Numerical modeling of the failure mechanisms in Si thin film anode for Li-ion batteries

In recent times, the demand for the storage of electrical energy has grown rapidly for both static applications and the portable electronics enforcing the substantial improvement in battery systems, and Li-ion batteries have been proven to have maximum energy storage density in all rechargeable batteries. However, major breakthroughs are required to consummate the requirement of higher energy density with lower cost to penetrate new markets. Graphite anode having limited capacity has become a bottle neck in the process of developing next generation batteries and can be replaced by higher capacity metals such as Silicon. In the present study we are focusing on the mechanical behavior of the Si-thin film anode under various operating conditions. A numerical model is developed to simulate the intercalation induced stress and the failure mechanism of the complex anode structure. Effect of the various physical phenomena such as diffusion induced stress, plasticity and the crack propagation are investigated to predict better performance parameters for improved design.

The past ecology of Abies alba provides new perspectives on future responses of silver fir forests to global warming

Paleoecology can provide valuable insights into the ecology of species that complement observation and experiment-based assessments of climate impact dynamics. New paleoecological records (e.g., pollen, macrofossils) from the Italian Peninsula suggest a much wider climatic niche of the important European tree species Abies alba (silver fir) than observed in its present spatial range. To explore this discrepancy between current and past distribution of the species, we analyzed climatic data (temperature, precipitation, frost, humidity, sunshine) and vegetation-independent paleoclimatic reconstructions (e.g., lake levels, chironomids) and use global coupled carbon-cycle climate (NCAR CSM1.4) and dynamic vegetation (LandClim) modeling. The combined evidence suggests that during the mid-Holocene (6000 years ago), prior to humanization of vegetation, A. alba formed forests under conditions that exceeded the modern (1961-1990) upper temperature limit of the species by 5-7°C (July means). Annual precipitation during this natural period was comparable to today (>700-800 mm), with drier summers and wetter winters. In the meso-Mediterranean to sub-Mediterranean forests A. alba co-occurred with thermophilous taxa such as Quercus ilex, Q. pubescens, Olea europaea, Phillyrea, Arbutus, Cistus, Tilia, Ulmus, Acer, Hedera helix, Ilex aquifolium, Taxus, and Vitis. Results from the last interglacial (ca. 130 000-115 000 BP), when human impact was negligible, corroborate the Holocene evidence. Thermophilous Mediterranean A. alba stands became extinct during the last 5000 years when land-use pressure and specifically excessive anthropogenic fire and browsing disturbance increased. Our results imply that the ecology of this key European tree species is not yet well understood. On the basis of the reconstructed realized climatic niche of the species, we anticipate that the future geographic range of A. alba may not contract regardless of migration success, even if climate should become significantly warmer than today with summer temperatures increasing by up to 5-7°C, as long as precipitation does not fall below 700-800 mm/yr, and anthropogenic disturbance (e.g., fire, browsing) does not become excessive. Our finding contradicts recent studies that projected range contractions under global-warming scenarios, but did not factor how millennia of human impacts reduced the realized climatic niche of A. alba.

Frontiers of finance: Evolution and efficient markets

In this review article, we explore several recent advances in the quantitative modeling of financial markets. We begin with the Efficient Markets Hypothesis and describe how this controversial idea has stimulated a number of new directions of research, some focusing on more elaborate mathematical models that are capable of rationalizing the empirical facts, others taking a completely different tack in rejecting rationality altogether. One of the most promising directions is to view financial markets from a biological perspective and, specifically, within an evolutionary framework in which markets, instruments, institutions, and investors interact and evolve dynamically according to the “law” of economic selection. Under this view, financial agents compete and adapt, but they do not necessarily do so in an optimal fashion. Evolutionary and ecological models of financial markets is truly a new frontier whose exploration has just begun.

Green, Pink & Silver? The Future of Labour in Europe, Vol. 2. CEPS Paperback, 3 March 2015

Work is both an essential part of our daily lives and one of the major policy concerns across Europe. In this second volume of The Future of Labour in Europe, the authors explain in accessible language the findings of the NEUJOBS project on the job prospects of key industries and groups of people. They use three colours – green, pink and silver – to pinpoint areas with the largest challenges as well as the greatest potential. The conclusions are addressed to policy-makers, the business world, journalists, fellow academics and to anyone interested in the shape, size and character of the labour markets of tomorrow.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Projecting the fate of fish populations using ecological-economic modeling

Four marine fish species are among the most important on the world market: cod, salmon, tuna, and sea bass. While the supply of North American and European markets for two of these species - Atlantic salmon and European sea bass - mainly comes from fish farming, Atlantic cod and tunas are mainly caught from wild stocks. We address the question what will be the status of these wild stocks in the midterm future, in the year 2048, to be specific. Whereas the effects of climate change and ecological driving forces on fish stocks have already gained much attention, our prime interest is in studying the effects of changing economic drivers, as well as the impact of variable management effectiveness. Using a process-based ecological-economic multispecies optimization model, we assess the future stock status under different scenarios of change. We simulate (i) technological progress in fishing, (ii) increasing demand for fish, and (iii) increasing supply of farmed fish, as well as the interplay of these driving forces under different sce- narios of (limited) fishery management effectiveness. We find that economic change has a substantial effect on fish populations. Increasing aquaculture production can dampen the fishing pressure on wild stocks, but this effect is likely to be overwhelmed by increasing demand and technological progress, both increasing fishing pressure. The only solution to avoid collapse of the majority of stocks is institutional change to improve management effectiveness significantly above the current state. We conclude that full recognition of economic drivers of change will be needed to successfully develop an integrated ecosystem management and to sustain the wild fish stocks until 2048 and beyond.

New Developments in Tourism and Hotel Demand Modeling and Forecasting

Abstract Purpose The purpose of the study is to review recent studies published from 2007-2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field. Design/Methodology/approach Articles on tourism and hotel demand modeling and forecasting published in both science citation index (SCI) and social science citation index (SSCI) journals were identified and analyzed. Findings This review found that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area. Research limitations/implications The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implications This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/value The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

ASSESSING QUALITY IN HIGH-UNCERTAINTY MARKETS: ONLINE REVIEWS OF CREDENCE SERVICES

In economics of information theory, credence products are those whose quality is difficult or impossible for consumers to assess, even after they have consumed the product (Darby & Karni, 1973). This dissertation is focused on the content, consumer perception, and power of online reviews for credence services. Economics of information theory has long assumed, without empirical confirmation, that consumers will discount the credibility of claims about credence quality attributes. The same theories predict that because credence services are by definition obscure to the consumer, reviews of credence services are incapable of signaling quality. Our research aims to question these assumptions. In the first essay we examine how the content and structure of online reviews of credence services systematically differ from the content and structure of reviews of experience services and how consumers judge these differences. We have found that online reviews of credence services have either less important or less credible content than reviews of experience services and that consumers do discount the credibility of credence claims. However, while consumers rationally discount the credibility of simple credence claims in a review, more complex argument structure and the inclusion of evidence attenuate this effect. In the second essay we ask, “Can online reviews predict the worst doctors?” We examine the power of online reviews to detect low quality, as measured by state medical board sanctions. We find that online reviews are somewhat predictive of a doctor’s suitability to practice medicine; however, not all the data are useful. Numerical or star ratings provide the strongest quality signal; user-submitted text provides some signal but is subsumed almost completely by ratings. Of the ratings variables in our dataset, we find that punctuality, rather than knowledge, is the strongest predictor of medical board sanctions. These results challenge the definition of credence products, which is a long-standing construct in economics of information theory. Our results also have implications for online review users, review platforms, and for the use of predictive modeling in the context of information systems research.

Modeling perspective for the relevant market of voice services: mobile to mobile

Los mercados asociados a los servicios de voz móvil a móvil, brindados por operadoras del Sistema Móvil Avanzado en Latinoamérica, han estado sujetos a procesos regulatorios motivados por la dominancia en el mercado de un operador, buscando obtener óptimas condiciones de competencia. Específicamente en Ecuador, la Superintendencia de Telecomunicaciones (Organismo Técnico de Control de Telecomunicaciones) desarrolló un modelo para identificar acciones de regulación que puedan proporcionar al mercado efectos sostenibles de competencia en el largo plazo. Este artículo trata sobre la aplicación de la ingeniería de control para desarrollar un modelo integral del mercado, empleando redes neuronales para la predicción de trarifas de cada operador y un modelo de lógica difusa para predecir la demanda. Adicionalmente, se presenta un modelo de inferencia de lógica difusa para reproducir las estrategias de mercadeo de los operadores y la influencia sobre las tarifas. Dichos modelos permitirían la toma adecuada de decisiones y fueron validados con datos reales.

Software engineering: methods, modeling and teaching

Since the emergence of software engineering in the late 1960's as a response to the software crisis, researchers throughout the world are trying to give theoretical support to this discipline. Several points of view have to be reviewed in order to complete this task. In the middle 70's Frederick Brooks Jr. coined the term "silver bullet" suggesting the solution to several problems rela-ted to software engineering and, hence, we adopted such a metaphor as a symbol for this book. Methods, modeling, and teaching are the insights reviewed in this book. Some work related to these topies is presented by software engineering researchers, led by Ivar Jacobson, one of the most remarkable researchers in this area. We hope our work will contribute to advance in giving the theoretieal support that software engineering needs.

Lawsonia Inermis-mediated Synthesis Of Silver Nanoparticles: Activity Against Human Pathogenic Fungi And Bacteria With Special Reference To Formulation Of An Antimicrobial Nanogel.

Lawsonia inermis mediated synthesis of silver nanoparticles (Ag-NPs) and its efficacy against Candida albicans, Microsporum canis, Propioniabacterium acne and Trichophyton mentagrophytes is reported. A two-step mechanism has been proposed for bioreduction and formation of an intermediate complex leading to the synthesis of capped nanoparticles was developed. In addition, antimicrobial gel for M. canis and T. mentagrophytes was also formulated. Ag-NPs were synthesized by challenging the leaft extract of L. inermis with 1 mM AgNO₃. The Ag-NPs were characterized by Ultraviolet-Visible (UV-Vis) spectrophotometer and Fourier transform infrared spectroscopy (FTIR). Transmission electron microscopy (TEM), nanoparticle tracking and analysis sytem (NTA) and zeta potential was measured to detect the size of Ag-NPs. The antimicrobial activity of Ag-NPs was evaluated by disc diffusion method against the test organisms. Thus these Ag-NPs may prove as a better candidate drug due to their biogenic nature. Moreover, Ag-NPs may be an answer to the drug-resistant microorganisms.

Preparation Of An Agar-silver Nanoparticles (a-agnp) Film For Increasing The Shelf-life Of Fruits.

Preparation of protective coating possessing antimicrobial properties is present day need as they increase the shelf life of fruits and vegetables. In the present study, preparation of agar-silver nanoparticle film for increasing the shelf life of fruits is reported. Silver nanoparticles (Ag-NPs) biosynthesised using an extract of Ocimum sanctum leaves, were mixed with agar-agar to prepare an agar-silver nanoparticles (A-AgNp) film. This film was surface-coated over the fruits, Citrus aurantifolium (Thornless lime) and Pyrus malus (Apple), and evaluated for the determination of antimicrobial activity of A-AgNp films using disc diffusion method, weight loss and shelf life of fruits. This study demonstrates that these A-AgNp films possess antimicrobial activity and also increase the shelf life of fruits.

Graded Meshes In Bio-thermal Problems With Transmission-line Modeling Method.

In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

Biogenic Silver Nanoparticles Associated With Silver Chloride Nanoparticles (ag@agcl) Produced By Laccase From Trametes Versicolor.

In the present study, semi-purified laccase from Trametes versicolor was applied for the synthesis of silver nanoparticles, and the properties of the produced nanoparticles were characterized. All of the analyses of the spectra indicated silver nanoparticle formation. A complete characterization of the silver nanoparticles showed that a complex of silver nanoparticles and silver ions was produced, with the majority of the particles having a Ag(2+) chemical structure. A hypothetical mechanistic scheme was proposed, suggesting that the main pathway that was used was the interaction of silver ions with the T1 site of laccase, producing silver nanoparticles with the concomitant inactivation of laccase activity and posterior complexing with silver ions.