Ensemble of Efficient Minimal Learning Machines for Classification and Regression

Minimal Learning Machine (MLM) is a recently proposed supervised learning algorithm with performance comparable to most state-of-the-art machine learning methods. In this work, we propose ensemble methods for classification and regression using MLMs. The goal of ensemble strategies is to produce more robust and accurate models when compared to a single classifier or regression model. Despite its successful application, MLM employs a computationally intensive optimization problem as part of its test procedure (out-of-sample data estimation). This becomes even more noticeable in the context of ensemble learning, where multiple models are used. Aiming to provide fast alternatives to the standard MLM, we also propose the Nearest Neighbor Minimal Learning Machine and the Cubic Equation Minimal Learning Machine to cope with classification and single-output regression problems, respectively. The experimental assessment conducted on real-world datasets reports that ensemble of fast MLMs perform comparably or superiorly to reference machine learning algorithms.     

From software extensions to product lines of dataflow programs

Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the \(\mathtt{ReFlO}\) tool and present two non-trivial case studies as evidence of our work’s generality.     

Input output linearization approach to state observer design fornonlinear system

Presents a state observer for a class of nonlinear systems based on the input output linearization. While the previous result presented state observers for nonlinear systems of full relative degree, we proposed a procedure fur the design of nonlinear state observers which do not require the hypothesis of full relative degree. Assuming that there exists a global state observer for internal dynamics and that some functions are globally Lipschitz, we can design a globally convergent state observer. It is also shown that if the zero dynamics are locally exponentially stable, then there exists a local state observer. An example is given to illustrate the proposed design of nonlinear state observers     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.     

Oxidation of proteins: Basic principles and perspectives for blood proteomics

Protein oxidation mechanisms result in a wide array of modifications, from backbone cleavage or protein crosslinking to more subtle modifications such as side chain oxidations. Protein oxidation occurs as part of normal regulatory processes, as a defence mechanism against oxidative stress, or as a deleterious processes when antioxidant defences are overcome. Because blood is continually exposed to reactive oxygen and nitrogen species, blood proteomics should inherently adopt redox proteomic strategies. In this review, we recall the biochemical basis of protein oxidation, review the proteomic methodologies applied to analyse redox modifications, and highlight some physiological and in vitro responses to oxidative stress of various blood components.     

Three-dimensional micro-channel fabrication in polydimethylsiloxane(PDMS) elastomer

This paper describes a fabrication technique for building three-dimensional (3-D) micro-channels in polydimethylsiloxane (PDMS) elastomer. The process allows for the stacking of many thin (less than 100-μm thick) patterned PDMS layers to realize complex 3-D channel paths. The master for each layer is formed on a silicon wafer using an epoxy-based photoresist (SU 8). PDMS is cast against the master producing molded layers containing channels and openings. To realize thin layers with openings, a sandwich molding configuration was developed that allows precise control of the PDMS thickness. The master wafer is clamped within a sandwich that includes flat aluminum plates, a flexible polyester film layer, a rigid Pyrex wafer, and a rubber sheet. A parametric study is performed on PDMS surface activation in a reactive-ion-etching system and the subsequent methanol treatment for bonding and aligning very thin individual components to a substrate. Low RF power and short treatment times are better than high RF power and long treatment times, respectively, for instant bonding. Layer-to-layer alignment of less then 15 μm is achieved with manual alignment techniques that utilize surface tension driven self-alignment methods. A coring procedure is used to realize off-chip fluidic connections via the bottom PDMS layer, allowing the top layer to remain smooth and flat for complete optical access     

Rayonnement en ondes métriques et décimétriques des orages

This article presents the result of the current knowledge on the very high frequency electromagnetic radiation of lightning. A phenomenology analysis of the new results obtained from the study of triggered lightning in New Mexico (TRIP 82) and at Saint-Privat-d’ Allier in Haute-Loire, France (1983) is first described. The authors then present the spectral and temporal characteristics of the VHF/UHF radiation which can be applied to the electromagnetic compatibility of systems. From a synthesis of the experimental and theoretical contributions, they propose a reflection on the lightning initiation process and on the mechanisms generating lightning radiation.     

Three tokens in Herman’s algorithm

Herman’s algorithm is a synchronous randomized protocol for achieving self-stabilization in a token ring consisting of N processes. The interaction of tokens makes the dynamics of the protocol very difficult to analyze. In this paper we study the distribution of the time to stabilization, assuming that there are three tokens in the initial configuration. We show for arbitrary N and for an arbitrary timeout t that the probability of stabilization within time t is minimized by choosing as the initial three-token configuration the configuration in which the tokens are placed equidistantly on the ring. Our result strengthens a corollary of a theorem of McIver and Morgan (Inf. Process Lett. 94(2): 79–84, 2005), which states that the expected stabilization time is minimized by the equidistant configuration.