Characterization of pili nut (Canarium ovatum) oil: Fatty acid and triacylglycerol composition and physicochemical properties

The fatty acid and triacylglycerol composition of pili nut (Canarium ovatum) oil and fractions were analyzed by gas chromatography and reversed-phase high-performance liquid chromatography, respectively. The oil obtained by solvent extraction was low in polyunsaturated fatty acids and high in saturates. The polyunsaturated fatty acid (18∶2 and 18∶3) contents were less than 11%, whereas palmitic (16∶0) and stearic acid (18∶0) were 33.3 and 10.9%, respectively. The saturated fatty acid level of the low-melting fraction oil was reduced from 44.4 to 35.5% and the total unsaturated fatty acid levels were increased from 55.6 to 65% by fractional crystallization. Triacylglycerol analysis showed that the high-melting fraction (HM) from pili nut oil consisted of POP, POS, and SOS+SSO (P=palmitic acid, O=oleic acid, and S=stearic acid) in the proportion of 48.6, 38.8, and 8.7%, respectively. The physicochemical properties of the HM fraction were studied using differential scanning calorimetry and pulsed nuclear magnetic resonance. The results showed that the melting range and solid fat content of the HM fraction were very similar to those isolated from cocoa butter and olive oil. The content of POP played an important role in determining the melting range of the HM fraction. It is suggested that this HM fraction may have applications as a cocoa butter substitute in confectionery products.     

Modulatory Effects of Polyphenols on Apoptosis Induction: Relevance for Cancer Prevention

Polyphenols, occurring in fruit and vegetables, wine, tea, extra virgin olive oil, chocolate and other cocoa products, have been demonstrated to have clear antioxidant properties in vitro, and many of their biological actions have been attributed to their intrinsic reducing capabilities. However, it has become clear that, in complex biological systems, polyphenols exhibit several additional properties which are yet poorly understood. Apoptosis is a genetically controlled and evolutionarily conserved form of cell death of critical importance for the normal embryonic development and for the maintenance of tissue homeostasis in the adult organism. The malfunction of the death machinery may play a primary role in various pathological processes, since too little or too much apoptosis can lead to proliferative or degenerative diseases, respectively. Cancer cells are characterized by a deregulated proliferation, and/or an inability to undergo programmed cell death. A large body of evidence indicates that polyphenols can exert chemopreventive effects towards different organ specific cancers, affecting the overall process of carcinogenesis by several mechanisms: inhibition of DNA synthesis, modulation of ROS production, regulation of cell cycle arrest, modulation of survival/proliferation pathways. In addition, polyphenols can directly influence different points of the apoptotic process, and/or the expression of regulatory proteins. Although the bulk of data has been obtained in in vitro systems, a number of clinical studies suggesting a preventive and therapeutic effectiveness of polyphenols in vivo is available. However, a deeper knowledge of the underlying mechanisms responsible for the modulation of apoptosis by polyphenols, and their real effectiveness, is necessary in order to propose them as potential chemopreventive and chemotherapeutic candidates for cancer treatment.     

A multimodal semantic location service for intelligent environments: an application for Smart Hospitals

This paper presents semantic models, mechanisms and a service to locate mobile entities in Smart and Intelligent Environments. The key feature of the service is the semantic integration of different positioning systems that not only enables the environment to handle transparently such physical positioning systems, but also to reason on location information coming from different systems and to combine it to obtain higher context information. Indeed, the service relies on the use of ontologies and rules to define a uniform, unambiguous and well-defined model for the location information, independently of the particular positioning system. Moreover, the location service performs logic and reasoning mechanisms to provide both physical and semantic locations of mobile objects and to infer the finest granularity in the case when a mobile object is located by more than one positioning system. Finally, we present an application of the proposed approach to the case of a Smart Hospital.     

Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning

The microservice architecture has gained remarkable attention in recent years. Microservices allow developers to implement and deploy independent services, so they are a naturally effective architecture for continuously deployed systems. Because of this, several organizations are undertaking the costly process of manually migrating their traditional software architectures to microservices. The research in this paper aims at facilitating the migration from monolithic software architectures to microservices. We propose a framework which enables software developers/architects to migrate their software systems more efficiently by helping them remodularize the source code of their systems. The framework leverages model-driven reverse engineering to obtain a model of the legacy system and reinforcement learning to propose a mapping of this model toward a set of microservices.

     

Twin mirrors for laser interferometric gravitational-wave detectors

Gravitational-wave detectors such as Virgo and the laser interferometric gravitational-wave observatory (LIGO) use a long-baseline Michelson interferometer with Fabry-Perot cavities in the arms to search for gravitational waves. The symmetry between the two Fabry-Perot cavities is crucial to reduce the interferometer's sensitivity to the laser amplitude and frequency noise. To this purpose, the transmittance of the mirrors in both cavities should be as close as possible. This paper describes the realization and the characterization of the first twin large low-loss mirrors with transmissions differing by less than 0.01%.     

The ANNS approach to DEM reconstruction

This research has 6 fundamental aims: (i) to present a modified version of Taylor's interpolation, one that is more effective and faster than the original; (ii) outline the capability of artificial neural networks (ANNs) to perform an optimal functional approximation of the digital elevation model reconstruction from a satellite map, using a small and independent sample of Global Positioning System observations; (iii) demonstrate experimentally how ANNs outperform the traditional and most used algorithm for the height interpolation (Taylor's interpolation); (iv) introduce a new ANN, the Conic Net, able to outperform the results of the classic and more known multilayer perceptron; (v) determine that Conic Nets, even when using Taylor's modified interpolation as input features, are able to optimally approximate the heights with one order of magnitude more than the original satellite map; and (vi) make evident the possibility to interpolate the DEM heights through an ANN, which learns a data set of known points.     

Multidrug Idebenone/Naproxen Co-loaded Aspasomes for Significant in vivo Anti-inflammatory Activity

The use of proper nanocarriers for dermal and transdermal delivery of anti-inflammatory drugs recently gained several attentions in the scientific community because they pass intact and accumulate payloads in the deepest layers of skin tissue. Ascorbyl palmitate-based vesicles (aspasomes) can be considered a promising nanocarrier for dermal and transdermal delivery due to their skin whitening properties and suitable delivery of payloads through the skin. The aim of this study was the synthesis of multidrug Idebenone/naproxen co-loaded aspasomes for the development of an effective anti-inflammatory nanomedicine. Aspasomes had suitable physicochemical properties and were safe in vivo if topically applied on human healthy volunteers. Idebenone/naproxen co-loaded aspasomes demonstrated an increased therapeutic efficacy of payloads compared to the commercially available Naprosyn® gel, with a rapid decrease of chemical-induced erythema on human volunteers. These promising results strongly suggested a potential application of Idebenone/naproxen multidrug aspasomes for the development of an effective skin anti-inflammatory therapy.     

Implementation of a real option in a sustainable supply chain: an empirical study of alkaline battery recycling

Green supply chain management (GSCM) has emerged as a key approach for enterprises seeking to become environmentally sustainable. This paper aims to evaluate and describe the advantages of a GSCM approach by analysing practices and performance consequences in the battery recycling sector. It seeks to integrate works in supply chain management (SCM), environmental management, performance management and real option (RO) theory into one framework. In particular, life cycle assessment (LCA) is applied to evaluate the environmental impact of a battery recycling plant project, and life cycle costing (LCC) is applied to evaluate its economic impact. Firms, also understanding the relevance of GSCM, have often avoided applying the green principles because of the elevated costs that such management involved. Such costs could also seem superior to the potential advantages since standard performance measurement systems are internally and business focused; for these reasons, we consider all the possible value deriving also by uncertainty associated to a green project using the RO theory. This work is one of the few and pioneering efforts to investigate GSCM practices in the battery recycling sector.     

A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm

The JPEG algorithm is one of the most used tools for compressing images. The main factor affecting the performance of the JPEG compression is the quantization process, which exploits the values contained in two tables, called quantization tables. The compression ratio and the quality of the decoded images are determined by these values. Thus, the correct choice of the quantization tables is crucial to the performance of the JPEG algorithm. In this paper, a two-objective evolutionary algorithm is applied to generate a family of optimal quantization tables which produce different trade-offs between image compression and quality. Compression is measured in terms of difference in percentage between the sizes of the original and compressed images, whereas quality is computed as mean squared error between the reconstructed and the original images. We discuss the application of the proposed approach to well-known benchmark images and show how the quantization tables determined by our method improve the performance of the JPEG algorithm with respect to the default tables suggested in Annex K of the JPEG standard.