Particle grouping, a new method for reducing emission of submicron particles from diesel engines

A new vehicle-exhaust concept is described which leads to a reduced risk for the health and for the environment from particulate matter (PM). The geometry of the exhaust induces particle grouping and coagulation leading to a shift in particle size distribution, which increases the mass/number of the larger particles at the expense of the reduction in the amount of smaller ones. Such a shift in size distribution has implications with respect to particle capturing from diesel engines and other facilities, and with respect to lower residence time of particles which are emitted to the air. The theoretical basis and the supportive experiments are described. The results show that the concept is easy to apply and has significant implications with ramification to reduction of the concentration of submicron PM in main roads, and in work places.     

A parallel FFT on an MIMD machine

In this paper we present a parallelization of the Cooley- Tukey FFT algorithm that is implemented on a shared-memory MIMD (non-vector) machine that was built in the Dept. of Computer Science, Tel Aviv University. A parallel algorithm is presented for one dimension Fourier transform with performance analysis. For a large array of complex numbers to be transformed, an almost linear speed-up is demonstrated. This algorithm can be executed by any number of processors, but generally the number is much less than the length of the input data.     

Sigiri: uniform resource abstraction for grids and clouds

With the maturation of grid computing facilities and recent explosion of cloud computing data centers, midscale computational science has more options than ever before to satisfy computational needs. But heterogeneity brings complexity. We propose a simple abstraction for interaction with heterogeneous resource managers spanning grid and cloud computing and on features that make the tool useful for the midscale physical or natural scientist. Key strengths of the abstraction are its support for multiple standard job specification languages, preservation of direct user interaction with the service, removing the delay that can come through layers of services, and the predictable behavior under heavy loads. Copyright © 2012 John Wiley & Sons, Ltd.     

Tabulated decision aids and airfare pricing

When people shop for airline tickets, the effort-demanding cognitive process of assessing alternative travel dates may have significant effects on consumer decisions. With the advent of the Internet, consumers are gaining access to a growing number of alternative flights. Decision support tools can assist consumers in their search for travel dates and price combinations. Airline carriers have started offering such tools to support flexible travel-date searches on their websites. In this research, we analyze the economic effects of such tools. We hypothesize that these tools directly affect airline carriers’ pricing schemes. As airline carriers display more alternatives on a flexible date search, price variation and number of price changes are expected to decrease, and the average price is expected to increase. We empirically test our hypotheses using airfares from a wide range of US domestic routes. The results broadly support our hypotheses.     

Abstraction-guided synthesis of synchronization

We present a novel framework for automatic inference of efficient synchronization in concurrent programs, a task known to be difficult and error-prone when done manually. Our framework is based on abstract interpretation and can infer synchronization for infinite state programs. Given a program, a specification, and an abstraction, we infer synchronization that avoids all (abstract) interleavings that may violate the specification, but permits as many valid interleavings as possible. Combined with abstraction refinement, our framework can be viewed as a new approach for verification where both the program and the abstraction can be modified on-the-fly during the verification process. The ability to modify the program, and not only the abstraction, allows us to remove program interleavings not only when they are known to be invalid, but also when they cannot be verified using the given abstraction. We implemented a prototype of our approach using numerical abstractions and applied it to verify several example programs.     

Acoustic Cryptanalysis

Many computers emit a high-pitched noise during operation, due to vibration in some of their electronic components. These acoustic emanations are more than a nuisance: They can convey information about the software running on the computer and, in particular, leak sensitive information about security-related computations. In a preliminary presentation (Eurocrypt’04 rump session), we have shown that different RSA keys induce different sound patterns, but it was not clear how to extract individual key bits. The main problem was the very low bandwidth of the acoustic side channel (under 20  kHz using common microphones, and a few hundred kHz using ultrasound microphones), and several orders of magnitude below the GHz-scale clock rates of the attacked computers. In this paper, we describe a new acoustic cryptanalysis key extraction attack, applicable to GnuPG’s implementation of RSA. The attack can extract full 4096-bit RSA decryption keys from laptop computers (of various models), within an hour, using the sound generated by the computer during the decryption of some chosen ciphertexts. We experimentally demonstrate such attacks, using a plain mobile phone placed next to the computer, or a more sensitive microphone placed 10 meters away.     

Jellyfish‐Based Smart Wound Dressing Devices Containing In Situ Synthesized Antibacterial Nanoparticles

Although the negative consequences of the global phenomenon of jellyfish (JF) swarms are well recognized, the use of their biomass for practical applications is mostly limited to a niche in the Asian food industry. This fact is quite surprising since JF's biomass comprises useful biomaterials such as Q‐mucin glycoprotein and collagen. In this work, the JF biomass, collected from two different species, is used to prepare electrospun scaffolds composed of nanometric “core–shell”‐type fibers, in which adjustment of the electrospinning process parameters can easily control their mechanical, morphological, and chemical properties. This nonwoven scaffold shows excellent biocompatibility and biodegradability, indicating suitability for biomedical research contexts. Performed cell proliferation assays show that the scaffold could support the growth of cardiac cells, fitting the requirement of tissue engineering. Additional incorporation of in situ‐generated silver nanoparticles in these nanofibers produced mats with potent antibacterial properties. Preclinical trials with the resulted mats on porcine wound healing models exhibit fast and complete healing of wounds.     

Impulse-based control of joints and muscles

We propose a novel approach to proportional derivative (PD) control exploiting the fact that these equations can be solved analytically for a single degree of freedom. The analytic solution indicates what the PD controller would accomplish in isolation without interference from neighboring joints, gravity and external forces, outboard limbs, etc. Our approach to time integration includes an inverse dynamics formulation that automatically incorporates global feedback so that the per joint predictions are achieved. This effectively decouples stiffness from control so that we obtain the desired target regardless of the stiffness of the joint, which merely determines when we get there. We start with simple examples to illustrate our method, and then move on to more complex examples including PD control of line segment muscle actuators.     

Dependence of neuronal correlations on filter characteristics and marginal spike train statistics

Correlated neural activity has been observed at various signal levels (e.g., spike count, membrane potential, local field potential, EEG, fMRI BOLD). Most of these signals can be considered as superpositions of spike trains filtered by components of the neural system (synapses, membranes) and the measurement process. It is largely unknown how the spike train correlation structure is altered by this filtering and what the consequences for the dynamics of the system and for the interpretation of measured correlations are. In this study, we focus on linearly filtered spike trains and particularly consider correlations caused by overlapping presynaptic neuron populations. We demonstrate that correlation functions and statistical second-order measures like the variance, the covariance, and the correlation coefficient generally exhibit a complex dependence on the filter properties and the statistics of the presynaptic spike trains. We point out that both contributions can play a significant role in modulating the interaction strength between neurons or neuron populations. In many applications, the coherence allows a filter-independent quantification of correlated activity. In different network models, we discuss the estimation of network connectivity from the high-frequency coherence of simultaneous intracellular recordings of pairs of neurons.