Determinants of farmer retirement and farm succession in Finland

In the past decade, the Finnish agricultural sector has undergone rapid structural changes. The number of farms has decreased and the average farm size has increased when the number of farms transferred to new entrants has decreased. Part of the structural change in agriculture is manifested in early retirement programmes. In studying farmers exit behaviour in different countries, institutional differences, incentive programmes and constraints are found to matter. In Finland, farmers early retirement programmes were first introduced in 1974 and, during the last ten years, they have been carried out within the European Union framework for these programmes. The early retirement benefits are farmer specific and de-pend on the level of pension insurance the farmer has paid over his active farming years. In order to predict the future development of the agricultural sector, farmers have been frequently asked about their future plans and their plans for succession. However, the plans the farmers made for succession have been found to be time inconsistent. This study estimates the value of farmers stated succession plans in predicting revealed succession decisions. A stated succession plan exists when a farmer answers in a survey questionnaire that the farm is going to be transferred to a new entrant within a five-year period. The succession is revealed when the farm is transferred to a suc-cessor. Stated and revealed behaviour was estimated as a recursive Binomial Probit Model, which accounts for the censoring of the decision variables and controls for a potential correlation between the two equations. The results suggest that the succession plans, as stated by elderly farmers in the questionnaires, do not provide information that is significant and valuable in predicting true, com-pleted successions. Therefore, farmer exit should be analysed based on observed behaviour rather than on stated plans and intentions. As farm retirement plays a crucial role in determining the characteristics of structural change in agriculture, it is important to establish the factors which determine an exit from farming among eld-erly farmers and how off-farm income and income losses affect their exit choices. In this study, the observed choice of pension scheme by elderly farmers was analysed by a bivariate probit model. Despite some variations in significance and the effects of each factor, the ages of the farmer and spouse, the age and number of potential successors, farm size, income loss when retiring and the location of the farm together with the production line were found to be the most important determi-nants of early retirement and the transfer or closure of farms. Recently, the labour status of the spouse has been found to contribute significantly to individual retirement decisions. In this study, the effect of spousal retirement and economic incentives related to the timing of a farming couple s early retirement decision were analysed with a duration model. The results suggest that an expected pension in particular advances farm transfers. It was found that on farms operated by a couple, both early retirement and farm succession took place more often than on farms operated by a single person. However, the existence of a spouse delayed the timing of early retirement. Farming couples were found to co-ordinate their early retirement decisions when they both exit through agricultural retirement programmes, but such a co-ordination did not exist when one of the spouses retired under other pension schemes. Besides changes in the agricultural structure, the share and amount of off-farm income of a farm family s total income has also increased. In the study, the effect of off-farm income on farmers retirement decisions, in addition to other financial factors, was analysed. The unknown parameters were first estimated by a switching-type multivariate probit model and then by the simulated maxi-mum likelihood (SML) method, controlling for farmer specific fixed effects and serial correlation of the errors. The results suggest that elderly farmers off-farm income is a significant determinant in a farmer s choice to exit and close down the farm. However, off-farm income only has a short term effect on structural changes in agriculture since it does not significantly contribute to the timing of farm successions.

In vivo delivery of bovine viral diahorrea virus, E2 protein using hollow mesoporous silica nanoparticles

Our work focuses on the application of mesoporous silica nanoparticles as a combined delivery vehicle and adjuvant for vaccine applications. Here we present results using the viral protein, E2, from bovine viral diarrhoea virus (BVDV). BVDV infection occurs in the target species of cattle and sheep herds worldwide and is therefore of economic importance. E2 is a major immunogenic determinant of BVDV and is an ideal candidate for the development of a subunit based nanovaccine using mesoporous silica nanoparticles. Hollow type mesoporous silica nanoparticles with surface amino functionalisation (termed HMSA) were characterised and assessed for adsorption and desorption of E2. A codon-optimised version of the E2 protein (termed Opti-E2) was produced in Escherichia coli. HMSA (120 nm) had an adsorption capacity of 80 [small mu ]g Opti-E2 per mg HMSA and once bound E2 did not dissociate from the HMSA. Immunisation studies in mice with a 20 [small mu ]g dose of E2 adsorbed to 250 [small mu ]g HMSA was compared to immunisation with Opti-E2 (50 [small mu ]g) together with the traditional adjuvant Quillaja saponaria Molina tree saponins (QuilA, 10 [small mu ]g). The humoral responses with the Opti-E2/HMSA nanovaccine although slightly lower than those obtained for the Opti-E2 + QuilA group demonstrated that HMSA particles are an effective adjuvant that stimulated E2-specific antibody responses. Importantly the cell-mediated immune responses were consistently high in all mice immunised with Opti-E2/HMSA nanovaccine formulation. Therefore we have shown the Opti-E2/HMSA nanoformulation acts as an excellent adjuvant that gives both T-helper 1 and T-helper 2 mediated responses in a small animal model. This study has provided proof-of-concept towards the development of an E2 subunit nanoparticle based vaccine.

Silica vesicles as nanocarriers and adjuvants for generating both antibody and T-cell mediated immune resposes to Bovine Viral Diarrhoea Virus E2 protein

Bovine Viral Diarrhoea Virus (BVDV) is widely distributed in cattle industries and causes significant economic losses worldwide annually. A limiting factor in the development of subunit vaccines for BVDV is the need to elicit both antibody and T-cell-mediated immunity as well as addressing the toxicity of adjuvants. In this study, we have prepared novel silica vesicles (SV) as the new generation antigen carriers and adjuvants. With small particle size of 50 nm, thin wall (similar to 6 nm), large cavity (similar to 40 nm) and large entrance size (5.9 nm for SV-100 and 16 nm for SV-140), the SV showed high loading capacity (similar to 250 mu g/mg) and controlled release of codon-optimised E2 (oE2) protein, a major immunogenic determinant of BVDV. The in vivo functionality of the system was validated in mice immunisation trials comparing oE2 plus Quil A (50 mu g of oE2 plus 10 mu g of Quil A, a conventional adjuvant) to the oE2/SV-140 (50 mu g of oE2 adsorbed to 250 mu g of SV-140) or oE2/SV-140 together with 10 mu g of Quil A. Compared to the oE2 plus Quil A, which generated BVDV specific antibody responses at a titre of 10(4), the oE2/SV-140 group induced a 10 times higher antibody response. In addition, the cell-mediated response, which is essential to recognise and eliminate the invading pathogens, was also found to be higher [1954-2628 spot forming units (SFU)/million cells] in mice immunised with oE2/SV-140 in comparison to oE2 plus Quil A (512-1369 SFU/million cells). Our study has demonstrated that SV can be used as the next-generation nanocarriers and adjuvants for enhanced veterinary vaccine delivery. (C) 2014 Elsevier Ltd. All rights reserved.

Using UHF proximity loggers to quantify male–female interactions: A scoping study of estrous activity in cattle

Reproductive efficiency is an important determinant of profitable cattle breeding systems and the success of assisted reproductive techniques (ART) in wildlife conservation programs. Methods of estrous detection used in intensive beef and dairy cattle systems lack accuracy and remain the single biggest issue for improvement of reproductive rates and such methods are not practical for either large-scale extensive beef cattle enterprises or free-living mammalian species. Recent developments in UHF (ultra high frequency) proximity logger telemetry devices have been used to provide a continuous pair-wise measure of associations between individual animals for both livestock and wildlife. The objective of this study was to explore the potential of using UHF telemetry to identify the reproductive cycle phenotype in terms of intensity and duration of estrus. The study was conducted using Belmont Red (interbred Africander Brahman Hereford–Shorthorn) cattle grazing irrigated pasture on Belmont Research Station, northeastern Australia. The cow-bull associations from three groups of cows each with one bull were recorded over a 7-week breeding season and the stage of estrus was identified using ultrasonography. Telemetry data from bull and cows, collected over 4 8-day logger deployments, were log transformed and analyzed by ANOVA. Both the number and duration of bull-cow affiliations were significantly (P < 0.001) greater in estrous cows compared to anestrus cows. These results support the development of the UHF technology as a hands-off and noninvasive means of gathering socio-sexual information on both wildlife and livestock for reproductive management.

Single network adaptive critic design for power system stabilisers

The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Application of Artificial Viscosity in Establishing Supercritical Solutions to the Transonic Integra

The nonlinear singular integral equation of transonic flow is examined in the free-stream Mach number range where only solutions with shocks are known to exist. It is shown that, by the addition of an artificial viscosity term to the integral equation, even the direct iterative scheme, with the linear solution as the initial iterate, leads to convergence. Detailed tables indicating how the solution varies with changes in the parameters of the artificial viscosity term are also given. In the best cases (when the artificial viscosity is smallest), the solutions compare well with known results, their characteristic feature being the representation of the shock by steep gradients rather than by abrupt discontinuities. However, 'sharp-shock solutions' have also been obtained by the implementation of a quadratic iterative scheme with the 'artificial viscosity solution' as the initial iterate; the converged solution with a sharp shock is obtained with only a few more iterates. Finally, a review is given of various shock-capturing and shock-fitting schemes for the transonic flow equations in general, and for the transonic integral equation in particular, frequent comparisons being made with the approach of this paper.

Renormalization methods in KAM theory

It is well known that an integrable (in the sense of Arnold-Jost) Hamiltonian system gives rise to quasi-periodic motion with trajectories running on invariant tori. These tori foliate the whole phase space. If we perturb an integrable system, the Kolmogorow-Arnold-Moser (KAM) theorem states that, provided some non-degeneracy condition and that the perturbation is sufficiently small, most of the invariant tori carrying quasi-periodic motion persist, getting only slightly deformed. The measure of the persisting invariant tori is large together with the inverse of the size of the perturbation. In the first part of the thesis we shall use a Renormalization Group (RG) scheme in order to prove the classical KAM result in the case of a non analytic perturbation (the latter will only be assumed to have continuous derivatives up to a sufficiently large order). We shall proceed by solving a sequence of problems in which theperturbations are analytic approximations of the original one. We will finally show that the approximate solutions will converge to a differentiable solution of our original problem. In the second part we will use an RG scheme using continuous scales, so that instead of solving an iterative equation as in the classical RG KAM, we will end up solving a partial differential equation. This will allow us to reduce the complications of treating a sequence of iterative equations to the use of the Banach fixed point theorem in a suitable Banach space.

On the Geometry of Infinite-Dimensional Grassmannian Manifolds and Gauge Theory

This PhD Thesis is about certain infinite-dimensional Grassmannian manifolds that arise naturally in geometry, representation theory and mathematical physics. From the physics point of view one encounters these infinite-dimensional manifolds when trying to understand the second quantization of fermions. The many particle Hilbert space of the second quantized fermions is called the fermionic Fock space. A typical element of the fermionic Fock space can be thought to be a linear combination of the configurations m particles and n anti-particles . Geometrically the fermionic Fock space can be constructed as holomorphic sections of a certain (dual)determinant line bundle lying over the so called restricted Grassmannian manifold, which is a typical example of an infinite-dimensional Grassmannian manifold one encounters in QFT. The construction should be compared with its well-known finite-dimensional analogue, where one realizes an exterior power of a finite-dimensional vector space as the space of holomorphic sections of a determinant line bundle lying over a finite-dimensional Grassmannian manifold. The connection with infinite-dimensional representation theory stems from the fact that the restricted Grassmannian manifold is an infinite-dimensional homogeneous (Kähler) manifold, i.e. it is of the form G/H where G is a certain infinite-dimensional Lie group and H its subgroup. A central extension of G acts on the total space of the dual determinant line bundle and also on the space its holomorphic sections; thus G admits a (projective) representation on the fermionic Fock space. This construction also induces the so called basic representation for loop groups (of compact groups), which in turn are vitally important in string theory / conformal field theory. The Thesis consists of three chapters: the first chapter is an introduction to the backround material and the other two chapters are individually written research articles. The first article deals in a new way with the well-known question in Yang-Mills theory, when can one lift the action of the gauge transformation group on the space of connection one forms to the total space of the Fock bundle in a compatible way with the second quantized Dirac operator. In general there is an obstruction to this (called the Mickelsson-Faddeev anomaly) and various geometric interpretations for this anomaly, using such things as group extensions and bundle gerbes, have been given earlier. In this work we give a new geometric interpretation for the Faddeev-Mickelsson anomaly in terms of differentiable gerbes (certain sheaves of categories) and central extensions of Lie groupoids. The second research article deals with the question how to define a Dirac-like operator on the restricted Grassmannian manifold, which is an infinite-dimensional space and hence not in the landscape of standard Dirac operator theory. The construction relies heavily on infinite-dimensional representation theory and one of the most technically demanding challenges is to be able to introduce proper normal orderings for certain infinite sums of operators in such a way that all divergences will disappear and the infinite sum will make sense as a well-defined operator acting on a suitable Hilbert space of spinors. This research article was motivated by a more extensive ongoing project to construct twisted K-theory classes in Yang-Mills theory via a Dirac-like operator on the restricted Grassmannian manifold.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Numerical studies on quasilinear and linear elliptic equations

We explore here the acceleration of convergence of iterative methods for the solution of a class of quasilinear and linear algebraic equations. The specific systems are the finite difference form of the Navier-Stokes equations and the energy equation for recirculating flows. The acceleration procedures considered are: the successive over relaxation scheme; several implicit methods; and a second-order procedure. A new implicit method—the alternating direction line iterative method—is proposed in this paper. The method combines the advantages of the line successive over relaxation and alternating direction implicit methods. The various methods are tested for their computational economy and accuracy on a typical recirculating flow situation. The numerical experiments show that the alternating direction line iterative method is the most economical method of solving the Navier-Stokes equations for all Reynolds numbers in the laminar regime. The usual ADI method is shown to be not so attractive for large Reynolds numbers because of the loss of diagonal dominance. This loss can however be restored by a suitable choice of the relaxation parameter, but at the cost of accuracy. The accuracy of the new procedure is comparable to that of the well-tested successive overrelaxation method and to the available results in the literature. The second-order procedure turns out to be the most efficient method for the solution of the linear energy equation.

Non-linear bending of beams of variable cross-section

For the non-linear bending of cantilever beams of variable cross-section, the effect of large deformations, but with linear elasticity, is considered. The governing integral equation is solved by a numerical iterative procedure. Results for some typical cases are obtained and compared with some of those available in the literature.

Moving beyond the business plan in enterprise education

Purpose The purpose of this paper is to approach the debate surrounding the role of business plans in enterprise/entrepreneurship education from a different perspective; that of the student. The paper argues that much of the consternation within this stubborn debate derives from a lack of appreciation of the context actually occurring in the lives of our students. The paper aims to explore several arguments directly related to these contexts. Design/methodology/approach The approach is to build around a combining of cycles of reflective practice via the authors' iterative consultation with each other. The paper seeks to explore the world of the student via an enfolding of the literature, but ultimately we do not claim to have hidden our personal biases. Findings It is important to separate enterprise education (EE) from entrepreneurship education when discussing the role of the business plan. While the business plan has a place in the latter, it makes little sense for it to be a focal learning activity in the former. In addition, we see this outcome as a positive outcome for our field with little point in continuing on with what has become a fairly pointless debate. Practical implications: The paper concludes that once EE is viewed as being distinctly different from entrepreneurship education it is free to be considered with more precision what learning needs exist. Focusing on learning needs changes the direction of the discussion, with the business plan only up for discussion if it contributes a learning activity related to pre-determined learning outcomes. Originality/value The paper offers a constructive way forward from a debate that has been beset with extreme vested interests for too long.

Constrained linear minimax filter for systems with large plant uncertainties

This paper presents a method of designing a minimax filter in the presence of large plant uncertainties and constraints on the mean squared values of the estimates. The minimax filtering problem is reformulated in the framework of a deterministic optimal control problem and the method of solution employed, invokes the matrix Minimum Principle. The constrained linear filter and its relation to singular control problems has been illustrated. For the class of problems considered here it is shown that the filter can he constrained separately after carrying out the mini maximization. Numorieal examples are presented to illustrate the results.

Planar pursuit-evasion with variable speeds, part 2, barrier sections

An iterative method of constructing sections of the game surfaces from the players'' extremal trajectory maps is discussed. Barrier sections are presented for aircraft pursuit-evasion at constant altitude, with one aircraft flying at sustained speed and the other varying its speed.

Learning Nonlinear Visual Processing from Natural Images

The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.