The effects of soluble gas stabilisation on the quality of packed sardine fillets (Sardina pilchardus) stored in air,VP and MAP

Sardine (Sardina pilchardus) is a species that for its abundance assumes great importance in the Portuguese fishing sector. In order to contribute for a better utilisation of this species, the aim of this study was to investigate the effect of the pre‐treatment with soluble gas stabilisation (SGS) (100% CO₂ at 2 bar, during 15 and 30 min) on the quality and shelf‐life of sardine fillets, packed in air (AP), vacuum (VP) and modified atmosphere (MAP: 5% O₂/35% CO₂/60% N₂). During the chilled storage, the quality changes were evaluated by sensory evaluation, chemical and microbiological analysis. The total volatile basic nitrogen content remained almost constant, between 16 and 19 mg N/100 g muscle, during the storage period, for all samples. The TBARs values increased with storage time, for all batches and storage conditions. The application of SGS treatment to sardine fillets, resulted in a bacteriostatic effect, contributing to the improvement of the microbiological quality of fillets. Considering a sensory criteria, the shelf‐life of SGS pre‐treated sardine fillets was found to be 5 days in AP and MAP while in VP‐treated fillets a shelf‐life of 8 days was reported. At sensory rejection, sardine fillets presented a K‐value of 30% in AP and MAP batches and 40% in VP batch.     

Density and viscosity of tetralin and trans-decalin

New measurements are reported for the density and viscosity of tetralin and trans-decalin. The density was determined from room temperature to 60°C for tetralin and to 95°C for trans-decalin. The kinematic viscosity was measured up to temperatures slightly above 100°C. Our results improve upon the values recommended by the American Petroleum Institute for these liquids.     

Luminous impact of balcony floor at atrium spaces with different well geometries

The atrium concept allows the exploitation of daylighting by bringing natural light into the center of the buildings, thus enhancing a more even distribution of daylight. The configuration of interior balconies, however, is determined based on the purpose of the interior space and the use of the building, which may defeat the primary daylighting advantages inherent in the atrium concept. The authors have developed insights regarding the critical daylighting performance factors by evaluating the relative effect of various interior balcony configurations on illumination level and its distribution with different atrium geometries. For these, parametric measurements of illumination level with a scale model of a four-sided atrium building and various interior balcony configurations have been conducted under diffuse sky conditions within the sky simulator at a Texas university. This paper represents the atrium performance results in terms of daylight factor, Well index, balcony Well index, the configuration of interior balcony; and the results are compared with basecase atria without any interior balcony. As expected, Well index and balcony depth are the most significant factors in daylighting performance in atrium spaces with interior balconies. For the position not covered by balcony, adequate illumination can be achieved for circulation regardless of building Well index and balcony depth although it may be that involved well indices are relatively low. On the other hand, light attenuation on the position under balcony floor is up to 70–90%, in particular, when the Well index becomes higher than 1 m and balcony floor becomes deeper than 3 m.     

Analysis of intraparticle diffusion on adsorption of crystal violet on bentonite

Abstract

In the present work, kinetics of crystal violet (CV) adsorption on bentonite was studied by pore volume and surface diffusion model (PVSDM), surface diffusion model (SDM), and pore volume diffusion model (PVDM). The adsorption decay curves were obtained in batch system using different adsorbent dosages. The PVDM model did not interpreted the kinetic adsorption since the calculated value of D_p equal to 5.64?×?10^?7 cm² s^?1 predicted a slower adsorption than that obtained by the experimental data. The PVSDM results indicates that the intraparticle diffusion is predominantly due to surface diffusion (93%) and the pore volume diffusion can be negligible. Once the surface diffusion was the limiting step, the estimation with one (D_s) and two (D_sq and α) parameters were tested in the SDM model. The statistical analysis revealed that the one-parameter SDM model was most appropriate to predict the CV adsorption on bentonite. The optimal values of Ds ranged from 6.19?×?10^?10 to 6.49?×?10^?10 cm² s^?1, and decrease with the adsorbent dosage.     

An alternative to the search for single polymorphisms: Toward molecular personality scales for the five-factor model.

There is growing evidence that personality traits are affected by many genes, all of which have very small effects. As an alternative to the largely unsuccessful search for individual polymorphisms associated with personality traits, the authors identified large sets of potentially related single nucleotide polymorphisms (SNPs) and summed them to form molecular personality scales (MPSs) with from 4 to 2,497 SNPs. Scales were derived from two thirds of a large (N = 3,972) sample of individuals from Sardinia who completed the Revised NEO Personality Inventory (P. T. Costa, Jr., & R. R. McCrae, 1992) and were assessed in a genomewide association scan. When MPSs were correlated with the phenotype in the remaining one third of the sample, very small but significant associations were found for 4 of the 5e personality factors when the longest scales were examined. These data suggest that MPSs for Neuroticism, Openness to Experience, Agreeableness, and Conscientiousness (but not Extraversion) contain genetic information that can be refined in future studies, and the procedures described here should be applicable to other quantitative traits. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Best economical hybrid energy solution: Model development and case study of a WDS in Portugal

This work aims at the development of an integrated model for analysis and optimization of operating strategies of Water Distribution Systems (WDS), taking into consideration economical-hydraulic-power performances. For this purpose, a software tool has been developed based on the following procedures: (i) an Artificial Neural Network (ANN) to determine the best economical hybrid energy system; (ii) for the ANN training process an energy Configuration type and Economical base Simulator model (CES) is used; (iii) as well a Hydraulic and Power Simulator model (HPS) to describe the hydraulic system behaviour; (iv) a performance assessment tool based on an optimization module to minimize pumping costs and maximize the hydraulic reliability and energy efficiency is then implemented. The Artificial Neural Network uses scenarios with only grid supply, grid combined with hydro-turbine, or with wind turbine and a mutual solution, with hydro and wind turbine. The results obtained show how the model is useful for decision support solutions in the planning of sustainable hybrid energy solutions that can be applied to water distribution systems or others existent hydro-systems, allowing the improvement of the global energy efficiency. A real case study of a small WDS in Portugal is analyzed.     

Inoculum acclimation to oleate promotes the conversion of olive mill wastewater to methane

This work aims at selecting a suitable strategy to accelerate the start-up of the anaerobic treatment of olive mill wastewater (OMW) and to enhance the biogas production. Two anaerobic sludges were tested in toxicity and biodegradability batch experiments: biomass acclimated to oleate (BAO) and biomass non-acclimated (BNA). The results showed that the resistance to OMW toxicity was higher for the BAO than for the BNA. In the presence of OMW, the BNA was inhibited at all concentrations tested, whereas for the BAO no inhibition occurred at 5 and 10 g COD L⁻¹. In fact, even at 25 g COD L⁻¹ both substrates (acetate + OMW) were degraded. The biodegradation rate of OMW was higher in batch vials with the acclimated sludge.The results demonstrate that the use of an acclimated microbial consortium to LCFA compounds is a promising strategy to accelerate the start-up of the digestion process, and to improve the overall anaerobic treatment of a real oily wastewater such as OMW with simultaneous bioenergy production (biogas).     

Dynamic Oscillation via Negative Differential Resistance in Type III Junction Organic/Two-Dimensional and Oxide/Two-Dimensional Transition Metal Dichalcogenide Diodes

Among many of 2D semiconductor-based devices, type III PN junction diodes are given special attentions due to their unique function, negative differential resistance (NDR). However, it has been found uneasy to achieve well-matched type III PN junctions from 2D–2D van der Waals heterojunctions. Here, the authors present other alternatives of type III heterojunctions, using 2D p-MoTe₂/organic n-type dipyrazino[2,3-f:2′,3′-h]quinoxaline-2,3,6,7,10,11-hexacarbonitrile (HAT-CN) and 2D p-WSe₂/n-MoO_x systems. Those junction diodes appear to well-demonstrate static and dynamic NDR behavior via resonant tunneling and electron–hole recombination. Extended to an inverter circuit, p-MoTe₂/n-HAT-CN diode enables multilevel inverter characteristics as monolithically integrated with p-MoTe₂ channel field effect transistor. The same NDR diode shows dynamic LC oscillation behavior under a constant DC voltage, connected to an external inductor. From p-WSe₂/n-MoO_x oxide diode, similar NDR behavior to those of p-MoTe₂/n-HAT-CN is again observed along with LC oscillations. The authors attribute these visible oscillation results to high peak-to-valley current ratios of their organic or oxide/2D heterojunction diodes.     

An Ensemble Based Approach for Sentiment Classification in Asian Regional Language

In today’s digital world, millions of individuals are linked to one another via the Internet and social media. This opens up new avenues for information exchange with others. Sentiment analysis (SA) has gotten a lot of attention during the last decade. We analyse the challenges of Sentiment Analysis (SA) in one of the Asian regional languages known as Marathi in this study by providing a benchmark setup in which we first produced an annotated dataset composed of Marathi text acquired from microblogging websites such as Twitter. We also choose domain experts to manually annotate Marathi microblogging posts with positive, negative, and neutral polarity. In addition, to show the efficient use of the annotated dataset, an ensemble-based model for sentiment analysis was created. In contrast to others machine learning classifier, we achieved better performance in terms of accuracy for ensemble classifier with 10-fold cross-validation (cv), outcomes as 97.77%, f-score is 97.89%.