bluuebunny/crossref_metadata_2025_split huggingface dataset:
First detection of Hedgehog coronavirus 1 in Poland
Authors: Pomorska-Mól Małgorzata , Ruszkowski Jakub J. , Gogulski Maciej , Domanska-Blicharz Katarzyna 
Published: February 2022

AbstractHedgehogs are common in the majority of European countries and are known to host various pathogens, including viruses. The recent discovery of MERS-related coronaviruses (CoVs) in hedgehogs from Germany, France, the UK, China, and Italy suggests that hedgehogs may represent a wild reservoir of betacoronaviruses. This study reports the first detection and characterization of novel betacoronovirus, subgenus Merbecovirus in wild hedgehogs in Poland. The CoV RNA was detected in 10 out of 40 hedgehogs’ rectal swabs and in 1 out of 18 samples of the lung. No viral RNA was identified in the duodenum and kidney. There was no significant relationship between clinical status, gender, hedgehogs' age, and coronaviral RNA detection. Phylogenetic analysis showed that CoVs detected in our study grouped together with other representatives of Hedgehog coronavirus 1 species identified in Western Europe. Our findings provide further evidence that hedgehogs are a natural reservoir of Merbecovirus. Considering the high mutation rate of CoVs and their potential for crossing interspecies barriers, the proper management of hedgehogs admitted to wildlife rehabilitation centres is needed. It cannot be excluded that merbecovirus strains detected in hedgehogs may recombine with other CoVs leading to new viruses with potential for interspecies transmission.
Data-driven testing program improves detection of COVID-19 cases and reduces community transmission
Authors: Krieg Steven J. , Avendano Carolina , Grantham-Brown Evan , Lilienfeld Asbun Aaron , Schnur Jennifer J. , Miranda Marie Lynn , Chawla Nitesh V. 
Published: February 2022

AbstractCOVID-19 remains a global threat in the face of emerging SARS-CoV-2 variants and gaps in vaccine administration and availability. In this study, we analyze a data-driven COVID-19 testing program implemented at a mid-sized university, which utilized two simple, diverse, and easily interpretable machine learning models to predict which students were at elevated risk and should be tested. The program produced a positivity rate of 0.53% (95% CI 0.34–0.77%) from 20,862 tests, with 1.49% (95% CI 1.15–1.89%) of students testing positive within five days of the initial test—a significant increase from the general surveillance baseline, which produced a positivity rate of 0.37% (95% CI 0.28–0.47%) with 0.67% (95% CI 0.55–0.81%) testing positive within five days. Close contacts who were predicted by the data-driven models were tested much more quickly on average (0.94 days from reported exposure; 95% CI 0.78–1.11) than those who were manually contact traced (1.92 days; 95% CI 1.81–2.02). We further discuss how other universities, business, and organizations could adopt similar strategies to help quickly identify positive cases and reduce community transmission.
Adaptive laboratory evolution in S. cerevisiae highlights role of transcription factors in fungal xenobiotic resistance
Authors: Ottilie Sabine , Luth Madeline R. , Hellemann Erich , Goldgof Gregory M. , Vigil Eddy , Kumar Prianka , Cheung Andrea L. , Song Miranda , Godinez-Macias Karla P. , Carolino Krypton , Yang Jennifer , Lopez Gisel , Abraham Matthew , Tarsio Maureen , LeBlanc Emmanuelle , Whitesell Luke , Schenken Jake , Gunawan Felicia , Patel Reysha , Smith Joshua , Love Melissa S. , Williams Roy M. , McNamara Case W. , Gerwick William H. , Ideker Trey , Suzuki Yo , Wirth Dyann F. , Lukens Amanda K. , Kane Patricia M. , Cowen Leah E. , Durrant Jacob D. , Winzeler Elizabeth A. 
Published: February 2022

AbstractIn vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in Saccharomyces cerevisiae. Sequence analysis identified many genes contributing to the resistance phenotype as well as numerous amino acids in potential targets that may play a role in compound binding. Our work shows that compound-target pairs can be conserved across multiple species. The set of 25 most frequently mutated genes was enriched for transcription factors, and for almost 25 percent of the compounds, resistance was mediated by one of 100 independently derived, gain-of-function SNVs found in a 170 amino acid domain in the two Zn2C6 transcription factors YRR1 and YRM1 (p < 1 × 10−100). This remarkable enrichment for transcription factors as drug resistance genes highlights their important role in the evolution of antifungal xenobiotic resistance and underscores the challenge to develop antifungal treatments that maintain potency.
Urban land expansion: the role of population and economic growth for 300+ cities
Authors: Mahtta Richa , Fragkias Michail , Güneralp Burak , Mahendra Anjali , Reba Meredith , Wentz Elizabeth A. , Seto Karen C. 
Published: February 2022

AbstractGlobal urban populations are projected to increase by 2.5 billion over the next 30 years. Yet, there is limited understanding of how this growth will affect urban land expansion (ULE). Here, we develop a large-scale study to test explicitly the relative importance of urban population and Gross Domestic Product (GDP) growth in affecting ULE for different regions, economic development levels and governance types for 300+ cities. Our results show that population growth, more than GDP, is consistently the dominant determinant of ULE during 1970–2014. However, the effect of GDP growth on ULE increases in importance after 2000. In countries with strong governance, economic growth contributes more to ULE than population growth. We find that urban population growth and ULE are correlated but this relationship varies for countries at different developmental stages. Lastly, this study illustrates that good governance is a necessary condition for economic growth to affect ULE.
Relationship Between Cognitive Functions and Multilevel Language Processing: Data From Chinese Speakers With Aphasia and Implications
Authors: Wong Wing Sze Winsy , Law Sam Po 
Published: February 2022

Purpose:
This study aims to investigate the relationship between nonverbal cognitive functions and language processing of people with aphasia (PWA) by taking a data-driven approach, as well as multiple cognitive components and multilevel linguistic perspectives. It is hypothesized that language performance is differentially associated with cognitive processing of PWA, with executive functions (EFs) playing a stronger role in language tasks with increasing linguistic complexity.

Method:
A language battery assessing word comprehension/production, sentence comprehension, and discourse production, together with a series of nonlinguistic cognitive tasks targeting simple/complex attention, short-term/working memory, or EFs, was administered to 53 Cantonese-speaking PWA. Cognitive factors extracted from principal component analysis applied to the cognitive battery served as predictors in four multiple regression analyses to predict PWA's performance at various linguistic levels.

Results:
Two cognitive factors, representing (a) simple attention and memory and (b) EF, were extracted. The former predicted performance in word processing tasks, whereas EF significantly predicted performance in all language tasks with increasing contribution as a function of linguistic complexity.

Conclusion:
The results based on Chinese PWA provide comprehensive evidence for the view that language performance is the end product of interaction between linguistic and nonlinguistic functions and have clear implications for clinical management of PWA.
Adaptive event‐triggered output‐feedback control for switched nonlinear systems with time‐varying delays: A modified MDADT method
Authors: Kong Jie , Niu Ben , Zhang Jia‐Ming , Wang Zhen‐Hua , Wang Huan‐Qing 
Published: February 2022

AbstractIn this paper, the issue of adaptive event‐triggered output‐feedback control for a class of switched nonlinear systems with time‐varying delays is investigated. By adopting the mode‐dependent average dwell time (MDADT) method and the backstepping technique, an adaptive neural output‐feedback control strategy is proposed for the switched system with event‐triggered mechanism. In the process of controller design, an intelligent approximation technique and a switched filter are introduced to overcome the difficulties caused by the unknown nonlinear functions and the immeasurable states, respectively. Moreover, the appropriate Lyapunov–Krasovskii functionals are designed to compensate the effects of time delays. It is proved that the proposed control strategy guarantees that all the signals in the switched closed‐loop systems are bounded under arbitrary switchings with MDADT. In the end, two simulation examples are provided to illustrate the feasibility of the developed control strategy.
Super‐resolution reconstruction method of infrared images of composite insulators with abnormal heating based on improved SRGAN
Authors: Zhong Zheng , Chen Yuan , Hou Sizu , Wang Bowen , Liu Yunpeng , Geng Jianghai , Fan Shuochao , Wang Dewen , Zhang Xu 
Published: February 2022

AbstractAbnormal heating of composite insulators on ultra‐high voltage (UHV) transmission lines is widespread under high humidity and heat in southern China. The infrared imaging technology can be used of quickly and effectively detect insulators with abnormal heating and determine their defect types. However, it may cause misjudgement when the infrared images are not clear. A super‐resolution reconstruction method of infrared images of composite insulators with abnormal heating based on improved super‐resolution generative adversarial networks (SRGAN) is proposed in this paper, and the dense residual network in SRGAN is perfected by introducing the residual channel attention (ResCA). This method overcomes the problems that the resolution of images reconstructed by traditional methods is not significantly improved, and images are too smooth, and the edge details are easily lost. Compared with the traditional methods, the five reference‐free image quality evaluation indexes of the image reconstructed by the improved SRGAN are increased by −0.73% to 63.84%. Further the effectiveness and superiority of the improved SRGAN are verified by comparing the changes in the distribution of grey values of infrared images before and after reconstruction. Finally, the improved SRGAN is used to perform super‐resolution reconstruction of the low‐resolution infrared image examples.
Type III radio bursts and excitation of Langmuir waves by energetic electrons
Authors: Mann G. , Vocks C. , Warmuth A. 
Published: February 2022

Context.Solar activity occurs not only in terms of the well-known 11-year Sun spot cycle but also in terms of short-lived phenomena as radio bursts. For instance, type III radio bursts are the most common phenomenon of this activity in the Sun’s radio radiation. In dynamic radio spectra, they appear as short-lived stripes of enhanced radio emission rapidly drifting from high to low frequencies. They are regarded as the radio signature of beams of energetic electrons travelling along magnetic field lines in the corona. The radio emission is thought to be plasma emission, that is to say the radio emission happens near the electron plasma frequency and/or its harmonics. Plasma emission means, that energetic electrons excite Langmuir waves, which convert into radio waves.Aims.Initially, energetic electrons are injected in a small region in the corona. Due to their spatio-temporal evolution, they develop a beam-like velocity distribution function (VDF), which is able to excite Langmuir waves. The aim of the paper is to study the spatio-temporal behaviour of the generation of Langmuir waves under coronal cirumstances and its effect on type III radio bursts.Methods.The generation of Langmuir waves is treated by means of the Maxwell-Vlasov equations. The results are discussed by employing plasma parameters usually found in the corona, for instance at the 150 MHz level.Results.The Langmuir waves associated with the type III bursts are not generated by a monoenergetic electron beam, but by a population of energetic electrons with a broad velocity distribution. Hence, the Langmuir waves are produced by different parts of the energetic electron population at different times and positions.Conclusions.In the case of type III bursts, the velocities derived from their drift rates in dynamic radio spectra are not the velocities of electrons, which generate the onset of the type III burst at a given frequency. That can lead to an apparent accelerated motion of the type III radio burst source.
Construction Industry–Associated Penetrating Craniocerebral Injuries
Authors: Su Jiahao , Liang Sitao , Lin Qichang , Hu Zihui , Liao Wei , Zhu Yonghua 
Published: February 2022

Abstract
Background Various high-energy tasks in the construction industry can lead to craniocerebral injuries. Construction industry–associated penetrating craniocerebral injuries due to metal foreign bodies have unique characteristics. However, no norms exist for removing metal foreign bodies and preventing secondary trauma. This study aimed to explore the characteristics and treatment of construction industry–associated penetrating craniocerebral injuries due to metal foreign bodies.
Methods Data of patients who suffered from penetrating injuries due to metal foreign bodies and were treated in the Zhongshan People's Hospital from 2001 to 2021 were collected based on the causes of injuries to explore disease characteristics and therapeutic effects.
Results A total of six patients with penetrating craniocerebral injuries due to metal foreign bodies, who underwent surgeries, were included in the study. Five patients recovered well after the surgery, and one patient died. In four patients, intracranial infection complicated the course after surgery, and two patients had delayed intracranial hematoma.
Conclusion Patients with construction industry–associated penetrating craniocerebral injuries due to metal foreign bodies are prone to coma and intracranial vascular injuries. Early surgical removal and prevention of intracranial infection are key to achieving good therapeutic effects.
Glycosite-deleted mRNA of SARS-CoV-2 spike protein as a broad-spectrum vaccine
Authors: Wu Chung-Yi , Cheng Cheng-Wei , Kung Chih-Chuan , Liao Kuo-Shiang , Jan Jia-Tsrong , Ma Che , Wong Chi-Huey 
Published: February 2022

Significance
To contain the spread of SARS-CoV-2, the mRNA vaccine of viral spike protein has proven to be highly effective, although the efficacy against the emerging variants is decreasing. Here, we show that the mRNA of spike protein with deletion of glycosites in the RBD or especially the S2 domain to expose more conserved epitopes can be used as a broadly protective vaccine against the wild type and variants of concern. The spike protein translated from such mRNA was not properly folded, and thus induced cell apoptosis and a strong T cell response. Our findings demonstrate the importance of the glycosylation effect on the development of broadly protective mRNA vaccines.
Sinful wives and queens
Authors: Alfie Fabian 
Published: February 2022

AbstractThe author of theDivine Comedy, Dante Alighieri (1265–1321), dealt with “sodomites” twice in his masterpiece, once inInfernoand again inPurgatorio. In their examinations of the passage inInferno, literary critics have typically conflated the modern-day definition of “homosexual” with the medieval “sodomite.” In order to see how Dante viewed non-normative sexuality accurately, however, it is necessary first to uncouple the medieval term “sodomite” from today’s term, “homosexual,” and to apply instead the medieval definition of the former. Numerous sources of Dante’s time indicate that “sodomy” did not mean, strictly speaking, same sex practices between men, but rather it encompassed a wide array of sexual activities. The same is probably true of the sodomites in Dante’sInferno, some of whom might not have bedded other men. Examination of the passage inPurgatorio, moreover, indicates a greater degree of subtlety in Dante’s thought regarding non-normative sexual attraction.
Plurilingualism, multimodality and machine translation in medical consultations
Authors: Piccoli Vanessa 
Published: February 2022

Abstract
This contribution deals with the use of Google Translate as one among many resources that participants mobilize to
overcome the language barrier in plurilingual medical consultations. It is grounded on a two-hour interaction involving a family
of Albanian asylum seekers newly arrived in France and a French general practitioner. To reach mutual comprehension, participants
rely on the mediation of a lay interpreter (one of the family’s children) who translates for the doctor and the other family
members. In this interaction, English is used as a lingua franca, while machine translation is conducted between French and
Albanian. The analysis will focus on the interactional work that participants accomplish in order to: (1) propose or solicit the
use of Google Translate and make the computer accessible to all participants; (2) detect and repair misunderstandings caused by an
unsuitable translation.
Applying augmented feedback in basketball training facilitates improvements in jumping performance
Authors: Leukel Christian , Gollhofer Albert 
Published: February 2022

ABSTRACTAugmented feedback, which is feedback about movement characteristics provided by an external source, can facilitate performance improvements. Results from recent studies, in which information about the jumping height were presented, indicated increased jumping performance due to augmented feedback. In the present study we aimed to utilize augmented feedback about the jumping height in regular basketball training. Therefore, augmented feedback was implemented and part of the training regime, and information about the jumping height was displayed while subjects performed catch and shoot exercises with the basketball. 18 subjects (9 with augmented feedback, 9 without augmented feedback) practiced for 3 weeks (9 training sessions). The subjects receiving augmented feedback, but not subjects in the control group, displayed increased jumping heights of countermovement‐jumps and drop‐jumps after the training. The ground contact times of countermovement‐jumps and drop‐jumps were not significantly changed after training. The number of successful hits, indicating ball performance, did also not change after training. Thus augmented feedback had no detrimental effect on sport‐specific performance. The unchanged ground contact times of drop‐jumps in combination with increased jumping heights indicate increased efficiency of stretch shortening cycle contractions. According to the positive effect of augmented feedback on jumping performance and the simplicity with which it was integrated into the training regime we recommend this method for regular basketball training.Highlights
Augmented feedback about the jumping height in basketball training facilitated jumping height of countermovement‐jumps and drop‐jumps.
The ground contact times were not altered, suggesting increased efficiency of the stretch‐shortening cycle during jumping.
According to the positive effect and its simple implementation augmented feedback is recommended for regular basketball training.
Body-worn enzymatic biofuel cell with automated pencil drawn bioelectrodes for energy harvesting from human sweat
Authors: U S Jayapiriya , Goel Sanket 
Published: February 2022

Abstract
Epidermal bioelectronics is a field of integrated electronic system which consists of conductive materials used in a variety of applications with external energy supply. Arguably, biofuel cells, which can produce energy directly from the physiological environment, are the best power sources for wearable bioelectronics. Optimized electrode materials, which are highly flexible, light-weight and disposable, are an key features to be considered. In this work, a novel method of developing enzymatic bioelectrode using automated pencil strokes for biofuel cell application is discussed. The developed lactate/O2 biofuel cell shows a maximum power density of 11.5 µW cm−2 and 7.8 µW cm−2 in the presence of lactate and human sweat, respectively with high open-circuit voltage. This cost-effective and straightforward electrode fabrication technique delivering enhanced performance without any metallic catalyst is commendable for future wearable devices.
SAT-assembly: a new approach for designing self-assembling systems
Authors: Russo John , Romano Flavio , Kroc Lukáš , Sciortino Francesco , Rovigatti Lorenzo , Šulc Petr 
Published: February 2022

Abstract
We propose a general framework for solving inverse self-assembly problems, i.e. designing interactions between elementary units such that they assemble spontaneously into a predetermined structure. Our approach uses patchy particles as building blocks, where the different units bind at specific interaction sites (the patches), and we exploit the possibility of having mixtures with several components. The interaction rules between the patches is determined by transforming the combinatorial problem into a Boolean satisfiability problem (SAT) which searches for solutions where all bonds are formed in the target structure. Additional conditions, such as the non-satisfiability of competing structures (e.g. metastable states) can be imposed, allowing to effectively design the assembly path in order to avoid kinetic traps. We demonstrate this approach by designing and numerically simulating a cubic diamond structure from four particle species that assembles without competition from other polymorphs, including the hexagonal structure.
Bone anatomical landmark localization with cascaded spatial configuration network
Authors: Zhao Qijie , Zhu Junhao , Zhu Junjun , Zhou Anwen , Shao Hui 
Published: February 2022

Abstract
Accurate localization of bone anatomical landmarks in medical images is of great significance for decision-making in surgical plans and orthopedic surgery visual navigation systems development. However, due to the high dimensionality and large size of medical images, current automatic anatomical landmarks detection methods still have issues in terms of accuracy, robustness, and efficiency. To improve the accuracy of bone anatomical landmark detection in medical images, a new network model with a two-step strategy (coarse localizing and fine localizing) was proposed in this study. By combining fully convolutional neural networks and the heatmap regression model, a cascaded spatial configuration network was designed to combine the global and local features of 3D image features and localize anatomical landmarks stepwise. The model was evaluated with a collected knee CT image dataset and a published spine CT image dataset. The results were compared to existing state-of-the-art models. The proposed method outperformed other models with an average error of 1.31 mm for knee landmarks and 5.31 mm for the localization of spine landmarks. The outlier rates at error radius 3 mm, 5 mm, and 7 mm are also smaller compared with other models, indicating good robustness of the model. Our proposed method provides a new neural network model with reasonably good accuracy and robustness with a limited computational cost for landmark localization tasks.