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As the complex influencing factors for financing decisions and limited information at the early project stage often render inappropriate financing mode and scheme (FMS) selection in the large-scale urban rail transit (URT) field, this study aims to identify the multiple influencing factors and establish a revised case-based reasoning (CBR) model by drawing on experience in historical URT projects to provide support for effective FMS decisions.

Our research proposes a two-phase, five-step CBR model for FMS decisions. We first establish a case database containing 116 large-scale URT projects and a multi-attribute FMS indicator system. Meanwhile, grey relational analysis (GRA), the entropy-revised G1 method and the time decay function have been employed to precisely revise the simple CBR model for selecting high-similarity cases. Then, the revised CBR model is verified by nine large-scale URT projects and a demonstration project to prove its decision accuracy and effectiveness.

We construct a similarity case indicator system of large-scale URT projects with 11 indicators across three attributes, in which local government fiscal pressure is considered the most influential indicator for FMS decision-making. Through the verification with typical URT projects, the accuracy of our revised CBR model can reach 89%. The identified high-similarity cases have been confirmed to be effective for recommending appropriate financing schemes matched with a specific financing mode.

This is the first study employing the CBR model, an artificial intelligence approach that simulates human cognition by learning from similar past experiences and cases to enhance the accuracy and reliability of FMS decisions. Based on the characteristics of the URT projects, we revise the CBR model in the case retrieval process to achieve a higher accuracy. The revised CBR model utilizes expert experience and historical information to provide a valuable auxiliary tool for guiding the relevant government departments in making systematic decisions at the early project stage with limited and ambiguous project information.

The construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.

This paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.

Without government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.

Considering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

Previous studies have produced mixed findings regarding the relationship between social networking site (SNS) use and psychological outcomes. To provide new evidence on this relationship, this study investigates the influence of SNS involvement on psychological outcomes. This study also examines the moderating role of information sharing on the link between SNS involvement and relationship quality and that between SNS involvement and social life satisfaction.

This study investigates a sample of 383 Facebook users in Vietnam. Structural equation modeling is performed to test the theoretical model and research hypotheses.

Results show that SNS involvement positively influences information sharing, relationship quality and social life satisfaction. In addition, information sharing positively affects relationship quality, which in turn is positively related to social life satisfaction. Moreover, information sharing positively moderates the link between SNS involvement and relationship quality but negatively moderates that between SNS involvement and social life satisfaction.

This study sheds a new light on the effect of SNS involvement on psychological outcomes. Specifically, the findings of this study help clarify the influence of SNS involvement on social life satisfaction. Furthermore, this study provides evidence on the moderating mechanism of information sharing on the link between SNS involvement and psychological outcomes. The findings can help SNS users and administrators make better decisions in their SNS engagement.

To provide a selective bibliography in the emerging area of library content personalization for the benefit of library and information professionals.

A range of recently published works (in the period 1993–2004), which aim to provide pragmatic application of content personalization rather than theoretical works, are discussed and sorted into “classified” sections to help library professionals understand more about the various options for formulating content as per the specific needs of their clientele.

This paper provides information about each category of tool and technique of personalization, indicating what is achieved and how particular developments can help other libraries or professionals. It recognises that personalization of library resources is a viable way of helping users deal with the information explosion, conserving their time for more productive intellectual tasks. It identifies how computer and information technology has enabled document mapping to be more efficient, especially because of the ease with which a document can be indexed and represented with multiple terms, and confirms that this same functionality can be used to represent a user's interests, facilitating the easy linking of relevant sources to prospective users. Personalization of library resources is an effective way for maximizing user benefit.

This is not an exhaustive list of developments in personalization. Rather it identifies a mix of products and solutions that are of immediate use to librarians.

A very useful source of pragmatic applications of personalization so far, that can guide a practicing professional interested in creating similar solutions for more productive information support in his/her library.

This paper fulfils an identified need for a “review of technology” for LIS practitioners and offers practical help to any professional exploring solutions similar to those outlined in this paper.

The purpose of this paper is to review available technologies, analyse their features, propose a new approach of 3D sand mould printing based on line forming, introduce the manufacturing principle and show advantages of this approach, especially for larger parts with large Z steps in the build, such as 2 mm stepwise.

This paper introduces 3D sand mould printing, compares and analyses technological process and existing fabrication approaches among available technologies first. Then, a new approach of 3D sand mould printing is proposed to improve build speed. In addition, the proposed system will be analysed or benchmarked against existing systems.

A new approach based on line forming of sand mould printing is put forward by reviewing and analysing available technologies, to improve build speed from the aspect of basic moulding movement instead of optimization of moulding methods and process parameters. The theoretical calculation and analysis shows that build speed can be improved greatly, and it is more suitable for the manufacture of large-scale casting’s sand mould when considering dimensional accuracy and printing error, as well as uniformity of each layer.

The specific implement scheme of line forming and nozzle’s specific structure of this new approach need further study.

Much higher build speed of 3D sand mould printing with new approach brings evident implication for moulds companies and manufacturing industry, having a far-reaching influence on the development of national economy.

This paper reviews available technologies and presents a new approach of 3D sand mould printing for the first time. Analysis of the new approach shows that this new method of sand mould printing can boost build speed greatly. So, its application prospect is great.

Conventional learning-based visual odometry (VO) systems usually use convolutional neural networks (CNN) to extract features, where some important context-related and attention-holding global features might be ignored. Without essential global features, VO system will be sensitive to various environmental perturbations. The purpose of this paper is to design a novel learning-based framework that aims to improve accuracy of learning-based VO without decreasing the generalization ability.

Instead of CNN, a context-gated convolution is adopted to build an end-to-end learning framework, which enables convolutional layers that dynamically capture representative local patterns and composes local features of interest under the guidance of global context. In addition, an attention mechanism module is introduced to further improve learning ability and enhance robustness and generalization ability of the VO system.

The proposed system is evaluated on the public data set KITTI and the self-collected data sets of our college building, where it shows competitive performance compared with some classical and state-of-the-art learning-based methods. Quantitative experimental results on the public data set KITTI show that compared with CNN-based VO methods, the average translational error and rotational error of all the test sequences are reduced by 45.63% and 37.22%, respectively.

The main contribution of this paper is that an end-to-end deep context gate convolutional VO system based on lightweight attention mechanism is proposed, which effectively improves the accuracy compared with other learning-based methods.

The study examines health care inequities in viral load testing among hepatitis C (HCV) antibody-positive patients. The analysis predicts whether individual and census tract sociodemographic characteristics impact the likelihood of viral load testing.

This a study of 26,218 HCV antibody-positive patients in Orange County, California, from 2010 to 2020. The case data were matched with the 2017 American Community Survey to help understand the role of neighborhood socioeconomic characteristics in testing for viral load. Multivariable logistic regression was used to predict the probability of ever testing for HCV viral load.

Thirty-six percent of antibody-positive persons were never viral load tested. The results show inequalities in viral load testing by sociodemographic factors. The following groups were less likely to ever test for viral load than their counterparts: (1) individuals under 65 years old, (2) females, (3) residents of census tracts with lower levels of health insurance enrollment, (4) residents of census tracts with lower levels of government health insurance, and (5) residents of census tracts with a higher proportion of non-white residents.

This is a secondary database from public health department reports. Using census tract data raises the issue of the ecological fallacy. Detailed medical records were not available. The results of this study emphasize the social inequality in viral load testing for HCV. These groups are less likely to be treated and cured, and may spread the disease to others.

This chapter is unique as it combines routinely collected public health department data with census tract level data to examine social inequities associated with lower rates of HCV viral load testing.

This paper aims to simulate the nanofluid forced convection in a microchannel. According to the results, at high Reynolds numbers and higher nanofluid volume fractions, an increase in the rib height and slip coefficient further improved the heat transfer rate. The ribs also affect the flow physics depending on the Reynolds number so that the slip velocity decreases with increasing the nanofluid volume fraction and rib height.

Forced heat transfer of the water–copper nanofluid is numerically studied in a two dimensional microchannel. The effects of the slip coefficient, Reynolds number, nanofluid volume fraction and rib height are investigated on the average Nusselt number, slip velocity on the microchannel wall and the performance evaluation criterion.

In contrast, the slip velocity increases with increasing the Reynolds number and slip coefficient. Afterwards, a non-parametric function estimation is performed relying on the artificial neural network.

Finally, the Genetic Algorithm was used to establish a set of optimal decision parameters for the problem

This study aims to numerically investigate the heat transfer and laminar forced and two-phase flow of Water/Cu nanofluid in a rectangular microchannel with oblique ribs with angle of attacks equal to 0-45°. This simulation was conducted in the range of Reynolds numbers of 5-120 in volume fractions of 0, 2 and 4 per cent of solid nanoparticles in three-dimensional space.

This study investigates the effect of the changes of angle of attack of rectangular rib on heat transfer and hydrodynamics of two-phase flow. This study was done in three-dimensional space and simulation was done with finite volume method. SIMPLEC algorithm and second-order discretization of equations were used to increase the accuracy of results. The usage of nanofluid, application of rips with different angles of attacks and using the two-phase mixture method is the distinction of this paper compared with other studies.

The results of this research revealed that the changing angle of attack of ribs is an effective factor in heat transfer enhancement. On the other hand, the existence of rib on the internal surfaces of a microchannel increases friction coefficient. By increasing the volume fraction of nanoparticles, due to the augmentation of fluid density and viscosity, the pressure drop increases significantly. For all of the angle of attacks studied in this paper, the maximum rate of performance evaluation criterion has been obtained in Reynolds number of 30 and the minimum amount of performance evaluation criterion was been obtained in Reynolds numbers of 5 and 120.

Many studies have been done in the field of heat transfer in ribbed microchannel. In this paper, the laminar flow in the ribbed microchannel Water/Cu nanofluid in a rectangular microchannel by using two-phase mixture method is numerically investigated with different volume fractions (0-4 per cent), Reynolds numbers (5-120) and angle of attacks of rectangular rib in the indented microchannel (0-45°).