Routine vaccination against pertussis and the risk of childhood asthma: a population-based cohort study

BACKGROUND: In industrialized countries vaccination coverage remains suboptimal, partly because of perception of an increased risk of asthma. Epidemiologic studies of the association between childhood vaccinations and asthma have provided conflicting results, possibly for methodologic reasons such as unreliable vaccination data, biased reporting, and reverse causation. A recent review stressed the need for additional, adequately controlled large-scale studies. OBJECTIVE: Our goal was to determine if routine childhood vaccination against pertussis was associated with subsequent development of childhood wheezing disorders and asthma in a large population-based cohort study. METHODS: In 6811 children from the general population born between 1993 and 1997 in Leicestershire, United Kingdom, respiratory symptom data from repeated questionnaire surveys up to 2003 were linked to independently collected vaccination data from the National Health Service database. We compared incident wheeze and asthma between children of different vaccination status (complete, partial, and no vaccination against pertussis) by computing hazard ratios. Analyses were based on 6048 children, 23 201 person-years of follow-up, and 2426 cases of new-onset wheeze. RESULTS: There was no evidence for an increased risk of wheeze or asthma in children vaccinated against pertussis compared with nonvaccinated children. Adjusted hazard ratios comparing fully and partially vaccinated with nonvaccinated children were close to one for both incident wheeze and asthma. CONCLUSION: This study provides no evidence of an association between vaccination against pertussis in infancy and an increased risk of later wheeze or asthma and does not support claims that vaccination against pertussis might significantly increase the risk of childhood asthma.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

Effectiveness of an Online Social Constructivist Mathematical Problem Solving Course for Malaysian Pre-Service Teachers

This study assessed the effectiveness of an online mathematical problem solving course designed using a social constructivist approach for pre-service teachers. Thirty-seven pre-service teachers at the Batu Lintang Teacher Institute, Sarawak, Malaysia were randomly selected to participate in the study. The participants were required to complete the course online without the typical face-to-face classes and they were also required to solve authentic mathematical problems in small groups of 4-5 participants based on the Polya’s Problem Solving Model via asynchronous online discussions. Quantitative and qualitative methods such as questionnaires and interviews were used to evaluate the effects of the online learning course. Findings showed that a majority of the participants were satisfied with their learning experiences in the course. There were no significant changes in the participants’ attitudes toward mathematics, while the participants’ skills in problem solving for “understand the problem” and “devise a plan” steps based on the Polya’s Model were significantly enhanced, though no improvement was apparent for “carry out the plan” and “review”. The results also showed that there were significant improvements in the participants’ critical thinking skills. Furthermore, participants with higher initial computer skills were also found to show higher performance in mathematical problem solving as compared to those with lower computer skills. However, there were no significant differences in the participants’ achievements in the course based on gender. Generally, the online social constructivist mathematical problem solving course is beneficial to the participants and ought to be given the attention it deserves as an alternative to traditional classes. Nonetheless, careful considerations need to be made in the designing and implementing of online courses to minimize problems that participants might encounter while participating in such courses.

Constructing a user experience user experience-based mobile learning environment

Mobile learning, in the past defined as learning with mobile devices, now refers to any type of learning-on-the-go or learning that takes advantage of mobile technologies. This new definition shifted its focus from the mobility of technology to the mobility of the learner (O'Malley and Stanton 2002; Sharples, Arnedillo-Sanchez et al. 2009). Placing emphasis on the mobile learner’s perspective requires studying “how the mobility of learners augmented by personal and public technology can contribute to the process of gaining new knowledge, skills, and experience” (Sharples, Arnedillo-Sanchez et al. 2009). The demands of an increasingly knowledge based society and the advances in mobile phone technology are combining to spur the growth of mobile learning. Around the world, mobile learning is predicted to be the future of online learning, and is slowly entering the mainstream education. However, for mobile learning to attain its full potential, it is essential to develop more advanced technologies that are tailored to the needs of this new learning environment. A research field that allows putting the development of such technologies onto a solid basis is user experience design, which addresses how to improve usability and therefore user acceptance of a system. Although there is no consensus definition of user experience, simply stated it focuses on how a person feels about using a product, system or service. It is generally agreed that user experience adds subjective attributes and social aspects to a space that has previously concerned itself mainly with ease-of-use. In addition, it can include users’ perceptions of usability and system efficiency. Recent advances in mobile and ubiquitous computing technologies further underline the importance of human-computer interaction and user experience (feelings, motivations, and values) with a system. Today, there are plenty of reports on the limitations of mobile technologies for learning (e.g., small screen size, slow connection), but there is a lack of research on user experience with mobile technologies. This dissertation will fill in this gap by a new approach in building a user experience-based mobile learning environment. The optimized user experience we suggest integrates three priorities, namely a) content, by improving the quality of delivered learning materials, b) the teaching and learning process, by enabling live and synchronous learning, and c) the learners themselves, by enabling a timely detection of their emotional state during mobile learning. In detail, the contributions of this thesis are as follows: • A video codec optimized for screencast videos which achieves an unprecedented compression rate while maintaining a very high video quality, and a novel UI layout for video lectures, which together enable truly mobile access to live lectures. • A new approach in HTTP-based multimedia delivery that exploits the characteristics of live lectures in a mobile context and enables a significantly improved user experience for mobile live lectures. • A non-invasive affective learning model based on multi-modal emotion detection with very high recognition rates, which enables real-time emotion detection and subsequent adaption of the learning environment on mobile devices. The technology resulting from the research presented in this thesis is in daily use at the School of Continuing Education of Shanghai Jiaotong University (SOCE), a blended-learning institution with 35.000 students.

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.

Evaluating watershed service availability under future management and climate change scenarios in the Pangani Basin

Watershed services are the benefits people obtain from the flow of water through a watershed. While demand for such services is increasing in most parts of the world, supply is getting more insecure due to human impacts on ecosystems such as climate or land use change. Population and water management authorities therefore require information on the potential availability of watershed services in the future and the trade-offs involved. In this study, the Soil and Water Assessment Tool (SWAT) is used to model watershed service availability for future management and climate change scenarios in the East African Pangani Basin. In order to quantify actual “benefits”, SWAT2005 was slightly modified, calibrated and configured at the required spatial and temporal resolution so that simulated water resources and processes could be characterized based on their valuation by stakeholders and their accessibility. The calibrated model was then used to evaluate three management and three climate scenarios. The results show that by the year 2025, not primarily the physical availability of water, but access to water resources and efficiency of use represent the greatest challenges. Water to cover basic human needs is available at least 95% of time but must be made accessible to the population through investments in distribution infrastructure. Concerning the trade-off between agricultural use and hydropower production, there is virtually no potential for an increase in hydropower even if it is given priority. Agriculture will necessarily expand spatially as a result of population growth, and can even benefit from higher irrigation water availability per area unit, given improved irrigation efficiency and enforced regulation to ensure equitable distribution of available water. The decline in services from natural terrestrial ecosystems (e.g. charcoal, food), due to the expansion of agriculture, increases the vulnerability of residents who depend on such services mostly in times of drought. The expected impacts of climate change may contribute to an increase or decrease in watershed service availability, but are only marginal and much lower than management impacts up to the year 2025.

Enterprise Integration of Smart Objects using Semantic Service Descriptions

Integrating physical objects (smart objects) and enterprise IT systems is still a labor intensive, mainly manual task done by domain experts. On one hand, enterprise IT backend systems are based on service oriented architectures (SOA) and driven by business rule engines or business process execution engines. Smart objects on the other hand are often programmed at very low levels. In this paper we describe an approach that makes the integration of smart objects with such backends systems easier. We introduce semantic endpoint descriptions based on Linked USDL. Furthermore, we show how different communication patterns can be integrated into these endpoint descriptions. The strength of our endpoint descriptions is that they can be used to automatically create REST or SOAP endpoints for enterprise systems, even if which they are not able to talk to the smart objects directly. We evaluate our proposed solution with CoAP, UDP and 6LoWPAN, as we anticipate the industry converge towards these standards. Nonetheless, our approach also allows easy integration with backend systems, even if no standardized protocol is used.

Does culture affect public service motivation? Evidence of sub-national differences in Switzerland

This article explores societal culture as an antecedent of public service motivation. Culture can be a major factor in developing an institution-based theory of public service motivation. In the field of organization theory, culture is considered a fundamental factor for explaining organization behavior. But our review of the literature reveals that culture has not been fully integrated into public service motivation theory or carefully investigated in this research stream. This study starts to fill this gap in the literature by using institutionalism and social-identity theory to predict how the sub-national Germanic and Latin cultures of Switzerland, which are measured through the mother tongues of public employees and the regional locations of public offices, affect their levels of public service motivation. Our analysis centers on two large data sets of federal and municipal employees, and produces evidence that culture has a consistent impact on public service motivation. The results show that Swiss German public employees have a significantly higher level of public service motivation on the whole, while Swiss French public employees have a significantly lower level overall. Implications for theory development and future research are discussed.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand

The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and academia commit to jointly establish the vision of Mobile Cloud Networking, to develop a fully cloud-based mobile communication and application platform.

THE MULTIPLE LOCATION TIME WEIGHTED INDEX: USING PATIENT ACTIVITY SPACES TO CALCULATE PRIMARY CARE SERVICE AREAS

Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

Social skills as predictors of communication, performance and quality of collaboration in project-based learning

The assumption that social skills are necessary ingredients of collaborative learning is well established but rarely empirically tested. In addition, most theories on collaborative learning focus on social skills only at the personal level, while the social skill configurations within a learning group might be of equal importance. Using the integrative framework, this study investigates which social skills at the personal level and at the group level are predictive of task-related e-mail communication, satisfaction with performance and perceived quality of collaboration. Data collection took place in a technology-enhanced long-term project-based learning setting for pre-service teachers. For data collection, two questionnaires were used, one at the beginning and one at the end of the learning cycle which lasted 3 months. During the project phase, the e-mail communication between group members was captured as well. The investigation of 60 project groups (N = 155 for the questionnaires; group size: two or three students) and 33 groups for the e-mail communication (N = 83) revealed that personal social skills played only a minor role compared to group level configurations of social skills in predicting satisfaction with performance, perceived quality of collaboration and communication behaviour. Members from groups that showed a high and/or homogeneous configuration of specific social skills (e.g., cooperation/compromising, leadership) usually were more satisfied and saw their group as more efficient than members from groups with a low and/or heterogeneous configuration of skills.

Institutionalizing Intensive Family Preservation Services: A Strategy for Creating Staffing Standards Based on Projections of At-Risk Children from Referral Sources

In spite of new legislation and much public and professional interest, intensive family preservation service (IFPS) remains in a vulnerable position as compared to other child welfare services. This article details a method to project ideal IFPS caseloads as a function of children who are at-risk for placement by various referral sources. Using this approach, resource allocation for IFPS can be more nearly on equal ground with the traditional child welfare functions and help IFPS to assume its needed place as a core service in the child welfare continuum.