Microstructure, Precipitation and Micro-segregation in Inconel 825 Weldments: A Comparative study between GTAW and EBW

Inconel 825 is a Ni-Fe-Cr alloy which is widely used in engineering due to its exceptional corrosion resistance and high-temperature strength. Welding (joining) of Inconel 825 has attracted strong research attention over the past few years. In this work, the effects of heat input leading to precipitation and micro segregation of Inconel 825 weldments were examined in light of comparing them while using two popular welding techniques namely, Gas tungsten arc welding (GTAW) and Electron beam welding (EBW). It was discovered that excessive heat input during GTAW can lead to root cracking and solidification cracking; while EBW demonstrated better control over undercut and maintains consistent weld quality even for higher heat inputs. Both GTAW and EBW samples exhibit dendritic grain morphologies with distinctive grain boundaries. Precipitates, such as Al4C3 and TiN were observed in both processes, contributing to improved mechanical properties. While GTAW weldments show some degree of segregation for Mo, Cu, Ti, and Al, EBW weldments demonstrate negligible segregation for major alloying elements but micro-segregation of Ti and Al. In general, the mechanical properties of EBW weldments was better as the average hardness, tensile strength, and ductility was much better compared to the GTAW weldments. This can be attributed to lower heat input, faster cooling rates, and a reduced rate of elemental segregation during EBW. Finally, the fractographic analysis revealed the presence of voids and micro-voids, indicating a ductile mode of failure for both GTAW and EBW samples. These findings offer invaluable insights for selecting the appropriate environment and welding method to join Inconel 825 for critical safety applications

GROWTH, SPECTRAL, NLO AND IMPEDANCE STUDIES OF POTASSIUM AMMONIUM SULPHATE CRYSTALS GROWN BY AQUEOUS SOLUTION TECHNIQUE

Single crystals of Potassium Ammonium Sulphate (PAS) have been grown by the free evaporation method and characterized structurally, electrically, optically and mechanically. X-ray diffraction analysis indicates the crystal system as orthorhombic .The functional groups have been identified using Fourier transform infrared spectral analysis. UV-visible transmittance spectra showed wide transparency window in visible and near IR region. The hardness values of the grown sample have been found by Vickers microhardness test. Studies of electrical properties of PAS crystal using a complex impedance spectroscopy (CIS) technique show the decrease of bulk resistance with rise in temperature indicating a typical negative temperature coefficient of resistance (NTCR) type behavior similar to that of an insulator. The nature of Nyquist plots reveals the presence of bulk and grain boundary effects in PAS crystal. Moreover, the variation in dc conductivity is found to increase with temperature

Alteration in peripheral muscle strength among overweight and obese individuals: A systematic review

© Journal of Krishna Institute of Medical Sciences University. Peripheral muscle dysfunction in Overweight (OW) and Obesity (OB) leads to fatigue and activity limitations. However, there are contradictory views regarding the exact level with regard to hand grip and quadriceps muscle strength in OW and OB. The main objective of the present systematic review was to synthesize the literature for the strength part of the hand grip and quadriceps muscle strength among OW and OB. Literature search of Scopus, EBSCO and PubMed databases from 01.01.2004 to 30.06.2016, was performed. We set our search strategy using the terms “overweight OR obesity” AND “muscle strength” AND “grip OR quadriceps”. Two reviewers administered established eligible criteria and extracted the data. Strengthening the Reporting of Observational studies in Epidemiology (STROBE) was used to assess the risk of bias. Sixteen articles which were included identified Handgrip Strength (HGS), shoulder flexor, elbow flexor and knee extensor were found to be altered. There were consistent results with an increase in quadriceps muscle strength, whereas differed results were found in hand grip to increase and decrease in muscle strength in the presence of OW and OB. It is concluded that HGS appeared to be diversified with findings of increased and decrease strength, whereas regarding the quadriceps muscles, the findings were homogeneous

Surface acoustic wave distribution and acousto-optic interaction in proton exchanged LiNbO<SUB>3</SUB> waveguides

The efficiency of acoustooptic (AO) interaction in YZ-cut proton exchanged (PE) LiNbO3 waveguides is theoretically analysed by determining the overlap between the optical and acoustic field distributions. The present analysis takes into account the perturbed SAW field distribution due to the presence of the PE layer on the LiNbO3 substrate determined by the rigorous layered medium approach. The overlap is found to be significant upto very high acoustic frequencies of the order of 5 GHz, whereas in the earlier analysis by vonHelmolt and Schaffer [6] for diffused waveguides, it was shown that the overlap integral rolls down to nearly zero at this high frequency range

Mechanisms of variability and predictability of the tropical coupled ocean-atmosphere system

A conceptual model is proposed to explain the observed aperiodicity in the short term climate fluctuations of the tropical coupled ocean-atmosphere system. This is based on the evidence presented here that the tropical coupled ocean-atmosphere system sustains a low frequency inter-annual mode and a host of higher frequency intra-seasonal unstable modes. At long wavelengths, the low frequency mode is dominant while at short wavelengths, the high frequency modes are dominant resulting in the co-existence of a long wave low frequency mode with some short wave intra-seasonal modes in the tropical coupled system. It is argued that due to its long wavelength, the low frequency mode would behave like a linear oscillator while the higher frequency short wave modes would be nonlinear. The conceptual model envisages that an interaction between the low frequency linear oscillator and the high frequency nonlinear oscillations results in the observed aperiodicity of the tropical coupled system. This is illustrated by representing the higher frequency intra-seasonal oscillations by a nonlinear low order model which is then coupled to a linear oscillator with a periodicity of four years. The physical mechanism resulting in the aperiodicity in the low frequency oscillations and implications of these results on the predictability of the coupled system are discussed

Adaptive neuro-fuzzy inference system and particle swarm optimization: A modern paradigm for securing VANETs

Vehicular Adhoc Networks (VANET) facilitate inter-vehicle communication using their dedicated connection infrastructure. Numerous advantages and applications exist associated with this technology, with road safety particularly noteworthy. Ensuring the transportation and security of information is crucial in the majority of networks, similar to other contexts. The security of VANETs poses a significant challenge due to the presence of various types of attacks that threaten the communication infrastructure of mobile vehicles. This research paper introduces a new security scheme known as the Soft Computing-based Secure Protocol for VANET Environment (SC-SPVE) method, which aims to tackle security challenges. The SC-SPVE technique integrates an adaptive neuro-fuzzy inference system and particle swarm optimisation to identify different attacks in VANETs efficiently. The proposed SC-SPVE method yielded the following average outcomes: a throughput of 148.71 kilobits per second, a delay of 23.60 ms, a packet delivery ratio of 95.62%, a precision of 92.80%, an accuracy of 99.55%, a sensitivity of 98.25%, a specificity of 99.65%, and a detection time of 6.76 ms using the Network Simulator NS2

Sliding principal component and dynamic reward reinforcement learning based IIoT attack detection

The Internet of Things (IoT) involves the gathering of all those devices that connect to the Internet with the purpose of collecting and sharing data. The application of IoT in the different sectors, including health, industry has also picked up the threads to augment over the past few years. The IoT and, by integrity, the IIoT, are found to be highly susceptible to different types of threats and attacks owing to the networks nature that in turn leads to even poor outcomes (i.e., increasing error rate). Hence, it is critical to design attack detection systems that can provide the security of IIoT networks. To overcome this research work of IIoT attack detection in large amount of evolutions is failed to determine the certain attacks resulting in a minimum detection performance, reinforcement learning-based attack detection method called sliding principal component and dynamic reward reinforcement learning (SPC-DRRL) for detecting various IIoT network attacks is introduced. In the first stage of this research methodology, preprocessing of raw TON_IoT dataset is performed by employing min-max normalization scaling function to obtain normalized values with same scale. Next, with the processed sample data as output, to extract data from multi-sources (i.e., different service profiles from the dataset), a robust log likelihood sliding principal component-based feature extraction algorithm is applied with an arbitrary size sliding window to extract computationally-efficient features. Finally, dynamic reward reinforcement learning-based IIoT attack detection model is presented to control the error rate involved in the design. Here, with the design of dynamic reward function and introducing incident repository that not only generates the reward function in an arbitrary fashion but also stores the action results in the incident repository for the next training, therefore reducing the attack detection error rate. Moreover, an IIoT attack detection system based on SPC-DRRL is constructed. Finally, we verify the algorithm on the ToN_IoT dataset of University of New South Wales Australia. The experimental results show that the IIoT attack detection time and overhead along with the error rate are reduced considerably with higher accuracy than that of traditional reinforcement learning methods

Involvement of Essential Signaling Cascades and Analysis of Gene Networks in Diabesity

(1) Aims: Diabesity, defined as diabetes occurring in the context of obesity, is a serious health problem that is associated with an increased risk of premature heart attack, stroke, and death. To date, a key challenge has been to understand the molecular pathways that play significant roles in diabesity. In this study, we aimed to investigate the genetic links between diabetes and obesity in diabetic individuals and highlight the role(s) of shared genes in individuals with diabesity. (2) Methods: The interactions between the genes were analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) tool after the compilation of obesity genes associated with type 1 diabetes (T1D), type 2 diabetes (T2D), and maturity-onset diabetes of the young (MODY). Cytoscape plugins were utilized for enrichment analysis. (3) Results: We identified 546 obesity genes that are associated with T1D, T2D, and MODY. The network backbone of the identified genes comprised 514 nodes and 4126 edges with an estimated clustering coefficient of 0.242. The Molecular Complex Detection (MCODE) generated three clusters with a score of 33.61, 16.788, and 6.783, each. The highest-scoring nodes of the clusters were , , and genes. The genes from cluster 1 were enriched in FOXO-mediated transcription of oxidative stress, renin secretion, and regulation of lipolysis in adipocytes. The cluster 2 genes enriched in Src homology 2 domain-containing (SHC)-related events triggered by , regulation of lipolysis in adipocytes, and GRB2: SOS produce a link to mitogen-activated protein kinase (MAPK) signaling for integrins. The cluster 3 genes ere enriched in IGF1R signaling cascade and insulin signaling pathway. (4) Conclusion: This study presents a platform to discover potential targets for diabesity treatment and helps in understanding the molecular mechanism.The APC was funded by Qatar University Internal Grant number [QUST-2-CHS-2020-12

Regulation of mammary gland branching morphogenesis by the extracellular matrix and its remodeling enzymes.

A considerable body of research indicates that mammary gland branching morphogenesis is dependent, in part, on the extracellular matrix (ECM), ECM-receptors, such as integrins and other ECM receptors, and ECM-degrading enzymes, including matrix metalloproteinases (MMPs) and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs). There is some evidence that these ECM cues affect one or more of the following processes: cell survival, polarity, proliferation, differentiation, adhesion, and migration. Both three-dimensional culture models and genetic manipulations of the mouse mammary gland have been used to study the signaling pathways that affect these processes. However, the precise mechanisms of ECM-directed mammary morphogenesis are not well understood. Mammary morphogenesis involves epithelial 'invasion' of adipose tissue, a process akin to invasion by breast cancer cells, although the former is a highly regulated developmental process. How these morphogenic pathways are integrated in the normal gland and how they become dysregulated and subverted in the progression of breast cancer also remain largely unanswered questions