bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation Tool for Tuning and Performance Analysis of Robust, Tracking, Disturbance Rejection and Aggressiveness Controller
Authors: Bagyaveereswaran Veeramani , Umashankar Subramaniam , Arulmozhivarman Pachiyappan
Published: July 2019

The RTD-A (robust, tracking, disturbance rejection and aggressiveness) controller is a novel control scheme that substitutes the classical proportional integral derivative (PID) controller. This novel controller’s performance depends on the four controller tuning parameters (θR, θT, θD and θA). The tuning of RTD-A controller is more transparent than classic PID controllers. The RTD-A tuning parameters values lies between ZERO and ONE. Availability of a tool to design optimal parameters for this controller and evaluating the performance on a given system is necessary for the researchers. In this paper, the new simulation tool is presented to deal with the RTD-A control scheme. There are four graphical user interface tools included in the proposed tool and working of each tool is explained in detail. To demonstrate the proposed tool, two examples, which involve a liquid level control application and an air pressure control application, are presented in this work. The performance of the RTD-A controller is compared with PID controller. RTD-A controllers are tuned using optimization algorithms and their performances are observed and analyzed in both cases under deterministic and uncertain conditions.
Dynamic Spatial Responsiveness in Concert Halls
Authors: Green Evan , Kahle Eckhard
Published: July 2019

In musical perception, a proportion of the reflected sound energy arriving at the ear is not consciously perceived. Investigations by Wettschurek in the 1970s showed the detectability to be dependent on the overall loudness and direction of arrival of reflected sound. The relationship Wettschurek found between reflection detectability, listening level, and direction of arrival correlates well with the subjective progression of spatial response during a musical crescendo: from frontal at pianissimo, through increasing apparent source width, to a fully present room acoustic at forte. “Dynamic spatial responsiveness” was mentioned in some of the earliest psychoacoustics research and recent work indicates that it is a key factor in acoustical preference. This article describes measurements of perception thresholds made using a binaural virtual acoustics system—these show good agreement with Wettschurek’s results. The perception measurements indicate that the subjective effect of reflections varies with overall listening level, even when the reflection level, delay, and direction relative to the direct sound are maintained. Reflections which are perceptually fused with the source may at louder overall listening levels become allocated to the room presence. An algorithm has been developed to visualize dynamic spatial responsiveness—i.e., which aspects of a three-dimensional (3D) Room Impulse Response would be detectable at different dynamic levels—and has been applied to measured concert hall impulse responses.
Advantages and Disadvantages of Surround-Type Concert Halls
Authors: Harris Robert
Published: July 2019

Following the significant number of new shoebox-type halls that opened in the last decades of the 20th century, the first decades of the 21st century have seen large concert hall design and construction dominated by halls in a surround format. This typology is characterised by the audience surrounding the concert platform, with a significant percentage of the audience seated to the sides of or behind the platform. These halls often use vineyard-style terracing. This paper discusses some advantages and disadvantages of surround halls, with respect to both acoustics and wider performance aspects. The perspectives of audiences, performers and hall operators are considered. Factors include acoustical quality, equality of audience experience, multiple performance genre use and ticket revenue. In particular, the implications of locating a high percentage of the audience behind the concert platform are examined. This is because, in most surround halls, a significantly higher percentage of the audience is located behind the platform as compared, for example, to shoebox halls.
Deciphering the Molecular Basis of Melatonin Protective Effects on Breast Cells Treated with Doxorubicin: TWIST1 a Transcription Factor Involved in EMT and Metastasis, a Novel Target of Melatonin
Authors: Menéndez-Menéndez Javier , Hermida-Prado Francisco , Granda-Díaz Rocío , González Alicia , García-Pedrero Juana María , Del-Río-Ibisate Nagore , González-González Alicia , Cos Samuel , Alonso-González Carolina , Martínez-Campa Carlos
Published: July 2019

Melatonin mitigates cancer initiation, progression and metastasis through inhibition of both the synthesis of estrogens and the transcriptional activity of the estradiol-ER (Estrogen receptor) complex in the estrogen-dependent breast cancer cell line MCF-7. Moreover, melatonin improves the sensitivity of MCF-7 to chemotherapeutic agents and protects against their side effects. It has been described that melatonin potentiates the anti-proliferative effects of doxorubicin; however, the molecular changes involving gene expression and the activation/inhibition of intracellular signaling pathways remain largely unknown. Here we found that melatonin enhanced the anti-proliferative effect of doxorubicin in MCF-7 but not in MDA-MB-231 cells. Strikingly, doxorubicin treatment induced cell migration and invasion, and melatonin effectively counteracted these effects in MCF-7 but not in estrogen-independent MDA-MB-231 cells. Importantly, we describe for the first time the ability of melatonin to downregulate TWIST1 (Twist-related protein 1) in estrogen-dependent but not in estrogen-independent breast cancer cells. Combined with doxorubicin, melatonin inhibited the activation of p70S6K and modulated the expression of breast cancer, angiogenesis and clock genes. Moreover, melatonin regulates the levels of TWIST1-related microRNAs, such as miR-10a, miR-10b and miR-34a. Since TWIST1 plays a pivotal role in the epithelial to mesenchymal transition, acquisition of metastatic phenotype and angiogenesis, our results suggest that inhibition of TWIST1 by melatonin might be a crucial mechanism of overcoming resistance and improving the oncostatic potential of doxorubicin in estrogen-dependent breast cancer cells.
Comparative Assessment of Antitumor Effects and Autophagy Induction as a Resistance Mechanism by Cytotoxics and EZH2 Inhibition in INI1-Negative Epithelioid Sarcoma Patient-Derived Xenograft
Authors: Stacchiotti Silvia , Zuco Valentina , Tortoreto Monica , Cominetti Denis , Frezza Anna Maria , Percio Stefano , Indio Valentina , Barisella Marta , Monti Valentina , Brich Silvia , Astolfi Annalisa , Colombo Chiara , Pasquali Sandro , Folini Marco , Gounder Mrinal M. , Pantaleo Maria A. , Collini Paola , Dei Tos Angelo Paolo , Casali Paolo Giovanni , Gronchi Alessandro , Zaffaroni Nadia
Published: July 2019

Epithelioid sarcoma (ES) is a rare mesenchymal malignancy marked by SMARCB1/INI1 deficiency. Retrospective clinical data report on the activity of anthracycline- and gemcitabine-based regimens. EZH2 inhibitors are currently being tested in clinical trials. Since comparisons of these agents are unlikely to be prospectively evaluated in the clinics, we took advantage of an INI1-deficient proximal-type ES patient-derived xenograft (PDX ES-1) to comparatively assess its preclinical antitumor activity. Mice were treated with doxorubicin and ifosfamide, singly or in combination, gemcitabine, and the EZH2 inhibitor EPZ-011989. Comparable antitumor activity (max tumor volume inhibition: ~90%) was caused by gemcitabine, EPZ-011989, and the doxorubicin–ifosfamide combination. The integration of RNAseq data, generated on tumors obtained from untreated and EPZ-011989-treated mice, and results from functional studies, carried out on the PDX-derived ES-1 cell line, revealed autophagy induction as a possible survival mechanism in residual tumor cells following EPZ-011989 treatment and identified HMGA2 as a main player in this process. Our data support the clinical use of gemcitabine and the doxorubicin–ifosfamide combination, confirm EZH2 as a therapeutic target in proximal-type ES, and suggest autophagy as a cytoprotective mechanism against EZH2 inhibition.
The Molecular Hallmarks of the Serrated Pathway in Colorectal Cancer
Authors: De Palma Fatima , D’Argenio Valeria , Pol Jonathan , Kroemer Guido , Maiuri Maria , Salvatore Francesco
Published: July 2019

Colorectal cancer (CRC) is a leading cause of cancer death worldwide. It includes different subtypes that differ in their clinical and prognostic features. In the past decade, in addition to the conventional adenoma-carcinoma model, an alternative multistep mechanism of carcinogenesis, namely the “serrated pathway”, has been described. Approximately, 15 to 30% of all CRCs arise from neoplastic serrated polyps, a heterogeneous group of lesions that are histologically classified into three morphologic categories: hyperplastic polyps, sessile serrated adenomas/polyps, and the traditional serrated adenomas/polyps. Serrated polyps are characterized by genetic (BRAF or KRAS mutations) and epigenetic (CpG island methylator phenotype (CIMP)) alterations that cooperate to initiate and drive malignant transformation from normal colon mucosa to polyps, and then to CRC. The high heterogeneity of the serrated lesions renders their diagnostic and pathological interpretation difficult. Hence, novel genetic and epigenetic biomarkers are required for better classification and management of CRCs. To date, several molecular alterations have been associated with the serrated polyp-CRC sequence. In addition, the gut microbiota is emerging as a contributor to/modulator of the serrated pathway. This review summarizes the state of the art of the genetic, epigenetic and microbiota signatures associated with serrated CRCs, together with their clinical implications.
The Bone Extracellular Matrix as an Ideal Milieu for Cancer Cell Metastases
Authors: Kolb Alexus D. , Bussard Karen M.
Published: July 2019

Bone is a preferential site for cancer metastases, including multiple myeloma, prostate, and breast cancers.The composition of bone, especially the extracellular matrix (ECM), make it an attractive site for cancer cell colonization and survival. The bone ECM is composed of living cells embedded within a matrix composed of both organic and inorganic components. Among the organic components, type I collagen provides the tensile strength of bone. Inorganic components, including hydroxyapatite crystals, are an integral component of bone and provide bone with its rigidity. Under normal circumstances, two of the main cell types in bone, the osteoblasts and osteoclasts, help to maintain bone homeostasis and remodeling through cellular communication and response to biophysical signals from the ECM. However, under pathological conditions, including osteoporosis and cancer, bone remodeling is dysregulated. Once in the bone matrix, disseminated tumor cells utilize normal products of bone remodeling, such as collagen type I, to fuel cancer cell proliferation and lesion outgrowth. Models to study the complex interactions between the bone matrix and metastatic cancer cells are limited. Advances in understanding the interactions between the bone ECM and bone metastatic cancer cells are necessary in order to both regulate and prevent metastatic cancer cell growth in bone.
Spatiotemporal pH Heterogeneity as a Promoter of Cancer Progression and Therapeutic Resistance
Authors: Korenchan David E. , Flavell Robert R.
Published: July 2019

Dysregulation of pH in solid tumors is a hallmark of cancer. In recent years, the role of altered pH heterogeneity in space, between benign and aggressive tissues, between individual cancer cells, and between subcellular compartments, has been steadily elucidated. Changes in temporal pH-related processes on both fast and slow time scales, including altered kinetics of bicarbonate-CO2 exchange and its effects on pH buffering and gradual, progressive changes driven by changes in metabolism, are further implicated in phenotypic changes observed in cancers. These discoveries have been driven by advances in imaging technologies. This review provides an overview of intra- and extracellular pH alterations in time and space reflected in cancer cells, as well as the available technology to study pH spatiotemporal heterogeneity.
Mutations in the ND2 Subunit of Mitochondrial Complex I Are Sufficient to Confer Increased Tumorigenic and Metastatic Potential to Cancer Cells
Authors: Marco-Brualla Joaquín , Al-Wasaby Sameer , Soler Ruth , Romanos Eduardo , Conde Blanca , Justo-Méndez Raquel , Enríquez José A. , Fernández-Silva Patricio , Martínez-Lostao Luis , Villalba Martín , Moreno-Loshuertos Raquel , Anel Alberto
Published: July 2019

Multiprotein complexes of the mitochondrial electron transport chain form associations to generate supercomplexes. The relationship between tumor cell ability to assemble mitochondrial supercomplexes, tumorigenesis and metastasis has not been studied thoroughly. The mitochondrial and metabolic differences between L929dt cells, which lost matrix attachment and MHC-I expression, and their parental cell line L929, were analyzed. L929dt cells have lower capacity to generate energy through OXPHOS and lower respiratory capacity than parental L929 cells. Most importantly, L929dt cells show defects in mitochondrial supercomplex assembly, especially in those that contain complex I. These defects correlate with mtDNA mutations in L929dt cells at the ND2 subunit of complex I and are accompanied by a glycolytic shift. In addition, L929dt cells show higher in vivo tumorigenic and metastatic potential than the parental cell line. Cybrids with L929dt mitochondria in L929 nuclear background reproduce all L929dt properties, demonstrating that mitochondrial mutations are responsible for the aggressive tumor phenotype. In spite of their higher tumorigenic potential, L929dt or mitochondrial L929dt cybrid cells are sensitive both in vitro and in vivo to the PDK1 inhibitor dichloroacetate, which favors OXPHOS, suggesting benefits for the use of metabolic inhibitors in the treatment of especially aggressive tumors.
Mathematical Analysis of the Coating Process over a Porous Web Lubricated with Upper-Convected Maxwell Fluid
Authors: Zafar Muhammad , A. Rana Muhammad , Zahid Muhammad , Ahmad Babar
Published: July 2019

The present study offers mathematical calculations of the roll-coating procedure lubricated with an upper-convected Maxwell fluid. An incompressible isothermal viscoelastic fluid was considered, with both the roll and the porous web having uniform velocities. By using the lubrication approximation theory, the desired equations of motion for the fluid applied to the porous web were modelled and analyzed. The suction rate on the web and the injection rate at the roll surface were proportionately anticipated. Results for the velocity profile and pressure gradient were received analytically. Fluid parameters of industrial significance (i.e., detachment point, pressure, sheet/roll separating force, power contribution, and coating thickness) were also calculated numerically. A substantial and monotonic increase was witnessed in these quantities with the increase of flow parameters.
Many-Body Systems and Quantum Chaos: The Multiparticle Quantum Arnol’d Cat
Authors: Mantica Giorgio
Published: July 2019

A multi-particle extension of the Arnol’d cat Hamiltonian system is presented, which can serve as a fully dynamical model of decoherence. The behavior of the von Neumann entropy of the reduced density matrix is studied, in time and as a function of the physical parameters, with special regard to increasing the mass of the cat particle.
Electricity Consumption Forecasting using Support Vector Regression with the Mixture Maximum Correntropy Criterion
Authors: Duan Jiandong , Tian Xuan , Ma Wentao , Qiu Xinyu , Wang Peng , An Lin
Published: July 2019

The electricity consumption forecasting (ECF) technology plays a crucial role in the electricity market. The support vector regression (SVR) is a nonlinear prediction model that can be used for ECF. The electricity consumption (EC) data are usually nonlinear and non-Gaussian and present outliers. The traditional SVR with the mean-square error (MSE), however, is insensitive to outliers and cannot correctly represent the statistical information of errors in non-Gaussian situations. To address this problem, a novel robust forecasting method is developed in this work by using the mixture maximum correntropy criterion (MMCC). The MMCC, as a novel cost function of information theoretic, can be used to solve non-Gaussian signal processing; therefore, in the original SVR, the MSE is replaced by the MMCC to develop a novel robust SVR method (called MMCCSVR) for ECF. Besides, the factors influencing users’ EC are investigated by a data statistical analysis method. We find that the historical temperature and historical EC are the main factors affecting future EC, and thus these two factors are used as the input in the proposed model. Finally, real EC data from a shopping mall in Guangzhou, China, are utilized to test the proposed ECF method. The forecasting results show that the proposed ECF method can effectively improve the accuracy of ECF compared with the traditional SVR and other forecasting algorithms.
Gaussian Belief Propagation for Solving Network Utility Maximization with Delivery Contracts
Authors: Liao Shengbin , Sun Jianyong
Published: July 2019

Classical network utility maximization (NUM) models fail to capture network dynamics, which are of increasing importance for modeling network behaviors. In this paper, we consider the NUM with delivery contracts, which are constraints to the classical model to describe network dynamics. This paper investigates a method to distributively solve the given problem. We first transform the problem into an equivalent model of linear equations by dual decomposition theory, and then use Gaussian belief propagation algorithm to solve the equivalent issue distributively. The proposed algorithm has faster convergence speed than the existing first-order methods and distributed Newton method. Experimental results have demonstrated the effectiveness of our proposed approach.
On MV-Algebraic Versions of the Strong Law of Large Numbers
Authors: Nowak Piotr , Hryniewicz Olgierd
Published: July 2019

Many-valued (MV; the many-valued logics considered by Łukasiewicz)-algebras are algebraic systems that generalize Boolean algebras. The MV-algebraic probability theory involves the notions of the state and observable, which abstract the probability measure and the random variable, both considered in the Kolmogorov probability theory. Within the MV-algebraic probability theory, many important theorems (such as various versions of the central limit theorem or the individual ergodic theorem) have been recently studied and proven. In particular, the counterpart of the Kolmogorov strong law of large numbers (SLLN) for sequences of independent observables has been considered. In this paper, we prove generalized MV-algebraic versions of the SLLN, i.e., counterparts of the Marcinkiewicz–Zygmund and Brunk–Prokhorov SLLN for independent observables, as well as the Korchevsky SLLN, where the independence of observables is not assumed. To this end, we apply the classical probability theory and some measure-theoretic methods. We also analyze examples of applications of the proven theorems. Our results open new directions of development of the MV-algebraic probability theory. They can also be applied to the problem of entropy estimation.
Thermal Optimization of a Dual Pressure Goswami Cycle for Low Grade Thermal Sources
Authors: Guzmán Gustavo , De Los Reyes Lucía , Noriega Eliana , Ramírez Hermes , Bula Antonio , Fontalvo Armando
Published: July 2019

This paper presents a theoretical investigation of a new configuration of the combined power and cooling cycle known as the Goswami cycle. The new configuration consists of two turbines operating at two different working pressures with a low-heat source temperature, below 150 °C. A comprehensive analysis was conducted to determine the effect of key operation parameters such as ammonia mass fraction at the absorber outlet and boiler-rectifier, on the power output, cooling capacity, effective first efficiency, and effective exergy efficiency, while the performance of the dual-pressure configuration was compared with the original single pressure cycle. In addition, a Pareto optimization with a genetic algorithm was conducted to obtain the best power and cooling output combinations to maximize effective first law efficiency. Results showed that the new dual-pressure configuration generated more power than the single pressure cycle, by producing up to 327.8 kW, while the single pressure cycle produced up to 110.8 kW at a 150 °C boiler temperature. However, the results also showed that it reduced the cooling output as there was less mass flow rate in the refrigeration unit. Optimization results showed that optimum effective first law efficiency ranged between 9.1% and 13.7%. The maximum effective first law efficiency at the lowest net power (32 kW) and cooling (0.38 kW) outputs was also shown. On the other hand, it presented 13.6% effective first law efficiency when the net power output was 100 kW and the cooling capacity was 0.38 kW.
Efficacy of Quantitative Muscle Ultrasound Using Texture-Feature Parametric Imaging in Detecting Pompe Disease in Children
Authors: Chiou Hong-Jen , Yeh Chih-Kuang , Hwang Hsuen-En , Liao Yin-Yin
Published: July 2019

Pompe disease is a hereditary neuromuscular disorder attributed to acid α-glucosidase deficiency, and accurately identifying this disease is essential. Our aim was to discriminate normal muscles from neuropathic muscles in children affected by Pompe disease using a texture-feature parametric imaging method that simultaneously considers microstructure and macrostructure. The study included 22 children aged 0.02–54 months with Pompe disease and six healthy children aged 2–12 months with normal muscles. For each subject, transverse ultrasound images of the bilateral rectus femoris and sartorius muscles were obtained. Gray-level co-occurrence matrix-based Haralick’s features were used for constructing parametric images and identifying neuropathic muscles: autocorrelation (AUT), contrast, energy (ENE), entropy (ENT), maximum probability (MAXP), variance (VAR), and cluster prominence (CPR). Stepwise regression was used in feature selection. The Fisher linear discriminant analysis was used for combination of the selected features to distinguish between normal and pathological muscles. The VAR and CPR were the optimal feature set for classifying normal and pathological rectus femoris muscles, whereas the ENE, VAR, and CPR were the optimal feature set for distinguishing between normal and pathological sartorius muscles. The two feature sets were combined to discriminate between children with and without neuropathic muscles affected by Pompe disease, achieving an accuracy of 94.6%, a specificity of 100%, a sensitivity of 93.2%, and an area under the receiver operating characteristic curve of 0.98 ± 0.02. The CPR for the rectus femoris muscles and the AUT, ENT, MAXP, and VAR for the sartorius muscles exhibited statistically significant differences in distinguishing between the infantile-onset Pompe disease and late-onset Pompe disease groups (p < 0.05). Texture-feature parametric imaging can be used to quantify and map tissue structures in skeletal muscles and distinguish between pathological and normal muscles in children or newborns.
Dynamic Maximum Entropy Reduction
Authors: Klika Václav , Pavelka Michal , Vágner Petr , Grmela Miroslav
Published: July 2019

Any physical system can be regarded on different levels of description varying by how detailed the description is. We propose a method called Dynamic MaxEnt (DynMaxEnt) that provides a passage from the more detailed evolution equations to equations for the less detailed state variables. The method is based on explicit recognition of the state and conjugate variables, which can relax towards the respective quasi-equilibria in different ways. Detailed state variables are reduced using the usual principle of maximum entropy (MaxEnt), whereas relaxation of conjugate variables guarantees that the reduced equations are closed. Moreover, an infinite chain of consecutive DynMaxEnt approximations can be constructed. The method is demonstrated on a particle with friction, complex fluids (equipped with conformation and Reynolds stress tensors), hyperbolic heat conduction and magnetohydrodynamics.
Evaluating the Impact of Fossil Fuel Vehicle Exit on the Oil Demand in China
Authors: Feng Ziru , Cai Tian , Xiang Kangli , Xiang Chenxi , Hou Lei
Published: July 2019

Vehicle ownership is one of the most important factors affecting fuel demand. Based on the forecast of China’s vehicle ownership, this paper estimates China’s fuel demand in 2035 and explores the impact of new energy vehicles replacing fossil fuel vehicles. The paper contributes to the existing literature by taking into account the heterogeneity of provinces when using the Gompertz model to forecast future vehicle ownership. On that basis, the fuel demand of each province in 2035 is calculated. The results show that: (1) The vehicle ownership rate of each province conforms to the S-shape trend with the growth of real GDP per capita. At present, most provinces are at a stage of accelerating growth. However, the time for the vehicle ownership rate of each province to reach the inflection point is quite different. (2) Without considering the replacement of new energy vehicles, China’s auto fuel demand is expected to be 746.69 million tonnes (Mt) in 2035. Guangdong, Henan, and Shandong are the top three provinces with the highest fuel demand due to economic and demographic factors. The fuel demand is expected to be 76.76, 64.91, and 63.95 Mt, respectively. (3) Considering the replacement of new energy vehicles, China’s fuel demand in 2035 will be 709.35, 634.68, and 560.02 Mt, respectively, under the scenarios of slow, medium, and fast substitution—and the replacement levels are 37.34, 112.01, and 186.67 Mt, respectively. Under the scenario of rapid substitution, the reduction in fuel demand will reach 52.2% of China’s net oil imports in 2016. Therefore, the withdrawal of fuel vehicles will greatly reduce the oil demand and the dependence on foreign oil of China. Faced with the dual pressure of environmental crisis and energy crisis, the forecast results of this paper provide practical reference for policy makers to rationally design the future fuel vehicle exit plan and solve related environmental issues.
Large-Scale Waste Bio-Remediation Using Microalgae Cultivation as a Platform
Authors: Silkina Alla , Ginnever Naomi E. , Fernandes Fleuriane , Fuentes-Grünewald Claudio
Published: July 2019

Municipal and agricultural waste treatment is one of the key elements of reducing environmental impact with direct effects on the economy and society. Algal technology has been tested to enable effective recycling and valorisation of wastewater nutrients including carbon, nitrogen and phosphorus. An integrated evaluation and optimisation of the sustainability of an algal bio-refinery, including mass and energy balances, carbon, water and nutrient use and impact analysis, was assessed. A bio-refinery approach of waste remediation using algal cultivation was developed at Swansea University, focusing on nutrient recovery via algal biomass exploitation in pilot facilities. Mass cultivation (up to 1.5 m3) was developed with 99% of nitrogen and phosphorus uptake by microalgal cultures. Nannochloropsis oceanica was used as a biological model and grown on three waste sources. The compounds obtained from the biomass were evaluated for animal feed and as a potential source of energy. The bioremediation through algal biotechnology was examined and compared to alternative nutrient recovery passive and active methods in order to know the most efficient way of excess nutrient management. Conclusions emphasise the high potential of algal biotechnology for waste remediation and nutrients recovery, despite the need for further development and scalable applications of this new technology.
Oscillations Analysis of Front-Mounted Beet Topper Machine for Biomass Harvesting
Authors: Bulgakov Volodymyr , Pascuzzi Simone , Anifantis Alexandros Sotirios , Santoro Francesco
Published: July 2019

The beet leaves and tops, which currently are excluded from the production process of sugar, could be an interesting opportunity for the production of renewable energy. Usually, the defoliators are joined with root collar remover machines, which are installed in front of the tractor. In working conditions on soils having natural roughness these front-mounted beet topper machines carried by tractors are affected by angular oscillations in a longitudinal-vertical plane that strongly affect the cutting uniformity. A theoretical study of these oscillations was carried out in this paper using Lagrange II kind equations, with the aim to assess the design and kinematic parameters of a front-mounted beet topper, corresponding to more stable and suitable movements in the longitudinal-vertical plane. A numerical simulation was then performed adopting the developed mathematical model. In order to improve the efficiency of this harvesting machine, a significant role is assumed by the soil preparation. In this work the stiffness and damping parameters of the feeler wheels pneumatic tires have been considered constant but further studies are in progress to assess their effective importance and influence for reducing the vibration of the front-mounted beet topper machine with the final aim to achieve a better machine design.
Control and Restrictions of a Hybrid Renewable Energy System Connected to the Grid: A Battery and Supercapacitor Storage Case
Authors: Arkhangelski Jura , Roncero-Sánchez Pedro , Abdou-Tankari Mahamadou , Vázquez Javier , Lefebvre Gilles
Published: July 2019

This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the high-frequency component of the storage system reference for the supercapacitor from the low-frequency component for the batteries system. This solution greatly increases the reliability and durability of the HRES.
Assessment of Measurement Accuracy of a Micro-PIV Technique for Quantitative Visualization of Al2O3 and MWCNT Nanofluid Flows
Authors: Park Hanwook , Ham Jeonggyun , Cho Honghyun , Jung Sung Yong
Published: July 2019

Nanofluids, which are liquids containing nanoparticles, are used to modify heat transfer performance in various systems. To explain the mechanism of heat transfer modification with nanofluids, many theories have been suggested based on numerical simulations without experimental validation because there is no suitable experimental method for measuring the velocity fields of nanofluid flows. In this study, the measurement accuracy of micro-particle image velocimetry (μ-PIV) is systemically quantified with Al2O3 and multi-walled carbon nanotube (MWCNT) nanofluids. Image quality, cross-correlation signal-to-noise ratio, displacement difference, and spurious vector ratio are investigated with static images obtained at various focal plane positions along the beam pathway. Applicable depth is enough to investigate micro-scale flows when the concentrations of Al2O3 and MWCNT nanofluids are lower than 0.01% and 0.005%, respectively. The velocity fields of Hagen–Poiseuille flow are measured and compared with theoretical velocity profiles. The measured velocity profiles present good agreement with the theoretical profiles throughout. This study provides the criteria for μ-PIV application and demonstrates that μ-PIV is a promising technique for measuring the velocity field information of nanofluids.
Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set
Authors: Lee Jared A. , Doubrawa Paula , Xue Lulin , Newman Andrew J. , Draxl Caroline , Scott George
Published: July 2019

Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found to be skillful and with near-zero average bias (−0.4–0.2 m s−1) when averaged over the domain. Small sample sizes made regional validation noisy, however.
Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar
Authors: Khandakar Amith , E. H. Chowdhury Muhammad , Khoda Kazi Monzure- , Benhmed Kamel , Touati Farid , Al-Hitmi Mohammed , Jr S. P. Gonzales Antonio
Published: July 2019

Photovoltaics (PV) output power is highly sensitive to many environmental parameters and the power produced by the PV systems is significantly affected by the harsh environments. The annual PV power density of around 2000 kWh/m2 in the Arabian Peninsula is an exploitable wealth of energy source. These countries plan to increase the contribution of power from renewable energy (RE) over the years. Due to its abundance, the focus of RE is on solar energy. Evaluation and analysis of PV performance in terms of predicting the output PV power with less error demands investigation of the effects of relevant environmental parameters on its performance. In this paper, the authors have studied the effects of the relevant environmental parameters, such as irradiance, relative humidity, ambient temperature, wind speed, PV surface temperature and accumulated dust on the output power of the PV panel. Calibration of several sensors for an in-house built PV system was described. Several multiple regression models and artificial neural network (ANN)-based prediction models were trained and tested to forecast the hourly power output of the PV system. The ANN models with all the features and features selected using correlation feature selection (CFS) and relief feature selection (ReliefF) techniques were found to successfully predict PV output power with Root Mean Square Error (RMSE) of 2.1436, 6.1555, and 5.5351, respectively. Two different bias calculation techniques were used to evaluate the instances of biased prediction, which can be utilized to reduce bias to improve accuracy. The ANN model outperforms other regression models, such as a linear regression model, M5P decision tree and gaussian process regression (GPR) model. This will have a noteworthy contribution in scaling the PV deployment in countries like Qatar and increase the share of PV power in the national power production.
Battery Remaining Useful Life Prediction with Inheritance Particle Filtering
Authors: Li Lin , Saldivar Alfredo Alan Flores , Bai Yun , Li Yun
Published: July 2019

Accurately forecasting a battery’s remaining useful life (RUL) plays an important role in the prognostics and health management of rechargeable batteries. An effective forecast is reported using a particle filter (PF), but it currently suffers from particle degeneracy and impoverishment deficiencies in RUL evaluations. In this paper, an inheritance PF is developed to predict lithium-ion battery RUL for the first time. A battery degradation model is first mapped onto a PF problem using the genetic algorithm (GA) framework. Then, a Lamarckian inheritance operator is designed to improve the light-weight particles by heavy-weight ones and thus to tackle particle degeneracy. In addition, the inheritance mechanism retains certain existing information to tackle particle impoverishment. The performance of the inheritance PF is compared with an elitism GA-based PF. The former has fewer tuning parameters than the latter and is less sensitive to tuning parameters. Both PFs are applied to the prediction of lithium-ion battery RUL, which is validated using capacity degradation data from the NASA Ames Research Center. The experimental results show that the inheritance PF method offers improved RUL prediction and wider applications. Further improvement is obtained with one-step ahead prediction when the charging and discharging cycles move along.
Evaluating the Operational Potential of LRV Signatures Derived from UAV Imagery in Performance Evaluation of Cool Roofs
Authors: Park Seong-Il , Ryu Taek-Hyoung , Choi Ick-Chang , Um Jung-Sup
Published: July 2019

It is quite difficult to find studies regarding area-wide data from UAV (Unmanned Aerial Vehicle) remote sensing in evaluating the energy saving performance of a cool roof. Acknowledging these constraints, we investigated whether LRV (Light Reflectance Value) signatures derived from UAV imagery could be used effectively as an indicator of area-wide heating and cooling load that distinctively appears according to rooftop color. The case study provides some quantitative tangible evidence for two distinct colors: A whitish color roof appears near the edge of the highest LRV (91.36) and with a low temperature (rooftop surface temperature: (38.03 °C), while a blackish color roof shows the lowest LRV (18.14) with a very high temperature (65.03 °C) where solar radiation is extensively absorbed. A strong negative association (Pearson correlation coefficient, r = −0.76) was observed between the LRV and surface temperature, implying that a higher LRV (e.g., a white color) plays a decisive role in lowering the surface temperature. This research can be used as a valuable reference introducing LRV in evaluating the thermal performance of rooftop color as rooftops satisfying the requirement of a cool roof (reflecting 75% or more of incoming solar energy) are identified based on area-wide objective evidence from UAV imagery.
Design Optimisation of a Unidirectional Centrifugal Radial-Air-Turbine for Application in OWC Wave Energy Converters
Authors: Ansarifard Nazanin , Fleming Alan , Henderson Alan , Kianejad S.S. , Chai Shuhong
Published: July 2019

Research on employing unidirectional air turbines for oscillating water columns (OWC) has received much attention in the last few years. Most unidirectional turbine topologies considered to date use axial flow unidirectional turbines. The radial turbine offers an alternative with increased resistance to backflow. However, in general, the efficiency of radial turbines is lower than axial turbines. This study describes a computational fluid dynamics (CFD)-based design optimisation of an outflow radial turbine for the intended application in an OWC system configured to enable primarily unidirectional flow through the turbine. The rotor blade geometry is parametrically described in addition to other turbine components. The central composite design (CCD) and genetic algorithm were used to explore an optimum design of a centrifugal radial turbine for a maximum total-to-static efficiency. Seven computer aided design (CAD) parameters were investigated as the design variables, and the optimum turbine design was identified in a population of 79 design points. The optimum outflow turbine was found to have a peak steady-state efficiency of 72%, and the leading-edge angle, guide vane angle, trailing edge angle, and the chord length were found to have the highest sensitivity. Compared to an inflow radial turbine, the geometrical features of the outflow turbine permit higher absolute velocities of the flow at the rotor entrance and increase the dynamic pressure changes across the rotor. Therefore, the optimised outflow radial turbine can obtain acceptable rotor energy transfer despite having a negative centrifugal energy transfer term.
Current Mode Control of a Series LC Converter Supporting Constant Current, Constant Voltage (CCCV)
Authors: Heidinger Michael , Xia Qihao , Simon Christoph , Denk Fabian , Eizaguirre Santiago , Kling Rainer , Heering Wolfgang
Published: July 2019

This paper introduces a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant current, constant voltage (CCCV) control, required for demanding applications, for example, lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the pulse width modulation (PWM) parameters. The power supply achieves fast large-signal responses, e.g., from 5 V to 24 V , where 95% of the target value is reached in less than 400 s . The design is evaluated extensively in simulation and on a prototype. A match between simulation and measurement is achieved.
The Multiple Benefits of the 2030 EU Energy Efficiency Potential
Authors: Thema Johannes , Suerkemper Felix , Couder Johan , Mzavanadze Nora , Chatterjee Souran , Teubler Jens , Thomas Stefan , Ürge-Vorsatz Diana , Hansen Martin Bo , Bouzarovski Stefan , Rasch Jana , Wilke Sabine
Published: July 2019

The implementation of energy efficiency improvement actions not only yields energy and greenhouse gas emission savings, but also leads to other multiple impacts such as air pollution reductions and subsequent health and eco-system effects, resource impacts, economic effects on labour markets, aggregate demand and energy prices or on energy security. While many of these impacts have been studied in previous research, this work quantifies them in one consistent framework based on a common underlying bottom-up funded energy efficiency scenario across the EU. These scenario data are used to quantify multiple impacts by energy efficiency improvement action and for all EU28 member states using existing approaches and partially further developing methodologies. Where possible, impacts are integrated into cost-benefit analyses. We find that with a conservative estimate, multiple impacts sum up to a size of at least 50% of energy cost savings, with substantial impacts coming from e.g., air pollution, energy poverty reduction and economic impacts.
Feasibility of New Liquid Fuel Blends for Medium-Speed Engines
Authors: Sirviö Katriina , Niemi Seppo , Heikkilä Sonja , Kiijärvi Jukka , Hissa Michaela , Hiltunen Erkki
Published: July 2019

Several sustainable liquid fuel alternatives are needed for different compression ignition (CI) engine applications. In the present study, five different fuel blends were investigated. Rapeseed methyl ester (RME) was used as the basic renewable fuel, and it was blended with low-sulfur light fuel oil (LFO), kerosene, marine gas oil (MGO), and naphtha. Of these fuels, MGO is a circulation economy fuel, manufactured from used lubricants. Naphtha is renewable as it is a by-product of renewable diesel production process using tall oil as feedstock. In addition to RME, naphtha was also blended with LFO. The aim of the current study was to determine the most important properties of the five fuel blends in order to gather fundamental knowledge about their suitability for medium-speed CI engines. The share of renewables within these five blends varied from 20 to 100 vol.%. The properties that were investigated and compared were the cetane number, distillation, density, viscosity, cold properties, and lubricity. According to the results, all the studied blends may be operable in medium-speed engines. Blending of new, renewable fuels with more conventional ones will help ease the technical transitional period as long as the availability of renewable fuels is limited.
Experimental Investigations of Flow Field and Atomization Field Characteristics of Pre-Filming Air-Blast Atomizers
Authors: Fan Xiongjie , Liu Cunxi , Mu Yong , Wang Kaixing , Wang Yulan , Xu Gang
Published: July 2019

Flow field, atomization field characteristics, and liquid film breakup behaviors of a pre-filming air-blast atomizer are investigated using PIV (Particle Imaging Velocimetry), PLIF (Fuel Planar Laser Induced Fluorescence), and high-speed shadowgraph technique under different air mass rates (ma), fuel mass rates (mf), and fuel temperatures (T). The influence of structures constituting the pre-filming air-blast atomizer on the flow field organization and atomization field organization are investigated too. The results illustrate that air-blast atomizer structures have a great difference on the flow fields and atomization fields. Air-blast atomizer structures have great differences on the liquid film breakup processes too. Flow field structure and atomization structure are mainly determined by the swirler structure, whereas there are seldom influences of air mass rate and fuel mass rate on them. The results of the mechanisms of flow field organization and atomization field organization in this study can be used to support the design of new low-emission combustor.
Evaluation of Interconnection Configuration Schemes for PV Modules with Switched-Inductor Converters under Partial Shading Conditions
Authors: Niazi Kamran Ali Khan , Yang Yongheng , Nasir Mashood , Sera Dezso
Published: July 2019

Partial shading on photovoltaic (PV) arrays reduces the overall output power and causes multiple maximas on the output power characteristics. Due to the introduction of multiple maximas, mismatch power losses become apparent among multiple PV modules. These mismatch power losses are not only a function of shading characteristics, but also depend on the placement and interconnection patterns of the shaded modules within the array. This research work is aimed to assess the performance of 4 × 4 PV array under different shading conditions. The desired objective is to attain the maximum output power from PV modules at different possible shading patterns by using power electronic-based differential power processing (DPP) techniques. Various PV array interconnection configurations, including the series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL), and center-cross-tied (CCT) are considered under the designed shading patterns. A comparative performance analysis is carried out by analyzing the output power from the DPP-based architecture and the traditional Schottky diode-based architecture. Simulation results show the gain in the output power by using the DPP-based architecture in comparison to the traditional bypassing diode method.