bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neutrophil extracellular traps-related lncRNAs prognostic signature for gastric cancer and immune infiltration: potential biomarkers for predicting overall survival and clinical therapy
Authors: Yang Shuhan , Liang Jiahui , Wang Xin , Qi Yijun , Chan Shixin , Song Yonghu , Pei Xiaohan , Ren Zhiyao 
Published: July 2024

AbstractGastric cancer (GC) is one of the most common digestive tract malignant tumors in the world. At the time of initial diagnosis, it frequently presents with local or distant metastasis, contributing to poor prognosis in patients. Neutrophil extracellular traps (NETs) constitute a mechanism employed by neutrophils that is intricately associated with tumor progression, prognosis, and response to immunotherapy and chemotherapy. Despite this, the specific involvement of NETs-related long non-coding RNAs (lncRNAs) in gastric cancer remains unclear. A prognostic model for NETs-related lncRNAs was constructed through correlation analysis, COX regression analysis, and least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the model was assessed using Kaplan–Meier survival curves, receiver operating characteristic (ROC) curves, facilitating the exploration of the relationship between disease onset and prognosis in gastric cancer. Additionally, differences in the tumor microenvironment and response to immunotherapy among gastric cancer patients across high- and low-risk groups were analyzed. Furthermore, a prognostic nomogram integrating the risk score with relevant clinicopathological parameters was developed. The prognostic prediction model for gastric cancer, derived from NETs-related lncRNAs in this study, demonstrates robust prognostic capabilities, serving as a valuable adjunct to traditional tumor staging. This model holds promise in offering novel guidelines for the precise treatment of gastric cancer, thereby potentially improving patient outcomes.
New Surgical Approaches to Scoliosis Repair in Pediatric Patients—Implications for Anesthetic Management
Authors: Ferschl Marla B. , Shibata Gail , Wong Jocelyn 
Published: July 2024

Abstract
Purpose of Review
The treatment of pediatric scoliosis has evolved over time. Newer treatment modalities provide alternative options for patients that optimize outcomes. In this manuscript, we will review pediatric scoliosis and focus on the anesthetic management techniques for its surgical correction.

Recent Findings
Many modifications to the surgical repair of scoliosis have occurred since the procedure was first performed in the 1960s. Improved surgical equipment and imaging techniques have improved outcomes for posterior spinal fusion. Many centers are now employing anterior spinal tethering procedures. In all cases, anesthetic techniques have been refined over time to improve pre-, intra-, and post-operative management.

Summary
Innovative surgical approaches and novel anesthetic protocols have impacted the management of patients with scoliosis. Future research is needed to further refine techniques.
Enhancing Human Comfort in eVTOL Aircraft Assisted by Control Moment Gyroscopes
Authors: Bhalla Sameer , Kim Donghoon , Choi Daegyun 
Published: July 2024

Abstract
This study investigates the integration of Control Moment Gyroscopes (CMGs) to enhance the comfort of human occupants in electric Vertical Take-Off and Landing (eVTOL) aircraft. Our study encompasses not only the development of a dynamic model for the eVTOL by integrating the CMGs but also the implementation of backstepping sliding mode-based controllers for translation and attitude control. To simulate realistic disturbance scenarios, wind disturbance models and a motor dynamics model are considered to replicate practical rotor responses. To validate the performance of the proposed approach, comprehensive Monte-Carlo simulations under varying wind conditions are performed. In particular, the aircraft oscillations are analyzed in the frequency domain to focus on a specific frequency that causes human discomfort. The simulation results demonstrate that the use of CMGs not only alleviates oscillations induced by wind disturbances with low power consumption but also significantly enhances passenger comfort.
Building collaboration and trust in emergency preparedness: a model for planning collaboration exercises
Authors: Elvegård Rune , Andreassen Natalia , Badu James 
Published: July 2024

AbstractCollaborative preparedness exercises are essential in emergency management. In this conceptual paper, we examine the planning processes of emergency preparedness collaborative exercises, aiming to develop a model that enhances learning, collaboration, communication, and trust among participants. We propose a model that guides the planning of collaborative preparedness exercises, focusing on creating and maximizing knowledge among participants. The model emphasizes the importance of defining clear learning objectives, selecting engaging scenarios, and incorporating flexible exercise designs to improve effectiveness. By systematically integrating communication and trust-building strategies across planning, execution, debriefing, and evaluation phases, the model seeks to foster a collaborative environment conducive to shared learning and decision-making. This conceptual study contributes to the literature by offering a structured approach to exercise planning that could enhance the competencies of emergency preparedness organizations and improve collaborative efforts in crisis management. Future research could apply this model in practice and empirically evaluate its impact on emergency preparedness exercises across various sectors.
Enhancing Educational Technology in Lectures for School Students with Learning Disabilities: A Comprehensive Analysis
Authors: Adjiovski Benjamin , Bogatinoska Dijana Capeska , Ismajloska Mersiha , Malekian Reza 
Published: July 2024

AbstractLearning disabilities present formidable obstacles for children in their educational journeys, often overlooked or misunderstood. This research aims to address two critical issues: the differentiation between learning and intellectual disabilities, and the resistance of teachers to integrating technology into education. In response, a comprehensive approach was adopted. Firstly, a mobile application was developed to screen for potential learning disabilities, offering teachers insights into individual student challenges and personalized lecture adaptations. Secondly, a quasi-experimental pretest–posttest study was conducted, comparing student performance following traditional and technologically supported lectures. Results from the study revealed significant score improvements among students identified as potentially having learning disabilities when exposed to technologically supported lectures. Conversely, students not identified as potential cases remained within the normal range of performance. These findings underscore the potential of technology to enhance educational outcomes for children with learning disabilities while highlighting the importance of recognizing and addressing these challenges in educational settings. By bridging the gap between identification and intervention, this research contributes to a more inclusive and effective educational environment.
Gesundheit, Psychiatrie und Klimakatastrophe
Authors: Adelmann Georg 
Published: July 2024

Was ist zu diesem Thema bereits bekannt? Die schwerwiegenden Folgen der Klimakatastrophe für die psychische Gesundheit sind klar. Die besondere Betroffenheit von Menschen mit psychiatrischen Diagnosen z.B. bei Extremwetterereignissen betont auch die Fachliteratur. Wie wird eine neue Perspektive eingebracht? Die Zusammenschau von Klimaaktivismus, Psychiatriesystem und Resilienz des Gesundheits- und Gesellschaftssystems angesichts der zunehmenden sozialökologischen Krisen wird versucht. Was sind die Auswirkungen für die Praxis? Aktiv werden gegen ein Verschlimmern der Krisen und für ein resilientes, macht- und diskriminierungssensibles Miteinander auf der Arbeit, privat und politisch schützt die Gesundheit aller.
Green Hospital – eine Vision
Authors: Voß Thomas 
Published: July 2024

Was ist zu diesem Thema bereits bekannt? Alle reden vom Green Hospital und wissen, dass wir handeln müssen, um dem Klimawandel und dem dramatischen Verlust an Biodiversität entgegenzuwirken. Aber die Konkurrenz mit Problemen wie Finanzierung, Arbeitskräftemangel und Bürokratie ist groß. Wie wird eine neue Perspektive eingebracht? Die LWL-Kliniken Münster und Lengerich engagieren sich schon seit Jahren für nachhaltige Unternehmensführung. Der Beitrag zeigt, dass sehr viel machbar ist, wenn man will und die Beschäftigten mitnimmt. Was sind die Auswirkungen für die Praxis? Führung und Beschäftigte engagieren sich gemeinsam, die Entwicklung der CO2-Bilanz ist beeindruckend. Die Kliniken werden in der Öffentlichkeit positiv wahrgenommen.
Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data
Authors: Li Guoliang , Ben‐Zion Yehuda 
Published: July 2024

AbstractWe develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.
Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project
Authors: Sitch Stephen , O’Sullivan Michael , Robertson Eddy , Friedlingstein Pierre , Albergel Clément , Anthoni Peter , Arneth Almut , Arora Vivek K. , Bastos Ana , Bastrikov Vladislav , Bellouin Nicolas , Canadell Josep G. , Chini Louise , Ciais Philippe , Falk Stefanie , Harris Ian , Hurtt George , Ito Akihiko , Jain Atul K. , Jones Matthew W. , Joos Fortunat , Kato Etsushi , Kennedy Daniel , Klein Goldewijk Kees , Kluzek Erik , Knauer Jürgen , Lawrence Peter J. , Lombardozzi Danica , Melton Joe R. , Nabel Julia E. M. S. , Pan Naiqing , Peylin Philippe , Pongratz Julia , Poulter Benjamin , Rosan Thais M. , Sun Qing , Tian Hanqin , Walker Anthony P. , Weber Ulrich , Yuan Wenping , Yue Xu , Zaehle Sönke 
Published: July 2024

AbstractThe terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land‐atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio‐temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO2, climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote‐sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (−0.58 ± 0.54 PgC/yr). Forests and semi‐arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi‐arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (−1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions.
Impact of Marine Shipping Emissions on Ozone Pollution During the Warm Seasons in China
Authors: Zheng Songci , Jiang Fei , Feng Shuzhuang , Liu Huan , Wang Xiaoyuan , Tian Xudong , Ying Chuanyou , Jia Mengwei , Shen Yang , Lyu Xiaopu , Guo Hai , Cai Zhe 
Published: July 2024

AbstractAs China's land‐based anthropogenic emissions are decreasing, the impact of marine shipping emissions (MSEs) on the atmosphere, especially in coastal areas, deserves further attention. This study investigates the impact of MSEs on MDA8 ozone (O3) levels during the warm seasons of 2017 in China, considering different seasons and synoptic patterns. The results indicate that the average impact of MSEs on O3 decreases from offshore to inland, peaking at over 29.0 ppb at sea and 13.8 ppb along the coast of mainland China. Influenced by precursor emissions, meteorology and other factors, MSEs contribute differently to O3 in Beijing‐Tianjin‐Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD), with contributions of 3.0, 5.2, and 4.9 ppb, respectively, and ranging from 2.7 to 7.3 ppb in 13 coastal port cities. The O3 impacts of MSEs are higher on polluted days than on clean days, especially during onshore winds. In the BTH, MSEs increase O3 by 5.5 ppb on polluted days and 3.0 ppb on clean days with northeast winds from the Bohai Sea. In the YRD, MSEs increase O3 by 9.4 ppb on polluted days and 7.3 ppb on clean days with southeast winds. MSEs significantly increase O3 levels in the PRD by 11.0 ppb on polluted days and 5.0 ppb on clean days with southeast winds. Although the emission inventories, initial and boundary conditions, etc. may introduce uncertainties, our results still provide useful information for O3 pollution management in coastal cities as a reasonable way to track mass contributions.
Voice signals database of ALS patients with different dysarthria severity and healthy controls
Authors: Dubbioso Raffaele , Spisto Myriam , Verde Laura , Iuzzolino Valentina Virginia , Senerchia Gianmaria , Salvatore Elena , De Pietro Giuseppe , De Falco Ivanoe , Sannino Giovanna 
Published: July 2024

AbstractThis paper describes a new publicly-available database of VOiCe signals acquired in Amyotrophic Lateral Sclerosis (ALS) patients (VOC-ALS) and healthy controls performing different speech tasks. This dataset consists of 1224 voice signals recorded from 153 participants: 51 healthy controls (32 males and 19 females) and 102 ALS patients (65 males and 37 females) with different severity of dysarthria. Each subject’s voice was recorded using a smartphone application (Vox4Health) while performing several vocal tasks, including a sustained phonation of the vowels /a/, /e/, /i/, /o/, /u/ and /pa/, /ta/, /ka/ syllable repetition. Basic derived speech metrics such as harmonics-to-noise ratio, mean and standard deviation of fundamental frequency (F0), jitter and shimmer were calculated. The F0standard deviation of vowels and syllables showed an excellent ability to identify people with ALS and to discriminate the different severity of dysarthria. These data represent the most comprehensive database of voice signals in ALS and form a solid basis for research on the recognition of voice impairment in ALS patients for use in clinical applications.
Intelligent breast cancer diagnosis with two-stage using mammogram images
Authors: Yaqub Muhammad , Jinchao Feng , Aijaz Nazish , Ahmed Shahzad , Mehmood Atif , Jiang Hao , He Lan 
Published: July 2024

AbstractBreast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. Mammography is a key tool for identifying and diagnosing breast abnormalities; however, accurately distinguishing malignant mass lesions remains challenging. To address this issue, we propose a novel deep learning approach for BC screening utilizing mammography images. Our proposed model comprises three distinct stages: data collection from established benchmark sources, image segmentation employing an Atrous Convolution-based Attentive and Adaptive Trans-Res-UNet (ACA-ATRUNet) architecture, and BC identification via an Atrous Convolution-based Attentive and Adaptive Multi-scale DenseNet (ACA-AMDN) model. The hyperparameters within the ACA-ATRUNet and ACA-AMDN models are optimized using the Modified Mussel Length-based Eurasian Oystercatcher Optimization (MML-EOO) algorithm. The performance is evaluated using a variety of metrics, and a comparative analysis against conventional methods is presented. Our experimental results reveal that the proposed BC detection framework attains superior precision rates in early disease detection, demonstrating its potential to enhance mammography-based screening methodologies.
Circular economy reinforcement through molecular fabrication of textile wastes with microbial synthesized ZnO nanoparticles to have multifunctional properties
Authors: Darwesh Osama M. , Matter Ibrahim A. , Al-Balakocy Naser G. , Abo-Alkasem Mohamed I. 
Published: July 2024

AbstractThe fibrous wastes generated from the mills of textile production can be recycled and converted into high add-values products to be implemented in several applications. The current study aimed to employ commercial free cellulase enzyme to partially hydrolyze (activate) the polyester cotton blended (PET/C) fibrous wastes by creation functional groups such as OH and COOH on their surfaces. The activated fibrous wastes were then modified by coating with ZnO nanoparticles (ZnO-NPs) biosynthesized by actinobacterial cultures free supernatant. The isolate was identified as Streptomyces pseudogriseolus with accession number of OR574241. The conditions that influence the actino-synthesis of ZnO-NPs were optimized and the product was characterized using spectroscopic vision, FTIR, XRD, TEM and SEM. The characteristic ZnO peaks were obviously observed by EDX analysis with 0.38 and 0.75% (wt%), respectively. TEM analyses proved the nanoscale of ZnO-NPs (5–15 nm) which was followed by cytotoxic evaluation for the produced NPs. Fortunately, the tested actino-ZnO-NPs didn’t have any cytotoxicity against human normal fibroblast cell line (BJ1), which means that the product can be safely used in a direct-contact with human skin. The treated PET/C blended waste fabrics coated with ZnO-NPs showed high antimicrobial activity and ultraviolet protection values after functionalization by cellulase. EDX analysis demonstrates the presence of Zn peaks on the coated fabrics compared with their absence in blank and control samples, while SEM images showed the formation of a thin layer of ZnO-NPs on the fabric surface. The obtained smart textile can be applied several needed sectors.
Automated PD-L1 status prediction in lung cancer with multi-modal PET/CT fusion
Authors: Da-ano Ronrick , Andrade-Miranda Gustavo , Tankyevych Olena , Visvikis Dimitris , Conze Pierre-Henri , Rest Catherine Cheze Le 
Published: July 2024

AbstractProgrammed death-ligand 1 (PD-L1) expressions play a crucial role in guiding therapeutic interventions such as the use of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) in lung cancer. Conventional determination of PD-L1 status includes careful surgical or biopsied tumor specimens. These specimens are gathered through invasive procedures, representing a risk of difficulties and potential challenges in getting reliable and representative tissue samples. Using a single center cohort of 189 patients, our objective was to evaluate various fusion methods that used non-invasive computed tomography (CT) and$$^{18}$$18F-FDG positron emission tomography (PET) images as inputs to various deep learning models to automatically predict PD-L1 in non-small cell lung cancer (NSCLC). We compared three different architectures (ResNet, DenseNet, and EfficientNet) and considered different input data (CT only, PET only, PET/CT early fusion, PET/CT late fusion without as well as with partially and fully shared weights to determine the best model performance. Models were assessed utilizing areas under the receiver operating characteristic curves (AUCs) considering their 95% confidence intervals (CI). The fusion of PET and CT images as input yielded better performance for PD-L1 classification. The different data fusion schemes systematically outperformed their individual counterparts when used as input of the various deep models. Furthermore, early fusion consistently outperformed late fusion, probably as a result of its capacity to capture more complicated patterns by merging PET and CT derived content at a lower level. When we looked more closely at the effects of weight sharing in late fusion architectures, we discovered that while it might boost model stability, it did not always result in better results. This suggests that although weight sharing could be beneficial when modality parameters are similar, the anatomical and metabolic information provided by CT and PET scans are too dissimilar to consistently lead to improved PD-L1 status predictions.
On the role of longitudinal currents in radiating systems of charges
Authors: Nemkov Nikita A. , Fedotov Vassili A. 
Published: July 2024

AbstractThe time derivative of a charge density is linked to a current density by the continuity equation. However, it features only the longitudinal part of a current density, which is known to produce no radiation. This fact usually remains unnoticed and may appear puzzling at first, suggesting that the temporal variation of a charge density should be also irrelevant to radiation. We alleviate the apparent contradiction by showing that the effective longitudinal currents are not spatially confined, even when the time-dependent radiating charge density that generates them is. This enforces the co-existence of the complementary, i.e. transverse, part of the current, which, in turn, gives rise to radiation. We illustrate the necessarily delocalized nature and relevance of longitudinal currents to the emission of electromagnetic waves by a dynamic electric dipole, discussing the practical implications of that for radation in partially conducting condensed matter. More generally, we show how the connection between the longitudinal and transverse currents shapes the structure of the conventional multipole expansion and fuels the ongoing confusion surrounding the charge and toroidal multipoles.