bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlates of jaw functional limitation, somatization and psychological distress among different temporomandibular disorder diagnostic subtypes
Authors: Yap Adrian Ujin , Kim Sunghae , Lee Byeong‐min , Jo Jung Hwan , Park Ji Woon 
Published: October 2023

AbstractObjectivesThis study investigated the jaw functional status and severity of somatic/psychological symptoms in different Diagnostic Criteria for temporomandibular disorders (DC/TMD) diagnostic subtypes and established the correlates between jaw functional limitation, somatization, depression and anxiety.MethodsData were accrued from consecutive ‘first‐visit’ patients seeking TMD treatment at a university‐based oral medicine/diagnosis clinic. Axis I physical TMD diagnoses were derived using the DC/TMD methodology and patients were categorized into pain‐related (PT), intra‐articular (IT) and combined (CT) TMD groups. Axis II measures were also administered and included the Jaw Functional Limitation Scale‐20 (JFLS‐20), Patient Health Questionnaire‐15 and 9 (PHQ‐15 and PHQ‐9) and General Anxiety Disorder Scale‐7 (GAD‐7). Chi‐square/Kruskal–Wallis tests and Spearman's correlation were employed for statistical evaluations (α = .05).ResultsThe final dataset consisted of 772 TMD patients (mean age of 37.7 ± 15.9 years; 70.2% females). The prevalence of PT, IT and CT was 11.9%, 15.7% and 72.4%, respectively. Significant differences in functional jaw limitations, somatization, depression (CT, PT > IT) and anxiety (CT > PT, IT) were observed. Moderate‐to‐severe somatization, depression and anxiety were detected in 12.6%–15.7% of patients. For all three TMD groups, JFLS global scale/subscale scores were weakly associated with somatization, depression and anxiety scores (rs < 0.4). Moderate‐to‐strong correlations were noted between somatization, depression and anxiety (rs = 0.50–0.74).ConclusionsFunctional jaw limitations were associated with painful TMDs but appear to be unrelated to somatization and psychological distress. Somatization and depression/anxiety were moderately correlated, underscoring the importance of somatic symptom screening when managing TMD patients.
Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network
Authors: Chu Honghu , Chun Pang‐jo 
Published: October 2023

AbstractHigh‐resolution (HR) crack images offer more detailed information for assessing structural conditions compared to low‐resolution (LR) images. This wealth of detail proves indispensable in bolstering the safety of unmanned aerial vehicle (UAV)‐based inspection procedures and elevating the precision of small crack segmentation. Nonetheless, achieving a balance between segmentation accuracy and GPU memory consumption poses a substantial challenge for deep learning models when processing HR crack images. To overcome this challenge, a novel “HR crack segmentation framework” (HRCSF) is proposed, specifically designed to meticulously segment crack images with resolutions exceeding 4K. First, a multiscale crack feature extraction network (MsCFEN) was proposed with the embedment of the strip pooling operation to enhance the representation of the transverse and longitudinal crack pixels from the complex backgrounds. Subsequently, two cascaded operations were tailored to MsCFEN, enabling a comprehensive refinement process that incorporates both global and local aspects. Furthermore, to fully leverage the potential of each proposed component in the refinement process, the complete architecture was trained using a loss function with embedded boundary optimization. Conclusively, a UAV‐based case study was conducted on a real bridge in Changsha, demonstrating HRCSF's practicability in segmenting HR crack images. The implementation of HRCSF allows the UAV to perform crack inspection effectively from a distance of 3 m away from the girder, resulting in a significant 50% reduction in inspection time compared to LR segmentation methods while maintaining high detection accuracy.
Social justice orientations: Exploring their impact on poverty attributions and support for social protection
Authors: Alcañiz‐Colomer Joaquín , Valor‐Segura Inmaculada , Moya Miguel 
Published: October 2023

AbstractDistributive justice remains a central issue in contemporary welfare states, even more during times of economic hardship and social uncertainty. In this article, we analyze how attitudes toward the principles of normative distributive justice (equality, need, equity, and entitlement) are related to support for the redistribution of resources (Study 2) and attitudes toward social protection policies (Studies 1 and 3). In Study 1 (N = 325), we found that equality and need positively predicted attitudes toward social protection policies while equity and entitlement negatively predicted these attitudes. In Study 2 (N = 49,519), using data from Round 9 of the European Social Survey, we replicated this linking normative orientation toward different distributive justice principles with support for redistribution. We replicated these results in Study 3 (N = 494). In addition, we explored the role of attributions for poverty in the relationship found in Studies 1 and 2. Attributions for poverty mediated the relationship between orientations toward justice principles and attitudes toward social protection policies.
Violence in pandemic times: The dynamic relationship between COVID‐19 and intimate partner violence
Authors: Hernández Wilson , Cozzubo Angelo , Aguilar José Carlos , Agüero Jorge M. , Mendoza José 
Published: October 2023

AbstractIntimate partner violence (IPV) increased during the COVID‐19 lockdown, but few studies use national data and explore underlying mechanisms. To address this gap, we study the changes in IPV during the first ten months of the pandemic in Peru. We study the number of calls received by the national helpline for domestic violence victims, Línea 100, using an event study model. Results show that during lockdown, IPV calls experienced nonlinear variations. Calls for psychological violence showed the most significant variation, followed by those for physical violence, while no significant changes for sexual violence were identified. Prior history of violence and alcohol or drug consumption appears to be the most important underlying mechanisms. Results suggest that policy efforts during acute health and economic crises should aim at risk factors that typically predict violence and prioritize rapidly connecting survivors to quality services.
Understanding Collective Human Behavior in Social Media Networks Via the Dynamical Hypothesis: Applications to Radicalization and Conspiratorial Beliefs
Authors: Necaise Aaron , Han Jingjing , Vrzáková Hana , Amon Mary Jean 
Published: October 2023

AbstractThe dynamical hypothesis has served to explore the ways in which cognitive agents can be understood dynamically and considered dynamical systems. Originally used to explain simple physical systems as a metaphor for cognition (i.e., the Watt governor) and eventually more complex animal systems (e.g., bird flocks), we argue that the dynamical hypothesis is among the most viable approaches to understanding pressing modern‐day issues that arise from collective human behavior in online social networks. First, we discuss how the dynamical hypothesis is positioned to describe, predict, and explain the time‐evolving nature of complex systems. Next, we adopt an interdisciplinary perspective to describe how online social networks are appropriately understood as dynamical systems. We introduce a dynamical modeling approach to reveal information about emergent properties in social media, where radicalized conspiratorial beliefs arise via coordination between user‐level and community‐level comments. Lastly, we contrast how the dynamical hypothesis differs from alternatives in explaining collective human behavior in social networks.
Steady‐state versus chemotherapy‐based hematopoietic cell mobilization after anti‐CD38‐based induction therapy in newly diagnosed multiple myeloma
Authors: Teipel Raphael , Rieprecht Susanne , Trautmann‐Grill Karolin , Röllig Christoph , Klötzer Christina , Zimmer Kristin , Rathaj Grit , Bach Enrica , Brückner Mandy , Heyn Simone , Wang Song‐Yau , Jentzsch Madlen , Schwind Sebastian , Kretschmann Theresa , Egger‐Heidrich Katharina , Remane Yvonne , Franke Georg‐Nikolaus , von Bonin Malte , Bornhäuser Martin , Platzbecker Uwe , Hölig Kristina , Merz Maximilian , Vučinić Vladan 
Published: October 2023

AbstractBackgroundThe incorporation of anti‐CD38 monoclonal antibodies (mAb) in induction regimens of newly diagnosed transplant‐eligible multiple myeloma (MM) patients has been established as a new standard. However, the optimal strategy of stem cell mobilization in this context is not yet clear.Study Design and MethodsFrom May 2020 till September 2022, we retrospectively reviewed patients receiving anti‐CD38 mAb‐based induction therapy followed by stem cell mobilization either in a steady‐state protocol (SSM) using 10 μg/kg granulocyte colony‐stimulating factor (G‐CSF) for 5 days or in a chemotherapy‐based protocol (CM) using 1–4 g/m2 cyclophosphamide and G‐CSF.ResultsOverall, 85 patients (median age 61 years) were included in the analysis. In total, 90 mobilization attempts were performed, 42 with SSM and 48 with CM. There was no significant difference in the median concentration of CD34+ cells in peripheral blood (PB) prior to apheresis between SSM and CM (61/μL vs. 55.4/μL; p = .60). Cumulative CD34+ yields did not differ between the groups with median of 6.68 and 6.75 × 106/kg body weight, respectively (p = .35). The target yield (≥4 × 106 CD34+ cells/kg body weight) was reached in 88% (CM) and 86% (SSM), with a high proportion even after a single apheresis session (76% vs. 75%).Plerixafor was found to be more frequently used in SSM (52%) than in CM (23%; p < .01). A total of 83 patients underwent autologous transplantation and all were engrafted.ConclusionsStem cell collection in patients undergoing anti‐CD38‐based induction therapy is feasible with either CM or SSM, although SSM more frequently requires plerixafor.
Efficacy and safety of turoctocog alfa in patients with hemophilia A requiring surgical procedures: A multicentre retrospective study
Authors: Drillaud Nicolas , Cussac Vincent , Bertho Pierre‐Olivier , Horvais Valérie , Beurrier Philippe , Ternisien Catherine , Rose Johann , Fouassier Marc , Babuty Antoine , Trossaërt Marc 
Published: October 2023

AbstractBackgroundTuroctocog alfa is a recombinant Factor VIII used in patients with hemophilia A. The aim is to assess the real‐life evidence of turoctocog alfa in surgery.Study Design and MethodsData were extracted from a national database.ResultsTuroctocog alfa was used for 86 surgeries (49 major and 37 minor) in 56 patients. The results are expressed as medians (interquartile range).Six (10.7%) patients had severe hemophilia A, four (7.1%) moderate, and 46 (82.2%) mild. For patients who underwent major surgeries, basal plasma FVIII coagulant activity (FVIII:C) levels were 15 IU.dL−1 (8–22). Eight (5–14) infusions were given, at a preoperative loading dose of 40.0 (35.0–45.5) IU.kg−1 and a total dose of 253.3 (125.0–507.0) IU.kg−1. In patients who underwent minor surgeries, basal FVIII:C levels were 18 IU.dL−1 (9–31). Two (1–3) infusions were required, at a preoperative loading dose of 34.0 (28.8–38.5) IU.kg−1 and a total dose of 73.7 (37.6–122.1) IU.kg−1. The overall clinical efficacy was judged excellent/good in 77 procedures (89.5%) and fair/poor in nine (10.5%). The fair/poor efficacy concerned seven patients (six mild hemophilia and one severe), for four urological surgeries, two dermatological procedures, one heart surgery, one ear‐nose‐throat procedure, and one dental avulsion in the patient with severe hemophilia. Three out of those seven patients received antiplatelet therapy. No thromboembolic events, anti‐FVIII antibodies, or adverse events were reported.DiscussionThe efficacy and safety of turoctocog alfa were confirmed for the management of surgery in patients with hemophilia A. No adverse events were observed and overall efficacy was good.
Regulatory convergence within technical barriers to trade
Authors: Ghodsi Mahdi 
Published: October 2023

AbstractThis paper analyses how regulatory convergence in different categories of technical barriers to trade (TBTs) imposed on imports of goods in information and communications technology (ICT) globally affected the values, volumes and unit values of imported goods during the period 1996–2019. Keywords cited in TBTs that are notified to the World Trade Organisation (WTO) give an indication of the regulatory objectives behind the imposition of TBTs. MAST also classifies TBTs based on their applicability, procedural and administrative uses, factors which will also be taken into consideration in the analysis. However, the objectives of TBTs may provide better insights to policymakers. TBTs are non‐discriminatory measures that are imposed unilaterally on all trading partners and on domestic producers. It is not feasible to analyse unilateral TBTs in a gravity setting, as they are excluded by the introduction of country‐product‐time fixed effects that control for multilateral resistances. However, regulatory convergence in TBT categories is a bilateral time‐varying variable that is analysed in a gravity model in this paper. The empirical results suggest that regulatory convergence between trading partners in some TBT categories stimulates import values and volumes. However, the impact is very heterogeneous across TBT objectives and classes and across ICT product categories.
Presumed residual thymic tissue is a common finding in thoracic computed tomography in adult dogs
Authors: Vester Siemone C. , Bergmann Wilhelmina , van den Broek Dirk H. N. , Veraa Stefanie , Schaafsma Irene A. 
Published: October 2023

AbstractResidual thymic tissue is a common incidental finding in thoracic CT of human adults. To determine whether presumed residual thymic tissue is also a common incidental finding in adult dogs, a two part‐study was performed. The first part was a prospective, descriptive design where CT examination was performed in six canine cadavers within 24 h after death and presumed residual thymic tissue was examined pathologically. The second part of the study was a retrospective, analytical design where medical records of our institution were searched for thoracic CT scans of adult dogs performed in the year 2020. Age, sex, breed, presence of presumed thymic tissue, location, shape, attenuation, homogeneity, and width of the tissue were recorded and comparisons were performed using these data. In 4 of 6 of the prospective cases, thymic tissue was present on histology and in 2 of 6 dogs the presence of thymic tissue could not be confirmed. For the retrospective study, in 161/169 (95.3%) cases with presumed residual thymic tissue were detected. Shape and size were highly variable with either homogeneous (46.6%), heterogeneous (42.9%), or mixed (10.6%) attenuation. Dogs with presumed residual thymic tissue were significantly younger (median: 9.1 years; range: 1.2–14.3 vs. median: 10.5 years; range: 9.4–12.3) as were dogs with homogeneous attenuation of the tissue (median: 8.1 years; range: 1.2–14.3 vs. median: 9.5 years; range: 4.0–14.3). In conclusion, results indicated that presumed residual thymic tissue is a common CT finding in adult dogs and can be considered incidental.
Totally real algebraic integers in short intervals, Jacobi polynomials, and unicritical families in arithmetic dynamics
Authors: Noytaptim Chatchai , Petsche Clayton 
Published: October 2023

AbstractWe classify all postcritically finite unicritical polynomials defined over the maximal totally real algebraic extension of . Two auxiliary results used in the proof of this result may be of some independent interest. The first is a recursion formula for the diameter of an interval, which uses properties of Jacobi polynomials. The second is a numerical criterion that allows one to give a bound on the degree of any algebraic integer having all of its complex embeddings in a real interval of length less than 4.
Leveraging Additive Manufacturing to Fabricate High Temperature Alloys With Co-Designed Mechanical Properties and Environmental Resistance
Authors: Pillai R. , Ren Q.Q. , Su Yi-Feng , Kurfess Rebecca , Feldhausen Thomas , Nag Soumya 
Published: October 2023

Abstract
A paradigm shift in the traditional sequential design approaches is critically essential to create application-specific hierarchical and multifunctional materials with superior long-term performance for next-generation energy technologies involving extreme environments. In the current work, we aim to leverage the flexibility and geometric/compositional complexity offered by additive manufacturing to demonstrate this new approach by codesigning a compositionally graded Ni-based alloy for molten salts\sCO2 heat exchangers to enable mitigation of environmental degradation of surfaces exposed to molten halide salts, while simultaneously suppressing the consequent deterioration in mechanical stability. Thermokinetic modeling describing the underlying physics of thermally- and environmentally induced spatiotemporal compositional and microstructural evolution will be employed to predict the parameter space of material deposition processes and precisely identify the required composition gradient. Preliminary corrosion and mechanical testing of the dual material demonstrated the potential of the material to replace existing solid solution strengthened materials for this application.
Performance, Emissions, and Decarbonization of an Industrial Gas Turbine Operated With Hydrotreated Vegetable Oil
Authors: Runyon Jon , James Stuart , Kadam Tanmay , Ofir Barak , Graham David 
Published: October 2023

Abstract
As part of Uniper's strategy for carbon neutrality in its European power generation by 2035, a Kraftwerk Union/Siemens V93.0 gas turbine (GT) in Malmö, Sweden was operated with hydrotreated vegetable oil (HVO) as a low-carbon replacement for gas oil in July 2021. Prior to HVO operation, a feasibility study was conducted including fuel comparison, flame temperature modeling, and a hazard identification study. During the two-day demonstration, GT performance was monitored using either gas oil or HVO at startup, full load, part load, and shut-down. Accredited emissions of NOx, CO, SO2, and dust were measured to allow comparison between fuels. When firing HVO, no adverse GT operations were encountered, and direct flame imaging was used to observe the successful HVO ignition process at startup. NOx emissions were nominally similar to gas oil during HVO operation. Therefore, the water injection rate for NOx control was unchanged between fuels, confirming the predictions of the flame temperature modeling. Dust, CO, and SO2 emissions reduced during HVO operation. HVO also enables significant lifecycle CO2 emissions reductions compared with fossil gas oil with ∼163 tCO2 emissions avoided in this trial. This trial provides evidence for future site fuel conversion. Further testing and monitoring is required to develop evidence regarding the long-term impact of HVO operation on fuel storage, fuel delivery, and hot gas path components. To the authors' knowledge, this trial is the first successful demonstration of HVO use in an industrial gas turbine in the world.
Spatially Resolved Modeling of the Nonlinear Dynamics of a Laminar Premixed Flame With a Multilayer Perceptron—Convolution Autoencoder Network
Authors: Rywik Marcin , Zimmermann Axel , Eder Alexander J. , Scoletta Edoardo , Polifke Wolfgang 
Published: October 2023

Abstract
This work presents a multilayer perceptron-convolutional auto-encoder (MLP-CAE) neural network, which accurately predicts the two-dimensional flame dynamics of an acoustically excited premixed laminar flame. The architecture maps the acoustic perturbation time series into a heat release rate field, capturing flame lengths and shapes. This extends previous neural network models, which predicted only the field-integrated value. The MLP-CAE comprises two submodels: an MLP and a CAE. The idea behind the CAE network is to find a lower dimensional latent space of the heat release rate field. The MLP is responsible for modeling the flame dynamics by transforming the acoustic forcing signal into this latent space, enabling the decoder to produce the flow field distributions. To train the MLP-CAE, computational fluid dynamics (CFD) flame simulations with a broadband acoustic forcing were used. Its normalized amplitude was set to 0.5 and 1.0, ensuring a nonlinear flame response. The network was found to accurately predict the perturbed flame shapes. Additionally, it conserved the correct frequency response as verified by the global and local flame describing functions. The MLP-CAE provides a building block toward a potential shift away from a “0D” flame analysis with the acoustic compactness assumption. Combined with an acoustic network, the generated flame fields could provide more physical insight into the thermoacoustic dynamics. Those capabilities do not come at an additional significant computational cost, as even previous nonspatial flame models had to train on the CFD data, which included field distributions.
A Fault Detection Framework Based on Data-Driven Digital Shadows
Authors: Michalski Miguel Angelo de Carvalho , Melani Arthur Henrique de Andrade , da Silva Renan Favarão , de Souza Gilberto Francisco Martha 
Published: October 2023

Abstract
The popularization of Industry 4.0 and its technological pillars has allowed prognostics and health management (PHM) strategies to be applied in complex systems to optimize their performance and extend their useful life by taking advantage of a digitalized, integrated environment. Due to this context, the use of digital twins and digital shadows, which are virtual representations of physical systems that provide real-time monitoring and analysis of the health and performance of the system, has been increasingly used in the application of fault detection, a key component of PHM. Taking that into consideration, this work proposes a framework for fault detection in engineering systems based on the construction and application of a digital shadow. This digital shadow is based on a digital model composed of a system of equations and a continuous, real-time communication process with a supervisory control and data acquisition (SCADA) system. The digital model is generated using monitoring data from the system under study. The proposed method was applied in two case studies, one based on synthetic data and another that uses a simulated database of an operational generating unit of a hydro-electric power plant. The method, in both case studies, was able to detect faults accurately and effectively. Besides, the method provides by-products that can be used in the future in other applications, helping with the PHM in other aspects.