734 research outputs found

    Justice at Sea: Fishers’ politics and marine conservation in coastal Odisha, India

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    This is a paper about the politics of fishing rights in and around the Gahirmatha marine sanctuary in coastal Odisha, in eastern India. Claims to the resources of this sanctuary are politicised through the creation of a particularly damaging narrative by influential Odiya environmental actors about Bengalis, as illegal immigrants who have hurt the ecosystem through their fishing practices. Anchored within a theoretical framework of justice as recognition, the paper considers the making of a regional Odiya environmentalism that is, potentially, deeply exclusionary. It details how an argument about ‘illegal Bengalis’ depriving ‘indigenous Odiyas’ of their legitimate ‘traditional fishing rights’ derives from particular notions of indigeneity and territory. But the paper also shows that such environmentalism is tenuous, and fits uneasily with the everyday social landscape of fishing in coastal Odisha. It concludes that a wider class conflict between small fishers and the state over a sanctuary sets the context in which questions about legitimate resource rights are raised, sometimes with important effects, like when out at sea

    High-throughput, quantitative analyses of genetic interactions in E. coli.

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    Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

    A comparison of laboratory and in situ methods to determine soil thermal conductivity for energy foundations and other ground heat exchanger applications

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    Soil thermal conductivity is an important factor in the design of energy foundations and other ground heat exchanger systems. It can be determined by a field thermal response test, which is both costly and time consuming, but tests a large volume of soil. Alternatively, cheaper and quicker laboratory test methods may be applied to smaller soil samples. This paper investigates two different laboratory methods: the steady-state thermal cell and the transient needle probe. U100 soil samples were taken during the site investigation for a small diameter test pile, for which a thermal response test was later conducted. The thermal conductivities of the samples were measured using the two laboratory methods. The results from the thermal cell and needle probe were significantly different, with the thermal cell consistently giving higher values for thermal conductivity. The main difficulty with the thermal cell was determining the rate of heat flow, as the apparatus experiences significant heat losses. The needle probe was found to have fewer significant sources of error, but tests a smaller soil sample than the thermal cell. However, both laboratory methods gave much lower values of thermal conductivity compared to the in situ thermal response test. Possible reasons for these discrepancies are discussed, including sample size, orientation and disturbance

    Female labour market outcomes and the impact of maternity leave policies

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    ABSTRACT: This paper shows how family policies aimed at reconciling the pressures of family and work generate substantial variation in labour market outcomes across developed countries. We use a life-cycle model of female labour supply and savings behaviour, calibrated to the US economy, to assess the effect of introducing to the US a maternity leave policy similar to Scandinavian-type policies. We focus on the impact on gender differences in participation and in wages. We distinguish between the effect of the job protection offered by maternity leave and the effect of income replacement. Job protection leads to substantial increases in participation of mothers with children under 6, but with little long term effects. The effects on wages are minimal, with negative selection effects offsetting the reduced human capital depreciation. Income replacement has a limited impact on participation or wages.Virginia SĂĄnchez-Marcos thanks the Spanish Ministry of Science and Technology for Grant ECO2009-09614 and RecerCaixa for financial support

    Educational Homogamy Lowers the Odds of Reproductive Failure

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    Assortative mating based on education is a common phenomenon. We investigated whether it affected parameters of reproductive performance such as childlessness, offspring number and age at first marriage. On the basis of the US census from 1980 (n = 670,631 married US couples), we find that the proportion of childless individuals is usually minimal in women married to a husband of the same educational level. This holds particularly true in the highest and the lowest educated women. Educational homogamy is also associated with a lower average age at first marriage. No obvious effect of educational homogamy on a woman's average offspring number is found, where mean offspring number generally increases both with decreasing woman's and decreasing husband's educational attainment. We conclude that educational homogamy reduces the likelihood of reproductive failure

    Selective formation of tungsten nanowires

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    We report on a process for fabricating self-aligned tungsten (W) nanowires with polycrystalline silicon core. Tungsten nanowires as thin as 10 nm were formed by utilizing polysilicon sidewall transfer technology followed by selective deposition of tungsten by chemical vapor deposition (CVD) using WF6 as the precursor. With selective CVD, the process is self-limiting whereby the tungsten formation is confined to the polysilicon regions; hence, the nanowires are formed without the need for lithography or for additional processing. The fabricated tungsten nanowires were observed to be perfectly aligned, showing 100% selectivity to polysilicon and can be made to be electrically isolated from one another. The electrical conductivity of the nanowires was characterized to determine the effect of its physical dimensions. The conductivity for the tungsten nanowires were found to be 40% higher when compared to doped polysilicon nanowires of similar dimensions

    Molecular Characterization, Tissue Distribution, Subcellular Localization and Actin-Sequestering Function of a Thymosin Protein from Silkworm

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    We identified a novel gene encoding a Bombyx mori thymosin (BmTHY) protein from a cDNA library of silkworm pupae, which has an open reading frame (ORF) of 399 bp encoding 132 amino acids. It was found by bioinformatics that BmTHY gene consisted of three exons and two introns and BmTHY was highly homologous to thymosin betas (Tβ). BmTHY has a conserved motif LKHTET with only one amino acid difference from LKKTET, which is involved in Tβ binding to actin. A His-tagged BmTHY fusion protein (rBmTHY) with a molecular weight of approximately 18.4 kDa was expressed and purified to homogeneity. The purified fusion protein was used to produce anti-rBmTHY polyclonal antibodies in a New Zealand rabbit. Subcellular localization revealed that BmTHY can be found in both Bm5 cell (a silkworm ovary cell line) nucleus and cytoplasm but is primarily located in the nucleus. Western blotting and real-time RT-PCR showed that during silkworm developmental stages, BmTHY expression levels are highest in moth, followed by instar larvae, and are lowest in pupa and egg. BmTHY mRNA was universally distributed in most of fifth-instar larvae tissues (except testis). However, BmTHY was expressed in the head, ovary and epidermis during the larvae stage. BmTHY formed complexes with actin monomer, inhibited actin polymerization and cross-linked to actin. All the results indicated BmTHY might be an actin-sequestering protein and participate in silkworm development

    Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

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    yesDrug vehicles are chemical carriers that provide beneficial aid to the drugs they bear. Taking advantage of their favourable properties can potentially allow the safer use of drugs that are considered highly toxic. A means for vehicle selection without experimental trial would therefore be of benefit in saving time and money for the industry. Although machine learning is increasingly used in predictive toxicology, to our knowledge there is no reported work in using machine learning techniques to model drug-vehicle relationships for vehicle selection to minimise toxicity. In this paper we demonstrate the use of data mining and machine learning techniques to process, extract and build models based on classifiers (decision trees and random forests) that allow us to predict which vehicle would be most suited to reduce a drug’s toxicity. Using data acquired from the National Institute of Health’s (NIH) Developmental Therapeutics Program (DTP) we propose a methodology using an area under a curve (AUC) approach that allows us to distinguish which vehicle provides the best toxicity profile for a drug and build classification models based on this knowledge. Our results show that we can achieve prediction accuracies of 80 % using random forest models whilst the decision tree models produce accuracies in the 70 % region. We consider our methodology widely applicable within the scientific domain and beyond for comprehensively building classification models for the comparison of functional relationships between two variables

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO
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