bluuebunny/crossref_metadata_2025_split huggingface dataset:
Documentation, structural health monitoring and numerical modelling for damage assessment of the Morris Island Lighthouse
Authors: Blyth Anna , Napolitano Rebecca , Glisic Branko 
Published: August 2019

Heritage structures serve as invaluable records of cultural achievement that should be preserved for future generations. To ensure the successful preservation of these structures, there must be an affordable and effective way to conduct conservation. The objective of this work is to outline an efficient workflow for the structural analysis of preservation projects through a case study on the Morris Island Lighthouse in Charleston, South Carolina. Thorough documentation of the cultural significance and structural condition of the lighthouse was completed through archival research, photogrammetry and crack mapping. Structural Health Monitoring and Distinct Element Modelling were used to analyse past structural damage and the present condition. The behaviour of masonry and crack propagation was evaluated under gravity, wind, wave and seismic loading. The results of these analyses were summarized in a virtual tour and informational modelling environment, which allows the results to be accessed and associated with their physical location on the structure. The benefits and limitations of this process are discussed, and a standardized workflow for efficient structural analysis of cultural heritage is proposed.
This article is part of the theme issue ‘Environmental loading of heritage structures’.
Structural response of French offshore heritage lighthouses
Authors: Denarié Emmanuel , Fady Nicolas 
Published: August 2019

Offshore lighthouses are a remarkable historical heritage often over 100 years old. The management of their ageing is a challenge and requires a thorough understanding of their structural response under wave loading. With this aim in view, the dynamic response of the ‘La Jument’ lighthouse in the French Iroise Sea was characterizedin situ, with accelerometers, under the action of a breaking wave, during a winter storm in January 2018. Detailed exploitation of the measurement data complemented by photographic documentation of the same wave event helped determine eigenfrequencies and damping coefficients of the structure as well as the likely orientation of the wave and the position of its crest with respect to the lighthouse tower. The results of these analyses were put into perspective with those of literature and more specifically from three-dimensional finite element modelling of the structural response of the lighthouse under the action effects of breaking waves.This article is part of the theme issue ‘Environmental loading of heritage structures’.
A Bayesian model updating framework for robust seismic fragility analysis of non-isolated historic masonry towers
Authors: Bartoli Gianni , Betti Michele , Marra Antonino Maria , Monchetti Silvia 
Published: August 2019

Seismic assessment of existing masonry structures requires a numerical model able to both reproduce their nonlinear behaviour and account for the different sources of uncertainties; the latter have to be dealt with since the unavoidable lack of knowledge on the input parameters (material properties, geometry, boundary conditions, etc.) has a relevant effect on the reliability of the seismic response provided by the numerical approaches. The steadily increasing necessity of combining different sources of information/knowledge makes the Bayesian approach an appealing technique, not yet fully investigated for historic masonry constructions. In fact, while the Bayesian paradigm is currently employed to solve inverse problems in several sectors of the structural engineering domain, only a few studies pay attention to its effectiveness for parameter identification on historic masonry structures. This study combines a Bayesian framework with probabilistic structural analyses: starting from the Bayesian finite element model updating by using experimental data it provides the definition of robust seismic fragility curves for non-isolated masonry towers. A comparison between this method and the standard deterministic approach illustrates its benefits.
This article is part of the theme issue ‘Environmental loading of heritage structures’.
Stochastic subspace identification of modal parameters during ice–structure interaction
Authors: Nord Torodd S. , Petersen Øyvind W. , Hendrikse Hayo 
Published: August 2019

Identifying the modal parameters of structures located in ice-infested waters may be challenging due to the interaction between the ice and structure. In this study, both simulated data from a state-of-the-art ice–structure interaction model and measured data of ice–structure interaction were both used in conjunction with a covariance-driven stochastic subspace identification method to identify the modal parameters and their corresponding variances. The variances can be used to assign confidence to the identified eigenfrequencies, and effectively eliminate the eigenfrequencies with large variances. This enables a comparison between the identified eigenfrequencies for different ice conditions. Simulated data were used to assess the accuracy of the identified modal parameters during ice–structure interactions, and they were further used to guide the choice of parameters for the subspace identification when applied to measured data. The measured data consisted of 150 recordings of ice actions against the Norströmsgrund lighthouse in the Northern Baltic Sea. The results were sorted into groups defined by the observed ice conditions and governing ice failure mechanisms during the ice–structure interaction. The identified eigenfrequencies varied within each individual group and between the groups. Based on identified modal parameters, we suggested which eigenmodes play an active role in the interaction processes at the ice–structure interface and discussed the possible sources of errors.
This article is part of the theme issue ‘Environmental loading of heritage structures’.
A Single-Cell Transcriptome Atlas for Zebrafish Development
Authors: Farnsworth Dylan R. , Saunders Lauren , Miller Adam C. 
Published: August 2019

ABSTRACTThe ability to define cell types and how they change during organogenesis is central to our understanding of animal development and human disease. Despite the crucial nature of this knowledge, we have yet to fully characterize all distinct cell types and the gene expression differences that generate cell types during development. To address this knowledge gap, we produced an Atlas using single-cell RNA-sequencing methods to investigate gene expression from the pharyngula to early larval stages in developing zebrafish. Our single-cell transcriptome Atlas encompasses transcriptional profiles from 44,102 cells across four days of development using duplicate experiments that confirmed high reproducibility. We annotated 220 identified clusters and highlighted several strategies for interrogating changes in gene expression associated with the development of zebrafish embryos at single-cell resolution. Furthermore, we highlight the power of this analysis to assign new cell-type or developmental stage-specific expression information to many genes, including those that are currently known only by sequence and/or that lack expression information altogether. The resulting Atlas is a resource of biologists to generate hypotheses for genetic (mutant) or functional analysis, to launch an effort to define the diversity of cell-types during zebrafish organogenesis, and to examine the transcriptional profiles that produce each cell type over developmental time.
Modulation of human intracranial theta oscillations during freely moving spatial navigation and memory
Authors: Aghajan Zahra M. , Villaroman Diane , Hiller Sonja , Wishard Tyler J. , Topalovic Uros , Christov-Moore Leonardo , Shaterian Nader , Hasulak Nicholas R. , Knowlton Barbara , Eliashiv Dawn , Rao Vikram , Fried Itzhak , Suthana Nanthia 
Published: August 2019

SummaryHow the human brain supports accurate navigation of a learned environment has been an active topic of research for nearly a century1–5. In rodents, the theta rhythm within the medial temporal lobe (MTL) has been proposed as a neural basis for fragmenting incoming information and temporally organizing experiences and is thus widely implicated in spatial and episodic memory6. In addition, high-frequency theta (~8Hz) is associated with navigation, and loss of theta results in spatial memory deficits in rats 7. Recently, high-frequency theta oscillations during ambulatory movement have been identified in humans8,9, though their relationship to spatial memory remains unexplored. Here, we were able to record MTL activity during spatial memory and navigation in freely moving humans immersed in a room-scale virtual reality (VR) environment. Naturalistic movements were captured using motion tracking combined with wireless VR in participants implanted with an intracranial electroencephalographic (iEEG) recording system for the treatment of epilepsy. We found that prevalence of theta oscillations across brain sites during both learning and recall of spatial locations during ambulatory navigation is critically linked to memory performance. This finding supports the reinstatement hypothesis of episodic memory—thought to underlie our ability to recreate a prior experience10–12—and suggests that theta prevalence within the MTL may act as a potential representational state for memory reinstatement during spatial navigation. Additionally, we found that theta power is hexadirectionally modulated13–15 as a function of the direction of physical movement, most prominently after learning has occurred. This effect bears a resemblance to the rodent grid cell system16 and suggests an analog in human navigation. Taken together, our results provide the first characterization of neural oscillations in the human MTL during ambulatory spatial memory tasks and provide a platform for future investigations of neural mechanisms underlying freely moving navigation in humans.
Interplay between metrical and semantic processing in French: an N400 study
Authors: Rietmolen Noémie te , Yagoubi Radouane El , Astésano Corine 
Published: August 2019

AbstractFrench accentuation is held to belong to the level of the phrase. Consequently French is considered ‘a language without accent’ with speakers that are ‘deaf to stress’. Recent ERP-studies investigating the French initial accent (IA) however demonstrate listeners to not only discriminate between different stress patterns, but also expect words to be marked with IA early in the process of speech comprehension. Still, as words were presented in isolation, it remains unclear whether the preference applied to the lexical or to the phrasal level. In the current ERP-study, we address this ambiguity and manipulate IA on words embedded in a sentence. Furthermore, we orthogonally manipulate semantic congruity to investigate the interplay between accentuation and later speech processing stages. Results reveal an early fronto-centrally located negative deflection when words are presented without IA, indicating a general dispreference for words presented without IA. Additionally, we found an effect of semantic congruity in the centro-parietal region (the traditional region for N400), which was bigger for words without IA than for words with IA. Furthermore, we observed an interaction between metrical structure and semantic congruity such that ±IA continued to modulate N400 amplitude fronto-centrally, but only in the sentences that were semantically incongruent. The results indicate that presenting word without initial accent hinders semantic conflict resolution. This interpretation is supported by the behavioral data which show that participants were slower and made more errors words had been presented without IA. As participants attended to the semantic content of the sentences, the finding underlines the automaticity of stress processing and indicates that IA may be encoded at a lexical level where it facilitates semantic processing.
Spherical deconvolution with tissue-specific response functions and multi-shell diffusion MRI to estimate multiple fiber orientation distributions (mFODs)
Authors: De Luca Alberto , Guo Fenghua , Froeling Martijn , Leemans Alexander 
Published: August 2019

AbstractIn diffusion MRI, spherical deconvolution approaches can estimate local white matter (WM) fiber orientation distributions (FOD) which can be used to produce fiber tractography reconstructions. The applicability of spherical deconvolution to grey matter (GM), however, is still limited, despite its critical role as start/endpoint of WM fiber pathways. The advent of multi-shell diffusion MRI data offers additional contrast to model the GM signal but, to date, only isotropic models have been applied to GM. Evidence from both histology and high-resolution diffusion MRI studies suggests a marked anisotropic character of the diffusion process in GM, which could be exploited to improve the description of the cortical organization. In this study, we investigated whether performing spherical deconvolution with tissue specific models of both WM and GM can improve the characterization of the latter while retaining state-of-the-art performances in WM. To this end, we developed a framework able to simultaneously accommodate multiple anisotropic response functions to estimate multiple, tissue-specific, fiber orientation distributions (mFODs). As proof of principle, we used the diffusion kurtosis imaging model to represent the WM signal, and the neurite orientation dispersion and density imaging (NODDI) model to represent the GM signal. The feasibility of the proposed approach is shown with numerical simulations and with data from the Human Connectome Project (HCP). The performance of our method is compared to the current state of the art, multi-shell constrained spherical deconvolution (MSCSD). The simulations show that with our new method we can accurately estimate a mixture of two FODs at SNR≥50. With HCP data, the proposed method was able to reconstruct both tangentially and radially oriented FODs in GM, and performed comparably well to MSCSD in computing FODs in WM. When performing fiber tractography, the trajectories reconstructed with mFODs reached the cortex with more spatial continuity and for a longer distance as compared to MSCSD and allowed to reconstruct short trajectories tangential to the cortical folding. In conclusion, we demonstrated that our proposed method allows to perform spherical deconvolution of multiple anisotropic response functions, specifically improving the performances of spherical deconvolution in GM tissue.HighlightsWe introduce a novel framework to perform spherical deconvolution with multiple anisotropic response functions (mFOD)We show that the proposed framework can be used to improve the FOD estimation in the cortical grey matterFiber tractography performed with mFOD reaches the cortical GM with more coverage and contiguity than with previous methodsThe proposed framework is a first step towards GM to GM fiber tractography
Antibody binding epitope Mapping (AbMap) of two hundred antibodies in a single run
Authors: Qi Huan , Ma Mingliang , Hu Chuansheng , Xu Zhao-wei , Wu Fan-lin , Wang Nan , Lai Dan-yun , Li Yang , Guo Shu-juan , Zhao Xiaodong , Li Hua , Tao Sheng-ce 
Published: August 2019

AbstractEpitope mapping is essential for the understanding how an antibody works. Given millions of antibodies short of epitope information, there is an urgent need for high-throughput epitope mapping. Here we combined a commercial phage displayed random peptide library of 109diversity with next generation sequencing to developAntibodybinding epitopeMapping (AbMap) technology. Over two hundred antibodies were analyzed in a single test and epitopes were determined for >50% of them. Strikingly, the antibodies were able to recognize different proteins from multiple species with similar epitopes. We successfully identified the epitopes of 14 anti-PD-1 antibodies, including Sintilimab (i.e., L128, A129 and P130), and confirmed that the binding epitopes of Nivolumab and Sintilimab are very close to the binding interface of PD-1 and PD-L1. The predicted conformational epitopes of Pembrolizumab and Nivolumab are consistent with their antibody-antigen co-crystal structures. AbMap is the first technology enables high-throughput epitope mapping.HighlightsThe first technology enables epitope mapping of two hundred antibodies in a single runLinear epitope was determined for >50% of the antibodiesDistinct epitopes of 14 anti-PD-1 antibodies, including Sintilimab, were determinedThe predicted conformational epitopes of Pembrolizumab and Nivolumab are consistent with the known antibody-antigen co-crystal structures
PASER for automated analysis of neural signals recorded in pulsating magnetic fields
Authors: Brouns Terence , Celikel Tansu 
Published: August 2019

AbstractThanks to the advancements in multichannel intracranial neural recordings, magnetic neuroimaging and magnetic neurostimulation techniques (including magnetogenetics), it is now possible to perform large-scale high-throughput neural recordings while imaging or controlling neural activity in a magnetic field. Analysis of neural recordings performed in a switching magnetic field, however, is not a trivial task as gradient and pulse artefacts interfere with the unit isolation. Here we introduce a toolbox called PASER, Processing and Analysis Schemes for Extracellular Recordings, that performs automated denoising, artefact removal, quality control of electrical recordings, unit classification and visualization. PASER is written in MATLAB and modular by design. The current version integrates with third party applications to provide additional functionality, including data import, spike sorting and the analysis of local field potentials. After the description of the toolbox, we evaluate 9 different spike sorting algorithms based on computational cost, unit yield, unit quality and clustering reliability across varying conditions including self-blurring and noise-reversal. Implementation of the best performing spike sorting algorithm (KiloSort) in the default version of the PASER provides the end user with a fully automated pipeline for quantitative analysis of broadband extracellular signals. PASER can be integrated with any established pipeline that sample neural activity with intracranial electrodes. Unlike the existing algorithmic solutions, PASER provides an end-to-end solution for neural recordings made in switching magnetic fields independent from the number of electrodes and the duration of recordings, thus enables high-throughput analysis of neural activity in a wide range of electro-magnetic recording conditions.
SVFX: a machine-learning framework to quantify the pathogenicity of structural variants
Authors: Kumar Sushant , Harmanci Arif , Vytheeswaran Jagath , Gerstein Mark B. 
Published: August 2019

AbstractA rapid decline in sequencing cost has made large-scale genome sequencing studies feasible. One of the fundamental goals of these studies is to catalog all pathogenic variants. Numerous methods and tools have been developed to interpret point mutations and small insertions and deletions. However, there is a lack of approaches for identifying pathogenic genomic structural variations (SVs). That said, SVs are known to play a crucial role in many diseases by altering the sequence and three-dimensional structure of the genome. Previous studies have suggested a complex interplay of genomic and epigenomic features in the emergence and distribution of SVs. However, the exact mechanism of pathogenesis for SVs in different diseases is not straightforward to decipher. Thus, we built an agnostic machine-learning-based workflow, called SVFX, to assign a “pathogenicity score” to somatic and germline SVs in various diseases. In particular, we generated somatic and germline training models, which included genomic, epigenomic, and conservation-based features for SV call sets in diseased and healthy individuals. We then applied SVFX to SVs in six different cancer cohorts and a cardiovascular disease (CVD) cohort. Overall, SVFX achieved high accuracy in identifying pathogenic SVs. Moreover, we found that predicted pathogenic SVs in cancer cohorts were enriched among known cancer genes and many cancer-related pathways (including Wnt signaling, Ras signaling, DNA repair, and ubiquitin-mediated proteolysis). Finally, we note that SVFX is flexible and can be easily extended to identify pathogenic SVs in additional disease cohorts.
Glycopeptide variable window SWATH for improved Data Independent Acquisition glycoprotein analysis
Authors: Zhou Chun , Schulz Benjamin L. 
Published: August 2019

AbstractN-glycosylation plays an essential role in regulating protein folding and function in eukaryotic cells. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH) has proven useful as a data independent acquisition (DIA) MS method for analysis of glycoproteins and their glycan modifications. By separating the entire m/z range into consecutive isolation windows, DIA-MS allows comprehensive MS data acquisition and high-sensitivity detection of molecules of interest. Variable width DIA windows allow optimal analyte measurement, as peptide ions are not evenly distributed across the full m/z range. However, the m/z distribution of glycopeptides is different to that of unmodified peptides because of their large glycan structures. Here, we improved the performance of DIA glycoproteomics by using variable width windows optimized for glycopeptides. This method allocates narrow windows at m/z ranges rich in glycopeptides, improving analytical specificity and performance. We show that related glycoforms must fall in separate windows to allow accurate glycopeptide measurement. We demonstrate the utility of the method by comparing the cell wall glycoproteomes of wild-type and N-glycan biosynthesis deficient yeast and showing improved measurement of glycopeptides with different glycan structures. Our results highlight the importance of appropriately optimized DIA methods for measurement of post-translationally modified peptides.
The absence of SOX2 in the anterior foregut alters the esophagus into trachea and bronchi in both epithelial and mesenchymal components
Authors: Teramoto Machiko , Sugawara Ryo , Minegishi Katsura , Uchikawa Masanori , Takemoto Tatsuya , Kuroiwa Atsushi , Ishii Yasuo , Kondoh Hisato 
Published: August 2019

AbstractIn the anterior foregut (AFG) of mouse embryos, the transcription factor SOX2 is expressed in the epithelia of the esophagus and proximal branches of respiratory organs comprising the trachea and bronchi, whereas NKX2.1 is expressed only in the epithelia of respiratory organs. Previous studies using hypomorphic Sox2 alleles have indicated that reduced SOX2 expression causes the esophageal epithelium to display some respiratory organ characteristics. In the present study, we produced mouse embryos with AFG-specific SOX2 deficiency. In the absence of SOX2 expression, a single NKX2.1-expressing epithelial tube connected the pharynx and the stomach, and a pair of bronchi developed in the middle of the tube. Expression patterns of NKX2.1 and SOX9 revealed that the anterior and posterior halves of SOX2-deficient AFG epithelial tubes assumed the characteristics of the trachea and bronchus, respectively. In addition, we found that mesenchymal tissues surrounding the SOX2-deficient NKX2.1-expressing epithelial tube changed to those surrounding the trachea and bronchi in the anterior and posterior halves, as indicated by the arrangement of smooth muscle cells and SOX9-expressing cells and by the expression of Wnt4 (esophagus specific), Tbx4 (respiratory organ specific), and Hoxb6 (distal bronchus specific). The impact of mesenchyme-derived signaling on the early stage of AFG epithelial specification has been indicated. Our study demonstrated an opposite trend where epithelial tissue specification causes concordant changes in mesenchymal tissues, indicating a reciprocity of epithelial-mesenchymal interactions.