bluuebunny/crossref_metadata_2025_split huggingface dataset:
Torque- and Muscle-Driven Flexion Induce Disparate Risks of In Vitro Herniation: A Multiscale and Multiphasic Structure-Based Finite Element Study
Authors: Zhou Minhao , Huff Reece D. , Abubakr Yousuf , O'Connell Grace D. 
Published: January 2022

AbstractThe intervertebral disc is a complex structure that experiences multiaxial stresses regularly. Disc failure through herniation is a common cause of lower back pain, which causes reduced mobility and debilitating pain, resulting in heavy socioeconomic burdens. Unfortunately, herniation etiology is not well understood, partially due to challenges in replicating herniation in vitro. Previous studies suggest that flexion elevated risks of herniation. Thus, the objective of this study was to use a multiscale and multiphasic finite element model to evaluate the risk of failure under torque- or muscle-driven flexion. Models were developed to represent torque-driven flexion with the instantaneous center of rotation (ICR) located on the disc, and the more physiologically representative muscle-driven flexion with the ICR located anterior of the disc. Model predictions highlighted disparate disc mechanics regarding bulk deformation, stress-bearing mechanisms, and intradiscal stress–strain distributions. Specifically, failure was predicted to initiate at the bone-disc boundary under torque-driven flexion, which may explain why endplate junction failure, instead of herniation, has been the more common failure mode observed in vitro. By contrast, failure was predicted to initiate in the posterolateral annulus fibrosus under muscle-driven flexion, resulting in consistent herniation. Our findings also suggested that muscle-driven flexion combined with axial compression could be sufficient for provoking herniation in vitro and in silico. In conclusion, this study provided a computational framework for designing in vitro testing protocols that can advance the assessment of disc failure behavior and the performance of engineered disc implants.
Spectral Bandedness in High-Fidelity Computational Fluid Dynamics Predicts Rupture Status in Intracranial Aneurysms
Authors: MacDonald Daniel E. , Najafi Mehdi , Temor Lucas , Steinman David A. 
Published: January 2022

Abstract
Recent studies using high-fidelity computational fluid dynamics (CFD) have revealed high-frequency flow instabilities consistent with clinical reports of bruits and “musical murmurs”, which have been speculated to contribute to aneurysm growth and rupture. We hypothesized that harmonic flow instabilities (“spectral bandedness”) in aneurysm CFD data may be associated with rupture status. Before testing this hypothesis, we first present a novel method for quantifying and visualizing spectral bandedness in cardiovascular CFD datasets based on musical audio-processing tools. Motivated by previous studies of aneurysm hemodynamics, we also computed a selection of existing metrics that have demonstrated association with rupture in large studies. In a dataset of 50 bifurcation aneurysm geometries modeled using high-fidelity CFD, our spectral bandedness index (SBI) was the only metric significantly associated with rupture status (AUC = 0.76, p = 0.002), with a specificity of 79% (correctly predicting 19/24 unruptured cases) and sensitivity of 65% (correctly predicting 17/26 ruptured cases). Three-dimensional flow visualizations revealed coherent regions of high SBI to be associated with strong near-wall inflow jets and vortex-shedding/flutter phenomena in the aneurysm sac. We speculate that these intracycle, coherent flow instabilities may preferentially contribute to the progressive degradation of the aneurysm wall through flow-induced vibrational mechanisms, and that their absence in high-fidelity CFD may be useful for identifying intracranial aneurysms at lower risk of rupture.
Integral Form of the Heat Transfer Equation With Arbitrarily Moving Boundary and Arbitrary Heat Source
Authors: Novozhilov V. , Kulish V. 
Published: January 2022

Abstract
For the first time, an integral form of one-dimensional heat transfer equation in a semi-infinite domain with a boundary, moving arbitrarily in time, and a heat source, depending arbitrarily on time and space location, is obtained. The obtained integral equation relates time histories of the temperature and its gradient at the boundary of the domain with the temperature at any given point inside or at the boundary of the domain. In the latter case, it delivers closed form integral equation for the rate of boundary movement in nonlinear problems where the time history of boundary movement is one of problem unknowns. The obtained equation accounts explicitly for the presence of an arbitrary heat source in the domain, while other existing methods do not allow a closed integral formulation to be obtained in such a case. The equation may be used for an analytical investigation of several types of boundary value problems (BVPs), as well as for numerical solution of such problems. Particular cases of this equation with a trivial heat source are known to demonstrate chaotic behavior. It is expected that the same is true for some nontrivial heat source functions, and this conjecture will be explored in subsequent publications.
Generalized Bio-Heat Transfer Model Combining With the Relaxation Mechanism and Nonequilibrium Heat Transfer
Authors: Li Meijun , Wang Yingze , Liu Dong 
Published: January 2022

Abstract
The heat transport within living biological tissue is a complicated process coupled with various physiological activities. The nonhomogeneous inner anatomical structure leads to an essential difference from classical heat transfer. The generalized model of bioheat transfer involving the relaxation mechanism as well as nonequilibrium heat transfer is first proposed to explore the heat transport properties within living biological tissues. Due to the volume averaging theory, the new local instantaneous energy equations of blood and tissue are constructed separately by introducing the phase lags, in which the delay effect between the heat flux and temperature gradient absent in existing generalized models is considered. The effective phase lags covering the delay effect and nonequilibrium effect are obtained on this basis. A detailed parametric study has been conducted to estimate the values of these effective phase lags and evaluate their contributions on heat transport within living biological tissues. The results state that the effective phase lags depend on the anatomical structure of tissues and its physical properties. The delay effect is dominated in general and has a higher temperature elevation than that induced by nonequilibrium effect only.
Investigation of the Effect of the Stages Number, the Impeller Outlet Width, and the Impeller Outlet Angle on the Performance of an Industrial Electric Submersible Pump
Authors: Firatoglu Zeynel A. , Alihanoglu Mustafa N. 
Published: January 2022

Abstract
This study has investigated the effect of the number of stages, the blade outlet spacing, and the blade outlet angle of a selected industrial submersible pump on the pump performance. The main steps in the study are outlined below: Firstly, the operating characteristics in different stages of a selected industrial submersible pump were measured by the experiment. Following the measurements, the effects of two basic geometric parameters, such as impeller outlet width and impeller outlet angle on the pump performance were examined with computational fluid dynamics (CFD) simulations verified by the experimental measurements. It was seen that the geometric parameters, which were considered in the simulations, changed the size of the time-dependent variables, but the flow structure did not. Another striking finding from the CFD simulations carried out is it has been observed that while geometric arrangements have a partial effect on the flow structure along with the pump, they cause a difference in the critical values on the basic variables that define pump performance, such as pressure.
Numerical Simulation and Experimental Study on Hydraulic Bursting Failure of Aluminum Alloy T-Shaped Tube in Hydroforming
Authors: Fan Yubin , Xu Xuefeng , Wu Yiwang , Wei Liming , Huang Lin , Xiao Yao 
Published: January 2022

Abstract
In this work, the hydraulic bursting method was used to investigate the bursting failure of aluminum alloy as-formed T-shaped tube by hydroforming, which consisted of the rupture region and bursting pressure. The bursting pressure was calculated by theoretical formula and two finite element models of T-shaped tubes with uniform thickness and hydroforming thickness were established. The hydraulic bursting failure simulation and experiment was carried out. In the simulation results, the failure directions of T-shaped tubes with uniform thickness were along the circumferential direction, while the failure directions of T-shaped tubes with hydroforming thickness were along axis of the main tube. Through stress analysis, the allowable circumferential film stress was about 1/2 of the allowable axial film stress, which indicated that the rupture failure should be along axis of the main tube. The failure location appeared at the shoulder. The fractured morphology was observed by scanning electron microscopy (SEM). A large number of equiaxed dimples and secondary phase particles appeared in the failure location. The experimental results were consistent with the simulation results of the as-formed T-shaped tube by hydroforming. Finally, the accuracy of the bursting pressure formula was evaluated according to the experimental results.
Robust Vibration Control for Active Suspension System of In-Wheel-Motor-Driven Electric Vehicle Via μ-Synthesis Methodology
Authors: Jin Xianjian , Wang Jiadong , Yan Zeyuan , Xu Liwei , Yin Guodong , Chen Nan 
Published: January 2022

Abstract
This paper proposes a robust vibration controller design for active suspension system of in-wheel-motor-driven electric vehicles (IWMD-EVs) based on unified μ-synthesis framework. First, multiple parameter uncertainties and unmodeled high-order dynamics of the suspension are analyzed and discussed. By applying the mixed uncertainties and linear fraction transformation, model perturbations are separated from the suspension system and their perturbation bounds can also be limited. Then, the uncertain quarter-vehicle active suspension model with dynamic damping in-wheel-motor-driven system is established, in which in-wheel motor is suspended as a dynamic vibration absorber. The resulting robust μ-synthesis feedback controller of generalized closed-loop active suspension system is designed with the concept of structured singular value (SSV) μ and μ-synthesis theoretics, and solved via comprehensive solution of the D–G–K iteration. The μ analysis results show that the μ-controller possesses less conservative stability and performance margins as compared to the H∞ method against system uncertainties. Furthermore, simulations of nominal and perturbed suspension systems are implemented and the corresponding frequency and time-domain responses are compared, and then simulation results confirm that the developed μ-controller is capable of attenuating the negative vibration of the active suspension system compared with H∞ controller and passive suspension.
Review of Methods and Results for Reactor Physics Analysis of Thorium-Based Fuels From Irradiation Experiments Conducted in the National Research Universal Reactor
Authors: Sinh Nguyen T. , Wang Xiaolin , Bromley Blair P. 
Published: January 2022

Abstract
The development of advanced fuels and fuel cycles for conventional Generation III+ reactors, advanced reactors (such as Generation IV), and small modular reactors will help ensure the long-term sustainability and safety of the use of nuclear energy. Thorium-based fuels are an example of an advanced fuel that could augment and extend uranium resources. As part of previous efforts in Canada to investigate the use of thorium-based fuels for potential use in pressure-tube heavy-water reactors and other technologies, irradiation experiments with various thorium-containing fuels had been conducted in the National Research Universal (NRU) reactor at the Chalk River Laboratories. The NRU reactor physics computational tools and methods, developed initially for conventional enriched uranium fuel, had also been extended for analysis of thorium-based fuel experiments, with most satisfactory results. In this study, a number of physics and operation factors have been analyzed to quantify their effects on the production and burnup of 233U in thorium-based fuel, as well as to improve both the analysis and the use of thorium fuels and fuel cycles.
The effects of Pilates on health-related outcomes in individuals with increased risk of fracture: a systematic review
Authors: McLaughlin Emily Claire , Bartley Joan , Ashe Maureen C. , Butt Debra A. , Chilibeck Philip D. , Wark John D. , Thabane Lehana , Stapleton Jackie , Giangregorio Lora M. 
Published: January 2022

This systematic review examined the effect of Pilates on health-related outcomes in individuals with increased fracture risk to inform the 2021 Clinical Practice Guidelines for Management of Osteoporosis and Fracture Prevention in Canada. Seven electronic databases were searched to December 2020. Studies of Pilates in men and postmenopausal women aged ≥50 years with low bone mineral density (BMD), history of fragility fracture, or moderate-high risk of fragility fracture were included. Two reviewers independently screened studies and performed risk of bias assessment. Of 7286 records and 504 full-text articles, 5 studies were included, encompassing data from 143 participants (99% female). Data were insufficient for meta-analyses. There is low-certainty evidence that Pilates improved physical functioning and health-related quality of life. The effect of Pilates on falls and BMD is uncertain. No evidence was available for the effect of Pilates on mortality, fractures, or adverse events. Overall, Pilates may improve physical functioning and quality of life. Evidence of benefits relative to harms of Pilates in people with increased fracture risk, particularly males, is limited. PROSPERO registration: CRD42019122685. Novelty: Pilates may improve physical functioning and quality of life in women with osteoporosis. Evidence of the effect of Pilates on BMD, falls, fractures, or adverse events is limited.
Design and Scaffolded Training of an Efficient DNN Operator for Computer Vision on the Edge
Authors: Ganesan Vinod , Kumar Pratyush 
Published: January 2022

Massively parallel systolic arrays and resource-efficient depthwise separable convolutions are two promising hardware and software techniques to accelerate DNN inference on the edge. Interestingly, their combination is inefficient: Computational patterns of depthwise separable convolutions do not exhibit a rhythmic systolic flow and lack sufficient data reuse to saturate systolic arrays. In this article, we formally analyse this inefficiency and propose an efficient operator, an optimal hardware dataflow, and a superior training methodology towards alleviating this. The efficient operator, called
Fully-Separable Convolutions (FuSeConv)
,

1

is a drop-in replacement for depthwise-separable convolutions. FuSeConv generalizes factorization of convolution fully along their spatial and depth dimensions. The resultant computation is systolic and efficiently maps to systolic arrays. The optimal hardware dataflow, called
Spatial-Tiled Output Stationary
(ST-OS)
, maximizes the efficiency of FuSeConv on systolic arrays. It maps independent convolutions to rows of the systolic array to maximise resource-utilization with negligible VLSI overheads.
Neural Operator Scaffolding (NOS)
scaffolds the training of FuSeConv operators by distilling knowledge from the more expensive depthwise separable convolution operation. This bridges the accuracy gap between FuSeConv networks and networks with depthwise-separable convolutions. Additionally, NOS can be combined with
Neural Architecture Search (NAS)
to trade off latency and accuracy.

The hardware-software co-design of FuSeConv with ST-OS achieves a significant speedup of 4.1-9.25× with state-of-the-art efficient networks for the ImageNet dataset. The parameter efficiency of FuSeConv and its significant superiority over depthwise-separable convolutions on systolic arrays illustrates their promise as a strong solution on the edge. Training FuSeConv networks with NOS achieves accuracy comparable to the depthwise-separable convolution baselines. Further, by combining NOS with NAS, we design networks that define state-of-the-art models improving on both accuracy and latency for computer vision on systolic arrays.
Research on State of Health for the Series Battery Module Based on the Weibull Distribution
Authors: Zhao Qian , Jiang Haobin , Chen Biao , Wang Cheng , Xu Shanzhen , Zhu Jianhui , Chang Lv 
Published: January 2022

The state of health (SOH) of the battery module is one of the important parameters in the battery management system. Accurately grasping the SOH of the battery module can provide the basis for its detection and diagnosis. In this work, the series battery module SOH is taken as the research object. Firstly, based on the characteristics of the series battery module, a two-parameter Weibull distribution is selected as the module failure data distribution form. Secondly, linearize the reliability function of the Weibull distribution and preprocess the module failure data. The least square method is used to identify the unknown parameters of the linear equation and carry out correlation analysis and model verification. The result shows the correlation coefficient

ρ

X
,
Y

=
0.9725
,

indicating that the variables X and Y are significantly correlated. The selected model is tested by the Kolmogorov-Smirnov (K–S) method, and the K-S test statistic D achieves the maximum value

D

max

=
0.0371
,

which is much smaller than the Dc = 0.301 obtained by checking the K-S D critical value table. In the reliability analysis, the failure data are evenly distributed on both sides of the reliability function, indicating that the selected model can well reflect the SOH transformation trend of the series battery module.
Modeling Androgen Deprivation Therapy–Induced Prostate Cancer Dormancy and Its Clinical Implications
Authors: Dong Xin , Xue Hui , Mo Fan , Lin Yen-yi , Lin Dong , Wong Nelson K.Y. , Sun Yingqiang , Wilkinson Scott , Ku Anson T. , Hao Jun , Ci Xinpei , Wu Rebecca , Haegert Anne , Silver Rebecca , Taplin Mary-Ellen , Balk Steven P. , Alumkal Joshi J. , Sowalsky Adam G. , Gleave Martin , Collins Colin , Wang Yuzhuo 
Published: January 2022

Abstract

Treatment-induced tumor dormancy is a state in cancer progression where residual disease is present but remains asymptomatic. Dormant cancer cells are treatment-resistant and responsible for cancer recurrence and metastasis. Prostate cancer treated with androgen-deprivation therapy (ADT) often enters a dormant state. ADT-induced prostate cancer dormancy remains poorly understood due to the challenge in acquiring clinical dormant prostate cancer cells and the lack of representative models. In this study, we aimed to develop clinically relevant models for studying ADT-induced prostate cancer dormancy. Dormant prostate cancer models were established by castrating mice bearing patient-derived xenografts (PDX) of hormonal naïve or sensitive prostate cancer. Dormancy status and tumor relapse were monitored and evaluated. Paired pre- and postcastration (dormant) PDX tissues were subjected to morphologic and transcriptome profiling analyses. As a result, we established eleven ADT-induced dormant prostate cancer models that closely mimicked the clinical courses of ADT-treated prostate cancer. We identified two ADT-induced dormancy subtypes that differed in morphology, gene expression, and relapse rates. We discovered transcriptomic differences in precastration PDXs that predisposed the dormancy response to ADT. We further developed a dormancy subtype-based, predisposed gene signature that was significantly associated with ADT response in hormonal naïve prostate cancer and clinical outcome in castration-resistant prostate cancer treated with ADT or androgen-receptor pathway inhibitors.

Implications:
We have established highly clinically relevant PDXs of ADT-induced dormant prostate cancer and identified two dormancy subtypes, leading to the development of a novel predicative gene signature that allows robust risk stratification of patients with prostate cancer to ADT or androgen-receptor pathway inhibitors.
Revival of Eastern Swamp Deer Rucervus duvaucelii ranjitsinhi (Groves, 1982) in Manas National Park of Assam, India
Authors: Islam Nazrul , Ahmed Aftab , Barman Rathin , Deka Sanatan , Choudhury Bhaskar , Saikia Prasanta Kumar , Jyotishman Deka  
Published: January 2022

A healthy population of the threatened Eastern Swamp Deer Rucervus duvaucelii ranjitsinhi in Manas National Park was almost exterminated due to politico-ethnic disturbances in the late 1980s that culminated with the formation of Bodoland Territorial Council in 2003. The Swamp Deer population in Manas began to revive with augmentation starting in 2014, in keeping with a UNESCO World Heritage Site Committee mandate. The Eastern Swamp Deer population in Kaziranga was threatened by the annual flood of the Brahmaputra River, and to secure the future of this threatened species, 36 deer were relocated in two batches in 2014 and 2017 from Kaziranga to Manas. The population of Manas had grown to an estimated 121 individuals by March 2021. Swamp deer is considered an important prey species for Swamp Deer population top predators, especially tigers, which have also increased in number in Manas over the last decade. Thus the revival of Eastern Swamp Deer has contributed to the rewilding programme of the Manas landscape.
Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia
Authors: Billot Anne , Lai Sha , Varkanitsa Maria , Braun Emily J. , Rapp Brenda , Parrish Todd B. , Higgins James , Kurani Ajay S. , Caplan David , Thompson Cynthia K. , Ishwar Prakash , Betke Margrit , Kiran Swathi 
Published: January 2022

Background:
Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent and complementary prognostic role of different patient-related factors in predicting response to language rehabilitation after a stroke.

Methods:
Fifty-five individuals with chronic poststroke aphasia underwent a battery of standardized assessments and structural and functional magnetic resonance imaging scans, and received 12 weeks of language treatment. Support vector machine and random forest models were constructed to predict responsiveness to treatment using pretreatment behavioral, demographic, and structural and functional neuroimaging data.

Results:

The best prediction performance was achieved by a support vector machine model trained on aphasia severity, demographics, measures of anatomic integrity and resting-state functional connectivity (F1=0.94). This model resulted in a significantly superior prediction performance compared with support vector machine models trained on all feature sets (F1=0.82,
P
<0.001) or a single feature set (F1 range=0.68–0.84,
P
<0.001). Across random forest models, training on resting-state functional magnetic resonance imaging connectivity data yielded the best F1 score (F1=0.87).

Conclusions:
While behavioral, multimodal neuroimaging data and demographic information carry complementary information in predicting response to rehabilitation in chronic poststroke aphasia, functional connectivity of the brain at rest after stroke is a particularly important predictor of responsiveness to treatment, both alone and combined with other patient-related factors.