Electric-field induced fluctuations in laser generated plasma plume

The effect of an external electric field on laser-generated plasma has been studied. It is observed that the laser-generated plasma can be used for the ignition of a spark in the presence of a low voltage external electric field. An eight-fold emission intensity enhancement in Cu Ⅰ spectral lines are measured as compared to the signal intensity in the absence of an external electric field.The plasma parameters remain the same initially, up to a few microseconds after the generation of plasma, and this feature makes it more interesting for the quantitative analysis of any sample using laser induced breakdown spectroscopy(LIBS). In the presence of an external electric field,fluctuations(contraction and expansion) in the laser-generated plasma are observed which increase the plasma decay time and consequently result in enhanced signal intensity.     

Highly Functional TNTs with Superb Photocatalytic,Optical, and Electronic Performance Achieving Record PV Efficiency of 10.1% for 1D‐Based DSSCs

Different nanostructures of TiO₂ play an important role in the photocatalytic and photoelectronic applications. TiO₂ nanotubes (TNTs) have received increasing attention for these applications due to their unique physicochemical properties. Focusing on highly functional TNTs (HF‐TNTs) for photocatalytic and photoelectronic applications, this study describes the facile hydrothermal synthesis of HF‐TNTs by using commercial and cheaper materials for cost‐effective manufacturing. To prove the functionality and applicability, these TNTs are used as scattering structure in dye‐sensitized solar cells (DSSCs). Photocatalytic, optical, Brunauer‐Emmett‐Teller (BET), electrochemical impedance spectrum, incident‐photon‐to‐current efficiency, and intensity‐modulated photocurrent spectroscopy/intensity‐modulated photovoltage spectroscopy characterizations are proving the functionality of HF‐TNTs for DSSCs. HF‐TNTs show 50% higher photocatalytic degradation rate and also 68% higher dye loading ability than conventional TNTs (C‐TNTs). The DSSCs having HF‐TNT and its composite‐based multifunctional overlayer show effective light absorption, outstanding light scattering, lower interfacial resistance, longer electron lifetime, rapid electron transfer, and improved diffusion length, and consequently, J _SC, quantum efficiency, and record photoconversion efficiency of 10.1% using commercial N‐719 dye is achieved, for 1D‐based DSSCs. These new and highly functional TNTs will be a concrete fundamental background toward the development of more functional applications in fuel cells, dye‐sensitized solar cells, Li‐ion batteries, photocatalysis process, ion‐exchange/adsorption process, and photoelectrochemical devices.     

Adsorption of dyes from aqueous solutions on activated charcoal

Adsorption of industrially important dyes namely bromophenol blue, alizarine red-S, methyl blue, methylene blue, eriochrome black-T, malachite green, phenol red and methyl violet from aqueous media on activated charcoal has been investigated. The effect of shaking time, pH and temperature on the adsorption behaviour of these dyes has been studied. It was noted that adsorption of all the dyes on activated charcoal decreases with an increase in the pH and the temperature. The adsorption isotherms at different temperatures were found to be of L-type. Adsorption data was fitted to Freundlich, BET and Langmuir isotherms and various adsorption parameters have been calculated. The thermodynamic parameters such as DeltaG, DeltaH and DeltaS were calculated from the slopes and intercepts of the linear variation of lnK against 1/T, where K is the adsorption coefficient obtained from Langmuir equation, was used. The calculated values for the heat of adsorption and the free energy indicate that adsorption of dyes is favored at low temperatures and the dyes are chemisorbed on activated charcoal.     

Exponentially Weighted Moving Average Chart and Two‐Component Measurement Error

The two‐component measurement error (TCME) model effectively quantifies both the additive and multiplicative errors in analytical measurements. The performance of control charts in presence of TCME model has been investigated by researchers in recent past, but these studies are based on only considering fixed levels for the two‐component model parameters. In this study, we investigated the exponentially weighted moving average chart's performance in presence of TCME for varying levels of two‐component model parameters. A cost function analysis is also presented to determine the optimal number of multiple measurements and the sample size for reducing the effect of TCME. Copyright © 2015 John Wiley & Sons, Ltd.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

A Single Injection of NTG-101 Reduces the Expression of Pain-Related Neurotrophins in a Canine Model of Degenerative Disc Disease

Background: Tissue sources of pain emanating from degenerative discs remains incompletely understood. Canine intervertebral discs (IVDs) were needle puncture injured, 4-weeks later injected with either phosphate-buffered saline (PBS) or NTG-101, harvested after an additional fourteen weeks and then histologically evaluated for the expression of NGFr, BDNF, TrkB and CALCRL proteins. Quantification was performed using the HALO automated cell-counting scoring platform. Immunohistochemical analysis was also performed on human IVD tissue samples obtained from spinal surgery. Immunohistochemical analysis and quantification of neurotrophins and neuropeptides was performed using an in vivo canine model of degenerative disc disease and human degenerative disc tissue sections. Discs injected with NTG-101 showed significantly lower levels of Nerve Growth Factor receptor (NGFr/TrkA, p = 0.0001), BDNF (p = 0.009), TrkB (p = 0.002) and CALCRL (p = 0.008) relative to PBS injections. Human IVD tissue obtained from spinal surgery due to painful DDD show robust expression of NGFr, BDNF, TrkB and CALCRL proteins. A single intradiscal injection of NTG-101 significantly inhibits the expression of NGFr, BDNF, TrkB and CALCRL proteins in degenerative canine IVDs. These results strongly suggest that NTG-101 inhibits the development of neurotrophins that are strongly associated with painful degenerative disc disease and may have profound effects upon the management of patients living with discogenic pain.     

High-feed turning of AISI D2 tool steel using multi-radii tool inserts: Tool life,material removed,and workpiece surface integrity evaluation

Multi-radii tool inserts offer novel configuration that comprises of multiple radii at tool nose. A review of the available literature indicates that there exists a need for experimental investigation on certain key machining characteristics of such tools. This paper reports on tool wear/life, material removed, and workpiece surface roughness when multi-radii mixed alumina TiN coated tool inserts are employed for turning D2 steel. Inserts of three different nose radii (0.40, 0.80, 1.20?mm) at six levels of feed rates (ranging from 0.157 to 0.562?mm/rev) are used. Results show that flank wear is the dominant wear mode with catastrophic tool failure occurring at highest nose radius (1.20?mm) and feed rate (0.562?mm/rev) combination. Also, there is ～59% reduction in tool life accompanied by ～62% increase in quantity of material removed as the feed rate increases from 0.157 to 0.562?mm/rev at maximum nose radius (1.20?mm). Feed rate is found to be statistically significant factor for all three responses considered herein at 95% confidence level. Surface integrity assessment at maximum feed rate reveals presence of a strain hardened layer extending to the depth of 150?µm below the machined surface without any observance of white layer for all the tool conditions and nose radius.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.