A Novel Long-term, Multi-Channel and Non-invasive Electrophysiology Platform for Zebrafish.

Zebrafish are a popular vertebrate model for human neurological disorders and drug discovery. Although fecundity, breeding convenience, genetic homology and optical transparency have been key advantages, laborious and invasive procedures are required for electrophysiological studies. Using an electrode-integrated microfluidic system, here we demonstrate a novel multichannel electrophysiology unit to record multiple zebrafish. This platform allows spontaneous alignment of zebrafish and maintains, over days, close contact between head and multiple surface electrodes, enabling non-invasive long-term electroencephalographic recording. First, we demonstrate that electrographic seizure events, induced by pentylenetetrazole, can be reliably distinguished from eye or tail movement artifacts, and quantifiably identified with our unique algorithm. Second, we show long-term monitoring during epileptogenic progression in a scn1lab mutant recapitulating human Dravet syndrome. Third, we provide an example of cross-over pharmacology antiepileptic drug testing. Such promising features of this integrated microfluidic platform will greatly facilitate high-throughput drug screening and electrophysiological characterization of epileptic zebrafish

Community sewage sensors towards evaluation of drug use trends: detection of cocaine in wastewater with DNA-directed immobilization aptamer sensors

Illicit drug use has a global concern and effective monitoring and interventions are highly required to combat drug abuse. Wastewater-based epidemiology (WBE) is an innovative and cost-effective approach to evaluate community-wide drug use trends, compared to traditional population surveys. Here we report for the first time, a novel quantitative community sewage sensor (namely DNA-directed immobilization of aptamer sensors, DDIAS) for rapid and cost-effective estimation of cocaine use trends via WBE. Thiolated single-stranded DNA (ssDNA) probe was hybridized with aptamer ssDNA in solution, followed by co-immobilization with 6-mercapto-hexane onto the gold electrodes to control the surface density to effectively bind with cocaine. DDIAS was optimized to detect cocaine at as low as 10 nM with a dynamic range from 10 nM to 5 μM, which were further employed for the quantification of cocaine in wastewater samples collected from a wastewater treatment plant in seven consecutive days. The concentration pattern of the sampling week is comparable with that from mass spectrometry. Our results demonstrate that the developed DDIAS can be used as community sewage sensors for rapid and cost-effective evaluation of drug use trends, and potentially implemented as a powerful tool for on-site and real-time monitoring of wastewater by un-skilled personnel

Advances in Microfluidic Technologies for Energy and Environmental Applications

Microfluidics have aroused a new surge of interest in recent years in environmental and energy areas, and inspired novel applications to tackle the worldwide challenges for sustainable development. This book aims to present readers with a valuable compendium of significant advances in applying the multidisciplinary microfluidic technologies to address energy and environmental problems in a plethora of areas such as environmental monitoring and detection, new nanofluid application in traditional mechanical manufacturing processes, development of novel biosensors, and thermal management. This book will provide a new perspective to the understanding of the ever-growing importance of microfluidics

Enhancing Social Media Platforms for Educational and Humanitarian Knowledge Sharing:Analytics, Privacy, Discovery, and Delivery Aspects

Social media (SM) platforms have demonstrated their ability to facilitate knowledge sharing on the global scale. They are increasingly often employed in educational and humanitarian domains where, despite their general benefits, they expose challenges peculiar to these domains. Specifically, the research context of this thesis is directed by my participation in the Go-Lab European project and my collaboration with Médecins Sans Frontières (MSF) where SM platforms were used extensively. In this thesis, we address four challenges regarding analytics, privacy, discovery, and delivery, aiming to answer corresponding four research questions. How to provide user-oriented analytics in knowledge sharing systems to support awareness and reflection? What privacy management interfaces and mechanisms are suitable for knowledge analytics and learning analytics? How to enable discovery of knowledge relevant to user interests? How to facilitate knowledge delivery into settings where Internet connectivity is limited or absent? Henceforward, we provide an overview of our results. Analytics. To enable awareness and reflection for an SM platform users, we propose the embedded contextual analytics model where the analytics is embedded into the interaction context and presents information relevant to that particular context. Also, we propose two general architectures materializing this model respectfully based on real-time analytical applications and a scalable analytic back-end. Using these architectures, we provided analytics services to the SM platform users. We conducted an evaluation with the users demonstrating that embedded contextual analytics was useful to support their awareness and reflection. Privacy. To address the privacy concerns associated with the recording, storage, and analysis of user interaction traces, we propose a novel agent-based privacy management model. Our proposal uses a metaphor of physical presence of a tracking agent in an interaction context making the platform user aware of the tracking and allows to manage the tracking policy in a way similar to the physical world. We have implemented the proposed privacy interface in an SM platform and obtained positive evaluation results with the users. Discovery. Due to a large number of content items stored in SM platforms, it can be challenging for the users to find relevant knowledge. Addressing this challenge, we propose an interactive recommender system based on user interests enabling discovery of relevant content and people. We have implemented the proposed recommender in an SM platform and conducted two evaluations with platform users. The evaluations demonstrated the ability of the approach to identify relevant user interests and to recommend relevant content. Delivery. At the moment of writing in 2016, near half of the world's population still does not have reliable Internet access. Often, the places where humanitarian action is needed have limited Internet connection. We propose a novel knowledge delivery model that relies on a peer-to-peer middleware and uses low-cost computers for local knowledge replication. We have developed a system implementing the model and evaluated it during eight deployments in MSF missions. The evaluation demonstrated its knowledge delivery abilities and its usefulness for the field staff

Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Mobile collaborative working environment of product design

In response to the arrival of new Web/Internet environments, one of the most attractive challenges in current research is to exploit wireless computing technologies in collaborative product design, and hence to build a ubiquitous mobile information system to enable the collaborative product design within a mobile environment. However, the literature review reveals that although the progress of mobile technologies on wireless networks has largely changed the way people access the Internet; little has been achieved in mobile computing for collaborative product design. The reason is that, due to the distinct features of mobile devices and wireless networks (such as small display screen, limited bandwidth, unreliability of wireless networks, etc.), the methodologies and technologies used in stationary networks are not always applicable to mobile systems. The aim of this research is to establish a Wireless Internet-based Collaborative Working Environment for product design through the combination of multiple technologies, by including: Web services, Parametric Design, the Semantic Web, Agent and Flex Technologies. In order to create, deploy, and manage the distributed resources, Web service is used to implement design resource integration in a platform-independent manner. In addition, Semantic Web Technology is used to create a general knowledge base. This approach includes two components: (1) ontology is used to represent abstract views of product data and (2) added semantic rules are also used to represent relationships among product data. Therefore, an ontology-based description model is thus proposed to facilitate expression and organisation of product information in order to manage and deploy the distributed design resources