The psychometric properties of the brief Other as Shamer Scale for Children (OAS���C) : preliminary validation studies in a sample of Portuguese children

Shame is a social emotion with adaptive functions involved in human be-havior and social interactions. This emotion is regarded as an involuntary response associated with increased self-awareness, loss of status and self-devaluation (Gilbert, 1998), that may render individuals more prone to psychopathology (Gilbert, 1998; Pinto-Gouveia & Matos, 2011). Thus, identifying and assessing feelings of shame in childhood is essential in addressing the actual impact of shame on individual���s developmental trajectory. The Other As Shamer Scale (OAS; Goss, Gilbert & Allan, 1994) is a widely used measure of external shame, adapted and translated to several languages ��� including Portuguese (Matos, Pinto-Gouveia, Gilbert, Duarte & Figueiredo, 2015) ��� to adult and to adolescent populations (OASB-A - Other As Shamer Brief for adolescents; translated and adapted by Cunha, Xavier, Cherpe & Pinto-Gouveia, 2014). The current study aims to adapt and to explore the psychometric proper-ties of the brief OAS in a sample of Portuguese children attending to elementary schools.

Rapport sur le fonctionnement du Service Oc��anographique des P��ches de L'Indochine pendant l'ann��e 1926-1927

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1926-1927.

Rapport sur le fonctionnement du Service Oc��anographique des P��ches de l'Indochine pendant l'ann��e 1927-1928

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1927-1928.

Rapport sur le fonctionnement du Service Oc��anographique des P��ches de l'Indochine pendant l'ann��e 1928-1929

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1928-1929.

Rapport sur le fonctionnement du l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1929-1930

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1929-1930.

Rapport sur le fonctionnement du l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1930-1931

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1930-1931.

Rapport sur le fonctionnement du l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1931-1932

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1931-1932.

Rapport sur le fonctionnement de l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1932-1933

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1932-1933.

Rapport sur le fonctionnement du l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1933-1934

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1933-1934.

Rapport sur le fonctionnement de l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1934-1935

The present note deals with the functions and activities done by the Institute of oceanography of Indochina during 1934-1935.

'Bayesian Optimisation for Nurse Scheduling'

A Bayesian optimisation algorithm for a nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. When a human scheduler works, he normally builds a schedule systematically 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 yet completed, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this paper, we design a more human-like scheduling algorithm, by using a Bayesian optimisation algorithm to implement explicit learning from past solutions. A nurse scheduling problem from a UK hospital is used for testing. Unlike our previous work that used Genetic Algorithms to implement implicit learning [1], the learning in the proposed algorithm is explicit, i.e. we identify and mix building blocks directly. The Bayesian optimisation algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, new rule strings have been obtained. Sets of rule strings are generated in this way, some of which will replace previous strings based on fitness. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. For clarity, consider the following toy example of scheduling five nurses with two rules (1: random allocation, 2: allocate nurse to low-cost shifts). In the beginning of the search, the probabilities of choosing rule 1 or 2 for each nurse is equal, i.e. 50%. After a few iterations, due to the selection pressure and reinforcement learning, we experience two solution pathways: Because pure low-cost or random allocation produces low quality solutions, either rule 1 is used for the first 2-3 nurses and rule 2 on remainder or vice versa. In essence, Bayesian network learns 'use rule 2 after 2-3x using rule 1' or vice versa. It should be noted that for our and most other scheduling problems, the structure of the network model is known and all 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. For our problem, we use our rules: Random, Cheapest Cost, Best Cover and Balance of Cost and Cover. In more detail, the steps of our Bayesian optimisation algorithm for nurse scheduling are: 1. Set t = 0, and generate an initial population P(0) at random; 2. Use roulette-wheel selection to choose a set of promising rule strings S(t) from P(t); 3. Compute conditional probabilities of each node according to this set of promising solutions; 4. Assign each nurse using roulette-wheel selection based on the rules' conditional probabilities. A set of new rule strings O(t) will be generated in this way; 5. Create a new population P(t+1) by replacing some rule strings from P(t) with O(t), and set t = t+1; 6. If the termination conditions are not met (we use 2000 generations), go to step 2. Computational results from 52 real data instances demonstrate the success of this approach. They also suggest that the learning mechanism in the proposed approach might be suitable for other scheduling problems. Another direction for further research is to see if there is a good constructing sequence for individual data instances, given a fixed nurse scheduling order. If so, the good patterns could be recognized and then extracted as new domain knowledge. Thus, by using this extracted knowledge, we can assign specific rules to the corresponding nurses beforehand, and only schedule the remaining nurses with all available rules, making it possible to reduce the solution space. Acknowledgements The work was funded by the UK Government's major funding agency, Engineering and Physical Sciences Research Council (EPSRC), under grand GR/R92899/01. References [1] Aickelin U, "An Indirect Genetic Algorithm for Set Covering Problems", Journal of the Operational Research Society, 53(10): 1118-1126,

O papel das representa����es na resolu����o de problemas de Matem��tica: um estudo no 1�� ano de escolaridade

Este estudo tem como objectivo investigar o papel que as representa����es, constru��das por alunos do 1.o ano de escolaridade, desempenham na resolu����o de problemas de Matem��tica. Mais concretamente, a presente investiga����o procura responder ��s seguintes quest��es: Que representa����es preferenciais utilizam os alunos para resolver problemas? De que forma �� que as diferentes representa����es s��o influenciadas pelas estrat��gias de resolu����o de problemas utilizadas pelos alunos? Que pap��is t��m os diferentes tipos de representa����o na resolu����o dos problemas? Nesta investiga����o assume-se que a resolu����o de problemas constitui uma actividade muito importante na aprendizagem da Matem��tica no 1.o Ciclo do Ensino B��sico. Os problemas devem ser variados, apelar a estrat��gias diversificadas de resolu����o e permitir diferentes representa����es por parte dos alunos. As representa����es cativas, ic��nicas e simb��licas constituem importantes ferramentas para os alunos organizarem, registarem e comunicarem as suas ideias matem��ticas, nomeadamente no ��mbito da resolu����o de problemas, servindo igualmente de apoio �� compreens��o de conceitos e rela����es matem��ticas. A metodologia de investiga����o segue uma abordagem interpretativa tomando por design o estudo de caso. Trata-se simultaneamente de uma investiga����o sobre a pr��pria pr��tica, correspondendo os quatro estudos de caso a quatro alunos da turma de 1.0 ano de escolaridade da investigadora. A recolha de dados teve lugar durante o ano lectivo 2007/2008 e recorreu �� observa����o, �� an��lise de documentos, a di��rios, a registos ��udio/v��deo e ainda a conversas com os alunos. A an��lise de dados que, numa primeira fase, acompanhou a recolha de dados, teve como base o problema e as quest��es da investiga����o bem como o referencial te��rico que serviu de suporte �� investiga����o. Com base no referencial te��rico e durante o in��cio do processo de an��lise, foram definidas as categorias de an��lise principais, sujeitas posteriormente a um processo de adequa����o e refinamento no decorrer da an��lise e tratamento dos dados recolhidos -com vista �� constru����o dos casos em estudo. Os resultados desta investiga����o apontam as representa����es do tipo ic��nico e as do tipo simb��lico como as representa����es preferenciais dos alunos, embora sejam utilizadas de formas diferentes, com fun����es distintas e em contextos diversos. Os elementos simb��licos apoiam-se frequentemente em elementos ic��nicos, sendo estes ��ltimos que ajudam os alunos a descompactar o problema e a interpret��-lo. Nas representa����es ic��nicas enfatiza-se o papel do diagrama, o qual constitui uma preciosa ferramenta de apoio ao racioc��nio matem��tico. Conclui-se ainda que enquanto as representa����es activas d��o mais apoio a estrat��gias de resolu����o que envolvem simula����o, as representa����es ic��nicas e simb��licas s��o utilizadas com estrat��gias diversificadas. As representa����es constru��das, com pap��is e fun����es diferentes entre si, e que desempenham um papel crucial na correcta interpreta����o e resolu����o dos problemas, parecem estar directamente relacionadas com as carater��sticas da tarefa proposta no que diz respeito ��s estruturas matem��ticas envolvidas. ABSTRACT; The objective of the present study is to investigate the role of the representations constructed by 1st grade students in mathematical problem solving. More specifically, this research is oriented by the following questions: Which representations are preferably used by students to solve problems? ln which way the strategies adopted by the students in problem solving influence those distinct representations? What is the role of the distinct types of representation in the problems solving process? ln this research it is assumed that the resolution of problems is a very important activity in the Mathematics learning at the first cycle of basic education. The problems must be varied, appealing to diverse strategies of resolution and allow students to construct distinct representations. The active, iconic and symbolic representations are important tools for students to organize, to record and to communicate their mathematical ideas, particularly in problem solving context, as well as supporting the understanding of mathematical concepts and relationships. The adopted research methodology follows an interpretative approach, and was developed in the context of the researcher classroom, originating four case studies corresponding to four 1 st grade students of the researcher's class. Data collection was carried out during the academic year of 2007/2008 and was based on observation, analysis of documents, diaries, audio and video records and informal conversations with students. The initial data analysis was based on the problems and issues of research, as well in the theoretical framework that supports it. The main categories of analysis were defined based on the theoretical framework, and were subjected to a process of adaptation and refining during data processing and analysis aiming the -case studies construction. The results show that student's preferential representations are the iconic and the symbolic, although these types of representations are used in different ways, with different functions and in different contexts. The symbolic elements are often supported by iconic elements, the latter helping students to unpack the problem and interpret it. ln the iconic representations the role of the diagrams is emphasized, consisting in a valuable tool to support the mathematical reasoning. One can also conclude that while the active representations give more support to the resolution strategies involving simulation, the iconic and symbolic representations are preferably used with different strategies. The representations constructed with distinct roles and functions, are crucial in the proper interpretation and resolution of problems, and seem to be directly related to the characteristics of the proposed task with regard to the mathematical structures involved.

Rapport sur le fonctionnement de l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1935-1936

The present note deals with the functions and activities carried out by the Institute of oceanography of Indochina during 1935-1936

Rapport sur le fonctionnement de l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1936-1937

The present note deals with the functions and activities carried out by the Institute of oceanography of Indochina during 1936-1937

Rapport sur le fonctionnement de l'Institut Oc��anographique de l'Indochine pendant l'ann��e 1937-1938

The present note deals with the functions and activities carried out by the Institute of oceanography of Indochina during 1937-1938