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Combined with finite element numerical simulation analysis, the hot-spin forming technology of cylindrical AZ80 magnesium alloy parts was studied in the paper. The multipass hot-spin forming of magnesium alloy shell parts was simulated by the ABAQUS software to analyze the stress and strain distribution and change during spinning for the preliminary test process parameters in the magnesium alloy spinning test. Then, the process parameters were optimized during the hot spinning test, especially the matching relationship between temperature parameter and thinning rate parameter, and the hot spinning magnesium alloy shell parts with the expected technical specifications were finished.

It is difficult to predict student graduation status in a college. Higher education needs to predict student behavior from active students so that it can be seen the failure factor of students who do not graduate on time. Data mining classification techniques used to predict students are using artificial neural networks. Artificial neural network is one method to predict student graduation. This researcher tries to apply artificial neural network methods using genetic algorithms to predict student graduation. In this study using the learning rate parameter 0.1 with optimization using genetic algorithms then evaluating to get accuracy. The results of this study get an accuracy value for artificial neural network models of 71.48% and accuracy for artificial neural network models based on genetic algorithms by 99.33% with an accuracy difference of 27.85%.

Epidemics of wheat blast, caused the Triticum pathotype of Magnaporthe oryzae, were studied in the Santa Cruz del la Sierra region of Bolivia to quantify and compare the temporal dynamics of the disease under different growing conditions. Six plots of a susceptible wheat cultivar were planted at Cuatro Cañadas (CC), Okinawa 1 (OK1), and Okinawa 2 (OK2) in 2015. Spike blast incidence (INC) and severity (SEV) and leaf blast severity (LEAF) were quantified in each plot at regular intervals on a 10 × 10 grid (n = 100 clusters of spikes), beginning at head emergence (Feekes growth stage 10.5), for a total of nine assessments at CC, six at OK1, and six at OK2. Spike blast increased over time for 20 to 30 days before approaching a mean INC of 100% and a mean SEV of 60 to 75%. The logistic model was the most appropriate for describing the temporal dynamics of spike blast. The highest absolute rates of disease increase occurred earliest at OK1 and latest at OK2, and in all cases it coincided with major rain events. Estimated y0 values (initial blast intensity) were significantly (P < 0.05) higher at OK1 than at CC or OK2, whereas rL values (the logistic rate parameter) were significantly higher at OK2 than at CC or OK1. It took about 10 fewer days for SEV to reach 10, 15, or 20% at OK1 compared with OK2 and CC. Based on survival analyses, the survivor functions for time to 10, 15 and 20% SEV (ts) were significantly different between OK1 and the other locations, with the probabilities of SEV reaching the thresholds being highest at OK1. LEAF at 21 days after Feekes 10.5 had a significant effect on ts at OK1. For every 5% increase in LEAF, the chance of SEV reaching the thresholds by day 21 increased by 30 to 55%.

Oscillatory behavior in tissue biology is ubiquitous and may be observed in the form of either chemical or mechanical signals. We present here and solve a mechanical cell model that exhibits oscillations emerging from delayed viscoelastic rheological laws. These include a time delay between the mechanical response and the rest-length changes, which evolve proportionally to the delayed cell deformation and use a remodeling rate parameter. We show that different regimes (no oscillatory response, sustained oscillations, and unstable oscillations) are obtained for different values of the delay or the remodeling rate. The results are analytically demonstrated in a one-dimensional problem with one and two cells that are represented by simple line elements. Oscillations of the cell deformations are obtained whenever different delays coexist, or when the delay is size-dependent. We also extend our results to a multicellular two-dimensional vertex model that includes the same rheological law, and which inherits the presence of critical values of the delay or remodeling rate. We numerically show that indeed the size-dependent rest-length changes induce oscillations in the cell shapes and areas.

The geometry and frictional properties of a fault system are key parameters required to understand its seismic behavior. The Main Himalayan Thrust in Nepal is the type example of a continental megathrust and forms part of a fault system which accommodates a significant fraction of India‐Eurasia convergence. Despite extensive study of this zone of shortening, the geometry of the fault system remains controversial. Here, we use interseismic, coseismic, and postseismic geodetic data in Nepal to investigate the proposed downdip geometries. We use interseismic and coseismic data from previous studies, acquired before and during the 2015 urn:x-wiley:jgrb:media:jgrb53987:jgrb53987-math-0001 7.8 Gorkha earthquake. We then supplement these by processing our own postseismic deformation data, acquired following the Gorkha earthquake. We find that kinematic modeling of geodetic data alone cannot easily distinguish between the previously proposed geometries. We therefore develop a mechanical joint coseismic‐postseismic slip inversion which simultaneously solves for the distribution of coseismic slip and rate‐strengthening friction parameters. We run this inversion using the proposed geometries and find that they are all capable of explaining the majority of geodetic data. We find values for the rate parameter, urn:x-wiley:jgrb:media:jgrb53987:jgrb53987-math-0002, from the rate‐and‐state friction law that are between 0.8 and urn:x-wiley:jgrb:media:jgrb53987:jgrb53987-math-0003, depending on the geometry used. These values are in agreement with results from laboratory studies and those inferred from other earthquakes. We suggest that the limitations of earthquake cycle geodesy partly explain the continued controversy over the geometry and role of various faults in the Nepal Himalaya.

Several methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihood-based as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMA-CUSUM multi-chart schemes to detect changes in disease incidence. Multi-chart is a combination of several single charts that detects changes in a process and have been shown to have elegant properties in the sense that they are fast in detecting changes in a process as well as being computationally less expensive. Simulation results show that the multi-CUSUM chart is faster than EWMA and EWMA-CUSUM multi-charts in detecting shifts in the rate parameter. A real illustration with health data is used to demonstrate the efficiency of the schemes.

In this paper, we define a fractional negative binomial process FNBP by replacing the Poisson process by a fractional Poisson process FPP in the gamma subordinated form of the negative binomial process. It is shown that the one-dimensional distributions of the FPP and the FNBP are not infinitely divisible. Also, the space fractional Pólya process SFPP is defined by replacing the rate parameter λ by a gamma random variable in the definition of the space fractional Poisson process. The properties of the FNBP and the SFPP and the connections to PDEs governing the density of the FNBP and the SFPP are also investigated.

The performance of resultant topological structure of Kohonen Self Organizing Map SOM is highly dependent of the learning rate and neighborhood parameters. In literature there are plenty many different types of approaches to and proposals for those parameters. It has been investigated that in general the learning rate and neighborhood parameters are data independent and predefined before the training period. Here in this paper a novel approach has been proposed to change the learning rate parameter according to the interaction of neurons with data. During training, the worst matching neuron also tracked and used to trace the formation of topological structure of SOM. A slight modification on conventional learning rate with proposed method has a considerable influence on resultant topologies in a positive way. The effects of this approach have been tested with the real world problem and different synthetic data.

Dieback disease by the fungus Botryodiplodia theobromae in Jabon seedlings (Anthocephalus cadamba) inhibits the regeneration of Jabon plant. Synthetic fungicides utilization to several problems such as residue on the environment and pathogen resistance. Chitosan is a potential natural compound used as an alternative to control plant disease.This research aims to examine the effectiveness of chitosan to control B. theobromae as causal agent of dieback on Jabon seedlings and to examine the effect of chitosan to control the viscosity of dieback disease on Jabon seedlings. The results showed that the chitosan solution can decrease the severity of disease in Jabon seedlings. However, it was different with the disease incidence rate parameter. Chitosan solution was not significantly affecting the disease because B. theobromae caused dieback symptoms on Jabon seedlings. The most effective treatment was chitosan solution with a concentration of 0.1% before inoculation with the severity of the disease by 25%. Chitosan solution viscosity was responsible in affecting the percentage of dieback disease in Jabon seeds. The higher the viscosity of chitosan, the higher the percentage of dieback disease attacks. The best viscosity to suppress the development of dieback disease on Jabon seedlings was 8.80 with 7.90% attack.Key words: Anthocephalus cadamba , Botryodiplodia theobromae, chitosan, dieback.

BackgroundCardiac fibrillation is thought to be maintained by rotational activity, with pivoting regions called phase singularities (PSs). Despite a century of research, no clear quantitative framework exists to model the fundamental processes responsible for the continuous formation and destruction of rotors in fibrillation.ObjectiveWe conducted a multi-modality, multi-species study of AF/VF under the hypothesis that PS formation/destruction in fibrillation can be modelled as self-regenerating renewal processes, producing exponential distributions of inter-event times governed by constant rate-parameters defined by the prevailing properties of the system.MethodsPS formation/destruction was studied and cross-validated in 5 models, using basket recordings and optical mapping from: i) human persistent AF (n = 20), ii) tachypaced sheep AF (n = 5), iii) rat AF (n = 4), iv) rat VF (n = 11) and v) computer simulated AF (SIM). Hilbert phase maps were constructed. PS lifetime data were fitted by exponential probability distribution functions (PDFs) computed using maximum entropy theory, and the rate parameter (λ) determined. A systematic review was conducted to cross-validate with source data from literature.ResultsPS destruction/formation distributions showed good fits to an exponential in all systems (R2≥ 0.90). In humans,λ= 4.6%/ms (95%CI,4.3,4.9)), sheep 4.4%/ms (95%CI,4.1,4.7)), rat AF 38%/ms (95%CI,22,55), rat VF 46%/ms (95%CI,31.2,60.2) and SIM 5.4%/ms (95%CI,4.1,6.7). All PS distributions identified through systematic review were exponential with λ comparable to experimental data.ConclusionThese results provide a universal quantitative framework to explain rotor formation and destruction in AF/VF, and a platform for therapeutic advances in cardiac fibrillation.

In this modern era, restaurants are becoming very popular, especially in big cities. However, this can lead to density or queues of visitors at a restaurant, which should be avoided during the current Covid-19 pandemic. So that accurate information that can predict the density of restaurant will be very useful. In predicting the density of restaurants, data processing on the number of visitors obtained from one of the restaurants is carried out using artificial intelligence in the form of LSTM (Long Short Term Memory) RNN (Recurrent Neural Network). The results of the research on Recurrent Neural Network based on LSTM (Long Short Term Memory) at the best learning rate parameter of 0.001 and a maximum epoch of 2000 resulted in an MSE value of 0.00000278 on the training data and 0.0069 on the test data

Diversification of assets by an investor offers reduced exposure to risk compared to investing in a single asset. A multi-asset option gives an investor this advantage as its payout depends on the overall performance of several underlying assets. This study uses an information-based model to derive an approximate price for European call multi-asset options. The single asset price is derived using the risk-neutral pricing approach, and the multi-asset case uses the notion of comonotonicity. A numerical illustration is looked at to validate the theoretical results and to show the accuracy of the information-based model. The results show that prices from the information-based model provide a close fit to the empirical prices using a suitable information flow rate parameter. Hence, by making use of the information available in the market, an investor can price multi-asset European call options.

Sparsity and missing data problems are very common in spatiotemporal traffic data collected from various sensing systems. Making accurate imputation is critical to many applications in intelligent transportation systems. In this paper, we formulate the missing data imputation problem in spatiotemporal traffic data in a low-rank tensor completion (LRTC) framework and define a novel truncated nuclear norm (TNN) on traffic tensors of location × day × time of day. In particular, we introduce an universal rate parameter to control the degree of truncation on all tensor modes in the proposed LRTC-TNN model, and this allows us to better characterize the hidden patterns in spatiotemporal traffic data. Based on the framework of the Alternating Direction Method of Multipliers (ADMM), we present an efficient algorithm to obtain the optimal solution for each variable. We conduct numerical experiments on four spatiotemporal traffic data sets, and our results show that the proposed LRTC-TNN model outperforms many state-of-the-art imputation models with missing rates/patterns. Moreover, the proposed model also outperforms other baseline models in extreme missing scenarios.

Significance Understanding the structure and function of the human brain at a cellular level is a fundamental aim of neuroscience. Tremendous progress has been made in recent years based on different in vivo and ex vivo approaches, including major advances in brain MRI. However, uncertainties remain in determining how brain MRI measurements relate to the brain’s underlying cellular composition. In this paper we use a recently developed MRI technique, quantitative gradient recalled echo (qGRE), and information on gene profiles in the human brain available from the Allen Human Brain Atlas. We demonstrate that qGRE and related MRI techniques can be used to probe the underlying cellular composition of the human brain in vivo., fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.

We present a new, efficient algorithm for inferring, from time-series data or high-throughput data (e.g., flow cytometry), stochastic rate parameters for chemical reaction network models. Our algorithm combines the Gillespie stochastic simulation algorithm (including approximate variants such as tau-leaping) with the cross-entropy method. Also, it can work with incomplete datasets missing some model species, and with multiple datasets originating from experiment repetitions. We evaluate our algorithm on a number of challenging case studies, including bistable systems (Schlogl’s and toggle switch) and experimental data.

The wake behind a sphere, rotating about an axis aligned with the streamwise direction, has been experimentally investigated in a low-velocity water tunnel using LIF visualizations and PIV measurements. The measurements focused on the evolution of the flow regimes that appear depending on two control parameters, namely the Reynolds number $Re$ and the dimensionless rotation or swirl rate $\Omega$, which is the ratio of the maximum azimuthal velocity of the body to the free stream velocity. In the present investigation, we cover the range of $Re$ smaller than 400 and $\Omega$ from 0 and 4. Different wakes regimes such as an axisymmetric flow, a low helical state and a high helical mode are represented in the ($Re$, $\Omega$) parameter plane.

We conducted a series of experiments to explore the rate and state frictional properties of gabbro at conditions thought to be representative of slow slip events (SSEs) in subduction zones. The experiments were conducted using a heated direct shear apparatus. We tested both solid and simulated gouge samples at low effective normal stress (5-30 MPa) over a broad range of temperatures (20–600°C) under dry and hydrated conditions. In tests performed on dry solid samples we observed stable sliding at low temperatures (20–150°C), stick-slip at high temperatures (350–600°C) and a transitional “episodic slow slip” behavior at intermediate temperatures (200–300°C). In tests performed on dry gouge samples we observed stable sliding at all temperatures. Under hydrated conditions, the gouge samples exhibited episodic slow slip and stick-slip behavior at temperatures between 300–500°C. Our results show a decrease in the rate parameter (a– b) with temperature for both solid and gouge samples; friction transitions from velocity-strengthening to velocity-weakening at temperature of about 150°C for both solid and gouge samples. We do not observe transition to velocity-strengthening friction at the high end of the tested temperature range. Our results suggest that the occurrence of slow slip events and the downdip limit of the seismogenic zone on subduction megathrusts cannot be solely explained by the temperature dependence of frictional properties of gabbro. Further experimental studies are needed to evaluate the effects of water fugacity and compositional heterogeneity (e.g., the presence of phyllosilicates) on frictional stability of subduction megathrusts. This article is protected by copyright. All rights reserved.

This paper studies the stability and Hopf bifurcation in a class of high-dimension neural network involving the discrete and distributed delays under a new framework. By introducing some virtual neurons to the original system, the impact of distributed delay can be described in a simplified way via an equivalent new model. This paper extends the existing works on neural networks to high-dimension cases, which is much closer to complex and real neural networks. Here, we first analyze the Hopf bifurcation in this special class of high dimensional model with weak delay kernel from two aspects: one is induced by the time delay, the other is induced by a rate parameter, to reveal the roles of discrete and distributed delays on stability and bifurcation. Sufficient conditions for keeping the original system to be stable, and undergoing the Hopf bifurcation are obtained. Besides, this new framework can also apply to deal with the case of the strong delay kernel and corresponding analysis for different dynamical behaviors is provided. Finally, the simulation results are presented to justify the validity of our theoretical analysis.

Fault slip and healing history may crucially affect the fault seismogenic potential in the earthquake nucleation regime. Here we report direct shear friction tests on simulated gouges derived from a carbonate fault breccia, and from a clay/carbonate fault-core gouge, retrieved from a surface exposure of the Longmenshan Fault Zone (LFZ) which hosted the 2008 Wenchuan earthquake. The experiments were conducted under dry and hydrothermal conditions, at temperatures up to 140°C, at an effective normal stress of 50 MPa, and involved sequential velocity-stepping (VS), slide-hold-slide (SHS), and velocity-stepping stages. Dry tests performed on breccia-derived samples showed no dependence of (quasi) steady state friction (μss) on SHS or VS history, and a log linear relation between transient peak healing (Δμpk) and hold time, or classical “Dieterich-type” healing behavior. By contrast, all experiments conducted under hydrothermal conditions were characterized by “non-Dieterich” healing behavior. This included (1) an increase in μss upon resliding after a hold period and (2) an increase in friction rate parameter (a − b), after SHS testing. Comparison with previous results suggests that the healing behavior seen in our wet tests may be attributed to solution transfer processes occurring during hold periods. Our findings imply that the shallow portions of faults with carbonate/clay-rich cores (e.g., the LFZ) can heal much faster than previously recognized, while the upper limit of the seismogenic zone may migrate to deeper levels during interseismic periods. These effects have important implications for understanding the seismic cycle in tectonically active carbonate terrains.

Hyperbranched polymers (HBPs) formed by a self-condensing vinyl copolymerization, SCVCP, of monofunctional monomers M gradually fed into a reactor containing inimers AB*, which had been charged initially, were investigated using a kinetic model. Under the assumption that no cyclization occurred during polymerization, changes in the average degree of polymerization (DP), the degree-of-polymerization dispersity, the degree of branching (DB), and the number of structural units in the hyperbranched copolymers at different feed rates of monomers M were calculated by a generating function method. The distribution of the degree of polymerization could be narrowed with the addition of monomers M, and the degree-of-polymerization dispersity was increased slightly at a slower feed rate parameter of M, ϕ. A higher DB of the HBPs could be obtained at a slower feed rate and a specific stopping ratio of M, θ. For instance, a final DB of approximately 0.62 was attained at ϕ = 0.2 and θ = 1.2, which was higher than the maximum DB of 0.5 attained in a batch system with monomers M at θ = 0.6.

The relation between the strength law rate parameter and the observed rate effect from full-flow penetrometer soundings performed at different penetration velocities is discussed and examined herein through an analytical investigation. It is shown, using numerical results of steady-state (continuous) penetrations, that the shear strength and global penetration resistance follow a similar law in which the shear strength and penetration resistance increase linearly with the logarithm of shear strain and penetration velocity, respectively. However, the strain rate parameter that is associated with the in situ penetration is found to be different from the conventional laboratory-based strain rate factor when considering the logarithmic relation between strength and rate. Consequently, previous suggestions to estimate the laboratory-based strength rate parameter as equal to the in situ rate parameter can only be considered a first-order approximation. Analytical examination of the energy terms involved in the plasticity solution, under the relaxing assumption of a constant plastic flow field, has led to the development of a simplified expression that resulted in an in-situ-based rate parameter of µ/(1 + 5µ) (where µ is the conventional laboratory-based strength rate parameter). Comparison of the numerically derived values with the simplified analytical expression shows good agreement, suggesting that this relation may help establish the soil rate strength parameter from full-flow penetration tests.

To classify the diagnosis of dengue fever is not easy, an accurate accuracy is needed for doctors and health workers in making a decision related to the diagnosis of dengue fever. In the classification of diagnosis of dengue fever, the Neural Network is used as the model applied. To implement the Neural Network there are several parameters that we must determine such as learning rate and momentum, the problem is the absence of standard guidelines in determining the parameters to be used in this method whom the experimental method is used. For this reason, a method that can solve the problem is needed, with the parameters obtained can be optimized. The solution that can be applied with applying the Genetic Algorithm (GA) on the Neural Network, in order to optimize the learning rate parameter value and momentum. The results obtained are apparently the application of optimization techniques with Genetic Algorithms which can make it easier to find parameter values optimally and can increase the accuracy value in the Neural Network algorithm, thus the model obtained can be used for doctors and health workers in determining the classification of dengue fever diagnosis.

Black women tend to be diagnosed with breast cancer at a more advanced stage than whites and subsequently experience elevated breast cancer mortality. We sought to determine whether there are racial differences in tumor natural history that contribute to these disparities. We used the University of Wisconsin Breast Cancer Simulation Model, a validated member of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network, to evaluate the contribution of racial differences in tumor natural history to observed disparities in breast cancer incidence. We fit eight natural history parameters in race-specific models by calibrating to the observed race- and stage-specific 1975-2000 U.S. incidence rates, while accounting for known racial variation in population structure, underlying risk of breast cancer, screening mammography utilization, and mortality from other causes. The best fit models indicated that a number of natural history parameters must vary between blacks and whites to reproduce the observed stage-specific incidence patterns. The mean of the tumor growth rate parameter was 63.6 % higher for blacks than whites (0.18, SE 0.04 vs. 0.11, SE 0.02). The fraction of tumors considered highly aggressive based on their tendency to metastasize at a small size was 2.2 times greater among blacks than whites (0.41, SE 0.009 vs. 0.019, SE 0.008). Based on our simulation model, breast tumors in blacks grow faster and are more likely to metastasize earlier than tumors in whites. These differences suggest that targeted prevention and detection strategies that go beyond equalizing access to mammography may be needed to eliminate breast cancer disparities.

In this communication, we consider the stationary problem of a non-linear parabolic system which arises in the context of dry-land vegetation. In the first part, we examine the existence and multiplicity of biomass stationary solutions, in terms of the precipitation rate parameter p, for a localized simplification of the system, with non-homogeneous rate of biomass loss. In fact, we show that under appropriate conditions on fixed parameters of the problem, multiple positive solutions exist for a range of the parameter p. In the second part, we consider the case of an idealized “oasis”, ω ⊂⊂ Ω, where we study the transition of the surface-water height in a neighborhood of the set ω

Effect of pH change on the shell thickness of calcium carbonate hollow particles was investigated. Calcium carbonate hollow particles were synthesized at different pH change rates by Carbon dioxide bubbling into a solution. And influence of pH change rate on the shell thickness was estimated by observing SEM images of cross section of hollow particles. pH change curve could be divided into two stages, before and after the point where pH changes rapidly, and could express each stage with the approximated curve. Rate parameters of pH change rate were determined from these approximated curves, and the relation with shell thickness was investigated. As a result, it has become clear that thickness of hollow particles is expressible by the rate parameter of approximation curve corresponding to the first stage which is characterized as the process from start of bubbling to the point where shell is formed.

This Paper studies the effect of redial calls attempt on answer seize rate parameter and we show new modeling of ASR. In previous analysis of ASR only the expected value of successful calls was expressed as ASR value. ASR is the most important parameter in the teletraffic measurement. Because it has one by one relation between charging and subscriber's satisfaction. The ASR parameter expresses the successfully rate in all of the our trying at the communication set (subscriber-switch-transfer to access the desired result. Then studying about it is very important.

Traditional approaches to ecosystem modelling have relied on spatially homogeneous approximations to interaction, growth and death. More recently, spatial interaction and dispersal have also been considered. While these leads to certain changes in fine-scale community dynamics, their effect is sometimes fairly minimal, and demographic scenarios in which this difference is important have not been systematically investigated. We take a simple mean-field model which simulates birth, growth and death processes, and rewrite it with spatially distributed discrete individuals. Each individual's growth and mortality is determined by a competition measure which captures the effects of neighbours in a way which retains the conceptual simplicity of a generic, analytically-solvable model. Although the model is generic, we here parameterise it using data from Caledonian Scots Pine stands. The dynamics of simulated populations, starting from a plantation lattice configuration, mirror those of well-established qualitative descriptions of natural forest stand behaviour; an analogy which assists in understanding the transition from artificial to old-growth structure. When parameterised for Scots Pine populations, the signature of spatial processes is evident, but their effect on first-order statistics, such as density and biomass, is fairly limited. The sensitivity of this result to variation in each individual rate parameter is investigated; distinct differences between spatial and mean-field models are seen only upon alteration of the interaction strength parameters, and in low density populations. Under the Scots pine parameterisation, dispersal also has an effect on spatial structure, but not density and biomass. Only in more intense competitive scenarios does altering the relative scales of dispersal and interaction lead to a clear signal in first order behaviour. The study acts as an important reminder that, even in scenarios where individual processes are localised in space, simple models are often sufficient to capture many population scale aspects of observed ecological dynamics.

The cement industry is one of the largest carbon dioxide (CO2) emitters in the Thai industry. The cement sector accounted for about 20,633 kilotonnes (ktonnes) CO2 emissions in 2005 in Thailand. A bottom-up CO2 abatement cost curve (ACC) is constructed in this study for the Thai cement industry to determine the potentials and costs of CO2 abatement, taking into account the costs and CO2 abatement of different technologies. The period of 2010–2025 is chosen as the scenario period. We analyzed 41 CO2 abatement technologies and measures for the cement industry. Using the bottom-up CO2 ACC model, the cost-effective annual CO2 abatement potential for the Thai cement industry during the 15 year scenario period (2010–2025) is equal to 3095 ktonnes CO2/year. This is about 15% of the Thai cement industry’s total CO2 emissions in 2005. The total technical annual CO2 abatement potential is 3143 ktonnes CO2/year, which is about 15.2% of the Thai cement industry’s total CO2 emissions in 2005. We also conducted a sensitivity analysis for the discount rate parameter.

Determination of rate parameter for kinetics of nitrification The nitrification process is the bottleneck step in the total nitrogen removal. The formation of nitrate is considered as the rate limiting step in the whole process and its kinetics determine the design of the nitrification reactor. Heavy metals (Zn2+ and Cu2+) and different organic compounds are used as micropollutants. These kinetics were experimentally measured by respirometry. In line with the aim of the paper, the experimental investigation are conducted to develop design equations to describe kinetic rate relationships under optimum conditions, study the parameter influence such as pH and inhibition by reaction intermediates and inhibition by external pollutants. Results demonstrate that the maximum value of the specific growth rate of autotrophic biomass() is 1.02 day at pH=7 and decreases at pH 7.5; inhibition occurs at substrate (NH 4 ) concentrations in excess of 15 mg N/l; inhibition occurs at increasing concentrations of NO –N and Cu 2+ has more pronounced inhibitory effect than Zn 2+ . The inhibitory effect of organic compounds are listed as the Chlorobenzene > Trichloroethylene> Phenol> Ethyl benzene; the experimental oxygen uptake rate (OUR)-test results the autotrophic kinetic parameter values, which can be used in design equations. Keywords: Respirometry, Autotrophic Biomass, Nitrification, Oxygen Uptake Rate Abstrak Proses nitrifikasi merupakan langkah penting pada penurunan kadar total nitrogen. Pembentukan nitrat dianggap sebagai tahap pembatas kecepatan reaksi pada keseluruhan proses dan kinetikanya menentukan perancangan dari bagian proses nitrifikasi. Logam berat (Zn 2+ dan Cu 2+ ) dan berbagai jenis komponen organik digunakan sebagai mikropolutan. Kinetika ini secara eksperimental diukur menggunakan respirometer. Tujuan penelitian adalah mengembangkan persamaan perancangan yang menggambarkan hubungan laju kinetika pada kondisi optimum, studi pengaruh parameter seperti pH, inhibisi karena reaksi intermediat, dan inhibisi oleh polutan dari luar. Hasil penelitian ditunjukkan sebagai berikut: harga laju pertumbuhan biomasa autotrof maksimum spesifik adalah 1,02 hari -1 pada pH=7 dan menurun pada pH 7,5; inhibisi terjadi pada konsentrasi substrat (NH 4 + ) lebih besar dari 15 mg N/l; inhibisi terjadi pada peningkatan konsentrasi NO -N ;Cu 2+ lebih dikenal sebagai penyebab inhibisi daripada Zn 2+ . Efek inhibisi dari komponen organik di daftar mulai dari Chlorobenzene sampai Ethylbenzen. Tes OUR menghasilkan harga parameter kinetika yang dapat dipakai pad apersamaan perencanaan lumpur aktif nitrifikasi. Kata Kunci: Respirometer, BiomasaAutotrof, Nitrifikasi, Laju Kenaikan Oksigen

Optical tweezers play an important role in many domains, especially in life science. And optical gradient force is necessary for constructing optical tweezers. In this paper, the optical gradient force in the focal region of radial varying polarization Bessel- Gauss beam is investigated numerically by means of vector diffraction theory. Results show that the beam parameter and vary rate parameter that indicates the change speed of polarization rotation angle affect the optical gradient force pattern very considerably, and some novel force distributions may come into being, such as multiple force minimums, force ring, and force crust. Therefore, the focusing of radial varying polarization Bessel-Gauss beam can be used to construct optical traps.

Several previous discounting studies have used the R2 measure to identify data sets with poor fits to a mathematical discounting model as nonsystematic data to be eliminated before further analyses are conducted. Data from three previous delay-discounting studies (6 separate groups, with a total of 161 individuals) were used to demonstrate why using R2 to assess the fits of discounting data is problematic. A significant, positive correlation between discounting rate parameter and R2 was found in most groups, showing that R2 is more stringent as a measure of fit for low discounting rates than for high discounting rates. Furthermore, it is suggested that identifying nonsystematic data based on any measure of fit to a mathematical discounting model may be problematic because it confounds discounting rate comparison with the issue of discounting model assessment. Therefore, a model-free method to identify nonsystematic data is needed. An algorithm for identifying nonsystematic data is presented that is based on the expectation of a monotonically decreasing discounting function. This algorithm identified 13 cases out of the 161 reanalyzed data sets as nonsystematic. These nonsystematic data are presented, along with examples of data not identified as nonsystematic. This algorithm, or modifications of it, may be useful in a variety of human and nonhuman animal discounting studies (e.g., delay discounting, probability discounting) as an alternative to the R2 measure for identifying nonsystematic data. The algorithm may be used in empirical investigations to improve discounting methodology, and may be used to identify outliers to be removed from analyses.

Crevice corrosion is the accelerated attack occurred in the occluded cell under a crevice on the metal surface. Crevice corrosion behaviors of nickel-based alloys such as Alloy 600 and Alloy 690 were investigated in acidic solution with different chloride ion concentrations. Tests were carried out using the specially designed crevice cell with a very narrow Luggin capillary assembly to measure the potential inside the crevice. It is believed that crevice corrosion in active/passive system like nickel-based alloys has much to do with the properties of passive film and its repassivation characteristics, investigated by the capacitance measurement and by the abrading electrode technique, respectively. An attempt was made to elucidate the relationship between crevice corrosion behaviors, properties of passive film and its repassivation kinetics. Results showed that repassivation rate parameter and/or indicated the possible occurrence of crevice corrosion.

We show that the heating effect of spontaneous wave-function collapse models implies an experimentally significant increment $\Delta T$ of equilibrium temperature in a mechanical oscillator. The obtained form $\Delta T$ is linear in the oscillator's relaxation time $\tau$ and independent of the mass. The oscillator can be in a classical thermal state, the effect $\Delta T$ is classical for a wide range of frequencies and quality factors. We note that the test of $\Delta T$ does not necessitate quantum state monitoring but tomography. In both gravity-related (DP) and continuous spontaneous localization (CSL) models the strong-effect edge of their parameter range can be challenged in existing experiments on classical oscillators. For the CSL theory, the conjectured highest collapse rate parameter values become immediately constrained by evidences from current experiments on extreme slow-ring-down oscillators., Comment: 5pp

International audience; In population dynamics, more precisely in cell structured population, experimental measures of the temporal dynamics of some parameters are often difficult or even impossible because of the lack of appropriate technology. It is the case of the division rate parameter for a structured population of cells. So theoretical and numerical approaches are needed to recover such parameters by indirect observation of the solution of the modeling system. In this work we present how to estimate the division rate from a growth-fragmentation type equation as done in the work of Doumic and Tine (see [1]) and following the work done in [2] and [3]. The estimation strategy is based on the observation of the long-term solution of the model for a size structured population when the growth and division rates are fully general. The issue of the theoretical and numerical results are discussed here.

International audience; We study the existence of planar flames, in the case of a single-step chemical reaction with volumetric heat losses, with a general reaction term. We prove that for all positive Lewis numbers, and for small values of the heat loss rate parameter, two distinct solutions exist. We also give upper bounds for the flame speed and for the heat loss rate parameter. Moreover, we explicitly compute a lower bound for the unburned gases after reaction.

We present optical and/or infrared photometry of the Type Ia supernovae SN 1991T, SN 1991bg, SN 1999ek, SN 2001bt, SN 2001cn, SN 2001cz, and SN 2002bo. All but one of these supernovae have decline rate parameters Delta m_15(B) close to the median value of 1.1 for the whole class of Type Ia supernovae. The addition of these supernovae to the relationship between the near-infrared absolute magnitudes and Delta m_15(B) strengthens the previous relationships we have found, in that the maximum light absolute magnitudes are essentially independent of the decline rate parameter. (SN 1991bg, the prototype of the subclass of fast declining Type Ia supernovae, is a special case.) The dispersion in the Hubble diagram in JHK is only ~0.15 mag. The near-infrared properties of Type Ia supernovae continue to be excellent measures of the luminosity distances to the supernova host galaxies, due to the need for only small corrections from the epoch of observation to maximum light, low dispersion in absolute magnitudes at maximum light, and the minimal reddening effects in the near-infrared., Astron. J., 128, 3034 (Dec. 2004). This version with updated author list, addresses, acknowledgments, references

This paper estimates a dynamic model of interfuel substitution for Swedish heating plants. We use the cost share linear logit model developed by Considine and Mount [Considine, T.J., Mount, T.D., 1984. The use of linear logit models for dynamic input demand systems. Review of Economics and Statistics 66, 434–443]. All estimated own-price elasticities are negative and all cross-price elasticities are positive. The estimated dynamic adjustment rate parameter is small, however, increasing with the size of the plant and time, indicating fast adjustments in the fuel mix when changing relative fuel prices. The estimated model is used to illustrate the effects of two different policy changes.

Published isothermal semilogarithmic survival curves of Escherichia coli K-12 MG1655, in the range of 49.8 to 60.6 degrees C, all had noticeable downward concavity. They could be described by the model log S(t) = -b(T)t n, where S(t) = N(t)/N0, N(t) and N0 being the momentary and initial number of organisms, respectively; b(T) is a temperature-dependent rate parameter; and n is a constant found to be about 1.5. The temperature dependence of b(T) could be described by the log-logistic model, b(T) = ln[1 + exp[k(T - Tc)]], which had an almost perfect fit, with k = 0.88 degrees C(-1) and Tc = 60.5 degrees C. The constants, n, k, and Tc were considered the organism's survival parameters in the particular medium. They were incorporated into a rate equation on the assumption that in nonisothermal heating, the momentary inactivation rate is the isothermal rate at the momentary temperature at a time that corresponds to the momentary survival ratio. This model's estimates matched the actual survival curves obtained in the same work under two different nonisothermal heating profiles, lending support to the notion that the Weibull-log-logistic model combination can be used not only to describe isothermal inactivation mathematically, but also to predict survival patterns under nonisothermal conditions.

The Gompertz is one of a family of growth functions that, when the environment (e.g. food, housing) is non-limiting, provides a useful description of growth as a comparatively simple, single equation. It has three parameters of which the important ones are mature size, A, and the rate parameter, B. Estimates of A and B, however, are highly correlated and defining their separate values for individual animals is problematic. This problem was explored using five methods for estimating the parameters, or transformations of them, to describe the growth of two genotypes of Suffolk sheep kept under non-limiting conditions. One genotype was under selection for high lean growth rate and the other was its control. Live weights that were collected at least fortnightly from near birth to 150 days of age over a 9-year period on 1934 lambs were used. The Gompertz form adequately described the growth of the great majority of the lambs evaluated. When considering A and B as a lumped parameter, Z = A·B, and fitting Z, B and an initial condition (a transformed birth weight) as the parameters, the problems in estimation were substantially overcome as shown by a low correlation of Z with estimates of B both within and across animals. Usefully Z has a biological interpretation in that Z/e is the maximum daily growth rate. Since the Gompertz form adequately described growth in these sheep, the extent of genetic co-variation for the growth parameters values (A, B, Z) was estimated to determine if they were amenable to selection. A weighted univariate animal model was fitted. Mature size, A, and the rate parameter, B, were moderately heritable (0·37 (s.e. 0·04) and 0·38 (s.e. 0·05), respectively) as was live weight at 150 days of age (0·31 (s.e. 0·06)). However there was a substantial negative genetic relationship between A and B (–0·48). Z was highly heritable (0·72 (s.e.0·05)). After 9 years of selection, the genotype selected for high lean growth rate was heavier (P < 0·001) at 150 days of age (5·2 kg) and at maturity (6·6 kg), with a maximum growth rate (Z/e) that was 1·12 times that of the control. Our lumped parameter Z, in effect a rate parameter scaled for mature size, avoided problems in estimating A and B and, in so doing, offers a general and robust description of lamb growth amenable to selection.

As the enormous use of internet increases day by day so as security concern is also raise day by day over the internet. In this paper we discuss the network security and its related threats and also study the types of protocols and few issues related to protocols in computer networks. We also simulate the design of 5 node wired network scenario, its packet drop rate analysis through TCP protocol using NS2 as a simulator. Analyzed the performance of 5-node network when the packet is drop down by graphical method also called as Xgraph when rate parameter is in mb and also analyzed the performance of same network by changing the value of rate parameter at same time so no packets would drop down at same time and also analyzed the performance by Xgraph method., 14 pages

The Brazilian cerrado presents strong climate seasonality. During the dry season, plants may be exposed to stressful situations, such as a soil surface water deficit, that stimulate their chemical defenses. However, the seasonality effect on the production of allelopathic compounds of cerrado plant species is poorly understood. In this study, the phytotoxic activities of common native cerrado plants were evaluated during rainy and dry seasons. Crude leaves extracts (10% concentration: weight/volume, with dry leaves and distilled water) from eleven species were tested on lettuce and sesame germination. The negative effects on germination percentages, rates and informational entropies of the target species were higher when submitted to plant extracts from the dry season, where the germination rate was the most sensible parameter. The higher sensibility of lettuce and the germination rate parameter showed this difference. Only two exceptions had higher effects for rainy season extracts; one species showed higher negative effects on germination informational entropy of lettuce and another species on the germination rate of sesame. Thus, increases in the allelopathic activity were seen in the majority of the studied cerrado plant species during the dry season. These distinct responses to stressful situations in a complex environment such as the Brazilian cerrado may support the establishment and survival of some species.

Stone and colleagues’ results are consistent with mathematical models of hospital transmission of meticillin resistant Staphylococcus aureus (MRSA).1 This can be shown using Cooper and colleagues’ model, whereby transmission within hospital is described by an effective contact rate parameter between susceptible and infectious people. Improved hygiene conditions reduce the probability that contact between people results …

A procedure for modelling single flotation columns and column circuits is described. In general terms, column models comprise three key components or expressions, to describe particle/bubble attachment, axial dispersion in the pulp zone, and net detachment in the froth zone. Previous models of these components are reviewed. In the current study, each column unit or stage is represented by a single zone model. Mineral recovery from each stage is related to a first order rate parameter and a residence time distribution. Based on experimental evidence and theory, an improved expression for the rate parameter is proposed. The model parameters are back-calculated from or fitted to experimental data. In this paper a number of model fitting examples are presented, these include single columns and column circuits. In the circuit examples, the mineral specific parameters are related to the properties of the feed, rather than to the operation of individual column stages. Consequently mineral behaviour is separated from column operation and circuit configuration. Mineral behaviour is related to particle size and arbitrary floatability distribution. The relative merits of a number of floatability distributions are examined.

Probing the non-elastic deformation of solid polymers in the pre-yield range has proved to be a very sensitive test of the structural response to plasticity nucleation. A work-hardening rate parameter,K, deduced from repeated stress relaxations was thus introduced to quantify this behaviour. It is shown that considerable improvement and more extensive information may be gained by measuring the work-hardening rate by the so-called direct method from a simple stress-non-elastic strain plot. A comparison is given of the two methods in the case of unsaturated polyester resins, together with a careful evaluation of potential sources of discrepancy.