bluuebunny/crossref_metadata_2025_split huggingface dataset:
TeV/m catapult acceleration of electrons in graphene layers
Authors: Bonţoiu Cristian , Apsimon Öznur , Kukstas Egidijus , Rodin Volodymyr , Yadav Monika , Welsch Carsten , Resta-López Javier , Bonatto Alexandre , Xia Guoxing 
Published: January 2023

AbstractRecent nanotechnology advances enable fabrication of layered structures with controllable inter-layer gap, giving the ultra-violet (UV) lasers access to solid-state plasmas which can be used as medium for electron acceleration. By using a linearly polarized 3 fs-long laser pulse of 100 nm wavelength and 10$$^{21}$$

21

W/cm$$^2$$

2

peak intensity, we show numerically that electron bunches can be accelerated along a stack of ionized graphene layers. Particle-In-Cell (PIC) simulations reveal a new self-injection mechanism based on edge plasma oscillations, whose amplitude depends on the distance between the graphene layers. Nanometre-size electron ribbons are electrostatically catapulted into buckets of longitudinal electric fields in less than 1 fs, as opposed to the slow electrostatic pull, common to laser wakefield acceleration (LWFA) schemes in gas-plasma. Acceleration then proceeds in the blowout regime at a gradient of 4.79 TeV/m yielding a 0.4 fs-long bunch with a total charge in excess of 2.5 pC and an average energy of 6.94 MeV, after travelling through a graphene target as short as 1.5 $$\upmu $$
μ
m. These parameters are unprecedented within the LWFA research area and, if confirmed experimentally, may have an impact on fundamental femtosecond research.
Associations between oral health status and risk of fractures in elder adults
Authors: Hong Seok Woo , Lee JunYeop , Kang Jeong-Hyun 
Published: January 2023

AbstractOral health condition, bone mineral density, skeletal muscle mass, fall, fracture, and frailty seem to be strongly interconnected. This study aimed to investigate associations between probability of osteoporotic fractures and oral health in the elderly. In total, 2322 Korean subjects from the 2008—2009 Korea National Health and Nutritional Examination Survey aged over 65 years were included. The 10-year probabilities of major and hip fractures were calculated using the Fracture Risk Assessment (FRAX) tool. Data on anthropometry, skeletal bone mineral density, sociodemographic characteristics, physical activity, individual history of fractures and falls, parental history of osteoporosis, number of teeth, metabolic syndrome, the Decayed, Missing, and Filled permanent Teeth index, and Community Periodontal Index (CPI), were collected. Participants were classified into three groups based on FRAX score for major osteoporotic fractures. A multivariate linear regression analysis was conducted to analyze associations between FRAX scores and oral health-related factors, adjusting for confounding factors. BMI, presence of metabolic syndrome, number of teeth, dental patterns, and CPI score showed significant differences among three groups in males and females. Results from multivariate linear regression analysis demonstrated significant relationships between total tooth number and probabilities of fracture in male and female elderly. The interdisciplinary approach for handling osteoporosis and sarcopenia including dentists, physicians is necessary to facilitate a better quality of life in the elderly.
Combined oceanic and atmospheric forcing of the 2013/14 marine heatwave in the northeast Pacific
Authors: Chen Huan-Huan , Wang Yuntao , Xiu Peng , Yu Yi , Ma Wentao , Chai Fei 
Published: January 2023

AbstractAn unprecedented warm sea surface temperature (SST) anomaly event, namely, the Blob, occurred in the northeast Pacific during the winter (October–January) of 2013/2014, causing substantial economic and ecological impacts. Here, we explore the driving forces of the Blob from both atmospheric and oceanic perspectives and show that the Blob primarily resulted from weak wintertime cooling due to the reduced air-sea heat flux transfer from the ocean to the atmosphere and the reduced horizontal advection of cold water in the upper ocean. Both mechanisms were attributed to an anomalous high-pressure system over the study region. Specifically, the anomalous air-sea heat flux, which was dominated by turbulent heat flux anomalies, was mainly induced by the increased air temperature (i.e., with a contribution of approximately 70%) and the weakened wind speed associated with the high-pressure system. The reduced horizontal heat advection was mainly due to the weakened winds acting on the ocean temperature meridional gradient. Using a regional ocean numerical model with different experimental runs, we evaluated the contributions of air temperature and wind drivers to the Blob at both the surface and subsurface of the ocean. The Blob was absent when the model was forced by climatology-air-temperature. Both the SST and integrated ocean heat content (OHC, 0–150 m) decreased, and the mixed layer depth (MLD) was deeper than that in the control run forced by real atmospheric conditions. In the climatology-winds experiment, obvious warm anomalies still existed, which were similar to but weaker than the control run. The SST (OHC) and MLD values in the climatology-winds run were between those of the climatology-air-temperature run and the control run. Compared to former studies that attribute the formation of the Blob to an anomalous air-sea heat flux and horizontal advection mainly induced by reduced winds, our study demonstrates that anomalous warm air temperatures played a more important role in its formation.
Making machine learning matter to clinicians: model actionability in medical decision-making
Authors: Ehrmann Daniel E. , Joshi Shalmali , Goodfellow Sebastian D. , Mazwi Mjaye L. , Eytan Danny 
Published: January 2023

AbstractMachine learning (ML) has the potential to transform patient care and outcomes. However, there are important differences between measuring the performance of ML models in silico and usefulness at the point of care. One lens to use to evaluate models during early development is actionability, which is currently undervalued. We propose a metric for actionability intended to be used before the evaluation of calibration and ultimately decision curve analysis and calculation of net benefit. Our metric should be viewed as part of an overarching effort to increase the number of pragmatic tools that identify a model’s possible clinical impacts.
A temporal classifier predicts histopathology state and parses acute-chronic phasing in inflammatory bowel disease patients
Authors: Peters Lauren A. , Friedman Joshua R. , Stojmirovic Aleksandar , Hagen Jacob , Houten Sander , Dodatko Tetyana , Amaro Mariana P. , Restrepo Paula , Chai Zhi , Rodrigo Mora J. , Raymond Holly A. , Curran Mark , Dobrin Radu , Das Anuk , Xiong Huabao , Schadt Eric E. , Argmann Carmen , Losic Bojan 
Published: January 2023

AbstractPrevious studies have conducted time course characterization of murine colitis models through transcriptional profiling of differential expression. We characterize the transcriptional landscape of acute and chronic models of dextran sodium sulfate (DSS) and adoptive transfer (AT) colitis to derive temporal gene expression and splicing signatures in blood and colonic tissue in order to capture dynamics of colitis remission and relapse. We identify sub networks of patient-derived causal networks that are enriched in these temporal signatures to distinguish acute and chronic disease components within the broader molecular landscape of IBD. The interaction between the DSS phenotype and chronological time-point naturally defines parsimonious temporal gene expression and splicing signatures associated with acute and chronic phases disease (as opposed to ordinary time-specific differential expression/splicing). We show these expression and splicing signatures are largely orthogonal, i.e. affect different genetic bodies, and that using machine learning, signatures are predictive of histopathological measures from both blood and intestinal data in murine colitis models as well as an independent cohort of IBD patients. Through access to longitudinal multi-scale profiling from disease tissue in IBD patient cohorts, we can apply this machine learning pipeline to generation of direct patient temporal multimodal regulatory signatures for prediction of histopathological outcomes.
Asp-containing actinomycin and tetracyclic chromophoric analogues from the Streptomyces sp. strain S22
Authors: Zhao Wanzhu , Wang Guangfei , Guo Lin , Wang Jingmin , Jing Congcong , Liu Ben , Zhao Feng , Zhang Shumin , Xie Zeping 
Published: January 2023

First Asp-containing actinomycin and two unusual tetracyclic chromophoric analogues with potent cytotoxic and antibacterial activities from marine-derived Streptomyces sp. strain S22.
Inflammatory processes involved in NASH-related hepatocellular carcinoma
Authors: Cannito Stefania , Dianzani Umberto , Parola Maurizio , Albano Emanuele , Sutti Salvatore 
Published: January 2023

Abstract
Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide. In the recent years nonalcoholic fatty liver disease (NAFLD) is becoming a growing cause of HCCs and the incidence of NAFLD-related HCCs is expected to further dramatically increase by the next decade. Chronic inflammation is regarded as the driving force of NAFLD progression and a key factor in hepatic carcinogenesis. Hepatic inflammation in NAFLD results from the persistent stimulation of innate immunity in response to hepatocellular injury and gut dysbiosis as well as by the activation of adaptive immunity. However, the relative roles of innate and adaptive immunity in the processes leading to HCC are still incompletely characterized. This is due to the complex interplay between different liver cell populations, which is also strongly influenced by gut-derived bacterial products, metabolic/nutritional signals. Furthermore, carcinogenic mechanisms in NAFLD/NASH appear to involve the activation of signals mediated by hypoxia inducible factors. This review discusses recent data regarding the contribution of different inflammatory cells to NAFLD-related HCC and their possible impact on patient response to current treatments.
Prevalence of Cognitive Impairment and Its Association With Hearing Loss Among Adults Over 50 Years of Age: Results From a Population-Based Survey in Santiago, Chile
Authors: Tamblay Natalia , Boggs Dorothy , Huidobro Barbara , Tapia-Mora Daniel , Anabalon Katherine , Delgado Carolina , Polack Sarah , Bright Tess , Torrente Mariela C. 
Published: January 2023

Purpose:
The purpose of this study was to estimate the prevalence of cognitive impairment and explore its association with hearing loss and other sociodemographic and clinical risk factors, using an objective measurement of hearing levels, in adults over 50 years of age.

Method:
A population-based survey was completed in Santiago, Chile between December 2019 and March 2020. Participants were screened for cognitive impairment using the Short Chilean Mini-Mental State Examination and hearing levels were assessed with tonal audiometry (hearTest). Data on demographic, socioeconomic, and clinical characteristics were collected.

Results:

A total of 538 persons completed the assessment. The prevalence of cognitive impairment in the 50+ population was 9.3% (95% confidence interval [CI] [5.8, 14.7]). Cognitive impairment was significantly higher in individuals with any level of hearing loss (odds ratio [
OR
] = 2.19, 95% CI [1.00, 4.80], adjusted for age, sex, education, socioeconomic position [SEP], and head trauma). Subjects with hearing loss and who reported any use of hearing aids (16% of the sample) had a lower risk of cognitive impairment (
OR
of nonusers 3.64, 95% CI [1.00, 13.28], adjusted for age, sex, education, SEP, and head trauma).

Conclusion:
Strategies for addressing cognitive impairment should further explore the integration of early diagnosis of hearing loss and the regular use of hearing aids.
Multisource localization based on angle distribution of time–frequency points using an FOA microphone
Authors: Tao Liang , Jia Maoshen , Li Lu , Wang Jing , Xiang Yang 
Published: January 2023

AbstractMultisource localization occupies an important position in the field of acoustic signal processing and is widely applied in scenarios, such as human‐machine interaction and spatial acoustic parameter acquisition. The direction‐of‐arrival (DOA) of a sound source is convenient to render spatial sound in the audio metaverse. A multisource localization method in a reverberation environment is proposed based on the angle distribution of time–frequency (TF) points using a first‐order ambisonics (FOA) microphone. The method is implemented in three steps. 1) By exploring the angle distribution of TF points, a single‐source zone (SSZ) detection method is proposed by using a standard deviation‐based measure, which reveals the degree of convergence of TF point angles in a zone. 2) To reduce the effect of outliers on localization, an outlier removal method is designed to remove the TF points whose angles are far from the real DOAs, where the median angle of each detected zone is adopted to construct the outlier set. 3) DOA estimates of multiple sources are obtained by postprocessing of the angle histogram. Experimental results in both the simulated and real scenarios verify the effectiveness of the proposed method in a reverberation environment, which also show that the proposed method outperforms reference methods.
Smooth commutation of brushless DC motor by model‐free predictive current control without back‐EMF estimation
Authors: Moradpour Reza , Tavakoli Abdolreza 
Published: January 2023

AbstractThis study presents a new predictive control approach for brushless DC (BLDC) motor to smooth its commutation process. The proposed predictive control method is applied to the BLDC motor's equivalent DC current. Therefore, this method utilises only one prediction equation, which means less calculation than the standard predictive control schemes. Here, the equivalent DC current equation is defined according to the model‐free control theory to remove the back‐EMF voltage estimation from the control system. In consequence, the proposed predictive DC current control (DC‐PCC) has a smooth commutation. Because of applying the model‐free theory, both commutation and non‐commutation periods of the BLDC motor have similar dynamic equations. Hence, one simple prediction equation can be utilised for both periods. Besides, the proposed method has less computational burden due to using only one prediction equation and removing the back‐EMF estimation process. To validate the proposed model‐free DC‐PCC, experimental tests are performed, and the results are discussed in this research.
Medical image blind super‐resolution based on improved degradation process
Authors: Shao Dangguo , Qin Li , Xiang Yan , Ma Lei , Xu Hui 
Published: January 2023

AbstractClinical diagnosis has high requirements for the resolution of medical images, but most existing medical images super‐ resolution (SR) methods are performed under a known or specific degradation kernel. However, the difference between the actual degradations and their assumed degradation kernels results in a severe performance drop for the advanced SR methods in real applications. This paper proposes a medical image blind super‐resolution model (Med‐BSR) based on an improved degradation process to handle this issue. The model makes each of the degradation factors in medical image blind SR, such as blur, noise, and downsampling, more complex and practical. Specifically, the authors use the random select/combine strategy to randomly arrange and combine the type and order of each degradation factor, which significantly expands the degradation space. The authors also improved the loss function of the primary enhanced super‐resolution generative adversarial networks (ESRGAN) network. The extensive experimental results demonstrate that the authors’ designed model can accurately restore the natural degradation process, which can reconstruct high‐quality SR medical images. It also has a good generalization ability to realistic images simultaneously.
Short‐term traffic travel time forecasting using ensemble approach based on long short‐term memory networks
Authors: Jia Xingli , Zhou Wuxiao , Yang Hongzhi , Li Shuangqing , Chen Xingpeng 
Published: January 2023

AbstractTo enhance the control effect of intelligent transportation system (ITS) of expressway, avoid blind travel causing traffic congestion, improve road capacity, and achieve the purpose of smooth and efficient operation of the network, 3σ criterion and 2σ cycle removal criterion were used to eliminate the abnormal data of travel time. Thereafter, a combined prediction model of Long Short‐Term Memory (LSTM) based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm and attention mechanism is proposed. Travel time data, collected from the real world, is decomposed into several Intrinsic Mode Functions (IMFs) and a residue with the CEEMDAN. Then, the decomposed sub‐sequence is predicted and the final prediction result is obtained by comprehensive superposition. The results indicate that: the CEEMDAN algorithm has significantly improved the prediction performance. Compared with the AT‐LSTM model, mean absolute percentage error (MAPE) is reduced by 10.75%, 24.84%, 31.80%, 24.98%, 14.29%, and 31.42% when the time window was 3, 6, 9, 12, 15, and 18, respectively, in the dataset of Yaxi expressway. In the dataset of Chengnan expressway, the number of error points with MAPE greater than 40% is significantly reduced after the adoption of the LSTM model. After the introduction of CEEMDAN algorithm, the error at each time point is controlled within 30%. The proposed model controls the error at each time point within 25%. In different datasets, the proposed model has better prediction ability for highly non‐linear travel time, and can better capture the trend abrupt characteristics of rush hour traffic flow.
Sensitivity enhancement for micromechanical vibro‐impact resonators using snap‐through curved beams
Authors: Yi Yun , Tsai Chun‐Pu , Li Wei‐Chang 
Published: January 2023

AbstractThis work enhances the driving sensitivity of micromechanical vibro‐impact resonators by reducing the output switching gap. Differing from previous works for gap narrowing that either require a dedicated pull‐in bias voltage and stopper structures or post‐fabrication refill processes, the use of the snap‐through technique calls for only the initial activation step without the need for constantly applied voltage or additional process steps. Doing so realizes a final gap spacing from a typical 2‐μm limitation to a 0.9‐μm sub‐micron gap. While probes are used to mechanically initiate the bistable transition in this proof‐of‐concept demonstration, this could be done electrically once properly designed actuation electrodes are available. This transducer gap narrowing technique can help facilitate higher sensitivity for vibro‐impact resonator embedded applications such as zero‐quiescent power communication receivers.
Retracted: Visualisation‐based binary classification of android malware using vgg16
Authors: Marwaha Aryan , Malik Rami Qays , Beram Shehab Mohamed , Rizwan Ali , Kishore Kakarla Hari , Thakur Deepak , Gera Tanya , Shabaz Mohammad 
Published: January 2023

AbstractRetraction: [Aryan Marwaha, Rami Qays Malik, Shehab Mohamed Beram, Ali Rizwan, Hari Kishore Kakarla, Deepak Thakur, Tanya Gera, Mohammad Shabaz, Visualisation‐based binary classification of android malware using vgg16, IET Software 2023 (https://doi.org/10.1049/sfw2.12094)].The above article from IET Software, published online on 23 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.
Optical switch by direct modulated laser diode using fiber laser for pulse picking
Authors: Kaneko Satoru , Yasui Manabu , Kurouchi Masahito , York Robert , Hagiwara Yuna , Nakamura Masaru 
Published: January 2023

AbstractA new method of direct modulating a pre‐amplifier laser diode as an optical switch is proposed. To modulate the laser diode with lower repetition rate, the repetition rate in the kilohertz region can be achieved using a source laser of 100 MHz without electro‐optical modulators (EOM) or acousto‐optical modulators (AOM). Using a direct modulated laser diode, an ON/OFF ratio (extinction ratio) of 25 dB was demonstrated in this study.
Modelling, simulation and performance comparison of different membership functions based fuzzy logic control for an active magnetic bearing system
Authors: Gupta Suraj , Biswas Pabitra Kumar , Aljafari Belqasem , Thanikanti Sudhakar Babu , Das Sajal K. 
Published: January 2023

AbstractIn‐house prototype model of an active magnetic bearing is built and using its physical parameter values a linearized transfer function of order two, is mathematically obtained for a specific point of operation. In this work, a closed loop active magnetic bearing system is proposed and controller for this closed loop is designed using fuzzy logic control. Two different fuzzy inference systems: Mamdani and Sugeno fuzzy inference system constructed individually with eleven different types of membership functions separately. The considered membership functions are—linear, generalized bell‐shaped, Gaussian distribution based, quadratic, cubic polynomial and sigmoidal curve‐based membership functions. Calculating the transient state and steady state parameter values together with the controller output allows to see how these various membership functions perform on the proposed closed loop active magnetic bearing system. Observed data shows that changing the fuzzy inference system for a specific membership function will result in 67.41% reduction in the overshoot value, 29.70% reduction in settling time value, 10.42% change in rise time value and 2.91% variation is peak time value. Practicality of all membership functions are analysed based on calculated data and their performances with the proposed model.