Abbatouy, Mohammed; Renn Hürgen and Weinig, Paul (Eds.). Intercultural Transmission of Scientific Knowledge in the Middle Ages: Graeco-Arabic-Latin. Science in Context

As the editors explain in the introduction, a workshop dedicated to 'Experience and Knowledge Structures in Arabic and Latin sciences' was held at the Max Plank Institue for the HIstory of Science...

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.

Moral disengagement: Towards a context-general category-based measure of the concept

Bandura (1986) developed the concept of moral disengagement to explain how individuals can engage in detrimental behavior while experiencing low levels of negative feelings such as guilt-feelings. Most of the research conducted on moral disengagement investigated this concept as a global concept (e.g., Bandura, Barbaranelli, Caprara, & Pastorelli, 1996; Moore, Detert, Klebe Treviño, Baker, & Mayer, 2012) while Bandura (1986, 1990) initially developed eight distinct mechanisms of moral disengagement grouped into four categories representing the various means through which moral disengagement can operate. In our work, we propose to develop measures of this concept based on its categories, namely rightness of actions, rejection of personal responsibility, distortion of negative consequences, and negative perception of the victims, and which is not specific a particular area of research. Through our measures, we aim at better understanding the cognitive process leading individuals to behave unethically by investigating which category plays a role in explaining unethical behavior depending on the situations in which individuals are. To this purpose, we conducted five studies to develop the measures and to test its predictive validity. Particularly, we assessed the ability of the newly developed measures to predict two types of unethical behaviors, i.e. discriminatory behavior and cheating behavior. Confirmatory Factor analyses demonstrated a good fit of the model and findings generally supported our predictions.

Social Cognition and Behavior in Relationship Context

Social information processing (SIP; Crick & Dodge, 1994) and social-cognitive learning theories have been often used to understand children’s problem behaviors, such as aggression. According to these theories, children’s thinking guides their subsequent behaviors. Although most of us agree that social behavior and underlying thought processes are context-dependent, personality and social development researchers have usually engaged in searching for stable patterns of dispositions and behaviors, ignoring (or treating as error) the variance across different situations and relationship types. This, however, can result in erroneous conclusions and question the interpretation of previous findings. Four studies were conducted to explore the influence of relationship context on children’s social-cognitive evaluations and behavior. Samples were fourth to sixth graders from Estonia and Finland. Social cognitions were assessed by presenting children with hypothetical vignettes where the previously identified relationship partner’s behavior had a negative consequence for the child (Studies I, II, and IV), followed by questions measuring different social-cognitive processes (e.g., hostile attributions, behavioral strategies, outcome expectations and self-efficacy beliefs for aggression). In addition, in Studies II and IV, children provided information about their behavior within a specific relationship context. In Study III, an affective priming paradigm was employed where participants were presented with a short display of photographs of children’s liked and disliked classmates, and unknown peers. The results of this thesis suggest that children’s thinking and behavior are largely influenced by the affective valence of the relationship. Moreover, cognitions guide behavior within the relationship. The current findings offer a fruitful avenue for studying the heterogeneity of peer interactions.

Innovation – from individual intuition to collaborative innovation. The role of individual key actor in facilitation of innovation in large organization context

The objective of this research was to study the role of key individuals in facilitation of technology enabled bottom-up innovation in large organization context. The development of innovation was followed from the point of view of individual actor (key individual) in two cases, through three levels: individual, team and organization, by using knowledge creation and innovation models. This study provides theoretical synthesis and framework through which the study is driven. The results of the study indicate, that in bottom-up initiated innovations the role of key individuals is still crucial, but innovation today is collective effort and there acts several entrepreneurial key individuals: innovator, user champion and organizational sponsor, whose collaboration and developing interaction drives innovation further. The team work is functional and fluent, but it meets great problems in interaction with organization. The large organizations should develop its practices and ability to react on emerging bottom-up initiations, in order to embed innovation to organization and gain sustainable innovation. In addition, bottom-up initiated innovations are demonstrations of peoples knowing, tacit knowledge and therefore renewing of an organization.

The Armc10/SVH gene: Genome context, regulation of mitochondrial dynamics and protection against Aβ-induced mitochondrial fragmentation

Mitochondrial function and dynamics are essential for neurotransmission, neural function and neuronal viability. Recently, we showed that the eutherian-specific Armcx gene cluster (Armcx1-6 genes), located in the X chromosome, encodes for a new family of proteins that localise to mitochondria, regulating mitochondrial trafficking. The Armcx gene cluster evolved by retrotransposition of the Armc10 gene mRNA, which is present in all vertebrates and is considered to be the ancestor gene. Here we investigate the genomic organisation, mitochondrial functions and putative neuroprotective role of the Armc10 ancestor gene. The genomic context of the Armc10 locus shows considerable syntenic conservation among vertebrates, and sequence comparisons and CHIP-data suggest the presence of at least three conserved enhancers. We also show that the Armc10 protein localises to mitochondria and that it is highly expressed in the brain. Furthermore, we show that Armc10 levels regulate mitochondrial trafficking in neurons, but not mitochondrial aggregation, by controlling the number of moving mitochondria. We further demonstrate that the Armc10 protein interacts with the KIF5/Miro1-2/Trak2 trafficking complex. Finally, we show that overexpression of Armc10 in neurons prevents A beta-induced mitochondrial fission and neuronal death. Our data suggest both conserved and differential roles of the Armc10/Armcx gene family in regulating mitochondrial dynamics in neurons, and underscore a protective effect of the Armc10 gene against A beta-induced toxicity. Overall, our findings support a further degree of regulation of mitochondrial dynamics in the brain of more evolved mammals.

The Armc10/SVH gene: Genome context, regulation of mitochondrial dynamics and protection against Aβ-induced mitochondrial fragmentation

Mitochondrial function and dynamics are essential for neurotransmission, neural function and neuronal viability. Recently, we showed that the eutherian-specific Armcx gene cluster (Armcx1-6 genes), located in the X chromosome, encodes for a new family of proteins that localise to mitochondria, regulating mitochondrial trafficking. The Armcx gene cluster evolved by retrotransposition of the Armc10 gene mRNA, which is present in all vertebrates and is considered to be the ancestor gene. Here we investigate the genomic organisation, mitochondrial functions and putative neuroprotective role of the Armc10 ancestor gene. The genomic context of the Armc10 locus shows considerable syntenic conservation among vertebrates, and sequence comparisons and CHIP-data suggest the presence of at least three conserved enhancers. We also show that the Armc10 protein localises to mitochondria and that it is highly expressed in the brain. Furthermore, we show that Armc10 levels regulate mitochondrial trafficking in neurons, but not mitochondrial aggregation, by controlling the number of moving mitochondria. We further demonstrate that the Armc10 protein interacts with the KIF5/Miro1-2/Trak2 trafficking complex. Finally, we show that overexpression of Armc10 in neurons prevents A beta-induced mitochondrial fission and neuronal death. Our data suggest both conserved and differential roles of the Armc10/Armcx gene family in regulating mitochondrial dynamics in neurons, and underscore a protective effect of the Armc10 gene against A beta-induced toxicity. Overall, our findings support a further degree of regulation of mitochondrial dynamics in the brain of more evolved mammals.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted

L’orquestra inclusiva dintre del context escolar

Aquest treball d’investigació pretén conèixer els factors que condicionen una pràctica instrumental inclusiva en el context escolar i d’aula; un tema poc treballat amb consciència d’universalitat en l’àrea curricular d’Educació Musical. En primer lloc, a la fonamentació teòrica, s’han extret les principals idees de diferents autors que tracten sobre el Disseny Universal, l’Ensenyament Multinivell, el treball cooperatiu i el treball musical amb instrumentació Orff. De cada un d’aquests blocs s’ha realitzat una relació entre aquestes teories i l’aplicació al context musical. Posteriorment, treballant des de la base teòrica, s’ha aplicat una intervenció a nivell escolar de dues setmanes on es pretén identificar els ítems que dificulten o afavoreixen la pràctica instrumental a l’aula i idear alternatives de pràctica instrumental inclusiva.

Challenges to patient-centred care in a general internal medicine context: findings from an exploratory study

Introduction. If we are to promote more patient-centred approaches in care delivery, we have to better characterize the situations in which being patient-centred is difficult to achieve. Data from professionals in health and social care are important because they are the people charged with operationalizing patient-centred care (PCC) in their daily practice. However, empirical accounts from frontline care providers are still lacking, and it is important to gather experiences not only from doctors but also from the other care providers. Indeed, experiences from different professions can help inform our understanding of patient care, which is expected to be both patient-centred and collaborative. Methods. This study was based on the following research question: What factors make the provision of PCC difficult to achieve? Sample and setting. A purposeful sampling technique was used, allowing for a series of choices about the participants and their professional affiliation. Because patient-centredness is the focus, 3 professions appeared to be of special interest: general internists, nurses and social workers. The study was undertaken in the General Internal Medicine Division of a teaching hospital located in a North American context. Data Collection. To answer the research question, a methodological approach based on a theory called phenomenology was chosen. Accordingly, semi-structured interviews were used since they generate understanding of the meanings different individuals have of their lived world. Interviews with 8 physicians, 10 nurses and 10 social workers were eventually conducted. Data analysis. An inductive thematic analysis was employed to make sense of the interview data. Results. The thematic analysis allowed identifying various types of challenges to PCC. Although most of the challenges were perceived by all three groups of professionals, they were perceived to a different degree across the professions, which likely reflected the scope of practice of each profession. The challenges and their distribution across the professions are illustrated in Table 1. Examples of challenges are provided in Table 2. Discussion. There is a tension between what is supposed to be done - what stands in the philosophy of patient -centredness - and what is currently done - the real life with all the challenges to PCC. According to some participants' accounts, PCC clearly risks becoming a mere illusion for health care professionals on which too great pressures are imposed.