bluuebunny/crossref_metadata_2025 huggingface dataset:
A Damage Model Reflecting the Interaction between Delamination and Intralaminar Crack for Failure Analysis of FRP Laminates
Authors: Yun Kumchol , Kwak Songhun , Wang Zhenqing , Chang Mengzhou , Kim Jonggun , Liu Jingbiao , Ri Cholsu
Published: January 2019

In this paper, a progressive damage model reflecting the interaction between delamination and intralaminar crack is developed to predict fracture behaviors and the ultimate load-bearing ability of the fiber-reinforced polymer laminates subject to quasi-static load. Initiation and evolution of intralaminar crack in composites are modeled using a continuum damage mechanics model, which has the capability to reliably predict the discrete crack direction by introducing the crack direction parameter while analyzing the multi-failure of FRP composites. Delamination is modeled using a cohesive zone method with the mixed bilinear law. When the continuum damage model and cohesive zone model are used together, the interactive behavior between multiple failure mechanisms such as delamination induced by matrix cracking often seen in the failure of composite laminates is not generally captured. Interaction between delamination and intralaminar crack in FRP composite structures is investigated in detail and reflected in a finite element analysis in order to eliminate the drawbacks of using both models together. Good agreements between numerical results and experimental data are obtained.
Nanomaterials in Craniofacial Tissue Regeneration: A Review
Authors: Tao Owen , Wu David T. , Pham Hieu M. , Pandey Neelakshi , Tran Simon D.
Published: January 2019

Nanotechnology is an exciting and innovative field when combined with tissue engineering, as it offers greater versatility in scaffold design for promoting cell adhesion, proliferation, and differentiation. The use of nanomaterials in craniofacial tissue regeneration is a newly developing field that holds great potential for treating craniofacial defects. This review presents an overview of the nanomaterials used for craniofacial tissue regeneration as well as their clinical applications for periodontal, vascular (endodontics), cartilage (temporomandibular joint), and bone tissue regeneration (dental implants and mandibular defects). To enhance periodontal tissue regeneration, nanohydroxyapatite was used in conjunction with other scaffold materials, such as polylactic acid, poly (lactic-co-glycolic acid), polyamide, chitosan, and polycaprolactone. To facilitate pulp regeneration along with the revascularization of the periapical tissue, polymeric nanofibers were used to simulate extracellular matrix formation. For temporomandibular joint (cartilage) engineering, nanofibrous-type and nanocomposite-based scaffolds improved tissue growth, cell differentiation, adhesion, and synthesis of cartilaginous extracellular matrix. To enhance bone regeneration for dental implants and mandibular bone defects, nanomaterials such as nanohydroxyapatite composite scaffolds, nanomodified mineral trioxide aggregate, and graphene were tested. Although the scientific knowledge in nanomaterials is rapidly advancing, there remain many unexplored data regarding their standardization, safety, and interactions with the nanoenvironment.
The Characterisation and Quantification of Immobilised Concanavalin A on Quartz Surfaces Based on The Competitive Binding to Glucose and Fluorescent Labelled Dextran
Authors: Hoang Trinh Bich , Stokke Bjørn Torger , Hanke Ulrik , Johannessen Agne , Johannessen Erik Andrew
Published: January 2019

The competition between various carbohydrates in the binding to Concanavalin A (Con A) can be exploited in gravimetric microsensors that detect changes in mass or viscoelasticity as a function of glucose concentration. Such sensors are based on the immobilisation of Con A as the ligand specific element, and a successful application requires that the binding property of Con A is retained. This paper presents a simplified immobilisation procedure of Con A on a quartz surface, a common material for gravimetric microsensors. Structural assessment with atomic force microscopy confirmed that the surface was covered with a layer of macromolecules. This layer shows the presence of entities of various sizes, presumably monomers, dimers and tetramers among which dimers of the Con A are the most dominant structure. Functional assessment using fluorescent labelled dextran (FITC and Alexa 488) suggests a surface coverage ranging from 1.8 × 1011 to 2.1 × 1012 immobilised fluorescent molecules per cm2. The assay was responsive to glucose over a concentration range from 0–40 mM, but became gradually saturated above 20 mM. Hence, the immobilised Con A is able to bind dextran, which is displaced by glucose in a concentration dependent manner, thus triggering a mass change proportional to the MW of dextran.
Governance, Risk, and Compliance in Cloud Scenarios
Authors: Brandis Knud , Dzombeta Srdan , Colomo-Palacios Ricardo , Stantchev Vladimir
Published: January 2019

Cloud computing is changing the way organizations approach technology and its infrastructure. However, in spite of its attractiveness, cloud computing can be seen as a threat in terms of compliance. Given its intrinsic distributed nature, regulations and laws may differ and customers and cloud providers must find a way to balance increasing compliance pressures with cloud computing benefits. In this paper, the authors present a framework aimed to help organizations to cope with compliance aspects in their cloud-oriented environments. Built upon current literature on the topic and qualitative approaches, the framework has been implemented in two organizations. Results from its contribution are encouraging, leading to adopter organizations to less reported compliance violations and higher contribution of cloud computing to overall quality of service and organizational compliance management.
Integrating the Shape Constants of a Novel Material Stress-Strain Characterization Model for Parametric Numerical Analysis of the Deformational Capacity of High-Strength X80-Grade Steel Pipelines
Authors: Ndubuaku Onyekachi , Martens Michael , Cheng J. J. Roger , Adeeb Samer
Published: January 2019

Pipelines typically exhibit significant inelastic deformation under various loading conditions, making it imperative for limit state design to include considerations for the deformational capacity of pipelines. The methods employed to achieve higher strength of API X80 line pipe steels during the plate manufacturing process tend to increase the hardness of the pipe material, albeit at the cost of ductility and strain hardenability. This study features a simple and robust material stress-strain characterization model, which is able to mathematically characterize the shape of a diverse range of stress-strain curves, even for materials with a distinct yield point and an extended yield plateau. Extensive parametric finite element analysis is performed to study the relationship between relevant parameters and the deformational capacity of API X80 pipelines subjected to uniform axial compression, uniform bending, and combined axial compression and bending. Nonlinear regression analysis is employed to develop six nonlinear semi-empirical equations for the critical limit strain, wherein the shape constants of the material model are adapted as dimensionless parameters. The goodness-of-fit of the developed equations was graphically and statistically evaluated, and excellent predictive accuracy was obtained for all six developed equations.
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
Authors: Zeng Junjie , Qin Long , Hu Yue , Hu Cong , Yin Quanjun
Published: January 2019

In this paper, we present a hierarchical path planning framework called SG–RL (subgoal graphs–reinforcement learning), to plan rational paths for agents maneuvering in continuous and uncertain environments. By “rational”, we mean (1) efficient path planning to eliminate first-move lags; (2) collision-free and smooth for agents with kinematic constraints satisfied. SG–RL works in a two-level manner. At the first level, SG–RL uses a geometric path-planning method, i.e., simple subgoal graphs (SSGs), to efficiently find optimal abstract paths, also called subgoal sequences. At the second level, SG–RL uses an RL method, i.e., least-squares policy iteration (LSPI), to learn near-optimal motion-planning policies which can generate kinematically feasible and collision-free trajectories between adjacent subgoals. The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments. The second advantage is that, when the environment changes slightly (i.e., unexpected obstacles appearing), SG–RL does not need to reconstruct subgoal graphs and replan subgoal sequences using SSGs, since LSPI can deal with uncertainties by exploiting its generalization ability to handle changes in environments. Simulation experiments in representative scenarios demonstrate that, compared with existing methods, SG–RL can work well on large-scale maps with relatively low action-switching frequencies and shorter path lengths, and SG–RL can deal with small changes in environments. We further demonstrate that the design of reward functions and the types of training environments are important factors for learning feasible policies.
A New Bloom Filter Architecture for FIB Lookup in Named Data Networking
Authors: Byun Hayoung , Lim Hyesook
Published: January 2019

Network traffic has increased rapidly in recent years, mainly associated with the massive growth of various applications on mobile devices. Named data networking (NDN) technology has been proposed as a future Internet architecture for effectively handling this ever-increasing network traffic. In order to realize the NDN, high-speed lookup algorithms for a forwarding information base (FIB) are crucial. This paper proposes a level-priority trie (LPT) and a 2-phase Bloom filter architecture implementing the LPT. The proposed Bloom filters are sufficiently small to be implemented with on-chip memories (less than 3 MB) for FIB tables with up to 100,000 name prefixes. Hence, the proposed structure enables high-speed FIB lookup. The performance evaluation result shows that FIB lookups for more than 99.99% of inputs are achieved without needing to access the database stored in an off-chip memory.
Breast Cancer Detection in Thermal Infrared Images Using Representation Learning and Texture Analysis Methods
Authors: Abdel-Nasser Mohamed , Moreno Antonio , Puig Domenec
Published: January 2019

Nowadays, breast cancer is one of the most common cancers diagnosed in women. Mammography is the standard screening imaging technique for the early detection of breast cancer. However, thermal infrared images (thermographies) can be used to reveal lesions in dense breasts. In these images, the temperature of the regions that contain tumors is warmer than the normal tissue. To detect that difference in temperature between normal and cancerous regions, a dynamic thermography procedure uses thermal infrared cameras to generate infrared images at fixed time steps, obtaining a sequence of infrared images. In this paper, we propose a novel method to model the changes on temperatures in normal and abnormal breasts using a representation learning technique called learning-to-rank and texture analysis methods. The proposed method generates a compact representation for the infrared images of each sequence, which is then exploited to differentiate between normal and cancerous cases. Our method produced competitive (AUC = 0.989) results when compared to other studies in the literature.
Disturbance Rejection Control Method of Double-Switch Buck-Boost Converter Using Combined Control Strategy
Authors: You Jiang , Fan Weiyan , Yu Lijun , Fu Bin , Liao Mengyan
Published: January 2019

Since it has strong ability to realize a conversion to adapt to a wide variation of input voltage, the double-switch buck-boost (DSBB) converter is usually employed as a front-end converter in two-stage power converter systems, where conversion efficiency is always highly valued. Because there is only one switch in the Pulse Width Modulation (PWM) state in the buck or boost work mode, the combined control scheme was investigated for its advantages in inductor average current and conversion efficiency. However, in this method, the operation mode should be determined by additional logic according to the change of input voltage. Moreover, different control systems should be designed for different operation modes to guarantee dynamic control performance and smooth transition between different work modes. To address these issues, the linear active disturbance rejection control (LADRC) method is introduced to develop an inner current control loop in this paper. In this method, the model deviations in different work modes are considered as a generalized disturbance, and a unified current control plant can be derived for current controller design. Furthermore, the duty cycle limitations in practice are considered, an additional mode for transitional operation is produced, and the corresponding control scheme is also developed. Simulation and experimental test results are provided to validate the correctness and effectiveness of the proposed control scheme.
Relationship between Water Activity and Moisture Content in Floral Honey
Authors: Chen Chiachung
Published: January 2019

The water activity (Aw) and moisture content (MC) data of floral honey at five temperatures were determined using the Aw method and it was found that temperature significantly affected the Aw/MC data. The linear equation could be used to express the relationship between Aw and MC of honeys. The empirical regression equations between parameters and temperature were established. To evaluate the factors affecting the Aw/MC data, we used categorical tests of regression analysis to assess the effect of the correlation between Aw and MC of honey and examined the factors affecting the regression parameters. Six datasets from five countries were selected from the literature. The significance of the levels of qualitative categories was tested by t-test. The slope of the relationship between Aw and MC was affected by the state of honey (liquid and crystallized). The intercepts were significantly affected by honey type (flower or honeydew), harvesting year, geographical collection site, botanical source and other factors. The outliers in the datasets significantly affected the results. With modern regression analysis, useful information on the correlation between Aw and MC could be found. The results indicated that no universal linear equation for Aw and MC could be used. The Aw value could be used as a criterion for the honey industry; then, the MC of honey could be calculated by the specific linear equation between Aw and MC.
Characterization, Antimicrobial Properties and Coatings Application of Gellan Gum Oxidized with Hydrogen Peroxide
Authors: Lu Yushuang , Zhao Xiaojian , Fang Sheng
Published: January 2019

The effect of hydrogen peroxide (H2O2) oxidation on the physicochemical, gelation and antimicrobial properties of gellan gum was studied. The oxidized gellan gum (OGG) was characterized by measuring the carboxyl/carbonyl group contents, Fourier transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H-NMR) spectroscopy. The H2O2 oxidation resulted in a large increase in the carboxyl groups in gellan gum. The OGG lost gelation ability by oxidation even in the presence of metal ions. The antimicrobial activities of the OGG against Gram-positive bacteria (Staphylococcus aureus), Gram-negative bacteria (Escherichia coli), and fungal (Aspergillus niger) were tested. The OGG could inhibit the growth of both bacteria and fungal, and the activity was improved with an increase in the oxidation level. Finally, the application of the OGG as an active coatings material to extend the storage of apples was tested.
Acknowledgement to Reviewers of Foods in 2018
Authors:   Foods Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Special Issue: Computational Analysis of RNA Structure and Function
Authors: Gorodkin Jan
Published: January 2019

RNA structure often plays a key role in determining the function of non-coding and coding transcripts [...]
Salt Weathering of 7th Century CE Granite Monument of Shore Temple, Mahabalipuram—Scientific Investigation and Conservation Strategy
Authors: Kumar S. Vinodh , Singh M. R.
Published: January 2019

Salt-induced deterioration of architectural heritage is accelerated drastically in marine environments. This paper investigates the deterioration mechanism of the Shore Temple using various analytical techniques. Deteriorated and pristine stone samples were analyzed using X-ray fluorescence spectroscopy (XRF), thin section studies, and SEM in order to understand the deterioration mechanism. The meteorological and micro-climatic conditions of Shore Temple in the tropical Indian climate were studied, as they have played a vital role in the deterioration of the stone matrix. The sides of the temple that face the sea as well as the upper part of the temple show intense alveolarization and the stone variety was petrologically identified as “garnetiferous hornblende biotite granite”. The evaluation of results in terms of the efficacy of ethyl silicate consolidation of stone after desalination is very difficult due to continuous sea sprays. The compatible lime rendering evidenced in the shelter area and then scientifically examined during this study may be applied as a protective layer to safeguard and conserve the lone Pallava edifice on the seashore from deterioration in tropical and hygric saline conditions.
Organ-Specific Analysis of Morus alba Using a Gel-Free/Label-Free Proteomic Technique
Authors: Zhu Wei , Zhong Zhuoheng , Liu Shengzhi , Yang Bingxian , Komatsu Setsuko , Ge Zhiwei , Tian Jingkui
Published: January 2019

Morus alba is an important medicinal plant that is used to treat human diseases. The leaf, branch, and root of Morus can be applied as antidiabetic, antioxidant, and anti-inflammatory medicines, respectively. To explore the molecular mechanisms underlying the various pharmacological functions within different parts of Morus, organ-specific proteomics were performed. Protein profiles of the Morus leaf, branch, and root were determined using a gel-free/label-free proteomic technique. In the Morus leaf, branch, and root, a total of 492, 414, and 355 proteins were identified, respectively, including 84 common proteins. In leaf, the main function was related to protein degradation, photosynthesis, and redox ascorbate/glutathione metabolism. In branch, the main function was related to protein synthesis/degradation, stress, and redox ascorbate/glutathione metabolism. In root, the main function was related to protein synthesis/degradation, stress, and cell wall. Additionally, organ-specific metabolites and antioxidant activities were analyzed. These results revealed that flavonoids were highly accumulated in Morus root compared with the branch and leaf. Accordingly, two root-specific proteins named chalcone flavanone isomerase and flavonoid 3,5-hydroxylase were accumulated in the flavonoid pathway. Consistent with this finding, the content of the total flavonoids was higher in root compared to those detected in branch and leaf. These results suggest that the flavonoids in Morus root might be responsible for its biological activity and the root is the main part for flavonoid biosynthesis in Morus.
Novel DnaJ Protein Facilitates Thermotolerance of Transgenic Tomatoes
Authors: Wang Guodong , Cai Guohua , Xu Na , Zhang Litao , Sun Xiuling , Guan Jing , Meng Qingwei
Published: January 2019

DnaJ proteins, which are molecular chaperones that are widely present in plants, can respond to various environmental stresses. At present, the function of DnaJ proteins was studied in many plant species, but only a few studies were conducted in tomato. Here, we examined the functions of a novel tomato (Solanum lycopersicum) DnaJ protein (SlDnaJ20) in heat tolerance using sense and antisense transgenic tomatoes. Transient conversion assays of Arabidopsis protoplasts showed that SlDnaJ20 was targeted to chloroplasts. Expression analysis showed that SlDnaJ20 expression was induced by chilling, NaCl, polyethylene glycol, and H2O2, especially via heat stress. Under heat stress, sense plants showed higher fresh weights, chlorophyll content, fluorescence (Fv/Fm), and D1 protein levels, and a lower accumulation of reactive oxygen species (ROS) than antisense plants. These results suggest that SlDnaJ20 overexpression can reduce the photoinhibition of photosystem II (PSII) by relieving ROS accumulation. Moreover, higher expression levels of HsfA1 and HsfB1 were observed under heat stress in sense plants, indicating that SlDnaJ20 overexpression contributes to HSF expression. The yeast two-hybrid system proved that SlDnaJ20 can interact with the chloroplast heat-shock protein 70. Our results indicate that SlDnaJ20 overexpression enhances the thermotolerance of transgenic tomatoes, whereas suppression of SlDnaJ20 increases the heat sensitivity of transgenic tomatoes.
A Hybrid Hamiltonian for the Accelerated Sampling along Experimental Restraints
Authors: Peter Emanuel K. , Černý Jiří
Published: January 2019

In this article, we present an enhanced sampling method based on a hybrid Hamiltonian which combines experimental distance restraints with a bias dependent from multiple path-dependent variables. This simulation method determines the bias-coordinates on the fly and does not require a priori knowledge about reaction coordinates. The hybrid Hamiltonian accelerates the sampling of proteins, and, combined with experimental distance information, the technique considers the restraints adaptively and in dependency of the system’s intrinsic dynamics. We validate the methodology on the dipole relaxation of two water models and the conformational landscape of dialanine. Using experimental NMR-restraint data, we explore the folding landscape of the TrpCage mini-protein and in a second example apply distance restraints from chemical crosslinking/mass spectrometry experiments for the sampling of the conformation space of the Killer Cell Lectin-like Receptor Subfamily B Member 1A (NKR-P1A). The new methodology has the potential to adaptively introduce experimental restraints without affecting the conformational space of the system along an ergodic trajectory. Since only a limited number of input- and no-order parameters are required for the setup of the simulation, the method is broadly applicable and has the potential to be combined with coarse-graining methods.
Review of Current Strategies for Delivering Alzheimer’s Disease Drugs across the Blood-Brain Barrier
Authors: Wong Ka Hong , Riaz Muhammad Kashif , Xie Yuning , Zhang Xue , Liu Qiang , Chen Huoji , Bian Zhaoxiang , Chen Xiaoyu , Lu Aiping , Yang Zhijun
Published: January 2019

Effective therapy for Alzheimer’s disease is a major challenge in the pharmaceutical sciences. There are six FDA approved drugs (e.g., donepezil, memantine) that show some effectiveness; however, they only relieve symptoms. Two factors hamper research. First, the cause of Alzheimer’s disease is not fully understood. Second, the blood-brain barrier restricts drug efficacy. This review summarized current knowledge relevant to both of these factors. First, we reviewed the pathophysiology of Alzheimer’s disease. Next, we reviewed the structural and biological properties of the blood-brain barrier. We then described the most promising drug delivery systems that have been developed in recent years; these include polymeric nanoparticles, liposomes, metallic nanoparticles and cyclodextrins. Overall, we aim to provide ideas and clues to design effective drug delivery systems for penetrating the blood-brain barrier to treat Alzheimer’s disease.
Cytokine Modulation in Breast Cancer Patients Undergoing Radiotherapy: A Revision of the Most Recent Studies
Authors: Marconi Raffaella , Serafini Annalisa , Giovanetti Anna , Bartoleschi Cecilia , Pardini Maria Chiara , Bossi Gianluca , Strigari Lidia
Published: January 2019

Breast cancer (BC) is the most common tumor and the second cause for cancer-related death in women worldwide, although combined treatments are well-established interventions. Several effects seem to be responsible for poor outcomes in advanced or triple-negative BC patients. Focusing on the interaction of ionizing radiation with tumor and normal tissues, the role of cytokine modulation as a surrogate of immunomodulation must still be explored. In this work, we carried out an overview of studies published in the last five years involving the cytokine profile in BC patients undergoing radiotherapy. The goal of this review was to evaluate the profile and modulation of major cytokines and interleukins as potential biomarkers of survival, treatment response, and toxicity in BC patient undergoing radiotherapy. Out of 47 retrieved papers selected using PubMed search, 15 fulfilled the inclusion criteria. Different studies reported that the modulation of specific cytokines was time- and treatment-dependent. Radiotherapy (RT) induces the modulation of inflammatory cytokines up to 6 months for most of the analyzed cytokines, which in some cases can persist up to several years post-treatment. The role of specific cytokines as prognostic and predictive of radiotherapy outcome is critically discussed.
Regulatory Effect of Bacillus subtilis on Cytokines of Dendritic Cells in Grass Carp (Ctenopharyngodon Idella)
Authors: Zhou Chengchong , Wang Hui , Li Xige , Luo Yaner , Xie Mengqi , Wu Zhixin , Chen Xiaoxuan
Published: January 2019

Bacillus subtilis is a common group of probiotics that have been widely used in the feed industry as they can increase host resistance to pathogens and balance the immune response. However, the regulatory mechanism of Bacillus subtilis on the host immune system remains unclear in teleosts. In this study, we isolated and enriched dendritic cells from white blood cells (WBCs), and then stimulated them with Bacillus subtilis. Morphological features, specific biological functions, and authorized functional molecular markers were used in the identification of dendritic cells. Subsequently, we collected stimulated cells at 0, 4, and 18 h, and then constructed and sequenced the transcriptomic libraries. A transcriptome analysis showed that 2557 genes were up-regulated and 1708 were down-regulated at 4 h compared with the control group (|Fold Change| ≥ 4), and 1131 genes were up-regulated and 1769 were down-regulated between the cells collected at 18 h and 4 h (|Fold Change| ≥ 4). Gene Ontology (GO) annotations suggested many differentially expressed genes (DEGs) (p < 0.05 and |Fold Change| ≥ 4) were involved in immune-related biological functions including immune system progress, cytokine receptor binding, and cytokine binding. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the cytokine–cytokine receptor interaction pathways were significantly enriched at both time points (p < 0.05), which may play a key role in the response to stimulation. Furthermore, mRNA expression level examination of several pro-inflammatory cytokines and anti-inflammatory cytokines genes by quantitative real-time polymerase chain reaction (qRT-PCR) indicated that their expressions can be significantly increased in Bacillus subtili, which suggest that Bacillus subtilis can balance immune response and tolerance. This study provides dendritic cell (DC)-specific transcriptome data in grass carp by Bacillus subtilis stimulation, allowing us to illustrate the molecular mechanism of the DC-mediated immune response triggered by probiotics in grass carp.
Gut-Liver Axis, Gut Microbiota, and Its Modulation in the Management of Liver Diseases: A Review of the Literature
Authors: Milosevic Ivana , Vujovic Ankica , Barac Aleksandra , Djelic Marina , Korac Milos , Radovanovic Spurnic Aleksandra , Gmizic Ivana , Stevanovic Olja , Djordjevic Vladimir , Lekic Nebojsa , Russo Edda , Amedei Amedeo
Published: January 2019

The rapid scientific interest in gut microbiota (GM) has coincided with a global increase in the prevalence of infectious and non-infectivous liver diseases. GM, which is also called “the new virtual metabolic organ”, makes axis with a number of extraintestinal organs, such as kidneys, brain, cardiovascular, and the bone system. The gut-liver axis has attracted greater attention in recent years. GM communication is bi-directional and involves endocrine and immunological mechanisms. In this way, gut-dysbiosis and composition of “ancient” microbiota could be linked to pathogenesis of numerous chronic liver diseases such as chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), development of liver cirrhosis, and hepatocellular carcinoma (HCC). In this paper, we discuss the current evidence supporting a GM role in the management of different chronic liver diseases and potential new therapeutic GM targets, like fecal transplantation, antibiotics, probiotics, prebiotics, and symbiotics. We conclude that population-level shifts in GM could play a regulatory role in the gut-liver axis and, consequently, etiopathogenesis of chronic liver diseases. This could have a positive impact on future therapeutic strategies.
Predicting Intensification on the Brazilian Agricultural Frontier: Combining Evidence from Lab-In-The-Field Experiments and Household Surveys
Authors: Bragança Arthur , Cohn Avery Simon
Published: January 2019

The expansion of crop agriculture onto low productivity cattle pastures in the agricultural frontier of Brazil is a form of agricultural intensification that can help to contribute to global food and climate goals. However, the amount of pasture to crop conversion in the region lags both agronomic and economic potential. We administered a survey in combination with a lab-in-the-field experiment to 559 farmers in Mato Grosso, Brazil. We used the results to explore behavioral determinants of pasture to crop conversion. We compared subjects’ choices across two rounds of a risk game meant to mimic the economic risk of decisions to convert pasture to crops. We found framing the risk game to concern agriculture profoundly altered subjects’ experimental choices. These discrepancies involved the majority of experimental subjects, and were highly heterogenous in nature. They were also somewhat predictive of subjects’ behavior converting pasture to cropland. Our findings indicate that farmers may make economic decisions involving agriculture and/or agricultural land differently from other economic decisions. Our finding are of relevance for research into the propensity of farmers to intensify and for policies seeking to influence rates of agricultural intensification.
Acknowledgement to Reviewers of Marine Drugs in 2018
Authors:   Marine Drugs Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Influence of Ellagitannins Extracted by Pomegranate Fruit on Disulfide Isomerase PDIA3 Activity
Authors: Altieri Fabio , Cairone Francesco , Giamogante Flavia , Carradori Simone , Locatelli Marcello , Chichiarelli Silvia , Cesa Stefania
Published: January 2019

Pomegranate fruit is a functional food of high interest for human health due to its wide range of phytochemicals with antioxidant properties are implicated in the prevention of inflammation and cancer. Ellagitannins, such as punicalagin and ellagic acid, play a role as anti-atherogenic and neuroprotective molecules in the complex fighting against the degenerative diseases. The aim of this work was to evaluate the composition in punicalagins and ellagic acid of differently obtained extracts from whole fruit, peels and juices, prepared by squeezing or by centrifugation, of pomegranate belonging to different cultivars. Moreover, a wider phenolic fingerprint was also determined. The bioactivity of the extracts was tested on the redox activity of PDIA3 disulfide isomerase, an enzyme involved in the regulation of several cellular functions and associated with different diseases such as cancer, prion disorders, Alzheimer’s and Parkinson’s diseases. The results demonstrate that the different ratios between punicalagin and ellagic acid modulate the enzyme activity and other ellagitannins could interfere with this activity.
Glucose Response during the Night Is Suppressed by Wheat Albumin in Healthy Participants: A Randomized Controlled Trial
Authors: Saito Shinichiro , Oishi Sachiko , Shudo Aiko , Sugiura Yoko , Yasunaga Koichi
Published: January 2019

Postprandial blood glucose excursions are important for achieving optimal glycemic control. In normal-weight individuals, glucose tolerance is diminished in the evening compared to glucose tolerance in the morning. Wheat albumin (WA) has the potential to suppress the postprandial glucose response with a relatively small dose, compared to the dose required when using dietary fiber. In the present study, the effect of WA on glycemic control during the night was investigated after a late evening meal. A randomly assigned crossover trial involving a single oral ingestion in healthy male participants was performed in a double-blind placebo-controlled manner. The participants ingested the placebo (PL) tablets or the WA (1.5 g)-containing tablets 3 min before an evening meal at 22:00 hour, and blood samples were drawn during the night until 07:00 hour using an intravenous cannula. The participants slept from 00:30 hour to 06:30 hour. Glucose response, as a primary outcome during the night, was suppressed significantly by the WA treatment compared to the PL treatment, but the insulin response was not. Plasma glucose-dependent insulinotropic polypeptide concentration during the night was lowered significantly by the WA treatment compared to the PL treatment. In conclusion, WA may be a useful food constituent for glycemic control during the night.
The Formation of Glycerol Oligomers with Two New Types of End Groups in the Presence of a Homogeneous Alkaline Catalyst
Authors: Kansy Dawid , Bosowska Kornelia , Czaja Krystyna , Poliwoda Anna
Published: January 2019

The purpose of this work was to synthesize and characterize oligoglycerols with the chains of more than four repeating units. Those oligoglycerols may have some interesting applications, among others, as polyoxyalkylation starters. The glycerol oligomerization process was carried out during 12 h, at 230 °C, under the pressure of 0.4 bar, with the use of sodium carbonate as a homogeneous basic catalyst; various concentrations of the catalyst in the reaction medium were used. The reaction products were analyzed with the use of direct infusion electrospray ionization mass spectrometry (ESI-MS), nuclear magnetic resonance (13C NMR) and Fourier transform infrared spectroscopy (FTIR) techniques. Based on the analytical findings, the compositions of the obtained product mixtures and the structures of oligoglycerols present in individual fractions were determined. The effect of catalyst concentration on the composition of the post-reaction mixture was observed. Moreover, in addition to the conventional linear oligomers (α,α-oligoglycerols), two new types of the oligomers were for the first time detected in the post-reaction mixture: one with two hydroxyl groups and the other with a carboxylate group at the α-carbon atom.
Characterization, Expression Profiling, and Functional Analyses of a 4CL-Like Gene of Populus trichocarpa
Authors: Wei Hui , Xu Chen , Movahedi Ali , Sun Weibo , Zhuge Qiang
Published: January 2019

Adenosine 5′-monophosphate (AMP) (adenylate)-forming acetyl-CoA synthetase (ACS) catalyzes the formation of acetyl-coenzyme A (CoA), and the ACS family is closely related to the 4-coumarate CoA ligase (4CL) family. In this study, a 4CL-like gene was cloned from Populus trichocarpa and named Pt4CL-like. Characterization of Pt4CL-like, using bioinformatics, showed that it contained box I and box II domains at the end of the C-terminal sequence, and there is a characteristic sequence of ACS, namely, peroxisome-targeting sequence (PTS). Real-time PCR results showed that the 4CL-like gene was expressed in all tissues tested, and was highly expressed in the stems. A denaturation and renaturation process was conducted, and the recombinant Pt4CL-like protein was purified through HisTrapTM high performance affinity chromatography. It showed Pt4CL-like protein did not catalyze substrates of 4CL, but could significantly catalyzed sodium acetate. These results indicate that Pt4CL-like protein belongs to the ACS family, providing a theoretical basis for further analysis and comparison of the functions of adenylate-forming enzymes and 4CL family.
China: Some Exceptions of Secularization Thesis
Authors: Liao Xianghui
Published: January 2019

The aim of this article is to present the controversial features of the secularization thesis about Chinese religions performed via analyzing the newly published Chinese religious policy named The Several Opinions on Further Governance of Commercial Problems in Buddhism and Taoism. This article proposes a complex hypothesis: (1) though the public influence of religion has acquired momentum of expansion in China, the growth and expansion of Chinese religions accompanied the decline of private religiosity; (2) Chinese religions possess controversial features of secularization: though they experience the reduction of their power, range of control, and prestige, meanwhile they embrace the increase in numbers of members, intensity, frequency, and importance of public life; (3) Nonreligious factors play an important role in promoting the growth of Chinese religions temporarily, while religious factors will be responsible for resurgence of Chinese religions chronically. This paper is the first in a series to apply the secularization thesis to Chinese religions.
The Frequency Selective Effect of Radar Backscattering from Multiscale Sea Surface
Authors: Xie Dengfeng , Chen Kun-Shan , Zeng Jiangyuan
Published: January 2019

The sea surface essentially contains multiscale roughness with capillary waves of many sizes riding on large-scale waves that are also of many sizes. It is instructive to exploit the effect of radar frequency and observation geometry on the effective roughness scales responsible for radar backscattering so that the scattering mechanism and the scattering source can be better understood and quantitated. Based on common sea spectra and a theoretical scattering model, an attempt is made to attain the above objective. Model predictions, with selective roughness scales, are compared with wide validation data, including L-band radar observations, and predictions from C-band and Ku-band empirical models: geophysical model function (CMOD7) and NASA scatterometer (NSCAT-4) for C- and Ku-bands at different incident angles. Numerical results indicate that effective roughness scales for radar backscattering vary with radar frequency and incidence angle and are related to a portion of sea spectral components; the low limit of which is linearly proportional to the Bragg wavenumber determined by frequency and incidence angle, and the scale factor of the linear relationship is about 0.05. In addition, the root mean square (RMS) height and the correlation length of the effective roughness (i.e., scattering source) derived from the effective roughness decrease gradually as incident angle increases. In particular, the correlation length also linearly depends on the effective wavelength with a coefficient of 3.2. Moreover, these two coefficients are both independent of wind speed, radar frequency, and incident angle. These findings also reveal the essential properties of the spectral components contributing to radar backscattering and its variation with radar frequency and incident angle.
Using the Bayesian Network to Map Large-Scale Cropping Intensity by Fusing Multi-Source Data
Authors: Tao Jianbin , Wu Wenbin , Xu Meng
Published: January 2019

Global food demand will increase over the next few decades, and sustainable agricultural intensification on current cropland may be a preferred option to meet this demand. Mapping cropping intensity with remote sensing data is of great importance for agricultural production, food security, and agricultural sustainability in the context of global climate change. However, there are some challenges in large-scale cropping intensity mapping. First, existing indicators are too coarse, and fine indicators for measuring cropping intensity are lacking. Second, the regional, intra-class variations detected in time-series remote sensing data across vast areas represent environment-related clusters for each cropping intensity level. However, few existing studies have taken into account the intra-class variations caused by varied crop patterns, crop phenology, and geographical differentiation. In this research, we first presented a new definition, a normalized cropping intensity index (CII), to quantify cropping intensity precisely. We then proposed a Bayesian network model fusing prior knowledge (BNPK) to address the issue of intra-class variations when mapping CII over large areas. This method can fuse regional differentiation factors as prior knowledge into the model to reduce the uncertainty. Experiments on five sample areas covering the main grain-producing areas of mainland China proved the effectiveness of the model. Our research proposes the framework of obtain a CII map with both a finer spatial resolution and a fine temporal resolution at a national scale.
Superpixel-Guided Layer-Wise Embedding CNN for Remote Sensing Image Classification
Authors: Liu Han , Li Jun , He Lin , Wang Yu
Published: January 2019

Irregular spatial dependency is one of the major characteristics of remote sensing images, which brings about challenges for classification tasks. Deep supervised models such as convolutional neural networks (CNNs) have shown great capacity for remote sensing image classification. However, they generally require a huge labeled training set for the fine tuning of a deep neural network. To handle the irregular spatial dependency of remote sensing images and mitigate the conflict between limited labeled samples and training demand, we design a superpixel-guided layer-wise embedding CNN (SLE-CNN) for remote sensing image classification, which can efficiently exploit the information from both labeled and unlabeled samples. With the superpixel-guided sampling strategy for unlabeled samples, we can achieve an automatic determination of the neighborhood covering for a spatial dependency system and thus adapting to real scenes of remote sensing images. In the designed network, two types of loss costs are combined for the training of CNN, i.e., supervised cross entropy and unsupervised reconstruction cost on both labeled and unlabeled samples, respectively. Our experimental results are conducted with three types of remote sensing data, including hyperspectral, multispectral, and synthetic aperture radar (SAR) images. The designed SLE-CNN achieves excellent classification performance in all cases with a limited labeled training set, suggesting its good potential for remote sensing image classification.
Optimal Placement of Virtual Masses for Structural Damage Identification
Authors: Hou Jilin , Li Zhenkun , Zhang Qingxia , Zhou Runfang , Jankowski Łukasz
Published: January 2019

Adding virtual masses to a structure is an efficient way to generate a large number of natural frequencies for damage identification. The influence of a virtual mass can be expressed by Virtual Distortion Method (VDM) using the response measured by a sensor at the involved point. The proper placement of the virtual masses can improve the accuracy of damage identification, therefore the problem of their optimal placement is studied in this paper. Firstly, the damage sensitivity matrix of the structure with added virtual masses is built. The Volumetric Maximum Criterion of the sensitivity matrix is established to ensure the mutual independence of measurement points for the optimization of mass placement. Secondly, a method of sensitivity analysis and error analysis is proposed to determine the values of the virtual masses, and then an improved version of the Particle Swarm Optimization (PSO) algorithm is proposed for placement optimization of the virtual masses. Finally, the optimized placement is used to identify the damage of structures. The effectiveness of the proposed method is verified by a numerical simulation of a simply supported beam structure and a truss structure.
Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
Authors: Han Fangfang , Liu Bin , Zhu Junchao , Zhang Baofeng
Published: January 2019

For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Especially, the existence of noise in industrial field environment makes the extraction of fuzzy edges become a more difficult problem when analyzing the posture of a high-speed moving target. Because noise and edge are always both the kind of high-frequency information, it is difficult to make trade-offs only by frequency bands. In this paper, a noise-tolerant edge detection method based on the correlation relationship between layers of wavelet transform coefficients is proposed. The goal of the paper is not to recover a clean image from a noisy observation, but to make a trade-off judgment for noise and edge signal directly according to the characteristics of wavelet transform coefficients, to realize the extraction of edge information from a noisy image directly. According to the wavelet coefficients tree and the Lipschitz exponent property of noise, the idea of neural network activation function is adopted to design the activation judgment method of wavelet coefficients. Then the significant wavelet coefficients can be retained. At the same time, the non-significant coefficients were removed according to the method of judgment of isolated coefficients. On the other hand, based on the design of Daubechies orthogonal compactly-supported wavelet filter, rational coefficients wavelet filters can be designed by increasing free variables. By reducing the vanishing moments of wavelet filters, more high-frequency information can be retained in the wavelet transform fields, which is benefit to the application of edge detection. For a noisy image of high-speed moving targets with fuzzy edges, by using the length 8-4 rational coefficients biorthogonal wavelet filters and the algorithm proposed in this paper, edge information could be detected clearly. Results of multiple groups of comparative experiments have shown that the edge detection effect of the proposed algorithm in this paper has the obvious superiority.
Metasurfaces for Advanced Sensing and Diagnostics
Authors: La Spada Luigi
Published: January 2019

Interest in sensors and their applications is rapidly evolving, mainly driven by the huge demand of technologies whose ultimate purpose is to improve and enhance health and safety. Different electromagnetic technologies have been recently used and achieved good performances. Despite the plethora of literature, limitations are still present: limited response control, narrow bandwidth, and large dimensions. MetaSurfaces, artificial 2D materials with peculiar electromagnetic properties, can help to overcome such issues. In this paper, a generic tool to model, design, and manufacture MetaSurface sensors is developed. First, their properties are evaluated in terms of impedance and constitutive parameters. Then, they are linked to the structure physical dimensions. Finally, the proposed method is applied to realize devices for advanced sensing and medical diagnostic applications: glucose measurements, cancer stage detection, water content recognition, and blood oxygen level analysis. The proposed method paves a new way to realize sensors and control their properties at will. Most importantly, it has great potential to be used for many other practical applications, beyond sensing and diagnostics.