Implementation of fractional-order electromagnetic potential through a genetic algorithm

Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

Filtering method in backlash phenomena analysis

The behavior of robotic manipulators with backlash is analyzed. Based on the pseudo-phase plane two indices are proposed to evaluate the backlash effect upon the robotic system: the root mean square error and the fractal dimension. For the dynamical analysis the noisy signals captured from the system are filtered through wavelets. Several tests are developed that demonstrate the coherence of the results.

Adherend thickness effect on the tensile fracture toughness of a structural adhesive using an optical data acquisition method

Adhesive bonding is nowadays a serious candidate to replace methods such as fastening or riveting, because of attractive mechanical properties. As a result, adhesives are being increasingly used in industries such as the automotive, aerospace and construction. Thus, it is highly important to predict the strength of bonded joints to assess the feasibility of joining during the fabrication process of components (e.g. due to complex geometries) or for repairing purposes. This work studies the tensile behaviour of adhesive joints between aluminium adherends considering different values of adherend thickness (h) and the double-cantilever beam (DCB) test. The experimental work consists of the definition of the tensile fracture toughness (GIC) for the different joint configurations. A conventional fracture characterization method was used, together with a J-integral approach, that take into account the plasticity effects occurring in the adhesive layer. An optical measurement method is used for the evaluation of crack tip opening and adherends rotation at the crack tip during the test, supported by a Matlab® sub-routine for the automated extraction of these quantities. As output of this work, a comparative evaluation between bonded systems with different values of adherend thickness is carried out and complete fracture data is provided in tension for the subsequent strength prediction of joints with identical conditions.

Efeito da velocidade média nos parâmetros espaciotemporais, angulares e de pressão plantar durante a marcha em indivíduos com meniscopatia

Introdução: A velocidade da marcha quando analisada, conjuntamente com outras variáveis, permite-nos uma melhor compreensão acerca da natureza dos défices e como direcionar o tratamento. Objectivo(s): avaliar a associação da velocidade média da marcha com as variáveis espaciotemporais, angulares e de distribuição das pressões plantares em indivíduos com lesão meniscal há 4 anos, utilizando o membro não lesado como controlo. Métodos: estudo realizado em dez participantes com lesão meniscal (idade 35,3 ± 10,63 anos, altura 170,0 ± 0,09 cm, massa 67,5 ± 7,22 kg) avaliados em 3 ciclos de marcha a uma velocidade auto-selecionada. A quantificação das variáveis foi calculada através do programa Ariel Performance Analysis System e pelo Pedar System. As imagens foram editadas, digitalizadas, transformadas e suavizadas com um filtro digital com uma frequência de corte de 6HZ. Para estimar a associação das variáveis foram efetuados modelos de regressão linear e apresentados os coeficiente de regressão (β) e os respetivos intervalos de confiança (IC95%). Resultados: Foi possível verificar que a velocidade está significativa e positivamente associada aos parâmetros temporais das fases oscilantes (βML=0,044; IC95%:0,015;0,073; βMNL=0,061; IC95%:0,037;0,086), oscilação inicial (βML=0,055; IC95%:0,006;0,105; βMNL=0,091; IC95%:0,011;0,170) e cadência (βML=0,016; IC95%:0,009;0,023; βMNL=0,011; IC95%:0,006;0,017), em ambos os membros, e aos parâmetros temporais das fases de apoio unilateral (βML=0,046; IC95%:0,019;0,07), oscilação terminal (βML=0,081; IC95%:0,003;0,159) e apoio médio (βML=0,046; IC95%:0,008;0,085), apenas no membro lesado. Foi também observada, em ambos os membros, a existência de associações negativas significativas com os parâmetros temporais das fases de duplo apoio (βML=-0,024; IC95%:-0,037;-0,011; βMNL=-0,032; IC95%:-0,048;-0,015), apoio (βML=-0,044; IC95%:-0,073;-0,015; βMNL=-0,061; IC95%:-0,086;-0,037), resposta de carga (βML=-0,029; IC95%:-0,055;-0,004; βMNL=-0,047; IC95%:-0,081;-0,013), pré-oscilação (βML=-0,047; IC95%:-0,082;-0,013; βMNL=-0,060; IC95%:-0,098;-0,023) e tempo do ciclo de marcha (βML=-1,435; IC95%:-2,090;-0,781; βMNL=-0,941; IC95%:-1,431;-0,451). Foi ainda identificada, no membro lesado, uma associação positiva com a pressão plantar máxima normalizada durante o contacto do calcanhar terminal (βML=0,612; IC95%:0,077;1,147) e com o passo normalizado (βML=2,413; IC95%:0,264;4,561) e uma associação negativa limítrofe com a amplitude de flexão do joelho durante a elevação da ponta dos dedos (βML=-0,031; IC95%:-0,061;0,000). Conclusão: A velocidade média da marcha parece influenciar bastante os parâmetros temporais, sem provocar grandes alterações nos parâmetros espaciais, angulares e de pressão plantar, sendo esta associação semelhante em ambos os membros e independente do local da lesão.

An Exercise Program Improves Health-Related Quality of Life of Workers

Low back problems are associated with decreased quality of life. Specific exercises can improve quality of life, resulting in better professional performance and functionality. The purpose of this study was to evaluate the effect of following a 21-month exercise program on the quality of life of warehouse workers. The population included 557 male warehouse workers from a food distribution company in Oporto, Portugal. Upon application of the selection criteria, 249 workers were deemed eligible, which were randomized into two groups (125 in the intervention group and 124 in the control group). Then, subjects were asked to volunteer for the study, the sample being formed by 229 workers (112 in the intervention group and 117 in the control group). All subjects completed the SF-36 questionnaire prior to beginning the program and on the 11th and 21st months following it. The exercises were executed in the company facilities once a day for 8 min. Data were analyzed using SPSS® 17.0 for Windows®. After 11 months of following the exercise program, there was an increase in all scores for the experimental group, with statistically significant differences in the dimensions physical functioning (0.019), bodily pain (0.010), general health (0.004), and rolephysical (0.037). The results obtained at the end of the study (21 months) showed significant improvements in the dimensions physical functioning (p = 0.002), rolephysical (p = 0.007), bodily pain (p = 0.001), social functioning (p = 0.015), role-emotional (p = 0.011), and mental health (p = 0.001). In the control group all dimensions showed a decrease in mean scores. It can be concluded that the implementation of a low back specific exercise program has changed positively the quality of life of warehouse workers.

MicroRNA-375 plays a dual role in prostate carcinogenesis

Background: Prostate cancer (PCa), a highly incident and heterogeneous malignancy, mostly affects men from developed countries. Increased knowledge of the biological mechanisms underlying PCa onset and progression are critical for improved clinical management. MicroRNAs (miRNAs) deregulation is common in human cancers, and understanding how it impacts in PCa is of major importance. MiRNAs are mostly downregulated in cancer, although some are overexpressed, playing a critical role in tumor initiation and progression. We aimed to identify miRNAs overexpressed in PCa and subsequently determine its impact in tumorigenesis. Results: MicroRNA expression profiling in primary PCa and morphological normal prostate (MNPT) tissues identified 17 miRNAs significantly overexpressed in PCa. Expression of three miRNAs, not previously associated with PCa, was subsequently assessed in large independent sets of primary tumors, in which miR-182 and miR-375 were validated, but not miR-32. Significantly higher expression levels of miR-375 were depicted in patients with higher Gleason score and more advanced pathological stage, as well as with regional lymph nodes metastases. Forced expression of miR-375 in PC-3 cells, which display the lowest miR-375 levels among PCa cell lines, increased apoptosis and reduced invasion ability and cell viability. Intriguingly, in 22Rv1 cells, which displayed the highest miR-375 expression, knockdown experiments also attenuated the malignant phenotype. Gene ontology analysis implicated miR-375 in several key pathways deregulated in PCa, including cell cycle and cell differentiation. Moreover, CCND2 was identified as putative miR-375 target in PCa, confirmed by luciferase assay. Conclusions: A dual role for miR-375 in prostate cancer progression is suggested, highlighting the importance of cellular context on microRNA targeting.

Evaluation of ultrasound, ultrasonophoresis and homeopathic mesotherapy on Cellulite treatment

Introduction: Cellulite is a complex architectural disorder with multifactorial etiologies that is prevalent in 98% of the women (1). Nowadays several aesthetic treatments are being used: surgical, cosmetic, physical, mechanical, and thermal. (2) Most treatments lack a substantial proof of efficacy. Objective: The purpose of this study was to test and evaluate the efficacy of Ultrasound, Homeopathic Ultrasonophoresis, and Homeopathic Mesotherapy versus control in cellulite in a population of women from ESTSP. Methods: Female volunteers (n=23), Caucasian, aged between 18-31 years, with BMI 19-27 kg/m2 with clinical cellulite gradation on the Cellulite Grading Scale of 1 to 4 were included in a control controlled study. Subjects were assigned in four different groups: Group I (Control, n=6), Group II (Ultrasound, (n=5), Group III (Homeopathic Ultrasonophoresis, n=6), Group IV (Homeopathic Mesotherapy, n=6). Groups II to IV were treated 3 times per week, for a total of 10 sessions. Cellulite gradation was evaluated at the beginning and the end of the trial by means of clinical photography, using a Canon IXUS 65 (6 mega pixels). For homeopathic treatments Dr. Reckeweg® Rekin® 59, 13 and 42 – Dietmed were used. The rating of perceived pain during Homeopathic Mesotherapy was evaluated by a visual analogic scale (VAS). The equipment Sonopuls 692, Enraf-Nonius was used for Ultrasound and Ultrasonophoresis treatments. Results:The higher number of participants with improvement in cellulite graduation occurred in group II (80%), followed group III (50%) and by group IV (33%). The group in which more changes in cellulite gradation occurred was group II, 20% of the individuals improved their score in 2 points. Results were statistically different between Group I and Group II, p=0,015. During the treatments of homeopathic mesotherapy the pain diminished 1 value in VAS scale. Discussion and Conclusion: Although all the three interventions groups were effective in the improvement of cellulite, as expected from previous works described in the literature, (2) only the ultrasound group was statistically different from control. These preliminary results point to the need of a new study using a higher number of participants and the same methodology.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

A Green Approach for Selfish Misbehavior Detection in 802.11-Based Wireless Networks

IEEE 802.11 is one of the most well-established and widely used standard for wireless LAN. Its Medium Access control (MAC) layer assumes that the devices adhere to the standard’s rules and timers to assure fair access and sharing of the medium. However, wireless cards driver flexibility and configurability make it possible for selfish misbehaving nodes to take advantages over the other well-behaving nodes. The existence of selfish nodes degrades the QoS for the other devices in the network and may increase their energy consumption. In this paper we propose a green solution for selfish misbehavior detection in IEEE 802.11-based wireless networks. The proposed scheme works in two phases: Global phase which detects whether the network contains selfish nodes or not, and Local phase which identifies which node or nodes within the network are selfish. Usually, the network must be frequently examined for selfish nodes during its operation since any node may act selfishly. Our solution is green in the sense that it saves the network resources as it avoids wasting the nodes energy by examining all the individual nodes of being selfish when it is not necessary. The proposed detection algorithm is evaluated using extensive OPNET simulations. The results show that the Global network metric clearly indicates the existence of a selfish node while the Local nodes metric successfully identified the selfish node(s). We also provide mathematical analysis for the selfish misbehaving and derived formulas for the successful channel access probability.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Microcystin-LR detection in water by the Fabry–Pérot interferometer using an optical fibre coated with a sol–gel imprinted sensing membrane

Cyanobacteria deteriorate the water quality and are responsible for emerging outbreaks and epidemics causing harmful diseases in Humans and animals because of their toxins. Microcystin-LR (MCT) is one of the most relevant cyanotoxin, being the most widely studied hepatotoxin. For safety purposes, the World Health Organization recommends a maximum value of 1 μg L−1 of MCT in drinking water. Therefore, there is a great demand for remote and real-time sensing techniques to detect and quantify MCT. In this work a Fabry–Pérot sensing probe based on an optical fibre tip coated with a MCT selective thin film is presented. The membranes were developed by imprinting MCT in a sol–gel matrix that was applied over the tip of the fibre by dip coating. The imprinting effect was obtained by curing the sol–gel membrane, prepared with (3-aminopropyl) trimethoxysilane (APTMS), diphenyl-dimethoxysilane (DPDMS), tetraethoxysilane (TEOS), in the presence of MCT. The imprinting effect was tested by preparing a similar membrane without template. In general, the fibre Fabry–Pérot with a Molecular Imprinted Polymer (MIP) sensor showed low thermal effect, thus avoiding the need of temperature control in field applications. It presented a linear response to MCT concentration within 0.3–1.4 μg L−1 with a sensitivity of −12.4 ± 0.7 nm L μg−1. The corresponding Non-Imprinted Polymer (NIP) displayed linear behaviour for the same MCT concentration range, but with much less sensitivity, of −5.9 ± 0.2 nm L μg−1. The method shows excellent selectivity for MCT against other species co-existing with the analyte in environmental waters. It was successfully applied to the determination of MCT in contaminated samples. The main advantages of the proposed optical sensor include high sensitivity and specificity, low-cost, robustness, easy preparation and preservation.

Nonlinear Dynamics for Local Fractional Burgers Equation Arising in Fractal Flow

The local fractional Burgers’ equation (LFBE) is investigated from the point of view of local fractional conservation laws envisaging a nonlinear local fractional transport equation with a linear non-differentiable diffusion term. The local fractional derivative transformations and the LFBE conversion to a linear local fractional diffusion equation are analyzed.

A Review of Operational Matrices and Spectral Techniques for Fractional Calculus

Recently, operational matrices were adapted for solving several kinds of fractional differential equations (FDEs). The use of numerical techniques in conjunction with operational matrices of some orthogonal polynomials, for the solution of FDEs on finite and infinite intervals, produced highly accurate solutions for such equations. This article discusses spectral techniques based on operational matrices of fractional derivatives and integrals for solving several kinds of linear and nonlinear FDEs. More precisely, we present the operational matrices of fractional derivatives and integrals, for several polynomials on bounded domains, such as the Legendre, Chebyshev, Jacobi and Bernstein polynomials, and we use them with different spectral techniques for solving the aforementioned equations on bounded domains. The operational matrices of fractional derivatives and integrals are also presented for orthogonal Laguerre and modified generalized Laguerre polynomials, and their use with numerical techniques for solving FDEs on a semi-infinite interval is discussed. Several examples are presented to illustrate the numerical and theoretical properties of various spectral techniques for solving FDEs on finite and semi-infinite intervals.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.