bluuebunny/crossref_metadata_2025_split huggingface dataset:
A sliding sequence importance resample filtering method for rolling bearings remaining useful life prediction based on two Wiener-process models
Authors: Song Youshuo , Xu Shaoqiang , Lu Xi 
Published: October 2023

Abstract
The remaining useful life (RUL) prediction of rolling bearings is an important part of prognostic and health management of mechanical systems. The model based on Wiener process can describe the time variability in the degradation process of bearings. However, in practical engineering, the degradation trends of bearings are often inconsistent, and it is difficult to fit the actual degradation trends of bearings with a single Wiener process model-based filtering method. Therefore, to improve the generalization ability, this paper uses linear model and exponential model based on Wiener process to predict bearing RUL. A sliding sequence importance resample filtering algorithm is proposed to track the degradation state of the bearing and reduce the prediction error by combining the two degradation models. Last, the superiority and effectiveness of the proposed method are illustrated by comparing with other commonly used RUL prediction methods on the basis of PRONOSTIA dataset.
A thin-film polymer heating element with a continuous silver nanowires network embedded inside
Authors: Kozhina Elizaveta , Panov Dmitry , Kovalets Nataliya , Apel Pavel , Bedin Sergey 
Published: October 2023

Abstract
This study presents a method for fabricating a film-based heating element using a polymer material with an array of intersecting conductive elements embedded within it. Track-etched membranes (TM) with a thickness of 10 μm were used as the template, and their pores were filled with metal, forming a three-dimensional grid. Due to the unique manufacturing process of TM, the pores inside intersect with each other, allowing for contacts between individual nanowires (NWs) when filled with metal. Experimental results demonstrated that filling the TM pores with silver allows for heating temperatures up to 78 degrees without deformation or damage to the heating element. The resulting flexible heating element can be utilized in medical devices for heating purposes or as a thermal barrier coating.
Deep learning based uncertainty prediction of deformable image registration for contour propagation and dose accumulation in online adaptive radiotherapy
Authors: Smolders A , Lomax A , Weber D C , Albertini F 
Published: October 2023

Abstract

Objective. Online adaptive radiotherapy aims to fully leverage the advantages of highly conformal therapy by reducing anatomical and set-up uncertainty, thereby alleviating the need for robust treatments. This requires extensive automation, among which is the use of deformable image registration (DIR) for contour propagation and dose accumulation. However, inconsistencies in DIR solutions between different algorithms have caused distrust, hampering its direct clinical use. This work aims to enable the clinical use of DIR by developing deep learning methods to predict DIR uncertainty and propagating it into clinically usable metrics. Approach. Supervised and unsupervised neural networks were trained to predict the Gaussian uncertainty of a given deformable vector field (DVF). Since both methods rely on different assumptions, their predictions differ and were further merged into a combined model. The resulting normally distributed DVFs can be directly sampled to propagate the uncertainty into contour and accumulated dose uncertainty. Main results. The unsupervised and combined models can accurately predict the uncertainty in the manually annotated landmarks on the DIRLAB dataset. Furthermore, for 5 patients with lung cancer, the propagation of the predicted DVF uncertainty into contour uncertainty yielded for both methods an expected calibration error of less than 3%. Additionally, the probabilisticly accumulated dose volume histograms (DVH) encompass well the accumulated proton therapy doses using 5 different DIR algorithms. It was additionally shown that the unsupervised model can be used for different DIR algorithms without the need for retraining. Significance. Our work presents first-of-a-kind deep learning methods to predict the uncertainty of the DIR process. The methods are fast, yield high-quality uncertainty estimates and are useable for different algorithms and applications. This allows clinics to use DIR uncertainty in their workflows without the need to change their DIR implementation.
Unified Bayesian network for uncertainty quantification of physiological parameters in dynamic contrast enhanced (DCE) MRI of the liver
Authors: Dejene Edengenet M , Brenner Winfried , Makowski Marcus R , Kolbitsch Christoph 
Published: October 2023

Abstract

Objective. Physiological parameter estimation is affected by intrinsic ambiguity in the data such as noise and model inaccuracies. The aim of this work is to provide a deep learning framework for accurate parameter and uncertainty estimates for DCE-MRI in the liver. Approach. Concentration time curves are simulated to train a Bayesian neural network (BNN). Training of the BNN involves minimization of a loss function that jointly minimizes the aleatoric and epistemic uncertainties. Uncertainty estimation is evaluated for different noise levels and for different out of distribution (OD) cases, i.e. where the data during inference differs strongly to the data during training. The accuracy of parameter estimates are compared to a nonlinear least squares (NLLS) fitting in numerical simulations and in vivo data of a patient suffering from hepatic tumor lesions. Main results. BNN achieved lower root-mean-squared-errors (RMSE) than the NLLS for the simulated data. RMSE of BNN was on overage of all noise levels lower by 33% ± 1.9% for k
trans, 22% ± 6% for v

e
and 89% ± 5% for v

p
than the NLLS. The aleatoric uncertainties of the parameters increased with increasing noise level, whereas the epistemic uncertainty increased when a BNN was evaluated with OD data. For the in vivo data, more robust parameter estimations were obtained by the BNN than the NLLS fit. In addition, the differences between estimated parameters for healthy and tumor regions-of-interest were significant (p < 0.0001). Significance. The proposed framework allowed for accurate parameter estimates for quantitative DCE-MRI. In addition, the BNN provided uncertainty estimates which highlighted cases of high noise and in which the training data did not match the data during inference. This is important for clinical application because it would indicate cases in which the trained model is inadequate and additional training with an adapted training data set is required.
Effect of Cu, Co, and Pb doping on physical properties of ZnO Zinc Blende and Hexagonal mixed phases thin films prepared by spray pyrolysis
Authors: Aboud Ahmed A , El-Dosari M , EL-Gawaad N S Abd , Yong Wang 
Published: October 2023

Abstract
Here we report the preparation of the Zinc Blende ZnO phase mixed with a small ratio of the Wurtzite phase. The spray pyrolysis technique has been employed for all films deposited onto amorphous glass substrates. The XRD results revealed the formation of mixed ZnO Zinc Blende (ZB) and Wurtzite (WU) phases with the ZB phase as the predominant phase. The crystallite size of both phases had estimated using Scherer’s equation and both phases were found to have the same crystallite size. The FE-SEM images show the formation of grain sizes bigger than those recorded from Scherer’s equation. XPS results confirm the existence of doped elements in the deposited films with different ratios. The optical band gap of the pure film was estimated and found to be 3.24 eV. Upon doping the band gap optical has been decreasing to 3.2 eV for Cu-doped ZnO and 3.22 and 3.24 eV for Pb and Co-doped films. The refractive index dispersion was found to change from normal to anomalous behavior for a pure film as the wavelength increases. Cu and Pb-doped films show dispersion relation and Co-doped film shows normal behavior. Also, the high-frequency dielectric constant has been determined and found to decrease upon all doping elements as compared to pure film.
Finite-time synchronization of fractional multi-wing chaotic system
Authors: Wang Shaofu 
Published: October 2023

Abstract
The objective of this article is to obtain multi-wing chaotic attractors of fractional chaotic systems through computerized symbolic computation. By applying the Julia fractal technique, the different number wing attractors are constructed for proposed equations. Moreover, the dynamics of the multi-wing system are analyzed by phase diagram, Poincare mapping, etc Consequently, the system exhibits complex dynamics, and the motion states at different order can be known from the bifurcation diagram with the change of order. Additionally, aiming at multi- wing fractional chaotic system, the controllers are designed, and the finite time synchronization control of the proposed system is performed. The results prove that the proposed finite-time synchronization method has important research value in the field of engineering.
A novel color image encryption scheme using elliptic curve cryptography and hyperchaotic system
Authors: Fang Jie , Zhao Kaihui , Liang Wanyong 
Published: October 2023

Abstract
This paper develops an asymmetric color image encryption algorithm based on elliptic curve cryptography(ECC), five dimensions(5D) hyperchaotic system, and DNA dynamic coding. To embed the characteristics of original image in the image encryption algorithm, this algorithm builds a mathematical model to strengthen the connection between the original image, elliptic curve Diffie-Hellman(ECDH) algorithm and hyperchaotic system. The red, green and blue(RGB) channels of encrypted image is reshaped into a three dimensions(3D) matrix. Grouping and scrambling of 3D matrix is accomplished at pixel level, bit level and DNA level based on a 5D hyperchaotic system, which effectively enhances the cross-layer variation of images. Then, improved ECC is performed on the scrambled image where multiple elliptic curves and dynamic shared private keys can guarantee the forward secrecy of the image encryption algorithm. At last, the image is performed diffusion to obtain the final encrypted image. Simulation results and security analysis both indicate the image encryption algorithm has better performances in terms of key space, Shannon entropy, clipping attack resistance, etc.
Thin-shell wormholes and modified Chaplygin gas with relativistic corrections
Authors: Bhatti M Z , Yousaf Z , Yousaf M 
Published: October 2023

Abstract
In this paper, we analyze thin-shell wormholes from two identical copies of charged static cylindrically symmetric spacetimes using Visser’s ‘cut and paste’ approach under the influence of f(R, T) gravity Harko, Lobo, Nojiri, and Odintsov (2011, Phys. Rev. D
84, 024020). In this scenario, the modified Chaplygin gas supports the exotic matter in the shell which allows, one to examine the dynamics of constructed wormholes. We utilize the junction condition to connect the interior and exterior geometries across the hypersurface and calculate different components of the Lanczos equation recently computed by Roza in Rosa (2021, Phy. Rev. D
103, 104069). We analyze the stability of the thin-shell wormhole models under linear perturbations while keeping the cylindrical symmetry and also examine the influence of charge on their stability. The positive quantity of the second derivative of potential at the throat radius might be interpreted as the stability criterion. We find both unstable and stable wormhole solutions for different parameters included in the equation of state and specific forms of considered gravity and illustrate them theoretically as well as graphically. We examine the impact of electric charge on the stability region of a constructed wormhole, which suggests that a wormhole model with a charge may exhibit more stable behavior compared to an uncharged system.
Update of Bragg edge analysis software “GUI-RITS”
Authors: Oikawa K , Sato H , Watanabe K , Su Y H , Shinohara T , Kai T , Kiyanagi Y , Hasemi H 
Published: October 2023

Abstract
The energy-resolved neutron imaging system, RADEN at J-PARC, has been providing to users a Rietveld-type analysis code, RITS, for pulsed neutron Bragg-edge transmission (BET) imaging with a graphical user interface (GUI) version, for fitting spectral data obtained with this instrument. In the last year, we updated the computational platform of GUI-RITS software from Scientific Linux 6 (SL6) and Python 2 to Windows 10 and Python 3, and added some functions to improve usability. The license agreement for this updated software is the Berkeley Software Distribution (BSD) 2-Clause License (non-copyleft) and is currently available for download from the RADEN website.
A freely distributable professional computed tomography system using NICOS
Authors: Schillinger B , Krüger J 
Published: October 2023

AbstractBased on the control system of the ANTARES neutron imaging system at FRM II, we have designed a portable, but professional neutron computed tomography system using the same TANGO device servers and the instrument control system NICOS. We have created a minimalistic setup to control a computed tomography setup using a single control computer that directly connects to a camera detector and interfaces a Raspberry Pi computer with motor control board via a local network. The setup has the full capability of a large instrument controller and can control arbitrary hardware (like professional motor controllers) for which hundreds of free drivers are available. Full schematics for the controller as well as print files for 3D printers for the detector housing and disk or virtual machine images are available for free to allow for the quick implementation of a low-cost, but professional neutron CT system even at very low power research reactors.
Tomographic reconstruction with Mantid Imaging
Authors: Tygier S , Akello-Egwel D , Allen J , Baust R , Bradley J , Burca G , Fedrigo A , Gigg M , Jones S , Kockelmann W , Nixon D , Pooley D E , Tasev D 
Published: October 2023

Abstract
Mantid Imaging has been developed to provide a graphical reconstruction process for users of neutron imaging instruments to eliminate the need to fall back on commercial software. Mantid Imaging builds on algorithms provided by libraries including Astra Toolbox and Tomopy to offer noise reduction, artifact removal, alignment, filtered back projection and iterative reconstruction methods. Extra functionality was added by using algorithms from ALGOTOM for ring removal and from the Core Imaging Library (CIL) for regularised 3D reconstruction.
Mantid Imaging 2.4 has recently been released. It is an open source Python GUI, runs under Linux and Windows and can easily be installed on end user systems. Mantid Imaging is aimed at users with no programming background and with little image processing experience. At ISIS Mantid Imaging runs on the ISIS-Data-Analysis-as-a-Service (IDAaaS) platform, which is remotely accessible with any modern web browser and gives users access to sufficient hardware resources to handle large datasets. Extensions of Mantid Imaging for energy-resolved neutron imaging are planned for the future.
How can Neutron Imaging contribute to Heritage Science? An overview at the ISIS Neutron and Muon Source
Authors: Fedrigo Anna , Grazzi Francesco , O’Flynn Daniel , Kockelmann Winfried , Cantini Francesco , Scherillo Antonella 
Published: October 2023

Abstract
Heritage Science HS spans a large variety of objects and materials, as well as anything that has historic, artistic, anthropological, and natural significance. This paper aims to bridge the gap between the physical and natural sciences and the humanities, and divulge neutron imaging techniques to a wider community. Here we give an introduction of the neutron imaging capabilities at the ISIS Neutron and Muon Source (UK), and a brief overview of some research activities in HS carried out at the facility in recent years, from neutron tomography to elemental imaging.
The INCHAMEL facility – a new device for in-situ neutron investigations under defined temperatures with applicable mechanical load
Authors: Weick S , Grosse M , Steinbrueck M 
Published: October 2023

Abstract
In order to in-situ quantify the hydrogen diffusion in metals or more precisely in zircaloy cladding tubes with the influence of an applied stress field, a new device was constructed in cooperation with the company ZwickRoell - the transportable INCHAMEL facility. It is a modification of ZwickRoell’s Kappa Mini 1 kN tensile testing machine. The facility is equipped with all features of a tensile testing machine, additionally a defined temperature can be applied. The machine’s design was dedicated in detail to fulfil the requirements for the usage in facilities with neutron radiation. In this manner, neutron radiography investigations can be performed in-situ with the neutron beam passing through the sample without any disturbances by installations like beam windows, thermo-couples, furnace tubes, heater wires, clamps for strain measurements, etc.
Design and application testing of imaging probe for strain measurement
Authors: Yu Peifeng , Cheng Jie , Tang Minwen , lin Feng , Zhang Zezhan , Gao Shan , Niu Yi , Wang Chao , Jiang Jing 
Published: October 2023

Abstract
To address the challenge of obtaining key device strain
parameters within narrow spaces, this paper presents the design of a
small-sized optical imaging probe with an independent optical system
based on the basic principle of digital image correlation (DIC). To
validate the strain measurement accuracy of the probe, a
high-temperature heating system was built under in a laboratory
setting, and experimental tests involving room temperature strain
measurement and high temperature thermal expansion coefficient
measurement were conducted. The findings demonstrate the potential
of the developed probe for strain measurement in critical components
situated in restricted spaces.
Increased extreme humid heat hazard faced by agricultural workers
Authors: Diaz Connor D , Ting Mingfang , Horton Radley , Singh Deepti , Rogers Cassandra D W , Coffel Ethan 
Published: October 2023

Abstract
Increases in population exposure to humid heat extremes in agriculturally-dependent areas of the world highlights the importance of understanding how the location and timing of humid heat extremes intersects with labor-intensive agricultural activities. Agricultural workers are acutely vulnerable to heat-related health and productivity impacts as a result of the outdoor and physical nature of their work and by compounding socio-economic factors. Here, we identify the regions, crops, and seasons when agricultural workers experience the highest hazard from extreme humid heat. Using daily maximum wet-bulb temperature data, and region-specific agricultural calendars and cropland area for 12 crops, we quantify the number of extreme humid heat days during the planting and harvesting seasons for each crop between 1979–2019. We find that rice, an extremely labor-intensive crop, and maize croplands experienced the greatest exposure to dangerous humid heat (integrating cropland area exposed to >27 °C wet-bulb temperatures), with 2001–2019 mean rice and maize cropland exposure increasing 1.8 and 1.9 times the 1979–2000 mean exposure, respectively. Crops in socio-economically vulnerable regions, including Southeast Asia, equatorial South America, the Indo-Gangetic Basin, coastal Mexico, and the northern coast of the Gulf of Guinea, experience the most frequent exposure to these extremes, in certain areas exceeding 60 extreme humid heat days per year when crops are being cultivated. They also experience higher trends relative to other world regions, with certain areas exceeding a 15 day per decade increase in extreme humid heat days. Our crop and location-specific analysis of extreme humid heat hazards during labor-intensive agricultural seasons can inform the design of policies and efforts to reduce the adverse health and productivity impacts on this vulnerable population that is crucial to the global food system.
Undergraduate teaching of surgical skills in the UK: systematic review
Authors: Glossop Sean C , Bhachoo Hari , Murray Thomas M , Cherif Rayan A , Helo John Y , Morgan Evie , Poacher Arwel T 
Published: October 2023

Abstract

Background
Students must be proficient in surgical skills according to General Medical Council and Royal College of Surgeons of England guidelines. If these skills are not appropriately taught, there is a risk of an incoming junior workforce with inadequate surgical skills. This paper aimed to review the literature relating to undergraduate teaching of surgical skills in the UK and summarize future suggested training methods.

Methods
The databases MEDLINE, Embase and SCOPUS were searched, and the existing literature relating to methodology of undergraduate teaching of surgical skills in the UK over the past 10 years was summarized. The Medical Education Research Quality Instrument was used to assess research quality.

Results
A total of 19 papers were included. Cross-sectional evaluations and survey-based studies highlight a clear deficit in surgical skills teaching in the UK. Medical students are currently unable to fulfil their own learning needs and meet requirements set out by the General Medical Council. This lack of surgical teaching appears to negatively affect student desire to pursue a surgical career. The three main themes for improvement are extracurricular surgical skills days, near-peer teaching and simulation. Each method appeared to improve learning, although no studies utilized medium- to long-term follow-up to demonstrate efficacy and there lacks a clear consensus as to the ‘standard’ of undergraduate surgical skill education. There was also potential for selection bias and response shift bias in many of the studies assessing pre- and postintervention confidence and opinions.

Conclusion
There is a concerning lack of surgical skills teaching that has resulted in medical students and junior doctors not having the necessary surgical skills as per General Medical Council guidance and students feel that their own learning needs are not met. This failure to address the learning deficit may be responsible for the fall in surgical competition ratios. While surgical skills teaching must be improved urgently, more robust evidence is required to evaluate the optimal ways of approaching this issue.