bluuebunny/crossref_metadata_2025 huggingface dataset:
Faster R-CNN and Geometric Transformation-Based Detection of Driver’s Eyes Using Multiple Near-Infrared Camera Sensors
Authors: Park Sung Ho , Yoon Hyo Sik , Park Kang Ryoung
Published: January 2019

Studies are being actively conducted on camera-based driver gaze tracking in a vehicle environment for vehicle interfaces and analyzing forward attention for judging driver inattention. In existing studies on the single-camera-based method, there are frequent situations in which the eye information necessary for gaze tracking cannot be observed well in the camera input image owing to the turning of the driver’s head during driving. To solve this problem, existing studies have used multiple-camera-based methods to obtain images to track the driver’s gaze. However, this method has the drawback of an excessive computation process and processing time, as it involves detecting the eyes and extracting the features of all images obtained from multiple cameras. This makes it difficult to implement it in an actual vehicle environment. To solve these limitations of existing studies, this study proposes a method that uses a shallow convolutional neural network (CNN) for the images of the driver’s face acquired from two cameras to adaptively select camera images more suitable for detecting eye position; faster R-CNN is applied to the selected driver images, and after the driver’s eyes are detected, the eye positions of the camera image of the other side are mapped through a geometric transformation matrix. Experiments were conducted using the self-built Dongguk Dual Camera-based Driver Database (DDCD-DB1) including the images of 26 participants acquired from inside a vehicle and the Columbia Gaze Data Set (CAVE-DB) open database. The results confirmed that the performance of the proposed method is superior to those of the existing methods.
Wireless Charging Deployment in Sensor Networks
Authors: Lai Wei-Yu , Hsiang Tien-Ruey
Published: January 2019

Charging schemes utilizing mobile wireless chargers can be applied to prolong the lifespan of a wireless sensor network. In considering charging schemes with mobile chargers, most current studies focus on charging each sensor from a single position, then optimizing the moving paths of the chargers. However, in reality, a wireless charger may charge the same sensor from several positions in its path. In this paper we consider this fact and seek to minimize both the number of charging locations and the total required charging time. Two charging plans are developed. The first plan considers the charging time required by each sensor and greedily selects the charging service positions. The second one is a two-phase plan, where the number of charging positions is first minimized, then minimum charging times are assigned to every position according to the charging requirements of the nearby sensors. This paper also corrects a problem neglected by some studies in minimizing the number of charging service positions and further provides a corresponding solution. Empirical studies show that compared with other minimal clique partition (MCP)-based methods, the proposed charging plan may save up to 60% in terms of both the number of charging positions and the total required charging time.
Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data
Authors: Li Chenming , Wang Yongchang , Zhang Xiaoke , Gao Hongmin , Yang Yao , Wang Jiawei
Published: January 2019

With the development of high-resolution optical sensors, the classification of ground objects combined with multivariate optical sensors is a hot topic at present. Deep learning methods, such as convolutional neural networks, are applied to feature extraction and classification. In this work, a novel deep belief network (DBN) hyperspectral image classification method based on multivariate optical sensors and stacked by restricted Boltzmann machines is proposed. We introduced the DBN framework to classify spatial hyperspectral sensor data on the basis of DBN. Then, the improved method (combination of spectral and spatial information) was verified. After unsupervised pretraining and supervised fine-tuning, the DBN model could successfully learn features. Additionally, we added a logistic regression layer that could classify the hyperspectral images. Moreover, the proposed training method, which fuses spectral and spatial information, was tested over the Indian Pines and Pavia University datasets. The advantages of this method over traditional methods are as follows: (1) the network has deep structure and the ability of feature extraction is stronger than traditional classifiers; (2) experimental results indicate that our method outperforms traditional classification and other deep learning approaches.
In-Fiber Mach-Zehnder Interferometer Based on Three-Core Fiber for Measurement of Directional Bending
Authors: Ding Lei , Li Yu , Zhou Cai , Hu Min , Xiong Yuli , Zeng Zhongliang
Published: January 2019

A highly sensitive directional bending sensor based on a three-core fiber (TCF) Mach-Zehnder interferometer (MZI) is presented in this study. This MZI-based bending sensor was fabricated by fusion-splicing a section of TCF between two single-mode fibers (SMF) with core-offset. Due to the location of the core in the TCF, a bend applied to the TCF-based MZI led to an elongation or shortening of the core, which makes the sensor suitable for directional bending measurement. To analyze the bending characteristics, two types of TCF-based sensors, with the fusion-spliced core located at different positions between the SMFs, were investigated. A swept source was employed in the measurement technique. The experimental results showed that, for the two types of sensors in this setup, the bending sensitivities of the two sensors were 15.36 nm/m−1 and 3.11 nm/m−1 at the bending direction of 0°, and −20.48 nm/m−1 and −5.29 nm/m−1 at the bending direction of 180°. The temperature sensitivities of the two sensors were 0.043 nm/°C and 0.041 nm/°C, respectively. The proposed sensors are compact, versatile, inexpensive to fabricate, and are expected to have potential applications in biomedical sensing.
Low-Dose Computed Tomography Image Super-Resolution Reconstruction via Random Forests
Authors: Gu Peijian , Jiang Changhui , Ji Min , Zhang Qiyang , Ge Yongshuai , Liang Dong , Liu Xin , Yang Yongfeng , Zheng Hairong , Hu Zhanli
Published: January 2019

Aiming at reducing computed tomography (CT) scan radiation while ensuring CT image quality, a new low-dose CT super-resolution reconstruction method based on combining a random forest with coupled dictionary learning is proposed. The random forest classifier finds the optimal solution of the mapping relationship between low-dose CT (LDCT) images and high-dose CT (HDCT) images and then completes CT image reconstruction by coupled dictionary learning. An iterative method is developed to improve robustness, the important coefficients for the tree structure are discussed and the optimal solutions are reported. The proposed method is further compared with a traditional interpolation method. The results show that the proposed algorithm can obtain a higher peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) and has better ability to reduce noise and artifacts. This method can be applied to many different medical imaging fields in the future and the addition of computer multithreaded computing can reduce time consumption.
A Tangible Solution for Hand Motion Tracking in Clinical Applications
Authors: Salchow-Hömmen Christina , Callies Leonie , Laidig Daniel , Valtin Markus , Schauer Thomas , Seel Thomas
Published: January 2019

Objective real-time assessment of hand motion is crucial in many clinical applications including technically-assisted physical rehabilitation of the upper extremity. We propose an inertial-sensor-based hand motion tracking system and a set of dual-quaternion-based methods for estimation of finger segment orientations and fingertip positions. The proposed system addresses the specific requirements of clinical applications in two ways: (1) In contrast to glove-based approaches, the proposed solution maintains the sense of touch. (2) In contrast to previous work, the proposed methods avoid the use of complex calibration procedures, which means that they are suitable for patients with severe motor impairment of the hand. To overcome the limited significance of validation in lab environments with homogeneous magnetic fields, we validate the proposed system using functional hand motions in the presence of severe magnetic disturbances as they appear in realistic clinical settings. We show that standard sensor fusion methods that rely on magnetometer readings may perform well in perfect laboratory environments but can lead to more than 15 cm root-mean-square error for the fingertip distances in realistic environments, while our advanced method yields root-mean-square errors below 2 cm for all performed motions.
City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT Devices
Authors: Johnston Steven J. , Basford Philip J. , Bulot Florentin M. J. , Apetroaie-Cristea Mihaela , Easton Natasha H. C. , Davenport Charlie , Foster Gavin L. , Loxham Matthew , Morris Andrew K. R. , Cox Simon J.
Published: January 2019

Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment, six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that (i) the physical device developed can operate at a city scale; (ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends; (iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project, a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.
Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals
Authors: Tayeb Zied , Fedjaev Juri , Ghaboosi Nejla , Richter Christoph , Everding Lukas , Qu Xingwei , Wu Yingyu , Cheng Gordon , Conradt Jörg
Published: January 2019

Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject’s motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g., hand movements. This type of BCI has been widely studied and used as an alternative mode of communication and environmental control for disabled patients, such as those suffering from a brainstem stroke or a spinal cord injury (SCI). Notwithstanding the success of traditional machine learning methods in classifying EEG signals, these methods still rely on hand-crafted features. The extraction of such features is a difficult task due to the high non-stationarity of EEG signals, which is a major cause by the stagnating progress in classification performance. Remarkable advances in deep learning methods allow end-to-end learning without any feature engineering, which could benefit BCI motor imagery applications. We developed three deep learning models: (1) A long short-term memory (LSTM); (2) a spectrogram-based convolutional neural network model (CNN); and (3) a recurrent convolutional neural network (RCNN), for decoding motor imagery movements directly from raw EEG signals without (any manual) feature engineering. Results were evaluated on our own publicly available, EEG data collected from 20 subjects and on an existing dataset known as 2b EEG dataset from “BCI Competition IV”. Overall, better classification performance was achieved with deep learning models compared to state-of-the art machine learning techniques, which could chart a route ahead for developing new robust techniques for EEG signal decoding. We underpin this point by demonstrating the successful real-time control of a robotic arm using our CNN based BCI.
Decoupling of Airborne Dynamic Bending Deformation Angle and Its Application in the High-Accuracy Transfer Alignment Process
Authors: Yang Ping , Chen Xiyuan , Wang Junwei
Published: January 2019

In the traditional airborne distributed position and orientation system (DPOS) transfer alignment process, the coupling angle between the dynamic deformation and body angular motion is not estimated or compensated, which causes the process to have low precision and long convergence time. To achieve high-precision transfer alignment, a decoupling method for the airborne dynamic deformation angle is proposed in this paper. The model of the coupling angle is established through mathematical derivation. Then, taking the coupling angle into consideration, angular velocity error and velocity error between the master INS and slave IMU are corrected. Based on this, a novel 27-state Kalman filter model is established. Simulation results demonstrate that, compared with the traditional transfer alignment model, the model proposed in this paper has faster convergence time and higher accuracy.
Implicit Calibration Using Probable Fixation Targets
Authors: Kasprowski Pawel , Harȩżlak Katarzyna , Skurowski Przemysław
Published: January 2019

Proper calibration of eye movement signal registered by an eye tracker seems to be one of the main challenges in popularizing eye trackers as yet another user-input device. Classic calibration methods taking time and imposing unnatural behavior on eyes must be replaced by intelligent methods that are able to calibrate the signal without conscious cooperation by the user. Such an implicit calibration requires some knowledge about the stimulus a user is looking at and takes into account this information to predict probable gaze targets. This paper describes a possible method to perform implicit calibration: it starts with finding probable fixation targets (PFTs), then it uses these targets to build a mapping-probable gaze path. Various algorithms that may be used for finding PFTs and mappings are presented in the paper and errors are calculated using two datasets registered with two different types of eye trackers. The results show that although for now the implicit calibration provides results worse than the classic one, it may be comparable with it and sufficient for some applications.
Development of a LeNet-5 Gas Identification CNN Structure for Electronic Noses
Authors: Wei Guangfen , Li Gang , Zhao Jie , He Aixiang
Published: January 2019

A new LeNet-5 gas identification convolutional neural network structure for electronic noses is proposed and developed in this paper. Inspired by the tremendous achievements made by convolutional neural networks in the field of computer vision, the LeNet-5 was adopted and improved for a 12-sensor array based electronic nose system. Response data of the electronic nose to different concentrations of CO, CH4 and their mixtures were acquired by an automated gas distribution and test system. By adjusting the parameters of the CNN structure, the gas LeNet-5 was improved to recognize the three categories of CO, CH4 and their mixtures omitting the concentration influences. The final gas identification accuracy rate reached 98.67% with the unused data as test set by the improved gas LeNet-5. Comparison with results of Multiple Layer Perceptron neural networks and Probabilistic Neural Network verifies the improvement of recognition rate while with the same level of time cost, which proved the effectiveness of the proposed approach.
The Role of Military Service in the Integration/Segregation of Muslims, Christians and Druze within Israel
Authors: Zeedan Rami
Published: January 2019

This study applies the negative peace/positive peace approach to internal nation-state relations between the majority and ethnic minority. This approach focuses on the policies implemented by the state. In order to understand the social system from its formation, an important focus should be given to the period of establishment of a new state, whereas physical borders are defined along with the borders of society, which determines who is included in the new nation and who is excluded. The conclusions are based on the case of the Israeli Druze, an ethnic minority with whom the state of Israel and its Jewish majority have achieved positive peace. This study suggests that the positive peace with the Druze was achieved following their integration in the army—as a decision of the state of Israel—that lead to their integration in the Israeli society. Conversely to the Israeli Muslims, where a negative peace is maintained, following the early year’s state policy to exclude them.
Mothers’ Perceptions of the Phenomenon of Bullying among Young Children in South Korea
Authors: Ju Hyun-jung , Lee Seung-ha
Published: January 2019

This study aimed to investigate mothers’ different perspectives on bullying in early childhood. Twelve mothers having children under eight years old were interviewed in South Korea. All the interviews were transcribed in Korean and analyzed using Nvivo. The constant comparison method was used to analyze the data. The results showed six themes consisting of categories: (1) concept of bullying (2) difficulty in defining bullying in early childhood, (3) difficulty in telling other mothers about bullying, (4) children who do not reveal their experiences, (5) ways to be aware of bullying, and (6) mothers’ concern. Categories were sometimes divided into subcategories. Findings showed that mothers seemed to view bullying differently, and that relationships among them contributed to differences in their perspectives on bullying. Mothers’ relationships also interacted with children’s relationships. Children were unlikely to tell their victimization experiences, due to certain reasons. These findings can contribute to understanding the nature of bullying in early childhood, increasing the social awareness of bullying among young children, and emphasizing the need for intervention/prevention programs.
The Effects of Maturity of Project Portfolio Management and Business Alignment on PMO Efficiency
Authors: Ko Joong Hoon , Kim Daecheol
Published: January 2019

The purpose of this research is to analyze efficiencies of project management offices (PMOs) using the data envelopment analysis (DEA). As the post-analysis of the efficiency analysis, the causal factors affecting the efficiencies of PMOs were tested. 87 PMOs were used to analyze their efficiencies. In the constant returns-to-scale model, 11 PMOs were completely efficient and 76 PMOs were inefficient. In the variable returns-to-scale (VRS) model, 26 PMOs were efficient and 61 PMOs were inefficient. The efficiency analysis by the DEA has the advantage of deriving the scale efficiency for each DMU. From the result of the post-analysis, it was found that the PMO efficiency was positively influenced by the project portfolio management maturity (PPMM) and the degree of strategic alignments with the business goals. In conclusion, by improving PPMM and strengthening the strategic alignments with business goals, higher efficiency and performance of the PMO can be expected.
Assessing the Sustainable Room for Growth for a Particular Romanian Tourism Area of Business: The Case of Accommodation Businesses
Authors: Berinde Sorin-Romulus , Corpădean Adrian-Gabriel
Published: January 2019

In recent years, the Romanian accommodation business sector has recorded a dramatic increase in accommodation units, but even under these circumstances it is below half of the average registered by the European Union. The study aims to evaluate whether there is still room for sustainable growth in this regard. For this purpose, the accounting–financial indicators have been assessed for an annual average of 3447 companies reporting every year to the European Union for 18 years, between 1999 and 2016, for all the accommodation units in Romania and the European Union. For data processing and to assess sustainable growth, we have used simple regression and resorted to the distance method and the geometric mean method to analyze competitiveness. The findings show a likelihood of sustainable growth of 20.6% in the development of Romanian accommodation businesses, in the light of the aspects analyzed, correlated to the EU average. Some managerial decision-making suggestions are provided at the end of the paper for accommodation businesses’ sustainable growth, related to accounting–financial issues. For Romanian businesses, sustainable growth is promoted by the low level of staff costs and, to a lesser extent, by the investments made per employed person. For the corporate governance of these companies to recover growth space in terms of sustainability, managerial decisions should be taken to increase sales, profitability, production value and added value.
Entrepreneurial Business Ties and New Venture Growth: The Mediating Role of Resource Acquiring, Bundling and Leveraging
Authors: Wang Gang , Li Linwei , Jiang Xu
Published: January 2019

Adopting insights from a resource management perspective, this study investigates how entrepreneurs utilize their business ties to promote new venture growth. We propose a multiple mediator model in which different resource management processes (i.e., resource acquiring, resource bundling, and resource leveraging) act as critical mediating mechanisms. We undertook a two-stage survey design, and collected data during the period from 2013 to 2016. Drawing on a longitudinal sample of 229 new ventures in China, we tested the hypotheses through the optimal scaling regression (OSR) analysis. We find empirical support for the mediated effects of entrepreneurial business ties via resource bundling and resource leveraging to promote new venture growth. However, our results find the mediating effect of resource acquiring non-significant. These findings will deepen understanding of the role of entrepreneurial business ties in the new venture growth process and expand resource management perspective into the entrepreneurial field.
A Circular Economy Approach to Military Munitions: Valorization of Energetic Material from Ammunition Disposal through Incorporation in Civil Explosives
Authors: Ferreira Carlos , Ribeiro José , Clift Roland , Freire Fausto
Published: January 2019

Ammunition that has reached its end of life or become obsolete is considered hazardous waste due to the energetic material content that must be decommissioned. One of the technologies to dispose of ammunition involves the use of incinerators with sophisticated gas treatment systems; however, this disposal process has important limitations in terms of incinerator capacity, energy requirements and high costs. This article assesses the potential primary energy avoided and environmental benefits arising from the valorization of energetic material from military ammunition by incorporating it into civil emulsion explosives, as an alternative to destructive disposal. This approach follows the circular economy principle, as articulated inter alia in BS 8001:2007, by giving a new service to a residue through its incorporation into a new product. A prospective life-cycle model is implemented based on primary data from previous studies on the conventional disposal process and on the production of emulsion explosive. The model applies system expansion to calculate the environmental burdens avoided when energetic material from ammunition is incorporated into civil explosives. The results show that re-using ammunition through valorization of energetic material greatly reduces the environmental impacts in all categories compared to the conventional disposal process. The benefits arise mainly from avoiding the incineration and flue gas treatment processes in ammunition disposal, and displacing production of civil explosive components with the energetic material from ammunition.
Sources of Economic Growth: A Global Perspective
Authors: Błażejowski Marcin , Kwiatkowski Jacek , Gazda Jakub
Published: January 2019

The main goal of this paper is to determine the factors responsible for economic growth at the global level. The indication of the sources of economic growth may be an important element of the sustainable economic policy for development. The novelty of this research lies in employing an analysis based on data, which consist of an average growth rate of the Gross Domestic Product (GDP) for 168 countries for the years 2002–2013. The Bayesian model averaging approach is used to identify potential factors responsible for differences in countries’ GDPs. Additionally, a jointness analysis is performed to assess the potential independence, substitutability, and complementarity of the factors of economic growth. The robustness of the results is confirmed by Bayesian averaging of classical estimates. We identify the most probable factors of economic growth, and we find that the most important determinants are variables associated with the so-called “Asian development model”.
The Effect of Firewood Moisture Content on the Atmospheric Thermal Load by Flue Gases Emitted by a Boiler
Authors: Dzurenda Ladislav , Banski Adrian
Published: January 2019

In this paper, we present an analysis on the effect of the moisture content of firewood on the atmospheric thermal load created by the heating of flue gases with temperatures of tfg = 120–200 °C, emitted by a boiler when wood with moisture content of W = 10%–60% is combusted. The load of the atmosphere created by the heat of the flue gases with temperatures of ts = 120 °C from the boiler, where dried wood with the moisture content of W = 10% is combusted, is Q = 9.2 MJ·GJ−1. The atmospheric thermal load caused by flue gases with the temperature of ts = 200 °C, resulting from the combustion process of wet firewood with a moisture content of W = 60%, is 3.8 times higher compared with the above-mentioned conditions. The heating of water vapor from the evaporated water occurring in combusted wood, as well as the heat of the heated nitrogen and unoxidized oxygen in the combustion air delivered to the furnace of a firewood boiler, are considered to be reasons for the increasing atmospheric thermal load caused by the heating of flue gases, resulting from the combustion of wood with higher moisture content.
Evaluation of the Supply-Side Efficiency of China’s Real Estate Market: A Data Envelopment Analysis
Authors: Li Kai , Ma Zhili , Zhang Guozhou
Published: January 2019

With the gradual slowdown of economic growth in China, the Chinese government proposed the task of supply-side reform. As a vital part of China’s economy, supply-side reform in the real estate market is particularly important. Using 29 provinces (divided into seven regions) in China as examples, this paper empirically studies the supply-side efficiency of China’s real estate market using data envelopment analysis (DEA) for the period of 2012–2016. The results showed that (1) the main problem of low supply-side efficiency in the Chinese real estate market is the low land-use efficiency, with a redundancy rate of 60.59% in China’s land space pending development; and (2) China’s southeastern coastal region, with the highest supply-side efficiency in the real estate market, reached a level of decreasing returns, and it is no longer appropriate to increase the supply-side efficiency by expanding the market scale. However, the southwestern region and the Yangtze River’s middle region, which both have lower supply-side efficiency, can improve the land utilization ratio and technology investment to change the current situations. The study results suggest (1) improving the construction land development efficiency by adjusting the input and output of the market according to the specific conditions of each city, and (2) promoting the supply-side reform of China’s real estate market and sustainable urbanization.
The Contribution of China’s Civil Law to Sustainable Development: Progress and Prospects
Authors: Zhai Tiantian , Chang Yen-Chiang
Published: January 2019

Environmental protection is mainly the focus of environmental law in China, but as China has started to pursue ecological civilization, its civil law has begun to respond to environmental problems as well, which is called the “greening of civil law”. As a result, the newly passed General Provisions of Civil Law adopted a “Green Principle” requiring private actors to contribute to resources conservation and environmental protection in civil activities. Through normative and comparative analysis, this article explores the establishment of the “Green Principle”, the rationales for civil law’s response to environmental problems in China, the progress already made, and the further efforts that are needed. It argues that the major challenge for the greening of China’s civil law at present is the modification of the subsequent sections of the forthcoming civil code. Despite the progress that has already been made, further efforts are needed regarding the following aspects: environmental and resources protection should be taken into account in contract rules concerning the validity, performance, and interpretation of contracts, and rules on emission trading contracts should be added; the property section should stipulate the unified exercise of state ownership over natural resources; and the “personality rights” section should stipulate environmental rights so as to clarify the right that is violated in environmental public interest litigation.
Microwave Assisted Green Synthesis of Silver Nanoparticles Using Mulberry Leaves Extract and Silver Nitrate Solution
Authors: Liem Le Ngoc , The Nguyen Phuoc , Nguyen Dieu
Published: January 2019

In this work, silver nanoparticles (AgNPs) were synthesized quickly and in an eco-friendly manner using the extract of Mulberry leaves and aqueous solution of silver nitrate without any toxic chemicals (Yuet et al. Int. J. Nanomed. 2012, 7, 4263–4267; Krishnakuma and Adavallan. Adv. Nat. Sci. Nanosci. Nanotechnol. 2014, 5, 025018). The Mulberry leaves extract functions as both a stabilizing and reducing agent. The UV-Vis spectroscopy shows a peak maximum at 430 nm. The transmission electron microscopy (TEM) image illustrated of synthesized AgNPs were nearly spherical-shaped particles whose sizes range from 15 to 20 nm. The TEM image of Nano Silver solution sample synthesized by the microwave assisted method shows nearly spherical particles, with an average particle size estimated at 10 nm. The absorption UV-vis spectrum of silver nanoparticles synthesized by the microwave assisted method (AgNPsmw) shows a sharp absorption band around 415 nm. The UV-Vis spectrum of AgNPsmw after two months of storage shows negligible peak changes of silver nanoparticles.
Interannual Variability of Dinophysis acuminata and Protoceratium reticulatum in a Chilean Fjord: Insights from the Realized Niche Analysis
Authors: Alves-de-Souza Catharina , Iriarte José Luis , Mardones Jorge I.
Published: January 2019

Here, we present the interannual distribution of Dinophysis acuminata and Protoceratium reticulatum over a 10-year period in the Reloncaví Fjord, a highly stratified fjord in southern Chile. A realized subniche approach based on the Within Outlying Mean Index (WitOMI) was used to decompose the species’ realized niche into realized subniches (found within subsets of environmental conditions). The interannual distribution of both D. acuminata and P. reticulatum summer blooms was strongly influenced by climatological regional events, i.e., El Niño Southern Oscillation (ENSO) and the Southern Annual Mode (SAM). The two species showed distinct niche preferences, with blooms of D. acuminata occurring under La Niña conditions (cold years) and low river streamflow whereas P. reticulatum blooms were observed in years of El Niño conditions and positive SAM phase. The biological constraint exerted on the species was further estimated based on the difference between the existing fundamental subniche and the realized subniche. The observed patterns suggested that D. acuminata was subject to strong biological constraint during the studied period, probably as a result of low cell densities of its putative prey (the mixotrophic ciliate Mesodinium cf. rubrum) usually observed in the studied area.
Overview of Fungi and Mycotoxin Contamination in Capsicum Pepper and in Its Derivatives
Authors: Costa Jéssica , Rodríguez Rodrigo , Garcia-Cela Esther , Medina Angel , Magan Naresh , Lima Nelson , Battilani Paola , Santos Cledir
Published: January 2019

Capsicum products are widely commercialised and consumed worldwide. These substrates present unusual nutritional characteristics for microbial growth. Despite this, the presence of spoilage fungi and the co-occurrence of mycotoxins in the pepper production chain have been commonly detected. The main aim of this work was to review the critical control points, with a focus on mycotoxin contamination, during the production, storage and distribution of Capsicum products from a safety perspective; outlining the important role of ecophysiological factors in stimulating or inhibiting mycotoxin biosynthesis in these food commodities. Moreover, the human health risks caused by the ingestion of peppers contaminated with mycotoxins were also reviewed. Overall, Capsicum and its derivative-products are highly susceptible to contamination by mycotoxins. Pepper crop production and further transportation, processing and storage are crucial for production of safe food.
Recovery of Soil Hydraulic Properties for Assisted Passive and Active Restoration: Assessing Historical Land Use and Forest Structure
Authors: Lozano-Baez Sergio Esteban , Cooper Miguel , Frosini de Barros Ferraz Silvio , Ribeiro Rodrigues Ricardo , Castellini Mirko , Di Prima Simone
Published: January 2019

Tree planting and natural regeneration are the main approaches to achieve global forest restoration targets, affecting multiple hydrological processes, such as infiltration of rainfall. Our understanding of the effect of land use history and vegetation on the recovery of water infiltration and soil attributes in both restoration strategies is limited. Therefore, we investigated the recovery of top-soil saturated soil hydraulic conductivity (Ks), soil physical and hydraulic properties in five land use types: (i) a secondary old-growth forest; (ii) a forest established through assisted passive restoration 11 years ago; (iii) an actively restored forest, with a more intensive land use history and 11 years of age; (iv) a pasture with low-intensity use; and (v) a pasture with high-intensity use, in the Brazilian Atlantic Forest. For these land use types, we determined the historical land use patterns and conducted soil sampling, using the Beerkan method to determine Ks values in the field. We also measured tree basal area, canopy cover, vegetation height, tree density and species richness in forest covers. The Ks decreased when land use was more intense prior to forest restoration actions. Our results indicate that land use legacy is a crucial factor to explain the current difference in soil and vegetation attributes among study sites.
Comparison of Multiple Linear Regression, Artificial Neural Network, Extreme Learning Machine, and Support Vector Machine in Deriving Operation Rule of Hydropower Reservoir
Authors: Niu Wen-Jing , Feng Zhong-Kai , Feng Bao-Fei , Min Yao-Wu , Cheng Chun-Tian , Zhou Jian-Zhong
Published: January 2019

Operation rule plays an important role in the scientific management of hydropower reservoirs, because a scientifically sound operating rule can help operators make an approximately optimal decision with limited runoff prediction information. In past decades, various effective methods have been developed by researchers all the over world, but there are few publications evaluating the performances of different methods in deriving the hydropower reservoir operation rule. To achieve satisfying scheduling process triggered by limited streamflow data, four methods are used to derive the operation rule of hydropower reservoirs, including multiple linear regression (MLR), artificial neural network (ANN), extreme learning machine (ELM), and support vector machine (SVM). Then, the data from 1952 to 2015 in Hongjiadu reservoir of China are chosen as the survey case, and several quantitative statistical indexes are adopted to evaluate the performances of different models. The radial basis function is chosen as the kernel function of SVM, while the sigmoid function is used in the hidden layer of ELM and ANN. The simulations show that three artificial intelligence algorithms (ANN, SVM, and ELM) are able to provide better performances than the conventional MLR and scheduling graph method. Hence, for scholars in the hydropower operation field, the applications of artificial intelligence algorithms in deriving the operation rule of hydropower reservoir might be a challenge, but represents valuable research work for the future.
The Combination of Coagulation and Adsorption for Controlling Ultra-Filtration Membrane Fouling in Water Treatment
Authors: Bu Fan , Gao Baoyu , Yue Qinyan , Liu Caiyu , Wang Wenyu , Shen Xue
Published: January 2019

Ultra-filtration technology has been increasingly used in drinking water treatment due to improvements in membrane performance and lowering of costs. However, membrane fouling is the main limitation in the application of ultra-filtration technology. In this study, we investigated the impact of four different pre-treatments: Coagulation, adsorption, coagulation followed by adsorption (C-A), and simultaneous coagulation and adsorption (C+A), on membrane fouling and natural organic matter removal efficiency. The results showed that adsorption process required a large amount of adsorbent and formed a dense cake layer on the membrane surface leading to severe membrane fouling. Compared to adsorption alone, the coagulation and C-A processes decreased the transmembrane pressure by 4.9 kPa. It was due to less accumulation of particles on the membrane surface. As for water quality, the C-A ultra-filtration process achieved the highest removal efficiencies of natural organic matter and disinfection by-product precursors. Therefore, the addition of adsorbent after coagulation is a potentially important approach for alleviating ultra-filtration membrane fouling and enhancing treatment performance.
The Use of Non-Conventional Water Resources as a Means of Adaptation to Drought and Climate Change in Semi-Arid Regions: South-Eastern Spain
Authors: Morote Álvaro-Francisco , Olcina Jorge , Hernández María
Published: January 2019

Drought is a climatic risk with notable repercussions on water supply systems. The aim of this study is to analyze the principal measures for management and planning implemented during recent decades in south-eastern Spain (Segura River Basin) to respond to drought situations, focusing on the role played by non-conventional water resources (desalination and treated water). The results demonstrate that the study area (despite being one of the driest places of Spain) is less vulnerable to drought than regions with an Atlantic climate and greater availability of water. This has been possible thanks to the integration of non-conventional water resources as a means of adaptation to confront this natural risk, which is estimated to become more intense and frequent in the future owing to climate change.
STRESS ANALYSIS OF TURBINE COMPONENTS UNDER SPIN RIG THERMOMECHANICAL CONDITION
Authors: Witek Lucjan
Published: January 2019

This paper presents the stress analysis of a second stage turbine disc, subjected to spin rig test. To solve the problem, the finite element analysis of complex geometrical model of the disc/blade segment with much physical nonlinearity such as contact and plasticity was carried out. The adequate mechanical and thermal conditions for the spin rig test were next defined to determine the stress state of the disc/blade segment. High stress zones were found at the regions of the turbine where the first fatigue cracks are expected to appear. The results of this study are useful during the laboratory spin rig test of turbine. The zones of maximum stress indicated in this analysis will be in detail inspected under laboratory crack initiation and crack growth tests of turbine. For better understanding the phenomena occurring in spin rig test of turbine, the test details were also described.
Learner Support Experienced by RNs in a Collaborative Distance RN-to-BSN Program
Authors: Oehlkers Robert A , Gibson Chère C
Published: January 2019

ABSTRACT

Sixteen RN-to-BSN students participated in interviews at the start and at the completion of taking their first class from a newly implemented, university-based, collaborative distance learning program. The purpose of the taped, semi-structured telephone interviews was to identify the support RNs experienced. Institutional themes of support that emerged were orientation programs, technical support/ mentors, library resources, and prompt feedback from instructors. Non-institutional support themes focused on family, friends, peers, the workplace, and learners.
Enhancing Metacognition Through the Reflective Use of Self-Regulated Learning Strategies
Authors: Kuiper RuthAnne
Published: January 2019

ABSTRACT

Background: An important concern of nursing practice and education is the difficulty new graduates experience while making the transition from graduate nurse to practicing nurse.

Method: Using a comparative descriptive design, self-regulated learning strategies were used to enhance metacognitive critical thinking abilities as 32 new graduate nurses reflected during 8-week preceptorship programs.

Results: Verbal protocol analysis revealed the majority of noun referente as metacognitive with thinking nouns increasing in rank from Week 1 to Week 8, present tense verbs were used most frequently with lower-level thinking phrases. Common themes in the narrative were knowledge observation, thinking strategies, judgments of self-improvement, judgments of competence, judgments of resources, self-reactions, and selfcorrection strategies.

Conclusions: New graduate nurses have unique circumstances to overcome in making a transition to the workplace, and having self-regulatory skills would enable this process. The data suggest nursing education and practice consider self-regulated learning prompts with new graduates to promote thinking strategies.
New Choices for Continuing Education: A Statewide Survey of the Practices and Preferences of Nurse Practitioners
Authors: Charles Patricia A , Mamary Edward M
Published: January 2019

ABSTRACT

Technological innovations in the past decade have made possible several promising new modes for delivering continuing education (CE). Offering a wide variety of educational approaches is necessary to satisfy the different learning needs and preferences of program participants. Continuing education planners need to assess the preferences and practices of Advanced Practitioners of Nursing (AFNs) when choosing the modes they will offer for delivering CE programs. A survey was conducted with the entire population of licensed APNs in Nevada to assess practices, preferences, and barriers to use of various CE delivery modes. In-person conferences and live satellite conferences were the most frequently used methods. The top three preferences/ in rank order, were in-person conference, print-based self-study, and interactive video conference. Live satellite conference was the least preferred method of earning CE credits. Computer-based modes of CE delivery, which include the Internet and CD-ROM, were among the least used. Findings from this study provide useful information for planners of CE programs for APNs. Data acquired in this study also address the dearth of information related to computer use by APNs for obtaining CE.
Paddy Soil Profile Distribution of δ13C Subjected to Rice Straw Amendment and Burning
Authors: Kulsawat Wutthikrai , Porntepkasemsan Boonsom , Nochit Phatchada
Published: January 2019

Paddy residues are the most generous agricultural biomass from the paddy cultivation, Paddy residues practices include crop residue amendment and in-situ burning. It indicated that residue amendment increased the organic carbon and nutrient contents in soil, However, an open residue burning is still a common practice in Thailand despite of strict law enforcements and proper education to farmers about its implications on soil, human and animal health The present study determined how residues management practices: residue amendment and stubble burning, influence the soil organic carbon by determining δ13C in paddy soil profile. The 30 cm depth soil samples from the naturally straw amendment and stubble burning paddy fields were collected in Chiang Khwan district, Roi-et province during 2017. The δ13C values with soil depth showed that residue management practices produce statistical differences in both soils. The δ13C values of soil samples from amendment and burning sites ranged from-23.19‰ to-17.98‰ and-24.79‰ to-19.28‰, respectively. Carbon isotopes differentiate clearly between amendment site (more positive values) and burning site (more negative values). The results from this study were in accordance with literatures which reported that the δ13C distribution in the soil profile can be applied to study in SOC dynamics as a result of different paddy residue management practices (amendment or burning). Further research is needed to confirm the validity of the stable carbon isotope technique in this type of studies.
Inhibition of Coliform Bacteria by Lactic Acid Bacteria Isolated from Nham Hed (Fermented Mushroom)
Authors: Wittanalai Suttida , Tanruean Keerati , Mapoong Phanida
Published: January 2019

Four samples of Nham Hed which fermented from different carbon sources; Homnil rice (HN), sticky rice (SR), LeumPua rice (LP) and rice berry (RB) were evaluated for total viable count of lactic acid bacteria (LAB). The rice berry Nham Hed samples showed the highest of total lactic bacteria count with values 2.83 x 105 cfu/g. The thirty one distinct colonies of LAB were isolated and categorized into 6 groups on the basis of their colony characteristics on MRS agar, microscopic morphology and biochemical characteristic. These 6 isolates were screened for their antimicrobial activity against 2 strains of coliform bacteria and it was found that LAB isolate E exhibited the highest antimicrobial activity against Escherichia coli and Enterobacter sp. which the zone of inhibition zone 14.22 ± 1.50 mm and 13.38 ± 1.25 mm, respectively. According to the morphology characterization, isolate E was probably classified to Weissella spp. These obtained results revealed the possibility for further characterization and purification the antimicrobial compound produced by the studied isolate as food bio preservatives to control food spoilage and pathogenic bacteria.