Improving Trust in Deep Neural Networks with Nearest Neighbors

Deep neural networks are used increasingly for perception and decision-making in UAVs. For example, they can be used to recognize objects from images and decide what actions the vehicle should take. While deep neural networks can perform very well at complex tasks, their decisions may be unintuitive to a human operator. When a human disagrees with a neural network prediction, due to the black box nature of deep neural networks, it can be unclear whether the system knows something the human does not or whether the system is malfunctioning. This uncertainty is problematic when it comes to ensuring safety. As a result, it is important to develop technologies for explaining neural network decisions for trust and safety. This paper explores a modification to the deep neural network classification layer to produce both a predicted label and an explanation to support its prediction. Specifically, at test time, we replace the final output layer of the neural network classifier by a k-nearest neighbor classifier. The nearest neighbor classifier produces 1) a predicted label through voting and 2) the nearest neighbors involved in the prediction, which represent the most similar examples from the training dataset. Because prediction and explanation are derived from the same underlying process, this approach guarantees that the explanations are always relevant to the predictions. We demonstrate the approach on a convolutional neural network for a UAV image classification task. We perform experiments using a forest trail image dataset and show empirically that the hybrid classifier can produce intuitive explanations without loss of predictive performance compared to the original neural network. We also show how the approach can be used to help identify potential issues in the network and training process

Evaluation of bast fibre retting systems on hemp

In this paper the effect of eight different retting methods on decorticated hemp skins were analyzed. The methods were taken from six publications that looked at the retting of different bast fibres such as ramie, flax and kenaf. The fibres were batch retted in a package dye-vat at 100oC under 2 bar of pressure. The rinsed fibres were opened twice using a Shirley cotton trash separator. The opened fibre was assessed for fibre width, fibre width variation, colour and handle. It was found that the fibre that had undergone chemical retting with 7% Sodium Hydroxide (NaOH) and 0.5% Sodium Sulphite (Na2SO3) had the best diameter (18.39 micron) and the best coefficient of variation of diameter (57.32%). The fibre that was processed with 7% Sodium Hydroxide (NaOH) and 0.5% Sodium Sulphite (Na2SO3) had the whitest colour (YI D1925 = 31.61). The method treated with 1% Sodium Hydroxide (NaOH) and 1% Sodium Sulphite (Na2SO3) had the softest handle and the method treated with 1% Sodium Hydroxide (NaOH) and pre-rinsed with 0.3% Hydrochloric Acid (HCl) showed the best conversion of decorticated skins into spin able fibre (33.9% of dry green skins). It was decided that method treated with 1% Sodium Hydroxide (NaOH) and pre-rinsed with 0.3% Hydrochloric Acid (HCl) had the best fineness of fibre micron, conversion to spin able fibre (33.9% of dry green skins), whitest colour (YI D1925 = 36.13) and softest handle for the cost of chemicals involved.<br /

Phenotypic and transcriptomic acclimation of the green microalga Raphidocelis subcapitata to high environmental levels of the herbicide diflufenican

Herbicide pollution poses a worldwide threat to plants and freshwater ecosystems. However, the understanding of how organisms develop tolerance to these chemicals and the associated trade-off expenses are largely unknown. This study aims to investigate the physiological and transcriptional mechanisms underlying the acclimation of the green microalgal model species Raphidocelis subcapitata (Selenastraceae) towards the herbicide diflufenican, and the fitness costs associated with tolerance development. Algae were exposed for 12 weeks (corresponding to 100 generations) to diflufenican at the two environmental concentrations 10 and 310 ng/L. The monitoring of growth, pigment composition, and photosynthetic performance throughout the experiment revealed an initial dose-dependent stress phase (week 1) with an EC50 of 397 ng/L, followed by a time-dependent recovery phase during weeks 2 to 4. After week 4, R. subcapitata was acclimated to diflufenican exposure with a similar growth rate, content of carotenoids, and photosynthetic performance as the unexposed control algae. This acclimation state of the algae was explored in terms of tolerance acquisition, changes in the fatty acids composition, diflufenican removal rate, cell size, and changes in mRNA gene expression profile, revealing potential fitness costs associated with acclimation, such as up-regulation of genes related to cell division, structure, morphology, and reduction of cell size. Overall, this study demonstrates that R. subcapitata can quickly acclimate to environmental but toxic levels of diflufenican; however, the acclimation is associated with trade-off expenses that result in smaller cell size

Sub-Sets of Cancer Stem Cells Differ Intrinsically in Their Patterns of Oxygen Metabolism

PMCID: PMC3640080This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Safety and Immunogenicity of Malaria Vectored Vaccines Given with Routine Expanded Program on Immunization Vaccines in Gambian Infants and Neonates: A Randomized Controlled Trial.

BACKGROUND: Heterologous prime-boost vaccination with chimpanzee adenovirus 63 (ChAd63) and modified vaccinia virus Ankara (MVA) encoding multiple epitope string thrombospondin-related adhesion protein (ME-TRAP) has shown acceptable safety and promising immunogenicity in African adult and pediatric populations. If licensed, this vaccine could be given to infants receiving routine childhood immunizations. We therefore evaluated responses to ChAd63 MVA ME-TRAP when co-administered with routine Expanded Program on Immunization (EPI) vaccines. METHODS: We enrolled 65 Gambian infants and neonates, aged 16, 8, or 1 week at first vaccination and randomized them to receive either ME-TRAP and EPI vaccines or EPI vaccines only. Safety was assessed by the description of vaccine-related adverse events (AEs). Immunogenicity was evaluated using IFNγ enzyme-linked immunospot, whole-blood flow cytometry, and anti-TRAP IgG ELISA. Serology was performed to confirm all infants achieved protective titers to EPI vaccines. RESULTS: The vaccines were well tolerated in all age groups with no vaccine-related serious AEs. High-level TRAP-specific IgG and T cell responses were generated after boosting with MVA. CD8+ T cell responses, previously found to correlate with protection, were induced in all groups. Antibody responses to EPI vaccines were not altered significantly. CONCLUSION: Malaria vectored prime-boost vaccines co-administered with routine childhood immunizations were well tolerated. Potent humoral and cellular immunity induced by ChAd63 MVA ME-TRAP did not reduce the immunogenicity of co-administered EPI vaccines, supporting further evaluation of this regimen in infant populations. CLINICAL TRIAL REGISTRATION: The clinical trial was registered on http://Clinicaltrials.gov (NCT02083887) and the Pan-African Clinical Trials Registry (PACTR201402000749217)