Rayleigh-like instability in the ion-shaping of Au-Ag alloy nanoparticles embedded within a silica matrix

We have studied how spherical 23 ± 3 nm Au(45)Ag(55) nanoparticles embedded within a silica matrix transform into prolate nanorods and nanowires by irradiating them with swift heavy ions. Samples were irradiated at room temperature and normal incidence with 74 MeV Kr and 36 MeV S ions for fluences up to 1.0 × 10(15) cm(-2). We demonstrate the existence of two regimes: (i) below a critical fluence, ～ 2.0 × 10(14) cm(-2), the transformation of the spherical nanoparticle into a nanorod is an individual process, i.e. each nanoparticle transforms into a single nanorod; (ii) for larger fluences the transformation from nanorod to nanowire becomes a collective process, i.e. the break up and dissolution of unstable nanorods contribute to the growth of long nanowires. The passage from the first to the second regime can be interpreted in terms of a Rayleigh-like instability under irradiation. The latter becomes active when the diameter of the nanowire approaches its saturation width under irradiation. Furthermore, we show that the composition of the alloy is only slightly modified during the ion-shaping process. Finally, the energy and the fluence thresholds for deformation and the deformation strain-rate are estimated.     

Solvent-Aided Crystallization for Biodiesel Purification

The application of solvent-aided crystallization (SAC) is based on the addition of a solvent, here 1-butanol, to crude biodiesel to catalyze the purification process by separating biodiesel from contaminants via crystallization process. Response surface methodology was applied to optimize the process parameters of SAC, represented by biodiesel purity. The purified biodiesel was analyzed by means of gas chromatography-mass spectrometry for the composition of the present fatty acid methyl ester (FAME). Under the predicted optimum process conditions within the experimental ranges for the highest biodiesel purity, the predicted biodiesel purity was 99.375 %.     

Involvement of GPx-3 in the Reciprocal Control of Redox Metabolism in the Leukemic Niche

The bone marrow (BM) microenvironment plays a crucial role in the development and progression of leukemia (AML). Intracellular reactive oxygen species (ROS) are involved in the regulation of the biology of leukemia-initiating cells, where the antioxidant enzyme GPx-3 could be involved as a determinant of cellular self-renewal. Little is known however about the role of the microenvironment in the control of the oxidative metabolism of AML cells. In the present study, a coculture model of BM mesenchymal stromal cells (MSCs) and AML cells (KG1a cell-line and primary BM blasts) was used to explore this metabolic pathway. MSC-contact, rather than culture with MSC-conditioned medium, decreases ROS levels and inhibits the Nrf-2 pathway through overexpression of GPx3 in AML cells. The decrease of ROS levels also inactivates p38MAPK and reduces the proliferation of AML cells. Conversely, contact with AML cells modifies MSCs in that they display an increased oxidative stress and Nrf-2 activation, together with a concomitant lowered expression of GPx-3. Altogether, these experiments suggest that a reciprocal control of oxidative metabolism is initiated by direct cell–cell contact between MSCs and AML cells. GPx-3 expression appears to play a crucial role in this cross-talk and could be involved in the regulation of leukemogenesis.     

Safety and cost-effectiveness of outpatient total body irradiation in pediatric patients undergoing stem cell transplantation

Political changes in Poland in 1989 initiated a transition period for country's economy into a free market. This new situation prompted the pharmaceutical sector to apply for marketing authorization of a huge number of drugs. Subsequently, the availability, supply and variety of drugs was changing to resemble the one existing on the European Union market. We have analyzed the pattern of adverse drug reactions reported in Poland during the past 10 years. Subsequently we compared our data for years 1991-1995 with the reports received by the Belgian National Center for Monitoring of Adverse Drug Reactions over period 1990-1994. It was found that the number of reports increased in parallel with the number of drugs available. Also the variety of reported reactions was greater. Spontaneous reporting by individual physicians increased and the number of reports from the pharmaceutical inspection diminished. Comparison with the patterns of reporting in Belgium showed the range of drugs included in the reports to be similar in both countries during the studied period. In conclusion: we found that the increase in range and availability of drugs changed substantially the patterns of reporting of adverse drug reactions in Poland. It became similar to that observed in EU countries.     

Electrophysiological evidence for a shared representational medium for visual images and visual percepts.

Systematic effects of imagery on visual signal detection performance have been used to argue that imagery and the perceptual processing of stimuli interact at some common locus of activity (Farah, 1985). However, such a result is neutral with respect to the question of whether the interaction occurs during modality-specific visual processing of the stimulus. If imagery affects stimulus processing at early, modality-specific stages of stimulus representation, this implies that the shared stimulus representations are visual, whereas if imagery affects stimulus processing only at later, amodal stages of stimulus representation, this implies that imagery involves more abstract, postvisual stimulus representations. To distinguish between these 2 possibilities, we repeated the earlier imagery-perception interaction experiment while recording event-related potentials (ERPs) to stimuli from 16 scalp electrodes. By observing the time course and scalp distribution of the effect of imagery on the ERP to stimuli, we can put constraints on the locus of the shared representations for imagery and perception. An effect of imagery was seen within 200 ms following stimulus presentation, at the latency of the 1st negative component of the visual ERP, localized at the occipital and posterior temporal regions of the scalp, that is, directly over visual cortex. This finding supports the claim that mental images interact with percepts in the visual system proper and hence that mental images are themselves visual representations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Multi-scale Single Image Super-Resolution with Remote-Sensing Application Using Transferred Wide Residual Network

In the integrated circuit (IC) designing floorplanning is an important phase in the process of obtaining the layout of the circuit to be designed. The floorplanning determines the performance, size, yield, and reliability of VLSI ICs. The obtained results in this step are necessary for the other consecutive process of the chip designing. VLSI floorplanning from the computational point of view is a non-polynomial hard (NP-hard problem), and hence cannot be efficiently solved by the classical optimization techniques. In this paper, we have proposed a metaheuristic approach to address the problem by using the parallel particle swarm optimization (P-PSO) technique. The P-PSO uses a new greedy operation on the sequence pair (SP) to explore the search space to find an optimal solution. Experimental results on the Microelectronic Centre of North Carolina and Gigascale Systems Research Center benchmark shows that the applied parallel PSO (P-PSO) may be used to produce an optimal solution.

     

A mortar finite element approach for point,line, and surface contact

An approach for investigating finite deformation contact problems with frictional effects with a special emphasis on nonsmooth geometries such as sharp corners and edges is proposed in this contribution. The contact conditions are separately enforced for point contact, line contact, and surface contact by employing 3 different sets of Lagrange multipliers and, as far as possible, a variationally consistent discretization approach based on mortar finite element methods. The discrete unknowns due to the Lagrange multiplier approach are eliminated from the system of equations by employing so‐called dual or biorthogonal shape functions. For the combined algorithm, no transition parameters are required, and the decision between point contact, line contact, and surface contact is implicitly made by the variationally consistent framework. The algorithm is supported by a penalty regularization for the special scenario of nonparallel edge‐to‐edge contact. The robustness and applicability of the proposed algorithms are demonstrated with several numerical examples.     

Emotional speaker recognition in real life conditions using multiple descriptors and i-vector speaker modeling technique

Multimedia Tools and Applications - Emotional speaker recognition under real life conditions becomes an urgent need for several applications. This paper proposes a novel approach using multiple...     

Anomaly Detection in ICS Datasets with Machine Learning Algorithms

An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as the first line of defense, have been detailed. The machine learning algorithms have been performed with labeled output for prediction classification. The activity traffic between ICS components is analyzed and packet inspection of the dataset is performed for the ICS network. The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.