122 research outputs found

    Eco-Driving Optimization Based on Variable Grid Dynamic Programming and Vehicle Connectivity in a Real-World Scenario

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    In a context in which the connectivity level of last-generation vehicles is constantly onthe rise, the combined use of Vehicle-To-Everything (V2X) connectivity and autonomous drivingcan provide remarkable benefits through the synergistic optimization of the route and the speedtrajectory. In this framework, this paper focuses on vehicle ecodriving optimization in a connectedenvironment: the virtual test rig of a premium segment passenger car was used for generatingthe simulation scenarios and to assess the benefits, in terms of energy and time savings, that theintroduction of V2X communication, integrated with cloud computing, can have in a real-worldscenario. The Reference Scenario is a predefined Real Driving Emissions (RDE) compliant route,while the simulation scenarios were generated by assuming two different penetration levels of V2Xtechnologies. The associated energy minimization problem was formulated and solved by means of aVariable Grid Dynamic Programming (VGDP), that modifying the variable state search grid on thebasis of the V2X information allows to drastically reduce the DP computation burden by more than95%. The simulations show that introducing a smart infrastructure along with optimizing the vehiclespeed in a real-world urban route can potentially reduce the required energy by 54% while shorteningthe travel time by 38%. Finally, a sensitivity analysis was performed on the biobjective optimizationcost function to find a set of Pareto optimal solutions, between energy and travel time minimization

    Development of a neural network-based energy management system for a plug-in hybrid electric vehicle

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    The high potential of Artificial Intelligence (AI) techniques for effectively solving complex parameterization tasks also makes them extremely attractive for the design of the Energy Management Systems (EMS) of Hybrid Electric Vehicles (HEVs). In this framework, this paper aims to design an EMS through the exploitation of deep learning techniques, which allow high non-linear relationships among the data characterizing the problem to be described. In particular, the deep learning model was designed employing two different Recurrent Neural Networks (RNNs). First, a previously developed digital twin of a state-of-the-art plug-in HEV was used to generate a wide portfolio of Real Driving Emissions (RDE) compliant vehicle missions and traffic scenarios. Then, the AI models were trained off-line to achieve CO2 emissions minimization providing the optimal solutions given by a global optimization control algorithm, namely Dynamic Programming (DP). The proposed methodology has been tested on a virtual test rig and it has been proven capable of achieving significant improvements in terms of fuel economy for both charge-sustaining and charge-depleting strategies, with reductions of about 4% and 5% respectively if compared to the baseline Rule-Based (RB) strategy

    Innovative Helicopter In-Flight Noise Monitoring Systems Enabled by Rotor-State Measurements

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    The present contribution aims at providing a comprehensive illustration of a new approach to rotorcraft noise abatement, especially during terminal procedures, when the vehicle approaches the ground and the acoustic impact is higher. This approach pursues the development of technologies and tools for real-time, in-flight monitoring of the emitted noise. The effect of the acoustic radiation is presented to the pilot in a condensed, practical form on a new cockpit instrumentation, the Pilot Acoustic Indicator (PAI), to be used for performing quieter maneuvers. The PAI is based on the synergetic composition of pre-calculated acoustic data, which are used in a noise estimation algorithm together with the data gathered by an innovative contactless measurement system, capable of acquiring the main rotor blade motion. The paper reports on the current studies in unsteady and quasi-steady aeroacoustic prediction and tip-path-plane angle of attack and thrust coefficient observation. Results on novel methodologies are discussed, together with the main features of the PAI design and development process

    Análisis comparativo del valor nutricional de la cerveza artesanal y la cerveza industrial

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    El presente artículo se desarrolló con el objetivo realizar un análisis sobre los componentes nutricionales de la cerveza artesanal en contraposición con la cerveza industrial. Se establecieron comparaciones de los valores nutricionales que posee la bebida desarrollada de forma industrial y la artesanal. En el contexto metodológico se estableció un estudio de diseño documental, mostrando resultados de experiencias de varios autores, valores obtenidos conclusiones y hallazgos más representativos. Destacamos la revisión de varias bases de datos: Google Scholar, Library Génesis, se extrajo el contenido y se expuso en el apartado de los resultados. Las conclusiones obtenidas relevantes son que el valor nutritivo de la cerveza artesanal sin importar el cereal que se utilice como base es el fundamento de su mayor concentración de vitaminas y minerales, en comparación con la cerveza industrializada, por los procesos mecánicos que debilitan los componentes alimenticios en la ingesta de la bebida

    Extrinsic and intrinsic factors affecting the activity budget of alpine marmots ( Marmota marmota )

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    From Springer Nature via Jisc Publications RouterHistory: received 2021-05-24, accepted 2022-02-07, registration 2022-02-08, pub-electronic 2022-03-15, online 2022-03-15, pub-print 2022-07Publication status: PublishedAbstract: Extrinsic and intrinsic factors may influence the activity budget of wild animals, resulting in a variation in the time spent in different activities among populations or individuals of the same species. In this study, we examined how extrinsic and intrinsic factors affect the behaviour of the alpine marmot (Marmota marmota), a hibernating social rodent inhabiting high-elevation prairies in the European Alps. We collected behavioural observations during scan sampling sessions on marked individuals at two study sites with different environmental characteristics. We used Bayesian hierarchical multinomial regression models to analyse the influence of both intrinsic (sex and age-dominance status) and extrinsic (environmental and climatic variables) factors on the above-ground activity budget. Marmots spent most of their time above ground foraging, and were more likely to forage when it was cloudy. Extrinsic factors such as the site, period of the season (June, July–August, and August–September), and time of the day were all related to the probability of engaging in vigilance behaviour, which reaches its peak in early morning and late afternoon and during July, the second period included in the study. Social behaviours, such as affiliative and agonistic behaviours, were associated mostly with sex and age-dominance status, and yearlings were the more affiliative individuals compared to other status. Overall, our results suggest that in alpine marmots, intrinsic factors mostly regulate agonistic and affiliative behaviours, while extrinsic factors, with the unexpected exception of temperature, affect the probabilities of engaging in all types of behavioural categories

    Using Prior Information from the Medical Literature in GWAS of Oral Cancer Identifies Novel Susceptibility Variant on Chromosome 4 - the AdAPT Method

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    Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config)

    Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis)

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    Background: The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods: The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results: This 90K "SNP-Chip" was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion: The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.Daniela Iamartino, Ezequiel L. Nicolazzi, Curtis P. Van Tassell, James M. Reecy, Eric R. Fritz-Waters, James E. Koltes, Stefano Biffani, Tad S. Sonstegard, Steven G. Schroeder, Paolo Ajmone-Marsan, Riccardo Negrini, Rolando Pasquariello, Paola Ramelli, Angelo Coletta, José F. Garcia, Ahmad Ali, Luigi Ramunno, Gianfranco Cosenza, Denise A.A. de Oliveira, Marcela G. Drummond, Eduardo Bastianetto, Alessandro Davassi, Ali Pirani, Fiona Brew, John L. William

    Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

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    Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie
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