Toxicokinetics of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) in the European corn borer,Ostrinia nubilalis (Hübner)

2,4-Dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), the major hydroxamic acid present in corn, and its tritiated derivative, were prepared synthetically for use in the determination of the toxicokinetics of this insect deterrent in the European corn borer (ECB),Ostrinia nubilalis. In growth studies with DIMBOA (0, 0.05, 0.2, and 0.5 mg/g diet), the mean time to pupation and adult emergence were significantly lengthened by an increase in concentration. Pupal and adult weights, for both female and male, decreased with an increase in concentration. Increased larval and pupal mortality occurred at the highest concentration of DIMBOA. DIMBOA, at concentrations of 0.2 and 0.5 mg/g diet, resulted in a decrease in the number of egg masses produced per female, and at 0.5 mg/g diet, in a decrease in the number of eggs per egg mass. Larvae fed from the neonate stage on a diet containing 0.2 mg [³H]- + [¹H]DIMBOA/g diet showed an increase in the content of label from fourth to fifth instar, but levels declined at pupation and emergence. A large amount of the labeled compounds was excreted by the insect in the pupal case. In dose-related studies, both uptake and excretion increased with an increase in concentration of DIMBOA (0.05, 0.2, 0.4 mg/g diet), while a body burden (concentration in the tissues/concentration in the frass) of approximately 0.25 was maintained for all concentrations. At the highest dose of DIMBOA (0.4 mg/g), the ECB increased consumption, possibly to compensate for the toxic effects of the compound. In topical application studies, elimination of the labeled compound in the frass was rapid, reaching 65% by 4 hr and 88% by 48 hr. Accumulation of label in tissues other than hemolymph was low. The results show that the ECB does possess adaptive mechanisms to deal with the effects of this host-derived compound.     

Gripper Design for Radio Base Station Autonomous Maintenance System

For an autonomous system to perform maintenance tasks in a networking device or a radio base station (RBS), it has to deal with a series of technological challenges ranging from identifying hardware-related problems to manipulating connectors. This paper describes the development of a robot maintenance system dedicated to detect and resolve faulty links caused by unplugged or poorly connected cables. Although the maintenance system relies on four subsystems, we significantly focus on our low-cost and efficient custom gripper solution developed to handle RJ45 Ethernet connectors. To examine our gripper, we conducted three experiments. First, a qualitative questionnaire was submitted to 30 users in the case of the teleoperated scenario of the gripper attached to a robotic arm. Similarly, we also tested the automatic operation mode. The results showed that our system is reliable and delivers a highly efficient maintenance tool in both teleoperated and autonomous operation modes. The practical experiment containing the removal or unplugging of connectors demonstrated our gripper’s ability to adequately handle these, whereas the feedback from the questionnaire pointed to a positive user experience. The automatic test assessed the gripper’s robustness against the continuous operation.

     

Time-domain Analysis of Laboratory Experiments on the Transient Pressure Damping in a Leaky Polymeric Pipe

Water Resources Management - The pressure damping occurring in pressurized pipes with a leak during transients has been examined as a diagnostic tool – the so-called transient damping method...     

Evaluation of the removal of n-butanol vapor by the poly(lactic acid)-zeolite-TiO2 composite and formation of by-products

The use of polymeric films incorporated with zeolite-TiO₂ composites associated with UV radiation can be an alternative in the removal of volatile organic compounds (VOCs) through the adsorption and photodegradation processes. This study produced poly(lactic acid) (PLA) films incorporated with 13× zeolite, TiO₂, and 13×-TiO₂ zeolite composite to remove n-butanol and evaluate the by-products generated in the process. The results showed that 13× zeolite and TiO₂ added individually or as a composite to PLA, gave the polymer matrix a significant increase in the removal capacity of n-butanol. The best performance was presented by the zeolite-TiO₂, composite, confirming a synergistic effect. However, the formation of CO and CO₂ exceeded the expected values, with the verification that the polymeric matrix underwent photodegradation action by TiO₂. The polymeric film only containing zeolite is the most suitable for the removal of VOCs, as it did not present degradation of the PLA, generating a lower concentration of by-products.     

Aramid pulp treated with imidazolium ionic liquids as a filler in rigid polyurethane bio-foams

This article reports an aramid pulp (AP) treated with two ionic liquids (IL), namely 1-n-butyl-3-methylimidazolium chloride (C₄.Cl) and 1-carboxymethyl-3-methylimidazolium chloride (HO₂C), and its use as a filler in reinforced rigid polyurethane foams (RPUF). The RPUF were incorporated with the treated AP at three weight fractions (c.a. 0.1, 0.5, and 1.0 wt%) and were produced by the free rising method. The results showed that the studied IL promoted a better interaction between the AP and the RPUF system, which increased the overall reactivity, imparting a higher cell anisotropy. This also yielded a positive effect in mechanical properties and thermal stability of the RPUF. Compared to the neat RPUF, outstanding increases of approximately 50 and 20% were achieved in compressive modulus and strength, respectively. In all, the use of IL promoted increased compatibility between matrix and reinforcement, especially that HO₂C IL.     

A finite volume–finite difference method with a stiff ordinary differential equation solver for advection–diffusion–reaction equation

A model for atmospheric pollutant transport is proposed considering an advection–diffusion–reaction equation. A splitting method is used to decouple the advection, diffusion and reaction parts. A scheme based on finite volume, finite difference and backward differentiation formula is used for solving an atmospheric transport-chemistry problem.     

Predicting teamwork results from social network analysis

Modelling students' behaviours has reached a status that can only be overcome by improving the ability of predicting the results on teamwork. Indeed, teamwork is an important piece on the learning process, but understanding their mechanisms and predicting the results achieved is far from being solved by traditional classifiers. In this paper, we address the problem of predicting teamwork results, and propose a recommender system that suggests new teams, in the context of a given curricular unit. Any student, who is looking for a team, may use the system; in particular, he may ask for the best team to join, either considering all available colleagues or just the set of his previous teammates. Our system makes use of social network analysis and classification methods as the algorithmic core of the decision‐making process. System evaluation is presented through a set of experimental results, which report the performance of social network analysis and classification algorithms over real datasets.     

Towards Smooth Particle Methods Without Smoothing

In this article we present a new class of particle methods which aim at being accurate in the uniform norm with a minimal amount of smoothing. The crux of our approach is to compute local polynomial expansions of the characteristic flow to transport the particle shapes with improved accuracy. In the first order case the method consists of representing the transported density with linearly-transformed particles, the second order version transports quadratically-transformed particles, and so on. For practical purposes we provide discrete versions of the resulting LTP and QTP schemes that only involve pointwise evaluations of the forward characteristic flow, and we propose local indicators for the associated transport error. On a theoretical level we extend these particle schemes up to arbitrary polynomial orders and show by a rigorous analysis that for smooth flows the resulting methods converge in \(L^\infty \) without requiring remappings, extended overlapping or vanishing moments for the particles. Numerical tests using different passive transport problems demonstrate the accuracy of the proposed methods compared to basic particle schemes, and they establish their robustness with respect to the remapping period. In particular, it is shown that QTP particles can be transported without remappings on very long periods of time, without hampering the accuracy of the numerical solutions. Finally, a dynamic criterion is proposed to automatically select the time steps where the particles should be remapped. The strategy is a by-product of our error analysis, and it is validated by numerical experiments.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

Factors influencing the decision to crowdsource: A systematic literature review

Crowdsourcing is currently attracting much attention from organisations for its competitive advantages over traditional work structures regarding how to utilise skills and labour and especially to harvest expertise and innovation. Prior research suggests that the decision to crowdsource cannot simply be based on perceived advantages; rather multiple factors should be considered. However, a structured account and integration of the most important decision factors is still lacking. This research fills the gap by providing a systematic literature review of the decision to crowdsource. Our results identify nine factors and sixteen sub-factors influencing this decision. These factors are structured into a decision framework concerning task, people, management, and environmental factors. Based on this framework, we give several recommendations for managers making the crowdsourcing decision.