bluuebunny/crossref_metadata_2025 huggingface dataset:
Constitutive Expression of Aechmea fasciata SPL14 (AfSPL14) Accelerates Flowering and Changes the Plant Architecture in Arabidopsis
Authors: Lei Ming , Li Zhi-ying , Wang Jia-bin , Fu Yun-liu , Ao Meng-fei , Xu Li
Published: July 2018

Variations in flowering time and plant architecture have a crucial impact on crop biomass and yield, as well as the aesthetic value of ornamental plants. Aechmea fasciata, a member of the Bromeliaceae family, is a bromeliad variety that is commonly cultivated worldwide. Here, we report the characterization of AfSPL14, a squamosa promoter binding protein-like gene in A. fasciata. AfSPL14 was predominantly expressed in the young vegetative organs of adult plants. The expression of AfSPL14 could be upregulated within 1 h by exogenous ethephon treatment. The constitutive expression of AfSPL14 in Arabidopsis thaliana caused early flowering and variations in plant architecture, including smaller rosette leaves and thicker and increased numbers of main inflorescences. Our findings suggest that AfSPL14 may help facilitate the molecular breeding of A. fasciata, other ornamental and edible bromeliads (e.g., pineapple), and even cereal crops.
Using Spectral Representation to Classify Proteins’ Conformational States
Authors: Saberi Fathi Seyed Majid , Tuszynski Jack A.
Published: July 2018

Numerous proteins are molecular targets for drug action and hence are important in drug discovery. Structure-based computational drug discovery relies on detailed information regarding protein conformations for subsequent drug screening in silico. There are two key issues in analyzing protein conformations in virtual screening. The first considers the protein’s conformational change in response to physical and chemical conditions. The second is the protein’s atomic resolution reconstruction from X-ray crystallography or nuclear magnetic resonance (NMR) data. In this latter problem, information is needed regarding the sample’s position relative to the source of X-rays. Here, we introduce a new measure for classifying protein conformational states using spectral representation and Wigner’s D-functions. Predictions based on the new measure are in good agreement with conformational states of proteins. These results could also be applied to improve conformational alignment of the snapshots given by protein crystallography.
Efficient Lead Finding, Activity Enhancement and Preliminary Selectivity Control of Nuclear Receptor Ligands Bearing a Phenanthridinone Skeleton
Authors: Nishiyama Yuko , Fujii Shinya , Makishima Makoto , Hashimoto Yuichi , Ishikawa Minoru
Published: July 2018

Background: Nuclear receptors (NRs) are considered as potential drug targets because they control diverse biological functions. However, steroidal ligands for NRs have the potential to cross-react with other nuclear receptors, so development of non-steroidal NR ligands is desirable to obtain safer agents for clinical use. We anticipated that efficient lead finding and enhancement of activity toward nuclear receptors recognizing endogenous steroidal ligands might be achieved by exhaustive evaluation of a steroid surrogate library coupled with examination of structure-activity relationships (SAR). Method: We evaluated our library of RORs (retinoic acid receptor-related orphan receptors) inverse agonists and/or PR (progesterone receptor) antagonists based on the phenanthridinone skeleton for antagonistic activities toward liver X receptors (LXRs), androgen receptor (AR) and glucocorticoid receptor (GR) and examined their SAR. Results: Potent LXRβ, AR, and GR antagonists were identified. SAR studies led to a potent AR antagonist (IC50: 0.059 μM). Conclusions: Our approach proved effective for efficient lead finding, activity enhancement and preliminary control of selectivity over other receptors. The phenanthridinone skeleton appears to be a promising steroid surrogate.
Interference with Processing Negative Stimuli in Problematic Internet Users: Preliminary Evidence from an Emotional Stroop Task
Authors: Schimmenti Adriano , Starcevic Vladan , Gervasi Alessia , Deleuze Jory , Billieux Joël
Published: July 2018

Although it has been proposed that problematic Internet use (PIU) may represent a dysfunctional coping strategy in response to negative emotional states, there is a lack of experimental studies that directly test how individuals with PIU process emotional stimuli. In this study, we used an emotional Stroop task to examine the implicit bias toward positive and negative words in a sample of 100 individuals (54 females) who also completed questionnaires assessing PIU and current affect states. A significant interaction was observed between PIU and emotional Stroop effects (ESEs), with participants who displayed prominent PIU symptoms showing higher ESEs for negative words compared to other participants. No significant differences were found on the ESEs for positive words among participants. These findings suggest that PIU may be linked to a specific emotional interference with processing negative stimuli, thus supporting the view that PIU is a dysfunctional strategy to cope with negative affect. A potential treatment implication for individuals with PIU includes a need to enhance the capacity to process and regulate negative feelings.
Lubrication Performance of α-Zirconium Phosphates as an Anti-Wear Additive in Vegetable Oil-Based Anhydrous Calcium Grease
Authors: Dai Yingjing , Xu Hong , Dong Jinxiang
Published: July 2018

Vegetable oil has significant potential as a base oil, and substitute for mineral oil in grease formulation due to its biodegradability, low toxicity and excellent lubrication. This paper studied the development of vegetable oil-based greases with α-Zr(HPO4)2·H2O (α-ZrP) as an additive, exploring base oil influence in tribological behavior. The results demonstrated that the addition of α-ZrP in vegetable-based greases is beneficial to anti-wear property. α-ZrP particles exhibit good performance in anti-wear, friction-reduction and load-carrying capacity, and its tribological performances are better than the normally used molybdenum disulfide and graphite additives. Owing to its superior tribological properties as a vegetable oil-based grease additive, α-ZrP holds great potential for use in environmentally friendly applications in the future.
Analytical Solutions for Stochastic Vibration of Orthotropic Membrane under Random Impact Load
Authors: Li Dong , Zheng Zhou-Lian , Yang Rui , Zhang Peng
Published: July 2018

Orthotropic membrane materials have been applied in the numerous fields, such as civil engineering, space and aeronautics, and mechanical engineering, among others. During their serving lifespan, these membranes are always facing strong stochastic vibrations induced by the random impact load such as hail, heavy rain, and noise, among others. In this paper, the stochastic vibration problem of orthotropic membrane subjected to random impact load is investigated. The statistical characteristics of random impact load are initially obtained based on the stochastic pulse theory. Then, the Von Karman theory is applied to model the nonlinear vibration of membrane with geometric nonlinearity, which is then used to derive and solve the corresponding fokker–plank–kolmogorov (FPK). The theoretical model developed is validated by means of experiment study and monte carlo simulation (MCS) analysis. The effects of variables like pretension force, velocity of impact load, and material features on stochastic dynamic behavior of membranes are discussed in detail. This exposition provides theoretical framework for stochastic vibration control and design of membranes subjected to random dynamic load.
Influence of Acid, Ethanol, and Anthocyanin Pigment on the Optical and Mechanical Properties of a Nanohybrid Dental Composite Resin
Authors: Hwang Sukhyun , Chung Shin Hye , Lee Jung-Tae , Kim Yong-Tae , Kim Yoo Jin , Oh Soram , Yeo In-Sung Luke
Published: July 2018

This study investigated the influences of acidity, ethanol, and pigment on the optical properties, microhardness, and surface roughness (Ra) of a nanohybrid dental composite resin. A total of 108 disc-shaped specimens were fabricated using a nanohybrid dental composite and allocated into 36 different storage solutions according to the levels of pH (2.0, 3.0, 4.0, and 5.5), ethanol (0%, 20%, and 40%), and anthocyanin pigment (0%, 2.5%, and 12.5%). Measurements of the colorimetric parameter and the amount of color change (ΔE), translucency parameter (TP), microhardness, and surface roughness (Ra) were performed at 24 h (baseline), 1-, 2-, 3-, and 4-weeks. Repeated measures of analysis of variance (ANOVA) with a Tukey honestly significant difference test and Pearson correlation analysis were carried out (α = 0.05). Pigment of 12.5% or 40% ethanol significantly increased the ΔE (P < 0.001, P = 0.048, respectively). Pigment of 2.5% or 12.5% significantly decreased the TP (P = 0.001, P < 0.001, respectively). Microhardness of composite resin stored in pH 2.0, 3.0, 4.0 solution was lower than that for pH 5.5 (P < 0.001). Pigment, ethanol, and pH did not influence the Ra. TP change and ΔE, and Ra and ΔE had a significant positive correlation (P < 0.05). In conclusion, pigment and ethanol levels influenced the optical properties and acidity affected the microhardness of composite resin.
Beam Diameter Dependence of Performance in Thick-Layer and High-Power Selective Laser Melting of Ti-6Al-4V
Authors: Shi Wentian , Liu Yude , Shi Xuezhi , Hou Yanjun , Wang Peng , Song Guohua
Published: July 2018

A 400 W high-power laser was used to fabricate 200-µm-thick Ti-6Al-4V samples to evaluate the effects of small (50 μm) and large (200 μm) beam diameter on density, microstructure and mechanical properties. A series of single-track experiments demonstrated that it was challenging for the small-beam laser to fabricate smooth and defect-free scan tracks. A larger beam diameter efficiently avoided process instability and provided a more stable and uniform melt pool. By increasing the beam diameter, the density of multilayer samples reached 99.95% of the theoretical value, which is much higher than that achieved with the small beam diameter. However, it was difficult to completely eliminate defects due to serious spatter and evaporation. Moreover, all of the generated samples had relatively coarse surfaces. For the large beam diameter of 200 µm, the optimal yield strength, ultimate tensile strength and elongation were 1150 MPa, 1200 MPa and 8.02%, respectively. In comparison, the small beam diameter of 50 µm resulted in values of 1035 MPa, 1100 MPa and 5.91%, respectively. Overall, the large-diameter laser is more suitable for high-power selective laser melting (SLM) technology, especially for thick layers.
Soft Rough Neutrosophic Influence Graphs with Application
Authors: Masood Malik Hafsa , Akram Muhammad , Smarandache Florentin
Published: July 2018

In this paper, we apply the notion of soft rough neutrosophic sets to graph theory. We develop certain new concepts, including soft rough neutrosophic graphs, soft rough neutrosophic influence graphs, soft rough neutrosophic influence cycles and soft rough neutrosophic influence trees. We illustrate these concepts with examples, and investigate some of their properties. We solve the decision-making problem by using our proposed algorithm.
Zinc Recovery from Steelmaking Dust by Hydrometallurgical Methods
Authors: Palimąka Piotr , Pietrzyk Stanisław , Stępień Michał , Ciećko Katarzyna , Nejman Ilona
Published: July 2018

Hydrometallurgical recovery of zinc from electric arc furnace dust was investigated on a laboratory scale, using aqueous sodium hydroxide solution as a leaching agent. Special attention was paid to the effect of NaOH concentration, temperature and liquid/solid phase ratio on the zinc leachability. It was found that all tested factors increased the leachability, with the maximum efficiency of 88% obtained in a 6 M NaOH solution at a temperature of 80 °C and the liquid/solid phase ratio of 40. The test results confirmed the high selectivity of the zinc leaching agent. In spite of this, complete recovery of zinc from steelmaking dust has proved to be very difficult due to the occurrence of this element in the form of stable and sparingly soluble ZnFe2O4 ferrite. Purification of the solution by cementation and electrolysis gave zinc of purity 99.88% in powder form.
316L Stainless Steel Manufactured by Selective Laser Melting and Its Biocompatibility with or without Hydroxyapatite Coating
Authors: Luo Jiapeng , Jia Xiao , Gu Ruinan , Zhou Peng , Huang Yongjiang , Sun Jianfei , Yan Ming
Published: July 2018

To fabricate metallic 316L/HA (hydroxyapatite) materials which meet the requirements of an implant’s mechanical properties and bioactivity for its function as human bone replacement, selective laser melting (SLM) has been employed in this study to prepare a 316L stainless steel matrix, which was subsequently covered with a hydroxyapatite (HA) coating using the sol-gel method. High density (98.9%) as-printed parts were prepared using a laser power of 230 W and a scanning speed of 800 mm/s. Austenite and residual acicular ferrite existed in the microstructure of the as-printed 316L stainless steel, and the sub-grain was uniform, whose primary dendrite spacing was around 0.35 μm. The as-printed 316L stainless steel showed the highest Vickers hardness, elastic modulus, and tensile strength at ~ (~ means about; same applies below unless stated otherwise) 247 HV, ~214.2 GPa, and ~730 MPa, respectively. The elongation corresponding to the highest tensile strength was ~38.8%. The 316L/HA structure, measured by the Relative Growth Rate (RGR) value, exhibited no cell cytotoxicity, and presented better biocompatibility than the uncoated as-printed and as-cast 316L samples.
Metastable Eutectoid Transformation in Spheroidal Graphite Cast Iron: Modeling and Validation
Authors: Carazo Fernando D. , García Laura N. , Celentano Diego J.
Published: July 2018

This paper presents a new microstructural model of the metastable eutectoid transformation in spheroidal graphite cast irons. The model takes into account the nucleation and growth of pearlite nodules. The nucleation is assumed to be continuous and dependent on the metastable undercooling associated with the upper limit of the three-phase field, while the growth rate is considered to be ruled by the silicon partitioning between ferrite and cementite at the pearlite/austenite front. The initial conditions for the metastable transformation are obtained from a microstructural simulation of solidification, graphite growth, and stable eutectoid transformation. These microstructural models are coupled with the thermal balance solved at a macroscopic level via the finite element method. The experimental validation of the metastable eutectoid model achieved by comparison with measured values of ferrite, graphite, and pearlite fractions at the end of the cooling process demonstrates the sound predictive capabilities of the proposed model.
Detection of Legionella anisa in Water from Hospital Dental Chair Units and Molecular Characterization by Whole-Genome Sequencing
Authors: Fleres Giuseppe , Couto Natacha , Lokate Mariette , Van der Sluis Luc , Ginevra Christophe , Jarraud Sophie , Deurenberg Ruud , Rossen John , García-Cobos Silvia , Friedrich Alex
Published: July 2018

This study aims to assess contamination with Legionella spp. in water from dental chair units (DCUs) of a hospital dental ward and to perform its molecular characterization by whole-genome sequencing (WGS). We collect eight water samples (250 mL) from four DCUs (sink and water-syringe). Samples are tested for the presence of Legionella spp. (CFUs/mL) by culturing according to the Nederland Norm (NEN) 6265. Three DCUs are found positive for Legionella anisa, and four isolates are cultured (sink n = 2, water-syringe n = 1; two isolates from the same chair) with 1 × 102 CFU/mL. Whole-genome multi-locus sequence typing (wgMLST) results indicate that all strains belong to the same cluster with two to four allele differences. Classical culture combined with WGS allows the identification of a unique clone of L. anisa in several DCUs in the same hospital dental ward. This may indicate a common contamination source in the dental unit waterlines, which was fixed by replacing the chairs and main pipeline of the unit. Our results reveal tap water contamination in direct contact with patients and the usefulness of WGS to investigate bacterial molecular epidemiology.
Continuous or Batch Solid-Liquid Extraction of Antioxidant Compounds from Seeds of Sterculia apetala Plant and Kinetic Release Study
Authors: Mosca Federica , Hidalgo Gádor Indra , Villasante Juliana , Almajano María Pilar
Published: July 2018

This work has been intended to investigate the antioxidant properties of compounds extracted from seeds of Sterculia apetala (a plant from Central America) in order to add further results to the relatively poor existing literature on the beneficial properties of this plant. Different extraction methodologies were used such as batch or continuous extraction conditions using water or ethanol 50% as solvents. The kinetic study has allowed estimation of the effective diffusion coefficients in a continuous solid-liquid extraction, highlighting the strict dependence of the diffusion rate and temperature and kind of solvent, showing the highest diffusion rate with ethanol 50% at 60 °C. The comparison between different techniques and two solvents led to the selection of water as the best extraction solvent while batch mechanically-agitated extraction was the most efficient mode, with the benefits of use of an environmental-friendly solvent and reduction in process time to achieve a high amount of extracted phenolic compounds. The analysis techniques used were ABTS and Folin-Ciocalteau methods to investigate the antioxidant activity and quantify the Total Phenolic Content (TPC) respectively. Also, different fatty acids were extracted from Sterculia apetala seeds and analysed by Gas Chromatography in order to quantify other interesting chemical species besides antioxidants.
Heterometallic ZnII–LnIII–ZnII Schiff Base Complexes with Linear or Bent Conformation—Synthesis, Crystal Structures, Luminescent and Magnetic Characterization
Authors: Miroslaw Barbara , Cristóvão Beata , Hnatejko Zbigniew
Published: July 2018

A series of racemic, heteronuclear complexes [Zn2Nd(ac)2(HL)2]NO3·3H2O (1), [Zn2Sm(ac)2(HL)2]NO3·3CH3OH·0.3H2O (2), [Zn2Ln(ac)2(HL)2]NO3·5.33H2O (3–5) (where HL is the dideprotonated form of N,N′-bis(5-bromo-3-methoxysalicylidene)-1,3-diamino-2-propanol, ac = acetate ion, and Ln = Eu (3), Tb (4), Dy (5), respectively) with an achiral multisite coordination Schiff base ligand (H3L) were synthesized and characterized. The X-ray crystallography revealed that the chirality in complexes is centered at lanthanide(III) ions due to two vicinally located μ-acetato-bridging ligands. The presented crystals have isoskeletal coordination units but they crystallize in monoclinic (1, 2) or trigonal crystal systems (3–5) with slightly different conformation. In 1 and 2 the ZnII–LnIII–ZnII coordination core is linear, whereas in isostructural crystals 3–5 the chiral coordination cores are bent and lie on a two-fold axis. The complexes 1, 3–5 show a blue emission attributed to the emission of the ligand. For ZnII2SmIII complex (2) the characteristic emission bands of f-f* transitions were observed. The magnetic properties for compounds 1, 4 and 5 are characteristic for the paramagnetism of the corresponding lanthanide(III) ions.
DNA Origami Nanomachines
Authors: Endo Masayuki , Sugiyama Hiroshi
Published: July 2018

DNA can assemble various molecules and nanomaterials in a programmed fashion and is a powerful tool in the nanotechnology and biology research fields. DNA also allows the construction of desired nanoscale structures via the design of DNA sequences. Structural nanotechnology, especially DNA origami, is widely used to design and create functionalized nanostructures and devices. In addition, DNA molecular machines have been created and are operated by specific DNA strands and external stimuli to perform linear, rotational, and reciprocating movements. Furthermore, complicated molecular systems have been created on DNA nanostructures by arranging multiple molecules and molecular machines precisely to mimic biological systems. Currently, DNA nanomachines, such as molecular motors, are operated on DNA nanostructures. Dynamic DNA nanostructures that have a mechanically controllable system have also been developed. In this review, we describe recent research on new DNA nanomachines and nanosystems that were built on designed DNA nanostructures.
Effects of Cold Rolling and Annealing Prior to Dealloying on the Microstructure of Nanoporous Gold
Authors: Hui Hanyu , Xia Re , Li Juying , Mei Qingsong , Ma Ye , Chen Feng , Lei Yan
Published: July 2018

The properties of nanoporous gold (NPG) were known to be dependent on the microstructure of NPG. In this study, the effects of cold rolling and annealing of the original Ag0.7Au0.3 alloy on the microstructure of NPG produced by dealloying under free corrosion condition were investigated. Ag0.7Au0.3 alloy samples were cold-rolled to different strain levels/thickness reductions up to 98% and annealed at 900 °C for 3 h before dealloying. It was found that cold rolling and annealing of the original alloy can lead to reduced ligament and pore sizes of NPG. Moreover, post-deformation annealing of the original alloy was found to facilitate the formation of a homogeneous and continuous NPG structure. The minima of pore and ligament sizes (both being ~8 nm) with uniform distribution were obtained in the annealed sample with a thickness reduction of 60% for a dealloying time of 7 h. The present study indicated the significant effect of a pre-dealloying treatment of the original alloy (by plastic deformation and annealing) on the formation and optimization of the NPG microstructure produced by dealloying.
Visible Light Driven Photoanodes for Water Oxidation Based on Novel r-GO/β-Cu2V2O7/TiO2 Nanorods Composites
Authors: Shuang Shuang , Girardi Leonardo , Rizzi Gian , Sartorel Andrea , Marega Carla , Zhang Zhengjun , Granozzi Gaetano
Published: July 2018

This paper describes the preparation and the photoelectrochemical performances of visible light driven photoanodes based on novel r-GO/β-Cu2V2O7/TiO2 nanorods/composites. β-Cu2V2O7 was deposited on both fluorine doped tin oxide (FTO) and TiO2 nanorods (NRs)/FTO by a fast and convenient Aerosol Assisted Spray Pyrolysis (AASP) procedure. Ethylenediamine (EN), ammonia and citric acid (CA) were tested as ligands for Cu2+ ions in the aerosol precursors solution. The best-performing deposits, in terms of photocurrent density, were obtained when NH3 was used as ligand. When β-Cu2V2O7 was deposited on the TiO2 NRs a good improvement in the durability of the photoanode was obtained, compared with pure β-Cu2V2O7 on FTO. A further remarkable improvement in durability and photocurrent density was obtained upon addition, by electrophoretic deposition, of reduced graphene oxide (r-GO) flakes on the β-Cu2V2O7/TiO2 composite material. The samples were characterized by X-ray Photoelectron Spectroscopy (XPS), Raman, High Resolution Transmission Electron Microscopy (HR-TEM), Scanning Electron Microscopy (SEM), Wide Angle X-ray Diffraction (WAXD) and UV-Vis spectroscopies. The photoelectrochemical (PEC) performances of β-Cu2V2O7 on FTO, β-Cu2V2O7/TiO2 and r-GO/β-Cu2V2O7/TiO2 were tested in visible light by linear voltammetry and Electrochemical Impedance Spectroscopy (EIS) measurements.
Nutrition and Lung Growth
Authors: Arigliani Michele , Spinelli Alessandro Mauro , Liguoro Ilaria , Cogo Paola
Published: July 2018

Experimental evidence from animal models and epidemiology studies has demonstrated that nutrition affects lung development and may have a lifelong impact on respiratory health. Chronic restriction of nutrients and/or oxygen during pregnancy causes structural changes in the airways and parenchyma that may result in abnormal lung function, which is tracked throughout life. Inadequate nutritional management in very premature infants hampers lung growth and may be a contributing factor in the pathogenesis of bronchopulmonary dysplasia. Recent evidence seems to indicate that infant and childhood malnutrition does not determine lung function impairment even in the presence of reduced lung size due to delayed body growth. This review will focus on the effects of malnutrition occurring at critical time periods such as pregnancy, early life, and childhood, on lung growth and long-term lung function.
Epstein-Barr Virus-Induced Epigenetic Pathogenesis of Viral-Associated Lymphoepithelioma-Like Carcinomas and Natural Killer/T-Cell Lymphomas
Authors: Li Lili , Ma Brigette , Chan Anthony , Chan Francis , Murray Paul , Tao Qian
Published: July 2018

Cancer genome studies of Epstein-Barr virus (EBV)-associated tumors, including lymphoepithelioma-like carcinomas (LELC) of nasopharyngeal (NPC), gastric (EBVaGC) and lung tissues, and natural killer (NK)/T-cell lymphoma (NKTCL), reveal a unique feature of genomic alterations with fewer gene mutations detected than other common cancers. It is known now that epigenetic alterations play a critical role in the pathogenesis of EBV-associated tumors. As an oncogenic virus, EBV establishes its latent and lytic infections in B-lymphoid and epithelial cells, utilizing hijacked cellular epigenetic machinery. EBV-encoded oncoproteins modulate cellular epigenetic machinery to reprogram viral and host epigenomes, especially in the early stage of infection, using host epigenetic regulators. The genome-wide epigenetic alterations further inactivate a series of tumor suppressor genes (TSG) and disrupt key cellular signaling pathways, contributing to EBV-associated cancer initiation and progression. Profiling of genome-wide CpG methylation changes (CpG methylome) have revealed a unique epigenotype of global high-grade methylation of TSGs in EBV-associated tumors. Here, we have summarized recent advances of epigenetic alterations in EBV-associated tumors (LELCs and NKTCL), highlighting the importance of epigenetic etiology in EBV-associated tumorigenesis. Epigenetic study of these EBV-associated tumors will discover valuable biomarkers for their early detection and prognosis prediction, and also develop effective epigenetic therapeutics for these cancers.
Systematic Development of Self-Nanoemulsifying Liquisolid Tablets to Improve the Dissolution and Oral Bioavailability of an Oily Drug, Vitamin K1
Authors: Tong Yongtao , Wang Yuli , Yang Meiyan , Yang Jiahui , Chen Lu , Chu Xiaoyang , Gao Chunhong , Jin Qian , Gong Wei , Gao Chunsheng
Published: July 2018

The purpose of this study is to improve the dissolution and oral bioavailability of an oily drug, vitamin K1 (VK1) by combination of self-nanoemulsifying and liquisolid technologies. The optimal liquid self-nanoemulsifying drug delivery systems (SNEDDS) formulation including VK1 (oil), mixture of soybean lecithin and glycocholic acid (surfactant) and Transcutol HP (cosurfactant) was obtained according to ternary phase diagrams and a central composite design. Based on compatibility, adsorption capacity and dissolution profile, liquid SNEDDS was then solidified on Fujicalin® to form solid SNEDDS by liquisolid technology and compressed directly with excipients into self-nanoemulsifying liquisolid (SNE-L) tablets. Uniform nano-emulsion suspension was formed rapidly when the SNE-L tablets disintegrated in dissolution media and higher drug dissolution was observed compared with the conventional tablets. The results of pharmacokinetic study in beagle dogs showed that the mean Cmax and the area under the curve of SNE-L tablets were remarkably higher than those of conventional tablets, which were consistent with the results of the in vitro dissolution. The relative bioavailability of SNE-L tablets and conventional tablets was approximately 200%. In conclusion, this combination method showed promise to improve the dissolution and oral bioavailability of oily drug vitamin K1.
Dynamics of a Polymer Network Modeled by a Fractal Cactus
Authors: Jurjiu Aurel , Galiceanu Mircea
Published: July 2018

In this paper, we focus on the relaxation dynamics of a polymer network modeled by a fractal cactus. We perform our study in the framework of the generalized Gaussian structure model using both Rouse and Zimm approaches. By performing real-space renormalization transformations, we determine analytically the whole eigenvalue spectrum of the connectivity matrix, thereby rendering possible the analysis of the Rouse-dynamics at very large generations of the structure. The evaluation of the structural and dynamical properties of the fractal network in the Rouse type-approach reveals that they obey scaling and the dynamics is governed by the value of spectral dimension. In the Zimm-type approach, the relaxation quantities show a strong dependence on the strength of the hydrodynamic interaction. For low and medium hydrodynamic interactions, the relaxation quantities do not obey power law behavior, while for slightly larger interactions they do. Under strong hydrodynamic interactions, the storage modulus does not follow power law behavior and the average displacement of the monomer is very low. Remarkably, the theoretical findings with respect to scaling in the intermediate domain of the relaxation quantities are well supported by experimental results from the literature.
Modeling and Optimal Design of Absorbent Enhanced Ammonia Synthesis
Authors: Palys Matthew J. , McCormick Alon , Cussler E. L. , Daoutidis Prodromos
Published: July 2018

Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber–Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber–Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process scales with a 0.77 capacity exponent, and at production scales below 6075 kg/h, it is less expensive than the conventional Haber–Bosch process.
Critical Hydraulic Gradient of Internal Erosion at the Soil–Structure Interface
Authors: Xie Quanyi , Liu Jian , Han Bo , Li Hongtao , Li Yuying , Li Xuanzheng
Published: July 2018

Internal erosion at soil–structure interfaces is a dangerous failure pattern in earth-fill water-retaining structures. However, existing studies concentrate on the investigations of internal erosion by assuming homogeneous materials, while ignoring the vulnerable soil–structure-interface internal erosion in realistic cases. Therefore, orthogonal and single-factor tests are carried out with a newly designed apparatus to investigate the critical hydraulic gradient of internal erosion on soil–structure interfaces. The main conclusions can be draw as follows: (1) the impact order of the three factors is: degree of compaction > roughness > clay content; (2) the critical hydraulic gradient increases as the degree of compaction and clay content increases. This effect is found to be more obvious in the higher range of the degree of soil compaction and clay content. However, there exists an optimum interface roughness making the antiseepage strength at the interface reach a maximum; (3) the evolution of the interface internal erosion develops from inside to outside along the interface, and the soil particles at the interface flow as a whole; and (4) the critical hydraulic gradient of interface internal erosion is related to the shear strength at the interface and the severity and porosity of the soil.
Spatio-Temporal Analysis of Wetland Changes Using a Kernel Extreme Learning Machine Approach
Authors: Lin Yi , Yu Jie , Cai Jianqing , Sneeuw Nico , Li Fengting
Published: July 2018

Natural wetland ecosystems provide not only important habitats for many wildlife species, but also food for migratory and resident animals. In Shanghai, the Chongming Dongtan International Wetland, located at the mouth of the Yangtze River, plays an important role in maintaining both ecosystem health and ecological security of the island. Meanwhile it provides an especially important stopover and overwintering site for migratory birds, being located in the middle of the East Asian-Australasian Flyway. However, with the increase in development intensity and human activities, this wetland suffers from increasing environmental pressure. On the other hand, biological succession in the mudflat wetland makes Chongming Dongtan a rapidly developing and rare ecosystem in the world. Therefore, studying the wetland spatio-temporal change is an important precondition for analyzing the relationship between wetland evolution processes and human activities. This paper presents a novel method for analyzing land-use/cover changes (LUCC) on Chongming Dongtan wetland using multispectral satellite images. Our method mainly takes advantages of a machine learning algorithm, named the Kernel Extreme Learning Machine (K-ELM), which is applied to distinguish between different objects and extract their information from images. In the K-ELM, the kernel trick makes it more stable and accurate. The comparison between K-ELM and three other conventional classification methods indicates that the proposed K-ELM has the highest overall accuracy, especially for distinguishing between Spartina alternflora, Scirpus mariqueter, and Phragmites australis. Meanwhile, its efficiency is remarkable as well. Then a total of eight Landsat TM series images acquired from 1986 to 2013 were used for the LUCC analysis with K-ELM. According to the classification result, the change detection and spatio-temporal quantitative analysis were performed. The specific analysis of different objects are significant for learning about the historical changes to Chongming Dongtan and obtaining the evaluation rules. Generally, the rapid speed of Chongming Dongtan’s urbanization brought about great influence with respect to natural resources and the environment. Integrating the results into the ecological analysis and ecological regional planning of Dongtan could provide a reliable scientific basis for rational planning, development, and the ecological balance and regional sustainability of the wetland area.
Automatic Raft Labeling for Remote Sensing Images via Dual-Scale Homogeneous Convolutional Neural Network
Authors: Shi Tianyang , Xu Qizhi , Zou Zhengxia , Shi Zhenwei
Published: July 2018

Raft-culture is a way of utilizing water for farming aquatic product. Automatic raft-culture monitoring by remote sensing technique is an important way to control the crop’s growth and implement effective management. This paper presents an automatic pixel-wise raft labeling method based on fully convolutional network (FCN). As rafts are always tiny and neatly arranged in images, traditional FCN method fails to extract the clear boundary and other detailed information. Therefore, a homogeneous convolutional neural network (HCN) is designed, which only consists of convolutions and activations to retain all details. We further design a dual-scale structure (DS-HCN) to integrate higher-level contextual information for accomplishing sea–land segmentation and raft labeling at the same time in a uniform framework. A dataset with Gaofen-1 satellite images was collected to verify the effectiveness of our method. DS-HCN shows a satisfactory performance with a better interpretability and a more accurate labeling result.
Estimating the Speed of Ice-Going Ships by Integrating SAR Imagery and Ship Data from an Automatic Identification System
Authors: Similä Markku , Lensu Mikko
Published: July 2018

The automatic identification system (AIS) was developed to support the safety of marine traffic. In ice-covered seas, the ship speeds extracted from AIS data vary with ice conditions that are simultaneously reflected by features in synthetic aperture radar (SAR) images. In this study, the speed variation was related to the SAR features and the results were applied to generate a chart of expected speeds from the SAR image. The study was done in the Gulf of Bothnia in March 2013 for ships with ice class IA Super that are able to navigate without icebreaker assistance. The speeds were normalized to dimensionless units ranging from 0 to 10 for each ship. As the matching between AIS and SAR was complicated by ice drift during the time gap (from hours to two days), we calculated a set of local statistical SAR features over several scales. Random forest tree regression was used to estimate the speed. The accuracy was quantified by mean squared error and by the fraction of estimates close to the actual speeds. These depended strongly on the route and the day. The error varied from 0.4 to 2.7 units2 for daily routes. Sixty-five percent of the estimates deviated by less than one speed unit and 82% by less than 1.5 speed units from the AIS speeds. The estimated daily mean speeds were close to the observations. The largest speed decreases were provided by the estimator in a dampened form or not at all. This improved when the ice chart thickness was included as a predictor.
Detection of Shoot Beetle Stress on Yunnan Pine Forest Using a Coupled LIBERTY2-INFORM Simulation
Authors: Lin Qinan , Huang Huaguo , Yu Linfeng , Wang Jingxu
Published: July 2018

Yunnan pine shoot beetles (PSB), Tomicus yunnanensis and Tomicus minor have spread through southwestern China in the last five years, leading to millions of hectares of forest being damaged. Thus, there is an urgent need to develop an effective approach for accurate early warning and damage assessment of PSB outbreaks. Remote sensing is one of the most efficient methods for this purpose. Despite many studies existing on the mountain pine beetle (MPB), very little work has been undertaken on assessing PSB stress using remote sensing. The objective of this paper was to develop a spectral linear mixing model aided by radiative transfer (RT) and a new Yellow Index (YI) to simulate the reflectance of heterogeneous canopies containing damaged needles and quantitatively inverse their PSB stress. The YI, the fraction of dead needles, is a physically-explicit stress indicator that represents the plot shoots damage ratio (plot SDR). The major steps of this methods include: (1) LIBERTY2 was developed to simulate the reflectance of damaged needles using YI to linearly mix the green needle spectra with the dead needle spectra; (2) LIBERTY2 was coupled with the INFORM model to scale the needle spectra to the canopy scale; and (3) a look-up table (LUT) was created against Sentinel 2 (S2) imagery and inversed leaf chlorophyll content (LCC), green leaf area index (LAI) and plot SDR. The results show that (1) LIBERTY2 effectively simulated the reflectance spectral values on infested needles (mean relative error (MRE) = 1.4–18%), and the YI can indicate the degrees of needles damage; (2) the coupled LIBERTY2-INFORM model is suitable to estimate LAI (R2 = 0.73, RMSE = 0.17 m m−2, NRMSE = 11.41% and the index of agreement (IOA) = 0.92) and LCC (R2 = 0.49, RMSE = 56.24 mg m−2, NRMSE = 25.22% and IOA = 0.72), and is better than the original LIBERTY model (LAI: R2 = 0.38, RMSE = 0.43 m m−2, NRMSE = 28.85% and IOA = 0.68; LCC: R2 = 0.34, RMSE = 76.44 mg m−2, NRMSE = 34.23% and IOA = 0.57); and (3) the inversed YI is positively correlated with the measured plot SDR (R2 = 0.40, RMSE = 0.15). We conclude that the LIBERTY2 model improved the reflectance simulation accuracy of both the needles and canopies, making it suitable for assessing PSB stress. The YI has the potential to assess PSB damage.
Improved Fully Convolutional Network with Conditional Random Fields for Building Extraction
Authors: Shrestha Sanjeevan , Vanneschi Leonardo
Published: July 2018

Building extraction from remotely sensed imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Several published contributions dedicated to the applications of deep convolutional neural networks (DCNN) for building extraction using aerial/satellite imagery exists. However, in all these contributions, high accuracy is always obtained at the price of extremely complex and large network architectures. In this paper, we present an enhanced fully convolutional network (FCN) framework that is designed for building extraction of remotely sensed images by applying conditional random fields (CRFs). The main objective is to propose a methodology selecting a framework that balances high accuracy with low network complexity. A modern activation function, namely, the exponential linear unit (ELU), is applied to improve the performance of the fully convolutional network (FCN), thereby resulting in more accurate building prediction. To further reduce the noise (falsely classified buildings) and to sharpen the boundaries of the buildings, a post-processing conditional random fields (CRFs) is added at the end of the adopted convolutional neural network (CNN) framework. The experiments were conducted on Massachusetts building aerial imagery. The results show that our proposed framework outperformed the fully convolutional network (FCN), which is the existing baseline framework for semantic segmentation, in terms of performance measures such as the F1-score and IoU measure. Additionally, the proposed method outperformed a pre-existing classifier for building extraction using the same dataset in terms of the performance measures and network complexity.
A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
Authors: Yue Jibo , Feng Haikuan , Jin Xiuliang , Yuan Huanhuan , Li Zhenhai , Zhou Chengquan , Yang Guijun , Tian Qingjiu
Published: July 2018

Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot hyperspectral sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates of crop parameters and to map the parameters. The estimated leaf area index (LAI) and above-ground biomass (AGB) are obtained by using linear and exponential equations, random forest (RF) regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot hyperspectral sensor and high-definition digital camera is similar to the results from the ground spectrometer when using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the sensors is crucial in LAI estimates (the wheat LAI cannot be accurately estimated over multiple growing stages when using only crop height). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot hyperspectral sensor, and UAV high-definition digital camera.
Towards a Scalable Software Defined Network-on-Chip for Next Generation Cloud
Authors: Scionti Alberto , Mazumdar Somnath , Portero Antoni
Published: July 2018

The rapid evolution of Cloud-based services and the growing interest in deep learning (DL)-based applications is putting increasing pressure on hyperscalers and general purpose hardware designers to provide more efficient and scalable systems. Cloud-based infrastructures must consist of more energy efficient components. The evolution must take place from the core of the infrastructure (i.e., data centers (DCs)) to the edges (Edge computing) to adequately support new/future applications. Adaptability/elasticity is one of the features required to increase the performance-to-power ratios. Hardware-based mechanisms have been proposed to support system reconfiguration mostly at the processing elements level, while fewer studies have been carried out regarding scalable, modular interconnected sub-systems. In this paper, we propose a scalable Software Defined Network-on-Chip (SDNoC)-based architecture. Our solution can easily be adapted to support devices ranging from low-power computing nodes placed at the edge of the Cloud to high-performance many-core processors in the Cloud DCs, by leveraging on a modular design approach. The proposed design merges the benefits of hierarchical network-on-chip (NoC) topologies (via fusing the ring and the 2D-mesh topology), with those brought by dynamic reconfiguration (i.e., adaptation). Our proposed interconnect allows for creating different types of virtualised topologies aiming at serving different communication requirements and thus providing better resource partitioning (virtual tiles) for concurrent tasks. To further allow the software layer controlling and monitoring of the NoC subsystem, a few customised instructions supporting a data-driven program execution model (PXM) are added to the processing element’s instruction set architecture (ISA). In general, the data-driven programming and execution models are suitable for supporting the DL applications. We also introduce a mechanism to map a high-level programming language embedding concurrent execution models into the basic functionalities offered by our SDNoC for easing the programming of the proposed system. In the reported experiments, we compared our lightweight reconfigurable architecture to a conventional flattened 2D-mesh interconnection subsystem. Results show that our design provides an increment of the data traffic throughput of 9.5% and a reduction of 2.2× of the average packet latency, compared to the flattened 2D-mesh topology connecting the same number of processing elements (PEs) (up to 1024 cores). Similarly, power and resource (on FPGA devices) consumption is also low, confirming good scalability of the proposed architecture.