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The objective of this work is to investigate the rate of entropy generation of a hybrid nanoliquid (Cu-Ag/Water) flowing on a stretching sheet in the presence of convective boundary conditions, heat generation/absorption, double stratification and Stefan blowing. At present, the capability of interchange of thermal energy is not concerned only with an estimation of the amplification in the rate of heat exchange but also depends on profitable and obliging contemplation. Acknowledging the demands, researchers have been associated with the refinement of the performance of a heat exchange, which is referred to as an intensification of the interchange of heat.

By using a similarity transformation, the system of governing partial differential equations (PDEs) is transformed into the system of nonlinear ordinary differential equations (ODEs). The rebuilt ordinary differential equations are then solved by applying the homotopy analysis method. After computing the temperature, concentration and velocity profiles for a range of relevant study parameters, the resulting results are examined and discussed.

Elevating the Stefan blowing parameter values enhances the temperature profile. Conversely, it diminishes with increasing concentration stratification, thermal stratification and heat generation/absorption coefficient. The rate of entropy generation rises with increasing diffusion parameter, Brinkman number and concentration difference parameter. Stronger viscous forces between the sheet and the fluid flow cause skin friction to increase as fw and Sϕ increase. The local Nusselt number falls as fw and ω rise. However, as Sθ rises, the local Nusselt number gets higher.

The transmission of mass and heat is the basis of the current study, which is useful in a number of industrial and technological domains.

The paper investigates entropy production and heat transmission in a hybrid nanoliquid flow over a stretching sheet, incorporating factors such as heat generation/absorption, convective boundary conditions, Stefan blowing and double stratification. The research highlights a gap in the existing literature, indicating that this specific combination of factors has not been previously explored.

Grey relational analysis (GRA) has already proved itself as an efficient tool for multi-objective optimization of many of the machining processes. In GRA, the distinguishing coefficient (ξ) plays an important role in identifying the optimal parametric combinations of the machining processes and almost all the past researchers have considered its value as 0.5. In this paper, based on past experimental data, the application of GRA is extended to dynamic GRA (DGRA) to optimize two electrochemical machining (ECM) processes.

Instead of a static distinguishing coefficient, this paper considers dynamic distinguishing coefficient for each of the responses for both the ECM processes under consideration. Based on these coefficients, the application of DGRA leads to determination of the dynamic grey relational grade (DGRG) and grey relational standard deviation (GRSD), helping in initial ranking of the alternative experimental trials. Considering the ranks obtained by DGRG and GRSD, a composite rank in terms of rank product score is obtained, aiding in final rankings of the experimental trials for both the ECM processes.

In the first example, the maximum material removal rate (MRR) would be obtained at an optimal combination of ECM parameters as electrolyte concentration = 2 mol/l, voltage = 16V and current = 4A, while another parametric intermix as electrolyte concentration = 2 mol/l, voltage = 14V and current = 2A would result in minimum radial overcut and delamination. For the second example, an optimal combination of ECM parameters as electrode temperature = 30°C, voltage = 12V, duty cycle = 90% and electrolyte concentration = 15 g/l would simultaneously maximize MRR and minimize surface roughness and conicity.

In this paper, two ECM operations are optimized using a newly developed but yet to be popular multi-objective optimization tool in the form of the DGRA technique. For both the examples, the derived rankings of the ECM experiments exactly match with those obtained by the past researchers. Thus, DGRA can be effectively adopted to solve parametric optimization problems in any of the machining processes.

This paper aims to produce sustainable sport-hijab or veiling using cotton and bamboo as renewable and eco-material blending with polyester. Due to the unique characteristics of the knitting fabrics, the research focused on constructing the proposed samples using a circular knitting technique with a French terry structure, to achieve comfort, ease of care, good appearance and sustainability in different climatic conditions.

The researchers formed three different knitted samples using yarn count 30/1Ne for cotton and bamboo and 70 dens for polyester yarn, using the same blending ratio of 50:50% (cotton/polyester, bamboo/ polyester and cotton/ bamboo). They tested several mechanical and physical properties (weight, thickness, air permeability, water permeability, electrostatic charges, ultraviolet protection factor, stiffness, pilling resistance and bursting strength).

Using different tools, the researchers statistically analyzed the influence of variables on sample properties, including a Chart line, ANOVA test at p-value = 0.05 and the least significant differences values to identify the effect significantly as well as demonstrate the interaction among the samples at each tested property. Finally, radar chart areas to clarify the preferable sample performance.

The findings declared that blending materials used significantly affected most properties of the produced samples, except for the water permeability and an electrostatic charge. Furthermore, the findings pointed out that blending (cotton or bamboo/polyester) is more efficient and desirable than blending (cotton/ bamboo). Additionally, based on radar charts analysis, the cotton/polyester knitted outperforms other blended materials samples in producing sport-hijab or veiling fabric.

Humans now enjoy a better life because of Artificial Intelligence (AI). AI has a significant impact on the creation of smart cities. Modern applications based on big data, Internet of Things (IoT) systems, and deep learning require extensive use of complex computational solutions. Thus, the following problems arise: (1) what are smart cities? (2) what is AI? (3) How is AI used in smart cities? To respond to this problem, the following objective was set: to map how AI is used in smart cities. For this purpose, a qualitative methodology based on a narrative analysis of the literature was used. It is concluded that AI and smart cities are complementary technologies that can assist cities in tackling difficult issues including public safety, transportation, energy management, environmental monitoring, and predictive maintenance. This chapter’s findings, while broadly applicable, offer valuable insights into the Gulf region’s unique context, where rapid urbanization and technological adoption intersect with cultural and environmental considerations. The integration of AI in smart cities presents a promising avenue for the Gulf region to address its specific challenges and leverage its economic and infrastructural strengths, thereby contributing to the broader goals of innovation, development, prosperity, and well-being as envisioned in the region’s Vision 2040 initiatives.

Non-performing assets (NPAs) are classified as loans and advances which are in default, either refund of principal or interest payments are not duly met. This not only leads to dishonour of loan agreement from the recipients' point of view but also huge NPAs result macroeconomic instability and economic crisis. The financial crisis may create hindrances towards achievement of sustainable development of an economy. Keeping NPA in balance sheet portrays lacunae in management of the lender. The non-recovery of interest and principal reduces the lender's operating cash flow, which upsets the budget and drops the earnings. Statutory provisions, set aside to cover probable losses, reduce the income further. When the non-recovery is determined to be definite in nature, they are written off against earnings of the lending institution. Thus, presence of NPAs in balance sheet gives a distress signal to the stakeholders of the lending institution. Under this consideration, the present study will look upon some of these issues related to NPA management in Indian banking sector. The main objective of this study is to discuss the nexus between the NPA of Indian scheduled banks for priority sector, non-priority sector and public sector and the gross domestic product (GDP) of Indian economy for the time period 2005–2020. To study this objective, the ratio analysis and the trend analysis of NPA of three sectors and GDP of Indian economy over the given time frame have been done. Finally, some policy prescriptions regarding achievement of sustainable development after taking into account NPA management of an economy have also been proposed.

One of the most innovative materials available today is polyester resin, which finds application in a wide range of industries, including consumer products, automotive, aircraft, marine, construction, sports and renewable energy, due to its impressive mechanical properties and low cost. In recent years, significant progress has been achieved in the development of polyester resin composites. This paper aims to provide an overview of the recent advances in the field of polyester resin composites.

The review introduces the properties of polyester resins and the fabrication techniques used to prepare polyester resin composites. It provides an overview of the reinforcement materials such as fibers and nanoparticles that are commonly used to enhance the properties of the composites. Recent advances in the use of fillers such as nanocellulose, graphene and carbon nanotubes are also discussed. This work highlights the latest developments in the functionalization of polyester resin composites, which aims to improve the properties of the composite materials for specific applications in diverse fields such as aerospace, biomedical and energy. It highlights how collaborations worldwide, business and academia are working together to advance polyester resin composite technologies.

The study emphasizes how urgent it is to adopt sustainable practices, which, in turn, is driving research into polyester resins that are recycled and biobased to create a circular economy. Constant advancements open up new possibilities for application development and improve performance, such as nanotechnology and smart materials. Furthermore, businesses are being revolutionized by sophisticated production processes like 3Dimensional printing and Internet of Things integration, which enable mass customization and real-time monitoring. These partnerships advance the sector and encourage the use of polyester resin composites in environmentally friendly applications. The remarkable mechanical, thermal and chemical capabilities of polyester resin composites are highlighted, showcasing their importance in a range of applications.

The study is a major step toward a sustainable tomorrow since it highlights the potential of polyester resin composites to build a more durable and environmentally friendly future. This review paper summarizes the recent advances in the development of polyester resin composites, highlighting their potential for advancing technologies in various fields. The knowledge gained from this review paper will undoubtedly aid researchers in designing novel polyester resin composite materials with tailored properties for specific applications.

This paper examines the transformation of York College Library’s services through automation before, during and after the COVID-19 pandemic. This paper aims to evaluate how automation tools such as Integrated Library Systems (ILS) and e-resource platforms facilitated the transition to remote services, while identifying challenges related to staff training, accessibility and digital engagement. By analyzing user feedback, operational data and automation trends, the study provides actionable insights for optimizing academic library services. The findings offer scalable recommendations to enhance service delivery, ensure inclusivity and strengthen the resilience of libraries in adapting to evolving educational demands in a post-pandemic landscape.

This study uses a mixed-methods approach to analyze York College Library’s automation trends across three phases: pre-pandemic, during the pandemic and post-pandemic. Quantitative data was collected through surveys and library usage statistics, measuring e-resource downloads and virtual reference inquiries. Qualitative insights were obtained via interviews with library staff and users, exploring challenges and the impact of automation systems on service delivery. The combined analysis provides a comprehensive understanding of the library’s transition to remote services, identifying key strengths and areas for improvement to inform future strategies for academic library operations.

This study revealed that York College Library’s pre-pandemic investment in automation tools, such as ILS and e-resource platforms, enabled a rapid shift to remote services during the COVID-19 pandemic. Virtual reference inquiries surged by 200%, and e-resource usage increased by 45%, demonstrating high user reliance on digital services. However, gaps in staff training and accessibility highlighted areas for improvement. Post-pandemic, the library adopted a hybrid model that blends physical and virtual services to meet diverse user needs. The findings underscore the importance of continuous professional development, robust digital infrastructure and accessibility-focused strategies to ensure resilient and inclusive library operations.

This paper provides a unique case study of York College Library’s transition to remote services during the COVID-19 pandemic, offering insights into how automation tools were leveraged to maintain academic support. It highlights the dual role of technology in enabling service continuity and exposing gaps in training and accessibility. By integrating user feedback, operational data and automation trends, the study offers actionable recommendations for libraries navigating post-pandemic challenges. Its focus on scalable solutions for hybrid service models, staff development and digital equity adds significant value to the evolving discourse on academic library automation and resilience in higher education.

This study aims to investigate numerically the impact of the three-dimensional convective nanoliquid flow on a rotating frame embedded in the non-Darcy porous medium in the presence of activation energy. The cross-diffusion effects, i.e. Soret and Dufour effects, and heat generation are included in the study. The convective heating condition is applied on the bounding surface.

The control model consisted of a system of partial differential equations (PDE) with boundary constraints. Using suitable similarity transformation, the PDE transformed into an ordinary differential equation and solved numerically by the Runge–Kutta–Fehlberg method. The obtained results of velocity, temperature and solute concentration characteristics plotted to show the impact of the pertinent parameters. The heat and mass transfer rate and skin friction are also calculated.

It is found that both Biot numbers enhance the heat and mass distribution inside the boundary layer region. The temperature increases by increasing the Dufour number, while concentration decreases by increasing the Dufour number. The heat transfer is increased up to 8.1% in the presence of activation energy parameter (E). But, mass transfer rate declines up to 16.6% in the presence of E.

The applications of combined Dufour and Soret effects are in separation of isotopes in mixture of gases, oil reservoirs and binary alloys solidification. The nanofluid with porous medium can be used in chemical engineering, heat exchangers and nuclear reactor.

This study is mainly useful for thermal sciences and chemical engineering.

The uniqueness in this research is the study of the impact of activation energy and cross-diffusion on rotating nanoliquid flow with heat generation and convective heating condition. The obtained results are unique and valuable, and it can be used in various fields of science and technology.

The purpose of this study is to explore the impact of Joule heating, slip conditions, Dufour and Soret effects on three-dimensional magneto-convection of nanoliquid over a rotating surface in the existence of thermal radiation, viscous dissipation and internal heat generation/absorption.

The considered physical system is modelled by a set of partial differential equations (PDEs) with conditions at surface. Then, the nonlinear PDEs are altered into a system of ordinary differential equations and they are solved numerically by the Runge−Kutta−Fehlberg method. Plotting the collected velocity, temperature and solute concentration characteristics allows one to see how relevant parameters affect the results. Calculations are made for skin friction and the rate of heat and mass transfer.

The outcomes are portrayed in the form of tables and graphs with a wide range of parameter involved in the study. It is observed that the local thermal energy transfer rate enriches on increasing the value of both thermal and solute slips. The solutal slip parameter suppresses the solute transport rate and thermal slip supports the solute transport.

Combining the Dufour and Soret effects is used in oil reservoirs, binary alloy solidification and isotope separation in mixtures of gases. Heat exchangers, nuclear reactors and thermal engineering can all benefit from the usage of nanofluid with Joule heating.

This study is mainly useful for thermal sciences and chemical engineering.

The investigation of the effects of slip circumstances and Joule heating on magnetohydrodynamic rotating nanoliquid stream with thermal radiation and cross-diffusion makes this work unique. The discoveries produced are valuable and distinctive, and they have applications in many areas of thermal science and technology.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.