bluuebunny/crossref_metadata_2025_split huggingface dataset:
The structure and behaviour of hierarchical infrastructure networks
Authors: Robson Craig , Barr Stuart , Ford Alistair , James Philip 
Published: September 2021

AbstractCritical services depend on infrastructure networks for their operation and any disruption to these networks can have significant impacts on society, the economy, and quality of life. Such networks can be characterised as graphs which can be used to understand their structural properties, and the effect on their behaviour and robustness to hazards. Using a suite of graphs and critical infrastructure networks, this study aims to show that networks which exhibit a hierarchical structure are more likely to be less robust comparatively to non-hierarchical networks when exposed to failures, including those which supply critical services. This study investigates the properties of a hierarchical structure through identifying a set of key characteristics from an ensemble of graph models which are then used in a comparative analysis against a suite of spatial critical infrastructure networks. A failure model is implemented and applied to understand the implications of hierarchical structures in real world networks for their robustness to perturbations. The study concludes that a set of three graph metrics, cycle basis, maximum betweenness centrality and assortativity coefficient, can be used to identify the extent of a hierarchy in graphs, where a lack of robustness is linked to the hierarchical structure, a feature exhibited in both graph models and infrastructure networks.
Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks
Authors: Medeuov Darkhan , Roth Camille , Puzyreva Kseniia , Basov Nikita 
Published: September 2021

AbstractThis article proposes an approach to compare semantic networks using concept-centered sub-networks. A concept-centered sub-network is defined as an induced network whose vertex set consists of the given concept (ego) and all its adjacent concepts (alters) and whose link set consists of all the links between the ego and alters (including alter-alter links). By looking at the vertex and link overlap indices of concept-centered networks we infer semantic similarity of the underlying concepts. We cross-evaluate the semantic similarity by close-reading textual contexts from which networks are derived. We illustrate the approach on written and interview texts from an ethnographic study of flood management practice in England.
Visualization and Perception of Data Gaps in the Context of Citizen Science Projects
Authors: Hoyer Tom , Moritz Julia , Moser Jana 
Published: September 2021

AbstractCitizen Science initiatives often collect the data in an unsystematic way and dependent on the voluntary participation of interested citizens. The visualization of such data must present this incompleteness in a way that is understandable and comprehensible even to scientific laypersons if the correct conclusions are to be drawn. Using the project “Experiencing Biodiversity” as an example, this article shows how these requirements can be taken into account in the development of an online portal. Thereby, we discuss how data gaps can be pointed out by means of maps in order to be able to better interpret the significance of crowd-based data. We use empirical user studies to show the extent to which this was successful in the “Experiencing Biodiversity” project and the role of additional interpretation aids. Finally, we discuss how the findings of this project could be transferred to other use cases.
Expertise Detection in Crowdsourcing Forums Using the Composition of Latent Topics and Joint Syntactic–Semantic Cues
Authors: Woldemariam Yonas Demeke 
Published: September 2021

AbstractWe develop an NLP method for inferring potential contributors among multitude of users within crowdsourcing forums (CSFs). The method basically provides a way to predict expertise from their structures (syntax–semantic patterns) when crowdsourced votes are unavailable. It primarily deals with tackling core adverse conditions, which hinder the identification of crowds’ expertise levels, and standardization of measuring linguistic quality of crowdsourced text. To solve the former, an expertise estimation and linguistic feature annotation algorithm is developed. To approach the later, a comprehensive linguistic characterization of crowdsourced text, along with extensive joint syntax–punctuation analyses, have been carried out. The entire corpora are comprised of approximately 8 different domains, 3 million and 50,000 sentences, and 32 million and 90,000 words, contributed by a crowd of 50,000 users. The analyses revealed six major linguistic patterns, identified on the basis of ordered lists of structural (syntactic) categories, learned from grammatical constructions, practiced by major groups of experts. In addition, nine different text-oriented expertise dimensions are identified, as crucial steps towards establishing standard linguistic-based expertise-framework for most CSFs. Potentially, the resulting framework simplifies the measurement of crowds’ proficiency, in those particular forums, where crowds’ tasks (e.g., answering questions, technically discerning deep features within images of galaxies for classifying them into certain categories) are intimately connected with their writing (e.g., describing answers illustratively, expressing complex phenomena observed in classified images). Moreover, wide varieties of linguistic annotations: latent topic annotations, named entities, syntactic and punctuation annotations, semantic and character set annotations, word and character n-grams (n= 2 and 3) annotations, are extracted. That is for building baseline and enhanced versions of expertise models (about 20 different models built). The successive achievements of enhancing baseline models, with iteratively adding linguistic feature annotations in a two-stage enhancement process, indicate the adaptability of the learned models.
Revisiting Daily MODIS Evapotranspiration Algorithm Using Flux Tower Measurements in China
Authors: Huang Lei , Steenhuis Tammo S. , Luo Yong , Tang Qiuhong , Tang Ronglin , Zheng Junqing , Shi Wen , Qiao Chen 
Published: September 2021

AbstractEvapotranspiration (ET) is the major component of the hydrology cycle. Satellites provide a convenient way for gathering information to estimate regional ET. The most widely applied method for converting the instantaneous satellite measurement to daily scale assumes that evaporative fraction (EF), defined as the ratio of ET to the available energy, is constant during the daytime. However, this method was proved to underestimate the daily ET. This study implemented a theoretically improved EF algorithm to calculate daily ET with the decoupling factor method based on the Penman‐Monteith and McNaughton‐Jarvis equations. Seven improved algorithms were developed by assuming that various parameters remain constant during the day. The satellite‐based ET estimates were compared with seven local flux tower measurements in China. The results showed that: (a) The original ET method calculated the daily evaporation more accurately than the other algorithms. However, the good fit was based on two compensating inaccuracies. Compared to the flux tower measurement, the original ET method underestimated the daily EF by 26% and overestimated the daily net radiation by 30%. (b) Six of the seven proposed algorithms underpredicted the daily ET by 30%–60%, mainly due to the inaccurate daily net radiation. (c) The algorithm that assumed that the instantaneous decoupling parameter was equal to its daily value method calculated EF and ET with relative errors of 8% and 10% separately when the inaccurate estimated daily net radiation was replaced by the observed flux tower data.
Noise Integration Kernel Design for the Wave Distribution Function Method: Robust Direction Finding With Different Sensor Noise Levels
Authors: Tanaka Yuji , Ota Mamoru , Kasahara Yoshiya 
Published: September 2021

AbstractPlasma wave direction determined by propagation characteristics and remote sensing technology provides important information for understanding not only the local plasma environment but also the global features of space plasma. The wave distribution function method, a direction finding method, derives the directional distribution of wave energy density using a priori information such as the propagation mode, plasma density, and geomagnetic field intensity. The Markov random field model includes a noise integration kernel that corresponds to the noise used for the estimation, which improves the robustness of the model. However, the effectiveness of this noise integration kernel was only verified for the case where the electromagnetic field sensor noise levels were equal. The noise levels of the electromagnetic field sensors on board scientific satellites often change due to the degradation of the sensors during long‐term instrument operation. Therefore, we proposed two design methods for a noise integration kernel to improve the estimation accuracy when the noise levels among electromagnetic field sensors are different. In proposed model 1, the noise integration kernel was designed for each sensor, and in proposed model 2, the noise integration kernel was designed with the information that the noise level ratio between the sensors was known. The simulation results showed that proposed model 2 improved the misalignment of the peak in the direction of arrival when the noise levels were different regardless of whether the sensor was parallel or perpendicular to the external magnetic field.
Integrative brain transcriptome analysis links complement component 4 and HSPA2 to the APOE ε2 protective effect in Alzheimer disease
Authors: Panitch Rebecca , Hu Junming , Chung Jaeyoon , Zhu Congcong , Meng Gaoyuan , Xia Weiming , Bennett David A. , Lunetta Kathryn L. , Ikezu Tsuneya , Au Rhoda , Stein Thor D. , Farrer Lindsay A. , Jun Gyungah R. 
Published: September 2021

AbstractMechanisms underlying the protective effect of apolipoprotein E (APOE) ε2 against Alzheimer disease (AD) are not well understood. We analyzed gene expression data derived from autopsied brains donated by 982 individuals including 135APOEɛ2/ɛ3 carriers. Complement pathway genesC4AandC4Bwere among the most significantly differentially expressed genes between ɛ2/ɛ3 AD cases and controls. We also identified anAPOEε2/ε3 AD-specific co-expression network enriched for astrocytes, oligodendrocytes and oligodendrocyte progenitor cells containing the genesC4A, C4B, andHSPA2. These genes were significantly associated with the ratio of phosphorylated tau at position 231 to total Tau but not with amyloid-β 42 level, suggesting thisAPOEɛ2 related co-expression network may primarily be involved with tau pathology.HSPA2expression was oligodendrocyte-specific and significantly associated with C4B protein. Our findings provide the first evidence of a crucial role of the complement pathway in the protective effect ofAPOEε2 for AD.
Neuropharmacokinetic visualization of regional and subregional unbound antipsychotic drug transport across the blood–brain barrier
Authors: Luptáková Dominika , Vallianatou Theodosia , Nilsson Anna , Shariatgorji Reza , Hammarlund-Udenaes Margareta , Loryan Irena , Andrén Per E. 
Published: September 2021

AbstractComprehensive determination of the extent of drug transport across the region-specific blood–brain barrier (BBB) is a major challenge in preclinical studies. Multiple approaches are needed to determine the regional free (unbound) drug concentration at which a drug engages with its therapeutic target. We present an approach that merges in vivo and in vitro neuropharmacokinetic investigations with mass spectrometry imaging to quantify and visualize both the extent of unbound drug BBB transport and the post-BBB cerebral distribution of drugs at regional and subregional levels. Direct imaging of the antipsychotic drugs risperidone, clozapine, and olanzapine using this approach enabled differentiation of regional and subregional BBB transport characteristics at 20-µm resolution in small brain regions, which could not be achieved by other means. Our approach allows investigation of heterogeneity in BBB transport and presents new possibilities for molecular psychiatrists by facilitating interpretation of regional target-site exposure results and decision-making.
PPFIBP1 induces glioma cell migration and invasion through FAK/Src/JNK signaling pathway
Authors: Dong Caihua , Li Xinying , Yang Jiao , Yuan Detian , Zhou Yuanshuai , Zhang Yina , Shi Guohua , Zhang Ruobing , Liu Jianping , Fu Peng , Sun Minxuan 
Published: September 2021

AbstractGlioblastoma multiforme (GBM) is the most aggressive brain tumor, with a 5-year survival ratio <5%. Invasive growth is a major determinant of the poor prognosis in GBM. In this study, we demonstrate that high expression of PPFIA binding protein 1 (PPFIBP1) correlates with remarkable invasion and poor prognosis of GBM patients. Using scratch and transwell assay, we find that the invasion and migration of GBM cells are promoted by overexpression of PPFIBP1, while inhibited by knockdown of PPFIBP1. Then, we illustrate that overexpression of PPFIBP1 facilitates glioma cell infiltration and reduces survival in xenograft models. Next, RNA-Seq and GO enrichment analysis reveal that PPFIBP1 regulates differentially expressed gene clusters involved in the Wnt and adhesion-related signaling pathways. Furthermore, we demonstrate that PPFIBP1 activates focal adhesion kinase (FAK), Src, c-Jun N-terminal kinase (JNK), and c-Jun, thereby enhancing Matrix metalloproteinase (MMP)-2 expression probably through interacting with SRCIN1 (p140Cap). Finally, inhibition of phosphorylation of Src and FAK significantly reversed the augmentation of invasion and migration caused by PPFIBP1 overexpression in GBM cells. In conclusion, these findings uncover a novel mechanism of glioma invasion and identify PPFIBP1 as a potential therapeutic target of glioma.
Deep learning with digital holographic microscopy discriminates apoptosis and necroptosis
Authors: Verduijn Joost , Van der Meeren Louis , Krysko Dmitri V. , Skirtach André G. 
Published: September 2021

AbstractRegulated cell death modalities such as apoptosis and necroptosis play an important role in regulating different cellular processes. Currently, regulated cell death is identified using the golden standard techniques such as fluorescence microscopy and flow cytometry. However, they require fluorescent labels, which are potentially phototoxic. Therefore, there is a need for the development of new label-free methods. In this work, we apply Digital Holographic Microscopy (DHM) coupled with a deep learning algorithm to distinguish between alive, apoptotic and necroptotic cells in murine cancer cells. This method is solely based on label-free quantitative phase images, where the phase delay of light by cells is quantified and is used to calculate their topography. We show that a combination of label-free DHM in a high-throughput set-up (~10,000 cells per condition) can discriminate between apoptosis, necroptosis and alive cells in the L929sAhFas cell line with a precision of over 85%. To the best of our knowledge, this is the first time deep learning in the form of convolutional neural networks is applied to distinguish—with a high accuracy—apoptosis and necroptosis and alive cancer cells from each other in a label-free manner. It is expected that the approach described here will have a profound impact on research in regulated cell death, biomedicine and the field of (cancer) cell biology in general.
Zanthoxylum-specific whole genome duplication and recent activity of transposable elements in the highly repetitive paleotetraploid Z. bungeanum genome
Authors: Feng Shijing , Liu Zhenshan , Cheng Jian , Li Zihe , Tian Lu , Liu Min , Yang Tuxi , Liu Yulin , Liu Yonghong , Dai He , Yang Zujun , Zhang Qing , Wang Gang , Zhang Jisen , Jiang Huifeng , Wei Anzhi 
Published: September 2021

Abstract
Zanthoxylum bungeanum is an important spice and medicinal plant that is unique for its accumulation of abundant secondary metabolites, which create a characteristic aroma and tingling sensation in the mouth. Owing to the high proportion of repetitive sequences, high heterozygosity, and increased chromosome number of Z. bungeanum, the assembly of its chromosomal pseudomolecules is extremely challenging. Here, we present a genome sequence for Z. bungeanum, with a dramatically expanded size of 4.23 Gb, assembled into 68 chromosomes. This genome is approximately tenfold larger than that of its close relative Citrus sinensis. After the divergence of Zanthoxylum and Citrus, the lineage-specific whole-genome duplication event η-WGD approximately 26.8 million years ago (MYA) and the recent transposable element (TE) burst ~6.41 MYA account for the substantial genome expansion in Z. bungeanum. The independent Zanthoxylum-specific WGD event was followed by numerous fusion/fission events that shaped the genomic architecture. Integrative genomic and transcriptomic analyses suggested that prominent species-specific gene family expansions and changes in gene expression have shaped the biosynthesis of sanshools, terpenoids, and anthocyanins, which contribute to the special flavor and appearance of Z. bungeanum. In summary, the reference genome provides a valuable model for studying the impact of WGDs with recent TE activity on gene gain and loss and genome reconstruction and provides resources to accelerate Zanthoxylum improvement.
Insights into angiosperm evolution, floral development and chemical biosynthesis from the Aristolochia fimbriata genome
Authors: Qin Liuyu , Hu Yiheng , Wang Jinpeng , Wang Xiaoliang , Zhao Ran , Shan Hongyan , Li Kunpeng , Xu Peng , Wu Hanying , Yan Xueqing , Liu Lumei , Yi Xin , Wanke Stefan , Bowers John E. , Leebens-Mack James H. , dePamphilis Claude W. , Soltis Pamela S. , Soltis Douglas E. , Kong Hongzhi , Jiao Yuannian 
Published: September 2021

AbstractAristolochia, a genus in the magnoliid order Piperales, has been famous for centuries for its highly specialized flowers and wide medicinal applications. Here, we present a new, high-quality genome sequence ofAristolochia fimbriata, a species that, similar toAmborella trichopoda, lacks further whole-genome duplications since the origin of extant angiosperms. As such, theA. fimbriatagenome is an excellent reference for inferences of angiosperm genome evolution, enabling detection of two novel whole-genome duplications in Piperales and dating of previously reported whole-genome duplications in other magnoliids. Genomic comparisons betweenA. fimbriataand other angiosperms facilitated the identification of ancient genomic rearrangements suggesting the placement of magnoliids as sister to monocots, whereas phylogenetic inferences based on sequence data we compiled yielded ambiguous relationships. By identifying associated homologues and investigating their evolutionary histories and expression patterns, we revealed highly conserved floral developmental genes and their distinct downstream regulatory network that may contribute to the complex flower morphology inA. fimbriata. Finally, we elucidated the genetic basis underlying the biosynthesis of terpenoids and aristolochic acids inA. fimbriata.
Global topographic uplift has elevated speciation in mammals and birds over the last 3 million years
Authors: Igea Javier , Tanentzap Andrew J. 
Published: September 2021

AbstractTopographic change shapes the evolution of biodiversity by influencing both habitat connectivity and habitat diversity as well as abiotic factors like climate. However, its role in creating global biodiversity gradients remains poorly characterized because geology, climate and evolutionary data have rarely been integrated across concordant timescales. Here we show that topographic uplift over the last 3 million years explains more spatial variation in the speciation of all mammals and birds than do the direct effects of palaeoclimate change and both present-day elevation and present-day temperature. By contrast, the effects of topographic changes are much smaller than those of present-day temperatures in eroded areas. Together, our results stress that historical geological processes rather than traditionally studied macroecological gradients may ultimately generate much of the world’s biodiversity. More broadly, as the Earth’s surface continues to rise and fall, topography will remain an important driver of evolutionary change and novelty.
The emergence of heterogeneous scaling in research institutions
Authors: Burghardt Keith A. , He Zihao , Percus Allon G. , Lerman Kristina 
Published: September 2021

AbstractResearch institutions provide the infrastructure for scientific discovery, yet their role in the production of knowledge is not well characterized. To address this gap, we analyze interactions of researchers within and between institutions from millions of scientific papers. Our analysis reveals that collaborations densify as each institution grows, but at different rates (heterogeneous densification). We also find that the number of institutions scales with the number of researchers as a power law (Heaps’ law) and institution sizes approximate Zipf’s law. These patterns can be reproduced by a simple model in which researchers are preferentially hired by large institutions, while new institutions complimentarily generate more new institutions. Finally, new researchers form triadic closures with collaborators. This model reveals an economy of scale in research: larger institutions grow faster and amplify collaborations. Our work deepens the understanding of emergent behavior in research institutions and their role in facilitating collaborations.
Dysphagia, COVID-19, and the Clinical Swallow Evaluation: Consistently Inconsistent
Authors: Schwartz Talia H. 
Published: September 2021

Purpose
Dysphagia management in COVID-19 patients during the New York City spring surge in early 2020 was challenging for many speech-language pathologists, as instrumental swallow evaluations were unavailable. Renewed attention was brought to the value of the clinical swallow evaluation.

Conclusion
While consistently utilized, the experience also brought back into light the inconsistences in which the clinical swallow evaluation is executed.
Contrast-Enhanced Ultrasound Improves the Accuracy of the ACR TI-RADS in the Diagnosis of Thyroid Nodules Located in the Isthmus
Authors: Huang Yunlin , Hong Yurong , Xu Wen , Song Kai , Huang Pintong 
Published: September 2021

Abstract
Objectives To evaluate the diagnostic performance of the American College of Radiology (ACR) Thyroid Image Reporting and Data System (TI-RADS), contrast-enhanced ultrasound (CEUS), and a modified TI-RADS in differentiating benign and malignant nodules located in the isthmus.
Methods This retrospective study was approved by the institutional review board. Informed consent was obtained. Grayscale ultrasound (US) and CEUS images were obtained for 203 isthmic thyroid nodules (46 benign and 157 malignant) in 198 consecutive patients (156 women, mean age: 44.7 years ± 11.3 [standard deviation]; 47 men, mean age: 40.9 years ± 11.0). The area under the receiver operating characteristic curve (AUC) of the diagnostic performance of the ACR TI-RADS, CEUS, and the modified TI-RADS were evaluated.
Results Lobulated or irregular margins (P = 0.001; odds ratio [OR] = 9.250) and punctate echogenic foci (P = 0.007; OR = 4.718) on US and hypoenhancement (P < 0.001; OR = 20.888) on CEUS displayed a significant association with malignancy located in the isthmus. The most valuable method to distinguish benign nodules from malignant nodules was the modified TI-RADS (AUC: 0.863 with modified TR5), which was significantly better than the ACR TI-RADS (AUC: 0.738 with ACR TR5) (P < 0.001) but showed no significant difference with respect to CEUS (AUC: 0.835 with hypoenhancement) (P = 0.205). The diagnostic value was significantly different between CEUS and the ACR TI-RADS (P = 0.028).
Conclusion The modified TI-RADS could significantly improve the accuracy of the diagnosis of thyroid nodules located in the isthmus.