bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Flaxseed and Its Components on Mammary Gland MiRNome: Identification of Potential Biomarkers to Prevent Breast Cancer Development
Authors: Taibi Amel , Lin Zhen , Tsao Rong , Thompson Lilian U. , Comelli Elena M.
Published: November 2019

Breast cancer is the most common cancer among women worldwide. We previously showed that early-life exposure to flaxseed (FS) or its components, FS oil (FSO) and secoisolariciresinol diglucoside (SDG), affects the mammary gland (MG) and is associated with the reduction of breast cancer risk during adulthood. However, the underlying mechanisms are not understood. This study aimed to investigate the effect of FS, FSO, and SDG on the MG miRNA signature at a late stage of development. Female C57BL/6 mice, 4–5 weeks of age, were randomized into four groups to receive: (i) basal AIN-93G, (ii) 10% FS, (iii) 3.67% FSO, or (iv) 0.15% SDG. After 21 days, the mice were sacrificed and MG miRNAs were profiled. Diet-specific MG miRNA signatures were identified. Deregulated miRNAs were associated with breast cancer and targeted genes involved in MG development, growth, and cancer. The study allowed for the identification of potential biomarkers or novel therapeutic targets to prevent and/or reduce the risk of breast cancer.
“I Did Not Believe You Could Get Better”—Reversal of Diabetes Risk Through Dietary Changes in Older Persons with Prediabetes in Region Stockholm
Authors: Timm Linda , Daivadanam Meena , Lager Anton , Forsberg Birger , Östenson Claes-Göran , Mölsted Alvesson Helle
Published: November 2019

Diabetes risk can be controlled and even reversed by making dietary changes. The aim of this study was to improve the understanding of how older persons with a high risk of developing Type 2 diabetes manage and relate to information about diabetes risk over a ten-year period. Fifteen qualitative interviews were conducted among participants from the Stockholm Diabetes Prevention Program (SDPP). The participants were asked to recall the health examinations conducted by the SDPP related to their prediabetes and to describe their experiences and potential changes related to diet and physical activity. Data were analyzed using qualitative content analysis. The main theme found was that T2D (type 2 diabetes) risk is not perceived as concrete enough to motivate lifestyle modifications, such as changing dietary patterns, without other external triggers. Diagnosis was recognized as a reason to modify diet, and social interactions were found to be important for managing behavior change. Diagnosis was also a contributing factor to lifestyle modification, while prognosis of risk was not associated with efforts to change habits. The results from this study suggest that the potential of reversing prediabetes needs to be highlighted and more clearly defined for older persons to serve as motivators for lifestyle modification.
Correction: Wilk et al. “The Effects of High Doses of Caffeine on Maximal Strength and Muscular Endurance in Athletes Habituated to Caffeine” Nutrients, 2019, 11(8), 1912
Authors: Wilk Michal , Krzysztofik Michal , Filip Aleksandra , Zajac Adam , Del Coso Juan
Published: November 2019

The authors wish to make a correction to the published version of their paper [...]
The Effect of Caffeine on the Velocity of Half-Squat Exercise during the Menstrual Cycle: A Randomized Controlled Trial
Authors: Romero-Moraleda Blanca , Del Coso Juan , Gutiérrez-Hellín Jorge , Lara Beatriz
Published: November 2019

Recent literature confirms the ergogenic effect of acute caffeine intake to increase muscle strength and power in men. However, the information about the effect of caffeine on muscle performance in women is uncertain and it is unknown whether its ergogenicity is similar during the menstrual cycle. The goal of this investigation was to assess the effect of acute caffeine intake on mean and peak velocity of half-squat exercise during three different phases of the menstrual cycle. Thirteen trained eumenorrheic athletes (age = 31 ± 6 years; body mass = 58.6 ± 7.8 kg) participated in a double-blind, crossover and randomized experimental trial. In the early follicular (EFP), late follicular (LFP) and mid luteal phases (MLP), participants either ingested a placebo (cellulose) or 3 mg/kg/bm of caffeine in an opaque and unidentifiable capsule. In each trial, participants performed a half-squat exercise at maximal velocity with loads equivalent to 20%, 40% 60% and 80% of one repetition maximum (1RM). In each load, mean and peak velocity were measured during the concentric phase of the exercise using a rotatory encoder. In comparison to the placebo, a two-way ANOVA showed that the ingestion of 3 mg/kg/bm of caffeine increased mean velocity at 60% 1RM in EFP (Δ = 1.4 ± 2.7%, p = 0.04; ES: 0.2 ± 0.2) and LFP (Δ = 5.0 ± 10.4%, p = 0.04; ES: 0.3 ± 0.4). No other statistical differences were found for the caffeine-placebo comparison for mean velocity, but caffeine induced an ergogenic effect of small magnitude in all of the menstrual cycle phases. These results suggest that the acute intake of 3 mg/kg/bm of caffeine induces a small effect to increase movement velocity during resistance exercise in eumenorrheic female athletes. The positive effect of caffeine was of similar magnitude in all the three phases of the menstrual cycle.
Metagenomic Analysis of Infectious F-Specific RNA Bacteriophage Strains in Wastewater Treatment and Disinfection Processes
Authors: Lee Suntae , Suwa Mamoru , Shigemura Hiroyuki
Published: November 2019

F-specific RNA bacteriophages (FRNAPHs) can be used to indicate water contamination and the fate of viruses in wastewater treatment plants (WWTPs). However, the occurrence of FRNAPH strains in WWTPs is relatively unknown, whereas FRNAPH genotypes (GI–GIV) are well documented. This study investigated the diversity of infectious FRNAPH strains in wastewater treatment and disinfection processes using cell culture combined with next-generation sequencing (integrated culture–NGS (IC–NGS)). A total of 32 infectious strains belonging to FRNAPH GI (nine strains), GI-JS (two strains), GII (nine strains), GIII (seven strains), and GIV (five strains) were detected in wastewater samples. The strains of FRNAPH GI and GII exhibited greater resistance to wastewater treatment than those of GIII. The IC–NGS results in the disinfected samples successfully reflected the infectivity of FRNAPHs by evaluating the relationship between IC–NGS results and the integrated culture–reverse-transcription polymerase chain reaction combined with the most probable number assay, which can detect infectious FRNAPH genotypes. The diversity of infectious FRNAPH strains in the disinfected samples indicates that certain strains are more resistant to chlorine (DL52, GI-JS; T72, GII) and ultraviolet (T72, GII) disinfection. It is possible that investigating these disinfectant-resistant strains could reveal effective mechanisms of viral disinfection.
Clinical Course of Opportunistic Infections—Toxoplasmosis and Cytomegalovirus Infection in HIV-Infected Patients in Slovakia
Authors: Šimeková Katarína , Nováková Elena , Rosoľanka Róbert , Masná Jana , Antolová Daniela
Published: November 2019

The HIV/acquired immunodeficiency syndrome (AIDS) pandemic has affected the health status of the population in many countries. Early symptomatic HIV infection includes persistent generalized lymphadenopathy (PGL), which can be associated with opportunistic infections, e.g., toxoplasmosis and Cytomegalovirus (CMV) infection. This study followed the occurrence of PGL, toxoplasmosis, and Cytomegalovirus infection in 32 HIV-positive patients and analyzed the clinical signs of disease in relation to the number of CD4 T lymphocytes. In monitored patients, the average number of CD4 T lymphocytes was 940.8 ± 396.7/µL of blood. Severe immunodeficiency was recorded in four persons, who also suffered from colitis and/or retinitis and pneumonitis. The number of CD4 T cells in patients with PGL was significantly lower than that in patients without lymphadenopathy. In 6 (18.8%) IgM and 11 (34.4%) IgG Toxoplasma gondii seropositive patients, the number of CD4 T lymphocytes was significantly lower than that in seronegative patients. The presence of IgM and IgG antibodies to Cytomegalovirus was recorded in all examined patients, and CMV infection clinically manifested in five persons. The occurrence of PGL, the higher viral load, and seropositivity to T. gondii were significantly related to decline in the CD4 T lymphocyte number. The clinical course of the diseases was influenced by the status of the patient’s immunodeficiency and suggests ongoing immunosuppression and possible reactivation of both infections in all patients.
Synthesis, Characterization, and Three-Dimensional Structure Generation of Zinc Oxide-Based Nanomedicine for Biomedical Applications
Authors: Jin Su-Eon , Jin Hyo-Eon
Published: November 2019

Zinc oxide (ZnO) nanoparticles have been studied as metal-based drugs that may be used for biomedical applications due to the fact of their biocompatibility. Their physicochemical properties, which depend on synthesis techniques involving physical, chemical, biological, and microfluidic reactor methods affect biological activity in vitro and in vivo. Advanced tool-based physicochemical characterization is required to identify the biological and toxicological effects of ZnO nanoparticles. These nanoparticles have variable morphologies and can be molded into three-dimensional structures to enhance their performance. Zinc oxide nanoparticles have shown therapeutic activity against cancer, diabetes, microbial infection, and inflammation. They have also shown the potential to aid in wound healing and can be used for imaging tools and sensors. In this review, we discuss the synthesis techniques, physicochemical characteristics, evaluation tools, techniques used to generate three-dimensional structures, and the various biomedical applications of ZnO nanoparticles.
Opportunities for Successful Stabilization of Poor Glass-Forming Drugs: A Stability-Based Comparison of Mesoporous Silica Versus Hot Melt Extrusion Technologies
Authors: Ditzinger Felix , Price Daniel J. , Nair Anita , Becker-Baldus Johanna , Glaubitz Clemens , Dressman Jennifer B. , Saal Christoph , Kuentz Martin
Published: November 2019

Amorphous formulation technologies to improve oral absorption of poorly soluble active pharmaceutical ingredients (APIs) have become increasingly prevalent. Currently, polymer-based amorphous formulations manufactured by spray drying, hot melt extrusion (HME), or co-precipitation are most common. However, these technologies have challenges in terms of the successful stabilization of poor glass former compounds in the amorphous form. An alternative approach is mesoporous silica, which stabilizes APIs in non-crystalline form via molecular adsorption inside nano-scale pores. In line with these considerations, two poor glass formers, haloperidol and carbamazepine, were formulated as polymer-based solid dispersion via HME and with mesoporous silica, and their stability was compared under accelerated conditions. Changes were monitored over three months with respect to solid-state form and dissolution. The results were supported by solid-state nuclear magnetic resonance spectroscopy (SS-NMR) and scanning electron microscopy (SEM). It was demonstrated that mesoporous silica was more successful than HME in the stabilization of the selected poor glass formers. While both drugs remained non-crystalline during the study using mesoporous silica, polymer-based HME formulations showed recrystallization after one week. Thus, mesoporous silica represents an attractive technology to extend the formulation toolbox to poorly soluble poor glass formers.
Kinetics and Chemorheological Analysis of Cross-Linking Reactions in Humins
Authors: Sangregorio Anna , Guigo Nathanaël , Jong Ed de , Sbirrazzuoli Nicolas
Published: November 2019

Humins is a biomass-derived material, co-product of the acid-catalyzed conversion of cellulose and hemicellulose to platform chemicals. This work presents a thorough study concerning the crosslinking kinetics of humins by chemorheological analysis and model-free kinetics under isothermal and non-isothermal curing. Humins can auto-crosslink under the effect of temperature, and the reaction can be fastener when adding an acidic initiator. Thus, the effect of P-Toluenesulfonic acid monohydrate (pTSA) on the crosslinking kinetics was also studied. The dependencies of the effective activation energy (Eα-dependencies) were determined by an advanced isoconversional method and correlated with the variation of complex viscosity during curing. It is shown that humins curing involves multi-step complex reactions and that the use of an acidic initiator allows faster crosslinking at lower temperatures, involving lower Eα. The shift from chemical to diffusion control was also estimated.
Friction and Wear Behavior of Polyimide Composites Reinforced by Surface-Modified Poly-p-Phenylenebenzobisoxazole (PBO) Fibers in High Ambient Temperatures
Authors: Yu Liang , Zhang Yuanjie , Tang Jiaming , Gao Jicheng
Published: November 2019

(1) In order to improve the properties of antifriction and wear resistance of polyimide (PI) composite under high temperature conditions, (2) 3-Aminopropyltriethoxysilane (APTES) and Lanthanum (La) salt modifications were employed to manufacture poly-p-phenylenebenzobisoxazole (PBO)/PI composites with different interface properties. The representative ambient temperatures of 130 and 260 °C were chosen to study the friction and wear behavior of composites with different interface properties. (3) Results revealed that while both modification methods can improve the chemical activity of the surface of PBO fibers, the La salt modification is more effective. The friction coefficient of all composites decreases with the increase of sliding velocity and load at two temperatures, and the specific wear rate is increases. Contrary to the situation in the 130 °C environment, the wear resistance of the unmodified composite in the 260 °C environment is greatly affected by the sliding velocity and load, while the modified composites are less affected. Under the same test parameters, the PBO–La/PI composite has the lowest specific wear rate and friction coefficient, and (4) La salt modification is a more effective approach to improve the properties of antifriction and wear resistance of PI composite than APTES modification in high ambient temperatures.
Crosslinking of Electrospun Fibres from Unsaturated Polyesters by Bis-Triazolinediones (TAD)
Authors: Chiaradia Viviane , Hanay Saltuk B. , Kimmins Scott D. , Oliveira Débora de , Araújo Pedro H. H. , Sayer Claudia , Heise Andreas
Published: November 2019

Crosslinking of an unsaturated aliphatic polyester poly(globalide) (PGl) by bistriazolinediones (bisTADs) is reported. First, a monofunctional model compound, phenyl–TAD (PTAD), was tested for PGl functionalisation. 1H-NMR showed that PTAD–ene reaction was highly efficient with conversions up to 97%. Subsequently, hexamethylene bisTAD (HM–bisTAD) and methylene diphenyl bisTAD (MDP–bisTAD) were used to crosslink electrospun PGl fibres via one- and two-step approaches. In the one-step approach, PGl fibres were collected in a bisTAD solution for in situ crosslinking, which resulted in incomplete crosslinking. In the two-step approach, a light crosslinking of fibres was first achieved in a PGl non-solvent. Subsequent incubation in a fibre swelling bisTAD solution resulted in fully amorphous crosslinked fibres. SEM analysis revealed that the fibres’ morphology was uncompromised by the crosslinking. A significant increase of tensile strength from 0.3 ± 0.08 MPa to 2.7 ± 0.8 MPa and 3.9 ± 0.5 MPa was observed when PGI fibres were crosslinked by HM–bisTAD and MDP–bisTAD, respectively. The reported methodology allows the design of electrospun fibres from biocompatible polyesters and the modulation of their mechanical and thermal properties. It also opens future opportunities for drug delivery applications by selected drug loading.
Synthesis, Characterization, and the Antioxidant Activity of Carboxymethyl Chitosan Derivatives Containing Thiourea Salts
Authors: Sun Xueqi , Zhang Jingjing , Chen Yuan , Mi Yingqi , Tan Wenqiang , Li Qing , Dong Fang , Guo Zhanyong
Published: November 2019

A new class of chitosan derivatives possessing thiourea salts were synthesized to improve the solubility and the antioxidant activity of chitosan. Firstly, chitosan was modified to carboxymethyl chitosan, combining carboxymethyl chitosan with thiourea salts that have different structures to form new chitosan derivatives. The chitosan and chitosan derivatives were characterized by FT-IR, 13C NMR, TGA, and elemental analyses. The new peaks of thiourea salts could be clearly observed at about 1240 cm–1 in the IR spectra, and the peak of C=S was clearly observed at around 180 ppm in the 13C NMR. IR spectra and 13C NMR of the structural units of these polymers validated the chitosan derivatives possessing thiourea salts were successfully synthesized. Their antioxidant properties were tested, including DPPH-radical scavenging ability, superoxide-radical scavenging ability, and hydroxyl-radical scavenging ability. Our results suggested the increase of thiourea salt groups in chitosan derivatives promotes the scavenging effect. The scavenging activity of 4TMCMCS, TMCMCS. 4,4DCMCS, and 4ACMCS against DPPH-radical and superoxide-radical were more than 90% at 1.6 mg/mL, respectively. In the cytotoxicity assay, no cytotoxicity was observed for the L929 cells with chitosan and its derivatives at all testing concentrations. These results demonstrated that the combination of chitosan and thiourea salt groups improved the antioxidant activity of chitosan, and the antioxidants or free radical scavengers based on natural polymers and thiourea salts showed potential applications.
Nanofibrillar Green Composites of Polylactide/Polyhydroxyalkanoate Produced in Situ Due to Shear Induced Crystallization
Authors: Vozniak Iurii , Hosseinnezhad Ramin , Morawiec Jerzy , Galeski Andrzej
Published: November 2019

This study addresses the new concept of in situ inducing fibrillar morphology (micro or nanofibrils) of a minority component based on the simultaneous occurrence of orientation and shear induced crystallization of polymer fibers directly at the stage of extrusion in a single step. This possibility is demonstrated by using two entirely bio-sourced polymers: polylactide (PLA) and polyhydroxyalkanoate (PHA) as components. The shear induced crystallization allowed crystallization of PHA nanofibers immediately after applying high shear rate and elongation strain, avoiding subsequent cooling to initiate crystallization. Shearing of PHA increased non-isothermal crystallization temperature by 50 °C and decreased the temperature range in which the transition from a molten state to a crystallized one occurs by 17 °C. SEM observations demonstrate the successful transformation of the dispersed PHA phase into nanofibrils with diameters of nearly 200 nm. The transition from the droplets of PHA to fibers causes the brittle-to-ductile transition of the PLA matrix at a low concentration of PHA and contributes to the simultaneous increase of its rigidity and strength.
The Fast Potential Evaluation Method of Enhanced Oil Recovery Based on Statistical Analysis
Authors: Wang Zhengbo , Wang Qiang , Ma Desheng , Zhao Wanchun , Feng Xiaohan , Liu Zhaoxia
Published: November 2019

Based on a large number of empirical statistics of tertiary oil recovery technology in China, including polymer flooding, chemical flooding, gas flooding, in situ combustion, steam flooding, ect., 22 key reservoir parameters were filterized. Five levels of quantitative screening criteria were developed for different tertiary oil recovery methods. The mean algorithm for the downward approximation and the grey correlation theory were used in this paper to quickly select the appropriate tertiary oil recovery method for the target blocks, which provides a preferred development method for subsequent potential evaluation. In the rapid analogy evaluation method of tertiary oil recovery potential, the total similarity ratio between the target block and the example block is determined. The target block is matched with the appropriate instance block according to the total similarity ratio value, using 80% as the boundary. The ratio of the geological reserves is used to predict the oil recovery interval, the actual annual injection data, and the economic profit, thus quickly predicting the economic potential of the tertiary oil recovery technology in the target block. Currently, our research team has integrated these two methods into the tertiary oil production potential evaluation software EORSYS3.0. The empirical analysis shows that this method is reasonable and the conclusion is reliable. In addition, the actual enhanced recovery value is within the effective range predicted by the method. The method and results of this paper will provide an important decision-making reference for the application and sustainable development of China Petroleum’s main tertiary oil recovery technology in the next 5–10 years.
Numerical Simulations of Polymer Solution Droplet Impact on Surfaces of Different Wettabilities
Authors: Tembely Moussa , Vadillo Damien , Soucemarianadin Arthur , Dolatabadi Ali
Published: November 2019

This paper presents a physically based numerical model to simulate droplet impact, spreading, and eventually rebound of a viscoelastic droplet. The simulations were based on the volume of fluid (VOF) method in conjunction with a dynamic contact model accounting for the hysteresis between droplet and substrate. The non-Newtonian nature of the fluid was handled using FENE-CR constitutive equations which model a polymeric fluid based on its rheological properties. A comparative simulation was carried out between a Newtonian solvent and a viscoelastic dilute polymer solution droplet. Droplet impact analysis was performed on hydrophilic and superhydrophobic substrates, both exhibiting contact angle hysteresis. The effect of substrates’ wettability on droplet impact dynamics was determined the evolution of the spreading diameter. While the kinematic phase of droplet spreading seemed to be independent of both the substrate and fluid rheology, the recoiling phase seemed highly influenced by those operating parameters. Furthermore, our results implied a critical polymer concentration in solution, between 0.25 and 2.5% of polystyrene (PS), above which droplet rebound from a superhydrophobic substrate could be curbed. The present model could be of particular interest for optimized 2D/3D printing of complex fluids.
Optimization of Enzyme-Assisted Extraction of Flavonoids from Corn Husks
Authors: Zuorro Antonio , Lavecchia Roberto , González-Delgado Ángel Darío , García-Martinez Janet Bibiana , L’Abbate Pasqua
Published: November 2019

Corn husks are an important byproduct of the corn processing industry. Although they are a rich source of bioactive compounds, especially flavonoids, corn husks are usually disposed of or used as animal feed. In this paper, we investigate their recovery by an enzyme-assisted extraction process consisting of a pretreatment of the plant material with cellulase followed by solvent extraction with aqueous ethanol. A four-factor, three-level Box–Behnken design combined with the response surface methodology was used to optimize the enzyme dosage (0.3–0.5 g/100 g), incubation time (1.5–2.5 h), liquid-to-solid ratio (30–40 mL g−1) and ethanol concentration in the solvent (60–80% v/v). Under the optimal conditions, about 1.3 g of total flavonoids per 100 g of dry waste were recovered. A statistical analysis of the results was performed to provide a quantitative estimation of the influence of the four factors, alone or in combination, on the extraction yields. Overall, the results from this study indicate that corn husks are a valuable source of flavonoids and that they can be easily recovered by a sustainable and environmentally friendly extraction process.
Pixel Tracking to Estimate Rivers Water Flow Elevation Using Cosmo-SkyMed Synthetic Aperture Radar Data
Authors: Biondi Filippo , Tarpanelli Angelica , Addabbo Pia , Clemente Carmine , Orlando Danilo
Published: November 2019

The lack of availability of historical and reliable river water level information is an issue that can be overcome through the exploitation of modern satellite remote sensing systems. This research has the objective of contributing in solving the information-gap problem of river flow monitoring through a synthetic aperture radar (SAR) signal processing technique that has the capability to perform water flow elevation estimation. This paper proposes the application of a new method for the design of a robust procedure to track over the time double-bounce reflections from bridges crossing rivers to measure the gap space existing between the river surface and bridges. Specifically, the difference in position between the single and double bounce is suitably measured over the time. Simulated and satellite temporal series of SAR data from COSMO-SkyMed data are compared to the ground measurements recorded for three gauges sites over the Po and Tiber Rivers, Italy. The obtained performance indices confirm the effectiveness of the method in the estimation of water level also in narrow or ungauged rivers.
The Seamless Solar Radiation (SESORA) Forecast for Solar Surface Irradiance—Method and Validation
Authors: Urbich Isabel , Bendix Jörg , Müller Richard
Published: November 2019

Due to the integration of fluctuating weather-dependent energy sources into the grid, the importance of weather and power forecasts grows constantly. This paper describes the implementation of a short-term forecast of solar surface irradiance named SESORA (seamless solar radiation). It is based on the the optical flow of effective cloud albedo and available for Germany and parts of Europe. After the clouds are shifted by applying cloud motion vectors, solar radiation is calculated with SPECMAGIC NOW (Spectrally Resolved Mesoscale Atmospheric Global Irradiance Code), which computes the global irradiation spectrally resolved from satellite imagery. Due to the high spatial and temporal resolution of satellite measurements, solar radiation can be forecasted from 15 min up to 4 h or more with a spatial resolution of 0.05 ∘ . An extensive validation of this short-term forecast is presented in this study containing two different validations based on either area or stations. The results are very promising as the mean RMSE (Root Mean Square Error) of this study equals 59 W/m 2 (absolute bias = 42 W/m 2 ) after 15 min, reaches its maximum of 142 W/m 2 (absolute bias = 97 W/m 2 ) after 165 min, and slowly decreases after that due to the setting of the sun. After a brief description of the method itself and the method of the validation the results will be presented and discussed.
Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)
Authors: Arabameri Alireza , Cerda Artemi , Rodrigo-Comino Jesús , Pradhan Biswajeet , Sohrabi Masoud , Blaschke Thomas , Tien Bui Dieu
Published: November 2019

Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we tested the efficiency of the index of entropy (IoE), the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and their combination. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion. Firstly, a gully erosion inventory map (GEIM) with 206 gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data). Fifteen gully-related conditioning factors (GRCFs) including elevation, slope, aspect, plan curvature, stream power index, topographical wetness index, rainfall, soil type, drainage density, distance to river, distance to road, distance to fault, lithology, land use/land cover, and soil type, were used for modeling. The advanced land observing satellite (ALOS) digital elevation model with a spatial resolution of 30 m was used for the extraction of the above-mentioned topographic factors. The tolerance (TOL) and variance inflation factor (VIF) were also included for checking the multicollinearity among the GRCFs. Based on IoE, we concluded that soil type, lithology, and elevation were the most significant in terms of gully formation. Validation results using the area under the receiver operating characteristic curve (AUROC) showed that IoE (0.941) reached a higher prediction accuracy than VIKOR (0.857) and VIKOR-IoE (0.868). Based on our results, the combination of statistical (IoE) models along with remote sensing and GIS can convert the multi-criteria decision-making (MCDM) models into efficient and powerful tools for gully erosion prediction. We strongly suggest that decision-makers and managers should use these kinds of results to develop more consistent solutions to achieve sustainable development on degraded lands such as in the Semnan province.
A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest
Authors: Carvajal-Ramírez Fernando , Serrano João Manuel Pereira Ramalho , Agüera-Vega Francisco , Martínez-Carricondo Patricio
Published: November 2019

Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way.
Automated Detection of Conifer Seedlings in Drone Imagery Using Convolutional Neural Networks
Authors: Fromm Michael , Schubert Matthias , Castilla Guillermo , Linke Julia , McDermid Greg
Published: November 2019

Monitoring tree regeneration in forest areas disturbed by resource extraction is a requirement for sustainably managing the boreal forest of Alberta, Canada. Small remotely piloted aircraft systems (sRPAS, a.k.a. drones) have the potential to decrease the cost of field surveys drastically, but produce large quantities of data that will require specialized processing techniques. In this study, we explored the possibility of using convolutional neural networks (CNNs) on this data for automatically detecting conifer seedlings along recovering seismic lines: a common legacy footprint from oil and gas exploration. We assessed three different CNN architectures, of which faster region-CNN (R-CNN) performed best (mean average precision 81%). Furthermore, we evaluated the effects of training-set size, season, seedling size, and spatial resolution on the detection performance. Our results indicate that drone imagery analyzed by artificial intelligence can be used to detect conifer seedling in regenerating sites with high accuracy, which increases with the size in pixels of the seedlings. By using a pre-trained network, the size of the training dataset can be reduced to a couple hundred seedlings without any significant loss of accuracy. Furthermore, we show that combining data from different seasons yields the best results. The proposed method is a first step towards automated monitoring of forest restoration/regeneration.
Attention Graph Convolution Network for Image Segmentation in Big SAR Imagery Data
Authors: Ma Fei , Gao Fei , Sun Jinping , Zhou Huiyu , Hussain Amir
Published: November 2019

The recent emergence of high-resolution Synthetic Aperture Radar (SAR) images leads to massive amounts of data. In order to segment these big remotely sensed data in an acceptable time frame, more and more segmentation algorithms based on deep learning attempt to take superpixels as processing units. However, the over-segmented images become non-Euclidean structure data that traditional deep Convolutional Neural Networks (CNN) cannot directly process. Here, we propose a novel Attention Graph Convolution Network (AGCN) to perform superpixel-wise segmentation in big SAR imagery data. AGCN consists of an attention mechanism layer and Graph Convolution Networks (GCN). GCN can operate on graph-structure data by generalizing convolutions to the graph domain and have been successfully applied in tasks such as node classification. The attention mechanism layer is introduced to guide the graph convolution layers to focus on the most relevant nodes in order to make decisions by specifying different coefficients to different nodes in a neighbourhood. The attention layer is located before the convolution layers, and noisy information from the neighbouring nodes has less negative influence on the attention coefficients. Quantified experiments on two airborne SAR image datasets prove that the proposed method outperforms the other state-of-the-art segmentation approaches. Its computation time is also far less than the current mainstream pixel-level semantic segmentation networks.
Functionalized Electrospun Nanofibers as Colorimetric Sensory Probe for Mercury Detection: A Review
Authors: Balusamy Brabu , Senthamizhan Anitha , Uyar Tamer
Published: November 2019

Mercury is considered the most hazardous pollutant of aquatic resources; it exerts numerous adverse effects on environmental and human health. To date, significant progress has been made in employing a variety of nanomaterials for the colorimetric detection of mercury ions. Electrospun nanofibers exhibit several beneficial features, including a large surface area, porous nature, and easy functionalization; thus, providing several opportunities to encapsulate a variety of functional materials for sensing applications with enhanced sensitivity and selectivity, and a fast response. In this review, several examples of electrospun nanofiber-based sensing platforms devised by utilizing the two foremost approaches, namely, direct incorporation and surface decoration envisioned for detection of mercury ions are provided. We believe these examples provide sufficient evidence for the potential use and progress of electrospun nanofibers toward colorimetric sensing of mercury ions. Furthermore, the summary of the review is focused on providing an insight into the future directions of designing electrospun nanofiber-based, metal ion colorimetric sensors for practical applications.
An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease
Authors: Albani Giovanni , Ferraris Claudia , Nerino Roberto , Chimienti Antonio , Pettiti Giuseppe , Parisi Federico , Ferrari Gianluigi , Cau Nicola , Cimolin Veronica , Azzaro Corrado , Priano Lorenzo , Mauro Alessandro
Published: November 2019

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.
HYBRID: Ambulatory Robotic Gait Trainer with Movement Induction and Partial Weight Support
Authors: Urendes Eloy , Asín-Prieto Guillermo , Ceres Ramón , García-Carmona Rodrigo , Raya Rafael , L. Pons José
Published: November 2019

Robotic exoskeletons that induce leg movement have proven effective for lower body rehabilitation, but current solutions offer limited gait patterns, lack stabilization, and do not properly stimulate the proprioceptive and balance systems (since the patient remains in place). Partial body weight support (PBWS) systems unload part of the patient’s body weight during rehabilitation, improving the locomotive capabilities and minimizing the muscular effort. HYBRID is a complete system that combines a 6DoF lower body exoskeleton (H1) with a PBWS system (REMOVI) to produce a solution apt for clinical practice that offers improves on existing devices, moves with the patient, offers a gait cycle extracted from the kinematic analysis of healthy users, records the session data, and can easily transfer the patient from a wheelchair to standing position. This system was developed with input from therapists, and its response times have been measured to ensure it works swiftly and without a perceptible delay.
A Study on the Gaze Range Calculation Method During an Actual Car Driving Using Eyeball Angle and Head Angle Information
Authors: Sakurai Keiko , Tamura Hiroki
Published: November 2019

Car operation requires advanced brain function. Currently, evaluation of the motor vehicle driving ability of people with higher brain dysfunction is medically unknown and there are few evaluation criteria. The increase in accidents by elderly drivers is a social problem in Japan, and a method to evaluate whether elderly people can drive a car is needed. Under these circumstances, a system to evaluate brain dysfunction and driving ability of elderly people is needed. Gaze estimation research is a rapidly developing field. In this paper, we propose the gaze calculation method by eye and head angles. We used the eye tracking device (TalkEyeLite) made by Takei Scientific Instruments Cooperation. For our image processing technique, we estimated the head angle using the template matching method. By using the eye tracking device and the head angle estimate, we built a system that can be used during actual on-road car operation. In order to evaluate our proposed method, we tested the system on Japanese drivers during on-road driving evaluations at a driving school. The subjects were one instructor of the car driving school and eight general drivers (three 40–50 years old and five people over 60 years old). We compared the gaze range of the eight general subjects and the instructor. As a result, we confirmed that one male in his 40s and one elderly driver had narrower gaze ranges.
Investigations of Different Ion Intercalations on the Performance of FBG Hydrogen Sensors Based on Pt/MoO3
Authors: Wang Gaopeng , Yang Shiwen , Dai Jixiang , Dai Yutang , Zou Tong , Roths Johannes , Yang Minghong
Published: November 2019

α-MoO3 has been used as a hydrogen sensing material due to its excellent properties and unique crystalline layer structure. However, the low repeatability of α-MoO3 based hydrogen sensor restricts its practical application. In this paper, the effect of intercalated ion species and the amount in α-MoO3 is experimentally investigated and discussed. It is concluded that the repeatability of the sensor depends on the radius of intercalated ions and amount of ionic bonds. The optimal ion species is Na+ and the optimal amount of precursor is 1 mmol.
Porous Silicon Optical Biosensors: Still a Promise or a Failure?
Authors: De Stefano Luca
Published: November 2019

Even if the first published article on a porous silicon (PSi)-based biosensor dates back to more than twenty years ago, this technology still attracts great attention from many research groups around the world. In this brief review, the pros and cons of porous silicon-based optical biosensors will be highlighted on the basis of some recent results and published papers on this subject. The aim of the paper is to give a straightforward introduction to PhD students and young researchers on this subject, which is particularly full of educative content, since it is highly multidisciplinary. Fabrication of PSi-based optical biosensors requires competencies related to many different scientific topics ranging from material science, physics and optics to healthcare and environmental monitoring through surface chemistry and more.
Detecting IoT User Behavior and Sensitive Information in Encrypted IoT-App Traffic
Authors: Subahi Alanoud , Theodorakopoulos George
Published: November 2019

Many people use smart-home devices, also known as the Internet of Things (IoT), in their daily lives. Most IoT devices come with a companion mobile application that users need to install on their smartphone or tablet to control, configure, and interface with the IoT device. IoT devices send information about their users from their app directly to the IoT manufacturer’s cloud; we call this the ”app-to-cloud way”. In this research, we invent a tool called IoT-app privacy inspector that can automatically infer the following from the IoT network traffic: the packet that reveals user interaction type with the IoT device via its app (e.g., login), the packets that carry sensitive Personal Identifiable Information (PII), the content type of such sensitive information (e.g., user’s location). We use Random Forest classifier as a supervised machine learning algorithm to extract features from network traffic. To train and test the three different multi-class classifiers, we collect and label network traffic from different IoT devices via their apps. We obtain the following classification accuracy values for the three aforementioned types of information: 99.4%, 99.8%, and 99.8%. This tool can help IoT users take an active role in protecting their privacy.
A Comprehensive Review of Microfluidic Water Quality Monitoring Sensors
Authors: Jaywant Swapna A. , Arif Khalid Mahmood
Published: November 2019

Water crisis is a global issue due to water contamination and extremely restricted sources of fresh water. Water contamination induces severe diseases which put human lives at risk. Hence, water quality monitoring has become a prime activity worldwide. The available monitoring procedures are inadequate as most of them require expensive instrumentation, longer processing time, tedious processes, and skilled lab technicians. Therefore, a portable, sensitive, and selective sensor with in situ and continuous water quality monitoring is the current necessity. In this context, microfluidics is the promising technology to fulfill this need due to its advantages such as faster reaction times, better process control, reduced waste generation, system compactness and parallelization, reduced cost, and disposability. This paper presents a review on the latest enhancements of microfluidic-based electrochemical and optical sensors for water quality monitoring and discusses the relative merits and shortcomings of the methods.
Crack Detection on a Retaining Wall with an Innovative, Ensemble Learning Method in a Dynamic Imaging System
Authors: Lin Chern-Sheng , Chen Shih-Hua , Chang Che-Ming , Shen Tsu-Wang
Published: November 2019

In this study, an innovative, ensemble learning method in a dynamic imaging system of an unmanned vehicle is presented. The feasibility of the system was tested in the crack detection of a retaining wall in a climbing area or a mountain road. The unmanned vehicle can provide a lightweight and remote cruise routine with a Geographic Information System sensor, a Gyro sensor, and a charge-coupled device camera. The crack was the target to be tested, and the retaining wall was patrolled through the drone flight path setting, and then the horizontal image was instantly returned by using the wireless transmission of the system. That is based on the cascade classifier, and the feature comparison classifier was designed further, and then the machine vision correlation algorithm was used to analyze the target type information. First, the system collects the target image and background to establish the samples database, and then uses the Local Binary Patterns feature extraction algorithm to extract the feature values for classification. When the first stage classification is completed, the classification results are target features, and edge feature comparisons. The innovative ensemble learning classifier was used to analyze the image and determine the location of the crack for risk assessment.