bluuebunny/crossref_metadata_2025_split huggingface dataset:
Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population
Authors: Boerwinkle Varina L. , Appavu Brian , Cediel Emilio Garzon , Erklaurer Jennifer , Ganesan Saptharishi Lalgudi Lalgudi , Gibbons Christie , Hahn Cecil , LaRovere Kerri L. , Moberg Dick , Natarajan Girija , Molteni Erika , Reuther William R. , Slomine Beth S. 
Published: October 2023

Abstract
Background
The fundamental gap obstructing forward progress of evidenced based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical exams and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain.
Methods
To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society’s Curing Coma® Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics.
Results
We report the working groups’ pediatric-focused DoC CDE recommendations and disseminate CDE to be used in studies of pediatric patients with DoC.
Conclusions
The CDE recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research.
Evaluation of CNN Models Using Deep Reinforcement Learning for Band Selection on Hyperspectral Image Classification
Authors: Atik Saziye Ozge 
Published: October 2023

Abstract
Along with the high spectral rich information it provides, one of the difficulties in processing a hyperspectral image is the need for expert knowledge and high-spec hardware to process very high-dimensional data. The use of the most relevant bands in the hyperspectral image is quite decisive in deep CNN networks without loss of information and loss of accuracy. It is crucial to classify hyperspectral images with faster and less hardware-requiring models by creating subset groups by choosing a limited number of optimal bands. In this study, a comparative analysis about the effect of deep reinforcement learning (DRL)-based hyperspectral band selection on the classification performance of deep learning networks is presented. 3D CNN, 3D + 1D CNN and Multiscale 3D deep convolutional neural network (M3D-DCNN) algorithms were used for hyperspectral image classification. By choosing the most effective bands determined by DRL, it is aimed to perform classification with high accuracy with fewer bands instead of all bands. All tests were performed on popular hyperspectral datasets, Indian Pines, Salinas, and Pavia Center. The 3D + 1D approach reached 92.28% OA in the IP dataset. In Salinas, 94.87% OA with 3D CNN and 94.62% OA with M3D-DCNN was obtained. 3D + 1D CNN has 98.64% OA in PaviaC.
Semantic-wise hybrid attention generative adversarial network for image inpainting
Authors: Shi Changhong , Liu Weirong , Meng Jiahao , Li Zhijun , Liu Jie 
Published: October 2023

Abstract
Deep learning based image inpainting methods can synthesize plausible results based on known information of undamaged areas of the input image. However, most of the existing methods fail to generate high quality structures and textures due to a lack of fully exploring the potential high level semantic information of the generator. To address this issue, we first propose a novel Semantic-Wise Hybrid Attention Generative Adversarial Network (SWHA-GAN), which leverages a lightweight single-stream GAN framework to reconstruct reasonable and natural results. Secondly, a Semantic-Wise Hybrid Attention module is designed to simultaneously promote correct structure and rich details of the generated result. The channel self-attention emphasizes long range semantic dependencies among channels to improve structure accuracy, and spatial attention ensures texture inpainting. Experiments on multiple datasets including faces and natural images show that the proposed SWHA-GAN can generate higher quality results with more details than the state-of-the-arts.
Immunology of severe febrile illness in children in the COVID-19 era
Authors: Shankar-Hari Manu , Patel Harsita , Carter Michael , Jackson Heather , Powell Oliver , Fish Matthew , Barberio Manuela Terranova , Spada Filomena , Petrov Nedyalko , Wellman Paul , Darnell Sara , Mustafa Sobia , Todd Katrina , Bishop Cynthia , Cohen Jonathan , Kenny Julia , Berg Sarah van den , Sun Thomas , Davis Francesca , Jennings Aislinn , Timms Emma , Thomas Jessica , Nyirendra Maggie , Nichols Samuel , Elorrieta Leire Estramiana , D'Souza Giselle , Wright Victoria , De Tisham , Habgood-Coote Dominic , Ramnarayan Padmanabhan , Tissières Pierre , Whittaker Liz , Herberg Jethro , Cunnington Aubrey , Kaforou Myrsini , Ellis Richard , Malim Michael , Tibby Shane , Levin Michael 
Published: October 2023

Abstract

Severe febrile illnesses in children, such as multi-system inflammatory syndrome in children (MIS-C), severe bacterial infection (SBI), severe viral infection (SVI), and Kawasaki disease (KD), have shared clinical features. We used immunophenotyping with mass cytometry and cell stimulation experiments to illustrate shared and distinct mechanisms of immune dysfunction in 74 children with MIS-C, 30 with SBI, 16 with SVI, 8 with KD, and 42 controls. We then used targeted gene expression analysis to explore these findings in a secondary cohort of 500 children with these illnesses and 134 controls. Immunophenotyping and clustering analysis revealed neutrophil activation and apoptosis and T cell activation to be prominent in MIS-C and SBI. Cell stimulation experiments showed T cells from patients with acute MIS-C were exhausted. SVI was characterized by phosphorylated STAT signaling but lower gene expression for interferon receptors. Improved understanding of immune dysfunction may improve immunomodulator therapy in severe childhood febrile illnesses.
EIF4A3-mediated biogenesis of circSTX6 promotes bladder cancer metastasis and cisplatin resistance
Authors: Wei Wenjie , Liu Kan , Huang Xing , Tian Shuo , Wang Hanfeng , Zhang Chi , Ye Jiali , Dong Yuhao , An Ziyan , Ma Xin , Wang Baojun , Huang Yan , Zhang Xu 
Published: October 2023

Abstract
Background
Cisplatin (CDDP)-based chemotherapy is a standard first-line treatment for metastatic bladder cancer (BCa) patients, and chemoresistance remains a major challenge in clinical practice. Circular RNAs (circRNAs) have emerged as essential regulators in carcinogenesis and cancer progression. However, the role of circRNAs in mediating CDDP chemosensitivity has yet to be well elucidated in BCa.
Methods
CircSTX6 (hsa_circ_0007905) was identified by mining the public circRNA datasets and verified by Sanger sequencing, agarose gel electrophoresis, RNase R treatment and qRT-PCR assays. Then, function experiments were performed to evaluate the effects of circSTX6 on BCa metastasis. Luciferase reporter assay, RNA pull-down, RNA immunoprecipitation (RIP), RNA stability assay, fluorescence in situ hybridization (FISH) and immunofluorescence (IF) were conducted to evaluate the interaction among circSTX6, miR-515-3p, PABPC1 and SUZ12. Animal experiments were performed to explore the function of circSTX6 in tumor metastasis and CDDP sensitivity.
Results
We identified that circSTX6 was significantly upregulated in clinical samples and cells of BCa. Functionally, circSTX6 promoted cell migration and invasion both in vitro and in vivo. Mechanistically, circSTX6 could act as a miR-515-3p sponge and abolish its effect on SUZ12. Moreover, circSTX6 was confirmed to increase the stability of SUZ12 mRNA by interacting with a mRNA stabilizer PABPC1 and subsequently promote the expression of SUZ12. Importantly, silencing of circSTX6 improved the chemosensitivity of cisplatin-resistant bladder cancer cells to cisplatin. Furthermore, in vivo analysis supported that knockdown of circSTX6 attenuated the CDDP resistance in BCa tumors.
Conclusion
These studies demonstrate that circSTX6 plays a pivotal role in BCa metastasis and chemoresistance, and has potential to serve as a therapeutic target for treatment of BCa.
Empirical wavelet transform and wavelet mode decomposition for frequency characteristic extraction of EEG during sevoflurane general anesthesia
Authors: Yamochi Shoko , Yamada Tomomi , Obata Yurie , Sudo Kazuki , Kinoshita Mao , Akiyama Koichi , Sawa Teiji 
Published: October 2023

Abstract
Purpose
Mode decomposition methods are used to extract the characteristic intrinsic mode function (IMF) from various multidimensional time-series signals. Here, we applied wavelet transform-based mode decomposition to analysis of an electroencephalogram (EEG) recorded during general anesthesia.
Methods
An empirical wavelet transform (EWT) algorithm and a wavelet mode decomposition (WMD) algorithm with fixed frequency boundaries were added to previously reported EEG Mode Decompositor application software. Using our recently reported sevoflurane anesthesia data set, we performed EWT and WMD operations, and evaluated the significant characteristics via comparison with an existing variational mode decomposition (VMD) method.
Results
The EWT method, when decomposed into six IMFs, enabled narrowband separation of low-frequency bands IMF-1 to IMF-3, where all central frequencies were under 10 Hz. However, in the upper IMF of the high-frequency band with a center frequency ≥ 10 Hz, the dispersion of the frequency band covered was spread widely among the individual cases. In WMD, a narrow band of clinical interest can be specified using a band-pass filter via a Meyer wavelet filter bank within a specific mode decomposition discipline. When compared with VMD and EWT methods, the IMF decomposed using WMD is accommodated in a narrow band with a small variance for each case.
Conclusion
Although issues remain with the EWT, e.g., optimizing the process, the EWT can perform feature extraction similar to VMD. The Meyer filter bank used in the WMD represents an attractive technique for characteristic frequency band extraction when used as a band-pass filter in combination with the mode decomposition method.
Green tea is a protective factor that can preserve sperm DNA integrity: A retrospective study
Authors: Yang Wen , Geng Hao , Duan Zongliu , Gao Yang , shen Qunshan , Liu Liting , Wang Guanxiong , Zha Xiaomin , Xu Chuan , Zhou Ping , Wei Zhaolian , Song Bing , Tang Dongdong , Wu Huan , Li Guanjian , Cao Yunxia , He Xiaojin 
Published: October 2023

Abstract
Background: Although sperm DNA fragmentation index (DFI) is an vital biomarker for sperm DNA integrity and male fertility, factors that influence DFI have not been fully elucidated, particularly for occupational exposures and lifestyle factors. Here, we sought to explore the effects of self-reported occupational exposures and lifestyle factors on sperm DNA integrity.
Methods: The baseline characteristics, occupational exposures, and lifestyle factors of participants were collected immediately prior to or following semen evaluation through a self-report questionnaire. Participants were separated into three DFI-based groups: DFI<15%, 15%≤ DFI<30%, and 30%≤DFI. Initially, one-way ANOVAs and chi-square tests were employed to investigate the possible factors related to sperm DNA integrity. Then, we performed an ordered logistic regression analysis to detect factors independently associated with sperm DFI. To adjust for relevant confounders, we included factors with a P< 0.25 in univariate analyses as covariates.
Results: Among 1,060 subjects who participated in this study, 826 met the icludion cretieria. Univariate analysis showed that age, infertility type, infertility duration, semen parameters (concentration, motility and morphology) and smoking were related to sperm DNA integrity (P<0.05). At ordered logistic regression analysis, compared with the group that drank green tea 5-7 times/week, the groups that drank green tea <1 time/week (OR=1.52, 95% CI=1.05-2.2, and p=0.027) and 1-4 times/week (OR=1.61, 95% CI=1.02-2.54, and p=0.042) exhibited significantly increased sperm DFI values. Of the traditional semen parameters measured, a positive correlation was noted between sperm DFI and semen volume (OR=1.18, 95% CI=1.07-1.31) and abnormal sperm morphology (OR=1.2, 95% CI=1.11-1.3), whereas it was negatively correlated with sperm motility (OR=0.94, 95% CI=0.93-0.95). Relative to men over 40 years of age, we detected a 65% (95% CI=0.2-0.62) and 58% (95% CI=0.26-0.7) decrease in sperm DFI values in the 20-30 and 30-40 age groups, respectively.
Conclusions: These data suggest that green tea consumption is a protective factor associated with the preservation of sperm DNA integrity, which may offer new insights to guide the prevention and treatment of clinical male infertility.
Impact of an oral care subsidization reform on intersectional inequities in self-rated oral health in Sweden
Authors: Anticona Cynthia , Suominen Anna Liisa , Holgerson Pernilla Lif , Gustafsson Per E 
Published: October 2023

Abstract
Background
Oral health in Sweden is good at the population level, but seemingly with persisting or increasing inequities over the last decades. In 2008, a major Swedish reform introduced universal partial subsidies to promote preventive care and reduce the treatment cost for patients with extensive care needs. This study aimed to apply an intersectional approach to assess the impact of the 2008 subsidization reform on inequities in self-rated oral health among adults in Sweden over the period 2004–2018.
Methods
Data from 14 national surveys conducted over 2004–2018 were divided into three study periods: pre-reform (2004–2007), early post-reform (2008–2012) and late post-reform (2013–2018). The final study population was 118,650 individuals aged 24–84 years. Inequities in self-rated oral health were examined by intersectional analysis of individual heterogeneity and discriminatory accuracy across 48 intersectional strata defined by gender, age, educational level, income, and immigrant status.
Results
Overall, the prevalence of poor self-rated oral health decreased gradually after the reform. Gender-, education- and income-related inequities increased after the reform, but no discernable change was seen for age- or immigration-related inequities. The majority of intersectional strata experienced patterns of persistently or delayed increased inequities following the reform.
Conclusions
Increased inequities in self-rated oral health were found in most intersectional strata following the reform, despite the seemingly positive oral health trends at the population level. Applying an intersectional approach might be particularly relevant for welfare states with overall good oral health outcomes but unsuccessful efforts to reduce inequities.
Validation of a method based on liquid chromatography-tandem mass spectrometry for multiclass screening and analysis of 59 veterinary drugs in fishery foods
Authors: Park Sun-Young , Park Hyunjin , Kim Ji-Young , Choi Jang-Deok , Moon Gui-Im , Shin Dong Woo 
Published: October 2023

Abstract
Veterinary drugs (VDs) are regulated to prevent their abuse or misuse and protect humans that consume animal-based food products from exposure to VD residues. VD residues are managed according to the maximum residue limits (MRLs) or by prohibiting the use of VDs based on their residual properties and toxicities. However, all VD resides, even those that are not managed by MRLs, in animal-based food products will be regulated for public health improvement. Accordingly, herein, the applicability of an existing multiclass analytical method to the analysis of 59 VDs in fishery foods was validated. Applicability of this method to the analysis of VDs in livestock foods has already been confirmed. In this method, the sample was extracted with water:acetonitrile (1:4, v/v) followed by cooling, concentration, and analysis via liquid chromatography-mass spectrometry. Accuracies and precisions for three fishery foods (namely, flat fish, eel, and shrimp) were 63.7 − 120% and 1.9 − 30%, respectively, and a minimum of 63% (44/70) compounds could be quantified. This method is expected to improve the capabilities and efficiencies of monitoring VD residues in animal-based food products and will enhance food safety.
MAS-Net:A Novel Malaria Cell Detection Algorithm
Authors: Xiong Zhao , Wu Jiang 
Published: October 2023

Abstract
Malaria is one of the major global health threats. Microscopy examination is the ”gold standard” for malaria diagnosis designated by the World Health Organization. However, microscopy heavily relies on doctors’ expertise, leading to prolonged diagnosis times, reduced efficiency, and the risk of misdiagnosis. This paper introduces a multi-level attention split network (MAS-Net) that addresses the challenges of information loss in detecting small targets and the discrepancy between the detection head’s receptive field and target size. Additionally, we introduce a split contextual attention structure (SPCot) that incorporates contextual information and builds a novel feature extraction network around it. SPCot avoids excessive feature map channel compression, fully utilizes contextual information, reduces information loss, and improves detection performance. Furthermore, we propose the inclusion of a multi-scale receptive field detection head (MRFH) in the shallow detection layer. This module effectively adapts to targets of varying scales, enhances the receptive fields, and improves the detection performance of malaria cells. The model achieves a significant average accuracy of 75.9% on the publicly available malaria dataset.
Influence of impact-centrifugal hardener on microhardness of workpiece surface made of aluminium alloys
Authors: Kazimirov D. Yu. , Isachenko A. S. 
Published: October 2023

This article develops a tool for impact-centrifugal processing and establishes processing modes that increase the microhardness of the surface. An experimental study was carried out, where the tightening force, the number of working strokes, the rotation frequency of the hardener and the motion were proposed as technological parameters of impact-centrifugal processing. The experiments were carried out using ﬂat machine-cut samples based on aluminium alloy D16T. A prototype of the rotary hardener with the standard fastening was designed and manufactured. During the experiment, it was revealed that, for the variation in average microhardness, the contribution of the rotation frequency is higher than that of the longitudinal motion. A signiﬁcant inﬂuence of the tension on the surface microhardness is noted: following processing with a rotary hardener, it increases. It is shown that, to a greater extent, this increase depends on the technological tightening force and to a lesser extent on the rotation speed of the tool; it is recommended to increase these parameters. It was found that a 2-fold increase in tightening force resulted in an increase in microhardness by 70 HV 0.1, while increasing the tool rotation speed by 200 rpm led to an increase in microhardness by 42 HV 0.1. However, technological parameters must be selected taking into account the operability of the hardener. It was shown that the longitudinal motion has little inﬂuence on the increase in microhardness. The prototype of the designed tool can be used for processing at milling, boring, and grinding machines with computerised numerical control through a standardised fastening unit. This ensures sufﬁcient technological ﬂexibility and allows it to be used for reinforcing ﬂat surfaces and ﬁllet radii. The forecasted increase in the surface microhardness of the D16T sample using a rotary hardener amounts to 38.5% of the initial value in the experimental area with satisfactory productivity.
Processing of experimental results for super-cavitating flow past cone by local polynomial regression (LOESS)
Authors: Grishaev D. A. , Radzyuk A. Yu. , Istyagina E. B. 
Published: October 2023

The aim of the study is to deﬁne the correlations describing the ﬂow parameters during super-cavitating ﬂow past an obstacle, often found in various elements of thermal power systems and units, as well as to offer a simple and reliable method for analysing experimental datasets for the ﬂows in such systems. Full-scale modelling of cavitation processes was carried out using a circulating hydrodynamic set-up. The process of super-cavitation ﬂow past cones with base diameters of15.45 and 21.75 mm and opening angles of 154° and 127°, respectively, in a working section having a diameter of 30 mm, was investigated. The obtained experimental data comprises a four-dimensional array that describes the dependence of the cavity length arising behind the obstacle and the pressure inside the cavity on the ﬂow rate and temperature. Due to the complexity of processing and visual representation, this array was divided into two three-dimensional arrays. The approximation of the obtained data was carried out by locally estimated scatterplot smoothing (LOESS). The results demonstrated that the transition from vapour–gas to vapour cavitation is independent of the geometric dimensions of the obstacle. In addition, the dependence corresponding to the transition process to vapour cavitation was obtained by processing the experimental data. An empirical equation describing such a transition is proposed. Therefore, the method of smoothing a locally estimated scatter plot (local polynomial regression) illustrates the correlation between the processed data. The proposed empirical equation allows the critical length of the cavity to be determined that corresponds to the transition from vapour–gas to vapour cavitation and can be used for the design and operation of thermal power equipment.
Unraveling the dynamics of climate: empirical evidence from the Indian state of West Bengal
Authors: Das Soumik , Goswami Kishor 
Published: October 2023

Abstract

Understanding climate variability and trends is crucial for managing a host of sectors. Everything from water availability to agricultural productivity is affected by variability and trends in temperature, rainfall, evapotranspiration, and solar radiation. Nevertheless, their dynamics have seldom been explored together, especially in India. To address this gap, the present study investigates the variability, trend, and magnitude of those parameters individually and concurrently using fractal dimension and non-parametric statistics over the Indian state of West Bengal from 1951 to 2020. The results show a south–north gradient in overall climate variability. The Gangetic West Bengal (GWB) is experiencing higher variability, along with a rising minimum temperature (≥0.008 °C year−1) and declining rainfall (≥− 1 mm year−1). Though the Sub-Himalayan West Bengal as a whole shows less variability, its foothills reveal modest variation coupled with increasing maximum temperature (≥0.005 °C year−1), reference evapotranspiration (≥0.4 mm year−1), and decreasing rainfall in the post-monsoon and winter seasons. Based on the results, we identified the western GWB, the Sundarbans, and the sub-Himalayan foothills as the most vulnerable areas and recommended proactive crop and water management strategies. Finally, we underline the need to analyze climate dynamics holistically to manage climate-sensitive sectors efficiently and sustainably.