bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Warming Hiatuses on Vegetation Growth in the Northern Hemisphere
Authors: Wei Hong , Zhao Xiang , Liang Shunlin , Zhou Tao , Wu Donghai , Tang Bijian
Published: April 2018

There have been hiatuses in global warming since the 1990s, and their potential impacts have attracted extensive attention and discussion. Changes in temperature not only directly affect the greening of vegetation but can also indirectly alter both the growth state and the growth tendency of vegetation by altering other climatic elements. The middle-high latitudes of the Northern Hemisphere (NH) constitute the region that has experienced the most warming in recent decades; therefore, identifying the effects of warming hiatuses on the vegetation greening in that region is of great importance. Using satellite-derived Normalized Difference Vegetation Index (NDVI) data and climatological observation data from 1982–2013, we investigated hiatuses in warming trends and their impact on vegetation greenness in the NH. Our results show that the regions with warming hiatuses in the NH accounted for 50.1% of the total area and were concentrated in Mongolia, central China, and other areas. Among these regions, 18.8% of the vegetation greenness was inhibited in the warming hiatus areas, but 31.3% of the vegetation grew faster. Because temperature was the main positive climatic factor in central China, the warming hiatuses caused the slow vegetation greening rate. However, precipitation was the main positive climatic factor affecting vegetation greenness in Mongolia; an increase in precipitation accelerated vegetation greening. The regions without a warming hiatus, which were mainly distributed in northern Russia, northern central Asia, and other areas, accounted for 49.9% of the total area. Among these regions, 21.4% of the vegetation grew faster over time, but 28.5% of the vegetation was inhibited. Temperature was the main positive factor affecting vegetation greenness in northern Russia; an increase in temperature promoted vegetation greening. However, radiation was the main positive climatic factor in northern central Asia; reductions in radiation inhibited the greenness of vegetation. Our findings suggest that warming hiatuses differentially affect vegetation greening and depend on meteorological factors, especially the main meteorological factors.
Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks
Authors: Hefron Ryan , Borghetti Brett , Schubert Kabban Christine , Christensen James , Estepp Justin
Published: April 2018

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance.
Smart Web-Based Platform to Support Physical Rehabilitation
Authors: Rybarczyk Yves , Kleine Deters Jan , Cointe Clément , Esparza Danilo
Published: April 2018

The enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the development of a suitable tele-rehabilitation application, which are: (i) being based on an affordable technology, and (ii) providing the patients with a real-time assessment of the correctness of their movements. A probabilistic approach based on the development and training of ten Hidden Markov Models (HMMs) is used to discriminate in real time the main faults in the execution of the therapeutic exercises. Two experiments are designed to evaluate the precision of the algorithm for classifying movements performed in the laboratory and clinical settings, respectively. A comparative analysis of the data shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors. The results are discussed in terms of the required setup for a successful application in the field and further implementations to improve the accuracy and usability of the system.
Appdaptivity: An Internet of Things Device-Decoupled System for Portable Applications in Changing Contexts
Authors: Martín Cristian , Hoebeke Jeroen , Rossey Jen , Díaz Manuel , Rubio Bartolomé , Van den Abeele Floris
Published: April 2018

Currently, applications in the Internet of Things (IoT) are tightly coupled to the underlying physical devices. As a consequence, upon adding a device, device replacement or user’s relocation to a different physical space, application developers have to re-perform installation and configuration processes to reconfigure applications, which bears costs in time and knowledge of low-level details. In the emerging IoT field, this issue is even more challenging due to its current unpredictable growth in term of applications and connected devices. In addition, IoT applications can be personalised to each end user and can be present in different environments. As a result, IoT scenarios are very changeable, presenting a challenge for IoT applications. In this paper we present Appdaptivity, a system that enables the development of portable device-decoupled applications that can be adapted to changing contexts. Through Appdaptivity, application developers can intuitively create portable and personalised applications, disengaging from the underlying physical infrastructure. Results confirms a good scalability of the system in terms of connected users and components involved.
Improving Fall Detection Using an On-Wrist Wearable Accelerometer
Authors: Khojasteh Samad Barri , Villar José R. , Chira Camelia , González Víctor M. , De la Cal Enrique
Published: April 2018

Fall detection is a very important challenge that affects both elderly people and the carers. Improvements in fall detection would reduce the aid response time. This research focuses on a method for fall detection with a sensor placed on the wrist. Falls are detected using a published threshold-based solution, although a study on threshold tuning has been carried out. The feature extraction is extended in order to balance the dataset for the minority class. Alternative models have been analyzed to reduce the computational constraints so the solution can be embedded in smart-phones or smart wristbands. Several published datasets have been used in the Materials and Methods section. Although these datasets do not include data from real falls of elderly people, a complete comparison study of fall-related datasets shows statistical differences between the simulated falls and real falls from participants suffering from impairment diseases. Given the obtained results, the rule-based systems represent a promising research line as they perform similarly to neural networks, but with a reduced computational cost. Furthermore, support vector machines performed with a high specificity. However, further research to validate the proposal in real on-line scenarios is needed. Furthermore, a slight improvement should be made to reduce the number of false alarms.
Fused Microknot Optical Resonators in Folded Photonic Tapers for in-Liquid Durable Sensing
Authors: Logvinova Alexandra , Shahal Shir , Fridman Moti , Linzon Yoav
Published: April 2018

Optical microknot fibers (OMFs) serve as localized devices, where photonic resonances (PRs) enable self-interfering elements sensitive to their environment. However, typical fragility and drifting of the knot severely limit the performance and durability of microknots as sensors in aqueous settings. Herein we present the fabrication, electrical fusing, preparation, and persistent detection of volatile liquids in multiple wetting–dewetting cycles of volatile compounds and quantify the persistent phase shifts with a simple model relating to the ambient liquid, enabling durable in-liquid sensing employing OMF PRs.
All-Optical Photoacoustic Sensors for Steel Rebar Corrosion Monitoring
Authors: Du Cong , Owusu Twumasi Jones , Tang Qixiang , Guo Xu , Zhou Jingcheng , Yu Tzuyang , Wang Xingwei
Published: April 2018

This article presents an application of an active all-optical photoacoustic sensing system with four elements for steel rebar corrosion monitoring. The sensor utilized a photoacoustic mechanism of gold nanocomposites to generate 8 MHz broadband ultrasound pulses in 0.4 mm compact space. A nanosecond 532 nm pulsed laser and 400 μm multimode fiber were employed to incite an ultrasound reaction. The fiber Bragg gratings were used as distributed ultrasound detectors. Accelerated corrosion testing was applied to four sections of a single steel rebar with four different corrosion degrees. Our results demonstrated that the mass loss of steel rebar displayed an exponential growth with ultrasound frequency shifts. The sensitivity of the sensing system was such that 0.175 MHz central frequency reduction corresponded to 0.02 g mass loss of steel rebar corrosion. It was proved that the all-optical photoacoustic sensing system can actively evaluate the corrosion of steel rebar via ultrasound spectrum. This multipoint all-optical photoacoustic method is promising for embedment into a concrete structure for distributed corrosion monitoring.
Thermochromic Polymer Film Sensors for Detection of Incipient Thermal Damage in Carbon Fiber–Epoxy Composites
Authors: Toivola Ryan , Jang Sei-Hum , Baker Shawn , Jen Alex K. -Y. , Flinn Brian D.
Published: April 2018

Carbon fiber–epoxy composites have become prevalent in the aerospace industry where mechanical properties and light weight are at a premium. The significant non-destructive evaluation challenges of composites require new solutions, especially in detecting early-stage, or incipient, thermal damage. The initial stages of thermal damage are chemical rather than physical, and can cause significant reduction in mechanical properties well before physical damage becomes detectable in ultrasonic testing. Thermochromic fluorescent probe molecules have the potential to sense incipient thermal damage more accurately than traditional inspection methods. We have designed a molecule which transitions from a colorless, non-fluorescent state to a colorful, highly fluorescent state when exposed to temperature–time combinations that can cause damage in composites. Moreover, this molecule can be dispersed in a polymer film and attached to composite parts as a removable sensor. This work presents an evaluation of the sensor performance of this thermochromic film in comparison to ultrasonic C-scan as a method to detect incipient thermal damage in one of the most widely used carbon fiber–epoxy composite systems. Composite samples exposed to varying thermal exposures were used to evaluate the fluorescent thermal sensor films, and the results are compared to the results of ultrasonic imaging and short-beam shear tests for interlaminar shear strength.
Long-Period Gratings in Highly Germanium-Doped, Single-Mode Optical Fibers for Sensing Applications
Authors: Schlangen Sebastian , Bremer Kort , Zheng Yulong , Böhm Sebastian , Steinke Michael , Wellmann Felix , Neumann Jörg , Roth Bernhard , Overmeyer Ludger
Published: April 2018

Long-period fiber gratings (LPGs) are well known for their sensitivity to external influences, which make them interesting for a large number of sensing applications. For these applications, fibers with a high numerical aperture (i.e., fibers with highly germanium (Ge)-doped fused silica fiber cores) are more attractive since they are intrinsically photosensitive, as well as less sensitive to bend- and microbend-induced light attenuations. In this work, we introduce a novel method to inscribe LPGs into highly Ge-doped, single-mode fibers. By tapering the optical fiber, and thus, tailoring the effective indices of the core and cladding modes, for the first time, an LPG was inscribed into such fibers using the amplitude mask technique and a KrF excimer laser. Based on this novel method, sensitive LPG-based fiber optic sensors only a few millimeters in length can be incorporated in bend-insensitive fibers for use in various monitoring applications. Moreover, by applying the described inscription method, the LPG spectrum can be influenced and tailored according to the specific demands of a particular application.
Trusted Operations on Sensor Data †
Authors: Janjua Hassaan , Joosen Wouter , Michiels Sam , Hughes Danny
Published: April 2018

The widespread use of mobile devices has allowed the development of participatory sensing systems that capture various types of data using the existing or external sensors attached to mobile devices. Gathering data from such anonymous sources requires a mechanism to establish the integrity of sensor readings. In many cases, sensor data need to be preprocessed on the device itself before being uploaded to the target server while ensuring the chain of trust from capture to the delivery of the data. This can be achieved by a framework that provides a means to implement arbitrary operations to be performed on trusted sensor data, while guaranteeing the security and integrity of the data. This paper presents the design and implementation of a framework that allows the capture of trusted sensor data from both external and internal sensors on a mobile phone along with the development of trusted operations on sensor data while providing a mechanism for performing predefined operations on the data such that the chain of trust is maintained. The evaluation shows that the proposed system ensures the security and integrity of sensor data with minimal performance overhead.
Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing
Authors: Lin Yu-Hsiu , Hu Yu-Chen
Published: April 2018

The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved by 13.97%.
Method for Compensating Signal Attenuation Using Stepped-Frequency Ground Penetrating Radar
Authors: Liu Tao , Zhu Yutao , Su Yi
Published: April 2018

Ground penetrating radar (GPR) is a subsurface remote sensor that allows the user to detect, classify, and identify the buried target and structures. The radar signals are rapidly attenuated as they propagate into the ground; therefore, attenuation compensation is necessary for the visualization of the buried targets from GPR data. In this work, we developed a novel attenuation compensation approach based on the recently developed stepped-frequency continuous wave (SFCW) GPR system, which is a frequency domain sampling system with improved performance in dynamic range, sensitivity, and anti-interference ability. Because the regularly used time-varying gain function for compensating the attenuation of impulse GPR data does not make full use of the advancement of the SFCW modulation, an alternative procedure is proposed herein. The new approach is based the SFCW mechanism, and aims at improving the visualization of deeper targets by compensating the SFCW GPR signal attenuation. We first present the attenuation mode of the SFCW GPR echo, from which an inverse attenuation function is derived to compensate the amplitude loss. For the field measurement where the theoretical inverse attenuation function is difficult to achieve, we introduced a pseudo time–frequency distribution for estimating the inverse attenuation function. A procedure for amplitude attenuation has also been developed. Testing with both synthetic and experimental data return a good reconstruction of the signal amplitude, subsequently improving the ability for visualizing and detecting deeper targets.
Economic Analysis of the Reduction of Blood Transfusions during Surgical Procedures While Continuous Hemoglobin Monitoring Is Used
Authors: Ribed-Sánchez Borja , González-Gaya Cristina , Varea-Díaz Sara , Corbacho-Fabregat Carlos , Pérez-Oteyza Jaime , Belda-Iniesta Cristóbal
Published: April 2018

Background: Two million transfusions are performed in Spain every year. These come at a high economic price for the health system, increasing the morbidity and mortality rates. The way of obtaining the hemoglobin concentration value is via invasive and intermittent methods, the results of which take time to obtain. The drawbacks of this method mean that some transfusions are unnecessary. New continuous noninvasive hemoglobin measurement technology can save unnecessary transfusions. Methods: A prospective study was carried out with a historical control of two homogeneous groups. The control group used the traditional hemoglobin measurement methodology. The experimental group used the new continuous hemoglobin measurement technology. The difference was analyzed by comparing the transfused units of the groups. The economic savings was calculated by multiplying the cost of a transfusion by the difference in units, taking into account measurement costs. Results: The percentage of patients needing a transfusion decreased by 7.4%, and the number of transfused units per patient by 12.56%. Economic savings per patient were €20.59. At the national level, savings were estimated to be 13,500 transfusions (€1.736 million). Conclusions: Constant monitoring of the hemoglobin level significantly reduces the need for blood transfusions. By using this new measurement technology, health care facilities can significantly reduce costs and improve care quality.
Displacements Study of an Earth Fill Dam Based on High Precision Geodetic Monitoring and Numerical Modeling
Authors: Acosta Luis Enrique , De Lacy M. Clara , Ramos M. Isabel , Cano Juan Pedro , Herrera Antonio Manuel , Avilés Manuel , Gil Antonio José
Published: April 2018

The aim of this paper is to study the behavior of an earth fill dam, analyzing the deformations determined by high precision geodetic techniques and those obtained by the Finite Element Method (FEM). A large number of control points were established around the area of the dam, and the measurements of their displacements took place during several periods. In this study, high-precision leveling and GNSS (Global Navigation Satellite System) techniques were used to monitor vertical and horizontal displacements respectively. Seven surveys were carried out: February and July 2008, March and July 2013, August 2014, September 2015 and September 2016. Deformations were predicted, taking into account the general characteristics of an earth fill dam. A comparative evaluation of the results derived from predicted (FEM) and observed deformations shows the differences on average being 20 cm for vertical displacements, and 6 cm for horizontal displacements at the crest. These differences are probably due to the simplifications assumed during the FEM modeling process: critical sections are considered homogeneous along their longitude, and the properties of the materials were established according to the general characteristics of an earth fill dam. These characteristics were taken from the normative and similar studies in the country. This could also be due to the geodetic control points being anchored in the superficial layer of the slope when the construction of the dam was finished.
National Identity and Migration in an Emerging Gateway Community
Authors: Byrne Jennifer
Published: April 2018

This paper examines how conceptions of national and local identity influence reactions to migration in the Shenandoah Valley, a rural location in Southwest Virginia with unique demographic characteristics. While Shenandoah Valley residents have been predominantly non-Hispanic whites of European descent, a recent visible influx of Hispanic laborers, a higher than national average Muslim population, a history of refugee resettlement and the migration of urbanites from Northern Virginia have made the Valley one of the most diverse locations in the state of Virginia today. Using a qualitative methods approach with both apriori and emergent coding, I offer some insights as to how a traditional ethnic and civic framework of national identity and emergent themes of local identity, including family values and traditionalism, influence reactions to the changing demographics in this rural community.
Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions Using Bat Algorithm
Authors: Seyedmahmoudian Mehdi , Kok Soon Tey , Jamei Elmira , Thirunavukkarasu Gokul Sidarth , Horan Ben , Mekhilef Saad , Stojcevski Alex
Published: April 2018

The vibrant, noiseless, and low-maintenance characteristics of photovoltaic (PV) systems make them one of the fast-growing technologies in the modern era. This on-demand source of energy suffers from low-output efficiency compared with other alternatives. Given that PV systems must be installed in outdoor spaces, their efficiency is significantly affected by the inevitable complication called partial shading (PS). Partial shading occurs when different sections of the solar array are subjected to different levels of solar irradiance, which then leads to a multiple-peak function in the output characteristics of the system. Conventional tracking techniques, along with some nascent/novel approaches used for the tracking maximum power point (MPP), are unsatisfactory when subjected to PS, eventually leading to the reduced efficiency of the PV system. This study aims at investigating the use of the bat algorithm (BA), a nature-inspired metaheuristic algorithm for MPP tracking (MPPT) subjected to PS conditions. A brief explanation of the behavior of the PV system under the PS condition and the advantages of using BA for estimating the MPPT of the PV system under PS condition is discussed. The deployment of the BA for the MPPT in PV systems is then explained in detail highlighting the simulation results which verifies whether the proposed method is faster, more efficient, sustainable and more reliable than conventional and other soft computing-based methods. Three testing conditions are considered in the simulation, and the results indicate that the proposed technique has high efficiency and reliability even when subjected to an acute shading condition.
A Comparative Study of the Role of China and India in Sustainable Textile Competition in the U.S. Market under Green Trade Barriers
Authors: Xu Junqian , Liu Yong , Yang Liling
Published: April 2018

The United States is the most important textile import market in the world, and one of the most important export targets of developing countries. In view of its ecological environment and consumer health, the United States has put forward increasingly harsh environmental protection systems and standards for imported textile products, and its environmental trade barriers have been steadily strengthened. China’s textile exports increased substantially after joining the World Trade Organization (WTO) in 2000; at present, the textile imports of the United States from China and India reach in total more than one third of all their imports. China and India both have comparative advantages in the import trade of textile raw materials and clothing in the United States (U.S.). On the basis of the United Nation ComTrade Rev. 3, this paper studies the role of China and India in the United States textile market, including calculating the trade competitiveness index, revealing the competitive advantages of China and India, and investigating the impact of both Chinese and Indian textiles on United States imports from the rest of the world across three main textile sectors in the period 2000–2016, especially in the context of green trade barriers. We find that the relative textile import prices, the ecological standard of China’s textile production re-edited Oeko-Tex Standard 100 in 2008 and export tax policy, and the competitive advantages of China and India had varied impacts on relative U.S. textile imports across related sectors under green environmental trade barriers. These findings recognize China’s competitiveness in international trading, and also provide suggestions regarding China’s competitiveness and sustainable development in the U.S. market.
Risk Perceptions of Airbnb Hosts: Evidence from a Mediterranean Island
Authors: Malazizi Nahid , Alipour Habib , Olya Hossein
Published: April 2018

In the context of the sharing economy, Airbnb has become a formidable mode of accommodation in the tourism industry worldwide, with a presence in over 34,000 cities in 191 countries. However, the risks associated with online bookings are significant dimensions of this e-market domain. This study assesses Airbnb hosts’ perceived risks and investigates the effects of service, financial, safety and security, psychological and political risks on the host’s satisfaction and intention to continue and recommend this business to potential hosts. A survey was administered to 221 Airbnb hosts located in Northern Cyprus. Structural equation modeling (SEM) was used to test the proposed conceptual model. The results revealed that host satisfaction is negatively influenced by financial and safety and security risks; continuance intention is negatively affected by financial, safety and security, and political risks; intention to recommend this business is negatively affected by political risk; and psychological risk increases satisfaction and intention to continue and recommend. By highlighting the theoretical and managerial implications, this study informs Airbnb management of the potential risks associated with this peer-to-peer (P2P) business in order to minimize the associated risks, enhance host satisfaction and the quality of their services, and encourage hosts to recommend Airbnb to their peers.
Identifying Farm Pond Habitat Suitability for the Common Moorhen (Gallinula chloropus): A Conservation-Perspective Approach
Authors: Lai Chun-Hsien , Lin Shin-Hwei , Tsai Chia-Yi , Chen Szu-Hung
Published: April 2018

The purpose of this study was to establish a habitat-suitability assessment model for Gallinula chloropus, or the Common Moorhen, to be applied to the selection of the most suitable farm pond for habitat conservation in Chiayi County, Taiwan. First, the fuzzy Delphi method was employed to evaluate habitat selection factors and calculate the weights of these factors. The results showed that the eight crucial factors, by importance, in descending order, were (1) area ratio of farmlands within 200 m of the farm pond; (2) pond area; (3) pond perimeter; (4) aquatic plant coverage of the pond surface; (5) drought period; (6) coverage of high and low shrubs around the pond bank; (7) bank type; and (8) water-surface-to-bank distance. Subsequently, field evaluations of 75 farm ponds in Chiayi County were performed. The results indicated that 15 farm ponds had highly-suitable habitats and were inhabited by unusually high numbers of Common Moorhens; these habitats were most in need of conservation. A total of two farm ponds were found to require habitat-environment improvements, and Common Moorhens with typical reproductive capacity could be appropriately introduced into 22 farm ponds to restore the ecosystem of the species. Additionally, the habitat suitability and number of Common Moorhens in 36 farm ponds were lower than average; these ponds could be used for agricultural irrigation, detention basins, or for recreational use by community residents. Finally, the total habitat suitability scores and occurrence of Common Moorhens in each farm pond were used to verify the accuracy of the habitat-suitability assessment model for the Common Moorhen. The overall accuracy was 0.8, and the Kappa value was 0.60, which indicates that the model established in this study exhibited high credibility. To sum up, this is an applicable framework not only to assess the habitat suitability of farm ponds for Common Moorhens, but also to determine whether a particular location may require the implementation of conservation practices. Furthermore, the findings in this research can provide useful information to all relevant stakeholders involved in the implementation of wildlife-habitat conservation and restoration at farm ponds.
Augmented-Reality Visualization of Aerodynamics Simulation in Sustainable Cloud Computing
Authors: Kim Myungil , Yi Sukkeun , Jung Daeyong , Park Sangjin , Seo Dongwoo
Published: April 2018

This paper proposes visualization based on augmented reality (AR) for aerodynamics simulation in a sustainable cloud computing environment that allows the Son of Grid Engine different types of computers to perform concurrent job requests. A simulation of an indoor air-purification system is performed using OpenFOAM computational fluid dynamics solver in the cloud computing environment. Post-processing converts the results to a form that is suitable for AR visualization. Simulation results can be displayed on devices, such as smart phones, tablets, and Microsoft HoloLens. This AR visualization allows for users to monitor purification of indoor air in real time.
A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services
Authors: Tirkolaee Erfan , Hosseinabadi Ali , Soltani Mehdi , Sangaiah Arun , Wang Jin
Published: April 2018

Greenhouse gases (GHG) are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing Problem (G-CARP) with the aim of minimizing total cost including the cost of generation and emission of greenhouse gases, the cost of vehicle usage and routing cost. The cost of generation and emission of greenhouse gases is based on the calculation of the amount of carbon dioxide emitted from vehicles, which depends on such factors as the vehicle speed, weather conditions, load on the vehicle and traveled distance. The main applications of this problem are in municipalities for urban waste collection, road surface marking and so forth. Due to NP-hardness of the problem, a Hybrid Genetic Algorithm (HGA) is developed, wherein a heuristic and simulated annealing algorithm are applied to generate initial solutions and a Genetic Algorithm (GA) is then used to generate the best possible solution. The obtained numerical results indicate that the proposed algorithm could present desirable performance within a suitable computational run time. Finally, a sensitivity analysis is implemented on the maximum available time of the vehicles in order to determine the optimal policy.
Dependency of Businesses on Flows of Ecosystem Services: A Case Study from the County of Dorset, UK
Authors: Watson Stephen C. L. , Newton Adrian C.
Published: April 2018

Although it is widely assumed that business activity is dependent on flows of ecosystem services (ES), little evidence is available with which to evaluate this contention. To address this knowledge gap, we conducted a questionnaire survey of business dependencies on twenty-six different ES in the English county of Dorset, where the environment supports a significant component of the local economy. Responses were received from 212 businesses across twenty-eight sectors. While virtually all businesses (98%) were familiar with the concept of ES, dependency on ES was highly divided with 50% of businesses surveyed claiming no dependence on any ES flows. The highest businesses dependencies reported in this study were for regulating services with the ES of water quality and waste water treatment being of particular importance to businesses. The results however, advised that greater efforts are needed in highlighting the indirect benefits provided by Dorset’s ecosystems, with eight business sectors (58% of respondents) claiming no or little dependence on supporting and habitat services including the ES of biodiversity, habitats for species and maintenance of genetic diversity. Many businesses also indicated little or no dependence on the globally important ES of pollination and soil condition, which may reflect a lack of awareness of dependencies occurring upstream of their value chains. At the sector level, businesses directly involved in protecting, extracting, or manufacturing raw materials were found to be more dependent on provisioning, regulatory and supporting ES than those operating in the service sector who favored cultural ES. These results highlight the value of assessing business dependencies on ES flows, which could usefully inform environmental management and accounting systems and improve monitoring of business performance, and thereby contribute to achievement of sustainability goals.
Reinforcement Learning Based Data Self-Destruction Scheme for Secured Data Management
Authors: Kim Young Ki , Ullah Saeed , Kwon Kiuk , Jang Yunchul , Lee Jongsoo , Hong Choong Seon
Published: April 2018

As technologies and services that leverage cloud computing have evolved, the number of businesses and individuals who use them are increasing rapidly. In the course of using cloud services, as users store and use data that include personal information, research on privacy protection models to protect sensitive information in the cloud environment is becoming more important. As a solution to this problem, a self-destructing scheme has been proposed that prevents the decryption of encrypted user data after a certain period of time using a Distributed Hash Table (DHT) network. However, the existing self-destructing scheme does not mention how to set the number of key shares and the threshold value considering the environment of the dynamic DHT network. This paper proposes a method to set the parameters to generate the key shares needed for the self-destructing scheme considering the availability and security of data. The proposed method defines state, action, and reward of the reinforcement learning model based on the similarity of the graph, and applies the self-destructing scheme process by updating the parameter based on the reinforcement learning model. Through the proposed technique, key sharing parameters can be set in consideration of data availability and security in dynamic DHT network environments.
Liver Injury by Carbon Tetrachloride Intoxication in 16 Patients Treated with Forced Ventilation to Accelerate Toxin Removal via the Lungs: A Clinical Report
Authors: Teschke Rolf
Published: April 2018

Carbon tetrachloride (CCl4) is an efficient but highly toxic solvent, used in households and commercially in the industry under regulatory surveillance to ensure safety at the working place and to protect the workers’ health. However, acute unintentional or intentional intoxications by CCl4 may rarely occur and are potentially life-threatening. In this review article, therapy options are discussed that are based on a literature review of traditional poisoning cases and the clinical experience with 16 patients with acute poisoning by CCl4. Among various therapy options, the CO2-induced hyperventilation therapy will be considered in detail as the most promising approach. This special therapy was developed because only around 1% of the intoxicating CCl4 is responsible for the liver injury after conversion to toxic radicals via microsomal cytochrome P450 2E1 whereas 99% of the solvent will leave the body unchanged by exhalation. Therefore, to enhance CCl4 elimination through the lungs, CO2 is added to the inspiration air at a flow rate of 2–3 L min−1 in order to achieve hyperventilation with a respiratory volume of 25–30 L min−1. Under this therapy, the clinical course was favorable in 15/16 patients, corresponding to 93.8%. In essence, patients with acute CCl4 intoxication should be treated by forced ventilation.
Proteopeptidomic, Functional and Immunoreactivity Characterization of Bothrops moojeni Snake Venom: Influence of Snake Gender on Venom Composition
Authors: Amorim Fernanda Gobbi , Costa Tassia Rafaela , Baiwir Dominique , De Pauw Edwin , Quinton Loic , Sampaio Suely Vilela
Published: April 2018

Venom composition varies across snakes from all taxonomic levels and is influenced by the snakes’ age, habitat, diet, and sexual dimorphism. The present study reports the first in-depth investigation of venom composition in male and female Bothrops moojeni (B. moojeni) snakes (BmooM and BmooF, respectively) through three proteomics approaches associated with functional, cytotoxic, and immunoreactivity characterization. Compared with BmooM venom, BmooF venom exhibited weaker hyaluronidase, metalloproteinase, and phospholipase activity; stronger recognition by anti-bothropic serum; 1.4-fold stronger cytotoxicity; and greater number of peptides. The increased L-amino acid oxidase expression probably accounted for the stronger immunoreactivity and cytotoxicity of BmooF venom. BmooF and BmooM venom shared only 19% peptides. Some venom components were gender-specific, such as phospholipases B, phospholipase inhibitor, and hyaluronidases in BmooM, and cysteine-rich secretory proteins in BmooF. In conclusion, we describe herein the first proteomics study of B. moojeni snake venom and an in-depth characterization of gender-specific differences in venom composition. Altogether, our findings not only stress the importance of considering the snake’s gender during antivenom production, but also help to identify new potential drugs and biotechnological tools.
Anti-Inflammatory Effect of Baicalein on Polyinosinic–Polycytidylic Acid-Induced RAW 264.7 Mouse Macrophages
Authors: Kim Young-Jin , Kim Hyun-Ju , Lee Ji Young , Kim Do-Hoon , Kang Mi Suk , Park Wansu
Published: April 2018

Baicalein (3,3′,4′,5,6-pentahydroxyflavone) is a well-known antioxidant found in many plants, such as in the roots of Scutellaria baicalensis. In this study, we evaluate the inhibitory effect of baicalein on the inflammatory cascade in RAW 264.7 mouse macrophages induced by viral-like material. Experimental assays used in this study included Griess reagent assay for nitric oxide (NO) production, Fluo-4 assay for intracellular calcium release, multiplex cytokine assay, and quantitative real time RT-PCR assay. To induce inflammation, RAW 264.7 cells were treated with polyinosinic–polycytidylic acid (poly I:C), a synthetic analog of double-stranded RNA (dsRNA). Baicalein at concentrations up to 100 μM significantly inhibited the production of NO, IL-1α, IL-6, G-CSF, GM-CSF, VEGF, MCP-1, IP-10, LIX, and RANTES as well as calcium release in RAW 264.7 cells induced by poly I:C (50 µg/mL) (all p < 0.05). Baicalein at concentrations up to 50 μM also significantly inhibited mRNA expression of STAT1, STAT3, CHOP, and Fas in poly I:C-induced RAW 264.7 cells (p < 0.05). In conclusion, baicalein has anti-inflammatory effect in double-stranded RNA (dsRNA)-induced macrophages by inhibiting NO, cytokines, chemokines, and growth factors via the endoplasmic reticulum stress–CHOP/STAT pathway.
Influence of Gravel-Bed Porosity and Grain Orientation on Bulk Flow Resistance
Authors: Navaratnam Christy Ushanth , Aberle Jochen , Qin Jie , Henry Pierre-Yves
Published: April 2018

This paper presents results from experiments that were carried out to study the effect of porosity and grain orientation on flow resistance. Experiments were performed over three rough surfaces; a water-worked gravel-bed, its non-porous facsimile (cast-bed) and the rotated cast-bed (cast tiles rotated through 180°). The first two beds were used to isolate the influence of gravel-bed porosity on the bulk flow resistance and the rotated cast was used to study effect of the grain orientation on the flow resistance. The results showed that the rotated cast-bed exerted the highest flow resistance whereas the porous water-worked gravel-bed was, for comparable hydraulic boundary conditions, characterized by slightly higher flow resistance than its non-porous counterpart. The results from the bulk flow analysis were substantiated by a preliminary analysis of flow velocity data.
Analysis of the Precipitation Regime over the Ligurian Sea
Authors: Pensieri Sara , Schiano Maria Elisabetta , Picco Paola , Tizzi Marco , Bozzano Roberto
Published: April 2018

The regions surrounding the North West Mediterranean Sea are often sites of intense precipitation events, particularly during the autumn months. The many casualties and the high economic costs due to these events demand a continuous improvement in forecasting models in support of early warning systems. The main weather conditions that determine episodes of heavy rain over these regions are known, but the high number of processes and interactions taking place at different time and space scales makes it extremely difficult to increase the skill pertaining to their predictability. To deepen the knowledge of the phenomena, both numerical simulations and analysis of historical data sets are required. This paper presents the analysis of a five-year-long time series of rain data collected in the open Ligurian Sea from the fixed platform W1M3A and coastal stations. The analysis aims to characterize the main features of the precipitation over this area and its seasonal and annual variability. Furthermore, the work includes a description of the main atmospheric and oceanic surface parameters measured from the platform during some intense events that occurred in the period 2009–2013 and suggests to what extent offshore observations may contribute to improve the forecast of rainfall events.
The Water-Energy-Food Nexus: Climate Risks and Opportunities in Southern Africa
Authors: Nhamo Luxon , Ndlela Bekithemba , Nhemachena Charles , Mabhaudhi Tafadzwanashe , Mpandeli Sylvester , Matchaya Greenwell
Published: April 2018

The discourse on the need for water, energy, and food security has dominated the development agenda of southern African countries, centred on improving livelihoods, building resilience, and regional integration. About 60% of the population in the Southern African Development Community (SADC) live in rural areas relying mainly on rainfed agriculture, lacking access to clean water and energy, yet the region is endowed with vast natural resources. The water-energy-food (WEF) nexus is a conceptual framework that presents opportunities for greater resource coordination, management, and policy convergence across sectors. This is particularly relevant in the SADC region as resources are transboundary and supports efforts linked to regional integration and inclusive socio-economic development and security. We conducted an appraisal of WEF-related policies and institutions in SADC and identified linkages among them. The present ‘silo’ approach in resource management and allocation, often conducted at the national level, contributes to the region’s failure to meet its development targets, exacerbating its vulnerabilities. The lack of coordination of WEF nexus synergies and trade-offs in planning often threatens the sustainability of development initiatives. We highlighted the importance of the WEF nexus to sustainably address the sectoral coordination of resources through harmonised institutions and policies, as well as setting targets and indicators to direct and monitor nexus developments. We illustrate the significance of the nexus in promoting inclusive development and transforming vulnerable communities into resilient societies. The study recommends a set of integrated assessment models to monitor and evaluate the implementation of WEF nexus targets. Going forward, we propose the adoption of a regional WEF nexus framework.
Lagoon Sediment Dynamics: A Coupled Model to Study a Medium-Term Silting of Tidal Channels
Authors: Petti Marco , Bosa Silvia , Pascolo Sara
Published: April 2018

The silting of tidal channels is a natural process that affects several shallow lagoons and makes it difficult to navigate, requiring regular maintenance interventions. This phenomenon is the result of the complex non-linear interaction between tidal currents and wave motion. In this work, the morphodynamic evolution of the Marano and Grado lagoon is investigated by means of a two-dimensional horizontal (2DH) morphological-hydrodynamic and a spectral coupled model. An innovative procedure to reproduce the overall bathymetric changes in the medium term and, in particular, the volumes deposited inside channels, is presented. An average year with a sequence of winds and tides acting over that time was reconstructed, carrying out cross correlation techniques and spectral analyses of measured data. The predicted morphological evolution matches the annual dredged volumes in the lagoon critical branches and shows the distribution of erosion and deposition of cohesive sediments according to spatially variable values of critical shear stress.