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.     

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.     

Superior electrocatalytic activity of mesoporous Au film templated from diblock copolymer micelles

Mesoporous Au films consisting of a network of interconnected Au ligaments around ultra-large pores were found to exhibit a promising electrocatalytic activity towards sluggish reactions. Mesoporous Au films with pore sizes up to 25 nm were successfully fabricated using a polymeric micelle approach. A superior catalytic activity of the mesoporous Au films towards methanol oxidation was confirmed, which was thoroughly analyzed and compared with that of other Au materials. An intrinsic investigation on the high catalytic activity revealed that the superior performance of the as-prepared mesoporous Au film was related to its unique atomic structures around the mesopores with well-crystallized facets and several step/kink sites on the Au surfaces. These findings showcase a strategic and feasible design for preparing highly active Au-based catalysts that could be used as promising candidates in electrocatalytic applications.

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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.     

Green Synthesis of Silymarin–Chitosan Nanoparticles as a New Nano Formulation with Enhanced Anti-Fibrotic Effects against Liver Fibrosis

Background: Silymarin (SIL) has long been utilized to treat a variety of liver illnesses, but due to its poor water solubility and low membrane permeability, it has a low oral bioavailability, limiting its therapeutic potential. Aim: Design and evaluate hepatic-targeted delivery of safe biocompatible formulated SIL-loaded chitosan nanoparticles (SCNPs) to enhance SIL’s anti-fibrotic effectiveness in rats with CCl₄-induced liver fibrosis. Methods: The SCNPs and chitosan nanoparticles (CNPs) were prepared by ionotropic gelation technique and are characterized by physicochemical parameters such as particle size, morphology, zeta potential, and in vitro release studies. The therapeutic efficacy of successfully formulated SCNPs and CNPs were subjected to in vivo evaluation studies. Rats were daily administered SIL, SCNPs, and CNPs orally for 30 days. Results: The in vivo study revealed that the synthesized SCNPs demonstrated a significant antifibrotic therapeutic action against CCl₄-induced hepatic injury in rats when compared to treated groups of SIL and CNPs. SCNP-treated rats had a healthy body weight, with normal values for liver weight and liver index, as well as significant improvements in liver functions, inflammatory indicators, antioxidant pathway activation, and lipid peroxidation reduction. The antifibrotic activities of SCNPs were mediated by suppressing the expression of the main fibrosis mediators TGFβR1, COL3A1, and TGFβR2 by boosting the hepatic expression of protective miRNAs; miR-22, miR-29c, and miR-219a, respectively. The anti-fibrotic effects of SCNPs were supported by histopathology and immunohistochemistry (IHC) study. Conclusions: According to the above results, SCNPs might be the best suitable carrier to target liver cells in the treatment of liver fibrosis.     

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.     

Mammogram Enhancement Using Lifting Dyadic Wavelet Transform and Normalized Tsallis Entropy

In this paper, we present a new technique for mammogram enhancement using fast dyadic wavelet transform （FDyWT） based on lifted spline dyadic wavelets and normalized Tsallis entropy. First, a mammogram image is decom- posed into a multiscale hierarchy of low-subband and high-subband images using FDyWT. Then noise is suppressed using normalized Tsallis entropy of the local variance of the modulus of oriented high-subband images. After that, the wavelet coefficients of high-subbands are modified using a non-linear operator and finally the low-subband image at the first scale is modified with power law transformation to suppress background. Though FDyWT is shift-invariant and has better poten- tial for detecting singularities like edges, its performance depends on the choice of dyadic wavclcts. On the other hand, the nulnber of vanishing moments is an important characteristic of dyadic wavelets for singularity analysis because it provides an upper bound measurement for singularity characterization. Using lifting dyadic schemes, we construct lifted spline dyadic wavelets of different degrees with increased number of vanishing moments. We also examine the effect of these wavelets on mammogram enhancement. The method is tested on mammogram images, taken from MIAS （Mammographic Image Analysis Society） database, having various background tissue types and containing different abnormalities. The comparison with tile state-of-the-art contrast enhancement methods reveals that the proposed method performs better and the difference is statistically significant.