bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptional analysis reveals that the intracellular lipid accumulation impairs gene expression profiles involved in insulin response-associated cardiac functionality
Authors: Dato Virginia Actis , Paz María C. , Rey Federico E. , Sánchez María C. , Llorente-Cortés Vicenta , Chiabrando Gustavo A. , Ceschin Danilo G. 
Published: April 2023

Abstract
Cardiovascular disease (CVD) is a multisystemic and multicellular pathology that is generally associated with high levels of atherogenic lipoproteins in circulation. These lipoproteins tend to be retained and modified, for example, aggregated low-density lipoprotein (aggLDL), in the extracellular matrix of different tissues, such as the vascular wall and heart. The uptake of aggLDL generates a significant increase in cholesteryl ester (CE) in these tissues. We previously found that the accumulation of CE generates alterations in the insulin response in the heart. Although the insulin response is mainly associated with the uptake and metabolism of glucose, other studies have shown that insulin would fulfill functions in this tissue, such as regulating the calcium cycle and cardiac contractility. Here, we found that aggLDL induced-lipid accumulation altered the gene expression profile involved in processes essential for cardiac functionality, including insulin response and glucose uptake (Insr, Ins1, Pik3ip1, Slc2a4 gene expression), calcium cycle (Cacna1s and Gjc2 gene expression) and calcium-dependent cardiac contractility (Myh3), and cholesterol efflux (Abca1), in HL-1 cardiomyocytes. These observations were recapitulated using an in vivo model of hypercholesterolemic ApoE-KO mice. Altogether, these results may explain the deleterious effect of lipid accumulation in the myocardium, with important implications for lipid-overloaded associated CVD.
Flash entropy search to query all mass spectral libraries in real time
Authors: Fiehn Oliver , Li Yuanyue 
Published: April 2023

Abstract
Public repositories of metabolomics mass spectra encompass more than 1 billion entries. Full dot product or entropy similarity comparisons of a single MS/MS spectrum take more than 8 hours. Flash entropy search speeds up calculations more than 10,000 times to query 1 billion spectra in less than 2 seconds, without loss in accuracy. It benefits from using multiple threads and GPU calculations. This algorithm can fully exploit large spectral libraries with little memory overhead for any mass spectrometry laboratory.
Leukoencephalomacia due to ischemic vascular accident in a Tremarctos ornatus (Spectacled bear)
Authors: Echenique Joanna V.Z. , Piva Manoela M. , Gris Anderson H. , Perosa Fernanda F. , Ribeiro Paula R. , Silva Emanoelly M. S. , Slaviero Mônica , Santos Igor R. dos , Hohendorff Raquel V. , Gomes Caroline W.C. , Sonne Luciana 
Published: April 2023

Abstract
Tremactor ornatus (Spectacled bear) are the only ursids natives of South America and are present in many Zoo collections. Neurologic diseases are not common in this species and brain injuries are linked mainly to viral diseases; however ischemic brain events are not commonly reported. The aim of this paper is to describe the clinical, gross, microscopic, and immunolabeling findings of leukoencephalomacia due to an ischemic vascular accident in a Tremactor ornatus. A captive spectacled bear presented left-sided non-ambulatory hemiparesis, and left-sided hemineglect, but without mentation impair. The animal died spontaneously. Gross findings included asymmetric bilateral friable dusky discoloration areas of malacia, sharply defined in the white matter of the forebrain right hemisphere. Lesions were observed in right parietal and temporal cortex, extending to the thalamus, striate body, and medullary body. Histologically, there was a non-hemorrhagic leukoencephalomacia, with accentuated myelin rarefaction and astrocytes proliferation embedded with Gitter cell infiltrate. Moreover, Luxol Fast Blue highlighted extensive severe myelin loss. The diagnosis was established through the clinical history along with extensive ischemic right hemisphere leukoencephalomacia. Immunohistochemistry was primordial to access repair and inflammatory lesions. To the best authors' knowledge, this is the first report of leukoencephalomacia due to ischemic vascular accident in a Tremarctos ornatus.
Optimization of financial market risk prediction system based on computer data simulation and markov chain monte carlo
Authors: Yuanfang Zhang 
Published: April 2023

Abstract
With the continuous development of the times, the business scope of the financial market is also expanding, and more and more unknown risks have emerged in the process of development, which has brought a certain impact to the financial market. The exchange rate fluctuation, interest rate and other factors related to the international financial market make financial market risk one of the important risks faced by securities companies. Therefore, securities companies need intuitive, accurate and effective quantitative management tools for financial market risk assessment to improve the overall risk management level of the company. Therefore, this paper constructs a financial market risk prediction system based on computer data simulation technology and Markov chain Monte Carlo algorithm. This system is mainly composed of three parts: financial risk management, data exchange management and background risk application services. The front end of the financial market risk prediction system is divided into risk monitoring, risk allocation, risk report, risk decision-making and system log modules according to functions. Data collection management functions mainly include data collection, data encryption, data conversion, data return and other functions. The measured results show that the system can predict the significant inflection points in most economic risks synchronously or in advance, and the forecast data shows that the financial security index has an upward trend from bottom to top. In this paper, the Markov chain Monte Carlo algorithm is introduced into the financial market, through data simulation to predict the risks of companies with economic risks, and make a small contribution to the market development.
Esterification of carboxymethyl debranched waxy corn starch, its characterization and performances
Authors: Tang Hongbo , Haohao Sun , Yanping Li , Xiaojun Liu 
Published: April 2023

Abstract
A combination of pullulanase debranching, chloroacetic acid etherification, and sodium tripolyphosphate esterification was selected for the modification of waxy corn starch (WCS) to ameliorate its properties and expand its application. The results showed that the carboxymethylation and phosphorylation were chiefly completed on the big particles. The crystalline structure of WCS was an A-type, but the crystalline structure of debranched waxy corn starch (DWCS) was a C-type. The carboxymethylation destroyed the crystal structure of DWCS. The debranching could result in the reduction of the swelling capacity of WCS, while the carboxymethylation and esterification improved the swelling capacity. The characteristic absorption peaks of carbonyl bonds at 1736.8 cm− 1 and P = O bonds at 1301.2 cm− 1 confirmed that WCS was successfully etherified and esterified. Phosphate carboxymethyl debranched waxy corn starch (PDWCS) could be used to remove Zn2+, and at suitable adsorption conditions, the removal rate of Zn2+ could reach 72.9%
Periodic solution and asymptotic behavior of the three-dimensional sixth-order Boussinesq equation in shallow water waves
Authors: Zhao Baojun , Wang Jiaxin , Dong Huanhe , Fu Lei 
Published: April 2023

Abstract
In this study, the surface wave in inviscid fluid was analyzed. Starting from Euler equation and mass conservation equation, coupled with a set of boundary conditions, the equations obtained by dimensionless method contains two parameters: amplitude parameter α and shallowness parameter β. Using double-series perturbation analysis and scale transformation, the (2+1)-dimensional sixth-order Boussinesq equation is derived for the first time. Based on the Lie group analysis, the generator and the single parameter invariant group of the new Boussinesq equation are obtained. The conservation laws of the equation are given by using the generator and the adjoint equation. Using Hirota’s bilinear method, we obtain the bilinear equation and residual equation. The existence of the residual equation shows the incomplete integrability of the Boussinesq equation. The one soliton solution and two soliton solution are obtained from the Hirota bilinear form. With the Riemann theta function θ3(φ, q), we study the periodic wave solution. When q → 0, it is proved that the periodic solution can be reduced to the one soliton solution in the limit case based on the asymptotic behavior. Finally, using the graph, it is found that the periodic wave solution can be regarded as the parallel superposition of the one soliton solution, and the effects of amplitude parameter α and shallowness parameter β on the amplitude of surface wave are analyzed.
Social determinants and exposure to intimate partner violence in women with severe acute maternal morbidity in the intensive care unit: a systematic review
Authors: Quintanilla Beatriz Paulina Ayala , Taft Angela , McDonald Susan , Pollock Wendy , Henriquez Joel Christian Roque 
Published: April 2023

Abstract
Background
Studying severe acute maternal morbidity in the intensive care unit improves our understanding of potential factors affecting maternal health.
Aim
To review evidence on maternal exposure to intimate partner violence and social determinants of health in women with severe acute maternal morbidity in the intensive care unit.
Methods
The protocol for this review was registered in PROSPERO (registration number CRD42016037492). A systematic search was performed in MEDLINE, CINAHL, ProQuest, LILACS and SciELO using the search terms “intensive care unit”, “intensive care”, “critical care” and “critically ill” in combination with “intimate partner violence”, “social determinants of health”, “severe acute maternal morbidity”, pregnancy, postpartum and other similar terms. Eligible studies were i) quantitative, ii) published in English and Spanish, iii) from 2000 to 2021, iv) with data related to intimate partner violence and/or social determinants of health, and v) investigating severe acute maternal morbidity (maternity patients treated in the intensive care unit during pregnancy, childbirth or within 42 days of pregnancy termination). Of 52,866 studies initially identified, 1087 full texts were assessed and 156 studies included. Studies were independently assessed by two reviewers for screening, revision, quality assessment and abstracted data. Studies were categorised into high/middle/low-income countries and summarised data were presented using a narrative description, due to heterogenic data as: i) exposure to intimate partner violence and ii) social determinants of health.
Results
One study assessed intimate partner violence among mothers with severe acute maternal morbidity in the intensive care unit and found that women exposed to intimate partner violence before and during pregnancy had a nearly four-fold risk of severe acute maternal morbidity requiring ICU admission. Few social determinants of health other than age were reported in most studies.
Conclusion
This review identified a significant gap in knowledge concerning intimate partner violence and social determinants of health in women with severe acute maternal morbidity in the intensive care unit, which is essential to better understand the complete picture of the maternal morbidity spectrum and reduce maternal mortality.
Biomechanical effects of sacroiliac screw selection on sacroiliac screws combined with a lumbar iliac fixation for vertical fractures of the sacrum: a biomechanical finite element analysis
Authors: Ma Yupeng , Li Yu , Hong Huanyu , Huang Tao , Lin Jiangtao , Zhao Yong , Liu Weiwei 
Published: April 2023

Abstract
[Objective] To examine the impact of altering the sacroiliac screw's position and length on the biomechanical properties of the triangle osteosynthesis used to treat unilateral vertical sacral fractures and serve as a clinical reference.
[Methods] Unilateral sacral fractures of the Denis II type were modeled using finite elements to represent Tile C pelvic ring injuries. Six sacroiliac screws combined with lumbar-iliac fixation patterns were used to fix the sacral fracture. To compare sacral stability, maximum pressure, and stress distribution after fixation of sacral fractures with each internal fixation modality.
[Results] The best vertical stability of the internal fixation model was achieved when the S1 segment was fixed with lengthened sacroiliac screws. This was followed by using normal sacroiliac screws for the S1 segment. There was no statistical difference between the vertical stability of the S1 plus S2 dual-segment fixation model and the S1-segment fixation model.The maximum pressures under a vertical force of 600 N, L5LS1 <L5NS1<L5S1S2<L5LS2<L5NS2<L5NS1S2.
[Conclusions] In unilateral vertical fracture of the sacrum (AO C3.1 DENISS II) treated with triangular osteosynthesis, using triangular jointing combined with unilateral iliolumbar fixation + sacroiliac screw fixation, it is recommended that the best vertical stability of the sacrum is obtained with a single lengthened sacroiliac screw for the S1 segment, with less maximum compression on the internal fixation. If it is not possible to apply a lengthened sacroiliac screw, it is recommended to use a plain sacroiliac screw for the S1 segment. Adding an S2 segment screw does not significantly increase the vertical stability of the sacrum.
Utilizing Variable Auto Encoder-based TDO Optimization Algorithm for Predicting Loneliness from Electrocardiogram Signals
Authors: R Bharathi Vidhya , Selvaraj Jerritta 
Published: April 2023

Abstract
Several seniors and a substantial part of the general population are living in social isolation. This frequently occurs in vulnerability, isolation, and depression, which then have a poor impact on other health-related factors. A number of health problems, including a higher risk of cardio problems, are brought on by social isolation and loneliness. Electrocardiogram (ECG) usage for mental condition recognition enables accurate determination of a person's internal representation. The electrocardiogram (ECG) signals can be thoroughly analyzed to uncover hidden data that may be helpful for the precise identification of cardiac problems. ECG time-series information typically have great dimensions and complicated componentry. Using relevant information to guide training is among the main achievements of this type of learning. An ECG signal plays a significant part in the individual body's ability to manage behavior. Furthermore, loneliness identification is crucial since it has the worse effect on the circumstances that afflict persons. This study suggested an approach for detecting loneliness from an ECG signal to use a variable auto encoder-based optimization algorithm for ESN (VAE-OESN) technique. The suggested approach consists of three phases for identifying a person's loneliness. Firstly, Undecimated Discrete Wavelet Transform (UDWT) is used to preprocess the acquired ECG data. Next, further characteristics are extracted from the precompiled signals using a variable auto encoder. For the precise categorization of loneliness in the ECG signal, a metaheuristic optimized ESN is therefore presented. The outcomes of the tests demonstrate that the suggested system with suitable ECG representations produces improved accuracy as well as performance.
Method of surface defect detection for agricultural machinery parts based on image recognition technology
Authors: Zhang Jie , Li Dan 
Published: April 2023

Abstract
At present, the large use of agricultural machinery for agricultural production has increased the efficiency of agricultural production, thus greatly improving the speed of agricultural production, and also greatly increasing the demand for agricultural machinery. Under the current market scenario, the surface quality of agricultural machinery will have a certain degree of impact on its grade pricing and competitiveness. To find product surface defects in the process of product quality control, product surface fault detection is very important in the process of product quality control. Traditional surface defects are mainly detected manually, which will lead to low efficiency and error prone. In order to solve and find the problems of surface defects and low accuracy of agricultural machinery, this paper proposes a method of inspection of surface micro defects based on image recognition technology. Canny operator is used to extract the weakness of the fault edge, and the algorithm of corrosion function is used to remove the relatively small structural elements in the image, so that the boundary becomes part of the internal contraction, complete the filling of the specified holes, connect the two points that meet the set value, on the other side, the integrity of the second image edge is defective, and complete the identification and detection of the defect section according to the defect type, Complete defect edge images can be obtained by adjusting characteristic defect behavior parameters, so as to complete defect category identification and inspection. In the simulation experiment, the proposed method can accurately detect various small defects of parts, and produce appropriate detection results.
Design of 3d animation color rendering system based on image enhancement algorithm and machine learning
Authors: Xuan Danyang 
Published: April 2023

Abstract
At present, this paper points out the color problem of 3D animation, comprehensively studies the mechanism of machine image quality degradation and the related image enhancement methods integrating multiple scene variables, and improving the image enhancement method is an important problem to be solved in the industry. One or more image quality evaluation indicators are used to extract some features of the image, maintain the consistency with the subjective perception of the human eye, build an appropriate image quality evaluation machine model, and use machine learning technology to analyze image improvement algorithm data to achieve image quality evaluation results. With the change of lighting conditions in complex scenes, the gray distribution, clarity and color reproducibility of the captured image will have a great impact. Therefore, this paper mainly takes these three attributes as the key parameters to evaluate the image quality. At this stage, computer learning technology has developed rapidly. Therefore, based on computer learning technology, 3D animation has brought great changes. It can continuously improve the rendering quality of animation, and also increase the complexity of animation program development. The 3D animation rendering engine, including cross platform, image rendering, memory management, resource management and other related technologies, provides a simple and easy-to-use interface for developers to develop graphical programs, and greatly improves the work efficiency of developers. At the same time, some mainstream 3D color systems are analyzing the architecture and modules to design and develop a set of architecture suitable for the engine. The 3D animation color rendering system designed in this paper is mainly divided into multiple modules according to different functions. In addition, this paper uses the cache memory management strategy in the memory management module, which significantly reduces the number of dynamic memory allocation, avoids the generation of memory fragments, and improves the efficiency of memory use.
Enterprise financial early warning based on improved particle swarm optimization algorithm and data mining
Authors: Ma Xiaohua 
Published: April 2023

Abstract
In the Internet era, enterprises are surrounded by massive information, and the information ability of effective organization is becoming more and more important for modern enterprise management. How to continuously dig into the economic data formed in the operation of enterprises, and then discover the intelligence with the effect of financial risk warning, has become an urgent problem to be dealt with. Sophisticated data mining techniques continue to evolve, creating a clear sense of direction for dealing with this problem. Like most collective intelligence algorithms, optimized particle swarm optimization is a typical algorithm for optimizing collective intelligence. Usually, a set of solutions is started randomly, but these solutions are also updated through continuous repetition. Therefore, this paper, aiming at this problem, has carried on a series of improvement methods, improved the particle property algorithm and analyzed the particle swarm optimization algorithm, at the same time, clarified its long time in the elimination stage and can not be applied to some problems. Therefore, how to design improved strategies for swarm intelligence algorithms, especially better particle walking algorithms and their variants, to further improve the solving quality and efficiency of such algorithms when solving complex optimization problems is also a research focus in this field.
Design of Cloud Computing Database and Tourism Intelligent Platform Based on Machine Learning
Authors: Wang Weijia 
Published: April 2023

Abstract
Analyzing data in real time or offline through machine learning has played a very positive role in making practical decisions for enterprises. Cloud computing database needs to be based on artificial intelligence under big data as the background, and cloud computing database has gradually become a new upsurge in the field of computer research. In the cloud computing database environment, users can obtain powerful computing resources and powerful storage capacity. Smartphones and mobile applications are increasingly integrated into our daily life and widely used in the tourism field, such as smart phone system navigation, hotel booking and other applications. Mobile tourism applications based on intelligent platforms are becoming an important part of contemporary tourism. However, in the face of a large amount of tourism information, such as tourism strategies, famous scenic spots and other information, the main way to obtain tourism information from these mobile travel applications is still manual search. By searching and filtering a large number of useful information, and classifying them, a mobile terminal with poor operating experience will eventually be formed, which makes users have a very bad sense of experience. In the face of a large number of data problems in the tourism system designed based on the intelligent platform, we can use the characteristics of cloud computing to deal with a large number of data problems in tourism information.