bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterizing students’ peer–peer questions: frequency, nature, responses and learning
Authors: Tiffany Grace , Grieger Krystal , Johnson Kassidy , Nyachwaya James
Published: February 2023

In group activities, students work collaboratively to accomplish specific objectives. Students have to engage and interact with each other in order to complete collaborative assignments. One way that students stay engaged is through asking questions. In the research reported here, we looked at peer-to-peer questions in the context of a collaborative activity. Specifically, we examined the frequency of questions, types of questions, types of responses elicited by student questions, whether peer question-and-answer interactions led to verbalized learning, and the disciplinary content of the questions asked by students in their groups. Our results show that there was a wide range in the frequency of questions asked across groups. The types of questions asked were broadly classified as confirmation seeking, clarification seeking, information seeking, and questions seeking understanding. Types of responses elicited included explanations (conceptual), informational, unsure, and no response. Most of the question-and-answer exchanges did not lead to verbalized learning. Some types of question-and-answer combinations were more likely to lead to verbalized learning than others. The most commonly asked disciplinary content questions sought facts and descriptions of procedures. Questions seeking conceptual understanding, which are more likely to lead to learning, were least common. Implications for instruction and research are discussed.
A rapid and green GC-MS method for the sampling of volatile organic compounds in spices and flowers by concurrent headspace single-drop microextraction and solid-phase microextraction
Authors: Gupta Manju , Soni Soumitra , Jain Archana , Verma Krishna K.
Published: February 2023

Concurrent headspace single-drop microextraction/solid-phase microextraction has been conducted on the same sample and vial and sample preparation was completed in the time duration of a single experiment.
Au-modified PtCu nanodendrites as a highly stable and active electrocatalyst
Authors: Gu Yuelin , Guo Weiyi , Bao Jingqi , Li Yunxia , Lu Linfang
Published: February 2023

Direct galvanic replacement of surface Cu with Au3+ in PtCu3 nanodendrites is used to prepare an Au-modified PtCu3 nanodendrite catalyst, which shows superior stability and activity for the methanol oxidation reaction and oxygen reduction reaction.
Self-assembly of protein–DNA superstructures for alkaline phosphatase detection in blood
Authors: Chang Yangyang , Zhang Qian , Xue Wei , Wu Yanfang , Liu Yi , Liu Meng
Published: February 2023

We designed a paper-based analytical device by integrating horseradish peroxidase (HRP)-encapsulated 3D DNA for visual detection of alkaline phosphatase (ALP).
Group 13 salphen compounds (In, Ga and Al): a comparison of their structural features and activities as catalysts for cyclic carbonate synthesis
Authors: Cabrera Diego Jaraba , Lewis Ryan D. , Díez-Poza Carlos , Álvarez-Miguel Lucía , Mosquera Marta E. G. , Hamilton Alex , Whiteoak Christopher J.
Published: February 2023

[InBr(salphen)] is identified as the most active catalyst for conversion of CO2and epoxides to cyclic carbonates compared to the Al and Ga congeners. The elucidated mechanism highlights the importance of both Lewis acidity and ligand fluxionality.
GaSb doping facilitates conduction band convergence and improves thermoelectric performance in n-type PbS
Authors: Chen Zixuan , Cui Hong-Hua , Hao Shiqiang , Liu Yukun , Liu Hui , Zhou Jing , Yu Yan , Yan Qingyu , Wolverton Christopher , Dravid Vinayak P. , Luo Zhong-Zhen , Zou Zhigang , Kanatzidis Mercouri G.
Published: February 2023

We improve n-type lead chalcogenides by adding GaSb to reduce lattice thermal conductivity and achieve conduction band convergence. This significantly enhances the thermoelectric performance of n-type PbS, making it comparable to its p-type counterpart.
Cu-catalysed Chan–Lam synthesis of unsymmetrical aryl chalcogenides under aqueous micellar conditions
Authors: Sun Nan , Zheng Kai , Zhang Mingqiang , Zheng Guowen , Jin Liqun , Hu Baoxiang , Shen Zhenlu , Hu Xinquan
Published: February 2023

Herein, we report a green and sustainable Cu-catalysed Chan–Lam oxidative protocol for the synthesis of (hetero)aryl selenides/sulfides from diorganyl dichalcogenides and (hetero)aryl boronic acids in an aqueous micellar medium.
Dual-cation doping precisely reducing the energy barrier of the rate-determining step for promoting oxygen-evolving activity
Authors: Xu Hui , Wang Cheng , Huang Bingji , Shang Hongyuan , Du Yukou
Published: February 2023

A sunflower-like Ir, Fe-codoped Co(OH)2catalyst assembled by nanosheets is designed for boosting electrocatalytic OER, where dual-cation doping can significantly decrease the energy barrier of the rate-determining step for OER.
Cp*Co(iii)-catalyzed C–H functionalization/spiroannulation for the synthesis of spiroindenes from 1,3-indandione and alkenes
Authors: Xu Xuefeng , Wang Di , Chang Mengfan , Shi Yue , Zhang Xu
Published: February 2023

A Co(iii)-catalyzed C–H functionalization/spiroannulation of 1,3-indandione with alkenes has been developed for the synthesis of spiroindenes. This efficient protocol features excellent functional group tolerance and high atom- and step-economy.
Design and optimisation of energy‐efficient PM‐assisted synchronous reluctance machines for electric vehicles
Authors: Shao Lingyun , Tavernini Davide , Hartavi Karci Ahu Ece , Sorniotti Aldo
Published: February 2023

The design and optimisation of a permanent magnet‐assisted synchronous reluctance (PMaSynR) traction machine is described to improve its energy efficiency over a selection of driving cycles, when installed on a four‐wheel‐drive electrically powered vehicle for urban use, with two on‐board powertrains. The driving cycle‐based optimisation is defined with the objective of minimising motor energy loss under strict size constraints, while maintaining the peak torque and restricting the torque ripple. The key design parameters that exert the most significant influence on the selected performance indicators are identified through a parametric sensitivity analysis. The optimisation brings a motor design that is characterised by an energy loss reduction of 8.2% over the WLTP Class 2 driving cycle and 11.7% over the NEDC and Artemis Urban driving cycles, at the price of a 4.7% peak torque reduction with respect to the baseline machine. Additional analysis, implemented outside the optimisation framework, revealed that different coil turn adjustments would reduce the energy loss along the considered driving cycles. However, under realistic size constraints, the optimal design solutions are the same.
A high‐efficiency power management unit with wide dynamic range for RF energy harvesting system
Authors: Xie Zushuai , Zhang Wenxu , Zhou Quancai , Wang Yanyan , Wu Jianhui , Gou Jingjing , Liu Lu , Wang Zixuan , Cai Zhikuang
Published: February 2023

A high‐efficiency power management unit (PMU) with wide dynamic range for radio frequency (RF) energy harvesting system is proposed in this paper. A digital zero current switching (ZCS) and a digital maximum power point tracking (MPPT) circuits are adopted. A sub‐threshold current reference circuit and a subthreshold voltage detection circuit are proposed to reduce the power consumption of always‐on control circuits and improve the conversion efficiency at low input power. A dual‐oscillator is designed to extend the frequency range and widen the input power range with optimized power consumption under low‐end band and high‐end band, respectively. Switch size and on‐time are adjusted according to the input power, which optimizes the conversion efficiency in a wide power range. Proposed PMU is implemented in a standard 180 nm CMOS process. The post‐layout simulation results show that proposed PMU can achieve cold‐start at the input voltage of 280 mV, the power consumption to maintain the PMU is only 9.6 nW. The input power range of the PMU is 11 nW–677 μW. When the input power is 50 nW, a power conversion efficiency (PCE) of 65% is achieved, and the peak PCE can reach 93% at 23.5 μW.
In-flight validation of the Metis visible-light polarimeter coronagraph on board Solar Orbiter
Authors: Liberatore A. , Fineschi S. , Casti M. , Capobianco G. , Abbo L. , Andretta V. , Da Deppo V. , Fabi M. , Frassati F. , Jerse G. , Landini F. , Moses D. , Naletto G. , Nicolini G. , Pancrazzi M. , Romoli M. , Russano G. , Sasso C. , Spadaro D. , Stangalini M. , Susino R. , Telloni D. , Teriaca L. , Uslenghi M.
Published: February 2023

Context. The Metis coronagraph is one of the remote sensing instruments of the ESA-NASA Solar Orbiter mission. The goal for the instrument is to enable the study of the solar atmosphere and solar wind by simultaneously acquiring images of the solar corona at two different wavelengths: visible light (VL), within a band ranging from 580 nm to 640 nm, and ultraviolet light, in the HI Lyα 121.6 ± 10 nm. The visible-light channel of the coronagraph includes a polarimeter with electro-optically modulating liquid crystal variable retarders to measure the linearly polarized brightness of the K-corona and derive the electron density.

Aims. In this paper, we present the first in-flight validation results of the Metis polarimetric channel together with a comparison to the on-ground calibrations. This paper seeks to validate the first use of an electro-optical device, the liquid crystal-based polarimeter, in deep space and within a hard radiation environment.

Methods. We used the orientation of the K-corona’s linear polarization vector during the roll maneuvers of the Space Orbiter spacecraft for the in-flight calibration.

Results. The Metis coronagraph on board the Solar Orbiter shows good agreement with the on-ground measurements. The in-flight validation confirms the expected performance of the visible-light channel polarimeter. Furthermore, a comparison between the first polarized brightness value obtained by Metis and the polarized brightness values obtained by the space-based coronagraph LASCO and the ground-based coronagraph K-Cor shows the consistency of the Metis calibrated results.
Nystagmus bei Kindern – eine Übersicht
Authors: Salchow Daniel J.
Published: February 2023

Nystagmus ist definiert als unwillkürliche, periodische Bewegung, bei der eines oder beide Augen vom Fixationspunkt wegdriften (sog. Drift). Auf die Drift, die langsame Phase, folgt entweder eine schnelle, refixierende Bewegung (sog. Refixationssakkade oder schnelle Phase) oder eine langsamere Bewegung zur Wiederaufnahme der Fixation. In dieser Übersichtsarbeit sollen die wichtigsten Formen von Nystagmus bei Kindern erörtert werden, für eine Übersicht bei Erwachsenen sei auf 1 verwiesen.
Influence of Lithium- and Zinc-Containing Bioactive Glasses on Pulpal Regeneration
Authors: Tran An Thi Loc , Sukajintanakarn Charnsak , Senawongse Pisol , Sritanaudomchai Hathaitip , Ruangsawasdi Nisarat , Lapthanasupkul Puangwan , Kitkumthorn Nakarin , Monmaturapoj Naruporn , Khamsut Chutikarn , Naruphontjirakul Parichart , Pongprueksa Pong
Published: February 2023

Objective To evaluate the potential of modified bioactive glasses containing lithium and zinc as pulp capping materials by investigating the odontogenic differentiation and mineralization response in the tooth culture model.

Materials and Methods Lithium- and zinc-containing bioactive glasses (45S5.1Li, 45S5.5Li, 45S5.1Zn, 45S5.5Zn, 45S5.1Zn sol-gel, and 45S5.5Zn sol-gel), fibrinogen-thrombin, and biodentine were prepared to assess Axin2 gene expression at 0, 30 minutes, 1 hour, 12 hours, and 1 day and DSPP gene expression at 0, 3, 7, and 14 days in stem cells from human exfoliated deciduous teeth (SHEDs) using qRT-PCR. The experimental bioactive glasses incorporated with fibrinogen-thrombin and biodentine were placed on the pulpal tissue in the tooth culture model. Histology and immunohistochemistry were analyzed at 2 weeks and 4 weeks.

Results Axin2 gene expression for all experimental groups was significantly higher than the control at 12 hours. The DSPP gene expression for all experimental groups was significantly higher than the control at 14 days. The presence of mineralization foci was significantly higher at 4 weeks for the modified bioactive glasses 45S5.5Zn, 45S5.1Zn sol-gel, and 45S5.5Zn sol-gel as well as Biodentine compared with the fibrinogen-thrombin control.

Conclusion Lithium- and zinc-containing bioactive glasses increased Axin2 and DSPP gene expression in SHEDs and can potentially enhance pulp mineralization and regeneration. Zinc-containing bioactive glasses are a promising candidate to be used as pulp capping materials.
Differential Expression Profile of Salivary oncomiRNAs among Smokeless Tobacco Users
Authors: AL-Rawi Natheer H. , Rizvi Zuha , Mkadmi Sarra , Abu Kou Rawan , Elmabrouk Neibal , Alrashdan Mohammad S. , Koippallil Gopalakrishnan Aghila Rani
Published: February 2023

Objective The aim of this study was to evaluate the expression of selected salivary oncomiRNAs among smokeless tobacco users and nonsmokers.

Materials and Methods Twenty-five subjects with chronic smokeless tobacco habit (> 1 year) and 25 nonsmokers were selected for this study. MicroRNA was extracted from saliva samples using the miRNeasy Kit (Qiagen, Hilden, Germany). The forward primers used in the reactions include hsa-miR-21-5p, hsa-miR-146a-3p, hsa-miR-155-3p, and hsa-miR-199a-3p. Relative expression of miRNAs was calculated using the 2-ΔΔCt method. Fold change is calculated by raising 2 to the power of the negative ΔΔCT value.

Statistical Analysis Statistical analysis was carried out using GraphPad Prism 5 software. A p-value less than 0.05 was considered statistically significant.

Results The four tested miRNAs were found overexpressed in saliva of subjects with smokeless tobacco habit when compared with saliva from nontobacco users. miR-21 expression was 3.74 ± 2.26 folds higher among subjects with smokeless tobacco habit compared to nontobacco users (p < 0.01). The expression for miR-146a (5.56 ± 8.3 folds; p < 0.05), miR-155 (8.06 ± 23.4 folds; p < 0.0001) and miR-199a (14.39 ± 30.3 folds; p < 0.05) was significantly higher among subjects with smokeless tobacco habit.

Conclusion Smokeless tobacco leads to salivary overexpression of the miRs 21, 146a, 155, and 199a. Monitoring the levels of these four oncomiRs may provide insight about the future development of oral squamous cell carcinoma, especially in patients with smokeless tobacco habits.
Synaptic behavior of Fe3O4-based artificial synapse by electrolyte gating for neuromorphic computing
Authors: Monalisha P. , Li Shengyao , Bhat Shwetha G. , Jin Tianli , Anil Kumar P. S. , Piramanayagam S. N.
Published: February 2023

Neuromorphic computing (NC) is a crucial step toward realizing power-efficient artificial intelligence systems. Hardware implementation of NC is expected to overcome the challenges associated with the conventional von Neumann computer architecture. Synaptic devices that can emulate the rich functionalities of biological synapses are emerging. Out of several approaches, electrolyte-gated synaptic transistors have attracted enormous scientific interest owing to their similar working mechanism. Here, we report a three-terminal electrolyte-gated synaptic transistor based on Fe3O4 thin films, a half-metallic spinel ferrite. We have realized gate-controllable multilevel, non-volatile, and rewritable states for analog computing. Furthermore, we have emulated essential synaptic functions by applying electrical stimulus to the gate terminal of the synaptic device. This work provides a new candidate and a platform for spinel ferrite-based devices for future NC applications.
Multi-functional electroactive tetrafluoroethylene-hexafluoropropylene-vinylidene fluoride (THV)/magnesium diboride (MgB2) composite reactive material
Authors: Zaitzeff Mikel J. , Groven Lori J.
Published: February 2023

Fluoropolymers have weak electroactive properties but are often paired with other materials (inclusions) to form a composite with enhanced electroactive properties and when those inclusions are a metal or metalloid fuel (e.g., Al, Si, B) they can then function as electroactive reactive materials. There is strong interest in understanding the electromechanical (piezo, flexo, dielectric) properties toward the development of multifunctional energetics. Specifically, in this effort, we report the influence of magnesium diboride (MgB2) on the electroactive and combustion properties in a composite system with the fluoropolymer tetrafluoroethylene-hexafluoropropylene-vinylidene fluoride (THV). The dielectric, flexoelectric, piezoelectric, burning rate, and heat of reaction are investigated for composites with 50–70 wt. % MgB2 loading. It is observed that with an increase in solids loading that the dielectric, flexoelectric, and burning rate increase. For example, at 70 wt. % MgB2, the measured dielectric constant was 298 ± 10, and the flexoelectric coefficient was 16.6 ± 1.2 nC/m. Unexpectedly, a true piezoelectric coefficient (d33) was measured between 11.4 ± 0.2 and 13.0 ± 0.3 pC/N at these solids loadings. Due to the mechanical properties of these composite systems, an apparent piezoelectric coefficient of 108 pC/N was calculated indicating that these reactive materials are highly electroactive. The multifunctional properties are demonstrated by applying the force of the human body (via jumping) to a THV/MgB2 (50 wt. %) film. A peak voltage of 0.75 V was observed. This work indicates that a variety of reactive materials may offer multifunctional capabilities.
Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers
Authors: Saha Soumyadeep , Sachdev Manoj , Mitra Sushanta K.
Published: February 2023

Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.
A study of the valence photoelectron spectrum of uracil and mixed water–uracil clusters
Authors: Mattioli Giuseppe , Avaldi Lorenzo , Bolognesi Paola , Casavola Annarita , Morini Filippo , Van Caekenberghe Thomas , Bozek John D. , Castrovilli Mattea C. , Chiarinelli Jacopo , Domaracka Alicja , Indrajith Suvasthika , Maclot Sylvain , Milosavljević Aleksandar R. , Nicolafrancesco Chiara , Nicolas Christophe , Rousseau Patrick
Published: February 2023

The valence ionization of uracil and mixed water–uracil clusters has been studied experimentally and by ab initio calculations. In both measurements, the spectrum onset shows a red shift with respect to the uracil molecule, with the mixed cluster characterized by peculiar features unexplained by the sum of independent contributions of the water or uracil aggregation. To interpret and assign all the contributions, we performed a series of multi-level calculations, starting from an exploration of several cluster structures using automated conformer-search algorithms based on a tight-binding approach. Ionization energies have been assessed on smaller clusters via a comparison between accurate wavefunction-based approaches and cost-effective DFT-based simulations, the latter of which were applied to clusters up to 12 uracil and 36 water molecules. The results confirm that ( i) the bottom-up approach based on a multilevel method [Mattioli et al. Phys. Chem. Chem. Phys. 23, 1859 (2021)] to the structure of neutral clusters of unknown experimental composition converges to precise structure–property relationships and ( ii) the coexistence of pure and mixed clusters in the water–uracil samples. A natural bond orbital (NBO) analysis performed on a subset of clusters highlighted the special role of H-bonds in the formation of the aggregates. The NBO analysis yields second-order perturbative energy between the H-bond donor and acceptor orbitals correlated with the calculated ionization energies. This sheds light on the role of the oxygen lone-pairs of the uracil CO group in the formation of strong H-bonds, with a stronger directionality in mixed clusters, giving a quantitative explanation for the formation of core–shell structures.
A hybrid approach for coarse-graining helical peptoids: Solvation, secondary structure, and assembly
Authors: Banerjee Akash , Dutt Meenakshi
Published: February 2023

Protein mimics such as peptoids form self-assembled nanostructures whose shape and function are governed by the side chain chemistry and secondary structure. Experiments have shown that a peptoid sequence with a helical secondary structure assembles into microspheres that are stable under various conditions. The conformation and organization of the peptoids within the assemblies remains unknown and is elucidated in this study via a hybrid, bottom-up coarse-graining approach. The resultant coarse-grained (CG) model preserves the chemical and structural details that are critical for capturing the secondary structure of the peptoid. The CG model accurately captures the overall conformation and solvation of the peptoids in an aqueous solution. Furthermore, the model resolves the assembly of multiple peptoids into a hemispherical aggregate that is in qualitative agreement with the corresponding results from experiments. The mildly hydrophilic peptoid residues are placed along the curved interface of the aggregate. The composition of the residues on the exterior of the aggregate is determined by two conformations adopted by the peptoid chains. Hence, the CG model simultaneously captures sequence-specific features and the assembly of a large number of peptoids. This multiscale, multiresolution coarse-graining approach could help in predicting the organization and packing of other tunable oligomeric sequences of relevance to biomedicine and electronics.
An assessment of the spatial distribution of bulk billing-only GP services in Australia in relation to area-based socio-economic status
Authors: Graham Bree , Kruger Estie , Tennant Marc , Shiikha Yulia
Published: February 2023

Background The accessibility to affordable primary healthcare services contributes to population health and health equity. A key aspect to accessibility is the geographical distribution of primary healthcare services. Limited studies have assessed the nationwide spatial distribution of bulk billing-only medical practices or ‘no-fee’ services. The aim of this study was to provide a nationwide approximation of bulk billing-only services and evaluate the socio-demographic status and population characteristics in relation to the distribution of bulk billing-only GP services. Methods The methodology in this study used Geographic Information System (GIS) technology to map the locations of all bulk bulking-only medical practices collected in mid-2020 and linked this with population data. The population data and practice locations were analysed at the level of Statistical Areas Level 2 (SA2) regions and used the most recent Census data. Results The study sample included (n = 2095) bulk billing-only medical practice locations. The nationwide average Population-to-Practice (PtP) ratio was 1 practice to 8529 people for regions with access to bulk billing-only practice, and 57.4% of the Australian population lives within an SA2 that has access to at least one bulk billing-only medical practices. No significant associations were identified between practice distribution and area socio-economic status. Conclusion The study identified areas with low access to affordable GP services, with many SA2 regions having no access to bulk billing-only practices. Findings also indicate that there was no association between area socio-economic status and the distribution of bulk billing-only services.
The potential distribution of the yellow monitor, Varanus flavescens (Hardwick & Gray) under multiple climate, land cover and dispersal scenarios in Nepal
Authors: Baral Suraj , Kunwar Amar , Adhikari Dipendra , Kandel Kanti , Mandal Dev Narayan , Thapa Arjun , Neupane Dinesh , Thapa Tej B.
Published: February 2023

Context Human-induced changes in climate and land cover have altered the distribution of fauna around the globe. Some reptiles have been found to be vulnerable to these changes; therefore, studies to identify the impact of the changes on other groups of reptiles are necessary. Aims We aimed to study the impact of climate and land cover change on the yellow monitor (Varanus flavescens) in Nepal. We also aimed to identify the current distribution range and predict the potential distribution under multiple climate change, corresponding land cover change, and dispersion scenarios in the near- and mid-future. Methods We used available presence locations with a candidate set of the least-correlated environmental variables and an Ensemble of Small Models (ESM), a Species Distribution Model (SDM) approach suitable for species with small sample size. Additionally, dispersal scenarios of 1 km, 5 km, and 10 km were added to the model to determine the future distribution under the dispersal scenarios. Key results We found soil particle size, distance to forest, precipitation of wettest quarter, bulk density, and elevation were the five most important variables contributing to the distribution of the species. The Terai lowland and wide valleys in Outer Himalayas are currently suitable but are expected to experience a substantial decrease under most future climate projections and dispersal scenarios. Conclusions The distribution is mostly dependent on soil-related variables; however, climatic variables might have a greater impact on future suitability. Implications Limiting emissions contributing to climatic changes, conserving the soil outside the protected areas, and the potential areas where the species will not experience habitat loss might contribute to the conservation of the species.
Authoritarianism on the Front Page
Authors: Serafis Dimitris
Published: February 2023

This volume offers a critical discursive-argumentative framework that scrutinizes the discursive construction and, moreover, the argumentative justification of authoritarian attitudes on newspaper front pages in highly polarized times of multiple ‘crises’ in Greece. At the same time, it aspires to outline novel research avenues for scholars working in the fields of critical discourse and argumentation studies, multimodality and communication studies, that go beyond the study of the meaning potential of multimodal artifacts and focus on the study of the argumentative inferences that are triggered by multimodal discourses in polarized contexts. It frames the theoretical discussion based on concepts such as Nikos Poulantzas’ ‘authoritarian statism’ as well as Antonio Gramsci’s ‘hegemony’ and ‘intellectuals’. Methodologically, it draws on the agenda of multimodal critical discourse analysis, integrating principles and tools from social semiotics and (multimodal) argumentation studies with a particular focus on inference in argumentation.
Diagnosing perilymphatic fistula with 3D flair MRI
Authors: Kemps Glen , Mistry Jayran , Connor Steve , Obholzer Rupert , Ainsworth Carolyn
Published: February 2023

Introduction

The diagnosis of a perilymphatic fistula (PLF) has long been a challenge, as its presentation is variable and can mimic other vestibular disorders. Currently, it is suggested that resolution of symptoms after treatment should be used as a gold standard in diagnosing PLF. Recently, improvement in Magnetic Resonance Imaging (MRI) have caused PLF to be diagnosed more consistently with a higher sensitivity and specificity, preceding surgery.

Case report

We report a 43-year-old patient, who was seen with progressive vertigo since 15 years, triggered by bending forward, and lasting from 20 min to 2 h. During these spells, she would also have pulse-synchronous tinnitus and mild left-sided mixed hearing loss. Physical examination was normal and vestibular function tests did not reveal evidence of peripheral or central audiovestibular dysfunction. Delayed acquisition MRI, with 3-dimensional fluid attenuated inversion recovery (3D FLAIR) of the inner ear displayed a left ‘round window sign’ (RWS): focal enhancement in the round window niche. There were no signs of vestibular or cochlear hydrops to suggest Meniere’s syndrome. Her symptoms resolved after surgery.

Conclusion

RWS on 3D FLAIR MRI sequence seems to be a sensitive and specific pre-operative diagnostic phenomenon for the detection of PLF.
B-1 plasma cells require non-cognate CD4 T cell help to generate a unique repertoire of natural IgM
Authors: Smith Fauna L. , Savage Hannah P. , Luo Zheng , Tipton Christopher M. , Lee F. Eun-Hyung , Apostol April C. , Beaudin Anna E. , Lopez Diego A. , Jensen Ingvill , Keller Stefan , Baumgarth Nicole
Published: February 2023

Evolutionarily conserved, “natural” (n)IgM is broadly reactive to both self and foreign antigens. Its selective deficiency leads to increases in autoimmune diseases and infections. In mice, nIgM is secreted independent of microbial exposure to bone marrow (BM) and spleen B-1 cell–derived plasma cells (B-1PC), generating the majority of nIgM, or by B-1 cells that remain non-terminally differentiated (B-1sec). Thus, it has been assumed that the nIgM repertoire is broadly reflective of the repertoire of body cavity B-1 cells. Studies here reveal, however, that B-1PC generate a distinct, oligoclonal nIgM repertoire, characterized by short CDR3 variable immunoglobulin heavy chain regions, 7–8 amino acids in length, some public, many arising from convergent rearrangements, while specificities previously associated with nIgM were generated by a population of IgM-secreting B-1 (B-1sec). BM, but not spleen B-1PC, or B-1sec also required the presence of TCRαβ CD4 T cells for their development from fetal precursors. Together, the studies identify important previously unknown characteristics of the nIgM pool.
Synergistic effect of total ionizing dose on single-event gate rupture in SiC power MOSFETs
Authors: Cao Rongxing , Wang Kejia , Meng Yang , Li Linhuan , Zhao Lin , Han Dan , Liu Yang , Zheng Shu , Li Hongxia , Jiang Yuqi , Zeng Xianghua , Xue Yuxiong
Published: February 2023

The synergistic effect of total ionizing dose (TID) and single event gate rupture (SEGR) in SiC power metal–oxide–semiconductor field effect transistors (MOSFETs) is investigated via simulation. The device is found to be more sensitive to SEGR with TID increasing, especially at higher temperature. The microscopic mechanism is revealed to be the increased trapped charges induced by TID and subsequent enhancement of electric field intensity inside the oxide layer.
Hysteresis loss free soft magnetic ferrites based on Larmor precession
Authors: Feng Shuang-Jiu , Zhao Xin-Li , Zhu Shou-Jin , Lv Qing-Rong , Kan Xu-Cai , Liu Xian-Song
Published: February 2023

A big enough transverse magnetic field applied to soft magnetic ferrite toroid can magnetize the ferrite to a saturation level in transverse direction and almost completely suppresses magnetic domain structures in the ferrite, the response to the longitudinal alternating electromagnetic field changes from the original domain wall displacements and spin rotations to the precession of magnetization around the transverse field, and the hysteresis loss disappears in the ferrites. Both theoretical and experimental results indicate that the permeability and magnetic loss in the ferrite can be controlled by adjusting the transverse magnetic field. A higher Q value with relatively low permeability can be achieved by increasing the transverse field, which ensures that the ferrite can be operated at high frequencies, with magnetic loss being very low.
Energy conversion materials for the space solar power station
Authors: Ren Xiao-Na , Ge Chang-Chun , Chen Zhi-Pei , Irfan 凡 , Tu Yongguang , Zhang Ying-Chun , Wang Li , Liu Zi-Li , Guan Yi-Qiu
Published: February 2023

Since it was first proposed, the space solar power station (SSPS) has attracted great attention all over the world; it is a huge space system and provides energy for Earth. Although several schemes and abundant studies on the SSPS have been proposed and conducted, it is still not realized. The reason why SSPS is still an idea is not only because it is a giant and complex project, but also due to the requirement for various excellent space materials. Among the diverse required materials, we believe energy materials are the most important. Herein, we review the space energy conversion materials for the SSPS.
Scheduling multi-pattern precooling service resources for post-harvest fruits and vegetables using the adaptive large neighborhood search
Authors: Lin Na , Yang Huimin , Li Ya , Wang Xuping
Published: February 2023

This study focuses on the multi-pattern precooling service resources scheduling (MPPSRS) issue recently derived from the practice of small-scale farming. In this issue, a heterogeneous fleet of vehicles belonging to different service pattens is considered to fulfil precooling requests of farmers in the service time windows. The studied issue is regarded as a variant of heterogeneous fleet vehicle routing problem with time windows (HFVRPTW) in which heterogeneous service efficiencies among vehicles are considered. To the best of our knowledge, this is the first time that such a characteristic of vehicles’ heterogenous service efficiencies is considered in vehicle routing problems. This new characteristic increases the potential combination ways of nodes in the temporal aspect, which expands the search space of the problem and leads to a more challenging optimization issue. This study formulates the MPPSRS issue using a mixed-integer programming model in which details from the real world are considered. Motivated by the challenge of computational time, an adaptive large neighborhood search (ALNS) metaheuristic is proposed to solve the model. Results obtained from a case study of the apple industry from Luochuan County, China show advantages of using multi-pattern precooling service resources in reducing total operating cost.
Research on the Prediction of Ancient Glass Artifact Types based on XGBoost and Random Forest Algorithm
Authors: Li Zeyan , Wang Yanting , Zhao Shuyue
Published: February 2023

Ancient Chinese glass is susceptible to weathering by environmental influences, and its chemical composition has changed considerably thus affecting the category judgment. The classification of ancient glass is mainly divided into two types: high potassium and lead-barium. In this paper, in order to determine the type of ancient glass according to its chemical composition, the multicollinearity phenomenon of many chemical compositions is reduced by using LDA model and then the parameters of XGBoost and RF models are optimized by using GA algorithm and the five-fold cross-validation of existing data sets, and then the weights of XGBoost and RF are optimized by GA algorithm, and finally the GA - XGBoost - RF dual optimization model. The predicted categories can be derived by bringing the chemical composition content of unknown categories of artifacts into the well-trained model, which provides more accurate and faster categorization guidance for ancient glass artifact types to a certain extent.
Design of Recommendation Algorithm Based on Knowledge Graph
Authors: Fang Xue , Li Lin , Wei Zheng
Published: February 2023

The commodity data in the shopping system contains a wealth of feature information, and different commodities are related by these features. Traditional collaborative filtering algorithms represent commodity data in a structured way, but they have issues such as low commodity similarity calculation accuracy, poor recommendation effect, and unfriendly recommendation results. The commodity recommendation algorithm based on the knowledge graph put forward in this paper initially automatically extracts the entities and entity relationships in the commodity data as the vertices and edges of the graph and then stores the commodity data in the Neo4j graph database. Finally, the similarity between commodities is calculated based on the graph’s path similarity, and the list of TOP-K commodities with the highest similarity is chosen for recommendation. The experimental findings indicate that the recommendation algorithm based on the knowledge graph can not only more accurately represent the similarity between commodities, but also that the graph structure can display the recommended path in a more user-friendly manner, and has better recommendation explainability as well as higher recommendation trust.
A low-light image enhancement method based on AUDD-GAN
Authors: Zhao Longyang , Li Xinran , Meng Ruimin
Published: February 2023

A large number of images taken under conditions of insufficient lighting, often with overall darkness, low contrast, noise and inconspicuous details, thus affecting people’s observation of the image content and the subsequent use of the image. This paper presents a novel method, Attention U-Net Dual Discriminator-Generative Adversarial Networks (AUDD-GAN), which combines attention mechanism, U-Net network structure and the dual discriminator. First, the method generates a normalized attention map to guide the subsequent modules to perform illumination enhancement to prevent overexposure or underexposure problems; second, the U-Net generative network extracts characteristics of diverse levels to acquire richer detail information; then, a dual discriminator is used as the discriminative network, where PatchGAN is used as the local discriminator to achieve better enhancement effects; ultimately, we combine multiple loss functions as the joint loss function. AUDD-GAN is verified to enhance the global contrast of the image while enhancing the detail features more effectively.
Application of Self-supervised Learning in Non-intrusive Load Monitoring
Authors: Tan Zhukui , Liu Bin , Xu Yutao , Feng Shengyong , Zhao Haixiang
Published: February 2023

With the proposal of smart grid, the demand of both source and load for fine monitoring and control of power load is becoming increasingly prominent. Non-intrusive load monitoring is a technical means to better meet this demand. However, the research at home and abroad focuses on the existing data sets and labeled data to improve the accuracy of load identification, while the research on the training method of the model under the massive unlabeled monitoring data in the actual scene is still in a relatively blank stage. Aiming at the problem of how to make full use of unlabeled monitoring data for model training, a non-intrusive-load monitoring method based on self-supervised learning is proposed in this paper. This method designs a self-supervised learning task, so that the model can make full use of the massive unlabeled monitoring data for training, eliminating the step of manually labelling the data; Based on the encoder-decoder structure, a deep learning model is established, and the load is identified through the load characteristic vector output by the encoder, so that the method has generalization performance. In this paper, AMPds2 data set is used to verify the method, and test examples verify the effectiveness of the method.
Convolutional Neural Networks Combined with Machine Vision for Mechanical Compressor Defect Detection
Authors: Li Kunshan
Published: February 2023

The study aims to detect the defects in the production line of compressor, promote the development of convolution neural network (CNN) in defect diagnosis and recognition, and expand the application of intelligent algorithm tools in the detection and recognition of defect and fault. The detection and recognition of the defects in the compressor workpiece were discussed based on the optimization of CNN. First, the active learning under the background of machine learning (ML) was introduced into the selection of sample training model for the annotation of massive data sets in diagnosing the compressor defect, and compared with the random selection method. Second, aiming at the limitation of deep CNN, through the introduction of deep separable convolution and reverse residual structure, an improved space-separable residual CNN model was proposed, and its training process was observed and analyzed. Finally, the improved space-separable residual CNN model was applied to the defect detection and recognition of compressor workpiece, and the effect of defect recognition was evaluated. The results showed that the accuracy of the active learning was higher than that of the random selection, and it can save about 18.76% of the cost of manual annotation data. The recognition accuracy of the improved CNN model is more than 90%, and the accuracy curve of the training set and the test set basically coincided in the later training period. The average recognition accuracy of the compressor defect detection model was 96.87%, and the normal workpiece could be fully recognized. The combination of improved and optimized CNN and ML has great potential in the detection of compressor defect.
Analysis of Chinese Named Entity Recognition Results Based on Different Paradigm
Authors: Luan Fangjun , Sun Xiaotang
Published: February 2023

Named-entity recognition (NER) is a sub-task of information extraction. Currently, there are various approaches to achieve the NER task and the results are getting better. However, the internal structure of the models is becoming more and more complex, making them much less comparable. In view of the above reasons, we categorize NER methods and implement three different NER paradigms (classification-based model, sequence annotation-based model, and pointer network-based model) using the simplest structure for three Chinese NER datasets (PeopleDailyNER, FinanceSinaNER, and CLUENER). We find that the pointer network-based model works well for datasets with short sentence lengths and large data sizes; the classification-based model is good for datasets with large data sizes and numerous entity categories; in the vast majority of cases, the sequence annotation-based model has better entity recognition performance than the other two models.
Research on online test question recommendation technology based on multi-dimensional user dynamic portrait
Authors: Lei Qingfeng , Yang Hua , Deng Taiyong , Liu Jiangrong , Jiang Falin
Published: February 2023

This paper proposes a research method of personalized recommendation of test questions for users by fully collecting and studying the user’s characteristic data in multiple dimensions, establishing a dynamic user portrait, and mining and analyzing the characteristic information of test questions in the test question bank. Firstly, collect the user’s data, calculate the user’s similarity by analyzing the user’s behavior sequence, and use the cosine similarity algorithm to calculate the text similarity of the test questions. Then, the tag system is established to analyze the user activity, and the TF-IDF algorithm is used to calculate the user’s proficiency in different keyword classification questions. Based on the above information, a hybrid recommendation mechanism is adopted to provide users with personalized test question recommendation services.
The Design of Calibration System Based on Cable Accessories
Authors: Zhao Tiemin , Liu Jianshu , Zheng Shiyang , LeYang  , Ding Zhen , Li Dongsheng , Li Kai , Li Wenpeng , Yang Xue , Chai Fangsen
Published: February 2023

In today’s society, people can’t live without electricity. During the operation of power equipment, there may be various potential safety risks. In particular, partial discharge is easy to occur at the terminal. If people can not deal with the problem of partial discharge in time, equipment continue to live.Setting can cause security, so the electric power industry staff attaches great importance to the local discharge monitoring problem.Ultrasonic technology is better so it is gradually into the application of partial discharge detection.But the ultrasonic detection technology is to detect the intensity of ultrasound, and our traditional method is to measure the discharge of partial discharge method, Therefore, in order to obtain the relationship between ultrasonic intensity and partial discharge, the following experiments are made. After we pass the power frequency voltage withstand device, the transformer is continuously pressurized.Gain DB and discharge PC were obtained by digital partial discharge instrument and ultrasonic partial discharge instrument. After fitting, the linear relation is obtained and the quality inspection of PD detector is completed.It can make the detection effect of partial discharge detector more complete, and provide the basis for the quality inspection of the detector, This system also provides a strong support for the wide application of ultrasonic partial discharge detector.
Research on short-term power load forecasting method based on multi-factor feature analysis and LSTM
Authors: Zeng Bing , Qiu Yupeng , Yang Xiaopin , Chen Wu , Xie Yunmin , Wang Yifan , Jiang Pengfei
Published: February 2023

In order to improve the accuracy of short-term power load forecasting and fully consider the influence of weather factors on power load, a short-term power load forecasting model based on multi-factor analysis and Long-Short Term Memory (LSTM) neural network is proposed. Firstly, the correlation between different weather factors and load is analysed using the Spearman coefficient method to extract the weather features that have a greater impact on power load. Then the original time series data are reconstructed using the sliding window method. Finally, the forecasting model is established by using LSTM. The proposed model is validated by using the power load data from the 2016 Electrician’s Cup modelling competition, and compared with other models. The results show that the average absolute percentage error of the forecasting model proposed in this paper reaches 7.41% and the average absolute value error is 380.67 MW, which is better than the other models mentioned in the paper.
Study on ultrasonic detection method of a honeycomb sandwich panel
Authors: Wang Zhulin , He Xiao
Published: February 2023

A new material for the structure of the honeycomb sandwiched XinBi board has been in active service. In this paper, structural defects are embedded in the easily damaged parts of this new material, and the ultrasonic method is used to detect the easily damaged parts, and the acoustic signals and defect echo signals of the easily damaged parts are obtained, which provides a reference for damage evaluation of this kind of structures in site detection.