bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association between Omega-3 Fatty Acid Intake and Human Brain Connectivity in Middle-Aged Depressed Women
Authors: Park Seon-Joo , Lee Do-Kyung , Kim Bokyoung , Na Kyoung-Sae , Lee Chang-Ho , Son Young-Don , Lee Hae-Jeung
Published: July 2020

Omega-3 fatty acid (n-3 FA) intake is known to have a preventive effect on depressive symptoms in a general population. This study assessed the effects of n-3 FA intake on depressive symptoms and brain function in middle-aged women. Depressive symptoms were screened using the Beck Depression Inventory-II (BDI-II) and Center for Epidemiologic Studies-Depression scale (CES-D) assessment questionnaires, and n-3 FA intakes were assessed using semiquantitative food frequency questionnaire. We found that n-3 FA intakes were negatively associated with depressive symptoms in middle-aged women. Psychiatrists diagnosed the presence of depressive disorders using the 5th edition of the Mental Disorder Diagnosis and Statistics Manual (DSM-5). Resting-state functional magnetic resonance imaging (rs-fMRI) was performed to investigate the association between n-3 FA intake and brain functional connectivity. Functional connectivity of the right middle frontal cortex (default mode network) and the right middle temporal pole (frontoparietal network) was positively associated with depressive symptom scores and negatively associated with n-3 FA intakes. In conclusion, high n-3 FA intake decreases the risk of depressive symptoms and modifies the brain functional connectivity in middle-aged women.
Dynamics of Structural and Functional Changes in Gut Microbiota during Treatment with a Microalgal β-Glucan, Paramylon and the Impact on Gut Inflammation
Authors: Taylor Harrison B. , Gudi Radhika , Brown Robert , Vasu Chenthamarakshan
Published: July 2020

Previously, we have shown that oral administration of yeast derived β-1,3/1,6-d-glucan enhances immune regulation and alters the composition of the gut microbiota. However, it is not known if other structurally distinct β-glucans have similar properties. Here, using C57BL/6 mice, we show the potential of a microalgae derived β-1,3-d-glucan, paramylon (PM), in shaping the gut microbiota and modulating the susceptibility to colitis. The community structure within the gut microbiota showed progressive changes including selective enrichment of specific communities and lowered community richness and diversity during prolonged oral treatment with PM. Compared to control mice, the gut microbiota of PM-treated mice had significantly higher abundance of Verrucomicrobia and lower abundance of Firmicutes. Specific taxa that were significantly more abundant in PM-treated mice include Akkermansia muciniphila and several Bacteroides members. Predictive functional analysis revealed overrepresentation of carbohydrate metabolism function in the fecal microbiota of PM recipients compared to controls, and this function was linked to Bacteroides spp. Prolonged pretreatment with PM not only diminished susceptibility to dextran sulfate sodium induced colitis severity, but also caused enhanced immune regulation. Overall, this study demonstrates the prebiotic properties of PM and the potential benefits of its prolonged oral consumption to gut health.
Effects of Short-Term Dietary Protein Restriction on Blood Amino Acid Levels in Young Men
Authors: Sjøberg Kim , Schmoll Dieter , Piper Matthew , Kiens Bente , Rose Adam
Published: July 2020

Pre-clinical studies show that dietary protein restriction (DPR) improves healthspan and retards many age-related diseases such as type 2 diabetes. While mouse studies have shown that restriction of certain essential amino acids is required for this response, less is known about which amino acids are affected by DPR in humans. Here, using a within-subjects diet design, we examined the effects of dietary protein restriction in the fasted state, as well as acutely after meal feeding, on blood plasma amino acid levels. While very few amino acids were affected by DPR in the fasted state, several proteinogenic AAs such as isoleucine, leucine, lysine, phenylalanine, threonine, tyrosine, and valine were lower in the meal-fed state with DPR. In addition, the non-proteinogenic AAs such as 1- and 3-methyl-histidine were also lower with meal feeding during DPR. Lastly, using in silico predictions of the most limiting essential AAs compared with human exome AA usage, we demonstrate that leucine, methionine, and threonine are potentially the most limiting essential AAs with DPR. In summary, acute meal feeding allows more accurate determination of which AAs are affected by dietary interventions, with most essential AAs lowered by DPR.
Antimicrobial Activities of Highly Bioavailable Organic Salts and Ionic Liquids from Fluoroquinolones
Authors: Santos Miguel M. , Alves Celso , Silva Joana , Florindo Catarina , Costa Alexandra , Petrovski Željko , Marrucho Isabel M. , Pedrosa Rui , Branco Luís C.
Published: July 2020

As the development of novel antibiotics has been at a halt for several decades, chemically enhancing existing drugs is a very promising approach to drug development. Herein, we report the preparation of twelve organic salts and ionic liquids (OSILs) from ciprofloxacin and norfloxacin as anions with enhanced antimicrobial activity. Each one of the fluoroquinolones (FQs) was combined with six different organic hydroxide cations in 93–100% yield through a buffer-assisted neutralization methodology. Six of those were isomorphous salts while the remaining six were ionic liquids, with four of them being room temperature ionic liquids. The prepared compounds were not toxic to healthy cell lines and displayed between 47- and 1416-fold more solubility in water at 25 and 37 °C than the original drugs, with the exception of the ones containing the cetylpyridinium cation. In general, the antimicrobial activity against Klebsiella pneumoniae was particularly enhanced for the ciprofloxacin-based OSILs, with up to ca. 20-fold decreases of the inhibitory concentrations in relation to the parent drug, while activity against Staphylococcus aureus and the commensal Bacillus subtilis strain was often reduced. Depending on the cation–drug combination, broad-spectrum or strain-specific antibiotic salts were achieved, potentially leading to the future development of highly bioavailable and safe antimicrobial ionic formulations.
Changes in the Content of Some Groups of Phenolic Compounds and Biological Activity of Extracts of Various Parts of Heather (Calluna vulgaris (L.) Hull) at Different Growth Stages
Authors: Chepel Victoria , Lisun Valery , Skrypnik Liubov
Published: July 2020

Heather (Calluna vulgaris (L.) Hull.) is noted for a diverse chemical composition and a broad range of biological activity. The current study was aimed at monitoring changes in the accumulation of certain groups of phenolic compounds in various organs of heather (leaves, stems, roots, rhizomes, flowers, and seeds) at different growth stages (vegetative, floral budding, flowering, and seed ripening) as well as studying antioxidant (employing the DPPH and FRAP assays) and antibacterial activity of its extracts. The highest total amount of phenolic compounds, tannins, flavonoids, hydroxycinnamic acids, and proanthocyanidins was detected in leaves and roots at all growth stages, except for the flowering stage. At the flowering stage, the highest content of some groups of phenolic compounds (flavonoids, proanthocyanidins, and anthocyanins) was observed in flowers. Highest antioxidant activity was recorded for the flower extracts (about 500 mg of ascorbic acid equivalents per gram according to the DPPH assay) and for the leaf extract at the ripening stage (about 350 mg of ascorbic acid equivalents per gram according to the FRAP assay). Strong correlation was noted between antioxidant activity (DPPH) and the content of anthocyanins (r = 0.75, p ≤ 0.01) as well as between antioxidant activity (FRAP) and the total content of phenolic compounds (r = 0.77, p ≤ 0.01). Leaf extracts and stem extracts turned out to perform antibacterial action against both gram-negative and gram-positive bacteria, whereas root extracts appeared to be active only against B. subtilis, and rhizome extracts against E. coli.
Enhanced UV-Reflection Facilitated a Shift in the Pollination System of the Red Poppy, Papaver rhoeas (Papaveraceae)
Authors: Martínez-Harms Jaime , Hadar Ravit , Márquez Natalia , Menzel Randolf , Shmida Avi , Stavenga Doekele G. , Vorobyev Misha
Published: July 2020

Evolutionary change is considered a major factor influencing the invasion of new habitats by plants. Yet, evidence on how such modifications promote range expansion remains rather limited. Here we investigated flower color modifications in the red poppy, Papaver rhoeas (Papaveraceae), as a result of its introduction into Central Europe and the impact of those modifications on its interactions with pollinators. We found that while flowers of Eastern Mediterranean poppies reflect exclusively in the red part of the spectrum, those of Central European poppies reflect both red and ultraviolet (UV) light. This change coincides with a shift from pollination by glaphyrid beetles (Glaphyridae) to bees. Glaphyrids have red-sensitive photoreceptors that are absent in bees, which therefore will not be attracted by colors of exclusively red-reflecting flowers. However, UV-reflecting flowers are easily detectable by bees, as revealed by visual modeling. In the North Mediterranean, flowers with low and high UV reflectance occur sympatrically. We hypothesize that Central European populations of P. rhoeas were initially polymorphic with respect to their flower color and that UV reflection drove a shift in the pollination system of P. rhoeas that facilitated its spread across Europe.
Maize Thymidine Kinase Activity Is Present throughout Plant Development and Its Heterologous Expression Confers Tolerance to an Organellar DNA-Damaging Agent
Authors: Nájera-Martínez Manuela , Pedroza-García José Antonio , Suzuri-Hernández Luis Jiro , Mazubert Christelle , Drouin-Wahbi Jeannine , Vázquez-Ramos Jorge , Raynaud Cécile , Plasencia Javier
Published: July 2020

Thymidine kinase 1 (TK1) phosphorylates thymidine nucleosides to generate thymidine monophosphate. This reaction belongs to the pyrimidine salvage route that is phylogenetically conserved. In the model plant Arabidopsis thaliana, TK activity contributes to maintain nuclear and organellar genome integrity by providing deoxythymidine-triphosphate (dTTP) for DNA synthesis. Arabidopsis has two TK1 genes (TK1a and TK1b) and double mutants show an albino phenotype and develop poorly. In contrast, maize (Zea mays L.) has a single TK1 (ZmTK1) gene and mutant plants are albino and display reduced genome copy number in chloroplasts. We studied the role of ZmTK1 during development and genotoxic stress response by assessing its activity at different developmental stages and by complementing Arabidopsis tk1 mutants. We found that ZmTK1 transcripts and activity are present during germination and throughout maize development. We show that ZmTK1 translocation to chloroplasts depends on a 72-amino-acid N-signal and its plastid localization is consistent with its ability to complement Arabidopsis tk1b mutants which are hypersensitive to ciprofloxacin (CIP), a genotoxic agent to organellar DNA. Also, ZmTK1 partly complemented the Arabidopsis double mutant plants during development. Our results contribute to the understanding of TK1 function in monocot species as an organellar enzyme for genome replication and repair.
Anti-Inflamatory Activity of Neolignan Compound Isolated from the Roots of Saururus chinensis
Authors: Yoo Sae-Rom , Ha Hyekyung , Shin Hyeun-Kyoo , Seo Chang-Seob
Published: July 2020

Saururus chinensis (Lour.) Baill. is a perennial herb and grows in Korea, China, and Japan. Interestingly, (7S,8S)-Δ8′-3,4-methylenedioxy-3′,5,5′-trimethoxy-7-monoacetate-8.O.4′-neolignan (MTMN), one of the active neolignans, was first isolated from the roots of Saururus chinensis. The compound was screened for anti-inflammatory activity using a RAW264.7 murine macrophage cell line. The dried roots of S. chinensis (9.7 kg) were extracted with 70% methanol and then solvent fractionation. From the ethyl acetate fraction, MTMN was purified through silica gel column and reverse-phase column chromatography and its structure was identified by spectroscopic analysis with nuclear magnetic resonance, circular dichroism, and mass spectrometry. RAW264.7 cells were induced using lipopolysaccharide (LPS) and treated with or without MTMN. Production of nitric oxide (NO) and prostaglandin E2 (PGE2) levels were measured and protein expressions of nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) were analyzed by immunoblotting. The isolated neolignan was (7S,8S)-Δ8′-3,4-methylenedioxy-3′,5,5′-trimethoxy-7-monoacetate-8.O.4′-neolignan. This compound suppressed the LPS-induced iNOS and COX-2 protein expressions, which led to a decrease in the production of NO and PGE2 levels. Further studies, including in animal models, will be required to establish the precise pharmacological effect of MTMN.
Extrusion Characteristics of Thin Walled Tubes for Catheters Using Thermoplastic Elastomer
Authors: Cho Soonmo , Lee Euntaek , Jo Seunggi , Kim Gyu Man , Kim Woojin
Published: July 2020

As the market for minimally invasive surgery has grown, the demand for high-precision and high-performance catheters has increased. Catheters for the diagnosis and treatment of cardiovascular or cerebrovascular disease mainly use a braided wire tube with a polymer inner liner and outer jacket to improve the pushability and trackability. The outer jacket should have an accurate inner and outer diameter and while maintaining a wall thickness of 150 µm or less. In this study, we designed and manufactured a tip and die capable of extruding an outer jacket with a wall thickness of 150 µm or less using a medical thermoplastic elastomer for manufacturing 8Fr (2.64 mm diameter) thin-walled tubes. The ovality and inner/outer diameters of the tube were studied according to changes in the screw speed (mass flow rate), puller speed, air pressure applied to the lumen, and distance between the quench and head, which are the main variables of microextrusion processes. The screw speed (mass flow rate), puller speed, and air pressure affected the inner/outer diameter of the tube, with screw speed and puller speed having the largest influence on diameter. The air pressure and distance between quench and head had the greatest influence on ovality. The results show the effect of different processing parameters on the characteristics of the extruded tube, which will help to establish a stable extrusion process for the manufacture of outer jackets for braided catheter shafts.
Enzymatic Protein Biopolymers as a Tool to Synthetize Eukaryotic Messenger Ribonucleic Acid (mRNA) with Uses in Vaccination, Immunotherapy and Nanotechnology
Authors: Urbina Fabiola , Morales-Pison Sebastián , Maldonado Edio
Published: July 2020

Multi-subunit enzymes are protein biopolymers that are involved in many cellular processes. The enzyme that carries out the process of transcription of mRNAs is RNA polymerase II (RNAPII), which is a multi-subunit enzyme in eukaryotes. This protein biopolymer starts the transcription from specific sites and is positioned by transcription factors, which form a preinitiation complex (PIC) on gene promoters. To recognize and position the RNAPII and the transcription factors on the gene promoters are needed specific DNA sequences in the gene promoters, which are named promoter elements. Those gene promoter elements can vary and therefore several kinds of promoters exist, however, it appears that all promoters can use a similar pathway for PIC formation. Those pathways are discussed in this review. The in vitro transcribed mRNA can be used as vaccines to fight infectious diseases, e.g., in immunotherapy against cancer and in nanotechnology to deliver mRNA for a missing protein into the cell. We have outlined a procedure to produce an mRNA vaccine against the SARS-CoV-2 virus, which is the causing agent of the big pandemic, COVID-19, affecting human beings all over the world. The potential advantages of using eukaryotic RNAPII to synthetize large transcripts are outlined and discussed. In addition, we suggest a method to cap the mRNA at the 5′ terminus by using enzymes, which might be more effective than cap analogs. Finally, we suggest the construction of a future multi-talented RNAPII, which would be able to synthetize large mRNA and cap them in the test tube.
3D Printing and Bioprinting Nerve Conduits for Neural Tissue Engineering
Authors: Yu Xiaoling , Zhang Tian , Li Yuan
Published: July 2020

Fabrication of nerve conduits for perfectly repairing or replacing damaged peripheral nerve is an urgent demand worldwide, but it is also a formidable clinical challenge. In the last decade, with the rapid development of manufacture technologies, 3D printing and bioprinting have been becoming remarkable stars in the field of neural engineering. In this review, we explore that the biomaterial inks (hydrogels, thermoplastic, and thermoset polyesters and composite) and bioinks have been selected for 3D printing and bioprinting of peripheral nerve conduits. This review covers 3D manufacturing technologies, including extrusion printing, inkjet printing, stereolithography, and bioprinting with inclusion of cells, bioactive molecules, and drugs. Finally, an outlook on the future directions of 3D printing and 4D printing in customizable nerve therapies is presented.
A Novel Cysteine-Functionalized MxOy Material as Support for Laccase Immobilization and a Potential Application in Decolorization of Alizarin Red S
Authors: Kołodziejczak-Radzimska Agnieszka , Jesionowski Teofil
Published: July 2020

Immobilization process improves the enzyme properties, like stability, activity, selectivity or specificity. In the study, a novel cysteine-functionalized MxOy (ZrO2, SiO2) material was used as a support for the immobilization of laccase from Trametes versicolor. The proposed matrix was prepared using a simple sol-gel method. The cysteine was introduced during the synthesis of a sample. Additionally, the obtained supports were modified with glutaraldehyde. The basic properties of the prepared cysteine functionalized ZrO2 and SiO2 were determined using spectroscopic, thermal, porous, electrostatic and elemental analysis. Furthermore, the obtained biocatalytic systems were used as catalysts in the oxidation of sulfonic acid. Catalytic and kinetic parameters were determined based on the proposed model reaction. Next, laccase immobilized on ZrO2- and SiO2-based materials were, for the first time, utilized in the decolorization of Alizarin Red S. In that process, the influence of duration, pH and temperature on the efficiency of decolorization was evaluated. The results show that the proposed biocatalytic systems offer good specific activity (ca. 19 U/mg) and activity retention (ca. 77%). Importantly, they can be successfully used in the decolorization of Alizarin Red S with high efficiency (above 95%).
Sacred Architecture and Public Space under the Conditions of a New Visibility of Religion
Authors: Deibl Jakob Helmut
Published: July 2020

Embedded in the paradigm of the “New Visibility of Religion,” this article addresses the question of the significance of sacred buildings for public spaces. ‘Visibility’ is conceived as religion’s presence in cities through the medium of architecture. In maintaining sacred buildings in cities, religions expose themselves to the conditions of how cities work. They cannot avoid questions such as how to counteract the tendency of public space to erode. Following some preliminary remarks on the “New Visibility of Religion,” I examine selected sacred buildings in Vienna. Next, I focus on the motifs of the city, the “ark” as a model for sacred buildings and the aesthetic dimension of public space. Finally, I consider the contribution of sacred buildings to contemporary public spaces. What is at issue is not the subject that moves in public and visits sacred buildings with the aim of acquiring knowledge or with the urgency to act, but rather the subject that feels and experiences itself in its dealings with public space and sacred buildings. In this context, I refer to the experience of disinterested beauty (Kant), anachronism, multi-perspectivity (Klaus Heinrich), and openness (Hans-Dieter Bahr).
Ship-Iceberg Classification in SAR and Multispectral Satellite Images with Neural Networks
Authors: Heiselberg Henning
Published: July 2020

Classification of ships and icebergs in the Arctic in satellite images is an important problem. We study how to train deep neural networks for improving the discrimination of ships and icebergs in multispectral satellite images. We also analyze synthetic-aperture radar (SAR) images for comparison. The annotated datasets of ships and icebergs are collected from multispectral Sentinel-2 data and taken from the C-CORE dataset of Sentinel-1 SAR images. Convolutional Neural Networks with a range of hyperparameters are tested and optimized. Classification accuracies are considerably better for deep neural networks than for support vector machines. Deeper neural nets improve the accuracy per epoch but at the cost of longer processing time. Extending the datasets with semi-supervised data from Greenland improves the accuracy considerably whereas data augmentation by rotating and flipping the images has little effect. The resulting classification accuracies for ships and icebergs are 86% for the SAR data and 96% for the MSI data due to the better resolution and more multispectral bands. The size and quality of the datasets are essential for training the deep neural networks, and methods to improve them are discussed. The reduced false alarm rates and exploitation of multisensory data are important for Arctic search and rescue services.
Direct Short-Term Forecast of Photovoltaic Power through a Comparative Study between COMS and Himawari-8 Meteorological Satellite Images in a Deep Neural Network
Authors: Kim Minho , Song Hunsoo , Kim Yongil
Published: July 2020

Meteorological satellite images provide crucial information on solar irradiation and weather conditions at spatial and temporal resolutions which are ideal for short-term photovoltaic (PV) power forecasts. Following the introduction of next-generation meteorological satellites, investigating their application on PV forecasts has become imminent. In this study, Communications, Oceans, and Meteorological Satellite (COMS) and Himawari-8 (H8) satellite images were inputted in a deep neural network (DNN) model for 2 hour (h)- and 1 h-ahead PV forecasts. A one-year PV power dataset acquired from two solar power test sites in Korea was used to directly forecast PV power. H8 was used as a proxy for GEO-KOMPSAT-2A (GK2A), the next-generation satellite after COMS, considering their similar resolutions, overlapping geographic coverage, and data availability. In addition, two different data sampling setups were designed to implement the input dataset. The first setup sampled chronologically ordered data using a relatively more inclusive time frame (6 a.m. to 8 p.m. in local time) to create a two-month test dataset, whereas the second setup randomly sampled 25% of data from each month from the one-year input dataset. Regardless of the setup, the DNN model generated superior forecast performance, as indicated by the lowest normalized mean absolute error (NMAE) and normalized root mean squared error (NRMSE) results in comparison to that of the support vector machine (SVM) and artificial neural network (ANN) models. The first setup results revealed that the visible (VIS) band yielded lower NMAE and NRMSE values, while COMS was found to be more influential for 1 h-ahead forecasts. For the second setup, however, the difference in NMAE results between COMS and H8 was not significant enough to distinguish a clear edge in performance. Nevertheless, this marginal difference and similarity of the results suggest that both satellite datasets can be used effectively for direct short-term PV forecasts. Ultimately, the comparative study between satellite datasets as well as spectral bands, time frames, forecast horizons, and forecast models confirms the superiority of the DNN and offers insights on the potential of transitioning to applying GK2A for future PV forecasts.
Comparative Study of IoT-Based Topology Maintenance Protocol in a Wireless Sensor Network for Structural Health Monitoring
Authors: Haque Md. Ershadul , Asikuzzaman Md. , Khan Imran Ullah , Ra In-Ho , Hossain Md. Sanwar , Shah Syed Bilal Hussain
Published: July 2020

A structural health monitoring (SHM) system is an approach for identifying the damages caused to various kinds of structures using different system functions and providing the necessary feedback about structure’s conditions. As civil structures are the backbone of our society, to determine its daily operations is a very important issue. The performance measurement of those structures is manual whereas a computer-based monitoring system could automatically assess the structural damages and identify its exact location. Recently, wireless sensor networks (WSNs) have attracted a great deal of attention for remote sensing applications due to flexibility to measure of various activity of large scale network. Since technology is advancing day by day, the overall cost of a monitoring system is also decreased. However, the major challenging fact of a WSNs is to provide scalability for covering a large area. The main question is arisen how much capable have of a monitoring system to turn off unnecessary nodes to save energy while there are no events detected. To support the scalability required of an existing network and save the node energy for future use, we propose a topology maintenance protocol integrated with construction to address the issue of a node’s energy consumption by placing it optimally and extending the monitoring system’s lifetime. As per the authors’ acknowledgement that, a little attention has been paid to developing such a hybrid approach. To mitigate node energy consumption issue with large scale support, an Internet of Things (IoT)-based maintenance approach is the best candidate for obtaining better system lifetime responses. Therefore, the main goal of this work is to develop an ‘on-the-fly’-based topology maintenance monitoring system, which can maintain a network’s infrastructure while gathering a node’s information to switch its state regularly when the present network is no longer optimal.
Potential of UAS-Based Remote Sensing for Estimating Tree Water Status and Yield in Sweet Cherry Trees
Authors: Blanco Víctor , Blaya-Ros Pedro José , Castillo Cristina , Soto-Vallés Fulgencio , Torres-Sánchez Roque , Domingo Rafael
Published: July 2020

The present work aims to assess the usefulness of five vegetation indices (VI) derived from multispectral UAS imagery to capture the effects of deficit irrigation on the canopy structure of sweet cherry trees (Prunus avium L.) in southeastern Spain. Three irrigation treatments were assayed, a control treatment and two regulated deficit irrigation treatments. Four airborne flights were carried out during two consecutive seasons; to compare the results of the remote sensing VI, the conventional and continuous water status indicators commonly used to manage sweet cherry tree irrigation were measured, including midday stem water potential (Ψs) and maximum daily shrinkage (MDS). Simple regression between individual VIs and Ψs or MDS found stronger relationships in postharvest than in preharvest. Thus, the normalized difference vegetation index (NDVI), resulted in the strongest relationship with Ψs (r2 = 0.67) and MDS (r2 = 0.45), followed by the normalized difference red edge (NDRE). The sensitivity analysis identified the optimal soil adjusted vegetation index (OSAVI) as the VI with the highest coefficient of variation in postharvest and the difference vegetation index (DVI) in preharvest. A new index is proposed, the transformed red range vegetation index (TRRVI), which was the only VI able to statistically identify a slight water deficit applied in preharvest. The combination of the VIs studied was used in two machine learning models, decision tree and artificial neural networks, to estimate the extra labor needed for harvesting and the sweet cherry yield.
Application of Empirical Land-Cover Changes to Construct Climate Change Scenarios in Federally Managed Lands
Authors: Soulard Christopher E. , Rigge Matthew
Published: July 2020

Sagebrush-dominant ecosystems in the western United States are highly vulnerable to climatic variability. To understand how these ecosystems will respond under potential future conditions, we correlated changes in National Land Cover Dataset “Back-in-Time” fractional cover maps from 1985-2018 with Daymet climate data in three federally managed preserves in the sagebrush steppe ecosystem: Beaty Butte Herd Management Area, Hart Mountain National Antelope Refuge, and Sheldon National Wildlife Refuge. Future (2018 to 2050) abundance and distribution of vegetation cover were modeled at a 300-m resolution under a business-as-usual climate (BAU) scenario and a Representative Concentration Pathway (RCP) 8.5 climate change scenario. Spatially explicit map projections suggest that climate influences may make the landscape more homogeneous in the near future. Specifically, projections indicate that pixels with high bare ground cover become less bare ground dominant, pixels with moderate herbaceous cover contain less herbaceous cover, and pixels with low shrub cover contain more shrub cover. General vegetation patterns and composition do not differ dramatically between scenarios despite RCP 8.5 projections of +1.2 °C mean annual minimum temperatures and +7.6 mm total annual precipitation. Hart Mountain National Antelope Refuge is forecast to undergo the most change, with both models projecting larger declines in bare ground and larger increases in average herbaceous and shrub cover compared to Beaty Butte Herd Management Area and Sheldon National Wildlife Refuge. These scenarios present plausible future outcomes intended to guide federal land managers to identify vegetation cover changes that may affect habitat condition and availability for species of interest.
Evaluation of Ocean Color Remote Sensing Algorithms for Diffuse Attenuation Coefficients and Optical Depths with Data Collected on BGC-Argo Floats
Authors: Xing Xiaogang , Boss Emmanuel , Zhang Jie , Chai Fei
Published: July 2020

The vertical distribution of irradiance in the ocean is a key input to quantify processes spanning from radiative warming, photosynthesis to photo-oxidation. Here we use a novel dataset of thousands local-noon downwelling irradiance at 490 nm (Ed(490)) and photosynthetically available radiation (PAR) profiles captured by 103 BGC-Argo floats spanning three years (from October 2012 to January 2016) in the world’s ocean, to evaluate several published algorithms and satellite products related to diffuse attenuation coefficient (Kd). Our results show: (1) MODIS-Aqua Kd(490) products derived from a blue-to-green algorithm and two semi-analytical algorithms show good consistency with the float-observed values, but the Chla-based one has overestimation in oligotrophic waters; (2) The Kd(PAR) model based on the Inherent Optical Properties (IOPs) performs well not only at sea-surface but also at depth, except for the oligotrophic waters where Kd(PAR) is underestimated below two penetration depth (2zpd), due to the model’s assumption of a homogeneous distribution of IOPs in the water column which is not true in most oligotrophic waters with deep chlorophyll-a maxima; (3) In addition, published algorithms for the 1% euphotic-layer depth and the depth of 0.415 mol photons m−2 d−1 isolume are evaluated. Algorithms based on Chla generally work well while IOPs-based ones exhibit an overestimation issue in stratified and oligotrophic waters, due to the underestimation of Kd(PAR) at depth.
Estimating River Sediment Discharge in the Upper Mississippi River Using Landsat Imagery
Authors: A. Flores Jonathan , Q. Wu Joan , O. Stöckle Claudio , P. Ewing Robert , Yang Xiao
Published: July 2020

With the decline of operational river gauges monitoring sediments, a viable means of quantifying sediment transport is needed. In this study, we address this issue by applying relationships between hydraulic geometry of river channels, water discharge, water-leaving surface reflectance (SR), and suspended sediment concentration (SSC) to quantify sediment discharge with the aid of space-based observations. We examined 5490 Landsat scenes to estimate water discharge, SSC, and sediment discharge for the period from 1984 to 2017 at nine gauging sites along the Upper Mississippi River. We used recent advances in remote sensing of fluvial systems, such as automated river width extraction, Bayesian discharge inference with at-many-stations hydraulic geometry (AMHG), and SSC-SR regression models. With 621 Landsat scenes available from all the gauging sites, the results showed that the water discharge and SSC retrieval from Landsat imagery can yield reasonable sediment discharge estimates along the Upper Mississippi River. An overall relative bias of −25.4, mean absolute error (MAE) of 6.24 × 104 tonne/day, relative root mean square error (RRMSE) of 1.21, and Nash–Sutcliffe Efficiency (NSE) of 0.49 were obtained for the sediment discharge estimation. Based on these statistical metrics, we identified three of the nine gauging sites (St. Louis, MO; Chester, IL; and Thebes, IL), which were in the downstream portion of the river, to be the best locations for estimating water and sediment discharge using Landsat imagery.
A SAR Image Despeckling Method Based on an Extended Adaptive Wiener Filter and Extended Guided Filter
Authors: Salehi Hadi , Vahidi Javad , Abdeljawad Thabet , Khan Aziz , Rad Seyed Yaser Bozorgi
Published: July 2020

The elimination of multiplicative speckle noise is the main issue in synthetic aperture radar (SAR) images. In this study, a SAR image despeckling filter based on a proposed extended adaptive Wiener filter (EAWF), extended guided filter (EGF), and weighted least squares (WLS) filter is proposed. The proposed EAWF and EGF have been developed from the adaptive Wiener filter (AWF) and guided Filter (GF), respectively. The proposed EAWF can be applied to the SAR image, without the need for logarithmic transformation, considering the fact that the denoising performance of EAWF is better than AWF. The proposed EGF can remove the additive noise and preserve the edges’ information more efficiently than GF. First, the EAWF is applied to the input image. Then, a logarithmic transformation is applied to the resulting EAWF image in order to convert multiplicative noise into additive noise. Next, EGF is employed to remove the additive noise and preserve edge information. In order to remove unwanted spots on the image that is filtered by EGF, it is applied twice with different parameters. Finally, the WLS filter is applied in the homogeneous region. Results show that the proposed algorithm has a better performance in comparison with the other existing filters.
Ionospheric S4 Scintillations from GNSS Radio Occultation (RO) at Slant Path
Authors: Wu Dong L.
Published: July 2020

Ionospheric scintillation can significantly degrade the performance and the usability of space-based communication and navigation signals. Characterization and prediction of ionospheric scintillation can be made from the Global Navigation Satellite System (GNSS) radio occultation (RO) technique using the measurement from a deep slant path where the RO tangent height (ht) is far below the ionospheric sources. In this study, the L–band S4 from the RO measurements at ht = 30 km is used to infer the amplitude scintillation on the ground. The analysis of global RO data at ht = 30 km shows that sporadic–E (Es), equatorial plasma bubbles (EPBs), and equatorial spread–F (ESF) produce most of the significant S4 enhancements, although the polar S4 is generally weak. The enhanced S4 is a strong function of local time and magnetic dip angle. The Es–induced daytime S4 tends to have a negative correlation with the solar cycle at low latitudes but a positive correlation at high latitudes. The nighttime S4 is dominated by a strong semiannual variation at low latitudes.
LARa: Creating a Dataset for Human Activity Recognition in Logistics Using Semantic Attributes
Authors: Niemann Friedrich , Reining Christopher , Moya Rueda Fernando , Nair Nilah Ravi , Steffens Janine Anika , Fink Gernot A. , ten Hompel Michael
Published: July 2020

Optimizations in logistics require recognition and analysis of human activities. The potential of sensor-based human activity recognition (HAR) in logistics is not yet well explored. Despite a significant increase in HAR datasets in the past twenty years, no available dataset depicts activities in logistics. This contribution presents the first freely accessible logistics-dataset. In the ’Innovationlab Hybrid Services in Logistics’ at TU Dortmund University, two picking and one packing scenarios were recreated. Fourteen subjects were recorded individually when performing warehousing activities using Optical marker-based Motion Capture (OMoCap), inertial measurement units (IMUs), and an RGB camera. A total of 758 min of recordings were labeled by 12 annotators in 474 person-h. All the given data have been labeled and categorized into 8 activity classes and 19 binary coarse-semantic descriptions, also called attributes. The dataset is deployed for solving HAR using deep networks.
Collaborative Solutions for Interference Management in GNSS-Based Aircraft Navigation
Authors: Nicola Mario , Falco Gianluca , Morales Ferre Ruben , Lohan Elena-Simona , de la Fuente Alberto , Falletti Emanuela
Published: July 2020

Nowadays, the Global Navigation Satellite Systems (GNSS) technology is not the primary means of navigation for civil aviation and Air Traffic Control, but its role is increasing. Consequently, the vulnerabilities of GNSSs to Radio Frequency Interference, including the dangerous intentional sources of interference (i.e., jamming and spoofing), raise concerns and special attention also in the aviation field. This panorama urges for figuring out effective solutions able to cope with GNSS interference and preserve safety of operations. In the frame of a Single European Sky Air traffic management Research (SESAR) Exploratory Research initiative, a novel, effective, and affordable concept of GNSS interference management for civil aviation has been developed. This new interference management concept is able to raise early warnings to the on-board navigation system about the detection of interfering signals and their classification, and then to estimate the Direction of Arrival (DoA) of the source of interference allowing the adoption of appropriate countermeasures against the individuated source. This paper describes the interference management concept and presents the on-field tests which allowed for assessing the reached level of performance and confirmed the applicability of this approach to the aviation applications.
How We Found Our IMU: Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications
Authors: Zhou Lin , Fischer Eric , Tunca Can , Brahms Clemens Markus , Ersoy Cem , Granacher Urs , Arnrich Bert
Published: July 2020

Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
Experimental Evaluation of a 3D-Printed Fluidic System for a Directional Anemometer
Authors: Ria Andrea , Catania Alessandro , Bruschi Paolo , Piotto Massimo
Published: July 2020

An evolution of a previously proposed anemometer capable of detecting both the magnitude and the direction of the wind on a plane is proposed. The device is based on a recently formalized principle, consisting of combining the differential pressures measured across distinct diameters of a cylinder to estimate the wind velocity and incidence angle. Differently from previous sensors based on the same principle, the proposed anemometers use 3D printing to fabricate the channel structure that calculates the pressure combination in the fluidic domain. Furthermore, commercial sensors with low power consumption are used to read the two pressures that result from the fluidic processing. The whole fabrication procedure requires inexpensive equipment and can be adopted by small enterprises or research laboratories. Two original channel structures, predicted by previous theoretical work but never experimentally validated, are proposed. The results of detailed experiments performed in a wind tunnel are reported.
EERS: Energy-Efficient Reference Node Selection Algorithm for Synchronization in Industrial Wireless Sensor Networks
Authors: Elsharief Mahmoud , El-Gawad Mohamed A. Abd , Ko Haneul , Pack Sangheon
Published: July 2020

Time synchronization is an essential issue in industrial wireless sensor networks (IWSNs). It assists perfect coordinated communications among the sensor nodes to preserve battery power. Generally, time synchronization in IWSNs has two major aspects of energy consumption and accuracy. In the literature, the energy consumption has not received much attention in contrast to the accuracy. In this paper, focusing on the energy consumption aspect, we introduce an energy-efficient reference node selection (EERS) algorithm for time synchronization in IWSNs. It selects and schedules a minimal sequence of connected reference nodes that are responsible for spreading timing messages. EERS achieves energy consumption synchronization by reducing the number of transmitted messages among the sensor nodes. To evaluate the performance of EERS, we conducted extensive experiments with Arduino Nano RF sensors and revealed that EERS achieves considerably fewer messages than previous techniques, robust time synchronization (R-Sync), fast scheduling and accurate drift compensation for time synchronization (FADS), and low power scheduling for time synchronization protocols (LPSS). In addition, simulation results for a large sensor network of 450 nodes demonstrate that EERS reduces the whole number of transmitted messages by 52%, 30%, and 13% compared to R-Sync, FADS, and LPSS, respectively.
Electromagnetic Sensors for Underwater Scour Monitoring
Authors: Maroni Andrea , Tubaldi Enrico , Ferguson Neil , Tarantino Alessandro , McDonald Hazel , Zonta Daniele
Published: July 2020

Scour jeopardises the safety of many civil engineering structures with foundations in riverbeds and it is the leading cause for the collapse of bridges worldwide. Current approaches for bridge scour risk management rely mainly on visual inspections, which provide unreliable estimates of scour and of its effects, also considering the difficulties in visually monitoring the riverbed erosion around submerged foundations. Thus, there is a need to introduce systems capable of continuously monitoring the evolution of scour at bridge foundations, even during extreme flood events. This paper illustrates the development and deployment of a scour monitoring system consisting of smart probes equipped with electromagnetic sensors. This is the first application of this type of sensing probes to a real case-study for continuous scour monitoring. Designed to observe changes in the permittivity of the medium around bridge foundations, the sensors allow for detection of scour depths and the assessment of whether the scour hole has been refilled. The monitoring system was installed on the A76 200 Bridge in New Cumnock (S-W Scotland) and has provided a continuous recording of the scour for nearly two years. The scour data registered after a peak flood event (validated against actual measurements of scour during a bridge inspection) show the potential of the technology in providing continuous scour measures, even during extreme flood events, thus avoiding the deployment of divers for underwater examination.
Classification of Neurological Patients to Identify Fallers Based on Spatial-Temporal Gait Characteristics Measured by a Wearable Device
Authors: Zhou Yuhan , Zia Ur Rehman Rana , Hansen Clint , Maetzler Walter , Del Din Silvia , Rochester Lynn , Hortobágyi Tibor , Lamoth Claudine J. C.
Published: July 2020

Neurological patients can have severe gait impairments that contribute to fall risks. Predicting falls from gait abnormalities could aid clinicians and patients mitigate fall risk. The aim of this study was to predict fall status from spatial-temporal gait characteristics measured by a wearable device in a heterogeneous population of neurological patients. Participants (n = 384, age 49–80 s) were recruited from a neurology ward of a University hospital. They walked 20 m at a comfortable speed (single task: ST) and while performing a dual task with a motor component (DT1) and a dual task with a cognitive component (DT2). Twenty-seven spatial-temporal gait variables were measured with wearable sensors placed at the lower back and both ankles. Partial least square discriminant analysis (PLS-DA) was then applied to classify fallers and non-fallers. The PLS-DA classification model performed well for all three gait tasks (ST, DT1, and DT2) with an evaluation of classification performance Area under the receiver operating characteristic Curve (AUC) of 0.7, 0.6 and 0.7, respectively. Fallers differed from non-fallers in their specific gait patterns. Results from this study improve our understanding of how falls risk-related gait impairments in neurological patients could aid the design of tailored fall-prevention interventions.
Materials Contamination and Indoor Air Pollution Caused by Tar Products and Fungicidal Impregnations: Intervention Research in 2014–2019
Authors: Kozicki Mateusz , Niesłochowski Adam
Published: July 2020

Construction materials containing tar products are a source of indoor air pollution in buildings. This particularly concerns old buildings, in which wooden structures were impregnated with tar compositions (creosote oil and Xylamite oil containing tar products) and buildings in which bituminous seal containing hydrocarbon solvents was used. During the 1970s and 1980s, an impregnant known as Xylamite was commonly used in Polish buildings. This material still emits organic vapors into the building’s environment, significantly worsening indoor air quality (IAQ). Xylamites and other impregnating materials are a source of indoor air pollution through toxic organic compounds, such as phenol, cresols, naphthalenes, chlorophenols (CPs), and chloronaphthalenes (CNs), which emit specific odors. TD-GC/MS enables detailed identification of the reasons behind chemical indoor air pollution. The results of laboratory tests on the chemical emissions of bitumen-impregnated materials were presented in 32 case studies. In turn, the results of indoor air pollution by volatile bitumen components were presented on 11 reference rooms and 14 case studies, including residential buildings, office buildings, and others. Laboratory tests of samples of construction products confirmed the main emission sources into indoor air. The research results for the period 2014–2019 are tabulated and described in detail in this manuscript.