Properties of LiMnBO3 glasses and nanostructured glass-ceramics

Polycrystalline LiMnBO3 is a promising cathode material for Li-ion batteries. In this work, we investigated the thermal, structural and electrical properties of glassy and nanocrystallized materials having the same chemical composition. The original glass was obtained via a standard meltquenching method. SEM and 7Li solid-state NMR indicate that it contains a mixture of two distinct glassy phases. The results suggest that the electrical conductivity of the glass is dominated by the ionic one. The dc conductivity of initial glass was estimated to be in the order of 10-18 S.cm-1 at room temperature. The thermal nanocrystallization of the glass produces a nanostructured glass-ceramics containing MnBO3 and LiMnBO3 phases. The electric conductivity of this glass-ceramics is increased by 6 orders of magnitude, compared to the starting material at room temperature. Compared to other manganese and borate containing glasses reported in the literature, the conductivity of the nanostructured glass ceramics is higher than that of the previously reported glassy materials. Such improved conductivity stems from the facilitated electronic transport along the grain boundaries

Longitudinal assessment of community psychobehavioral responses during and after the 2003 outbreak of severe acute respiratory syndrome in Hong Kong

Background. In previous literature, the stability and temporal evolution of psychobehavioral responses to an outbreak remained undefined, because of the exclusively cross-sectional nature of such study designs. Methods. Using random-digit dialing, we sampled 4481 Hong Kong residents in 6 population-based surveys that were conducted at different times during and after the 2003 outbreak of severe acute respiratory syndrome (SARS). Results. Respondents' State-Trait Anxiety Inventory score (range, 10-40) showed a decreasing temporal trend, from a high mean value of 24.8 during the peak of the Amoy Gardens outbreak to a postepidemic mean baseline value of 14.5. Those who perceived a higher likelihood of contracting or dying of SARS had significantly higher anxiety scores. Female respondents, individuals aged 30-49 years, and individuals with only a primary education or less were predisposed to greater anxiety. There was a positive dose-response gradient between anxiety level and uptake of personal protective measures. Males respondents, individuals at the extremes of age, and individuals with lower educational levels were less likely to engage in self-protective behavior. The presence of symptoms was the only consistent predictor for greater use of health services. There was remarkable stability in the magnitude and the direction of associations between predictors and outcomes over time. Conclusions. Our findings can assist in modifying public service announcements in the future, which should be tailored to psychobehavioral surveillance intelligence to achieve the desired behavioral outcomes. Future research should explore the use of more-sophisticated techniques, including structural equation modeling and game-theoretical frameworks, to analyze population psychology and behavior, and it should integrate such findings with transmission dynamics modeling. © 2005 by the Infectious Diseases Society of America. All rights reserved.published_or_final_versio

Energy Efficient Mobile Routing in Actuator and Sensor Networks with Connectivity Preservation

International audienceIn mobile wireless sensor networks, flows sent from data col- lecting sensors to a sink could traverse inefficient resource expensive paths. Such paths may have several negative effects such as devices bat- tery depletion that may cause the network to be disconnected and packets to experience arbitrary delays. This is particularly problematic in event- based sensor networks (deployed in disaster recovery missions) where flows are of great importance. In this paper, we use node mobility to im- prove energy consumption of computed paths. Mobility is a two-sword edge, however. Moving a node may render the network disconnected and useless. We propose CoMNet (Connectivity preservation Mobile routing protocol for actuator and sensor NETworks), a localized mechanism that modifies the network topology to support resource efficient transmissions. To the best of our knowledge, CoMNet is the first georouting algorithm which considers controlled mobility to improve routing energy consump- tion while ensuring network connectivity. CoMNet is based on (i) a cost to progress metric which optimizes both sending and moving costs, (ii) the use of a connected dominating set to maintain network connectivity. CoMNet is general enough to be applied to various networks (actuator, sensor). Our simulations show that CoMNet guarantees network connec- tivity and is effective in achieving high delivery rates and substantial energy savings compared to traditional approaches

How to improve CSMA-based MAC protocol for dense RFID reader-to-reader Networks?

International audienceDue to the dedicated short range communication feature of passive radio frequency identification (RFID) and the closest proximity operation of both tags and readers in a large-scale dynamic RFID system, when nearby readers simultaneously try to communicate with tags located within their interrogation range, serious interference problems may occur. Such interferences may cause signal collisions that lead to the reading throughput barrier and degrade the system performance. Although many efforts have been done to maximize the throughput by proposing protocols such as NFRA or more recently GDRA, which is compliant with the EPCglobal and ETSI EN 302 208 standards. However, the above protocols are based on unrealistic assumptions or require additional components with more control packet and perform worse in terms of collisions and latency, etc. In this paper, we explore the use of some well-known Carrier Sense Multiple Access (CSMA) backoff algorithms to improve the existing CSMA-based reader-to-reader anti-collision protocol in dense RFID networks. Moreover, the proposals are compliant with the existing standards. We conduct extensive simulations and compare their performance with the well-known state-of-the-art protocols to show their performance under various criteria. We find that the proposals improvement are highly suitable for maximizing the throughput, efficiency and for minimizing both the collisions and coverage latency in dense RFID Systems

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases

ACE gene insertion/deletion polymorphism has a mild influence on the acute development of left ventricular dysfunction in patients with ST elevation myocardial infarction treated with primary PCI

<p>Abstract</p> <p>Background</p> <p>We evaluated the associations among angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism, ACE activity and post-myocardial infarction (MI) left ventricular dysfunction and acute heart failure (AHF) early after presentation with MI with ST-segment elevation (STEMI).</p> <p>Methods</p> <p>A total of 556 patients with STEMI treated by primary PCI (421 patients without AHF and 135 patients with AHF) were the study population. The activity of BNP, NT-ProBNP and ACE were measured at hospital admission and 24 h after MI onset. Left ventricular angiography was done before PCI; echocardiography was undertaken between the third and fifth day after MI.</p> <p>Results</p> <p>In comparison with the II genotypes group, the DD/ID group had a higher level of ACE activity upon hospital admission (p < 0.001). We found a significantly higher level of ACE activity in patients with moderate LV dysfunction (EF 40-54%) in comparison both with patients with preserved LV function (EF ≥55%) and with patients with severe LV dysfunction (p = 0.028). A non-significant trend towards a higher incidence of mild AHF (22.1% vs. 16.02%, p = 0,093), a significantly higher value of end-systolic volume (ESV/BSA) (30.0 ± 12.3 vs. 28.5 ± 13.0; p < 0.05) and lower EF (50.2 ± 11.1 vs. 52.7 ± 11.7; p < 0.05) in the DD/ID genotypes group was noted. Even after multiple adjustments according to multivariate models, the EF for the DD/ID group remained significantly lower (p = 0,033). The DD/ID genotypes were associated with a significantly higher risk of EF <45% (OR 2.04 [95% CI 1.28; 3.25]).</p> <p>Conclusions</p> <p>These results suggest that the I/D polymorphism of ACE is associated with the development of LV dysfunction in the acute phase after STEMI. We demonstrated for the first time an association of the low ACE activity with the severe LV dysfunction, although patients with moderate LV dysfunction had higher level ACE activity than patients with preserved LV function.</p