bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Utility of Plant Growth-Promoting Rhizobacteria as Biological Control Agents towards Plant-Parasitic Nematodes
Authors: Subedi Pratima , Gattoni Kaitlin , Liu Wenshan , Lawrence Kathy S. , Park Sang-Wook
Published: September 2020

Plant-parasitic nematodes (PPN) are among the most economically and ecologically damaging pests, causing severe losses of crop production worldwide. Chemical-based nematicides have been widely used, but these may have adverse effects on human health and the environment. Hence, biological control agents (BCAs) have become an alternative option for controlling PPN, since they are environmentally friendly and cost effective. Lately, a major effort has been made to evaluate the potential of a commercial grade strain of plant growth-promoting rhizobacteria (PGPR) as BCAs, because emerging evidence has shown that PGPR can reduce PPN in infested plants through direct and/or indirect antagonistic mechanisms. Direct antagonism occurs by predation, release of antinematicidal metabolites and semiochemicals, competition for nutrients, and niche exclusion. However, the results of direct antagonism may be inconsistent due to unknown endogenous and exogenous factors that may prevent PGPR from colonizing plant’s roots. On the other hand, indirect antagonism may occur from the induced systemic resistance (ISR) that primes whole plants to better fight against various biotic and abiotic constraints, actuating faster and/or stronger defense responses (adaption), enhancing their promise as BCAs. Hence, this review will briefly revisit (i) two modes of PGPR in managing PPN, and (ii) the current working models and many benefits of ISR, in the aim of reassessing current progresses and future directions for isolating more effective BCAs and/or developing better PPN management strategy.
Differential Regulation of Phytoene Synthase PSY1 During Fruit Carotenogenesis in Cultivated and Wild Tomato Species (Solanum section Lycopersicon)
Authors: Efremov Gleb I. , Slugina Maria A. , Shchennikova Anna V. , Kochieva Elena Z.
Published: September 2020

In plants, carotenoids define fruit pigmentation and are involved in the processes of photo-oxidative stress defense and phytohormone production; a key enzyme responsible for carotene synthesis in fruit is phytoene synthase 1 (PSY1). Tomatoes (Solanum section Lycopersicon) comprise cultivated (Solanum lycopersicum) as well as wild species with different fruit color and are a good model to study carotenogenesis in fleshy fruit. In this study, we identified homologous PSY1 genes in five Solanum section Lycopersicon species, including domesticated red-fruited S. lycopersicum and wild yellow-fruited S. cheesmaniae and green-fruited S. chilense, S. habrochaites and S. pennellii. PSY1 homologs had a highly conserved structure, including key motifs in the active and catalytic sites, suggesting that PSY1 enzymatic function is similar in green-fruited wild tomato species and preserved in red-fruited S. lycopersicum. PSY1 mRNA expression directly correlated with carotenoid content in ripe fruit of the analyzed tomato species, indicating differential transcriptional regulation. Analysis of the PSY1 promoter and 5′-UTR sequence revealed over 30 regulatory elements involved in response to light, abiotic stresses, plant hormones, and parasites, suggesting that the regulation of PSY1 expression may affect the processes of fruit senescence, seed maturation and dormancy, and pathogen resistance. The revealed differences between green-fruited and red-fruited Solanum species in the structure of the PSY1 promoter/5′-UTR, such as the acquisition of ethylene-responsive element by S. lycopersicum, could reflect the effects of domestication on the transcriptional mechanisms regulating PSY1 expression, including induction of carotenogenesis during fruit ripening, which would contribute to red coloration in mature fruit.
Iron-Sulfur Cluster Complex Assembly in the Mitochondria of Arabidopsis thaliana
Authors: Armas Alejandro M. , Balparda Manuel , Terenzi Agustina , Busi Maria V. , Pagani Maria A. , Gomez-Casati Diego F.
Published: September 2020

In plants, the cysteine desulfurase (AtNFS1) and frataxin (AtFH) are involved in the formation of Fe-S groups in mitochondria, specifically, in Fe and sulfur loading onto scaffold proteins, and the subsequent formation of the mature Fe-S cluster. We found that the small mitochondrial chaperone, AtISD11, and AtFH are positive regulators for AtNFS1 activity in Arabidopsis. Moreover, when the three proteins were incubated together, a stronger attenuation of the Fenton reaction was observed compared to that observed with AtFH alone. Using pull-down assays, we found that these three proteins physically interact, and sequence alignment and docking studies showed that several amino acid residues reported as critical for the interaction of their human homologous are conserved. Our results suggest that AtFH, AtNFS1 and AtISD11 form a multiprotein complex that could be involved in different stages of the iron–sulfur cluster (ISC) pathway in plant mitochondria.
Longer Photoperiods with the Same Daily Light Integral Increase Daily Electron Transport through Photosystem II in Lettuce
Authors: Elkins Claudia , van Iersel Marc W.
Published: September 2020

Controlled environment crop production recommendations often use the daily light integral (DLI) to quantify the light requirements of specific crops. Sole-source electric lighting, used in plant factories, and supplemental electric lighting, used in greenhouses, may be required to attain a specific DLI. Electric lighting is wasteful if not provided in a way that promotes efficient photochemistry. The quantum yield of photosystem II (ΦPSII), the fraction of absorbed light used for photochemistry, decreases with increasing photosynthetic photon flux density (PPFD). Thus, we hypothesized that the daily photochemical integral (DPI), the total electron transport through photosystem II (PSII) integrated over 24 h, would increase if the same DLI was provided at a lower PPFD over a longer photoperiod. To test this, ΦPSII and the electron transport rate (ETR) of lettuce (Lactuca sativa ‘Green Towers’) were measured in a growth chamber at DLIs of 15 and 20 mol m−2 d−1 over photoperiods ranging from 7 to 22 h. This resulted in PPFDs of 189 to 794 μmol m−2 s−1. The ΦPSII decreased from 0.67 to 0.28 and ETR increased from 55 to 99 μmol m−2 s−1 as PPFD increased from 189 to 794 μmol m−2 s−1. The DPI increased linearly as the photoperiod increased, but the magnitude of this response depended on DLI. With a 7-h photoperiod, the DPI was ≈2.7 mol m−2 d−1, regardless of DLI. However, with a 22-h photoperiod, the DPI was 4.54 mol m−2 d−1 with a DLI of 15 mol m−2 d−1 and 5.78 mol m−2 d−1 with a DLI of 20 mol m−2 d−1. Our hypothesis that DPI can be increased by providing the same DLI over longer photoperiods was confirmed.
Evaluation of Anti-Colitis Effect of KM1608 and Biodistribution of Dehydrocostus Lactone in Mice Using Bioimaging Analysis
Authors: Lee Sullim , Kim Sang-Back , Lee Jaemin , Park Jimin , Choi Sungyoul , Hwang Gwi Seo , Choi Han-Seok , Kang Ki Sung
Published: September 2020

Inflammatory bowel disease (IBD) is a chronic relapsing disorder modulated by numerous factors. Recent failures of drugs targeting single factors suggest that multitargeting drugs could be useful for the treatment of IBD. Natural medicines may be an alternative option for the treatment of IBD, owing to the complex nature of the disease. However, most natural medicines have poor in vitro and in vivo translational potential because of inadequate pharmacokinetic study. KM1608, a mixture of the medicinal plants Aucklandia lappa, Terminalia chebula, and Zingiber officinale, was examined for its anti-colitis effects and biodistribution using bioimaging. Dehydrocostus lactone, as a marker compound, was analyzed to assess the biodistribution of KM1608. KM1608 significantly attenuated the disease activity of dextran sodium sulfate-induced colitis in mice and suppressed inflammatory mediators such as myeloperoxidase, proinflammatory cytokines (TNF-α and IL-6), and the Th2-type cytokine IL-4 in the colon. Optical fluorescence imaging revealed that KM1608 was distributed in the intestinal area as a target organ. Collectively, our findings suggest that KM1608 is a potential therapeutic formulation for IBD.
Uptake of Trace Elements in the Water Fern Azolla filiculoides after Short-Term Application of Chestnut Wood Distillate (Pyroligneous Acid)
Authors: Fačkovcová Zuzana , Vannini Andrea , Monaci Fabrizio , Grattacaso Martina , Paoli Luca , Loppi Stefano
Published: September 2020

Treatments of crops with additives to increase their productivity may pose environmental risks and induce negative effects also on non-target organisms. In this study, we investigated the potential effect of chestnut wood distillate (pyroligneous acid) used in agriculture, on the accumulation of trace elements in aquatic plants. As a model species, the common water fern Azolla filiculoides Lam. was selected, being often used also in phytoremediation processes. The content of selected elements of toxicological concern (As, Ba, Cd, Cu, Fe, Mn, Ni, Pb, Zn) was assessed in the fern after short-term treatments (1–3 days) over a range of wood distillate concentrations 1:300 (3.33 mL/L), 1:500 (2.00 mL/L), 1:700 (1.43 mL/L). A statistically significant accumulation of Cd, Cu, Mn, Pb, Zn (1:700) and Pb (1:300) was recorded after three days of incubation, despite the concentrations remained overall low. Using treatment vs. control ratios, a trend of increasing temporal uptake was detected for As, Ba, Fe, Mn, Pb (1:700); Mn, Pb (1:500), and only Pb at 1:300. The results suggested that, under the experimental conditions, element uptake is positively influenced by time and negatively by increasing concentrations of wood distillate, likely due to the acidification of the medium. On the whole, the element concentrations measured in A. filiculoides were low and did not pose any toxicological concern.
On the Physicochemical Characteristics and Applications of an “Undesirable” Pyrenean Thorny Cushion Dwarf: Echinospartum horridum (Vahl) Roth
Authors: Martín-Ramos Pablo , Martín-Gil Jesús , Gómez-García Daniel , Cuchí-Oterino José Antonio
Published: September 2020

Small evergreen shrubs of the family Fabaceae represent a large proportion of current Mediterranean mountain vegetation. Their low pastoral value and tendency for encroachment makes these plants undesirable. In this paper, the thermal and chemical characteristics of Echinospartum horridum, a thorny cushion-shaped dwarf shrub native to the French Central Massif and the Pyrenees (particularly dominant in the shrublands of the Pyrenees), have been analyzed with a view to its valorization. Although the higher and lower heating values of the biomass from E. horridum met the ISO 17225-2:2014 requirements for its use in pellets, the ash content was slightly above the upper limit, so it would not comply with the normative for its acceptable use as a fuel. Nevertheless, the presence of high added-value flavonoids and lignans in its extracts, which are receiving increasing recent interest as efficient anti-tumor drugs and antivirals, may open the door to the valorization of this shrub for pharmacological applications.
Role of Organic Anions and Phosphatase Enzymes in Phosphorus Acquisition in the Rhizospheres of Legumes and Grasses Grown in a Low Phosphorus Pasture Soil
Authors: Touhami Driss , McDowell Richard W. , Condron Leo M.
Published: September 2020

Rhizosphere processes play a critical role in phosphorus (P) acquisition by plants and microbes, especially under P-limited conditions. Here, we investigated the impacts of nutrient addition and plant species on plant growth, rhizosphere processes, and soil P dynamics. In a glasshouse experiment, blue lupin (Lupinus angustifolius), white clover (Trifolium repens L.), perennial ryegrass (Lolium perenne L.), and wheat (Triticum aestivum L.) were grown in a low-P pasture soil for 8 weeks with and without the single and combined addition of P (33 mg kg−1) and nitrogen (200 mg kg−1). Phosphorus addition increased plant biomass and total P content across plant species, as well as microbial biomass P in white clover and ryegrass. Alkaline phosphatase activity was higher for blue lupin. Legumes showed higher concentrations of organic anions compared to grasses. After P addition, the concentrations of organic anions increased by 11-,10-, 5-, and 2-fold in the rhizospheres of blue lupin, white clover, wheat, and ryegrass, respectively. Despite the differences in their chemical availability (as assessed by P fractionation), moderately labile inorganic P and stable organic P were the most depleted fractions by the four plant species. Inorganic P fractions were depleted similarly between the four plant species, while blue lupin exhibited a strong depletion of stable organic P. Our findings suggest that organic anions were not related to the acquisition of inorganic P for legumes and grasses. At the same time, alkaline phosphatase activity was associated with the mobilization of stable organic P for blue lupin.
F-Box Family Genes, LTSF1 and LTSF2, Regulate Low-Temperature Stress Tolerance in Pepper (Capsicum chinense)
Authors: Venkatesh Jelli , Kang Min-Young , Liu Li , Kwon Jin-Kyung , Kang Byoung-Cheorl
Published: September 2020

The F-box proteins belong to a family of regulatory proteins that play key roles in the proteasomal degradation of other proteins. Plant F-box proteins are functionally diverse, and the precise roles of many such proteins in growth and development are not known. Previously, two low-temperature-sensitive F-box protein family genes (LTSF1 and LTSF2) were identified as candidates responsible for the sensitivity to low temperatures in the pepper (Capsicum chinense) cultivar ‘sy-2’. In the present study, we showed that the virus-induced gene silencing of these genes stunted plant growth and caused abnormal leaf development under low-temperature conditions, similar to what was observed in the low-temperature-sensitive ‘sy-2’ line. Protein–protein interaction analyses revealed that the LTSF1 and LTSF2 proteins interacted with S-phase kinase-associated protein 1 (SKP1), part of the Skp, Cullin, F-box-containing (SCF) complex that catalyzes the ubiquitination of proteins for degradation, suggesting a role for LTSF1 and LTSF2 in protein degradation. Furthermore, transgenic Nicotiana benthamiana plants overexpressing the pepper LTSF1 gene showed an increased tolerance to low-temperature stress and a higher expression of the genes encoding antioxidant enzymes. Taken together, these results suggest that the LTSF1 and LTSF2 F-box proteins are a functional component of the SCF complex and may positively regulate low-temperature stress tolerance by activating antioxidant-enzyme activities.
Transient Gene Expression is an Effective Experimental Tool for the Research into the Fine Mechanisms of Plant Gene Function: Advantages, Limitations, and Solutions
Authors: Tyurin Alexander A. , Suhorukova Alexandra V. , Kabardaeva Ksenia V. , Goldenkova-Pavlova Irina V.
Published: September 2020

A large data array on plant gene expression accumulated thanks to comparative omic studies directs the efforts of researchers to the specific or fine effects of the target gene functions and, as a consequence, elaboration of relatively simple and concurrently effective approaches allowing for the insight into the physiological role of gene products. Numerous studies have convincingly demonstrated the efficacy of transient expression strategy for characterization of the plant gene functions. The review goals are (i) to consider the advantages and limitations of different plant systems and methods of transient expression used to find out the role of gene products; (ii) to summarize the current data on the use of the transient expression approaches for the insight into fine mechanisms underlying the gene function; and (iii) to outline the accomplishments in efficient transient expression of plant genes. In general, the review discusses the main and critical steps in each of the methods of transient gene expression in plants; areas of their application; main results obtained using plant objects; their contribution to our knowledge about the fine mechanisms of the plant gene functions underlying plant growth and development; and clarification of the mechanisms regulating complex metabolic pathways.
Characterization of Hybrid Oil Palm Empty Fruit Bunch/Woven Kenaf Fabric-Reinforced Epoxy Composites
Authors: Hanan Farah , Jawaid Mohammad , Paridah Md Tahir , Naveen Jesuarockiam
Published: September 2020

In this research, the physical, mechanical and morphological properties of oil palm empty fruit bunch (EFB) mat/woven kenaf fabric-reinforced epoxy composites have been investigated. The oil palm EFB/woven kenaf fabrics were varied, with weight ratios of 50/0 (T1), 35/15 (T2), 25/25 (T3), 15/35 (T4) and 0/50 (T5). The composites were fabricated using a simple hand lay-up technique followed by hot pressing. The result obtained shows that an increase in kenaf fiber content exhibited higher tensile and flexural properties. On the other hand, the opposite trend was observed in the impact strength of hybrid composites, where an increase in kenaf fiber content reduced the impact strength. This can be corroborated with the physical properties analysis, where a higher void content, water absorption and thickness swelling were observed for pure oil palm EFB (T1) composites compared to other samples. The scanning electron microscopy analysis results clearly show the different failure modes of the tensile fractured samples. Statistical analysis was performed using one-way ANOVA and shows significant differences between the obtained results.
Thermoreversible Polymer Gels in DMF Formed from Charge- and Crystallization-Induced Assembly
Authors: Zhang Tao , Chang Guangtao , Guo Qipeng
Published: September 2020

Polymer organogels formed through dynamic interactions are interesting for various applications. The fabrication of polymer organogels in polar solvents through ionic interaction is rare, although such organogels in non-polar organic solvents have been well studied. Herein, polymer organogels in a polar solvent N,N-dimethyl formamide (DMF) were fabricated from a triblock copolymer, poly(4-vinyl pyridine)-block-poly(ethylene glycol)-block-poly(4-vinyl pyridine) (4VPm-EGn-4VPm), and a fluorinated surfactant, perfluorooctanoic acid (PFOA), and their microphase separation and properties were studied. Ordered microphase separation and the crystalline structures were revealed by small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS), respectively. All the 4VPm-EGn-4VPm/PFOA organogels are sensitive to temperature, and the ratio of PFOA to pyridine groups reversibly. The polymer organogels are also responsive to triethylamine and triethylammonium acetate.
Novel Activated Carbon Nanofibers Composited with Cost-Effective Graphene-Based Materials for Enhanced Adsorption Performance toward Methane
Authors: Che Othman Faten Ermala , Yusof Norhaniza , Yub Harun Noorfidza , Bilad Muhammad Roil , Jaafar Juhana , Aziz Farhana , Wan Salleh Wan Norharyati , Ismail Ahmad Fauzi
Published: September 2020

Various types of activated carbon nanofibers’ (ACNFs) composites have been extensively studied and reported recently due to their extraordinary properties and applications. This study reports the fabrication and assessments of ACNFs incorporated with graphene-based materials, known as gACNFs, via simple electrospinning and subsequent physical activation process. TGA analysis proved graphene-derived rice husk ashes (GRHA)/ACNFs possess twice the carbon yield and thermally stable properties compared to other samples. Raman spectra, XRD, and FTIR analyses explained the chemical structures in all resultant gACNFs samples. The SEM and EDX results revealed the average fiber diameters of the gACNFs, ranging from 250 to 400 nm, and the successful incorporation of both GRHA and reduced graphene oxide (rGO) into the ACNFs’ structures. The results revealed that ACNFs incorporated with GRHA possesses the highest specific surface area (SSA), of 384 m2/g, with high micropore volume, of 0.1580 cm3/g, which is up to 88% of the total pore volume. The GRHA/ACNF was found to be a better adsorbent for CH4 compared to pristine ACNFs and reduced graphene oxide (rGO/ACNF) as it showed sorption up to 66.40 mmol/g at 25 °C and 12 bar. The sorption capacity of the GRHA/ACNF was impressively higher than earlier reported studies on ACNFs and ACNF composites. Interestingly, the CH4 adsorption of all ACNF samples obeyed the pseudo-second-order kinetic model at low pressure (4 bar), indicating the chemisorption behaviors. However, it obeyed the pseudo-first order at higher pressures (8 and 12 bar), indicating the physisorption behaviors. These results correspond to the textural properties that describe that the high adsorption capacity of CH4 at high pressure is mainly dependent upon the specific surface area (SSA), pore size distribution, and the suitable range of pore size.
Facile One-Pot Synthesis of Hyperbranched Glycopolymers in Aqueous Solution via a Hydroxy/Cu(III) Redox Process
Authors: Liu Feng , Zhang Yuangong , Hao Xiaohui , Zhou Qian , Zheng Ying , Bai Libin , Zhang Hailei
Published: September 2020

In this study, a self-condensing vinyl copolymerization/redox (SCVP/Redox) system was constructed to prepare hyperbranched poly(methyl-6-O-methacryloyl-α-D-glucoside) by using Cu(III) as the initiator in aqueous solution, in which the –OH group in C-2, C-3 and C-4 position on pyranose rings could be initiated by Cu(III). The branched and linear units were clearly distinguished by nuclear magnetic resonance (1H NMR) to estimate the degree of branching (DB). When the ratio of Cu(III) to monomer fixed at 0.5:1, the DB value reached 0.32, which was higher than the product initiated by Ce(IV). Moreover, the inhibition activity of the products on amyloid fibrillation was investigated by using the hen egg-white lysozyme (HEWL) as a model based on the difference of the initiation sites. The results showed that the –OH groups in C-4 position might play an important role in this process.
A Review on Fault Detection and Process Diagnostics in Industrial Processes
Authors: Park You-Jin , Fan Shu-Kai S. , Hsu Chia-Yu
Published: September 2020

The main roles of fault detection and diagnosis (FDD) for industrial processes are to make an effective indicator which can identify faulty status of a process and then to take a proper action against a future failure or unfavorable accidents. In order to enhance many process performances (e.g., quality and throughput), FDD has attracted great attention from various industrial sectors. Many traditional FDD techniques have been developed for checking the existence of a trend or pattern in the process or whether a certain process variable behaves normally or not. However, they might fail to produce several hidden characteristics of the process or fail to discover the faults in processes due to underlying process dynamics. In this paper, we present current research and developments of FDD approaches for process monitoring as well as a broad literature review of many useful FDD approaches.
Multi-Condition Optimization of Cavitation Performance on a Double-Suction Centrifugal Pump Based on ANN and NSGA-II
Authors: Wang Wenjie , Li Yanpin , Osman Majeed Koranteng , Yuan Shouqi , Zhang Benying , Liu Jun
Published: September 2020

Double-suction centrifugal pumps form an integral part of power plant systems in maintaining operational stability. However, there has been a common problem of achieving a better cavitation performance over a wider operating range because the traditional approach for impeller design often leads to the design effect not meeting the operational needs at off-design conditions. In addressing the problem, an optimization scheme was designed with the hub and shroud inlet angles of the double-suction impeller to minimize the suction performance at non-design flow conditions. A practical approach that speeds up the cavitation simulation process was applied to solve the experimental design, and a multi-layer feed forward artificial neural network (ANN) was combined with the non-dominated sorting genetic algorithm II to solve the multi-objective problem into three-dimensional (3D) Pareto optimal solutions that meet the optimization objective. At the design point, the suction performance was improved by 6.9%. At non-design flow conditions, the cavitation performance was improved by 3.5% at 1.2Qd overload condition, 4% at 0.8Qd, and 5% at 0.6Qd. Additionally, there was significant reduction in the attached cavity distribution in the impeller and suction domains when the optimized model was compared to the original model at off-design points. Finally, the optimization established a faster method for a three-objective optimization of cavitation performance using ANN and 3D Pareto solutions.
New Perspectives on Iron-Based Nanostructures
Authors: Taghizadeh Seyedeh-Masoumeh , Berenjian Aydin , Zare Marziyeh , Ebrahiminezhad Alireza
Published: September 2020

Among all minerals, iron is one of the elements identified early by human beings to take advantage of and be used. The role of iron in human life is so great that it made an era in the ages of humanity. Pure iron has a shiny grayish-silver color, but after combining with oxygen and water it can make a colorful set of materials with divergent properties. This diversity sometimes appears ambiguous but provides variety of applications. In fact, iron can come in different forms: zero-valent iron (pure iron), iron oxides, iron hydroxides, and iron oxide hydroxides. By taking these divergent materials into the nano realm, new properties are exhibited, providing us with even more applications. This review deals with iron as a magic element in the nano realm and provides comprehensive data about its structure, properties, synthesis techniques, and applications of various forms of iron-based nanostructures in the science, medicine, and technology sectors.
Influence of β-Stabilizers on the α-Ti→ω-Ti Transformation in Ti-Based Alloys
Authors: Kilmametov Askar , Gornakova Alena , Karpov Mikhail , Afonikova Natalia , Korneva Anna , Zięba Pawel , Baretzky Brigitte , Straumal Boris
Published: September 2020

The development of next generation Ti-based alloys demand completely new processes and approaches. In particular, the Ti-alloys of next generation will contain not only α-Ti and β-Ti phases, but also small amounts of ω-phase and intermetallic compounds. The β→ω phase transformation induced by high-pressure torsion (HPT) has been studied in detail recently. In this work, we investigated the HPT-induced α→ω phase transformation. For this purpose, we added various β-stabilizers into α-Ti matrix of studied Ti-alloys. Ti-alloys with 4% Fe, 2% Cr, 3% Ni, and 4% Co (wt. %) have been annealed at the temperatures below their point of eutectoid decomposition, from β-Ti to α-Ti, and respective intermetallics (TiFe, Ti2Co, Ti2Ni, TiCr2). Volume fraction of HPT-driven ω-phase (from ≤5 up to ~80%) depended on the amount of alloying element dissolved in the α-matrix. Evaluation of lattice parameters revealed accelerated mass transfer during HPT at room temperature corresponding to bulk diffusion in α-Ti at ~600 °С.
Optimization Algorithm and Joint Simulation to Micro Thermal Deformation Using Temperature Measurement in the Orifice of Hydraulic Valve
Authors: Chen Qianpeng , Ji Hong , Zhao Hongke , Zhao Jing
Published: September 2020

When exposed to viscous heating, hydraulic valve orifices experience thermal deformation, which causes spool clamping and actuator disorder. Quantitative research on thermal deformation can help reveal the micro-mechanism of spool clamping. In this study, miniature thermocouples are embedded into a valve orifice with an opening size of 1 mm to measure temperature distribution. An optimization algorithm based on measurement data (M-OA) for the thermal deformation of the valve orifice is proposed. The temperature and thermal deformation of the valve orifice are calculated through Fluent and Workbench joint simulation, with the measurement data serving as boundary conditions. Results show that, for a valve orifice with a valve wall length of 18 mm, when the temperature of the sharp edge is at 60 °C, thermal deformation measures 7.7 μm via observation and 7.62803 μm via M-OA, indicating that the M-OA method is reliable. The results of the joint simulation can be accepted because measurements of temperature reached an accuracy rate of 95%, and that of deformation reached 82.7%. A large drop in pressure led to a rapid increase in temperature, causing serious thermal deformation of the valve orifice. With an inlet pressure of 3 MPa, the temperature of the sharp edge reached 72.9 °C within 110 min, and radial thermal deformation can reach 8.3 μm. Such deformation poses great risk of spool clamping for a spool valve of Φ36 mm.
A Review of Stereolithography: Processes and Systems
Authors: Huang Jigang , Qin Qin , Wang Jie
Published: September 2020

Being the earliest form of additive manufacturing, stereolithography (SLA) fabricates 3D objects by selectively solidifying the liquid resin through a photopolymerization reaction. The ability to fabricate objects with high accuracy as well as a wide variety of materials brings much attention to stereolithography. Since its invention in the 1980s, SLA underwent four generations of major technological innovation over the past 40 years. These innovations have thus resulted in a diversified range of stereolithography systems with dramatically improved resolution, throughput, and materials selection for creating complex 3D objects and devices. In this paper, we review the four generations of stereolithography processes, which are scanning, projection, continuous and volumetric stereolithography. For each generation, representative stereolithography system configurations are also discussed in detail. In addition, other derivative technologies, such as scanning–projection, multi-material, and magnetically assisted stereolithography processes, are also included in this review.
Principles and Policies for Recycling Decisions and Risk Management
Authors: Gehandler Jonatan , Millgård Ulrika
Published: September 2020

Swedish recycling businesses argue that the Non-Toxic Environmental target gets too much weight and that resource efficiency gets too little focus, which results in decreased recycling. The purpose of this paper is to highlight different factors that recycling of waste decisions should consider, as well as contributing to a constructive discussion of the overall principles and policies for recycling. How recycling works in practice is explored based on nine interviews with stakeholders from the governmental agency level to recycling businesses. Theory with regards to ethics, risk, decision-making, governmental policy and laws is summarised. Finally, the discrepancy and connection between practice and theory is analysed. If recycling of waste is seen as a decision problem, the choice is between to recycle (in different ways) or not to recycle (i.e., energy recovery and/or landfill). Based on risk and decision theory, all relevant goals should be considered. This requires a broader problem framing when goals are in conflict. All parties agree that recycled and virgin material should be treated equally. From a higher policy perspective, it should then be demonstrated that any use of material (recycled and/or virgin) minimize environmental impact and promotes long-term sustainability.
Optimal Dividend Payment in De Finetti Models: Survey and New Results and Strategies
Authors: Hipp Christian
Published: September 2020

We consider optimal dividend payment under the constraint that the with-dividend ruin probability does not exceed a given value α. This is done in most simple discrete De Finetti models. We characterize the value function V(s,α) for initial surplus s of this problem, characterize the corresponding optimal dividend strategies, and present an algorithm for its computation. In an earlier solution to this problem, a Hamilton-Jacobi-Bellman equation for V(s,α) can be found which leads to its representation as the limit of a monotone iteration scheme. However, this scheme is too complex for numerical computations. Here, we introduce the class of two-barrier dividend strategies with the following property: when dividends are paid above a barrier B, i.e., a dividend of size 1 is paid when reaching B+1 from B, then we repeat this dividend payment until reaching a limit L for some 0≤L≤B. For these strategies we obtain explicit formulas for ruin probabilities and present values of dividend payments, as well as simplifications of the above iteration scheme. The results of numerical experiments show that the values V(s,α) obtained in earlier work can be improved, they are suboptimal.
Computational Design Thinking and Physical Computing: Preliminary Observations of a Pilot Study
Authors: Alden Dochshanov , Tramonti Michela
Published: September 2020

Today’s technological development inevitably defies educational approaches in terms of future demand for skills to be imparted. Among other skills, the capacity to operate and communicate effectively within multidisciplinary realms is duly considered as the fundamental one. Educational robotics (ER) and STEM do constitute a suitable framework for the development of these specific skills. Moreover, competences such as computational (CT) and design thinking (DT) have already been nominated as necessary to adapt to the future and relevant for innovation. The years of independent development and evidence of practical implementation justify the maturity of the related methodological approaches and emerging gradual shift towards their combination. In this regard, the actual work presents a pilot experience of the combined application of computational design thinking and educational robotics in the case of a 9-to-11-year-old target audience. The approach utilizes a novel platform developed under the project Coding4Girls combining design thinking and game-based learning and introduces physical computing through consecutive assembling and programming an IR-controlled robot-car. The core of the learning path consists in the development of primary programming skills and their gradual transfer into the physical realm. The method, as the study demonstrates, is capable of helping keep students both motivated and result-oriented throughout the duration of the course.
Assessing Salt Marsh Vulnerability Using High-Resolution Hyperspectral Imagery
Authors: Goldsmith Sarah B. , Eon Rehman S. , Lapszynski Christopher S. , Badura Gregory P. , Osgood David T. , Bachmann Charles M. , Tyler Anna Christina
Published: September 2020

Change in the coastal zone is accelerating with external forcing by sea-level rise, nutrient loading, drought, and over-harvest, leading to significant stress on the foundation plant species of coastal salt marshes. The rapid evolution of marsh state induced by these drivers makes the ability to detect stressors prior to marsh loss important. However, field work in coastal salt marshes can be challenging due to limited access and their fragile nature. Thus, remote sensing approaches hold promise for rapid and accurate determination of marsh state across multiple spatial scales. In this study, we evaluated the use of remote sensing tools to detect three dominant stressors on Spartina alterniflora. We took advantage of a barrier island salt marsh chronosequence in Virginia, USA, where marshes of different ages and level of stressor exist side by side. We collected hyperspectral imagery of plants along with salinity, sediment redox potential, and foliar nitrogen content in the field. We also conducted a greenhouse study where we manipulated environmental conditions. We found that models developed for stressors based on plant spectral response correlated well with salinity and foliar nitrogen within the greenhouse and field data, but were not transferable from lab to field, likely due to the limited range of conditions explored within the greenhouse experiments and the coincidence of multiple stressors in the field. This study is an important step towards the development of a remote sensing tool for tracking of ecosystem development, marsh health, and future ecosystem services.
An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover
Authors: Lyu Du , Liu Baoyuan , Zhang Xiaoping , Yang Xihua , He Liang , He Jie , Guo Jinwei , Wang Jufeng , Cao Qi
Published: September 2020

Remote sensing technology has been widely used to estimate fractional vegetation cover (FVC) at global and regional scales. Accurate and consistent field spectral measurements are required to develop and validate spectral indices for FVC estimation. However, there are rarely any experimental studies to determine the appropriate times for field spectral measurements, and the existing guidelines or references are rather general or inconsistent, it is still not agreed upon and detailed experiments are missing for a local research. In this experiment, five groundcover objects were measured continuously from 07:30 a.m. to 17:30 p.m. local time in three consecutive sunny days using a portable spectrometer. The coefficients of variation (CV) were applied to investigate the reflectance variation at wavelengths corresponding to MODIS satellite channels and the derived spectral indices used to estimate FVC, including photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV). The results reveal little variation in the reflectance measured between 10:00 a.m. and 16:00 p.m., with CV values generally less than 10%. The CV values of FVC spectral indices for estimating PV, NPV and bare soil (BS) are generally less than 3%. While more experiments are yet to be carried out at different locations and in different seasons, the findings so far imply that the in situ spectrum measured between 9:00 a.m. and 17:00 p.m. local time would be useful to discriminate FVC objects and validate satellite estimates-based indices using visible, near-infrared and shortwave infrared channels.
Application Study on Double-Constrained Change Detection for Land Use/Land Cover Based on GF-6 WFV Imageries
Authors: Yu Jingxian , Liu Yalan , Ren Yuhuan , Ma Haojie , Wang Dacheng , Jing Yafei , Yu Linjun
Published: September 2020

As a new satellite sensor of the GaoFen (GF) series, GF-6 Wide Field of View (WFV) with the resolution of 16 m has the characteristics of wide coverage, high-frequency imaging and has four new bands of two red-edge, yellow, and purple compared with GF-1 WFV. In order to test the validity of the supplementary bands of GF-6WFV data for change detection of land use/land cover (LULC), this study applied the Double-constrained Change Detection Method (DCDM) that uses the double constraints (change vector intensity and correlation coefficient) for change detection on object-level. According to two GF-6WFV imageries acquired in the Xiong’an New Area in June of 2018 and 2019, feature analysis was performed to determine whether the new bands are helpful to detect the change of LULC first. Then, by coupling these selected features, the intensity of change vector and correlation coefficient were used as the double constraints to perform the change detection. The study demonstrates that the relevant features of the two red-edge bands can achieve the overall accuracy of 89% for change detection of LULC and improved by 2% comparing with using the corresponding temporal GF-1WFV data, while the purple and yellow bands cannot provide enough effective information for this detection. This study can provide theoretical support for the in-depth applications of GF-6 WFV data products in the change detection fields and has explored its applicability and potential in resource and environment monitoring, it is helpful to the further applications.
Drought Model DISS Based on the Fusion of Satellite and Meteorological Data under Variable Climatic Conditions
Authors: Dabrowska-Zielinska Katarzyna , Malinska Alicja , Bochenek Zbigniew , Bartold Maciej , Gurdak Radoslaw , Paradowski Karol , Lagiewska Magdalena
Published: September 2020

The use of effective methods for large-area drought monitoring is an important issue; hence, there have been many attempts to solve this problem. In this study, the Drought Information Satellite System (DISS) index is presented, based on the synergistic use of meteorological data and information derived from satellite images. The index allows us to monitor drought phenomena in various climatic and environmental conditions. The approach utilizes two indices for constructing a drought index: (1) the hydrothermal coefficient (HTC), which characterizes meteorological conditions across the study area over a long-term period; and (2) the temperature condition index (TCI) derived from Moderate-resolution Imaging Spectroradiometer (MODIS) data, which refers instantaneous land surface temperature (LST) to long-term extreme values. The model for drought assessment based on the DISS index was applied for generating drought index maps for Poland for the 2001–2019 vegetation seasons. The performance of the index was verified through comparison of the extent of agricultural drought to the reduction in cereal and maize yield. Analysis of variance revealed a significant relationship between the area of drought determined by the drought index and the decrease in cereal yield due to unfavorable growth conditions. The presented study proves that the proposed drought index can be an effective tool for large-area drought monitoring under variable environmental conditions.
VIIRS Nighttime Light Data for Income Estimation at Local Level
Authors: Ivan Kinga , Holobâcă Iulian-Horia , Benedek József , Török Ibolya
Published: September 2020

The aim of the paper is to develop a model for the real-time estimation of local level income data by combining machine learning, Earth Observation, and Geographic Information System. More exactly, we estimated the income per capita by help of a machine learning model for 46 cities with more than 50,000 inhabitants, based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime satellite images from 2012–2018. For the automation of calculation, a new ModelBuilder type tool was developed within the ArcGIS software called EO-Incity (Earth Observation–Income city). The sum of light (SOL) data extracted by means of the EO-Incity tool and the observed income data were integrated in an algorithm within the MATLAB software in order to calculate a transfer equation and the average error. The results achieved were subsequently reintegrated in EO-Incity and used for the estimation of the income value at local level. The regression analyses highlighted a stable and strong relationship between SOL and income for the analyzed cities. The EO-Incity tool and the machine learning model proved to be efficient in the real-time estimation of the income at local level. When integrated in the information systems specific for smart cities, they can serve as a support for decision-making in order to fight poverty and reduce social inequalities.
Mapping Crop Types in Southeast India with Smartphone Crowdsourcing and Deep Learning
Authors: Wang Sherrie , Di Tommaso Stefania , Faulkner Joey , Friedel Thomas , Kennepohl Alexander , Strey Rob , Lobell David B.
Published: September 2020

High resolution satellite imagery and modern machine learning methods hold the potential to fill existing data gaps in where crops are grown around the world at a sub-field level. However, high resolution crop type maps have remained challenging to create in developing regions due to a lack of ground truth labels for model development. In this work, we explore the use of crowdsourced data, Sentinel-2 and DigitalGlobe imagery, and convolutional neural networks (CNNs) for crop type mapping in India. Plantix, a free app that uses image recognition to help farmers diagnose crop diseases, logged 9 million geolocated photos from 2017–2019 in India, 2 million of which are in the states of Andhra Pradesh and Telangana in India. Crop type labels based on farmer-submitted images were added by domain experts and deep CNNs. The resulting dataset of crop type at coordinates is high in volume, but also high in noise due to location inaccuracies, submissions from out-of-field, and labeling errors. We employed a number of steps to clean the dataset, which included training a CNN on very high resolution DigitalGlobe imagery to filter for points that are within a crop field. With this cleaned dataset, we extracted Sentinel time series at each point and trained another CNN to predict the crop type at each pixel. When evaluated on the highest quality subset of crowdsourced data, the CNN distinguishes rice, cotton, and “other” crops with 74% accuracy in a 3-way classification and outperforms a random forest trained on harmonic regression features. Furthermore, model performance remains stable when low quality points are introduced into the training set. Our results illustrate the potential of non-traditional, high-volume/high-noise datasets for crop type mapping, some improvements that neural networks can achieve over random forests, and the robustness of such methods against moderate levels of training set noise. Lastly, we caution that obstacles like the lack of good Sentinel-2 cloud mask, imperfect mobile device location accuracy, and preservation of privacy while improving data access will need to be addressed before crowdsourcing can widely and reliably be used to map crops in smallholder systems.
An Efficient Near-Field Localization Method of Coherently Distributed Strictly Non-circular Signals
Authors: Kuang Meidong , Wang Ling , Wang Yuexian , Xie Jian
Published: September 2020

For the near-field localization of non-circular distributed signals with spacial probability density functions (PDF), a novel algorithm is proposed in this paper. The traditional algorithms dealing with the distributed source are only for the far-field sources, and they need two-dimensional (2D) search or omit the angular spread parameter. As a result, these algorithms are no longer inapplicable for near-filed localization. Hence the near-filed sources that obey a classical probability distribution are studied and the corresponding specific expressions are given, providing merits for the near-field signal localization. Additionally, non-circularity of the incident signal is taken into account in order to improve the estimation accuracy. For the steering vector of spatially distributed signals, we first give an approximate expression in a non-integral form, and it provides the possibility of separating the parameters to be estimated from the spatially discrete parameters of the signal. Next, based on the rank-reduced (RARE) algorithm, direction of arrival (DOA) and range can be obtained through two one-dimensional (1-D) searches separately, and thus the computational complexity of the proposed algorithm is reduced significantly, and improvements to estimation accuracy and identifiability are achieved, compared with other existing algorithms. Finally, the effectiveness of the algorithm is verified by simulation.