bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Carrier Lipophilicity and Preparation Method on the Properties of Andrographolide–Solid Dispersion
Authors: Zhao Guowei , Zeng Qingyun , Zhang Shoude , Zhong Youquan , Wang Changhao , Chen Yashao , Ou Liquan , Liao Zhenggen
Published: February 2019

Solid dispersion (SD) is a useful approach to improve the dissolution rate and bioavailability of poorly water-soluble drugs. This work investigated the effects of carrier material lipophilicity and preparation method on the properties of andrographolide (AG)–SD. The SDs of AG and the carrier materials, polyethylene glycol (PEG) and PEG grafted with carbon chains of different length (grafted PEG), have been prepared by spray-drying and vacuum-drying methods. In AG–SDs prepared by the different preparation methods with the same polymer as carrier material, the intermolecular interaction, 5% weight-loss temperature, the melting temperature (Tm), surface morphology, crystallinity, and dissolution behavior have significant differences. In the AG–SDs prepared by the same spray-drying method with different grafted PEG as carrier material, Tm, surface morphology, crystallinity, and dissolution behavior had little difference. In the AG–SDs prepared by the same vacuum-drying method with different grafted PEG as carrier material, the crystallinity and Tm decreased, and the dissolution rate of AG increased with the increase of grafted PEG lipophilicity. The preparation method has an important effect on the properties of SD. The increase of carrier material lipophilicity is beneficial to the thermal stability of SD, the decrease of crystallinity and the increase of dissolution rate of a poorly water-soluble drug in the SD.
Thermal Healing, Reshaping and Ecofriendly Recycling of Epoxy Resin Crosslinked with Schiff Base of Vanillin and Hexane-1,6-Diamine
Authors: Mai Van-Dung , Shin Se-Ra , Lee Dai-Soo , Kang Ilho
Published: February 2019

A bio-derived dihydroxylimine hardener, Van2HMDA, for the curing of epoxy resin was prepared from vanillin (Van) and hexamethylene-1,6-diamine (HMDA) by Schiff base formation. The epoxy resin of diglycidyl ether of bisphenol A was cured with Van2HMDA in the presence of the catalyst, 2-ethyl-4-methylimidazole (EMI). The crosslinked epoxy resin showed thermal-healing properties at elevated temperatures. Moreover, the crosslinked epoxy resin can be reshaped by heating via imine metathesis of the hardener units. The imine metathesis of Van2HMDA was confirmed experimentally. Stress-relaxation properties of the epoxy resin crosslinked with Van2HMDA were investigated, and the activation energy obtained from Arrhenius plots of the relaxation times was 44 kJ/mol. The imine bonds in the epoxy polymer matrix did not undergo hydrolysis after immersing in water at room temperature for one week. However, in the presence of acid, the crosslinked polymer was easily decomposed due to the hydrolysis of imine bonds. The hydrolysis of imine bonds was used for the ecofriendly recycling of crosslinked polymer. It is inferred that thermal-healing, reshaping, and reprocessing properties can be implemented in the various crosslinked epoxy resins with the bio-derived dihydroxylimine hardener, albeit the recycled epoxy resin is of inevitably lower quality than the original material.
Estimation of Leaf Inclination Angle in Three-Dimensional Plant Images Obtained from Lidar
Authors: Itakura Kenta , Hosoi Fumiki
Published: February 2019

The leaf inclination angle is a fundamental variable for determining the plant profile. In this study, the leaf inclination angle was estimated automatically from voxel-based three-dimensional (3D) images obtained from lidar (light detection and ranging). The distribution of the leaf inclination angle within a tree was then calculated. The 3D images were first converted into voxel coordinates. Then, a plane was fitted to some voxels surrounding the point (voxel) of interest. The inclination angle and azimuth angle were obtained from the normal. The measured leaf inclination angle and its actual value were correlated and indicated a high correlation (R2 = 0.95). The absolute error of the leaf inclination angle estimation was 2.5°. Furthermore, the leaf inclination angle can be estimated even when the distance between the lidar and leaves is about 20 m. This suggests that the inclination angle estimation of leaves in a top part is reliable. Then, the leaf inclination angle distribution within a tree was calculated. The difference in the leaf inclination angle distribution between different parts within a tree was observed, and a detailed tree structural analysis was conducted. We found that this method enables accurate and efficient leaf inclination angle distribution.
Performance of Multi-GNSS Precise Point Positioning Time and Frequency Transfer with Clock Modeling
Authors: Ge Yulong , Dai Peipei , Qin Weijin , Yang Xuhai , Zhou Feng , Wang Shengli , Zhao Xingwang
Published: February 2019

Thanks to the international GNSS service (IGS), which has provided multi-GNSS precise products, multi-GNSS precise point positioning (PPP) time and frequency transfer has of great interest in the timing community. Currently, multi-GNSS PPP time transfer is not investigated with different precise products. In addition, the correlation of the receiver clock offsets between adjacent epochs has not been studied in multi-GNSS PPP. In this work, multi-GNSS PPP time and frequency with different precise products is first compared in detail. A receiver clock offset model, considering the correlation of the receiver clock offsets between adjacent epochs using an a priori value, is then employed to improve multi-GNSS PPP time and frequency (scheme2). Our numerical analysis clarify how the approach performs for multi-GNSS PPP time and frequency transfer. Based on two commonly used multi-GNSS products and six GNSS stations, three conclusions are obtained straightforwardly. First, the GPS-only, Galileo-only, and multi-GNSS PPP solutions show similar performances using GBM and COD products, while BDS-only PPP using GBM products is better than that using COD products. Second, multi-GNSS time transfer outperforms single GNSS by increasing the number of available satellites and improving the time dilution of precision. For single-system and multi-GNSS PPP with GBM products, the maximum improvement in root mean square (RMS) values for multi-GNSS solutions are up to 7.4%, 94.0%, and 57.3% compared to GPS-only, BDS-only, and Galileo-only solutions, respectively. For stability, the maximum improvement of multi-GNSS is 20.3%, 84%, and 45.4% compared to GPS-only, BDS-only and Galileo-only solutions. Third, our approach contains less noise compared to the solutions with the white noise model, both for the single-system model and the multi-GNSS model. The RMS values of our approach are improved by 37.8–91.9%, 10.5–65.8%, 2.7–43.1%, and 26.6–86.0% for GPS-only, BDS-only, Galileo-only, and multi-GNSS solutions. For frequency stability, the improvement of scheme2 ranges from 0.2 to 51.6%, from 3 to 80.0%, from 0.2 to 70.8%, and from 0.1 to 51.5% for GPS-only, BDS-only, Galileo-only, and multi-GNSS PPP solutions compared to the solutions with the white noise model in the Eurasia links.
Direction-of-Arrival Estimation in Coprime Array Using the ESPRIT-Based Method
Authors: Meng Zhen , Zhou Weidong
Published: February 2019

Coprime arrays have shown potential advantages for direction-of-arrival (DOA) estimation by increasing the number of degrees-of-freedom in the difference coarray domain with fewer physical sensors. In this paper, a new DOA estimation algorithm for coprime array based on the estimation of signal parameter via rotational invariance techniques (ESPRIT) is proposed. We firstly derive the observation vector of the virtual uniform linear array but the covariance matrix of this observation vector is rank-deficient. Different from the traditional Toeplitz matrix reconstruction method using the observation vector, we propose a modified Toeplitz matrix reconstruction method using any non-zero row of the covariance matrix in the virtual uniform linear array. It can be proved in theory that the reconstructed Toeplitz covariance matrix has full rank. Therefore, the improved ESPRIT method can be used for DOA estimation without peak searching. Finally, the closed-form solution for DOA estimation in coprime array is obtained. Compared to the traditional coprime multiple signal classification (MUSIC) methods, the proposed method circumvents the use of spatial smoothing technique, which usually results in performance degradation and heavy computational burden. The effectiveness of the proposed method is demonstrated by numerical examples.
Picking Towels in Point Clouds
Authors: Wang Xiaoman , Jiang Xin , Zhao Jie , Wang Shengfan , Yang Tao , Liu Yunhui
Published: February 2019

Picking clothing has always been a great challenge in laundry or textile industry automation, especially when some clothes are of the same colors, material and entangled with each other. In order to solve the problem, we present a grasp pose determination method to pick towels placed in a laundry basket or on a table. In our method, it is not needed to segment towels into independent items and the target towels are not necessarily distinguishable in color. The proposed algorithm firstly segments point clouds into several convex wrinkles, and then selects the appropriate grasp point on the candidate convex wrinkle. Moreover, we plan the grasp orientation with respect to the wrinkle which can effectively reduce the grasp failure caused by the inappropriate grasp direction. We evaluate our method on picking white towels and square towels, respectively, and achieved an average success rate of about 80%.
Recognition and Repetition Counting for Complex Physical Exercises with Deep Learning
Authors: Soro Andrea , Brunner Gino , Tanner Simon , Wattenhofer Roger
Published: February 2019

Activity recognition using off-the-shelf smartwatches is an important problem in human activity recognition. In this paper, we present an end-to-end deep learning approach, able to provide probability distributions over activities from raw sensor data. We apply our methods to 10 complex full-body exercises typical in CrossFit, and achieve a classification accuracy of 99.96%. We additionally show that the same neural network used for exercise recognition can also be used in repetition counting. To the best of our knowledge, our approach to repetition counting is novel and performs well, counting correctly within an error of ±1 repetitions in 91% of the performed sets.
A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
Authors: Luo Xin , Chen Dan , Wang Yongjun , Xie Peidai
Published: February 2019

Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often coarse-grained with the intrinsic type information hidden in messages largely ignored. Aiming at this problem, this study proposes a type-aware approach to message clustering guided by type information. The approach regards a message as a combination of n-grams, and it employs the Latent Dirichlet Allocation (LDA) model to characterize messages with types and n-grams via inferring the type distribution of each message. The type distribution is finally used to measure the similarity of messages. According to this similarity, the approach clusters messages and further extracts message formats. Experimental results of the approach against Netzob in terms of a number of protocols indicate that the correctness and conciseness can be significantly improved, e.g., figures 43.86% and 3.87%, respectively for the CoAP protocol.
Accurate 3D Shape, Displacement and Deformation Measurement Using a Smartphone
Authors: Yu Liping , Tao Ran , Lubineau Gilles
Published: February 2019

The stereo-digital image correlation technique using two synchronized industrial-grade cameras has been extensively used for full-field 3D shape, displacement and deformation measurements. However, its use in resource-limited institutions and field settings is inhibited by the need for relatively expensive, bulky and complicated experimental set-ups. To mitigate this problem, we established a cost-effective and ultra-portable smartphone-based stereo-digital image correlation system, which only uses a smartphone and an optical attachment. This optical attachment is composed of four planar mirrors and a 3D-printed mirror support, and can split the incoming scene into two sub-images, simulating a stereovision system using two virtual smartphones. Although such a mirror-based system has already been used for stereo-image correlation, this is the first time it has been combined with a commercial smartphone. This publication explores the potential and limitations of such a configuration. We first verified the effectiveness and accuracy of this system in 3D shape and displacement measurement through shape measurement and in-plane and out-of-plane translation tests. Severe thermal-induced virtual strains (up to 15,000 με) were found in the measured results due to the smartphone heating. The mechanism for the generation of the temperature-dependent errors in this system was clearly and reasonably explained. After a simple preheating process, the smartphone-based system was demonstrated to be accurate in measuring the strain on the surface of a loaded composite specimen, with comparable accuracy to a strain gauge. Measurements of 3D deformation are illustrated by tracking the deformation on the surface of a deflating ball. This cost-effective and ultra-portable smartphone-based system not only greatly decreases the hardware investment in the system construction, but also increases convenience and efficiency of 3D deformation measurements, thus demonstrating a large potential in resource-limited and field settings.
Energy/Area-Efficient Scalar Multiplication with Binary Edwards Curves for the IoT
Authors: Lara-Nino Carlos Andres , Diaz-Perez Arturo , Morales-Sandoval Miguel
Published: February 2019

Making Elliptic Curve Cryptography (ECC) available for the Internet of Things (IoT) and related technologies is a recent topic of interest. Modern IoT applications transfer sensitive information which needs to be protected. This is a difficult task due to the processing power and memory availability constraints of the physical devices. ECC mainly relies on scalar multiplication (kP)—which is an operation-intensive procedure. The broad majority of kP proposals in the literature focus on performance improvements and often overlook the energy footprint of the solution. Some IoT technologies—Wireless Sensor Networks (WSN) in particular—are critically sensitive in that regard. In this paper we explore energy-oriented improvements applied to a low-area scalar multiplication architecture for Binary Edwards Curves (BEC)—selected given their efficiency. The design and implementation costs for each of these energy-oriented techniques—in hardware—are reported. We propose an evaluation method for measuring the effectiveness of these optimizations. Under this novel approach, the energy-reducing techniques explored in this work contribute to achieving the scalar multiplication architecture with the most efficient area/energy trade-offs in the literature, to the best of our knowledge.
Household Power Demand Prediction Using Evolutionary Ensemble Neural Network Pool with Multiple Network Structures
Authors: Ai Songpu , Chakravorty Antorweep , Rong Chunming
Published: February 2019

The progress of technology on energy and IoT fields has led to an increasingly complicated electric environment in low-voltage local microgrid, along with the extensions of electric vehicle, micro-generation, and local storage. It is required to establish a home energy management system (HEMS) to efficiently integrate and manage household energy micro-generation, consumption and storage, in order to realize decentralized local energy systems at the community level. Domestic power demand prediction is of great importance for establishing HEMS on realizing load balancing as well as other smart energy solutions with the support of IoT techniques. Artificial neural networks with various network types (e.g., DNN, LSTM/GRU based RNN) and other configurations are widely utilized on energy predictions. However, the selection of network configuration for each research is generally a case by case study achieved through empirical or enumerative approaches. Moreover, the commonly utilized network initialization methods assign parameter values based on random numbers, which cause diversity on model performance, including learning efficiency, forecast accuracy, etc. In this paper, an evolutionary ensemble neural network pool (EENNP) method is proposed to achieve a population of well-performing networks with proper combinations of configuration and initialization automatically. In the experimental study, power demand predictions of multiple households are explored in three application scenarios: optimizing potential network configuration set, forecasting single household power demand, and refilling missing data. The impacts of evolutionary parameters on model performance are investigated. The experimental results illustrate that the proposed method achieves better solutions on the considered scenarios. The optimized potential network configuration set using EENNP achieves a similar result to manual optimization. The results of household demand prediction and missing data refilling perform better than the naïve and simple predictors.
Collective Anomalies Detection for Sensing Series of Spacecraft Telemetry with the Fusion of Probability Prediction and Markov Chain Model
Authors: Pang Jingyue , Liu Datong , Peng Yu , Peng Xiyuan
Published: February 2019

Telemetry series, generally acquired from sensors, are the only basis for the ground management system to judge the working performance and health status of orbiting spacecraft. In particular, anomalies within telemetry can reflect sensor failure, transmission errors, and the major faults of the related subsystem. Therefore, anomaly detection for telemetry series has drawn great attention from the aerospace area, where probability prediction methods, e.g., Gaussian process regression and relevance vector machine, have an inherent advantage for anomaly detection in time series with uncertainty presentation. However, labelling a single point with probability prediction faces many isolated false alarms, as well as a lower detection rate for collective anomalies that significantly limits its practical application. Simple sliding window fusion can decrease the false positives, but the support number of anomalies within the sliding window is difficult to set effectively for different series. Therefore, in this work, fused with the probability prediction-based method, the Markov chain is designed to compute the support probability of each testing series to realize the improvement on collective anomaly mode. The experiments on simulated data sets and the actual telemetry series validated the effectiveness and applicability of our proposed method.
A Wear Debris Segmentation Method for Direct Reflection Online Visual Ferrography
Authors: Feng Song , Qiu Guang , Luo Jiufei , Han Leng , Mao Junhong , Zhang Yi
Published: February 2019

Wear debris in lube oil was observed using a direct reflection online visual ferrograph (OLVF) to monitor the machine running condition and judge wear failure online. The existing research has mainly concentrated on extraction of wear debris concentration and size according to ferrograms under transmitted light. Reports on the segmentation algorithm of the wear debris ferrograms under reflected light are lacking. In this paper, a wear debris segmentation algorithm based on edge detection and contour classification is proposed. The optimal segmentation threshold is obtained by an adaptive canny algorithm, and the contour classification filling method is applied to overcome the problems of excessive brightness or darkness of some wear debris that is often neglected by traditional segmentation algorithms such as the Otsu and Kittler algorithms.
Establishment and Verification of the Cutting Grinding Force Model for the Disc Wheel Based on Piezoelectric Sensors
Authors: Ni Jing , Feng Kai , Al-Furjan M.S.H. , Xu Xiaojiao , Xu Jing
Published: February 2019

In this paper, a new model of cutting grinding force for disc wheels is presented. Initially, it was proposed that the grinding cutting force was formed by the grinding force and cutting force in combination. Considering the single-grit morphology, the single-grit average grinding depth, the effective number of grits, and the contact arc length between the grit and the workpiece comprehensively, the grinding force model and the cutting force model were established, respectively. Then, a universal grinding cutting force model was optimized by introducing the effective grit coefficient model, dependent on the probability statistical method and the grit height coefficient model with Rayleigh’s distribution theory. Finally, according to the different proportions of the grinding force and cutting force, the grinding cutting force model, with multi-particles, was established. Simulation and experimental results based on piezoelectric sensors showed that the proposed model could predict the intermittent grinding cutting force well. Moreover, the inclusion of the grit height coefficient and the effective grits number coefficient improved the modeling accuracy. The error between the simulation and experimental findings in grinding cutting force was reduced to 7.8% in comparison with the traditional model. In addition, the grinding cutting force can be divided into three segments; increasing, steadiness, and decreasing, respectively found through modeling.
Improving IoT Botnet Investigation Using an Adaptive Network Layer
Authors: Ceron João Marcelo , Steding-Jessen Klaus , Hoepers Cristine , Granville Lisandro Zambenedetti , Margi Cíntia Borges
Published: February 2019

IoT botnets have been used to launch Distributed Denial-of-Service (DDoS) attacks affecting the Internet infrastructure. To protect the Internet from such threats and improve security mechanisms, it is critical to understand the botnets’ intents and characterize their behavior. Current malware analysis solutions, when faced with IoT, present limitations in regard to the network access containment and network traffic manipulation. In this paper, we present an approach for handling the network traffic generated by the IoT malware in an analysis environment. The proposed solution can modify the traffic at the network layer based on the actions performed by the malware. In our study case, we investigated the Mirai and Bashlite botnet families, where it was possible to block attacks to other systems, identify attacks targets, and rewrite botnets commands sent by the botnet controller to the infected devices.
Hybrid Printed Energy Harvesting Technology for Self-Sustainable Autonomous Sensor Application
Authors: Kim Sangkil , Tentzeris Manos M. , Georgiadis Apostolos
Published: February 2019

In this paper, the far-field energy harvesting system for self-sustainable wireless autonomous sensor application is presented. The proposed autonomous sensor system consists of a wireless power supplier (active antenna) and far-field energy harvesting technology-enabled autonomous battery-less sensors. The wireless power supplier converts solar power to electromagnetic power in order to transfer power to multiple autonomous sensors wirelessly. The autonomous sensors have far-field energy harvesters which convert transmitted RF power to voltage regulated DC power to power-on the sensor system. The hybrid printing technology was chosen to build the autonomous sensors and the wireless power suppliers. Two popular hybrid electronics technologies (direct nano-particle printing and indirect copper thin film printing techniques) are discussed in detail.
Financial Resources for the Circular Economy: A Perspective from Businesses
Authors: Aranda-Usón Alfonso , Portillo-Tarragona Pilar , Marín-Vinuesa Luz , Scarpellini Sabina
Published: February 2019

In recent years, a number of case studies of the circular economy in business have been analysed by academics. However, some areas of research are little explored at the micro level, such as the study of the characteristics of the financial resources applied to investments to introduce circular activities in businesses. Therefore, the main objective of this study is to define the resources applied to circular activities by firms. To describe the influence of financial resources on achieving a more advanced circular economy in business is also an objective of this paper. Using a sample of Spanish companies, we applied a partial least square structural equation model (PLS-SEM) to enhance the knowledge about financial resource management in the framework of the resource-based view. We find that availability of funds, quality of the firm’s own financial resources and public subsidies have a positive effect in stimulating the implementation of circular economy initiatives in businesses.
It’s All in the SKU: Getting Food from Somewhere from the Field to the Dinner Plate while Using a Large Scale Retailer
Authors: Haythorn Carolyn M. , Knudsen Daniel C. , Farmer James R. , Antreasian Carmen C. , Betz Megan E.
Published: February 2019

The local food movement provides sustainable food, but often suffers from a lack of economic viability. We examine the need for concerned consumers, qualified growers, and responsible retailers. Concerned consumers are individuals who desire food from somewhere, but must shop at food retailers. Qualified growers sell sustainable food from somewhere, and must be able to set their own prices. Responsible retailers provide consumers with food from somewhere. Taken together, currently there is no good system in place to allow for large scale purchases and long term sales of food from somewhere for a retailer. To solve this, we propose a benevolent wholesaler model, in which stock keeping unit (SKU) numbers are given to each type of product from each farm. This enables tracking of the origin of the produce by retail customers and individual consumers, while retaining the attributes of a food system that allow for large scale purchases and long term sales. Such systems are no less sustainable, but potentially provide enhanced economic viability for producers.
The Concept of Risk Capital and Its Application in Non-Financial Companies: A Sustainable Dimension
Authors: Wieczorek-Kosmala Monika
Published: February 2019

The prime purpose of this paper is to explain the concept of risk capital and advocate for its implementation in the management of non-financial companies. The paper is kept in the discursive tone, as the problem is new, and it first requires to establish the conceptual framework for further empirical considerations. With reference to the origins of the concept of risk capital (related to its understanding in financial institutions), the paper discusses the utility of risk capital for the management of risk in non-financial companies, with the recognition of the sustainable dimension of risk capital. The discussion is framed within the corporate finance approach. In the applicative dimension, the paper identifies the universe of the sources of risk capital and proposes a taxonomy of these sources. It considers both the well-established traditional sources, as well as the state-of-the-art solutions that are in the early stages of their adoption for the needs of corporate end-users. The conclusions address the possible areas of tensions and of the inclusion of risk capital in the decision-making process, as well as the areas of further empirical research within.
Sustainable Development through the Right to Access to Justice in Environmental Matters in China
Authors: He Miao
Published: February 2019

Access to justice is an irreplaceable complementary right. Without enforcement, environmental law would be ‘toothless’ in practice. Recently, China has made some significant progress in protecting the relevant parties’ right to access to justice in environmental matters. However, there are still some problems and challenges in the protection of this right in theory and in practice. To effectively realize this right, it is necessary to analyze the present situations and problems of the right in China from a legal perspective. This is done by introducing and analyzing the laws, regulations, policies, and practice concerning the right to access to justice in environmental matters in China. Specifically, this paper discusses the present situations of this right from several aspects. Based thereon, a brief problems analysis will be made. Some possible suggestions on how to better protect the right in China will be proposed from the perspectives of engaging, effectiveness and efficiency. These suggestions include empowering various parties with more capacity and possibilities; establishing a legal aid system and special fund; improving the exemption system and attorney fee transfer system; establishing a pre-litigation examination mechanism; and stimulating various parties’ potential roles.
Introduction of Biodiesel to Rail Transport: Lessons from the Road Sector
Authors: Stead Charlotte , Wadud Zia , Nash Chris , Li Hu
Published: February 2019

Biodiesel is a potentially low-carbon, renewable alternative fuel to diesel, sharing similar chemical and physical properties to diesel. There have been significant efforts in introducing primarily bioethanol and some biodiesel to the road transport sector, with varying levels of success. However, the rail sector has not seen as large an effort in introducing biodiesel. This paper summarizes the literature on the introduction of biodiesel (bioethanol was a relevant fuel) in order to learn lessons, which can be applied to the rail transport sector. A decision-making framework PESTLE (Political/Policies, Economic, Social, Technological, Legal, and Environmental) is used to analyze these lessons, and their relevance (or not) to the rail sector. While introduction of biodiesel in the rail sector has some inherent advantages, such as fewer refueling points, customers and manufacturers compared to the road sector, it also faces some challenges, especially in the context of the longer life of locomotives, making fleet turnover and potential transition to 100% biodiesel slow. Additionally, maintenance costs are still uncertain.
A Continuous Coordinate System for the Plane by Triangular Symmetry
Authors: Nagy Benedek , Abuhmaidan Khaled
Published: February 2019

The concept of the grid is broadly used in digital geometry and other fields of computer science. It consists of discrete points with integer coordinates. Coordinate systems are essential for making grids easy to use. Up to now, for the triangular grid, only discrete coordinate systems have been investigated. These have limited capabilities for some image-processing applications, including transformations like rotations or interpolation. In this paper, we introduce the continuous triangular coordinate system as an extension of the discrete triangular and hexagonal coordinate systems. The new system addresses each point of the plane with a coordinate triplet. Conversion between the Cartesian coordinate system and the new system is described. The sum of three coordinate values lies in the closed interval [−1, 1], which gives many other vital properties of this coordinate system.
An Adaptive Strategy for Tuning Duplicate Trails in SAT Solvers
Authors: Chang Wenjing , Xu Yang , Chen Shuwei
Published: February 2019

In mainstream conflict driven clause learning (CDCL) solvers, because of frequent restarts and phase saving, there exists a large proportion of duplicate assignment trails before and after restarts, resulting in unnecessary time wastage during solving. This paper proposes a new strategy—identifying those duplicate assignments trails and dealing with them by changing the sort order. This approach’s performance is compared with that of the Luby static restart scheme and a dynamic Glucose-restart strategy. We show that the number of solved instances is increased by 3.2% and 4.6%. We also make a compassion with the MapleCOMSPS solver by testing against application benchmarks from the SAT Competitions 2015 to 2017. These empirical results provide further evidence of the benefits of the proposed heuristic, having the advantage of managing duplicate assignments trails and choosing appropriate decision variables adaptively.
Uncertainty Measurement for a Set-Valued Information System: Gaussian Kernel Method
Authors: He Jiali , Wang Pei , Li Zhaowen
Published: February 2019

A set-valued information system (SIS) is the generalization of a single-valued information system. This article explores uncertainty measurement for a SIS by using Gaussian kernel. The fuzzy T c o s -equivalence relation lead by a SIS is first obtained by using Gaussian kernel. Then, information structures in this SIS are described by set vectors. Next, dependence between information structures is presented and properties of information structures are investigated. Lastly, uncertainty measures of a SIS are presented by using its information structures. Moreover, effectiveness analysis is done to assess the feasibility of our presented measures. The consequence of this article will help us understand the intrinsic properties of uncertainty in a SIS.
Searches for Electric Dipole Moments—Overview of Status and New Experimental Efforts
Authors: Kuchler Florian , on behalf of the TUCAN and HeXeEDM Collaborations
Published: February 2019

Searches for permanent electric dipole moments (EDMs) of fundamental particles, atoms and molecules are promising experiments to constrain and potentially reveal beyond Standard Model (SM) physics. A non-zero EDM is a direct manifestation of time-reversal (T) violation, and, equivalently, violation of the combined operation of charge-conjugation (C) and parity inversion (P). Identifying new sources of CP violation can help to solve fundamental puzzles of the SM, e.g., the observed baryon-asymmetry in the Universe. Theoretical predictions for magnitudes of EDMs in the SM are many orders of magnitude below current experimental limits. However, many theories beyond the SM require larger EDMs. Experimental results, especially when combined in a global analysis, impose strong constraints on CP violating model parameters. Including an overview of EDM searches, I will focus on the future neutron EDM experiment at TRIUMF (Vancouver). For this effort, the TUCAN (TRIUMF Ultra Cold Advanced Neutron source) collaboration is aiming to build a strong, world leading source of ultra cold neutrons (UCN) based on a unique combination of a spallation target and a superfluid helium UCN converter. Another focus will be the search for an EDM of the diamagnetic atom 129 Xe using a 3 He comagnetometer and SQUID detection. The HeXeEDM collaboration has taken EDM data in 2017 and 2018 in the magnetically shielded room (BMSR-2) at PTB Berlin.
Horizon Areas and Logarithmic Correction to the Charged Accelerating Black Hole Entropy
Authors: Pradhan Parthapratim
Published: February 2019

It has been shown by explicit and exact calculation that the geometric product formula i.e., area (or entropy) product formula of outer horizon ( H + ) and inner horizon ( H − ) for charged accelerating black hole (BH) should neither be mass-independent nor quantized. This implies that the area (or entropy ) product is mass-independent conjecture has been broken down for charged accelerating BH. This also further implies that the mass-independent feature of the area product of H ± is not a generic feature at all. We also compute the Cosmic-Censorship-Inequality for this BH. Moreover, we compute the specific heat for this BH to determine the local thermodynamic stability. Under certain criterion, the BH shows the second order phase transition. Furthermore, we compute logarithmic corrections to the entropy for the said BH due to small statistical fluctuations around the thermal equilibrium.
Complementary Role of CD4+ T Cells in Response to Pneumococcal Polysaccharide Vaccines in Humans
Authors: Jha Vibha , Janoff Edward N.
Published: February 2019

Bacterial pathogens expressing capsular polysaccharides are common causes of mucosal infections (pneumonia, intestinal), as well as often fatal, invasive infections (meningitis, bloodstream infections) in children and adults worldwide. These chemically simple but structurally complex carbohydrate structures on the bacterial surface confer resistance to recognition and clearance by the immune system through a range of mechanisms. Such recognition of capsular polysaccharides may be reduced by their limited ability to directly stimulate B cells and the T cells that may facilitate these humoral responses. The capsules may promote the evasion of complement deposition and activation and may sterically shield the recognition of other subjacent protein antigens by innate factors. Antibodies to capsular polysaccharides, elicited by infection and vaccines, may overcome these obstacles and facilitate bacterial agglutination at mucosal surfaces, as well as the opsonization and clearance of these organisms in tissues and the systemic compartment. However, the immunogenicity of these antigens may be limited by their lack of direct recognition by T cells (“T-independent” antigens) and their restricted ability to generate effective memory responses. In this review, we consider the mechanisms by which polysaccharides may initiate B cell responses and specific antibody responses and the role of T cells, particularly CD4+ follicular helper (TFH) cells to support this process. In addition, we also consider more recent counterintuitive data that capsular polysaccharides themselves may bind major histocompatibility antigen HLA class II to provide a more physiologic mechanism of T cell enhancement of B cell responses to capsular polysaccharides. Defining the contributions of T cells in the generation of effective humoral responses to the capsular polysaccharides will have important implications for understanding and translating this immunobiology for the development of more effective vaccines, to prevent the morbidity and mortality associated with these common mucosal and invasive pathogens in populations at risk.
Reliability and Generalizability of Similarity-Based Fusion of MEG and fMRI Data in Human Ventral and Dorsal Visual Streams
Authors: Mohsenzadeh Yalda , Mullin Caitlin , Lahner Benjamin , Cichy Radoslaw Martin , Oliva Aude
Published: February 2019

To build a representation of what we see, the human brain recruits regions throughout the visual cortex in cascading sequence. Recently, an approach was proposed to evaluate the dynamics of visual perception in high spatiotemporal resolution at the scale of the whole brain. This method combined functional magnetic resonance imaging (fMRI) data with magnetoencephalography (MEG) data using representational similarity analysis and revealed a hierarchical progression from primary visual cortex through the dorsal and ventral streams. To assess the replicability of this method, we here present the results of a visual recognition neuro-imaging fusion experiment and compare them within and across experimental settings. We evaluated the reliability of this method by assessing the consistency of the results under similar test conditions, showing high agreement within participants. We then generalized these results to a separate group of individuals and visual input by comparing them to the fMRI-MEG fusion data of Cichy et al (2016), revealing a highly similar temporal progression recruiting both the dorsal and ventral streams. Together these results are a testament to the reproducibility of the fMRI-MEG fusion approach and allows for the interpretation of these spatiotemporal dynamic in a broader context.
Impacts of Antecedent Soil Moisture on the Rainfall-Runoff Transformation Process Based on High-Resolution Observations in Soil Tank Experiments
Authors: Song Shuang , Wang Wen
Published: February 2019

An experimental soil tank (12 m long × 1.5 m wide × 1.5 m deep) equipped with a spatially distributed instrument network was designed to conduct the artificial rainfall-runoff experiments. Soil moisture (SM), precipitation, surface runoff (SR) and subsurface runoff (SSR) were continuously monitored. A total of 32 rainfall-runoff events were analyzed to investigate the non-linear patterns of rainfall-runoff response and estimate the impact of antecedent soil moisture (ASM) on runoff formation. Results suggested that ASM had a significant impact on runoff at this plot scale, and a moisture threshold-like value which was close to field capacity existed in the relationship between soil water content and event-based runoff coefficient (φe), SSR and SSR/SR. A non-linear relationship between antecedent soil moisture index (ASI) that represented the initial storage capacity of the soil tank and total runoff was also observed. Response times of SR and SM to rainfall showed a marked variability under different conditions. Under wet conditions, SM at 10 cm started to increase prior to SR on average, whereas it responds slower than SR under dry conditions due to the effect of water repellency. The predominant contributor to SR generation for all events is the Hortonian overland flow (HOF). There is a hysteretic behavior between subsurface runoff flow and soil moisture with a switch in the hysteretic loop direction based on the wetness conditions prior to the event.
Water Quality Changes during Riverbank Filtration in Budapest, Hungary
Authors: Nagy-Kovács Zsuzsanna , Davidesz János , Czihat-Mártonné Katalin , Till Gábor , Fleit Ernő , Grischek Thomas
Published: February 2019

The paper gives an overview on the changes in water quality during riverbank filtration (RBF) in Budapest. As water from the Danube River is of high quality, no problems occur during regular operation of RBF systems. Additionally, water quality improved through the past three decades due to the implementation of communal wastewater treatment plants and the decline of extensive use of artificial fertilizers in agriculture. Algae counts are used as tracer indicators to identify input of surface water into wells and to make decisions regarding shutdowns during floods. RBF systems have a high buffering capacity and resistance against accidental spills of contaminants in the river, which was proven during the red mud spill in October 2010. The removal rate of microorganisms was between 1.5 log and 3.5 log efficiency and is in the same order as for other RBF sites worldwide.
Experimental Determination of Moisture Sorption Isotherm of Fecal Sludge
Authors: Bourgault Catherine , Lessard Paul , Remington Claire , Dorea Caetano C.
Published: February 2019

Dewatering and drying of fecal sludge (FS) is a key treatment objective in fecal sludge management as it reduces volume (thereby reducing emptying frequency and associated transportation costs), inactivates pathogens, and is beneficial and/or necessary to resource recovery activities such as composting and combustion as fuel. However, studies on dewatering performances of FS are limited. The physical water distribution of such matrices is not fully understood, limiting the progress in the development and optimization of FS dewatering technologies. The objective of this study is to present a gravimetric method intended to assess the dewatering characteristics and associated modelling of FS through moisture sorption isotherms. Samples were placed in airtight jars containing different saturated salt (NaOH, CaCl2, NaCl, KCl, K2SO4) solutions to reproduce a range of relative humidity values (6 to 97%). Results confirmed the achievement of characteristic sigma-shaped moisture sorption isotherms with increasing moisture adsorption at higher values of relative humidity. Furthermore, experimental data best fit the three-parameter Guggenheim–Anderson–de Boer (GAB) model. This method can be replicated to contribute critical data about the characterization of fecal sludge, a seriously under-researched matrix.
Specific Protocols of Controlled Ovarian Stimulation for Oocyte Cryopreservation in Breast Cancer Patients
Authors: Cavagna F. , Pontes A. , Cavagna M. , Dzik A. , Donadio N. F. , Portela R. , Nagai M. T. , Gebrim L.H.
Published: February 2019

Background: Fertility preservation is an important concern in breast cancer patients. In the present investigation, we set out to create a specific protocol of controlled ovarian stimulation (COS) for oocyte cryopreservation in breast cancer patients. Methods: From November 2014 to December 2016, 109 patients were studied. The patients were assigned to a specific random-start ovarian stimulation protocol for oocyte cryopreservation. The endpoints were the numbers of oocytes retrieved and of mature oocytes cryopreserved, the total number of days of ovarian stimulation, the total dose of gonadotropin administered, and the estradiol level on the day of the trigger. Results: Mean age in this cohort was 31.27 ± 4.23 years. The average duration of COS was 10.0 ± 1.39 days. The mean number of oocytes collected was 11.62 ± 7.96 and the mean number of vitrified oocytes was 9.60 ± 6.87. The mean estradiol concentration on triggering day was 706.30 ± 450.48 pg/mL, and the mean dose of gonadotropins administered was 2610.00 ± 716.51 IU. When comparing outcomes by phase of the cycle in which COS was commenced, we observed no significant differences in the numbers of oocytes collected and vitrified, the length of ovarian stimulation, and the estradiol level on trigger day. The total dose of follicle-stimulating hormone and human menopausal gonadotropin administered was statistically greater in the group starting COS in the luteal phase than in the group starting in the late follicular phase. Conclusions: Our results suggest that using a specific protocol with random-start ovarian stimulation for oocyte cryopreservation in breast cancer patients is effective and could be offered to young women undergoing oncologic treatment.
Patient-Reported Outcome Measurement Compared with Professional Judgment of Cosmetic Results after Breast-Conserving Therapy
Authors: Brands-Appeldoorn Angelique T. P. M. , Maaskant-Braat A. J. G. , Zwaans W. A. R. , Dieleman J. P. , Schenk K. E. , Broekhuysen C. L. , Weerdenburg H. , Daniels R. , Tjan-Heijnen V. C. G. , Roumen R. M. H.
Published: February 2019

Background: In the present study, we set out to compare patient-reported outcomes with professional judgment about cosmesis after breast-conserving therapy (bct) and to evaluate which items (position of the nipple, color, scar, size, shape, and firmness) correlate best with subjective outcome. Methods: Dutch patients treated with bct between 2008 and 2009 were analyzed. Exclusion criteria were prior amputation or bct of the contralateral breast, metastatic disease, local recurrence, or any prior cosmetic breast surgery. Structured questionnaires and standardized six-view photographs were obtained with a minimum of 3 years’ follow-up. Cosmetic outcome was judged by the patients and, based on photographs, by 5 different medical professionals using 3 different scoring systems: the Harvard scale, the Sneeuw questionnaire, and a numeric rating scale. Agreement was scored using the intraclass correlation coefficient (icc). The association between items of the Sneeuw questionnaire and a fair–poor Harvard score was estimated using logistic regression analysis. Results: The study included 108 female patients (age: 40–91 years). Based on the Harvard scale, agreement on cosmetic outcome between the professionals was good (icc: 0.78). In contrast, agreement between professionals as a group compared with the patients was found to be fair to moderate (icc range: 0.38–0.50). The items “size” and “shape” were identified as the strongest determinants of cosmetic outcome. Conclusions: Cosmetic outcome was scored differently by patients and professionals. Agreement was greater between the professionals than between the patients and the professionals as a group. In general, size and shape were the most prominent items on which cosmetic outcome was judged by patients and professionals alike.