios lactate/pyruvate and β-hydroxybutyrate/acetoacetate are considered valuable tools to evaluate the in vivo redox cellular state by estimating the free NAD+/NADH in cytoplasm and mitochondria, respectively. The aim of the current study was to validate a gas-chromatography mass spectrometry method for simultaneous determination of the four metabolites in plasma and liver tissue. The procedure included an o-phenylenediamine microwave-assisted derivatization, followed by liquid-liquid extraction with ethyl acetate and silylation with bis(trimethylsilyl)trifluoroacetamide:trimethylchlorosilane 99:1. The calibration curves presented acceptable linearity, with a limit of quantification of 0.001 mM for pyruvate, β-hydroxybutyrate and acetoacetate and of 0.01 mM for lactate. The intra-day and inter-day accuracy and precision were within the European Medicines Agency’s Guideline specifications. No significant differences were observed in the slope coefficient of three-point standard metabolite-spiked curves in plasma or liver and water, and acceptable recoveries were obtained in the metabolite-spiked samples. Applicability of the method was tested in precision-cut liver rat slices and also in HepG2 cells incubated under different experimental conditions challenging the redox state. In conclusion, the validated method presented good sensitivity, specificity and reproducibility in the quantification of lactate/pyruvate and β-hydroxybutyrate/acetate metabolites and may be useful in the evaluation of in vivo redox states.     

Performance of Green Solvents in the Extraction of Sunflower Oil from Enzyme-Treated Collets

The main goal of this work is to evaluate the extraction of sunflower oil from enzyme-treated collets using ethanol and isopropanol (IPA) as solvents. The sunflower collets are pretreated with the multienzyme complex Viscozyme L prior to solvent extraction by the Soxhlet method. The influence of the moisture content of the collets, pretreatment, processing time, and solvent type on the amount of total extracted material and the oil extraction efficiency is studied. Some quality parameters such as phospholipid content of the oil and chlorogenic acid content of the residual meal are also analyzed. At low moisture content (7%) the solvents exhibit similar oil extraction ability (98–99%), but with increasing moisture the extraction efficiency of ethanol decreases to about 85%, while no significant differences are observed for IPA. The enzymatic treatment increases the extraction efficiency for all times, especially for ethanol. It is observed that IPA is more efficient in the extraction compared to ethanol, and the amount of nonlipid material is reduced by ≈70%. In addition, the oil extracted with IPA have lower phospholipid content and the residual meal presents a higher chlorogenic acid content. Practical Applications:This work would contribute toward the use of green solvents in the extraction of sunflower oil from collets. Ethanol and isopropanol, used as solvents, present attractive advantages, including low toxicity, good operational security, as well as being obtained from a renewable source. The obtained data provide up-to-date information on the use of these alcohols in the extraction of sunflower oil from collets and the influence of operating conditions, such as moisture content, enzymatic pretreatment of the collets, and the extraction time. Information about oil and meal quality is also reported.     

Determination of the solubility parameter of poly(ethylene oxide) at 25°C by gas-liquid chromatography

The solubility parameter of poly(ethylene oxide) at 25°C has been determined using the method developed by DiPaola-Baranyi and Guillet, by the extrapolation of the values of the interaction parameter χ, at high temperatures, ranging from 70°–90°, 90°–110° and 110°–130°C down to 25°C. The values of the solubility parameter obtained, depending on the temperature ranges employed, are 9.8, 9.9 and 10.1, respectively.     

EvoMiner: frequent subtree mining in phylogenetic databases

The problem of mining collections of trees to identify common patterns, called frequent subtrees (FSTs), arises often when trying to interpret the results of phylogenetic analysis. FST mining generalizes the well-known maximum agreement subtree problem. Here we present EvoMiner, a new algorithm for mining frequent subtrees in collections of phylogenetic trees. EvoMiner is an Apriori-like levelwise method, which uses a novel phylogeny-specific constant-time candidate generation scheme, an efficient fingerprinting-based technique for downward closure, and a lowest-common-ancestor-based support counting step that requires neither costly subtree operations nor database traversal. Our algorithm achieves speedups of up to 100 times or more over Phylominer, the current state-of-the-art algorithm for mining phylogenetic trees. EvoMiner can also work in depth-first enumeration mode to use less memory at the expense of speed. We demonstrate the utility of FST mining as a way to extract meaningful phylogenetic information from collections of trees when compared to maximum agreement subtrees and majority-rule trees—two commonly used approaches in phylogenetic analysis for extracting consensus information from a collection of trees over a common leaf set.     

Selective dynamic serialization for reducing energy consumption in hardware transactional memory systems

In the search for new paradigms to simplify multithreaded programming, Transactional Memory (TM) is currently being advocated as a promising alternative to deadlock-prone lock-based synchronization. In this way, future many-core CMP architectures may need to provide hardware support for TM. On the other hand, power dissipation constitutes a first class consideration in multicore processor designs. In this work, we propose Selective Dynamic Serialization (SDS) as a new technique to improve energy consumption without degrading performance in applications with conflicting transactions by avoiding wasted work due to aborted transactions. Our proposal, which is implemented on top of a hardware transactional memory (HTM) system with an eager conflict management policy, detects and serializes conflicting transactions dynamically (at run-time). In its simplest form, in case of conflict, one transaction is allowed to continue whilst the rest are completely stalled. Once the executing transaction has finished, it wakes up several of the stalling transactions. More elaborated implementations of SDS try to delay this behavior until serialization of transactions is profitable, achieving the best trade-off between performance, energy savings and network traffic. SDS implementations differ from each other in the condition that triggers the serialization mode. We have evaluated several SDS schemes using GEMS, a full-system simulator implementing the LogTM-SE Eager–Eager HTM system, and several benchmarks from the STAMP suite. Results for a 16-core CMP show that SDS obtains reductions of 6 % on average in energy consumption (more than 20 % in high contention scenarios) in a wide range of benchmarks without affecting, on average, execution time. At the same time, network traffic level is also reduced by 22 %.     

Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.     

Changes in serum lipids in rats treated with oral cooper

Disturbances in lipid metabolism during copper deficiency in rats are well recognized. Copper deficiency is associated with the spontaneous retention of hepatic iron. Previous studies have reported that hypercholesterolemia and hypertriglyceridemia are associated with elevated hepatic iron concentrations in copper deficient rats. There was a direct relationship between the magnitude of blood lipids and the concentration of hepatic iron. Based on these data, it has been hypothesized that iron was responsible for the development of lipemia of copper deficiency. In this study was determined the effect of increasing doses of Cu(10, 20 and 50 ppm) in the diet, on the serum total lipids, total cholesterol, triglycerides (triacylglicerols), phospholipids, non-esterified fatty acids (NEFA) and liver iron and zinc concentrations in normal rats. The results were compared with normal rats that received a balanced diet containing 0.6 and 6 ppm of Cu, respectively. The results show that Cu-supplement diminished the cholesterol and triglyceride serum levels, increased the level of phospholipids, NEFA and concomitantly decreased the hepatic concentrations of Fe and Zn. There was a statistically significant (p < 0.05) simple correlation between triglycerides and liver Fe (r = 0.917; R2 = 64.03%), cholesterol and liver Zn (r = 0.872; R2 = 76.07%), cholesterol and liver Fe (r = 0.995; R2 = 99.10%), liver Fe and liver Cu (r = -0.612), liver Fe and liver Zn (r = 0.837), liver Cu and liver Zn (r = -0.612), and serum triglycerides and liver Zn (r = 0.967). The mechanism(s) by which Fe and Zn determine these changes is not known; none of the enzymes that act in cholesterol and triglyceride metabolism and biosynthesis require Fe and/or Zn. The increase of NEFA is due to changes in the process of lipolysis and re-esterification of the fatty acids in blood. However, additional studies are needed for the precise mechanisms of this interrelationships to be clarified.     

Online FPS games: effect of router buffer and multiplexing techniques on subjective quality estimators

First Person Shooters are a genre of online games in which users demand a high interactivity, because the actions and the movements are very fast. They usually generate high rates of small packets which have to be delivered to the server within a deadline. When the traffic of a number of players shares the same link, these flows can be aggregated in order to save bandwidth. Certain multiplexing techniques are able to merge a number of packets, in a similar way to voice trunking, creating a bundle which is transmitted using a tunnel. In addition, the headers of the original packets can be compressed by means of standard algorithms. The characteristics of the buffers of the routers which deliver these bundled packets may have a strong influence on the network impairments (mainly delay, jitter and packet loss) which determine the quality of the game. A subjective quality estimator has been used in order to study the mutual influence of the buffer and multiplexing techniques. Taking into account that there exist buffers which size is measured in terms of bytes, and others measured in packets, both kinds of buffers have been tested, using different sizes. Traces from real game parties have been merged in order to obtain the traffic of 20 simultaneous players sharing the same Internet access. The delay and jitter produced by the buffer of the access router have been obtained using simulations. In general, the quality is expected to be reduced as the background traffic grows, but the results show an anomalous region in which the quality rises with the background traffic amount. Small buffers present better subjective quality results than bigger ones. When the total traffic amount gets above the available bandwidth, the buffers measured in bytes add to the packets a fixed delay, which grows with buffer size. They present a jitter peak when the offered traffic is roughly the link capacity. On the other hand, buffers which size is measured in packets add a smaller delay, but they increase packet loss for gaming traffic. The obtained results illustrate the need of knowing the characteristics of the buffer in order to make the correct decision about traffic multiplexing. As a conclusion, it would be interesting for game developers to identify the behaviour of the router buffer so as to adapt the traffic to it.