Similar Variation Research Articles

Comparative Analysis for the Seasonal Variations of the IF2 and T Ionospheric Indices during Solar Cycles 23 and 24

In this work, a comparative analysis for the behavior and pattern of the variations of the IF2 and T Ionospheric indices was conducted for the minimum and maximum years of solar cycles 23 and 24. Also, the correlative relationship between the two ionospheric indices was examined for the seasonal periods spanning from August 1996 to November 2008 for solar cycle 23 and from December 2008 to November 2019 for solar cycle 24. Statistical calculations were performed to compare predicted values with observed values for the selected indices during the tested timeframes. The study's findings revealed that the behavior of the examined indices exhibited almost similar variations throughout the studied timeframe. The seasonal variations were adopted to examine the cross-correlation between the studied indices. The seasonal correlation between tested indices demonstrated that the two indices are highly correlated to each other, with determination coefficient (R2) values ranging from 0.991 to 0.998 during solar cycle 23 and from 0.996 to 0.998 during solar cycle 24. Furthermore, the results of the comparative analytical study revealed that the mathematical correlation equation between the tested indices could be described as a first-order polynomial equation. The proposed mathematical correlation formula for these two indices exhibited a high level of accuracy and good fit between observed values and generated datasets for all seasons during both solar cycles 23 and 24.

A scientific report on heat transfer analysis due to generated and absorbed heat over an oscillatory stretching sheet: a finite difference-based study.

A non-Newtonian liquid motion across a stretchable surface is relevant to various industrial applications, including extruding plastic sheets and stretching plastic films. In connection with this, the impact of endothermic and exothermic chemical reactions on the flow of rate-type liquid via an oscillatory stretching sheet in the presence of permeable media with the Maxwell liquid model is elucidated in the present study. Scientists and engineers may enhance the efficiency of chemical reactions or heat transmission by optimising system flow and investigating the effect of reactions on flow dynamics. The present study's governing partial differential equations (PDEs) are transformed into their non-dimensional form using similarity variables. The resulting equations are numerically solved using the finite difference method (FDM). Outcomes disclose that the temperature profile declines as the activation energy and unsteadiness parameters increase. The influence of the Maxwell and unsteadiness parameters on the fluid's velocity with respect to time is represented. The rise in the values of chemical reaction parameter upsurges the thermal profile. As the activation energy and unsteadiness parameters upsurge, the thermal profile declines. As the chemical reaction parameter and the ratio of oscillation frequency to stretching rate values rise, the concentration profile falls.

Characteristics of oxygenated volatile organic compounds in Zurich, Switzerland: Sources, composition, and implication for secondary aerosol formation

Volatile organic compounds (VOCs) are of vital importance in the formation of secondary organic aerosol (SOA). Understanding SOA formation remains challenging, requiring further investigation of both oxygenated VOCs (OVOCs) and SOA composition with novel measurement techniques. In this work, we deployed a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS) to measure VOCs and their oxidation products in urban Zurich in summer 2016. The positive matrix factorization (PMF) source apportionment method identified five sources, including two primary sources (traffic and local), and three OVOC sources associated with different oxidation processes in the atmosphere. Together with the deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF-MS), this enabled a detailed understanding of the SOA components which were dominated by biogenic SOA and distinguished by daytime and nighttime chemistry. The combination of the two instruments provided new insights in the understanding of atmospheric processes by comparison of molecular-level secondary components between gas phase and particle phase. In the gas phase, two OVOC factors (32.1% and 16.7%) showed strong influence from the oxidation of aromatic compounds, exhibiting low atomic H to C ratios, and were distinguished by daytime and night-time chemistry. The third OVOC factor (19.3%) was characterized by strong biogenic influence. Similar temporal variations were found for the gas and aerosol phase, indicating co-evolution of OVOCs and SOA in summer. Besides, comparisons of OVOC compounds and SOA composition exhibited similar H to C ratio distributions for both the gas phase and particle phase.

An integrated approach for studying exposure, metabolism, and disposition of traditional Chinese medicine using PATBS and MDRB tools: a case study of semen Armeniacae Amarum.

Deciphering the in vivo processes of traditional Chinese medicine (TCM) is crucial for identifying new pharmacodynamic substances and new drugs. Due to the complexity and diversity of components, investigating the exposure, metabolism, and disposition remains a major challenge in TCM research. In recent years, a number of non-targeted smart mass-spectrometry (MS) techniques, such as precise-and-thorough background-subtraction (PATBS) and metabolomics, have realized the intelligent identification of in vivo components of TCM. However, the metabolites characterization still largely relies on manual identification in combination with online databases. We developed a scoring approach based on the structural similarity and minimal mass defect variations between metabolites and prototypes. The current method integrates three dimensions of mass spectral data including m/z, mass defect of MS1 and MS2, and the similarity of MS2 fragments, which was sequentially analyzed by a R-based mass dataset relevance bridging (MDRB) data post-processing technique. The MDRB technology constructed a component relationship network for TCM, significantly improving metabolite identification efficiency and facilitating the mapping of translational metabolic pathways. By combining MDRB with PATBS through this non-targeted identification technology, we developed a comprehensive strategy for identification, characterization and bridging analysis of TCM metabolite in vivo. As a proof of concept, we adopted the proposed strategy to investigate the process of exposure, metabolism, and disposition of Semen Armeniacae Amarum (CKXR) in mice. The currently proposed analytical approach is universally applicable and demonstrates its effectiveness in analyzing complex components of TCMs in vitro and in vivo. Furthermore, it enables the correlation of in vitro and in vivo data, providing insights into the metabolic transformationsamong components sharing the same parent nucleus structure. Finally, the developed MDRB platform is publicly available for ( https://github.com/933ZhangDD/MDRB ) for accelerating TCM research for the scientific community.

Cattaneo‐Christov model for cross nanofluid with Soret and Dufour effects under endothermic/exothermic reactions: a modified Buongiorno tetra‐hybrid nanofluid approach

AbstractThe previous researchers used a slightly different version of the Buongiorno hybrid nanofluid (BHNF) concept. In the existing research, there is not a single effort that was undertaken to explore the effect that tetra hybrid nanoparticles (tethnf) implanted with the BHNF model have on liquid movement that is then exposed to an elastic sheet. This endeavor focuses on researching the implication of a modified Buongiorno tetra hybrid cross nanofluid concept on magnetized radiative cross nanofluid transport, along with impacts such as Cattaneo–Christov heat flux and Cattaneo–Christov mass flux, variable thermal conductivity, diffusion‐thermo and thermo‐diffusion effects, and endothermic/exothermic type chain reactions. This approach integrates both Buongiorno and tethnf. By inserting similar variables, the controlling model partial differential equations have been transformed into dimensionless Ordinary differential equations. These equations are then treated computationally with the help of the Lobatto III A technique. The MATLAB computer program is used to produce simulation solutions, as well as the findings, which are displayed in the form of graphs and tables. Based on the results that have been gathered, it was discovered that the speed of heat delivery increases when there is an increase in the speed of an endothermic reaction. When the Dufour and thermal relaxation factors are increased, the speed at which heat is transmitted also increases. The fluid viscosity becomes more pronounced as a result of an increase in the viscosity index n, the Weissenberg number We, and the magnetic field M, all of which contribute to a reduction in the velocity distribution. A progressive change in the radiation parameters Rd, Dufour effect, and thermal conductivity which magnifies Nusselt number causes an increase in the heat delivery rate, which in turn amplifies Nusselt number.

Evaluating the mixed convection flow of Casson fluid from the semi-infinite vertical plate with radiation absorption effect

This study examines a steady laminar Casson fluid flow induced by a semi-infinite vertical plate under the impact of the Darcy-Forchheimer relation and thermal radiation. The features of mixed convection, cross-diffusion, radiation absorption, heat generation, chemical reactions and viscous dissipation are also considered to explain the transport phenomenon. The resultant system of equations, concerned with the problem under consideration, is transformed into a group of non-linear ordinary differential equations (ODEs) by means of similarity variables. The bvp4c method, an instrument popular for its numerical accomplishments, is utilized to solve this problem. The effect of flow parameters on heat transfer, concentration and velocity is evaluated via diagrams. To validate our code, we have compared the present outcomes to the prevenient literature, and stable consent has been detected. Moreover, the friction coefficient Cfx, Nusselt number Nux, and Sherwood number Shx are also computed to assess velocity gradient, efficiency of heat transfer and mass transfer process, respec-tively.

Dynamics of Viscous Jeffrey Fluid Flow Through Darcian Medium With Hall Current and Quadratic Buoyancy.

This contribution builds on existing studies by investigating the dynamics of Hall current in Jeffery fluid under radiative heat, convective boundary conditions, Joule heating, and Darcy dissipation. Hall current, an important phenomenon in engineering applications involving strong magnetic fields, highlights the impact of electromagnetic force in examining blood flow rate, determining charge drift velocity, density, and movement, and is used in power generators and high-voltage transformers. This analysis incorporates dissipative and thermal radiative heat and employs the effects of Hall current and Joule heating, resulting from porous medium resistance, to derive the partial differential equationsgoverning the dynamic systems. These equationsare then reduced to ordinary differential equations (ODEs) through similarity variables. The Galerkin weighted residual method (GWRM) is employed to examine the dynamics of Hall current and quadratic thermal buoyancy, shedding light on the thermal properties and hydrodynamics of Jeffrey fluid convection within a porous medium. The analysis reveals that in the presence of an applied magnetic field, the contribution of Hall current to flow and heat dynamics induces a magnetic force that enhances fluid motion and negatively impacts heat energy patterns. The imposition of dissipative heat physically increases the fluid temperature, owing to an increase in buoyancy current. The occurrence of thermal radiation, Hall current, viscous dissipation, and Joule heating can efficiently optimize the rate of heat transfer and shear stress. Moreover, the tabular results indicate that Jeffrey fluid, exhibiting higher relaxation time, will experience a lower friction coefficient and heat transferrate.

Identification of optimum scopes of environmental drivers for schistosome-transmitting Oncomelania hupensis using agent-based model in Dongting Lake Region, China.

Oncomelania hupensis (O. hupensis), the sole intermediate host of Schistosoma japonicum, greatly influence the prevalence and distribution of schistosomiasis japonica. The distribution area of O. hupensis has remained extensive for numerous years. This study aimed to establish a valid agent-based model of snail density and further explore the environmental conditions suitable for snail breeding. A marshland with O. hupensis was selected as a study site in Dongting Lake Region, and snail surveys were monthly conducted from 2007 to 2016. Combined with the data from historical literature, an agent-based model of snail density was constructed in NetLogo 6.2.0 and validated with the collected survey data. BehaviorSpace was used to identify the optimal ranges of soil temperature, pH, soil water content, and vegetation coverage for snail growth, development and reproduction. An agent-based model of snail density was constructed and showed a strong agreement with the monthly average snail density from the field surveys. As soil temperature increased, the snail density initially rose before declining, reaching its peak at around 21°C. There were similar variation patterns for other environmental factors. The findings from the model suggested that the optimum ranges of soil temperature, pH, soil water content and vegetation coverage were 19°C to 23 °C, 6.4 to 7.6, 42% to 75%, and 70% to 93%, respectively. A valid agent-based model of snail density was constructed, providing more objective information about the optimum ranges of environmental factors for snail growth, development and reproduction.

Thermal performance analysis of magnetohydrodynamic Al[formula omitted]O[formula omitted]-SiO2-TiO[formula omitted]/water ternary hybrid nanofluid in converging and diverging channels with nanoparticle shape effects

Improving heat transfer in thermal systems is critical to achieving better results in a variety of systems. The study aims to investigate the laminar flow dynamics of Al2O3-SiO2-TiO2/water hybrid nanofluids, emphasizing how the channel geometry affects the velocity, temperature distribution, and heat transfer efficiency. This understanding is crucial for optimizing industrial processes, such as cooling systems and heat exchangers. Effects of various nanoparticle shapes, joule heating, viscous dissipation, thermal radiation, and heat source/sink on the system’s behavior are evaluated. Governing partial differential equations are transformed into ordinary differential equations using similarity variables and are solved semi-analytically via the homotopy analysis method. As the Hartmann number increases from 1 to 7, the heat transfer rate rises from 0.02% to 0.9%. When the radiation parameter and Eckert number are varied from 0.05 to 0.2, the heat transfer rate increases significantly, from 1.2% to 4.86% and 3.43% to 13.73%, respectively. Heat transfer rate increased by 16.28% with heat source (Q=2) and decreased by -16.12% with heat sink (Q=−2). Platelet-shaped nanoparticles demonstrate lower skin friction in divergent channels, whereas spherical nanoparticles exhibit higher skin friction; this trend reverses in convergent channels. Suspensions of nanoparticles with a 5% volume fraction achieve heat transfer rates of 1.88%, 4.07%, 10.54%, 19.20%, and 8.74% for spheres, bricks, cylinders, platelets, and blades, respectively. The study reveals that Al2O3/H2O, Al2O3-TiO2/H2O, and Al2O3-SiO2-TiO2/H2O nanofluids have the best heat transfer rates for mono nanofluid, hybrid nanofluid, and ternary hybrid nanofluid by 15.24%, 19.92%, and 19.20%, respectively. Finally, multiple linear regression is employed to analyze the impact of relevant parameters on heat transfer rate and skin friction.

Investigation of activation energy of Maxwell fluid with Newtonian heat effect at the boundary layer flow on a cylinder embedded in porous medium

AbstractThis study aims to investigate the flow of Maxwell fluid over a cylinder, considering the combined effect of Magnetohydrodynamics (MHD) and a permeable medium on the equation of momentum, heat generation and radiation on the equation of energy, and activation energy on the mass equation. The objective is to analyze the impression of these physical phenomena on the fluid's behavior under specified boundary conditions, with a focus on the Newtonian heating effect. The significance of this research lies in its application to industrial processes, polymer extrusion and cooling of metallic sheets, where controlling fluid flow and energy transfer is crucial. The dimensional governing equations for momentum, energy, and concentration were changed into non‐dimensional forms via appropriate dimensionless quantities and similarity variables. The subsequent nonlinear ordinary differential equations were answered using the BPV4C inbuilt MATLAB solver. The key findings reveal that the concentration outline rises with a rise in activation energy and declines with a rise in the chemical reaction. Additionally, the Nusselt number profile displays an increasing trend with the Newtonian heating parameter, indicating enhanced heat transfer. Quantitative results demonstrate that the occurrence of a porous medium and MHD significantly impacts the velocity and temperature contours. The real‐time application of this study can be seen in the optimization and design of chemical reactors, heat exchangers, and cooling systems in engineering processes. The developed model delivers insights into controlling energy and mass transfer in processes involving stretching surfaces, which is essential for improving efficiency and product excellence in various industrial applications.

Computational study with neural networks to double diffusion in Prandtl thermal nanofluid flow adjacent to a stretching surface design with numerical treatment

The study focuses on the implementation of neural networks in analyzing the behavior of Prandtl nanofluid near a extending surface in the existence of dual diffusion. The research investigates the merged consequence of thermal and concentration gradients on the fluid flow and heat transfer characteristics using advanced computational techniques. The investigation delves into the phenomenon of double diffusion in the flow of Prandtl nanofluid near a stretching surface (DD-PNSS), employing the Levenberg-Marquardt scheme with Artificial Neural Networks (LMS-ANNs). The application of similarity variables converts the non-linear partial differential equations into non-linear ordinary differential equations. Through the application of the Lobatto IIIa formula in a three-stage process, various data sets are generated for the LMS-ANNs by varying parameters such as the Prandtl fluid parameter ([Formula: see text]), Prandtl number (Pr), Brownian motion parameter (Nb), thermophoresis parameter (Nt), and Dufour-solutal Lewis number (Ld). The range of parameter α is from 2 to 3.5, parameter β from 0.1 to 0.9, Nb is from 0.1 to 0.4, Nt is from 0.1 to 0.7, Le is from 1 to 3 and Ld is from 0.1 to 0.5. The intrinsic behavior of embedded parameters on dimensionless velocity, temperature, solutal concentration, and nanoparticle concentration profiles is graphically evaluated. The proposed LMS-ANNs model is meticulously tested, validated, and trained using a multi-stage approach, and its performance is compared to established references to ensure its reliability. The effectiveness of the suggested LMS-ANNs model is further affirmed through regression analysis, Mean Squared Error (MSE) evaluation, and histogram studies, showcasing an exceptional accuracy level ranging from 10−08 to 10−10, setting it apart from alternative approaches and reference models.

Neuroimaging-based variability in subtyping biomarkers for psychiatric heterogeneity.

Neuroimaging-based subtyping is increasingly used to explain heterogeneity in psychiatric disorders. However, the clinical utility of these subtyping efforts remains unclear, and replication has been challenging. Here we examined how the choice of neuroimaging measures influences the derivation of neuro-subtypes and the consequences for clinical delineation. On a clinically heterogeneous dataset (total n = 566) that included controls (n = 268) and cases (n = 298) of psychiatric conditions, including individuals diagnosed with post-traumatic stress disorder (PTSD), traumatic brain injury (TBI), and comorbidity of both (PTSD&TBI), we identified neuro-subtypes among the cases using either structural, resting-state, or task-based measures. The neuro-subtypes for each modality had high internal validity but did not significantly differ in their clinical and cognitive profiles. We further show that the choice of neuroimaging measures for subtyping substantially impacts the identification of neuro-subtypes, leading to low concordance across subtyping solutions. Similar variability in neuro-subtyping was found in an independent dataset (n = 1642) comprised of major depression disorder (MDD, n = 848) and controls (n = 794). Our results suggest that the highly anticipated relationships between neuro-subtypes and clinical features may be difficult to discover.

First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements

Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) on board the GEO-KOMPSAT-2B satellite is the first geostationary satellite launched to monitor the environment. GEMS conducts hourly measurements during the day over eastern and southeastern Asia. This work presents glyoxal (CHOCHO) vertical column densities (VCDs) retrieved from GEMS, with optimal settings for glyoxal retrieval based on sensitivity tests involving reference spectrum sampling and fitting window selection. We evaluated GEMS glyoxal VCDs by comparing them to the TROPOspheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) ground-based observations. On average, GEMS and TROPOMI VCDs show a spatial correlation coefficient of 0.63, increasing to 0.87 for northeastern Asia. While GEMS and TROPOMI demonstrate similar monthly variations in the Indochinese Peninsula regions (R > 0.67), variations differ in other areas. Specifically, GEMS VCDs are higher in the winter and either lower or comparable to TROPOMI and MAX-DOAS VCDs in the summer across northeastern Asia. We attributed the discrepancies in the monthly variation to a polluted reference spectrum and high NO2 concentrations. When we correct GEMS glyoxal VCDs as a function of NO2 SCDs, the monthly correlation coefficients substantially increase from 0.16–0.40 to 0.45–0.72 in high NO2 regions. When averaged hourly, GEMS and MAX-DOAS VCDs exhibit similar diurnal variations, especially at stations in Japan (Chiba, Kasuga, and Fukue).

Deep north atlantic circulation strength: Glacial-interglacial variability over the last 400,000 years

Most of the high-resolution studies investigating the past variability of the deep North Atlantic circulation are focused on recent timescales, but little is known for periods older than the last glacial period. Based on magnetic, elemental and physical grain-size proxies of three pairs of sediment cores located South of Iceland, we reconstructed the past changes in grain-size and basaltic-derived grain concentration over the last 400 ka (1 ka = 1000 years). The source and grain-size proxies exhibit highly similar variations between the three sites, suggesting they are affected by the same regional process. Persistently lower concentrations and finer grain-sizes recorded in the southernmost and deeper site compared to the northern sites indicate a North to South gradient that is consistent with the southward transport of sediments from a northern basaltic source by a deep current. Therefore, we interpret changes recorded by the ensemble of proxies at the three sites as past variations in the ISOW intensity. These new results show persistent influence, over the entire 400 ka, of a southward deep-water flow in the subpolar North Atlantic, from 1800 to 2800 m water depth. The “off mode” of deep Atlantic circulation during Heinrich events suggested by many studies is therefore questioned. This study extends the previous observations made for the 20–65 ka period over the last 400 ka. Our results also show that the three studied sites are bathed by a deep-water mass formed in the Nordic Seas, during both glacial and interglacial periods, suggesting that the present-day convection areas were still active during glacial periods. Our ISOW intensity records are highly similar to those of deep-water ventilation. We propose that the strength of overflows in the North Atlantic regulates the volume of North Atlantic Deep Water (NADW) and its southward transport in the Atlantic basin. Therefore, the Southern source waters may only act as an opportunistic component of the deep Atlantic circulation, invading or retreating depending on the NADW strength.

Investigation of convective heat transport in a Carreau hybrid nanofluid between two stretchable rotatory disks

Abstract Hybrid nanofluids (HNFs) have outstanding energy transfer capabilities that are comparable to mono-nanofluids. Materials had appliances in obvious fields such as heat generation, micropower generation, and solar collectors. The objective of this study is to investigate the new aspects of convective heat transfer in an electrically conducting Carreau HNF situated between two parallel discs. In addition to the presumed stretchability and rotation of the discs, physical phenomena like nonlinear radiation, viscous dissipation, Joule dissipation, and heat generation and absorption are considered. The Cu and TiO2 nanoparticles dispersed in engine oil to understand the intricate phenomenon of hybridization. The Tiwari and Das nanofluid model is employed to model the governing partial differential equations (PDEs) and then simplified using boundary layer approximation. The suitable transformations of similarity variables are defined and implemented to change the set of formulated PDEs into ordinary differential equations. The reduced system is solved semi-analytically by the homotopy analysis method. The influences of involving physical parameters on the velocity and temperature are plotted with the help of graphical figures. This study brings forth a significant contribution by uncovering novel flow features that have previously remained unexplored. By addressing a well-defined problem, our research provides valuable insights into the enhancement of thermal transport, with direct implications for diverse engineering devices such as solar collectors, heat exchangers, and microelectronics.

Assessment of heavy metal contamination in groundwater and its implications for dental and public health

Groundwater contamination with heavy metals is a critical environmental issue, especially in regions heavily reliant on groundwater for drinking purpose. These metals can seep into groundwater from soil and rock weathering or through improper disposal of industrial waste and effluents. Access to safe drinking water is essential for maintaining public health. This study aimed to assess heavy metal contamination in groundwater and its implications for dental and public health. The objective of the study was to measure the concentration of the heavy metals in the dentine of extracted tooth of the study population. The study concurrently measured heavy metal concentrations in groundwater and tooth dentine samples, analyzing demographic profiles, heavy metal correlations, and underlying structures using Principal Component Analysis (PCA). The average level of heavy metals in the groundwater samples varied from 9.763 ± 3.362 μg/L for Cd to 3426.204 ± 875.264 μg/L for Fe. The mean concentrations (μg/g) in teeth dentine showed significant variations, with iron (Fe) ranging from 0.149 ± 0.03 μg/g in water purifiers to 4.62 ± 0.578 μg/g in local water sources. Similar variations were observed for other heavy metals across different water sources. Principal component analysis (PCA) revealed seven principal components, with the first two components explaining 96.1% of the total variance. The findings revealed varied concentrations of heavy metals across all water sources. Statistical analyses underscored the complex relationship between water sources and heavy metal contamination levels, highlighting the need for targeted interventions to improve water quality and mitigate health risks. The study highlights the urgent need for monitoring and mitigation efforts to ensure safe drinking water and mitigate health risks associated with heavy metal contamination.

A Comprehensive Analysis on Thermally Enhanced Electro-Magneto-Hydrodynamic Micropolar Flow Mixture Comprising Water (70%) and Ethylene-Glycol (30%) with Alumina Nanoparticles over a Riga Plate

In this research paper, a two-dimensional flow of an electro-magneto-hydrodynamic water-ethylene glycol-based nanofluid over a Riga plate has been presented. The nanofluid mixture has micropolar and electrical behaviors. Furthermore, the effects of chemical reaction and activation energy are imposed in the present investigation. It is important to mention that the nanofluid mixture is composed of alumina nanoparticles (Al2O3) and base fluid as water-ethylene glycol (70:30). It is important to mention that the significance of this study lies in engineering cooling systems, drug delivery, and microfluidic devices. The main equations of problem have converted to dimension-free form using similarity variables. The transformed ODEs are then converted into first-order differential equations and solved numerically by executing the shooting method. The validation on the modeled equations is confirmed by validating the present analysis with the results available literature. From this analysis, it is obtained that the greater micropolar parameter and modified Hartmann number enhanced the streamwise velocity profile while reducing micro-rotational velocity. The greater micro-gyration constraint reduced streamwise velocity profile while enhancing micro-rotational velocity. The greater thermophoresis factor and thermal Biot number enhanced both thermal and concentration profiles. The greater activation energy factor enhanced the concentration distribution, and the greater Brownian motion factor and Schmit number reduced the concentration distribution. The higher thermophoresis factor reduced the heat transfer rate, and the higher heat source factor and thermal Biot number enhanced heat transfer rate.

Heat transport analysis of three-dimensional Magnetohydrodynamics nanofluid flow through an extending sheet with thermal radiation and heat source/sink

Regarding heat transformation efficiency, the hybrid nanofluid performs superior to the nanofluid. The majority of hybrid nanofluid uses are in the industrial sector, producing solar energy, cooling generators, and vehicle heat transformation. Heat transfer and nanofluid velocity are the two most crucial transport properties that must be evaluated before the first and second thermodynamics equations are applied to nanoscale fluids. The objective of this work is to investigate the characteristics of transmission of heat of magnetohydrodynamic (MHD) nanofluid (Ag/H2O)and hybrid nanofluid (Ag+Al2O3/H2O)flow on a linear extensible sheet when magnetic forces are present. Similarity variables are applied to transform a set of nonlinear dimensionless partial-differential equations to collection of ordinary-differential equations. The non-analytical solutions of these transformed equations are found utilizing the MATLAB mathematical program's bvp4c function. The impression of various physical attributes along skin friction coefficients and properties of heat transmission are analyzed. The behavior of key parameters, including surface stretching ratio, rotational and magnetic effects, for temperature and velocity, is shown using graphs and tables. In conclusion, hybrid nanofluids, which comprise silver and aluminum oxide nanoparticles dispersed in water, outperform silver-water nanofluids by around 10-15% under magnetohydrodynamic (MHD). The higher thermal conductivity of these hybrid nanofluids allows for better heat dissipation, making them an appealing option for applications that need optimal thermal management in the presence of magnetic fields.

Thermodynamics of Giant Molecular Clouds: The Effects of Dust Grain Size

The dust grain size distribution (GSD) likely varies significantly across star-forming environments in the Universe, but its impact on star formation remains unclear. This ambiguity arises because the GSD interacts nonlinearly with processes like heating, cooling, radiation, and chemistry, which have competing effects and varying environmental dependencies. Processes such as grain coagulation, expected to be efficient in dense star-forming regions, reduce the abundance of small grains and increase that of larger grains. Motivated by this, we investigate the effects of similar GSD variations on the thermochemistry and evolution of giant molecular clouds (GMCs) using magnetohydrodynamic simulations spanning a range of cloud masses and grain sizes, which explicitly incorporate the dynamics of dust grains within the full-physics framework of the STARFORGE project. We find that grain size variations significantly alter GMC thermochemistry: the leading-order effect is that larger grains, under fixed dust mass, GSD dynamic range, and dust-to-gas ratio, result in lower dust opacities. This reduced opacity permits interstellar radiation field and internal radiation photons to penetrate more deeply. This leads to rapid gas heating and inhibited star formation. Star formation efficiency is highly sensitive to grain size, with an order-of-magnitude reduction when grain size dynamic range increases from 10−3–0.1 μm to 0.1–10 μm. Additionally, warmer gas suppresses low-mass star formation, and decreased opacities result in a greater proportion of gas in diffuse ionized structures.

Breaststroke and butterfly intercycle kinematic variation according to different competitive levels with Statistical Parametric Mapping analysis

Breaststroke and butterfly are complex swimming techniques requiring refined motor skills to perform successfully, with coordinated and consistent interaction between propulsive and resistive forces being decisive when considering swimmers expertise. The current study analysed those techniques intercycle kinematic variation in two swimmers cohorts. Twenty elite and 15 national level swimmers performed one 25 m breaststroke and one 25 m butterfly sprints, with an underwater camera recording images at 120 Hz in the sagittal plane. Mean velocity, maximum and minimum velocities, stroke rate and length, intracycle velocity variation and phases relative duration were calculated for consecutive cycles (elite: five breaststroke/butterfly, national level: eight breaststroke/seven butterfly). The two highest peaks and the lower peak in between in breaststroke were also addressed. Intercycle and inter-groups analysis were performed using ANOVA, ANCOVA and Statistical Parametric Mapping. Elite and national level differed regarding breaststroke mean and maximum velocities, 1st and 2nd peaks and minimum between peaks (1.30 ± 0.02 vs 1.15 ± 0.02 m/s, 2.13 ± 0.05 vs 1.88 ± 0.06 m/s, 1.63 ± 0.05 vs 1.48 ± 0.05 m/s, 2.13 ± 0.05 vs 1.86 ± 0.05 m/s, 1.33 ± 0.04 vs 1.23 ± 0.04 m/s), and butterfly mean, maximum and minimum velocities, stroke rate and intracycle velocity variation, respectively (1.65 ± 0.01 vs 1.50 ± 0.01 m/s, 2.20 ± 0.04 vs 2.09 ± 0.04 m/s, 1.12 ± 0.04 vs 0.79 ± 0.04 m/s, (57.9 ± 0.9 vs 54.9 ± 1.0cycles/min, 18.4 ± 1.3 vs 23.7 ± 1.3 %). Elite and national level swimmers showed consistent breaststroke intercycle kinematic variation, but a butterfly mean velocity decay, with the upper limbs release and recovery, and the outsweep phases originating variability between butterfly cycles. Skill levels contrasted in technical and strategic features at sprint breaststroke and butterfly but showed similar velocity variability between consecutive swimming cycles.