bluuebunny/crossref_metadata_2025 huggingface dataset:
A Simulation‐Based Approach of QoS‐Aware Service Selection in Mobile Edge Computing
Authors: Huang Jiwei , Lan Yihan , Xu Minfeng
Published: November 2018

Edge computing is an emerging computational model that enables efficient offloading of service requests to edge servers. By leveraging the well‐developed technologies of cloud computing, the computing capabilities of mobile devices can be significantly enhanced in edge computing paradigm. However, upon the arrival of user requests, whether to dispatch them to the edge servers or cloud servers in order to guarantee the quality of service (QoS), i.e., the QoS‐aware service selection problem, still remains an open problem. Due to the dynamic mobility of users and the variation of task arrivals and service processes, it is extremely costly to obtain the global optimal solution by both mathematical approaches and simulation‐based schemes. To attack this challenge, this paper proposes a simulation‐based approach of QoS‐aware dynamic service selection for mobile edge computing systems. Stochastic system models are presented and mathematical analyses are provided. Based on the analytical results, the QoS‐aware service selection problem is formulated by a dynamic optimization problem. Goal softening is applied to the original problem, and service selection algorithms are designed using ordinal optimization techniques. Simulation experiments are conducted to validate the efficacy of the approach presented in this paper.
A Multidimensional Data‐Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition
Authors: Ibáñez Rubén , Abisset-Chavanne Emmanuelle , Ammar Amine , González David , Cueto Elías , Huerta Antonio , Duval Jean Louis , Chinesta Francisco
Published: November 2018

Sparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves the need for large amount of data, unfeasible in such a high dimensional settings. This well‐known phenomenon, coined as the curse of dimensionality, is here overcome by means of the use of separate representations. We present a technique based on the same principles of the Proper Generalized Decomposition that enables the identification of complex laws in the low‐data limit. We provide examples on the performance of the technique in up to ten dimensions.
Comparison of the Outcomes of Three Different Nutritional Supports in Patients with Oral and Maxillofacial Malignant Tumors following Surgery
Authors: Zou Chen , Zhou Xuan , Zhuang Shuhan , Huang Guowei , Wang Hongwu
Published: November 2018

Objective. This study aimed to compare the physical and mental states and the clinical effects of parenteral nutrition combined with enteral nutrition (PN+EN), total enteral nutrition (TEN), and total parenteral nutrition (TPN) after surgery in patients with maxillofacial malignant tumors. Methods. A total of 112 patients were divided into three groups, with 58, 33, and 21 patients in the PN+EN, TPN, and TEN groups, respectively. The psychological survey contained the Faces Pain Scale‐Revised (FRS‐R), visual analog scale (VAS), numerical rating scale (NRS), Hamilton anxiety rating scale (HAMA), and short‐form 36 health survey questionnaire (SF‐36). Spirit symptoms, length of hospital stay, nutritional assessments, and related biochemical indices were recorded and compared. Results. The traditional Chinese medicine (TCM) symptoms of anxiety and dysphoria were least frequently identified in the TPN group. The levels of lymphocytes, hemoglobin (HB), albumin (ALB), and prealbumin (PA) were significantly higher in the PE+EN group, whereas white blood cell count, neutrophil count, HB, PA, and ALB were significantly lower in the TPN group. Better psychological scores were observed in the TPN group. The PE+EN group had a shorter length of stay and higher SGA categories. Potassium, sodium, and chlorine levels were significantly lower in the TEN group (all P < 0.05). Conclusions. As an auxiliary method, TCM symptoms can help to identify spirit disequilibrium earlier and are associated with blood indices. Without the consideration of cost and long length of hospital stay, patients in the TPN group had the best mental status, with PN+EN therapy being an alternative.
Preoperative PET/CT 18F-FDG Standardized Uptake by Lymph Nodes as a Significant Prognostic Factor in Patients with Colorectal Cancer
Authors: Chen Ruohua , Wang Yining , Zhou Xiang , Huang Gang , Liu Jianjun
Published: November 2018

Purpose. We evaluated the prognostic value of preoperative 18F-FDG uptake by suspected lymph nodes (LNs) using 18F-FDG PET/CT in colorectal cancer patients. Methods. Patients with CRC underwent 18F-FDG PET/CT before radical surgery. We used Cox proportional hazards regression to examine the relationship between recurrence and the 18F-FDG maximum standardized uptake value (SUVmax) in the suspected LNs (SUVLN) on 18F-FDG PET/CT. Results. Clinical data, treatment modalities, and results from 90 CR C patients were reviewed. The median follow-up was 19 months (range 3 to 72 months). Receiver operating characteristic analysis identified SUVLN 1.15 was the optimal cut-off value for predicting recurrence. SUVLN correlated with tumour size (P=0.045), lymph node metastasis (P=0.03), and recurrence (P<0.0001). Univariate analysis showed significant associations between recurrence and SUVLN (P=0.017), and tumour grade (P=0.013). Multivariate analysis identified SUVLN (P<0.0001), and tumour grade (P=0.005) as independent risk factors for recurrence. Patients with SUVLN ≤ 1.15 and SUVLN > 0.15 differed significantly in terms of recurrence (P<0.0001). Conclusion. Preoperative SUVLN measured by 18F-FDG PET/CT was significantly associated with recurrence and had significant prognostic value for recurrence-free survival in patients with colorectal cancer.
Design of the Online Gross γ Monitoring Instrument at the Exit of the Helium Purification System in HTR-PM
Authors: Lou Mengqi , Zhang Liguo , Xie Feng , Cao Jianzhu , Tong Jiejuan , Liu Weirong , Wang Yong
Published: November 2018

After the successful construction and operation experience of the 10 MW high-temperature gas-cooled reactor (HTR-10), a high-temperature gas-cooled pebble-bed modular (HTR-PM) demonstration plant is under construction in Shidao Bay, Rongcheng City, Shandong province, China. An online gross γ monitoring instrument has been designed and placed at the exit of the helium purification system (HPS) of HTR-PM and is used to detect the activity concentration in the primary circuit after purification. The source terms in the primary loop of HTR-PM and the helium purification process were described. The detailed configuration of the gross γ monitoring instrument was presented in detail. The Monte Carlo method was used to simulate the detection efficiency of the monitoring system. Since the actual source terms in the primary loop of HTR-PM may be different than the current design values, a sensitivity analysis of the detection efficiency was implemented based on different relative proportions of the nuclides. The accuracy and resolution of the NaI(Tl) detector were discussed as well.
An Optimization Framework of Multiobjective Artificial Bee Colony Algorithm Based on the MOEA Framework
Authors: Huo Jiuyuan , Liu Liqun
Published: November 2018

The artificial bee colony (ABC) algorithm has become one of the popular optimization metaheuristics and has been proven to perform better than many state-of-the-art algorithms for dealing with complex multiobjective optimization problems. However, the multiobjective artificial bee colony (MOABC) algorithm has not been integrated into the common multiobjective optimization frameworks which provide the integrated environments for understanding, reusing, implementation, and comparison of multiobjective algorithms. Therefore, a unified, flexible, configurable, and user-friendly MOABC algorithm framework is presented which combines a multiobjective ABC algorithm named RMOABC and the multiobjective evolution algorithms (MOEA) framework in this paper. The multiobjective optimization framework aims at the development, experimentation, and study of metaheuristics for solving multiobjective optimization problems. The framework was tested on the Walking Fish Group test suite, and a many-objective water resource planning problem was utilized for verification and application. The experiment’s results showed the framework can deal with practical multiobjective optimization problems more effectively and flexibly, can provide comprehensive and reliable parameters sets, and can complete reference, comparison, and analysis tasks among multiple optimization algorithms.
Scare Behavior Diffusion Model of Health Food Safety Based on Complex Network
Authors: Luo Jun , Wang Jiepeng , Zhao Yongle , Chen Tingqiang
Published: November 2018

This study constructs a heterogeneous model of health food safety scare behavior diffusion through a complex network model by considering health food safety information transparency and health food consumers’ ability to process information. This study first analyzes the effects of network structure and heterogeneity of health food consumers on the health food safety scare behavior diffusion using network stochastic dominance theory. Subsequently, a computer mathematical simulation is performed to explore the characteristics and laws of the evolution of health food safety scare behavior diffusion. The following three major conclusions can be drawn from the results. First, increases in the health food safety information transparency, the health food consumers’ ability to process information, and the recovery rate of health food consumers can increase the threshold of the rate of health food safety scare behavior diffusion. The health food safety information transparency and the recovery rate of health food consumers show marginal incremental rising characteristics in relation to the rate of health food safety scare behavior diffusion, whereas the health food consumers’ ability to process information shows a marginal diminishing rising characteristic in relation to the rate of health food safety scare behavior diffusion. Second, increases in the health food safety information transparency, the health food consumers’ ability to process information, and the recovery rate of health food consumers can decrease the scale of the health food safety scare behavior diffusion. The health food safety information transparency shows a marginal diminishing decreasing characteristic in relation to the scale of the health food safety scare behavior diffusion, whereas the health food consumers’ ability to process information and the recovery rate of the health food consumers show marginal incremental decreasing characteristics in relation to the scale of the health food safety scare behavior diffusion. Finally, the network structure of health food consumers significantly affects the health food safety scare behavior diffusion. A high heterogeneity of the health food consumer network indicates a high threshold of the rate of health food safety scare behavior diffusion and low diffusion scale.
Trends and Drivers of Inpatient Antibiotic Consumption among 89 China Tertiary General Hospitals from 2011Q1 to 2015Q4
Authors: Chen Jiangyun , Min Rui , Wang He , Zhao Shengwen , Li Haomiao , Fang Pengqian
Published: November 2018

Antibacterial surveillance is an essential measure for strengthening the management of clinical antibiotic use. This study aimed to determine the trends and drivers of inpatient antibiotic consumption in China. A sample of 89 hospitals with complete data from 2011Q1 to 2015Q4 was included. Accumulative defined daily doses (DDDs), antibiotic use density (AUD), and drug variety were calculated to evaluate antibiotic consumption. From 2011Q1 to 2015Q4, the median values of DDDs, AUD, and drug variety dropped by 10.49%, 39.19%, and 27.96%, respectively. Panel regression results showed, for each additional quarter, DDDs reduced by 6.714 DDDs, AUD reduced by 0.013 DDDs per 100 inpatients per day, and drug variety reduced by 0.012 types (p < 0.001). National hospitals were more likely to use antibiotics, with the highest number of DDDs (106 709 DDDs) and AUD (60 DDDs per 100 inpatients per day) and a large number of drug variety (71 types of drug) all reported from national hospitals. Overall, a downward trend of inpatient antibiotic consumption was observed in competitive tertiary general hospitals in China. However, antibiotic use in China, especially in national hospitals, continues to exceed the guidelines set forth by the nationwide antibiotic stewardship program. China must continue to improve surveillance of antibiotic consumption by constructing a more comprehensive, continuous, and targeted stewardship program. Policy interventions in China should be made in consideration of unbalanced regional development and the consequences this may have on antibiotic consumption.
Prevalence of Steatosis Hepatis in the Eurotransplant Region: Impact on Graft Acceptance Rates
Authors: Moosburner Simon , Gassner Joseph M. G. V. , Nösser Maximilian , Pohl Julian , Wyrwal David , Claussen Felix , Ritschl Paul V. , Dragun Duska , Pratschke Johann , Sauer Igor M. , Raschzok Nathanael
Published: November 2018

Due to the shortage of liver allografts and the rising prevalence of fatty liver disease in the general population, steatotic liver grafts are considered for transplantation. This condition is an important risk factor for the outcome after transplantation. We here analyze the characteristics of the donor pool offered to the Charité – Universitätsmedizin Berlin from 2010 to 2016 with respect to liver allograft nonacceptance and steatosis hepatis. Of the 2653 organs offered to our center, 19.9% (n=527) were accepted for transplantation, 58.8% (n=1561) were allocated to other centers, and 21.3% (n = 565) were eventually discarded from transplantation. In parallel to an increase of the incidence of steatosis hepatis in the donor pool from 20% in 2010 to 30% in 2016, the acceptance rates for steatotic organs increased in our center from 22.3% to 51.5% in 2016 (p < 0.001), with the majority (86.9%; p > 0.001) having less than 30% macrovesicular steatosis hepatis. However, by 2016, the number of canceled transplantations due to higher grades of steatosis hepatis had significantly increased from 14.7% (n = 15) to 63.6% (42; p < 0.001). The rising prevalence of steatosis hepatis in the donor pool has led to higher acceptance rates of steatotic allografts. Nonetheless, steatosis hepatis remains a predominant phenomenon in discarded organs necessitating future concepts such as organ reconditioning to increase graft utilization.
Targeted Influential Nodes Selection in Location‐Aware Social Networks
Authors: Yang Susu , Li Hui , Jiang Zhongyuan
Published: November 2018

Given a target area and a location‐aware social network, the location‐aware influence maximization problem aims to find a set of seed users such that the information spread from these users will reach the most users within the target area. We show that the problem is NP‐hard and present an approximate algorithm framework, namely, TarIM‐SF, which leverages on a popular sampling method as well as spatial filtering model working on arbitrary polygons. Besides, for the large‐scale network we also present a coarsening strategy to further improve the efficiency. We theoretically show that our approximate algorithm can provide a guarantee on the seed quality. Experimental study over three real‐world social networks verified the seed quality of our framework, and the coarsening‐based algorithm can provide superior efficiency.
Efficient Biocatalytic Synthesis of Chiral Intermediate of Pregabalin Using Immobilized Talaromyces thermophilus Lipase
Authors: Ding Xu , Tang Xiao-Ling , Zheng Ren-Chao , Zheng Yu-Guo
Published: November 2018

A mutant L206F/P207F/L259F of Talaromyces thermophilus lipase (TTL) exhibited high hydrolytic activity towards 2-carboxyethyl-3-cyano-5-methylhexanoic acid ethyl ester (CNDE) for synthesis of (S)-2-carboxyethyl-3-cyano-5-methylhexanoic acid (S-CCMA), a key chiral intermediate of pregabalin. However, low conversion at high CNDE concentration and unreusability of the free TTL mutant restricted its industrial applications. In this study, the TTL mutant was immobilized onto epoxy resin and its catalytic properties for kinetic resolution of CNDE were investigated. Under the optimized conditions, the immobilized lipase exhibited an increased catalytic efficiency even at a CNDE concentration of 3 M with 49.7% conversion and 95% eep. The conversion retained higher than 46.3% even after 10 times repeated use of the immobilized lipase in n-heptane-water biphasic system. These results demonstrated great potential of the immobilized TTL mutant for industrial production of the chiral intermediate of pregabalin.
Challenges for Air Transport Providers in Czech Republic and Poland
Authors: Toruń Anna , Burniak Czesław , Biały Jerzy , Tomaszewska Justyna , Grzesik Norbert , Hoskova-Mayerova Sarka , Woch Marta , Zieja Mariusz , Rurak Adam
Published: November 2018

The aim of this paper is to find a trend in air transport behaviour in the Czech Republic and Poland, based on data collected between the years of 2004 and 2016. The choice of data period for the analysis was made because of the date when both mentioned countries joined the European Union and availability of data. The data used in this article is provided from the Eurostat web page where many revealing statistics are collected. The correlations of indicators were chosen as a method of the analysis. It was observed that the number of passengers increased up to 30% and 460%, respectively, in the Czech Republic and in Poland. The authors will explain possible reasons and aspects of such behaviour in order to make some predictions for future trends in air transport. The additional aim is to understand transport processes and economic growth in neighbouring countries during the period of focus. The knowledge of conditional changes in the number of passengers utilizing air transport grants the ability to make forecasts about the needed infrastructure, number of aircrafts, pilots, and staff needed at the airports.
Exergy Analysis of Two Kinds of Solar-Driven Cogeneration Systems in Lhasa, Tibet, China
Authors: Zhang Haofei , Lei Bo , Yu Tao , Zhao Zhida
Published: November 2018

In this study, an exergy analysis of two kinds of solar-driven cogeneration systems consisting of solar collectors and an organic Rankine cycle (ORC) is presented for series mode and parallel mode. Three kinds of solar collectors are considered: flat-plate collectors (FPC), evacuated tube collectors (ETC), and parabolic trough collectors (PTC). This study mainly compares the exergy output of the two kinds of solar cogeneration systems under different temperatures of the return heating water and different inlet temperatures of the solar collectors. This study shows that, from the perspective of Wnet or E̲n, the parallel mode is superior to the series mode. From the perspective of Ez, the parallel mode is superior to the series mode when the solar collector is FPC; however, the series mode is superior to the parallel mode when the solar collector is PTC. When the solar collector is ETC, the result depends on the temperature of the return heating water. When the temperature of the return heating water is low (below 46°C), the series mode is better, and when the temperature of the return heating water is high (above 46°C), the parallel mode is better.
Embedding Undersampling Rotation Forest for Imbalanced Problem
Authors: Guo Huaping , Diao Xiaoyu , Liu Hongbing
Published: November 2018

Rotation Forest is an ensemble learning approach achieving better performance comparing to Bagging and Boosting through building accurate and diverse classifiers using rotated feature space. However, like other conventional classifiers, Rotation Forest does not work well on the imbalanced data which are characterized as having much less examples of one class (minority class) than the other (majority class), and the cost of misclassifying minority class examples is often much more expensive than the contrary cases. This paper proposes a novel method called Embedding Undersampling Rotation Forest (EURF) to handle this problem (1) sampling subsets from the majority class and learning a projection matrix from each subset and (2) obtaining training sets by projecting re-undersampling subsets of the original data set to new spaces defined by the matrices and constructing an individual classifier from each training set. For the first method, undersampling is to force the rotation matrix to better capture the features of the minority class without harming the diversity between individual classifiers. With respect to the second method, the undersampling technique aims to improve the performance of individual classifiers on the minority class. The experimental results show that EURF achieves significantly better performance comparing to other state-of-the-art methods.
Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach
Authors: Krishnagopal Sanjukta , Aloimonos Yiannis , Girvan Michelle
Published: November 2018

We investigate the ways in which a machine learning architecture known as Reservoir Computing learns concepts such as “similar” and “different” and other relationships between image pairs and generalizes these concepts to previously unseen classes of data. We present two Reservoir Computing architectures, which loosely resemble neural dynamics, and show that a Reservoir Computer (RC) trained to identify relationships between image pairs drawn from a subset of training classes generalizes the learned relationships to substantially different classes unseen during training. We demonstrate our results on the simple MNIST handwritten digit database as well as a database of depth maps of visual scenes in videos taken from a moving camera. We consider image pair relationships such as images from the same class; images from the same class with one image superposed with noise, rotated 90°, blurred, or scaled; images from different classes. We observe that the reservoir acts as a nonlinear filter projecting the input into a higher dimensional space in which the relationships are separable; i.e., the reservoir system state trajectories display different dynamical patterns that reflect the corresponding input pair relationships. Thus, as opposed to training in the entire high‐dimensional reservoir space, the RC only needs to learns characteristic features of these dynamical patterns, allowing it to perform well with very few training examples compared with conventional machine learning feed‐forward techniques such as deep learning. In generalization tasks, we observe that RCs perform significantly better than state‐of‐the‐art, feed‐forward, pair‐based architectures such as convolutional and deep Siamese Neural Networks (SNNs). We also show that RCs can not only generalize relationships, but also generalize combinations of relationships, providing robust and effective image pair classification. Our work helps bridge the gap between explainable machine learning with small datasets and biologically inspired analogy‐based learning, pointing to new directions in the investigation of learning processes.
A Network Pharmacology Approach to Uncover the Mechanisms of Shen‐Qi‐Di‐Huang Decoction against Diabetic Nephropathy
Authors: Di Sha , Han Lin , Wang Qing , Liu Xinkui , Yang Yingying , Li Fan , Zhao Linhua , Tong Xiaolin
Published: November 2018

Shen‐Qi‐Di‐Huang decoction (SQDHD), a well‐known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein‐protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine‐mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.
Improved Interference Cancelation Channel Estimation Method in OFDM/OQAM System
Authors: Qiu Shangfei , Xue Lunsheng , Wu Peng
Published: November 2018

To the significant amount of pilot overhead of the interference cancelation methods in orthogonal frequency division multiplexing (OFDM) based on offset quadrature amplitude modulation (OFDM/OQAM) system, we proposed an improved interference cancelation method (ICM) for OFDM/OQAM system in this paper. In this method, we use the auxiliary pilot (AP) to eliminate the influence of the intersymbol interference on channel estimation, which can reduce the pilot overhead of OFDM/OQAM system significantly. At the same time, to improve the channel estimation performance, we analyze the source of the intrinsic interference of system and its distribution in time and frequency domain, then, we reset the interference cancelation range of AP, which can cancel more intrinsic interference for OFDM/OQAM system. According to the results of performance analysis, compared to the conventional interference cancelation methods, the proposed method performs better in terms of energy efficiency and spectral efficiency. Also, the simulation results of the proposed method show that the proposed method can outperform traditional interference cancelation methods in channel estimation performance.
Efficient Processing of Moving Top‐k Spatial Keyword Queries in Directed and Dynamic Road Networks
Authors: Attique Muhammad , Cho Hyung-Ju , Chung Tae-Sun
Published: November 2018

A top‐k spatial keyword (TkSk) query ranks objects based on the distance to the query location and textual relevance to the query keywords. Several solutions have been proposed for top‐k spatial keyword queries. However, most of the studies focus on Euclidean space or only investigate the snapshot queries where both the query and data object are static. A few algorithms study TkSk queries in undirected road networks where each edge is undirected and the distance between two points is the length of the shortest path connecting them. However, TkSk queries have not been thoroughly investigated in directed and dynamic spatial networks where each edge has a particular orientation and its weight changes according to the traffic conditions. Therefore, in this study, we address this problem by presenting a new method, called COSK, for processing continuous top‐k spatial keyword queries for moving queries in directed and dynamic road networks. We first propose an efficient framework to process snapshot TkSK queries. Furthermore, we propose a safe‐exit‐based approach to monitor the validity of the results for moving TkSK queries. Our experimental results demonstrate that COSK significantly outperforms existing techniques in terms of query processing time and communication cost.
Region Space Guided Transfer Function Design for Nonlinear Neural Network Augmented Image Visualization
Authors: Yang Fei , Meng Xiangxu , Lang JiYing , Lu Weigang , Liu Lei
Published: November 2018

Visualization provides an interactive investigation of details of interest and improves understanding the implicit information. There is a strong need today for the acquisition of high quality visualization result for various fields, such as biomedical or other scientific field. Quality of biomedical volume data is often impacted by partial effect, noisy, and bias seriously due to the CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) devices, which may give rise to an extremely difficult task of specifying transfer function and thus generate poor visualized image. In this paper, firstly a nonlinear neural network based denoising in the preprocessing stage is provided to improve the quality of 3D volume data. Based on the improved data, a novel region space with depth based 2D histogram construction method is then proposed to identify boundaries between materials, which is helpful for designing the proper semiautomated transfer function. Finally, the volume rendering pipeline with ray-casting algorithm is implemented to visualize several biomedical datasets. The noise in the volume data is suppressed effectively and the boundary between materials can be differentiated clearly by the transfer function designed via the modified 2D histogram.
On FTCS Approach for Box Model of Three-Dimension Advection-Diffusion Equation
Authors: Kusuma Jeffry , Ribal Agustinus , Mahie Andi Galsan
Published: November 2018

This paper describes a numerical solution for mathematical model of the transport equation in a simple rectangular box domain. The model of street tunnel pollution distribution using two-dimension advection and three-dimension diffusion is solved numerically. Because of the nature of the problem, the model is extended to become three-dimension advection and three-dimension diffusion to study the sea-sand mining pollution distribution. This model with various advection and diffusion parameters and the boundaries conditions is also solved numerically using a finite difference (FTCS) method.
Use of a Biomimetic Scaffold for the Treatment of Osteochondral Lesions in Early Osteoarthritis
Authors: Condello Vincenzo , Filardo Giuseppe , Madonna Vincenzo , Andriolo Luca , Screpis Daniele , Bonomo Marco , Zappia Marcello , Dei Giudici Luca , Zorzi Claudio
Published: November 2018

The aim of this study is to investigate clinical and radiographic outcomes of a biomimetic scaffold for the treatment of osteochondral knee lesions in patients with early OA. Study population was represented by 26 patients with a mean age of 44 years affected by early OA. Inclusion criteria were two episodes of knee pain for more than 10 days in the last year, Kellgren-Lawrence OA grade 0 or I or II, and arthroscopic findings of cartilage defects. Nineteen patients had a previous surgery, 11 of which were revision surgeries of osteochondral unit. All patients were treated with a biomimetic scaffold with a tri-layered structure of type I equine collagen and magnesium-enriched hydroxyapatite. Clinical outcomes were evaluated using the IKDC, Lysholm, VAS, KOOS, and Tegner scores at baseline and at an average follow-up of 35 months. Magnetic resonance imaging (MRI) was performed at follow-up time in 19 patients. Clinical outcomes showed significant improvement in VAS, Lysholm, IKDC subjective score, and KOOS subscales in 69% of the patients. Complication rate of this cases series was 11%, with no surgical failure, although 31% of patients did not reach a significant improvement and were thus considered as clinical failure. MRI analysis showed integration of the scaffold only in 47% of the patients, with partial regeneration of the subchondral bone. No correlation between clinics and radiological images was found. The use of a biomimetic osteochondral scaffold in the setting of an early OA, alone or associated with other procedures, appeared to be a valid and safe option, able to provide good and stable clinical outcomes with high patient’s satisfaction and low complication rate.
Functionalization of Gadolinium Chelates Silica Nanoparticle through Silane Chemistry for Simultaneous MRI/64Cu PET Imaging
Authors: Tran Vu-Long , Thakare Vivek , Natuzzi Marco , Moreau Mathieu , Oudot Alexandra , Vrigneaud Jean-Marc , Courteau Alan , Louis Cédric , Roux Stéphane , Boschetti Frédéric , Denat Franck , Tillement Olivier , Lux François
Published: November 2018

Multimodal nanoprobes are highly demanded for biomedical imaging applications to enhance the reliability of the diagnostic results. Among different types of nano-objects, ultrasmall silica gadolinium nanoparticle (SiGdNP) appears as a safe, effective, and versatile platform for this purpose. In this study, a new method to functionalize SiGdNP based on silane chemistry has been reported. Two types of chelating silanes (APTES-DOTAGA and APTES-NODAGA) have been synthesized and grafted on SiGdNP by a simple one-step protocol. This functionalization strategy requires no other reactants or catalyzers and does not compromise the ultrasmall size of the particles. NODAGA-functionalized particle has been labeled with 64Cu isotope and injected intravenously to mice bearing TS/A carcinoma tumor for biodistribution study to demonstrate its potential as a bimodal MRI/PET imaging agent. A fully integrated MRI/PET system was used to simultaneously monitor the distribution of the particle. The results showed that the functionalized particle maintained properties of a renal clearable NP which could rapidly escape through kidneys and had low retention in other organs, especially liver, even though its accumulation in the tumor was modest.
Modified Weights‐of‐Evidence Modeling with Example of Missing Geochemical Data
Authors: Zhang Daojun , Agterberg Frits
Published: November 2018

Weights of evidence (WofE) and logistic regression (LR) are two loglinear methods for mineral potential mapping. Both models are limited by their respective basic assumptions in application. Ideally, WofE indicator patterns have the property of conditional independence (CI) with respect to the point pattern of mineral deposits to be predicted; in LR, there supposedly are no interactions between the point pattern and two or more of the indicator patterns. If the CI assumption is satisfied, estimated LR coefficients become approximately equal to WofE contrasts and the two methods produce similar results; additionally, bias then is avoided in that the sum of all estimated posterior probabilities becomes approximately equal to the number of observed discrete events. WofE allows construction of input layers that have missing data as a separate category in addition to known presence‐absence type input, while logistic regression as such is not capable of handling missing data. As an improved WofE model based on LR, modified weights of evidence (MWofE) inherit the advantages of both LR and WofE, i.e., eliminates bias due to lack of CI and can handle missing data as well. Pixel or unit area input for MWofE consists of positive and negative weights for presence and absence of a pattern plus zeros for missing data. MWofE first is illustrated by application to simple examples. Next, it is applied to a study area with 20 known gold occurrences in southwestern Nova Scotia in relation to four input layers based on geological and lake geochemical data. Assuming that geochemical data were missing for the northern part of the study area, MWofE, like WofE but unlike LR, provides posterior probabilities for the entire area.
A Novel Sparse False Data Injection Attack Method in Smart Grids with Incomplete Power Network Information
Authors: Zhong Huixin , Du Dajun , Li Chuanjiang , Li Xue
Published: November 2018

The paper investigates a novel sparse false data injection attack method in a smart grid (SG) with incomplete power network information. Most existing methods usually require the known complete power network information of SG. The main objective of this paper is to propose an effective sparse false data injection attack strategy under a more practical situation where attackers can only have incomplete power network information and limited attack resources to access the measurements. Firstly, according to the obtained measurements and power network information, some incomplete power network information is compensated by using the power flow equation approach. Then, the fault tolerance range of bad data detection (BDD) for the attack residual increment is estimated by calculating the detection threshold of the residual L2‐norm test. Finally, an effective sparse imperfect strategy is proposed by converting the choice of measurements into a subset selection problem, which is solved by the locally regularized fast recursive (LRFR) algorithm to effectively improve the sparsity of attack vectors. Simulation results on an IEEE 30‐bus system and a real distribution network system confirm the feasibility and effectiveness of the proposed new attack construction method.
Numerical Investigation of Combustion Characteristics of a Wave Rotor Combustor Based on a Reduced Reaction Mechanism of Ethylene
Authors: Li Jianzhong , Yuan Li , Li Wei , Zhang Kaichen
Published: November 2018

To improve simulations of the flame and pressure wave propagation process and investigate the combustion characteristics of a wave rotor combustor (WRC), direct relation graphs with error propagation (DRGEP), quasi-steady-state assumption (QSSA), and sensitivity analysis were used to establish a reduced reaction mechanism comprised of 23 species and 55 elementary reactions, based on the LLNL N-Butane mechanism. The reduced reaction mechanism of ethylene was combined with an eddy dissipation concept (EDC) model to simulate the flame propagation characteristics in a simplified WRC channel. The effects of spoilers with different blockage ratios and hot-jets of different species on combustion characteristics of flame propagation and pressure rise in the WRC channel were investigated. When the heated inert air was used as hot-jet, the ignition delay time of WRC would increase, which indicated that the activity of the burned gas from the hot-jet igniter would affect the ignition delay time. The spoiler facilitates the coupling of flame and shock waves to reduce the coupling time and distance. With the blockage ratio of the spoiler increasing, the coupling time and distance would be reduced.
Investigation and Suppression of Fiber Nonlinearities Using Injection-Locking in OFDM-WDM System
Authors: Nehra Monika , Kedia Deepak
Published: November 2018

The fiber nonlinearities play a major role in optical communication with respect to the system performance and transmission capacity. Here, fiber nonlinear impairments are investigated through consideration of several parameters of optical fiber system, such as fiber length and core effective area. We also demonstrate the mitigation of fiber nonlinearities by using single-stage injection-locking in 3 × 10 Gb/s OFDM-WDM system. This paper focuses on selection of appropriate bias current for slave laser to suppress the four wave mixing (FWM) crosstalk effects. These findings resemble the importance of single-stage injection-locking for FWM suppression for high-speed data communication.
An Improved Multiobjective Quantum‐Behaved Particle Swarm Optimization Based on Double Search Strategy and Circular Transposon Mechanism
Authors: Han Fei , Sun Yu-Wen-Tian , Ling Qing-Hua
Published: November 2018

Although multiobjective particle swarm optimization (MOPSO) has good performance in solving multiobjective optimization problems, how to obtain more accurate solutions as well as improve the distribution of the solutions set is still a challenge. In this paper, to improve the convergence performance of MOPSO, an improved multiobjective quantum‐behaved particle swarm optimization based on double search strategy and circular transposon mechanism (MOQPSO‐DSCT) is proposed. On one hand, to solve the problem of the dramatic diversity reduction of the solutions set in later iterations due to the single search pattern used in quantum‐behaved particle swarm optimization (QPSO), the double search strategy is proposed in MOQPSO‐DSCT. The particles mainly learn from their personal best position in earlier iterations and then the particles mainly learn from the global best position in later iterations to balance the exploration and exploitation ability of the swarm. Moreover, to alleviate the problem of the swarm converging to local minima during the local search, an improved attractor construction mechanism based on opposition‐based learning is introduced to further search a better position locally as a new attractor for each particle. On the other hand, to improve the accuracy of the solutions set, the circular transposon mechanism is introduced into the external archive to improve the communication ability of the particles, which could guide the population toward the true Pareto front (PF). The proposed algorithm could generate a set of more accurate and well‐distributed solutions compared to the traditional MOPSO. Finally, the experiments on a set of benchmark test functions have verified that the proposed algorithm has better convergence performance than some state‐of‐the‐art multiobjective optimization algorithms.
Examining the Intergovernmental and Interorganizational Network of Responding to Major Accidents for Improving the Emergency Management System in China
Authors: Tang Pan , Chen Haojia , Shao Shiqi
Published: November 2018

Since the SARS crisis in 2003, institutionalized emergency management systems have been established in each government level for improving inter‐organizational collaboration in China. Major accidents require participation of public organizations affiliated with multiple government levels, and the lack of collaboration and coordination among the involved organizations within the critical time constraints during the response process is an existing problem. In this research, a case study of examining the intergovernmental and cross‐sectoral collaboration for responding to a well‐known oil pipeline explosion accident in China by a complex network method is conducted. The aim is to obtain managerial insights in improving the existing emergency management system in a centralized political‐administrative context, such as China. A mixed method of data collection is applied to identify the participating organizations and to determine the interaction spanning organizational boundaries in both hierarchical and horizontal dimensions. An emergency response network is built and visualized for representing intergovernmental and interorganizational collaboration during the response process of the major accident by social network analysis (SNA) tools. The SNA indicators are used to measure quantitatively the network structure at the levels of the whole network, subnetwork, and node. The obstacles of achieving intergovernmental collaboration are found, and managerial suggestions for improving the existing emergency management system are provided. This research indicates that the Chinese government should pay attention to establishing and sustaining partnerships with private and nonprofit organizations and conduct a blend of hierarchical, market, and network principles in fostering collaboration for addressing major accidents. The public organizations in the local government level are shown to be more active than other participators in coordinating their response operations, and their capability should be emphasized for improvement. Additionally, the interactive relationships among specific emergency function groups and between the affected communities and organizations performing emergency command and coordination function should be strengthened.
Large Scale Experiments Representing a Containment Natural Circulation Loop during an Accident Scenario
Authors: Kapulla R. , Mignot G. , Paranjape S. , Andreani M. , Paladino D.
Published: November 2018

The assessment of hydrogen release, distribution, and mitigation measures in the containment of a nuclear power plant is increasingly based on code calculations. These calculations require state-of-the-art experiments to benchmark the codes against them. Two of these experiments are presented in this paper. These experiments were conducted in the PANDA facility (Switzerland) in the framework of the OECD/NEA HYMERES project. The experiments consider natural circulation flow in a two-room type containment where flow loops can form between the inner and the outer zones. During normal operation these zones are separated and in the case of an accident they become either connected by the opening of rupture disks, convective foils, and dampers or connected by bursting of doors and opening of other connections between compartments. For the experiments considered here one lower PANDA-vessel represents the steam generator (SG) tower and the inaccessible area whereas the other vessel represents the outer room area. The lower vessels are isolated from one another except for a small aperture that represents the damper. The two upper vessels—representing the containment dome—are connected to the lower vessels through tubes. The scenario consisted of four phases. In phase 1, a high steam mass flow rate was injected in the vessel representing the SG tower. After the relaxation phase 2, helium (representing hydrogen) was injected in the same vessel (phase 3). Finally in phase 4 no active interventions were done until the end of the test. Two tests were conducted to evaluate the developing helium transport by the natural circulation flow: one with and one without damper (by closing the aperture). The results showed that a two-room containment (TRC) mixing scenario can be well represented with the PANDA facility. It is found that, with the mixing damper open, a global natural circulation loop develops over all four vessels, whereas with closed damper the natural circulation loop is established only between the three vessels representing the inner zone and the upper dome. It is shown that the presence of the damper has a strong effect on the resulting helium content in the inner zone with 3 times less helium at the end of the test compared with the configuration without damper. The formation of a stable helium stratification in the upper vessels was observed in the presence of the open damper.
An Improved Nishihara Model for Frozen Loess considering the Influence of Temperature
Authors: Li Xin , Liu Enlong , Song Bingtang , Liu Xingyan
Published: November 2018

A series of triaxial creep tests under the constant confining pressure are performed on frozen loess specimens, and the creep behavior of the frozen loess with respect to variations in both temperature and deviator stress is examined. Experimental results illustrate that the frozen loess specimens present the attenuation creep at the lower deviatoric stress, whereas the nonattenuation creep under the higher deviatoric stress level, and with a drop in the temperature, the deviator stress value which the exhibition of nonattenuation creep needs will increase under the constant confining pressure condition. According to the microscopic analysis on deformation characteristics in the creep process of frozen soil, both temperature and external stress will cause the hardening and weakening effects, affecting the creep properties of frozen loess. By introducing the hardening variable and damage variable to consider the hardening and weakening effects of the frozen loess, an improved Nishihara model is proposed. The correlations between model parameters and the temperature as well as deviator stress are determined. The comparisons between model predictions and experimental results show that the improved creep constitutive model proposed here can not only describe the whole creep process well, but also reveal the influences of the temperature and deviator stress on the creep behavior of frozen loess, which demonstrate its accuracy and usefulness.