Initial results on fuzzy floating point computation for multimedia processors

During the recent years, the market of mid/low-end portable systems such as PDAs or mobile digital phones have experimented a revolution in both selling volume and features as handheld devices incorporate Multimedia applications. This fact brings to an increase in the computational demands of the devices, while still having the limitation of power (and energy) consumption. Instruction memoization is a promising technique to help alleviate the problem of power consumption of expensive functional units such as the floating-point one. Unfortunately, this technique could be energy-inefficient for low-end systems due to the additional power consumption of the relatively big tables required. In this paper we present a novel way of understanding multimedia floating point operations based on the fuzzy computation paradigm: losses in the computation precision may exchange performance for negligible errors in the output. Exploiting the implicit characteristics of media FP computation, we propose a new technique called fuzzy memoization. Fuzzy memoization expands the capabilities of classic memoization by attaching entries with similar inputs to the same output. We present a case of study for a SH4 like processor and report good performance and power-delay improvements with feasible hardware requirements.Peer ReviewedPostprint (published version

From general research questions to specific answers: Underspecificity as a source of uncertainty in biological conservation

P. 167-180Species distribution modelling may support ecologists in conservation decision-making. However, the applicability of management recommendations depends on the uncertainty associated to the modelling process. A key source of uncertainty is the underspecificity of the research question. Modelling specific questions is straightforward since they drive clearly the methodological choices about input data and model building. Nevertheless, when the research questions remain underspecific, modellers must choose among a wide spectrum of choices, with each decision sequence driving to a different outcome that explain partially the target question. We show how the underspecificity associated to a general research question about Great Bustard breeding success at geographic scale drives to multiple decision choices, leads to a variety of model outcomes and hampers the identification of specific conservation actions. We ran generalised linear models using multi-model inference on a set of databases built according to specific sequences of methodological choices. Then, we evaluated variations in model performance, complexity (parsimony) and nature of predictors, as well as averaged model predictions and spatial congruence among model outputs. Deviance and parsimony varied widely (11.46% to 83.33% and 7 to 18, respectively), as did model averaged mean predictions in occupied areas, contributing predictors and spatial congruence among outputs (rPearson = 0.44 ± 0.23 for models calibrated in occupied areas; 0.48 ± 0.06 for models calibrated in potential/accessible areas). We recommend to carefully fix research questions and associated methodological options through collaborative working frameworks to conceptualize modelling approaches and, thus, to mitigate problems arising from underspecificity and other forms of uncertainty in conservation applications.S

Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A nonlinear model predictive control (NMPC) for the thermal management (TM) of Plug-in Hybrid Electric Vehicles (PHEVs) is presented. TM in PHEVs is crucial to ensure good components performance and durability in all possible climate scenarios. A drawback of accurate TM solutions is the higher electrical consumption due to the increasing number of low voltage (LV) actuators used in the cooling circuits. Hence, more complex control strategies are needed for minimizing components thermal stress and at the same time electrical consumption. In this context, NMPC arises as a powerful method for achieving multiple objectives in Multiple input- Multiple output systems. This paper proposes an NMPC for the TM of the High Voltage (HV) battery and the power electronics (PE) cooling circuit in a PHEV. It distinguishes itself from the previously NMPC reported methods in the automotive sector by the complexity of its controlled plant which is highly nonlinear and controlled by numerous variables. The implemented model of the plant, which is based on experimental data and multi- domain physical equations, has been validated using six different driving cycles logged in a real vehicle, obtaining a maximum error, in comparison with the real temperatures, of 2C. For one of the six cycles, an NMPC software-in-the loop (SIL) is presented, where the models inside the controller and for the controlled plant are the same. This simulation is compared to the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and in addition reduces the cooling electrical consumption by more than 5%. In terms of the objective function, an accumulated and weighted sum of the two goals, this improvement amounts 30%. Finally, the online SIL presented in this paper, suggests that the used optimizer is fast enough for a future implementation in the vehicle.Accepted versio

Modelling the spatial variation of vital rates: An evaluation of the strengths and weaknesses of correlative species distribution models

P. 841-853Aim: Species distribution models based on breeding occurrence data allow for identifying both environmental drivers and geographic areas potentially relevant for breeding. However, the interpretation of model predictions in terms of reproductive performance should be further investigated, as this information is crucial for conservation planning. We evaluated the strengths and weaknesses of a correlative modelling approach based on breeding occurrence data (presence–absence) against another approach based on vital rates’ data (breeding success) for gaining insights on species persistence in the case of Great Bustards (Otis tarda). Location: Spain. Methods: Breeding occurrence and breeding success were independently modelled using generalized linear models and multimodel inference analyses. Sensitivities to the way in which the population parameter (breeding success) was defined were explored by building five versions of the dependent variable. We evaluated differences in model performance and identified areas of congruence for breeding occurrence and breeding success. Results: The agreement between the spatial predictions achieved by breeding occurrence and breeding success models differed substantially across databases, with the largest differences in occupied breeding areas. The deviance explained by the breeding occurrence model was 64.98% and ranged from 7.83% to 62.27% for the breeding success models. Model performance was higher for models calibrated within potential than within occupied breeding areas. Main conclusions: The combination of data on both breeding occurrence and breeding success into a species distribution modelling framework showed the limitations of breeding occurrence models for inferring reproductive parameters. The definition of the population parameter as dependent variable was a key factor that strongly affected the inference of vital rates’ models. The approach allowed for discriminating between areas and landscape attributes necessary for the long-term species persistence from others that may be relevant, but not so much for reproductive performance

COMPARING OUTSTANDING PAPAYA LINES FOR SELECTING AND PRESERVING IMPROVED CHARACTERS

Objective: To evaluate outstanding and adapted papaya lines derived from selection to conserve desirable characteristics. Design/methodology/approach: 23 lines of the 'Maradol' type were evaluated at Antunez Michoacan, Mexico. Initially, the plants' height, stem circumference, number of leaves, and first fruit height were recorded. During their development, outstanding plants were identified, and their self-pollinating was promoted. In the fruits, their polar and equatorial circumference, shape index, weight, width and pulp firmness, and soluble solids were assessed. Results: The plants' development was different, their variability between lines allowed identifying morphological characteristics of interest. Only 10 lines had this condition. The number of fruits formed over covered flower buds and collected fruits on formed fruits was reduced. The fruits´ characterization, except for their soluble solids, showed differences. Multivariate analysis indicated variability associated with each principal component. Limitations on study/implications: Currently in Mexico, there are few papaya varieties, the 'Maradol' variety being dominant, and vulnerable to phytosanitary problems over time. However, developing varieties and seed production is challenging and the pollination control of the plants necessarily intervenes. Findings/conclusions: Out of 23 assessed papaya lines, only 43.48 % reported outstanding plants. Inside these lines, between 5 and 10 % of the plants were chosen. In the developmental progress from the covered flower buds’ stage to formed and collected fruits, only 28 % of fruits were obtained. The selected lines showed fruit variability

Melatonin non-linearly modulates bull spermatozoa motility and physiology in capacitating and non-capacitating conditions

Bull spermatozoa physiology may be modulated by melatonin. We washed ejaculated spermatozoa free of melatonin and incubated them (4 h, 38 °C) with 0-pM, 1-pM, 100-pM, 10-nM and 1-µM melatonin in TALP-HEPES (non-capacitating) and TALP-HEPES-heparin (capacitating). This range of concentrations encompassed the effects mediated by melatonin receptors (pM), intracellular targets (nM–µM) or antioxidant activity (µM). Treatment effects were assessed as motility changes by computer-assisted sperm analysis (CASA) of motility and physiological changes by flow cytometry. Melatonin effects were more evident in capacitating conditions, with 100 pM reducing motility and velocity (VCL) while increasing a “slow” subpopulation. All concentrations decreased apoptotic spermatozoa and stimulated mitochondrial activity in viable spermatozoa, with 100 pM–1 µM increasing acrosomal damage, 10 nM–1 µM increasing intracellular calcium and 1 pM reducing the response to a calcium-ionophore challenge. In non-capacitating media, 1 µM increased hyperactivation-related variables and decreased apoptotic spermatozoa; 100 pM–1 µM increased membrane disorders (related to capacitation); all concentrations decreased mitochondrial ROS production. Melatonin concentrations had a modal effect on bull spermatozoa, suggesting a capacitation-modulating role and protective effect at physiological concentrations (pM). Some effects may be of practical use, considering artificial reproductive techniques

Genetic structure in the paternal lineages of South East Spain revealed by the analysis of 17 Y-STRs

Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-41580-9.The content of this article is part of the Ph.D. thesis of María Saiz which was conducted at the University of Granada under the doctoral programme “Biomedicine”. The authors thank all of the participants who donated buccal swabs and all those who helped in the sample collection—namely, María Luisa Aceituno Villalva, Leticia Olga Rubio Lamia, and Verónica Delgado López. In addition, the authors want to thank Xiomara Gálvez for the technical assistance in the laboratory.The genetic data of 17 Y chromosome short tandem repeats in 146 unrelated donor residents in the provinces of Granada, Málaga, and Almería (GMA) were analyzed to determine the genetic legacy of the male inhabitants of the former Kingdom of Granada. A total of 139 unique haplotypes were identified. Observed allele frequencies and haplogroup frequencies were also analyzed. By AMOVA and STRUCTURE analysis, the populations of the 3 provinces could be treated genetically as a single population. The most frequent haplogroup was R1b1b2 (58.22%). By network analysis of all individuals, we observed a distribution according to haplogroup assignment. To improve the characterization of GMA population, it was compared with those of North Africa, the Iberian Peninsula, and southern Europe. In our analysis of allele frequencies and genetic distances, the GMA population lay within the Spanish population group. Further, in the STRUCTURE analysis, there was no African component in the GMA population, confirming that, based on our genetic markers, the GMA population does not reflect any male genetic influence of the North African people. The presence of African haplogroups in the GMA population is irrelevant when their frequency is compared with those in other European populations

Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control

In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy. Some mathematical models are developed from experimental data to describe the system behavior. The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed. The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework.Peer ReviewedPostprint (author's final draft

Thermal Management in Plug-In Hybrid Electric Vehicles: a Real-Time Nonlinear Model Predictive Control Implementation

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A real-time nonlinear model predictive control (NMPC) for the thermal management (TM) of the electrical components cooling circuit in a Plug-In Hybrid Electric Vehicle (PHEV) is presented. The electrical components are highly temperature-sensitive and therefore working out of the ranges recommended by the manufacturer can lead to their premature aging or even failure. Consequently, the goals for an accurate and efficient TM are two: to keep the main component, the Li-ion battery, within optimal working temperatures, and to consume the minimum possible electrical energy through the cooling circuit actuators. This multi-objective requirement is formulated as a finite-horizon optimal control problem (OCP) that includes a multi-objective cost function, several constraints and a prediction model especially suitable for optimization. The associated NMPC is performed on real-time by the optimization package MUSCOD-II and is validated in three different repeatable test-drives driven with a PHEV. Starting from identical conditions, each cycle is driven once being the cooling circuit controlled with NMPC and once with a conventional approach based on a finite-state machine. Compared to the conventional strategy, the NMPC proposed here results in a more accurate and healthier temperature performance, and at the same time, leads to reductions in the electrical consumption up to 8%.Postprint (author's final draft