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Purpose Since the biomedical implants with an improved compressive strength, near bone elastic modulus, controlled porosity, and sufficient surface roughness, can assist in long term implantation. Therefore, the fine process tuning plays its crucial role to develop optimal settings to achieve these desired properties. This paper aims to find applications for fine process tuning in laser powder bed fusion of biomedical Ti alloys for load-bearing implants. Design/methodology/approach In this work, the parametric porosity simulations were initially performed to simulate the process-induced porosity for selective laser-melted Ti6Al4V as per full factorial design. Continually, the experiments were performed to validate the simulation results and perform multiresponse optimization to fine-tune the processing parameters. Three levels of each control variable, namely, laser power – Pl (180, 190, 200) W, scanning speed – Vs (1500, 1600, 1700) mm/s and scan orientation – ϴ{1(0,0), 2(0,67°), 3(0,90°)} were used to investigate the processing performance. The measured properties from this study include compressive yield strength, elastic modulus, process-induced porosity and surface roughness. Finally, confirmatory experiments and comparisons with the already published works were also performed to validate the research results. Findings The results of porosity parametric simulation and experiments in selective laser melting of Ti6Al4V were found close to each other with overall porosity (less than 10%). The fine process tuning was resulted in optimal settings [Pl (200 W), Vs (1500 mm/s), ϴ (0,90°)], [Pl (200 W), Vs (1500 mm/s), ϴ (0,67°)], [Pl (200 W), Vs (1500 mm/s), ϴ (0,0)] and [Pl (200 W), Vs (1500 mm/s), ϴ (0,0)] with higher compressive strength (672.78 MPa), near cortical bone elastic modulus (12.932 GPa), process-induced porosity (0.751%) and minimum surface roughness (2.72 µm). The morphology of the selective laser melted (SLMed) surface indicated that the lack of fusion pores was prominent because of low laser energy density among the laser and powder bed. Confirmatory experimentation revealed that an overall percent improvement of around 15% was found between predicted and the experimental values. Originality/value Since no significant works are available on the collaborative optimization and fine process tuning in laser powder bed fusion of biomedical Ti alloys for different load bearing implants. Therefore, this work involves the comprehensive investigation and multi-objective optimization to determine optimal parametric settings for better mechanical and physical properties. Another novel aspect is the parametric porosity simulation using Ansys Additive to assist in process parameters and their levels selection. As a result, selective laser melted Ti alloys at optimal settings may help in examining the possibility for manufacturing metallic implants for load-bearing applications.

The present study was carried out to determine the floristic diversity and their distribution in Bangus valley of Langate Forest Division, District Kupwara (J&K) India. The aim of this study was to evaluate the distinction in diversity of medicinal plants at varying altitudes based on the onsite vegetation analysis. Hence, the phytosociological study was conducted to assess the floristic diversity of the region and the discussions were held with local people to ascertain the socio-economic importance of the plant diversity. The study reveals that majority of the medicinal plant species are mainly distributed between 2900 to 3200 meters altitude from this relatively unexplored valley. In all the sampled sites, around 51 plant species belonging to 24 families were recorded, among which 2 were tree, 3 shrub and 46 herb species. The tree vegetation was found to be dominated by Abies pindrow whereas Pinus wallichiana has very rare distribution in all the sampled sites. The shrub vegetation was dominated by Viburnum grandiflorum followed by Rosa brunonii and Berberis lycium respectively. In addition, around 80 plant species were reported to be used in different systems of traditional medicine. Therefore, the study provided first comprehensive baseline information on the distribution, diversity and use of plants in different traditional systems of medicine in Bangus valley of Kashmir. This baseline study can be effective for framing various conservation strategies of medicinal plants.

Background: The phenomenon of rotating disks involving flows serves as a crucial element in the field of fluid mechanics. Owing to its massive practical importance in engineering and industry, considerable attention is being paid to the extension of the problems associated with rotating stretching disks. In this regard, Carbon Nanotubes (CNT) are chosen as the best example of true nano technology. CNTs have an incredible range of applications due to their extraordinary characteristics. But single rotating-stretching disk with CNTs fluid flow has not been plowed yet. Objective: The objective of this work is to outstretch the study of viscous fluid with Carbon Nanotubes (CNTs) and transfer of heat due to radially stretching and rotating disk contingent to Navier slip, nonlinear radiations and convective boundary conditions. Methods: Cylindrical coordinates are utilized in the modeling and the mathematical formulation of the flow equations. These flow equations take the form of ordinary differential equations by means of similarity transformations. The emanated equations are solved by two numerical methods i.e. the shooting method and the Keller box method respectively. Xue model of carbon nanotubes is incorporated to carry out the research. Results: The acquired solutions are tabulated and precise values of the physical parameters with excellent matching results are shown. These results are juxtaposed with CNTs of multi-wall and single-wall carbon nanotubes, while water is taken as a base fluid. Conclusion: Results reveal a significant depletion in skin friction with an increase in the slip parameter. Slip, nonlinear radiation and Biot number proved as liable factors in escalating the rate of heat transfer.

The present investigation was carried out, during the year 2019-2021 to investigate the primary sources and preferred species for fuelwood consumption among the local people of Kashmir Himalayas, India. The sample of study area was drawn by multi-stage random sampling technique. The data were collected through personal interviews of respondents using well-structured pre-tested interview schedule and non-participant observations. The study revealed that people extract enormous quantity of fuelwood mostly from forests and utilize maximum portion of extracted fuelwood for cooking and heating. Fuelwood collection was mainly done by women along with children. Winter season consumption was more than summer season consumption. Consumption of fuelwood was maximum at high elevation (>2000m) and minimum at middle and low elevation (1900-2000m and

The topological index is a numerical representation of a molecular structure and predicts the physical property of a chemical compound. In the present work, we have developed explicit expressions of recently defined novel Ve- degrees and Ev-degrees based topological indices of Magnesium Oxide MgO (111). For this by consider a unit cell of MgO (111) which is extended to its general structure. After that, we have computed Ve-degrees and Ev-degrees of this general structure of MgO (111) then by employing well-known topological indices on these computed Ve- degrees and Ev-degrees of the general structure, obtained numerical results. A variety of graphical invariants have been described and tested, offering lots of applications in the fields of nano-chemistry, computational networks, and indifferent scientific research areas. These computed results will help study the physical, chemical, and biological properties of the structure such as boiling, melting, and flickering point; moisture and forming heat; temperature, strain, density, etc.

Some motion problems of Burgers fluids between parallel plates are analytically and numerically investigated when magnetic and porous effects are taken into account and a differential expression of the non-trivial shear stress is prescribed on the lower plate. Closed-form expressions are determined for the non-dimensional steady state velocity and shear stress fields and the corresponding Darcy’s resistances. They are the first exact solutions for hydromagnetic motions of Burgers fluids through porous media when a differential expression of shear stress is given on the boundary. The results that have been obtained are used to get the necessary time to reach the steady state and to bring to light the influence of magnetic field and porous medium on the flow resistance of the fluid. They can immediately be particularized to provide exact solutions for similar motions of Oldroyd-B, Maxwell, second grade and Newtonian fluids. It was found that the steady state is rather obtained in the presence of a magnetic field or porous medium. In addition, the flow resistance of the fluid declines in the presence of a magnetic field and, as expected, increases through porous media.

Three-dimensional (3D) printing of polylactic acid using the fused filament fabrication approach is a widely used additive manufacturing method in various fields, despite the historical issue of substantial surface roughness in fused filament fabrication products. Several strategies have been utilized to minimize the surface roughness of 3D-printed items. However, laser polishing is a novel technique for reducing surface roughness and improving other material qualities. In this study, polylactic acid was examined using the laser polishing method for surface roughness and mechanical properties, such as tensile and flexural strength and laser scan time. Several trials were conducted to determine how changing the laser’s characteristics may affect the materials’ surface quality and mechanical qualities. Before the final test, preliminary tests were performed to determine the lowest potential heat-affected zone. Laser polishing reduced surface roughness by more than 88.8% (from 7.8 µm to 0.87 µm). The tensile strength of the specimen increased by 14.03%, from 39.2 MPa to 44.7 MPa. Polylactic acid had a constant flexural strength of 70.1 MPa before and after polishing, and the laser scan time for samples was 19.4 s. Polished morphologies were studied to learn more about the microstructure. These findings show that laser polishing can improve and modify the surface properties of a fused filament fabrication product, which can benefit the industry and researchers.

Coronavirus disease (COVID-19), also known as Severe acute respiratory syndrome (SARS-COV2) and it has imposed deep concern on public health globally. Based on its fast-spreading breakout among the people exposed to the wet animal market in Wuhan city of China, the city was indicated as its origin. The symptoms, reactions, and the rate of recovery shown in the coronavirus cases worldwide have been varied. The number of patients is still rising exponentially, and some countries are now battling the third wave. Since the most effective treatment of this disease has not been discovered so far, early detection of potential COVID-19 patients can help isolate them socially to decrease the spread and flatten the curve. In this study, we explore state-of-the-art research on coronavirus disease to determine the impact of this illness among various age groups. Moreover, we analyze the performance of the Decision tree (DT), K-nearest neighbors (KNN), Naive bayes (NB), Support vector machine (SVM), and Logistic regression (LR) to determine COVID-19 in the patients based on their symptoms. A dataset obtained from a public repository was collected and pre-processed, before applying the selected Machine learning (ML) algorithms on them. The results demonstrate that all the ML algorithms incorporated perform well in determining COVID-19 in potential patients. NB and DT classifiers show the best performance with an accuracy of 93.70%, whereas other algorithms, such as SVM, KNN, and LR, demonstrate an accuracy of 93.60%, 93.50%, and 92.80% respectively. Hence, we determine that ML models have a significant role in detecting COVID-19 in patients based on their symptoms.

Wood-based industries fall under secondary economic activity. The industrial process involves changing the form of goods to enhance their value. To undertake the manufacturing of goods, inputs in the form of capital, labor, power, and raw materials are required. The output is a finished product that can either be used again as a raw material for another manufactured or consumed in its present form. The location of an industry, thus, largely depends on the avail­ability of raw materials, power, capital, labor, infrastructure, and managerial skill. The establishment of the wood industry is also influenced by the gen­eral climatic conditions, weather, industrial inertia, historical accident, and government policy. The Kashmiris have an age-old tradition in the manufacturing of, paper machines, willow-wicker, cricket bat and toys making are some of the important industries which pro­vide full or part-time employment to the people.

Graphical Abstract Additively manufactured nano-MEH systems are widely used to harvest energy from renewable and sustainable energy sources such as wind, ocean, sunlight, raindrops, and ambient vibrations. A comprehensive study focusing on in-depth technology evolution, applications, problems, and future trends of specifically 3D printed nano-MEH systems with an energy point of view is rarely conducted. Therefore, this paper looks into the state-of-the-art technologies, energy harvesting sources/methods, performance, implementations, emerging applications, potential challenges, and future perspectives of additively manufactured nano-mechanical energy harvesting (3DP-NMEH) systems. The prevailing challenges concerning renewable energy harvesting capacities, optimal energy scavenging, power management, material functionalization, sustainable prototyping strategies, new materials, commercialization, and hybridization are discussed. A novel solution is proposed for renewable energy generation and medicinal purposes based on the sustainable utilization of recyclable municipal and medical waste generated during the COVID-19 pandemic. Finally, recommendations for future research are presented concerning the cutting-edge issues hurdling the optimal exploitation of renewable energy resources through NMEHs. China and the USA are the most significant leading forces in enhancing 3DP-NMEH technology, with more than 75% contributions collectively. The reported output energy capacities of additively manufactured nano-MEH systems were 0.5–32 mW, 0.0002–45.6 mW, and 0.3–4.67 mW for electromagnetic, piezoelectric, and triboelectric nanogenerators, respectively. The optimal strategies and techniques to enhance these energy capacities are compiled in this paper. Supplementary Information The online version contains supplementary material available at 10.1186/s40580-021-00289-0., Highlights The current technology evolution and advancements in 3DP-NMEHs were evaluated.Categorization and comparison of 3DP-NMEHs were performed in terms of inputs and energy conversion.The emerging applications of 3DP-NMEHs were discussed briefly.The potential challenges confronted by 3DP-NMEHs and respective recommendations were summarized.Sustainable use of recyclable waste generated during the COVID-19 pandemic was proposed. Supplementary Information The online version contains supplementary material available at 10.1186/s40580-021-00289-0.

The idea for the Internet of Robotic Things (IoRT) comes from activities. IoRT allows smart devices to combine sensor information from multiple sources, use broader nearby insights to determine the best reason for the activity and display events on-screen. The Internet of Things can connect web applications to other gadgets to make them smarter. Automated engineers combine the two and arm themselves with sensors that can analyze the current situation. Mechanical improvements such as ordinary voice links (PC) vision sensor innovations and artificial intelligence (AI) have resulted in a turn of events and programmed placement frameworks under advanced machinery. This article examines frameworks for arranging programmed objects to assemble robots and innovative patterns in ordinary language programmed programming, and three-dimensional (3D) visual insight. The relevant statement "regulation scene" should describe the combination of all three modules. This computation enables people to relate through a three-tiered information scene and guides managers to use discourse to provide reasonable criteria whenever an order is legitimate. After receiving precise criteria, the robot can use this diary's planned execution calculations and programmed programming to direct the placement of programmed items. The play area provides a context for the natural product, while the landscape design provides a valuable part of the framework.

Purpose Additive manufacturing (AM) technology has a huge influence on the real world because of its ability to manufacture massively complicated geometrics. The purpose of this study is to use CiteSpace (CS) visual analysis to identify fused deposition modeling (FDM) research and development patterns to guide researchers to decide future research and provide a framework for corporations and organizations to prepare for the development in the rapid prototyping industry. Three-dimensional printing (3DP) is defined to budget minimize manufactured input and output for aviation and the medical product industrial sectors. 3DP has implemented its potential in the Coronavirus Disease of 2019 (COVID-19) reaction. Design/methodology/approach First, 396 original publications were extracted from the web of science (WOS) with the comprehensive list and did scientometrics analysis in CS software. The parameters are specified in CS including the span (from 2011 to 2019, one year slice for the co-authorship and the co-accordance analysis), visualization (show the merged networks), specific criteria for selection (top 20%), node form (author, organization, region, reference cited; cited author, journal and keywords) and pruning (pathfinder and slicing network). Finally, correlating data was studied and showed the results of the visualization study of FDM research were shown. Findings The framework of FDM information is beginning to take shape. About hot research topics, there are “Morphology,” “Tensile Property by making Blends,” “Use of Carbon nanotube in 3DP” and “Topology optimization.” Regarding the latest research frontiers of FDM printing, there are “Fused Filament Fabrication,” “AM,” in FDM printing. Where “Post-processing” and “environmental impact” are the research hotspots in FDM printing. These research results can provide insight into FDM printing and useful information to consider the existing studies and developments in FDM researchers’ analysis. Research limitations/implications Despite some important obtained results through FDM-related publications’ visualization, some deficiencies remain in this research. With >99% of articles written in English, the input data for CS was all downloaded from WOS databases, resulting in a language bias of papers in other languages and neglecting other data sources. Although, there are several challenges being faced by the FDM that limit its wide variety of applications. However, the significance of the current work concerning the technical and engineering prospects is discussed herein. Originality/value First, the novelty of this work lies in describing the FDM approach in a Scientometric way. In Scientometric investigation, leading writers, organizations, keywords, hot research and emerging knowledge points were explained. Second, this research has thoroughly and comprehensively examined the useful sustainability effects, i.e. economic sustainability, energy-based sustainability, environmental sustainability, of 3DP in industrial development in qualitative and quantitative aspects by 2025 from a global viewpoint. Third, this work also described the practical significance of FDM based on 3DP since COVID-19. 3DP has stepped up as a vital technology to support improved healthcare and other general response to emergency situations.

Some mixed initial-boundary value problems are analytically studied. They correspond to unsteady motions of the incompressible upper-convected Maxwell (IUCM) fluids with linear dependence of viscosity on the pressure between infinite horizontal parallel plates. The fluid motion is generated by the upper plate that applies time-dependent shear stresses to the fluid. Exact solutions are established for the dimensionless velocity and nontrivial shear stress fields using a suitable change of the spatial variable and the Laplace transform technique. They are presented as sum of the steady-state and transient components and are used to determine the required time to reach the permanent state. Comparisons between exact and numerical solutions indicate an excellent agreement. Analytical solutions for the unsteady motion of the same fluids induced by an exponential shear stress on the boundary are obtained as limiting cases of the general solutions. Moreover, the steady-state solutions corresponding to the ordinary IUCM fluids performing the initial motions are provided by means of asymptotic approximations of standard Bessel functions. Finally, spatial variation of starting solutions and the influence of physical parameters on the fluid motion are graphically underlined and discussed.

The Internet of Things has provided people with a seamless, automated home and industrial experience. The concept is now integrated into more domains like Internet of robotic things (IoRT), Internet of medicine Things (IoMT), etc., to improve domain-specific outcomes. For IoRT, which is the robotics implementation of Internet of Things (IoT), poor network security could cause economic and physical damage to both the networked devices and human users of the network. Also, the tendency for data and privacy breaches becomes more prevalent with an increase in the number of devices in the network. Hence, these identified vulnerabilities are the limiting elements for proper IoRT implementation. Various works have proposed security schemes for ensuring the realization of a secure and efficient IoRT network, but with computational time and complexity limitations. However, machine learning methodologies have shown the best promise for identifying malicious traffic in an IoRT network. This work proposes a security architecture using a Deep Neural Network and an ensemble of Decision Trees. This architecture can be implemented online or offline with minimal trade-offs between resources and efficiency. Also, the proposed machine learning models are compared with other commonly implemented schemes using the IoT-23 Dataset. Experimentation and comparison show that the proposed model and architecture are optimal for the malware detection task and security of a typical IoRT network. These contributions are significant for realizing secure and efficient IoRT networks for the future of industrial automation in this post-COVID era.

Sustainable and cleaner manufacturing systems have found broad applications in industrial processes, especially aerospace, automotive and power generation. Conventional manufacturing methods are highly unsustainable regarding carbon emissions, energy consumption, material wastage, costly shipment and complex supply management. Besides, during global COVID-19 pandemic, advanced fabrication and management strategies were extremely required to fulfill the shortfall of basic and medical emergency supplies. Three-dimensional printing (3DP) reduces global energy consumption and CO2 emissions related to industrial manufacturing. Various renewable energy harvesting mechanisms utilizing solar, wind, tidal and human potential have been fabricated through additive manufacturing. 3D printing aided the manufacturing companies in combating the deficiencies of medical healthcare devices for patients and professionals globally. In this regard, 3D printed medical face shields, respiratory masks, personal protective equipment, PLA-based recyclable air filtration masks, additively manufactured ideal tissue models and new information technology (IT) based rapid manufacturing are some significant contributions of 3DP. Furthermore, a bibliometric study of 3D printing research was conducted in CiteSpace. The most influential keywords and latest research frontiers were found and the 3DP knowledge was categorized into 10 diverse research themes. The potential challenges incurred by AM industry during the pandemic were categorized in terms of design, safety, manufacturing, certification and legal issues. Significantly, this study highlights the versatile role of 3DP in battle against COVID-19 pandemic and provides up-to-date research frontiers, leading the readers to focus on the current hurdles encountered by AM industry, henceforth conduct further investigations to enhance 3DP technology.

Exact and simple expressions for the permanent solutions corresponding to two oscillatory motions of incompressible upper-convected Maxwell fluids with exponential dependence of viscosity on the pressure between parallel plates have been established using suitable changes of the spatial variable and the unknown function and the Laplace transform technique. The solutions that have been obtained satisfy the boundary conditions and governing equations but are independent of the initial conditions. They are important for those who want to eliminate the transients from their experiments. The similar solutions for the simple Couette flow of the same fluids as well as known results for the Newtonian fluids performing the same motions were obtained as limiting cases. The convergence of starting solutions to the corresponding permanent components that has been graphically proved could constitute an asset on the correctness of obtained results. The influence of pertinent parameters on the fluid motion and the spatial profiles of starting solutions have been graphically depicted and discussed. The oscillations’ amplitude is an increasing function with respect to the dimensionless pressure–viscosity coefficient and the Weissenberg number. It is lower for the shear stress as compared to the fluid velocity. The three-dimensional distribution of the starting velocity fields has been numerically visualized by means of the two-dimensional contour graphs.

The dominant Intrusion Detection Models in the field of IoT/IIoT cybersecurity use network-based datasets. This paper proposes a way to perform Intrusion Detection with just the values in the registers of a device over a Modbus communication protocol. The proposed method of performing Intrusion Detection is by introducing an Embedding Layer into an otherwise simple neural network. Three neural networks were designed for the experiment and trained for both a binary classification of whether an attack occurred or not, and a multi-class classification of different types of attacks. The models performed better than the results previously reported without the use of Embedding Layers. This paper shows that a neural network with an Embedding Layer can effectively be used to model not only whether an attack occurred on a device, but also the class of attack that occurred.