bluuebunny/crossref_metadata_2025 huggingface dataset:
One-Pot Synthesized Pd@N-Doped Graphene: An Efficient Catalyst for Suzuki–Miyaura Couplings
Authors: Kuniyil Mufsir , Kumar J. V. Shanmukha , Adil Syed Farooq , Shaik Mohammed Rafi , Khan Mujeeb , Assal Mohamed E. , Siddiqui Mohammed Rafiq H. , Al-Warthan Abdulrahman
Published: May 2019

Nitrogen-doped graphene (NDG)-palladium (Pd)-based nanocatalysts (NDG@Pd) can be potentially applied as an efficient catalyst for the preparation of biaryls in a Suzuki–Miyaura coupling reaction. Herein, we report the one-pot facile synthesis of an NDG@Pd nanocatalyst, wherein the nanocatalyst was prepared by the simultaneous reduction of graphene oxide (GRO) and PdCl2 in the presence of hydrazine hydrate as a reducing agent, while ammonium hydroxide was used as a source of “N’’ on the surface of graphene. The as-synthesized NDG@Pd nanocatalyst, consisting of smaller-sized, spherical-shaped palladium nanoparticles (Pd-NPs) on the surface of NDG, was characterized by several spectroscopic and microscopic techniques, including high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), ultraviolet–visible spectroscopy (UV-Vis), Fourier-transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and Brunauer–Emmett–Teller (BET). The nanocatalyst displayed outstanding catalytic activity in the Suzuki–Miyaura cross-coupling reactions of phenyl halides with phenyl boronic acids under facile conditions in water. The catalytic activity of NDG@Pd was found to be a more efficient catalyst when compared to pristine highly reduced graphene oxide (HRG) based Pd nanocatalyst (HRG@Pd). Furthermore, the reusability of the catalyst was also tested by repeatedly performing the same reaction using the recovered catalyst. The N-doped catalyst displayed excellent reusability even after several reactions.
Ni-Based Composites from Chitosan Biopolymer a One-Step Synthesis for Oxygen Evolution Reaction
Authors: Aghabarari Behzad , Luque-Centeno José Manuel , Capel-Sánchez Maricarmen , Lázaro Elorri Maria Jesús , Martínez-Huerta Maria Victoria
Published: May 2019

Cost-efficient and sustainable electrocatalysts for oxygen evolution reaction (OER) is highly desired in the search for clean and renewable energy sources. In this study, we develop a new one-step synthesis strategy of novel composites based on Ni and molybdenum carbide embedded in N- and P-dual doped carbon matrices using mainly chitosan biopolymer as the carbon and nitrogen source, and molybdophosphoric acid (HMoP) as the P and Mo precursor. Two composites have been investigated through annealing a mixture of Ni/chitosan and HMoP with two unlike carbon matrices, melamine and graphene oxide, at a high temperature. Both composites exhibit similar multi-active sites with high electrocatalytic activity for OER in an alkaline medium, which is comparable to the IrO2 catalyst. For this study, an accurate measurement of the onset potential for O2 evolution has been used by means of a rotating ring-disk electrode (RRDE). The use of this method allows confirming a better stability in the chitosan/graphene composite. This work serves as a promising approach for the conversion of feedstock and renewable chitosan into desired OER catalysts.
7-Ketocholesterol Promotes Oxiapoptophagy in Bone Marrow Mesenchymal Stem Cell from Patients with Acute Myeloid Leukemia
Authors: Paz Jessica Liliane , Levy Debora , Oliveira Beatriz Araujo , de Melo Thatiana Correia , de Freitas Fabio Alessandro , Reichert Cadiele Oliana , Rodrigues Alessandro , Pereira Juliana , Bydlowski Sergio Paulo
Published: May 2019

7-Ketocholesterol (7-KC) is a cholesterol oxidation product with several biological functions. 7-KC has the capacity to cause cell death depending on the concentration and specific cell type. Mesenchymal stem cells (MSCs) are multipotent cells with the ability to differentiate into various types of cells, such as osteoblasts and adipocytes, among others. MSCs contribute to the development of a suitable niche for hematopoietic stem cells, and are involved in the development of diseases, such as leukemia, to a yet unknown extent. Here, we describe the effect of 7-KC on the death of bone marrow MSCs from patients with acute myeloid leukemia (LMSCs). LMSCs were less susceptible to the death-promoting effect of 7-KC than other cell types. 7-KC exposure triggered the extrinsic pathway of apoptosis with an increase in activated caspase-8 and caspase-3 activity. Mechanisms other than caspase-dependent pathways were involved. 7-KC increased ROS generation by LMSCs, which was related to decreased cell viability. 7-KC also led to disruption of the cytoskeleton of LMSCs, increased the number of cells in S phase, and decreased the number of cells in the G1/S transition. Autophagosome accumulation was also observed. 7-KC downregulated the SHh protein in LMSCs but did not change the expression of SMO. In conclusion, oxiapoptophagy (OXIdative stress + APOPTOsis + autophagy) seems to be activated by 7-KC in LMSCs. More studies are needed to better understand the role of 7-KC in the death of LMSCs and the possible effects on the SHh pathway.
Correction: Anup C. Katheria. Neonatal Resuscitation with an Intact Cord: Current and Ongoing Trials. Children 2019, 6, 60
Authors: Katheria Anup C.
Published: May 2019

The author wishes to make the following corrections to this paper [...]
Layered Double Hydroxide Clusters as Precursors of Novel Multifunctional Layers: A Bottom-Up Approach
Authors: Neves Cristina S. , Bastos Alexandre C. , Salak Andrei N. , Starykevich Maksim , Rocha Daisy , Zheludkevich Mikhail L. , Cunha Angela , Almeida Adelaide , Tedim João , Ferreira Mário G.S.
Published: May 2019

The specific microstructure of aluminum alloys is herein explored to grow spatially-resolved layered double hydroxide (SR-LDH) clusters on their surface. Upon chemical modification of LDHs via intercalation, adsorption and grafting with different functional molecules, novel surface-engineered surfaces were obtained. Crystal structure and phase composition were analyzed by X-ray diffraction (XRD) and surface morphology was observed by scanning electron microscopy (SEM). X-ray photoelectron spectroscopy (XPS) and glow discharge optical emission spectrometry (GDOES) were used to correlate structural changes upon ion-exchange and interfacial modifications with chemical composition and surface profiles of the SR-LDH films, respectively. The protection conferred by these films against localized corrosion was investigated at microscale using the scanning vibrating electrode technique (SVET). LDH-NO3 phase was obtained by direct growth onto AA2024 surface, as evidenced by (003) and (006) XRD diffraction reflections. After anion exchange of nitrate with 2-mercaptobenzothiazole (MBT) there was a decrease in the SR-LDH thickness inferred from GDOES profiles. The subsequent surface functionalization with HTMS was confirmed by the presence of Si signal in XPS and GDOES analyses, leading to an increase in the water contact angle (c.a 144° ± 3°). SVET measurements of the SR-LDH films revealed exceptional corrosion resistance, whereas the bioluminescent bacteria assay proved the anti-microbial character of the obtained films. Overall the results obtained show an effective corrosion protection of the SR-LDHs when compared to the bare substrate and the potential of these films for biofouling applications as new Cr-free pre-treatments.
Semiperiodic Ultra-Broadband Double-Grating to Improve c-Si Thin-Film Solar Cell’s Optical Absorption, through Numerical Structural Optimization
Authors: Jalali Mandana , Nadgaran Hamid , Erni Daniel
Published: May 2019

Plasmonic gratings provide effective photon management techniques in thin-film solar cells, capable of extending the optical thickness of the solar cell’s active layer. However, the ultra-broadband nature of such application makes an optimal design of the grating structure quite challenging, since a fully periodic grating operates only in specific spectral ranges. To achieve a more broadband design, semiperiodicity is introduced, which, due to having controllable disorder, is an apt solution in broadband optical applications. In this work, semiperiodic double gratings as a broadband photon management technique are introduced in order to improve the optical absorption of c-Si thin-film solar cells, and optimized through numerical structural optimization. Physical parameters of both front and back gratings are determined taking the spectrally integrated optical absorption as the figure of merit and subsequently a semiperiodic double grating is established through adding defects to the fully periodic structure. It is shown that such semiperiodic structure is capable of enhancing the spectrally integrated optical absorption 88.6 % compared to a reference structure without gratings.
A Multi-Year Data Set of Beach-Foredune Topography and Environmental Forcing Conditions at Egmond aan Zee, The Netherlands
Authors: Ruessink Gerben , Schwarz Christian S. , Price Timothy D. , Donker Jasper J. A.
Published: May 2019

Coastal dunes offer numerous functions to society, such as sea defense and recreation, and host unique habitats with high biodiversity. Research on coastal dune dynamics has traditionally focused on the erosional impact of short-duration (hours to days), high-wave storm events on the most seaward dune, called the foredune. In contrast, research data on its subsequent slow (months to years), wind-driven recovery are rather rare, yet essential to aid studying wind-driven processes, identifying the most relevant wind-forcing conditions, and testing and improving dune-growth models. The present data set contains 39 digital elevation models and 11 orthophotos of the beach-foredune system near Egmond aan Zee, The Netherlands. The novelty of the data set lies in the combination of long-term observations (6 years; January 2013 to January 2019), with high temporal (intervals of 2–4 months) and spatial resolution (1 × 1 m) covering an extensive spatial domain (1.4 km alongshore). The 25-m high foredune eroded substantially in October 2014, with a maximum recession of 75 m3/m, and subsequently recovered with a rate of approximately 15 m3/m/yr, although with substantial alongshore variability. The data set is supplemented with high-frequency time series of offshore wave, water level, and wind characteristics, as well as various annual subtidal cross-shore profiles, to facilitate its future application in coastal dune research.
Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Mediterranean Rice Crops Caused by Western Swamphen (Porphyrio porphyrio)
Authors: Pla Magda , Bota Gerard , Duane Andrea , Balagué Jaume , Curcó Antoni , Gutiérrez Ricard , Brotons Lluís
Published: May 2019

Making agricultural production compatible with the conservation of biological diversity is a priority in areas in which human–wildlife conflicts arise. The threatened Western Swamphen (Porphyrio porphyrio) feeds on rice, inducing crop damage and leading to decreases in rice production. Due to the Swamphen protection status, economic compensation policies have been put in place to compensate farmers for these damages, thus requiring an accurate, quantitative, and cost-effective evaluation of rice crop losses over large territories. We used information captured from a UAV (Unmanned Aerial Vehicle) equipped with a multispectral Parrot SEQUOIA camera as ground-truth information to calibrate Sentinel-2 imagery to quantify damages in the region of Ebro Delta, western Mediterranean. UAV vegetation index NDVI (Normalized Difference Vegetation Index) allowed estimation of damages in rice crops at 10 cm pixel resolution by discriminating no-green vegetation pixels. Once co-registered with Sentinel grid, we predicted the UAV damage proportion at a 10 m resolution as a function of Sentinel-2 NDVI, and then we extrapolated the fitted model to the whole Sentinel-2 Ebro Delta image. Finally, the damage predicted with Sentinel-2 data was quantified at the agricultural plot level and validated with field information compiled on the ground by Rangers Service. We found that Sentinel2-NDVI data explained up to 57% of damage reported with UAV. The final validation with Rangers Service data pointed out some limitations in our procedure that leads the way to improving future development. Sentinel2 imagery calibrated with UAV information proved to be a viable and cost-efficient alternative to quantify damages in rice crops at large scales.
Study of Thermal Management System Using Composite Phase Change Materials and Thermoelectric Cooling Sheet for Power Battery Pack
Authors: Zhang Chuan-Wei , Chen Shang-Rui , Gao Huai-Bin , Xu Ke-Jun , Xia Zhan , Li Shuai-Tian
Published: May 2019

Scientific and reasonable battery thermal management systems contribute to improve the performance of a power battery, prolong its life of service, and improve its safety. Based on TAFEL-LAE895 type 100Ah ternary lithium ion power battery, this paper is conducted on charging and discharging experiments at different rates to study the rise of temperature and the uniformity of the battery. Paraffin can be used to reduce the surface temperature of the battery, while expanded graphite (EG) is added to improve the thermal conductivity and viscosity of the composite phase change material (CPCM), and to reduce the fluidity after melting. With the increase of graphite content, the heat storage capacity of phase change material (PCM) decreases, which affects the thermal management effect directly. Therefore, this paper combines heat pipe and semiconductor refrigeration technology to transform heat from the inner CPCM to the thermoelectric cooling sheet for heat dissipation. The results show that the surface temperature of the battery can be kept within a reasonable range when discharging at high rate. The temperature uniformity of the battery is improved and the energy of the battery is saved.
Combustion Characteristics of Methane Hydrate Flames
Authors: Chien Yu-Chien , Dunn-Rankin Derek
Published: May 2019

This research studies the structure of flames that use laboratory-produced methane hydrates as fuel, specifically for the purpose of identifying their key combustion characteristics. Combustion of a methane hydrate involves multiple phase changes, as large quantities of solid clathrate transform into fuel gas, water vapor, and liquid water during burning. With its unique and stable fuel energy storage capability, studies in combustion are focused on the potential usage of hydrates as an alternative fuel source or on their fire safety. Considering methane hydrate as a conventional combustion energy resource and studying hydrate combustion using canonical experimental configurations or methodology are challenges. This paper presents methane hydrate flame geometries from the time they can be ignited through their extinguishment. Ignition and burning behavior depend on the hydrate initial temperature and whether the clathrates are chunks or monolithic shapes. These behaviors are the subject of this research. Physical properties that affect methane hydrate in burning can include packing density, clathrate fraction, and surface area. Each of these modifies the time or the temperature needed to ignite the hydrate flames as well as their subsequent burning rate, thus every effort is made to keep consistent samples. Visualization methods used in combustion help identify flame characteristics, including pure flame images that give reaction zone size and shape and hydrate flame spectra to identify important species. The results help describe links between hydrate fuel characteristics and their resulting flames.
Reduction of Power Production Costs in a Wind Power Plant–Flywheel Energy Storage System Arrangement
Authors: Tomczewski Andrzej , Kasprzyk Leszek , Nadolny Zbigniew
Published: May 2019

The paper presents issues of optimisation of a wind power plant–energy storage system (WPP-ESS) arrangement operating in a specific geographical location. An algorithm was developed to minimise the unit discounted cost of electricity generation in a system containing a wind power plant and flywheel energy storage. In order to carry out the task, population heuristics of the genetic algorithm were used with modifications introduced by the author (taking into account the coefficient of variation of the generation in the quasi-static term of the penalty and the selection method). The set of inequality restrictions related to the technical parameters of turbines and energy storage and the parameters of energy storage management has been taken into account with the application of the Powell–Skolnick penalty function (Michalewicz modification). The results of sample optimisation calculations for two wind power plants of 2 MW were presented. The effects achieved in the process of optimisation were described—especially the influence of the parameters of the energy storage management system on the unit cost of electricity generation. The use of a system with higher unit costs of energy generation compared to independently operating wind turbines was justified in the context of improving the conditions of compatibility with the power system—the strategy belongs to a power firming group.
A Remotely Controlled Sea Level Compensation System for Wave Energy Converters
Authors: Ayob Mohd Nasir , Castellucci Valeria , Abrahamsson Johan , Waters Rafael
Published: May 2019

The working principle of the wave energy converter (WEC) developed at Uppsala University (UU) is based on a heaving point absorber with a linear generator. The generator is placed on the seafloor and is connected via a steel wire to a buoy floating on the surface of the sea. The generator produces optimal power when the translator's oscillations are centered with respect to the stator. However, due to the tides or other changes in sea level, the translator's oscillations may shift towards the upper or lower limit of the generator's stroke length, resulting in a limited stroke and a consequent reduction in power production. A compensator has been designed and developed in order to keep the generator's translator centered, thus compensating for sea level variations. This paper presents experimental tests of the compensator in a lab environment. The wire adjustments are based on online sea level data obtained from the Swedish Meteorological and Hydrological Institute (SMHI). The objective of the study was to evaluate and optimize the control and communication system of the device. As the device will be self-powered with solar and wave energy, the paper also includes estimations of the power consumption and a control strategy to minimize the energy requirements of the whole system. The application of the device in a location with high tides, such as Wave Hub, was analyzed based on offline tidal data. The results show that the compensator can minimize the negative effects of sea level variations on the power production at the WEC. Although the wave energy concept of UU is used in this study, the developed system is also applicable to other WECs for which the line length between seabed and surface needs to be adjusted.
Projecting Monterey Pine (Pinus radiata) Populations over Time in the Presence of Various Representations of Pitch Canker Disease, Caused by Fusarium circinatum
Authors: Reynolds Gregory J. , Gordon Thomas R. , McRoberts Neil
Published: May 2019

Monterey pine (Pinus radiata D. Don) is native to California and widely planted in Mediterranean climates around the world. Pitch canker, a disease caused by Fusarium circinatum Nirenberg and O’Donnell, is a serious threat to P. radiata in native forests and in plantations. Because of its economic importance worldwide, conservation of P. radiata native populations is a high priority. We developed a demographic matrix projection model to simulate dynamics of naturally occurring P. radiata populations in California in the presence of the disease. Tree demography data for the model were collected from seven sites in a native forest on the Monterey Peninsula. Height and stem diameter were recorded for all trees, which were divided into five size classes based on these data. Transition probabilities were calculated for each size class; cone production, seed release, and seed transition probability were estimated using an iterative search process. In the model, pitch canker influences state-specific fecundity and survival probabilities. Five different approaches to include these effects were compared. Populations were projected over 50 decades from three specified initial population sizes. Elasticity analysis indicated that facilitating survival of all size classes is vital to maintaining the structure of the forest.
Potential for Forest Restoration and Deficit Compensation in Itacaiúnas Watershed, Southeastern Brazilian Amazon
Authors: Nunes Sâmia , Cavalcante Rosane B. L. , Nascimento Wilson R. , Souza-Filho Pedro Walfir M. , Santos Diogo
Published: May 2019

The conservation and restoration of native vegetation is vital for providing key hydrological services (i.e., maintaining high water quality, atmospheric humidity, and precipitation patterns). However, this research area lacks fine-scale studies at the watershed level to evaluate opportunities for forest restoration and deficit (the shortfall of forest required to be restored or compensated), as well as the implications for watershed management. We provide the first fine-scale estimation of forest and deficit distribution, integrating permanent preservation areas (APPs, in Portuguese) and legal reserves (RL, in Portuguese), according to Brazilian environmental law, for the 41,300 km2 Itacaiúnas watershed in the Brazilian state of Pará, which has lost 50% of its vegetation cover. Using 30 m- and 10 m-resolution imagery, a multi-temporal land use classification was performed by geographic object-based image analysis (GEOBIA). The results were combined with a set of Brazilian regulations on the conservation and restoration of APPs and RL to assess patterns of forest cover and legal compliance. We found that the total RL deficit (4383 km2) was higher than the total forest surplus (above legal obligation) (3241 km2). However, most of this deficit (56%) could be compensated by protecting a forest area in another property within the Amazon biome, while 44% must be legally restored. Only 4% of the total forest surplus can be legally deforested, and the remaining 96% is already protected by law but can be used to compensate for areas under the deficit. We also found that, despite 57% (3017 km2) of the total APP being forested, only 26% (1356 km2) of the APP must be restored and 17% (881 km2) can remain deforested (consolidated areas). The 2012 law revision reduced the obligation to restore RL and APPs. This change could affect hydrological and ecological services. Compensation mechanisms could be used to protect forest within the Itacaiúnas watershed, rather than in the biome, to reduce further deforestation pressure.
A Decision Support Tool for Assessing the Impact of Climate Change on Multiple Ecosystem Services
Authors: Cristal Irina , Ameztegui Aitor , González-Olabarria Jose Ramon , Garcia-Gonzalo Jordi
Published: May 2019

In the climate change era, forest managers are challenged to use innovative tools to encourage a sustained provision of goods and services. Many decision support tools (DSTs), developed to address global changes in forest management practices, reflect the complexity of the scientific knowledge produced, a fact that could make it difficult for practitioners to understand and adopt them. Acknowledging the importance of knowledge transfer to forestry practitioners, this study describes a user-centric decision support software tool, aiming to assess forest management and climate change impacts on multiple ecosystem services (ESs) at a stand level. SORTIE-ND, a spatially explicit tree-level simulator for projecting stand dynamics that is sensitive to climate change, is encapsulated into the decision support tool and used as the simulation engine for stand development. Linking functions are implemented to evaluate ecosystem services and potential risks, and decision support is provided in form of interactive 2D and 3D visualizations. Five main components were identified to delineate the workflow and to shape the decision support tool: the information base, the alternative generator, the forest simulator, the ecosystem services calculator, and the visualization component. In order to improve the interaction design and general user satisfaction, the usability of the system was tested at an early stage of the development. While we have specifically focused on a management-oriented approach through user-centric interface design, the utilization of the product is likely to be of importance in facilitating education in the field of forest management.
Enhancing IoT Data Dependability through a Blockchain Mirror Model
Authors: Bellini Alessandro , Bellini Emanuele , Gherardelli Monica , Pirri Franco
Published: May 2019

The Internet of Things (IoT) is a remarkable data producer and these data may be used to prevent or detect security vulnerabilities and increase productivity by the adoption of statistical and Artificial Intelligence (AI) techniques. However, these desirable benefits are gained if data from IoT networks are dependable—this is where blockchain comes into play. In fact, through blockchain, critical IoT data may be trusted, i.e., considered valid for any subsequent processing. A simple formal model named “the Mirror Model” is proposed to connect IoT data organized in traditional models to assets of trust in a blockchain. The Mirror Model sets some formal conditions to produce trusted data that remain trusted over time. A possible practical implementation of an application programming interface (API) is proposed, which keeps the data and the trust model in synch. Finally, it is noted that the Mirror Model enforces a top-down approach from reality to implementation instead of going the opposite way as it is now the practice when referring to blockchain and the IoT.
Intelligent Dynamic Data Offloading in a Competitive Mobile Edge Computing Market
Authors: Mitsis Giorgos , Apostolopoulos Pavlos Athanasios , Tsiropoulou Eirini Eleni , Papavassiliou Symeon
Published: May 2019

Software Defined Networks (SDN) and Mobile Edge Computing (MEC), capable of dynamically managing and satisfying the end-users computing demands, have emerged as key enabling technologies of 5G networks. In this paper, the joint problem of MEC server selection by the end-users and their optimal data offloading, as well as the optimal price setting by the MEC servers is studied in a multiple MEC servers and multiple end-users environment. The flexibility and programmability offered by the SDN technology enables the realistic implementation of the proposed framework. Initially, an SDN controller executes a reinforcement learning framework based on the theory of stochastic learning automata towards enabling the end-users to select a MEC server to offload their data. The discount offered by the MEC server, its congestion and its penetration in terms of serving end-users’ computing tasks, and its announced pricing for its computing services are considered in the overall MEC selection process. To determine the end-users’ data offloading portion to the selected MEC server, a non-cooperative game among the end-users of each server is formulated and the existence and uniqueness of the corresponding Nash Equilibrium is shown. An optimization problem of maximizing the MEC servers’ profit is formulated and solved to determine the MEC servers’ optimal pricing with respect to their offered computing services and the received offloaded data. To realize the proposed framework, an iterative and low-complexity algorithm is introduced and designed. The performance of the proposed approach was evaluated through modeling and simulation under several scenarios, with both homogeneous and heterogeneous end-users.
The Next Generation Platform as A Service: Composition and Deployment of Platforms and Services
Authors: Mimidis-Kentis Angelos , Soler Jose , Veitch Paul , Broadbent Adam , Mobilio Marco , Riganelli Oliviero , Van Rossem Steven , Tavernier Wouter , Sayadi Bessem
Published: May 2019

The emergence of widespread cloudification and virtualisation promises increased flexibility, scalability, and programmability for the deployment of services by Vertical Service Providers (VSPs). This cloudification also improves service and network management, reducing the Capital and Operational Expenses (CAPEX, OPEX). A truly cloud-native approach is essential, since 5G will provide a diverse range of services - many requiring stringent performance guarantees while maximising flexibility and agility despite the technological diversity. This paper proposes a workflow based on the principles of build-to-order, Build-Ship-Run, and automation; following the Next Generation Platform as a Service (NGPaaS) vision. Through the concept of Reusable Functional Blocks (RFBs), an enhancement to Virtual Network Functions, this methodology allows a VSP to deploy and manage platforms and services, agnostic to the underlying technologies, protocols, and APIs. To validate the proposed workflow, a use case is also presented herein, which illustrates both the deployment of the underlying platform by the Telco operator and of the services that run on top of it. In this use case, the NGPaaS operator facilitates a VSP to provide Virtual Network Function as a Service (VNFaaS) capabilities for its end customers.
Whole Genome Sequencing of Giant Schnauzer Dogs with Progressive Retinal Atrophy Establishes NECAP1 as a Novel Candidate Gene for Retinal Degeneration
Authors: Hitti Rebekkah J. , Oliver James A. C. , Schofield Ellen C. , Bauer Anina , Kaukonen Maria , Forman Oliver P. , Leeb Tosso , Lohi Hannes , Burmeister Louise M. , Sargan David , Mellersh Cathryn S.
Published: May 2019

Canine progressive retinal atrophies (PRA) are genetically heterogeneous diseases characterized by retinal degeneration and subsequent blindness. PRAs are untreatable and affect multiple dog breeds, significantly impacting welfare. Three out of seven Giant Schnauzer (GS) littermates presented with PRA around four years of age. We sought to identify the causal variant to improve our understanding of the aetiology of this form of PRA and to enable development of a DNA test. Whole genome sequencing of two PRA-affected full-siblings and both unaffected parents was performed. Variants were filtered based on those segregating appropriately for an autosomal recessive disorder and predicted to be deleterious. Successive filtering against 568 canine genomes identified a single nucleotide variant in the gene encoding NECAP endocytosis associated 1 (NECAP1): c.544G>A (p.Gly182Arg). Five thousand one hundred and thirty canids of 175 breeds, 10 cross-breeds and 3 wolves were genotyped for c.544G>A. Only the three PRA-affected GS were homozygous (allele frequency in GS, excluding proband family = 0.015). In addition, we identified heterozygotes belonging to Spitz and Dachshund varieties, demonstrating c.544G>A segregates in other breeds of German origin. This study, in parallel with the known retinal expression and role of NECAP1 in clathrin mediated endocytosis (CME) in synapses, presents NECAP1 as a novel candidate gene for retinal degeneration in dogs and other species.
Identification of a Missense Variant in MFSD12 Involved in Dilution of Phaeomelanin Leading to White or Cream Coat Color in Dogs
Authors: Hédan Benoit , Cadieu Edouard , Botherel Nadine , Dufaure de Citres Caroline , Letko Anna , Rimbault Maud , Drögemüller Cord , Jagannathan Vidhya , Derrien Thomas , Schmutz Sheila , Leeb Tosso , André Catherine
Published: May 2019

White coat color in mammals has been selected several times during the domestication process. Numerous dog breeds are fixed for one form of white coat color that involves darkly pigmented skin. The genetic basis of this color, due to the absence of pigment in the hairs, was suggested to correspond to extreme dilution of the phaeomelanin, by both the expression of only phaeomelanin (locus E) and its extreme dilution (locus I). To go further, we performed genome-wide association studies (GWAS) using a multiple breed approach. The first GWAS, using 34 white dogs and 128 non-white dogs, including White Shepherds, Poodles, Cotons de Tulear and Bichons allowed us to identify two significantly associated loci on the locus E and a novel locus on chromosome 20. A second GWAS using 15 other breeds presenting extreme phaeomelanin dilution confirmed the position of locus I on the chromosome 20 (position 55 Mb pcorrected = 6 × 10−13). Using whole-genome sequencing, we identified a missense variant in the first exon of MFSD12, a gene recently identified to be involved in human, mouse and horse pigmentation. We confirmed the role of this variant in phaeomelanin dilution of numerous canine breeds, and the conserved role of MFSD12 in mammalian pigmentation.
Molecular Processes Connecting DNA Methylation Patterns with DNA Methyltransferases and Histone Modifications in Mammalian Genomes
Authors: Jeltsch Albert , Broche Julian , Bashtrykov Pavel
Published: May 2019

The authors wish to make the following correction to their paper [...]
The Noise Properties and Velocities from a Time-Series of Estonian Permanent GNSS Stations
Authors: Kall Tarmo , Oja Tõnis , Kollo Karin , Liibusk Aive
Published: May 2019

The aim of this study was to estimate the noise properties, velocities, and their uncertainties from a time-series of selected (~9 years long) Estonian continuously operating Global Navigation Satellite System (GNSS) stations. Two software packages based on different processing methods, Gipsy–Oasis and Bernese, were used for daily coordinate calculations. Different methods and software (Tsview, Hector, and MIDAS) were used for coordinate time-series analysis. Outliers were removed using three different strategies. Six different stochastic noise models were used for trend estimation altogether with the analysis of the noise properties of the residual time-series with Hector. Obtained velocities were compared with different land uplift and glacial isostatic adjustment models (e.g., ICE-6G (VM5a), NKG2016LU, etc.). All compared solutions showed similar fit to the compared models. It was confirmed that the best fit to the time-series residuals were with the flicker noise plus white noise model (for the North and East component) and generalized Gauss–Markov model (for Up). Velocities from MIDAS, Tsview, and Hector solutions within the same time-series (Gipsy–Oasis or Bernese) agreed well but velocity uncertainties differed up to four times. The smallest uncertainties were obtained from Tsview; the MIDAS solution produced the most conservative values. Although the East and Up component velocities between Gipsy and Bernese solutions agreed well, the North component velocities were systematically shifted.
Genius and Genitality: William S. Burroughs Reading Wilhelm Reich
Authors: Antonic Thomas
Published: May 2019

This article explores the impact of Wilhelm Reich’s theories and writings on the works and thinking of William S. Burroughs. Reich’s significance for Burroughs’ fiction is beyond doubt, as the appearance of Reich’s discoveries and inventions, such as orgones and orgone accumulators, in Burroughs’ major works demonstrates. Yet to date, no attempt has been made in academia to make all those references to Reich in Burroughs’ complete œuvre visible. In order to make the thinking of the Austrian-American psychoanalyst and scientist comprehensible for readers not familiar with Reich, the first section will provide a brief biographical outline. In the subsequent sections, the article will describe how Burroughs and other Beat writers discovered Reich, how and to what extent Burroughs incorporated Reich in his texts throughout his career and what opinions Burroughs expressed about Reich in interviews and letters. For the first time, with a summary as undertaken in this article and by documenting most of the references to Reich in Burroughs’ work, the importance of the former to the latter is revealed in a compact form.
Organisational Climate, Role Stress, and Public Employees’ Job Satisfaction
Authors: Pecino Vicente , Mañas Miguel A. , Díaz-Fúnez Pedro A. , Aguilar-Parra José M. , Padilla-Góngora David , López-Liria Remedios
Published: May 2019

The Job Demands-Resources (JD-R) model is an integrative theoretical framework for monitoring workplaces with the aim to increase job engagement and prevent burnout. This framework is of great interest since the management of job resources and demands can negatively affect employees, especially in organisational contexts characterised by high job demands. This study uses the job demands-resources model to investigate the relationships between organisational climate, role stress, and employee well-being (burnout and job satisfaction) in public organisations. This is a descriptive, cross-sectional study. The research participants are 442 public employees. A structural equation model was developed (organisational climate, job satisfaction, burnout, role stress). These confirm that organisational climate is correlated with role stress (−0.594), job satisfaction (0.746), and burnout (−0.408), while role stress is correlated with burnout (0.953) and job satisfaction (−0.685). Finally, there is a correlation between burnout and job satisfaction that is negative and significant (−0.664). The study confirms that a positive organisational climate could lead to less stressed and burned-out workers and, at the same time, to more satisfied employees with improved well-being.
Analysis of Determinants of Readiness for Professional Development Among Polish Nurses
Authors: Bartosiewicz Anna , Łuszczki Edyta , Różański Andrzej , Nagórska Małgorzata
Published: May 2019

The continuous development of medical sciences and the introduction of new diagnostic methods and treatment with the use of specialized equipment means that the knowledge and skills acquired during university studies are no longer sufficient. This obliges nursing staff to raise their professional qualifications in order to provide the appropriate quality of medical services. The aim of the study was an analysis of nurses readiness for learning and development and factors determining this readiness. The study was conducted among 756 nurses. The questionnaire method adopted was the readiness of employees for learning and development (RELD) standardized questionnaire, and a questionnaire containing sociodemographic data of the respondents. For the subscales of readiness for learning and development, average results were predominant and concerned in particular the level of openness to changes in environment (A1 scale), and self-evaluation of past educational development (C5 scale). The readiness of the nurses examined to learn and develop was on an average level for all the subscales. Younger nurses, with a lower seniority, having higher education and additional qualifications had a higher readiness for learning and development.
SME Steeplechase: When Obtaining Money Is Harder Than Innovating
Authors: Guercio M. Belén , Martinez Lisana B. , Bariviera Aurelio F.
Published: May 2019

In this paper, we analyze the main characteristics of European Small and Medium Enterprises (SMEs), related to the demand for and access to external financial resources. We use microdata from an extensive database, elaborated by the European Central Bank and the European Commission: the Survey on the Access to Finance of Enterprises. Firstly, we consider a set of variables as determinants to the decision to apply for different financial instruments. Secondly, we use the same set of variables to analyze the actual access to these instruments. For each regression, several SMEs profiles were created, in order to detect SMEs archetypes according to their decisions. The results are thought-provoking, and highlight that differences in firms characteristics (size, innovative activities, etc.), influence not only the access to, but also the demand for external finance.
Analyzing Newspaper Maps for Earthquake News through Cartographic Approach
Authors: Sarın Pınar , Uluğtekin Necla
Published: May 2019

This study focuses on newspaper maps, which have an important role in conveying spatial information to newspaper readers. Maps and map-like items in the main Turkish newspapers within a certain period were evaluated in regard to the scope of the study. A database was constructed to organize the collected data and conduct the analysis. In addition to cartographic and thematic analyses, the database allows “georeferencing” to be conducted as well. However, the current study focused on the cartographic and thematic properties of these maps. Their deficiencies were identified from a cartographic perspective and with that, the parts of newspapers that maps are mostly included in were investigated, and we aimed to identify the topics and events that increase map usage in newspapers. For this purpose, maps of earthquake-related news were evaluated as a case study to show some spatial and thematic determinations. Thus, the contribution of newspapers to spatial thinking abilities and geographic knowledge of the readers was evaluated by cartographers. The study proves the importance of cartography in spreading knowledge through maps in newspapers. This opens up new possibilities for future studies to develop a different cartographic perspective on map usage and improve the geographic knowledge of newspaper readers.
A Hybrid of Differential Evolution and Genetic Algorithm for the Multiple Geographical Feature Label Placement Problem
Authors: Lu Fuyu , Deng Jiqiu , Li Shiyu , Deng Hao
Published: May 2019

Label placement is a difficult problem in automated map production. Many methods have been proposed to automatically place labels for various types of maps. While the methods are designed to automatically and effectively generate labels for the point, line and area features, less attention has been paid to the problem of jointly labeling all the different types of geographical features. In this paper, we refer to the labeling of all the graphic features as the multiple geographical feature label placement (MGFLP) problem. In the MGFLP problem, the overlapping and occlusion among labels and corresponding features produces poorly arranged labels, and results in a low-quality map. To solve the problem, a hybrid algorithm combining discrete differential evolution and the genetic algorithm (DDEGA) is proposed to search for an optimized placement that resolves the MGFLP problem. The quality of the proposed solution was evaluated using a weighted metric regarding a number of cartographical rules. Experiments were carried out to validate the performance of the proposed method in a set of cartographic tasks. The resulting label placement demonstrates the feasibility and the effectiveness of our method.
Extracting Main Center Pattern from Road Networks Using Density-Based Clustering with Fuzzy Neighborhood
Authors: Cui Xiaojie , Wang Jiayao , Wu Fang , Li Jinghan , Gong Xianyong , Zhao Yao , Zhu Ruoxin
Published: May 2019

The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalization and spatial data matching. Previous studies mainly focus on the topological centrality calculation of road network graphs, and pay less attention to the delineation of main centers. Therefore, this study proposes an automatic recognition method of main center pattern in road networks. We firstly extract the main clusters from road nodes by improving the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with fuzzy set theory. Moreover, the center area is generated with road meshes according to the area ratio with the covering discs of the main clusters. This proposed algorithm is applied to the road networks of a monocentric city and polycentric city respectively. The results show that our method is effective for identifying the main center pattern in the road networks. Furthermore, the contrast experiments demonstrate our method’s higher accuracy.
Heuristic Bike Optimization Algorithm to Improve Usage Efficiency of the Station-Free Bike Sharing System in Shenzhen, China
Authors: Gu Zhihui , Zhu Yong , Zhang Yan , Zhou Wanyu , Chen Yu
Published: May 2019

Station-free bike sharing systems (BSSs) are a new type of public bike system that has been widely deployed in China since 2017. However, rapid growth has vastly outpaced the immediate demand and overwhelmed many cities around the world. This paper proposes a heuristic bike optimization algorithm (HBOA) to determine the optimal supply and distribution of bikes considering the effect of bicycle cycling. In this approach, the different bike trips with separate bikes can be connected in space and time and converted into a continuous trip chain for a single bike. To improve this cycling efficiency, it is important to properly design the bicycle distribution. Taking Shenzhen as an example, we implement the algorithm with OD matrix data from Mobike and Ofo, the two large bike sharing companies which account for 80% of the shared bike market in Shenzhen, over two days. The HBOA results are as follows. 1) Only one-fifth of the bike supply is needed to meet the current usage demand if the bikes are used efficiently, which means a large number of shared bikes in Shenzhen remain in an idle state for long periods. 2) Although the cycling demand is high in many areas, it does not mean that large numbers of bikes are needed because the continuous inflow caused by the cycling effect of bikes will meet most of the demand by itself. 3) The areas with the highest demands for optimal bikes are residential, followed by industrial, public transportation, official and commercial areas, on both working and non-working days. This algorithm can be an objective basis for city related departments to manage station-free BSSs and be applied to design the layout of bikes in small-scale spatial units to help station-free BSSs operate efficiently and minimize the need to relocate the bikes without reducing the level of user satisfaction.
A Comparison Between Major Artificial Intelligence Models for Crop Yield Prediction: Case Study of the Midwestern United States, 2006–2015
Authors: Kim Nari , Ha Kyung-Ja , Park No-Wook , Cho Jaeil , Hong Sungwook , Lee Yang-Won
Published: May 2019

This paper compares different artificial intelligence (AI) models in order to develop the best crop yield prediction model for the Midwestern United States (US). Through experiments to examine the effects of phenology using three different periods, we selected the July–August (JA) database as the best months to predict corn and soybean yields. Six different AI models for crop yield prediction are tested in this research. Then, a comprehensive and objective comparison is conducted between the AI models. Particularly for the deep neural network (DNN) model, we performed an optimization process to ensure the best configurations for the layer structure, cost function, optimizer, activation function, and drop-out ratio. In terms of mean absolute error (MAE), our DNN model with the JA database was approximately 21–33% and 17–22% more accurate for corn and soybean yields, respectively, than the other five AI models. This indicates that corn and soybean yields for a given year can be forecasted in advance, at the beginning of September, approximately a month or more ahead of harvesting time. A combination of the optimized DNN model and spatial statistical methods should be investigated in future work, to mitigate partly clustered errors in some regions.