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Eco-friendly and cost-effective biomass-derived materials have garnered significant attention for producing porous activated carbon with a high surface area, particularly for applications in supercapacitors. In this study, the stalks of Gossypium hirsutum L. flower were utilized to prepare activated carbon (AC), and thus act as a supercapacitor electrode material. Furthermore, carbon has undergone doping with nitrogen (N) and sulfur (S) atoms to enhance the surface properties of the activated carbons. Out of all the recently prepared materials based on activated carbon, the sulfur-doped activated carbon (S-doped AC) exhibits notable features, particularly in terms of high surface area properties. In 1 M Na2SO4 electrolyte, the S-doped AC electrode presents the specific capacitance of 424 F g− 1 at 1 A g− 1 with a remarkable rate capability of 64.8% at 5 A g− 1 of current density in an electrode electrochemical system. Furthermore, the capacitance retention of 95% after 5000 charge/discharge cycles at 5 A g− 1. The symmetric device composed of S-doped AC//S-doped AC material demonstrates a cell-specific capacitance of 153.6 F g− 1 at 1 A g− 1, along with impressive energy and power densities of 41.8 Wh kg− 1 and 700 W kg− 1, respectively, at 1 A g− 1. At 10 A g− 1, the symmetric device maintains energy and power densities of 7.7 Wh kg− 1 and 7000 W kg− 1, respectively. The device demonstrates cyclic stability, retaining 89% of its initial specific capacitance after undergoing 5000 charge/discharge cycles at 10 A g− 1. Therefore, activated carbon derived from the stalks of Gossypium hirsutum L. flowers emerges as a promising avenue for creating cost-effective, large-scale materials suitable for applications in energy storage devices. [ABSTRACT FROM AUTHOR]

In the recent years, Additive Manufacturing (AM) has become a very demanding process utilized by majority of the manufacturing industries due to its complex geometrical capabilities, high accuracy, minimal material usage and better build quality. Among the various types of AM methods, Direct Metal Laser Sintering (DMLS) is a feasible method with many applications and a lot of scope for research. This paper focuses on optimizing the important parameters of DMLS process for better build quality of AlSi10Mg Aluminium alloy. The parameters identified are laser power, hatch distance, scanning speed, and layer thickness. Grey–Taguchi multi response optimization method has been used. Experimental specimens were fabricated and tested. Micro-Vickers hardness and average surface roughness were studied. Experiments were analyzed to determine the best combination of parameters of the DMLS process. A detailed micro-structural study was conducted on the specimens. Also, crystallographic study was made. The resultant specimen thus produced had a better build quality along with satisfying micro-structural characteristics. [ABSTRACT FROM AUTHOR]

The present work investigates the structural and luminescence behaviour of Dy3+‐Sm3+ co‐doped glass ceramics obtained through heat treatment of precursor glasses. The growth of SiO2 polycrystalline particles and evolution of these crystallites in the glass domain are witnessed via XRD and FESEM study. The presence of network vibrational bands, hydroxyl groups and the increased quantity of bridging oxygens (BOs) in glass ceramics are analysed through FTIR spectroscopy study. The absorption study (UV–Visible–NIR) showed the possible electronic transitions of Dy3+ and Sm3+ ions. The red shift in the absorption band edges and the lower bandgap values are obtained as a result of improved heat treatment in glass ceramics. Emission studies show the enhanced luminescence intensity of glass ceramics under 350 and 402 nm excitations. Decay measurement of glass ceramics showed the improved lifetimes of Dy3+ and Sm3+ ions to have appeared in microseconds (×10−6 s). The colour characteristics of glass ceramics analysed using CIE colour chromaticity diagram and correlated colour temperature (CCT) values suggest the neutral to cool white light emissions. Therefore, prepared glass ceramics with SiO2 polycrystalline phase are considered to be suitable materials in cool white LEDs applications. [ABSTRACT FROM AUTHOR]

Utilizing a single-step hydrothermal method, we prepared both pure ZnMoO4 and ZnMoO4/g-C3N4 composite, showcasing distinctive electronic and structural features that render it promising for environmental and energy remediation applications. XRD analysis confirmed the successful formation of ZnMoO4/g-C3N4 composites. The FESEM image of g-C3N4 displayed stacked flat sheets with noticeable wrinkles, showcasing its two-dimensional structure and irregular pores, enhancing its unique characteristics. Pure ZnMoO4 exhibited self-growth into hexagonal plate structures, with additional decoration of g-C3N4 sheets on its surface. UV–Vis absorption spectra analysis confirmed the interlayer structure of g-C3N4 and ZnMoO4 in the heterojunction, leading to a considerable increase in UV absorption and enhanced charge-separation efficiency within the binary ZnMoO4/g-C3N4 heterostructure. The photocatalytic activity of the synthesized ZnMoO4 and ZnMoO4/g-C3N4 nanocomposites was evaluated through the degradation of methylene blue (MB) dye under UV light irradiation. The results indicated that ZnMoO4 surface decorated with g-C3N4 sheets significantly influenced photocatalysis. Moreover, an increase in the nanocomposite composition led to enhanced efficiency in the photocatalytic process, with the incorporation of carbon nitride on zinc molybdates resulting in a threefold increase in photocatalytic activity. [ABSTRACT FROM AUTHOR]

The association of quantum Griffiths singularity (QGS) to the magnetic-field-induced superconductor-metal transition predicts the unconventional diverging behaviour of dynamical critical exponent in low disorder crystalline two-dimensional superconductors. But whether this state exists in the superconducting systems exhibiting superconductor-insulator transition remains elusive. Here, we report the emergence of quantum Griffiths singularity in ultrathin disordered TiN thin films with more than two orders of magnitude variation in their normal state resistance. For both superconductor-metal transition and superconductor-insulator transition types, a diverging critical exponent is observed while approaching the quantum phase transition. Further, the magnetoresistance isotherms obey a direct activated scaling governed by an infinite-randomness fixed critical point. Finally, this work establishes the robustness of the QGS phenomenon towards a wide range of temperature and also towards a wide range of disorder strength as correlated with the normal state resistance.The quantum Griffiths singularity (QGS) emerges due to the formation of disorder-mediated superconducting puddles, embedded in metallic or insulating states background. Here, the authors demonstrate the existence of QGS in disordered TiN thin films by divergence of dynamical critical exponent, while approaching the quantum phase transition at T → 0. [ABSTRACT FROM AUTHOR]

A smart grid is a network that utilizes a digital network to monitor the passage of electricity from one node to another within the network. Some of the applications of the smart grid are dynamic control of voltage, substation automation, outage management, and so on. The smart grid become an important topic since the inclusion of digital systems to monitor the electricity flow enhances usage and at the same time, it is affected by malicious attacks. Hence, it is necessary to protect the smart grid from attackers so that the authenticated user gets all the benefits without any scarcity. For this, many approaches have proposed by the researchers and have shortcomings of less accuracy in classifying the normal and abnormal flow, computational complexities, and less throughput. In context with these problems, we proposed a Convolutional Neural Network (CNN) based African Vulture Optimization Algorithm (AVOA) for the enhancement of cybersecurity in the blockchain-based Smart grid. To offer a novel way for improving smart grid security and defect detection in the industry by utilising block chain technology with deep learning architectures. The smart grid network's security performance can be improved by the use of a blockchain-based smart grid node based network module. In addition, the simulation results are carried out utilising a hybrid framework to monitor the attacks in the network. The data from the switches and PMU wascollected in the physical layer of the system. Then a blockchain controller controls the data. This also monitors the transaction details in the smart grids. The data are pre-processed with the aid of a Label encoder, and MIN–MAX scaling approaches. Then the features are extracted by using the CNN and the classification data is also performed by the CNN; however, the conventional CNN lacks scalability, and to enhance the scalability we utilize the AVO algorithm. The AVO algorithm effectively improves the scalability and thus our proposed classifies the normal and abnormal data from the smart grid. For the experimental purpose, we have taken the UNSW_NB15 dataset and compared it with the state of artworks in terms of different parameters. From the analysis, it is observed that the proposed method enhances the cybersecurity level by enhancing the throughput, accuracy (97.40%), F1-score (99.17%), precision (98.25%), recall (98.37%)computational time (1.34 ms) and detection rate (97.3%). [ABSTRACT FROM AUTHOR]

The current research work presents the synthesis and characterization of graphene-reinforced bimodal (Bi) AA7075 matrix composite by powder metallurgy route. The bimodal AA7075 alloy is optimized with micro (µ)- and nano (n)-crystalline grain morphologies in order to achieve better strength while retaining the vital minimal ductility. The effect of milling duration on grain size and particle uniformity is characterized by XRD and TEM. Density, hardness, compressive strength, and wear rate of bimodal composites are investigated. The addition of optimized 20% µAA7075 particles to nAA7075 particles provides the minimum necessary ductility in bimodal composites while increasing the interplanar space between the phase lattices. The use of graphene up to 0.75% enhanced wear resistance in comparison with the other compositions. The existence of both adhesive mechanisms and abrasive wear further reveals the plasticity of the bimodal composites, which are ideally suitable for engineering applications requiring greater strength and reliability. [ABSTRACT FROM AUTHOR]

The primary objective of this manuscript is to verify the LBB criterion, by carrying out fatigue crack growth (FCG) and fracture tests on SA 312 Type 304LN stainless steel pipes having a part-through crack in the circumferential direction. FCG tests were carried out on pipe specimens under constant amplitude loading in bending till the crack became through-wall and further reached 1/8th of the circumference of the pipe. During the FCG tests, beach marks were introduced by changing the minimum load of the cycle, keeping the maximum load as constant for clear identification of marks on the fracture surface. Subsequent to FCG tests, fracture tests were carried out on the through-wall cracked pipes under displacement control. During the fracture tests, load, load-line displacement, deflection of the pipe at critical locations, Crack Mouth Opening displacement (CMOD), surface crack length (circumferential) and angular rotation of the pipe with respect to the supports were monitored. Stress intensity factor (SIF) was determined by using API Code, RCC-MR and R6 approaches. SIF range and number of cycles predicted using the three analytical approaches are found to be very close to each other with a variation of ± 10% and hence any of the approaches can be used for the prediction of SIF range. Results of the study are helpful in LBB justification and for ensuring the structural integrity of piping components used in the nuclear industry. [ABSTRACT FROM AUTHOR]

The influence of AA7075 grain refinement, graphene reinforcement and SiC addition on the mechanical and tribological properties of hybrid composites is examined in the current work. The composites are synthesized using the powder metallurgy technique and reinforced with different mass fractions of graphene in micro, nano, bimodal and hybrid structures. XRD is used to study the structural behaviour of a phase lattice arrangement with grains of different sizes and TEM is used to characterize the dispersion of the constituents in the composites. Properties notably density, hardness, compressive strength and wear have all been investigated. The density of the composite increased with a finer nAA7075 matrix, and the addition of SiC further enhanced the density of the hybrid composite, despite the fact that the density of the composite reduced as more graphene was added. The hybrid composite provided better hardness and compressive strength, and the properties progressively started to improve with the inclusion of graphene particles. The SiC particles of hybrid composite prevent the surface material from deteriorating, reducing adhesive wear and delamination. [ABSTRACT FROM AUTHOR]

Ficus benghalensis is remarkable tree native to India. It is commonly known as banyan tree. It contributes to business, religious and medicinal purposes. The classical literature of Siddha system of Indian medicine depicts the use of ashes of its leaves especially yellow matured leaves to heal the various ailments like skin diseases, chronic diseases etc. The ash obtained from matured yellow leaves of Ficus benghalensis mixed with sesame oil is used in the treatment of skin disorders as per Siddha system of Indian medicine. Hence an attempt was made to analyse the ash of Ficus benghalensis in both yellow matured as well as green leaves for exploring the mineral constituents through instrumental characterization such as scanning electron microscopy energy dispersive spectrometery, X-ray fluorescence spectrometery, powder X-ray diffractometery and inductively coupled plasma-optical emission spectroscopy. In this study, the presence of various elements such as calcium and potassium as major elements, magnesium, sodium, iron, boron, zinc and copper as minor elements were detected in the ash of leaves of Ficus benghalensis. Ashes of both green and yellow leaves of Ficus benghalensis have minor variations in the contents of mineral composition. [ABSTRACT FROM AUTHOR]

The coronavirus diseases (COVID-19) are transmittable diseases which are caused by Severe Acute Respiratory Syndrome human coronavirus (SARS-CoV). This paper describes the identification of coronavirus disease infections and better treatments based on recent technology. The categorization and projection of COVID-19 from the dataset of the most significant Computed tomography (CT) image features. The CT image databases are collected from the online access Kaggle database. The features are extracted by the CT images with the Gray-Level Co-occurrence Matrix (GLCM) feature extraction techniques. The selected features are then segmented using the Improved Whale Optimization and Moth Flame Optimization (IWOMFO) algorithm. Improved Whale Optimization and Moth Flame Optimization (IWOMFO) algorithm are utilized to calculate the feature selection for image segmentation, which increases the objective function. Accuracy, F1-score, sensitivity, and precision are the various parameters utilized for evaluating performance. The segmented features were classified using Black widow optimization with a faster recurrent neural network (BWOFRCNN) method. The proposed BWOFRCNN classifier achieves a maximum accuracy of about 98.78%, a sensitivity of about 97.58%, and a precision of about 96.95% when compared to other methods. [ABSTRACT FROM AUTHOR]

Background: In-office three-dimensional (3D) printers and metal sleeveless surgical guides are becoming a major trend recently. However, metal sleeve-free designs are reported to be more prone to distortion which might lead to variation in the inner diameter of the drill hole and cause deviation and inaccuracy in the placement of the implant. Carbon fiber nanoparticles are reported to improve the properties of 3D printing resin material in industrial application. Aim: The purpose of the study is to evaluate and compare the wear resistance of 3D-printed implant guides with metal sleeve, sleeve-free, and reinforced sleeve-free resin to the guide drill. Materials and Methods: A total of 66 samples with 22 samples in each group. Three groups including 3D-printed surgical guide with metal sleeve (Group A), without metal sleeve (Group B), an carbon fiber reinforced without metal sleeve (Group C) were included in the study. All samples were evaluated before sequential drilling and after sequential drilling using Vision Measuring Machine. The data were tabulated and statistically evaluated. Results: The data obtained were statistically analyzed with one-way analysis of variance and post hoc test. The data obtained for wear observed in the samples showed that the wear was highest in Group B with a mean of 0.5036 ± 0.1118 and the least was observed in Group A with a mean of 0.0228 ± 0.0154 and Group C was almost similar to Group A with mean of 0.0710 ± 0.0381. The results showed there was a significant difference between Group B with Group A and C, respectively (P < 0.05). The results showed that there was no significant difference regarding the wear observed between Groups A and C (P > 0.05). Conclusion: The wear observed in the guide with a metal sleeve and carbon fiber reinforced without a metal sleeve was almost similar. The carbon fiber-reinforced guide showed better tolerance to guide drill equivalent to metal sleeve. Thus, carbon fiber nanoparticles reinforced in 3D printing resin have shown improved strength and can be used as a good replacement for a metal sleeve for an accurate placement of the implant. [ABSTRACT FROM AUTHOR]

The formation of sheet metal products is now widely utilized for multi-purposes in the automotive, aerospace and in industrial sectors. In this study, the phenomenon of plastic strain, von Mises stress, shear train by the V-bending method and to analyze the results theoretically, by using a special program called ANSYS. The multi-layer sheet metal in the rectangular plate of Al and Cu with three different thicknesses (1.0, 1.25, and 1.5 mm) is carried out by the Explicit solver. These parameters have been investigated such as effect sheet setting condition (Al/Cu/Al and Cu/Al/Cu), sheet thickness, and traveling of punch. In the explicit analysis, the position of Al/Cu/Al achieved maximum plastic strain in maximum thickness and punch travel is improved to save computation duration at cost of solution accuracy. Also, maximum shear stress obtained in larger punch travel in position Al/Cu/Al than Cu/Al/Cu. As the thickness is increased, the shear stress and von Mises stress becomes increases in Al/Cu/Al, and position of Cu/Al/Cu produced decreasing shear stress and von Mises stress in increasing sheet thickness with different punch travel. [ABSTRACT FROM AUTHOR]

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Structural walls are subjected to axial load with bi-axial bending. Despite this, structural walls are designed considering the demand along the strong axis. However, to minimize damage to structural wall it is necessary to design structural walls considering P–Mx–My interaction. Currently, IS 456:2000 recommends design P–Mx–My interaction for columns using a non-dimensional parameter ( α n ). In theory, the recommended α n are meant for symmetric column sections with uniform distribution of longitudinal reinforcement. Consequently, it is necessary to verify the applicability of the design P–Mx–My interaction equation for structural walls. Furthermore, the α n values recommended in the design code are shown to underestimate the flexural capacity of columns, particularly at lower axial load ratios (i.e., Pu/Puz; where Pu is the axial load demand and Puz is the maximum compressive load capacity of the column). To address these issues, the paper recommends design α n values for rectangular RC structural walls. Additionally, the paper presents simplified design equations to develop bi-axial interaction for structural walls. The simplified equations present in this paper are developed using regression analyses of rectangular structural walls with: (a) aspect ratios ranging between 4 and 25, (b) longitudinal reinforcement ratios from 0.5% to 1.5%, (c) reinforcement grades of 415 and 500 MPa, and (d) grade of concrete between M20 and M55. The proposed bi-axial interaction for structural walls will help designers to assess the adequacy of wall with relative ease. [ABSTRACT FROM AUTHOR]

The interaction between superconductivity and spin-polarized surface states of topological materials provides an exciting platform for the research and development of proximity induced coupling effects, Majorana fermions, spin valves, spintronics, etc. and so on. In this work, the inverse proximity effect observed exactly at the super conducting transition temperature of indium (3.5 K) demonstrates the complex interplay between robust 2D spin-polarized surface states observed in our (002n) oriented MoTe2 nanolayer sheets with that of superconducting states. Interestingly, our phenomenological model based on the Werthamer-Helfand-Hohenberg (WHH) model and Ginzburg–Landau formalism, invoked to validate the experimental observations, indicates a competition between superconductivity and topological order, marked by a close correspondence between the temperature of crossover (Tcr = 2.45 K) of their respective length scales, ξ and Lφ, and the saturation temperature in resistivity. [ABSTRACT FROM AUTHOR]

Superconducting topological materials have generated considerable interest in condensed matter research due to their unusual gap structures and topological properties. In this study, the normal and superconducting characteristics of a potential topological semimetal, 1T‐NbSeTe are investigated through comprehensive transport and magnetization measurements on bulk single crystals. The results suggest the topological semimetallic nature of NbSeTe, as evidenced by the observation of the planar Hall effect. Moreover, it displays quasi‐2D anisotropic superconductivity, which breaks the Pauli limit. The coexistence of the topological semimetallic nature and superconductivity of NbSeTe makes it a potential contender for topological superconductivity. [ABSTRACT FROM AUTHOR]

The current research was conducted during May-October, 2023 aimed to assess the haemato-biochemical parameters in cattle affected with S. aureus affected subclinical mastitis. Mastitis in dairy cattle is the persistent, inflammatory reaction of the udder tissue. Financial losses due to mastitis occur in the case of both sub-clinically and clinically affected animals. Subclinical mastitis exhibits no clinical signs and mostly remains unnoticed by the farmer and can be detected if specific tests are performed in milk samples. Sub-clinical mastitis has an erosive effect on the economy of dairy farmers as it effect directly on the milk quality and quantity. In India prevalence of sub-clinical mastitis was found to be more in cows when compared to clinical mastitis. Blood samples were collected from the jugular vein of 10 healthy and 10 subclinical mastitis affected cattle. Blood samples were analyzed for Hb, PCV, TEC, TLC, while serum samples were examined for ALT, AST, ALP, Glucose, Total protein, Albumin, Cholesterol and Calcium. Haematology report showed significantly (p<0.01) decrease in Hb, PCV and TEC in subclinical affected cattle when compared to healthy animals. TLC was significantly increased in (p<0.01) subclinical affected animal than healthy animal. Biochemical estimate revealed significantly (p<0.05) higher average values of AST, ALP and Ca in subclinical mastitis affected animals compared to healthy animals. Glucose, total protein, albumin, cholesterol and ALT levels are significantly (p<0.05) decrease in subclinical mastitis affected animals when compared to healthy cows. Haemato-biochemical parameters can be used as important for pathological state of subclinical mastitis animals. [ABSTRACT FROM AUTHOR]

The constant development and the wider usage of computed tomography (CT) has gained the attention of researchers during medical practice related to radiation dose. The intention to eradicate the dosage causes increased artefacts and noise influences the confidentiality of the radiologist. Specifically, various noises like speckle, pepper, impulse, salt and Gaussian noise are determined as the complex source of image noise. Therefore, the enhancements in image reconstruction from the CT image need to be enhanced with the diagnostic performance are a challenging issue related to ill-posed nature. Various CT prediction approaches have given superior outcomes. Moreover, there are fewer works in image denoising using learning approaches as these approaches pretend to reduce mean square error (MSE) among the denoised CT images. The outcomes of the models are compromising and show the visibility of aggressive denoising. This research focuses on modelling an efficient approach for CT image denoising with an adaptive adversarial network model that uses weighted similarity measure ( aa - WSM ). The anticipated model has the key concept of enhancing the performance and reducing the error rate. The proposed model concentrates on migrating the noise distribution and learning the visual perception knowledge to perform the denoising task. The PSNR of the proposed model is 16.6 and SSIM is 0.64 which is comparatively better than existing methods. The suppressed noise is 5.2, artefacts reduction is 3.6 and the overall quality is 3.8 which is nominal than others. The model handles the essential information and manages the error rate with promising outcomes. [ABSTRACT FROM AUTHOR]

This case report illustrates an integrated approach to prosthetic rehabilitation for a patient with missing lower front teeth. The utilization of intentional root canal treatment, precise tooth preparation, and digital technologies, including computer-assisted designing/computer-aided manufacturing, and direct metal laser sintering, showcases the advancements in contemporary prosthodontics. The incorporation of fixed and removable components, notably the Andrews bridge, demonstrates a patient-centered strategy prioritizing both esthetics and functionality. In alignment with evidence-based practices and past research, this case emphasizes the significance of multidisciplinary approaches and cutting-edge technologies. The successful outcome highlights the efficacy of this comprehensive treatment, contributing to the ongoing evolution of prosthodontic care. [ABSTRACT FROM AUTHOR]

Background and Objectives: Epidermal growth factor receptor (EGFR) mutation analysis has become an important part of the initial workup of non-squamous non-small cell lung cancer (NS-NSCLC) patients. This study is attempted as South Indians population is comprised of ethnic groups with diverse genetic makeup and only very limited data on EGFR mutation is available from south India. A detailed understanding of EGFR mutation profile will help in better planning of treatment strategies and resource allocation. Methods: A retrospective analysis of EGFR mutation frequency in 350 patients diagnosed with adenocarcinoma of lung and its association with pathological characteristics was done. Results: Out of 350 cases of pulmonary adenocarcinoma, within an age group ranging from 30 to 86 years. EGFR mutations were identified in 34.8% (n = 122) cases, out of which 35.24% (n = 43) were in non-smoker females (P = 0.001). Of the 14 cases with resistant type of EGFR mutations, nine were in smoker males and the remaining five in non-smoker females. Interpretation and Conclusion: Overall EGFR mutation frequency observed in our study was similar to other Indian studies. However, in our study, we observed that mutation in exon 21 was less frequent compared to other studies. A similar slightly increased frequency of rare mutations and double mutations were observed in our study. A detailed study of the molecular epidemiology of lung cancer and its association with different geographical zones of India is needed. This understanding will help in better planning of treatment strategies and resource allocation. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to access the awareness and knowledge of finding out errors in prescription among general public which include determination of the quality of prescription in hospital pharmacy and to address the errors identified in prescriptions. Implementation of teaching electronic medical record within didactic using drug info assignment. This survey emphasised the need for monitoring and evaluating the prescription handling conducted through google form. Therefore, the present study will help to understand the prescribing patterns and errors to the general community which will, in turn, improve the quality of the use of medicine and healthcare facilities. This following report has comprehensive studies that public have developed knowledge about prescription parts, drug information, selfevaluation, health care factors when compared to previous studies. [ABSTRACT FROM AUTHOR]

The advancement of Industrial Internet of Things (IIoT) applications has increased the demand for efficient and energy-aware task scheduling in fog-cloud environments. This paper presents a novel multi-objective energy efficient task scheduling based reinforcement learning (MEETS-RL) model for fog-cloud IIoT-based systems. The IIoT, fog, and cloud are the three layers obtained in the proposed method. Tasks are captured from various industries through industrial devices such as actuators, sensors, and control systems placed near fog nodes. The task classification stage utilizes the ID3 algorithm to classify tasks based on their priority, Quality of Service (QoS), and processing requirements. After classification, appropriate fog nodes are selected for task execution considering factors such as energy consumption, processing capabilities, and proximity to IIoT devices. The unhandled task in fog nodes is offloaded to cloud data centers using the first fit (FF) algorithm, based on available resources, QoS requirements, and fog node location. Once the suitable fog nodes or cloud data centers have been identified, the tasks are scheduled for execution using a reinforcement learning-based task scheduling algorithm. Experimental evaluations demonstrate that the proposed MEETS-RL model outperforms existing task scheduling models, including first come first serve (FCFS), greedy for energy (GfE), shortest job first (SJF), round Robin (RR), and Laxity based priority with Ant colony system (LBP-ACS). The experimental results of the proposed architecture showed an accuracy rate of 98.8%, task completion rate of 95% and energy consumption of 0.4 J. The proposed architecture offers a comprehensive solution for modern IIoT systems demanding flexibility, scalability, and efficient resource management while enhancing energy efficiency through the application of reinforcement learning in task scheduling. [ABSTRACT FROM AUTHOR]

Potassium dihydrogen phosphate (KDP) is an effective NLO substance. Much research has been concentrated on KDP crystals to increase the effectiveness of KDP's nonlinear optical property. The effectiveness of laser radiation conversion can be increased by altering its expansion. The excellent molecular chirality of organic acids is employed to improve the properties of KDP. Our main objective in this study was to describe the studies on the mechanical, thermal, surface, antibacterial, self-defocusing, and electro-optic properties of doped potassium dihydrogen phosphate solitary crystals for optical, electronic, and biological applications. The effect of itaconic acid (ITA) at concentrations ranging from 1, 3, and 5 mol% on the thermal, SEM, microhardness behaviors, NLO, antibacterial properties, and half-wave voltage of KDP (potassium dihydrogen phosphate) single crystals grown by the slow cooling technique. The existence of dopants was proved with energydispersive spectrometry. The mechanical properties of various temperatures for undoped and doped-KDP crystals with rising dopant combinations have been prepared, and the hardness was expanded due to doping. In contrast to several potentially dangerous microorganisms like Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli, the produced crystals were exposed to antibiotic activity. The superiority of the fully-fledged crystal is determined by the etching studies. Using the Z-scan method, the good third-order nonlinear response for different planes (2 0 0), (2 1 1), and (1 1 2) of the ITAdoped KDP crystal sample was determined. Half-wave voltage may be discovered in the crystal produced via electro-optic examination. The Z-scan analysis of pure and ITA-doped KDP crystals for different planes reveals good self-defocussing and NLO responses. The electro-optic experiment generated a significant and consistent half-wave voltage. The photoelastic behavior of KDP crystals with ITA as a variable birefringent compensator has been investigated. [ABSTRACT FROM AUTHOR]

In urban area vehicular adhoc network ascertaining appropriate channel for load balanced high data transferring, in dynamic network location is addressed by several industries and researchers using various routing algorithms. Particularly load balancing in traffic congestion and channel optimization in dynamic vehicular topology extends coverage and line-of-sight relay association issue and probability of hold-up link is high. For preventing problems instigated by traffic congestion and estimating optimistic channel for transferring high data rate without affecting network performances machine learning with orthogonal frequency division multiplexing and multi-input and multi-output (OFDM–MIMO) approach is incorporated for that takes care of load balancing and channel optimisation respectively in this paper for effective communication in vehicular network. Through miscellaneous simulations we implement Q-learning based load balancing routing (Q-LLBR) and OFDM–MIMO scheme is incorporated to achieve better performance in packet delivery ratio, latency, network utilization and signal to noise ratio are performed significantly to improve network performance in vehicular communications. [ABSTRACT FROM AUTHOR]

In service, the piping components (pipes/elbows) are subjected to different operational loadings such as thermal stress, internal pressure, self-weight, external loading from soil movement, flow induced vibration, vortex induced vibrations and third party damage. Structural integrity assessment of these piping components under postulated accidental conditions is essential for ensuring smooth operation of power plant piping system. In order to understand crack growth behaviour of piping components under operating conditions, fracture studies were carried out on two straight pipes and three elbows of 219 mm OD having circumferential through-wall notch with internal pressure. Fracture tests on pipes were carried out under four-point bending and elbows were tested under in-plane bending. A sealing arrangement consisting of stainless steel plate as backing material and silicon rubber sheet with two-component super strength epoxy based adhesive was used to seal the through-wall notch in the pipes and elbows. The pipe and elbows specimens were filled with water through threadolets and the desired internal pressure was achieved using an automatic high-pressure hydraulic pump. The internal pressure was varied from 10 to 25 MPa. The load carrying capacity of pipes decreased by a factor 1.95 with the increase of initial notch angle from 90.5° to 152.8° under an internal pressure of 10 MPa. In the case of elbows, with an increase of internal pressure from 10 to 25 MPa, load-line displacement corresponding to maximum load increased by 41.1%. Ovalization (intrados-extrados) in the elbows was found to be varying from 2.74% to 6.85% at the end of fracture tests. The pipe specimens have undergone initial stable crack growth followed by crack instability and crack growth deviated from the initial plane of the notch. The collapse load obtained for through-wall cracked elbows under internal pressure was found to be conservative compared to the values obtained using twice elastic slope method. [ABSTRACT FROM AUTHOR]

This research focuses on a comprehensive exploration of the experimental and mechanical aspects of the electrical discharge machining (EDM) process, specifically targeting the machining characteristics of AA2014/Si3N4/Mg/cenosphere hybrid composites. The aim is to optimize the process parameters for enhanced machining performance through a combination of testing, optimization, and modelling methodologies. The study examines the effects of key EDM variables—peak current, pulse on time, and pulse off time—on critical output responses: surface roughness (Ra), electrode wear rate (EWR), and material removal rate (MRR). Leveraging an L9 Taguchi orthogonal array experimental design, the impact of controllable factors on these responses is analysed. An integrated approach utilizing MATLAB's logic toolbox and Mamdani's technique is employed to model the EDM process, and a multiple-response performance index is calculated using fuzzy logic theory, enabling multiobjective optimizations. Furthermore, a mechanical behaviour evaluation of AA2014/Si3N4/Mg/cenosphere hybrid composites is performed through mechanical testing, with a comparison between experimental machining results and predicted values. Scanning electron microscopy (SEM) images reveal the presence of filler reinforcements within the base alloy, displaying an improved microstructure and uniform reinforcement dispersion. An X-ray diffraction (XRD) analysis confirms the major elemental constituents—aluminium, silicon, and magnesium—in the hybrid composites. A microstructural analysis of the hybrid metal matrix composites (MMCs) prepared for EDM showcases closely packed reinforcement structures, circular ash-coloured spots indicating silicon and nitrates, and a fine dispersion of cenosphere reinforcement particles. The study's outcomes demonstrate a promising application potential for these hybrid composites in various fields. [ABSTRACT FROM AUTHOR]

3-Nitrobenzaldehyde thiosemicarbazone demonstrates a versatile nature in forming coordination complexes with various metals. These complexes have garnered significant interest in fields such as coordination chemistry, medicinal chemistry, catalysis, and material science. The ligand's nitrogen and sulfur atoms serve as potential coordination sites, allowing for the formation of diverse complexes with different metals. These complexes exhibit bioactive properties in medicinal chemistry, serve as catalysts in catalytic processes, and contribute to the development of novel materials with tailored functionalities in material science. The exploration of 3-nitrobenzaldehyde thiosemicarbazone complexes with multiple metals offers promising avenues for research and application in various scientific disciplines. [ABSTRACT FROM AUTHOR]

The existing work reveals the novel character of organic compounds like 4-Methoxyphenoxyacetic acid and p-dihydroxybenzene. The compounds were investigated for their antibacterial and antifungal prospective against gram-positive bacteria. At increasing doses of 2- Methoxyphenoxyacetic acid, the zone of inhibition for Salmonella paratyphi was (30 mm/ml) at 100 µl and p-dihydroxybenzene is more resistant to bacterial such as Bacillus subtilis (38 mm/ml), Enterococcus faecalis (40 mm/ml), Mucor (42 mm/ml), Aspergillus niger (40 mm/ml). The docking investigation was carried out using Auto Dock 4.2.6; interactions between hydrogen atoms and the smallest ligands with macromolecules had the lowest binding energies. [ABSTRACT FROM AUTHOR]

The aim of this present study was to investigate and optimize the effect of adding brown rice husk ash (BRHA)–derived α-silicon nitride (Si3N4) and nickel-phosphorus (Ni–P) reinforcements onto the surface of austenitic AISI 316L bioimplantable stainless steel via electroless coating. This study brings the rationale about how the agricultural biomass-turned biomaterials serve as functional materials for recent advance engineering applications. α-Si3N4 was prepared via a carbothermal reduction and nitriding process from brown rice husk ash. Using the Taguchi L9 orthogonal array experimental setup and the grey relational approach, the α-Si3N4/Ni–P-toughened austenitic stainless steel composite coatings were prepared and optimized. According to the optimization results, the coating temperature was found to be the most controlling process parameter among other variables such as reinforcement ratio and immersion time. Similarly, the process variables such as immersion time of 500 min, coating temperature of 90 °C, and reinforcement ratio of 0.9 (A3B3C3) were found to be the new optimum process variables. Atomic force microscope (AFM) micrographs of coated surfaces confirm the uniform deposition of α-Si3N4, Ni and P at 70 and 90 °C. The additions of Si3N4 neatly reinforce into the crystal lattice of iron and offered high hardness and wear resistance than Ni–P. The grey relational grade value was improved from 0.879 to 0.896 for optimized process variables. The tensile strength of 911.12 MPa, surface hardness of 197.45 BHN, and specific wear rate of 0.00000491 mm3/Nm were observed from the optimized study, which was about 1.94% of improvement in comparison with the Taguchi model. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is likely to impact the daily activities of people in many ways; from small items to large manufacturing products, including all kinds of processes. A Wireless Sensor Network (WSN) forms part of the topology of the IoT and is the basis of numerous IoT appliances like surveillance, defence technology, remote monitoring, and others. It is advantageous to replace nodes having low power during data transmission in WSNs, especially when deploying such nodes in a secluded area in which energy utilization becomes the crucial factor. Existing solutions that addressed this issue focused on selecting the head node of a cluster based on remaining energy, node density, and network type. A novel fuzzy-based scheme is proposed in this article to group heterogeneous sensor nodes in different clusters and then select the cluster head with the aim of improving the lifetime of the underlying WSN. Besides, many factors, like the density of power-constrained nodes and the distance from a node to its associated base station, are also considered when picking the right cluster head. Simulation experimental outcomes have confirmed that our proposed novel clustering proposal can work effectively in WSNs and improve their lifetime to a certain extent. [ABSTRACT FROM AUTHOR]

This paper reports on the structural, optical and luminescence studies of Dy3+–Eu3+ co-doped glass ceramics that are obtained via thermal treatment method. The initial confirmation on glass ceramics with the formation of NaBSiO4 crystalline phase was made through XRD study. The FTIR study showed the vibrations of network formers (B2O3, SiO2) and other functional groups. The quantity of non-bridging oxygens (NBOs) are increased in the glass ceramics with increase in annealing temperature. The absorption spectra (UV–visible-NIR) showed the possible transitions of Dy3+ and Eu3+ ions in the glass ceramics. A red-shift in the absorption band-edge and reduction in the optical band gap values were obtained for glass ceramics owing to their heating temperatures. Photoluminescence studies showed the excitations of Dy3+ and Eu3+ ions under 575 nm and 613 nm emission wavelengths. The obtained NaBSiO4 crystalline phase in the glass ceramics has enhanced the luminescence intensity, and lifetimes of Dy3+ and Eu3+ ions compared to unheated precursor glass when excited under 350 nm and 393 nm. Color chromaticity diagram and correlated color temperature (CCT) values showed a shift in the color of light from warm white of precursor glass to neutral white of glass ceramics. The overall results justify the possibility of considering the Dy3+-Eu3+ co-doped glass ceramics as efficient materials for solid-state lighting applications like W-LEDs. [ABSTRACT FROM AUTHOR]

Spanness of fuzzy graph is introduced. By spanness, a new vulnerability parameter, span integrity is defined in fuzzy graph. The span integrity values are found for path, cycle, complete fuzzy graph, complete bipartite fuzzy graphs. Path and cycle with node strength sequence are discussed. Brain network is modeled as a fuzzy graph and Span integrity is applied to the brain network. Span integrity of fuzzy brain network is calculated for before and after meditation models. The results are compared and the improvement in the stability of the brain network is shown. [ABSTRACT FROM AUTHOR]

Aim: Antibiotics treat various diseases by targeting microorganisms by killing them or reducing their multiplication rate. New Delhi Metallo-beta-lactamase-1 (NDM-1) is produced by bacteria possessing the resistance gene blaNDM-1, the enzyme that makes bacteria resistant to beta-lactams. Bacteriophages, especially Lactococcus, have shown their ability to break down lactams. Hence, the current study computationally evaluated the binding potential of Lactococcus bacteriophages with NDM using Molecular docking and dynamics. Methods: Modelling of NDM I-TASSER for Main tail protein gp19 OS=Lactococcus phage LL-H or Lactobacillus delbrueckii subsp. lactis after downloading from UNIPROT ID- Q38344. Cluspro tool helps in Understanding cellular function and organization with protein-protein interactions. MD simulations(19) typically compute atom movements over time. Simulations were used to predict the ligand binding status in the physiological environment. Results: The best binding affinity score was found -1040.6 Kcal/mol compared to other docking scores. MD simulations show in RMSD values for target remains within 1.0 Angstrom, which is acceptable. The ligand-protein fit to receptor protein RMSD values of 2.752 fluctuates within 1.5 Angstrom after equilibration. Conclusions: Lactococcus bacteriophages showed a strong affinity to the NDM. Hence, this hypothesis, supported by evidence from a computational approach, will solve this life-threatening superbug problem. [ABSTRACT FROM AUTHOR]

The growing severity of the world’s energy issues has sparked a keen interest in cutting-edge photocatalytic materials for water splitting. Herein, outstanding performance photocatalysts for solar-powered hydrogen evolution employing NiTe2/g-C3N4 heterojunction thin films were produced. NiTe2 quantum dots of tunable size and dosage quantity may be grown hydrothermally on the surface of g-C3N4 nanosheets, thanks to the elaborate ion exchange. Photocatalyst with 5wt% 0D-2D NiTe2/g-C3N4. At 420 nm monochromatic light, NiTe2 demonstrated an H2 evolution rate of 3155 mol h−1 g−1, with an apparent quantum yield of 9.8%, significantly higher than that of bare NiTe2 photocatalyst. The huge surface area and generated heterojunction between NiTe2 and g-C3N4 nanosheets are responsible for the significant photocatalytic H2 generation activity of the 0D-2D NiTe2/g-C3N4 photocatalyst. Photoluminescence dampening experiments have shown that NiTe2/g-C3N4 photocatalyst significantly boosts the rate of photoinduced charge transfer, which is essential for efficient photocatalytic H2 generation. This research presents a novel approach to improving the efficiency of g-C3N4-based photocatalysts for H2 generation by facilitating the separation and transfer of charges through photoexcitation. [ABSTRACT FROM AUTHOR]