bluuebunny/crossref_metadata_2025_split huggingface dataset:
Superior cerebellar artery occlusion remaining after thrombectomy for acute basilar artery occlusion
Authors: Baek Byung Hyun , Lee Yun Young , Kim Seul Kee , Yoon Woong 
Published: December 2023

AbstractTo investigate the incidence and impact of superior cerebellar artery (SCA) occlusion remaining after thrombectomy for acute basilar artery occlusion (BAO). We retrospectively analyzed data from 116 patients who underwent thrombectomy for BAO. The patency of SCA was assessed on final angiograms. Clinical and radiologic data of the patients were retrieved from a prospectively collected database and analyzed. All patients underwent pretreatment and follow-up DWI to detect new infarctions in SCA territory. Ten patients (8.6%) had SCA occlusions on final angiograms. Of these, two patients had bilateral occlusions. A new infarction with a diameter ranged from 4 to 11 mm in corresponding SCA territory occurred in 5 of 10 patients. No patients with SCA occlusions experienced symptomatic cerebellar hemorrhage or malignant cerebellar infarction. Nine of 12 SCA occlusions showed spontaneous recanalization on follow-up CT angiography. Four of 10 patients showed 90-day favorable outcome (mRS 0–3) and 90-day mortality occurred in one patient. SCA occlusions remaining after thrombectomy for acute BAO had a benign clinical course. Most of these lesions recanalized spontaneously. Our study suggests that attempts to recanalize remnant SCA occlusion may be unnecessary after basilar artery thrombectomy.
Design and implementation of load intensity monitoring platform supported by big data technology in stage training for women’s sitting volleyball
Authors: Liang Zhijun , Liang Chen 
Published: December 2023

AbstractThis study aims to discuss the load intensity monitoring in the training process of sitting volleyball, to help coaches understand the training status of athletes, and to provide a scientific basis for the follow-up training plan. Through big data technology, the physiological changes of athletes can be more accurately grasped. This includes classification and summary of exercise load intensity and experimental study of the relationship between heart rate and rating perceived exertion (RPE). Through monitoring the training process of a provincial women’s sitting volleyball team, it is found that there is a significant positive correlation between athletes’ RPE and average heart rate. This result shows that by monitoring the change in heart rate and RPE of athletes, athletes' training state and physical condition can be more accurately understood. The results reveal that through the use of big data technology and monitoring experiments, it is found that heart rate and RPE are effective monitoring indicators, which can scientifically reflect the load intensity during sitting volleyball training. The conclusions provide coaches with a more scientific basis for making training plans and useful references for sports involving people with disabilities.
Nurse navigation, symptom monitoring and exercise in vulnerable patients with lung cancer: feasibility of the NAVIGATE intervention
Authors: Langballe Rikke , Svendsen Lukas , Jakobsen Erik , Dalton Susanne Oksbjerg , Karlsen Randi Valbjørn , Iachina Maria , Freund Karen M. , Leclair Amy , Jørgensen Lars Bo , Skou Søren T. , Ehlers Jeanette Haar , Torenholt Rikke , Svendsen Mads Nordahl , Envold Bidstrup Pernille 
Published: December 2023

AbstractWe developed the Navigate intervention to improve survival among vulnerable lung cancer patients. In this intervention-only study, we examined feasibility in terms of recruitment, retention, attendance, adherence, and acceptability to specify adjustments to study procedures and intervention components prior to a randomized trial. The Navigate intervention includes nurse navigation, patient-reported outcomes, and physical exercise. Patients ≥ 18 years old, diagnosed with non-small cell lung cancer at any stage, with performance status ≤ 2, eligible for cancer treatment and vulnerable according to a screening instrument were included. The recruitment goal of eligible patients was 40% while the retention goal was 85%. The predefined cut-offs for sufficient attendance and adherence were ≥ 75%. Acceptability was evaluated by semi-structured interviews with participants, nurse navigators, and physiotherapists. Seventeen (56%) out of 30 screened patients were considered vulnerable and eligible for the study, 14 (82%) accepted participation, and 3 (21%) were subsequently excluded due to ineligibility, leaving 11 patients. Four patients dropped out (36%) and four patients died (36%) during follow-up and 3 (27%) were retained. All 11 patients participated in nurse sessions (mean 16, range 1–36) with 88% attendance and dialogue tools being applied in 68% of sessions. Ninety-one percent of patients responded to PROs (mean of 9 PROs, range 1–24) with 76% of the PRO questionnaires used (attendance) and 100% adherence (completion of all questions in PRO questionnaires), and 55% participated in exercise sessions with 58% attendance and 85% adherence. We identified important barriers primarily related to transportation, but overall acceptability was high. The Navigate intervention was feasible with high participation, acceptability and satisfactory adherence. Retention and exercise attendance were low, which resulted in adjustments.Trial registration: The feasibility study was initiated prior to the multicenter randomized controlled trial registered by ClinicalTrials.gov (number: NCT05053997; date 23/09/2021).
Embryonic-stem-cell-derived mesenchymal stem cells relieve experimental contact urticaria by regulating the functions of mast cells and T cells
Authors: Hyun Seung Yeun , Kim Eun-Young , Kang Minseong , Park Jeong Won , Hong Ki-Sung , Chung Hyung-Min , Choi Wahn Soo , Park Se-Pill , Noh Geunwoong , Kim Hyuk Soon 
Published: December 2023

AbstractContact urticaria (CU) is an inflammatory skin disorder triggered by specific substances upon skin contact, leading to immediate acute or chronic manifestations characterized by swelling and redness. While mesenchymal stem cells (MSCs) are increasingly recognized for their therapeutic potential in immune diseases, research on the efficacy and mechanisms of stem cell therapy for urticaria remains scarce. This study investigates the regulatory role of embryonic-stem-cell-derived multipotent MSCs (M-MSCs) administered in a CU mouse model. Therapeutic effects of M-MSC administration were assessed in a Trimellitic anhydride-induced contact urticaria model, revealing significant inhibition of urticarial reactions, including ear swelling, itchiness, and skin lesion. Moreover, M-MSC administration exerted control over effector T cell activities in major lymphoid and peripheral tissues, while also suppressing mast cell degranulation in peripheral tissues. Notably, the inhibitory effects mediated by M-MSCs were found to be TGF-β-dependent. Our study demonstrates the capacity of M-MSCs to regulate contact urticaria in a murine model, harmonizing the activation of inflammatory T cells and mast cells. Additionally, we suggest that TGF-β derived from M-MSCs could play a pivotal role as an inhibitory mechanism in contact urticaria.
An increase in widespread extreme precipitation events during the northeast monsoon season over south peninsular India
Authors: Shahi Namendra Kumar , Rai Shailendra 
Published: December 2023

AbstractWhile the spatio-temporal characteristics of Indian summer monsoon precipitation and its extreme spells have been extensively studied, the northeast monsoon, which occurs from October to December (i.e., post-monsoon season) and affects the southern peninsula of India, has not received as much attention. In light of this, the present study explores the spatio-temporal characteristics of precipitation during the northeast monsoon, with a particular emphasis on widespread extreme precipitation events and their associated large-scale synoptic systems, using recent ensemble of high-resolution regional climate models (RCMs) simulations and the Indian monsoon data assimilation and analysis (IMDAA) reanalysis. The study reveals that both models tend to underestimate the intensity and frequency of observed precipitation events, although their skills in reproducing the observed spatial patterns of both mean and extreme precipitation are quite high (r > 0.75). A substantial increase in widespread extreme precipitation events (nearly twofold), along with a 30% rise in precipitation intensity, has been observed in the recent decade compared to the 1980s, and models demonstrate a similar directional change but tend to underestimate the magnitude of observed precipitation. This increase appears to be linked to the rapid warming of the Indian Ocean, which, in turn, increases the water vapor in the atmosphere, ultimately supplying more moisture to the southeastern peninsular India. On the other hand, observed discrepancies in replicating some of the reported widespread impactful extreme precipitation events in the years 2007 and 2015 over the southern India region underscore the need for caution when interpreting model simulations. Low-pressure systems, such as troughs, associated with cyclonic circulations originating from the Bay of Bengal, have been identified as the primary sources of moisture fueling heavy precipitation during these events. Cluster analysis highlights varying synoptic patterns within the general framework, emphasizing the need for a more nuanced approach in simulating and forecasting extreme precipitation events. Overall, this study underscores the importance of enhancing modeling capabilities to better understand and prepare for the growing challenges posed by extreme precipitation events.
Bcl-xL targeting eliminates ageing tumor-promoting neutrophils and inhibits lung tumor growth
Authors: Bodac Anita , Mayet Abdullah , Rana Sarika , Pascual Justine , Bowler Amber D , Roh Vincent , Fournier Nadine , Craciun Ligia , Demetter Pieter , Radtke Freddy , Meylan Etienne 
Published: December 2023

AbstractElevated peripheral blood and tumor-infiltrating neutrophils are often associated with a poor patient prognosis. However, therapeutic strategies to target these cells are difficult to implement due to the life-threatening risk of neutropenia. In a genetically engineered mouse model of lung adenocarcinoma, tumor-associated neutrophils (TAN) demonstrate tumor-supportive capacities and have a prolonged lifespan compared to circulating neutrophils. Here, we show that tumor cell-derived GM-CSF triggers the expression of the anti-apoptotic Bcl-xL protein and enhances neutrophil survival through JAK/STAT signaling. Targeting Bcl-xL activity with a specific BH3 mimetic, A-1331852, blocked the induced neutrophil survival without impacting their normal lifespan. Specifically, oral administration with A-1331852 decreased TAN survival and abundance, and reduced tumor growth without causing neutropenia. We also show that G-CSF, a drug used to combat neutropenia in patients receiving chemotherapy, increased the proportion of young TANs and augmented the anti-tumor effect resulting from Bcl-xL blockade. Finally, our human tumor data indicate the same role for Bcl-xL on pro-tumoral neutrophil survival. These results altogether provide preclinical evidence for safe neutrophil targeting based on their aberrant intra-tumor longevity.
A novel miniaturized waveguide all pole band pass filter using confined multi‐layered frequency selective surfaces
Authors: Patnaik Kalyan Mohan , Basavarajappa Gowrish 
Published: December 2023

AbstractThis letter presents a novel technique for realizing waveguide all pole band pass filters (BPFs). To the best of the authors’ knowledge this work is the first of its kind to confine the frequency selective surface (FSS) within a waveguide to realize highly miniatured high‐performance BPF. For the proof of the concept, a sixth‐order all pole BPF is realized at 10 GHz with a fractional bandwidth of 10%. The measured peak insertion loss of the filter is better than 1.2 dB and return loss is better than 15 dB. The proposed concept yields a remarkable miniaturization with an internal volume reduction of 30%. Space mapping technique has been adopted to systematically design the filter.
Joint transceiver optimization for secure OFDMA over‐the‐air computation systems
Authors: Li Quanzhong , Yang Liang 
Published: December 2023

AbstractFor over‐the‐air computation (AirComp) systems, secure data aggregation is an important issue. This letter investigates joint transceiver optimization for secure data aggregation in orthogonal frequency division multiple access (OFDMA) AirComp systems. The aim is to minimize the computation mean square error of the fusion centre, while satisfying the security constraint of the computation mean square error of the eavesdropper and the power constraints of the sensors. The formulated optimization problem is non‐convex, and an effective iterative algorithm is proposed to solve it. Simulation results demonstrate the superiority of the proposed scheme.
Optimizing chest tuberculosis image classification with oversampling and transfer learning
Authors: Alqahtani Ali , Abu Al‐Haija Qasem , Alsulami Abdulaziz A. , Alturki Badraddin , Alqahtani Nayef , Alsini Raed 
Published: December 2023

AbstractTuberculosis (TB) is an extremely contagious illness caused by Mycobacterium tuberculosis. Chest tuberculosis classification is conducted based on a deep convolutional neural network architecture. In this research, a pre‐trained network is utilized to demonstrate the advantage of using the oversampling technique on the classification of TB and compare results with recent research that used the same dataset. Therefore, the dataset consists of 3500 uninfected TB cases and 700 infected with TB. This paper circumvents the imbalance by using the oversampling technique in X‐ray TB images to be fed into several pre‐trained networks for TB classification. The oversampling technique is crucial in enhancing the performance of TB classification compared with other pre‐trained models reported here. Inceptionv3 shows a promising result compared to other pre‐trained models; it achieves 99.94% accuracy, 99.88% precision, 100% recall, and 99.94% F1‐Score.
Characterization and application of lamellar zeolite‐X prepared from kaolin
Authors: Jia Weilin , Wang Suyang , Deng Yingying , Shen Jie , Zhao Ping , Wang Zepeng , Shao Jiaojing , Wang Yuanyu , Sun Qi 
Published: December 2023

AbstractA simple and effective method was reported for the rapid synthesis of zeolite X from kaolin by adding a template agent. The results of X‐ray diffraction confirm the good crystallinity of the synthesized X‐zeolite with lamellar structure. Transmission electron microscopy images clearly demonstrate the lamellar structure of the synthesized X‐zeolite. The corresponding selective electron diffraction pattern suggests that the crystal structure of X‐type zeolite is octahedral. The co‐existence and uniform distribution of Si, Al, O, and Na in the layered structure of the synthesized X‐type zeolite are detected by element mapping. In addition, N2 adsorption–desorption measurement indicates that the specific surface area of the lamellar zeolite X is 153.4625 m2 g−1. The micropore surface area is 148.8374 m2 g−1, and the micropore volume is 0.073377 m2 g−1. After exploring the influence of different temperatures on the adsorption of carbon dioxide, the research shows that two‐dimensional zeolite X has the best adsorption capacity for carbon dioxide. The adsorption and separation performance of CO2/CH4 was investigated. The study showed that the adsorption and separation coefficient of two‐dimensional zeolite X was the highest.
Semi-supervised deep learning for molecular clump verification
Authors: Luo Xiaoyu , Zheng Sheng , Jiang Zhibo , Chen Zhiwei , Huang Yao , Zeng Shuguang , Zeng Xiangyun 
Published: December 2023

Context.A reliable molecular clump detection algorithm is essential for studying these clumps. Existing detection algorithms for molecular clumps still require that detected candidates be verified manually, which is impractical for large-scale data. Semi-supervised learning methods, especially those based on deep features, have the potential to accomplish the task of molecular clump verification thanks to the powerful feature extraction capability of deep networks.Aims.Our main objective is to develop an automated method for the verification of molecular clump candidates. This method utilises a 3D convolutional neural network (3D CNN) to extract features of molecular clumps and employs semi-supervised learning to train the model, with the aim being to improve its generalisation ability and data utilisation. It addresses the issue of insufficient labelled samples in traditional supervised learning and enables the model to better adapt to new, unlabelled samples, achieving high accuracy in the verification of molecular clumps.Methods.We propose SS-3D-Clump, a semi-supervised deep clustering method that jointly learns the parameters of a 3D CNN and the cluster assignments of the generated features for automatic verification of molecular clumps. SS-3D-Clump iteratively classifies the features with the Constrained-KMeans and uses these class labels as supervision to update the weights of the entire network.Results.We used CO data from the Milky Way Imaging Scroll Painting project covering 350 square degrees in the Milky Way’s first, second, and third quadrants. The ClumpFind algorithm was applied to extract molecular clump candidates in these regions, which were subsequently verified using SS-3D-Clump. The SS-3D-Clump model, trained on a dataset comprising three different density regions, achieved an accuracy of 0.933, a recall rate of 0.955, a precision rate of 0.945, and an F1 score of 0.950 on the corresponding test dataset. These results closely align with those obtained through manual verification.Conclusions.Our experiments demonstrate that the SS-3D-Clump model achieves high accuracy in the automated verification of molecular clumps. It effectively captures the essential features of the molecular clumps and overcomes the challenge of limited labelled samples in supervised learning by using unlabelled samples through semi-supervised learning. This enhancement significantly improves the generalisation capability of the SS-3D-Clump model, allowing it to adapt effectively to new and unlabelled samples. Consequently, SS-3D-Clump can be integrated with any detection algorithm to create a comprehensive framework for the automated detection and verification of molecular clumps.
Empirical instability strip for classical Cepheids
Authors: Espinoza-Arancibia F. , Pilecki B. , Pietrzyński G. , Smolec R. , Kervella P. 
Published: December 2023

Context. The instability strip (IS) of classical Cepheids has been extensively studied theoretically. Comparing the theoretical IS edges with those obtained empirically, using the most recent Cepheids catalogs available, can provide us with insights into the physical processes that determine the position of the IS boundaries.
Aims. We aim to investigate the empirical positions of the IS of the classical Cepheids in the Large Magellanic Cloud (LMC), considering any effect that increases its width, to obtain intrinsic edges that can be compared with theoretical models.
Methods. We used data of classical fundamental-mode (F) and first-overtone (1O) LMC Cepheids from the OGLE-IV variable star catalog, together with a recent high-resolution reddening map from the literature. Our final sample includes 2058 F and 1387 1O Cepheids. We studied their position on the Hertzsprung-Russell diagram and determined the IS borders by tracing the edges of the color distribution along the strip.
Results. We obtained the blue and red edges of the IS in V- and I-photometric bands, in addition to log Teff and log L. The results obtained show a break located at the Cepheids’ period of about three days, which was not reported before. We compared our empirical borders with theoretical ones published in the literature, obtaining a good agreement for specific parameter sets.
Conclusions. The break in the IS borders is most likely explained by the depopulation of second- and third-crossing classical Cepheids in the faint part of the IS, since blue loops of evolutionary tracks in this mass range do not extend blueward enough to cross the IS at the LMC metallicity. Results from the comparison of our empirical borders with theoretical ones prove that our empirical IS is a useful tool for constraining theoretical models.
MAGIC: MUSE gAlaxy Groups In COSMOS – A survey to probe the impact of environment on galaxy evolution over the last 8 Gyr
Authors: Epinat B. , Contini T. , Mercier W. , Ciesla L. , Lemaux B. C. , Johnson S. D. , Richard J. , Brinchmann J. , Boogaard L. A. , Carton D. , Michel-Dansac L. , Bacon R. , Krajnović D. , Finley H. , Schroetter I. , Ventou E. , Abril-Melgarejo V. , Boselli A. , Bouché N. F. , Kollatschny W. , Kovač K. , Paalvast M. , Soucail G. , Urrutia T. , Weilbacher P. M. 
Published: December 2023

Context. Galaxies migrate along filaments of the cosmic web from small groups to clusters, which creates the appearance that the evolution of their properties speeds up as environments get denser.
Aims. We introduce the MUSE gAlaxy Groups in COSMOS (MAGIC) survey, which was built to study the impact of environment on galaxy evolution down to low stellar masses over the last 8 Gyr.
Methods. The MAGIC survey consists of 17 Multi-Unit Spectrocopic Exporer (MUSE) fields targeting 14 massive, known structures at intermediate redshift (0.3 < z < 0.8) in the COSMOS area, with a total on-source exposure of 67 h. We securely measured the redshifts for 1419 sources and identified 76 galaxy pairs and 67 groups of at least three members using a friends-of-friends algorithm. The environment of galaxies is quantified from group properties, as well as from global and local density estimators.
Results. The MAGIC survey has increased the number of objects with a secure spectroscopic redshift over its footprint by a factor of about 5 compared to previous extensive spectroscopic campaigns on the COSMOS field. Most of the new redshifts have apparent magnitudes in the z++ band zapp++ > 21.5. The spectroscopic redshift completeness is high: in the redshift range of [O II] emitters (0.25 ≤ z < 1.5), where most of the groups are found, it globally reaches a maximum of 80% down to zapp++ = 25.9, and locally decreases from ∼100% to ∼50% in magnitude bins from zapp++ = 23−24 to zapp++ = 25.5. We find that the fraction of quiescent galaxies increases with local density and with the time spent in groups. A morphological dichotomy is also found between bulge-dominated quiescent and disk-dominated star-forming galaxies. As environment gets denser, the peak of the stellar mass distribution shifts towards M⋆ > 1010 M⊙, and the fraction of galaxies with M⋆ < 109 M⊙ decreases significantly, even for star-forming galaxies. We also highlight peculiar features such as close groups, extended nebulae, and a gravitational arc.
Conclusions. Our results suggest that galaxies are preprocessed in groups of increasing mass before entering rich groups and clusters. We publicly release two catalogs containing the properties of galaxies and groups, respectively.