Integrative Musterbildung kranialer Strukturen

Form und Gestalt kraniofazialer Strukturen sind primär beeinflusst durch die inhärente Integration der unterschiedlichsten Funktionssysteme und externer selektiver Einflüsse. Die Variabilität der Schädel-Morphe ist ein Indikator für solche Einflussfaktoren und damit ein idealer Gegenstand für vergleichende Analysen morphogenetischer Formbildung. Zur Ermittlung morphologisch-adaptiver Trends und Muster wurden sowohl Hypothesen zur morphologischen Differenziertheit als auch zu Korrelationen zwischen modularen Schädelkompartimenten (fazial, neurokranial, basikranial) untersucht. Zusätzlich wurden aus Schichtröntgenaufnahmen (CT) virtuelle Modelle rekonstruiert, welche die Interpretation der statistischen Befunde unterstützen sollten. Zur Berechnung der Gestaltunterschiede wurden mittels eines mechanischen Gelenkarm-Messgerätes (MicroScribe-G2) max. 85 ektokraniale Messpunkte (Landmarks) bzw. dreidimensionale Koordinaten an ca. 520 Schädeln von fünf rezenten Gattungen der Überfamilie Hominoidea (Hylobates, Pongo, Gorilla, Pan und Homo) akquiriert. Aus dem Datensatz wurden geometrische Störfaktoren (Größe, Translation, Rotation) mathematisch eliminiert und die verbleibenden Residuale bzw. ‚Gestalt-Variablen‘ diversen multivariat-statistischen Verfahren unterzogen (Faktoren, Cluster-, Regressions- und Korrelationsanalysen sowie statistische Tests). Die angewandten Methoden erhalten die geometrische Information der Untersuchungsobjekte über alle Analyseschritte hinweg und werden unter der Bezeichnung „Geometric Morphometrics (GMM)“ als aktueller Ansatz der Morphometrie zusammengefasst. Für die unterschiedlichen Fragestellungen wurden spezifische Datensätze generiert. Es konnten diverse morphologische Trends und adaptive Muster mit Hilfe der Synthese statistischer Methoden und computer-basierter Rekonstruktionen aus den generierten Datensätzen ermittelt werden. Außerdem war es möglich, präzise zu rekonstruieren, welche kranialen Strukturen innerhalb der Stichprobe miteinander wechselwirken, einzigartige Variabilitäten repräsentieren oder eher homogen gestaltet sind. Die vorliegenden Befunde lassen erkennen, dass Fazial- und Neurokranium am stärksten miteinander korrelieren, während das Basikranium geringe Abhängigkeiten in Bezug auf Gesichts- oder Hirnschädelveränderungen zeigte. Das Basikranium erweist sich zudem bei den nicht-menschlichen Hominoidea und über alle Analysen hinweg als konservative und evolutiv-persistente Struktur mit dem geringsten Veränderungs-Potential. Juvenile Individuen zeigen eine hohe Affinität zueinander und zu Formen mit einem kleinem Gesichts- und großem Hirnschädel. Während das Kranium des rezenten Menschen primär von Enkephalisation und fazialer Retraktion (Orthognathisierung) dominiert ist und somit eine einzigartige Gestalt aufweist, zeigt sich der Kauapparat als maßgeblich formbildendes Kompartiment bei den nicht-menschlichen Formen. Die Verbindung von GMM mit den interaktiven Möglichkeiten computergenerierter Modelle erwies sich als valides Werkzeug zur Erfassung der aufgeworfenen Fragestellungen. Die Interpretation der Befunde ist durch massive Interkorrelationen der untersuchten Strukturen und der statistisch-mathematischen Prozeduren als hoch komplex zu kennzeichnen. Die Studie präsentiert einen innovativen Ansatz der modernen Morphometrie, welcher für zukünftige Untersuchungen im Bereich der kraniofazialen Gestaltanalyse ausgebaut werden könnte. Dabei verspricht die Verknüpfung mit ‚klassischen’ und modernen Zugängen (z. B. Molekularbiologie) gesteigerte Erkenntnismöglichkeiten für künftige morphometrische Fragestellungen.

The role of metabotropic glutamate receptor 5 in the pathogenesis of mood disorders and addiction: combining preclinical evidence with human Positron Emission Tomography (PET) studies.

In the present review, we deliver an overview of the involvement of metabotropic glutamate receptor 5 (mGluR5) activity and density in pathological anxiety, mood disorders and addiction. Specifically, we will describe mGluR5 studies in humans that employed Positron Emission Tomography (PET) and combined the findings with preclinical animal research. This combined view of different methodological approaches-from basic neurobiological approaches to human studies-might give a more comprehensive and clinically relevant view of mGluR5 function in mental health than the view on preclinical data alone. We will also review the current research data on mGluR5 along the Research Domain Criteria (RDoC). Firstly, we found evidence of abnormal glutamate activity related to the positive and negative valence systems, which would suggest that antagonistic mGluR5 intervention has prominent anti-addictive, anti-depressive and anxiolytic effects. Secondly, there is evidence that mGluR5 plays an important role in systems for social functioning and the response to social stress. Finally, mGluR5's important role in sleep homeostasis suggests that this glutamate receptor may play an important role in RDoC's arousal and modulatory systems domain. Glutamate was previously mostly investigated in non-human studies, however initial human clinical PET research now also supports the hypothesis that, by mediating brain excitability, neuroplasticity and social cognition, abnormal metabotropic glutamate activity might predispose individuals to a broad range of psychiatric problems.

El desarrollo como estrategia adaptativa : Características exclusivas de la infancia humana

En este trabajo se presenta una hipótesis evolucionista acerca del desarrollo. Se compara la infancia humana con la de los primates no humanos y se describen sus rasgos exclusivos vinculados con la extensión y transformación del mundo emocional, la interacción adulto-bebé y la formación de procesos psicológicos complejos. Se argumenta a favor del papel constitutivo de las artes temporales en cada uno de los rasgos descriptos

El desarrollo como estrategia adaptativa : Características exclusivas de la infancia humana

En este trabajo se presenta una hipótesis evolucionista acerca del desarrollo. Se compara la infancia humana con la de los primates no humanos y se describen sus rasgos exclusivos vinculados con la extensión y transformación del mundo emocional, la interacción adulto-bebé y la formación de procesos psicológicos complejos. Se argumenta a favor del papel constitutivo de las artes temporales en cada uno de los rasgos descriptos

El desarrollo como estrategia adaptativa : Características exclusivas de la infancia humana

En este trabajo se presenta una hipótesis evolucionista acerca del desarrollo. Se compara la infancia humana con la de los primates no humanos y se describen sus rasgos exclusivos vinculados con la extensión y transformación del mundo emocional, la interacción adulto-bebé y la formación de procesos psicológicos complejos. Se argumenta a favor del papel constitutivo de las artes temporales en cada uno de los rasgos descriptos

Multiple genotypes of Chlamydia pneumoniae identified in human carotid plaque

Chlamydia pneumoniae is an obligate intracellular respiratory pathogen that causes 10% of community-acquired pneumonia and has been associated with cardiovascular disease. Both whole-genome sequencing and specific gene typing suggest that there is relatively little genetic variation in human isolates of C. pneumoniae. To date, there has been little genomic analysis of strains from human cardiovascular sites. The genotypes of C. pneumoniae present in human atherosclerotic carotid plaque were analysed and several polymorphisms in the variable domain 4 (VD4) region of the outer-membrane protein-A (ompA) gene and the intergenic region between the ygeD and uridine kinase (ygeD-urk) genes were found. While one genotype was identified that was the same as one reported previously in humans (respiratory and cardiovascular), another genotype was found that was identical to a genotype from non-human sources (frog/koala).

Mirror neurons in the tree of life, development and evolution of sensorimotor matching responses

Mirror neurons in the tree of life rappresenta lo sviluppo e l' evoluzione del sistema dei neuroni specchio nei primati umani, non - umani e di alcune specie di uccelli, utilizzando metodi cooptati dalla filosofia della biologia e la biologia teorica, per integrare dati relativi al sistema nervoso e al comportamento delle specie in esame.

Emerging of human factor in risk analysis of home care service

Risk management in healthcare represents a group of various complex actions, implemented to improve the quality of healthcare services and guarantee the patients safety. Risks cannot be eliminated, but it can be controlled with different risk assessment methods derived from industrial applications and among these the Failure Mode Effect and Criticality Analysis (FMECA) is a largely used methodology. The main purpose of this work is the analysis of failure modes of the Home Care (HC) service provided by local healthcare unit of Naples (ASL NA1) to focus attention on human and non human factors according to the organization framework selected by WHO. © Springer International Publishing Switzerland 2014.

Humankindness: Illness, Animality, and the Limits of the Human in the Victorian Novel

This project posits a link between representations of animals or animality and representations of illness in the Victorian novel, and examines the narrative uses and ideological consequences of such representations. Figurations of animality and illness in Victorian fiction have been examined extensively as distinct phenomena, but examining their connection allows for a more complex view of the role of sympathy in the Victorian novel. The commonplace in novel criticism is that Victorian authors, whether effectively or not, constructed their novels with a view to the expansion of sympathy. This dissertation intervenes in the discussion of the Victorian novel as a vehicle for sympathy by positing that texts and scenes in which representations of illness and animality are conjoined reveal where the novel draws the boundaries of the human, and the often surprising limits it sets on sympathetic feeling. In such moments, textual cues train or direct readerly sympathies in ways that suggest a particular definition of the human, but that direction of sympathy is not always towards an enlarged sympathy, or an enlarged definition of the human. There is an equally (and increasingly) powerful antipathetic impulse in many of these texts, which estranges readerly sympathy from putatively deviant, degenerate, or dangerous groups. These two opposing impulses—the sympathetic and the antipathetic—often coexist in the same novel or even the same scene, creating an ideological and affective friction, and both draw on the same tropes of illness and animality. Examining the intersection of these different discourses—sympathy, illness, and animality-- in these novels reveals the way that major Victorian debates about human nature, evolution and degeneration, and moral responsibility shaped the novels of the era as vehicles for both antipathy and sympathy. Focusing on the novels of the Brontës and Thomas Hardy, this dissertation examines in depth the interconnected ways that representations of animals and animality and representations of illness function in the Victorian novel, as they allow authors to explore or redefine the boundary between the human and the non-human, the boundary between sympathy and antipathy, and the limits of sympathy itself.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

Imigrantes bolivianos em São Paulo : a Praça Kantuta e o futebol

Universidade Estadual de Campinas . Faculdade de Educação Física

Análises do matching de identidade generalizado por contingências de três e quatro termos: implicações para equivalência de estímulos

A expansão da tríplice continência em unidades com quatro ou mais elementos abriu novas perspectivas para a compreensão de comportamentos complexos, como a emergência de respostas que derivam da formação de classes de estímulos equivalentes e que modelam comportamentos simbólicos e conceituais. Na investigação experimental, o procedimento de matching to sample tem sido frequentemente empregado para estabelecer discriminações condicionais. Em particular, a obtenção do matching de identidade generalizado é considerada demonstrativa da aquisição dos conceitos de igualdade e diferença. Segundo argumentamos, o fato de se buscar a compreensão desses conceitos a partir de processos discriminativos condicionais pode ter sido responsável pelos frequentes fracassos em demonstrá-los em sujeitos não humanos. A falta de correspondência entre os processos discriminativos responsáveis por estabelecer a relação de reflexividade entre estímulos que formam classes equivalentes e o matching de identidade generalizado, nesse sentido, é aqui revista ao longo de estudos empíricos e discutida com respeito às suas implicações.

O mar não está para peixe : uma etnografia dos conflitos socioambientais em torno da Zona de Proteção Marinha e da comunidade pesqueira do Bugigão – RESEXMAR do Corumbau/Bahia.

A Reserva Extrativista Marinha (RESEXMAR) do Corumbau foi criada no ano de 2000, a partir de uma ação coletiva, iniciada em 1997 por meio das lideranças de pescadores locais, na busca de instrumento jurídico que garantisse o acesso exclusivo dos recursos pesqueiros contra a atividade da pesca comercial de camarão sete-barbas que se instalou na década de 1980. Durante o processo de criação da RESEXMAR do Corumbau, os pescadores obtiveram apoio de órgãos governamentais, como a Coordenação Nacional de Populações Tradicionais (CNPT) e de entidades ambientalistas do terceiro setor – Associação Pradense de Proteção Ambiental (APPA), e posteriormente a Conservation International do Brasil (CI-Brasil). Entretanto, após a criação da RESEXMAR do Corumbau – entre os anos 2000 e 2002 – foi elaborado o Plano de Manejo que orientaria a gestão da Unidade de Conservação (UC). O documento foi capitaneado pela equipe técnica e científica vinculada à CI-Brasil, tendo como ponto de destaque a criação de áreas de exclusão total da atividade da pesca, por meio da Zona de Proteção Marinha (ZPM). A ideia de uma ZPM, para a CI-Brasil, era que de forma indireta e em médio e longo prazo, os pescadores se beneficiariam com o possível aumento de produção de pescado, contanto que 30% de cobertura de recifes tivesse algum tipo de proteção dos processos ecológicos, tais como reprodução e crescimento de espécies. Durante as discussões do Plano de Manejo e atualmente uma parcela de pescadores locais contestaram os limites da ZPM, pois iria restringir o acesso aos recursos pesqueiros. No entanto, tal contestação foi suprimida pelas relações não formais que os membros da CI-Brasil possuíam com o núcleo familiar principal da Vila do Corumbau, forçando os demais em um acordo formal temporário. Tal questionamento evidenciou um conflito de conjunto de normas distintas entre pescadores artesanais em relação à CI-Brasil e IBAMA: a pesca artesanal ‒ um tipo de ação que segue normas específicas das quais elementos humanos e não humanos interagem conjuntamente, evidenciando um conhecimento prático e corporizado constituindo um modelo compreensivo de mundo e de natureza; conceitos modernos e globalizantes de uma natureza totalmente desvinculada das práticas locais artesanais, com forte articulação de uma entidade ambientalista de alcance internacional, guiada pela emergência das questões ambientais, imprimindo no local (o lugar da prática da pesca tradicional) a ideia de um espaço (Áreas Marinhas Protegidas), desencaixado de formas específicas de natureza/culturas.

Redes, (en)traves e cercas : notas etnográficas de um conflito socioambiental

Esta dissertação pretende contribuir no debate sobre o conflito socioambiental existente no Campinho, situado no alto do morro da Fonte Grande, Vitória (ES), cenário de uma disputa, profundamente desigual em termos de poder político dos agentes humanos envolvidos, por um espaço urbano “verde” imprensado entre duas secções de uma área de proteção integral, em que habita um coletivo há gerações. Através da etnografia, procurei seguir atores humanos e não-humanos para entender as representações dos ambientalistas, gestores e técnicos ambientais bem como do coletivo, cujas perspectivas defendidas reiteram de um lado a oposição entre natureza e sociedade, consolidando políticas de reclusão (natural) e exclusão (social), e de outro a permanência e o pertencimento ao lugar, como guardiões atuantes de outro regime de relações entre humanos e não-humanos.