Bayesian inference methods to calibrate crowd dynamics models for safety applications

Two new species, Xylodon bambusinus and X. xinpingensis, are proposed based on morphological and molecular evidences. Both species share the annual growth habit, resupinate basidiomata and monomitic hyphal system with clamped, colorless generative hyphae, smooth, thin-walled basidiospores, but X. bambusinus is characterized by the smooth to tuberculate hymenial surface, presence of capitate and fusiform cystidia, broad ellipsoid basidiospores, while X. xinpingensis by the reticulate hymenophore with cream hymenial surface, and subglobose basidiospores (4.5–6 × 3.5–5 µm). Sequences of ITS and LSU nrRNA gene regions of the studied samples were generated, and phylogenetic analyses were performed with maximum likelihood, maximum parsimony and Bayesian inference methods. The phylogenetic analyses based on molecular data of ITS and ITS+nLSU sequences showed that X. bambusinus was sister to X. subclavatus, while X. xinpingensis grouped with X. astrocystidiatus and X. paradoxus. The nLSU dataset revealed that X. bambusinus grouped with X. asperus and X. brevisetus with lower supports, and that X. xinpingensis grouped with X. astrocystidiatus and X. paradoxus and then with X. rimosissimus without supports. Both morphological and molecular evidences confirmed the placement of two new species in Xylodon. Description and figures from the new species and a key to the known species of Xylodon from China are presented.

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Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK

PLoS ONE ◽

10.1371/journal.pone.0258968 ◽

2021 ◽

Vol 16 (11) ◽

pp. e0258968

Author(s):

Patrick Pietzonka ◽

Erik Brorson ◽

William Bankes ◽

Michael E. Cates ◽

Robert L. Jack ◽

...

Keyword(s):

Bayesian Inference ◽

Time Window ◽

Fold Increase ◽

Strong Increase ◽

Mortality Data ◽

New Variant ◽

Model Evidence ◽

Age Structured ◽

The Uk ◽

Inference Methods

We apply Bayesian inference methods to a suite of distinct compartmental models of generalised SEIR type, in which diagnosis and quarantine are included via extra compartments. We investigate the evidence for a change in lethality of COVID-19 in late autumn 2020 in the UK, using age-structured, weekly national aggregate data for cases and mortalities. Models that allow a (step-like or graded) change in infection fatality rate (IFR) have consistently higher model evidence than those without. Moreover, they all infer a close to two-fold increase in IFR. This value lies well above most previously available estimates. However, the same models consistently infer that, most probably, the increase in IFR preceded the time window during which variant B.1.1.7 (alpha) became the dominant strain in the UK. Therefore, according to our models, the caseload and mortality data do not offer unequivocal evidence for higher lethality of a new variant. We compare these results for the UK with similar models for Germany and France, which also show increases in inferred IFR during the same period, despite the even later arrival of new variants in those countries. We argue that while the new variant(s) may be one contributing cause of a large increase in IFR in the UK in autumn 2020, other factors, such as seasonality, or pressure on health services, are likely to also have contributed.

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Patternising Students’ performance in post graduate examinations using bayesian inference methods – a case study

The International Conference on "Information Science & Technology For Sustainability & Innovation" ◽

10.3850/978-981-09-4426-1_041 ◽

2015 ◽

Author(s):

Y. N. Ananth ◽

N. S. Narahari

Keyword(s):

Bayesian Inference ◽

Post Graduate ◽

Inference Methods

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Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior

Modern Applied Science ◽

10.5539/mas.v10n7p1 ◽

2016 ◽

Vol 10 (7) ◽

pp. 1

Author(s):

Mohammed Mahmod Shuaib

Keyword(s):

Quantitative Measurement ◽

Force Model ◽

Social Force ◽

Lane Changing ◽

Crowd Dynamics ◽

Proposed Model ◽

The Social ◽

Lane Formation ◽

Dynamics Models ◽

The Impact

Incorporating decision-making capability as an intelligence aspect into crowd dynamics models is crucial factor for reproducing realistic pedestrian flow. Crowd dynamics models are still suffering from poor representation of essential behaviors such as lane changing behavior. In this article, we provide the simulated pedestrians in the social force model more intelligence as an extension to the pedestrian’s investigation capability in bidirectional walkways, to let the model appear more representative of what actually happens in reality. In the proposed model, the lane’s structure is modeled as social network. Thereby, the simulated pedestrians with inconvenient walking can detect the available lanes inside his environment, investigate their attractions, and then make decisions to join the most attractive one. Simulations are performed to validate the work qualitatively by tracing the behavior of the simulated pedestrians and studying the impact of this behavior on lane formation. Finally, a quantitative measurement is used to study the effect of our contribution on the pedestrians’ efficiency of motion.

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Nonlocal Crowd Dynamics Models for Several Populations

Acta Mathematica Scientia ◽

10.1016/s0252-9602(12)60011-3 ◽

2012 ◽

Vol 32 (1) ◽

pp. 177-196 ◽

Cited By ~ 45

Author(s):

Rinaldo M. Colombo ◽

Magali Lécureux-Mercier

Keyword(s):

Crowd Dynamics ◽

Dynamics Models

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Kinematic calibration of serial manipulators using Bayesian inference

Robotica ◽

10.1017/s0263574718000024 ◽

2018 ◽

Vol 36 (5) ◽

pp. 738-766 ◽

Cited By ~ 1

Author(s):

Elie Shammas ◽

Shadi Najjar

Keyword(s):

Bayesian Inference ◽

Measurement Data ◽

Calibration Method ◽

Confidence Bounds ◽

Open Chain ◽

Robotic Arms ◽

Serial Manipulators ◽

Regression Methods ◽

Three Degree Of Freedom ◽

Inference Methods

SUMMARYIn this paper, a new calibration method for open-chain robotic arms is developed. By incorporating both prior parameter information and artifact measurement data, and by taking recourse to Bayesian inference methods, not only are the robot kinematic parameters updated but also confidence bounds are computed for all measurement data. In other words, for future measurement data not only the most likely end-effector configuration is estimated but also the uncertainty represented as 95% confidence bounds of that pose is computed. To validate the proposed calibration method, a three degree-of-freedom robotic arm was designed, constructed, and calibrated using both typical regression methods and the proposed calibration method. The results of an extensive set of experiments are presented to gauge the accuracy and utility of the proposed calibration method.

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An Investigation Capability Model for Bidirectional Pedestrian Flow

Modern Applied Science ◽

10.5539/mas.v9n12p88 ◽

2015 ◽

Vol 9 (12) ◽

pp. 88 ◽

Cited By ~ 6

Author(s):

Mohammed Mahmod Shuaib ◽

Zarita Zainuddin

Keyword(s):

Average Density ◽

Fundamental Diagram ◽

Crowd Dynamics ◽

Self Organized ◽

Pedestrian Traffic ◽

Representative Model ◽

Tactical Decision ◽

Dynamics Models ◽

The Impact ◽

Bidirectional Flow

The pedestrian traffic flow in bidirectional walkways is very crucial aspect influenced by the level of pedestrians’ decisions. In this article, the authors show that the simulated pedestrians walking based on crowd dynamics models of low level mechanism of navigation (operational level) are short-sighted in avoiding counter flow. Such limitation resulted in unrealistic formation of motion in bidirectional flow, that the movement is less systematic and the lanes are less coherent than what in real situation. To obtain a more representative model, the authors improve the investigation capability model as a tactical decision model to be incorporated into a crowd dynamics model to reproduce better formation of motion. This is accomplished by granting the pedestrians the ability to investigate the macroscopic behaviors in their investigation areas and make decisions for convenience flow. The new model considers the average density and flow inside such areas and models their effect on the pedestrians' decisions. Simulations are performed to validate the work qualitatively by tracing the behavior of the simulated pedestrians and studying the impact of this behavior on the self-organized phenomenon: lane formation. Furthermore, the fundamental diagram of bidirectional flow is reproduced and compared with experimental fundamental diagrams.

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Gloeodontia yunnanensis sp. nov. (Russulales, Basidiomycota) from China, evidenced by morphological characters and phylogenetic analyses

Phytotaxa ◽

10.11646/phytotaxa.432.2.1 ◽

2020 ◽

Vol 432 (2) ◽

pp. 111-118

Author(s):

LU CHEN ◽

ZHENG-JUN SHI ◽

CHUN-HUA WU ◽

CHANG-LIN ZHAO

Keyword(s):

Bayesian Inference ◽

Maximum Likelihood ◽

Maximum Parsimony ◽

Phylogenetic Analyses ◽

Strong Support ◽

Morphological Characters ◽

Fungal Species ◽

Monophyletic Lineage ◽

Thin Walled ◽

Inference Methods

A new wood-inhabiting fungal species, Gloeodontia yunnanensis, is proposed based on a combination of morphological features and DNA data. The species is characterized by an annual, resupinate basidiomata with smooth hymenial surface, a monomitic hyphal system with thin-walled, clamped generative hyphae and obclavate cystidia and subglobose to globose, hyaline, thick-walled, asperulate, strongly amyloid, acyanophilous basidiospores measuring 3.3–4.3 × 2.5–3.5 µm. Sequences of ITS and 28S gene regions of the studied samples were generated and phylogenetic analyses were performed with Maximum Likelihood, Maximum Parsimony and Bayesian Inference methods. The analyses based on ITS+28S sequences showed that G. yunnanensis nested in the Gloeodontia clade and formed a monophyletic lineage with strong support (100% BS, 100% BP, 1.00 BPP).

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