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996 results on '"Zhang, Yibin"'

106. Development of a Fluorescence-based Sensor based on 1,8-naphthalimide for Highly Sensitive Detection of Phosgene

Author

Zhang, Yibin, primary, Qiu, Xianyu, additional, Sun, Lin, additional, Wang, Boling, additional, Rong, Xiaoqian, additional, Liu, Jie, additional, Jun, Liu, additional, Wei, Gao, additional, Wang, Haiping, additional, Wang, Chen, additional, Gao, Wanxia, additional, Liu, Wei, additional, Shu, Xiji, additional, and Shang, Jinting, additional

Published
2023
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108. Concentrating solutions for a planar elliptic problem with large nonlinear exponent and Robin boundary condition

Author

Zhang Yibin and Shi Lei

Subjects
concentrating solutions, large exponent, robin boundary condition, finite-dimensional reduction, primary 35j25, secondary 35b25, 35b38, Analysis, QA299.6-433
Abstract

Let Ω ⊂ ℝ2 be a bounded domain with smooth boundary and b(x) > 0 a smooth function defined on ∂Ω. We study the following Robin boundary value problem:

Published
2019
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123. Proactive Safety Analysis Using Roadside LiDAR Based Vehicle Trajectory Data: A Study of Rear-End Crashes

Author

Bhattarai, Nischal, Zhang, Yibin, Liu, Hongchao, Pakzad, Yaser, and Xu, Hao

Abstract

This paper presents a methodology to detect rear-end conflicts at signalized intersections with the help of roadside LiDAR sensors. Raw data collected in the point cloud format from the sensors was processed using a series of data processing algorithms to obtain vehicle trajectories. Time-based (MTTC), deceleration-based (SDI), and severity-based (CSI) surrogate safety indices were calculated from the vehicle trajectories to identify the conflict threats at every frame of the dataset, which were further aggregated together to evaluate the risk exposure and risk severity at different temporal segments of the leader/follower car-following period to obtain a rear-end conflict index. The identified conflicts were compared with the historical crash records using negative binomial models. The results indicate correlation between the identified conflicts and the crashes, and further provide new information about the rear-end crash risks at the intersection which could support the proactive approach of traffic safety analysis.

Published
2024
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125. Concentrating solutions for an anisotropic planar elliptic Neumann problem with Hardy-Hénon weight and large exponent

Author

Zhang, Yibin

Subjects
Applied Mathematics, FOS: Mathematics, Analysis, Analysis of PDEs (math.AP)
Abstract

Let $Ω$ be a bounded domain in $\mathbb{R}^2$ with smooth boundary, we study the following anisotropic elliptic Neumann problem with Hardy-Hénon weight $$ \begin{cases} -\nabla(a(x)\nabla u)+a(x)u=a(x)|x-q|^{2α}u^p,\,\,\,\, u>0\,\,\,\,\, \textrm{in}\,\,\,\,\, Ω,\\[2mm] \frac{\partial u}{\partialν}=0\,\, \qquad\quad\qquad\qquad\qquad \qquad\qquad\qquad\qquad \,\ \ \,\,\,\, \textrm{on}\,\,\, \partialΩ, \end{cases} $$ where $ν$ denotes the outer unit normal vector to $\partialΩ$, $q\in\overlineΩ$, $α\in(-1,+\infty)\setminus\mathbb{N}$, $p>1$ is a large exponent and $a(x)$ is a positive smooth function. We investigate the effect of the interaction between anisotropic coefficient $a(x)$ and singular source $q$ on the existence of concentrating solutions. We show that if $q\inΩ$ is a strict local maximum point of $a(x)$, there exists a family of positive solutions with arbitrarily many interior spikes accumulating to $q$; while if $q\in\partialΩ$ is a strict local maximum point of $a(x)$ and satisfies $\langle\nabla a(q),\,ν(q)\rangle=0$, such a problem has a family of positive solutions with arbitrarily many mixed interior and boundary spikes accumulating to $q$. In particular, we find that concentration at singular source $q$ is always possible whether $q\in\overlineΩ$ is an isolated local maximum point of $a(x)$ or not., This manuscript has been accepted for publication in Topological Methods in Nonlinear Analysis(TMNA). arXiv admin note: text overlap with arXiv:1904.02936

Published
2022

126. FRA MISTRIVSEL TIL RESILIENS I ET DIGITALISERET ARBEJDSLIV – ET ALTERNATIVT PERSPEKTIV.

Author

Zhang, Yibin Fabricius, Lauritsen, Sannah Knutz, Villumsen, Sidsel, and Sawatzki, Dela

Abstract

Copyright of Psyke & Logos is the property of Dansk Psykologisk Forlag and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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127. Effect of e‐learning program for improving nurse knowledge and practice towards managing pressure injuries: A systematic review and meta‐analysis.

Author

Ding, Yufang, Qian, Jia, Zhou, Yuqiong, and Zhang, Yibin

Subjects
ONLINE education, MEDICAL databases, LECTURE method in teaching, NURSING, META-analysis, MEDICAL information storage & retrieval systems, CONFIDENCE intervals, PRESSURE ulcers, SYSTEMATIC reviews, HEALTH outcome assessment, NURSING practice, PSYCHOLOGY of nurses, UNDERGRADUATES, NURSES, DESCRIPTIVE statistics, MEDLINE, STATISTICAL models, RESEARCH bias, DATA analysis software, ODDS ratio, SENSITIVITY & specificity (Statistics)
Abstract

Aim: The aim of this review was to determine the effectiveness of the e‐learning programs for improving the knowledge and professional practices of nursing personnel in managing pressure injuries patients. Design: Systematic review and meta‐analysis. Methods: Systematic search was done in EMBASE, SCOPUS, Cochrane library, MEDLINE, Google Scholar, ScienceDirect and Clinicaltrials.gov databases until August 2022. Meta‐analysis was carried out using random‐effects model, and the results were reported as pooled standardized mean differences (SMD), or odds ratios (OR) with 95% confidence intervals (CIs). Results: Eight studies were included in the analysis. Most of the studies had higher risk of bias. The pooled SMD for knowledge score and for the classification skill were 1.40 (95%CI: 0.45–2.35; I2 = 93.1%) and 1.75 (95%CI: 0.94–3.24; I2 = 78.3%) respectively. The pooled OR for the classification skills was 1.75 (95%CI: 0.94–3.24; I2 = 78.3%). Patient or Public Contribution: No patient or public contribution. [ABSTRACT FROM AUTHOR]

Published
2024
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130. Controlling the Energy Relaxation: Organic Doping in AIEgenNanoparticles for Highly Enhanced Intravital Two‐Photon Imaging

Author

Fan, Miaozhuang, primary, Feng, Gang, additional, Xia, Lu, additional, Zhang, Yibin, additional, Liu, Maixian, additional, Li, Zhengzheng, additional, Jiang, Yihang, additional, Yang, Chengbin, additional, Law, Wing‐Cheung, additional, Yong, Ken‐Tye, additional, Shen, Yuanyuan, additional, Xu, Zhourui, additional, and Xu, Gaixia, additional

Published
2023
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131. Aptamer-Mediated Enrichment of Rare Circulating Fetal Nucleated Red Blood Cells for Noninvasive Prenatal Diagnosis

Author

Li, Xiaodong, primary, Wang, Tiantian, additional, Xie, Tiantian, additional, Dai, Jing, additional, Zhang, Yibin, additional, Ling, Neng, additional, Guo, Junxiao, additional, Li, Chang, additional, Sun, Xing, additional, Zhang, Xiaotian, additional, Peng, Ying, additional, Wang, Hua, additional, Peng, Tianhuan, additional, Ye, Mao, additional, and Tan, Weihong, additional

Published
2023
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136. Designing sensitive viral diagnostics with machine learning

Author

Massachusetts Institute of Technology. Department of Biological Engineering, Metsky, Hayden C, Welch, Nicole L, Pillai, Priya P, Haradhvala, Nicholas J, Rumker, Laurie, Mantena, Sreekar, Zhang, Yibin B, Yang, David K, Ackerman, Cheri M, Weller, Juliane, Blainey, Paul C, Myhrvold, Cameron, Mitzenmacher, Michael, Sabeti, Pardis C, Massachusetts Institute of Technology. Department of Biological Engineering, Metsky, Hayden C, Welch, Nicole L, Pillai, Priya P, Haradhvala, Nicholas J, Rumker, Laurie, Mantena, Sreekar, Zhang, Yibin B, Yang, David K, Ackerman, Cheri M, Weller, Juliane, Blainey, Paul C, Myhrvold, Cameron, Mitzenmacher, Michael, and Sabeti, Pardis C

Abstract

AbstractDesign of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome’s conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic–target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus’s genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT’s designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus’s variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.

Published
2023

140. Planning and Sharing Learning Designs: Cross-Cultural Use of a Learning Design Support Tool

Author

Zhang, Yibin and Laurillard, Diana

Abstract

In order to facilitate their teaching design, more teachers are beginning to engage in collective efforts, with some Chinese teachers also now sharing their resources online to plan their teaching. The learning design support tool described here (the Learning Designer), resulting from an interdisciplinary research project in the UK, provides a new form of collaboration between teachers. This paper tests the value of the tool for cross-cultural sharing of learning designs. It documents the process of a Chinese teacher who tries to represent and share his language teaching planning by using this innovative web-based prototype. The paper reflects on the issues that arise from this cross-cultural study, and the implications for the future of pedagogical innovation.

Published
2015
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141. Building a norm-referenced dataset for vocabulary assessment based on Chinese vocD and word classes

Author

Zhang, Yibin and Zhou, Jing

Abstract

Exploration of trajectories of expressive language samples is essential for understanding potential indicators for language disorder assessment. This study examined conversational language samples from 341 typically developing Mandarin-speaking children aged 3–7. Through analysis of lexical diversity and word classes, a norm-referenced dataset for vocabulary assessment was built, including indicators such as vocD and the types and tokens of nouns, verbs, measures, adverbs, conjunctions and prepositions. As norm-referenced indicators for the language development of children speaking Mandarin, these developmental data could also inform clinical therapists about the direction of intervention for children with vocabulary deficits.

Published
2024
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142. Interacting Federated and Transfer Learning-Aided CSI Prediction for Intelligent Cellular Networks

Author

Sun, Jinlong, Zhang, Yibin, Gui, Guan, Zhao, Haitao, Gacanin, Haris, and Sari, Hikmet

Abstract

To establish more intelligent cellular networks for future ubiquitous access and heterogeneous devices, we need to obtain channel state information (CSI) in a more agile and economical manner, especially for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) architectures. Unlike conventional CSI feedback or limited feedback methods, we can predict downlink CSI by leveraging channel reciprocity between uplink and downlink. The downlink CSI prediction can be formulated as a data-driven deep learning task, however, there exist isolated data silos and online adaptation problem for the offline trained neural network-based models. In this article, we propose an interacting federated and transfer learning (IFTL) based framework for downlink CSI prediction and online update, where several factors including asynchrony of different clients are considered, and light heterogeneity of diverse cells can be tolerated. Both model-level and link-level simulations are conducted under standardized FDD massive MIMO scenarios. The results outline promising prospect and potential of the utilization of federated learning and transfer learning in physical layer of wireless communications.

Published
2023
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143. Origin-Destination-Based Travel Time Reliability under Different Rainfall Intensities: An Investigation Using Open-Source Data

Author

Zhang, Qi, Chen, Hong, Liu, Hongchao, Li, Wei, and Zhang, Yibin

Subjects
Company legal issue, Rain and rainfall -- Analysis -- Usage -- Investigations -- Models, Limousine services -- Usage, Uber Technologies Inc. -- Investigations
Abstract

Origin-destination- (O-D-) based travel time reliability (TTR) is fundamental to next-generation navigation tools aiming to provide both travel time and reliability information. While previous works are mostly focused on route-based TTR and use either ad hoc data or simulation in the analyses, this study uses open-source Uber Movement and Weather Underground data to systematically analyze the impact of rainfall intensity on O-D-based travel time reliability. The authors classified three years of travel time data in downtown Boston into one hundred origin-destination pairs and integrated them with the weather data (rain). A lognormal mixture model was applied to fit travel time distributions and calculate the buffer index. The median, trimmed mean, interquartile range, and one-way analysis of variance were used for quantification of the characteristics. The study found some results that tended to agree with the previous findings in the literature, such that, in general, rain reduces the O-D-based travel time reliability, and some seemed to be unique and worthy of discussion: firstly, although in general the reduction in travel time reliability gets larger as the intensity of rainfall increases, it appears that the change is more significant when rainfall intensity changes from light to moderate but becomes fairly marginal when it changes from normal to light or from moderate to extremely intensive; secondly, regardless of normal or rainy weather, the O-D-based travel time reliability and its consistency in different O-D pairs with similar average travel time always tend to improve along with the increase of average travel time. In addition to the technical findings, this study also contributes to the state of the art by promoting the application of real-world and publicly available data in TTR analyses., Author(s): Qi Zhang [1]; Hong Chen (corresponding author) [1]; Hongchao Liu [2]; Wei Li [3]; Yibin Zhang [2] 1. Introduction Travel time reliability (TTR) plays a vital role in various [...]

Published
2020
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