Efficient and Unbiased Estimation of Population Size

Population sizing from still aerial pictures is of wide applicability in ecological and social sciences. The problem is long standing because current automatic detection and counting algorithms are known to fail in most cases, and exhaustive manual counting is tedious, slow, difficult to verify and unfeasible for large populations. An alternative is to multiply population density with some reference area but, unfortunately, sampling details, handling of edge effects, etc., are seldom described. For the first time we address the problem using principles of geometric sampling. These principles are old and solid, but largely unknown outside the areas of three dimensional microscopy and stereology. Here we adapt them to estimate the size of any population of individuals lying on an essentially planar area, e.g. people, animals, trees on a savanna, etc. The proposed design is unbiased irrespective of population size, pattern, perspective artifacts, etc. The implementation is very simple—it is based on the random superimposition of coarse quadrat grids. Also, an objective error assessment is often lacking. For the latter purpose the quadrat counts are often assumed to be independent. We demonstrate that this approach can perform very poorly, and we propose (and check via Monte Carlo resampling) a new theoretical error prediction formula. As far as efficiency, counting about 50 (100) individuals in 20 quadrats, can yield relative standard errors of about 8% (5%) in typical cases. This fact effectively breaks the barrier hitherto imposed by the current lack of automatic face detection algorithms, because semiautomatic sampling and manual counting becomes an attractive option

On the stereological estimation of reduced moment measures

Boolean model, Hausdorff measures, marked point processes, measure decomposition, moment measures, stereology, stochastic geometry,

Dédifférenciation des cellules épithéliales mammaires primaires en culture : un modèle ex vivo de la plasticité du tissu mammaire

Dédifférenciation des cellules épithéliales mammaires primaires en culture : un modèle ex vivo de la plasticité du tissu mammaire. Journées d’Animation des Crédits Incitatifs du Département de Physiologie Animale et Systèmes d’Elevage (JACI Phase 2016

The fear of COVID-19 scale: Its structure and measurement invariance across 48 countries

Coronavirus disease (COVID-19) has been a source of fear around the world. We asked whether the measurement of this fear is trustworthy and comparable across countries. In particular, we explored the measurement invariance and cross-cultural replicability of the widely used Fear of COVID-19 scale (FCV-19S), testing community samples from 48 countries (N = 14,558). The findings indicate that the FCV-19S has a somewhat problematic structure, yet the one-factor solution is replicable across cultural contexts and could be used in studies that compare people who vary on gender and educational level. The validity of the scale is supported by a consistent pattern of positive correlations with perceived stress and general anxiety. However, given the unclear structure of the FCV-19S, we recommend using latent factor scores, instead of raw scores, especially in cross-cultural comparisons. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Basic quantitative morphological methods applied to the central nervous system

Generating numbers has become an almost inevitable task associated with studies of the morphology of the nervous system. Numbers serve a desire for clarity and objectivity in the presentation of results and are a prerequisite for the statistical evaluation of experimental outcomes. Clarity, objectivity, and statistics make demands on the quality of the numbers that are not met by many methods. This review provides a refresher of problems associated with generating numbers that describe the nervous system in terms of the volumes, surfaces, lengths, and numbers of its components. An important aim is to provide comprehensible descriptions of the methods that address these problems. Collectively known as design-based stereology, these methods share two features critical to their application. First, they are firmly based in mathematics and its proofs. Second and critically underemphasized, an understanding of their mathematical background is not necessary for their informed and productive application. Understanding and applying estimators of volume, surface, length or number does not require more of an organizational mastermind than an immunohistochemical protocol. And when it comes to calculations, square roots are the gravest challenges to overcome. Sampling strategies that are combined with stereological probes are efficient and allow a rational assessment if the numbers that have been generated are "good enough." Much may be unfamiliar, but very little is difficult. These methods can no longer be scapegoats for discrepant results but faithfully produce numbers on the material that is assessed. They also faithfully reflect problems that associated with the histological material and the anatomically informed decisions needed to generate numbers that are not only valid in theory. It is within reach to generate practically useful numbers that must integrate with qualitative knowledge to understand the function of neural systems

The fear of COVID-19 scale: Its structure and measurement invariance across 48 countries

COVID-19 has been a source of fear around the world. We asked whether the measurement of this fear is trustworthy and comparable across countries. In particular, we explored the measurement invariance and cross-cultural replicability of the widely-used Fear of COVID-19 scale (FCV-19S), testing community samples from 48 countries (N = 14,558). The findings indicate that the FCV-19S has a somewhat problematic structure, yet the one-factor solution is replicable across cultural contexts and could be used in studies that compare people who vary on gender and educational level. The validity of the scale is supported by a consistent pattern of positive correlations with perceived stress and general anxiety. However, given the unclear structure of the FCV-19S, we recommend using latent factor scores, instead of raw scores, especially in cross-cultural comparisons