A 1.6 Gbyte/s data transfer rate 8 Mb embedded DRAM

An 8 Mb embedded DRAM has been developed. The salient feature of this embedded DRAM is page fault tolerance. Accessing across different pages can be performed using a minimum column cycle. This feature is achieved by placing a data latch and a transfer gate between the bit line sense amplifier and the column select gate. This DRAM can be reconfigured as separated 2 Mb units when it is embedded as a macro cell of an ASIC library     

Is the tyramine test for depressive illness useful in elderly patients?

There were no significant differences in tyramine sulphate excretion following tyramine ingestion between elderly depressed, demented or control patient groups, in contrast with younger subjects where this test is a trait marker for unipolar endogenous depression. There are inherent problems in urine collection studies in the elderly and the results may have been influenced by the medication that elderly patients have to take for other disorders. This study suggests that the tyramine test is unlikely to be of clinical usefulness in the over 65 age group.     

Reliable tracking of facial features in semantic-based video coding

A new method of tracking the position of important facial features for semantic-based moving image coding is presented. Reliable and fast tracking of the facial features in head-and-shoulders scenes is of paramount importance for reconstruction of the speakers motion in videophone systems. The proposed method is based on eigenvalue decomposition of the sub-images extracted from subsequent frames of the video sequence. The motion of each facial feature (the left eye, the right eye, the nose and the lips) is tracked separately; this means that the algorithm can be easily adapted for a parallel machine. No restrictions, other than the presence of the speaker's face, were imposed on the actual contents of the scene. The algorithm was tested on numerous widely used head-and-shoulders video sequences containing moderate head pan, rotation and zoom, with remarkably good results. Tracking was maintained even when the facial features were occluded. The algorithm can also be used in other semantic-based systems     

Bifunctional Perovskite-BiVO4 Tandem Devices for Uninterrupted Solar and Electrocatalytic Water Splitting Cycles

Photoelectrochemical (PEC) fuel synthesis depends on the intermittent solar intensity of the diurnal cycle and ceases at night. Here, an integrated device that does not only possess PEC water splitting functionality, but also operates as an electrolyzer in the nocturnal period to improve the overall capacity factor is described. The bifunctional system is based on an “artificial leaf” tandem PEC architecture that contains an inverse-structure lead halide perovskite protected by a graphite epoxy/parylene-C coating (conferring 96 h stability of operation in water), and a porous BiVO₄ semiconductor. The light-absorbers are interfaced with a H₂ evolution catalyst (Pt) and a Co-based water oxidation catalyst, respectively, which can also be directly driven by electricity. Thus, the device can operate in PEC mode during irradiation and switch to an electricity-powered mode in the dark through bypassing of the semiconductor configuration. The bifunctional perovskite-BiVO₄ tandem provides a solar-to-hydrogen efficiency of 1.3% under simulated solar irradiation and an onset for water electrolysis at 1.8 V. The compact design and low cost of the proposed device may provide an advantage over other technologies for round-the-clock fuel production.     

Focused Ultrasound Enabled Trans‐Blood Brain Barrier Delivery of Gold Nanoclusters: Effect of Surface Charges and Quantification Using Positron Emission Tomography

Focused ultrasound (FUS) technology is reported to enhance the delivery of ⁶⁴Cu‐integrated ultrasmall gold nanoclusters (⁶⁴Cu‐AuNCs) across the blood‐brain barrier (BBB) as measured by positron emission tomography (PET). To better define the optimal physical properties for brain delivery, ⁶⁴Cu‐AuNCs with different surface charges are synthesized and characterized. In vivo biodistribution studies are performed to compare the individual organ uptake of each type of ⁶⁴Cu‐AuNCs. Quantitative PET imaging post‐FUS treatment shows site‐targeted brain penetration, retention, and diffusion of the negative, neutral, and positive ⁶⁴Cu‐AuNCs. Autoradiography is performed to compare the intrabrain distribution of these nanoclusters. PET Imaging demonstrates the effective BBB opening and successful delivery of ⁶⁴Cu‐AuNCs into the brain. Of the three ⁶⁴Cu‐AuNCs investigated, the neutrally charged nanostructure performs the best and is the candidate platform for future theranostic applications in neuro‐oncology.     

Estimating Energy Conversion Efficiency of Thermoelectric Materials: Constant Property Versus Average Property Models

Maximum thermoelectric energy conversion efficiencies are calculated using the conventional “constant property” model and the recently proposed “cumulative/average property” model (Kim et al. in Proc Natl Acad Sci USA 112:8205, 2015) for 18 high-performance thermoelectric materials. We find that the constant property model generally predicts higher energy conversion efficiency for nearly all materials and temperature differences studied. Although significant deviations are observed in some cases, on average the constant property model predicts an efficiency that is a factor of 1.16 larger than that predicted by the average property model, with even lower deviations for temperature differences typical of energy harvesting applications. Based on our analysis, we conclude that the conventional dimensionless figure of merit ZT obtained from the constant property model, while not applicable for some materials with strongly temperature-dependent thermoelectric properties, remains a simple yet useful metric for initial evaluation and/or comparison of thermoelectric materials, provided the ZT at the average temperature of projected operation, not the peak ZT, is used.     

Traffic collision avoidance system: false injection viability

The Journal of Supercomputing - Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects...     

Dynamic Syntax

Dynamic Syntax (DS: Kempson et al. 2001; Cann et al. 2005) is an action-based grammar formalism which models the process of natural language understanding as monotonic tree growth. This paper presents an introduction to the notions of incrementality and underspecification and update, drawing on the assumptions made by DS. It lays out the tools of the theoretical framework that are necessary to understand the accounts developed in the other contributions to the Special Issue. It also represents an up-to-date account of the framework, combining the developments that have previously remained distributed in a diverse body of literature.

     

Feature selection using swarm-based relative reduct technique for fetal heart rate

Fetal heart rate helps in diagnosing the well-being and also the distress of fetal. Cardiotocograph (CTG) monitors the fetal heart activity to estimate the fetal tachogram based on the evaluation of ultrasound pulses reflected from the fetal heart. It consists in a simultaneous recording and analysis of fetal heart rate signal, uterine contraction activity and fetal movements. Generally CTG comprises more number of features. Feature selection also called as attribute selection is a process of selecting a subset of highly relevant features which is responsible for future analysis. In general, medical datasets require more number of features to predict an activity. This paper aims at identifying the relevant and ignores the redundant features, consequently reducing the number of features to assess the fetal heart rate. The features are selected by using unsupervised particle swarm optimization (PSO)-based relative reduct (US-PSO-RR) and compared with unsupervised relative reduct and principal component analysis. The proposed method is then tested by applying various classification algorithms such as single decision tree, multilayer perceptron neural network, probabilistic neural network and random forest for maximum number of classes and clustering accuracies like root mean square error, mean absolute error, Davies–Bouldin index and Xie–Beni index for minimum number of classes. Empirical results show that the US-PSO-RR feature selection technique outperforms the existing methods by producing sensitivity of 72.72 %, specificity of 97.66 %, F-measure of 74.19 % which is remarkable, and clustering results demonstrate error rate produced by US-PSO-RR is less as well.