bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiac Rehabilitation Models around the Globe
Authors: Lima de Melo Ghisi Gabriela , Pesah Ella , Turk-Adawi Karam , Supervia Marta , Lopez Jimenez Francisco , Grace Sherry L.
Published: September 2018

Alternative models of cardiac rehabilitation (CR) delivery, such as home or community-based programs, have been developed to overcome underutilization. However, their availability and characteristics have never been assessed globally. In this cross-sectional study, a piloted survey was administered online to CR programs globally. CR was available in 111/203 (54.7%) countries globally; data were collected in 93 (83.8% country response rate). 1082 surveys (32.1% program response rate) were initiated. Globally, 85 (76.6%) countries with CR offered supervised programs, and 51 (45.9%; or 25.1% of all countries) offered some alternative model. Thirty-eight (34.2%) countries with CR offered home-based programs, with 106 (63.9%) programs offering some form of electronic CR (eCR). Twenty-five (22.5%) countries with CR offered community-based programs. Where available, programs served a mean of 21.4% ± 22.8% of their patients in home-based programs. The median dose for home-based CR was 3 sessions (Q25−Q75 = 1.0–4.0) and for community-based programs was 20 (Q25–Q75 = 9.6–36.0). Seventy-eight (47.0%) respondents did not perceive they had sufficient capacity to meet demand in their home-based program, for reasons including funding and insufficient staff. Where alternative CR models are offered, capacity is insufficient half the time. Home-based CR dose is insufficient to achieve health benefits. Allocation to program model should be evidence-based.
How Specific Abilities Might Throw ‘g’ a Curve: An Idea on How to Capitalize on the Predictive Validity of Specific Cognitive Abilities
Authors: Ziegler Matthias , Peikert Aaron
Published: September 2018

School grades are still used by universities and employers for selection purposes. Thus, identifying determinants of school grades is important. Broadly, two predictor categories can be differentiated from an individual difference perspective: cognitive abilities and personality traits. Over time, evidence accumulated supporting the notion of the g-factor as the best single predictor of school grades. Specific abilities were shown to add little incremental validity. The current paper aims at reviving research on which cognitive abilities predict performance. Based on ideas of criterion contamination and deficiency as well as Spearman’s ability differentiation hypothesis, two mechanisms are suggested which both would lead to curvilinear relations between specific abilities and grades. While the data set provided for this special issue does not allow testing these mechanisms directly, we tested the idea of curvilinear relations. In particular, polynomial regressions were used. Machine learning was applied to identify the best fitting models in each of the subjects math, German, and English. In particular, we fitted polynomial models with varying degrees and evaluated their accuracy with a leave-one-out validation approach. The results show that tests of specific abilities slightly outperform the g-factor when curvilinearity is assumed. Possible theoretical explanations are discussed.
Exponentially Adiabatic Switching in Quantum-Dot Cellular Automata
Authors: Pidaparthi Subhash S. , Lent Craig S.
Published: September 2018

We calculate the excess energy transferred into two-dot and three-dot quantum dot cellular automata systems during switching events. This is the energy that must eventually be dissipated as heat. The adiabaticity of a switching event is quantified using the adiabaticity parameter of Landau and Zener. For the logically reversible operations of WRITE or ERASE WITH COPY, the excess energy transferred to the system decreases exponentially with increasing adiabaticity. For the logically irreversible operation of ERASE WITHOUT COPY, considerable energy is transferred and so must be dissipated, in accordance with the Landauer Principle. The exponential decrease in energy dissipation with adiabaticity (e.g., switching time) distinguishes adiabatic quantum switching from the usual linear improvement in classical systems.
Spheroidization of Nickel Powder and Coating with Carbon Layer through Laser Heating
Authors: Li Shuang , Shao Yu-Ling , Cui Lan , Kulinich Sergei A. , Du Xi-Wen
Published: September 2018

We developed a simple and efficient process, laser heating of nickel powder in ethanol, to produce carbon-encapsulated nickel microspheres. Long-pulse-width laser heated nickel powder suspended in pure ethanol into liquid droplets. In turn, the latter droplets became sphere-like, pyrolyzed surrounding ethanol and dissolved the produced carbon atoms. Because of their lower solubility in solid nickel, excess carbon atoms were then expelled from the metal core after solidification, thus forming graphite-like shells on the laser-modified Ni spheres. Hence, after pyrolysis the transformation of carbon was found to follow the dissolution-precipitation mechanism. The produced carbon-encapsulated nickel microspheres exhibited higher oxidation resistance compared with the initial nickel powder, while keeping their magnetic properties essentially unchanged.
Enhancement in Curie Temperature of Yttrium Iron Garnet by Doping with Neodymium
Authors: Baños-López Esperanza , Sánchez-De Jesús Félix , Cortés-Escobedo Claudia A. , Barba-Pingarrón Arturo , Bolarín-Miró Ana María
Published: September 2018

The effect of the substitution of Y3+ by Nd3+ on the structural and magnetic properties of neodymium-doped yttrium iron garnet, NdxY3−xFe5O12 with x in the range of 0–2.5, is presented. Oxide powders of Fe2O3, Nd2O3, and Y2O3 were mixed in a stoichiometric ratio and milled for 5 h using high-energy ball milling, before being uniaxially pressed at 900 MPa and annealed at 1373 K for 2 h to obtain NdxY3−xFe5O12 (0 ≤ x ≤ 2.5). It was found that the mechanical milling of oxides followed by annealing promotes the complete structural formation of the garnet structure. Additionally, the X-ray diffraction patterns confirm the complete introduction of Nd3+ into the garnet structure with a neodymium doping concentration (x) of 0–2.0, which causes a consistent increment in the lattice parameters with the Nd3+ content. When x is higher than 2.0, the yttrium orthoferrite is the predominant phase. Besides, the magnetic results reveal an increase in the Curie temperature (583 K) as the amount of Nd3+ increases, while there was enhanced saturation magnetization as well as modified remanence and coercivity with respect to non-doped YIG.
Thermoresponsive Core-Shell Nanoparticles: Does Core Size Matter?
Authors: Schroffenegger Martina , Reimhult Erik
Published: September 2018

Nanoparticles grafted with a dense brush of hydrophilic polymers exhibit high colloidal stability. However, reversible aggregation can be triggered by an increase in temperature if the polymer is thermoresponsive, as the polymer shell partly loses its hydration. We investigate the role of nanoparticle curvature on the critical solution temperature (CST) of grafted poly(2-isopropyl-2-oxazoline) (PiPOx) and critical flocculation temperature (CFT) of the core-shell nanoparticle dispersion. Cores with diameters ranging from 5 to 21 nm were studied by temperature-cycled dynamic light scattering and differential scanning calorimetry over a large range of concentrations. We show that core size and curvature only have a minor influence on particle aggregation (CFT and cluster size), while they have major influence on the CST of the polymer shell. The densely grafted shells exhibit three distinct solvation transitions, the relative contributions of each is controlled by the core curvature. We link these transitions to different polymer density regimes within the spherical brush and demonstrate that the CST of the innermost part of the brush coincides with the CFT of the particle dispersion.
Creating the Coupled Band Gaps in Piezoelectric Composite Plates by Interconnected Electric Impedance
Authors: Li Lin , Jiang Zhou , Fan Yu , Li Jun
Published: September 2018

In this paper, we investigate the coupled band gaps created by the locking phenomenon between the electric and flexural waves in piezoelectric composite plates. To do that, the distributed piezoelectric materials should be interconnected via a ‘global’ electric network rather than the respective ‘local’ impedance. Once the uncoupled electric wave has the same wavelength and opposite group velocity as the uncoupled flexural wave, the desired coupled band gap emerges. The Wave Finite Element Method (WFEM) is used to investigate the evolution of the coupled band gap with respect to propagation direction and electric parameters. Further, the bandwidth and directionality of the coupled band gap are compared with the LR and Bragg gaps. An indicator termed ratio of single wave (RSW) is proposed to determine the effective band gap for a given deformation (electric, flexural, etc.). The features of the coupled band gap are validated by a forced response analysis. We show that the coupled band gap, despite directional, can be much wider than the LR gap with the same overall inductance. This might lead to an alternative to adaptively create band gaps.
Brazing of Mo to Glidcop Dispersion Strengthened Copper for Accelerating Structures
Authors: Casalegno Valentina , Perero Sergio , Ferraris Monica , Taborelli Mauro , Arnau Izquierdo Gonzalo , Sgobba Stefano , Salvo Milena
Published: September 2018

Alumina dispersion-strengthened copper, Glidcop, is used widely in high-heat-load ultra-high-vacuum components for synchrotron light sources (absorbers), accelerator components (beam intercepting devices), and in nuclear power plants. Glidcop has similar thermal and electrical properties to oxygen free electrical (OFE) copper, but has superior mechanical properties, thus making it a feasible structural material; its yield and ultimate tensile strength are equivalent to those of mild-carbon steel. The purpose of this work has been to develop a brazing technique to join Glidcop to Mo, using a commercial Cu-based alloy. The effects of the excessive diffusion of the braze along the grain boundaries on the interfacial chemistry and joint microstructure, as well as on the mechanical performance of the brazed joints, has been investigated. In order to prevent the diffusion of the braze into the Glidcop alloy, a copper barrier layer has been deposited on Glidcop by means of RF-sputtering.
Investigation of Growth Factor and Tenocyte Proliferation Induced by Platelet Rich Plasma (PRP) in a 3-Chamber Co-Culture Device
Authors: Chiu Chih-Hao , Higashikawa Rei , Yeh Wen-Ling , Lei Kin Fong , Chen Alvin Chao-Yu
Published: September 2018

The platelet-rich plasma (PRP) has become an attractive topic for soft tissue healing therapy recently. While some clinical reports revealed the effective treatments for knee osteoarthritis, lateral epicondylitis, and rotator cuff tears, other case studies showed that there was no statistically significant healing improvement. The efficacy of the PRP therapy is still unclear clinically. Thus, a significant amount of basic studies should be conducted to optimize the preparation procedure and the platelet concentration of the PRP. In this work, a 3-chamber co-culture device was developed for the PRP study in order to reduce the usage of primary cells and to avoid the PRP gelation effect. The device was a culture, well partitioning into 3 sub-chambers. Tenocytes and PRP could be respectively loaded into the sub-chambers and co-cultured under the interlinked medium. The results showed that a higher platelet number in the PRP could diffuse higher concentration of the growth factors in the medium and induce higher tenocyte proliferation. The 3-chamber co-culture device provides a simple and practical tool for the PRP study. It is potentially applied for optimizing the preparation procedure and platelet concentration of the PRP therapy.
Quantifying Discretization Errors in Electrophoretically-Guided Micro Additive Manufacturing
Authors: Pritchet David , Moser Newell , Ehmann Kornel , Cao Jian , Huang Jiaxing
Published: September 2018

This paper presents process models for a new micro additive manufacturing process termed Electrophoretically-guided Micro Additive Manufacturing (EPμAM). In EPμAM, a planar microelectrode array generates the electric potential distributions which cause colloidal particles to agglomerate and deposit in desired regions. The discrete microelectrode array nature and the used pulse width modulation (PWM) technique for microelectrode actuation create unavoidable process errors—space and time discretization errors—that distort particle trajectories. To combat this, we developed finite element method (FEM) models to study trajectory deviations due to these errors. Mean square displacement (MSD) analysis of the computed particle trajectories is used to compare these deviations for several electrode geometries. The two top-performing electrode geometries evaluated by MSD were additionally investigated through separate case studies via geometry variation and MSD recomputation. Furthermore, separate time-discretization error simulations are also studied where electrode actuating waveforms were simulated. The mechanical impulse of the electromechanical force, generated from these waveforms is used as the basis for comparison. The obtained results show a moderate MSDs variability and significant differences in the computed mechanical impulses for the actuating waveforms. The observed limitations of the developed process model and of the error comparison technique are briefly discussed and future steps are recommended.
Carbonaceous Materials in the Fault Zone of the Longmenshan Fault Belt: 2. Characterization of Fault Gouge from Deep Drilling and Implications for Fault Maturity
Authors: Kuo Li-Wei , Huang Jyh-Rou , Fang Jiann-Neng , Si Jialiang , Song Sheng-Rong , Li Haibing , Yeh En-Chao
Published: September 2018

In recent works on the determination of graphitization of carbonaceous materials (CM) within the principal slip zone (PSZ) of the Longmenshan fault (China), we demonstrated that the formation of graphite, resulted from strain and frictional heating, could be evidence of past seismic slip. Here we utilize Raman Spectroscopy of CM (RSCM) on the CM-bearing gouges in the fault zone of the Longmenshan fault belt, at the borehole depth of 760 m (FZ760) from the Wenchuan earthquake Fault Scientific Drilling project-1 (WFSD-1), to quantitatively characterize CM and further retrieve ancient fault deformation information in the active fault. RSCM shows that graphitization of CM is intense in the fault core with respect to the damage zone, with the graphitized carbon resembling those observed on experimentally formed graphite that was frictionally generated. Importantly, compared to the recognized active fault zone of the Longmenshan fault, the RSCM of measured CM-rich gouge shows a higher degree of graphitization, likely derived from high-temperature-perturbation faulting events. It implies that FZ760 accommodated numerous single-event displacement and/or at higher normal stresses and/or in the absence of pore fluid and/or along a more localized slip surface(s). Because graphite is a well-known lubricant, we surmise that the presence of the higher degree graphitized CM within FZ760 will reduce the fault strength and inefficiently accumulate tectonic stress during the seismic cycle at the current depth, and further infer a plausible mechanism for fault propagation at the borehole depth of 590 m during the Mw 7.9 Wenchuan earthquake.
Architecting 3D Interactive Educational Applications for the Web: The Case Study of CrystalWalk
Authors: Bardella Fernando , Moraes Rafael Castilho de , Saringelos Thanos , Karatzaferis Alexandros , Rodrigues Andre Montes , Silva Andre Gomes da , Neto Ricardo Mendes Leal
Published: September 2018

This paper describes the technical development of CrystalWalk, a crystal editor and visualization software designed for teaching materials science and engineering aiming to provide an accessible and interactive platform to students, professors and researchers. Justified by the lack of proper didactic tools, an evaluation of the existing crystallographic software has further shown opportunities for the development of a new software, more focused on the educational approach. CrystalWalk’s was guided by principles of free software, accessibility and democratization of knowledge, which was reflected in the application’s architecture strategy and the adoption of state-of-the-art technologies for the development of interactive web applications, such as HTML5/WebGL, service-oriented architecture (SOA) and responsive, resilient and elastic distributed systems. CrystalWalk’s architecture was successful in supporting the implementation of all specified software requirements proposed by state-of-the-art research and deemed to exert a positive impact in building accessible 3D interactive educational applications for the web.
Review of Deep Learning Methods in Robotic Grasp Detection
Authors: Caldera Shehan , Rassau Alexander , Chai Douglas
Published: September 2018

For robots to attain more general-purpose utility, grasping is a necessary skill to master. Such general-purpose robots may use their perception abilities to visually identify grasps for a given object. A grasp describes how a robotic end-effector can be arranged to securely grab an object and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task-specific algorithm, but this is an arduous and time-consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods have driven robotics researchers to explore the use of deep learning methods in task-generalised robotic applications. This paper reviews the current state-of-the-art in regards to the application of deep learning methods to generalised robotic grasping and discusses how each element of the deep learning approach has improved the overall performance of robotic grasp detection. Several of the most promising approaches are evaluated and the most suitable for real-time grasp detection is identified as the one-shot detection method. The availability of suitable volumes of appropriate training data is identified as a major obstacle for effective utilisation of the deep learning approaches, and the use of transfer learning techniques is proposed as a potential mechanism to address this. Finally, current trends in the field and future potential research directions are discussed.
Metalenses Based on Symmetric Slab Waveguide and c-TiO2: Efficient Polarization-Insensitive Focusing at Visible Wavelengths
Authors: Liang Yaoyao , Wei Zhongchao , Guo Jianping , Wang Faqiang , Meng Hongyun , Liu Hongzhan
Published: September 2018

A key goal of metalens research is to achieve wavefront shaping of light using optical elements with thicknesses on the order of the wavelength. Here we demonstrate ultrathin highly efficient crystalline titanium dioxide metalenses at blue, green, and red wavelengths (λ0 = 453 nm, 532 nm, and 633 nm, respectively) based on symmetric slab waveguide theory. These metalenses are less than 488 nm-thick and capable of focusing incident light into very symmetric diffraction-limited spots with strehl ratio and efficiency as high as 0.96 and 83%, respectively. Further quantitative characterizations about metalenses’ peak focusing intensities and focal spot sizes show good agreement with theoretical calculation. Besides, the metalenses suffer only about 10% chromatic deviation from the ideal spots in visible spectrum. In contrast with Pancharatnam–Berry phase mechanism, which limit their incident light at circular polarization, the proposed method enables metalenses polarization-insensitive to incident light.
Mediation of FoxO1 in Activated Neuroglia Deficient for Nucleoside Diphosphate Kinase B during Vascular Degeneration
Authors: Qiu Yi , Huang Hongpeng , Chatterjee Anupriya , Teuma Loïc , Baumann Fabienne , Hammes Hans-Peter , Wieland Thomas , Feng Yuxi
Published: September 2018

The pathogenesis of diabetic retinopathy is closely associated with the breakdown of the neurovascular unit including the glial cells. Deficiency of nucleoside diphosphate kinase B (NDPK-B) results in retinal vasoregression mimicking diabetic retinopathy. Increased retinal expression of Angiopoietin-2 (Ang-2) initiates vasoregression. In this study, Müller cell activation, glial Ang-2 expression, and the underlying mechanisms were investigated in streptozotocin-induced diabetic NDPK-B deficient (KO) retinas and Müller cells isolated from the NDPK-B KO retinas. Müller cells were activated and Ang-2 expression was predominantly increased in Müller cells in normoglycemic NDPK-B KO retinas, similar to diabetic wild type (WT) retinas. Diabetes induction in the NDPK-B KO mice did not further increase its activation. Additionally, cultured NDPK-B KO Müller cells were more activated and showed higher Ang-2 expression than WT cells. Müller cell activation and Ang-2 elevation were observed upon high glucose treatment in WT, but not in NDPK-B KO cells. Moreover, increased levels of the transcription factor forkhead box protein O1 (FoxO1) were detected in non-diabetic NDPK-B KO Müller cells. The siRNA-mediated knockdown of FoxO1 in NDPK-B deficient cells interfered with Ang-2 upregulation. These data suggest that FoxO1 mediates Ang-2 upregulation induced by NDPK-B deficiency in the Müller cells and thus contributes to the onset of retinal vascular degeneration.
Lactobacillus acidophilus DDS-1 Modulates the Gut Microbiota and Improves Metabolic Profiles in Aging Mice
Authors: Vemuri Ravichandra , Shinde Tanvi , Gundamaraju Rohit , Gondalia Shakuntla V. , Karpe Avinash V. , Beale David J. , Martoni Christopher J. , Eri Rajaraman
Published: September 2018

Recent evidence suggests that gut microbiota shifts can alter host metabolism even during healthy aging. Lactobacillus acidophilus DDS-1, a probiotic strain, has shown promising probiotic character in vitro, as well as in clinical studies. The present study was carried out to investigate whether DDS-1 can modulate the host metabolic phenotype under the condition of age-affected gut microbial shifts in young and aging C57BL/6J mice. Collected fecal samples were analyzed using 16S rRNA gene sequencing for identifying gut microbiota and untargeted gas chromatography-mass spectrometry (GC-MS) metabolomics analysis. Gut microbial shifts were observed in the control groups (young and aging), leading to an alteration in metabolism. Principal coordinate analysis (PCoA) of microbiota indicated distinct separation in both the DDS-1-treated groups. L. acidophilus DDS-1 increased the relative abundances of beneficial bacteria, such as Akkermansia muciniphila and Lactobacillus spp., and reduced the relative levels of opportunistic bacteria such as Proteobacteria spp. Metabolic pathway analysis identified 10 key pathways involving amino acid metabolism, protein synthesis and metabolism, carbohydrate metabolism, and butanoate metabolism. These findings suggest that modulation of gut microbiota by DDS-1 results in improvement of metabolic phenotype in the aging mice.
ACEI-Inhibitory Peptides Naturally Generated in Meat and Meat Products and Their Health Relevance
Authors: Mora Leticia , Gallego Marta , Toldrá Fidel
Published: September 2018

Meat and meat products have been described as a very good source of angiotensin I converting enzyme (ACEI)-inhibitory peptides. The generation of bioactive peptides can occur through the action of endogenous muscular enzymes during processing, gastrointestinal digestion, or by using commercial enzymes in laboratory or industry under controlled conditions. Studies of bioavailability are necessary in order to prove the positive health effect of bioactive peptides in the body as they should resist gastrointestinal digestion, cross the intestinal barrier, and reach blood stream and target organs. However, in order to better understand their effect, interactions, and bioavailability, it is necessary to consider food matrix interactions and continue the development of quantitative methodologies in order to obtain more data that will enable advances in the field of bioactive peptides and the determination of their influence on health.
Sex Differences in Hepatic De Novo Lipogenesis with Acute Fructose Feeding
Authors: Low Wee Suan , Cornfield Thomas , Charlton Catriona A. , Tomlinson Jeremy W. , Hodson Leanne
Published: September 2018

Dietary free sugars have received much attention over the past few years. Much of the focus has been on the effect of fructose on hepatic de novo lipogenesis (DNL). Therefore the aim of the present study was to investigate the effects of meals high and low in fructose on postprandial hepatic DNL and fatty acid partitioning and dietary fatty acid oxidation. Sixteen healthy adults (eight men, eight women) participated in this randomised cross-over study; study days were separated by a 4-week wash-out period. Hepatic DNL and dietary fatty acid oxidation were assessed using stable-isotope tracer methodology. Consumption of the high fructose meal significantly increased postprandial hepatic DNL to a greater extent than consumption of the low fructose meal and this effect was evident in women but not men. Despite an increase in hepatic DNL, there was no change in dietary fatty acid oxidation. Taken together, our data show that women are more responsive to ingestion of higher amounts of fructose than men and if continued over time this may lead to changes in hepatic fatty acid partitioning and eventually liver fat content.
Added Sugars and Low- and No-Calorie Sweeteners in a Representative Sample of Food Products Consumed by the Spanish ANIBES Study Population
Authors: Samaniego-Vaesken María de Lourdes , Ruiz Emma , Partearroyo Teresa , Aranceta-Bartrina Javier , Gil Ángel , González-Gross Marcela , Ortega Rosa M. , Serra-Majem Lluis , Varela-Moreiras Gregorio
Published: September 2018

Low- and no-calorie sweeteners (LNCS), intensely sweet compounds that virtually contain no calories, are used to replace added sugars in food and drinks. Knowledge about different LNCS data in Spanish foods and added sugar sources in Spain is limited, therefore our aim was to identify and compare their presence across main food groups consumed. Food and beverage products (n = 434) were obtained from the ANIBES Study (anthropometric data, macronutrients and micronutrients intake, practice of physical activity, socioeconomic data and lifestyles), a cross-sectional study of a representative sample of the Spanish population (9–75 years old; n = 2009) carried out in 2013. Food records were obtained from a three-day dietary record using a tablet device. Label data from 1,164 products of different brands were collected and reviewed for content of added sugars and LNCS. LNCS were present in diet soft drinks (100%), “other sweets” (89%), soya drinks (45%), and yogurt and fermented milks (18%). Added sugars were present mainly in sugar soft drinks (100%), energy drinks (96%), sports drinks (96%), bakery and pastry (100%), chocolates (100%), ice cream (100%), breakfast cereals/bars (96%) and jams (89%). Main LNCS were acesulfame K, aspartame, cyclamate and sucralose. Sucrose, dextrose, glucose-fructose syrup, caramel and honey were the main added sugars. Our results show the diversity of foods groups including these ingredients. These data are not compiled in food composition databases, which should be periodically updated to include LNCS and added sugars to facilitate their assessment and monitoring in nutritional surveys.
Frequency or Amplitude?—Rheo-Electrical Characterization of Carbon Nanoparticle Filled Epoxy Systems
Authors: Meeuw Hauke , Wisniewski Valea , Fiedler Bodo
Published: September 2018

Dispersion of carbon nanoparticles in epoxy resin is the key factor to adjust the resulting electrical and mechanical properties of the nanocomposite. A profound understanding of the driving forces of standard methods like ultrasonic and mechanical dispersion is necessary. To derive the impact of applied frequency and strain on the resulting dispersion of multi-walled carbon nanotube (MWCNT)-filled epoxy resin, this work addresses the strain and frequency dependency of oscillatory shear flow-induced network changes. Strain- and frequency-sweeps were performed for a wide parameter set with in-line measurement of electrical DC resistance to monitor changes in the MWCNT network. Changes in electrical resistance reveal destruction and formation of the MWCNT network. A fundamental novel finding is the governing dependency of changes in the electrical network on applied shear amplitude. The applied frequency barely induces network changes. Applied shear rates do not correlate with particular network states.
Cellulose Nanofiber/Carbon Nanotube Conductive Nano-Network as a Reinforcement Template for Polydimethylsiloxane Nanocomposite
Authors: Chen Chuchu , Bu Xiangting , Feng Qian , Li Dagang
Published: September 2018

Both cellulose nanofiber (CNF) and carbon nanotube (CNT) are nanoscale fibers that have shown reinforcing effects in polymer composites. It’s worth noting that CNF and CNT could form a three-dimensional nano-network via mixing and vacuum filtration, which exhibit excellent mechanical strength and electrical conductivity. In this study, the developed CNF/CNT film was applied as a nano-network template and immersed into polydimethylsiloxane (PDMS) solutions. By controlling the immersed polydimethylsiloxane pre-polymer concentration, the PDMS/CNF/CNT nanocomposite with various PDMS contents were fabricated after a curing process. Morphological images showed that the CNF/CNT nano-network was well-preserved inside the PDMS, which resulted in significantly improved mechanical strength. While increasing the PDMS content (~71.3 wt %) gave rise to decreased tensile strength, the PDMS-30/CNF/CNT showed a fracture strain of 7.5%, which was around seven fold higher than the rigid CNF/CNT and still kept a desirable strength—Young’s modulus and conductivity of 18.3 MPa, 805 MPa, and 0.8 S/cm, respectively. Therefore, with the enhanced mechanical properties and the electrical conductivity, the prepared PDMS/CNF/CNT composite films may offer promising and broad prospects in the field of flexible devices.
Systematic and Model-Assisted Process Design for the Extraction and Purification of Artemisinin from Artemisia annua L.—Part I: Conceptual Process Design and Cost Estimation
Authors: Sixt Maximilian , Schmidt Axel , Mestmäcker Fabian , Huter Maximilian Johannes , Uhlenbrock Lukas , Strube Jochen
Published: September 2018

The article summarizes a systematic process design for the extraction and purification of artemisinin from annual mugwort (Artemisia annua L.). Artemisinin serves as an anti-malaria drug, therefore, resource-efficient and economic processes for its production are needed. The process design was based on lab-scale experiments and afterwards piloted on miniplant-scale at the institute. In this part of the article, a detailed economic feasibility studies including a reference process as a benchmark the lab-scale process and the pilot-scale process is given. Relevant differences between the different scales are discussed. The details of the respective unit operations (solid-liquid extraction, liquid-liquid extraction, chromatography and crystallization) are presented in dedicated articles. The study showed that even miniaturized lab-scale experiments are able to deliver data detailed enough for scale-up calculations on a theoretical basis. To our knowledge, a comparable systematic process design and piloting was never performed by academia before.
Photocatalytic Membranes in Photocatalytic Membrane Reactors
Authors: Argurio Pietro , Fontananova Enrica , Molinari Raffaele , Drioli Enrico
Published: September 2018

The present work gives a critical overview of the recent progresses and new perspectives in the field of photocatalytic membranes (PMs) in photocatalytic membrane reactors (PMRs), thus highlighting the main advantages and the still existing limitations for large scale applications in the perspective of a sustainable growth. The classification of the PMRs is mainly based on the location of the photocatalyst with respect to the membranes and distinguished in: (i) PMRs with photocatalyst solubilized or suspended in solution and (ii) PMRs with photocatalyst immobilized in/on a membrane (i.e., a PM). The main factors affecting the two types of PMRs are deeply discussed. A multidisciplinary approach for the progress of research in PMs and PMRs is presented starting from selected case studies. A special attention is dedicated to PMRs employing dispersed TiO2 confined in the reactor by a membrane for wastewater treatment. Moreover, the design and development of efficient photocatalytic membranes by the heterogenization of polyoxometalates in/on polymeric membranes is discussed for applications in environmental friendly advanced oxidation processes and fine chemical synthesis.
The Double Character of Cuban Protestantism and Philanthropy
Authors: Goodwin Jamie
Published: September 2018

In Cuba and the United States, Protestant institutions exist that are both reflective and nonreflective about their culture’s influence on belief and practice. The case of Cuba sheds light on how Christian churches and voluntary associations operate in an authoritarian regime. Despite the tension and enmity that have typified Cuba’s geopolitical relationship with the United States since the colonial days, cross-cultural Christian philanthropic partnerships exist. The “doble carácter” (double character) of Cuban Protestant churches has grown out of both collaboration with, and resistance to U.S.-style evangelicalism (Arce Valentín 2016). Adaptations of liberation theology, adopted among Cuban Christians, provide an influential counterweight to the mighty Western theological and philanthropic tradition (González 2012). The nature of this engagement influences Cuban civil society, the survival of the Cuban regime, and provides an extreme case for cross-cultural philanthropy worldwide. This socio-historical account utilizes the data collected from personal interviews with Cuban Protestant leaders, primary sources found in the library at the San Cristobal Presbyterian Seminary and Cuban theological journals, and a qualitative analysis of literature on Cuba, Protestants, missions, philanthropy, nongovernment organizations (NGOs) and civil society.
FVI—A Floating Vegetation Index Formed with Three Near-IR Channels in the 1.0–1.24 μm Spectral Range for the Detection of Vegetation Floating over Water Surfaces
Authors: Gao Bo-Cai , Li Rong-Rong
Published: September 2018

Through the analysis of hyperspectral imaging data collected over water surfaces covered by floating vegetation, such as Sargassum and algae, we observed that the spectra commonly contain a reflectance peak centered near 1.07 μm. This peak results from the competing effects between the well-known vegetation reflectance plateau in the 0.81–1.3 μm spectral range and the absorption effects above 0.75 μm by liquid water within the vegetation and in the surrounding water bodies. In this article, we propose a new index, namely the floating vegetation index (FVI), for the hyperspectral remote sensing of vegetation over surface layers of oceans and inland lakes. In the formulation of the FVI, one channel centered near 1.0 μm and another 1.24 μm are used to form a linear baseline. The reflectance value of the third channel centered at the 1.07-μm reflectance peak above the baseline is defined as the FVI. Hyperspectral imaging data acquired with the AVIRIS (Airborne Visible Infrared Imaging Spectrometer) instrument over the Gulf of Mexico and over salt ponds near Moffett Field in southern portions of the San Francisco Bay were used to demonstrate the success in detecting Sargassum and floating algae with this index. It is expected that the use of this index for the global detection of floating vegetation from hyperspectral imaging data to be acquired with future satellite sensors will result in improved detection and therefore enhanced capability in estimating primary production, a measure of how much carbon is fixed per unit area per day by oceans and inland lakes.
WeedMap: A Large-Scale Semantic Weed Mapping Framework Using Aerial Multispectral Imaging and Deep Neural Network for Precision Farming
Authors: Sa Inkyu , Popović Marija , Khanna Raghav , Chen Zetao , Lottes Philipp , Liebisch Frank , Nieto Juan , Stachniss Cyrill , Walter Achim , Siegwart Roland
Published: September 2018

The ability to automatically monitor agricultural fields is an important capability in precision farming, enabling steps towards more sustainable agriculture. Precise, high-resolution monitoring is a key prerequisite for targeted intervention and the selective application of agro-chemicals. The main goal of this paper is developing a novel crop/weed segmentation and mapping framework that processes multispectral images obtained from an unmanned aerial vehicle (UAV) using a deep neural network (DNN). Most studies on crop/weed semantic segmentation only consider single images for processing and classification. Images taken by UAVs often cover only a few hundred square meters with either color only or color and near-infrared (NIR) channels. Although a map can be generated by processing single segmented images incrementally, this requires additional complex information fusion techniques which struggle to handle high fidelity maps due to their computational costs and problems in ensuring global consistency. Moreover, computing a single large and accurate vegetation map (e.g., crop/weed) using a DNN is non-trivial due to difficulties arising from: (1) limited ground sample distances (GSDs) in high-altitude datasets, (2) sacrificed resolution resulting from downsampling high-fidelity images, and (3) multispectral image alignment. To address these issues, we adopt a stand sliding window approach that operates on only small portions of multispectral orthomosaic maps (tiles), which are channel-wise aligned and calibrated radiometrically across the entire map. We define the tile size to be the same as that of the DNN input to avoid resolution loss. Compared to our baseline model (i.e., SegNet with 3 channel RGB (red, green, and blue) inputs) yielding an area under the curve (AUC) of [background=0.607, crop=0.681, weed=0.576], our proposed model with 9 input channels achieves [0.839, 0.863, 0.782]. Additionally, we provide an extensive analysis of 20 trained models, both qualitatively and quantitatively, in order to evaluate the effects of varying input channels and tunable network hyperparameters. Furthermore, we release a large sugar beet/weed aerial dataset with expertly guided annotations for further research in the fields of remote sensing, precision agriculture, and agricultural robotics.
Assessment of Forest above Ground Biomass Estimation Using Multi-Temporal C-band Sentinel-1 and Polarimetric L-band PALSAR-2 Data
Authors: Huang Xiaodong , Ziniti Beth , Torbick Nathan , Ducey Mark J.
Published: September 2018

Synthetic Aperture Radar (SAR), as an active sensor transmitting long wavelengths, has the advantages of working day and night and without rain or cloud disturbance. It is further able to sense the geometric structure of forests more than passive optical sensors, making it a valuable tool for mapping forest Above Ground Biomass (AGB). This paper studies the ability of the single- and multi-temporal C-band Sentinel-1 and polarimetric L-band PALSAR-2 data to estimate live AGB based on ground truth data collected in New England, USA in 2017. Comparisons of results using the Simple Water Cloud Model (SWCM) on both VH and VV polarizations show that C-band reaches saturation much faster than the L-band due to its limited forest canopy penetration. The exhaustive search multiple linear regression model over the many polarimetric parameters from PALSAR-2 data shows that the combination of polarimetric parameters could slightly improve the AGB estimation, with an adjusted R2 as high as 0.43 and RMSE of around 70 Mg/ha when decomposed Pv component and Alpha angle are used. Additionally, the single- and multi-temporal C-band Sentinel-1 data are compared, which demonstrates that the multi-temporal Sentinel-1 significantly improves the AGB estimation, but still has a much lower adjusted R2 due to the limitations of the short wavelength. Finally, a site-level comparison between paired control and treatment sites shows that the L-band aligns better with the ground truth than the C-band, showing the high potential of the models to be applied to relative biomass change detection.
Hyperspectral Image Classification Based on Parameter-Optimized 3D-CNNs Combined with Transfer Learning and Virtual Samples
Authors: Liu Xuefeng , Sun Qiaoqiao , Meng Yue , Fu Min , Bourennane Salah
Published: September 2018

Recent research has shown that spatial-spectral information can help to improve the classification of hyperspectral images (HSIs). Therefore, three-dimensional convolutional neural networks (3D-CNNs) have been applied to HSI classification. However, a lack of HSI training samples restricts the performance of 3D-CNNs. To solve this problem and improve the classification, an improved method based on 3D-CNNs combined with parameter optimization, transfer learning, and virtual samples is proposed in this paper. Firstly, to optimize the network performance, the parameters of the 3D-CNN of the HSI to be classified (target data) are adjusted according to the single variable principle. Secondly, in order to relieve the problem caused by insufficient samples, the weights in the bottom layers of the parameter-optimized 3D-CNN of the target data can be transferred from another well trained 3D-CNN by a HSI (source data) with enough samples and the same feature space as the target data. Then, some virtual samples can be generated from the original samples of the target data to further alleviate the lack of HSI training samples. Finally, the parameter-optimized 3D-CNN with transfer learning can be trained by the training samples consisting of the virtual and the original samples. Experimental results on real-world hyperspectral satellite images have shown that the proposed method has great potential prospects in HSI classification.
A Geographically Weighted Regression Analysis of the Underlying Factors Related to the Surface Urban Heat Island Phenomenon
Authors: Zhao Chunhong , Jensen Jennifer , Weng Qihao , Weaver Russell
Published: September 2018

This study investigated how underlying biophysical attributes affect the characterization of the Surface Urban Heat Island (SUHI) phenomenon using (and comparing) two statistical techniques: global regression and geographically weighted regression (GWR). Land surface temperature (LST) was calculated from Landsat 8 imagery for 20 July 2015 for the metropolitan areas of Austin and San Antonio, Texas. We sought to examine SUHI by relating LST to Lidar-derived terrain factors, land cover composition, and landscape pattern metrics developed using the National Land Cover Database (NLCD) 2011. The results indicate that (1) land cover composition is closely related to the SUHI effect for both metropolitan areas, as indicated by the global regression coefficients of building fraction and NDVI, with values of 0.29 and −0.74 for Austin, and 0.19 and −0.38 for San Antonio, respectively. The terrain morphology was also an indicator of the SUHI phenomenon, implied by the elevation (0.20 for Austin and 0.09 for San Antonio) and northness (0.20 for Austin and 0.09 for San Antonio); (2) the SUHI phenomenon of Austin on 20 July 2015 was affected by the spatial pattern of the land use and land cover (LULC), which was not detected for San Antonio; and (3) with a local determination coefficient higher than 0.8, GWR had higher explanatory power of the underlying factors compared to global regression. By accommodating spatial non-stationarity and allowing the model parameters to vary in space, GWR illustrated the spatial heterogeneity of the relationships between different land surface properties and the LST. The GWR analysis of SUHI phenomenon can provide unique information for site-specific land planning and policy implementation for SUHI mitigation.
Monitoring of Thermal Activity at the Hatchobaru–Otake Geothermal Area in Japan Using Multi-Source Satellite Images—With Comparisons of Methods, and Solar and Seasonal Effects
Authors: Mia Md. Bodruddoza , Fujimitsu Yasuhiro , Nishijima Jun
Published: September 2018

The Hatchobaru–Otake (HO) geothermal field is proximal to the Kuju volcano on Kyushu, Japan. There are currently three geothermal power plants operating within this geothermal field. Herein, we explore the thermal status of the HO geothermal area using ASTER thermal infrared data to monitor heat losses from 2009 to 2017. We assessed the solar effects and seasonal variation on heat losses based on day- and night-time Landsat thermal infrared images, and compared three conventional methods of land surface temperature (LST) measurements. The normalized difference vegetation index threshold method of emissivity, the split window algorithm for LST, and the Stefan–Boltzmann equation for radiative heat flux (RHF) were used to determine the heat loss within the study area. The radiative heat loss (RHL) was 0.36 MW, 38.61 MW, and 29.14 MW in 2009, 2013, and 2017, respectively, from the HO geothermal field. The highest anomaly in RHF was recorded in 2013, while the lowest was in 2009. The RHLs were higher from Otake than from the Hatchobaru thermal area in the year of 2013 (~31%) and 2017 (~78%). The seasonal variation in the RHLs based on all three LST estimation methods had a similar pattern, with the highest RHL (about 383–451 MW) in spring and the lowest (about 10–222 MW) in autumn for the daytime images from the HO geothermal field. In the nighttime images, the highest RHL was about 35–67 MW in autumn and the lowest was about 1–3 MW in spring, based on the three LST methods for RHFs. The highest RHL was about 35–42 MW in spring (day) and 3–7 MW in autumn (night) from the Hatchobaru thermal area, analyzed separately. Similarly, the highest RHL was about 22–25 MW in spring (day) and 4–5 MW in winter (night) from the Otake thermal area. The seasonal variation was greatly influenced by the regional ambient temperature. We also observed that clouds had a huge effect, with the highest values for both LST and RHF recorded below clouds on an autumn day. Overall, we obtained higher LSTs at nighttime and lower LSTs during the day from the improved mono-window algorithm than the split window algorithms for all of the seasons. The heat losses were also higher for the improved mono-window algorithm than the split window algorithms, based on the LST nighttime thermal infrared data. Considering the error level of the LST methods and Landsat 8 band 11, this study recommends the IWM method for LST using the Landsat 8 band 10 data. This study also suggests that both the nighttime ASTER and Landsat 8 thermal infrared data could be effective for monitoring the thermal status of the HO geothermal area, given that data is available for the entire period.