An experimental comparison between LPG and engine exhaust gas as energy source for an absorption refrigeration system

This paper presents an experimental analysis of an absorption refrigeration system, comparing two different energy sources. The exhaust gas from an internal combustion engine was evaluated against the original energy source, liquefied petroleum gas (LPG). The experiments were performed in a domestic refrigerator, monitoring the air temperature and humidity inside the equipment. A production engine was tested with 25% and wide‐open throttle valve (WOT), mounted on a bench dynamometer. The energy demand, cooling capacity and coefficient of performance (COP) were determined for both energy sources. The results showed that engine exhaust gas is a potential source for absorption refrigeration systems. When the engine exhaust gas was used as energy source, the energy available for the refrigerator was higher with 25% throttle valve opening. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling of potassium sorbate diffusion through chitosan films

The mechanism of potassium sorbate (K-sorbate) release from chitosan films was studied as a function of immersion time in aqueous solution. Fick's law was applied to calculate the diffusion coefficient and the power law defining the type of diffusion mechanism. The novelty in this study is the compound diffusion mechanisms comparison through chitosan film (CF) and chitosan emulsion film. Initially, the lipid was selected to obtain the emulsion films. The evaluation was based on the water vapor permeability (WVP). The lower WVP (32.45% less than chitosan film) was found using 0.5 g/100 g of palmitic acid for 2.0 g/100 g of chitosan. Then, active chitosan films (ACF) were obtained incorporating K-sorbate on CF at 0.1 and 0.5 g/100 g of K-sorbate. Also, active palmitic acid-chitosan films (APEF) were obtained, incorporating 0.1 g/100 g of K-sorbate. The mechanisms of K-sorbate diffusion through ACF and APEF were mainly non-Fickian. However, the K-sorbate diffusion coefficient did not reduced in lipid presence.     

Protein Aggregation Landscape in Neurodegenerative Diseases: Clinical Relevance and Future Applications

Intrinsic disorder is a natural feature of polypeptide chains, resulting in the lack of a defined three-dimensional structure. Conformational changes in intrinsically disordered regions of a protein lead to unstable β-sheet enriched intermediates, which are stabilized by intermolecular interactions with other β-sheet enriched molecules, producing stable proteinaceous aggregates. Upon misfolding, several pathways may be undertaken depending on the composition of the amino acidic string and the surrounding environment, leading to different structures. Accumulating evidence is suggesting that the conformational state of a protein may initiate signalling pathways involved both in pathology and physiology. In this review, we will summarize the heterogeneity of structures that are produced from intrinsically disordered protein domains and highlight the routes that lead to the formation of physiological liquid droplets as well as pathogenic aggregates. The most common proteins found in aggregates in neurodegenerative diseases and their structural variability will be addressed. We will further evaluate the clinical relevance and future applications of the study of the structural heterogeneity of protein aggregates, which may aid the understanding of the phenotypic diversity observed in neurodegenerative disorders.     

Engineering nanoparticles for targeting rheumatoid arthritis: Past,present, and future trends

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by synovial joint inflammation and cartilage and bone tissue destruction. Although there exist some treatment strategies for RA, they are not completely safe and effective. Therefore, it is important to develop and test new drugs for RA that specifically target inflamed/swollen joints and simultaneously attenuate other possible damages to healthy tissues. Nanotechnology can be a good alternative to consider when envisioning precise medication for treating RA. Through the use of nanoparticles, it is possible to increase bioavailability and bioactivity of therapeutics and enable selective targeting to damaged joints. Herein, recent studies using nanoparticles for the treatment of RA, namely with liposomes, polymeric nanoparticles, dendrimers, and metallic nanoparticles, have been reviewed. These therapeutic strategies have shown great promise in improving the treatment over that by traditional drugs. The results of these studies confirm that feasibility of the use of nanoparticles is mainly due to their biocompatibility, low toxicity, controlled release, and selective drug delivery to inflamed tissues in animal RA models. Therefore, it is possible to claim that nanotechnology will, in the near future, play a crucial role in advanced treatments and patient-specific therapies for human diseases such as RA.

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Thin-Layer Drying of Mate Leaves (Ilex paraguariensis) in a Conveyor-Belt Dryer: A Semi-Automatic Control Strategy Based on a Dynamic Model

A feedback strategy of drying control of mate leaves in a thin-layer conveyor-belt dryer was experimentally evaluated. Moisture content in the discharge of the continuous dryer was controlled by manually adjusting the speed of the moving belt between 3.7 × 10^?4 and 15.2 × 10^?4 m s^?1 for approximately 7200 s in 120 s time steps. The sets of PID controller parameters and manipulated conveyor velocities were computed with a dynamic drying model at conditions identical to those found in the closed-loop experiments. The model is represented by a system of two partial differential equations built by energy and solute mass balances in the solid phase of the dryer. A large set of experimental drying curves and temperature of mate leaves as a function of drying time, in the temperature range from 55 to 130°C, confirmed the reliability of the considered model. Experimental closed-loop responses of discharge moisture content in the presence of disturbances in the feed moisture content (≈ 0.5 ? 1.7 dry basis) and variations in set-point (≈ 0.1 ? 1.0 dry basis) validated the suggested control scheme.     

The use of olive mill wastewater by wild type Yarrowia lipolytica strains: medium supplementation and surfactant presence effect

BACKGROUND: The aim of this work was to study the ability of two different wild type strains of the yeast Yarrowia lipolytica to grow on olive mill wastewater (OMW) and their potential to produce high‐value products such as lipases. Factors that affect cellular growth and OMW degradation were studied, such as nitrogen supplementation, cells concentration and surfactant addition. RESULTS: Both strains, W29 and IMUFRJ 50682, were able to grow in OMW with 19 g L^?1 of COD and approximately 800 mg L^?1 of total phenols concentration. The strain W29 presented the highest potential for extracellular lipase production in OMW medium. Lipase productivity was improved by the medium supplementation with ammonium sulphate up to 6 g L^?1, leading to 80% of COD degradation and 70% of total phenols reduction. The surfactant Tween 80 enhanced cell growth and COD degradation, but had a negative effect on lipase activity. CONCLUSIONS Y. lipolytica has a great potential for OMW valorisation by its use as culture medium for biomass and enzymes production. The operating conditions that favoured lipase production differ from the conditions that improve COD reduction. Copyright © 2008 Society of Chemical Industry     

Data mining with Temporal Abstractions: learning rules from time series

A large volume of research in temporal data mining is focusing on discovering temporal rules from time-stamped data. The majority of the methods proposed so far have been mainly devoted to the mining of temporal rules which describe relationships between data sequences or instantaneous events and do not consider the presence of complex temporal patterns into the dataset. Such complex patterns, such as trends or up and down behaviors, are often very interesting for the users. In this paper we propose a new kind of temporal association rule and the related extraction algorithm; the learned rules involve complex temporal patterns in both their antecedent and consequent. Within our proposed approach, the user defines a set of complex patterns of interest that constitute the basis for the construction of the temporal rule; such complex patterns are represented and retrieved in the data through the formalism of knowledge-based Temporal Abstractions. An Apriori-like algorithm looks then for meaningful temporal relationships (in particular, precedence temporal relationships) among the complex patterns of interest. The paper presents the results obtained by the rule extraction algorithm on a simulated dataset and on two different datasets related to biomedical applications: the first one concerns the analysis of time series coming from the monitoring of different clinical variables during hemodialysis sessions, while the other one deals with the biological problem of inferring relationships between genes from DNA microarray data.     

Deterioration status of asbestos-cement roofing sheets assessed by analyzing hyperspectral data

This paper describes a systematic procedure for recognizing corrugated asbestos-cement roofing sheets and evaluating their deterioration status related to the asbestos fiber air dispersion that can cause lung cancer. To develop this procedure, we made field and laboratory measurements and gathered airborne MIVIS data covering two industrial test areas in Italy.Laboratory analyses of asbestos-cement samples representing various levels of deterioration allowed for: (a) recognizing dominant minerals using XRD and FTIR instruments, (b) identifying their optical characteristics using portable field spectrometers (ASD and μFTIR), (c) assessing the abundance of surfacing asbestos fibers using a high resolution scanner.Based on the spectral analyses, two linear regression lines were identified by relating optical asbestos-cement material characteristics (i.e. band-depth ratio of the continuum removed calculated for the two asbestos diagnostic bands at 2.32 μm and at 9.44 μm) to the relative percentage of surfacing asbestos fibers related to AC deterioration status.Suitable MIVIS spectral regions were used in a spectral classification procedure to map asbestos-cement roofs. The detected roofs were further analyzed using the obtained linear regression lines to estimate surfacing asbestos fiber abundance, using the MIVIS TIR range at 9.44 μm, selected by means of the asbestos-cement detection limit analysis.The results showed that a hyperspectral scanner with suitable operational characteristics allows for good clustering of AC roofs as a function of their deterioration status. Therefore, this technique can furnish government authorities with an efficient, rapid and repeatable environmental mapping procedure that can provide information about the location of hazardous AC roofing sheets.     

Technical feasibility assessment of a solar chimney for food drying

Solar dryers use free and renewable energy sources, reduce drying losses (as compared to sun drying) and show lower operational costs than the artificial drying, thus presenting an interesting alternative to conventional dryers. This work proposes to study the feasibility of a solar chimney to dry agricultural products. To assess the technical feasibility of this drying device, a prototype solar chimney, in which the air velocity, temperature and humidity parameters were monitored as a function of the solar incident radiation, was built. Drying tests of food, based on theoretical and experimental studies, assure the technical feasibility of solar chimneys used as solar dryers for agricultural products. The constructed chimney generates a hot airflow with a yearly average rise in temperature (compared to the ambient air temperature) of 13 ± 1 °C. In the prototype, the yearly average mass flow was found to be 1.40 ± 0.08 kg/s, which allowed a drying capacity of approximately 440 kg.