bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing Waves of COVID-19 in the US: Scale of response changes over time
Authors: Richards Robert L. , Foster Grant , Elderd Bret D. , Dallas Tad A. 
Published: March 2022

ABSTRACTLocal response to the SARS-CoV-2 pandemic differed spatially across the United States but the drivers of this spatial variation remain unclear. We approach this open question by studying the relationship between the growth rate of subsequent waves of the pandemic at the county level during the first year of the pandemic, asking whether state or county demographics better explain variation in this relationship. We found clear spatiotemporal patterns in the relationship between the slopes of subsequent waves in a given county. Generally the standardized difference between the growth rates of waves 1 and 2 and waves 2 and 3 were strongly positively correlated over short distances and shifted to a weak negative correlation at intermediate distances. We also found that peer county health group (a categorization of counties by demographic information relevant to public health) explained variation in response better between wave 1 and 2, while state identity was most important between wave 2 and 3. Taken together, we suggest that there are identifiable spatial patterns in pandemic response across the US but that the nature of these patterns change over the course of the pandemic.
MemBrain: A Deep Learning-aided Pipeline for Automated Detection of Membrane Proteins in Cryo-electron Tomograms
Authors: Lamm Lorenz , Righetto Ricardo D. , Wietrzynski Wojciech , Pöge Matthias , Martinez-Sanchez Antonio , Peng Tingying , Engel Benjamin D. 
Published: March 2022

AbstractBackground and ObjectiveCryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the automated detection of membrane-embedded proteins is a problem still lacking satisfactory solutions.MethodsWe present MemBrain – a new deep learning-based pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. After subvolumes are sampled along a segmented membrane, each subvolume is assigned a score using a convolutional neural network (CNN), and protein positions are extracted by a clustering algorithm. Incorporating rotational subvolume normalization and using a tiny receptive field simplify the task of protein detection and thus facilitate the network training.ResultsMemBrain requires only a small quantity of training labels and achieves excellent performance with only a single annotated membrane (F1 score: 0.88). A detailed evaluation shows that our fully trained pipeline outperforms existing classical computer vision-based and CNN-based approaches by a large margin (F1 score: 0.92 vs. max. 0.63). Furthermore, in addition to protein center positions, MemBrain can determine protein orientations, which has not been implemented by any existing CNN-based method to date. We also show that a pre-trained MemBrain program generalizes to tomograms acquired using different cryo-ET methods and depicting different types of cells.ConclusionsMemBrain is a powerful and label-efficient tool for the detection of membrane protein complexes in cryo-ET data, with the potential to be used in a wide range of biological studies. It is generalizable to various kinds of tomograms, making it possible to use pretrained models for different tasks. Its efficiency in terms of required annotations also allows rapid training and fine-tuning of models. The corresponding code, pretrained models, and instructions for operating the MemBrain program can be found at: https://github.com/CellArchLab/MemBrain
Two Interaction Surfaces between XPA and RPA Organize the Preincision Complex in Nucleotide Excision Repair
Authors: Kim Mihyun , Kim Hyun Suk , D’Souza Areetha , Gallagher Kaitlyn , Jeong Eunwoo , Topolska-Wos Agnieszka , Le Meur Kateryna Ogorodnik , Tsai Chi-Lin , Tsai Miaw-Sheue , Kee Minyong , Tainer John A. , Yeo Jung-Eun , Chazin Walter J. , Schärer Orlando D. 
Published: March 2022

AbstractThe XPA and RPA proteins fulfill essential roles in the assembly of the preincision complex in the nucleotide excision repair pathway. We have previously characterized the two interaction surfaces between XPA and RPA, with the RPA32 and RPA70AB subunits. Here we show that the mutations in the two individual interaction surfaces reduce NER activity in biochemical and cellular systems, and that combining mutations in two domains leads to an additive inhibition of NER, suggesting that they fulfill distinct roles. Our data suggest that the interaction between XPA and RPA32 is important for the initial association of XPA with NER complexes, while the interaction between XPA and RPA70 is needed for structural organization of the complex to license the dual incision reaction. SAXS analysis of complexes of XPA and RPA bound to ss/dsDNA junction substrates reveals the architecture of XPA and RPA in the preincision complex and shows that the two interaction domains between RPA and XPA are located at opposite sides of the two molecules. We propose a structure for the overall NER preincision complex that shows that the two strands of the NER bubble assume a U-shape with the two ss/dsDNA junctions localized in close proximity, with the interaction between XPA and RPA70 as one of the key organizing elements.
A Pluripotent Developmental State Confers a Low Fidelity of Chromosome Segregation
Authors: Deng Chenhui , Ya Amanda , Compton Duane A. , Godek Kristina M. 
Published: March 2022

SummaryHuman pluripotent stem cells (hPSCs) frequently become aneuploid with abnormal chromosome numbers due to mitotic chromosome segregation errors during propagation in culture. Yet, we do not understand why hPSCs exhibit a low mitotic fidelity. Here we investigate the mechanisms responsible for mitotic errors in hPSCs and show that the primary cause is lagging chromosomes with improper merotelic chromosome microtubule attachments in anaphase. Accordingly, we can improve merotelic error correction and reduce lagging chromosome rates in hPSCs using small molecules that prolong mitotic duration or destabilize chromosome microtubule attachments providing chemical strategies to preserve genome stability. Strikingly, we also demonstrate that mitotic error rates correlate with developmental potential decreasing upon differentiation and loss of pluripotency and conversely increasing after reprogramming to a pluripotent state. Thus, chromosome segregation fidelity is inherently low in hPSCs and depends on developmental state in normal human cells.
The RNA Virome of Echinoderms
Authors: Jackson Elliot W. , Wilhelm Roland C. , Buckley Daniel H. , Hewson Ian 
Published: March 2022

AbstractEchinoderms are a phylum of marine invertebrates that include model organisms, keystone species, and animals commercially harvested for seafood. Despite their scientific, ecological, and economic importance, there is little known about the diversity of RNA viruses that infect echinoderms compared to other invertebrates. We screened over 900 transcriptomes and viral metagenomes to characterize the RNA virome of 38 echinoderm species from all five classes (Crinoidea, Holothuroidea, Asteroidea, Ophiuroidea and Echinoidea). We identified 347 viral genome fragments that were classified to genera and families within nine viral orders - Picornavirales, Durnavirales, Martellivirales, Nodamuvirales, Reovirales, Amarillovirales, Ghabrivirales, Mononegavirales, and Hepelivirales. We compared the relative viral representation across three life stages (embryo, larvae, adult) and characterized the gene content of contigs which encoded complete or near-complete genomes. The proportion of viral reads in a given transcriptome was not found to significantly differ between life stages though the majority of viral contigs were discovered from transcriptomes of adult tissue. This study illuminates the biodiversity of RNA viruses from echinoderms, revealing the occurrence of viral groups in natural populations.
The Root of the Red Maple Paradox: Two distinct regeneration mechanisms determine leaf morphology, physiology, and competitive success inAcer rubrum
Authors: Ostrowsky Laura , Ashton Mark 
Published: March 2022

ABSTRACTRed maple is one of the most abundant and wide-ranging tree species in eastern North America and has rapidly increased in abundance over the past century following forest disturbances. This species is both a site- and light-generalist and has the unique ability to regenerate in forms that represent multiple stages of forest succession. However, red maple has modest physiological traits compared to its competitors, including low maximum photosynthetic rate, low photosynthetic nitrogen-use efficiency, and low foliar nutrient content. Red maple’s unremarkable physiology contradicts its competitive success. To untangle this paradox, we examine red maple’s two distinct regeneration mechanisms: seedlings and vegetative sprouts. Red maple can regenerate from seed, but can also sprout clonally from a stump following forest disturbance. We compare the morphology, physiology, and plasticity of these two regeneration mechanisms over 24 years of forest succession using a chronosequence of regenerating forest stands. We found that sprout-origin maples grow on average 6.5x taller and 5.5x faster than seed-origin maples. Sprout-origin trees display greater leaf spectral reflectance in the near-infrared range and greater stomatal density than seed-origin trees, demonstrating vegetative sprouts’ low water-use efficiency. Sprout-origin trees have more robust light-capture traits, including thicker palisade mesophyll than seed-origin trees. Sprouts also have a high plasticity between upper and lower leaves in many morphological and physiological traits, while seed-origin trees exhibited much less plasticity. The two distinct regeneration mechanisms of seed-origin and sprout-origin give rise to red maple trees with dramatically different leaf traits, allowing red maples to regenerate and thrive in a range of ecological conditions. Seed-origin maples are slow-growing, late successional, and shade-tolerant. Sprout-origin maples are fast-growing, early successional, and shade intolerant. This unique bimodal regeneration strategy may explain the red maple paradox and help predict forest composition and structure following disturbance.
CLEAN: Leveraging spatial autocorrelation in neuroimaging data in clusterwise inference
Authors: Park Jun Young , Fiecas Mark 
Published: March 2022

AbstractWhile clusterwise inference is a popular approach in neuroimaging that improves sensitivity, current methods do not account for explicit spatial autocorrelations because most use univariate test statistics to construct cluster-extent statistics. Failure to account for such dependencies could result in decreased reproducibility. To address methodological and computational challenges, we propose a new powerful and fast statistical method called CLEAN (Clusterwise inference Leveraging spatial Autocorrelations in Neuroimaging). CLEAN computes multivariate test statistics by modelling brain-wise spatial autocorrelations, constructs cluster-extent test statistics, and applies a refitting-free resampling approach to control false positives. We validate CLEAN using simulations and applications to the Human Connectome Project. This novel method provides a new direction in neuroimaging that paces with advances in high-resolution MRI data which contains a substantial amount of spatial autocorrelation.
Robust and tunable performance of a cell-free biosensor encapsulated in lipid vesicles
Authors: Boyd Margrethe A. , Thavarajah Walter , Lucks Julius B. , Kamat Neha P. 
Published: March 2022

AbstractCell-free systems have enabled the development of genetically encoded biosensors to detect a range of environmental and biological targets. By encapsulating these systems in synthetic membranes, we can reintroduce features of the cell membrane, including molecular containment and selective permeability, which together could significantly enhance sensing capabilities. Here, we demonstrate robust and tunable performance of an encapsulated fluoride riboswitch inside of lipid vesicles. The riboswitch remains active upon encapsulation in lipid vesicles and responds to fluoride added to the surrounding solution. We find the sensitivity of the encapsulated sensor can be tuned by varying membrane composition. We then show that encapsulation protects the sensor from degradation by the sample and use two types of genetically encoded outputs to detect fluoride in real-world samples. This work establishes the feasibility of vesicle-encapsulated cell-free systems to detect environmentally relevant small molecules.
Social recovery and economy: a thematic analysis of staffs’ experiences with promoting social community participation for residents with co-occurring problems
Authors: Ogundipe Esther , Sælør Knut Tore , Biong Stian 
Published: March 2022

Purpose
This study aims to explore and describe staff working in a Norwegian supportive housing site’s experiences with promoting social community participation for residents with co-occurring problems. The research question addressed was: how does residential support staff experience promoting social community participation for residents with co-occurring problems?

Design/methodology/approach
Nine residential support staff participated in qualitative interviews. All interviews were recorded and transcribed verbatim. The transcripts were analysed using Braun and Clarke's approach to thematic analysis.

Findings
The analysis process resulted in two themes: “It is all about economics” and “Who will pay for it?”

Practical implications
Regarding the Nordic welfare system, the need for a redistribution of financial resources in health services is discussed. The authors recommend that further studies explore people outside the regular health-care system perspectives on how they can contribute to making community inclusion a reality for persons experiencing co-occurring problems.

Originality
This study provides a nuanced understanding of how financial resources can impede or support efforts and opportunities to promote community inclusion for residents experiencing co-occurring problems.
Supply chain insights from social media users’ responses to panic buying during COVID-19: the herd mentality
Authors: Wilk Violetta , Mat Roni Saiyidi , Jie Ferry 
Published: March 2022

PurposeThis study applied the herd mentality theory to explore local and global social media users’ responses to panic buying across the USA, UK and Australia during the COVID-19 crisis to understand the implications on operations and supply chains.Design/methodology/approachA total of 208,806 social media user-generated content (UGC) pieces were collected from Twitter in three countries – the USA, UK and Australia. The analysis of this big qualitative data was performed using machine learning–based software – Leximancer.FindingsPositive and negative sentiment towards panic buying during the COVID-19 crisis was observed in the UGC. No significant differences in social media UGC sentiment between the three countries were found; however, differences did exist in key themes. This suggests that the focus, not the sentiment, of consumers’ responses to panic buying differed across countries. Social media users follow their location-based and topic-consonant social “herd”, rather than the global “herd”.Research limitations/implicationsThis study was the first to show that social media users’ herd mentality differs in a crisis. The herd mentality of social networks is dependent on factors such as the geographic location of the social network (herd), which can differ from the global herd’s reaction, specifically in terms of topics evident in UGC.Practical implicationsOperations and supply chain managers need to include social media UGC analysis in their strategies in crisis management responses. The topics, not the sentiment, of consumers’ responses to panic buying require managerial actions.Originality/valueThis is the first study to show that herd mentality during a crisis, such as COVID-19, is not unidimensional and varies according to the location of the social media network with profound implications for operations and supply chain managers.
Workplace ostracism and job performance: the moderated mediation model of organization-based self-esteem and performance goal orientation
Authors: Kuo Chien-Chih , Wu Chih-Ying 
Published: March 2022

PurposeThis study established and examined a moderated mediation model connecting workplace ostracism with job performance. Drawing from the viewpoint of self-esteem threat, the model posits that the effect of workplace ostracism on job performance is mediated by levels of organization-based self-esteem, while the relationship between workplace ostracism and organization-based self-esteem is moderated by performance goal orientation.Design/methodology/approachMultisource data were collected from 160 employees and their immediate supervisors in Taiwan.FindingsAs predicted in the research model, workplace ostracism was found to decrease organization-based self-esteem and, therefore, hinder employees' job performance. Performance goal orientation was found to buffer the negative effect of workplace ostracism on job performance via organization-based self-esteem.Practical implicationsTo eliminate the negative impact of workplace ostracism, supervisors can help ostracized employees to self-regulate by aligning their performance goal orientation to reduce the perception of self-esteem threat.Originality/valueThis study provides evidence of boundary conditions for the relationship between workplace ostracism and job performance and explores the impact of self-regulation on ostracized employees' organization-based self-esteem and subsequent job performance.
An improved pure pursuit path tracking control method based on heading error rate
Authors: Wang Lihui , Chen ZongLiang , Zhu Wenxing 
Published: March 2022

Purpose
In path tracking, pure pursuit (PP) has great superiority due to its simple control. However, when in agricultural applications, the performance and accuracy of PP are not so well; it cannot be tracked in time has slow convergence, and low tracking accuracy. Furthermore, in some severe driving scenarios, PP is insufficient to convey the effects of the tracking error. This paper aims to propose an autonomous driving controller to improve the PP model based on heading error rate (Improved PP-improved search strategy ant colony optimization [ISSACO]).

Design/methodology/approach
First, the heading error rate is added as the control method in the PP model. Second, the predicted heading error was selected as the objective function; the ISSACO is used to obtain the minimum value of the predicted heading error. A PP controller is integrated with the heading error rate by ISSACO to better deal with tracking error by trading off between PP and heading error rate. Third, the ISSACO was used to obtain the optimal values of PP and heading error rate weight. Finally, the error feedback adaptive dynamic adjustment of the improved algorithm is realized to reduce the convergence time and tracking error.

Findings
The proposed method was tested on a four-wheeled vehicle robot, and the effectiveness of its convergence was proved. Experiments show that the proposed method can effectively reduce the tracking error, increase convergence, then improve the robot’s working quality.

Originality/value
An adaptive improved PP path tracking control is proposed, which considers both heading error rate and parameter uncertainties. The new autonomous controller has a simple structure and is easy to implement. It can be adjusted according to the path tracking status to improve the adaptability of the system.
Social media analytics in hospitality and tourism
Authors: Mirzaalian Farshid , Halpenny Elizabeth 
Published: March 2022

Purpose
The purpose of this paper is to provide a review of hospitality and tourism studies that have used social media analytics to collect, examine, summarize and interpret “big data” derived from social media. It proposes improved approaches by documenting past and current analytic practice addressed by the selected studies in social media analytics.

Design/methodology/approach
Studies from the past 18 years were identified and collected from five international electronic bibliographic databases. Social media analytics-related terms and keywords in the titles, keywords or abstracts were used to identify relevant articles. Book chapters, conference papers and articles not written in English were excluded from analysis. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guided the search, and Stieglitz and Dang-Xuan’s (2013) social media analytics framework was adapted to categorize methods reported in each article.

Findings
The research purpose of each study was identified and categorized to better understand the questions social media analytics were being used to address, as well as the frequency of each method’s use. Since 2014, rapid growth of social media analytics was observed, along with an expanded use of multiple analytic methods, including accuracy testing. These factors suggest an increased commitment to and competency in conducting comprehensive and robust social media data analyses. Improved use of methods such as social network analysis, comparative analysis and trend analysis is recommended. Consumer-review networks and social networking sites were the main social media platforms from which data were gathered; simultaneous analysis of multi-platform/sources of data is recommended to improve validity and comprehensive understanding.

Originality/value
This is the first systematic literature review of the application of social media analytics in hospitality and tourism research. The study highlights advancements in social media analytics and recommends an expansion of approaches; common analytical methods such as text analysis and sentiment analysis should be supplemented by infrequently used approaches such as comparative analysis and spatial analysis.