Selectivity of Supercritical CO<Subscript>2 </Subscript>in the Fractionation of Hake Liver Oil Ethyl Esters

The solubility of different ethyl esters derivatized from hake liver oil in supercritical carbon dioxide was studied. A selectivity factor was used to determine optimal conditions to fractionate the ethyl ester mixture. A strong influence of solvent pressure and temperature was observed within 8.63–18.04 MPa and 40–70 °C. The lowest total solubility of the ethyl ester mixture was obtained when using supercritical carbon dioxide at the lowest density (the lowest pressure and the highest temperatures value tested). The highest discrimination against long-chain polyunsaturated fatty acids (e.g. EPA and DHA) was also obtained at these above conditions. Conversely, higher solubility and lower selectivity were obtained when solvent density increased. Considering this inverse correlation between selectivity and solubility, a single-step batch-fractionation process was designed to increase the 22:6 ethyl ester content from an initial value of 17.5% in the starting material to 55% in the final extract.     

Rheology studies of polyethylene/chemical blowing agent solutions within an injection molding machine

An in‐line capillary rheometer nozzle equipped to a conventional reciprocating 55‐ton injection molding machine was used to study the viscosity of single phase low density polyethylene (LDPE)/chemical blowing agent (CBA) solutions under high shear rate in the concentration range of 0 to 5 wt%. The steady shear viscosity of LDPE with endothermic and exothermic chemical blowing agents was measured for shear rates ranging from 170 to 200,000 s^?1 and under pressure conditions up to 36 MPa. Pressure‐volume‐temperature (pvT) measurements were determined to account for the pressure effects and the changes of the free volume during processing. The viscosity reduction of the polymer‐CBA solution was found to be dependent on the concentration of the chemical blowing agent and melt pressure. A model based on a simplified Cross‐Carreau model, incorporating the pvT behavior of LDPE, and the free volume concept was proposed to estimate the viscosity reduction resulting from the addition of a chemical blowing agent. The model employs a scaling method based on concentration‐dependent and pressure‐dependent shift factors to collapse the viscosity measurement to a master curve at each temperature. POLYM. ENG. SCI., 45:1108–1118, 2005. © 2005 Society of Plastics Engineers     

Influence of maize kernel hardness on flour hydration and cooking properties

Knowledge of the association between cooking properties and endosperm hardness may help nutritionist and processors to select raw materials for preparing maize based food products, particularly those eaten as cooked dispersions. Seven commercial maize cultivars differing in hardness were selected to evaluate endosperm hardness on the kernels and some characteristics such as composition and hydration and cooking properties on the grits obtained from those maizes. Results show that the differences in endosperm hardness (directly related to grits protein content) can explain the differences in swelling and amylographic consistencies values. Cultivars with the hardest endosperm show the lowest values at high temperature. They also show the lowest amylographic consistencies. On the other hand softer endosperms present the highest swelling power and the highest amylographic consistencies. These differences are attributed to the restriction for starch swelling caused by the protein matrix. Endosperm hardness measurements and swelling power at 95 degrees C, can be useful to select cultivars that are going to be used to prepare maize based foods like atoles, polenta, etc.     

Effects of the blending sequence and interfacial agent on the morphology and mechanical properties of injection molded PC/PP Blends

Summary The effects of blending sequence and the addition of an interfacial agent (triblock copolymer styrene-butylene ethylene/styrene, Kraton G1652) on the morphology and the mechanical properties of Polycarbonate (PC)/Polypropylene (PP) blends prepared by injection molding were studied. This study presents an analysis of impact resistance, tensile properties and morphology of the raw materials and the blends at different compositions. The blends, before being injected, were prepared in a twin-screw extruder by different sequences of blending. The results indicate that the blending sequence and the presence of humidity significantly affect the properties and morphology of the blends. For ternary blends (PC/PP/Kraton), only one-step mixing before injection molding proved to be sufficient to improve mechanical properties. Increasing the amount of blending steps did not present a significant change in properties. With the addition of the interfacial agent, higher impact resistance and particle size reduction were observed.     

云环境下基于本体的用户行为分析引擎研究

针对当前大型互联网站提升用户体验的需求,本研究创造性地提出基于本体的用户行为分析引擎的思想,它通过上下文感知技术,实时获取用户访问页面时的上下文信息(以下也称为动态行为),基于本体对用户行为建模,建立基于规则的上下文推理算法,对监测到的动态用户行为进行实时推理,及时反馈结果信息给用户。实验表明:本研究理论上独辟蹊径,设计实现上结合了云存储技术,能够一定程度改善用户体验效果。     

Torrefied agro-industrial residue as filler in natural rubber compounds

This study explored the feasibility of using torrefied biomass as a reinforcing filler in natural rubber compounds. Carbon black was then replaced with the torrefied biomass in elastomer formulations for concentrations varying from 0% to 100% (60 parts per hundred rubber or phr total). Their influence on the curing process, dynamic properties, and mechanical properties was investigated. Results were compared with the properties of vulcanizates containing solely carbon black fillers. Time to cure (t₉₀) for compounds with torrefied biomass fillers increased, while filler-filler interactions (ΔG') decreased, compared to carbon black controls. At low strains, the tan δ values of the torrefied fillers vulcanizates were similar to the controls. Incorporation of torrefied biomass into natural rubber decreased compound tensile strength and modulus but increased elongation. Replacement with torrefied fillers resulted in a weaker filler network in the matrix. Still, results showed that moderate substitution concentrations (~20 phr) could be feasible for some natural rubber applications.     

User simulation in a stochastic dialog system

We present a new methodology of user simulation applied to the evaluation and refinement of stochastic dialog systems. Common weaknesses of these systems are the scarceness of the training corpus and the cost of an evaluation made by real users. We have considered the user simulation technique as an alternative way of testing and improving our dialog system. We have developed a new dialog manager that plays the role of the user. This user dialog manager incorporates several knowledge sources, combining statistical and heuristic information in order to define its dialog strategy. Once the user simulator is integrated into the dialog system, it is possible to enhance the dialog models by an automatic strategy learning. We have performed an extensive evaluation, achieving a slight but clear improvement of the dialog system.     

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

Renal amyloidosis in a drug abuser

Drug abusers, particularly those who inject drugs s.c. ("skin popping"), may develop amyloidosis. Chronic infections are thought to play a pathogenetic role in this setting. A patient is presented who had a history of "skin popping" cocaine and heroin and developed nephrotic syndrome, with an elevated serum creatinine and a creatinine clearance of 61 mL/min. Renal biopsy demonstrated amyloidosis. Treatment with colchicine was initiated, and proteinuria decreased to near normal levels after 12 months. Concomitant with the decrease in proteinuria, creatinine clearance improved, although a repeat renal biopsy failed to show any significant improvement in amyloid burden. These observations suggest that colchicine may be a useful treatment in reversing the proteinuria of renal amyloidosis associated with drug abuse. Furthermore, clinical improvement may occur before any demonstrable regression in the amyloidosis.