bluuebunny/crossref_metadata_2025 huggingface dataset:
Toward of Safer Phenylbutazone Derivatives by Exploration of Toxicity Mechanism
Authors: Borges Rosivaldo S. , Palheta Ivanete C. , Ota Sirlene S. B. , Morais Roberto B. , Barros Valéria A. , Ramos Ryan S. , Silva Rai C. , Costa Josivan da S. , Silva Carlos H. T. P. , Campos Joaquín M. , Santos Cleydson B. R.
Published: January 2019

A drug design for safer phenylbutazone was been explored by reactivity and docking studies involving single electron transfer mechanism, as well as toxicological predictions. Several approaches about its structural properties were performed through quantum chemistry calculations at the B3LYP level of theory, together with the 6-31+G(d,p) basis sets. Molecular orbital and ionization potential were associated to electron donation capacity. The spin densities contribution showed a preferential hydroxylation at the para-positions of phenyl ring when compared to other positions. In addition, on electron abstractions the aromatic hydroxylation has more impact than alkyl hydroxylation. Docking studies indicate that six structures 1, 7, 8 and 13–15 have potential for inhibiting human as well as murine COX-2, due to regions showing similar intermolecular interactions to the observed for the control compounds (indomethacin and refecoxib). Toxicity can be related to aromatic hydroxylation. In accordance to our calculations, the derivatives here proposed are potentially more active as well safer than phenylbutazone and only structures 8 and 13–15 were the most promising. Such results can explain the biological properties of phenylbutazone and support the design of potentially safer candidates.
Classification of Frozen Corn Seeds Using Hyperspectral VIS/NIR Reflectance Imaging
Authors: Zhang Jun , Dai Limin , Cheng Fang
Published: January 2019

A VIS/NIR hyperspectral imaging system was used to classify three different degrees of freeze-damage in corn seeds. Using image processing methods, the hyperspectral image of the corn seed embryo was obtained first. To find a relatively better method for later imaging visualization, four different pretreatment methods (no pretreatment, multiplicative scatter correction (MSC), standard normal variation (SNV) and 5 points and 3 times smoothing (5-3 smoothing)), four wavelength selection algorithms (successive projection algorithm (SPA), principal component analysis (PCA), X-loading and full-band method) and three different classification modeling methods (partial least squares-discriminant analysis (PLS-DA), K-nearest neighbor (KNN) and support vector machine (SVM)) were applied to make a comparison. Next, the visualization images according to a mean spectrum to mean spectrum (M2M) and a mean spectrum to pixel spectrum (M2P) were compared in order to better represent the freeze damage to the seed embryos. It was concluded that the 5-3 smoothing method and SPA wavelength selection method applied to the modeling can improve the signal-to-noise ratio, classification accuracy of the model (more than 90%). The final classification results of the method M2P were better than the method M2M, which had fewer numbers of misclassified corn seed samples and the samples could be visualized well.
Aflatoxin B1–Formamidopyrimidine DNA Adducts: Relationships between Structures, Free Energies, and Melting Temperatures
Authors: Klvana Martin , Bren Urban
Published: January 2019

Thermal stabilities of DNA duplexes containing Gua (g), α- (a) or β-anomer of formamidopyrimidine-N7-9-hydroxy-aflatoxin B1 (b) differ markedly (Tm: a < g < b ), but the underlying molecular origin of this experimentally observed phenomenon is yet to be identified and determined. Here, by employing explicit-solvent molecular dynamics simulations coupled with free-energy calculations using a combined linear-interaction-energy/linear-response-approximation approach, we explain the quantitative differences in T m in terms of three structural features (bulkiness, order, and compactness) and three energetical contributions (non-polar, electrostatic, and preorganized-electrostatic), and thus advance the current understanding of the relationships between structures, free energies, and thermal stabilities of DNA double helices.
The Anti-Candida albicans Agent 4-AN Inhibits Multiple Protein Kinases
Authors: Masłyk Maciej , Janeczko Monika , Martyna Aleksandra , Czernik Sławomir , Tokarska-Rodak Małgorzata , Chwedczuk Marta , Foll-Josselin Béatrice , Ruchaud Sandrine , Bach Stéphane , Demchuk Oleg M. , Kubiński Konrad
Published: January 2019

Small molecules containing quinone and/or oxime moieties have been found as promising anti-fungal agents. One of them is 4-AN, a recently reported potent anti-Candida compound, which inhibits the formation of hyphae, decreases the level of cellular phosphoproteome, and finally shows no toxicity towards human erythrocytes and zebrafish embryos. Here, further research on 4-AN is presented. The results revealed that the compound: (i) Kills Candida clinical isolates, including these with developed antibiotic resistance, (ii) affects mature biofilm, and (iii) moderately disrupts membrane permeability. Atomic force microscopy studies revealed a slight influence of 4-AN on the cell surface architecture. 4-AN was also shown to inhibit multiple various protein kinases, a characteristic shared by most of the ATP-competitive inhibitors. The presented compound can be used in novel strategies in the fight against candidiasis, and reversible protein phosphorylation should be taken into consideration as a target in designing these strategies.
Biosynthesis, Chemistry, and Pharmacology of Polyphenols from Chinese Salvia Species: A Review
Authors: Wang Jie , Xu Jianping , Gong Xue , Yang Min , Zhang Chunhong , Li Minhui
Published: January 2019

Salvia species find widespread application in food and pharmaceutical products owing to their large polyphenol content. The main polyphenols in Chinese Salvia species are phenolic acids and flavonoids, which exhibit anti-oxygenation, anti-ischemia-reperfusion injury, anti-thrombosis, anti-tumour, and other therapeutic effects. However, there are few peer-reviewed studies on polyphenols in Chinese Salvia species, especially flavonoids. This review is a systematic, comprehensive collation of available information on the biosynthesis, chemistry, and pharmacology of Chinese Salvia species. We believe that our study makes a significant contribution to the literature because this review provides a detailed literary resource on the currently available information on various polyphenolic components of Chinese Salvia species, including their bioactivities and structures. In addition, the study provides information that would encourage further investigation of this plant material as a natural resource with potential for a broad range of applications in various industries, such as the food and pharmaceutical industries.
(−)-Epigallocatechin-3-Gallate Decreases Osteoclastogenesis via Modulation of RANKL and Osteoprotegrin
Authors: Chen Shih-Tse , Kang Lin , Wang Chau-Zen , Huang Peng-Ju , Huang Hsuan-Ti , Lin Sung-Yen , Chou Shih-Hsiang , Lu Cheng-Chang , Shen Po-Chih , Lin Yi-Shan , Chen Chung-Hwan
Published: January 2019

Osteoporosis is the second most common epidemiologic disease in the aging population worldwide. Previous studies have found that frequent tea drinkers have higher bone mineral density and less hip fracture. We previously found that (−)-epigallocatechin gallate (EGCG) (20–100 µmol/L) significantly suppressed receptor activator of nuclear factor-kB ligand (RANKL)-induced osteoclastogenesis and pit formation via inhibiting NF-κB transcriptional activity and nuclear transport of NF-κB in RAW 264.7 cells and murine primary bone marrow macrophage cells. The most important regulation in osteoclastogenesis is the receptor activator of nuclear factor-kB/RANKL/osteoprotegrin (RANK/RANKL/OPG) pathway. In this study, we used the coculture of RAW 264.7 cells and the feeder cells, ST2, to evaluate how EGCG regulated the RANK/RANKL/OPG pathway in RAW 264.7 cells and ST2 cells. We found EGCG decreased the RANKL/OPG ratio in both mRNA expression and secretory protein levels and eventually decreased osteoclastogenesis by TRAP (+) stain osteoclasts and TRAP activity at low concentrations—1 and 10 µmol/L—via the RANK/RANKL/OPG pathway. The effective concentration can be easily achieved in daily tea consumption. Taken together, our results implicate that EGCG could be an important nutrient in modulating bone resorption.
Introduction to “Advances in Photodynamic Therapy 2018”
Authors: Hamblin Michael R
Published: January 2019

This Special Issue of Molecules entitled “Advances in Photodynamic Therapy 2018” contains seven papers, including five original reports and two reviews. [...]
Alicyclic β- and γ-Amino Acids: Useful Scaffolds for the Stereocontrolled Access to Amino Acid-Based Carbocyclic Nucleoside Analogs
Authors: Remete Attila Márió , Kiss Loránd
Published: January 2019

Stereocontrolled synthesis of some amino acid-based carbocyclic nucleoside analogs containing ring C=C bond has been performed on β- and γ-lactam basis. Key steps were N-arylation of readily available β- or γ-lactam-derived amino ester isomers and amino alcohols with 5-amino-4,6-dichloropyrimidine; ring closure of the formed adduct with HC(OMe)3 and nucleophilic displacement of chlorine with various N-nucleophiles in the resulting 6-chloropurine moiety.
New Polymers for Needleless Electrospinning from Low-Toxic Solvents
Authors: Wortmann Martin , Frese Natalie , Sabantina Lilia , Petkau Richard , Kinzel Franziska , Gölzhäuser Armin , Moritzer Elmar , Hüsgen Bruno , Ehrmann Andrea
Published: January 2019

Electrospinning is a new technology whose scope is gradually being developed. For this reason, the number of known polymer–solvent combinations for electrospinning is still very low despite the enormous variety of substances that are potentially available. In particular, electrospinning from low-toxic solvents, such as the use of dimethyl sulfoxide (DMSO) in medical technology, is rare in the relevant scientific literature. Therefore, we present in this work a series of new polymers that are applicable for electrospinning from DMSO. From a wide range of synthetic polymers tested, poly(vinyl alcohol) (PVOH), poly(2ethyl2oxazolene) (PEOZ), and poly(vinylpyrrolidone) (PVP) as water-soluble polymers and poly(styrene-co-acrylonitrile) (SAN), poly(vinyl alcohol-co-ethylene) (EVOH), and acrylonitrile butadiene styrene (ABS) as water-insoluble polymers were found to be suitable for the production of nanofibers. Furthermore, the influence of acetone as a volatile solvent additive in DMSO on the fiber morphology of these polymers was investigated. Analyses of the fiber morphology by helium ion microscopy (HIM) showed significantly different fiber diameters for different polymers and a reduction in beads and branches with increasing acetone content.
A Controllability Investigation of Magnetic Properties for FePt Alloy Nanocomposite Thin Films
Authors: Yu Jian , Xiao Tingting , Wang Xuemin , Zhou Xiuwen , Wang Xinming , Peng Liping , Zhao Yan , Wang Jin , Chen Jie , Yin Hongbu , Wu Weidong
Published: January 2019

An appropriate writing field is very important for magnetic storage application of L10 FePt nanocomposite thin films. However, the applications of pure L10 FePt are limited due to its large coercivity. In this paper, the ratios of L10 and non-L10 phase FePt alloy nanoparticles in FePt/MgO (100) nanocomposite thin films were successfully tuned by pulsed laser deposition method. By adjusting the pulsed laser energy density from 3 to 7 J/cm2, the ordering parameter initially increased, and then decreased. The highest ordering parameter of 0.9 was obtained at the pulsed laser energy density of 5 J/cm2. At this maximum value, the sample had the least amount of the soft magnetic phase of almost 0%, as analyzed by a magnetic susceptibility study. The saturation magnetization decreased with the increase in the content of soft magnetic phase. Therefore, the magnetic properties of FePt nanocomposite thin films can be controlled, which would be beneficial for the magnetic applications of these thin films.
Realization of the Kohn’s Theorem in Ge/Si Quantum Dots with Hole Gas: Theory and Experiment
Authors: Sarkisyan Hayk A. , Hayrapetyan David B. , Petrosyan Lyudvig S. , Kazaryan Eduard M. , Sofronov Anton N. , Balagula Roman M. , Firsov Dmitry A. , Vorobjev Leonid E. , Tonkikh Alexander A.
Published: January 2019

This article discusses specific quantum transitions in a few-particle hole gas, localized in a strongly oblate lens-shaped quantum dot. Based on the adiabatic method, the possibility of realizing the generalized Kohn theorem in such a system is shown. The criteria for the implementation of this theorem in a lens-shaped quantum dot, fulfilled in the experiment, is presented. An analytical expression is obtained for the frequencies of resonant absorption of far-infrared radiation by a gas of heavy holes, which depends on the geometric parameters of the quantum dot. The results of experiments on far-infrared absorption in the arrays of p-doped Ge/Si quantum dots grown by molecular beam epitaxy (MBE) with gradually increasing average number of holes in dot are presented. Experimental results show that the Coulomb interaction between the holes does not affect the resonant frequency of the transitions. A good agreement between the theoretical and experimental results is shown.
Hot Deformation Behavior and Processing Maps of SiC Nanoparticles and Second Phase Synergistically Reinforced Magnesium Matrix Composites
Authors: Nie Kaibo , Zhu Zhihao , Deng Kunkun , Wang Ting , Han Jungang
Published: January 2019

Magnesium matrix composites synergistically reinforced by SiC nanoparticles and second phases were prepared by 12 passes of multi-pass forging, varying the temperature. The effects of grain refinement and the precipitates on the hot deformation behavior were analyzed. Deformation zones which could be observed in the fine-grained nanocomposite before hot compression disappeared, and the trend of streamlined distribution for the precipitated phases was weakened. At the same compression rate, as the compression temperature increased, the number of precipitated phases decreased, and the grain size increased. For fine-grained nanocomposites, after the peak stress, there was no obvious dynamic softening stage on the stress–strain curve, and then the steady stage was quickly reached. The critical stress of the fine-grained nanocomposites was lower than that of the coarse-grained nanocomposites, which can be attributed to the large amounts of precipitates and significantly refined grains. The deformation mechanism of the coarse-grained nanocomposite was controlled by dislocation climb resulting from lattice diffusion, while the deformation mechanism for the fine-grained nanocomposite was dislocation climb resulting from grain boundary slip. The activation energy of the fine-grained nanocomposite was decreased, compared with the coarse-grained nanocomposite. The area of the workability region for the fine-grained nanocomposite was significantly larger than that of the coarse-grained nanocomposite, and there was no instability region at a low strain rate (0.001–0.01 s−1) under all deformation temperatures. The optimal workability region was 573 K /0.001–0.01 s−1 for the fine-grained nanocomposite, and the processing temperature was lower than the coarse-grained nanocomposite (623–673 K).
Selenium Intake in Iodine-Deficient Pregnant and Breastfeeding Women in New Zealand
Authors: Jin Ying , Coad Jane , Weber Janet L , Thomson Jasmine S , Brough Louise
Published: January 2019

Selenium plays a role in antioxidant status and, together with iodine, in thyroid function. Iodine deficiency exists in New Zealand during pregnancy and lactation, and selenium deficiency may further affect thyroid function. This study investigated selenium intakes of pregnant and lactating women, in Palmerston North, in the North Island of New Zealand. Dietary intake was estimated using three repeated 24-h dietary recalls. Dietary intake in pregnancy was also estimated from 24-h urinary excretion of selenium. Selenium concentrations were determined in urine and breastmilk using inductively-coupled plasma mass spectrometry. Median selenium intakes based on dietary data were 51 (39, 65) μg/day in pregnancy and 51 (36, 80) μg/day in lactation, with 61% and 68% below estimated average requirement (EAR). Median daily selenium intake in pregnancy based on urinary excretion was 49 (40, 60) µg/day, with 59% below EAR. Median selenium concentration in breastmilk was 11 (10, 13) µg/L and estimated median selenium intake for infants was 9 (8, 10) µg/day, with 91% below the Adequate Intake of 12 μg/day. These pregnant and breastfeeding women were at risk of dietary selenium inadequacy. Further research is required to assess selenium status in relation to thyroid function and health in this group.
Development of [131I]I-EOE-TPZ and [131I]I-EOE-TPZMO: Novel Tirapazamine (TPZ)-Based Radioiodinated Pharmaceuticals for Application in Theranostic Management of Hypoxia
Authors: Elsaidi Hassan , Ahmadi Fatemeh , Wiebe Leonard , Kumar Piyush
Published: January 2019

Introduction: Benzotriazine-1,4-dioxides (BTDOs) such as tirapazamine (TPZ) and its derivatives act as radiosensitizers of hypoxic tissues. The benzotriazine-1-monoxide (BTMO) metabolite (SR 4317, TPZMO) of TPZ also has radiosensitizing properties, and via unknown mechanisms, is a potent enhancer of the radiosensitizing effects of TPZ. Unlike their 2-nitroimidazole radiosensitizer counterparts, radiolabeled benzotriazine oxides have not been used as radiopharmaceuticals for diagnostic imaging or molecular radiotherapy (MRT) of hypoxia. The radioiodination chemistry for preparing model radioiodinated BTDOs and BTMOs is now reported. Hypothesis: Radioiodinated 3-(2-iodoethoxyethyl)-amino-1,2,4-benzotriazine-1,4-dioxide (I-EOE-TPZ), a novel bioisosteric analogue of TPZ, and 3-(2-iodoethoxyethyl)-amino-1,2,4-benzotriazine-1-oxide (I-EOE-TPZMO), its monoxide analogue, are candidates for in vivo and in vitro investigations of biochemical mechanisms in pathologies that develop hypoxic microenvironments. In theory, both radiotracers can be prepared from the same precursors. Methods: Radioiodination procedures were based on classical nucleophilic [131I]iodide substitution on Tos-EOE-TPZ (P1) and by [131I]iodide exchange on I-EOE-TPZ (P2). Reaction parameters, including temperature, reaction time, solvent and the influence of pivalic acid on products’ formation and the corresponding radiochemical yields (RCY) were investigated. Results: The [131I]iodide labeling reactions invariably led to the synthesis of both products, but with careful manipulation of conditions the preferred product could be recovered as the major product. Radioiodide exchange on P2 in ACN at 80 ± 5 °C for 30 min afforded the highest RCY, 89%, of [131I]I-EOE-TPZ, which upon solid phase purification on an alumina cartridge gave 60% yield of the product with over 97% of radiochemical purity. Similarly, radioiodide exchange on P2 in ACN at 50 ± 5 °C for 30 min with pivalic acid afforded the highest yield, 92%, of [131I]I-EOE-TPZMO exclusively with no trace of [131I]I-EOE-TPZ. In both cases, extended reaction times and/or elevated temperatures resulted in the formation of at least two additional radioactive reaction products. Conclusions: Radioiodination of P1 and P2 with [131I]iodide leads to the facile formation of [131I]I-EOE-TPZMO. At 80 °C and short reaction times, the facile reduction of the N-4-oxide moiety was minimized to afford acceptable radiochemical yields of [131I]I-EOE-TPZ from either precursor. Regeneration of [131I]I-EOE-TPZ from [131I]I-EOE-TPZMO is impractical after reaction work-up.
Intermolecular Interactions in Polyelectrolyte and Surfactant Complexes in Solution
Authors: Khan Nasreen , Brettmann Blair
Published: January 2019

Polyelectrolytes are an important class of polymeric materials and are increasingly used in complex industrial formulations. A core use of these materials is in mixtures with surfactants, where a combination of hydrophobic and electrostatic interactions drives unique solution behavior and structure formation. In this review, we apply a molecular level perspective to the broad literature on polyelectrolyte-surfactant complexes, discussing explicitly the hydrophobic and electrostatic interaction contributions to polyelectrolyte surfactant complexes (PESCs), as well as the interplay between the two molecular interaction types. These interactions are sensitive to a variety of solution conditions, such as pH, ionic strength, mixing procedure, charge density, etc. and these parameters can readily be used to control the concentration at which structures form as well as the type of structure in the bulk solution.
Synthesis of Bithiophene-Based D-A1-D-A2 Terpolymers with Different A2 Moieties for Polymer Solar Cells via Direct Arylation
Authors: Huang Jinfeng , Lin Zhenkun , Feng Wenhuai , Wang Wen
Published: January 2019

A series of bithiophene (2T)-based D-A1-D-A2 terpolymers with different A2 moieties were prepared via direct arylation reaction. In these terpolymers, pyrrolo[3,4-c]pyrrole-1,4-dione (DPP) was selected as the first electron-accepting (A1) moiety, 2,1,3-benzothiadiazole (BT) or fluorinated benzothiadiazole (FBT) or octyl-thieno[3,4-c]pyrrole-4,6-dione (TPD) or 2,1,3-benzoselendiazole (SeT) was selected as the second electron-accepting (A2) moiety, while bithiophene with hexyl side chain was used as the electron-donating moiety. The UV-vis absorption, electrochemical properties, blend film morphology, and photovoltaic properties were studied to explore the effects of the A2 moiety. It is shown that these terpolymer films exhibit broad absorption (350–1000 nm), full width at half-maximum of more than 265 nm and ordered molecular packing. Varying the A2 moiety could affect the energy levels and blend film morphology leading to different polymer solar cell (PSC) performances of these (2T)-based D-A1-D-A2 terpolymers. As a result, the highest Jsc of 10.70 mA/cm2 is achieved for Polymer 1 (P1) with BT as A2 moiety, while the higher highest occupied molecular orbital (HOMO) level limits the open circuit voltage (Voc) and leads to a power conversion efficiency (PCE) of 3.46%.
Deterioration in the Physico-Mechanical and Thermal Properties of Biopolymers Due to Reprocessing
Authors: Shojaeiarani Jamileh , Bajwa Dilpreet S. , Rehovsky Chad , Bajwa Sreekala G. , Vahidi Ghazal
Published: January 2019

Biopolymers are an emerging class of materials being widely pursued due to their ability to degrade in short periods of time. Understanding and evaluating the recyclability of biopolymers is paramount for their sustainable and efficient use in a cost-effective manner. Recycling has proven to be an important solution, to control environmental and waste management issues. This paper presents the first recycling assessment of Solanyl, Bioflex, polylactic acid (PLA) and PHBV using a melt extrusion process. All biopolymers were subjected to five reprocessing cycles. The thermal and mechanical properties of the biopolymers were investigated by GPC, TGA, DSC, mechanical test, and DMA. The molecular weights of Bioflex and Solanyl showed no susceptible effect of the recycling process, however, a significant reduction was observed in the molecular weight of PLA and PHBV. The inherent thermo-mechanical degradation in PHBV and PLA resulted in 20% and 7% reduction in storage modulus, respectively while minimal reduction was observed in the storage modulus of Bioflex and Solanyl. As expected from the Florry-Fox equation, recycled PLA with a high reduction in molecular weight (78%) experienced 9% reduction in glass transition temperature. Bioflex and Solanyl showed 5% and 2% reduction in molecular weight and experienced only 2% reduction in glass transition temperature. These findings highlight the recyclability potential of Bioflex and Solanyl over PLA and PHBV.
Giorgio Agamben—A Modern Sabbatian? Marranic Messianism and the Problem of Law
Authors: Sawczyński Piotr
Published: January 2019

The article analyzes the influence of the kabbalistic doctrine of Sabbatianism on the messianic philosophy of Giorgio Agamben. I argue against Simon Critchley that Agamben’s critique of the sovereign law is not inspired by Marcion’s idea of the total annihilation of law but by Sabbatai Zevi’s project of deactivating its repressive function. I further argue that Agamben also adopts the Sabbatian idea of Marranic messianism, which makes him repeatedly contaminate the Jewish tradition with foreign influences. Although this strategy is potentially fruitful, it eventually leads Agamben to overemphasize antinomianism and problematically associate all Jewish-based messianism with the radical critique of law. In the article, I demonstrate that things are more complex and even in the openly antinomian works of Walter Benjamin—Agamben’s greatest philosophical inspiration—Jewish law is endued with some emancipatory potential.
The Theology of Dog Training in Vicki Hearne’s Adam’s Task
Authors: Mershon Katharine
Published: January 2019

“The Theology of Dog Training” demonstrates the rich and surprising ways in which religion plays a primary role in how people make sense of their relationships with their companion animals. In the first sustained analysis of Adam’s Task in religious studies, I argue that feminist writer and dog trainer Vicki Hearne describes a form of relational redemption that allows for the restoration of a prelapsarian language between humans and animals; a recovery of a time before humans sinned against God and subsequently lost their authority over animals. Training, which begins with the act of naming a dog and bringing them into the moral life, is Hearne’s attempt to restore what was lost in the Fall for both humans and animals. In making this argument, I join a growing community of scholars who are committed to bringing animal studies to the academic study of religion. In addition to analyzing religion as it occurs in non-institutional spaces, I examine phenomena that would not necessarily be considered religious, but, as I show, make ethical and religious claims on human–canine relationships. By investigating institutions, texts, and practices in contemporary America that traditionally have not been identified as religious, my article shows how religious beliefs and forms can help us build an ethics of multispecies relations.
Benefit Analysis and Regulatory Actions for Imported Palm Kernel Shell as an Environment-Friendly Energy Source in Taiwan
Authors: Tsai Wen-Tien
Published: January 2019

In response to the lack of locally natural sources and the environmental concerns about greenhouse gas (GHG) emissions, using a wide variety of biomass residues as energy sources has attracted much attention in the past two decades. The purpose of the case study was to examine the energy use of imported palm kernel shell (PKS) in Taiwan, which has generated superheated steam for the end users in the industrial sector. In this work, characterizing the thermochemical properties of imported PKS (including proximate analysis, elemental analysis and calorific value) was first conducted by the standard test methods. Based on the statistics of imported PKS and the method developed by the Intergovernmental Panel on Climate Change (IPCC), the preliminary benefit analysis of PKS-to-energy was further addressed in the paper to verify its equivalent GHG emission mitigation. The results showed the annual benefit of equivalent GHG mitigation of about 78,647 metric tons (using annual imported PKS of 60,000 metric tons on an average). In addition, the economic benefit for purchasing PKS in the industrial boilers can gain the cost-down at approximately NT$60,000,000 (US$2,000,000) in comparison with that of fuel oil. Furthermore, the regulatory measures for upgrading PKS-to-energy and countermeasures for controlling air pollutant emissions from PKS-to-energy facilities were briefly summarized to create another circular economy. Finally, some technological recommendations have been addressed to upgrade the added values of imported PKS in Taiwan.
Multi-Temporal SAR Data Large-Scale Crop Mapping Based on U-Net Model
Authors: Wei Sisi , Zhang Hong , Wang Chao , Wang Yuanyuan , Xu Lu
Published: January 2019

Due to the unique advantages of microwave detection, such as its low restriction from the atmosphere and its capability to obtain structural information about ground targets, synthetic aperture radar (SAR) is increasingly used in agricultural observations. However, while SAR data has shown great potential for large-scale crop mapping, there have been few studies on the use of SAR images for large-scale multispecies crop classification at present. In this paper, a large-scale crop mapping method using multi-temporal dual-polarization SAR data was proposed. To reduce multi-temporal SAR data redundancy, a multi-temporal images optimization method based on analysis of variance (ANOVA) and Jeffries–Matusita (J–M) distance was applied to the time series of images after preprocessing to select the optimal images. Facing the challenges from smallholder farming modes, which caused the complex crop planting patterns in the study area, U-Net, an improved fully convolutional network (FCN), was used to predict the different crop types. In addition, the batch normalization (BN) algorithm was introduced to the U-Net model to solve the problem of a large number of crops and unbalanced sample numbers, which had greatly improved the efficiency of network training. Finally, we conducted experiments using multi-temporal Sentinel-1 data from Fuyu City, Jilin Province, China in 2017, and we obtained crop mapping results with an overall accuracy of 85% as well as a Kappa coefficient of 0.82. Compared with the traditional machine learning methods (e.g., random forest (RF) and support vector machine (SVM)), the proposed method can still achieve better classification performance under the condition of a complex crop planting structure.
Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks
Authors: Langford Zachary L. , Kumar Jitendra , Hoffman Forrest M. , Breen Amy L. , Iversen Colleen M.
Published: January 2019

Land cover datasets are essential for modeling and analysis of Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, often limited due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The fusion of hyperspectral, multispectral, and terrain datasets was performed using unsupervised and supervised classification techniques over a ∼343 km2 area, and a high-resolution (5 m) vegetation classification map was generated. An unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters. We employed a quantitative method to add supervision to the unlabeled clusters, producing a fully labeled vegetation map. We then developed convolutional neural networks (CNNs) using the multi-sensor fusion datasets to map vegetation distributions using the original classes and the classes produced by the unsupervised classification method. To validate the resulting CNN maps, vegetation observations were collected at 30 field plots during the summer of 2016, and the resulting vegetation products developed were evaluated against them for accuracy. Our analysis indicates the CNN models based on the labels produced by the unsupervised classification method provided the most accurate mapping of vegetation types, increasing the validation score (i.e., precision) from 0.53 to 0.83 when evaluated against field vegetation observations.
Group Line Energy in Phase-Resolved Ocean Surface Wave Orbital Velocity Reconstructions from X-band Doppler Radar Measurements of the Sea Surface
Authors: Kammerer Andrew J. , Hackett Erin E.
Published: January 2019

The wavenumber-frequency spectra of many radar measurements of the sea surface contain a linear feature at frequencies lower than the first order dispersion relationship commonly referred to as the “group line”. Plant and Farquharson, showed numerically that the group line is at least partially caused by wave interference-induced breaking of steep short gravity waves. This paper uses two wave retrieval techniques, proper orthogonal decomposition (POD) and FFT-based dispersion curve filtering, to examine two X-band radar datasets, and compare wave orbital velocity reconstructions to ground truth wave buoy measurements within the field of view of the radar. POD allows group line energy to be retained in the reconstruction, while dispersion curve filtering removes all energy not associated with the first order dispersion relationship. Results show that when group line energy is higher or comparable to dispersion curve energy, the inclusion of this group line energy in phase-resolved orbital velocity reconstructions increases the accuracy of the reconstruction. This increased accuracy is demonstrated by higher correlations between POD reconstructed time series with buoy ground truth measurements than dispersion curve filtered reconstructions. When energy lying on the dispersion relationship is much higher than the group line energy, the FFT and POD reconstruction methods perform comparably.
Indoor Topological Localization Using a Visual Landmark Sequence
Authors: Zhu Jiasong , Li Qing , Cao Rui , Sun Ke , Liu Tao , Garibaldi Jonathan M. , Li Qingquan , Liu Bozhi , Qiu Guoping
Published: January 2019

This paper presents a novel indoor topological localization method based on mobile phone videos. Conventional methods suffer from indoor dynamic environmental changes and scene ambiguity. The proposed Visual Landmark Sequence-based Indoor Localization (VLSIL) method is capable of addressing problems by taking steady indoor objects as landmarks. Unlike many feature or appearance matching-based localization methods, our method utilizes highly abstracted landmark sematic information to represent locations and thus is invariant to illumination changes, temporal variations, and occlusions. We match consistently detected landmarks against the topological map based on the occurrence order in the videos. The proposed approach contains two components: a convolutional neural network (CNN)-based landmark detector and a topological matching algorithm. The proposed detector is capable of reliably and accurately detecting landmarks. The other part is the matching algorithm built on the second order hidden Markov model and it can successfully handle the environmental ambiguity by fusing sematic and connectivity information of landmarks. To evaluate the method, we conduct extensive experiments on the real world dataset collected in two indoor environments, and the results show that our deep neural network-based indoor landmark detector accurately detects all landmarks and is expected to be utilized in similar environments without retraining and that VLSIL can effectively localize indoor landmarks.
Detection of Glacier Calving Margins with Convolutional Neural Networks: A Case Study
Authors: Mohajerani Yara , Wood Michael , Velicogna Isabella , Rignot Eric
Published: January 2019

The continuous and precise mapping of glacier calving fronts is essential for monitoring and understanding rapid glacier changes in Antarctica and Greenland, which have the potential for significant sea level rise within the current century. This effort has been mostly restricted to the slow and painstaking manual digitalization of the calving front positions in thousands of satellite imagery products. Here, we have developed a machine learning toolkit to automatically detect glacier calving front margins in satellite imagery. The toolkit is based on semantic image segmentation using Convolutional Neural Networks (CNN) with a modified U-Net architecture to isolate the calving fronts from satellite images after having been trained with a dataset of images and their corresponding manually-determined calving fronts. As a case study we train our neural network on a varied set of Landsat images with lowered resolutions from Jakobshavn, Sverdrup, and Kangerlussuaq glaciers, Greenland and test the results on images from Helheim glacier, Greenland to evaluate the performance of the approach. The neural network is able to identify the calving front in new images with a mean deviation of 96.3 m from the true fronts, equivalent to 1.97 pixels on average, while the corresponding error for manually-determined fronts on the same resolution images is 92.5 m (1.89 pixels). We find that the trained neural network significantly outperforms common edge detection techniques, and can be used to continuously map out calving-ice fronts with a variety of data products.
Joint Learning of the Center Points and Deep Metrics for Land-Use Classification in Remote Sensing
Authors: Gong Zhiqiang , Zhong Ping , Hu Weidong , Hua Yuming
Published: January 2019

Deep learning methods, especially convolutional neural networks (CNNs), have shown remarkable ability for remote sensing scene classification. However, the traditional training process of standard CNNs only takes the point-wise penalization of the training samples into consideration, which usually makes the learned CNNs sub-optimal especially for remote sensing scenes with large intra-class variance and low inter-class variance. To address this problem, deep metric learning, which incorporates the metric learning into the deep model, is used to maximize the inter-class variance and minimize the intra-class variance for better representation. This work introduces structured metric learning for remote sensing scene representation, a special deep metric learning which can take full advantage of the training batch. However, the deep metrics only consider the pairwise correlation between the training samples, and ignores the classwise correlation from the class view. To take the classwise penalization into consideration, this work defines the center points of the learned features of each class in the training process to represent the class. Through increasing the variance between different center points and decreasing the variance between the learned features from each class and the corresponding center point, the representational ability can be further improved. Therefore, this work develops a novel center-based structured metric learning to take advantage of both the deep metrics and the center points. Finally, joint supervision of the cross-entropy loss and the center-based structured metric learning is developed for the land-use classification in remote sensing. It can joint learn the center points and the deep metrics to take advantage of the point-wise, the pairwise, and the classwise correlation. Experiments are conducted over three real-world remote sensing scene datasets, namely UC Merced Land-Use dataset, Brazilian Coffee Scene dataset, and Google dataset. The classification performance can achieve 97.30%, 91.24%, and 92.04% with the proposed method over the three datasets which are better than other state-of-the-art methods under the same experimental setups. The results demonstrate that the proposed method can improve the representational ability for the remote sensing scenes.
Sensing Properties of Oxidized Nanostructured Silicon Surface on Vaporized Molecules
Authors: Baran Nikola , Gebavi Hrvoje , Mikac Lara , Ristić Davor , Gotić Marijan , Syed Kamran Ali , Ivanda Mile
Published: January 2019

Porous silicon has been intensely studied for the past several decades and its applications were found in photovoltaics, biomedicine, and sensors. An important aspect for sensing devices is their long–term stability. One of the more prominent changes that occur with porous silicon as it is exposed to atmosphere is oxidation. In this work we study the influence of oxidation on the sensing properties of porous silicon. Porous silicon layers were prepared by electrochemical etching and oxidized in a tube furnace. We observed that electrical resistance of oxidized samples rises in response to the increasing ambient concentration of organic vapours and ammonia gas. Furthermore, we note the sensitivity is dependent on the oxygen treatment of the porous layer. This indicates that porous silicon has a potential use in sensing of organic vapours and ammonia gas when covered with an oxide layer.
RiverCore: IoT Device for River Water Level Monitoring over Cellular Communications
Authors: Moreno Carlos , Aquino Raúl , Ibarreche José , Pérez Ismael , Castellanos Esli , Álvarez Elisa , Rentería Raúl , Anguiano Luis , Edwards Arthur , Lepper Paul , Edwards Robert M. , Clark Ben
Published: January 2019

Flooding is one of the most frequent and costly natural disasters affecting mankind. However, implementing Internet of Things (IoT) technology to monitor river behavior may help mitigate or prevent future disasters. This article outlines the hardware development of an IoT system (RiverCore) and defines an application scenario in a specific hydrological region of the state of Colima (Mexico), highlighting the characteristics of data acquisition and data processing used. Both fixed position and moving drifter node systems are described along with web-based data acquisition platform developments integrated with IoT techniques to retrieve data through 3G cellular networks. The developed architecture uses the Message Queuing Telemetry Transport (MQTT) protocol, along with encryption and security mechanisms, to send real-time data packages from fixed nodes to a server that stores retrieved data in a non-relational database. From this, data can be accessed and displayed through different customizable queries and graphical representations, allowing future use in flood analysis and prediction systems. All of these features are presented along with graphical evidence of the deployment of the different devices and of several cellular communication and on-site data acquisition tests.
Hg2+-Promoted Spirolactam Hydrolysis Reaction: A Design Strategy for the Highly Selective Sensing of Hg2+ over other Metal Ions in Aqueous Media
Authors: Bay Mai , Hien Nguyen , Son Subin , Trinh Nguyen , Trung Nguyen , Nam Pham , Kim Jong , Quang Duong
Published: January 2019

A mercury sensor (N-(rhodamine-6G)lactam-ethylenediamine-4-dimethylamino-cinnamaldehyde—RLED) based on the Hg2+-promoted hydrolysis reaction has been designed and developed with a combination of theoretical calculations and experimental investigations. The interaction between RLED and Hg2+ goes through a fast-initial stage with formation of a 1:1 complex, followed by a slow hydrolysis process. The formation of durable intermediate complexes is due to quite a long hydrolysis reaction time. As a result, RLED can selectively detect Hg2+ in the presence of other metal ions, with a detection limit of 0.08 μM for the colorimetric method, and of 0.008 μM with the fluorescent method. In addition, the RLED sensor can work in a solution with a small amount of organic solvent, with a wide pH range from 5 to 10. The time-dependent density functional theory has been used for investigations of the excitation and de-excitation processes in RLED, intermediate complexes, and reaction products, thereby clarifying the changes in the fluorescence intensity before and after the RLED interacts with Hg2+ ions.
Improvement of Kafka Streaming Using Partition and Multi-Threading in Big Data Environment
Authors: Leang Bunrong , Ean Sokchomrern , Ryu Ga-Ae , Yoo Kwan-Hee
Published: January 2019

The large amount of programmable logic controller (PLC) sensing data has rapidly increased in the manufacturing environment. Therefore, a large data store is necessary for Big Data platforms. In this paper, we propose a Hadoop ecosystem for the support of many features in the manufacturing industry. In this ecosystem, Apache Hadoop and HBase are used as Big Data storage and handle large scale data. In addition, Apache Kafka is used as a data streaming pipeline which contains many configurations and properties that are used to make a better-designed environment and a reliable system, such as Kafka offset and partition, which is used for program scaling purposes. Moreover, Apache Spark closely works with Kafka consumers to create a real-time processing and analysis of the data. Meanwhile, data security is applied in the data transmission phase between the Kafka producers and consumers. Public-key cryptography is performed as a security method which contains public and private keys. Additionally, the public-key is located in the Kafka producer, and the private-key is stored in the Kafka consumer. The integration of these above technologies will enhance the performance and accuracy of data storing, processing, and securing in the manufacturing environment.
A Two-Dimensional Wireless and Passive Sensor for Stress Monitoring
Authors: Tan Yisong , Zhu Jianhua , Ren Limin
Published: January 2019

A new two-dimensional wireless and passive stress sensor using the inverse magnetostrictive effect is proposed, designed, analyzed, fabricated, and tested in this work. Three pieces of magnetostrictive material are bonded on the surface of a smart elastomer structure base to form the sensor. Using the external load, an amplitude change in the higher-order harmonic signal of the magnetic material is detected (as a result of the passive variation of the magnetic permeability wirelessly). The finite element method (FEM) is used to accomplish the design and analysis process. The strain-sensitive regions of the tension and torque are distributed at different locations, following the FEM analysis. After the fabrication of a sensor prototype, the mechanical output performance is measured. The effective measurement range is 0–40 N and 0–4 N·M under tension and torque, respectively. Finally, the error of the sensor after calibration and decoupling for Fx is 3.4% and for Tx is 4.2% under a compound test load (35 N and 3.5 N·M). The proposed sensor exhibits the merits of being passive and wireless, and has an ingenious structure. This passive and wireless sensor is useful for the long-term detection of mechanical loading within a moving object, and can even potentially be used for tracing dangerous overloads and for preventing implant failures by monitoring the deformation of implants in the human body.
Defining a Cyber Resilience Investment Strategy in an Industrial Internet of Things Context
Authors: Carías Juan Francisco , Labaka Leire , Sarriegi José María , Hernantes Josune
Published: January 2019

The fourth industrial revolution has brought several risks to factories along with its plethora of benefits. The convergence of new technologies, legacy technologies, information technologies and operational technologies in the same network generates a wide attack surface. At the same time, factories need continuous production to meet their customers’ demand, so any stopped production can have harsh effects on a factory’s economy. This makes cyber resilience a key requirement in factories nowadays. However, it is difficult for managers to define effective cyber resilience strategies, especially considering the difficulty of estimating adequate investment in cyber resilience policies before the company has suffered cyber incidents. In this sense, the purpose of this article is to define and model an effective cyber resilience strategy. To achieve this, the system dynamics methodology was followed in order to get five experts’ opinions on the best strategy to invest in cyber resilience. Interviews were conducted with these experts; their reasoning was put into behavior over time graphs and a system dynamics model was built from these findings. The main conclusion is that a cyber resilience investment strategy should be dynamic, investing in both technical security and personnel training, but at first with an emphasis on technical security and later shifting to have an emphasis on training.