Livestock abortion is a source of economic loss for farmers, but its economic impact has not been estimated in many Low and Middle-Income Countries. This article presents an estimation methodology and estimates for the gross and net cost of an abortion based on a sample of livestock-owning households in three regions of northern Tanzania and market data. We then generate aggregate estimates of abortion losses across Tanzania. We estimate annual gross and net annual losses of about $263 Million (about TZS 600 billion) and $131 million (about TZS 300 billion), respectively.

Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

Reasonable stochastic model and function model are the premise of accurate velocity determination, especially in the time-differenced carrier-phase (TDCP) method. This paper presents, first, an elevation-dependent stochastic model (ESM), and then gives a simplified and unified Galileo/GPS combined TDCP function model, where the inter-system bias (ISB) variations are analysed based on correlation coefficients and the scaled sensitivity matrix. To evaluate the performance of the proposed models, datasets collected at 10 multi-GNSS experiment (MGEX) stations and a vehicle kinematic experiment are employed. The results indicate that the ESM model can improve the accuracy of the velocity solution, especially for the Galileo/GPS combined system, in comparison with the equivalent weight ratio method. In contrast to the Galileo-only velocity solution, the Galileo/GPS combined velocity solution can bring improvements of about 1–1⋅5 mm/s, 0⋅5 mm/s and 1⋅5–2⋅5 mm/s in East, North and Up components, respectively. Compared with the traditional Galileo/GPS TDCP model, the simplified and unified model shows no obvious differences in all components in the environment with more visible satellites, but it performs better in a challenging environment with few visible satellites.

This paper deals with design of an alternative secure Blockchain network framework to prevent damages from an attacker. The alliance concept from the strategic management perspectives is applied on the top of a general stochastic game framework. This new enhanced hybrid theoretical model is designed to find the best strategies toward preparation for preventing a network malfunction from an attacker through strategic alliances with other genuine nodes and it is developed based on the combination of a strategic management framework and a conventional stochastic model based on the Blockchain Governance Game. Analytically, tractable results for decision-making parameters are fully obtained to predict of the moment for operations and also to provide the optimal number of allegiance nodes to protect a Blockchain network. This research helps those whom are considering initial coin offering or launching new Blockchain-based services by enhancing security features through strategic alliances in a decentralized network.

The accuracy of the Global Positioning System (GPS) observable, especially for the code observable, has improved with the development of Global Navigation Satellite System (GNSS) receiver technology. An evaluation of the GPS code observable is presented in this paper, together with a stochastic model for the code and phase observables in Precise Point Positioning (PPP), established using the evaluated results. The results show that the code observables of Leica GNSS receivers are generally better than those of some other brand receivers and the Root Mean Square (RMS) for the code observables of the Leica GRX1200PRO, which includes the multipath effect, reaches 0·71 m, although Coarse/Acquisition (C/A) code observables are tracked. The static positioning of the code observable can reach centimetre level and the convergence time for the JPLM station is just 2·5 hours. The positioning results show that it is difficult to converge the Up direction to the centimetre level, compared with the North and East directions. The results show that static positioning can be correlated with the accumulation characteristic of the error for the code observable, while that that of the kinematic mode can be correlated to the error value. The shortened PPP convergence times verify that the presented stochastic models are effective.

Soil moisture is a key factor in the ecohydrological cycle in water-limited ecosystems, and it integrates the effects of climate, soil, and vegetation. The water balance and the hydrological cycle are significantly important for vegetation restoration in water-limited regions, and these dynamics are still poorly understood. In this study, the soil moisture and water balance were modelled with the stochastic soil water balance model in the Loess Plateau, China. This model was verified by monitoring soil moisture data of black locust plantations in the Yangjuangou catchment in the Loess Plateau. The influences of a rainfall regime change on soil moisture and water balance were also explored. Three meteorological stations were selected (Yulin, Yan'an, and Luochuan) along the precipitation gradient to detect the effects of rainfall spatial variability on the soil moisture and water balance. The results showed that soil moisture tended to be more frequent at low levels with decreasing precipitation, and the ratio of evapotranspiration under stress in response to rainfall also changed from 74.0% in Yulin to 52.3% in Luochuan. In addition, the effects of a temporal change in rainfall regime on soil moisture and water balance were explored at Yan'an. The soil moisture probability density function moved to high soil moisture in the wet period compared to the dry period of Yan'an, and the evapotranspiration under stress increased from 59.5% to 72% from the wet period to the dry period. The results of this study prove the applicability of the stochastic model in the Loess Plateau and reveal its potential for guiding the vegetation restoration in the next stage.

We propose a stochastic model describing a process of awareness, evaluation, and decision making by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0, 1, 2. In this model 0 stands for ignorants, 1 for aware, and 2 for adopters. Aware and adopters inform its nearest ignorant neighbors about a new product innovation at rate λ. At rate α an agent in aware state becomes an adopter due to the influence of adopters' neighbors. Finally, aware and adopters forget the information about the new product, thus becoming ignorant, at rate 1. Our purpose is to analyze the influence of the parameters on the qualitative behavior of the process. We obtain sufficient conditions under which the innovation diffusion (and adoption) either becomes extinct or propagates through the population with positive probability.

If a series of glacial advances occurs over the same pathway, the moraines that are now present may constitute an incomplete record of the total history. This is because a given advance can destroy the moraine left by a previous one, if the previous advance was less extensive. Gibbons, Megeath and Pierce (GMP) formulated an elegant stochastic model for this process; the key quantity in their analysis is $\bi P(n\vert N)$, the probability that n moraines are preserved after N glacial advances. In their paper, GMP derive a recursion formula satisfied by $\bi P(n\vert N)$, and use this formula to compute values of P for a range of values of n and N. In the present paper, we derive an explicit general answer for $\bi P(n\vert N)$, and show explicit, exact results for the mean value and standard deviation of n. We use these results to develop more insight into the consequences of the GMP model; for example, to a good approximation, 〈n〉 increases as ln(N). We explain how a Bayesian approach can be used to analyze $\bi P(N\vert n)$, the probability that there were N advances, given that we now observe n moraines.

There is a global imperative to reduce phosphorous (P) excretion from pig systems. In this study, a previously validated deterministic model was modified to be stochastic, in order to investigate the consequences of different management strategies on P excretion by a group of growing pigs. The model predicts P digestion, retention and excretion from feed composition and growth parameters that describe a specified pig phenotype. Stochasticity was achieved by introducing random variation in the latter. The strategies investigated were: (1) changing feed composition frequently in order to match more closely pig digestible P (digP) requirements to feed composition (phase feeding) and (2) grouping pigs into light and heavy groups and feeding each group according to the requirements of their group average BW (sorting). Phase feeding reduced P excretion as the number of feeding phases increased. The effect was most pronounced as feeding phases increased from 1 to 2, with a 7.5% decrease achieved; the increase in phases from 2 to 3 was associated with a further 2.0% reduction. Similarly, the effect was more pronounced when the feed targeted the population requirements for digP at the average BW of the first third, rather than the average requirements at the mid-point BW of each feeding sequence plan. Increasing the number of feeding phases increased the percentage of pigs that met their digP requirements during the early stages of growth and reduced the percentage of pigs that were supplied <85% of their digP requirements at any stage of their growth; the latter may have welfare implications. Sorting of pigs reduced P excretion to a lesser extent; the reduction was greater as the percentage of pigs in the light group increased from 10% to 30% (from 1.5% to 3.0% reduction, respectively). This resulted from an increase in the P excreted by the light group, accompanied by a decrease in the P excreted by the remaining pigs. Sorting increased the percentage of light pigs that met their dig P requirements, but only slightly decreased the percentage of heavy pigs that met these requirements at any point of their growth. Exactly the converse was the case as far as the percentage of pigs that were supplied <85% of their digP requirements were concerned. The developed model is flexible and can be used to investigate the effectiveness of other management strategies in reducing P excretion from groups of pigs, including precision livestock feeding.

Expansion of sandflies and increasing pet travel have raised concerns about canine leishmaniasis (CanL) spread to new areas of Europe. This study aimed to estimate the probability of CanL introduction and persistence following movements of infected dogs. Stochastic modelling was used to estimate the probabilities of (1) CanL infection during travels or imports of infected dogs (Pinf and PinfCA, respectively), (2) CanL persistence in a dog network with sandflies after introduction of an infected dog (Pper), and (3) persistence in a CanL-free region (Pper region) for N dogs moving between endemic and free regions. Different mitigation measures (MMs) were assessed. Pinf [7·8%, 95% predictive interval (PI) 2·6–16·4] and Pper (72·0%, 95% PI 67·8–76·0) were reduced by use of repellent, vaccine, prophylactic medication, and insecticide, in decreasing order of effectiveness. Testing and exclusion of positive dogs was most effective in reducing Pper region for a small N. The spread of CanL to CanL-free areas with sandflies is thus likely, but can be reduced by MMs.

Ionospheric disturbances affect Global Positioning System (GPS) performance in terms of accuracy and integrity, especially over the equatorial region. During the period of the disturbances, GPS receivers suffer from a high noise level. Not taken into account by the current stochastic model, the ionospheric disturbances degrade GPS positioning accuracy. In addition, non-Gaussian tails are observed in the distribution of the noise during the period of the disturbances; therefore the integrity of GPS can also be affected. This paper develops a statistical solution that is able to mitigate effects of ionospheric disturbances on GPS accuracy and integrity using a commercial dual frequency receiver. The Rate of Total Electron Content (TEC) change Index (ROTI), a parameter derived from the dual frequency receiver, is used to group the levels of ionospheric disturbances. The standard deviations of the pseudorange noise under different groups are evaluated. By incorporating both the ROTI and the satellite elevation, a modified stochastic model is proposed to reduce the effect of the disturbed observation on the positioning accuracy. The performance of the model is evaluated by a test and an inflated sigma for each group is recommended for over-bounding anomalies of observations to protect the user against threats from ionospheric disturbances. This technique, together with results in this paper, can be applied to mitigate the effects of ionospheric disturbances on GPS.

We use economic indicators to improve the prediction of the number of incurred but not recorded disability insurance claims, assuming that there is a link between the number of claims and the chosen economic indicators. We propose a Bayesian model where we model the claims development in three directions: along incurred periods, recording lag periods and calendar periods. A stochastic model of the economic indicators is incorporated into the calendar period development direction. Thus we allow for the impact of the economic environment on the number of claims. Applying the proposed model to data, we illustrate how the inclusion of economic indicators affects the prediction of the number of incurred but not recorded disability claims.

Interference competition between closely related alien and indigenous species often influences the outcome of biological invasions. The whitefly Bemisia tabaci species complex contains ≥28 putative species and two of them, Mediterranean (MED, formally referred to as the ‘Q biotype’) and Middle East-Asia Minor 1 (MEAM1, formally referred to as the ‘B biotype’), have recently spread to much of the world. In many invaded regions, these species have displaced closely related indigenous whitefly species. In this study, we integrated laboratory population experiments, behavioural observations and simulation modelling to investigate the capacity of MED to displace Asia II 1 (AII1, formally referred to as the ‘ZHJ2 biotype’), an indigenous whitefly widely distributed in Asia. Our results show that intensive mating interactions occur between MED and AII1, leading to reduced fecundity and progeny female ratio in AII1, as well as an increase in progeny female ratio in MED. In turn, our population cage experiments demonstrated that MED has the capacity to displace AII1 in a few generations. Using simulation models, we then show that both asymmetric mating interactions and differences in life history traits between the two species contribute substantially to the process of displacement. These findings would help explain the displacement of AII1 by MED in the field and, together with earlier studies on mating interactions between other species of the B. tabaci complex, indicate the widespread significance of asymmetric mating interactions in whitefly species exclusions.

Increasingly, modern business and investment management techniques are founded on approaches to measurement of profit and risk developed by financial economists. This paper begins by analysing corporate pension provision from the perspective of such financial theory. The results of this analysis are then reconciled with the sometimes contradictory messages from traditional actuarial valuation approaches and the alternative market-based valuation paradigm is introduced. The paper then proposes a successful blueprint for this mark-to-market valuation discipline and considers whether and how it can be applied to pension schemes both in theory and in practice. It is asserted that adoption of this market based approach appears now to be essential in many of the most critical areas of actuarial advice in the field of defined benefit corporate pension provision and that the principles can in addition be used to establish more efficient and transparent methodologies in areas which have traditionally relied on subjective or arbitrary methods. We extend the hope that the insights gained from financial theory can be used to level the playing field between defined benefit and defined contribution arrangements from both corporate and member perspectives.

The purpose of this paper is to describe a methodology for determining an appropriate structure for time-series models of inflation rates, short-term and long-term interest rates, dividend growth rates, dividend yields, rental growth rates and rental yields and to demonstrate the application of that methodology to the development of a model based on South African data. It is suggested that the methodology used in this paper may be applied to other economic environments.

To filter perturbed local measurements on a random medium, a dynamic model jointly with an observation transfer equation are needed. Some media given by PDE could have a local probabilistic representation by a Lagrangian stochastic process with mean-field interactions. In this case, we define the acquisition process of locally homogeneous medium along a random path by a Lagrangian Markov process conditioned to be in a domain following the path and conditioned to the observations. The nonlinear filtering for the mobile signal is therefore those of an acquisition process contaminated by random errors. This will provide a Feynman-Kac distribution flow for the conditional laws and an N particle approximation with a $\mathcal{O}$ $(\frac{1}{\sqrt{N}})$ asymptotic convergence. An application to nonlinear filtering for 3D atmospheric turbulent fluids will be described.

In this note, we study deterministic and stochastic models for the spread of cholera. The deterministic model for the total number of cholera cases fits the observed total number of cholera cases in some recent outbreaks. The stochastic model for the total number of cholera cases leads to a binomial type distribution with a mean that agrees with the deterministic model.

A simple model of biological evolution of community food webs is introduced. This modelis based on the niche model, which is known to generate model food webs that are verysimilar to empirical food webs. The networks evolve by speciation and extinction.Co-extinctions due to the loss of all prey species are found to play a major role indetermining the longterm shape of the food webs. The central aim is to design the modelsuch that the characteristic parameters of the niche model food webs remain in realisticintervals. When the mutation rule is chosen accordingly, it is found that food webs with acomplex, biologically meaningful structure emerge and that the statistics of extinctionevents agrees well with that observed in the paleontological data.

We propose the following simple stochastic model for phylogenetic trees. New types are born and die according to a birth and death chain. At each birth we associate a fitness to the new type sampled from a fixed distribution. At each death the type with the smallest fitness is killed. We show that if the birth (i.e. mutation) rate is subcritical, we obtain a phylogenetic tree consistent with an influenza tree (few types at any given time and one dominating type lasting a long time). When the birth rate is supercritical, we obtain a phylogenetic tree consistent with an HIV tree (many types at any given time, none lasting very long).

De nombreuses courbes de percée, obtenues en particulier en milieu poreux insaturé avec des traceurs passifs, décroissent comme des puissances du temps. Ce comportement est incompatible avec les lois de Fourier et Fick, par contre il correspond aux solutions d'une vaste classe d'équations aux dérivées partielles, incluant des opérateurs non-locaux en temps. De plus, ces équations représentent la limite macroscopique d'un grand nombre de modèles à petite échelle. Ce résultat, qui a été démontré à l'aide d'une méthode probabiliste dans le cas de paramètres uniformes et constants, est illustré par des simulations numériques dépassant ce cadre.