Hierarchical Partitioning Techniques for Structured Adaptive Mesh Refinement Applications

This paper presents the design and preliminary evaluation of hierarchical partitioning and load-balancing techniques for distributed structured adaptive mesh refinement (SAMR) applications. The overall goal of these techniques is to enable the load distribution to reflect the state of the adaptive grid hierarchy and exploit it to reduce synchronization requirements, improve load-balance, and enable concurrent communications and incremental redistribution. The hierarchical partitioning algorithm (HPA) partitions the computational domain into subdomains and assigns them to hierarchical processor groups. Two variants of HPA are presented in this paper. The static hierarchical partitioning algorithm (SHPA) assigns portions of overall load to processor groups. In SHPA, the group size and the number of processors in each group is setup during initialization and remains unchanged during application execution. It is experimentally shown that SHPA reduces communication costs as compared to the Non-HPA scheme, and reduces overall application execution time by up to 59%. The adaptive hierarchical partitioning algorithm (AHPA) dynamically partitions the processor pool into hierarchical groups that match the structure of the adaptive grid hierarchy. Initial evaluations of AHPA show that it can reduce communication costs by up to 70%.     

LF55GN Photosensitive Flexopolymer: A New Material for Ultrathick and High-Aspect-Ratio MEMS Fabrication

A growing interest in the development of thick functional structures with high aspect ratio for microelectromechanical system (MEMS) applications has triggered the investigation of several polymer materials. This paper presents LF55GN flexopolymer material as a new negative-tone photoresist to fabricate ultrathick MEMS microstructures. Up to 4-mm-thick layers are obtained using a casting method in a single photolithography step. Standard UV illumination is used to polymerize such thick microstructures in less than 1 min and with an aspect ratio up to 27. We have fabricated microstructures on rigid, flexible, and stepped substrates. Using oblique UV exposure, tilted pillars are achieved with an angle of 25deg to the substrate normal. Due to the elastomeric nature of the LF55GN flexopolymer, the microstructures can be easily deformed without causing any stress-related problems.     

Proactive thermal management in green datacenters

The increasing demand for faster computing and high storage capacity has resulted in an increase in energy consumption and heat generation in datacenters. Because of the increase in heat generation, cooling requirements have become a critical concern, both in terms of growing operating costs as well as their environmental and societal impacts. Presently, thermal management techniques make an effort to thermally profile and control datacenters’ cooling equipment to increase their efficiency. In conventional thermal management techniques, cooling systems are triggered by the temperature crossing predefined thresholds. Such reactive approaches result in delayed response as the temperature may already be too high, which can result in performance degradation of hardware.     

ISHair: Importance Sampling for Hair Scattering

We present an importance sampling method for the bidirectional scattering distribution function (bsdf) of hair. Our method is based on the multi‐lobe hair scattering model presented by Sadeghi et al. [ [SPJT10] ]. We reduce noise by drawing samples from a distribution that approximates the bsdf well. Our algorithm is efficient and easy to implement, since the sampling process requires only the evaluation of a few analytic functions, with no significant memory overhead or need for precomputation. We tested our method in a research raytracer and a production renderer based on micropolygon rasterization. We show significant improvements for rendering direct illumination using multiple importance sampling and for rendering indirect illumination using path tracing.     

Mercuric chloride induces increases in both cytoplasmic and nuclear free calcium ions through a protein phosphorylation-linked mechanism

The mechanism of the lymphocyte stimulatory action of sulfhydryl group-reactive mercuric ions was studied with respect to its potential ability to induce a protein tyrosine phosphorylation-linked signal for mobilization of free Ca2+ into cytoplasm and nucleus of the cell. Exposure of human leukamic T cell line (Jurkat) cells to high (1 mM) and low (0.01 mM) concentrations of HgCl2 induced tyrosine phosphorylation of multiple proteins in a concentration-dependent manner. Confocal microscopy directly visualized the time course localization of Ca2+ inside the cells after exposure to HgCl2. The onset and level of Ca2+ mobilization following HgCl2 exposure were in parallel to those of protein tyrosine phosphorylation. Interestingly, by either concentration of HgCl2, Ca2+ was mobilized in both cytoplasm and nucleus almost simultaneously, and the level of Ca2+ mobilization in the nucleus was more than that in the cytoplasm. All the HgCl2-mediated Ca2+ mobilization was prevented by addition of protein kinase inhibitor staurosporin prior to HgCl2. These results suggest that heavy metal stress triggers a protein tyrosine phosphorylation-linked signal that leads to a nuclear event-dominant Ca2+ mobilization.     

The large scale electric power system as a distributed continuum

By modeling an electric power system of generators and transmissions lines as a continuum, a nonlinear partial differential equation is written which exhibits the travelling wave behavior that has been observed in experiments with synchronized phasor measurements. The fact that disturbances spread through the interconnected power system with a certain velocity of propagation is reasonable but not quantitatively well understood. The model relates the velocity of propagation to parameters in the distributed model. Numerical simulations of the continuum model are presented     

Machine learning model for mapping of music mood and human emotion based on physiological signals

Emotion is considered a physiological state that appears whenever a transformation is observed by an individual in their environment or body. While studying the literature, it has been observed that combining the electrical activity of the brain, along with other physiological signals for the accurate analysis of human emotions is yet to be explored in greater depth. On the basis of physiological signals, this work has proposed a model using machine learning approaches for the calibration of music mood and human emotion. The proposed model consists of three phases (a) prediction of the mood of the song based on audio signals, (b) prediction of the emotion of the human-based on physiological signals using EEG, GSR, ECG, Pulse Detector, and finally, (c) the mapping has been done between the music mood and the human emotion and classifies them in real-time. Extensive experimentations have been conducted on the different music mood datasets and human emotion for influential feature extraction, training, testing and performance evaluation. An effort has been made to observe and measure the human emotions up to a certain degree of accuracy and efficiency by recording a person’s bio- signals in response to music. Further, to test the applicability of the proposed work, playlists are generated based on the user’s real-time emotion determined using features generated from different physiological sensors and mood depicted by musical excerpts. This work could prove to be helpful for improving mental and physical health by scientifically analyzing the physiological signals.

     

Reaction rate enhancement during swollen-state polymerization of poly(ethylene terephthalate)

Experimental data are obtained for the extent of swelling and progress of the step-growth swollen-state polymerization (SwSP) of polyethylene terephthalate (PET). The SwSP is carried out in biphenyl and diphenyl ether mixture (26 : 74 w/w) solvent under appropriate conditions designed to understand the factors responsible for enhanced reaction rates. The kinetics rate constants, evaluated in terms of simple model, are found to be 2.5–5 times higher for SwSP as compared to the solid-state polymerization (SSP). As the diffusional/mass transfer effects are eliminated in our experiments, this increase in rate constants can be attributed to increased mobility of reactive chain ends. Polymerization rate is found to be further enhanced by addition of a polycondensation catalyst (Sb₂O₃) to the solvent during SwSP. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 67:1589–1595, 1998