bluuebunny/crossref_metadata_2025 huggingface dataset:
Entropy as a Metric Generator of Dissipation in Complete Metriplectic Systems
Authors: Materassi Massimo
Published: August 2016

This lecture is a short review on the role entropy plays in those classical dissipative systems whose equations of motion may be expressed via a Leibniz Bracket Algebra (LBA). This means that the time derivative of any physical observable f of the system is calculated by putting this f in a “bracket” together with a “special observable” F, referred to as a Leibniz generator of the dynamics. While conservative dynamics is given an LBA formulation in the Hamiltonian framework, so that F is the Hamiltonian H of the system that generates the motion via classical Poisson brackets or quantum commutation brackets, an LBA formulation can be given to classical dissipative dynamics through the Metriplectic Bracket Algebra (MBA): the conservative component of the dynamics is still generated via Poisson algebra by the total energy H, while S, the entropy of the degrees of freedom statistically encoded in friction, generates dissipation via a metric bracket. The motivation of expressing through a bracket algebra and a motion-generating function F is to endow the theory of the system at hand with all the powerful machinery of Hamiltonian systems in terms of symmetries that become evident and readable. Here a (necessarily partial) overview of the types of systems subject to MBA formulation is presented, and the physical meaning of the quantity S involved in each is discussed. Here the aim is to review the different MBAs for isolated systems in a synoptic way. At the end of this collection of examples, the fact that dissipative dynamics may be constructed also in the absence of friction with microscopic degrees of freedom is stressed. This reasoning is a hint to introduce dissipation at a more fundamental level.
Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets
Authors: Zhang Xin , Kim Donggyu , Wang Yazhen
Published: August 2016

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two-step procedure with detection and estimation. In Step 1, we detect the jump locations by performing wavelet transformation on the observed noisy price processes. Since wavelet coefficients are significantly larger at the jump locations than the others, we calibrate the wavelet coefficients through a threshold and declare jump points if the absolute wavelet coefficients exceed the threshold. In Step 2 we estimate the jump variation by averaging noisy price processes at each side of a declared jump point and then taking the difference between the two averages of the jump point. Specifically, for each jump location detected in Step 1, we get two averages from the observed noisy price processes, one before the detected jump location and one after it, and then take their difference to estimate the jump variation. Theoretically, we show that the two-step procedure based on average realized volatility processes can achieve a convergence rate close to O P ( n − 4 / 9 ) , which is better than the convergence rate O P ( n − 1 / 4 ) for the procedure based on the original noisy process, where n is the sample size. Numerically, the method based on average realized volatility processes indeed performs better than that based on the price processes. Empirically, we study the distribution of jump variation using Dow Jones Industrial Average stocks and compare the results using the original price process and the average realized volatility processes.
Convergence and Heterogeneity in Euro Based Economies: Stability and Dynamics
Authors: Haynes Philip , Haynes Jonathan
Published: August 2016

Cluster analysis is used to explore the performance of key macroeconomic variables in European countries that share the euro, from the inception of the currency in 2002 through to 2013. An original applied statistical approach searches for a pattern synthesis across a matrix of macroeconomic data to examine if there is evidence for country clusters and whether there is convergence of the cluster patterns over time. A number of different clusters appear and these change over time as the economies of the member states dynamically interact. This includes some new countries joining the currency during the period of examination. As found in previous research, Southern European countries tend to remain separate from other countries. The new methods used, however, add to an understanding of some differences between Southern European countries, in addition to replicating their broad similarities. Hypotheses are formed about the country clusters existing in 2002, 2006 and 2013, at key points in time of the euro integration process. These hypotheses are tested using the rigour of a bivariate analysis and the multivariate method of Qualitative Comparative Analysis (QCA). The results confirm the hypotheses of cluster memberships in all three periods. The confirmation analysis provides evidence about which variables are most influencing cluster memberships at each time point. In 2002 and 2006, differences between countries are influenced by their different Harmonised Index of Consumer Prices (HICP) and labour productivity scores. In 2013, after the crisis, there is a noticeable change. Long term interest rates and gross government debt become key determinants of differences, in addition to the continuing influence of labour productivity. The paper concludes that in the last decade the convergence of countries sharing the euro has been limited, by the joining of new countries and the circumstances of the global economic crisis. The financial crisis has driven divergences from pre-existing integration. Country convergence needs to be understood as a dynamic and multivariate concept. This is a significant development of convergence theory and is an addition to how the concept has been understood previously.
Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing) and Artificial Intelligence Models (ANN, SVM): The Case of Greek Electricity Market
Authors: Papaioannou George , Dikaiakos Christos , Dramountanis Anargyros , Papaioannou Panagiotis
Published: August 2016

In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC) technique and the traditional multiple regression (PC-regression), for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity Market for the period 2004–2014. PC-regression is shown to effectively capture the intraday, intraweek and annual patterns of load. We compare our model with a number of classical statistical approaches (Holt-Winters exponential smoothing of its generalizations Error-Trend-Seasonal, ETS models, the Seasonal Autoregressive Moving Average with exogenous variables, Seasonal Autoregressive Integrated Moving Average with eXogenous (SARIMAX) model as well as with the more sophisticated artificial intelligence models, Artificial Neural Networks (ANN) and Support Vector Machines (SVM). Using a number of criteria for measuring the quality of the generated in-and out-of-sample forecasts, we have concluded that the forecasts of our hybrid model outperforms the ones generated by the other model, with the SARMAX model being the next best performing approach, giving comparable results. Our approach contributes to studies aimed at providing more accurate and reliable load forecasting, prerequisites for an efficient management of modern power systems.
Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting
Authors: Ma Xuejiao , Liu Dandan
Published: August 2016

Big data mining, analysis, and forecasting play vital roles in modern economic and industrial fields, especially in the energy system. Inaccurate forecasting may cause wastes of scarce energy or electricity shortages. However, forecasting in the energy system has proven to be a challenging task due to various unstable factors, such as high fluctuations, autocorrelation and stochastic volatility. To forecast time series data by using hybrid models is a feasible alternative of conventional single forecasting modelling approaches. This paper develops a group of hybrid models to solve the problems above by eliminating the noise in the original data sequence and optimizing the parameters in a back propagation neural network. One of contributions of this paper is to integrate the existing algorithms and models, which jointly show advances over the present state of the art. The results of comparative studies demonstrate that the hybrid models proposed not only satisfactorily approximate the actual value but also can be an effective tool in the planning and dispatching of smart grids.
Rheology of Emulsion-Filled Gels Applied to the Development of Food Materials
Authors: Geremias-Andrade Ivana , Souki Nayla , Moraes Izabel , Pinho Samantha
Published: August 2016

Emulsion-filled gels are classified as soft solid materials and are complex colloids formed by matrices of polymeric gels into which emulsion droplets are incorporated. Several structural aspects of these gels have been studied in the past few years, including their applications in food, which is the focus of this review. Knowledge of the rheological behavior of emulsion-filled gels is extremely important because it can measure interferences promoted by droplets or particle inclusion on the textural properties of the gelled systems. Dynamic oscillatory tests, more specifically, small amplitude oscillatory shear, creep-recovery tests, and large deformation experiments, are discussed in this review as techniques present in the literature to characterize rheological behavior of emulsion-filled gels. Moreover, the correlation of mechanical properties with sensory aspects of emulsion-filled gels appearing in recent studies is discussed, demonstrating the applicability of these parameters in understanding mastication processes.
Comparison of the Ability to Predict Mortality between the Injury Severity Score and the New Injury Severity Score: A Meta-Analysis
Authors: Deng Qiangyu , Tang Bihan , Xue Chen , Liu Yuan , Liu Xu , Lv Yipeng , Zhang Lulu
Published: August 2016

Background: Description of the anatomical severity of injuries in trauma patients is important. While the Injury Severity Score has been regarded as the “gold standard” since its creation, several studies have indicated that the New Injury Severity Score is better. Therefore, we aimed to systematically evaluate and compare the accuracy of the Injury Severity Score and the New Injury Severity Score in predicting mortality. Methods: Two researchers independently searched the PubMed, Embase, and Web of Science databases and included studies from which the exact number of true-positive, false-positive, false-negative, and true-negative results could be extracted. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies checklist criteria. The meta-analysis was performed using Meta-DiSc. Meta-regression, subgroup analyses, and sensitivity analyses were conducted to determine the source(s) of heterogeneity and factor(s) affecting the accuracy of the New Injury Severity Score and the Injury Severity Score in predicting mortality. Results: The heterogeneity of the 11 relevant studies (total n = 11,866) was high (I2 > 80%). The meta-analysis using a random-effects model resulted in sensitivity of 0.64, specificity of 0.93, positive likelihood ratio of 5.11, negative likelihood ratio of 0.27, diagnostic odds ratio of 27.75, and area under the summary receiver operator characteristic curve of 0.9009 for the Injury Severity Score; and sensitivity of 0.71, specificity of 0.87, positive likelihood ratio of 5.22, negative likelihood ratio of 0.20, diagnostic odds ratio of 24.74, and area under the summary receiver operating characteristic curve of 0.9095 for the New Injury Severity Score. Conclusion: The New Injury Severity Score and the Injury Severity Score have similar abilities in predicting mortality. Further research is required to determine the appropriate use of the Injury Severity Score or the New Injury Severity Score based on specific patient condition and trauma type.
Surface Water Impacted by Rural Activities Induces Genetic Toxicity Related to Recombinagenic Events in Vivo
Authors: Soares Neto José , De Carli Raíne , Kotzal Queila , Latroni Francine , Lehmann Mauricio , Dias Johnny , De Souza Cláudia , Niekraszewicz Liana , Da Silva Fernanda , Da Silva Juliana , Dihl Rafael
Published: August 2016

This investigation assessed the interaction of surface water samples with DNA to quantitatively and qualitatively characterize their mutagenic and/or recombinagenic activity. Samples were obtained at three different sites along the Tocantins River (Tocantins State, Brazil). The area has withstood the impact mainly of rural activities, which release different chemical compounds in the environment. The Drosophila melanogaster Somatic Mutation and Recombination Test (SMART) was performed in standard (ST) and high bioactivation (HB) crosses. SMART is useful for the detection of mutational and recombinational events induced by genotoxins of direct and indirect action. Results demonstrated that samples collected in both seasons were able to induce increments on the mutant spot frequencies in the larvae of the HB cross. Genotoxicity was related to a massive recombinagenic activity. The positive responses ascribed to only the HB cross means that it is linked to pro-genotoxins requiring metabolic activation. The SMART wing test in Drosophila melanogaster was shown to be highly sensitive to detect genotoxic agents present in the aquatic environment impacted by agriculture.
Can Hawaii Meet Its Renewable Fuel Target? Case Study of Banagrass-Based Cellulosic Ethanol
Authors: Tran Chinh , Yanagida John
Published: August 2016

Banagrass is a biomass crop candidate for ethanol production in the State of Hawaii. This study examines: (i) whether enough banagrass can be produced to meet Hawaii’s renewable fuel target of 20% highway fuel demand produced with renewable sources by 2020 and (ii) at what cost. This study proposes to locate suitable land areas for banagrass production and ethanol processing, focusing on the two largest islands in the state of Hawaii—Hawaii and Maui. The results suggest that the 20% target is not achievable by using all suitable land resources for banagrass production on both Hawaii and Maui. A total of about 74,224,160 gallons, accounting for 16.04% of the state’s highway fuel demand, can be potentially produced at a cost of $6.28/gallon. Lower ethanol cost is found when using a smaller production scale. The lowest cost of $3.31/gallon is found at a production processing capacity of about 9 million gallons per year (MGY), which meets about 2% of state demand. This cost is still higher than the average imported ethanol price of $3/gallon. Sensitivity analysis finds that it is possible to produce banagrass-based ethanol on Hawaii Island at a cost below the average imported ethanol price if banagrass yield increases of at least 35.56%.
Molecular Insights into the Potential Toxicological Interaction of 2-Mercaptothiazoline with the Antioxidant Enzyme—Catalase
Authors: Huang Zhenxing , Huang Ming , Mi Chenyu , Wang Tao , Chen Dong , Teng Yue
Published: August 2016

2-mercaptothiazoline (2-MT) is widely used in many industrial fields, but its residue is potentially harmful to the environment. In this study, to evaluate the biological toxicity of 2-MT at protein level, the interaction between 2-MT and the pivotal antioxidant enzyme—catalase (CAT) was investigated using multiple spectroscopic techniques and molecular modeling. The results indicated that the CAT fluorescence quenching caused by 2-MT should be dominated by a static quenching mechanism through formation of a 2-MT/CAT complex. Furthermore, the identifications of the binding constant, binding forces, and the number of binding sites demonstrated that 2-MT could spontaneously interact with CAT at one binding site mainly via Van der Waals’ forces and hydrogen bonding. Based on the molecular docking simulation and conformation dynamic characterization, it was found that 2-MT could bind into the junctional region of CAT subdomains and that the binding site was close to enzyme active sites, which induced secondary structural and micro-environmental changes in CAT. The experiments on 2-MT toxicity verified that 2-MT significantly inhibited CAT activity via its molecular interaction, where 2-MT concentration and exposure time both affected the inhibitory action. Therefore, the present investigation provides useful information for understanding the toxicological mechanism of 2-MT at the molecular level.
Octanoic Hydrazide-Linked Chitooligosaccharides-2,5-Anhydro-d-Mannofuranose
Authors: Moussa Amani , Trombotto Stéphane
Published: August 2016

Chitooligosaccharide with one 2,5-anhydro-d-mannofuranose unit at the reducing end (COSamf) was prepared by nitrous acid depolymerization of chitosan. The reducing-end functionalization of COSamf by reductive amination with octanoic hydrazide in the presence of NaBH3CN was achieved in high yield. The chemical structure of the targeted octanoic hydrazide-linked COSamf was fully characterized by NMR spectroscopy and MALDI-TOF mass spectrometry. This synthesis opens the way to a new generation of COSamf derivatives with potential amphiphilic properties.
Tailorable Burning Behavior of Ti14 Alloy by Controlling Semi-Solid Forging Temperature
Authors: Chen Yongnan , Yang Wenqing , Zhan Haifei , Zhang Fengying , Huo Yazhou , Zhao Yongqing , Song Xuding , Gu Yuantong
Published: August 2016

Semi-solid processing (SSP) is a popular near-net-shape forming technology for metals, while its application is still limited in titanium alloy mainly due to its low formability. Recent works showed that SSP could effectively enhance the formability and mechanical properties of titanium alloys. The processing parameters such as temperature and forging rate/ratio, are directly correlated with the microstructure, which endow the alloy with different chemical and physical properties. Specifically, as a key structural material for the advanced aero-engine, the burn resistant performance is a crucial requirement for the burn resistant titanium alloy. Thus, this work aims to assess the burning behavior of Ti14, a kind of burn resistant alloy, as forged at different semi-solid forging temperatures. The burning characteristics of the alloy are analyzed by a series of burning tests with different burning durations, velocities, and microstructures of burned sample. The results showed that the burning process is highly dependent on the forging temperature, due to the fact that higher temperatures would result in more Ti2Cu precipitate within grain and along grain boundaries. Such a microstructure hinders the transport of oxygen in the stable burning stage through the formation of a kind of oxygen isolation Cu-enriched layer under the burn product zone. This work suggests that the burning resistance of the alloy can be effectively tuned by controlling the temperature during the semi-solid forging process.
Transverse Crack Detection in 3D Angle Interlock Glass Fibre Composites Using Acoustic Emission
Authors: Gresil Matthieu , Saleh Mohamed , Soutis Constantinos
Published: August 2016

In addition to manufacturing cost and production rates, damage resistance has become a major issue for the composites industry. Three-dimensional (3D) woven composites have superior through-thickness properties compared to two-dimensional (2D) laminates, for example, improved impact damage resistance, high interlaminar fracture toughness and reduced notch sensitivity. The performance of 3D woven preforms is dependent on the fabric architecture, which is determined by the binding pattern. For this study, angle interlock (AI) structures with through-thickness binding were manufactured. The AI cracking simulation shows that the transverse component is the one that leads to transverse matrix cracking in the weft yarn under tensile loading. Monitoring of acoustic emission (AE) during mechanical loading is an effective tool in the study of damage processes in glass fiber-reinforced composites. Tests were performed with piezoelectric sensors bonded on a tensile specimen acting as passive receivers of AE signals. An experimental data has been generated which was useful to validate the multi-physics finite element method (MP-FEM), providing insight into the damage behaviour of novel 3D AI glass fibre composites. MP-FEM and experimental data showed that transverse crack generated a predominant flexural mode A0 and also a less energetic extensional mode S0.
Extended N-Arylsulfonylindoles as 5-HT6 Receptor Antagonists: Design, Synthesis & Biological Evaluation
Authors: Vera Gonzalo , Lagos Carlos , Almendras Sebastián , Hebel Dan , Flores Francisco , Valle-Corvalán Gissella , Pessoa-Mahana C. , Mella-Raipán Jaime , Montecinos Rodrigo , Recabarren-Gajardo Gonzalo
Published: August 2016

Based on a known pharmacophore model for 5-HT6 receptor antagonists, a series of novel extended derivatives of the N-arylsulfonyindole scaffold were designed and identified as a new class of 5-HT6 receptor modulators. Eight of the compounds exhibited moderate to high binding affinities and displayed antagonist profile in 5-HT6 receptor functional assays. Compounds 2-(4-(2-methoxyphenyl)piperazin-1-yl)-1-(1-tosyl-1H-indol-3-yl)ethanol (4b), 1-(1-(4-iodophenylsulfonyl)-1H-indol-3-yl)-2-(4-(2-methoxyphenyl)piperazin-1-yl)ethanol (4g) and 2-(4-(2-methoxyphenyl)piperazin-1-yl)-1-(1-(naphthalen-1-ylsulfonyl)-1H-indol-3-yl)ethanol (4j) showed the best binding affinity (4b pKi = 7.87; 4g pKi = 7.73; 4j pKi = 7.83). Additionally, compound 4j was identified as a highly potent antagonist (IC50 = 32 nM) in calcium mobilisation functional assay.
Is Cancer Cachexia Attributed to Impairments in Basal or Postprandial Muscle Protein Metabolism?
Authors: Horstman Astrid , Olde Damink Steven , Schols Annemie , Van Loon Luc
Published: August 2016

Cachexia is a significant clinical problem associated with very poor quality of life, reduced treatment tolerance and outcomes, and a high mortality rate. Mechanistically, any sizeable loss of skeletal muscle mass must be underpinned by a structural imbalance between muscle protein synthesis and breakdown rates. Recent data indicate that the loss of muscle mass with aging is, at least partly, attributed to a blunted muscle protein synthetic response to protein feeding. Whether such anabolic resistance is also evident in conditions where cachexia is present remains to be addressed. Only few data are available on muscle protein synthesis and breakdown rates in vivo in cachectic cancer patients. When calculating the theoretical changes in basal or postprandial fractional muscle protein synthesis and breakdown rates that would be required to lose 5% of body weight within a six-month period, we can define the changes that would need to occur to explain the muscle mass loss observed in cachectic patients. If changes in both post-absorptive and postprandial muscle protein synthesis and breakdown rates contribute to the loss of muscle mass, it would take alterations as small as 1%–2% to induce a more than 5% decline in body weight. Therefore, when trying to define impairments in basal and/or postprandial muscle protein synthesis or breakdown rates using contemporary stable isotope methodology in cancer cachexia, we need to select large homogenous groups of cancer patients (>40 patients) to allow us to measure physiological and clinically relevant differences in muscle protein synthesis and/or breakdown rates. Insight into impairments in basal or postprandial muscle protein synthesis and breakdown rates in cancer cachexia is needed to design more targeted nutritional, pharmaceutical and/or physical activity interventions to preserve skeletal muscle mass and, as such, to reduce the risk of complications, improve quality of life, and lower mortality rates during the various stages of the disease.
TPGS-Stabilized Curcumin Nanoparticles Exhibit Superior Effect on Carrageenan-Induced Inflammation in Wistar Rat
Authors: Rachmawati Heni , Safitri Dewi , Pradana Aditya , Adnyana I
Published: August 2016

Curcumin, a hydrophobic polyphenol compound derived from the rhizome of the Curcuma genus, has a wide spectrum of biological and pharmacological applications. Previously, curcumin nanoparticles with different stabilizers had been produced successfully in order to enhance solubility and per oral absorption. In the present study, we tested the anti-inflammatory effect of d-α-Tocopheryl polyethylene glycol 1000 succinate (TPGS)-stabilized curcumin nanoparticles in vivo. Lambda-carrageenan (λ-carrageenan) was used to induce inflammation in rats; it was given by an intraplantar route and intrapelurally through surgery in the pleurisy test. In the λ-carrageenan-induced edema model, TPGS-stabilized curcumin nanoparticles were given orally one hour before induction and at 0.5, 4.5, and 8.5 h after induction with two different doses (1.8 and 0.9 mg/kg body weight (BW)). Sodium diclofenac with a dose of 4.5 mg/kg BW was used as a standard drug. A physical mixture of curcumin-TPGS was also used as a comparison with a higher dose of 60 mg/kg BW. The anti-inflammatory effect was assessed on the edema in the carrageenan-induced paw edema model and by the volume of exudate as well as the number of leukocytes reduced in the pleurisy test. TPGS-stabilized curcumin nanoparticles with lower doses showed better anti-inflammatory effects, indicating the greater absorption capability through the gastrointestinal tract.
On the Capital Allocation Problem for a New Coherent Risk Measure in Collective Risk Theory
Authors: Assa Hirbod , Morales Manuel , Omidi Firouzi Hassan
Published: August 2016

In this paper we introduce a new coherent cumulative risk measure on a subclass in the space of càdlàg processes. This new coherent risk measure turns out to be tractable enough within a class of models where the aggregate claims is driven by a spectrally positive Lévy process. We focus our motivation and discussion on the problem of capital allocation. Indeed, this risk measure is well-suited to address the problem of capital allocation in an insurance context. We show that the capital allocation problem for this risk measure has a unique solution determined by the Euler allocation method. Some examples and connections with existing results as well as practical implications are also discussed.
Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding
Authors: Wilkening André , Puleva Nikolina , Ivlev Oleg
Published: August 2016

The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs). This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user’s participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS), the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient’s extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user’s comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.
Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation
Authors: Sun Rui , Zhang Guanghai , Yan Xiaoxing , Gao Jun
Published: August 2016

Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.
A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques
Authors: Gholizadeh Mohammad , Melesse Assefa , Reddi Lakshmi
Published: August 2016

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).
Using a Hexagonal Mirror for Varying Light Intensity in the Measurement of Small-Angle Variation
Authors: Hsieh Meng-Chang , Lin Jiun-You , Chang Chia-Ou
Published: August 2016

Precision positioning and control are critical to industrial-use processing machines. In order to have components fabricated with excellent precision, the measurement of small-angle variations must be as accurate as possible. To achieve this goal, this study provides a new and simple optical mechanism by varying light intensity. A He-Ne laser beam was passed through an attenuator and into a beam splitter. The reflected light was used as an intensity reference for calibrating the measurement. The transmitted light as a test light entered the optical mechanism hexagonal mirror, the optical mechanism of which was created by us, and then it entered the power detector after four consecutive reflections inside the mirror. When the hexagonal mirror was rotated by a small angle, the laser beam was parallel shifted. Once the laser beam was shifted, the hitting area on the detector was changed; it might be partially outside the sensing zone and would cause the variation of detection intensity. This variation of light intensity can be employed to measure small-angle variations. The experimental results demonstrate the feasibility of this method. The resolution and sensitivity are 3 × 10−40 and 4 mW/° in the angular range of 0.6°, respectively, and 9.3 × 10−50 and 13 mW/° in the angular range of 0.25°.
Research on the Error Characteristics of a 110 kV Optical Voltage Transformer under Three Conditions: In the Laboratory, Off-Line in the Field and During On-Line Operation
Authors: Xiao Xia , Hu Haoliang , Xu Yan , Lei Min , Xiong Qianzhu
Published: August 2016

Optical voltage transformers (OVTs) have been applied in power systems. When performing accuracy performance tests of OVTs large differences exist between the electromagnetic environment and the temperature variation in the laboratory and on-site. Therefore, OVTs may display different error characteristics under different conditions. In this paper, OVT prototypes with typical structures were selected to be tested for the error characteristics with the same testing equipment and testing method. The basic accuracy, the additional error caused by temperature and the adjacent phase in the laboratory, the accuracy in the field off-line, and the real-time monitoring error during on-line operation were tested. The error characteristics under the three conditions—laboratory, in the field off-line and during on-site operation—were compared and analyzed. The results showed that the effect of the transportation process, electromagnetic environment and the adjacent phase on the accuracy of OVTs could be ignored for level 0.2, but the error characteristics of OVTs are dependent on the environmental temperature and are sensitive to the temperature gradient. The temperature characteristics during on-line operation were significantly superior to those observed in the laboratory.
Coping with Migration-Induced Urban Growth: Addressing the Blind Spot of UN Habitat
Authors: Aerni Philipp
Published: August 2016

The demography of cities in the 21st century will be shaped, to a large extent, by migration. This paper argues that the rights-based approach to urban policy advocated in the preparatory work of Habitat III, the UN Conference on Housing and Sustainable Urban Development to be held in October 2016 in Quito, Ecuador, may not be conducive to this goal. The approach lacks a contextual and dynamic understanding of urbanization. It implicitly assumes that a growing and expansive urban economy would primarily benefit the rich and harm the poor. The resulting containment policies to stop “urban sprawl” and defend “the right to the city” can, however, be counterproductive if adopted in cities in less developed countries (LDCs) that grow fast due to internal migration. Attempts to limit urban growth may merely lead to more informal settlements, less affordable housing, and increasing costs of doing business. In other words, it may benefit the rich and harm the poor. LDCs should, therefore, refrain from adopting defensive urban policies mostly advocated by more developed countries (MDCs) and, instead, plan for sustainable urban expansion designed to improve access to essential urban services and to create a level playing field for newcomers in business. In this context, urban policies may build upon the basic insights of the late urbanist Jane Jacobs. She recognized that the vital function of cities is to provide affordable infrastructure and an institutional environment that enable migrants and other marginal urban communities to contribute to urban prosperity and problem-solving with their skills, networks, and entrepreneurial minds. The resulting social and economic empowerment increases access to essential human rights and ensures that cities become more inclusive, resilient, and sustainable.
Simulation and Assessment of Whole Life-Cycle Carbon Emission Flows from Different Residential Structures
Authors: Wen Rikun , Qi Shenjun , Jrade Ahmad
Published: August 2016

To explore the differences in carbon emissions over the whole life-cycle of different building structures, the published calculated carbon emissions from residential buildings in China and abroad were normalized. Embodied carbon emission flows, operations stage carbon emission flows, demolition and reclamation stage carbon emission flows and total life-cycle carbon emission flows from concrete, steel, and wood structures were obtained. This study is based on the theory of the social cost of carbon, with an adequately demonstrated social cost of carbon and social discount rate. Taking into consideration both static and dynamic situations and using a social discount rate of 3.5%, the total life-cycle carbon emission flows, absolute carbon emission and building carbon costs were calculated and assessed. The results indicated that concrete structures had the highest embodied carbon emission flows and negative carbon emission flows in the waste and reclamation stage. Wood structures that started the life-cycle with stored carbon had the lowest carbon emission flows in the operations stage and relatively high negative carbon emission flows in the reclamation stage. Wood structures present the smallest carbon footprints for residential buildings.
Model of the Russian Federation Construction Innovation System: An Integrated Participatory Systems Approach
Authors: Suprun Emiliya , Sahin Oz , Stewart Rodney , Panuwatwanich Kriengsak
Published: August 2016

This research integrates systemic and participatory techniques to model the Russian Federation construction innovation system. Understanding this complex construction innovation system and determining the best levers for enhancing it require the dynamic modelling of a number of factors, such as flows of resources and activities, policies, uncertainty and time. To build the foundations for such a dynamic model, the employed study method utilised an integrated stakeholder-based participatory approach coupled with structural analysis (MICMAC—Matrice d'Impacts Croisés Multiplication Appliquée à un Classement Cross-Impact Matrix). This method identified the key factors of the Russian Federation construction innovation system, their causal relationship (i.e., influence/dependence map) and, ultimately, a causal loop diagram. The generated model reveals pathways to improving construction innovation in the Russian Federation and underpins the future development of an operationalised system dynamics model.
Handcrafted Electrocorticography Electrodes for a Rodent Behavioral Model
Authors: Tasnim Nishat , Ajam Ali , Ramos Raul , Koripalli Mukhesh , Chennamsetti Manisankar , Choi Yoonsu
Published: August 2016

Electrocorticography (ECoG) is a minimally invasive neural recording method that has been extensively used for neuroscience applications. It has proven to have the potential to ease the establishment of proper links for neural interfaces that can offer disabled patients an alternative solution for their lost sensory and motor functions through the use of brain-computer interface (BCI) technology. Although many neural recording methods exist, ECoG provides a combination of stability, high spatial and temporal resolution with chronic and mobile capabilities that could make BCI systems accessible for daily applications. However, many ECoG electrodes require MEMS fabricating techniques which are accompanied by various expenses that are obstacles for research projects. For this reason, this paper presents an animal study using a low cost and simple handcrafted ECoG electrode that is made of commercially accessible materials. The study is performed on a Lewis rat implanted with a handcrafted 32-channel non-penetrative ECoG electrode covering an area of 3 × 3 mm2 on the cortical surface. The ECoG electrodes were placed on the motor and somatosensory cortex to record the signal patterns while the animal was active on a treadmill. Using a Tucker-Davis Technologies acquisition system and the software Synapse to monitor and analyze the electrophysiological signals, the electrodes obtained signals within the amplitude range of 200 µV for local field potentials with reliable spatiotemporal profiles. It was also confirmed that the handcrafted ECoG electrode has the stability and chronic features found in other commercial electrodes.
Groundwater Contamination by Uranium and Mercury at the Ridaura Aquifer (Girona, NE Spain)
Authors: Navarro Andrés , Font Xavier , Viladevall Manuel
Published: August 2016

Elevated concentrations of uranium and mercury have been detected in drinking water from public supply and agricultural wells in alluvial and granitic aquifers of the Ridaura basin located at Catalan Coastal Ranges (CCR). The samples showed high concentrations of U above the U.S. standards and the World Health Organization regulations which set a maximum value of 30 µg/L. Further, high mercury concentrations above the European Drinking Water Standards (1 μg/L) were found. Spatial distribution of U in groundwater and geochemical evolution of groundwater suggest that U levels appear to be highest in granitic areas where groundwater has long residence times and a significant salinity. The presence of high U concentrations in alluvial groundwater samples could be associated with hydraulic connection through fractures between the alluvial system and deep granite system. According to this model, oxidizing groundwater moving through fractures in the leucocratic/biotitic granite containing anomalous U contents are the most likely to acquire high levels of U. The distribution of Hg showed concentrations above 1 μg/L in 10 alluvial samples, mainly located near the limit of alluvial aquifer with igneous rocks, which suggests a possible migration of Hg from granitic materials. Also, some samples showed Hg concentrations comprised between 0.9 and 1.5 μg/L, from wells located in agricultural areas.
Are Culinary and Hospitality Service Attributes Key Predictors of Returning Visits for Culinary Tourism Locations?
Authors: Harrington Robert J. , Ottenbacher Michael , Löwenhagen Nina
Published: August 2016

While a growing number of tourists view culinary and hospitality service as a major aspect of the travel experience, little research has been performed to assess if these attributes are primary predictors of return visits. To assess these relationships, the study used an expectation-based
approach to assess expectation fulfillment and its impact on visitor intentions for future visits. A survey was conducted in South Tyrol, Italy and 721 tourists participated. The results supported the notion that a region known for its outstanding culinary profile could create a bundle of
primary hospitality service and culinary attributes with the potential to become key decision factors for return visits to the destination. Other core tourism activities were nonsignificant predictors of return visits. Older visitors and those traveling in smaller groups were also more likely
to revisit the destination.
Gastronomy as a Factor of Tourism Development: Case Study of the City of Córdoba in Spain
Authors: Beltrán Francisco Javier Jiménez , Cruz Francisco González Santa , López-Guzmán Tomás
Published: August 2016

Gastronomy is a key factor in the competitiveness of tourist destinations, especially for those who have a recognized cultural heritage. The ability to make a destination attractive from a culinary perspective lies, beyond having an adequate level of restaurants and local gastronomic
resources, in designing and marketing a full-range cultural offer, where gastronomy is mixed with other aspects of the local culture. The objective of this research is to present an analysis of tourists visiting the city of Córdoba, Spain, noted for its architectural heritage and its
relationship with gastronomy. The main contribution of this study reflects a highly educated tourist profile, with purchasing power and interest in knowing the cultural and culinary heritage of the city. Its achievement depends largely on the satisfaction with the visit.
Taking Stock of the New Nordic Cuisine at Danish Coastal Destinations
Authors: Therkelsen Anette
Published: August 2016

This article deals with coastal tourists' food experiences and focuses on the potentials and challenges the new Nordic cuisine (NNC) concept holds in relation to German tourists visiting Danish coastal destinations. By means of a conceptual model, the characteristics of the NNC are
related to scholarly knowledge on tourists' food experiences and potentially critical points are identified. Analyses of qualitative interviews with German tourists at five Danish coastal destinations expand on these critical points and show that the NNC and coastal tourists give different
priority to product qualities as well as spatial and social context qualities of food consumption. Sense of place gained through food consumption seems to be where the German demand perspective and the NNC concept meet. However, as place-specific food experiences are perceived to be scarce
at Danish coastal destinations this represents yet another challenge.
Practical synthetic strategies towards lipophilic 6-iodotetrahydroquinolines and -dihydroquinolines
Authors: Chisholm David R , Zhou Garr-Layy , Pohl Ehmke , Valentine Roy , Whiting Andrew
Published: August 2016

The synthesis of novel tetrahydroquinolines (THQ) and dihydroquinolines (DHQ) are reported using three practical, scalable synthetic approaches to access highly lipophilic analogues bearing a 6-iodo substituent, each with a different means of cyclisation. A versatile and stable quinolin-2-one intermediate was identified, which could be reduced to the corresponding THQ with borane reagents, or to the DHQ with diisobutylaluminium hydride via a novel elimination that is more favourable at higher temperatures. Coupling these strongly electron-donating scaffolds to electron-accepting moieties caused the resulting structures to exhibit strong fluorescence.
Herds of Wildebeest, Flasks of Vodka, Heaps of Trouble: An Embodied Construction Grammar Approach to English Measure Phrases
Authors: Dodge Ellen , Wright Abby
Published: August 2016

In this paper we examine English Measure Phrases (EMPs), for example, herd of zebras, cup of coffee, square of cloth, and miles of beach. Although EMPs internally resemble other phrases of the same form (a noun followed by of followed by a noun phrase), they interact with other elements in the clause in unique ways. On the basis of the phenomena studied in this paper, it will be necessary to distinguish EMPs from other N-of-NP phrases.
Consistency and Creativity in First Language Acquisition
Authors: Israel Michael
Published: August 2016

In this paper I argue that a general PRINCIPLE OF CONSISTENCY both motivatesand constrains the process of analogical learning in a usage-based grammar. The basic idea is that children learning a language, and speakers in general, represent linguistic units in ways that maximize their motivation and emphasize their commonalities. Two units are consistent with each other to the degree that they match in their formal and semantic specifications. LOCAL CONSISTENCY applies to linguistic units activated online in usage events, and requires these to be as consistent as possible with entrenched utterance types. GLOBAL CONSISTENCY applies to the repertoire of constructions as a whole, and requires that units be represented in ways which maximize their consistency with each other. Local consistency favors a massive inventory of low-scope constructions to represent the rich details of experienced usage events: it thus fosters arbitrariness in the grammar, but also makes on-line processing easier by offering conventional units for every occasion. Global consistency favors the development of abstract representations and recurrent inheritance links across constructions: it thus increases motivation in the grammar, but also makes processing harder as the schematic units it favors are farther removed from the details of actual usage.