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Although extensive research has been carried out on collocation processing, it is still unclear how cross-language overlap and transparency influence the processing of collocations by L2 learners. In the current study, a phrase judgment task was used to investigate the processing of congruent (i.e., exist in both English and Arabic) and incongruent collocations (i.e., exist only in English) by Arabic non-native speakers of English. The semantic transparency of the items was controlled for. Results demonstrated the effect of congruency on processing: congruent items yielded more correct responses and faster response times than incongruent items. The effect of congruency was modulated by proficiency, with congruency having a stronger effect on lower-proficiency learners than higher-proficiency learners. Transparency had no effect, with no differences in response times and accuracy between transparent and opaque collocations. The findings have implications for the learning and teaching of L2 collocations.

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Soil moisture plays an important role in the water and heat exchanges between the land surface and atmosphere, and it has great importance for agricultural production, ecological planning, and water resources management. Although microwave remote sensing has been widely used in large-scale soil moisture monitoring, the accuracy of the downscaled retrieval results cannot be guaranteed for regions with high vegetation coverage and high soil heterogeneity. To address these challenges, this study built soil moisture indice set based on MODIS and elevation data by calculating the Pearson correlation coefficient (R) and Maximum Information Coefficient (MIC), then constructed decision tree models (Gradient Boosting Decision Tree and Random Forest) about the indice set and low-resolution Soil Moisture Active Passive (SMAP) by using two ensemble learning methods (Bagging and Boosting). The models were applied to the high-resolution soil moisture indices in Jilin Province for the years 2017 to 2020 to generate 1 km-resolution products. In the validation process, Triple Collocation Analysis (TCA), comparison of soil moisture maps with coarse and fine resolution, and in-situ measurements in Lishu County, Tongyu County, and Jilin City were used to evaluate the differences between downscaling soil moisture results and ground observations at network, seasonal and point scales. The results were as follows: (1) The correlation coefficient (R2) calculated by the TCA method was 0.733 (GBDT_36km) > 0.649 (RF_36km), and the error variance was 0.0004 (GBDT_36km) < 0.00058 (RF_36km). (2) R at network scale was 0.798 (GBDT_SM) > 0.662 (RF_SM), RMSE was 0.040 (GBDT_SM) < 0.044 (RF_SM), the point scale R was 0.864 (GBDT_SM) > 0.833 (RF_SM), RMSE was 0.029 (GBDT_SM) < 0.039 (RF_SM). The R in four stages of the growth period was GBDT_SM > RF_SM, RMSE was GBDT_SM < RF_SM. In conclusion, the GBDT and RF models can reliably downscale soil moisture in Jilin Province, and the Boosting ensemble learning method represented by GBDT had a better estimation performance.

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This study presents a computational investigation of a stochastic Zika virus along with optimal control model using the Legendre spectral collocation method (LSCM). By accumulation of stochasticity into the model through the proposed stochastic differential equations, we appropriating the random fluctuations essential in the progression and disease transmission. The stability, convergence and accuracy properties of the LSCM are conscientiously analyzed and also demonstrating its strength for solving the complex epidemiological models. Moreover, the study evaluates the various control strategies, such as treatment, prevention and treatment pesticide control, and identifies optimal combinations that the intervention costs and also minimize the proposed infection rates. The basic properties of the given model, such as the reproduction number, were determined with and without the presence of the control strategies. For R 0 < 0 , the model satisfies the disease-free equilibrium, in this case the disease die out after some time, while for R 0 > 1 , then endemic equilibrium is satisfied, in this case the disease spread in the population at higher scale. The fundamental findings acknowledge the significant impact of stochastic phonemes on the robustness and effectiveness of control strategies that accelerating the need for cost-effective and multi-faceted approaches. In last the results provide the valuable insights for public health department to enabling more impressive mitigation of Zika virus outbreaks and management in real-world scenarios.

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Pauses in speech are indicators of cognitive effort during language production and have been examined to inform theories of lexical, grammatical and discourse processing in healthy speakers and individuals with aphasia (IWA). Studies of pauses have commonly focused on their location and duration in relation to grammatical properties such as word class or phrase complexity. However, recent studies of speech output in aphasia have revealed that utterances of IWA are characterised by stronger collocations, i.e., combinations of words that are often used together. We investigated the effects of collocation strength and lexical frequency on pause duration in comic strip narrations of IWA and non-brain-damaged (NBD) individuals with part of speech (PoS; content and function words) as covariate. Both groups showed a decrease in pause duration within more strongly collocated bigrams and before more frequent content words, with stronger effects in IWA. These results are consistent with frameworks which propose that strong collocations are more likely to be processed as holistic, perhaps even word-like, units. Usage-based approaches prove valuable in explaining patterns of preservation and impairment in aphasic language production.

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This study investigated how input modes (reading vs. listening) and learners' perceptual learning style (visual vs. auditory) affected the incidental learning of collocations. A total of 182 college students were first assigned to either a visual or auditory group based on their performance on a perceptual learning style questionnaire. Each style group was subsequently subdivided into three groups who were exposed to a series of texts containing unfamiliar collocation items under one of the input conditions: written input, aural input, or no input. Results of the study indicated that both written and aural input led to gains in collocational knowledge, and aural input was more effective than written input. Furthermore, the study provided empirical evidence that there was a moderating role of perceptual learning style on incidental collocation learning. The auditory learners under aural input showed the highest rate of collocation learning among all treatment subgroups.

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In this study, we develop a numerical optimization approach to address the challenge of optimal control in the spread of COVID-19. We evaluate the impact of various control strategies aimed at reducing the number of exposed and infectious individuals. Our novel approach employs Legendre wavelets, their derivative operational matrix, and a collocation method to transform the COVID-19 transmission optimal control model into a nonlinear programming (NLP) problem. To solve this problem, we employ a coronavirus optimization algorithm (COVIDOA) to determine the optimal control, state variables, and objective value. We investigate three control plans for this highly contagious disease, focusing on individual protection, rapid detection and treatment, detection with delay in treatment, and environmental viral dispersion as time-based control functions. These strategies are applied within an SEIR-type control model specific to COVID-19 in China, designed to mitigate disease spread. Lastly, we analyze the effects of various parameters within the COVID-19 spread model. Our numerical results highlight the significant impact of strategies that minimize the number of exposed and infectious individuals, particularly those related to rapid detection, detection delay, and environmental viral dispersion, in controlling and preventing the transmission of the COVID-19 virus.

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In this paper, we introduce a general numerical method to approximate the reproduction numbers of a large class of multi-group, age-structured, population models with a finite age span. To provide complete flexibility in the definition of the birth and transition processes, we propose an equivalent formulation for the age-integrated state within the extended space framework. Then, we discretize the birth and transition operators via pseudospectral collocation. We discuss applications to epidemic models with continuous and piecewise continuous rates, with different interpretations of the age variable (e.g., demographic age, infection age and disease age) and the transmission terms (e.g., horizontal and vertical transmission). The tests illustrate that the method can compute different reproduction numbers, including the basic and type reproduction numbers as special cases.

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Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

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Sturm-Liouville problems have yielded the biggest achievement in the spectral theory of ordinary differential operators. Sturm-Liouville boundary value issues appear in many key applications in natural sciences. All the eigenvalues for the standard Sturm-Liouville problem are guaranteed to be real and simple, and the related eigenfunctions form a basis in a suitable Hilbert space. This article uses the weighted residual collocation technique to numerically compute the eigenpairs of both regular and singular Strum Liouville problems. Bernstein polynomials over [0,1] has been used to develop a weighted residual collocation approach to achieve an improved accuracy. The properties of Bernstein polynomials and the differentiation formula based on the Bernstein operational matrix are used to simplify the given singular boundary value problems into a matrix-based linear algebraic system. Keeping this fact in mind such a polynomial with space defined collocation scheme has been studied for Strum Liouville problems. The main reasons to use the collocation technique are its affordability, ease of use, well-conditioned matrices, and flexibility. The weighted residual collocation method is found to be more appealing because Bernstein polynomials vanish at the two interval ends, providing better versatility. A multitude of test problems are offered along with computation errors to demonstrate how the suggested method behaves. The numerical algorithm and its applicability to particular situations are described in detail, along with the convergence behavior and precision of the current technique.

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A novel (nonlinear) mathematical model for the transmission of Coronavirus 19 (COVID-19) with eight compartments and considering the impact of vaccination is examined in this manuscript. The qualitative behavior of the system such as the boundedness of solutions, the basic reproduction number, and the stability of the equilibrium points is investigated in detail. Some domestic real data collected from the Kerman University of Medical Science (KUMC) is used to estimate the parameters of the proposed model. We predict the dynamical behavior of the system through numerical simulations based on a combined spectral matrix collocation methodology. In this respect, we first linearize the nonlinear system of equations by the method of quasilinearization (QLM). Hence, the shifted version of Chebyshev polynomials of the second kind (SCPSK) is utilized along with the domain-splitting strategy to acquire the solutions of the system over a long time interval. The uniform convergence and upper bound estimation of the SCPSK bases are proved in a rigorous manner. Moreover, the technique of residual error functions is used to testify the accuracy of the QLM-SCPSK method. The presented numerical results justify the robustness and good accuracy of the QLM-SCPSK technique. The achieved numerical orders of convergence indicate that the QLM-SCSK algorithm has exponential rate of convergence. Using the linearization technique in one hand and the domain-splitting strategy on the other hand, enable us to predict the behaviour of similar disease problems with high accuracy and maximum efficiency on an arbitrary domain of interest.

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As a novel fluid of functional material, magnetohydrodynamic (MHD) micropolar fluid has the special properties of light, heat, magnetic and so on. It is of highly practical significance. The characteristics of flow, heat and mass transfer in MHD micropolar nanofluid boundary layer past a stretching plate are investigated based on the micropolar fluid theory in the present numerical work. In the presence of magnetic field, viscous dissipation and the cross-diffusion caused by Dufour effect and Soret effect are considered. First order slip velocity condition is employed. Mathematical models are built based on the assumptions. Collocation spectral method (CSM) via matrix multiplication is adopted to solve the two-dimensional dimensionless nonlinear partial governing equations. The program codes based on CSM is developed, validated and employed. The coupled effects of microrotation, Dufour effect, Soret effect, magnetic field as well as first order slip velocity boundary condition on the flow, heat and mass transfer are revealed. Besides, the variation trends of local Nusselt number and Sherwood number are analyzed in detail. The numerical results indicate that the fluid flow can be suppressed obviously in the consideration n of slip condition and magnetic field. As slip parameter δ and magnetic parameter M rise, the velocity in the boundary layer becomes lower gradually; further, both temperature and concentration increase. On the other hand, the opposite trend can be noticed with the effect of material parameter K. Moreover, Ec and Df augment the temperature; while, Sr leads to an upsurge in concentration. The temperature rises by about 79.73% with Dufour effect and Sh enlarges by a factor of about 38.15% with Soret effect. The concentration boundary layer decreases by about 37.50% is when K=5.0.

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This work presents dynamic optimization strategies of batch hydrothermal liquefaction of two microalgal species, Aurantiochytrium sp. KRS101 and Nannochloropsis sp. to optimize the reactor temperature profiles. Three dynamic optimization problems are solved to maximize the endpoint biocrude yield, minimize the final time, and minimize the reactor thermal energy. The biocrude maximization and time minimization problems demonstrated 11% and 6.18% increment in the optimal biocrude yields and reduction of 78.2% and 61.66% in batch times compared to the base cases for the microalgae with higher lipid and protein fractions, respectively. The energy minimization problem revealed a significant reduction in the reactor thermal energies to generate the targeted biocrude yields compared to the biocrude maximization. Therefore, the identified optimal temperature trajectories outperformed the conventional fixed temperature profiles and could improve the overall economics of the batch bio-oil production from the algal-based biorefineries by significantly enhancing the reactor performance.

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It has been well documented that formulaic language (such as collocations; e.g., provide information) enjoys a processing advantage over novel language (e.g., compare information). In natural language use, however, many formulaic sequences are often inserted with words intervening in between the individual constituents (e.g., provided information → provide some of the information). Whether or not the processing advantage persists in nonadjacent forms remains largely unknown. The present study thus sought to address this gap by recording the eye movements of Chinese native speakers when they were reading sentences embedded with formulaic sequences (high frequency collocations) versus novel phrases (low frequency controls), in their adjacent (e.g., 'resolve difficulties' vs. 'experience difficulties'), short-insertion (e.g., 'resolve these difficulties' vs. 'experience these difficulties'), and long-insertion forms (e.g., 'resolved so many difficulties' vs. 'experienced so many difficulties'). Results suggested that the processing advantage for formulaic language over novel language existed not only in their adjacent form, but also in their short-insertion form, albeit the magnitude of the processing advantage diminished with the increase of insertion length. The persistence of FL processing advantage is in line with usage-based approach to language learning, processing, and use.

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The subject of the article is devoted to the development of a matrix collocation technique based upon the combination of the fractional-order shifted Vieta-Lucas functions (FSVLFs) and the quasilinearization method (QLM) for the numerical evaluation of the fractional multi-order heat conduction model related to the human head with singularity and nonlinearity. The fractional operators are adopted in accordance with the Liouville-Caputo derivative. The quasilinearization method (QLM) is first utilized in order to defeat the inherent nonlinearity of the problem, which is converted to a family of linearized subequations. Afterward, we use the FSVLFs along with a set of collocation nodes as the zeros of these functions to reach a linear algebraic system of equations at each iteration. In the weighted [Formula: see text] norm, the convergence analysis of the FSVLFs series solution is established. We especially assert that the expansion series form of FSVLFs is convergent in the infinity norm with order [Formula: see text], where K represents the number of FSVLFs used in approximating the unknown solution. Diverse computational experiments by running the presented combined QLM-FSVLFs are conducted using various fractional orders and nonlinearity parameters. The outcomes indicate that the QLM-FSVLFs produces efficient approximate solutions to the underlying model with high-order accuracy, especially near the singular point. Furthermore, the methodology of residual error functions is employed to measure the accuracy of the proposed hybrid algorithm. Comparisons with existing numerical models show the superiority of QLM-FSVLFs, which also is straightforward in implementation.

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In this study, an approach using gravity observations utilizing the Least Squares Collocation (LSC) method is developed with the aim of mapping the depth spatial variability of the Mohorovicic discontinuity. This approach is based on a spherical two-layer isostatic model where the exterior gravity field only varies because of the shifting topographic masses and the related isostatic adjustment since it is believed that the Earth's core has a uniform density distribution. Assuming mass conservation between the Moho column of height δR with respect to Rm representing the mean Moho and following a Helmert condensation approach, the relationship between the surface layer density to the potential δT can be obtained and δR can be estimated via LSC from observed values of any functional derived from δT. With such approach, the depth of Moho in the Iranian Plateau is estimated from Trr data generated by GOCO06S model reduced by topography, bathymetry and sediments effects by considering GEBCO2021 and CRUST1.0 models. The needed a-priori assumptions on Rm and the density contrast Δρ are tuned so to obtain the best fit with seismic Moho depths reported by literature. 73 stations were matched with 3 km of standard deviation, which is coherent with the expected accuracy of the benchmark values. The remaining greater discrepancies showed to be clustered in defined areas like the Zagros chain and the reliefs along the Caspian coastline and the East borders.

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We propose a method for computing the Lyapunov exponents of renewal equations (delay equations of Volterra type) and of coupled systems of renewal and delay differential equations. The method consists of the reformulation of the delay equation as an abstract differential equation, the reduction of the latter to a system of ordinary differential equations via pseudospectral collocation and the application of the standard discrete QR method. The effectiveness of the method is shown experimentally and a MATLAB implementation is provided.

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Introduction: Spaceflight is associated with substantial and variable musculoskeletal (MSK) adaptations. Characterisation of muscle and joint loading profiles can provide key information to better align exercise prescription to astronaut MSK adaptations upon return-to-Earth. A case-study is presented of single-leg hopping in hypogravity to demonstrate the additional benefit computational MSK modelling has when estimating lower-limb MSK loading. Methods: A single male participant performed single-leg vertical hopping whilst attached to a body weight support system to replicate five gravity conditions (0.17, 0.25, 0.37, 0.50, 1 g). Experimental joint kinematics, joint kinetics and ground reaction forces were tracked in a data-tracking direct collocation simulation framework. Ground reaction forces, sagittal plane hip, knee and ankle net joint moments, quadriceps muscle forces (Rectus Femoris and three Vasti muscles), and hip, knee and ankle joint reaction forces were extracted for analysis. Estimated quadriceps muscle forces were input into a muscle adaptation model to predict a meaningful increase in muscle cross-sectional area, defined in (DeFreitas et al., 2011). Results: Two distinct strategies were observed to cope with the increase in ground reaction forces as gravity increased. Hypogravity was associated with an ankle dominant strategy with increased range of motion and net plantarflexor moment that was not seen at the hip or knee, and the Rectus Femoris being the primary contributor to quadriceps muscle force. At 1 g, all three joints had increased range of motion and net extensor moments relative to 0.50 g, with the Vasti muscles becoming the main muscles contributing to quadriceps muscle force. Additionally, hip joint reaction force did not increase substantially as gravity increased, whereas the other two joints increased monotonically with gravity. The predicted volume of exercise needed to counteract muscle adaptations decreased substantially with gravity. Despite the ankle dominant strategy in hypogravity, the loading on the knee muscles and joint also increased, demonstrating this provided more information about MSK loading. Discussion: This approach, supplemented with muscle-adaptation models, can be used to compare MSK loading between exercises to enhance astronaut exercise prescription.

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Background: In transtibial limb loss, computer simulations suggest that the maintenance of muscle strength between pre- and post-limb loss can maintain the pre-limb loss metabolic cost. These results are consistent with comparable costs found experimentally in select cases of high functioning military service members with transtibial limb loss. It is unlikely that similar results would be found with transfemoral limb loss, although the theoretical limits are not known. Here we performed optimal control simulations of walking with and without an above-knee prosthesis to determine if transfemoral limb loss per se increases the metabolic cost of walking. Methods: OpenSim Moco was used to generate optimal control simulations of walking in 15 virtual "subjects" that minimized the weighted sum of (i) deviations from average able-bodied gait mechanics and (ii) the gross metabolic cost of walking, pre-limb loss in models with two intact biological limbs, and post-limb loss with one of the limbs replaced by a prosthetic knee and foot. No other changes were made to the model. Metabolic cost was compared between pre- and post-limb loss simulations in paired t-tests. Results: Metabolic cost post-limb loss increased by 0.7-9.3% (p < 0.01) depending on whether cost was scaled by total body mass or biological body mass and on whether the prosthetic knee was passive or non-passive. Conclusions: Given that the post-limb loss model had numerous features that predisposed it to low metabolic cost, these results suggest transfemoral limb loss per se increases the metabolic cost of walking. However, the large differences above able-bodied peers of ∼20-45% in most gait analysis experiments may be avoidable, even when minimizing deviations from able-bodied gait mechanics. Portions of this text were previously published as part of a preprint (https://www.biorxiv.org/content/10.1101/2023.06.26.546515v2.full.pdf).

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BACKGROUND: This study reports on new contexts in which formulaic language has been used in the years since 2013 when the last synthesis was carried out. The background presents an old but still useful definition and lists themes under which research was arranged in 2013 and which continue to be used. AIMS: This study has a particular emphasis on the relevance of formulaic language to people living with dementia. METHODS: Section 3, identifying new directions, reviews new 'third waves' of research priorities in several fields in which formulaic sequences play a major role, including sociolinguistic variation, corpus-based and corpus-driven analyses, pragmatics, human-computer interaction, and psycholinguistics, all of which are relevant to speech-language therapists. Section 4, outreach and expansions, illustrates new contributions from cognitively impaired person-to-person exchanges in online environments, recent examinations of infant- and pet-directed speech incorporating formulaic language, and online graphic explorations such as emojis. Section 5 focuses on growth of research in theoretical and clinical applications by Van Lancker Sidtis, as illustrated by references to her recent work. MAIN CONTRIBUTION: The paper's main contribution is to summarize the work on formulaic language over the last 10 years, to indicate its continued importance and relevance in ordinary conversation, and especially in allowing people living with dementia to continue to interact with others. CONCLUSION: The paper concludes by suggesting that more focus be placed on the analysis of formulaic language with an emphasis on its relevance for speech-language therapists and other clinicians. WHAT THIS PAPER ADDS: What is already known on the subject Research has been growing since the late 1970s and early 1980s on non-propositional language (as opposed at that time to the Chomskyan paradigm) and especially on lexical bundles, idioms, second language acquisition and multiword expressions. Studies beginning with Hughlings Jackson (1874) have been annotated through early 2012 (Wray, 2013). What this study adds This study examines 'third waves' in pragmatics, sociolinguistics and areas of neurology and speech perception contributing to what Van Lancker Sidtis (2021) calls the third wave of acceptance of the range and depth of formulaic sequences in ordinary or familiar language. What are the clinical implications of this work? Conversations with pet robots or web-based composition with emojis are but two of the developing areas built on formulaic sequences currently being used for communication interventions with persons living with dementia or other major neurocognitive disorder. Overviews of major contributions in theory and social contexts by Wray (2020, 2021) and theoretical and cognitive applications by Van Lancker Sidtis (2021) detail new areas for the study of formulaic sequences and their contributions to a range of neurocognitive disorders.

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This study aimed at studying the variational effect of nonlinear thermal radiation on the flow of Casson nanofluid ( Al 2 O 3 - Blood ${\rm Al}_2 {\rm O}_3\text{-}{\rm Blood}$ ) through a porous microchannel with entropy generation. The novelty of this investigation includes the incorporation of porous media, nonlinear radiative heat flux, and convective heat transfer at the channel interface into the energy equation, which results in an enhanced analysis for the cooling design and heat transfer of microdevices that utilize Al 2 O 3 - Blood ${\rm Al}_2 {\rm O}_3\text{-}{\rm Blood}$ nanofluid flow. Particularly, alumina (Al2 O3 ) is considered as the nanoparticles in this blood base fluid due to associated advanced pharmaceutical applications. With dimensionless variables being utilized, the governing equations are minimized to their simplest form. The Chebysev-based collocation technique was employed to numerically solve the resultant ordinary differential equations with the associated boundary conditions and the impact of flow, thermal, and irreversibility distribution fields are determined through graphs. The findings identified that higher levels of Hartmann number produce the Lorentz force, which limits fluid flow and lowers velocity, the response of nonlinear thermal radiation diminishes the heat transfer rate, and a rise in the Casson parameter also reduces the Bejan number. The results of this research can be used to improve heat transfer performance in biomedical devices, design-efficient energy conversion cycles, optimize cooling systems, and cover a wide range of energy technologies from renewable energy to aerospace propulsion.