bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of multipartite quantum steering for different types of decoherence channels
Authors: Li Wei-Chen , Xiao Ya , Han Xin-Hong , Fan Xuan , Hei Xiao-Bing , Gu Yong-Jian 
Published: March 2023

AbstractMultipartite quantum steering, a unique resource for asymmetric quantum network information tasks, is very fragile to the inevitable decoherence, which makes it useless for practical purposes. It is thus of importance to understand how it decays in the presence of noise channels. We study the dynamic behaviors of genuine tripartite steering, reduced bipartite steering, and collective steering of a generalized three-qubit W state when only one qubit interacts independently with the amplitude damping channel (ADC), phase damping channel (PDC) or depolarizing channel (DC). Our results provide the region of decoherence strength and state parameters that each type of steering can survive. The results show that these steering correlations decay the slowest in PDC and some non-maximally entangled states more robust than the maximally entangled ones. Unlike entanglement and Bell nonlocality, the thresholds of decoherence strength that reduced bipartite steering and collective steering can survive depend on the steering direction. In addition, we find that not only one party can be steered by a group system, but also two parties can be steered by a single system. There is a trade-off between the monogamy relation involving one steered party and two steered parties. Our work provides comprehensive information about the effect of decoherence on multipartite quantum steering, which will help to realize quantum information processing tasks in the presence of noise environments.
Ligamentum flavum analysis in patients with lumbar discus hernia and lumbar spinal stenosis
Authors: Aleksić Vuk , Todorović Jovana , Miladinović Nenad , Aleksić Nemanja , Bogosavljević Vojislav , Đurović Marko , Kocić Svetlana , Aleksić Radmila , Joković Miloš 
Published: March 2023

AbstractThe normal ligamentum flavum (LF) is a well-defined elastic structure with specific innervation. Several studies investigated LF in patients with lumbar spinal stenosis (LSS) and used lumbar discus hernia (LDH) patients as control group, only on the presumed thesis that LF in this patients have normal morphology. In patients with LSS thickening of the LF is the main cause of stenosis, which is most often presented with neurogenic claudication, whose pathophysiological mechanism is not completely understood. We conducted observational cohort study of 60 operated patients divided into two groups. The first group of 30 patients underwent micro-discectomy (LSH group), and second group with 30 patients underwent decompression, after which analysis of harvested LF was performed. Patients from the LDH group and LSS group differed significantly in the frequencies of chief complaints, duration of symptoms, physical examination, and specific morphological/radiological parameters. The LF analysis showed that the groups differed significantly in the amount of collagen and elastic fibers, as well as in the histological appearance/architectonics of elastic fibers. Also, groups differ in the presence of LF nerve fibers. Our findings speak in favor of the recently postulated inflammatory theory in the origin of spinal neurogenic claudication’s.
Real-world data on the incidence and risk of Guillain–Barré syndrome following SARS-CoV-2 vaccination: a prospective surveillance study
Authors: Ha Jongmok , Park Suyeon , Kang Hyunwook , Kyung Taeeun , Kim Namoh , Kim Dong Kyu , Kim Hyeonjoon , Bae Kihoon , Song Min Cheol , Lee Kwang June , Lee Euiho , Hwang Beom Seuk , Youn Jinyoung , Seok Jin Myoung , Park Kunhee 
Published: March 2023

AbstractIncreasing evidence suggests an association between SARS-CoV-2 vaccines and Guillain–Barré syndrome (GBS). Nevertheless, little is understood about the contributing risk factors and clinical characteristics of GBS post SARS-CoV-2 vaccination. In this prospective surveillance study of 38,828,691 SARS-CoV-2 vaccine doses administered from February 2021 to March 2022 in the Gyeonggi Province, South Korea, 55 cases of GBS were reported post vaccination. We estimated the incidence rate of GBS per million doses and the incidence rate ratio for the vaccine dose, mechanism, age, and sex. Additionally, we compared the clinical characteristics of GBS following mRNA-based and viral vector-based vaccinations. The overall incidence of GBS following SARS-CoV-2 vaccination was 1.42 per million doses. Viral vector-based vaccines were associated with a higher risk of GBS. Men were more likely to develop GBS than women. The third dose of vaccine was associated with a lower risk of developing GBS. Classic sensorimotor and pure motor subtypes were the predominant clinical subtypes, and demyelinating type was the predominant electrodiagnostic subtype. The initial dose of viral-vector based vaccine and later doses of mRNA-based vaccine were associated with GBS, respectively. GBS following SARS-CoV-2 vaccination may not be clinically distinct. However, physicians should pay close attention to the classic presentation of GBS in men receiving an initial dose of viral vector-based SARS-CoV-2 vaccines.
Wiederbelebungsmaßnahmen bei leblosen Pflegeheimbewohnern durchführen oder unterlassen?
Authors: Günther Andreas , Primc Nadia , Hasseler Martina , Poeck Juliane , Schwabe Sven , Rubeis Giovanni , Janda Constanze , Hartleb Birgit , Czaputa Eileen , Fischer Matthias 
Published: March 2023

Zusammenfassung
Ziel der Arbeit Entscheidungen über Reanimationsversuche (RV) müssen die Chancen auf Überleben gegen die Aussichten auf zusätzliches Leid abwägen. Für Pflegeheimbewohner soll die Basis dieser Abwägung auf Grundlage der im Deutschen Reanimationsregister verfügbaren Endpunkte verbreitert werden.
Methodik Retrospektive Auswertung prähospitaler RV der Jahre 2012 bis 2019.
Ergebnisse Eingeschlossen wurden 2510 Datensätze. Das Durchschnittsalter betrug 83,7 (±7,5) Jahre, 1497 (59,6%) waren weiblich. Es erfolgten 98 (3,9%) Lebendentlassungen; davon 61 (2,4%) mit neurologisch gutem Outcome. Im Krankenhaus verstarben 791 (31,5%); 561 (22,4%) innerhalb 24 Stunden. Am Einsatzort verstarben 1621 (64,6%). Diese und weitere Endpunkte wurden stratifiziert als Spektrum dargestellt und Subgruppen nach Alter, Pre Emergency Status und Einsatzsituationen gebildet.
Schlussfolgerung Für die Entscheidungsfindung scheinen neben den prähospitalen Einsatzsituationen besonders Patientencharakteristika relevant zu sein.
Polycyclic High-Density Cage Compounds via Cross Metathesis
Authors: Kotha Sambasivarao , Chaurasia Usha Nandan 
Published: March 2023

AbstractThe synthesis of various highly functionalized caged systems suitable as high energy density materials, which were assembled by utilization of an olefin cross-metathesis strategy, is reported. E-Selectivity was observed during the cross-metathesis by using Grubbs second generation catalyst (G-II) and N-tolyl Grubbs catalyst in most of the cross-metathesis products. The stereochemistry of the olefin formed during the cross-metathesis has been determined unambiguously by a single-crystal X-ray diffraction study.
Voice and Mental Health Support for Trans Teens and Their Parents: A Workshop Model
Authors: Schatzki Myra , Risueño R.J. , Spector Jonah 
Published: March 2023

AbstractProviding parents and their teenage children with an opportunity to experience voice modification techniques and discussions about mental health issues could alleviate some of their tremendous minority stress. Speech-language pathologists and counselors can use experiential learning and a multidimensional family approach to support parents and their trans teenagers to build connections and learn individual perspectives on their personal phases of transitioning. Participants of the 3-hour webinar included nine dyads of parents and youths across the United States. Topics on voice modification and mental health strategies were presented. Only parents completed the pre- and post-surveys to measure confidence in their knowledge to support their youth's voice and mental health needs. There were 10 Likert scale questions (5 voice, 5 mental health). The Kruskal–Wallis H-test results revealed that the median responses to the pre and post voice survey did not show a statistically significant change (H = 8.0, p = 0.342). Similarly, the mental health surveys did not reach significance (H = 8.0, p = 0.433). However, the growth trend shows strong promise for developing effective future experiential training workshops as a viable service provision for increasing parents' knowledge in supporting their trans child's voice and mental health needs.
An axisymmetric mirror device for studying confinement and instability
Authors: Yang Zhida , Xu Zelin , Zhu Guanghui , Ren BaoMing , Sun Xuan 
Published: March 2023

We describe a magnetic mirror device, namely, the Keda Mirror with AXisymmetricity (KMAX), which aims to study new approaches to confine and stabilize the mirror plasma as well as basic plasma research. KMAX consists of one central cell, two side cells, and two end chambers at two ends of the device. For the central cell, the mirror-to-mirror distance is 5.2 m, while the central cylinder is 2.5 m in length and 1.2 m in diameter. The plasmas are generated by two washer guns located in the end chambers, which subsequently flow into the central cell and merge there. The density in the central cell is usually adjusted by changing the magnetic field strength inside the side cell, and it ranges from 1017 to 1019 m−3, depending on the experimental requirement. Ion cyclotron frequency heating with two 100 kW transmitters is routinely used to heat up the ions. Plasma controls mainly rely on configuring the magnetic geometry and rotating magnetic fields to improve the confinement and suppress instability. Routine diagnostics, such as probes, interferometers, spectrometers, diamagnetic loops, and bolometers, are also reported in this paper.
Cryo-EM structure of the human chemerin receptor 1–Gi protein complex bound to the C-terminal nonapeptide of chemerin
Authors: Wang Junlin , Chen Geng , Liao Qiwen , Lyu Wenping , Liu Aijun , Zhu Lizhe , Du Yang , Ye Richard D. 
Published: March 2023

Chemerin is a processed protein that acts on G protein-coupled receptors (GPCRs) for its chemotactic and adipokine activities. The biologically active chemerin (chemerin 21-157) results from proteolytic cleavage of prochemerin and uses its C-terminal peptide containing the sequence YFPGQFAFS for receptor activation. Here we report a high-resolution cryo-electron microscopy (cryo-EM) structure of human chemerin receptor 1 (CMKLR1) bound to the C-terminal nonapeptide of chemokine (C9) in complex with Gi proteins. C9 inserts its C terminus into the binding pocket and is stabilized through hydrophobic interactions involving its Y1, F2, F6, and F8, as well as polar interactions between G4, S9, and several amino acids lining the binding pocket of CMKLR1. Microsecond scale molecular dynamics simulations support a balanced force distribution across the whole ligand–receptor interface that enhances thermodynamic stability of the captured binding pose of C9. The C9 interaction with CMKLR1 is drastically different from chemokine recognition by chemokine receptors, which follow a two-site two-step model. In contrast, C9 takes an “S”-shaped pose in the binding pocket of CMKLR1 much like angiotensin II in the AT1 receptor. Our mutagenesis and functional analyses confirmed the cryo-EM structure and key residues in the binding pocket for these interactions. Our findings provide a structural basis for chemerin recognition by CMKLR1 for the established chemotactic and adipokine activities.
The relationships between individual differences in working memory and language analytical ability and the effectiveness of different types of corrective feedback
Authors: Sato Yusuke 
Published: March 2023

Abstract
This study examined the relationships between individual differences in the executive component of working memory, and language analytical ability and the effectiveness of recasts, explicit correction and, metalinguistic prompts on the second-language (L2) development of the English past progressive. Participants were 155 Japanese learners of English, who were divided into recast, explicit correction, metalinguistic prompt, and task-only groups. The treatment groups completed tasks that required past progressive usage and received feedback. The executive component of working memory and language analytical ability were measured by the reading span test and LLAMA F. The outcome measures were an untimed grammaticality judgment test (UGJT) and elicited imitation test (EIT), which measured the participants’ declarative and procedural knowledge, respectively. The participants performed the pretest, immediate posttest, and delayed posttest. Multiple regression analyses showed that the executive component of working memory was significantly associated with the gain scores of the UGJT for the recast group and with the gain scores of the EIT for the metalinguistic prompt group. Language analytical ability was not associated with gain scores regardless of the test type for all groups.
Relativistic theory of elastic bodies in the presence of gravitational waves
Authors: Hudelist Mario , Mieling Thomas B , Palenta Stefan 
Published: March 2023

Abstract
The equations of motion governing small elastic oscillations of materials, induced by gravitational waves, are derived from the general framework of Carter and Quintana. In transverse-traceless gauge, no bulk forces are present, and the gravitational wave is found to act as an effective surface traction. For thin rods, an equivalent description is given, in which there is no surface traction, but a bulk acceleration, which is related to the Riemann curvature of the gravitational wave. The resulting equations are compared to those of the Synge–Bennoun elasticity theory.
A bagging-strategy based heterogeneous ensemble deep neural networks approach for the multiple components fault diagnosis of hydraulic systems
Authors: Wang Junlang , Xu Huoyao , Liu Jie , Peng Xiangyu , He Chaoming 
Published: March 2023

Abstract
Hydraulic systems faults have the characteristics of being highly concealed and unclear. Due to the characteristics of the complex vibration transmission mechanism and strong nonlinear time-varying signals in hydraulic systems, it is extremely difficult to achieve fault diagnosis for hydraulic systems. Different components of the system can fail individually or simultaneously. Signal processing faces the problem of coupling between multi-component faults, which makes it more difficult to realise multi-component fault diagnosis. On the one hand, existing techniques rely on hand-designed features and only use a traditional single shallow machine model as the base classifier, and these do not have the ability to self-learn meaningful features. On the other hand, the diagnostic performance of a single base classifier sometimes does not meet engineering requirements. To handle the above problems, a bagging strategy based heterogeneous ensemble deep neural networks (DNNs) approach is proposed for the multiple components fault diagnosis of hydraulic systems. First, Pearson correlation coefficient and neighbourhood component analysis are developed for data channel selection and feature dimensionality reduction. Second, two distinct DNNs are constructed as base learners: a stacked sparse autoencoder and a deep hierarchical extreme-learning machine. Finally, a bagging strategy is adopted to integrate different DNNs to obtain robust diagnostic results. The results from this experiment demonstrate that the proposed method can precisely diagnose hydraulic system faults compared with comparative methods.
Early sub-surface fault detection in rolling element bearing using acoustic emission signal based on a hybrid parameter of energy entropy and deep autoencoder
Authors: Wang Yu , Hestmo Rune Harald , Vinogradov Alexei 
Published: March 2023

Abstract
Bearings are a crucial component of wind turbines. The acoustic emission (AE) technique offers the advantage of earlier detection of defects and failures of bearings in comparison to traditional vibration techniques. Parameter-based analysis is the most widely used approach to interpret AE waveforms, partly due to the challenges arising in the processing of large amounts of streaming data. In this work, the AE technique is applied to monitor a run-to-failure process of a roller bearing, and it is found that the use of multiple known parameters, such as the root mean square, skewness, crest factor, impulse factor etc, fails to characterise the evolution of the acquired AE signals, thus highlighting the long-standing necessity and significance of developing new AE indicators that are more adequate to detect the failure of rotating machines. We propose a hybrid parameter—the information entropy penalty factor (IEPF)—which uses the advantages of the entropy theory and deep learning methods. The effectiveness of the proposed method has been investigated and demonstrated for roller bearing contact fatigue experiments, and the results show that IEPF can timely and accurately detect the incipient sub-surface faults.
Road classification using 3D LiDAR sensor on vehicle
Authors: Liu Bo , Zhao Dingxuan , Zhang Hanyang 
Published: March 2023

Abstract
Road classification is essential in outdoor vehicle perception systems to evaluate driving scenarios. A light detection and ranging (LiDAR) sensor can provide accurate measurements of an environment composed of range, intensity, and angular information. This study proposes a weakly supervised learning algorithm for classifying road surface types based on laser measurements. The proposed algorithm first separates the laser points on the road surface based on the angular structure of the initial range measures obtained using 3D LiDAR in a noniterative manner. Then, a physical-data-driven model that represents the retroreflective nature of the different surface types is abstracted from the intensity measures and their factors. The linear regression parameters of the model are employed as feature descriptions of the road surface. The K-means method is used to classify the different road types. The learning process requires weak supervision at the training centroid stage and is robust to new road types. The classification performance was evaluated in different outdoor scenarios, and the classification accuracies exceeded 98%. The proposed algorithm outperforms similar existing methods, performs at the same frequency as that of LiDAR, and can be implemented in real time.
DNA lattice growth with single, double, and triple double-crossover boundaries by stepwise self-assembly
Authors: Raza Muhammad Tayyab , Tandon Anshula , Park Suyoun , Lee Sungjin , Nguyen Thi Bich Ngoc , Vu Thi Hong Nhung , Park Sung Ha 
Published: March 2023

Abstract
Construction of various nanostructures with nanometre-scale precision through various DNA building blocks depends upon self-assembly, base-pair complementarity and sequence programmability. During annealing, unit tiles are formed by the complementarity of base pairs in each strand. Enhancement of growth of target lattices is expected if seed lattices (i.e. boundaries for growth of target lattices) are initially present in a test tube during annealing. Although most processes for annealing DNA nanostructures adopt a one-step high temperature method, multi-step annealing provides certain advantages such as reusability of unit tiles and tuneability of lattice formation. We can construct target lattices effectively (through multi-step annealing) and efficiently (via boundaries) by multi-step annealing and combining boundaries. Here, we construct efficient boundaries made of single, double, and triple double-crossover DNA tiles for growth of DNA lattices. Two unit double-crossover DNA tile-based lattices and copy-logic implemented algorithmic lattices were introduced to test the growth of target lattices on boundaries. We used multi-step annealing to tune the formation of DNA crystals during fabrication of DNA crystals comprised of boundaries and target lattices. The formation of target DNA lattices was visualized using atomic force microscopy (AFM). The borders between boundaries and lattices in a single crystal were clearly differentiable from AFM images. Our method provides way to construct various types of lattices in a single crystal, which might generate various patterns and enhance the information capacity in a given crystal.
Vascular wall motion detection models based on long short-term memory in plane-wave-based ultrasound imaging
Authors: Seo Jeongwung , Nguon Leang Sim , Park Suhyun 
Published: March 2023

Abstract

Objective. Vascular wall motion can be used to diagnose cardiovascular diseases. In this study, long short-term memory (LSTM) neural networks were used to track vascular wall motion in plane-wave-based ultrasound imaging. Approach. The proposed LSTM and convolutional LSTM (ConvLSTM) models were trained using ultrasound data from simulations and tested experimentally using a tissue-mimicking vascular phantom and an in vivo study using a carotid artery. The performance of the models in the simulation was evaluated using the mean square error from axial and lateral motions and compared with the cross-correlation (XCorr) method. Statistical analysis was performed using the Bland–Altman plot, Pearson correlation coefficient, and linear regression in comparison with the manually annotated ground truth. Main results. For the in vivo data, the median error and 95% limit of agreement from the Bland–Altman analysis were (0.01, 0.13), (0.02, 0.19), and (0.03, 0.18), the Pearson correlation coefficients were 0.97, 0.94, and 0.94, respectively, and the linear equations were 0.89x + 0.02, 0.84x + 0.03, and 0.88x + 0.03 from linear regression for the ConvLSTM model, LSTM model, and XCorr method, respectively. In the longitudinal and transverse views of the carotid artery, the LSTM-based models outperformed the XCorr method. Overall, the ConvLSTM model was superior to the LSTM model and XCorr method. Significance. This study demonstrated that vascular wall motion can be tracked accurately and precisely using plane-wave-based ultrasound imaging and the proposed LSTM-based models.