bluuebunny/crossref_metadata_2025 huggingface dataset:
Sulfur Species, Bonding Environment, and Metal Mobilization in Mining-Impacted Lake Sediments: Column Experiments Replicating Seasonal Anoxia and Deposition of Algal Detritus
Authors: Langman Jeff , Ali Jaabir , Child Andrew , Wilhelm Frank , Moberly James
Published: September 2020

The oxidation state of sulfur [S] is a primary control on mobility of metals in sediments impacted by legacy mining practices. Coeur d’Alene Lake of northern Idaho, USA, has been impacted by upstream legacy mining practices that deposited an estimated 75 Mt of metal(loid)- and S-rich sediments into the lake. Future lake conditions are expected to include algal blooms, which may alter S and metal remobilization during the seasonal euxinic environment. Cores of the lake sediments were exposed to anoxic and anoxic + algal detritus conditions for eight weeks at 4.5 °C through introduction of a N2 atmosphere and addition of algal detritus. At a location 2.5 cm below the sediment-water interface, anoxic conditions promoted a shift in S species to continually larger concentrations of reduced species and an associated shift in the bonding environment reflective of increased S–metal bonds. Anoxic + algal detritus conditions suppressed the increasing trend of reduced S species and induced greater release of Mn compared to the anoxic-only conditions but did not appear to enhance the release of As, Cd, or Fe. The addition of algal detritus to the sediment-water interface of these Fe- and S-rich sediments enhanced mobilization of Mn likely because of dissimilatory metal reduction where the anaerobic oxidation of the algal detritus stimulated Mn reduction. Results of the study indicate that future metal release from the lake sediments will be altered with the likely deposition of algal detritus, but the effect may not enhance the release of acutely toxic metals, such as As or Cd, or substantially impact Fe cycling in the sediments.
A Series of Isatin-Hydrazones with Cytotoxic Activity and CDK2 Kinase Inhibitory Activity: A Potential Type II ATP Competitive Inhibitor
Authors: Al-Salem Huda S. , Arifuzzaman Md , Alkahtani Hamad M. , Abdalla Ashraf N. , Issa Iman S. , Alqathama Aljawharah , Albalawi Fatemah S. , Rahman A. F. M. Motiur
Published: September 2020

Isatin derivatives potentially act on various biological targets. In this article, a series of novel isatin-hydrazones were synthesized in excellent yields. Their cytotoxicity was tested against human breast adenocarcinoma (MCF7) and human ovary adenocarcinoma (A2780) cell lines using MTT assay. Compounds 4j (IC50 = 1.51 ± 0.09 µM) and 4k (IC50 = 3.56 ± 0.31) showed excellent activity against MCF7, whereas compound 4e showed considerable cytotoxicity against both tested cell lines, MCF7 (IC50 = 5.46 ± 0.71 µM) and A2780 (IC50 = 18.96± 2.52 µM), respectively. Structure-activity relationships (SARs) revealed that, halogen substituents at 2,6-position of the C-ring of isatin-hydrazones are the most potent derivatives. In-silico absorption, distribution, metabolism and excretion (ADME) results demonstrated recommended drug likeness properties. Compounds 4j (IC50 = 0.245 µM) and 4k (IC50 = 0.300 µM) exhibited good inhibitory activity against the cell cycle regulator CDK2 protein kinase compared to imatinib (IC50 = 0.131 µM). A molecular docking study of 4j and 4k confirmed both compounds as type II ATP competitive inhibitors that made interactions with ATP binding pocket residues, as well as lacking interactions with active state DFG motif residues.
The Key Role of IP6K: A Novel Target for Anticancer Treatments?
Authors: Minini Mirko , Senni Alice , Unfer Vittorio , Bizzarri Mariano
Published: September 2020

Inositol and its phosphate metabolites play a pivotal role in several biochemical pathways and gene expression regulation: inositol pyrophosphates (PP-IPs) have been increasingly appreciated as key signaling modulators. Fluctuations in their intracellular levels hugely impact the transfer of phosphates and the phosphorylation status of several target proteins. Pharmacological modulation of the proteins associated with PP-IP activities has proved to be beneficial in various pathological settings. IP7 has been extensively studied and found to play a key role in pathways associated with PP-IP activities. Three inositol hexakisphosphate kinase (IP6K) isoforms regulate IP7 synthesis in mammals. Genomic deletion or enzymic inhibition of IP6K1 has been shown to reduce cell invasiveness and migration capacity, protecting against chemical-induced carcinogenesis. IP6K1 could therefore be a useful target in anticancer treatment. Here, we summarize the current understanding that established IP6K1 and the other IP6K isoforms as possible targets for cancer therapy. However, it will be necessary to determine whether pharmacological inhibition of IP6K is safe enough to begin clinical study. The development of safe and selective inhibitors of IP6K isoforms is required to minimize undesirable effects.
Chemometric Assessment of Bulgarian Wastewater Treatment Plants’ Effluents
Authors: Yotova Galina , Venelinov Tony , Tsakovski Stefan
Published: September 2020

Surface water quality strongly depends on anthropogenic activity. Among the main anthropogenic sources of this activity are the wastewater treatment plant (WWTP) effluents. The discharged loads of nutrients and suspended solids could provoke serious problems for receiving water bodies and significantly alter the surface water quality. This study presents inventory analysis and chemometric assessment of WWTP effluents based on the mandatory monitoring data. The comparison between the Bulgarian WWTPs and previously reported data from other countries reveals that discharged loads from investigated WWTPs are lower. This is particularly valid for total suspended solids (TSS). The low TSS loads are the reason for the deviations of the typical calculated WWTP effluent ratios of Bulgarian WWTPs compared to the WWTPs worldwide. The performed multivariate analysis reveals the hidden factors that determine the content of WWTP effluents. The source apportioning based on multivariate curve resolution analysis provides detailed information for source contribution profiles of the investigated WWTP effluent loads and elucidate the difference between WWTPs included in this study.
Targeting Host Defense System and Rescuing Compromised Mitochondria to Increase Tolerance against Pathogens by Melatonin May Impact Outcome of Deadly Virus Infection Pertinent to COVID-19
Authors: Tan Dun-Xian , Hardeland Ruediger
Published: September 2020

Fighting infectious diseases, particularly viral infections, is a demanding task for human health. Targeting the pathogens or targeting the host are different strategies, but with an identical purpose, i.e., to curb the pathogen’s spreading and cure the illness. It appears that targeting a host to increase tolerance against pathogens can be of substantial advantage and is a strategy used in evolution. Practically, it has a broader protective spectrum than that of only targeting the specific pathogens, which differ in terms of susceptibility. Methods for host targeting applied in one pandemic can even be effective for upcoming pandemics with different pathogens. This is even more urgent if we consider the possible concomitance of two respiratory diseases with potential multi-organ afflictions such as Coronavirus disease 2019 (COVID-19) and seasonal flu. Melatonin is a molecule that can enhance the host’s tolerance against pathogen invasions. Due to its antioxidant, anti-inflammatory, and immunoregulatory activities, melatonin has the capacity to reduce the severity and mortality of deadly virus infections including COVID-19. Melatonin is synthesized and functions in mitochondria, which play a critical role in viral infections. Not surprisingly, melatonin synthesis can become a target of viral strategies that manipulate the mitochondrial status. For example, a viral infection can switch energy metabolism from respiration to widely anaerobic glycolysis even if plenty of oxygen is available (the Warburg effect) when the host cell cannot generate acetyl-coenzyme A, a metabolite required for melatonin biosynthesis. Under some conditions, including aging, gender, predisposed health conditions, already compromised mitochondria, when exposed to further viral challenges, lose their capacity for producing sufficient amounts of melatonin. This leads to a reduced support of mitochondrial functions and makes these individuals more vulnerable to infectious diseases. Thus, the maintenance of mitochondrial function by melatonin supplementation can be expected to generate beneficial effects on the outcome of viral infectious diseases, particularly COVID-19.
Influence of SERS Activity of SnSe2 Nanosheets Doped with Sulfur
Authors: Tian Yuan , Wei Haonan , Xu Yujie , Sun Qianqian , Man Baoyuan , Liu Mei
Published: September 2020

The application of 2D semiconductor nanomaterials in the field of SERS is limited due to its weak enhancement effect and the unclear enhancement mechanism. In this study, we changed the surface morphology and energy level structure of 2D SnSe2 nanosheets using different amounts of S dopant. This caused the vibration coupling of the substrate and the adsorbed molecules and affects the SERS activities of the SnSe2 nanosheets. SERS performance of the 2D semiconductor substrate can effectively be improved by suitable doping, which can effectively break the limitation of 2D semiconductor compounds in SERS detection and will have very important significance in the fields of chemical, biological, and materials sciences. In this work, the intensities of SERS signals for R6G molecules on SnSe0.93S0.94 are 1.3 to 1.7 times stronger than those on pure SnSe2 substrate. It not only provides a new way to effectively improve the SERS activity of a semiconductor SERS substrates but also helps to design more efficient and stable semiconductor SERS substrates for practical application.
Protective Effects of ALDH1A Enzyme Inhibition on Helicobacter-Induced Colitis in Smad3−/− Mice are Associated with Altered α4ß7 Integrin Expression on Activated T Cells
Authors: Seamons Audrey , Haenisch Michael , Meeker Stacey , Pershutkina Olesya , Brabb Thea , Treuting Piper M. , Paik Jisun
Published: September 2020

Many inflammatory bowel disease (IBD) patients require surgical intervention due to limited pharmacological treatment options. Antibodies targeting α4ß7, a gut-homing integrin, are one of the most promising IBD treatments. As retinoic acid (RA) regulates expression of gut-homing proteins including α4ß7 integrin, we tested if ALDH1A enzymes in the RA synthesis pathway could be targeted for IBD treatment using a potent inhibitor, WIN 18,446. Age- and sex-matched Smad3−/− mice were fed a diet with and without WIN 18,446 for 3 weeks before triggering inflammation with Helicobacter bilis infection. Colitis was evaluated by histopathology one week following the IBD trigger, and T cell subsets were evaluated before and after the IBD trigger. WIN 18,446 treatment significantly reduced IBD severity in Smad3−/− mice and reduced expression of α4ß7 integrin on multiple activated CD4+ T cell subsets. This change was associated with increased ratios of induced regulatory T cells to Th17 cells during the inflammatory response in the draining lymph nodes. These studies indicate that RA reduction via ALDH1A enzyme inhibition is a potential new target for IBD treatment. Further studies are needed to examine its effects on other types of immune cells, to evaluate the efficacy window for this target, and to determine its efficacy in other animal models of IBD.
Is There Such a Thing as “Anti-Nutrients”? A Narrative Review of Perceived Problematic Plant Compounds
Authors: Petroski Weston , Minich Deanna M.
Published: September 2020

Plant-based diets are associated with reduced risk of lifestyle-induced chronic diseases. The thousands of phytochemicals they contain are implicated in cellular-based mechanisms to promote antioxidant defense and reduce inflammation. While recommendations encourage the intake of fruits and vegetables, most people fall short of their target daily intake. Despite the need to increase plant-food consumption, there have been some concerns raised about whether they are beneficial because of the various ‘anti-nutrient’ compounds they contain. Some of these anti-nutrients that have been called into question included lectins, oxalates, goitrogens, phytoestrogens, phytates, and tannins. As a result, there may be select individuals with specific health conditions who elect to decrease their plant food intake despite potential benefits. The purpose of this narrative review is to examine the science of these ‘anti-nutrients’ and weigh the evidence of whether these compounds pose an actual health threat.
Diet Quality, Food Groups and Nutrients Associated with the Gut Microbiota in a Nonwestern Population
Authors: García-Vega Ángela S. , Corrales-Agudelo Vanessa , Reyes Alejandro , Escobar Juan S.
Published: September 2020

Diet plays an important role in shaping gut microbiota. However, much remains to be learned regarding this association. We analyzed dietary intake and gut microbiota in a community-dwelling cohort of 441 Colombians. Diet quality, intake of food groups and nutrient consumption were paired with microbial diversity and composition using linear regressions, Procrustes analyses and a random-forest machine-learning algorithm. Analyses were adjusted for potential confounders, including the five cities from where the participants originated, sex (male, female), age group (18–40 and 41–62 years), BMI (lean, overweight, obese) and socioeconomic status. Microbial diversity was higher in individuals with increased intake of nutrients obtained from plant-food sources, whereas the intake of food groups and nutrients correlated with microbiota structure. Random-forest regressions identified microbial communities associated with different diet components. Two remarkable results confirmed previous expectations regarding the link between diet and microbiota: communities composed of short-chain fatty acid (SCFA) producers were more prevalent in the microbiota of individuals consuming diets rich in fiber and plant-food sources, such as fruits, vegetables and beans. In contrast, an inflammatory microbiota composed of bile-tolerant and putrefactive microorganisms along with opportunistic pathogens thrived in individuals consuming diets enriched in animal-food sources and of low quality, i.e., enriched in ultraprocessed foods and depleted in dietary fiber. This study expands our understanding of the relationship between dietary intake and gut microbiota. We provide evidence that diet is strongly associated with the gut microbial community and highlight generalizable connections between them.
Impacts of Calorie Restriction and Intermittent Fasting on Health and Diseases: Current Trends
Authors: Chung Hae Young , Kim Dae Hyun , Bang EunJin , Yu Byung Pal
Published: September 2020

This special issue on the effects of calorie restriction (CR) and intermittent fasting (IF) on health and diseases includes five scholarly reviews and four original articles that provide an insight into the molecular and cellular action mechanisms of epigenetically manipulated dietary paradigms [...]
Inhibition of Mixed Biofilms of Candida albicans and Methicillin-Resistant Staphylococcus aureus by Positively Charged Silver Nanoparticles and Functionalized Silicone Elastomers
Authors: Lara Humberto H. , Lopez-Ribot Jose L.
Published: September 2020

Both bacterial and fungal organisms display the ability to form biofilms; however, mixed bacterial/fungal biofilms are particularly difficult to control and eradicate. The opportunistic microbial pathogens Candida albicans and Staphylococcus aureus are among the most frequent causative agents of healthcare-acquired infections, and are often co-isolated forming mixed biofilms, especially from contaminated catheters. These mixed species biofilms display a high level of antibiotic resistance; thus, these infections are challenging to treat resulting in excess morbidity and mortality. In the absence of effective conventional antibiotic treatments, nanotechnology-based approaches represent a promising alternative for the treatment of highly recalcitrant polymicrobial biofilm infections. Our group has previously reported on the activity of pure positively charged silver nanoparticles synthesized by a novel microwave technique against single-species biofilms of C. albicans and S. aureus. Here, we have expanded our observations to demonstrate that that silver nanoparticles display dose-dependent activity against dual-species C. albicans/S. aureus biofilms. Moreover, the same nanoparticles were used to functionalize catheter materials, leading to the effective inhibition of the mixed fungal/bacterial biofilms. Overall, our results indicate the potent activity of silver nanoparticles against these cross-kingdom biofilms. More studies are warranted to examine the ability of functionalized catheters in the prevention of catheter-related bloodstream infections.
Sequence Permutation Generates Peptides with Different Antimicrobial and Antibiofilm Activities
Authors: Mishra Biswajit , Lakshmaiah Narayana Jayaram , Lushnikova Tamara , Zhang Yingxia , Golla Radha M. , Zarena D. , Wang Guangshun
Published: September 2020

Antibiotic resistance poses a threat to our society, and 10 million people could die by 2050. To design potent antimicrobials, we made use of the antimicrobial peptide database (APD). Using the database filtering technology, we identified a useful template and converted it into an effective peptide WW291 against methicillin-resistant Staphylococcus aureus (MRSA). Here, we compared the antibacterial activity and cytotoxicity of a family of peptides obtained from sequence permutation of WW291. The resulting eight WW peptides (WW291-WW298) gained different activities against a panel of bacteria. While WW295 inhibited the growth of Escherichia coli, WW298 was highly active against S. aureus USA300 LAC. Consistently with this, WW298 was more effective in permeating or depolarizing the S. aureus membranes, whereas WW295 potently permeated the E. coli membranes. In addition, WW298, but not WW295, inhibited the MRSA attachment and could disrupt its preformed biofilms more effectively than daptomycin. WW298 also protected wax moths Galleria mellonella from MRSA infection causing death. Thus, sequence permutation provides one useful avenue to generating antimicrobial peptides with varying activity spectra. Taken together with amino acid composition modulation, these methods may lead to narrow-spectrum peptides that are more promising to selectively eliminate invading pathogens without damaging commensal microbiota.
Development of Metronidazole Loaded Chitosan Nanoparticles Using QbD Approach—A Novel and Potential Antibacterial Formulation
Authors: Sreeharsha Nagaraja , Rajpoot Kuldeep , Tekade Muktika , Kalyane Dnyaneshwar , Nair Anroop B. , Venugopala Katharigatta N. , Tekade Rakesh K.
Published: September 2020

The aim of this study was to design, optimize, and develop metronidazole (Met) loaded nanoparticles (MetNp) by employing quality-based design (QbD) as well as a risk assessment methodology. A fractional factorial design was used by selecting five independent variables viz., chitosan concentration, tripolyphosphate concentration, and acetic acid concentration as material attributes, stirring speed, and stirring time as process parameters, whereby their influence on two dependent variables such as particle size (PS) and %entrapment efficiency (%EE) was studied. MetNp were synthesized by employing an ionic-gelation technique and optimized formula obtained from the QbD design study. PS and %EE studies revealed the formation of MetNp with 558.06 ± 2.52 nm and 59.07 ± 2.15%, respectively. Furthermore, a Met release study in various simulated gastro-intestinal media suggested pH-triggered (pH > 7.0) and sustained release profile of Met from Eudragit S100 enteric-coated MetNp capsule (MetNp cap). Moreover, the stability investigation of formulations confirmed good stability with respect to their PS and residual drug content (RDC) at different temperature conditions. In conclusion, the QbD method was effectively utilized in the development of MetNp and enteric-coated MetNp cap depicting their potential to release Met through MetNp cap only in the colon region and can be utilized for the treatment of amoebiasis in the colon.
Tunable THz Pulses Generation in Non-Equilibrium Magnetized Plasma: The Role of Plasma Kinetics
Authors: Bogatskaya Anna , Gnezdovskaia Nelli , Popov Alexander
Published: September 2020

In this paper the theoretical model to consider the influence of kinetic properties of nonequilibrium two-color plasma during the THz pulses generation in the presence of static magnetic field is developed. It is shown that applying a static magnetic field on a gas along the direction of propagation of an ionizing two-color laser pulse allows one to produce two-frequency emissions in THz range with tunable central frequency and bandwidth, which are strongly dependent on electron velocity distribution function (EVDF) formed in the plasma as well as relations between collisional, plasma and cyclotron frequencies.
Genome-Wide Discovery of InDel Markers in Sesame (Sesamum indicum L.) Using ddRADSeq
Authors: Kizil Sibel , Basak Merve , Guden Birgul , Tosun Hilal Sule , Uzun Bulent , Yol Engin
Published: September 2020

The development and validation of different types of molecular markers is crucial to conducting marker-assisted sesame breeding. Insertion-deletion (InDel) markers are highly polymorphic and suitable for low-cost gel-based genotyping. From this perspective, this study aimed to discover and develop InDel markers through bioinformatic analysis of double digest restriction site-associated DNA sequencing (ddRADSeq) data from 95 accessions belonging to the Mediterranean sesame core collection. Bioinformatic analysis indicated the presence of 7477 InDel positions genome wide. Deletions accounted for 61% of the InDels and short deletions (1–2 bp) were the most abundant type (94.9%). On average, InDels of at least 2 bp in length had a frequency of 2.99 InDels/Mb. The 86 InDel sites having length ≥8 bp were detected in genome-wide analysis. These regions can be used for the development of InDel markers considering low-cost genotyping with agarose gels. In order to validate these InDels, a total of 38 InDel regions were selected and primers were successfully amplified. About 13% of these InDels were in the coding sequences (CDSs) and in the 3′- and 5′- untranslated regions (UTRs). Furthermore, the efficiencies of these 16 InDel markers were assessed on 32 sesame accessions. The polymorphic information content (PIC) of these 16 markers ranged from 0.06 to 0.62 (average: 0.33). These results demonstrated the success of InDel identification and marker development for sesame with the use of ddRADSeq data. These agarose-resolvable InDel markers are expected to be useful for sesame breeders.
Improved Porosity of Insect Proof Screens Enhances Quality Aspects of Zucchini Squash without Compromising the Yield
Authors: Formisano Luigi , Pannico Antonio , El-Nakhel Christophe , Starace Giuseppe , Poledica Milena , Pascale Stefania De , Rouphael Youssef
Published: September 2020

In a global climate change environment, assuring optimal growing conditions is a difficult challenge, compromising the food supply for a rapidly rising population. The climatic conditions in the protected environment lead to high temperatures and fast insect development, impacting productivity and vegetables qualitative attributes. Consumers’ interest in healthy food requires sustainable tools to manage biotic and abiotic factors and, from this perspective, anti-insect nets represent an excellent “green” solution. For this purpose, our goal was to compare two different anti-insect nets on microclimate, production, and qualitative traits of Cucurbita pepo L. fresh fruits. The experiment was conducted in three separate polyethylene high tunnels, with 50 mesh anti-insect nets of different porosities being installed on the openings of two tunnels, while the third tunnel was a control without nets. Microclimate measurements, as well as yield, physiological, and phytochemicals variables, were assessed. The 50 mesh net led to a decrease in marketable yield (22.5%), fruit number (18.0%), CO2 net assimilation rate (6.0%), and transpiration rate (29.5%). Total soluble solids, antioxidant activities and total ascorbic acid concentration had an opposite trend. The 50 mesh AirPlus net improved quality aspects of zucchini fruits by increasing total ascorbic acid, total phenols, and antioxidant compounds, with no negative impact on yield.
Structure and Properties of Polyamide Fabrics with Insect-Repellent Functionality by Electrospinning and Oxygen Plasma-Treated Surface Coating
Authors: Xiang Chunhui , Etrick Nicholas R. , Frey Margaret W. , Norris Edmund J. , Coats Joel R.
Published: September 2020

The need for light-weight and high-strength insect-repellant fabrics is of critical importance to the cessation of viral diseases. The goal of the study is to investigate the structure and properties of insect-repellent polyamide fabrics for use in protective garments to guard against mosquitos. Permethrin was applied to the polyamide fabrics through incorporation into the nylon 6 polymer solution during electrospinning and dip coating onto the control untreated and oxygen plasma-treated polyamide fabrics: electropun nylon 6 nanofiber nonwovens, commercially available nylon 6 warp knit tricot, and nylon 66 double weft, knit interlock fabrics. The incorporation of permethrin into the polymer solution before the formation of fibers demonstrated the most efficient way to apply permethrin to the fiber/fabric systems. The plasma treatment significantly increased the amount of permethrin on the surface of the fabrics. All permethrin-containing polyamide fabrics showed excellent fastness of the insecticide to light. The electrospun nylon 6 nonwovens demonstrated the best fastness to washing among the plasma-treated electrospun nylon 6, nylon 66 double weft knit, and nylon 6 warp-knit tricot. All permethrin-treated fabrics were repellent and caused higher percentage of mosquito escape compared to the control untreated fabrics.
Influence of the Processing Conditions on the Mechanical Performance of Sustainable Bio-Based PLA Compounds
Authors: Patti Antonella , Acierno Domenico , Latteri Alberta , Tosto Claudio , Pergolizzi Eugenio , Recca Giuseppe , Cristaudo Mirko , Cicala Gianluca
Published: September 2020

Cellulose/PLA-based blends (up to 77 vol./vol.% of the added fibers) for applications in extrusion-based technology were realized in an internal mixer by setting different operating conditions. In particular, both the mixing time and temperature were increased in order to simulate a recycling operation (10 or 25 min, 170 or 190 °C) and gain information on the potential reuse of the developed systems. The torque measurements during the compound’s preparation, and the compound’s mechanical tensile features, both in the static and dynamic mode, were evaluated for each investigated composition. The final results confirmed a reduction of the torque trend over time for the PLA matrix, which was attributed to a possible degradation mechanism, and confirmed by infrared spectroscopy. The mechanical behaviour of the pristine polymer changed from elastoplastic to brittle, with a significant loss in ductility going from the lower mixing temperatures up to the higher ones for the longest time. Through the addition of cellulose fibers into the composite systems, a higher stabilization of the torque in the time and an improvement in the mechanical performance were always verified compared to the neat PLA, with a maximum increase in the Young modulus (+100%) and the tensile strength (+57%), and a partial recovery of the ductility.
Microfluidic Fabrication of Monodisperse Microcapsules for Thermo-Triggered Release of Liposoluble Drugs
Authors: Wang Yuanyuan , Li Yongyue , Gong Jinghua , Ma Jinghong
Published: September 2020

Here, we report a novel thermo-triggered-releasing microcapsule for liposoluble drug delivery. Monodisperse microcapsules with a poly(N-isopropylacrylamide-co-methacrylic acid) hydrogel shell and an oil core were successfully fabricated by a double coaxial microfluidic device. Fluorescent dye Lumogen Red F300 as a model liposoluble drug was dissolved in the oil core with controllable loading capacity. The volume phase transition temperature (VPTT) of the microcapsule was adjusted by copolymerizing with the hydrophilic methacrylic acid. The in vitro release study demonstrates that the shells shrink, leading to the thermo-triggered release of the model drug from the microcapsules at the environmental temperature above the VPTT, while the swollen hydrogel shells can protect the encapsulated drug from leakage and contamination below the VPTT. The proposed microcapsule is a promising liposoluble drug delivery system with controllable loading and smart thermo-triggered release.
Effect of Hydration Layer on the Adsorption of Dodecane Collector on Low-Rank Coal: A Molecular Dynamics Simulation Study
Authors: Liu Lingyun , Qiao Erle , Shen Liang , Min Fanfei , Xue Changguo
Published: September 2020

The hydration layer has a significant effect on the adsorption behavior of reagents during the flotation process of low-rank coal. Understanding the effect of hydration layer on the adsorption of common collectors on low-rank coal is a prerequisite for proposing a new enhanced coal floatation method. In this study, a smooth low-rank coal surface model with a density of 1.2 g/cm3 was constructed and compared with the XPS results. Three different systems, coal-water, coal-collector, and coal-water-collector, were constructed. Molecular dynamics method was applied to study the adsorption behaviors of water and dodecane molecules. Simulation results revealed that a stable hydration layer with a thickness of about 5 Å was formed due to the strong attraction of coal surface. The negative value of interaction energy (IE) indicated that dodecane molecules could spontaneously adsorb on the coal surface. Dodecane molecules were successfully adsorbed on the coal surface when it was located inside the hydration layer. While the dodecane molecule was outside the hydration layer, it could not pass through the hydration layer on the surface of low-rank coal.
Quantile Credibility Models with Common Effects
Authors: Wang Wei , Wen Limin , Yang Zhixin , Yuan Quan
Published: September 2020

Different from classical Bühlmann and Bühlmann Straub credibility models in which independence between different risks are assumed, this paper takes dependence between risks into consideration and extends the classical Bühlmann model by introducing a common stochastic shock element. What is more, instead of relying on complete information of historical data, we aim to derive the premium using quantile of the available data. By the method of linear regression, we manage to obtain the quantile credibility premium with common effects. Our result is the generalization of existing results in credibility theory. Both quantile credibility model proposed by Pitselis (2013) and credibility premium for models with dependence induced by common effects obtained by Wen et al. (2009) are special cases of our model. Numerical simulations are also presented to illustrate the impact of quantile credibility with common effect.
Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
Authors: AlAttar Ahmad , Kormushev Petar
Published: September 2020

Conventional control of robotic manipulators requires prior knowledge of their kinematic structure. Model-learning controllers have the advantage of being able to control robots without requiring a complete kinematic model and work well in less structured environments. Our recently proposed Encoderless controller has shown promising ability to control a manipulator without requiring any prior kinematic model whatsoever. However, this controller is only limited to position control, leaving orientation control unsolved. The research presented in this paper extends the state-of-the-art kinematic-model-free controller to handle orientation control to manipulate a robotic arm without requiring any prior model of the robot or any joint angle information during control. This paper presents a novel method to simultaneously control the position and orientation of a robot’s end effector using locally weighted dual quaternions. The proposed novel controller is also scaled up to control three-degrees-of-freedom robots.
A High-Performance Spectral-Spatial Residual Network for Hyperspectral Image Classification with Small Training Data
Authors: Khotimah Wijayanti Nurul , Bennamoun Mohammed , Boussaid Farid , Sohel Ferdous , Edwards David
Published: September 2020

In this paper, we propose a high performance Two-Stream spectral-spatial Residual Network (TSRN) for hyperspectral image classification. The first spectral residual network (sRN) stream is used to extract spectral characteristics, and the second spatial residual network (saRN) stream is concurrently used to extract spatial features. The sRN uses 1D convolutional layers to fit the spectral data structure, while the saRN uses 2D convolutional layers to match the hyperspectral spatial data structure. Furthermore, each convolutional layer is preceded by a Batch Normalization (BN) layer that works as a regularizer to speed up the training process and to improve the accuracy. We conducted experiments on three well-known hyperspectral datasets, and we compare our results with five contemporary methods across various sizes of training samples. The experimental results show that the proposed architecture can be trained with small size datasets and outperforms the state-of-the-art methods in terms of the Overall Accuracy, Average Accuracy, Kappa Value, and training time.
Object Detection in UAV Images via Global Density Fused Convolutional Network
Authors: Zhang Ruiqian , Shao Zhenfeng , Huang Xiao , Wang Jiaming , Li Deren
Published: September 2020

Object detection in Unmanned Aerial Vehicle (UAV) images plays fundamental roles in a wide variety of applications. As UAVs are maneuverable with high speed, multiple viewpoints, and varying altitudes, objects in UAV images are distributed with great heterogeneity, varying in size, with high density, bringing great difficulty to object detection using existing algorithms. To address the above issues, we propose a novel global density fused convolutional network (GDF-Net) optimized for object detection in UAV images. We test the effectiveness and robustness of the proposed GDF-Nets on the VisDrone dataset and the UAVDT dataset. The designed GDF-Net consists of a Backbone Network, a Global Density Model (GDM), and an Object Detection Network. Specifically, GDM refines density features via the application of dilated convolutional networks, aiming to deliver larger reception fields and to generate global density fused features. Compared with base networks, the addition of GDM improves the model performance in both recall and precision. We also find that the designed GDM facilitates the detection of objects in congested scenes with high distribution density. The presented GDF-Net framework can be instantiated to not only the base networks selected in this study but also other popular object detection models.
Variational Based Estimation of Sea Surface Temperature from Split-Window Observations of INSAT-3D/3DR Imager
Authors: Gangwar Rishi Kumar , Thapliyal Pradeep Kumar
Published: September 2020

Infrared (IR) radiometers from geostationary (GEO) satellites have an advantage over low-earth orbiting (LEO) satellites as they provide continuous observations to monitor the diurnal variations in the sea surface temperature (SST), typically better than 30-minute interval. However, GEO satellite observations suffer from significant diurnal and seasonal biases arising due to varying sun-earth-satellite geometry, leading to biases in SST estimates from conventional non-linear regression-based algorithms (NLSST). The midnight calibration issue occurring in GEO sensors poses a different challenge altogether. To mitigate these issues, we propose SST estimation from split-window IR observations of INSAT-3D and 3DR Imagers using One-Dimensional Variational (1DVAR) scheme. Prior to SST estimation, the bias correction in Imager observations is carried out using cumulative density function (CDF) matching. Then NLSST and 1DVAR algorithms were applied on six months of INSAT-3D/3DR observations to retrieve the SST. For the assessment of the developed algorithms, the retrieved SST was validated against in-situ SST measurements available from in-situ SST Quality Monitor (iQuam) for the study period. The quantitative assessment confirms the superiority of the 1DVAR technique over the NLSST algorithm. However, both the schemes under-estimate the SST as compared to in-situ SST, which may be primarily due to the differences in the retrieved skin SST versus bulk in-situ SST. The 1DVAR scheme gives similar accuracy of SST for both INSAT-3D and 3DR with a bias of −0.36 K and standard deviation (Std) of 0.63 K. However, the NLSST algorithm provides slightly less accurate SST with bias (Std) of −0.18 K (0.87 K) for INSAT-3DR and −0.27 K (0.95 K) for INSAT-3D. Both the NLSST and 1DVAR algorithms are capable of producing the accurate thermal gradients from the retrieved SST as compared to the gradients calculated from daily Multiscale Ultrahigh Resolution (MUR) level-4 analysis SST acquired from Group for High-Resolution Sea Surface Temperature (GHRSST). Based on these spatial gradients, thermal fronts can be generated that are very useful for predicting potential fishery zones (PFZ), which is available from GEO satellites, INSAT-3D/3DR, in near real-time at 15-minute intervals. Results from the proposed 1DVAR and NLSST algorithms suggest a marked improvement in the SST estimates with reduced diurnal/seasonal biases as compared to the operational NLSST algorithm.
Missing Pixel Reconstruction on Landsat 8 Analysis Ready Data Land Surface Temperature Image Patches Using Source-Augmented Partial Convolution
Authors: Chen Maosi , Sun Zhibin , Newell Benjamin H. , Corr Chelsea A. , Gao Wei
Published: September 2020

Missing pixels is a common issue in satellite images. Taking Landsat 8 Analysis Ready Data (ARD) Land Surface Temperature (LST) image as an example, the Source-Augmented Partial Convolution v2 model (SAPC2) is developed to reconstruct missing pixels in the target LST image with the assistance of a collocated complete source image. SAPC2 utilizes the partial convolution enabled U-Net as its framework and accommodates the source into the framework by: (1) performing the shared partial convolution on both the source and the target in encoders; and (2) merging the source and the target by using the partial merge layer to create complete skip connection images for the corresponding decoders. The optimized SAPC2 shows superior performance to four baseline models (i.e., SAPC1, SAPC2-OPC, SAPC2-SC, and STS-CNN) in terms of nine validation metrics. For example, the masked MSE of SAPC2 is 7%, 20%, 44%, and 59% lower than that of the four baseline models. On the six scrutinized cases, the repaired target images generated by SAPC2 have the fewest artifacts near the mask boundary and the best recovery of color scales and fine textures compared with the four baseline models.
Improving PSI Processing of Mining Induced Large Deformations with External Models
Authors: Du Sen , Mallorqui Jordi J. , Fan Hongdong , Zheng Meinan
Published: September 2020

Ground subsidences, either caused by natural phenomena or human activities, can threaten the safety of nearby infrastructures and residents. Among the different causes, mining operations can trigger strong subsidence phenomena with a fast nonlinear temporal behaviour. Therefore, a reliable and precise deformation monitoring is of great significance for safe mining and protection of facilities located above or near the mined-out area. Persistent Scatterer Interferometry (PSI) is a technique that uses stacks Synthetic Aperture Radar (SAR) images to remotely monitor the ground deformation of large areas with a high degree of precision at a reasonable cost. Unfortunately, PSI presents limitations when monitoring large gradient deformations when there is phase ambiguity among adjacent Persistent Scatterer (PS) points. In this paper, an improvement of PSI processing, named as External Model-based Deformation Decomposition PSI (EMDD-PSI), is proposed to address this limitation by taking advantage of an external model. The proposed method first uses interferograms generated from SAR Single Look Complex (SLC) images to optimize the parameter adjustments of the external model. Then, the modelled spatial distribution of subsidence is utilized to reduce the fringes of the interferograms generated from the SAR images and to ease the PSI processing. Finally, the ground deformation is retrieved by jointly adding the external model and PSI results. In this paper, fourteen Radarsat-2 SAR images over Fengfeng mining area (China) are used to demonstrate the capabilities of the proposed method. The results are evaluated by comparing them with leveling data of the area covering the same temporal period. Results have shown that, after the optimization, the model is able to mimic the real deformation and the fringes of the interferograms can be effectively reduced. As a consequence, the large gradient deformation then can be better retrieved with the preservation of the nonlinear subsidence term. The ground truth shows that, comparing with the classical PSI and PSI with unadjusted parameters, the proposed scheme reduces the error by 35.2% and 20.4%, respectively.
Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019)
Authors: Chen Junhan , Yan Feng , Lu Qi
Published: September 2020

Vegetation is the terrestrial ecosystem component most sensitive to climate change. The Qinghai–Tibet Plateau (QTP), characterized by a cold climate and vulnerable ecosystems, has experienced significant warming in previous decades. Identifying the variation in vegetation coverage and elucidating its main driving factors are critical for ecological protection on the QTP. In this study, MOD13A2 Normalized Difference Vegetation Index (NDVI) data in the growing season (May to September) was used to represent QTP vegetation coverage during 2000–2019. The univariate linear regression, partial correlation analysis, residual analysis, and the Hurst exponent were used to detect the vegetation spatiotemporal dynamic, analyze the relationship between the vegetation and main driving factors, and predict the future vegetation dynamic. The growing season NDVI (GNDVI) of the QTP showed an extremely significant rate of increase (0.0011/a) during the study period, and 79.29% of the vegetated areas showed a greening trend. Over the past 20 years, the northeast, mid-east, and western edges of the plateau have been cooling and wetting, while the southwest, mid-west, and southeast have been warming and drying. Different climatic conditions lead to spatial differences in the response of plateau vegetation to climatic factors with generally 1–4 months lag time. The vegetation in the north of the plateau was mainly positively correlated with moisture, and negatively correlated with temperature, while the southern part showed positive correlation with temperature and negative correlation with moisture. Due to the enhancement of cooling and wetting trend in the last decade (2010–2019), especially in the south of the plateau, the greening trend of the plateau vegetation slowed down appreciably and even degraded in some areas. Human activities were mainly concentrated in the eastern part of the plateau—and its positive effect on vegetation was gradually increasing in most areas during study period, especially in the northeastern part. However, vegetation degradation caused by human activities in the southeast of the plateau should not be ignored. The future vegetation dynamic based on the Hurst exponent showed that the plateau faces a higher risk of vegetation degradation, which deserves more attention. This study explored the effect of climatic factors and human activities on vegetation of the QTP, thereby providing some guidance for the study of vegetation dynamic in the alpine areas.
Hybrid Memetic Algorithm for the Node Location Problem in Local Positioning Systems
Authors: Díez-González Javier , Verde Paula , Ferrero-Guillén Rubén , Álvarez Rubén , Pérez Hilde
Published: September 2020

Local Positioning Systems (LPS) have shown excellent performance for applications that demand high accuracy. They rely on ad-hoc node deployments which fit the environment characteristics in order to reduce the system uncertainties. The obtainment of competitive results through these systems requires the solution of the Node Location Problem (finding the optimal cartesian coordinates of the architecture sensors). This problem has been assigned as NP-Hard, therefore a heuristic solution is recommended for addressing this complex problem. Genetic Algorithms (GA) have shown an excellent trade-off between diversification and intensification in the literature. However, in Non-Line-of-Sight (NLOS) environments in which there is not continuity in the fitness function evaluation of a particular node distribution among contiguous solutions, challenges arise for the GA during the exploration of new potential regions of the space of solutions. Consequently, in this paper, we first propose a Hybrid GA with a combination of the GA operators in the evolutionary process for the Node Location Problem. Later, we introduce a Memetic Algorithm (MA) with a Local Search (LS) strategy for exploring the most different individuals of the population in search of improving the previous results. Finally, we combine the Hybrid Genetic Algorithm (HGA) and Memetic Algorithm (MA), designing an enhanced novel methodology for solving the Node Location Problem, a Hybrid Memetic Algorithm (HMA). Results show that the HMA proposed in this article outperforms all of the individual configurations presented and attains an improvement of 14.2% in accuracy for the Node Location Problem solution in the scenario of simulations with regards to the previous GA optimizations of the literature.
Deep Quality Assessment of a Solar Reflector Based on Synthetic Data: Detecting Surficial Defects from Manufacturing and Use Phase
Authors: Papacharalampopoulos Alexios , Tzimanis Konstantinos , Sabatakakis Kyriakos , Stavropoulos Panagiotis
Published: September 2020

Vision technologies are used in both industrial and smart city applications in order to provide advanced value products due to embedded self-monitoring and assessment services. In addition, for the full utilization of the obtained data, deep learning is now suggested for use. To this end, the current work presents the implementation of image recognition techniques alongside the original the quality assessment of a Parabolic Trough Collector (PTC) reflector surface to locate and identify surface irregularities by classifying images as either acceptable or non-acceptable. The method consists of a three-step solution that promotes an affordable implementation in a relatively small time period. More specifically, a 3D Computer Aided Design (CAD) of the PTC was used for the pre-training of neural networks, while an aluminum reflector surface was used to verify algorithm performance. The results are promising, as this method proved applicable in cases where the actual part was manufactured in small batches or under the concept of customized manufacturing. Consequently, the algorithm is capable of being trained with a limited number of data.