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"Zhu, He"
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Modern emergency management
This book provides essential information on emergency management. It is composed of two parts, addressing the basic theory and related methods of emergency management, including risk management, coordination management, crisis management and disaster management. By putting the emphasis on interdisciplinary, systematic perspectives and building a bridge between basic knowledge and further research, it is well suited as an emergency management textbook and offers a valuable guide to prepare readers for their future emergency management careers.
Book
Measuring communities’ efficiencies within the global tourism network
Tourist flows between countries shape the global tourism network, with tightly interconnected nations forming distinct communities. These communities have significant implications for the global tourism patterns. However, existing research on tourism networks rarely provides an in-depth analysis of these communities, particularly lacking systematic and quantifiable methodologies. To address this gap, we apply complex network theory and analyze international tourist flow data from 1995 to 2021 to construct global tourism networks. Using community detection and similarity calculations, we categorize the global tourism network evolution into four distinct stages. Additionally, through theoretical deduction, we develop methods to assess the communities’ structural, performance, and functional efficiency, calculating their efficiencies to reveal evolutionary trends. Finally, utilizing a mixed-effects model, the impact of 11 indicators on community efficiencies has been examined. This study contributes to the theoretical foundation of tourism networks and offers valuable insights for global international tourism organizations.
Journal Article
Insights into the water retention behaviour of GMZ bentonite pellet mixture
Bentonite pellets are recognized as good buffer/backfill materials for sealing technological voids in high-level radioactive waste (HLW) repository. Compared to that of a traditional compacted bentonite block, one of the most important particularities of this material is the initially discrete pellets and the inevitable heterogeneous porosity formed, leading to a distinctive water retention behaviour. In this paper, water retention and mercury intrusion porosimetry (MIP) tests were conducted on pellet mixture (constant volume), single pellet (free swelling) and compacted block (constant volume) of GMZ bentonite, water retention properties and pore structure evolutions of the specimens were comparatively investigated. Results show that the water retention properties of the three specimens are almost similar to each other in the high suction range (> 10 MPa), while the water retention capacity of pellet mixture is lower than those of the compacted block and single pellet in the low suction range (< 10 MPa). Based on the capillary water retention theory (the Young–Laplace equation), a new concept ‘saturated void ratio’ that was positively related to water content and dependent on pore size distribution of the specimen was defined. Then, according to the product of saturated void ratio and water density in saturated void, differences of water retention properties for the three specimens at low suctions were explained. Meanwhile, MIP tests indicate that as suction decreases, the micro- and macrovoid ratios of pellet mixture and compacted block decrease as the mesovoid ratio increases, while all the void ratios of single pellets increase. This could be explained that upon wetting, water is successively adsorbed into the inter-layer, inter-particle and inter-pellet voids, leading to the subdivision of particles and swelling of aggregates and pellets. Under constant volume condition, aggregates and pellets tend to swell and fill into the inter-aggregates or inter-pellets voids. While under free swelling condition, the particles and aggregates in a single pellet tend to swell outward rather than squeezing into the inter-aggregate voids, leading to the expansion of the pores and even formation of cracks. Results including the effects of initial conditions (initial dry density and fabric) and constraint conditions (constant volume or free swelling) on the water retention capacity and pore structure evolution reached in this work are of great importance in designing of engineering barrier systems for the HLW repository.
Journal Article
حول (الاستعمار وكل الرجعيين نمور من ورق) /
يتناول كتاب (ماوتسي يونج) وهو صاحب سيرة طويلة عبر ما يقرب من سبعين عاما، نشأ في ريف الصين لأب فلاح فقير، استهوته الماركسية فانتمى إليها، ثم صار أحد نجومها في الحزب الشيوعي الصيني، ثم صار رئيسا للحزب، ثم استقل بعرش الصين وجلس عليه حوالي ثلاثين عاما، قاد فيها الصين برؤيته الخاصة فصنع منها دولة قوية في وقت وجيز، ولا يزال كتابه الأحمر مرجعا أساسيا للفكر الصيني والسياسة الصينية، بل إن دواوين شعره هي الأكثر مبيعا في الصين، ولا تزال سيرته مقصد كثير من المطلعين.
Book
Autonomous underwater adhesion driven by water-induced interfacial rearrangement
Underwater adhesives receive extensive attention due to their wide applications in marine explorations and various related industries. However, current adhesives still suffer from excessive water absorption and lack of spontaneity. Herein, we report an autonomous underwater adhesive based on poly(2-hydroxyethyl methacrylate-
co
-benzyl methacrylate) amphiphilic polymeric matrix swollen by hydrophobic imidazolium ionic liquid. The as-prepared adhesive is tough and flexible, showing little to none instantaneous underwater adhesion onto the PET substrate, whereas its adhesion energy on the substrate can grow more than 5 times to 458 J·m
−2
after 24 hours. More importantly, this process is entirely spontaneous, without any external pressing force. Our comprehensive studies based on experimental characterizations and molecular dynamic simulations confirm that such autonomous adhesion process is driven by water-induced rearrangement of the functional groups. It is believed that such material can provide insights into the development of next-generation smart adhesives.
The underwater adhesives developed so far usually show water adsorption and lack of spontaneity as major drawbacks. Herein, the authors develop a tough, flexible and autonomous underwater adhesive based on an amphiphilic polymeric matrix swollen by hydrophobic ionic liquid.
Journal Article
Tests of fit for the power function lognormal distribution
In this study, tests of fit for the power function lognormal distribution is considered. The probability plot, probability plot correlation coefficient, and goodness-of-fit tests—the Kolmogorov–Smirnov (KS), Cramér–von Mises (CvM), and Anderson–Darling (AD) tests are provided. Tables of critical values are presented by using simulation techniques, and the AD test outperforms KS and CvM tests based on power comparisons. Finally, to illustrate these test procedures, we fit this distribution to the data which represent the survival times of 121 breast cancer patients from one hospital.
Journal Article
The osseointegration and stability of dental implants with different surface treatments in animal models: a network meta-analysis
Dental implants are commonly used to repair missing teeth. The implant surface plays a critical role in promoting osseointegration and implant success. However, little information is available about which implant surface treatment technology best promotes osseointegration and implant stability. The aim of this network meta-analysis was to evaluate the osseointegration and stability of four commonly used dental implants (SLA, SLActive, TiUnite, and Osseotite). The protocol of the current meta-analysis is registered in PROSPERO (International Prospective Register of Systematic Reviews) under the code CRD42020190907 (
https://www.crd.york.ac.uk
). We conducted a systematic review following PRISMA and Cochrane Recommendations. Medline (PubMed), Cochrane Library, Embase, and the Web of Science databases were searched. Only randomized controlled trials were considered. Twelve studies were included in the current network meta-analysis, eleven studies were included concerning the osseointegration effect and five studies were included for stability analysis (four studies were used to assess both stability and osseointegration). Rank possibility shows that the SLActive surface best promoted bone formation at an early healing stage and TiUnite seemed to be the best surface for overall osseointegration. For stability, TiUnite seemed to be the best surface. The present network meta-analysis showed that the SLActive surface has the potential to promote osseointegration at an early stage. The TiUnite surface had the best effect on osseointegration regarding the overall healing period. The TiUnite surface also had the best effect in stability.
Journal Article
DECA: a novel multi-scale efficient channel attention module for object detection in real-life fire images
Channel attention mechanisms have attracted more and more researchers because of their generality and effectiveness in deep convolutional neural networks(DCNNs). However, the signal encoding methods of the current popular channel attention mechanisms are limited. For example, SENet uses the full-connection method to encode channel relevance, which is parameters-costly; ECANet uses 1D-Convolution to encode channel relevance, which is parameter fewer but can only encode per k adjacent channels in a fixed scale. This paper proposes a novel dilated efficient channel attention module(DECA), which consists of a novel multi-scale channel encoding method and a novel channel relevance feature fusion method. We empirically show that different scale channel relevance also contributes to performance, and fusing various scale channel relevance features can obtain more powerful channel feature representation. Besides, we widely use the weight-sharing method in the DECA module to make it more efficient. Specifically, we have applied our module to the real-life fire image detection task to evaluate its effectiveness. Extensive experiments on different backbone depths, detectors, and fire datasets have shown that the average performance boost of DECA module is more than 4.5% compare to the baselines. Meanwhile, DECA outperforms other state-of-art attention modules while keeping lower or comparable parameters in the experiments. The experimental results on different datasets also shown that the DECA module holds great generalization ability.
Journal Article