bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computed tomographic characteristics of anatomical variations of external and internal jugular veins in dogs
Authors: Lau Seng Fong , Dubansky Brooke , Liu Chin‐Chi , Rademacher Nathalie 
Published: August 2024

AbstractThe external jugular vein (EJV) has been commonly used for clinical procedures in veterinary medicine, while the internal jugular vein (IJV) has been used mainly for research. Limited literature regarding anatomical variants in both EJV and IJV is available. The objectives of this descriptive retrospective study were to identify the number of dogs with variations of the jugular veins in canine patients undergoing CT of the head and neck and characterize these variations. Of 1000 dogs, 193 dogs (19.3%) had anatomical variations. Six types of anatomical variations were identified. The most common Type I was the absence of the linguofacial vein (72.0%, n = 139), with the lingual, facial, and maxillary veins entering the EJV at a common branching point. Type II described a variable course of the EJV and IJV, which in some dogs resulted in the absence of the EJV (14.0%, n = 27). Type III was a variable anastomotic loop formed by the linguofacial or maxillary vein cranial or at the junction of the EJV (4.2%, n = 8). In Type IV, the EJV was either suspected to be aplastic or markedly reduced in diameter compared with the contralateral side just distal to its formation (3.6%, n = 7). Type V was found in only six dogs (3.1%) with unilateral differences in the diameter of the IJV. Six of 193 dogs had a combination of more than one variation (Type VI, 3.1%). Type I was significantly observed more frequently in meso‐ and dolichocephalic breeds. Type II was significantly observed more frequently in brachycephalic breeds.
Ex vivo MRI and histological comparison of the canine adrenal glands
Authors: Carafí Olga Amorós , Imlau Michelle , Dalla Serra Giulia , Puggioni Antonella , Shorten Eimear , Cloack Brain , Hoey Seamus 
Published: August 2024

AbstractCross‐sectional imaging is widely used to characterize adrenal gland tumors in humans. In small animal veterinary medicine, while some studies have attempted to distinguish between types of adrenal gland neoplasia using CT, peer‐reviewed studies investigating canine adrenal glands on MRI are scant. This prospective, pilot, single‐center, method comparison, cadaveric study aimed to assess the agreement between ex vivo MRI findings and analogous histopathological findings of the adrenal glands in dogs. The adrenal glands of randomly selected dogs presented for necropsy were examined by MRI (n = 31). Additionally, five adrenal masses in dogs who underwent invasive adrenalectomy (including three adrenocortical carcinomas, one pheochromocytoma, and one adenoma) were imaged. Subsequently, gross pathology and histopathology of all the specimens were performed and correlated with the imaging findings. Adrenal gland lesions were identified on MRI with a sensitivity of 24%, a specificity of 100%, a positive predictive value of 100%, a negative predictive value of 31%, and an accuracy of 45%. The present study provides MRI features of multiple adrenal gland lesions that had never been described in dogs, including cortical hyperplasia, nodular fibrosis, hemorrhage, or multiple tumors, such as adenoma, carcinoma, and hemangiosarcoma. While MRI identified numerous adrenal gland lesions, a significant portion of those went undetected. Therefore, the absence of adrenal gland lesions on MRI does not exclude the possibility of histological lesions being present.
A Review on Recent Progress of Biodegradable Magnetic Microrobots for Targeted Therapeutic Delivery: Materials, Structure Designs, and Fabrication Methods
Authors: Cao Yang , Michel Karen Nunez , Alimardani Farzam , Wang Yi 
Published: August 2024

Abstract
Targeted therapeutic delivery employs various technologies to enable precise delivery of therapeutic agents (drugs or cells) to specific areas within the human body. Compared with traditional drug administration routes, targeted therapeutic delivery has higher efficacy and reduced medication dosage and side effects. Soft microscale robotics have demonstrated great potential to precisely deliver drugs to the targeted region for performing designated therapeutic tasks. Microrobots can be actuated by various stimuli, such as heat, light, chemicals, acoustic waves, electric fields, and magnetic fields. Magnetic manipulation is well-suited for biomedical applications, as magnetic fields can safely permeate through organisms in a wide range of frequencies and amplitudes. Therefore, magnetic actuation is one of the most investigated and promising approaches for driving microrobots for targeted therapeutic delivery applications. To realize safe and minimally invasive therapies, biocompatibility and biodegradability are essential for these microrobots, which eliminate any post-treatment endoscopic or surgical removals. In this review, recent research efforts in the area of biodegradable magnetic microrobots used for targeted therapeutic delivery are summarized in terms of their materials, structure designs, and fabrication methods. In the end, remaining challenges and future prospects are discussed.
Data-Informed Risk Analysis of Power Grids: Application of Method for Managing Heterogeneous Datasets
Authors: Pacevicius Michael Felix , Ramos Marilia , Eriksen Christian Thun , Paltrinieri Nicola 
Published: August 2024

Abstract
Power utilities are continuously under high pressure to ensure the best performance of their grid. Nevertheless, power outages continue to be periodically observed. This paper assesses the applicability and implications of the Three-Phases method for optimized dataset selection in dynamic risk analysis, through a case study focusing on vegetation along power lines—a major hazard in power grid management. The case study comprises 17 different real-world datasets originating from 12 different types of data sources. We estimate how these datasets can inform eight parameters related to the physical configuration—one of the three dimensions impacting the probability of tree falls on power lines. The results provide two main take-aways: (1) datasets initially considered as less valuable for risk analysis can end up being the most relevant ones; (2) the potential of knowledge of a dataset needs to be assessed parameter per parameter. The results demonstrate that the Three-Phases method is a step toward traceable, data-driven, and dynamic risk analyses of power grids, resulting in a more reliable management of those large-scale infrastructures.
Time-Critical Unified Rendezvous Guidance for an Unmanned Autonomous Vehicle
Authors: Sinha Abhinav , Kumar Shashi Ranjan 
Published: August 2024

Abstract
This paper addresses the time-critical rendezvous problem for a pursuing autonomous unmanned vehicle, e.g., an unmanned aerial vehicle (UAV), guided using the concept of true proportional-navigation guidance, which is a variant of proportional-navigation guidance. In existing vehicle routing and flight time-constrained guidance techniques, specific rendezvous guidance commands are designed based on the specific motion of the target. In contrast to that, we propose a unified guidance command for a UAV that guarantees a time-critical rendezvous with a target that moves arbitrarily. We explore the purview of true proportional-navigation guidance and posit that a guidance law thus designed may be a potential candidate for designing time-critical rendezvous strategies against various target motions, even when the pursuer does not necessarily have a speed advantage over the target. We first derive a closed-form expression for the flight duration until rendezvous, over which we exercise control to make the pursuing vehicle rendezvous with the target at any feasible time prescribed a priori. Next, we ensure that the necessary flight-time-based error variable converges to zero with an optimal convergence pattern with respect to a suitable cost function. We finally validate the efficacy of the proposed unified guidance command via numerical simulations.
Control-Oriented Modeling of a Solid Oxide Fuel Cell Affected by Redox Cycling Using a Novel Deep Learning Approach
Authors: Tofigh Mohamadali , Fakouri Hasanabadi Masood , Smith Daniel , Kharazmi Ali , Hanifi Amir Reza , Koch Charles R. , Shahbakhti Mahdi 
Published: August 2024

Abstract
A solid oxide fuel cell (SOFC) is a multiphysics system that involves heat transfer, mass transport, and electrochemical reactions to produce electrical power. Reduction and re-oxidation (Redox) cycling is a destructive reaction that can occur during SOFC operation. Redox induces various degradation mechanisms, such as electrode delamination, nickel agglomeration, and microstructural changes, which should be mitigated. The interplay of these mechanisms makes a post-Redox SOFC a nonlinear, time-varying, nonstationary dynamic system. Physics-based modeling of these complexities often leads to computationally expensive equations that are not suitable for the control and diagnostics of SOFCs. Here, a data-driven approach based on dilated convolutions and a self-attention mechanism is introduced to effectively capture the dynamics underlying SOFCs affected by Redox. Controlled Redox cycles are designed to collect appropriate experimental data for developing deep learning models, which are lacking in the current literature. The performance of the proposed model is validated on diverse unseen data sets gathered from different fuel cells and benchmarked against state-of-the-art models, in terms of prediction accuracy and computation complexity. The results indicate 31% accuracy improvement and 27% computation speed enhancement compared to the benchmarks.
Thermal Management and Optimization of Automotive Film Capacitors Based on Parallel Microchannel Cooling Plates
Authors: Huang Linhao , Yuan Tao , Wang Yansong , Guo Hui , Li Zhanghao , Zhao Lihui , Chang Bin , Wang Yi 
Published: August 2024

Abstract
The automotive film capacitors (AFCs) stand as a widely employed components in electric vehicles. Yet, a notable concern arises with the potential for excessive ripple current, which can prompt self-heating in the AFC and diminish its reliability. Therefore, it becomes crucial to conduct thermal management and effective heat dissipation design for the AFC to ensure its optimal performance. In this study, considering the trend toward integrated and lightweight motor controllers, a parallel microchannel cooling plate (PMCP) is designed at the bottom of the AFC. Through optimization, the thermal performance of the AFC and the overall cooling performance of the PMCP are enhanced. The AFC thermal model is established, and the calculation method for equivalent thermal properties of the film capacitor core is described. A conjugate heat transfer simulation model for the AFC and the PMCP is created by fluent and validated through two experimental tests. In addition, based on an optimal Latin hypercube sample size, the accuracy of five fitting models is compared and the nondominated sorting genetic algorithm II (NSGA-II) for optimization is employed. The results indicate that the error between the simulation method and the two experiments is within 5%. The application of the PMCP effectively redistributes the hottest region of the AFC to the outer housing, reducing the maximum AFC temperature by 10.90 °C. Among the five fitting models, the response surface model (RSM) proved to be the most accurate. The optimized PMCP enhances the overall cooling performance by 10.32% and increases the maximum withstand ripple current of the AFC by 43.83%.
Sparse Convolution-Based 6D Pose Estimation for Robotic Bin-Picking With Point Clouds
Authors: Zhuang Chungang , Niu Wanhao , Wang Hesheng 
Published: August 2024

Abstract
Estimating the orientation and position of objects is a crucial step in robotic bin-picking tasks. The challenge lies in the fact that, in real-world scenarios, a diverse array of objects is often randomly stacked, resulting in significant occlusion. This study introduces an innovative approach aimed at predicting 6D poses by processing point clouds through a two-stage neural network. In the initial stage, a network for scenes with low-textured environments is designed. Its purpose is to perform instance segmentation and provide an initial pose estimation. Entering the second stage, a pose refinement network is suggested. This network is intended to enhance the precision of pose prediction, building upon the output from the first stage. To tackle the challenge of resource-intensive annotation, a simulation technique is employed to generate a synthetic dataset. Additionally, a dedicated software tool has been developed to annotate real point cloud datasets. In practical experiments, our method demonstrated superior performance compared to baseline methods such as PointGroup and Iterative Closest Point. This superiority is evident in both segmentation accuracy and pose refinement. Moreover, practical grasping experiments have underscored the method's efficacy in real-world industrial robot bin-picking applications. The results affirm its capability to successfully address the challenges produced by occluded and randomly stacked objects.
Modeling of Fiber Optic Acoustic Coupler for Ultrasonic Sensing
Authors: Kim Jee Myung , Peters Kara 
Published: August 2024

Abstract
Fiber Bragg grating sensors have been applied in the remote-bonding configuration for structural health monitoring, in which ultrasonic modes are propagated along the optical fiber to the sensor. Recently, coupling of the ultrasonic mode from optical fiber to optical fiber through an adhesive coupler has also been demonstrated. This paper develops a finite element (FE) model to describe the coupler behavior as a function of the fiber and coupler properties, for future optimization of couplers. The FE model is validated with previous experimental data. We also compare the FE model to three theoretical models (spring and damper frictional contact models and coupled mode theory). The results show that the FE model and spring well replicate the experimental results. Future work will use the resulting FE and spring models to derive solutions for the coupling coefficient as a function of the geometrical and material parameters of the coupler.
Technological Limit of Solar Concentration Technique Applied to Hybrid Photovoltaic-Thermal Solar Collector Equipped With Thermoelectric Generator Incorporating Ternary Nanofluid
Authors: Mouaici K. , Fersadou B. , Arslan K. , Kahalerras H. , Traiche M. 
Published: August 2024

Abstract
This paper aims to explore the technological limits of the synergy between the solar concentration technique, facilitated by a parabolic concentrator, and the thermoelectric effect induced by a thermoelectric generator within a hybrid photovoltaic-thermal collector, incorporating a ternary nanofluid Cu–Al2O3-MWCNT (multiwalled carbon nanotubes)/water. Each system component is subject to energy balance equations, and the Runge–Kutta fourth-order method is employed to solve the resultant mathematical model. The effects of the concentration ratio (CR), the mass flowrate ṁ, and the type of heat transfer fluid on the system's performance are scrutinized. The simulations are carried out under the meteorological conditions of Ain Salah City in southern Algeria for a moderate wind velocity. The results show better performance when operating ternary nanofluid than other heat transfer fluids. Moreover, the outcomes indicate that by using a 2% volume fraction of nanoparticles of ternary nanofluid, the thermal output, electrical yield, and thermoelectric production reach enhancements of 14.5%, 11.2%, and 22.6%, respectively. Incorporating the solar concentrator resulted in a 3.54 and 5.88 times increase in electrical and thermal powers, respectively. With the growths in ṁ, the temperature of the photovoltaic panel decreases by 53 °C, and the electrical efficiency improves by 34.5%. Correlations encompassing the concentration ratio and mass flowrate for various types of heat transfer fluids are established to predict the technological limits of solar concentration technique in photovoltaic-thermal-thermoelectric generator collectors under the meteorological conditions specific to Ain Salah.
The Antiwear and Friction-Reducing Performance of Magnesium Silicate Hydroxide/Graphite Nanocomposite as a Lubricant Additive
Authors: Wang Kai , Chang Qiuying , Gao Kai , Wang Bin , Gao Rongqin , Yan Qingqing 
Published: August 2024

Abstract
In this article, magnesium silicate hydroxide-graphite (MSH-C) and magnesium silicate hydroxide-graphene oxide (MSH-GO) composites were prepared by doping magnesium silicate hydroxide (MSH) with micron-sized few-layer graphene oxide (∼10 µm) and nanoscale graphite (∼300 nm), respectively, during the hydrothermal synthesis process. Octadecyltrimethoxysilane (ODTMS) was used as a surfactant to disperse these two types of additives into the fully formulated oil. Tribological tests demonstrated that MSH-C exhibited superior tribological properties compared to MSH-GO. The findings reveal that the oil sample containing 0.5 wt% MSH-C can effectively reduce wear volume by approximately 26.4% compared to fully formulated oil, with the friction coefficient decreased to ∼0.02. scanning electron microscopy (SEM), Raman, focused ion beam-transmission eletron microscope (FIB-TEM), and time of flight secondary ion mass spectrometry (TOF-SIMS) characterizations, along with molecular dynamics simulation, were used to investigate the tribological mechanism. A tribofilm composed of two layers of different compositions was formed on the worn surface of MSH-C, indicating the synergistic effect of MSH and graphite.
Optimization of Oil Bores on Connecting Rod Small End to Prevent Bushing Failures at Maximum Speed
Authors: Fu Hongyu , Zhang Hao , Niu Penghao , Fan Zhihan , Gao Zhonghao 
Published: August 2024

Abstract
The bushing of connecting rod small end is one of the most prone components to failure in diesel engines. According to the previous study, the oil flowrate and storage of small-end bearing with splash lubrication are both minimal at maximum speed. Thus, the optimization of oil bores was performed using a model based on smooth particle hydrodynamics. By adjusting the angle between the axes of two oil bores to 90 deg, the oil flowrate and storage increase from 0.036 mL/s and 0.04 mL to 0.094 mL/s and 0.045 mL, respectively. A semicolumn baffle above the oil bore away from the piston cooling nozzle further increases them to 3.564 mL/s and 0.8 mL. The optimization greatly enhances the cooling intensity and oil supply stability of small-end bearing, conducing to prevent bushing failures.
Probing the Synergy of Calcium Sulfonate Complex Soap and Polyurea Complex Thickener Toward Good Lubrication and Rheological Properties
Authors: Zhang Hong , Mo Yimin , Liu Changye , Wang Jun 
Published: August 2024

Abstract
Polyurea complex thickener was introduced into calcium sulfonate complex grease (CSCG) to prepare a new type of grease. The microstructure, rheological properties, and tribological properties of new greases were studied in detail. The experimental results show that the combination of calcium sulfonate complex soap and polyurea complex thickener can form a new thickener system, which combines the layered structure of calcium sulfonate complex soap and the rod-shaped structure of polyurea complex thickener. The thermal decomposition temperature of new greases is reduced, but their fluidity is improved and the friction coefficient is lower. Their synergistic effect is related to the special structural skeleton of the new thickener system, and calcium sulfonate and urea molecules share the same calcium ion, which may be an important reason for maintaining the stability of this special structure skeleton.
Piezoelectric Impedance-Based Structural Damage Identification Empowered With Tunable Circuitry Integration and Multi-Objective Optimization-Based Inverse Analysis
Authors: Zhang Yang , Dupont Joshua , Wang Ting , Tang Jiong 
Published: August 2024

Abstract
The piezoelectric impedance-based technique is increasingly recognized for its promise in structural health monitoring and damage identification. Built upon their self-sensing actuation capability, piezoelectric transducers can be integrated into host structures to acquire the system-level impedance information in a high-frequency range with a small wavelength. Furthermore, the frequency-sweeping harmonic excitations in impedance measurements lead to the potential for model-based inverse identification of damage location and severity. A major challenge in damage identification, however, is that the inverse analysis is generally underdetermined, as the measurement information may not be adequate to yield a unique solution. In this research, a new methodology of tunable sensing in conjunction with multi-objective optimization inverse analysis is established. Taking advantage of the two-way electromechanical coupling of piezoelectric transducers, tunable inductance is integrated into the measurement circuit. For the same damage scenario, by tuning the inductance to a series of values, a family of impedance measurements can be acquired. Meanwhile, the inverse analysis is cast into a multi-objective optimization problem, aiming at minimizing the difference between measurement and model prediction and achieving sparsity in damage index vector. A Q-learning-based multi-objective particle swarm optimization is synthesized to reach a small yet diverse solution set. We report the circuitry integration details as well as the algorithm enhancement with systematic case investigations. It is validated that the new methodology with enriched measurement can produce a smaller solution set encompassing the true damage scenario, thereby providing vital information for diagnoses and prognosis.
On Dynamic Analysis and Prevention of Transmission Squawk in Wet Clutches
Authors: Ali Junaid , Natarajan Bharat , Horen Jezrah , Evans John , Shaver Gregory , Bajaj Anil K. 
Published: August 2024

Abstract
The genesis of clutch noise, encompassing squeaks, chatter, shudders, or judders, predominantly arises from friction-induced vibrations. As time progresses, the degradation of the clutch friction lining manifests due to diverse factors, such as the smearing of surface irregularities, elevated transmission fluid temperatures, fluctuating axial pressure, or aggressive shifting. Consequently, the slope of the friction curves tends to assume a negative gradient, giving rise to adverse damping effects like self-excited oscillations or stick-slip oscillations within the clutch pack. A lesser-discussed phenomenon, known as squawking, occurs through analogous mechanisms discussed in this paper. This paper delves into investigating the occurrence of squawking noise observed in automatic transmission multi-disc clutches during low-speed up-shifts. The study discerns friction-induced vibrations as the primary contributor to squawk during the inertia phase of the clutch engagement cycle, a facet previously unidentified. During this phase, high-frequency weakly damped oscillating modes become self-excited due to the negative slope of the coefficient of friction versus slip speed curve. The coefficient of friction functions as negative damping during the inertia phase, where the energy dissipation from damping is insufficient to completely halt the oscillations, allowing them to persist approximately at the natural frequency until clutch lock-up. Experimental data validate the proposed model and hypothesis, with results closely aligning with numerical simulations. The paper concludes by offering practical suggestions to prevent and mitigate squawk in automatic transmission wet clutches, with the aim of enhancing overall performance and reducing undesirable noise.