bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive reinforcement learning for task scheduling in aircraft maintenance
Authors: Silva Catarina , Andrade Pedro , Ribeiro Bernardete , F. Santos Bruno 
Published: October 2023

AbstractThis paper proposes using reinforcement learning (RL) to schedule maintenance tasks, which can significantly reduce direct operating costs for airlines. The approach consists of a static algorithm for long-term scheduling and an adaptive algorithm for rescheduling based on new maintenance information. To assess the performance of both approaches, three key performance indicators (KPIs) are defined: Ground Time, representing the hours an aircraft spends on the ground; Time Slack, measuring the proximity of tasks to their due dates; and Change Score, quantifying the similarity level between initial and adapted maintenance plans when new information surfaces. The results demonstrate the efficacy of RL in producing efficient maintenance plans, with the algorithms complementing each other to form a solid foundation for routine tasks and real-time responsiveness to new information. While the static algorithm performs slightly better in terms of Ground Time and Time Slack, the adaptive algorithm excels overwhelmingly in terms of Change Score, offering greater flexibility in handling new maintenance information. The proposed RL-based approach can improve the efficiency of aircraft maintenance and has the potential for further research in this area.
The effect of image fractal properties and its interaction with visual discomfort on gait kinematics
Authors: Burtan D. , Burn J. F. , Spehar B. , Leonards U. 
Published: October 2023

AbstractExposure to images of urban environments affords higher cognitive processing demands than exposure to images of nature scenes; an effect potentially related to differences in low-level image statistics such as fractals. The aim of the current study was to investigate whether the fractal dimensions of an abstract scene affect cognitive processing demands, using gait kinematics as a measure of cognitive demand. Participants (n = 40) were asked to walk towards different types of synthetic images which were parametrically varied in their fractal dimensions. At the end of each walk, participants rated each image for its visual discomfort (n = 20) or for its likability (n = 20) as potential confounding factors. Fractal dimensions were predictors of walking speed. Moreover, the interaction between fractal dimensions and subjective visual discomfort but not liking predicted velocity. Overall, these data suggest that fractal dimensions indeed contribute to environmentally induced cognitive processing demands.
Investigation on mechanical properties of nickel open cell metal foam after heat treatment
Authors: Shajari Y. , Nikzad L. , Razavi M. 
Published: October 2023

AbstractThis investigation aims to assess the mechanical behavior and energy absorption properties of the open-cell nickel foams. The metal foams produced by electroforming of nickel on PU foams, also a heat treatment has applied to evaporate the PU foam, then a uniaxial compression test was applied to measure maximum compressive strength, energy absorption density, efficiency, and normalized stresses. The results indicate that compared with typical open-cell nickel foams and polymer precursors when the electroforming time is 12 h and a heat treatment has applied, the aforementioned properties of the metal foams had a significant improvement. Improvement of properties will change by increasing the time of electroforming. The heat treatment improved the energy absorption density of open-cell nickel foams for 3.7 times. For the best sample which is a metal foam with 12 h of electroforming with heat treatment the first maximum compressive strength, energy absorption density, and energy absorption efficiency reach 1.84 (MPa), 3.29 (mJ/mm3), and 73%, respectively.
Sit-to-walk strategy classification in healthy adults using hip and knee joint angles at gait initiation
Authors: Perera Chamalka Kenneth , Gopalai Alpha Agape , Gouwanda Darwin , Ahmad Siti Anom , Salim Mazatulfazura Sf Binti 
Published: October 2023

AbstractForward continuation, balance, and sit-to-stand-and-walk (STSW) are three common movement strategies during sit-to-walk (STW) executions. Literature identifies these strategies through biomechanical parameters using gold standard laboratory equipment, which is expensive, bulky, and requires significant post-processing. STW strategy becomes apparent at gait-initiation (GI) and the hip/knee are primary contributors in STW, therefore, this study proposes to use the hip/knee joint angles at GI as an alternate method of strategy classification. To achieve this, K-means clustering was implemented using three clusters corresponding to the three STW strategies; and two feature sets corresponding to the hip/knee angles (derived from motion capture data); from an open access online database (age: 21–80 years; n = 10). The results identified forward continuation with the lowest hip/knee extension, followed by balance and then STSW, at GI. Using this classification, strategy biomechanics were investigated by deriving the established biomechanical quantities from literature. The biomechanical parameters that significantly varied between strategies (P < 0.05) were time, horizontal centre of mass (COM) momentum, braking impulse, centre of pressure (COP) range and velocities, COP–COM separation, hip/knee torque and movement fluency. This alternate method of strategy classification forms a generalized framework for describing STW executions and is consistent with literature, thus validating the joint angle classification method.
Cancer characterization using light backscattering spectroscopy and quantitative ultrasound: an ex vivo study on sarcoma subtypes
Authors: Malinet Cyril , Montcel Bruno , Dutour Aurélie , Fajnorova Iveta , Liebgott Hervé , Muleki-Seya Pauline 
Published: October 2023

AbstractHistological analysis is the gold standard method for cancer diagnosis. However, it is prone to subjectivity and sampling bias. In response to these limitations, we introduce a quantitative bimodal approach that aims to provide non-invasive guidance towards suspicious regions. Light backscattering spectroscopy and quantitative ultrasound techniques were combined to characterize two different bone tumor types from animal models: chondrosarcomas and osteosarcomas. Two different cell lines were used to induce osteosarcoma growth. Histological analyses were conducted to serve as references. Three ultrasound parameters and intensities of the light reflectance profiles showed significant differences between chondrosarcomas and osteosarcomas at the 5% level. Likewise, variations in the same biomarkers were reported for the two types of osteosarcoma, despite their similar morphology observed in the histological examinations. These observations show the sensitivity of our techniques in probing fine tissue properties. Secondly, the ultrasound spectral-based technique identified the mean size of chondrosarcoma cells and nuclei with relative errors of about 22% and 9% respectively. The optical equivalent technique correctly extracted scatterer size distributions that encompass nuclei and cells for chondrosarcomas and osteosarcomas ($$R^2 = 0.80$$

R
2

=
0.80

and $$R^2 = 0.73$$

R
2

=
0.73

respectively). The optical scattering contributions of nuclei were estimated at 52% for the chondrosarcomas and 69% for the osteosarcomas, probably indicating the abundant and the absent extracellular matrix respectively. Thus, the ultrasound and the optical methods brought complementary parameters. They successfully estimated morphological parameters at the cellular and the nuclear scales, making our bimodal technique promising for tumor characterization.
Epidemiology and analysis of SARS-CoV-2 Omicron subvariants BA.1 and 2 in Taiwan
Authors: Liu Li-Teh , Chiou Shyh-Shin , Chen Po-Chih , Chen Chun-Hong , Lin Ping-Chang , Tsai Ching-Yi , Chuang Wan-Long , Hwang Shang-Jyh , Chong Inn-Wen , Tsai Jih-Jin 
Published: October 2023

AbstractThe Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in October 2021, possessed many mutations compared to previous variants. We aimed to identify and analyze SARS-CoV-2 Omicron subvariants among coronavirus disease 2019 (COVID-19) patients between January 2022 and September 2022 in Taiwan. The results revealed that BA.2.3.7, featuring K97E and G1251V in the spike protein compared with BA.2, emerged in March 2022 and persistently dominated between April 2022 and August 2022, resulting in the largest COVID-19 outbreak since 2020. The accumulation of amino acid (AA) variations, mainly AA substitution, in the spike protein was accompanied by increasing severity in Omicron-related COVID-19 between April 2022 and January 2023. Older patients were more likely to have severe COVID-19, and comorbidity was a risk factor for COVID-19-related mortality. The accumulated case fatality rate (CFR) dropped drastically after Omicron variants, mainly BA.2.3.7, entered Taiwan after April 2022, and the CFR was 0.16% in Taiwan, which was lower than that worldwide (0.31%) between April 2021 and January 2023. The relatively low CFR in Omicron-related COVID-19 patients can be attributed to adjustments to public health policies, promotion of vaccination programs, effective antiviral drugs, and the lower severity of the Omicron variant.
KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity
Authors: Chen Hong , Xu Yongping , Jin Jianshi , Su Xiao-dong 
Published: October 2023

AbstractIt is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box “TTGAC(C/T)” but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.
Predicting compressive strength of RCFST columns under different loading scenarios using machine learning optimization
Authors: Wu Feng , Tang Fei , Lu Ruichen , Cheng Ming 
Published: October 2023

AbstractAccurate bearing capacity assessment under load conditions is essential for the design of concrete-filled steel tube (CFST) columns. This paper presents an optimization-based machine learning method to estimate the ultimate compressive strength of rectangular concrete-filled steel tube (RCFST) columns. A hybrid model, GS-SVR, was developed based on support vector machine regression (SVR) optimized by the grid search (GS) algorithm. The model was built based on a sample of 1003 axially loaded and 401 eccentrically loaded test data sets. The predictive performance of the proposed model is compared with two commonly used machine learning models and two design codes. The results obtained for the axial loading dataset with R2 of 0.983, MAE of 177.062, RMSE of 240.963, and MAPE of 12.209%, and for the eccentric loading dataset with R2 of 0.984, MAE of 93.234, RMSE of 124.924, and MAPE of 10.032% show that GS-SVR is the best model for predicting the compressive strength of RCFST columns under axial and eccentric loadings. It is an effective alternative method that can be used to assist and guide the design of RCFST columns to save time and cost of some laboratory experiments. Additionally, the impact of input parameters on the output was investigated.
Risk of data leakage in estimating the diagnostic performance of a deep-learning-based computer-aided system for psychiatric disorders
Authors: Lee Hyung-Tak , Cheon Hye-Ran , Lee Seung-Hwan , Shim Miseon , Hwang Han-Jeong 
Published: October 2023

AbstractDeep-learning approaches with data augmentation have been widely used when developing neuroimaging-based computer-aided diagnosis (CAD) systems. To prevent the inflated diagnostic performance caused by data leakage, a correct cross-validation (CV) method should be employed, but this has been still overlooked in recent deep-learning-based CAD studies. The goal of this study was to investigate the impact of correct and incorrect CV methods on the diagnostic performance of deep-learning-based CAD systems after data augmentation. To this end, resting-state electroencephalogram (EEG) data recorded from post-traumatic stress disorder patients and healthy controls were augmented using a cropping method with different window sizes, respectively. Four different CV approaches were used to estimate the diagnostic performance of the CAD system, i.e., subject-wise CV (sCV), overlapped sCV (oSCV), trial-wise CV (tCV), and overlapped tCV (otCV). Diagnostic performances were evaluated using two deep-learning models based on convolutional neural network. Data augmentation can increase the performance with all CVs, but inflated diagnostic performances were observed when using incorrect CVs (tCV and otCV) due to data leakage. Therefore, the correct CV (sCV and osCV) should be used to develop a deep-learning-based CAD system. We expect that our investigation can provide deep-insight for researchers who plan to develop neuroimaging-based CAD systems for psychiatric disorders using deep-learning algorithms with data augmentation.
Effects of tea, catechins and catechin derivatives on Omicron subvariants of SARS-CoV-2
Authors: Shin-Ya Masaharu , Nakashio Maiko , Ohgitani Eriko , Suganami Akiko , Kawamoto Masaya , Ichitani Masaki , Kobayashi Makoto , Takihara Takanobu , Inaba Tohru , Nukui Yoko , Kinugasa Hitoshi , Ishikura Hiroyasu , Tamura Yutaka , Mazda Osam 
Published: October 2023

AbstractThe Omicron subvariants of SARS-CoV-2 have multiple mutations in the S-proteins and show high transmissibility. We previously reported that tea catechin (−)-epigallocatechin gallate (EGCG) and its derivatives including theaflavin-3,3’-di-O-digallate (TFDG) strongly inactivated the conventional SARS-CoV-2 by binding to the receptor binding domain (RBD) of the S-protein. Here we show that Omicron subvariants were effectively inactivated by green tea, Matcha, and black tea. EGCG and TFDG strongly suppressed infectivity of BA.1 and XE subvariants, while effect on BA.2.75 was weaker. Neutralization assay showed that EGCG and TFDG inhibited interaction between BA.1 RBD and ACE2. In silico analyses suggested that N460K, G446S and F490S mutations in RBDs crucially influenced the binding of EGCG/TFDG to the RBDs. Healthy volunteers consumed a candy containing green tea or black tea, and saliva collected from them immediately after the candy consumption significantly decreased BA.1 virus infectivity in vitro. These results indicate specific amino acid substitutions in RBDs that crucially influence the binding of EGCG/TFDG to the RBDs and different susceptibility of each Omicron subvariant to EGCG/TFDG. The study may suggest molecular basis for potential usefulness of these compounds in suppression of mutant viruses that could emerge in the future and cause next pandemic.
Physico-functional and nutritional characteristics of germinated pigeon pea (Cajanus cajan) flour as a functional food ingredient
Authors: Atuna Richard Atinpoore , Mensah Mary-Ann Sarpong , Koomson Gifty , Akabanda Fortune , Dorvlo Selorm Yaotse , Amagloh Francis Kweku 
Published: October 2023

AbstractThe study investigated the effect of germination on pigeon pea flour’s physico-functional (pH, color, water and oil absorption capacities, swelling and foaming capacities and bulk densities) and proximate, total polyphenols and antioxidant activity. The physico-functional and proximate parameters were determined using standard protocols. The color analysis showed that germination significantly increased the flour samples’ lightness (L*) (70.7; p = 0.009) by almost 1.5-fold. Germination resulted in almost 1.1 times higher oil absorption capacity than the control (219.9%; p = 0.022). The foaming capacity of the germinated samples significantly (p = 0.015) increased by 6.4%. Germination significantly reduced the loose bulk density (0.54 vs 0.63; p = 0.012) but significantly increased the tapped bulk density (0.84 vs 0.77; p = 0.002). The germinated samples recorded significantly (1.62%; p = 0.010) lower crude fat, about 1.2 times lower than the raw flour. Germination significantly increased the flour’s total ash (4.2% vs 3.6%; p = 0.003) and crude protein (11.6% vs 9.4%; p = 0.047) content. Germinated pigeon pea flour will perform better in formulating baked products, aerated foods and food extenders than non-germinated pigeon pea flour. Hence, the germination of pigeon peas should be encouraged because it harnesses the functional and proximate attributes measured.
Size-driven parr-smolt transformation in masu salmon (Oncorhynchus masou)
Authors: Ugachi Yuki , Kitade Haruka , Takahashi Eisuke , Suzuki Shotaro , Hayashi Mizuki , Yamada Taiga , Cui Wenda , Shimizu Munetaka 
Published: October 2023

AbstractAnadromous salmonids exhibit partial migration, where some individuals within a population migrate down to the ocean through complex interactions between body size and photoperiod. This study aimed to integrate the ontogenetic and seasonal patterns of smoltification, a series of changes for future marine life, in a strain of masu salmon (Oncorhynchus masou). Spring smoltification, as evidenced by the activation of gill Na+,K+-ATPase (NKA), was induced during winter under an advanced photoperiod. In addition, juveniles showed an additional peak in gill NKA activity in August regardless of the photoperiod. When juvenile masu salmon were subjected to feeding manipulations during the first spring/summer, only fish exceeding a fork length of 12 cm exhibited an increased gill NKA activity. We tested whether size-driven smoltification required a long-day period by exposing juveniles to a constant short-day length (9-h light and 15-h dark) from January to November. Juveniles under short-day conditions exceeded 12 cm in June but showed no signs of smoltification. Thus, masu salmon undergo photoperiod-limited, size-driven smoltification during the first summer and size-limited, photoperiod-driven smoltification the following spring. The findings of the present study provide a framework for further elucidation of the physiological mechanisms underlying partial migration in salmonids.
Exploring the role of esketamine in alleviating depressive symptoms in mice via the PGC-1α/irisin/ERK1/2 signaling pathway
Authors: Hu Na , Chen Xuemei , Chen Chengchuan , Liu Xing , Yi Peng , Xu Tianhao , Jia Jing , Feng Jianguo , Zhang Chunxiang , Wang Xiaobin 
Published: October 2023

AbstractEsketamine provides an immediate and noticeable antidepressant effect, although the underlying molecular processes are yet unclear. Irisin induced by aerobic exercise has been implicated in the alleviation of depressive symptoms, whether irisin expression responds to the administration of esketamine remains unknown. In this study, we found that irisin was reduced in the hippocampus and peripheral blood of chronic unpredictable mild stress (CUMS) mice, whereas the irisin level was rescued by esketamine treatment. The reduction of PGC-1α expression (transcriptional regulator of irisin gene expression) in the CUMS mice was rescued by esketamine treatment, PGC-1α knockdown significantly reduced the irisin level induced by esketamine. Additionally, FNDC5/irisin-knockout mice developed more severe depressant-like behaviors than wild-type mice under CUMS stimulation, with an attenuated the antidepressant effect of esketamine. Further research indicated that irisin-mediated modulation of esketamine on depressive-like behaviors in CUMS mice involved the ERK1/2 pathway. Overall, the PGC-1α/irisin/ERK1/2 signaling activation may be a new mechanism underlying the antidepressant activity of esketamine, denoting that irisin may be a promising therapeutic target for the treatment of depression.
Differential gene expression analysis based on linear mixed model corrects false positive inflation for studying quantitative traits
Authors: Tang Shizhen , Buchman Aron S. , Wang Yanling , Avey Denis , Xu Jishu , Tasaki Shinya , Bennett David A. , Zheng Qi , Yang Jingjing 
Published: October 2023

AbstractDifferential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer’s Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues.