Imperative role of electron microscopy in toxicity assessment: A review

Electron microscope (EM) was developed in 1931 and since then microscopical examination of both the biological and non-biological samples has been revolutionized. Modifications in electron microscopy techniques, such as scanning EM and transmission EM, have widened their applicability in the various sectors such as understanding of drug toxicity, development of mechanism, criminal site investigation, and characterization of the nano-molecule. The present review summarizes its role in important aspects such as toxicity assessment and disease diagnosis in special reference to SARS-COV2. In the biological system, EM studies have elucidated the impact of toxicants at the ultra-structural level in various tissue in conformity to physiological alterations. Thus, EM can be concluded as an important tool in toxicity assessment and disease prognosis.     

An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties

This paper proposes a novel hybrid technique called enhanced grey wolf optimization-sine cosine algorithm-cuckoo search (EGWO-SCA-CS) algorithm to improve the electrical power system stability. The proposed method comprises of a popular grey wolf optimization (GWO) in an enhanced and hybrid form. It embraces the well-balanced exploration and exploitation using the cuckoo search (CS) algorithm and enhanced search capability through the sine cosine algorithm (SCA) to elude the stuck to the local optima. The proposed technique is validated with the 23 benchmark functions and compared with state-of-the-art methods. The benchmark functions consist of unimodal, multimodal function from which the best suitability of the proposed technique can be identified. The robustness analysis also presented with the proposed method through boxplot, and a detailed statistical analysis is performed for a set of 30 individual runs. From the inferences gathered from the benchmark functions, the proposed technique is applied to the stability problem of a power system, which is heavily stressed with the nonlinear variation of the load and thereby operating conditions. The dynamics of power system components have been considered for the mathematical model of a multimachine system, and multiobjective function has been framed in tuning the optimal controller parameters. The effectiveness of the proposed algorithm has been assessed by considering two case studies, namely, (i) the optimal controller parameter tuning, and (ii) the coordination of oscillation damping devices in the power system stability enhancement. In the first case study, the power system stabilizer (PSS) is considered as a controller, and a self-clearing three-phase fault is considered as the system uncertainty. In contrast, static synchronous compensator (STATCOM) and PSS are considered as controllers to be coordinated, and perturbation in the system states as uncertainty in the second case study.     

Enzymatic degradation,electronic, and thermal properties of graphite- and graphene oxide-filled biodegradable polylactide/poly(ε-caprolactone) blend composites

Commodity polymers are the most widely used materials for electronic packaging applications. However, they are nondegradable and causing serious environmental damage. Addressing this challenge, the relative effects of graphite (G) and graphene oxide (GO) dispersion on the enzymatic degradation, electronic properties, thermal degradation, and crystallization behavior of enzyme degradable polylactide/poly(ε-caprolactone) blend composites is investigated. Owing to the oxygenated surface functionalities and excellent thermal conductivity arising from the carbon structure, the randomly dispersed GO particles do not provide electrical pathways and facilitate large enhancements in the electrical resistivity (126%) and thermal conductivity (72%) of the blend composites. However, while the G particles enhanced the thermal conductivity of the composites, they had little effect on enzymatic degradation. Furthermore, they reduced the electrical resistivity, particularly at high concentration (0.25 wt % G), as a result of the conducting delocalized electrons in the G structure and due to network formation. We also find that the energy required to initiate and propagate the thermal degradation process for GO-filled blend composites is relatively lower than that of G-filled blend composite. However, the former composites show higher crystallization rate coefficients value than that of G-filled composites and the neat blend, thereby providing better crystallization ability and miscibility with the matrix. In summary, the GO-filled blend composites are observed to show potential for use in sustainable materials for thermal management applications. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47387.     

Performance of near-infrared dyes as effective contrast agents for breast cancer detection through simulation of photoacoustic imaging

ABSTRACT

Targeted photoacoustic imaging using exogenous contrast agents can potentially improve early detection of breast cancer, even at significant depths inside the breast. In this study, computer simulations were performed to compare the photoacoustic performance of 11 different near-infrared (NIR) dyes for detecting tumours deep inside the breast tissue. It was observed that the three high performing NIR dyes produced at least two-fold contrast enhancement of a spherical breast tumour embedded at 4?cm depth inside the breast than those of the corresponding endogenous contrast agents. These three selected dyes were employed to visualize small blood vessels deep inside the breast tissue. Although methylene blue provided the best contrast in visualizing tumour blood vessels at depths beyond 3?cm, considering other factors such as availability of suitable targeting agent, indocyanine green at 800?nm may be preferred over all other dyes for deep breast imaging applications.     

Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

Smelting Process of Chromite Ore Fines to Produce Crude Fe–Cr–Ni–N Alloy

Transactions of the Indian Institute of Metals - The smelting behavior of waste chromite ore fines containing Cr and Ni to produce crude Fe–Cr–Ni–N alloy was investigated in this...     

Assessment of relative impacts of various geo-mining factors on methane dispersion for safety in gassy underground coal mines: an artificial neural networks approach

Neural Computing and Applications - Dispersing methane to a safer level is crucial for mines safety as methane has been the greatest contributor of explosion hazard in underground coal mines...     

Building a fuzzy logic-based McCulloch-Pitts Neuron recommendation model to uplift accuracy

The Journal of Supercomputing - Recommender system is one of the most popular technique used for information filtering. It helps in discovering hidden knowledge patterns from a large set of...