bluuebunny/crossref_metadata_2025 huggingface dataset:
About this title - The Changing Role of Geological Surveys
Authors: Hill P. R. , Lebel D. , Hitzman M. , Smelror M. , Thorleifson H.
Published: December 2020

Senior managers and Heads of Geological Survey Organizations (GSOs) from around the world have contributed a collection of papers to provide a benchmark on how GSOs are responding to national and international needs in a rapidly changing world. GSOs continue to provide key scientific information about Earth systems, natural hazards and climate change. As countries adopt sustainable development principles and the public increasingly turns to social media to find information about resource and environmental issues, the generation and communication of Earth science knowledge become increasingly important. This volume provides a snapshot of how GSOs are adapting their activities to this changing world. The different national perspectives presented converge around several common themes related to resources, environment and big data. Climate change and the UN's Sustainable Development Goals provide an increased incentive for GSOs of the world to work in harmony, to generate knowledge of Earth systems and to provide solutions for sustainable management of the planet.
Coral Probiotics: Premise, Promise, Prospects
Authors: Peixoto Raquel S. , Sweet Michael , Villela Helena D.M. , Cardoso Pedro , Thomas Torsten , Voolstra Christian R. , Høj Lone , Bourne David G.
Published: December 2020

The use of Beneficial Microorganisms for Corals (BMCs) has been proposed recently as a tool for the improvement of coral health, with knowledge in this research topic advancing rapidly. BMCs are defined as consortia of microorganisms that contribute to coral health through mechanisms that include ( a) promoting coral nutrition and growth, ( b) mitigating stress and impacts of toxic compounds, ( c) deterring pathogens, and ( d) benefiting early life-stage development. Here, we review the current proposed BMC approach and outline the studies that have proven its potential to increase coral resilience to stress. We revisit and expand the list of putative beneficial microorganisms associated with corals and their proposed mechanismsthat facilitate improved host performance. Further, we discuss the caveats and bottlenecks affecting the efficacy of BMCs and close by focusing on the next steps to facilitate application at larger scales that can improve outcomes for corals and reefs globally.
Optimal Transport in Systems and Control
Authors: Chen Yongxin , Georgiou Tryphon T. , Pavon Michele
Published: December 2020

Optimal transport began as the problem of how to efficiently redistribute goods between production and consumers and evolved into a far-reaching geometric variational framework for studying flows of distributions on metric spaces. This theory enables a class of stochastic control problems to regulate dynamical systems so as to limit uncertainty to within specified limits. Representative control examples include the landing of a spacecraft aimed probabilistically toward a target and the suppression of undesirable effects of thermal noise on resonators; in both of these examples, the goal is to regulate the flow of the distribution of the random state. A most unlikely link turned up between transport of probability distributions and a maximum entropy inference problem posed by Erwin Schrödinger, where the latter is seen as an entropy-regularized version of the former. These intertwined topics of optimal transport, stochastic control, and inference are the subject of this review, which aims to highlight connections, insights, and computational tools while touching on quadratic regulator theory and probabilistic flows in discrete spaces and networks.
The Connection Between Student Identities and Outcomes Related to Academic Persistence
Authors: Destin Mesmin , Williams Joanna Lee
Published: December 2020

Young people begin to explore and develop a deeper understanding of who they are, or their identities, during adolescence and young adulthood. The various aspects of these dynamic and developing identities guide how students navigate the world and pursue their goals, including how they engage with academic opportunities and challenges. This article uses the identity-based motivation framework to integrate a selective review of research demonstrating connections between student identities and outcomes related to academic persistence. First, a foundation of significant theoretical and empirical contributions describes how different types of identities—including future identities and social identities—influence academic persistence. Additional evidence builds upon socioecological and sociocultural perspectives to demonstrate various levels of contextual influence on student identities and outcomes related to academic persistence. The area of research has implications for the promotion of more holistic approaches to student success, health, and well-being in addition to effective goal pursuit across the life span.
Thermal Decontamination Technologies for Microorganisms and Mycotoxins in Low-Moisture Foods
Authors: Deng Li-Zhen , Sutar Parag Prakash , Mujumdar Arun S. , Tao Yang , Pan Zhongli , Liu Yan-Hong , Xiao Hong-Wei
Published: December 2020

The contamination risks of microorganisms and mycotoxins in low-moisture foods have heightened public concern. Developing novel decontamination technologies to improve the safety of low-moisture foods is of great interest in both economics and public health. This review summarizes the working principles and applications of novel thermal decontamination technologies such as superheated steam, infrared, microwave, and radio-frequency heating as well as extrusion cooking. These methods of decontamination can effectively reduce the microbial load on products andmoderately destruct the mycotoxins. Meanwhile, several integrated technologies have been developed that take advantage of synergistic effects to achieve the maximum destruction of contaminants and minimize the deterioration of products.
High Potential-Applied Catalyst Behavior of a Mononuclear Ruthenium(II) Complex on a Mesoporous ITO Electrode for Water Oxidation
Authors: Tsubonouchi Yuta , Tanahashi Yuki , Eo Tatsuya , Honta Junichiro , Sato Taisei , Mohamed Eman A. , Zahran Zaki N. , Saito Kenji , Yui Tatsuto , Yagi Masayuki
Published: December 2020

The catalytic aspect of a mononuclear Ru complex, [Ru(C8Otpy)(dcbpy)(OH)]− (1) (C8Otpy = 4′-octyloxy-2,2′:6′,2″-terpyridine, H2dcbpy = 4,4′-dicarboxy-2,2′-bipyridine) on a mesoporous indium tin oxide (m-ITO) electrode was investigated by multi-potential-step chronocoulo(ampero)spectrometry (MPSCC(A)S) combined with in situ O2 evolution analysis. For the repetitive MPSCC(A)S measurement between 0.2 and 1.7 V vs Ag/AgCl, 39% of 1 recovered on the first back potential-step to 0.2 V, but 1 no longer recovered after the 4th back potential-step, although the in situ measured amount of O2 increased monotonously with time. XPS and Raman spectroscopic measurements reveal that 1 on the electrode pronouncedly undergoes the oxidative transformation to form the hydrated RuO2 as the alternative catalysts under the high applied potential of 1.7 V. The RuV=O state is more active for water oxidation than the RuIV=O state but could be prone to transform to hydrated RuO2. This tells us that the low applied potential but enough for formation of the RuIV=O species is important for 1 to work stably as a molecular catalyst on the electrode.
Bazedoxifene Plays a Protective Role against Inflammatory Injury of Endothelial Cells by Targeting CD40
Authors: Song Wenmin , Lv Yu , Tang Zizhao , Nie Fangqin , Huang Panhao , Pei Qi , Guo Ren
Published: December 2020

The inflammatory response and oxidative stress play key roles in the formation and development of atherosclerosis. Bazedoxifene is a new IL6/GP130 inhibitor recommended by the FDA for clinical use as a selective estrogen receptor modulator. However, its role in cardiovascular diseases has been poorly studied. In our study, we explored the mechanism of bazedoxifene’s protective effect against inflammatory injury of vascular endothelial cells (VECs) stimulated by TNF-α. Various methods were used to verify the effect of bazedoxifene on VECs, including a cell viability assay, a wound healing assay, immunofluorescence staining, and western blotting. Our results showed that TNF-α could induce inflammatory damage to VECs, which manifested as upregulated expression of CD40, increased production of ROS, enhanced adhesion of THP-1 cells to VECs, and impaired viability and migration of VECs, while bazedoxifene could significantly reduce the endothelial damage caused by TNF-α. In addition, we found that an siRNA targeting CD40 dramatically alleviated the VEC damage induced by TNF-α. Therefore, we explored the potential relationship between bazedoxifene and CD40. Our data suggest that bazedoxifene has a protective effect against VEC damage induced by TNF-α and that its underlying mechanism may be related to the regulation of CD40.
Lightweight Threshing Rack under Multisource Excitation Based on Modal Optimization Method
Authors: Zhang Haotian , Tang Zhong , Li Yu , Liu Xin , Ren Hui
Published: December 2020

Crawler rice combine harvester threshing rack excited by different frequencies of multiple working parts would cause strong vibration response. In this paper, the rack‐type rice combine harvester threshing rack was taken as research objective, and then the static analysis of the existing threshing rack was carried out by ANSYS Finite Element software. The topology of the rack structure was optimized according to the stress and strain distribution of the threshing rack. Based on solving the 6 natural frequencies and mode shapes of the threshing rack of combine harvester, the morphological test of threshing rack was carried out and the reliability of the modal analysis was verified. Finally, the multivibration source was assembled on the rack for simulation to test and verify the optimization effectiveness. Results showed that the 1st to 6th natural frequency of threshing rack after modal optimization could avoid the excitation frequency of the working part. Compared with the original design, the optimized threshing rack had a weight reduction of 13.7%. This study can provide a theoretical reference for the structural design and optimization of combine harvester threshing rack.
Study on Prediction Method for Postconstruction Settlement of Loess Fill Foundation in Northern Shaanxi, China
Authors: Liu Kui , Yuan Kangze , Shi Boyi
Published: December 2020

In order to solve the problem of shortage of construction land in the loess hilly and gully area of northern Shaanxi, the local people usually adopted the method of excavating and filling. The postconstruction settlement was an important index to evaluate the stability of the loess fill foundation. Through laboratory test analysis, the stress‐strain and the strain‐time relationship of compacted loess were obtained. It showed that the stress‐strain curves varied as power functions, and the relationship between strain and time was hyperbolic. Based on the layerwise summation method, a creep equation to predict the postconstruction settlement of loess fill foundation was established. The field monitoring data show that the fitting effect is better. Using this equation, the postconstruction settlement of loess fill foundation with different compaction coefficients and thickness was predicted. Finally, the stability evaluation criteria of loess fill foundation with various thickness and compaction coefficient were proposed. This method provided a new idea to solve the problem of postconstruction settlement of loess fill foundation.
Task Transfer Learning for EEG Classification in Motor Imagery-Based BCI System
Authors: Zheng Xuanci , Li Jie , Ji Hongfei , Duan Lili , Li Maozhen , Pang Zilong , Zhuang Jie , Rongrong Lu , Tianhao Gao
Published: December 2020

The motor-imagery brain-computer interface system (MI-BCI) has a board prospect for development. However, long calibration time and lack of enough MI commands limit its use in practice. In order to enlarge the command set, we add the combinations of traditional MI commands as new commands into the command set. We also design an algorithm based on transfer learning so as to decrease the calibration time for collecting EEG signal and training model. We create feature extractor based on data from traditional commands and transfer patterns through the data from new commands. Through the comparison of the average accuracy between our algorithm and traditional algorithms and the visualization of spatial patterns in our algorithm, we find that the accuracy of our algorithm is much higher than traditional algorithms, especially as for the low-quality datasets. Besides, the visualization of spatial patterns is meaningful. The algorithm based on transfer learning takes the advantage of the information from source data. We enlarge the command set while shortening the calibration time, which is of significant importance to the MI-BCI application.
Effect of Surface Site Defects on Photocatalytic Properties of BiVO4/TiO2 Heterojunction for Enhanced Methylene Blue Degradation
Authors: Mansour Sahar , Akkari Rym , Ben Chaabene Semy , Saïd Zina Mongia
Published: December 2020

Combining a super photoresponsive BiVO4 catalyst to the large band gap TiO2 material seems to be a great interest in order to improve the visible‐light‐driven photodegradation of hazardous pollutants. BiVO4/TiO2 heterojunction composites have been synthesized via a simple one‐pot hydrothermal route. Herein, we carefully highlighted the effect of BiVO4 content on the physicochemical and photocatalytic properties of solids towards the decomposition of methylene blue (MB) under solar light irradiation. The main results revealed that the formation of the heterostructures catalyst by incorporating BiVO4 into TiO2 stabilizes the anatase phase of TiO2 by inhibiting its crystal growth and improves significantly the light absorbance of titanium dioxide. The results showed that the best photocatalytic performance is assigned to the catalyst with 2 wt% BiVO4 loading which is higher than both pure BiVO4 and TiO2. This improvement of photocatalytic activity is related to the synergetic effect between both materials. Furthermore, the constructed junction leads to an increase in the concentration of oxygen defects on the semiconductor surface which could create an acceptor energy level into the valence band of TiO2. Four cyclic runs for the photocatalytic degradation of MB on BiVO4/TiO2 composite revealed its stability and sustainable reusability.
A Lightweight Object Detection Network for Real-Time Detection of Driver Handheld Call on Embedded Devices
Authors: Zhao Zuopeng , Zhang Zhongxin , Xu Xinzheng , Xu Yi , Yan Hualin , Zhang Lan
Published: December 2020

It is necessary to improve the performance of the object detection algorithm in resource-constrained embedded devices by lightweight improvement. In order to further improve the recognition accuracy of the algorithm for small target objects, this paper integrates 5 × 5 deep detachable convolution kernel on the basis of MobileNetV2-SSDLite model, extracts features of two special convolutional layers in addition to detecting the target, and designs a new lightweight object detection network—Lightweight Microscopic Detection Network (LMS-DN). The network can be implemented on embedded devices such as NVIDIA Jetson TX2. The experimental results show that LMS-DN only needs fewer parameters and calculation costs to obtain higher identification accuracy and stronger anti-interference than other popular object detection models.
Mechanical Properties of Microsteel Fiber Reinforced Concrete and Its Gradient Design in the Partially Reinforced RC Beam
Authors: He Xiaobing , Fang Yakun , Luo Qi , Cao Yong , Lu Han , Ma Runping
Published: December 2020

Effects of two kinds of microsteel fibers were employed in reinforced concrete (RC) with different fiber volumes fraction. The RC beam was partially reinforced by microsteel fiber reinforced concrete (MSFRC) based on the idea of gradient design. Flexural performances were specially investigated. Results show that microsteel fiber highly strengthened and toughened the concrete matrix. With the same fiber volume content, the concrete reinforced by Type I fiber was generally better in strength compared with that of Type II, while the bending toughness was substantially improved. The bending strength of the concrete reinforced by microsteel fiber in partial section of tensile region was comparable to that in whole section. Based on the traditional strength theory, the critical MSFRC layer depth of in the partially reinforced RC beam was about 0.3 times of the beam depth, which possessed the same crack resistance ability with the beam composed of MSFRC in the whole section. Compared with that of the reference beam, the cracking load of the partially reinforced beam was enhanced by 119%, and the ratio of the cracking moment to ultimate moment improved by 91%. Moreover, the width and height of the cracks in the partially reinforced beam developed much slower than those in the reference beam, and the steady state in which all cracks emerged appeared later; meanwhile, the crack spacing in the pure bending region was smaller, and the number of cracks in the bending‐shear region was less, which means that the partially reinforced beam is of excellent properties to resist cracking and bending. Finally, the calculation formula of the bearing capacity of the partially reinforced beam was proposed, which was in good agreement with experimental results.
Bearing Defect Classification Algorithm Based on Autoencoder Neural Network
Authors: Lu Manhuai , Mou Yuanxiang
Published: December 2020

The postproduction defect classification and detection of bearings still relies on manual detection, which is time‐consuming and tedious. To address this, we propose a bearing defect classification network based on an autoencoder to enhance the efficiency and accuracy of bearing defect detection. An improved autoencoder is used to reduce dimension feature extraction and reduce large‐scale images to small‐scale images through encoder dimensional reduction. Defect classification is completed by feeding the extracted features into a convolutional classification network. Comparative experiments show that the neural network can effectively complete feature selection and substantially improve classification accuracy while avoiding the laborious algorithm of the conventional method.
Structural Mechanical Characteristics and Instability Law of Roof Key Block Breaking in Gob‐Side Roadway
Authors: Wang Xinfeng , Lu Mingyuan , Gao Yuhao , Luo Wenbo , Liu Wengang
Published: December 2020

The influence of mining on the upper section of working face leads to the fracture of the lateral key block of the roof. From the goaf to the coal body, a group of “left‐middle‐right” key blocks are formed. According to the three different spatial position structure relations formed by roadway and broken key block in practical engineering, the mechanical causes of broken structure of key block in roof of roadway along goaf are analyzed. FLAC3D is used to simulate and analyze the deformation characteristics and stress state of key block structure model before and after roadway excavation, and the mechanical characteristics and instability mechanism of key block sliding and breaking under three spatial structure modes are obtained. With the help of the mathematical model of material mechanics, the structural mechanical behavior of key block model of roof before and after roadway excavation and the temporal and spatial evolution law of unloading and breaking are studied. The results show that the complex influence factors of mining disturbance and low strength of the weak rock mass will weaken the internal balance of “masonry beam” structure. When the roadway is located below the fracture line of the key block, the middle key block will rotate and lose stability with the side hinge joint of the goaf as the axis; when the roadway is located in the fracture line of the key block, it is easy for the middle key block to slide and lose stability; when the roadway is located outside the fracture line of the key block, the middle key block is in the state of complete collapse, the mechanical transmission mechanism of the surrounding rock in the vertical direction is weakened, and the surrounding rock is the most stable.
Design and Simulation of Compound Eye Lens for Visible Light Communication and Illumination
Authors: Li Jiehui , Zhang Qian
Published: December 2020

We proposed a scheme for designing an optical launch system that can make the light intensity more uniform on the receiving plane via a compound eye lens combined with a sunflower plano-convex lens. The simulation results demonstrate that the light converges on the optical axis after passing through the sunflower-shaped plano-convex lens array and compound eye lens. The divergence angle and central light intensity of the receiving plane are, respectively, 26.57° and 80.50% of the total emitted light power for the array structure of the compact compound eye plano-convex lens, while those are 21.80° and 62.50% for the discrete compound eye lens. From the above results, it can be seen that the compact compound eye lens is more conducive to the uniform distribution of light intensity on the receiving plane compared with the discrete compound eye lens, taking into account the dual application of illumination and communication.
Chronic Venous Disease Patients Showed Altered Expression of IGF‐1/PAPP‐A/STC‐2 Axis in the Vein Wall
Authors: Ortega Miguel A. , Fraile-Martínez Oscar , Asúnsolo Ángel , Martínez-Vivero Clara , Pekarek Leonel , Coca Santiago , Guijarro Luis G. , Álvarez-Mon Melchor , Buján Julia , García-Honduvilla Natalio , Sainz Felipe
Published: December 2020

Chronic venous disease (CVeD) has a remarkable prevalence, with an estimated annual incidence of 2%. It has been demonstrated how the loss of homeostatic mechanisms in the vein wall can take part in the physiopathology of CVeD. In this regard, it has been described how different axis, such as IGF‐1/PAPP‐A/STC‐2 axis, may play an essential role in tissue homeostasis. The aim of this research is to study both genetic and protein expressions of the IGF‐1/PAPP‐A/STC‐2 axis in CVeD patients. It is a cross‐sectional study in which genetic (RT‐qPCR) and protein (immunohistochemistry) expression analysis techniques were accomplished in saphenous veins from CVeD patients (n = 35) in comparison to individuals without vascular pathology (HV). Results show a significant increase in both genetic and protein expressions of PAPP‐A and IGF‐1, and a decrement STC‐2 expression at the same time in CVeD patients. Our study is a pioneer for demonstrating that the expression of the different components of the IGF‐1/PAPP‐A/STC‐2 axis is altered in CVeD patients. This fact can be a part of the loss of homeostatic mechanisms of the venous tissue. Further research should be destined to deepen into alterations of this axis, as well as to evaluate the usage of these components as therapeutic targets for CVeD.
Image Annotation via Reconstitution Graph Learning Model
Authors: Chen Shi , Wang Meng , Chen Xuan
Published: December 2020

With great developments of computing technologies and data mining methods, image annotation has attracted much attraction in smart agriculture. However, the semantic gap between labels and images poses great challenges on image annotation in agriculture, due to the label imbalance and difficulties in understanding obscure relationships of images and labels. In this paper, an image annotation method based on graph learning is proposed to accurately annotate images. Specifically, inspired by nearest neighbors, the semantic neighbor graph is introduced to generate preannotation, balancing unbalanced labels. Then, the correlations between labels and images are modeled by the random dot product graph, to deeply mine semantics. Finally, we perform experiments on two image sets. The experimental results show that our method is much better than the previous method, which verifies the effectiveness of our model and the proposed method.
Graphene-Assisted Goos–Hänchen Shift in a Planar Multilayer Configuration in the Visible Light Range
Authors: Lin Wei , Xiao Zhichen , Zhou Wenyun , Ren Mengjiao , Zheng Zhiwei
Published: December 2020

In this paper, the graphene-assisted Goos–Hänchen (GH) shift of the optical beam reflected from a planar multilayer configuration is investigated. The increased positive Goos–Hänchen shifts can be modulated by adjusting the Fermi energy due to graphene with unique optical properties in the visible light range. Moreover, the GH shift can be tuned by varying the layers of graphene, the thickness of the medium, incident wavelength, and so on. These results will be useful for designing the novel graphene-based optical sensing and switching.
Experimental Exploration of Bearing Capacity of Clay with Multiple Inflatable Anchors
Authors: Chen Qiu-nan , Yang Meng , Huang Xiao-cheng
Published: December 2020

Inflatable anchors have been applied to reinforce foundations because soft soil deposits have a low bearing capacity. However, previous research on the mechanical behaviors of inflatable anchors has focused on a single anchor. Since anchors are always used in a group, the uplift behavior of multiple inflatable anchors in soft soil should be investigated. A series of pull-out tests were conducted in this framework by changing the number, spacing, and layout of inflatable anchors. Additionally, the effect coefficient (ECO) of multiple inflatable anchors is discussed. It is found that the failure behavior of multiple inflatable anchors exhibits a three-stage curve: an initial linear stage, followed by nonlinear, and steady-state stages. In addition, the ultimate bearing capacity of multiple inflatable anchors is maximized if the ratio of the spacing of inflatable anchors to the equivalent expanding section diameter of an inflatable anchor is 6.84. It is recognized that the ECO of this new multiple inflatable anchor group is sometimes greater than 1, unlike that of conventional anchors, which have ECOs of less than 1. In addition, the layout of multiple inflatable anchors in the shape of a cinquefoil is recommended due to its high ECO.
An Android Malware Detection Model Based on DT-SVM
Authors: Yang Min , Chen Xingshu , Luo Yonggang , Zhang Hang
Published: December 2020

In order to improve the accuracy and efficiency of Android malware detection, an Android malware detection model based on decision tree (DT) with support vector machine (SVM) algorithm (DT-SVM) is proposed. Firstly, the original opcode, Dalvik opcode, is extracted by reversing Android software, and the eigenvector of the sample is generated by using the n-gram model. Then, a decision tree is generated via training the sample and updating decision nodes as SVM nodes from the bottom up according to the evaluation result of the test set in the decision path. The model effectively combines DT with SVM. Under the premise of maintaining a high-accuracy decision path, SVM is used to effectively reduce the overfitting problem in DT and thus improve the generalization ability, and maintain the superiority of SVM for the small sample training set. Finally, to test our approach, several simulation experiments are carried out, and the results demonstrate that the improved algorithm has better accuracy and higher speed as compared with other malware detection approaches.
Research Status of Evolution of Microstructure and Properties of Sn-Based Lead-Free Composite Solder Alloys
Authors: Li Shuai , Wang Xingxing , Liu Zhongying , Mao Feng , Jiu Yongtao , Luo Jingyi , Shangguan Linjian , Jin Xiangjie , Wu Gang , Zhang Shuye , He Peng , Long Weimin
Published: December 2020

With the miniaturization of solder joints and deterioration of serving environment, much effort had been taken to improve the properties of Sn-based lead-free solders. And the fabrication of Sn-based lead-free composite solder alloys by the addition of nanoparticles is one of the effective ways to enhance the properties. In this paper, the recent research progress on the Sn-based lead-free composite solder alloys is reviewed by summarizing the relevant results in representative ones of Sn-Ag-Cu (SAC), Sn-Bi, and other multielement lead-free composite solder alloys. Specifically speaking, the effect of the added nanoparticles on the evolution of wettability, microstructure morphology, and mechanical properties of Sn-based lead-free composite solder alloys are summarized. It is hoped that this paper could supply some beneficial suggestions in developing the novel Sn-based lead-free composite solder alloys. Additionally, the existed issues and future development trends in the exploitation of new novel Sn-based lead-free composite solder alloys are proposed.
CPT Model-Based Prediction of the Temporal and Spatial Distributions of Passenger Flow for Urban Rail Transit under Emergency Conditions
Authors: Li Wei , Zhou Min , Dong Hairong
Published: December 2020

Emergencies have a significant impact on the passenger flow of urban rail transit. It is of great practical significance to accurately predict the urban rail transit passenger flow and carry out research on its temporal and spatial distributions under emergency conditions. Urban rail transit operating units currently use video surveillance information mainly to process emergencies and rarely use computer vision technology to analyze passenger flow information collected. Accordingly, this paper proposes a passenger flow-based temporal and spatial distribution model for urban rail transit emergencies based on the CPT. First, this paper clarifies the categories and classification of urban rail transit emergencies, analyzes the factors affecting passenger route selection, and establishes a generalized travel cost model for passengers under emergencies. Second, this paper establishes a passenger route choice behavior model for urban rail transit based on the cumulative prospect theory. Finally, taking Beijing as an example, this paper analyzes passenger travel behavior under emergencies based on multiple logistic regression models and analyzes the impact of emergencies on rail transit travel behavior. The research results show that the cumulative prospect theory can better describe the route choice behavior of rail transit passengers under emergencies than the existing models, and this model is of great significance for handling urban rail transit emergencies. The model proposed in this paper can provide a theoretical basis for the government and relevant departments to formulate traffic management measures.
Continuous Similarity Learning with Shared Neural Semantic Representation for Joint Event Detection and Evolution
Authors: Zhou Pengpeng , Luo Yao , Ning Nianwen , Cao Zhen , Jia Bingjing , Wu Bin
Published: December 2020

In the era of the rapid development of today’s Internet, people often feel overwhelmed by vast official news streams or unofficial self-media tweets. To help people obtain the news topics they care about, there is a growing need for systems that can extract important events from this amount of data and construct the evolution procedure of events logically into a story. Most existing methods treat event detection and evolution as two independent subtasks under an integrated pipeline setting. However, the interdependence between these two subtasks is often ignored, which leads to a biased propagation. Besides, due to the limitations of news documents’ semantic representation, the performance of event detection and evolution is still limited. To tackle these problems, we propose a Joint Event Detection and Evolution (JEDE) model, to detect events and discover the event evolution relationships from news streams in this paper. Specifically, the proposed JEDE model is built upon the Siamese network, which first introduces the bidirectional GRU attention network to learn the vector-based semantic representation for news documents shared across two subtask networks. Then, two continuous similarity metrics are learned using stacked neural networks to judge whether two news documents are related to the same event or two events are related to the same story. Furthermore, due to the limited available dataset with ground truths, we make efforts to construct a new dataset, named EDENS, which contains valid labels of events and stories. The experimental results on this newly created dataset demonstrate that, thanks to the shared representation and joint training, the proposed model consistently achieves significant improvements over the baseline methods.
A Validated Volumetric Absorptive Microsampling-Liquid Chromatography Tandem Mass Spectrometry Method to Quantify Doxycycline Levels in Urine: An Application to Monitor the Malaria Chemoprophylaxis Compliance
Authors: Penot Mylène , Linard Cyril , Taudon Nicolas
Published: December 2020

Because of logistics and cost constraints, monitoring of the compliance to antimalarial chemoprophylaxis by the quantitation of drugs in biological samples is not a simple operation on the field. Indeed, analytical devices are fragile to transport and must be used in a perfectly controlled environment. This is also the case for reagents and supplies, and the waste management is constraining. Thus, samples should be repatriated. They should be frozen after collection and transported with no rupture in the cold chain. This is crucial to generate available and interpretable data but often without any difficulties. Hence, to propose an alternative solution easier to implement, a quantitation method of determining doxycycline in urine has been validated using a volumetric absorptive microsampling (VAMS®) device. As blotting paper, the device is dried after collection and transferred at room temperature, but contrarily to dried spot, the collection volume is perfectly repeatable. Analysis of VAMS® was performed with a high-performance liquid chromatography coupled to a mass spectrometer. The chromatographic separation was achieved on a core-shell C18 column. The mean extraction recovery was 109% (mean RSD, 5.4%, n = 6) for doxycycline and 102% (mean RSD, 7.0%) for the internal standard. No matrix effect has been shown. Within-run as within-day precision and accuracy were, respectively, below 14% and ranged from 96 to 106%. The signal/concentration ratio was studied in the 0.25–50 µg/mL range, and recoveries from back-calculated concentrations were in the 96–105% range (RSD < 11.0%). The RSD on slope was 10%. To achieve the validation, this new quantitation method was applied to real samples. In parallel, samples were analyzed directly after a simple dilution. No statistical difference was observed, confirming that the use of VAMS® is an excellent alternative device to monitor the doxycycline compliance.
Severe Acral Necrosis Complicating Thrombotic Microangiopathy in Two Toddlers
Authors: Nassih H. , Lazrak Z. , Younous S.
Published: December 2020

Acral ischemia/necrosis is one of the rarest but most dreadful complications of thrombotic microangiopathy in pediatric patients. It is more reported with thrombotic thrombocytopenic purpura than with hemolytic and uremic syndrome. Even with anticoagulant therapy, it is often irreversible, leading to amputation.
Effect of Broken Coffee Beans Particle Size, Roasting Temperature, and Roasting Time on Quality of Coffee Beverage
Authors: Getaneh Ezana , Fanta Solomon Workneh , Satheesh Neela
Published: December 2020

Optimum flavor and aroma of the coffee are developed during the roasting process. However, certain problems exist in the coffee roasting process such as partial charring, over roasting, and poor temperature distribution across the coffee bean (due to the low thermal conductivity of bean), if conditions are not optimized. Hence, uniform temperature distribution across the coffee bean in the roasting process is highly desirable. To achieve these requirements, the broken coffee beans were positioned in a single layer packed bed arrangement using the closed system by circulating hot air. In this experiment, three factors were arranged in a completely randomized design with three levels and three replications. The first factor considered was roasting temperature (200°C, 230°C, and 260°C), second factor was roasting time (5 min, 10 min, and 15 min), and third was particle size (4–6 mm, 2.36–3.35 mm, and 1.7–2.36 mm). The initial moisture content of raw beans (cv. Limu) was determined. The data were collected on selective physical properties of roasted coffee beans and sensory acceptability of prepared beverage. The results showed that the physical properties and sensory acceptability are significantly high (

P
<
0.001

). It depends on the interaction effect of all the studied factors. Among the studies parameters, roasting temperature of 230°C with a particle size range of 4–6 mm showed the steady transition in dry mass loss and change in bulk density with increase in roasting duration. Coffee roasted at 230°C for 10 min with a particle size of 4–6 mm showed the highest sensory acceptability score (89.21). In conclusion, it can be said that a temperature of 230°C, a time of 10 min, and a particle size between 2.36–3.35 mm and 4–6 mm are recommended conditions for the roasting process of coffee beans.
Cooperative Governance of Complex Public‐Private Partnership Program: Case Study of Characteristic Town Program
Authors: Chen Zhen
Published: December 2020

PPP program is characterized by great organizational complexity, complicated communication network, and high coordination cost, which lead governance problems to be more complex than usual construction projects. Investigating 49 stakeholders of the D characteristic town construction program, the author constructs the work interaction network and supervision network of characteristic town PPP program based on organizational relationship. Through the calculation and comparison of network parameters, the network problems were analyzed, and the governance improvement scheme was proposed. The results show that, during the construction phase of the PPP program, (1) the SPV is still the core stakeholders; (2) the PPP program supervison belongs to hierarchical supervision characteristics and (3) the government regulators and loan institutions have limited influences on the program but they can restrict the SPV by strengthening supervision with subprogram stakeholders.
Visual Object Multimodality Tracking Based on Correlation Filters for Edge Computing
Authors: Yang Guosheng , Wei Qisheng
Published: December 2020

In recent years, visual object tracking has become a very active research field which is mainly divided into the correlation filter-based tracking and deep learning (e.g., deep convolutional neural network and Siamese neural network) based tracking. For target tracking algorithms based on deep learning, a large amount of computation is required, usually deployed on expensive graphics cards. However, for the rich monitoring devices in the Internet of Things, it is difficult to capture all the moving targets in each device in real time, so it is necessary to perform hierarchical processing and use tracking based on correlation filtering in insensitive areas to alleviate the local computing pressure. In sensitive areas, upload the video stream to a cloud computing platform with a faster computing speed to perform an algorithm based on deep features. In this paper, we mainly focus on the correlation filter-based tracking. In the correlation filter-based tracking, the discriminative scale space tracker (DSST) is one of the most popular and typical ones which is successfully applied to many application fields. However, there are still some improvements that need to be further studied for DSST. One is that the algorithms do not consider the target rotation on purpose. The other is that it is a very heavy computational load to extract the histogram of oriented gradient (HOG) features from too many patches centered at the target position in order to ensure the scale estimation accuracy. To address these two problems, we introduce the alterable patch number for target scale tracking and the space searching for target rotation tracking into the standard DSST tracking method and propose a visual object multimodality tracker based on correlation filters (MTCF) to simultaneously cope with translation, scale, and rotation in plane for the tracked target and to obtain the target information of position, scale, and attitude angle at the same time. Finally, in Visual Tracker Benchmark data set, the experiments are performed on the proposed algorithms to show their effectiveness in multimodality tracking.
Lessons Learnt from the Second Generation of Anti-Amyloid Monoclonal Antibodies Clinical Trials
Authors: Tian Hui Kwan Angela , Arfaie Saman , Therriault Joseph , Rosa-Neto Pedro , Gauthier Serge
Published: December 2020

Background: Alzheimer disease (AD) is a chronic neurodegenerative disorder with complex pathophysiology that affects over 50 million people worldwide. Most drug therapies, to date, have focused on targeting the amyloid-beta (Aβ) pathway, but clinical outcomes of anti-Aβ antibodies have been unsuccessful and unable to meet their primary endpoints. Similar trends have also been observed in treatments that target the tau pathway. Summary: This paper reviews recent anti-Aβ passive monotherapies, since Bapineuzumab, that have progressed to phase 3 clinical trials. Specifically, we discuss the 4 clinical trial programs of Solanezumab (targets Aβ monomers), Aducanumab (targets Aβ oligomers and plaques), Crenezumab (targets Aβ oligomers), and Gantenerumab (targets Aβ fibrils) which are all exogenous monoclonal antibodies. We conclude with potential reasons for why they have not met their primary endpoints and discuss lessons learnt from these trials. Key Message: Future disease-modifying trials (DMTs) for AD should be conducted in asymptomatic, Aβ-positive individuals. Moreover, potential additive and/or synergistic benefits focusing on anti-Aβ and anti-tau drug combinations merit further investigation.
Time Trends in Intracerebral Hemorrhage Associated with Oral Anticoagulation and Its Risks Factors in Spain from 2008 to 2015
Authors: Quintas Sonia , Zapata-Wainberg Gustavo , Arias-Rivas Susana , Ximénez-Carrillo Álvaro , Castillo Jose , Benavente Fernández Lorena , Masjuan Vallejo Jaime , Freijó Guerrero María del Mar , Egido José , García Pastor Andrés , Cardona Pere , Lago Aida , Castellanos Rodrigo Mar , Fuentes Blanca , Sobrado Mónica , Vivancos Jose
Published: December 2020

Background: Intracerebral hemorrhage (ICH) is 7- to 10-fold higher in anticoagulated patients. Given the more extended use of oral anticoagulants, an increase in the prevalence of ICH associated with oral anticoagulation (ICH-OAC) could be expected. However, there is no previous study that assesses the time trends of ICH-OAC in Spain. Methods: We conducted a combined data analysis after creating a joint database of the 3 most important epidemiological studies on ICH-OAC of our country: the EPICES study (2008–2009), the TAC Registry (TR) study (2012–2013) and the TAC Registry 2 (TR2) study (2015). We finally included 65, 235, and 366 patients from the EPICES, TR, and TR2 studies, respectively. Results: We have observed a 3.73-fold increase in the crude annual incidence of ICH-OAC throughout the period of study, with proportion of ICH-OAC out of total ICH increasing from 8.4% in 2008 to 18.2% in 2015. Age, dyslipidemia, and prior antiplatelet treatment increased during the study, but we found no statistically significant differences in other risk factors for ICH-OAC. Conclusions: The incidence of ICH-OAC is increasing in our country. It might at least be partly explained by aging of the population, with mean age at presentation being higher in the last years.
Hypotrichosis with Juvenile Macular Dystrophy in Saudi Arabia: A Case Report
Authors: Ahmed Azhar , Alali Azhar , Alsharif Osama , Kaki Adnan
Published: December 2020

Hypotrichosis with juvenile macular dystrophy is an autosomal recessive disorder due to a mutation in the CDH3 gene. As its name indicates, the disease classically presented with hypotrichosis and early visual impairment. We describe herein a family member with alopecia since birth associated with severe visual impairment in their early life. We suspect the diagnosis of hypotrichosis with juvenile macular dystrophy. Genetic testing confirms the clinical suspension. We emphasize the importance of genetic testing for proper genetic counseling.
Trichotillomania Incognito: Two Case Reports and Literature Review
Authors: Fernandes Mariana Rita de Novaes , Melo Daniel Fernandes , Vincenzi Colombina , Lima Caren dos Santos , Tosti Antonella
Published: December 2020

Trichotillomania is a compulsive disorder characterized by repetitive hairpulling. It is an important cause of patchy alopecia, especially in children between 9 and 13 years of age. The aim of this paper is to report 2 pediatric cases presenting with trichotillomania without patches. This condition may be extremely distressful, impacting psychosocial development of children. In these case reports, we reinforce the relevance of trichoscopy in hair disorder evaluation, which allowed early recognition to better advise and conduct these unique pediatric cases.
A Comparative Study of the Behavioral Profile of the Behavioral Variant of Frontotemporal Dementia and Parkinson’s Disease Dementia
Authors: Saini Dinesh , Mukherjee Adreesh , Roy Arijit , Biswas Atanu
Published: December 2020

Background: Executive dysfunction is the common thread between pure cortical dementia like the behavioral variant of frontotemporal dementia (bvFTD) and subcortical dementia like Parkinson’s disease dementia (PDD). Although there are clinical and cognitive features to differentiate cortical and subcortical dementia, the behavioral symptoms differentiating these 2 conditions are still not well known. Objective: To evaluate the behavioral profile of bvFTD and PDD and compare them to find out which behavioral symptoms can differentiate between the two. Methods: Twenty consecutive patients with bvFTD (>1 year after diagnosis) and 20 PDD patients were recruited according to standard diagnostic criteria. Behavioral symptoms were collected from the reliable caregiver by means of a set of questionnaires and then compared between the 2 groups. Results: bvFTD patients had more severe disease and more behavioral symptoms than PDD. bvFTD patients were different from PDD patients due to their significantly greater: loss of basic emotion (p < 0.001, odds ratio [OR] 44.33), loss of awareness of pain (p < 0.001, OR 44.33), disinhibition (p < 0.001, OR 35.29), utilization phenomenon (p = 0.008, OR 22.78), loss of taste discrimination (p < 0.001, OR 17), neglect of hygiene (p = 0.001, OR 13.22), loss of embarrassment (p = 0.003, OR 10.52), wandering (p = 0.004, OR 9.33), pacing (p = 0.014, OR 9), selfishness (p = 0.014, OR 9), increased smoking (p = 0.014, OR 9), increased alcohol consumption (p = 0.031, OR 7.36), social avoidance (p = 0.012, OR 6.93), mutism (p = 0.041, OR 5.67), and failure to recognize objects (p = 0.027, OR 4.33). The bvFTD patients were also significantly less suspicious (p = 0.001, OR 0.0295), less inclined to have a false belief that people were in their home (p = 0.014, OR 0.11) and had fewer visual illusions/hallucinations (p = 0.004, OR 0.107) than PDD patients. Conclusion: Behavioral symptoms are helpful to distinguish bvFTD from PDD, and thus also cortical dementia with frontal-lobe dysfunction from subcortical dementia.