Revised Model of Chloride Diffusion in Concrete Bridge by Considering Complex Action of Load and Chloride Binding Capacity

Coastal concrete bridges will suffer from deterioration of RC structural performance and resistance attenuation because of the chloride penetration and other environment factors. This article discusses current different chloride diffusion models and puts forward the revised model of chloride diffusion in concrete bridge by considering the complex action of load influence and chloride-binding capacity. Comparison of numerical predicted values and relative experimental tests show the presented chloride diffusion model to be more accurate. It provides a theoretical basis for the performance assessment and accurate prediction of the remaining life of highway concrete bridges

A Multiclass Cumulative Prospect Theory-Based Stochastic User Equilibrium Model with Path Constraints in Degradable Transport Networks

The limited driving range and the unavailability or insufficiency of battery charging/swapping stations cause the so-called range anxiety issue for traffic assignment involving battery electric vehicle (BEV) users. In addition, expected utility theory-based stochastic user equilibrium (EUT-SUE) model generates the perfectly rational issue when the travellers make route choice decisions. To tackle these two problems, this article improves the cumulative prospect theory-based stochastic user equilibrium (CPT-SUE) model in a degradable transport network through incorporating the constraints of multiple user classes and distance limit. In this degradable network, the travellers experience stochastic travel times due to network link capacity degradations. For this improved CPT-SUE model, the equivalent variational inequality (VI) model and associated method of successive averages (MSA) based solution are provided. The improved CPT-SUE model is tested and compared with the EUT-SUE model with distance limit, with results showing that the improved CPT-SUE model can handle jointly the range anxiety issue and the perfectly rational issue

INTERVENTION EFFECT OF THEME BUILDING BLOCK GAMES ON THE MENTAL HEALTH AND BEHAVIOR OF CHILDREN WITH ATTENTION DEFICIT HYPERACTIVITY DISORDER

Background: Children with attention deficit hyperactivity disorder (ADHD) are mainly characterized by learning difficulties, emotional impulsion, excessive activity, and distracted attention, which have a certain impact on their social ability, physical and mental health, and their living ability. This study aims to explore the effects of theme building block games on the psychological behaviors of children with ADHD, and to provide some reference for promoting the mental health development of children with ADHD. Subjects and methods: A total of 180 children with ADHD in Healthcare Center for Children from January 2020 to June 2021 were selected via convenient sampling. They were randomly divided into control (n=90) and observation (n=90) groups. Children in the control and observation groups received routine and theme building block games, respectively, once a week and a total of 8 weeks of building block game interventions. Improvement of symptoms, Eysenck Personality Questionnaire (EPQ), Achenback Child Behavior Scale List (CBLC), Child Sensory Integration Development Scale, and Piers-Harris Child Self-concept Scale (PHCSS) of two groups were compared before and after intervention. Results: After intervention, children in the two groups showed lower T scores in P and N, and higher T scores in E and L of EPQ; T scores of children in the observation group improved more significantly. Children (boys) in the two groups showed lower scores in discipline violation, hostility, compulsion, immaturity, poor communication, schizophrenia-like, and physical complaints in CBCL. Moreover, those in the observation group obtained significantly lower scores in CBCL than those in the control group. Children (girls) in the two groups showed lower scores in cruelty, aggressiveness, immaturity, depression withdrawal, schizophrenia- like, somatic complaints, and anxiety compulsion in CBCL. Meanwhile, those in the observation group obtained significantly lower scores in CBCL than those in the control group. After intervention, scores of children in the two groups in symptom improvement, sensory integration ability, and PHCSS were significantly improved. Lastly, those in the observation group obtained higher scores in these aspects compared with those in the control group. Conclusions: The theme building block game can effectively improve symptoms of children with ADHD and also help promote their sensory integration ability, self-concept, and personality development, as well as improve their psychological and behavioral status. Accordingly, this rehabilitation intervention method is worthy of promotion, which can be recognized and accepted easily

A Novel Hybrid Evaluation Method for Transfer Efficiency Assessment between Rail Transit and Public Bicycles

This paper proposes a new hybrid evaluation method including Improved Analytic Hierarchy Process (IAHP), Entropy Method (EM), and Grey Comprehensive Evaluation Method (GCEM) to assess the transfer efficiency between rail transit and public bicycles. In particular, the IAHP method that replaces the nine-scale approach with three-scale approach to naturally meet the consistency requirements is applied to qualitatively calculate the weights of evaluation indices, the EM method is utilized to calculate the weights of evaluation indices with relatively high degrees of quantification, and the GCEM method is used to calculate the transfer efficiency between rail transit and public bicycles. In addition, a three-level evaluation-index system including target level, criteria level and index level is established. A numerical example is also provided to verify the feasibility of the proposed hybrid evaluation method and explore the reasons for low transfer efficiency between rail transit and public bicycles.</p

Pricing Moving Window Parisian Option and Applications in Convertible Bonds

AbstractParisian options are complex path-dependent options developed by barrier option. Moving window Parisian options are higher path-dependent options, which are widely used in the field of convertible bonds in recent years. In this work we propose to price moving window Parisian option by use of hitting time. A simulation algorithm of the pricing is presented. As an application, we provide the pricing equations of convertible bonds with reset clause. Furthermore our simulation method is applied to price convertible bonds with reset clause using the data in China mainland stock exchange. The results show that this algorithm can undoubtedly improve the accuracy of the convertible bonds pricing

Inferring Bacterial Infiltration in Primary Colorectal Tumors From Host Whole Genome Sequencing Data

Colorectal cancer is the third most common cancer worldwide with abysmal survival, thus requiring novel therapy strategies. Numerous studies have frequently observed infiltrating bacteria within the primary tumor tissues derived from patients. These studies have implicated the relative abundance of these bacteria as a contributing factor in tumor progression. Infiltrating bacteria are believed to be among the major drivers of tumorigenesis, progression, and metastasis and, hence, promising targets for new treatments. However, measuring their abundance directly remains challenging. One potential approach is to use the unmapped reads of host whole genome sequencing (hWGS) data, which previous studies have considered as contaminants and discarded. Here, we developed rigorous bioinformatics and statistical procedures to identify tumor-infiltrating bacteria associated with colorectal cancer from such whole genome sequencing data. Our approach used the reads of whole genome sequencing data of colon adenocarcinoma tissues not mapped to the human reference genome, including unmapped paired-end read pairs and single-end reads, the mates of which were mapped. We assembled the unmapped read pairs, remapped all those reads to the collection of human microbiome reference, and then computed their relative abundance of microbes by maximum likelihood (ML) estimation. We analyzed and compared the relative abundance and diversity of infiltrating bacteria between primary tumor tissues and associated normal blood samples. Our results showed that primary tumor tissues contained far more diverse total infiltrating bacteria than normal blood samples. The relative abundance of Bacteroides fragilis, Bacteroides dorei, and Fusobacterium nucleatum was significantly higher in primary colorectal tumors. These three bacteria were among the top ten microbes in the primary tumor tissues, yet were rarely found in normal blood samples. As a validation step, most of these bacteria were also closely associated with colorectal cancer in previous studies with alternative approaches. In summary, our approach provides a new analytic technique for investigating the infiltrating bacterial community within tumor tissues. Our novel cloud-based bioinformatics and statistical pipelines to analyze the infiltrating bacteria in colorectal tumors using the unmapped reads of whole genome sequences can be freely accessed from GitHub at https://github.com/gutmicrobes/UMIB.git

LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models

Creating graphic layouts is a fundamental step in graphic designs. In this work, we present a novel generative model named LayoutDiffusion for automatic layout generation. As layout is typically represented as a sequence of discrete tokens, LayoutDiffusion models layout generation as a discrete denoising diffusion process. It learns to reverse a mild forward process, in which layouts become increasingly chaotic with the growth of forward steps and layouts in the neighboring steps do not differ too much. Designing such a mild forward process is however very challenging as layout has both categorical attributes and ordinal attributes. To tackle the challenge, we summarize three critical factors for achieving a mild forward process for the layout, i.e., legality, coordinate proximity and type disruption. Based on the factors, we propose a block-wise transition matrix coupled with a piece-wise linear noise schedule. Experiments on RICO and PubLayNet datasets show that LayoutDiffusion outperforms state-of-the-art approaches significantly. Moreover, it enables two conditional layout generation tasks in a plug-and-play manner without re-training and achieves better performance than existing methods.Comment: Accepted by ICCV2023, project page: https://layoutdiffusion.github.i

Cirrhosis Classification Based on Texture Classification of Random Features

Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM) features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage). CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM