Catalytic ozonation of gaseous reduced sulfur compounds using wood fly ash

The feasibility of reusing wood ash as an inexpensive catalyst in a catalytic ozonation process has been demonstrated. Catalytic ozonation was demonstrated to oxidize H2S, methanethiol (MT), dimethyl sulfide (DMS), and dimethyl disulfide (DMDS) at low temperatures (23-25 degrees C). The process oxidized 25-50% of an inlet MT stream at 70 ppmv without the formation of DMDS (contrary to ash plus oxygen in air), oxidized 90-95% of an 85 ppmv stream of DMS, and oxidized 50% of a 100 ppmv DMDS stream using 2 g of wood ash at a space velocity of 720 h(-1) using ozone concentrations ranging from 100 to 300 ppmv. Similarly, 60-70% conversion of a 70 ppmv H2S stream was achieved with 2 g of ash in 1.1 s without catalytic deactivation (approximately 44 h). The overall oxidation rate of H2S, DMS, and DMDS increased with increasing ozone concentration contrary to the oxidation rate of MT, which was independent of ozone concentration. Dimethyl sulfoxide and dimethyl sulfone were identified as the primary end products of DMS oxidation, and SO2 was the end product of H2S and MT oxidation.     

Balancing behavioral privacy and information utility in sensory data flows

Miniaturized smart sensors are increasingly being used to collect personal data which embed minute details of our everyday life. When shared, the data streams can easily be mined to draw a rich set of inferences regarding private behaviors and lifestyle patterns. Disclosure of some of these unintended inferences gives rise to the notion of behavioral privacy different from traditional identity privacy typically addressed in the literature. From the provider’s perspective, we summarize these privacy concerns into three basic questions: (i) Whom to share data with? (ii) How much data to share? and (iii) What data to share?In this paper, we outline the architecture of SensorSafe as a software-based framework with support for three basic mechanisms to allow privacy-aware data sharing. First, it provides a library of routines accessible using a simple GUI for providers to define fine-grained, context-dependent access control. Second, it uses the trust network between consumers and providers to derive the optimal rate of information flow which would maintain both provider privacy and consumer utility. Finally, it introduces a compressive sensing based feature-sharing procedure to further control the amount of information release. We provide simulation results to illustrate the efficacy of each of these mechanisms.     

A linear space algorithm for the LCS problem

Summary The LCS problem is to determine the longest common subsequence (LCS) of two strings. A new linear-space algorithm to solve the LCS problem is presented. The only other algorithm with linear-space complexity is by Hirschberg and has runtime complexity O(mn). Our algorithm, based on the divide and conquer technique, has runtime complexity O(n(m-p)), where p is the length of the LCS.     

Perfectly Reliable Message Transmission

We consider the problem of reliable message transmission between two synchronous players connected by n wires, some of which may be faulty. We show how to get reliability “for free”—reliable transmission of b bits involves a total communication of only O(b) bits, when b is large enough. We also construct an efficient Perfectly Secure Message Transmission Protocol.     

“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix

We examine the time-series relationship between house prices in Los Angeles, Las Vegas, and Phoenix. First, temporal Granger causality tests reveal that Los Angeles house prices cause house prices in Las Vegas (directly) and Phoenix (indirectly). In addition, Las Vegas house prices cause house prices in Phoenix. Los Angeles house prices prove exogenous in a temporal sense and Phoenix house prices do not cause prices in the other two markets. Second, we calculate out-of-sample forecasts in each market, using various vector autoregressive and vector error-correction models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different cities.     

Controllability and Universal Three-qubit Quantum Computation with Trapped Electron States

We show how to control and perform universal three-qubit quantum computation with trapped electron quantum states. The three qubits are the electron spin, and the first two quantum states of the cyclotron and axial harmonic oscillators. We explicitly show how universal three-qubit gates can be performed. As an example of a quantum algorithm, we outline the implementation of the three-qubit Deutsch-Jozsa algorithm in this system.