No phylogenomic support for a Cenozoic origin of the "living fossil" Isoetes.

PREMISE: The isoetalean lineage has a rich fossil record that extends to the Devonian, but the age of the living clade is unclear. Recent results indicate that it is young, from the Cenozoic, whereas earlier work based on less data from a denser taxon sampling yielded Mesozoic median ages. METHODS: We analyzed node ages in Isoetes using two genomic data sets (plastome and nuclear ribosomal cistron), three clock models implemented in MrBayes (ILN, WN, and TK02 models), and a conservative approach to calibration. RESULTS: While topological results were consistently resolved in Isoetes estimated crown group ages range from the latest Paleozoic (mid-Permian) to the Mesozoic depending on data type and clock model. The oldest estimates were retrieved using the autocorrelated TK02 clock model. An (early) Cenozoic age was only obtained under one specific condition (plastome data analyzed with the uncorrelated ILN clock model). That same plastome data set also yielded the oldest (mid-Permian) age estimate when analyzed with the autocorrelated TK02 clock model. Adding the highly divergent, recently established sister species Isoetes wormaldii to the data set approximately doubled the average median node depth to the Isoetes crown group. CONCLUSIONS: There is no consistent support for a Cenozoic origin of the living clade Isoetes. We obtained seemingly well-founded, yet strongly deviating results depending on data type and clock model. The single most important future improvement is probably to add calibration points, which requires an improved understanding of the isoetalean fossil record or alternative bases for calibration.

Estimating the optimal timing of surgery by imputing potential outcomes.

Hypoplastic left heart syndrome is a congenital anomaly that is uniformly fatal in infancy without immediate treatment. The standard treatment consists of an initial Norwood procedure (stage 1) followed some months later by stage 2 palliation (S2P). The ideal timing of the S2P is uncertain. The Single Ventricle Reconstruction Trial (SVRT) randomized the procedure used in the initial Norwood operation, leaving the timing of the S2P to the discretion of the surgical team. To estimate the causal effect of the timing of S2P, we propose to impute the potential post-S2P survival outcomes using statistical models under the Rubin Causal Model framework. With this approach, it is straightforward to estimate the causal effect of S2P timing on post-S2P survival by directly comparing the imputed potential outcomes. Specifically, we consider a lognormal model and a restricted cubic spline model, evaluating their performance in Monte Carlo studies. When applied to the SVRT data, the models give somewhat different imputed values, but both support the conclusion that the optimal time for the S2P is at 6 months after the Norwood procedure.

BER and Channel Capacity Performance of an FSO Communication System over Atmospheric Turbulence with Different Types of Noise.

The propagation performance of a free-space optical (FSO) communication system in an atmospheric environment is restricted and degraded due to the influence of atmospheric turbulence. In this paper, both the lognormal and Gamma-Gamma channel models are employed to characterize this turbulence under weak-to-strong conditions. In addition, the average bit error rate and average channel capacity of an FSO communication system under the influence of background noise, thermal noise and quantum noise (resulting from the environment, the device, manual operation, etc.) are considered. Moreover, the comparison of system performance under different turbulence conditions and various noises are conducted. Simulation results reveal that thermal noise has a dominant effect on the FSO system. In addition, both the channel parameters and the system parameters have a significant influence on the performance of an FSO communication system.

Sigma-Lognormal Modeling of Speech.

Human movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition to robotics, health care to sports, and beyond. Previous speech motor models were proposed to understand how speech movement is produced and how the resulting speech varies when some parameters are changed. However, the inverse approach, in which the muscular response parameters and the subject's age are derived from real continuous speech, is not possible with such models. Instead, in the handwriting field, the kinematic theory of rapid human movements and its associated Sigma-lognormal model have been applied successfully to obtain the muscular response parameters. This work presents a speech kinematics-based model that can be used to study, analyze, and reconstruct complex speech kinematics in a simplified manner. A method based on the kinematic theory of rapid human movements and its associated Sigma-lognormal model are applied to describe and to parameterize the asymptotic impulse response of the neuromuscular networks involved in speech as a response to a neuromotor command. The method used to carry out transformations from formants to a movement observation is also presented. Experiments carried out with the (English) VTR-TIMIT database and the (German) Saarbrucken Voice Database, including people of different ages, with and without laryngeal pathologies, corroborate the link between the extracted parameters and aging, on the one hand, and the proportion between the first and second formants required in applying the kinematic theory of rapid human movements, on the other. The results should drive innovative developments in the modeling and understanding of speech kinematics.

Central and Peripheral Shoulder Fatigue Pre-screening Using the Sigma-Lognormal Model: A Proof of Concept.

BACKGROUND: Clinical tests for detecting central and peripheral shoulder fatigue are limited. The discrimination of these two types of fatigue is necessary to better adapt recovery intervention. The Kinematic Theory of Rapid Human Movements describes the neuromotor impulse response using lognormal functions and has many applications in pathology detection. The ideal motor control is modeled and a change in the neuromuscular system is reflected in parameters extracted according to this theory. OBJECTIVE: The objective of this study was to assess whether a shoulder neuromuscular fatigue could be detected through parameters describing the theory, if there is the possibility to discriminate central from peripheral fatigue, and which handwriting test gives the most relevant information on fatigue. METHODS: Twenty healthy participants performed two sessions of fast stroke handwriting on a tablet, before and after a shoulder fatigue. The fatigue was in internal rotation for one session and in external rotation during the other session. The drawings consisted of simple strokes, triangles, horizontal, and vertical oscillations. Parameters of these strokes were extracted according to the Sigma-Lognormal model of the Kinematic Theory. The evolution of each participant was analyzed through a U-Mann-Whitney test for individual comparisons. A Hotelling's T 2-test and a U-Mann-Whitney test were also performed on all participants to assess the group evolution after fatigue. Moreover, a correlation among parameters was calculated through Spearman coefficients to assess intrinsic parameters properties of each handwriting test. RESULTS: Central and peripheral parameters were statistically different before and after fatigue with a possibility to discriminate them. Participants had various responses to fatigue. However, when considering the group, parameters related to the motor program execution showed significant increase in the handwriting tests after shoulder fatigue. The test of simple strokes permits to know more specifically where the fatigue comes from, whereas the oscillations tests were the most sensitive to fatigue. CONCLUSION: The results of this study suggest that the Sigma-Lognormal model of the Kinematic Theory is an innovative approach for fatigue detection with discrimination between the central and peripheral systems. Overall, there is a possibility to implement the setting for clinics and sports personalized follow-up.

Cyclist-vehicle crash modeling with measurement error in traffic exposure.

Exposure measures are always among the explanatory variables of any crash model. Regardless of the technique used to model crash, the mean crash frequency will increase with an increase in exposure since more crashes are likely to occur at higher exposure. For cyclist-vehicle crash models, bike and vehicle exposure measures are essential for an accurate and reliable estimate of the cyclist crash risk. However, traffic exposure measures are an example of variables that are measured with error. Generally, measurement error in regression estimates has three effects: 1) produce bias in parameter estimation for statistical models, 2) lead to a loss of explanation power, 3) mask important features of the data. This study proposes a full Bayesian Poisson Lognormal crash models that account for measurement error in traffic exposure measures (i.e., Vehicle Kilometers Travelled and Bike Kilometers Travelled). The underlying approach is to adjust the traffic exposure measures for measurement error to improve the accuracy of the crash model and crash model estimates. The full Bayesian models are developed using data for 134 traffic analysis zones (TAZs) in the city of Vancouver, Canada. The results show that Poisson Lognormal models that account for measurement error have a better fit for the modeled cyclist-vehicle crash data compared to traditional Poisson Lognormal models. The estimates of the Poisson Lognormal model that accounts for measurement error are consistent, with traditional Poisson Lognormal models' estimates except for the BKT and VKT estimates. Estimates of the BKT and VKT increased after introducing measurement error, which indicates an underestimation (downward bias) to BKT and VKT estimates in case of overlooking measurement error.

Kinematic analysis of fast pen strokes in children with ADHD.

In this study, we aimed to determine whether a new measure of fine motor skills, the Pen Stroke Test (PST), can discriminate between children with and without attention-deficit/hyperactivity disorder (ADHD). Twelve children with ADHD and 12 controls age 8-11 were asked to produce handwriting strokes on a digitizer. The sigma-lognormal model derived from the Kinematic Theory of rapid human movements was used to analyze the strokes. Standard measurements of fine motor skills and handwriting were also obtained. Children with ADHD demonstrated poorer motor planning (t0, D) and execution (nbLog) and greater variability in motor control (SNR/nbLog) than did controls. Parameters extracted from the PST were significantly correlated with performance on other motor and handwriting measures. This study provides preliminary evidence that the PST may be useful as a tool for rapidly detecting motor skill problems in the context of ADHD.

Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model.

Colorectal cancer (CRC) is the third most common cancer worldwide. Its incidence is still increasing, and the mortality rate is high. New therapeutic and prognostic strategies are urgently needed. It became increasingly recognized that the gut microbiota composition differs significantly between healthy people and CRC patients. Thus, identifying the difference between gut microbiota of the healthy people and CRC patients is fundamental to understand these microbes' functional roles in the development of CRC. We studied the microbial community structure of a CRC metagenomic dataset of 156 patients and healthy controls, and analyzed the diversity, differentially abundant bacteria, and co-occurrence networks. We applied a modified zero-inflated lognormal (ZIL) model for estimating the relative abundance. We found that the abundance of genera: Anaerostipes, Bilophila, Catenibacterium, Coprococcus, Desulfovibrio, Flavonifractor, Porphyromonas, Pseudoflavonifractor, and Weissella was significantly different between the healthy and CRC groups. We also found that bacteria such as Streptococcus, Parvimonas, Collinsella, and Citrobacter were uniquely co-occurring within the CRC patients. In addition, we found that the microbial diversity of healthy controls is significantly higher than that of the CRC patients, which indicated a significant negative correlation between gut microbiota diversity and the stage of CRC. Collectively, our results strengthened the view that individual microbes as well as the overall structure of gut microbiota were co-evolving with CRC.

Is the safety-in-numbers effect still observed in areas with low pedestrian activities? A case study of a suburban area in the United States.

In previous studies, the safety-in-numbers effect has been found, which is a phenomenon that when the number of pedestrians or cyclists increases, their crash rates decrease. The previous studies used data from highly populated areas. It is questionable that the safety-in-numbers effect is still observed in areas with a low population density and small number of pedestrians. Thus, this study aims at analyzing pedestrian crashes in a suburban area in the United States and exploring if the safety-in-numbers effect is also observed. We employ a Bayesian random-parameter Poisson-lognormal model to evaluate the safety-in-numbers effects of each intersection, which can account for the heterogeneity across the observations. The results show that the safety-in-numbers effect were found only at 32 intersections out of 219. The intersections with the safety-in-numbers effect have relatively larger pedestrian activities whereas those without the safety-in-numbers effect have extremely low pedestrian activities. It is concluded that just encouraging walking might result in serious pedestrian safety issues in a suburban area without sufficient pedestrian activities. Therefore, it is plausible to provide safe walking environment first with proven countermeasures and a people-oriented policy rather than motor-oriented. After safe walking environments are guaranteed and when people recognize that walking is safe, more people will consider walking for short-distance trips. Eventually, increased pedestrian activities will result in the safety-in-numbers effects and walking will be even further safer.

Predicting crash frequency for multi-vehicle collision types using multivariate Poisson-lognormal spatial model: A comparative analysis.

According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables.

A multivariate spatial crash frequency model for identifying sites with promise based on crash types.

Many studies have proposed the use of a systemic approach to identify sites with promise (SWiPs). Proponents of the systemic approach to road safety management suggest that it is more effective in reducing crash frequency than the traditional hot spot approach. The systemic approach aims to identify SWiPs by crash type(s) and, therefore, effectively connects crashes to their corresponding countermeasures. Nevertheless, a major challenge to implementing this approach is the low precision of crash frequency models, which results from the systemic approach considering subsets (crash types) of total crashes leading to higher variability in modeling outcomes. This study responds to the need for more precise statistical output and proposes a multivariate spatial model for simultaneously modeling crash frequencies for different crash types. The multivariate spatial model not only induces a multivariate correlation structure between crash types at the same site, but also spatial correlation among adjacent sites to enhance model precision. This study utilized crash, traffic, and roadway inventory data on rural two-lane highways in Pennsylvania to construct and test the multivariate spatial model. Four models with and without the multivariate and spatial correlations were tested and compared. The results show that the model that considers both multivariate and spatial correlation has the best fit. Moreover, it was found that the multivariate correlation plays a stronger role than the spatial correlation when modeling crash frequencies in terms of different crash types.

PLNseq: a multivariate Poisson lognormal distribution for high-throughput matched RNA-sequencing read count data.

High-throughput RNA-sequencing (RNA-seq) technology provides an attractive platform for gene expression analysis. In many experimental settings, RNA-seq read counts are measured from matched samples or taken from the same subject under multiple treatment conditions. The induced correlation therefore should be evaluated and taken into account in deriving tests of differential expression. We proposed a novel method 'PLNseq', which uses a multivariate Poisson lognormal distribution to model matched read count data. The correlation is directly modeled through Gaussian random effects, and inferences are made by likelihood methods. A three-stage numerical algorithm is developed to estimate unknown parameters and conduct differential expression analysis. Results using simulated data demonstrate that our method performs reasonably well in terms of parameter estimation, DE analysis power, and robustness. PLNseq also has better control of FDRs than the benchmarks edgeR and DESeq2 in the situations where the correlation is different across the genes but can still be accurately estimated. Furthermore, direct evaluation of correlation through PLNseq enables us to develop a new and more powerful test for DE analysis. Application to a lung cancer study is provided to illustrate the practical utilities of our method. An R package implementing the method is also publicly available.

Multi-level hot zone identification for pedestrian safety.

According to the National Highway Traffic Safety Administration (NHTSA), while fatalities from traffic crashes have decreased, the proportion of pedestrian fatalities has steadily increased from 11% to 14% over the past decade. This study aims at identifying two zonal levels factors. The first is to identify hot zones at which pedestrian crashes occurs, while the second are zones where crash-involved pedestrians came from. Bayesian Poisson lognormal simultaneous equation spatial error model (BPLSESEM) was estimated and revealed significant factors for the two target variables. Then, PSIs (potential for safety improvements) were computed using the model. Subsequently, a novel hot zone identification method was suggested to combine both hot zones from where vulnerable pedestrians originated with hot zones where many pedestrian crashes occur. For the former zones, targeted safety education and awareness campaigns can be provided as countermeasures whereas area-wide engineering treatments and enforcement may be effective safety treatments for the latter ones. Thus, it is expected that practitioners are able to suggest appropriate safety treatments for pedestrian crashes using the method and results from this study.

Utilizing Response Times in Computerized Classification Testing.

A well-known approach in computerized mastery testing is to combine the Sequential Probability Ratio Test (SPRT) stopping rule with item selection to maximize Fisher information at the mastery threshold. This article proposes a new approach in which a time limit is defined for the test and examinees' response times are considered in both item selection and test termination. Item selection is performed by maximizing Fisher information per time unit, rather than Fisher information itself. The test is terminated once the SPRT makes a classification decision, the time limit is exceeded, or there is no remaining item that has a high enough probability of being answered before the time limit. In a simulation study, the new procedure showed a substantial reduction in average testing time while slightly improving classification accuracy compared with the original method. In addition, the new procedure reduced the percentage of examinees who exceeded the time limit.

Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.

This study presents multi-level analyses for single- and multi-vehicle crashes on a mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were investigated. Both aggregate and disaggregate models for the two crash conditions were developed. Five years of crash data were used in the aggregate investigation, while the disaggregate models utilized one year of crash data along with real-time traffic and weather data. For the aggregate analyses, safety performance functions were developed for the purpose of revealing the contributing factors for each crash type. Two methodologies, a Bayesian bivariate Poisson-lognormal model and a Bayesian hierarchical Poisson model with correlated random effects, were estimated to simultaneously analyze the two crash conditions with consideration of possible correlations. Except for the factors related to geometric characteristics, two exposure parameters (annual average daily traffic and segment length) were included. Two different sets of significant explanatory and exposure variables were identified for the single-vehicle (SV) and multi-vehicle (MV) crashes. It was found that the Bayesian bivariate Poisson-lognormal model is superior to the Bayesian hierarchical Poisson model, the former with a substantially lower DIC and more significant variables. In addition to the aggregate analyses, microscopic real-time crash risk evaluation models were developed for the two crash conditions. Multi-level Bayesian logistic regression models were estimated with the random parameters accounting for seasonal variations, crash-unit-level diversity and segment-level random effects capturing unobserved heterogeneity caused by the geometric characteristics. The model results indicate that the effects of the selected variables on crash occurrence vary across seasons and crash units; and that geometric characteristic variables contribute to the segment variations: the more unobserved heterogeneity have been accounted, the better classification ability. Potential applications of the modeling results from both analysis approaches are discussed.

Time-dependence between upper arm muscles activity during rapid movements: observation of the proportional effects predicted by the kinematic theory.

Rapid human movements can be assimilated to the output of a neuromuscular system with an impulse response modeled by a Delta-Lognormal equation. In such a model, the main assumption concerns the cumulative time delays of the response as it propagates toward the effector following a command. To verify the validity of this assumption, delays between bursts in electromyographic (EMG) signals of agonist and antagonist muscles activated during a rapid hand movement were investigated. Delays were measured between the surface EMG signals of six muscles of the upper limb during single rapid handwriting strokes. From EMG envelopes, regressions were obtained between the timing of the burst of activity produced by each monitored muscle. High correlation coefficients were obtained supporting the proportionality of the cumulative time delays, the basic hypothesis of the Delta-Lognormal model. A paradigm governing the sequence of muscle activities in a rapid movement could, in the long run, be useful for applications dealing with the analysis and synthesis of human movements.

Diversidade de um cerrado sensu stricto com base em modelos de abundância de espécies / Diversity of a cerrado sensu stricto based on species abundance models

Este estudo teve como objetivo avaliar a diversidade de uma comunidade lenhosa de cerrado sensu stricto no sudeste de Goiás, a partir de modelos de distribuição de abundância de espécies. Foram alocadas aleatoriamente 10 parcelas de 20 x 20 m em um trecho de 4 km2 de cerrado sensu stricto preservado, onde todos os indivíduos com DB ≥ 5 cm (diâmetro a altura da base = 30 cm do nível do solo) foram amostrados e identificados. A comunidade apresentou ajuste aos modelos de vara-quebrada (χ 2 = 37,62, P = 0,99) e normal-logarítmico (χ 2 = 2,61, P = 0,63), que refletem equilíbrio ecológico. O modelo normal-logarítmico foi o de melhor ajuste, mostrando que as espécies se distribuem ao longo de mosaicos de recursos, fato corroborado pela diferenciação na distribuição das espécies a partir de uma análise de gradientes (análise de correspondência segmentada - DCA).

This study aimed to evaluate the diversity of the woody community of a cerrado sensu stricto in southeastern of Goiás State (Brazil), through species abundance models. Ten plots of 20 x 20 m were randomly allocated in an undisturbed cerrado sensu stricto area of 4 km2, and all individuals with DSH ≥ 5 cm (diameter at soil height = 30 cm aboveground) were sampled and identified. The broken-stick (χ 2 = 37.62, P = 0.99) and lognormal (χ 2 = 2.61, P = 0.63) models fits to community, reflecting an ecological equilibrium. The lognormal model was the most adequate, showing that the species are distributed along resource patches, in agreement to the pattern found in the gradient analysis (Detrended correspondence analysis - DCA)

Chironomidae assemblage structure in relation to organic enrichment of an aquatic environment / Estrutura da assembléia de chironomidae em relação ao enriquecimento orgânico de um ambiente aquático

In this study we determined the taxonomic diversity of larval Chironomidae upstream and downstream to discharges of the sewage treatment plant (STP) from Agro-industrial District of Anápolis, State of Goiás, Brazil. Additionally, we evaluated the use of the lognormal distribution as a measure of biotic integrity of this system. The Chironomidae communities were sampled in three sites, upstream and downstream of the discharge of the sewage treatment plant (STP). We fitted the truncate lognormal distribution based on a nonlinear regression of the datasets using least squares as loss function in an iterative quasi-Newton procedure. The total of 21,498 individuals were sampled, from 24 Chironomidae genera, Chironomus, Polypedilum, Rheotanytarsus e Thienemanniella, with 73.9 percent, 14.4 percent, 7.1 percent and 4.5 percent, respectively, of all analyzed community; they are generally considered resistant to organic pollution. The assemblage of the site upstream was described for a truncate lognormal distribution. The extreme increase in abundance of some genera in the first site downstream produced a distribution not fitted to lognormal. The second site downstream however, permits a good fit to lognormal, probably due to the decrease in abundance of the dominant groups. These data substantiate the hypothesis that Chironomidae community is not suitably characterized by lognormal distribution at disturbed environments. Consequently, these aquatic communities were ecological disordered by organic pollution which caused the lost of sensible species and the dominance of those tolerants to this sort of impact. Additionally, the study highlighted the distribution lognormal approach as a valuable method to assess environmental impacts.

A diversidade taxonômica da comunidade de Chironomidae em ambientes aquáticos poluídos e não-poluídos foi estudada na área de influência do Distrito Agroindustrial de Anápolis, Anápolis, GO, avaliando-se a distribuição lognormal como indicador da integridade biótica desses sistemas. Larvas de Chironomidae foram coletadas em três pontos a montante e jusante do lançamento do efluente da estação de tratamento de esgoto desse distrito industrial. O ajuste do modelo de distribuição foi realizado utilizando-se o modelo de regressão não-linear, adotando procedimento iterativo quasi-Newton. Foram amostrados 21.498 indivíduos de 24 gêneros de Chironomidae. Chironomus, Polypedilum, Rheotanytarsus e Thienemanniella foram os mais abundantes, visto que são geralmente considerados resistentes à poluição orgânica. A assembléia do ponto a montante do lançamento foi bem descrita pelo modelo de distribuição lognormal truncada. O grande aumento da abundância de alguns gêneros no primeiro ponto a jusante impossibilitou o ajuste da distribuição lognormal truncada. O segundo a jusante, no entanto, possibilitou bom ajuste, possivelmente devido à diminuição na abundância dos grupos dominantes. Esses dados corroboram a hipótese de que as assembléias de chironomideos em ambientes não alterados são bem descritas por uma distribuição lognormal, o que não pode ser observado em ambientes degradados. Desta forma, evidenciou-se que a poluição orgânica causa desestruturação das comunidades aquáticas desse sistema, com perda das espécies sensíveis e dominância das tolerantes a esse tipo de impacto. Além disso, fica evidente que a distribuição lognormal pode ser considerada uma valiosa abordagem para avaliação de impactos ambientais.