bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crimes of the powerful in Latin America and the Caribbean: Toward a research agenda
Authors: Atiles Jose 
Published: November 2023

AbstractThe scholarship on crimes of the powerful encompasses a critical examination of social harms, and crimes perpetrated by privately or publicly operated businesses and corporations, the state, international organizations, elites, as well as the state‐mediated administrative and political responses to these crimes. Going beyond state‐centric definitions of crime and deviance, this scholarship emphasizes studying power and the harmful and criminogenic operations of the neoliberal‐capitalism. However, this scholarship has overlooked the systemic examination of these crimes in the Global South, Latin America and the Caribbean, and their impact on racialized, gendered, and other marginalized communities. This article aims to contribute to this scholarship by providing an overview of the current developments in the scholarship on crimes of the powerful and proposing some future research areas for Latin America and the Caribbean. Thus, the article aims to demonstrate that the Latin American and Caribbean experiences with crimes of the powerful can expand our understanding of the social harms generated by powerful organizations and actors and magnify the analytical and methodological reach of this critical scholarship.
Outcome prediction in dogs admitted through the emergency room: Accuracy of staff prediction and comparison with an illness severity stratification system for hospitalized dogs
Authors: Le Gal Alice , Barfield Dominic Martin , Wignall Roseanne Helen , Cook Simon David 
Published: November 2023

AbstractObjectiveTo determine whether emergency staff and students can predict patient outcome within 24 hours of admission, comparing the accuracy of clinician prognostication with outcome prediction by Acute Patient Physiologic and Laboratory Evaluation (APPLE)fast scoring and identifying whether experience or mood would be associated with accuracy.DesignProspective observational study between April 2020 and March 2021.SettingUniversity teaching hospital.AnimalsOne hundred and sixty‐one dogs admitted through an Emergency Service were assessed. Where data were available, an APPLEfast score was calculated per patient. An APPLEfast score of >25 was deemed a predictor for mortality.InterventionsNone.Measurements and Main ResultsEmergency staff and students were asked to complete surveys about dogs admitted to the emergency room. All clinicopathological data were available for review, and the animals were available for examination. Data collected included opinions on whether the patient would be discharged from hospital, a mood score, position, and experience in Emergency and Critical Care. One‐hundred and twenty‐five dogs (77.6%) were discharged; 36 dogs (22.4%) died or were euthanized. Two hundred and sixty‐six responses were obtained; 202 responses (75.9%) predicted the correct outcome. Students, interns, residents, faculty, and nurses predicted the correct outcome in 81.4%, 58.3%, 83.3%, 82.1%, and 65.5% of cases, respectively. Of 64 incorrect predictions, 43 (67.2%) predicted death in hospital. APPLEfast scores were obtained in 121 cases, predicting the correct outcome in 83 cases (68.6%). Of 38 cases in which APPLEfast was incorrect, 27 (71.1%) were dogs surviving to discharge. Mean APPLEfast score was 22.9 (± 6.2). There was no difference in outcome prediction accuracy between staff and APPLEfast scores (P = 0.13). Neither experience nor mood score was associated with outcome prediction ability (P = 0.55 and P = 0.74, respectively).ConclusionsOutcome prediction accuracy by staff is not significantly different to APPLEfast scoring where a cutoff of >25 is used to predict mortality. When predictions were incorrect, they often predicted nonsurvival.
Sonographic features of the uncomplicated postoperative abdomen in dogs treated for pyometra by ovariohysterectomy
Authors: Nilsson Mia K. , Toresson Linda , Ljungvall Ingrid , Nyman Lee Helena T. , McEvoy Fintan J. 
Published: November 2023

AbstractPyometra is a prevalent disease in intact bitches and the standard treatment is ovariohysterectomy (OHE). Published descriptions of normal sonographic findings after OHE are currently lacking. The aims of this prospective observational study were to describe and compare postoperative abdominal sonographic features for three timepoints following OHE in a group of dogs with pyometra and an uneventful recovery. A total of 22 dogs had sequential focused abdominal ultrasound examinations on days 1, 4–6, and 10–15 postsurgery. Recorded sonographic features for each examination time point and characteristics of the cervical stump and the mesovarium, size, and echogenicity of medial iliac lymph nodes (MILNs), presence of free peritoneal fluid, and pneumoperitoneum. The cervical stump appeared as a heterogenous area with a hypoechoic center surrounded by hyperechogenic tissue in all dogs. The cervical stump transverse‐sectional area was larger on day 4–6 compared with day 1 and day 10–15 (P = .0009). Mesovarium ligature reactions were identified as heterogeneous and hyperechoic areas with central and/or edge shadowing in all dogs. The size and echogenicity of MILNs and the mesovarium reactions did not significantly differ among time points. Free peritoneal fluid was detected in 45%, 41%, and 9% and pneumoperitoneum in 95%, 82%, and 14% of dogs at sequential time points. Findings from this sample of dogs with an uneventful recovery following OHE due to pyometra can be used to assist veterinarians in interpreting postoperative abdominal ultrasonographic characteristics in future dogs treated surgically for pyometra.
Agri-Food Supply Chain Traceability Supported by a Formal Ontology: A Grain Elevator to Processor Use Case
Authors: Ameri Farhad , Wallace Evan , Yoder Reid , Riddick Frank 
Published: November 2023

Abstract
Traceability of food products to their sources is critical for quick responses to food emergencies. However, having the complete and consistent information needed to quickly investigate sources and identify affected material has proven difficult. Food trace-ability is challenging for a variety of reasons including diversity and heterogenicity of participants, complexity of the supply chain and its processes and lack of a common understanding of steps in a supply chain, and incompleteness of data, and unwillingness of actors to expose information of their internal operations. The objective of this work is to address the traceability challenge by developing a formal ontology that can provide a shared and common understanding of the traceability model across all stakeholders in a food supply chain. In previous research, an ontological approach was adopted to address the traceability problem in the context of a use case related to harvest to on-farm storage activities. This work extends the Supply Chain Traceability ontology by introducing additional critical tracking events including transform event, sampling event, observation event, custody change event, and ownership change event in the context of a scenario involving shipments of commodity grain from a primary grain elevator to a processor of grain such as a feed manufacturer. A knowledge graph is generated based on a simulated dataset and the ontology is validated through query, reasoning, and visualization conducted in the RDFox environment.
Orientation Optimization With Topological Derivative for Anisotropic Materials With Rotational Symmetry
Authors: Noda Masaki , Matsushima Kei , Yamada Takayuki 
Published: November 2023

Abstract
This paper proposes a method for optimizing the orientation of multi-directionally reinforced materials that exhibit rotational symmetry, such as woven CFRP sheets or laminated CFRP sheets. The orientation is represented in a “relaxed” Cartesian format, and symmetry modifications are employed to prevent overlapping design variables for identical material constants. The optimal orientation is estimated using topological derivatives for anisotropic materials, and the orientation distribution is subsequently optimized based on this estimate. The proposed method is validated using a range of numerical examples of elasticity problems.
Improving Nonuniform Utilization of Li-Ion Pouch Cells Using Tapered Electrodes Through Calendering
Authors: Cho Changik , Kelley Seth , Tylka Joseph G. , He Miao , Nandola Naresh N. , Rahn Christopher D. 
Published: November 2023

Abstract
Large format lithium-ion pouch cells can have fewer tabs, less packaging material and interconnects, and lower cost but nonuniform material utilization reduces the achievable power and energy densities. The impedance varies across the cell with active material farthest from the tabs having the highest impedance. As a result, these underutilized parts of the cell do not become fully charged or discharged, especially at high current rates, and the energy storage capability of the cell is not fully realized. The current collector thickness can be thickened to increase material utilization, but cost and energy density suffer. In this paper, we propose and simulate linearly tapered electrode coatings to decrease thickness (and increase impedance) in low impedance areas, improving the impedance uniformity and material utilization across the cell. The taper is introduced in the calendering process, by tilting the rollers to change thickness and porosity across the width of the cell. A multiple particle (MP) model is developed and validated in COMSOL to optimize the slope of the taper based on Brute-force algorithm. Higher impedance near the tab balances the higher impedance in the current collector away from the tab. The analysis results show that a 10% linearly tapered positive electrode can improve uniformity by 8 times with 3C charging and increase capacity by 13% with 5C charging.
Topology Optimization of Rarefied Gas Devices With Discrete Velocity Method
Authors: Guan Kaiwen , Matsushima Kei , Yamada Takayuki 
Published: November 2023

Abstract
This paper presents a topology optimization method for rarefied gas devices. Based on the discrete velocity method, which is a conventional iterative scheme to solve the Boltzmann equation, we propose an extension to include a pseudo design density that characterizes distribution of materials in the design domain. Using a discrete version of the optimization problem, we obtain a system of discrete adjoint equations, which can be solved by recording necessary information during the discrete velocity method calculation. Design sensitivity to maximize (or minimize) an objective function can be calculated from the solution of the adjoint equations. Validity of the optimization method is demonstrated through optimization of a bent pipe.
Shape-Based Force Estimation Method for Guidewire Navigation in Neurointervention Surgery
Authors: Xu Yang , Golden Jacob , Mangla Ronin , Wu Karen , Mangla Sundeep , Masur Sean , Shi Yong 
Published: November 2023

Abstract
A study is currently being conducted on a robotic system designed to assist surgeons during neuroendovascular interventions. To navigate the robotic-assisted system through the vascular artery network, a guidewire is employed. However, the existing commercial robotic system lacks a force feedback mechanism, which could potentially pose safety concerns due to the contact force or friction between the guidewire and the vascular artery. Since the entire procedure is captured by X-ray imaging, it is feasible to estimate the force exerted on the artery by analyzing the shape of the guidewire. This article proposes a force estimation method that relies on the changes in the guidewire’s shape during the contact process. By examining its curvature, the contact force and friction force of the guidewire can be calculated. The turning points on the curvature curve enable the determination of the contact positions for multi-point loading. The effectiveness of the proposed shape-based force estimation method is validated through Finite Element Method (FEM) simulations, which demonstrate a good approximation. The error between the actual and estimated forces at most contact points is approximately 10%. Furthermore, the proposed method is further substantiated through an experimental test, where it is observed that the accuracy of curvature calculation is directly linked to the contour fitting process. Improved results in curvature calculation are achieved by employing more points for each segment fitting.
The Economic and Environmental Sustainability of Additive Manufacturing for Tooling: A Case Study on Using Laser Powder Bed Fusion for Making Injection Molding Tool Inserts
Authors: Liao Jiankan , De Kleine Robert , Powell Jason , Cooper Daniel 
Published: November 2023

Abstract
Laser powder bed fusion (L-PBF) can make injection molding tools with conformal cooling channels that can reduce plastic part warpage and production cycle times. In this study, we define the design space in which L-PBF tools are economically and environmentally beneficial compared to traditional toolmaking methods. We develop mechanistic production cost, lead time, and cradle-to-grave life cycle assessment models of the cumulative energy demand (CED) and greenhouse gas (GHG) emissions associated with injection molding (IM) tool inserts made from tool steel using a Renishaw AM500Q L-PBF machine versus conventional 3-axis machining of equivalent beryllium copper (BeCu) inserts. These models are applied to a set of seven tool inserts used to make glass fiber reinforced plastic engine intake filter housings. The models are informed using insert build time and electrical power measurements on the L-PBF machine. Across all the inserts, using L-PBF was found to be slower, costlier, and more energy and emissions intensive than conventional mold making. However, benefits from reduced IM cycle times and plastic part rejection rates when using the L-PBF inserts can lead to whole life cycle improvements. We calculate how the breakeven plastic part production volumes (above which L-PBF inserts are faster, cheaper, and more environmentally benign over the life cycle) change for varying cycle time and part reject rate improvements. Assuming the L-PBF inserts result in 15% and 2.5% reductions in cycle time and part rejects respectively, then the breakeven production volumes are 60,000 parts for lead time, 4,000 parts for CED and GHG emissions, and greater than the likely mold lifespan (100,000 parts) for cost.
A Proposal of an Efficient and Accurate Methodology for Accounting the Static Transmission Error in Epicyclic Gearset
Authors: Bruzzone Fabio , Rosso Carlo 
Published: November 2023

Abstract
Epicyclic gearsets are commonly used in a variety of industrial applications and while these systems offer many advantages they can also suffer from dynamic problems such as vibration and noise due to their complex geometry and multiple contact points. One important factor in understanding and mitigating these dynamic problems is the calculation of Static Transmission Error (STE). By accurately calculating STE, engineers can gain insights into the behavior of the gear system and make informed decisions regarding design changes and operational parameters to improve performance and reduce dynamic issues. Therefore, the calculation of STE is an essential tool in the design and analysis of epicyclic gear systems. In this paper a simplified but accurate methodology is proposed for the rapid computation of this important parameter. The foundation stiffness of the internal ring gear is first analyzed using a parametric Finite Element (FE) model and an analytical expression is derived. In addition, the engagement stiffness is accurately computed and used as connection element between gears. A schematization of the system using a limited number of degrees of freedom for each component is then presented along with the procedure to compute the STE using the proposed approach. Results are then obtained for a simple test case and conclusions are drawn.
Design and Nonlinear Analysis of 2-Body Centrifugal Pendulum Vibration Absorber for Suppression of Multiple Harmonic Frequencies in Torsional Vibration of Rotor System
Authors: Zhou Xingyu , Inoue Tsuyoshi , Heya Akira 
Published: November 2023

Abstract
The centrifugal pendulum vibration absorber (CPVA) is widely used as an effective vibration suppression device. Most of the CPVAs that have been studied so far are composed of a single mass point or a rigid body (1-body CPVA). They are effective in reducing the vibration of a single-order component. This property makes them highly suitable for using in gasoline-powered vehicles. The development of electric vehicles (EVs) and hybrid electric vehicles (HEVs) has introduced complex torsional vibrations to the vehicle’s rotational shaft. As a result, it has become necessary to suppress vibrations of different order components simultaneously. Therefore, in this study, a rigid body model for a 2-body CPVA is proposed to suppress rotor system vibrations with multiple order components. A multi-body dynamics (MBD) analysis model is constructed to analyze a rotor system equipped with the 2-body CPVA. Furthermore, tuning equations for the 2-body CPVA to suppress multiple order components are derived, and the shape of the 2-body CPVA is investigated to further enhance its effectiveness. The designed 2-body CPVAs are installed on the rotor system, and numerical analysis is performed using the direct integration method and shooting method. Subsequently, it is confirmed that the 2-body CPVA is effective in reducing torsional vibrations with two-order components. Furthermore, it demonstrated the superiority of one 2-body CPVA in suppressing vibrations of multiple order components compared to two different 1-body CPVAs.
VariableTypography: Artificial Intelligence Augmented Reading Experience
Authors: Shi Shuhui , You Weitao , Han Kaixin , Song Jinyu , Sun Lingyun 
Published: November 2023

Abstract
Nowadays, digital information has overloaded and reading time has been fragmented due to the significant development of digital devices, such as phones, computers, etc. Optimizing the reading experience has become a challenge. Prior studies on Chinese digital reading have primarily focused on uniform and consistent typography settings. Nevertheless, this standard typography is not applicable to real-world scenarios. Usually, people leverage different typographical variables to emphasize part of a sentence to highlight key information. Inspired by this, we propose a novel screen reading method, dubbed VariableTypography (VT), that highlights key information in various typographic ways by utilizes artificial intelligence tool ChatGPT to identify key information in the text, aiming to enhance the reading experience. In the field of artificial intelligence, significant progress has been made in natural language processing, resulting in innovative tools like ChatGPT. With its low operating threshold and the ability to use natural language for prompt engineering, ChatGPT has attracted widespread attention. In this study, we incorporated ChatGPT into a real-world reading scenario and integrated it with VT to examine its potential for assisted reading. To evaluate the effectiveness of VT, objective and subjective experiments were conducted in naturalistic remote settings with 70 participants using their smartphones in daily Interlude Reading scenarios. The results show that our proposed VT effectively improved readers’ subjective information acquisition while significantly reducing cognitive load during reading, without affecting the original reading efficiency. Additionally, VT is evidenced with good subjective acceptance. We hope that our findings will shed light on the field of digital Chinese readability.
A Digital Twin Assisted Framework for Quality Assurance in Mould Manufacturing
Authors: Böttjer Till , Ramanujan Devarajan 
Published: November 2023

Abstract
This paper discusses a Digital Twin framework for quality assurance in mould manufacturing consisting of the physical and virtual manufacturing process connected by a data lake. To this end, we present the DT framework and demonstrate its applicability at the example of ensuring the quality of milling features on a mould tool part. For the demonstration we build two cascaded models, a tool wear state model and an insert part quality model. The tool wear state model assigns a label corresponding to the tool wear state using cutting force measurements. The part quality model then uses the tool state and engineering data to classify quality of individual milling features on the mould tool part. To develop the cascaded models, we conducted a case study which experimentally collected machine controller data and cutting forces using a Kistler dynamometer for machining a test part on a Makino V33i three-axis vertical milling machine. The test part contains mould tool specific features and is made of hardened tool steel (46-52 HRC). Three milling tools were repeatedly used to machine test parts and gather data at different tool wear states. For validating the part quality model, we further collected metrology data from a coordinate measurement machine. Results show that the developed cascaded models are able to monitor the tool wear stage and to classify quality deviations with a weighted F1 measure of 89.0%.
Electric Machine and Battery Sizing for Hybrid Electric Heavy Duty Vehicles
Authors: Hegde Shailesh , Bonfitto Angelo , Castellanos Molina Luis M. 
Published: November 2023

Abstract
Medium- to heavy duty vehicles make a major contribution to freight transportation and are expected to keep growing continuously. In order to reduce the CO2 emissions and avoid climate change, ambitious regulations have been introduced. To fulfill these requirements, aerodynamic drag and vehicle mass reduction, more efficient conventional internal combustion engines (ICE) and alternative powertrain architectures are being developed. Hybrid electric vehicles (HEVs) are one of the solutions with the highest potential for fuel economy improvement, provided that all the subsystems at play are correctly sized. In this work, a power based approach is used to define the electric machine (EM) and battery size by considering the power request in braking and technology constraints in the battery and power electronics. The hybrid layouts under study are P0, P1, and P2 parallel applied to a 35 Ton vehicle whose model is developed in a Matlab/Simulink environment using the velocity profile from the European Union Commission simulation tool (VECTO). The Equivalent Consumption Minimization Strategy is used as an energy management system to provide optimal torque references to ICE and EM. The regional delivery and long haul driving cycles, which are the official driving cycles for the certification of heavy duty vehicles in the EU, were used to evaluate the performance of hybrid solutions with respect to conventional pure ICE.