Extremes of Gaussian fields with a smooth random variance

2016 ◽  
Vol 110 ◽  
pp. 185-190 ◽  
Author(s):  
Goran Popivoda ◽  
Siniša Stamatović
Keyword(s):  
Gaussian Fields ◽  
Extremes Of Gaussian Fields ◽  
Random Variance

PEMANFAATAN KULIT KAYU GEMOR (Alseodaphne sp.) DAN CANGKANG KEMIRI (Aleurites molucca) UNTUK OBAT NYAMUK ALAMI

2011 ◽  
Vol 3 (2) ◽  
pp. 13
Author(s):  
Budi Tri Cahyana ◽  
Andri Taruna Rachmadi
Keyword(s):  
Human Health ◽  
Chemical Compound ◽  
Variance Analysis ◽  
Force Analysis ◽  
Mosquito Coil ◽  
Research Product ◽  
Economic View ◽  
Hazelnut Shell ◽  
Random Variance ◽  
Main Material

Blood fever and Chikungunya cases in Indonesia are increasing annually. For preventing the mosquios, people use mosquito coil which is contain dangerous chemical compound. This research has successly created a natural mosquito coil with gemor bark and hazelnut fruit shell as the main material. Gemor bark is positive containing alcaloid,tanin, phenolk, flvonoid, triterpnoid and glycocydic compounds which are natural bioinsecticide. As formulation the comparison of gemor bark and hazelnut shell as follow :100% : 0 %  ; 80 % : 20 % ; 65 % : 35 % ; 50 % : 50 % ; 35 % : 65% and 20 % : 80% were used. Base one random variance analysis, the best formula was the using of gemor bark in 50%, 35% and  20% of concentration. The mosquitos killing force analysis was using the LT50 for 6 days with 5 diferent concentrations. The result showed that 50 %  of gemor bark was significantly influenced in the killing force. From the economic view, the producion of this coil was cheaper then the same product in the maket. Base on all the result, the research product is applicable in mass producion and safe for human health and the environment.Keywords: gemor bark , hazelnut fruit shell ,  mosquito coil, natural ,  ecofriendly

scholarly journals Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys

2021 ◽  
Author(s):  
Robin E Upham ◽  
Michael L Brown ◽  
Lee Whittaker
Keyword(s):  
Power Spectrum ◽  
Random Noise ◽  
Power Spectra ◽  
Stage Iv ◽  
Wishart Distribution ◽  
Weak Lensing ◽  
Dependence Structure ◽  
Gaussian Fields ◽  
Non Gaussian ◽  
Parameter Constraints

Abstract We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid-like combined tomographic power spectrum analysis of weak lensing, galaxy clustering and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from Stage IV weak lensing surveys.

scholarly journals Derivatives of local times for some Gaussian fields II

2021 ◽  
Vol 172 ◽  
pp. 109063
Author(s):  
Minhao Hong ◽  
Fangjun Xu
Keyword(s):  
Local Times ◽  
Gaussian Fields ◽  
Derivatives Of

Computer simulations of the effects of different synaptic input systems on motor unit recruitment

1993 ◽  
Vol 70 (5) ◽  
pp. 1827-1840 ◽  
Author(s):  
C. J. Heckman ◽  
M. D. Binder
Keyword(s):  
Motor Unit ◽  
Computer Simulations ◽  
Synaptic Input ◽  
Reciprocal Inhibition ◽  
Excitatory Input ◽  
Medial Gastrocnemius ◽  
Synaptic Inputs ◽  
Monte Carlo Techniques ◽  
Recruitment Order ◽  
Random Variance

1. The effects of four different synaptic input systems on the recruitment order within a mammalian motoneuron pool were investigated using computer simulations. The synaptic inputs and motor unit properties in the model were based as closely as possible on the available experimental data for the cat medial gastrocnemius pool and muscle. Monte Carlo techniques were employed to add random variance to the motor unit thresholds and forces and to sample the resulting recruitment orders. 2. The effects of the synaptic inputs on recruitment order depended on how they modified the range of recruitment thresholds established by differences in the intrinsic current thresholds of the motoneurons. Application of a uniform synaptic input to the pool (i.e., distributed equally to all motoneurons) resulted in a recruitment sequence that was quite stable even with the addition of large amounts of random variance. With 50% added random variance, the recruitment reversals did not exceed 8%. 3. The simulated monosynaptic input from homonymous Ia afferent fibers generated a twofold expansion of the range of recruitment thresholds beyond that attributed to the differences in the intrinsic current thresholds. The Ia input generated a small reduction in the number of recruitment reversals due to random variance (6% reversals at 50% random variance). The simulated monosynaptic vestibulospinal input generated a twofold compression of the range of recruitment thresholds that exerted a modest increase in the number of recruitment reversals (12% reversals at 50% random variance). 4. In comparison with the modest effects of the two monosynaptic inputs, the simulated oligosynpatic rubrospinal excitatory input exerted a nine-fold compression in the recruitment threshold range that resulted in a recruitment sequence that was highly sensitive to random variance. With 50% added random variance, the sequence became nearly random (40% reversals). 5. Reciprocal Ia inhibition was simulated by a uniform distribution within the pool, but its effects on recruitment order were highly dependent on the distribution of the excitatory input. Reciprocal inhibition exerted only minor effects on recruitment order when combined with the Ia or vestibulospinal inputs. However, when the excitatory drive was supplied by the rubrospinal input, even small amounts of reciprocal inhibition were sufficient to completely reverse the normal recruitment sequence. 6. The simulated monosynaptic Ia input was highly effective in compensating for the disruptive effects of rubrospinal excitation on recruitment order. Even a small Ia bias combined with the rubrospinal excitation was sufficient to halve the effects of random variance and to restore the normal recruitment sequence in the presence of rather large amounts of reciprocal inhibition.(ABSTRACT TRUNCATED AT 400 WORDS)

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