bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of discrete-frequency noise generated by a propfan at cruise
Authors: Wang Hanyi , Shan Peng 
Published: August 2024

Abstract
This study employs the specialized prediction program FODNOPPb, based on Farassat’s time-domain collapsing sphere method (Formulation 1-Sph), to calculate the discrete-frequency noise generated by the propfan model SRPF with a diameter of 0.622 m. Designed by using compressible lifting surface theory, SRPF operates at a cruising altitude of 11 km and a flight Mach number of 0.8, featuring a transonic helical-tip Mach number of 1.13. The observer point, located in the far field, moves synchronously with the airframe. The results indicate that the maximum harmonic sound pressure level of the overall noise is 107.6 dB, and the acoustic pressure waveform of the overall noise is primarily determined by the acoustic pressure waveform of the thickness noise. By the collapsing sphere method, quite a smooth shape is obtained in the sharply varying segment of the blade acoustic pressure curve, which corresponds to significant changes in the blade acoustic planforms at various observer times. This paper provides valuable insights into the low-noise design of propfans during the aerodynamic inverse design phase.
Study on the influence of hydrogen injector flow rate in hydrogen-oxygen engine thrust chamber
Authors: He Wanlin , Sun Changzheng , Zhang Ze , Zhao Hongjie , Yang Bing 
Published: August 2024

Abstract
With the rapid development of China’s aerospace industry, the numerical control processing of product shells is becoming increasingly complex and diversified. Based on the experimental data of hydrogen injector flow rate in the thrust chamber of hydrogen-oxygen engines, the experimental design method was adopted to explore the relationship between nozzle flow rate and various key influencing factors. Based on real production data, the previous conclusions were corrected and verified, thoroughly analyzing the factors affecting nozzle flow rate and successfully identifying the key influencing factors. Based on the different degrees of influence of key factors, a set of refined product production and process control plans were formulated, significantly improving the qualification rate of hydrogen nozzles and bringing substantial financial benefits.
Corrosion behavior monitoring of saturated carbonate micro droplets on the surface of X52 pipeline steel based on SVET
Authors: Pan J , Xu G T , Zhang J , Fan Z N , Liu J W 
Published: August 2024

Abstract
The CCUS pipeline transportation environment often causes pitting corrosion initiation and expansion of pipeline steel under the action of saturated carbonate micro droplets.In order to monitor the corrosiveness of corrosive micro droplets precipitated from liquid CO2 containing impurities such as water in a dense state on X52 pipeline steel, the scanning vibration electrode technology in micro area electrochemical technology was used to monitor the corrosion potential of micro droplets on the surface of X52 pipeline steel. The surface morphology evolution of micro droplet corrosion products under different corrosion times was analyzed using a 3D profilometer. The results established a structure-activity relationship between corrosion behavior and surface corrosion morphology, innovatively combining electrochemical signals with product structural parameters, and revealing the subtle corrosion process inside CO2 pipelines through simulation methods.
Innovative proposal for N2 capturing in Liquid Argon using the Li-FAU molecular Sieve
Authors: Cardoso Dilson , Segreto Ettore , Cruz Ivana , da Silva Edilene Deise , Zapelini Iago William , Gonçalves Rosembergue G. , Freitas G.S. , Caffer Ana Maria , Souza J.C. , Christovam D.S. , Mazali Italo O. , Reis Cristhiane , Assaf Elisabete , Assaf José Mansur , Soccol Renato , Bianchi Pedro , Wiederhecker Gustavo , Noriler Dirceu , dos Santos Cezar Rodrigo Aguiar , Brant Krystal , Fontes Magda , Oliveira N.F. , Correia Daniel , Frandini Heriques , Demolin Frederico , Augusto André , Doubnik Roza , Adamowski Mark , Montanari David , Alegre Thiago P.M. , Adriano Cris , Machado Ana Amélia , Pagliuso P.G. 
Published: August 2024

Abstract
In this work, we unveil the potential of nitrogen (N2) adsorption from Liquid Argon (LAr) through the molecular sieves (zeolites) Li-FAU Adsorbents. We report detailed studies about N2 gas adsorption at T = 89 K using a commercial Micromeritics ASAP-2420 equipment and N2 purification from LAr using the Purification Cryostat (PuLArC) at IFGW/Unicamp. We argue that the N2 adsorption by the Li-FAU is possible thanks to the stronger interaction of N2 with the lithium cations present in zeolite Li-FAU. In fact, the experiments performed in PuLArC have unequivocally shown that the Li-FAU adsorbent was capable of capturing N2, reducing a N2 contamination of 20–50 ppm to 0.1–1.0 ppm in 1–2 hours of circulation time in LAr for several runs.
This result demonstrated the great potential of the Li-FAU adsorbent for N2 capturing in LAr and invoke further tests of this material in larger scale LAr cryostats in order to confirm the innovative proposal of using the Li-FAU molecular sieve in replacement of Molecular Sieve 4A, currently used in LAr cryostats for neutrino experiments.
An accurate tidal peak localization method in radial arterial pulse signals based on hybrid neural networks
Authors: Chen Chao , Chen Zhendong , Luo Hongmiin , Peng Bo , Hao Yinan , Li Xinxin , Xie Haiqing 
Published: August 2024

Abstract

Background: cardiovascular diseases (CVDs) have
become the leading causes of death worldwide. Arterial stiffness and
elasticity are important indicators of cardiovascular health. Pulse
wave analysis (PWA) is essential for analyzing arterial stiffness
and elasticity, which are highly dependent on the tidal peak
(P
2). P
2 is one of the four key physiological points,
which also include percussion peaks (P
1), diastolic notches
(P
3), and diastolic peaks (P
4). P
1, P
3, and
P
4 are often local maxima or minima, facilitating their
identification via the second derivatives method, a classic
localization method for key physiological points. Classic methods
such as the second derivative method, Empirical Mode Decomposition
(EMD), and Wavelet Transform (WT), have been employed for the
extraction and analysis of the P
2. Due to individual variation
and arterial stiffness, locating the P
2 using classic methods
is particularly challenging.

Methods: we propose a hybrid neural network based on Residual
Networks (ResNet) and bidirectional Long Short-Term Memory Networks
(Bi-LSTM), successfully achieving high-precision localization of the
P
2 in radial artery pulse signals. Meanwhile, we compared our
method with the second derivative method, EMD, WT, Convolutional
Neural Networks (CNN) and the hybrid model with ResNet and LSTM.

Results: the results indicate that our proposed model
exhibits significantly higher accuracy compared to other
algorithms. Overall, MAEs and RMSEs for our proposed method are
62.60% and 58.84% on average less than those for other
algorithms. The average R
Adj
2 is 29.20% higher. The
outcomes of the efficiency evaluation suggest that the hybrid model
performs more balancedly without any significant shortcomings, which
indicates that the Bi-LSTM structure upgrades the performances of
LSTM.

Significance: our hybrid model can provide the medical field
with improved diagnostic tools and promote the development of
clinical practice and research.
Performance testing of a novel short axis photomultiplier tube for the HUNT project
Authors: Peng Yijiang , Wang Zike , Gao Bo , Tang Yiyue , Chen Mingjun , Li Kai , Ren Ling , You Xiaohao , Liu Maoyuan 
Published: August 2024

Abstract
Photomultiplier tubes (PMTs) with large-area cathodes are
increasingly being used in cosmic-ray experiments to enhance
detection efficiency. The optical modules (OMs) of the High-Energy
Underwater Neutrino Telescope (HUNT) have employed a brand new N6205
20-inch microchannel plate photomultiplier tube (MCP-PMT) developed
by the North Night Vision Science & Technology (Nanjing) Research
Institute Co. Ltd. (NNVT). In order to make the 20-inch PMT fit into
the 23-inch diameter pressure-resistant glass sphere, NNVT improved
the internal structure of PMT and shortened the height of PMT by
more than 10 cm. The first batch of these PMTs has been delivered
for preliminary research work. This paper describes a specific PMT
testing platform built for the first batch of 15 MCP-PMTs, and some
performance parameters of PMT, such as peak-to-valley ratio, TTS and
nonliniearity, are measured. The measurement results show that the
new PMT still has good performance and can meet the requirements of
HUNT project.
Nano-mediated strategy: recent advance in the application of drug delivery systems in melanoma treatment and diagnosis
Authors: Wang Yinan , Tian Yuan , Jia Liwei , Xu Shujun , Meng Xin 
Published: August 2024

Abstract
Melanoma is a common malignant tumor, with a five-year mortality rate as high as 62% in cases of metastatic melanoma according to cancer statistics (2024). In recent years, the focus of melanoma research has predominantly centered on immunotherapy and targeted therapy, grappling with challenges such as resistance and immunogenicity. The discovery of nanoparticles (NPs) has brought nano-delivery systems to the forefront of melanoma diagnosis and treatment. Although certain NPs, like liposomes, have gained clinical approval, utilizing most nano-delivery systems for melanoma diagnosis and treatment remains largely exploratory. The inherent limitations of NPs present a major obstacle to their clinical translation. By selecting suitable nanocarriers and functionalizing NPs to optimize nano-delivery systems, and combining these systems with other therapies, it is possible to reduce the systemic toxicity and resistance associated with conventional therapies and the NPs themselves. This optimization could significantly improve the effectiveness of nano-delivery systems in the early detection and timely treatment of melanoma. However, there have been few reviews on the optimization of NPs and the combined application of other therapies in the treatment and diagnostic application of melanoma in the past three years. This review summarizes the latest applications of nano-delivery systems in the diagnosis and treatment of melanoma over the past three years, including innovations and achievements in both preclinical and clinical studies, offering new perspectives on their potential and future application prospects. It integrates clinical data and patent information, highlights trends in nano-delivery system development, and offers new insights into their clinical translation. Additionally, it discusses the challenges and opportunities of nano-delivery systems in melanoma treatment, providing a foundation for advancing their application in diagnosis, treatment, and clinical translation.
Constraint based Bayesian optimization of bioink precursor: a machine learning framework
Authors: Xu Yihao , Sarah Rokeya , Habib Ahasan , Liu Yongmin , Khoda Bashir 
Published: August 2024

Abstract
Current research practice for optimizing bioink involves exhaustive experimentation with multi-material composition for determining the printability, shape fidelity and biocompatibility. Predicting bioink properties can be beneficial to the research community but is a challenging task due to the non-Newtonian behavior in complex composition. Existing models such as Cross model become inadequate for predicting the viscosity for heterogeneous composition of bioinks. In this paper, we utilize a machine learning framework to accurately predict the viscosity of heterogeneous bioink compositions, aiming to enhance extrusion-based bioprinting techniques. Utilizing Bayesian optimization (BO), our strategy leverages a limited dataset to inform our model. This is a technique especially useful of the typically sparse data in this domain. Moreover, we have also developed a mask technique that can handle complex constraints, informed by domain expertise, to define the feasible parameter space for the components of the bioink and their interactions. Our proposed method is focused on predicting the intrinsic factor (e.g. viscosity) of the bioink precursor which is tied to the extrinsic property (e.g. cell viability) through the mask function. Through the optimization of the hyperparameter, we strike a balance between exploration of new possibilities and exploitation of known data, a balance crucial for refining our acquisition function. This function then guides the selection of subsequent sampling points within the defined viable space and the process continues until convergence is achieved, indicating that the model has sufficiently explored the parameter space and identified the optimal or near-optimal solutions. Employing this AI-guided BO framework, we have developed, tested, and validated a surrogate model for determining the viscosity of heterogeneous bioink compositions. This data-driven approach significantly reduces the experimental workload required to identify bioink compositions conducive to functional tissue growth. It not only streamlines the process of finding the optimal bioink compositions from a vast array of heterogeneous options but also offers a promising avenue for accelerating advancements in tissue engineering by minimizing the need for extensive experimental trials.
Liquid-phase exfoliated 2D materials for lithium-ion battery anode: current status and future direction
Authors: Li Ziyu , Liu Xuefeng , Xu Ke , Xie Qiao , Li Yage , Zhang Haijun , Zhang Shaowei , Lei Wen 
Published: August 2024

Abstract
With the increasing need for energy and the swift advancement of the electric vehicle industry, the field of energy storage has garnered significant attention. Especially, lithium-ion batteries (LIBs) serve as crucial energy storage devices and have received particular attention. As an emerging class of electrode materials, two-dimensional (2D) materials have become promising candidates for solving the challenges of LIBs owing to their high theoretical capacity, high specific surface area, high ionic conductivity, and long cycle life. The research progress on 2D materials, especially those prepared through liquid-phase exfoliation (LPE), has shown great potential in improving the performance of LIBs. LPE is a powerful and efficient method for preparing 2D materials with various sizes and properties, which is suitable for practical applications. Given these, this paper underscores the great potential of 2D materials prepared via LPE as anode materials for LIBs. Meanwhile, the existence of challenges that need to be overcome in relation to the scalability of the LPE method and the use of 2D materials in practical applications are also proposed.
Effect of tempering process on the mechanical properties and corrosion resistance of E690 marine steel
Authors: Liu Zhimin , Fu Kuijun , Xu Zhen , Wang Jiaji , Zhao Ming , Wang Dong 
Published: August 2024

Abstract
To accurately replicate actual production and save production costs, this study examines the influence of the tempering process on the structure, mechanical properties, and corrosion resistance of E690 marine steel. Various techniques were employed to evaluate its properties, behavior, and performance, including metallurgical microscopy, scanning electron microscopy, transmission electron microscopy, electron backscatter diffraction, impact experiments, tensile tests, and electrochemical corrosion tests. The results indicate that as the tempering temperature increases, the tempering degree of the tempered martensite structure improves, the martensite strip coarsens, the size of the precipitated carbide increases, and the proportion of large-angle grain boundaries decreases. Consequently, the tensile strength and yield strength initially increase and then decrease, while the impact toughness and elongation gradually improve. At a tempering temperature of 600 °C, the steel exhibits the best overall mechanical properties, with a tensile strength of 729 MPa, yield strength of 649 MPa, and elongation of 18%. Furthermore, at a tempering temperature of 550 °C, the test steel shows an optimal corrosion resistance, with a corrosion rate of 0.03233 mm y−1 and an open-circuit potential of −0.36 V.
Study on plasma expansion model of primary discharge on spacecraft solar array
Authors: WEI 尉 Dejie 德杰 , (武建文) Jianwen WU , ZHU 朱 Liying 立颖 
Published: August 2024

Abstract
In the space plasma environment, primary discharge may occur on the solar array and evolve into a destructive sustained arc, which threatens the safe operation of the spacecraft. Based on the plasma expansion fluid theory, a new multicomponent plasma expansion model is proposed in this study, which takes into account the effects of ion species, ion number, initial discharge current, and Low Earth Orbit (LEO) plasma environment. The expansion simulation of single-component and multicomponent ions is carried out respectively, and the variations of plasma number density, expansion distance, and speed during the expansion process are obtained. Compared with the experimental results, the evolution of propagation distance and speed is closed and the error is within a reasonable range, which verifies the validity and rationality of the model. The propagation characteristics of the primary discharge on the solar array surface and the influence of the initial value on the maximum propagation distance and the propagation current peaks are investigated. This study can provide important theoretical support for the propagation and evolution of the primary discharge and the key behavior of the transition to secondary discharge on spacecraft solar array.
A short-term wind speed prediction method based on the IDBO-BPNN
Authors: Wang Lingzhi , Li Cheng , Li Chenyang , Zhao Ling 
Published: August 2024

Abstract
Wind energy is known for its uncertainty and volatility, necessitating accurate wind speed prediction for stable wind farm operations. To enhance wind speed prediction accuracy, this study proposes a BP neural network (BPNN) short-term wind speed prediction model based on the Improved Dung Beetle Optimization (IDBO) algorithm. Addressing the issue of local optimization and reduced accuracy in the BPNN optimized by the Dung Beetle Optimization (DBO) algorithm, the circle chaotic mapping is utilized for population initialization to achieve a more uniform initial distribution. The improved sine-cosine algorithm, triangle wandering strategy, and adaptive weight coefficient are then employed to optimize dung beetle positions, balancing global exploration and local development capabilities and improving the algorithm’s search performance. Finally, the improved DBO algorithm optimizes the weights and thresholds of the BPNN, and the IDBO-BPNN prediction model was constructed. Simulation experiments were conducted based on wind speed data from a wind farm in Ohio, USA. The IDBO-BPNN model was compared with other prediction models, and error evaluation indexes were introduced to evaluate the experimental results. The findings demonstrate that the suggested model yields the most accurate predictions and achieves the optimal error evaluation indexes. MAE, MSE, RMSE, NSE and R2 of dataset 1 are 0.42247, 0.28775, 0.53642, 88.8785%, 89.161%, those of dataset 2 are 0.28283, 0.14952, 0.38668, 85.7383%, 86.577%, and those of dataset 3 are 0.45406, 0.39268, 0.62664, 84.3859%, 84.931%. In particular, compared with BPNN model, the five evaluation indexes of the IDBO-BPNN model promoted by 41.53%, 57.38%, 34.71%, 24.91%, and 11.44%, respectively in dataset 3. Therefore, that the proposed IDBO-BPNN model exhibits higher accuracy in short-term wind speed prediction, indicating its feasibility and superiority in the realm of wind energy.
Effect of process variables on microhardness and surface roughness in SPIF of beryllium copper
Authors: Verma Nikesh , Kumar Vikas 
Published: August 2024

Abstract
Beryllium copper is gaining the popularity among material research community owing to its excellent properties like high strength-to-weight ratio, corrosion resistance, and high electrical conductivity. This work aims to enhance the performance of ‘Single Point Incremental Forming (SPIF)’ of Beryllium copper using desirability function analysis (DFA). Feed rate (FEED), Step size (SS), wall angle (WA), and tool rotation speed (TRPM) are the four vital input parameters that have been chosen. This research investigates the effects of variations in these four factors on the truncated cone’s surface roughness and microhardness. After testing different levels of these parameters, the optimal setting using desirability function analysis was 0.4 mm step size, 200 mm min−1 feed rate, 47° wall angle, and a tool rotation speed of 1500 rpm with desirability of 70.7%. Further, measured data was subjected to Analysis of Variance (ANOVA) tests to determine the significance of all parameters on the responses. Results of the ANOVA analysis showed that the step size and tool rotation speed had the most profound impact on surface roughness and micro-hardness respectively. Feed rate and wall angle were the least significant parameters in affecting the surface roughness and micro-hardness respectively. The confirmation experiments validated fine-tuning with predicted and experimental values.
Material me
Authors: Gerrans Philip 
Published: August 2024

Abstract
Self awareness is at heart a form of bodily awareness. But self awareness is not identical to bodily awareness. Pain is a good example. Pain is not experienced as a simple signal of bodily damage. Rather the experience of pain is an emergent product of sensorimotor, interoceptive, emotional and higher cognitive processing integrated to deal with a signal of damage or threat. This explains patterns of overlapping activity between neural substrates of self awareness, affect, and interoceptive/nociceptive experience. Self awareness arise in the process of integration which is why as Wittgenstein among others observed pain is intimately and insistently experienced as “mine”. Rather the insula cortex serves as a crucial relay station in the integration of interoception, sensorimotor regulation, cognition and control. The feeling that I am the subject of bodily and affective experience is an emergent result of patterned activity across a distributed system . This processing is anchored by the avatar: a representation of the entity that regulates the system and feels the consequences.
Alienation and identification in addiction
Authors: Gerrans Philip 
Published: August 2024

Abstract
Addiction is often explained as a loss of self-control . It is also explained as a form of brain disease. Neural adaptation accounts split the difference, arguing that addiction results from ‘hijack’ by addictive targets of mechanisms of reward prediction, habit formation, decision-making, and cognitive control. The idea that addiction is ultimately a problem of self modelling integrates the ‘brain disease’ and self control accounts. It explains the role of the insula (a hub of self modelling) in addiction and some cases of disruption of addiction following a lesion to the anterior insula cortex. Deactivation of the anterior insula can disrupt addiction by alienating the subject from her addictive tendencies. This account is consistent with neural evidence but also incorporates personal and social aspects of addiction that are opaque to neural-level explanation. The self modelling account is consistent with accounts that argue that an important aspect of addiction consists in inability to with a non-addicted future self.