bluuebunny/crossref_metadata_2025_split huggingface dataset:
The halo bispectrum multipoles in redshift space
Authors: Rizzo Federico , Moretti Chiara , Pardede Kevin , Eggemeier Alexander , Oddo Andrea , Sefusatti Emiliano , Porciani Cristiano , Monaco Pierluigi 
Published: January 2023

Abstract
We present the analysis of the halo bispectrum in redshift-space in terms of its multipoles, monopole, quadrupole and hexadecapole, measured from a large set of simulations. We fit such measurements with a tree-level model in perturbation theory that depends on linear and nonlinear bias parameters as well as on the growth rate f of density fluctuations. The likelihood analysis takes advantage of a very large set of mock catalogs, enabling a robust estimation of the covariance properties for all multipoles. We compare the numerical estimate of the covariance matrix to its Gaussian prediction finding discrepancies of 10% or less for all configurations with the sole exception of the squeezed triangles in the monopole case. We find the range of validity of the tree-level model, for the total simulation volume of about
1000 h
-3Gpc3, reaches a maximum wavenumber of 0.08 h Mpc-1 for the monopole, while it is limited to 0.06 and 0.045 h Mpc-1 respectively for quadrupole and hexadecapole. Despite this, the addition of the quadrupole to the analysis allows for significant improvements on the determination of the model parameters and specifically on f, similarly to the power spectrum case. Finally, we compare our numerical estimate for the full covariance with its theoretical prediction in the Gaussian approximation and find the latter to work remarkably well in the context of simulation boxes with periodic boundary condition.
Multipacting study for fundamental power coupler of a superconducting cavity
Authors: Tang Yungai , Wu Cong-Feng , Wang Lin , Zhang Shancai , Feng Guangyao , Li Weimin , Tan Mingsheng , Zhang Kai 
Published: January 2023

Abstract
The research work of Hefei Advanced Light Facility (HALF) is
in progress. A 499.8 MHz superconducting cavity will be used in the
HALF RF system. The preliminary RF design and thermal analysis for
the fundamental power coupler (FPC) of HALF 499.8 MHz
superconducting cavity have been completed. Multipacting (MP) is one
of the major causes of the breakdown in many high power input
couplers and RF cavities, thus, MP simulation for our FPC is
necessary. In this paper, the MP simulation for the FPC was
performed by using the CST. The MP performance of the FPC was
studied. The formation process of the MP in the FPC was investigated
and the physical mechanism of the delay of the MP establishment was
analyzed. The simulation results show that MP will occur when the
power level is higher than 175 kW, and the MP location is near the
ceramic. Therefore, MP suppression is required in the FPC. In order
to suppress the MP, the effect of the biasing DC electric voltage to
MP in the FPC was analyzed in this paper. The simulation results
indicates that the biasing DC electric voltage not only can suppress
the MP, but also can excites new MP in the coupler. Thus, it is
crucial to select the appropriate biasing DC electric voltage for
the MP suppression in the coupler. The results show that the MP in
the FPC can be suppressed very well by using 2 kV or 3 kV biasing
DC electric voltage.
A Study on Site Specific Ground Response Analysis in Bihar
Authors: Noolu Venkatesh , Paluri Yeswanth 
Published: January 2023

Abstract
The influence of local soil conditions on earthquake earthquakes is assessed using seismic site response analysis. Earthquakes are natural phenomena that have claimed the lives and property of millions of people over the centuries. As a result, classifying these strong ground motions, predicting their damage potential, and suggesting mitigation measures become critical. The present study area is Kanti (Muzaffarpur), which is located in north Bihar and covers a geographical area of 3,132 square kilometres and lies between North Latitude 250 54’00”-260 23’00” and East Longitude 84053’00”- 85045’00” which falls in seismic zone IV of IS 1893: 2016. The geotechnical characterization of the site has been investigated using borehole data collected from various locations. The bedrock depth could not be determined due to a lack of deep boreholes, but traces of rock found in the collected data suggest rock outcrops in this region. According to geotechnical characterization, the soil profile in the region is dominated by silty sands, clayey silts, and poorly graded soils. DEEPSOIL software was used to estimate peak ground acceleration. Peak ground acceleration has been estimated using equivalent linear analysis with soil layer depth, bulk density, shear wave velocities, and damping as inputs.
A novel extrusion-based 3D bioprinting system for skeletal muscle tissue engineering
Authors: Fornetti E , De Paolis F , Fuoco C , Bernardini S , Giannitelli S M , Rainer A , Seliktar D , Magdinier F , Baldi J , Biagini R , Cannata S , Testa S , Gargioli C 
Published: January 2023

Abstract
Three-dimensional (3D) bioprinting is an emerging technology, which turned out to be an optimal tool for tissue engineering approaches. To date, different printing systems have been developed. Among them, the extrusion-based approach demonstrated to be the most suitable for skeletal muscle tissue engineering, due to its ability to produce and deposit printing fibers in a parallel pattern that well mimic the native skeletal muscle tissue architecture. In tissue bioengineering, a key role is played by biomaterials, which must possess the key requisite of ‘printability’. Nevertheless, this feature is not often well correlated with cell requirements, such as motives for cellular adhesion and/or absorbability. To overcome this hurdle, several efforts have been made to obtain an effective bioink by combining two different biomaterials in order to reach a good printability besides a suitable biological activity. However, despite being efficient, this strategy reveals several outcomes limitations. We report here the development and characterization of a novel extrusion-based 3D bioprinting system, and its application for correction of volumetric muscle loss (VML) injury in a mouse model. The developed bioprinting system is based on the use of PEG-Fibrinogen, a unique biomaterial with excellent biocompatibility, well-suited for skeletal muscle tissue engineering. With this approach, we obtained highly organized 3D constructs, in which murine muscle progenitors were able to differentiate into muscle fibers arranged in aligned bundles and capable of spontaneously contracting when cultured in vitro. Furthermore, to evaluate the potential of the developed system in future regenerative medicine applications, bioprinted constructs laden with either murine or human muscle progenitors were transplanted to regenerate the Tibialis Anterior muscle of a VML murine model, one month after grafting.
Elevated-temperature wear behavior of Ti6Al4V alloy: microstructural evolution and properties change in subsurfaces and mild-severe wear transition
Authors: An J , Zhang S G , Du D H , Chen H X 
Published: January 2023

Abstract
Dry sliding wear behavior of Ti6Al4V alloy was studied at elevated temperatures of 50 °C–400 °C. The constituent phases and morphologies of worn surfaces were examined to evaluate the roles of oxide layers and wear mechanisms in mild-severe wear transition (M-SWT). Microstructural evolution and hardness change in subsurfaces were also investigated to reveal the most fundamental reason for M-SWT. The results showed that M-SWT happened via severe plastic deformation (SPD) within 20 °C–350 °C, while mild wear prevailed via a protective mechanically mixed layer (MML) containing multiple oxide phases at 400 °C. Large surface plastic deformation and frictional heat activated dynamic recrystallization (DRX) softening in subsurface, which resulted in M-SWT. The critical load for M-SWT presented an approximate linear relationship with testing temperature within 20 °C–250 °C, from which a critical temperature of 555.8 °C for M-SWT was obtained by linearly fitting method. It was thought as the critical temperature for DRX realization in surface layer, and it was utilized to calculate the transition loads at 300 °C and 350 °C.
Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients
Authors: Ahmed Abdella M , Gargett Maegan , Madden Levi , Mylonas Adam , Chrystall Danielle , Brown Ryan , Briggs Adam , Nguyen Trang , Keall Paul , Kneebone Andrew , Hruby George , Booth Jeremy 
Published: January 2023

Abstract
Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour motions. Fast and accurate fiducial marker segmentation is a Requirement of real-time marker-based verification. Deep learning (DL) segmentation techniques are ideal because they don’t require additional learning imaging or prior marker information (e.g., shape, orientation). In this study, we evaluated three DL frameworks for marker tracking applied to pancreatic cancer patient data. The DL frameworks evaluated were (1) a convolutional neural network (CNN) classifier with sliding window, (2) a pretrained you-only-look-once (YOLO) version-4 architecture, and (3) a hybrid CNN-YOLO. Intrafraction kV images collected during pancreas SBRT treatments were used as training data (44 fractions, 2017 frames). All patients had 1-4 implanted fiducial markers. Each model was evaluated on unseen kV images (42 fractions, 2517 frames). The ground truth was calculated from manual segmentation and triangulation of markers in orthogonal paired kV/MV images. The sensitivity, specificity, and area under the precision-recall curve (AUC) were calculated. In addition, the mean-absolute-error (MAE), root-mean-square-error (RMSE) and standard-error-of-mean (SEM) were calculated for the centroid of the markers predicted by the models, relative to the ground truth. The sensitivity and specificity of the CNN model were 99.41% and 99.69%, respectively. The AUC was 0.9998. The average precision of the YOLO model for different values of recall was 96.49%. The MAE of the three models in the left-right, superior-inferior, and anterior-posterior directions were under 0.88 ± 0.11 mm, and the RMSE were under 1.09 ± 0.12 mm. The detection times per frame on a GPU were 48.3, 22.9, and 17.1 milliseconds for the CNN, YOLO, and CNN-YOLO, respectively. The results demonstrate submillimeter accuracy of marker position predicted by DL models compared to the ground truth. The marker detection time was fast enough to meet the requirements for real-time application.
Wood and bark structure inBuddleja: anatomical background of stem morphology
Authors: Frankiewicz K E , Chau J H , Baczyński J , Wdowiak A , Oskolski A 
Published: January 2023

AbstractBark (all tissues outside of the vascular cambium) has been extensively studied in recent years, especially its anatomy and physiology. Macromorphological bark characters can be important taxonomically for many plant groups, including the genus Buddleja (Scrophulariaceae). However, the relationship between macroscopic bark appearance and its microscopic structure remains obscure, hampering the use and interpretation of bark traits in plant taxonomy and phylogenetics as well as in other fields of botany. We studied micro- and macrostructure of bark in the species of Buddleja representing wide taxonomic and geographic diversity to identify general relationships between bark anatomy and morphology. We also examined Buddleja xylem and discussed the importance of anatomical traits for understanding the relationships between clades in this genus. The smooth bark surface in sect. Gomphostigma and the outgroup (Freylinia spp.) relates to the small number of periderms of superficial origin and limited sclerification. This allows for the retention of visible lenticels. In the rest of Buddleja, bark sloughs off and division of labour is present: collapsed phloem undergoes sclerification and acts as a protective layer, while thin-walled phellem forms the separation layers. A similar pattern is found in some groups (e.g. Lonicera), but in others (e.g. Vitis and the species of Eucalyptus with stringy bark), the pattern is inversed. Wood and bark anatomy supports a sister relationship between the southern African section Gomphostigma and the rest of Buddleja but is taxonomically uninformative among remaining clades. Limited development of periderms and sclerification allows for the retention of a smooth bark surface and conspicuous lenticels. Sloughing off of bark requires division of labour into a lignified protective layer and a thin-walled separation layer. These two functions are never served by a single tissue but are rather divided between phloem and periderm. How more subtle features (e.g. size and shape of fissures) are determined requires further study. Simultaneously, bark anatomy could be a useful source of data to complement molecular phylogenetic studies in a total evidence approach for systematics.
Characterizing the Network Structure of Post-Concussion Symptoms
Authors: Goodwin Grace J , Salva Christine E , Rodrigues Jessica , Maietta Julia , Kuwabara Hana C , Ross Staci , Kinsora Thomas F , Allen Daniel N 
Published: January 2023

AbstractObjectiveAssessment of post-concussion symptoms is implemented at secondary, post-secondary, and professional levels of athletics. Network theory suggests that disorders can be viewed as a set of interacting symptoms that amplify, reinforce, and maintain one another. Examining the network structure of post-concussion symptoms may provide new insights into symptom comorbidity and may inform targeted treatment. We used network analysis to examine the topology of post-concussion symptoms using the Post-Concussion Symptom Scale (PCSS) in high school athletes with recent suspected sport-related concussion.MethodUsing a cross-sectional design, the network was estimated from Post Concussion Symptom Scale scores from 3,292 high school athletes, where nodes represented symptoms and edges represented the association between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network.ResultsThe network consisted of edges within and across symptom domains. “Difficulty concentrating” and “dizziness” were the most central symptoms in the network. Although not highly central in the network, headaches were the highest rated symptom.ConclusionsThe interconnectedness among symptoms supports the notion that post-concussion symptoms are interrelated and mutually reinforcing. Given their central role in the network, “difficulty concentrating” and “dizziness” are expected to affect the activation and persistence of other post-concussion symptoms. Interventions targeting difficulties with concentration and dizziness may help alleviate other symptoms. Our findings could inform the development of targeted treatment with the aim of reducing overall symptom burden. Future research should examine the trajectory of post-concussion symptom networks to advance the clinical understanding of post-concussive recovery.
Multivariate Base Rates of Low Score on Neuropsychological Tests of Individuals with Coca Paste Use Disorder
Authors: Vergara-Moragues Esperanza , Barreto María Rocío Acosta , Rivera Diego , Santiago-Ramajo Sandra , González-Saiz Francisco , Lasprilla Juan Carlos Arango 
Published: January 2023

Abstract

Objective
The aim of this study was to determine the prevalence of low scores on eight commonly used neuropsychological tests to evaluate learning and memory, language, and executive functions in individuals with coca paste use disorders (CPUD) and to identify the differences with respect to a group of healthy nonconsuming subjects (HCs).

Methods
162 Colombian adults with CPUD and a group of 162 Colombian adult HCs participated in this comparative study. Eight tests (eighteen test scores) were grouped into three categories: learning and memory, language, and executive functions. Each participant was categorized based on the number of low scoring tests in specific percentile cut-off groups (25th, 16th, 10th, 5th, and 2nd).

Results
In the learning and memory domain, 89.5% of individuals with CPUD and 55.6% of HCs scored below the 25th percentile on at least one of the five test scores, in the language domain, 80.7% of individuals with CPUD and 58% of HCs and in the executive function domain, 92% of individuals with CPUD and 67.3% of HCs. Having two or more scores below the 10th percentile or 10 or more at the 5th percentile shows an optimal cut-off for determining the sensitivity and specificity for discriminating between the two groups.

Conclusions
The individuals with CPUD had a higher percentage of low scores than the HCs in the domains of learning and memory, language, and executive function. It is important for clinicians to be aware of low scores in individuals with CPUD to avoid false-positive diagnoses of cognitive impairment.
cvlr: finding heterogeneously methylated genomic regions using ONT reads
Authors: Raineri Emanuele , Alberola i Pla Mariona , Dabad Marc , Heath Simon 
Published: January 2023

AbstractSummaryNanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here, we exploit this property to search for regions where one can define subpopulations of molecules based on methylation patterns. As an example, we run our clustering algorithm on known imprinted genes; we also scan chromosome 15 looking for windows corresponding to heterogeneous methylation. Our software can also compute the covariance of methylation across these regions while keeping into account the mixture of different types of reads.Availability and implementationhttps://github.com/EmanueleRaineri/cvlr.Contactsimon.heath@cnag.crg.euSupplementary informationSupplementary data are available at Bioinformatics Advances online.
Faltwerk: a library for spatial exploratory data analysis of protein structures
Authors: Viehweger Adrian 
Published: January 2023

AbstractSummaryProteins are fundamental building blocks of life and are investigated in a broad range of scientific fields, especially in the context of recent progress using in silico structure prediction models and the surge of resulting protein structures in public databases. However, exploratory data analysis of these proteins can be slow because of the need for several methods, ranging from geometric and spatial analysis to visualization. The Python library faltwerk provides an integrated toolkit to perform explorative work with rapid feedback. This toolkit includes support for protein complexes, spatial analysis (point density or spatial autocorrelation), ligand binding site prediction and an intuitive visualization interface based on the grammar of graphics.Availability and implementationfaltwerk is distributed under the permissive BSD-3 open source license. Source code and documentation, including an extensive common-use case tutorial, can be found at github.com/phiweger/faltwerk; binaries are available from the pypi repository.
Cistrome Explorer: an interactive visual analysis tool for large-scale epigenomic data
Authors: L’Yi Sehi , Keller Mark S , Dandawate Ariaki , Taing Len , Chen Chen-Hao , Brown Myles , Meyer Clifford A , Gehlenborg Nils 
Published: January 2023

Abstract

Summary
The regulation of genes by cis-regulatory elements (CREs) is complex and differs between cell types. Visual analysis of large collections of chromatin profiles across diverse cell types, integrated with computational methods, can reveal meaningful biological insights. We developed Cistrome Explorer, a web-based interactive visual analytics tool for exploring thousands of chromatin profiles in diverse cell types. Integrated with the Cistrome Data Browser database which contains thousands of ChIP-seq, DNase-seq and ATAC-seq samples, Cistrome Explorer enables the discovery of patterns of CREs across cell types and the identification of transcription factor binding underlying these patterns.

Availability and implementation
Cistrome Explorer and its source code are available at http://cisvis.gehlenborglab.org/ and released under the MIT License. Documentation can be accessed via http://cisvis.gehlenborglab.org/docs/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Phosformer: an explainable transformer model for protein kinase-specific phosphorylation predictions
Authors: Zhou Zhongliang , Yeung Wayland , Gravel Nathan , Salcedo Mariah , Soleymani Saber , Li Sheng , Kannan Natarajan 
Published: January 2023

Abstract

Motivation
The human genome encodes over 500 distinct protein kinases which regulate nearly all cellular processes by the specific phosphorylation of protein substrates. While advances in mass spectrometry and proteomics studies have identified thousands of phosphorylation sites across species, information on the specific kinases that phosphorylate these sites is currently lacking for the vast majority of phosphosites. Recently, there has been a major focus on the development of computational models for predicting kinase–substrate associations. However, most current models only allow predictions on a subset of well-studied kinases. Furthermore, the utilization of hand-curated features and imbalances in training and testing datasets pose unique challenges in the development of accurate predictive models for kinase-specific phosphorylation prediction. Motivated by the recent development of universal protein language models which automatically generate context-aware features from primary sequence information, we sought to develop a unified framework for kinase-specific phosphosite prediction, allowing for greater investigative utility and enabling substrate predictions at the whole kinome level.

Results
We present a deep learning model for kinase-specific phosphosite prediction, termed Phosformer, which predicts the probability of phosphorylation given an arbitrary pair of unaligned kinase and substrate peptide sequences. We demonstrate that Phosformer implicitly learns evolutionary and functional features during training, removing the need for feature curation and engineering. Further analyses reveal that Phosformer also learns substrate specificity motifs and is able to distinguish between functionally distinct kinase families. Benchmarks indicate that Phosformer exhibits significant improvements compared to the state-of-the-art models, while also presenting a more generalized, unified, and interpretable predictive framework.

Availability and implementation
Code and data are available at https://github.com/esbgkannan/phosformer.

Supplementary information
Supplementary data are available at Bioinformatics online.