Social aspects of organic agriculture and other multifunctional benefits - Successful EU models compared with possibilities for organic developments in Croatia

Main objective of the dissertation is to illustrate how social and educational aspects (in close interaction with other multifunctional aspects in organic agriculture) which are developed on different multifunctional organic farms in Italy and Netherlands, as well as established agricultural policy frameworks in these countries, can be compared with the situation in Croatian organics and can contribute to further developent of organic issues in the Repubic of Croatia. So, through different chapters, the dissertation describes the performance of organic agriculture sectors in Italy, Netherlands and Croatia within the national agricultural policy frameworks, it analyzes the role of national institutions and policy in Croatia in connection with Croatia's status of candidate country for enterance into EU and harmonization of legislation with the CAP, as well as analyzes what is the role of national authorities, universities, research centres, but also of private initiatives, NGOs and cooperatives in organic agriculture in Netherlands, Italy and Croatia. Its main part describes how social and educational aspects are interacting with other multifunctional aspects in organic agriculture and analyzes the benefits and contribution of multifunctional activites performed on organic farms to education, healthy nourishment, environment protection and health care. It also assess the strengths and weaknesses of organic agriculture in all researched countries. The dissertation concludes with development opportunities for multifunctional organic agriculture in Croatia, as well as giving perspectives and recommendations for different approaches on the basis of experiences learned from successful EU models accompanied with some personal ideas and proposals.

Knowledge Management and Decision Support for Sustainable Land Management

Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

How do different aspects of self-regulation predict successful adaptation to school?

Self-regulation plays an important role in successful adaptation to preschool and school contexts as well as in later academic achievement. The current study relates different aspects of self-regulation such as temperamental effortful control and executive functions (updating, inhibition, and shifting) to different aspects of adaptation to school such as learning-related behavior, school grades, and performance in standardized achievement tests. The relationship between executive functions/effortful control and academic achievement has been established in previous studies; however, little is known about their unique contributions to different aspects of adaptation to school and the interplay of these factors in young school children. Results of a 1-year longitudinal study (N = 459) revealed that unique contributions of effortful control (parental report) to school grades were fully mediated by children’s learning-related behavior. On the other hand, the unique contributions of executive functions (performance on tasks) to school grades were only partially mediated by children’s learning-related behavior. Moreover, executive functions predicted performance in standardized achievement tests exclusively, with comparable predictive power for mathematical and reading/writing skills. Controlling for fluid intelligence did not change the pattern of prediction substantially, and fluid intelligence did not explain any variance above that of the two included aspects of self-regulation. Although effortful control and executive functions were not significantly related to each other, both aspects of self-regulation were shown to be important for fostering early learning and good classroom adjustment in children around transition to school.

Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. ^ In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). ^ The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models.^

Evaluation of the mechanical properties of self compacting concrete using current estimating models. Estimating the modulus of elasticity, tensile strength, and modulus of rupture of self compacting concrete

This study includes an analysis of the applicability of current models used for estimating the mechanical properties of conventional concrete to self-compacting concrete. The mechanical properties evaluated are: modulus of elasticity, tensile strength, and modulus of rupture. An extensive database which included the dosifications and the mechanical properties of 627 mixtures from 138 different references, was used. The models considered are: ACI, EC-2, NZS 3101:2006 (New Zealand code) and the CSA A23.3-04 (Canadian code). The precision in estimating the modulus of elasticity and tensile strength is acceptable for all models; however, all models are less precise in estimating the modulus of rupture.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Mechanical properties of self-consolidating concrete using conventional concrete models

The objective of this study is to analyze the applicability of current models used for estimating the mechanical properties of conventional concrete to self-consolidating concrete (SCC). The mechanical properties evaluated are modulus of elasticity, tensile strength,and modulus of rupture. As part of the study, it was necessary to build an extensive database that included the proportions and mechanical properties of 627 mixtures from 138 different references. The same models that are currently used for calculating the mechanical properties of conventional concrete were applied to SCC to evaluate their applicability to this type of concrete. The models considered are the ACI 318, ACI 363R, and EC2. These are the most commonly used models worldwide. In the first part of the study, the overall behavior and adaptability of the different models to SCC is evaluated. The specific characterization parameters for each concrete mixture are used to calculate the various mechanical properties applying the different estimation models. The second part of the analysis consists of comparing the experimental results of all the mixtures included in the database with the estimated results to evaluate the applicability of these models to SCC. Various statistical procedures, such as regression analysis and residual analysis, are used to compare the predicted and measured properties. It terms of general applicability, the evaluated models are suitable for estimating the modulus of elasticity, tensile strength, and modulus of rupture of SCC. These models have a rather low sensitivity, however, and adjust well only to mean values. This is because the models use the compressive strength as the main variable to characterize the concrete and do not consider other variables that affect these properties.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

On the generative equations of fractal self-similarity in granular media and the related PSD models

The physical appearance of granular media suggests the existence of geometrical scale invariance. The paper discuss how this physico-empirical property can be mathematically encoded leading to different generative models: a smooth one encoded by a differential equation and another encoded by an equation coming from a measure theoretical property.

Characteristic study, its identification and self-tuned approach to control hydro-power plants

The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

Compaslab.org, competences to be an ace. Learning design for a successful sustainable employability

Companies are looking for workers trained in soft skills, and we want to help in the learning process. How? Through three courses (Building trust through values, soft skills and entrepreneurship) and historical aces, characters who joined strong values, intellectual and social capabilities and an entrepreneurial spirit, to leave a legacy. CompasLab.org = Values + Skills + Action.