Correlation approach to work extraction from finite quantum systems

Reversible work extraction from identical quantum systems via collective operations was shown to be possible even without producing entanglement among the sub-parts. Here, we show that implementing such global operations necessarily imply the creation of quantum correlations, as measured by quantum discord. We also reanalyze the conditions under which global transformations outperform local gates as far as maximal work extraction is considered by deriving a necessary and sufficient condition that is based on classical correlations.

Evaluation of information extraction techniques to label extracted data from e-commerce web page

Automatically determining and assigning shared and meaningful text labels to data extracted from an e-Commerce web page is a challenging problem. An e-Commerce web page can display a list of data records, each of which can contain a combination of data items (e.g. product name and price) and explicit labels, which describe some of these data items. Recent advances in extraction techniques have made it much easier to precisely extract individual data items and labels from a web page, however, there are two open problems: 1. assigning an explicit label to a data item, and 2. determining labels for the remaining data items. Furthermore, improvements in the availability and coverage of vocabularies, especially in the context of e-Commerce web sites, means that we now have access to a bank of relevant, meaningful and shared labels which can be assigned to extracted data items. However, there is a need for a technique which will take as input a set of extracted data items and assign automatically to them the most relevant and meaningful labels from a shared vocabulary. We observe that the Information Extraction (IE) community has developed a great number of techniques which solve problems similar to our own. In this work-in-progress paper we propose our intention to theoretically and experimentally evaluate different IE techniques to ascertain which is most suitable to solve this problem.

Automatic extraction of reduced-order models from CFD simulations for building energy modelling

Accurate modelling of the internal climate of buildings is essential if Building Energy Management Systems (BEMS) are to efficiently maintain adequate thermal comfort. Computational fluid dynamics (CFD) models are usually utilised to predict internal climate. Nevertheless CFD models, although providing the necessary level of accuracy, are highly computationally expensive, and cannot practically be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. ROMs are shown to be adequately accurate with a total error below 5% and to retain satisfactory representation of the phenomena modelled. Each ROM has a time to solution under 20seconds, which opens the potential of their integration with BEMS, giving real-time physics-based building energy modelling. A parameter study was conducted to investigate the applicability of the extracted ROM to initial boundary conditions different from those from which it was extracted. The results show that the ROMs retained satisfactory total errors when the initial conditions in the room were varied by ±5°C. This allows the production of a finite number of ROMs with the ability to rapidly model many possible scenarios.

Cataract extraction and patient vision-related quality of life: a cohort study

Aims: Cataract surgery is one of the most common surgeries performed, but its overuse has been reported. The threshold for cataract surgery has become increasingly lenient; therefore, the selection process and surgical need has been questioned. The aim of this study was to evaluate the changes associated with cataract surgery in patient-reported vision-related quality of life (VR-QoL).

Methods: A prospective cohort study was conducted. Consecutive patients referred to cataract clinics in an NHS unit in Scotland were identified. Those listed for surgery were invited to complete a validated questionnaire (TyPE) to measure VR-QoL pre- and post-operatively. TyPE has five different domains (near vision, distance vision, daytime driving, night-time driving, and glare) and a global score of vision. The influence of pre-operative visual acuity (VA) levels, vision, and lens status of the fellow eye on changes in VR-QoL were explored. 

Results: A total of 320 listed patients were approached, of whom 36 were excluded. Among the 284 enrolled patients, 229 (81%) returned the questionnaire after surgery. Results revealed that the mean overall vision improved, as reported by patients. Improvements were also seen in all sub-domains of the questionnaire.

Conclusion: The majority of patients appear to have improvement in patient-reported VR-QoL, including those with good pre-operative VA and previous surgery to the fellow eye. VA thresholds may not capture the effects of the quality of life on patients. This information can assist clinicians to make more informed decisions when debating over the benefits of listing a patient for cataract extraction.

Naphthenic acid extraction and speciation from Doba crude oil using carbonate-based ionic liquids

A number of tetraalkylammonium methylcarbonate and hydrogencarbonate based ionic liquids are shown to be capable of reacting with the naphthenic acids contained in Doba crude oil via a neutralisation reaction. Spectral studies show that the ionic liquids neutralisation mechanism involves the formation of an ionic liquid-naphthenate complex, liberating methanol and carbon dioxide. Extraction of the neutralised complex into a separate methanol phase and subsequent regeneration using aqueous carbonic acid results in ∼70% of the ionic liquid being recovered for recycle. Isolation of the naphthenic acids shows that these make up to 0.85 wt% of the crude oil. Speciation of the naphthenic acids shows a mixture of monocyclic, through to tetracyclic structures with carbon numbers in the range C₁₂-C₄₀.

Ionic liquid solvents of perhalide type for metals for extraction radioactive metals from mineral ores.

The invention relates to a process for dissolving metals (e.g., Al, Cu, Fe, Cr, Sb, Ti, and W) in perhalide contg. ionic liqs. having the formula (I), and to the extn. of metals from mineral ores; the remediation of materials contaminated with heavy, toxic, or radioactive metals; and to the removal of heavy and toxic metals from hydrocarbon streams. In the formula (I), [X] comprises at least one perhalide anion selected from [I3]-, [BrI2]-, [Br2I]-, [ClI2]-, [ClBr2]-, [BrCl2]-, or [ICl2]-, [ClI3]-. The (Cat+) is a cationic species selected from: ammonium, azaannulenium, azathiazolium, benzimidazolium, benzofuranium, benzotriazolium, borolium, cinnolinium, diazabicyclodecenium, diazabicyclononenium, diazabicyclo- undecenium, dithiazolium, furanium, guanidinium, imidazolium, indazolium, indolinium, indolium, morpholinium, oxaborolium, oxaphospholium, oxazinium, oxazolium, iso-oxazolium, oxathiazolium, pentazolium, phospholium, phosphonium, phthalazinium, piperazinium, piperidinium, pyranium, pyrazinium, pyrazolium, pyridazinium, pyridinium, pyrimidinium, pyrrolidinium, pyrrolium, quinazolinium, quinolinium, isoquinolinium, quinoxalinium, selenozolium, sulfonium, tetrazolium, iso-thiadiazolium, thiazinium, thiazolium, thiophenium, thiuronium, triazadecenium, triazinium, triazolium, iso-triazolium, and uronium. [on SciFinder(R)]

Ionic liquids and their use in extraction processes.

There is provided a process for the extn. of at least one arom. compd. from a mixt. with at least one aliph. hydrocarbon, which process comprises contacting said mixt. with a salt that is in a liq. state at a temp. below 150°C, said salt having a cation which comprises an arom. nitrogen-contg. heterocyclic ring system, in which a nitrogen atom forming part of said ring system is quaternized and in which said ring system is substituted by at least one electron-withdrawing substituent. Some of said salts are novel. [on SciFinder(R)]

Moleculary imprinted polymers for extraction of components from foodstruffs

The present invention relates to a novel class of water compatible molecularly imprinted polymers (AquaMIPs) capable of selectively binding target molecules such as riboflavin, or analogues thereof, in water or aqueous media, their synthesis and use thereof in food processing and extraction or separation processes.

Tetrabutylammonium methacrylate as a novel receptor for selective extraction of sulphonylurea drugs from biological fluids using molecular imprinting

Glibenclamide (GLIB), an oral antidiabetic medication of the sulphonylurea drugs family, was stoichiometrically imprinted using tetrabutylammonium methacrylate as the functional monomer, for the first time in molecular imprinting, and utilising the sulphonylurea affinity for carboxylate anions. Solution association between the drug and the novel functional monomer was studied by 1H-NMR titrations, whereby evidence of sulphonylurea deprotonation followed by the formation of “narcissistic” GLIB dimers was found when tested in CDCl3, while an affinity constant in excess of 105 L mol-1 was measured in DMSO-d6. Detailed analysis of GLIB binding on the subsequently prepared imprinted and non-imprinted polymers confirmed deactivation of binding sites by exchange of a proton between GLIB and methacrylate, followed by extraction of the tetrabutylammonium counterion from the polymer matrix, resulting in overall reduced binding capacities and affinities by the imprinted material under equilibrium conditions. An optimised MI-SPE protocol, which included a binding site re-activation step, was developed for the extraction of GLIB from blood serum, whereby recoveries of up to 92.4% were obtained with exceptional sample clean-up.

Control of wild rubber extraction in the forests of northeast India, 1850-1880

This paper uses the history of rubber extraction to explore competing attempts to control the forest environments of Assam and beyond in the second half of the nineteenth century. Forest communities faced rival efforts at environmental control from both European and Indian traders, as well as from various centres of authority within the Raj. Government attempts to regulate rubber collection were undermined by the weak authority of the Raj in these regions, leading to widespread smuggling. Partly in response to the disruptive influence of rubber traders on the frontier, the Raj began to restrict the presence of outsiders in tribal regions, which came to be understood as distinct areas outside British control. When rubber yields from the forests nearest the Brahmaputra fell in the wake of intensive exploitation, India's scientific foresters demanded and from 1870 obtained the ability to regulate the Assamese forests, blaming indigenous rubber tapping strategies for the declining yields and arguing that Indian rubber could be ‘equal [to] if not better' than Amazonian rubber if only tappers would change their practices. The knowledge of the scientific foresters was fundamentally flawed, however, and their efforts to establish a new type of tapping practice failed. By 1880, the government had largely abandoned attempts to regulate wild Indian rubber, though wild sources continued to dominate the supply of global rubber until after 1910.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Evaluation of the ionic liquids 1-alkyl-3-methylimidazolium hexafluorophosphate as a solvent for the extraction of benzene from cyclohexane : ( Liquid + liquid ) equilibria

In the catalytic hydrogenation of benzene to cyclohexane, the separation of unreacted benzene from the product stream is inevitable and essential for an economically viable process. In order to evaluate the separation efficiency of ionic liquids (ILs) as a solvent in this extraction processes, the ternary (liquid + liquid) equilibrium of 1-alkyl-3-methylimidazolium hexafluorophosphate, [Cnmim][PF6] (n = 4, 5, 6), with benzene and cyclohexane was studied at T = 298.15 K and atmospheric pressure. The reliability of the experimentally determined tie-line data was confirmed by applying the Othmer–Tobias equation. The solute distribution coefficient and solvent selectivity for the systems studied were calculated and compared with literature data for other ILs and sulfolane. It turns out that the benzene distribution coefficient increases and solvent selectivity decreases as the length of the cation alkyl chain grows, and the ionic liquids [Cnmim][PF6] proved to be promising solvents for benzene–cyclohexane extractive separation. Finally, an NRTL model was applied to correlate and fit the experimental LLE data for the ternary systems studied.

Deep separation of benzene from cyclohexane by liquid extraction using ionic liquids as the solvent

Separation of benzene and cyclohexane is one of the most important and difficult processes in the petrochemical industry, especially for low benzene concentration. In this work, three ionic liquids (ILs), [Bmim][BF ₄], [Bpy][BF ₄], and [Bmim][SCN], were investigated as the solvent in the extraction of benzene from cyclohexane. The corresponding ternary liquid-liquid equilibria (LLE) were experimentally determined at T = 298.15 K and atmospheric pressure. The LLE data were correlated with the nonrandom two-liquid model, and the parameters were fitted. The separation capabilities of the ILs were evaluated in terms of the benzene distribution coefficient and solvent selectivity. The effect of the IL structure on the separation was explained based on a well-founded physical model, COSMO-RS. Finally, the extraction processes were defined, and the operation parameters were analyzed. It shows that the ILs studied are suitable solvents for the extractive separation of benzene and cyclohexane, and their separation efficiency can be generally ranked as [Bmim][BF ₄] > [Bpy][BF ₄] > [Bmim][SCN]. The extraction process for a feed with 15 mol % benzene was optimized. High product purity (cyclohexane 0.997) and high recovery efficiency (cyclohexane 96.9% and benzene 98.1%) can be reached. © 2012 American Chemical Society.

Improving Recall of Regular Expressions for Information Extraction

Learning or writing regular expressions to identify instances of a specific
concept within text documents with a high precision and recall is challenging.
It is relatively easy to improve the precision of an initial regular expression
by identifying false positives covered and tweaking the expression to avoid the
false positives. However, modifying the expression to improve recall is difficult
since false negatives can only be identified by manually analyzing all documents,
in the absence of any tools to identify the missing instances. We focus on partially
automating the discovery of missing instances by soliciting minimal user
feedback. We present a technique to identify good generalizations of a regular
expression that have improved recall while retaining high precision. We empirically
demonstrate the effectiveness of the proposed technique as compared to
existing methods and show results for a variety of tasks such as identification of
dates, phone numbers, product names, and course numbers on real world datasets