bluuebunny/crossref_metadata_2025 huggingface dataset:
Plasma Metabolomics Identifies Lipid and Amino Acid Markers of Weight Loss in Patients with Upper Gastrointestinal Cancer
Authors: Miller Janice , Alshehri Ahmed , Ramage Michael I. , Stephens Nathan A. , Mullen Alexander B. , Boyd Marie , Ross James A. , Wigmore Stephen J. , Watson David G. , Skipworth Richard J.E.
Published: October 2019

Cachexia is a multifactorial wasting syndrome associated with high morbidity and mortality in patients with cancer. Diagnosis can be difficult and, in the clinical situation, usually relies upon reported weight loss. The ‘omics’ technologies allow us the opportunity to study the end points of many biological processes. Among these, blood-based metabolomics is a promising method to investigate the pathophysiology of human cancer cachexia and identify candidate biomarkers. In this study, we performed liquid chromatography mass spectrometry (LC/MS)-based metabolomics to investigate the metabolic profile of cancer-associated weight loss. Non-selected patients undergoing surgery with curative intent for upper gastrointestinal cancer were recruited. Fasting plasma samples were taken at induction of anaesthesia. LC/MS analysis showed that 6 metabolites were highly discriminative of weight loss. Specifically, a combination profile of LysoPC 18.2, L-Proline, Hexadecanoic acid, Octadecanoic acid, Phenylalanine and LysoPC 16:1 showed close correlation for eight weight-losing samples (≥5% weight loss) and nine weight-stable samples (<5%weight loss) between predicted and actual weight change (r = 0.976, p = 0.0014). Overall, 40 metabolites were associated with ≥5% weight loss. This study provides biological validation of the consensus definition of cancer cachexia (Fearon et al.) and provides feasible candidate markers for further investigation in early diagnosis and the assessment of therapeutic intervention.
Targeting Autophagy for Cancer Treatment and Tumor Chemosensitization
Authors: Pérez-Hernández Marta , Arias Alain , Martínez-García David , Pérez-Tomás Ricardo , Quesada Roberto , Soto-Cerrato Vanessa
Published: October 2019

Autophagy is a tightly regulated catabolic process that facilitates nutrient recycling from damaged organelles and other cellular components through lysosomal degradation. Deregulation of this process has been associated with the development of several pathophysiological processes, such as cancer and neurodegenerative diseases. In cancer, autophagy has opposing roles, being either cytoprotective or cytotoxic. Thus, deciphering the role of autophagy in each tumor context is crucial. Moreover, autophagy has been shown to contribute to chemoresistance in some patients. In this regard, autophagy modulation has recently emerged as a promising therapeutic strategy for the treatment and chemosensitization of tumors, and has already demonstrated positive clinical results in patients. In this review, the dual role of autophagy during carcinogenesis is discussed and current therapeutic strategies aimed at targeting autophagy for the treatment of cancer, both under preclinical and clinical development, are presented. The use of autophagy modulators in combination therapies, in order to overcome drug resistance during cancer treatment, is also discussed as well as the potential challenges and limitations for the use of these novel therapeutic strategies in the clinic.
Mutational Landscape of the BAP1 Locus Reveals an Intrinsic Control to Regulate the miRNA Network and the Binding of Protein Complexes in Uveal Melanoma
Authors: Sharma Amit , Biswas Arijit , Liu Hongde , Sen Sagnik , Paruchuri Anoosha , Katsonis Panagiotis , Lichtarge Olivier , Chand Dakal Tikam , Maulik Ujjwal , Gromiha M. Michael , Bandyopadhyay Sanghamitra , Ludwig Michael , Holz Frank G. , Loeffler Karin U. , Herwig-Carl Martina C.
Published: October 2019

The BAP1 (BRCA1-associated protein 1) gene is associated with a variety of human cancers. With its gene product being a nuclear ubiquitin carboxy-terminal hydrolase with deubiquitinase activity, BAP1 acts as a tumor suppressor gene with potential pleiotropic effects in multiple tumor types. Herein, we focused specifically on uveal melanoma (UM) in which BAP1 mutations are associated with a metastasizing phenotype and decreased survival rates. We identified the ubiquitin carboxyl hydrolase (UCH) domain as a major hotspot region for the pathogenic mutations with a high evolutionary action (EA) score. This also includes the mutations at conserved catalytic sites and the ones overlapping with the phosphorylation residues. Computational protein interaction studies revealed that distant BAP1-associated protein complexes (FOXK2, ASXL1, BARD1, BRCA1) could be directly impacted by this mutation paradigm. We also described the conformational transition related to BAP1-BRCA-BARD1 complex, which may pose critical implications for mutations, especially at the docking interfaces of these three proteins. The mutations affect - independent of being somatic or germline - the binding affinity of miRNAs embedded within the BAP1 locus, thereby altering the unique regulatory network. Apart from UM, BAP1 gene expression and survival associations were found to be predictive for the prognosis in several (n = 29) other cancer types. Herein, we suggest that although BAP1 is conceptually a driver gene in UM, it might contribute through its interaction partners and its regulatory miRNA network to various aspects of cancer. Taken together, these findings will pave the way to evaluate BAP1 in a variety of other human cancers with a shared mutational spectrum.
Overcoming Stability Problems in Microwave-Assisted Heterogeneous Catalytic Processes Affected by Catalyst Coking
Authors: Julian Ignacio , Pedersen Christoffer M. , Achkasov Kostiantyn , Hueso Jose L. , Hellstern Henrik L. , Silva Hugo , Mallada Reyes , Davis Zachary J. , Santamaria Jesus
Published: October 2019

Microwave-assisted heterogeneous catalysis (MHC) is gaining attention due to its exciting prospects related to selective catalyst heating, enhanced energy-efficiency, and partial inhibition of detrimental side gas-phase reactions. The induced temperature difference between the catalyst and the comparatively colder surrounding reactive atmosphere is pointed as the main factor of the process selectivity enhancement towards the products of interest in a number of hydrocarbon conversion processes. However, MHC is traditionally restricted to catalytic reactions in the absence of catalyst coking. As excellent MW-susceptors, carbon deposits represent an enormous drawback of the MHC technology, being main responsible of long-term process malfunctions. This work addresses the potentials and limitations of MHC for such processes affected by coking (MHCC). It also intends to evaluate the use of different catalyst and reactor configurations to overcome heating stability problems derived from the undesired coke deposits. The concept of long-term MHCC operation has been experimentally tested/applied to for the methane non-oxidative coupling reaction at 700 °C on Mo/ZSM-5@SiC structured catalysts. Preliminary process scalability tests suggest that a 6-fold power input increases the processing of methane flow by 150 times under the same controlled temperature and spatial velocity conditions. This finding paves the way for the implementation of high-capacity MHCC processes at up-scaled facilities.
Cofactor F420-Dependent Enzymes: An Under-Explored Resource for Asymmetric Redox Biocatalysis
Authors: Shah Mihir V. , Antoney James , Kang Suk Woo , Warden Andrew C. , Hartley Carol J. , Nazem-Bokaee Hadi , Jackson Colin J. , Scott Colin
Published: October 2019

The asymmetric reduction of enoates, imines and ketones are among the most important reactions in biocatalysis. These reactions are routinely conducted using enzymes that use nicotinamide cofactors as reductants. The deazaflavin cofactor F420 also has electrochemical properties that make it suitable as an alternative to nicotinamide cofactors for use in asymmetric reduction reactions. However, cofactor F420-dependent enzymes remain under-explored as a resource for biocatalysis. This review considers the cofactor F420-dependent enzyme families with the greatest potential for the discovery of new biocatalysts: the flavin/deazaflavin-dependent oxidoreductases (FDORs) and the luciferase-like hydride transferases (LLHTs). The characterized F420-dependent reductions that have the potential for adaptation for biocatalysis are discussed, and the enzymes best suited for use in the reduction of oxidized cofactor F420 to allow cofactor recycling in situ are considered. Further discussed are the recent advances in the production of cofactor F420 and its functional analog FO-5′-phosphate, which remains an impediment to the adoption of this family of enzymes for industrial biocatalytic processes. Finally, the prospects for the use of this cofactor and dependent enzymes as a resource for industrial biocatalysis are discussed.
The Steric Effect in Green Benzylation of Arenes with Benzyl Alcohol Catalyzed by Hierarchical H-beta Zeolite
Authors: Liu Xinyu , Lu Meihuan , Wang Xuan , Lu Juyou , Yang Jianxin
Published: October 2019

For decades the steric effect was still ambiguously understood in catalytic benzylation reactions of arenes with benzyl alcohol, which limited the green synthesis of phenylmethane derivates in industrial scale. This research applies a series of silica–alumina beta zeolites to systematically evaluate factors like catalyst porosity, reactants molecule size, and reaction temperature on catalytic benzylation. First, a suitable hierarchical beta zeolite catalyst was screened out by X-ray powder diffraction, N2 adsorption−desorption, and probe benzylation with p-xylene. In the following substrates expanding study, for a typical benzylation of benzene, it showed extraordinary performance among literature reported ones that the conversion was 98% while selectivity was 90% at 353 K only after 10 min. The steric effect of aromatics with different molecular sizes on benzylation was observed. The reaction activities of four different aromatics followed the order: benzene > toluene > p-xylene > mesitylene. Combined with macroscopic kinetic analysis, this comprehensive study points out for the first time that the nature of this steric effect was dominated by the relative adsorption efficiency of different guest aromatic molecules on the host zeolite surface.
Eco-Toxicological and Kinetic Evaluation of TiO2 and ZnO Nanophotocatalysts in Degradation of Organic Dye
Authors: Khezrianjoo Sajjad , Lee Jechan , Kim Ki-Hyun , Kumar Vanish
Published: October 2019

In this study, the photocatalytic degradation of azo dye “Food Black 1” (FB1) was investigated using TiO2 and ZnO nanoparticles under ultraviolet (UV) light. The performances of the two photocatalysts were evaluated in terms of key parameters (e.g., decolorization, dearomatization, mineralization, and detoxification of dye) in relation to variables including pre-adsorption period, pH, and temperature. Under acidic conditions (pH 5), the ZnO catalyst underwent photocorrosion to increase the concentration of zinc ions in the system, thereby increasing the toxic properties of the treated effluent. In contrast, TiO2 efficiently catalyzed the degradation of the dye at pH 5 following the Langmuir–Hinshelwood (L–H) kinetic model. The overall results of this study indicate that the decolorization rate of TiO2 on the target dye was far superior to ZnO (i.e., by 1.5 times) at optimum catalyst loading under UV light.
Intrinsically Disordered SRC-3/AIB1 Protein Undergoes Homeostatic Nuclear Extrusion by Nuclear Budding While Ectopic Expression Induces Nucleophagy
Authors: Cabrita Miguel A. , Renart L. Isabel , Lau Rosanna , Pratt M. A. Christine
Published: October 2019

SRC-3/AIB1 (Amplified in Breast Cancer-1) is a nuclear receptor coactivator for the estrogen receptor in breast cancer cells. It is also an intrinsically disordered protein when not engaged with transcriptional binding partners and degraded upon transcriptional coactivation. Given the amplified expression of SRC-3 in breast cancers, the objective of this study was to determine how increasing SRC-3 protein levels are regulated in MCF-7 breast cancer cells. We found that endogenous SRC-3 was expelled from the nucleus in vesicle-like spheres under normal growth conditions suggesting that this form of nuclear exclusion of SRC-3 is a homeostatic mechanism for regulating nuclear SRC-3 protein. Only SRC-3 not associated with CREB-binding protein (CBP) was extruded from the nucleus. We found that overexpression in MCF-7 cells results in aneuploid senescence and cell death with frequent formation of nuclear aggregates which were consistently juxtaposed to perinuclear microtubules. Transfected SRC-3 was SUMOylated and caused redistribution of nuclear promyelocytic leukemia (PML) bodies and perturbation of the nuclear membrane lamin B1, hallmarks of nucleophagy. Increased SRC-3 protein-induced autophagy and resulted in SUMO-1 localization to the nuclear membrane and formation of protrusions variously containing SRC-3 and chromatin. Aspects of SRC-3 overexpression and toxicity were recapitulated following treatment with clinically relevant agents that stabilize SRC-3 in breast cancer cells. We conclude that amplified SRC-3 levels have major impacts on nuclear protein quality control pathways and may mark cancer cells for sensitivity to protein stabilizing therapeutics.
Enhancer Dysfunction in 3D Genome and Disease
Authors: Xia Ji-Han , Wei Gong-Hong
Published: October 2019

Spatiotemporal patterns of gene expression depend on enhancer elements and other factors during individual development and disease progression. The rapid progress of high-throughput techniques has led to well-defined enhancer chromatin properties. Various genome-wide methods have revealed a large number of enhancers and the discovery of three-dimensional (3D) genome architecture showing the distant interacting mechanisms of enhancers that loop to target gene promoters. Whole genome sequencing projects directed at cancer have led to the discovery of substantial enhancer dysfunction in misregulating gene expression and in tumor initiation and progression. Results from genome-wide association studies (GWAS) combined with functional genomics analyses have elucidated the functional impacts of many cancer risk-associated variants that are enriched within the enhancer regions of chromatin. Risk variants dysregulate the expression of enhancer variant-associated genes via 3D genomic interactions. Moreover, these enhancer variants often alter the chromatin binding affinity for cancer-relevant transcription factors, which in turn leads to aberrant expression of the genes associated with cancer susceptibility. In this review, we investigate the extent to which these genetic regulatory circuits affect cancer predisposition and how the recent development of genome-editing methods have enabled the determination of the impacts of genomic variation and alteration on cancer phenotype, which will eventually lead to better management plans and treatment responses to human cancer in the clinic.
Transcriptional Regulator TonEBP Mediates Oxidative Damages in Ischemic Kidney Injury
Authors: Yoo Eun Jin , Lim Sun Woo , Kang Hyun Je , Park Hyun , Yoon Sora , Nam Dougu , Sanada Satoru , Kwon Mi Jin , Lee-Kwon Whaseon , Choi Soo Youn , Kwon Hyug Moo
Published: October 2019

TonEBP (tonicity-responsive enhancer binding protein) is a transcriptional regulator whose expression is elevated in response to various forms of stress including hyperglycemia, inflammation, and hypoxia. Here we investigated the role of TonEBP in acute kidney injury (AKI) using a line of TonEBP haplo-deficient mice subjected to bilateral renal ischemia followed by reperfusion (I/R). In the TonEBP haplo-deficient animals, induction of TonEBP, oxidative stress, inflammation, cell death, and functional injury in the kidney in response to I/R were all reduced. Analyses of renal transcriptome revealed that genes in several cellular pathways including peroxisome and mitochondrial inner membrane were suppressed in response to I/R, and the suppression was relieved in the TonEBP deficiency. Production of reactive oxygen species (ROS) and the cellular injury was reproduced in a renal epithelial cell line in response to hypoxia, ATP depletion, or hydrogen peroxide. The knockdown of TonEBP reduced ROS production and cellular injury in correlation with increased expression of the suppressed genes. The cellular injury was also blocked by inhibitors of necrosis. These results demonstrate that ischemic insult suppresses many genes involved in cellular metabolism leading to local oxidative stress by way of TonEBP induction. Thus, TonEBP is a promising target to prevent AKI.
A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking
Authors: Kadioglu Onat , Efferth Thomas
Published: October 2019

P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of various established chemotherapy drugs in many clinically resistant and refractory tumors. This leads to insufficient therapeutic targeting of tumor populations, representing a major drawback of cancer chemotherapy. Therefore, P-gp is a target for pharmacological inhibitors to overcome MDR. In the present study, we utilized machine learning strategies to establish a model for P-gp modulators to predict whether a given compound would behave as substrate or inhibitor of P-gp. Random forest feature selection algorithm-based leave-one-out random sampling was used. Testing the model with an external validation set revealed high performance scores. A P-gp modulator list of compounds from the ChEMBL database was used to test the performance, and predictions from both substrate and inhibitor classes were selected for the last step of validation with molecular docking. Predicted substrates revealed similar docking poses than that of doxorubicin, and predicted inhibitors revealed similar docking poses than that of the known P-gp inhibitor elacridar, implying the validity of the predictions. We conclude that the machine-learning approach introduced in this investigation may serve as a tool for the rapid detection of P-gp substrates and inhibitors in large chemical libraries.
The Charcot–Marie Tooth Disease Mutation R94Q in MFN2 Decreases ATP Production but Increases Mitochondrial Respiration under Conditions of Mild Oxidative Stress
Authors: Wolf Christina , Zimmermann Rahel , Thaher Osamah , Bueno Diones , Wüllner Verena , Schäfer Michael K.E. , Albrecht Philipp , Methner Axel
Published: October 2019

Charcot–Marie tooth disease is a hereditary polyneuropathy caused by mutations in Mitofusin-2 (MFN2), a GTPase in the outer mitochondrial membrane involved in the regulation of mitochondrial fusion and bioenergetics. Autosomal-dominant inheritance of a R94Q mutation in MFN2 causes the axonal subtype 2A2A which is characterized by early onset and progressive atrophy of distal muscles caused by motoneuronal degeneration. Here, we studied mitochondrial shape, respiration, cytosolic, and mitochondrial ATP content as well as mitochondrial quality control in MFN2-deficient fibroblasts stably expressing wildtype or R94Q MFN2. Under normal culture conditions, R94Q cells had slightly more fragmented mitochondria but a similar mitochondrial oxygen consumption, membrane potential, and ATP production as wildtype cells. However, when inducing mild oxidative stress 24 h before analysis using 100 µM hydrogen peroxide, R94Q cells exhibited significantly increased respiration but decreased mitochondrial ATP production. This was accompanied by increased glucose uptake and an up-regulation of hexokinase 1 and pyruvate kinase M2, suggesting increased pyruvate shuttling into mitochondria. Interestingly, these changes coincided with decreased levels of PINK1/Parkin-mediated mitophagy in R94Q cells. We conclude that mitochondria harboring the disease-causing R94Q mutation in MFN2 are more susceptible to oxidative stress, which causes uncoupling of respiration and ATP production possibly by a less efficient mitochondrial quality control.
Helicobacter pylori Induces IL-33 Production and Recruits ST-2 to Lipid Rafts to Exacerbate Inflammation
Authors: Kuo Chia-Jung , Chen Chun-Ya , Lo Horng-Ren , Feng Chun-Lung , Wu Hui-Yu , Huang Mei-Zi , Liao Tung-Nan , Chen Yu-An , Lai Chih-Ho
Published: October 2019

Helicobacter pylori colonizes human gastric epithelial cells and contributes to the development of several gastrointestinal disorders. Interleukin (IL)-33 is involved in various immune responses, with reported proinflammatory and anti-inflammatory effects, which may be associated with colitis and colitis-associated cancer. IL-33 induces the inflammatory cascade through its receptor, suppression of tumorigenicity-2 (ST-2). Binding of IL-33 to membrane-bound ST-2 (mST-2) recruits the IL-1 receptor accessory protein (IL-1RAcP) and activates intracellular signaling pathways. However, whether IL-33/ST-2 is triggered by H. pylori infection and whether this interaction occurs in lipid rafts remain unclear. Our study showed that both IL-33 and ST-2 expression levels were significantly elevated in H. pylori-infected cells. Confocal microscopy showed that ST-2 mobilized into the membrane lipid rafts during infection. Depletion of membrane cholesterol dampened H. pylori-induced IL-33 and IL-8 production. Furthermore, in vivo studies revealed IL-33/ST-2 upregulation, and severe leukocyte infiltration was observed in gastric tissues infected with H. pylori. Together, these results demonstrate that ST-2 recruitment into the lipid rafts serves as a platform for IL-33-dependent H. pylori infection, which aggravates inflammation in the stomach.
Central Asia’s Changing Climate: How Temperature and Precipitation Have Changed across Time, Space, and Altitude
Authors: Haag Isabell , Jones Philip D. , Samimi Cyrus
Published: October 2019

Changes in climate can be favorable as well as detrimental for natural and anthropogenic systems. Temperatures in Central Asia have risen significantly within the last decades whereas mean precipitation remains almost unchanged. However, climatic trends can vary greatly between different subregions, across altitudinal levels, and within seasons. Investigating in the seasonally and spatially differentiated trend characteristics amplifies the knowledge of regional climate change and fosters the understanding of potential impacts on social, ecological, and natural systems. Considering the known limitations of available climate data in this region, this study combines both high-resolution and long-term records to achieve the best possible results. Temperature and precipitation data were analyzed using Climatic Research Unit (CRU) TS 4.01 and NASA’s Tropical Rainfall Measuring Mission (TRMM) 3B43. To study long-term trends and low-frequency variations, we performed a linear trend analysis and compiled anomaly time series and regional grid-based trend maps. The results show a strong increase in temperature, almost uniform across the topographically complex study site, with particular maxima in winter and spring. Precipitation depicts minor positive trends, except for spring when precipitation is decreasing. Expected differences in the development of temperature and precipitation between mountain areas and plains could not be detected.
Electrochemical Corrosion of Nano-Structured Magnetron-Sputtered Coatings
Authors: Calderon Sebastian , Alves Cristiana F. Almeida , Manninen Noora K. , Cavaleiro Albano , Carvalho Sandra
Published: October 2019

Magnetron sputtering has been employed for several decades to produce protective and multi-functional coatings, thanks to its versatility and ability to achieve homogeneous layers. Moreover, it is suitable for depositing coatings with very high melting points and that are thermodynamical unstable, which is difficult to accomplish by other techniques. Among these types of coating, transition metal (Me) carbides/nitrides (MeC/N) and amorphous carbon (a-C) films are particularly interesting because of the possibility of tailoring their properties by selecting the correct amount of phase fractions, varying from pure MeN, MeC, MeCN to pure a-C phases. This complex phase mixture can be even enhanced by adding a fourth element such Ag, Pt, W, Ti, Si, etc., allowing the production of materials with a large diversity of properties. The mixture of phases, resulting from the immiscibility of phases, allows increasing the number of applications, since each phase can contribute with a specific property such as hardness, self-lubrication, antibacterial ability, to create a multifunctional material. However, the existence of different phases, their fractions variation, the type of transition metal and/or alloying element, can drastically alter the global electrochemical behaviour of these films, with a strong impact on their stability. Consequently, it is imperative to understand how the main features intrinsic to the production process, as well as induced by Me and/or the alloying element, influence the characteristics and properties of the coatings and how these affect their electrochemical behaviour. Therefore, this review will focus on the fundamental aspects of the electrochemical behaviour of magnetron-sputtered films as well as of the substrate/film assembly. Special emphasis will be given to the influence of simulated body fluids on the electrochemical behaviour of coatings.
A Note for Probabilistic Model of Polymer Crystallization in Temperature Gradients
Authors: Ruan Chunlei , Lv Yunlong
Published: October 2019

A polymer crystallization kinetics model is the most important way to characterize the crystallization rate of polymers. Because polymers are poor heat conductors, the cooling of thick-walled shapes results in temperature gradients. Piorkowska (Piorkowska, E. J. Appl. Polym. Sci., 2002, 86: 1351–1362.) derived the probabilistic analytical model of polymer crystallization in temperature gradients based on the Avrami equation. However, there are some misunderstandings when using this model. Here, isotactic polypropylene (iPP) is chosen as a model polymer and its crystallization is studied in a temperature gradient field. Based on the results of the Monte Carlo method, the probabilistic model methodology is discussed. The results show that when the product has a large temperature gradient and a large temperature difference, the probabilistic model cannot be used directly; instead, it is necessary to use the average probabilistic model. This means that the sample should be divided into several smaller parts and the probabilistic model used separately for each small part. The values are then averaged to obtain the mean conversion degree of the melt into spherulites for the whole product. The effects of the division number are also discussed. The goal of the present paper is to better understand the polymer crystallization kinetics model in terms of temperature gradients.
Localized Conical Edge Modes of Higher Orders in Photonic Liquid Crystals
Authors: Belyakov Vladimir A. , Semenov Sergei V.
Published: October 2019

Most studies of the localized edge (EM) and defect (DM) modes in cholesteric liquid crystals (CLC) are related to the localized modes in a collinear geometry, i.e., for the case of light propagation along the spiral axis. It is due to the fact that all photonic effects in CLC are most pronounced just for a collinear geometry, and also partially due to the fact that a simple exact analytic solution of the Maxwell equations is known for a collinear geometry, whereas for a non-collinear geometry, there is no exact analytic solution of the Maxwell equations and a theoretical description of the experimental data becomes more complicated. It is why in papers related to the localized modes in CLC for a non-collinear geometry and observing phenomena similar to the case of a collinear geometry, their interpretation is not so clear. Recently, an analytical theory of the conical modes (CEM) related to a first order of light diffraction was developed in the framework of the two-wave dynamic diffraction theory approximation ensuring the results accuracy of order of δ, the CLC dielectric anisotropy. The corresponding experimental results are reasonably well described by this theory, however, some numerical problems related to the CEM polarization properties remain. In the present paper, an analytical theory of a second order diffraction CEM is presented with results that are qualitatively similar to the results for a first order diffraction order CEM and have the accuracy of order of δ2, i.e., practically exact. In particular, second order diffraction CEM polarization properties are related to the linear σ and π polarizations. The known experimental results on the CEM are discussed and optimal conditions for the second order diffraction CEM observations are formulated.
Internalization of Phospholipid-Coated Gold Nanoparticles
Authors: Shearer Lindsay J. , Petersen Nils O.
Published: October 2019

Gold nanoparticles are used in health-related research; however, their effectiveness appears to depend on how well they are internalized and where they are destined to travel. Internalization in cells is efficient if the gold nanoparticles are biocompatible, where one possible pathway of cell entry and processing is clathrin-mediated endocytosis. In this work we studied the co-localization of phospholipid-coated gold nanoparticles (PCAuNPs) with markers of the endocytic pathway (Rab and LAMP-1 proteins) in C2C12 and A549 cells and found that the internalization was consistent with clathrin-mediated endocytosis and was cell type dependent. We further found that the time evolution of uptake and disposal of these PCAuNPs was similar for both cell types, but aggregation was more significant in A549 cells. Our results support the use of these PCAuNPs as models for potential drug delivery platforms.
Fast, Asymptotically Efficient, Recursive Estimation in a Riemannian Manifold
Authors: Zhou Jialun , Said Salem
Published: October 2019

Stochastic optimisation in Riemannian manifolds, especially the Riemannian stochastic gradient method, has attracted much recent attention. The present work applies stochastic optimisation to the task of recursive estimation of a statistical parameter which belongs to a Riemannian manifold. Roughly, this task amounts to stochastic minimisation of a statistical divergence function. The following problem is considered: how to obtain fast, asymptotically efficient, recursive estimates, using a Riemannian stochastic optimisation algorithm with decreasing step sizes. In solving this problem, several original results are introduced. First, without any convexity assumptions on the divergence function, we proved that, with an adequate choice of step sizes, the algorithm computes recursive estimates which achieve a fast non-asymptotic rate of convergence. Second, the asymptotic normality of these recursive estimates is proved by employing a novel linearisation technique. Third, it is proved that, when the Fisher information metric is used to guide the algorithm, these recursive estimates achieve an optimal asymptotic rate of convergence, in the sense that they become asymptotically efficient. These results, while relatively familiar in the Euclidean context, are here formulated and proved for the first time in the Riemannian context. In addition, they are illustrated with a numerical application to the recursive estimation of elliptically contoured distributions.
Teaching Ordinal Patterns to a Computer: Efficient Encoding Algorithms Based on the Lehmer Code
Authors: Berger Sebastian , Kravtsiv Andrii , Schneider Gerhard , Jordan Denis
Published: October 2019

Ordinal patterns are the common basis of various techniques used in the study of dynamical systems and nonlinear time series analysis. The present article focusses on the computational problem of turning time series into sequences of ordinal patterns. In a first step, a numerical encoding scheme for ordinal patterns is proposed. Utilising the classical Lehmer code, it enumerates ordinal patterns by consecutive non-negative integers, starting from zero. This compact representation considerably simplifies working with ordinal patterns in the digital domain. Subsequently, three algorithms for the efficient extraction of ordinal patterns from time series are discussed, including previously published approaches that can be adapted to the Lehmer code. The respective strengths and weaknesses of those algorithms are discussed, and further substantiated by benchmark results. One of the algorithms stands out in terms of scalability: its run-time increases linearly with both the pattern order and the sequence length, while its memory footprint is practically negligible. These properties enable the study of high-dimensional pattern spaces at low computational cost. In summary, the tools described herein may improve the efficiency of virtually any ordinal pattern-based analysis method, among them quantitative measures like permutation entropy and symbolic transfer entropy, but also techniques like forbidden pattern identification. Moreover, the concepts presented may allow for putting ideas into practice that up to now had been hindered by computational burden. To enable smooth evaluation, a function library written in the C programming language, as well as language bindings and native implementations for various numerical computation environments are provided in the supplements.
An Effective Multiclass Twin Hypersphere Support Vector Machine and Its Practical Engineering Applications
Authors: Ai Qing , Wang Anna , Zhang Aihua , Wang Wenhui , Wang Yang
Published: October 2019

Twin-KSVC (Twin Support Vector Classification for K class) is a novel and efficient multiclass twin support vector machine. However, Twin-KSVC has the following disadvantages. (1) Each pair of binary sub-classifiers has to calculate inverse matrices. (2) For nonlinear problems, a pair of additional primal problems needs to be constructed in each pair of binary sub-classifiers. For these disadvantages, a new multi-class twin hypersphere support vector machine, named Twin Hypersphere-KSVC, is proposed in this paper. Twin Hypersphere-KSVC also evaluates each sample into 1-vs-1-vs-rest structure, as in Twin-KSVC. However, our Twin Hypersphere-KSVC does not seek two nonparallel hyperplanes in each pair of binary sub-classifiers as in Twin-KSVC, but a pair of hyperspheres. Compared with Twin-KSVC, Twin Hypersphere-KSVC avoids computing inverse matrices, and for nonlinear problems, can apply the kernel trick to linear case directly. A large number of comparisons of Twin Hypersphere-KSVC with Twin-KSVC on a set of benchmark datasets from the UCI repository and several real engineering applications, show that the proposed algorithm has higher training speed and better generalization performance.
A Deep Learning Method for 3D Object Classification Using the Wave Kernel Signature and A Center Point of the 3D-Triangle Mesh
Authors: Hoang Long , Lee Suk-Hwan , Kwon Oh-Heum , Kwon Ki-Ryong
Published: October 2019

Computer vision recently has many applications such as smart cars, robot navigation, and computer-aided manufacturing. Object classification, in particular 3D classification, is a major part of computer vision. In this paper, we propose a novel method, wave kernel signature (WKS) and a center point (CP) method, which extracts color and distance features from a 3D model to tackle 3D object classification. The motivation of this idea is from the nature of human vision, which we tend to classify an object based on its color and size. Firstly, we find a center point of the mesh to define distance feature. Secondly, we calculate eigenvalues from the 3D mesh, and WKS values, respectively, to capture color feature. These features will be an input of a 2D convolution neural network (CNN) architecture. We use two large-scale 3D model datasets: ModelNet10 and ModelNet40 to evaluate the proposed method. Our experimental results show more accuracy and efficiency than other methods. The proposed method could apply for actual-world problems like autonomous driving and augmented/virtual reality.
A Semi-Floating Gate Memory Based on SOI Substrate by TCAD Simulation
Authors: Li Han , Wang Chen , Chen Lin , Zhu Hao , Sun Qingqing
Published: October 2019

Over the past decade, the dimensional scaling of semiconductor electronic devices has been facing fundamental and physical challenges, and there is currently an urgent need to increase the ability of dynamic random-access memory (DRAM). A semi-floating gate (SFG) transistor has been proposed as a capacitor-less memory with faster speed and higher density as compared with the conventional one-transistor one-capacitor (1T1C) DRAM technology. The integration of SFG-based memory on the silicon-on-insulator (SOI) substrate has been demonstrated in this work by using the Sentaurus Technology Computer-Aided Design (TCAD) simulation. An enhancement in retention characteristics, anti-disturbance ability, and fast writing capability, have been illustrated. The device exhibits a low operation voltage, a large threshold voltage window of ~3 V, and an ultra-fast writing of 4 ns. In addition, the SOI-based memory has shown a much-improved anti-irradiation capability compared to the devices based on bulk silicon, which makes it much more attractive in broader applications.
A Study on the Use of Water as a Medium for the Thermal Inactivation of Endogenous Lipase in Oil of Palm Fruit
Authors: Shehu Umar Etsu , Mokhtar Mohd Noriznan , Mohd Nor Mohd Zuhair , Baharuddin Azhari Samsu , Nawi Nazmi Mat
Published: October 2019

The heat treatment of oil palm fruit using saturated steam (413 K) in conventional oil palm processing has been reported to be ineffective in terms of heat distribution and penetration into the fruit bunch inner layer; hence, there is a desire to explore other alternative processes. In this study, oil palm fruit was treated in water at temperatures between 308 K and 343 K. The effects of the treatment on the in vivo activity of the lipase, the abscission layer of the fruit, and the integrity of the oil globule membrane were observed. The results showed in vivo residual lipase activity to be almost completely inactivated after 40 min of heat treatment at 343 K. The micrograph of the fruit mesocarp exhibited disintegration of the oil globule membrane as well as dissolution of the pectin layer architecture of the abscission zone after the treatment at this temperature. A dynamic mathematical modeling of heat transfer was employed, and coupled with reaction kinetics of lipase inactivation. The inactivation kinetics was found to be a non-elementary reaction, and the initial rate constant, k0dec, and activation energy, Edec, of the reaction were estimated to be 0.035 U−0.85/kg-mes−0.85⋅min and 153,052 kJ/kmol, respectively. The findings suggested the viability of water as a medium of heat treatment instead of the conventional steam treatment in oil palm processing.
Radiation Heat Transfer in a Complex Geometry Containing Anisotropically-Scattering Mie Particles
Authors: Ettaleb Ali , Abbassi Mohamed , Farhat Habib , Guedri Kamel , Omri Ahmed , Borjini Mohamed , Goodarzi Marjan , Sarafraz M.
Published: October 2019

This study aims to numerically investigate the radiation heat transfer in a complex, 3-D biomass pyrolysis reactor which is consisted of two pyrolysis chambers and a heat recuperator. The medium assumes to be gray, absorbs, emits, and Mie-anisotropically scatters the radiation energy. The finite volume method (FVM) is applied to solve the radiation transfer equation (RTE) using the step scheme. To treat the complex geometry, the blocked-off-region procedure is employed. Mie equations (ME) are applied to evaluate the scattering phase function and analyze the angular distribution of the anisotropically scattered radiation by particles. In this study, three different states are considered to test the anisotropic scattering impacts on the temperature and radiation heat flux distribution. These states are as: (i) Isotropic scattering, (ii) forward and backward scattering and (iii) scattering with solid particles of different coals and fly ash. The outcomes demonstrate that the radiation heat flux enhances by an increment of the albedo and absorption coefficients for the coals and fly ash, unlike the isotropic case and the forward and backward scattering functions. Moreover, the particle size parameter does not have an important influence on the radiation heat flux, when the medium is thin optical. Its effect is more noticeable for higher extinction coefficients.
An Investigation into Sub-Critical Choke Flow Performance in High Rate Gas Condensate Wells
Authors: Nasriani Hamid Reza , Khan Khalid , Graham Tony , Ndlovu Shephard , Nasriani Mehrdad , Mai Jianqiang , Rafiee Mohammad Rafie
Published: October 2019

There have been some correlations in the literature to predict the gas and liquid flow rate through wellhead chokes under subcritical flow conditions. The majority of these empirical correlations have been developed based on limited production data sets that were collected from a small number of fields. Therefore, these correlations are valid within the parameter variation ranges of those fields. If such correlations are used elsewhere for the prediction of the subcritical choke flow performance of the other fields, significant errors will occur. Additionally, there are only a few empirical correlations for sub-critical choke flow performance in high rate gas condensate wells. These led the authors to develop a new empirical correlation based on a wider production data set from different gas condensate fields in the world; 234 production data points were collected from a large number of production wells in twenty different gas condensate fields with diverse reservoir conditions and different production histories. A non-linear regression analysis method was applied to their production. The new correlation was validated with a new set of data points from some other production wells to confirm the accuracy of the established correlation. The results show that the new correlation had minimal errors and predicted the gas flow rate more accurately than the other three existing models over a wider range of parameter variation ranges.
Voltage Balance Switching Scheme for Series-Connected SiC MOSFET LLC Resonant Converter
Authors: Cha Hwa-Rang , Kim Rae-Young
Published: October 2019

To achieve high efficiency and power density, silicon carbide (SiC)-based Inductor-Inductor-Capacitor (LLC) resonant converters are applied to the DC/DC converter stage of a solid-state transformer (SST). However, because the input voltage of an SST is higher than the rated voltage of a commercial SiC device, it is essential to connect SiC devices in series. This structure is advantageous in terms of voltage rating, but a parasitic capacitance tolerance between series-connected SiC devices causes voltage imbalance. Such imbalance greatly reduces system stability as it causes overvoltage breakdown of SiC device. Therefore, this paper proposes a switching scheme to solve the voltage imbalance between SiC metal-oxide-semiconductor field-effect transistors (MOSFETs). The proposed scheme sequentially turns off series-connected SiC MOSFETs to compensate for the turn-off delays caused by parasitic capacitor tolerances. In addition, dead-time selection methods to achieve voltage balance and zero voltage switching simultaneously are provided in detail. To verify the effectiveness of the proposed scheme, experiments were conducted on a 2 kW series-connected SiC MOSFET LLC resonant converter prototype.
Control Strategy of Three-Phase Inverter with Isolation Transformer
Authors: Chen Jie , Li Jun , Qiu Ruichang , Liu Zhigang
Published: October 2019

In order to improve the control performance of a train auxiliary inverter and satisfy the requirements of power quality, harmonics, and unbalanced factor, this paper proposed a design method of a double closed-loop control system based on a complex state variable structure. The method simplifies the design process and takes full account of the effects of coupling and discretization. In the current closed-loop process, this paper analyzed the limitations of the proportional integral (PI) controller and simplified to P controller. In the voltage closed-loop, the paper employed the PI controller plus the resonant controller, designed the parameters of the PI controller. and analyzed the optimal discretization method of the resonant controller under dq axis coupling. Finally, experiments and simulations were conducted to show that the proposed method can achieve the above improvements.
Intercropping the Sharp-Leaf Galangal with the Rubber Tree Exhibits Weak Belowground Competition
Authors: Wu Junen , Zeng Huanhuan , Chen Chunfeng , Liu Wenjie , Jiang Xiaojin
Published: October 2019

Intercropping the sharp-leaf galangal with the rubber tree could help to improve the sustainability of the rubber tree planting industry. However, our understanding of belowground competition in such agroforestry systems is still limited. Therefore, we used stable isotope methods (i.e., water δ2H and δ18O and leaf δ13C) to investigate plant water-absorbing patterns and water use efficiency (WUE) in a monocultural rubber plantation and in an agroforestry system of rubber trees and sharp-leaf galangal. We also measured leaf carbon (C), nitrogen (N), and phosphorus (P) to evaluate the belowground competition effects on plant nutrient absorption status. Through a Bayesian mixing model, we found that the monocultural rubber trees and the intercropped sharp-leaf galangal absorbed much more surface soil water at a depth of 0–5 cm, while the rubber trees in the agroforestry system absorbed more water from the shallow and middle soil layers at a depth of 5–30 cm. This phenomenon verified the occurrence of plant hydrologic niche segregation, whereas the WUE of rubber trees in this agroforestry system suggested that the competition for water was weak. In addition, the negative correlation between the leaf P concentration of the rubber trees and that of the sharp-leaf galangal demonstrated their competition for soil P resources, but this competition had no obvious effects on the leaf nutrient status of the rubber trees. Therefore, this study verified that the belowground competition between rubber trees and sharp-leaf galangal is weak, and this weak competition may benefit their long-term intercropping.
Variation in Carbon Concentration and Allometric Equations for Estimating Tree Carbon Contents of 10 Broadleaf Species in Natural Forests in Northeast China
Authors: Dong Lihu , Liu Yongshuai , Zhang Lianjun , Xie Longfei , Li Fengri
Published: October 2019

In this study, the effects of tree species, tissue types, and tree size on the carbon concentration were studied, and the two additive systems, one with tree diameter (D), and the other with both D and tree height (H), were developed to estimate the stem, root, branch, and foliage carbon content of 10 broadleaf species in northeast China. The coefficients of the two systems were estimated with the nonlinear seemingly unrelated regression (NSUR), while the heteroscedasticity of the model residual was solved with the weight function. Our results showed that carbon concentrations varied along with tree species and size; the tissues and foliage contained higher carbon concentration than other observed tissues. The two additive carbon equation systems exhibited good predictive and fitting performance, with Ra2 > 0.87, average prediction error of approximately 0, and small average absolute error and absolute error percentage. The carbon equation system constructed with D and H exhibited better fit and performance, particularly for the stem and total carbon. Thus, the additive carbon equation systems estimated the tree carbon of 10 broadleaf species more accurately. These carbon equations can be used to monitor the carbon pool sizes for natural forests in the Chinese National Forest Inventory.