bluuebunny/crossref_metadata_2025 huggingface dataset:
Agricultural Expansion and Intensification in the Foothills of Mount Kenya: A Landscape Perspective
Authors: Eckert Sandra , Kiteme Boniface , Njuguna Evanson , Zaehringer Julie
Published: August 2017

This study spatially assesses, quantifies, and visualizes the agricultural expansion and land use intensification in the northwestern foothills of Mount Kenya over the last 30 years: processes triggered by population growth, and, more recently, by large-scale commercial investments. We made use of Google Earth Engine to access the USGS Landsat data archive and to generate cloud-free seasonal composites. These enabled us to accurately differentiate between rainfed and irrigated cropland, which was important for assessing agricultural intensification. We developed three land cover and land use classifications using the random forest classifier, and assessed land cover and land use change by creating cross-tabulation matrices for the intervals from 1987 to 2002, 2002 to 2016, and 1987 to 2016 and calculating the net change. We then applied a landscape mosaic approach to each classification to identify landscape types categorized by land use intensity. We discuss the impacts of landscape changes on natural habitats, biodiversity, and water. Kappa accuracies for the three classifications lay between 78.3% and 82.1%. Our study confirms that rainfed and irrigated cropland expanded at the expense of natural habitats, including protected areas. Agricultural expansion took place mainly in the 1980s and 1990s, whereas agricultural intensification largely happened after 2000. Since then, not only large-scale producers, but also many smallholders have begun to practice irrigated farming. The spatial pattern of agricultural expansion and intensification in the study area is defined by water availability. Agricultural intensification and the expansion of horticulture agribusinesses increase pressure on water. Furthermore, the observed changes have heightened pressure on pasture and idle land due to the decrease in natural and agropastoral landscapes. Conflicts between pastoralists, smallholder farmers, large-scale ranches, and wildlife might further increase, particularly during the dry seasons and in years of extreme drought.
Autonomous Collection of Forest Field Reference—The Outlook and a First Step with UAV Laser Scanning
Authors: Jaakkola Anttoni , Hyyppä Juha , Yu Xiaowei , Kukko Antero , Kaartinen Harri , Liang Xinlian , Hyyppä Hannu , Wang Yunsheng
Published: August 2017

A compact solution for the accurate and automated collection of field data in forests has long been anticipated, and tremendous efforts have been made by applying various remote sensing technologies. The employment of advanced techniques, such as the smartphone-based relascope, terrestrial and mobile photogrammetry, and laser scanning, have led to steady progress, thus steering their applications to a practical stage. However, all recent strategies require human operation for data acquisition, either to place the instrument on site (e.g., terrestrial laser scanning, TLS) or to carry the instrument by an operator (e.g., personal laser scanning, PLS), which remained laborious and expensive. In this paper, a new concept of autonomous forest field investigation is proposed, which includes data collection above and inside the forest canopy by integrating an unmanned aircraft vehicle (UAV) with autonomous driving. As a first step towards realizing this concept, the feasibility of automated tree-level field measurements from a mini-UAV laser scanning system is evaluated. A “low-cost” Velodyne Puck LITE laser scanner is applied for the test. It is revealed that, with the above canopy flight data, the detection rate was 100% for isolated and dominant trees. The accuracy of direct measurements on the diameter at breast height (DBH) from the point cloud is between 5.5 and 6.8 cm due to the system and the methodological error propagation. The estimation of DBH from point cloud metrics, on the other hand, showed an accuracy of 2.6 cm, which is comparable to the accuracies obtained with terrestrial surveys using mobile laser scanning (MLS), TLS or photogrammetric point clouds. The estimation of basal area, stem volume and biomass of individual trees could be obtained with less than 20% RMSE, which is adequate for field reference measurements at tree level. Such results indicate that the concept of UAV laser scanning-based automated tree-level field reference collection can be feasible, even though the whole topic requires further research.
Preface: Land Surface Processes and Interactions—From HCMM to Sentinel Missions and Beyond
Authors: Su Zhongbo , Vekerdy Zoltán , Zeng Yijian
Published: August 2017

The scientific understanding of the energy and water fluxes between land and atmosphere primarily predicates our capacity to describe, model, and predict the highly complex Earth system, which is formed by mutually interlinked components (land, atmosphere, and ocean) [...]
Application of Abundance Map Reference Data for Spectral Unmixing
Authors: Williams McKay , Kerekes John , Aardt Jan
Published: August 2017

Reference data (“ground truth”) maps have traditionally been used to assess the accuracy of classification algorithms. These maps typically classify pixels or areas of imagery as belonging to a finite number of ground cover classes, but do not include sub-pixel abundance estimates; therefore, they are not sufficiently detailed to directly assess the performance of spectral unmixing algorithms. Our research aims to efficiently generate, validate, and apply abundance map reference data (AMRD) to airborne remote sensing scenes. Scene-wide AMRD for this study were generated using the remotely sensed reference data (RSRD) technique, which spatially aggregates classification or unmixing results from fine scale imagery (e.g., 1-m GSD) to co-located coarse scale imagery (e.g., 10-m GSD or larger). Validation of the accuracy of these methods was previously performed for generic 10 m × 10 m coarse scale imagery, resulting in AMRD with known accuracy. The purpose of this paper was to apply this previously validated AMRD to specific examples of airborne coarse scale imagery. Application of AMRD involved three main parts: (1) spatial alignment of coarse and fine scale imagery; (2) aggregation of fine scale abundances to produce coarse scale imagery specific AMRD; and (3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our new scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point-spread function (PSF) aggregation, and found that PSF returned lower error, but that rectangular aggregation more accurately estimated true AMRD at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including several new techniques which adjust for known error in the reference data itself. These metrics indicated that fully constrained linear unmixing of AVIRIS imagery across all three scenes returned an average error of 10.83% per class and pixel. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.
Sparse Representation Based Frequency Detection and Uncertainty Reduction in Blade Tip Timing Measurement for Multi-Mode Blade Vibration Monitoring
Authors: Pan Minghao , Yang Yongmin , Guan Fengjiao , Hu Haifeng , Xu Hailong
Published: August 2017

The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number.
Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands
Authors: Salem Salem , Higa Hiroto , Kim Hyungjun , Kobayashi Hiroshi , Oki Kazuo , Oki Taikan
Published: August 2017

Numerous algorithms have been proposed to retrieve chlorophyll-a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m−3, 16.25 mg·m−3, and 19.05 mg·m−3, respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll-a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the algorithms that incorporate the 665-nm band outperform other algorithms for measured dataset (RMSE = 36.84 mg·m−3), while algorithms that incorporate the band tuning approach provide the highest retrieval accuracy for the simulated dataset (RMSE = 25.05 mg·m−3).
Imaging of Subsurface Corrosion Using Gradient-Field Pulsed Eddy Current Probes with Uniform Field Excitation
Authors: Li Yong , Ren Shuting , Yan Bei , Zainal Abidin Ilham , Wang Yi
Published: August 2017

A corrosive environment leaves in-service conductive structures prone to subsurface corrosion which poses a severe threat to the structural integrity. It is indispensable to detect and quantitatively evaluate subsurface corrosion via non-destructive evaluation techniques. Although the gradient-field pulsed eddy current technique (GPEC) has been found to be superior in the evaluation of corrosion in conductors, it suffers from a technical drawback resulting from the non-uniform field excited by the conventional pancake coil. In light of this, a new GPEC probe with uniform field excitation for the imaging of subsurface corrosion is proposed in this paper. The excited uniform field makes the GPEC signal correspond only to the field perturbation due to the presence of subsurface corrosion, which benefits the corrosion profiling and sizing. A 3D analytical model of GPEC is established to analyze the characteristics of the uniform field induced within a conductor. Following this, experiments regarding the imaging of subsurface corrosion via GPEC have been carried out. It has been found from the results that the proposed GPEC probe with uniform field excitation not only applies to the imaging of subsurface corrosion in conductive structures, but provides high-sensitivity imaging results regarding the corrosion profile and opening size.
On-Chip High-Finesse Fabry-Perot Microcavities for Optical Sensing and Quantum Information
Authors: Bitarafan Mohammad , DeCorby Ray
Published: August 2017

For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities—with an air or vacuum gap between a pair of high reflectance mirrors—offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, and they enable atomic emitters or target analytes to be located at high field regions of the optical mode. Integration of curved-mirror Fabry-Perot cavities on chips containing electronic, optoelectronic, and optomechanical elements is a topic of emerging importance. Micro-fabrication techniques can be used to create mirrors with small radius-of-curvature, which is a prerequisite for cavities to support stable, small-volume modes. We review recent progress towards chip-based implementation of such cavities, and highlight their potential to address applications in sensing and cavity quantum electrodynamics.
A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring
Authors: García Óscar , Prieto Javier , Alonso Ricardo , Corchado Juan
Published: August 2017

Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated.
A Method to Reduce Non-Nominal Troposphere Error
Authors: Wang Zhipeng , Xin Pumin , Li Rui , Wang Shujing
Published: August 2017

Under abnormal troposphere, Ground-Based Augmentation System (GBAS) is unable to eliminate troposphere delay, resulting in non-nominal troposphere error. This paper analyzes the troposphere meteorological data of eight International GNSS Monitoring Assessment System (iGMAS) stations and 10 International GNSS Service (IGS) stations in China and records the most serious conditions during 2015 and 2016. Simulations show that the average increase in Vertical Protection Level (VPL) of all visible satellites under non-nominal troposphere is 2.32 m and that more satellites increase the VPL. To improve GBAS integrity, this paper proposes a satellite selection method to reduce the non-nominal troposphere error. First, the number of satellites in the optimal subset is determined to be 16 based on the relationship among VPL, non-nominal troposphere error and satellite geometry. Second, the distributions of the optimal satellites are determined. Finally, optimal satellites are selected in different elevation ranges. Results show that the average VPL increase caused by non-nominal troposphere error is 1.15 m using the proposed method. Compared with the brute method and greedy method, the running rate of the proposed method is improved by 390.91% and 111.65%, respectively. In summary, the proposed method balances the satellite geometry and non-nominal troposphere error while minimizing the VPL and improving the running rate.
Highly Sensitive Hot-Wire Anemometry Based on Macro-Sized Double-Walled Carbon Nanotube Strands
Authors: Wang Dingqu , Xiong Wei , Zhou Zhaoying , Zhu Rong , Yang Xing , Li Weihua , Jiang Yueyuan , Zhang Yajun
Published: August 2017

This paper presents a highly sensitive flow-rate sensor with carbon nanotubes (CNTs) as sensing elements. The sensor uses micro-size centimeters long double-walled CNT (DWCNT) strands as hot-wires to sense fluid velocity. In the theoretical analysis, the sensitivity of the sensor is demonstrated to be positively related to the ratio of its surface. We assemble the flow sensor by suspending the DWCNT strand directly on two tungsten prongs and dripping a small amount of silver glue onto each contact between the DWCNT and the prongs. The DWCNT exhibits a positive TCR of 1980 ppm/K. The self-heating effect on the DWCNT was observed while constant current was applied between the two prongs. This sensor can evidently respond to flow rate, and requires only several milliwatts to operate. We have, thus far, demonstrated that the CNT-based flow sensor has better sensitivity than the Pt-coated DWCNT sensor.
An Opto-Electronic Sensor for Detecting Soil Microarthropods and Estimating Their Size in Field Conditions
Authors: Gedeon Csongor , Flórián Norbert , Liszli Péter , Hambek-Oláh Beáta , Bánszegi Oxána , Schellenberger Judit , Dombos Miklós
Published: August 2017

Methods to estimate density of soil-dwelling arthropods efficiently, accurately and continuously are critical for investigating soil biological activity and evaluating soil management practices. Soil-dwelling arthropods are currently monitored manually. This method is invasive, and time- and labor-consuming. Here we describe an infrared opto-electronic sensor for detection of soil microarthropods in the size range of 0.4–10 mm. The sensor is built in a novel microarthropod trap designed for field conditions. It allows automated, on-line, in situ detection and body length estimation of soil microarthropods. In the opto-electronic sensor the light source is an infrared LED. Two plano-convex optical lenses are placed along the virtual optical axis. One lens on the receiver side is placed between the observation space at 0.5–1 times its focal length from the sensor, and another emitter side lens is placed between the observation space and the light source in the same way. This paper describes the setup and operating mechanism of the sensor and the control unit, and through basic tests it demonstrates its potential in automated detection of soil microarthropods. The sensor may be used for monitoring activities, especially for remote observation activities in soil and insect ecology or pest control.
A Chip for Estrogen Receptor Action: Detection of Biomarkers Released by MCF-7 Cells through Estrogenic and Anti-Estrogenic Effects
Authors: Gier Konstanze , Preininger Claudia , Sauer Ursula
Published: August 2017

The fluorescence-based multi-analyte chip platform for the analysis of estrogenic and anti-estrogenic substances is a new in vitro tool for the high throughput screening of environmental samples. In contrast to existing tools, the chip investigates the complex action of xenoestrogens in a human cell model by characterizing protein expression. It allows for the quantification of 10 proteins secreted by MCF-7 cells, representing various biological and pathological endpoints of endocrine action and distinguishing between estrogen- and anti-estrogen-dependent secretion of proteins. Distinct protein secretion patterns of the cancer cell line after exposure to known estrogen receptor agonists ß-estradiol, bisphenol A, genistein, and nonylphenol as well as antagonists fulvestrant and tamoxifen demonstrate the potential of the chip. Stimulation of cells with Interleukin-1ß shifts concentrations of low abundant biomarkers towards the working range of the chip. In the non-stimulated cell culture, Matrix Metalloproteinase 9 (MMP-9) and Vascular Endothelial Growth Factor (VEGF) show differences upon treatment with antagonists and agonists of the estrogen receptor. In stimulated MCF-7 cells challenged with receptor agonists secretion of Monocyte Chemoattractant Protein (MCP-1), Interleukin-6 (IL-6), Rantes, and Interleukin-8 (IL-8) significantly decreases. In parallel, the proliferating effect of endocrine-disrupting substances in MCF-7 cells is assessed in a proliferation assay based on resazurin. Using ethanol as a solvent for test substances increases the background of proliferation and secretion experiments, while using dimethyl sulfoxide (DMSO) does not show any adverse effects. The role of the selected biomarkers in different physiological processes such as cell development, reproduction, cancer, and metabolic syndrome makes the chip an excellent tool for either indicating endocrine-disrupting effects in food and environmental samples, or for screening the effect of xenoestrogens on a cellular and molecular level.
Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs
Authors: Javaid Nadeem , Ahmed Farwa , Wadud Zahid , Alrajeh Nabil , Alabed Mohamad , Ilahi Manzoor
Published: August 2017

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.
Impedance Matching Antenna-Integrated High-Efficiency Energy Harvesting Circuit
Authors: Shinki Yuharu , Shibata Kyohei , Mansour Mohamed , Kanaya Haruichi
Published: August 2017

This paper describes the design of a high-efficiency energy harvesting circuit with an integrated antenna. The circuit is composed of series resonance and boost rectifier circuits for converting radio frequency power into boosted direct current (DC) voltage. The measured output DC voltage is 5.67 V for an input of 100 mV at 900 MHz. Antenna input impedance matching is optimized for greater efficiency and miniaturization. The measured efficiency of this antenna-integrated energy harvester is 60% for −4.85 dBm input power and a load resistance equal to 20 kΩ at 905 MHz.
Postural Control in Workplace Safety: Role of Occupational Footwear and Workload
Authors: Chander Harish , Garner John , Wade Chip , Knight Adam
Published: August 2017

Maintaining postural stability is crucial, especially in hazardous occupational environments. The purpose of the study was to assess the role of three occupational footwear (low top shoe (LT); tactical work boot (TB) and steel-toed work boot (WB)) on postural stability when exposed to an occupational workload (4-h) involving standing/walking using the sensory organization test (SOT) equilibrium (EQ) scores and comparing current results with previously published postural sway variables from the same study. Fourteen male adults were tested on three separate days wearing a randomized occupational footwear, at the beginning (pre) and every 30 min of the 4-h workload until 240th min. SOT EQ scores were analyzed using a 3 × 9 repeated measures analysis of variance at an alpha level of 0.05. Significant differences between footwear was found in eyes open (p = 0.03) and eyes closed (p = 0.001) conditions. Pairwise comparisons revealed that LT had significantly lower postural stability compared to TB and WB. No other significant differences were found between footwear and over time. Significant differences between footwear can be attributed to design characteristics of footwear. Lack of significant differences over time suggests that, even though the average EQ scores decreased during the workload implying less postural stability, SOT EQ scores alone may not be sufficient to detect postural stability changes over the 4-h workload.
Acute and Chronic Effects of Isometric Handgrip Exercise on Cardiovascular Variables in Hypertensive Patients: A Systematic Review
Authors: Farah Breno , Germano-Soares Antônio , Rodrigues Sergio , Santos Camila , Barbosa Sávio , Vianna Lauro , Cornelissen Véronique , Ritti-Dias Raphael
Published: August 2017

The aim of this study was to describe, through a systematic review, the acute and chronic effects of isometric handgrip exercise on cardiovascular variables in hypertensive individuals. In this systematic review, we included studies that analyzed whether a single bout or a program with isometric exercises affect cardiovascular variables in hypertensive adults. The electronic database PubMed/Medline was searched for relevant studies published until May 2017. Of the 2927 studies initially identified, 2916 were excluded based on title and abstract and five on the basis of full-text assessment, leaving six studies remaining. In addition, one further study cited in the references of the included articles was included in this review, totaling seven studies included (five studies on the chronic effects of isometric handgrip exercise on cardiovascular parameters). None of the acute studies observed post-exercise hypotension. The majority of the chronic studies found decreases in office blood pressure after isometric handgrip training, with training ranging from 6 to 10 weeks, while heart rate variability parameters were improved in one study and did not change in another. Reduction in oxidative stress was observed; however, this variable was only analyzed in one study. In hypertensives, acute responses to isometric handgrip exercise are very limited due to the small number of studies, therefore more research is required. Furthermore, chronic isometric handgrip training reduces blood pressure; however, there is still a gap in the knowledge on the effects of this modality of exercise on other cardiovascular variables—such as endothelial function, oxidative stress, and cardiac autonomic modulation—which should be addressed in future studies.
Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia
Authors: Erokhin Vasilii
Published: August 2017

Providing sustainability of the food supply is becoming increasingly challenging in today’s rapidly changing global economic environment. Food security remains a serious problem, especially in developing countries where the challenge of the sustainable food supply is exacerbated by the rapid rise in the population, limited access to food intake, vulnerability, price volatilities, protection measures imposed by the government, and other distorting influences. Russia is classified as a middle-income country that is nationally self-sufficient in its food supply. However, amid the economic recession and restrictions on foreign trade in food, many households in Russia are becoming increasingly vulnerable to food insecurity. In the case of Russia, this paper aims to assess the sustainability of the food supply, and identify the factors that affect food security. In order to establish the impact of socio-economic variables on food security at the macroeconomic level, a regression model was estimated. The study has identified the factors that influence food security in terms of agricultural production, food self-sufficiency, and foreign trade. The relationships between the regressands and corresponding regressors have been discovered, in view of alternations between positive and negative influences on the dependent variables. Additionally, a significance of the relationships has been measured. The results of the regression analysis suggest that the sustainability of the food supply in Russia is threatened by inflation and a degrading purchasing power of the population from people shifting towards cheaper products of lower quality, while exporters seek higher profits outside the country and thus create food shortages in the domestic market.
Impact of Wind Electricity Forecasts on Bidding Strategies
Authors: Ballester Cristina , Furió Dolores
Published: August 2017

The change in the generation mix from conventional electricity sources to renewables has important implications for bidding behaviour and may have an impact on prices. The main goal of this work is to discover the role played by expected wind production, together with other relevant factors, in explaining the day-ahead market price through a data panel model. The Spanish market, given the huge increase in wind generation observed in the last decade, has been chosen for this study as a paradigmatic example. The results obtained suggest that wind power forecasts are a new key determinant for supply market participants when bidding in the day-ahead market. We also provide a conservative quantification of the effect of such trading strategies on marginal prices at an hourly level for a specific year in the sample. The consequence has been an increase in marginal price to levels higher than what could be expected in a context with notable wind penetration. Therefore, the findings of this work are of interest to practitioners and regulators and support the existence of a wind risk premium embedded in electricity prices to compensate for the uncertainty of wind production.
Sustainable Design: A Case of Environmental and Cost Life Cycle Assessment of a Kitchen Designed for Seniors and Disabled People
Authors: Lewandowska Anna , Branowski Bogdan , Joachimiak-Lechman Katarzyna , Kurczewski Przemyslaw , Selech Jaroslaw , Zablocki Marek
Published: August 2017

Sustainable production and consumption patterns require a change in approach at the early conceptual stages, i.e., when planning and designing products and services. This article presents an example of sustainable kitchen design aimed at the needs of seniors and people with physical disabilities, which takes into account social, economic, and environmental aspects. The interdisciplinary project team used a variety of traditional design methods such as the identification of requirements using QFD (Quality Function Deployment) and FMEA (Failure Mode Effects Analysis), the development and verification of the technical concepts of the designed objects and their use, the development of construction and technological documentation, assembly drawings of the product architecture and its parts, function cost analysis, virtual and real prototyping, and tools based on the concept of a life cycle such as environmental life cycle assessment (LCA) and life cycle costing (LCC). The analysis of the design solutions from the point of view of several criteria and several life cycle stages shows the complexity of the decision-making process and the difficulties in selecting a clearly favourable solution. Environmentally preferred materials may be difficult for users to accept due to their costs. On the other hand, materials that have a high environmental impact at the production stage may show great potential for final disposal.
Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach
Authors: Dong Jun , Huo Huijuan , Liu Dongran , Li Rong
Published: August 2017

In order to guarantee the sustainability of power industries, demand response is widely developed in China with the improvement of power markets. Massive potential flexible resources in the commercial sector are valuable to carry out continuous demand response programs. This paper presented a hybrid framework to evaluate the performance of such programs. Considering that assessment processes involve multiple decisions for massive criteria under fuzzy conditions, we proposed a fuzzy multi-criteria decision making model to evaluate the performance of commercial demand response based on the concepts of a fuzzy Vlsekriterijumska Optimizacijia I Kompromisno Resenje method and a L2-metric distance. The weighting determination process in the model was modified by integrating subjective opinions and objective information according to a fuzzy Analytic Hierarchy Process and Criteria Importance Through Intercriteria Correlation methods. Then a comprehensive evaluation index system for demand response performance was established by using a fuzzy Delphi method based on experts’ opinions, including the five aspects of economy, society, technology, environment and management. Finally, the practicality of the proposed hybrid framework was verified through an empirical analysis of five such programs in Chinese commercial buildings. Their comprehensive performances were ranked effectively. Sub-criteria affiliated with society and environment should be more attention than the other evaluation criteria based on experts’ judgments and objective information. Moreover, a set of sensitivity analyses were performed to confirm the robustness and effectiveness of the proposed framework and the evaluation results. The study findings can offer references for the improvement of demand response and relevant policy formulation.
Crop Parameters for Modeling Sugarcane under Rainfed Conditions in Mexico
Authors: Baez-Gonzalez Alma , Kiniry James , Meki Manyowa , Williams Jimmy , Alvarez-Cilva Marcelino , Ramos-Gonzalez Jose , Magallanes-Estala Agustin , Zapata-Buenfil Gonzalo
Published: August 2017

Crop models with well-tested parameters may help improve sugarcane productivity for food and biofuel generation, especially in rainfed areas where studies are scarce. This study aimed to calibrate crop parameters for the sugarcane cultivar CP 72-2086, an early-maturing cultivar widely grown in Mexico and other countries, and evaluate their adequacy in simulating sugarcane in a diverse range of rainfed conditions. For the calibration and evaluation of parameters, the ALMANAC model was used with climate, soil, management, and yield for two growing seasons from 30 farms in three regions (Northeastern Mexico, Gulf of Mexico, and Pacific Mexico). Statistical analyses were made using regression analysis and mean squared deviation and its three components, i.e., the squared bias, the lack of correlation weighted by the standard deviations, and the squared difference between standard deviations. Model simulations with a light extinction coefficient (k) of 0.69, maximum leaf area index of 7.5, leaf area index decline rate of 0.3, optimal and minimum temperature for plant growth of 32 °C and 11 °C, respectively, potential heat units of 6000 to 7400 degree days (base 11 °C), harvest index of 0.9; maximum crop height of 4.0 m, and root depth of 2.0 m showed highest accuracy and captured best the magnitude of yield fluctuations with a root mean squared deviation of 7.8 Mg ha−1. The parameters were found to be reasonable to use in simulating sugarcane in diverse regions under rainfed conditions. Using a dynamic value of k (varying during the growing season) deserves further study as it may help improve crop model precision.
Measuring Efficiency and Effectiveness of Highway Management in Sustainability
Authors: Choi NakHyeok , Jung Kyujin
Published: August 2017

This study analyses efficiency and effectiveness of highway management at the state level in the United States. While the current literature on highway management has contributed to understanding infrastructure budget and finance, the relationship between efficiency and effectiveness measurements has not been sufficiently discussed in the context of sustainability. To fill this gap, this study was systemically designed to test the relationship by controlling the states’ political factors, fiscal capacity, median voter, and economic conditions. Data envelopment and principal component analysis with panel data covering 11-year time waves were used to measure both efficiency and effectiveness. The results of the fixed effects model and the spatial autoregressive panel model show a statistically strong relationship between efficiency and effectiveness which are respectively measured by two analysis approaches.
Recognition of Traffic Sign Based on Bag-of-Words and Artificial Neural Network
Authors: Islam Kh Tohidul , Raj Ram Gopal , Mujtaba Ghulam
Published: August 2017

The traffic sign recognition system is a support system that can be useful to give notification and warning to drivers. It may be effective for traffic conditions on the current road traffic system. A robust artificial intelligence based traffic sign recognition system can support the driver and significantly reduce driving risk and injury. It performs by recognizing and interpreting various traffic sign using vision-based information. This study aims to recognize the well-maintained, un-maintained, standard, and non-standard traffic signs using the Bag-of-Words and the Artificial Neural Network techniques. This research work employs a Bag-of-Words model on the Speeded Up Robust Features descriptors of the road traffic signs. A robust classifier Artificial Neural Network has been employed to recognize the traffic sign in its respective class. The proposed system has been trained and tested to determine the suitable neural network architecture. The experimental results showed high accuracy of classification of traffic signs including complex background images. The proposed traffic sign detection and recognition system obtained 99.00% classification accuracy with a 1.00% false positive rate. For real-time implementation and deployment, this marginal false positive rate may increase reliability and stability of the proposed system.
Analysis of the Masked Metabolite of Deoxynivalenol and Fusarium Resistance in CIMMYT Wheat Germplasm
Authors: Nakagawa Hiroyuki , He Xinyao , Matsuo Yosuke , Singh Pawan , Kushiro Masayo
Published: August 2017

Fusarium head blight (FHB) causes significant grain loss and contamination of grains with harmful mycotoxins, especially deoxynivalenol (DON). Fusarium resistance and DON accumulation have been extensively investigated in various cultivars; however, the level of DON-3-O-glucoside (D3G) has not been as carefully studied. In this study, we measured accumulated DON and D3G levels in CIMMYT wheat elite germplasm using an analytical method validated in-house. Co-occurring nivalenol (NIV) and ergostrerol (ERG) were also analyzed. LC-MS/MS and LC-UV analyses were applied to the 50 CIMMYT elite wheat lines. D3G showed rather high correlation with DON (r = 0.82), while FHB symptoms showed slight correlation with DON and D3G (r = 0.36 and 0.32, respectively). D3G/DON ratio varied widely from 8.1 to 37.7%, and the ratio was not related with FHB resistance in this dataset.
Evaluation of Taterapox Virus in Small Animals
Authors: Parker Scott , Crump Ryan , Hartzler Hollyce , Buller R.
Published: August 2017

Taterapox virus (TATV), which was isolated from an African gerbil (Tatera kempi) in 1975, is the most closely related virus to variola; however, only the original report has examined its virology. We have evaluated the tropism of TATV in vivo in small animals. We found that TATV does not infect Graphiurus kelleni, a species of African dormouse, but does induce seroconversion in the Mongolian gerbil (Meriones unguiculatus) and in mice; however, in wild-type mice and gerbils, the virus produces an unapparent infection. Following intranasal and footpad inoculations with 1 × 106 plaque forming units (PFU) of TATV, immunocompromised stat1−/− mice showed signs of disease but did not die; however, SCID mice were susceptible to intranasal and footpad infections with 100% mortality observed by Day 35 and Day 54, respectively. We show that death is unlikely to be a result of the virus mutating to have increased virulence and that SCID mice are capable of transmitting TATV to C57BL/6 and C57BL/6 stat1−/− animals; however, transmission did not occur from TATV inoculated wild-type or stat1−/− mice. Comparisons with ectromelia (the etiological agent of mousepox) suggest that TATV behaves differently both at the site of inoculation and in the immune response that it triggers.
A Method of Evaluating Water Resource Assets and Liabilities: A Case Study of Jinan City, Shandong Province
Authors: Yang Yuheng , Liu Yang , Cao Shengle , Cheng Yufei
Published: August 2017

The traditional concepts of water resource development and utilization have caused serious hydrological and environmental issues in some regions. In addition, policy issues in China have led to a severe water crisis. The quantitative accounting of water resources is a theoretical approach to solving these problems. In this paper, 13 indicators were selected from four classes, including resources, the environment, society, and efficiency, and a case study of Jinan, Shandong Province, was performed using a set pair analysis model to calculate the water resource assets from 2011–2015. In previous methods of water resource accounting, the water quality was not considered; therefore, the loss coefficient of water resource assets was proposed to improve the reliability of accounting. According to the relationships among the unit price of water, water quantity, and water quality, physical and quantitative accounting methods were used to create water balance sheets from 2011–2015. The calculation results showed that the physical change in water resource assets in Jinan City was −30 million m 3 , and water resource assets initially increased and then decreased. In 2011, 2012, 2013, 2014, and 2015, water resource assets totalled 36.5 million USD, 45.9 million USD, 66.7 million USD, 35.5 million USD, and 37.5 million USD, respectively (at 6.4588, 6.3125, 6.1932, 6.2166, 6.2284 USRMB, respectively). This initial accounting provides quantitative and physical support for the improved management of water resources.
Biomechanical comparison of pin and nitinol bone staple fixation to pin and tension band wire fixation for the stabilization of canine olecranon osteotomies
Authors: Christou Chris , Bailey Craig , Tan Chris , Culvenor John , Wang Tian , Walsh William , Lai Alen
Published: August 2017

Objective: To compare the initial biomechanical properties of olecranon osteotomies stabilized with intramedullary pins and a Nitinol bone staple to osteotomies stabilized with pin and tension band wire fixation.

Study design: Ex vivo mechanical evaluation on cadaveric bones.

Material and methods: Ten pairs of cadaveric forelimbs from skeletally mature Greyhounds with an olecranon osteotomy stabilized with either a pin and Nitinol bone staple or a pin and tension band wire. A single load to failure was applied to each specimen through the triceps tendon. Biomechanical properties were compared based on stiffness, yield load, and maximum load to failure and load at 2 mm of axial displacement.

Results: Specimens stabilized with the bone staple were biomechanically superior in all the variables tested. There was significantly greater stiffness (118.0 ± 25.9 N/mm versus 70.1 ± 40.4 N/mm; p = 0.005), yield load (319.0 ± 99.8 N versus 238.0 ± 42.5 N; p = 0.03), maximum load sustained (385.0 ± 99.2 N versus 287.0 ± 37.4 N; p = 0.009), and load at 2 mm of axial displacement (218.0 ± 51.5 N versus 138.0 ± 48.7 N; p = 0.002) in specimens stabilized with pins and a Nitinol bone staple than specimens stabilized with pin and tension band wire fixation.

Clinical significance: The pin and Nitinol bone staple construct provides a biomechanically superior alternative to pin and tension band wire fixation for stabilization of olecranon osteotomies, and its use warrants further clinical investigation.

Supplementary material for this article is available at https://doi.org/10.3415/VCOT-17-02-0025
Long Noncoding RNA NEAT1 Promotes Proliferation and Invasion via Targeting miR-181a-5p in Non-Small Cell Lung Cancer
Authors: Li ShiDong , Yang JiaMei , Xia Yubing , Fan QingXia , Yang Kun-peng
Published: August 2017

Long noncoding RNAs (lncRNAs) have been implicated in various biological processes and pathological conditions, including tumorigenesis. However, the exact roles of NEAT1 and its underlying mechanisms in non-small cell lung cancer (NSCLC) remain largely unclear. In the present study,
lncRNA NEAT1 was detected to be significantly upregulated in NSCLC tissues and closely associated with advanced TNM stages, lymph node metastasis, distant metastasis, and poor prognosis. Further experiments revealed that lncRNA NEAT1 silencing inhibited cell proliferation and invasion in vitro.
In addition, mechanistic analysis showed that lncRNA NEAT1 upregulated the miR-181a-5p-targeted gene HMGB2 through acting as a competitive “sponge” of miR-181a-5p. In conclusion, our study suggested that lncRNA NEAT1 plays an oncogenic role in NSCLC progression and provides potential mechanisms by which lncRNA NEAT1 contributes to this disease.
Emodin Induces Apoptosis of Colon Cancer Cells via Induction of Autophagy in a ROS-Dependent Manner
Authors: Wang Yuanyuan , Luo Qin , He Xianlu , Wei He , Wang Ting , Shao Jichun , Jiang Xinni
Published: August 2017

Recent studies revealed that emodin extracted from Chinese herbs exhibits an anticancer effect on different cancer types, including colon cancer. However, the mechanism is not well understood. In our study, we confirmed that emodin treatment inhibited cell viability and induced apoptosis
in colon cancer cells. Further experiments found that emodin was also able to induce autophagy, which is indispensible for apoptosis induced by emodin. More interestingly, emodin treatment also results in mitochondrial dysfunction and ROS accumulation in colon cancer cells. Finally, we stressed
that ROS accumulation is essential for autophagy and apoptosis induced by emodin. In conclusion, emodin induces apoptosis in colon cancer cells through induction of autophagy, during which ROS generation is of the essence. Our findings improve understanding of emodin’s effect on colon
cancer suppression and provide a new theoretical basis for colon cancer therapy.