Novel hardware and software combination for automotive motorsport vehicles based on direct processing of graphical functions

The main motivation for the work presented here began with previously conducted experiments with a programming concept at the time named "Macro". These experiments led to the conviction that it would be possible to build a system of engine control from scratch, which could eliminate many of the current problems of engine management systems in a direct and intrinsic way. It was also hoped that it would minimize the full range of software and hardware needed to make a final and fully functional system. Initially, this paper proposes to make a comprehensive survey of the state of the art in the specific area of software and corresponding hardware of automotive tools and automotive ECUs. Problems arising from such software will be identified, and it will be clear that practically all of these problems stem directly or indirectly from the fact that we continue to make comprehensive use of extremely long and complex "tool chains". Similarly, in the hardware, it will be argued that the problems stem from the extreme complexity and inter-dependency inside processor architectures. The conclusions are presented through an extensive list of "pitfalls" which will be thoroughly enumerated, identified and characterized. Solutions will also be proposed for the various current issues and for the implementation of these same solutions. All this final work will be part of a "proof-of-concept" system called "ECU2010". The central element of this system is the before mentioned "Macro" concept, which is an graphical block representing one of many operations required in a automotive system having arithmetic, logic, filtering, integration, multiplexing functions among others. The end result of the proposed work is a single tool, fully integrated, enabling the development and management of the entire system in one simple visual interface. Part of the presented result relies on a hardware platform fully adapted to the software, as well as enabling high flexibility and scalability in addition to using exactly the same technology for ECU, data logger and peripherals alike. Current systems rely on a mostly evolutionary path, only allowing online calibration of parameters, but never the online alteration of their own automotive functionality algorithms. By contrast, the system developed and described in this thesis had the advantage of following a "clean-slate" approach, whereby everything could be rethought globally. In the end, out of all the system characteristics, "LIVE-Prototyping" is the most relevant feature, allowing the adjustment of automotive algorithms (eg. Injection, ignition, lambda control, etc.) 100% online, keeping the engine constantly working, without ever having to stop or reboot to make such changes. This consequently eliminates any "turnaround delay" typically present in current automotive systems, thereby enhancing the efficiency and handling of such systems.

Uncovering Dependence Clusters and Linchpin Functions

Dependence clusters are (maximal) collections of mutually dependent source code entities according to some dependence relation. Their presence in software complicates many maintenance activities including testing, refactoring, and feature extraction. Despite several studies finding them common in production code, their formation, identification, and overall structure are not well understood, partly because of challenges in approximating true dependences between program entities. Previous research has considered two approximate dependence relations: a fine-grained statement-level relation using control and data dependences from a program’s System Dependence Graph and a coarser relation based on function-level controlflow reachability. In principal, the first is more expensive and more precise than the second. Using a collection of twenty programs, we present an empirical investigation of the clusters identified by these two approaches. In support of the analysis, we consider hybrid cluster types that works at the coarser function-level but is based on the higher-precision statement-level dependences. The three types of clusters are compared based on their slice sets using two clustering metrics. We also perform extensive analysis of the programs to identify linchpin functions – functions primarily responsible for holding a cluster together. Results include evidence that the less expensive, coarser approaches can often be used as e�ective proxies for the more expensive, finer-grained approaches. Finally, the linchpin analysis shows that linchpin functions can be e�ectively and automatically identified.

Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear functions as well.

Boundary value problems for analytic functions in the class of Cauchy-type integrals with density in

We study the Riemann boundary value problem , for analytic functions in the class of analytic functions represented by the Cauchy-type integrals with density in the spaces with variable exponent. We consider both the case when the coefficient is piecewise continuous and it may be of a more general nature, admitting its oscillation. The explicit formulas for solutions in the variable exponent setting are given. The related singular integral equations in the same setting are also investigated. As an application there is derived some extension of the Szegö-Helson theorem to the case of variable exponents.

Joaquim Rodrigo:a contínua reinvenção da pintura

Tese de doutoramento, História (História da Arte), Universidade de Lisboa, Faculdade de Letras, 2014

Higher order derivatives and norms of certain matrix functions

Tese de doutoramento, Matemática (Álgebra Lógica e Fundamentos), Universidade de Lisboa, Faculdade de Ciências, 2014

Regulatory interactions between the metabolic sensors SIRT1 and AMPK in modulating PPARα linked functions, in obesity-dependent type 2 diabetes mellitus

Tese de doutoramento, Ciências Biomédicas (Ciências Funcionais), Universidade de Lisboa, Faculdade de Medicina, 2014

Image quality optimization, via application of contextual contrast sensitivity and discrimination functions

What is the best luminance contrast weighting-function for image quality optimization? Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. We suggest contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant. In this investigation, test images are weighted with a traditional CSF, cCSF, cVPF and a constant function. Controlled mutations of these functions are also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness are then assessed in two-alternative forced-choice psychophysical tests. We show that maximal quality for our test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.

The effect of a selective CXCR2 antagonist (AZD5069) on human blood neutrophil count and innate immune functions.

Abstract AIMS: The aim of the present study was to investigate whether selective antagonism of the cysteine-X-cysteine chemokine receptor-2 (CXCR2) receptor has any adverse effects on the key innate effector functions of human neutrophils for defence against microbial pathogens. METHODS: In a double-blind, crossover study, 30 healthy volunteers were randomized to treatment with the CXCR2 antagonist AZD5069 (100 mg) or placebo, twice daily orally for 6 days. The peripheral blood neutrophil count was assessed at baseline, daily during treatment and in response to exercise challenge and subcutaneous injection of granulocyte-colony stimulating factor (G-CSF). Neutrophil function was evaluated by phagocytosis of Escherichia coli and by the oxidative burst response to E. coli. RESULTS: AZD5069 treatment reversibly reduced circulating neutrophil count from baseline by a mean [standard deviation (SD)] of -1.67 (0.67) ×10(9) l(-1) vs. 0.19 (0.78) ×10(9) l(-1) for placebo on day 2, returning to baseline by day 7 after the last dose. Despite low counts on day 4, a 10-min exercise challenge increased absolute blood neutrophil count, but the effect with AZD5069 was smaller and not sustained, compared with placebo treatment. Subcutaneous G-CSF on day 5 caused a substantial increase in blood neutrophil count in both placebo- and AZD5069-treated subjects. Superoxide anion production in E. coli-stimulated neutrophils and phagocytosis of E. coli were unaffected by AZD5069 (P = 0.375, P = 0.721, respectively vs. baseline, Day 4). AZD5069 was well tolerated. CONCLUSIONS: CXCR2 antagonism did not appear adversely to affect the mobilization of neutrophils from bone marrow into the peripheral circulation, phagocytosis or the oxidative burst response to bacterial pathogens. This supports the potential of CXCR2 antagonists as a treatment option for diseases in which neutrophils play a pathological role.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

Effects of dual-task training on balance and executive functions in Parkinson's disease: A pilot study

The aim of this study was to analyze the efficacy of cognitive-motor dual-task training compared with single-task training on balance and executive functions in individuals with Parkinson's disease. Fifteen subjects, aged between 39 and 75 years old, were randomly assigned to the dual-task training group (n = 8) and single-task training group (n = 7). The training was run twice a week for 6 weeks. The single-task group received balance training and the dual-task group performed cognitive tasks simultaneously with the balance training. There were no significant differences between the two groups at baseline. After the intervention, the results for mediolateral sway with eyes closed were significantly better for the dual-task group and anteroposterior sway with eyes closed was significantly better for the single-task group. The results suggest superior outcomes for the dual-task training compared to the single-task training for static postural control, except in anteroposterior sway with eyes closed.

Crowdsourcing innovation intermediaries functions

Open innovation is a hot topic in innovation management. Its basic premise is open up the innovation process. The innovation process, in general sense, may be seen as the process of designing, developing and commercializing a novel product or service to improve the value added of a company. The development of Web 2.0 tools facilitates this kind of contributions, opening space to the emergence of crowdsourcing innovation initiatives. Crowdsourcing is a form of outsourcing not directed to other companies but to the crowd by means of an open call mostly through an Internet platform. Innovation intermediaries, in general sense, are organizations that work to enable innovation, that just act as brokers or agents between two or more parties. Usually, they are also engaged in other activities like inter-organizational networking and technology development and related activities. A crowdsourcing innovation intermediary is an organization that mediates the communication and relationship between the seekers – companies that aspire to solve some problem or to take advantage of any business opportunity – with a crowd that is prone to give ideas based on their knowledge, experience and wisdom. This paper identifies and analyses the functions to be performed by an intermediary of crowdsourcing innovation through grounded theory analyses from literature. The resulting model is presented and explained. The resulting model summarizes eight main functions that can be performed by a crowdsourcing process, namely, diagnoses, mediation, linking knowledge, community, evaluation, project management, intellectual property governance and marketing and support. These functions are associated with a learning cycle process which covers all the crowdsourcing activities that can be realized by the broker.

Manipulation of host cell functions by Salmonella: the role of the bacterial effector protein SteA

Salmonella enterica serovars are Gram-negative facultative intracellular bacterial pathogens that infect a wide variety of animals. Salmonella infections are common in humans, causing usually typhoid fever and gastrointestinal diseases. Salmonella enterica serovar Typhimurium (S. Typhimurium), which is a leading cause of human gastroenteritis, has been extensively used to study the molecular pathogenesis of Salmonella, because of the availability of sophisticated genetic tools, and of suitable animal and tissue culture models mimicking different aspects of Salmonella infections.(...)