Progress in the design of zeolite catalysts for biomass conversion into biofuels and bio-based chemicals

This article reviews the recent advances in the development of zeolite catalysts for biomass valorization processes to produce both biofuels and/or bio-based chemicals, which is an emerging and fast expanding field. The work deals with different types of feedstocks, including vegetable oils, lignocellulose and sugars, as well as with a number of relevant intermediates and platform molecules. Transformation of biomass into valuable products is hindered by a number of factors, mainly related to its complex composition, as biomass typically consists of bulky molecules with high oxygen content. Accordingly, biomass processing usually requires the combination of multiple steps and severe conditions, hence concepts like atom efficiency, product selectivity, and catalyst deactivation become of special relevance. A great progress has been achieved in the past years engineering the properties of zeolites for being adapted to the challenges associated to biomass valorization. The possibility of tailoring the main physicochemical properties of zeolites has become now a reality, being the major reason that explains the success achieved by this class of materials in a growing variety of biomass conversion pathways, as those described in this work: catalytic cracking and pyrolysis, hydrotreatments, with special relevance for hydrodeoxygenation processes, as well as in a high number of condensation, isomerization, and dehydration reactions. Thus, the development of hierarchical zeolites, exhibiting enhanced accessibility, and the possibility of introducing and combining in a controlled way different types of active sites (Brønsted and Lewis acid centers, basic sites, and metal phases) are the main basis of the excellent performance of zeolites in numerous biomass conversion routes.     

Rare Titin (TTN) Variants in Diseases Associated with Sudden Cardiac Death

A leading cause of death in western countries is sudden cardiac death, and can be associated with genetic disease. Next-generation sequencing has allowed thorough analysis of genes associated with this entity, including, most recently, titin. We aimed to identify potentially pathogenic genetic variants in titin. A total of 1126 samples were analyzed using a custom sequencing panel including major genes related to sudden cardiac death. Our cohort was divided into three groups: 432 cases from patients with cardiomyopathies, 130 cases from patients with channelopathies, and 564 post-mortem samples from individuals showing anatomical healthy hearts and non-conclusive causes of death after comprehensive autopsy. None of the patients included had definite pathogenic variants in the genes analyzed by our custom cardio-panel. Retrospective analysis comparing the in-house database and available public databases also was performed. We identified 554 rare variants in titin, 282 of which were novel. Seven were previously reported as pathogenic. Of these 554 variants, 493 were missense variants, 233 of which were novel. Of all variants identified, 399 were unique and 155 were identified at least twice. No definite pathogenic variants were identified in any of genes analyzed. We identified rare, mostly novel, titin variants that seem to play a potentially pathogenic role in sudden cardiac death. Additional studies should be performed to clarify the role of these variants in sudden cardiac death.     

Causal Network Models in Expert Systems

Abstract: The paper describes causal network models, giving a detailed discussion of their basic assumptions and their associated algorithms for marginalization and updating. Conditional probability tables are shown to be the basis for the aggregation formulas of if-then rules allowing for deriving the uncertainty of conclusions from that of premises. Examples of a pressure tank and a power system are used for illustrating the concepts and all steps of explained algorithms.     

Application of systems identification to the implementation of motion camouflage in mobile robots

Motion camouflage is an animal stealth behaviour in which a shadower—or predator—moves in the vicinity of a shadowee—or prey—in such a way that the later perceives no apparent motion apart from the self motion. Despite some light has been shed on the control mechanism generating this pursuit strategy, it is not fully understood. Motion camouflage represents an interesting challenge in biological motion, and although simulated controllers can be found in the literature, no implementation on real robots has been done so far. This paper presents the first implementation of motion camouflage in real wheeled robots through a polynomial NARMAX model controller. The trajectories to adjust the model are generated using a heuristic approach. The NARMAX model outperforms the heuristic approach in terms of computational time and generates good camouflage trajectories in real robots and simulation. The transparency of polynomial models can also shed some light over this complex animal behaviour.     

Vehicle speed measurement: Cosine error correction

Although laser devices are commonly used to measure distances and vehicle speed in traffic safety-related studies, they suffer from a drawback known as the cosine effect. Furthermore, such traffic safety studies analyze both vehicle speed and a large amount of geographical data. As such, the development of efficient and cost-effective techniques for correcting the cosine error and managing the data involved in vehicle speed studies are needed. This paper presents an algorithm for correcting cosine error based on a Geographic Information System (GIS) that makes use of vehicle speed measurements and Global Positioning System (GPS) coordinates. An experiment using more than 350 vehicle speeds was conducted to test the algorithm, and the case study shows that controlling the quality of laser-measured speeds in order to suppress low quality data or correct measurement errors due to the cosine effect is very useful.     

Antioxidant mechanism of grape procyanidins in muscle tissues: Redox interactions with endogenous ascorbic acid and α-tocopherol

The present study investigates the antioxidant mechanism of grape procyanidins and, in particular, their aptitude to establish redox interactions with two important components of the endogenous antioxidant system of muscle tissues, α-tocopherol (α-TOH) and ascorbic acid (AA). To this end, the progress of lipid oxidation was monitored in fish muscle supplemented with grape procyanidins at the concentrations usually employed in antioxidant food applications, and then related to the redox stability of the endogenous α-TOH and AA. In addition to the lipid oxidation protective effect, the incorporation of procyanidins also provided an improvement of the redox stability of the endogenous components in a straight procyanidinic concentration-dependent manner. Results showed the capacity of procyanidins to repair oxidised α-TOH at medium-long term, and to delay the AA depletion. Therefore, such cooperative redox interaction of exogenous procyanidins adequately complements the natural α-TOH regenerative system supplied by AA that is efficient at the early post mortem stages.     

An efficient algorithm for optimal routing applied to convoy merging manoeuvres in urban environments

This paper describes an innovative routing strategy for intelligent transportation units willing to perform merging manoeuvres with a moving convoy. In particular, we consider a transportation unit located inside a city (pursuer unit), and which wishes to join a convoy that is constantly moving around the city. We first describe a solution that considers idealistic conditions, i.e., the traveling time along each street is constant. We then go on to improve our first approach to deal with the realistic random nature of the traveling times experienced by the pursuer and by the convoy leader. Our search strategy applies Dynamic Programming to achieve a meeting point that is optimal in two ways: on one hand, the optimal destination is the one closest to the current pursuer??s position; on the other hand, the optimal meeting point must minimize the time that elapses until the pursuer meets the convoy (considering that the pursuer must always arrive first). Calculating the optimal path to every possible destination is highly inefficient, error prone and time consuming. On the contrary, we propose an efficient search strategy that will achieve the meeting point and the path to it, both optimally and in a very short time. This enables the real-time application of our approach either for finding new solutions or for re-planning old ones owing to unexpected real-conditions.