Presence of Maximal Characteristic Time in Photoluminescence Blinking of MAPbI 3 Perovskite

AbstractCurrent codes for fire protection of buildings are mainly based on the movement of adults and neglect the movement characteristic of pre-school children. Having a profound comprehension of the difference between children and adults passing bottlenecks is of great help to improve the safety levels of preschool children. This paper presents an experimental study on the bottleneck flow of pre-school children in a room. The movement characteristics of children’s and adults’ bottleneck flow are investigated with two macroscopic properties: density and speed profiles as well as microscopic characteristic time: motion activation time, relaxation time, exit travel time and time gap. Arch-like density distributions are observed both for highly motivated children and adults, while the distance between the peak density region and the exit location is shorter for children and longer for adults. Children’s movement is less flexible manifested as longer motion activation time and longer relaxation time compared to that of adults. The findings from this study could enhance the understanding of crowd dynamics among the children population and provide supports for the scientific building design for children’s facilities.

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Analysis and Simulation of Epidemic COVID-19 Curves with the Verhulst Model Applied to Statistical Inhomogeneous Age Groups

Applied Sciences ◽

10.3390/app11094159 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4159

Author(s):

Lode K. J. Vandamme ◽

Paulo R. F. Rocha

Keyword(s):

Mental Health ◽

Exponential Growth ◽

Characteristic Time ◽

Age Groups ◽

Recovery Phase ◽

Limited Growth ◽

Logistic Equations ◽

Quantitative Understanding ◽

Returning Travellers ◽

Verhulst Model

Pandemic curves, such as COVID-19, often show multiple and unpredictable contamination peaks, often called second, third and fourth waves, which are separated by wide plateaus. Here, by considering the statistical inhomogeneity of age groups, we show a quantitative understanding of the different behaviour rules to flatten a pandemic COVID-19 curve and concomitant multi-peak recurrence. The simulations are based on the Verhulst model with analytical generalized logistic equations for the limited growth. From the log–lin plot, we observe an early exponential growth proportional to . The first peak is often τgrow @ 5 d. The exponential growth is followed by a recovery phase with an exponential decay proportional to . For the characteristic time holds: . Even with isolation, outbreaks due to returning travellers can result in a recurrence of multi-peaks visible on log–lin scales. The exponential growth for the first wave is faster than for the succeeding waves, with characteristic times, τ of about 10 d. Our analysis ascertains that isolation is an efficient method in preventing contamination and enables an improved strategy for scientists, governments and the general public to timely balance between medical burdens, mental health, socio-economic and educational interests.

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Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

Annales Geophysicae ◽

10.5194/angeo-28-381-2010 ◽

2010 ◽

Vol 28 (2) ◽

pp. 381-393 ◽

Cited By ~ 10

Author(s):

L. Cai ◽

S. Y. Ma ◽

Y. L. Zhou

Keyword(s):

Neural Network ◽

Solar Wind ◽

Correlation Coefficient ◽

Characteristic Time ◽

Ring Current ◽

Wind Data ◽

Distinct Advantage ◽

Elman Network ◽

H Index ◽

Narx Neural Network

Abstract. Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW) and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min). This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring current decay which involves various decay mechanisms with ion lifetimes from tens of minutes to tens of hours. The Elman network makes feedback from hidden layer to input only one step, which is of 5 min for SYM-H index in this work and thus insufficient to catch the characteristic time length.

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Coordinate control of prostaglandin E2 synthesis and uptake by hyperosmolarity in renal medullary interstitial cells

AJP Renal Physiology ◽

10.1152/ajprenal.00426.2004 ◽

2006 ◽

Vol 290 (3) ◽

pp. F641-F649 ◽

Cited By ~ 16

Author(s):

Michael L. Pucci ◽

Shinichi Endo ◽

Teruhisa Nomura ◽

Run Lu ◽

Cho Khine ◽

...

Keyword(s):

Cell Surface ◽

Characteristic Time ◽

Water Deprivation ◽

Interstitial Cells ◽

Time Dependent ◽

Prostaglandin E ◽

Coordinate Control ◽

Time Period ◽

Cox 2 ◽

Net Release

During water deprivation, prostaglandin E2 (PGE2), formed by renal medullary interstitial cells (RMICs), feedback inhibits the actions of antidiuretic hormone. Interstitial PGE2 concentrations represent the net of both PGE2 synthesis by cyclooxygenase (COX) and PGE2 uptake by carriers such as PGT. We used cultured RMICs to examine the effects of hyperosmolarity on both PG synthesis and PG uptake in the same RMIC. RMICs expressed endogenous PGT as assessed by mRNA and immunoblotting. RMICs rapidly took up [3H]PGE2 to a level 5- to 10-fold above background and with a characteristic time-dependent “overshoot.” Inhibitory constants ( Ki) for various PGs and PGT inhibitors were similar between RMICs and the cloned rat PGT. Increasing extracellular hyperosmolarity to the range of 335–485 mosM increased the net release of PGE2 by RMICs, an effect that was concentration dependent, maximal by 24 h, reversible, and associated with increased expression of COX-2. Over the same time period, there was decreased cell-surface activity of PGT due to internalization of the transporter. With continued exposure to hyperosmolarity over 7–10 days, PGE2 release remained elevated, COX-2 returned to baseline, and PGT-mediated uptake became markedly reduced. Our findings suggest that hyperosmolarity induces coordinated changes in COX-2-mediated PGE2 synthesis and PGT-mediated PGE2 uptake in RMICs.

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Light-Induced Metastable Defects or Light-Induced Metastable H Atoms in a-Si:H Films?

MRS Proceedings ◽

10.1557/proc-467-79 ◽

1997 ◽

Vol 467 ◽

Author(s):

C. Godet

Keyword(s):

Experimental Data ◽

Characteristic Time ◽

Defect Density ◽

Hydrogenated Amorphous Silicon ◽

Exponential Time ◽

Mobile Species ◽

Hydrogenated Amorphous ◽

Two Parameter ◽

Metastable Defect ◽

Trapping Sites

ABSTRACTIn hydrogenated amorphous silicon (a-Si:H) films, the increase of the metastable defect density under high-intensity illumination is usually described by an empirical two-parameter stretched-exponential time dependence (characteristic time τSE and dispersion parameter β). In this study, a clearly different (one-parameter) analytic function is obtained from a microscopic model based on the formation of metastable H (MSH) atoms in a-Si:H films. Assuming that MSH atoms are the only mobile species, only three chemical reactions are significant : MSH are produced from doubly hydrogenated (SiH HSi) configurations and trapped either at broken bonds or Si-H bonds, corresponding respectively to light-induced annealing (LIA) and light-induced creation (LIC) of defects. Competition between trapping sites results in a saturation of N(t) at a steady-state value Nss. A one-parameter fit of this analytical function to experimental data is generally good, indicating that the use of a statistical distribution of trap energies is not necessary.

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Effect of Particle Residence Time on Particle Dispersion in a Plane Mixing Layer

Journal of Fluids Engineering ◽

10.1115/1.2910208 ◽

1993 ◽

Vol 115 (4) ◽

pp. 751-759 ◽

Cited By ~ 22

Author(s):

Tsuneaki Ishima ◽

Koichi Hishida ◽

Masanobu Maeda

Keyword(s):

Gas Phase ◽

Residence Time ◽

Time Scale ◽

Characteristic Time ◽

Mixing Layer ◽

Particle Dispersion ◽

Laser Doppler Velocimeter ◽

Characteristic Time Scale ◽

Two Phase ◽

Particle Residence Time

A particle dispersion has been experimentally investigated in a two-dimensional mixing layer with a large relative velocity between particle and gas-phase in order to clarify the effect of particle residence time on particle dispersion. Spherical glass particles 42, 72, and 135 μm in diameter were loaded directly into the origin of the shear layer. Particle number density and the velocities of both particle and gas phase were measured by a laser Doppler velocimeter with modified signal processing for two-phase flow. The results confirmed that the characteristic time scale of the coherent eddy apparently became equivalent to a shorter characteristic time scale due to a less residence time. The particle dispersion coefficients were well correlated to the extended Stokes number defined as the ratio of the particle relaxation time to the substantial eddy characteristic time scale which was evaluated by taking account of the particle residence time.

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