Quantum Interference of Force

We show that a quantum particle subjected to a positive force in one path of a Mach-Zehnder interferometer and a null force in the other path may receive a negative average momentum transfer when it leaves the interferometer by a particular exit. In this scenario, an ensemble of particles may receive an average momentum in the opposite direction of the applied force due to quantum interference, a behavior with no classical analogue. We discuss some experimental schemes that could verify the effect with current technology, with electrons or neutrons in Mach-Zehnder interferometers in free space and with atoms from a Bose-Einstein condensate.Comment: 5 figures. Accepted in Quantum on 2018-12-0

Using Factor Mixture Modeling to Counter Faking

Self-reports (SRs) of typical behavior are often the only existing feasible method to gather data on important drivers of human performance. In applications such as personnel selection, SRs are vulnerable to intentional distortions, often referred to as faking. A review of the literature suggests that so far, the methods proposed to address faking are unsatisfactory. In a recent breakthrough, Pavlov et al. (2019) showed that high-stakes scale scores are best modeled as a function of a) propensity to fake, b) honest scores, and c) the interaction of these two terms. Pavlov et al. did not, however, propose any method to extract honest scores in assessment settings, when only high stakes data is available. In this dissertation I investigate using factor mixture modeling (FMM) with class specific intercepts and factor loadings to this aim. I assume that responses to high stakes items are a function of the respondents’ “honest” factor scores on the attribute being measured, an unobserved categorical “tendency to fake” latent class, and their interaction. I perform simulations using parameter estimates based on Pavlov et al.’s data to determine the extent to which factor scores estimated using a two class factor analysis model outperform the current standard, a single class model. Results suggest that only under specific conditions FMM scores provide higher correlations with true factor scores compared to single class models. Moreover, empirical findings indicate that the theoretical potential of FMM to detect faking is not realized in practice, where class separations are not as defined

Bollen-Stine Bootstrapping of the Chi-Square Statistic in Structural Equation Models: The Effect of Model Size

Previous research on the accuracy of p-values for the chi-square test of model fit has been limited to small models (around 10 variables), revealing that they are accurate provided sample size is not too small. At small sample sizes (N \u3c 100), the usual p-values, obtained using asymptotic methods, are more accurate. However, asymptotic p-values incorrectly suggest that models fit poorly when the number of variables is large. We investigate whether Bollen-Stine (1992) bootstrap p-values are accurate in large models (up to 30 variables) for continuous outcomes using both normal and non-normal data. We found that as model size increases bootstrap p-values become too conservative (rejection rates are too small) and remarkably less accurate than asymptotic p-values obtained using robust methods (i.e., mean and variance corrected chi-square statistics). Further, there is a significant interaction between model size and sample size such that p-values for bootstrap are less accurate when the model is large and the sample size is small. Bollen-Stine p-values cannot be recommended to assess the fit of large models

Classificaçao imunológica das leucemias linfocíticas agudas

Dissertaçao (mestrado) -Universidade Federal do Paran

Reduced-risk insecticides in Neotropical stingless bee species: impact on survival and activity

Background: As honeybees are the main pollinator species subject to an intense research regarding effects of pesticides, other ecologically important native bee pollinators have received little attention in ecotoxicology and risk assessment of pesticides in general, and insecticides in particular, some of which are perceived as reduced-risk compounds. Here the impact of three reduced-risk insecticides – azadirachtin, spinosad, and chlorantraniliprole – was assessed in two species of stingless bees, Partamona helleri and Scaptotrigona xanthotrica, which are important native pollinators in Neotropical America. The neonicotinoid imidacloprid was used as a positive control.Results: Spinosad exhibited high oral and contact toxicities in adult workers of both species at the recommended label rates, with median survival times (LT50s) ranging from 1 to 4 h, whereas these estimates were below 15 min for imidacloprid. Azadirachtin and chlorantraniliprole exhibited low toxicity at the recommended label rates, with negligible mortality that did not allow LT50 estimation. Sublethal behavioral assessments of these two insecticides indicated that neither one of them affected the overall group activity of workers of the two species. However, both azadirachtin and chlorantraniliprole impaired individual flight take-off of P. helleri and S. xanthotrica worker bees, which may compromise foraging activity, potentially leading to reduced colony survival.Conclusion: These findings challenge the common perception of non-target safety of reduced-risk insecticides and bioinsecticides, particularly regarding native pollinator species.Keywords: behavioral impact; biopesticides; colony and individual level effects; native bee pollinators; sublethal effect