bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent topics of spinocerebellar ataxia type 31
Authors: Ishikawa Kinya 
Published: December 2023

AbstractSpinocerebellar ataxia type 31 (SCA31) is an autosomal‐dominant neurodegenerative condition caused by a 2.5–3.8 kb‐long complex repeat containing (TGGAA/TTCCA)n in an intron shared by two genes called brain expressed, associated with Nedd4 (BEAN1) and thymidine kinase 2 (TK2) located in the human chromosome 16q22.1. Since BEAN1 and TK2 are transcribed in mutually opposite directions in human brains, two independently transcribed RNAs containing either (UGGAA)n or (UUCCA)n are likely to associate with the pathogenesis of SCA31. Recently, a minor TK2 mRNA isoform called TK2‐EXT was confirmed to be transcribed in human cerebellum, suggesting that (UUCCA)n is indeed expressed. The level of TK2 mRNA and TK2 protein expression levels was both preserved in SCA31 human cerebellum, suggesting that the expression of (UUCCA)n does not affect the expression of TK2, and hence, the function of TK2 seemed to be preserved. On the other hand, the other penta‐nucleotide RNA repeat (UGGAA)n, expressed through BEAN1 transcription, is likely to conform toxicity through forming abnormal RNA structures called RNA foci in the nucleus of expressing cells. In addition, three proteins TDP‐43, FUS, and hnRNPA2/B1 that commonly have a capacity to bind with (UGGAA)n reduced the number of RNA foci, and ameliorated the phenotype brought by (UGGAA)n in Drosophila. A small compound naphthyridine carbamate dimer that binds to (UGGAA)n dampened the (UGGAA)n toxicity in Drosophila, further supporting the idea that (UGGAA)n expressed by BEAN1 is pathogenic. Therefore, a plausible approach to treat SCA31 may be considered by administering agents with a capacity binding to (UGGAA)n.
Capnodynamic end‐expiratory lung volume assessment in anesthetized healthy children
Authors: Lundquist Johanna , Shams Niki , Wallin Mats , Hallbäck Magnus , Lönnqvist Per‐Arne , Karlsson Jacob 
Published: December 2023

AbstractBackgroundCapnodynamic lung function monitoring generates variables that may be useful for pediatric perioperative ventilation.AimsEstablish normal values for end‐expiratory lung volume CO2 in healthy children undergoing anesthesia and to compare these values to previously published values obtained with alternative end‐expiratory lung volume methods. The secondary aim was to investigate the ability of end‐expiratory lung volume CO2 to react to positive end‐expiratory pressure‐induced changes in end‐expiratory lung volume. In addition, normal values for associated volumetric capnography lung function variables were examined.MethodsFifteen pediatric patients with healthy lungs (median age 8 months, range 1–36 months) undergoing general anesthesia were examined before start of surgery. Tested variables were recorded at baseline positive end‐expiratory pressure 3 cmH2O, 1 and 3 min after positive end‐expiratory pressure 10 cmH2O and 3 min after returning to baseline positive end‐expiratory pressure 3 cmH2O.ResultsBaseline end‐expiratory lung volume CO2 was 32 mL kg−1 (95% CI 29–34 mL kg−1) which increased to 39 mL kg−1 (95% CI 35–43 mL kg−1, p < .0001) and 37 mL kg−1 (95% CI 34–41 mL kg−1, p = .0003) 1 and 3 min after positive end‐expiratory pressure 10 cmH2O, respectively. End‐expiratory lung volume CO2 returned to baseline, 33 mL kg−1 (95% CI 29–37 mL kg−1, p = .72) 3 min after re‐establishing positive end‐expiratory pressure 3 cmH2O. Airway dead space increased from 1.1 mL kg−1 (95% CI 0.9–1.4 mL kg−1) to 1.4 (95% CI 1.1–1.8 mL kg−1, p = .003) and 1.5 (95% CI 1.1–1.8 mL kg−1, p < .0001) 1 and 3 min after positive end‐expiratory pressure 10 cmH2O, respectively, and 1.2 mL kg−1 (95% CI 0.9–1.4 mL kg−1, p = .08) after 3 min of positive end‐expiratory pressure 3 cmH2O. Additional volumetric capnography and lung function variables showed no major changes in response to positive end‐expiratory pressure variations.ConclusionsCapnodynamic noninvasive and continuous end‐expiratory lung volume CO2 values assessed during anesthesia in children were in close agreement with previously reported end‐expiratory lung volume values generated by alternative methods. Furthermore, positive end‐expiratory pressure changes resulted in physiologically expected end‐expiratory lung volume CO2 responses in a timely manner, suggesting that it can be used to trend end‐expiratory lung volume changes during anesthesia.
Help yourself before helping others: When corporate social responsibility does not make a company more attractive to job seekers
Authors: Ong Madeline , Kim Yong H. , Koopman Joel 
Published: December 2023

AbstractThis paper explores the conditions under which job seekers may not respond positively to a potential employer's corporate social responsibility (CSR) activities. We propose that the relationship between an organization's externally‐directed CSR activities and job seekers’ perceptions of the organization's attractiveness is moderated by whether the organization is also engaging in internally‐directed high‐investment human resource systems (HIHRS). Results from a combination of three studies—an archival study of Fortune 500 companies (Study 1), a survey study (Study 2), and an experiment (Study 3)—provide support for our hypotheses. When an organization has lower levels of internally‐directed HIHRS, the positive influence of externally‐directed CSR on attraction to an organization diminishes (Study 3) or disappears (Studies 1 and 2). Importantly, we identify perceptions of organizational authenticity as one key mechanism driving these effects (Studies 2 and 3).
Rethinking class, capitalism and exploitation from the perspective of family farming in Aotearoa/New Zealand
Authors: Pomeroy Ann 
Published: December 2023

AbstractUsing empirical evidence and an exploration of literature on simple commodity and capitalist farm production, a theoretical argument is developed to show that, despite not employing labour, self‐employed family farmers (at least in New Zealand) are capitalist, not simple commodity, producers. This has major implications for not only class theorists from a Marxist perspective, with whom we are primarily concerned, but also poses questions for Weberian inspired stratification adherents preoccupied with occupation and lifestyle. Land ownership, together with the different way capital can be generated in broad‐acre livestock farming compared to other industrial settings, enables family farmers to generate profits and accumulate capital. This means that rather than being subsumed by capital, self‐employed owners of farm enterprises appropriate surplus value not by directly hiring labour to generate income from their large landholdings but indirectly by utilising the labour of other enterprises and by hiring bourgeois or petit‐bourgeois operators (purchasing equipment, technology and knowledge, and using the distribution, processing, marketing and other services supplied by other businesses). Buying and selling land also supports these capitalist enterprises. Although not expropriating surplus value directly to operate their enterprises, capitalised family producers have, as was pointed out in 1985 by David Goodman and Michael Redclift, achieved political legitimacy by distancing themselves at the ideological level from capitalism (despite embracing capitalism at the economic level). By disguising their class interests, such producers are adept at legitimating state policy in their interests.
Integral Picard group of moduli of polarized K3 surfaces
Authors: Di Lorenzo Andrea , Fringuelli Roberto , Vistoli Angelo 
Published: December 2023

AbstractWe compute the integral Picard group of the moduli stack of polarized K3 surfaces of fixed degree whose singularities are at most rational double points, and of its coarse moduli space. We also compute the integral Picard group of the stack of quasi‐polarized K3 surfaces, and of the stacky period domain.
Measurement of Binder/Active Material Interface Fracture in Rechargeable Batteries and the Effect of Oxide Coating
Authors: Pakhare Akshay S. , Nadimpalli Siva P.V. 
Published: December 2023

Abstract
Interface fracture is a critical issue for next-generation rechargeable batteries. The integrity of the binder/active material interface is essential for successful battery operation, and the interface failure is a major capacity fade mechanism. In spite of the importance, no systematic study on understanding/characterization of this issue exists at present. Here, the interface fracture was studied using a model polyvinylidene fluoride (PVdF)/Si system due to its importance in future Li-ion batteries. The interface failure was characterized in terms of critical energy release rate Gc using an experimental technique based on blister test and Michelson interferometry. The effect of the oxide layer on the interface fracture was also quantified. The critical energy release rate Gc of PVdF/Si interface is 0.55 ± 0.14 Jm−2, and the presence of oxide layer at the interface increased the Gc by an order of magnitude higher, i.e., the Gc of PVdF/SiO2 interface is 2.46 ± 0.40 Jm−2. The scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) analysis of the fracture surfaces showed that the crack growth mechanism is adhesive for both interface systems, and the strong adhesion of PVdF to SiO2 surface is attributed to the nature of bonding, i.e., a higher concentration of silanol (Si-OH) group on the SiO2 surface as compared to the Si surface to which PVdF forms a bond with. The experimental methodology proposed here is more general and can be used to study the fracture behavior of interfaces in other electrode systems and with other battery chemistries.
Transient Tip Clearance Prediction Model Considering Transient Radial Temperature Distribution of Discs in a Gas Turbine Engine
Authors: Wei Jie , Yang Heli , Zheng Pengbo , Wang Baotong , Zheng Xinqian 
Published: December 2023

Abstract
The tip clearance of turbomachinery components, such as compressor and turbine, significantly impacts the gas turbine engine performance, including the thrust and fuel consumption. Therefore, an appropriate prediction of the turbomachinery tip clearance is indispensable in improving the accuracy of engine performance evaluations. The traditional 1D transient tip clearance prediction model does not consider the radial temperature distribution of the disk (also called disc). However, as the engine performance keeps improving, the radial temperature gradient of the disk also increases. In order to maintain the prediction accuracy within an acceptable range, a generic transient tip clearance prediction model is developed in this paper. Based on the special treatment of the axial and radial convective heat transfer boundary regions of the disk, a 2D transient heat transfer model is established, and the radial temperature of the disk is predicted. At the same time, the interaction effect of the thermal expansion between the two different layers of the shroud is studied to improve the prediction accuracy further. In addition, the centrifugal deformation of the blade and disk with variable-thickness characteristics is considered in the new transient model. Compared with the traditional 1D transient prediction model, the model developed in this paper further improves the predicting accuracy of the transient tip clearance, which is verified by the high-fidelity fluid–solid–thermal coupling method. The prediction model provides a useful tool for evaluating the transient tip clearance. It may also benefit the future design strategy of active clearance control.
Design and Cooling Performance of Additively Manufactured Ceramic Turbine Vanes
Authors: Fox Andrew , Lynch Stephen , Young Jason C. , Frick Carl P. , Hankins Jennifer , Kuhn Kyle , Brinckmann Stephan A. , Fertig Ray S. 
Published: December 2023

Abstract
Ceramic materials are of significant interest in aviation and power generation gas turbine engines due to their low density and ability to withstand high temperatures. Increased cycle thermal efficiency and higher specific power output is possible by incorporating ceramic components that enable high turbine inlet temperatures and lower required cooling airflow levels. However, ceramics can be difficult and costly to form into the complex shapes used in gas turbine components, often requiring specialized multi-step processes. Furthermore, ceramic components in the hottest areas of a gas turbine, such as vanes or blade shroud seals, will still likely require cooling which is challenging to implement in conventional ceramic manufacturing approaches. Therefore, this study presents a multidisciplinary approach that investigates the design, fabrication, and overall cooling effectiveness evaluation of additively manufactured (AM), polymer derived ceramic (PDC) turbine vanes. A thermo-mechanically optimized vane design was generated, ceramic additive manufacturing of the complex cooling configuration was developed, and quantification of the increase in overall cooling effectiveness was performed in a 1X scale, high-speed facility using infrared thermography. This study produced a PDC AM process, capable of printing complex internal cooling schemes in 1X scale turbine vanes. It was found that the optimized vane more than doubled the overall cooling effectiveness observed in the baseline design, which reasonably agreed with thermomechanical optimization model predictions. Additionally, the optimized ceramic vane outperformed an identical metal vane, in terms of area averaged cooling effectiveness, suggesting that the ceramic vane could operate at reduced coolant flowrates to achieve comparable levels of cooling performance.
Variation Analysis Method Based on Product Feature Information Network
Authors: Chen Liang , Wei Naikun , Zheng Yu , Xi Juntong 
Published: December 2023

Abstract
Dimensional and geometric variations are significant factors of products at the manufacturing stage. Because of these variations, the physical appearance or functionality of the final product may deviate from expectations. As of the present, research on variation analysis has been conducted at the feature level. To model the information and analyze the variation transfers of products, a graphical model is constructed by using the product feature and information. Through analysis of the relationship between the product and network model, a modeling process for the feature information network is proposed. Nodes, lines, and constraints in the network are defined in detail, and the dimension unit is defined to represent the dimension information within a part. Variations caused by connections between parts are divided into two categories of influence. Combining the dimension unit and the influence between parts, a variation analysis process is devised based on the proposed network model. To verify the effectiveness and feasibility of the proposed method, a case study is performed based on the grand assembly of a hull block. The result shows that the product can be modeled and the variation can be analyzed by the proposed network model.
Rigid-Compliant Hybrid Cellular Expansion Mechanisms With Motion Amplification and Superposition
Authors: Wang Tingwei , Yu Jingjun , Zhao Hongzhe 
Published: December 2023

Abstract
Motivated by heat dissipation, the rigid-compliant hybrid cellular expansion mechanisms with motion amplification and superposition are proposed in this paper. Compared with existing studies, the expansion mechanism is not only easy to realize the plane tessellation via cellular design due to its regular polygon structure but also has the ability of motion amplification and superposition due to its compliant displacement amplifier and rigid scissors. First, the scheme of expansion mechanisms, especially the working principle of motion amplification and superposition, is introduced. The configuration design of a family of expansion mechanisms is presented, including varying number of edges, concave/convex property, and inner/outer layout. Second, the constraint condition and analytical modeling of relations between output performances of expansion mechanisms and dimensional parameters are carried out. Third, the displacement amplification ratio of expansion mechanisms and output performances of several typical expansion mechanisms when they act as cells to tessellate a plane with a constrained area are analyzed. Finally, the output performances of expansion mechanisms are verified via the finite element analysis. The results show that proposed cellular expansion mechanisms are beneficial for realizing plane tessellation and offer motion amplification and superposition, which provide prospects in the field of mechanism design such as metamaterials.
An Improved Shape Annealing Algorithm for the Generation of Coated Deoxyribonucleic Acid Origami Nanostructures
Authors: Babatunde Bolutito , Cagan Jonathan , Taylor Rebecca E. 
Published: December 2023

Abstract
In recent years, the field of structural DNA nanotechnology has advanced rapidly due to transformative design tools. Although these tools have been revolutionary, they still bear one overall limitation of requiring users to fully conceptualize their designs before designing. Recently, a simple computational casting technique was developed using generative optimization strategies to automate the DNA origami nanostructure design. This approach employs a shape annealing algorithm, which creates a formal language of honeycomb nanostructures with shape grammars and drives designs from the language toward a desired configuration using simulated annealing. This initial demonstration of the approach can generate novel scaffold routing schemes for creating solid or hollow structures constrained by the boundaries of polyhedral meshes. The results from the initial approach, particularly from the hollow structures, reveal a challenging design space. This simple technique generates novel scaffold routing schemes that do not replicate the overall polyhedral mesh shape and are limited in their ability to control scaffold path exploration in the design space. This paper demonstrates an approach for achieving different levels of consistent effective wall thicknesses and improving the quality of mesh coverage for hollow structures that can be tuned and optimized by introducing a more refined computational casting technique. We achieve these improvements through changes in the simulated annealing algorithm by adding a Hustin move set algorithm that dynamically adjusts the performance of the overall design and redefining how these hollow designs are articulated. This work illustrates how the technique can navigate a challenging design space to generate effective hollow designs.
Evaluation of Neural Network-Based Derivatives for Topology Optimization
Authors: Najmon Joel , Tovar Andres 
Published: December 2023

Abstract
Neural networks have gained popularity for modeling complex non-linear relationships. Their computational efficiency has led to their growing adoption in optimization methods, including topology optimization. Recently, there have been several contributions toward improving derivatives of neural network outputs, which can improve their use in gradient-based optimization. However, a comparative study has yet to be conducted on the different derivative methods for the sensitivity of the input features on the neural network outputs. This paper aims to evaluate four derivative methods: analytical neural network’s Jacobian, central finite difference method, complex step method, and automatic differentiation. These methods are implemented into density-based and homogenization-based topology optimization using multilayer perceptrons (MLPs). For density-based topology optimization, the MLP approximates Young’s modulus for the solid isotropic material with penalization (SIMP) model. For homogenization-based topology optimization, the MLP approximates the homogenized stiffness tensor of a representative volume element, e.g., square cell microstructure with a rectangular hole. The comparative study is performed by solving two-dimensional topology optimization problems using the sensitivity coefficients from each derivative method. Evaluation includes initial sensitivity coefficients, convergence plots, and the final topologies, compliance, and design variables. The findings demonstrate that neural network-based sensitivity coefficients are sufficiently accurate for density-based and homogenization-based topology optimization. The neural network’s Jacobian, complex step method, and automatic differentiation produced identical sensitivity coefficients to working precision. The study’s open-source code is provided through a python repository.
A Multi-Fidelity Bayesian Optimization Approach for Constrained Multi-Objective Optimization Problems
Authors: Lin Quan , Hu Jiexiang , Zhou Qi , Shu Leshi , Zhang Anfu 
Published: December 2023

Abstract
In this paper, a multi-fidelity Bayesian optimization approach is presented to tackle computationally expensive constrained multiobjective optimization problems (MOPs). The proposed approach consists of a three-stage optimization framework designed to search for promising candidate points. In the first stage, an acquisition function is proposed to identify a feasible solution if none is available in the current set of sampling points. Subsequently, a new multi-fidelity weighted expected hypervolume improvement function is developed to find better solutions. In the third stage, a constrained weighted lower confidence bound acquisition function is presented to enhance the constraint predictions and refine the solutions near the constraint boundary. Additionally, a filter strategy is suggested to determine whether constraint updating is necessary, aiming to save computational resources and improve optimization efficiency. Moreover, to expedite the optimization process, a parallel optimization approach is further developed based on the suggested three-stage optimization framework. To achieve this, a multi-fidelity influence function is introduced, allowing the proposed approach to determine a desired number of candidate points within a single iteration. Lastly, the proposed approach is demonstrated through six numerical benchmark examples, which verifies its significant advantages in addressing expensive constrained MOPs. Besides, the proposed approach is applied to the multiobjective optimization of a metamaterial vibration isolator, resulting in the attainment of satisfactory solutions.
A Design Framework for Semi-Active Structural Controlled Adjustable Constant Force Mechanisms
Authors: Rehman Tanzeel Ur , Li Jing , Qaiser Zeeshan , Johnson Shane 
Published: December 2023

Abstract
Semi-active adjustable constant force mechanisms (ACFMs) are an emerging alternative in applications where energy-efficient control of constant force environments is required. However, there is a lack of design strategies in the literature for semi-active ACFMs. This study addresses this gap by presenting a design strategy for ACFMs that semi-actively tunes the constant force by structural control. A design framework is presented, which consists of an optimization of a high slenderness large stroke constant force mechanism (CFM) followed by a parametric study on adjusting constant force through slenderness reduction by repositioning the boundary condition location. The design framework was able to change constant force ranging from two to four times with a stroke of 11–26% of the mechanism footprint. A selected design with a larger force magnitude was fabricated and experimentally tested, demonstrating a change in constant force of 2.01 times, which is comparable to that of active control designs and improved compactness, i.e., stroke of 11% of the footprint of the mechanism. In conclusion, the proposed ACFM design framework maximizes the initial CFM stroke and achieves constant force tuning by changing beam slenderness, resulting in compact and efficient ACFM designs.