1,005 research outputs found

    Coalescence and Anti-Coalescence Interference of Two-Photon Wavepacket in a Beam Splitter

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    We study a general theory on the interference of two-photon wavepacket in a beam splitter (BS). We find that the perfect coalescence interference requires a symmetric spectrum of two-photon wavepacket which can be entangled or un-entangled. Furthermore, we introduce a two-photon wavepacket with anti-symmetric spectrum, which is related with photon entanglement and shows a perfect anti-coalescence effect. The theory present uniform and complete explanation to two-photon interference.Comment: 5 pages, 2 figure

    Response of spectral reflectances and vegetation indices on varying juniper cone densities

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    Juniper trees are widely distributed throughout the world and are common sources of allergies when microscopic pollen grains are transported by wind and inhaled. In this study, we investigated the spectral influences of pollen-discharging male juniper cones within a juniper canopy. This was done through a controlled outdoor experiment involving ASD FieldSpec Pro Spectroradiometer measurements over juniper canopies of varying cone densities. Broadband and narrowband spectral reflectance and vegetation index (VI) patterns were evaluated as to their sensitivity and their ability to discriminate the presence of cones. The overall aim of this research was to assess remotely sensed phenological capabilities to detect pollen-bearing juniper trees for public health applications. A general decrease in reflectance values with increasing juniper cone density was found, particularly in the Green (545-565 nm) and NIR (750-1,350 nm) regions. In contrast, reflectances in the shortwave-infrared (SWIR, 2,000 nm to 2,350 nm) region decreased from no cone presence to intermediate amounts (90 g/m2) and then increased from intermediate levels tothe highest cone densities (200 g/m2). Reflectance patterns in the Red (620-700 nm) were more complex due to shifting contrast patterns in absorptance between cones and juniper foliage, where juniper foliage is more absorbing than cones only within the intense narrowband region of maximum chlorophyll absorption near 680 nm. Overall, narrowband reflectances were more sensitive to cone density changes than the equivalent MODIS broadbands. In all VIs analyzed, there were significant relationships with cone density levels, particularly with the narrowband versions and the two-band vegetation index (TBVI) based on Green and Red bands, a promising outcome for the use of phenocams in juniper phenology trait studies. These results indicate that spectral indices are sensitive to certain juniper phenologic traits that can potentially be used for juniper cone detection in support of public health applications. © 2013 by the authors

    Functional response of U.S. grasslands to the early 21st-century drought

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    Grasslands across the United States play a key role in regional livelihood and national food security. Yet, it is still unclear how this important resource will respond to the prolonged warm droughts and more intense rainfall events predicted with climate change. The early 21st-century drought in the southwestern United States resulted in hydroclimatic conditions that are similar to those expected with future climate change. We investigated the impact of the early 21st-century drought on aboveground net primary production (ANPP) of six desert and plains grasslands dominated by C4 (warm season) grasses in terms of significant deviations between observed and expected ANPP. In desert grasslands, drought-induced grass mortality led to shifts in the functional response to annual total precipitation (PT), and in some cases, new species assemblages occurred that included invasive species. In contrast, the ANPP in plains grasslands exhibited a strong linear function of the current-year PT and the previous-year ANPP, despite prolonged warm drought. We used these results to disentangle the impacts of interannual total precipitation, intra-annual precipitation patterns, and grassland abundance on ANPP, and thus generalize the functional response of C4 grasslands to predicted climate change. This will allow managers to plan for predictable shifts in resources associated with climate change related to fire risk, loss of forage, and ecosystem services. © 2014 by the Ecological Society of America

    An Empirical Evaluation of Evolutionary Algorithms for Unit Test Suite Generation

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    Context: Evolutionary algorithms have been shown to be e ective at generating unit test suites optimised for code coverage. While many speci c aspects of these algorithms have been evaluated in detail (e.g., test length and di erent kinds of techniques aimed at improving performance, like seeding), the in uence of the choice of evolutionary algorithm has to date seen less attention in the literature. Objective: Since it is theoretically impossible to design an algorithm that is the best on all possible problems, a common approach in software engineering problems is to rst try the most common algorithm, a Genetic Algorithm, and only afterwards try to re ne it or compare it with other algorithms to see if any of them is more suited for the addressed problem. The objective of this paper is to perform this analysis, in order to shed light on the in uence of the search algorithm applied for unit test generation. Method: We empirically evaluate thirteen di erent evolutionary algorithms and two random approaches on a selection of non-trivial open source classes. All algorithms are implemented in the EvoSuite test generation tool, which includes recent optimisations such as the use of an archive during the search and optimisation for multiple coverage criteria. Results: Our study shows that the use of a test archive makes evolutionary algorithms clearly better than random testing, and it con rms that the DynaMOSA many-objective search algorithm is the most e ective algorithm for unit test generation. Conclusions: Our results show that the choice of algorithm can have a substantial in uence on the performance of whole test suite optimisation. Although we can make a recommendation on which algorithm to use in practice, no algorithm is clearly superior in all cases, suggesting future work on improved search algorithms for unit test generatio

    The human histone chaperone sNASP interacts with linker and core histones through distinct mechanisms

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    Somatic nuclear autoantigenic sperm protein (sNASP) is a human homolog of the N1/N2 family of histone chaperones. sNASP contains the domain structure characteristic of this family, which includes a large acidic patch flanked by several tetratricopeptide repeat (TPR) motifs. sNASP possesses a unique binding specificity in that it forms specific complexes with both histone H1 and histones H3/H4. Based on the binding affinities of sNASP variants to histones H1, H3.3, H4 and H3.3/H4 complexes, sNASP uses distinct structural domains to interact with linker and core histones. For example, one of the acidic patches of sNASP was essential for linker histone binding but not for core histone interactions. The fourth TPR of sNASP played a critical role in interactions with histone H3/H4 complexes, but did not influence histone H1 binding. Finally, analysis of cellular proteins demonstrated that sNASP existed in distinct complexes that contained either linker or core histones

    Improving SNR and reducing training time of classifiers in large datasets via kernel averaging

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    Kernel methods are of growing importance in neuroscience research. As an elegant extension of linear methods, they are able to model complex non-linear relationships. However, since the kernel matrix grows with data size, the training of classifiers is computationally demanding in large datasets. Here, a technique developed for linear classifiers is extended to kernel methods: In linearly separable data, replacing sets of instances by their averages improves signal-to-noise ratio (SNR) and reduces data size. In kernel methods, data is linearly non-separable in input space, but linearly separable in the high-dimensional feature space that kernel methods implicitly operate in. It is shown that a classifier can be efficiently trained on instances averaged in feature space by averaging entries in the kernel matrix. Using artificial and publicly available data, it is shown that kernel averaging improves classification performance substantially and reduces training time, even in non-linearly separable data

    Whipple's disease: rare disorder and late diagnosis

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    Whipple's disease is a rare systemic infectious disorder caused by the bacterium Tropheryma whipplei. We report the case of a 61-year-old male patient who presented to emergency room complaining of asthenia, arthralgia, anorexia, articular complaints intermittent diarrhea, and a 10-kg weight loss in one year. Laboratory tests showed the following results: Hb = 7.5 g/dL, albumin = 2.5 mg/dL, weight = 50.3 kg (BMI 17.4 kg/m²). Upper gastrointestinal endoscopy revealed areas of focal enanthema in the duodenum. An endoscopic biopsy was suggestive of Whipple's disease. Diagnosis was confirmed based on a positive serum polymerase chain reaction. Treatment was initiated with intravenous ceftriaxone followed by oral trimethoprim-sulfamethoxazole. After one year of treatment, the patient was asymptomatic, with Hb = 13.5 g/dL, serum albumin = 5.3 mg/dL, and weight = 70 kg (BMI 24.2 kg/m²). Whipple's disease should be considered a differential diagnosis in patients with prolonged constitutional and/or gastrointestinal symptoms. Appropriate antibiotic treatment improves the quality of life of patients

    Stochastic Gravity: Theory and Applications

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    Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a black hole and describe the metric fluctuations near the event horizon of an evaporating black holeComment: 100 pages, no figures; an update of the 2003 review in Living Reviews in Relativity gr-qc/0307032 ; it includes new sections on the Validity of Semiclassical Gravity, the Stability of Minkowski Spacetime, and the Metric Fluctuations of an Evaporating Black Hol

    Binocular summation and other forms of non-dominant eye contribution in individuals with strabismic amblyopia during habitual viewing

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    YesAdults with amblyopia ('lazy eye'), long-standing strabismus (ocular misalignment) or both typically do not experience visual symptoms because the signal from weaker eye is given less weight than the signal from its fellow. Here we examine the contribution of the weaker eye of individuals with strabismus and amblyopia with both eyes open and with the deviating eye in its anomalous motor position. The task consisted of a blue-on-yellow detection task along a horizontal line across the central 50 degrees of the visual field. We compare the results obtained in ten individuals with strabismic amblyopia with ten visual normals. At each field location in each participant, we examined how the sensitivity exhibited under binocular conditions compared with sensitivity from four predictions, (i) a model of binocular summation, (ii) the average of the monocular sensitivities, (iii) dominant-eye sensitivity or (iv) non-dominant-eye sensitivity. The proportion of field locations for which the binocular summation model provided the best description of binocular sensitivity was similar in normals (50.6%) and amblyopes (48.2%). Average monocular sensitivity matched binocular sensitivity in 14.1% of amblyopes' field locations compared to 8.8% of normals'. Dominant-eye sensitivity explained sensitivity at 27.1% of field locations in amblyopes but 21.2% in normals. Non-dominant-eye sensitivity explained sensitivity at 10.6% of field locations in amblyopes but 19.4% in normals. Binocular summation provided the best description of the sensitivity profile in 6/10 amblyopes compared to 7/10 of normals. In three amblyopes, dominant-eye sensitivity most closely reflected binocular sensitivity (compared to two normals) and in the remaining amblyope, binocular sensitivity approximated to an average of the monocular sensitivities. Our results suggest a strong positive contribution in habitual viewing from the non-dominant eye in strabismic amblyopes. This is consistent with evidence from other sources that binocular mechanisms are frequently intact in strabismic and amblyopic individuals
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