Avoiding negative information as a strategy for emotion regulation

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The Vector Population Monitoring Tool (VPMT): High-Throughput DNA-Based Diagnostics for the Monitoring of Mosquito Vector Populations

Regular monitoring of mosquito vector populations is an integral component of most vector control programmes. Contemporary data on mosquito species composition, infection status, and resistance to insecticides are a prerequisite for effective intervention. For this purpose we, with funding from the Innovative Vector Control Consortium (IVCC), have developed a suite of high-throughput assays based on a single “closed-tube” platform that collectively comprise the “Vector Population Monitoring Tool” (VPMT). The VPMT can be used to screen mosquito disease vector populations for a number of traits including Anopheles gambiae s.l. and Anopheles funestus species identification, detection of infection with Plasmodium parasites, and identification of insecticide resistance mechanisms. In this paper we focus on the Anopheles-specific assays that comprise the VPMT and include details of a new assay for resistance todieldrin Rdl detection. The application of these tools, general and specific guidelines on their use based on field testing in Africa, and plans for further development are discussed

Mind the gap: Robotic Mission Planning Meets Software Engineering

In the context of robotic software, the selection of an appropriate planner is one of the most crucial software engineering decisions. Robot planners aim at computing plans (i.e., blueprint of actions) to accomplish a complex mission. While many planners have been proposed in the robotics literature, they are usually evaluated on showcase examples, making hard to understand whether they can be effectively (re)used for realising complex missions, with heterogeneous robots, and in real-world scenarios. In this paper we propose ENFORCE, a framework which allows wrapping FM-based planners into comprehensive software engineering tools, and considers complex robotic missions. ENFORCE relies on (i) realistic maps (e.g, fire escape maps) that describe the environment in which the robots are deployed; (ii) temporal logic for mission specification; and (iii) Uppaal model checker to compute plans that satisfy mission specifications. We evaluated ENFORCE by analyzing how it supports computing plans in real case scenarios, and by evaluating the generated plans in simulated and real environments. The results show that while ENFORCE is adequate for handling single-robot applications, the state explosion still represents a major barrier for reusing existing planners in multi-robot applications

Endoscopic Management of a Primary Duodenal Carcinoid Tumor

Carcinoids are rare, slow-growing tumors originating from a variety of different neuroendocrine cell types. They are identified histologically by their affinity for silver salts and by positive reactions to neuroendocrine markers such as neuron-specific enolase, synaptophysin and chromogranin. They can present with various clinical symptoms and are difficult to diagnose. We present the case of a 43-year-old woman who was referred for evaluation of anemia. Upper endoscopy showed a duodenal bulb mass around 1 cm in size. Histopathological and immunohistochemistry staining were consistent with the diagnosis of a carcinoid tumor. Further imaging and endoscopic studies showed no other synchronous carcinoid lesions. Endoscopic ultrasound (EUS) revealed a 1 cm lesion confined to the mucosa and no local lymphadenopathy. Successful endoscopic mucosal resection of the mass was performed. Follow-up surveillance 6 months later with EUS and Octreoscan revealed no new lesions suggestive of recurrence. No consensus guidelines exist for the endoscopic management of duodenal carcinoid tumors. However, endoscopic resection is safe and preferred for tumors measuring 1 cm or less with no evidence of invasion of the muscularis layer

Biochemical Comparison of Anopheles gambiae and Human NADPH P450 Reductases Reveals Different 2′-5′-ADP and FMN Binding Traits

NADPH-cytochrome P450 oxidoreductase (CPR) plays a central role in chemical detoxification and insecticide resistance in Anopheles gambiae, the major vector for malaria. Anopheles gambiae CPR (AgCPR) was initially expressed in Eschericia coli but failed to bind 2′, 5′-ADP Sepharose. To investigate this unusual trait, we expressed and purified a truncated histidine-tagged version for side-by-side comparisons with human CPR. Close functional similarities were found with respect to the steady state kinetics of cytochrome c reduction, with rates (kcat) of 105 s−1 and 88 s−1, respectively, for mosquito and human CPR. However, the inhibitory effects of 2′,5′-ADP on activity were different; the IC50 value of AgCPR for 2′, 5′ –ADP was significantly higher (6–10 fold) than human CPR (hCPR) in both phosphate and phosphate-free buffer, indicative of a decrease in affinity for 2′, 5′- ADP. This was confirmed by isothermal titration calorimetry where binding of 2′,5′-ADP to AgCPR (Kd = 410±18 nM) was ∼10 fold weaker than human CPR (Kd = 38 nM). Characterisation of the individual AgFMN binding domain revealed much weaker binding of FMN (Kd = 83±2.0 nM) than the equivalent human domain (Kd = 23±0.9 nM). Furthermore, AgCPR was an order of magnitude more sensitive than hCPR to the reductase inhibitor diphenyliodonium chloride (IC50 = 28 µM±2 and 361±31 µM respectively). Taken together, these results reveal unusual biochemical differences between mosquito CPR and the human form in the binding of small molecules that may aid the development of ‘smart’ insecticides and synergists that selectively target mosquito CPR

An empirical analysis of the determinants of mobile instant messaging appropriation in university learning

Published ArticleResearch on technology adoption often profiles device usability (such as perceived usefulness) and user dispositions (such as perceived ease of use) as the prime determinants of effective technology adoption. Since any process of technology adoption cannot be conceived out of its situated contexts, this paper argues that any pre-occupation with technology acceptance from the perspective of device usability and user dispositions potentially negates enabling contexts that make successful adoption a reality. Contributing to contemporary debates on technology adoption, this study presents flexible mobile learning contexts comprising cost (device cost and communication cost), device capabilities (portability, collaborative capabilities), and learner traits (learner control) as antecedents that enable the sustainable uptake of emerging technologies. To explore the acceptance and capacity of mobile instant messaging systems to improve student performance, the study draws on these antecedents, develops a factor model and empirically tests it on tertiary students at a South African University of Technology. The study involved 223 national diploma and bachelor’s degree students and employed partial least squares for statistical analysis. Overall, the proposed model displayed a good fit with the data and rendered satisfactory explanatory power for students’ acceptance of mobile learning. Findings suggest that device portability, communication cost, collaborative capabilities of device and learner control are the main drivers of flexible learning in mobile environments. Flexible learning context facilitated by learner control was found to have a positive influence on attitude towards mobile learning and exhibited the highest path coefficient of the overall model. The study implication is that educators need to create varied learning opportunities that leverage learner control of learning in mobile learning systems to enhance flexible mobile learning. The study also confirmed the statistical significance of the original Technology Acceptance Model constructs

3D Volume Reconstruction by Serially Acquired 2D Slices Using a Distance Transform-Based Global Cost Function

Abstract. An accurate, computationally eÆcient and fully-automated algorithm for the alignment of 2D serially acquired sections forming a 3D volume is presented. The method accounts for the main shortcomings of 3D image alignment: corrupted data (cuts and tears), dissimilarities or discontinuities between slices, missing slices. The approach relies on the optimization of a global energy function, based on the object shape, measuring the similarity between a slice and its neighborhood in the 3D volume. Slice similarity is computed using the distance transform measure in both directions. No particular direction is privileged in the method avoiding global osets, biases in the estimation and error prop-agation. The method was evaluated on real images (medical, biological and other CT scanned 3D data) and the experimental results demon-strated the method's accuracy as reconstuction errors are less than 1 degree in rotation and less than 1 pixel in translation.