803 research outputs found
On the Exponentials of Some Structured Matrices
In this note explicit algorithms for calculating the exponentials of
important structured 4 x 4 matrices are provided. These lead to closed form
formulae for these exponentials. The techniques rely on one particular Clifford
Algebra isomorphism and basic Lie theory. When used in conjunction with
structure preserving similarities, such as Givens rotations, these techniques
extend to dimensions bigger than four.Comment: 19 page
Towards the development of cascaded surface plasmon resonance POF sensors exploiting gold films and synthetic recognition elements for detection of contaminants in transformer oil
The possibility of developing a multichannel optical chemical sensor, based on molecularly imprinted polymers (MIPs) and surface plasmon resonance (SPR) in a D-shaped multimode plastic optical fiber (POF), is presented by two cascaded SPR-POF-MIP sensors with different thicknesses of the gold layer. The low cost, the high selectivity and sensitivity of the SPR-POF-MIP platforms and the simple and modular scheme of the optical interrogation layout make this system a potentially suitable on-line multi-diagnostic tool. As a proof of principle, the possibility of simultaneous determination of two important analytes, dibenzyl disulfide (DBDS) and furfural (2-FAL), in power transformer oil was investigated. Their presence gives useful indication of underway corrosive or ageing processes in power transformers, respectively. Preliminarily, the dependence of the performance of the D-shaped optical platform on the gold film thickness has been studied, comparing two platforms with 30 nm and 60 nm thick gold layers. It has been found that the resonance wavelengths are different on platforms with gold layer of different thickness, furthermore when MIPs are present on the gold as receptors, the performances of the platforms are similar in the two considered sensors. Keywords: Cascaded multianalyte detection, Surface plasmon resonance, Dibenzyl disulfide, Furfural (furan-2-carbaldehyde), Molecularly imprinted polymers, Plastic optical fiber
Lightlike infinity in GCA models of Spacetime
This paper discusses a 7 dimensional conformal geometric algebra model for
spacetime based on the notion that spacelike and timelike infinities are
distinct. I show how naturally of the dimensions represents the lightlike
infinity and appears redundant in computations, yet usefull in interpretationComment: 12 page
Desenvolvimento de aveia branca em diferentes manejos fisicos e quimicos em nitossolo.
A utilização de aveia como cobertura do solo manejado em sistema plantio direto vem sendo muito empregada no sul do Brasil, contudo, impedimentos físicos e químicos do solo limitam o seu desenvolvimento radicular. O objetivo desse trabalho foi avaliar a combinação de estratégias de melhoria física e química na semeadura sobre o desenvolvimento da aveia branca em Nitossolo Vermelho sob sistema plantio direto. Os tratamentos foram distribuídos em blocos ao acaso em esquema fatorial, possuindo como fator principal o manejo mecânico e secundário o manejo químico. Os manejos mecânicos empregados foram: o SPD7 ? Sistema de Plantio Direto com sulcador da semeadora atuando a 7 cm de profundidade, como Testemunha, e a 11 cm como SPD11, esse como estratégia de manutenção do SPD; e CM ? cultivo mínimo realizado com um subsolador, como estratégia de melhoria física, porém contra os ideais do SPD. Os tipos de manejo químico foram à adição na linha de semeadura, de calcário de xisto e de calcário dolomítico. Avaliou-se a produção de massa verde e seca e a concentração mineral de nitrogênio, cálcio, magnésio, cobre e zinco. O calcário de xisto disponibilizou mais minerais para aveia resultando em maior desenvolvimento da planta, expresso pela maior massa verde e seca, bem como, a estratégia de melhoria física na semeadura, o SPD11, quando comparado ao SPD7, no entanto, o CM foi o que apresentou as maiores concentrações e massa seca da parte aérea das plantas
Evaluation of an optimized enzymatic biosensor for ethanol used in apple storage management with low oxygen stress
Ethanol has been proposed to be one of the target molecules to monitor the dynamic controlled atmosphere (DCA) technique during apple storage, measured in the squeezed juice or in the air of the storage chamber. One of the proposed commercial sensors for ethanol in apple juice is based on amperometry, after a two-step enzyme-based reaction that involves a diaphorase and an alcohol-dehydrogenase. Even though this method has been reported to overestimate ethanol, this difference is fairly fixed and it is industrially used to check the correct application of the treatment and to set the gas composition protocols when the maximum acceptable ethanol is reached. During the 2018 harvest, the ethanol concentration in juices measured with the commercial sensor appeared much higher than those usually reported in precedent years, particularly for the lower concentrations. Laboratory experiments suggested that differences between years could be due to the presence of a secondary enzyme activity present in the commercial diaphorase employed. In order to increase the sensitivity and accuracy, it has been evaluated the performance of the biosensor emploting a further diaphorase. The performances of both sensors were compared with those obtained with a gaschromatophy mass spectrometry approach after head space extraction (HS-GC-MS) in which the mass spectra was acquired in selected-ion monitoring mode. Samples belonging to ‘Red Delicious’ cv. were picked up at different temporary points from industrial storage rooms following the application of low oxygen stress. The new biosensor reduced 97% the mean difference respect to the values obtained with the GC-MS method. The difference between sensors was even clearer for samples with concentrations up to 100 mg/L, that could be used as a discriminating value for the evaluation of the technique success in ‘Red Delicious’ apple juice. The increased sensitivity of the sensor allowed a more accurate monitoring of the DCA at industrial conditions, limiting the risks linked to a false positive on the monitoring during storage
Learning algorithms estimate pose and detect motor anomalies in flies exposed to minimal doses of a toxicant
Pesticide exposure, even at low doses, can have detrimental effects on ecosystems. This study aimed at validating the use of machine learning for recognizing motor anomalies, produced by minimal insecticide exposure on a model insect species. The Mediterranean fruit fly, Ceratitis capitata (Diptera: Tephritidae), was exposed to food contaminated with low concentrations of Carlina acaulis essential oil (EO). A deep learning approach enabled fly pose estimation on video recordings in a custom-built arena. Five machine learning algorithms were trained on handcrafted features, extracted from the predicted pose, to distinguish treated individuals. Random Forest and K-Nearest Neighbor algorithms best performed, with an area under the receiver operating characteristic (ROC) curve of 0.75 and 0.73, respectively. Both algorithms achieved an accuracy of 0.71. Results show the machine learning potential for detecting sublethal effects arising from insecticide exposure on fly motor behavior, which could also affect other organisms and environmental health
LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment
Pairwise sequence alignment is one of the most computationally intensive
kernels in genomic data analysis, accounting for more than 90% of the runtime
for key bioinformatics applications. This method is particularly expensive for
third-generation sequences due to the high computational cost of analyzing
sequences of length between 1Kb and 1Mb. Given the quadratic overhead of exact
pairwise algorithms for long alignments, the community primarily relies on
approximate algorithms that search only for high-quality alignments and stop
early when one is not found. In this work, we present the first GPU
optimization of the popular X-drop alignment algorithm, that we named LOGAN.
Results show that our high-performance multi-GPU implementation achieves up to
181.6 GCUPS and speed-ups up to 6.6x and 30.7x using 1 and 6 NVIDIA Tesla V100,
respectively, over the state-of-the-art software running on two IBM Power9
processors using 168 CPU threads, with equivalent accuracy. We also demonstrate
a 2.3x LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for
sequence alignment implemented in minimap2, a long-read mapping software. To
highlight the impact of our work on a real-world application, we couple LOGAN
with a many-to-many long-read alignment software called BELLA, and demonstrate
that our implementation improves the overall BELLA runtime by up to 10.6x.
Finally, we adapt the Roofline model for LOGAN and demonstrate that our
implementation is near-optimal on the NVIDIA Tesla V100s
Relativistic Chasles' theorem and the conjugacy classes of the inhomogeneous Lorentz group
This work is devoted to the relativistic generalization of Chasles' theorem,
namely to the proof that every proper orthochronous isometry of Minkowski
spacetime, which sends some point to its chronological future, is generated
through the frame displacement of an observer which moves with constant
acceleration and constant angular velocity. The acceleration and angular
velocity can be chosen either aligned or perpendicular, and in the latter case
the angular velocity can be chosen equal or smaller than than the acceleration.
We start reviewing the classical Euler's and Chasles' theorems both in the Lie
algebra and group versions. We recall the relativistic generalization of
Euler's theorem and observe that every (infinitesimal) transformation can be
recovered from information of algebraic and geometric type, the former being
identified with the conjugacy class and the latter with some additional
geometric ingredients (the screw axis in the usual non-relativistic version).
Then the proper orthochronous inhomogeneous Lorentz Lie group is studied in
detail. We prove its exponentiality and identify a causal semigroup and the
corresponding Lie cone. Through the identification of new Ad-invariants we
classify the conjugacy classes, and show that those which admit a causal
representative have special physical significance. These results imply a
classification of the inequivalent Killing vector fields of Minkowski spacetime
which we express through simple representatives. Finally, we arrive at the
mentioned generalization of Chasles' theorem.Comment: Latex2e, 49 pages. v2: few typos correcte
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