Palladium nanoclusters-coated polyfuran as a novel sensor for catecholamine neurotransmitters and paracetamol

A promising electrochemical biosensor was developed by electrodeposition of palladium nanoclusters on polyfuran film modified platinum electrode. This biosensor electrode was used to determine some catecholamines, namely dopamine, epinephrine and norepinephrine, ascorbic acid and paracetamol. The method of formation of the polymer film and deposition of Pd particles plays a key role in the electroactivity of the resulting hybrid material. This sensor effectively resolved the overlapping anodic peaks of ascorbic acid (AA), dopamine (DA) and paracetamol (ACOP) into three well-defined voltammetric peaks in differential pulse voltammetry analysis. The detection limit of DA in the absence and presence of AA and ACOP are eventually the same which indicates that the oxidation processes of DA, AA and ACOP are independent and that the simultaneous measurements of the three analytes are possible without interference. The electrodeposition of Pd on polyfuran improved exceptionally the detection limit about four decades. Moreover, diffusion coefficient measurements confirmed the fast electron transfer kinetics of the electrochemical oxidation of the analyte molecules at the sensor/solution interface. It is very interesting to note that the electrocatalytic effect of PF/Pd composite has been increased to be sometimes 21 times that of the pristine PF which has been considered for a long time to be of low conductivity and attracted low attention as a result of the difficulty of its formation and poor conductivity.     

Culture & biometrics: regional differences in the perception of biometric authentication technologies

Previous research has identified user concerns about biometric authentication technology, but most of this research has been conducted in European contexts. There is a lack of research that has investigated attitudes towards biometric technology in other cultures. To address this issue, data from India, South Africa and the United Kingdom were collected and compared. Cross-cultural attitudinal differences were seen, with Indian respondents viewing biometrics most positively while respondents from the United Kingdom were the least likely to have a positive opinion about biometrics. Multiple barriers to the acceptance of biometric technology were identified with data security and health and safety fears having the greatest overall impact on respondents’ attitudes towards biometrics. The results of this investigation are discussed with reference to Hofstede’s cultural dimensions and theories of technology acceptance. It is argued that contextual issues specific to each country provide a better explanation of the results than existing theories based on Hofstede’s model. We conclude that cultural differences have an impact on the way biometric systems will be used and argue that these factors should be taken into account during the design and implementation of biometric systems.     

Narrow Band FLIP for Liquid Simulations

The Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small‐scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid's visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation.     

Assessing tropical cyclone impacts using object-based moderate spatial resolution image analysis: a case study in Bangladesh

The environmental and societal impacts of tropical cyclones could be reduced using a range of management initiatives. Remote sensing can be a cost effective, accurate, and potential tool for mapping the multiple impacts caused by tropical cyclones using high-to-moderate spatial resolution (5–30 m) satellite imagery to provide data on the following essential parameters – evacuation, relief, and management of natural resources. This study developed and evaluated an approach for assessing the impacts of tropical cyclones through object-based image analysis and moderate spatial resolution imagery. Pre- and post-cyclone maps of artificial and natural features are required for assessing the overall impacts in the landscape that could be acquired by mapping specific land cover types. We used the object-based approach to map land-cover types in pre- and post-cyclone Satellite Pour l’Observation de la Terre (SPOT) 5 image data and the post-classification comparison technique to identify changes in the particular features in the landscape. Cyclone Sidr (2007) was used to test the applicability of this approach in Sarankhola Upazila in Bangladesh. The object-based approach provided accurate results for classifying features from pre- and post-cyclone satellite images with an overall accuracy of 95.43% and 93.27%, respectively. Mapped changes identified the extent, type, and form of cyclone induced impacts. Our results indicate that 63.15% of the study area was significantly affected by cyclone Sidr. The majority of mapped damage was found in vegetation, cropped lands, settlements, and infrastructure. The damage results were verified through the high spatial resolution satellite imagery, reports and pictures that were taken after the cyclone. The methods developed may be used in future to assess the multiple impacts caused by tropical cyclones in Bangladesh and other similar environments for the purposes of tropical cyclone disaster management.     

Recommendations to support interaction with broadcast debates: a study on older adults’ interaction with <Emphasis Type="Italic">The Moral Maze</Emphasis>

Current methods to capture, analyse and present the audience participation of broadcast events are increasingly carried out using social media. Uptake of such technology tools has so far been poor amongst older adults, and it has the worrying effect of excluding the demographic from participation. Our work explores whether a common desire to interact with debates can be tapped with technology with a very low barrier to entry, to both support better engagement with broadcast debates and encourage greater use of social media. This paper describes experiments where older adults interact with a BBC radio debate programme: The Moral Maze. As a result, we obtained common interaction patterns which then are used to define recommendations for software-supported interaction with debates based on theories of argumentation. Our goal is to combine research on computational models of argument and user-driven research on human-centred computing in a project with the potential for high-profile impact in addressing older adults inclusion in the digital economy.     

Board-Level Information Technology Governance Effects on Organizational Performance: The Roles of Strategic Alignment and Authoritarian Governance Style

ABSTRACT

We report on two empirical studies that explore key factors that help translate information technology governance by the board of directors into organizational performance. The first study shows that strategic alignment partially mediates the effect of board-level information technology governance on performance. The second study demonstrates that authoritarian governance style negatively moderates the effect of board-level information technology governance on performance. Together, these studies open up the black box between board-level information technology governance and organizational performance.     

A fuzzy reasoning and fuzzy-analytical hierarchy process based approach to the process of railway risk information: A railway risk management system

Risk management is becoming increasingly important for railway companies in order to safeguard their passengers and employees while improving safety and reducing maintenance costs. However, in many circumstances, the application of probabilistic risk analysis tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents the development of a risk management system for railway risk analysis using fuzzy reasoning approach and fuzzy analytical hierarchy decision making process. In the system, fuzzy reasoning approach (FRA) is employed to estimate the risk level of each hazardous event in terms of failure frequency, consequence severity and consequence probability. This allows imprecision or approximate information in the risk analysis process. Fuzzy analytical hierarchy process (fuzzy-AHP) technique is then incorporated into the risk model to use its advantage in determining the relative importance of the risk contributions so that the risk assessment can be progressed from hazardous event level to hazard group level and finally to railway system level. This risk assessment system can evaluate both qualitative and quantitative risk data and information associated with a railway system effectively and efficiently, which will provide railway risk analysts, managers and engineers with a method and tool to improve their safety management of railway systems and set safety standards. A case study on risk assessment of shunting at Hammersmith depot is used to illustrate the application of the proposed risk assessment system.     

A deadlock-free routing algorithm for dynamically reconfigurable Networks-on-Chip

We address routing in Networks-On-Chip (NoC) architectures that use irregular mesh topologies with Long-Range Links (LRL). These topologies create difficult conditions for routing algorithms, as standard algorithms assume a static, regular link structure and exploit the uniformity of regular meshes to avoid deadlock and maintain routability. We present a novel routing algorithm that can cope with these irregular topologies and adapt to run-time LRL insertion and topology reconfiguration. Our approach to accommodate dynamic topology reconfiguration is to use a new technique that decomposes routing relations into two stages: the calculation of output ports on the current minimal path and the application of routing restrictions designed to prevent deadlock. In addition, we present a selection function that uses local topology data to adaptively select optimal paths.The routing algorithm is shown to be deadlock-free, after which an analysis of all possible routing decisions in the region of an LRL is carried out. We show that the routing algorithm minimises the cost of sub-optimally placed LRL and display the hop savings available. When applied to LRLs of less than seven hops, the overall traffic hop count and associated routing energy cost is reduced. In a simulated 8 × 8 network the total input buffer usage across the network was reduced by 6.5%.     

Modeling the glucose regulatory system in extreme preterm infants

Background

Premature infants represent a significant proportion of the neonatal intensive care population. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition. Hypo- and hyperglycemia are frequently reported in very low birth weight infants, and more mature infants often experience low levels of glycemia. A model capturing the unique fundamental dynamics of the neonatal glucose regulatory system could be used to develop better blood glucose control methods.

Methods

A metabolic system model is adapted from adult critical care to the unique physiological case of the neonate. Integral-based fitting methods were used to identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles. The clinically important predictive ability of the model was assessed by assuming insulin sensitivity was constant over prediction intervals of 1, 2 and 4 h forward and comparing model-simulated versus actual clinical glucose values for all recorded interventions. The clinical data included 1091 glucose measurements over 3567 total patient hours, along with all associated insulin and nutritional infusion data, for N = 25 total cases. Ethics approval was obtained from the Upper South A Regional Ethics Committee for this study.

Results

The identified model had a median absolute percentage error of 2.4% [IQR: 0.9-4.8%] between model-fitted and clinical glucose values. Median absolute prediction errors at 1-, 2- and 4-h intervals were 5.2% [IQR: 2.5-10.3%], 9.4% [IQR: 4.5-18.4%] and 13.6% [IQR: 6.3-27.6%] respectively.

Conclusions

The model accurately captures and predicts the fundamental dynamic behaviors of the neonatal metabolism well enough for effective clinical decision support in glycemic control. The adaptation from adult to a neonatal case is based on the data from the literature. Low prediction errors and very low fitting errors indicate that the fundamental dynamics of glucose metabolism in both premature neonates and critical care adults can be described by similar mathematical models.