bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Study of Language Learning Strategies Used by Freshmen of Gedu College of Business Studies
Authors: Wangchuk Chencho 
Published: November 2021

Aim: To study the use of language learning strategies among freshmen of Gedu College of Business Studies.
Study Design: A cross-sectional survey.
Methodology: Data were collected through SILL, and they were analyzed by means of descriptive statistics.
Results: Descriptive statistics revealed meta-cognitive as the most favored strategies while memory strategies were the least preferred ones among the respondents. However, the usage of all six strategies among Bhutanese college students was medium, which means the strategies were sometimes used. The independent t-test revealed statistically insignificant difference between the two groups of genders.
Conclusion: This study examined the use of LLS among the freshmen of Gedu College of Business Studies. The findings of this study will have implications for learner autonomy and naturalistic exposure to English language. Such experiences are, therefore, expected to assist acquisition of English as a second language and develop learners’ communicative competence.
Broadening the Scope and Utility of Frontal Sinus Morphology for Predicting the Growth Pattern and Skeletal Malocclusion in Cleft Lip and Palate Cases
Authors: V. Jadhav Vikrant , Daigavane Pallavi , Kamble Ranjit , Shrivastav Sunita , Tiwari Meenakshi 
Published: November 2021

Introduction: The three dimensionally affected growth and development of craniofacial structures in CLCP leads to problems dealing with facial appearance, skeletal and dental malocclusion, feeding, airway, hearing, and speech.
Objectives: Evaluation and utilisation of fs morphology as a forecast of future growth for growth pattern and skeletal malocclusion in CLCP cases.
Methodology: A 30 Cases from Skeletal Class I, III and CLCP will be selected from Department of Orthodontics. Dimensions and area of frontal sinus is evaluated using 3DVT. Parameters are evaluated in sagittal and coronal section. The measurement's dependability will be determined using a reliability test (Cronbach alpha test). Chisquare Test, One Way ANOVA, and Multiple Comparison will be used to do descriptive and analytical statistics. The Tukey Test is a statistical test that is used.
Expected Results: Frontal sinus dimensions when observed for Class III will be found greater. Average dimensions will be observed for skeletal Class I cases. Based on the dimensions of frontal sinus observed in cleft lip and palate, we can predict the skeletal malocclusion and growth pattern.
Conclusion: The morphology of the fs is evaluated in cleft cases for the upcoming growth pattern and skeletal malocclusion if is known during formulating a treatment plan for the three dimensionally affected jaw bases and craniofacial structure the requirement for later surgical intervention can be prevented.
Quantitative evaluation of dosimetric uncertainties in electron therapy by measurement and calculation using the electron Monte Carlo dose algorithm in the Eclipse treatment planning system
Authors: Ali Imad , Alsbou Nesreen , Ahmad Salahuddin 
Published: November 2021

AbstractIn the electron beam radiation therapy, customized blocks are mostly used to shape treatment fields to generate conformal doses. The goal of this study is to investigate quantitatively dosimetric uncertainties associated with heterogeneities, detectors used in the measurement of the beam data commissioning, and modeling of the interactions of high energy electrons with tissue. These uncertainties were investigated both by measurements with different detectors and calculations using electron Monte Carlo algorithm (eMC) in the Eclipse treatment planning system. Dose distributions for different field sizes were calculated using eMC and measured with a multiple‐diode‐array detector (MapCheck2) for cone sizes ranging from 6 to 25 cm. The dose distributions were calculated using the CT images of the MapCheck2 and water‐equivalent phantoms. In the umbra region (<20% isodose line), the eMC underestimated dose by a factor of 3 for high energy electron beams due to lack of consideration of bremsstrahlung emitted laterally that was not accounted by eMC in the low dose region outside the field. In the penumbra (20%–80% isodose line), the eMC overestimated dose (40%) for high energy 20 MeV electrons compared to the measured dose with small diodes in the high gradient dose region. This was mainly due to lack of consideration of volume averaging of the ion chamber used in beam data commissioning which was input to the eMC dose calculation algorithm. Large uncertainties in the CT numbers (25%) resulted from the image artifacts in the CT images of the MapCheck2 phantom due to metal artifacts. The eMC algorithm used the electron and material densities extracted from the CT numbers which resulted large dosimetric uncertainties (10%) in the material densities and corresponding stopping power ratios. The dose calculations with eMC are associated with large uncertainties particularly in penumbra and umbra regions and around heterogeneities which affect the low dose level that cover nearby normal tissue or critical structures.
COVID‐19‐associated immune‐mediated encephalitis mimicking acute‐onset Creutzfeldt‐Jakob disease
Authors: Beretta Simone , Stabile Andrea , Balducci Claudia , DiFrancesco Jacopo C. , Patruno Adriana , Rona Roberto , Bombino Michela , Capraro Cristina , Andreetta Francesca , Cavalcante Paola , Moda Fabio , Citerio Giuseppe , Foti Giuseppe , Bogliun Graziella , Ferrarese Carlo 
Published: November 2021

AbstractWe report a subtype of immune‐mediated encephalitis associated with COVID‐19, which closely mimics acute‐onset sporadic Creutzfeldt–Jakob disease. A 64‐year‐old man presented with confusion, aphasia, myoclonus, and a silent interstitial pneumonia. He tested positive for SARS‐CoV‐2. Cognition and myoclonus rapidly deteriorated, EEG evolved to generalized periodic discharges and brain MRI showed multiple cortical DWI hyperintensities. CSF analysis was normal, except for a positive 14‐3‐3 protein. RT‐QuIC analysis was negative. High levels of pro‐inflammatory cytokines were present in the CSF and serum. Treatment with steroids and intravenous immunoglobulins produced EEG and clinical improvement, with a good neurological outcome at a 6‐month follow‐up.
Quantum Confinement in Aligned Zigzag “Pseudo‐Ribbons” Embedded in Graphene on Ni(100)
Authors: Sala Alessandro , Zou Zhiyu , Carnevali Virginia , Panighel Mirco , Genuzio Francesca , Menteş Tevfik O. , Locatelli Andrea , Cepek Cinzia , Peressi Maria , Comelli Giovanni , Africh Cristina 
Published: November 2021

AbstractLateral quantum confinement is of great interest in tuning the electronic properties of graphene‐based nanostructures, making them suitable for technological applications. In principle, these properties might be controlled through the edge topology: for example, zigzag nanoribbons are predicted to have spin‐polarized edge states. The practical realization of these structures is of utmost importance in fully harnessing the electronic properties of graphene. Here, the formation of regular, 1.4 nm wide ribbon‐like graphene structures with zigzag edges are reported, showing 1D electronic states. It is found that these “pseudo‐ribbons” embedded in single‐layer graphene supported on Ni(100) can spontaneously form upon carbon segregation underneath 1D graphene moiré domains, extending hundreds of nanometers in length. On the basis of both microscopy/spectroscopy/diffraction experiments and theoretical simulations, it is shown that these structures, even though seamlessly incorporated in a matrix of strongly interacting graphene, exhibit electronic properties closely resembling those of zigzag nanoribbons.
Unraveling the Synergistic Coupling Mechanism of Li+ Transport in an “Ionogel‐in‐Ceramic” Hybrid Solid Electrolyte for Rechargeable Lithium Metal Battery
Authors: Song Xianli , Wang Chenlu , Chen Junwu , Xin Sen , Yuan Du , Wang Yanlei , Dong Kun , Yang Lipeng , Wang Gongying , Zhang Haitao , Zhang Suojiang 
Published: November 2021

AbstractUnderstanding the ionic transport behaviors in hybrid solid electrolytes (HSEs) is critically important for the practical realization of rechargeable Li‐metal batteries (LMBs) with high safety. Herein, it is reported a new solid “Ionogel‐in‐Ceramic” electrolyte by using the Li1.3Al0.3Ti1.7(PO4)3 (LATP) ceramic particles as a framework and “Poly(ionic liquid)s‐in‐Salt” (“PolyIL‐in‐Salt”) ionogel as an ionic bridge via a simple pressing process. The “PolyIL‐in‐Salt” ionogel precursor is designed to improve the chemical compatibility at solid–solid interfaces. Molecular dynamics simulations reveal the roles of salt concentrations on the distribution of co‐coordination of “PolyIL‐in‐Salt” ionogel. Moreover, the “PolyIL‐in‐Salt” ionogel containing co‐coordination not only inhibits the parasitic reactions between LATP and Li anode but also provides efficient Li+ conducting pathways. Benefiting from the designed structure, the “Ionogel‐in‐Ceramic” HSE exhibits an excellent ionic conductivity of 0.17 mS cm−1 at 50 °C. Meanwhile, the as‐formed solid electrolyte enables a long cycle of over 3500 h in Li/Li symmetric cell. Further, all‐solid‐state lithium metal batteries fabricated on LiFePO4 and high voltage LiCoO2 cathodes deliver 160.0 mAh g−1, 125.0 mAh g−1, respectively. This study sheds light on the rational design of solid‐state electrolytes with efficient interparticle Li+ conduction, compatible, stable, compact, and durable electrode–electrolyte interfaces.
Ultrasmooth Gold Nanogroove Arrays: Ultranarrow Plasmon Resonators with Linewidth down to 2 nm and Their Applications in Refractive Index Sensing
Authors: Shen Yang , He Kai , Zou Qiushun , Xing Shan , Huang Jiayuan , Zheng Manchun , She Xiaoyi , Jin Chongjun 
Published: November 2021

AbstractPlasmonic nanostructures offer an enticing prospect in many applications, ranging from lasing to biosensing, due to their unrivaled light concentration beyond the diffraction limit. However, this promise is substantially undercut by the intrinsically high losses in metals. Here, an experimental ultra‐high‐Q plasmon resonance with a linewidth down to 2 nm (Q‐factor ≈ 350) and a resonance intensity of 51% in an ultrasmooth gold nanogroove array is reported. Such an experimental ultranarrow resonance arises from two key factors. First, a geometrical‐induced coupling between the Fabry–Pérot and Wood's anomaly modes significantly suppresses the groove array's radiative damping. Second, an ultrasmooth gold surface fabricated by template stripping minimizes its surface scattering and grain boundary scattering. Benefiting from this ultranarrow resonance, a figure of merit (FOM) of 284 and an FOM* of 617 in refraction index (RI) sensing under normally incident detection are demonstrated, the former of which is the record FOM in all reported broad‐RI‐range plasmonic RI sensors. The array is further demonstrated as a surface thickness sensor for detecting mercaptocarboxylic acids with the surface sensitivity of 0.18 nm/CH2, which suggests that the array is a promising platform for thickness detection of surface analytes and label‐free biomedical sensing.
Optimization and Performance Prediction of Tunnel Field‐Effect Transistors Based on Deep Learning
Authors: Wang Gang , Wang Shulong , Ma Lan , Wang Guosheng , Wu Jieyu , Duan Xiaoling , Chen Shupeng , Liu Hongxia 
Published: November 2021

AbstractThe tunnel field‐effect transistor (TFET) is considered to be a suitable substitute for metal oxide semiconductor‐field effect transistors in the post‐“Moore's Law” era owing to its low power consumption. However, Si‐TFETs face the drawbacks of low on‐state currents and significant ambipolar leakage. This study proposes a GeSi/Si heterojunction double‐gate TFET with a T‐channel hetero‐gate dielectric (HJ‐HGD‐DGTFET) structure to overcome these problems. It also presents a novel method of predicting and optimizing the performance of the existing TFETs which use deep learning to accelerate the device design. Furthermore, this study proposes a neural network based on different requirements to perform two functions: prediction of the device performance using the forward design, and the forecast of the device structure using the inverse design. It can thus be used to determine whether the output of the network meets the design objectives and if it is necessary to change the output by adjusting the input, and lastly achieve the TFET performance prediction and device optimization. The proposed method can be used to design TFETs accurately and efficiently even without professional knowledge. This study provides guidance for the design and optimization of TFETs along with other microelectronic devices.
Roll‐to‐Roll Gravure‐Printed Carbon Nanotube‐based Transistor Arrays for a Digital Column Chromatograph
Authors: Jung Younsu , Park Jinhwa , Sun Junfeng , Park Hyejin , Parajuli Sajjan , Shrestha Sagar , Shrestha Kiran , Majima Yutaka , Cho Gyoujin 
Published: November 2021

AbstractRoll‐to‐roll (R2R)‐printed thin‐film transistor‐based devices have apparent advantages over their silicon‐based counterparts to explore a new device concept where form factor and cost are critical. Here, the R2R gravure‐printed single‐walled carbon nanotube (SWCNT)‐based thin‐film transistor (TFT) arrays are demonstrated to show advantages in developing inexpensive digital column chromatography (DiCC). The DiCC can be easily constructed by cutting and pasting the fluoropolymer, CYTOP, coated R2R gravure‐printed SWCNT‐TFT arrays on the inside wall of the column. The coated CYTOP acts as an electret and induces charges depending on dipole moments of the molecules in nonpolar eluents. Since the induced charges act as an n‐type dopant to the printed p‐type SWCNT‐TFT, the off‐currents of SWCNT‐TFT arrays are raised when analyte molecules with a dipole moment move to the CYTOP‐coated SWCNT‐TFT. By monitoring the off‐current variations of the CYTOP‐coated SWCNT‐TFT, the flow of molecules can be digitally monitored, and even the structural isomers of molecules can be digitally differentiated in real time.
Machine‐Learning‐Assisted Accurate Prediction of Molecular Optical Properties upon Aggregation
Authors: Xu Shidang , Liu Xiaoli , Cai Pengfei , Li Jiali , Wang Xiaonan , Liu Bin 
Published: November 2021

AbstractFor practical applications, molecules often exist in an aggregate state. Therefore, it is of great value if one can predict the performance of molecules when forming aggregates, for example, aggregation‐induced emission (AIE) or aggregation‐caused quenching (ACQ). Herein, a database containing AIE/ACQ molecules reported in the literature is first established. Through training, these machine learning (ML) models can build up the structure–property relationship and thus implement fast prediction of AIE/ACQ properties. To this end, a multi‐modal approach is proposed, multiple prediction methods are compared and designed, and thus an ensemble strategy is developed. First, multiple molecular descriptors are considered at the same time, major features are extracted by dimensionality reduction, and multi‐modal features are synthesized. Then, several state‐of‐the‐art methods are designed and compared to analyze the advantages of the different methods. Finally, the ensemble strategy combines the advantages of the multiple methods to obtain the final prediction result. The reliability of this approach in an unknown molecular space is further verified by three newly designed molecules. Reasonable consistency between model predictions and experimental outcomes is obtained. The result indicates that ML can be a powerful tool to predict molecular properties in the aggregated state, thus accelerating the development of solid‐state optical materials.
Masks for COVID‐19
Authors: Deng Wei , Sun Yajun , Yao Xiaoxue , Subramanian Karpagam , Ling Chen , Wang Hongbo , Chopra Shauhrat S. , Xu Ben Bin , Wang Jie‐Xin , Chen Jian‐Feng , Wang Dan , Amancio Honeyfer , Pramana Stevin , Ye Ruquan , Wang Steven 
Published: November 2021

AbstractSustainable solutions on fabricating and using a face mask to block the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) spread during this coronavirus pandemic of 2019 (COVID‐19) are required as society is directed by the World Health Organization (WHO) toward wearing it, resulting in an increasingly huge demand with over 4 000 000 000 masks used per day globally. Herein, various new mask technologies and advanced materials are reviewed to deal with critical shortages, cross‐infection, and secondary transmission risk of masks. A number of countries have used cloth masks and 3D‐printed masks as substitutes, whose filtration efficiencies can be improved by using nanofibers or mixing other polymers into them. Since 2020, researchers continue to improve the performance of masks by adding various functionalities, for example using metal nanoparticles and herbal extracts to inactivate pathogens, using graphene to make masks photothermal and superhydrophobic, and using triboelectric nanogenerator (TENG) to prolong mask lifetime. The recent advances in material technology have led to the development of antimicrobial coatings, which are introduced in this review. When incorporated into masks, these advanced materials and technologies can aid in the prevention of secondary transmission of the virus.
Emerging Theranostic Nanomaterials in Diabetes and Its Complications
Authors: Liu Yuntao , Zeng Siqi , Ji Wei , Yao Huan , Lin Lin , Cui Haiying , Santos Hélder A. , Pan Guoqing 
Published: November 2021

AbstractDiabetes mellitus (DM) refers to a group of metabolic disorders that are characterized by hyperglycemia. Oral subcutaneously administered antidiabetic drugs such as insulin, glipalamide, and metformin can temporarily balance blood sugar levels, however, long‐term administration of these therapies is associated with undesirable side effects on the kidney and liver. In addition, due to overproduction of reactive oxygen species and hyperglycemia‐induced macrovascular system damage, diabetics have an increased risk of complications. Fortunately, recent advances in nanomaterials have provided new opportunities for diabetes therapy and diagnosis. This review provides a panoramic overview of the current nanomaterials for the detection of diabetic biomarkers and diabetes treatment. Apart from diabetic sensing mechanisms and antidiabetic activities, the applications of these bioengineered nanoparticles for preventing several diabetic complications are elucidated. This review provides an overall perspective in this field, including current challenges and future trends, which may be helpful in informing the development of novel nanomaterials with new functions and properties for diabetes diagnosis and therapy.
Outstanding Strengthening and Toughening Behavior of 3D‐Printed Fiber‐Reinforced Composites Designed by Biomimetic Interfacial Heterogeneity
Authors: Yu Siwon , Hwang Yun Hyeong , Lee Kang Taek , Kim Sang Ouk , Hwang Jun Yeon , Hong Soon Hyung 
Published: November 2021

Abstract3D printing of fiber‐reinforced composites is expected to be the forefront technology for the next‐generation high‐strength, high‐toughness, and lightweight structural materials. The intrinsic architecture of 3D‐printed composites closely represents biomimetic micro/macrofibril‐like hierarchical structure composed of intermediate filament assembly among the micron‐sized reinforcing fibers, and thus contributes to a novel mechanism to simultaneously improve mechanical properties and structural features. Notably, it is found that an interfacial heterogeneity between numerous inner interfaces in the hierarchical structure enables an exceptional increase in the toughness of composites. The strong interfacial adhesion between the fibers and matrix, with accompanying the inherently weak interfacial adhesion between intermediate filaments and the resultant interfacial voids, provide a close representation of the toughness behavior of natural architectures relying on the localized heterogeneity. Given the critical embedment length of fiber reinforcement, extraordinary improvement has been attained not only in the strength but also in toughness taking advantage of the synergy effect from the aforementioned nature‐inspired features. Indeed, the addition of a small amount of short fiber to the brittle bio‐filaments results in a noticeable increase of more than 200% in the tensile strength and modulus with further elongation increment. This article highlights the inherent structural hierarchy of 3D‐printed composites and the relevant sophisticated mechanism for anomalous mechanical reinforcement.
Single‐Cell Transcriptome Profiling Reveals Multicellular Ecosystem of Nucleus Pulposus during Degeneration Progression
Authors: Tu Ji , Li Wentian , Yang Sidong , Yang Pengyi , Yan Qi , Wang Shenyu , Lai Kaitao , Bai Xupeng , Wu Cenhao , Ding Wenyuan , Cooper‐White Justin , Diwan Ashish , Yang Cao , Yang Huilin , Zou Jun 
Published: November 2021

AbstractAlthough degeneration of the nucleus pulposus (NP) is a major contributor to intervertebral disc degeneration (IVDD) and low back pain, the underlying molecular complexity and cellular heterogeneity remain poorly understood. Here, a comprehensive single‐cell resolution transcript landscape of human NP is reported. Six novel human NP cells (NPCs) populations are identified by their distinct molecular signatures. The potential functional differences among NPC subpopulations are analyzed. Predictive transcripts, transcriptional factors, and signal pathways with respect to degeneration grades are explored. It is reported that fibroNPCs is the subpopulation for end‐stage degeneration. CD90+NPCs are observed to be progenitor cells in degenerative NP tissues. NP‐infiltrating immune cells comprise a previously unrecognized diversity of cell types, including granulocytic myeloid‐derived suppressor cells (G‐MDSCs). Integrin αM (CD11b) and oxidized low density lipoprotein receptor 1 (OLR1) as surface markers of NP‐derived G‐MDSCs are uncovered. The G‐MDSCs are found to be enriched in mildly degenerated (grade II and III) NP tissues compared to severely degenerated (grade IV and V) NP tissues. Their immunosuppressive function and alleviation effects on NPCs’ matrix degradation are revealed in vitro. Collectively, this study reveals the NPC‐type complexity and phenotypic characteristics in NP, thereby providing new insights and clues for IVDD treatment.
Advanced Zinc Anode with Nitrogen‐Doping Interface Induced by Plasma Surface Treatment
Authors: Jia Hao , Qiu Minghui , Lan Chuntao , Liu Hongqi , Dirican Mahmut , Fu Shaohai , Zhang Xiangwu 
Published: November 2021

AbstractAqueous zinc‐ion batteries (ZIBs) are one of the most ideal candidates for grid‐scale energy storage applications due to their excellent price and safety advantages. However, formation of Zn dendrites and continuous side reactions during cycling result in serious instability problems for ZIBs. In this work, the authors develop a facile and versatile plasma‐induced nitrogen‐doped Zn (N‐Zn) foil for dendrite‐free Zn metal anode. Benefitting from the uniform nucleation sites and enhanced surface kinetics, the N‐Zn anode exhibits exceptionally low overpotential (around 23 mV) at 1 mA cm−2 and can be cycled for over 3000 h under 1 mA cm−2 because of the enhanced interface behavior. The potential application of N‐Zn anode is also confirmed by introducing a full Zn/MnO2 battery with outstanding capacity stability for 2000 cycles at 1 A g–1. Overall, this work offers new fundamental insights into homogenizing Zn electrodeposition processes by pre‐introduced active nucleation sites and provides a novel direction of interface design engineering for ultra‐stable Zn metal anode.