bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Concentrated Flowpaths in Riparian Forest Buffer Contributing Areas Using LiDAR Imagery and Topographic Metrics
Authors: Wallace Carlington W. , McCarty Gregory , Lee Sangchul , Brooks Robert P. , Veith Tamie L. , Kleinman Peter J. A. , Sadeghi Ali M.
Published: April 2018

Riparian forest (CP22) buffers are implemented in the Chesapeake Bay Watershed to trap pollutants in surface runoff thus minimizing the amount of pollutants entering the stream network. For these buffers to function effectively, overland flow must enter the riparian zones as dispersed sheet flow to facilitate slowing, filtering, and infiltrating of surface runoff. The occurrence of concentrated flowpaths, however, is prevalent across the watershed. Concentrated flowpaths limit buffer filtration capacity by channeling overland flow through or around buffers. In this study, two topographic metrics (topographic openness and flow accumulation) were used to evaluate the occurrence of concentrated flowpaths and to derive effective CP22 contributing areas in four Long-Term Agroecosystem Research (LTAR) watersheds within the Chesapeake Bay Watershed. The study watersheds include the Tuckahoe Creek watershed (TCW) located in Maryland, and the Spring Creek (SCW), Conewago Creek (CCW) and Mahantango Creek (MCW) watersheds located in Pennsylvania. Topographic openness identified detailed topographic variation and critical source areas in the lower relief areas while flow accumulation was better at identifying concentrated flowpaths in higher relief areas. Results also indicated that concentrated flowpaths are prevalent across all four watersheds, reducing CP22 effective contributing areas by 78% in the TCW, 54% in the SCW, 38% in the CCW and 22% in the MCW. Thus, to improve surface water quality within the Chesapeake Bay Watershed, the implementation of riparian forest buffers should be done in such a way as to mitigate the effects of concentrated flowpaths that continue to short-circuit these buffers.
Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors
Authors: Bulgin Claire E. , Merchant Christopher J. , Ghent Darren , Klüser Lars , Popp Thomas , Poulsen Caroline , Sogacheva Larisa
Published: April 2018

Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR). We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST) retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics), cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance). Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.
Monitoring of Carbon Fiber-Reinforced Old Timber Beams via Strain and Multiresonant Acoustic Emission Sensors
Authors: Rescalvo Francisco J. , Valverde-Palacios Ignacio , Suarez Elisabet , Roldán Andrés , Gallego Antolino
Published: April 2018

This paper proposes the monitoring of old timber beams with natural defects (knots, grain deviations, fissures and wanes), reinforced using carbon composite materials (CFRP). Reinforcement consisted of the combination of a CFRP laminate strip and a carbon fabric discontinuously wrapping the timber element. Monitoring considered the use and comparison of two types of sensors: strain gauges and multi-resonant acoustic emission (AE) sensors. Results demonstrate that: (1) the mechanical behavior of the beams can be considerably improved by means of the use of CFRP (160% in bending load capacity and 90% in stiffness); (2) Acoustic emission sensors provide comparable information to strain gauges. This fact points to the great potential of AE techniques for in-service damage assessment in real wood structures.
A Novel Detection Model and Its Optimal Features to Classify Falls from Low- and High-Acceleration Activities of Daily Life Using an Insole Sensor System
Authors: Cates Benjamin , Sim Taeyong , Heo Hyun Mu , Kim Bori , Kim Hyunggun , Mun Joung Hwan
Published: April 2018

In order to overcome the current limitations in current threshold-based and machine learning-based fall detectors, an insole system and novel fall classification model were created. Because high-acceleration activities have a high risk for falls, and because of the potential damage that is associated with falls during high-acceleration activities, four low-acceleration activities, four high-acceleration activities, and eight types of high-acceleration falls were performed by twenty young male subjects. Encompassing a total of 800 falls and 320 min of activities of daily life (ADLs), the created Support Vector Machine model’s Leave-One-Out cross-validation provides a fall detection sensitivity (0.996), specificity (1.000), and accuracy (0.999). These classification results are similar or superior to other fall detection models in the literature, while also including high-acceleration ADLs to challenge the classification model, and simultaneously reducing the burden that is associated with wearable sensors and increasing user comfort by inserting the insole system into the shoe.
Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks
Authors: Lim Chiwoo , Jang Min , Kim Sang-Hyo
Published: April 2018

In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA), is proposed for peer discovery of distributed device-to-device (D2D) communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR). The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA)-based discovery.
LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices
Authors: He Ziyang , Zhang Xiaoqing , Cao Yangjie , Liu Zhi , Zhang Bo , Wang Xiaoyan
Published: April 2018

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices.
IoT On-Board System for Driving Style Assessment
Authors: Jachimczyk Bartosz , Dziak Damian , Czapla Jacek , Damps Pawel , Kulesza Wlodek J.
Published: April 2018

The assessment of skills is essential and desirable in areas such as medicine, security, and other professions where mental, physical, and manual skills are crucial. However, often such assessments are performed by people called “experts” who may be subjective and are able to consider a limited number of factors and indicators. This article addresses the problem of the objective assessment of driving style independent of circumstances. The proposed objective assessment of driving style is based on eight indicators, which are associated with the vehicle’s speed, acceleration, jerk, engine rotational speed and driving time. These indicators are used to estimate three driving style criteria: safety, economy, and comfort. The presented solution is based on the embedded system designed according to the Internet of Things concept. The useful data are acquired from the car diagnostic port—OBD-II—and from an additional accelerometer sensor and GPS module. The proposed driving skills assessment method has been implemented and experimentally validated on a group of drivers. The obtained results prove the system’s ability to quantitatively distinguish different driving styles. The system was verified on long-route tests for analysis and could then improve the driver’s behavior behind the wheel. Moreover, the spider diagram approach that was used established a convenient visualization platform for multidimensional comparison of the result and comprehensive assessment in an intelligible manner.
Older Adults with Weaker Muscle Strength Stand up from a Sitting Position with More Dynamic Trunk Use
Authors: Van Lummel Rob , Evers Jordi , Niessen Martijn , Beek Peter , Van Dieën Jaap
Published: April 2018

The ability to stand up from a sitting position is essential for older adults to live independently. Body-fixed inertial sensors may provide an approach for quantifying the sit-to-stand (STS) in clinical settings. The aim of this study was to determine whether measurements of STS movements using body-fixed sensors yield parameters that are informative regarding changes in STS performance in older adults with reduced muscle strength. In twenty-seven healthy older adults, handgrip strength was assessed as a proxy for overall muscle strength. Subjects were asked to stand up from a chair placed at three heights. Trunk movements were measured using an inertial sensor fixed to the back. Duration, angular range, and maximum angular velocity of STS phases, as well as the vertical velocity of the extension phase, were calculated. Backwards elimination using Generalized Estimating Equations was used to determine if handgrip strength predicted the STS durations and trunk kinematics. Weaker subjects (i.e., with lower handgrip strength) were slower during the STS and showed a larger flexion angular range and a larger extension angular range. In addition, weaker subjects showed a greater maximum angular velocity, which increased with lower seat heights. Measurements with a single inertial sensor did reveal that older adults with lower handgrip strength employed a different strategy to stand up from a sitting position, involving more dynamic use of the trunk. This effect was greatest when elevating body mass. Trunk kinematic parameters were more sensitive to reduced muscle strength than durations.
Key Processes of Silicon-On-Glass MEMS Fabrication Technology for Gyroscope Application
Authors: Ma Zhibo , Wang Yinan , Shen Qiang , Zhang Han , Guo Xuetao
Published: April 2018

MEMS fabrication that is based on the silicon-on-glass (SOG) process requires many steps, including patterning, anodic bonding, deep reactive ion etching (DRIE), and chemical mechanical polishing (CMP). The effects of the process parameters of CMP and DRIE are investigated in this study. The process parameters of CMP, such as abrasive size, load pressure, and pH value of SF1 solution are examined to optimize the total thickness variation in the structure and the surface quality. The ratio of etching and passivation cycle time and the process pressure are also adjusted to achieve satisfactory performance during DRIE. The process is optimized to avoid neither the notching nor lag effects on the fabricated silicon structures. For demonstrating the capability of the modified CMP and DRIE processes, a z-axis micro gyroscope is fabricated that is based on the SOG process. Initial test results show that the average surface roughness of silicon is below 1.13 nm and the thickness of the silicon is measured to be 50 μm. All of the structures are well defined without the footing effect by the use of the modified DRIE process. The initial performance test results of the resonant frequency for the drive and sense modes are 4.048 and 4.076 kHz, respectively. The demands for this kind of SOG MEMS device can be fulfilled using the optimized process.
Evaluation of Over-The-Row Harvester Damage in a Super-High-Density Olive Orchard Using On-Board Sensing Techniques
Authors: Pérez-Ruiz Manuel , Rallo Pilar , Jiménez M. Rocío , Garrido-Izard Miguel , Suárez M. Paz , Casanova Laura , Valero Constantino , Martínez-Guanter Jorge , Morales-Sillero Ana
Published: April 2018

New super-high-density (SHD) olive orchards designed for mechanical harvesting using over-the-row harvesters are becoming increasingly common around the world. Some studies regarding olive SHD harvesting have focused on the effective removal of the olive fruits; however, the energy applied to the canopy by the harvesting machine that can result in fruit damage, structural damage or extra stress on the trees has been little studied. Using conventional analyses, this study investigates the effects of different nominal speeds and beating frequencies on the removal efficiency and the potential for fruit damage, and it uses remote sensing to determine changes in the plant structures of two varieties of olive trees (‘Manzanilla Cacereña’ and ‘Manzanilla de Sevilla’) planted in SHD orchards harvested by an over-the-row harvester. ‘Manzanilla de Sevilla’ fruit was the least tolerant to damage, and for this variety, harvesting at the highest nominal speed led to the greatest percentage of fruits with cuts. Different vibration patterns were applied to the olive trees and were evaluated using triaxial accelerometers. The use of two light detection and ranging (LiDAR) sensing devices allowed us to evaluate structural changes in the studied olive trees. Before- and after-harvest measurements revealed significant differences in the LiDAR data analysis, particularly at the highest nominal speed. The results of this work show that the operating conditions of the harvester are key to minimising fruit damage and that a rapid estimate of the damage produced by an over-the-row harvester with contactless sensing could provide useful information for automatically adjusting the machine parameters in individual olive groves in the future.
Tightly-Coupled GNSS/Vision Using a Sky-Pointing Camera for Vehicle Navigation in Urban Areas
Authors: Gakne Paul , O’Keefe Kyle
Published: April 2018

This paper presents a method of fusing the ego-motion of a robot or a land vehicle estimated from an upward-facing camera with Global Navigation Satellite System (GNSS) signals for navigation purposes in urban environments. A sky-pointing camera is mounted on the top of a car and synchronized with a GNSS receiver. The advantages of this configuration are two-fold: firstly, for the GNSS signals, the upward-facing camera will be used to classify the acquired images into sky and non-sky (also known as segmentation). A satellite falling into the non-sky areas (e.g., buildings, trees) will be rejected and not considered for the final position solution computation. Secondly, the sky-pointing camera (with a field of view of about 90 degrees) is helpful for urban area ego-motion estimation in the sense that it does not see most of the moving objects (e.g., pedestrians, cars) and thus is able to estimate the ego-motion with fewer outliers than is typical with a forward-facing camera. The GNSS and visual information systems are tightly-coupled in a Kalman filter for the final position solution. Experimental results demonstrate the ability of the system to provide satisfactory navigation solutions and better accuracy than the GNSS-only and the loosely-coupled GNSS/vision, 20 percent and 82 percent (in the worst case) respectively, in a deep urban canyon, even in conditions with fewer than four GNSS satellites.
Leadership Styles and War and Peace Policies in the Spanish–Basque Conflict: A Discourse Analysis of José María Aznar and José Luis Rodríguez Zapatero
Authors: Tarín Sanz Adrián , Rivas Otero José Manuel
Published: April 2018

The purpose of this paper is to establish possible links between leadership styles and war and peace policies in the Spanish–Basque conflict. To this end, an analysis was performed of the styles of two Spanish premiers, José María Aznar (1996–2004) and José Luis Rodríguez Zapatero (2004–2011), both of whom were involved in the same conflict with similar peace policies. The structure of the paper is as follows: an overview of the literature on leadership styles in armed conflict situations and the construction of a theoretical framework; a review of the historical and biographical context; a description of the interview content analysis methodology for measuring leadership styles; a classification of Aznar and Zapatero on the basis of their leadership styles and a comparative analysis of their policies and those enforced by other leaders in a context of internal armed conflict; and the conclusions.
Identifying Effective Fugitive Dust Control Measures for Construction Projects in Korea
Authors: Noh Hyun-jun , Lee Seul-ki , Yu Jung-ho
Published: April 2018

In recent years, the awareness of the seriousness of the damage caused by fugitive dust and the need to manage it have increased. In particular, construction sites comprise 84% of business places that have reported fugitive dust generation, and they are required to have inspection and management to prevent the occurrence of fugitive dust at construction sites. However, the number of complaints in the construction industry due to fugitive dust has increased. The reason for this increase is the fact that existing control measures are defined based on emission processes rather than construction work types, which makes it difficult to apply fugitive dust control measures to construction sites. Therefore, this research evaluated the effectiveness of fugitive dust control measures for construction sites in Korea through a Delphi study. This Delphi study was conducted in two rounds with 12 experts in an on-site panel, and the factors that were determined to be effective control measures were convergence, the content validity ratio (CVR), and stability. This study’s results will be utilized to direct the establishment of future guidelines for fugitive dust control measures based on types of construction work.
The Spanish Turn against Renewable Energy Development
Authors: Gabaldón-Estevan Daniel , Peñalvo-López Elisa , Alfonso Solar David
Published: April 2018

In this study, we focus on the case of Spanish energy policy and its implications for sustainable energy development. In recent years, Spanish legislation has changed dramatically in its approach to sustainable energy sources. This change is despite EU and international efforts to increase energy efficiency, and to accelerate the transition to renewable energy sources (RES) in order to reduce greenhouse gas emissions. Based on the socio-technical transitions literature, this paper assesses the role of the new legislation in this altered scenario, and analyzes the evolution of energy production in Spain in the EU context. The results are triangulated with two expert assessments. We find that Spanish energy policy is responding to the energy lobby’s demands for protection for both their investment and their dominant position. This has resulted in a reduction in the number of investors combined with a lack of trust in both local and foreign investors in the sustainable energy sector, affecting also social innovations in energy transitions. We conclude that Spain is a particular case of concomitance between the energy sector and political power which raises concern about the viability of a higher level of energy sovereignty and the achievement of international commitments regarding climate change.
Exploring the Potentials of ICT Tools for Human-Centric Regenerative Design
Authors: Sonetti Giulia , Naboni Emanuele , Brown Martin
Published: April 2018

Aiming for sustainable buildings and cities is critical to achieving a future that is socially just, ecologically regenerative, culturally rich, and economically viable. However, our current concepts of sustainability often exclude the essential domains of data, information, and the knowledge relating to the relationship between buildings and people that inhabit them. Thus, the research questions at the core of this paper have been as follows: Can technologies and artificial intelligence (AI) be used to create systems that enhance relationships between buildings and inhabitants? Can social networks and natural interactions support further research relating to human-centric design tools for the built environment? The Human Observation Meta-Environment (HOME) project was developed to address this question. The ICT architecture has been tested to observe and collect human behaviour data within a sentient room at the Politecnico di Torino (IT), where the inhabitants were strategically aware of their behaviours. Methods of analysis included technologies related to the domain of AI (such as Natural Language Analysis, Computer Vision, Machine Learning and Deep Learning) that have been used in social network analysis in connection with the word ‘comfort’, and definitions resonate strongly with the realm of regenerative design. Results were used to further research the role of users that could serve as leverages to design (both spaces and related smart systems) according to actual user needs. People from very different disciplinary backgrounds interacted with the prototype in a workshop and provided stimuli for further considerations regarding the possible technological, psychological, cognitive, cultural, social, political, and aesthetical impacts of the use of these technologies inside sentient buildings. The paper enriches the discourse on how ICT data can be organised and read in a human-centric regenerative design process perspective.
Determination of Initial Stiffness of Timber–Steel Composite (TSC) Beams Based on Experiment and Simulation Modeling
Authors: Tsai Meng-Ting , Le Truong Di Ha
Published: April 2018

Due to improvements in the use of recyclable materials in construction, timber–steel composite (TSC) beams demonstrate high potential for future construction. In this study, a proposed simulation modeling, which was adopted from the simulation modeling of a timber I-shape composite, was applied to estimate the initial stiffness of TSC beams. The strength of each beam could be determined once the initial stiffness was estimated. In addition, a series of experiments were performed to examine the accuracy of the proposed simulation modeling, including the effects of different shapes of steel members, fasteners, and applying and not applying a dowel connection. The results indicated that the simulation modeling could adequately determine strength at a deflection of 1/360 of the span. The ratio of difference between the experimental results and the simulation modeling results was less than 10% if a dowel connection at the web was applied. However, the ratio of difference reached 26% and 24% in the TSC beams without a dowel connection at the web that were fastened with screws and nails at the flange, respectively, revealing the importance of applying a dowel connection at the web. Moreover, the strength of the TSC beams with a dowel connection at the web that were fastened by screws was approximately 15% higher than that of TSC beams without screw fasteners. In conclusion, the proposed simulation modeling can provide designers with a method for estimating the initial stiffness and strength of TSC beams within a deflection of 1/360 of the span, supporting the future application of TSC beams in construction.
A Supply Chain Coordination Mechanism with Cost Sharing of Corporate Social Responsibility
Authors: Liu Yong , Quan Bing-ting , Li Jiao , Forrest Jeffrey Yi-Lin
Published: April 2018

The competition of modern enterprises has shifted from brand competition among enterprises of the past to that of supply chains; and considering corporate social responsibility (CSR) within supply chain management has become an inevitable requirement for improving the competitiveness of enterprises and conforms to the trend of standardization of social responsibility guidelines. This paper deals with channel coordination and decision-making in a CSR supply chain that is comprised of a dominant retailer and n homogeneous suppliers. The Stackelberg game is employed to analyze the optimal decision-making of this supply chain under either decentralized or centralized decision-making processes. After that, the thought and method of super conflict equilibrium are used to design the coordination decision-making mechanism of this supply chain based on the cost sharing of CSR to solve channel conflict and to optimize the decision. The results show that the proposed mechanism based on the cost sharing of CSR is better than those with only either the retailer or the suppliers being CSR; and it can well describe the relationship between the retailer and the suppliers, and increase the eagerness of the retailer and suppliers to carry out their CSR under various circumstances without having the profits adversely affected. As a matter of fact, this mechanism maximizes the profits of the entire supply chain system and also enhances the competitiveness of the chain.
An Overview of Problems and Solutions for Urban Freight Transport in Brazilian Cities
Authors: Oliveira Leise K. , Barraza Betty , Bertocini Bruno V. , Isler Cassiano A. , Pires Dannúbia R. , Madalon Ellen C. N. , Lima Jéssica , Vieira José G. V. , Meira Leonardo H. , Bracarense Lilian S. F. P. , Bandeira Renata A. , Oliveira Renata L. M. , Ferreira Suellem
Published: April 2018

Urban freight transport is a challenge for Brazilian cities due to the lack of adequate planning for freight flow movement. Public managers also show negligence and a lack of awareness when dealing with urban logistics. Decision-support data on urban freight transport are still scarce, despite being of fundamental value to economic development. With this in mind, this paper presents problems and solutions regarding urban freight transport in Brazilian cities. Data were obtained through a survey conducted in nine cities and analysed by means of descriptive statistics and the successive intervals method. Additionally, a cluster analysis was performed to identify patterns regarding the typical characteristics of each city in order to compare and generalise the perception of retailers regarding problems and solutions at the national level. The results indicate divergent opinions among retailers from different cities, even from cities with similar socioeconomic profiles and urban dynamics. The municipalities which demonstrated the most similarities were (i) Betim and Niteroi, in the Southeast of Brazil; (ii) Palmas and Quixada, in the North and Northeast, respectively; and (iii) Palmas and Caruaru, also in the North and Northeast. The results reinforce the importance of studying the local context and involving stakeholders in the process of planning urban logistics solutions.
Application of Sliding Nest Window Control Chart in Data Stream Anomaly Detection
Authors: Li Guang , Wang Jie , Liang Jing , Yue Caitong
Published: April 2018

Since data stream anomaly detection algorithms based on sliding windows are sensitive to the abnormal deviation of individual interference data, this paper presents a sliding nest window chart anomaly detection based on the data stream (SNWCAD-DS) by employing the concept of the sliding window and control chart. By nesting a small sliding window in a large sliding window and analyzing the deviation distance between the small window and the large sliding window, the algorithm increases the out-of-bounds detection ratio and classifies the conceptual drift data stream online. The designed algorithm is simulated on the industrial data stream of drilling engineering. The proposed algorithm SNWCAD is compared with Automatic Outlier Detection for Data Streams (A-ODDS) and Distance-Based Outline Detection for Data Stream (DBOD-DS). The experimental results show that the new algorithm can obtain higher detection accuracy than the compared algorithms. Furthermore, it can shield the influence of individual interference data and satisfy actual engineering needs.
Understanding Review Expertise of Developers: A Reviewer Recommendation Approach Based on Latent Dirichlet Allocation
Authors: Kim Jungil , Lee Eunjoo
Published: April 2018

The code reviewer assignment problem affects the reviewing time of a source code change. To effectively perform the code review process of a software project, the code reviewer assignment problem must be dealt with. Reviewer recommendation can reduce the time required for finding appropriate reviewers for a given source code change. In this paper, we propose a reviewer recommendation approach based on latent Dirichlet allocation (LDA). The proposed reviewer recommendation approach consists of a review expertise generation phase and a reviewer recommendation phase. The review expertise generation phase generates the review expertise of developers for topics of source code changes from the review history of a software project. The reviewer recommendation phase computes the review scores of the developers according to the topic distribution of a given source code change and the review expertise of the developers. In an empirical evaluation of five open source projects, we confirm that the proposed reviewer recommendation approach obtains better average top-10 accuracy than existing reviewer recommendation approaches.
New Multiple Attribute Decision Making Method Based on DEMATEL and TOPSIS for Multi-Valued Interval Neutrosophic Sets
Authors: Yang Wei , Pang Yongfeng
Published: April 2018

Interval neutrosophic fuzzy decision making is an important part of decision making under uncertainty, which is based on preference order. In this study, a new multi-valued interval neutrosophic fuzzy multiple attribute decision making method has been developed by integrating the DEMATEL (decision making trial and evaluation laboratory) method and the TOPSIS (the technique for order preference by similarity to an ideal solution) method. Evaluation values are given in the form of multi-valued interval neutrosophic fuzzy values. By using DEMATEL, dependencies among attributes can be modeled, and attribute weights are determined. The normalized Euclidean distance and the normalized Hamming distance between multi-valued interval neutrosophic fuzzy values are defined. Alternatives are ranked by using the TOPSIS method based on the distance measures. The truck selection problem in the logistics industry is presented to illustrate the feasibility and practical advantages of the proposed method. Some comparisons of the new method with other methods are also made.
Human Bodily Asymmetry Relates to Behavioral Lateralization and May not Reliably Reflect Developmental Instability
Authors: Van Dongen Stefan
Published: April 2018

(1) Background: The link between behavioral lateralization and bodily asymmetry in humans is studied to investigate the reliability of fluctuating asymmetry as a measure of developmental instability; (2) Methods: Morphological asymmetries of arms and legs, obtained from 3D body scans, were correlated with different measures of behavioral lateralization; (3) Results: Observed associations were in the directions expected, showing that more asymmetric use of the body increases asymmetry, especially in the arms, and more symmetric body use appears to have a symmetrizing effect; and (4) Conclusions: The results presented here question the suitability of human bodily asymmetry in arms and legs—or at least part of them—as a measure of developmental instability. There is a need for future research that identifies regions of the body that are not affected by behavioral lateralization and can reliably reflect developmental instability.
A Simple Method for Measuring the Bilateral Symmetry of Leaves
Authors: Shi Peijian , Zheng Xiao , Ratkowsky David A. , Li Yang , Wang Ping , Cheng Liang
Published: April 2018

Many plant leaves exhibit bilateral symmetry, but such symmetry has rarely been measured because of the lack of practical methods. We propose a simple method for achieving the above objective. A leaf is divided into left and right sides, and several equally-sized strips are generated to intersect each side of that leaf to generate pairwise left and right sub-regions. A standardized index (SI) for measuring bilateral symmetry is built based on the left–right areal differences of those sub-regions. The leaves of 10 species of plants were sampled for testing the method’s validity. Based on the experimental data, we compared the root-mean-squared error (RMSE), SI, and areal ratio (AR) of the left side to the right side of the leaf. The SI measures the bilateral symmetry of plant leaves well, and it is better than the RMSE and AR for eliminating the effect of leaf size on the goodness of fit. The SI proposed here is the best indicator for evaluating the degree of bilateral symmetry and can be potentially used for comparing the difference in the bilateral symmetry of leaves of different plants.
Ribosome Inactivating Proteins: From Plant Defense to Treatments against Human Misuse or Diseases
Authors: Barbier Julien , Gillet Daniel
Published: April 2018

Ribosome inactivating proteins (RIPs) form a vast family of hundreds of toxins from plants, fungi, algae, and bacteria. RIP activities have also been detected in animal tissues. They exert an N-glycosydase catalytic activity that is targeted to a single adenine of a ribosomal RNA, thereby blocking protein synthesis and leading intoxicated cells to apoptosis. In many cases, they have additional depurinating activities that act against other nucleic acids, such as viral RNA and DNA, or genomic DNA. Although their role remains only partially understood, their functions may be related to plant defense against predators and viruses, plant senescence, or bacterial pathogenesis.
An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas
Authors: Yang Liang , Hoffmann Peter , Scheffran Jürgen , Rühe Sven , Fischereit Jana , Gasser Ingenuin
Published: April 2018

Several approaches have been used to assess potential human exposure to environmental stresses and achieve optimal results under various conditions, such as for example, for different scales, groups of people, or points in time. A thorough literature review in this paper identifies the research gap regarding modeling approaches for assessing human exposure to environment stressors, and it indicates that microsimulation tools are becoming increasingly important in human exposure assessments of urban environments, in which each person is simulated individually and continuously. The paper further describes an agent-based model (ABM) framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision-making processes can be included for each individual based on rule-based behavior in order to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A basic modeling scenario of the ABM framework in Hamburg, Germany, demonstrates its utility in various urban environments and individual activity patterns, as well as its portability to other models, programs, and frameworks. The prototype model can potentially be extended to support environmental incidence management through exploring the daily routines of different groups of citizens, and comparing the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.
Inhibition of Rabies Virus by 1,2,3,4,6-Penta-O-galloyl-β-d-Glucose Involves mTOR-Dependent Autophagy
Authors: Tu Zhongzhong , Gong Wenjie , Zhang Yan , Feng Ye , Liu Yan , Tu Changchun
Published: April 2018

The compound 1,2,3,4,6-penta-O-galloyl-β-d-glucose (PGG), a gallotannin present in various plants such as Rhus chinensis Mill and Paeonia suffruticosa, has a broad spectrum of antiviral effects. The present study investigated its potency against infection of mice with rabies virus (RABV). Results demonstrated that PGG strongly inhibited virus titers (50-fold), viral mRNA expression (up to 90%), and protein synthesis in vitro. Importantly, we found that PGG not only suppressed viral adsorption and entry, but also directly inactivated RABV through suppression of autophagy by mediating activation of the mTOR-dependent autophagy signaling pathway. In vivo, PGG (10 mg/kg) alleviated the clinical symptoms and reduced the mortality of infected mice by 27.3%. Collectively, our results indicate that PGG has potent anti-RABV effect, and merits further investigation as an anti-RABV drug.
Evolutionary Toxicology as a Tool to Assess the Ecotoxicological Risk in Freshwater Ecosystems
Authors: Rusconi Marianna , Bettinetti Roberta , Polesello Stefano , Stefani Fabrizio
Published: April 2018

Borrowing the approaches of population genetics, evolutionary toxicology was particularly useful in assessing the transgenerational effects of a substance at sublethal concentrations, as well as evaluating genetic variation in populations exposed to pollutants. Starting from assays in controlled conditions, in recent years this approach has also found successful applications multi-stressed natural systems. It is also able to exploit the huge amount of data provided by Next Generation Sequencing (NGS) techniques. Similarly, the focus has shifted from effects on the overall genetic variability, the so-called “genetic erosion”, to selective effects induced by contaminants at more specific pathways. In the aquatic context, effects are usually assessed on non-model species, preferably native fish or macroinvertebrates. Here we provide a review of current trends in this specific discipline, with a focus on population genetics and genomics approaches. In addition, we demonstrate the potential usefulness of predictive simulation and Bayesian techniques. A focused collection of field and laboratory studies is discussed to demonstrate the effectiveness of this approach, covering a range of molecular markers, different endpoints of genetic variation, and different classes of chemical contaminants. Moreover, guidelines for a future implementation of evolutionary perspective into Ecological Risk Assessment are provided.
Nitrogen and Organics Removal during Riverbank Filtration along a Reclaimed Water Restored River in Beijing, China
Authors: Pan Weiyan , Huang Quanzhong , Huang Guanhua
Published: April 2018

Reclaimed water has been widely used to restore rivers and lakes in water scarce areas as well as in Beijing municipality, China. However, refilling the rivers with reclaimed water may result in groundwater pollution. A three-year field monitoring program was conducted to assess the effect of a riverbank filtration (RBF) system on the removal of nitrogen and organics from the Qingyang River of Beijing, which is replenished with reclaimed water. Water samples from the river, sediment, and groundwater were collected for NO3-N, NH4-N, and chemical oxygen demand (COD) was measured. The results indicate that about 85% of NO3-N was removed from the riverbed sediments. Approximate 92% of NH4-N was removed during the infiltration of water from river to aquifer. On average, 54% of COD was removed by RBF. The attenuation of NO3-N through RBF to the groundwater varied among seasons and was strongly related to water temperature. On the other hand, no obvious temporal variability was identified in the removal of COD. These results suggest that the RBF system is an effective barrier against NO3-N, NH4-N and COD in the Qingyang River, as well as those rivers with similar geological and climatic conditions refilled with reclaimed water.
Effect of Tidal Cycling Rate on the Distribution and Abundance of Nitrogen-Oxidizing Bacteria in a Bench-Scale Fill-and-Drain Bioreactor
Authors: Battistelli Joseph M. , Franklin Rima B. , Mills Aaron L.
Published: April 2018

Most domestic wastewater can be effectively treated for secondary uses by engineered biological systems. These systems rely on microbial activity to reduce nitrogen (N) content of the reclaimed water. Such systems often employ a tidal-flow process to minimize space requirements for the coupling of aerobic and anaerobic metabolic processes. In this study, laboratory-scale tidal-flow treatment systems were studied to determine how the frequency and duration of tidal cycling may impact reactor performance. Fluorescent in situ hybridization and epifluorescence microscopy were used to enumerate the key functional groups of bacteria responsible for nitrification and anaerobic ammonium oxidation (anammox), and N-removal efficiency was calculated via a mass-balance approach. When water was cycled (i.e., reactors were filled and drained) at high frequencies (16–24 cycles day−1), nitrate accumulated in the columns—presumably due to inadequate periods of anoxia that limited denitrification. At lower frequencies, such as 4 cycles day−1, nearly complete N removal was achieved (80–90%). These fill-and-drain systems enriched heavily for nitrifiers, with relatively few anammox-capable organisms. The microbial community produced was robust, surviving well through short (up to 3 h) anaerobic periods and frequent system-wide perturbation.
Reference Evapotranspiration Variation Analysis and Its Approaches Evaluation of 13 Empirical Models in Sub-Humid and Humid Regions: A Case Study of the Huai River Basin, Eastern China
Authors: Li Meng , Chu Ronghao , Islam Abu Reza Md. Towfiqul , Shen Shuanghe
Published: April 2018

Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman–Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash–Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961–2000 and 2001–2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April–October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.
Trends and Consumption Structures of China’s Blue and Grey Water Footprint
Authors: Wang Huixiao , Yang Yaxue
Published: April 2018

Water footprint has become a common method to study the water resources utilization in recent years. By using input–output analysis and dilution theory, the internal water footprint, blue water footprint and grey water footprint of China from 2002 to 2012 were estimated, and the consumption structure of water footprint and virtual water trade were analyzed. The results show: (1) From 2002 to 2012, the average annual internal water footprint was 3.83 trillion m3 in China, of which the blue water footprint was 0.25 trillion m3, and the grey water footprint was 3.58 trillion m3 (with Grade III water standard accounting); both the internal water footprint and grey water footprint experienced decreasing trends from 2002 to 2012, except for a dramatic increase in 2010; (2) Average annual virtual blue water footprint was the greatest in agriculture (39.2%), while tertiary industry (27.5%) and food and tobacco processing (23.7%) were the top two highest for average annual virtual grey water footprint; (3) Virtual blue water footprint in most sectors showed increasing trends due to the increase of final demand, while virtual grey water footprint in most sectors showed decreasing trends due to the decreases of total return water coefficients and conversion coefficients of virtual grey water footprint; (4) For water resources, China was self-reliant: the water used for producing the products and services to meet domestic consumption was taken domestically; meanwhile, China exported virtual water to other countries, which aggravated the water stress in China.