Highly conductive buried n+ layers in lnp:fe created by MeV energy Si,S, and Si/S implantation for application to microwave devices

To obtain highly conductive buried layers in InP:Fe, MeV energy Si, S, and Si/ Simplantations are performed at 200°C. The silicon and sulfer implants gave 85 and 100 percent activation, respectively, for a fluence of 8 × 10¹⁴ cm⁻². The Si/S co-implantation also gave almost 100 percent donor activation for a fluence of 8 × 10¹⁴ cm⁻² of each species. An improved silicon donor activation is observed in the Si/S co-implanted material compared to the material implanted with silicon alone. The peak carrier concentration achieved for the Si/S co-implant is 2 × 10¹⁹ cm³. The lattice damage on the surface side of the profile is effectively removed after rapid thermal annealing. Multiple-energy silicon and sulfur implantations are performed to obtain thick and buried n⁺ layers needed for microwave devices and also hyper-abrupt profiles needed for varactor diodes.     

Axial mixing in a 15 cm diameter reciprocating plate bubble column

Axial dispersion coefficients (E) in the liquid phase have been measured by unsteady tracer response methods in a 15 cm internal diameter reciprocating plate bubble column, using air and water in countercurrent and cocurrent flow. The operating variables studied were amplitude (0.6–1.27 cm) and frequency (0–5 Hz) of reciprocation, and the superficial velocities of the liquid and gas phases and the spacing between plates. Three types of plate were studied; conventional Karr-type plates with perforation diameters 1.43 cm, plates with smaller (0.635 cm) perforations, and single-perforation (doughnut) plates with internal diameter 7 cm. Measured values of E ranged from about 1 cm²/s to a maximum of 116 cm²/s. In general, the plates with 0.635 cm perforations gave the smallest values of E while the largest values of E were obtained with the doughnut plates, due to vortex ring shedding. The single liquid phase data for the three types of plate were approximately consistent with the correlation of Stevens and Baird (1990). The gas-liquid flow results were interpreted in terms of several different hydrodynamic effects.     

Impact of Zinc oxide nanoparticles on eggplant (S. melongena): studies on growth and the accumulation of nanoparticles

The increasing use of nanoparticles and their occurrence in the environment has made it imperative to elucidate their impact on the environment. Although several studies have advanced the authors’ understanding of nanoparticle–plant interactions, their knowledge of the exposure of plants to nanoparticles and their effects on edible crop plants remain meager and is often paradoxical. The aim of this study was to increase their knowledge on the effect of zinc oxide (ZnO) nanoparticles on eggplant seed germination and seedling growth. ZnO nanoparticles had a negative effect on the growth of eggplant in plant tissue‐culture conditions, as the growth of seedlings decreased with the increase in the concentration of ZnO nanoparticles. In contrast, ZnO nanoparticles enhanced eggplant growth under greenhouse conditions. The accumulation of ZnO nanoparticles in various parts of eggplant was observed through scanning electron microscopy of both plant tissue‐culture and greenhouse‐raised eggplant seedlings. To the best of their knowledge, this is the first study to report on ZnO nanoparticle accumulation in eggplant and its effect on seed germination and seedling growth.Inspec keywords: crops, zinc compounds, scanning electron microscopy, II‐VI semiconductors, nanoparticles, agriculture, cellular biophysics, nanofabricationOther keywords: plant tissue‐culture, greenhouse‐raised eggplant seedlings, ZnO nanoparticle accumulation, seedling growth, ZnO nanoparticles, nanoparticle–plant interactions, zinc oxide nanoparticles, eggplant seed germination, eggplant growth, ZnO     

Intensity tunable optical limiting behaviour of an organic material 2-aminopyridinium succinate succinic acid single crystal

Journal of Materials Science: Materials in Electronics - A mixed solution of 2-aminopyridine and succinic acid, with a 1:1 molar ratio, was kept at room temperature to develop a 2-aminopridinium...     

The importance of information localization in scene gist recognition.

People can recognize the meaning or gist of a scene from a single glance, and a few recent studies have begun to examine the sorts of information that contribute to scene gist recognition. The authors of the present study used visual masking coupled with image manipulations (randomizing phase while maintaining the Fourier amplitude spectrum; random image structure evolution [RISE]; J. Sadr & P. Sinha, 2004) to explore whether and when unlocalized Fourier amplitude information contributes to gist perception. In 4 experiments, the authors found that differences between scene categories in the Fourier amplitude spectrum are insufficient for gist recognition or gist masking. Whereas the global 1/f spatial frequency amplitude spectra of scenes plays a role in gist masking, local phase information is necessary for gist recognition and for the strongest gist masking. Moreover, the ability to recognize the gist of a target image was influenced by mask recognizability, suggesting that conceptual masking occurs even at the earliest stages of scene processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effect of Microstructure and Mechanical Properties of Al–Mg Alloy Processed by ECAP at Room Temperature and Cryo Temperature

This research primarily focuses on improving the strength of Al 5083 alloy by both the ECAP and Cryo ECAP methodology. Equal Channel Angular Pressing (ECAP) is one of the best technologies that enable the direct transformation of conventional macro grained metals into sub-micron, ultra-fine and nano grained materials. Fine grain size increases the strength and the fracture toughness of the material and provides the potential for super plastic deformation at moderate temperatures and at high strain rates. The microstructure evolution in Al 5083, subjected to Room Temperature ECAP and Cryo ECAP were analysed. ECAP was carried out using an optimized die with Channel angle ‘?’ = 90°and corner angle ‘Ψ’ = 20° through processing route A and C up to four passes. The results were thoroughly studied using TEM, SEM, and optical microscopic images. Initially the annealed sample had the grain size of 80 µm with the equi-axed grains. In Room Temperature, the hardness values and the mechanical strength were found to be increased from 88 to 410 HV and 306 to 453 MPa after four passes in route A and in route C the strength increased from 390 to 416 MPa after four ECAP passes. Moreover, in Cryo Condition, the sample was processed up to four ECAP passes at route A and route C. The hardness of 153 HV was obtained after four passes in route C and 164 HV obtained after four passes on route A. Additionally, fracture behaviour using SEM, grain size using TEM and crystallite size by X-ray diffraction studies were analyzed. It was observed that the Cryo ECAP showed marginal improvements in mechanical properties relative to the RT ECAP in case of Al 5083.     

FFCAEs: An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas

Intracranial tumors arise from constituents of the brain and its meninges. Glioblastoma (GBM) is the most common adult primary intracranial neoplasm and is categorized as high-grade astrocytoma according to the World Health Organization (WHO). The survival rate for 5 and 10 years after diagnosis is under 10%, contributing to its grave prognosis. Early detection of GBM enables early intervention, prognostication, and treatment monitoring. Computer-aided diagnostics (CAD) is a computerized process that helps to differentiate between GBM and low-grade gliomas (LGG), using the perceptible analysis of magnetic resonance (MR) of the brain. This study proposes a framework consisting of a feature fusion algorithm with cascaded autoencoders (CAEs), referred to as FFCAEs. Here we utilized two CAEs and extracted the relevant features from multiple CAEs. Inspired by the existing work on fusion algorithms, the obtained features are then fused by using a novel fusion algorithm. Finally, the resultant fused features are classified with the Softmax classifier to arrive at an average classification accuracy of 96.7%, which is 2.45% more than the previously best-performing model. The method is shown to be efficacious thus, it can be useful as a utility program for doctors.     

Size Segregation of Nickel Pellets Flowing into a Packed Bed

The size segregation of nickel pellets fed to a packed bed has been measured with mixtures of sizes ranging from less than 1 mm to about 10 mm. The pellet mixture is fed to one side of a rectangular cell and then samples are removed from different lateral positions in the cell for screen analysis. During the feeding process the finer pellets tend to percolate vertically downwards while the larger pellets tend to roll down the sloping surface of the bed. The resulting segregation has been correlated with the size distribution of the feed pellets and the lateral position in the cell, using polynomial equations with three or four adjustable coefficients.     

Structural,electrical and magnetic properties of cobalt ferrite with Nd3+ doping

A systematic study on the influence of Nd³⁺ substitution on structural,magnetic and electrical properties of cobalt ferrite nanopowders obtained by sol–gel auto-combustion routewas reported.The formation of spinel phasewas confirmed by X-ray diffraction(XRD)data,and percolation limit ofNd3?into the spinel lattice was also observed.Fourier transform infrared spectroscopy(FTIR)bands observed ≈580 and ≈390 cm^(-1 ) support the presence of Fe³⁺ at A andBsites in the spinel lattice.The variation in microstructure was investigated by scanning electronmicroscopy(SEM),and the average grain size varies from 5.3 to 3.3 lm.The substitution of Nd³⁺ significantly affects the formation of pores and grain size of cobalt ferrite.Room-temperature saturation magnetization and coercivity decrease from 60 to 30 mA·m²·g^-1 and 19.9–17.8 mT,respectively,with Nd³⁺ substitution increasing.These decreases in magnetic properties are explained based on the presence of non-magnetic nature of Nd³⁺ concentration and the dilution of super-exchange interaction in the spinel lattice.The room-temperature direct-current electrical resistivity increases with Nd³⁺ concentration increasing,which is due to the unavailability of Fe²⁺ at octahedral B sites.     

The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition

There is a growing interest on using ambient and wearable sensors for human activity recognition, fostered by several application domains and wider availability of sensing technologies. This has triggered increasing attention on the development of robust machine learning techniques that exploits multimodal sensor setups. However, unlike other applications, there are no established benchmarking problems for this field. As a matter of fact, methods are usually tested on custom datasets acquired in very specific experimental setups. Furthermore, data is seldom shared between different groups. Our goal is to address this issue by introducing a versatile human activity dataset recorded in a sensor-rich environment. This database was the basis of an open challenge on activity recognition. We report here the outcome of this challenge, as well as baseline performance using different classification techniques. We expect this benchmarking database will motivate other researchers to replicate and outperform the presented results, thus contributing to further advances in the state-of-the-art of activity recognition methods.