bluuebunny/crossref_metadata_2025 huggingface dataset:
Motion Estimation-Assisted Denoising for an Efficient Combination with an HEVC Encoder
Authors: Lee Seung-Yong , Rhee Chae Eun
Published: February 2019

Noise, which is commonly generated in low-light environments or by low-performance cameras, is a major cause of the degradation of compression efficiency. In previous studies that attempted to combine a denoise algorithm and a video encoder, denoising was used independently of the code for pre-processing or post-processing. However, this process must be tightly coupled with encoding because noise affects the compression efficiency greatly. In addition, this represents a major opportunity to reduce the computational complexity, because the encoding process and a denoise algorithm have many similarities. In this paper, a simple, add-on denoising scheme is proposed through a combination of high-efficiency video coding (HEVC) and block matching three-dimensional collaborative filtering (BM3D) algorithms. It is known that BM3D has excellent denoise performance but that it is limited in its use due to its high computational complexity. This paper employs motion estimation in HEVC to replace the block matching of BM3D so that most of the time-consuming functions are shared. To overcome the challenging algorithmic differences, the hierarchical structure in HEVC is uniquely utilized. As a result, the computational complexity is drastically reduced while the competitive performance capabilities in terms of coding efficiency and denoising quality are maintained.
Improving AoA Localization Accuracy in Wireless Acoustic Sensor Networks with Angular Probability Density Functions
Authors: Thoen Bart , Wielandt Stijn , De Strycker Lieven
Published: February 2019

Advances in energy efficient electronic components create new opportunities for wireless acoustic sensor networks. Such sensors can be deployed to localize unwanted and unexpected sound events in surveillance applications, home assisted living, etc. This research focused on a wireless acoustic sensor network with low-profile low-power linear MEMS microphone arrays, enabling the retrieval of angular information of sound events. The angular information was wirelessly transmitted to a central server, which estimated the location of the sound event. Common angle-of-arrival localization approaches use triangulation, however this article presents a way of using angular probability density functions combined with a matching algorithm to localize sound events. First, two computationally efficient delay-based angle-of-arrival calculation methods were investigated. The matching algorithm is described and compared to a common triangulation approach. The two localization algorithms were experimentally evaluated in a 4.25 m by 9.20 m room, localizing white noise and vocal sounds. The results demonstrate the superior accuracy of the proposed matching algorithm over a common triangulation approach. When localizing a white noise source, an accuracy improvement of up to 114% was achieved.
Contact-Based Methods for Measuring Respiratory Rate
Authors: Massaroni Carlo , Nicolò Andrea , Lo Presti Daniela , Sacchetti Massimo , Silvestri Sergio , Schena Emiliano
Published: February 2019

There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject’s body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.
Graphene Decorated with Iron Oxide Nanoparticles for Highly Sensitive Interaction with Volatile Organic Compounds
Authors: Rodner Marius , Puglisi Donatella , Ekeroth Sebastian , Helmersson Ulf , Shtepliuk Ivan , Yakimova Rositsa , Skallberg Andreas , Uvdal Kajsa , Schütze Andreas , Eriksson Jens
Published: February 2019

Gases, such as nitrogen dioxide, formaldehyde and benzene, are toxic even at very low concentrations. However, so far there are no low-cost sensors available with sufficiently low detection limits and desired response times, which are able to detect them in the ranges relevant for air quality control. In this work, we address both, detection of small gas amounts and fast response times, using epitaxially grown graphene decorated with iron oxide nanoparticles. This hybrid surface is used as a sensing layer to detect formaldehyde and benzene at concentrations of relevance (low parts per billion). The performance enhancement was additionally validated using density functional theory calculations to see the effect of decoration on binding energies between the gas molecules and the sensor surface. Moreover, the time constants can be drastically reduced using a derivative sensor signal readout, allowing the sensor to work at detection limits and sampling rates desired for air quality monitoring applications.
ICENET: An Information Centric Protocol for Big Data Wireless Sensor Networks
Authors: Lachowski Rosana , Pellenz Marcelo E. , Jamhour Edgard , Penna Manoel C. , Brante Glauber , Moritz Guilherme , Souza Richard D.
Published: February 2019

Wireless Sensors Networks (WSNs) are an essential element of the Internet of Things (IoT), and are the main producers of big data. Collecting a huge amount of data produced by a resource-constrained network is a very difficult task, presenting several challenges. Big data gathering involves not only periodic data sensing, but also the forwarding of queries and commands to the network. Conventional network protocols present unfeasible strategies for large-scale networks and may not be directly applicable to IoT environments. Information-Centric Networking is a revolutionary paradigm that can overcome such big data gathering challenges. In this work, we propose a soft-state information-centric protocol, ICENET (Information Centric protocol for sEnsor NETworks), for big data gathering in large-scale WSNs. ICENET can efficiently propagate user queries in a wireless network by using a soft-state recovery mechanism for lossy links. The scalability of our solution is evaluated in different network scenarios. Results show that the proposed protocol presents approximately 84% less overhead and a higher data delivery rate than the CoAP (Constrained Application Protocol), which is a popular protocol for IoT environments.
Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics
Authors: Byeon Yeong-Hyeon , Pan Sung-Bum , Kwak Keun-Chang
Published: February 2019

This paper conducts a comparative analysis of deep models in biometrics using scalogram of electrocardiogram (ECG). A scalogram is the absolute value of the continuous wavelet transform coefficients of a signal. Since biometrics using ECG signals are sensitive to noise, studies have been conducted by transforming signals into a frequency domain that is efficient for analyzing noisy signals. By transforming the signal from the time domain to the frequency domain using the wavelet, the 1-D signal becomes a 2-D matrix, and it could be analyzed at multiresolution. However, this process makes signal analysis morphologically complex. This means that existing simple classifiers could perform poorly. We investigate the possibility of using the scalogram of ECG as input to deep convolutional neural networks of deep learning, which exhibit optimal performance for the classification of morphological imagery. When training data is small or hardware is insufficient for training, transfer learning can be used with pretrained deep models to reduce learning time, and classify it well enough. In this paper, AlexNet, GoogLeNet, and ResNet are considered as deep models of convolutional neural network. The experiments are performed on two databases for performance evaluation. Physikalisch-Technische Bundesanstalt (PTB)-ECG is a well-known database, while Chosun University (CU)-ECG is directly built for this study using the developed ECG sensor. The ResNet was 0.73%—0.27% higher than AlexNet or GoogLeNet on PTB-ECG—and the ResNet was 0.94%—0.12% higher than AlexNet or GoogLeNet on CU-ECG.
A Magnet-Based Timing System to Detect Gate Crossings in Alpine Ski Racing
Authors: Fasel Benedikt , Spörri Jörg , Kröll Josef , Müller Erich , Aminian Kamiar
Published: February 2019

In alpine skiing, intermediate times are usually measured with photocells. However, for practical reasons, the number of intermediate cells is limited to three–four, making a detailed timing analysis difficult. In this paper, we propose and validate a magnet-based timing system allowing for the measurement of intermediate times at each gate. Specially designed magnets were placed at each gate and the athletes wore small magnetometers on their lower back to measure the instantaneous magnetic field. The athlete’s gate crossings caused peaks in the measured signal which could then be related to the precise instants of gate crossings. The system was validated against photocells placed at four gates of a slalom skiing course. Eight athletes skied the course twice and one run per athlete was included in the validation study. The 95% error intervals for gate-to-gate timing and section times were below 0.025 s. Each athlete’s gate-to-gate times were compared to the group’s average gate-to-gate times, revealing small performance differences that would otherwise be difficult to measure with a traditional photocell-based system. The system could be used to identify the effect of tactical choices and athlete specific skiing skills on performance and could allow a more efficient and athlete-specific performance analysis and feedback.
Driver Drowsiness Detection Based on Steering Wheel Data Applying Adaptive Neuro-Fuzzy Feature Selection
Authors: Arefnezhad Sadegh , Samiee Sajjad , Eichberger Arno , Nahvi Ali
Published: February 2019

This paper presents a novel feature selection method to design a non-invasive driver drowsiness detection system based on steering wheel data. The proposed feature selector can select the most related features to the drowsiness level to improve the classification accuracy. This method is based on the combination of the filter and wrapper feature selection algorithms using adaptive neuro-fuzzy inference system (ANFIS). In this method firstly, four different filter indexes are applied on extracted features from steering wheel data. After that, output values of each filter index are imported as inputs to a fuzzy inference system to determine the importance degree of each feature and select the most important features. Then, the selected features are imported to a support vector machine (SVM) for binary classification to classify the driving conditions in two classes of drowsy and awake. Finally, the classifier accuracy is exploited to adjust parameters of an adaptive fuzzy system using a particle swarm optimization (PSO) algorithm. The experimental data were collected from about 20.5 h of driving in the simulator. The results show that the drowsiness detection system is working with a high accuracy and also confirm that this method is more accurate than the recent available algorithms.
Community as Story and the Dynamic Nature of Community: Perceptions, Place, and Narratives about Change
Authors: Cope Michael R. , Park Paige N. , Jackson Jorden E. , Muirbrook Kayci A. , Sanders Scott R. , Ward Carol , Brown Ralph B.
Published: February 2019

We present a theoretical discussion conceptualizing “community as story”—narratives that create and recreate one’s definition of and relationship to their community. We use a variety of disciplinary sources and representative quotes to help develop the theory. In so doing, we discuss the importance of subjective perception, narrative and place to the creation of a community story. Community stories take place in time and place, and as changes to the place occur, residents are compelled to adjust their stories and definitions. These changes are reflected in narratives that reminisce about what the community was and what it is becoming. The narratives then become part of a new community story. Above and beyond our theoretical conceptualization of “community as story”, to help illustrate our arguments in an empirical setting, we present a historical narrative from interviews with residents of Vance, Alabama, home of the Mercedes-Benz plant, which discuss the changing nature of and relationship to their community after the arrival of the plant in the 1990s.
Wolves’ Conservation through Educational Workshops: Which Method Works Best?
Authors: Oražem Vesna , Tomažič Iztok , Kos Ivan , Nagode Dolores , Randler Christoph
Published: February 2019

(1) Background: Conservation biology education is an important societal goal, targeting the worldwide promotion of biodiversity conservation. When learning about animals, direct experience poses an ideal opportunity to influence the participants’ attitudes and knowledge. However, in the case of large carnivores, direct experiences are scarcely possible, except at local zoos. School teaching should therefore rely on preserved materials, which are still originals. (2) Methods: Here, we investigated how students’ attitudes and knowledge regarding wolves can be improved in three different teaching contexts: (a) through conventional lectures, (b) through lectures combined with hands-on activities in the real classroom setting, and (c) through lectures with hands-on activities at the university. Students from general and vocational (veterinary) upper secondary school participated in the study. Attitudes and knowledge were tested before and after the teaching. (3) Results: Students displayed positive attitudes toward wolves and their prior knowledge had the highest influence on attitude ratings. Knowledge about wolves improved during teaching regardless of the teaching approach. The highest influence on attitudes and knowledge was observed in the university setting. (4) Conclusion: The university setting evidently produces the strongest effect so it is a recommended approach when designing conservational topics.
Ensuring the Safety Sustainability of Large UAS: Learning from the Maintenance Risk Dynamics of USAF MQ-1 Predator Fleet in Last Two Decades
Authors: Lu Yi , Qian Ying , Huangfu Huayan , Zhang Shuguang , Fu Shan
Published: February 2019

The mishap statistics of large military unmanned aerial systems (UAS) reveal that human errors and organizational flaws pose great threats to their operation safety, especially considering the future application of derived civilian types. Moreover, maintenance accidents due to human factors have reached a significant level, but have received little attention in the existing research. To ensure the safety and sustainability of large UAS, we propose a system dynamics approach to model the maintenance risk mechanisms involving organizational, human, and technical factors, which made a breakthrough in the traditional event-chain static analysis method. Using the United States Air Force (USAF) MQ-1 Predator fleet case, the derived time-domain simulation represented the risk evolution process of the past two decades and verified the rationality of the proposed model. It was identified that the effects of maintainer human factors on the accident rate exceeded those of the technical systems in a long-term view, even though the technical reliability improvements had obvious initial effects on risk reduction. The characteristics of maintainer errors should be considered in system and maintenance procedure design to prevent them in a proactive way. It is also shown that the approach-derived SD model can be developed into a semi-quantitative decision-making support tool for improving the safety of large UAS in a risk-based view of airworthiness.
Shifts in Climatic Niche Occupation in Astrophytum Coahuilense (H. Möller) Kayser and Its Potential Distribution in Mexico
Authors: Cardoza-Martínez Gabriel Fernando , Becerra-López Jorge Luis , Esparza-Estrada Citlalli Edith , Estrada-Rodríguez José Luis , Czaja Alexander , Ehsan Muhammad , Baltierra-Trejo Eduardo , Romero-Méndez Ulises
Published: February 2019

It has frequently been reported that species with strong niche conservatism will not be able to adapt to new climatic conditions, so they must migrate or go extinct. We have evaluated the shifts in climatic niche occupation of the species Astrophytum coahuilense and its potential distribution in Mexico. We understand niche occupation as the geographic zones with available habitats and with the presence of the species. To assess shifts in climatic niche occupation, we used niche overlap analysis, while potential distribution modeling was performed based on the principle of maximum entropy. The results indicate that this species presents a limited amplitude in its climate niche. This restriction of the climatic niche of A. coahuilense limits its ability to colonize new geographical areas with different climatic environments. On the other hand, the potential distribution models obtained from the present study allow us to identify potential zones based on the climatic requirements of the species. This information is important to identify high priority areas for the conservation of A. coahuilense.
Application of Artificial Neural Network for Predicting Maize Production in South Africa
Authors: Adisa Omolola M. , Botai Joel O. , Adeola Abiodun M. , Hassen Abubeker , Botai Christina M. , Darkey Daniel , Tesfamariam Eyob
Published: February 2019

The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R2 of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.
Recovering-Innovation-Exportation Triangle as an Instrument for Sustainable Development: Proposal for Peruvian Agro-Export Development
Authors: Asmat-Campos David , Carreño-Ortega Ángel , Díaz-Pérez Manuel
Published: February 2019

This study aims to investigate one of the most traditional Peruvian income generators: the agricultural sector, addressing specifically endogenous fruits. Based on sales data related to local and external markets, it is shown that nowadays farmers from several regions and towns have changed the practice of sowing endogenous fruits for the trading of lands and the sowing of other types of products. This has caused the farmer’s economic and social recoil within the agricultural sector. We restrict our study to the case of lucuma (Pouteria Lucuma), an endogenous fruit possessing excellent nutritional properties and exotic flavor that can be used for the production of a variety of products. These features make it an exportable product with great acceptance in international markets, but mainly in its dehydrated form. Therefore, in order to stimulate farmers’ exporting opportunities, it is necessary to transform their products by employing clean technologies that, at the same time, reduce production costs. In this sense, we propose a set of strategies to revitalize the sowing of lucuma in regions where it used to be cultivated, as well as to promote a sustainable business program based on the use of an innovative proposal for hybrid solar dehydration process (dehydration process that preserves the organoleptic properties, which is different from other processes). This will assist the commercialization of farmers’ products in local and international markets, as well as complying with the quality standards required for agro-export.
Bibliometric Analysis of Trends in Global Sustainable Livelihood Research
Authors: Zhang Chenjia , Fang Yiping , Chen Xiujuan , Congshan Tian
Published: February 2019

The concept of sustainable livelihoods (SL) is one of the most important subjects of sustainable development, and is an important long-term goal for poverty alleviation. There has been growing interest in the nature and practical application of SL in recent decades. This paper applies bibliometric analysis to collect and analyze data on sustainable livelihoods from the expanded Science Citation index (SCIE) and the Social Sciences Citation Index (SSCI). Bibliometric maps can assist greatly in visualizing and summarizing large volumes of data and in studying scientific outputs. The findings offer insights into research trends pertaining to SL, such as these: (1) In recent decades there has been an increase in both the number of papers on SL and their scientific influence. (2) The most active journals are Sustainability, Ecology and Society, Land Use Policy, and International Journal of Sustainable Development and World Ecology. (3) SL papers are distributed mainly in the fields of Environmental Sciences, Environmental Studies, Ecology, Planning & Development, and Green & Sustainable Science & Technology. (4) The USA and UK are leaders in SL research as measured by both the quantity and quality of SL publications. Some developing countries, notably India and China, have seen an increase in SL publications in recent years. (5) Wageningen University in Netherlands, the Chinese Academy of Science, and the Center for International Forestry Research (CIFOR), headquartered in Indonesia, have had a major influence in the field of international SL research. (6) International cooperation has a positive effect on the growth of SL research, suggesting that there is a need for strengthening cooperation among countries, international institutions, and individuals. (7) Major areas of SL research (“hot topics”) are theoretical research on the SL concept; ecosystem conservation; poverty reduction in the poverty-stricken areas; the impact of climate change on livelihoods; and linkages between SL-related policies and institutional change.
Hybrid Weighted Arithmetic and Geometric Aggregation Operator of Neutrosophic Cubic Sets for MADM
Authors: Shi Lilian , Yuan Yue
Published: February 2019

Neutrosophic cubic sets (NCSs) can express complex multi-attribute decision-making (MADM) problems with its interval and single-valued neutrosophic numbers simultaneously. The weighted arithmetic average (WAA) and geometric average (WGA) operators are common aggregation operators for handling MADM problems. However, the neutrosophic cubic weighted arithmetic average (NCWAA) and neutrosophic cubic geometric weighted average (NCWGA) operators may result in some unreasonable aggregated values in some cases. In order to overcome the drawbacks of the NCWAA and NCWGA, this paper developed a new neutrosophic cubic hybrid weighted arithmetic and geometric aggregation (NCHWAGA) operator and investigates its suitability and effectiveness. Then, we established a MADM method based on the NCHWAGA operator. Finally, a MADM problem with neutrosophic cubic information was provided to illustrate the application and effectiveness of the proposed method.
An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec
Authors: Yeh Cheng-Yu , Huang Hung-Hsun
Published: February 2019

Adaptive multi-rate wideband (AMR-WB) speech codecs have been widely used for high speech quality in modern mobile communication systems, e.g., handheld mobile devices. Nevertheless, a major handicap is that a remarkable computational load is required in the vector quantization (VQ) of immittance spectral frequency (ISF) coefficients of an AMR-WB coding. In view of this, a two-stage search algorithm is presented in this paper as an efficient way to reduce the computational complexity of ISF quantization in AMR-WB coding. At stage 1, an input vector is assigned to a search subspace in an efficient manner using the binary search space-structured VQ (BSS-VQ) algorithm, and a codebook search is performed over the subspace at stage 2 using the iterative triangular inequality elimination (ITIE) approach. Through the use of the codeword rejection mechanisms equipped in both stages, the computational load can be remarkably reduced. As compared with the original version of the BSS-VQ algorithm, the upgraded version provides a computational load reduction of up to 51%. Furthermore, this work is expected to satisfy the energy saving requirement when implemented on an AMR-WB codec of mobile devices.
Global Image Thresholding Adaptive Neuro-Fuzzy Inference System Trained with Fuzzy Inclusion and Entropy Measures
Authors: Bogiatzis Athanasios , Papadopoulos Basil
Published: February 2019

Thresholding algorithms segment an image into two parts (foreground and background) by producing a binary version of our initial input. It is a complex procedure (due to the distinctive characteristics of each image) which often constitutes the initial step of other image processing or computer vision applications. Global techniques calculate a single threshold for the whole image while local techniques calculate a different threshold for each pixel based on specific attributes of its local area. In some of our previous work, we introduced some specific fuzzy inclusion and entropy measures which we efficiently managed to use on both global and local thresholding. The general method which we presented was an open and adaptable procedure, it was free of sensitivity or bias parameters and it involved image classification, mathematical functions, a fuzzy symmetrical triangular number and some criteria of choosing between two possible thresholds. Here, we continue this research and try to avoid all these by automatically connecting our measures with the wanted threshold using some Artificial Neural Network (ANN). Using an ANN in image segmentation is not uncommon especially in the domain of medical images. However, our proposition involves the use of an Adaptive Neuro-Fuzzy Inference System (ANFIS) which means that all we need is a proper database. It is a simple and immediate method which could provide researchers with an alternative approach to the thresholding problem considering that they probably have at their disposal some appropriate and specialized data.
Global In-Silico Scenario of tRNA Genes and Their Organization in Virus Genomes
Authors: Morgado Sergio , Vicente Ana Carolina
Published: February 2019

Viruses are known to be highly dependent on the host translation machinery for their protein synthesis. However, tRNA genes are occasionally identified in such organisms, and in addition, few of them harbor tRNA gene clusters comprising dozens of genes. Recently, tRNA gene clusters have been shown to occur among the three domains of life. In such a scenario, the viruses could play a role in the dispersion of such structures among these organisms. Thus, in order to reveal the prevalence of tRNA genes as well as tRNA gene clusters in viruses, we performed an unbiased large-scale genome survey. Interestingly, tRNA genes were predicted in ssDNA (single-stranded DNA) and ssRNA (single-stranded RNA) viruses as well in many other dsDNA viruses of families from Caudovirales order. In the latter group, tRNA gene clusters composed of 15 to 37 tRNA genes were characterized, mainly in bacteriophages, enlarging the occurrence of such structures within viruses. These bacteriophages were from hosts that encompass five phyla and 34 genera. This in-silico study presents the current global scenario of tRNA genes and their organization in virus genomes, contributing and opening questions to be explored in further studies concerning the role of the translation apparatus in these organisms.
Estimating Disability-Adjusted Life Years (DALYs) in Community Cases of Norovirus in England
Authors: Harris John P. , Iturriza-Gomara Miren , O’Brien Sarah J.
Published: February 2019

Disability adjusted life years (DALYs) have been used since the 1990s. It is a composite measure of years of life lost with years lived with disability. Essentially, one DALY is the equivalent of a year of healthy life lost if a person had not experienced disease. Norovirus is the most common cause of gastrointestinal diseases worldwide. Norovirus activity varies from one season to the next for reasons not fully explained. Infection with norovirus is generally not severe, and is normally characterized as mild and self-limiting with no long-term sequelae. In this study, we model a range of estimates of DALYs for community cases of norovirus in England and Wales. We estimated a range of DALYs for norovirus to account for mixing of the severity of disease and the range of length of illness experienced by infected people. Our estimates were between 1159 and 4283 DALYs per year, or 0.3–1.2 years of healthy life lost per thousand cases of norovirus. These estimates provide evidence that norovirus leads to a considerable level of ill health in England and Wales. This information will be helpful should candidate norovirus vaccines become available in the future.
Chronic Hepatitis E in Rheumatology and Internal Medicine Patients: A Retrospective Multicenter European Cohort Study
Authors: Pischke Sven , Peron Jean-Marie , von Wulffen Moritz , von Felden Johann , Höner zu Siederdissen Christoph , Fournier Sophie , Lütgehetmann Marc , Iking-Konert Christoph , Bettinger Dominik , Par Gabriella , Thimme Robert , Cantagrel Alain , Lohse Ansgar W. , Wedemeyer Heiner , de Man Robert , Mallet Vincent
Published: February 2019

Objectives: Hepatitis E virus (HEV) infection is a pandemic with regional outbreaks, including in industrialized countries. HEV infection is usually self-limiting but can progress to chronic hepatitis E in transplant recipients and HIV-infected patients. Whether other immunocompromised hosts, including rheumatology and internal medicine patients, are at risk of developing chronic HEV infection is unclear. Methods: We conducted a retrospective European multicenter cohort study involving 21 rheumatology and internal medicine patients with HEV infection between April 2014 and April 2016. The underlying diseases included rheumatoid arthritis (n = 5), psoriatic arthritis (n = 4), other variants of chronic arthritis (n = 4), primary immunodeficiency (n = 3), systemic granulomatosis (n = 2), lupus erythematosus (n = 1), Erdheim–Chester disease (n = 1), and retroperitoneal fibrosis (n = 1). Results: HEV infection lasting longer than 3 months was observed in seven (33%) patients, including two (40%) patients with rheumatoid arthritis, three (100%) patients with primary immunodeficiency, one (100%) patient with retroperitoneal fibrosis and one (100%) patient with systemic granulomatosis. Patients with HEV infection lasting longer than 3 months were treated with methotrexate without corticosteroids (n = 2), mycophenolate mofetil/prednisone (n = 1), and sirolimus/prednisone (n = 1). Overall, 8/21 (38%) and 11/21 (52%) patients cleared HEV with and without ribavirin treatment, respectively. One patient experienced an HEV relapse after initially successful ribavirin therapy. One patient (5%) was lost to follow-up, and no patients died from hepatic complications. Conclusion: Rheumatology and internal medicine patients, including patients treated with methotrexate without corticosteroids, are at risk of developing chronic HEV infection. Rheumatology and internal medicine patients with abnormal liver tests should be screened for HEV infection.
Tomato Chlorotic Spot Virus (TCSV) Putatively Incorporated a Genomic Segment of Groundnut Ringspot Virus (GRSV) Upon a Reassortment Event
Authors: Silva João , de Oliveira Athos , de Almeida Mariana , Kormelink Richard , Nagata Tatsuya , Resende Renato
Published: February 2019

Tomato chlorotic spot virus (TCSV) and groundnut ringspot virus (GRSV) share several genetic and biological traits. Both of them belong to the genus Tospovirus (family Peribunyaviridae), which is composed by viruses with tripartite RNA genome that infect plants and are transmitted by thrips (order Thysanoptera). Previous studies have suggested several reassortment events between these two viruses, and some speculated that they may share one of their genomic segments. To better understand the intimate evolutionary history of these two viruses, we sequenced the genomes of the first TCSV and GRSV isolates ever reported. Our analyses show that TCSV and GRSV isolates indeed share one of their genomic segments, suggesting that one of those viruses may have emerged upon a reassortment event. Based on a series of phylogenetic and nucleotide diversity analyses, we conclude that the parental genotype of the M segment of TCSV was either eliminated due to a reassortment with GRSV or it still remains to be identified.
Viruses of Polar Aquatic Environments
Authors: Yau Sheree , Seth-Pasricha Mansha
Published: February 2019

The poles constitute 14% of the Earth’s biosphere: The aquatic Arctic surrounded by land in the north, and the frozen Antarctic continent surrounded by the Southern Ocean. In spite of an extremely cold climate in addition to varied topographies, the polar aquatic regions are teeming with microbial life. Even in sub-glacial regions, cellular life has adapted to these extreme environments where perhaps there are traces of early microbes on Earth. As grazing by macrofauna is limited in most of these polar regions, viruses are being recognized for their role as important agents of mortality, thereby influencing the biogeochemical cycling of nutrients that, in turn, impact community dynamics at seasonal and spatial scales. Here, we review the viral diversity in aquatic polar regions that has been discovered in the last decade, most of which has been revealed by advances in genomics-enabled technologies, and we reflect on the vast extent of the still-to-be explored polar microbial diversity and its “enigmatic virosphere”.
The Virioneuston: A Review on Viral–Bacterial Associations at Air–Water Interfaces
Authors: Rahlff Janina
Published: February 2019

Vast biofilm-like habitats at air–water interfaces of marine and freshwater ecosystems harbor surface-dwelling microorganisms, which are commonly referred to as neuston. Viruses in the microlayer, i.e., the virioneuston, remain the most enigmatic biological entities in boundary surface layers due to their potential ecological impact on the microbial loop and major air–water exchange processes. To provide a broad picture of the viral–bacterial dynamics in surface microlayers, this review compiles insights on the challenges that viruses likely encounter at air–water interfaces. By considering viral abundance and morphology in surface microlayers, as well as dispersal and infection mechanisms as inferred from the relevant literature, this work highlights why studying the virioneuston in addition to the bacterioneuston is a worthwhile task. In this regard, major knowledge gaps and possible future research directions are discussed.
Modeling Two-Dimensional Infiltration with Constant and Time-Variable Water Depth
Authors: Castanedo Vladimir , Saucedo Heber , Fuentes Carlos
Published: February 2019

Water infiltration is simulated by obtaining the time infiltrated depth evolution and humidity profiles with the numerical solution of the two-dimensional Richards’ equation. The contact time hypothesis is accepted in this study and used to apply a unique form on time of the water depth evolution in the solution domain (furrow), as boundary condition. The specific form of such evolution in time was obtained from results reported in the literature based on the internal numerical full coupling of the Saint-Venant and Richards’ equations in border irrigation. Moreover, the equivalent hydraulic area between the border and the furrow was achieved by scaling the values of water depth. The analysis was made for three contrasting soil textures, and the comparison was done by computing the root mean square error (RMSE) indicator. The comparison was performed from the selection of five finite element meshes with different densities to discretize the solution domain of the two-dimensional Richards’ equation, combined with several time steps. Finally, a comparison was made between infiltrated depth evolution calculated with a constant water depth in the furrow to the one proposed in this work, finding important differences between both approaches. To expand the scope of this study and for a fuller exploration of the subject, the results were compared with results obtained by applying the HYDRUS-2D software. The results confirm that it is important to consider an internal full coupling of the Saint-Venant and Richards´ equations to improve furrow irrigation simulations.
Crop Coefficients and Transpiration of a Super Intensive Arbequina Olive Orchard using the Dual Kc Approach and the Kcb Computation with the Fraction of Ground Cover and Height
Authors: Paço Teresa A. , Paredes Paula , Pereira Luis S. , Silvestre José , Santos Francisco L.
Published: February 2019

The SIMDualKc model was used to simulate crop water requirements for a super high density olive orchard in the region of Alentejo, Portugal. This model uses the dual crop coefficient approach to estimate and partitioning the actual crop evapotranspiration (ETc act) and therefore to perform the soil water balance. The model was calibrated with 2011 tree transpiration using trunk sap flow measurements and was validated using similar data from 2012 and tested with 2013 data. Low root mean square errors (RMSE < 0.53 mm·d−1) and acceptable modelling efficiency indicators (EF > 0.25) were obtained. Further validation was performed comparing modelled ETc act with eddy covariance measurements. These indicators support the appropriateness of using SIMDualKc to guide irrigation management. The basal crop coefficient (Kcb) curves obtained with SIMDualKc for those 3 years were compared with the Kcb values computed with the Allen and Pereira approach (A&P approach) where Kcb is estimated from the fraction of ground cover and plant height considering an adjustment factor for crop stomatal control (Fr). Fr values were obtained through a trial and error procedure through comparing the Kcb estimated with this approach and with SIMDualKc. The Kcb curves obtained by both methods resulted highly correlated, which indicates that the A&P approach may be used in the irrigation management practice to estimate crop water requirements. Results of performing the soil water balance with SIMDualKc have shown that soil evaporation is a large fraction of ETc act, varying between 41% and 45% for the 3 years under study. Irrigation, applied with a drip system, represented 39 to 56% of ETc act, which shows the great importance of irrigation to achieve the water requirements of super intensive olive orchards. Nevertheless, the analysis has shown that the irrigation management adopted at the orchard produces a water deficit larger than desirable, with a ratio of ETc act to non-stressed crop evapotranspiration (ETc) varying from 70% to 94% during the mid-season, when that ratio for a eustress irrigation management could be around 90%.
IDENTIFYING OPTIMAL LOCATION AND NECESSARY QUANTITY OF WAREHOUSES IN LOGISTIC SYSTEM USING A RADIATION THERAPY METHOD
Authors: Danchuk Viktor , Bakulich Olena , Svatko Vitaliy
Published: February 2019

The paper suggests a method for determining the optimal location of service points (warehouses) based on the method for optimal planning of radiation therapy of malignant tumors. This method enabled us to identify the location of the most optimal number of warehouses taking into account their capacity for the required volume of freight transportation and distance from warehouses to consumers. The results of the study coincide with the results obtained by using the method of ant algorithm. The proposed method of finding the optimal location of warehouses enables to significantly minimize the cost of delivering goods from a producer to a consumer.
Little known Orphninae (Coleoptera, Scarabaeidae) collected by the Madagascan expeditions of the California Academy of Sciences
Authors: Frolov Andrey
Published: February 2019

New locality records for Madecorphnusniger Frolov, 2010, Madecorphnusfalcatus Paulian, 1992, Madecorphnussimplex Frolov, 2010, and Triodontusitremoi Paulian, 1977, are given. Endophallus armature of Madecorphnusniger Frolov, 2010, is described and illustrated.
The Cerrado (Brazil) plant cytogenetics database
Authors: Roa Fernando , Telles Mariana Pires de Campos
Published: February 2019

Cerrado is a biodiversity hotspot that has lost ca. 50% of its original vegetation cover and hosts ca. 11,000 species belonging to 1,423 genera of phanerogams. For a fraction of those species some cytogenetic characteristics like chromosome numbers and C-value were available in databases, while other valuable information such as karyotype formula and banding patterns are missing. In order to integrate and share all cytogenetic information published for Cerrado species, including frequency of cytogenetic attributes and scientometrics aspects, Cerrado plant species were searched in bibliographic sources, including the 50 richest genera (with more than 45 taxa) and 273 genera with only one species in Cerrado. Determination of frequencies and the database website (http://cyto.shinyapps.io/cerrado) were developed in R. Studies were pooled by employed technique and decade, showing a rise in non-conventional cytogenetics since 2000. However, C-value estimation, heterochromatin staining and molecular cytogenetics are still not common for any family. For the richest and best sampled families, the following modal 2n counts were observed: Oxalidaceae 2n = 12, Lythraceae 2n = 30, Sapindaceae 2n = 24, Solanaceae 2n = 24, Cyperaceae 2n = 10, Poaceae 2n = 20, Asteraceae 2n = 18 and Fabaceae 2n = 26. Chromosome number information is available for only 16.1% of species, while there are genome size data for only 1.25%, being lower than the global percentages. In general, genome sizes were small, ranging from 2C = ca. 1.5 to ca. 3.5 pg. Intra-specific 2n number variation and higher 2n counts were mainly related to polyploidy, which relates to the prevalence of even haploid numbers above the mode of 2n in most major plant clades. Several orphan genera with almost no cytogenetic studies for Cerrado were identified. This effort represents a complete diagnosis for cytogenetic attributes of plants of Cerrado.
Notulae to the Italian flora of algae, bryophytes, fungi and lichens: 5
Authors: Ravera Sonia , Vizzini Alfredo , Cogoni Annalena , Aleffi Michele , Benesperi Renato , Bianchi Elisabetta , von Brackel Wolfgang , Cataldo Daniela , D'Antonio Costantino , Di Nuzzo Luca , Favero Longo Sergio Enrico , Gheza Gabriele , Isocrono Deborah , Matteucci Enrica , Martellos Stefano , Morosini Lorenzo , Nimis Pier Luigi , Ongaro Silvia , Poponessi Silvia , Puntillo Domenico , Sguazzin Francesco , Tretiach Mauro
Published: February 2019

In this contribution, new data concerning bryophytes, fungi, and lichens of the Italian flora are presented. It includes new records and confirmations for the bryophyte genera Diplophyllum and Ptychostomum, the fungal genera Arrhenia, Gymnosporangium, and Sporidesmium and the lichen genera Arthonia, Coenogonium, Flavoplaca, Gyalolechia, Parmotrema, Peltigera, Pterygiopsis, Squamarina, Tornabea, and Waynea.
Colony distribution and prey diversity of Cerceris fumipennis (Hymenoptera, Crabronidae) in British Columbia
Authors: Kimoto Troy , Roberts Josie , Westcott Richard L. , Jendek Eduard , Buck Matthias , Holden David , Careless Philip D.
Published: February 2019

Cercerisfumipennis Say, 1837 (Hymenoptera: Crabronidae) is a wasp that provisions its subterranean nests with jewel beetles (Coleoptera: Buprestidae). At 3 newly discovered colonies in British Columbia (BC), Cercerisfumipennis prey were collected by excavating the subterranean nests, using sweep nets to capture paralyzed prey in the grasp of a female returning to her nest, or collecting prey discarded at the nest entrance. In total, 9 species were collected: Acmaeoderaidahoensis Barr, Agriluscrataegi Frost, Agrilusgranulatuspopuli Fisher, Anthaxia (Haplanthaxia) caseyicaseyi Obenberger, Chrysobothrislaricis Van Dyke, Chrysobothrisleechi Barr, Phaenopsdrummondi (Kirby), Phaenopsgentilis (LeConte) and Phaenopsintrusa (Horn). Anthaxiacaseyicaseyi was the smallest beetle (4.2 mm) while Chrysobothrisleechi was the largest (12.0 mm). The average size of all buprestid prey taken by females from all 3 colonies was 8.8 mm. These represent the first prey records for Cercerisfumipennis in BC and with the exception of Phaenopsdrummondi are new prey records for this wasp. A single Harpalusaffinis (Schrank) (Coleoptera: Carabidae) was discovered within a brood cell containing Acmaeodera spp. elytra, but it is unclear if this beetle was placed in the cell by a female wasp.
Neodendryphiella, a novel genus of the Dictyosporiaceae (Pleosporales)
Authors: Iturrieta-González Isabel , Gené Josepa , Guarro Josep , Castañeda-Ruiz Rafael F. , García Dania
Published: February 2019

In a survey of soil and herbivore dung microfungi in Mexico and Spain, several dendryphiella-like species were found. Phylogenetic analyses based on ITS and LSU sequences showed that these fungi belonged to the family Dictyosporiaceae (Pleosporales) and represent an undescribed monophyletic lineage distant fromDendryphiella. Therefore, the genusNeodendryphiellais proposed to accommodate three new species,N.mali,N.michoacanensisandN.tarraconensis. The novel genus shares morphological features withDendryphiellasuch as differentiated conidiophores and polytretic integrated conidiogenous cells, that produce acropetal branched chains of conidia.Neodendryphielladiffers in the absence of nodulose conidiophores bearing conidiogenous cells with pores surrounded by a thickened and darkened wall, typical features in the conidiogenous apparatus ofDendryphiella. In addition, the phylogenetic and morphological analysis of several reference strains of differentDendryphiellaspecies, available for comparison, support the proposal ofD.variabilissp. nov., which mainly differs from the other species of the genus by having conidia up to 7 septa and highlight thatD.vinosaandD.infuscansare obscure species that require further taxonomic review.