bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the Influence of the Cavitation of the Feedwater Pump in the Nuclear Power Unit Cogeneration Mode
Authors: Gao Ning , Shao Jiaye , Geng Tao , Xing Zhaokai , Song Ze 
Published: April 2022

Abstract
This paper conducts modeling and simulation of a nuclear power cogeneration unit system, and analyzes the impact of feedwater pump cavitation through important transient conditions such as steam turbine tripping, load rejection, and feedwater pump tripping. The simulation results show that cogeneration The influence of the mode on the NPSH of the feedwater front pump is generally not large, and the NPSH of the feedwater front pump is slightly improved in all working conditions. Provide a reference for the safe and stable operation of nuclear power cogeneration units.
Optimal power flow calculation of UPFC power system based on PSAT
Authors: Hu Yuan , Wu Peng , Xing Lin , Zhang Shuai , Wang Ning , Li Yan , Zhao Penghui , Wang Shuo 
Published: April 2022

Abstract
With the continuous improvement of the accuracy of power grid equipment components, the flexible control of unified power flow controller can better improve the stability of power grid. The continuous deepening of UPFC research meets the development needs of new power systems. Simulation analysis in PSAT environment can better study the power flow calculation of UPFC. In this paper, an improved power injection model is proposed for power flow calculation, and the optimal power flow is solved by the stability of power system and the economy of power market. The ieee9 node system is modeled, and the simulation calculation method is compared with BP neural network. The results are close, which shows that the PSAT analysis has high accuracy.
Dynamic Monitoring Method of Enterprise Power Consumption Based on Energy Big Data
Authors: Guo Jiangtao , Li Yajie , Fan Mao , Ma Wanzhen 
Published: April 2022

Abstract
With the global shortage of resources and energy and the intensification of environmental pollution, the problems of energy consumption and pollution emission in the manufacturing industry have become increasingly prominent. Green development, quality improvement and efficiency increase have gradually become an important development trend of the manufacturing industry. Green manufacturing engineering must be vigorously constructed and developed. Discrete manufacturing is characterized by discontinuous processes. The manufacturing process is accompanied by a large amount of primary energy consumption and environmental emissions. Compared with process manufacturing, discrete manufacturing process control is more complex and changeable, its green development level needs to be improved, and the implementation process is more difficult. As one of the common workshops in discrete manufacturing, NC workshop has problems such as high energy consumption. Based on the above reasons, this paper takes the energy-saving optimization and energy management of discrete manufacturing enterprises as the research goal, and carries out the research on energy-saving optimization and energy management system for NC workshop. It is of great significance to reduce the energy consumption of NC workshop, improve the energy utilization efficiency, solve the pain points of many enterprise information islands and difficult to control energy consumption, and improve the green level of production process in discrete manufacturing enterprises.
Optimization of synthetic conditions of explosive emulsifier Span 80
Authors: Gu Guizhou , Zhang Tao , Jiang Linshi , Li Zheng 
Published: April 2022

Abstract
In this paper, the effects of the two-step synthesis process on the acid value, saponification value and hydroxyl value of the samples, such as the molar ratio of Span 80 sorbitol to industrial oleic acid, the amount of catalyst used in etherification and esterification stages, reaction temperature and reaction time were studied. The results showed that 200g of sorbitol and 500g of industrial oleic acid had a vacuum degree of 0.085 MPa in the etherification stage, phosphoric acid with a mass concentration of 0.5% was used as catalyst in etherification stage, and the reaction time was 2 h with a gradient temperature rise of 150 °C; for esterification stage, NaOH solution with a mass concentration of 0.6% was used as catalyst, and the gradient temperature rise formula was 220 °C, and the reaction time was 2.5 h with a final quench method to obtain high-quality Span 80 had an acid value of 1.781 mgKOH/g, a hydroxyl value of 201.136 mgKOH/g and a saponification value of 152.614 mgKOH/g, which conforms to the national standard of high quality Span 80.
Optimal design of energy-taking power supply based on AC electric field induction
Authors: Liu Hongwei , Li Yufu 
Published: April 2022

Abstract
AC electric field induction based energy extraction power supply is a new power supply method for the on-line monitoring device of transmission lines, but because of its low output power, it is difficult to meet the electricity demand of the on-line monitoring device. In order to solve this problem, a new induction electrode structure is proposed based on the theoretical analysis of the factors affecting the energy taking power, and the simulation analysis and experimental verification are carried out. The results show that the designed induction electrode can generate a displacement current of 3.35mA at 10kV voltage level, and the power output can be more than 600mW when the load resistance is greater than 5kΩ. The principle and method of this paper provide a new idea for solving the power supply problem of on-line monitoring device.
Research on Safety Evaluation Method of Hydrogen Diaphragm Compressor Based on Multi-Model Weighted Combination
Authors: Shu Yue , Liu Xiaoming , Mao Chaopeng , Yu Yang 
Published: April 2022

Abstract
By establishing a remote monitoring system for the hydrogen diaphragm compressor, the thermodynamic real-time performance parameters of the unit are obtained. Using the multi-model weighted combination method, the safety evaluation system of hydrogen diaphragm compressors is established, and the risk assessment and safety evaluation analysis of three hydrogen diaphragm compressors are carried out. The analysis and calculation results show that the three hydrogen diaphragm compressors are all within the rating range of safe operation, which verifies that the multi-model weighted combination is a high-precision unit safety evaluation method, which can be used to evaluate the safe operation status of the hydrogen diaphragm compressor, so as to ensure the long-term safe and stable operation of the pressurized equipment of the hydrogen refueling station.
Research on improved sparrow algorithm based on random walk
Authors: Xie Shaohua , He Shan , Cheng Jing 
Published: April 2022

Abstract
The optimization problem is a hot issue in today’s science and engineering research. The sparrow algorithm has the advantages of simple structure, few control parameters and high solution accuracy, and has been widely used in the research of optimization problems. Purposing at the problem that the sparrow search algorithm (SSA) can’t take into account the global and local optimization, an improved sparrow algorithm based on random walk strategy is proposed. After the sparrow search, the random walk is used to perturb the optimal sparrow to demonstrate its search-ability. At the original of the iteration, the random walk boundary is large, which is favourable to demonstrate the whole search-ability. After several iterations, the walk boundary becomes smaller, which improves the local search-ability of the best location of the algorithm. Taking the convergence speed, algorithm stability and convergence precision as evaluation indicators, the improved Sparrow Algorithm (RWSSA) is verified by 4 unimodal functions and 5 multimodal classical test functions, and compared with the traditional Sparrow algorithm. The experimental results show that the capacity of the improved sparrow algorithm based on random walk is significantly improved. At the same time, RWSSA is put into practice the power prediction problem, which checkouts the feasibility of RWSSA in actual engineering problems.
Quantum regression in dephasing phenomena
Authors: Lonigro Davide , Chruściński Dariusz 
Published: April 2022

AbstractWe investigate the validity of quantum regression for a family of quantum Hamiltonians on a multipartite system leading to phase-damping reduced dynamics. After finding necessary and sufficient conditions for the CP-divisibility of the corresponding channel, we evaluate a hierarchy of equations equivalent to the validity of quantum regression under arbitrary interventions; in particular, we find necessary conditions for a nontrivial dephasing to be compatible with quantum regression. In this framework, we study a class of dephasing-type generalized spin–boson models, investigating the existence of qubit-environment coupling functions that ensure the exact validity of quantum regression.
Petroleum system modelling of Pelotas basin, offshore Brazil using 2D basin modelling approach
Authors: Hufaizal Muhammad Zulhakim , Abidin Nor Syazwani Zainal , Firdauz Mohd Syafiq 
Published: April 2022

Abstract
The ongoing exploration activities at the Pelotas basin of Brazil uncover some missing gaps in the existing wells for hydrocarbon accumulation prediction. Therefore, there is a need to further investigate the petroleum system of the basin, especially the organic facies, variations and distributions of the effectiveness of potential source rock. The adjacent basin, Santos basin is currently producing oil and gas fields will be used as the analogs to the Pelotas Basin. The aims of this research are to justify the presence of geological elements and processes of the petroleum system of the Pelotas Basin and to evaluate the potential of hydrocarbon prospectivity for exploration and exploitation of the basin. Two – dimensional basin modelling using TemisFlow will be used in this study. Hydrocarbon generation from the Turonian and Ypresian to Bartonian source rock started during Late Eocene. Visible Hydrocarbon migration can be seen from the Hydrocarbon saturation model. Hydrocarbon migration for Turonian source rock occurred during Early Miocene while for Ypresian to Bartonian, hydrocarbon migrate during Middle Miocene. Peak hydrocarbon expulsion reached during Middle Miocene for Turonian source rock and Ypresian to Bartonian source rock. Based on modelling result, hydrocarbon accumulation can be seen in Upper slope Early Miocene Sandstone, Early Miocene turbiditic sandstone and Early Oligocene turbiditic sandstone. Hydrocarbon composition in Early Miocene turbiditic sandstone and Upper Oligocene sandstone is mainly hydrocarbon liquid while for Early Miocene sandstone, the hydrocarbon composition is mix of hydrocarbon liquid and gas. Based on the prediction of source facies distribution, thermal maturity assessment, and migration and trapping mechanism, the oil and gas pool can be proposed for the future exploration and exploitation in the Pelotas Basin, offshore Brazil.
Real time imaging of the excitation volume of a multiphoton microscope
Authors: Kumar Maity Barun , Roy Debsankar Saha , Maiti Sudipta 
Published: April 2022

Abstract
Knowledge of the excitation profile in a confocal or multiphoton microscope can improve the image resolution, e.g. by using deconvolution, pixel reassignment or adaptive optics strategies. Here we demonstrate a method by which the scanning beam can be used to place a stationary, virtual ‘guide star’ at any chosen location in the sample, during imaging. This can then be used to directly image the excitation profile. The major advantage of our easy-to-install method, compared to competing methods, is that it can work for non-descanned multiphoton microscopy, the method of choice for deep tissue or ultraviolet imaging. Our experimental results reproduce diffraction theory based calculations in a minimally-scattering sample, and provide detailed information about the aberrated excitation profile in a highly scattering sample.
Effect of slitting of carbon fiber-reinforced plastic strip on flexural properties of reinforced concrete
Authors: Kwon Ji Eun , Chae See Hyeon , Kwon Sun Min , Jeong Ye Dam , Jeong Euigyung , Kim Jongwon 
Published: April 2022

Abstract
In this study, reinforced concrete was manufactured by attaching a carbon fiber reinforced plastic (CFRP) strips to the surface of the concrete. Strips with the same total area were slitted into one, two, three, four, and six pieces and attached to the upper, lower, and side parts of the concrete. The flexural strength and fracture toughness of the reinforced concrete were investigated. As the number of slits in the strip increased, for the upper reinforcement, the flexural strength gradually increased from 7.88 MPa to 11.21 MPa; for the lower reinforcement, the flexural strength increased significantly from 7.88 MPa to 26.48 MPa and then gradually increased to 33.90 MPa; and for the side reinforcement, the flexural strength increased from 7.12 MPa to 13.96 MPa and then gradually decreased. In the adhesive fracture toughness test, the fracture toughness energy significantly increased from 142.38 J m−2 to 516.63 J m−2 as the contact area between the adhesive and the strip increased. Therefore, in reinforcing concrete using a CFRP strip, it was confirmed that the reinforcement effect was enhanced when the strip was slit and then attached.
Root and xylem anatomy varies with root length, root order, soil depth and environment in intermediate wheatgrass (Kernza®) and alfalfa
Authors: Clément Corentin , Schneider Hannah M , Dresbøll Dorte Bodin , Lynch Jonathan P , Thorup-Kristensen Kristian 
Published: April 2022

Abstract

Background and Aims
Deep roots (i.e. &gt;1 m depth) are important for crops to access water when the topsoil is dry. Root anatomy and hydraulic conductance play important roles in the uptake of soil water, particularly water located deep in the soil. We investigated whether root and xylem anatomy vary as a function of root type, order and length, or with soil depth in roots of two deep-rooted perennial crops: intermediate wheatgrass [Thinopyrum intermedium (Kernza®)] and alfalfa (Medicago sativa). We linked the expression of these anatomical traits to the plants’ capacity to take up water from deep soil layers.

Methods
Using laser ablation tomography, we compared the roots of the two crops for cortical area, number and size of metaxylem vessels, and their estimated root axial hydraulic conductance (ERAHCe). The deepest roots investigated were located at soil depths of 2.25 and at 3.5 m in the field and in rhizoboxes, respectively. Anatomical differences were characterized along 1-m-long individual roots, among root types and orders, as well as between environmental conditions.

Key Results
For both crops, a decrease in the number and diameter, or both, of metaxylem vessels along individual root segments and with soil depth in the field resulted in a decrease in ERAHCe. Alfalfa, with a greater number of metaxylem vessels per root throughout the soil profile and, on average, a 4-fold greater ERAHCe, took up more water from the deep soil layers than intermediate wheatgrass. Root anatomical traits were significantly different across root types, classes and growth conditions.

Conclusions
Root anatomical traits are important tools for the selection of crops with enhanced exploitation of deep soil water. The development and breeding of perennial crops for improved subsoil exploitation will be aided by greater understanding of root phenotypes linked to deep root growth and activity.
Female blue tits sing frequently: a sex comparison of occurrence, context, and structure of song
Authors: Sierro Javier , de Kort Selvino R , Riebel Katharina , Hartley Ian R 
Published: April 2022

AbstractIn species with mutual mate choice, we should expect adaptive signaling in both sexes. However, the role of female sexual signals is generally understudied. A case in point is female birdsong that has received considerably less attention than male song. This holds even for well-studied species such as the blue tit (Cyanistes caeruleus), an important model in evolutionary ecology. Although there have been anecdotal reports of female song from three populations, there are no quantitative studies on female song in this species. Here, we report systematic sampling from a population of individually marked blue tits over 3 years, revealing that females sang frequently throughout the sampling period. Notably, daytime singing of females occurred in functionally similar contexts as in males (agonistic, solo song, and alarm contexts) but females had lower song output than males and were not observed singing dawn song, while males showed long singing displays at dawn before copulations take place. Female and male song overlapped substantially in acoustic structure (i.e., same song types or peak frequency) but females had smaller individual song-type repertoires, shorter trills, and lower vocal consistency. Differential selection pressures related to functional differences in male and female song might explain the observed variation in acoustic structure. With the first quantitative study of female song in such a well-studied species, we hope to stimulate further investigations into the functions of female singing, especially in the Northern temperate zones where female song may have been overlooked, not only in this but perhaps in other monomorphic species.
A heterogeneous network-based method with attentive meta-path extraction for predicting drug–target interactions
Authors: Wang Hongzhun , Huang Feng , Xiong Zhankun , Zhang Wen 
Published: April 2022

Abstract
Predicting drug–target interactions (DTIs) is crucial at many phases of drug discovery and repositioning. Many computational methods based on heterogeneous networks (HNs) have proved their potential to predict DTIs by capturing extensive biological knowledge and semantic information from meta-paths. However, existing methods manually customize meta-paths, which is overly dependent on some specific expertise. Such strategy heavily limits the scalability and flexibility of these models, and even affects their predictive performance. To alleviate this limitation, we propose a novel HN-based method with attentive meta-path extraction for DTI prediction, named HampDTI, which is capable of automatically extracting useful meta-paths through a learnable attention mechanism instead of pre-definition based on domain knowledge. Specifically, by scoring multi-hop connections across various relations in the HN with each relation assigned an attention weight, HampDTI constructs a new trainable graph structure, called meta-path graph. Such meta-path graph implicitly measures the importance of every possible meta-path between drugs and targets. To enable HampDTI to extract more diverse meta-paths, we adopt a multi-channel mechanism to generate multiple meta-path graphs. Then, a graph neural network is deployed on the generated meta-path graphs to yield the multi-channel embeddings of drugs and targets. Finally, HampDTI fuses all embeddings from different channels for predicting DTIs. The meta-path graphs are optimized along with the model training such that HampDTI can adaptively extract valuable meta-paths for DTI prediction. The experiments on benchmark datasets not only show the superiority of HampDTI in DTI prediction over several baseline methods, but also, more importantly, demonstrate the effectiveness of the model discovering important meta-paths.
Imputing dropouts for single-cell RNA sequencing based on multi-objective optimization
Authors: Jin Ke , Li Bo , Yan Hong , Zhang Xiao-Fei 
Published: April 2022

AbstractMotivationSingle-cell RNA sequencing (scRNA-seq) technologies have been testified revolutionary for their promotion on the profiling of single-cell transcriptomes at single-cell resolution. Excess zeros due to various technical noises, called dropouts, will mislead downstream analyses. Therefore, it is crucial to have accurate imputation methods to address the dropout problem.ResultsIn this article, we develop a new dropout imputation method for scRNA-seq data based on multi-objective optimization. Our method is different from existing ones, which assume that the underlying data has a preconceived structure and impute the dropouts according to the information learned from such structure. We assume that the data combines three types of latent structures, including the horizontal structure (genes are similar to each other), the vertical structure (cells are similar to each other) and the low-rank structure. The combination weights and latent structures are learned using multi-objective optimization. And, the weighted average of the observed data and the imputation results learned from the three types of structures are considered as the final result. Comprehensive downstream experiments show the superiority of our method in terms of recovery of true gene expression profiles, differential expression analysis, cell clustering and cell trajectory inference.Availability and implementationThe R package is available at https://github.com/Zhangxf-ccnu/scMOO and https://zenodo.org/record/5785195. The codes to reproduce the downstream analyses in this article can be found at https://github.com/Zhangxf-ccnu/scMOO_experiments_codes and https://zenodo.org/record/5786211. The detailed list of data sets used in the present study is represented in Supplementary Table S1 in the Supplementary materials.Supplementary informationSupplementary data are available at Bioinformatics online.
Comprehensive comparison of two types of algorithm for circRNA detection from short-read RNA-Seq
Authors: Liu Hongfei , Akhatayeva Zhanerke , Pan Chuanying , Liao Mingzhi , Lan Xianyong 
Published: April 2022

AbstractMotivationCircular RNA is generally formed by the ‘back-splicing’ process between the upstream splice acceptor and the downstream donor in/not in the regulation of the corresponding RNA-binding proteins or cis-elements. Therefore, more and more software packages have been developed and they are mostly based on the identification of the back-spliced junction reads. However, recent studies developed two software tools that can detect circRNA candidates by constructing k-mer table or/and de Bruijn graph rather than reads mapping.ResultsHere, we compared the precision, sensitivity and detection efficiency between software tools based on different algorithms. Eleven representative detection tools with two types of algorithm were selected for the overall pipeline analysis of RNA-seq datasets with/without RNase R treatment in two cell lines. Precision, sensitivity, AUC, F1 score and detection efficiency metrics were assessed to compare the prediction tools. Meanwhile, the sensitivity and distribution of highly expressed circRNAs before and after RNase R treatment were also revealed by their enrichment, unaffected and depleted candidate frequencies. Eventually, we found that compared to the k-mer based tools, CIRI2 and KNIFE based on reads mapping had relatively superior and more balanced detection performance regardless of the cell line or RNase R (-/+) datasets.Availability and implementationAll predicted results and source codes can be retrieved from https://github.com/luffy563/circRNA_tools_comparison.Supplementary informationSupplementary data are available at Bioinformatics online.