bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Recovery of Antioxidant Compounds from Hazelnut (Corylus avellana L.) Involucre Based on Extraction Optimization: Phytochemical Profile and Biological Activities
Authors: Rusu Marius Emil , Fizeșan Ionel , Pop Anca , Gheldiu Ana-Maria , Mocan Andrei , Crișan Gianina , Vlase Laurian , Loghin Felicia , Popa Daniela-Saveta , Tomuta Ioan
Published: October 2019

Tree nut by-products could contain a wide range of phytochemicals, natural antioxidants, which might be used as a natural source for dietary supplements. The aim of the present study was to evaluate the phenolic and sterolic composition, as well as the antioxidant and other biological activities, of hazelnut involucre (HI) extracts. Experimental designs were developed in order to select the optimum extraction conditions (solvent, temperature, time) using turbo-extraction by Ultra-Turrax for obtaining extracts rich in bioactive compounds. Qualitative and quantitative analyses were performed by LC-MS and LC-MS/MS and they revealed important amounts of individual polyphenols and phytosterols, molecules with antioxidant potential. The richest polyphenolic HI extract with the highest antioxidant activity by TEAC assay was further evaluated by other in vitro antioxidant tests (DPPH, FRAP) and enzyme inhibitory assays. Additionally, the cytotoxic and antioxidant effects of this extract on two cancerous cell lines and on normal cells were tested. This is the first study to analyze the composition of both hydrophilic and lipophilic bioactive compounds in HI extracts. Our findings reveal that this plant by-product presents strong biological activities, justifying further research, and it could be considered an inexpensive source of natural antioxidants for food, pharmaceutical, or cosmetic industry.
In Vitro Toxicity Assessment of Stilbene Extract for Its Potential Use as Antioxidant in the Wine Industry
Authors: Medrano-Padial Concepción , Puerto María , Moreno F. Javier , Richard Tristan , Cantos-Villar Emma , Pichardo Silvia
Published: October 2019

The reduction of sulfur dioxide in wine is a consumer’s demand, considering the allergic effects that may occur in people who are sensitive to it. Stilbenes are candidates of great interest for this purpose because of their antioxidant/antimicrobial activities and health properties, and also because they are naturally found in the grapevine. In the present study, the in vitro toxicity of an extract from grapevine shoots (with a stilbene richness of 45.4%) was assessed in two human cell lines. Significant damage was observed from 30 μg/mL after 24 h, and 40 µg/mL after 48 h of exposure. Similarly, the ultrastructural study revealed a significant impairment of cell growing. The extract was able to protect cells against an induced oxidative stress at all concentrations studied. In view of the promising results, a more exhaustive toxicological assessment of the extract is needed to confirm the safety of its further use as additive in wine.
Quality and Defect Inspection of Green Coffee Beans Using a Computer Vision System
Authors: García Mauricio , Candelo-Becerra John E. , Hoyos Fredy
Published: October 2019

There is an increased industry demand for efficient and safe methods to select the best-quality coffee beans for a demanding market. Color, morphology, shape and size are important factors that help identify the best quality beans; however, conventional techniques based on visual and/or mechanical inspection are not sufficient to meet the requirements. Therefore, this paper presents an image processing and machine learning technique integrated with an Arduino Mega board, to evaluate those four important factors when selecting best-quality green coffee beans. For this purpose, the k-nearest neighbor algorithm is used to determine the quality of coffee beans and their corresponding defect types. The system consists of logical processes, image processing and the supervised learning algorithms that were programmed with MATLAB and then burned into the Arduino board. The results showed this method has a high effectiveness in classifying each single green coffee bean by identifying its main visual characteristics, and the system can handle several coffee beans present in a single image. Statistical analysis shows the process can identify defects and quality with high accuracy. The artificial vision method was helpful for the selection of quality coffee beans and may be useful to increase production, reduce production time and improve quality control.
Smart Cities Big Data Algorithms for Sensors Location
Authors: Estrada Elsa , Martínez Vargas Martha Patricia , Gómez Judith , Peña Pérez Negron Adriana , López Graciela Lara , Maciel Rocío
Published: October 2019

A significant and very extended approach for Smart Cities is the use of sensors and the analysis of the data generated for the interpretation of phenomena. The proper sensor location represents a key factor for suitable data collection, especially for big data. There are different methodologies to select the places to install sensors. Such methodologies range from a simple grid of the area to the use of complex statistical models to provide their optimal number and distribution, or even the use of a random function within a set of defined positions. We propose the use of the same data generated by the sensor to locate or relocate them in real-time, through what we denominate as a ‘hot-zone’, a perimeter with significant data related to the observed phenomenon. In this paper, we present a process with four phases to calculate the best georeferenced locations for sensors and their visualization on a map. The process was applied to the Guadalajara Metropolitan Zone in Mexico where, during the last twenty years, air quality has been monitored through sensors in ten different locations. As a result, two algorithms were developed. The first one classifies data inputs in order to generate a matrix with frequencies that works along with a matrix of territorial adjacencies. The second algorithm uses training data with machine learning techniques, both running in parallel modes, in order to diagnose the installation of new sensors within the detected hot-zones.
A Weighted Estimation Algorithm for Enhancing Pulsed Eddy Current Infrared Image in Ecpt Non-Destructive Testing
Authors: Li Hanchao , Yu Yating , Li Linfeng , Liu Bowen
Published: October 2019

Non-destructive testing (NDT) plays a crucial role in large scale industrial production such as in the nuclear industry and bridge structures where even a small crack can lead to severe accidents. The pulsed eddy current infrared thermography testing method, as a classic non-destructive testing technology, is proposed to detect cracks in the presence of excitation sources that cause temperature changes in the vicinity of defects, which is higher than normal area. However, in the vicinity of the excitation sources, the temperature is higher than normal even if there is no defect. Traditional infrared image enhancing algorithms do not work efficiently when processing infrared images because the colors in the images represent the temperature. To address this, a novel algorithm is proposed in this paper. A weighted estimation algorithm is proposed because each pixel value has a strong relationship with its neighboring pixels. The value of each pixel is determined by calculating the values of its neighboring pixels with a specific step-size and the correlation coefficients between them. These coefficients are obtained by calculating the differences between the pixels. The experimental results indicated that the outline of the welding defect became significantly clearer after being processed using the proposed algorithm, which can eliminate the errors caused by the excitation source.
Hydrodynamic Ram Effect Caused by Debris Hypervelocity Impact on Satellite Tank
Authors: Zhao Beilei , Zhao Jiguang , Cui Cunyan , Duan Yongsheng
Published: October 2019

To study the hydrodynamic ram effect caused by the debris hypervelocity impact on the satellite tank, a numerical simulation of the spherical debris impacting the satellite tank at the velocity of 7000 m/s was carried out based on ANSYS/LS-DYNA software. The attenuation law of debris velocity, the propagation process of the shock wave and the deformation of the tank walls were investigated. The influences of the liquid-filling ratio, the magnitude, and direction of angular velocity on the hydrodynamic ram effect were analyzed. Results show that the debris velocity decreased rapidly and the residual velocity was 263 m/s when the debris passed through the tank. The shock wave was hemispherical, and the pressure of shock wave was the smallest at the element with an angle of 90° to the impact line. The maximum diameter of the front perforation was larger than that of the back perforation and the bulge height on the front wall was smaller than that on the back wall. With the decrease of the liquid-filling ratio, the diameter of the perforations and bulge height decreased. When the debris impacted the satellite tank with the angular velocity in the x direction, the debris trajectory did not deflect. When the debris impacted the satellite tank with the angular velocities in the y and z direction, the debris trajectory deflected to the negative direction of the z axis and y axis, respectively. The magnitude of the angular velocity affects the residual velocity of debris and the diameter of perforations.
Suppression of Melatonin 2-Hydroxylase Increases Melatonin Production Leading to the Enhanced Abiotic Stress Tolerance against Cadmium, Senescence, Salt, and Tunicamycin in Rice Plants
Authors: Choi Geun-Hee , Back Kyoungwhan
Published: October 2019

Melatonin 2-hydroxylase (M2H) catalyzes the conversion of melatonin into 2hydroxymelatonin (2OHM), which is present in plants at a higher concentration than melatonin. Although M2H has been cloned, the in vivo function of its product is unknown. Here, we generated stable T2 homozygous transgenic rice plants in which expression of endogenous M2H was suppressed (RNAi lines). However, we failed to generate M2H overexpression transgenic rice due to failure of somatic embryogenesis. The M2H transcript level showed a diurnal rhythm with a peak at night concomitantly with the peak concentration of 2OHM. RNAi rice showed a reduced M2H mRNA level and 2OHM and melatonin concentrations. The unexpected decrease in the melatonin concentration was caused by redirection of melatonin into cyclic 3hydroxymelatonin via a detour catabolic pathway. Thus, the decrease in the melatonin concentration in M2H RNAi rice led to slowed seedling growth and delayed germination. By contrast, the transient increase in the melatonin concentration was of greater magnitude in the M2H RNAi than the wild-type rice upon cadmium treatment due to possible suppression of melatonin degradation. Due to its higher concentration of melatonin, the M2H RNAi rice displayed tolerance to senescence, salt, and tunicamycin stresses. Therefore, the increase in the melatonin concentration caused by suppression of melatonin degradation or by overexpression of melatonin biosynthetic genes enhances stress tolerance in rice.
Ascending Axonal Degeneration of the Corticospinal Tract in Pure Hereditary Spastic Paraplegia: A Cross-Sectional DTI Study
Authors: List Julia , Kohl Zacharias , Winkler Juergen , Marxreiter Franz , Doerfler Arnd , Schmidt Manuel A.
Published: October 2019

Objective: To identify structural white matter alterations in patients with pure hereditary spastic paraplegia (HSP) using high angular resolution diffusion tensor imaging (DTI). Methods: We examined 37 individuals with high resolution DTI, 20 patients with pure forms of hereditary spastic paraplegia and 17 age and gender matched healthy controls. DTI was performed using a 3 T clinical scanner with whole brain tract-based spatial statistical (TBSS) analysis of the obtained fractional anisotropy (FA) data as well as a region-of-interest (ROI)-based analysis of affected tracts including the cervical spinal cord. We further conducted correlation analyses between DTI data and clinical characteristics. Results: TBSS analysis in HSP patients showed significantly decreased fractional anisotropy of the corpus callosum and the corticospinal tract compared to healthy controls. ROI-based analysis confirmed significantly lower FA in HSP compared to controls in the internal capsule (0.77 vs. 0.80, p = 0.048), the corpus callosum (0.84 vs. 0.87, p = 0.048) and the cervical spinal cord (0.72 vs. 0.79, p = 0.003). FA values of the cervical spinal cord significantly correlated with disease duration. Conclusion: DTI metrics of the corticospinal tract from the internal capsule to the cervical spine suggest microstructural damage and axonal degeneration of motor neurons. The CST at the level of the cervical spinal cord is thereby more severely affected than the intracranial part of the CST, suggesting an ascending axonal degeneration of the CST. Since there is a significant correlation with disease duration, FA may serve as a future progression marker for assessment of the disease course in HSP.
Endoplasmic Reticulum Stress Signaling as a Therapeutic Target in Malignant Pleural Mesothelioma
Authors: Xu Duo , Yang Haitang , Yang Zhang , Berezowska Sabina , Gao Yanyun , Liang Shun-Qing , Marti Thomas M. , Hall Sean R. R. , Dorn Patrick , Kocher Gregor J. , Schmid Ralph A. , Peng Ren-Wang
Published: October 2019

Malignant pleural mesothelioma (MPM) is a lethal cancer with limited treatment options. No targeted therapy has emerged yet. Here, we performed an integrated molecular characterization of patient tumors in the TCGA dataset, and discovered that endoplasmic reticulum (ER) stress and the adaptive unfolded protein response (UPR) signaling are characteristically deregulated in MPM. Consequently, pharmacological perturbation of ER stress/UPR axis by HA15, an agent that induces persistent proteotoxic stress in the ER, selectively suppresses the viability of MPM cells including those refractory to standard chemotherapy. Mechanically, HA15 augments the already high basal level of ER stress in MPM cells, embarks pro-apoptotic malfunctional UPR and autophagy, which eventually induces cell death in MPM. Importantly, HA15 exerts anti-MPM effectiveness in a mouse model of patient-derived xenografts (PDX) without eliciting overt toxicity when compared to chemotherapy. Our results revealed that programs orchestrating ER stress/UPR signaling represent therapeutic vulnerabilities in MPM and validate HA15 as a promising agent to treat patients with MPM, naïve or resistant to chemotherapy.
Sarcopenia Is a Negative Prognostic Factor in Patients Undergoing Transarterial Chemoembolization (TACE) for Hepatic Malignancies
Authors: Loosen Sven H. , Schulze-Hagen Maximilian , Bruners Philipp , Tacke Frank , Trautwein Christian , Kuhl Christiane , Luedde Tom , Roderburg Christoph
Published: October 2019

Background and Aims: While transarterial chemoembolization (TACE) represents a standard of therapy for intermediate-stage hepatocellular carcinoma (HCC) and is also routinely performed in patients with liver metastases, it is still debated which patients represent the ideal candidates for TACE therapy in terms of overall survival. Sarcopenia, the degenerative loss of skeletal muscle mass and strength, has been associated with an adverse outcome for various malignancies, but its role in the context of TACE has largely remained unknown. Here, we evaluated the role of sarcopenia on the outcome of patients undergoing TACE for primary and secondary liver cancer. Methods: The patients’ psoas muscle size was measured on axial computed tomography (CT) scans and normalized for the patients’ height squared. This value was referred to as the psoas muscle index (PMI). The PMI was correlated with clinical and laboratory markers. Results: While pre-interventional sarcopenia had no impact on the direct tumor response to TACE, sarcopenic patients with a pre-interventional PMI below our ideal cut-off value of 13.39 mm/m2 had a significantly impaired long-term outcome with a median overall survival of 491 days compared to 1291 days for patients with a high PMI. This finding was confirmed by uni- and multivariate Cox-regression analyses. Moreover, a progressive rapid decline in muscle mass after TACE was a predictor for an unfavorable prognosis. Conclusion: Our data suggest that sarcopenia represents a previously unrecognized prognostic factor for patients undergoing TACE therapy which might yield important information on the patients’ post-interventional outcome and should therefore be implemented into clinical stratification algorithms.
Tumor Drug Distribution after Local Drug Delivery by Hyperthermia, In Vivo
Authors: Besse Helena , Barten-van Rijbroek Angelique , van der Wurff-Jacobs Kim , Bos Clemens , Moonen Chrit , Deckers Roel
Published: October 2019

Tumor drug distribution and concentration are important factors for effective tumor treatment. A promising method to enhance the distribution and the concentration of the drug in the tumor is to encapsulate the drug in a temperature sensitive liposome. The aim of this study was to investigate the tumor drug distribution after treatment with various injected doses of different liposomal formulations of doxorubicin, ThermoDox (temperature sensitive liposomes) and DOXIL (non-temperature sensitive liposomes), and free doxorubicin at macroscopic and microscopic levels. Only ThermoDox treatment was combined with hyperthermia. Experiments were performed in mice bearing a human fibrosarcoma. At low and intermediate doses, the largest growth delay was obtained with ThermoDox, and at the largest dose, the largest growth delay was obtained with DOXIL. On histology, tumor areas with increased doxorubicin concentration correlated with decreased cell proliferation, and substantial variations in doxorubicin heterogeneity were observed. ThermoDox treatment resulted in higher tissue drug levels than DOXIL and free doxorubicin for the same dose. A relation with the distance to the vasculature was shown, but vessel perfusion was not always sufficient to determine doxorubicin delivery. Our results indicate that tumor drug distribution is an important factor for effective tumor treatment and that its dependence on delivery formulation merits further systemic investigation.
Epidemiology of Simultaneous Medullary and Papillary Thyroid Carcinomas (MTC/PTC): An Italian Multicenter Study
Authors: Appetecchia Marialuisa , Lauretta Rosa , Barnabei Agnese , Pieruzzi Letizia , Terrenato Irene , Cavedon Elisabetta , Mian Caterina , Castagna Maria , Elisei Rossella
Published: October 2019

Background: The concomitant presence of papillary thyroid cancer (PTC) and medullary TC (MTC) is rare. In this multicentric study, we documented the epidemiological characteristics, disease conditions and clinical outcome of patients with simultaneous MTC/PTC. Methods: We collected data of patients with concomitant MTC/PTC at 14 Italian referral centers. Results: In total, 183 patients were enrolled. Diagnosis was mostly based on cytological examination (n = 58, 32%). At diagnosis, in the majority of cases, both PTC (n = 142, 78%) and MTC (n = 100, 54%) were at stage I. However, more cases of stage II–IV were reported with MTC (stage IV: n = 27, 15%) compared with PTC (n = 9, 5%). Information on survival was available for 165 patients: 109 patients (66%) were disease-free for both PTC and MTC at the last follow-up. Six patients died from MTC. Median time to progression was 123 months (95% confidence interval (CI): 89.3–156.7 months). Overall, 45% of patients were disease-free after >10 years from diagnosis (125 months); this figure was 72.5% for PTC and 51.1% for MTC. Conclusions: When MTC and PTC are concurrent, the priority should be given to the management of MTC since this entity appears associated with the most severe impact on prognosis.
Late Onset of Estrogen Therapy Impairs Carotid Function of Senescent Females in Association with Altered Prostanoid Balance and Upregulation of the Variant ERα36
Authors: Januário Costa Tiago , Jiménez-Altayó Francesc , Echem Cinthya , Akamine Eliana Hiromi , Tostes Rita , Vila Elisabet , Dantas Ana Paula , Catelli de Carvalho Maria Helena
Published: October 2019

Recent analysis of clinical trials on estrogen therapy proposes the existence of a therapeutic window of opportunity for the cardiovascular benefits of estrogens, which depend on women’s age and the onset of therapy initiation. In this study, we aimed to determine how vascular senescence and the onset of estrogen treatment influence the common carotid artery (CCA) function in senescent and non-senescent females. Ovariectomized female senescence-accelerated (SAMP8) or non-senescent (SAMR1) mice were treated with vehicle (OVX) or 17β-estradiol starting at the day of ovariectomy (early-onset, E2E) or 45 days after surgery (late-onset, E2L). In SAMR1, both treatments, E2E and E2L, reduced constriction to phenylephrine (Phe) in CCA [(AUC) OVX: 193.8 ± 15.5; E2E: 128.1 ± 11.6; E2L: 130.2 ± 15.8, p = 0.004] in association with positive regulation of NO/O2- ratio and increased prostacyclin production. In contrast, E2E treatment did not modify vasoconstrictor responses to Phe in OVX-SAMP8 and, yet, E2L increased Phe vasoconstriction [(AUC) OVX: 165.3 ± 10; E2E: 183.3 ± 11.1; E2L: 256.3 ± 30.4, p = 0.005]. Increased vasoconstriction in E2L-SAMP8 was associated with augmented thromboxane A2 and reduced NO production. Analysis of wild-type receptor alpha (ERα66) expression and its variants revealed an increased expression of ERα36 in E2L-SAMP8 in correlation with unfavorable effects of estrogen in those animals. In conclusion, estrogen exerts beneficial effects in non-senescent CCA, regardless of the initiation of the therapy. In senescent CCA, however, estrogen loses its beneficial action even when administered shortly after ovariectomy and may become detrimental when given late after ovariectomy. Aging and onset of estrogen treatment are two critical factors in the mechanism of action of this hormone in CCA.
A Diet Induced Maladaptive Increase in Hepatic Mitochondrial DNA Precedes OXPHOS Defects and May Contribute to Non-Alcoholic Fatty Liver Disease
Authors: Malik Afshan N , Simões Inês C.M. , Rosa Hannah S. , Khan Safa , Karkucinska-Wieckowska Agnieszka , Wieckowski Mariusz R.
Published: October 2019

Non-alcoholic fatty liver disease (NAFLD), an increasingly prevalent and underdiagnosed disease, is postulated to be caused by hepatic fat mediated pathological mechanisms. Mitochondrial dysfunction is proposed to be involved, but it is not known whether this is a pathological driver or a consequence of NAFLD. We postulate that changes to liver mitochondrial DNA (mtDNA) are an early event that precedes mitochondrial dysfunction and irreversible liver damage. To test this hypothesis, we evaluated the impact of diet on liver steatosis, hepatic mtDNA content, and levels of key mitochondrial proteins. Liver tissues from C57BL/6 mice fed with high fat (HF) diet (HFD) and Western diet (WD, high fat and high sugar) for 16 weeks were used. Steatosis/fibrosis were assessed using haematoxylin and eosin (H&E) Oil Red and Masson’s trichome staining and collagen content. Total DNA was isolated, and mtDNA content was determined by quantifying absolute mtDNA copy number/cell using quantitative PCR. Selected mitochondrial proteins were analysed from a proteomics screen. As expected, both HFD and WD resulted in steatosis. Mouse liver contained a high mtDNA content (3617 ± 233 copies per cell), which significantly increased in HFD diet, but this increase was not functional, as indicated by changes in mitochondrial proteins. In the WD fed mice, liver dysfunction was accelerated alongside downregulation of mitochondrial oxidative phosphorylation (OXPHOS) and mtDNA replication machinery as well as upregulation of mtDNA-induced inflammatory pathways. These results demonstrate that diet induced changes in liver mtDNA can occur in a relatively short time; whether these contribute directly or indirectly to subsequent mitochondrial dysfunction and the development of NAFLD remains to be determined. If this hypothesis can be substantiated, then strategies to prevent mtDNA damage in the liver may be needed to prevent development and progression of NAFLD.
Computationally Efficient Force and Moment Models for Propellers in UAV Forward Flight Applications
Authors: Gill Rajan , D’Andrea Raffaello
Published: October 2019

Two low-order, parametric models are developed for the forces and moments that a rotating propeller undergoes in forward flight. The models are derived using a first-principles-based approach, and are computationally efficient in the sense of being represented by explicit expressions. The parameters for the models can be identified either using supervised learning/grey-box fitting from labelled data, or can be predicted using only the static load coefficients (i.e., the hover thrust and torque coefficients). The second model is a multinomial model that is derived by means of a Taylor series expansion of the first model, and can be viewed as a lower-order lumped parameter model. The models and parameter generation methods are experimentally tested against 19 propellers tested in a wind tunnel under oblique flow conditions, for which the data is made available. The models are tested against 181 additional propellers from existing datasets.
Criticality as a Determinant of Integrated Information Φ in Human Brain Networks
Authors: Kim Hyoungkyu , Lee UnCheol
Published: October 2019

Integrated information theory (IIT) describes consciousness as information integrated across highly differentiated but irreducible constituent parts in a system. However, in a complex dynamic system such as the brain, the optimal conditions for large integrated information systems have not been elucidated. In this study, we hypothesized that network criticality, a balanced state between a large variation in functional network configuration and a large constraint on structural network configuration, may be the basis of the emergence of a large Φ, a surrogate of integrated information. We also hypothesized that as consciousness diminishes, the brain loses network criticality and Φ decreases. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness under general anesthesia. In the modeling study, maximal criticality coincided with maximal Φ. The EEG study demonstrated an explicit relationship between Φ, criticality, and level of consciousness. The conscious resting state showed the largest Φ and criticality, whereas the balance between variation and constraint in the brain network broke down as the response rate dwindled. The results suggest network criticality as a necessary condition of a large Φ in the human brain.
Experimental and Numerical Study on the Effect of Interfacial Heat Transfer on Performance of Thermoelectric Generators
Authors: Li Gen , Wang Zhongcheng , Wang Feng , Wang Xiaozhong , Li Shibo , Xue Mingsuo
Published: October 2019

The application of thermoelectric generator (TEG) systems in waste heat recovery has attracted more and more attention. In this work, the effect of interfacial heat transfer on the performance of TEG module was experimentally and numerically investigated. Three kinds of thermal greases with thermal conductivities of 2.0, 2.5, and 3.0 W/(m∙K) were used as thermal interface materials (TIMs) to improve interfacial heat transfer at different external pressures ranging from 0.1 to 0.4 MPa. The open-circuit voltage, output power, and thermal interfacial resistance were measured at different experimental conditions. It was found that the performance of the TEG module can be greatly improved by using thermal greases as TIMs. The open-circuit voltages increased from 1.73 to either 3.07, 3.4, or 3.57 V with k = 2.0, 2.5, and 3.0 W/(m∙K) thermal greases respectively used as TIMs when the temperature difference was 60 °C and external pressure was 0.1 MPa. However, the performance of the TEG was slightly affected by external pressure when thermal greases used as TIMs. The open-circuit voltages were 3.07, 3.13, 3.17, and 3.20 V at external pressures of 0.1, 0.2, 0.3, and 0.4 MPa when the temperature difference ΔT = 60 °C and k = 2.0 W/(m∙K) thermal greases were used as TIMs.
Large Photovoltaic Power Plants Integration: A Review of Challenges and Solutions
Authors: Mansouri Nouha , Lashab Abderezak , Sera Dezso , Guerrero Josep M. , Cherif Adnen
Published: October 2019

Renewable energy systems (RESs), such as photovoltaic (PV) systems, are providing increasingly larger shares of power generation. PV systems are the fastest growing generation technology today with almost ~30% increase since 2015 reaching 509.3 GWp worldwide capacity by the end of 2018 and predicted to reach 1000 GWp by 2022. Due to the fluctuating and intermittent nature of PV systems, their large-scale integration into the grid poses momentous challenges. This paper provides a review of the technical challenges, such as frequency disturbances and voltage limit violation, related to the stability issues due to the large-scale and intensive PV system penetration into the power network. Possible solutions that mitigate the effect of large-scale PV system integration on the grid are also reviewed. Finally, power system stability when faults occur are outlined as well as their respective achievable solutions.
An Enhanced Method to Assess MPC Performance Based on Multi-Step Slow Feature Analysis
Authors: Shang Linyuan , Wang Yanjiang , Deng Xiaogang , Cao Yuping , Wang Ping , Wang Yuhong
Published: October 2019

Due to the wide application of model predictive control (MPC) in industrial processes, the assessment of MPC performance is essential to ensure product quality and improve energy efficiency. Recently, the slow feature analysis (SFA) algorithm has been successfully applied to assess the performance of MPC. However, the disadvantage of the traditional SFA-based predictable index is that it can only extract one-step predictable information in the monitored variables. In order to better mine the predictable information contained in the monitored variables with large lag, an enhanced method to assess MPC performance based on multi-step SFA (MSSFA) is proposed. Based on the relationship between the slowness of slow features (SFs) and data predictability, an MSSFA model SFA(τ) is built through extending the temporal derivatives of the SFs from one step to multiple steps to extract multi-step predictable information in the monitored variables, which is used to construct a multi-step predictable index. Then, the predictable information in the SFs is further extracted for enhancing the multi-step predictable index to improve its sensitivity to performance changes. The effectiveness of the proposed method has been verified through two process simulation examples.
High Reduction Efficiencies of Adsorbed NOx in Pilot-Scale Aftertreatment Using Nonthermal Plasma in Marine Diesel-Engine Exhaust Gas
Authors: Kuwahara Takuya , Yoshida Keiichiro , Kuroki Tomoyuki , Hanamoto Kenichi , Sato Kazutoshi , Okubo Masaaki
Published: October 2019

An efficient NOx reduction aftertreatment technology for a marine diesel engine that combines nonthermal plasma (NTP) and NOx adsorption/desorption is investigated. The aftertreatment technology can also treat particulate matter using a diesel particulate filter and regenerate it via NTP-induced ozone. In this study, the NOx reduction energy efficiency is investigated. The investigated marine diesel engine generates 1 MW of output power at 100% engine load. NOx reduction is performed by repeating adsorption/desorption processes with NOx adsorbents and NOx reduction using NTP. Considering practical use, experiments are performed for a larger number of cycles compared with our previous study; the amount of adsorbent used is 80 kg. The relationship between the mass of desorbed NOx and the energy efficiency of NOx reduction via NTP is established. This aftertreatment has a high reduction efficiency of 71% via NTP and a high energy efficiency of 115 g(NO2)/kWh for a discharge power of 12.0 kW.
Optimal Preventive Maintenance of Wind Turbine Components with Imperfect Continuous Condition Monitoring
Authors: Raza Ahmed , Ulansky Vladimir
Published: October 2019

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.
Energy Use Efficiency Past-to-Future Evaluation: An International Comparison
Authors: Wang Chia-Nan , Nguyen Thi-Duong , Yu Min-Chun
Published: October 2019

Despite the many benefits that energy consumption brings to the economy, consuming energy also leads nations to expend more resources on environmental pollution. Therefore, energy efficiency has been proposed as a solution to improve national economic competitiveness and sustainability. However, the growth in energy demand is accelerating while policy efforts to boost energy efficiency are slowing. To solve this problem, the efficiency gains in countries where energy consumption efficiency is of the greatest concern such as China, India, the United States, and Europe, especially, emerging economies, is central. Additionally, governments must take greater policy actions. Therefore, this paper studied 25 countries from Asia, the Americas, and Europe to develop a method combining the grey method (GM) and data envelopment analysis (DEA) slack-based measure model (SMB) to measure and forecast the energy efficiency, so that detailed energy efficiency evaluation can be made from the past to the future; moreover, this method can be extended to more countries around the world. The results of this study reveal that European countries have a higher energy efficiency than countries in Americas (except the United States) and Asian countries. Our findings also show that an excess of total energy consumption is the main reason causing the energy inefficiency in most countries. This study contributes to policymaking and strategy makers by sharing the understanding of the status of energy efficiency and providing insights for the future.
Separation Flow Control of a Generic Ground Vehicle Using an SDBD Plasma Actuator
Authors: Hui Zheng , Hu Xingjun , Guo Peng , Wang Zewei , Wang Jingyu
Published: October 2019

Quiescent flow and wind tunnel tests were performed to gain additional physical insights into flow control for automotive aerodynamics using surface dielectric barrier discharge plasma actuators. First, the aerodynamic characteristics of ionic wind were studied, and a maximum induced velocity of 3.3 m/s was achieved at an excitation voltage of 17 kV. Then, the optimal installation position of the actuator and the influence of the excitation voltage on flow control at different wind speeds were studied. The conclusions drawn are as follows. The effect of flow control is better when the upper electrode of the actuator is placed at the end of the top surface, increasing the likelihood of the plasma generation region approaching the natural separation location. The pressure on top of the slanted surface is primarily affected by airflow acceleration at a low excitation voltage and by the decrease of the separation zone at a high excitation voltage. The maximum drag reduction can be realized when the maximum velocity of ionic wind reaches 1.71 m/s at a wind speed of 10 m/s and 2.54 m/s at a wind speed of 15 m/s. Moreover, effective drag reduction can be achieved only by continuing to optimize the actuator to generate considerable thrust at a high wind speed.
Stochastic Bilevel Program for Optimal Coordinated Energy Trading of an EV Aggregator
Authors: Vardanyan Yelena , Madsen Henrik
Published: October 2019

Gradually replacing fossil-fueled vehicles in the transport sector with Electric Vehicles (EVs) may help ensure a sustainable future. With regard to the charging electric load of EVs, optimal scheduling of EV batteries, controlled by an aggregating agent, may provide flexibility and increase system efficiency. This work proposes a stochastic bilevel optimization problem based on the Stackelberg game to create price incentives that generate optimal trading plans for an EV aggregator in day-ahead, intra-day and real-time markets. The upper level represents the profit maximizer EV aggregator who participates in three sequential markets and is called a Stackelberg leader, while the second level represents the EV owner who aims at minimizing the EV charging cost, and who is called a Stackelberg follower. This formulation determines endogenously the profit-maximizing price levels constraint by cost-minimizing EV charging plans. To solve the proposed stochastic bilevel program, the second level is replaced by its optimality conditions. The strong duality theorem is deployed to substitute the complementary slackness condition. The final model is a stochastic convex problem which can be solved efficiently to determine the global optimality. Illustrative results are reported based on a small case with two vehicles. The numerical results rely on applying the proposed methodology to a large scale fleet of 100, 500, 1000 vehicles, which provides insights into the computational tractability of the current formulation.
Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir
Authors: Liu Yi , Jiang Zhiqiang , Feng Zhongkai , Chen Yuyun , Zhang Hairong , Chen Ping
Published: October 2019

In view of the problems that have not been solved or studied in the previous studies of cascade Energy Storage Operation Chart (ESOC), based on a brief description of the composition, principle, drawing methods, and simulation methods of ESOC, the following innovative work has been done in this paper. Firstly, considering the inconsistency of inflow frequency of upstream and downstream watershed in selecting the typical dry years, a novel optimization model for selecting the overall inflow process considering the integrity of watershed was proposed, which aimed at minimizing the sum of squares of inflow frequency differences. Secondly, aiming at the influence of output coefficients (including number and values) on the results of ESOC, this paper proposed a new method to construct the initial solution of output coefficients and established an optimization model of output coefficients based on progressive optimality algorithms. Thirdly, to the optimization of ESOC with multi-year regulating reservoir, a discrete optimization model of drawdown level was constructed based on the idea of ergodic optimization. On these bases, taking the seven reservoirs in the Yalong River basin of China as an example, the typical dry years considering the inflow frequency inconsistency, the optimal output coefficients of ESOC and the optimal end-of-year drawdown level of a multi-year regulating reservoir (Lianghekou) were obtained, and compared with the previous research results, the ESOC optimized in this paper can increase the total power generation of the cascade system by 9% under the condition that the guaranteed rate did not change much. Furthermore, the difference of the optimal end-of-year drawdown levels between the cascade joint operation and single reservoir operation was discussed for the Lianghekou reservoir at the end of the case study. The obtained results were of great significance for guiding the actual operation of cascade reservoirs.
Solar Panels as Tip Masses in Low Frequency Vibration Harvesters
Authors: Wang Jie , Nabawy Mostafa R. A. , Cioncolini Andrea , Revell Alistair
Published: October 2019

Tip masses are used in cantilevered piezoelectric energy harvesters to shift device resonance towards the required frequency for harvesting and to improve the electric power generation. Tip masses are typically in the form of concentrated passive weights. The aim of this study is to assess the inclusion of solar panels as active tip masses on the dynamics and power generation performance of cantilevered PVDF (polyvinylidene fluoride)-based vibration energy harvesters. Four different harvester geometries with and without solar panels are realized using off-the-shelf components. Our experimental results show that the flexible solar panels considered in this study are capable of reducing resonance frequency by up to 14% and increasing the PVDF power generated by up to 54%. Two analytical models are developed to investigate this concept; employing both an equivalent concentrated tip mass to represent the case of flexible solar panels and a distributed tip mass to represent rigid panels. Good prediction agreement with experimental results is achieved with an average error in peak power of less than 5% for the cases considered. The models are also used to identify optimum tip mass configurations. For the flexible solar panel model, it is found that the highest PVDF power output is produced when the length of solar panels is two thirds of the total length. On the other hand, results from the rigid solar panel model show that the optimum length of solar panels increases with the relative tip mass ratio, approaching an asymptotic value of half of the total length as the relative tip mass ratio increases significantly.
Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model
Authors: Bapin Yerzhigit , Bagheri Mehdi , Zarikas Vasilios
Published: October 2019

The proposed study presents a novel probabilistic method for optimal allocation of spinning reserves taking into consideration load, wind and solar forecast errors, inter-zonal spinning reserve trading, and demand response provided by consumers as a single framework. The model considers the system contingencies due to random generator outages as well as the uncertainties caused by load and renewable energy forecast errors. The study utilizes a novel approach to model wind speed and its direction using the bivariate parametric model. The proposed model is applied to the IEEE two-area reliability test system (RTS) to analyze the influence of inter-zonal power generation and demand response (DR) on the adequacy and economic efficiency of energy systems. In addition, the study analyzed the effect of the bivariate wind prediction model on obtained results. The results demonstrate that the presence of inter-zonal capacity in ancillary service markets reduce the total expected energy not supplied (EENS) by 81.66%, while inclusion of a DR program results in an additional 1.76% reduction of EENS. Finally, the proposed bivariate wind prediction model showed a 0.27% reduction in spinning reserve requirements, compared to the univariate model.
Soil Nematode Fauna and Microbial Characteristics in an Early-Successional Forest Ecosystem
Authors: Renčo Marek , Čerevková Andrea , Gömöryová Erika
Published: October 2019

Windstorms can often decrease the diversity of native local biota in European forests. The effects of windstorms on the species richness of flora and fauna in coniferous forests of natural reserves are well established, but the effects on biotas in productive deciduous forests have been less well studied. We analyzed the impact of windstorms on the diversity and abundance of soil nematode communities and microbial activity and their relationships with the succession of plant species and basic soil physicochemical properties 12 and 36 months after a windstorm in Fagus sylvatica forests. The relationships were investigated in cleared early-successional forest ecosystems and at undamaged forest sites as a control. The windstorm significantly affected total nematode abundance, number of nematode species, and the diversity and abundance of all nematode functional guilds, but no functional guilds disappeared after the disturbance. The abundance of several nematode taxa but not total nematode abundance was positively correlated with soil-moisture content. Indices of the nematode communities were inconsistent between sites due to their variable ability to identify ecosystem disturbance 12 months after the storm. In contrast, the metabolic activity of various functional groups identified ecosystem disturbance well throughout the study. Positive correlations were identified between the number of plant parasites and soil-moisture content and between carnivore abundance and soil pH. Positive mutual links of some nematode genera (mainly plant parasites) with the distribution of dominant grasses and herbs depended on the habitat. In contrast, microbial activity differed significantly between disturbed and undisturbed sites up to 36 months after the storm, especially soil basal respiration, N mineralization, and microbial biomass. Our results indicated different temporal responses for two groups of soil organisms to the destruction of the tree canopy. Soil nematodes reacted immediately, but changes in the microbial communities were visible much later after the disturbance.
Canopy Temperature Differences between Liana-Infested and Non-Liana Infested Areas in a Neotropical Dry Forest
Authors: Yuan Xu , Laakso Kati , Marzahn Philip , Sanchez-Azofeifa G. Arturo
Published: October 2019

Lianas (woody vines) are important non-structural elements of all tropical forests. Current field observations across the Neotropics suggest that liana abundance is rising as a result of forest disturbance, increasing atmospheric CO2, and more frequent extreme climate events. Lianas can cause mechanical stress on their host trees, thus increasing mortality, in addition to potentially reducing carbon storage capacity. Furthermore, previous studies have suggested that liana leaves have an overall higher temperature than tree leaves, which presents the question of whether these differences can be extended from the leaf to the canopy. In this context, the ability to detect these temperature differences from a remote sensing platform has so far not been put into test, despite the importance such knowledge can have in large-scale land surface modeling studies and liana extent monitoring. To partially fill this knowledge gap, we acquired thermal infrared data using an unmanned aerial vehicle (UAV) system over an intermediate tropical dry forest in Costa Rica, Central America. Classification results from a previous study in the same area were used to subset the thermal infrared images into liana-infested areas, non-liana infested areas, and forest gaps. The temperature differences between these three image components were then investigated using the Welch and Games–Howell post-hoc statistical tests. Our results suggest that liana-infested areas have, on average, a statistically significant higher temperature than non-liana infested areas. Shadowed forest gaps, used as reference, have a cooler temperature than forest canopies. Our findings on the temperature differences between liana-infested and non-liana infested areas support previous leaf-level observations and open the door to the use of new approaches for the classification and modeling of liana infestation in tropical ecosystems.