bluuebunny/crossref_metadata_2025 huggingface dataset:
Antibacterial Effect of Carbosilane Metallodendrimers in Planktonic Cells of Gram-Positive and Gram-Negative Bacteria and Staphylococcus aureus Biofilm
Authors: Llamazares Celia , Sanz del Olmo Natalia , Ortega Paula , Gómez Rafael , Soliveri Juan , de la Mata F. Javier , García-Gallego Sandra , Copa-Patiño José Luis
Published: August 2019

Antibiotic resistance is currently one of the main threats to public health security. Biofilm formation is a resistance mechanism that is responsible for most human bacterial infections and requires new and effective therapeutic approaches, such as those provided by nanotechnology. In this work, the antibacterial effect of carbosilane metallodendrimers with different metals (copper(II) and ruthenium(II)), ligands (chloride and nitrate) and generations (generation 0, 1 and 2) has been studied using planktonic Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria. Furthermore, the ability of the metallodendrimers to avoid the formation of S. aureus biofilms was also evaluated. The results showed a promising biocide activity in both types of planktonic bacteria, especially for first-generation dendrimers, which arises from the metal complexation to the dendrimer. Cu(II) metallodendrimers require lower concentration than Ru(II) counterpart to inhibit the production of S. aureus biofilms, but none produce hemolysis at the inhibitory concentrations and can be safely used as antibacterial agents. In particular, the first-generation Cu(II) metallodendrimer with nitrate ligands displayed the most promising properties to continue with further studies in both planktonic cells and biofilms.
The Impact of Basalt Components on the Structure of Bricks Formed as a Result of Hydrothermal Treatment
Authors: Stepien Anna , Kostrzewa Paulina
Published: August 2019

The article focuses on brick products, the production of which is based on natural components, such as lime (CaO), quartz sand (SiO2) and water (H2O), and which are created during the process of the so-called hydrothermal treatment. In the production process of the modified brick, basalt components (basalt aggregate, with graining of 2–4 mm, basalt powder and basalt fibers) were used because of their natural origin, mineralogical composition, high volume density, and possibly minimal absorbability. In the article thermodynamic properties of minerals forming the construction of basalt components were determined, as well as the phases that arise during the autoclaving process. Compressive strength and density were investigated due to acoustic properties. The product modified with basalt aggregate shows decrease in water absorption as a result of capillary action and in absorbability up to 9% (in the reference sample up to 16%). The sample with basalt aggregate shows compressive resistance of 33 MPa on average, with the increase of volume density to 2.29 kg/dm3. Modification of sand-lime mixture presented satisfying results with 10% basalt powder additive. Application of basalt fibers slightly changed the volume density and absorbability compared with the norm sample. However, it affected the compressive resistance.
Circular and Flexible Indoor Partitioning—A Design Conceptualization of Innovative Materials and Value Chains
Authors: Geldermans Bob , Tenpierik Martin , Luscuere Peter
Published: August 2019

This article sheds light on the materialization and operation of residential partitioning wall components in relation to circular and flexible performance. The hypothesis is twofold: (1) A stronger integration of materialization and operation aspects is indispensable in establishing sustainable value-models, and (2) recent innovations, concerning the reversibility of material connections, will help disrupting the status-quo in that respect. Attention is drawn to renewable natural fibre composites (NFC), reversible adhesives, and biodegradable insulation materials. After a background sketch regarding the notion of time, change, and material circularity in design and planning, the housing challenge in the Amsterdam metropolitan area (AMA, the Netherlands) is described. Next, a design conceptualization stage is introduced, informed by two methods and tools in particular: Circ-Flex assessment, and activity-based spatial material flow analysis. Results of the conceptualization stage are presented regarding materialization and operation, culminating in Circ-Flex partitioning components, more specifically: Side panels and insulation. It was found that NFC can tackle current issues relating, most prominently, to circularity performance. Associated modifications in the value-chain occur, above all, in raw material sourcing, manufacturing, reutilization logistics, and data-sharing. The outcomes are valid for multiple building components other than indoor partitioning, such as kitchens and furniture, but also insulation—and interior side-sheeting—of walls and roofs in energy-renovations.
Cancer Diagnosis Using Deep Learning: A Bibliographic Review
Authors: Munir Khushboo , Elahi Hassan , Ayub Afsheen , Frezza Fabrizio , Rizzi Antonello
Published: August 2019

In this paper, we first describe the basics of the field of cancer diagnosis, which includes steps of cancer diagnosis followed by the typical classification methods used by doctors, providing a historical idea of cancer classification techniques to the readers. These methods include Asymmetry, Border, Color and Diameter (ABCD) method, seven-point detection method, Menzies method, and pattern analysis. They are used regularly by doctors for cancer diagnosis, although they are not considered very efficient for obtaining better performance. Moreover, considering all types of audience, the basic evaluation criteria are also discussed. The criteria include the receiver operating characteristic curve (ROC curve), Area under the ROC curve (AUC), F1 score, accuracy, specificity, sensitivity, precision, dice-coefficient, average accuracy, and Jaccard index. Previously used methods are considered inefficient, asking for better and smarter methods for cancer diagnosis. Artificial intelligence and cancer diagnosis are gaining attention as a way to define better diagnostic tools. In particular, deep neural networks can be successfully used for intelligent image analysis. The basic framework of how this machine learning works on medical imaging is provided in this study, i.e., pre-processing, image segmentation and post-processing. The second part of this manuscript describes the different deep learning techniques, such as convolutional neural networks (CNNs), generative adversarial models (GANs), deep autoencoders (DANs), restricted Boltzmann’s machine (RBM), stacked autoencoders (SAE), convolutional autoencoders (CAE), recurrent neural networks (RNNs), long short-term memory (LTSM), multi-scale convolutional neural network (M-CNN), multi-instance learning convolutional neural network (MIL-CNN). For each technique, we provide Python codes, to allow interested readers to experiment with the cited algorithms on their own diagnostic problems. The third part of this manuscript compiles the successfully applied deep learning models for different types of cancers. Considering the length of the manuscript, we restrict ourselves to the discussion of breast cancer, lung cancer, brain cancer, and skin cancer. The purpose of this bibliographic review is to provide researchers opting to work in implementing deep learning and artificial neural networks for cancer diagnosis a knowledge from scratch of the state-of-the-art achievements.
Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways
Authors: Bax Carmen , Lotesoriere Beatrice Julia , Sironi Selena , Capelli Laura
Published: August 2019

Cancer is one of the major causes of mortality worldwide and its already large burden is projected to increase significantly in the near future with a predicted 22 million new cancer cases and 13 million cancer-related deaths occurring annually by 2030. Unfortunately, current procedures for diagnosis are characterized by low diagnostic accuracies. Given the proved correlation between cancer presence and alterations of biological fluid composition, many researchers suggested their characterization to improve cancer detection at early stages. This paper reviews the information that can be found in the scientific literature, regarding the correlation of different cancer forms with the presence of specific metabolites in human urine, in a schematic and easily interpretable form, because of the huge amount of relevant literature. The originality of this paper relies on the attempt to point out the odor properties of such metabolites, and thus to highlight the correlation between urine odor alterations and cancer presence, which is proven by recent literature suggesting the analysis of urine odor for diagnostic purposes. This investigation aims to evaluate the possibility to compare the results of studies based on different approaches to be able in the future to identify those compounds responsible for urine odor alteration.
Evolution of Char Structure During In-Situ Biomass Tar Reforming: Importance of the Coupling Effect Among the Physical-Chemical Structure of Char-Based Catalysts
Authors: Zhang Yu , Feng Dongdong , Zhao Yijun , Dong Heming , Chang Guozhang , Quan Cui , Sun Shaozeng , Qin Yukun
Published: August 2019

In order to illustrate the importance of a coupling effect in the physical-chemical structure of char-based catalysts on in-situ biomass tar reforming, three typical char-based catalysts (graphite, Zhundong coal char, and sawdust biochar) were studied in the fixed-bed/fluidized-bed reactor. The physical-chemical properties of carbon-based catalysts associated with their catalytic abilities were characterized by inductively coupled plasma-atomic emission spectroscopy (ICP-AES), Raman, X-ray photoelectron spectroscopy (XPS), scanning electron microscope–energy dispersive spectrometer (SEM-EDS) and N2 adsorption. The relationship between the specific reactivity and tar reforming ability of carbon-based catalysts was discussed through a micro fluidized bed reaction analyzer (MFBRA–MR). The results indicate that the char-based catalyst has a certain removal ability for in-situ biomass tar of corn straw in an inert atmosphere, which is as follows: sawdust biochar > Zhundong (ZD) coal char > graphite. During the in-situ tar reforming, the alkali and alkaline earth metal species (AAEMs) act as adsorption/reaction sites, affecting the evolution of the aromatic ring structure and oxygen-containing functional groups of the char-based catalyst, and also its pore structure. AAEM species on the surface of char-based catalysts are the active sites for tar reforming, which promotes the increase of active intermediates (C-O bond and C-O-AAEMs), and enhances the interactions between char-based catalysts and biomass tar. The abundant AAEMs may lead to the conversion of O=C–O and C=O to C–O. For tar reforming, the internal pore structure of char-based catalysts is little changed, mainly with the carbon deposit forming on the surface pore structure. The carbon deposit from the reformation of straw tar on the char surface has better reactivity than the inherent carbon structure of ZD coal char and sawdust biochar. There is a positive relationship between the MFBRA–MR specific reactivity and tar catalytic reforming ability of char-based catalysts (decided by the coupling effect in their physical-chemical structure), which can be used to determine the catalytic ability of char-based catalysts on tar reforming directly.
Adipose Mesenchymal Extracellular Vesicles as Alpha-1-Antitrypsin Physiological Delivery Systems for Lung Regeneration
Authors: Bari Elia , Ferrarotti Ilaria , Di Silvestre Dario , Grisoli Pietro , Barzon Valentina , Balderacchi Alice , Torre Maria Luisa , Rossi Rossana , Mauri Pierluigi , Corsico Angelo Guido , Perteghella Sara
Published: August 2019

Accumulating evidence shows that Mesenchymal Stem/Stromal Cells (MSCs) exert their therapeutic effects by the release of secretome, made of both soluble proteins and nano/microstructured extracellular vesicles (EVs). In this work, for the first time, we proved by a proteomic investigation that adipose-derived (AD)-MSC-secretome contains alpha-1-antitrypsin (AAT), the main elastase inhibitor in the lung, 72 other proteins involved in protease/antiprotease balance, and 46 proteins involved in the response to bacteria. By secretome fractionation, we proved that AAT is present both in the soluble fraction of secretome and aggregated and/or adsorbed on the surface of EVs, that can act as natural carriers promoting AAT in vivo stability and activity. To modulate secretome composition, AD-MSCs were cultured in different stimulating conditions, such as serum starvation or chemicals (IL-1β and/or dexamethasone) and the expression of the gene encoding for AAT was increased. By testing in vitro the anti-elastase activity of MSC-secretome, a dose-dependent effect was observed; chemical stimulation of AD-MSCs did not increase their secretome anti-elastase activity. Finally, MSC-secretome showed anti-bacterial activity on Gram-negative bacteria, especially for Klebsiella pneumoniae. These preliminary results, in addition to the already demonstrated immunomodulation, pave the way for the use of MSC-secretome in the treatment of AAT-deficiency lung diseases.
PI3K (Phosphatidylinositol 3-Kinase) Activation and Endothelial Cell Proliferation in Patients with Hemorrhagic Hereditary Telangiectasia Type 1
Authors: Iriarte Adriana , Figueras Agnes , Cerdà Pau , Mora José María , Jucglà Anna , Penín Rosa , Viñals Francesc , Riera-Mestre Antoni
Published: August 2019

Hemorrhagic hereditary telangiectasia (HHT) type 2 patients have increased activation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway in telangiectasia. The main objective is to evaluate the activation of the PI3K pathway in cutaneous telangiectasia of HHT1 patients. A cutaneous biopsy of a digital hand telangiectasia was performed in seven HHT1 and eight HHT2 patients and compared with six controls. The study was approved by the Clinical Research Ethics Committee of our center. A histopathological pattern with more dilated and superficial vessels that pushed up the epidermis was identified in HHT patients regardless of the type of mutation and was associated with older age, as opposed to the common telangiectasia pattern. The mean proliferation index (Ki-67) was statistically higher in endothelial cells (EC) from HHT1 than in controls. The percentage of positive EC for pNDRG1, pAKT, and pS6 in HHT1 patients versus controls resulted in higher values, statistically significant for pNDRG1 and pS6. In conclusion, we detected an increase in EC proliferation linked to overactivation of the PI3K pathway in cutaneous telangiectasia biopsies from HHT1 patients. Our results suggest that PI3K inhibitors could be used as novel therapeutic agents for HHT.
A Novel Computational Model for Predicting microRNA–Disease Associations Based on Heterogeneous Graph Convolutional Networks
Authors: Li Chunyan , Liu Hongju , Hu Qian , Que Jinlong , Yao Junfeng
Published: August 2019

Identifying the interactions between disease and microRNA (miRNA) can accelerate drugs development, individualized diagnosis, and treatment for various human diseases. However, experimental methods are time-consuming and costly. So computational approaches to predict latent miRNA–disease interactions are eliciting increased attention. But most previous studies have mainly focused on designing complicated similarity-based methods to predict latent interactions between miRNAs and diseases. In this study, we propose a novel computational model, termed heterogeneous graph convolutional network for miRNA–disease associations (HGCNMDA), which is based on known human protein–protein interaction (PPI) and integrates four biological networks: miRNA–disease, miRNA–gene, disease–gene, and PPI network. HGCNMDA achieved reliable performance using leave-one-out cross-validation (LOOCV). HGCNMDA is then compared to three state-of-the-art algorithms based on five-fold cross-validation. HGCNMDA achieves an AUC of 0.9626 and an average precision of 0.9660, respectively, which is ahead of other competitive algorithms. We further analyze the top-10 unknown interactions between miRNA and disease. In summary, HGCNMDA is a useful computational model for predicting miRNA–disease interactions.
A Perspective on Recent Advances in Piezoelectric Chemical Sensors for Environmental Monitoring and Foodstuffs Analysis
Authors: Kuchmenko Tatyana A. , Lvova Larisa B.
Published: August 2019

This paper provides a selection of the last two decades publications on the development and application of chemical sensors based on piezoelectric quartz resonators for a wide range of analytical tasks. Most of the attention is devoted to an analysis of gas and liquid media and to industrial processes controls utilizing single quartz crystal microbalance (QCM) sensors, bulk acoustic wave (BAW) sensors, and their arrays in e-nose systems. The unique opportunity to estimate several heavy metals in natural and wastewater samples from the output of a QCM sensor array highly sensitive to changes in metal ion activity in water vapor is shown. The high potential of QCM multisensor systems for fast and cost-effective water contamination assessments “in situ” without sample pretreatment is demonstrated.
Electrochemical Properties of Niobium Coating for Biomedical Application
Authors: Shi Kunyu , Zhang Yi , Zhang Jinzhong , Xie Zonghan
Published: August 2019

The preparation of the Nb coating was performed on the bare Ti–6Al–4V alloy using the double glow discharge plasma technique. It was characterized that the Nb coating exhibited a face centered cubic (fcc) crystal structure and a pronounced (200) preferred orientation. The SEM micrograph of the cross section for the coating displayed dense microstructure with a thickness of approximately 18 µm. The critical load (Lc) of the coating was determined to be about 83.5 N by the scratch tests. The electrochemical corrosion resistance of the coating was examined in Ringer’s solution at 37 °C by a series of electrochemical techniques, including open-circuit potential (OCP), potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and a Mott–Schottky analysis. As the result of the potentiodynamic polarization, the Nb coating possessed a more positive corrosion potential and lower corrosion current density than the Ti–6Al–4V substrate. EIS fitting date showed that the Nb coating always possessed a higher value of impedance and lower effective capacitance than those of the substrate during the five days of immersion testing. The main component of the passive film developed on the Nb coating was Nb2O5, confirmed by an X-ray photoelectron spectroscopy (XPS) analysis. A Mott–Schottky analysis demonstrated typical n-type semiconductor characteristics of the Nb coating, and both the donor density and flat band potential of the coating were lower than those of the substrate at all the given formation potential. These investigations demonstrate that the Nb coating can significantly improve the corrosion protection of uncoated Ti–6Al–4V and is thus a promising coating for the surface protection of bioimplants.
Composition of ω-Phase Particles in Ti(Mo) Alloys Studied by Anomalous X-ray Diffraction
Authors: Šmilauerová Jana , Harcuba Petr , Janeček Miloš , Holý Václav
Published: August 2019

Nanoparticles of hexagonal ω phase in bcc-Ti(Mo) single crystals ( β phase) occur due to a diffusionless athermal β to ω transformation and they grow during follow-up ageing at elevated temperatures, while the alloying atoms (Mo in our case) are expelled from the nanoparticle volumes. We investigated the Mo content in growing ω nanoparticles by anomalous X-ray diffraction and demonstrate that the Mo expulsion from the ω phase is not full; a thin shell of a nanoparticles where the β to ω transformation is not complete still contains a considerable amount of Mo atoms.
An Alien Invader is the Cause of Homogenization in the Recipient Ecosystem: A Simulation-Like Approach
Authors: Morri Carla , Montefalcone Monica , Gatti Giulia , Vassallo Paolo , Paoli Chiara , Bianchi Carlo Nike
Published: August 2019

Biotic homogenization is an expected effect of biological invasions. Invasive alien species typically show great adaptability to a wide range of environmental conditions and may expand into different habitats, thus reducing the dissimilarity among the recipient communities. We tested this assumption by analyzing a comprehensive database (78 species × 229 samples) collected between 2012 and 2017 in the marine protected area of Portofino (NW Italy), where Caulerpa cylindracea, one of the worst invaders in the Mediterranean Sea, exhibits high substratum cover at depths between 1 m and 45 m in 14 different communities (identified according to the European Nature Information System EUNIS for habitat classification). Five samples for each of the eight depth zones (i.e., 5 m, 10 m, 15 m, 20 m, 25 m, 30 m, 35 m, and 40 m) were randomly re-sampled from the comprehensive database to produce a dataset of 67 species × 40 samples. Then, a second dataset of 66 species × 40 samples was simulated by excluding Caulerpa cylindracea. Both re-sampled datasets underwent multivariate analysis. In the presence of C. cylindracea, the overall similarity among samples was higher, thus indicating homogenization of the rocky reef communities of Portofino Marine Protected Area. Continued monitoring activity is needed to understand and assess the pattern and extent of C. cylindracea’s inclusion in the recipient ecosystems.
Reactive Power Optimization of a Distribution System Based on Scene Matching and Deep Belief Network
Authors: Wu Junyong , Shi Chen , Shao Meiyang , An Ran , Zhu Xiaowen , Huang Xing , Cai Rong
Published: August 2019

With a large number of distributed generators (DGs) and electrical vehicles (EVs) integrated into the power distribution system, the complexity of distribution system operation is increased, which arises to higher requirements for online reactive power optimization. This paper proposes two methods for online reactive power optimization, a scene-matching method based on Random Matrix (RM) features and a deep learning method based on Deep Belief Network (DBN). Firstly, utilizing the operation and ambient Big Data (BD) of the distribution system, we construct the high-dimension Random Matrices and extract 57 state features for the subsequent scene-matching and DBN training. Secondly, the feature-based scene-matching method is proposed. Furtherly, to effectively deal with the uncertainty of DGs and to avoid the performance deterioration of the scene-matching method under a new unknown scene, the DBN-based model is constructed and trained, with the former features as the inputs and the conventional reactive power control solutions as the outputs. This DBN model can learn the nonlinear complicated relationship between the system features and the reactive power control solutions. Finally, the comprehensive case studies have been conducted on the modified IEEE-37 nodes active distribution system, and the performances of the proposed two methods are compared with the conventional method. The results show that the DBN-based method possesses the better performance than the others, and it can reduce the network losses and node voltage deviations obviously, even under the new unknown and unmatched scenes. It does not depend on the distribution system model and parameters anymore and can provide online decision-making more quickly. The discussions of the two methods under different DG penetrations and the historical data volume were given, verifying the adaptability, robustness and generalization ability of the DBN-based method.
Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review
Authors: Runge Jason , Zmeureanu Radu
Published: August 2019

During the past century, energy consumption and associated greenhouse gas emissions have increased drastically due to a wide variety of factors including both technological and population-based. Therefore, increasing our energy efficiency is of great importance in order to achieve overall sustainability. Forecasting the building energy consumption is important for a wide variety of applications including planning, management, optimization, and conservation. Data-driven models for energy forecasting have grown significantly within the past few decades due to their increased performance, robustness and ease of deployment. Amongst the many different types of models, artificial neural networks rank among the most popular data-driven approaches applied to date. This paper offers a review of the studies published since the year 2000 which have applied artificial neural networks for forecasting building energy use and demand, with a particular focus on reviewing the applications, data, forecasting models, and performance metrics used in model evaluations. Based on this review, existing research gaps are identified and presented. Finally, future research directions in the area of artificial neural networks for building energy forecasting are highlighted.
Dielectric Insulation Characteristics of Natural Ester Fluid Modified by Colloidal Iron Oxide Ions and Silica Nanoparticles
Authors: Charalampakos Vasilios P. , Peppas Georgios D. , Pyrgioti Eleftheria C. , Bakandritsos Aristides , Polykrati Aikaterini D. , Gonos Ioannis F.
Published: August 2019

In this study, the dielectric characteristics of two types of natural esters modified into nanofluids are studied. The AC breakdown voltage was investigated for colloidal Fe2O3 and SiO2 nanoparticles effectively scattered in natural ester oil. The experimental results identify an increase in the breakdown voltage of the nanofluid with colloidal Fe2O3 conductive nanoparticles. In contrast, the breakdown voltage was reduced by adding SiO2 nanoparticles in the same matrix. The potential well distribution of the two different types of nanoparticles was also calculated in order for the results of the experiment to be explained. The dielectric losses of the colloidal nanofluid are compared with the matrix oil and studied at 25 °C and 100 °C in the frequency regime of 10−1–106 Hz. The experimental data and the theoretical study reveal that conductivity along with the permittivity of nanoparticles constitute a pivotal parameter in the performance of nanofluid. Specific concentrations of nanoparticles with different electrical conductivity and permittivity than those of matrix oil increase the breakdown voltage strength. Simultaneously, the addition of nanoparticles having electrical conductivity and permittivity comparable to the matrix oil results in reducing the breakdown voltage.
The Investigation of Permeability Calculation Using Digital Core Simulation Technology
Authors: Zhang Lei , Jing Wenlong , Yang Yongfei , Yang Hainan , Guo Yaohao , Sun Hai , Zhao Jianlin , Yao Jun
Published: August 2019

Digital core simulation technology, as an emerging numerical simulation method, has gradually come to play a significant role in the study of petrophysical properties. By using this numerical simulation method, the influence of micro factors on seepage properties of reservoir rock is taken into consideration, making up the shortcomings of the traditional physical experiment. Three-dimensional core images are reconstructed by a computed tomography scanning technique. Different sizes of the sub-region were simulated by three methods including the direct computation of Navier-Stokes equations, the simulation of the pore network model, and the lattice Boltzmann method. The permeability computed by each simulation was compared. After comparison between these three methods, the results of the direct computation method based on Navier-Stokes equations were found to be higher than the other two methods. The pore network model simulation has an obvious advantage on the computation speed and the simulation area. The lattice Boltzmann method shows the low efficiency due to the time-consuming process. At last, the permeability calculated by the three methods is matched by the Kozeny-Carman equation. A more accurate formula can be obtained by a series of numerical simulations, which can be applied to marco-scale simulation.
Thermal Performance of a PCM-Based Thermal Energy Storage with Metal Foam Enhancement
Authors: Chen Xue , Li Xiaolei , Xia Xinlin , Sun Chuang , Liu Rongqiang
Published: August 2019

The energy transport inside a phase change material (PCM) based thermal energy storage system using metal foam as an enhancement technique is investigated numerically. The paraffin is used as the PCM and water as the heat transfer fluid (HTF). The transient heat transfer during the charging and discharging processes is solved, based on the volume averaged conservation equations. The flow in PCM/foam and HTF/foam composites is modelled by the Forchheimer-extended Darcy equation, while the two-temperature model is employed to account for the local thermal non-equilibrium effect between the foam matrix and fluid phase. The results show that the overall performance is greatly improved by inserting metal foam in both HTF and PCM sides. A nearly 84.9% decrease in the time needed for the total process is found compared with the case of pure PCM, and 40% compared with the case of metal foam insert only in the PCM side. Foam porosity and HTF inlet temperature greatly affect the dynamic heat storage/release process.
Sliding-Mode-Observer-Based Open-Switch Diagnostic Method for Permanent Magnet Synchronous Motor Drive Connected with LC Filter
Authors: Wang Minghui , Xu Yongxiang , Zou Jibin
Published: August 2019

At present, pulse width modulation (PWM) technique is widely applied in motor drive systems. However, it may cause some unexpected effects: Bearing currents, overvoltage, power losses and unwanted noise. In some industrial cases, LC filters are always equipped in motor drive systems to suppress those unexpected effects. In order to improve the reliability and safety of the drive system, fault diagnostic strategies for power switches should be utilized as other drive systems without LC filters. In the literature, some open-switch diagnostic approaches are based on the observers derived from the mathematical models. However, the models are changed by the LC filters. Therefore, the existing approaches, based on the observers are failed, due to the change of the models. This study proposes an open-switch diagnostic method for permanent magnet synchronous motor (PMSM) drive equipped with LC Filter. The novelty of the proposed method is that the model of the LC filter is considered. Therefore, open-switch faults can be detected and located in the drive systems with LC filters. The switching function model of the drive system is analyzed at first. Then a sliding mode observer (SMO) considering the model of the filter is proposed to estimate the filter voltages and other state variables. Consequently, the faults can be detected and located through the residual errors between the expected and estimated filter voltages. This approach features simplicity. Furthermore, any extra sensors are not necessary. Experimental results on a 750-W PMSM drive system with an LC filter proved the feasibility of the proposed method.
Profiling the Functional Diversity of Termite Mound Soil Bacteria as Revealed by Shotgun Sequencing
Authors: Enagbonma Ben Jesuorsemwen , Aremu Bukola Rhoda , Babalola Olubukola Oluranti
Published: August 2019

Profiling the metabolic processes performed by bacteria is vital both for understanding and for manipulating ecosystems for industrial or research purposes. In this study we aim to assess the bacterial functional diversity in termite mound soils with the assumption that significant differences will be observed in the functional diversity of bacteria between the termite mound soils and their surrounding soils and that each environment has a distinguishing metabolic profile. Here, metagenomic DNA extracted from termite mound soils and their corresponding surrounding soils, which are 10 m apart, were sequenced using a shotgun sequencing approach. Our results revealed that the relative abundances of 16 functional categories differed significantly between both habitats. The α diversity analysis indicated no significant difference in bacterial functional categories within the habitats while the β diversity showed that the bacterial functional categories varied significantly between the termite mound soils and the surrounding soil samples. The variations in soil physical and chemical properties existing between the two environments were held accountable for the differences in bacterial functional structure. With the high relative abundance of functional categories with unknown function reported in this study, this could signify the likelihood of getting novel genes from termite mound soils, which are needed for research and commercial applications.
Integration of Bioinformatic Predictions and Experimental Data to Identify circRNA-miRNA Associations
Authors: Dori Martina , Bicciato Silvio
Published: August 2019

Circular RNAs (circRNAs) have recently emerged as a novel class of transcripts, characterized by covalently linked 3′–5′ ends that result in the so-called backsplice junction. During the last few years, thousands of circRNAs have been identified in different organisms. Yet, despite their role as disease biomarker started to emerge, depicting their function remains challenging. Different studies have shown that certain circRNAs act as miRNA sponges, but any attempt to generalize from the single case to the “circ-ome” has failed so far. In this review, we explore the potential to define miRNA “sponging” as a more general function of circRNAs and describe the different approaches to predict miRNA response elements (MREs) in known or novel circRNA sequences. Moreover, we discuss how experiments based on Ago2-IP and experimentally validated miRNA:target duplexes can be used to either prioritize or validate putative miRNA-circRNA associations.
Coseismic Ground Deformation Reproduced through Numerical Modeling: A Parameter Sensitivity Analysis
Authors: Panara Yuri , Toscani Giovanni , Cooke Michele L. , Seno Silvio , Perotti Cesare
Published: August 2019

Coseismic ground displacements detected through remote sensing surveys are often used to invert the coseismic slip distribution on geologically reliable fault planes. We analyze a well-known case study (2009 L’Aquila earthquake) to investigate how three-dimensional (3D) slip configuration affects coseismic ground surface deformation. Different coseismic slip surface configurations reconstructed using aftershocks distribution and coseismic cracks, were tested using 3D boundary element method numerical models. The models include two with slip patches that reach the surface and three models of blind normal-slip surfaces with different configurations of slip along shallowly-dipping secondary faults. We test the sensitivity of surface deformation to variations in stress drop and rock stiffness. We compare numerical models’ results with line of sight (LOS) surface deformation detected from differential SAR (Synthetic Aperture Radar) interferometry (DInSAR). The variations in fault configuration, rock stiffness and stress drop associated with the earthquake considerably impact the pattern of surface subsidence. In particular, the models with a coseismic slip patch that does not reach the surface have a better match to the line of sight coseismic surface deformation, as well as better match to the aftershock pattern, than models with rupture that reaches the surface. The coseismic slip along shallowly dipping secondary faults seems to provide a minor contribution toward surface deformation.
The Evaluation of IDEAL-REACH Program to Improve Nutrition among Asian American Community Members in the Philadelphia Metropolitan Area
Authors: Ma Grace X. , Zhu Lin , Shive Steven E. , Zhang Guo , Senter Yvette R. , Topete Pablo , Seals Brenda , Zhai Shumenghui , Wang MinQi , Tan Yin
Published: August 2019

Objective Asian Americans’ food purchasing, cooking, and eating patterns are not well understood. Greater insight into these behaviors is urgently needed to guide public health interventions of dietary behaviors in this population. The present study aims to examine the effects of a community-level intervention on food purchasing and preparation, nutrition knowledge, and health awareness in Asian Americans. Methods From 2015 to 2017, we conducted the Improving Diets with an Ecological Approach for Lifestyle (IDEAL-REACH) intervention to increase access to healthy food or beverage options for the Asian-American population in the Philadelphia metropolitan area. Participants (1110 at pre- and 1098 at post-assessment) were recruited from 31 community-based organizations (CBOs). We assessed Asian Americans’ dietary behaviors, nutrition knowledge, and awareness of heart health. Results The results of pre-post intervention comparisons showed that the IDEAL-REACH intervention was successful in promoting whole grains consumption, reducing sodium consumption, and raising knowledge and awareness related to nutrition and heart health. Conclusions To our knowledge, this is one of the first initiatives in the U.S. to engage CBOs to promote healthier dietary behaviors. The findings show that CBOs serve as a powerful platform for community-level interventions to improve healthy nutrition behaviors in Asian-American communities.
Early Eating Patterns and Overweight and Obesity in a Sample of Preschool Children in South-East Poland
Authors: Baran Joanna , Weres Aneta , Czenczek-Lewandowska Ewelina , Łuszczki Edyta , Sobek Grzegorz , Pitucha Grzegorz , Leszczak Justyna , Mazur Artur
Published: August 2019

The aim of this study was to assess the impact of a child’s diet in the first year of life (breastfeeding duration, introduction of solid meals to the diet, the time of starting nutrition consistent with an adult diet) on the prevalence of overweight and obesity in preschool age. Three-hundred children aged 4–6 were included in the analysis. The children’s height and body weight were assessed and their body mass category was determined based on the BMI (Body Mass Index) percentile. Parents provided a photocopy of the child’s health book (with information concerning breastfeeding period, start of eating the same meals as the rest of the family, etc.). Obese children were breastfed for the shortest time, cow’s milk was introduced to their diets the earliest, they started eating the same food as the rest of the family the earliest, and they received vegetables, fruits, cereals, and meat products in their diet the latest. The results of this study suggest that extending the breastfeeding period beyond 6 months, starting to feed the child the same meals as the rest of the family after 12 months of age, and later introduction of cow’s milk to the diet would reduce the risk of the occurrence of excessive body weight in preschool children.
Spatio-Temporal Variation in Nutrient Profiles and Exchange Fluxes at the Sediment-Water Interface in Yuqiao Reservoir, China
Authors: Wen Shuailong , Wu Tao , Yang Jie , Jiang Xue , Zhong Jicheng
Published: August 2019

Nutrients released from sediments have a significant influence on the water quality in eutrophic lakes and reservoirs. To clarify the internal nutrient load and provide reference for eutrophication control in Yuqiao Reservoir, a drinking water source reservoir in China, pore water profiles and sediment core incubation experiments were conducted. The nutrients in the water (soluble reactive P (SRP), nitrate-N (NO3−-N), nitrite-N (NO2−-N), and ammonium-N (NH4+-N)) and in the sediments (total N (TN), total P (TP) and total organic carbon (TOC)) were quantified. The results show that NH4+-N was the main component of inorganic N in the pore water. NH4+-N and SRP were higher in the pore water than in the overlying water, and the concentration gradient indicated a diffusion potential from the sediment to the overlying water. The NH4+-N, NO3−-N, and SRP fluxes showed significant differences amongst the seasons. The NH4+-N and SRP fluxes were significantly higher in the summer than in other seasons, while NO3−-N was higher in the autumn. The sediment generally acted as a source of NH4+-N and SRP and as a sink for NO3−-N and NO2−-N. The sediments release 1133.15 and 92.46 tons of N and P, respectively, to the overlying water each year.
Rett Syndrome in Males: The Different Clinical Course in Two Brothers with the Same Microduplication MECP2 Xq28
Authors: Pitzianti Maria Bernarda , Santamaria Palombo Angelo , Esposito Susanna , Pasini Augusto
Published: August 2019

Rett syndrome (RTT) is a neurodevelopmental disorder with a genetic basis that is associated with the mutation of the X-linked methyl-CpG binding protein 2 (MECP2) gene in approximately 90% of patients. RTT is characterized by a brief period of normal development followed by loss of acquired skills and evolution towards impairment of brain and motor functions and multi-organ dysfunction. Originally, RTT was considered lethal in males as it has an X-linked dominant inheritance. However, although this syndrome has a higher incidence in females, rare cases are also documented in males. Here, we describe the case of an 11-year-old male patient with a microduplication MECP2 Xq28. Our patient is currently living, while his older brother with the same mutation died at the age of 9 years. We showed that the role of MECP2 as an epigenetic modulator and the X-chromosome inactivation pattern can explain the lethal clinical form of the older brother with the same microduplication MECP2 Xq28 presented by our patient who is still alive. Given the limited case history of RTT in males, further studies are needed to better characterize this syndrome in males and consequently improve the currently available therapeutic strategies.
Relevance Analysis of Sustainable Development of China’s Yangtze River Economic Belt Based on Spatial Structure
Authors: Tang Decai , Li Zhijiang , Bethel Brandon J.
Published: August 2019

Scientifically justifiable spatial structure can not only promote the efficient use of regional resources, but can also effectively avoid “urban diseases”, such as traffic congestion, housing shortage, resource scarcity, and so on. It is the “regulator” and “booster” of regional development. Firstly, this paper measures the spatial structure of the Yangtze River Economic Belt from the four dimensions of scale distribution, central structure, spatial connection, and compactness: Gini coefficient of urban scale, urban primacy, regional economic linkage strength, and spatial compactness. Secondly, the optimized Super-Slack Based Measure-Undesirable model is used to evaluate the sustainable development status of the Yangtze River Economic Belt. Finally, a sustainable development correlation analysis model based on regional spatial structure is constructed. Based on the overall perspective of the Yangtze River Economic Belt and the individual perspective of 11 provinces and cities, the relationship between the spatial structure of the Yangtze River Economic Belt and sustainable development is analyzed. It is found that the impact of the four spatial structure indicators on the sustainable development level of the Yangtze River Economic Zone is relatively stable in five different periods. The ranking results are as follows: Gini coefficient of urban scale > urban primacy > regional economic linkage strength > spatial compactness.
Health Policies in Romania to Reduce the Mortality Caused by Cardiovascular Diseases
Authors: Simionescu Mihaela , Bilan Svitlana , Gavurova Beata , Bordea Elena-Nicoleta
Published: August 2019

Cardiovascular diseases (CVDs) are the main cause of death in Romania. The objective of the paper is to explain the number of deaths caused by the diseases of circulatory system in relation to health expenditures per capita, the number of public hospitals with cardiology sections and the number of cardiologists. The analysis in the paper is based on panel data models and Bayesian linear models. A panel data approach for Romanian macro-regions in the period from 1995–2016 was used to show that an increase in the number of cardiologists would reduce the number of deaths caused by the diseases of circulatory system. The Bayesian approach to national data indicated that the increase in expenditures per capita would alleviate the incidence of deaths caused by CVD. The public health policies in relation to patients with CVD should focus on the future on higher expenditures per person, but the number of public hospitals and doctors treating these diseases should also continue to grow. Future healthcare policies should be also focused on reducing the number of specialists migrating to wealthier countries.
Current Status, Challenges, and Policy Recommendations of China’s Marine Monitoring Systems for Coastal Persistent Organic Pollution Based on Experts’ Questionnaire Analysis
Authors: Zhao Wenlu , Chen Huorong , Wang Jun , Zhang Mingyu , Chen Kai , Guo Yali , Ke Hongwei , Huang Wenyi , Liu Lihua , Yang Shengyun , Cai Minggang
Published: August 2019

Persistent organic pollutants (POPs) monitoring and management in typical semi-enclosed bays is a major global environmental issue. This study concentrated on a questionnaire survey and analysis of marine environmental management and monitoring departments at all levels in China, and proposed suggestions on the construction and improvement of POPs monitoring and management system. Results show that POPs are initially involved in China’s current marine environmental monitoring system, and the monitoring strength and capability still need to be continuously improved, mainly in the recognition, funding input, relevant standards, monitoring, and evaluation technical regulations of marine environmental POPs monitoring. Therefore, in order to gradually improve the monitoring and management system of China’s offshore marine environment POPs, this study suggests starting from four directions: (1) Building POPs monitoring system of a marine ecological environment, and strengthening POPs monitoring in different environmental media; (2) strengthening land-based POPs emission and the related human activities’ intensity survey, and establishing a POPs information sharing database; (3) optimizing POPs monitoring technology in the marine environment, and improving POPs supervision and management technical support system; and (4) participating in regional and international marine environment POPs monitoring and evaluation projects, and strengthening the construction of talent teams.