Details Of Components Research Articles

Simultaneous Time-monitoring Observations of H2O and SiO Masers toward the Supergiant VX Sagittarii

We performed simultaneous monitoring observations of the 22.2 GHz H2O and 43.1/42.8/86.2/129.3 GHz SiO masers toward the red supergiant VX Sagittarii using the Korean VLBI Network single-dish telescopes. The observations were conducted about every 2 months from 2013 May to 2019 January (30 epochs in total). They included four optical maxima in the active phase of the optical pulsation cycles. The line profile of a H2O maser always comprised various velocity components with a wider velocity range and varied from highly redshifted to blueshifted velocities with respect to the stellar velocity, in contrast to those of the SiO masers. We examined the relation between peak intensities and velocities of 11 detailed components in the line profile of the H2O maser and the pulsation phases. The peak intensity of each component generally exhibited a better correlation with the pulsation phases than that of total intensity. The peak velocities of several components gradually decreased or increased with respect to the stellar velocity, implying an accelerating motion and the development of asymmetries in the H2O maser region. The characteristics of four transition SiO maser properties were compared according to the stellar pulsation phases. The intensity and velocity variation trend of the 43.1 GHz SiO maser was similar to that of the 42.8 GHz SiO maser. However, the variation trend of the 43.1 and 42.8 GHz SiO masers was different from that of the 86.2 and 129.3 GHz SiO masers. This difference stems from the different location of each maser reflecting a different excitation condition.

The adaptive Fourier decomposition for financial time series

This paper explores the application of the adaptive Fourier decomposition (AFD) to a deconstruction of financial time series. After the decomposition of the time series into mono-components through AFD, we reconstruct the mono-components to obtain the series’ trend and the detailed components. AFD is compared with the Empirical Mode Decomposition (EMD) and Fourier decomposition method (FDM), which could decompose time series into trends and detailed components as well. The results based on the data from stock, commodity, exchange rate, and carbon markets show that, compared to EMD and FDM, the trends extracted by AFD are more sensitive to the peaks so that they can generally track the tendencies of the financial time series better with fewer energy differences. Besides, the detailed components of AFD better reflect the structural breaks of the original time series.

A novel cell image fusion approach based on the collaboration of multilevel latent Low-Rank representation and the convolutional neural network

Multilevel cell image fusion is an image enhancement technique that improves the quality of images. The procedure of the multilevel approach follows an image decomposition and fusion strategy. The image decomposition phase partitions the medical observations into the basic (luminance and contour information) and detailed (structural information) components. Whereas the image fusion stage reconstructs the fused image from the decomposed data patterns. Recent techniques have paid more attention to the fusion of detailed components. These components contain hidden data patterns and they are fused with a well-adopted strategy. The basic components are considered less important features and they are combined with weighted sum rules. Which results in the generation of an insignificant feature map containing more detailed texture and less luminance information. We have addressed the given problem by performing the efficient fusion of sub-components. The basic components of the image are affected by blur regions and varying illuminations. These distortions are minimized by the CNN-based fusion approach. Which generates a powerful decision map by processing the features through multiple stages, which include focus map generation, binary segmentation, consistency verification, and decision map. Parallel strategies are followed for the fusion of detailed data components. These components are combined with a nuclear-norm-based fusion framework. Which is the efficient fusion policy for the combination of local structural patterns. We have evaluated the model by nine quality metrics. The performance of the proposed model is compared with state-of-art methods. It has overpowered the related techniques in qualitative and quantitative analysis.

Analyzing the engineering feasibility of the direct fusion drive

The Direct Fusion Drive (DFD) and its terrestrial counterpart, the Princeton Field Reversed Configuration (PFRC) reactor, have seen significant developments in the past decade. Various groups conducted detailed research on the required specifications of the engine and associated technology for power delivery to onboard avionics and payloads. Multiple studies have also addressed the thrust generation mechanism using empirical specific power scaling relations and plasma flow simulations. Recent studies have designed spacecraft for missions to Earth’s second Lagrange point, Mars, transneptunian bodies like Pluto, and the neighboring star systems Alpha Centauri A and B. However, significant work is needed to design the engine components in detail using scientific scaling relations and ab inito calculations to develop the physical systems for prototyping and testing. After critically analyzing the reference design of the DFD and the underlying fusion reactor, this paper addresses the technological gaps and suggests avenues to improve specifications toward targets outlined in previous studies while considering costs. Further, the authors present a prototype engine and magnetohydrodynamic power conversion system design to study the engineering hurdles relevant to the practical implementation of the DFD.

Abstract WP56: Improvement In Motor And Language Domains Mediates Most Of The Effect Of 24h NIHSS Improvement On Functional Independence

Introduction: Improvement in NIH stroke scale scores on 24h follow-up is considered a key prognostic element after endovascular thrombectomy (EVT). We aimed to evaluate the proportion of effect of 24h NIHSS improvement on mRS 0-2 at 90d mediated through improvement in motor and language domains. Methods: From SELECT study, EVT patients with detailed NIHSS components on presentation and 24h follow-up as well as complete mRS on discharge and 90d were selected. Motor improvement was defined as ≥2 point in cumulative arms and legs score or 0 score at 24h and language improvement was defined as ≥1 point in cumulative aphasia and dysarthria scores at 24h. Mediation analysis framework using 4-step method (Figure 1a) was used to evaluate the effect of 24h NIHSS improvement mediated through improvement in motor and language scores. Results: Of 192 eligible EVT patients, 176 demonstrated motor deficits and 187 demonstrated language deficits. 24h NIHSS improvement was significantly associated with mRS 0-2 (aOR:1.15[1.07-1.23], p<0.001) - step 1. 24h NIHSS improvement was also significantly associated with motor (aOR:1.77[1.48-2.12],p<0.001) and speech improvement (aOR:1.25[1.16-1.36],p<0.001) - step 2. In the full model, motor (aOR:3.00[1.07-8.46],p=0.037) and speech improvement (aOR:3.15[1.37-7.27],p=0.007) were significantly associated with mRS 0-2, whereas 24h NIHSS improvement was no longer a significant predictor (aOR:1.05[0.96-1.15],p=0.33) - step 3 of figure 1a. Motor improvement mediated 68% and speech improvement mediated 27% of the association of 24h NIHSS improvement with mRS 0-2 (Figure 1b) - step 4. Conclusions: Almost all (~95%) of the effect of 24h NIHSS improvement on functional independence (mRS 0-2) was mediated through specific improvement in motor and language domains, suggesting a large role of improvement in motor and language domains in achieving better functional independence. Further studies are needed to confirm the findings.

A dual channel decomposition and remapping fusion model for low illumination images with a wide field of view

In this paper, we investigate the problem of low illumination image enhancement under wide field of view condition. Our contribution consists of two parts: Firstly, we propose an adaptive two-parameter luminance remapping enhancement function (A2BREF) based on biological visual properties. Secondly, we propose a simple and effective noise suppression method for composite weighted map. In this paper, an image decomposition method based on the total variational energy is used to decompose the input image into structure and detail components. We apply luminance enhancement to the structure component and noise suppression to the detail component. The two components are processed in parallel without interfering with each other. First, we transform the structure component from RGB space to HSV space, and A2BREF combines the global and local luminance information of the input image to perform an adaptive luminance remapping of the V component. Then, the mapping result and the initial V component are fused with PCA in a specific order to enhance the image brightness. Secondly, the detail component contains a lot of noise and detail information of the input image. In this paper, we extract two weight maps from different stages of the detail component by means of improved adaptive Gaussian filters, and the two weight maps are combined to obtain the final weight map. After multiplying the weight maps with the initial detail components and stretching the contrast, the ideal detail components are obtained. Finally, the processed structure and detail components are combined to obtain the final result. The experimental results show that the proposed method has advantages over the contrast algorithm in terms of both subjective visual and objective metrics.

Ancient genome of Empress Ashina reveals the Northeast Asian origin of Göktürk Khanate

Ancient genome of Empress Ashina reveals the Northeast Asian origin of Göktürk Khanate

A zero‐sample state evaluation model for valve‐side bushing of UHV converter transformer oriented to digital twin under attribute analysis

AbstractThe valve‐side bushing of the UHV converter transformer is the key equipment in the DC transmission project, and its running state directly affects the security and stability of the power system. This paper analyses the attributes of the physical entities, uses the digital twins to establish the state feature set and proposes a zero‐sample state evaluation algorithm for the valve‐side bushing. First, the geometric, materials and electrical characteristics are analyzed, and the detailed components of carrier current are obtained by empirical mode decomposition. Then, COMSOL is used to establish digital twins, verify the validity of twins with axial heat distribution of bushing, and establish a state feature set with the extreme temperature inside and outside bushing. Finally, the fuzzy clustering algorithm is used to classify the state feature set, and the similarity is used as the index to realize the zero‐sample state evaluation of the valve‐side bushing. Through the demonstration and analysis of examples, the evaluation model solves the problems of difficulty in extracting the internal features, fewer fault samples, and training difficulty, which is conducive to improving the operation and maintenance management level of power transmission equipment.

Advanced Casting Techniques for Complex-Shaped Components: Design, Simulation and Process Control

The advancement of manufacturing technology has resulted in an increasing need for detailed, lightweight, and high-performance components with complicated geometries across many sectors. The emergence of advanced casting processes has been crucial in addressing these needs, as they provide the potential to manufacture components with complex geometries, enhanced mechanical characteristics, and minimised material wastage. The present study delves into the intricate domain of advanced casting processes, with a specific emphasis on the areas of design, simulation, and process control. The design of components with intricate shapes poses difficulties that conventional casting techniques encounter difficulties in surmounting. Simulation methods are crucial for accurately predicting the solidification and flow characteristics in casting processes, as this is essential for the production of components without any defects. Sophisticated simulation technologies, like as computational fluid dynamics (CFD) and finite element analysis (FEA), are utilised in advanced casting processes to model and analyse the intricate thermal and fluid dynamics phenomena that transpire during the casting process. This research provides an in-depth analysis of the role of simulations in enhancing the comprehension of solidification patterns, the identification of probable faults, and the optimisation of gating and riser designs to improve the overall quality of castings.

Mass spectrometry-based techniques for identification of compounds in milk and meat matrix.

Food including milk and meat is often viewed as the mixture of different components such as fat, protein, carbohydrates, moisture and ash, which are estimated using well-established protocols and techniques. However, with the advent of metabolomics, low-molecular weight substances, also known as metabolites, have been recognized as one of the major factors influencing the production, quality and processing. Therefore, different separation and detection techniques have been developed for the rapid, robust and reproducible separation and identification of compounds for efficient control in milk and meat production and supply chain. Mass-spectrometry based techniques such as GC-MS and LC-MS and nuclear magnetic resonance spectroscopy techniques have been proven successful in the detailed food component analysis owing to their associated benefits. Different metabolites extraction protocols, derivatization, spectra generated, data processing followed by data interpretation are the major sequential steps for these analytical techniques. This chapter deals with not only the detailed discussion of these analytical techniques but also sheds light on various applications of these analytical techniques in milk and meat products.

Watermarking System for Medical Images Using Optimization Algorithm

One of the main methods used to provide security for medical records when exchanging these records through open networks is digital watermarking. In order to preserve the privacy of patients, this system also requires a means to secure images. In this paper, a watermarking based on discrete wavelet transform (DWT), and discrete and discrete cosine transform (DCT) in cascade provides more robustness and security. DCT divides the image into low and high-frequency regions, watermarking message can be embedded into low-frequency regions to prevent distortion of the original image. DWT splits the image into four frequency coefficients; horizontal, vertical, approximation, and detailed frequency component. The judgment factors for the strength of the watermark system are robustness, invisibility, and embedded message capacity. Invisibility means transparency of the watermark logo or data in the original or host image without any distortion. Capacity data payload means the size of the embedded image which is related to the amount of data or logo size that will be embedded in the host image. Robustness refers to the capability of the watermark to stand with the host image operations. In this paper, we propose an optimizer to trade-off between robustness, invisibility, and message capacity. Three metrics were employed to assess the results achieved by the proposed approach, namely, Peak Signal-to-Noise Ratio (PSNR), Normalized Cross Correlation (NCC), and Image Fidelity (IF). The achieved results confirmed the effectiveness and superiority of the proposed approach for real-world digital watermarking applications.

Hybrid Electric with a Smart Platform Source Modeling

This paper develops how to manage and to save electric energy produced by hybrid sources. Research focuses on the detailed hybrid system component modeling. HOMER software is used for study feasibility and RETScreen software for results validation. Smart platform automatically chooses energy sources to be used by a home electric system in prioritizing renewable energy. Multi-sources system includes photovoltaic, wind turbine and generator. Switching and control between thermal and renewable energy sources are ensured by a microcontroller. Based on electric energy need, modeling can manage various energy sources by running each source independently showing its best performance. Therefore, this research allows the chosen villages to get out of blackout stress thanks to smart platform which is able to provide high availability of electricity from a hybrid system combined with battery storage.

Conception of a home-based sleep apnoea identification and monitoring system

Healthy sleep is one of the prerequisites for a good human body and brain condition, including general well-being. Unfortunately, there are several sleep disorders that can negatively affect this. One of the most common is sleep apnoea, in which breathing is impaired. Studies have shown that this disorder often remains undiagnosed. To avoid this, developing a system that can be widely used in a home environment to detect apnoea and monitor the changes once therapy has been initiated is essential. The conceptualisation of such a system is the main aim of this research. After a thorough analysis of the available literature and state of the art in this area of knowledge, a concept of the system was created, which includes the following main components: data acquisition (including two parts), storage of the data, apnoea detection algorithm, user and device management, data visualisation. The modules are interchangeable, and interfaces have been defined for data transfer, most of which operate using the MQTT protocol. System diagrams and detailed component descriptions, including signal requirements and visualisation mockups, have also been developed. The system's design includes the necessary concepts for the implementation and can be realised in a prototype in the next phase.

Total pain in advanced dementia: a quick literature review.

Objective: This quick literature review aimed to organize information on the detailed components of total pain in older people with advanced dementia in a holistic manner. Materials and Methods: The authors analyzed qualitative data from relevant clinical guidelines or textbooks, focusing on certain types of pain and distress in older people with advanced dementia, followed by an expert panel review by research team members. In the search, the authors defined a person with advanced dementia as having a functional assessment staging tool scale score greater than or equal to six. Results: The model covered a wide variety of pain, from physical pain to dementia-related psychological and spiritual aspects of total pain, including living environment change, stigma, discrimination, lack of communication and understanding, loss of sense of control and dignity, and cultural distress. It also identified physical appearance as an important factor in dying with dignity, as established by existing research on individuals with incurable cancers. Conclusion: The conceptual model of total pain in people with advanced dementia is expected to help turn healthcare professionals' attention to physical, psychological, social, and spiritual contributors to total pain in advanced dementia.

Ingarden and Blaustein on Image Consciousness

The article explores two phenomenologies of image consciousness that were formulated by Ingarden and Blaustein, both of whom were students of Husserl. Both philosophers analyze image consciousness in the context of the phenomenon of contemplating a painting. The article is divided into seven sections. Section 1 presents the historical background of Blaustein’s and Ingarden’s explorations. In Section 2, Ingarden’s description of a painting as different from an image is reconstructed. In Section 3, Ingarden’s analysis of Husserl’s image consciousness is discussed. Section 4 concerns Blaustein’s theory of intentionality, which was formulated in a critical elaboration of Husserl’s philosophy. Section 5 discusses the detailed components of Blaustein’s theory of intentionality, i.e., his theory of psychic representations. This theory is then used in Section 6 in an analysis of Blaustein’s reading of § 111 of Husserl’s Ideas I. Section 7 summarizes both theories in order to draw parallels and differences between Ingarden and Blaustein. In this regard, it is argued that both philosophers refer to different theoretical contexts when discussing Husserl’s idea of image consciousness.

스타벅스 매장의 공간구성요소에 관한 탐색적 분석

This study examined the spatial characteristics of Starbox stores through exploratory factor analysis that discovers detailed spatial components based on the spatial experience experienced by visitors to Starbucks general stores. As a result of the analysis, a total of five factors were grouped and derived, and each factor was named as ‘culture/artistry’, ‘five senses/hospitality’, ‘behavior/psychology’, ‘taste/hardware’, and ‘lead/pandemic’. Through exploratory factor analysis based on the visitor's experience, the significance of this study was able to identify the cause of continuous visits to Starbucks stores and infer detailed components related to Starbucks' third place, which shows a commercialized space but differentiated place. This is a strategic projection of Starbucks' corporate philosophy and ideology into space and place, and it is judged that this positioning is perceived and experienced by the visitor group through five senses.It is judged that these attributes will be a very important space and place strategy for commercial real estate, especially retail real estate, which requires continuous visits. As a future research topic, the factors derived through exploratory factor analysis are independent variables, and it is necessary to measure dependent variables for visitor satisfaction and revisit intention, and to analyze visitors by group to examine the differences.nalyze visitors by group to examine the differences.

중국의 소득불균형 해소를 위한 상속세제 도입 연구

Inheritance tax in China was first implemented during the Republic of China era. At that time, the Nanjing government proposed imposing an inheritance tax and enacted related ordinances, but it was not implemented.
 However, after the Anti-Japanese War broke out on July 1, 1940 and the national finances were in crisis, inheritance tax was officially imposed. 
 However, inheritance tax was proposed several times as one of the taxes imposed after the founding of New China, but all of them were postponed. 
 As the Chinese economy has grown rapidly since the reform and opening up and the gap between the rich and the poor has widened, personal income tax can no longer meet the need to adjust the income gap. As a policy tool to control this and as a way to narrow the income gap, the question of whether or not to impose inheritance tax has been revisited. It was once the people’s choice. However, considering the current situation of China’s economic level and the gap between the rich and the poor, the introduction of the inheritance tax is considered sufficient. 
 Inheritance tax also has a positive meaning in improving the national tax system, properly adjusting the distribution of wealth among members of society, increasing financial resources for the government and social welfare programs, and maintaining national income.
 Therefore, in order for China to introduce and actually implement the inheritance tax system, it is necessary to establish a theoretically desirable basic direction. In other words, it is very important to clearly establish the
 purpose pursued by the national policy and to establish the basic direction to achieve the purpose well. 
 On the other hand, when introducing the inheritance tax system, the tax conditions such as which inheritance tax method to choose, whether to separate or integrate with the gift tax, the determination of the minimum tax amount, and the tax rate should be tailored to the actual situation in China in consideration of the inheritance tax legislative principle, efficiency and fairness. You will have to decide. In addition, research on countries that are currently successfully operating the inheritance tax system and specific plans for detailed components to suit China’s situation should be established.
 This study focused on the implementation (proposal) of the Inheritance Tax Law, which was reviewed by the Chinese Ministry of Finance in 2010, and further research by experts is also required.

A suggested data structure for transparent and repeatable reporting of bibliographic searching.

Academic searching is integral to research activities: (1) searching to retrieve specific information, (2) to expand our knowledge iteratively, (3) and to collate a representative and unbiased selection of the literature. Rigorous searching methods are vital for reliable, repeatable and unbiased searches needed for these second and third forms of searches (exploratory and systematic searching, respectively) that form a core part of evidence syntheses. Despite the broad awareness of the importance of transparency in reporting search activities in evidence syntheses, the importance of searching has been highlighted only recently and has been the explicit focus of reporting guidance (PRISMA-S). Ensuring bibliographic searches are reported in a way that is transparent enough to allow for full repeatability or evaluation is challenging for a number of reasons. Here, we detail these reasons and provide for the first time a standardised data structure for transparent and comprehensive reporting of search histories. This data structure was produced by a group of international experts in informatics and library sciences. We explain how the data structure was produced and describe its components in detail. We also demonstrate its practical applicability in tools designed to support literature review authors and explain how it can help to improve interoperability across tools used to manage literature reviews. We call on the research community and developers of reference and review management tools to embrace the data structure to facilitate adequate reporting of academic searching in an effort to raise the standard of evidence syntheses globally.

Perceived Government Control and its Influence on Climate Change Knowledge and Perceptions: Applications for Effective Communication

Climate change is one of the biggest challenges facing the global agricultural food system at the current moment. While scientists agree that anthropogenic climate change is a critical issue, many United States residents remain skeptical, presenting a significant communication challenge. Understanding the factors influencing public perceptions of climate change are essential to informing agricultural and environmental communication efforts if they are to be effective at mitigating its effects. Previous studies have identified political affiliation and ideology as key predictors for climate change perceptions; however, understanding more detailed components of political ideology and affiliation could strengthen the predictive capacity of these variables. The current study explored the predictive capacity of perceptions of government control on environmental behavior related to political affiliation and ideology to inform effective communication based on climate change knowledge. Using an online survey of U.S. residents, political ideology and affiliation were found to be important predictors of climate change knowledge but including perceptions of government control on environmental behavior expanded their predictive capacity. Agricultural and environmental communicators are encouraged to integrate more nuanced components of political affiliation and ideology, such as perceptions of government control, into their messaging strategies to increase potential message uptake in the midst of a politically polarized media environment. Future research should identify and explore other aspects of political affiliation and ideology, such as economic and social factors, that may influence the public’s perception of climate change and its related policy implications.

Abstract 11972: Economic Burden of Congenital Heart Surgery in China: Results From the National Center for Cardiovascular Diseases

Introduction: According to Reports on the Prevention and Control of Birth Defects in China, the total lifelong economic burden of new congenital heart diseases (CHD) cases was more than 12.6 billion Chinese Yuan. We aim at exploring the economic burden driven by congenital heart surgery and filling the gap in the health economics in China. Methods: We used data from CDCHS database (Registry No. ChiCTR1800014577) to prospectively analyze the economic burden of congenital heart surgery. The total expenditures were divided into eleven subjects and classified by STAT category, year, and different types of CHD. Stepwise multivariable linear regression model was utilized to analyze the contributing factor to the total expenditure. National economic data was accessed to better describe the burden. Results: A total of 6568 hospitalizations were enrolled from 2018 to 2020. The median of total expenditure of all enrolled patients during hospitalization was 63,129.14 (≈9,910.52 USD), and significant cost-related difference was defined among the five STAT categories (P<0.001) with the lowest in STAT-1 (55,720.43, ≈8,747.46 USD) and highest in STAT-5 (190,587.01, ≈29,919.94 USD). The median total costs during the 3-year 2018 to 2020 period were 57,248.72 (≈8,987.38 USD), 63,423.45 (≈9,956.74 USD) and 67,867.37 (≈10,654.39 USD), respectively. Multivariable linear regression model showed that STAT category, complication, emergent operation and delay sternal closure were the major contributing factor to the total expenditure. Conclusions: For the first time, the economic burden of congenital heart surgery in China is delineated not only in terms of total expenditure but also the detail components. Also, the current healthcare policies in China were analyzed, and combined with the expenditure information, this analysis provides substantial information about specific factors driving to the economic burden with the purpose of aiding policy adjustments.