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The solar radiations are absorbed in the form of heat energy by using the solar centering systems in solar collectors, this energy is then transmitted to nanofluid. This study concerns the production of entropy in a Maxwell nanofluid passed over an infinite horizontal surface. Then the non-linear stretching of the surface causes a flow in parabolic trough solar collector (PTSC). The similarity transformations are employed to transmute the system of PDEs into a system of solvable ODEs provided with the boundary conditions. Eventually, the classical Keller box scheme is applied to find the numerical solutions of transmutes ODEs. The analysis of two distinct nanofluids including copper-engine oil (Cu-EO) and zirconium dioxide-engine oil ZrO2-EO is taken into account and the results for both of them are discussed. The extracted results demonstrate a decline in Nusselt number with growing permeable media parameter and augmentation for increasing values of skin friction coefficient. A recent study is presented to provide information related to the enhancement of heat collector in the PTSC with Maxwell nanofluid. The minimal level of efficiency of Cu-EO over ZrO2-EO is 7.1% and the maximum level is up to 18.7%. [ABSTRACT FROM AUTHOR]

In addition to solar water heating and transformers, these applications of research include heat exchangers and braking fluids, as well as acoustics and microelectronics. The mathematical model of Poiseuille hybrid nanofluid flow through a microchannel is considered with differing thermal conductivity and viscosity parameters. This mathematical model has mainly been developed to cater to the diversity of the hybrid nanofluid properties, which contains oxide and metal nanoparticles, for example, Cu and Al2O3 immersed in water (H2O) and Ethylene glycol (EG) as the base liquid. The substructure for hybrid nanofluid abides by the mixture of 20% water while the rest is filled with EG. Moreover, the perception of entropy is analyzed. The dimensional form of the current problem is deformed into a non-dimensional form using the appropriate choice of similarity transformation. Thence, the Runge–Kutta-Fehlberg method is being used to treat the numerical solution for the problem. The graphs spectacle the entropy, Bejan numbers, and physical behavior of the contributing factors to the flow phenomena. The numerical results of the rate coefficients for these parameters are shown in the table below. Furthermore, a comparison analysis is conducted to confirm the current result with prior work demonstrating a higher degree of concordance. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to empirically examine the influence of financial constraints on firm carbon emissions. In addition to the role of financial constraints in firm-level carbon emissions, this study also examines this influence in the presence of governance, environmental orientation and firm-level attributes. Design/methodology/approach: Using pooled ordinary least square, this study examines the impact of financial constraints on firm-level carbon emissions using a panel of 1,536 US firm-year observations from 2008 to 2019. This study also used two-step generalized method of moment–based dynamic panel data and two-stage least square approaches to address potential endogeneity. The results are robust to endogeneity and collinearity issues. Findings: The results suggest that financial constraints enhance the carbon emissions of the firms. The economic significance of financial constraints on carbon emissions is more pronounced for the firms that do not report environment-related expenditure investment and those that are highly leveraged. The authors further document that firms with a nondiverse gender board signify a statistically significant impact of financial constraints on carbon emissions. These results are also economically significant, as one standard deviation increase in financial constraints is associated with a 3.340% increase in carbon emissions at the firm level. Research limitations/implications: Some implicit and explicit factors like corporate emissions policy and culture may condition the relationship of financial constraints with carbon emissions. Therefore, it would be worthwhile to consider these factors for future research. In addition, it is beneficial to identify the thresholds and/or quantiles at which financial constraints may significantly make a difference in enhancing carbon emissions. Practical implications: The findings offer policy implications for investment in stakeholder engagement for capital acquisitions, thereby effectively enforcing environmental innovation and leading to a reduction in carbon emissions. Originality/value: This study integrated governance and environment-oriented variables in the model to empirically examine the role of financial constraints on the carbon emissions of the firms in the USA over and above what has already been documented in the earlier literature. [ABSTRACT FROM AUTHOR]

This study brings a novel dimension to mentoring theory by exploring the relatively unexamined aspect of cross-gender infatuation between mentors and mentees. At the heart of the mentoring relationship, according to this study, lies personal identification, which is characterized by feelings of connectedness, belonging, and a strong desire to forge a relationship. To examine into this topic, the study employed phenomenological methods, conducting thorough interviews with a balanced group of 20 participants. This group included five male mentors, five male mentees, five female mentors, and five female mentees. The data gathered from these interviews were meticulously analyzed using first and second cycle coding techniques, and the findings are articulated through a process model. Drawing on psychoanalytic theory, the study posits that gender differences play a crucial role in the process of personal identification within mentoring relationships. It examines situations where infatuation, driven by sexual desires, arises in one or both parties involved. The study discusses how societal gender norms often compel individuals to suppress these intimate desires. This suppression and avoidance can lead to sexual repression, manifesting as disruptive behavior and hindering the development of personal identification. Consequently, this dynamic adversely affects the caregiving aspect of the mentor-mentee relationship. The findings of this study enrich mentoring theory by shedding light on the impact of gender roles in the identification process within mentorship relationships. It highlights the complex interplay of personal emotions and societal norms in mentoring dynamics, offering a deeper understanding of the factors that influence these relationships. [ABSTRACT FROM AUTHOR]

The presented work examines the dynamics of convective Eyring–Powell magneto-nanofluid model (CEP-MNFM) with a stretching cylinder by using stupendous knacks of supervised stochastic Levenberg–Marquardt intelligent networks (SSLMINs). The partial differential equations governing the CEP-MNFM are reduced into coupled ODEs by incorporating the similarity transformations. The dataset of the proposed SSLMINs approach is generated with state-of-the-art Adam numerical method for seven different scenarios of CEP-MNFM including variation of radiation, Brownian diffusivity, and thermophoresis parameter, as well as, Biot, Schmidh, and Prandtl numbers. The reference dataset is further utilized for numerical calculation of various physical quantities on CEP-MNFM by applying the AI based methods via SSLMINs. The precision and accuracy of the designed SSLMINs approach is efficaciously substantiated through the negligible level of mean squared error with magnitude around 10–8 to 10–10, histograms with maximum instances error range 10–5, very near to the optimum correlation/regression measures. [ABSTRACT FROM AUTHOR]

Electrically conductive, thin, and flexible materials with outstanding mechanical properties are desired to meet the electromagnetic shielding requirements of next-generation electronic devices. Herein, we report the synthesis of nanostructured MXene/polyvinylidene fluoride (PVDF) polymer composites by tuning the architecture by three different approaches (sandwiched, dip coated, and solution mixing) and evaluating their potential for electromagnetic shielding. A sandwich architecture (PVDF/MXene/PVDF) dominates in terms of mechanical strength (tensile strength of 40 MPa) with complete waterproof characteristics. The sandwich architecture and solution-processed composites offered a shielding effectiveness (SE) of 65 and 51 dB, respectively, with a similar weight-to-thickness ratio for 70 μm-thick samples. The dip-coated MXene nanosheet-coated PVDF film, however, demonstrated an outstanding SE of 90 dB for a small thickness of 30 μm, which is the highest value reported for comparable thickness among polymer composites. The research emphasizes the significance of structural design in regulating the properties of polymer composites, which integrate 2D nanomaterials with similar compositions. [ABSTRACT FROM AUTHOR]

Citrus disease Huanglongbing (HLB) causes sparse (thinner) canopies due to reduced leaf and shoot biomass. Herein, we present results demonstrating the possible mechanisms behind compromised leaf growth of HLB-affected ‘Valencia’ sweet orange trees by comparing morphological, transcriptome, and phytohormone profiles at different leaf development phases (1. buds at the start of the experiment; 2. buds on day 5; . 3. leaf emergence; 4. leaf expansion; and 5. leaf maturation) to healthy trees. Over a period of 3 months (in greenhouse conditions), HLB-affected trees had ≈40% reduction in growth traits such as tree height, number of shoots per tree, shoot length, internode length, and leaf size compared to healthy trees. In addition, buds from HLB-affected trees lagged by ≈1 week in sprouting as well as leaf growth. Throughout the leaf development, high accumulation of defense hormones, salicylic acid (SA) and abscisic acid (ABA), and low levels of growth-promoting hormone (auxin) were found in HLB-affected trees compared to healthy trees. Concomitantly, HLB-affected trees had upregulated differentially expressed genes (DEGs) encoding SA, ABA, and ethylene-related proteins in comparison to healthy trees. The total number of cells per leaf was lower in HLB-affected trees compared to healthy trees, which suggests that reduced cell division may coincide with low levels of growth-promoting hormones leading to small leaf size. Both bud dieback and leaf drop were higher in HLB-affected trees than in healthy trees, with concomitant upregulated DEGs encoding senescence-related proteins in HLB-affected trees that possibly resulted in accelerated aging and cell death. Taken together, it can be concluded that HLB-affected trees had a higher tradeoff of resources on defense over growth, leading to sparse canopies and a high tree mortality rate with HLB progression. [ABSTRACT FROM AUTHOR]

In this research article we delve into the aspects of trade practices paying particular attention to environmental considerations. With the pressing challenges posed by climate change and environmental degradation worldwide it becomes crucial to evaluate how international trade law can contribute to promoting practices. We explore the frameworks, treaties and mechanisms that govern trade and examine their effectiveness, in tackling environmental concerns. Additionally we shed light on emerging trends and potential areas, for reform to foster a trade system that is more environmentally conscious and sustainable. [ABSTRACT FROM AUTHOR]

Toxic fission products, such as cesium (137Cs) and iodine (129I) are of great concern because of their long half-lives and high solubility in water. The simultaneous removal of Cs and I using a single adsorbent is an area of increasing interest. In this study, MXene/silver nanowire (AgNW) composite was synthesized through physical mixing and employed for simultaneous removal of iodide (I−) and cesium (Cs+) ions from contaminated water. The MXene/AgNW composite demonstrated excellent adsorption capacities of 84.70 and 26.22 mg/g for I− and Cs+, respectively. The experimental data supported the hypothesis of multilayer adsorption of Cs+ owing to the inter-lamellar structures and the presence of heterogeneous adsorption sites in MXene. The interaction between I− and the AgNW involved chemisorption followed by monolayer adsorption. MXene/AgNW composite material exhibited promising results in the presence of competitive ions under extreme pH conditions. Thus, synthesized composite materials holds promising potential as an adsorbent for the remediation of radioactive liquid waste. [ABSTRACT FROM AUTHOR]

In view of ever-increasing environmental pollution, there is an immediate requirement to promote cheap, multiplexed, sensitive and fast biosensing systems to monitor these pollutants or contaminants. Aptamers have shown numerous advantages in being used as molecular recognition elements in various biosensing devices. Graphene and graphene-based materials/nanohybrids combined with several detection methods exhibit great potential owing to their exceptional optical, electronic and physicochemical properties which can be employed extensively to monitor environmental contaminants. For environmental monitoring applications, aptamers have been successfully combined with graphene-based nanohybrids to produce a wide range of innovative methodologies. Aptamers are immobilized at the surface of graphene based nanohybrids via covalent and non-covalent strategies. This review highlights the design, working principle, recent developmental advances and applications of graphene based nanohybrid aptasensors (GNH-Apts) (since January 2014 to September 2021) with a special emphasis on two major signal-transduction methods, i.e., optical and electrochemical for the monitoring of pesticides, heavy metals, bacteria, antibiotics, and organic compounds from different environmental samples (e.g., water, soil and related). Lastly, the challenges confronted by scientists and the possible future outlook have also been addressed. It is expected that high-performance graphene-based nanohybrid aptasensors would find broad applications in the field of environmental monitoring. [ABSTRACT FROM AUTHOR]

The current investigation aims to investigate the effects of ohmic heating, heat source, and adhesive dispersion in third-grade nanofluid flowing magnetohydrodynamics (MHD) boundary layer heat transmission using the Koo–Kleinstreuer–Li (KKL) model. As a basic fluid, copper oxide nano molecules are suspended in engine oil. The controlling formulas that regulate the fields of flow and heat conduction are partial differential equations (PDEs) which are then converted into models of nonlinear ordinary differential equations (ODEs) that use the necessary similarity conversions. The resulting ODEs are numerically resolved using the Keller-Box approach. The effects of different common liquids, nano molecule sizes, magnetic parameter, Prandtl, material constant, and Eckert numbers are described using diagrams and tables for the field of motion, the field of temperature, the rate of heat transfer, and the drag force factor. The results show that the speed, drag force, and nozzle number for copper oxide engine oil nanofluids are lower than that of the basic liquid, while the addition of nanoparticles raises the temperature. The drag force factor and the rate of heat transfer are both found to increase when the material constant rises. [ABSTRACT FROM AUTHOR]

Solar collectors absorb solar radiation at the focus of solar concentrating systems as heat energy which is further transferred to nanofluid. Entropy creation in Maxwell nanofluid flow over an infinite horizontal surface of a porous media is the subject of the current investigation. A non-linear stretching surface then induces a parabolic trough solar collector (PTSC) flow. The thermal boundary layer is studied using a modified version of Buongiorno's Model. As a result, the PDEs, which encompass the physical aspects of the issue, must be transformed into solvable and boundary-constrained ODEs. By using a proper similarity transformation, boundary conditions and partial differential expressions are reduced to a set of non-linear ordinary differential equations. The Keller box method is used to find approximate solutions to ODEs. Tests are carried out on a nanofluid known as Copper-engine oil (Cu-EO). The Nusselt number was lowered, but the skin friction coefficient was increased as a result of a substantial magnetic parameter. In addition, Reynolds number and Brinkman number are used to measure fluctuations in viscosity, and, as a result, entropy variations throughout the domain are increased. Temperature decreased due to chemical reaction and Schmidt number, while thermal radiation increased skin friction and Nusselt. According to the current analysis, the heat collector has enhanced PTSC with Maxwell nanofluid. [ABSTRACT FROM AUTHOR]

35884260 7 Youssef J., Zhu S., Crunteanu A., Orlianges J.-C., Ho H.-P., Bachelot R., Zeng S. Highly Sensitive Plasmonic Biosensors with Precise Phase Singularity Coupling on the Metastructures. Nanomaterials have been widely exploited in the preparation of sensors and biosensors owing to their excellent features, such as high surface area, quantum size effect, and active surface [[3]]. The identification of the target molecule is required for rapid and reliable clinical diagnosis and disease monitoring [[1]]. The findings reported in this Special Issue suggest that nanomaterials possess the potential to be used for the development of various electrochemical sensors and biosensors. [Extracted from the article]

Devastating citrus disease Huanglongbing (HLB) is without existing cures. Herein, we present results demonstrating the possible mechanisms (hypoxia stress) behind HLB-triggered shoot dieback by comparing the transcriptomes, hormone profiles, and key enzyme activities in buds of severely and mildly symptomatic ‘Hamlin’ sweet orange (Citrus sinensis). Within six months (October – May) in field conditions, severe trees had 23% bud dieback, greater than mild trees (11%), with a concomitant reduction in canopy density. In February, differentially expressed genes (DEGs) associated with responses to osmotic stress, low oxygen levels, and cell death were upregulated, with those for photosynthesis and cell cycle downregulated in severe versus mild trees. For severe trees, not only were the key markers for hypoxia, including anaerobic fermentation, reactive oxygen species (ROS) production, and lipid oxidation, transcriptionally upregulated, but also alcohol dehydrogenase activity was significantly greater compared to mild trees, indicating a link between bud dieback and hypoxia. Tricarboxylic acid cycle revival, given the upregulation of glutamate dehydrogenase and alanine aminotransferase DEGs, suggests that ROS may also be generated during hypoxia-reoxygenation. Greater (hormonal) ratios of abscisic acid to cytokinins and jasmonates and upregulated DEGs encoding NADPH oxidases in severe versus mild trees indicate additional ROS production under limited oxygen availability due to stomata closure. Altogether, our results provided evidence that as HLB progresses, excessive ROS produced in response to hypoxia and during hypoxia-reoxygenation likely intensify the oxidative stress in buds leading to cell death, contributing to marked bud and shoot dieback and decline of the severely symptomatic sweet orange trees. [ABSTRACT FROM AUTHOR]

Gamma irradiation-based synthesis and modification of nanomaterials has emerged as a versatile technique to increase the electrochemically active sites for catalytic reactions. Ionizing radiation has a tremendous effect on the optical, electrical, microstructural, and physicomechanical properties of nanomaterials. By controlling the irradiation parameters such as the absorbed dose rate and the total absorbed dose, tunable synthesis and surface modifications can be achieved. Herein, the gamma irradiation technique was used to modify the Ti3C2Tx MXene and the effect on the electrochemical performance of gamma-irradiated Ti3C2Tx (γ-Ti3C2Tx) for the hydrogen evolution reaction (HER) and supercapacitor applications was studied. The irradiated structure was characterized using X-ray diffraction and scanning electron microscopy, which confirmed the formation of γ-Ti3C2Tx MXene. The electrochemical properties were examined by cyclic voltammetry, galvanostatic charge–discharge, and linear sweep voltammetry. The γ-Ti3C2Tx exhibits a specific capacitance of 169 F g−1 at 10 A g−1, with 87% capacitance retention after 5000 charge/discharge cycles. Furthermore, the γ-Ti3C2Tx-300 electrocatalyst shows an overpotential of 478 mV with a Tafel slope of 157 mV dec−1. The enhanced electrochemical properties of the gamma-irradiated MXene electrodes were attributed to quick diffusion pathways enabled by increased d-spacing upon irradiation. [ABSTRACT FROM AUTHOR]

The search for Earthquake (EQ) precursors in the ionosphere and atmosphere from satellite data has provided significant information about the upcoming main shock. This study presents the abnormal atmospheric and ionospheric perturbations associated with the Mw 7.2 Haiti EQ on 14 August 2021 at geographical coordinates (18° N, 73° W) and shallow hypocentral depth of 10 km from the data of permanent Global Navigation Satellite System (GNSS) stations near the epicenter, followed by Swarm satellites data. The total vertical electron (VTEC) anomalies occur within a 5-day window before the main shock in the analysis of nearby operation stations, followed by Swarm (A and C satellites) ionospheric anomalies in the same 5-day window before the main shock. Moreover, the geomagnetic activities are completely quiet within 10 days before and 10 days after the main shock. Similarly, the atmospheric parameters endorse the EQ anomalies within 5 days before the main shock day. The evolution of gases from the lithosphere at the epicentral region possessed significant atmospheric and ionospheric perturbations within the EQ preparation period of 5-day before the main shock under the hypothesis of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC). [ABSTRACT FROM AUTHOR]

Hollow capsules with multi-shelled or multicomponent structures are essential materials for various applications. Biomedical applications like disease diagnosis, therapy, and monitoring have special significance as they aim to improve health conditions. This review demonstrated a comprehensive overview of hollow, multifunctional structures incorporating meaningful use of nanotechnology and its' unique prospects in medicine such as patient-specific treatment, multimodal imaging, multimodal therapy, simultaneous delivery of drugs and imaging probes, and actively targeted delivery. The internal hollow cavity provides safe and controlled drug release while also enabling transport of functional moieties to target sites. This review explored the performance of different organic, inorganic, and metallic multicomponent capsules that have been reported for biomedical applications, mainly diagnostic imaging and drug delivery. Material compositions, morphologies, and synthesis strategies involved in fabricating such multifunctional systems have been discussed in detail. It is expected that with time, more sophisticated and precise systems will come to light as the outcome of ongoing concentrated research efforts. [ABSTRACT FROM AUTHOR]

The flow of a fluid across a revolving disc has several technical and industrial uses. Examples of rotating disc flows include centrifugal pumps, viscometers, rotors, fans, turbines, and spinning discs. An important technology with implications for numerous treatments utilized in numerous sectors is the use of hybrid nanofluids (HNFs) to accelerate current advancements. Through investigation of ternary nanoparticle impacts on heat transfer (HT) and liquid movement, the thermal properties of tri-HNFs were to be ascertained in this study. Hall current, thermal radiation, and heat dissipation have all been studied in relation to the use of flow-describing equations. The ternary HNFs under research are composed of the nanomolecules aluminum oxide (Al2O3), copper oxide (CuO), silver (Ag), and water (H2O). For a number of significant physical characteristics, the physical situation is represented utilizing the boundary layer investigation, which produces partial differential equations (PDEs). The rheology of the movement is extended and computed in a revolving setting under the assumption that the movement is caused by a rotatingfloppy. Before the solution was found using the finite difference method, complicated generated PDEs were transformed into corresponding ODEs (Keller Box method). A rise in the implicated influencing factors has numerous notable physical impacts that have been seen and recorded. The Keller Box method (KBM) approach is also delivered for simulating the determination of nonlinear system problems faced in developing liquid and supplementary algebraic dynamics domains. The rate of entropy formation rises as the magnetic field parameter and radiation parameter increase. Entropy production rate decreases as the Brinkman number and Hall current parameter become more enriched. The thermal efficiency of ternary HNFs compared to conventional HNFs losses to a low of 4.8% and peaks to 5.2%. [ABSTRACT FROM AUTHOR]

Solar radiation, which is emitted by the sun, is required to properly operate photovoltaic cells and solar water pumps (SWP). A parabolic trough surface collector (PTSC) installation model was created to investigate the efficacy of SWP. The thermal transfer performance in SWP is evaluated thru the presence of warmth radiation and heat cause besides viscid dissipation. This evaluation is performed by measuring the thermal transmission proportion of the selected warmth transmission liquid in the PTSC, known as a hybrid nano-fluid. Entropy analysis of Oldroyd-B hybrid nano-fluid via modified Buongiorno's model was also tested. The functions of regulating parameters are quantitatively observed by using the Keller-box approach in MATLAB coding. Short terms define various parameters for tables in velocity, shear pressure and temperature, gravity, and Nusselt numbers. In the condition of thermal radiation and thermal conductivity at room temperature, the competence of SWP is proven to be enhanced. Unlike basic nano-fluids, hybrid nano-fluids are an excellent source of heat transfer. Additionally, with at least 22.56% and 35.01% magnitude, the thermal efficiency of AA7075–Ti–6Al–4 V/EO is higher than AA7075–EO. [ABSTRACT FROM AUTHOR]

The purpose of this research was to estimate the thermal characteristics of tri-HNFs by investigating the impacts of ternary nanoparticles on heat transfer (HT) and fluid flow. The employment of flow-describing equations in the presence of thermal radiation, heat dissipation, and Hall current has been examined. Aluminum oxide (Al2O3), copper oxide (CuO), silver (Ag), and water (H2O) nanomolecules make up the ternary HNFs under study. The physical situation was modelled using boundary layer analysis, which generates partial differential equations for a variety of essential physical factors (PDEs). Assuming that a spinning disk is what causes the flow; the rheology of the flow is enlarged and calculated in a rotating frame. Before determining the solution, the produced PDEs were transformed into matching ODEs using the second order convergent technique (SOCT) also known as Keller Box method. Due to an increase in the implicated influencing elements, several significant physical effects have been observed and documented. For resembling the resolution of nonlinear system issues come across in rolling fluid and other computational physics fields. [ABSTRACT FROM AUTHOR]

The world of the Internet and networking is exposed to many cyber-attacks and threats. Over the years, machine learning models have progressed to be integrated into many scenarios to detect anomalies accurately. This paper proposes a novel approach named cloud-based anomaly detection (CAD) to detect cloud-based anomalies. CAD consist of two key blocks: ensemble machine learning (EML) model for binary anomaly classification and convolutional neural network long short-term memory (CNN-LSTM) for multiclass anomaly categorization. CAD is evaluated on a complex UNSW dataset to analyze the performance of binary anomaly detection and categorization of multiclass anomalies. Furthermore, the comparison of CAD with other machine learning conventional models and state-of-the-art studies have been presented. Experimental analysis shows that CAD outperforms other studies by achieving the highest accuracy of 97.06% for binary anomaly detection and 99.91% for multiclass anomaly detection. [ABSTRACT FROM AUTHOR]

Pulsatory movements appear in a variety of fascinating applications involving periodic flow propagation and control. Pulsing encourages mixing and, as a result, mass and heat exchange with the boundaries. Pulsing also helps to decrease surface fouling by allowing solid particles to migrate. An exact solution of the Navier–Stokes equations for the transport of an incompressible viscous fluid in a channel with arbitrary pressure distribution is described in this study. The flow is defined by two primary parameters: the pulsation parameter, which is determined by the periodic pressure gradient, and the kinetic Reynolds number, which is determined by the pulsation frequency. The purpose of employing hybrid nanofluid (HNF) is to increase the base fluid's thermal conductivity. We regard Ag and Au as nanoparticles (NPs) and blood as a base fluid for this phenomenon. Broadening this reveals that the consideration of nanoparticles has impressively extended the warm movement at the parcels of both turbulent and laminar frameworks. Attention is paid to the slope of speed, temperature, and voltage. The geometric model is therefore described using a symmetry technique. We developed the governing equation for this problem's analytical solutions. The velocity and temperature fields solution is given in the form of the Bessel and modified Bessel functions. Graph results show the mathematical benefits of the current limits: for instance, Hartmann number M , solid volume part of nanoparticles ϕ , Reynolds number R e β , Prandtl number P r , intermittent slob limit, etc. The strain angles introduced in the stress contrast, frictional force, velocity profile, and temperature profile were obtained, and the characteristics of the vortex were investigated. Resources at various boundaries of the perceptual flow are examined. As with the final essence, the smoothest results are analyzed and recorded. It has also been discovered that the velocity may be regulated by the external magnetic field, which affects the temperature profiles and hence the heat transfer, which can be enhanced or lowered by mastering the magnetic field. [ABSTRACT FROM AUTHOR]

It is well known that solar energy is the main source of thermal energy coming from the sun responsible for huge operations in engineering studies. It can be seen in the technology of photovoltaic cells, solar streetlights, solar energy plates, and solar water pumping. This study is for investigating solar radiation as well as a method to improve the performance of the solar water pump (SWP) with the use of solar radiation along with nanotechnology. The thermal transfer performance of the pump is checked for the case of many impacts including heat radiations and variable thermal conductivity. An Oldroyd‐B nanofluid with entropy production analysis has been scrutinized as a working coolant liquid in the system. Graphene oxide (GO) and Cu nanoparticles have been employed in engine oil (EO) as the base liquid. It is noticed that the heat transfer performance of SWP increases in the case of amplification in thermal radiation and temperature‐dependent thermal conductivity characteristics. In comparison to low thermal conductivity nanofluid, high thermal conductivity nanofluid provides the best capability for heat transmission. The thermal efficiency of the used (GO/EG) nanofluid has been enhanced by between 7.70% and 26.68% than (Cu/EO) nanofluid. [ABSTRACT FROM AUTHOR]

In order to understand the characteristics of bio-convection and moving microorganisms in flows of magnetized Walters-B nano-liquid, we developed a model employing Riga plate with stretchy sheet. The Buongiorno phenomenon is likewise employed to describe nano-liquid motion in the Walters-B fluid. Expending correspondence transformations, the partial differential equation (PDE) control system has been transformed into an ordinary differential equation (ODE) control system. The COMSOL program is used to generate mathematical answers for non-linear equations by employing the Galerkin finite element strategy (G-FEM). Utilizing logical and graphical metrics, temperature, velocity, and microbe analysis are all studied. Various estimates of well-known physical features are taken into account while calculating nanoparticle concentrations. It is demonstrated that this model's computations directly relate the temperature field to the current Biot number and parameter of the Walters-B fluid. The temperature field is increased to increase the approximations of the current Biot number and parameter of the Walters-B fluid. [ABSTRACT FROM AUTHOR]

A fluid's moving class improves its heat transmission capability, as well as its rigidity, owing to multivariate molecule suspension. In this way, nanofluids are superior to common fluids. In this study, we evaluated the features of ease and heat transfer. Furthermore, we investigated permeable media, heat source, variable heat conductivity, and warm irradiation results. A mathematical technique known as the Galerkin finite element (G-FEM) approach was used to solve the supervising conditions. Third-grade nanofluid (TGNF), which consists of two types of nanoparticles (NPs), single-walled carbon nanotubes (SWCNT), and multi-walled carbon nanotubes (MWCNTs) distributed in a base liquid of carboxymethyl cellulose (CMC) water, was used for this examination. The main conclusion of this study is that MWCNT-CMC nanofluid has a higher heat transfer velocity than SWCNT-CMC nanofluid. The entropy of the framework can be increased by adjusting the thermal conductivity. Additionally, we found that increasing the main volume section decreases the speed but increases the dispersion of atomic energy. In order to separately account for the development properties of inertial forces and shallow heat dispersion forces, Reynolds and Brinkman values can be used to accelerate the entropy rate of the heating framework. [ABSTRACT FROM AUTHOR]

In our research work, we have developed a model describing the characteristics of the bio-convection and moving microorganisms in the flows of a magnetized generalized Burgers' nanoliquid with Fourier's and Fick's laws in a stretchable sheet. Considerations have been made to Cattaneo–Christov mass and heat diffusion theory. According to the Cattaneo–Christov relation, the Buongiorno phenomenon for the motion of a nanoliquid in the generalized Burgers' fluid has also been applied. Similarity transformations have been used to convert the control system of the regulating partial differential equations (PDEs) into ordinary differential equations (ODEs). The COMSOL software has been applied to obtain mathematical results of non-linear equations via the Galerkin finite element method (G-FEM). Logical and graphical measurements for temperature, velocity, and microorganisms analysis have also been examined. Moreover, nanoparticle concentrations have been achieved by examining different approximations of obvious physical parameters. Computations of this model show that there is a direct relationship among the temperature field and thermal Biot number and parameter of the generalized Burgers' fluid. The temperature field is increased to grow the approximations of the thermal Biot number and parameter of generalized Burgers' fluid. It is reasonable to deduce that raising the chemical reaction parameter and concentricity relaxation parameter or decreasing the Prandtl number, concentricity Biot quantity, and active energy parameter can significantly increase the nanoparticles concentration dispersion. [ABSTRACT FROM AUTHOR]

In this study, an incompressible, steady, and magnetohydrodynamic flow of Buongiorno nanofluid through a stretchable surface has been analyzed by adopting a theoretical and numerical approach. This paper involves the impacts of buoyancy forces, thermal conductivity, chemically diffusion, and Arrhenius activation energy. Moreover, the influence of the suspension of gyrotactic microorganisms in the nanofluids is also a part of this study. It is assumed that the behavior of viscosity varies as a function of time and the suspension of microorganisms remain consistent throughout the study. A system of PDEs is reduced to a solvable system of ODEs by applying a suitable similarity transformation. For the sake of numerical solutions, the shooting method has been employed. Wolfram Mathematica has been used to deal with the BVP. In addition, the behaviors of different emerging parameters comprising velocity outline, temperature outline, concentration distribution, the density outline of gyrotactic microorganisms have also been demonstrated by graphical illustrations. From the extracted results, it has been observed that the rising values of viscosity of fluid produce a decline in the velocity parameter. Also, an increment has been noticed in the temperature profile for the growing behavior of the mixed convective factor. [ABSTRACT FROM AUTHOR]

In this study, a honeycomb-like porous-structured nickel–iron–cobalt layered double hydroxide/Ti3C2Tx (NiFeCo–LDH@MXene) composite was successfully fabricated on a three-dimensional nickel foam using a simple hydrothermal approach. Owing to their distinguishable characteristics, the fabricated honeycomb porous-structured NiFeCo–LDH@MXene composites exhibited outstanding bifunctional electrocatalytic activity for pair hydrogen and oxygen evolution reactions in alkaline medium. The developed NiFeCo–LDH@MXene electrocatalyst required low overpotentials of 130 and 34 mV to attain a current density of 10 mA cm−2 for OER and HER, respectively. Furthermore, an assembled NiFeCo–LDH@MXene‖NiFeCo–LDH@MXene device exhibited a cell voltage of 1.41 V for overall water splitting with a robust firmness for over 24 h to reach 10 mA cm−2 current density, signifying outstanding performance for water splitting reactions. These results demonstrated the promising potential of the designed 3D porous NiFeCo–LDH@MXene sheets as outstanding candidates to replace future green energy conversion devices. [ABSTRACT FROM AUTHOR]

Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. Although the sensed data could be useful for various applications (e.g., event detection in cities, energy management in commercial buildings), it first requires pre-processing to clean various inconsistencies (e.g., anomalies, redundancies, missing values). In this work, we focus on managing data redundancies in connected environments. Existing approaches suffer from (i) disregarding edge data redundancies either at the edge or at the core of the network; (ii) disregarding sensor mobility and the dynamicity of the network; (iii) disregarding the limited resources of edge devices; (iv) disregarding network/infrastructure resources; and (v) disregarding data consumer needs/requirements when cleaning the data redundancies. To address these limitations, we propose here DRMF: Data Redundancy Management for leaF-edges allowing to identify and remove data redundancies in connected environments at the device level. DRMF considers both static and mobile edge devices, and provides two algorithms for temporal and spatio-temporal redundancy detection. Once redundancies are identified, DRMF performs data deduplication taking into account the dynamic requirements of data consumers and device resources (e.g., processing, battery, memory). Experimental results highlight the performance and accuracy of our solution in detecting and eliminating edge data redundancies. [ABSTRACT FROM AUTHOR]

Summary: Hydrogen and oxygen evolution through electrochemical water splitting is essential for effective and inexpensive production of hydrogen and oxygen, which depends on the development of economical, and extremely active electrocatalysts. Two‐dimensional (2D) nano‐laminated materials are imperious as electrocatalysts due to their phenomenal properties and extensive scope of applications. In this work, we report a greener way of synthesizing MXene without hydrofluoric acid (HF) treatment and demonstrated its excellent electrochemical characteristics as an overall water‐splitting catalyst. Cl‐terminated MXenes (Ti3C2Cl2) were synthesized via a molten salt approach, in which the MAX phase (Ti3AlC2) was reacted with copper chloride (CuCl2) salt followed by thermal treatment at a temperature of 550°C for 5 hours. The resulting Cl‐terminated MXene was characterized by scanning electron microscopy, X‐ray diffraction, transmission electron microscope, Raman, Fourier transform infrared spectroscopy, energy dispersive X‐ray analysis, X‐ray photoelectron spectroscopy, and electrochemical testing was performed in the alkaline media for oxygen evolution reactions (OER) and hydrogen evolution reactions (HER). For OER in 1 M KOH, Cl‐terminated MXene achieves a benchmark of 30 mA cm−2 current density at an overpotential of 330 mV and a Tafel slope of 48 mV dec−1, while HF‐MXene exhibits an overpotential of 390 mV and a Tafel slope of 136 mV dec−1. For HER, Cl‐MXene attains an overpotential of 259 mV, and a Tafel slope of 92 mV dec−1 to achieve the 10 mA cm−2 current density, on the other hand, HF‐MXene achieves an overpotential of 444 mV and a Tafel slope of 311 mV dec−1. Furthermore, the electrocatalyst exhibited excellent long‐term stability of 0.7 V at 100 mA cm−2 current density for 36 hours. The synthesis methodology for greener Cl‐terminated MXene coupled with an outstanding electrocatalytic activity is set to open new avenues of catalyst design for water splitting. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends mainly on the IoT. Advanced machine learning (ML) techniques are being used to strengthen the STI smartness further. However, some decisions are very challenging due to the vast number of STI components and big data generated from STIs. Computation cost, communication overheads, and privacy issues are significant concerns for wide-scale ML adoption within STI. These issues can be addressed using Federated Learning (FL) and blockchain. FL can be used to address the issues of privacy preservation and handling big data generated in STI management and control. Blockchain is a distributed ledger that can store data while providing trust and integrity assurance. Blockchain can be a solution to data integrity and can add more security to the STI. This survey initially explores the vehicular network and STI in detail and sheds light on the blockchain and FL with real-world implementations. Then, FL and blockchain applications in the Vehicular Ad Hoc Network (VANET) environment from security and privacy perspectives are discussed in detail. In the end, the paper focuses on the current research challenges and future research directions related to integrating FL and blockchain for vehicular networks. [ABSTRACT FROM AUTHOR]

Drugs are directly connected to the approaches by which they are administered and their delivery affects cellular uptake, biodistribution, toxicity, and excretion. Drug delivery methods are also necessary to be modified with the development of new therapeutic agents. This review summarizes the information about advancements in the field of drug delivery and mechanisms of drug action followed by factors affecting biocompatibility. Graphene, graphene oxide, mesoporous silica nanoparticles (MSNs), iron oxide nanoparticles, polyethylene glycol ligands and gold nanoparticles are prominent advancements in the field of drug delivery. These nanocarriers are engulfed by the cells through endocytosis followed by intracellular trafficking to reach the cytoplasm and their biocompatibility can be affected by various physicochemical parameters like surface charge, size, and shape. This review article may prove essential for the modification of drug delivery methods with the development of new therapeutic agents to eliminate the hurdles in near future. [ABSTRACT FROM AUTHOR]

MXene, a novel class of 2-dimensional transition metal carbides has evolved as a promising material for various applications owing to its outstanding characteristics such as hydrophilicity, high electrical conductivity, surface area, and attractive topological structure. MXenes can form dispersion in common solvents and constitute composite with other nanomaterials, which can be utilized as effective transducers for molecular sensing. MXene-modified support materials, thus provide an intriguing platform for immobilization of target molecules onto their surface. The literature reveals that it has been increasingly utilized in the sensing of diverse types of analytes including glucose, pharmaceuticals, metals and dyes, cancer markers, pesticides, neurotransmitters, small valuable molecules, and so on. In this review, we summarize the recent updates in the MXene modified materials for sensing. For the convenience of our audience, we have distributed the analytes into categories and discussed them comprehensively. Not only we present the synthesis approach, electrochemical properties and surface chemistry of MXenes but also discussed briefly the current challenges and an outlook for future research in the related area. [ABSTRACT FROM AUTHOR]

Summary: Heterogeneous networks (HetNets) seem to be the future of data networks supported by macrocells, small cells, relays, and D2D communication. The main purpose of HetNets is to facilitate maximum users while keeping energy efficiency (EE) to its peak. In this research work, we have formulated joint users association and EE maximization problem for HetNets, where our main goal is to increase the number of users associated with HetNets while keeping EE to its maximum. Formulated problem is a concave fractional problem in nature. We have used Charnes–Cooper Transformation to convert it to the concave optimization problem. We have used the (MADS) algorithm to solve the formulated optimization problem. Results have been analyzed after extensive simulations. Performance of MADS algorithm have been shown with respect to different system parameters, that is, the number of users associated, the minimum required data rate, and joint maximization of users associated and EE. [ABSTRACT FROM AUTHOR]

BACKGROUND: The growing food‐feed‐fuel competition, declining availability of traditional feeds, higher prices, and the urgent need to provide long‐term sustainability for animal production have all triggered global research into the optimum extraction of energy and nutrients from lignin‐rich plant biomass. Recent studies have shown that the Pleurotus species of white rot fungus can selectively degrade lignin in lignin‐rich plant biomass; however, its effectiveness in selectively degrading lignin depends on the type of substrate and species of fungus. This study was therefore designed to treat wheat straw, rice straw, and corn cob, with Pleurotus eryngii, P. ostreatus, and P. florida for 30 days under solid‐state fermentation, to identify a promising fungus‐substrate combination for the selective degradation of lignin and optimal improvement in the nutritional value and digestibility of each substrate. RESULTS: The type of fungus strongly influenced (P < 0.01) selectivity in lignin degradation, and the level of improvement in crude protein (CP), in vitro dry matter digestibility (IVDMD), and in vitro gas production (IVGP), in wheat straw, rice straw, and corn cob. Fungus‐substrate interaction data revealed that P. ostreatus caused maximum (P < 0.05) degradation of lignin, and greater (P < 0.05) improvement in CP, IVDMD, and IVGP in wheat straw and rice straw. The lowest (P < 0.05) degradation of lignin and improvement in CP, IVDMD, and IVGP was caused by P. eryngii in corn cob. Among the fungi, the maximum (P < 0.05) degradation of lignin, and greater (P < 0.05) improvement in CP, IVDMD, and IVGP were caused by P. florida as compared with those of P. ostreatus and P. eryngii. CONCLUSION: The results highlight significant influence of fungus‐substrate combination for selective lignin degradability and the consequent improvement in the nutritional value of the substrates. Maximum selective lignin degradability and improvement in nutritional value and digestibility was caused by P. ostreatus in wheat straw and in rice straw, and by P. florida in corn cob. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The rapid increase in COVID-19 cases has become the symbol of fear, anxiety, and panic among people around the globe. Mass media has played an active role in community education by addressing the health information of this pandemic. People interact by sharing their ideas and feelings through social media platforms. There is a considerable need to implement different measures and better perceive COVID-19 pertinent facts and information by demystifying public sentiments. In this study, the Quarantine Life dataset of thousand tweets is based on #Quarantine, #Quarantine Days, #Quarantine Life, #My Pandemic Plan, and #Quarantine and Chill from January to September 2020 has been collected from Twitter. The extracted data have been scrubbed through preprocessing techniques. The sentiments and topics extracted from tweets have been analyzed through the TEXT BLOB, VADER, and AFFIN approach. Results show that people were distressed and fearful due to the COVID-19 pandemic. However, most people enjoyed by playing games, watching movies, and reading books during the lockdown period. According to the present meta-analysis, physical activity interventions are beneficial for patients with dementia in terms of cognition. The proposed framework illustrates the insight impact of COVID-19 on human physiological and mainly focuses on the evaluation of sentiment dynamics at the topical level. [ABSTRACT FROM AUTHOR]

Fault monitoring is often employed for the secure functioning of industrial systems. To assess performance and enhance product quality, statistical process control (SPC) charts such as Shewhart, CUSUM, and EWMA statistics have historically been utilized. When implemented to multivariate procedures, unfortunately, such univariate control charts demonstrate low fault sensing ability. Due to some limitations of univariate charts, numerous process monitoring techniques dependent on multivariate statistical approaches such as principal component analysis (PCA) and partial least squares (PLS) have been designed. Yet, in some challenging scenarios in industrial chemical and biological processes with notably nonlinear properties, PCA works poorly, according to its presumption that the dataset generally be linear. However, Kernel Principal Component Analysis (KPCA) is a reliable and precise nonlinear process control methodology, but the interaction mainly through upper control limits (UCLs) dependent on the Gaussian distribution may weaken its output. This article introduces time-varying statistical error tracking through Kernel Principal Component Analysis (KPCA) based on Generalized Likelihood Ratio statistics (GLR) using a sequential sampling scheme named KPCA-SSGLR for nonlinear fault detection. The main issue of employing just T2 and Q statistic in KPCA is that they cannot correctly give practitioners the change point of the system fault, preventing practitioners from diagnosing the issue. Based on this perspective, this study attempts to incorporate KPCA with sequential sampling Generalized Likelihood Ratio (SSGLR) for monitoring the nonlinear fault in multivariate systems. The KPCA is utilized for dimension reduction, while the SSGLR is employed as a tracking statistic. The kernel density estimation (KDE) was employed to approximate UCLs for variational system operation relying on KPCA. The testing efficiency of the corresponding KPCA-KDE-SSGLR technique was then analyzed and competed with KPCA and kernel locality preserving projection (KLPP), the UCLs of which were focused on the Gaussian distribution. The purpose of this analysis is to enhance the development of KPCA-KDE-SSGLR to accomplish future enhancements and to advance the practical use of the established model by implementing the sequential sampling GLR approach. The fault monitoring efficiency is demonstrated through different simulation scenarios, one utilizing synthetic data, the other from the Tennessee Eastman technique, and lastly through a hot strip mill. The findings indicate the applicability of the KPCA-KDE-based SSGLR system over the KLPP and KPCA-KDE methods by its two T2 and Q charts to recognize the faults. [ABSTRACT FROM AUTHOR]

The magnetohydrodynamics (MHD) viscous Jeffrey heat transport flow past a permeable extending sheet is analyzed. The Alumina ( A l 2 O 3 ) is chosen as nanoparticles immersed in sodium alginate ( SA ) as the based fluid. The effect of heat generation, Ohmic heating and viscous dissipation are also being investigated adopting Tiwari and Das model. The adequate similarity transformation is used to convert the governing equations to non-linear of higher-order ordinary differential equations (ODEs). The numerical solution of the transformed ODEs is accomplished using a finite-difference technique. The results are described in graphs according to selected parameters' values provided. The flow velocity reductions when the porosity parameter is augmented. The thermal distribution is affected by the presence of Pr , M , β , γ ∗ , δ ∗ and ϕ . Deborah number and the volume fraction of nanoparticles affect the skin friction coefficient in opposite ways. A higher volume percentage of nanoparticles and a higher Deborah number are both shown to boost the rate of heat transfer. These findings suggest that the concentration of nanoparticles can be used to manipulate heat transport and nanofluid motions. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the moderating effect of ownership concentration on the relationship between corporate social responsibility performance (CSRP) and information asymmetry using a sample of Chinese firms. Design/methodology/approach: The authors use a sample of 208 listed firms from nine different sectors in China over the period of 2008–2018. They use the generalized method of moment approach to examine the dynamic relationship between CSRP, information asymmetry and ownership concentration. CSRP index is constructed using environmental performance, social performance and corporate governance performance measures. Findings: The results indicate that CSRP positively affects the information asymmetry. Moreover, by taking ownership concentration as a moderating variable, the results indicate that ownership concentration negatively moderates the association between CSRP and information asymmetry. Research limitations/implications: The findings of the study advance the understanding of CSR practices in China. The findings have important implications for the regulators and managers in China for adopting socially responsible activities for the improvement of firm performance and protecting shareholder rights. Originality/value: The study extends the existing research on the association between CSRP and information asymmetry by including the ownership concentration as a moderating variable. The research showed that CSR plays an important role in reducing the informational gap between managers and outside stakeholders. However, the relationship between CSR and information asymmetry is not studied yet with the moderating role of ownership concentration. [ABSTRACT FROM AUTHOR]

A novel hybrid nanofluid was explored in order to find an efficient heat-transmitting fluid to replace standard fluids and revolutionary nanofluids. By using tangent hyperbolic hybrid combination nanoliquid with non-Newtonian ethylene glycol (EG) as a basis fluid and a copper (Cu) and titanium dioxide (TiO2) mixture, this work aims to investigate the viscoelastic elements of the thermal transferring process. Flow and thermal facts, such as a slippery extended surface with magnetohydrodynamic (MHD), suction/injection, form factor, Joule heating, and thermal radiation effects, including changing thermal conductivity, were also integrated. The Keller–Box method was used to perform collective numerical computations of parametric analysis using governing equivalences. In the form of graphs and tables, the results of TiO2–Cu/EG hybrid nanofluid were compared to those of standard Cu/EG nanofluid in important critical physical circumstances. The entropy generation study was used to examine energy balance and usefulness for important physically impacting parameters. Detailed scrutiny on entropy development get assisted with Weissenberg number, magnetic parameter, fractional volumes, injection parameter, thermal radiation, variable thermal conductivity, Biot number, shape variation parameter, Reynolds and Brinkman number. Whereas the entropy gets resisted for slip and suction parameter. In this case, spotted entropy buildup with important parametric ranges could aid future optimization. [ABSTRACT FROM AUTHOR]

Prandtl–Eyring hybrid nanofluid (P-EHNF) heat transfer and entropy generation were studied in this article. A slippery heated surface is used to test the flow and thermal transport properties of P-EHNF nanofluid. This investigation will also examine the effects of nano solid tubes morphologies, porosity materials, Cattaneo–Christov heat flow, and radiative flux. Predominant flow equations are written as partial differential equations (PDE). To find the solution, the PDEs were transformed into ordinary differential equations (ODEs), then the Keller box numerical approach was used to solve the ODEs. Single-walled carbon nanotubes (SWCNT) and multi-walled carbon nanotubes (MWCNT) using Engine Oil (EO) as a base fluid are studied in this work. The flow, temperature, drag force, Nusselt amount, and entropy measurement visually show significant findings for various variables. Notably, the comparison of P-EHNF's (MWCNT-SWCNT/EO) heat transfer rate with conventional nanofluid (SWCNT-EO) results in ever more significant upsurges. Spherical-shaped nano solid particles have the highest heat transport, whereas lamina-shaped nano solid particles exhibit the lowest heat transport. The model's entropy increases as the size of the nanoparticles get larger. A similar effect is seen when the radiative flow and the Prandtl–Eyring variable-II are improved. [ABSTRACT FROM AUTHOR]

The present study analyses the effect of storage time and varying fat levels in fermented laban milk samples obtained from different sources through physicochemical, sensory and microbiological attributes. The milk samples were divided into three groups (T1 = Buffalo Milk, T2 = Cow Milk, T3 = Mixed Milk) with replication. Viscosity, acidity and syneresis of all three laban milk samples increased, whereas pH decreased significantly (P ≤.05) across storage days. The viscosity, protein and total solids (TS) were significantly (P ≤.05) decreased in all Laban milk samples with a 3.5% fat level compared to a 1.5% fat level at the 21st day of the storage period. The colour and appearance scores were unaffected for the T1 group but decreased with increased fat levels for T2 and T3 groups. The Total Plate Count tended to decrease with a 3.5% fat level in all three laban milk samples. However, days of storage had a non-significant effect. Buffalo laban milk seems best in terms of viscosity, protein, TS, taste and aroma. Furthermore, these attributes are affected by days of storage and fat level. The fermented laban prepared from mixed milk (T3) showed results at par with that from buffalo milk. Hence, considering the economical aspect, mixed milk laban at a fat level of 3.5% is highly recommended. [ABSTRACT FROM AUTHOR]

Purpose: The extant literature provides substantial evidence that various facets of national culture play a significant role in corporate financial decision making. We systematically review the role of national culture on the various thematic domains of corporate financial decision making to outline what have been studies thus far and what needs to be studied. Design/methodology/approach: Keywords such as national culture, organizational culture, power distance, uncertainty avoidance, masculinity, risk aversion and individualism for a search in the prominent academic literature databases are used. The studies related to the corporate financial decision making that is tied with these keywords are identified and selected for the systematic review. Findings: The review of extant literature suggests strong evidence that national culture has a significant role in influencing corporate cash holding, corporate risk-taking, individual behaviour of the financial managers and initial public offering by the corporations. The review also indicates, although extant studies have examined the role of national culture in the key corporate financial decisions, evidence on the role of national culture in the firm's investment efficiency aspects is rather scarce. Also, what explains the role of national culture in corporate financial decision making has not been empirically exploited through causal mechanisms. Practical implications: The findings of the studies help advance our understanding of the current research status concerning the role played by the national culture in shaping corporate financial decisions and raise important future calls. Originality/value: To best of our knowledge, no prior study has systematically reviewed the role of national culture in the thematic domains of corporate financial decision making. [ABSTRACT FROM AUTHOR]

As a try, this work has been focused in the way towards the effective contribution in the field of solar aviation using renowned nanotechnology. After realizing the causes and effects of traditionally used energy forms, the search of cost-efficient, eco-friendly, and most prominent renewable source leads us back to the solar utilities. Research era of solar radiation-powered aircraft has been in trend. Focusing on that, an efficient numerical model representing the flow and thermal aspects of a parabolic trough surface collector (PTSC) embedded on solar aircraft wings has been adopted for this study. As the first time with the note, an eminent and leading form of thermal efficient fluid of kind, the Casson hybrid nanofluid has been engaged with the expectations of enhanced performance in the solar aircraft wings. To test it, a trending reputable numerical scheme of the Keller-box method has been utilized and the parametrical studies were carried out. The upshots of those studies provide the affable proofs in favor of our expectations towards the improved solar wings with better thermal efficiency. The glimpse of those successes in the parametrical level has been showcased in the forms of tables and graphs. The lateral "x" direction significant about the inertial forces, suspended particle ratio, and skin resistance phenomena, while for the transverse fluidity in the "y" direction were has to be concern about the magnetic interactions, rotational coordinates, viscous nature of the fluid along with the porous states. The power of hybrid nanofluid combos was exposed in higher notes in a unique state of solar aircraft wings. Furthermore, the thermal efficiency of hybrid nanofluids over nanofluids got down to a minimal level of 6.1% and peaked up to 21.8%. [ABSTRACT FROM AUTHOR]

Solar thermal collectors distribute, capture, and transform the solar energy into a solar thermal concentration device. The present paper provides a mathematical model for analyzing the flow characteristics and transport of heat to solar collectors (SCs) from non-Newtonian nanofluids. The non-Newtonian power-law scheme is considered for the nanofluid through partial slip constraints at the boundary of a porous flat surface. The nanofluid is assumed to differ in viscosity and thermal conductivity linearly with temperature changes and the magnetic field is appliqued to the stream in the transverse direction. The method of similarity conversion is used to convert the governing structure of partial differential formulas into the system of ordinary differential ones. Using the Keller box procedure, the outcoming ordinary differential formulas along with partial slip constraints are numerically resolved. A discussion on the flowing and heat transport characteristics of nanofluid influenced by power law index, Joule heating parameter, MHD parameter and slip parameters are included from a physical point of view. Comparison of temperature profiles showed a marked temperature increase in the boundary layer due to Joule heating. The thickness of the motion boundary-layer is minimized and the transport of heat through boundary-layer is improved with the partial slip velocity and magnetic parameters rising. Finally, With an increase in the Eckert number, the distribution of temperature within boundary layer is increased. [ABSTRACT FROM AUTHOR]

Survey of literature unveils that nanofluids are more efficient for heat transport in comparison to the traditional fluids. However, the enlightenment of developed techniques for the augmentation of heat transport in nanomaterials has considerable gaps and, consequently, an extensive investigation for aforementioned models is vital. The ongoing investigation aims to study the 2-D, incompressible Jeffrey nanofluid heat transference flow due to a stretchable surface. Furthermore, the effect of dispersion of graphene nanoparticles in base liquid ethylene glycol (EG) on the performance of flow and heat transport using the Tawari-Das model in the existence of Ohmic heating (electroconductive heating) and viscous heat dissipation is contemplated. The boundary-layer PDEs are reconstituted as ODEs employing appropriate similarity transformation. Keller-Box Method (KBM) is utilized to determine the numerical findings of the problem. Graphene conducts heat greater in rate than all of the other materials and it is a good conductor of electrical energy. Graphene/EG nanofluid is employed to look out the parametric aspects of heat transport flow, drag coefficient, and heat transference rate phenomena with the aid of graphs and tables. The numerical outcomes indicate that concentration and magnetic field abate the shear stresses for the nanofluid. An increase of Graphene nanoparticle volume fraction parameter can boost the heat transport rate. The effect of Prandtl Number is to slow down the rate of heat transport as well as decelerate the temperature. Additionally, the rate of heat transportation augments on a surface under Deborah's number. Results indicate that the temperature of the graphene-EG nanofluid is greater than the convectional fluid hence graphene-EG nanofluid gets more important in the cooling process, biosensors and drug delivery than conventional fluids. [ABSTRACT FROM AUTHOR]