bluuebunny/crossref_metadata_2025 huggingface dataset:
Color Visual Secret Sharing for QR Code with Perfect Module Reconstruction
Authors: Liu Tao , Yan Bin , Pan Jeng-Shyang
Published: November 2019

Visual secret sharing is a secret sharing scheme where the decryption requires no computation. It has found many applications in online transaction security, privacy protection, and bar code security, etc. Recently, researches have indicated that combining visual secret sharing with the widely used Quick Response code may provide additional security mechanism to online transaction. However, current methods are either pixel-based, which requires high computational complexity or module-based, which sacrifices error correction capability of the original Quick Response code. Designing module-based visual secret sharing for the Quick Response code without sacrificing error correction capability is a challenging problem. To solve this problem, this paper proposes a (3, 3)-threshold visual secret sharing for Quick Response code scheme that fully explores the extra freedom provided by color visual secret sharing and color stacking. The binary secret Quick Response code is encoded into color shares. By stacking all the three shares, a binary color Quick Response code can be reconstructed. After the inherent pre-processing steps in a standard Quick Response code decoder, the original binary secret Quick Response code can be completely reconstructed. Thus, the original error correction capability of the Quick Response code is fully preserved. Theoretical analysis shows that the visual secret sharing for Quick Response code is secure under the condition that the computational device available to the attacker is limited to a decoder for standard Quick Response code. Experimental results verify that the secret Quick Response code cannot be reconstructed from just one share or any two shares. However, it can be 100% reconstructed once the three shares are stacked. The proposed visual secret sharing for Quick Response code is module-based, and it does not sacrifice the error correction capability. Furthermore, No extra pre-processing steps other than the standard Quick Response code decoder are required.
A Multiscale Flow-Focused Geographically Weighted Regression Modelling Approach and Its Application for Transport Flows on Expressways
Authors: Zhang Lianfa , Cheng Jianquan , Jin Cheng , Zhou Hong
Published: November 2019

Scale is a fundamental geographical concept and its role in different geographical contexts has been widely documented. The increasing availability of transport mobility data, in the form of big datasets, enables further incorporation of spatial dependencies and non-stationarity into spatial interaction modeling of transport flows. In this paper a newly developed multiscale flow-focused geographically weighted regression (MFGWR) approach has been applied, in addition to global and local Moran I indices of flow data, to model multiscale socio-economic determinants of regional transport flows between counties across the Jiangsu Province in China. The results have confirmed the power of local Moran I of flow data for identifying urban agglomerations and the effectiveness of MFGWR in exploring multiscale processes of spatial interactions. A comparison between MFGWR and flow-focused geographically weighted regression (FGWR) showed that the MFGWR approach can better interpret the heterogeneous processes of spatial interaction.
Deep Neural Network Equalization for Optical Short Reach Communication
Authors: Schaedler Maximilian , Bluemm Christian , Kuschnerov Maxim , Pittalà Fabio , Calabrò Stefano , Pachnicke Stephan
Published: November 2019

Nonlinear distortion has always been a challenge for optical communication due to the nonlinear transfer characteristics of the fiber itself. The next frontier for optical communication is a second type of nonlinearities, which results from optical and electrical components. They become the dominant nonlinearity for shorter reaches. The highest data rates cannot be achieved without effective compensation. A classical countermeasure is receiver-side equalization of nonlinear impairments and memory effects using Volterra series. However, such Volterra equalizers are architecturally complex and their parametrization can be numerical unstable. This contribution proposes an alternative nonlinear equalizer architecture based on machine learning. Its performance is evaluated experimentally on coherent 88 Gbaud dual polarization 16QAM 600 Gb/s back-to-back measurements. The proposed equalizers outperform Volterra and memory polynomial Volterra equalizers up to 6th orders at a target bit-error rate (BER) of 10 − 2 by 0.5 dB and 0.8 dB in optical signal-to-noise ratio (OSNR), respectively.
Security-Constrained Day-Ahead Operational Planning for Flexible Hybrid AC/DC Distribution Networks
Authors: Ibrahim Ahmad Asrul , Kazemtabrizi Behzad , Renedo Javier
Published: November 2019

A new active network management framework is presented based on a multi-period optimal power flow problem that is bounded by security constraints at the distribution level for upholding the security of supply. This can be achieved through active engagement with flexible demand and distributed generation to prepare for contingency events in day-ahead operational planning. This framework is coupled with a flexible hybrid AC/DC medium voltage (MV) distribution network topology. It contains an integrated multi-terminal medium voltage DC (MVDC) interface for a seamless interaction and integration of the flexible demand and generation on both AC and DC sides of the hybrid network. The active energy management framework when coupled with a flexible hybrid AC/DC topology provides unprecedented degrees of flexibility as well as security of operation under a variety of conditions. To this end, the 75-bus UK generic distribution network has been modified and converted into a hybrid AC/DC network using the integrated MVDC interface. This framework is then deployed to minimise operational costs to the network operator, considering costs of schemes such as distributed generation curtailment and flexible demand shifting, as well as network losses. Results show a significant improvement in operational costs when the network operates as a flexible hybrid when compared to a pure AC or a more conventional AC/DC hybrid.
Spatial Interpolation of GNSS Troposphere Wet Delay by a Newly Designed Artificial Neural Network Model
Authors: Selbesoglu Mahmut Oguz
Published: November 2019

Global Navigation Satellite System (GNSS) signals arrive at the Earth in a nonlinear and slightly curved way due to the refraction effect caused by the troposphere. The troposphere delay of the GNSS signal consists of hydrostatic and wet parts. In particular, tropospheric wet delay prediction and interpolation are more difficult than those of the dry component due to the rapid temporal and spatial variation of the water vapor content. Wet delay estimation and interpolation with a sufficient accuracy is an important issue for all parameters obtained by GNSS positioning techniques. In particular, in real-time positioning applications, errors caused by interpolation of the wet troposphere delay are reflected in the height component of about 1 to 2 cm. Furthermore, the amount of water vapor in the troposphere is very important information in weather forecast applications obtained as a function of wet delay. Therefore, real-time monitoring of the troposphere can be achieved with a higher resolution and accuracy by utilizing neural network models for interpolation of the wet tropospheric delay. In addition, in the absence of the GNSS station, wet delays can be interpolated by means of the surrounding stations to the desired location. In this study, a back propagation artificial neural network (BPNN) model based on meteorological parameters obtained from The New Austrian Meteorological Measuring Network (TAWES) was used to interpolate wet troposphere delay. Analysis was carried out at 40 reference stations of the Echtzeit Positionierung Austria (EPOSA) GNSS Network covering the whole of Austria. The interpolation of zenith wet delays based on the artificial neural network was performed by using latitude, longitude, altitude and meteorological parameters (temperature, pressure, weighted mean temperature, and water vapor pressure). These parameters were then subtracted from the artificial neural network model one by one and six different artificial neural networks were designed. In addition, the linear interpolation method (LIN) and inverse distance weighted interpolation method (IDW) were used as conventional interpolation methods. In order to investigate the effect of the network density on interpolation methods, three networks, including 40, 30, and 20 reference stations, were formed and the increased distance effect on interpolation methods was evaluated. In addition, analyses were conducted in winter, spring, and summer to evaluate the seasonal effects on interpolation methods. According to the statistical analysis, the root mean square error (RMSE) values of the IDW, LIN, and BPNN methods were found to be 12.6, 13.4, and 5.9 mm, respectively.
On Non-Completeness and G-Equivariance
Authors: Baek Yoo-Jin
Published: November 2019

With the growing threat of the side-channel attack (SCA) to the cryptographic algorithm’s implementations, the masking method has become one of the most promising SCA countermeasures for securely implementing, for example, block ciphers. The basic principle of the masking method is that if the sensitive variable (which, by definition, depends on sensitive information) is split into some random variables and they are manipulated in a secure manner, then the relationship between the random variables and the corresponding side-channel information may look independent from the outside world. However, after the introduction of the glitch attack, there has been a lot of concern about the security of the masking method itself. And, to mitigate the threat of the glitch attack, the threshold implementation (TI) and G-equivariant gates were independently introduced as countermeasures. In this paper, we consider the main notions of two such independent glitch attack’s countermeasures, say, non-completeness and G-equivariance, and investigate their relationship. The contribution of this paper is three-fold. First, we show that the widely-circulated proof that the non-complete TI with uniform inputs guarantees the security against the 1st order DPA even in the presence of glitches is not satisfactory. Next, using the extended notion of G-equivariance to the higher-order setting, we prove that non-completeness implies G-equivariance, which, in turn, means that the non-complete TI with uniform inputs has resistance against the glitch attack. Thirdly, we prove that the set of non-complete gates is a proper subset of the set of G-equivariant gates by showing there is a gate that is G-equivariant but not non-complete.
Shape Memory Polyurethane and its Composites for Various Applications
Authors: Gupta Arvind , Maharjan Anoth , Kim Beom Soo
Published: November 2019

The inherent capability to deform and reform in a predefined environment is a unique property existing in shape memory polyurethane. The intrinsic shape memory ability of the polyurethane is due to the presence of macro domains of soft and hard segments in its bulk, which make this material a potential candidate for several applications. This review is focused on manifesting the applicability of shape memory polyurethane and its composites/blends in various domains, especially to human health such as shielding of electromagnetic interference, medical bandage development, bone tissue engineering, self-healing, implants development, etc. A coherent literature review highlighting the prospects of shape memory polyurethane in versatile applications has been presented.
Latency-Classification-Based Deadline-Aware Task Offloading Algorithm in Mobile Edge Computing Environments
Authors: Choi HeeSeok , Yu Heonchang , Lee EunYoung
Published: November 2019

In this study, we consider an edge cloud server in which a lightweight server is placed near a user device for the rapid processing and storage of large amounts of data. For the edge cloud server, we propose a latency classification algorithm based on deadlines and urgency levels (i.e., latency-sensitive and latency-tolerant). Furthermore, we design a task offloading algorithm to reduce the execution time of latency-sensitive tasks without violating deadlines. Unlike prior studies on task offloading or scheduling that have applied no deadlines or task-based deadlines, we focus on a comprehensive deadline-aware task scheduling scheme that performs task offloading by considering the real-time properties of latency-sensitive tasks. Specifically, when a task is offloaded to the edge cloud server due to a lack of resources on the user device, services could be provided without delay by offloading latency-tolerant tasks first, which are presumed to perform relatively important functions. When offloading a task, the type of the task, weight of the task, task size, estimated execution time, and offloading time are considered. By distributing and offloading latency-sensitive tasks as much as possible, the performance degradation of the system can be minimized. Based on experimental performance evaluations, we prove that our latency-based task offloading algorithm achieves a significant execution time reduction compared to previous solutions without incurring deadline violations. Unlike existing research, we applied delays with various network types in the MEC (mobile edge computing) environment for verification, and the experimental result was measured not only by the total response time but also by the cause of the task failure rate.
Raman Spectroscopic Study of Coal Samples during Heating
Authors: Xie Yingfang , You Jinglin , Lu Liming , Wang Min , Wang Jian
Published: November 2019

Raman spectroscopy can be used to record the characteristic spectra of carbonaceous materials. The D and G bands are the most popular and most important spectral characteristics when discussing carbonaceous materials. In this paper, a Raman spectroscopic study of different coals was first carried out using a 355 nm wavelength laser beam as an excitation source. The spectral parameters of the resultant spectra were evaluated and analyzed. Raman spectral characteristics of different kinds of coals were explored. The high temperature-dependent Raman spectra of the coals were further collected in a temperature range from 298 to 1473 K in order to investigate the transformations of the internal structure of the coals during the pyrolysis process. An abnormal blue shift of the G band occurred at moderate temperature (600–900 K), and the intensity of the G band became weaker at high temperatures, indicating pyrolysis and graphitization of the sample at moderate and high temperature, respectively.
Application of Thermal Image Data to Detect Rebar Corrosion in Concrete Structures
Authors: Na Seunguk , Paik Inkwan
Published: November 2019

Rebar corrosion monitoring techniques have been used in studies involving embedded sensors that can detect changes in the corrosion currents and the polarization resistance of rebars in large structures. Defect detection methods that employ infrared cameras are useful non-destructive testing methods to detect defects in concrete structures. However, the measurement results from these methods would vary depending upon several factors that affect thermography. Because of these reasons, they have not been able to provide sufficient reliability. The goal of this study is to develop a technique that uses infrared cameras to quantitatively measure rebar corrosion rates. To examine the impact of the cover thickness, the experiment variables were set at cover thicknesses of 10, 20, and 30 mm and rebar corrosion ratios of 0%, 1%, 3%, 5%, 7%, and 10%. Each variable was tested and a total of 60 specimens were created (i.e., 54 specimens and 6 preliminary specimens). In this study, corrosion was applied using an electrochemical corrosion method that employs Faraday’s law, i.e., the law of conservation of electric charge. The test results of height, width, and area of temperature distribution curve were analyzed, the height of temperature distribution curve was increased as the heating time was grown. In addition, the area of temperature distribution was varied dependent upon the corrosion rate and cover thickness.
A Text Abstraction Summary Model Based on BERT Word Embedding and Reinforcement Learning
Authors: Wang Qicai , Liu Peiyu , Zhu Zhenfang , Yin Hongxia , Zhang Qiuyue , Zhang Lindong
Published: November 2019

As a core task of natural language processing and information retrieval, automatic text summarization is widely applied in many fields. There are two existing methods for text summarization task at present: abstractive and extractive. On this basis we propose a novel hybrid model of extractive-abstractive to combine BERT (Bidirectional Encoder Representations from Transformers) word embedding with reinforcement learning. Firstly, we convert the human-written abstractive summaries to the ground truth labels. Secondly, we use BERT word embedding as text representation and pre-train two sub-models respectively. Finally, the extraction network and the abstraction network are bridged by reinforcement learning. To verify the performance of the model, we compare it with the current popular automatic text summary model on the CNN/Daily Mail dataset, and use the ROUGE (Recall-Oriented Understudy for Gisting Evaluation) metrics as the evaluation method. Extensive experimental results show that the accuracy of the model is improved obviously.
Is Deployment of Charging Station the Barrier to Electric Vehicle Fleet Development in EU Urban Areas? An Analytical Assessment Model for Large-Scale Municipality-Level EV Charging Infrastructures
Authors: Talluri Giacomo , Grasso Francesco , Chiaramonti David
Published: November 2019

This work investigates minimum charging infrastructure size and cost for two typical EU urban areas and given passenger car electric vehicle (EV) fleets. Published forecasts sources were analyzed and compared with actual EU renewal fleet rate, deriving realistic EV growth figures. An analytical model, accounting for battery electric vehicle-plug-in hybrid electric vehicle (BEV-PHEV) fleets and publicly accessible and private residential charging stations (CS) were developed, with a novel data sorting method and EV fleet forecasts. Through a discrete-time Markov chain, the average daily distribution of charging events and related energy demand were estimated. The model was applied to simulated Florence and Bruxelles scenarios between 2020 and 2030, with a 1-year timestep resolution and a multiple scenario approach. EV fleet at 2030 ranged from 2.3% to 17.8% of total fleet for Florence, 4.6% to 16.5% for Bruxelles. Up to 2053 CS could be deployed in Florence and 5537 CS in Bruxelles, at estimated costs of ~8.3 and 21.4 M€ respectively. Maximum energy demand of 130 and 400 MWh was calculated for Florence and Bruxelles (10.3 MW and 31.7 MW respectively). The analysis shows some policy implications, especially as regards the distribution of fast vs. slow/medium CS, and the associated costs. The critical barrier for CS development in the two urban areas is thus likely to become the time needed to install CS in the urban context, rather than the related additional electric power and costs.
A Framework for Real-Time 3D Freeform Manipulation of Facial Video
Authors: Park Jungsik , Seo Byung-Kuk , Park Jong-Il
Published: November 2019

This paper proposes a framework that allows 3D freeform manipulation of a face in live video. Unlike existing approaches, the proposed framework provides natural 3D manipulation of a face without background distortion and interactive face editing by a user’s input, which leads to freeform manipulation without any limitation of range or shape. To achieve these features, a 3D morphable face model is fitted to a face region in a video frame and is deformed by the user’s input. The video frame is then mapped as a texture to the deformed model, and the model is rendered on the video frame. Because of the high computational cost, parallelization and acceleration schemes are also adopted for real-time performance. Performance evaluation and comparison results show that the proposed framework is promising for 3D face editing in live video.
Electrochemical Evidence of non-Volatile Reduced Sulfur Species in Water-Soluble Fraction of Fine Marine Aerosols
Authors: Cvitešić Kušan Ana , Frka Sanja , Ciglenečki Irena
Published: November 2019

The traditional voltammetric method at the mercury electrode, and an acidification step developed for the determination of reduced sulfur species (RSS) in natural waters, was for the first time used for the quantification of RSS in the water-soluble fraction of fine marine aerosols collected at the Middle Adriatic location (Rogoznica Lake). The evidence of two types of non-volatile RSS that have different interaction with the Hg electrode was confirmed: mercapto-type which complexes Hg as RS–Hg and sulfide/S0-like compounds which deposits HgS. The analytical protocol that was used for RSS determination in aerosol samples is based on separate voltammetric studies of a methyl 3-mercaptopropionate (3-MPA) as a representative of mercapto-type compounds and sulfide as a representative of inorganic RSS. Our preliminary study indicates the presence of mainly RS–Hg compounds in spring samples, ranging from 2.60–15.40 ng m−3, while both, the mercapto-type (0.48–2.23 ng m−3) and sulfide and/or S0-like compounds (0.02–0.26 ng m−3) were detected in early autumn samples. More expressed and defined RS–Hg peaks recorded in the spring potentially indicate their association with biological activity in the area. Those samples were also characterized by a higher water-soluble organic carbon content and a more abundant surface-active fraction, pointing to enhanced solubility and stabilization of RSS in the aqueous atmospheric phase.
Interdecadal Variations of the Midlatitude Ozone Valleys in Summer
Authors: Zhang Zhiming , Rao Jian , Guo Dong , Zhang Wenhui , Li Liping , Tang Zhou , Shi Chunhua , Su Yucheng , Zhang Fuying
Published: November 2019

Using the ERA-Interim total column ozone data, the spatial distributions of the long-term mean of the global total ozone in summer are analyzed. The results demonstrate that there are three midlatitude ozone “valleys” on earth—they are centered over the Tibetan Plateau (TIP), the Rocky Mountains (ROM), and the Southwest Pacific (SWP), respectively. The interdecadal variations of the three ozone valleys are positively modulated by the solar radiation, and the TIP ozone’s correlation with the solar radiation gets maximized with a two-year lag. The interdecadal variation of the SWP ozone valley has a significantly negative relationship with the Pacific Decadal Oscillation (PDO) and the South Pacific quadrupole (SPQ). Warm sea surface temperature anomalies (SSTAs) associated with the SPQ strengthen the vertical ascending motion, which dilutes the high concentration ozone at high altitudes. The interdecadal variation of the ROM ozone valley is positively correlated with the PDO, leading by three years. The ROM ozone content is also modulated by SSTAs in the Indian Ocean basin (IOB) by the circumglobal teleconnection (CGT). The observed regional SSTAs can exert a significant impact on the regional and even global circulation, via which the ozone content in midlatitudes also varies.
Tracking Temporal Development of Optical Thickness of Hydrogen Alpha Spectral Radiation in a Laser-Induced Plasma
Authors: Surmick David M. , Parigger Christian G.
Published: November 2019

In this paper, we consider the temporal development of the optical density of the H α spectral line in a hydrogen laser-induced plasma. This is achieved by using the so-called duplication method in which the spectral line is re-imaged onto itself and the ratio of the spectral line with it duplication is taken to its measurement without the duplication. We asses the temporal development of the self-absorption of the H α line by tracking the decay of duplication ratio from its ideal value of 2. We show that when 20% loss is considered along the duplication optical path length, the ratio is 1.8 and decays to a value of 1.25 indicating an optically thin plasma grows in optical density to an optical depth of 1.16 by 400 ns in the plasma decay for plasma initiation conditions using Nd:YAG laser radiation at 120 mJ per pulse in a 1.11 × 10 5 Pa hydrogen/nitrogen gas mixture environment. We also go on to correct the H α line profiles for the self-absorption impact using two methods. We show that a method in which the optical depth is directly calculated from the duplication ratio is equivalent to standard methods of self-absorption correction when only relative corrections to spectral emissions are needed.
Regularized Solution of Singularly Perturbed Cauchy Problem in the Presence of Rational “Simple” Turning Point in Two-Dimensional Case
Authors: Eliseev Alexander , Ratnikova Tatjana
Published: November 2019

By Lomov’s S.A. regularization method, we constructed an asymptotic solution of the singularly perturbed Cauchy problem in a two-dimensional case in the case of violation of stability conditions of the limit-operator spectrum. In particular, the problem with a ”simple” turning point was considered, i.e., one eigenvalue vanishes for t = 0 and has the form t m / n a ( t ) (limit operator is discretely irreversible). The regularization method allows us to construct an asymptotic solution that is uniform over the entire segment [ 0 , T ] , and under additional conditions on the parameters of the singularly perturbed problem and its right-hand side, the exact solution.
Human-Error Prevention for Autonomous Edge Software Using Minimalistic Modern C++
Authors: Fukano Ryo , Ishikawa Masato
Published: November 2019

In science and engineering using edge-embedded software, it is necessary to demonstrate the validity of results; therefore, the software responsible for operating an edge system is required to guarantee its own validity. The aim of this study is to guarantee the validity of the sampled-time filter and time domain as fundamental elements of autonomous edge software. This requires the update law of a sampled-time filter to be invoked once per every control cycle, which we guaranteed by using the proposed domain specific language implemented by a metaprogramming design pattern in modern C++ (C++11 and later). The time-domain elements were extracted from the software, after which they were able to be injected into the extracted software independent from the execution environment of the software. The proposed approach was shown to be superior to conventional approaches that only rely on the attention of programmers to detect design defects. This shows that it is possible to guarantee the validity of edge software by using only a general embedded programming language such as modern C++ without auxiliary verification and validation toolchains.
Understanding the Effect of Structural Diversity in WRKY Transcription Factors on DNA Binding Efficiency through Molecular Dynamics Simulation
Authors: Singh Akshay , Sharma Ajay Kumar , Singh Nagendra Kumar , Sonah Humira , Deshmukh Rupesh , Sharma Tilak Raj
Published: November 2019

A precise understanding of the molecular mechanism involved in stress conditions has great importance for crop improvement. Biomolecules, such as WRKY proteins, which are the largest transcription factor family that is widely distributed in higher plants, plays a significant role in plant defense response against various biotic and abiotic stressors. In the present study, an extensive homology-based three-dimensional model construction and subsequent interaction study of WRKY DNA-binding domain (DBD) in CcWRKY1 (Type I), CcWRKY51 (Type II), and CcWRKY70 (Type III) belonging to pigeonpea, a highly tolerant crop species, was performed. Evaluation of the generated protein models was done to check their reliability and accuracy based on the quantitative and qualitative parameters. The final model was subjected to investigate the comparative binding analysis of different types of WRKY–DBD with DNA-W-box (a cis-acting element) by protein–DNA docking and molecular dynamics (MD) simulation. The DNA binding specificity with WRKY variants was scrutinized through protein–DNA interaction using the HADDOCK server. The stability, as well as conformational changes of protein–DNA complex, was investigated through molecular dynamics (MD) simulations for 100 ns using GROMACS. Additionally, the comparative stability and dynamic behavior of each residue of the WRKY–DBD type were analyzed in terms of root mean square deviation (RMSD), root mean square fluctuation (RMSF)values of the backbone atoms for each frame taking the minimized structure as a reference. The details of DNA binding activity of three different types of WRKY–DBD provided here will be helpful to better understand the regulation of WRKY gene family members in plants.
Coupled Response of Membrane Hydration with Oscillating Metabolism in Live Cells: An Alternative Way to Modulate Structural Aspects of Biological Membranes?
Authors: Bagatolli Luis A. , Stock Roberto P. , Olsen Lars F.
Published: November 2019

We propose that active metabolic processes may regulate structural changes in biological membranes via the physical state of cell water. This proposition is based on recent results obtained from our group in yeast cells displaying glycolytic oscillations, where we demonstrated that there is a tight coupling between the oscillatory behavior of glycolytic metabolites (ATP, NADH) and the extent of the dipolar relaxation of intracellular water, which oscillates synchronously. The mechanism we suggest involves the active participation of a polarized intracellular water network whose degree of polarization is dynamically modulated by temporal ATP fluctuations caused by metabolism with intervention of a functional cytoskeleton, as conceived in the long overlooked association-induction hypothesis (AIH) of Gilbert Ling. Our results show that the polarized state of intracellular water can be propagated from the cytosol to regions containing membranes. Since changes in the extent of the polarization of water impinge on its chemical activity, we hypothesize that metabolism dynamically controls the local structure of cellular membranes via lyotropic effects. This hypothesis offers an alternative way to interpret membrane related phenomena (e.g., changes in local curvature pertinent to endo/exocytosis or dynamical changes in membranous organelle structure, among others) by integrating relevant but mostly overlooked physicochemical characteristics of the cellular milieu.
Gene Expression Signature-Based Approach Identifies Antifungal Drug Ciclopirox As a Novel Inhibitor of HMGA2 in Colorectal Cancer
Authors: Huang Yu-Min , Cheng Chia-Hsiung , Pan Shiow-Lin , Yang Pei-Ming , Lin Ding-Yen , Lee Kuen-Haur
Published: November 2019

Human high-mobility group A2 (HMGA2) encodes for a non-histone chromatin protein which influences a variety of biological processes, including the cell cycle process, apoptosis, the DNA damage repair process, and epithelial–mesenchymal transition. The accumulated evidence suggests that high expression of HMGA2 is related to tumor progression, poor prognosis, and a poor response to therapy. Thus, HMGA2 is an important molecular target for many types of malignancies. Our recent studies revealed the positive connections between heat shock protein 90 (Hsp90) and HMGA2 and that the Hsp90 inhibitor has therapeutic potential to inhibit HMGA2-triggered tumorigenesis. However, 43% of patients suffered visual disturbances in a phase I trial of the second-generation Hsp90 inhibitor, NVP-AUY922. To identify a specific inhibitor to target HMGA2, the Gene Expression Omnibus (GEO) database and the Library of Integrated Network-based Cellular Signatures (LINCS) L1000platform were both analyzed. We identified the approved small-molecule antifungal agent ciclopirox (CPX) as a novel potential inhibitor of HMGA2. In addition, CPX induces cytotoxicity of colorectal cancer (CRC) cells by induction of cell cycle arrest and apoptosis in vitro and in vivo through direct interaction with the AT-hook motif (a small DNA-binding protein motif) of HMGA2. In conclusion, this study is the first to report that CPX is a novel potential inhibitor of HMGA2 using a drug-repurposing approach, which can provide a potential therapeutic intervention in CRC patients.
Ginkgo Biloba Extract Alleviates Methotrexate-Induced Renal Injury: New Impact on PI3K/Akt/mTOR Signaling and MALAT1 Expression
Authors: Sherif Iman O. , Al-Shaalan Nora H. , Sabry Dina
Published: November 2019

Renal injury induced by the chemotherapeutic agent methotrexate (MTX) is a serious adverse effect that has limited its use in the treatment of various clinical conditions. The antioxidant activity of Ginkgo biloba extract (GB) was reported to mitigate renal injury induced by MTX. Our research was conducted to examine the nephroprotective role of GB versus MTX-induced renal injury for the first time through its impact on the regulation of phosphatidylinositol 3-kinase/protein kinase B/ mammalian target of rapamycin (PI3K/Akt/mTOR) signaling together with the renal level of TGF-β mRNA and long non-coding RNA-metastasis-associated lung adenocarcinoma transcript-1 (MALAT1) expression. A group of adult rats was intraperitoneally (ip) injected with MTX 20 mg/kg as a single dose to induce kidney injury (MTX group). The other group of rats was orally administered with GB 60 mg/kg every day for 10 days (GB+ MTX group). The MTX increased the serum creatinine and urea levels, renal TGF-β mRNA and MALAT1 expression, in addition to dysregulation of the PI3K/Akt/mTOR signaling when compared with normal control rats that received saline only (NC group). Moreover, renal damage was reported histopathologically in the MTX group. The GB ameliorated the renal injury induced by MTX and reversed the changes of these biochemical analyses. The involvement of PI3K/Akt/mTOR signaling and downregulation of TGF-β mRNA and MALAT1 renal expressions were firstly reported in the nephroprotective molecular mechanism of GB versus MTX-induced renal injury.
Two Novel Amyloid Proteins, RopA and RopB, from the Root Nodule Bacterium Rhizobium leguminosarum
Authors: Kosolapova Anastasiia O. , Belousov Mikhail V. , Sulatskaya Anna I. , Belousova Maria E. , Sulatsky Maksim I. , Antonets Kirill S. , Volkov Kirill V. , Lykholay Anna N. , Shtark Oksana Y. , Vasileva Ekaterina N. , Zhukov Vladimir A. , Ivanova Alexandra N. , Zykin Pavel A. , Kuznetsova Irina M. , Turoverov Konstantin K. , Tikhonovich Igor A. , Nizhnikov Anton A.
Published: November 2019

Amyloids represent protein fibrils with a highly ordered spatial structure, which not only cause dozens of incurable human and animal diseases but also play vital biological roles in Archaea, Bacteria, and Eukarya. Despite the fact that association of bacterial amyloids with microbial pathogenesis and infectious diseases is well known, there is a lack of information concerning the amyloids of symbiotic bacteria. In this study, using the previously developed proteomic method for screening and identification of amyloids (PSIA), we identified amyloidogenic proteins in the proteome of the root nodule bacterium Rhizobium leguminosarum. Among 54 proteins identified, we selected two proteins, RopA and RopB, which are predicted to have β-barrel structure and are likely to be involved in the control of plant-microbial symbiosis. We demonstrated that the full-length RopA and RopB form bona fide amyloid fibrils in vitro. In particular, these fibrils are β-sheet-rich, bind Thioflavin T (ThT), exhibit green birefringence upon staining with Congo Red (CR), and resist treatment with ionic detergents and proteases. The heterologously expressed RopA and RopB intracellularly aggregate in yeast and assemble into amyloid fibrils at the surface of Escherichia coli. The capsules of the R. leguminosarum cells bind CR, exhibit green birefringence, and contain fibrils of RopA and RopB in vivo.
Transcriptome Mechanism of Utilizing Corn Steep Liquor as the Sole Nitrogen Resource for Lipid and DHA Biosynthesis in Marine Oleaginous Protist Aurantiochytrium sp.
Authors: Wang Dong-Sheng , Yu Xin-Jun , Zhu Xiao-Yu , Wang Zhao , Li Hui-Juan , Wang Zhi-Peng
Published: November 2019

In the current study, corn steep liquor (CSL) is evaluated as an ideal raw agro-material for efficient lipid and docosahexaenoic acid DHA production by Aurantiochytrium sp. Low CSL level in medium (nitrogen deficiency) stimulated the biosynthesis of lipids and DHA while inhibiting cellular growth. The transcriptomic profiles of the Aurantiochytrium sp. cells are analyzed and compared when cultured under high (H group), normal (N group), and low (L group) levels of CSL in the medium. The discriminated transcriptomic profiles from the three groups indicates that changes in CSL level in medium result in a global change in transcriptome of Aurantiochytrium sp. The overall de novo assembly of cDNA sequence data generated 61,163 unigenes, and 18,129 of them were annotated in at least one database. A total of 5105 differently expressed (DE) genes were found in the N group versus the H group, with 2218 downregulated and 2887 upregulated. A total of 3625 DE genes were found in the N group versus the L group, with 1904 downregulated and 1721 upregulated. The analysis and categorization of the DE genes indicates that the regulation mechanism of CSL involved in the perception and transduction of the limited nitrogen signal, the interactions between the transcription factors (TFs) and multiple downstream genes, and the variations in downstream genes and metabolites, in sequence, are illuminated for the first time in the current study.
Natural Bis-Benzylisoquinoline Alkaloids-Tetrandrine, Fangchinoline, and Cepharanthine, Inhibit Human Coronavirus OC43 Infection of MRC-5 Human Lung Cells
Authors: Kim Dong , Min Jung , Jang Min , Lee Jun , Shin Young , Park Chul , Song Jong , Kim Hyoung , Kim Seungtaek , Jin Young-Hee , Kwon Sunoh
Published: November 2019

Stephania tetrandra and other related species of Menispermaceae are the major sources of the bis-benzylisoquinoline alkaloids tetrandrine (TET), fangchinoline (FAN), and cepharanthine (CEP). Although the pharmacological properties of these compounds include anticancer and anti-inflammatory activities, the antiviral effects of these compounds against human coronavirus (HCoV) remain unclear. Hence, the aims of the current study were to assess the antiviral activities of TET, FAN, and CEP and to elucidate the underlying mechanisms in HCoV-OC43-infected MRC-5 human lung cells. These compounds significantly inhibited virus-induced cell death at the early stage of virus infection. TET, FAN, and CEP treatment dramatically suppressed the replication of HCoV-OC43 as well as inhibited viral S and N protein expression. The virus-induced host response was reduced by compound treatment as compared with the vehicle control. Taken together, these findings demonstrate that TET, FAN, and CEP are potential natural antiviral agents for the prevention and treatment of HCoV-OC43 infection.
Review of Electroanalytical-Based Approaches for the Determination of Benzodiazepines
Authors: Honeychurch Kevin C.
Published: November 2019

The benzodiazepine class of drugs are characterised by a readily electrochemically reducible azomethine group. A number are also substituted by other electrochemically active nitro, N-oxide, and carbonyl groups, making them readily accessible to electrochemical determination. Techniques such as polarography, voltammetry, and potentiometry have been employed for pharmaceutical and biomedical samples, requiring little sample preparation. This review describes current developments in the design and applications of electrochemical-based approaches for the determination of the benzodiazepine class of drugs form their introduction in the early 1960s to 2019. Throughout this period, state-of-the-art electroanalytical techniques have been reported for their determination. Polarography was first employed focused on mechanistic investigations. Subsequent studies showed the adsorption of many the benzodiazepines at Hg electrodes allowed for the highly sensitive technique of adsorptive stripping voltammetry to be employed. The development and introduction of other working electrode materials such as carbon led to techniques such as voltammetry to become commonly reported, and the modification of these electrodes has now become the most commonly employed approach using molecularly imprinting and nanotechnology.
Insomnia Symptoms among African-American Older Adults in Economically Disadvantaged Areas of South Los Angeles
Authors: Bazargan Mohsen , Mian Nadia , Cobb Sharon , Vargas Roberto , Assari Shervin
Published: November 2019

Background. Although psychosocial and health factors impact insomnia symptoms, less is known about these effects in economically disadvantaged African-American older adults. Aims. This study investigated social and health determinants of insomnia symptoms among economically disadvantaged African-American older adults. Methods. This survey enrolled 398 African-American older adults (age ≥ 65 years) from economically disadvantaged areas of South Los Angeles. Gender, age, educational attainment, financial difficulty, number of chronic diseases, self-rated health, pain intensity, and depression were covariates. Total insomnia, insomnia symptoms, and insomnia impact were our outcomes. Linear regression was applied for data analysis. Results. Based on linear regression, higher financial difficulty (B = 0.48, 95% CI = 0.35–0.61), smoking status (B = 1.64, 95% CI = 0.13–3.16), higher pain intensity (B = 0.39, 95% CI = 0.11–0.67), higher number of chronic diseases (B = 0.34, 95% CI = 0.05–0.64), and more depressive symptoms (B = 0.35, 95% CI = 0.12–0.57) were associated with a higher frequency of insomnia symptoms. Based on a logistic regression model, lower age (B = 0.91, 95% CI = 0.91–1.00) and high financial difficulty (OR = 1.15, 95% CI = 1.08–1.24), pain (OR = 2.08, 95% CI = 1.14–3.80), chronic disease (OR = 1.27, 95% CI = 1.07–1.51) and depression (OR = 2.38, 95% CI = 1.22–4.65) were associated with higher odds of possible clinical insomnia. We also found specific predictors for insomnia symptoms and insomnia impact. Conclusions. Among African-American older adults in economically disadvantaged areas of South Los Angeles, insomnia symptoms co-occur with other economic, physical, and mental health challenges such as financial difficulty, smoking, multimorbidity, pain, and depression. There is a need to address sleep as a component of care of economically disadvantaged African-American older adults who have multiple social and health challenges.
Manifold Learning of Dynamic Functional Connectivity Reliably Identifies Functionally Consistent Coupling Patterns in Human Brains
Authors: Yang Yuyuan , Wang Lubin , Lei Yu , Zhu Yuyang , Shen Hui
Published: November 2019

Most previous work on dynamic functional connectivity (dFC) has focused on analyzing temporal traits of functional connectivity (similar coupling patterns at different timepoints), dividing them into functional connectivity states and detecting their between-group differences. However, the coherent functional connectivity of brain activity among the temporal dynamics of functional connectivity remains unknown. In the study, we applied manifold learning of local linear embedding to explore the consistent coupling patterns (CCPs) that reflect functionally homogeneous regions underlying dFC throughout the entire scanning period. By embedding the whole-brain functional connectivity in a low-dimensional manifold space based on the Human Connectome Project (HCP) resting-state data, we identified ten stable patterns of functional coupling across regions that underpin the temporal evolution of dFC. Moreover, some of these CCPs exhibited significant neurophysiological meaning. Furthermore, we apply this method to HCP rsfMR and tfMRI data as well as sleep-deprivation data and found that the topological organization of these low-dimensional structures has high potential for predicting sleep-deprivation states (classification accuracy of 92.3%) and task types (100% identification for all seven tasks).In summary, this work provides a methodology for distilling coherent low-dimensional functional connectivity structures in complex brain dynamics that play an important role in performing tasks or characterizing specific states of the brain.
Quantitative, Multi-institutional Evaluation of MR Thermometry Accuracy for Deep-Pelvic MR-Hyperthermia Systems Operating in Multi-vendor MR-systems Using a New Anthropomorphic Phantom
Authors: Curto Sergio , Aklan Bassim , Mulder Tim , Mils Oliver , Schmidt Manfred , Lamprecht Ulf , Peller Michael , Wessalowski Ruediger , Lindner Lars H. , Fietkau Rainer , Zips Daniel , Bellizzi Gennaro G. , van Holthe Netteke , Franckena Martine , Paulides Margarethus M. , van Rhoon Gerard C.
Published: November 2019

Clinical outcome of hyperthermia depends on the achieved target temperature, therefore target conformal heating is essential. Currently, invasive temperature probe measurements are the gold standard for temperature monitoring, however, they only provide limited sparse data. In contrast, magnetic resonance thermometry (MRT) provides unique capabilities to non-invasively measure the 3D-temperature. This study investigates MRT accuracy for MR-hyperthermia hybrid systems located at five European institutions while heating a centric or eccentric target in anthropomorphic phantoms with pelvic and spine structures. Scatter plots, root mean square error (RMSE) and Bland–Altman analysis were used to quantify accuracy of MRT compared to high resistance thermistor probe measurements. For all institutions, a linear relation between MRT and thermistor probes measurements was found with R2 (mean ± standard deviation) of 0.97 ± 0.03 and 0.97 ± 0.02, respectively for centric and eccentric heating targets. The RMSE was found to be 0.52 ± 0.31 °C and 0.30 ± 0.20 °C, respectively. The Bland-Altman evaluation showed a mean difference of 0.46 ± 0.20 °C and 0.13 ± 0.08 °C, respectively. This first multi-institutional evaluation of MR-hyperthermia hybrid systems indicates comparable device performance and good agreement between MRT and thermistor probes measurements. This forms the basis to standardize treatments in multi-institution studies of MR-guided hyperthermia and to elucidate thermal dose-effect relations.
Conversion Surgery with HIPEC for Peritoneal Oli-gometastatic Gastric Cancer
Authors: Mielko Jerzy , Rawicz-Pruszyński Karol , Skórzewska Magdalena , Ciseł Bogumiła , Pikuła Agnieszka , Kwietniewska Magdalena , Gęca Katarzyna , Sędłak Katarzyna , Kurylcio Andrzej , Polkowski Wojciech P.
Published: November 2019

Peritoneal metastases (PM) of gastric cancer (GC) are characterized by a particularly poor prognosis, with median survival time of 6 months, and virtually no 5-year survival reported. Conversion therapy for GC is defined as a surgical treatment aiming at an R0 resection after systemic chemotherapy for tumours that were originally unresectable (or marginally resectable) for technical and/or oncological reasons. The aim of the present study was to evaluate early and late outcomes in GC patients with PM who underwent the cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) after neoadjuvant (conversion) chemotherapy. Thirty patients with stage IV GC underwent CRS plus HIPEC. Severe grade III/IV (Clavien-Dindo classification) complications occurred in 13 (43%) patients. The Comprehensive Complication Index (CCI) ranged from 8.7 to 100 (median, 42.4). In the multivariate survival analysis, ypT2 and P3 (according to the Japanese classification of the PM severity) were favourable and adverse prognostic factors p = 0.031 and o = 0.035, respectively. Estimated 1- and 3-year survival was 73.9% and 36.6%, respectively. The median survival was 19.3 months. Conclusion: Conversion surgery, including extended gastrectomy and multi-organ resections followed by HIPEC performed after systemic chemotherapy therapy for GC with PM is justified in downstaged patients with ypT2 and limited (less than P3) PM.