Response of Corn Seedlings (Zea mays L.) to Different Concentrations of Nitrogen in Absence and Presence of Silicon

Silicon - Corn plants are highly demanding of nitrogen and the application of silicon has been studied because it minimizes stress from different natures, and for the better utilization of some...     

Stability of feature selection algorithms: a study on high-dimensional spaces

With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. This study is an attempt to fill that gap by quantifying the sensitivity of feature selection algorithms to variations in the training set. We assess the stability of feature selection algorithms based on the stability of the feature preferences that they express in the form of weights-scores, ranks, or a selected feature subset. We examine a number of measures to quantify the stability of feature preferences and propose an empirical way to estimate them. We perform a series of experiments with several feature selection algorithms on a set of proteomics datasets. The experiments allow us to explore the merits of each stability measure and create stability profiles of the feature selection algorithms. Finally, we show how stability profiles can support the choice of a feature selection algorithm. Alexandros Kalousis received the B.Sc. degree in computer science, in 1994, and the M.Sc. degree in advanced information systems, in 1997, both from the University of Athens, Greece. He received the Ph.D. degree in meta-learning for classification algorithm selection from the University of Geneva, Department of Computer Science, Geneva, in 2002. Since then he is a Senior Researcher in the same university. His research interests include relational learning with kernels and distances, stability of feature selection algorithms, and feature extraction from spectral data. Julien Prados is a Ph.D. student at the University of Geneva, Switzerland. In 1999 and 2001, he received the B.Sc. and M.Sc. degrees in computer science from the University Joseph Fourier (Grenoble, France). After a year of work in industry, he joined the Geneva Artificial Intelligence Laboratory, where he is working on bioinformatics and datamining tools for mass spectrometry data analysis. Melanie Hilario has a Ph.D. in computer science from the University of Paris VI and currently works at the University of Geneva’s Artificial Intelligence Laboratory. She has initiated and participated in several European research projects on neuro-symbolic integration, meta-learning, and biological text mining. She has served on the program committees of many conferences and workshops in machine learning, data mining, and artificial intelligence. She is currently an Associate Editor of theInternational Journal on Artificial Intelligence Toolsand a member of the Editorial Board of theIntelligent Data Analysis journal.     

Latent variable based model predictive control: Ensuring validity of predictions

This paper presents a methodology to constrain the optimisation problem in LV-MPC so that validity of predictions can be ascertained. LV-MPC is a model-based predictive control methodology implemented in the space of the latent variables and is based on a linear predictor. Provided real processes are non-linear, there is model-process mismatch, and under tight control, the predictor can be used for extrapolation. Extrapolation leads to bad predictions which deteriorates control performance, hence the interest in validity of predictions. In the proposed approach first two validity indicators on predictions are defined. The novelty in the two indicators proposed is they neglect past data, and so validity of predictions is ascertained in terms of future moves which are actually the degrees of freedom in the optimisation. Second, the indicators are introduced in the optimisation as constraints. Provided the indicators are quadratic, recursive optimisation with linearised constraints is implemented. A MIMO example shows how ensuring validity of predictions neglecting past data can improve closed-loop performance, specially under tight control outside the identification region.     

Development and immunobiological evaluation of nanoparticles containing an immunodominant epitope of herpes simplex virus

Herpes simplex virus (HSV) 1 and 2 are viruses that infect individuals worldwide and for which there is no cure or vaccine available. The protective response against herpes is mostly mediated by CD8 T lymphocytes that respond to the immunodominant SSIEFARL epitope. However, there are some obstacles concerning the use of free SSIEFARL for vaccine or immunotherapy. The aim of this study was to evaluate the feasibility of nanoencapsulation of SSIEFARL and its immunostimulatory properties. Nano/SSIEFARL was produced by interfacial polymerization in methylmetacrylate, and the physico‐chemical properties, morphology and immunobiological parameters were evaluated. To evaluate the ex vivo capacity of Nano/SSIEFARL, we used splenocytes from HSV‐1‐infected mice to enhance the frequency of SSIEFARL‐specific CD8 T lymphocytes. The results indicate that Nano/SSIEFARL has a spherical shape, an average diameter of 352 ± 22 nm, the PDI was 0.361 ± 0.009 and is negatively charged (−26.30 ± 35). The stability at 4°C was 28 days. Also, Nano/SSIEFARL is not toxic for cells at low concentrations in vitro and it is taken up by JAWS II dendritic cells. No histopathological changes were observed in kidneys, liver and lymph nodes of animals treated with Nano/SSIEFARL. Nan/SSIEFARL increased the production of IL‐1β, TNF‐α and IL‐12 by the dendritic cells. Finally, Nano/SSIEFARL expanded the frequency of SSIEFARL‐specific CD8+T lymphocytes at the same rate as free SSIEFARL. In conclusion all data together indicate that SSIEFARL is suitable for nanoencapsulation, and the system produced presents some immunoadjuvant properties that can be used to improve the immune response against herpes.     

Neuroprotective Effect of Melatonin: A Novel Therapy against Perinatal Hypoxia-Ischemia

One of the most common causes of mortality and morbidity in children is perinatal hypoxia-ischemia (HI). In spite of the advances in neonatology, its incidence is not diminishing, generating a pediatric population that will require an extended amount of chronic care throughout their lifetime. For this reason, new and more effective neuroprotective strategies are urgently required, in order to minimize as much as possible the neurological consequences of this encephalopathy. In this sense, interest has grown in the neuroprotective possibilities of melatonin, as this hormone may help to maintain cell survival through the modulation of a wide range of physiological functions. Although some of the mechanisms by which melatonin is neuroprotective after neonatal asphyxia remain a subject of investigation, this review tries to summarize some of the most recent advances related with its use as a therapeutic drug against perinatal hypoxic-ischemic brain injury, supporting the high interest in this indoleamine as a future feasible strategy for cerebral asphyctic events.     

A procedure for the simultaneous determination of lipid and protein in biomembranes and other biological samples

Very small sample sizes frequently become the limiting factor in biochemical and biomembrane studies in which routine quantification of protein and bulk lipids are required. The procedure described here allows the simultaneous determination of protein and lipid without initial, multiple aliquots. The method is based on the quantitative precipitation of proteins from a defined hexane/isopropanol mixture. The liquid phase resulting after decanting and concentrating to dryness can then be used to assay the lipid content directly. Quantitative assay of protein can be achieved after resuspension of the pelleted material by addition of sodium dodecyl sulfate (0.1%) and deoxycholate (1%). The method is also applicable to other types of lipid- and protein-containing samples with a broad range of protein/lipid ratios and lipid compositions, as they occur, for example, in serum lipoproteins.     

Comparison of electrostatic fins with piezoelectric impact hammer techniques to extend impulse calibration range of a torsional thrust stand

With the progression of high-power electric propulsion and high thrust-to-power propulsions system, thrust stand diagnostics require high-fidelity calibration systems that are accurate over a large-range of thrust levels. Multi-mode and variable I(sp) propulsion devices also require that a single stand be capable of measuring thrust from 10's of uNs to 100's of mNs. While the torsional thrust stand mechanic and diagnostics are capable of operating over such a large range, current pulsed calibration schemes are typically limited to a few orders of magnitude of dynamic range. In order to develop a stand with enough dynamic range, two separate calibration methods have been examined and compared to create a combined system. Electrostatic fin (ESF) and piezoelectric impact hammer (PIH) calibration systems were simultaneously tested on a large scale torsional thrust stand system. The use of the these two methods allowed the stand to be calibrated over four orders of magnitude, from 0.01 mNs to 750 mNs. The ESF system produced linear results within 0.52% from 0.01 mNs to 20 mNs, while the PIH system extended this calibration range from 10 mNs to 750 mNs with an error of 0.99%. The two calibration methods agreed within 4.51% over their overlapping range of 10-20 mNs.     

Experimental thermal behavior of a power plant reheater

The process conditions of power plant components subjected to high pressures and temperatures are essential to determine their remaining life, availability and efficiency. It is, therefore, expedient to pay special attention to critical components, such as superheater and reheater heat exchangers, headers, and main and reheated steam lines. In this paper, on-line and off-line variables of a power plant reheater that has presented problems of thickness losses and repetitive tube fissures are studied. The fissures are associated with the effect of a thermal–mechanical mechanism. Off-line measurements were taken of the following variables: pressure, temperature, velocity and composition of the gases. On-line instrumentation was completed by the installation of specific thermocouples to ascertain the temperatures in the tubes outlet. Various angles for the fuel inlet of the burners and variations in the number and location of the working burners were also assayed. As a consequence of this analysis, it can be deduced that there are important differences in the outlet temperature of the reheater tubes that decrease for lower powers. Finally, it is pointed that a non-uniform distribution of the steam flow in the reheater might be the cause of the problem.