Second Type Of Models Research Articles

Organization and implementation of judicial control at the stage of pre-trial investigation in foreign countries

The scientific article examines the peculiarities of the organization and conduct of judicial control of the preliminary investigation in European countries. It was determined that judicial control in historical retrospect dates back to the Middle Ages, so it has a long practical experience of application. It has been established that in the national legal systems of European countries, judicial control is organized differently, therefore the scientific literature confirms the existence of two types of models of judicial control depending on the purpose of judicial control in a criminal process. The first type of models is characterized by the presence of investigative functions and powers in the field of investigative actions for the representatives of the judiciary, who are authorized to exercise judicial control over the pre-trial investigation. The second type of models of judicial control in European countries is organized in such a way that representatives of the judiciary in pre-trial investigation are empowered with powers that are limited to resolving issues related to monitoring the observance of the rights and freedoms of the participants in the pre-trial investigation, without decisive influence on the course of the pre-trial investigation. The peculiarities of the specialization of entities that perform the functions of judicial control were analyzed and it was determined that they are divided into judicial bodies that are not separated from general courts (they lack specialization); judicial bodies in which there are separate positions of investigative judges in general courts; specialized judicial bodies. The advantages and disadvantages of the models of the first and second type of organization of judicial control over pre-trial investigation in Europeancountriesareestablished. Theadvantages of the first-type models are the cost-effectiveness of the organization of judicial control, the second- type models are characterized by a higher degree of quality protection of the rights and freedoms of a person in pre-trial investigation due to the exclusive specialization of representatives of the judiciary. It was determined that the peculiarities of legal regulation of judicial control over pre-trial investigation in Ukraine allow us to conclude that it belongs to the second type of models. Depending on the degree of specialization, the Ukrainian model of judicial control provides for the position of an investigative judge in the system of courts of general jurisdiction.

Statistical modeling of COVID-19 deaths with excess zero counts

Abstract Objectives Modeling and forecasting possible trajectories of COVID-19 infections and deaths using statistical methods is one of the most important topics in present time. However, statistical models use different assumptions and methods and thus yield different results. One issue in monitoring disease progression over time is how to handle excess zeros counts. In this research, we assess the statistical empirical performance of these models in terms of their fit and forecast accuracy of COVID-19 deaths. Methods Two types of models are suggested in the literature to study count time series data. The first type of models is based on Poisson and negative binomial conditional probability distributions to account for data over dispersion and using auto regression to account for dependence of the responses. The second type of models is based on zero-inflated mixed auto regression and also uses exponential family conditional distributions. We study the goodness of fit and forecast accuracy of these count time series models based on autoregressive conditional count distributions with and without zero inflation. Results We illustrate these methods using a recently published online COVID-19 data for Tunisia, which reports daily death counts from March 2020 to February 2021. We perform an empirical analysis and we compare the fit and the forecast performance of these models for death counts in presence of an intervention policy. Our statistical findings show that models that account for zero inflation produce better fit and have more accurate forecast of the pandemic deaths. Conclusions This paper shows that infectious disease data with excess zero counts are better modelled with zero-inflated models. These models yield more accurate predictions of deaths related to the pandemic than the generalized count data models. In addition, our statistical results find that the lift of travel restrictions has a significant impact on the surge of COVID-19 deaths. One plausible explanation of the outperformance of zero-inflated models is that the zero values are related to an intervention policy and therefore they are structural.

Added-value of ensemble prediction system on the quality of solar irradiance probabilistic forecasts

Abstract Accurate solar forecasts is one of the most effective solution to enhance grid operations. As the solar resource is intrinsically uncertain, a growing interest for solar probabilistic forecasts is observed in the solar research community. In this work, we compare two approaches for the generation of day-ahead solar irradiance probabilistic forecasts. The first class of models termed as deterministic-based models generates probabilistic forecasts from a deterministic value of the irradiance predicted by a Numerical Weather Prediction (NWP) model. The second type of models denoted by ensemble-based models issues probabilistic forecasts through the calibration of an Ensemble Prediction System (EPS) or from information (such as mean and variance) derived from the ensemble. The verification of the probabilistic forecasts is made using a sound framework. A numerical score, the Continuous Ranked Probability Score (CRPS), is used to assess the overall performance of the different models. The decomposition of the CRPS into reliability and resolution provides a further detailed insight into the quality of the probabilistic forecasts. In addition, a new diagnostic tool which evaluates the contribution of the statistical moments of the forecast distributions to the CRPS is proposed. This tool denoted by MC-CRPS allows identifying the characteristics of an ensemble that have an impact on the quality of the probabilistic forecasts. The assessment of the different models is done on several sites experiencing very different climatic conditions. Results show a general superior performance of ensemble-based models as the gain in forecast quality measured by the CRPS ranges from 4% to 16% depending on the site.

Comparison of a spatial, spatial and hybrid methods for predicting inter-rill and rill soil sensitivity to erosion at the field scale

Soil erosion prediction and conservation planning require detailed soil data under different environmental conditions. When such data are needed at the field scale, aspatial and spatial models could be used to predict soil erosion processes. This study was conducted to develop spatial models including geostatistical models (i.e. ordinary kriging (OK) and cokriging (CK)) and hybrid geostatistical models (i.e. multiple linear regression-kriging (MLRK) and artificial neural network-kriging (ANNK)) for estimating WEPP baseline soil sensitivity to erosion parameters for calcareous agricultural soils in northwest Iran. Inter-rill and rill erosion simulation experiments were carried out at 100 locations at the field scale with 3 replications. At each location, the soil properties (organic matter, calcium carbonate equivalent, sand, silt, clay, base infiltration rate) were measured and auxiliary data obtained from attributes derived from digital elevation models (elevation, slope, stream power index, wetness index and sediment transport index) and remote sensing data (three visible bands, NIR, SWIR (5 and 7 bands), NDVI indices). The MLR and ANN models were used to estimate baseline inter-rill soil sensitivity to erosion (Kib) and rill soil sensitivity to erosion (Krb and τcb) using two types of input data. For the first type of prediction models (type I), the measured soil properties and auxiliary data were used, whereas for the second type of models (type II), principal components (PCs) based on the soil and auxiliary data were used. In comparison to the models that were developed here, the WEPP inter-rill and rill soil sensitivity to erosion models showed a relatively poor performance. The ANN models developed here predicted Kib, Krb and τcb parameters better than the MLR models using both types of data (type I and II). Moreover, the results indicated that the ANNK model was the most appropriate spatial or hybrid model for predicting soil sensitivity to erosion parameters.

Environment specific TCP upstream throughput models in IEEE802.11b WLAN

This paper presents our study on environment based dependence of TCP Upstream Throughput (TCPupT) on signal to noise ratio (SNR) for a single user in an IEEE 802.11b Wireless Local Area Network (WLAN). Small offices, open corridors and free space environments were studied using an infrastructure based network for different quality of service (QoS) traffic. Environment based Models that predict TCPupT directly from SNR for different signal categories were statistically generated, validated and compared with similar models that were earlier developed without considering specific environments. The first type of models developed in this work were developed from all data specifically collected from each environment while the second type of models were developed by first categorizing the data in each specific environment into different signal categories and then models were statistically generated for each signal category before combining them into one model equation. At the stated levels of significance and the different degrees of freedom, the developed models were accepted at 1% (for F test) and 0.5% (for T test). From the RMS errors computed, the specific environment based models developed in this work were more accurate (as they showed lower RMS errors compared with earlier similar models) in predicting TCPupT in IEEE 802.11b WLAN for a single user on the network. It was also observed that the second type of models were found to be more accurate having shown lower RMS errors.Keywords: TCP Upstream throughput, Signal to noise ratio, environment based empirical model,IEEE802.11b, WLANs

Measuring Method Effects

This article presents an overview of recent psychometric developments in the area of multimethod measurement, in which we argue that different types of research designs require different types of models. In particular, two types of measurement models for method effects can be distinguished. First, models with a general factor, in which method effects are defined as deviations from a common trait, and second, models for contrasting methods, in which method effects are defined relative to another method but not to a general trait. We argue that the first type of models require a two-level research design (interchangeable methods) whereas the second type of models can be applied to a one-level research design (structurally different methods). Current directions in the uses of these approaches for longitudinal research and multiple-rater studies are described.

Optokinetic circular vection: a test of visual-vestibular conflict models of vection nascensy.

The propensity to experience circular vection (the illusory perception of self-turning evoked by a rotating scene, CV) as reflected by its onset latency exhibits considerable interindividual variation. Models of CV nascensy have linked this delay to the time it takes the visual-vestibular conflict to disappear. One line of these "conflict models" (Zacharias and Young in Exp Brain Res 41:159-171, 1981) predicts that, across individuals, CV latency (CVL) correlates positively with the vestibular time constant (TC) and negatively with the vestibular motion detection threshold (vTHR). A second type of models (Mergner et al. in Arch Ital Biol 138:139-166, 2000) predicts only an increase in CVL with TC. We here examine which of these predictions can be experimentally substantiated. Also, we ask whether the relative weight W O of the optokinetic contribution to the perception of real self-turning could also be a factor influencing CVL. We conducted 5 experiments in 29 subjects measuring: (1) CVL, (2) the TCs of velocity perception and of accompanying nystagmus during rotation in darkness and (3) likewise for displacement perception, (4) vTHR, and (5) W O as revealed by discordant visual-vestibular stimulation. CVL correlated with the nystagmus TC recorded during velocity estimation but with none of the other vestibular TCs nor with vTHR. Confirming earlier findings, CVL shortened with rising scene velocity. Finally, CVL correlated inversely with W O: the larger an individual's optokinetic weight, the shorter was his CVL. Taken together, our data favour the second type of models which invoke an antagonism between CV inhibition by the optokinetic-vestibular conflict and disinhibition by optokinetic stimulation. Idiosyncratic factors appear to strongly modulate the balance between inhibition and disinhibition, thus increasing CVL variability and obscuring the expected relation between CVL and TC.

Investigation of L10 FePt-based soft/hard composite bit-patterned media by micromagnetic simulation**Project supported by the National Natural Science Foundation of China (Grant Nos. 51171086 and 61272076) and the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61003041).

The soft/hard composite patterned media have potential to be the next generation of magnetic recording, but the composing modes of soft and hard materials have not been investigated systematically. L10 FePt-based soft/hard composite patterned media with an anisotropic constant distribution are studied by micromagnetic simulation. Square arrays and hexagonal arrays with various pitch sizes are simulated for two composing types: the soft layer that encloses the hard dots and the soft layer that covers the whole surface. It is found that the soft material can reduce the switching fields of bits effectively for all models. Compared with the first type, the second type of models possess low switching fields, narrow switching field distributions, and high gain factors due to the introduction of inter-bit exchange coupling. Furthermore, the readout waveforms of the second type are not deteriorated by the inter-bit soft layers. Since the recording density of hexagonal arrays are higher than that of square arrays with the same center-to-center distances, the readout waveforms of hexagonal arrays are a little worse, although other simulation results are similar for these two arrays.

Dispersion of low frequency plasma waves upstream of the quasi-perpendicular terrestrial bow shock

Abstract. Low frequency waves in the foot of a supercritical quasi-perpendicular shock front have been observed since the very early in situ observations of the terrestrial bow shock (Guha et al., 1972). The great attention that has been devoted to these type of waves since the first observations is explained by the key role attributed to them in the processes of energy redistribution in the shock front by various theoretical models. In some models, these waves play the role of the intermediator between the ions and electrons. It is assumed that they are generated by plasma instability that exist due to the counter-streaming flows of incident and reflected ions. In the second type of models, these waves result from the evolution of the shock front itself in the quasi-periodic process of steepening and overturning of the magnetic ramp. However, the range of the observed frequencies in the spacecraft frame are not enough to distinguish the origin of the observed waves. It also requires the determination of the wave vectors and the plasma frame frequencies. Multipoint measurements within the wave coherence length are needed for an ambiguous determination of the wave vectors. In the main multi-point missions such as ISEE, AMPTE, Cluster and THEMIS, the spacecraft separation is too large for such a wave vector determination and therefore only very few case studies are published (mainly for AMPTE UKS AMPTE IRM pair). Here we present the observations of upstream low frequency waves by the Cluster spacecraft which took place on 19 February 2002. The spacecraft separation during the crossing of the bow shock was small enough to determine the wave vectors and allowed the identification of the plasma wave dispersion relation for the observed waves. Presented results are compared with whistler wave dispersion and it is shown that contrary to previous studies based on the AMPTE data, the phase velocity in the shock frame is directed downstream. The consequences of this finding for both types of models that were developed to explain the generation of these waves are discussed.

ODE models for oncolytic virus dynamics

Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remains uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the “fast spread” models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the “slow spread” models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers.

Stochastic models for simulation of strong ground motion in Iceland

AbstractTwo types of modelling approaches for simulating ground motion in Iceland are studied and compared. The first type of models, named discrete‐time series models (ARMA), are based solely on measured acceleration in earthquakes occurring in Iceland. The second type of models are based on a theoretical seismic source model called the extended Brune model. Based on measured acceleration in Iceland during the period 1986–1996, the parameters for the extended Brune models have been estimated. The seismic source models are presented here as ARMA models, which simplifies the simulation process. A single‐layer soil amplification model is used in conjunction with the extended Brune model to estimate local site amplification. Emphasis is put on the ground motion models representing the variability in the measured earthquakes, with respect to energy, duration and frequency content. Demonstration is made using these models for constructing linear and non‐linear probabilistic response spectra using a discretised version of the Bouc–Wen model for the hysteresis of the second‐order system. Copyright © 2001 John Wiley & Sons, Ltd.

Irreversible adsorption of colloidal particles on solid substrates

In this article, we summarize the basic results relative to the field of irreversible deposition processes of colloidal particles on solid surfaces. An irreversible deposition process is defined as a process in which, once adsorbed, a particle can neither diffuse along, nor desorb from the surface. However, some extensions leading to reversible adsorption models are also outlined. First the basic tools used in these studies are introduced, notably the concept of available surface function. General results relative to these processes are then presented. We discuss, in particular, the connection between the reduced variance of the number density fluctuations of adsorbed particles and the available surface function. We then review the main models which were introduced in the literature to account for these processes. They can be divided in two classes: (i) the models which are based entirely on statistical and geometrical grounds. The most widely studied of them is the Random Sequential Adsorption (RSA) model which is discussed in detail. For the processes in which gravity plays an important role one uses the Ballistic Deposition (BD) model. We also present models which are aimed at accounting for the behavior lying between the ballistic deposition and the RSA. (ii) The second type of models corresponds to those which take explicitly the diffusion of the particles in the vicinity of the adsorption plane into account. The results relative to these models, called diffusional models, are discussed in detail. Finally, the last part of the article is devoted to experimental results. We present and discuss in a critical way experimental evidence which seems to indicate the validity of the RSA and BD models.

Mathematical methods for modelling and identification of nonlinear agricultural systems

Two types of models can be used to describe nonlinear agricultural systems: mechanistic and empirical. For the first type of models, mathematical methods for simulating, a set of differential equations which characterise the underpinning process relationships are outlined. For the second type of models, mathematical methods for identifying the system using input/output responses are also outlined. The study focuses on continuous rather than discrete representation of the system dynamics and on deterministic rather than stochastic description of the system dynamics. The theory is illustrated with two examples of agricultural systems where the above methods have been applied successfully.

Irreversible deposition/adsorption processes on solid surfaces

In this article, we summarize the knowledge in the field of irreversible deposition processes of large molecules or colloidal particles on solid surfaces. An irreversible adsorption process is defined as a process in which, once adsorbed, a particle can neither diffuse along, nor desorb from the surface. We first introduce the basic tools used in these studies, one of the most important being the concept of available surface function. General results relative to these processes are then presented. We discuss, in particular, the connection between the reduced variance of the number density fluctuations of adsorbed particles and the available surface function. We then review the main models which were introduced in the literature to account for these phenomena. They can be divided in two classes: (i) the models which are based entirely on statistical and geometrical grounds. The best known and most widely studied of them is the Random Sequential Adsorption (RSA) model which is discussed in details. For the processes in which gravity plays an important role one uses the Ballistic Deposition (BD) model. We also present models which are aimed at accounting for the behavior lying between the ballistic deposition and the RSA. (ii) The second type of models corresponds to those which take explicitly the diffusion of the particles in the vicinity of the adsorption plane into account. The results relative to these models, called diffusional models, are discussed in details. Finally, the last part of the review is devoted to experimental results. We show, in particular, that the Langmuir model, which is the most widely used model in the literature to account for the protein adsorption kinetics, does not predict correctly the experimental observations. We present and discuss in a critical way experimental evidence which seems to indicate the validity of the RSA and ballistic models.

Mathematical Methods for Modelling and Identification of Nonlinear Systems

Two types of models are often used to describe nonlinear agricultural systems: mechanistic and empirical. For the first type of models, mathematical methods for solving a set of differential and algebraic equations (which characterize the underpinning process relationships) are outlined. For the second type of models, mathematical methods for identification of the nonlinear systems using cross-correlation analysis of input/output responses are also outlined. The study focuses on continuous rather than discrete representation of the systems' dynanlics and on deterministic rather than stochastic description of the systems. The theory is illustrated with two examples of agricultural systems where the above methods have been applied: near-ambient grain drying and winter wheat production.

Root, shoot and soil parameters required for process-oriented models of crop growth limited by water or nutrients

A review is given of the prospects for using process-oriented models of water and nutrient uptake in improving ‘integrated agriculture’. Government-imposed restrictions on the use of external inputs will increase the likelihood of (temporary) nutrient or water stress in crop production in NW Europe and thus a better understanding is required of shoot-root-soil interactions than presently available. In modelling nutrient and water uptake, three approaches are possible: 1) models-without-roots, based on empirically derived efficiency ratios for uptake of available resources, 2) models evaluating the uptake potential of root systems as actually found in the field and 3) models which also aim at a prediction of root development as influenced by interactions with environmental factors. For the second type of models the major underlying processes are known and research can concentrate on model refinement on the one hand and practical application on the other. The main parameters required for such models are discussed and examples are given of practical applications. For the third type of models quantification of processes known only qualitatively is urgently needed.

Kaluza-Klein approach with noninteger and scale-dependent dimensions

Possibilities of application of Euclidean spaces with noninteger dimension in space-time theories are studied. Two cases are described: the extension of the Salam-Strathdee scheme for the description of Yang-Mills interaction models based on compact internal coset group manifoldsG/H with noninteger dimensions, on the one hand, and a sort of models which could be considered as an alternative to the Kaluza-Klein approach but which do not require assumptions either on compactness or on finiteness of internal manifolds, on the other. The second type of models is close in spirit to the Kaluza-Klein ones and uses spaces with scale-dependent dimensions.