Factorization in the Cloud: Integer Factorization Using F# and Windows Azure

Implementations are presented of two common algorithms for integer factorization, Pollard’s “p – 1” method and the SQUFOF method. The algorithms are implemented in the F# language, a functional programming language developed by Microsoft and officially released for the first time in 2010. The algorithms are thoroughly tested on a set of large integers (up to 64 bits in size), running both on a physical machine and a Windows Azure machine instance. Analysis of the relative performance between the two environments indicates comparable performance when taking into account the difference in computing power. Further analysis reveals that the relative performance of the Azure implementation tends to improve as the magnitudes of the integers increase, indicating that such an approach may be suitable for larger, more complex factorization tasks. Finally, several questions are presented for future research, including the performance of F# and related languages for more efficient, parallelizable algorithms, and the relative cost and performance of factorization algorithms in various environments, including physical hardware and commercial cloud computing offerings from the various vendors in the industry.

Extended electrochemical windows made accessible by room temperature ionic liquid/organic solvent electrolyte systems

The electrochemical windows of acetonitrile solutions doped with 0.1 m concentrations of several ionic liquids were examined by cyclic voltammetry at gold and platinum microelectrodes. These results were compared with those observed in the commonly used 0.1 m tetrabutylammonium perchlorate/acetonitrile system as well as with neat ionic liquids. The use of a trifluorotris(pentofluoroethyl)phosphate-based ionic liquid, specifically, as supporting electrolyte in acetonitrile solutions affords a wider anodic window, which is attributed to the high stability of the anionic component of these intrinsically conductive and thermally robust compounds.

Electrochemistry in Room-Temperature Ionic Liquids: Potential Windows at Mercury Electrodes

The cathodic and anodic: potential limit of eleven different ionic liquids were determined at a mercury hemisphere electrode. Ionic liquids containing the phosphonium cation (tri(n-hexyl)tetradecylphosphonium, [P-14.6,P-6.6](+)) give the largest potential window, especially When Coupled to a trifluorotris(pentafluoroethyl)- [FAP](-). or bis(trifluoromethanesulfonyl)imide, [NTf2](-), anion.

Solutes determine the temperature windows for microbial survival and growth

Microbial cells, and ultimately the Earth's biosphere, function within a narrow range of physicochemical conditions. For the majority of ecosystems, productivity is cold-limited, and it is microbes that represent the failure point. This study was carried out to determine if naturally occurring solutes can extend the temperature windows for activity of microorganisms. We found that substances known to disorder cellular macromolecules (chaotropes) did expand microbial growth windows, fungi preferentially accumulated chaotropic metabolites at low temperature, and chemical activities of solutes determined microbial survival at extremes of temperature as well as pressure. This information can enhance the precision of models used to predict if extraterrestrial and other hostile environments are able to support life; furthermore, chaotropes may be used to extend the growth windows for key microbes, such as saprotrophs, in cold ecosystems and manmade biomes.

Direct Visual Indication of pH Windows: 'Off-On-Off' Fluorescent PET (Photoinduced Electron Transfer) Sensors/Switches

1–3, which contain a fluorophore and two proton receptors with opposite PET (photoinduced electron transfer) characteristics, only display strong fluorescence within a pH window whose position and width are tunable.

Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

Cloud computing sobre a plataforma Windows Azure

A utilização massiva da internet e dos serviços que oferece por parte do utilizador final potencia a evolução dos mesmos, motivando as empresas a apostarem no desenvolvimento deste tipo de soluções. Requisitos como o poder de computação, flexibilidade e escalabilidade tornam-se cada vez mais indissociáveis do desenvolvimento aplicacional, o que leva ao surgimento de paradigmas como o de Cloud Computing. É neste âmbito que surge o presente trabalho. Com o objetivo de estudar o paradigma de Cloud Computing inicia-se um estudo sobre esta temática, onde é detalhado o seu conceito, a sua evolução histórica e comparados os diferentes tipos de implementações que suporta. O estudo detalha posteriormente a plataforma Azure, sendo analisada a sua topologia e arquitetura, detalhando-se os seus componentes e a forma como esta mitiga alguns dos problemas mencionados. Com o conhecimento teórico é desenvolvido um protótipo prático sobre esta plataforma, em que se exploram algumas das particularidades da topologia e se interage com as principais redes sociais. O estudo culmina com uma análise sobre os benefícios e desvantagens do Azure e através de um levantamento das necessidades da empresa, determinam-se as oportunidades que a utilização da plataforma poderá proporcionar.

Genome-wide association studies reveal genomic windows and candidate genes related to fat deposition in chickens.

2016