Abstract:Digital twin (DT) has provided numerous opportunities for product development businesses to leverage data acquired from the physical model. Ideally, many companies are improving their use cases by using the collected physical data in a virtual model. Thanks to emerging communication technologies, 5th generation mobile network (5G), the internet of things (IoT), industrial internet of things (IIoT) sensors, etc., which help to collect data from the physical product and send data to cloud computing, called big data. With the gap in the non-availability of standard architecture, many companies are using big data and building their digital models. This paper proposes a novel DT-enabled new product design framework that has built an interaction between the DT and product design environments. This framework enables the data to be captured from various physical entities, stored in a centralized location, and pushed into the digital entity, which processes the data and converts the raw data into information used for decision-making. In the digital entity, multiple technologies are used to process data into information, such as artificial intelligence (AI) and machine learning (ML) models, mathematical models, and simulation models. The processed data that emerges from these models are called synthetic or DT data; this data is later used for control / monitoring and visualization / interaction purposes. In this paper, the data classified as visualization and interaction is integrated with the new product design framework in all four design stages, viz., concept design, detailed design, design verification, and redesign, with various data contributions to the design. A case study was discussed by applying the DT data processed using the AI / ML model in the concept design phase. Using synthetic data, the medium-duty truck frame assembly�s design concept was validated using ten load cases iteratively, and the design was finalized. The results are encouraging that the overall weight of the frame assembly was optimized by 9% without impacting the strength and factor of safety of the frame assembly.
Abstract:In the urban and suburban areas of Lanzhou, a petrochemical industry city located in northwest China, 99 Volatile Organic Compounds (VOCs) excluding aldehydes and ketones were measured using both PAMS and TO-15 methods between 2021 and 2022. The analysis of the collected data aimed to explore the seasonal trends in air pollution and its correlation with respiratory diseases in Lanzhou. The average annual concentrations of VOCs were found to be 121 ppbv for urban living areas, 165 ppbv for industrial areas, and 114 ppbv for background areas, with industrial areas exhibiting the highest concentration. These VOCs consist of various organic compounds, including alkanes, olefins, halogenated hydrocarbons, and aromatic hydrocarbons, which act as organic tracers of specific marker molecules or their sources. By employing principal component analysis and grouping the species using the maximum variance method, the VOC concentration levels were assessed across different regions. Subsequently, the associated changes were calculated based on the number of reported respiratory morbidity cases from public health hospitals in each region. The results suggest a correlation between VOC concentration levels and the onset of respiratory illnesses during the fall and winter seasons. Therefore, reducing VOC emissions during these months can effectively mitigate the public health risks associated with respiratory illnesses.
Abstract:This study analyses combined impacts of radiation and ion slip on unsteady MHD\nchemically reacting fluid flow past on plate with variable wall temperature and mass transfer in the presence of Hall current. The geometry of the flow model has been consider exponentially accelerated inclined surface and medium of the flow taken porous. A set of non-dimensional governing MHD fluid model is obtained and the governing equations of this fluid model are linear, an exact solution of our model can be obtained by using Laplace transform method. The impact of various parameters on flow\nof the fluid are discussed with the help of graph and table.
Abstract:Abstract\n\nFinancial services have been fundamentally transformed by FinTech, an innovation in technology that has caused significant shifts in the financial sector. This study delves into the impact of two prominent FinTech platforms, Stripe and Square, on the banking industry. Stripe specializes in online payments, customization, and agility, with a focus on in-person transactions, catering to technologically adept startups. Conversely, Square offers tools tailored for small retail and restaurant enterprises. The study aims to bridge the gap between user perceptions and actual performance, focusing on security and reliability concerns. Despite the convenience offered by FinTech, concerns over security persist, highlighting the need for improved user confidence through robust security standards and transparency. The research explores the historical evolution of FinTech, emphasizing the integration of advanced technologies like AI and blockchain. The research analyzes FinTech performance evaluation methodologies, including key performance indicators (KPIs), to showcase the significance of assessing financial success, customer satisfaction, and user experience. The study outlines the criteria for selecting Stripe and Square, considering industry prominence, market share, a diverse user base, service offerings, innovation, accessibility, and financial inclusion initiatives. The methodology employs a qualitative approach to systematically analyze the performance and user experience of both platforms. Features, pricing, target audience, security, and user experience influence user preferences, according to key findings. The comparative analysis between Stripe and Square indicates a market trend where businesses choose platforms based on operational nature, settlement speed, and specific financial needs. The study underscores the transformative role of FinTech within the financial sector, driven by technological innovation, financial inclusion initiatives, diverse user bases, user-centric design, and robust security measures. The implications suggest a future FinTech landscape characterized by continued emphasis on innovation, inclusivity, user-centric approaches, and security. The research concludes by highlighting the significant impact of Stripe and Square on the financial sector and providing insights for stakeholders to adapt strategies in the dynamic FinTech landscape. Further research opportunities lie in exploring evolving user preferences, emerging technologies, and regulatory developments shaping the future of FinTech.
Abstract:Higher education institutions worldwide have been greatly affected by the COVID-19 pandemic about two years ago. As a consequence, learning and teaching mode were then changed into online platform. Today, even though most of the class activities have resumed back to physical mode, online learning is still remained as an important platform for learning. Apart from desktop computers and laptops, students use smartphones considerably for online learning. However, the physical characteristics of a smartphone could hinder its ability to work as an effective tool for academic task. In the context of online learning, this study aims to explore the adoption of an advanced feature of a modern smartphone: the desktop mode, which could possibly overcome the physical limitations of a standard smartphone. The factors that influence the undergraduate students� intention to use the smartphone�s desktop mode for online learning were examined. By using constructs from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), Learning Value (LV) and Empowerment in Learning (EiL), the PLS-SEM method was used to analyze the data collected with a self-administered survey. The results revealed that Performance Expectancy, Social Influence, Hedonic Motivation, Habit and EiL positively influence students� behavioral intention (BI) to use smartphone�s desktop mode in online learning. Additionally, gender was found to have moderating effects on the relationship between some constructs and BI.
Abstract:Welding, a crucial manufacturing process across various industries, involves forming permanent component joints. Friction stir welding (FSW), an efficient technique is employed for this purpose. FSW requires a fixture to securely hold the workpiece during welding, ensuring precise alignment, minimal deformation and effective heat dissipation. This work focuses on designing a fixture tailored for T-joint configuration FSW of aluminum alloys. Initial concept design was refined for optimal performance with material selection (Mild Steel and EN8) based on requirements. Real-time welding conditions were considered for analysis, leading to the choice of EN8 due to reduced deformation. This paper outlines the steps involved in designing, analyzing and manufacturing a T-joint welding fixture, guaranteeing proper alignment, clamping and heat management during welding.
Abstract:In this research article, we attempted to synthesize some new isatin derivatives, 3-((4-(arylideneamino)phenyl)imino)indolin-2-ones (2a-2g) by Schiff\'s base reaction under microwave technique. The structural characterizations of synthesized compounds were done by using different analytical techniques such as IR, 1HNMR, mass spectrometry, and elemental analysis. We aim to develop new compounds with improved antimycobacterial activities. These title compounds were screened for their antimycobacterial activity against the Mycobacterium tuberculosis H37Rv strain by using the microplate Alamar blue dye assay (MABA) method. All title compounds showed significant antimycobacterial activity. Compound 2g was found most potent compound with a MIC value of 6.25 µg/mL among all tested compounds when compared with standard drugs streptomycin (6.25µg/mL) and isoniazid (6.25 µg/mL).
Abstract:Insufficient insulin production results in hyperglycemia, a metabolic disorder known as diabetes mellitus (DM). The medical establishment still struggles to treat DM effectively and without side effects. As a result, there is an increase in demand for natural remedies with antidiabetic properties and few negative effects. The plant Syzygium cumini, which is used in traditional herbal medicine, is thought to have a variety of pharmacological properties. It also contains various additional chemical components in addition to terpenoids, tannins, anthocyanins, flavonoids, and other phenolic compounds. It has been hypothesized that S. cumini has antidiabetic characteristics because of the plant\'s high polyphenol and flavonoid content. The main aim of the current study was In silico test of the antidiabetic effects of various polyphenol-rich compounds such as anthocyanin (1), delphinidin (2), malvidin (3), petunidin (4), ellagic acid (5), gallic acid (6), myricetin (7), kaempherol (8), quercetin (9), betulinic acid (10), caffeic acid (11) and ferulic acid (12) from S. cumini against many targets related with DM to investigate the antidiabetic effect and prediction of the binding mode using molecular docking studies. These phytochemicals were chosen using computational techniques, and their ability to inhibit α-amylase was tested. These phytoconstituents have shown a lower α-amylase inhibitory activity capacity than voglibose. These phytochemicals additionally showed high binding energies, hydrogen bonds, and protein-ligand interactions. Additionally, these phytoconstituents\' ADMET characteristics met the safety requirements. As a result, S. cumini might be effective in the treatment of DM. The possible bioactive compounds discovered in this study could be used to develop diabetes-led medications. Serum levels of triglycerides and total cholesterol were also markedly decreased. The findings suggest that S. cumini may have pharmacological promise as a natural antidiabetic drug. The design and development of powerful, multi-functional candidate medications with few side effects for DM treatments can make use of this information.
Abstract:Novel coronavirus disease (COVID-19) is the major health crisis in the world. World Health Organization has declared COVID-19 as a global pandemic. There are no effective drugs to treat COVID-19 infection. Some drugs include remdesivir, umifenovir, favipiravir, lopinavir/ ritonavir, ribavirin, hydroxychloroquine, etc are used to treat this disease. There is an urgent need for public health measures to implement preventive approaches to control severe COVID-19 disease. Justica adhatoda is a well-known plant drug in Ayurvedic and Unani medicines. Various phytochemical constituents have been isolated from J. adhatoda which possesses activities like antitussive, abortifacient, antimicrobial, cardiovascular protection, anticholinesterase, anti-inflammatory and other important activities. The alkaloids from leaf extracts of J. adhatoda possess anti-viral activity. Molecular docking interaction study against 6W63 showed that molecule 4d showed maximum docking interaction with dock score of (-) 8.1 kcal/mol. MD simulation data reflected the stable ligand-receptor interaction. Maximum and minimum energy gap were showed by 7 and 4d, respectively. The order of stability of the synthesized molecules were 4d>2>3>5>4c>4a>4b>1>6>7. The order of ionization potential and electron affinity of the synthesized molecules were 3>4c>4b>4a>1>6>7>4d>5>2. These data confirmed that molecule 4d would be a boon for society.
Abstract:The present study evaluated the toxic effect of smokeless tobacco product extract (STPE) in phosphate buffer saline (PBS) on various body organs in albino Wistar rats. The toxicities of orally administered STPE were studied at the dose of 500, 1000 and 1500 mg/kg body weight, respectively, and the control group contained 1 ml/kg of normal saline in albino rats for 28 days. Acute toxicity was studied in albino rats by orally administering a single dose of STPE at 2000 mg/kg. The results showed that the relative organ weight of the liver, stomach, and spleen was found to increase significantly (p<0.05) in comparison to the control group. From a hematological study, it was observed that white blood cells (WBC) count was increased significantly (p < 0.05) with all three doses, but red blood cell (RBC) count remained unchanged. The biochemical parameter revealed a significant increase in serum alanine transaminase (ALT) level, blood glucose, and cholesterol level. Histopathological results suggested that administration of STPE caused damage to the liver and stomach. There was no significant change in behavior and mortality during the 14-day observation period. In conclusion, short term consumption of STPE caused gastritis in stomach and liver cell damage, hyperglycemia, hypercholesterolemia and immunotoxicity. A further long-term study is required to unveil all the risk factors associated with STPE consumption.