bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Important Risk Factor Affecting Hypercalciuria in Children: Vesicoureteral Reflux
Authors: Haberal Hakan Bahadir , Artykov Meylis , Hazir Berk , Altan Mesut , Citamak Burak , Kahraman Oguzhan , Tekgul Serdar , Dogan Hasan Serkan 
Published: November 2020

Abstract
Introduction A large number of genes and environmental factors, like dietary habits, play a role in the development of hypercalciuria in children. In this study, we aimed to determine the effects of the presence and grade of vesicoureteral reflux (VUR) on hypercalciuria status in children.
Materials and Methods Data for 165 patients who admitted to the Pediatric Urology Department were retrospectively analyzed. The patients were composed of following four different groups: (1) urinary stone patients, (2) VUR patients under follow-up, (3) corrected VUR patients, and (4) control. The demographic features, clinical data, and laboratory tests for the groups were compared.
Results The mean age of the patients was 100.6 ± 54.69 months and the female/male ratio was 79:86. The mean urinary calcium/creatinine (UCa/Cr) excretion and the frequency of high UCa/Cr ratios in the corrected VUR group were similar to those in the control group (p = 0.375 and 0.965, respectively). In contrast, the mean UCa/Cr excretion and frequency of high UCa/Cr ratios in the urinary stone and follow-up VUR groups were significantly higher than those in the corrected VUR group (p < 0.001, < 0.001, 0.003, and 0.029, respectively). The mean UCa/Cr excretion and frequency of high UCa/Cr ratios in the follow-up VUR group were similar to those in the urinary stone group (p = 0.323 and 0.425, respectively). In the follow-up VUR group, although reflux laterality had no effect on the UCa/Cr ratios (p = 0.180 and 0.108, respectively), the mean and frequency of high UCa/Cr ratios were higher in high-grade reflux cases (p < 0.001 and p = 0.042, respectively).
Conclusion Both the mean UCa/Cr ratio and the rate of hypercalciuria in the corrected reflux group were significantly lower than the corresponding values in the follow-up VUR and urinary stone groups. Further, the follow-up VUR patients had similar urinary calcium excretion levels as the stone patients. VUR treatment is associated with a decrease in urinary calcium excretion to the normal population level. A positive correlation between reflux degree and calcium excretion was observed.
Optimal selection of energy storage nodes based on improved cumulative prospect theory in China
Authors: Liu Jicheng , Wang Zhenzhen , Yin Yu , Li Yinghuan , Lu Yunyuan 
Published: November 2020

With the rapid development of the wind power value chain, the selection of appropriate node companies has become the focus of wind power alliance, especially in the value chain of energy storage. Through the optimization of the selection of energy storage node enterprises, the role of energy storage in the wind power value chain can be better utilized. At the same time, the optimal selection of energy storage nodes can accelerate the realization of value increment in the wind power value chain. In this study, we combine Interval type-2 fuzzy number and Grey Theory the Interval type-2 fuzzy number with Cumulative Prospect Theory, which is called IGCPT, and select the optimal energy storage nodes in the value chain based on it. First, considering the sustainable development of the entire value chain, 10 decision criteria from the four dimensions of BOCR: benefits, opportunities, costs, and risks are determined. Based on this, the IGCPT method is used to select the optimal scheme, and an optimization model is proposed to determine the significance of the criteria. Then, through the comparative analysis of the multi-criteria decision-making method and the sensitivity analysis of the obtained results, it is shown that the method can be effectively applied to the selection of energy storage nodes in the wind power value chain. Finally, suggestions and conclusions for the selection of wind power value chain node companies are given.
Beam propagation simulations for LISA in the presence of telescope aberrations
Authors: Kenny F , Devaney N 
Published: November 2020

Abstract
Accurate simulation of the propagation of light between the spacecraft of the laser interferometer space antenna (LISA) gravitational wave observatory will be a vital tool in determining the optical design of the telescopes used in the constellation. In this work, we examine the methods available for numerical simulation of this propagation, and consider the effect of an aberrated transmitting telescope (Tx) on the light collected by the receiving telescope (Rx). Propagation software has been developed using direct numerical integration methods, and has been validated by comparison to analytical solutions for particular cases. Zernike modal aberrations up to and including primary spherical have been considered in the Tx, and, in particular, the effects of defocus, astigmatism and coma were examined. It was found that minimization of the even radial order aberrations in Tx resulted in a reduced wavefront error at Rx, while odd aberrations such as coma can displace the maximum irradiance away from the optical axis. Thus careful consideration of the impact of telescope aberrations will be required to minimise detrimental effects on the detection of gravitational waves.
A novel approximate method to calculate the force applied on an elastic half space by a rigid sphere
Authors: Kontomaris S V , Malamou A 
Published: November 2020

Abstract
Assume a rigid sphere that is slightly pushed towards an elastic half space. The applied force on the half space can be easily calculated using the basic theoretical tools provided by the Hertzian contact mechanics theory. It should be noted that the aforementioned analysis is valid under the condition that the deformation depth is significantly smaller compared to the sphere’s radius (h ≪ R). So, a significant question arises; what if the sphere is pushed deeper in the elastic half space (e.g. h > R)? In this paper, the aforementioned question is answered and a relative discussion regarding the application of the results is presented.
A mathematical model for image saturation with an application to the restoration of solar images via adaptive sparse deconvolution
Authors: Guastavino S , Benvenuto F 
Published: November 2020

Abstract
In this paper we introduce a mathematical model of the image saturation phenomenon occurring in a charged coupled device (CCD), and we propose a novel computational method for restoring saturated images acquired by the atmospheric imaging assembly (AIA) telescope. The mathematical model takes into account both primary saturation, when the photon-induced charge reaches the CCD full well capacity, and the blooming effect, when the excess charge flows into adjacent pixels. The restoration of AIA saturated images is then formulated as an inverse problem with a forward operator encoding the standard diffraction of light rays by a convolution, the primary saturation by an upper limit to the number of photons and the blooming effect by the conservation of the photon-induced charge spilled over adjacent pixels. As a result of this theoretical formulation we propose an adaptive ℓ
1 regularized inversion method improving the desaturation capabilities of the existing SE-DESAT method [Guastavino S et al 2019 Astrophys. J.
882 109]. We prove that this method has the consistency estimation property also in the case that a fixed unknown background is considered. We test the adaptive method both in the case of synthetic and real data, comparing the performance with the one of the SE-DESAT method, showing that the proposed method avoids edge effects and artifacts in reconstructions even when the background solar activity is particularly intense.
Roadmap: proton therapy physics and biology
Authors: Paganetti Harald , Beltran Chris , Both Stefan , Dong Lei , Flanz Jacob , Furutani Keith , Grassberger Clemens , Grosshans David R , Knopf Antje-Christin , Langendijk Johannes A , Nystrom Hakan , Parodi Katia , Raaymakers Bas W , Richter Christian , Sawakuchi Gabriel O , Schippers Marco , Shaitelman Simona F , Teo B K Kevin , Unkelbach Jan , Wohlfahrt Patrick , Lomax Tony 
Published: November 2020

Abstract
The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, ‘improving efficiency’, ‘improving planning and delivery’, ‘improving imaging’, and ‘improving patient selection’.
A multivariable study of deformable image registration evaluation metrics in 4DCT of thoracic cancer patients
Authors: Juan-Cruz Celia , Fast Martin F , Sonke Jan-Jakob 
Published: November 2020

Abstract
Deformable image registration (DIR) accuracy is often validated using manually identified landmarks or known deformations generated using digital or physical phantoms. In daily practice, the application of these approaches is limited since they are time-consuming or require additional equipment. An alternative is the use of metrics automatically derived from the registrations, but their interpretation is not straightforward. In this work we aim to determine the suitability of DIR-derived metrics to validate the accuracy of 4 commonly used DIR algorithms. First, we investigated the DIR accuracy using a landmark-based metric (target registration error (TRE)) and a digital phantom-based metric (known deformation recovery error (KDE)). 4DCT scans of 16 thoracic cancer patients along with corresponding pairwise anatomical landmarks (AL) locations were collected from two public databases. Digital phantoms with known deformations were generated by each DIR algorithm to test all other algorithms and compute KDE. TRE and KDE were evaluated at AL. KDE was additionally quantified in coordinates randomly sampled (RS) inside the lungs. Second, we investigated the associations of 5 DIR-derived metrics (distance discordance metric (DDM), inverse consistency error (ICE), transitivity (TE), spatial (SS) and temporal smoothness (TS)) with DIR accuracy through uni- and multivariable linear regression models. TRE values were found higher compared to KDE values and these varied depending on the phantom used. The algorithm with the best accuracy achieved average values of TRE = 1.1 mm and KDE ranging from 0.3 to 0.8 mm. DDM was the best predictor of DIR accuracy, with moderate correlations (R
2 < 0.61). Poor correlations were obtained at AL for algorithms with better accuracy, which improved when evaluated at RS. Only slight correlation improvement was obtained with a multivariable analysis (R
2 < 0.64). DDM can be a useful metric to identify inaccuracies for different DIR algorithms without employing landmarks or digital phantoms.
Magnetic separation of iron oxide nanoparticles to improve their application for magnetic particle imaging
Authors: Arsalani Soudabeh , Löwa Norbert , Kosch Olaf , Radon Patricia , Baffa Oswaldo , Wiekhorst Frank 
Published: November 2020

Abstract
Magnetic particle imaging (MPI) is a promising medical imaging technique for visualizing the three-dimensional distribution of tracer materials, specifically iron oxide nanoparticles (IONP). The optimization of magnetic nanoparticles (MNP) plays an essential role to improve the image resolution and sensitivity of imaging techniques. Objective. In this work, the optimization of commercial IONP (EMG 700, Ferrotec) coated with anionic surfactants was carried out using magnetic separation (MS) technique, by a low gradient magnetic separation (LGMS) (<15 T m−1) method, to improve their performance as MPI tracers. Approach. The magnetophoretical behavior of the samples in different concentrations ranging from 2 to 120 mmol l−1 was investigated over 24 h of separation. The samples were characterized by dynamic light scattering (DLS), AC susceptibility (ACS), magnetic particle spectroscopy (MPS) and they were imaged in a preclinical MPI scanner, before and after MS. Main results. DLS results showed that by increasing the concentration from 2 to 120 mmol l−1 the hydrodynamic diameter of MNP decrease from 75 to 47 nm and size distribution decrease from 0.19 to 0.11 after 4 min MS. In addition, the MPS results demonstrated the third harmonic amplitude normalized to the iron amount

(

A

3

*

)

and harmonic ratio

A

5

/

A

3

of signal increase from 8.38 to 10.59 Am2 kg−1 (Fe) and 24.21–26.60, respectively. Furthermore, the MPI images of the samples after separation showed higher MPI resolution. Significance. Therefore, LGMS can be considered as a valuable method to narrow and control the size distribution of MNP for MPI.
4D deep image prior: dynamic PET image denoising using an unsupervised four-dimensional branch convolutional neural network
Authors: Hashimoto Fumio , Ohba Hiroyuki , Ote Kibo , Kakimoto Akihiro , Tsukada Hideo , Ouchi Yasuomi 
Published: November 2020

Abstract
Although convolutional neural networks (CNNs) demonstrate the superior performance in denoising positron emission tomography (PET) images, a supervised training of the CNN requires a pair of large, high-quality PET image datasets. As an unsupervised learning method, a deep image prior (DIP) has recently been proposed; it can perform denoising with only the target image. In this study, we propose an innovative procedure for the DIP approach with a four-dimensional (4D) branch CNN architecture in end-to-end training to denoise dynamic PET images. Our proposed 4D CNN architecture can be applied to end-to-end dynamic PET image denoising by introducing a feature extractor and a reconstruction branch for each time frame of the dynamic PET image. In the proposed DIP method, it is not necessary to prepare high-quality and large patient-related PET images. Instead, a subject’s own static PET image is used as additional information, dynamic PET images are treated as training labels, and denoised dynamic PET images are obtained from the CNN outputs. Both simulation with [18F]fluoro-2-deoxy-D-glucose (FDG) and preclinical data with [18F]FDG and [11C]raclopride were used to evaluate the proposed framework. The results showed that our 4D DIP framework quantitatively and qualitatively outperformed 3D DIP and other unsupervised denoising methods. The proposed 4D DIP framework thus provides a promising procedure for dynamic PET image denoising.
Design of HL-2A plasma position predictive model based on deep learning
Authors: Yang Bin , Liu Zhenxing , Song Xianmin , Li Xiangwen 
Published: November 2020

Abstract
In tokamak discharge experiments, the plasma position prediction model’s research is to understand the law of plasma motion and verify the correctness of the plasma position controller design. Although Maxwell equations can completely describe plasma movement, obtaining an accurate physical model for predicting plasma behavior is still challenging. This paper describes a deep neural network model that can accurately predict the HL-2A plasma position. That is a hybrid neural network model based on a long short-term memory network. We introduce the topology, training parameter setting, and prediction result analysis of this model in detail. The test results show that a trained deep neural network model has high prediction accuracy for plasma vertical and horizontal displacements.
3D printing and dynamic modeling of a polymer-based bimodal piezoelectric motor
Authors: Li Xiaoniu , Yu De , Cao Teng , Wen Zhiyi , Lu Chunyao , Liu Wei , Zhu Chunling , Wu Dawei 
Published: November 2020

Abstract
Owing to characteristics of single-step fabrication and rapid prototyping, 3D printing have potential applications in processing piezoelectric motors with complex structures. In this paper, a 3D printed resin-based bimodal piezoelectric motor is proposed. Four slots of the motor are designed to reduce the influence of large damping caused by polymer’s viscoelastic and enhance mechanical properties. Considering the viscoelasticity and internal structure of the stator, a dynamic model based on the proposed motor is developed. Furthermore, parameters of these slots are optimized using the Taguchi method. Prototypes are fabricated and experimentally investigated. The results demonstrate that the first longitudinal mode and the second bending mode are 17 765 Hz and 18 006 Hz respectively, which are consistent with the analytical model results. Under the voltage of 300 Vpp, the maximum no-load speed and maximum driving load of the slotted motor are 200 r min−1 and 20 g with a speed of 6 r min−1, respectively. Compared with the motor without slots, the speed and load capacity are increased by 25% and 33%. Therefore, the motor with slots exhibits better mechanical output performance.
Global pattern of historical and future changes in rapid temperature variability
Authors: Xu Zhongfeng , Huang Fang , Liu Qi , Fu Congbin 
Published: November 2020

Abstract
Day-to-day (DTD) temperature variation reflects a rapid weather variability, which significantly affects human health and ecosystems. However, while a few of studies have addressed certain regional variations, no global pattern of rapid temperature variability has yet been investigated. Here, using global daily temperature observation data, we present a study of the worldwide spatial heterogeneity of rapid temperature variability and its long-term trends over the past 60 years. We found a significant decline in northern mid and high latitudes in boreal winter but a significant increase in the Arctic coast, South China and Australia in boreal summer during the study period. Using observational data and Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble simulations, we further demonstrate that the human-caused increase in greenhouse gases (GHGs) concentration leads to a significant change in meridional temperature gradient, which in turn results in the observed decline of rapid temperature variability in the mid and high latitudes and the increase in rapid temperature variability in Arctic Coast in summer. In contrast, human-induced increase in GHGs and aerosol accounts for approximately one third and two third of the decline of rapid temperature variability in North China in boreal summer, respectively. However, the increase in summer rapid temperature variability in southern China appears to be primarily associated with the long-term internal climate variability. It is further shown that, based on the CMIP5 multi-model ensemble simulations, the projected rapid temperature variability shows a significant decrease in the high latitudes in winter but a slight increase in tropical zones by the end of this century. These findings clearly reveal an important role of human activities on the historical and future rapid temperature variability.
Detecting the net effect of flooding on infectious diarrheal disease in Anhui Province, China: a quasi-experimental study
Authors: Liao Wenmin , Wu Jiabing , Yang Lianping , Benmarhnia Tarik , Liang Xin-Zhong , Murtugudde Raghu , Sapkota Amir , Ma Wenjun , Zhong Shuang , Huang Cunrui 
Published: November 2020

Abstract
Though a number of studies have shown positive relationships between flooding events and infectious diarrhea, there is a paucity of rigorous evidence regarding the net effect of flooding on diarrhea incidence, controlling for existing pre-trends and meteorological confounders. The study treats the 2016 catastrophic flood event in Anhui Province, China as a natural experiment using a difference-in-differences design with propensity score matching to exclude background variations of diarrhea occurrence and meteorological effects, thus isolating the net effect of flooding on diarrhea. A triple-differences analysis was further deployed to identify the potential effect modifiers, including gender, age, occupation and community health resources. By analyzing 359 580 cases of diarrhea that occurred before, during and after the flooding, we show that the 2016 flood event significantly increased the risk of dysentery (RR: 1.29, 95%CI: 1.15–1.46) in during-flood period, and also increased the risk of all-cause diarrhea (RR: 1.21, 95%CI: 1.17–1.26), typhoidal diarrhea, dysentery, and other infectious diarrhea in post-flood period. Children, males and non-farmers were particularly vulnerable to flooding impacts and the density of health professionals was found to be protective against diarrheal risk in both during-flood (RR: 0.81, 95% CI: 0.72–0.92) and post-flood (RR: 0.83, 95% CI: 0.77–0.88) periods. This study employs quasi-experimental design and provides a better understanding on both acute and sustained effects of flooding on diarrhea, which is important for accurate health impact assessments and developing targeted intervention strategies.
Geometry of efficient Electromagnetic Linear actuators for flapping wing MAVs
Authors: McIvor Blake A , Ogunwa Titilayo T , Chahl Javaan S 
Published: November 2020

Abstract
A constraining factor in the development of flapping wing micro air vehicles (MAVs) is the power density and efficiency of actuators. Piezoelectric and rotary electromagnetic actuators have been shown to have functional power densities but can require mechanically complex transmissions to create flapping motion. Electromagnetic Linear actuators (ELAs) have unique characteristics, allowing them to be controlled and implemented similarly to muscles but demonstrated much lower efficiency. This study presents configurations of ELA consisting of multiple coils and magnets that have the potential to improve efficiency. The use of lightweight conductors in the form of copper clad aluminium (CCA) is explored as a method to improve power density. A numerical method of optimising the geometry and mass distribution of the magnetic and conductive material is presented. The results show the power consumption of these actuators can range between 910-260 W/kg. The inclusion of an additional magnet and coil can improve efficiency by up to 3.5 times over typical flapping wing ELAs.