Application of Time Dependent Green’s Function Method to Scattering of Elastic Waves in Anisotropic Solids

The propagation and scattering of elastic waves provides a valuable tool for the QNDE of composite materials. Since, in general, the composite materials are highly anisotropic, it is important to develop theoretical methods for calculation of wave propagation characteristics in anisotropic media. A lot of work has been done on transient wave propagation in isotropic media but not much in anisotropic media (see, for example [1,2] and other references given there)

Leishmania lipophosphoglycan activates the transcription factor activating protein 1 in J774A.1 macrophages through the extracellular signal-related kinase (ERK) and p38 mitogen-activated protein kinase

Leishmania donovani is an obligatory intracellular pathogen that resides and multiplies in the phagolysosomes of macrophages. The outcome of this infection depends on the balance between the host ability to activate macrophage killing and the parasite ability to suppress or evade this host immune response. Lipophosphoglycan (LPG) glycoconjugate, the surface molecule of the protozoan parasite is a virulence determinant and a major parasite molecule involved in this process. In this study, we examined the ability of Leishmania and its surface molecule, lipophosphoglycan to activate activating protein 1 (AP-1) through the mitogen-activated protein kinase (MAPK) cascade. We report here that the Leishmania surface molecule, lipophosphoglycan stimulates the simultaneous activation of all three classes of MAP kinases, extracellular signal-related kinases (ERKs), the c-jun amino-terminal kinase (JNK) and the p38 MAP kinase with differential kinetics in J774A.1 macrophage cell line. Furthermore, both L. donovani and its surface molecule lipophosphoglycan resulted in a dose- and time-dependent induction of AP-1 DNA-binding activity. We have also shown a dose-dependent increase of AP-1 binding activity in both low and high virulent strains of parasite. The use of inhibitors selective for ERK (PD98059) and p38 (SB203580) pathway showed that pre-incubation of cells with either SB203580 or PD98059 affected the binding activity of AP-1 suggesting that both p38 and ERK MAP kinase activation appear to be necessary for AP-1 activation by LPG. Lipophosphoglycan induced IL-12 production and generation of nitric oxide in murine macrophages. These results demonstrate that L. donovani LPG activates pro-inflammatory, endotoxin-like response pathway in J774A.1 macrophages and the interaction may play a pivotal role in the elimination of the parasite

Discrete wavelet transforms analysis of vibration signals for correlating tool wear in diamond turning of additive manufactured Ti-6Al-4V alloy

Ultra-precision machining (UPM) of Ti-6Al-4V alloy is widely regarded as a challenging material processing due to excessive tool wear and chemical reactivity of the tool and workpiece. Tool wear has a significant influence on the surface quality and also causes damage to the substrate. Therefore, it is critical to consider the tool condition during diamond turning, especially as precision machining moves toward intelligent systems. Consequently, there is a need for effective ways for in-process tool wear monitoring in UPM. This study aims to monitor the diamond tool wear using time-frequency-based wavelet analysis on vibrational signals acquired during the machining of Additively Manufactured (AM) Ti6Al4V alloy. The analysis employed Daubechies wavelet (db4, level 8) to establish a correlation between the Standard Deviation (SD) of the magnitude in the decomposed vibrational signal obtained from both the fresh and used tools. The analysis revealed that at a feed rate of 1 mm/min, the change in SD is 32.3% whereas at a feed rate of 5 mm/min, the change in SD is 8.4%. Furthermore, the flank wear and microfractures are observed using a scanning electron microscope on the respective flank and rake face of the diamond tool.The author(s) received no financial support for the research, authorship, and/or publication of this article

Monitoring and Predicting the Surface Generation and Surface Roughness in Ultraprecision Machining: A Critical Review

Copyright: © 2021 by the authors. The aim of manufacturing can be described as achieving the predefined high quality product in a short delivery time and at a competitive cost. However, it is unfortunately quite challenging and often difficult to ensure that certain quality characteristics of the products are met following the contemporary manufacturing paradigm, such as surface roughness, surface texture, and topographical requirements. Ultraprecision machining (UPM) requirements are quite common and essential for products and components with optical finishing, including larger and highly accurate mirrors, infrared optics, laser devices, varifocal lenses, and other freeform optics that can satisfy the technical specifications of precision optical components and devices without further post-polishing. Ultraprecision machining can provide high precision, complex components and devices with a nanometric level of surface finishing. Nevertheless, the process requires an in-depth and comprehensive understanding of the machining system, such as diamond turning with various input parameters, tool features that are able to alter the machining efficiency, the machine working environment and conditions, and even workpiece and tooling materials. The non-linear and complex nature of the UPM process poses a major challenge for the prediction of surface generation and finishing. Recent advances in Industry 4.0 and machine learning are providing an effective means for the optimization of process parameters, particularly through in-process monitoring and prediction while avoiding the conventional trial-and-error approach. This paper attempts to provide a comprehensive and critical review on state-of-the-art in-surfaces monitoring and prediction in UPM processes, as well as a discussion and exploration on the future research in the field through Artificial Intelligence (AI) and digital solutions for harnessing the practical UPM issues in the process, particularly in real-time. In the paper, the implementation and application perspectives are also presented, particularly focusing on future industrial-scale applications with the aid of advanced in-process monitoring and prediction models, algorithms, and digital-enabling technologies

A Study of Air Pollution load assessment around opencast coal project in India

Opencast mining technology results in the release of a huge amount of air borne dust. The air borne dust peculiarly below 100 micron in size, are environmentally nuisance and cause health hazards. Total suspended particulate matter (TSPM) and respiratory particulate mater (PM10) are the major pollutants in the air environment of opencast coal mines. Therefore, dust generation, its dispersion, and pollution load assessment have been found to be major concer4ns in air quality modeling of opencast coal mines. The present paper focuses on the quantification of sourcewise emission inventory for different point, area and line sources considering the background dust concentration at one of opencast coal project (OCP), nakmely Hindustan Lalpet of Western Coalfields Limited (WCL). The 24 hr average concentrations of TSPM and PM10 were monitored at three monitoring stations during winter season. On an average the PM10 concentration in the ambient air constituted 17.00 to 60.3% of TSPM concentration. TSPM concentration ranged from 313.11 to 565.57 µg/m3 and 79.48 to 270.61 µg/m3

Fugitive emission studies of workplace air of an opencast mining locality to know the overall impacts on ambient air quality - A case study

Dust generated by the wheels of dumper, trucks, etc of granular materials exposed to the air known as fugitive emission because it is not discharged to the atmosphere in a confined flow stream. Study has been conducted at Block – II OCP for the evaluation of emission due to area source in order to assess its impact over general ambient air quality. Application of Oak Ridge Air Quality Index (ORAQI) highlight about the status of workplace air as well as overall impacts on the quality of its surrounding atmosphere of the region

Manipulation of graphene's dynamic ripples by local harmonic out-of-plane excitation

With use of carefully designed molecular dynamics simulations, we demonstrate tuning of dynamic ripples in free-standing graphene by applying a local out-of-plane sinusoidal excitation. Depending on the boundary conditions and external modulation, we show control of the local dynamic morphology, including flattening and stable rippling patterns. In addition to studying the dynamic response of atomically thin layers to external time-varying excitation, our results open intriguing possibilities for modulating their properties via local dynamic morphology control

Biostabilization of Mandaman dump slope, India

An integrated study of the biological stabilization of a coal-mine overburden dump slope has been carried out at Mandaman, 35 km from Dhanbad in eastern India native grasses-bamboo (Dendrocalmus strictus) and kashi (Saccharum spontaneoum)-are important species that can stabilize the dump slopes. The grasses have good soil binding capacity and help to control soil erosion and improve dump stability. Field observation of their growth performance has indicated that the mean grass height and root depth are 232(±74) cm and 46 (±5) cm, respectively, after there years and the below-ground root biomass is 474 (±69) g m-2. The mechanical and hydrogeological actions of the grass roots have improved the shear strength properties of the dump material. Numerical modeling has shown that the roots of these grasses increase the factor of safety of the dump slope from 1.2 to 1.4 and thus play a substantial role in the maintenance of long-term stability