bluuebunny/crossref_metadata_2025 huggingface dataset:
Biogeochemical Cycle of Lanthanides in a Light Rare Earth Element-Enriched Geological Area (Quebec, Canada)
Authors: Romero-Freire Ana , Turlin François , André-Mayer Anne-Sylvie , Pelletier Mia , Cayer Alain , Giamberini Laure
Published: September 2019

This work investigated a rare earth element (REE) natural biogeochemical cycle in an area with a light rare earth element (LREE)-rich ferrocarbonatite intrusion. An REE determination in this geological environment allowed us to trace REE natural transfers in order to better manage future REE mining exploitations. Our findings suggest that although REE concentrations in abiotic compartments (soil and freshwater systems) and biotic samples (terrestrial and aquatic plants) were low, the LREE fractionation observed in the parent material was maintained along compartments. Additionally, Nd anomalies observed in the sediment pore water suggest a potential different biogeochemical cycle of this element in aquatic systems. According to the potential bioaccumulation of REEs in the organisms of two studied plants belonging to terrestrial and aquatic compartments, Equisetum arvense L. and Typha latifolia L. (respectively), we observed that REEs were not accumulated and that they showed limited REE transfer inside plants, but with an increased uptake of Eu relative to the other REEs. Our results indicated a low mobility and transfer of REEs from REE-rich bedrocks in a natural area toward terrestrial and freshwater systems, but also pointed to a dilution of the REE content in the different compartments, maintaining the LREE fractionation. Our findings provide new knowledge about the REE biochemical cycle in a natural area (from rocks to plants) and represent a starting point for an environmentally friendly exploitation of future REE mining areas.
Exploring the Synergy Between HPTLC and HPLC-DAD for the Investigation of Wine-Making By-Products
Authors: Bernardi Tatiana , Bortolini Olga , Massi Alessandro , Sacchetti Gianni , Tacchini Massimo , De Risi Carmela
Published: September 2019

Both environmental and economic issues are increasingly pushing for the revalorization of agri-food by-products, including those arising from wine industry. Wastes produced from wine-making processes are important sources of biologically active compounds, mainly phenolic acids and flavonoids, which could be re-used for several applications, for example as additive surrogates or new ingredients in foodstuffs and/or pharmaceuticals. Therefore, the development of methods aimed at isolating, characterizing and quantifying molecules present in winery by-products acquires considerable importance in view of their re-utilization on a large scale. In this connection, this study demonstrated that high-performance thin-layer chromatography (HPTLC) and high-performance liquid chromatography with diode array detection (HPLC-DAD) can operate in synergy for the investigation of pomace and seed materials arising from both white and red cultivars of Vitis Vinifera. By virtue of fingerprint profiling, mass spectrometry (MS) interfacing and band comparison method, HPTLC enabled detection and identification of phenolic acids, non-anthocyanic flavonoids and anthocyanins. On the contrary, only anthocyanins could be identified by HPLC-DAD, and their subsequent quantification showed that malvidin-3-O-glucoside (oenin) was the most abundant one. In parallel, HPTLC has allowed to detect and quantify proanthocyanidins (PAC), showing that only catechin was present in the test samples. Both quantitative analytical methods were validated in terms of linearity, detection and quantification limits and precision.
Comparison of Anticancer Activity and HPLC-DAD Determination of Selected Isoquinoline Alkaloids from Thalictrum foetidum, Berberis sp. and Chelidonium majus Extracts
Authors: Petruczynik Anna , Tuzimski Tomasz , Plech Tomasz , Misiurek Justyna , Szalast Karolina , Szymczak Grażyna
Published: September 2019

Background: Plants are an important origin of natural substances that the raw material for various pharmaceutical and therapeutic applications due to the presence of phytochemicals, such as alkaloids. Alkaloids, which are found in different plant species, possess numerous biological activities. Some alkaloids have strong cytotoxic effects on various cancer cells. The search for new drugs to treat various cancers is one of the most important challenges of modern scientific research. Objective: This study aimed to investigate of cytotoxic activity of extracts that were obtained from Chelidonium Majus; Berberis sp.; Thalictrum foetidum containing various alkaloids on selected cancer cell lines. The aim was also the quantification of selected alkaloids in the investigated extracts by HPLC. Methods: The analysis of alkaloids contents were performed while using HPLC in reversed phase (RP) mode using Polar RP column and mobile phase containing acetonitrile, water, and ionic liquid. The cytotoxic effect of the tested plant extracts and respective alkaloids’ standards were examined while using human pharyngeal squamous carcinoma cells (FaDu), human tongue squamous carcinoma cells (SCC-25), human breast adenocarcinoma cell line (MCF-7), and human triple-negative breast adenocarcinoma cell line (MDA-MB-231). Conclusion: All of the investigated plant extracts possess cytotoxic activity against cancer cell lines: FaDu, SCC-25, MCF-7, and MDA-MB-231. The highest cytotoxic activity against FaDu and MDA-MB-231 cells was observed for Chelidonium majus root extract, while the highest cytotoxic activity against SCC-25 and MCF-7 cells was estimated for the Thalictrum foetidum root extract. There obtained significant differences in the cytotoxic activity of extracts that were obtained from the roots and herbs of Chelidonium majus and Thalictrum foetidum. Based on these results, investigated plant extracts can be recommended for further investigations of anticancer activity.
Xanthommatin is Behind the Antioxidant Activity of the Skin of Dosidicus gigas
Authors: Chan-Higuera Jesús Enrique , Santacruz-Ortega Hisila del Carmen , Carbonell-Barrachina Ángel A. , Burgos-Hernández Armando , Robles-Sánchez Rosario Maribel , Cruz-Ramírez Susana Gabriela , Ezquerra-Brauer Josafat Marina
Published: September 2019

Marine bioactive compounds have been found in very different sources and exert a very vast array of activities. Squid skin, normally considered a discard, is a source of bioactive compounds such as pigments. Recovering these compounds is a potential means of valorizing seafood byproducts. Until now, the structure and molecular properties of the bioactive pigments in jumbo squid skin (JSS) have not been established. In this study, methanol–HCl (1%) pigment extracts from JSS were fractionated by open column chromatography and grouped by thin-layer chromatography in order to isolate antioxidant pigments. Antioxidant activity was determined by the 2,2-diphenyl-1-picrylhydrazyl (DPPH●) and 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS●+) radical scavenging assays and ferric reducing power (FRAP) assay. Fractions 11–34 were separated and grouped according to flow rate values (F1–F8). Fractions F1, F3, and F7 had the lowest IC50 against ABTS●+ per milligram, and fractions F3 and F7 showed the lowest IC50 in the FRAP assay. Finally, fraction F7 had the highest DPPH● scavenging activity. The chemical structure of the F7 fraction was characterized by infrared spectroscopy, 1H nuclear magnetic resonance, and electrospray ionization–mass spectrometry. One of the compounds identified in the fraction was xanthommatin (11-(3-amino-3-carboxypropanoyl)-1-hydroxy-5-oxo-5H-pyrido[3,2-a]phenoxazine-3-carboxylic acid) and their derivatives (hydro- and dihydroxanthommatin). The results show that JSS pigments contain ommochrome molecules like xanthommatin, to which the antioxidant activity can be attributed.
Design, Synthesis, and Biological Evaluation of Novel Thienopyrimidine Derivatives as PI3Kα Inhibitors
Authors: Yu Lide , Wang Qinqin , Wang Caolin , Zhang Binliang , Yang Zunhua , Fang Yuanying , Zhu Wufu , Zheng Pengwu
Published: September 2019

Three series of novel thienopyrimidine derivatives 9a–l, 15a–l, and 18a–h were designed and synthesized, and their IC50 values against four cancer cell lines HepG-2, A549, PC-3, and MCF-7 were evaluated. Most compounds show moderate cytotoxicity against the tested cancer cell lines. The most promising compound 9a showed moderate activity with IC50 values of 12.32 ± 0.96, 11.30 ± 1.19, 14.69 ± 1.32, and 9.80 ± 0.93 µM, respectively. The inhibitory activities of compounds 9a and 15a against PI3Kα and mTOR kinase were further evaluated. Compound 9a exhibited PI3Kα kinase inhibitory activity with IC50 of 9.47 ± 0.63 µM. In addition, docking studies of compounds 9a and 15a were also investigated.
A Beta/ZSM-22 Zeolites-Based-Mixed Matrix Solid-Phase Dispersion Method for the Simultaneous Extraction and Determination of Eight Compounds with Different Polarities in Viticis Fructus by High-Performance Liquid Chromatography
Authors: He Gaogao , Li Jin , Pang Xiaoli , Wang Hui , Jin Hua , He Jun , Fang Shi-Ming , Chang Yan-Xu
Published: September 2019

Viticis Fructus (VF) was named Manjingzi as a commonly used traditional Chinese medicine (TCM) targeting various pains and inflammation for more than 2000 years. To guarantee the quality of Viticis Fructus, a simple, quick and eco-friendly Beta/ZSM-22 zeolites-based-mixed matrix solid-phase dispersion method (B/Z-MMSPD) was established for simultaneous extraction and determination of eight compounds (two phenolic acids, two iridoid glycosides, vanillin and three flavonoids) with different polarities from Viticis Fructus by high performance liquid chromatography coupled with a diode array detector (HPLC-DAD). Beta and ZSM-22 were mixed as the sorbent. Water, tetrahydrofuran and methanol were blended with certain ratio as the eluent. Several parameters including types of sorbents, mass ratio of Beta to ZSM-22, mass ratio of matrix to sorbent, grinding time, types, concentration and volume of eluent were optimized. The recoveries of eight analytes were within the range of 95.0%–105% (RSDs ≤ 4.13%). The limits of detection and limits of quantitation ranged from 0.5 to 5.5 μg/g and from 1.5 to 16 μg/g, respectively. Compared to the traditional extract methods, it was a simple, rapid, efficient and green method. The results demonstrated that a simple, rapid, efficient and green B/Z-MMSPD was developed for the simultaneous extraction and determination of eight target analytes with different polarities for quality control of Viticis Fructus.
Validation of a Cell Proliferation Assay to Assess the Potency of a Dialyzable Leukocyte Extract Intended for Batch Release
Authors: Carballo-Uicab Gregorio , Linares-Trejo José E. , Mellado-Sánchez Gabriela , López-Morales Carlos A. , Velasco-Velázquez Marco , Pavón Lenin , Estrada-Parra Sergio , Pérez-Tapia Sonia Mayra , Medina-Rivero Emilio
Published: September 2019

Transferon® is a blood product with immunomodulatory properties constituted by a complex mixture of peptides obtained from a human dialyzable leukocyte extract (DLE). Due to its complex nature, it is necessary to demonstrate batch consistency in its biological activity. Potency is the quantitative measure of biological activity and is also a quality attribute of drugs. Here we developed and validated a proliferation assay using Jurkat cells exposed to azathioprine, which is intended to determine the potency of Transferon® according to international guidelines for pharmaceuticals. The assay showed a linear response (2.5 to 40 µg/mL), coefficients of variation from 0.7 to 13.6% demonstrated that the method is precise, while r2 = 0.97 between the nominal and measured values obtained from dilutional linearity showed that the method is accurate. We also demonstrated that the cell proliferation response was specific for Transferon® and was not induced by its vehicle nor by other peptide complex mixtures (glatiramer acetate or hydrolyzed collagen). The bioassay validated here was used to assess the relative potency of eight released batches of Transferon® with respect to a reference standard, showing consistent results. The collective information from the validation and the assessment of several batches indicate that the bioassay is suitable for the release of Transferon®.
Carboxylic Acid Functionalization at the Meso-Position of the Bodipy Core and Its Influence on Photovoltaic Performance
Authors: Ambroz Filip , Donnelly Joanna L. , Wilden Jonathan D. , Macdonald Thomas J. , Parkin Ivan P.
Published: September 2019

Two bodipy dyes with different carboxylic acids on the meso-position of the bodipy core were prepared and used to sensitize TiO2 photoelectrodes. On the basis of spectroscopic characterization, the photoelectrodes were used to fabricate photoelectrochemical cells (PECs) for solar light harvesting. Photovoltaic measurements showed that both bodipy dyes successfully sensitized PECs with short-circuit current densities (JSC) two-fold higher compared to the control. The increase in generated current was attributed to the gain in spectral absorbance due to the presence of bodipy. Finally, the influence of co-sensitization of bodipy and N719 dye was also investigated and photovoltaic device performance discussed.
Multi-Purpose Nanovoid Array Plasmonic Sensor Produced by Direct Laser Patterning
Authors: Pavlov Dmitrii V. , Zhizhchenko Alexey Yu. , Honda Mitsuhiro , Yamanaka Masahito , Vitrik Oleg B. , Kulinich Sergei A. , Juodkazis Saulius , Kudryashov Sergey I. , Kuchmizhak Aleksandr A.
Published: September 2019

We demonstrate a multi-purpose plasmonic sensor based on a nanovoid array fabricated via inexpensive and highly-reproducible direct femtosecond laser patterning of thin glass-supported Au films. The proposed nanovoid array exhibits near-IR surface plasmon (SP) resonances, which can be excited under normal incidence and optimised for specific applications by tailoring the array periodicity, as well as the nanovoid geometric shape. The fabricated SP sensor offers competitive sensitivity of ≈ 1600 nm/RIU at a figure of merit of 12 in bulk refractive index tests, as well as allows for identification of gases and ultra-thin analyte layers, making the sensor particularly useful for common bioassay experiments. Moreover, isolated nanovoids support strong electromagnetic field enhancement at lattice SP resonance wavelength, allowing for label-free molecular identification via surface-enhanced vibration spectroscopy.
Expression of Long Non-Coding RNAs by Human Retinal Müller Glial Cells Infected with Clonal and Exotic Virulent Toxoplasma gondii
Authors: Rochet Elise , Appukuttan Binoy , Ma Yuefang , Ashander Liam M. , Smith Justine R.
Published: September 2019

Retinal infection with Toxoplasma gondii—ocular toxoplasmosis—is a common cause of vision impairment worldwide. Pathology combines parasite-induced retinal cell death and reactive intraocular inflammation. Müller glial cells, which represent the supporting cell population of the retina, are relatively susceptible to infection with T. gondii. We investigated expression of long non-coding RNAs (lncRNAs) with immunologic regulatory activity in Müller cells infected with virulent T. gondii strains—GT1 (haplogroup 1, type I) and GPHT (haplogroup 6). We first confirmed expression of 33 lncRNA in primary cell isolates. MIO-M1 human retinal Müller cell monolayers were infected with T. gondii tachyzoites (multiplicity of infection = 5) and harvested at 4, 12, 24, and 36 h post-infection, with infection being tracked by the expression of parasite surface antigen 1 (SAG1). Significant fold-changes were observed for 31 lncRNAs at one or more time intervals. Similar changes between strains were measured for BANCR, CYTOR, FOXD3-AS1, GAS5, GSTT1-AS1, LINC-ROR, LUCAT1, MALAT1, MIR22HG, MIR143HG, PVT1, RMRP, SNHG15, and SOCS2-AS1. Changes differing between strains were measured for APTR, FIRRE, HOTAIR, HOXD-AS1, KCNQ1OT1, LINC00968, LINC01105, lnc-SGK1, MEG3, MHRT, MIAT, MIR17HG, MIR155HG, NEAT1, NeST, NRON, and PACER. Our findings suggest roles for lncRNAs in regulating retinal Müller cell immune responses to T. gondii, and encourage future studies on lncRNA as biomarkers and/or drug targets in ocular toxoplasmosis.
Measuring Daylight: A Review of Dosimetry in Daylight Photodynamic Therapy
Authors: O’Mahoney Paul , Khazova Marina , Eadie Ewan , Ibbotson Sally
Published: September 2019

Successful daylight photodynamic therapy (DPDT) relies on the interaction of light, photosensitisers and oxygen. Therefore, the ‘dose’ of light that a patient receives during treatment is a clinically relevant quantity, with a minimum dose for effective treatment recommended in the literature. However, there are many different light measurement methods used in the published literature, which may lead to confusion surrounding reliable and traceable dose measurement in DPDT, and what the most appropriate method of light measurement in DPDT might be. Furthermore, for the majority of practitioners who do not carry out any formal dosimetry and for the patients receiving DPDT, building confidence in the evidence supporting this important treatment option is of key importance. This review seeks to clarify the methodology of DPDT and discusses the literature relating to DPDT dosimetry.
Religion and Positive Youth Development: Challenges for Children and Youth with Autism Spectrum Disorder
Authors: Crawford Sullivan Susan , Aramini Victoria
Published: September 2019

While previous research confirms the role religion can play in positive youth development, much existing research leaves out consideration of underrepresented populations. One important underrepresented population is children and youth with autism spectrum disorder (ASD), which now impacts one in 59 children in the United States. Using qualitative data collected from in depth, semi-structured, face-to-face interviews of 53 parents/caregivers, in this article, we analyze barriers and opportunities in religious education for children and youth with autism spectrum disorder. We analyze factors impacting whether parents perceive their children to have a supportive and appropriate religious education experience or an unsupportive and alienating experience. We also provide recommendations for congregations and argue for inclusion of children with autism spectrum disorder in future research on religion and positive youth development.
Integration of Automatic Identification System (AIS) Data and Single-Channel Synthetic Aperture Radar (SAR) Images by SAR-Based Ship Velocity Estimation for Maritime Situational Awareness
Authors: Graziano Maria Daniela , Renga Alfredo , Moccia Antonio
Published: September 2019

The synergic utilization of data from different sources, either ground-based or spaceborne, can lead to effective monitoring of maritime activities. To this end, the integration of synthetic aperture radar (SAR) images with data reported by the automatic identification system (AIS) is of high interest. Accurate matching of ships detected in SAR images with AIS data requires compensation of the azimuth offset, which depends on the ship’s velocity. The existing procedures interpolate the route information gathered by AIS to estimate the ship’s velocity at the epoch of the SAR data, to remove the offset. Matching accuracy is limited by interpolation errors and AIS route information unavailability or uncertainties. This paper proposes the use of SAR-based ship velocity estimations to improve the integration of AIS and SAR data. A case study has been analyzed, in which the method has been tested on TerraSAR-X images collected over the Gulf of Naples, Italy. Presented results show that the matching is improved with respect to standard procedures. The proposed method limits the distance between the AIS report and the SAR-based detection to less than 150 m, which is in line with maritime surveillance needs.
Decision-Making for the Autonomous Navigation of Maritime Autonomous Surface Ships Based on Scene Division and Deep Reinforcement Learning
Authors: Zhang Xinyu , Wang Chengbo , Liu Yuanchang , Chen Xiang
Published: September 2019

This research focuses on the adaptive navigation of maritime autonomous surface ships (MASSs) in an uncertain environment. To achieve intelligent obstacle avoidance of MASSs in a port, an autonomous navigation decision-making model based on hierarchical deep reinforcement learning is proposed. The model is mainly composed of two layers: the scene division layer and an autonomous navigation decision-making layer. The scene division layer mainly quantifies the sub-scenarios according to the International Regulations for Preventing Collisions at Sea (COLREG). This research divides the navigational situation of a ship into entities and attributes based on the ontology model and Protégé language. In the decision-making layer, we designed a deep Q-learning algorithm utilizing the environmental model, ship motion space, reward function, and search strategy to learn the environmental state in a quantized sub-scenario to train the navigation strategy. Finally, two sets of verification experiments of the deep reinforcement learning (DRL) and improved DRL algorithms were designed with Rizhao port as a study case. Moreover, the experimental data were analyzed in terms of the convergence trend, iterative path, and collision avoidance effect. The results indicate that the improved DRL algorithm could effectively improve the navigation safety and collision avoidance.
Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review
Authors: Bustamante Sergio , Manana Mario , Arroyo Alberto , Castro Pablo , Laso Alberto , Martinez Raquel
Published: September 2019

Power transformers are the most important assets of electric power substations. The reliability in the operation of electric power transmission and distribution is due to the correct operation and maintenance of power transformers. The parameters that are most used to assess the health status of power transformers are dissolved gas analysis (DGA), oil quality analysis (OQA) and content of furfuraldehydes (FFA) in oil. The parameter that currently allows for simple online monitoring in an energized transformer is the DGA. Although most of the DGA continues to be done in the laboratory, the trend is online DGA monitoring, since it allows for detection or diagnosis of the faults throughout the life of the power transformers. This study presents a review of the main DGA monitors, single- or multi-gas, their most important specifications, accuracy, repeatability and measurement range, the types of installation, valve or closed loop, and number of analogue inputs and outputs. This review shows the differences between the main existing DGA monitors and aims to help in the selection of the most suitable DGA monitoring approach according to the needs of each case.
Boosting Multi-Vehicle Tracking with a Joint Object Detection and Viewpoint Estimation Sensor
Authors: López-Sastre Roberto , Herranz-Perdiguero Carlos , Guerrero-Gómez-Olmedo Ricardo , Oñoro-Rubio Daniel , Maldonado-Bascón Saturnino
Published: September 2019

In this work, we address the problem of multi-vehicle detection and tracking for traffic monitoring applications. We preset a novel intelligent visual sensor for tracking-by-detection with simultaneous pose estimation. Essentially, we adapt an Extended Kalman Filter (EKF) to work not only with the detections of the vehicles but also with their estimated coarse viewpoints, directly obtained with the vision sensor. We show that enhancing the tracking with observations of the vehicle pose, results in a better estimation of the vehicles trajectories. For the simultaneous object detection and viewpoint estimation task, we present and evaluate two independent solutions. One is based on a fast GPU implementation of a Histogram of Oriented Gradients (HOG) detector with Support Vector Machines (SVMs). For the second, we adequately modify and train the Faster R-CNN deep learning model, in order to recover from it not only the object localization but also an estimation of its pose. Finally, we publicly release a challenging dataset, the GRAM Road Traffic Monitoring (GRAM-RTM), which has been especially designed for evaluating multi-vehicle tracking approaches within the context of traffic monitoring applications. It comprises more than 700 unique vehicles annotated across more than 40.300 frames of three videos. We expect the GRAM-RTM becomes a benchmark in vehicle detection and tracking, providing the computer vision and intelligent transportation systems communities with a standard set of images, annotations and evaluation procedures for multi-vehicle tracking. We present a thorough experimental evaluation of our approaches with the GRAM-RTM, which will be useful for establishing further comparisons. The results obtained confirm that the simultaneous integration of vehicle localizations and pose estimations as observations in an EKF, improves the tracking results.
Temperature Sensor Based on Side-Polished Fiber SPR Device Coated with Polymer
Authors: Liu Shuhui , Cao Shaoqing , Zhang Zhe , Wang Ying , Liao Changrui , Wang Yiping
Published: September 2019

A highly sensitive temperature sensor based on surface plasmon resonance (SPR) of a side-polished single mode fiber is demonstrated. The sensor consists of a gold film coated side-polished fiber covered by a layer of UV-curable adhesive. Before introducing the UV-curable adhesive, the gold-coated fiber exhibits refractive index (RI) sensitivity of 1691.6 nm/RIU to 8800 nm/RIU in the range of 1.32 to 1.43. The resonant wavelength of the SPR sensor shifts to 650 nm when the adhesive is coated on the gold film, and is fixed at about 725 nm when the adhesive is cured. Due to the high thermo-optic and thermal expansion coefficient of the adhesive, the sensor structure achieves a temperature sensitivity of −0.978 nm/°C between 25 °C and 100 °C. The proposed optical fiber SPR sensor is simple, highly sensitive and cost effective, which may find potential applications for temperature measurements in the biomedical and environmental industries.
Identification of Soybean Varieties Using Hyperspectral Imaging Coupled with Convolutional Neural Network
Authors: Zhu Susu , Zhou Lei , Zhang Chu , Bao Yidan , Wu Baohua , Chu Hangjian , Yu Yue , He Yong , Feng Lei
Published: September 2019

Soybean variety is connected to stress resistance ability, as well as nutritional and commercial value. Near-infrared hyperspectral imaging was applied to classify three varieties of soybeans (Zhonghuang37, Zhonghuang41, and Zhonghuang55). Pixel-wise spectra were extracted and preprocessed, and average spectra were also obtained. Convolutional neural networks (CNN) using the average spectra and pixel-wise spectra of different numbers of soybeans were built. Pixel-wise CNN models obtained good performance predicting pixel-wise spectra and average spectra. With the increase of soybean numbers, performances were improved, with the classification accuracy of each variety over 90%. Traditionally, the number of samples used for modeling is large. It is time-consuming and requires labor to obtain hyperspectral data from large batches of samples. To explore the possibility of achieving decent identification results with few samples, a majority vote was also applied to the pixel-wise CNN models to identify a single soybean variety. Prediction maps were obtained to present the classification results intuitively. Models using pixel-wise spectra of 60 soybeans showed equivalent performance to those using the average spectra of 810 soybeans, illustrating the possibility of discriminating soybean varieties using few samples by acquiring pixel-wise spectra.
Online Feature Selection for Robust Classification of the Microbiological Quality of Traditional Vanilla Cream by Means of Multispectral Imaging
Authors: Lianou Alexandra , Mencattini Arianna , Catini Alexandro , Di Natale Corrado , Nychas George-John E. , Martinelli Eugenio , Panagou Efstathios Z.
Published: September 2019

The performance of an Unsupervised Online feature Selection (UOS) algorithm was investigated for the selection of training features of multispectral images acquired from a dairy product (vanilla cream) stored under isothermal conditions. The selected features were further used as input in a support vector machine (SVM) model with linear kernel for the determination of the microbiological quality of vanilla cream. Model training (n = 65) was based on two batches of cream samples provided directly by the manufacturer and stored at different isothermal conditions (4, 8, 12, and 15 °C), whereas model testing (n = 132) and validation (n = 48) were based on real life conditions by analyzing samples from different retail outlets as well as expired samples from the market. Qualitative analysis was performed for the discrimination of cream samples in two microbiological quality classes based on the values of total viable counts [TVC ≤ 2.0 log CFU/g (fresh samples) and TVC ≥ 6.0 log CFU/g (spoiled samples)]. Results exhibited good performance with an overall accuracy of classification for the two classes of 91.7% for model validation. Further on, the model was extended to include the samples in the TVC range 2–6 log CFU/g, using 1 log step to define the microbiological quality of classes in order to assess the potential of the model to estimate increasing microbial populations. Results demonstrated that high rates of correct classification could be obtained in the range of 2–5 log CFU/g, whereas the percentage of erroneous classification increased in the TVC class (5,6) that was close to the spoilage level of the product. Overall, the results of this study demonstrated that the UOS algorithm in tandem with spectral data acquired from multispectral imaging could be a promising method for real-time assessment of the microbiological quality of vanilla cream samples.
Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology
Authors: Yang Yifan , Zhu Ming , Wang Yuqing , Yang Hang , Wu Yanfeng , Li Bei
Published: September 2019

Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively remove noise and high-resolution visualization. The contrast experiments show that the pseudo-color image Kullback–Leiber (KL) entropy of the color image obtained by the method is small, the boundary is obvious, and the noise is small, which provide technical support for the development of sophisticated single-cell imaging Raman spectroscopy instruments.
On-Orbit Signal-to-Noise Ratio Test Method for Night-Light Camera in Luojia 1-01 Satellite Based on Time-Sequence Imagery
Authors: Wang Wei , Zhong Xing , Su Zhiqiang
Published: September 2019

Night-light remote sensing imaging technologies have increasingly attracted attention with the development and application of focal plane arrays. On-orbit signal-to-noise ratio (SNR) test is an important link to evaluate night-light camera’s radiometric performance and the premise for quantitative application of remote sensing imageries. Under night-light illumination conditions, the illuminance of ground objects is very low and varies dramatically, the spatial uniformity of each pixel’s output cannot be guaranteed, and thus the traditional on-orbit test methods represented by variance method are unsuitable for low-resolution night-light cameras. To solve this problem, we proposed an effective on-orbit SNR test method based on consecutive time-sequence images that including the same objects. We analyzed the radiative transfer process between night-light camera and objects, and established a theoretical SNR model based on analysis of the generation and main sources of signal electrons and noise electrons. Finally, we took Luojia 1-01 satellite, the world’s first professional night-light remote sensing satellite, as reference and calculated the theoretical SNR and actual on-orbit SNR using consecutive images captured by Luojia 1-01 satellite. The actual results show the similar characteristics as theoretical results, and are higher than the theoretical results within the reasonable error tolerance, which fully guarantee the detection ability of night-light camera and verify the validity of this time-sequence-based method.
The Concept of Financial Sustainability Measurement: A Case of Food Companies from Northern Europe
Authors: Zabolotnyy Serhiy , Wasilewski Mirosław
Published: September 2019

A managerial approach to the financial sustainability of a company derives from the principle of value maximization for shareholders at an acceptable level of risk, using the best combination of investments and available sources of financing. The research presents the concept of financial sustainability measurement in the example of food companies from Northern Europe. We applied fuzzy logic to quantify complex interrelations among various financial factors and classify companies according to the level of their financial sustainability. A unique combination of factors formed a single complex indicator, which measured a relative level of financial sustainability of food companies. Considering the duality of financial sustainability in terms of risk and return, the relationship framework for synthetic evaluation included the vector of value and the vector of continuity that consisted of such variables as profitability, market capitalization, productivity, operating efficiency, debt, liquidity, interest coverage, and retained earnings. We received evidence that the level of financial sustainability of entities changed in 2005–2015 and was statistically different among sample companies. The proposed method can be applied as a practical tool in a decision-making process to evaluate financial sustainability or other aspects of business performance in larger groups of entities on the basis of various financial criteria.
Combinational Scheduling Model Considering Multiple Vehicle Sizes
Authors: Gong Liang , Li Yinzhen , Xu Dejie
Published: September 2019

Urban public transport is an effective way to solve urban traffic problems and promote sustainable development of urban traffic. A scientific operation scheduling system has an important guiding significance for optimizing the configuration of urban public transport capacity resources, improving the level of operation organization and management, and providing for the sustainability of the transportation system. According to the inhomogeneous distribution of passenger flow along transit lines, this study develops a combinational scheduling model in which the enterprise supplies zonal service based on regular service. The objective function minimizes the sum of passenger travel cost and operation cost, and the simulated annealing algorithm is designed to solve the optimization model. This paper abstracts an ideal example by taking a real-world case of Bus Line 131 in Lanzhou, China. The numerical example is used to verify the validity of the model and algorithm. Results show that the combinational operation scheme can effectively satisfy passengers’ demand and reduce the total cost by 7.03% in comparison with the regular operation system. The optimal combinational system with the lowest total cost can increase the vehicle load factor and improve the utilization ratio.
An Investigation of the Effectiveness of Prefabrication Incentive Policies in China
Authors: Jiang Weiping , Luo Lirong , Wu Zezhou , Fei Jianbo , Antwi-Afari Maxwell Fordjour , Yu Tao
Published: September 2019

Prefabrication is a technology that can reduce the material consumption during the construction process. Thus, it is regarded as a technology that be of assistance in the pursuit of sustainable development in the construction industry. In China, a series of policies has been formulated to promote the implementation of prefabrication; however, the effectiveness of these policies has not been investigated. The aim of this paper is to evaluate the effectiveness of the current prefabrication incentive policies in China. To achieve this research aim, a policy framework was first developed in order to understand the existing policies. Then, four indicators—namely, the number of prefabricated component production enterprises, the prefabricated floor area, the prefabricated building market size, and the expected prefabricated building area ratio—were selected to evaluate each policy’s effectiveness. It was found that the growth rates of these four indicators had increased slowly, and had even shown declining trends before 2015; however, with the incentive policies promulgated after 2015, the growth rates have increased. This study is of value not only in helping readers to understand the existing framework of incentive policies in China, but also in revealing the effectiveness of the identified prefabrication incentive policies. These research findings can also provide insights useful for policy formulation in other jurisdictions for the promotion of prefabrication.
Roles of Tourism Involvement and Place Attachment in Determining Residents’ Attitudes Toward Industrial Heritage Tourism in a Resource-Exhausted City in China
Authors: Yuan Qing , Song HakJun , Chen Nan , Shang Wenwen
Published: September 2019

An in-depth discussion of place attachment in the relationship between residents’ perceived tourism impacts and their support for tourism is still lacking. The predictor of tourism involvement in this relationship has also been underestimated and little attention has been paid to industrial heritage tourism in relation to residents’ attitudes toward tourism development. To fill this gap, we extend upon the existing studies of residents’ attitudes toward tourism with place attachment (both place identity and place dependence) and tourism involvement based on social exchange theory, attitude theory, and the theory of planned behavior. A self-administered survey was completed by 336 residents of Huangshi, a city undergoing a transition to industrial heritage tourism in China. The findings show that residents’ support for tourism is the result of a complete behavior generation process. This has gradually formed through tourism involvement, cognition, affection, and behavior intention, emphasizing the importance of participation and affective attitude in determining residents’ attitudes toward tourism. To maintain the sustainable development of industrial heritage tourism in the economic transition from an old industrial region to new sectors, local authorities should attach more importance to strengthening residents’ native emotional bonds and concentrate on how to encourage local residents to participate in tourism activities.
Facial Expression Recognition: A Survey
Authors: Huang Yunxin , Chen Fei , Lv Shaohe , Wang Xiaodong
Published: September 2019

Facial Expression Recognition (FER), as the primary processing method for non-verbal intentions, is an important and promising field of computer vision and artificial intelligence, and one of the subject areas of symmetry. This survey is a comprehensive and structured overview of recent advances in FER. We first categorise the existing FER methods into two main groups, i.e., conventional approaches and deep learning-based approaches. Methodologically, to highlight the differences and similarities, we propose a general framework of a conventional FER approach and review the possible technologies that can be employed in each component. As for deep learning-based methods, four kinds of neural network-based state-of-the-art FER approaches are presented and analysed. Besides, we introduce seventeen commonly used FER datasets and summarise four FER-related elements of datasets that may influence the choosing and processing of FER approaches. Evaluation methods and metrics are given in the later part to show how to assess FER algorithms, along with subsequent performance comparisons of different FER approaches on the benchmark datasets. At the end of the survey, we present some challenges and opportunities that need to be addressed in future.
RGB Inter-Channel Measures for Morphological Color Texture Characterization
Authors: Durañona Sosa Nelson Luis , Vázquez Noguera José Luis , Cáceres Silva Juan José , García Torres Miguel , Legal-Ayala Horacio
Published: September 2019

The perception of textures is based on high-level features such as symmetry, brightness, color or direction. Texture characterization is a widely studied topic in the image processing community. The normalized volume of morphological series is used as a texture descriptor in RGB images. However, the correlation between different color channels is not exploited with this descriptor. We propose the usage of inter-channel measures in addition to the volume, to enhance the descriptors potential to discriminate textures. The experiments show that standard texture classification techniques increase between 3%–10% in performance when using our descriptor instead of other state of the art descriptors that do not use inter-channel measures.
Synergistic Phytotoxic Effects of Culmorin and Trichothecene Mycotoxins
Authors: Wipfler Rebecca , McCormick Susan , Proctor Robert , Teresi Jennifer , Hao Guixia , Ward Todd , Alexander Nancy , Vaughan Martha
Published: September 2019

Species of the fungus Fusarium cause Fusarium head blight (FHB) of cereal crops and contaminate grain with sesquiterpenoid mycotoxins, including culmorin (CUL) and trichothecenes. While the phytotoxicity of trichothecenes, such as deoxynivalenol (DON), and their role in virulence are well characterized, less is known about the phytotoxicity of CUL and its role in the development of FHB. Herein, we evaluated the phytotoxic effects of purified CUL and CUL-trichothecene mixtures using Chlamydomonas reinhardtii growth and Triticum aestivum (wheat) root elongation assays. By itself, CUL did not affect growth in either system. However, mixtures of CUL with DON, 3-acetyldeoxynivalenol, 15-acetyldeoxynivalenol, or NX-3, but not with nivalenol, inhibited growth in a synergistic manner. Synergistic phytotoxic effects of CUL and DON were also observed on multiple plant varieties and species. The severity of wheat FHB caused by 15 isolates of Fusarium graminearum was negatively correlated with the CUL/DON ratio, but positively correlated with the sum of both CUL and DON. Additionally, during the first week of infection, CUL biosynthetic genes were more highly expressed than the TRI5 trichothecene biosynthetic gene. Furthermore, genomic analysis of Fusarium species revealed that CUL and trichothecene biosynthetic genes consistently co-occur among species closely related to F. graminearum.
The Application of Different Biological Remediation Strategies to PCDDs/PCDFs Contaminated Urban Sediments
Authors: Urbaniak Magdalena , Wyrwicka Anna , Siebielec Grzegorz , Siebielec Sylwia , Kidd Petra , Zieliński Marek
Published: September 2019

Our aim was to assess the efficacy of four different bioremediation strategies applied to soil treated with urban sediments for alleviating soil phytotoxicity (examined using Lepidium sativum), by removing polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), and mitigating the toxic effect on plants by the applied sediment: (1) Natural attenuation, (2) phytoremediation with the use of two plants Tagetes patula L. and Festuca arundinacea, (3) rhizobacterial inoculation with Massilia niastensis p87 and Streptomyces costaricanus RP92 strains, (4) rhizobacteria-assisted phytoremediation with both plants and strains. The applied sediment had a positive influence on L. sativum growth (90% higher than in the unamended soil), mostly due to its high content of nutrients, mainly Ca and Fe, which immobilize pollutants. The positive effect of sediments continued for up to 10-week duration of the experiment; however, the rhizobacterial inoculated samples were characterized by higher growth of L. sativum. The application of rhizobacteria-assisted phytoremediation further increased the growth of L. sativum, and was also found to improve the efficiency of PCDD/PCDF removal, resulting in a maximum 44% reduction of its content. This strategy also alleviated the negative impact of urban sediments on T. patula and F. arundinacea biomass, and had a beneficial effect on protein and chlorophyll content in the studied plants.
The Evaluation of SfM Technique in the Determination of Surface Deformation on Skidding Roads Following Timber Harvesting
Authors: GÜLCİ Sercan , ŞİRELİ Seçkin
Published: September 2019

Forest roads are necessary engineering structures for accessing and managing forestry resources. Considering the difficult terrain and its numerous variable effects, it must be ensured that the capacity of forest roads function adequately and that the road platform is suitable for vehicle traffic. This study aimed to focus on the determination and evaluation of deformation on the surface of the soil roads in the forest using SfM (Structure from Motion) technique. The study focused on the usage opportunity of close-range photogrammetry in the analysis of surface deformation on skidding roads used for forestry operations. Field surveys were conducted on a newly constructed skidding road for forestry operations with a four-wheel farm tractor. The geo-spatial location of the road was obtained by a Total Station (TS) prior to harvesting operation. A digital camera mounted on a 3.5 m high pole was used as a carrier platform in the field survey. The photographs with front and side overlaps (approximately 60% and -80%) were obtained from 95 m segment of the unpaved road. The spatial (X, Y and Z) differences between field measurements- and SfM-based models were compared using Root Mean Square Error (RMSE), and the values of spatial error (SfMXY: 0.048; SfMZ: 0.010 for estimated model) were calculated. The change rate of stable, accumulations and abrasions on the road surface were calculated as 0.165%, 48.642% and 51.192%, respectively. The present study demonstrated that the use of semi-automatic measurement technique offers a promising potential for the evaluation of forest road surface deformation.
КРИМІНАЛЬНО-ПРАВОВА МОДЕЛЬ ПРОТИДІЇ НЕЗАКОННОМУ ЗБАГАЧЕННЮ В УКРАЇНІ
Authors: Вознюк А. , Титко А.
Published: September 2019

У статті розглядаються актуальні проблеми функціонування кримінально-правової моделі протидії незаконному збагаченню в України. Проаналізовано її недоліки, які обумовлені насамперед конструкцією заборонної кримінально-правової норми, а також стандартами доказування, які на сьогодні існують у Кримінальному процесі України. Враховуючи зарубіжний досвід визначено перспективи можливого використання цієї моделі в майбутньому. Розроблено пропозиції щодо підвищення ефективності її функціонування, що передбачають удосконалення положень не лише кримінально-правового, але й інших механізмів протидії незаконному збагаченню в Україні.