Plant Copper Amine Oxidases: Key Players in Hormone Signaling Leading to Stress-Induced Phenotypic Plasticity

Polyamines are ubiquitous, low-molecular-weight aliphatic compounds, present in living organisms and essential for cell growth and differentiation. Copper amine oxidases (CuAOs) oxidize polyamines to aminoaldehydes releasing ammonium and hydrogen peroxide, which participates in the complex network of reactive oxygen species acting as signaling molecules involved in responses to biotic and abiotic stresses. CuAOs have been identified and characterized in different plant species, but the most extensive study on a CuAO gene family has been carried out in Arabidopsis thaliana. Growing attention has been devoted in the last years to the investigation of the CuAO expression pattern during development and in response to an array of stress and stress-related hormones, events in which recent studies have highlighted CuAOs to play a key role by modulation of a multilevel phenotypic plasticity expression. In this review, the attention will be focused on the involvement of different AtCuAOs in the IAA/JA/ABA signal transduction pathways which mediate stress-induced phenotypic plasticity events.     

Design and Characterization of a New pVII Combinatorial Phage Display Peptide Library for Protease Substrate Mining Using Factor VII Activating Protease (FSAP) as Model

We describe a novel, easy and efficient combinatorial phage display peptide substrate-mining method to map the substrate specificity of proteases. The peptide library is displayed on the pVII capsid of the M13 bacteriophage, which renders pIII necessary for infectivity and efficient retrieval, in an unmodified state. As capture module, the 3XFLAG was chosen due to its very high binding efficiency to anti-FLAG mAbs and its independency of any post-translational modification. This library was tested with Factor-VII activating protease (WT-FSAP) and its single-nucleotide polymorphism variant Marburg-I (MI)-FSAP. The WT-FSAP results confirmed the previously reported Arg/Lys centered FSAP cleavage site consensus as dominant, as well as reinforcing MI-FSAP as a loss-of-function mutant. Surprisingly, rare substrate clones devoid of basic amino acids were also identified. Indeed one of these peptides was cleaved as free peptide, thus suggesting a broader range of WT-FSAP substrates than previously anticipated.     

PRATIT: a CNN-based emotion recognition system using histogram equalization and data augmentation

Multimedia Tools and Applications - Emotions are spontaneous feelings that are accompanied by fluctuations in facial muscles, which leads to facial expressions. Categorization of these facial...     

A novel compact circuit for 4-PAM energy-efficient high speed interconnect data transmission and reception

Transmission of signals, whether on-chip or off-chip, places severe constraints on timing and extracts a large price in energy. New silicon device technologies, such as back-plane CMOS, provide a programmable and adaptable threshold voltage as an additional tool that can be used for low power design. We show that one particularly desirable use of this freedom is energy-efficient high-speed transmission across long interconnects using multi-valued encoding. Our multi-valued CMOS circuits take advantage of the threshold voltage control of the transistors, by using the signal-voltage-to-threshold-voltage span, in order to make area-efficient implementations of 4-PAM (pulse amplitude modulation) transceivers operating at high speed. In a comparison of a variety of published technologies, for signal transmission with interconnects of 10-15 mm length, we show up to 50% improvement in energy for on-chip signal transmission over binary encoding together with higher limits for operating speeds without a penalty in circuit noise margin.     

An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Investigation of rectangular solid-core photonic crystal fiber as temperature sensor

Microsystem Technologies - In this article, a rectangular solid-core photonic crystal fiber (PCF) is proposed as temperature sensor. The air-holes of the PCF have been filled with Ethyl alcohol...     

Security concepts for the dynamics of autonomous vehicle networks

The secure operation of autonomous vehicle networks in the presence of adversarial observation is examined, in the context of a canonical double-integrator-network (DIN) model. Specifically, we study the ability of a sentient adversary to estimate the full network’s state, from noisy local measurements of vehicle motions. Algebraic, spectral, and graphical characterizations are provided, which indicate the critical role of the inter-vehicle communication topology and control scheme in achieving security.     

Evolution of Surface Morphology in Laser-Dressed Alumina Grinding Wheel Material

An approach to laser dressing of alumina grinding wheels is proposed based on solidification microstructures associated with rapid cooling rates obtained in laser surface processing. Laser dressing of alumina grinding wheels forms surface microstructures characterized by multifaceted grains that are expected to facilitate the micro-scale material removal during precision machining. A detailed investigation of variation of grain size and melt depth with laser fluence is conducted. The results are correlated with calculated cooling rates derived from a thermal model. In addition, based on microscopic observations, the formation of surface grains by stacking of individual multifaceted grains formed during laser dressing is suggested.