Field evaluation of effectiveness of the BG-Sentinel, a new trap for capturing adult Aedes aegypti (Diptera: Culicidae)

In recent years, the development of new tools to gather field information about vector ecological parameters has increased. This report evaluated the BG-Sentinel Trap (BGS-Trap), a promising new attempt to improve collection of the dengue vector, Aedes aegypti. The efficacy of the BGS-Trap was compared with the CDC backpack aspirator, one of the commonest used methods for capturing adult mosquitoes. BGS-Traps captured significantly more Ae. aegypti males (chi2 = 21.774, df = 1, P < 0.05) and females (chi2 = 56.007, df = 1, P < 0.05) than CDC aspirator during all days of field collection. However, CDC aspirator was significantly more efficient to capture Culex quinquefasciatus males (chi2 = 5.681, df = 1, P < 0.05) and females (chi2 = 6.553, df = 1, P < 0.05). BGS-Traps captured host-seeking females (varying between 68.75 to 89.8%) in detriment of females in other behavioral and physiological stages. BGS-Traps proved to be efficient and can be used for monitoring adult mosquito populations.

A Public Service Gap: Capturing Contexts in a Comparative Approach of Street-Level Bureaucracy

Studies of street-level bureaucracy have introduced a variety of conceptualizations, research approaches, and causal inferences. While this research has produced several insights, the impact of variety in the institutional context has not been adequately explored. We present the construct of a public service gap as a way to incorporate contextual factors and facilitate comparison. This construct addresses the differences between what is asked of and what is offered to public servants working at the street level. The heuristic enables the systematic capture of macro- and meso-contextual influences, thus enhancing comparative research on street-level bureaucracy.

Capturing and Organizing Prior Student Learning with the OCW Backpack

The purpose of this paper is to present an approach for students to have non-traditional learning assessed for credit and introduce a tool that facilitates this process. The OCW Backpack system can connect self-learners with KNEXT assessment services to obtain college credit for prior learning. An ex post facto study based on historical data collected over the past two years at Kaplan University (KU) is presented to validate the portfolio assessment process. Cumulative GPA was compared for students who received experiential credit for learning derived from personal or professional experience with a matched sample of students with no experiential learning credits. The study found that students who received experiential credits perform better than the matched sample students on GPA. The findings validate the KU portfolio assessment process. Additionally, the results support the capability of the OCW Backpack to capture the critical information necessary to evaluate non-traditional learning for university credit.

Histopathological examination of nerve samples from pure neural leprosy patients: obtaining maximum information to improve diagnostic efficiency

Nerve biopsy examination is an important auxiliary procedure for diagnosing pure neural leprosy (PNL). When acid-fast bacilli (AFB) are not detected in the nerve sample, the value of other nonspecific histological alterations should be considered along with pertinent clinical, electroneuromyographical and laboratory data (the detection of Mycobacterium leprae DNA with polymerase chain reaction and the detection of serum anti-phenolic glycolipid 1 antibodies) to support a possible or probable PNL diagnosis. Three hundred forty nerve samples [144 from PNL patients and 196 from patients with non-leprosy peripheral neuropathies (NLN)] were examined. Both AFB-negative and AFB-positive PNL samples had more frequent histopathological alterations (epithelioid granulomas, mononuclear infiltrates, fibrosis, perineurial and subperineurial oedema and decreased numbers of myelinated fibres) than the NLN group. Multivariate analysis revealed that independently, mononuclear infiltrate and perineurial fibrosis were more common in the PNL group and were able to correctly classify AFB-negative PNL samples. These results indicate that even in the absence of AFB, these histopathological nerve alterations may justify a PNL diagnosis when observed in conjunction with pertinent clinical, epidemiological and laboratory data.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Are the maximum hardness and minimum polarizability principles always obeyed in nontotally symmetric vibrations?

An overview is given on a study which showed that not only in chemical reactions but also in the favorable case of nontotally symmetric vibrations where the chemical and external potentials keep approximately constant, the generalized maximum hardness principle (GMHP) and generalized minimum polarizability principle (GMPP) may not be obeyed. A method that allows an accurate determination of the nontotally symmetric molecular distortions with more marked GMPP or anti-GMPP character through diagonalization of the polarizability Hessian matrix is introduced

A new chance-constrained maximum capture location problem

The paper presents a new model based on the basic Maximum Capture model,MAXCAP. The New Chance Constrained Maximum Capture modelintroduces astochastic threshold constraint, which recognises the fact that a facilitycan be open only if a minimum level of demand is captured. A metaheuristicbased on MAX MIN ANT system and TABU search procedure is presented tosolve the model. This is the first time that the MAX MIN ANT system isadapted to solve a location problem. Computational experience and anapplication to 55 node network are also presented.

Maximum-likelihood estimation of specific differential phase and attenuation in rain

Precise estimation of propagation parameters inprecipitation media is of interest to improve the performanceof communications systems and in remote sensing applications.In this paper, we present maximum-likelihood estimators ofspecific attenuation and specific differential phase in rain. Themodel used for obtaining the cited estimators assumes coherentpropagation, reflection symmetry of the medium, and Gaussianstatistics of the scattering matrix measurements. No assumptionsabout the microphysical properties of the medium are needed.The performance of the estimators is evaluated through simulateddata. Results show negligible estimators bias and variances closeto Cramer–Rao bounds.

Avaliação de Panicum maximum jacq. para tolerância ao alumínio em solução nutritiva

Em condições controladas de temperatura, umidade e iluminação, 30 genótipos de Panicum maximum foram avaliados para a verificação de tolerância às doses de alumínio de 0, 12 e 24 mg L-1 em solução nutritiva. Os efeitos do alumínio na inibição do alongamento radicular e no índice de tolerância possibilitaram a estratificação dos genótipos em três categorias: tolerantes, intermediários e sensíveis. A maior parte dos genótipos apresentou de média a baixa tolerância ao alumínio, destacando-se, como os mais tolerantes, os genótipos K191, T95, T84, T91 e Centenário e, como os mais sensíveis, os genótipos Centauro, K68, K214 e T46.