Vitamin D supplementation during the first year of life and risk of schizophrenia: a Finnish birth cohort study

Objective: Based on clues from epidemiology and animal experiments, low vitamin D during early life has been proposed as a risk factor for schizophrenia. The aim of this study was to explore the association between the use of vitamin D supplements during the first year of life and risk of developing schizophrenia. Method: Subjects were drawn from the Northern Finland 1966 Birth Cohort (n = 9 114). During the first year of life, data were collected about the frequency and dose of vitamin D supplementation. Our primary outcome measures were schizophrenia, psychotic disorders other than schizophrenia, and nonpsychotic disorders as diagnosed by age 31 years. Males and females were examined separately. Results: In males, the use of either irregular or regular vitamin D supplements was associated with a reduced risk of schizophrenia (Risk ratio (RR) = 0.08, 95% CI 0.01-0.95; RR = 0.12, 95% CI 0.02-0.90, respectively) compared with no supplementation. In males, the use of at least 2000 IU of vitamin D was associated with a reduced risk of schizophrenia (RR = 0.23, 95% CI 0.06-0.95) compared to those on lower doses. There were no significant associations between either the frequency or dose of vitamin D supplements and (a) schizophrenia in females, nor with (b) nonpsychotic disorder or psychotic disorders other than schizophrenia in either males or females. Conclusion: Vitamin D supplementation during the first year of life is associated with a reduced risk of schizophrenia in males. Preventing hypovitaminosis D during early life may reduce the incidence of schizophrenia. (C) 2003 Elsevier B.V. All rights reserved.

Referência e contra referência em saúde bucal: regulação do acesso aos centros de especialidades odontológicas

Objective Based on the system of reference and counter-reference and comprehensiveness in oral health care, we aimed to examine ways of refering users to Specialized Dental Care Centers (SDCC) and the interface between them and Primary Care. Methods This is a cross-sectional study carried out with users and dentists of SDCC in a metropolitan region of Northeast of Brazil. Analyses were descriptive, and the association test was done with chi-square. Results Six forms of entry to specialized service were identified: free demand (13.8 %) and reference by the Primary Care dentist (63.2 %) were most frequent. Users referred by the basic health unit dentist had more interest in making a counter-reference than the others (p<0.001, PR=4.65, 95 % CI: 2.74 to 7.91), while individuals without this referral had 1.49 times more difficulty obtaining care (95 % CI: 1.02 to 2.17). Referral procedures are a decisive factor for counter-references. However, the high demand for primary care services and the short supply these services can offer in the face of needs make SDCC performance difficult. Conclusion The analysis of oral health practices from the perspective of network modeling points to the service's need to establish protocols for regulation in a bid to improve access to and the quality of care provided.

Referência e contra referência em saúde bucal: regulação do acesso aos centros de especialidades odontológicas

Objective Based on the system of reference and counter-reference and comprehensiveness in oral health care, we aimed to examine ways of refering users to Specialized Dental Care Centers (SDCC) and the interface between them and Primary Care. Methods This is a cross-sectional study carried out with users and dentists of SDCC in a metropolitan region of Northeast of Brazil. Analyses were descriptive, and the association test was done with chi-square. Results Six forms of entry to specialized service were identified: free demand (13.8 %) and reference by the Primary Care dentist (63.2 %) were most frequent. Users referred by the basic health unit dentist had more interest in making a counter-reference than the others (p<0.001, PR=4.65, 95 % CI: 2.74 to 7.91), while individuals without this referral had 1.49 times more difficulty obtaining care (95 % CI: 1.02 to 2.17). Referral procedures are a decisive factor for counter-references. However, the high demand for primary care services and the short supply these services can offer in the face of needs make SDCC performance difficult. Conclusion The analysis of oral health practices from the perspective of network modeling points to the service's need to establish protocols for regulation in a bid to improve access to and the quality of care provided.

Sjuksköterskans uppfattning om omvårdnadsinsatser som främjar livskvalitet vid bipolär sjukdom : En kvalitativ intervjustudie

Bakgrund: Flera studier har visat att personer med bipolär sjukdom har en sämre livskvalitet jämfört med övriga befolkningen. Som sjuksköterska inom psykiatrisk vård är det viktigt att ha kunskap om sjukdomen för att ge bästa möjliga behandling med mål att stabilisera symtom, förebygga återfall och främja livskvalitet. Syfte: Att utifrån sjuksköterskans uppfattning beskriva vilka omvårdnadsinsatser som främjar livskvalitet vid bipolär sjukdom. Metod: En kvalitativ innehållsanalys som baserades på åtta semistrukturerade intervjuer. Resultat: Resultatet visade tre huvudteman: Kunskap om sjukdomen: betydelsen av att både patient och anhöriga fick kunskap om sjukdomen; Trygghet och kontinuitet i vården: veta var och till vem man vänder sig i vården hade stor betydelse samt Personcentrerad vård: att bli sedd och bemött som en unik person. Slutsats: Patientutbildning där man tar upp vikten av regelbundna levnadsvanor, att undvika stress samt att bli medveten om sina tidiga tecken kan hjälpa att stabilisera symtom och förebygga återfall.

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.

Using an evidence-based online module to improve parents’ ability to manage their child with Developmental Coordination Disorder

Background : Developmental coordination disorder (DCD) is a prevalent neurodevelopmental disorder. Best practices include raising parents’ awareness and building capacity but few interventions incorporating these best practices are documented. Objective : To examine whether an evidence-based online module can increase the perceived knowledge and skills of parents of children with DCD, and lead to behavioural changes when managing their child’s health condition. Methods : A mixed-methods, before-after-follow-up design guided by the theory of planned behaviour was employed. Data about the knowledge, skills and behaviours of parents of children with DCD were collected using questionnaires prior to completing the module, immediately after, and three months later. One-way repeated measures ANOVAs and thematic analyses were performed on data as appropriate. Results : Fifty-eight participants completed all questionnaires. There was a significant effect of time on self-reported knowledge [F(2.00,114.00)=16.37, p=0.00] and skills [F(1.81,103.03)=51.37, p=0.00] with higher post- and follow-up scores than pre-intervention scores. Thirty-seven (65%) participants reported an intention to change behaviour postintervention; 29 (50%) participants had tried recommended strategies at follow-up. Three themes emerged to describe parents’ behavioural change: sharing information, trialing strategies and changing attitudes. Factors influencing parents’ ability to implement these behavioural changes included clear recommendations, time, and ‘right’ attitude. Perceived outcomes associated with the parental behavioural changes involved improvement in well-being for the children at school, at home, and for the family as a whole. Conclusions : The online module increased parents’ self-reported knowledge and skills in DCD management. Future research should explore its impacts on children’s outcomes long-term.

Using an evidence-based online module to improve parents’ ability to manage their child with Developmental Coordination Disorder

Background : Developmental coordination disorder (DCD) is a prevalent neurodevelopmental disorder. Best practices include raising parents’ awareness and building capacity but few interventions incorporating these best practices are documented. Objective : To examine whether an evidence-based online module can increase the perceived knowledge and skills of parents of children with DCD, and lead to behavioral changes when managing their child’s health condition. Methods : A mixed-methods, before-after design guided by the theory of planned behavior was employed. Data about the knowledge, skills and behaviors of parents of children with DCD were collected using questionnaires prior to completing the module, immediately after, and three months later. Paired T-tests, sensitivity analyses and thematic analyses were performed on data as appropriate. Results: One hundred-sixteen, 81 and 58 participants respectively completed the three questionnaires. For knowledge and skills, post- and follow-up scores were significantly higher than baseline scores (p<0.01). Fifty-two (64%) participants reported an intention to change behavior post-intervention and 29 (50%) participants had tried recommended strategies at follow-up. Three themes emerged to describe parents’ behavioral change: sharing information, trialing strategies and changing attitudes. Factors influencing parents’ ability to implement these behavioral changes included clear recommendations, time, and ‘right’ attitude. Perceived outcomes associated with the parental behavioral changes involved improvement in well-being for the children at school, at home, and for the family as a whole. Conclusions : The online module increased parents’ self-reported knowledge and skills in DCD management. Future research should explore its impacts on children’s long-term outcomes.

S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization

This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.

A feedback-based decentralised coordination model for distributed open real-time systems

Moving towards autonomous operation and management of increasingly complex open distributed real-time systems poses very significant challenges. This is particularly true when reaction to events must be done in a timely and predictable manner while guaranteeing Quality of Service (QoS) constraints imposed by users, the environment, or applications. In these scenarios, the system should be able to maintain a global feasible QoS level while allowing individual nodes to autonomously adapt under different constraints of resource availability and input quality. This paper shows how decentralised coordination of a group of autonomous interdependent nodes can emerge with little communication, based on the robust self-organising principles of feedback. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The proposed protocol is general enough to be used in a wide range of scenarios characterised by a high degree of openness and dynamism where coordination tasks need to be time dependent. As the reported results demonstrate, it requires less messages to be exchanged and it is faster to achieve a globally acceptable near-optimal solution than other available approaches.

Novel coordination polymers with (Pyrazolato)-based tectons: catalytic activity in the peroxidative oxidation of alcohols and cyclohexane

Coupling five rigid or flexible bis(pyrazolato)based tectons with late transition metal ions allowed us to isolate 18 coordination polymers (CPs). As assessed by thermal analysis, all of them possess a remarkable thermal stability, their decomposition temperatures lying in the range of 340-500 degrees C. As demonstrated by N-2 adsorption measurements at 77 K, their Langmuir specific surface areas span the rather vast range of 135-1758 m(2)/g, in agreement with the porous or dense polymeric architectures retrieved by powder X-ray diffraction structure solution methods. Two representative families of CPs, built up with either rigid or flexible spacers, were tested as catalysts in (0 the microwave-assisted solvent-free peroxidative oxidation of alcohols by t-BuOOH, and (ii) the peroxidative oxidation of cydohexane to cydohexanol and cydohexanone by H2O2 in acetonitrile. Those CPs bearing the rigid spacer, concurrently possessing higher specific surface areas, are more active than the corresponding ones with the flexible spacer. Moreover, the two copper(I)-containing CPs investigated exhibit the highest efficiency in both reactions, leading selectively to a maximum product yield of 92% (and TON up to 1.5 x 10(3)) in the oxidation of 1-phenylethanol and of 11% in the oxidation of cydohexane, the latter value being higher than that granted by the current industrial process.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Towards an engine for coordination-based architectural reconfigurations

Software reconfigurability became increasingly relevant to the architectural process due to the crescent dependency of modern societies on reliable and adaptable systems. Such systems are supposed to adapt themselves to surrounding environmental changes with minimal service disruption, if any. This paper introduces an engine that statically applies reconfigurations to (formal) models of software architectures. Reconfigurations are specified using a domain specific language— ReCooPLa—which targets the manipulation of software coordinationstructures,typicallyusedinservice-orientedarchitectures(soa).Theengine is responsible for the compilation of ReCooPLa instances and their application to the relevant coordination structures. The resulting configurations are amenable to formal analysis of qualitative and quantitative (probabilistic) properties.

Objective function based fuzzy clustering in air traffic management

Data analysis, fuzzy clustering, fuzzy rules, air traffic management

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors