bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Assessment of the Performance of Two Marine Coatings to Curb Biofilm Formation of Microfoulers
Authors: Faria Sara I. , Teixeira-Santos Rita , Gomes Luciana C. , Silva Elisabete R. , Morais João , Vasconcelos Vítor , Mergulhão Filipe J. M.
Published: September 2020

Biofilms formed on submerged marine surfaces play a critical role in the fouling process, causing increased fuel consumption, corrosion, and high maintenance costs. Thus, marine biofouling is a major issue and motivates the development of antifouling coatings. In this study, the performance of two commercial marine coatings, a foul-release silicone-based paint (SilRef) and an epoxy resin (EpoRef), was evaluated regarding their abilities to prevent biofilm formation by Cyanobium sp. and Pseudoalteromonas tunicata (common microfoulers). Biofilms were developed under defined hydrodynamic conditions to simulate marine settings, and the number of biofilm cells, wet weight, and thickness were monitored for 7 weeks. The biofilm structure was analyzed by confocal laser scanning microscopy (CLSM) at the end-point. Results demonstrated that EpoRef surfaces were effective in inhibiting biofilm formation at initial stages (until day 28), while SilRef surfaces showed high efficacy in decreasing biofilm formation during maturation (from day 35 onwards). Wet weight and thickness analysis, as well as CLSM data, indicate that SilRef surfaces were less prone to biofilm formation than EpoRef surfaces. Furthermore, the efficacy of SilRef surfaces may be dependent on the fouling microorganism, while the performance of EpoRef was strongly influenced by a combined effect of surface and microorganism.
Influence of Element Penetration Region on Adhesion and Corrosion Performance of Ni-Base Coatings
Authors: Fu Xiuqing , Shen Zhenyu , Chen Xinxin , Lin Jinran , Cao Hongbing
Published: September 2020

In this study, Ni–P/Ni–P–SiC coatings were prepared on pretreated 45 steel substrates by scanning electrodeposition. Prior to the electrodeposition, the substrates were subjected to two types of pretreatments: polishing and sandblasting. The 3D morphology of the pretreated substrates was characterized by laser scanning confocal microscopy. The micromorphology and section morphology of the coating surface were characterized by field emission scanning electron microscopy. The section element composition was characterized using an EDS energy spectrum analyzer. The adhesion and corrosion resistance of 15 coatings were analyzed using an automatic scratch tester and CS350 electrochemical workstation. The results showed the presence of an element penetration region between the coating and the substrate. The sandblasting pretreatment and SiC nanoparticle addition helped widen the penetration region of the elements. The Ni–P–SiC coating prepared by scanning electrodeposition on the sandblasted substrate exhibited the thickest penetration region, up to 28.39 µm. A scratch test conducted on this coating showed that it exhibits the best adhesion force, up to 36.5 N. In electrochemical corrosion experiments, its corrosion potential was found to be the highest, reaching −0.30 V, and the corrosion current density was the lowest, reaching 8.45 × 10−7 A·cm−2. The presence of the element penetration region increased the coating adhesion and improved the corrosion resistance.
High-Thermal-Conductivity SiC Ceramic Mirror for High-Average-Power Laser System
Authors: Miyasaka Yasuhiro , Kondo Kotaro , Kiriyama Hiromitsu
Published: September 2020

The importance of heat-resistant optics is increasing together with the average power of high-intensity lasers. A silicon carbide (SiC) ceramic with high thermal conductivity is proposed as an optics substrate to suppress thermal effects. The temperature rise of the substrate and the change in the surface accuracy of the mirror surface, which degrades the laser beam quality, are investigated. Gold mirrors on synthetic fused silica and SiC ceramic substrates are heated with a 532 nm wavelength laser diode. The synthetic fused silica substrate placed on an aluminum block shows a temperature increase by ~32 °C and a large temperature gradient. In contrast, the SiC ceramic substrate shows a uniform temperature distribution and a temperature increase of only ~4 °C with an absorbed power of ~2 W after 20 min laser irradiation. The surface accuracy (roughness) when using the synthetic fused silica substrate changes from /21.8 (29.0 nm) to /7.2 (88.0 nm), increasing by a factor of ~3.0. However, that of the SiC ceramic substrate changes from /21.0 (30.2 nm) to /13.3 (47.7 nm), increasing by only a factor of ~1.6. Based on these experimental results, detailed considerations and calculations of actively cooled SiC ceramic substrates for high-average-power laser systems are also discussed.
Engineering Aspheric Liquid Crystal Lenses by Using the Transmission Electrode Technique
Authors: Algorri José , Zografopoulos Dimitrios , Rodríguez-Cobo Luis , Sánchez-Pena José , López-Higuera José
Published: September 2020

The transmission electrode technique has been recently proposed as a versatile method to obtain various types of liquid-crystal (LC) lenses. In this work, an equivalent electric circuit and new analytical expressions based on this technique are developed. In addition, novel electrode shapes are proposed in order to generate different phase profiles. The analytical expressions depend on manufacturing parameters that have been optimized by using the least squares method. Thanks to the proposed design equations and the associated optimization, the feasibility of engineering any kind of aspheric LC lenses is demonstrated, which is key to obtain aberration-free lenses. The results are compared to numerical simulations validating the proposed equations. This novel technique, in combination with the proposed design equations, opens a new path for the design and fabrication of LC lenses and even other types of adaptive-focus lenses based on voltage control.
Permittivity of 3D-Printed Nylon Substrates with Different Infill Patterns and Densities for Design of Microwave Components
Authors: Hu Hanxiong , Sinha Swapnil , Meisel Nicholas , Bilén Sven G.
Published: September 2020

Printed circuit boards, chemical etching, and computer numerical control milling currently dominate industrial processes for manufacturing microwave components. However, these manufacturing methods do not provide the flexibility for customization possible with additive manufacturing. Additive manufacturing (AM) has the potential to fabricate microwave components for desired frequency ranges with less effort in prototyping and fabrication. Relative permittivity (εr) of materials is a critical parameter in microwave component design, yet the value changes during the AM process. This article investigates how relative permittivity for nylon substrates, created with AM, changes with different infill densities and infill patterns. The measurement method and procedure can be used to design AM microwave components like antennas or dielectric-filled waveguides with desired characteristics. The two-microstrip-line method was used and improved for the accurate and convenient measurement of the relative permittivity of AM nylon substrates. Several nylon substrates with different infill patterns, including rectangular, hexagonal, triangular, and solid, were fabricated with AM to demonstrate how the relative permittivity value changes as the infill density increases. A linear relationship between the infill density of the rectangular pattern and the substrate permittivity was found. The permittivity data were applied to the design of a rectangular patch antenna for use in the 2.5-GHz WiMAX band. The fabricated antenna with AM, which was tested using a vector network analyzer, showed good agreement with simulation results. The method and procedure of permittivity measurements are specially designed to be applied in the design of microwave components with AM dielectric substrates.
Photoacoustic Imaging for Assessing Tissue Oxygenation Changes in Rat Hepatic Fibrosis
Authors: Karmacharya Mrigendra B. , Sultan Laith R. , Kirkham Brooke M. , Brice Angela K. , Wood Andrew K.W. , Sehgal Chandra M.
Published: September 2020

Chronic liver inflammation progressively evokes fibrosis and cirrhosis resulting in compromised liver function, and often leading to cancer. Early diagnosis and staging of fibrosis is crucial because the five-year survival rate of early-stage liver cancer is high. This study investigates the progression of hepatic fibrosis induced in rats following ingestion of diethylnitrosamine (DEN). Changes in oxygen saturation and hemoglobin concentration resulting from chronic inflammation were assayed longitudinally during DEN ingestion by photoacoustic imaging (PAI). Accompanying liver tissue changes were monitored simultaneously by B-mode sonographic imaging. Oxygen saturation and hemoglobin levels in the liver increased over 5 weeks and peaked at 10 weeks before decreasing at 13 weeks of DEN ingestion. The oxygenation changes were accompanied by an increase in hepatic echogenicity and coarseness in the ultrasound image. Histology at 13 weeks confirmed the development of severe fibrosis and cirrhosis. The observed increase in PA signal representing enhanced blood oxygenation is likely an inflammatory physiological response to the dietary DEN insult that increases blood flow by the development of neovasculature to supply oxygen to a fibrotic liver during the progression of hepatic fibrosis. Assessment of oxygenation by PAI may play an important role in the future assessment of hepatic fibrosis.
Mini-Review of the New Therapeutic Possibilities in Asherman Syndrome—Where Are We after One Hundred and Twenty-Six Years?
Authors: Doroftei Bogdan , Dabuleanu Ana-Maria , Ilie Ovidiu-Dumitru , Maftei Radu , Anton Emil , Simionescu Gabriela , Matei Theodor , Armeanu Theodora
Published: September 2020

Asherman syndrome is a multifaceted condition describing the partial or complete removal of the uterine cavity and/or cervical canal. It is a highly debatable topic because of its pronounced influence on both reproductive outcomes and gynaecologic symptoms. The latest reports demonstrated that trauma to the endometrium is the main cause of intrauterine adhesion formation. Left untreated, such adhesions gradually lead to a range of repercussions ranging from mild to severe. Considering the lack of non-invasive approaches, the advent of hysteroscopy has revolutionized the entire field, being otherwise considered the most efficient tool offering new directions and amplifying the chances of treating the Asherman syndrome.
Stasis Leg Ulcers: Venous System Revises by Triggered Angiography Non-Contrast-Enhanced Sequence Magnetic Resonance Imaging
Authors: Chen Chien-Wei , Tseng Yuan-Hsi , Wong Min Yi , Wu Chao-Ming , Lin Bor-Shyh , Huang Yao-Kuang
Published: September 2020

Objectives: The distribution of venous pathology in stasis leg ulcers is unclear. The main reason for this uncertainty is the lack of objective diagnostic tools. To fill this gap, we assessed the effectiveness of triggered angiography non-contrast-enhanced (TRANCE)-magnetic resonance imaging (MRI) in determining the venous status of patients with stasis leg ulcers. Methods: This prospective observational study included the data of 23 patients with stasis leg ulcers who underwent TRANCE-MRI between April 2017 and May 2020; the data were retrospectively analyzed. TRANCE MRI utilizes differences in vascular signal intensity during the cardiac cycle for subsequent image subtraction, providing not only a venogram but also an arteriogram without the use of contrast agents or radiation. Results: TRANCE MRI revealed that the stasis leg ulcers of nine of the 23 patients could be attributed to valvular insufficiency and venous occlusion (including deep venous thrombosis [DVT], May–Thurner syndrome, and other external compression). Moreover, TRANCE MRI demonstrated no venous pathology in five patients (21.7%). We analyzed TRANCE MRI hemodynamic parameters, namely stroke volume, forward flow volume, backward flow volume, regurgitant fraction, absolute volume, mean flux, stroke distance, and mean velocity, in the external iliac vein, femoral vein, popliteal vein, and great saphenous vein (GSV) in three of the patients with valvular insufficiency and three of those with venous occlusion. We found that the mean velocity and stroke volume in the GSV was higher than that in the popliteal vein in all patients with venous valvular insufficiency. Conclusions: Stasis leg ulcers may have no underlying venous disease and could be confirmed by TRANCE-MRI. TRANCE MRI has good Interrater reliability between Duplex study in greater saphenous venous insufficiency. It also potentially surpasses existing diagnostic modalities in terms of distinguishable hemodynamic figures. Accordingly, TRANCE-MRI is a safe and useful tool for examining stasis leg ulcers and is extensively applied currently.
Radiomic Analysis in Contrast-Enhanced Spectral Mammography for Predicting Breast Cancer Histological Outcome
Authors: La Forgia Daniele , Fanizzi Annarita , Campobasso Francesco , Bellotti Roberto , Didonna Vittorio , Lorusso Vito , Moschetta Marco , Massafra Raffaella , Tamborra Pasquale , Tangaro Sabina , Telegrafo Michele , Pastena Maria Irene , Zito Alfredo
Published: September 2020

Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcome and two cancer molecular subtypes, namely Human Epidermal growth factor Receptor 2 (HER2)-positive and triple-negative. From 52 patients, 68 lesions were identified and confirmed on histological examination. Radiomic analysis was performed on regions of interest (ROIs) selected from both low-energy (LE) and ReCombined (RC) CESM images. Fourteen statistical features were extracted from each ROI. Expression of estrogen receptor (ER) was significantly correlated with variation coefficient and variation range calculated on both LE and RC images; progesterone receptor (PR) with skewness index calculated on LE images; and Ki67 with variation coefficient, variation range, entropy and relative smoothness indices calculated on RC images. HER2 was significantly associated with relative smoothness calculated on LE images, and grading tumor with variation coefficient, entropy and relative smoothness calculated on RC images. Encouraging results for differentiation between ER+/ER−, PR+/PR−, HER2+/HER2−, Ki67+/Ki67−, High-Grade/Low-Grade and TN/NTN were obtained. Specifically, the highest performances were obtained for discriminating HER2+/HER2− (90.87%), ER+/ER− (83.79%) and Ki67+/Ki67− (84.80%). Our results suggest an interesting role for radiomics in CESM to predict histological outcomes and particular tumors’ molecular subtype.
MiRNAs, Myostatin, and Muscle MRI Imaging as Biomarkers of Clinical Features in Becker Muscular Dystrophy
Authors: Marozzo Roberta , Pegoraro Valentina , Angelini Corrado
Published: September 2020

Becker muscular dystrophy (BMD) is an X-linked recessive disorder caused by dystrophin gene mutations. The phenotype and evolution of this muscle disorder are extremely clinical variable. In the last years, circulating biomarkers have acquired remarkable importance in their use as noninvasive biological indicators of prognosis and in monitoring muscle disease progression, especially when associated to muscle MRI imaging. We investigated the levels of circulating microRNAs (myo-miRNAs and inflammatory miRNAs) and of the proteins follistatin (FSTN) and myostatin (GDF-8) and compared results with clinical and radiological imaging data. In eight BMD patients, including two cases with evolving lower extremity weakness treated with deflazacort, we evaluated the expression level of 4 myo-miRNAs (miR-1, miR-206, miR-133a, and miR-133b), 3 inflammatory miRNAs (miR-146b, miR-155, and miR-221), FSTN, and GDF-8 proteins. In the two treated cases, there was pronounced posterior thigh and leg fibrofatty replacement assessed by muscle MRI by Mercuri score. The muscle-specific miR-206 was increased in all patients, and inflammatory miR-221 and miR-146b were variably elevated. A significant difference in myostatin expression was observed between steroid-treated and untreated patients. This study suggests that microRNAs and myostatin protein levels could be used to better understand the progression and management of the disease.
Antigen-Specific Cytokine and Chemokine Gene Expression for Diagnosing Latent and Active Tuberculosis
Authors: Korma Workneh , Mihret Adane , Chang Yunhee , Tarekegn Azeb , Tegegn Metasebiya , Tuha Adem , Hwang Dasom , Asefa Mesfin , Hasen Mahlet O. , Kim Seoyoung , Tessema Tesfaye S. , Lee Hyeyoung
Published: September 2020

Tuberculosis infection exhibits different forms, namely, pulmonary, extrapulmonary, and latent. Here, diagnostic markers based on the gene expression of cytokines and chemokines for differentiating between tuberculosis infection state(s) were identified. Gene expression of seven cytokines (Interferon gamma (IFN-γ), Interferon gamma-induced protein 10 (IP-10), Interleukin-2 receptor (IL-2R), C-X-C Motif Chemokine Ligand 9 (CXCL-9), Interleukin 10 (IL-10), Interleukin 4 (IL-4), and Tumor Necrosis Factor alpha (TNF-α)) in response to tuberculosis antigen was analyzed using real-time polymerase reaction. The sensitivity and specificity of relative quantification (2^-ΔΔCt) of mRNA expression were analyzed by constructing receiver operating characteristic curves and measuring the area under the curve (AUC) values. Combinations of cytokines were analyzed using the R statistical software package. IFN-γ, IP-10, IL2R, and CXCL-9 showed high expression in latent and active tuberculosis patients (p = 0.001), with a decrease in IL10 expression, and no statistical difference in IL-4 levels among all the groups (p = 0.999). IL-10 differentiated pulmonary tuberculosis patients from latent cases with an AUC of 0.731. IL10 combined with CXCL-9 distinguished pulmonary tuberculosis patients from extrapulmonary cases with a sensitivity, specificity, and accuracy of 85.7%, 73.9%, and 81.0%, respectively. IL-10 together with IP-10 and IL-4 differentiated pulmonary tuberculosis from latent cases with a sensitivity and specificity of 77.1% and 88.1%, respectively. Decision tree analysis demonstrated that IFN-γ IL-2R, and IL-4 can diagnose tuberculosis infection with a sensitivity, specificity, and accuracy of 89.7%, 96.1%, and 92.7%, respectively. A combination of gene expression of cytokines and chemokines might serve as an effective marker to differentiate tuberculosis infection state(s).
Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
Authors: Platiša Mirjana M. , Radovanović Nikola N. , Kalauzi Aleksandar , Milašinović Goran , Pavlović Siniša U.
Published: September 2020

It is known that in pathological conditions, physiological systems develop changes in the multiscale properties of physiological signals. However, in real life, little is known about how changes in the function of one of the two coupled physiological systems induce changes in function of the other one, especially on their multiscale behavior. Hence, in this work we aimed to examine the complexity of cardio-respiratory coupled systems control using multiscale entropy (MSE) analysis of cardiac intervals MSE (RR), respiratory time series MSE (Resp), and synchrony of these rhythms by cross multiscale entropy (CMSE) analysis, in the heart failure (HF) patients and healthy subjects. We analyzed 20 min of synchronously recorded RR intervals and respiratory signal during relaxation in the supine position in 42 heart failure patients and 14 control healthy subjects. Heart failure group was divided into three subgroups, according to the RR interval time series characteristics (atrial fibrillation (HFAF), sinus rhythm (HFSin), and sinus rhythm with ventricular extrasystoles (HFVES)). Compared with healthy control subjects, alterations in respiratory signal properties were observed in patients from the HFSin and HFVES groups. Further, mean MSE curves of RR intervals and respiratory signal were not statistically different only in the HFSin group (p = 0.43). The level of synchrony between these time series was significantly higher in HFSin and HFVES patients than in control subjects and HFAF patients (p < 0.01). In conclusion, depending on the specific pathologies, primary alterations in the regularity of cardiac rhythm resulted in changes in the regularity of the respiratory rhythm, as well as in the level of their asynchrony.
Complexity in Economic and Social Systems: Cryptocurrency Market at around COVID-19
Authors: Drożdż Stanisław , Kwapień Jarosław , Oświęcimka Paweł , Stanisz Tomasz , Wątorek Marcin
Published: September 2020

Social systems are characterized by an enormous network of connections and factors that can influence the structure and dynamics of these systems. Among them the whole economical sphere of human activity seems to be the most interrelated and complex. All financial markets, including the youngest one, the cryptocurrency market, belong to this sphere. The complexity of the cryptocurrency market can be studied from different perspectives. First, the dynamics of the cryptocurrency exchange rates to other cryptocurrencies and fiat currencies can be studied and quantified by means of multifractal formalism. Second, coupling and decoupling of the cryptocurrencies and the conventional assets can be investigated with the advanced cross-correlation analyses based on fractal analysis. Third, an internal structure of the cryptocurrency market can also be a subject of analysis that exploits, for example, a network representation of the market. In this work, we approach the subject from all three perspectives based on data from a recent time interval between January 2019 and June 2020. This period includes the peculiar time of the Covid-19 pandemic; therefore, we pay particular attention to this event and investigate how strong its impact on the structure and dynamics of the market was. Besides, the studied data covers a few other significant events like double bull and bear phases in 2019. We show that, throughout the considered interval, the exchange rate returns were multifractal with intermittent signatures of bifractality that can be associated with the most volatile periods of the market dynamics like a bull market onset in April 2019 and the Covid-19 outburst in March 2020. The topology of a minimal spanning tree representation of the market also used to alter during these events from a distributed type without any dominant node to a highly centralized type with a dominating hub of USDT. However, the MST topology during the pandemic differs in some details from other volatile periods.
Bagged Tree Based Frame-Wise Beforehand Prediction Approach for HEVC Intra-Coding Unit Partitioning
Authors: Li Yixiao , Li Lixiang , Fang Yuan , Peng Haipeng , Yang Yixian
Published: September 2020

High Efficiency Video Coding (HEVC) has achieved about 50% bit-rates saving compared with its predecessor H.264 standard, while the encoding complexity increases dramatically. Due to the introduction of more flexible partition structures and more optional prediction directions, HEVC takes a brute force approach to find the optimal partitioning result which is much more time consuming. Therefore, this paper proposes a bagged trees based fast approach (BTFA) and focuses on the coding unit (CU) size decision for HEVC intra-coding. First, several key features of a target CU are extracted for three-output classifiers. Then, to avoid feature extraction and prediction time over head, our approach is designed frame-wisely, and the procedure is applied parallel with the encoding process. Using the adaptive threshold determination algorithm, our approach achieves 42.04% time saving with negligible 0.92% Bit-Distortion (BD)-rate loss. Furthermore, in order to calculate the optimal thresholds to balance BD-rate loss and complexity reduction, the neural network based mathematical fitting is added to BTFA, which is called the advanced bagged trees based fast approach (ABTFA). Finally, experimental results show that ABTFA achieves 47.87% time saving with only 0.96% BD-rate loss, which outperforms other state-of-the-art approaches.
Managing Wireless Communications for Emergency Situations in Urban Environments through Cyber-Physical Systems and 5G Technologies
Authors: Bordel Sánchez Borja , Alcarria Ramón , Robles Tomás
Published: September 2020

Currently, urban environments are the basic human habitat. Large and complex infrastructures coordinate urban life and make it possible in high-density scenarios. In this context, one basic infrastructure to be considered is communication networks. Nowadays, even emergency response teams (ERT) are dependent on those deployments. However, emergencies may cause important damage in those communication infrastructures and, then, a critical discoordination among ERT might appear, greatly affecting the ERT efficiency and response capacity. Different architectures to address this situation have been recently proposed, but none of them are able to dynamically adapt to highly variable situations such as emergency crisis. Therefore, in this paper, a new approach is proposed for ad hoc emergency wireless communications in urban environments based on 5G technologies and Cyber-Physical Systems (CPS). The proposed architecture consists of three layers, where different feedback control loops are defined and linked following the CPS paradigm. At physical level, the spectrum usage is monitored through CPS control loops, analyzing if power signals present a good quality. At network level, 5G virtualization technologies are employed to manage in a dynamic way the network configuration and user management. Finally, at service level, the global situation is analyzed to decide about what services from a catalogue, and according to their priority, can be deployed, including the amount of assigned resources. To evaluate the performance of the proposed solution, an experimental validation based on simulation techniques is also described.
A New Text Classification Model Based on Contrastive Word Embedding for Detecting Cybersecurity Intelligence in Twitter
Authors: Shin Han-Sub , Kwon Hyuk-Yoon , Ryu Seung-Jin
Published: September 2020

Detecting cybersecurity intelligence (CSI) on social media such as Twitter is crucial because it allows security experts to respond cyber threats in advance. In this paper, we devise a new text classification model based on deep learning to classify CSI-positive and -negative tweets from a collection of tweets. For this, we propose a novel word embedding model, called contrastive word embedding, that enables to maximize the difference between base embedding models. First, we define CSI-positive and -negative corpora, which are used for constructing embedding models. Here, to supplement the imbalance of tweet data sets, we additionally employ the background knowledge for each tweet corpus: (1) CVE data set for CSI-positive corpus and (2) Wikitext data set for CSI-negative corpus. Second, we adopt the deep learning models such as CNN or LSTM to extract adequate feature vectors from the embedding models and integrate the feature vectors into one classifier. To validate the effectiveness of the proposed model, we compare our method with two baseline classification models: (1) a model based on a single embedding model constructed with CSI-positive corpus only and (2) another model with CSI-negative corpus only. As a result, we indicate that the proposed model shows high accuracy, i.e., 0.934 of F1-score and 0.935 of area under the curve (AUC), which improves the baseline models by 1.76∼6.74% of F1-score and by 1.64∼6.98% of AUC.
Multi-Sensor Image Fusion Using Optimized Support Vector Machine and Multiscale Weighted Principal Component Analysis
Authors: Huang Shanshan , Yang Yikun , Jin Xin , Zhang Ya , Jiang Qian , Yao Shaowen
Published: September 2020

Multi-sensor image fusion is used to combine the complementary information of source images from the multiple sensors. Recently, conventional image fusion schemes based on signal processing techniques have been studied extensively, and machine learning-based techniques have been introduced into image fusion because of the prominent advantages. In this work, a new multi-sensor image fusion method based on the support vector machine and principal component analysis is proposed. First, the key features of the source images are extracted by combining the sliding window technique and five effective evaluation indicators. Second, a trained support vector machine model is used to extract the focus region and the non-focus region of the source images according to the extracted image features, the fusion decision is therefore obtained for each source image. Then, the consistency verification operation is used to absorb a single singular point in the decisions of the trained classifier. Finally, a novel method based on principal component analysis and the multi-scale sliding window is proposed to handle the disputed areas in the fusion decision pair. Experiments are performed to verify the performance of the new combined method.
Impact of a Composite Trombe Wall Incorporating Phase Change Materials on the Thermal Behavior of an Individual House with Low Energy Consumption
Authors: Leang Enghok , Tittelein Pierre , Zalewski Laurent , Lassue Stéphane
Published: September 2020

As the heating demands of buildings drop considerably, the use of solar walls makes increasing sense. One of the obstacles to the development of such walls is their need for on-site implementation by specialized companies. On the other hand, a storage wall is generally composed of heavy materials with high inertia, which prevents prefabrication of the solar component. To avoid this problem and allow for solar walls to be prefabricated in the factory, a novel approach to replacing this heavy wall with a lighter storage wall incorporating phase change materials (PCM) has been proposed. This paper aims to demonstrate the impact of PCM on the thermal energy performance once they have been integrated into the storage wall of the composite Trombe wall. Addressed herein will be the heat transfer exchange inside a house located in the northern part of France, where a composite Trombe wall has been fitted without PCM. Three configurations will be investigated—(1) the model house without the solar Trombe wall, defined as the reference configuration; (2) the model house integrating the concrete solar Trombe wall; and (3) the model house integrating the PCM solar Trombe wall. Two setpoint temperatures will be introduced—(a) a constant setpoint of 20 °C, and (b) a variable setpoint of 19 °C (14 h from 7:00 a.m. to 9:00 p.m.) and 16 °C (10 h from 9:00 p.m. to 7:00 a.m.). Furthermore, three different climate conditions will be adopted to run simulations—Paris-Orly, Lyon, and Nice. Dymola/Modelica, a dynamic thermal simulation tool, will be utilized to simulate the thermal performance of these defined configurations. The results obtained, regarding a solar Trombe wall installation that applies two distinct storage walls exposed to the weather of Paris, showed similar minimizations of the one-year energy heating demand inside the bedroom, equal to roughly 20% (i.e., 20.45% of concrete storage wall and 19.90% of PCM storage wall) compared to the reference configuration (i.e., the house with no solar Trombe wall). Based on the imposed setpoint temperature by means of night and day reductions, the resulting heating energy demand in the bedroom, through application of the two storage walls (concrete and PCM) and three different climatic regions could be minimized by 20.34% in Paris, 20.20% in Lyon, and 68.10% in Nice (for the concrete storage wall) vs. the reference configuration; and by 18.79% in Paris, 19.56% in Lyon, and 55.15% in Nice (for the PCM storage wall) vs. the reference configuration.
Design of Battery Storage System for Malaysia Low Voltage Distribution Network with the Presence of Residential Solar Photovoltaic System
Authors: Shamshiri Meysam , Gan Chin Kim , Sardi Junainah , Au Mau Teng , Tee Wei Hown
Published: September 2020

The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reduction.
The Impact of the Ventilation System on the Methane Release Hazard and Spontaneous Combustion of Coal in the Area of Exploitation—A Case Study
Authors: Tutak Magdalena , Brodny Jarosław , Szurgacz Dawid , Sobik Leszek , Zhironkin Sergey
Published: September 2020

Various types of natural hazards are inextricably linked to the process of underground hard coal mining. Ventilation hazards—methane and spontaneous combustion of coal—are the most dangerous; they pose a major threat to the safety of the workers and decrease the effectiveness of the whole coal production process. One of the methods designed to limit the consequences of such hazards is based on the selection of a ventilation system that will be suitable for the given mining area. The article presents a case study of an active longwall area, where—due to increasing ventilation hazard (methane and spontaneous combusting of coal)—the whole system was rebuilt. The U-type ventilation system was used in the initial stage of the extraction process, however, it often generated methane in amounts that exceeded the allowable values. Consequently, such conditions forced the change of the ventilation system from a U–type to Y–type system. The new system was installed during the ongoing mining process, unlike the usual practice. The article presents the results of tests on mine gas concentrations and descriptive statistics for both types of ventilation system. The results clearly demonstrate that the U-type longwall ventilation system, in the case of high methane release hazard, prevents safe and effective operation. At the same time, the use of this system limits the carbon oxidation reactions in the goaf, leading to spontaneous heating and combustion, which is confirmed by the low concentrations of gases—by-products of these reactions. In turn, the use of the Y-type longwall ventilation system ensures safe and effective operation in areas with high methane release hazard, but at the same time deteriorates the safety associated with the spontaneous combusting of coal. The presented case—both from a scientific and practical perspective—is quite interesting and greatly broadens the knowledge in the scope of an efficient ventilation system for underground workings.
Fault Prognostics for Photovoltaic Inverter Based on Fast Clustering Algorithm and Gaussian Mixture Model
Authors: He Zhenyu , Zhang Xiaochen , Liu Chao , Han Te
Published: September 2020

The fault prognostics of the photovoltaic (PV) power generation system is expected to be a significant challenge as more and more PV systems with increasingly large capacities continue to come into existence. The PV inverter is the core component of the PV system, and it is essential to develop approaches that accurately predict the occurrence of inverter faults to ensure the PV system’s safety. This paper proposes a fault prognostics method which makes full use of the similarities between inverter clusters. First, a feature space was constructed using the t-distributed stochastic neighbor embedding (t-SNE) algorithm. Then, the fast clustering algorithm was used to search the center inverter of each sampling time from the feature space. The status of the center inverter was adopted to establish the health baseline. Finally, the Gaussian mixture model was established with two data clusters based on the central inverter and the inverter to be predicted. The divergence of the two clusters could be used to predict the inverter’s fault. The performance of the proposed method was evaluated with real PV monitoring data. The experimental results showed that the proposed method successfully predicted the occurrence of an inverter fault 3 months in advance.
A Smart Grid AMI Intrusion Detection Strategy Based on Extreme Learning Machine
Authors: Zhang Ke , Hu Zhi , Zhan Yufei , Wang Xiaofen , Guo Keyi
Published: September 2020

The smart grid is vulnerable to network attacks, thus requiring a high detection rate and fast detection speed for intrusion detection systems. With a fast training speed and a strong model generalization ability, the extreme learning machine (ELM) perfectly meets the needs of intrusion detection of the smart grid. In this paper, the ELM is applied to the field of smart grid intrusion detection. Aiming at the problem that the randomness of input weights and hidden layer bias in the ELM cannot guarantee the optimal performance of the ELM intrusion detection model, a genetic algorithm (GA)-ELM algorithm based on a genetic algorithm (GA) is proposed. GA is used to optimize the input weight and hidden layer bias of the ELM. Firstly, the input weight and hidden layer bias of the ELM are mapped to the chromosome vector of a GA, and the test error of the ELM model is set as the fitness function of the GA. Then, the parameters of the ELM intrusion detection model are optimized by genetic operation; the input weight and bias, corresponding to the minimum test error, are selected to improve the performance of the ELM model. Compared with the ELM and online sequential extreme learning machine (OS-ELM), the GA-ELM effectively improves the accuracy, detection rate and precision of intrusion detection and reduces the false positive rate and missing report rate.
Linkages between Climate, Radial Growth and Defoliation in Abies pinsapo Forests from Southern Spain
Authors: Navarro-Cerrillo Rafael , Gazol Antonio , Rodríguez-Vallejo Carlos , Manzanedo Rubén , Palacios-Rodríguez Guillermo , Camarero J.
Published: September 2020

Systematic forest networks of health monitoring have been established to follow changes in tree vigor and mortality. These networks often lack long-term growth data, but they could be complemented with tree ring data, since both defoliation and radial growth are proxies of changes in tree vigor. For instance, a severe water shortage should reduce growth and increase tree defoliation in drought-prone areas. However, the effects of climatic stress and drought on growth and defoliation could also depend on tree age. To address these issues, we compared growth and defoliation data with recent climate variability and drought severity in Abies pinsapo old and young trees sampled in Southern Spain, where a systematic health network (Andalucía Permanent Plot Network) was established. Our aims were: (i) to assess the growth sensitivity of old and young A. pinsapo trees and (ii) to test if relative changes in radial growth were related with recent defoliation, for instance, after severe droughts. We also computed the resilience indices to quantify how old and young trees recovered growth after recent droughts. Wet-cool conditions during the prior autumn and the current early summer improved the growth of old trees, whereas late-spring wet conditions enhanced the growth of young trees. Old trees were more sensitive to wet and sunny conditions in the early summer than young trees. Old and young trees were more responsive to the Standardized Precipitation-Evapotranspiration Index drought index of June–July and July–August calculated at short (one–three months) and mid (three–six months) time scales, respectively. Old trees presented a higher resistance to a severe drought in 1995 than young trees. A positive association was found between stand defoliation and relative growth. Combining monitoring and tree ring networks is useful for the detection of early warning signals of dieback in similar drought-prone forests.
Mixed Effectiveness of REDD+ Subnational Initiatives after 10 Years of Interventions on the Yucatan Peninsula, Mexico
Authors: Ellis Edward A. , Sierra-Huelsz José Antonio , Ceballos Gustavo Celestino Ortíz , Binnqüist Citlalli López , Cerdán Carlos R.
Published: September 2020

Since 2010, the Reducing Emissions from Deforestation and Degradation (REDD+) mechanism has been implemented in Mexico’s Yucatan Peninsula, a biodiversity hotspot with persistent deforestation problems. We apply the before-after-control-intervention approach and quasi-experimental methods to evaluate the effectiveness of REDD+ interventions in reducing deforestation at municipal (meso) and community (micro) scales. Difference-in-differences regression and propensity score matching did not show an overall reduction in forest cover loss from REDD+ projects at both scales. However, Synthetic Control Method (SCM) analyses demonstrated mixed REDD+ effectiveness among intervened municipalities and communities. Funding agencies and number of REDD+ projects intervening in a municipality or community did not appear to affect REDD+ outcomes. However, cattle production and commercial agriculture land uses tended to impede REDD+ effectiveness. Cases of communities with important forestry enterprises exemplified reduced forest cover loss but not when cattle production was present. Communities and municipalities with negative REDD+ outcomes were notable along the southern region bordering Guatemala and Belize, a remote forest frontier fraught with illegal activities and socio-environmental conflicts. We hypothesize that strengthening community governance and organizational capacity results in REDD+ effectiveness. The observed successes and problems in intervened communities deserve closer examination for REDD+ future planning and development of strategies on the Yucatan Peninsula.
Production and Properties of Starch Citrates—Current Research
Authors: Golachowski Antoni , Drożdż Wioletta , Golachowska Magdalena , Kapelko-Żeberska Małgorzata , Raszewski Bartosz
Published: September 2020

Starch modification by chemical reaction is widely used to improve the properties of native starch. Modified by citric acid, starch is characterized by specific properties resulting from the presence of citrate residues and as a result of cross-linking starch. The chemicals used for preparing starch citrates are safe for human health and the natural environment compared to the harsh chemicals used for conventional modifications. Starch citrates are traditionally produced by heating starch–citric acid mixtures in semi-dry conditions or by a heat moisture treatment. The conditions of the modification process (roasting temperature, heating time, citric acid dose) and the botanic source or genotype of starch determine the degree of substitution and the properties of the obtained preparations. Changes of starch properties occurring during esterification lead to reduced relative crystallinity, resulting in a decrease in the affinity for water, the gelatinization parameters, and the viscosity of starch citrate. However, one of the most important outcome of the modification is the formation of resistant starch (RS), which has increased resistance to the action of amylolytic enzymes. Currently, new methods for producing starch citrates with improved functional and rheological properties while maintaining the highest possible content of resistant starch are being sought. The article presents an overview of recent studies on the production, properties. And applicability of starch citrates with special attention paid to their role as preparations of resistant starch (RS). The use of citric acid for modification of starch is better for the technology process, while using cross-linking is better than simply using esterification.
Associations between Psycho-Hedonic Responses to Sweet and Savoury Tastes with Diet and Body Composition in a Sample of Asian Females
Authors: Lim Amanda JiaYing , Teo Pey Sze , Tan Vicki Wei Kee , Forde Ciarán G.
Published: September 2020

Taste preferences guide food choices and dietary behaviours, yet few studies have shown a relationship between sweet and savoury taste preference and differences in dietary intakes or energy consumed from different “taste clusters”. We investigated differences in psycho-hedonic responses to sweet and savoury tastes and their association with energy intake, proportion of energy from macronutrients and energy intake from different “taste clusters”. In addition, we evaluated correspondence between two methods to classify “sweet-liker” status and the overlap between sweet and savoury taste preferences. Psycho-hedonic responses to sweet and savoury tastes of female participants (n = 66) were captured via staircase paired preference and the “sweet-liker phenotype” classification method. Quantitative dietary energy and macronutrient intakes were measured using three-day food diary, and the relative contributions of specific taste clusters to energy intake were derived for each participant. All participants completed anthropometric assessments measuring body mass index (BMI) and adiposity. Results showed no association between sweet and savoury preferences with dietary energy or macronutrient intakes, though there was a trend towards higher sweet food consumption among “sweet-likers”. A higher preference for savouriness was not associated with differences in daily energy intake, energy intake from protein, BMI or adiposity levels. There was little overlap in sweet and savoury preferences, suggesting a bi-modal split in taste preferences. “Sweet-likers” preferred a higher mean sucrose concentration than sweet “dislikers” (p < 0.001) indicating agreement between the two approaches. Future studies should consider comparing taste-liker differences using food choice tasks to address the current gap between taste preference measures and actual dietary behaviours.
Ultrasound Therapy: Experiences and Perspectives for Regenerative Medicine
Authors: de Lucas Beatriz , Pérez Laura M. , Bernal Aurora , Gálvez Beatriz G.
Published: September 2020

Ultrasound has emerged as a novel tool for clinical applications, particularly in the context of regenerative medicine. Due to its unique physico-mechanical properties, low-intensity ultrasound (LIUS) has been approved for accelerated fracture healing and for the treatment of established non-union, but its utility has extended beyond tissue engineering to other fields, including cell regeneration. Cells and tissues respond to acoustic ultrasound by switching on genetic repair circuits, triggering a cascade of molecular signals that promote cell proliferation, adhesion, migration, differentiation, and extracellular matrix production. LIUS also induces angiogenesis and tissue regeneration and has anti-inflammatory and anti-degenerative effects. Accordingly, the potential application of ultrasound for tissue repair/regeneration has been tested in several studies as a stand-alone treatment and, more recently, as an adjunct to cell-based therapies. For example, ultrasound has been proposed to improve stem cell homing to target tissues due to its ability to create a transitional and local gradient of cytokines and chemokines. In this review, we provide an overview of the many applications of ultrasound in clinical medicine, with a focus on its value as an adjunct to cell-based interventions. Finally, we discuss the various preclinical and clinical studies that have investigated the potential of ultrasound for regenerative medicine.