Bradykinin increases the proportion of neonatal rat dorsal root ganglion neurons that respond to capsaicin and protons

A number of studies have examined bradykinin-induced sensitization of primary afferent neurons to mechanical or thermal stimuli. However, bradykinin-induced sensitization to other chemical stimuli has not been systematically addressed. We used primary cultures of dorsal root ganglion neurons from neonatal rats to determine whether bradykinin alters the responsiveness of individual neurons to capsaicin and protons. An increase in the concentration of free intracellular Ca2+ was used as a measure of a response to capsaicin or low pH. Pretreatment with bradykinin (30 nM) increased the proportion of "intermediate-size" (240-320 microm2) dorsal root ganglion neurons that responded to capsaicin (100 nM) or low pH (6.1). However, among "small-size" (160-239 microm2) neurons, bradykinin increased the proportion of neurons that responded to low pH (6.1) but not to capsaicin (10 or 100 nM). Because treatment with arachidonic acid (10 microM) did not mimic the effect of bradykinin and inhibition of cyclo-oxygenase and lipoxygenase with 5,8,11,14-eicosatetraynoic acid (10 microM) did not inhibit the effect of bradykinin on the response to capsaicin, it is not likely that the bradykinin-induced enhancement of neuronal responsiveness is mediated by arachidonic acid or its metabolites in this model. These results support the hypothesis that bradykinin sensitizes primary afferent neurons to other chemicals such as protons that are present in inflamed tissue, particularly by recruiting additional sensory neurons to respond to a given chemical stimulus. An increase in the number of responsive nociceptors that innervate inflamed tissue would contribute to hyperalgesia via spatial summation on spinal neurons in the pathway for pain. Furthermore, since bradykinin enhanced the responsiveness of small-size neurons that responded to protons but not to capsaicin, these data suggest that bradykinin-induced sensitization to protons and capsaicin occur by different mechanisms.     

Attitude towards aggression and creative functioning in patients with breast cancer

Three projective personality tests were used to assess attitude to aggression (The Identification Test), anxiety and defenses (The Meta-Contrast Technique) and creative functioning (The Creative Functioning Test) in 70 patients with breast cancer. Discriminant analyses were applied pro primo to characterize psychologically patients with a better prognosis and patients with a poorer prognosis. A second aim was to characterize psychologically older (postmenopausal) and younger (premenopausal) women. Generally, high scores on the Identification Test indicated maladaptive attitudes towards aggression among all the patients. Patients with a poorer prognosis showed responses that in healthy subjects indicate acknowledgement of aggressive impulses, perhaps suggesting lack of "defenses" against such impulses among those patients. Another way to describe it would be that patients with a better prognosis seem to have (normally nonadaptive) "defenses" against aggressive impulses while those with poorer prognosis have not. Surprisingly, the patients with a better prognosis (but not those with a poorer prognosis) gave responses classified as depression in the Meta-Contrast Technique. Typical of premenopausal patients were responses classified as anxiety as well as reaction formation on the Identification Test. Responses classified as adaptive defenses (isolation) were seen in the Meta-Contrast Technique. A surprising finding was that many of these patients were characterized by high scores on the creativity test. These original statistically significant findings of attitudes towards aggression and creative functioning in breast cancer patients are discussed in relation to the underlying nature of aggression and creativity.     

Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach

Herbaceous aquatic macrophytes cover extensive areas on the floodplains of the Amazon basin and are an important habitat and input of organic carbon. These communities have large intra- and inter-annual variability, and characterization of this variability is necessary to quantify the role of macrophytes in the ecology and biogeochemistry of the floodplain. A novel approach for mapping the temporal evolution of aquatic vegetation in the Amazon floodplain, which could be adapted to other spatially and temporally changing environments, is presented. Macrophyte cover varied seasonally and inter-annually, ranging between 104 and 198 km² for the floodplain examined (total area, 984 km²). The observed evolution of plant distribution indicated a spatial and temporal partition of macrophyte communities into short-lived and annual groups. A simulation of macrophyte net primary production (NPP) based on the mapping results indicated that at least 3% of NPP could be attributed to the short-lived communities. The present results suggest that significant changes in the macrophyte's contribution to carbon cycling in the Amazon floodplain could occur as a result of the predicted increase in frequency of drought years for the Amazon system due to climate change.     

Numerical study of the mixture formation process in a four-stroke GDI engine for two-wheel applications

Guidelines for managing the mixture formation process in a high-performance four-stroke Gasoline Direct Injection (GDI) engine for two-wheel applications are discussed, as derived from a multidimensional modelling of the in-cylinder processes. Gasoline adduction from a multi-hole injector is simulated by resorting to a properly developed model that accounts for the dependence of the initial droplets size distribution upon injection pressure. The model portability is preliminary demonstrated by comparison with experimental measurements carried out on sprays entering a confined vessel at controlled conditions.The simulation of different engine operating conditions highlights the capability to work under the so-called “mixed mode” boosting with spray guided mixture formation.     

A web-based formative assessment tool for Masters students: A pilot study

The use of web-based learning and assessment tools is growing in tertiary institutions around the world. To date, very few papers have reported the development and evaluation of a web-based formative assessment tool for postgraduate students. The aim of the present paper was to report on the development and evaluation of an online formative assessment tool for this student group. The web-based formative assessment tool was evaluated by a sample of undergraduate students, postgraduate students and academic staff within a psychology department in order to determine the suitability and sensitivity of the tool. The results of this pilot test suggest that the development of such a tool is both appropriate and feasible for Masters students studying psychology.     

A computational model for developing semantic web-based educational systems

Recently, some initiatives to start the so-called semantic web-based educational systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.     

Skill Memory in Biped Locomotion

Robots must be able to adapt their motor behavior to unexpected situations in order to safely move among humans. A necessary step is to be able to predict failures, which result in behavior abnormalities and may cause irrecoverable damage to the robot and its surroundings, i.e. humans. In this paper we build a predictive model of sensor traces that enables early failure detection by means of a skill memory. Specifically, we propose an architecture based on a biped locomotion solution with improved robustness due to sensory feedback, and extend the concept of Associative Skill Memories (ASM) to periodic movements by introducing several mechanisms into the training workflow, such as linear interpolation and regression into a Dynamical Motion Primitive (DMP) system such that representation becomes time invariant and easily parameterizable. The failure detection mechanism applies statistical tests to determine the optimal operating conditions. Both training and failure testing were conducted on a DARwIn-OP inside a simulation environment to assess and validate the failure detection system proposed. Results show that the system performance in terms of the compromise between sensitivity and specificity is similar with and without the proposed mechanism, while achieving a significant data size reduction due to the periodic approach taken.     

Relational Learning with GPUs: Accelerating Rule Coverage

Relational learning algorithms mine complex databases for interesting patterns. Usually, the search space of patterns grows very quickly with the increase in data size, making it impractical to solve important problems. In this work we present the design of a relational learning system, that takes advantage of graphics processing units (GPUs) to perform the most time consuming function of the learner, rule coverage. To evaluate performance, we use four applications: a widely used relational learning benchmark for predicting carcinogenesis in rodents, an application in chemo-informatics, an application in opinion mining, and an application in mining health record data. We compare results using a single and multiple CPUs in a multicore host and using the GPU version. Results show that the GPU version of the learner is up to eight times faster than the best CPU version.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

Visually impaired people and the emerging connected TV: a comparative study of TV and Web applications’ accessibility

With the TV signal digitization and the current market growth of connected TVs, the authors envision the appearance of accessibility barriers to visually impaired persons. The paper addresses the following hypothesis: (1) visually impaired users want to extend their TV usage to explore new TV features; (2) TV applications are in less conformance with accessibility guidelines compared to their Desktop versions. Additionally, the authors wanted to assess whether guideline conformance reflected real TV accessibility problems experienced by users. The methods used for this study included surveys aimed at characterizing the interest of the visually impaired population regarding the use of TV, and specifically of Web applications on TV, an automated accessibility evaluation to compare TV and Desktop versions of the same Web application, to understand their conformance with accessibility guidelines, and a user study where participants with visual impairments were asked to perform some tasks on both versions. From the survey, we confirmed that people with visual disabilities are interested in extra features on their TV. Results from the automated accessibility evaluation show that TV applications are in a significantly better level of conformance with accessibility guidelines. The user study has illustrated that users were unable to complete any task using the TV versions of the applications. The results from these studies demonstrated that the new features that come with connected TVs still have a long way to go in order to be accessible by all. Furthermore, they lead us to concur with other works that automated evaluations are not enough to assess the accessibility of a Web page.