bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new method of ventilation inhomogeneity assessment based on a simulation study using clinical data on congenital diaphragmatic hernia cases
Authors: Stankiewicz Barbara , Mierzewska-Schmidt Magdalena , Pałko Krzysztof Jakub , Baranowski Artur , Darowski Marek , Kozarski Maciej 
Published: December 2022

AbstractCongenital Diaphragmatic Hernia (CDH) is a diaphragm defect associated with lung hypoplasia and ventilation inhomogeneity (VI). The affected neonates are usually born with respiratory failure and require mechanical ventilation after birth. However, significant interindividual VI differences make ventilation difficult. So far, there are no clinical methods of VI assessment that could be applied to optimize ventilation at the bedside. A new VI index is a ratio of time constants T1/T2 of gas flows in both lungs. Pressure-controlled ventilation simulations were conducted using an infant hybrid (numerical-physical) respiratory simulator connected to a ventilator. The parameters of the respiratory system model and ventilator settings were based on retrospective clinical data taken from three neonates (2, 2.6, 3.6 kg) treated in the Paediatric Teaching Clinical Hospital of the Medical University of Warsaw. We searched for relationships between respiratory system impedance (Z) and ventilation parameters: work of breathing (WOB), peak inspiratory pressure (PIP), and mean airway pressure (MAP). The study showed the increased VI described by the T1/T2 index value highly correlated with elevated Z, WOB, PIP and MAP (0.8–0.9, the Spearman correlation coefficients were significant at P < 0.001). It indicates that the T1/T2 index may help to improve the ventilation therapy of CDH neonates.
Single-cell resolved ploidy and chromosomal aberrations in nonalcoholic steatohepatitis-(NASH) induced hepatocellular carcinoma and its precursor lesions
Authors: Friemel Juliane , Torres Irianna , Brauneis Elizabeth , Thörner Tim , Schäffer Alejandro A. , Gertz E. Michael , Grob Tobias , Seidl Kati , Weber Achim , Ried Thomas , Heselmeyer-Haddad Kerstin 
Published: December 2022

AbstractNonalcoholic steatohepatitis (NASH)-induced hepatocellular carcinoma (HCC) and its precursor, nonalcoholic fatty liver disease (NAFLD) are an unmet health issue due to widespread obesity. We assessed copy number changes of genes associated with hepatocarcinogenesis and oxidative pathways at a single-cell level. Eleven patients with NASH-HCC and 11 patients with NAFLD were included. Eight probes were analyzed using multiplex interphase fluorescence in situ hybridization (miFISH), single-cell imaging and phylogenetic tree modelling: Telomerase reverse transcriptase (TERT), C-Myc (MYC), hepatocyte growth factor receptor tyrosine kinase (MET), tumor protein 53 (TP53), cyclin D1 (CCND1), human epidermal growth factor receptor 2 (HER2), the fragile histidine triad gene (FHIT) and FRA16D oxidoreductase (WWOX). Each NASH-HCC tumor had up to 14 distinct clonal signal patterns indicating multiclonality, which correlated with high tumor grade. Changes frequently observed were TP53 losses, 45%; MYC gains, 36%; WWOX losses, 36%; and HER2 gains, 18%. Whole-genome duplications were frequent (82%) with aberrant tetraploid cells evolving from diploid ancestors. Non-tumorous NAFLD/NASH biopsies did not harbor clonal copy number changes. Fine mapping of NASH-HCC using single-cell multiplex FISH shows that branched tumor evolution involves genome duplication and that multiclonality increases with tumor grade. The loss of oxidoreductase WWOX and HER2 gains could be potentially associated with NASH-induced hepatocellular carcinoma.
Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes
Authors: Libiseller-Egger Julian , Phelan Jody E. , Attia Zachi I. , Benavente Ernest Diez , Campino Susana , Friedman Paul A. , Lopez-Jimenez Francisco , Leon David A. , Clark Taane G. 
Published: December 2022

AbstractArtificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age (“delta age”) to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ($$p\le 5 \times 10^{-8}$$

p
≤
5
×

10

-
8

), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.
The severe impact of the COVID-19 pandemic on bullying victimization, mental health indicators and quality of life
Authors: Forsberg June T. , Thorvaldsen Steinar 
Published: December 2022

AbstractChildren and adolescents have been severely affected by the COVID-19 pandemic. The aim of this study was to explore the prevalence of traditional and digital bullying and mental health problems a year into the pandemic. Further, how anxiety level, loneliness, and self-perceived school functioning have influenced the quality of life. A comprehensive questionnaire was administered (N = 1239) in the city of Tromsø and compared to a similar data collection (N = 972) conducted in the same schools in 2017. The main findings were increased prevalence in bullying, more mental health problems and significantly reduced quality of life compared to before the pandemic. Implications and the importance of implementing anti-bullying and psychosocial measures after the pandemic are discussed.
Emergency collision avoidance strategy for autonomous vehicles based on steering and differential braking
Authors: Li Haiqing , Zheng Taixiong , Xia Fuhao , Gao Lina , Ye Qing , Guo Zonghuan 
Published: December 2022

AbstractThis paper develops a novel integrated collision avoidance strategy for autonomous vehicles in an emergency based on steering and braking. Specifically, the framework of the collision avoidance strategy is composed of two parts: an up-level decision-making layer and a low-level controller layer. The purpose of the up-level is to select the appropriate control strategy based on the vehicle information, and the low-level is to drive the vehicle according to the instructions generated by the up-level. More concretely, a novel control strategy is proposed by integrating four-wheel steering, active rear steering, and differential braking with guaranteed path-tracking accuracy and driving stability by adaptive model predictive control (AMPC). Finally, extensive co-simulations in MATLAB/Simulink and CarSim are conducted to verify the effectiveness of the proposed collision avoidance strategy in terms of tracking error, yaw rate, and roll angle.
The prognosis predictive score around primary debulking surgery (PPSP) improves diagnostic efficacy in predicting the prognosis of ovarian cancer
Authors: Kawahara Naoki , Kawaguchi Ryuji , Waki Keita , Maehana Tomoka , Yamanaka Shoichiro , Yamada Yuki , Kimura Fuminori 
Published: December 2022

AbstractIn recent years, the pretreatment inflammatory responses have proven to predict the prognosis, but no report exists analyzing the combined inflammatory response of the pre- and postsurgical treatment. The current study aims to extract the factors predicting the recurrence and create novel predictive scoring. This retrospective study was conducted at our institution between November 2006 and December 2020, with follow-up until September 2022. Demographic and clinicopathological data were collected from women who underwent primary debulking surgery. We created the scoring system named the prognosis predictive score around primary debulking surgery(PPSP) for progression-free survival(PFS). Univariate and multivariate analyses were performed to assess its efficacy in predicting PFS and overall survival(OS). Cox regression analyses were used to assess its time-dependent efficacy. Kaplan–Meier and the log-rank test were used to compare the survival rate. A total of 235 patients were included in the current study. The cut-off value of the scoring system was six. Multivariate analyses revealed that an advanced International Federation of Gynecology and Obstetrics(FIGO) stage (p < 0.001 for PFS; p = 0.038 for OS), the decreased white blood cell count difference (p = 0.026 for PFS) and the high-PPSP (p = 0.004 for PFS; p = 0.002 for OS) were the independent prognostic factors. Cox regression analysis also supported the above results. The PPSP showed good prognostic efficacy not only in predicting the PFS but also OS of ovarian cancer patients comparable to FIGO staging.
Energy efficiency of full‐duplex communication system assisted by reconfigurable intelligent surface
Authors: Wang Yiru , Guan Pengxin , Yu Hongkang , Zhao Yuping 
Published: December 2022

AbstractThe sixth generation advocates green communications, thus energy efficiency (EE) has become an important metric. In this study, a method to increase the EE of a reconfigurable intelligent surface (RIS) aided point‐to‐point communication system is proposed, where both sources are equipped with multi‐antenna and operate in the full‐duplex (FD) mode. The extra power consumption for self‐interference cancellation in the FD mode is considered and modelled as a linear function of the transmission power. The EE maximisation problem is divided into an active beamforming subproblem for the two multi‐antenna sources and a passive beamforming subproblem for RIS, and an alternative optimisation framework is adopted to solve them iteratively. Dinkelbach's method is used to address the fractional objective function in the active beamforming optimisation problem. The penalty method and successive convex approximation are exploited for passive beamforming design. Simulation results show that the scheme can greatly boost the EE performance compared with the half‐duplex mode and is superior to the sum‐rate‐maximisation scheme in larger transmission power settings. The proposed method can be used to extend the lifetime of communication devices without deteriorating communication performance.
Parallel primal‐dual interior point method for the solution of dynamic optimal power flow
Authors: Sundermann Rylee , Abhyankar Shrirang G. , Zhang Hong , Kimn Jung‐Han , Hansen Timothy M. 
Published: December 2022

AbstractThis work presents a novel solution for accelerating the dynamic optimal power flow using a distributed‐memory parallelization approach. Unlike other two‐stage relaxation‐based approaches (such as ADMM), the proposed approach constructs the entire dynamic optimal power flow problem in parallel and solves it using a parallel primal‐dual interior point method with an iterative Krylov subspace linear solver with a block‐Jacobi preconditioning scheme. The parallel primal‐dual interior point method has been implemented in the open‐source portable, extensible toolkit for scientific computation (PETSc) library. The formulation, implementation, and numerical results on multicore computers to demonstrate the performance of the proposed approach on medium‐ to large‐scale networks with varying time horizons are presented. The results show that a significant speedup is achieved by using a block‐Jacobi preconditioner with an iterative Krylov subspace method for solving the dynamic optimal power flow problems.
Fault identification of high voltage circuit breaker trip mechanism based on PSR and SVM
Authors: Ruan Jiangjun , Wang Xuezong , Zhou Taotao , Peng Xuelin , Deng Yongqing , Yang Qiuyu 
Published: December 2022

AbstractThe trip mechanism is a weakness in circuit breakers. Traditional fault identification based on the coil current is difficult to report early mechanical defects such as coil‐plunger jam. Here, the vibration signal during the trip process was extracted. Based on the coil current signal and vibration signal, the characteristics of the trip mechanism are analyzed. The phase space reconstruction (PSR) method is used to extract features from the vibration signal. Combined with the features from the coil current waveform, the feature set representing the health condition of the trip mechanism is proposed. The fault simulation tests are carried out and the variation of current vibration characteristics under fault conditions is studied. The fault identification model based on a support vector machine (SVM) is proposed and compared with the identification results when features are extracted from a single signal. When the power supply voltage is dispersed, the prediction accuracy of fault identification is 83.3% considering only the features of the current waveform or vibration signal. And the identification accuracy rises to 96.7% while using the feature set of current and vibration signals. On basis of the current signal, the method further combines the vibration signal so that the robustness of defect identification improves.
A survey on end‐to‐end point cloud learning
Authors: Tang Xikai , Huang Fangzheng , Li Chao , Ban Dayan 
Published: December 2022

AbstractPoint cloud is an important expression form of three‐dimensional (3D) data. It has enjoyed continuous development and attracted increasing attention due to its wide applications in many areas, such as artificial intelligence, deep learning, autonomous driving and tracking. Recently, there is a large number of end‐to‐end point cloud‐based deep learning methods being proposed which are successful in the 3D domain. In order to better use point cloud data for analysis and to explore future research directions, this paper presents a comprehensive review of existing methods and publicly available datasets, with a focus on the methods and research status of using point cloud data as direct input. The background of point cloud is first introduced, including data acquisition methods, basic concepts, and challenges. Following that, the deep learning methods based on point cloud data are investigated and analysed according to classification, detection and tracking, and segmentation. Furthermore, the existing public datasets and evaluation metrics are introduced. Finally, promising research directions are proposed in conjunction with existing methods.
Robust image compression‐encryption via scrambled block bernoulli sampling with diffusion noise
Authors: Chen Zan , Ma Chaocheng , Wang Tao , Feng Yuanjing , Hou Xingsong , Qian Xueming 
Published: December 2022

AbstractThis paper proposed an image compression‐encryption scheme based on compressive sensing theory, which achieves high security, strong robustness, and high rate‐distortion performance. First, the denoising preprocessing strategy is applied at the encoder side, which can enhance the rate‐distortion performance without sacrificing security and robustness. Second, the preprocessed image is randomly down‐sampled using scrambled block Bernoulli sampling with diffusion noise (SBBS‐DN), which is generated by combining a hyper‐chaotic system and SHA256 hash of the plain image. Third, a deep‐learned plug‐and‐play is embedded prior for plain image reconstruction at the decoder side. Simulation results show that the proposed scheme has desirable security performance (being resistant to different attacks), high R‐D performance (PSNR gains over 1.3 dB than JPEG at 0.50 bpp compression ratio), and high error resilience (reconstructed 29.92 dB at 0.50 bpp compression ratio even with 50% bit loss).
Clinical Outcome of Pedicle-Sparing Transfacet Diskectomy and Fusion with Segmental Instrumentation for Thoracic Disc Herniation
Authors: Eghbal Keyvan , Zafarshamspour Saber , Sookhaklari Mohammadamin , Saffarian Arash , Taheri Reza 
Published: December 2022

Abstract
Background Thoracic disk herniations (TDHs) are relatively rare compared with their cervical and lumbar counterparts. Posterior approaches allow for a simpler and less invasive surgery than anterior and lateral approaches. A pedicle-sparing transfacet approach was initially described in 1995, and modified in 2010. A few clinical series have reported the outcome of this procedure in patients with TDH. This study aimed to evaluate the outcomes and complications of pedicle-sparing transfacet diskectomy with interbody fusion and segmental instrumentation in patients with TDH.
Methods Twenty-one consecutive patients with symptomatic TDH referred to our tertiary care center were included in this retrospective study. All patients underwent a pedicle-sparing transfacet diskectomy with polyetheretherketone (PEEK) cage interbody fusion and short segmental instrumentation. Distribution of TDH, operative duration, blood loss, Visual Analog Scale (VAS) pain scores, Nurick grades, modified Japanese Orthopaedic Association (mJOA) scores, and fusion rate were assessed.
Results All patients had single-level herniations. The most common location was T12–L1 (38.1%), followed by T11–T12 (33.3%). All patients were successfully operated on with no cerebrospinal fluid (CSF) leaks or wrong-level surgery. The VAS scores significantly diminished from 4.9 (preoperatively) to 2 (18 months after surgery). The average mJOA score increased from 4.6 to 8.5, and the average Nurick grade decreased from 3.1 to 1.6. All patients reported significant improvement in quality of life relative to their preoperative status.
Conclusion A modified pedicle-sparing transfacet diskectomy combined with PEEK cage interbody fusion and segmental instrumentation offers a safe and less invasive approach for the treatment of TDHs.
Evidence-Based Medicine for Nonsurgical Facial Rejuvenation
Authors: Hari-Raj Amrita , Spataro Emily A. 
Published: December 2022

AbstractOptions for nonsurgical facial rejuvenation treatment have increased significantly in both availability and popularity over the past two decades. However, there remains a paucity of clinical practice guidelines and evidence-based recommendations for these procedures. The purpose of this article is to assess the presence of current high-level research for various methods of nonsurgical facial rejuvenation using the Oxford Centre for Evidence-Based Medicine. Botulinum toxin injections remain the best-studied method, with several randomized controlled trials guiding recommendations for safety and efficacy. Several studies on injectable fillers document complications and recommendations to avoid these, but sample sizes are small and many are noncomparative. Deoxycholic acid has been well examined and Food and Drug Administration approved to address submental fat but has not been studied in other areas of the face. Although chemical peels, laser skin resurfacing, energy-based facial rejuvenation, microneedling, and platelet-rich plasma have a variety of facial rejuvenation applications with minimal side effect profiles, there is significant variability with treatment protocols, outcomes measures, and randomized controlled trials with extended follow-up to develop clinical practice guidelines.
Hepatic Splenosis: A Rare Entity and Great Mimicker
Authors: KB Shruthi , PK Hanan 
Published: December 2022

AbstractSplenosis is a benign and rare condition that is usually caused by trauma or splenectomy or other procedures involving splenic tissue. The patient is usually asymptomatic and often diagnosed incidentally especially when presents as intrahepatic lesion, can be misdiagnosed as neoplasm. Here, we present case report of a 56-year-old male patient, who was incidentally detected to have focal liver lesion on routine ultrasound check up. He was further evaluated with computed tomography (CT) and magnetic resonance imaging (MRI) and the lesion was indistinguishable from neoplastic lesions and misdiagnosed to be hepatic adenoma. Retrospectively analyzing, the patient had history of splenectomy following road traffic accident 10 years before the present presentation. Following laparotomy, the liver lesion was resected and histopathology confirmed the diagnosis of hepatic splenosis. In this case report and review, we present the diagnostic features and the criteria that help in the diagnosis of splenosis which is a great mimicker.
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets
Authors: Christensen Erik , Luo Ping , Turinsky Andrei , Husić Mia , Mahalanabis Alaina , Naidas Alaine , Diaz-Mejia Juan Javier , Brudno Michael , Pugh Trevor , Ramani Arun , Shooshtari Parisa 
Published: December 2022

AbstractSingle-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated labelling methods rely on either unsupervised, cluster-based approaches or supervised, cell-based approaches to identify cell types. The high complexity of cancer poses a unique challenge, as tumor microenvironments are often composed of diverse cell subpopulations with unique functional effects that may lead to disease progression, metastasis and treatment resistance. Here, we assess 17 cell-based and 9 cluster-based scRNA-seq labelling algorithms using 8 cancer datasets, providing a comprehensive large-scale assessment of such methods in a cancer-specific context. Using several performance metrics, we show that cell-based methods generally achieved higher performance and were faster compared to cluster-based methods. Cluster-based methods more successfully labelled non-malignant cell types, likely because of a lack of gene signatures for relevant malignant cell subpopulations. Larger cell numbers present in some cell types in training data positively impacted prediction scores for cell-based methods. Finally, we examined which methods performed favorably when trained and tested on separate patient cohorts in scenarios similar to clinical applications, and which were able to accurately label particularly small or under-represented cell populations in the given datasets. We conclude that scPred and SVM show the best overall performances with cancer-specific data and provide further suggestions for algorithm selection. Our analysis pipeline for assessing the performance of cell type labelling algorithms is available in https://github.com/shooshtarilab/scRNAseq-Automated-Cell-Type-Labelling.