Long-term dynamic patterns and diversity of phytoplankton communities in a large eutrophic river (the case of River Danube, Hungary)

In this paper we present the composition, seasonal dynamics and fluctuations in diversity of the phytoplankton in the Danube River over 24 years. Weekly samplings were conducted at one section of the river at Göd, in the 1669 river kilometer segment. The change in the phytoplankton community structure was analyzed in relation of water temperature and discharge means. Our findings support the opinion that the Danube is very rich in species, although many of the species are rare and could be described only as coloring species. Results indicate trends in the phytoplankton abundance, which are only detectable in long-term studies. By the help of diversity indices we have observed an increase in the phytoplankton community diversity. With the relevant information, an explanation of the significant changes in diversity and richness was formed. Our goals were a construction of a solid database of the phytoplankton, examining the seasonal dynamics of the phytoplankton through a 24 year long study and to see the most important changing factors of the community. The results of this study are to assist and help future model developments to predict the phytoplankton seasonal dynamic patterns.

Change of composition and diversity of species and grassland management between different grazing intensity in Pannonian dry and wet grasslands

Investigations were carried out in wet and dry pasture. Coenological recordings were taken in three zones. The first zone (“A”) located 0-50 m near the stable, second zone (“B”) located 50-150 m from the stable, while the third zone (“C”) located farther than 150 m. We have carried out analyses of ecological and environmental factors and life form types. Based on our results for both dry and wet grasslands, quadrates of “A” zone were well isolated from the rest of the zones. Overgrazing, which involves considerable trampling, vanishes differences among vegetations, thereby promotes weed and disturbance tolerant rich vegetation. The lowest species number and diversity could be found here. Due to the nitrogen enrichment due to the constant presence of livestock, drier and less heat demanding habitat developed in the “A” zones, according to the environmental indicators. Because of the change in management, conservation and diversity values of “C” zone increased, however, according to nature protection values it underperformed compared to “B” zone. According to the sample area, wet grasslands from the sandy areas of Kiskunság, preserve nature protection values and grass composition better moving away from stables, due to less grazing pressure. Drier backgrounds tolerate stronger grazing pressure.

Remote learning and laboratory center over Internet and ISDN

Recent advances in telecommunications technologies have transformed the modes of learning and teaching. One potentially vital component in the equation will be Remote Education or Remote Learning, the ability to compress time and space between teachers and students through the judicious application of technology. The purpose of this thesis is to develop a Remote Learning and Laboratory Center over the Internet and ISDN, which provide education and access to resources to those living in remote areas, children in hospitals and traveling families, with audio, video and data.^ Remote Learning and Laboratory Center (RLLC) is not restricted to merely traditional education processes such as universities or colleges, it can be very useful for companies to train their engineers, via networks. This capability will facilitate the best use of scarce, high quality educational resources and will bring equity of services to students as well as will be helpful to the Industries to train their engineers. The RLLC over the Internet and ISDN has been described in details and implemented successfully. For the Remote Laboratory, the experiment procedure has been demonstrated on reprogrammable CPLD design using ISR Kit. ^

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Universal Design for Learning and Differentiated Instruction: Resolving Competing Mandates of the Individuals with Disabilities Education Act and No Child Left Behind

Recent federal mandates require accountability for providing students with disabilities access to the general education curriculum. In this paper, the authors recommend that principles of Universal Design for Learning and Differentiated Instruction can help school personnel tailor their teaching to meet the various strengths and needs of individual students.

Scaffolding in Second Language Learning and Instruction

In a study of the triadic interaction among pairs of advanced second language learners engaged in a complex language task, it was found that the scaffolding provided by the researcher was determinant in keeping the participants on task and encouraging language production, thus facilitating both language development and comprehension.

The Role of Forgiveness in Adult Learning and Education

Adverse experiences can initiate angry and negative emotions and if not addressed and resolved have the ability to impede learning. Forgiveness counseling gives learners and educators a way to extinguish the power of these hindering emotions and thereby enhance learning.

Global Learning and the Human Capability Approach: Florida International University Case Study

This case study traced the process in which Florida International University engaged to determine what students want and need from their undergraduate education. Using grounded theory, the authors discovered that the process was reflective of the human capability approach in the development of its global learning student learning outcomes.

Unity and Diversity: High School Students’ Perceptions on Multiculturalism and the Intercultural University of the State of Guerrero, Mexico

This is a mixed methods study conducted in Guerrero, Mexico, at the end of the academic year 2005-2006. The purpose of this study was to capture the perceptions held by high school students, of both indigenous and non-indigenous background, regarding the intercultural university, as well as their conceptualization of multiculturalism.

Noradrenergic modulatoins of odor learning and odor representation in the rat

How experience alters neuronal ensemble dynamics and how locus coeruleus-mediated norepinephrine release facilitates memory formation in the brain are the topics of this thesis. Here we employed a visualization technique, cellular compartment analysis of temporal activity by fluorescence in situ hybridization (catFISH), to assess activation patterns of neuronal ensembles in the olfactory bulb (OB) and anterior piriform cortex (aPC) to repeated odor inputs. Two associative learning models were used, early odor preference learning in rat pups and adult rat go-no-go odor discrimination learning. With catFISH of an immediate early gene, Arc, we showed that odor representation in the OB and aPC was sparse (~5-10%) and widely distributed. Odor associative learning enhanced the stability of the rewarded odor representation in the OB and aPC. The stable component, indexed by the overlap between the two ensembles activated by the rewarded odor at two time points, increased from ~25% to ~50% (p = 0.004-1.43E⁻4; Chapter 3 and 4). Adult odor discrimination learning promoted pattern separation between rewarded and unrewarded odor representations in the aPC. The overlap between rewarded and unrewarded odor representations reduced from ~25% to ~14% (p = 2.28E⁻⁵). However, learning an odor mixture as a rewarded odor increased the overlap of the component odor representations in the aPC from ~23% to ~44% (p = 0.010; Chapter 4). Blocking both α- and β-adrenoreceptors in the aPC prevented highly similar odor discrimination learning in adult rats, and reduced OB mitral and granule ensemble stability to the rewarded odor. Similar treatment in the OB only slowed odor discrimination learning. However, OB adrenoceptor blockade disrupted pattern separation and ensemble stability in the aPC when the rats demonstrated deficiency in discrimination (Chapter 5). In another project, the role of α₂-adrenoreceptors in the OB during early odor preference learning was studied. OB α2-adrenoceptor activation was necessary for odor learning in rat pups. α₂-adrenoceptor activation was additive with β-adrenoceptor mediated signalling to promote learning (Chapter 2). Together, these experiments suggest that odor representations are highly adaptive at the early stages of odor processing. The OB and aPC work in concert to support odor learning and top-down adrenergic input exerts a powerful modulation on both learning and odor representation.

Learning and accepting quantum physics. Re-analysis of a teaching proposal

Nella tesi è analizzata nel dettaglio una proposta didattica sulla Fisica Quantistica elaborata dal gruppo di ricerca in Didattica della Fisica dell’Università di Bologna, in collaborazione con il gruppo di ricerca in Fisica Teorica e con ricercatori del CNR di Bologna. La proposta è stata sperimentata in diverse classi V di Liceo scientifico e dalle sperimentazioni sono emersi casi significativi di studenti che non sono riusciti ad accettare la teoria quantistica come descrizione convincente ad affidabile della realtà fisica (casi di non accettazione), nonostante sembrassero aver capito la maggior parte degli argomenti e essersi ‘appropriati’ del percorso per come gli era stato proposto. Da questa evidenza sono state formulate due domande di ricerca: (1) qual è la natura di questa non accettazione? Rispecchia una presa di posizione epistemologica o è espressione di una mancanza di comprensione profonda? (2) Nel secondo caso, è possibile individuare precisi meccanismi cognitivi che possono ostacolare o facilitare l’accettazione della fisica quantistica? L’analisi di interviste individuali degli studenti ha permesso di mettere in luce tre principali esigenze cognitive (cognitive needs) che sembrano essere coinvolte nell’accettazione e nell’apprendimento della fisica quantistica: le esigenze di visualizzabilità, comparabilità e di ‘realtà’. I ‘cognitive needs’ sono stati quindi utilizzati come strumenti di analisi delle diverse proposte didattiche in letteratura e del percorso di Bologna, al fine di metterne in luce le criticità. Sono state infine avanzate alcune proposte per un suo miglioramento.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Convergence and translation: attitudes to inter-professional learning and teaching of creative problem-solving among medical and engineering students and staff

Background: Healthcare worldwide needs translation of basic ideas from engineering into the clinic. Consequently, there is increasing demand for graduates equipped with the knowledge and skills to apply interdisciplinary medicine/engineering approaches to the development of novel solutions for healthcare. The literature provides little guidance regarding barriers to, and facilitators of, effective interdisciplinary learning for engineering and medical students in a team-based project context. Methods: A quantitative survey was distributed to engineering and medical students and staff in two universities, one in Ireland and one in Belgium, to chart knowledge and practice in interdisciplinary learning and teaching, and of the teaching of innovation. Results: We report important differences for staff and students between the disciplines regarding attitudes towards, and perceptions of, the relevance of interdisciplinary learning opportunities, and the role of creativity and innovation. There was agreement across groups concerning preferred learning, instructional styles, and module content. Medical students showed greater resistance to the use of structured creativity tools and interdisciplinary teams. Conclusions: The results of this international survey will help to define the optimal learning conditions under which undergraduate engineering and medicine students can learn to consider the diverse factors which determine the success or failure of a healthcare engineering solution.

Facilitating Inclusion: Austrian Wisdom Councils as Democratic Innovation between Consensus and Diversity

Democratic innovations face the challenge of realizing deliberative democratic ideals in the context of structural inequality. Consensus decision making and expertise have been said to have exclusive effects on marginalized groups like women and ethnic and sexual minorities, which obstructs diversity. Wisdom Councils as practiced in Austria attempt to counter inequalities by including marginalized groups through the moderation technique dynamic facilitation. Exploratory participatory observations and interviews with a moderator and the participants of two Wisdom Councils in Austria provide a deeper understanding of the inclusive processes at work in Wisdom Councils facilitating a productive combination of consensus and diversity.