Semimetallic behavior in Heusler-type Ru2TaAl and thermoelectric performance improved by off-stoichiometry

We report a study of the temperature-dependent electrical resistivity, Seebeck coefficient, thermal conductivity, specific heat, and Al27 nuclear magnetic resonance (NMR) in Heusler-type Ru2TaAl, to shed light on its semimetallic behavior. While the temperature dependence of the electrical resistivity exhibits semiconductorlike behavior, the analysis of low-temperature specific heat reveals a residual Fermi-level density of states (DOS). Both observations can be realized by means of a semimetallic scenario with the Fermi energy located in the pseudogap of the electronic DOS. The NMR Knight shift and spin-lattice relaxation rate show activated behavior at higher temperatures, attributing to the thermally excited carriers across a pseudogap in Ru2TaAl. From the first-principles band structure calculations, we further provide a clear picture that an indirect overlap between electron and hole pockets is responsible for the formation of a pseudogap in the vicinity of the Fermi level of Ru2TaAl. In addition, an effort for improving the thermoelectric performance of Ru2TaAl has been made by investigating the thermoelectric properties of Ru1.95Ta1.05Al. We found significant enhancements in the electrical conductivity and Seebeck coefficient and marked reduction in the thermal conductivity via the off-stoichiomet ric approach. This leads to an increase in the figure-of-merit ZT value from 6.1×10-4 in Ru2TaAl to 3.4×10-3 in Ru1.95Ta1.05Al at room temperature. In this respect, a further improvement of thermoelectric performance based on Ru2TaAl through other off-stoichiometric attempts is highly probable

Interactive energy management for networked microgrids with risk aversion

Department of Finance and Education of Guangdong Province 2016[202]: Key Discipline Construction Programme, China; Guangdong Foshan Power Construction Corporation Group Co. Ltd., Foshan, China

Developing an EEG-based on-line closed-loop lapse detection and mitigation system

© 2014 Wang, Huang, Wei, Huang, Ko, Lin, Cheng and Jung. In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments

Hometronics – accessible production of graphene suspensions for health sensing applications using only household items

Nanoscience at times can seem out of reach to the developing world and the general public, with much of the equipment expensive and knowledge seemingly esoteric to nonexperts. Using only cheap, everyday household items, accessible research with real applications can be shown. Here, graphene suspensions were produced using pencil lead, tap water, kitchen appliances, soaps and coffee filters, with a children’s glue-based graphene nanocomposite for highly sensitive pulse measurements demonstrated

Dirac Equation with Spin Symmetry for the Modified P\"oschl-Teller Potential in DD-dimensions

We present solutions of the Dirac equation with spin symmetry for vector and scalar modified P\"oschl-Teller potential within framework of an approximation of the centrifugal term. The relativistic energy spectrum is obtained using the Nikiforov-Uvarov method and the two-component spinor wavefunctions are obtain are in terms of the Jacobi polynomials. It is found that there exist only positive-energy states for bound states under spin symmetry, and the energy levels increase with the dimension and the potential range parameter $\alpha$.Comment: 9 pages and 1tabl

Eosinophil and T Cell Markers Predict Functional Decline in COPD Patients

BACKGROUND. The major marker utilized to monitor COPD patients is forced expiratory volume in one second (FEV1). However, asingle measurement of FEV1 cannot reliably predict subsequent decline. Recent studies indicate that T lymphocytes and eosinophils are important determinants of disease stability in COPD. We therefore measured cytokine levels in the lung lavage fluid and plasma of COPD patients in order to determine if the levels of T cell or eosinophil related cytokines were predictive of the future course of the disease. METHODS. Baseline lung lavage and plasma samples were collected from COPD subjects with moderately severe airway obstruction and emphysematous changes on chest CT. The study participants were former smokers who had not had a disease exacerbation within the past six months or used steroids within the past two months. Those subjects who demonstrated stable disease over the following six months (ΔFEV1 % predicted = 4.7 ± 7.2; N = 34) were retrospectively compared with study participants who experienced a rapid decline in lung function (ΔFEV1 % predicted = -16.0 ± 6.0; N = 16) during the same time period and with normal controls (N = 11). Plasma and lung lavage cytokines were measured from clinical samples using the Luminex multiplex kit which enabled the simultaneous measurement of several T cell and eosinophil related cytokines. RESULTS AND DISCUSSION. Stable COPD participants had significantly higher plasma IL-2 levels compared to participants with rapidly progressive COPD (p = 0.04). In contrast, plasma eotaxin-1 levels were significantly lower in stable COPD subjects compared to normal controls (p < 0.03). In addition, lung lavage eotaxin-1 levels were significantly higher in rapidly progressive COPD participants compared to both normal controls (p < 0.02) and stable COPD participants (p < 0.05). CONCLUSION. These findings indicate that IL-2 and eotaxin-1 levels may be important markers of disease stability in advanced emphysema patients. Prospective studies will need to confirm whether measuring IL-2 or eotaxin-1 can identify patients at risk for rapid disease progression.National Heart, Lung, and Blood Institute (NO1-HR-96140, NO1-HR-96141-001, NO1-HR-96144, NO1-HR-96143; NO1-HR-96145; NO1-HR-96142, R01HL086936-03); The Flight Attendant Medical Research Institute; the Jo-Ann F. LeBuhn Center for Chest Diseas

Transfer learning with large-scale data in brain-computer interfaces

© 2016 IEEE. Human variability in electroencephalogram (EEG) poses significant challenges for developing practical real-world applications of brain-computer interfaces (BCIs). The intuitive solution of collecting sufficient user-specific training/calibration data can be very labor-intensive and time-consuming, hindering the practicability of BCIs. To address this problem, transfer learning (TL), which leverages existing data from other sessions or subjects, has recently been adopted by the BCI community to build a BCI for a new user with limited calibration data. However, current TL approaches still require training/calibration data from each of conditions, which might be difficult or expensive to obtain. This study proposed a novel TL framework that could nearly eliminate requirement of subject-specific calibration data by leveraging large-scale data from other subjects. The efficacy of this method was validated in a passive BCI that was designed to detect neurocognitive lapses during driving. With the help of large-scale data, the proposed TL approach outperformed the within-subject approach while considerably reducing the amount of calibration data required for each individual (∼1.5 min of data from each individual as opposed to a 90 min pilot session used in a standard within-subject approach). This demonstration might considerably facilitate the real-world applications of BCIs

Ultrafast Laser-Scanning Time-Stretch Imaging at Visible Wavelengths

published_or_final_versio