bluuebunny/crossref_metadata_2025 huggingface dataset:
Silver Nanoparticle-Based Assay for the Detection of Immunoglobulin Free Light Chains
Authors: Lizoń Anna , Wytrwal-Sarna Magdalena , Gajewska Marta , Drożdż Ryszard
Published: September 2019

There is a wide spectrum of malignant diseases that are connected with the clonal proliferation of plasma cells, which cause the production of complete immunoglobulins or their fragments (heavy or light immunoglobulin chains). These proteins may accumulate in tissues, leading to end organ damage. The quantitative determination of immunoglobulin free light chains (FLCs) is considered to be the gold standard in the detection and treatment of multiple myeloma (MM) and amyloid light-chain (AL) amyloidosis. In this study, a silver nanoparticle-based diagnostic tool for the quantitation of FLCs is presented. The optimal test conditions were achieved when a metal nanoparticle (MNP) was covered with 10 particles of an antibody and conjugated by 5–50 protein antigen particles (FLCs). The formation of the second antigen protein corona was accompanied by noticeable changes in the surface plasmon resonance spectra of the silver nanoparticles (AgNPs), which coincided with an increase of the hydrodynamic diameter and increase in the zeta potential, as demonstrated by dynamic light scattering (DLS). A decrease of repulsion forces and the formation of antigen–antibody bridges resulted in the agglutination of AgNPs, as demonstrated by transmission electron microscopy and the direct formation of AgNP aggregates. Antigen-conjugated AgNPs clusters were also found by direct observation using green laser light scattering. The parameters of the specific immunochemical aggregation process consistent with the sizes of AgNPs and the protein particles that coat them were confirmed by four physical methods, yielding complementary data concerning a clinically useful AgNPs aggregation test.
Mechanical and Fracture Properties of Fly Ash Geopolymer Concrete Addictive with Calcium Aluminate Cement
Authors: Wang Yamin , Hu Shaowei , He Zhen
Published: September 2019

In this paper, the mechanical and fracture properties of fly ash geopolymer concrete (FAGC) mixed with calcium aluminate cement (CAC) were explored. Fly ash was partially replaced by CAC with 2.5%, 5% and 7.5%. The results exhibit that the mechanical and fracture behaviors of FAGC are significantly influenced by CAC content. Based on the formation of more aluminum-rich gels, C-(A)-S-H and C-S-H gels, with the increase of CAC content, the compressive strength, splitting tensile strength and elastic modulus improved. Meanwhile, the peak load and effective fracture toughness show a monotone increasing trend. In addition, because C-S-H gels absorbed more energy, the fracture energy of FAGC increases. The maximal peak load, double-K fracture toughness and fracture energy reached up to1.79 kN, 4.27 MPam0.5, 10.1 MPam0.5 and 85.8 N/m with CAC content of 7.5%, respectively.
Sensitivity Analysis of the Frequency Response Function of Carbon-Fiber-Reinforced Plastic Specimens for Different Direction of Carbon Fiber as Well as Spectral Loading Pattern
Authors: Kim Chan-Jung
Published: September 2019

Carbon-fiber-reinforced plastic (CFRP) has been used in many industries owing to its excellent specific-strength characteristics; however, the control of its mechanical properties is difficult owing to the directivity nature of carbon fiber as well as the composition of layered structures. In addition, the damping coefficient of CFRP varies with spectral loading patterns under random and harmonic excitation owing to the high values of damping characteristics compared with conventional steel materials. A scaled sensitivity index was proposed to compare the magnitude of the frequency response function over two parameters of interest: the direction of the carbon fiber and the spectral loading pattern for CFRP specimens. Three specimens with different directions (0°, 45°, and 90°) were prepared and uniaxial excitation testing was conducted for two different spectral loading cases: random and harmonic. The summation of the frequency response was used to calculate the sensitivity index to eliminate the effects of the location of measurement data, and all sensitivity indexes were calculated using the measured responses. Finally, the sensitivity of each CFRP specimen was discussed for two cases, i.e., the direction of carbon fiber and the spectral loading pattern, using the scaled sensitivity index results.
The Effect of Fineness on the Hydration Activity Index of Ground Granulated Blast Furnace Slag
Authors: Dai Jinpeng , Wang Qicai , Xie Chao , Xue Yanjin , Duan Yun , Cui Xiaoning
Published: September 2019

To improve the properties of ground granulated blast furnace slag (GGBS) and utilize ground granulated blast furnace slag efficiently, this study investigates the effect of fineness on the hydration activity index (HAI) of ground granulated blast furnace slag. The hydration activity index of GGBS with six specific surface areas (SSAs) was characterized by the ratio of compressive strength of the prismatic mortar test block. The particle size distribution of GGBS with different grinding times was tested by laser particle size analyzer. The paste of different specific surface area GGBSs in different curing ages was investigated at the micro level by X-ray diffraction, scanning electron microscope, energy dispersive spectrometer, thermogravimetric scanning calorimeter, and differential scanning calorimeter. The effect of particle distribution of GGBS on the hydration activity index of different curing ages was studied by gray correlation analysis. The results indicated that the compressive strength and hydration activity index increases with the increase of a specific surface area of GGBS at different curing ages. The hydration activity index at different curing ages is almost a linear role for specific surface areas. With the increase in the specific surface area of GGBS, the content of Ca(OH)2 in paste decreases gradually. When GGBS was added into a mortar test block, the hydrate calcium silicate gel in paste changed from a high Ca/Si ratio to a low Ca/Si ratio. The 0–10 micron particles of GGBS particle distribution were highly correlated with the hydration activity index at different curing ages.
Electrochemical-Based Biosensors on Different Zinc Oxide Nanostructures: A Review
Authors: Napi Muhammad Luqman Mohd , Sultan Suhana Mohamed , Ismail Razali , How Khoo Wei , Ahmad Mohd Khairul
Published: September 2019

Electrochemical biosensors have shown great potential in the medical diagnosis field. The performance of electrochemical biosensors depends on the sensing materials used. ZnO nanostructures play important roles as the active sites where biological events occur, subsequently defining the sensitivity and stability of the device. ZnO nanostructures have been synthesized into four different dimensional formations, which are zero dimensional (nanoparticles and quantum dots), one dimensional (nanorods, nanotubes, nanofibers, and nanowires), two dimensional (nanosheets, nanoflakes, nanodiscs, and nanowalls) and three dimensional (hollow spheres and nanoflowers). The zero-dimensional nanostructures could be utilized for creating more active sites with a larger surface area. Meanwhile, one-dimensional nanostructures provide a direct and stable pathway for rapid electron transport. Two-dimensional nanostructures possess a unique polar surface for enhancing the immobilization process. Finally, three-dimensional nanostructures create extra surface area because of their geometric volume. The sensing performance of each of these morphologies toward the bio-analyte level makes ZnO nanostructures a suitable candidate to be applied as active sites in electrochemical biosensors for medical diagnostic purposes. This review highlights recent advances in various dimensions of ZnO nanostructures towards electrochemical biosensor applications.
Comparison of the Friction and Wear Characteristics between Copper and Paper Based Friction Materials
Authors: Yu Liang , Ma Biao , Chen Man , Li Heyan , Ma Chengnan , Liu Jikai
Published: September 2019

Copper-based friction material (CFM) and paper-based friction material (PFM) are the two most commonly used clutch friction materials. The friction and wear characteristics of these two kinds of friction materials under dry conditions were investigated by the pin-on-disc test over a broad range of applied loads, rotating speeds and ambient temperatures. Before experiments, the running-in test was conducted to stabilize the coefficient of friction (COF) and wear amount of the test samples. After experiments, the metallographic micrographs of the tested samples were presented to investigate the wear mechanisms. Experimental results showed that both the COF and wear depth of the CFM are much greater than these of PFM. The COF of CFM decreases with the increase of applied load, and changes slightly with the variation of rotating speed, whereas it increases first and then decreases with the increase of ambient temperature. However, the COF of PFM decreases dramatically with the increase of the rotating speed and ambient temperature, while it remains stable at first and then decreases slowly as the applied load increases. Additionally, under such three working conditions, the wear depth of CFM changes linearly, while the wear depth of PFM varies greatly. This study can be used as a guide for selecting friction materials for clutches with different applications.
Different Effects of Annealing on Microstructure Evolution and SERS Performance for Cu–Cr Alloy Film and Bulk Alloy
Authors: Huang Xiaoxue , Sun Haoliang , Shen Jun , Cui Kai , Wang Guangxin
Published: September 2019

Copper–chromium alloy film and Cu–Cr bulk alloy were obtained using magnetron sputtering and vacuum smelting. Experimental results indicated that Cu–Cr bulk alloy and alloy films having different residual stress and atomic diffusion exhibit a significant difference in microstructure evolution behaviors after annealing. Numerous polyhedral Cu particles and dendritic Cr particles precipitated on the surface of annealed Cu–Cr alloy film and as–cast Cu–Cr bulk alloy, respectively. Cu particles were formed under the driving of energy and residual stress in the film. The effect of annealing temperature and Cr content on the size and quantity of Cu particles is discussed. Cr particles precipitated on the bulk alloy due to the low solid solubility of Cr in Cu, and the crystallinity of Cu grains promoted the diffusion of Cr atoms. The surface–enhanced Raman scattering (SERS) intensity of the Cu–14.6%Cr alloy film was obviously higher than that of the Cu–14.2%Cr bulk alloy. The particles/film composite structure possessed the appropriate particle number, surface roughness, and interstitial gap, as opposed to the bulk material, to effectively improve SERS enhancement.
The Application of Statins in the Regeneration of Bone Defects. Systematic Review and Meta-Analysis
Authors: Roca-Millan Elisabet , González-Navarro Beatriz , Izquierdo-Gómez Keila , Marí-Roig Antonio , Jané-Salas Enric , López-López José , Velasco-Ortega Eugenio
Published: September 2019

This systematic review aims to analyze the effect of the local application of statins in the regeneration of non-periodontal bone defects. A systematic study was conducted with the Pubmed/Medline, Embase, Cochrane Library and Scielo databases for in vivo animal studies published up to and including February 2019. Fifteen articles were included in the analysis. The local application of the drug increased the percentage of new bone formation, bone density, bone healing, bone morphogenetic protein 2, vascular endothelial growth factor, progenitor endothelial cells and osteocalcin. Meta-analyses showed a statistically significant increase in the percentage of new bone formation when animals were treated with local statins, in contrast to the no introduction of filling material or the introduction of polylactic acid, both in an early (4–6 weeks) and in a late period (12 weeks) (mean difference 39.5%, 95% confidence interval: 22.2–56.9, p <0.001; and mean difference 43.3%, 95% confidence interval: 33.6–52.9, p < 0.001, respectively). Basing on the animal model, the local application of statins promotes the healing of critical bone size defects due to its apparent osteogenic and angiogenic effects. However, given the few studies and their heterogenicity, the results should be taken cautiously, and further pilot studies are necessary, with radiological and histological evaluations to translate these results to humans and establish statins’ effect.
Microstructural Characterization of 3D Printed Cementitious Materials
Authors: Van Der Putten Jolien , Deprez Maxim , Cnudde Veerle , De Schutter Geert , Van Tittelboom Kim
Published: September 2019

Three-dimensional concrete printing (3DCP) has progressed rapidly in recent years. With the aim to realize both buildings and civil works without using any molding, not only has the need for reliable mechanical properties of printed concrete grown, but also the need for more durable and environmentally friendly materials. As a consequence of super positioning cementitious layers, voids are created which can negatively affect durability. This paper presents the results of an experimental study on the relationship between 3DCP process parameters and the formed microstructure. The effect of two different process parameters (printing speed and inter-layer time) on the microstructure was established for fresh and hardened states, and the results were correlated with mechanical performance. In the case of a higher printing speed, a lower surface roughness was created due to the higher kinetic energy of the sand particles and the higher force applied. Microstructural investigations revealed that the amount of unhydrated cement particles was higher in the case of a lower inter-layer interval (i.e., 10 min). This phenomenon could be related to the higher water demand of the printed layer in order to rebuild the early Calcium-Silicate-Hydrate (CSH) bridges and the lower amount of water available for further hydration. The number of pores and the pore distribution were also more pronounced in the case of lower time intervals. Increasing the inter-layer time interval or the printing speed both lowered the mechanical performance of the printed specimens. This study emphasizes that individual process parameters will affect not only the structural behavior of the material, but they will also affect the durability and consequently the resistance against aggressive chemical substances.
Faces of 2-Dimensional Simplex of Order and Chain Polytopes
Authors: Mori Aki
Published: September 2019

Each of the descriptions of vertices, edges, and facets of the order and chain polytope of a finite partially ordered set are well known. In this paper, we give an explicit description of faces of 2-dimensional simplex in terms of vertices. Namely, it will be proved that an arbitrary triangle in 1-skeleton of the order or chain polytope forms the face of 2-dimensional simplex of each polytope. These results mean a generalization in the case of 2-faces of the characterization known in the case of edges.
New 8-Hydroxybriaranes from the Gorgonian Coral Junceella fragilis (Ellisellidae)
Authors: Chen You-Ying , Fang Lee-Shing , Chen Yu-Hsin , Peng Bo-Rong , Su Tung-Pin , Huynh Thanh-Hao , Lin Feng-Yu , Hu Chiung-Chin , Lin Nai-Cheng , Wen Zhi-Hong , Chen Jih-Jung , Lee Chieh-Yu , Wang Jin-Wei , Sung Ping-Jyun
Published: September 2019

Three new 8-hydroxybriaranes—fragilides R–T (1–3) were obtained from a sea whip gorgonian coral Junceella fragilis. The structures of briaranes 1–3 were elucidated by using spectroscopic methods, including 1D (1H and 13C NMR), 2D (COSY, HSQC, HMBC, and NOESY experiments) NMR studies, and (+)-HRESIMS. Fragilides S and T (2 and 3) are the only briaranes known to possess 8α-hydroxy and 17β-methyl groups, respectively. Briarane 2 exerted an inhibition effect on iNOS release from RAW264.7; a macrophage cell line that originated from a mouse monocyte macrophage, stimulated with lipopolysaccharides.
Editorial for the Special Issue on MEMS Technology for Biomedical Imaging Applications
Authors: Zhou Qifa , Zhang Yi
Published: September 2019

Biomedical imaging is the key technique and process to create informative images of the human body or other organic structures for clinical purposes or medical science [...]
Special Issue: Recombinant Protein Expression in Microorganisms
Authors: Brautaset Trygve , Valla Svein
Published: September 2019

Microorganisms are widely used in industrial biotechnology as cell factories for the sustainable production of a wide range of compounds and chemicals [...]
Role of Fibre in Nutritional Management of Pancreatic Diseases
Authors: Ribichini Emanuela , Stigliano Serena , Rossi Sara , Zaccari Piera , Sacchi Maria Carlotta , Bruno Giovanni , Badiali Danilo , Severi Carola
Published: September 2019

The role of fibre intake in the management of patients with pancreatic disease is still controversial. In acute pancreatitis, a prebiotic enriched diet is associated with low rates of pancreatic necrosis infection, hospital stay, systemic inflammatory response syndrome and multiorgan failure. This protective effect seems to be connected with the ability of fibre to stabilise the disturbed intestinal barrier homeostasis and to reduce the infection rate. On the other hand, in patients with exocrine pancreatic insufficiency, a high content fibre diet is associated with an increased wet fecal weight and fecal fat excretion because of the fibre inhibition of pancreatic enzymes. The mechanism by which dietary fibre reduces the pancreatic enzyme activity is still not clear. It seems likely that pancreatic enzymes are absorbed on the fibre surface or entrapped in pectin, a gel-like substance, and are likely inactivated by anti-nutrient compounds present in some foods. The aim of the present review is to highlight the current knowledge on the role of fibre in the nutritional management of patients with pancreatic disorders.
Sustainable Food Systems and the Mediterranean Diet
Authors: Berry Elliot M
Published: September 2019

During the past decade, the concept of sustainability has been added to the factors involved in food security. This has led to a more comprehensive and holistic approach to sustainable food systems which considers drivers—environment, geopolitics, demographics, policy regulations, socio-cultural-economic factors, science and technology and infrastructure. The outcomes, similarly, involve many dimensions—environment, food security and nutrition, health and socio-cultural-economic aspects. This article discusses the Mediterranean diet in the context of sustainable food systems and shows (as in all parts of the world) that there is food insecurity in every country as monitored by the Global Nutrition Index. Three recent, major reports published in 2019 suggest what measures need to be taken to improve sustainable food systems. All environmental analyses agree on the need to promote more plant-based diets—achieved practically by using “more forks than knives”. The Mediterranean Diet pattern is a case study for a sustainable diet. It has the best scientific evidence for being healthy, together with economic and socio-cultural benefits. A major challenge is that it is not consumed by the majority of the population in the Mediterranean region, and any solution must involve equity—the socially just allocation of resources. The task now is implementation with multi-stakeholder involvement, in the knowledge that “a well fed nation is a healthy nation is a sustainable and productive nation”.
Accounting for the Nutritional Context to Correctly Interpret Results from Studies of Exercise and Sedentary Behavior
Authors: Braun Barry , Newman Alissa
Published: September 2019

There is a wealth of research lauding the benefits of exercise to oppose cardiometabolic disease such as diabetes, CVD and hypertension. However, in the great majority of these studies, the nutritional context (energy balance, deficit, or surplus) has been ignored, despite its profound effect on responses to both exercise and inactivity. Even a minor energy deficit or surplus can strongly modulate the magnitude and duration of the metabolic responses to an intervention; therefore, failure to account for this important confounding variable obscures clear interpretation of the results from studies of exercise or inactivity. The aim of this review is to highlight key lessons from studies examining the interaction between exercise and sedentary behavior, energy status, and glucose and insulin regulation. In addition to identifying notable problems, we suggest a few potential solutions.
Microencapsulation of Enteric Bacteriophages in a pH-Responsive Solid Oral Dosage Formulation Using a Scalable Membrane Emulsification Process
Authors: Vinner Gurinder K. , Richards Kerry , Leppanen Miika , Sagona Antonia P. , Malik Danish J.
Published: September 2019

A scalable low-shear membrane emulsification process was used to produce microencapsulated Escherichia coli-phages in a solid oral dosage form. Uniform pH-responsive composite microparticles (mean size ~100 µm) composed of Eudragit® S100 and alginate were produced. The internal microstructure of the gelled microcapsules was studied using ion-milling and imaging, which showed that the microparticles had a solid internal core. The microencapsulation process significantly protected phages upon prolonged exposure to a simulated gastric acidic environment. Encapsulated phages that had been pre-exposed to simulated gastric acid were added to actively growing bacterial cells using in vitro cell cultures and were found to be effective in killing E. coli. Encapsulated phages were also shown to be effective in killing actively growing E. coli in the presence of human epithelial cells. Confocal microscopy images showed that the morphology of encapsulated phage-treated epithelial cells was considerably better than controls without phage treatment. The encapsulated phages were stable during refrigerated storage over a four-week period. The process of membrane emulsification is highly scalable and is a promising route to produce industrial quantities of pH-responsive oral solid dosage forms suitable for delivering high titres of viable phages to the gastrointestinal tract.
Numerical Simulation Study of Heavy Oil Production by Using In-Situ Combustion
Authors: Yang Zhao , Han Shuang , Liu Hongji
Published: September 2019

An in-situ combustion method is an effective method to enhance oil recovery with high economic recovery rate, low risk, fast promotion and application speed. Currently, in-situ combustion technique is regarded as the last feasible thermal recovery technology to replace steam injection in the exploitation of bitumen sands and heavy oil reservoirs. However, the oil-discharging mechanism during the in-situ combustion process is still not clearly understood. In this paper, the in-situ combustion process has been numerically simulated based on the Du 66 block. The effect of production parameters (huff and puff rounds, air injection speed, and air injection temperature) and geological parameters (bottom water thickness, stratigraphic layering, permeability ratio, and formation thickness) on the heavy oil recovery have been comprehensively analyzed. Results show that the flooding efficiency is positively correlated with the thickness of the bottom water, and negatively correlated with the formation heterogeneity. There exist optimum values for the oil layer thickness, huff and puff rounds, and air injection speed. And the effect of air injection temperature is not significant. The results of this paper can contribute to the understanding of mechanisms during in-situ combustion and the better production design for heavy oil reservoirs.
Regional Scale Dryland Vegetation Classification with an Integrated Lidar-Hyperspectral Approach
Authors: Dashti Hamid , Poley Andrew , F. Glenn Nancy , Ilangakoon Nayani , Spaete Lucas , Roberts Dar , Enterkine Josh , N. Flores Alejandro , L. Ustin Susan , J. Mitchell Jessica
Published: September 2019

The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral mixture analysis (MESMA) for optical vegetation classification. Lidar-derived maximum vegetation height and delineated riparian zones were then used to modify the optical classification. Incorporating the lidar information into the classification scheme increased the overall accuracy from 60% to 89%. Canopy structure can have a strong influence on spectral variability and the lidar provided complementary information for SAM’s sensitivity to shape but not magnitude of the spectra. Similar approaches to map large regions of drylands with low uncertainty may be readily implemented with unmixing algorithms applied to upcoming space-based imaging spectroscopy and lidar. This study advances our understanding of the nuances associated with mapping xeric and mesic regions, and highlights the importance of incorporating complementary algorithms and sensors to accurately characterize the heterogeneity of dryland ecosystems.
The Impact of Acquisition Date on the Prediction Performance of Topsoil Organic Carbon from Sentinel-2 for Croplands
Authors: Vaudour Emmanuelle , Gomez Cécile , Loiseau Thomas , Baghdadi Nicolas , Loubet Benjamin , Arrouays Dominique , Ali Leïla , Lagacherie Philippe
Published: September 2019

The spatial assessment of soil organic carbon (SOC) is a major environmental challenge, notably for evaluating soil carbon stocks. Recent works have shown the capability of Sentinel-2 optical data to predict SOC content over temperate agroecosystems characterized by annual crops, using a single acquisition date. Considering a Sentinel-2 time series, this work intends to analyze the impact of acquisition date, and related weather and soil surface conditions on the prediction performance of topsoil SOC content (plough layer). A Sentinel-2 time-series was gathered, comprised of the dates corresponding to both the maximum of bare soil coverage and minimum of cloud coverage. Cross-validated partial least squares regression (PLSR) models were constructed between soil reflectance image spectra, and SOC content analyzed from 329 top soil samples collected over the study area. Cross-validation R2 ranged from 0.005 to 0.58, root mean square error from 5.86 to 3.02 g·kg−1 and residual prediction deviation values from 1.0 to 1.5 (without unit), according to date. The main factors influencing these differences were soil roughness, in conjunction with soil moisture, and the cloud and cloud shadow cover of the entire tile. The best performing dates were spring dates characterized by both lowest soil surface roughness and moisture content. Normalized difference vegetation index (NDVI) values below 0.35 did not influence prediction performance. This consolidates the previous results obtained during single date acquisitions and offers wider perspectives for the further use of Sentinel-2 into multidate mosaics for digital soil mapping.
A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance
Authors: Fraga-Lamas Paula , Ramos Lucía , Mondéjar-Guerra Víctor , Fernández-Caramés Tiago M.
Published: September 2019

Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.
Editorial for the Special Issue “Remote Sensing of Evapotranspiration (ET)”
Authors: Wagle Pradeep , Gowda Prasanna H.
Published: September 2019

Evapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in 11 papers published in this special issue. The major research topics covered by this special issue include inter-comparison and performance evaluation of widely used one- and two-source energy balance models, a new dual-source model (Soil Plant Atmosphere and Remote Sensing Evapotranspiration, SPARSE), and a process-based model (ETMonitor); assessment of multi-source (e.g., remote sensing, reanalysis, and land surface model) ET products; development or improvement of data fusion frameworks to provide continuous daily ET at a high spatial resolution (field-scale or 30 m) by fusing the advanced space-borne thermal emission reflectance radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat data; and investigating uncertainties in ET estimates using an ET ensemble composed of 36 land surface models and four diagnostic datasets. The effects of the differences among ET products on water resources and ecosystem management were also investigated. More accurate ET estimates and improved understanding of remotely sensed ET products can help maximize crop productivity while minimizing water loses and management costs.
Volcano Monitoring from Space Using High-Cadence Planet CubeSat Images Applied to Fuego Volcano, Guatemala
Authors: Aldeghi Anna , Carn Simon , Escobar-Wolf Rudiger , Groppelli Gianluca
Published: September 2019

Fuego volcano (Guatemala) is one of the most active and hazardous volcanoes in the world. Its persistent activity generates lava flows, pyroclastic density currents (PDCs), and lahars that threaten the surrounding areas and produce frequent morphological change. Fuego’s eruption deposits are often rapidly eroded or remobilized by heavy rains and its constant activity and inaccessible terrain makes ground-based assessment of recent eruptive deposits very challenging. Earth-orbiting satellites can provide unique observations of volcanoes during eruptive activity, when ground-based techniques may be too hazardous, and also during inter-eruptive phases, but have typically been hindered by relatively low spatial and temporal resolution. Here, we use a new source of Earth observation data for volcano monitoring: high resolution (~3 m pixel size) images acquired from a constellation of over 150 CubeSats (‘Doves’) operated by Planet Labs Inc. The Planet Labs constellation provides high spatial resolution at high cadence (<1–72 h), permitting space-based tracking of volcanic activity with unprecedented detail. We show how PlanetScope images collected before, during, and after an eruption can be applied for mapping ash clouds, PDCs, lava flows, or the analysis of morphological change. We assess the utility of the PlanetScope data as a tool for volcano monitoring and rapid deposit mapping that could assist volcanic hazard mitigation efforts in Guatemala and other active volcanic regions.
Epoxy Composites with Reduced Graphene Oxide–Cellulose Nanofiber Hybrid Filler and Their Application in Concrete Strain and Crack Monitoring
Authors: Wu Zhiqiang , Wei Jun , Dong Rongzhen , Chen Hao
Published: September 2019

Advances in nanotechnology have provided approaches for the fabrication of new composite materials for sensing. Flexible sensors can make up for the shortcomings of traditional strain sensors in monitoring the surface strain and cracks of concrete structures. Using reduced graphene oxide (RGO) as a conductive filler, cellulose nanofiber (CNF) as a dispersant and structural skeleton, and waterborne epoxy (WEP) as a polymer matrix, a flexible composite material with piezoresistive effect was prepared by the solution blending and solvent evaporation method. The mechanical, electrical, and electromechanical properties of the composite were investigated. The results show that CNF can significantly improve the dispersion of RGO in the WEP matrix and help to form stable reinforcing and conductive networks, leading to great changes in the mechanical properties and resistivity of the composite. The composite film can withstand large deformations (>55% strain), and the resistance change rate demonstrates a high sensitivity to mechanical strain with a gauge factor of 34–71. Within a 4% strain range, the piezoresistive property of the composite is stable with good linearity and repeatability. The performance of the flexible film sensor made of the composite is tested and it can monitor the strain and crack of the concrete surface well.
Surface-Enhanced Raman Spectroscopy Based on a Silver-Film Semi-Coated Nanosphere Array
Authors: Zhang Wending , Xue Tianyang , Zhang Lu , Lu Fanfan , Liu Min , Meng Chao , Mao Dong , Mei Ting
Published: September 2019

In this paper, we present a convenient and economical method to fabricate a silver (Ag)-film semi-coated polystyrene (PS) nanosphere array substrate for surface-enhanced Raman spectroscopy (SERS). The SERS substrate was fabricated using the modified self-assembled method combined with the vacuum thermal evaporation method. By changing the thickness of the Ag film, the surface morphology of the Ag film coated on the PS nanospheres can be adjusted to obtain the optimized localized surface plasmonic resonance (LSPR) effect. The 3D-finite-difference time-domain simulation results show that the SERS substrate with an Ag film thickness of 10 nm has tens of times the electric field intensity enhancement. The Raman examination results show that the SERS substrate has excellent reliability and sensitivity using rhodamine-6G (R6G) and rhodamine-B (RB) as target analytes, and the Raman sensitivity can reach 10−10 M. Meanwhile, the SERS substrate has excellent uniformity based on the Raman mapping result. The Raman enhancement factor of the SERS substrate was estimated to be 5.1 × 106. This kind of fabrication method for the SERS substrate may be used in some applications of Raman examination.
Sensing and Self-Sensing Actuation Methods for Ionic Polymer–Metal Composite (IPMC): A Review
Authors: MohdIsa WanHasbullah , Hunt Andres , HosseinNia S. Hassan
Published: September 2019

Ionic polymer–metal composites (IPMC) are smart material transducers that bend in response to low-voltage stimuli and generate voltage in response to bending. IPMCs are mechanically compliant, simple in construction, and easy to cut into desired shape. This allows the designing of novel sensing and actuation systems, e.g., for soft and bio-inspired robotics. IPMC sensing can be implemented in multiple ways, resulting in significantly different sensing characteristics. This paper will review the methods and research efforts to use IPMCs as deformation sensors. We will address efforts to model the IPMC sensing phenomenon, and implementation and characteristics of different IPMC sensing methods. Proposed sensing methods are divided into active sensing, passive sensing, and self-sensing actuation (SSA), whereas the active sensing methods measure one of IPMC-generated voltage, charge, or current; passive methods measure variations in IPMC impedances, or use it in capacitive sensor element circuit, and SSA methods implement simultaneous sensing and actuation on the same IPMC sample. Frequency ranges for reliable sensing vary among the methods, and no single method has been demonstrated to be effective for sensing in the full spectrum of IPMC actuation capabilities, i.e., from DC to ∼100 Hz. However, this limitation can be overcome by combining several sensing methods.
Enabling Heart Self-Monitoring for All and for AAL—Portable Device within a Complete Telemedicine System
Authors: Bleda Andrés-Lorenzo , Melgarejo-Meseguer Francisco-Manuel , Gimeno-Blanes Francisco-Javier , García-Alberola Arcadi , Rojo-Álvarez José Luis , Corral Javier , Ruiz Ricardo , Maestre-Ferriz Rafael
Published: September 2019

During the last decades there has been a rapidly growing elderly population and the number of patients with chronic heart-related diseases has exploded. Many of them (such as those with congestive heart failure or some types of arrhythmias) require close medical supervision, thus imposing a big burden on healthcare costs in most western economies. Specifically, continuous or frequent Arterial Blood Pressure (ABP) and electrocardiogram (ECG) monitoring are important tools in the follow-up of many of these patients. In this work, we present a novel remote non-ambulatory and clinically validated heart self-monitoring system, which allows ABP and ECG monitoring to effectively identify clinically relevant arrhythmias. The system integrates digital transmission of the ECG and tensiometer measurements, within a patient-comfortable support, easy to recharge and with a multi-function software, all of them aiming to adapt for elderly people. The main novelty is that both physiological variables (ABP and ECG) are simultaneously measured in an ambulatory environment, which to our best knowledge is not readily available in the clinical market. Different processing techniques were implemented to analyze the heart rhythm, including pause detection, rhythm alterations and atrial fibrillation, hence allowing early detection of these diseases. Our results achieved clinical quality both for in-lab hardware testing and for ambulatory scenario validations. The proposed active assisted living (AAL) Sensor-based system is an end-to-end multidisciplinary system, fully connected to a platform and tested by the clinical team from beginning to end.
Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT
Authors: Minet Pascale , Tanaka Yasuyuki
Published: September 2019

The Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its ability to meet three Key Performance Indicators (KPIs), namely a maximum acceptable end-to-end latency L, a targeted end-to-end reliability R and a minimum network lifetime T. The IoT network has to guarantee that at least R % of messages generated by sensor nodes are delivered to the sink with a latency ≤L, whereas the network lifetime is at least equal to T. In this paper, we show how to provide the targeted end-to-end reliability R by means of retransmissions to cope with the unreliability of wireless links. We present two methods to compute the maximum number of transmissions per message required to achieve R. M F a i r is very easy to compute, whereas M O p t minimizes the total number of transmissions necessary for a message to reach the sink. M F a i r and M O p t are then integrated into a TSCH network with a load-based scheduler to evaluate the three KPIs on a generic data-gathering application. We first consider a toy example with eight nodes where the maximum number of transmissions M a x T r a n s is tuned per link and per flow. Finally, a network of 50 nodes, representative of real network deployments, is evaluated assuming M a x T r a n s is fixed. For both TSCH networks, we show that M O p t provides a better reliability and a longer lifetime than M F a i r , which provides a shorter average end-to-end latency. M O p t provides more predictable end-to-end performances than Kausa, a KPI-aware, state-of-the-art scheduler.
Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm
Authors: Cruz Carlos , Palomar Esther , Bravo Ignacio , Gardel Alfredo
Published: September 2019

The Internet of Things (IoT) and Demand Response (DR) combined have transformed the way Information and Communication Technologies (ICT) contribute to saving energy and reducing costs, while also giving consumers more control over their energy footprint. Unlike current price and incentive based DR strategies, we propose a DR model that promotes consumers reaching coordinated behaviour towards more sustainable (and green) communities. A cooperative DR system is designed not only to bolster energy efficiency management at both home and district levels, but also to integrate the renewable energy resource information into the community’s energy management. Initially conceived in a centralised way, a data collector called the “aggregator” will handle the operation scheduling requirements given the consumers’ time preferences and the available electricity supply from renewables. Evaluation on the algorithm implementation shows feasible computational cost (CC) in different scenarios of households, communities and consumer behaviour. Number of appliances and timeframe flexibility have the greatest impact on the reallocation cost. A discussion on the communication, security and hardware platforms is included prior to future pilot deployment.
A Framework for the Joint Placement of Edge Service Infrastructure and User Plane Functions for 5G
Authors: Leyva-Pupo Irian , Santoyo-González Alejandro , Cervelló-Pastor Cristina
Published: September 2019

Achieving less than 1 ms end-to-end communication latency, required for certain 5G services and use cases, is imposing severe technical challenges for the deployment of next-generation networks. To achieve such an ambitious goal, the service infrastructure and User Plane Function (UPF) placement at the network edge, is mandatory. However, this solution implies a substantial increase in deployment and operational costs. To cost-effectively solve this joint placement problem, this paper introduces a framework to jointly address the placement of edge nodes (ENs) and UPFs. Our framework proposal relies on Integer Linear Programming (ILP) and heuristic solutions. The main objective is to determine the ENs and UPFs’ optimal number and locations to minimize overall costs while satisfying the service requirements. To this aim, several parameters and factors are considered, such as capacity, latency, costs and site restrictions. The proposed solutions are evaluated based on different metrics and the obtained results showcase over 20 % cost savings for the service infrastructure deployment. Moreover, the gap between the UPF placement heuristic and the optimal solution is equal to only one UPF in the worst cases, and a computation time reduction of over 35 % is achieved in all the use cases studied.
SAR and Optical Data Comparison for Detecting Co-Seismic Slip and Induced Phenomena during the 2018 Mw 7.5 Sulawesi Earthquake
Authors: Polcari Marco , Tolomei Cristiano , Bignami Christian , Stramondo Salvatore
Published: September 2019

We use both Synthetic Aperture Radar (SAR) and Optical data to constrain the co-seismic ground deformation produced by the 2018 Mw 7.5 Sulawesi earthquake. We exploit data processing techniques mainly based on pixel cross-correlation approach, applied to Synthetic Aperture Radar (SAR) and optical images to estimate the North–South (NS) displacement component. This component is the most significant because of the NNW–SSE geometry of the fault responsible for the seismic event, i.e., the Palu-Koro fault, characterized by a strike-slip faulting mechanism. Our results show a good agreement between the different data allowing to clearly identify the surface rupture due to the fault slip. Moreover, we use SAR and optical intensity images to investigate several secondary phenomena generated by the seismic event such as tsunami, landslides, and coastal retreat. Finally, we discuss differences between SAR and optical outcomes showing strengths and disadvantages of each one according to the investigated phenomenon.
An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers
Authors: Charalampou Paris , Sykas Efstathios D.
Published: September 2019

There is a lot of effort to limit the impact of CO2 emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable gains are expected by regulating the operation network devices. In this context, we developed a mixed integer programming (MIP) algorithm to optimize the power consumption of network devices via energy aware traffic engineering. We verified our approach by simulating DC network topologies and demonstrated that clear benefits can be achieved for various network sizes and traffic volumes. Our algorithm can be easily implemented as an application in the software-defined networking (SDN) paradigm, making quite feasible its deployment in a production environment.
Deep Learning for Industrial Computer Vision Quality Control in the Printing Industry 4.0
Authors: Villalba-Diez Javier , Schmidt Daniel , Gevers Roman , Ordieres-Meré Joaquín , Buchwitz Martin , Wellbrock Wanja
Published: September 2019

Rapid and accurate industrial inspection to ensure the highest quality standards at a competitive price is one of the biggest challenges in the manufacturing industry. This paper shows an application of how a Deep Learning soft sensor application can be combined with a high-resolution optical quality control camera to increase the accuracy and reduce the cost of an industrial visual inspection process in the Printing Industry 4.0. During the process of producing gravure cylinders, mistakes like holes in the printing cylinder are inevitable. In order to improve the defect detection performance and reduce quality inspection costs by process automation, this paper proposes a deep neural network (DNN) soft sensor that compares the scanned surface to the used engraving file and performs an automatic quality control process by learning features through exposure to training data. The DNN sensor developed achieved a fully automated classification accuracy rate of 98.4%. Further research aims to use these results to three ends. Firstly, to predict the amount of errors a cylinder has, to further support the human operation by showing the error probability to the operator, and finally to decide autonomously about product quality without human involvement.