Improving light harvesting in polymer photodetector devices through nanoindented metal mask films

To enhance light harvesting in organic photovoltaic devices, we propose the incorporation of a metal (aluminum) mask film in the system’s usual layout. We fabricate devices in a sandwich geometry, where the mask (nanoindented with a periodic array of holes of sizes d and spacing s) is added between the transparent electrode and the active layer formed by a blend of the semiconducting polymer P3HT and substituted fullerene. Its function is to promote trapping of the incident light into the device’s cavity (the region corresponding to the active layer). For d, we set a value that allows light diffraction through the holes in the relevant absorption range of the polymer. To optimize the mask structure, we consider a very simple model to determine the s leading to trapped fields that are relatively intense and homogeneous within the device. From measurements of the action spectra, we show that, indeed, such architecture can considerably improve the resulting photocurrent efficiencies—one order of magnitude in the best situation studied.

The status of Fusarium mycotoxins in Sub-Saharan Africa : a review of emerging trends and post-harvest mitigation strategies towards food control

Fusarium fungi are common plant pathogens causing several plant diseases. The presence of these molds in plants exposes crops to toxic secondary metabolites called Fusarium mycotoxins. The most studied Fusarium mycotoxins include fumonisins, zearalenone, and trichothecenes. Studies have highlighted the economic impact of mycotoxins produced by Fusarium. These arrays of toxins have been implicated as the causal agents of wide varieties of toxic health effects in humans and animals ranging from acute to chronic. Global surveillance of Fusarium mycotoxins has recorded significant progress in its control; however, little attention has been paid to Fusarium mycotoxins in sub-Saharan Africa, thus translating to limited occurrence data. In addition, legislative regulation is virtually non-existent. The emergence of modified Fusarium mycotoxins, which may contribute to additional toxic effects, worsens an already precarious situation. This review highlights the status of Fusarium mycotoxins in sub-Saharan Africa, the possible food processing mitigation strategies, as well as future perspectives

Temporal effects of organic farming on biodiversity and ecosystem services

Agricultural intensification has caused a dramatic decline of global biodiversity and associated ecosystem services. Organic farming has been shown to partially counteract agricultural intensification by applying environmentally friendly and resource efficient farming practices, but opportunities to improve in efficiency still remain. This thesis investigates the contribution of organic farming to biodiversity and ecosystem services with focus on the effect of the time since transition (TST) to organic farming methods. Surveys on butterflies, plants, moths, carabid beetles and an experimental study on weed seed predation were performed on conventional and organic farms situated in landscapes differing in landscape complexity. The organic farms had been under organic management between 1 and 25 years before surveys. This design allowed for analyzes of the effect of organic farming while accounting for the time since transition and landscape composition. The overall effect of organic farming was small. Only butterflies and plants (in one out of two studies) had higher species richness and abundance on organic compared to conventional farms. However, analyses of the time since transition to organic farming revealed novel facts: butterfly abundance increased gradually by 100% over 25 years, whereas butterfly and plant species richness increased rapidly at the transition and then remained fairly constant. The moths that initially did not appear to increase in the organic farming system showed a clear positive response to newly transitioned farms (TST≤6 years), whereas conventional and old organic farms (TST≥15 years) had similar diversity. Two plant species occurred more frequently on new organic farms and two species on old organic farms. Neither carabids nor seed predation showed any temporal responses to organic farming. This thesis shows that explicitly addressing temporal effects of organic farming may result in novel and unexpected findings. Control for temporal effects opens up for better understanding of the complexities between organic farming, biodiversity and ecosystem services over time. Future evaluations need to address this factor for high credibility and usefulness in the development of improved policies for organic farming

Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

A robot that can carry out a natural-language instruction has been a dream since before the Jetsons cartoon series imagined a life of leisure mediated by a fleet of attentive robot helpers. It is a dream that remains stubbornly distant. However, recent advances in vision and language methods have made incredible progress in closely related areas. This is significant because a robot interpreting a natural-language navigation instruction on the basis of what it sees is carrying out a vision and language process that is similar to Visual Question Answering. Both tasks can be interpreted as visually grounded sequence-to-sequence translation problems, and many of the same methods are applicable. To enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, we present the Matterport3D Simulator -- a large-scale reinforcement learning environment based on real imagery. Using this simulator, which can in future support a range of embodied vision and language tasks, we provide the first benchmark dataset for visually-grounded natural language navigation in real buildings -- the Room-to-Room (R2R) dataset.Comment: CVPR 2018 Spotlight presentatio

Modeling the natural gas supply chain for sustainable growth policy

Natural gas has been used globally as a transitional fuel for supporting a green-energy-supply strategy, which has been questioned for the intermittence and lack of reliability of renewables. This paper proposes a System Dynamics model for assessing alternative security of supply policy along the natural gas value chain. The model incorporates demand, transport, production and reserves of natural gas variables according to a systemic perspective. It also includes a module for evaluating the effect of natural gas price on the demand and supply levels, respectively. Alternative supply policies are evaluated under different scenarios. The chosen case-study focuses on the Colombian natural gas industry with the purpose of assessing how the impact of public policies affect supply and demand. Particularly, policies consider the allocation of resources along the natural gas supply chain, seeking to promote the development of infrastructure oriented to mitigate the risk of provision shortages

Local and systemic biomarkers in gingival crevicular fluid increase odds of periodontitis

AimTo determine the independent and combined associations of interleukin-1beta (IL-1beta) and C-reactive protein (CRP) in gingival crevicular fluid (GCF) on periodontitis case status in the Australian population.Materials and methodsGCF was collected from 939 subjects selected from the 2004-2006 Australian National Survey of Adult Oral Health: 430 cases had examiner-diagnosed periodontitis, and 509 controls did not. IL-1beta and CRP in GCF were detected by enzyme-linked immunosorbent assays. Odds ratios (OR) and 95% confidence intervals (CIs) were calculated in bivariate and stratified analysis and fully adjusted ORs were estimated using multivariate logistic regression.ResultsGreater odds of having periodontitis was associated with higher amounts of IL-1beta (OR=2.4, 95% CI=1.7-3.4 for highest tertile of IL-1beta relative to lowest tertile) and CRP (OR=1.9, 95% CI=1.5-2.5 for detectable CRP relative to undetectable CRP). In stratified analysis, there was no significant interaction between biomarkers (p=0.68). In the multivariate analyses that controlled for conventional periodontal risk factors, these relationships remained (IL-1beta OR=1.8, 95% CI=1.1-2.6; CRP OR=1.7, 95% CI=1.3-2.3).ConclusionsElevated odds of clinical periodontitis was associated independently with each biomarker. This suggests that people with elevated biomarkers indicative of either local (IL-1beta) or systemic (CRP) inflammation are more likely to suffer from periodontal disease.Tracy R. Fitzsimmons, Anne E. Sanders, P. Mark Bartold and Gary D. Slad

Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer

An important goal of research in Deep Reinforcement Learning in mobile robotics is to train agents capable of solving complex tasks, which require a high level of scene understanding and reasoning from an egocentric perspective. When trained from simulations, optimal environments should satisfy a currently unobtainable combination of high-fidelity photographic observations, massive amounts of different environment configurations and fast simulation speeds. In this paper we argue that research on training agents capable of complex reasoning can be simplified by decoupling from the requirement of high fidelity photographic observations. We present a suite of tasks requiring complex reasoning and exploration in continuous, partially observable 3D environments. The objective is to provide challenging scenarios and a robust baseline agent architecture that can be trained on mid-range consumer hardware in under 24h. Our scenarios combine two key advantages: (i) they are based on a simple but highly efficient 3D environment (ViZDoom) which allows high speed simulation (12000fps); (ii) the scenarios provide the user with a range of difficulty settings, in order to identify the limitations of current state of the art algorithms and network architectures. We aim to increase accessibility to the field of Deep-RL by providing baselines for challenging scenarios where new ideas can be iterated on quickly. We argue that the community should be able to address challenging problems in reasoning of mobile agents without the need for a large compute infrastructure

Investigation of High-Level Language Support in a Resource-Constrained Embedded Environment

Personal computers have gained a significant boost in computational power and digital storage space at a reduced cost in the last decade. In the search of increased programmer productivity and cross platform portability, language popularity has shifted from lower level languages such as C to higher level languages such as Java and C#. Many of today’s embedded systems are experiencing the same development as the personal computers did. However, most companies dealing with embedded devices still use C. We investigated what effect a shift like this would have at Axis Communications. The study was done by setting up C# and Java on a camera and conducting performance tests on it. The analysis showed that when using C# as a replacement for C, we saw improvements in programmer productivity whilst still upholding performance for some applications. For the most performance intense use cases, the performance requirements were not satisfied. With the growth of high-level languages, we do see a bright future for the support for them in embedded systems