bluuebunny/crossref_metadata_2025 huggingface dataset:
Using a Bayesian hierarchical approach to study the association between non-pharmaceutical interventions and the spread of Covid-19 in Germany
Authors: Khazaei Yeganeh , Küchenhoff Helmut , Hoffmann Sabine , Syliqi Diella , Rehms Raphael
Published: November 2023

Non-Pharmaceutical Interventions (NPIs) are community mitigation strategies, aimed at reducing the spread of illnesses like the coronavirus pandemic, without relying on pharmaceutical drug treatments. This study aims to evaluate the effectiveness of different NPIs across sixteen states of Germany, for a time period of 21 months of the pandemic. We used a Bayesian hierarchical approach that combines different sub-models and merges information from complementary sources, to estimate the true and unknown number of infections. In this framework, we used data on reported cases, hospitalizations, intensive care unit occupancy, and deaths to estimate the effect of NPIs. The list of NPIs includes: “contact restriction (up to 5 people)”, “strict contact restriction”, “curfew”, “events permitted up to 100 people”, “mask requirement in shopping malls”, “restaurant closure”, “restaurants permitted only with test”, “school closure” and “general behavioral changes”. We found a considerable reduction in the instantaneous reproduction number by “general behavioral changes”, “strict contact restriction”, “restaurants permitted only with test”, “contact restriction (up to 5 people)”, “restaurant closure” and “curfew”. No association with school closures could be found. This study suggests that some public health measures, including general behavioral changes, strict contact restrictions, and restaurants permitted only with tests are associated with containing the Covid-19 pandemic. Future research is needed to better understand the effectiveness of NPIs in the context of Covid-19 vaccination.
Doubly elastic net regularized online portfolio optimization with transaction costs
Authors: Yao Xiaoting , Zhang Na
Published: November 2023

Online portfolio optimization with transaction costs is a big challenge in large-scale intelligent computing community, since its undersample from rapidly-changing market and complexity from varying transaction costs. In this paper, we focus on this problem and solve it by machine learning system. Specifically, we reformulate the optimization problem with the minimization over simplex containing three items, which are negative expected return, the elastic net regularization of transaction costs controlled term and portfolio variable, respectively. We propose to apply linearized augmented Lagrangian method (LALM) and the alternating direction method of multipliers (ADMM) to solve the optimization model in a higher efficiency, meanwhile theoretically guarantee their convergence and deduce closed-form solutions of their subproblems in each iteration. Furthermore, we conduct extensive experiments on five benchmark datasets from real market to demonstrate that the proposed algorithms outperform compared state-of-the-art strategies in most cases in six dimensions.
Machine learning-based prediction model for emergency department visits using prescription information in community-dwelling non-cancer older adults
Authors: Park Soyoung , Lee Changwoo , Lee Seung-Bo , Lee Ju-yeun
Published: November 2023

Older adults are more likely to require emergency department (ED) visits than others, which might be attributed to their medication use. Being able to predict the likelihood of an ED visit using prescription information and readily available data would be useful for primary care. This study aimed to predict the likelihood of ED visits using extensive medication variables generated according to explicit clinical criteria for elderly people and high-risk medication categories by applying machine learning (ML) methods. Patients aged ≥ 65 years were included, and ED visits were predicted with 146 variables, including demographic and comprehensive medication-related factors, using nationwide claims data. Among the eight ML models, the final model was developed using LightGBM, which showed the best performance. The final model incorporated 93 predictors, including six sociodemographic, 28 comorbidity, and 59 medication-related variables. The final model had an area under the receiver operating characteristic curve of 0.689 in the validation cohort. Approximately half of the top 20 strong predictors were medication-related variables. Here, an ED visit risk prediction model for older people was developed and validated using administrative data that can be easily applied in clinical settings to screen patients who are likely to visit an ED.
Doxorubicin-induced modulation of TGF-β signaling cascade in mouse fibroblasts: insights into cardiotoxicity mechanisms
Authors: Patricelli Conner , Lehmann Parker , Oxford Julia Thom , Pu Xinzhu
Published: November 2023

Doxorubicin (DOX)-induced cardiotoxicity has been widely observed, yet the specific impact on cardiac fibroblasts is not fully understood. Additionally, the modulation of the transforming growth factor beta (TGF-β) signaling pathway by DOX remains to be fully elucidated. This study investigated DOX’s ability to modulate the expression of genes and proteins involved in the TGF-β signaling cascade in mouse fibroblasts from two sources by assessing the impact of DOX treatment on TGF-β inducible expression of pivotal genes and proteins within fibroblasts. Mouse embryonic fibroblasts (NIH3T3) and mouse primary cardiac fibroblasts (CFs) were treated with DOX in the presence of TGF-β1 to assess changes in protein levels by western blot and changes in mRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Our results revealed a dose-dependent reduction in cellular communication network factor 2 (CCN2) protein levels upon DOX treatment in both NIH3T3 and CFs, suggesting an antifibrotic activity by DOX in these fibroblasts. However, DOX only inhibited the TGF-β1 induced expression of COL1 in NIH3T3 cells but not in CFs. In addition, we observed that DOX treatment reduced the expression of BMP1 in NIH3T3 but not primary cardiac fibroblasts. No significant changes in SMAD2 protein expression and phosphorylation in either cells were observed after DOX treatment. Finally, DOX inhibited the expression of Atf4 gene and increased the expression of Cdkn1a, Id1, Id2, Runx1, Tgfb1, Inhba, Thbs1, Bmp1, and Stat1 genes in NIH3T3 cells but not CFs, indicating the potential for cell-specific responses to DOX and its modulation of the TGF-β signaling pathway.
A novel SARS-CoV-2 Beta RBD DNA vaccine directly targeted to antigen-presenting cells induces strong humoral and T cell responses
Authors: Kuczkowska Katarzyna , Bjerkan Louise , Stubsrud Elisabeth , Husbyn Hannah Cuthbertson , Chellappa Stalin , Hauge Anette , Skarshaug Renate , Torgersen Maria Lyngaas , Heim Joel Benjamin , Jørgensen Marthe Jøntvedt , Wold Christian Winther , Schleimann Mariane Høgsbjerg , Tolstrup Martin , Granum Stine , Fredriksen Agnete Brunsvik , Pedersen Mikkel Wandahl , Norheim Gunnstein
Published: November 2023

Throughout the COVID-19 pandemic, several variants of concern (VoC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have evolved, affecting the efficacy of the approved COVID-19 vaccines. To address the need for vaccines that induce strong and persistent cross-reactive neutralizing antibodies and T cell responses, we developed a prophylactic SARS-CoV-2 vaccine candidate based on our easily and rapidly adaptable plasmid DNA vaccine platform. The vaccine candidate, referred to here as VB2129, encodes a protein homodimer consisting of the receptor binding domain (RBD) from lineage B.1.351 (Beta) of SARS-CoV-2, a VoC with a severe immune profile, linked to a targeting unit (human LD78β/CCL3L1) that binds chemokine receptors on antigen-presenting cells (APCs) and a dimerization unit (derived from the hinge and CH3 exons of human IgG3). Immunogenicity studies in mice demonstrated that the APC-targeted vaccine induced strong antibody responses to both homologous Beta RBD and heterologous RBDs derived from Wuhan, Alpha, Gamma, Delta, and Omicron BA.1 variants, as well as cross-neutralizing antibodies against these VoC. Overall, preclinical data justify the exploration of VB2129 as a potential booster vaccine that induces broader antibody- and T cell-based protection against current and future SARS-CoV-2 VoC.
Glucocorticoids alleviate particulate matter-induced COX-2 expression and mitochondrial dysfunction through the Bcl-2/GR complex in A549 cells
Authors: Park Yeon-Ji , Heo June , Kim Yonghyeon , Cho Hyeseong , Shim Myeongkuk , Im Kyunghyun , Lim Wonchung
Published: November 2023

Exposure to particulate matter (PM) causes mitochondrial dysfunction and lung inflammation. The cyclooxygenase-2 (COX-2) pathway is important for inflammation and mitochondrial function. However, the mechanisms by which glucocorticoid receptors (GRs) suppress COX-2 expression during PM exposure have not been elucidated yet. Hence, we examined the mechanisms underlying the dexamethasone-mediated suppression of the PM-induced COX-2/prostaglandin E2 (PGE2) pathway in A549 cells. The PM-induced increase in COX-2 protein, mRNA, and promoter activity was suppressed by glucocorticoids; this effect of glucocorticoids was antagonized by the GR antagonist RU486. COX-2 induction was correlated with the ability of PM to increase reactive oxygen species (ROS) levels. Consistent with this, antioxidant treatment significantly abolished COX-2 induction, suggesting that ROS is involved in PM-mediated COX-2 induction. We also observed a low mitochondrial membrane potential in PM-treated A549 cells, which was reversed by dexamethasone. Moreover, glucocorticoids significantly enhanced Bcl-2/GR complex formation in PM-treated A549 cells. Glucocorticoids regulate the PM-exposed induction of COX-2 expression and mitochondrial dysfunction and increase the interaction between GR and Bcl-2. These findings suggest that the COX-2/PGE2 pathway and the interaction between GR and Bcl-2 are potential key therapeutic targets for the suppression of inflammation under PM exposure.
Evaluation of COVID-19 intervention policies in South Korea using the stochastic individual-based model
Authors: Chae Min-Kyung , Hwang Dong-Uk , Nah Kyeongah , Son Woo-Sik
Published: November 2023

The COVID-19 pandemic has swept the globe, and countries have responded with various intervention policies to prevent its spread. In this study, we aim to analyze the effectiveness of intervention policies implemented in South Korea. We use a stochastic individual-based model (IBM) with a synthetic population to simulate the spread of COVID-19. Using statistical data, we make the synthetic population and assign sociodemographic attributes to each individual. Individuals go about their daily lives based on their assigned characteristics, and encountering infectors in their daily lives stochastically determines whether they are infected. We reproduce the transmission of COVID-19 using the IBM simulation from November 2020 to February 2021 when three phases of increasingly stringent intervention policies were implemented, and then assess their effectiveness. Additionally, we predict how the spread of infection would have been different if these policies had been implemented in January 2022. This study offers valuable insights into the effectiveness of intervention policies in South Korea, which can assist policymakers and public health officials in their decision-making process.
Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish
Authors: Koeberle Alexander L. , Pearsall Webster , Hammers Brad E. , Mulhall Daniel , McKenna James E. , Chalupnicki Marc , Sethi Suresh A.
Published: November 2023

Estimates of juvenile survival are critical for informing population dynamics and the ecology of fish, yet these demographic parameters are difficult to measure. Here, we demonstrate that advances in animal tracking technology provide opportunities to evaluate survival of juvenile tagged fish. We implemented a whole-lake telemetry array in conjunction with small acoustic tags (including tags < 1.0 g) to track the fate of stocked juvenile cisco (Coregonus artedi) as part of a native species restoration effort in the Finger Lakes region of New York, USA. We used time-to-event modeling to characterize the survival function of stocked fish, where we infer mortality as the cessation of tag detections. Survival estimates revealed distinct stages of juvenile cisco mortality including high immediate post-release mortality, followed by a period of elevated mortality during an acclimation period. By characterizing mortality over time, the whole-lake biotelemetry effort provided information useful for adapting stocking practices that may improve survival of stocked fish, and ultimately the success of the species reintroduction effort. The combination of acoustic technology and time-to-event modeling to inform fish survival may have wide applicability across waterbodies where receiver arrays can be deployed at scale and where basic assumptions about population closure can be satisfied.
Mercury determination in various environmental, food and material complex matrices using unified operating conditions for a cold vapor generation high-resolution continuum source quartz tube atomic absorption spectrometry method
Authors: Chirita Lucia , Covaci Eniko , Ponta Michaela , Frentiu Tiberiu
Published: November 2023

A sensitive, free-of-interference, broadly applicable method for Hg determination in various matrices by cold vapor high-resolution continuum source quartz tube atomic absorption spectrometry using unified operating conditions was proposed.
A low-cost optofluidic platform for the colorimetric assessment of bacterial activity in domestic wastewater
Authors: Chettri Prajal , Ganesh Kalathur Mohan , Mahapatra Sahashransu Satyajeet , Vishwanathan A. S. , Srivastava Shailesh
Published: November 2023

We present an innovative, cost-effective photodiode-based device with high sensitivity for microscale assessment of bacterial activity with a significant potential for applications in wastewater management and assessment of antimicrobial activity.
Cation-doped sea-urchin-like MnO2 for electrocatalytic overall water splitting
Authors: Sun Haolu , Chen Songlin , Zhang Bo , Wang Jing , Yao Jun , Li Deming , Yuan Guojun
Published: November 2023

It is necessary to take full account of the activity, selectivity, dynamic performance, economic benefits, and environmental impact of the catalysts in the overall water splitting of electrocatalysis for the reasonable design of electrocatalysts.
Lithium intercalation in two-dimensional penta-NiN2: insights from NiN2/NiN2 homostructure and G/NiN2 heterostructure
Authors: Mahmoudi Mohsen , König Dirk , Tan Xin , Smith Sean C.
Published: November 2023

First-principles calculations are employed to investigate the intercalation of lithium atoms in the interlayer gap of nitrogen-rich 2D bilayer NiN2 for anode applications.
Support-facet-dependent morphology of small Pt particles on ceria
Authors: Eliasson Henrik , Niu Yubiao , Palmer Richard E. , Grönbeck Henrik , Erni Rolf
Published: November 2023

Time-resolved scanning transmission electron microscopy reveals a support-facet-dependence in the dimensionality of small Pt nanoparticles supported on CeO2(111) and CeO2(100).
Turning on hotspots: supracolloidal SERS probes made brilliant by an external activation mechanism
Authors: Jancke Sophie , Liu Chen , Wang Ruosong , Sarkar Swagato , Besford Quinn A. , König Tobias A. F. , Popp Jürgen , Cialla-May Dana , Rossner Christian
Published: November 2023

Dynamic hot-spot re-configuration in supracolloidal structures enables staged analyte uptake and subsequent boosted SERS capability.
Depletion force optimization for high-purity gold nanotriangles prepared using different growth methods
Authors: Yamada Ryuichi , Kimura Ryusei , Kuwahara Shota
Published: November 2023

The high purity of the gold nanotriangles produced using the seedless growth method required a larger depletion force than the seed-mediated grown gold nanoparticles.
Design, synthesis, and biological evaluation of new pyrimidine-5-carbonitrile derivatives as novel anti-cancer, dual EGFRWT/COX-2 inhibitors with docking studies
Authors: Reda Nada , Elshewy Ahmed , EL-Askary Hesham I. , Mohamed Khaled O. , Helwa Amira A.
Published: November 2023

A series of pyrimidine-5-carbonitriles was designed and synthesized as potential anti-cancer agents with dual EGFRWT/COX-2 inhibition. Compounds 4e and 4f disclosed the highest activity on all NCI60 cell lines.
Correction: Effects of graphene oxide size on curing kinetics of epoxy resin
Authors: Chen Xuebing , Jiang Weijiao , Hu Bo , Liang Zhiming , Zhang Yue , Kang Jian , Cao Ya , Xiang Ming
Published: November 2023

Correction for ‘Effects of graphene oxide size on curing kinetics of epoxy resin’ by Xuebing Chen et al., RSC Adv., 2021, 11, 29215–29226, https://doi.org/10.1039/D1RA05234A.
Sustainable formulation polymers for home, beauty and personal care: challenges and opportunities
Authors: Picken Christina A. R. , Buensoz Orla , Price Paul D. , Fidge Christopher , Points Laurie , Shaver Michael P.
Published: November 2023

As researchers, industries and consumers move towards more sustainable products there is a clear need to define what sustainability means in fast moving consumer goods and how it can be considered at the design stage.
Trapped tracer in a non-equilibrium bath: dynamics and energetics
Authors: Goswami Koushik , Metzler Ralf
Published: November 2023

We study the dynamics of a tracer that is elastically coupled to active particles being kept at two different temperatures, as a prototype of tracer dynamics in a non-equilibrium bath.
Nanostructured metal oxide heterojunctions for chemiresistive gas sensors
Authors: Ma Shuai , Xu Jinyong
Published: November 2023

Metal oxides have been extensively used in environmental monitoring, breath analysis, and food quality assessment. This review summarizes the effects of nanoscale heterojunctions on enhancing the gas-sensing performance of metal oxide devices.
A rigid-flexible steric blocking strategy for highly bright and ultrawide piezochromism in the deep-red/near-infrared region
Authors: Li Chengjian , Zhang Qing , Sun Jingwei , Wang Kai , Ouyang Mi , Zhang Yujian
Published: November 2023

A rigid-flexible steric blocking strategy is proposed to effectively relieve luminescence quenching in the near-infrared (NIR) region and develop ultra-wide NIR piezochromic materials.
All organic double cable polymers of a polythiophene donor with rhodanine and perylene diimide acceptors and evaluation of photocurrent generation
Authors: Iqbal Sana , Khan Ammar Ahmed , Butt Nauman Zaffar , Ashraf Raja Shahid , Yameen Basit
Published: November 2023

Rhodanine and perylene diimide-based non-fullerene acceptors were covalently conjugated to a polythiophene donor. The new double cable polymers as photoactive layers in photodetectors exhibited marked enhancement in photocurrent generation.
Functional Magnetic Resonance Imaging Activation During Unscripted Discourse in People With Poststroke Aphasia
Authors: Maloney Thomas C. , Dietz Aimee , Vannest Jennifer , Wilkinson Krista , Szaflarski Jerzy P. , Stall Cassandra , Mamlekar Chitrali R.
Published: November 2023

Purpose:

The purpose of this project was to determine the feasibility of employing a functional magnetic resonance imaging (fMRI) task that captured activation associated with overt, unscripted (or free) discourse of people with aphasia (PWA), using a continuous scan paradigm.

Method:

Seven participants (six females, ages 48–70 years) with chronic poststroke aphasia underwent two fMRI scanning sessions that included a discourse fMRI paradigm that consisted of five 1-min picture description tasks, using personally relevant photographs, interspersed with two 30-s control periods where participants looked at a fixation cross. Audio during the continuous fMRI scan was collected and marked with speaking times and coded for correct information units. Activation maps from the fMRI data were generated for the contrast between speaking and control conditions. In order to show the effects of the multi-echo data analysis, we compared it to a single-echo analysis by using only the middle echo (echo time of 30 ms).

Results:

Through the implementation of the free discourse fMRI task, we were able to elicit activation that included bilateral regions in the planum polare, central opercular cortex, precentral gyrus, superior temporal gyrus, middle temporal gyrus, superior temporal gyrus, Crus I of the cerebellum, as well as bilateral occipital regions

Conclusions:

We describe a new tool for assessing discourse recovery in PWA. By demonstrating the feasibility of a natural language paradigm in patients with chronic, poststroke aphasia, we open a new area for future research.
Ebola-Virus- und Marburg-Viruserkrankung
Authors: Schmiedel Stefan , Wolf Timo
Published: November 2023

Was ist neu?

Ebola-Viruserkrankung Während der durch die Zaire-Virusvariante hervorgerufenen Ebola-Ausbrüche wurden klinische Studien mit Impfstoffen sowie antiviralen Substanzen durchgeführt. Aktuell stehen als Therapie die monoklonalen Antikörper Atoltivimab/Maftivimab/Odesivimab (kombiniert in Inmazeb) und Ansuvimab (Ebanga) zur Verfügung. Zur präventiven Impfung und zur Prä- und Postexpositionsprophylaxe einer Ebola-Virusinfektion (Variante Zaire) sind die Ebola-Zaire-Impfstoffe rVSVΔG-ZEBOV-GP, lebend (Ervebo), Ebola-Zaire-Impfstoff Ad26.ZEBOV-GP, rekombinant (Zabdeno) und der Ebola-Impfstoff (MVA-BN-Filo, rekombinant (Mvabea) geeignet.

Marburg-Viruserkrankung Es gibt derzeit kein zugelassenes Medikament zur Behandlung der Marburg-Viruserkrankung. Trotz erheblicher logistischer Schwierigkeiten und der Tatsache, dass die meisten Marburg-Ausbrüche eher zu klein waren, um Impfstoffstudien zu ermöglichen, wurden von der WHO 3 Impfstoffkandidaten für eine mögliche Studie favorisiert.
Curriculum for Early Exposure to Clinical Informatics and Data Science for Noninformatics Trainees to Promote Interest and Inclusion in Informatics
Authors: Ravi Akshay , Weia Benjamin , Sakumoto Matthew , Oates Aris , Liu Xinran
Published: November 2023

Background Curricula aimed at increasing exposure to informatics and practical data analytics among medical trainees could increase their effectiveness in clinical research, quality improvement, and clinical operations.

Objectives The Clinical Informatics Data Science (CI-DS) pathway is a cross-disciplinary curriculum aimed at improving informatics exposure among medical trainees. We describe the development of this novel curriculum, the inaugural cohort, and lessons learned.

Methods The CI-DS pathway is framed around upfront informatics didactics followed by a longitudinal, experiential training focused on mentorship, clinical data extraction/machine learning, and health technology governance. The curriculum was evaluated based on pre- and postpathway surveys completed by learners and logs of the elective activities selected by learners.

Results The CI-DS pathway attracted 19 learners across 12 medical subspecialties, from medical students to fellows. Baseline surveys showed limited exposure to informatics across learners. The top three longitudinal activities completed were participating in electronic health record (EHR) governance meetings, data science supplemental courses, and designated mentorship meetings. Comparison of baseline with postpathway surveys demonstrated significant improvements in learner self-reported confidence in appraising an EHR modification ticket, accessing UCSF's deidentified data, exploring a database with basic structured query language (SQL), extracting data using SQL, and interpreting machine learning models.

Conclusion An early exposure curriculum in clinical informatics with training in data extraction and governance can successfully recruit a diverse array of learners and improve confidence in practical informatics skills. We reflect on the strengths and weaknesses of this curriculum, and summarize the lessons learned to guide others in creating similar curricula for noninformatics clinicians.
Nonlinear dynamical analysis for globally modified incompressible non-Newtonian fluids
Authors: Caraballo Tomás , Carvalho Alexandre N. , López-Lázaro Heraclio
Published: November 2023

We present the global modification of the Ladyzhenskaya equations, for incompressible non-Newtonian fluids. This modification is through a cut-off function that multiplies the convective term of the equation and an additional artificial smoothing dissipation term as part of the viscous term of the equation. The goal of this work is the comparative analysis between the modified system and the non-modified system. Therefore, we show the existence and regularity of weak solutions, the existence of global attractors, the estimation of the fractal dimension of the global attractors, and finally, the relationship of the autonomous dynamics between the modified system and the non-modified system.
Nonlinear dynamics of small-scale Alfvén waves
Authors: Mallet Alfred , Dorfman Seth , Abler Mel , Bowen Trevor A. , Chen Christopher H. K.
Published: November 2023

We study the nonlinear evolution of very oblique small-scale Alfvén waves with k⊥di≳1. At these scales, the waves become significantly compressive, unlike in magnetohydrodynamics, due to the Hall term in the equations. We demonstrate that when frequencies are small compared to the ion gyrofrequency and amplitudes are small compared to unity, no new nonlinear interaction appears due to the Hall term alone at the lowest non-trivial order, even when k⊥di∼1. However, at the second non-trivial order, we discover that the Hall physics leads to a slow but resonant nonlinear interaction between co-propagating Alfvén waves, an inherently three-dimensional effect. Including the effects of finite temperature, finite frequency, and electron inertia, the two-fluid Alfvén wave also becomes dispersive once one or more of k⊥ρs, k⊥de, or k∥di becomes significant: for oblique waves at low β as studied here, this can be at a much smaller scale than di. We show that the timescale for one-dimensional steepening of two-fluid Alfvén waves is only significant at these smaller dispersive scales, and also derive an expression for the amplitude of driven harmonics of a primary wave. Importantly, both new effects are absent in gyrokinetics and other commonly used reduced two-fluid models. Our calculations have relevance for the interpretation of laboratory Alfvén wave experiments, as well as shedding light on the physics of turbulence in the solar corona and inner solar wind, where the dominant nonlinear interaction between counter-propagating waves is suppressed, allowing these new effects to become important.
Design of SiO2/4H–SiC MOS interfaces by sputter deposition of SiO2 followed by high-temperature CO2-post deposition annealing
Authors: Kil Tae-Hyeon , Kobayashi Takuma , Shimura Takayoshi , Watanabe Heiji
Published: November 2023

Oxidation of silicon carbide (SiC) is known to induce defects at the interface of the SiO2/SiC system. NO-annealing is a standard industrial method of nitridation, but oxidation may progress during NO-nitridation, which may generate interface defects. Here, we propose a new method of fabricating SiO2/SiC metal-oxide-semiconductor (MOS) devices: sputter deposition of SiO2 in an Ar/N2 gas mixture followed by high-temperature CO2-post deposition annealing to form SiO2 and incorporate nitrogen at the interface while suppressing oxidation of the SiC. We obtained the nitrogen depth profile by performing x-ray photoelectron spectroscopy and confirmed that most of the nitrogen atoms exist at the abrupt interface. While maintaining a low interface state density and good insulating property, we demonstrated much improved reliability of MOS devices compared to conventional NO-annealed samples, thanks to the well-designed SiO2/SiC interface by the proposed method.
Deformation and destruction of north-eastward drifting dipoles
Authors: Davies J. , Sutyrin G. G. , Crowe M. N. , Berloff P. S.
Published: November 2023

We systematically study the evolution of Larichev–Reznik dipoles in an equivalent-barotropic quasi-geostrophic beta-plane model in high-resolution numerical simulations. Our results shed light on the self-organization and rich dynamics of dipolar vortices, which are ubiquitous in geophysical flows. By varying both dipole strength and initial angle α0 of dipole tilt to the zonal direction, we discover new breakdown mechanisms of the dipole evolution. The dipoles are quickly destroyed by Rossby wave radiation, if initial tilt is too large or the dipole is too weak; otherwise, via damped oscillations, the dipoles tend to adjust themselves to different states drifting eastward. Two competing physical mechanisms that govern dipole transformations are found: (1) spontaneous dipole instability due to a growing critical linear mode and (2) meridional separation of dipole partners that accumulates over the adjustment period and prevents the above instability. Which mechanism prevails depends on the initial tilt and dipole strength, and the details of this are discussed.
On the Rosensweig instability of ferrofluid-infused surfaces under a uniform magnetic field
Authors: Li Xiang-Fan , Wang Ya-Ping , Zhang Yong-Chao , He Tian-Pei , Niu Xiao-Dong , Khan Adnan , Li De-Cai , Yamaguchi Hiroshi
Published: November 2023

This study numerically examines the Rosensweig instability of a ferrofluid-infused surface (FIS), which is an overlayer surface formed on the top of a porous substrate into which the ferrofluid is infused. FIS inherits the lubricating property of liquid-infused surfaces and the magnetic property of the ferrofluid, allowing an external control by a magnetic field. Currently, the evolution mechanisms of the Rosensweig instability of the FIS remain unclear. By using the recently developed coupled numerical scheme, which consists of the simplified multiphase lattice Boltzmann method and the self-correcting method for the Maxwell magnetic field equations, the intriguing mechanism and evolution dynamics of the ferrofluid spikes on the FIS are investigated systematically by examining the effects of overlayer thickness, substrate pore size, and magnetic field strength. The results are also analyzed by the Rosensweig instability theory. This study provides a theoretical and numerical basis for the magnetic field control of droplet or bubble motions on the FIS.
On the general classifiersgeandzàgin Hakka
Authors: Huang Han-Chun
Published: November 2023

This paper investigates the distribution and properties of the Hakka general classifiersgeandzàg. We focus on the [determiner/numeral + classifier + noun] construction where we observe the relations between the general classifiers and their following nouns, chosen based on their frequency in this construction. We adopt a corpus-based collostructional analysis which calculates the collocational strength values ofgeandzàgwith following nouns. A Hakka corpus was compiled for the study. The three-way distinction in the collostructional analysis (attractive, neutral, and repulsive) is directly mapped to acceptability of various degrees. The results show thatgeis highly correlated with human-denoting nouns, whereaszàgis highly correlated with animal-denoting nouns. Nouns denoting abstract entities or concrete objects without physical properties like size or shape usually lack specific classifiers, and bothgeandzàgcan collocate with them, albeit with varying degrees of preference. We argue that bothgeandzàgare general classifiers because both are more frequently used than specific classifiers and both exhibit disjointed semantic distribution and allow abstract nouns. While they show preferences for different nouns, requirements to qualify as general classifiers are equally met.
Electronic, magnetic, and structural properties of NiFeMnAl
Authors: Lukashev Pavel V , Wysong Jax , McFadden Stephen , Baker Gavin , Schmidt Brandon , Shand Paul M , Kharel Parashu
Published: November 2023

Half-metallic Heusler compounds have been extensively studied in the recent years, both experimentally and theoretically, for potential applications in spin-based electronics. Here, we present the results of a combined theoretical and experimental study of the quaternary Heusler compound NiFeMnAl. Our calculations indicate that this material is half-metallic in the ground state and maintains its half-metallic electronic structure under a considerable range of external hydrostatic pressure and biaxial strain. NiFeMnAl crystallizes in the regular cubic Heusler structure, and exhibits ferromagnetic alignment. The practical feasibility of the proposed system is confirmed in the experimental section of this work. More specifically, a bulk ingot of NiFeMnAl was synthesized in A2 type disordered cubic structure using arc melting. It shows a high Curie temperature of about 468 K and a saturation magnetization of 2.3

μ

B

/

f

.u

. The measured magnetization value is smaller than the one calculated for the ordered structure. This discrepancy is likely due to the A2 type atomic disorder, as demonstrated by our calculations. We hope that the presented results may be useful for researchers working on practical applications of spin-based electronics.
Multi-representation transferable attention network for remaining useful life prediction of rolling bearings under multiple working conditions
Authors: Shi Yabin , Cui Youchang , Cheng Han , Li Lin , Li Xiaopeng , Kong Xianguang
Published: November 2023

Remaining useful life (RUL) prediction improves equipment reliability by avoiding unexpected breakdowns. However, different operating conditions may cause the performance degradation of the prediction model due to the domain-shift problem. Therefore, a novel method based on the multiple representation transferable attention network (MRTAN) is proposed in this paper for RUL prediction under multiple working conditions. In the MRTAN-based method, multiple convolutional modules are first used to learn the degradation features. Next, the multi-representation adaptation module is utilized to further mine the multiple domain-invariant representations. Then, during the training process, the transferable attention module can activate the representation with high transferability dynamically. Finally, the prognostic model is optimized by multiple optimization objectives and the back-propagation algorithm. Besides, multiple cross-domain RUL prediction tasks are employed to validate the effectiveness of the MRTAN-based model. Experiments demonstrate that the proposed method can provide better prognostic performance and avoid the negative transfer problem.
Improved artificial gorilla troops optimizer with chaotic adaptive parameters - application to the parameter estimation problem of mixed additive and multiplicative random error models
Authors: Wang Leyang , Han Shuhao , Pang Ming
Published: November 2023

For mixed additive and multiplicative random error models (MAM models), due to the complex correlation between the parameters and the model power array, derivative operations will be inevitable in the actual calculation. When the observation equation is in nonlinear form, the operations will be more complicated. The swarm intelligence optimization algorithm (SIO) can effectively solve the derivative problem when estimating the nonlinear model parameters using conventional iterative algorithms. However, for different problems, the conventional SIO cannot effectively balance the ability of global and local behavior, resulting in the algorithm falling into prematureness and failing to output effective parameter information. To address the above problems, the improved artificial gorilla troops optimizer (CAGTO) algorithm with chaotic adaptive behavior is proposed. To address the problem that the population generated by the algorithm using pseudo-random numbers in the initialization population phase has poor traversability in the feasible domain, the chaotic sequence is applied to initialize the population instead of pseudo-random number generation to ensure that the population can traverse the feasible domain as much as possible and improve the global search capability of the algorithm. Adaptive parameters that vary linearly and nonlinearly with the algorithm process are constructed to balance the global search and local search ability, while accelerating the convergence speed. Two CAGTO algorithms with different parameter settings are constructed for different problems, and the experimental results show that both CAGTO algorithms can effectively solve the parameter estimation problem of MAM models with different nonlinear forms of observation equations compared with several other comparative algorithms.
A state detection method of offshore wind turbines’ gearbox bearing based on the transformer and GRU
Authors: Zhao Zi-han , Wang Qiang , Shao Chang-sheng , Chen Ning , Liu Xin-yao , Wang Guang-bin
Published: November 2023

Through the analysis of data from the SCADA system of a wind turbine unit in a specific offshore wind farm located in Zhanjiang, it was observed that the most prevalent type of fault is bearing alarms on the gearbox’s generator side. Considering the growing need for intelligent offshore wind turbine maintenance, this study employed GRA on SCADA data collected over a significant duration from a representative wind turbine unit. Relevant features were extracted, with temperature serving as the target parameter. To address the challenge of long-term dependencies in long-term time series forecasting tasks, this study uniquely combined the GRU with the advanced Transformer neural network which incorporates attention mechanisms, to predict the temperature trend of the gearbox’s generator-side bearing. Based on the prediction residuals obtained during normal operation and their subsequent analysis, the study devised an effective anomaly detection process to identify early abnormal states of the gearbox’s generator-side bearing. Comparative performance evaluations were conducted, comparing the combined model with its individual component models, as well as the traditional LightGBM, in terms of temperature time series prediction and their application in anomaly detection. The results unequivocally demonstrate that the combined model outperforms both the individual models and LightGBM in terms of time series prediction accuracy and anomaly detection effectiveness, indicating an enhanced ability to handle long-term memory challenges. Furthermore, the combined model exhibits great potential of practical application for the early warning of gearbox bearing anomalies during actual wind turbine daily operation and maintenance, providing a valuable solution for the offshore wind turbine industry.
Filament extrusion state monitoring in fused filament fabrication using Bhattacharyya distance and K-nearest neighbor
Authors: Li Feng , Yang Zhensheng , wang Chaoge , Huang Yuanyuan , Li Hao
Published: November 2023

Fused filament fabrication (FFF) is one of the most popular techniques of additive manufacturing. However, product quality issues still limit the further application of FFF technology. Filament extrusion state has a great influence on the quality of FFF fabricated products, since both under-extrusion and over-extrusion can lead to the deterioration of product quality. Therefore, monitoring the filament extrusion states is vital and essential. This paper aims to monitor the filament extrusion state by acoustic emission (AE). To achieve this goal, experiments are conducted on a desktop FFF machine, where the states of under-extrusion and over-extrusion are induced by different extrusion speeds. Original AE signals are collected during the experiments. Confronted with the challenge posed by the susceptibility of AE signals to noise during the complex extrusion process and different conditions, one calculates the statistical distribution of the features defined on the raw AE signals, without the need for noise reduction steps. The k-nearest neighbor algorithm is then adopted to identify the different extrusion states, where the Bhattacharyya distance is employed to measure the distances or similarities of the calculated distributions. The findings demonstrate the successful identification of various extrusion states induced by different extrusion speeds through the presented method. The outcomes of this study pave the way for the development of an affordable in-situ FFF monitoring system with comprehensive capabilities.
Research on dynamic characteristics of the turnover system of rail belt conveyor
Authors: Hao Nini , Yi Xiaoting , Zhang Yuan , Chang Xin , Liu Jinshan , Wang Zhen , Zhang Junwei
Published: November 2023

The rail belt conveyor is a new bulk material conveying system that combines the advantages of traditional belt conveyors and railway systems. However, the turnover system, which is a key part of the carriage’s direction-changing mechanism, experiences severe vibration and impact problems that affect its performance and reliability. In this study, a dynamic model of the carriage-rail coupling in the turnover system is established, and the vibration characteristics of the rail are analyzed. The influence of carriage speed, wheelbase, and wheel diameter on the vibration acceleration of the rail is investigated. The results show that higher carriage speeds intensify the vibration response of the rail when the carriage leaves the turnover wheel. The wheel diameter has a significant effect on the vibration acceleration, especially at high speeds. Additionally, the wheelbase affects the vibration acceleration, with smaller wheelbases resulting in more prominent effects. The established dynamic model is validated using measured data, providing insights into the dynamic behavior of the turnover system in rail belt conveyors.
Optimizing solvent dipole moment enables PVDF to improve piezoelectric performance
Authors: Wang Tianliang , Wang Yinglin , Dang Fan , Liu Mengge , Sun Shanfu , Jin Ke , Cheng Pengfei
Published: November 2023

The all-trans conformation (β-phase) possesses a significant impact on the piezoelectric polymer polyvinylidene fluoride (PVDF). Inducing more molecular chain [−CH2−CF2−]n to form all-trans conformation is one of the biggest obstacles for manufacturing high-performance piezoelectric sensing devices. Herein, the continuous vacuum technology is used to modulate the polarity of binary solvents by the proportion of the lower solvent. The regulated solvent forms a high dipole moment, an interaction between the dipole of β-phase and the dipole moment makes the phase reversal in PVDF. Fourier transform infrared spectroscopy, piezoelectric constant test and other characterization results show that when the weakly polar acetone and the strongly polar solvent DMF reach a ratio of 4:6, the pure PVDF film possesses high piezoelectricity (d
33 ∼ −44.8 pC N−1) and strong self-polarization. Additionally, the A4D6 device exhibits high sensitivity (S
1 = 0.182 V/N, 0.5 N ∼ 30 N), driven capability (0.49 mW m−2), and reliability during the electrical tests as a pressure device. This work provides an effective and cost-effective route of optimizing the solvent’s polarity to improve the piezoelectric characteristics of the polymer.
Mitigating challenges in aberration-corrected electron-beam lithography on electron-opaque substrates
Authors: Camino Fernando E , Tiwale Nikhil , Hwang Sooyeon , Du Xu , Yang Judith C
Published: November 2023

Aberration-corrected electron-beam lithography (AC-EBL) using ultra-thin electron transparent membranes has achieved single-digit nanometer resolution in two widely used electron-beam resists: poly (methyl methacrylate) (PMMA) and hydrogen silsesquioxane. On the other hand, AC-EBL implementation on thick, electron-opaque substrates is appealing for conventional top-down fabrication of quantum devices with nanometer-scale features. To investigate the performance of AC-EBL on thick substrates, we measured the lithographic point spread function of a 200 keV aberration-corrected scanning transmission electron microscope by defining both positive and negative patterns in PMMA thin films, spin-cast on thick SiO2/Si substrates. We present the problems encountered during pre-exposure beam focusing and discuss methods to overcome them. In addition, applying some of these methods using commercial 50 nm thick SiN
X
membranes with thick Si support frames, we printed arrays of holes in PMMA with pitches around 26 nm on SiN
X
/Si substrates with increasing Si thickness. Our results show that proximity effects from even 50 nm thick SiN
X
membranes limit hole arrays to 20 nm pitch; however, down to this limit, the effect of the substrate thickness on the pattern quality is minimal. These results highlight the need for novel resists less susceptible to proximity effects, or resists which can be used directly, after development, as the dielectric material in periodic gates in 2D quantum devices.
Energy efficiency of N2 vibrational excitation in the spark-and-glow phases of a long-pulse air discharge at atmospheric pressure
Authors: Qiao Jun-Jie , Yang Qi , Wang Da-Zhi , Xiong Qing
Published: November 2023

The vibrational excitation of N2 molecules has a significant impact on plasma chemical synthesis, including nitrogen fixation and ammonia formation, by reducing the energy barrier of chemical reactions. However, experimental data for energy efficiency of N2 vibrational excitation is very rare. In this work, vibrational coherent anti-Stokes Raman scattering was applied to a 200 μs long-pulse air plasma, and the time behaviours of rotational and vibrational temperatures of N2 in two different discharge modes, namely the spark and glow modes in the long discharge pulse, were quantified. It reveals that the spark discharge produced a vibrational temperature exceeding 5000 K but with a gas temperature as low as 400 K, while the glow discharge resulted in efficient gas heating with a gas temperature as high as 3500 K and a vibrational temperature higher than 5000 K. Combined with the 0D simulation of the air plasma, it demonstrates that the energy efficiency of N2 vibrational excitation in the glow phase is about three times higher than that of the spark phase. These results provide essential inspiration for further studies of plasma chemical synthesis dominated by N2 vibrational excitation.
Efficient computation of coherent multimode instabilities in lasers using a spectral approach
Authors: Kacmoli Sara , Khan Saeed A , Gmachl Claire F , Türeci Hakan E
Published: November 2023

Coherent multimode instabilities are responsible for several phenomena of recent interest in semiconductor lasers, such as the generation of frequency combs and ultrashort pulses. These techonologies have proven disruptive in optical telecommunications and spectroscopy applications. While the standard Maxwell-Bloch equations (MBEs) encompass such complex lasing phenomena, their integration is computationally expensive and offers limited analytical insight. In this paper, we demonstrate an efficient spectral approach to the simulation of multimode instabilities via a quantitative analysis of the instability of single-frequency lasing in ring lasers, referred to as the Lorenz-Haken (LH) instability or the RNGH instability in distinct parameter regimes. Our approach, referred to as CFTD, uses generally non-Hermitian Constant Flux modes to obtain projected Time Domain equations. CFTD provides excellent agreement with finite-difference integration of the MBEs across a wide range of parameters in regimes of non-stationary inversion, including frequency comb formation and spatiotemporal chaos. We also develop a modal linear stability analysis using CFTD to efficiently predict multimode instabilities in lasers. The combination of numerical accuracy, speedup, and semi-analytic insight across a variety of dynamical regimes make the CFTD approach ideal to analyze multimode instabilities in lasers, especially in more complex geometries or coupled laser arrays.