bluuebunny/crossref_metadata_2025 huggingface dataset:
Microalgae-Templated Spray Drying for Hierarchical and Porous Fe3O4/C Composite Microspheres as Li-ion Battery Anode Materials
Authors: Park Jinseok , Kim Jungmin , Jung Dae Soo , Phiri Isheunesu , Bae Hyeon-Su , Hong Jinseok , Kim Sojin , Lee Young-Gi , Ryou Myung-Hyun , Lee Kyubock
Published: October 2020

A method of microalgae-templated spray drying to develop hierarchical porous Fe3O4/C composite microspheres as anode materials for Li-ion batteries was developed. During the spray-drying process, individual microalgae serve as building blocks of raspberry-like hollow microspheres via self-assembly. In the present study, microalgae-derived carbon matrices, naturally doped heteroatoms, and hierarchical porous structural features synergistically contributed to the high electrochemical performance of the Fe3O4/C composite microspheres, enabling a discharge capacity of 1375 mA·h·g−1 after 700 cycles at a current density of 1 A/g. Notably, the microalgal frameworks of the Fe3O4/C composite microspheres were maintained over the course of charge/discharge cycling, thus demonstrating the structural stability of the composite microspheres against pulverization. In contrast, the sample fabricated without microalgal templating showed significant capacity drops (up to ~40% of initial capacity) during the early cycles. Clearly, templating of microalgae endows anode materials with superior cycling stability.
Efficacy of “High in” Nutrient Specific Front of Package Labels—A Retail Experiment with Canadians of Varying Health Literacy Levels
Authors: Mansfield Elizabeth D. , Ibanez Dominique , Chen Fuqi , Chen Emily , de Grandpré Elaine
Published: October 2020

Background: In 2018, Health Canada, the Federal department responsible for public health, put forward a regulatory proposal to introduce regulations requiring a “High in” front-of-package label (FOPL) on foods that exceed predetermined thresholds for sodium, sugars, or saturated fat. This study evaluated the efficacy of the proposed FOPL as a quick and easy tool for making food choices that support reduction in the intakes of these nutrients. Methods: Consumers (n = 625) of varying health literacy levels (HL) were assigned to control (current labeling with no FOPL) or one of four FOPL designs. They completed six shopping tasks, designed to control for internal motivations. Efficacy was measured with correct product selection and response time (seconds) to make food choices using repeated measures statistical modeling, adjusting for HL, task type, and task order. Eye-tracking and structured interviews were used to gather additional insights about participants’ choices. Results: Overall, FOPL was significantly more effective than current labeling at helping consumers of varying HL levels to identify foods high in nutrients of concern and make healthier food choices. All FOPL were equally effective. Conclusions: “High in” FOPL can be effective at helping Canadians of varying HL levels make more informed food choices in relation to sugars, sodium, and saturated fat.
Inulin Supplementation Disturbs Hepatic Cholesterol and Bile Acid Metabolism Independent from Housing Temperature
Authors: Pauly Mira J. , Rohde Julia K. , John Clara , Evangelakos Ioannis , Koop Anja Christina , Pertzborn Paul , Tödter Klaus , Scheja Ludger , Heeren Joerg , Worthmann Anna
Published: October 2020

Dietary fibers are fermented by gut bacteria into the major short chain fatty acids (SCFAs) acetate, propionate, and butyrate. Generally, fiber-rich diets are believed to improve metabolic health. However, recent studies suggest that long-term supplementation with fibers causes changes in hepatic bile acid metabolism, hepatocyte damage, and hepatocellular cancer in dysbiotic mice. Alterations in hepatic bile acid metabolism have also been reported after cold-induced activation of brown adipose tissue. Here, we aim to investigate the effects of short-term dietary inulin supplementation on liver cholesterol and bile acid metabolism in control and cold housed specific pathogen free wild type (WT) mice. We found that short-term inulin feeding lowered plasma cholesterol levels and provoked cholestasis and mild liver damage in WT mice. Of note, inulin feeding caused marked perturbations in bile acid metabolism, which were aggravated by cold treatment. Our studies indicate that even relatively short periods of inulin consumption in mice with an intact gut microbiome have detrimental effects on liver metabolism and function.
Associations of Non-Alcoholic Beverages with Major Depressive Disorder History and Depressive Symptoms Clusters in a Sample of Overweight Adults
Authors: Pérez-Ara M. Ángeles , Gili Margalida , Visser Marjolein , Penninx Brenda W.J.H. , Brouwer Ingeborg A. , Watkins Ed , Owens Matt , García-Toro Mauro , Hegerl Ulrich , Kohls Elisabeth , Bot Mariska , Roca Miquel
Published: October 2020

Background: Meta-analysis of observational studies concluded that soft drinks may increase the risk of depression, while high consumption of coffee and tea may reduce the risk. Objectives were to explore the associations between the consumption of soft drinks, coffee or tea and: (1) a history of major depressive disorder (MDD) and (2) the severity of depressive symptoms clusters (mood, cognitive and somatic/vegetative symptoms). Methods: Cross-sectional and longitudinal analysis based on baseline and 12-month-follow-up data collected from four countries participating in the European MooDFOOD prevention trial. In total, 941 overweight adults with subsyndromal depressive symptoms aged 18 to 75 years were analyzed. History of MDD, depressive symptoms and beverages intake were assessed. Results: Sugar-sweetened soft drinks were positively related to MDD history rates whereas soft drinks with non-nutritive sweeteners were inversely related for the high vs. low categories of intake. Longitudinal analysis showed no significant associations between beverages and mood, cognitive and somatic/vegetative clusters. Conclusion: Our findings point toward a relationship between soft drinks and past MDD diagnoses depending on how they are sweetened while we found no association with coffee and tea. No significant effects were found between any studied beverages and the depressive symptoms clusters in a sample of overweight adults.
All-Cause Mortality and Cardiovascular Death between Statins and Omega-3 Supplementation: A Meta-Analysis and Network Meta-Analysis from 55 Randomized Controlled Trials
Authors: Kim Jeongseon , Hoang Tung , Kim Ji-Myung , Bu So Young , Choi Jeong-Hwa , Park Eunju , Lee Seung-Min , Park Eunmi , Min Ji Yeon , Lee In Seok , Youn So Young , Yeon Jee-Young
Published: October 2020

Statins and omega-3 supplementation have shown potential benefits in preventing cardiovascular disease (CVD), but their comparative effects on mortality outcomes, in addition to primary and secondary prevention and mixed population, have not been investigated. This study aimed to examine the effect of statins and omega-3 supplementation and indirectly compare the effects of statin use and omega-3 fatty acids on all-cause mortality and CVD death. We included randomized controlled trials (RCTs) from meta-analyses published until December 2019. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated to indirectly compare the effect of statin use versus omega-3 supplementation in a frequentist network meta-analysis. In total, 55 RCTs were included in the final analysis. Compared with placebo, statins were significantly associated with a decreased the risk of all-cause mortality (RR = 0.90, 95% CI = 0.86–0.94) and CVD death (RR = 0.86, 95% CI = 0.80–0.92), while omega-3 supplementation showed a borderline effect on all-cause mortality (RR = 0.97, 95% CI = 0.94–1.01) but were significantly associated with a reduced risk of CVD death (RR = 0.92, 95% CI = 0.87–0.98) in the meta-analysis. The network meta-analysis found that all-cause mortality was significantly different between statin use and omega-3 supplementation for overall population (RR = 0.91, 95% CI = 0.85–0.98), but borderline for primary prevention and mixed population and nonsignificant for secondary prevention. Furthermore, there were borderline differences between statin use and omega-3 supplementation in CVD death in the total population (RR = 0.92, 95% CI = 0.82–1.04) and primary prevention (RR = 0.85, 95% CI = 0.68–1.05), but nonsignificant differences in secondary prevention (RR = 0.97, 95% CI = 0.66–1.43) and mixed population (RR = 0.92, 95% CI = 0.75–1.14). To summarize, statin use might be associated with a lower risk of all-cause mortality than omega-3 supplementation. Future direct comparisons between statin use and omega-3 supplementation are required to confirm the findings.
Erratum: Mwiiri, F.K.; et al. Electrospun Bioactive Wound Dressing Containing Colloidal Dispersions of Birch Bark Dry Extract. Pharmaceutics 2020, 12, 770
Authors: Mwiiri Francis Kamau , Brandner Johanna M. , Daniels Rolf
Published: October 2020

The authors wish to make the following correction to this paper [...]
Overexpression of CDSP32 (GhTRX134) Cotton Gene Enhances Drought, Salt, and Oxidative Stress Tolerance in Arabidopsis
Authors: Elasad Mohammed , Ahmad Adeel , Wang Hantao , Ma Liang , Yu Shuxun , Wei Hengling
Published: October 2020

Upland cotton (Gossypium hirsutum L.) is the main natural fiber crop worldwide and is an essential source of seed oil and biofuel products. Many abiotic stresses, such as drought and salinity, constrain cotton production. Thioredoxins (TRXs) are a group of small ubiquitous proteins that are widely distributed among organisms. TRXs play a crucial role in regulating diverse functions during plant growth and development. In the present study, a novel GhTRX134 gene was characterized and overexpressed in Arabidopsis and silenced in cotton under drought stress. Furthermore, the proline content and enzyme activity levels were measured in transgenic plants and wild-type (Wt) plants under drought and salt stress. The results revealed that the overexpression of GhTRX134 enhanced abiotic stress tolerance. When GhTRX134 was silenced, cotton plants become more sensitive to drought. Taken together, these findings confirmed that the overexpression of GhTRX134 improved drought and salt tolerance in Arabidopsis plants. Therefore, the GhTRX134 gene can be transformed into cotton plants to obtain transgenic lines for more functional details.
Phosphorus Nutrient Management through Synchronization of Application Methods and Rates in Wheat and Maize Crops
Authors: Rafiullah  , Khan Muhammad Jamal , Muhammad Dost , Fahad Shah , Adnan Muhammad , Wahid Fazli , Alamri Saud , Khan Farmanullah , Dawar Khadim Muhammad , Irshad Inam , Danish Subhan , Arif Muhammad , Amanullah  , Saud Shah , Khan Bushra , Mian Ishaq Ahmad , Datta Rahul , Zarei Tayebeh , Shah Anis Ali , Ramzan Musarrat , Zafar-ul-Hye Muhammad , Mussarat Maria , Siddiqui Manzer H.
Published: October 2020

Management of inorganic fertilizer is very important to obtain maximum crop yield and improved nutrient use efficiency in cereal crops. Fixation of phosphatic fertilizers in alkaline soils due to calcareousness is one of the major hurdles. It induces phosphorus nutritional stress that can decrease the yield of maize and wheat. Selection of a suitable application method and proper stage of crop for phosphorus (P) fertilizer has prime importance in better uptake of P and crop production. Among different application methods, soil and foliar application are widely adopted. In wheat and maize, knee height + tasseling and stem elongation + booting are critical stages towards P deficiency. That is why field trials were conducted to evaluate the supplemental effect of foliar P on maize and wheat yields. For that, 144 mM KH2PO4 was applied as foliar at knee height + tasseling and stem elongation + boot stages in maize and wheat, respectively. Soil application of 0, 20, 40 and 60 kg P ha−1 was done through broadcast and band methods. Results showed that foliar spray of 144 mM KH2PO4 at knee height + tasseling and stem elongation + boot stages in wheat and maize significantly enhanced grains yield and phosphorus use efficiency (PUE) where P was applied as banding or broadcast at the time of sowing. A significant decreasing trend in response to increasing soil P levels validated the efficacious role and suitability of foliar P. In conclusion, the use of P as foliar at knee height + tasseling and stem elongation + boot stages is an efficacious way to manage P fertilizer.
Prediction of Dhurrin Metabolism by Transcriptome and Metabolome Analyses in Sorghum
Authors: Choi Sang Chul , Chung Yong Suk , Lee Yun Gyeong , Kang Yuna , Park Yun Ji , Park Sang Un , Kim Changsoo
Published: October 2020

Sorghum (Sorghum bicolor (L.)) Moench is an important food for humans and feed for livestock. Sorghum contains dhurrin which can be degraded into toxic hydrogen cyanide. Here, we report the expression patterns of 14 candidate genes related to dhurrin ((S)-4-Hydroxymandelnitrile-β-D-glucopyranoside) metabolism and the effects of the gene expression on specific metabolite content in selected sorghum accessions. Dhurrin-related metabolism is vigorous in the early stages of development of sorghum. The dhurrin contents of most accessions tested were in the range of approximately 6–22 μg mg−1 fresh leaf tissue throughout growth. The p-hydroxybenzaldehyde (pHB) contents were high at seedling stages, but almost nonexistent at adult stages. The contents of p-hydroxyphenylacetic acid (pHPAAc) were relatively low throughout growth compared to those of dhurrin or pHB. Generally, the expression of the candidate genes was higher at seedling stage than at other stages and decreased gradually as plants grew. In addition, we identified significant SNPs, and six of them were potentially associated with non-synonymous changes in CAS1. Our results may provide the basis for choosing breeding materials to regulate cyanide contents in sorghum varieties to prevent HCN toxicity of livestock or to promote drought tolerance or pathogen resistance.
Preparation and Characterization of Semi-Flexible Substrates from Natural Fiber/Nickel Oxide/Polycaprolactone Composite for Microstrip Patch Antenna Circuitries for Microwave Applications
Authors: Ahmad Ahmad Fahad , Aziz Sidek Ab , Yaakob Yazid , Abd Ali Ammar , Issa Nour Attallah
Published: October 2020

The study intended to utilizing waste organic fiber for low-cost semi-flexible substrate fabrication to develop microstrip patch antennas for low band communication applications. All the semi-flexible substrates (12.2 wt. % OPEFF/87.8 wt. % PCL, 12.2 wt. % NiO/87.8 wt. % PCL, and 25 wt. % OPEFF/25 wt. % NiO/50 wt. % PCL) were fabricated by oil palm empty fruit fiber (OPEFF) mixed with nickel oxide (NiO) nanoparticles reinforced with polycaprolactone (PCL) as a matrix using a Thermo Haake blending machine. The morphology and crystalized structure of the substrates were tested using Fourier transform infrared (FTIR) spectrometry, X-ray diffraction (X-RD) technique, and scanning electron microscopy (SEM), respectively. The thermal stability behavior of the substrates was analyzed using thermogravimetric analysis (TGA) and differential thermogravimetric (DTG) thermogram. The dielectric properties were characterized by an open-ended coaxial probe (OEC) connected with Agilent N5230A PNA-L Network Analyzer included the 85070E2 dielectric software at frequency range of 8 to 12 GHz. The experimental results showed that NiO/OPEFF/PCL composites exhibit controllable permittivity dielectric constant εr′(f) between 1.89 and 4.2 (Farad/meter, (F/m)), with loss factor εr′′(f) between 0.08 and 0.62 F/m, and loss tangent (tan δ) between 0.05 and 0.18. Return losses measurement of the three patch antennas OPEFF/PCL, NiO/PCL, and OPEFF/NiO/PCL are −11.93, −14.2 and −16.3 dB respectively. Finally, the commercial software package, Computer Simulation Technology Microwave Studio (CSTMWS), was used to investigate the antenna performance by simulate S-parameters based on the measured dielectric parameters. A negligible difference is found between the measured and simulated results. Finally, the results obtained encourage the possibility of using natural fibers and nickel oxide in preparation of the substrates utilize at microwave applications.
Melt Rheology and Mechanical Characteristics of Poly(Lactic Acid)/Alkylated Graphene Oxide Nanocomposites
Authors: Park In Hye , Lee Jae Yoon , Ahn Seung Jae , Choi Hyoung Jin
Published: October 2020

Poly(lactic acid) (PLA) nanocomposites were synthesized by a solution blending and coagulation method using alkylated graphene oxide (AGO) as a reinforcing agent. Turbiscan confirmed that the alkylation of GO led to enhanced compatibility between the matrix and the filler. The improved dispersity of the filler resulted in superior interfacial adhesion between the PLA chains and AGO basal plane, leading to enhanced mechanical and rheological properties compared to neat PLA. The tensile strength and elongation at break, i.e., ductility, increased by 38% and 42%, respectively, at the same filler content nanocomposite (PLA/AGO 1 wt %) compared to nonfiller PLA. Rheological analysis of the nanocomposites in the molten state of the samples was performed to understand the filler network formed inside the matrix. The storage modulus increased significantly from PLA/AGO 0.5 wt % (9.6 Pa) to PLA/AGO 1.0 wt % (908 Pa). This indicates a percolation threshold between the two filler contents. A steady shear test was performed to examine the melt flow characteristics of PLA/AGO nanocomposites at 170 °C, and the viscosity was predicted using the Carreau−Yasuda model.
EMG Measurement with Textile-Based Electrodes in Different Electrode Sizes and Clothing Pressures for Smart Clothing Design Optimization
Authors: Kim Siyeon , Lee Sojung , Jeong Wonyoung
Published: October 2020

The surface electromyography (SEMG) is one of the most popular bio-signals that can be applied in health monitoring systems, fitness training, and rehabilitation devices. Commercial clothing embedded with textile electrodes has already been released onto the market, but there is insufficient information on the performance of textile SEMG electrodes because the required configuration may differ according to the electrode material. The current study analyzed the influence of electrode size and pattern reduction rate (PRR), and hence the clothing pressure (Pc) based on in vivo SEMG signal acquisition. Bipolar SEMG electrodes were made in different electrode diameters Ø 5–30 mm, and the clothing pressure ranged from 6.1 to 12.6 mmHg. The results supported the larger electrodes, and Pc showed better SEMG signal quality by showing lower baseline noise and a gradual increase in the signal to noise ratio (SNR). In particular, electrodes, Ø ≥ 20 mm, and Pc ≥ 10 mmHg showed comparable performance to Ag-Ag/Cl electrodes in current textile-based electrodes. The current study emphasizes and discusses design factors that are particularly required in the designing and manufacturing process of smart clothing with SEMG electrodes, especially as an aspect of clothing design.
Investigation of Interface Thermal Resistance between Polymer and Mold Insert in Micro-Injection Molding by Non-Equilibrium Molecular Dynamics
Authors: Weng Can , Li Jiangwei , Lai Jun , Liu Jiangwen , Wang Hao
Published: October 2020

Micro-injection molding has attracted a wide range of research interests to fabricate polymer products with nanostructures for its advantages of cheap and fast production. The heat transfer between the polymer and the mold insert is important to the performance of products. In this study, the interface thermal resistance (ITR) between the polypropylene (PP) layer and the nickel (Ni) mold insert layer in micro-injection molding was studied by using the method of non-equilibrium molecular dynamics (NEMD) simulation. The relationships among the ITR, the temperature, the packing pressure, the interface morphology, and the interface interaction were investigated. The simulation results showed that the ITR decreased obviously with the increase of the temperature, the packing pressure and the interface interaction. Both rectangle and triangle interface morphologies could enhance the heat transfer compared with the smooth interface. Moreover, the ITR of triangle interface was higher than that of rectangle interface. Based on the analysis of phonon density of states (DOS) for PP-Ni system, it was found that the mismatch between the phonon DOS of the PP atoms and Ni atoms was the main cause of the interface resistance. The frequency distribution of phonon DOS also affected the interface resistance.
Exploring the Function of Ion-Exchange Membrane in Membrane Capacitive Deionization via a Fully Coupled Two-Dimensional Process Model
Authors: Zhang Xin , Reible Danny
Published: October 2020

In the arid west, the freshwater supply of many communities is limited, leading to increased interest in tapping brackish water resources. Although reverse osmosis is the most common technology to upgrade saline waters, there is also interest in developing and improving alternative technologies. Here we focus on membrane capacitive deionization (MCDI), which has attracted broad attention as a portable and energy-efficient desalination technology. In this study, a fully coupled two-dimensional MCDI process model capable of capturing transient ion transport and adsorption behaviors was developed to explore the function of the ion-exchange membrane (IEM) and detect MCDI influencing factors via sensitivity analysis. The IEM enhanced desalination by improving the counter-ions’ flux and increased adsorption in electrodes by encouraging retention of ions in electrode macropores. An optimized cycle time was proposed with maximal salt removal efficiency. The usage of the IEM, high applied voltage, and low flow rate were discovered to enhance this maximal salt removal efficiency. IEM properties including water uptake volume fraction, membrane thickness, and fixed charge density had a marginal impact on cycle time and salt removal efficiency within certain limits, while increasing cell length and electrode thickness and decreasing channel thickness and dispersivity significantly improved overall performance.
Assessing the Impact of Water Salinization Stress on Biomass Yield of Cardoon Bio-Energetic Crops through Remote Sensing Techniques
Authors: Borfecchia Flavio , Crinò Paola , Correnti Angelo , Farneti Anna , De Cecco Luigi , Masci Domenica , Blasi Luciano , Iantosca Domenico , Pignatelli Vito , Micheli Carla
Published: October 2020

Various species of cultivated thistle, such as Cynara cardunculus L. (cardoon), exhibit interesting features for industrial biomass production as bioenergy crops, given also their advantageous adaptation capacities to typical Mediterranean climate trends, with noticeable resilience to drought and salinization stresses. The in situ hyperspectral reflectance responses of three genotypes of cardoon plants, irrigated with water at different salinity levels, have been tested for assessing the effects on their biophysical parameters, aiming at improving the biomass yield for bioenergy production, minimizing at same time the environmental impacts and the exploitation of soils and waters resources. The leaf and canopy reflectance hyperspectral signatures, acquired at three different growth stages with biometric measurements, were statistically analyzed (ANOVA, Tukey’s test, graphs), as noise-resilient spectral indices, sensible to different plant features of interest. Their broadband versions, based on the Landsat 8 OLI and Sentinel 2 MSI satellite sensors, were also evaluated in perspective of operative and extensive remote crop monitoring from space. The results highlighted significant differences in some spectral index responses, related to different cardoon genotypes and water salt concentration. The biometric data supported by red-edge indices modelling evidenced the impact of the highest salt water concentration (200 mM/L) on the plant growth and yield.
Finite-Time State Estimation for an Inverted Pendulum under Input-Multiplicative Uncertainty
Authors: Kossery Jayaprakash Anu , Kidambi Krishna Bhavithavya , MacKunis William , Drakunov Sergey V. , Reyhanoglu Mahmut
Published: October 2020

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous analysis of the finite-time state estimator under input-multiplicative parametric uncertainty in addition to a comparative numerical study that quantifies the performance improvement that is achieved by formally incorporating the proposed compensator for input-multiplicative parametric uncertainty in the observer. In summary, our results show performance improvements when applied to both SMC- and LQR-based control systems, with results that include a reduction in the root-mean square error of up to 39% in translational regulation control and a reduction of up to 29% in pendulum angular control.
Using the MODIS Sensor for Snow Cover Modeling and the Assessment of Drought Effects on Snow Cover in a Mountainous Area
Authors: Aghelpour Pouya , Guan Yiqing , Bahrami-Pichaghchi Hadigheh , Mohammadi Babak , Kisi Ozgur , Zhang Danrong
Published: October 2020

Snow is one of the essential factors in hydrology, freshwater resources, irrigation, travel, pastimes, floods, avalanches, and vegetation. In this study, the snow cover of the northern and southern slopes of Alborz Mountains in Iran was investigated by considering two issues: (1) Estimating the snow cover area and the (2) effects of droughts on snow cover. The snow cover data were monitored by images obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The meteorological data (including the precipitation, minimum and maximum temperature, global solar radiation, relative humidity, and wind velocity) were prepared by a combination of National Centers for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR) points and meteorological stations. The data scale was monthly and belonged to the 2000–2014 period. In the first part of the study, snow cover estimation was conducted by Multiple Linear Regression (MLR), Least Square Support Vector Machine (LSSVM), Group Method of Data Handling (GMDH), Multilayer Perceptron (MLP), and MLP with Grey Wolf Optimization (MLP-GWO) models. The most accurate estimations were produced by the MLP-GWO and GMDH models. The models produced better snow cover estimations for the northern slope compared to the southern slope. The GWO improved the MLP’s accuracy by 10.7%. In the second part, seven drought indices, including the Palmer Drought Severity Index (PDSI), Bahlme–Mooley Drought Index (BMDI), Standardized Precipitation Index (SPI), Multivariate Standardized Precipitation Index (MSPI), Modified Standardized Precipitation Index (SPImod), Joint Deficit Index (JDI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were calculated for both slopes. The results showed that the effects of a drought event on the snow cover area would remain up to 5 (or 6) months in the region. The highest impact of drought appears after two months in the snow cover area, and the drought index most related to snow cover variations is the 2–month time window of SPI (SPI2). The results of both subjects were promising and the methods can be examined in other snowy areas of the world.
Ground-based Assessment of Snowfall Detection over Land Using Polarimetric High Frequency Microwave Measurements
Authors: Kongoli Cezar , Meng Huan , Dong Jun , Ferraro Ralph
Published: October 2020

This paper explores the capability of high frequency microwave measurements at vertical and horizontal polarizations in detecting snowfall over land. Surface in-situ meteorological data were collected over Conterminous US during two winter seasons in 2014–2015 and 2015–2016. Statistical analysis of the in-situ data, matched with Global Precipitation Measurement (GPM) Microwave Imager (GMI) measurements on board NASA/JAXA Core Observatory, showed that the polarization difference at 166 GHz had the highest correlation to measured snowfall rate compared to the single channel high frequency measurements and the polarization difference at 89 GHz. A logistic regression model applied to the match-up data, using the polarization difference at 166 and 89 GHz as predictors, yielded an overall snowfall classification rate of 69.0%, with the largest contribution coming from the polarization difference at 166 GHz. Logistic regression using the four single channels as predictors (at 89 and 166 GHz, horizontal and vertical polarizations) further indicated that the horizontal polarization at 166 GHz was the most important contributor. An overall classification rate of 73% was achieved by including the 183.31 ± 3 GHz and 183.31 ± 7 GHz vertical polarization channels in the final logistic regression model. Evaluation of the final algorithm demonstrated skill in snowfall detection of two significant events.
Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application
Authors: Gharehchahi Saeideh , James William H. M. , Bhardwaj Anshuman , Jensen Jennifer L. R. , Sam Lydia , Ballinger Thomas J. , Butler David R.
Published: October 2020

Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in the past and lake formation in the future. This study uses the available information to predict potential sites for future lake formation in the Upper Rhône catchment located in the Southwestern Swiss Alps. The study integrates the latest available glacier outlines and high-quality digital elevation models (DEMs) into the Volume and Topography Automation (VOLTA) model to estimate ice thickness within the extent of the glaciers. Unlike the previous ice thickness models, VOLTA calculates ice thickness distribution based on automatically-derived centerlines, while optimizing the model by including the valley side drag parameter in the force equation. In this study, a total ice volume of 37.17 ± 12.26 km3 (1σ) was estimated for the Upper Rhône catchment. The comparison of VOLTA performance indicates a stronger relationship between measured and predicted bedrock, confirming the less variability in VOLTA’s results (r2 ≈ 0.92) than Glacier Bed Topography (GlabTop) (r2 ≈ 0.82). Overall, the mean percentage of ice thickness error for all measured profiles in the Upper Rhône catchment is around ±22%, of which 28 out of 42 glaciers are underestimated. By incorporating the vertical accuracy of free-ice DEM, we could identify 171 overdeepenings. Among them, 100 sites have a high potential for future lake formation based on four morphological criteria. The visual evaluation of deglaciated areas also supports the robustness of the presented methodology, as 11 water bodies were already formed within the predicted overdeepenings. In the wake of changing global climate, such results highlight the importance of combined datasets and parameters for projecting the future glacial landscapes. The timely information on future glacial lake formation can equip planners with essential knowledge, not only for managing water resources and hazards, but also for understanding glacier dynamics, catchment ecology, and landscape evolution of high-mountain regions.
On the Frequency Sweep Rate Estimation in Airborne FMCW SAR Systems
Authors: Esposito Carmen , Berardino Paolo , Natale Antonio , Perna Stefano
Published: October 2020

Use of Frequency Modulated Continuous Wave (FMCW) Synthetic Aperture Radar (SAR) systems requires to accurately know the electronic parameters of the system. In particular, the use of an incorrect value of the Frequency Sweep Rate (FSR) introduces geometric distortions in the focused images. Recently, a method, that we name FSR Estimate Through Corner reflectors (FSRETC), has been proposed to estimate the FSR value actually employed by the radar. The method is based on the use of the SAR image focused with the available erroneous FSR. Moreover, it exploits a number of Corner Reflectors (CRs) deployed over the illuminated area. In this work, we provide an assessment of the capabilities of the FSRETC algorithm. The overall analysis is performed through the use of a real dataset consisting of 10 acquisitions carried out in 2018 (5 acquisitions) and 2019 (5 acquisitions) with an airborne FMCW SAR system. The presented experimental analysis shows that even with a single acquisition, use of two CRs sufficiently far from each other in the range direction, allows achieving an accurate estimate of the searched FSR. Moreover, it is shown that the obtained estimate is very stable over the time. Therefore, the overall procedure can be applied only once, since the estimated values can be safely used for the subsequent missions, at least for the time interval considered in the work, that is, 14 months. In addition, the presented results pose the basis for an enhanced measurement strategy that allows effective application of the FSRETC algorithm through the use of only one CR.
An Adaptive Network Coding Scheme for Multipath Transmission in Cellular-Based Vehicular Networks
Authors: Yin Chenyang , Dong Ping , Du Xiaojiang , Zheng Tao , Zhang Hongke , Guizani Mohsen
Published: October 2020

With the emergence of vehicular Internet-of-Things (IoT) applications, it is a significant challenge for vehicular IoT systems to obtain higher throughput in vehicle-to-cloud multipath transmission. Network Coding (NC) has been recognized as a promising paradigm for improving vehicular wireless network throughput by reducing packet loss in transmission. However, existing researches on NC do not consider the influence of the rapid quality change of wireless links on NC schemes, which poses a great challenge to dynamically adjust the coding rate according to the variation of link quality in vehicle-to-cloud multipath transmission in order to avoid consuming unnecessary bandwidth resources and to increase network throughput. Therefore, we propose an Adaptive Network Coding (ANC) scheme brought by the novel integration of the Hidden Markov Model (HMM) into the NC scheme to efficiently adjust the coding rate according to the estimated packet loss rate (PLR). The ANC scheme conquers the rapid change of wireless link quality to obtain the utmost throughput and reduce the packet loss in transmission. In terms of the throughput performance, the simulations and real experiment results show that the ANC scheme outperforms state-of-the-art NC schemes for vehicular wireless multipath transmission in vehicular IoT systems.
New Approach of UAV Movement Detection and Characterization Using Advanced Signal Processing Methods Based on UWB Sensing
Authors: Digulescu Angela , Despina-Stoian Cristina , Stănescu Denis , Popescu Florin , Enache Florin , Ioana Cornel , Rădoi Emanuel , Rîncu Iulian , Șerbănescu Alexandru
Published: October 2020

In the last years, the commercial drone/unmanned aerial vehicles market has grown due to their technological performances (provided by the multiple onboard available sensors), low price, and ease of use. Being very attractive for an increasing number of applications, their presence represents a major issue for public or classified areas with a special status, because of the rising number of incidents. Our paper proposes a new approach for the drone movement detection and characterization based on the ultra-wide band (UWB) sensing system and advanced signal processing methods. This approach characterizes the movement of the drone using classical methods such as correlation, envelope detection, time-scale analysis, but also a new method, the recurrence plot analysis. The obtained results are compared in terms of movement map accuracy and required computation time in order to offer a future starting point for the drone intrusion detection.
Environment Monitoring of Rose Crops Greenhouse Based on Autonomous Vehicles with a WSN and Data Analysis
Authors: Rosero-Montalvo Paul D. , Erazo-Chamorro Vanessa C. , López-Batista Vivian F. , Moreno-García María N. , Peluffo-Ordóñez Diego H.
Published: October 2020

This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90% and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.
Development of Insert Condition Classification System for CNC Lathes Using Power Spectral Density Distribution of Accelerometer Vibration Signals
Authors: Huang Yi-Wen , Yeh Syh-Shiuh
Published: October 2020

Insert conditions significantly influence the product quality and manufacturing efficiency of lathe machining. This study used the power spectral density distribution of the vibration signals of a lathe machining accelerometer to design an insert condition classification system applicable to different machining conditions. For four common lathe machining insert conditions (i.e., built-up edge, flank wear, normal, and fracture), herein, the insert condition classification system was established with two stages—insert condition modeling and machining model fusion. In the insert condition modeling stage, the magnitude features of the segmented frequencies were captured according to the power spectral density distributions of the accelerometer vibration signals. Principal component analysis and backpropagation neural networks were used to develop insert condition models for different machining conditions. In the machining model fusion stage, a backpropagation neural network was employed to establish the weight function between the machining conditions and insert condition models. Subsequently, the insert conditions were classified based on the calculated weight values of all the insert condition models. Cutting tests were performed on a computer numerical control (CNC) lathe and utilized to validate the feasibility of the designed insert condition classification system. The results of the cutting tests showed that the designed system could perform insert condition classification under different machining conditions, with a classification rate exceeding 80%. Using a triaxial accelerometer, the designed insert condition classification system could perform identification and classification online for four common insert conditions under different machining conditions, ensuring that CNC lathes could further improve manufacturing quality and efficiency in practice.
NeQuick-G and Android Devices: A Compromise between Computational Burden and Accuracy
Authors: Gioia Ciro , Borio Daniele
Published: October 2020

Ionospheric delay is one of the largest errors affecting Global Navigation Satellite System (GNSS) positioning in open-sky conditions, and different methods are currently available for mitigating ionospheric effects including dual-frequency measurements and corrections from augmentation systems. For single-frequency standalone receivers, the most widely used approach to correct ionospheric delays is to rely on a model. In this respect, Klobuchar and NeQuick-G Ionospheric Correction Algorithms (ICAs) are the approaches adopted by GPS and Galileo, respectively. While the latter outperforms the Klobuchar model, it requires a significantly higher computational load, which can limit its exploitation in some market segments such as smartphones. In order to foster adoption of the NeQuick-G model in this type of device, a smart application of NeQuick-G is proposed. The solution relies on the assumption that ionospheric delays are practically constant over short time intervals. Thus, the update rate of the ionospheric correction computation can be significantly reduced. This solution was implemented, tested, and evaluated using real data collected with a static smartphone in an ad hoc set-up. The impact of reducing the ionospheric correction update rate has been evaluated in terms of processing time, of ionospheric correction deviations and in the Ranging Error (RE) and position domains. The analysis shows that a significant reduction of the processing time can be obtained with negligible degradation of the navigation solution.
Nanostructured SmFeO3 Gas Sensors: Investigation of the Gas Sensing Performance Reproducibility for Colorectal Cancer Screening
Authors: Gaiardo Andrea , Zonta Giulia , Gherardi Sandro , Malagù Cesare , Fabbri Barbara , Valt Matteo , Vanzetti Lia , Landini Nicolò , Casotti Davide , Cruciani Giuseppe , Della Ciana Michele , Guidi Vincenzo
Published: October 2020

Among the various chemoresistive gas sensing properties studied so far, the sensing response reproducibility, i.e., the capability to reproduce a device with the same sensing performance, has been poorly investigated. However, the reproducibility of the gas sensing performance is of fundamental importance for the employment of these devices in on-field applications, and to demonstrate the reliability of the process development. This sensor property became crucial for the preparation of medical diagnostic tools, in which the use of specific chemoresistive gas sensors along with a dedicated algorithm can be used for screening diseases. In this work, the reproducibility of SmFeO3 perovskite-based gas sensors has been investigated. A set of four SmFeO3 devices, obtained from the same screen-printing deposition, have been tested in laboratory with both controlled concentrations of CO and biological fecal samples. The fecal samples tested were employed in the clinical validation protocol of a prototype for non-invasive colorectal cancer prescreening. Sensors showed a high reproducibility degree, with an error lower than 2% of the response value for the test with CO and lower than 6% for fecal samples. Finally, the reproducibility of the SmFeO3 sensor response and recovery times for fecal samples was also evaluated.
Improving Real-Time Position Estimation Using Correlated Noise Models
Authors: Martin Andrew , Parry Matthew , Soundy Andy W. R. , Panckhurst Bradley J. , Brown Phillip , Molteno Timothy C. A. , Schumayer Daniel
Published: October 2020

We provide algorithms for inferring GPS (Global Positioning System) location and for quantifying the uncertainty of this estimate in real time. The algorithms are tested on GPS data from locations in the Southern Hemisphere at four significantly different latitudes. In order to rank the algorithms, we use the so-called log-score rule. The best algorithm uses an Ornstein–Uhlenbeck (OU) noise model and is built on an enhanced Kalman Filter (KF). The noise model is capable of capturing the observed autocorrelated process noise in the altitude, latitude and longitude recordings. This model outperforms a KF that assumes a Gaussian noise model, which under-reports the position uncertainties. We also found that the dilution-of-precision parameters, automatically reported by the GPS receiver at no additional cost, do not help significantly in the uncertainty quantification of the GPS positioning. A non-learning method using the actual position measurements and employing a constant uncertainty does not even converge to the correct position. Inference with the enhanced noise model is suitable for embedded computing and capable of achieving real-time position inference, can quantify uncertainty and be extended to incorporate complementary sensor recordings, e.g., from an accelerometer or from a magnetometer, in order to improve accuracy. The algorithm corresponding to the augmented-state unscented KF method suggests a computational cost of O(dx2dt), where dx is the dimension of the augmented state-vector and dt is an adjustable, design-dependent parameter corresponding to the length of “past values” one wishes to keep for re-evaluation of the model from time to time. The provided algorithm assumes dt=1. Hence, the algorithm is likely to be suitable for sensor fusion applications.
Flood and Contain: An Optimized Repeal-Based Flooding Algorithm for Wireless Ad Hoc and Sensor Networks
Authors: Gomez Javier , Montes-de-Oca Martha , Camacho-Escoto Jose Jaime
Published: October 2020

Flooding is a simple yet reliable way of discovering resources in wireless ad hoc networks such as mobile ad hoc networks (MANETs), ad hoc sensors, and recently, IoT networks. However, its operation is resource-intensive, especially in densely populated networks. Several approaches can be found in the literature to reduce the impact of flooding. Many of these approaches follow a repeal-based operation, chasing and stopping further propagation of flooding packets once the target is found. However, repeal-based protocols might end up transmitting even more packets than the original flooding. This work characterizes a maximum repeal-flooding boundary beyond which it is counterproductive to chase the original flooding. We present the Flood and Contain (F&C) algorithm, a method that can quickly establish the maximum repeal-flooding boundary for each node while making no assumptions on the underlying network. F&C’s packet overhead increases linearly with the hop count up to the maximum repeal-flooding boundary, in which case there is no attempt to chase the original flooding. In this latter case, F&C generates only as many packets as the original flooding. Simulations show that, on average, F&C reduces the total flooding overhead (compared to traditional flooding) up to 35 percent once considering all possible destinations, with only a slight increase in resource discovery latency, and it outperforms all other repeal-based protocols, particularly for longer routes.
Calibration of In-Plane Center Alignment Errors in the Installation of a Circular Slide with Machine-Vision Sensor and a Reflective Marker
Authors: Jeong Hyungjin , Yu Jiwon , Lee Donghun
Published: October 2020

This paper describes a method for calibrating in-plane center alignment error (IPCA) that occurs when installing the circular motion slide (CMS). In this study, by combini ng the moving carriage of the CMS and the planar PKM (parallel kinematic mechanism) with the machine tool, the small workspace of the PKM is expanded, and the workpiece is placed on the table with the CMS installed is processed through the machine tool. However, to rigidly mount the CMS on the table, the preload between the guide and the support bearings must be adjusted with the eccentric bearing, and in this process, the IPCA occurs. After installing a reflective marker on the PKM, the PKM is slowly rotated along with the ring guide in the way of stop-and-go without the PKM’s own motion. Then, using a machine vision camera installed at the top of the CMS, the IPCA, which is the difference between the actual center position and the nominal center position of the CMS with respect to the camera, can be successfully calibrated through the circular fitting process. Consequently, it was confirmed that the IPCA of 0.37 mm can be successfully identified with the proposed method.