A novel in silico Monte Carlo approach to optimize a PSD estimation problem. Generation of data fusion experiment rules

This article analyzes the performance of combining information from Scanning Electron Microscopy(SEM) micrographs with Static Light Scattering (SLS) measurements for retrieving the so-called ParticleSize Distribution (PSD) in terms of experimental features. The corresponding data fusion is implementedusing a novel Monte Carlo-based method consisting in a SMF (Sampling-Mapping-Filtering) approach.This approach provides an important reference to assess the strategy of the experiment for this specificproblem by means of solving an inverse problem. Furthermore, low levels of volume fraction and a PSDrepresented by log-normal distributions are considered in order to reduce processing and model errors dueto ill-posedness. The prior statistics corresponding to the SEM micrographs have been achieved by meansof the Jackknife procedure used as a resampling technique. The likelihood term considers iid normalmeasurements generated from the Local Monodisperse Approximation (LMA) and also makes use of thesame model as forward linear model, in an inversion case known as inverse crime. However, it has beenproved that the LMA performs well in practice for low fraction volume systems as considered here. ThePSD retrieval is measured in terms of improvement in precision with respect to one of the log-normalparameters in SEM micrographs, i.e., the desirability. Estimates are expressed as a function of a typicalsystem parameter such as polydispersity, as well as experimental variables, i.e., number of particles permicrograph (PPM) and noise level ε in the SLS measurements. These estimations are then analyzed bymeans of the Box-Behnken (BB) design and the response surface methodology (RSM) in order to generatea surrogate model from which rules for the optimization of the experiment are made when desirability ismaximized. Finally, a Rule-Based System (RBS) is proposed for future use.

Gene flow in three broiler chicken populations in Abeokuta using jackknife procedure

Jackknife procedure (JP) is a less biased and fascinating method of obtaining gene slow among populations. The purpose of this study was to use JP to eliminate bias associated with indirect estimators of gene slow, with microsatellite markers, it has been possible to estimate gene flow (Nm) in natural populations. To quantify Nm, in chicken populations, we used five polymorphic microsatellite markers with 115 genomic deoxyribonucleic acid (DNA) obtained from (dihybrid (DH = 37), trihybrid (TH = 32) and Anak White (AW = 46) broiler chicken populations, respectively. Through polymerase chain reaction, we amplified DNA from the broiler chicken populations, subjected amplicons to electrophoresis, fragment sizes determined and analysed across populations considering selected markers through which standardized genetic variance among sub-populations in total sample depicted as (FST) was obtained per marker for chicken population pairs. Its average across markers/population pairs was used to infer Nm, in the chicken population pairs. We used JP which is a mathematical approach that utilizes mean FST, across markers to obtain Nm in the chicken population pairs. Gene flow based on JP in chicken population pairs designated as (Nm)JP were 5.4267 (DH vs. TH), 7.0127 (TH vs. AW) and 11.7405 (DH vs. AW) and among chicken populations, (Nm)JP was 7.1969. Considering these estimates, we concluded that there was gene flow among the three broiler chicken populations examined in Abeokuta, Nigeria.

Gene flow in three broiler chicken populations in Abeokuta using jackknife procedure

Jackknife procedure (JP) is a less biased and fascinating method of obtaining gene flow among populations. The purpose of this study was to use JP to eliminate bias associated with indirect estimators of gene flow. With microsatellite markers, it has been possible to estimate gene flow (Nmo ) in natural populations. To quantify Nmo in chicken populations, we used five polymorphic microsatellite markers with 115 genomic deoxyribonucleic acid (DNA) obtained from (dihybrid (DH = 37), trihybrid (TH = 32) and Anak White (AW = 46) broiler chicken populations, respectively. Through polymerase chain reaction, we amplified DNA from the broiler chicken populations, subjected amplicons to electrophoresis, fragment sizes determined and analysed across populations considering selected markers through which standardized genetic variance among sub-populations in total sample depicted as (F)ST was obtained per marker for chicken population pairs. Its average across markers/population pairs was used to infer Nmo in the chicken population pairs. We used JP which is a mathematical approach that utilizes mean FST across markers to obtain Nmo in the chicken population pairs. Gene flow based on JP in chicken population pairs designated as (Nm)JP were 5.4267 (DH vs. TH), 7.0127 (TH vs. AW) and 11.7405 (DH vs. AW) and among chicken populations, (Nm)JP was 7.1969. Considering these estimates, we concluded that there was JP gene flow among the three broiler chicken populations examined in Abeokuta, Nigeria.

Geographical variation in Eurasian red squirrel (Sciurus vulgaris L., 1758) mandibles and the issue of subspecies-level organization: a failure of history?

Sciurus vulgaris is a widespread, highly polytypic tree squirrel species, under which a large number of subspecies have been described. This study tests the robustness of the current subspecific classification by using geometric morphometrics to quantify morphological variation in mandible shape, along with canonical variates analysis to test hypotheses of morphological distinctiveness. Patterns of mandible allometry were examined in eight out of 16 currently recognized subspecies. The significance of the discriminate functions was tested statistically, and the iterative jackknife procedure was applied to evaluate stability of the subspecies-specific discriminant functions. Applying criteria that focus on shape diagnosability, rather than mean group differences, indicates that most regional subspecific groupings show intergradations and continuity in mandible shape and size and that allometric effects on mandible shape are negligible. Evidence of a distinct subspecies confined to the Iberian Peninsula (Sciurus vulgaris infuscatus) and a discrete group originating from an extinct, 19th century population in Dorset, UK were identified based on these mandibular data. All other regional subspecific groupings were not diagnosably different. These results suggest that most red squirrel subspecies might represent non-diagnosable morphological variants whose taxonomic validity seems doubtful. More generally, our results highlight the importance of applying objective, quantitative and reproducible criteria to the issue of subspecies delimitation.

Persian leopard and wild sheep distribution modeling using the Maxent model in the Tang-e-Sayad protected area, Iran

The maximum entropy (Maxent) model was used to predict the distribution of Persian leopards and wild sheep in the Tang-e-Sayad protected area in Iran. For this purpose, eight variables, as well as 30 occurrence points of leopard and 98 points of wild sheep, were used. Two techniques, density-based occurrence points thinning and performance-based predictor variables selection were used to improve the results of the model. The model results were analyzed based on four threshold limit-based statistics (sensitivity, specificity, kappa and true skill statistics) and area under the curve (AUC), followed by determining the relative importance of variables based on the jackknife procedure. The results of threshold limit-based statistics revealed that the success of the model for distribution prediction of leopard and wild sheep were good and relatively good, respectively. According to the jackknife procedure, for wild sheep and for leopard, slope and distance to road, respectively, were the most important predictor variables. The results also indicated that the efficiency of the model did not improve by reducing the density of occurrence points for the wild sheep (AUC=0.784–0.773). However, the selection of predictor variables slightly improved the performance of the model (AUC=0.794–0.819). The results of the study also showed overlapping habitat for two species due to both human and ecological reasons for which we proposed some conservation actions such as excluding domestic grazing, controlling illegal poaching and restoration of old migratory corridors.

The models evaluating courier and messenger companies in Poland

Data Envelopment Analysis (DEA) is a well-established, popular, and often used method for efficiency evaluation of units from all sector, both commercial and non-profit organisations, of any scale of operations. Network DEA models are a relatively recent approach used to examine the efficiency of decision-making units (DMUs) having an internal structure of sub-processes. The article presents the concept of DEA network models in estimating the efficiency of courier and messenger companies with relations to their business clients. The considerations are supported by an example of data concerning leaders from the sector of couriers and messengers in Poland and one of the biggest and most popular online stores. The results are compared with the traditional DEA approach. In addition, to measure reliability for DEA scores, the jackknife procedure was performed. The author proves the usefulness of network DEA as a research and management tool.

Validation of the ALARO-0 model within the EURO-CORDEX framework

Using the regional climate model ALARO-0, the Royal Meteorological Institute of Belgium and Ghent University have performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979–2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44°. ALARO-0 is characterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989–2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature, some large biases, which are often also found in the ARPEGE results, persist. For precipitation, on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust, meaning independent of the period used to calculate them. Periods of 20 years are sampled from the 32-year simulation and used to construct the 95 % confidence interval for each score. For most scores, these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant.

Validation of the ALARO-0 model within the EURO-CORDEX framework

Using the regional climate model ALARO-0 the Royal Meteorological Institute of Belgium has performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979–2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44 °. ALARO-0 is characterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989–2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature some large biases, which are often also found in the ARPEGE results, persist. For precipitation, on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust, by which we mean independent of the period used to calculate them. Periods of 20 years are sampled from the 32 year simulation and used to construct the 95 % confidence interval for each score. For most scores these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant.

Development and Simulation Testing of a Computerized Adaptive Version of the Philadelphia Naming Test

Purpose The purpose of this study was to develop a computerized adaptive test (CAT) version of the Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996), to reduce test length while maximizing measurement precision. This article is a direct extension of a companion article (Fergadiotis, Kellough, & Hula, 2015), in which we fitted the PNT to a 1-parameter logistic item-response-theory model and examined the validity and precision of the resulting item parameter and ability score estimates. Method Using archival data collected from participants with aphasia, we simulated two PNT-CAT versions and two previously published static PNT short forms, and compared the resulting ability score estimates to estimates obtained from the full 175-item PNT. We used a jackknife procedure to maintain independence of the samples used for item estimation and CAT simulation. Results The PNT-CAT recovered full PNT scores with equal or better accuracy than the static short forms. Measurement precision was also greater for the PNT-CAT than the static short forms, though comparison of adaptive and static nonoverlapping alternate forms showed minimal differences between the two approaches. Conclusion These results suggest that CAT assessment of naming in aphasia has the potential to reduce test burden while maximizing the accuracy and precision of score estimates.