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Abstract Ventricular arrhythmias after myocardial infarction (MI) originate from discrete areas within the MI border zone (BZ), identified during functional electrophysiology tests. Accurate sampling of arrhythmogenic sites for ex-vivo study remains challenging, yet is critical to identify their tissue, cellular and molecular signature. In this study, we developed, validated, and applied a targeted sampling methodology based on individualized 3D prints of the human-sized pig heart. To this end, 3D anatomical models of the left ventricle were created from magnetic resonance imaging and fused with biplane fluoroscopy. Regions of interest for sampling were annotated on the anatomical models, from which we created a unique 3D printed cast with custom slits identifying the annotated regions for sampling. The methodology was validated by retrieving ablation lesions created at predefined locations on the anatomical model. We applied the methodology to sample arrhythmia-vulnerable regions after MI during adrenergic stimulation. A pipeline of imaging was developed to create a 3D high-resolution map of each sample, highlighting the complex interplay of cellular organization, and altered innervation in the BZ.

An effective solar forecasting is an important part of managing and enhancing the effectiveness of solar power systems. The purpose of this paper is to develop a distinct and smart energy prediction system for solar PV systems. An efficient Solar Synergistic Adversarial Energy Forecasting System (Solar-SAFS) has been developed, which greatly enhances the precision and reliability of solar power predictions. It combines various deep learning methods including Graph Convolutional Networks (GCNs), Variational Autoencoders (VAEs), Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to effectively understand spatial and time-related patterns in solar data. The strength and accuracy of this model are increased by using adversarial training, which makes sure it gives reliable predictions in different situations. For making the hyper parameters better and to increase model's effectiveness and efficiency, we are using Grey-Oystercatcher Hybrid Optimization (GOHO) technique. The Solar-SAFS is validated and tested with different data sets including Fingrid and DSK solar. It shows that this method gives better results compared to current deep learning models. Our findings suggest that Solar-SAFS improves the accuracy and stability of solar energy prediction by a large margin, offering an advanced solution for managing renewable energy resources. Moreover, it significantly helps to obtain better predictions for solar energy production, which is a crucial need in this sector. It also encourages more efficient and dependable forecasting methods for renewable energy sources like sunlight. Compared to existing deep learning models, the Solar-SAFS demonstrates significantly lower error rates across multiple performance metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Bias Error (MBE).

This research work reports the influence of 3-μm-sized Palm Sprout Shell Ash (PSSA) reinforcement on the mechanical and tribological behavior of the Al-Cu-Mg alloy. Composites of varying weight percentages of reinforcement ranging from 1 to 6 at intervals of 1 Wt.% were produced using the ultrasonic-assisted bottom-poured stir casting technique. Microstructural studies, mechanical testing, and wear properties analysis were performed on the alloy and the synthesized composites. The microstructure of the obtained samples was examined using Scanning Electron Microscope, Energy Dispersive Spectroscopy (SEM/EDS), and XRay Diffraction (XRD). The XRD patterns provided confirmation of the presence of PSSA (SiO2 and Al2O3) particles. The addition of PSSA reinforcement has significantly improved the hardness, tensile strength, and compression strength of composites. The hardness, ultimate tensile strength, and compression strength were improved by 13.89%, 24.04%, and 32.93%, respectively, with the 6 Wt.% PSSA-reinforced composite. However, the incorporation of reinforcement has resulted in a decrease in the ductility of the Al-Cu-Mg alloy composite; the maximum decrement of 42.87% was with the 6% PSSA-reinforced composite. Tests were conducted at different loads and speeds to evaluate the wear behavior of the prepared samples. Superior wear resistance was observed in the composites. The fracture and wear mechanisms of reinforced and unreinforced were observed using SEM.

Crop yield estimation has gained importance due to its vital significance for policymakers and decision-makers in enacting schemes, ensuring food security, and assessing crop insurance losses due to biotic and abiotic stress. This research focused on rice yield estimation at the field level in the Karimnagar district of Telangana during 2021 and 2022 by employing the leaf area index (LAI) as the primary criterion for integrating remote sensing technology and crop simulation models. Using Sentinel-2 satellite data, the rice crop was mapped with the help of ground data and machine learning algorithms, attaining an accuracy of 93.04%. Crop management data for the DSSAT tool were collected during the field visits; the model results revealed a 0.80 correlation between observed and predicted yields. Due to its strong correlation with LAI (0.82), the normalized difference vegetation index (NDVI) was selected as the critical element for integration with the model. A spatial LAI map was generated using the linear equation developed between the NDVI and LAI. The relationship between LAI and yield was used to create a spatial yield map. The study’s findings show that assimilating remote sensing data with crop models enhances the precision of rice yield prediction for insurance companies and policy- and decision-makers.

Abstract Aluminium MMCs are among the many metal composites and are regarded as progressive engineering materials in numerous industries because of their advantages compared to standard aluminium alloy. Among the reinforcements in MMCs, ceramic particles are preferred for their superior wear resistance, temperature resistance, and adhesion to their matrix, making them a popular choice. This research work has been carried out to synthesise ceramic particle-reinforced aluminium metal matrix composites and to evaluate their tribological properties at different temperatures (50–300℃). Al2618 alloy was selected as the matrix, and boron carbide (B4C) and graphite (Gr) were selected as reinforcements. Hybrid composites are prepared through stir casting by varying the wt.% of B4C and Gr reinforcement particles with a ratio of 3:2. Microstructural observation shows the uniform distribution of B4C and Gr particles throughout the matrix without any agglomeration, and it also exhibits excellent scanning electron microscope (SEM). X-ray diffraction analysis (XRD) was performed to verify the presence of different constituents in the developed material. Samples S4 (Al 2618 + 12 wt.% B4C—8 wt.% Gr) and S5 (Al 2618 + 15 wt.% B4C—10 wt.% Gr) exhibit enhanced wear resistance (16.45%) due to the incorporation of a higher quantity of Gr solid lubricants alongside B4C within the temperature range of 50 to 300℃. The thickness and stability of the glazed layer exhibited adequate resistance to wear.

The research for novel power conversion topologies and the development of cutting-edge power component technologies are driven by the demand for renewable and much more efficient electricity generation, delivery, and conversion. Simulation and Analysis High Voltage Gain DC-DC Converter with Double Voltage Booster Switched Inductor for PV Applications are analyzed in this paper. Multilevel boost converter topologies recently reintroduced, are gaining popularity as a solution for industrial and transportation power systems because they enable the use of innovative, efficient, but relatively low voltage low-voltage devices at greater voltage and power levels. there is only one power switch on the converter that is planned here, three diodes, two capacitors, and two inductors to achieve ultra-high gain with better efficiency. High voltage gain, minimal switch stress, and the ability to lessen input-current ripple and capacitor voltage ripple are all benefits of the topology. When it switches complementary, the capacitors' ripple is reduced, which lowers the size requirement for the capacitors. A 12V, 500 watts prototype was analyzed, simulated and designed. at a duty cycle of 0.75 it is achieved high DC-DC gain i.e 19 and efficiency 93%. The practicality of the converter will be demonstrated by the close agreement between the analysis and simulation findings.

The axial loads of high-speed rotating turbo machines are supported by self-acting hydrodynamic components known as air foil thrust bearings (AFTB). The load bearing capability of these bearings depends primarily on the foil structure and secondarily on the operating conditions. The present review enlightens on the tribological performance parameters of the said bearing in enhancing the load carrying capacity. Various design and fabrication methods including theoretical models are briefly summarised and comparisons of experimental results are presented in order to reveal the possible research gap that leads in optimising the gas lubricated foil thrust bearings (GFTB) for their better employment in typical applications.

The design of the heating system is critical in achieving optimal thermal efficiency. Solid Works, a well-known design software, was used to meticulously create heat sink fins in both rectangular and square designs. The company’s choice strikes a good balance between practical manufacture and outstanding heat dissipation. When the design was complete, a modification process was performed to boost their efficiency. The heat fins were coated with a thin layer of SiO2 thermal coating that was precisely 0.25 mm thick. Heat is effectively transferred away from the electronic components because to the remarkable thermal properties of this silicon dioxide layer. Aluminum alloy (Al-alloy) and copper alloy (Cu-alloy). The thermal characteristics of the two materials vary. It is anticipated that performance would change upon merging with the SiO2 layer, defining the conditions for a comparative analysis. ANSYS Workbench ® was used to analyze and objectively assess the performance of many heat sink designs that differed. The whole temperature distribution and heat flow of the settings two critical factors that determine the effectiveness heat management in thermal systems would be shown by this sophisticated instrument.

The study examines the thermal and structural properties of beams made of functionally graded materials (FGMs) using the Finite Element Analysis (FEA) method and Reddy’s beam theory. The distribution of material qualities in thickness and length directions is influenced by mechanical and thermal loads. We calculate the stress and deflection of FG beams with a uniform load distribution. Quantitative results demonstrating the effects of multiple factors are provided by the Fusion 360 software. These include the change from alumina (ceramic) to aluminum (metal), boundary conditions, volume fraction distribution, and geometric features.

The incorporation of AI has become a game-changer in the ever-changing world of digital marketing, opening up new possibilities for creativity and long-term viability. This theoretical study delves at the connections between sustainability, AI-enhanced content marketing, and the creation of environmentally conscious communication tactics. This research dives into the theory behind using AI to promote sustainable practices in content marketing strategies. This study takes a theoretical stance that sheds light on AI's capacity to optimize content production, distribution, and consumption in a way that is environmentally conscious. This article delves into the complexities of AI-driven personalization to find out how to make content that appeals to eco-conscious people while reducing our impact on the environment. Theoretically, the study also delves into what it would mean to use AI to constantly assess and adjust content strategy to conform to changing sustainability criteria. The study delves deeper into the ethical considerations of AI-powered content marketing, highlighting the need for responsible methods that promote honesty, openness, and ecological consciousness. Examining how AI may aid in the spread of eco-friendly messaging and encourage customers to be more environmentally conscious, this study takes a theoretical approach to navigating the junction of technology and sustainability. The theoretical underpinnings of environmentally conscious content production, the function of artificial intelligence in improving communication strategies for influence on the environment, and the possible ethical dilemmas and factors to be considered when combining AI with sustainability in content marketing are important subjects. With any luck, this study will provide the groundwork for a more ethical and environmentally friendly method of digital marketing by providing a thorough theoretical framework for AI-enhanced content marketing in the future.

This study explores the critical realm of Diabetic Foot Ulcers (DFUs) and proposes an innovative approach for early detection using Internet of Things (IoT) and Machine Learning (ML). A chronic metabolic condition with elevated blood glucose levels is called diabetes mellitus. A foot ulcer is an open wound that is typically located beneath the feet. It can be shallow and less severe, occurring just below the skin's surface, or it can be deep and expose the bones, tendons, and joints. However, diabetes patients may be able to avoid complications from diabetic foot ulcers if early prophylaxis is practiced. One of the complications that this condition is frequently linked to is diabetic foot ulcers. Focusing on Diabetes Mellitus, the chronic metabolic condition leading to DFUs, the study introduces a wearable shoe prototype equipped with temperature and pressure sensors. This IoT-enabled device facilitates daily foot evaluation at home, allowing for timely identification of early symptoms and severity monitoring. By integrating ML algorithms, the real-time ulcer detection system aims to prevent complications, reduce amputations, and enhance proactive diabetic care.

In the present day, technology, economics, and environmental sustainability have all combined to produce some very significant design problems for Gas-Insulated Substations (GIS). Substations that use gas-insulated switchgear must maximise their return on investment while dealing with these issues. This necessitates lowering total cost, enhancing reliability, maintaining operational flexibility, and regulating their operations environmental impact. Recently, the insulation failures of the Gas Insulated Busduct (GIB) have been observed due to several defects caused during the switching and manufacturing process, such as delamination, protrusion, depression, gap, etc. These defects make a significant impact on the surface of the insulator and hence deenergise the Gas Insulated busduct device, resulting in a huge economic loss. In this paper, the effect of a free particle is analysed on a disc type Functionally Graded Material (FGM) insulator for a single-phase GIB at Triple Junction. The developed electric stress is reduced by inserting metal inserts at the end of the enclosure. The new technique called doping of FGM materials with different permittivity values is spatially distributed with many filler materials to achieve uniform electrical field stress. The simulation is conducted at various voltages and for different gradings of FGM for the designed insulator. The results obtained are presented and analysed showing the effectiveness of the proposed insulator.

Use of bricks and their manufacturing process plays an important role in the construction sector. Despite its various methods of manufacturing, still large quantities of bricks are used in the building construction. Manufacturing of bricks consumes large quantities of natural resources, and it is energy intensive. Similarly, due to rapid industrialization large quantities of waste industrial byproducts are generated and causes handling and disposal challenges of these wastes. This review work attempts the possibilities and potential use of various types of waste industrial byproducts in fired and unfired bricks. This study also highlights the importance of waste and its usage guidelines in bricks manufacturing to enhance the strength and durability properties. To overcome the challenges associated with bricks manufacturing, firing is still considered as the most preferred method of making bricks. Use of industrial waste byproducts to the mix matrix of fire and unfired bricks will overcome the disposal challenges and reduce the depletion of natural resources. Since sustainability is a key factor that is considered when it comes to making bricks, innovative methods are needed to produce them using sustainable materials. The production and application of bricks and their usage guidelines are reviewed further in various aspects such as environment, social, economic, and technology to meet global standards and policies of the local government for sustainable development.

The increased demand for electricity, as well as the increasing energy density in urban areas, has necessitated the extension of the high voltage network all the way to the customer. Gas-insulated substations are the best solution to the problem described above and recently, the insulator failures of the Gas Insulated Busduct (GIB) have been observed due to several defects such as protrusion and depression. These defects make a significant impact on the surface of the insulator and hence de-energies the GIB device, resulting in a huge economic loss. In this paper, a Functionally Graded Material (FGM) insulator is designed for a single-phase GIB having protrusion and depression abnormalities for the study of electric stress at the Triple Junction and reduction of stress is done by inserting metal inserts. Simulation is carried with the designed insulator for various voltages and for different gradings of FGM.

Machining is the most significant process for any manufacturing company to improve the quality of the finished component. The objective of this article is to analyse the process performance of Hastelloy C-276 using PVD (Physical Vapour Deposition) coated, uncoated and alumina-based ceramic tool inserts of high grade quality. Turning process was performed on NC (Numerical Control) machine by varying RPM, feed rate and depth of cut based on the Taguchi L9 orthogonal array approach. In this study, crank wear, flank wear, nose wear, SR (Surface Roughness), MRR (Material Removal Rate), tool temperature and feed force are examined during machining of hardened material and simultaneously static structural analysis of the tool insert along with the tool holder was performed using ANSYS mechanical. This research investigation helps in determining appropriate parameters with varied coated inserts to make the process easier, efficient and economical.

The present article discusses the simulation and mathematical modelling of GTAW for various parameters of single and double V-groove butt joint welds. The chosen materials are EN 10025steel(grade S295) and D36 ship building steel, owing to their wide industrial applications and corrosion resistive nature. The simulation modelling was carried out at 90°, 60°, 45° and 30° groove angles for both similar and dissimilar base metals to predict the deformation, residual stress distribution, heat flux, and nodal temperature using ABAQUS software package. A subsequent mathematical model was developed using MATLAB tool to further predict the temperature distribution and total stress concentration at any localized nodal point. The model can be used to obtain optimal weld parameters such as weld, speed torch temperature, current and voltage. The obtained results were plotted to attain the clear conclusion over the results. The results under simulation showed 45° to be the most effective angle for both Single-V and Double-V grooved butt joints.

Biomass is one of the key components for bioenergy generation in recent epoch as traditional resources and depleting swiftly. Going through this fact, the present study aims to appraise the feasibility of Holy Thistle (HT) to produce energy and valuable organic chemicals through pyrolysis. The HT was pyrolyzed at four heating rates including, 10, 20, 30, and 40 °C min−1 to perform thermo kinetic modeling and estimate thermodynamics parameters to establish the pyrolysis reaction process. The pyrolysis process of HT illustrated about 85–88 % of thermal degradation achieved through three different stages from 30 to 800 °C. The major degradation stage was observed from 170 to 450 °C with 55% to 60 % product formation from mainly cellulose and hemicelluloses components. Moreover, the average activation energy and pre-exponential factors demonstrated to be 183–184 kJ mol−1 and 1010 min−1 to 1025 min−1, respectively. The pyrolytic products exhibited agreement to the cleaner production of bio-gas, char and bio-oil which is evident for the potential and productivity of the feed combination.

Solid anion exchange membrane (AEM) electrolytes are an essential commodity considering their importance as separators in alkaline polymer electrolyte fuel cells (APEFC). Mechanical and thermal stability are distinguished by polymer matrix characteristics, whereas anion exchange capacity, transport number, and conductivities are governed by the anionic group. The physico-chemical stability is regulated mostly by the polymer matrix and, to a lesser extent, the cationic head framework. The quaternary ammonium (QA), phosphonium, guanidinium, benzimidazolium, pyrrolidinium, and spirocyclic cation-based AEMs are widely studied in the literature. In addition, ion solvating blends, hybrids, and interpenetrating networks still hold prominence in terms of membrane stability. To realize and enhance the performance of an alkaline polymer electrolyte fuel cell (APEFC), it is also necessary to understand the transport processes for the hydroxyl (OH−) ion in anion exchange membranes. In the present review, the radiation grafting of the monomer and chemical modification to introduce cationic charges/moiety are emphasized. In follow-up, the recent advances in the synthesis of anion exchange membranes from poly(phenylene oxide) via chloromethylation and quaternization, and from aliphatic polymers such as poly(vinyl alcohol) and chitosan via direct quaternization are highlighted. Overall, this review concisely provides an in-depth analysis of recent advances in anion exchange membrane (AEM) and its viability in APEFC.

In this paper, the flow generated by the slow steady rotation of a permeable sphere with thin surface about its axis of symmetry in an incompressible couple stress fluid which is otherwise at rest is studied. Expressions for the velocity and couple stress tensor components are obtained in terms of modified Bessel functions and Gagenbauer’s polynomials. The couple experienced by the permeable sphere due to the internal and external flow is evaluated. The more is couple stress offered by the fluid (i.e. the lesser values of couple stress parameter), the more the fluid particles are thrown away from the sphere. It is noticed that the internal flow is similar to viscous flow and the couple acting on the sphere due to internal flow is zero. The problem differs from that of micro-polar fluids. Keywords: Permeable sphere, Couple stress fluid, Rotary flow, Modified Bessel functions, Gagenbauer functions

Lightweight composite materials have recently been recognized as appropriate materials have been adopted in many industrial applications because of their versatility. The present research recognizes the inclusion of ceramics such as Gr and B4C in manufacturing AMMCs through stir casting. Prepared composites were tested for hardness and wear behaviour. The tests’ findings revealed that the reinforced matrix was harder (60%) than the un-reinforced alloy because of the increased ceramic phase. The rising content of B4C and Gr particles led to continuous improvements in wear resistance. The microstructure and worn surface were observed through SEM (Scanning electron microscope) and revealed the formation of mechanically mixed layers of both B4C and Gr, which served as the effective insulation surface and protected the test sample surface from the steel disc. With the rise in the content of B4C and Gr, the weight loss declined, and significant wear resistance was achieved at 15 wt.% B4C and 10 wt.% Gr. A response surface analysis for the weight loss was carried out to obtain the optimal objective function. Artificial neural network methodology was adopted to identify the significance of the experimental results and the importance of the wear parameters. The error between the experimental and ANN results was found to be within 1%.

The present study investigates the entropy generation in magnetized-micropolar fluid flow in between two vertical concentric rotating cylinders of infinite length. The surface of the inner cylinder is heated while the surface of the outer cylinder is cooled. Internal heat generation is incorporated. The Eringen thermo-micropolar fluid model is used to simulate the micro-structural rheological flow characteristics in the annulus region. The flow is subjected to a constant, static, axial magnetic field. The surface of the inner cylinder is prescribed to be isothermal whereas the surface of the outer cylinder was exposed to convection cooling. The conservation equations are normalized and closed-form solutions are obtained for the velocity, microrotation, temperature, entropy generation number, Bejan number and total entropy generation rate. The effects of the relevant parameters are displayed graphically. It is observed that the external magnetic force enhances the entropy production rate and it is maximum in the proximity of the inner cylinder. This causes more wear and tear at the surface of the inner cylinder. Greater Hartmann number also elevates microrotation values in the entire annulus region. The study is relevant to optimization of chemical engineering processes, nuclear engineering cooling systems and propulsion systems utilizing non-Newtonian fluids and magnetohydrodynamics.

Resources play vital role in construction projects. The performance of construction industry depends chiefly on how best the resources are managed. Optimisation play pivotal role in resource management, but task is highly haphazard and chaotic under the influence of complexities and vastness. Management always looks for optimum utility of resources available with them. Hence, the project management has got important place especially in resource allocation and smooth functioning with allocated budget. To achieve these goals and to exercise enhance optimisation certain tools are used for resource allocation optimally. Present work illustrates resource optimisation exercises on two ongoing projects in Dubai, UAE. Resource demands of project A & B are individually levelled and observed cumulative requirement is 17475. In other option demands of projects A & B are aggregated and then together levelled, the necessary resource observed is 16490. Comparison of individually levelled and then combined option with aggregated and then levelled clearly indicates reduction in demand of resources by 5.65% in later option, which could be best considered for economy.

Multi dimensional data (multi frequency, incident angle and polarisation) measurements of σ0 provided better estimates of soil moisture over those derived from single. This particular paper explains a new methodology for soil moisture estimation with the use of multi angle and multi polarisation RISAT-1 data. The roughness component was derived by correlating root mean square height with the differences of cross polarisation and like polarisation backscatter values (σ HV - σ HH) and differences of low and high incidence backscatter values (σ HH high (θ) - σ HH Low). The derived roughness was inputted to the modified dubois model (MDM). The results show both the σ HV - σ HH & σ HH high (θ) - σ HH Low are sensitive to roughness. The derived soil moisture using the MDM model is shows reasonable correlation with ground soil moisture.

To assess the relative tectonic activity classes, five geomorphic indices such as stream-gradient index (SL), drainage basin asymmetry (Af), hypsometric integral (Hi), valley floor width – valley height ratio (Vf) and drainage basin shape (Bs) of ninety-four sub-basins of Valapattanam river basin have been analysed by applying the standard formulae. Relative tectonic activity classes (Iat) obtained by the average (S/n) of different classes of geomorphic indices have been classified into three groups. Group I shows high tectonic activity with values of S/n < 2; group II shows moderate tectonic activity with S/n > 2 to < 2.5; and group III shows low tectonic activity with values of S/n ≥ 2.5. Field evidences such as deep valleys, sudden changes in the river course and waterfalls at fault planes clearly agree with the values and classes of tectonic geomorphic indices.

Polyaniline- (PANI) praseodymium Oxide (Pr2O3) composites have been synthesized by in situ polymerization method with different weight percentages. The synthesized composites have been characterized by Fourier transform infrared spectroscopy, X-ray diffraction and scanning electron microscopy. The temperature dependent conductivity shows that the conductivity is due to the hopping of polarons and bipolarons. These composites show negative thermal coefficient (α) behavior as a function of temperature, which is characteristic behavior of semiconducting materials. Sensor studies have been carried out by two-probe method and found that the sensitivity increases with increase in % RH. It is noticed that stability increase is due to the presence of Pr2O3 in polyaniline up to 30 wt%. A fast recovery and response time along with high sensitivity make these composites suitable for humidity sensors.