bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tri‐layered alginate/poly(𝜀‐caprolactone) electrospun scaffold for cardiac tissue engineering
Authors: Karimi Seyed Nasir Hosseini , Aghdam Rouhollah Mehdinavaz , Ebrahimi S. A. Seyyed , Chehrehsaz Yalda 
Published: January 2022

AbstractNovel tri‐layered electrospun alginate–graphene oxide (GO)/poly(ε‐caprolactone) (PCL) conductive scaffolds were fabricated with a sequential electrospinning method for the first time, in which the middle PCL layer acts as a mechanical support of the scaffold. The top and bottom alginate–GO nanofibrous layers provide cell viability and attachment, and also electroconductivity for the scaffold. The fabrication of this nanofibrous scaffold aims to simulate cardiac extracellular matrix. Scanning electron microscopy and infrared spectroscopy were used to characterize the nanofibrous scaffolds, confirming the presence of GO in nanofibers and also crosslinking reaction of the alginate nanofibrous layer. The electroconductivity of the tri‐layered electrospun scaffolds reached 7.29 ± 0.91 μS with the incorporation of 1 wt% GO into the top and bottom alginate nanofibrous layers. The ultimate tensile strength and Young’s modulus of the alginate–0.5 wt% GO/PCL scaffold reached 22.46 ± 0.07 and 4.35 ± 0.56 MPa, respectively. The biocompatibility of the nanofibrous scaffolds was evaluated using cardiac progenitor cells. The results showed that the presence of GO accelerated the degradation of the scaffolds in phosphate‐buffered saline solution. The cell studies revealed that GO incorporation into alginate nanofibers on the surface of the tri‐layer scaffolds could enhance cell viability, adhesion and proliferation. Overall, the tri‐layered electroconductive alginate–PCL nanofibrous scaffolds could be considered as potential candidates for cardiac tissue regeneration. © 2022 Society of Industrial Chemistry.
You can't sit with us…just kidding! An investigation into the association between empathy and prosocial teasing
Authors: Platt Michelle , Malecki Christine K. , Luckner Amy , Wiemer Kristina , Pyun Yoonsun 
Published: January 2022

AbstractProsocial teasing is the positive playful form of relational aggression, and studies have found children engage in playful teasing more often than aggressive teasing. Therefore, understanding the basic characteristics or skills that contribute to the more complex social skill of prosocial teasing is important. The current study focused on the role of empathy in students' perception of their engagement in two different forms of relational behaviors, playful and aggressive. Associations between empathy and engagement in playful and aggressive relational behaviors were investigated with 389 fifth‐grade students in the Midwest with the Social Skills Improvement System (SSIS) rating scale and modified Children's Social Behavior Scale—Self‐Report (CSBS‐S), along with gender interaction in those relationships. Results demonstrated that empathy was significantly and negatively related to the level of engagement in both relational aggression and prosocial teasing. No gender differences were found in levels of relational aggression or in prosocial teasing. Gender differences were observed in empathy, where girls reported higher levels of empathy than boys. Results indicated that empathy was a significant predictor of engagement in both relational aggression and prosocial teasing for both fifth‐grade boys and girls. Implications concerning these findings are discussed.
Advance of click chemistry in anion exchange membranes for energy application
Authors: Yang Weihong , Chen Jin , Yan Jing , Liu Shuang , Yan Yi , Zhang Qiuyu 
Published: January 2022

AbstractClick chemistry has attracted tremendous attention in polymer synthesis due to its high efficiency, considerable yield, and simple synthesis/work‐up procedures. Among the various functional polymer materials prepared by click chemistry, anion exchange membrane (AEM) is a kind of polyelectrolyte which contains cations attached to the polymer skeleton. Click chemistry not only provides facile pathways for the preparation of AEMs but also generates diverse architectures of AEMs with robust performance. The commonly used click chemistry in AEMs consists of: (i) Diels‐Alder reaction, (ii) thiol‐ene, and (iii) Cu(I)‐catalyzed azide‐alkyne cycloaddition (CuAAC). This review will focus on the advance of click chemistry in the preparation of AEMs, especially synthetic approaches for different AEMs and their corresponding application in energy‐related fields, such as fuel cells, redox flow battery, electrodialysis, and so on.
Variations in infection control practices suggest a need for guidelines in primary ciliary dyskinesia patient care
Authors: Caliskan Ayse B. , Horani Amjad , Manion Michele , Brody Steven L. 
Published: January 2022

AbstractPrimary ciliary dyskinesis (PCD) is an autosomal recessive disorder associated with impaired mucociliary clearance caused by defects in ciliary structure and function. The major clinical feature of PCD is recurring or persistent respiratory tract infection. Respiratory tract colonization with drug‐resistant organisms impacts the frequency of infections and lung function decline. Protective gear has been employed by caregivers in an attempt to control respiratory tract bacterial spread between patients with cystic fibrosis, but use in PCD is not known. We conducted a web‐based survey to investigate infection control and prevention practices of PCD centers in North America, and how practices have been influenced by the COVID‐19 pandemic. The response rate was 87.0%. Before the COVID‐19 pandemic, glove, gown, and mask use were variable, and only 3.7% of centers used masks during encounters with PCD outpatients. After COVID‐19 mandates are lifted, 48.1% of centers plan to continue to use masks during outpatient care, while the practice regarding the use of gloves and gowns was not influenced by the current pandemic. There is no uniform practice for infection control in PCD care indicating the need for practice guidelines. Mitigation of respiratory virus transmission learned during the COVID‐19 pandemic may impact future infection control approaches used for patients with PCD and other lung diseases.
Trends of WoS educational research articles in the last half‐century
Authors: Tosun Cemal 
Published: January 2022

AbstractThe aim of this study was to reveal the development trends of the last 50 years of Web of Science (WoS) educational research. For this aim, 93,699 articles published in 116 journals were analysed with bibliometric techniques. The results of the analysis showed that the number of WoS educational research articles accelerated in 1980, 2008 and 2019. The first conclusion of the research was that funding support is an important factor in the number of WoS educational research articles. The core topics of educational research by countries, year intervals, Q categories of journals and all sub‐disciplines of education were revealed in this study, and the second conclusion of this research was that the core topics of the last half‐century of WoS educational research articles were higher education, teacher education, professional development and assessment. In addition, the study revealed that components of the core topics in educational research have differed according to countries, year intervals, Q categories of journals and all sub‐disciplines of education. The results of this study showed that the focus of the articles published in Q1 journals was technology‐assisted learning environments. The most productive countries were the USA, UK, Australia and Canada. In addition, China and Taiwan were among the top 10 with increasing article number in recent years. According to another conclusion of this study, the contribution rates of the top 10 countries to educational research tended to decrease with the contributions of other countries’ researchers to the field. It was found that the most productive authors were C.C. Tsai, G.J. Hwang and W.M. Roth. On the other hand, the most productive organisations, the journals that publish the most articles, the organisations that provide the most funds and the common features of the most cited articles were determined in the present study. The diversity in educational researches can be achieved by knowing the topics that researchers have been interested in the past periods. Therefore, the results of the present study are considered to be indicative for different studies in future.
Event‐triggered robust model predictive control for linear discrete‐time systems with a guaranteed average inter‐execution time
Authors: Deng Li , Shu Zhan , Chen Tongwen 
Published: January 2022

AbstractAn event‐triggered robust model predictive control (MPC) approach is proposed for linear discrete‐time systems with bounded disturbances. According to the probability distribution of bounded disturbances, an event‐triggered scheme involving a designed minimal robust positively invariant set is constructed to generate dynamic triggering sets. The MPC‐related optimization problem subject to hard constraints should be solved only at event‐triggered instants when the state is outside the corresponding triggering set. A classical tube‐based MPC that allows the initially predicted state different from the current actual state of the plant is considered to improve the feasible region. The designed event‐triggered controller can achieve a prescribed expectation of inter‐execution times and reduce the burden of communication and computation, while not sacrificing the quadratic performance significantly. It is proved that the proposed control approach ensures recursive feasibility and robust stability. Three examples are used to demonstrate the effectiveness and advantages of the proposed method.
How Sustainable Development Goals interlinkages influence European Union countries’ progress towards the 2030 Agenda
Authors: Kostetckaia Mariia , Hametner Markus 
Published: January 2022

AbstractThe analysis of interlinkages between the sustainable development goals (SDGs) and the assessment of countries' progress towards the goals are two prominent research areas in the debate around the 2030 Agenda. The central questions are whether countries are progressing towards the goals at sufficient speed, and whether the SDGs can be achieved in their entirety. While it is evident that trade‐offs between the 2030 Agenda's objectives might prevent countries from achieving all 17 SDGs simultaneously, the extent to which interactions (synergies and trade‐offs) between the goals facilitate or hinder countries' progress towards achieving the 2030 Agenda has so far received little attention. The present study combines the two topics by linking the analysis of synergies and trade‐offs between the SDGs in the European Union (EU) member states with a longitudinal assessment of these countries' progress towards the goals. SDG interlinkages are assessed through Spearman's rank order correlation, while progress is calculated according to Eurostat's progress measure. Using regression analysis, we find a significant negative relationship between countries' progress and the shares of trade‐offs among SDG indicators and a moderate positive relationship between progress and synergies, suggesting that trade‐offs have a bigger influence on the pace of countries' progress towards the goals than synergies. In order to achieve the SDGs by 2030, it is thus crucial to not only exploit synergies between the goals but also to overcome trade‐offs.
Correcting for partial verification bias in diagnostic accuracy studies: A tutorial using R
Authors: Arifin Wan Nor , Yusof Umi Kalsom 
Published: January 2022

AbstractDiagnostic tests play a crucial role in medical care. Thus any new diagnostic tests must undergo a thorough evaluation. New diagnostic tests are evaluated in comparison with the respective gold standard tests. The performance of binary diagnostic tests is quantified by accuracy measures, with sensitivity and specificity being the most important measures. In any diagnostic accuracy study, the estimates of these measures are often biased owing to selective verification of the patients, which is referred to as partial verification bias. Several methods for correcting partial verification bias are available depending on the scale of the index test, target outcome, and missing data mechanism. However, these are not easily accessible to the researchers due to the complexity of the methods. This article aims to provide a brief overview of the methods available to correct for partial verification bias involving a binary diagnostic test and provide a practical tutorial on how to implement the methods using the statistical programming language R.
Prediction of Carbon Dioxide Solubility in Polymers Based on Adaptive Particle Swarm Optimization and Least Squares Support Vector Machine
Authors: Chen Huijie , Zeng Ming , Zhang Hang , Chen Bingsheng , Guan Lixin , Li Mengshan 
Published: January 2022

AbstractSolubility is a significant physical and chemical property. The solubility of carbon dioxide(CO2) in polymers is an important application of green chemistry. Aimed at the problem of insufficient precision of the existing prediction model, a solubility prediction model based on the adaptive particle swarm optimization algorithm and the least‐squares support vector machine(APSO‐LSSVM) is proposed. Different from the traditional particle swarm algorithm, APSO algorithm improves the problem of easily falling into local optimal solution. The regularization parameters and kernel function tuning parameters of the LSSVM were optimized by APSO and then use this model to predict the solubility of CO2 in eight polymers within a wide range of temperatures and pressures. APSO‐LSSVM model has great prediction ability, with a good correlation between prediction data and experimental data, high prediction accuracy, short calculation time and strong stability. Compared with back propagation artificial neural network(BP ANN), back propagation‐particle swarm optimization algorithm artificial neural network(BP‐PSO ANN) and LSSVM, APSO‐LSSVM has better comprehensive performance. The average absolute relative deviation(AARD), root mean square error(RMSE), determination coefficient(R2) were respectively 0.2130, 0.0120, 0.9853. In addition, the model has good expansibility and can be applied to other fields such as chemistry and medicine.
Tailoring MSx Quantum Dots (M = Co, Ni, Cu, Zn) for Advanced Energy Storage Materials with Strong Interfacial Engineering
Authors: Zhang Liming , Zhao Wenqing , Yuan Shaohui , Yang Yue , Ge Peng , Sun Wei , Ji Xiaobo 
Published: January 2022

AbstractMetal sulfides, as vital members of electrodes materials, still suffer from serious volume expansion and polysulfides shuttling. Herein, through inexpensive and high efficiency chemical‐bonding/hydrophobic‐association methods, a series of metal‐sulfides quantum dots (QDs) with large‐scale synthesis (≈100 g) is successfully prepared, further forming low‐dimensional composites with high redox activity. For the derived electrodes samples, with the increasing of outer electron numbers (Co2+/Ni2+/Cu2+/Zn2+), interfacial coupling is significantly modified. Among them, nanoscale ZnS@double carbon with rich interfacial Zn‐O/S‐C bonds displays remarkable electrochemical activity, with the capacity of ≈1000 mAh g−1 after 100 loops. Through tailoring double carbons and interfacial merits, in situ sulfur formation is stabilized, and the cycling stability of Zn‐based samples can increase up to 4000 cycles. Even at 5.0 A g−1 after 1500 cycles, the full‐cells capacity can reach up to ≈380 mAh g−1. Supported by detailed kinetic analysis and ex situ technologies, the enhanced interfacial capacitances and ions moving are confirmed for the improved electrochemical properties. Given this, the work is expected to boost future developments of mineral processing, and QDs preparation, whilst providing effective strategies for advanced electrode materials.
A combination of deep learning and genetic algorithm for predicting the compressive strength of high‐performance concrete
Authors: Ranjbar Iman , Toufigh Vahab , Boroushaki Mehrdad 
Published: January 2022

AbstractThis article presented an efficient deep learning technique to predict the compressive strength of high‐performance concrete (HPC). This technique combined the convolutional neural network (CNN) and genetic algorithm (GA). Six CNN architectures were considered with different hyper‐parameters. GA was employed to determine the optimum number of filters in each convolutional layer of the CNN architectures. The resulted CNN architectures were then compared to each other to find the best architecture in terms of accuracy and capability of generalization. It was shown that all of the proposed CNN models are capable of predicting the HPC compressive strength with high accuracy. Finally, the best of the six considered models was validated through the 10‐fold cross‐validation method and compared to the previous studies on the same data set. Models were developed through a comprehensive data set consisting of 1030 HPC compressive strength test data. Comparing the proposed technique with previous studies showed that the proposed technique has a considerable advantage over previous methods and can be employed for reliable estimation of the mechanical properties of different engineering materials.
A revised subfamilial classification of Polypodiaceae based on plastome, nuclear ribosomal, and morphological evidence
Authors: Wei Ran , Zhang Xian‐Chun 
Published: January 2022

AbstractThe polygrammoid fern family Polypodiaceae represents one of the most diversified epiphytic fern groups, with more than 1600 species distributed on all continents except Antarctica, with the highest species diversity in tropical and subtropical regions. Despite progress in recent phylogenetic studies of Polypodiaceae, the infrafamilial classification of this group of ferns is still problematic. Here, we explore the phylogenetic relationship within Polypodiaceae using plastid genome (plastome) and nuclear ribosomal cistron genome data obtained from high‐throughput sequencing. Although genome skimming data strongly support the monophyly of many genera and clades of Polypodiaceae, relationships within some clades and along the backbone of the phylogeny remain incongruent between plastome and nuclear data. The explanation is possibly a factor of complex evolutionary history found in these clades, such as rapid radiation, incomplete lineage sorting, ancient hybridization, and recent introgression. Based on the concatenated dataset, our phylogenetic analyses support nine major clades in Polypodiaceae, which merit the recognition as subfamilies, Crypsinoideae, Grammitidoideae, Loxogrammoideae, Microsoroideae, Platycerioideae, Polypodioideae, Adetogrammoideae, Campyloneuroideae, and Serpocauloideae, while the latter three are separated from Polypodioideae as new subfamilies. All of these infrafamilial divisions, identified with molecular data, are further supported by non‐molecular features including leaf dissection, venation, scales and paraphyses, soral features, and geographical distributions. Systematic and taxonomic discussions on the subfamilial treatment are also provided.
Source choice and use in counterargument writing
Authors: Al Bulushi Zawan 
Published: January 2022

AbstractThis study contributes to research on source integration in argumentative writing, with a focus on the understudied aspect of source choice and use in counterarguments. Using source‐based argumentative essays written by 13 students in one English as a second language section of a first‐year composition course in the United States, the author examined the types of sources related to confirmation bias as cited by students in counterarguments. Analyses of the essays included observing students’ stances on the issues; identifying the counterarguments; classifying the sources as confirmatory of students’ stances, opposing, neutral, or background; and counting the number of citations. The findings reveal that the students mostly cited background and confirmatory sources when writing counterarguments. Insufficient citation was evident in both counterarguments and entire essays. Pedagogical implications include guiding students toward reading and integrating opposing sources to potentially improve the quality of counterarguments and to promote perceptual gains beyond the classroom as students write about social issues important to them.
Long noncoding RNA OIP5‐AS1 promotes the stemness of lung cancer cells through enhancing Oct4 mRNA stability
Authors: Mao Chengye , Li Xionghui 
Published: January 2022

AbstractLong noncoding RNA (lncRNA) OIP5‐AS1 was shown to facilitate drug resistance and metastasis in several tumors. As cancer stem cells (CSCs) have been elucidated as the origin of drug resistance and tumor progression, we speculate that lncRNA OIP5‐AS1 holds critical roles in the CSC‐like traits of lung cancer. Here, lncRNA OIP5‐AS1 was found to be highly expressed in lung cancer cell spheres. Following experiments showed that OIP‐AS1 knockdown reduced the CSC‐like traits of lung cancer spheres, while overexpression of OIP‐AS1 conferred the CSC‐like traits in lung cancer cells by performing sphere‐formation analysis, detecting stemness marker expression, and ALDH activity. Mechanistic studies revealed that lncRNA OIP5‐AS1 could increase Oct4 expression by directly interacting with Oct4 mRNA and enhancing Oct4 mRNA stability. Finally, we found that the knockdown of Oct4 could rescue the promoting effects of OIP5‐AS1 overexpression on the CSC‐like traits of lung cancer. These results demonstrate that lncRNA OIP5‐AS1 can confer lung cancer CSC‐like traits by directly interacting with Oct4 mRNA and thus increasing Oct4 mRNA stability and expression.
Emerging roles of RNA–RNA interactions in transcriptional regulation
Authors: Wang Di , Ye Rong , Cai Zhaokui , Xue Yuanchao 
Published: January 2022

AbstractPervasive transcription of the human genome generates a massive amount of noncoding RNAs (ncRNAs) that lack protein‐coding potential but play crucial roles in development, differentiation, and tumorigenesis. To achieve these biological functions, ncRNAs must first fold into intricate structures via intramolecular RNA–RNA interactions (RRIs) and then interact with different RNA substrates via intermolecular RRIs. RRIs are usually facilitated, stabilized, or mediated by RNA‐binding proteins. With this guiding principle, several protein‐based high‐throughput methods have been developed for unbiased mapping of defined or all RNA‐binding protein‐mediated RRIs in various species and cell lines. In addition, some chemical‐based approaches are also powerful to detect RRIs globally based on the fact that RNA duplex can be cross‐linked by psoralen or its derivative 4′‐aminomethyltrioxsalen. These efforts have significantly expanded our understanding of RRIs in determining the specificity and variability of gene regulation. Here, we review the current knowledge of the regulatory roles of RRI, focusing on their emerging roles in transcriptional regulation and nuclear body formation.This article is categorized under:
RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems
RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry
Variations of Short-Lived Climate Pollutants in Hanoi, Vietnam
Authors: Do Tung Duy , Kita Kazuyuki 
Published: January 2022

AbstractEmissions of air pollutants have been increasing significantly in Asian countries due to the rapid development of industry and economy. Long-range, transboundary transport of these pollutants probably affects the atmospheric environment and the regional climate in this region (Kita et al. 2009). Climate change, air pollution, and sustainable development are inter-linked, and co-benefits of cutting short-lived climate pollutants (SLCP) will avoid global warming higher than 1.5 °C and negative trade-offs (CCAC 2019; IPCC 2018). Therefore, identification of SLCP emission/production/ transportation sources is critical for planning mitigative measures to reduce SLCP.