bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Chènevotte, a Valuable Co-Product of Industrial Hemp Fiber, as Adsorbent for Pollutant Removal. Part I: Chemical, Microscopic, Spectroscopic and Thermogravimetric Characterization of Raw and Modified Samples
Authors: Mongioví Chiara , Lacalamita Dario , Morin-Crini Nadia , Gabrion Xavier , Ivanovska Aleksandra , Sala Federico , Placet Vincent , Rizzi Vito , Gubitosa Jennifer , Mesto Ernesto , Ribeiro Ana Rita Lado , Fini Paola , Vietro Nicoletta De , Schingaro Emanuela , Kostić Mirjana , Cosentino Cesare , Cosma Pinalysa , Bradu Corina , Chanet Gilles , Crini Grégorio
Published: July 2021

FINEAU (2021–2024) is a trans-disciplinary research project involving French, Serbian, Italian, Portuguese and Romanian colleagues, a French agricultural cooperative and two surface-treatment industries, intending to propose chènevotte, a co-product of the hemp industry, as an adsorbent for the removal of pollutants from polycontaminated wastewater. The first objective of FINEAU was to prepare and characterize chènevotte-based materials. In this study, the impact of water washing and treatments (KOH, Na2CO3 and H3PO4) on the composition and structure of chènevotte (also called hemp shives) was evaluated using chemical analysis, X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, X-ray computed nanotomography (nano-CT), attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, solid state NMR spectroscopy and thermogravimetric analysis. The results showed that all these techniques are complementary and useful to characterize the structure and morphology of the samples. Before any chemical treatment, the presence of impurities with a compact unfibrillated structure on the surfaces of chènevotte samples was found. Data indicated an increase in the crystallinity index and significant changes in the chemical composition of each sample after treatment as well as in surface morphology and roughness. The most significant changes were observed in alkaline-treated samples, especially those treated with KOH.
Iron Modified Titanate Nanotube Arrays for Photoelectrochemical Removal of E. coli
Authors: Chen Chia-Hung , Peng Yen-Ping , Lin Ming-Hsun , Chang Ken-Lin , Lin Yung-Chang , Sun Jian
Published: July 2021

This study used iron modified titanate nanotube arrays (Fe/TNAs) to remove E. coli in a photoelectrochemical system. The Fe/TNAs was synthesized by the anodization method and followed by the square wave voltammetry electrochemical deposition (SWVE) method with ferric nitrate as the precursor. Fe/TNAs were characterized by SEM, XRD, XPS, and UV-vis DRS to investigate the surface properties and light absorption. As a result, the iron nanoparticles (NPs) were successfully deposited on the tubular structure of the TNAs, which showed the best light utilization. Moreover, the photoelectrochemical (PEC) properties of the Fe/TNAs were measured by current-light response and electrochemical impedance spectroscopy. The photocurrent of the Fe/TNAs-0.5 (3.5 mA/cm2) was higher than TNAs (2.0 mA/cm2) and electron lifetime of Fe/TNAs-0.5 (433.3 ms) were also longer than TNAs (290.3 ms). Compared to the photolytic (P), photocatalytic (PC), and electrochemical (EC) method, Fe/TNAs PEC showed the best removal efficiency for methyl orange degradation. Furthermore, the Fe/TNAs PEC system also performed better removal efficiency than that of photolysis method in E. coli degradation experiments.
Optimization of the GSH-Mediated Formation of Mesoporous Silica-Coated Gold Nanoclusters for NIR Light-Triggered Photothermal Applications
Authors: Fernandes Natanael , Rodrigues Carolina F. , de Melo-Diogo Duarte , Correia Ilídio J. , Moreira André F.
Published: July 2021

Cancer light-triggered hyperthermia mediated by nanomaterials aims to eliminate cancer cells by inducing localized temperature increases to values superior to 42 °C, upon irradiation with a laser. Among the different nanomaterials with photothermal capacity, the gold-based nanoparticles have been widely studied due to their structural plasticity and advantageous physicochemical properties. Herein, a novel and straightforward methodology was developed to produce gold nanoclusters coated with mesoporous silica (AuMSS), using glutathione (GSH) to mediate the formation of the gold clusters. The obtained results revealed that GSH is capable of triggering and control the aggregation of gold nanospheres, which enhanced the absorption of radiation in the NIR region of the spectra. Moreover, the produced AuMSS nanoclusters mediated a maximum temperature increase of 20 °C and were able to encapsulate a drug model (acridine orange). In addition, these AuMSS nanoclusters were also biocompatible with both healthy (fibroblasts) and carcinogenic (cervical cancer) cells, at a maximum tested concentration of 200 μg/mL. Nevertheless, the AuMSS nanoclusters’ NIR light-triggered heat generation successfully reduced the viability of cervical cancer cells by about 80%. This confirms the potential of the AuMSS nanoclusters to be applied in cancer therapy, namely as theragnostic agents.
Iron Hydroxide/Oxide-Reduced Graphene Oxide Nanocomposite for Dual-Modality Photodynamic and Photothermal Therapy In Vitro and In Vivo
Authors: Chiu Wei-Jane , Chen Yi-Chun , Huang Chih-Ching , Yang Lingyan , Yu Jiantao , Huang Shih-Wei , Lin Chia-Hua
Published: July 2021

Minimal invasive phototherapy utilising near-infrared (NIR) laser to generate local reactive oxygen species (ROS) and heat has few associated side effects and is a precise treatment in cancer therapy. However, high-efficiency and safe phototherapeutic tumour agents still need developing. The application of iron hydroxide/oxide immobilised on reduced graphene oxide (FeOxH–rGO) nanocomposites as a therapeutic agent in integration photodynamic cancer therapy (PDT) and photothermal cancer therapy (PTT) was discussed. Under 808 nm NIR irradiation, FeOxH–rGO offers a high ROS generation and light-to-heat conversion efficiency because of its strong NIR absorption. These phototherapeutic effects lead to irreversible damage in FeOxH–rGO-treated T47D cells. Using a tumour-bearing mouse model, NIR ablated the breast tumour effectively in the presence of FeOxH–rGO. The tumour treatment response was evaluated to be 100%. We integrated PDT and PTT into a single nanodevice to facilitate effective cancer therapy. Our FeOxH–rGO, which integrates the merits of FeOxH and rGO, displays an outstanding tumoricidal capacity, suggesting the utilization of this nanocomposites in future medical applications.
Paliperidone to Treat Psychotic Disorders
Authors: Minwalla Hormazd D. , Wrzesinski Peter , Desforges Allison , Caskey Joshua , Wagner Brittany , Ingraffia Patrick , Patterson James C. , Edinoff Amber N. , Kaye Adam M. , Kaye Alan D. , Viswanath Omar , Urits Ivan
Published: July 2021

Purpose of Review: This is a comprehensive review of the literature regarding the use of paliperidone in the treatment of schizophrenia and schizoaffective disorder. It covers the background and presentation of schizophrenia and schizoaffective disorder, as well as the mechanism of action and drug information for paliperidone. It covers the existing evidence of the use of paliperidone for the treatment of schizophrenia and schizoaffective disorder. Recent Findings: Schizophrenia and schizoaffective disorder lead to significant cognitive impairment. It is thought that dopamine dysregulation is the culprit for the positive symptoms of schizophrenia and schizoaffective disorder. Similar to other second-generation antipsychotics, paliperidone has affinity for dopamine D2 and serotonin 5-HT2A receptors. Paliperidone was granted approval in the United States in 2006 to be used in the treatment of schizophrenia and in 2009 for schizoaffective disorder. Summary: Schizophrenia and schizoaffective disorder have a large impact on cognitive impairment, positive symptoms and negative symptoms. Patients with either of these mental illnesses suffer from impairments in everyday life. Paliperidone has been shown to reduce symptoms of schizophrenia and schizoaffective disorder.
A Comprehensive Approach to Rehabilitation Interventions in Patients with Angelman Syndrome: A Systematic Review of the Literature
Authors: Sommese Maddalena , Corrado Bruno
Published: July 2021

Angelman syndrome is a rare genetic disease affecting the central nervous system and neurobehavioral development causing severe mental, linguistic, and physical disabilities. The purpose of this review was to analyze the most recent evidence regarding the rehabilitation of subjects affected by this syndrome. The review was carried out in accordance with the preferred reporting items for systematic reviews and meta-analyses. A total of 3661 studies were identified in the databases. Once the inclusion/exclusion criteria were applied, 15 studies were considered for the paper’s preparation. The level of evidence of the studies was established according to the criteria of the Oxford Center for Evidence-Based Medicine—Levels of Evidence. From the selected studies, five rehabilitative approaches emerged: physiotherapy, applied behavioral analysis, toilet training, microswitch-cluster technology, and augmentative and alternative communication. Although the studies did not have a high level of evidence, the reported results appear to be encouraging and pave the way for further studies. It seems that individualized and multidisciplinary rehabilitation interventions help to improve patients’ autonomy and quality of life. In some studies, the caregivers’ role was fundamental to identify preferences and long-term improvements. Further studies on larger populations and with better methodological quality are needed to confirm the results.
Distribution of Responsibility for Climate Change within the Milieu
Authors: Droz Laÿna
Published: July 2021

This article approaches the challenges of the distribution of responsibility for climate change on a local level using the framework of the milieu. It suggests that the framework of the milieu, inspired by Japanese and cross-cultural environmental philosophy, provides pathways to address the four challenges of climate change (global dispersion, fragmentation of agency, institutional inadequacy, temporal delay). The framework of the milieu clarifies the interrelations between the individual, the community, and the local milieu and is open to a conservative view of human communities and an inclusive view of multispecies communities. On this basis, an account of individual responsibility that is anchored in the local milieu and includes a responsibility to collaborate across milieus is developed. It consists of a forward-looking responsibility that balances a degree of contributory responsibility for one’s imprints on the milieu with a degree of capacity-responsibility that varies regarding the individual’s knowledge and powers, and the acceptability of practices within the local milieu.
Validation of Reference Genes for Quantitative PCR in Johnsongrass (Sorghum halepense L.) under Glyphosate Stress
Authors: Ulrich María Noelia , Muñiz-Padilla Esteban , Corach Alejandra , Hopp Esteban , Tosto Daniela
Published: July 2021

Weeds are one of the main causes of the decrease in crop yields, with Johnsongrass (Sorghum halepense L.) being one of the most significant. Weeds can be controlled by herbicides, but some have developed resistance. Quantitative PCR is the technique of choice for studying gene expression related to herbicide resistance because of its high sensitivity and specificity, although its quantitative accuracy is highly dependent on the stability of the reference genes. Thus, in this study we evaluated the stability of different reference genes of glyphosate-resistant S. halepense. Nine genes frequently used as reference genes were selected: MDH, ADP, PP2A, EIF4α, ACT, ARI8, DnaJ, Hsp70, and ALS1, and their expression analyzed in susceptible and resistant biotypes at 0, 24 and 72 h post-application of glyphosate. The stability was analyzed with the geNorm, NormFinder, and BestKeeper software programs and using the ΔCt method. RefFinder was used to generate a comprehensive stability ranking. The results showed that PP2A and ARI8 were the most stable genes under the test conditions. EPSPS expression was also verified against the best two and the worst two reference genes. This study provides useful information for gene expression analysis under glyphosate stress and will facilitate resistance mechanism studies in this weed species.
Knowledge in Images and Sounds: Informative, Narrative and Aesthetic Analysis of the Video for MOOC
Authors: Rajas-Fernández Mario , Gértrudix-Barrio Manuel , Baños-González Miguel
Published: July 2021

The virtual courses developed by higher education institutions incorporate the video format as one of the most used resources in the delivery of their online training offer. Within the different types of audiovisual productions found in MOOCs, the introductory or presentation video of the courses has become an illustrative piece of the new edu-communicative context of distance education, when articulating, in the same work, informative, didactic, and advertising content. The objective of this research work is to study the triple communicative nature of this innovative format following a specific methodology of audiovisual textual analysis. For this, 420 videos of this type of promotional video, belonging to 105 universities and educational centres that have developed MOOC courses for the Miríadax platform, are analysed. After checking the results of the formal characteristics, content structures, discursive techniques, and audiovisual language components of the videos, it is concluded that they are mostly pieces linked to the staging style of the classroom, but that, by enriching the visual appearance of a master lesson with audiovisual resources, take advantage of the narrative, aesthetic, and creative potential of audiovisual and advertising communication to capture the attention of the student-spectator, inform about the characteristics of the courses, offer valuable educational content, and generate an image of the brand for the institution responsible for producing the course.
Ratzinger on Evolution and Evil: A Christological and Mariological Answer to the Problem of Suffering and Death in Creation
Authors: Ramage Matthew J.
Published: July 2021

This article argues that a compelling way to address the presence of suffering and death across evolutionary history lies in the thought of Joseph Ratzinger/Pope Benedict XVI. By situating human evolution within the broader divine plan for man’s salvation through the cross of Jesus, Ratzinger is able to show that the presence of natural evils in this world is not incompatible with God’s goodness but on the contrary is an eminent means by which the love of God is made manifest. Exploring Christ’s kenosis and the sinless suffering of the Blessed Virgin, it is argued that suffering properly embraced is the raw material for love and thus essential for true human flourishing in this life. The real problem for man, it is contended, is not having to suffer and die, but how to suffer and die well. Finally, it is suggested that the full Christian answer to the problem of suffering connected with evolution nevertheless lies in the eschatogical hope for a new heaven and new earth, where man—and all creation with him—will undergo a definitive “evolutionary leap” of “transubstantiation” in Christ.
Atmospheric Compensation of PRISMA Data by Means of a Learning Based Approach
Authors: Acito Nicola , Diani Marco , Procissi Gregorio , Corsini Giovanni
Published: July 2021

Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed.
Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools
Authors: Rodríguez-Lozano Borja , Rodríguez-Caballero Emilio , Maggioli Lisa , Cantón Yolanda
Published: July 2021

The Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a surrogate of many ecosystem functions and services and one of the main terrestrial carbon pools. Thus, accurate methodologies for AGB estimation are needed. This has been traditionally done by performing direct field measurements. However, field-based methods, such as biomass harvesting, are destructive, expensive, and time consuming and only provide punctual information, not being appropriate for large scale applications. Here, we propose a new non-destructive methodology for monitoring the spatiotemporal dynamics of AGB and green biomass (GB) of M. tenacissima L. plants by combining structural information obtained from terrestrial laser scanner (TLS) point clouds and spectral information. Our results demonstrate that the three volume measurement methods derived from the TLS point clouds tested (3D convex hull, voxel, and raster surface models) improved the results obtained by traditional field-based measurements. (Adjust-R2 = 0.86–0.84 and RMSE = 927.3–960.2 g for AGB in OLS regressions and Adjust-R2 = 0.93 and RMSE = 376.6–385.1 g for AGB in gradient boosting regression). Among the approaches, the voxel model at 5 cm of spatial resolution provided the best results; however, differences with the 3D convex hull and raster surface-based models were very small. We also found that by combining TLS AGB estimations with spectral information, green and dry biomass fraction can be accurately measured (Adjust-R2 = 0.65–0.56 and RMSE = 149.96–166.87 g in OLS regressions and Adjust-R2 = 0.96–0.97 and RMSE = 46.1–49.8 g in gradient boosting regression), which is critical in heterogeneous Mediterranean ecosystems in which AGB largely varies in response to climatic fluctuations. Thus, our results represent important progress for the measurement of M. tenacissima L. biomass and dynamics, providing a promising tool for calibration and validation of further studies aimed at developing new methodologies for AGB estimation at ecosystem regional scales.
Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
Authors: Désert Thibault , Knapp Graham , Aubrun Sandrine
Published: July 2021

Floating LIDAR systems (FLS) are a cost-effective way of surveying the wind energy potential of an offshore area. However, as turbulence intensity estimates are strongly affected by wave-induced buoy motion, it is essential to correct them. In this study, we quantify the turbulence intensity measurement error of a WindCube v2® mounted on a 12-ton anchored buoy as a function of met-ocean conditions, and we construct a subsequently applied correction method suitable for 10-min wind LIDAR data storage. To this end, we build a model to simulate the effect of buoyancy movements on the LIDAR’s wind measurements. We first apply the model to understand the mechanisms responsible for the wind LIDAR measurement error. The effect of the buoy’s rotational and translational motions on the radial wind speed measurements of the individual beams is first studied. Second, the temporality induced by the LIDAR operation is taken into account; the effect of motion subsampling and the interaction between the different measurement beam positions. From this model, a correction method is developed and successfully applied to a 13-week experimental campaign conducted off the shores of Fécamp (Normandie, France) involving the buoy-mounted WindCube v2® compared with cup anemometers from a met mast and a fixed WindCube v2® on a platform. The correction improves the linear regression against the fixed LIDAR turbulence intensity measurements, shifting the offset from ~0.03 to ~0.005 without post-processing the remaining peaks.
A Photogrammetric-Photometric Stereo Method for High-Resolution Lunar Topographic Mapping Using Yutu-2 Rover Images
Authors: Peng Man , Di Kaichang , Wang Yexin , Wan Wenhui , Liu Zhaoqin , Wang Jia , Li Lichun
Published: July 2021

Topographic products are important for mission operations and scientific research in lunar exploration. In a lunar rover mission, high-resolution digital elevation models are typically generated at waypoints by photogrammetry methods based on rover stereo images acquired by stereo cameras. In case stereo images are not available, the stereo-photogrammetric method will not be applicable. Alternatively, photometric stereo method can recover topographic information with pixel-level resolution from three or more images, which are acquired by one camera under the same viewing geometry with different illumination conditions. In this research, we extend the concept of photometric stereo to photogrammetric-photometric stereo by incorporating collinearity equations into imaging irradiance model. The proposed photogrammetric-photometric stereo algorithm for surface construction involves three steps. First, the terrain normal vector in object space is derived from collinearity equations, and image irradiance equation for close-range topographic mapping is determined. Second, based on image irradiance equations of multiple images, the height gradients in image space can be solved. Finally, the height map is reconstructed through global least-squares surface reconstruction with spectral regularization. Experiments were carried out using simulated lunar rover images and actual lunar rover images acquired by Yutu-2 rover of Chang’e-4 mission. The results indicate that the proposed method achieves high-resolution and high-precision surface reconstruction, and outperforms the traditional photometric stereo methods. The proposed method is valuable for ground-based lunar surface reconstruction and can be applicable to surface reconstruction of Earth and other planets.
A Comparison of Monoscopic and Stereoscopic 3D Visualizations: Effect on Spatial Planning in Digital Twins
Authors: Herman Lukáš , Juřík Vojtěch , Snopková Dajana , Chmelík Jiří , Ugwitz Pavel , Stachoň Zdeněk , Šašinka Čeněk , Řezník Tomáš
Published: July 2021

From the user perspective, 3D geospatial data visualizations are one of the bridges between the physical and the digital world. As such, the potential of 3D geospatial data visualizations is frequently discussed within and beyond the digital twins. The effects on human cognitive processes in complex spatial tasks is rather poorly known. No uniform standards exist for the 3D technologies used in these tasks. Although stereoscopic geovisualizations presented using 3D technologies enhance depth perception, it has been suggested that the visual discomfort experienced when using 3D technology outweighs its benefits and results in lower efficiency and errors. In the present study, sixty participants using 3D technologies were tested in terms of their ability to make informed decisions in selecting the correct position of a virtual transmitter in a digital twin and a digital terrain model, respectively. Participants (n = 60) were randomly assigned into two groups, one using 3D technology engaging stereoscopic shutter glasses and the second working with standard computer screen-based visualizations. The results indicated that the participants who used shutter glasses performed significantly worse in terms of response time (W = 175.0; p < 0.001, r = −0.524). This finding verifies previous conclusions concerning the unsuitability of stereoscopic visualization technology for complex decision-making in geospatial tasks.
Evaluation and Correction of Elevation Angle Influence for Coastal GNSS-R Ocean Altimetry
Authors: Zhang Guodong , Xu Zhichao , Wang Feng , Yang Dongkai , Xing Jin
Published: July 2021

The elevation angle influence on coastal GNSS-R ocean code-based altimetry for GPS signals (L1 C/A and L5) and BDS B1 signals is investigated, and the corresponding correction method is presented. The study first focuses on the coastal ocean altimetry method, including the general experiment geometry and the code delay estimation using the single-point tracking algorithm. The peak power and the maximum first derivative are used as the location of the specular point. Then, the sensitivity of the height retrieved using the above coastal ocean altimetry method to elevation angle is analyzed based on the Z-V model. It can be seen that the elevation angle has a significant influence on the height retrieval, which will affect the precision of the coastal GNSS-R ocean altimetry. Finally, two correction methods, the model-driven method and the data-driven method, are proposed. The coastal altimetry experiments demonstrate that the correction methods can correct the elevation angle influence, and the data-driven method is more effective. The experimental results show that, after correcting the elevation angle influence, the code-based altimetry precision of the GPS L1 C/A signal, L5 signal, and BDS B1 signal can be up to the meter level, decimeter level (less than 4 decimeters), and meter level with respect to a reference tide gauge (TG) data set, respectively, without smoothing over time. These results provide information to guide the sea surface height retrieval using coastal GNSS-R, especially multi-satellite observation and GNSS signal with a higher chipping rate.
Evaluation of Operational Monsoon Moisture Surveillance and Severe Weather Prediction Utilizing COSMIC-2/FORMOSAT-7 Radio Occultation Observations
Authors: Chen Yu-Chun , Tsai Chih-Chien , Wu Yi-chao , Wang An-Hsiang , Wang Chieh-Ju , Lin Hsin-Hung , Chen Dan-Rong , Yu Yi-Chiang
Published: July 2021

Operational monsoon moisture surveillance and severe weather prediction is essential for timely water resource management and disaster risk reduction. For these purposes, this study suggests a moisture indicator using the COSMIC-2/FORMOSAT-7 radio occultation (RO) observations and evaluates numerical model experiments with RO data assimilation. The RO data quality is validated by a comparison between sampled RO profiles and nearby radiosonde profiles around Taiwan prior to the experiments. The suggested moisture indicator accurately monitors daily moisture variations in the South China Sea and the Bay of Bengal throughout the 2020 monsoon rainy season. For the numerical model experiments, the statistics of 152 moisture and rainfall forecasts for the 2020 Meiyu season in Taiwan show a neutral to slightly positive impact brought by RO data assimilation. A forecast sample with the most significant improvement reveals that both thermodynamic and dynamic fields are appropriately adjusted by model integration posterior to data assimilation. The statistics of 17 track forecasts for typhoon Hagupit (2020) also show the positive effect of RO data assimilation. A forecast sample reveals that the member with RO data assimilation simulates better typhoon structure and intensity than the member without, and the effect can be larger and faster via multi-cycle RO data assimilation.
Classification Efficacy Using K-Fold Cross-Validation and Bootstrapping Resampling Techniques on the Example of Mapping Complex Gully Systems
Authors: Phinzi Kwanele , Abriha Dávid , Szabó Szilárd
Published: July 2021

The availability of aerial and satellite imageries has greatly reduced the costs and time associated with gully mapping, especially in remote locations. Regardless, accurate identification of gullies from satellite images remains an open issue despite the amount of literature addressing this problem. The main objective of this work was to investigate the performance of support vector machines (SVM) and random forest (RF) algorithms in extracting gullies based on two resampling methods: bootstrapping and k-fold cross-validation (CV). In order to achieve this objective, we used PlanetScope data, acquired during the wet and dry seasons. Using the Normalized Difference Vegetation Index (NDVI) and multispectral bands, we also explored the potential of the PlanetScope image in discriminating gullies from the surrounding land cover. Results revealed that gullies had significantly different (p < 0.001) spectral profiles from any other land cover class regarding all bands of the PlanetScope image, both in the wet and dry seasons. However, NDVI was not efficient in gully discrimination. Based on the overall accuracies, RF’s performance was better with CV, particularly in the dry season, where its performance was up to 4% better than the SVM’s. Nevertheless, class level metrics (omission error: 11.8%; commission error: 19%) showed that SVM combined with CV was more successful in gully extraction in the wet season. On the contrary, RF combined with bootstrapping had relatively low omission (16.4%) and commission errors (10.4%), making it the most efficient algorithm in the dry season. The estimated gully area was 88 ± 14.4 ha in the dry season and 57.2 ± 18.8 ha in the wet season. Based on the standard error (8.2 ha), the wet season was more appropriate in gully identification than the dry season, which had a slightly higher standard error (8.6 ha). For the first time, this study sheds light on the influence of these resampling techniques on the accuracy of satellite-based gully mapping. More importantly, this study provides the basis for further investigations into the accuracy of such resampling techniques, especially when using different satellite images other than the PlanetScope data.
Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research
Authors: le Roux Jeanné , Christopher Sundar , Maskey Manil
Published: July 2021

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.
Interactions between Teladorsagia circumcincta Infections and Microbial Composition of Sheep with or without Successful Monepantel Treatment—A Preliminary Study
Authors: Watkins Craig , Bartley Dave , Ergün Burcu , Yıldızhan Büşra , Ross-Watt Tracy , Morrison Alison , Rosales Sanmartín Maria , Strathdee Fiona , Andrews Leigh , Free Andrew
Published: July 2021

Nematodes are one of the main impactors on the health, welfare and productivity of farmed animals. Teladorsagia circumcincta are endemic throughout many sheep-producing countries, particularly in the northern hemisphere, and contribute to the pathology and economic losses seen on many farms. Control of these nematode infections is essential and heavily reliant on chemotherapy (anthelmintics), but this has been compromised by the development of anthelmintic resistance. In mammals, the composition of the intestinal microbiota has been shown to have a significant effect on overall health. The interactions between host, microbiota and pathogens are complex and influenced by numerous factors. In this study, comparisons between intestinal and faecal microbiota of sheep infected with sensitive or resistant strains of T. circumcincta, with or without monepantel administration were assessed. The findings from both faecal samples and terminal ileum mucosal scrapings showed clear differences between successfully treated animals and those sheep that were left untreated and/or those carrying resistant nematodes. Specifically, the potentially beneficial genus Bifidobacterium was identified as elevated in successfully treated animals. The detection of these and other biomarkers will provide the basis for new therapeutic reagents particularly relevant to the problems of emerging multidrug anthelmintic resistance.
An Optimized Nature-Inspired Metaheuristic Algorithm for Application Mapping in 2D-NoC
Authors: Sikandar Saleha , Baloch Naveed Khan , Hussain Fawad , Amin Waqar , Zikria Yousaf Bin , Yu Heejung
Published: July 2021

Mapping application task graphs on intellectual property (IP) cores into network-on-chip (NoC) is a non-deterministic polynomial-time hard problem. The evolution of network performance mainly depends on an effective and efficient mapping technique and the optimization of performance and cost metrics. These metrics mainly include power, reliability, area, thermal distribution and delay. A state-of-the-art mapping technique for NoC is introduced with the name of sailfish optimization algorithm (SFOA). The proposed algorithm minimizes the power dissipation of NoC via an empirical base applying a shared k-nearest neighbor clustering approach, and it gives quicker mapping over six considered standard benchmarks. The experimental results indicate that the proposed techniques outperform other existing nature-inspired metaheuristic approaches, especially in large application task graphs.
Deep and Wide Transfer Learning with Kernel Matching for Pooling Data from Electroencephalography and Psychological Questionnaires
Authors: Collazos-Huertas Diego Fabian , Velasquez-Martinez Luisa Fernanda , Perez-Nastar Hernan Dario , Alvarez-Meza Andres Marino , Castellanos-Dominguez German
Published: July 2021

Motor imagery (MI) promotes motor learning and encourages brain–computer interface systems that entail electroencephalogram (EEG) decoding. However, a long period of training is required to master brain rhythms’ self-regulation, resulting in users with MI inefficiency. We introduce a parameter-based approach of cross-subject transfer-learning to improve the performances of poor-performing individuals in MI-based BCI systems, pooling data from labeled EEG measurements and psychological questionnaires via kernel-embedding. To this end, a Deep and Wide neural network for MI classification is implemented to pre-train the network from the source domain. Then, the parameter layers are transferred to initialize the target network within a fine-tuning procedure to recompute the Multilayer Perceptron-based accuracy. To perform data-fusion combining categorical features with the real-valued features, we implement stepwise kernel-matching via Gaussian-embedding. Finally, the paired source–target sets are selected for evaluation purposes according to the inefficiency-based clustering by subjects to consider their influence on BCI motor skills, exploring two choosing strategies of the best-performing subjects (source space): single-subject and multiple-subjects. Validation results achieved for discriminant MI tasks demonstrate that the introduced Deep and Wide neural network presents competitive performance of accuracy even after the inclusion of questionnaire data.
Skin-Friction-Based Identification of the Critical Lines in a Transonic, High Reynolds Number Flow via Temperature-Sensitive Paint
Authors: Costantini Marco , Henne Ulrich , Klein Christian , Miozzi Massimo
Published: July 2021

In this contribution, three methodologies based on temperature-sensitive paint (TSP) data were further developed and applied for the optical determination of the critical locations of flow separation and reattachment in compressible, high Reynolds number flows. The methodologies rely on skin-friction extraction approaches developed for low-speed flows, which were adapted in this work to study flow separation and reattachment in the presence of shock-wave/boundary-layer interaction. In a first approach, skin-friction topological maps were obtained from time-averaged surface temperature distributions, thus enabling the identification of the critical lines as converging and diverging skin-friction lines. In the other two approaches, the critical lines were identified from the maps of the propagation celerity of temperature perturbations, which were determined from time-resolved TSP data. The experiments were conducted at a freestream Mach number of 0.72 and a chord Reynolds number of 9.7 million in the Transonic Wind Tunnel Göttingen on a VA-2 supercritical airfoil model, which was equipped with two exchangeable TSP modules specifically designed for transonic, high Reynolds number tests. The separation and reattachment lines identified via the three different TSP-based approaches were shown to be in mutual agreement, and were also found to be in agreement with reference experimental and numerical data.
A Review on the Development of Gold and Silver Nanoparticles-Based Biosensor as a Detection Strategy of Emerging and Pathogenic RNA Virus
Authors: Ibrahim Nadiah , Jamaluddin Nur Diyana , Tan Ling Ling , Mohd Yusof Nurul Yuziana
Published: July 2021

The emergence of highly pathogenic and deadly human coronaviruses, namely SARS-CoV and MERS-CoV within the past two decades and currently SARS-CoV-2, have resulted in millions of human death across the world. In addition, other human viral diseases, such as mosquito borne-viral diseases and blood-borne viruses, also contribute to a higher risk of death in severe cases. To date, there is no specific drug or medicine available to cure these human viral diseases. Therefore, the early and rapid detection without compromising the test accuracy is required in order to provide a suitable treatment for the containment of the diseases. Recently, nanomaterials-based biosensors have attracted enormous interest due to their biological activities and unique sensing properties, which enable the detection of analytes such as nucleic acid (DNA or RNA), aptamers, and proteins in clinical samples. In addition, the advances of nanotechnologies also enable the development of miniaturized detection systems for point-of-care (POC) biosensors, which could be a new strategy for detecting human viral diseases. The detection of virus-specific genes by using single-stranded DNA (ssDNA) probes has become a particular interest due to their higher sensitivity and specificity compared to immunological methods based on antibody or antigen for early diagnosis of viral infection. Hence, this review has been developed to provide an overview of the current development of nanoparticles-based biosensors that target pathogenic RNA viruses, toward a robust and effective detection strategy of the existing or newly emerging human viral diseases such as SARS-CoV-2. This review emphasizes the nanoparticles-based biosensors developed using noble metals such as gold (Au) and silver (Ag) by virtue of their powerful characteristics as a signal amplifier or enhancer in the detection of nucleic acid. In addition, this review provides a broad knowledge with respect to several analytical methods involved in the development of nanoparticles-based biosensors for the detection of viral nucleic acid using both optical and electrochemical techniques.
An Advanced Sensor for Particles in Gases Using Dynamic Light Scattering in Air as Solvent
Authors: Chicea Dan , Leca Cristian , Olaru Sorin , Chicea Liana Maria
Published: July 2021

Dynamic Light Scattering is a technique currently used to assess the particle size and size distribution by processing the scattered light intensity. Typically, the particles to be investigated are suspended in a liquid solvent. An analysis of the particular conditions required to perform a light scattering experiment on particles in air is presented in detail, together with a simple experimental setup and the data processing procedure. The results reveal that such an experiment is possible and using the setup and the procedure, both simplified to extreme, enables the design of an advanced sensor for particles and fumes that can output the average size of the particles in air.
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems
Authors: Cardenas Jorge D. , Gutierrez Carlos A. , Aguilar-Ponce Ruth
Published: July 2021

The growing elderly population living independently demands remote systems for health monitoring. Falls are considered recurring fatal events and therefore have become a global health problem. Fall detection systems based on WiFi radio frequency signals still have limitations due to the difficulty of differentiating the features of a fall from other similar activities. Additionally, the antenna orientation has not been taking into account as an influencing factor of classification performance. Therefore, we present in this paper an analysis of the classification performance in relation to the antenna orientation and the effects related to polarization and radiation pattern. Furthermore, the implementation of a device-free fall detection platform to collect empirical data on falls is shown. The platform measures the Doppler spectrum of a probe signal to extract the Doppler signatures generated by human movement and whose features can be used to identify falling events. The system explores two antenna polarization: horizontal and vertical. The accuracy reached by horizontal polarization is 92% with a false negative rate of 8%. Vertical polarization achieved 50% accuracy and false negatives rate.
Forecasting the Energy and Economic Benefits of Photovoltaic Technology in China’s Rural Areas
Authors: Zhang Wenjie , Zhao Yuqiang , Huang Fengcheng , Zhong Yongheng , Zhou Jianwei
Published: July 2021

In recent years, with the rapid development of China’s economy, China’s energy demand has also been growing rapidly. Promoting the use of renewable energy in China has become an urgent need. This study evaluates the potential of solar photovoltaic (PV) power generation on the roofs of residential buildings in rural areas of mainland China and calculates the area that can used for generating energy, the installed capacity, and the power generation, and conducts a comprehensive analysis of the economic benefits of investing in the construction of distributed PV systems in various provinces. The findings unveiled in this study indicate that China still has more than 6.4 billion m2 of rural construction area available for the installation of PV modules. If this is all used for solar power generation, the annual power generation can reach up to 1.55 times the electricity consumption of urban and rural residents for the whole society. Through a comprehensive evaluation of energy efficiency and economic benefits, the Chinese mainland can be divided into three types of resource areas. The three types of resource areas have their own advantages and disadvantages. According to their own characteristics and advantages, we can reasonably formulate relevant policies to accelerate the development of PV system application in rural areas.
Exploring Collaborative Problem Solving Behavioral Transition Patterns in Science of Taiwanese Students at Age 15 According to Mastering Levels
Authors: Li Cheng-Hsuan , Tsai Pei-Ling , Liu Zhi-Yong , Huang Wen-Chieh , Hsieh Pei-Jyun
Published: July 2021

This study analyzed the collaborative problem solving (CPS) behavioral transition patterns of 53,859 Taiwanese students in science at age 15 by using an online Taiwanese CPS assessment that was designed according to the Programme for International Student Assessment 2015 CPS framework. Because of behavioral changes over the testing period, the CPS target skills that corresponded to the assessment items can be viewed as a CPS behavioral sequence. Hence, a lag sequential analysis was applied to explore the significance of the interactions among the CPS skills. The behavioral sequence is coded according to the level of mastery (0, 1, or 2) of items. The CPS transition patterns were analyzed in three gaps, namely the gender gap, the urban–rural gap, and the achievement gap. The findings showed that “Monitoring and repairing the shared understanding” was a crucial CPS skill in science. Moreover, the female students who would follow rules of engagement effectively exhibited higher scores than male students did in monitoring the results of their actions and evaluating their success in solving the problem. No obvious differences were observed in the urban–rural gap, whereas differences were observed in the achievement gap.
Place-Based STEM Education for Sustainability: A Path towards Socioecological Resilience
Authors: Bascopé Martín , Reiss Kristina
Published: July 2021

This article analyzes STEM projects conducted in eight schools with children from 4 to 10 years old in southern Chile. The main purpose of the study was to describe and analyze how these projects can affect students’ and educators’ attitudes and create community capacities to tackle local socioecological challenges. We used an ethnographic design with an intentioned coding process of interviews and participant observations to summarize one year of collaborative and transdisciplinary project building. The results describe the main attitudinal changes of teachers and students and give evidence on how these projects create new links and foster collaborations with local actors and organizations that are usually sidelined from educational experiences. Examples of meaningful learning experiences to tackle sustainability challenges were systematized and shared, to inspire new initiatives, raise new voices, and promote active participation of the new generations to foster socioecological resilience.