Prosodic parallelism explaining morphophonological variation in German

AbstractWords in German show several instances of a seemingly optional schwa-zero alternation, both in relation with inflected forms as well as in the final position of stems and simplex words, as inLarge-scale corpora are used as the main source of evidence for the verification or falsification of the hypothesis. A diverse set of nouns and adverbs involving schwa-zero alternations were studied in appropriate phrasal contexts, both from present-day Standard German and from Early New High German. Based on comprehensive corpus counts, these phrases are tested for the hypothesis of prosodic parallelism. A series of chi square tests and a generalized linear model with mixed effects demonstrate statistically that the prosodic shapes of the target word and its adjacent form are not independent of each other. The focus of the paper is on empirical evidence for

Download Full-text

Model-based detection of putative synaptic connections from spike recordings with latency and type constraints

Journal of Neurophysiology ◽

10.1152/jn.00066.2020 ◽

2020 ◽

Vol 124 (6) ◽

pp. 1588-1604

Author(s):

Naixin Ren ◽

Shinya Ito ◽

Hadi Hafizi ◽

John M. Beggs ◽

Ian H. Stevenson

Keyword(s):

Linear Model ◽

Generalized Linear Model ◽

Large Scale ◽

Statistical Problem ◽

Detection Methods ◽

Multielectrode Array ◽

Synaptic Connections ◽

Synaptic Effects ◽

Synapse Detection

Detecting synaptic connections using large-scale extracellular spike recordings is a difficult statistical problem. Here, we develop an extension of a generalized linear model that explicitly separates fast synaptic effects and slow background fluctuations in cross-correlograms between pairs of neurons while incorporating circuit properties learned from the whole network. This model outperforms two previously developed synapse detection methods in the simulated networks and recovers plausible connections from hundreds of neurons in in vitro multielectrode array data.

Download Full-text

Joint modeling of a linear mixed effects model for selfesteem from mean ages 13 to 22 and a generalized linear model for anxiety disorder at mean age 33

Journal of Medical Statistics and Informatics ◽

10.7243/2053-7662-3-1 ◽

2015 ◽

Vol 3 (1) ◽

pp. 1 ◽

Cited By ~ 5

Author(s):

Henian Chen ◽

Yangxin Huang ◽

Nanhua Zhang

Keyword(s):

Anxiety Disorder ◽

Linear Model ◽

Generalized Linear Model ◽

Joint Modeling ◽

Mixed Effects ◽

Mixed Effects Model ◽

Linear Mixed Effects Model ◽

Linear Mixed Effects

Download Full-text

Exploring the Association between Compliance with Measures to Prevent the Spread of COVID-19 and Big Five Traits with Bayesian Generalized Linear Model

10.31234/osf.io/sf93m ◽

2021 ◽

Author(s):

Hyemin Han

Keyword(s):

Regression Model ◽

Linear Model ◽

Big Five ◽

Generalized Linear Model ◽

Regression Models ◽

Large Scale ◽

Negative Association ◽

Data Driven ◽

Big Five Traits ◽

Bayesian Generalized Linear Model

Research has examined the association between people’s compliance with measures to prevent the spread of COVID-19 and personality traits. However, previous studies were conducted with relatively small-size datasets and employed frequentist analysis that does not allow data-driven model exploration. To address the limitations, a large-scale international dataset, COVIDiSTRESS Global Survey dataset, was explored with Bayesian generalized linear model that enables identification of the best regression model. The best regression models predicting participants’ compliance with Big Five traits were explored. The findings demonstrated first, all Big Five traits, except extroversion, were positively associated with compliance with general measures and distancing. Second, neuroticism, extroversion, and agreeableness were positively associated with the perceived cost of complying with the measures while conscientiousness showed negative association. The findings and the implications of the present study were discussed.

Download Full-text

Potency of Dioscorea sansibarensis (Dioscoreaceae) Leaf Eluates on Callosobruchus chinensis, Linnaeus 1758 (Coleoptera: Bruchidae) in the Protection of Phaseolus vulgaris (Fabaceae)

Tanzania Journal of Science ◽

10.4314/tjs.v47i3.40 ◽

2021 ◽

Vol 47 (3) ◽

pp. 1330-1337

Author(s):

Godfrey Mauti

Keyword(s):

Liquid Chromatography ◽

Phaseolus Vulgaris ◽

Linear Model ◽

Generalized Linear Model ◽

Positive Control ◽

Egg Laying ◽

Callosobruchus Chinensis ◽

Leaf Extracts ◽

Chi Square ◽

Vacuum Liquid Chromatography

Post-harvest losses of stored Phaseolus vulgaris to the bean weevil Callosobruchus chinensis have reached levels of significant concern. Governments and health organisations propose the discovery of reliable, healthy and biodegradable pesticides with higher selectivity and a broad spectrum. This study presents investigations on the activities of Dioscorea sansibarensis leaf extracts on the mortality of C. chinensis and reduction of their egg-laying ability. Laboratory experiments under Completely Randomized Design (CRD) were carried out to determine the mortality and anti-oviposition activity of the vacuum liquid chromatography (VLC) eluates of n-hexane (HE), chloroform (CE), ethyl acetate (EE), n-butanol (BE) and methanol (BE) at different concentrations. Bioassay data were subjected to nonparametric statistical analysis and a generalized linear model at p = 0.05. Statistical results showed that the VLC eluates had a mortality activity of 88.01% (R2 = 0.8801). Treatment by 0.025 g of HE and 0.075 g of CE had 9.60 and 11.50, respectively at p = 0.181. These mortality records were high as to 0.1 g of ME, 0.05 g of EE and 0.075 g of BE that recorded 8.55, 8.45 and 7.80, respectively. Treatments by 0.05 g of CE, 0.025 g of HE, 0.05 g of EE and the positive control recorded mortality of 10.50, 9.60, 8.45 and 8.35, respectively. The highest mortality was observed in the treatment by 0.075 g of HE and 0.1 g of HE with 12.85 and 13.70, respectively at p = 0.377. The VLC eluates had an anti-oviposition activity of 24.98% (R2 = 0.2498) on the C. chinensis. The generalized linear model reported Wald Chi-Square values of 4.363; p = 0.037, 0.711; p = 0.399, 9.125; p = 0.003, 4.363; p = 0.037 on the treatment by 0.025 g of CE, 0.05 g of EE, 0.075 g of BE and 0.1 g of ME, respectively. At p = 0.051, 0.1 g of CE and the positive control attained oviposition of 89.25 and 96.75 respectively. The study presents the first documentation of the lethal activity of D. sansibarensis on the C. chinensis pulse beetle. This could help in the development of Integrated Pest Management (IPM) and could help in the elimination or suppression of the infestation. Keywords: anti-oviposition, Callosobruchus chinensis, Dioscorea sansibarensis leaf, mortality, Phaseolus vulgaris, vacuum liquid chromatography (VLC) eluates.

Download Full-text

Model-based detection of putative synaptic connections from spike recordings with latency and type constraints

10.1101/2020.02.12.944496 ◽

2020 ◽

Author(s):

Naixin Ren ◽

Shinya Ito ◽

Hadi Hafizi ◽

John M. Beggs ◽

Ian H. Stevenson

Keyword(s):

Linear Model ◽

Generalized Linear Model ◽

Large Scale ◽

Hypothesis Test ◽

Detection Methods ◽

Multielectrode Array ◽

Synaptic Connections ◽

Model Framework ◽

Synapse Detection

AbstractDetecting synaptic connections using large-scale extracellular spike recordings presents a statistical challenge. While previous methods often treat the detection of each putative connection as a separate hypothesis test, here we develop a modeling approach that infers synaptic connections while incorporating circuit properties learned from the whole network. We use an extension of the Generalized Linear Model framework to describe the cross-correlograms between pairs of neurons and separate correlograms into two parts: a slowly varying effect due to background fluctuations and a fast, transient effect due to the synapse. We then use the observations from all putative connections in the recording to estimate two network properties: the presynaptic neuron type (excitatory or inhibitory) and the relationship between synaptic latency and distance between neurons. Constraining the presynaptic neuron’s type, synaptic latencies, and time constants improves synapse detection. In data from simulated networks, this model outperforms two previously developed synapse detection methods, especially on the weak connections. We also apply our model to in vitro multielectrode array recordings from mouse somatosensory cortex. Here our model automatically recovers plausible connections from hundreds of neurons, and the properties of the putative connections are largely consistent with previous research.New & NoteworthyDetecting synaptic connections using large-scale extracellular spike recordings is a difficult statistical problem. Here we develop an extension of a Generalized Linear Model that explicitly separates fast synaptic effects and slow background fluctuations in cross-correlograms between pairs of neurons while incorporating circuit properties learned from the whole network. This model outperforms two previously developed synapse detection methods in the simulated networks, and recovers plausible connections from hundreds of neurons in in vitro multielectrode array data.

Download Full-text