Fabrication of ZnO-functionalized polypyrrole microcomposite as a protective coating to enhance anticorrosion performance of low carbon mild steel

In the present work, PPy, ZnO, and polypyrrole/zinc oxide (PPy/ZnO) microcomposites (1, 2, and 5 wt%) were prepared and their properties have been tuned for anticorrosion applications on low carbon mild steel. The synthesized products: ZnO, PPy, and composites were characterized by various sophisticated analytical techniques such as XRD, FTIR, Raman, FESEM, EDX, UV–VIS, TGA, and BET. The band frequencies observed at 480 and 588 cm⁻¹ in FTIR spectrum correspond to stretching vibrations of Zn-O and N-H bonds, respectively, broadening of the bands in the composites indicate strong interactions between ZnO and PPy matrix. The potentiodynamic polarization study of PPy and PPy/ZnO composite was carried out in 3.5% NaCl solution to investigate the corrosion resistance efficiency. PPy/1 wt% ZnO (I_corr = 190 nA) composite coating on low carbon mild steel was observed to exhibit best corrosion protection property compared to PPy (121 μA), 2 and 5 wt% ZnO (242, 295 nA) composites. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48319.     

Mathematical modelling of solar radiation incident on tilted surface for photovoltaic application at Bhopal,M.P., India

In general, solar radiations are the combination of beam plus diffuse and ground-reflected radiation. The availability of recorded data on a tilted surface is very rare due to lack of measuring equipment and techniques involved. In this study, a standard procedure is adopted for estimation of solar radiation on a tilted surface for a location in Central region of India. Solar radiation is estimated for three tilted positions: First, solar collector tilt equal to latitude angle, second, solar collector tilt equal to latitude angle +15° and third, solar collector tilt at latitude ?15°. Total global solar radiation estimated on the inclined surface for various photovoltaic (PV) modules was used to obtain the annual energy yield based on the estimated value. It was found that on an average, 14?kWh/m² of annual energy output can be obtained for monocrystalline solar PV module corresponding to the inclination of 23.26° latitude at Bhopal.     

Chromophore-Free Sealing and Repair of Soft Tissues Using Mid-Infrared Light-Activated Biosealants

Poor strength, infection, leakage, long procedure times, and inflammation limit the efficacy of common tissue sealing devices in surgeries and trauma. Light-activated sealing is attractive for tissue sealing and repair, and can be facilitated by the generation of local heat following absorption of nonionizing laser energy by chromophores. Here, the inherent ability of biomaterials is exploited to absorb nonionizing, mid-infrared (midIR) light in order to engender rapid photothermal sealing and repair of soft tissue wounds. In this approach, the biomaterial simultaneously acts as a photothermal convertor as well as a biosealant, which dispenses the need for exogeneous light-absorbing nanoparticles or dyes. Biomechanical recovery, mathematical modeling, histopathology analyses, tissue strain mapping using digital imaging correlation, and visualization of the biosealant-tissue interface using hyperspectral imaging indicate superior performance of midIR sealing in live mice compared to conventional sutures and glue. The midIR-biosealant approach demonstrates rapid sealing of soft tissues, improves cosmesis, lowers potential for scarring, obviates safety concerns because of the nonionizing light used, and allows adoption of a wide diversity of biomaterials. Taken together, the studies demonstrate a novel advance both in biomaterials for surgical sealing along with the use of nonionizing midIR light, with high potential for clinical translation.     

Novel Collision Detection and Avoidance System for Midvehicle Using Offset-Based Curvilinear Motion

In recent days, the manufacture of automotive vehicles is dramatically enhanced worldwide. Most vehicle crashes are due to the drive distraction on the real highway roads and traffic-density. In this proposed method, a novel collision detection and avoidance algorithm are coined for Midvehicle Collision Detection and Avoidance System (MCDAS), addressing two scenarios, namely, (a) A rear-end collision avoidance with host vehicle under no front-end vehicle condition and (b) offset-based curvilinear motion under critical conditions, while, suitable parallel parking manoeuvring also addressed using offset-based curvilinear motion. The Monte Carlo analysis of the proposed MCDAS is demonstrated using the Constant Velocity (CV) manoeuvring strategy and simulated with real-time data using the NGSIM database.

     

Design and evaluation of mucoadhesive microemulsion for neuroprotective effect of ibuprofen following intranasal route in the MPTP mice model

Background: The present study is to investigate the neuroprotective effect of ibuprofen by intranasal administration of mucoadhesive microemulsion (MMEI) against inflammation-mediated by dopaminergic neurodegeneration in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of Parkinson’s disease (PD).

Methods: Ibuprofen-loaded polycarbophil-based MMEI was developed by using response surface methodology (RSM). Ibuprofen with dose of 2.86 mg/kg/day was administered intranasally to male C57BL/6 mice for two consecutive weeks which were pre-treated with four intraperitoneal injections of MPTP (20?mg/kg of body weight) at 2?h intervals. Immunohistochemistry was performed.

Results: Optimal MMEI was stable and non-ciliotoxic with 66.29?±?4.15?nm as average globule size and??20.9?±?3.98?mV as zeta potential. PDI value and transmission electron microscopy result showed the narrow globule size distribution of MMEI. The result showed that all three independent variables had a significant effect (p?<?0.05) on the responses. Rota-rod and open-field test findings revealed the significant improvement in motor performance and gross behavioral activity of the mice. The results from in vivo study and immunohistochemistry showed that nasal administration of Ibuprofen significantly reduced the MPTP-mediated dopamine depletion. Furthermore TH neurons count in the substantia nigra and the density of striatal dopaminergic nerve terminals were found to be significant higher for ibuprofen treated groups.

Conclusion: Findings of the investigation revealed that Ibuprofen through developed MMEI was shown to protect neurons against MPTP-induced injury in the Substantia nigra pars compacta (SNpc) and striatum and hence, could be a promising approach for brain targeting of Ibuprofen through intranasal route to treat PD.     

Mechanisms of Hyperhomocysteinemia Induced Skeletal Muscle Myopathy after Ischemia in the CBS?/+ Mouse Model

Although hyperhomocysteinemia (HHcy) elicits lower than normal body weights and skeletal muscle weakness, the mechanisms remain unclear. Despite the fact that HHcy-mediated enhancement in ROS and consequent damage to regulators of different cellular processes is relatively well established in other organs, the nature of such events is unknown in skeletal muscles. Previously, we reported that HHcy attenuation of PGC-1α and HIF-1α levels enhanced the likelihood of muscle atrophy and declined function after ischemia. In the current study, we examined muscle levels of homocysteine (Hcy) metabolizing enzymes, anti-oxidant capacity and focused on protein modifications that might compromise PGC-1α function during ischemic angiogenesis. Although skeletal muscles express the key enzyme (MTHFR) that participates in re-methylation of Hcy into methionine, lack of trans-sulfuration enzymes (CBS and CSE) make skeletal muscles more susceptible to the HHcy-induced myopathy. Our study indicates that elevated Hcy levels in the CBS^−/+ mouse skeletal muscles caused diminished anti-oxidant capacity and contributed to enhanced total protein as well as PGC-1α specific nitrotyrosylation after ischemia. Furthermore, in the presence of NO donor SNP, either homocysteine (Hcy) or its cyclized version, Hcy thiolactone, not only increased PGC-1α specific protein nitrotyrosylation but also reduced its association with PPARγ in C2C12 cells. Altogether these results suggest that HHcy exerts its myopathic effects via reduction of the PGC-1/PPARγ axis after ischemia.     

Dictionary-based classifiers for exploiting feature sequence information and their application to hyperspectral remotely sensed data

The problem of classification is shared across various disciplines. Designing even less computationally demanding and more effective classifiers has been a key challenge for researchers for many years. No single classifier can be highly effective for all types of datasets and thus, depending on the data distribution, various classifiers have been proposed in the literature. To our knowledge, feature values have been vastly exploited as the base for discriminating classes, while feature sequence information has been somehow under-exploited so far. In the proposed approach normalised features are sorted and ranked, creating a sequence of finite numbers. The associated rank of the created sequence is used as an additional feature, which in a way defines the sample-specific intra-feature relationship. Three novel dictionary-based approaches such as Sequence Classifier (SC), Sequence-dictionary-based k-Nearest Neighbours Classifier (SDk-NN) and Combined-dictionary-based k-Nearest Neighbours Classifier (CDk-NN) are proposed in this paper.

In the case of remotely sensed data, and specifically in Hyper-Spectral Images (HSI), the spectral features (Spectral signatures) represent a strong, object-specific spectral relationship, which is a key point in our proposed approach. In this case, indeed, the proposed classifiers were tested over various (five) HS datasets and found to be effective. Based on the classifiers features, two derived distance measures are proposed and validated for the HS dataset, namely: the Normalised Sequence Distance (NSD) measure and Combined Distance (CD) measure. These measures appear to overperform the conventional Normalised Euclidean Distance (NED) in this context. Also, validation for both binary and multi-class datasets are experimented and their performances are evaluated in terms of accuracy and other standard measures. Experimental results over 21 datasets revealed that the proposed approaches perform comparably, and in some cases even better than other classifiers. Stack-operated, class-specific sparse dictionaries are also introduced in order to reduce the computational complexity, which can be used as an active learning-based approach for optimal training sample selection. Additional tests were performed with variable levels of dictionary sparsity for assessing its impact on accuracy.