Surface Treatment of Inorganic CsPbI3 Nanocrystals with Guanidinium Iodide for Efficient Perovskite Light-Emitting Diodes with High Brightness

The remarkable evolution of metal halide perovskites in the past dec-ade makes them promise for next-generation optoelectronic material.In particular,nanocrysta...     

Effect of rubber hardness on the properties of fiber reinforced plastic composites made by the newly proposed rubber pressure molding technique

The effect of rubber hardness on the properties of fiber‐reinforced plastic (FRP) composites is investigated in order to know the optimum composition of rubber mold used in rubber pressure molding (RPM) technique. A matching die set was used in RPM method, where the die was made of hard metal like steel and the punch from the flexible rubber like material, natural rubber. The use of flexible rubber punch generates and applies hydrostatic pressure on the surface of FRP composites. The hardness of rubber mold was controlled by incorporating carbon black as a filler material in the matrix of natural rubber and varied from 0 to 75 phr (per hundred rubber) in steps of 15 phr. Burn test, tension test, interlaminar shear test and interlaminar fracture toughness tests were conducted on the FRP composites to measure the void content, presence of delamination, tensile strength, inter laminar shear strength and inter laminar fracture toughness. The results are compared with the FRP composites made by conventional technique to evaluate the performance of RPM technique. It is observed that the laminates produced by RPM technique with different filler content in natural rubber mold show significant improvement in mechanical properties except interlaminar shear strength. POLYM. COMPOS., 28:618–630, 2007. © 2007 Society of Plastics Engineers     

LIBS based spectroscopic analysis and antidiabetic evaluation of a polyherbal formulation

Although plants have long been a major source of medicine, there is renewed interest in studying the phytochemistry and use of herbal formulations. This paper reports spectroscopic analysis using Laser Induced Breakdown Spectroscopy (LIBS) of a polyherbal formulation, whose antidiabetic activity has also been demonstrated on rat models. LIBS analysis revealed the presence of elements such as Na, K, Mg, Ca, H, O and N. The antidiabetic study showed that amongst the four doses studied (50, 100, 150 and 200 mg/kg bw), the dose of 150 mg/kg bw registered the maximum fall in Blood Glucose Level (BGL) in both normal and diabetic (sub and mild) rats in the Glucose Tolerance Test (GTT) study—normal rats (22 %), sub-diabetic (36.6 %) and mild-diabetic (39 %). The dose of 150 mg/kg also showed the maximum fall of 23.7 % and 22 % in BGL during fasting BGL and GTT studies of normal rats, respectively. The formulation also showed significant antioxidant activity assessed using in vitro assays. The study validates for the first time the therapeutic use of an antidiabetic polyherbal formulation.     

On Security and Reliability Using Cooperative Transmissions in Sensor Networks

Cooperative transmissions have received recent attention and research papers have demonstrated their benefits for wireless networks. Such benefits include improving the reliability of links through diversity and/or increasing the reach of a link compared to a single transmitter transmitting to a single receiver (single-input single-output or SISO). In one form of cooperative transmissions, multiple nodes can act as virtual antenna elements and provide diversity gain or range improvement using space-time coding. In a multi-hop ad hoc or sensor network, a source node can make use of its neighbors as relays with itself to reach an intermediate node with greater reliability or at a larger distance than otherwise possible. The intermediate node will use its neighbors in a similar manner and this process continues till the destination is reached. Thus, for the same reliability of a link as SISO, the number of hops between a source and destination may be reduced using cooperative transmissions as each hop spans a larger distance. However, the presence of malicious or compromised nodes in the network impacts the benefits obtained with cooperative transmissions. Using more relays can increase the reach of a link, but if one or more relays are malicious, the transmission may fail. However, the relationships between the number of relays, the number of hops, and success probabilities are not trivial to determine. In this paper, we analyze this problem to understand the conditions under which cooperative transmissions fare better or worse than SISO transmissions. We take into consideration additional parameters such as the path-loss exponent and provide a framework that allows us to evaluate the conditions when cooperative transmissions are better than SISO transmissions. This analysis provides insights that can be employed before resorting to simulations or experimentation.     

Consumer Attention to an Over‐the‐counter Warning in Four Different Styles of Design

The study consisted of three objectives: (a) to test the relative prominence and conspicuousness of a warning required by US law to be conspicuous; (b) to explore whether or not the conspicuousness of the said warning can be enhanced graphically; and (c) to develop preliminary data for power analysis that would guide decisions related to sample size in future studies. Seventeen subjects viewed four over‐the‐counter drug packages (each with a different style of warning) along with five other products while wearing an eye tracking device. Four styles of warning were used on the over‐the‐counter drug packages: no outline and no fill, outline and no fill, no outline and fill, and outline and fill. The surface area and the placement of the warnings were held constant across all four designs and were consistent with those on commercially available products. Collected data were broken into five zones: warning, brand name, strength, product benefit and net weight. Despite the fact that US law requires it to be conspicuous, the tested warning was significantly less noticeable than the brand name (objective one) for all dependent variables analyzed (α = 0.05). No significant difference was indicated for the varied warning designs (objective two). This could be because not much can be done to enhance prominence when constrained to the limited space that is typically used for such warnings or because of the limited sample size. Power calculations suggest that a sample size of nearly 200 subjects would be required to detect a 2.5 s mean difference at 80% confidence (objective three). Copyright © 2011 John Wiley & Sons, Ltd.     

Control of a robotic orthosis for gait rehabilitation

Robot assisted gait training may help in producing rapid improvements in functional gait parameters. This paper presents new experimental results with an intrinsically compliant robotic gait training orthosis. The newly developed robotic orthosis has 6 degrees of freedom (DOFs). A trajectory tracking controller based on the boundary layer augmented sliding control (BASMC) law was implemented to guide the subject’s limbs on physiological gait trajectories. The compliance of the robotic orthosis sagittal plane hip and knee joints was also controlled, independently of the trajectory tracking control. The robotic orthosis and the control scheme were evaluated on three neurologically intact subjects walking on a treadmill. A maximum trajectory tracking error of 10° was recorded at the hip and knee sagittal plane joints. The results showed that subjects can walk in the robotic orthosis with comfort and the BASMC law was able to guide the subject’s limbs on reference physiological trajectories.     

Determination of the fracture toughness of fabric reinforced composites by the J-integral approach

The fracture behaviour of a glass-fabric-reinforced epoxy composite has been investigated experimentally. Load-displacement curves for single-edge-notched specimens were obtained on an MTS system and the J-integral evaluated through its energy rate interpretation. J_c, the critical value of the J-integral, obtained directly for a₀/w > 0·4 and that obtained through an extrapolation procedure for a₀/w < 0·4 compare quite well. J_c appears to be independent of crack length for specimen widths between 15 and 45 mm. J_c for ±45° specimens is less than half that for 0/90 specimens.     

Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application

Many hydrologic phenomena and applications such as drought, flood, irrigation management and scheduling needs high resolution satellite soil moisture data at a local/regional scale. Downscaling is a very important process to convert a coarse domain satellite data to a finer spatial resolution. Three artificial intelligence techniques along with the generalized linear model (GLM) are used to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) derived soil moisture, which is currently available at a very coarse scale of ~40 Km. Artificial neural network (ANN), support vector machine, relevance vector machine and generalized linear models are chosen for this study to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) with the SMOS derived soil moisture. Soil moisture deficit (SMD) derived from a hydrological model called PDM (Probability Distribution Model) is used for the downscaling performance evaluation. The statistical evaluation has also been made with the day-time and night-time MODIS LST differences with the mean day and night-time PDM SMD data for the selection of effective MODIS products. The accuracy and robustness of all the downscaling algorithms are discussed in terms of their assumptions and applicability. The statistical performance indices such as R ² , %Bias and RMSE indicates that the ANN (R ² ? =?0.751, %Bias?=??0.628 and RMSE?=?0.011), RVM (R ² ? =?0.691, %Bias?=?1.009 and RMSE?=?0.013), SVM (R ² ? =?0.698, %Bias?=?2.370 and RMSE?=?0.013) and GLM (R ² ? =?0.698, %Bias?=?1.009 and RMSE?=?0.013) algorithms on the whole are relatively more skillful to downscale the variability of the soil moisture in comparison to the non-downscaled data (R ² ? =?0.418 and RMSE?=?0.017) with the outperformance of ANN algorithm. The other attempts related to growing and non-growing seasons have been used in this study to reveal that season based downscaling is even better than continuous time series with fairly high performance statistics.