bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transanal endoscopic cooperative surgery as a less invasive resection technique for anorectal tumors extending beyond the dentate line: Case series
Authors: Shigeta Kohei , Takada Kazunori , Hotta Kinichi , Imai Kenichiro , Ito Sayo , Sato Junya , Yamamoto Yoichi , Yoshida Masao , Maeda Yuki , Kawata Noboru , Ishiwatari Hirotoshi , Matsubayashi Hiroyuki , Shiomi Akio , Kagawa Hiroyasu , Shoichi Manabe , Yamaoka Yusuke , Kasai Shunsuke , Tanaka Yusuke , Hirashima Yasuyuki , Mochizuki Ayako , Yoshikawa Shusuke , Tsutsumida Arata , Omata Wataru , Oishi Takuma , Ono Hiroyuki 
Published: December 2024

AbstractEndoscopic submucosal dissection (ESD) and surgical local excision pose particular challenges for anorectal tumors extending beyond the dentate line, making technique selection difficult. We hypothesized that combining ESD and local excision (transanal endoscopy cooperative surgery; TaECS) can effectively resect such tumors. TaECS was performed for three patients with anorectal tumors extending beyond the dentate line between January and December 2022. TaECS was indicated for local resection of tumors extending beyond the dentate line with a low risk of lymph node metastases. TaECS was performed in an operating room after ensuring adequate bowel preparation. The oral side of the tumor was dissected endoscopically with resection margins precisely evaluated using magnifying endoscopy. The anal side was surgically dissected above the internal anal sphincter. The defect was repaired wtih bilateral V-Y advancement flap reconstruction. All three tumors were successfully resected in en bloc fashion without intraprocedural adverse events. No postoperative stricture and bleeding occurred. A postoperative abscess around the anastomosis was observed in one case. The anal sphincter was preserved in all cases. No recurrences were recorded at the 17- to 27-month follow-up. TaECS may be a viable treatment for minimally invasive local resection of anorectal tumors extending beyond the dentate line.
Optimizing duodenal tissue acquisition for mechanistic studies of duodenal ablation in type 2 diabetes
Authors: Busch Celine B.E. , van den Hoek Kim , Neefjes-Borst E. Andra , Nieuwdorp Max , van Baar Annieke C.G. , Bergman Jacques J.H.G.M. 
Published: December 2024

AbstractHistological analysis of regular duodenal biopsies to study morphologic changes after duodenal ablation for type 2 diabetes (T2D) and metabolic syndrome is hampered by variability in tissue orientation. We designed an optimized tissue acquisition protocol using duodenal cold snare resections to create tissue microarrays (TMAs) and to allow for single-cell RNA sequencing (scRNA-seq).The open-label DIRECT study included patients undergoing an upper gastrointestinal interventional endoscopy for non-duodenal indications. All underwent one ot two single-piece duodenal cold snare resections. Endpoints were safety, adequate histological orientation of specimen and TMA, and tissue dissociation quality for scRNA-seq. The optimized tissue acquisition protocol was validated in a duodenal ablation study, EMINENT-2.In DIRECT, nine patients were included in whom a total of 16 cold snare resections were obtained. No severe adverse events (SAEs) occurred. Eighty percent of specimens and corresponding TMAs showed optimal tissue orientation. Further improvement was achieved by reducing tissue damage during endoscopic retrieval and improving histologic evaluation by eliminating ink use and pinning the tissue on cork. High-quality tissue dissociation scores for scRNA-seq were achieved in 13 of 18 samples (72%). In EMINENT-2, 38 cold snares were obtained without SAEs, histopathologic analysis showed good orientation in all samples, and dissociation scores for scRNA-seq were qualified in 35/38 (92%) samples.Duodenal cold snare resection is safe and can provide high-quality tissue for optimally oriented TMAs and high-quality tissue dissociation scores for scRNA-seq (Clinicaltrials.gov, NCT06333093, NCT05984238). This approach will allow mechanistic studies about the effects of duodenal ablation on metabolic syndrome and T2D.
Movement parties in Europe: a comparative assessment
Authors: Borbáth Endre , Paxton Fred 
Published: December 2024

Abstract
Research on political parties and social movements has long developed independently, separated by the disciplinary boundaries of political science and sociology. We see the recent successes of ‘movement parties’ as a push to bridge the two disciplinary traditions in order to describe this new hybrid party type accurately. To this end, we ask to what extent and under what conditions do we observe movement parties in European party systems, and how can we define the various subtypes? In the introduction to the special issue, we make three contributions. First, we identify existing definitions and empirical examples in the study of movement parties based on a systematic review of the emerging literature. Second, we operationalize Herbert Kitschelt's influential definition of lower levels of programmatic and organizational investment coupled with a higher degree of protest mobilization. Third, we introduce the individual contributions to the special issue and situate them within the relevant theoretical debates. Utilizing a new set of quantitative indicators, we empirically assess how parties identified as movement parties in the existing literature score on programmatic, organizational, and protest dimensions. The analysis underscores the heterogeneity of movement parties, with only a few cases aligning with Kitschelt's comprehensive definition.
Bio-inspired piezoelectric stick–slip actuation: Synergistic bridge-type and leveraged amplification mechanism via rowing-motion mimicry
Authors: Yang Shitong , Dong Hao , Zhang Zhenguo , Zhang Daohong , Zhang Lin , Lu Xiaohui 
Published: December 2024

This paper presents the development of a new bionic piezoelectric stick–slip actuator (PSSA). This actuator is designed to simulate the human rowing motion. By synergizing a lever amplification structure with a bridge amplification mechanism, the design not only mimics the rowing motion, where the lever amplification structure acts like an oar and the bridge amplification mechanism resembles the force exerted by a person operating the oar, but also suppresses the problem of backward displacement in traditional PSSAs. Finite element analysis and experimental results demonstrate the feasibility of the design, with a peak velocity of 17.48 mm/s and a maximum load capacity of 55 g. Comparative experiments have shown that the rowing-motion piezoelectric actuation mode outperforms the traditional PSSA mode, with a 16.8% increase in peak velocity and a 120% increase in load capacity. The innovative design has significant implications for the development of high-performance actuators.
Vibrational strong coupling of organic molecules embedded within graphene plasmon nanocavities facilitated by perfect absorbers
Authors: Wu Zhiyong , Liu Baiquan , Liao Shaolin , Xu Zhengji 
Published: December 2024

The strong coupling between infrared photonic resonances and vibrational transitions of organic molecules is called vibrational strong coupling (VSC), which presents attractive prospects for modifying molecular chemical characteristics and behaviors. Currently, VSC studies suffer from limited bandwidth or enormous mode volumes. In addition, in certain instances, the absorption spectrum of VSC is weaker, thus impeding the effective monitoring of the VSC effect. Here, we theoretically study the VSC effect by embedding 5-nm-thick organic molecules into a graphene plasmon nanocavity (GPNC). Pronounced anti-crossing characteristics with Rabi splitting exceeding 80 cm−1 are disclosed from the spectra of the coupled molecular system, benefiting from the ultra-small mode volume provided by the GPNC. Further assembling the GPNC into a perfect absorber configuration can significantly enhance the spectral peaks of the VSC effect, thus maximizing the reachability of the VSC phenomenon. Furthermore, the tunability of graphene enables monitoring of spectral changes by electrically adjusting graphene’s Fermi level in a structure with fixed geometric parameters. In addition, we establish an analytical framework in alignment with computational simulations to elucidate the triggering criteria for the VSC mode, thereby giving a clear picture for understanding the physical processes that form the VSC mode. Given that graphene supports plasmon modes across an extensive range extending from infrared to terahertz, the suggested GPNC presents a suitable framework for investigating the VSC effect of diverse organic materials.
A comparative analysis of wildfire initial attack containment objectives and modelling strategies in Ontario, Canada
Authors: Korkola Kennedy , Wheatley Melanie , Beverly Jennifer , James Patrick M. A. , Wotton Mike 
Published: December 2024

Background Fire management agencies use the proportion of fires classified as initial attack (IA) success as a suppression performance metric, making IA success a common indicator of suppression effectiveness in research. The criteria and definition for IA success vary based on operational objectives, making comparisons across studies difficult. Aims To examine the sensitivity of different time and size-based IA success definitions on model predictive accuracy and compare different modelling approaches. Methods Using 30 years of historical fire report data from Ontario, Canada (n = 26,171), we developed logistic regression models, bagged classification trees and random forest models to predict IA success for eight different definitions. Model predictive accuracy, sensitivity and specificity were assessed on an independent validation dataset. Key results The eight definitions classified between 79 and 98% of fires as IA successes. There was no clear pattern between model strength across prediction metrics and IA success definition. Logistic regression generally outperformed machine learning methods in classifying IA escapes. Conclusions and implications The definition of IA success does not greatly impact model performance across the modelling techniques used. Models of IA success and suppression-system performance metrics should be set with specific research or operational objectives in mind.
The role of orthography and phonology during L1 vs. L2 typed production
Authors: Muylle Merel , Jarema Gonia 
Published: December 2024

Abstract
Dual-route models of typing assume two pathways to retrieve a word’s spelling: a direct route connecting word to
letter representations, and an indirect route via sound representations. The individual contribution of each route may depend on
the modality of language acquisition: the first language (L1) is acquired sequentially in spoken and written modality
respectively, whereas the second language (L2) is often acquired simultaneously in both modalities. We investigated whether
sequential bilinguals rely more on the direct route during L2 vs. L1 typing. French-English bilinguals performed a typed
picture-word interference task in their L1 and L2. We compared facilitation in naming for distractors that were phonologically (P)
related, phonologically + orthographically (PO) related, or unrelated to the target. We predicted more facilitation by PO vs. P
distractors in the L2 than in the L1. Participants showed significant facilitation by PO distractors, but not by P distractors,
suggesting that orthographic overlap (together with phonology) helped retrieving the target spelling, whereas phonological overlap
alone did not. The magnitude of this effect was similar across L1 and L2, contrary to our predictions. However, the absence of
mere phonological facilitation suggests that phonology only contributes to typing when supported by orthography.
Spanish for Emergency Room Nursing
Authors: Helms Lindsay L. 
Published: December 2024

Abstract
This study conducts a task-based needs analysis (NA) to (1)
determine the Spanish language needs of primarily English-speaking emergency
room nurses in the Southeastern US and (2) inform the design of a potential
Spanish for ER Nursing course. This mixed-methods study included three phases of
both data collection and analysis, adapted from Serafini and Torres (2015) and Malicka et al. (2019). In Phase 1, a variety of
open-ended measures were used to determine tasks common in ER settings as
reported by each type of participant. In Phase 2, participants rated the
frequency and importance of these tasks. In Phase 3, the participants reviewed
the list of tasks in follow-up interviews. Results are presented as a series of
tasks performed in the ER context, ranked according to frequency and importance.
The study improves upon previous task-based needs analyses by implementing
recent methodological considerations by Serafini (2022) and Gilabert and
Malicka (2022).
Task repetition and L2 grit
Authors: Róg Tomasz , Krawiec Marek 
Published: December 2024

Abstract
Task repetition (TR) has been shown to improve fluency, but empirical evidence of its impact on complexity and accuracy (CAF) remains mixed. Various individual difference factors appear to be intricately linked to the benefits of TR. One such individual difference is L2 grit, representing perseverance and passion for language learning goals, which has been positively correlated with L2 proficiency. The present study aimed to clarify the effects of TR on all CAF measures and elucidate whether learners with high and low levels of L2 grit benefit differently from TR. Forty-two Polish EFL secondary school learners participated, with their oral task performances analyzed before and after immediate exact TR. The findings show that both high- and low-grit learners benefit from TR, with significant improvements in fluency, complexity, and accuracy. Furthermore, high L2 grit learners consistently outperform low L2 grit learners. Notably, high L2 grit levels amplify the benefits of TR, particularly in accuracy and fluency measures. However, the interaction effect between TR and L2 grit appears to positively influence only the measures of lexical diversity and correct verb forms.
Effects of quantum corrections to Lorentzian vacuum transitions in the presence of gravity
Authors: García-Compeán H , Hernández-Aguilar J , Mata-Pacheco D , Ramírez C 
Published: December 2024

Abstract
We present a study of the vacuum transition probabilities taking into account quantum corrections. We first introduce a general method that expands previous works employing the Lorentzian formalism of the Wheeler–De Witt equation by considering higher order terms in the semiclassical expansion. The method presented is applicable in principle to any model in the minisuperspace and up to any desired order in the quantum correction terms. Then, we apply this method to obtain analytical solutions for the probabilities up to second quantum corrections for homogeneous isotropic and anisotropic universes. We use the Friedmann–Lemaitre–Robertson–Walker metric with positive and zero curvature for the isotropic case and the Bianchi III and Kantowski–Sachs metrics for the anisotropic case. Interpreting the results as distribution probabilities of creating universes by vacuum decay with a given size, we found that the general behaviour is that considering up to the second quantum correction leads to an avoidance of the initial singularity. However, we show that this result can only be achieved for the isotropic Universe. Furthermore, we also study the effect of anisotropy on the transition probabilities.
Fictitious null spaces for improving the solution of injective inverse problems
Authors: Elvetun Ole Løseth , Knudsen Kim , Nielsen Bjørn Fredrik 
Published: December 2024

Abstract
For linear ill-posed problems with nontrivial null spaces, Tikhonov regularization and truncated singular value decomposition typically yield solutions that are close to the minimum norm solution. Such a bias is not always desirable, and we have therefore in a series of papers developed a weighting procedure which produces solutions with a different and controlled bias. This methodology can also conveniently be invoked when sparsity regularization is employed. The purpose of the present work is to study the potential use of this weighting applied to injective operators. The image under a compact operator of the singular vectors/functions associated with very small singular values will be almost zero. Consequently, one may regard these singular vectors/functions to constitute a basis for a fictitious null space that allows us to mimic the previous weighting procedure. It turns out that this regularization by weighting can improve the solution of injective inverse problems compared with more traditional approaches. We present some analysis of this methodology and exemplify it numerically, using sparsity regularization, for three PDE-driven inverse problems: the inverse heat conduction problem, the Cauchy problem for Laplace’s equation, and the (linearized) Electrical Impedance Tomography problem with experimental data.
Modelling of microarcs in copper metal vapour dominated air
Authors: Baeva Margarita , Uhrlandt Dirk 
Published: December 2024

Abstract
A fluid model of direct current microarcs in copper metal vapour dominated air is developed to resemble the microarcs that occur at low-voltage and low-current conditions in switching devices during a contact separation. The model is capable of predicting the basic plasma parameters, including the electric potential, the temperatures of electrons and heavy particles, the number densities of charged and neutral particles in the spatially resolved inter-electrode region, the heating of the electrodes as well as the release of copper metal vapour from the electrodes. The model predicts a positive anode fall and an increase of the electron temperature in the proximity of the anode.
Global model of low-frequency-driven cold atmospheric He + air plasmas
Authors: Sun Bowen , Zhang Hao , Niu Zhe , Lu Baofeng , Zhang Mingyan , He Yujie , Liu Dingxin , Wang Xiaohua 
Published: December 2024

Abstract
He + air mixture is a commonly used background gas for cold atmospheric-pressure plasmas (CAPs) because of its good discharge stability and chemical reactivity. However, the internal physical and chemical characteristics, especially the mechanism of the reactive species in low-frequency (LF)-driven He + air CAPs, are not fully understood. Hence, in this study, a global model incorporating 59 species and 866 volume reactions is developed to investigate the species densities and chemical pathways in 50 kHz-driven He + air CAPs with air contents ranging from 200 to 5000 ppm. In the entire air content range, O4
+ is the most abundant cation, and NO3
− is the most abundant anion. HNO2 is the dominant reactive nitrogen species (RNS), and the dominant reactive oxygen species (ROS) changes from H2O2 to O3 when the air concentration increases above 1000 ppm. Moreover, since He + air CAPs are typically driven by low frequency to radio frequency (RF) power sources, in this work, the species densities in LF (f = 50 kHz)- and RF (f = 13.56 MHz)-driven He + air plasmas are compared.
Disorder-induced phase transitions in a two-dimensional magnetic topological insulator system
Authors: Song Yong-Liang , Shang Shu-xiu , Chen Xin-lian , Zhang Chang-wen , Zhang Shu-feng 
Published: December 2024

Abstract
We investigate the phase diagram of a two-dimensional magnetic topological system in the parameter space of uncorrelated Anderson disorder and Zeeman splitting energy. In the absence of disorder, the system undergoes the phases of higher-order topological insulators (HOTIs), Chern insulators (CIs) with Chern numbers C = 2 and C = 1, and band insulators successively with enhancing Zeeman energy. The phase boundary separating these phases is found to be strongly deformed by the disorder, which leads to several topological Anderson insulators. Specifically, there exist phase transitions between CI with C = 2 and HOTI, and between CIs with C = 1 and C = 2. For the former one, it is in fact a phase transition between first-order and second-order topological phases. Besides, these disorder induced phase transitions are well explained by self-consistent Born approximation.
A novel cross domain diagnosis method based on physical feature weighting and deep residual shrinkage network
Authors: ChaoYong Ma , Nan Si , Kun Zhang , XiangFeng Zhang , Jia Chen , YongGang Xu 
Published: December 2024

Abstract
Traditional intelligent diagnostic methods often exhibit poor generalization ability when faced with data from different experimental platforms due to their differing distributions. Current transfer learning methods typically require fine-tuning of the model with some target domain data to adapt to different data distributions. However, in practical applications, it is often difficult to obtain sufficient target domain data. To address this issue, this paper proposes an innovative cross-domain diagnostic method that can diagnose faults on a target platform without relying on its data. The method introduces fault information of bearings into the attention weights of a deep residual shrinkage network (DRSN) through a novel physical feature weighting layer. This effectively extracts the hidden fault information from the signals, which is further refined and classified by DRSN to obtain an accurate fault diagnosis result. Experiments conducted on three bearing datasets validate the effectiveness of the proposed method, demonstrating its promising application prospects for bearing fault diagnosis under different operating conditions.
Modified kernel global-local marginal fisher analysis for rolling bearing feature extraction
Authors: Tian Yu , Guo Shunsheng , Jiang Li , Li Yibing , Zhang Xin 
Published: December 2024

Abstract
The vibration signals of rolling bearings usually exhibit high-dimensional, nonlinear, and non-Gaussian distribution characteristics due to long-term operation under complex working conditions. Therefore, we proposed a novel algorithm named modified kernel global-local marginal fisher analysis (MKGLMFA) for bearing feature extraction and dimensionality reduction. The proposed MKGLMFA algorithm introduces the kernel function to map data into a high-dimensional space to represent data nonlinearly first. It enhances the within-class compactness and between-class dispersibility by considering spatial relationships and label information when constructing adjacency graphs and simultaneously exploits the local and global geometry of data. Furthermore, a bearing fault diagnosis approach is presented based on MKGLMFA. It first processes the original vibration signals through MKGLMFA to obtain low-dimensional manifold features. Then these characteristics were input into the K-nearest neighbor (KNN) classifier to achieve fault pattern recognition. The superiority of the proposed MKGLMFA algorithm in feature extraction is verified in comparison with some existing state-of-the-art machine learning methods on three rolling bearings datasets. And the subsequent classification diagnosis experiments indicate the effectiveness and high efficiency of the newly raised MKGLMFA algorithm. In comparison with the representative diagnosis methods, the proposed method can extract more sensitive discriminant features, and the classification accuracy of diagnosis is significantly improved in consequence.