bluuebunny/crossref_metadata_2025_split huggingface dataset:
Situation der Betreuung von Lungenkarzinompatienten im Hinblick auf Mindestmengenregelung und Personalmangel
Authors: Karampinis Ioannis , Schiller Philipp , Galata Christian , Scheubel Robert , Buhl Roland , Kreuter Michael , Hetzel Martin , Voshaar Thomas , Roessner Eric 
Published: September 2024

Zusammenfassung
Einleitung Das Lungenkarzinom ist die maligne Erkrankung mit der weltweit höchsten Mortalität. Durch die 2025 in Kraft tretende Mindestmengenregelung für die chirurgische Behandlung des Lungenkarzinoms ist in Deutschland eine relevante Personalverschiebung zu erwarten. Ziel dieser Umfrage war es, vor den zu erwartenden Veränderungen die aktuellen Strukturen sowie die Personalsituation in den pneumologischen und thoraxchirurgischen Abteilungen zu erheben.

Methodik Über den Verband der Pneumologischen Kliniken und die Deutsche Gesellschaft für Thoraxchirurgie (DGT) wurde eine Online-Umfrage an leitende Ärzte der Pneumologie und der Thoraxchirurgie in Deutschland verschickt. Die Ergebnisse wurden nach Zertifizierungsstatus analysiert.

Ergebnisse Die Rücklaufquote betrug 29,3% (Pneumologie) bzw. 31,9% (Thoraxchirurgie). 67% der befragten Abteilungen waren eigenständig. Zur personellen Abdeckung der Bereitschafsdienste bestehen häufig Kooperationen mit anderen internistischen oder chirurgischen Disziplinen. Der Anteil von nicht besetzten Stellen lag bei 35% (Pneumologie) bzw. 57% (Thoraxchirurgie).

Diskussion Nach Umsetzung der Mindestmengenregelung wird sich die Behandlung des Lungenkarzinoms mutmaßlich auf deutlich weniger Kliniken mit höherer Fallzahl konzentrieren. Bei bereits jetzt deutlich angespannter Personalsituation bleibt abzuwarten, inwieweit es diesen Einrichtungen gelingen wird, Personal für eine adäquate und zeitnahe Behandlung zu rekrutieren.
Machine Learning for the Prediction of Surgical Morbidity in Placenta Accreta Spectrum
Authors: Futterman Itamar D. , Sher Olivia , Saroff Chaskin , Cohen Alexa , Doulaveris Georgios , Dar Pe'er , Griffin Myah M. , Limaye Meghana , Owens Thomas , Brustman Lois , Rosenberg Henri , Jessel Rebecca , Chudnoff Scott , Haberman Shoshana 
Published: September 2024

Objective We sought to create a machine learning (ML) model to identify variables that would aid in the prediction of surgical morbidity in cases of placenta accreta spectrum (PAS).
Study Design A multicenter analysis including all cases of PAS identified by pathology specimen confirmation, across five tertiary care perinatal centers in New York City from 2013 to 2022. We developed models to predict operative morbidity using 213 variables including demographics, obstetrical information, and limited prenatal imaging findings detailing placental location. Our primary outcome was prediction of a surgical morbidity composite defined as including any of the following: blood loss (>1,500 mL), transfusion, intensive care unit admission, vasopressor use, mechanical ventilation/intubation, and organ injury. A nested, stratified, cross-validation approach was used to tune model hyperparameters and estimate generalizability. Gradient boosted tree classifier models incorporated preprocessing steps of standard scaling for numerical variables and one-hot encoding for categorical variables. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), positive and negative predictive values (PPV, NPV), and F1 score. Variable importance ranking was also determined.
Results Among 401 PAS cases, 326 (81%) underwent hysterectomy. Of the 401 cases of PAS, 309 (77%) had at least one event defined as surgical morbidity. Our predictive model had an AUC of 0.79 (95% confidence interval: 0.69, 0.89), PPV 0.79, NPV 0.76, and F1 score of 0.88. The variables most predictive of surgical morbidity were completion of a hysterectomy, prepregnancy body mass index (BMI), absence of a second trimester ultrasound, socioeconomic status zip code, BMI at delivery, number of prenatal visits, and delivery time of day.
Conclusion By identifying social and obstetrical characteristics that increase patients' risk, ML models are useful in predicting PAS-related surgical morbidity. Utilizing ML could serve as a foundation for risk and complexity stratification in cases of PAS to optimize surgical planning.
Key Points
Frequent Unrecognized Vertebral Fractures Associated with Increased Body Fat Mass in Children and Adolescents with Duchenne Muscular Dystrophy
Authors: Prasiw Kanlaya , Khongkhatithum Chaiyos , Fuangfa Praman , Kositwattanarerk Arpakorn , Mahachoklertwattana Pat , Poomthavorn Preamrudee 
Published: September 2024

Abstract
Objective Patients with Duchenne muscular dystrophy (DMD) have an increased risk of vertebral fractures (VFs). Ethnic variations may partly contribute to the fracture risk. This study aimed to demonstrate the VFs and body fat mass in Asian patients with DMD.
Methods Demographic data and DMD-related parameters of the enrolled patients were collected. Lateral thoracolumbar spine radiographs were performed for VF assessment. The Genant classification was applied for VF severity grading (mild, moderate, and severe). Body composition analysis using dual-energy X-ray absorptiometry was performed. Serum calcium, phosphate, intact parathyroid hormone, and 25-hydroxyvitamin D concentrations were determined.
Results There were 25 children and adolescents with DMD enrolled. The median (interquartile range [IQR]) age was 12.9 (9.6–19.3) years. Nine patients (36%) had VFs with a total of 31 sites of VFs (mild, N = 10; moderate, N = 3; and severe, N = 18). These VFs had never been recognized prior to this study. Comparing with the non-VF group, the VF group received a significantly greater cumulative prednisolone equivalent dose (1,258 [948–1,664] vs. 291 [17–823] mg/kg, p = 0.003). Body fat mass, represented by fat mass index and body fat percentage Z-scores, was greater in the VF group (2.46 [2.21–2.51] vs. 1.63 [0.36–2.07], p = 0.011 and 4.4 [3.1–5.5] vs. 1.8 [0.6–3.5], p = 0.008, respectively). No differences in serum calciotropic hormones and vitamin D status were demonstrated between patients with and without VFs.
Conclusions VFs were frequent in patients with DMD. Patients with VFs had greater cumulative glucocorticoid dose and body fat mass than those without VFs.
3d-Metal-Catalyzed Single-Electron-Transfer-Induced Conversion of Carboxylic Acids and Their Equivalents
Authors: Bhadra Sukalyan , Shinde Rupali Dasharath , Patel Upendra Kumar Brijmohan 
Published: September 2024

AbstractThis account describes the latest developments on 3d-metal-catalyzed single-electron-transfer (SET)-induced strategies that use carboxylic acids and their synthetic equivalents as substrates. In general, 3d-metal-promoted SET-mediated transformations of free carboxylic acids proceed readily via the formation of carboxylate radicals, whilst those of carboxylic acid equivalents, bearing an N-donor substituent, proceed via the formation of α-carbo radicals. The advantages of these strategies combine the low-cost of carboxylic acid starting materials and 3d metal catalysts with the possibility of realizing structurally diverse ranges of compounds in an atom- and step-economic manner. Developments primarily achieved by our group and a few by other researchers on this topic are discussed in this account.1	Introduction2	Mechanistic Considerations of 3d-Metal-Catalyzed SET-Mediated Transformations3	Developments Based on SET-Mediated Transformations of Carboxylic Acids4	Developments Based on SET-Mediated Transformations of Carboxylic Acid Equivalents5	Conclusion and Outlook
A Rapid, Greener, and Sustainable Synthesis of N-Acylhydrazones of Isoniazid in a Deep-Eutectic Solvent
Authors: Singh Parvesh , Gcabashe Nontobeko , Kumar Gobind , Seboletswe Pule , Manhas Neha 
Published: September 2024

AbstractThis study introduces an efficient, environmentally friendly, and sustainable method for synthesizing N-acylhydrazone analogues by engaging isoniazid in a condensation reaction with variously substituted benzaldehydes. The deep-eutectic solvent (ZnCl2/urea) employed in this study acted not only as a solvent but also as a catalyst to facilitate the synthesis of the target compounds within two to six minutes without the requirement of any lengthy purification techniques. The synthetic protocol is operationally simple and offers other remarkable advantages such as a short reaction time, good to excellent yields, a scalable protocol, and a recyclable and reusable catalyst. Additionally, green metrics calculations suggest the present method to be environmentally benign. Finally, the frontier molecular orbitals and the global reactivity parameters of the synthesized compounds were predicted by using density functional theory calculations.
A Single-Center Retrospective Cohort Study of Genotype–Phenotype Correlation of Osteogenesis Imperfecta in UAE
Authors: Zubaidi Abdulqader Al , Hassani Noura Al , Almazrouei Raya , AlShamsi Aisha 
Published: September 2024

Abstract
Background Osteogenesis imperfecta (OI) is a clinically and genetically heterogeneous group of inherited connective tissue disorders characterized by skeletal fragility. Patients with OI suffer recurrent fractures, limb deformities, and kyphoscoliosis. Multiple extraskeletal manifestations might also be present. Autosomal dominant variants in the COL1A1 or COL1A2 genes account for approximately 90% of cases.
Objective The aim of the study was to describe the variant spectrum and genotype–phenotype correlations in patients with OI seen in Tawam Hospital in the UAE.
Methods The authors conducted a retrospective chart review for all patients with OI assessed by geneticists at Tawam Hospital from January 2010 to December 2021. They retrieved each patient's baseline characteristics, detailed history and physical examination, laboratory, imaging, and genetic results.
Results A total of 40 patients with OI were found and included in this study. The majority (80%) were Emirati, and 57.5% were females. Consanguinity was documented in 24.3%. Thirty-seven patients (92.5%) had positive molecular testing; 28 patients (75.7%) had an autosomal dominant inheritance, and 9 patients (24.3%) had an autosomal recessive inheritance. The majority had missense variants. Four variants were novel. A high prevalence of pathogenic variants in the COL1A1 gene (57%) was found. Patients with variants in the LEPRE1 gene had early and severe phenotypes, while patients with variants in the TMEM38B gene had variable presentations. The majority of patients (85%) had skeletal phenotypes: fractures, bone deformity, scoliosis, and osteopenia. Extraskeletal phenotypes included blue sclera, dentinogenesis imperfecta, hearing loss, and dysmorphic features.
Conclusion This study reports the genotype–phenotype correlation of OI patients from the UAE. A high prevalence of pathogenic variants in the COL1A1 gene with OI type IV phenotype was found. Further multicenter more extensive studies are recommended.
Leakage current in GaN-on-GaN vertical GaN SBDs grown by HVPE on native GaN substrates
Authors: Jin Weiyi , Zhang Yumin , Xia Songyuan , Zhu Qizhi , Sun Yuanhang , Yi Juemin , Wang Jianfeng , Xu Ke 
Published: September 2024

This study investigates leakage mechanisms in vertical GaN-on-GaN Schottky barrier diodes (SBDs) and demonstrates effective mitigation strategies. The fabricated devices exhibit low reverse leakage current (1 × 10−5 A/cm2 at −200 V) and a high Ion/Ioff ratio (∼1010), surpassing the performance of GaN SBDs on foreign substrates. We elucidate dominant leakage mechanisms—thermionic emission, Poole–Frenkel emission, and variable-range hopping—and their evolution with temperature and bias. Optimized fabrication processes, including defect etching and a novel dual-layer passivation technique, achieve over a 1000-fold reduction in leakage current.
Room-temperature photonic quantum computing in integrated silicon photonics with germanium–silicon single-photon avalanche diodes
Authors: Na Neil , Hsu Chou-Yun , Chen Erik , Soref Richard 
Published: September 2024

Most, if not all, photonic quantum computing (PQC) relies upon superconducting nanowire single-photon detectors (SNSPDs) typically based on niobium nitride (NbN) operated at a temperature &lt;4 K. This paper proposes and analyzes 300 K waveguide-integrated germanium–silicon (GeSi) single-photon avalanche diodes (SPADs) based on the recently demonstrated normal-incidence GeSi SPADs operated at room temperature, and shows that their performance is competitive against that of NbN SNSPDs in a series of metrics for PQC with a reasonable time-gating window. These GeSi SPADs become photon-number-resolving avalanche diodes (PNRADs) by deploying a spatially-multiplexed M-fold-waveguide array of M GeSi SPADs. Using on-chip waveguided spontaneous four-wave mixing sources and waveguided field-programmable interferometer mesh circuits, together with the high-metric SPADs and PNRADs, high-performance quantum computing at room temperature is predicted for this PQC architecture.
A spectroscopic analysis code for spatially resolved x-ray absorption data from the COAX platform
Authors: Čamdžić Dž. , Johns H. M. , Kozlowski P. M. , Elshafiey A. , Fontes C. J. , Byvank T. , Urbatsch T. J. , Fryer C. L. , Barnak D. H. , Feinberg E. , Perry T. S. , Schmidt D. W. , Farhi B. Y. , Love K. N. , Christiansen N. S. , Colgan J. , Coffing S. X. , Cowan J. , Goodwin L. A. , Edwards S. , Fierro F. , Wilson C. , Randolph R. B. , Donovan P. , Sedillo T. , Jorgenson J. , Morrow T. , Garcia V. A. , Sherrill M. E. , Finnegan S. , Marshall A. 
Published: September 2024

Sophisticated tools such as computer vision techniques in combination with 1D lineout type analyses have been used in automating the analysis of spectral data for high energy density (HED) plasmas. Standardized automation can solve the problems posed by the complexity of HED spectra and the quantity of data. We present a spectroscopic code written for automated and streamlined analysis of spatially resolved x-ray absorption data from the COAX platform on Omega-60. COAX uses radiographs and spectroscopic diagnostics to provide shock position and density information. We also obtain the more novel spectral-derived spatial profile of the supersonic radiation flow into a low-density foam. Considerable effort has been spent modernizing our previous spectroscopic analysis method, including the development of new tools characterized by a faster runtime and minimal user input to reduce bias and a testing suite for verifying the accuracy of the various functions within the code. The new code analyzes our spectroscopic images in 1–2 min, with added uncertainty and confidence.
Fast photodiode arrays for high frequency fluctuation measurements of reconnecting flux ropes
Authors: Rood Thomas , Yadav Sonu , Bartolo Gustavo , Scime Earl 
Published: September 2024

An array of compact, high-bandwidth (&gt;200 MHz) and low-cost optical photodiodes has been developed and implemented on the PHASe MApping (PHASMA) experiment. Using purpose-built electronics, an array of 16 photodetectors was constructed and used to monitor broadband (1–5 MHz) fluctuations in light intensity emitted by flux ropes undergoing electron-only magnetic reconnection. These measurements reveal a swath of oscillatory behavior, including wave propagation inward toward the diffusion region at approximately the local electron Alfvén speed. Custom 3D-printed collection optics and mounting hardware allow quick reconfiguration of the array for radial or axial measurements. The electronics design is flexible enough to be used with other current-sourcing transducers, such as avalanche photodiodes; silicon photomultipliers; and infrared, x-ray, and UV photodiodes. A noise-rejecting electrical layout allows for low-noise operation close to pulsed plasma discharges. A 16-channel, 64-pixel tomographic array was constructed and initial reconstructions are presented.
Utility of a digital app to enhance patient–nurse communications and patient involvement in bedside handover: patient and nurse perceptions
Authors: Casey Penelope , Yuen Eva , Liskaser Raj , Blencowe Philippa , Boyd Leanne , Abdelrazek Mohamed , Wang Zoe , Considine Julie 
Published: September 2024

Objective This study aimed to explore patient and nurse perceptions of using a prototype co-designed app to support patient–nurse communication and patient engagement in bedside handover. Methods This qualitative descriptive study evaluated usability of the app with a convenience sample of patient–nurse dyads in a 22-bed medical/oncology ward, during morning shifts. Participants were nurses, and patients proficient in English but without cognitive impairment or physical or mental distress. Patients entered healthcare questions and preferences into the app, nurses acknowledged the information in the app and responded during their usual workflow. Patient comfort level with app use was surveyed. Handovers were observed, and patient involvement rated. After handover, semi-structured interviews and feedback surveys on app usability were conducted. Interviews were recorded, transcribed, and then analysed thematically. Survey data were analysed using descriptive statistics. Results Patient–nurse dyads (n = 18) used the app between March and May 2023. Patients were mostly older (median 69.5 years; IQR 52.3, 75), female, and frequent users of smartphones. Nurses were mostly younger (median 23 years; IQR 21, 40) and female. Five themes were identified, which indicated that using the app empowered patients to engage in healthcare communications, facilitated opportunities for patient-centred information sharing, and refocused nurses’ attention onto patient-centred care. Views differed on the app’s influence on patient involvement in handover. Surveys (n = 36, 100%) indicated that the interface was easy to navigate, features were useful, and only minor amendments were suggested. Conclusion This prototype app shows potential to facilitate patient-centred communication and patient engagement with health care, including bedside handover. With further refinement and testing, this app could enhance experiences of care and reduce harm from miscommunication.
Quantum and classical properties of the Universe according to unimodular quantum cosmology
Authors: Riahi Natascha 
Published: September 2024

Abstract
We investigate the dynamical behavior of wavepacket solutions due to unimodular quantum cosmology. We find early and late time quantum eras of the Universe. An Ehrenfest theorem ensures quasi-classical behavior for the late time Universe if the quantum uncertainties are small. The surprising prediction of late time quantum effects for a flat, homogeneous and isotropic Universe with a scalar field with an exponential potential is obtained by the analysis of the uncertainty dynamics using the results of the corresponding classical dynamical system. Furthermore quantum correction terms to the Hubble parameter and the matter density are derived. A positive matter expectation value for the de-Sitter Universe raises the question if correction terms due to quantum gravity could contribute to solve the dark matter problem.
Toroidal mode trapping in a magnetic meta-molecule
Authors: Wu Tong , Evlyukhin Andrey B , Tuz Vladimir R 
Published: September 2024

Abstract
In this paper, we establish the relationship between the eigenmodes and the scattering characteristics of a meta-molecule made of magnetic disks from the point of view of the manifestation of its toroidal response. In particular, we examine the electric and magnetic dipole contributions to the scattering cross-sections obtained in the framework of the multipole decomposition method while accounting for the polarizability and magnetization induced in the structure by the field of incoming radiation. We find out that with increasing permeability, the toroidal mode is trapped in the meta-molecule due to the presence of its magnetization part, which may have a practical perspective in gyrotropy, permittivity, and permeability sensing.
A collaborative fault diagnosis model based on an attention-weighted multiscale convolutional neural network and an improved multi-grained cascade forest
Authors: Liu Xiuyan , Wang Xiaofeng , Pang Chunqiu , Deng Zhaopeng , Guo Tingting 
Published: September 2024

Abstract
The health of rolling bearings is of great significance to ensure the smooth operation of rotating machinery. Failure of rolling bearings will lead to severe accidents, prolonged downtime or substantial economic losses. Therefore, timely monitoring and diagnosing the health status of rolling bearings is essential to ensure the reliable operation of industrial systems. Deep learning methods have widely applied in industry due to their powerful feature extraction capabilities. However, the fault signals of rolling bearings with complex and variable working conditions exhibit high nonlinearity. To extract the nonlinear features of the fault signal, the traditional deep models often have complex structures and large parameter matrices. It is challenging to train models, obtain high efficiency, and achieve satisfactory results. Therefore, a novel collaborative diagnostic model (MsCNN-IgcForest) based on an attention-weighted multiscale convolutional neural network (MsCNN) and an improved multi-grained cascade forest (IgcForest) is proposed to process bearing fault signals. First, inspired by Xception, we design a lightweight attention-weighted MsCNN feature extraction model that uses attention mechanisms to suppress scattered features and improve the running speed by reducing the number of network training parameters. Second, the improved deep forest employs an attention-weighted MsCNN structure as a classifier instead of multi-grained scanning to reduce memory consumption and achieve fault recognition. Finally, the MsCNN-IgcForest model is verified by two cases of bearing diagnosis and the contrastive results show high fault diagnosis accuracy and strong robustness. In conclusion, the improved model shows good fault diagnosis performance and has a potential reference value for industrial fault diagnosis.
Long-term tracking for high-frequency surface wave radar based on heading constraint filtering combined ELM
Authors: Wang Jiaqi , Liu Aijun , Yu Changjun 
Published: September 2024

Abstract
Aiming at the problem of low measurement resolution and poor tracking accuracy in high-frequency surface wave radar (HFSWR) tracking field, a tracking method that combines the heading constraint filter and extreme learning machine (ELM) is proposed. Compared with the existing research, the innovation of this study lies in proposing a two-stage tracking method based on the short-term stable state of the target, and similarity of long-term trajectory. Firstly, the heading constraint information is introduced into the estimator and improve the estimation accuracy. In multi-target tracking scenarios, many tracklets can be obtained. Then, the ELM learns robust features of tracklets to achieve the trajectory segment classification from the same target. This method can be widely applied to long-term tracking of cargo or passenger ships with fixed destinations, significantly improving tracking performance by utilizing implicit domain knowledge without additional information. The actual data of this paper comes from HFSWR on Bohai Bay. Both the simulation and actual measurement experiments show that the proposed cascaded tracking method achieves long-term continuous tracking, and generates more complete trajectories. Moreover, the proposed Extended Kalman filter based on pseudo-measurement and intercept parameters exhibits better tracking stability and accuracy in limited scan steps. This study provides new ideas and methods for improving the tracking performance of special targets in the HFSWR field by utilizing motion features.