Comparative pollen and foliar micromorphological studies using light microscopy and scanning electron microscopy of some selected species of Lamiaceae from Alpine Zone of Deosai Plateau,Western Himalayas

The study was conducted to highlight a detailed account of morphology of pollen chosen species of Lamiaceae through scanning electron microscopy, and the anatomical characteristics of leaf epidermis of seven species using simple light microscopy. In results, Anisomeles indica and Otostegia aucheri belong to subfamily Lamioideae because it has tricolpate pollen while the rest eight species belong to subfamily Nepetoideae (hexacolpate pollen). The exine sculpturing of pollen of studied species was found to be reticulate. In the family Lamiaceae, four kinds of stomata were found anomocytic, anisocytic, diacytic, and actinocytic, respectively. The cell wall patterns of epidermal cells were irregular or polygonal with straight or undulate walls. It was noted that the variety of the epidermal trichomes seems of taxonomically important for the identification of species of Lamiaceae. Both nonglandular and glandular trichomes were analyzed. The nonglandular trichomes were characterized with long, thin, and pointed apical unicellular cells. The nonglandular trichomes were A‐shaped in Thymus linearis. In Perovskia abrotanoides, stellate glandular trichomes were observed whereas in A. indica and Mentha royleana both glandular and nonglandular trichomes were found. In A. indica, the nonglandular trichomes were sessile and peltate in M. royleana. For the first time in this study, pollen and foliar micromorphological features of selected species of this area are carried out. These taxonomic characters were found to be important in discrimination of species from each other. In future, the detailed study with comprehensive morphology coupled with other important characters is required for delimitation of taxa at various levels.     

A robust multimedia authentication and restoration scheme in digital photography

Image authentication and restoration is an important area of modern research. In digital photography, copyright protection is very crucial. Visible signatures distract from the meaning of the photograph as well as they are easy to be removed by using advanced softwares. Invisible watermarks provide protection, offer a better look to photographs than visible watermarking, and prevent the photographs from unauthorized manipulations. A robust multiple watermarking scheme is required which could invisibly protect the content and also should survive the manipulations for later verification and restoration. In this paper, a robust and imperceptible multimedia authentication and restoration scheme is proposed. The security of Advanced Encryption Standard (AES) is utilized to make an encrypted watermark. The encrypted watermark is then embedded into photographs in the salient regions by proposed Feature-Closest Point Transform (F-CPT) algorithm. The second watermark is generated by wavelet decomposition and embedded in the second and third level wavelet sub-bands of the cover photographs. Several security attacks are performed e.g. noise attack, compression attack, resizing attack, rotation attack, collage attack, and cropping attack on multiple watermarked photographs to examine the system robustness by normalized cross correlation (NCC) for retrieved authentication watermarks. Result of PSNR, MSE, and SSIM show the high imperceptibility of our technique and aesthetic score (AS) shows the aesthetic quality of watermarked photographs (WPs).     

Thermal Conductivity of Multiwalled Carbon Nanotubes-Kapok Seed Oil-Based Nanofluid

The synthesis of a nanofluid from multiwalled carbon nanotubes (MWCNTs) and Kapok seed oil by a one-step method is reported. The nanofluid showed excellent stability of nanoparticle dispersion in the base fluid. Furthermore, this study deals with the prediction of the thermal conductivity of the MWCNTs-kapok seed oil nanofluid. To improve the prediction of the thermal conductivity of the nanofluid, the artificial neural network (ANN) computing approach was used with different algorithms including the back-propagation, Levenberg-Marquardt, and genetic algorithm (GA). Finally, the ANN-GA model is recommended for the prediction of thermal conductivity with higher accuracy.     

Synthesis of cardo containing asymmetric poly(ether‐naphthalimide‐phthalimide)s

A series of cardo based asymmetric polyimides containing bulky rigid naphthalimide and phthalimide groups were prepared from asymmetric monomer bishaloimide and bisphenols by solution polycondensation. Bishalo(naphthalimide‐phthalimide) monomers containing different terminal leaving groups (Cl, F, NO₂) were synthesized, and the reactivity difference of these monomers was compared for the successful synthesis of polyimides. The inherent viscosities of the polyimides were in the range 0.51 ? 0.60 dL g^?1 in N ‐methyl‐2‐pyrrolidone at 30 °C. These polyimides demonstrated good organosolubility and mechanical properties with tensile strengths of 93 ? 120 MPa, tensile moduli of 3.5 ? 5.3 GPa and elongations at break of 2.8% ? 4.3%. The polyimides showed high glass transition temperatures (T _g) ranging from 330 to 363 °C. The 10% weight loss (T _10%) of asymmetric polyimides reached 436 ? 500 °C in nitrogen and 417 ? 476 °C in air. The water uptake of the polyimides was in the range 0.35% ? 0.72%. © 2017 Society of Chemical Industry     

Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

This study is designed to develop Artificial Intelligence (AI) based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays (CXRs). The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of CXRs. In this study, AI-based analysis tools were developed that can precisely classify COVID-19 lung infection. Publicly available datasets of COVID-19 (N = 1525), non-COVID-19 normal (N = 1525), viral pneumonia (N = 1342) and bacterial pneumonia (N = 2521) from the Italian Society of Medical and Interventional Radiology (SIRM), Radiopaedia, The Cancer Imaging Archive (TCIA) and Kaggle repositories were taken. A multi-approach utilizing deep learning ResNet101 with and without hyperparameters optimization was employed. Additionally, the features extracted from the average pooling layer of ResNet101 were used as input to machine learning (ML) algorithms, which twice trained the learning algorithms. The ResNet101 with optimized parameters yielded improved performance to default parameters. The extracted features from ResNet101 are fed to the k-nearest neighbor (KNN) and support vector machine (SVM) yielded the highest 3-class classification performance of 99.86% and 99.46%, respectively. The results indicate that the proposed approach can be better utilized for improving the accuracy and diagnostic efficiency of CXRs. The proposed deep learning model has the potential to improve further the efficiency of the healthcare systems for proper diagnosis and prognosis of COVID-19 lung infection.     

Green fabricated CuO nanobullets via Olea europaea leaf extract shows auspicious antimicrobial potential

In present investigation, copper oxide (CuO) nanostructures have been prepared via green chemistry. Olea europaea leaf extract act as strong chelating agent for tailoring physical as well as bio‐medical characteristics of CuO at the nano‐size. Physical characterisation such as scanning electron microscope analysis depicts the formation of homogenised spherical shape nanoparticles (NPs) with average size of 42 nm. X‐ray diffraction and Fourier transform infrared spectroscopy further confirmed the crystalline pure phase and monoclinic structure. High performance liquid chromatography (HPLC) testing is performed to evaluate the relative concentration of bioactive molecules in the O. europaea leaf extract. From HPLC results capping action of organic molecules around CuO‐NPs is hypothesised. The antimicrobial potency of biosynthesised CuO‐NPs have been evaluated using colony forming unit (CFU) counting assay and disc diffusion method which shows a significant zone of inhibition against bacterial and fungal strains may be highly potential for future antimicrobial pharmaceutics. Furthermore, reduction of various precursors by plant extract will reduce environmental impact over chemical synthesis.Inspec keywords: copper compounds, antibacterial activity, biochemistry, nanoparticles, nanomedicine, biomedical materials, chromatographyOther keywords: CuO, size 42 nm, chemical synthesis, antimicrobial pharmaceutics, bacterial strain, fungal strain, disc diffusion method, colony forming unit counting assay, biosynthesised CuO‐NP, bioactive molecules, high‐performance liquid chromatography testing, monoclinic structure, crystalline pure phase, Fourier transform infrared spectroscopy, X‐ray diffraction, homogenised spherical shape nanoparticles, scanning electron microscope analysis, CuO biomedical characteristics, chelating agent, green fabricated CuO nanobullets, green chemistry, copper oxide nanostructures, antimicrobial potential, Olea europaea leaf extract     

Power control for interference mitigation by evolutionary game theory in uplink NOMA for 5G networks

The demand for mobile uplink traffic has increased significantly in the past few decades with the development of the Internet of Things (IoT) and mobile Internet. This has subsequently imposed challenges on 5G networks to provide high spectral efficiency and low-power massive connectivity. Non-orthogonal multiple access (NOMA) is a viable alternative to the current state-of-the-art orthogonal multiple access (OMA) techniques to address the challenges in 5G systems. In addition, a power control (PC) mechanism to mitigate the effect of interference between users can be accommodated to improve network performance. In this paper, we discuss the basic principles, key features, and strengths/weaknesses of the various power domain NOMA schemes. Moreover, we propose an uplink PC scheme for the users of a power domain NOMA network. The proposed PC method makes use of the evolutionary game theory (EGT) model to adaptively adjust the transmitted power level of the users which helps in mitigating user interference. A successive interference cancellation (SIC) receiver is applied at a base station (BS) in order to separate the users’ signals. By performing simulations, we show that the proposed EGT-based PC scheme achieves higher network efficiency, spectral efficiency, and energy efficiency.     

Strain-Mediated Lattice Rotation Design for Enhancing Thermoelectric Performance in Bi2S2Se

A unique strain-mediated lattice rotation strategy is introduced via nanocompositing to upsurge the optimized limits in the composition-to-structural pathway on rationally engineering the efficient thermoelectric material. In this study, a special lattice rotation via strain engineering is realized to optimize the desired electronic and chemical environment for enhancing thermoelectric properties in n-type Bi₂S₂Se. This approach results in a unique transport phenomenon to assist high-energy electrons in transferring through the optimized transport channels, and appropriate structure disparity to significantly localize phonons. As a result, Sb over Cl doping in Bi₂S₂Se gently reduces E_g and introduces defect states in bandgap with shifting down the Fermi level, thus causing increase in carrier concentration, which contributes to a higher power factor of ≈7.18 µW cm⁻¹ K⁻² (at T = 773 K). Besides, a lower thermal conductivity of ≈0.49 W m⁻¹ K⁻¹ is driven through lattice strain and defect engineering. Consequently, an ultra-high ZT_max = 1.13 (at T = 773 K) and a high ZT_ave = 0.54 (323 K-773 K) are realized. This study not only leads to an extraordinary thermoelectric performance but also reveals a unique paradigm for electron transportation and phonon localization via lattice strain engineering.     

Transesterification of oil extracted from freshwater algae for biodiesel production

Currently, energy crisis is a burning issue throughout the world, particularly in underdeveloped countries like Pakistan where the demand of conventional fuels has been increasing day by day. The main objective of this project was the production of biodiesel from Algae. Samples of freshwater were collected. The Chlorella species produced 6.26 g oil from 38.23 g of dry weight and the Oedogonium species produced 8.07 g of oil from 38.23 g of dried weight. The biomass obtained after oil extraction was 31.97 g from chlorella species and 30.16 g from Oedogonium species. The fatty acids that were displayed by a gas chromatographic machine in chlorella species were capric acid, nanoic acid, arachidonic acid, behenic acid, and erucic acid and in oedogonium species they were capric acid, butyric acid, behenic acid, luric acid, tridecanoic acid, and arachidonic acid.     

Mine Wastewater Treatment with Upflow Anaerobic Fixed Film Reactors

Mine Water and the Environment - Microbial bioremediation of metals in wastewater by sulfate-reducing bacteria (SRB) has received much attention due to its high efficiency, eco-friendly techniques,...