239 research outputs found
Separating Skill from Luck in REIT Mutual Funds
This study uses a bootstrap methodology to explicitly distinguish between skill and luck for 80 Real Estate Investment Trust Mutual Funds in the period January 1995 to May 2008. The methodology successfully captures non-normality in the idiosyncratic risk of the funds. Using unconditional, beta conditional and alpha-beta conditional estimation models, the results indicate that all but one fund demonstrates poor skill. Tests of robustness show that this finding is largely invariant to REIT market conditions and maturity.
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Separating skill from luck in REIT mutual funds
This study uses a bootstrap methodology to explicitly distinguish between skill and luck for 80 Real Estate Investment Trust Mutual Funds in the period January 1995 to May 2008. The methodology successfully captures non-normality in the idiosyncratic risk of the funds. Using unconditional, beta conditional and alpha-beta conditional estimation models, the results indicate that all but one fund demonstrates poor skill. Tests of robustness show that this finding is largely invariant to REIT market conditions and maturity
Recreating Wonder Woman's invisible plane: A quantitative analysis of UAV visual signature manipulation via counterillumination
This study analyzes the effectiveness of an optical camouflage method called counterillumination and its effectiveness on an unmanned aerial vehicle (UAV). Counterillumination is achieved by emitting blue light on the bottom of the UAV to blend into the sky. Preliminary results are underwhelming, but design modifications can be made to improve the performance of the system. Further testing is required in order to collect any relevant data. Due to the COVID-19 Pandemic, unfortunately, this project could not be completed.Lew Wentz FoundationMechanical and Aerospace Engineerin
A Nonstationary Model of Newborn EEG
The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively)
Development of a selection to recover improved DNA ligase enzymes during directed evolution
DNA ligases are essential enzymes used in many molecular biology applications. Of particular note, they are important enzymes in next generation sequencing (NGS) technologies. The improved speed, efficiency, and affordability of NGS over Sanger sequencing has greatly expanded the applications of DNA sequencing. In most NGS technologies ligase enzymes play a crucial role, for instance in ligating adaptors onto sequence fragments during sample preparation. This key step requires a blunt-ended ligation reaction, with highly efficient ligases required in order to create a sample library of high quality. The current go-to enzyme is T4 DNA ligase, which has not evolved in Nature to perform blunt ended ligations, and as such has relatively poor levels of activity when compared to other substrates. There is therefore potential to improve upon this enzyme and engineer a ligase that is more efficient with blunt-ended substrates. We have developed a novel function-based directed evolution selection to evolve blunt-ended ligases that have greater catalytic efficiency. The basis for this approach is the over-expression of a ligase enzyme variant which is then incubated with a linearised plasmid encoding for that same ligase variant. More efficient ligases will ligate the plasmid encoding for their own gene variant more efficiently (in a blunt-ended ligation), and so greater numbers of the circularised plasmid will be produced. Through successive rounds of transformation, amplification and ligation the most improved enzyme variants are enriched. This selection approach is being used to evaluate a panel of ligase variants in order to identify the best ligases for blunt-ended ligation applications.
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Direct resummation of the leading renormalons in inclusive semileptonic B decay
We present a Borel resummation method for the QCD corrections in inclusive,
charmless, semileptonic B meson decay. The renormalon contributions are
resummed to all orders by employing a bilocal expansion of the Borel transform
that accurately accounts for the first infrared renormalons in the Borel plane.
The renormalons in the pole mass and the QCD expansion are resummed separately,
and a precise relation is obtained between a properly defined pole mass and the
mass. The inclusive decay rate is calculated to three loop
order using an estimate of the yet unknown NNLO coefficient.Comment: 10 pages,3 figures, version to appear in Phys. Lett.
Acute kidney injury in patients undergoing elective primary lower limb arthroplasty
Acknowledgements The authors would like to thank Abhi Punit for his contributions in data collection towards the above article Funding No funds, grants or other support was received.Open access via springer agreementPeer reviewedPublisher PD
Study on impact of robotic-assisted orthopaedic industrial noise (SIREN)
Acknowledgements We would like to thank Mr Patrick Ashcroft for his contribution to this study, especially with the provision of the recording equipment used in this study. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.Peer reviewe
The impact of adsorptionādesorption reactions on the chemistry of Himalayan rivers and the quantification of silicate weathering rates
A.K. was supported by a NERC DTP studentship (NE/S007164/1). This work was funded by the NERC grant NE/T007214/1.Common environmental adsorbents (clay minerals, metal-oxides, metal-oxyhydroxides and organic matter) can significantly impact the chemistry of aqueous fluids via adsorptionādesorption reactions. The dissolved chemistry of rivers have routinely been used to quantify silicate mineral dissolution rates, which is a key process for removing carbon dioxide (CO2) from the atmosphere over geological timescales. The sensitivity of silicate weathering rates to climate is disproportionately weighted towards regions with high erosion rates. This study quantifies the impact of adsorption-desorption reactions on the chemistry of three large Himalayan rivers over a period of two years, utilising both the adsorbed and dissolved phases. The concentration of riverine adsorbed cations are found to vary principally as a function of the concentration and cation exchange capacity (CEC) of the suspended sediment. Over the study period, the adsorbed phase is responsible for transporting ā¼70% of the mobile (adsorbed and dissolved) barium and ā¼10% of the mobile calcium and strontium. The relative partitioning of cations between the adsorbed and dissolved phases follows a systematic order in both the monsoon and the dry-season (preferentially adsorbed: Ba > Sr & Ca > Mg & K > Na). Excess mobile sodium (Na*=Na-Cl) to silicon (Si) riverine ratios are found to vary systematically during an annual hydrological cycle due to the mixing of low temperature and geothermal waters. The desorption of sodium from uplifted marine sediments is one key process that may increase the Na*/Si ratios. Accounting for the desorption of sodium reduces silicate weathering rate estimates by up to 83% in the catchments. This study highlights that surficial weathering processes alone are unable to explain the chemistry of the rivers studied due to the influence of hydrothermal reactions, which may play an important role in limiting the efficiency of silicate weathering and hence modulating atmospheric CO2 concentrations over geological time.Peer reviewe
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