A web-based telemedicine system for low-resource settings 13 years on: insights from referrers and specialists

Background: One way to tackle health inequalities in resource-poor settings is to establish links between doctors and health professionals there and specialists elsewhere using web-based telemedicine. One such system run by the Swinfen Charitable Trust has been in existence for 13 years which is an unusually long time for such systems. Objective: We wanted to gain some insights into whether and how this system might be improved. Methods: We carried out a survey by questionnaire of referrers and specialists over a six months period. Results: During the study period, a total of 111 cases were referred from 35 different practitioners, of whom 24% were not doctors. Survey replies were received concerning 67 cases, a response rate of 61 per cent. Eighty-seven per cent of the responding referrers found the telemedicine advice useful, and 78% were able to follow the advice provided. As a result of the advice received, the diagnosis was changed in 22% of all cases and confirmed in a further 18 per cent. Patient management was changed in 33 per cent. There was no substantial difference between doctors and non-doctors. During the study period, the 111 cases were responded to by 148 specialists, from whom 108 replies to the questionnaire were received, a response rate of 73 per cent. About half of the specialists (47%) felt that their advice had improved the management of the patients. There were 62 cases where it was possible to match up the opinions of the referrer and the consultants about the value of a specific teleconsultation. In 34 cases (55%) the referrers and specialists agreed about the value. However, in 28 cases (45%) they did not: specialists markedly underestimated the value of a consultation compared to referrers. Both referrers and specialist were extremely positive about the system which appears to be working well. Minor changes such as a clearer referral template and an improved web interface for specialists may improve it

Designing libraries of chimeric proteins using SCHEMA recombination and RASPP

SCHEMA is a method for designing libraries of novel proteins by recombination of homologous sequences. The goal is to maximize the number of folded proteins while simultaneously generating significant sequence diversity. Here, we use the RASPP algorithm to identify optimal SCHEMA designs for shuffling contiguous elements of sequence. To exemplify the method, SCHEMA is used to recombine five fungal cellobiohydrolases (CBH1s) to produce a library of more than 390,000 novel CBH1 sequences

A Geographic Information System Framework for the Management of Sensor Deployments

A prototype Geographic Information System (GIS) framework has been developed to map, manage, and monitor sensors with respect to other geographic features, including land base and in-plant features. The GIS framework supports geographic placement and subsequent discovery, query, and tasking of sensors in a network-centric environment using Web services. The framework couples the GIS feature placement logic of sensors with an extensible ontology which captures the capabilities, properties, protocols, integrity constraints, and other parameters of interest for a large variety of sensor types. The approach is significant in that custom, GIS-based interfaces can be rapidly developed via the integration of sensors and sensor networks into applications without having detailed knowledge of the sensors’ underlying device drivers by leveraging service-oriented computing infrastructure within the GIS framework

A family of thermostable fungal cellulases created by structure-guided recombination

SCHEMA structure-guided recombination of 3 fungal class II cellobiohydrolases (CBH II cellulases) has yielded a collection of highly thermostable CBH II chimeras. Twenty-three of 48 genes sampled from the 6,561 possible chimeric sequences were secreted by the Saccharomyces cerevisiae heterologous host in catalytically active form. Five of these chimeras have half-lives of thermal inactivation at 63°C that are greater than the most stable parent, CBH II enzyme from the thermophilic fungus Humicola insolens, which suggests that this chimera collection contains hundreds of highly stable cellulases. Twenty-five new sequences were designed based on mathematical modeling of the thermostabilities for the first set of chimeras. Ten of these sequences were expressed in active form; all 10 retained more activity than H. insolens CBH II after incubation at 63°C. The total of 15 validated thermostable CBH II enzymes have high sequence diversity, differing from their closest natural homologs at up to 63 amino acid positions. Selected purified thermostable chimeras hydrolyzed phosphoric acid swollen cellulose at temperatures 7 to 15°C higher than the parent enzymes. These chimeras also hydrolyzed as much or more cellulose than the parent CBH II enzymes in long-time cellulose hydrolysis assays and had pH/activity profiles as broad, or broader than, the parent enzymes. Generating this group of diverse, thermostable fungal CBH II chimeras is the first step in building an inventory of stable cellulases from which optimized enzyme mixtures for biomass conversion can be formulated

RF Energy Harvester-based Wake-up Receiver

Wake-up receivers (WuRxs) can improve the life- time of a wireless sensor network by reducing energy consump- tion from undesirable idle listening. The amplitude level of the incoming RF signal is used by a WuRx to generate an interrupt and wake up the radio of a sleeping sensor node. Existing passive WuRx designs are generally based on RFID tags that incur high cost and complexity. Thus, there is a need for cost-effective and low-complexity WuRxs suited for both long-range and directed wake-ups. In this work, we present a WuRx design using an RF energy harvesting circuit (RFHC). Experimental results show that our RFHC-based WuRx can provide a wake-up range sensitivity around 4 cm/mW at low transmit RF powers ( < 20 mW), which scales to a long wake-up range at high powers. Our design also obtains accurate selective wake-ups. We finally present simulation-based studies for optimizing the design of RFHCs that enhance decoding efficiency with improved rise and fall times

Historical Building Monitoring Using an Energy-Efficient Scalable Wireless Sensor Network Architecture

We present a set of novel low power wireless sensor nodes designed for monitoring wooden masterpieces and historical buildings, in order to perform an early detection of pests. Although our previous star-based system configuration has been in operation for more than 13 years, it does not scale well for sensorization of large buildings or when deploying hundreds of nodes. In this paper we demonstrate the feasibility of a cluster-based dynamic-tree hierarchical Wireless Sensor Network (WSN) architecture where realistic assumptions of radio frequency data transmission are applied to cluster construction, and a mix of heterogeneous nodes are used to minimize economic cost of the whole system and maximize power saving of the leaf nodes. Simulation results show that the specialization of a fraction of the nodes by providing better antennas and some energy harvesting techniques can dramatically extend the life of the entire WSN and reduce the cost of the whole system. A demonstration of the proposed architecture with a new routing protocol and applied to termite pest detection has been implemented on a set of new nodes and should last for about 10 years, but it provides better scalability, reliability and deployment properties

A bayesian multilevel modeling approach for data query in wireless sensor networks

In power-limited Wireless Sensor Network (WSN), it is important to reduce the communication load in order to achieve energy savings. This paper applies a novel statistic method to estimate the parameters based on the realtime data measured by local sensors. Instead of transmitting large real-time data, we proposed to transmit the small amount of dynamic parameters by exploiting both temporal and spatial correlation within and between sensor clusters. The temporal correlation is built on the level-1 Bayesian model at each sensor to predict local readings. Each local sensor transmits their local parameters learned from historical measurement data to their cluster heads which account for the spatial correlation and summarize the regional parameters based on level-2 Bayesian model. Finally, the cluster heads transmit the regional parameters to the sink node. By utilizing this statistical method, the sink node can predict the sensor measurements within a specified period without directly communicating with local sensors. We show that this approach can dramatically reduce the amount of communication load in data query applications and achieve significant energy savings

A review on hierarchical routing protocols for wireless sensor networks

The routing protocol for Wireless Sensor Networks (WSNs) is defined as the manner of data dissemination from the network field (source) to the base station (destination). Based on the network topology, there are two types of routing protocols in WSNs, they are namely flat routing protocols and hierarchical routing protocols. Hierarchical routing protocols (HRPs) are more energy efficient and scalable compared to flat routing protocols. This paper discusses how topology management and network application influence the performance of cluster-based and chain-based hierarchical networks. It reviews the basic features of sensor connectivity issues such as power control in topology set-up, sleep/idle pairing and data transmission control that are used in five common HRPs, and it also examines their impact on the protocol performance. A good picture of their respective performances give an indication how network applications, i.e whether reactive or proactive, and topology management i.e. whether centralized or distributed would determine the network performance. Finally, from the ensuring discussion, it is shown that the chain-based HRPs guarantee a longer network lifetime compared to cluster-based HRPs by three to five times

O-SPIN: an Opportunistic Data Dissemination Protocol for Folk-enabled Information System in Least Developed Countries

International audienceWithout universal access to the Internet, Least Developed Countries are left by the wayside of the digital revolution. Research is underway to overstep the barrier to the development of information technology services in these areas. In this context, the Folk-IS (Folk-enabled Information System) is a new fully decentralized and participatory approach, in which, each individual can transparently perform data management and networking tasks through highly secure, portable, and low-cost storage and computing personal devices, as physically moving, so that global services can finally be delivered by crowd. In this paper we propose Opportunistic SPIN (O-SPIN), an information dissemination protocol that augments the well-known data-centric energy-aware SPIN protocol to enable networking facilities for Folk-nodes, by exploiting opportunistic contacts among users. Performance of the proposed solution has been evaluated through simulations carried out in the OMNeT++ framework under different settings. Achieved results demonstrate its effectiveness and efficiency in the information dissemination process