bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Flora (AF) Optimization Algorithm
Authors: Cheng Long , Wu Xue-han , Wang Yan
Published: February 2018

Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, it can spread seeds within a certain range to let offspring to find the most suitable environment. The stochastic process is easy to copy, and the spreading space is vast; therefore, it is suitable for applying in intelligent optimization algorithm. First, the algorithm randomly generates the original plant, including its position and the propagation distance. Then, the position and the propagation distance of the original plant as parameters are substituted in the propagation function to generate offspring plants. Finally, the optimal offspring is selected as a new original plant through the selection function. The previous original plant becomes the former plant. The iteration continues until we find out optimal solution. In this paper, six classical evaluation functions are used as the benchmark functions. The simulation results show that proposed algorithm has high accuracy and stability compared with the classical particle swarm optimization and artificial bee colony algorithm.
Compact 6 dB Two-Color Continuous Variable Entangled Source Based on a Single Ring Optical Resonator
Authors: Wang Ning , Du Shanna , Li Yongmin
Published: February 2018

Continuous-variable entangled optical beams at the degenerate wavelength of 0.8 μm or 1.5 μm have been investigated extensively, but separately. The two-color entangled states of these two useful wavelengths, with sufficiently high degrees of entanglement, still lag behind. In this work, we analyze the various limiting factors that affect the entanglement degree. On the basis of this, we successfully achieve 6 dB of two-color quadrature entangled light beams by improving the escape efficiency of the nondegenerate optical amplifier, the stability of the phase-locking servo system, and the detection efficiency. Our entangled source is constructed only from a single ring optical resonator, and thus is highly compact, which is suitable for applications in long-distance quantum communication networks.
Real Time Quantum Dynamics of Spontaneous Translational Symmetry Breakage in the Early Stage of Photo-Induced Structural Phase Transitions
Authors: Nasu Keiichiro
Published: February 2018

Real time quantum dynamics of the spontaneous translational symmetry breakage in the early stage of photo-induced structural phase transitions is reviewed and supplementally explained, under the guide of the Toyozawa theory, which is exactly in compliance with the conservation laws of the total momentum and energy. At the Franck-Condon state, an electronic excitation just created by a visible light, is in a plane wave state, which is extended all over the crystal. While, after the lattice relaxation having been completed, it is localized around a certain lattice site of the crystal, as a new excitation. Is there a sudden shrinkage of the excitation wave function, in between? No! The wave function never shrinks, but only the spatial (or inter lattice-site) quantum coherence (interference) of the excitation disappears, as the lattice relaxation proceeds. This is nothing but the spontaneous breakage of translational symmetry.
An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence
Authors: Wang Gangfeng , Hu Yongbiao , Tian Xitian , Geng Junhao , Hu Gailing , Zhang Min
Published: February 2018

Process innovation plays a vital role in the manufacture realization of increasingly complex new products, especially in the context of sustainable development and cleaner production. Knowledge-based innovation design can inspire designers’ creative thinking; however, the existing scattered knowledge has not yet been properly captured and organized according to Computer-Aided Process Innovation (CAPI). Therefore, this paper proposes an integrated approach to tackle this non-trivial issue. By analyzing the design process of CAPI and technical features of open innovation, a novel holistic paradigm of process innovation knowledge capture based on collective intelligence (PIKC-CI) is constructed from the perspective of the knowledge life cycle. Then, a multi-source innovation knowledge fusion algorithm based on semantic elements reconfiguration is applied to form new public knowledge. To ensure the credibility and orderliness of innovation knowledge refinement, a collaborative editing strategy based on knowledge lock and knowledge–social trust degree is explored. Finally, a knowledge management system MPI-OKCS integrating the proposed techniques is implemented into the pre-built CAPI general platform, and a welding process innovation example is provided to illustrate the feasibility of the proposed approach. It is expected that our work would lay the foundation for the future knowledge-inspired CAPI and smart process planning.
Comprehensive Evaluation of Machine Learning Techniques for Estimating the Responses of Carbon Fluxes to Climatic Forces in Different Terrestrial Ecosystems
Authors: Dou Xianming , Yang Yongguo
Published: February 2018

Accurately estimating the carbon budgets in terrestrial ecosystems ranging from flux towers to regional or global scales is particularly crucial for diagnosing past and future climate change. This research investigated the feasibility of two comparatively advanced machine learning approaches, namely adaptive neuro-fuzzy inference system (ANFIS) and extreme learning machine (ELM), for reproducing terrestrial carbon fluxes in five different types of ecosystems. Traditional artificial neural network (ANN) and support vector machine (SVM) models were also utilized as reliable benchmarks to measure the generalization ability of these models according to the following statistical metrics: coefficient of determination (R2), index of agreement (IA), root mean square error (RMSE), and mean absolute error (MAE). In addition, we attempted to explore the responses of all methods to their corresponding intrinsic parameters in terms of the generalization performance. It was found that both the newly proposed ELM and ANFIS models achieved highly satisfactory estimates and were comparable to the ANN and SVM models. The modeling ability of each approach depended upon their respective internal parameters. For example, the SVM model with the radial basis kernel function produced the most accurate estimates and performed substantially better than the SVM models with the polynomial and sigmoid functions. Furthermore, a remarkable difference was found in the estimated accuracy among different carbon fluxes. Specifically, in the forest ecosystem (CA-Obs site), the optimal ANN model obtained slightly higher performance for gross primary productivity, with R2 = 0.9622, IA = 0.9836, RMSE = 0.6548 g C m−2 day−1, and MAE = 0.4220 g C m−2 day−1, compared with, respectively, 0.9554, 0.9845, 0.4280 g C m−2 day−1, and 0.2944 g C m−2 day−1 for ecosystem respiration and 0.8292, 0.9306, 0.6165 g C m−2 day−1, and 0.4407 g C m−2 day−1 for net ecosystem exchange. According to the findings in this study, we concluded that the proposed ELM and ANFIS models can be effectively employed for estimating terrestrial carbon fluxes.
DOT1L and H3K79 Methylation in Transcription and Genomic Stability
Authors: Wood Katherine , Tellier Michael , Murphy Shona
Published: February 2018

The organization of eukaryotic genomes into chromatin provides challenges for the cell to accomplish basic cellular functions, such as transcription, DNA replication and repair of DNA damage. Accordingly, a range of proteins modify and/or read chromatin states to regulate access to chromosomal DNA. Yeast Dot1 and the mammalian homologue DOT1L are methyltransferases that can add up to three methyl groups to histone H3 lysine 79 (H3K79). H3K79 methylation is implicated in several processes, including transcription elongation by RNA polymerase II, the DNA damage response and cell cycle checkpoint activation. DOT1L is also an important drug target for treatment of mixed lineage leukemia (MLL)-rearranged leukemia where aberrant transcriptional activation is promoted by DOT1L mislocalisation. This review summarizes what is currently known about the role of Dot1/DOT1L and H3K79 methylation in transcription and genomic stability.
Abstraction and Idealization in Biomedicine: The Nonautonomous Theory of Acute Cell Injury
Authors: DeGracia Donald , Taha Doaa , Tri Anggraini Fika , Sutariya Shreya , Rababeh Gabriel , Huang Zhi-Feng
Published: February 2018

Neuroprotection seeks to halt cell death after brain ischemia and has been shown to be possible in laboratory studies. However, neuroprotection has not been successfully translated into clinical practice, despite voluminous research and controlled clinical trials. We suggested these failures may be due, at least in part, to the lack of a general theory of cell injury to guide research into specific injuries. The nonlinear dynamical theory of acute cell injury was introduced to ameliorate this situation. Here we present a revised nonautonomous nonlinear theory of acute cell injury and show how to interpret its solutions in terms of acute biomedical injuries. The theory solutions demonstrate the complexity of possible outcomes following an idealized acute injury and indicate that a “one size fits all” therapy is unlikely to be successful. This conclusion is offset by the fact that the theory can (1) determine if a cell has the possibility to survive given a specific acute injury, and (2) calculate the degree of therapy needed to cause survival. To appreciate these conclusions, it is necessary to idealize and abstract complex physical systems to identify the fundamental mechanism governing the injury dynamics. The path of abstraction and idealization in biomedical research opens the possibility for medical treatments that may achieve engineering levels of precision.
Spectroscopic Chemical Sensing and Imaging: From Plants to Animals and Humans
Authors: Strobbia Pietro , Odion Ren , Vo-Dinh Tuan
Published: February 2018

Chemical sensing and imaging technologies are of great importance in medical diagnostics and environmental sensing due to their ability to detect and localize chemical targets and provide valuable information in real-time. Biophotonic techniques are the most promising for in vivo applications due to their minimal invasivity. Our laboratory has introduced various biophotonics-based technologies for chemical sensing and imaging for biochemical sensing, medical diagnostics, and fundamental research. Over the years, we have developed a wide variety of fluorescence and surface-enhanced Raman scattering (SERS)-based technologies for the detection of biomarkers for cancer and other diseases. This paper provides an overview of the research on chemical and biological sensors developed in our laboratory, highlighting our work on in vivo imaging and sensing, including minimally invasive detection of endogenous fluorophores associated with malignant tissue, SERS-tag localization of cancer cells and tissues, and SERS-based detection of nucleic acid biotargets and its feasibility for in vivo applications. This manuscript also presents new development on the use of Raman imaging of SERS-labeled nanoprobes incubated in leaves for use in biofuel research, laying the foundation for studies on functional imaging of nucleic acid biomarkers in plants.
Conformational Flexibility of Proteins Involved in Ribosome Biogenesis: Investigations via Small Angle X-ray Scattering (SAXS)
Authors: Siliqi Dritan , Foadi James , Mazzorana Marco , Altamura Davide , Méndez-Godoy Alfonso , Sánchez-Puig Nuria
Published: February 2018

The dynamism of proteins is central to their function, and several proteins have been described as flexible, as consisting of multiple domains joined by flexible linkers, and even as intrinsically disordered. Several techniques exist to study protein structures, but small angle X-ray scattering (SAXS) has proven to be particularly powerful for the quantitative analysis of such flexible systems. In the present report, we have used SAXS in combination with X-ray crystallography to highlight their usefulness at characterizing flexible proteins, using as examples two proteins involved in different steps of ribosome biogenesis. The yeast BRCA2 and CDKN1A-interactig protein, Bcp1, is a chaperone for Rpl23 of unknown structure. We showed that it consists of a rigid, slightly elongated protein, with a secondary structure comprising a mixture of alpha helices and beta sheets. As an example of a flexible molecule, we studied the SBDS (Shwachman-Bodian-Diamond Syndrome) protein that is involved in the cytoplasmic maturation of the 60S subunit and constitutes the mutated target in the Shwachman-Diamond Syndrome. In solution, this protein coexists in an ensemble of three main conformations, with the N- and C-terminal ends adopting different orientations with respect to the central domain. The structure observed in the protein crystal corresponds to an average of those predicted by the SAXS flexibility analysis.
Intra-/Intermolecular Bifurcated Chalcogen Bonding in Crystal Structure of Thiazole/Thiadiazole Derived Binuclear (Diaminocarbene)PdII Complexes
Authors: Mikherdov Alexander , Novikov Alexander , Kinzhalov Mikhail , Zolotarev Andrey , Boyarskiy Vadim
Published: February 2018

The coupling of cis-[PdCl2(CNXyl)2] (Xyl = 2,6-Me2C6H3) with 4-phenylthiazol-2-amine in molar ratio 2:3 at RT in CH2Cl2 leads to binuclear (diaminocarbene)PdII complex 3c. The complex was characterized by HRESI+-MS, 1H NMR spectroscopy, and its structure was elucidated by single-crystal XRD. Inspection of the XRD data for 3c and for three relevant earlier obtained thiazole/thiadiazole derived binuclear diaminocarbene complexes (3a EYOVIZ; 3b: EYOWAS; 3d: EYOVOF) suggests that the structures of all these species exhibit intra-/intermolecular bifurcated chalcogen bonding (BCB). The obtained data indicate the presence of intramolecular S•••Cl chalcogen bonds in all of the structures, whereas varying of substituent in the 4th and 5th positions of the thiazaheterocyclic fragment leads to changes of the intermolecular chalcogen bonding type, viz. S•••π in 3a,b, S•••S in 3c, and S•••O in 3d. At the same time, the change of heterocyclic system (from 1,3-thiazole to 1,3,4-thiadiazole) does not affect the pattern of non-covalent interactions. Presence of such intermolecular chalcogen bonding leads to the formation of one-dimensional (1D) polymeric chains (for 3a,b), dimeric associates (for 3c), or the fixation of an acetone molecule in the hollow between two diaminocarbene complexes (for 3d) in the solid state. The Hirshfeld surface analysis for the studied X-ray structures estimated the contributions of intermolecular chalcogen bonds in crystal packing of 3a–d: S•••π (3a: 2.4%; 3b: 2.4%), S•••S (3c: less 1%), S•••O (3d: less 1%). The additionally performed DFT calculations, followed by the topological analysis of the electron density distribution within the framework of Bader’s theory (AIM method), confirm the presence of intra-/intermolecular BCB S•••Cl/S•••S in dimer of 3c taken as a model system (solid state geometry). The AIM analysis demonstrates the presence of appropriate bond critical points for these interactions and defines their strength from 0.9 to 2.8 kcal/mol indicating their attractive nature.
Information Thermodynamics Derives the Entropy Current of Cell Signal Transduction as a Model of a Binary Coding System
Authors: Tsuruyama Tatsuaki
Published: February 2018

The analysis of cellular signaling cascades based on information thermodynamics has recently developed considerably. A signaling cascade may be considered a binary code system consisting of two types of signaling molecules that carry biological information, phosphorylated active, and non-phosphorylated inactive forms. This study aims to evaluate the signal transduction step in cascades from the viewpoint of changes in mixing entropy. An increase in active forms may induce biological signal transduction through a mixing entropy change, which induces a chemical potential current in the signaling cascade. We applied the fluctuation theorem to calculate the chemical potential current and found that the average entropy production current is independent of the step in the whole cascade. As a result, the entropy current carrying signal transduction is defined by the entropy current mobility.
The Volume of Two-Qubit States by Information Geometry
Authors: Rexiti Milajiguli , Felice Domenico , Mancini Stefano
Published: February 2018

Using the information geometry approach, we determine the volume of the set of two-qubit states with maximally disordered subsystems. Particular attention is devoted to the behavior of the volume of sub-manifolds of separable and entangled states with fixed purity. We show that the usage of the classical Fisher metric on phase space probability representation of quantum states gives the same qualitative results with respect to different versions of the quantum Fisher metric.
Application of Permutation Entropy and Permutation Min-Entropy in Multiple Emotional States Analysis of RRI Time Series
Authors: Xia Yirong , Yang Licai , Zunino Luciano , Shi Hongyu , Zhuang Yuan , Liu Chengyu
Published: February 2018

This study’s aim was to apply permutation entropy (PE) and permutation min-entropy (PME) over an RR interval time series to quantify the changes in cardiac activity among multiple emotional states. Electrocardiogram (ECG) signals were recorded under six emotional states (neutral, happiness, sadness, anger, fear, and disgust) in 60 healthy subjects at a rate of 1000 Hz. For each emotional state, ECGs were recorded for 5 min and the RR interval time series was extracted from these ECGs. The obtained results confirm that PE and PME increase significantly during the emotional states of happiness, sadness, anger, and disgust. Both symbolic quantifiers also increase but not in a significant way for the emotional state of fear. Moreover, it is found that PME is more sensitive than PE for discriminating non-neutral from neutral emotional states.
Hierarchy of Relaxation Times and Residual Entropy: A Nonequilibrium Approach
Authors: Gujrati Purushottam
Published: February 2018

We consider nonequilibrium (NEQ) states such as supercooled liquids and glasses that are described with the use of internal variables. We classify the latter by the state-dependent hierarchy of relaxation times to assess their relevance for irreversible contributions. Given an observation time τ obs , we determine the window of relaxation times that divide the internal variables into active and inactive groups, the former playing a central role in the NEQ thermodynamics. Using this thermodynamics, we determine (i) a bound on the NEQ entropy and on the residual entropy and (ii) the nature of the isothermal relaxation of the entropy and the enthalpy in accordance with the second law. A theory that violates the second law such as the entropy loss view is shown to be internally inconsistent if we require it to be consistent with experiments. The inactive internal variables still play an indirect role in determining the temperature T ( t ) and the pressure P ( t ) of the system, which deviate from their external values.
Efficient Fault Localization and Failure Analysis Techniques for Improving IC Yield
Authors: Oberai Ankush , Yuan Jiann-Shiun
Published: February 2018

With the increase in the complexity of the semiconductor device processes and increase in the challenge to satisfy high market demands, enhancement in yield has become a crucial factor. Discovering and reacting to yield problems emerging at the end of the production line may cause unbearable yield loss leading to larger times to market. Thus, time and cost involved in fault isolation may be significantly shortened by effectively utilizing the fault diagnosis technology and supporting yield improvements. Hence for yield analysis, a highly integrated data network with software analysis tools have been established to reduce the fault analysis time. Synopsys Avalon, a product used for fault localization is described in this paper which aids in achieving better integrated circuit yields. This paper also illustrates various fault localization techniques for faster problem identification and discusses a few analytical tools like photon emission microscope and transmission emission microscope for faster determination of device failures.
Optimal Control Algorithms with Adaptive Time-Mesh Refinement for Kite Power Systems
Authors: Paiva Luís , Fontes Fernando
Published: February 2018

This article addresses the problem of optimizing electrical power generation using kite power systems (KPSs). KPSs are airborne wind energy systems that aim to harvest the power of strong and steady high-altitude winds. With the aim of maximizing the total energy produced in a given time interval, we numerically solve an optimal control problem and thereby obtain trajectories and controls for kites. Efficiently solving these optimal control problems is crucial when the results are used in real-time control schemes, such as model predictive control. For this highly nonlinear problem, we derive continuous-time models—in 2D and 3D—and implement an adaptive time-mesh refinement algorithm. By solving the optimal control problem with such an adaptive refinement strategy, we generate a block-structured adapted mesh which gives results as accurate as those computed using fine mesh, yet with much less computing effort and high savings in memory and computing time.
Mitigation Conducted Emission Strategy Based on Transfer Function from a DC-Fed Wireless Charging System for Electric Vehicles
Authors: Zhai Li , Cao Yu , Lin Liwen , Zhang Tao , Kavuma Steven
Published: February 2018

The large dv/dt and di/dt outputs of power devices in wireless charging system (WCS) in electric vehicles (EVs) always introduce conducted electromagnetic interference (EMI) emissions. This paper proposes a mitigation conducted emission strategy based on transfer function from a direct current fed (DC-fed) WCS for EVs. A complete test for the DC-fed WCS is set up to measure the conducted emission of DC power cables in a frequency range of 150 kHz–108 MHz. An equivalent circuit with high-frequency parasitic parameters for WCS for EV is built based on measurement results to obtain the characteristics of conducted emission from WCS. The transfer functions of differential mode (DM) interference and common mode (CM) interference were established. A judgment method of using transfer functions to determine the dominated interference mode responsible for EMI is proposed. From the comparison of simulation results between CM or DM and CM+DM interference, it can be seen that the CM interference is the dominated interference mode which causes the conducted EMI in WCS in EVs. A strategy of giving priority to the dominated interference mode is proposed for designing the CM interference filter. Finally, the conducted voltage experiment is performed to verify the mitigation conducted emission strategy. The conducted voltage of simulation and experiment is decreased respectively by 21.17 and 21.4 dBμV at resonance frequency 30 MHz. The conduced voltage at frequency range of 150 kHz–108 MHz can be mitigated to below the limit level-3 of CISPR25 standard (GB/T 18655-2010) by adding the CM interference filters.
Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters
Authors: Vergura Silvano
Published: February 2018

This paper deals with the monitoring of the performance of a photovoltaic plant, without using the environmental parameters such as the solar radiation and the temperature. The main idea is to statistically compare the energy performances of the arrays constituting the PV plant. In fact, the environmental conditions affect equally all the arrays of a small-medium-size PV plant, because the extension of the plant is limited, so any comparison between the energy distributions of identical arrays is independent of the solar radiation and the cell temperature, making the proposed methodology very effective for PV plants not equipped with a weather station, as it often happens for the PV plants located in urban contexts and having a nominal peak power in the 3÷50 kWp range, typically installed on the roof of a residential or industrial building. In this case, the costs of an advanced monitoring system based on the environmental data are not justified, consequently, the weather station is often also omitted. The proposed procedure guides the user through several inferential statistical tools that allow verifying whether the arrays have produced the same amount of energy or, alternatively, which is the worst array. The procedure is effective in detecting and locating abnormal operating conditions, before they become failures.
Remote Power Control Injection of Grid-Connected Power Converters Based on Virtual Flux
Authors: Roslan Nurul , Luna Alvaro , Rocabert Joan , Candela Jose , Rodriguez Pedro
Published: February 2018

Renewable Energy Source (RES)-based power plants need to control the active and reactive power at the Point of Common Connection (PCC) with the grid, in order to comply with the requirements of the Transmission System Operators (TSOs). This point is normally far away from the power converter station, and the cables and step-up transformers have a non-neglectable influence on the delivered power. In order to overcome this drawback, this paper presents a control algorithm that permits one to control remotely the power injected at the PCC, by adjusting the local controller of the Voltage Source Converters (VSCs). In this work, the synchronization with the grid is done based on the Virtual Flux (VF) concept. The results reveals that the VF estimation is able to produce a reliable estimation of the grid voltage in any point of the network, and makes it possible to calculate the necessary current reference for injecting a desired active and reactive power at a point that can be some kilometres away. In this paper the main principle for this remote power control is presented. Likewise, the simulation and experimental results will be shown in order to analyse the effectiveness of the proposed system.
A Comparison of Thermal Models for Temperature Profiles in Gas-Lift Wells
Authors: Mu Langfeng , Zhang Qiushi , Li Qi , Zeng Fanhua
Published: February 2018

Gas lift is a simple, reliable artificial lift method which is frequently used in offshore oil field developments. In order to enhance the efficiency of production by gas lift, it is vital to exactly predict the distribution of temperature-field for fluid within the wellbore. A new mechanistic model is developed for computing flowing fluid temperature profiles in both conduits simultaneously for a continuous-flow gas-lift operation. This model assumes steady heat transfer in the formation, as well as steady heat transfer in the conduits. A micro-units discrete from the wellbore, whose heat transfer process is analyzed and whose heat transfer equation is set up according to the law of conservation of energy. A simplified algebraic solution to our model is conducted to analyze the temperature profile. Sensitivity analysis was conducted with the new model. The results indicate that mass flow rate of oil and the tubing overall heat transfer coefficient are the main factors that influence the temperature distribution inside the tubing and that the mass flow rate of oil is the main factor affecting temperature distribution in the annulus. Finally, the new model was tested in three various wells and compared with other models. The results showed that the new model is more accurate and provides significant references for temperature prediction in gas lift well.
Analyzing and Forecasting Electrical Load Consumption in Healthcare Buildings
Authors: Gordillo-Orquera  Rodolfo , Lopez-Ramos Luis , Muñoz-Romero Sergio , Iglesias-Casarrubios Paz  , Arcos-Avilés Diego , Marques Antonio , Rojo-Álvarez José
Published: February 2018

Healthcare buildings exhibit a different electrical load predictability depending on their size and nature. Large hospitals behave similarly to small cities, whereas primary care centers are expected to have different consumption dynamics. In this work, we jointly analyze the electrical load predictability of a large hospital and that of its associated primary care center. An unsupervised load forecasting scheme using combined classic methods of principal component analysis (PCA) and autoregressive (AR) modeling, as well as a supervised scheme using orthonormal partial least squares (OPLS), are proposed. Both methods reduce the dimensionality of the data to create an efficient and low-complexity data representation and eliminate noise subspaces. Because the former method tended to underestimate the load and the latter tended to overestimate it in the large hospital, we also propose a convex combination of both to further reduce the forecasting error. The analysis of data from 7 years in the hospital and 3 years in the primary care center shows that the proposed low-complexity dynamic models are flexible enough to predict both types of consumption at practical accuracy levels.
Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps
Authors: Behrooz Farinaz , Mariun Norman , Marhaban Mohammad , Mohd Radzi Mohd , Ramli Abdul
Published: February 2018

Heating, Ventilating, and Air Conditioning (HVAC) systems are the major energy-consuming devices in buildings. Nowadays, due to the high demand for HVAC system installation in buildings, designing an effective controller in order to decrease the energy consumption of the devices while meeting the thermal comfort demands in buildings are the most important goals of control designers. The purpose of this article is to investigate the different control methods for Heating, Ventilating, and Air Conditioning and Refrigeration (HVAC & R) systems. The advantages and disadvantages of each control method are discussed and finally the Fuzzy Cognitive Map (FCM) method is introduced as a new strategy for HVAC systems. The FCM method is an intelligent and advanced control technique to address the nonlinearity, Multiple-Input and Multiple-Output (MIMO), complexity and coupling effect features of the systems. The significance of this method and improvements by this method are compared with other methods.
Towards Biochar and Hydrochar Engineering—Influence of Process Conditions on Surface Physical and Chemical Properties, Thermal Stability, Nutrient Availability, Toxicity and Wettability
Authors: Dieguez-Alonso Alba , Funke Axel , Anca-Couce Andrés , Rombolà Alessandro , Ojeda Gerardo , Bachmann Jörg , Behrendt Frank
Published: February 2018

The impact of conversion process parameters in pyrolysis (maximum temperature, inert gas flow rate) and hydrothermal carbonization (maximum temperature, residence time and post-washing) on biochar and hydrochar properties is investigated. Pine wood (PW) and corn digestate (CD), with low and high inorganic species content respectively, are used as feedstock. CD biochars show lower H/C ratios, thermal recalcitrance and total specific surface area than PW biochars, but higher mesoporosity. CD and PW biochars present higher naphthalene and phenanthrene contents, respectively, which may indicate different reaction pathways. High temperatures (>500 °C) lead to lower PAH (polycyclic aromatic hydrocarbons) content (<12 mg/kg) and higher specific surface area. With increasing process severity the biochars carbon content is also enhanced, as well as the thermal stability. High inert gas flow rates increase the microporosity and wettability of biochars. In hydrochars the high inorganic content favor decarboxylation over dehydration reactions. Hydrochars show mainly mesoporosity, with a higher pore volume but generally lower specific surface area than biochars. Biochars present negligible availability of NO 3 − and NH 4 + , irrespective of the nitrogen content of the feedstock. For hydrochars, a potential increase in availability of NO 3 − , NH 4 + , PO 4 3 − , and K + with respect to the feedstock is possible. The results from this work can be applied to “engineer” appropriate biochars with respect to soil demands and certification requirements.
Spatiotemporal Patterns of Carbon Emissions and Taxi Travel Using GPS Data in Beijing
Authors: Zhang Jinlei , Chen Feng , Wang Zijia , Wang Rui , Shi Shunwei
Published: February 2018

Taxis are significant contributors to carbon dioxide emissions due to their frequent usage, yet current research into taxi carbon emissions is insufficient. Emerging data sources and big data–mining techniques enable analysis of carbon emissions, which contributes to their reduction and the promotion of low-carbon societies. This study uses taxi GPS data to reconstruct taxi trajectories in Beijing. We then use the carbon emission calculation model based on a taxi fuel consumption algorithm and the carbon dioxide emission factor to calculate emissions and apply a visualization method called kernel density analysis to obtain the dynamic spatiotemporal distribution of carbon emissions. Total carbon emissions show substantial temporal variations during the day, with maximum values from 10:00–11:00 (57.53 t), which is seven times the minimum value of 7.43 t (from 03:00–04:00). Carbon emissions per kilometer at the network level are steady throughout the day (0.2 kg/km). The Airport Expressway, Ring Roads, and large intersections within the 5th Ring Road maintain higher carbon emissions than other areas. Spatiotemporal carbon emissions and travel patterns differ between weekdays and weekends, especially during morning rush hours. This research provides critical insights for taxi companies, authorities, and future studies.
Economic Analysis of Diesel-Fuel Replacement by Crude Palm Oil in Indonesian Power Plants
Authors: Procházka Petr , Hönig Vladimír
Published: February 2018

Indonesia needs to find an alternative fuel to substitute diesel in their power plants in order to reduce the use of nonrenewable energy sources. The Indonesian government has a target to reduce oil fuel consumption while improving the efficiency of energy utilization. Crude palm oil is proposed to be used for this substitution. In this paper, the authors conduct an economic analysis of the replacement of diesel by crude palm oil. To predict future prices, a time series analysis is conducted using AutoRegressive Integrated Moving-Average method. A financial analysis of a specific project (0.75-MW power plant) is conducted using static financial indicators (payback period, return on investment). Results show that replacing diesel with crude palm oil may be profitable. This is especially true for the proposed prospects of diesel price evolution. Analysis shows that the price of crude oil, which is the main factor in the pricing of diesel, may go up. Also, recently Indonesian currency depreciated against the US dollar, which also implies a higher cost of diesel.
Horizontal Axis Wind Turbine Blade Design Methodologies for Efficiency Enhancement—A Review
Authors: Rehman Shafiqur , Alam Md. , Alhems Luai , Rafique M.
Published: February 2018

Among renewable sources of energy, wind is the most widely used resource due to its commercial acceptance, low cost and ease of operation and maintenance, relatively much less time for its realization from concept till operation, creation of new jobs, and least adverse effect on the environment. The fast technological development in the wind industry and availability of multi megawatt sized horizontal axis wind turbines has further led the promotion of wind power utilization globally. It is a well-known fact that the wind speed increases with height and hence the energy output. However, one cannot go above a certain height due to structural and other issues. Hence other attempts need to be made to increase the efficiency of the wind turbines, maintaining the hub heights to acceptable and controllable limits. The efficiency of the wind turbines or the energy output can be increased by reducing the cut-in-speed and/or the rated-speed by modifying and redesigning the blades. The problem is tackled by identifying the optimization parameters such as annual energy yield, power coefficient, energy cost, blade mass, and blade design constraints such as physical, geometric, and aerodynamic. The present paper provides an overview of the commonly used models, techniques, tools and experimental approaches applied to increase the efficiency of the wind turbines. In the present review work, particular emphasis is made on approaches used to design wind turbine blades both experimental and numerical, methodologies used to study the performance of wind turbines both experimentally and analytically, active and passive techniques used to enhance the power output from wind turbines, reduction in cut-in-speed for improved wind turbine performance, and lastly the research and development work related to new and efficient materials for the wind turbines.
Development of a Biodegradable Electro-Insulating Liquid and Its Subsequent Modification by Nanoparticles
Authors: Mentlik Vaclav , Trnka Pavel , Hornak Jaroslav , Totzauer Pavel
Published: February 2018

The paper is focused on the possibility of replacing petroleum-based oils used as electro-insulating fluids in high voltage machinery. Based on ten years of study the candidate base oil for the central European region is rapeseed (Brassica napus) oil. Numerous studies on the elementary properties of pure natural esters have been published. An advantage of natural ester use is its easy biodegradability, tested according to OECD–301D (Organisation for Economic Co-operation and Development) standard, and compliance with sustainable development visions. A rapeseed oil base has been chosen for its better resistance to degradation in electric fields and its higher oxidation stability. The overall ester properties are not fully competitive with petroleum-based oils and therefore have to be improved. Percolation treatment and oxidation inhibition by a phenolic-type inhibitor is proposed and the resulting final properties are discussed. These resulting fluid properties are further improved using titanium dioxide (TiO2) nanoparticles with a silica surface treatment. This fluid has properties suitable for use in sealed distribution transformers with the advantage of a lower price in comparison with other currently used biodegradable fluids.
Secure Protocol and IP Core for Configuration of Networking Hardware IPs in the Smart Grid
Authors: Urbina Marcelo , Moreira Naiara , Rodriguez Mikel , Acosta Tatiana , Lázaro Jesús , Astarloa Armando
Published: February 2018

Nowadays, the incorporation and constant evolution of communication networks in the electricity sector have given rise to the so-called Smart Grid, which is why it is necessary to have devices that are capable of managing new communication protocols, guaranteeing the strict requirements of processing required by the electricity sector. In this context, intelligent electronic devices (IEDs) with network architectures are currently available to meet the communication, real-time processing and interoperability requirements of the Smart Grid. The new generation IEDs include an Field Programmable Gate Array (FPGA), to support specialized networking switching architectures for the electric sector, as the IEEE 1588-aware High-availability Seamless Redundancy/Parallel Redundancy Protocol (HSR/PRP). Another advantage to using an FPGA is the ability to update or reconfigure the design to support new requirements that are being raised to the standards (IEC 61850). The update of the architecture implemented in the FPGA can be done remotely, but it is necessary to establish a cyber security mechanism since the communication link generates vulnerability in the case the attacker gains physical access to the network. The research presented in this paper proposes a secure protocol and Intellectual Property (IP) core for configuring and monitoring the networking IPs implemented in a Field Programmable Gate Array (FPGA). The FPGA based implementation proposed overcomes this issue using a light Layer-2 protocol fully implemented on hardware and protected by strong cryptographic algorithms (AES-GCM), defined in the IEC 61850-90-5 standard. The proposed secure protocol and IP core are applicable in any field where remote configuration over Ethernet is required for IP cores in FPGAs. In this paper, the proposal is validated in communications hardware for Smart Grids.
A Graph-Based Power Flow Method for Balanced Distribution Systems
Authors: Shen Tao , Li Yanjun , Xiang Ji
Published: February 2018

A power flow method based on graph theory is presented for three-phase balanced distribution systems. The graph theory is used to describe the power network and facilitate the derivation of the relationship between bus Currents and the bus Voltage Bias from the feeder bus (the CVB equation). A distinctive feature of the CVB equation is its unified form for both radial and meshed networks. The method requires neither a tricky numbering and layering of nodes nor breaking meshes and loop-analysis, which are both necessary in previous works for meshed networks. The convergence of the proposed method is proven using the Banach fixed-point theorem.
Does Certification Change the Trajectory of Tree Cover in Working Forests in The Tropics? An Application of the Synthetic Control Method of Impact Evaluation
Authors: Rana Pushpendra , Sills Erin
Published: February 2018

Certification by the Forest Stewardship Council (FSC) remains rare among forest management units (FMUs) in natural tropical forests, presenting a challenge for impact evaluation. We demonstrate application of the synthetic control method (SCM) to evaluate the impact of FSC certification on a single FMU in each of three tropical forest landscapes. Specifically, we estimate causal effects on tree cover change from the year of certification to 2012 using SCM and open-access, pan-tropical datasets. We demonstrate that it is possible to construct synthetic controls, or weighted combinations of non-certified FMUs, that followed the same path of tree cover change as the certified FMUs before certification. By using these synthetic controls to measure counterfactual tree cover change after certification, we find that certification reduced tree cover loss in the most recent year (2012) in all three landscapes. However, placebo tests show that in one case, this effect was not significant, and in another case, it followed several years in which certification had the opposite effect (increasing tree cover loss). We conclude that SCM has promise for identifying temporally varying impacts of small-N interventions on land use and land cover change.
Adding Flavor to Beverages with Non-Conventional Yeasts
Authors: Ravasio Davide , Carlin Silvia , Boekhout Teun , Groenewald Marizeth , Vrhovsek Urska , Walther Andrea , Wendland Jürgen
Published: February 2018

Fungi produce a variety of volatile organic compounds (VOCs) during their primary and secondary metabolism. In the beverage industry, these volatiles contribute to the the flavor and aroma profile of the final products. We evaluated the fermentation ability and aroma profiles of non-conventional yeasts that have been associated with various food sources. A total of 60 strains were analyzed with regard to their fermentation and flavor profile. Species belonging to the genera Candida, Pichia and Wickerhamomyces separated best from lager yeast strains according to a principal component analysis taking alcohol and ester production into account. The speed of fermentation and sugar utilization were analysed for these strains. Volatile aroma-compound formation was assayed via gas chromatography. Several strains produced substantially higher amounts of aroma alcohols and esters compared to the lager yeast strain Weihenstephan 34/70. Consequently, co-fermentation of this lager yeast strain with a Wickerhamomyces anomalus strain generated an increased fruity-flavour profile. This demonstrates that mixed fermentations utilizing non-Saccharomyces cerevisiae biodiversity can enhance the flavour profiles of fermented beverages.
Robotics Construction Kits: From “Objects to Think with” to “Objects to Think and to Emote with”
Authors: D’Amico Antonella , Guastella Domenico
Published: February 2018

This paper discusses new ideas about the use of educational robotics in social-emotional learning. In particular, educational robotics could be a tool intended to allow children to acquire some of the basic aspects of human emotions and emotional functioning, and to understand how these relate to the mind and body. More specifically, by using robots such as the LEGO Mindstorm construction kits—which allow users to both construct the body of the robot and to provide it with a behavioural repertory—children have the opportunity to visualize (and manipulate) the relationship between the robot’s body and mind. This allows them to simulate “embodied emotional minds” and to reflect on new neuroscientific concepts regarding body-mind and cognition-emotion relationships.
Learning and Mining Player Motion Profiles in Physically Interactive Robogames
Authors: Oliveira Ewerton , Orrù Davide , Morreale Luca , Nascimento Tiago , Bonarini Andrea
Published: February 2018

Physically-Interactive RoboGames (PIRG) are an emerging application whose aim is to develop robotic agents able to interact and engage humans in a game situation. In this framework, learning a model of players’ activity is relevant both to understand their engagement, as well as to understand specific strategies they adopted, which in turn can foster game adaptation. Following such directions and given the lack of quantitative methods for player modeling in PIRG, we propose a methodology for representing players as a mixture of existing player’s types uncovered from data. This is done by dealing both with the intrinsic uncertainty associated with the setting and with the agent necessity to act in real time to support the game interaction. Our methodology first focuses on encoding time series data generated from player-robot interaction into images, in particular Gramian angular field images, to represent continuous data. To these, we apply latent Dirichlet allocation to summarize the player’s motion style as a probabilistic mixture of different styles discovered from data. This approach has been tested in a dataset collected from a real, physical robot game, where activity patterns are extracted by using a custom three-axis accelerometer sensor module. The obtained results suggest that the proposed system is able to provide a robust description for the player interaction.
SDN Based Collaborative Scheme for Mitigation of DDoS Attacks
Authors: Hameed Sufian , Ahmed Khan Hassan
Published: February 2018

Software Defined Networking (SDN) has proved itself to be a backbone in the new network design and is quickly becoming an industry standard. The idea of separation of control plane and data plane is the key concept behind SDN. SDN not only allows us to program and monitor our networks but it also helps in mitigating some key network problems. Distributed denial of service (DDoS) attack is among them. In this paper we propose a collaborative DDoS attack mitigation scheme using SDN. We design a secure controller-to-controller (C-to-C) protocol that allows SDN-controllers lying in different autonomous systems (AS) to securely communicate and transfer attack information with each other. This enables efficient notification along the path of an ongoing attack and effective filtering of traffic near the source of attack, thus saving valuable time and network resources. We also introduced three different deployment approaches i.e., linear, central and mesh in our testbed. Based on the experimental results we demonstrate that our SDN based collaborative scheme is fast and reliable in efficiently mitigating DDoS attacks in real time with very small computational footprints.