bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quasi‐static fracture characterization of fiber metal laminate with crack resistance curve based on δ5
Authors: Zhang Jipeng , Wang Yue , Yang Wen , Dai Xiangjun , Zhao Yuan , Fang Guodong 
Published: December 2022

AbstractFiber metal laminate (FML) is a hybrid composite typical in aircraft industry. It is necessary to effectively characterize the quasi‐static fracture performance of FML, considering the importance of damage tolerance design of aircraft structures and the complicated fracture mechanism of FML. In present investigation, glass fiber reinforced aluminum laminates (Glare) with middle cracks were tested under quasi‐static tensile load. The experimental crack resistance curve (R curve) based on the special crack opening displacement at original crack tip (δ5) was used for revealing the superior crack resistance of Glare laminate to aluminum sheet, which expressed in crack extension aspect was the extended critical crack length. This was thought to be benefit from the contributions of glass fiber layers and fiber/metal delamination, by performing the progressive damage analysis. Since δ5 can embody the elastic–plastic response of the crack but without need to interactively correct for crack tip plasticity. The δ5‐R curve‐based macro and meso fracture models were proposed to accurately predict the residual strength and stable crack extension of Glare laminate, which gave further evidence for the effectiveness of δ5‐R curve in characterizing the quasi‐static fracture performance of FML.
Federated analyses of multiple data sources in drug safety studies
Authors: Gedeborg Rolf , Igl Wilmar , Svennblad Bodil , Wilén Peter , Delcoigne Bénédicte , Michaëlsson Karl , Ljung Rickard , Feltelius Nils 
Published: December 2022

AbstractPurposeStudies of rare side effects of new drugs with limited exposure may require pooling of multiple data sources. Federated Analyses (FA) allow real‐time, interactive, centralized statistical processing of individual‐level data from different data sets without transfer of sensitive personal data.MethodsWe review IT‐architecture, legal considerations, and statistical methods in FA, based on a Swedish Medical Products Agency methodological development project.ResultsIn a review of all post‐authorisation safety studies assessed by the EMA during 2019, 74% (20/27 studies) reported issues with lack of precision in spite of mean study periods of 9.3 years. FA could potentially improve precision in such studies. Depending on the statistical model, the federated approach can generate identical results to a standard analysis. FA may be particularly attractive for repeated collaborative projects where data is regularly updated. There are also important limitations. Detailed agreements between involved parties are strongly recommended to anticipate potential issues and conflicts, document a shared understanding of the project, and fully comply with legal obligations regarding ethics and data protection. FA do not remove the data harmonisation step, which remains essential and often cumbersome. Reliable support for technical integration with the local server architecture and security solutions is required. Common statistical methods are available, but adaptations may be required.ConclusionsFederated Analyses require competent and active involvement of all collaborating parties but have the potential to facilitate collaboration across institutional and national borders and improve the precision of postmarketing drug safety studies.
Dielectric relaxation studies of poly(ethylene oxide) with the addition of salt or nanofiller
Authors: Yusoff Siti Nor Hafiza Mohd , Halim Suhaila Idayu Abdul , Tarmizi Amirah Amalina Ahmad , Chan Chin Han 
Published: December 2022

AbstractPoly(ethylene oxide) (PEO)–lithium perchlorate (LiClO4) serves as the classical model of polymer–salt systems with good polymer–salt molecular interaction at low salt concentration, whereas titanium dioxide (TiO2) without any surface treatment when added to PEO serves as a classical model of polymer–filler systems with weak polymer–filler molecular interaction. The correlation of molecular interactions of polymer–salt or polymer–filler with thermal properties of the systems, which govern the formation of morphologies of the systems, was attempted in a previous study. Hence, this work focuses on the correlation of morphologies and dielectric relaxation properties of PEO with the addition of LiClO4 or TiO2 investigated using polarized optical microscopy and electrochemical impedance spectroscopy over the frequency range from 50 Hz to 1 MHz at 25 °C. The effects of the addition of LiClO4 or TiO2 on the dynamics and relaxations of the polymer chain of PEO are discussed empirically following the fluctuation–dissipation effects from the common electrochemical terms and equivalent circuit model. The PEO–LiClO4 system seems to be one of the promising polymer electrolytes for application in lithium rechargeable batteries where the charged entities may arise from the interaction of salt with the ether oxygen of PEO in the amorphous region. Meanwhile, the PEO–TiO2 system may be analogous to a polar polymer with longitudinal dipoles along the PEO backbone, ethylene oxide monomers (from PEO) of which may represent the molecular dipole or charged entity. The findings show that the transport of charged entities in the PEO systems after the addition of LiClO4 or TiO2 is dominated by short‐range motion at room temperature. © 2022 Society of Industrial Chemistry.
Examining the construct validity of the Personality Assessment Questionnaire for ICD‐11 (PAQ‐11) personality trait domains in a community sample
Authors: Sellbom Martin , Chiasson Payton M. , Brown Tiffany A. , Bach Bo 
Published: December 2022

AbstractThe ICD‐11 has a new diagnostic system for personality disorder, which includes five optional trait specifiers to characterize the diagnosed pathology. The current study evaluated the internal structure and construct validity of the Personality Assessment Questionnaire for ICD‐11 (PAQ‐11) personality trait domains in a US population‐representative community sample. An exploratory factor analysis revealed the support for a four‐factor model underlying the 17 PAQ‐11 items, reflecting four of the five ICD‐11 trait domains (Negative Affectivity, Detachment, Disinhibition and Anankastia). Moreover, correlation analyses revealed that the PAQ‐11 domain scale scores were associated, as expected, with their counterparts from two other ICD‐11 trait domain measures, as well as with traditional personality disorder scores. More broadly, the results raised questions about the structural integrity of the Dissociality domain scale, and the discriminant validity of the Disinhibition and Anankastia scales. The overall conclusion was nevertheless promising with respect to the PAQ‐11 serving as a brief screening measure for the ICD‐11 trait domains.
Environment‐dependent influence of fruit size upon the distribution of the Malesian archipelagic flora
Authors: Trethowan Liam A. , Jennings Laura , Bramley Gemma , Clark Ruth , Dawson Sally , Moore Alison , Pearce Laura , Puglisi Carmen , Riwu‐Kaho Michael , Rosaria  , Trias‐Blasi Anna , Utteridge Timothy M. A. , Rustiami Himmah 
Published: December 2022

Societal Impact StatementWe found evidence that larger fruited plant species are more likely to be found in aseasonal wet areas of Malesia. These areas are likely to be impacted by increasing human encroachment, which threatens both large‐fruited species and the large fauna that are most likely responsible for their dispersal. This synergistic threat could drive the loss of fruit‐crop relatives that potentially have key traits for resilient fruit crops of the future.Summary

It is unclear how fruit size determines distributions of megadiverse tropical flora. Energetic constraints of ecosystems suggest plant species with larger fruit should be found in the higher productivity, aseasonal wet tropics. However, the probability of seed dispersal over large scales should be increased by fruits being smaller, due to being available to a greater number of dispersal agents.
We use a Bayesian phylogenetic model of species occurrence for >3400 species in Malesia to test how fruit size and environment interact to determine species distributions across the archipelago.
We show that larger fruited species are more likely to occur in aseasonal wet areas. We also found that smaller fruit size was associated with species occurrence in more mountainous areas.
Fruit size interacts with environmental variables to shape plant distributions across the megadiverse Malesian islands. The evolutionary processes that influence the patterns we have observed require further examination.
Pentacene Nanorods as Effective Photosensitizer for Photodynamic Therapy of Tumor via Singlet Fission
Authors: Zhang Rui , Cheng Ge , Li Mengxuan , Lv Hongying , Li Juan 
Published: December 2022

AbstractSinglet fission (SF), whereby a singlet exciton is converted into a pair of triplet excitons, can improve the efficiency of solar cells. Pentacene has been extensively studied as the most promising SF compound, owing to its 200% yield of triplet states. However, the easy degradation of pentacene in the presence of light and air owing to photooxidation cannot be explained by the classical 1O2 generation mechanism. To address this issue, in the present study, pentacene nanorods (Pc NRs) are prepared as a novel photosensitizer (PS); self‐carried Pc NRs exhibited higher 1O2 generation capacity. Thus, a novel 1O2 generation mechanism is proposed based on the SF effect. The initial photon absorption occurs to access single‐exciton states, S1–S3. Excited‐state Pc pairs accelerate the SF effect in pentacene NRs, leading to a non‐adiabatic transition to the dark D state. Dark D state is a singlet state by two triplets coupled overall, and it can transfer its energy to 3O2 for generating 1O2. Using Pc NRs as PSs, photodynamic therapy (PDT) inhibits tumor growth in 4T1 tumor‐bearing mice upon 405‐nm‐wavelength and 650‐nm‐wavelength laser irradiations. This study paves the way to discover novel PSs that are not considered with classical 1O2 generation mechanisms.
Surface Modification of Gold Nanoprisms and Their Self‐Assembly with Nanospheres
Authors: Zámbó Dániel , Kovács Dávid , Südi Gergely , Deák András 
Published: December 2022

AbstractControlled surface modification of gold particles is of central importance for the preparation of functional nano‐objects, which can be used both in fundamental research and in advanced photonic or nanomedicine applications. In this study, the surface modification of gold nanoprisms using different thiols, namely cysteamine, (16‐mercaptohexadecyl)trimethylammonium bromide (MTAB), and α‐methoxy‐ω‐mercapto polyethylene glycol (mPEG‐SH (5000 Da)) is investigated. The aim is to prepare binary surface‐modified thiol/PEG patchy gold nanoprisms, where the tips/edges and the face regions of the particles are covered by different thiol moieties. By investigating the time evolution of the prisms’ extinction spectra at different capping ligand concentration levels, the conditions to prepare such “patchy” particles are identified. While significantly faster adsorption kinetics are observed for MTAB compared to cysteamine, both molecule types can be used to prepare binary surface‐modified thiol/PEG particles. Prisms modified with only MTAB or PEG and subsequently assembled with negatively charged spheres show that MTAB forms hetero‐aggregates with the spheres, while PEG prevents particle attachment. For thiol (cysteamine or MTAB)/PEG binary surface‐modified prisms, it is found that the efficiency of sphere attachment at the tip/side region during self‐assembly is rather low, most likely due to the presence of PEG.
Comprehensive treatment of recurrent and metastatic nasopharyngeal carcinoma: advances and future directions
Authors: Fan Ming , Liu Dengqun , Zhu Guiquan , Ren Yazhou , Feng Mei 
Published: December 2022

AbstractThe standard of care for patients with recurrent and metastatic nasopharyngeal carcinoma remains unclear. There is an urgent need to identify effective and low‐toxicity treatment methods for such patients. The integration of current evidence to form an optimal treatment modality for recurrent and/or metastatic nasopharyngeal is worth exploring. In recent years, several outstanding clinical trials have emerged for the comprehensive treatment of recurrent and/or metastatic nasopharyngeal carcinoma . New evidence has been added for the local treatment of patients with metastasis. Endoscopic surgery, radiomics, and other technologies help achieve precise local treatment. Novel immunotherapeutic drugs have been approved for the treatment of patients with metastasis in China. The combination of immunotherapy, chemotherapy, and targeted therapy is promising and requires confirmation. Future studies will continue to focus on individualization and precision medicine.
Wavelength‐Dependent Photocurrent Generation Efficiency in the Carbon Nanowall Films
Authors: Zonov Ruslan , Fateev Arseniy , Obraztsov Alexander , Mikheev Gennady 
Published: December 2022

Herein, the efficiency of generation of unipolar photocurrent pulses under action of obliquely incident nanosecond laser pulses is studied in carbon nanowall (CNW) films on silicon substrate depending on the direction of the wave vector and polarization of the laser radiation. The films consist of flake‐like graphite crystallites of nanometer thickness. Each of the crystallites comprises stacked graphene atomic sheets oriented mostly perpendicular to the substrate surface with random orientation in other directions. The angular and polarization dependencies of the longitudinal and transverse photocurrents at wavelengths of 266, 354.7, 532, and 1064 nm are measured. The longitudinal and transverse photocurrents are odd functions of the incidence angle, and, for a given angle of incidence, they are even and odd functions of the polarization azimuth, respectively. It is noteworthy that with the decrease in exciting radiation wavelength, the conversion coefficients of laser pulse power into longitudinal and transverse photocurrents increase and decrease, respectively. At wavelength of 266 nm, the transverse photocurrent changes its polarity, and the longitudinal photocurrent generated by s‐polarized radiation exceeds the p‐polarized radiation photocurrent. The obtained results are explained by morphology peculiarities of the CNW films and the surface photogalvanic effect photocurrent generation.
A reliability allocation method for agricultural machinery based on AHP‐IFM
Authors: Dai Mengchu , Chen Chao , Zhou Le , Liang Yundong 
Published: December 2022

AbstractIn the product design phase, the available product failure data are limited, and the weight allocation method is often used to assign reliability targets to each unit. The integrated factors method (IFM) can calculate the reliability allocation weights considering multiple influencing factors simultaneously, but it cannot reflect the difference in the importance of each factor and each unit. The analytic hierarchy process (AHP) can calculate the relative importance weights of each factor and each unit. Combining the AHP with the IFM can make the IFM more adaptable to the system and more accurate for reliability allocation. However, the current combination method can cause two problems: the invalidation of the influencing factor weights and the imbalance of the unit weights. To address these two shortcomings, the AHP‐IFM proposed in this paper introduces a weight weakening factor and exponentially corrects the unit weights for units, which can better apply the relative importance weights of each influencing factor and each unit to the reliability allocation. The effectiveness of the AHP‐IFM is verified by comparison with existing methods and data. Finally, an AHP‐IFM applicable to agricultural machinery is proposed, and the reliability allocation of a no‐till seeder is used as a case to verify the feasibility of the AHP‐IFM.
An ensemble model considering health index based classification for remaining useful life prediction
Authors: Han Tengfei , Li Yaping 
Published: December 2022

AbstractAccurate prediction of remaining useful life (RUL) plays an important role in the formulation of maintenance strategies. However, due to the diversity of the failure mode of equipment, there are significant differences between the degradation data, which greatly affects the accuracy of RUL prediction. In this case, an ensemble prediction model considering health index‐based (HI‐based) classification is proposed in this paper. Firstly, the stacked autoencoder (SAE) is employed to construct the HI. Then, the time window is used to sequentially process the HI sequence, so that many data segments with the same length can be achieved. To differentiate the data with the similar degradation process, K‐means and Xgboost are selected to construct offline and online data classification models respectively. Finally, according to the results of the data classification, the ensemble model that integrates multiple machine learning methods are separately trained and then adaptively used for RUL prediction. In addition, integrating multiple methods helps to improve the generalization ability of the model. The NASA C‐MAPSS dataset is applied to verify the effectiveness of the proposed method, and the results show that the proposed method achieves a higher prediction accuracy and shorter computational time than other existing prediction models.
Proximal femur parameter measurement via improved PointNet++
Authors: Yang Jiayu , Li Zhe , Zhan Pengyu , Li Xinghua , Wang Kunzheng , Han Jungang , Yang Pei 
Published: December 2022

AbstractBackgroundFemoral morphological studies and parameter measurements play a crucial role in diagnosing hip joint disease, preoperative planning for total hip arthroplasty, and prosthesis design. Doctors usually perform parameter measurements manually in clinical practice, but it is time‐consuming and labor‐intensive. Moreover, the results rely heavily on the doctor's experience, and the repeatability is poor. Therefore, the accurate and automatic measurement methods of proximal femoral parameters are of great value.MethodWe collected 300 cases of clinical CT data of the femur. We introduced the adaptive function adjustment module to the neural network PointNet++ to strengthen the global feature extraction of the point cloud for improving the accuracy of femur segmentation. We used the improved PointNet++ network to segment the femur into three parts: femoral head, femoral neck, and femoral shaft. We evaluated the segmentation accracy using Dice Coefficient, MIoU, recall, and precision indicators. We achieved the automatic measurement of the proximal femoral parameters using the shape fitting algorithms, and compared the automatic and manual measurement results.ResultsThe Dice, MIoU, recall and precision indicator of the improved segmentation algorithm reached 98.05%, 96.55%, 96.63%, and 96.03%, respectively. The comparison between automatic and manual measurement results showed that the mean accuracies of all parameters were above 95%, the mean errors were less than 5 mm and 3°, and the ICC values were more than 0.8, indicating that the automatic measurement results were accurate.ConclusionOur improved PointNet++ network provided high‐precision segmentation of the femur. We further completed automatic measurement of the femur parameters and verified its high accuracy. This method is of great value for the diagnosis and preoperative planning of hip diseases.
Nonlinear set‐membership state estimation based on the Koopman operator
Authors: Pan Zhichao , Liu Fei 
Published: December 2022

SummaryIn this study, the Koopman operator is applied to solve the challenging nonlinear set‐membership (SM) state estimation problem. The basic idea is to lift the nonlinear system into a linear one with a higher dimension, and then linear SM estimation methods can be adopted. The Koopman operator is an infinite‐dimensional linear decomposition of nonlinear dynamics. This linearized system can fully describe the state evolution of the nonlinear dynamics with input, output, and noises. To apply SM state estimation algorithms, a finite‐dimensional approximation is obtained by using the data‐driven method. Meanwhile, the statistical properties of the approximation errors are also utilized to reduce the conservativeness of the filter. The probability distributions of approximation errors are described by sample particles. Coupled with the unknown but bounded noises, the linearized system is associated with two types of uncertainties. To this end, the merging SM and stochastic strategy is adopted to construct a class of confidence state set whose level approaches 1. After that, the optimal filter gain is given to minimize the size of the confidence state set. Finally, three numerical examples are given to demonstrate the effectiveness of the proposed method.
A simple method to determine the reactivity of calcium carbonate in soils
Authors: Sheikh‐Abdullah Shuela M. , Hirmas Daniel R. , Koop Aaron N. 
Published: December 2022

AbstractDetermination of soil carbonate is important for numerous chemical and physical soil processes in arid and semi‐arid zones. Here, we modify a conventional method to more easily determine active CaCO3 (ACC) fraction in soils. Unlike the conventional method where the oxalate used up after reaction with carbonate is determined by titration with KMnO4, the proposed method uses the difference between total carbonate analyzed before and after reaction with oxalate to determine ACC. The method compared well to the conventional approach; the procedure was faster, did not require KMnO4, and appeared to be unaffected by exchangeable Ca. The proposed method is well‐suited for samples across a wide range of total carbonate.
Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context
Authors: Harrison Joseph S. , Josefy Matthew A. , Kalm Matias , Krause Ryan 
Published: December 2022

AbstractResearch SummaryHuman coding of unstructured text can enable scholars to measure complex latent constructs for use in empirical analysis, but also requires substantial time and resources that limit the number and sample sizes of studies using this approach. We demonstrate how supervised machine learning (ML) can overcome these constraints by allowing scholars to scale human‐coded data. Using board leadership as an illustrative context, we apply this method to create a large‐scale dataset (N = 22,388) from smaller scale human codings of CEO duality and board chair orientations from company proxy statements. We further demonstrate the potential value of this approach by using the resulting dataset to examine the relationships among board leadership, firm performance, and CEO dismissal. The ML code and dataset are available at 10.5281/zenodo.7304697.Managerial SummaryManually converting unstructured text into usable data requires considerable time and resources. This article outlines a replicable process for applying supervised machine learning (ML) to overcome these constraints by scaling manually coded data. While ML is often used to identify patterns or predict relationships within a given dataset, we show how scholars and practitioners can build valuable custom algorithms at an earlier stage in the process—when first building a dataset. We illustrate this approach by training ML algorithms to replicate human codings of CEO duality and board chair control and collaboration orientations from over 22,000 company filings. We then show how this approach can support new knowledge development by using these data to explore the relationships among board leadership, company performance, and CEO dismissal.