bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence and Risk Factors for Postoperative Pulmonary Complications in Endoscopic Skull Base Surgery
Authors: Abdul-Rahman Nana-Hawwa , Snyderman Carl H. 
Published: February 2025

Abstract
Objective This study aimed to determine the incidence and risk factors for postoperative pulmonary complications (PPCs) following endoscopic endonasal surgery (ESS).
Design Retrospective review from January 2023 to May 2023.
Setting Tertiary academic center.
Participants One hundred EES cases, of which 97 met the inclusion criteria.
Main Outcome Measures The primary outcome was the incidence of PPC. Univariable and multivariable analyses were used to assess preoperative variables, demographics, and respiratory comorbidities; intraoperative variables of surgery and duration of intubation, endotracheal tube (ETT) size, estimated blood loss (EBL), gastric tube use during surgery; postoperative cerebrospinal fluid (CSF) leak, and length of hospital stay as predictors of PPC.
Results Ninety-seven patients met the inclusion criteria. Twenty-nine developed PPC including increased oxygen requirement (14.4%), pneumonia (9.3%), atelectasis (3.1%), respiratory failure (2.1%), and pulmonary embolism (2.1%). Sixty-four percent were clinically significant PPC. PPC was associated with age (p < 0.007), longer duration of surgery (p < 0.001), longer duration of intubation (p < 0.001), postoperative intubation (p < 0.001), higher EBL (p = 0.022), and longer length of hospital stay (p < 0.001). There was no significant association between PPC and sex (p = 0.705), body mass index (BMI; p = 0.403), gastric tube presence (p = 0.778), ETT size (p = 0.636), and preoperative history of pulmonary disease (p = 0.403).
Conclusion The incidence of PPC in patients undergoing EES is significant. Targeting perioperative risk factors including age ≥65, duration of intubation, postsurgical intubation status, and intraoperative blood loss should have a meaningful impact on decreasing PPC. The contribution of silent intraoperative aspiration during surgery needs to be investigated further in high-risk patient populations.
Coagulation Abnormalities in Chronic Liver Disease
Authors: Franchini Massimo , Mannucci Pier Mannuccio 
Published: February 2025

AbstractChronic liver disease is a frequently encountered disorder and a major concern worldwide with a complex pathophysiology, which often affects the hemostatic system. Such alterations, which affect both primary and secondary hemostasis, are heterogenous, including prohemorrhagic (i.e., decreased coagulation factors, increased fibrinolysis, thrombocytopenia, and platelet dysfunction) and prothrombotic (i.e., decreased natural anticoagulants) changes. As a consequence of this unstable balance, patients with liver cirrhosis may experience both hemorrhagic complications and venous thromboembolic events, which are often unpredictable and whose management is particularly challenging for clinicians. This narrative review will address the most recent advances in the pathophysiology of key derangements of hemostasis in patients with chronic liver disease, focusing on their clinical implications and management.
Myofunctional Therapy for the Treatment of Obstructive Sleep Apnea: Systematic Review and Meta-Analysis
Authors: Ferreira Lucas Gabriel dos Anjos , Miranda Vanessa Souza Gigoski de , Baseggio Maria Eduarda Pedroso , Marcolino Miriam Allein Zago , Vidor Deisi Cristina Gollo Marques 
Published: February 2025

Abstract
Introduction Given the severity with which obstructive sleep apnea (OSA) syndrome can affect the patient's health, many therapies have been presented to minimize the occurrence of episodes of airway obstruction during sleep. Regarding non-invasive and effective methods, orofacial myofunctional therapy (OMT) is an important adjuvant in the clinical treatment.
Objective To verify the effectiveness of OMT in the treatment of adult patients affected by OSA.
Data Synthesis A search strategy was developed with terms adapted to the requirements of the main databases in the health field (PubMed, Cochrane, Embase and secondary databases) to designate the adult OSA population and the OMT intervention. The analysis of the records found was performed by two independent examiners and, at the end, we included five randomized clinical trials that presented the outcome of effectiveness of the OMT verified through the apnea-hypopnea index (AHI).
Conclusion The effectiveness of the OMT in the treatment of adult OSA patients was verified, both alone and in association with other interventions, through the reduction in the AHI and the Epworth Sleepiness Scale.
Aplicações do retalho deltopeitoral na reconstrução de grandes defeitos da cabeça e pescoço: Relato de dois casos
Authors: Saint-Clair José Paulo Guedes , Andrade Alberto Figueiredo , Mendes João Luiz Tavares , Borges Marco Aurélio Vieira , Costa Mayra Joan , Francalacci Renata Lowndes 
Published: February 2025

Resumo
Introdução O retalho deltopeitoral foi descrito pela primeira vez por Aymard em 1917 para a reconstrução do nariz. Todavia, recebeu destaque a partir de 1965, quando Bakamjian começou a utilizar o retalho para reconstruções faringoesofágicas.
Métodos Análise retrospectiva de pacientes operados em 2022. Dentre estes, foram selecionados dois pacientes que foram submetidos à reconstrução cervicofacial com retalho deltopeitoral. Os pacientes foram avaliados em relação à idade, sexo, etiologia da lesão, localização do defeito e número de tempos cirúrgicos realizados por paciente. Foram ainda analisados complicações pós-operatórias e satisfação pessoal dos pacientes.
Resultados Os pacientes foram submetidos à reconstrução da região cervicofacial após ressecção tumoral e ambos necessitaram mais de um tempo cirúrgico para refinamento e transecção do pedículo. Um dos pacientes apresentou deiscência de ferida operatória após o reposicionamento do retalho na área doadora, evoluindo com cicatriz hipertrófica e hipocrômica em relação às áreas adjacentes. Nos dois casos descritos em nosso estudo, optou-se pela confecção do retalho deltopeitoral por fornecer um retalho com pele fina, textura e cor semelhantes à região cervicofacial, pedículo constante e previsível, bom alcance aos defeitos, segurança e reprodutividade do retalho, técnica cirúrgica rápida e sem necessidade de mudança de decúbito no intraoperatório.
Conclusões O retalho deltopeitoral permanece como importante opção de tratamento na reconstrução de grandes defeitos da cabeça e pescoço mesmo após o advento da microcirurgia. Permite a transferência de tecido de forma eficiente e confiável com pequena deformidade na área doadora, possibilitando uma reconstrução esteticamente aceitável.
Catch-22 Situation with Unexpected Reports in Acute Lymphoblastic Leukemia.
Authors: Palla Swetha , Gupta Parikshaa , Trehan Amita 
Published: February 2025

AbstractCentral nervous system (CNS) infections are relatively common among children receiving treatment for acute lymphoblastic leukemia (ALL). However, diagnosing these infections presents challenges. In this report, we present a case of asymptomatic adenoviral meningitis, which presented a diagnostic challenge as it mimicked CNS involvement in a child undergoing treatment for ALL. Our findings underscore the importance of thorough diagnostic evaluation for CNS infections in children undergoing ALL therapy, whether they present with symptoms or exhibit asymptomatic cerebrospinal fluid pleocytosis. Furthermore, distinguishing between infections and CNS leukemia is critical, highlighting the necessity of employing flow cytometry to mitigate the potential misinterpretation of morphological features.
Examining students’ understanding of burglary behaviour: a virtual reality, mixed methods approach
Authors: Lunt Robyn , Talbot Matthew 
Published: February 2025

Abstract
Research has highlighted gaps in the publics ‘awareness of burglar behaviour and their perceptions of vulnerability, perhaps indicating a need for further prevention training. No such research exists examining students’ awareness, but is vital given students’ relatively high levels of burglary victimisation. To provide this research, students were asked to complete a mock burglary in a simulated environment, with burglary awareness inferred based on their performance relative to previous experienced burglars. Further context was added by qualitatively analysing participants’ verbalisations during the task. Performance was also compared between first and third year undergraduates to further examine differences in awareness across student populations. No significant differences were found between the behaviour of first and third years. Nevertheless, both groups showed an overall limited understanding of burglary behaviour through their performance and verbalisations. Results demonstrate that raising awareness of victimisation and burglary behaviour is integral to improve the safety of University students.
High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo
Authors: Goswami Shubhang , Jensen Scott , Yang Yubo , Holzmann Markus , Pierleoni Carlo , Ceperley David M. 
Published: February 2025

We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate total energies in the training. We integrate a two phase method for estimating the melting temperature with estimates from the Clausius–Clapeyron relation to provide a more accurate melting curve from the model. We make detailed predictions of the melting temperature, solid and liquid volumes, latent heat, and internal energy from 50 to 180 GPa for both classical hydrogen and quantum hydrogen. At pressures of roughly 173 GPa and 1635 K, we observe molecular dissociation in the liquid phase. We compare with previous simulations and experimental measurements.
Zoo Tourism – A Typical Part of Central-European Travelling: An Example from Czechia
Authors: Nekolný Lukáš 
Published: February 2025

Summary
Zoos are among the most visited tourist and leisure destinations. Moreover, for post-socialist Central and Eastern Europe, visits to zoos are typical. Unlike Western “capitalist” Europe, in post-socialist Europe there were for a long time almost no amusement parks and thanks to this zoos have been long-term key places of (urban) recreation. Due to the different historical developments, the zoos of Central and Eastern Europe differ in terms of time of establishment, location, and ownership compared to those in the west. The collapse of the socialist establishment had a fundamental impact on the future of zoos. After the fall of the Iron Curtain, there was a sharp drop in zoo attendance in the countries of today’s post-socialist Europe, but since the mid-1990s after large innovations, it has been rising again, reaching record highs. The period after 1990 allowed private ownership and brought about the development of private zoos and further expanded forms of zoo tourism.

Information
© The Author 2025
Gravitational wave signal prediction technique based on advanced seasonal-trend decomposition using Loess
Authors: Jia Dongbao , Ma Rui , Xu Weixiang , Zhao Shiwei , Ruan Wenjun , Xu Zhongxun 
Published: February 2025

Abstract
Gravitational wave (GW) analysis is attracting widespread attention as an emerging research field. As the presence of substantial noise in GW signals, and the characteristics of inspiral and merger stage are different, coupled with the sidelobe effect caused by window length, traditional time–frequency analysis methods face significant challenges in accurately analyzing the frequency variations of GW signals. This poses a major limitation in the precise analysis stage following GW detection. Therefore, we proposed a novel method of seasonal-trend decomposition using Loess with multilayer perceptron (STLMLP), for predicting and validating the accuracy and effectiveness of GW frequency variations. Experiment results on three noiseless GW templates demonstrate that STLMLP exhibits the adaptability and highest prediction accuracy for the dynamic frequency variations of GW signals compared to five state-of-the-art machine learning and deep learning methods. Furthermore, experiments conducted on three noisy actual GW data compared with the state-of-the-art method of Fourier-based synchrosqueezing transform in the signal processing domain confirm that STLMLP maintains lower error in predicting frequency change over the whole duration of the actual noisy GW signals.
Constructing topological insulator-ferromagnet heterojunctions of Bi2Se3/Fe3GeTe2 and Bi2Te3/Fe3GaTe2
Authors: Liang Xinke , Chen Fuhong , Yang Liu , Yang Tingting , Xiao Peiyao , Liu Yuxiang , Wang Zhiwei , Xiao Wende 
Published: February 2025

Abstract
Heterostructures composed of topological insulators and ferromagnets are predicted to exhibit the quantum anomalous Hall effect (QAHE). The morphology and interfacial structure have a significant impact on physical properties and transport performances of such heterostructures. Here, we report the epitaxial growth of topological insulators Bi2Se3 and Bi2Te3 thin films on ferromagnetic substrates of Fe3GeTe2 and Fe3GaTe2, respectively. The morphology and composition of the Bi2Se3 and Bi2Te3 thin films were characterized using atomic force microscopy, x-ray photoelectron spectroscopy and Raman spectroscopy. After optimizing growth parameters, we successfully generated large-area films with high crystallinity, presenting new types of topological insulator-ferromagnet heterojunctions for the pursuit of QAHE.
Graphene-based materials and electrochemical biosensors: an overview
Authors: Joshi Rita , Ravindran K Veena , Lahiri Indranil 
Published: February 2025

Abstract
Graphene, an exceptional two-dimensional material, has attracted significant attention from the scientific community. Its unique physiochemical properties make it a suitable candidate for many applications in the field of biotechnology and medical sciences. High specific surface area, exceptionally high electrical conductivity, and good biocompatibility of graphene give it a large scope in disease diagnosis and biosensing applications. This review aims at presenting the advances in the journey of graphene-based materials and their successful implication as electrochemical nanobiosensors. The first part of the review summarizes the history, structure, and recent developments in the large-scale production of graphene. It further includes the sensing mechanism, the recent trends in biosensing, and improvements in graphene-based biosensors. The comparative analysis shows graphene-based electrochemical biosensors to have high sensitivity, long-term stability, and low detection limits compared to the various other biosensors.
The needle assembly mixed anomaly ray image detection method for needle roller bearings based on double threshold segmentation
Authors: Yang Yun , Liang ZhenYu 
Published: February 2025

Abstract
Needle roller bearings without cages are extensively utilized in the mechanical transmission systems of various equipment due to their high load-carrying capacity and compact design. However, due to the limited performance of the current needle loading equipment, abnormalities such as missing needles, skewed needles and toppling needles. If abnormal bearings are installed in the equipment above, it will make the equipment appear noisy, vibration is obvious, the smoothness of operation is reduced. To address this issue, this paper proposes a systematic detection method based on double-threshold segmentation for identifying mixed needle assembly anomalies. Initially, starting from the principles of ray detection, we analyze the characteristics of ray imaging for different needle assembly anomalies in needle roller bearings. Image samples of single and mixed needle assembly anomalies are collected using a ray detection platform. Subsequently, a dual-threshold segmentation method is introduced for mixed needle assembly abnormality images by combining different regions of the needle-bearing ray image and the grey value characteristics of the anomalies for threshold selection. A step-by-step detection method based on dual-threshold segmentation is then proposed. This method utilizes a mask to extract the non-needle assembly region in the high-threshold segmented image, achieving identification and quantification of skewed and toppling needles based on area threshold information of the abnormal needle roller contour. Additionally, a ring mask is employed to extract the needle roller gap in the low-threshold segmented image, allowing for the screening of the needle gap contour based on the area threshold, thus identifying and quantifying missing needle anomalies. Finally, experimental verification is conducted on various needle assembly anomaly images, demonstrating that the proposed method can effectively identify and quantify different needle assembly anomalies in needle roller bearings, offering valuable application insights for quality inspection during needle assembly processes.
A robust navigation algorithm without GNSS based on deep learning and variational Bayesian filter
Authors: Guo Yusheng , Sun Yihong , Zhuang Guangchen , Zhou Ding 
Published: February 2025

Abstract
Integrated navigation systems, combining inertial navigation system (INS) and global navigation satellite system (GNSS), are extensively used in land vehicle navigation. However, they often exhibit poor performance during GNSS outages and lack robustness in challenging urban environments. In order to reduce reliance on GNSS and fully leverage the vehicle dynamics hidden in the data, this study proposes a novel robust navigation algorithm without GNSS, based on deep learning and variational Bayesian methods. Firstly, a cascaded long and short term memory (LSTM) model with an ‘attitude-velocity’ two-step sequential structure is proposed. By incorporating quaternions, it overcomes the non-differentiable property of attitude caused by its bounded nature, resulting in more accurate attitude predictions. Subsequently, the attitude prediction results are utilized to enhance speed prediction, leading to a significant improvement in accuracy. Building upon the cascaded LSTM model, variational Bayesian filtering is employed to further address the complex time-varying error of its results. Through an adaptive data fusion of LSTM predictions and INS data, the data fluctuations are reduced, and the accuracy is significantly improved. The efficacy of the proposed robust navigation algorithm is validated through multiple vehicle experiments conducted on diverse paths. Experimental results demonstrate that even in scenarios where GNSS fails continuously for 15 min, the proposed algorithm maintains of speed and horizontal attitude errors within 0.6 m s−1 (root mean squared error (RMSE)) and 0.3° (RMSE) respectively. Consequently, the proposed algorithm has broad application prospects in GNSS-denied environments such as building occlusion, underground parking garages, and indoor positioning. In addition, we also provide attempts to improve the model for situations such as odometer assistance and different motion states.
CycleH-CUT: an unsupervised medical image translation method based on cycle consistency and hybrid contrastive learning
Authors: Jiang Weiwei , Qin Yingyu , Wang Xiaoyan , Chen Qiuju , Guan Qiu , Lu Minhua 
Published: February 2025

Abstract
Unsupervised medical image translation tasks are challenging due to the difficulty of obtaining perfectly paired medical images. CycleGAN-based methods have proven effective in unpaired medical image translation. However, these methods can produce artifacts in the generated medical images. To address this issue, we propose an unsupervised network based on cycle consistency and hybrid contrastive unpaired translation (CycleH-CUT). CycleH-CUT consists of two CUT (H-CUT) networks. In the H-CUT network, a query-selected attention mechanism is adopted to select queries with important features. The boosted contrastive learning loss is employed to reweight all negative patches via the optimal transport strategy. We further apply spectral normalization to improve training stability, allowing the generator to extract complex features. On the basis of the H-CUT network, a new CycleH-CUT framework is proposed to integrate contrastive learning and cycle consistency. Two H-CUT networks are used to reconstruct the generated images back to the source domain, facilitating effective translation between unpaired medical images. We conduct extensive experiments on three public datasets (BraTS, OASIS3, and IXI) and a private Spinal Column dataset to demonstrate the effectiveness of CycleH-CUT and H-CUT. Specifically, CycleH-CUT achieves an average SSIM of 0.926 in the BraTS dataset, an average SSIM of 0.796 on the OASIS3 dataset, an average SSIM of 0.932 on the IXI dataset, and an average SSIM of 0.890 on the private Spinal Column dataset.
High-performance KNN-based piezoelectric ceramics for buzzer application
Authors: Xiong Cheng , Li Bosen , Liao Zhongxin , Qiu Yan , Gao Daqiang 
Published: February 2025

Abstract
Piezoelectric ceramic material is an important component of piezoelectric buzzer, where the parameter of inverse piezoelectric coefficient (d
33
*) plays the decisive role in the performance of the buzzer. Here, we reported the manufacture and performance of lead-free ceramics (0.96(K0.5Na0.5)(Nb0.96Sb0.04)O3-0.04(Bi0.5Na0.5)ZrO3-1mol% Al2O3, abbreviated as KNNS-BNZ-1mol% Al2O3) based piezoelectric buzzer, compared with commercial (PbZr0.5Ti0.5O3, abbreviated as PZT) ceramics. Briefly, KNN-based ceramics had a typical perovskite structure and revealed the piezoelectric properties of d
33=480 pC/N, k
p =0.62 and d
33
*=830 pm/V, compared to d
33=500 pC/N, k
p=0.6 and d
33
*=918 pm/V of the commercial PZT-4 ceramics. Our results showed that the KNNS-BNZ-1% Al2O3 ceramics had a similar sound pressure level (SPL) performance over the testing frequency range with commercial PZT ceramics (even better in range of 3-4 kHz). These findings open vast possibilities toward the great application potential of the KNN-based piezoelectric ceramics.
Automated DC voltage and DC resistance real-time multiple standard for artifact calibration of calibrators and multimeters
Authors: Galliana F. , Capra P. , Cerri R. , Francese C. , Lanzillotti M. , Roncaglione Tet L. , Pennecchi F. , Pollarolo A. 
Published: February 2025

Abstract
An automated temperature-controlled electrical DC voltage
and DC resistance multiple reference standard (MRS) has been
developed by Measurements International (MI) with the scientific
support from the Istituto Nazionale di Ricerca Metrologica
(INRIM). The MRS includes a 10 V, a 1 Ω, and a
10 kΩ standards selectable via a switch unit. This setup
allows the artifact calibration of high-end calibrators and
multimeters used in low-frequency electrical measurements. The two
resistors are high-stability standards from MI, while the 10 V
standard is based on a low-noise circuit developed by INRIM in
collaboration with MI. A key innovation is the internal real-time
clock calendar, which displays the calibration values of the MRS
standards and their updated values internally calculated. This
ensures reliable use of the MRS standards over extended periods
between calibrations, effectively minimizing uncertainties due to
their drift. The standards are housed in a thermal box, minimizing
temperature variations. The MRS standards meet the uncertainty
requirements defined by calibrators and multimeters manufacturers
for artifact calibration and can also serve as laboratory references
or travelling standards for interlaboratory comparisons (ILCs). MI
is currently commercializing the MRS.