Adaptive value of ryegrass biotypes with low-level resistance and susceptible to the herbicide fluazifop and competitive ability with the wheat culture

Ryegrass is the main weed in wheat crop, causing yield loss due to competition by environmental resources. The objectives of this study were to estimate the fitness cost of ryegrass biotypes with low-level resistance and susceptible to fluazifop and to investigate the relative competitive ability of these biotypes between themselves and against the crop. Thus, fitness cost and competitive ability experiments were conducted under greenhouse conditions. For the fitness cost experiments, the low-level resistant ryegrass biotypes and those susceptible to fluazifop were used. For competitive ability, the treatments were arranged in a replacement series, with five proportions of the wheat cultivar FUNDACEP Horizonte and the low-level resistant and susceptible ryegrass biotypes 100:0, 75:25, 50:50, 25:75 and 0:100. Competitive analysis was carried out through diagrams applied to the replacement experiments and use of relative competitiveness indices. Variables evaluated were plant height, in the fitness cost experiment, and leaf area and shoot dry biomass in both experiments. The ryegrass biotypes show overall similar fitness cost and competitive ability. The wheat cultivar FUNDACEP Horizonte is superior in competitive ability to the ryegrass biotype with low-level resistance and equivalent to the susceptible biotype.

Adaptive control of Hydraulic Drive

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for the Hydraulic Drive. The calculation needed and the modeling were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™ etc. In the work there was applied the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial. The intelligent adaptive to nonlinearities algorithm for solving Lyapunov’s equation was developed. Developed algorithm works properly but considered plant is not met requirement of functioning with. The results showed confirmation that adaptive systems application significantly increases possibilities in use devices and might be used for correction a system’s behavior dynamics.

Tropical inselbergs: habitat types, adaptive strategies and diversity patterns

Inselbergs are isolated rock outcrops that rise abruptly above the surrounding plains. Granitic and gneissic inselbergs are geologically and geomorphologically old and occur throughout a broad spectrum of climatic zones. They form microclimatically and edaphically dry growth sites that support a highly specialized vegetation. Based on physiognomic criteria a number of habitat types can be distinguished that are widespread on inselbergs (e.g. ephemeral flush vegetation, monocotyledonous mats, rock pools). Three hot spots of global inselberg plant diversity can be identified which are both rich in species and endemics: a) southeastern Brazil, b) Madagascar and c) southwestern Australia.

The board of directors as a part of family business governance – multilevel participation and board development

In this study, I examine the board of directors as a part of family business governance. Both boards and governance have increased their attractiveness as a research topic lately. Research on boards has concentrated mostly on the study of different board attributes, like composition, and the relationship of these attributes to the firm’s performance. Family business governance studies are criticized for ignoring the multifaceted needs of companies. More research observing the context and contingencies affecting the governance and board of directors is needed. The objective of this study is to clarify: 1) how the board participates in family business governance, and 2) how the board develops along with the firm’s and family’s development. The study is implemented as qualitative research, and the longitudinal process approach has been used as it provides the opportunity to examine development in context. Selection criteria for the two cases selected for this study are: active board of directors, at least one implemented succession, and interviewees available from two generations and from different positions in the firm. The data consists of interviews and secondary data, and it is collected from different data sources. The analysis was done selecting first some critical events from both cases to closer examination, and analysing them by using content analysis technique. Several conclusions were drawn basing on the findings. First, the family business board participates in the firm’s activities much more widely than it is customary to think. Second, the family business board is not a static part of the business, but it develops and it has to develop for different reasons. Third, ownership is not only the basis for the board’s activities or existence, but the relationship between the board and ownership is two-way. The board contributes to a large extent to the ownership decisions, and in this way to the management of ownership. Fourth, according to the cases, the board has many unrecognized possibilities to facilitate succession in family firms.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.

Role of the cardiac nerve in the adaptive changes of heart rate in response to an aversive stimulus in Megalobulimus mogianensis

The effect of an aversive stimulus represented by contact with a hot plate on the heart rate of Megalobulimus mogianensis was evaluated with electrocardiogram recording in intact snails (N = 8). All stimulated animals showed an increase in heart rate, with mean values ranging from 35.6 ± 1.2 (basal heart rate) to 43.8 ± 0.9 bpm (post-stimulation heart rate). The cardioacceleration was followed by gradual recovery of the basal heart rate, with mean recovery times varying from 4.3 ± 0.3 to 5.8 ± 0.6 min. Repetition of the stimulus did not affect the magnitude of variation nor did it influence the basal heart rate recovery time. To investigate the role of the cardiac nerve in mediating the heart rate alterations induced by the aversive stimulus, denervated (N = 8) and sham-operated (N = 8) animals were also tested. Although the aversive stimulus caused the heart rate to increase significantly in both experimental groups, the mean increase in heart rate in denervated animals (4.4 ± 0.4 bpm) was 57% of the value obtained in sham-operated animals (7.7 ± 1.3 bpm), indicating that the cardiac nerve is responsible for 43% of the cardioacceleration induced by the aversive stimulus. The cardioacceleration observed in denervated snails may be due to an increase in venous return promoted by the intense muscular activity associated with the withdrawal response. Humoral factors may also be involved. A probable delaying inhibitory effect of the cardiac nerve on the recuperation of the basal heart rate is suggested.

Vascular adaptive responses to physical exercise and to stress are affected differently by nandrolone administration

Androgenic anabolic steroid, physical exercise and stress induce cardiovascular adaptations including increased endothelial function. The present study investigated the effects of these conditions alone and in combination on the vascular responses of male Wistar rats. Exercise was started at 8 weeks of life (60-min swimming sessions 5 days per week for 8 weeks, while carrying a 5% body-weight load). One group received nandrolone (5 mg/kg, twice per week for 8 weeks, im). Acute immobilization stress (2 h) was induced immediately before the experimental protocol. Curves for noradrenaline were obtained for thoracic aorta, with and without endothelium from sedentary and trained rats, submitted or not to stress, treated or not with nandrolone. None of the procedures altered the vascular reactivity to noradrenaline in denuded aorta. In intact aorta, stress and exercise produced vascular adaptive responses characterized by endothelium-dependent hyporeactivity to noradrenaline. These conditions in combination did not potentiate the vascular adaptive response. Exercise-induced vascular adaptive response was abolished by nandrolone. In contrast, the aortal reactivity to noradrenaline of sedentary rats and the vascular adaptive response to stress of sedentary and trained rats were not affected by nandrolone. Maximum response for 7-10 rats/group (g): sedentary 3.8 ± 0.2 vs trained 3.0 ± 0.2*; sedentary/stress 2.7 ± 0.2 vs trained/stress 3.1 ± 0.1*; sedentary/nandrolone 3.6 ± 0.1 vs trained/nandrolone 3.8 ± 0.1; sedentary/stress/nandrolone 3.2 ± 0.1 vs trained/stress/nandrolone 2.5 ± 0.1*; *P < 0.05 compared to its respective control. Stress and physical exercise determine similar vascular adaptive response involving distinct mechanisms as indicated by the observation that only the physical exercise-induced adaptive response was abolished by nandrolone.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

Data Governance and Automated Marketing – A Case Study of Expected Benefits of Organizing Data Governance in an ICT Company

This research is looking to find out what benefits employees expect the organization of data governance gains for an organization and how it benefits implementing automated marketing capabilities. Quality and usability of the data are crucial for organizations to meet various business needs. Organizations have more data and technology available what can be utilized for example in automated marketing. Data governance addresses the organization of decision rights and accountabilities for the management of an organization’s data assets. With automated marketing it is meant sending a right message, to a right person, at a right time, automatically. The research is a single case study conducted in Finnish ICT-company. The case company was starting to organize data governance and implementing automated marketing capabilities at the time of the research. Empirical material is interviews of the employees of the case company. Content analysis is used to interpret the interviews in order to find the answers to the research questions. Theoretical framework of the research is derived from the morphology of data governance. Findings of the research indicate that the employees expect the organization of data governance among others to improve customer experience, to improve sales, to provide abilities to identify individual customer’s life-situation, ensure that the handling of the data is according to the regulations and improve operational efficiency. The organization of data governance is expected to solve problems in customer data quality that are currently hindering implementation of automated marketing capabilities.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.