bluuebunny/crossref_metadata_2025 huggingface dataset:
Chaos and ergodicity in a partially integrable 3d Bohmian system: a comparison with 2d systems
Authors: Tzemos A C , Contopoulos G
Published: May 2023

In the present paper we study the Bohmian dynamics of a partially integrable 3d Bohmian system whose trajectories evolve on spherical surfaces. By use of spherical coordinates (R, ϕ, θ) we study the behaviour of unstable fixed points that generate chaos on the (ϕ, θ) plane and discuss the differences between them and those of planar 2d systems. Finally, we show for the first time that the chaotic trajectories of this system are ergodic although the number of its nodes is very small (two). Thus we can observe ergodicity not only in multinodal 2d systems but also in partially integrable systems with few nodes due to their curved geometry.
Primordial black hole isocurvature modes from non-Gaussianity
Authors: van Laak Raphaël , Young Sam
Published: May 2023

Primordial black holes (PBHs) are black holes that might have formed in high density
regions in the early universe. The presence of local-type non-Gaussianity can lead to large-scale
fluctuations in the PBH formation rate. If PBHs make up a non-negligible fraction of dark matter,
these fluctuations can appear as isocurvature modes, and be used to constrain the amplitude of
non-Gaussianity. Assuming that the parameters of non-Gaussianity are constant over all scales, we
build upon the results of previous work by extending the calculation to include peaks theory and
making use of the compaction C for the formation criteria, accounting for non-linearities
between C and the curvature perturbation ζ. For quadratic models of non-Gaussianity, our
updated calculation gives constraints that are largely unaltered compared to those previously
found, while for cubic models the constraints worsen significantly. In case all of the DM is made
up of PBHs, the parameters of non-Gaussianity are -2.9 · 10-4 < f < 3.8 · 10-4 and
-1.5 · 10-3 < g < 1.9 · 10-3 for quadratic and cubic models respectively.
Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach
Authors: Yu Mingzhao , Peterson Mallory R , Cherukuri Venkateswararao , Hehnly Christine , Mbabazi-Kabachelor Edith , Mulondo Ronnie , Nsubuga Kaaya Brian , Broach James R , Schiff Steven J , Monga Vishal
Published: May 2023

Objective. Hydrocephalus is the leading indication for pediatric neurosurgical care worldwide. Identification of postinfectious hydrocephalus (PIH) verses non-postinfectious hydrocephalus, as well as the pathogen involved in PIH is crucial for developing an appropriate treatment plan. Accurate identification requires clinical diagnosis by neuroscientists and microbiological analysis, which are time-consuming and expensive. In this study, we develop a domain enriched AI method for computerized tomography (CT)-based infection diagnosis in hydrocephalic imagery. State-of-the-art (SOTA) convolutional neural network (CNN) approaches form an attractive neural engineering solution for addressing this problem as pathogen-specific features need discovery. Yet black-box deep networks often need unrealistic abundant training data and are not easily interpreted. Approach. In this paper, a novel brain attention regularizer is proposed, which encourages the CNN to put more focus inside brain regions in its feature extraction and decision making. Our approach is then extended to a hybrid 2D/3D network that mines inter-slice information. A new strategy of regularization is also designed for enabling collaboration between 2D and 3D branches. Main results. Our proposed method achieves SOTA results on a CURE Children’s Hospital of Uganda dataset with an accuracy of 95.8% in hydrocephalus classification and 84% in pathogen classification. Statistical analysis is performed to demonstrate that our proposed methods obtain significant improvements over the existing SOTA alternatives. Significance. Such attention regularized learning has particularly pronounced benefits in regimes where training data may be limited, thereby enhancing generalizability. To the best of our knowledge, our findings are unique among early efforts in interpretable AI-based models for classification of hydrocephalus and underlying pathogen using CT scans.
Processing of offshore measurement data for multi-fidelity wake model performance assessments
Authors: Freitas S , Navarro Diaz G , Koutoulakos S , Mihoubi C , Rowen M , Erbslöh S
Published: May 2023

Numerical wake models used for offshore wind farm developments are regularly evaluated through comparisons with field measurements of atmospheric conditions and turbine performance data. However, measurement data from offshore sites can be plagued by a variety of issues that are often neglected from data processing procedures and can strongly impact the reliability of the metrics used for model evaluation. While some of these issues have been addressed through assumptions, a variety of shortcomings are frequently overlooked. In this work, the issues found with measurement data used to compile an evaluation dataset to be applied for numerical wake model assessments are presented. The dataset contains long-term operational data from two neighboring offshore wind farms in the German Bight and meteorological data from a met mast located in between the wind farms. The methodologies used to overcome these issues with minimal impact on the reliability of the evaluation dataset for modelling are presented and discussed. Furthermore, the repercussions of overlooking such shortcomings are highlighted and future challenges posed by the planned expansions of offshore wind energy capacity are addressed.
Entrainment model for wind turbine wakes considering blockage effect
Authors: Li Ning , Liu Yongqian , Li Li , Meng Hang
Published: May 2023

The entrainment model applied firstly by P. Luzzatto-Fegiz can predict the streamwise velocity of the far-wake more accurately than the traditional models (e.g., Jensen model, Frandsen model). The current model, however, neglects the wind speed drop approaching the rotor caused by the blockage effect, the phenomenon of which cannot be considered in the velocity recovery of the far-wake region, further affecting the precision of wake prediction. Hence, this paper proposes an entrainment model considering the blockage effect. We adopt several numerical simulation results to analyze the performance with the vortex cylinder model for the rotor vicinity. The initial entrainment parameter Einitial calculates, according to the formula of the breakdown position of tip vortices proposed by J.N. Sørensen. The Enear-wake can obtain with the length of the near-wake region, defined by P. E. J. Vermeulen. The linearized entrainment-parameterized expression we develop combines the linearization hypothesis with the above two positions and their entrainment values. The proposed model consists of two main components: the modified entrainment model and the vortex cylinder model, validated against the advanced Gaussian model of Bastankhah and Porté-Agel (BPA) and several LES cases. The results demonstrate that the proposed model significantly improves the streamwise wake distribution.
Simulating wake losses of the Danish Energy Island wind farm cluster
Authors: van der Laan M. P. , García-Santiago O. , Sørensen N. N. , Troldborg N. , Criado Risco J. , Badger J.
Published: May 2023

The increase in the number of installed offshore wind farms has led to clustering, where wind farm interaction can cause energy losses. The Danish government is planning an Energy Island in the North Sea consisting of ten 1 GW wind farms. The initial wind farm layout design from a consultant company (COWI) has reported a 5% annual energy production (AEP) wake loss based on a low-fidelity engineering wake model that is known to underestimate wind farm interaction. The present work employs higher-fidelity wake models based on Reynolds-averaged Navier-Stokes (RANS) and a mesoscale model, which predict higher AEP losses due to wind farm interaction; namely, between 8.6-10.1%. In addition, we investigate how a microscale model as RANS can be employed to simulate a large wind farm cluster efficiently, and we compare its results with mesoscale model simulations.
A baseline for ensemble-based, time-resolved inflow reconstruction for a single turbine using large-eddy simulations and latent diffusion models
Authors: Rybchuk A , Martínez-Tossas L A , Hamilton N , Doubrawa P , Vijayakumar G , Hassanaly M , Kuhn M B , Zalkind D S
Published: May 2023

We are interested in reconstructing winds flowing through a turbine on a second-by-second basis over a 10 min window. Previously, we developed a machine learning algorithm that takes in a snapshot of wind speed measurements and generates ensembles of three-dimensional wind field estimates. Here, we use these estimates as initial conditions in large-eddy simulations and reconstruct atmospheric and turbine response dynamic quantities in a synthetic field campaign. In doing so, we establish a baseline for model validation that future time-aware data assimilation techniques will be compared to. In turbine-free case studies, ground truth wind speeds consistently fall within our estimated wind speed distribution for the first 100 s after the simulation start. In simulations with turbines, the wind estimates show a small bias of 0.10 m s−1 and good correlation of 0.80 during the first 100 s. During this window, our estimates of the Blade 1 bending moment and generator power typically span the ground truth, with the estimate of the former performing better overall. In summary, this approach shows promise as a stand-alone technique for reconstructing real-world inflow and turbine dynamics in 1−2 min windows and as a foundation for future time-aware data assimilation techniques.
Analytical Descriptions of Swirling Wake Profiles
Authors: Schutz William , Naughton Jonathan
Published: May 2023

Wake behavior significantly affects the performance and lifetime of wind turbines on which it impacts. This study considers wake profile fits applied to velocity data gathered in a swirling turbulent wake. Wake rotation or swirl has been found to impact wake growth and evolution, and thus both wake deficit and swirl profiles are fit. Specifically, Gaussian and double Gaussian functions are applied to the wake deficit profiles, and Lamb-Oseen and Taylor distributions are used for the tangential velocity profiles. Fits that accurately represent the wake profiles promise to improve wake representations that can be used, for example, in stability theory analyses and wake modeling. The double Gaussian and Taylor vortex distributions were found to best represent the distributions, but Taylor vortex distribution failed to capture the true distribution at some radial locations. An example use of these fits to quantify the impact of swirl on wake evolution is provided.
Comparing scanning lidar configurations for wake measurements based on the reduction of associated measurement uncertainties
Authors: Hung Lin-Ya , Santos Pedro , Gottschall Julia
Published: May 2023

Scanning lidars are increasingly being used for new measurement applications, such as wake measurements. This type of measurement requires an uncertainty quantification, and the setup of such instruments should ideally be planned to minimize the overall measurement uncertainty. Based on a previous experimental study, we quantify the overall uncertainty for a scanning lidar wake measurement campaign by analyzing the pointing accuracy for distinct configuration scenarios. The selected scenarios are based on a single ground-based scanning lidar measuring the downstream flow, a scanning lidar mounted on the turbine’s nacelle and, finally, two scanning lidars measuring dual-Doppler points within the wake. The results for each configuration are presented in terms of the overall uncertainty and measurement outputs provided from these setups. In a case study using the experimental dataset to compare ground- and nacelle-based configurations, we find that – under slightly stable conditions at 5D downstream – the overall radial wind speed uncertainty, normalized by reference wind speed without counting the sample size uncertainty, decreases on average from 2.78% for the ground-based lidar to 1.33% for the nacelle-based setup. Another advantage of the nacelle-based setup is the potentially larger sample size, as it can measure multiple downstream distances at once. The dual-lidar configuration has advantages in providing horizontal wind speed and direction instead of radial wind speed components only, hence reducing uncertainties associated with wind direction. However, this comes with the cost of fewer measured points to be compared with an engineering wake model and less flexibility to position the lidars, since their relative spatial position impacts the uncertainty. In summary, the presented methodology can benefit the best selection of scanning lidar configuration for a particular application, here demonstrated for wake measurements, proving the user with an estimation of the overall measurement uncertainty and, most importantly, the sensitivity of each parameter.
Numerical investigation of rotor asymmetry to promote wake recovery
Authors: Abraham Aliza , Ramos-García Néstor , Sørensen Jens Nørkær , Leweke Thomas
Published: May 2023

Tip vortices in the wakes of wind turbines are known to have detrimental effects on downstream turbines such as reduced performance and increased fatigue loading. Rotor asymmetry is investigated as a passive method for mitigating these effects by triggering the helical vortex pairing instability. The study is conducted using MIRAS, a multi-fidelity vortex solver, to compare the wakes of the standard NREL 5MW turbine and a modified asymmetric version where one blade is extended radially relative to the other two. The asymmetric rotor is shown to successfully trigger the vortex instability, increasing the wake average velocity by a maximum of 3.5% and the power available to a downstream turbine by up to 11%. The turbulence in the wake of the asymmetric rotor is also modified, exhibiting enhanced mixing. Using the available power gains from the simulations and operational data from the Lillgrund wind farm, the total impact of rotor asymmetry on wind farm efficiency is estimated, showing increases > 2% under certain wind conditions. The findings of this study indicate that rotor asymmetry has strong potential as a wake control method and would benefit from further investigation to understand the effects of inflow turbulence and the impacts on rotor loading.
High-fidelity simulations of wake-to-wake interaction in an atmospheric boundary layer over a complex terrain
Authors: Jané-Ippel C. , Bempedelis N. , Palacios R. , Laizet S.
Published: May 2023

In this work, the wind farm simulator WInc3D is employed to perform large-eddy simulations (LES) of the flow over a complex terrain. The methodology used is validated through comparison with previously published wind tunnel experiments and numerical data for the flow over a cosine-squared hill with and without wind turbines. The study focuses on the wake-to-wake interaction between two wind turbines, with one on the hilltop and the other 2.5 or 5 turbine diameters downstream of the hilltop. The results indicate that the power output of the downstream turbine can be increased by a factor of three when a wind turbine is placed on the hilltop. This is explained by the accelerated flow that results from the favourable pressure gradient produced by the first half of the hill and the blockage of the hilltop turbine. It is also found that this effect is not sufficient to enhance the power of the downstream turbine if it is placed too far away from the upstream turbine.
Large-Eddy Simulation of airborne wind energy systems wakes
Authors: Crismer J-B , Trigaux F , Duponcheel M , Winckelmans G
Published: May 2023

Wind energy is usually harnessed using wind turbines but it is not the only way of collecting this energy. In this paper, Airborne Wind Energy Systems (AWES) are considered. The understanding of the wake shed by such devices is of primary importance when considering farms, yet it has not been much studied so far, and even less so when considering kites with soft curved wing. In this work, LES is used to analyse the wake of AWES. Two types of wings are considered: a straight wing, modelling the reference rigid wing AWES and a curved wing accounting for leading edge inflatable kites. Both types of wings are modelled using actuator lines. The wake analysis reveals that the wake of curved wings tends to be stronger and to recover faster. For the case of the tilted trajectory, asymmetries in the wake are also noted. The difference is explained by the azimuthal variation of the circulation distribution on the wing. It also relates to some wakes characteristics for tilted wind turbines. The wake of the curved wing is also more sensitive to the variation of the loading when it flies tilted trajectory, due to the varying loading on its tips.
Graph machine learning for predicting wake interaction losses based on SCADA data
Authors: Hammer Florian , Helbig Nora , Losinger Thomas , Barber Sarah
Published: May 2023

Six wind turbine generators (WTGs) within a larger wind farm were chosen to model wake interaction losses by means of graph machine learning. 10-minute averaged measurement data values at each turbine over a period of two years were available. Based on the measured power output and ”free-stream” (undisturbed) wind conditions, determined at an upstream WTG unaffected by wakes, a data-driven free-stream power curve model was built. The cluster of WTGs was then represented by a graph data structure in the form of an adjacency matrix, where the turbines are nodes, which in turn are connected by edges. The edges are represented by weightings, indicating the strength of wake interactions between connected turbines. To learn the weightings, the predicted power outputs of the free-stream power curve model were compared to the measured power outputs and then optimised to account for these differences, which are attributed to wake interaction losses. After that a new data-driven model was trained, with free-stream wind speed, direction and yaw misalignment as features and the optimised weightings as targets. It was shown that the model was able to predict power curves that show clear patterns due to wake effects and reduced the root mean squared error, based on the measured and predicted values, by 16.29% compared to the free-stream power curve model.
Comparison of three DWM-based wake models at above-rated wind speeds
Authors: Hanssen-Bauer Ø W , Doubrawa P , Aa Madsen H , Asmuth H , Jonkman J , Larsen G C , Ivanell S , Stenbro R
Published: May 2023

In this study we investigate three mid-fidelity wind turbine wake models based on the dynamic wake meandering (DWM) model principle, and compare their performance with a reference dataset, produced with large-eddy simulations using the actuator line model. The models are compared with respect to flow field, power, and loads on a row of four 5MW reference turbines experiencing above-rated wind conditions. In general, the DWM models show fairly good agreement with large-eddy simulation for the time-averaged flow fields, blade forces and power, with increasing differences along the turbine row. Also when comparing fatigue loads of blade root moments, the differences between the models increase further into the row, with deviations up to 25 % of the reference case. However, while the development in blade root moment fatigue along the turbine row is predominantly driven by the energy content at the frequency corresponding to the turbine’s rotational period (1P) for the DWM models, the large-eddy simulation results suggest that the key drivers for the blade root and tower loads are the increase in meandering and energy at higher frequencies (> 1P) deeper into the turbine row. For the tower loads, the DWM models highly underestimate the fatigue for the waked turbines. From these results, we suggest priorities for future model developments so that robust model implementations can be used in wind farm design and operation.
Research on Chemical Composition and Weathering of Ancient Glass Based on Grey Correlation
Authors: Wu Chi , Fu Xingyao , Shi Jinlong , Liu Quanwei
Published: May 2023

In this paper, the probability statistics method is used to convert the categorical values into quantitative values, and the TOPSIS method is used to obtain the weight of each index. After unification, the canonical correlation regression model is constructed to judge the correlation between glass weathering and its colour, type and decoration. Finally, the conclusion that the weathering of glass cultural relics is related to these attributes is drawn. In view of the chemical composition of glass cultural relics of unknown category, this paper uses grey correlation analysis to identify its type, and uses multi-factor sensitivity analysis to analyse its sensitivity. Finally, it is found that SiO2 has the highest sensitivity among all chemical components.
Simulation and Experimental Study on Anti-damage Performance of Gun & Ammunition Cabinet
Authors: He Yong-liang , Sun Chuan-ming
Published: May 2023

In order to meet the requirements that the gun & ammunition cabinets is carried and transported with the armed forces, it used the finite element analysis method to analyze the anti-damage performance by ANSYS software. Firstly, it established the analysis model of the finite element about gun & ammunition cabinet, and determined the stress distribution through static analysis. Secondly, it designs the dropping analysis test that in order to close to the real dropping in the finite element analysis. From three angles of left, right and vertical angle, the test is carried out that fall from a height of 1m. In the test, the cabinet contains three different materials thickness that are 1.5mm, 1.4mm and 1.3mm. Through the analysis of dropping, it knows that the cabinet can meet the requirements of carrying and transporting with armed forces, when the thickness is 1.5mm. Although the whole cabinet is seriously deformed, the stress in the key position is less than the fracture stress. Finally, the anti-damage experiment is designed that it verified by the anti-damage test. The experiment results show that the working time for damaging the cabinet should take 14min, and the damage area is not less than 38cm2. The results confirm that the gun & ammunition cabinet with a material thickness of 1.5mm meet the requirements of the army forces.
Rolling Bearing Fault Diagnosis Based on Multiscale Block Convolution Neural Network
Authors: Wang Peng , Luo Yuting , Gong Liming , Zhou Yiren
Published: May 2023

The working conditions of rolling bearings are always non-stationary, which will degrade the performance of the traditional intelligent fault diagnosis algorithm can achieves better results under constant working conditions. Aiming to the problems mentioned above, a novel fault diagnosis algorithm based on Multiscale Block Convolutional Neural Network (MBCNN) has been proposed in this paper. Compared with other intelligent fault diagnosis algorithms, the proposed algorithm achieves the reuse of effective features while simultaneously extracting global and local fault features end-to-end synchronously. Owing to the original one-dimensional vibration signal can effectively reveal the non-stationarity of bearing fault signal, it is selected as the input of MBCNN and the output of multiple fault categories. Finally, a experiment is conducted to verify the validity of the model, and the advantages of the model are analyzed through the visualization of features. The results show that compared with other methods, this method has higher prediction performance under variable working conditions.
Research on the Influence of the Parasitic Loop of the Roll-Pitch Seeker on the Stability of the Guidance System
Authors: Xiao Bowen , Zhou Hang , Yao Dongdong , Xia Qunli
Published: May 2023

Disturbance rejection rate is an important performance index of the seeker,the disturbance rejection rate affects the extraction accuracy of the line-of-sight angular velocity output by the seeker,and introduce an additional parasitic loop in the guidance loop,this loop affects the stability of the guidance system and reduces the accuracy of the missile guidance system. This paper analyzes the extraction principle of the line-of-sight angular velocity of the roll-pitch seeker,the parasitic loop model of the roll-pitch seeker caused by the scale deviation between the detector, the frame angle sensor and the angular rate gyroscope is established, and the stability and time domain response characteristics of the parasitic loop are analyzed. Then, based on the time-invariant theory, the influence of the parasitic loop of the roll-pitch seeker on the stability of the guidance system and the guidance parameters is analyzed.The simulation results show that the positive and negative feedback characteristics of the disturbance rejection rate parasitic loop have a great influence on the stability of the guidance system. It is necessary to design appropriate guidance parameters according to the characteristics of the parasitic loop to meet the guidance accuracy requirements.
Robust Control Design for Systems with Discrete Time Delay of 1,3-PD Fermentation
Authors: Li Xuan , Li Meixia , Zhu Xi
Published: May 2023

A disturbed model with discrete time delay for the continuous fermentation of glycerol bio-dissimilation to 1,3-propanediol by Klebsiella pneumoniae is presented in this paper. The biochemistry process cannot refrain from the disturbances caused by both time delay and exogenous disturbance. The above negative factors may restrict and undermine the accomplishment performance of the dynamic system, and even lead to unstable oscillations. In consideration of multiplicity phenomena, the stability behaviors of multiply equilibriums have been analyzed. In order to reduce the disturbance effect, we propose an H∞ controller through LMIs method. The simulation results indicate that the closed-loop system can be assured to be internal stable and to achieve the H∞ performance. The controller might be practicable for the continuous culture.
Gesture Recognition Algorithm Based on Computer Vision
Authors: Li Manhua , Xia Hongye , Li Peiyang , Lu Huacai
Published: May 2023

With the advent of the era of artificial intelligence, computer vision and machine learning are developing rapidly, and human-computer interaction technology has become one of the important research directions. This paper mainly combines computer vision and other related technologies to analyze and judge the gestures, and predict the corresponding models according to the different matching of gestures, so as to recognize the corresponding gesture information. By converting the image into HSV space, HSV channel separation is realized, and then filtering and skin color segmentation are carried out to carry out morphological operation. Finally, shape matching is carried out according to the contour information of the image to judge the information of gesture. The experimental results show that the gesture recognition algorithm proposed in this paper can effectively judge the gesture information contained in the image, has good operation effect and strong practicability.
Development and Application of Particle Transport Monte Carlo Simulation Modeling Toolkit
Authors: Shang Peng , Huang Liu-xing , Zhu Jin-hui , Niu Sheng-li , Liu Li
Published: May 2023

In particle transport Monte Carlo simulation, the manual modeling method is not suitable for complex geometric models. A Monte Carlo Simulation Modeling Toolkit (pyMCMT) is developed based on Python language. The toolkit can generate input card in several classical format such as MCNP and GDML format automatically. In this paper, two typical applications are presented based on the pyMCMT toolkit: 1, constructing a multilayer circular geometric model in complex density distribution by pyMCMT toolkit in order to satisfy the requirement of building large-space fine model with the influence of blast wave. A two-dimensional adaptive model is built for non-uniform atmospheric induced by blast wave. The number of the cells in this model is reduced vastly with the same model resolution; 2, producing the optimized weight window parameter using the mesh-based weight window variance reduction combined with density iteration method which is realized to solve the high statistical fluctuation and low counting efficiency problem in deep penetration process. The successful application of pyMCMT shows that pyMCMT is a modularized, parameterized, customizable and easy-to-debug toolkit for particle transport Monte Carlo simulation modeling, which can improve the modeling efficiency tremendously.
Research on Knowledge Graph Technology with Unbalanced Samples
Authors: Chen Hao , Bai Yang , Wei Miaomiao
Published: May 2023

The application of the existing knowledge graph is widely concentrated in the civil fields with sufficient sample size and uniform distribution, especially in the Internet, finance and other fields. Due to the particularity of its application background in the military field, there is a general lack of sample size, which greatly limits the support ability of knowledge atlas technology for military intelligent applications. Therefore, how to solve the problem of automatic knowledge extraction of multimodal data under the condition of unbalanced samples is the key core problem that affects the application effect of knowledge perception technology in the military field. This topic focuses on the characteristics of small batch, multi batch, imbalance and diversity of data in the field of military operations, introduces the self-monitoring method based on deep learning, solves the problem of low accuracy of automatic knowledge extraction of unstructured data, solves the dependence of traditional intelligent extraction algorithm on sample size, carries out research on automatic construction technology of knowledge atlas, and constructs equipment type spectrum library.
Research on Multi-Objective Optimization to the Shape of Air Cushion Surge Tank
Authors: Zhang Tianyu , Huang Yan , Zhou Jianzhong , Zhang Yongchuan , Cui Zilong
Published: May 2023

This paper aims to research on multi-objective optimization to the shape of air cushion surge tank (ACST) in hydropower station. Firstly, a novel nonlinear mathematical model of hydropower station with ACST is established. Then, the analysis of the structure parameter of ACST on hydropower station during transient process is carried out. Furthermore, a multi-objective optimization and decision-making method is applied to determine the shape of ACST. Finally, it is carried out that the comparison analysis by numerical simulation between the optimal parameter and initial parameters of ACST under the checking condition. The results indicate that the impedance hole area, initial gas pressure and cross-sectional area has influence on the transient process index of hydropower station to a certain extent, so they are selected as optimization variables. The hydropower station shows superior dynamic quality under the optimized shape of ACST both in the design condition and in the checking condition. Specifically, the maximum water pressure at the end of volute is reduced by 5.84m and 5.19m respectively, the maximum pressure of air chamber decreases by 2.18m and 1.76m separately, and the extreme water level of ACST goes down by 3.82m and 3.81m solely under design condition and checking condition.
Optimal Choices of Reconstruction Parameters United Improved C-C Algorithm and Improved G-P Algorithm
Authors: Wei Lai , Cao Hui , Wang Longde
Published: May 2023

For the phase space reconstruction of chaotic time series, the precise selection of delay and embedding dimension is indispensable. Therefore, this paper makes an in-depth study on the selection of reconstruction parameters, and puts forward some suggestions for improving the theoretical defects of the original C-C algorithm and G-P algorithm. The modified C-C algorithm optimizes the intermediate determination parameters of delay time and embedded window of the original algorithm, and makes the selection of delay time and embedded window more accurate. The improved G-P algorithm optimizes the range of neighborhood radius and the selection of scale-free interval, and improves the calculation accuracy of embedding dimension. On the theoretical basis, Lorenz sequence and Rossler sequence are used to verify, and the simulation results can be obtained. The improved algorithm can select parameters more accurately. Finally, the parameters obtained by the two improved algorithms are compared, and it is considered that the phase space reconstruction can be better by using the improved C-C algorithm to solve the delay and the improved G-P algorithm to solve the embedding dimension.
Proportional Counter array (PCa) — a new concept and its realization
Authors: Tian Xiangqi , Zhou Yi , Shao Ming , Liu Jianbei , Zhang Zhiyong , Shang Lunlin , Wu Zhexu , Wang Xu , He Siqi
Published: May 2023

In this study, we introduce a new structure of micro-pattern gaseous detector, named
proportional counter array (PCa). The standard Printed Circuit Board (PCB) process, which is
cost-effective and easy to scale up, is used to manufacture the PCa prototypes. Both simulation
and experimental studies were performed to characterise the prototypes, which demonstrated
promising performance in terms of gas gain, rate capability, and ion backflow suppression. The
prospects of the PCa technology are also discussed.
Therapeutic hyperthermia regulates complement C3 activation and suppresses tumor development through HSPA5/NFκB/CD55 pathway in nasopharyngeal carcinoma
Authors: Chen Chengcong , Ren Anbang , Yi Qi , Cai Jiazuo , Khan Muhammad , Lin Yunen , Huang Zhong , Lin Jie , Zhang Jian , Liu Wei , Xu Anan , Tian Yunhong , Yuan YaWei , Zheng Ronghui
Published: May 2023

Nasopharyngeal carcinoma (NPC) is endemic in Southern China and Southeast Asia. Hyperthermia is widely used in combination with chemotherapy and radiotherapy to enhance therapeutic efficacy in NPC treatment, but the underlying anti-tumor mechanisms of hyperthermia remain unclear. Complement C3 has been reported to participate in the activation of immune system in the tumor microenvironment, leading to tumor growth inhibition. In this study, we aimed to explore the effect and mechanisms of hyperthermia and investigate the functional role of complement C3 in NPC hyperthermia therapy (HT). The serum levels of complement C3 before and after hyperthermia therapy in patients with NPC were analyzed. NPC cell lines SUNE1 and HONE1 were used for in vitro experiment to evaluate the function of complement C3 and HT on cell proliferation and apoptosis. SUNE1 xenograft mouse model was established and tumor-bearing mice were treated in water bath at a constant temperature of 43°C. Tumor samples were collected at different time points to verify the expression of complement C3 by immunohistochemical staining and western blot. The differential expressed genes after hyperthermia were analyzed by using RNA sequencing. We found that complement could enhance hyperthermia effect on suppressing proliferation and promoting apoptosis of tumor cells in NPC. Hyperthermia decreased the mRNA expression of complement C3 in tumor cells, but promoted the aggregation and activation circulating C3 in NPC tumor tissue. By using in vitro hyperthermia-treated NPC cell lines and SUNE1 xenograft tumor-bearing mice, we found that the expression of heat shock protein 5 (HSPA5) was significantly upregulated. Knockdown of HSPA5 abrogated the anti-tumor effect of hyperthermia. Moreover, we demonstrated that hyperthermia downregulated CD55 expression via HSPA5/NFκB (P65) signaling and activated complement cascade. Our findings suggest that therapeutic hyperthermia regulates complement C3 activation and suppresses tumor development via HSPA5/NFκB/CD55 pathway in NPC.
Impact of Biotin Supplementation on Human Chorionic Gonadotropin Immunoassays Utilizing Biotin-Streptavidin Binding Methods in Urine
Authors: Goodrum Jenna M , Nair Vinod S , Moore Chad , Crouch Andre K , Eichner Daniel , Miller Geoffrey D
Published: May 2023

Background

Human chorionic gonadotropin (hCG) detection is indicative of pregnancy and can be indicative of some forms of cancerous tumors. The hCG drug itself, however, is a performance enhancing substance used by male athletes to increase testosterone production. Antidoping testing for hCG is conducted in urine, often on immunoanalyzer platforms, many of which utilize biotin-streptavidin dependent immunoassays in which the presence of biotin in samples is a known confounding factor. While biotin interference in serum has been well-studied, the extent of biotin interference in urine has not.

Methods

Ten active male individuals underwent a 2-week hCG administration protocol concurrent with supplementation with biotin (20 mg/day) or placebo. Urine and serum samples were collected throughout the study and analyzed for hCG and biotin concentrations.

Results

Urinary biotin levels in the hCG + biotin group increased 500-fold over baseline and 29-fold over corresponding serum biotin levels after biotin supplementation. When using a biotin-dependent immunoassay, the hCG + placebo group produced hCG-positive results (hCG ≥ 5 mIU/mL) in 71% of urine samples, while the hCG + biotin group produced positive results in only 19% of samples. Both groups had elevated hCG values in serum measurements by a biotin-dependent immunoassay and in urine when using a biotin-independent immunoassay. Urinary hCG measurements and biotin levels from the hCG + biotin group showed a negative correlation (Spearman r = −0.46, P < 0.0001) when measured using a biotin-dependent immunoassay.

Conclusions

Biotin supplementation can severely suppress urinary hCG values in assays utilizing biotin-streptavidin binding methods and therefore these types of assays are not recommended for use in urine samples containing high levels of biotin.

Clinicaltrials.gov Registration Number: NCT05450900
Stroke disease–specific quality of life trajectories and their associations with caregivers’ anxiety, depression, and burden in stroke population: a longitudinal, multicentre study
Authors: Bartoli Davide , Brugnera Agostino , Grego Andrea , Alvaro Rosaria , Vellone Ercole , Pucciarelli Gianluca
Published: May 2023

Aims

The aims of this study were to: (i) test if there are clusters of stroke survivors who experience distinct trajectories of quality of life (QOL) from hospital rehabilitation discharge to 12-month follow-up; (ii) test if any sociodemographic or clinical variables predict this class membership; and (iii) examine the associations between the clusters of stroke survivors’ and their caregivers’ trajectories of anxiety, depression, and burden over time.

Methods and results

A total of 415 stroke survivors and their caregivers were recruited in Italy for this 1-year, longitudinal, multicentre prospective study, filling out a survey at five time points. We found two distinct trajectories of change in stroke survivors’ psychological QOL (i.e. Memory, Communication, Emotion, and Participation). The first trajectory (86% of the survivors) included those who started with greater levels of QOL and improved slightly to markedly in all psychological domains, while the second trajectory (14% of the survivors) comprised those who started with lower overall levels of psychological QOL and experienced a worsening or no changes at all in these dimensions up to 12-month follow-up. Very few clinical and sociodemographic variables at baseline predicted class membership. Finally, caregivers of those patients who experienced no change or a worsening in psychological QOL reported greater distress and burden over time.

Conclusion

Our results highlight the need for more tailored interventions to improve patients’ psychological QOL and consequently their caregivers’ well-being. This requires a shift from a stroke survivor–centred approach to a stroke survivor– and caregiver-centred one.
Genetic characteristics of platinum-sensitive ovarian clear cell carcinoma
Authors: Saito Ryosuke , Kuroda Takafumi , Yoshida Hiroshi , Sudo Kazuki , Saito Motoaki , Tanabe Hiroshi , Takano Hirokuni , Yamada Kyosuke , Kiyokawa Takako , Yonemori Kan , Kato Tomoyasu , Okamoto Aikou , Kohno Takashi
Published: May 2023

Objective

Most ovarian clear cell carcinomas are resistant to platinum-based chemotherapy, while a small subset shows a positive response. The aim of this study was to clarify the clinical, pathological and genetic characteristics of platinum-sensitive ovarian clear cell carcinomas.

Methods

The study included 53 patients with stage III–IV ovarian clear cell carcinoma who had residual tumours after primary surgery and received platinum-based therapy between 2009 and 2018. A retrospective examination of platinum sensitivity was performed using the criterion of ≥6 months from the last day of first-line platinum therapy until recurrence/progression. Cases determined to be platinum-sensitive were subjected to immunohistochemical staining, genomic analyses using target sequencing (i.e. NCC Oncopanel) and homologous recombination deficiency (myChoice® HRD Plus) assays.

Results

Of the 53 stage III–IV ovarian clear cell carcinoma cases, 11 (21%) were platinum-sensitive. These cases showed better progression-free and overall survival than platinum-resistant cases (hazard ratio = 0.16, P < 0.001). Among the seven sensitive cases whose tumour tissues were available for molecular profiling, five were pure ovarian clear cell carcinoma based on pathological and genetic features, whereas the remaining two cases were re-diagnosed as high-grade serous ovarian carcinoma. The pure ovarian clear cell carcinomas lacked BRCA1 and BRCA2 mutations, consistent with the absence of the homologous recombination deficiency phenotype, whereas two cases (40%) had ATM mutations. By contrast, the two high-grade serous ovarian carcinoma cases had BRCA1 or BRCA2 mutations associated with the homologous recombination deficiency phenotype.

Conclusion

The subset of platinum-sensitive ovarian clear cell carcinomas includes a majority with pure ovarian clear cell carcinoma features that lack the homologous recombination deficiency phenotype.
Protocol for the systematic review and network meta-analysis of open versus video-assisted and robotic-assisted thymectomy for the treatment of thymic neoplasms
Authors: Huo Bright , Lee Yung , Kontouli Katerina-Maria , Patel Pooja , Yang Kevin , Jong Audrey , Coyle Kassandra , French Daniel G , Wallace Alison M , Plourde Madelaine
Published: May 2023

The surgical management of thymic neoplasms includes open and minimally invasive approaches. Previous studies have compared these techniques, but application in practice remains varied. This systematic review and network meta-analysis (NMA) will adhere to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) checklist. MEDLINE, Embase, Cochrane Centrale and Scopus will be searched from inception to perform a systematic review, NMA and evidence appraisal using the Grading of Recommendations Assessment, Development and Evaluations and the Confidence in Network Meta-Analysis methodologies. Randomized controlled trials and cohort studies will be included. Full texts of any citation will be included if they assessed a minimum of two arms of any type of thymectomy technique, including open, video-assisted thoracoscopic surgery, or robotic-assisted thoracoscopic surgery thymectomy, for the treatment of thymic neoplasms such as thymoma, thymic carcinoma or thymic neuroendocrine tumors with or without myasthenia gravis. Studies assessing operative thymectomy techniques for benign disease will be excluded. Short- and long-term perioperative safety and oncologic outcomes will be compared between open versus video-assisted versus robotic-assisted thymectomy for the surgical management of thymic neoplasms. The Risk of Bias In Non-Randomized Studies—of Interventions tool will be used to assess the risk of bias in nonrandomized studies. We will conduct a frequentist fixed- and random-effects NMA using the graph theory approach for each outcome. Summary of odds ratios will be estimated for all dichotomous outcomes with their 95% confidence interval.
Star-forming environments in smoothed particle magnetohydrodynamics simulations I: clump extraction and properties
Authors: Wurster James , Rowan Connar
Published: May 2023

What is the nature of a star-forming clump? Observations reveal these to be chaotic environments being modified and influenced by many physical processes. However, numerical simulations often define these initial star-forming clumps to be idealized objects. In this paper, we define and analyse 109 star-forming clumps extracted from our previous low-mass star cluster simulations. To define a clump, we identify all the gas in a simulation that ever becomes bound to or accreted onto a star, then follow the gas backwards in time until it decreases to a critical density. This gas and its neighbouring gas are defined as our star-forming clump. Our clumps span a mass range of 0.15 ≲ M/M⊙ ≲ 10.2, while the density range within each clump spans 2–4 orders of magnitude. The gas density distribution is not smooth, indicating that it is highly structured. The clumps are turbulent, with no coherent rotation. Independent of the initial magnetic field strength of the parent cloud, all clumps yield a similar range of field strengths. The clump magnetic field is ordered but not reflective of the initial field geometry of the parent cloud. In general, most clump properties have a slight trend with clump mass but are independent of (or only very weakly dependent on) the properties of the parent cloud. We conclude that stars are born from a wide variety of environments and there is not a single universal star-forming clump.
Scattering transparency of clouds in exoplanet transit spectra
Authors: Jaiswal Bhavesh , Robinson Tyler D
Published: May 2023

The presence of aerosols in an exoplanet atmosphere can veil the underlying material and can lead to a flat transmission spectrum during primary transit observations. In this work, we explore forward scattering effects from supermicron-sized aerosol particles present in the atmosphere of a transiting exoplanet. We find that the impacts of forward scattering from larger aerosols can significantly impact exoplanet transits and the strength of these effects can be dependent on wavelength. In certain cloud configurations, the forward-scattered light can effectively pass through the clouds unhindered, thus rendering the clouds transparent. The dependence of the aerosol scattering properties on wavelength can then lead to a positive slope in the transit spectrum. These slopes are characteristically different from both Rayleigh and aerosol absorption slopes. As examples, we demonstrate scattering effects for both a rocky world and a hot Jupiter. In these models, the predicted spectral slopes due to forward-scattering effects can manifest in the transit spectrum at the level of ∼10–∼100 s of parts per million and, hence, could be observable with NASA’s JWST.
The Underlying Unity of Hope and Trust
Authors: Ratcliffe Matthew
Published: May 2023

This paper addresses the relationships between hope and trust. I suggest that different kinds of hope and trust relate to one another in different ways, which I conceive of in dynamic terms. I propose that the movement of hope and trust has a unifying context: the changing structure of a human life and its dependence on other people. I further argue that the most fundamental forms of hope and trust are inextricable. Together, they comprise a diffuse way of anticipating things in general, which could equally be described in terms of “faith.” This sustains a life structure upon which more specific forms of hope and trust depend.