bluuebunny/crossref_metadata_2025 huggingface dataset:
Rumen and Hindgut Bacteria Are Potential Indicators for Mastitis of Mid-Lactating Holstein Dairy Cows
Authors: Zhong Yifan , Xue Ming-Yuan , Sun Hui-Zeng , Valencak Teresa G. , Guan Le Luo , Liu Jianxin
Published: December 2020

Mastitis is one of the major problems for the productivity of dairy cows and its classifications have usually been based on milk somatic cell counts (SCCs). In this study, we investigated the differences in milk production, rumen fermentation parameters, and diversity and composition of rumen and hindgut bacteria in cows with similar SCCs with the aim to identify whether they can be potential microbial biomarkers to improve the diagnostics of mastitis. A total of 20 dairy cows with SCCs over 500 × 103 cells/mL in milk but without clinical symptoms of mastitis were selected in this study. Random forest modeling revealed that Erysipelotrichaceae UCG 004 and the [Eubacterium] xylanophilum group in the rumen, as well as the Family XIII AD3011 group and Bacteroides in the hindgut, were the most influential candidates as key bacterial markers for differentiating “true” mastitis from cows with high SCCs. Mastitis statuses of 334 dairy cows were evaluated, and 96 in 101 cows with high SCCs were defined as healthy rather than mastitis according to the rumen bacteria. Our findings suggested that bacteria in the rumen and hindgut can be a new approach and provide an opportunity to reduce common errors in the detection of mastitis.
Biodegradable PLA/PBSA Multinanolayer Nanocomposites: Effect of Nanoclays Incorporation in Multinanolayered Structure on Mechanical and Water Barrier Properties
Authors: Messin Tiphaine , Follain Nadège , Lozay Quentin , Guinault Alain , Delpouve Nicolas , Soulestin Jérémie , Sollogoub Cyrille , Marais Stéphane
Published: December 2020

Biodegradable PLA/PBSA multinanolayer nanocomposites were obtained from semi-crystalline poly(butylene succinate-co-butylene adipate) (PBSA) nanolayers filled with nanoclays and confined against amorphous poly(lactic acid) (PLA) nanolayers in a continuous manner by applying an innovative coextrusion technology. The cloisite 30B (C30B) filler incorporation in nanolayers was considered to be an improvement of barrier properties of the multilayer films additional to the confinement effect resulting to forced assembly during the multilayer coextrusion process. 2049-layer films of ~300 µm thick were processed containing loaded PBSA nanolayers of ~200 nm, which presented certain homogeneity and were mostly continuous for the 80/20 wt% PLA/PBSA composition. The nanocomposite PBSA films (monolayer) were also processed for comparison. The presence of exfoliated and intercalated clay structure and some aggregates were observed within the PBSA nanolayers depending on the C30B content. A greater reduction of macromolecular chain segment mobility was measured due to combined effects of confinement effect and clays constraints. The absence of both polymer and clays interdiffusions was highlighted since the PLA glass transition was unchanged. Besides, a larger increase in local chain rigidification was evidenced through RAF values due to geometrical constraints initiated by close nanoclay contact without changing the crystallinity of PBSA. Tortuosity effects into the filled PBSA layers adding to confinement effects induced by PLA layers have caused a significant improvement of water barrier properties through a reduction of water permeability, water vapor solubility and water vapor diffusivity. The obtaining barrier properties were successfully correlated to microstructure, thermal properties and mobility of PBSA amorphous phase.
Strategies to Improve the Properties of Amaranth Protein Isolate-Based Thin Films for Food Packaging Applications: Nano-Layering through Spin-Coating and Incorporation of Cellulose Nanocrystals
Authors: López-Rubio Amparo , Blanco-Padilla Adriana , Oksman Kristiina , Mendoza Sandra
Published: December 2020

In this work, two different strategies for the development of amaranth protein isolate (API)-based films were evaluated. In the first strategy, ultrathin films were produced through spin-coating nanolayering, and the effects of protein concentration in the spin coating solution, rotational speed, and number of layers deposited on the properties of the films were evaluated. In the second strategy, cellulose nanocrystals (CNCs) were incorporated through a casting methodology. The morphology, optical properties, and moisture affinity of the films (water contact angle, solubility, water content) were characterized. Both strategies resulted in homogeneous films with good optical properties, decreased hydrophilic character (as deduced from the contact angle measurements and solubility), and improved mechanical properties when compared with the neat API-films. However, both the processing method and film thickness influenced the final properties of the films, being the ones processed through spin coating more transparent, less hydrophilic, and less water-soluble. Incorporation of CNCs above 10% increased hydrophobicity, decreasing the water solubility of the API films and significantly enhancing material toughness.
Photoinduced Enhancement of Photoluminescence of Colloidal II-VI Nanocrystals in Polymer Matrices
Authors: Dzhagan Volodymyr , Stroyuk Oleksandr , Raievska Oleksandra , Isaieva Oksana , Kapush Olga , Selyshchev Oleksandr , Yukhymchuk Volodymyr , Valakh Mykhailo , Zahn Dietrich R. T.
Published: December 2020

The environment strongly affects both the fundamental physical properties of semiconductor nanocrystals (NCs) and their functionality. Embedding NCs in polymer matrices is an efficient way to create a desirable NC environment needed for tailoring the NC properties and protecting NCs from adverse environmental factors. Luminescent NCs in optically transparent polymers have been investigated due to their perspective applications in photonics and bio-imaging. Here, we report on the manifestations of photo-induced enhancement of photoluminescence (PL) of aqueous colloidal NCs embedded in water-soluble polymers. Based on the comparison of results obtained on bare and core/shell NCs, NCs of different compounds (CdSe, CdTe, ZnO) as well as different embedding polymers, we conclude on the most probable mechanism of the photoenhancement for these sorts of systems. Contrary to photoenhancement observed earlier as a result of surface photocorrosion, we do not observe any change in peak position and width of the excitonic PL. Therefore, we suggest that the saturation of trap states by accumulated photo-excited charges plays a key role in the observed enhancement of the radiative recombination. This suggestion is supported by the unique temperature dependence of the trap PL band as well as by power-dependent PL measurement.
Biodegradable Poly(Lactic Acid) Nanocomposites for Fused Deposition Modeling 3D Printing
Authors: Bardot Madison , Schulz Michael D.
Published: December 2020

3D printing by fused deposition modelling (FDM) enables rapid prototyping and fabrication of parts with complex geometries. Unfortunately, most materials suitable for FDM 3D printing are non-degradable, petroleum-based polymers. The current ecological crisis caused by plastic waste has produced great interest in biodegradable materials for many applications, including 3D printing. Poly(lactic acid) (PLA), in particular, has been extensively investigated for FDM applications. However, most biodegradable polymers, including PLA, have insufficient mechanical properties for many applications. One approach to overcoming this challenge is to introduce additives that enhance the mechanical properties of PLA while maintaining FDM 3D printability. This review focuses on PLA-based nanocomposites with cellulose, metal-based nanoparticles, continuous fibers, carbon-based nanoparticles, or other additives. These additives impact both the physical properties and printability of the resulting nanocomposites. We also detail the optimal conditions for using these materials in FDM 3D printing. These approaches demonstrate the promise of developing nanocomposites that are both biodegradable and mechanically robust.
Recent Developments in Lead and Lead-Free Halide Perovskite Nanostructures towards Photocatalytic CO2 Reduction
Authors: Hiragond Chaitanya , Powar Niket , In Su-Il
Published: December 2020

Perovskite materials have been widely considered as emerging photocatalysts for CO2 reduction due to their extraordinary physicochemical and optical properties. Perovskites offer a wide range of benefits compared to conventional semiconductors, including tunable bandgap, high surface energy, high charge carrier lifetime, and flexible crystal structure, making them ideal for high-performance photocatalytic CO2 reduction. Notably, defect-induced perovskites, for example, crystallographic defects in perovskites, have given excellent opportunities to tune perovskites’ catalytic properties. Recently, lead (Pb) halide perovskite and their composites or heterojunction with other semiconductors, metal nanoparticles (NPs), metal complexes, graphene, and metal-organic frameworks (MOFs) have been well established for CO2 conversion. Besides, various halide perovskites have come under focus to avoid the toxicity of lead-based materials. Therefore, we reviewed the recent progress made by Pb and Pb-free halide perovskites in photo-assisted CO2 reduction into useful chemicals. We also discussed the importance of various factors like change in solvent, structure defects, and compositions in the fabrication of halide perovskites to efficiently convert CO2 into value-added products.
Knowledge about Sugar Sources and Sugar Intake Guidelines in Portuguese Consumers
Authors: Prada Marília , Saraiva Magda , Garrido Margarida V. , Rodrigues David L. , Lopes Diniz
Published: December 2020

In this work, we examined knowledge about sugars and guidelines for its consumption and explored the relationship between knowledge and measures related to nutritional information processing as well as sugar consumption. Specifically, we asked participants (n = 1010 Portuguese) to categorize a set of ingredients (e.g., glucose, aspartame) regarding their composition (i.e., intrinsic vs. added/free sugars) and origin (e.g., natural vs. artificial) and if they were aware of the WHO guidelines for sugar intake. Overall, despite using information about sugar frequently and considering attending to such information as very important to stay healthy, most participants were unaware of the WHO guidelines and revealed difficulties in the categorization task. Women, participants with a higher level of education, and those with children in the household reported higher use of sugar content information present in nutritional labels, higher perceived knowledge of nutritional guidelines, and higher hit rates in categorizing sugar sources. Almost one-fourth of the population exceeds the daily limit recommended by the WHO. Therefore, characterizing the knowledge of a Portuguese sample regarding sugar sources and sugar intake guidelines is particularly relevant, and our results emphasize the need to implement effective strategies to reduce sugar intake.
Impact of Early Nutrition, Physical Activity and Sleep on the Fetal Programming of Disease in the Pregnancy: A Narrative Review
Authors: Moreno-Fernandez Jorge , Ochoa Julio J. , Lopez-Frias Magdalena , Diaz-Castro Javier
Published: December 2020

Early programming is the adaptation process by which nutrition and environmental factors alter development pathways during prenatal growth, inducing changes in postnatal metabolism and diseases. The aim of this narrative review, is evaluating the current knowledge in the scientific literature on the effects of nutrition, environmental factors, physical activity and sleep on development pathways. If in utero adaptations were incorrect, this would cause a mismatch between prenatal programming and adulthood. Adequate caloric intake, protein, mineral, vitamin, and long-chain fatty acids, have been noted for their relevance in the offspring brain functions and behavior. Fetus undernutrition/malnutrition causes a delay in growth and have detrimental effects on the development and subsequent functioning of the organs. Pregnancy is a particularly vulnerable period for the development of food preferences and for modifications in the emotional response. Maternal obesity increases the risk of developing perinatal complications and delivery by cesarean section and has long-term implications in the development of metabolic diseases. Physical exercise during pregnancy contributes to overall improved health post-partum. It is also interesting to highlight the relevance of sleep problems during pregnancy, which influence adequate growth and fetal development. Taking into account these considerations, we conclude that nutrition and metabolic factors during early life play a key role of health promotion and public health nutrition programs worldwide to improve the health of the offspring and the health costs of hospitalization.
Overexpression of Key Sterol Pathway Enzymes in Two Model Marine Diatoms Alters Sterol Profiles in Phaeodactylum tricornutum
Authors: Jaramillo-Madrid Ana Cristina , Abbriano Raffaela , Ashworth Justin , Fabris Michele , Pernice Mathieu , Ralph Peter J.
Published: December 2020

Sterols are a class of triterpenoid molecules with diverse functional roles in eukaryotic cells, including intracellular signaling and regulation of cell membrane fluidity. Diatoms are a dominant eukaryotic phytoplankton group that produce a wide diversity of sterol compounds. The enzymes 3-hydroxy-3-methyl glutaryl CoA reductase (HMGR) and squalene epoxidase (SQE) have been reported to be rate-limiting steps in sterol biosynthesis in other model eukaryotes; however, the extent to which these enzymes regulate triterpenoid production in diatoms is not known. To probe the role of these two metabolic nodes in the regulation of sterol metabolic flux in diatoms, we independently over-expressed two versions of the native HMGR and a conventional, heterologous SQE gene in the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum. Overexpression of these key enzymes resulted in significant differential accumulation of downstream sterol pathway intermediates in P. tricornutum. HMGR-mVenus overexpression resulted in the accumulation of squalene, cycloartenol, and obtusifoliol, while cycloartenol and obtusifoliol accumulated in response to heterologous NoSQE-mVenus overexpression. In addition, accumulation of the end-point sterol 24-methylenecholesta-5,24(24’)-dien-3β-ol was observed in all P. tricornutum overexpression lines, and campesterol increased three-fold in P. tricornutum lines expressing NoSQE-mVenus. Minor differences in end-point sterol composition were also found in T. pseudonana, but no accumulation of sterol pathway intermediates was observed. Despite the successful manipulation of pathway intermediates and individual sterols in P. tricornutum, total sterol levels did not change significantly in transformed lines, suggesting the existence of tight pathway regulation to maintain total sterol content.
Brain and Nasal Cavity Anatomy of the Cynomolgus Monkey: Species Differences from the Viewpoint of Direct Delivery from the Nose to the Brain
Authors: Sakane Toshiyasu , Okabayashi Sachi , Kimura Shunsuke , Inoue Daisuke , Tanaka Akiko , Furubayashi Tomoyuki
Published: December 2020

Based on structural data on the nasal cavity and brain of the cynomolgus monkey, species differences in the olfactory bulb and cribriform plate were discussed from the viewpoint of direct delivery from the nose to the brain. Structural 3D data on the cynomolgus monkey skull were obtained using X-ray computed tomography. The dimensions of the nasal cavity of the cynomolgus monkey were 5 mm width × 20 mm height × 60 mm depth. The nasal cavity was very narrow and the olfactory region was far from the nostrils, similar to rats and humans. The weight and size of the monkey brain were 70 g and 55 mm width × 40 mm height × 70 mm depth. The olfactory bulb of monkeys is plate-like, while that of humans and rats is bulbar, suggesting that the olfactory area connected with the brain of monkeys is narrow. Although the structure of the monkey nasal cavity is similar to that of humans, the size and shape of the olfactory bulb are different, which is likely to result in low estimation of direct delivery from the nose to the brain in monkeys.
A Mixture of Tocopherol Acetate and L-Menthol Synergistically Promotes Hair Growth in C57BL/6 Mice
Authors: Ahn Seunghyun , Lee Jung Yeon , Choi Sang Mi , Shin Yujeong , Park Seyeon
Published: December 2020

Oral finasteride and topical minoxidil are single components approved by the US FDA for treating hair loss. Some other compounds originating from natural products are also traditionally used for promoting hair growth. In this study, observations of treated keratinocyte cells were used to demonstrate that tocopherol acetate, L-menthol, and stevioside exert an effect on cell regeneration. Furthermore, these were topically applied to the shaved skin of C57BL/6 mice to observe their effects on hair growth. A mixture of tocopherol acetate, L-menthol, and stevioside showed the highest potential for promoting hair growth in vivo. In in vivo experiments, the mixture of tocopherol acetate, L-menthol, and stevioside was more effective than tocopherol acetate or L-menthol alone in promoting hair growth. The transcriptome analysis of skin from the dorsal side of a mouse treated with tocopherol acetate or L-menthol versus vehicle revealed key changes in keratin, keratin-associated protein, forkhead box, sonic hedgehog, fibroblast growth factor 10, desmoglein 4, deoxyribonuclease 1-like 2, and cadherin 3, known to play roles in promoting hair growth.
Solubility, Permeability, and Dissolution Rate of Naftidrofuryl Oxalate Based on BCS Criteria
Authors: Kus-Slowinska Marta , Wrzaskowska Monika , Ibragimow Izabela , Czaklosz Piotr Igor , Olejnik Anna , Piotrowska-Kempisty Hanna
Published: December 2020

The Biopharmaceutics Classification System (BCS) was conceived to classify drug substances by their in vitro aqueous solubility and permeability properties. The essential activity of naftidrofuryl oxalate (NF) has been described as the inhibition of the serotonin receptors (5-HT2), resulting in vasodilation and decreasing blood pressure. Since the early 1980s, NF has been used to treat several venous and cerebral diseases. There is no data available on the BCS classification of NF. However, based on its physical-chemical properties, NF might be considered to belong to the 1st or the 3rd BCS class. The present study aimed to provide data concerning the solubility and permeability of NF through Caco-2 monolayers and propose its preliminary classification into BCS. We showed that NF is a highly soluble and permeable drug substance; thus, it might be suggested to belong to BCS class I. Additionally, a high dissolution rate of the encapsulated NF based on Praxilene® 100 mg formulation was revealed. Hence, it might be considered as an immediate-release (IR).
Editorial for the Special Issue “Polymeric and Polymer Nanocomposite Materials for Photonic Applications”
Authors: Gallego Sergi , Tomita Yasuo
Published: December 2020

Polymer nanocomposites are designed and engineered on a nanometer scale with versatile applications including optics and photonics [...]
In Vitro and In Vivo Studies of Biodegradability and Biocompatibility of Poly(εCL)-b-Poly(EtOEP)-Based Films
Authors: Nifant’ev Ilya , Shlyakhtin Andrey , Komarov Pavel , Tavtorkin Alexander , Kananykhina Evgeniya , Elchaninov Andrey , Vishnyakova Polina , Fatkhudinov Timur , Ivchenko Pavel
Published: December 2020

The control of surface bioadhesive properties of the subcutaneous implants is essential for the development of biosensors and controlled drug release devices. Poly(alkyl ethylene phosphate)-based (co)polymers are structurally versatile, biocompatible and biodegradable, and may be regarded as an alternative to poly(ethylene glycol) (PEG) copolymers in the creation of antiadhesive materials. The present work reports the synthesis of block copolymers of ε-caprolactone (εCL) and 2-ethoxy-1,3,2-dioxaphospholane-2-oxide (ethyl ethylene phosphate, EtOEP) with different content of EtOEP fragments, preparation of polymer films, and the results of the study of the impact of EtOEP/εCL ratio on the hydrophilicity (contact angle of wetting), hydrolytic stability, cytotoxicity, protein and cell adhesion, and cell proliferation using umbilical cord multipotent stem cells. It was found that the increase of EtOEP/εCL ratio results in increase of hydrophilicity of the polymer films with lowering of the protein and cell adhesion. MTT cytotoxicity test showed no significant deviations in toxicity of poly(εCL) and poly(εCL)-b-poly(EtOEP)-based films. The influence of the length of poly(EtOEP)chain in block-copolymers on fibrotic reactions was analyzed using subcutaneous implantation experiments (Wistar line rats), the increase of the width of the fibrous capsule correlated with higher EtOEP/εCL ratio. However, the copolymer-based film with highest content of polyphosphate had been subjected to faster degradation with a formation of developed contact surface of poly(εCL). The rate of the degradation of polyphosphate in vivo was significantly higher than the rate of the degradation of polyphosphate in vitro, which only confirms an objective value of in vivo experiments in the development of polymer materials for biomedical applications.
Effect of Melt-Compounding Protocol on Self-Aggregation and Percolation in a Ternary Composite
Authors: Kim Ji Hwan , Hong Joung Sook , Ishigami Akira , Kurose Takashi , Ito Hiroshi , Ahn Kyung Hyun
Published: December 2020

A ternary composite of poly(lactic acid) (PLA), poly(caprolactone) (PCL), and carbon black (CB) shows the PCL-induced CB self-aggregation and percolation formation when the amount of the PCL phase as the secondary phase is as small as the amount of CB. Furthermore, when the drop size of the PCL phase becomes smaller, the ternary composite forms a percolation of high order structure, resulting in a remarkable enhancement of the electrical conductivity (~4 × 10−2 S/m with 4 wt.% CB). To further control the percolation structure, the composite fabrication is controlled by splitting a typical single-step mixing process into two steps, focusing on the dispersion of the secondary PCL phase and the CB particles separately. Under the single-step mixing protocol, the ternary composite shows a structure with greater CB aggregation in the form of a high aspect ratio and large aggregates (aggregate perimeter~aggregate size 0.7). Meanwhile, the two-step mixing process causes the CB aggregates to expand and create a higher structure (aggregate perimeter~aggregate size 0.8). The reduced size of the secondary phase under a mixing condition with high shear force prior to the addition of CB provides a larger interfacial area for CB to diffuse into the PCL phase during the subsequent mixing step, resulting in a further expansion of CB aggregation throughout the composite. The particle percolation of such a high order structure is attributed to high storage modulus (G′), high Young’s modulus, high dielectric loss (ε″), and negative–positive switching of dielectric constant at high frequency (of 103 Hz) of composite.
The Potential of Polyethylene Terephthalate Glycol as Biomaterial for Bone Tissue Engineering
Authors: Hassan Mohamed H. , Omar Abdalla M. , Daskalakis Evangelos , Hou Yanhao , Huang Boyang , Strashnov Ilya , Grieve Bruce D. , Bártolo Paulo
Published: December 2020

The search for materials with improved mechanical and biological properties is a major challenge in tissue engineering. This paper investigates, for the first time, the use of Polyethylene Terephthalate Glycol (PETG), a glycol-modified class of Polyethylene Terephthalate (PET), as a potential material for the fabrication of bone scaffolds. PETG scaffolds with a 0/90 lay-dawn pattern and different pore sizes (300, 350 and 450 µm) were produced using a filament-based extrusion additive manufacturing system and mechanically and biologically characterized. The performance of PETG scaffolds with 300 µm of pore size was compared with polycaprolactone (PCL). Results show that PETG scaffolds present significantly higher mechanical properties than PCL scaffolds, providing a biomechanical environment that promotes high cell attachment and proliferation.
Electrical Conductivity Based Ammonia Sensing Properties of Polypyrrole/MoS2 Nanocomposite
Authors: Ahmad Sharique , Khan Imran , Husain Ahmad , Khan Anish , Asiri Abdullah M.
Published: December 2020

Polypyrrole (PPy) and Polypyrrole/MoS2 (PPy/MoS2) nanocomposites were successfully prepared, characterized and studied for ammonia sensing properties. The as-prepared PPy and PPy/MoS2 nanocomposites were confirmed by FTIR (Fourier transform infrared spectroscopy), XRD (X-ray diffraction), SEM (scanning electron microscopy) and TEM (transmission electron microscopy) techniques. The ammonia sensing properties of PPy and PPy/MoS2 nanocomposites were studied in terms of change in DC electrical conductivity on exposure to ammonia vapors followed by ambient air at room temperature. It was observed that the incorporation of MoS2 in PPy showed high sensitivity, significant stability and excellent reversibility. The enhanced sensing properties of PPy/MoS2 nanocomposites could be attributed to comparatively high surface area, appropriate sensing channels and efficiently available active sites. The sensing mechanism is explained on the basis of simple acid-base chemistry of polypyrrole.
Poly(d,l-lactide-co-glycolide) (PLGA) Nanoparticles Loaded with Proteolipid Protein (PLP)—Exploring a New Administration Route
Authors: Lima Alexandre Ferreira , Amado Isabel R. , Pires Liliana R.
Published: December 2020

The administration of specific antigens is being explored as a mean to re-establish immunological tolerance, namely in the context of multiple sclerosis (MS). PLP139-151 is a peptide of the myelin’s most abundant protein, proteolipid protein (PLP), which has been identified as a potent tolerogenic molecule in MS. This work explored the encapsulation of the peptide into poly(lactide-co-glycolide) nanoparticles and its subsequent incorporation into polymeric microneedle patches to achieve efficient delivery of the nanoparticles and the peptide into the skin, a highly immune-active organ. Different poly(d,l-lactide-co-glycolide) (PLGA) formulations were tested and found to be stable and to sustain a freeze-drying process. The presence of trehalose in the nanoparticle suspension limited the increase in nanoparticle size after freeze-drying. It was shown that rhodamine can be loaded in PLGA nanoparticles and these into poly(vinyl alcohol)–poly(vinyl pyrrolidone) microneedles, yielding fluorescently labelled structures. The incorporation of PLP into the PLGA nanoparticles resulted in nanoparticles in a size range of 200 µm and an encapsulation efficiency above 20%. The release of PLP from the nanoparticles occurred in the first hours after incubation in physiological media. When loading the nanoparticles into microneedle patches, structures were obtained with 550 µm height and 180 µm diameter. The release of PLP was detected in PLP–PLGA.H20 nanoparticles when in physiological media. Overall, the results show that this strategy can be explored to integrate a new antigen-specific therapy in the context of multiple sclerosis, providing minimally invasive administration of PLP-loaded nanoparticles into the skin.
Effect of Microcapsule Content on Diels-Alder Room Temperature Self-Healing Thermosets
Authors: Santos Sadella C. , La Scala John J. , Palmese Giuseppe R.
Published: December 2020

A furan functionalized epoxy-amine thermoset with an embedded microcapsule healing system that utilizes reversible Diels-Alder healing chemistry was used to investigate the influence of microcapsule loading on healing efficiency. A urea-formaldehyde encapsulation technique was used to create capsules with an average diameter of 150 µm that were filled with a reactive solution of bismaleimide in phenyl acetate. It was found that optimum healing of the thermoset occurred at 10 wt% microcapsule content for the compositions investigated. The diffusion of solvent through the crack interface and within fractured samples was investigated using analytical diffusion models. The decrease in healing efficiency at higher microcapsule loading was attributed partially to solvent-induced plasticization at the interface. The diffusion analysis also showed that the 10% optimum microcapsule concentration occurs for systems with the same interfacial solvent concentration. This suggests that additional physical and chemical phenomena are also responsible for the observed optimum. Such phenomena could include a reduction in surface area available for healing and the saturation of interfacial furan moieties by reaction with increasing amounts of maleimide. Both would result from increased microcapsule loading.
A Review of Process Systems Engineering (PSE) Tools for the Design of Ionic Liquids and Integrated Biorefineries
Authors: Chemmangattuvalappil Nishanth G. , Ng Denny K. S. , Ng Lik Yin , Ooi Jecksin , Chong Jia Wen , Eden Mario R.
Published: December 2020

In this review paper, a brief overview of the increasing applicability of Process Systems Engineering (PSE) tools in two research areas, which are the design of ionic liquids and the design of integrated biorefineries, is presented. The development and advances of novel computational tools and optimization approaches in recent years have enabled these applications with practical results. A general introduction to ionic liquids and their various applications is presented followed by the major challenges in the design of optimal ionic liquids. Significant improvements in computational efficiency have made it possible to provide more reliable data for optimal system design, minimize the production cost of ionic liquids, and reduce the environmental impact caused by such solvents. Hence, the development of novel computational tools and optimization tools that contribute to the design of ionic liquids have been reviewed in detail. A detailed review of the recent developments in PSE applications in the field of integrated biorefineries is then presented. Various value-added products could be processed by the integrated biorefinery aided with applications of PSE tools with the aim of enhancing the sustainability performance in terms of economic, environmental, and social impacts. The application of molecular design tools in the design of integrated biorefineries is also highlighted. Major developments in the application of ionic liquids in integrated biorefineries have been emphasized. This paper is concluded by highlighting the major opportunities for further research in these two research areas and the areas for possible integration of these research fields.
The Effects of Biofertilizers on Growth, Soil Fertility, and Nutrients Uptake of Oil Palm (Elaeis Guineensis) under Greenhouse Conditions
Authors: Ajeng Aaronn Avit , Abdullah Rosazlin , Malek Marlinda Abdul , Chew Kit Wayne , Ho Yeek-Chia , Ling Tau Chuan , Lau Beng Fye , Show Pau Loke
Published: December 2020

The full dependency on chemical fertilizers in oil palm plantation poses an enormous threat to the ecosystem through the degradation of soil and water quality through leaching to the groundwater and contaminating the river. A greenhouse study was conducted to test the effect of combinations of biofertilizers with chemical fertilizer focusing on the soil fertility, nutrient uptake, and the growth performance of oil palms seedlings. Soils used were histosol, spodosol, oxisol, and ultisol. The three treatments were T1: 100% chemical fertilizer (NPK 12:12:17), T2: 70% chemical fertilizer + 30% biofertilizer A (CF + BFA), and T3: 70% + 30% biofertilizer B (CF + BFB). T2 and T3, respectively increased the growth of oil palm seedlings and soil nutrient status but seedlings in oxisol and ultisol under T3 had the highest in almost all parameters due to the abundance of more efficient PGPR. The height of seedlings in ultisol under T3 was 22% and 17% more than T2 and T1 respectively, with enhanced girth size, chlorophyll content, with improved nutrient uptake by the seedlings. Histosol across all treatments has a high macronutrient content suggesting that the rate of chemical fertilizer application should be revised when planting using the particular soil. With the reduction of chemical fertilizer by 25%, the combined treatment with biofertilizers could enhance the growth of the oil palm seedlings and soil nutrient properties regardless of the soil orders.
MSLWENet: A Novel Deep Learning Network for Lake Water Body Extraction of Google Remote Sensing Images
Authors: Wang Zhaobin , Gao Xiong , Zhang Yaonan , Zhao Guohui
Published: December 2020

Lake water body extraction from remote sensing images is a key technique for spatial geographic analysis. It plays an important role in the prevention of natural disasters, resource utilization, and water quality monitoring. Inspired by the recent years of research in computer vision on fully convolutional neural networks (FCN), an end-to-end trainable model named the multi-scale lake water extraction network (MSLWENet) is proposed. We use ResNet-101 with depthwise separable convolution as an encoder to obtain the high-level feature information of the input image and design a multi-scale densely connected module to expand the receptive field of feature points by different dilation rates without increasing the computation. In the decoder, the residual convolution is used to abstract the features and fuse the features at different levels, which can obtain the final lake water body extraction map. Through visual interpretation of the experimental results and the calculation of the evaluation indicators, we can see that our model extracts the water bodies of small lakes well and solves the problem of large intra-class variance and small inter-class variance in the lakes’ water bodies. The overall accuracy of our model is up to 98.53% based on the evaluation indicators. Experimental results demonstrate that the MSLWENet, which benefits from the convolutional neural network, is an excellent lake water body extraction network.
Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks
Authors: Kalajdjieski Jovan , Zdravevski Eftim , Corizzo Roberto , Lameski Petre , Kalajdziski Slobodan , Pires Ivan Miguel , Garcia Nuno M. , Trajkovik Vladimir
Published: December 2020

Air pollution is becoming a rising and serious environmental problem, especially in urban areas affected by an increasing migration rate. The large availability of sensor data enables the adoption of analytical tools to provide decision support capabilities. Employing sensors facilitates air pollution monitoring, but the lack of predictive capability limits such systems’ potential in practical scenarios. On the other hand, forecasting methods offer the opportunity to predict the future pollution in specific areas, potentially suggesting useful preventive measures. To date, many works tackled the problem of air pollution forecasting, most of which are based on sequence models. These models are trained with raw pollution data and are subsequently utilized to make predictions. This paper proposes a novel approach evaluating four different architectures that utilize camera images to estimate the air pollution in those areas. These images are further enhanced with weather data to boost the classification accuracy. The proposed approach exploits generative adversarial networks combined with data augmentation techniques to mitigate the class imbalance problem. The experiments show that the proposed method achieves robust accuracy of up to 0.88, which is comparable to sequence models and conventional models that utilize air pollution data. This is a remarkable result considering that the historic air pollution data is directly related to the output—future air pollution data, whereas the proposed architecture uses camera images to recognize the air pollution—which is an inherently much more difficult problem.
Bathymetric Detection of Fluvial Environments through UASs and Machine Learning Systems
Authors: Emanuele Pontoglio , Nives Grasso , Andrea Cagninei , Carlo Camporeale , Paolo Dabove , Andrea Maria Lingua
Published: December 2020

In recent decades, photogrammetric and machine learning technologies have become essential for a better understanding of environmental and anthropic issues. The present work aims to respond one of the most topical problems in environmental photogrammetry, i.e., the automatic classification of dense point clouds using the machine learning (ML) technology for the refraction correction on the fluvial water table. The applied methodology for the acquisition of multiple photogrammetric flights was made through UAV drones, also in RTK configuration, for various locations along the Orco River, sited in Piedmont (Italy) and georeferenced with GNSS—RTK topographic method. The authors considered five topographic fluvial cross-sections to set the correction methodology. The automatic classification in ML has found a valid identification of different patterns (Water, Gravel bars, Vegetation, and Ground classes), in specific hydraulic and geomatic conditions. The obtained results about the automatic classification and refraction reduction led us the definition of a new procedure, with precise conditions of validity.
Assessment of the Segmentation of RGB Remote Sensing Images: A Subjective Approach
Authors: Kazakeviciute-Januskeviciene Giruta , Janusonis Edgaras , Bausys Romualdas , Limba Tadas , Kiskis Mindaugas
Published: December 2020

The evaluation of remote sensing imagery segmentation results plays an important role in the further image analysis and decision-making. The search for the optimal segmentation method for a particular data set and the suitability of segmentation results for the use in satellite image classification are examples where the proper image segmentation quality assessment can affect the quality of the final result. There is no extensive research related to the assessment of the segmentation effectiveness of the images. The designed objective quality assessment metrics that can be used to assess the quality of the obtained segmentation results usually take into account the subjective features of the human visual system (HVS). A novel approach is used in the article to estimate the effectiveness of satellite image segmentation by relating and determining the correlation between subjective and objective segmentation quality metrics. Pearson’s and Spearman’s correlation was used for satellite images after applying a k-means++ clustering algorithm based on colour information. Simultaneously, the dataset of the satellite images with ground truth (GT) based on the “DeepGlobe Land Cover Classification Challenge” dataset was constructed for testing three classes of quality metrics for satellite image segmentation.
A Comparison of Two Machine Learning Classification Methods for Remote Sensing Predictive Modeling of the Forest Fire in the North-Eastern Siberia
Authors: Janiec Piotr , Gadal Sébastien
Published: December 2020

The problem of forest fires in Yakutia is not as well studied as in other countries. Two methods of machine learning classifications were implemented to determine the risk of fire: MaxENT and random forest. The initial materials to define fire risk factors were satellite images and their products of various spatial and spectral resolution (Landsat TM, Modis TERRA, GMTED2010, VIIRS), vector data (OSM), and bioclimatic variables (WORLDCLIM). The results of the research showed a strong human influence on the risk in this region, despite the low population density. Anthropogenic factors showed a high correlation with the occurrence of wildfires, more than climatic or topographical factors. Other factors affect the risk of fires at the macroscale and microscale, which should be considered when modeling. The random forest method showed better results in the macroscale, however, the maximum entropy model was better in the microscale. The exclusion of variables that do not show a high correlation, does not always improve the modeling results. The random forest presence prediction model is a more accurate method and significantly reduces the risk territory. The reverse is the method of maximum entropy, which is not as accurate and classifies very large areas as endangered. Further study of this topic requires a clearer and conceptually developed approach to the application of remote sensing data. Therefore, this work makes sense to lay the foundations of the future, which is a completely automated fire risk assessment application in the Republic of Sakha. The results can be used in fire prophylactics and planning fire prevention. In the future, to determine the risk well, it is necessary to combine the obtained maps with the seasonal risk determined using indices (for example, the Nesterov index 1949) and the periodic dynamics of forest fires, which Isaev and Utkin studied in 1963. Such actions can help to build an application, with which it will be possible to determine the risk of wildfire and the spread of fire during extreme events.
Mapping Land Use from High Resolution Satellite Images by Exploiting the Spatial Arrangement of Land Cover Objects
Authors: Li Mengmeng , Stein Alfred
Published: December 2020

Spatial information regarding the arrangement of land cover objects plays an important role in distinguishing the land use types at land parcel or local neighborhood levels. This study investigates the use of graph convolutional networks (GCNs) in order to characterize spatial arrangement features for land use classification from high resolution remote sensing images, with particular interest in comparing land use classifications between different graph-based methods and between different remote sensing images. We examine three kinds of graph-based methods, i.e., feature engineering, graph kernels, and GCNs. Based upon the extracted arrangement features and features regarding the spatial composition of land cover objects, we formulated ten land use classifications. We tested those on two different remote sensing images, which were acquired from GaoFen-2 (with a spatial resolution of 0.8 m) and ZiYuan-3 (of 2.5 m) satellites in 2020 on Fuzhou City, China. Our results showed that land use classifications that are based on the arrangement features derived from GCNs achieved the highest classification accuracy than using graph kernels and handcrafted graph features for both images. We also found that the contribution to separating land use types by arrangement features varies between GaoFen-2 and ZiYuan-3 images, due to the difference in the spatial resolution. This study offers a set of approaches for effectively mapping land use types from (very) high resolution satellite images.
The Role of Micro Breaking of Small-Scale Wind Waves in Radar Backscattering from Sea Surface
Authors: Sergievskaya Irina A. , Ermakov Stanislav A. , Ermoshkin Aleksey V. , Kapustin Ivan A. , Shomina Olga V. , Kupaev Alexander V.
Published: December 2020

The study of the microwave scattering mechanisms of the sea surface is extremely important for the development of radar sensing methods. Some time ago, Bragg (resonance) scattering of electromagnetic waves from the sea surface was proposed as the main mechanism of radar backscattering at moderate incidence angles of microwaves. However, it has been recently confirmed that Bragg scattering is often unable to correctly explain observational data and that some other physical mechanisms should be taken into consideration. The newly introduced additional scattering mechanism was characterized as non-polarized, or non-Bragg scattering, from quasi-specular facets appearing due to breaking wave crests, the latter usually occurring in moderate and strong winds. In this paper, it was determined experimentally that such non-polarized radar backscattering appeared not only for rough sea conditions in which wave crests strongly break and “white caps” occur, but also at very low wind velocities close to their threshold values for the wave generation process. The experiments were performed using two polarized Doppler radars. The experiments demonstrated that a polarization ratio, which characterizes relative contributions of non-polarized and Bragg components to the total backscatter, changed slightly with wind velocity and wind direction. Detailed analysis of radar Doppler shifts revealed two types of scatterers responsible for the non-polarized component. One type of scatterer, moving with the velocities of decimeter-scale wind waves, determined radar backscattering at low winds. We identified these scatterers as “microbreakers” and related them to nonlinear features in the profile of decimeter-scale waves, like bulges, toes and parasitic capillary ripples. The scatterers of the second type were associated with strong breaking, moved with the phase velocities of meter-scale breaking waves and appeared at moderate winds additionally to the “microbreakers”. Along with strong breakers, the impact of microbreaking in non-polarized backscattering at moderate winds remained significant; specifically the microbreakers were found to be responsible for about half of the non-polarized component of the radar return. The presence of surfactant films on the sea surface led to a significant suppression of the small-scale non-Bragg scattering and practically did not change the non-Bragg scatterer speed. This effect was explained by the fact that the nonlinear structures associated with dm-scale waves were strongly reduced in the presence of a film due to the cascade mechanism, even if the reduction of the amplitude of dm waves was weak. At the same time, the velocities of non-Bragg scatterers remained practically the same as in non-slick areas since the phase velocity of dm waves was not affected by the film.
Using GRACE Data to Study the Impact of Snow and Rainfall on Terrestrial Water Storage in Northeast China
Authors: Qian An , Yi Shuang , Chang Le , Sun Guangtong , Liu Xiaoyang
Published: December 2020

Water resources are important for agricultural, industrial, and urban development. In this paper, we analyzed the influence of rainfall and snowfall on variations in terrestrial water storage (TWS) in Northeast China from Gravity Recovery and Climate Experiment (GRACE) gravity satellite data, GlobSnow snow water equivalent product, and ERA5-land monthly total precipitation, snowfall, and snow depth data. This study revealed the main composition and variation characteristics of TWS in Northeast China. We found that GRACE provided an effective method for monitoring large areas of stable seasonal snow cover and variations in TWS in Northeast China at both seasonal and interannual scales. On the seasonal scale, although summer rainfall was 10 times greater than winter snowfall, the terrestrial water storage in Northeast China peaked in winter, and summer rainfall brought about only a sub-peak, 1 month later than the maximum rainfall. On the interannual scale, TWS in Northeast China was controlled by rainfall. The correlation analysis results revealed that the annual fluctuations of TWS and rainfall in Northeast China appear to be influenced by ENSO (EI Niño–Southern Oscillation) events with a lag of 2–3 years. In addition, this study proposed a reconstruction model for the interannual variation in TWS in Northeast China from 2003 to 2016 on the basis of the contemporary terrestrial water storage and rainfall data.