EvoMiner: frequent subtree mining in phylogenetic databases

The problem of mining collections of trees to identify common patterns, called frequent subtrees (FSTs), arises often when trying to interpret the results of phylogenetic analysis. FST mining generalizes the well-known maximum agreement subtree problem. Here we present EvoMiner, a new algorithm for mining frequent subtrees in collections of phylogenetic trees. EvoMiner is an Apriori-like levelwise method, which uses a novel phylogeny-specific constant-time candidate generation scheme, an efficient fingerprinting-based technique for downward closure, and a lowest-common-ancestor-based support counting step that requires neither costly subtree operations nor database traversal. Our algorithm achieves speedups of up to 100 times or more over Phylominer, the current state-of-the-art algorithm for mining phylogenetic trees. EvoMiner can also work in depth-first enumeration mode to use less memory at the expense of speed. We demonstrate the utility of FST mining as a way to extract meaningful phylogenetic information from collections of trees when compared to maximum agreement subtrees and majority-rule trees—two commonly used approaches in phylogenetic analysis for extracting consensus information from a collection of trees over a common leaf set.     

Dense subgraph maintenance under streaming edge weight updates for real-time story identification

Recent years have witnessed an unprecedented proliferation of social media. People around the globe author, everyday, millions of blog posts, social network status updates, etc. This rich stream of information can be used to identify, on an ongoing basis, emerging stories, and events that capture popular attention. Stories can be identified via groups of tightly coupled real-world entities, namely the people, locations, products, etc, that are involved in the story. The sheer scale and rapid evolution of the data involved necessitate highly efficient techniques for identifying important stories at every point of time. The main challenge in real-time story identification is the maintenance of dense subgraphs (corresponding to groups of tightly coupled entities) under streaming edge weight updates (resulting from a stream of user-generated content). This is the first work to study the efficient maintenance of dense subgraphs under such streaming edge weight updates. For a wide range of definitions of density, we derive theoretical results regarding the magnitude of change that a single edge weight update can cause. Based on these, we propose a novel algorithm, DynDens, which outperforms adaptations of existing techniques to this setting and yields meaningful, intuitive results. Our approach is validated by a thorough experimental evaluation on large-scale real and synthetic datasets.     

Hydrogen from empty cotton boll agro-waste via thermochemical route and feasibility study of operating an IC engine in continuous mode

Hydrogen can be cited as prospective source of clean power. In this work hydrogen rich syn-gas generated from the agro-waste, empty cotton bolls was injected into an IC engine in continuous mode along with gasoline. At the air-fuel ratio of 23.40, specific fuel consumption of 0.35 kg kWh^?1, the engine could be operated with higher efficiency than with gasoline alone. A distinct reduction in emission characteristics could also be seen. Empty cotton bolls derived after removal of cotton from the flower in field, was first studied for fuel properties. The reasonably high heating value (HHV) of 17.54 MJ kg^?1 suggested that it could be a precursor to hydrogen via two stepped thermo-chemical process. The first step involved slow pyrolysis of the biomass at 500 °C for 60 min at a heating rate of 10 °C min^?1 yielding 39.71% bio-char by weight. The C, H, N, S and O contents of the produced bio-char was 59.91, 2.91, 0.72, 0.47 and 35.99% respectively and its HHV was 26.7 MJ kg^?1. Steam gasification of this bio-char, at 700 °C and water flowrate of 7 mL min^?1 exhibited maximum hydrogen yield of 67.42% (v/v) in the syn-gas mixture. Subsequent enrichment of the gas using ethanolamine/ethylene diamine and KMnO₄ solutions resulted in more than 90% (v/v) hydrogen in the combustible gas mixture and the test engine could be effectively operated.     

Silver(I) Polymer of Tripodal Amine: Synthesis,Structure and Photoluminescence

Starting from tripodal ligand tris-(methyl-imidazole) amine (1) the colourless complex tris-(methyl-imidazole)aminesilver(I)perchlorate (2) has been synthesized, characterized by IR, UV/Vis and ¹HNMR spectroscopic studies and finally solid state structure has been established by single crystal X-ray diffraction studies. A single crystal X-ray structure determination revealed the formation of coordination polymer. The crystal structure possesses weak d¹⁰–d¹⁰ ‘argentophilic’ interactions with Ag–Ag separation (3.348 Å). The weak luminance at 375 nm may be this Ag–Ag weak interaction. The molecule possesses weak H-bonding with C2 and C4H of imidazole with oxygen of ClO₄.     

User-Driven Frequency Scaling

We propose and evaluate user-driven frequency scaling (UDFS) for improved power management on processors that support dynamic voltage and frequency scaling (DVFS), e.g, those used in current laptop and desktop computers. UDFS dynamically adapts CPU frequency to the individual user and the workload through a simple user feedback mechanism, unlike currently-used DVFS methods which rely only on CPU utilization. Our UDFS algorithms dramatically reduce typical operating frequencies while maintaining performance at satisfactory levels for each user. We evaluated our techniques through user studies conducted on a Pentium M laptop running Windows applications. The UDFS scheme reduces measured system power by 22.1%, averaged across all our users and applications, compared to the Windows XP DVFS scheme     

Distributed Streams Algorithms for Sliding Windows

Massive data sets often arise as physically distributed, parallel data streams, and it is important to estimate various aggregates and statistics on the union of these streams. This paper presents algorithms for estimating aggregate functions over a “sliding window” of the N most recent data items in one or more streams. Our results include: 1. For a single stream,we present the first ε-approximation scheme for the number of 1’s in a sliding window that is optimal in both worst case time and space. We also present the first ε-approximation scheme for the sum of integers in [0..R] in a sliding window that is optimal in both worst case time and space (assuming R is at most polynomial in N). Both algorithms are deterministic and use only logarithmic memory words. 2. In contrast, we show that any deterministic algorithm that estimates, to within a small constant relative error, the number of 1’s (or the sum of integers) in a sliding window on the union of distributed streams requires Ω(N) space. 3. We present the first (randomized) (ε, δ)-approximation scheme for the number of 1’s in a sliding window on the union of distributed streams that uses only logarithmic memory words. We also present the first (ε, δ)-approximation scheme for the number of distinct values in a sliding window on distributed streams that uses only logarithmic memory words. Our results are obtained using a novel family of synopsis data structures called waves.     

On the designing of densely dispersion-managed optical fiber systems for ultrafast optical communication

We present some theoretical and experimental results which suggest the possibility of constructing a non-empirical methodology of designing optical transmission systems with ultra high bit-rate per channel. Theoretically, we present an average dispersion decreasing densely dispersion-managed (A4dm) fiber system, which exhibits many advantages over the densely dispersion-managed fiber system, such as the possibility of transmitting chirp-free Gaussian pulses at 160 Gbit/s per channel over transoceanic distances, with a reduced energy and minimal intra-channel interaction. Experimentally we present generation of a 160-GHz picosecond pulse train at 1550 nm using multiple four-wave mixing temporal compression of an initial dual frequency beat signal in the anomalous-dispersion regime of a non-zero dispersion shifted fiber. A complete intensity and phase characterization of the pulse train by means of a frequency-resolved optical gating technique is achieved, showing generation of transform-limited pedestal-free Gaussian pulses.