Power to detect normal mixtures: Simulation results

Twenty tests for normality were compared for the purpose of detecting mixtures of two normal components with unequal means but equal variance. The purpose of this study was to determine the power of tests specifically designed to detect mixtures, i.e., the likelihood ratio and Engelman-Hartigan tests, relative to other tests for normality. We considered the entire range of mixing proportions {pi}, 0 0.85 or {pi} < 0.15, {radical}b{sub 1} was among the best tests. For intermediate mixing proportions, the likelihood ratio test was best. For situations in which the preferred test had power 50% or more, the power of the likelihood ratio test was also above 50% and within 15 percentage points of the preferred test

The isotopic composition of normal krypton and xenon

Recently a mass-spectrometer investigation of the isotopes of krypton and xenon resulting from the fission of uranium-235 by thermal neutrons was reported.(1) This investigation was carried out with a 180°-deflection Nier-type mass spectrometer.(2

Comparison of energy spreads induced by a wakefield in a cavity

The energy spread of a beam bunch induced in a linear accelerator can be reduced to a minimum if the amplitude and the phase of the RF voltage are optimized. The energy spread is induced by the longitudinal wakefield and by the sinusoidal profile of the accelerating voltage acting on the beam. The cavity shape, the bunch profile, and the charge in the bunch determine the wake function. Aiming to have an approximately constant net voltage acting across the beam bunch, we optimize the amplitude and the phase of the RF voltage. The minimum energy spread, the required RF voltage, and the required RF phase are calculated as a function of the net charge and the length of the bunch. To find out the effect of cavity shape on the minimum energy spread, the optimization was performed for several types of cavities. 4 refs., 8 figs

Accommodating false positives within acoustic spatial capture–recapture, with variable source levels, noisy bearings and an inhomogeneous spatial density

Funding: Tiago Marques was partly supported by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia, Portugal, through the project UIDB/00006/2020).Passive acoustic monitoring is a promising method for surveying wildlife populations that are easier to detect acoustically than visually. When animal vocalisations can be uniquely identified on an array of sensors, the potential exists to estimate population density through acoustic spatial capture–recapture (ASCR). However, sound classification is imperfect, and in some situations, a high proportion of sounds detected on just a single sensor (‘singletons’) are not from the target species. We present a case study of bowhead whale calls (Baleana mysticetus) collected in the Beaufort Sea in 2010 containing such false positives. We propose a novel extension of ASCR that is robust to false positives by truncating singletons and conditioning on calls being detected by at least two sensors. We allow for individual-level detection heterogeneity through modelling a variable sound source level, model inhomogeneous call spatial density, and include bearings with varying measurement error. We show via simulation that the method produces near-unbiased estimates when correctly specified. Ignoring source-level variation resulted in a strong negative bias, while ignoring inhomogeneous density resulted in severe positive bias. The case study analysis indicated a band of higher call density approximately 30 km from shore; 59.8% of singletons were estimated to have been false positives.Publisher PDFPeer reviewe

Using Long-Term Volunteer Records to Examine Dormouse (Muscardinusavellanarius) Nestbox Selection.

Within ecology, there are unanswered questions about species-habitat interactions, which could potentially be resolved by a pragmatic analysis of a long-term volunteer-collected dataset. Here, we analysed 18 years of volunteer-collected data from a UK dormouse nestbox monitoring programme to determine the influence of habitat variables on nestbox choice by common dormice (Muscardinusavellanarius). We measured a range of habitat variables in a coppiced woodland in Gloucestershire, UK, and analysed these in relation to dormouse nestbox occupancy records (by dormice, other small mammals, and birds) collected by volunteers. While some characteristics of the woodland had changed over 18 years, simple transformation of the data and interpretation of the results indicated that the dataset was informative. Using stepwise regressions, multiple environmental and ecological factors were found to determine nestbox selection. Distance from the edge of the wood was the most influential (this did not change over 18 years), with boxes in the woodland interior being selected preferentially. There was a significant negative relationship with the presence of ferns (indicative of damp shady conditions). The presence of oak (a long-lived species), and the clumped structural complexity of the canopy were also important factors in the final model. There was no evidence of competition between dormice and birds or other mammals. The results provide greater understanding of artificial dormouse nest-site requirements and indicate that, in terms of habitat selection, long-term volunteer-collected datasets contribute usefully to understanding the requirements of species with an important conservation status

A comparison of three methods for estimating call densities of migrating bowhead whales using passive acoustic monitoring

TAM thanks partial support by Centro de Estatistica e Aplicações, Universidade de Lisboa (funded by FCT—Fundação para a Ciência e a Tecnologia, Portugal, through the project UID/MAT/00006/2013).Various methods for estimating animal density from visual data, including distance sampling (DS) and spatially explicit capture-recapture (SECR), have recently been adapted for estimating call density using passive acoustic monitoring (PAM) data, e.g., recordings of animal calls. Here we summarize three methods available for passive acoustic density estimation: plot sampling, DS, and SECR. The first two require distances from the sensors to calling animals (which are obtained by triangulating calls matched among sensors), but SECR only requires matching (not localizing) calls among sensors. We compare via simulation what biases can arise when assumptions underlying these methods are violated. We use insights gleaned from the simulation to compare the performance of the methods when applied to a case study: bowhead whale call data collected from arrays of directional acoustic sensors at five sites in the Beaufort Sea during the fall migration 2007–2014. Call detections were manually extracted from the recordings by human observers simultaneously scanning spectrograms of recordings from a given site. The large discrepancies between estimates derived using SECR and the other two methods were likely caused primarily by the manual detection procedure leading to non-independent detections among sensors, while errors in estimated distances between detected calls and sensors also contributed to the observed patterns. Our study is among the first to provide a direct comparison of the three methods applied to PAM data and highlights the importance that all assumptions of an analysis method need to be met for correct inference.Publisher PDFPeer reviewe

Malignant inflammation in cutaneous T-cell lymphoma: a hostile takeover

Cutaneous T-cell lymphomas (CTCL) are characterized by the presence of chronically inflamed skin lesions containing malignant T cells. Early disease presents as limited skin patches or plaques and exhibits an indolent behavior. For many patients, the disease never progresses beyond this stage, but in approximately one third of patients, the disease becomes progressive, and the skin lesions start to expand and evolve. Eventually, overt tumors develop and the malignant T cells may disseminate to the blood, lymph nodes, bone marrow, and visceral organs, often with a fatal outcome. The transition from early indolent to progressive and advanced disease is accompanied by a significant shift in the nature of the tumor-associated inflammation. This shift does not appear to be an epiphenomenon but rather a critical step in disease progression. Emerging evidence supports that the malignant T cells take control of the inflammatory environment, suppressing cellular immunity and anti-tumor responses while promoting a chronic inflammatory milieu that fuels their own expansion. Here, we review the inflammatory changes associated with disease progression in CTCL and point to their wider relevance in other cancer contexts. We further define the term "malignant inflammation" as a pro-tumorigenic inflammatory environment orchestrated by the tumor cells and discuss some of the mechanisms driving the development of malignant inflammation in CTCL