3487 research outputs found
Sort by
Oceanic Wahhabism
Full text linkAt some point around 1810, a leading Wahhabi theologian in the capital of the First Saudi State fielded an intriguing question: Although Wahhabi leaders preached the ideals of enmity and violence toward non-Wahhabi peoples, could Wahhabi merchants travel to non-Wahhabi lands, do business with non-Wahhabi persons, and reside among them while pursuing commercial agend as? The theologian answered yes. I argue that this question and its answer reveal a lived reality in Najd that historians have yet to fully uncover. The theologian’s answer reveals how Arabia’s interior where Wah habismemerged was enmeshed alongside Arabia’s coasts within the broader Afro-Asian Indian Ocean world. Oceanic Wah habism thus situates Najd, the emergence of Wahhabism and the First Saudi State as parts of an interregional world in which Najdi peoples helped forge, consolidate, and sustain political, social, and commercial connections before and after Wahhabism’s emergence. An oceanic, world historical framework highlights individuals, agendas, and events that add new dynamics to the standard tribes-religion-oilframe work for studying Arabia and its history, and helps to continue uncovering a portrait of Arabia—interior and all—as integral to modern world history
Teaching Physician Advocacy: A Collaborative Learning Approach
Full text linkPhysician advocacy is defined as the use of professional expertise to address socioeconomic factors that affect health.1 In the USA, physician advocacy is recognised as a professional responsibility, and the Accreditation Council for Graduate Medical Education has even adopted competencies for post-graduate education. However, there is no consensus on how to incorporate advocacy training into undergraduate medical education
Non-Finite Clause Use in Disciplinary Research Writing: A Formulaic Sequence-Based Functional Comparison Between Expert and Student Writers
Full text linkNon-finite clauses (NFCs), despite their increasingly recognized role in second language (L2) acquisition and academic writing as part of a multidimensional conceptualization of syntactic complexity, have not been analyzed in functional and discipline-specific perspectives. This study addresses this gap by providing a linguistic-descriptive account of NFC use in expert and advanced student English research writing. Using a 2.26-million-word corpus of published research articles and student manuscripts in Agricultural Science, this study profiles the distribution of NFC subtypes and identifies frequent discoursal functions realized by non-finite verb-centered formulaic sequences. The findings reveal significant differences in NFC use across writer groups, with student writers utilizing NFCs less overall and in the majority of structural subtypes. Functional analyses further demonstrate that advanced student writers employed a narrower range of formulaic frames for a narrower range of discoursal functions, highlighting both a reduced lexical repertoire and a rhetorically less sophisticated style, in regard to NFCs. Findings underscore the importance of considering a full range of lexical/phraseological and discourse-functional patterns of clause-level linguistic features, such as NFCs, in order to gain a more pedagogically interpretable understanding of syntactic complexity in L2 and academic writing
Soft Robotic Brittle Star Shows the Influence of Mass Distribution on Underwater Walking
No full textMost walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much higher mass and density compared to the body disk. To date, little is understood about how the relatively unique distribution of mass in these animals influences their locomotion. In this work, we use a brittle star inspired soft robot and computational modeling to examine how the distribution of mass and density in brittle stars affects their movement. The soft robot is fully untethered, powered using embedded shape memory alloy actuators, and designed based on the morphology of a natural brittle star. Computational simulations of the brittle star model are performed in a differentiable robotics physics engine in conjunction with an iterative linear quadratic regulator to explore the relationship between different mass distributions and their optimal gaits. The results from both methods indicate that there are robust physical advantages to having the majority of the mass concentrated in the limbs for brittle star-like locomotion, providing insight into the physical forces at play
Memgb-Diff: Memory-Efficient Multivariate Gaussian Bias Diffusion Model for 3D Bias Field Correction
No full textBias fields inevitably degrade MRI that seriously interferes the diagnosis of physicians for accurate analysis, and removing it is a crucial image analysis task. Generative models (such as GANs) are used for bias field correction, and outperform traditional methods, however are hindered by the high cost of data annotation and instability during training. Recently, the diffusion-based methods have excelled over GANs in many applications, and they are powerful in removing noise from images, while the bias field can be regarded as a smooth noise. However, it is a challenge to directly apply to 3D bias field correction due to sampling inefficiency, the heavy computational demand, and implicit correction process. We propose a Memory-Efficient Multivariate Gaussian Bias Diffusion Model (MeMGB-Diff) that is an explicit, sampling, and memory both efficient diffusion model for 3D bias field correction without using clinical labels. MeMGB-Diff extends the diffusion models to multivariate Gaussian and models the bias field as a multivariate Gaussian variable, allowing direct diffusion and removal of the 3D bias fields without Gaussian noise. For memory efficiency, MeMGB-Diff performs diffusion model in smaller readable image domain at the expense of a negligible accuracy loss, based on the strong correlation among adjacent voxels of bias field. We also propose a loss function to mainly learn the intensity trend, which mainly causes the inhomogeneity of MRI, and effectively increases the correction accuracy. For comprehensive performance comparison, we propose a synthetic method for generating more varied bias fields during testing. Both quantitative and qualitative assessments on synthetic and clinical data confirm the high fidelity and uniform intensity of our results. MeMGB-Diff reduces data size by 64 times to use less memory, improves sampling efficiency by more than 10 times compared to other diffusion-based methods, and achieves optimal metrics, including SSIM, PSNR, COCO, and CV for various tissues. Hence, our MeMGB-Diff is a state-of-the-art (SOTA) method for 3D bias field correction
Alzheimer’s Disease: Relationship of Cognition and Behavior to Neurochemistry
No full textAlzheimer’s disease is characterized by loss of cells and synapses in specific neural systems. The development of more effective therapies will depend on understanding the relationships between this pathology and the cognitive and behavioral impairments. In this review, focusing primarily on work in our laboratory, we will examine both classic and neuropeptide neurotransmitter systems and will discuss conceptual and methodological problems in relating clinical and biological measures
Scalability of a Graph Neural Network in Accurate Prediction of Frictional Contact Networks in Suspensions
No full textDense suspensions often exhibit shear thickening, characterized by a dramatic increase in viscosity under large external forcing. This behavior has recently been linked to the formation of a system-spanning frictional contact network (FCN), which contributes to increased resistance during deformation. However, identifying these frictional contacts poses experimental challenges and is computationally expensive. This study introduces a graph neural network (GNN) model designed to accurately predict FCNs by two dimensional simulations of dense shear thickening suspensions. The results demonstrate the robustness and scalability of the GNN model across various stress levels (s), packing fractions (f), system sizes, particle size ratios (D), and amounts of smaller particles. The model is further able to predict both the occurrence and structure of a FCN. The presented model is accurate and interpolates and extrapolates to conditions far from its control parameters. This machine learning approach provides an accurate, lower cost, and faster predictions of suspension properties compared to conventional methods, while it is trained using only small systems. Ultimately, the findings in this study pave the way for predicting frictional contact networks in real-life large-scale polydisperse suspensions, for which theoretical models are largely limited owing to computational challenges
Computed Microtomographic Imaging of Revascularization During Healing of Achilles Tendon Injury
No full textAngiogenesis in injured tendons may contribute to regeneration, but quantifying it post-injury has been mostly limited to 2D semi-quantitative histology. This study aimed to develop micro-CT as a 3D tool to quantitatively assess tendon blood vessels in an experimental animal model. Adult male Wistar rats (N = 36) had injuries induced in their Achilles tendons by needle insertion. The study included three post-injury groups: 12 hours post-injury (12H), 3 weeks post-injury (3W), and 8 weeks post-injury (8W). The uninjured left Achilles tendon served as the control for each group. Intravital cardiac perfusion with barium sulfate enhanced contrast between tendon and vasculature. Micro-CT imaging was performed on dissected tendons in proximal, middle, and distal regions to assess total volume, object count, and structural thickness from 3D reconstructions. Control tendons showed region-specific and age-related vascular changes, with a significant portion of blood supply originating from the muscle-tendon junction. Injury-induced vascular changes were detected by 3D micro-CT analysis. The 12H, 3W, and 8W groups exhibited increased total volume, structural thickness, and object volume in all tendon regions compared to controls (p \u3c 0.05). Structure separation was also higher in the middle and distal regions of these groups (p \u3c 0.05). Micro-CT combined with intravital contrast perfusion allows for 3D quantification of Achilles tendon angiogenesis, revealing a significant and sustained increase in vascularity post-injury, making it a valuable tool for studying vascularization during tendon injury and repair
A Continuous-Heat-Flux Phase Change Model for Simulating Realistic Two-Phase Unsaturated Evaporation Processes
No full textAccurately modeling liquid-vapor mass transfer rates is essential for optimizing cryogenic fluid management processes critical to advancing future space missions. This study introduces a continuous-heat-flux phase change model proposed to simulate conditions observed in realistic two-phase unsaturated evaporation phenomena. The mass transfer rate across the two-phase interface is calculated directly based on the local interfacial continuous heat flux on both liquid and vapor phases, effectively accounting for superheated, saturated, and subcooled liquid effects without requiring any empirical tuning parameters. Moreover, phase change occurs exclusively within interfacial cells, ensuring the sharp representation of deformed evaporating interfaces with high accuracy. The proposed model is implemented using user-defined functions in ANSYS Fluent and evaluated against various benchmark evaporation problems, including Stefan and film boiling test cases with nonequilibrium (temperature other than saturation) in a single phase and in both phases. The numerical results, encompassing liquid-vapor interface evolution and temperature distributions, exhibit excellent agreement with published analytical and numerical solutions. Additionally, the model is applied to simulate the complex heat and mass transfer processes in cryogenic tank self-pressurization under two heating configurations: vapor heating and uniform heating. The results demonstrate good agreement with the tank pressure rise trends reported in the literature, validating the applicability of the model to practical evaporation scenarios
Effect of Anesthesia and Diurnal Variation on Chronic Vagus Nerve Activity in Rats
No full textThe vagus nerve, serving as a pivotal link between the brain and vital organs, regulates crucial physiological functions. It plays a central role in maintaining homeostasis within the body and must dynamically adapt to changing conditions such as anesthesia or sleep. While vagal tone, typically estimated indirectly from heart rate variability, has been extensively studied, direct measurement of vagal activity during sleep and anesthesia remains unreported to date. Recent technological advancements have facilitated the recording of vagus nerve activity in freely moving rodents using small, highly flexible carbon nanotube yarns. Consequently, it is now feasible to directly investigate vagal activity during events known to impact homeostasis, such as diurnal variations and anesthesia. In this study, we explore the relationship between anesthesia and vagus nerve activity by comparing the effects of 2% isoflurane anesthesia with activity in freely moving male Sprague Dawley rats. The findings reveal that 2% isoflurane anesthesia significantly suppresses vagus nerve activity, and normal activity levels do not resume until 2 h after the termination of the anesthesia supply. Additionally, we examine the influence of diurnal variations on vagus nerve activity and observe a notable presence of diurnal variations in vagal activity patterns. These results provide insights into the interaction among anesthesia, diurnal variations, and vagal tone, offering valuable understanding of the autonomic nervous system during critical physiological states
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇