bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-covalent SARS-CoV-2 Mpro inhibitors developed from in silico screen hits
Authors: Rossetti Giacomo G. , Ossorio Marianna A. , Rempel Stephan , Kratzel Annika , Dionellis Vasilis S. , Barriot Samia , Tropia Laurence , Gorgulla Christoph , Arthanari Haribabu , Thiel Volker , Mohr Peter , Gamboni Remo , Halazonetis Thanos D. 
Published: February 2022

AbstractMpro, the main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is essential for the viral life cycle. Accordingly, several groups have performed in silico screens to identify Mpro inhibitors that might be used to treat SARS-CoV-2 infections. We selected more than five hundred compounds from the top-ranking hits of two very large in silico screens for on-demand synthesis. We then examined whether these compounds could bind to Mpro and inhibit its protease activity. Two interesting chemotypes were identified, which were further evaluated by characterizing an additional five hundred synthesis on-demand analogues. The compounds of the first chemotype denatured Mpro and were considered not useful for further development. The compounds of the second chemotype bound to and enhanced the melting temperature of Mpro. The most active compound from this chemotype inhibited Mpro in vitro with an IC50 value of 1 μM and suppressed replication of the SARS-CoV-2 virus in tissue culture cells. Its mode of binding to Mpro was determined by X-ray crystallography, revealing that it is a non-covalent inhibitor. We propose that the inhibitors described here could form the basis for medicinal chemistry efforts that could lead to the development of clinically relevant inhibitors.
Introducing a novel beta-ray sensor based on polycarbonate/bismuth oxide nanocomposite
Authors: Safdari Seyed Musa , Malekie Shahryar , Kashian Sedigheh , Akbari Morteza 
Published: February 2022

AbstractIn this research, for the first time, the polycarbonate/bismuth oxide (PC–Bi2O3) composite was studied as a beta-ray sensor using a pure beta-emitter 90Sr source. Firstly, the range and stopping power of the electrons in the composite at various loadings of 0, 10, 20, 30, 40, and 50 wt% were calculated using the ESTAR program. Results of simulation demonstrated that the concentration of the heavy metal oxide particles into the polymer matrix played an important role in evaluating the range and stopping power of the electrons in the composite. Secondly, at the experimental phase, the pure Polycarbonate and 50 wt% PC–Bi2O3 nanocomposite with dimensions of 4 × 4 × 0.1 cm3 were prepared and irradiated by 90Sr. Also, current–voltage (I–V) plot exhibited linear response ranging from 100 to 1000 V at the fixed source‐to‐surface distance (SSD). Then the amount of electric current as the sensor response was measured in various dose rates at the fixed voltage of 400 V for the pure Polycarbonate and 50 wt% PC–Bi2O3 nanocomposite using an electrometer, in which results showed that the sensitivities were found as 20.3, and 33.3 nC mSv−1 cm−3, respectively. This study showed that this composite could serve as a novel beta-ray sensor.
Ubiquitous karst hydrological control on speleothem oxygen isotope variability in a global study
Authors: Treble Pauline C. , Baker Andy , Abram Nerilie J. , Hellstrom John C. , Crawford Jagoda , Gagan Michael K. , Borsato Andrea , Griffiths Alan D. , Bajo Petra , Markowska Monika , Priestley Stacey C. , Hankin Stuart , Paterson David 
Published: February 2022

AbstractSpeleothem oxygen isotopic (δ18O) records are used to reconstruct past hydroclimate yet records from the same cave do not always replicate. We use a global database of speleothem δ18O to quantify the replicability of records to show that disagreement is common worldwide, occurs across timescales and is unrelated to climate, depth or lithology. Our global analysis demonstrates that within-cave differences in mean speleothem δ18O values are consistent with those of dripwater, supporting a ubiquitous influence of flowpaths. We present a case study of four new stalagmite records from Golgotha Cave, southwest Australia, where the isotopic differences between them are informed by cave monitoring. It is demonstrated that karst hydrology is a major driver of within-cave speleothem and dripwater δ18O variability, primarily due to the influence of fractures on flowpaths. Applying our understanding of water movement through fractures assists in quantitative reconstruction of past climate variability from speleothem δ18O records.
Carbide coating on nickel to enhance the stability of supported metal nanoclusters
Authors: Chesnyak Valeria , Stavrić Srdjan , Panighel Mirco , Comelli Giovanni , Peressi Maria , Africh Cristina 
Published: February 2022

Cobalt (Co) on bare Ni(100) surface forms 2D islands which are unstable and completely dissolve into bulk at 250 °C. Carbide coating favors the formation of 3D Co nanoclusters and acts as a protective layer against Co dissolution.
The Effects of Virtual Assessment on Capturing Skill Growth in Children With Hearing Loss
Authors: Lund Emily , Werfel Krystal L. 
Published: February 2022

Purpose:
The purpose of this study is to evaluate the effects of switching from in-person assessment to virtual assessment during the COVID-19 pandemic on the growth trajectories of children with hearing loss who are learning spoken language.

Method:
Sixty-eight children with typical hearing, 44 children with cochlear implants, and 47 children with hearing aids were assessed with a norm-referenced measure of receptive vocabulary, a criterion-referenced measure of phonological awareness, and a criterion-referenced measure of conceptual print knowledge at least 4 times, at 6-month intervals, between the ages of 4 and 6 years. Of those participants, 26 children with typical hearing, 13 children with cochlear implants, and 13 children with hearing aids entered virtual testing as a result of the COVID-19 pandemic. The slopes of growth for children who entered virtual testing were compared to their own slopes prepandemic and to the growth slopes of children who completed all testing in-person, prepandemic.

Results:
Within-subject comparisons across all measures did not show a change in growth slopes prepandemic to postpandemic. For the measure of conceptual print knowledge, children who were tested during the pandemic showed slower overall growth than children who were tested prepandemic. No effects of hearing status were found across growth on any measure.

Conclusion:
These preliminary data support the use of virtual assessment to measure growth in receptive vocabulary, phonological awareness, and conceptual print knowledge in children with hearing loss learning spoken language.
Profiling Bilingual Children: Using Monolingual Assessment to Inform Diagnosis
Authors: Rose Karen , Armon-Lotem Sharon , Altman Carmit 
Published: February 2022

Purpose:
Diagnostic tools developed for monolinguals are frequently used for bilingual linguistic assessment. The absence of evaluation criteria for using monolingual norms for bilinguals contributes to inconsistent diagnostic procedures, impacting research and clinical practice. This study considers the reliance on monolingual tools to assess the heritage language to identify bilingual atypical language development (ALD) even when bilingual norms are available for the societal language.

Method:
One hundred thirty-one English–Hebrew bilingual children aged 5;6–5;11 (years;months) were assessed using diagnostic tools. Bilingual standards are available for the societal language but not for the heritage language. Fifteen English–Hebrew bilingual children were suspected of ALD. They were individually compared with 116 typically developing bilingual peers. The Core Language Score and seven subtest standardized scores of the Clinical Evaluation of Language Fundamentals Preschool–Second Edition were analyzed in the heritage language, English.

Results:
Results revealed that a composite score used for differential diagnosis in monolingual children cannot be relied upon for bilingual children. Measurements vary in their diagnostic accuracy, with Concepts and Following Directions (comprehension of instructions), Receptive and Expressive Word Classes (lexicon), and Sentence Repetition (syntax) being the most promising for identifying ALD in bilingual children. Lastly, bilingual children's age of onset of bilingualism must be considered in the analysis of linguistic outcomes.

Conclusions:
Findings elucidate that monolingual assessments for heritage speakers must consider bilingual models of development to ensure a reliable and informative diagnosis. Interacting factors, such as reliance on language-specific knowledge and the recruitment of other nonlinguistic processing skills, may influence a measurement's sensitivity. The findings are pertinent to the practice of speech-language pathologists, informing evidence-based assessment procedures for bilingual children. A group study to determine whether the suggested bilingual standards can identify ALD with acceptable specificity and sensitivity is now recommended.
Voices From the Field: Strategies for Effective Telepractice for Children With Autism Who Use Augmentative and Alternative Communication
Authors: Biggs Elizabeth E. , Therrien Michelle C. S. , Snodgrass Melinda R. , Douglas Sarah N. 
Published: February 2022

Purpose:
Providing telepractice services to young children with autism who use augmentative and alternative communication (AAC) can present many challenges for speech-language pathologists (SLPs). At the same time, telepractice can be a valuable service delivery option with unique benefits, such as improving partnerships with families, integrating AAC services with other educational services, promoting communication skills in natural settings, and addressing the need for clinicians with AAC experience in locations that have been underserved. The purpose of this study was to learn from SLPs utilizing telepractice about the strategies they found most effective in serving children learning to use aided AAC, particularly young children with autism.

Method:
Participants were 230 SLPs who responded to a national survey about using telepractice to serve children who use aided AAC. The survey occurred during the COVID-19 pandemic, when more SLPs than ever before were navigating how to use telepractice effectively. Open-ended survey questions asked SLPs about advice and strategies they found to increase effectiveness. These responses were analyzed using an iterative, team-based approach to qualitative content analysis.

Results:
SLPs raised strategies to support the effectiveness of telepractice in three areas: (a) Be strategic about how to provide services. (b) Communicate and collaborate with others. (c) Keep learning and hold onto reasonable expectations.

Conclusions:
Telepractice can be an advantageous service delivery option for SLPs serving children with autism who use aided AAC. These strategies can help SLPs navigate challenges and support the effectiveness of their services.
An adaptive nonlinear filter with missing measurements compensation for manoeuvring target tracking
Authors: Lv Runyan , Cai Yunze , Dong Xiangxiang 
Published: February 2022

AbstractTo solve the problem of missing measurements in highly manoeuvring target tracking, an expected‐mode‐augmentation‐based unscented Kalman filter with missing measurements compensation (EMA‐MMCUKF) is designed based on the variable‐structure multiple model method. In the proposed EMA‐MMCUKF, the random missing measurements are described by the Bernoulli distribution, and the one‐step prediction is used as the compensation. Based on the proposed EMA‐MMCUKF, a Bayesian estimation‐based expected‐mode‐augmentation unscented Kalman filter with missing measurements compensation (BE‐EMA‐MMCUKF) is proposed for adaptive estimation of the sensor measurement reception rate, where the unknown measurement reception rate can be estimated by fully utilising prior information. Simulation results demonstrate that the proposed EMA‐MMCUKF can effectively track the manoeuvring target at different measurement reception rates. Moreover, when the sensor prior information differs significantly from the true measurement reception rate, the proposed BE‐EMA‐MMCUKF can effectively estimate the unknown sensor measurement reception rate and improve the accuracy of manoeuvring target tracking compared with non‐estimation of the sensor measurement reception rate.
Multivariate time series classification using kernel matrix
Authors: Sun Jiancheng , Niu Huimin , Tu Zongqing , Wu Zhinan , Chen Si 
Published: February 2022

AbstractMultivariate time series (MTS) classification is a fundamental problem in time series mining, and the approach based on covariance matrix is an attractive way to solve the classification. In this study, it is noted that a traditional covariance matrix is only a particular form of kernel matrices, and then presented a classification method for MTS. First, the Gaussian kernel matrix is employed to replace the traditional covariance matrix. Then the kernel matrix is mapped into the tangent space of Riemannian manifold. Finally, the classification is implemented by choosing a classification algorithm. The experimental results show that the classification performance based on the Gaussian kernel matrix outperforms the other two methods, which indicates that an appropriate kernel function is an essential factor in improving the classification performance.
Novel adaptive reclosing scheme of MMC‐HVDC transmission lines based on phase synchronization compensation control
Authors: Zhang Jingru , He Baina , Cui Rongxi , He Xingmin , Dong Yanchen 
Published: February 2022

AbstractModular multilevel converter based on high voltage director current is important for large‐scale power regional interconnection. Adaptive reclosing is critical to improving the safety and economy of power transmission. The time‐frequency characteristics during fault clearance are analysed by Hilbert transform to suppress over‐voltage or over‐current resulting from short‐circuit fault. A phase synchronization compensation control algorithm is designed based on voltage and current through the virtual network. The rapid suppression of fault overvoltage is achieved by synchronously switching network attributes. Furthermore, the line recovery voltage is introduced into the fault property identification. The proposed adaptive reclosing scheme with high‐speed dynamics can raise the comprehensive benefits of the power system. Studies have verified that phase synchronization compensation control can effectively reduce the impact of oscillation. Moreover, permanent and transient faults can be quickly and reliably discriminated during de‐ionization by multi‐device coordination, which is earlier than the traditional adaptive reclosing scheme. It provides a basis for the fault recovery optimization strategy coordinating with multiple equipment.
Inadequate dataset learning for major depressive disorder MRI semantic classification
Authors: Liu Jie , Dey Nilanjan , Crespo Ruben González , Shi Fuqian , Liu Chanjuan 
Published: February 2022

AbstractPredicting patients with major depression (MDD) is currently a difficult task. Magnetic resonance imaging (MRI) data analysis may provide insight into individual patient responses, allowing for more customized treatment decisions. Due to the absence of brain MRI data for MDD patients, a transfer learning (TL) method developed is used using calculation criteria. Combining an Inception‐v3 neural network with a typical pre‐trained neural network, the move learning‐based Inception‐v3 was proposed for the classification of MDD MRI datasets. An experiment was performed on the classification of eight semantic emotions (defined by IMAPS). Compared to other methods, the proposed method performs high efficiency for 90–10% and 80–20% (positive and negative classes), normal (N), unnormal (UN), and average/total sets, and for 70–30%, accuracy (A) is 92.90%, area under the curve (AUC) is 94.23%, and average precision score (APS) is 95.75%. Individual patients' responses to emotional stimulation can be predicted using the proposed methods, which can provide guidance in diagnosis and prognosis.
A generalized probabilistic multi‐objective method for optimal allocation of soft open point (SOP) in distribution networks
Authors: Rezaeian‐Marjani Saeed , Galvani Sadjad , Talavat Vahid 
Published: February 2022

AbstractSoft open point (SOP) as a novel power electronics‐based device has been introduced to control active power flow, compensate reactive power, and regulate voltage for flexible operation of distribution networks. The increasing penetration of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV) units with uncertain outputs in distribution networks increases the importance of optimal and robust allocation of SOP against multiple uncertainties to improve the performance of these networks. In this paper, a probabilistic multi‐objective framework is proposed for optimal allocation of SOP in RESs included distribution networks. A novel SOP modeling in the forward‐backward load flow method without any simplification is introduced. In addition, this study investigates the impact of various correlation levels between uncertain input variables in the problem. The multi‐objective particle swarm optimization (MOPSO) method is used to extract Pareto‐based solutions set considering the expected value of active power losses, feeder load balancing index (LBI), and investment cost of SOP as objective functions. Also, the Latin hypercube sampling (LHS) and Cholesky decomposition methods are implemented to uncertainties modeling and handling the correlations, respectively. The results of the proposed study framework are argued on the IEEE 33‐node and the IEEE 118‐node distribution networks.
Two‐stage voltage control strategy in distribution networks with coordinated multimode operation of PV inverters
Authors: Li Shiwei , Wu Hongbin , Zhou Yiyao , Bi Rui , Qi Xianjun , Sun Ming , Xu Bin 
Published: February 2022

AbstractTo solve the problems of voltage violation and fast voltage fluctuation caused by photovoltaic (PV) grid connections in distribution networks, a two‐stage coordinated voltage control strategy for PV inverters with multimode coordinated operation in distribution networks (DNs) is proposed. It is based on the characteristics of PV inverters that can be regulated rapidly and continuously. First, the voltage control process is divided into two control stages according to the voltage change rate, and the corresponding voltage control models are established. Then, the operating modes of PV inverters are classified into three modes: economic prevention, economic control, and efficient control. Different operating modes are used to adapt to the two‐stage voltage control. Finally, a voltage fast control solution algorithm is proposed, which considers adaptive time delays and combines local measurement, prediction, and communication information to update control commands. The effectiveness and feasibility of the proposed voltage control strategy were demonstrated through simulation tests on a real 10‐kV line with a high PV penetration rate in the Anhui province of China. The results show that the proposed strategy can prevent voltage violation and sudden changes and can smooth out voltage fluctuation.
An environmental‐friendly green energy system with a real wind speed prediction based on innovative hierarchical forecast error correction model
Authors: Akhtar Iram , Altamimi Abdullah , Khan Zafar Ali , Kirmani Sheeraz 
Published: February 2022

AbstractPrecise forecasting of wind speed is an important technology to permit the reliable and efficient operation of sustainable energy system. Here, the authors offer an effective wind speed prediction (EWSP) technique based on advanced forecast error correction model (AFECM). Ramapuram, Chennai is selected to fit the wind‐energy‐based systems and ENNORE thermal power station, Chennai is selected to decrease the carbon footprints. In the proposed technique, the error correction model is made to produce the final forecast. The proposed wind speed prediction based on innovative hierarchical forecast error correction model reveals that with the proposed AFEC+ MSVM technique, the hourly average RMSEs, MADs, MSEs and MAPEs in Delivery 24 are decreased by 2.277%, 1.012%, 0.234%, and 1.245 % as compared to the normal SVM technique, while with AFEC+SVM method, average errors in RMSEs, MADs, MSEs and MAPEs in Delivery‐24 are reduced by 3.385%, 2.056%, 1.956% and 2.546% as compared with the normal SVM technique, whereas the forecasting errors with AFEC+BP method, the middling errors in RMSEs, MADs, MSEs and MAPEs in Delivery‐24 are decreased by 2.867%, 1.654%, 1.834% and 2.298%, compared with simple BP method. The study displays that 1,485,550 kg CO2 emission is decreased from the ENNORE thermal power plant.
Calibration of the GOES 6–16 high-energy proton detectors based on modelling of ground level enhancement energy spectra
Authors: Hu Shaowen , Semones Edward 
Published: February 2022

For several decades, the Geostationary Operational Environmental Satellites (GOES) series have provided both real-time and historical data for radiation exposure estimation and solar proton radiation environment modelling. Recently, several groups conducted calibration studies that significantly reduced the uncertainties on the response of GOES proton detectors, thus improving the reliability of the spectral observations of solar energetic particle events. In this work, the long-established Band function fitting set for past ground level enhancements (GLEs) and their recent revision are used as references to estimate the best matching energies of proton channels of GOES 6–16, with emphasis on comparing with previous calibration studies on the high energetic proton measurements. The calculated energies for different missions in the same series (GOES 8, 10, 11) show overall consistency but with small variations, and differences among missions of different series are noticeable for measurements crossing the past three solar cycles, though the results are sensitive to the method used to subtract background fluxes. The discrepancy and agreement with previous calibration efforts are demonstrated with other independent analyses. It is verified that the integral channel P11 of GOES 6–16 can be reliably used as a differential proton channel with an effective energy of about 1 GeV. Therefore, the multi-decade in situ measurements of the GOES series can be utilized with more extensive energy coverage to improve space radiation environment models.