Prototype edge-grown nanowire sensor array for the real-time monitoring and classification of multiple gases

The monitoring and classification of different gases using a single resistive semiconductor sensor are challenging because of the similar response characteristics. An array of separated sensors can be used as an electronic nose, but such arrays have a bulky structure and complex fabrication processes. Herein, we easily fabricated a gas-sensor array based on edge-grown SnO2 nanowires for the real-time monitoring and classification of multiple gases. The array comprised four sensors and was designed on a glass substrate. SnO2 nanowires were grown on-chip from the edge of electrodes, made contact together, and acted as sensing elements. This method was advantageous over the post-synthesis technique because the SnO2 nanowires were directly grown from the edge of the electrodes rather than on the surface. Accordingly, damage to the electrode was avoided by alloying Sn with Pt at a high growth temperature. The sensing characteristics of the sensor array were further examined for different gases, including methanol, isopropanol, ethanol, ammonia, hydrogen sulphide and hydrogen. Radar plots were used to improve the selective detection of different gases and enable effective classification

Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)

© 2017 The Author(s). The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox's regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844-0.898) in the development cohort and 0.783 (95% CI, 0.743-0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests

Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks

© 2018 IEEE. We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mobile users while meeting their delay requirements. To find the optimal task offloading decisions for mobile users, we first formulate the joint task offloading and resource allocation optimization problem as a mixed integer non-linear programming (MINLP). The optimization involves both binary (offloading decisions) and real variables (resource allocations), making it an NP-hard and computational intractable problem. To circumvent, we relax the binary decision variables to transform the MINLP to a relaxed optimization problem with real variables. After proving that the relaxed problem is a convex one, we propose two solutions namely ROP and IBBA. ROP is adopted from the interior point method and IBBA is developed from the branch and bound algorithm. Through the numerical results, we show that our proposed approaches allow minimizing the total energy consumption and meet all delay requirements for mobile users

Phosphate Adsorption by Silver Nanoparticles-Loaded Activated Carbon derived from Tea Residue.

This study presents the removal of phosphate from aqueous solution using a new silver nanoparticles-loaded tea activated carbon (AgNPs-TAC) material. In order to reduce costs, the tea activated carbon was produced from tea residue. Batch adsorption experiments were conducted to evaluate the effects of impregnation ratio of AgNPs and TAC, pH solution, contact time, initial phosphate concentration and dose of AgNPs-AC on removing phosphate from aqueous solution. Results show that the best conditions for phosphate adsorption occurred at the impregnation ratio AgNPs/TAC of 3% w/w, pH 3, and contact time lasting 150 min. The maximum adsorption capacity of phosphate on AgNPs-TAC determined by the Langmuir model was 13.62 mg/g at an initial phosphate concentration of 30 mg/L. The adsorption isotherm of phosphate on AgNPs-TAC fits well with both the Langmuir and Sips models. The adsorption kinetics data were also described well by the pseudo-first-order and pseudo-second-order models with high correlation coefficients of 0.978 and 0.966, respectively. The adsorption process was controlled by chemisorption through complexes and ligand exchange mechanisms. This study suggests that AgNPs-TAC is a promising, low cost adsorbent for phosphate removal from aqueous solution

Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter

© 2018 IEEE. For an RF-powered cognitive radio network with ambient backscattering capability, while the primary channel is busy, the RF-powered secondary user (RSU) can either backscatter the primary signal to transmit its own data or harvest energy from the primary signal (and store in its battery). The harvested energy then can be used to transmit data when the primary channel becomes idle. To maximize the throughput for the secondary system, it is critical for the RSU to decide when to backscatter and when to harvest energy. This optimal decision has to account for the dynamics of the primary channel, energy storage capability, and data to be sent. To tackle that problem, we propose a Markov decision process (MDP)-based framework to optimize RSU's decisions based on its current states, e.g., energy, data as well as the primary channel state. As the state information may not be readily available at the RSU, we then design a low-complexity online reinforcement learning algorithm that guides the RSU to find the optimal solution without requiring prior-and complete-information from the environment. The extensive simulation results then clearly show that the proposed solution achieves higher throughputs, i.e., up to 50%, than that of conventional methods

Arrhythmia Detection Using Convolutional Neural Models

Our main goal was studying the effectiveness of transfer learning using 2D CNNs. For this task, we generated spectrograms from ECG segments that were fed to a CNN to automatically extract features. These features are classified by a MLP into arrhythmic or normal rhythm segments, achieving 90% accuracy.Nuestra meta principal consistió en estudiar la efectividad de la transferencia de aprendizaje en el uso de CNNs 2D. Para ello, generamos espectrogramas, a partir de segmentos de electrocardiogramas, que sirvieron como entrada de una CNN para extraer automáticamente sus características. Estas características son clasificadas por un MLP para discernir entre segmentos arrítmicos o normales, obteniendo una precisión del 90%

Defining the optimal dose of rifapentine for pulmonary tuberculosis: Exposure-response relations from two phase II clinical trials.

Rifapentine is a highly active antituberculosis antibiotic with treatment-shortening potential; however, exposure-response relations and the dose needed for maximal bactericidal activity have not been established. We used pharmacokinetic/pharmacodynamic data from 657 adults with pulmonary tuberculosis participating in treatment trials to compare rifapentine (n = 405) with rifampin (n = 252) as part of intensive-phase therapy. Population pharmacokinetic/pharmacodynamic analyses were performed with nonlinear mixed-effects modeling. Time to stable culture conversion of sputum to negative was determined in cultures obtained over 4 months of therapy. Rifapentine exposures were lower in participants who were coinfected with human immunodeficiency virus, black, male, or fasting when taking drug. Rifapentine exposure, large lung cavity size, and geographic region were independently associated with time to culture conversion in liquid media. Maximal treatment efficacy is likely achieved with rifapentine at 1,200 mg daily. Patients with large lung cavities appear less responsive to treatment, even at high rifapentine doses

Edge Waves and Transmissions for Temporal Laminates and Imperfect Chiral Interfaces

The analysis of wave patterns in a structure which possesses periodicity in the spatial and temporal dimensions is presented. The topic of imperfect chiral interfaces is also considered. Although causality is fundamental for physical processes, natural wave phenomena can be observed when a wave is split at a temporal interface. A wave split at a spatial interface is a more common occurrence; however when the coefficients of the governing equations are time-dependent, the temporal interface becomes important. Here, the associated edge waves are studied, and regimes are analysed where the growth of the solution in time is found. Imperfect interfaces, across which the displacements are discontinuous, are also considered in the vector case of chiral elastic systems. Analytical study and asymptotic approximations are supplied with illustrative numerical examples

The effect of participatory community communication on HIV preventive behaviors among ethnic minority youth in central Vietnam

<p>Abstract</p> <p>Background</p> <p>In Vietnam, socially marginalized groups such as ethnic minorities in mountainous areas are often difficult to engage in HIV research and prevention programs. This intervention study aimed to estimate the effect of participatory community communication (PCC) on changing HIV preventive ideation and behavior among ethnic minority youth in a rural district from central Vietnam.</p> <p>Methods</p> <p>In a cross-sectional survey after the PCC intervention, using a structured questionnaire, 800 ethnic minority youth were approached for face-to-face interviews. Propensity score matching (PSM) technique was then utilized to match these participants into two groups-intervention and control-for estimating the effect of the PCC.</p> <p>Results</p> <p>HIV preventive knowledge and ideation tended to increase as the level of recall changed accordingly. The campaign had a significant indirect effect on condom use through its effect on ideation or perceptions. When intervention and control group statistically equivalently reached in terms of individual and social characteristics by PSM, proportions of displaying HIV preventive knowledge, ideation and condom use were significantly higher in intervention group than in matched control counterparts, accounting for net differences of 7.4%, 12.7% and 5%, respectively, and can be translated into the number of 210; 361 and 142 ethnic minority youth in the population.</p> <p>Conclusions</p> <p>The study informs public health implications both theoretically and practically to guide effective HIV control programs for marginalized communities in resources-constrained settings like rural Vietnam and similar contexts of developing countries.</p