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

Exploiting Significance of Computations for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for environments with energy constraints, provided that applications are given the mechanisms to produce outputs of the highest possible quality within the available energy budget. This paper introduces a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows developers to structure the computation in different tasks, and to express the relative importance of these tasks for the quality of the end result. For non-significant tasks, the developer can also supply less costly, approximate versions. The target energy consumption for a given execution is specified when the application is launched. A significance-aware runtime system employs an application-specific analytical energy model to decide how many cores to use for the execution, the operating frequency for these cores, as well as the degree of task approximation, so as to maximize the quality of the output while meeting the user-specified energy constraints. Evaluation on a dual-socket 16-core Intel platform using 9 benchmark kernels shows that the proposed framework picks the optimal configuration with high accuracy. Also, a comparison with loop perforation (a well-known compile-time approximation technique), shows that the proposed framework results in significantly higher quality for the same energy budget.

Method for rapid extraction of pectic substances from plant materials

A method is described for the rapid extraction of pectic substances from alcohol insoluble solids (AIS) from material of plant origin, especially fruit. Samples of AIS can be prepared for galacturonic acid assay within 60 min using extraction with 0·5m HCl in a Fibertec-1 system (Tecator) for 30 min. The extraction conditions are carefully standardised and operator error is reduced by the elimination of transfer steps, particularly during filtration. The results obtained for plant-derived alcohol insoluble solids containing from 10% to 33% pectic substances were in close agreement with those obtained by enzymic hydrolysis using a commercially available enzyme preparation (Ultrazyme). The method will have application in the rapid, routine estimation of pectic substances in plant materials. © 1987.

Visual outcomes and astigmatism after sutureless, manual cataract extraction in rural China: study of cataract outcomes and up-take of services (SCOUTS) in the caring is hip project, report 1.

OBJECTIVE: To study the visual acuity and astigmatism of persons undergoing cataract extraction by local surgeons in rural China. METHODS: Visual acuity, keratometry, and refraction were measured 10 to 14 months postoperatively for all cataract cases during 4 months in Sanrao, China. RESULTS: Among 313 eligible subjects, 242 (77%) could be contacted, of whom 176 (73%) were examined. Of those who were examined, mean +/- SD age was 69.3 +/- 10.5 years, 66.5% were female, 35 had been operated on bilaterally at Sanrao, and 85.2% had a preoperative presenting visual acuity of 6/60 or worse. Presenting and best-corrected postoperative acuity in the eye that was operated on were 6/18 or better in 83.4% and 95.7%, respectively. Among 27 fellow eyes operated on elsewhere, 40.7% had a presenting acuity of 6/18 or better and 40.7% were blind (P < .001). Mean +/- SD postoperative astigmatism did not differ between 211 eyes that were operated on (-1.13 +/- 0.84 diopters) and 109 eyes that were not (-1.13 +/- 1.17 diopters; P = .27). Presence of operative complications (8.5%) and older age were associated with worse vision; bilateral surgery was associated with better vision. CONCLUSIONS: These results confirm the effectiveness of skill transfer in this setting, with superior outcomes to most studies in rural Asia and to eyes in this cohort operated on at other facilities.

Endothelial cell loss and surgically induced astigmatism after sutureless large-incision manual cataract extraction (SLIMCE).

OBJECTIVES:

To describe a modified manual cataract extraction technique, sutureless large-incision manual cataract extraction (SLIMCE), and to report its clinical outcomes.

METHODS:

Case notes of 50 consecutive patients with cataract surgery performed using the SLIMCE technique were retrospectively reviewed. Clinical outcomes 3 months after surgery were analyzed, including postoperative uncorrected visual acuity, best-corrected visual acuity, intraoperative and postoperative complications, endothelial cell loss, and surgically induced astigmatism using the vector analysis method.

RESULTS:

At the 3-month follow-up, all 50 patients had postoperative best-corrected visual acuity of at least 20/60, and 37 patients (74%) had visual acuity of at least 20/30. Uncorrected visual acuity was at least 20/68 in 28 patients (56%) and was between 20/80 and 20/200 in 22 patients (44%). No significant intraoperative complications were encountered, and sutureless wounds were achieved in all but 2 patients. At the 3-month follow-up, endothelial cell loss was 3.9%, and the mean surgically induced astigmatism was 0.69 diopter.

CONCLUSIONS:

SLIMCE is a safe and effective manual cataract extraction technique with low rates of surgically induced astigmatism and endothelial cell loss. In view of its low cost, SLIMCE may have a potential role in reducing cataract blindness in developing countries.

The challenge of MNCs and development: oil extraction, CSR, Nigeria and corruption

Globalisation has led to a shift in world order with the rise of the corporate non-state actor. This rise has led to an assumption that Multi-National Corporations (MNCs) must assume responsibilities beyond profit maximisation for shareholders. With the rise of the MNC as a corporate non-state actor there have been discussions around the role of business with regard to human rights.

This article looks at the case of oil extraction in Nigeria. Focussing on the historical dependency of Nigeria and the evolution of the state into a resource-dependent country, it looks at the limitations of existing human rights obligations as they relate to business. This article proposes that corporate social responsibility (CSR) policies of MNCs can act as a preliminary stage in the quest for wider human rights protections. It is in motivating MNCs to design and implement effective CSR policies in dependent states like Nigeria, that the challenge lies.

Sediment metal bioavailability in Lake Taihu, China: evaluation of sequential extraction, DGT, and PBET techniques

The European “Community Bureau of Reference” (BCR) sequential extraction procedure, diffusive gradient in thin-films technique (DGT), and physiologically based extraction test were applied to assess metal bioavailability in sediments of Lake Taihu (n = 13). Findings from the three methods showed that Cd was a significant problem in the western lake whereas Cu, Zn, and Ni pollution was most severe in the northern lake. Results from the sequential extraction revealed that more than 50 % of the Cu and Zn were highly mobile and defined within the extractable fraction (AS1 + FM2 + OS3) in the majority of the sediments, in contrast extractable fractions of Ni and Cd were lower than 50 % in most of the sampling sites. Average Cu, Zn, Ni, and Cd bioaccessibilities were <50 % in the gastric phase. Zn and Cd bioaccessibility in the intestinal phase was ∼50 % lower than the gastric phase while bioaccessibilities of Cu and Ni were 47–57 % greater than the gastric phase. Linear regression analysis between DGT and BCR measurements indicated that the extractable fractions (AS1 + FM2 + OS3) in the reducing environment were the main source of DGT uptake, suggesting that DGT is a good in situ evaluation tool for metal bioavailability in sediments.