bluuebunny/crossref_metadata_2025 huggingface dataset:
Ailanthus altissima Forests Determine a Shift in Herbaceous Layer Richness: A Paired Comparison with Hardwood Native Forests in Sub-Mediterranean Europe
Authors: Montecchiari Silvia , Tesei Giulio , Allegrezza Marina
Published: October 2020

Ailanthus altissima is an invasive alien species (IAS) present throughout Europe and included in the list of alien species of Union concern. In sub-Mediterranean areas of central Italy, there is a lack of knowledge about this invasive species and its interactions with the native forest ecosystems. We aim to find what are the main differences in vegetation structure and floristic diversity between A. altissima forests and native forests through the assessment of the principal ecological parameters that differ between the forest types. We performed 38 phytosociological relevés and sampling of ecological parameters in A. altissima forest communities and neighboring native forests. We analyzed how species richness, diversity, life forms, life strategies, structural characteristics, and ecological parameters changed in A. altissima forests compared with native ones. We found that in A. altissima forests, there is a shift in herbaceous layer richness, with a higher presence of annual ruderal herbs and the absence of herbaceous species linked to the forest environment. The ecological parameters that diverge from the native forests were total nitrogen, total carbon, and C/N ratio. A. altissima forest communities could threaten the biodiversity of the native forest ecosystems in the sub-Mediterranean landscape, favoring ruderal species and inhibiting the presence of typical forest species.
Expression Analysis of Key Auxin Biosynthesis, Transport, and Metabolism Genes of Betula pendula with Special Emphasis on Figured Wood Formation in Karelian Birch
Authors: Tarelkina Tatiana V. , Novitskaya Ludmila L. , Galibina Natalia A. , Moshchenskaya Yulia L. , Nikerova Kseniya M. , Nikolaeva Nadezhda N. , Sofronova Irina N. , Ivanova Diana S. , Semenova Ludmila I.
Published: October 2020

Auxin status in woody plants is believed to be a critical factor for the quantity and quality of the wood formed. It has been previously demonstrated that figured wood formation in Karelian birch (Betula pendula Roth var. carelica (Merckl.) Hämet-Ahti) is associated with a reduced auxin level and elevated sugar content in the differentiating xylem, but the molecular mechanisms of the abnormal xylogenesis remained largely unclear. We have identified genes involved in auxin biosynthesis (Yucca), polar auxin transport (PIN) and the conjugation of auxin with amino acids (GH3) and UDP-glucose (UGT84B1) in the B. pendula genome, and analysed their expression in trunk tissues of trees differing in wood structure. Almost all the investigated genes were overexpressed in Karelian birch trunks. Although Yucca genes were overexpressed, trunk tissues in areas developing figured grain had traits of an auxin-deficient phenotype. Overexpression of GH3s and UGT84B1 appears to have a greater effect on figured wood formation. Analysis of promoters of the differentially expressed genes revealed a large number of binding sites with various transcription factors associated with auxin and sugar signalling. These data agree with the hypothesis that anomalous figured wood formation in Karelian birch may be associated with the sugar induction of auxin conjugation.
Do Compositions of Lipid Fraction Correspond to Species Differentiation in Bupleurum L. (Apiaceae)?
Authors: Tykheev Zhargal Alexandrovich , Anenkhonov Oleg Arnoldovich , Zhigzhitzhapova Svetlana Vasilievna , Taraskin Vasiliy Vladimirovich , Radnaeva Larisa Dorzhievna , Zhang Faqi
Published: October 2020

Bupleurum L. has been widely used in various medical systems as an agent with a wide range of activities. The qualitative composition and content of lipid fraction components of the aerial parts of B. longifolium and B. chinense were elucidated in this work. The available data on the fatty acids (FAs) in Bupleurum plants were compiled and compared with species differentiation in the genus. As a result, the content of FAs in the studied Bupleurum plant species only partially corresponded to the species differentiation and, in some cases, contradicted it. The prognostic value of Bupleurum’s species differentiation for the identification of the potential composition of FAs was insignificant, and it was limited only by particular groups of species. This suggests that a complete phytochemical study of Bupleurum species needs to be conducted to determine the composition of FAs and to identify which species have a similar composition.
Malus domestica: A Review on Nutritional Features, Chemical Composition, Traditional and Medicinal Value
Authors: Patocka Jiri , Bhardwaj Kanchan , Klimova Blanka , Nepovimova Eugenie , Wu Qinghua , Landi Marco , Kuca Kamil , Valis Martin , Wu Wenda
Published: October 2020

Fruit-derived bioactive substances have been spotlighted as a regulator against various diseases due to their fewer side effects compared to chemical drugs. Among the most frequently consumed fruits, apple is a rich source of nutritional molecules and contains high levels of bioactive compounds. The main structural classes of apple constituents include polyphenols, polysaccharides (pectin), phytosterols, and pentacyclic triterpenes. Also, vitamins and trace elements complete the nutritional features of apple fruit. There is now considerable scientific evidence that these bioactive substances present in apple and peel have the potential to improve human health, for example contributing to preventing cardiovascular disease, diabetes, inflammation, and cancer. This review will focus on the current knowledge of bioactive substances in apple and their medicinal value for human health.
Potential Nutraceutical Benefits of In Vivo Grown Saffron (Crocus sativus L.) As Analgesic, Anti-inflammatory, Anticoagulant, and Antidepressant in Mice
Authors: Khan Asif , Muhamad Nur Airina , Ismail Hammad , Nasir Abdul , Khalil Atif Ali Khan , Anwar Yasir , Khan Zahid , Ali Amjad , Taha Rosna Mat , Al-Shara Baker , Latif Sara , Mirza Bushra , Fadladdin Yousef Abdal Jalil , Zeid Isam Mohamed Abu , Al-Thobaiti Saed Ayidh
Published: October 2020

Crocus sativus, a medicinally important herbaceous plant, has been traditionally used to cure coughs, colds, insomnia, cramps, asthma, and pain. Moreover, the therapeutic applications of saffron include its immunomodulatory and anticancer properties. The current experimental analysis was performed to explore the potential nutraceutical efficacy of corm, leaf, petal, and stigma of saffron ethanolic extracts as analgesic, anti-inflammatory, anticoagulant, and antidepressant using hot plate, carrageenan-induced paw edema, capillary tube and forced swim test, respectively in mice. The results indicated that among all the extracts, stigma ethanolic extract (SEE) represented maximum latency activity (72.85%) and edema inhibition (77.33%) followed by petal ethanolic extract (PEE) with latency activity and edema inhibition of 64.06 and 70.50%, respectively. Corm ethanolic extract (CEE) and leaf ethanolic extract (LEE) displayed mild analgesic activity of 22.40% and 29.07%, respectively. Additionally, LEE (53.29%) and CEE (47.47%) exhibited mild to moderate response against inflammation. The coagulation time of SEE (101.66 s) was almost equivalent to the standard drug, aspirin (101.66 s), suggesting a strong anticoagulant effect followed by PEE (86.5 s). LEE (66.83 s) represented moderate inhibitory effect on coagulation activity while CEE (42.83 s) showed neutral effect. Additionally, PEE and SEE also expressed itself as potential antidepressants with immobility time ≤76.66 s, while CEE (96.50 s) and LEE (106.83 s) indicated moderate to mild antidepressant efficacy. Based on the in vivo activities, saffron extract, particularly SEE and PEE, can be used as a potential nutraceutical and therapeutic agent due to its significant pharmacological activities.
Carbohydrate Accumulation and Differential Transcript Expression in Winter Wheat Lines with Different Levels of Snow Mold and Freezing Tolerance after Cold Treatment
Authors: Kruse Erika B. , Revolinski Samuel , Aplin Jesse , Skinner Daniel Z. , Murray Timothy D. , Edwards Charles G. , Carter Arron H.
Published: October 2020

Winter wheat (Triticum aestivum L.) undergoes a period of cold acclimation in order to survive the ensuing winter, which can bring freezing temperatures and snow mold infection. Tolerance of these stresses is conferred in part by accumulation of carbohydrates in the crown region. This study investigates the contributions of carbohydrate accumulation during a cold treatment among wheat lines that differ in their snow mold tolerance (SMT) or susceptibility (SMS) and freezing tolerance (FrT) or susceptibility (FrS). Two parent varieties and eight recombinant inbred lines (RILs) were analyzed. The selected RILs represent four combinations of tolerance: SMT/FrT, SMT/FrS, SMS/FrT, and SMS/FrS. It is hypothesized that carbohydrate accumulation and transcript expression will differ between sets of RILs. Liquid chromatography with a refractive index detector was used to quantify carbohydrate content at eight time points over the cold treatment period. Polysaccharide and sucrose content differed between SMT and SMS RILs at various time points, although there were no significant differences in glucose or fructose content. Glucose and fructose content differed between FrT and FrS RILs in this study, but no significant differences in polysaccharide or sucrose content. RNAseq was used to investigate differential transcript expression, followed by modular enrichment analysis, to reveal potential candidates for other mechanisms of tolerance, which included expected pathways such as oxidative stress, chitinase activity, and unexpected transcriptional pathways. These differences in carbohydrate accumulation and differential transcript expression begin to give insight into the differences of wheat lines when exposed to cold temperatures.
Morphological Variability of Pseudo-nitzschia pungens Clade I (Bacillariophyceae) in the Northwestern Adriatic Sea
Authors: Accoroni Stefano , Giulietti Sonia , Romagnoli Tiziana , Siracusa Melania , Bacchiocchi Simone , Totti Cecilia
Published: October 2020

Pseudo-nitzschia pungens is a common component of the phytoplankton community of the northern Adriatic Sea. In this study, an in-depth morphological analysis of P. pungens was carried out in both cultured strains isolated in different periods and field samples, revealing a surprisingly wide variability in a number of details, with both the gross morphology and ultrastructural levels deviating from the nominal P. pungens. Colonies showed an overlap (from one-third to one-sixth) and a transapical axis (rarely reaching 3 µm), strongly differing from the original description of the species. Moreover, valves may be either symmetrical or slightly asymmetrical, with striae almost always biseriate but sometimes uniseriate or triseriate. Poroids’ morphology in cingular bands was characterized by a wide variability (square, circular, or rectangular poroids without or with up to two hymen sectors), with several combination of them, even within the same cingular band. Phylogenetic analyses based on ITS rDNA showed that the P. pungens of the northern Adriatic Sea belonged to clade I. Domoic acid was not detected.
Glucosinolate Content in Brassica Genetic Resources and Their Distribution Pattern within and between Inner, Middle, and Outer Leaves
Authors: Rhee Ju-Hee , Choi Susanna , Lee Jae-Eun , Hur On-Sook , Ro Na-Young , Hwang Ae-Jin , Ko Ho-Cheol , Chung Yun-Jo , Noh Jae-Jong , Assefa Awraris Derbie
Published: October 2020

Glucosinolates (GSLs) are sulfur-containing secondary metabolites naturally occurring in Brassica species. The purpose of this study was to identify the GSLs, determine their content, and study their accumulation patterns within and between leaves of kimchi cabbage (Brassica rapa L.) cultivars. GSLs were analyzed using UPLC-MS/MS in negative electron-spray ionization (ESI−) and multiple reaction monitoring (MRM) mode. The total GSL content determined in this study ranged from 621.15 to 42434.21 μmolkg−1 DW. Aliphatic GSLs predominated, representing from 4.44% to 96.20% of the total GSL content among the entire samples. Glucobrassicanapin (GBN) contributed the greatest proportion while other GSLs such as glucoerucin (ERU) and glucotropaeolin (TRO) were found in relatively low concentrations. Principal component analysis (PCA) yielded three principal components (PCs) with eigenvalues ≥ 1, altogether representing 74.83% of the total variation across the entire dataset. Three kimchi cabbage (S/No. 20, 4, and 2), one leaf mustard (S/No. 26), and one turnip (S/No. 8) genetic resources were well distinguished from other samples. The GSL content varied significantly among the different positions (outer, middle, and inner) of the leaves and sections (top, middle, bottom, green/red, and white) within the leaves. In most of the samples, higher GSL content was observed in the proximal half and white sections and the middle layers of the leaves. GSLs are regarded as allelochemicals; hence, the data related to the patterns of GSLs within the leaf and between leaves at a different position could be useful to understand the defense mechanism of Brassica plants. The observed variability could be useful for breeders to develop Brassica cultivars with high GSL content or specific profiles of GSLs.
Herbal Combination of Phyllostachys pubescens and Scutellaria baicalensis Inhibits Adipogenesis and Promotes Browning via AMPK Activation in 3T3-L1 Adipocytes
Authors: Sung Yoon-Young , Son Eunjung , Im Gayoung , Kim Dong-Seon
Published: October 2020

To investigate the anti-obesity effects and underlying mechanism of BS21, a combination of Phyllostachys pubescens leaves and Scutellaria baicalensis roots was used to investigate the effects of BS21 on adipogenesis, lipogenesis, and browning in 3T3-L1 adipocytes. The expression of adipocyte-specific genes was observed via Western blot, and the BS21 chemical profile was analyzed using ultra-performance liquid chromatography (UPLC). BS21 treatment inhibited adipocyte differentiation and reduced the expression of the adipogenic proteins peroxisome proliferator-activated receptor γ (PPAR-γ), CCAAT/enhancer-binding protein (C/EBP-α), and adipocyte protein 2 (aP2), as well as the lipogenic proteins sterol regulatory element-binding protein 1c (SREBP-1c) and fatty-acid synthase (FAS). BS21 enhanced protein levels of the beta-oxidation genes carnitine palmitoyltransferase (CPT1) and phospho-acetyl-coA carboxylase (p-ACC). BS21 also induced protein expressions of the browning marker genes PR domain containing 16 (PRDM16), peroxisome proliferator-activated receptor gamma co-activator 1-alpha (PGC1α), and uncoupling protein (UCP) 1, and it induced the expression of the thermogenic gene UCP2. Furthermore, BS21 increased adenosine monophosphate-activated protein kinase (AMPK) activation. UPLC analysis showed that BS21 contains active constituents such as chlorogenic acid, orientin, isoorientin, baicalin, wogonoside, baicalein, tricin, wogonin, and chrysin. Our findings demonstrate that BS21 plays a modulatory role in adipocytes by reducing adipogenesis and lipogenesis, increasing fat oxidation, and inducing browning.
Innovative Hyperbranched Polybenzoxazine-Based Graphene Oxide—Poly(amidoamines) Nanomaterials
Authors: Bîru Elena Iuliana , Gârea Sorina Alexandra , Iovu Horia
Published: October 2020

The covalent functionalization of graphene oxide (GO) surface with hyperbranched benzoxazine (BZ) structures has been achieved using poly(amidoamine) dendrimers (PAMAM) of different generations. By increasing the PAMAM generation, multiple benzoxazine rings were synthesized decorating the GO layers. The polymerization process and the exfoliation behavior were investigated. The novel BZ-functionalized GO hybrid materials were characterized by a combination of techniques such as FT-IR, XPS, and 1H-NMR for the confirmation of benzoxazine formation onto the GO layer surfaces. Raman and XRD investigation showed that the GO stacking layers are highly disintegrated upon functionalization with hyperbranched benzoxazine monomers, the exfoliation being more probably to occur when lower PAMAM generation (G) is involved for the synthesis of hybrid GO-BZ nanocomposites. The polymerization of BZ rings may occur either between the BZ units from the same dendrimer molecule or between BZ units from different dendrimer molecules, thus influencing the intercalation/exfoliation of GO. DSC data showed that the polymerization temperature strongly depends on the PAMAM generation and a significant decrease of this value occurred for PAMAM of higher generation, the polymerization temperature being reduced with ~10 °C in case of GO-PAMAM(G2)-BZ. Moreover, the nanoindentation measurements showed significant mechanical properties improvement in case of GO-PAMAM(G2)-BZ comparing to GO-PAMAM(G0)-BZ in terms of Young modulus (from 0.536 GPa to 1.418 GPa) and stiffness (from 3617 N/m to 9621 N/m).
A Branched Polyelectrolyte Complex Enables Efficient Flame Retardant and Excellent Robustness for Wood/Polymer Composites
Authors: Huang Yanping , Zhang Shuai , Chen He , Ding Chunxiang , Xuan Yan , Pan Mingzhu , Mei Changtong
Published: October 2020

Wood/thermoplastic composites (WPCs) have been restricted in some fields of building construction and electrical equipment because of their inherent high flammability and lower toughness. In this work, a branched crosslinking network polyelectrolyte complex (PEC) has been designed by incorporation of polyethyleneimine (PEI), a cation polyelectrolyte end capped amine groups, into cellulose nanocrystals (CNC), and ammonium polyphosphate (APP) via self-assembling. The hydrogen bonding interactions, penetration, and mechanical interlock provided by PEC effectively enhance the interfacial bonding within matrix, wood fibers, and flame retardant. Interestingly, it generates abundant micropores on the inner structure of WPC. The excellent interfacial bonding performance and easy-to-move molecular chain successfully transfer the stress and induce energy dissipation, simultaneously giving rise to higher strength and toughness for WPC. As well as the PEC endows WPC with a promotion in both smoke suppression and UL-94 V-0 rate. Additionally, the peak heat release rate and total smoke release for WPC obviously reduce by 36.9% and 50.0% respectively in presence of 25% PEC. A simple, eco-friendly, and concise strategy exhibits prospects for fiber-reinforced polymer composites with effective flame retardancy and mechanical robust properties.
Polyacrylonitrile Nanofiber Membrane Modified with Ag/GO Composite for Water Purification System
Authors: Jang Wongi , Yun Jaehan , Park Yejun , Park In Kee , Byun Hongsik , Lee Chang Hyun
Published: October 2020

Silver nanoparticle-modified graphene oxide (Ag/GO) was reliably prepared by using sodium borohydride (NaBH4) in the presence of citric acid capping agent via a simple wet chemistry method. This rapidly formed Ag/GO composite exhibited good dispersity in a solution containing hydrophilic polyacrylonitrile (PAN). Subsequent electrospinning of this precursor solution resulted in the successful formation of nanofibers without any notable defects. The Ag/GO-incorporated PAN nanofibers showed thinner fiber strands (544 ± 82 nm) compared to those of GO-PAN (688 ± 177 nm) and bare-PAN (656 ± 59 nm). Subsequent thermal treatment of nanofibers resulted in the preparation of thin membranes to possess the desired pore property and outstanding wettability. The Ag/GO-PAN nanofiber membrane also showed 30% higher water flux value (390 LMH) than that of bare-PAN (300 LMH) for possible microfiltration (MF) application. In addition, the resulting Ag/GO-PAN nanofiber membrane exhibited antibacterial activity against Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive). Furthermore, this composite membrane exhibited outstanding anti-fouling property compared to the GO-PAN nanofiber membrane in the wastewater treatment. Therefore, the simple modification strategy allows for the effective formation of Ag/GO composite as a filler that can be reliably incorporated into polymer nanofiber membranes to possess improved overall properties for wastewater treatment applications.
Antibacterial Properties and pH Sensitive Swelling of Insitu Formed Silver-Curcumin Nanocomposite Based Chitosan Hydrogel
Authors: Abd El-Hady M. M. , Saeed S. El-Sayed
Published: October 2020

A simple method was used to prepare curcumin/silver nanocomposite based chitosan hydrogel. In an alkaline medium, chitosan and chitosan nanocomposite hydrogels were prepared using the physical crosslinking method. The prepared hydrogels were stable for a long period at room temperature. In one step, silver nanoparticles were prepared insitu using silver nitrate solution and curcumin oxide within the hydrogel network formation. In the meantime, curcumin compound served as both a reducing and stabilizing agent. The structure and surface morphology of nanocomposite hydrogels were characterized by FTIR, SEM, and EDX analysis confirmed the formation of silver nanoparticles within the hydrogel network. Moreover, Images of TEM showed a spherical shape of silver nanoparticles with an average size of 2–10 nm within the matrix of the hydrogel. The formation mechanism of nanocomposite based hydrogel was reported. Besides that, the effect of chitosan and silver nitrate concentrations were studied. The swelling capacity of the prepared nanocomposite hydrogels was also performed at different pH of 4, 7, and 9. From the experimental results, the swelling capacity of hydrogels depends on the concentrations of chitosan and silver nitrate. The prepared composite based hydrogel exceeds a higher swelling degree than chitosan hydrogels at low pH. The antibacterial activity of the nanocomposite hydrogels was also examined; the results showed that the prepared nanocomposite hydrogels outperformed the pure chitosan hydrogels. This shows them to be a promising material for the biomedical field as a wound dressing and drug release.
Parameters Affecting the Mechanical Properties of Three-Dimensional (3D) Printed Carbon Fiber-Reinforced Polylactide Composites
Authors: Lee Demei , Wu Guan-Yu
Published: October 2020

Three-dimensional (3D) printing is a manufacturing technology which creates three-dimensional objects layer-by-layer or drop-by-drop with minimal material waste. Despite the fact that 3D printing is a versatile and adaptable process and has advantages in establishing complex and net-shaped structures over conventional manufacturing methods, the challenge remains in identifying the optimal parameters for the 3D printing process. This study investigated the influence of processing parameters on the mechanical properties of Fused Deposition Modelling (FDM)-printed carbon fiber-filled polylactide (CFR-PLA) composites by employing an orthogonal array model. After printing, the tensile and impact strengths of the printed composites were measured, and the effects of different parameters on these strengths were examined. The experimental results indicate that 3D-printed CFR-PLA showed a rougher surface morphology than virgin PLA. For the variables selected in this analysis, bed temperature was identified as the most influential parameter on the tensile strength of CFR-PLA-printed parts, while bed temperature and print orientation were the key parameters affecting the impact strengths of printed composites. The 45° orientation printed parts also showed superior mechanical strengths than the 90° printed parts.
Motor Fault Detection Using Wavelet Transform and Improved PSO-BP Neural Network
Authors: Lee Chun-Yao , Cheng Yi-Hsin
Published: October 2020

This paper proposes a motor fault detection method based on wavelet transform (WT) and improved PSO-BP neural network which is combined with improved particle swarm optimization (PSO) and a back propagation (BP) neural network with linearly increasing inertia weight. First, this research used WT to analyze the current signals of the healthy motor, bearing damage motor, stator winding inter-turn short circuit motor, and broken rotor bar motor. Second, features after completing the signal analysis were extracted, and three types of classifiers were used to classify. The results show that the improved PSO-BP neural network can effectively detect the cause of failure. In addition, in order to simulate the actual operating environment of the motor, this study added white noise with signal noise ratios of 30 dB, 25 dB, and 20 dB to verify that this model has a better anti-noise ability.
A Novel Consensus Fuzzy K-Modes Clustering Using Coupling DNA-Chain-Hypergraph P System for Categorical Data
Authors: Jiang Zhenni , Liu Xiyu
Published: October 2020

In this paper, a data clustering method named consensus fuzzy k-modes clustering is proposed to improve the performance of the clustering for the categorical data. At the same time, the coupling DNA-chain-hypergraph P system is constructed to realize the process of the clustering. This P system can prevent the clustering algorithm falling into the local optimum and realize the clustering process in implicit parallelism. The consensus fuzzy k-modes algorithm can combine the advantages of the fuzzy k-modes algorithm, weight fuzzy k-modes algorithm and genetic fuzzy k-modes algorithm. The fuzzy k-modes algorithm can realize the soft partition which is closer to reality, but treats all the variables equally. The weight fuzzy k-modes algorithm introduced the weight vector which strengthens the basic k-modes clustering by associating higher weights with features useful in analysis. These two methods are only improvements the k-modes algorithm itself. So, the genetic k-modes algorithm is proposed which used the genetic operations in the clustering process. In this paper, we examine these three kinds of k-modes algorithms and further introduce DNA genetic optimization operations in the final consensus process. Finally, we conduct experiments on the seven UCI datasets and compare the clustering results with another four categorical clustering algorithms. The experiment results and statistical test results show that our method can get better clustering results than the compared clustering algorithms, respectively.
Bioactive and Topographically-Modified Electrospun Membranes for the Creation of New Bone Regeneration Models
Authors: Abdelmoneim Dina , Alhamdani Ghsaq M. , Paterson Thomas E. , Santocildes Romero Martin E. , Monteiro Beatriz J. C. , Hatton Paul V. , Ortega Asencio Ilida
Published: October 2020

Bone injuries that arise from trauma, cancer treatment, or infection are a major and growing global challenge. An increasingly ageing population plays a key role in this, since a growing number of fractures are due to diseases such as osteoporosis, which place a burden on healthcare systems. Current reparative strategies do not sufficiently consider cell-substrate interactions that are found in healthy tissues; therefore, the need for more complex models is clear. The creation of in vitro defined 3D microenvironments is an emerging topographically-orientated approach that provides opportunities to apply knowledge of cell migration and differentiation mechanisms to the creation of new cell substrates. Moreover, introducing biofunctional agents within in vitro models for bone regeneration has allowed, to a certain degree, the control of cell fate towards osteogenic pathways. In this research, we applied three methods for functionalizing spatially-confined electrospun artificial microenvironments that presented relevant components of the native bone stem cell niche. The biological and osteogenic behaviors of mesenchymal stromal cells (MSCs) were investigated on electrospun micro-fabricated scaffolds functionalized with extracellular matrix (ECM) proteins (collagen I), glycosaminoglycans (heparin), and ceramic-based materials (bioglass). Collagen, heparin, and bioglass (BG) were successfully included in the models without modifying the fibrous structures offered by the polycaprolactone (PCL) scaffolds. Mesenchymal stromal cells (MSCs) were successfully seeded in all the biofunctional scaffolds and they showed an increase in alkaline phosphatase production when exposed to PCL/BG composites. This research demonstrates the feasibility of manufacturing smart and hierarchical artificial microenvironments for studying stem cell behavior and ultimately the potential of incorporating these artificial microenvironments into multifunctional membranes for bone tissue regeneration
The Relationship between Mindfulness and Sleep Quality is Mediated by Emotion Regulation
Authors: Talley Garrett , Shelley-Tremblay John
Published: October 2020

Background: Sleep is critical to a person’s overall physical and mental health. The current study investigated the relationship between mindfulness and sleep quality, to determine if this relationship is influenced by emotion regulation and perceived stress. Method: Three hundred sixty-seven undergraduate students responded to five self-report measures, (1) The Cognitive and Affective Mindfulness Scale (CAMS-R), (2) The Impact of Event Scale (IES-R), (3) The Five Facet Mindfulness Questionnaire (FFMQ), (4) The Emotion Regulation Questionnaire (ERQ), and (5) The Pittsburgh Sleep Quality Index (PSQI). Results: Results revealed (1) sleep quality was predicted by the presence of hyperarousal, acting with awareness, and the CAMS-R, (2) the Impact of Event Scale was moderately positively correlated with a person’s global score on the Pittsburgh Sleep Quality Index, and (3) the relationship between mindfulness and sleep quality was mediated by hyperarousal. Conclusions: Together, our findings suggest that higher levels of intrusive thoughts, avoidance, and hyperarousal are correlated with lower overall sleep quality, and the use of mindfulness techniques such as acting with awareness and being non-reacting to negative thoughts or hyperarousal may help predict an individual’s sleep quality.
Introduction: The Making of Sámi Religion in Contemporary Society
Authors: Fonneland Trude , Äikäs Tiina
Published: October 2020

This Special Issue of Religions approaches “Sámi religion” from a long-term perspective seeing both the past religious practices and contemporary religious expressions as aspects of the same phenomena. This does not refer, however, to a focus on continuity or to a static or uniform understanding of Sámi religion. Sámi religion is an ambiguous concept that has to be understood as a pluralistic phenomenon consisting of multiple applications and associations and widely differing interpretations, and that highlights the complexities of processes of religion-making. In a historical perspective and in many contemporary contexts (such as museum displays, media stories, as well as educational programs) the term Sámi religion is mostly used as a reference to Sámi pre-Christian religious practices, to Laestadianism, a Lutheran revival movement that spread among the Sámi during the 19th Century, and last but not least to shamanism. In this issue, we particularly aim to look into contemporary contexts where Sámi religion is expressed, consumed, and promoted. We ask what role it plays in identity politics and heritagization processes, and how different actors connect with distant local religious pasts—in other words, in which contexts is Sámi religion activated, by whom, and for what?
Assessment of Global Ionospheric Maps Performance by Means of Ionosonde Data
Authors: Jerez Gabriel O. , Hernández-Pajares Manuel , Prol Fabricio S. , Alves Daniele B. M. , Monico João F. G.
Published: October 2020

This work presents a new method for assessing global ionospheric maps (GIM) using ionosonde data. The method is based on the critical frequency at the F2 layer directly measured by ionosondes to validate VTEC (vertical total electron content) values from GIMs. The analysis considered four different approaches to using foF2. The study was performed over one of the most challenging scenarios, the Brazilian region, considering four ionosondes (combined in six pairs) and thirteen GIM products available at CDDIS (Crustal Dynamics Data Information System). Analysis was conducted using daily, weekly, one year (2015), and four years (2014–2017) of data. Additional information from the ionosphere was estimated to complement the daily analysis, such as slab thickness and shape function peak. Results indicated that slab thickness and shape function peak could be used as alternative indicators of periods and regions where this method could be applied. The weekly analysis indicated the squared frequency ratio with local time correction as the best approach of using foF2, between the ones evaluated. The analysis of one-year data (2015) was performed considering thirteen GIMs, where CODG and UQRG were the two GIMs that presented the best performance. The four-year time series (2014–2017) were analyzed considering these two products. Regional and temporal ionospheric influences could be noticed in the results, with expected larger errors during the solar cycle peak in 2014 and at locations with pairs of ionosondes with the larger distance apart. Therefore, we have confirmed the viability of the developed approach as an assessment method to analyze GIMs quality based on ionosonde data.
A Quantitative Framework for Analyzing Spatial Dynamics of Flood Events: A Case Study of Super Cyclone Amphan
Authors: Hassan Mohammad Mehedy , Ash Kevin , Abedin Joynal , Paul Bimal Kanti , Southworth Jane
Published: October 2020

Identifying the flooding risk hotspot is crucial for aiding a rapid response and prioritizes mitigation efforts over large disaster impacted regions. While climate change is increasing the risk of floods in many vulnerable regions of the world, the commonly used crisis map is inefficient and cannot rapidly determine the spatial variation and intensity of flooding extension across the affected areas. In such cases, the Local Indicators of Spatial Association (LISA) statistic can detect heterogeneity or the flooding hotspot at a local spatial scale beyond routine mapping. This area, however, has not yet been studied in the context of the magnitude of the floods. The present study incorporates the LISA methodology including Moran’s I and Getis–Ord Gi* to identify the spatial and temporal heterogeneity of the occurrence of flooding from super cyclone Amphan across 16 coastal districts of Bangladesh. Using the Synthetic Aperture Radar (SAR) data from Sentinel-1 and a Support Vector Machine (SVM) classification, “water” and “land” were classified for the pre-event (16 May 2020) and post-events (22 May, 28 May, and 7 June 2020) of the area under study. A Modified Normalized Difference Water Index (MNDWI), and visual comparison were used to evaluate the flood maps. A compelling agreement was accomplished between the observed and predicted flood maps, with an overall precision of above 95% for all SAR classified images. As per this study, 2233 km2 (8%) of the region is estimated to have been inundated on 22 May. After this point, the intensity and aerial expansion of flood decreased to 1490 km2 by 28 May before it increased slightly to 1520 km2 (2.1% of the study area) on 7 June. The results from LISA indicated that the main flooding hotspots were located in the central part, particularly in the region off the north-east of the mangrove forest. A total of 238 Unions (smallest administrative units) were identified as high flooding hotspots (p < 0.05) on 22 May, but the number of flooding hotspots dropped to 166 in the second week (28 May) after Amphan subsided before it increased to a further 208 hotspots (p < 0.05) on 7 June due to incessant rainfall and riverbank failure in the south-west part of the study area. As such, an appropriate, timely, and cost-effective strategy would be to assess existing flooding management policies through the identified flooding hotspot regions. This identification would then allow for the creation of an improved policy to help curtail the destructive effects of flooding in the future.
An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
Authors: Abbasi Bilawal , Qin Zhihao , Du Wenhui , Fan Jinlong , Zhao Chunliang , Hang Qiuyan , Zhao Shuhe , Li Shifeng
Published: October 2020

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO2, ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm2 for the ARMP and 0.26 g/cm2 for the AERONET datasets, with bias of 0.072 g/cm2 and 0.096 g/cm2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales.
Quality Assessment of SAR-to-Optical Image Translation
Authors: Zhang Jiexin , Zhou Jianjiang , Li Minglei , Zhou Huiyu , Yu Tianzhu
Published: October 2020

Synthetic aperture radar (SAR) images contain severe speckle noise and weak texture, which are unsuitable for visual interpretation. Many studies have been undertaken so far toward exploring the use of SAR-to-optical image translation to obtain near optical representations. However, how to evaluate the translation quality is a challenge. In this paper, we combine image quality assessment (IQA) with SAR-to-optical image translation to pursue a suitable evaluation approach. Firstly, several machine-learning baselines for SAR-to-optical image translation are established and evaluated. Then, extensive comparisons of perceptual IQA models are performed in terms of their use as objective functions for the optimization of image restoration. In order to study feature extraction of the images translated from SAR to optical modes, an application in scene classification is presented. Finally, the attributes of the translated image representations are evaluated using visual inspection and the proposed IQA methods.
Multidisciplinary Analysis of Ground Movements: An Underground Gas Storage Case Study
Authors: Benetatos Christoforos , Codegone Giulia , Ferraro Carmela , Mantegazzi Andrea , Rocca Vera , Tango Giorgio , Trillo Francesco
Published: October 2020

The paper presents a multi-physics investigation of the ground movements related to the cyclical and seasonal injection and withdrawal of natural gas in/from a depleted reservoir located in the Po Plain area, Italy. Interferometric Synthetic Aperture Radar (InSAr) data (from 2003) and Global Navigation Satellite System (GNSS) data (from 2008) provided a full and coherent panorama of almost two decades of ground movement in the monitored area (more extended than the field boundary). The analysis of the acquired millimetric-scale movements together with the detailed geological analysis, both at reservoir and at regional scale, represents the focal point for understanding the investigated phenomena. Based on this information, a fully integrated and multidisciplinary geological, fluid-flow and geomechanical numerical modeling approach was developed to reproduce the main geometrical and structural features of the involved formations together with the poromechanics processes induced by the storage operations. The main achievement of the adopted methodology is a deep knowledge of the system and the involved processes, which is mandatory for the safety of the urbanized areas and the effective management of the underground resources.
A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems
Authors: Zhang Liang
Published: October 2020

Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There are two key research gaps for missing sensor data imputation in buildings: the lack of customized and automated imputation methodology, and the difficulty of the validation of data imputation methods. In this paper, a framework is developed to address these two gaps. First, a validation data generation module is developed based on pattern recognition to create a validation dataset to quantify the performance of data imputation methods. Second, a pool of data imputation methods is tested under the validation dataset to find an optimal single imputation method for each sensor, which is termed as an ensemble method. The method can reflect the specific mechanism and randomness of missing data from each sensor. The effectiveness of the framework is demonstrated by 18 sensors from a real campus building. The overall accuracy of data imputation for those sensors improves by 18.2% on average compared with the best single data imputation method.
Cross-Correlation Algorithm-Based Optimization of Aliasing Signals for Inductive Debris Sensors
Authors: Wang Xingjian , Sun Hanyu , Wang Shaoping , Huang Wenhao
Published: October 2020

An inductive debris sensor can monitor a mechanical system’s debris in real time. The measuring accuracy is significantly affected by the signal aliasing issue happening in the monitoring process. In this study, a mathematical model was built to explain two debris particles’ aliasing behavior. Then, a cross-correlation-based method was proposed to deal with this aliasing. Afterwards, taking advantage of the processed signal along with the original signal, an optimization strategy was proposed to make the evaluation of the aliasing debris more accurate than that merely using initial signals. Compared to other methods, the proposed method has fewer limitations in practical applications. The simulation and experimental results also verified the advantage of the proposed method.
Pervasive Lying Posture Tracking
Authors: Alinia Parastoo , Samadani Ali , Milosevic Mladen , Ghasemzadeh Hassan , Parvaneh Saman
Published: October 2020

Automated lying-posture tracking is important in preventing bed-related disorders, such as pressure injuries, sleep apnea, and lower-back pain. Prior research studied in-bed lying posture tracking using sensors of different modalities (e.g., accelerometer and pressure sensors). However, there remain significant gaps in research regarding how to design efficient in-bed lying posture tracking systems. These gaps can be articulated through several research questions, as follows. First, can we design a single-sensor, pervasive, and inexpensive system that can accurately detect lying postures? Second, what computational models are most effective in the accurate detection of lying postures? Finally, what physical configuration of the sensor system is most effective for lying posture tracking? To answer these important research questions, in this article we propose a comprehensive approach for designing a sensor system that uses a single accelerometer along with machine learning algorithms for in-bed lying posture classification. We design two categories of machine learning algorithms based on deep learning and traditional classification with handcrafted features to detect lying postures. We also investigate what wearing sites are the most effective in the accurate detection of lying postures. We extensively evaluate the performance of the proposed algorithms on nine different body locations and four human lying postures using two datasets. Our results show that a system with a single accelerometer can be used with either deep learning or traditional classifiers to accurately detect lying postures. The best models in our approach achieve an F1 score that ranges from 95.2% to 97.8% with a coefficient of variation from 0.03 to 0.05. The results also identify the thighs and chest as the most salient body sites for lying posture tracking. Our findings in this article suggest that, because accelerometers are ubiquitous and inexpensive sensors, they can be a viable source of information for pervasive monitoring of in-bed postures.
Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks
Authors: Chen Xuechen , Xiong Wenjun , Chu Sheng
Published: October 2020

Underwater acoustic sensor networks play an important role in assisting humans to explore information under the sea. In this work, we consider the combination of sensor selection and data routing in three dimensional underwater wireless sensor networks based on Bayesian compressive sensing and particle swarm optimization. The algorithm we proposed is a two-tier PSO approach. In the first tier, a PSO-based clustering protocol is proposed to synthetically consider the energy consumption and uniformity of cluster head distribution. Then in the second tier, a PSO-based routing protocol is proposed to implement inner-cluster one-hop routing and outer-cluster multi-hop routing. The nodes selected to constitute i-th effective routing path decide which positions in the i-th row of the measurement matrix are nonzero. As a result, in this tier the protocol comprehensively considers energy efficiency, network balance and data recovery quality. The Bayesian Cramér-Rao Bound (BCRB) in such a case is analyzed and added in the fitness function to monitor the mean square error of the reconstructed signal. The experimental results validate that our algorithm maintains a longer life time and postpones the appearance of the first dead node while keeps the reconstruction error lower compared with the cutting-edge algorithms which are also based on distributed multi-hop compressive sensing approaches.