bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on infrared spectroscopy detection of furfural content in transformer oil based on acetonitrile extraction
Authors: Tian Yi , Li Zhiwei , Wang Shuai , Zhu Guixin , Shi Haonan , Wang Yanru , Niu Bo , Zhu Yongcan , Huang Xinbo 
Published: May 2024

Abstract
The stable operation of power transformers depends on the oil-paper insulation system, in which the aging degree of insulating paper is the key to evaluate the remaining life of the transformer. Currently, methanol extraction is widely used to detect the furfural content in oil to evaluate the aging state of insulating paper, but it ignores the influence of methanol produced during the operation of the transformer on the extraction results. To address this issue, this paper proposes a new method that can replace methanol extraction for detecting furfural in oil through simulation and experiment. Firstly, through simulation and experiment, it is proved that the strong vibration absorption peaks at 1677 cm−1 for furfural carbonyl and 2240 cm−1 for acetonitrile cyano can be used to establish a new method for extracting furfural content in oil using acetonitrile. A quantitative model between the concentration x of furfural in the furfural-acetonitrile mixed solution and the area y of the infrared absorption peak at 1677 cm−1 is established, with a goodness of fit of 0.9974. Secondly, a comparison between direct detection and acetonitrile extraction methods is conducted. The results show that direct detection is simple to operate, but the minimum detection concentration is 40 mg l−1, which is difficult to meet practical requirements. Acetonitrile extraction can reduce the minimum detection concentration to 0.1 mg l−1. At the same time, the extraction conditions are analyzed to determine the extraction ratio of 30, extraction times of 5, and extraction rate of 60%. Finally, the proposed detection method is applied to thermal aging tests on insulating paper of different types. The experimental results show that the proposed method has good repeatability and improves the detection resolution of furfural content. This paper combines infrared spectroscopy with acetonitrile extraction technology to open up a more efficient and practical new method for detecting furfural content in transformer oil.
Tire defect detection based on low and high-level feature fusion
Authors: Wu Hao , Wang Yunfeng , Zhou Yi , Liu Xiyu , Zhai Xiaodi , Sun Kuizhi , Tian Chengliang , Li Tao , Jia Wenguang , Zhao Haixia , Zhang Yan 
Published: May 2024

AbstractRecently, object detection based on deep learning has made great progress in the field of defect detection. Due to its complex texture background and varied defect features, existing defect detection methods based on object detection face great challenges in the detection of tire internal defects. In this paper, a tire defect detection model based on low and high-level feature fusion is proposed. First, a multi-head feature extraction module is proposed, which extracts abundant effective information from multiple dimensions. Second, a spatial semantic fusion upsampling module is proposed to alleviate the problem of information loss in the upsampling process. Finally, a novel prediction head is designed to expand the receptive field by compressing the size of the feature map to improve the detection accuracy of large defects. Experimental results show that the mAP of the proposed method achieves 94.03% on the tire internal defect dataset, and the average detection time is 36.74 ms, which can meet the needs of industrial online detection.
Advancements in nanoparticle-based therapies for multidrug-resistant candidiasis infections: a comprehensive review
Authors: Izadi Alireza , Paknia Fatemeh , Roostaee Maryam , Mousavi Seyed Amin Ayatollahi , Barani Mahmood 
Published: May 2024

Abstract

Candida auris, a rapidly emerging multidrug-resistant fungal pathogen, poses a global health threat, with cases reported in over 47 countries. Conventional detection methods struggle, and the increasing resistance of C. auris to antifungal agents has limited treatment options. Nanoparticle-based therapies, utilizing materials like silver, carbon, zinc oxide, titanium dioxide, polymer, and gold, show promise in effectively treating cutaneous candidiasis. This review explores recent advancements in nanoparticle-based therapies, emphasizing their potential to revolutionize antifungal therapy, particularly in combating C. auris infections. The discussion delves into mechanisms of action, combinations of nanomaterials, and their application against multidrug-resistant fungal pathogens, offering exciting prospects for improved clinical outcomes and reduced mortality rates. The aim is to inspire further research, ushering in a new era in the fight against multidrug-resistant fungal infections, paving the way for more effective and targeted therapeutic interventions.
Long time existence of the non-isentropic slightly compressible Navier-Stokes equations with boundary conditions
Authors: Ju Qiangchang , Xu Jianjun 
Published: May 2024

Abstract
We investigate the long time existence of smooth solutions to the initial boundary value problem for the non-isentropic slightly compressible Navier–Stokes equations with slip or non-slip boundary conditions on the velocity. We verify that the compressible Navier–Stokes equations with boundary conditions admit a unique smooth solution on the time interval where the smooth solution of the incompressible Navier–Stokes equations exists, when the Mach number is sufficiently small. Moreover, we obtain the uniform convergence of smooth solutions for the compressible system toward those for the corresponding incompressible system on that time interval.
Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach
Authors: Chang Zhuo , Peng Chen-Hao , Chen Kai-Jung , Xu Guang-Kui 
Published: May 2024

Abstract
Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.
Uncertainty estimation and evaluation of deformation image registration based convolutional neural networks
Authors: Rivetti Luciano , Studen Andrej , Sharma Manju , Chan Jason , Jeraj Robert 
Published: May 2024

Abstract

Objective. Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challenges persist in proper uncertainty evaluation and hyperparameter optimization for these methods. This work aims to develop and evaluate a model that can perform fast DIR and predict its uncertainty in seconds. Approach. This study introduces a novel probabilistic multi-resolution image registration model utilizing convolutional neural networks to estimate a multivariate normal distributed dense displacement field (DDF) in a multimodal image registration problem. To assess the quality of the DDF distribution predicted by the model, we propose a new metric based on the Kullback–Leibler divergence. The performance of our approach was evaluated against three other DIR algorithms (VoxelMorph, Monte Carlo dropout, and Monte Carlo B-spline) capable of predicting uncertainty. The evaluation of the models included not only the quality of the deformation but also the reliability of the estimated uncertainty. Our application investigated the registration of a treatment planning computed tomography (CT) to follow-up cone beam CT for daily adaptive radiotherapy. Main results. The hyperparameter tuning of the models showed a trade-off between the estimated uncertainty’s reliability and the deformation’s accuracy. In the optimal trade-off, our model excelled in contour propagation and uncertainty estimation (p <0.05) compared to existing uncertainty estimation models. We obtained an average dice similarity coefficient of 0.89 and a KL-divergence of 0.15. Significance. By addressing challenges in DIR uncertainty estimation and evaluation, our work showed that both the DIR and its uncertainty can be reliably predicted, paving the way for safe deployment in a clinical environment.
DMGM: deformable-mechanism based cervical cancer staging via MRI multi-sequence
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Authors: Cheng Junqiang , Zhao Binnan , Liu Ziyi , Huang Deqing , Qin Na , Yang Aisen , Chen Yuan , Shu Jian 
Published: May 2024

Abstract

Objective. This study aims to leverage a deep learning approach, specifically a deformable convolutional layer, for staging cervical cancer using multi-sequence MRI images. This is in response to the challenges doctors face in simultaneously identifying multiple sequences, a task that computer-aided diagnosis systems can potentially improve due to their vast information storage capabilities. Approach. To address the challenge of limited sample sizes, we introduce a sequence enhancement strategy to diversify samples and mitigate overfitting. We propose a novel deformable ConvLSTM module that integrates a deformable mechanism with ConvLSTM, enabling the model to adapt to data with varying structures. Furthermore, we introduce the deformable multi-sequence guidance model (DMGM) as an auxiliary diagnostic tool for cervical cancer staging. Main results. Through extensive testing, including comparative and ablation studies, we validate the effectiveness of the deformable ConvLSTM module and the DMGM. Our findings highlight the model’s ability to adapt to the deformation mechanism and address the challenges in cervical cancer tumor staging, thereby overcoming the overfitting issue and ensuring the synchronization of asynchronous scan sequences. The research also utilized the multi-modal data from BraTS 2019 as an external test dataset to validate the effectiveness of the proposed methodology presented in this study. Significance. The DMGM represents the first deep learning model to analyze multiple MRI sequences for cervical cancer, demonstrating strong generalization capabilities and effective staging in small dataset scenarios. This has significant implications for both deep learning applications and medical diagnostics. The source code will be made available subsequently.
Virtual cylindrical PET for efficient DOI image reconstruction with sub-millimetre resolution
Authors: Enríquez-Mier-y-Terán Francisco E , Kyme Andre Z , Angelis Georgios , Meikle Steven R 
Published: May 2024

Abstract

Objective. Image reconstruction in high resolution, narrow bore PET scanners with depth of interaction (DOI) capability presents a substantial computational challenge due to the very high sampling in detector and image space. The aim of this study is to evaluate the use of a virtual cylinder in reducing the number of lines of response (LOR) for DOI-based reconstruction in high resolution PET systems while maintaining uniform sub-millimetre spatial resolution. Approach. Virtual geometry was investigated using the awake animal mousePET as a high resolution test case. Using GEANT4 Application for Tomographic Emission (GATE), we simulated the physical scanner and three virtual cylinder implementations with detector size 0.74 mm, 0.47 mm and 0.36 mm (vPET1, vPET2 and vPET3, respectively). The virtual cylinder condenses physical LORs stemming from various crystal pairs and DOI combinations, and which intersect a single virtual detector pair, into a single virtual LOR. Quantitative comparisons of the point spread function (PSF) at various positions within the field of view (FOV) were compared for reconstructions based on the vPET implementations and the physical scanner. We also assessed the impact of the anisotropic PSFs by reconstructing images of a micro Derenzo phantom. Main results. All virtual cylinder implementations achieved LOR data compression of at least 50% for DOI PET reconstruction. PSF anisotropy in radial and tangential profiles was chiefly influenced by DOI resolution and only marginally by virtual detector size. Spatial degradation introduced by virtual cylinders was most prominent in the axial profile. All virtual cylinders achieved sub-millimetre volumetric resolution across the FOV when 6-bin DOI reconstructions (3.3 mm DOI resolution) were performed. Using vPET2 with 6 DOI bins yielded nearly identical reconstructions to the non-virtual case in the transaxial plane, with an LOR compression factor of 86%. Resolution modelling significantly reduced the effects of the asymmetric PSF arising from the non-cylindrical geometry of mousePET. Significance. Narrow bore and high resolution PET scanners require detectors with DOI capability, leading to computationally demanding reconstructions due to the large number of LORs. In this study, we show that DOI PET reconstruction with 50%–86% LOR compression is possible using virtual cylinders while maintaining sub-millimetre spatial resolution throughout the FOV. The methodology and analysis can be extended to other scanners with DOI capability intended for high resolution PET imaging.
Finger photopletysmography detects early acute blood loss in compensated blood donors: a pilot study
Authors: Speroni Gerardo , Antedoro Patricia , Marturet Silvia , Martino Gabriela , Chavez Celia , Hidalgo Cristian , Villacorta María V , Ahrtz Ivo , Casadei Manuel , Fuentes Nora , Kremeier Peter , Böhm Stephan H , Tusman Gerardo 
Published: May 2024

Abstract

Objective. Diagnosis of incipient acute hypovolemia is challenging as vital signs are typically normal and patients remain asymptomatic at early stages. The early identification of this entity would affect patients’ outcome if physicians were able to treat it precociously. Thus, the development of a noninvasive, continuous bedside monitoring tool to detect occult hypovolemia before patients become hemodynamically unstable is clinically relevant. We hypothesize that pulse oximeter’s alternant (AC) and continuous (DC) components of the infrared light are sensitive to acute and small changes in patient’s volemia. We aimed to test this hypothesis in a cohort of healthy blood donors as a model of slight hypovolemia. Approach. We planned to prospectively study blood donor volunteers removing 450 ml of blood in supine position. Noninvasive arterial blood pressure, heart rate, and finger pulse oximetry were recorded. Data was analyzed before donation, after donation and during blood auto-transfusion generated by the passive leg-rising (PLR) maneuver. Main results. Sixty-six volunteers (44% women) accomplished the protocol successfully. No clinical symptoms of hypovolemia, arterial hypotension (systolic pressure < 90 mmHg), brady-tachycardia (heart rate <60 and >100 beats-per-minute) or hypoxemia (SpO2 < 90%) were observed during donation. The AC signal before donation (median 0.21 and interquartile range 0.17 a.u.) increased after donation [0.26(0.19) a.u; p < 0.001]. The DC signal before donation [94.05(3.63) a.u] increased after blood extraction [94.65(3.49) a.u; p < 0.001]. When the legs’ blood was auto-transfused during the PLR, the AC [0.21(0.13) a.u.; p = 0.54] and the DC [94.25(3.94) a.u.; p = 0.19] returned to pre-donation levels. Significance. The AC and DC components of finger pulse oximetry changed during blood donation in asymptomatic volunteers. The continuous monitoring of these signals could be helpful in detecting occult acute hypovolemia. New pulse oximeters should be developed combining the AC/DC signals with a functional hemodynamic monitoring of fluid responsiveness to define which patient needs fluid administration.
The influence of cholesterol and calcium ions on the interaction of cryoprotectors with a biological membrane model
Authors: Svechnikova V Y , Mishukova O V , Mironova A G , Khomutov G B , Marchenkova M A , Yakovenko S A 
Published: May 2024

Abstract
In this work, we studied the effects of three cryoprotectors – ethylene glycol, dimethyl sulfoxide and sucrose – on the compression isotherms of egg yolk Langmuir monolayers both in the presence and in the absence of cholesterol in the monolayer. The influence of calcium ions from the subphase affecting the effectiveness of cryoprotection on π-A isotherms is also examined. In addition, the elastic properties of the obtained monolayers are investigated by calculation and comparison the compression modulus of the monolayer. The scientific novelty of the work is in consideration of a complex biosimilar system (an egg yolk monolayer, cholesterol and their mixtures) on the surface of the aqueous solution of the nutrient mixture and obtaining information about the specific interaction of different cryoprotectors with lipid membranes. We found that when calcium ions and cryoprotectors are simultaneously added to the subphase, they block each other's influence on the lipid monolayer and reduce the effectiveness of cryoprotection. Cholesterol in the yolk in a ratio of 1:50 m m−1 changes the properties of the monolayer, which leads to increased action of cryoprotectors. Also, for the first time, the effect of a significant increase in surface pressure (by ∼20 mN m−1) was detected when cryoprotectors were added to the system under consideration. This effect can serve as an indicator of the effectiveness of membrane dehydration by cryoprotectors and can be used to find the most effective and safe cryoprotector compositions. The obtained data can provide important recommendations for the development of cryoprotective media for cell freezing. Since the study of the mechanisms of calcium interaction (the most important signaling cation) with biological membrane and membrane-like systems is important for understanding the various effects caused by medicinal and biologically active drugs at the cellular level, the study is of interest for various fields of biophysics and biomedicine.
Mechanical property optimization of Sn-1.5Ag-0.5Cu solder alloys with additions of Bi, In, and Te
Authors: Eid N A M , El-Daly A A , Ibrahiem A A 
Published: May 2024

Abstract
The mechanical characteristics of Sn-1.5Ag-0.5Cu (SAC155) alloy modified with In, Bi, and Te microalloying are investigated in relation to three strengthening mechanisms that withstand coarsening: (i) micron-scale Ag3Sn, Cu6Sn5, SnTe, Ag2In and InSn4 IMC precipitated phases, (ii) Bi in solid solution and (iii) Bi precipitated particles formed upon eutectic solidification. Compared to SAC155 alloy with a single strengthening mechanism, the combined effect of three deformation processes operating in SAC(155)-3Bi-2In with high In content and SAC(155)-3Bi-0.2Te (wt%) with low Te content alloys greatly improved the mechanical properties at high temperatures. It was found that, despite a discernible reduction in ductility, the high In content could refine the microstructure, enrich the elastic modulus (E), yield stress (YS), and ultimate tensile strength (UTS) of SAC(155)-3Bi-2In to almost 2.3 times that of SAC155 solder. On the other hand, a low Te content greatly increased SAC(155)-3Bi-0.2Te’s mechanical strength ∼2.3 times, while a large atomic size difference between Te and Sn atoms caused excessive misfit strain, which in turn increased Bi’s solubility in β-Sn grains, and improved ductility by approximately twice that of SAC(155)-3Bi-2In solder.
Thermoelectric effects in ballistic junctions of 2D-Weyl semimetals
Authors: Lotfi Jafar , Abdollahipour Babak 
Published: May 2024

Abstract
Two dimensional Weyl semimetals are a variant of topological materials in two dimensions, which are realized in three atomic layer materials. These materials possess isotropic or anisotropic dispersions around Weyl nodes and present some common physical properties with their 3D counterparts. We study the thermoelectric effects in a ballistic junction of 2D-Weyl semimetal with isotropic or anisotropic dispersions around the Weyl points. We demonstrate that these two types of 2D-Weyl semimetals exhibit different thermoelectric responses at low chemical potentials of the leads. The Weyl semimetal layer’s physical characteristics can significantly affect these junctions’ thermoelectric properties. Moreover, significant Seebeck coefficient and thermoelectric figure of merit of these junctions are only observed at the low chemical potential of the leads. In particular, we unveil that thermoelectric effects in the ballistic junction of 2D-Weyl semimetals are not as efficient as their 3D counterparts.
Michelson interferometer-based tunable multiwavelength thulium-doped fluoride fiber laser in S-band for 5 G networks
Authors: Ahmad Harith , Lohano Leela Wanti , Nizamani Bilal , Samion Muhamad Zharif , Ismail Mohamad Faizal 
Published: May 2024

Abstract
This work reported a multiwavelength thulium-doped fluoride fiber laser (TDFFL) for the S-band region using the Michelson interferometer as an optical filter. Michelson interferometer was utilized as a comb-like filter, whereas dispersion-compensated fiber (DCF) of 10 km length was used to increase the number of lasing lines and reduce mode competition. Approximately 61 lasing lines were achieved with a signal-to-noise ratio (SNR) of 40 dB in the wavelength region from 1501.36 to 1505.52 nm within 10 dB of maximum power. The stability of the multiwavelength fiber laser was also recorded for the time duration of two hours, and it was found that all lasing lines were stable and equally spaced at the free spectral range (FSR) of 0.07 nm. The variation in optical power was less than 0.5 dB; however, the wavelength shift was about 0.01 nm. Tunability of multiwavelength laser has also been observed up to the broader transmission span of 57 nm by incorporating the tunable band pass filter (TBPF). Moreover, FSR was observed to be tunable within the range of 0.02 to 0.14 nm by using the optical delay line (ODL) with a Michelson interferometer. Additionally, the proposed laser can generate frequency signals from 2.65 GHz to 18.54 GHz according to the obtained range of FSR.
On optical soliton solutions of the higher-order Lakshmanan-Porsezian-Daniel model having the cubic-quintic-septic law in the presence of spatio-temporal and chromatic dispersion
Authors: Ozdemir Neslihan , Secer Aydin , Ozisik Muslum , Bayram Mustafa , Yuce Salim 
Published: May 2024

Abstract
The higher-order Lakshmanan-Porsezian-Daniel equation (LPDE) with the cubic-quintic-septic (CQS) law having spatiotemporal and chromatic dispersion terms (STD-CD) is examined to derive new optical soliton solutions. To accomplish this aim, we operated on a simple version of the new extended auxiliary equation method (SAEM26). The optical soliton solutions of the LPDE with CQS as well as STD-CD are constructed in detail. Moreover, 3D-surface, contour, and 2D plots are presented for the bright and periodic singular soliton solutions. Additionally, the effects of diverse model parameters on the bright soliton structure are surveyed, and these effects are displayed with 2D graphics. The findings established in this work can positively contribute to research in nonlinear optics, while the SAEM26 can be effectively applied to similar nonlinear models.