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Open AccessLetter
Global Cyclone and Anticyclone Detection Model Based on Remotely Sensed Wind Field and Deep Learning
Remote Sens. 2020, 12(19), 3111; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12193111 (registering DOI) - 23 Sep 2020
Abstract
Cyclone detection is a classical topic and researchers have developed various methods of cyclone detection based on sea-level pressure, cloud image, wind field, etc. In this article, a deep-learning algorithm is incorporated with modern remote-sensing technology and forms a global-scale cyclone/anticyclone detection model. [...] Read more.
Cyclone detection is a classical topic and researchers have developed various methods of cyclone detection based on sea-level pressure, cloud image, wind field, etc. In this article, a deep-learning algorithm is incorporated with modern remote-sensing technology and forms a global-scale cyclone/anticyclone detection model. Instead of using optical images, wind field data obtained from Mean Wind Field-Advanced Scatterometer (MWF-ASCAT) is utilized as the dataset for model training and testing. The wind field vectors are reconstructed and fed to the deep-learning model, which is built based on a faster-region with convolutional neural network (faster-RCNN). The model consists of three modules: a series of convolutional and pooling layers as the feature extractor, a region proposal network that searches for the potential areas of cyclone/anticyclone within the dataset, and the classifier that classifies the proposed region as cyclone or anticyclone through a fully-connected neural network. Compared with existing methods of cyclone detection, the test results indicate that this model based on deep learning is able to reduce the number of false alarms, and at the same time, maintain high accuracy in cyclone detection. An application of this method is presented in the article. By processing temporally continuous data of wind field, the model is able to track the path of Hurricane Irma in September, 2017. The advantages and limitations of the model are also discussed in the article. Full article
(This article belongs to the Special Issue Artificial Intelligence for Weather and Climate)
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Open AccessArticle
Effect of Pretreatment on Hydraulic Performance of the Integrated Membrane Process for Concentrating Nutrient in Biogas Digestate from Swine Manure
Membranes 2020, 10(10), 249; https://0-doi-org.brum.beds.ac.uk/10.3390/membranes10100249 (registering DOI) - 23 Sep 2020
Abstract
Nanofiltration (NF) or reverse osmosis (RO) process has been widely applied for concentrating nutrient in biogas digestate. However, efficient pretreatment is key to the sustainable operation of NF or RO. In this study, the combination of NF and RO for concentrating biogas digestate [...] Read more.
Nanofiltration (NF) or reverse osmosis (RO) process has been widely applied for concentrating nutrient in biogas digestate. However, efficient pretreatment is key to the sustainable operation of NF or RO. In this study, the combination of NF and RO for concentrating biogas digestate was compared using different pretreatments of hollow fiber ultrafiltration membrane (HFUFM) and ceramic membrane (CUFM). Pilot-scale batch tests were conducted (500 L). CUFM showed a higher membrane flux than HFUFM (100 ~ 180 L·(m2·h)−1 vs. 17 ~ 35 L·(m2·h)−1), but they showed little impact on the NF + RO process. Membrane fluxes of NF and RO were 20 ~ 48 L·(m2·h)−1 and 16 ~ 40 L·(m2·h)−1, respectively. In the RO permeates, the removal rates of total suspended solids (TSS), total solids (TS), chemical oxygen demand (COD), total nitrogen (TN), NH4+-N, and Cl were above 91%. In the concentrates, TN and total potassium (TK) were concentrated by 1.60 and 2.00 folds in the NF stage, and by 2.10 and 2.30 folds in the RO stage. Further attention should be paid to the antibiotics risks in the concentrates before they are utilized as plant fertilizers. Full article
(This article belongs to the Special Issue Membranes: 10th Anniversary)
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Open AccessArticle
In Vitro Digestion and Fermentation by Human Fecal Microbiota of Polysaccharides from Flaxseed
Molecules 2020, 25(19), 4354; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25194354 (registering DOI) - 23 Sep 2020
Abstract
The digestion of flaxseed polysaccharides (FSP) in simulated saliva, gastric and small intestine conditions was assessed, as well as in vitro fermentation of FSP by human gut microbiota. FSP was not degraded in the simulated digestive systems (there was no change in molecular [...] Read more.
The digestion of flaxseed polysaccharides (FSP) in simulated saliva, gastric and small intestine conditions was assessed, as well as in vitro fermentation of FSP by human gut microbiota. FSP was not degraded in the simulated digestive systems (there was no change in molecular weight or content of reducing sugars), indicating that ingested FSP would reach the large intestine intact. Changes in carbohydrate content, reducing sugars and culture pH suggested that FSP could be broken down and used by gut microbiota. FSP modulated the composition and structure of the gut microbiota by altering the Firmicutes/Bacteroidetes ratio and increasing the relative abundances of Prevotella, Phascolarctobacterium, Clostridium and Megamonas, which can degrade polysaccharides. Meanwhile, FSP fermentation increased the concentration of short-chain fatty acids, especially propionic and butyric acids. Our results indicate that FSP might be developed as a functional food that benefits gut health. Full article
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Open AccessArticle
Influence of Culture Conditions and Medium Compositions on the Production of Bacteriocin-Like Inhibitory Substances by Lactococcus lactis Gh1
Microorganisms 2020, 8(10), 1454; https://0-doi-org.brum.beds.ac.uk/10.3390/microorganisms8101454 (registering DOI) - 23 Sep 2020
Abstract
Antibacterial peptides or bacteriocins produced by many strains of lactic acid bacteria have been used as food preservatives for many years without any known adverse effects. Bacteriocin titres can be modified by altering the physiological and nutritional factors of the producing bacterium to [...] Read more.
Antibacterial peptides or bacteriocins produced by many strains of lactic acid bacteria have been used as food preservatives for many years without any known adverse effects. Bacteriocin titres can be modified by altering the physiological and nutritional factors of the producing bacterium to improve the production in terms of yield and productivity. The effects of culture conditions (initial pH, inoculum age and inoculum size) and medium compositions (organic and inorganic nitrogen sources; carbon sources) were assessed for the production of bacteriocin-like inhibitory substances (BLIS) by Lactococcus lactis Gh1 in shake flask cultures. An inoculum of the mid-exponential phase culture at 1% (v/v) was the optimal age and size, while initial pH of culture media at alkaline and acidic state did not show a significant impact on BLIS secretion. Organic nitrogen sources were more favourable for BLIS production compared to inorganic sources. Production of BLIS by L. lactis Gh1 in soytone was 1.28-times higher as compared to that of organic nitrogen sources ((NH4)2SO4). The highest cell concentration (XmX = 0.69 ± 0.026 g·L−1) and specific growth rate (μmax = 0.14 h−1) were also observed in cultivation using soytone. By replacing carbon sources with fructose, BLIS production was increased up to 34.94% compared to BHI medium, which gave the biomass cell concentration and specific growth rate of 0.66 ± 0.002 g·L−1 and 0.11 h−1, respectively. It can be concluded that the fermentation factors have pronounced influences on the growth of L. lactis Gh1 and BLIS production. Results from this study could be used for subsequent application in process design and optimisation for improving BLIS production by L. lactis Gh1 at larger scale. Full article
(This article belongs to the Special Issue Microbial Secondary Metabolites and Biotechnology)
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Open AccessArticle
Comparative Analysis on the Deployment of Machine Learning Algorithms in the Distributed Brillouin Optical Time Domain Analysis (BOTDA) Fiber Sensor
Photonics 2020, 7(4), 79; https://0-doi-org.brum.beds.ac.uk/10.3390/photonics7040079 (registering DOI) - 23 Sep 2020
Abstract
This paper demonstrates a comparative analysis of five machine learning (ML) algorithms for improving the signal processing time and temperature prediction accuracy in Brillouin optical time domain analysis (BOTDA) fiber sensor. The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random [...] Read more.
This paper demonstrates a comparative analysis of five machine learning (ML) algorithms for improving the signal processing time and temperature prediction accuracy in Brillouin optical time domain analysis (BOTDA) fiber sensor. The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). In this proof-of-concept experiment, the performance of each algorithm was investigated by pairing Brillouin gain spectrum (BGS) with its corresponding temperature reading in the training dataset. It was found that all of the ML algorithms have significantly reduced the signal processing time to be between 3.5 and 655 times faster than the conventional Lorentzian curve fitting (LCF) method. Furthermore, the temperature prediction accuracy and temperature measurement precision made by some algorithms were comparable, and some were even better than the conventional LCF method. The results obtained from the experiments would provide some general idea in deploying ML algorithm for characterizing the Brillouin-based fiber sensor signals. Full article
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Open AccessArticle
Continuance Use of Cloud Computing in Higher Education Institutions: A Conceptual Model
Appl. Sci. 2020, 10(19), 6628; https://0-doi-org.brum.beds.ac.uk/10.3390/app10196628 (registering DOI) - 23 Sep 2020
Abstract
Resource optimization is a key concern for Higher Education Institutions (HEIs). Cloud Computing, as the recent generation in computing technology of the fourth industrial revolution, has emerged as the main standard of service and resource delivery. As cloud computing has grown into a [...] Read more.
Resource optimization is a key concern for Higher Education Institutions (HEIs). Cloud Computing, as the recent generation in computing technology of the fourth industrial revolution, has emerged as the main standard of service and resource delivery. As cloud computing has grown into a mature technology and is being rapidly adopted in many HEIs across the world, retaining customers of this innovative technology has become a challenge to the cloud service providers. Current research trends on cloud computing have sought to study the acceptance or adoption of technology; however, little research has been devoted to the continuance use in an organizational setting. To address this gap, this study aims to investigate the antecedents of cloud computing continuance use in HEIs. Hence, drawing on the prior literature in organizational-level continuance, this research established a conceptual model that extends and contextualizes the IS continuance model through the lens of the TOE framework (i.e., technological, organizational, and environmental influences). The results of a pilot study, conducted through a survey with information and communications technology (ICT) decision makers, and based on the proposed conceptual model, indicate that the instrument is both reliable and valid, and so point the way towards further research. The paper closes with a discussion of the research limitations, contribution, and future directions. Full article
(This article belongs to the Special Issue Innovations in the field of Cloud Computing and Education)
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Open AccessArticle
Growth Differentiation Factor 15 Ameliorates Anti-Glomerular Basement Membrane Glomerulonephritis in Mice
Int. J. Mol. Sci. 2020, 21(19), 6978; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21196978 (registering DOI) - 23 Sep 2020
Abstract
Growth differentiation factor 15 (GDF15) is a member of the transforming growth factor-β (TGF-β) cytokine family and an inflammation-associated protein. Here, we investigated the role of GDF15 in murine anti-glomerular basement membrane (GBM) glomerulonephritis. Glomerulonephritis induction in mice induced systemic expression of GDF15. [...] Read more.
Growth differentiation factor 15 (GDF15) is a member of the transforming growth factor-β (TGF-β) cytokine family and an inflammation-associated protein. Here, we investigated the role of GDF15 in murine anti-glomerular basement membrane (GBM) glomerulonephritis. Glomerulonephritis induction in mice induced systemic expression of GDF15. Moreover, we demonstrate the protective effects for GDF15, as GDF15-deficient mice exhibited increased proteinuria with an aggravated crescent formation and mesangial expansion in anti-GBM nephritis. Herein, GDF15 was required for the regulation of T-cell chemotactic chemokines in the kidney. In addition, we found the upregulation of the CXCR3 receptor in activated T-cells in GDF15-deficient mice. These data indicate that CXCL10/CXCR3-dependent-signaling promotes the infiltration of T cells into the organ during acute inflammation controlled by GDF15. Together, these results reveal a novel mechanism limiting the migration of lymphocytes to the site of inflammation during glomerulonephritis. Full article
(This article belongs to the Special Issue Kidney Inflammation, Injury and Regeneration 2020)
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Open AccessArticle
Composition and Antibacterial Activity of the Essential Oil from Pimenta dioica (L.) Merr. from Guatemala
Medicines 2020, 7(10), 59; https://0-doi-org.brum.beds.ac.uk/10.3390/medicines7100059 (registering DOI) - 23 Sep 2020
Abstract
Background: Pimenta dioica is a native tree of Central America, Southern Mexico, and the Caribbean used in traditional medicine. It grows in wet forests in the Guatemalan departments of Petén and Izabal. Since the plant is not being economically exploited in Guatemala, [...] Read more.
Background: Pimenta dioica is a native tree of Central America, Southern Mexico, and the Caribbean used in traditional medicine. It grows in wet forests in the Guatemalan departments of Petén and Izabal. Since the plant is not being economically exploited in Guatemala, this study was aimed at determining the composition of the essential oil of P. dioica leaves and fruits and the antibacterial activity of the leaves in order to evaluate its possible use in health products. The essential oils of fruits and leaves are used as rubefacient, anti-inflammatory, carminative, antioxidant, and antiflatulent in different countries. Fruits and leaves of P. dioica from Izabal Department were collected in April 2014 and extracted by hydrodistillation method. The oils were analyzed by gas chromatography coupled with mass spectrometry (GC/MS). Yields of 1.02 ± 0.11 % for dried leaves and 1.51 ± 0.26% for fruits were obtained. Eugenol was the main component (65.9–71.4%). The leaf oil showed growth inhibition against two Gram-positive and two Gram-negative bacteria. The authors consider that the tree’s leaves can be evaluated as a source of ingredients for antiseptic products, and that it is important to evaluate other types of properties such as anti-inflammatory activity. Full article
(This article belongs to the Special Issue Biological Potential and Medical Use of Essential Oils)
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Open AccessArticle
Asymptotically Normal Estimators of the Gerber-Shiu Function in Classical Insurance Risk Model
Mathematics 2020, 8(10), 1638; https://0-doi-org.brum.beds.ac.uk/10.3390/math8101638 (registering DOI) - 23 Sep 2020
Abstract
Nonparametric estimation of the Gerber-Shiu function is a popular topic in insurance risk theory. Zhang and Su (2018) proposed a novel method for estimating the Gerber-Shiu function in classical insurance risk model by Laguerre series expansion based on the claim number and claim [...] Read more.
Nonparametric estimation of the Gerber-Shiu function is a popular topic in insurance risk theory. Zhang and Su (2018) proposed a novel method for estimating the Gerber-Shiu function in classical insurance risk model by Laguerre series expansion based on the claim number and claim sizes of sample. However, whether the estimators are asymptotically normal or not is unknown. In this paper, we give the details to verify the asymptotic normality of these estimators and present some simulation examples to support our result. Full article
(This article belongs to the Special Issue Stochastic Statistics and Modeling)
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Open AccessArticle
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
Molecules 2020, 25(19), 4353; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25194353 (registering DOI) - 23 Sep 2020
Abstract
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. [...] Read more.
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. Different descriptors and different combinations may give different prediction results. We propose feature combination engineering based on correlation coefficients and F-values. The accuracy of our method is 65.38% in independent test set, indicating biological significance. Our predictions are consistent with the experimental results. It shows the effectiveness and reliability of our method to predict interface residue pairs of protein trimers. Full article
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Open AccessReview
Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
Sustainability 2020, 12(19), 7837; https://0-doi-org.brum.beds.ac.uk/10.3390/su12197837 (registering DOI) - 23 Sep 2020
Abstract
Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern [...] Read more.
Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern of grasslands’ sensitivity to any ED event remains unresolved. Here, frameworks were built to predict the sensitivity patterns of above-ground net primary productivity (ANPP) spanning the global precipitation gradient under ED. The frameworks particularly present three sensitivity patterns that could manipulate (weaken, strengthen, or erode) the orthodox positive precipitation–productivity relationship which exists under non-drought (ambient) condition. First, the slope of the relationship could become steeper via higher sensitivity at xeric sites than mesic and hydric ones. Second, if the sensitivity emerges highest in hydric, followed by mesic, then xeric, a weakened slope, flat line, or negative slope would emerge. Lastly, if the sensitivity emerges unexpectedly similar across the precipitation gradient, the slope of the relationship would remain similar to that of the ambient condition. Overall, the frameworks provide background knowledge on possible differences or similarities in responses of grasslands to forecast ED, and could stimulate increase in conduct of experiments to unravel the impacts of ED on grasslands. More importantly, the frameworks indicate the need for reconciliation of conflicting hypotheses of grasslands’ sensitivity to ED through global-scale experiments. Full article
(This article belongs to the Section Climate Change)
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Open AccessArticle
Exploring Metagenomic Enzymes: A Novel Esterase Useful for Short-Chain Ester Synthesis
Catalysts 2020, 10(10), 1100; https://0-doi-org.brum.beds.ac.uk/10.3390/catal10101100 (registering DOI) - 23 Sep 2020
Abstract
Enzyme-mediated esterification reactions can be a promising alternative to produce esters of commercial interest, replacing conventional chemical processes. The aim of this work was to verify the potential of an esterase for ester synthesis. For that, recombinant lipolytic enzyme EST5 was purified and [...] Read more.
Enzyme-mediated esterification reactions can be a promising alternative to produce esters of commercial interest, replacing conventional chemical processes. The aim of this work was to verify the potential of an esterase for ester synthesis. For that, recombinant lipolytic enzyme EST5 was purified and presented higher activity at pH 7.5, 45 °C, with a Tm of 47 °C. Also, the enzyme remained at least 50% active at low temperatures and exhibited broad substrate specificity toward p-nitrophenol esters with highest activity for p-nitrophenyl valerate with a Kcat/Km of 1533 s−1 mM−1. This esterase exerted great properties that make it useful for industrial applications, since EST5 remained stable in the presence of up to 10% methanol and 20% dimethyl sulfoxide. Also, preliminary studies in esterification reactions for the synthesis of methyl butyrate led to a specific activity of 127.04 U·mg−1. The enzyme showed higher esterification activity compared to other literature results, including commercial enzymes such as LIP4 and CL of Candida rugosa assayed with butyric acid and propanol which showed esterification activity of 86.5 and 15.83 U·mg−1, respectively. In conclusion, EST5 has potential for synthesis of flavor esters, providing a concept for its application in biotechnological processes. Full article
(This article belongs to the Special Issue Biocatalytic Applications in Biotechnology)
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Open AccessArticle
Anxiety and the Ecological Crisis: An Analysis of Eco-Anxiety and Climate Anxiety
Sustainability 2020, 12(19), 7836; https://0-doi-org.brum.beds.ac.uk/10.3390/su12197836 (registering DOI) - 23 Sep 2020
Abstract
Eco-anxiety and climate anxiety are widely discussed in contemporary media and are subjects of growing research interest. However, there is a lack of research about the definitions and variations of these phenomena. This article analyzes various views of eco-anxiety from a wide range [...] Read more.
Eco-anxiety and climate anxiety are widely discussed in contemporary media and are subjects of growing research interest. However, there is a lack of research about the definitions and variations of these phenomena. This article analyzes various views of eco-anxiety from a wide range of disciplines. Insights from various anxiety theories are used to discuss empirical studies about forms of eco-anxiety. The article points out that uncertainty, unpredictability, and uncontrollability seem to be important factors in eco-anxiety. Most forms of eco-anxiety appear to be non-clinical, but cases of “pathological” eco-anxiety are also discussed. Other relevant terms and phenomena are scrutinized, such as ecological grief, solastalgia, and ecological trauma. The relationship between studies on eco-anxiety and research about ecological emotions and affect is probed. Eco-anxiety is found to be closely connected to fear and worry, but several disciplines include discussion of its character as existential anxiety. Psychosocial and sociological perspectives point out that social dynamics shape forms of eco-anxiety in profound ways. While paralyzing forms of eco-anxiety emerge as a problem, it is noted that eco-anxiety manifests itself also as “practical anxiety”, which leads to gathering of new information and reassessment of behavior options. This variety of forms of eco-anxiety should be taken into account in healthcare and public discussion. Full article
(This article belongs to the Section Health and Sustainability)
Open AccessArticle
Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly
Nutrients 2020, 12(10), 2900; https://0-doi-org.brum.beds.ac.uk/10.3390/nu12102900 (registering DOI) - 23 Sep 2020
Abstract
Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are [...] Read more.
Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson’s correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in “taurine and hypotaurine metabolism” and “tryptophan metabolism” in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development. Full article
(This article belongs to the Special Issue Metabolomics in Nutrition and Human Health)
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Open AccessArticle
Effect of Addition of PVA/PG to Oil-in-Water Nanoemulsion Kojic Monooleate Formulation on Droplet Size: Three-Factors Response Surface Optimization and Characterization
Cosmetics 2020, 7(4), 73; https://0-doi-org.brum.beds.ac.uk/10.3390/cosmetics7040073 (registering DOI) - 23 Sep 2020
Abstract
An oil in water (O/W) nanoemulsion formulation containing kojic monooleate (KMO) in thin film system was developed. Response surface methodology (RSM) was used to optimize and analyzed the effect of three variables, namely concentration of polyvinyl alcohol (PVA) (20–30% w/w), [...] Read more.
An oil in water (O/W) nanoemulsion formulation containing kojic monooleate (KMO) in thin film system was developed. Response surface methodology (RSM) was used to optimize and analyzed the effect of three variables, namely concentration of polyvinyl alcohol (PVA) (20–30% w/w), concentration of propylene glycol (PG) (1–10% w/w), and shear rate of high shear homogenizer (3000–9000 rpm) on droplet size as a response, while other compositions remained constant such as KMO (10.0% w/w), Tween 80 (3.19% w/w), castor oil (3.74% w/w), xanthan gum (0.70% w/w), and germall plus (0.7% w/w, PG (and) diazolidinyl urea (and) iodopropynyl butylcarbamate). The optimized KMO nanoemulsion formulation with desirable criteria was PVA (27.61% w/w) and PG (1.05% w/w), and shear rate (8656.17 rpm) with a predicted droplet size (110.21 nm) and actual droplet size (105.93 nm) with a residual standard error (RSE) of less than 2.0% was obtained. Analysis of variance (ANOVA) showed that the fitness of the quadratic polynomial fit the experimental data with a F-value of 65.30, p–value of p < 0.0001, and a non-significant lack-of-fit. The optimized KMO formulation shows the desired criteria of the thin film system and the physicochemical properties (Zeta potential −37.37 mV, PDI 0.13, pH 4.74) and stability at four different conditions indicate its suitability for cosmeceutical applications. Full article
(This article belongs to the Special Issue Feature Papers in Cosmetics in 2020)
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Open AccessArticle
Investigating the Status of Cadmium, Chromium and Lead in the Drinking Water Supply Chain to Ensure Drinking Water Quality in Malaysia
Water 2020, 12(10), 2653; https://0-doi-org.brum.beds.ac.uk/10.3390/w12102653 (registering DOI) - 23 Sep 2020
Abstract
Prolonged persistence of toxic cadmium (Cd), chromium (Cr) and lead (Pb) in the aquatic environment are due to its nonbiodegradable characteristic. A few studies have reported higher concentrations of these metals in the transboundary Langat River, Malaysia. This study determined the spatial and [...] Read more.
Prolonged persistence of toxic cadmium (Cd), chromium (Cr) and lead (Pb) in the aquatic environment are due to its nonbiodegradable characteristic. A few studies have reported higher concentrations of these metals in the transboundary Langat River, Malaysia. This study determined the spatial and temporal distributions of Cd, Cr and Pb concentrations (2005–2015) in the Langat River along with assessing the status of these metals in the drinking water supply chain at the basin. Water samples were collected once in 2015 from the drinking water supply chain, i.e., from the river, treated water at plants, taps and filtration water at households. Determined mean concentrations of Cd, Cr and Pb by inductively coupled plasma mass spectrometry in the Langat River were within the drinking water quality standard of Malaysia and the WHO, except for the Pb (9.99 ± 1.40 µg/L) concentration, which was at the maximum limit, 10 µg/L. The spatial and temporal distribution of these metals’ concentrations indicate dilution of it downstream, along with the increasing trend in rainfall and water flow, especially during the northeast monsoon. Significant correlation and regression analysis of the Cd, Cr and Pb concentrations also indicate that the sources of this metal pollution are mainly the natural weathering of minerals along with anthropogenic activities in the basin. The determined overall water quality of the Langat River is categorized Class IIA (i.e., clean), which requires conventional treatment before drinking; however, the maximum removal efficiency of these metals by the plants at the basin was about 90.17%. Therefore, the proactive leadership roles of the local authorities will be appropriate to reduce the pollution of this river as well as introducing a two-layer water filtration system at the Langat River Basin to accelerate the achievement of a sustainable drinking water supply. Full article
(This article belongs to the Special Issue Environmental Chemistry of Water Quality Monitoring)
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Open AccessArticle
Gesture-Based User Interface for Vehicle On-Board System: A Questionnaire and Research Approach
Appl. Sci. 2020, 10(18), 6620; https://0-doi-org.brum.beds.ac.uk/10.3390/app10186620 - 22 Sep 2020
Abstract
Touchless interaction with electronic devices using gestures is gaining popularity and along with speech-based communication offers their users natural and intuitive control methods. Now, these interaction modes go beyond the entertainment industry and are successfully applied in real-life scenarios such as a car [...] Read more.
Touchless interaction with electronic devices using gestures is gaining popularity and along with speech-based communication offers their users natural and intuitive control methods. Now, these interaction modes go beyond the entertainment industry and are successfully applied in real-life scenarios such as a car interior. In the paper, we analyse the potential of hand gesture interaction in the vehicle environment by physically challenged drivers. A survey conducted with potential users shows that the knowledge of gesture-based interaction and its practical use by people with disabilities is low. Based on these results we proposed a gesture-based system for vehicle on-board system. It has been developed on the available state-of-the-art solutions and investigated in terms of usability on a group of people with different physical limitations who drive a car on daily basis mostly using steering aid tools. The obtained results are compared with the performance of users without any disabilities. Full article
(This article belongs to the Special Issue Advances in Image Processing, Analysis and Recognition Technology II)
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Open AccessArticle
MODIS Sensor Capability to Burned Area Mapping—Assessment of Performance and Improvements Provided by the Latest Standard Products in Boreal Regions
Sensors 2020, 20(18), 5423; https://0-doi-org.brum.beds.ac.uk/10.3390/s20185423 - 22 Sep 2020
Abstract
This paper presents an accuracy assessment of the main global scale Burned Area (BA) products, derived from daily images of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Fire_CCI 5.1 and MCD64A1 C6, as well as the previous versions of both products (Fire_CCI 4.1 and MCD45A1 [...] Read more.
This paper presents an accuracy assessment of the main global scale Burned Area (BA) products, derived from daily images of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Fire_CCI 5.1 and MCD64A1 C6, as well as the previous versions of both products (Fire_CCI 4.1 and MCD45A1 C5). The exercise was conducted on the boreal region of Alaska during the period 2000–2017. All the BA polygons registered by the Alaska Fire Service were used as reference data. Both new versions doubled the annual BA estimate compared to the previous versions (66% for Fire_CCI 5.1 versus 35% for v4.1, and 63% for MCD64A1 C6 versus 28% for C5), reducing the omission error (OE) by almost one half (39% versus 67% for Fire_CCI and 48% versus 74% for MCD) and slightly increasing the commission error (CE) (7.5% versus 7% for Fire_CCI and 18% versus 7% for MCD). The Fire_CCI 5.1 product (CE = 7.5%, OE = 39%) presented the best results in terms of positional accuracy with respect to MCD64A1 C6 (CE = 18%, OE = 48%). These results suggest that Fire_CCI 5.1 could be suitable for those users who employ BA standard products in geoinformatics analysis techniques for wildfire management, especially in Boreal regions. The Pareto boundary analysis, performed on an annual basis, showed that there is still a potential theoretical capacity to improve the MODIS sensor-based BA algorithms. Full article
(This article belongs to the Special Issue Remote Sensing and Geoinformatics in Wildfire Management)
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