3,290 research outputs found

    Everybody Needs Somebody Sometimes: Validation of Adaptive Recovery in Robotic Space Operations

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    This work assesses an adaptive approach to fault recovery in autonomous robotic space operations, which uses indicators of opportunity, such as physiological state measurements and observations of past human assistant performance, to inform future selections. We validated our reinforcement learning approach using data we collected from humans executing simulated mission scenarios. We present a method of structuring humanfactors experiments that permits collection of relevant indicator of opportunity and assigned assistance task performance data, as well as evaluation of our adaptive approach, without requiring large numbers of test subjects. Application of our reinforcement learning algorithm to our experimental data shows that our adaptive assistant selection approach can achieve lower cumulative regret compared to existing non-adaptive baseline approaches when using real human data. Our work has applications beyond space robotics to any application where autonomy failures may occur that require external intervention

    Alcohol Production as an Adaptive Livelihood Strategy for Women Farmers in Tanzania and Its Potential for Unintended Consequences on Women's Reproductive Health.

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    Although women occupy a central position in agriculture in many developing countries, they face numerous constraints to achieving their full potential including unequal access to assets and limited decision-making authority. We explore the intersection of agricultural livelihoods, food and economic security, and women's sexual and reproductive health in Iringa Region, Tanzania. Our goal was to understand whether the benefits of supporting women in the agricultural sector might also extend to more distal outcomes, including sexual and reproductive health. Using the Sustainable Livelihoods Framework to guide data collection, we conducted 13 focus group discussions (FGD) with female (n = 11) and male farmers (n = 2) and 20 in-depth interviews with agricultural extension officers (n = 10) and village agro-dealers (n = 10). Despite providing the majority of agricultural labor, women have limited control over land and earned income and have little bargaining power. In response to these constraints, women adopt adaptive livelihood strategies, such as alcohol production, that allow them to retain control over income and support their households. However, women's central role in alcohol production, in concert with the ubiquitous nature of alcohol consumption, places them at risk by enhancing their vulnerability to unsafe or transactional sex. This represents a dangerous confluence of risk for female farmers, in which alcohol plays an important role in income generation and also facilitates high-risk sexual behavior. Alcohol production and consumption has the potential to both directly and indirectly place women at risk for undesirable sexual and reproductive health outcomes. Group formation, better access to finance, and engaging with agricultural extension officers were identified as potential interventions for supporting women farmers and challenging harmful gender norms. In addition, joint, multi-sectoral approaches from health and agriculture and alternative income-generating strategies for women might better address the complexities of achieving safe and sustainable livelihoods for women in this context

    Failure is Not an Option: Policy Learning for Adaptive Recovery in Space Operations

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    This letter considers the problem of how robots in long-term space operations can learn to choose appropriate sources of assistance to recover from failures. Current assistant selection methods for failure handling are based on manually specified static lookup tables or policies, which are not responsive to dynamic environments or uncertainty in human performance. We describe a novel and highly flexible learning-based assistant selection framework that uses contextual multiarm bandit algorithms. The contextual bandits exploit information from observed environment and assistant performance variables to efficiently learn selection policies under a wide set of uncertain operating conditions and unknown/dynamically constrained assistant capabilities. Proof of concept simulations of long-term human-robot interactions for space exploration are used to compare the performance of the contextual bandit against other state-of-the-art assistant selection approaches. The contextual bandit outperforms conventional static policies and noncontextual learning approaches, and also demonstrates favorable robustness and scaling properties

    A genome-wide association study to identify genetic markers associated with endometrial cancer grade

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    RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    Plasmodium knowlesi Genome Sequences from Clinical Isolates Reveal Extensive Genomic Dimorphism.

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    Plasmodium knowlesi is a newly described zoonosis that causes malaria in the human population that can be severe and fatal. The study of P. knowlesi parasites from human clinical isolates is relatively new and, in order to obtain maximum information from patient sample collections, we explored the possibility of generating P. knowlesi genome sequences from archived clinical isolates. Our patient sample collection consisted of frozen whole blood samples that contained excessive human DNA contamination and, in that form, were not suitable for parasite genome sequencing. We developed a method to reduce the amount of human DNA in the thawed blood samples in preparation for high throughput parasite genome sequencing using Illumina HiSeq and MiSeq sequencing platforms. Seven of fifteen samples processed had sufficiently pure P. knowlesi DNA for whole genome sequencing. The reads were mapped to the P. knowlesi H strain reference genome and an average mapping of 90% was obtained. Genes with low coverage were removed leaving 4623 genes for subsequent analyses. Previously we identified a DNA sequence dimorphism on a small fragment of the P. knowlesi normocyte binding protein xa gene on chromosome 14. We used the genome data to assemble full-length Pknbpxa sequences and discovered that the dimorphism extended along the gene. An in-house algorithm was developed to detect SNP sites co-associating with the dimorphism. More than half of the P. knowlesi genome was dimorphic, involving genes on all chromosomes and suggesting that two distinct types of P. knowlesi infect the human population in Sarawak, Malaysian Borneo. We use P. knowlesi clinical samples to demonstrate that Plasmodium DNA from archived patient samples can produce high quality genome data. We show that analyses, of even small numbers of difficult clinical malaria isolates, can generate comprehensive genomic information that will improve our understanding of malaria parasite diversity and pathobiology

    Applying Benford’s law to detect accounting data manipulation in the banking industry

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    We utilise Benford’s Law to test if balance sheet and income statement data broadly used to assess bank soundness were manipulated prior to and also during the global financial crisis. We find that all banks resort to loan loss provisions to manipulate earnings and income upwards. Distressed institutions that have stronger incentives to conceal their financial difficulties resort additionally to manipulating loan loss allowances and non-performing loans downwards. Moreover, manipulation is magnified during the crisis and expands to encompass regulatory capital

    Downregulation of urokinase plasminogen activator receptor expression inhibits Erk signalling with concomitant suppression of invasiveness due to loss of uPAR–β1 integrin complex in colon cancer cells

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    Cancer invasion is regulated by cell surface proteinases and adhesion molecules. Interaction between specific cell surface molecules such as urokinase plasminogen activator receptor (uPAR) and integrins is crucial for tumour invasion and metastasis. In this study, we examined whether uPAR and beta1 integrin form a functional complex to mediate signalling required for tumour invasion. We assessed the expression of uPAR/beta1 integrin complex, Erk signalling pathway, adhesion, uPA and matrix metalloproteinase (MMP) expression, migration/invasion and matrix degradation in a colon cancer cell line in which uPAR expression was modified. Antisense inhibition of the cell surface expression of uPAR by 50% in human colon carcinoma HCT116 cells (A/S) suppressed Erk-MAP kinase activity by two-fold. Urokinase plasminogen activator receptor antisense treatment of HCT116 cells was associated with a 1.3-fold inhibition of adhesion, approximately four-fold suppression of HMW-uPA secretion and inhibition of pro-MMP-9 secretion. At a functional level, uPAR antisense resulted in a four-fold decline in migration/invasion and abatement of plasmin-mediated matrix degradation. In empty vector-transfected cells (mock), uPA strongly elevated basal Erk activation. In contrast, in A/S cells, uPA induction of Erk activation was not observed. Urokinase plasminogen activator receptor associated with beta1 integrin in mock-transfected cells. Disruption of uPAR-beta1 integrin complex in mock-transfected cells with a specific peptide (P25) inhibited uPA-mediated Erk-MAP kinase pathway and inhibited migration/invasion and plasmin-dependent matrix degradation through suppression of pro-MMP-9/MMP-2 expression. This novel paradigm of uPAR-integrin signalling may afford opportunities for alternative therapeutic strategies for the treatment of cancer

    Carnosine scavenging of glucolipotoxic free radicals enhances insulin secretion and glucose uptake

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    The worldwide prevalence of diabetes has risen to 8.5% among adults, which represents a staggering rise in prevalence from 4.7% in 1980. Whilst some treatments work by increasing insulin secretion, over time their effectiveness decreases. We aim to increase insulin secretion by developing strategies that work through mechanisms independent of current treatment options. Isolated CD1 mouse islets, INS-1 pancreatic β-cells, or C2C12 mouse myotubes were incubated in standard tissue culture media, or media supplemented with 28 mM glucose, 200 μM palmitic acid, and 200 μM oleic acid as a cellular model of diabetic glucolipotoxicity. Intracellular reactive species content was assayed using 2′,7′-dichlorofluorescein diacetate dye, inducible nitric oxide synthase levels determined by Western blot, 3-nitrotyrosine and 4-hydrpxnonenal both assayed by ELISA, insulin secretion quantified using ELISA or radioimmunoassay, and glucose uptake determined through 2-deoxy glucose 6 phosphate luminescence. Our data indicate that carnosine, a histidine containing dipeptide available through the diet, is an effective scavenger of each of the aforementioned reactive species. This results in doubling of insulin secretion from isolated mouse islets or INS-1 β-cells. Crucially, carnosine also reverses glucolipotoxic inhibition of insulin secretion and enhances glucose uptake into skeletal muscle cells. Thus, carnosine, or non-hydrolysable carnosine analogs, may represent a new class of therapeutic agent to fight type 2 diabetes
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