bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overall survival time prediction for glioblastoma using multimodal deep KNN
Authors: Tang Zhenyu , Cao Hongda , Xu Yuyun , Yang Qing , Wang Jinda , Zhang Han 
Published: May 2022

Abstract
Glioblastoma (GBM) is a severe malignant brain tumor with bad prognosis, and overall survival (OS) time prediction is of great clinical value for customized treatment. Recently, many deep learning (DL) based methods have been proposed, and most of them build deep networks to directly map pre-operative images of patients to the OS time. However, such end-to-end prediction is sensitive to data inconsistency and noise. In this paper, inspired by the fact that clinicians usually evaluate patient prognosis according to previously encountered similar cases, we propose a novel multimodal deep KNN based OS time prediction method. Specifically, instead of the end-to-end prediction, for each input patient, our method first search its K nearest patients with known OS time in a learned metric space, and the final OS time of the input patient is jointly determined by the K nearest patients, which is robust to data inconsistency and noise. Moreover, to take advantage of multiple imaging modalities, a new inter-modality loss is introduced to encourage learning complementary features from different modalities. The in-house single-center dataset containing multimodal MR brain images of 78 GBM patients is used to evaluate our method. In addition, to demonstrate that our method is not limited to GBM, a public multi-center dataset (BRATS2019) containing 211 patients with low and high grade gliomas is also used in our experiment. As benefiting from the deep KNN and the inter-modality loss, our method outperforms all methods under evaluation in both datasets. To the best of our knowledge, this is the first work, which predicts the OS time of GBM patients in the strategy of KNN under the DL framework.
Control of ion flux-energy distributions by low frequency square-shaped tailored voltage waveforms in capacitively coupled plasmas
Authors: Hartmann P , Korolov I , Escandón-López J , van Gennip W , Buskes K , Schulze J 
Published: May 2022

Abstract
Capacitively coupled plasmas are routinely used in an increasing number of technological applications, where a precise control of the quantity and the shape of the energy distribution of ion fluxes impacting boundary surfaces is required. Oftentimes, narrow peaks at controllable energies are required, e.g. to improve selectivity in plasma etching, which cannot be realized in classical discharges. We combine experimental ion flux-energy distribution measurements and PIC/MCC simulations to provide insights into the operation and ion acceleration mechanisms for discharges driven by square-shaped tailored voltage waveforms composed of low-frequency (100 kHz) pulsed and high-frequency (27.12 MHz) signals. The formation of ion flux-energy distributions with a narrow high energy peak and strongly reduced ion fluxes at intermediate energies is observed. The position of the high energy peak on the energy axis can be controlled by adjusting the low-frequency voltage pulse magnitude and duty cycle. The effects of tailoring the driving voltage waveform by adjusting these control parameters as well as its repetition rate on the plasma operation and the ion flux-energy distribution are analysed in depth. We find, e.g. that the duty cycle regime (

<
40

% or

>
60

%) determines if the high energy ions form at the grounded or the powered electrode and that the duration of the pulse must exceed the ion energy relaxation time, on the order of 0.5 μs.
Decade of bio-inspired soft robots: a review
Authors: Ahmed Faheem , Waqas Muhammad , Jawed Bushra , Soomro Afaque Manzoor , Kumar Suresh , Hina Ashraf , Khan Umair , Kim Kyung Hwan , Choi Kyung Hyun 
Published: May 2022

Abstract
Soft robotics is an emerging field of robotics that focuses on the design of soft machines and devices with effective human-machine interaction, high conformity, and environmental adaptability. The conventional robots made of hard materials have already achieved precision and accuracy, but they lack in reachability, adaptability, degree of freedom, and safe interaction. Moreover, soft robots mimic the behavior of biological creatures by mimicking their locomotive patterns. The actuation or the locomotion of the soft robots is achieved by soft actuators which are a very important part of soft robotic systems. Herein, a comprehensive review based on the evolution of six actuation methodologies is presented. Various approaches used for the design and fabrication of soft robots such as pneumatic, shape memory alloy, dielectric elastomers, chemical-reaction enforced, and pneumatic and magneto-rheological elastomers-based actuation methods reported in the last decade. Furthermore, the advancement of these approaches has been rigorously discussed in chronological order for parameters like efficiency, power requirement, frequency, and possible applications. Future challenges and directions toward the advancement in soft robotics are also discussed for achieving the remarkable performance of soft robots in a real-time environment. Furthermore, we believe, this is a complete review package for the young researchers which can help them to understand, how this field has evolved from a performance, application, and efficiency point of view.
Synergic realization of electrical insulation and mechanical strength in liquid nitrogen for high-temperature superconducting tapes with ultra-thin acrylic resin coating
Authors: Guo Chunjiang , Zhang Zhiwei , Wu Yue , Wang Yawei , Ma Guangtong , Shi Jiangtao , Zhong Zhuoyan , Hong Zhiyong , Jin Zhijian , Zhao Yue 
Published: May 2022

Abstract
Insulation coating is a sought after technique for REBa2Cu3O6+x
(REBCO) based high temperature superconducting tapes in practical applications. In this work, we developed a novel technique for preparing ultra-thin and fully surrounded insulation coatings on REBCO tapes. This technique completely eliminates the risk of critical current degradation in REBCO tapes induced by high temperature curing, without sacrificing the mechanical performance and the engineering current density. We adopted CRC-PLASTICOTE-70 as insulation precursor and verified its performance as insulation coating at 77 K. Thickness effect of the insulation coating in liquid nitrogen was investigated in details. Ultra-thin coating (below 5 μm) on REBCO tapes exhibited excellent strength during thermal shock test, while good adhesion of classification 1 was achieved (according to ISO2409-1992). A charge–discharge test was carried out on a test coil wound from as-coated tapes to assess the turn-to-turn insulation performance. The results show that a high turn-to-turn resistivity of 1060 μΩ cm2 is achieved by the insulation coating, which is about two orders of magnitude higher than that of its un-coated counterpart, indicating excellent insulation properties. This work provides a new idea for the development of novel insulation technology for REBCO tapes in practical applications.
Parametrized post-Newtonian formalism in higher-order Teleparallel Gravity
Authors: Gonzalez-Espinoza Manuel , Otalora Giovanni , Kraiselburd Lucila , Landau Susana 
Published: May 2022

Abstract
We study the parametrized post-Newtonian (PPN) limit of higher-derivative-torsion Modified Teleparallel Gravity. We start from the covariant formulation of modified Teleparallel Gravity by restoring the spin connection of the theory. Then, we perform the post-Newtonian expansion of the tetrad field around the Minkowski background and find the perturbed field equations. We compute the PPN metric for the higher-order Teleparallel Gravity theories which allows us to show that at the post-Newtonian limit this more general class of theories are fully conservative and indistinguishable from General Relativity . In this way, we extend the results that were already found for F(T) gravity in previous works. Furthermore, our calculations reveal the importance of considering a second post-Newtonian (2PN) order approximation or a parametrized post-Newtonian cosmology (PPNC) framework where additional perturbative modes coming from general modifications of Teleparallel Gravity could lead to new observable imprints.
Shadow thermodynamics of an AdS black hole in regular spacetime *
Authors: Guo Sen , Li Guan-Ru , Li Guo-Ping 
Published: May 2022

Abstract
The dependence of the black hole (BH) shadow and thermodynamics may be structured in regular spacetime. Taking a regular Bardeen-AdS BH as an example, the relationship between the shadow radius and event horizon radius is derived. It is found that these two radii display a positive correlation, implying that the BH temperature can be rewritten as a function of shadow radius in regular spacetime. By analyzing the phase transition curves under the shadow context, we find that the shadow radius can replace the event horizon radius to present the BH phase transition process, and the phase transition grade can also be revealed by the shadow radius, indicating that the shadow radius may serve as a probe for phase structure in regular spacetime. Utilizing the temperature-shadow radius function, the thermal profile of the Bardeen-AdS BH is established. Moreover, the temperature exhibits an N-type change trend in the

situation. These results suggest that the phase transition process of a regular AdS BH can be completely presented in the thermal profile, and the relationship between the BH shadow and thermodynamics can also be established in regular spacetime.
Aeroacoustic source prediction using material surfaces bounding the flow
Authors: McPhail M J , Krane M H 
Published: May 2022

Abstract
This article presents an extension of Liepmann’s characterization of an aeroacoustic source in terms of the motion of a bounding surface containing the source region. Rather than using an arbitrary surface, we express the problem in terms of bounding material surfaces, identified by Lagrangian coherent structures (LCSs), which demarcate flow into regions with distinct dynamics. The sound generation of the flow is written in terms of the motion of these material surfaces using the Kirchhoff integral equation, so that the flow noise problem now appears like that of a deforming body. This approach provides a natural connection between the flow topology, as revealed through LCS analysis, and sound generation mechanisms. As examples, we examine two-dimensional cases of co-rotating vortices and leap-frogging vortex pairs and compare estimated sound sources to vortex sound theory.
Vortex technique to track 3D object displacement in CGH
Authors: Villamizar Amado Astrid Lorena , Velez-Zea Alejandro , Tebaldi Myrian 
Published: May 2022

Abstract
In this work, we introduce and test a technique to track the movement of objects from computer-generated holographic videos, without the need for reconstruction. To achieve this, we first generated holographic videos of moving 3D objects using a random phase layer-based approach. Then, we analyzed the hologram phase to determine the locations of the optical vortices. We used the core properties of each vortex to track its movement over all the frames of the video, and then establish a relationship between the object and the vortex movement. We also tested the vortex tracking over a pseudo-phase obtained by performing the Laguerre–Gauss transform of the hologram, which enables more precise control over the number of optical vortices that can be tracked. Our proposal was tested with holographic videos generated with one and two objects, using two different hologram generation approaches.
Do marginal plant populations enhance the fitness of larger core units under ongoing climate change? Empirical insights from a rare carnation
Authors: Gargano Domenico , Bernardo Liliana , Rovito Simone , Passalacqua Nicodemo G , Abeli Thomas 
Published: May 2022

AbstractAssisted gene flow (AGF) can restore fitness in small plant populations. Due to climate change, current fitness patterns could vary in the future ecological scenario, as highly performant lineages can undergo maladaptation under the new climatic contexts. Peripheral populations have been argued to represent a potential source of species adaptation against climate change, but experimental evidence is poor. This paper considers the consequences of within- and between-population mating between a large core population and the southernmost population, the rare Dianthus guliae, to evaluate optimal AGF design under current and future conditions. We performed experimental self-pollinations and within- and between-population cross-pollinations to generate seed material and test its adaptive value to aridity. Seed germination, seedling growth and survival were measured under current and expected aridity. Effects of population type, pollination treatment and stress treatment on fitness components were analysed by generalized linear models. Relative measures of inbreeding depression and heterosis were taken under different stress treatments. Self-pollination reduced fitness for all the considered traits compared to within- and between-population cross-pollination. Under current aridity regime, the core population expressed higher fitness, and a larger magnitude of inbreeding depression. This indicated the core unit is close to its fitness optimum and could allow for restoring the fitness of the small peripheral population. Contrarily, under increased aridity, the fitness of outbred core lineages decreased, suggesting the rise of maladaptation. In this scenario, AGF from the small peripheral population enhanced the fitness of the core unit, whereas AGF from the core population promoted a fitness loss in the peripheral population. Hence, the small peripheral population could improve fitness of large core units versus climate change, while the contrary could be not true. Integrating reciprocal breeding programmes and fitness analyses under current and predicted ecological conditions can support optimal AGF design in a long-term perspective.
OMEN: network-based driver gene identification using mutual exclusivity
Authors: Van Daele Dries , Weytjens Bram , De Raedt Luc , Marchal Kathleen 
Published: May 2022

AbstractMotivationNetwork-based driver identification methods that can exploit mutual exclusivity typically fail to detect rare drivers because of their statistical rigor. Propagation-based methods in contrast allow recovering rare driver genes, but the interplay between network topology and high-scoring nodes often results in spurious predictions. The specificity of driver gene detection can be improved by taking into account both gene-specific and gene-set properties. Combining these requires a formalism that can adjust gene-set properties depending on the exact network context within which a gene is analyzed.ResultsWe developed OMEN: a logic programming framework based on random walk semantics. OMEN presents a number of novel concepts. In particular, its design is unique in that it presents an effective approach to combine both gene-specific driver properties and gene-set properties, and includes a novel method to avoid restrictive, a priori filtering of genes by exploiting the gene-set property of mutual exclusivity, expressed in terms of the functional impact scores of mutations, rather than in terms of simple binary mutation calls. Applying OMEN to a benchmark dataset derived from TCGA illustrates how OMEN is able to robustly identify driver genes and modules of driver genes as proxies of driver pathways.Availability and implementationThe source code is freely available for download at www.github.com/DriesVanDaele/OMEN. The dataset is archived at https://doi.org/10.5281/zenodo.6419097 and the code at https://doi.org/10.5281/zenodo.6419764.Supplementary informationSupplementary data are available at Bioinformatics online.
Genomic sequences and RNA-binding proteins predict RNA splicing efficiency in various single-cell contexts
Authors: Hou Ruiyan , Huang Yuanghua 
Published: May 2022

AbstractMotivationThe RNA splicing efficiency is of high interest for both understanding the regulatory machinery of gene expression and estimating the RNA velocity in single cells. However, its genomic regulation and stochasticity across contexts remain poorly understood.ResultsHere, by leveraging the recent RNA velocity tool, we estimated the relative splicing efficiency across a variety of single-cell RNA-Seq data sets. We further extracted large sets of genomic features and 120 RNA-binding protein features and found they are highly predictive to relative RNA splicing efficiency across multiple tissues and organs on human and mouse. This predictive power brings promise to reveal the complexity of RNA processing and to enhance the analysis of single-cell transcription activities.Availability and implementationIn order to ensure reproducibility, all preprocessed datasets and scripts used for the prediction and figure generation are publicly available at https://doi.org/10.5281/zenodo.6513669.Supplementary informationSupplementary data are available at Bioinformatics online.
Public Responsiveness to Declining Crime Rates in the United States and England and Wales
Authors: Enns Peter K , Harris Jacob , Kenny John , Roescu Andra , Jennings Will 
Published: May 2022

Abstract
During much of the second half of the twentieth century, public opinion in both the United States and Britain became more punitive as crime rates rose. These shifting public attitudes had a profound influence on criminal justice policies. What is less understood is how public attitudes in these countries have responded to declining crime rates since the early-1990s. To understand how the public reacts to declining crime rates, we focus on crimes recorded by the police as well as data on actual victimisation. We also draw on more than 4,000 national survey questions to construct measures of public concern about crime and support for punitive criminal justice responses. Our analyses illustrate parallels in the crime drop measured by victimisation surveys in the two countries (with recorded violent crime in England and Wales the exception to this overall trend). The over-time patterns in public concern about crime and punitive sentiment are more complex, with the US public becoming less punitive (in line with declining crime rates) while the British public’s concern with crime appears more in tune with actual crime rates. Given the distinct social, political and institutional settings offered by the two countries, the parallel dynamics of crime and the mixed response of public opinion help illustrate the importance of the comparative analysis of crime and its effects on society as well as the importance of considering multiple measures of public opinion related to crime and punishment.
Crime And Punishment: Public Opinion And Political Law-And-Order Rhetoric In Europe 1996–2019
Authors: Karstedt Susanne , Endtricht Rebecca 
Published: May 2022

AbstractThis article explores in which ways politicians’ law-and-order rhetoric and citizens’ attitudes and concerns about crime engage with each other in European countries. The focus is on the ‘constructionist’ or ‘framing’ model which posits that citizens’ attitudes about crime and punishment are influenced and ‘framed’ by political rhetoric. We capture the overall ‘tone’ of political rhetoric around crime and criminal justice using law-and-order statements in political party manifestos. Our indicators of crime concerns and punitive sentiment among the public are ‘crime salience’ (crime as the most important problem) and punitive preferences. We link law-and-order statements with survey data from the Eurobarometer and European Social Survey to explore the relationship between citizens and political elites for 26 European countries between 1996 and 2019. In line with previous research, we show that political law-and-order rhetoric indeed provides a framing narrative for citizens but limited to their punitive preferences. In contrast, European citizens’ assessment of crime as a problem is shaped by the level of serious violent crime (homicide) in their country during this period. This suggests a risk-based assessment and an ‘objectivist’ model. We discuss these results in the context of differences between the politization of criminal law in Europe and the United States.
Detection of 94 PDE-5is and Their Analogs Including N-Desmethylthiosildenafil in Various Formulations of Dietary Supplements and Food Samples Using HPLC and LC-Q-TOF/MS
Authors: Lee Ji Hyun , Park Ok Rim , Yang Yoon Ji , Han Ji Hye , Jung Eun Ju , Kim Nam Sook , Baek Sun Young 
Published: May 2022

Abstract
Consumption of foods and dietary supplements (DS) adulterated with unprescribed or non-permitted phosphodiesterase-5 inhibitors (PDE-5i) and their analogs can cause serious risk to human health. This study aims to analyze 93 PDE-5i and their analogs present in adulterated foods and DS using an established and validated method involving high-performance liquid chromatography (HPLC). The method was validated in solid and liquid samples, resulting in a limit of detection and quantitation of 0.03–0.5 and 0.08–1.6 μg/mL, respectively. Using the validated method, a total of 404 samples were screened. It was found that 32% of 404 samples were illegally adulterated with PDE-5i and their analogs; moreover, 16.9% of the adulterated samples were found to contain more than three compounds. HPLC-quadrupole-time-of-flight (TOF)/mass spectrometry (MS) analysis was conducted on all the samples to confirm the detected compounds accurately based on fragmentation ion patterns. In addition, sildenafil and tadalafil were detected from the capsule shells of DS unusually. Subsequently, the detected compounds were identified and quantified using HPLC at concentrations ranging from 0.007 to 370.0 mg/g. NMR analysis was carried out to confirm the accurate chemical structure of a compound found during the TOF/MS analysis, which did not match with the 93 reference standards.; it was identified to be N-desmethylthiosildenafil. In this study, various PDE-5i compounds and their analogs were detected from low to high concentrations in a sample. Therefore, the study sheds light on the misuse of PDE-5i and their analogs in consumable products, which pose a severe threat to public health.
Analysis of Fixed-Dose Combination of Three Antihypertensive Drugs by a Green and Quality by Design Approach
Authors: Mandić-Kovačević Nebojša , Kasagić-Vujanović Irena , Popović Bijelić Ana 
Published: May 2022

AbstractThis paper presents the result of a combined employment of Analytical Quality-by-Design and Green Analytical Chemistry principles for the development of a robust high-performance liquid chromatography method for simultaneous determination of fixed-dose combination of three drugs, perindopril tert-butylamine, amlodipine besylate and indapamide. Optimum conditions were achieved on ZORBAX Eclipse XDB-C18 column (150 mm × 4.6 mm, 5 μm particle size), the mobile phase comprising acetonitrile and phosphate buffer (30 mM, pH 2.7) in the ratio 34:66 (v/v), the flow rate of 1 mL min−1, injection volume of 10 μL and UV detection at 210 nm. By assigning the design space from the overlay plot, the regions within which the robustness of the method is achieved were defined and confirmed by Dong’s algorithm calculations. The proposed method was validated and shown to be applicable for the determination of the three drugs in commercially available tablets. In addition, the impact of the method on the environment was assessed through four different analytical tools: National Environmental Methods Index, Analytical Eco-Scale, Green Analytical Procedure Index and Assessment of Green Profile. The proposed method was determined to be greener, with minimal impact on the environment with regard to waste production, energy consumption and use of hazardous chemicals.