bluuebunny/crossref_metadata_2025 huggingface dataset:
Cooperative Caching in Mobile Ad Hoc Networks
Authors: Chauhan Naveen , Awasthi Lalit K. , Chand Narottam , Joshi Ramesh C. , Misra Manoj
Published: September 2012

Mobile ad hoc network (MANET) presents a constrained communication environment due to fundamental limitations of client’s resources, insufficient wireless bandwidth and users’ frequent mobility. MANETs have many distinct characteristics which distinguish them from other wireless networks. Due to frequent network disconnection, data availability is lower than traditional wired networks. Cooperative caching helps MANETs in alleviating the situation of non availability of data. In this paper, the authors present a scheme called global cluster cooperation (GCC) for caching in mobile ad hoc networks. In this scheme, network topology is partitioned into non-overlapping clusters based on the physical network proximity. This approach fully exploits the pull mechanism to facilitate cache sharing in a MANET. Simulation experiments show that GCC mechanism achieves significant improvements in cache hit ratio and average query latency in comparison with other caching strategies.
Modeling and Simulation of Alternative Energy Generation Processes using HONN
Authors: Hernández Salvador Carlos , Camperos Edgar Nelson Sanchez , Navarro Rocío Carrasco , Tun Joel Kelly Gurubel , García José Andrés Bueno
Published: September 2012

This chapter deals with the application of Higher Order Neural Networks (HONN) on the modeling and simulation of two processes commonly used to produce gas with energy potential: anaerobic digestion and gasification. Two control strategies for anaerobic digestion are proposed in order to obtain high biomethane flow rate from degradation of organic wastes such as wastewater. A neurofuzzy scheme which is composed by a neural observer, a fuzzy supervisor, and two control actions is presented first. After that, a speed-gradient inverse optimal neural control for trajectory tracking is designed and applied to an anaerobic digestion model. The control law calculates dilution rate and bicarbonate in order to track a methane production reference trajectory under controlled conditions and avoid washout. A nonlinear discrete-time neural observer (RHONO) for unknown nonlinear systems in presence of external disturbances and parameter uncertainties is used to estimate the biomass concentration, substrate degradation, and inorganic carbon. On the other side, a high order neural network structure is developed for the process identification in a gasification reactor; the gas, composed mainly of hydrogen and carbon monoxide (synthesis gas or syngas), is produced from thermo chemical transformation of solid organic wastes. The identifier is developed in order to reproduce a kinetic model of a biomass gasifier. In both cases (biological and thermo chemical processes), the Extended Kalman Filter (EKF) is used as a training algorithm. The proposed methodologies application is illustrated via numerical simulations.
Time Series Forecasting via a Higher Order Neural Network trained with the Extended Kalman Filter for Smart Grid Applications
Authors: Ricalde Luis J. , Catzin Glendy A. , Alanis Alma Y. , Sanchez Edgar N.
Published: September 2012

This chapter presents the design of a neural network that combines higher order terms in its input layer and an Extended Kalman Filter (EKF)-based algorithm for its training. The neural network-based scheme is defined as a Higher Order Neural Network (HONN), and its applicability is illustrated by means of time series forecasting for three important variables present in smart grids: Electric Load Demand (ELD), Wind Speed (WS), and Wind Energy Generation (WEG). The proposed model is trained and tested using real data values taken from a microgrid system in the UADY School of Engineering. The length of the regression vector is determined via the Lipschitz quotients methodology.
HONNs with Extreme Learning Machine to Handle Incomplete Datasets
Authors: Xu Shuxiang
Published: September 2012

An Extreme Learning Machine (ELM) randomly chooses hidden neurons and analytically determines the output weights (Huang, et al., 2005, 2006, 2008). With the ELM algorithm, only the connection weights between hidden layer and output layer are adjusted. The ELM algorithm tends to generalize better at a very fast learning speed: it can learn thousands of times faster than conventionally popular learning algorithms (Huang, et al., 2006). Artificial Neural Networks (ANNs) have been widely used as powerful information processing models and adopted in applications such as bankruptcy prediction, predicting costs, forecasting revenue, forecasting share prices and exchange rates, processing documents, and many more. Higher Order Neural Networks (HONNs) are ANNs in which the net input to a computational neuron is a weighted sum of products of its inputs. Real life data are not usually perfect. They contain wrong, incomplete, or vague data. Hence, it is usual to find missing data in many information sources used. Missing data is a common problem in statistical analysis (Little & Rubin, 1987). This chapter uses the Extreme Learning Machine (ELM) algorithm for HONN models and applies it in several significant business cases, which involve missing datasets. The experimental results demonstrate that HONN models with the ELM algorithm offer significant advantages over standard HONN models, such as faster training, as well as improved generalization abilities.
On Some Dynamical Properties of Randomly Connected Higher Order Neural Networks
Authors: Miyajima Hiromi , Shigei Noritaka , Yatsuki Shuji
Published: September 2012

This chapter presents macroscopic properties of higher order neural networks. Randomly connected Neural Networks (RNNs) are known as a convenient model to investigate the macroscopic properties of neural networks. They are investigated by using the statistical method of neuro-dynamics. By applying the approach to higher order neural networks, macroscopic properties of them are made clear. The approach establishes: (a) there are differences between stability of RNNs and Randomly connected Higher Order Neural Networks (RHONNs) in the cases of the digital state -model and the analog state model; (b) there is no difference between stability of RNNs and RHONNs in the cases of the digital state -model and the analog state -model; (c) with neural networks with oscillation, there are large differences between RNNs and RHONNs in the cases of the digital state -model and the analog state -model, that is, there exists complex dynamics in each model for ; (d) behavior of groups composed of RHONNs are represented as a combination of the behavior of each RHONN.
Virtual Interdisciplinary Experiences for Teachers of Writing
Authors: Rosalia Christine , Baecher Laura
Published: September 2012

This chapter describes how virtual fieldwork was perceived by candidates in two teacher education programs: Teaching English to Speakers of Other Languages (TESOL) and Adolescent English (AE) as they partnered with English Language Learners (ELLs) in a middle school and college setting. By jointly examining findings from these parallel initiatives, the affordances and constraints of technology as an interdisciplinary collaborative tool may be better understood. Overall, teacher candidates reported a desire for more such “real” fieldwork, even further contact with ELLs, and continued hands-on work with the texts of these diverse writers. Unanticipated findings relate to the benefits of the projects to the cooperating teachers at partner schools, who became involved in professional learning as the demands of the technology were negotiated and partnership with the university was strengthened. The projects also underscore the ways in which technology-based collaborations must be supervised and supported.
Enhancing Diversity in STEM Interdisciplinary Learning
Authors: Blake Reginald A. , Liou-Mark Janet
Published: September 2012

The Science, Technology, Engineering, and Mathematics (STEM) disciplines have traditionally been woefully unsuccessful in attracting, retaining, and graduating acceptable numbers of Underrepresented Minorities (URMs). A new paradigm of STEM practices is needed to address this vexing problem. This chapter highlights a novel interdisciplinary approach to STEM education. Instead of being siloed and mired in their respective STEM disciplines, students integrate real world, inquiry-based learning that is underpinned by a strong foundation in mathematics and a myriad of other pillars of STEM activities. These activities include Peer-Assisted Learning Workshops, Mentoring Programs, Undergraduate Research Experiences, STEM Exposure Trips, Conference Participation, and Peer Leadership. This strategy enhances STEM education among URMs by purposefully connecting and integrating knowledge and skills from across the STEM disciplines to solve real-world problems, by synthesizing and transferring knowledge across disciplinary boundaries, and by building critical thinking skills in a manner that is relevant to their experiences and yet transformative.
Integration of Civic Engagement Pedagogies in the STEM Disciplines
Authors: Brown Gwen Cohen , Karthikeyan Laina
Published: September 2012

This chapter discusses the development and implementation of an interdisciplinary learning community between the departments of Dental Hygiene and Biological Sciences, correlating nutrition with oral health and oral cancer and its prevention by early screening. The goal of the project was to engage underrepresented, urban undergraduate students in civic learning, with an eye toward expanding learning capacities and civic responsibilities beyond the classroom. The project followed participation in the 2010 Summer Institute offered by the National Science Foundation’s Science Education for New Civic Engagements and Responsibilities (SENCER). Oral and Maxillofacial Pathology integrates basic science curriculum and applies this unified foundation knowledge to the clinical evaluation of disease, thereby closing the gap between didactic and applied material. Dental Hygiene students enrolled in Nutrition and Anatomy and Physiology will learn to connect this knowledge gained with practical application outside the natural sciences, which in turn will make these courses more interesting and relevant.
Data Hiding for Text and Binary Files
Authors: Hirohisa Hioki
Published: September 2012

This chapter presents an overview of text-based and binary-based data hiding methods. Text methods, through which secret information is embedded into innocent-looking textual data, are mostly used for steganography. Binary methods are applied to program binary codes: executables and libraries. In binary methods, information is embedded into a binary code so that its functionality is preserved. Data hiding methods for binary codes have been studied intensively to perform watermarking for protecting software from piracy acts. A message can also be embedded into a binary code in a steganographic manner. Another method is also introduced, which is proposed for enhancing the performance of an executable file.
Data-Embedding Pen
Authors: Uchida Seiichi , Liwicki Marcus , Iwamura Masakazu , Omachi Shinichiro , Kise Koichi
Published: September 2012

In this chapter, the authors present a new writing device called data-embedding pen, where a single inkjet nozzle is attached to its pen tip. When writing a stroke, the nozzle produces an additional ink-dot sequence along the stroke. The ink-dot sequence can represent various meta-information, such as the writer’s ID, the writing date, and a certain URL. Since the embedded meta-information is placed on the paper, it can be extracted by scanning or photographing the paper. Accordingly, by the data-embedding pen, a physical paper conveys any digital information. In other words, handwriting by the data-embedding pen can be a new medium connecting the physical and cyber worlds.
ERP Upgrade vs. ERP Replacement
Authors: Albadri Fayez
Published: September 2012

ERP systems life cycle may extend in some business organizations up to fifteen years or more. Nevertheless, the time comes in the life of an ERP system when there is a need to evaluate and compare the value of continuing to use the existing ERP system version against the option to upgrade to a higher version of the same system or having it replaced all together by a different system. In many cases, this translates into a critical management-sponsored mission designating a dedicated team or task force to investigate the feasibility of the alternative options, and to report on the preferred option with a recommendation of the way forward and implementation approach. This case reflects the investigations of Gulf Telecom Company (GTC) in exploring the viability and feasibility of its ERP options to support and provide the grounds for a management decision to mark the next phase of the ERP in the organization. The case describes the approach that was adopted by Gulf Telecom and highlights the challenges to accomplish the mission successfully and any lessons learned from this experience.
ERP Implementation
Authors: Kovacevic Vladimir
Published: September 2012

Considering the high rate of failures in ERP implementation projects, there is an urgent need to identify the causes of such failures and the preventing actions associated with these causes. ERP practitioners and academics are unanimous that competencies and abilities of the ERP project manager have a direct impact on the project and its well-being. In fact, it is widely accepted that specific project manager’s attributes such as oversight, leadership, communication, problem solving, and conflict-resolution are critical to the success of ERP projects. This case highlights some of the important issues and challenges that the author has encountered as a project manager of ERP system implementation in an Oil and Gas company in Kuwait. The focus of the case is on lessons learned and tips that can be handy and useful for people who may resume this important role in implementation projects.
Managing Knowledge and Change in GCC Project
Authors: Albadri Fayez , Abdallah Salam
Published: September 2012

The “End-Users” factor is singled out as the one of the most important ERP Critical Success Factors (CSF). It is evident from reported ERP failure cases that commonly used approaches to ERP end-users’ “training and competency building” are inadequate and ineffective. The case reports on an alternative structured approach that was developed and adopted in GCC Project. The new approach redefines the traditional role of “ERP Training” from isolated project activities that aim to introduce end-users to “how-to” use applications to an integral component of a comprehensive “knowledge and change management” strategy that advocates a holistic life-cycle approach to managing ERP. The proposed approach, which was successfully adopted in GCC ERP project, was built around “end-user characterization” as the main input into “competency building.” It is also flexible enough to plug into standard ERP methodologies and could be projected throughout the ERP life cycle. The end-users characterization and Competency Building Approach (ECB) is expected to contribute to increased business gains and return on investment as a result of boosting levels of ERP usage and utilization.
Relational Attributes in Supply Chain Relationships
Authors: Law Sweety , Verville Jacques , Taskin Nazim
Published: September 2012

The objective of this research paper is to examine the relational attributes underpinning supply chain networks, which linked firms need to manage on an ongoing basis. In examining the connections, which are different from transaction-based connections, this study measures the effects of face-to-face communication, trust, involvement, job title, and sales volume on performance. The hypothesized relationships are mostly supported and provide nuanced insights into relational attributes that affect supply-chain relationships and performance. These attributes are the basis for creating relationship intensity, magnitude, and history, described as collaborative facilitators that can enhance performance. All levels of management have a role to play in how the relational attributes are applied and managed. Senior leadership such as CEOs may need to play a larger role in trust development and involvement maintenance, while mid-level and line managers may need to engage in more face-to-face communication in maintaining trust and collaboration intensity.
B2B Relationships in Modern Times
Authors: Hannås Gøril , Andersen Otto
Published: September 2012

Information technology (IT) enables businesses to integrate information systems across entities without altering the firms’ legal boundaries. New forms of inter-firm dependence and governance mechanisms may arise, due to the explicit investments made in technology and systems for collaboration purposes. There is an important distinction between general and customized investments in inter-organizational information systems (IOS), because the specificity level in IT exhibits certain characteristics that accentuate both the risk and value of inter-firm trade. Several research calls were made to validate governance theories on IOS. Based on a literature review, this paper provides a synthesis and integration of transaction cost economics (TCE) and IOS literature regarding governance forms. The paper discusses why the specificity level of IOS plays a central role in modern collaboration between firms, and how vertical electronic coordination (VEC) represents a mechanism for electronic governance forms and presents an agenda for future research.
Discrete-Event Simulation Models for Assessing Incidents in Railway Systems
Authors: Sánchez Álvaro García , Ortega-Mier Miguel
Published: September 2012

This paper presents a discrete event simulation model developed with a commercial environment. A modular approach is adopted, which facilitates building models for different railway systems. A key feature of this simulator is that it simultaneously models train movements and passenger behavior. The simulator has been used to assess two different policies when short incidents occur. Incidents are characterized by different factors, which are analyzed for both policies. A case-study is presented based on a subsystem of the commuter train network of the province of Madrid in Spain.
Solving a Bi-Criteria Hybrid Flowshop Scheduling Problem Occurring in Apparel Manufacturing
Authors: Montoya-Torres Jairo R. , Vargas-Nieto Fabián
Published: September 2012

This paper studies the problem of production scheduling in a company belonging to the apparel industry, where textile labels are manufactured through the process of thermal transfer. The problem is modelled as a flexible flowshop with two stages. The objectives are the maximisation of system productivity (or minimisation of makespan) and the minimisation of the number of production orders with late delivery. This paper proposes a scheduling procedure based on a bi-objective genetic algorithm. An experimental study was performed using real data from the enterprise. Since validation results showed the efficiency and effectiveness of the proposed procedure, a decision-aid tool is designed. The algorithm is implemented at the enterprise and allows improved key performance metrics.
Supply Chain Management Practices of Indian Automobile Industry
Authors: Sahay B. S. , Sharma Vikram , Sardana G. D.
Published: September 2012

The automobile industry is a major contributor to India’s economy. The Indian automobile manufacturers face stiff international competition in the wake of all major US and European car manufacturers entering the Indian market. In the contemporary scenario, supply chain management practices can be adopted to improve operational efficiency and profits. This paper presents the current status of Indian automotive supply chains. For this, data was collected by conducting a nationwide survey. The paper highlights some major problems plaguing the Indian automotive supply chains and finally, presents some recommendations that are potentially useful to bring Indian automotive supply chains at par with global industry leaders.
A Complementary Cyber Swarm Algorithm
Authors: Yin Peng-Yeng , Glover Fred , Laguna Manuel , Zhu Jia-Xian
Published: September 2012

A recent study (Yin et al., 2010) showed that combining particle swarm optimization (PSO) with the strategies of scatter search (SS) and path relinking (PR) produces a Cyber Swarm Algorithm that creates a more effective form of PSO than methods that do not incorporate such mechanisms. This paper proposes a Complementary Cyber Swarm Algorithm (C/CyberSA) that performs in the same league as the original Cyber Swarm Algorithm but adopts different sets of ideas from the tabu search (TS) and the SS/PR template. The C/CyberSA exploits the guidance information and restriction information produced in the history of swarm search and the manipulation of adaptive memory. Responsive strategies using long term memory and path relinking implementations are proposed that make use of critical events encountered in the search. Experimental results with a large set of challenging test functions show that the C/CyberSA outperforms two recently proposed swarm-based methods by finding more optimal solutions while simultaneously using a smaller number of function evaluations. The C/CyberSA approach further produces improvements comparable to those obtained by the original CyberSA in relation to the Standard PSO 2007 method (Clerc, 2008).
Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem
Authors: James Tabitha , Rego Cesar
Published: September 2012

This paper introduces a new path relinking algorithm for the well-known quadratic assignment problem (QAP) in combinatorial optimization. The QAP has attracted considerable attention in research because of its complexity and its applicability to many domains. The algorithm presented in this study employs path relinking as a solution combination method incorporating a multistart tabu search algorithm as an improvement method. The resulting algorithm has interesting similarities and contrasts with particle swarm optimization methods. Computational testing indicates that this algorithm produces results that rival the best QAP algorithms. The authors additionally conduct an analysis disclosing how different strategies prove more or less effective depending on the landscapes of the problems to which they are applied. This analysis lays a foundation for developing more effective future QAP algorithms, both for methods based on path relinking and tabu search, and for hybrids of such methods with related processes found in particle swarm optimization.
A Multiobjective Particle Swarm Optimizer for Constrained Optimization
Authors: Yen Gary G. , Leong Wen-Fung
Published: September 2012

Constraint handling techniques are mainly designed for evolutionary algorithms to solve constrained multiobjective optimization problems (CMOPs). Most multiojective particle swarm optimization (MOPSO) designs adopt these existing constraint handling techniques to deal with CMOPs. In the proposed constrained MOPSO, information related to particles’ infeasibility and feasibility status is utilized effectively to guide the particles to search for feasible solutions and improve the quality of the optimal solution. This information is incorporated into the four main procedures of a standard MOPSO algorithm. The involved procedures include the updating of personal best archive based on the particles’ Pareto ranks and their constraint violation values; the adoption of infeasible global best archives to store infeasible nondominated solutions; the adjustment of acceleration constants that depend on the personal bests’ and selected global best’s infeasibility and feasibility status; and the integration of personal bests’ feasibility status to estimate the mutation rate in the mutation procedure. Simulation to investigate the proposed constrained MOPSO in solving the selected benchmark problems is conducted. The simulation results indicate that the proposed constrained MOPSO is highly competitive in solving most of the selected benchmark problems.
Experimental Study on Boundary Constraint Handling in Particle Swarm Optimization
Authors: Cheng Shi , Shi Yuhui , Qin Quande
Published: September 2012

Premature convergence happens in Particle Swarm Optimization (PSO) for solving both multimodal problems and unimodal problems. With an improper boundary constraints handling method, particles may get “stuck in” the boundary. Premature convergence means that an algorithm has lost its ability of exploration. Population diversity is an effective way to monitor an algorithm’s ability of exploration and exploitation. Through the population diversity measurement, useful search information can be obtained. PSO with a different topology structure and a different boundary constraints handling strategy will have a different impact on particles’ exploration and exploitation ability. In this paper, the phenomenon of particles gets “stuck in” the boundary in PSO is experimentally studied and reported. The authors observe the position diversity time-changing curves of PSOs with different topologies and different boundary constraints handling techniques, and analyze the impact of these setting on the algorithm’s ability of exploration and exploitation. From these experimental studies, an algorithm’s ability of exploration and exploitation can be observed and the search information obtained; therefore, more effective algorithms can be designed to solve problems.
Image Segmentation Based on Bacterial Foraging and FCM Algorithm
Authors: Mo Hongwei , Yin Yujing
Published: September 2012

This paper addresses the issue of image segmentation by clustering in the domain of image processing. The clustering algorithm taken account here is the Fuzzy C-Means which is widely adopted in this field. Bacterial Foraging Optimization Algorithm is an optimal algorithm inspired by the foraging behavior of E.coli. For the purpose to reinforce the global search capability of FCM, the Bacterial Foraging Algorithm was employed to optimize the objective criterion function which is interrelated to centroids in FCM. To evaluate the validation of the composite algorithm, cluster validation indexes were used to obtain numerical results and guide the possible best solution found by BF-FCM. Several experiments were conducted on three UCI data sets. For image segmentation, BF-FCM successfully segmented 8 typical grey scale images, and most of them obtained the desired effects. All the experiment results show that BF-FCM has better performance than that of standard FCM.
Exploring Social Media for Health and Wellness
Authors: Mitra Sinjini , Padman Rema
Published: September 2012

The use of social media for health and wellness promotion is a relatively new concept. Nonetheless, several early adopting health plans and provider organizations have begun to design and pilot social and mobile media platforms to empower members to enhance self management of health and wellness goals. In this case study of a large health plan in Pennsylvania, the authors describe the design and execution of a member survey to identify some factors that are significantly associated with interest in adopting such technology platforms for obtaining health-related information and services. Analysis of relevant data from more than 4,000 responses indicates significant differences among important segments of the member population defined with respect to demographic factors, level of computer and social media usage, and frequency of engagement in specific online activities. They anticipate that these insights can assist health plans to develop and deploy targeted services and tools for health and wellness management.
Thymic Function Is Maintained during Salmonella-Induced Atrophy and Recovery
Authors: Ross Ewan A. , Coughlan Ruth E. , Flores-Langarica Adriana , Lax Sian , Nicholson Julia , Desanti Guillaume E. , Marshall Jennifer L. , Bobat Saeeda , Hitchcock Jessica , White Andrea , Jenkinson William E. , Khan Mahmood , Henderson Ian R. , Lavery Gareth G. , Buckley Christopher D. , Anderson Graham , Cunningham Adam F.
Published: September 2012

Thymic atrophy is a frequent consequence of infection with bacteria, viruses, and parasites and is considered a common virulence trait between pathogens. Multiple reasons have been proposed to explain this atrophy, including premature egress of immature thymocytes, increased apoptosis, or thymic shutdown to prevent tolerance to the pathogen from developing. The severe loss in thymic cell number can reflect an equally dramatic reduction in thymic output, potentially reducing peripheral T cell numbers. In this study, we examine the relationship between systemic Salmonella infection and thymic function. During infection, naive T cell numbers in peripheral lymphoid organs increase. Nevertheless, this occurs despite a pronounced thymic atrophy caused by viable bacteria, with a peak 50-fold reduction in thymocyte numbers. Thymic atrophy is not dependent upon homeostatic feedback from peripheral T cells or on regulation of endogenous glucocorticoids, as demonstrated by infection of genetically altered mice. Once bacterial numbers fall, thymocyte numbers recover, and this is associated with increases in the proportion and proliferation of early thymic progenitors. During atrophy, thymic T cell maturation is maintained, and single-joint TCR rearrangement excision circle analysis reveals there is only a modest fall in recent CD4+ thymic emigrants in secondary lymphoid tissues. Thus, thymic atrophy does not necessarily result in a matching dysfunctional T cell output, and thymic homeostasis can constantly adjust to systemic infection to ensure that naive T cell output is maintained.
Th17 Cells Upregulate Polymeric Ig Receptor and Intestinal IgA and Contribute to Intestinal Homeostasis
Authors: Cao Anthony T. , Yao Suxia , Gong Bin , Elson Charles O. , Cong Yingzi
Published: September 2012

Although CD4+ Th17 cells are enriched in normal intestines, their role in regulation of the host response to microbiota, and whether and how they contribute to intestinal homeostasis, is still largely unknown. It is also unclear whether Th17 cells regulate intestinal IgA production, which is also abundant in the intestinal lumen and has a crucial role as the first defense line in host response to microbiota. In this study, we found that intestinal polymeric Ig receptor (pIgR) and IgA production was impaired in T cell-deficient TCR-βxδ−/− mice. Repletion of TCR-βxδ−/− mice with Th17 cells from CBir1 flagellin TCR transgenic mice, which are specific for a commensal Ag, increased intestinal pIgR and IgA. The levels of intestinal pIgR and IgA in B6.IL-17R (IL-17R−/−) mice were lower than wild type mice. Treatment of colonic epithelial HT-29 cells with IL-17 increased pIgR expression. IL-17R−/− mice demonstrated systemic antimicroflora Ab response. Consistently, administering dextran sulfate sodium (DSS) to C57BL/6 mice after treatment with IL-17–neutralizing Ab resulted in more severe intestinal inflammation compared with control Ab. Administering DSS to IL-17R−/− mice resulted in increased weight loss and more severe intestinal inflammation compared with wild type mice, indicating a protective role of Th17 cells in intestinal inflammation. Individual mice with lower levels of pIgR and intestinal-secreted IgA correlated with increased weight loss at the end of DSS administration. Collectively, our data reveal that microbiota-specific Th17 cells contribute to intestinal homeostasis by regulating intestinal pIgR expression and IgA secretion.
The Role of IL-15 in Activating STAT5 and Fine-Tuning IL-17A Production in CD4 T Lymphocytes
Authors: Pandiyan Pushpa , Yang Xiang-Ping , Saravanamuthu Senthil S. , Zheng Lixin , Ishihara Satoru , O’Shea John J. , Lenardo Michael J.
Published: September 2012

IL-15 is an important IL-2–related cytokine whose role in Th17 cell biology has not been fully elucidated. In this study, we show that exogenous IL-15 decreased IL-17A production in Th17 cultures. Neutralization of IL-15 using an Ab led to increases in IL-17A production in Th17 cultures. Both Il15−/− and Il15r−/− T cell cultures displayed higher frequency of IL-17A producers and higher amounts of IL-17A in the supernatants compared with those of wild-type (WT) cells in vitro. IL-15 down-modulated IL-17A production independently of retinoic acid-related orphan receptor-γt, Foxp3, and IFN-γ expression. Both Th17 cells and APCs produced IL-15, which induced binding of STAT5, an apparent repressor to the Il17 locus in CD4 T cells. Also, in a model of myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE), Il15−/− mice displayed exacerbated inflammation—correlating with increased IL-17A production by their CD4+ T cells—compared with WT controls. Exogenous IL-15 administration and IL-17A neutralization reduced the severity of EAE in Il15−/− mice. Taken together, these data indicate that IL-15 has a negative regulatory role in fine-tuning of IL-17A production and Th17-mediated inflammation.
Giant Cell Temporal Arteritis Associated with Overlying Basal Cell Carcinoma: Co-Incidence or Connection?
Authors: Mahe Etienne , Demellawy Dina El , Bane Anita , Alowami Salem
Published: September 2012

Giant cell arteritis is a granulomatous vasculitis of large and medium sized arteries manifesting as temporal arteritis and/or polymyalgia rheumatica. The histological assessment of temporal artery biopsies is frequently encountered in anatomical pathology and has important diagnostic consequences in patients clinically suspected of having giant cell arteritis. We present an intriguing case of giant cell arteritis associated with a Basal cell carcinoma and discuss the ongoing controversy pertaining to the association of giant cell arteritis/polymyalgia rheumatica with malignancy.
Statistics of severe tornadoes and severe tornado outbreaks
Authors: Malamud B. D. , Turcotte D. L.
Published: September 2012

Abstract. The standard measures of the intensity of a tornado in the USA and many other countries are the Fujita and Enhanced Fujita scales. These scales are based on the damage that a tornado causes. Another measure of the strength of a tornado is its path length of touchdown, L. In this study we consider severe tornadoes, which we define as L≥10 km, in the continental USA (USA Storm Prediction Center Severe Weather Database). We find that for the period 1982–2011, for individual severe tornadoes (L≥10 km): (i) There is a strong linear scaling between the number of severe tornadoes in a year and their total path length in that year. (ii) The cumulative frequency path length data suggests that, not taking into account any changing trends over time, we would expect in a given year (on average) one severe tornado with a path length L≥115 km and in a decade (on average) one severe tornado with a path length L≥215 km. (iii) The noncumulative frequency-length statistics of severe tornado touchdown path lengths, 20
An assessment of CALIOP polar stratospheric cloud composition classification
Authors: Pitts M. C. , Poole L. R. , Lambert A. , Thomason L. W.
Published: September 2012

Abstract. This study assesses the robustness of the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) polar stratospheric cloud (PSC) composition classification algorithm – which is based solely on the spaceborne lidar data – through the use of nearly coincident gas-phase HNO3 data from the Microwave Limb Sounder (MLS) on Aura and Goddard Earth Observing System Model, Version 5 (GEOS-5) temperature analyses. Following the approach of Lambert et al. (2012), we compared the observed temperature-dependent HNO3 uptake by CALIOP PSCs with modeled uptake for equilibrium STS (supercooled ternary solution) and NAT (nitric acid trihydrate), which indicates how well PSCs in the various composition classes conform to expected temperature existence regimes and also offers some insight into PSC growth kinetics. We examined the CALIOP PSC data record from both polar regions over the period from 2006 through 2011 and over a range of potential temperature levels spanning the 15–30 km altitude range. We found that most PSCs identified as STS exhibit gas phase uptake of HNO3 consistent with theory, but with a small temperature bias, similar to Lambert et al. (2012). Ice PSC classification is also robust in the CALIOP optical data, with the mode in the ice observations occurring about 0.5 K below the frost point. We found that CALIOP PSCs identified as liquid/NAT mixtures exhibit two distinct preferred modes. One mode is significantly out of thermodynamic equilibrium with respect to NAT (4–5 K below the equilibrium NAT existence temperature), with HNO3 uptake dominated by the more numerous liquid droplets. The other liquid/NAT mixture mode is much closer to NAT thermodynamic equilibrium, indicating that the particles have been exposed to temperatures below the NAT existence temperature for extended periods of time. The CALIOP PSC composition classification scheme was found to be excellent in an overall sense, and we have a good understanding of the cause of the minor misclassifications that do occur. We will investigate means to correct these deficiencies in our next generation algorithm.
Raman Lidar for Meteorological Observations, RALMO – Part 2: Validation of water vapor measurements
Authors: Brocard E. , Philipona R. , Haefele A. , Romanens G. , Ruffieux D. , Simeonov V. , Calpini B.
Published: September 2012

Abstract. The Raman Lidar for Meteorological Observations (RALMO) was installed at the MeteoSwiss Regional Center of Payerne, Switzerland, in Summer 2008. One of its aim is to provide continuous vertical profiles of tropospheric water vapor during day and night at a high temporal resolution. Twelve months (October 2009–September 2010) of lidar data are analyzed. During this period of time, the lidar produced 9086 profiles, representing 52.6% of the time (this figure reached 63.2% for the first 6 months of 2011). Under cloud-free conditions, half of the profiles reached more than 8610 m above ground level at night, and 4050 m during the day. In order to validate the capabilities of the instrument, the year of lidar data was compared to the collocated radiosondes. On average, lidar water vapor mixing ratio was found to be within 5 to 10% of radiosonde values up to 8 km at night, and within 3% up to 3 km during the day. Relative humidity results show an agreement within 2 and 5% for day and night, respectively. Integrated water vapor comparison also shows a good correlation with both radiosondes and GPS measurements: the lidar had a 4.2% dry bias compared to radiosondes and a 5.3% wet bias compared to GPS. These results validate the performance of the lidar and the humidity profiles with a 30-min time resolution.
Alaskan soil carbon stocks: spatial variability and dependence on environmental factors
Authors: Mishra U. , Riley W. J.
Published: September 2012

Abstract. The direction and magnitude of soil organic carbon (SOC) changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5). Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%), followed by discontinuous (28%), isolated (24.3%), and sporadic (23.6%) permafrost areas. Our high-resolution mapping of soil carbon stock reveals the potential vulnerability of high-latitude soil carbon and can be used as a basis for future studies of anthropogenic and climatic perturbations.
Applying a time-lapse camera network to observe snow processes in mountainous catchments
Authors: Garvelmann J. , Pohl S. , Weiler M.
Published: September 2012

Abstract. A network of 45 spatially distributed time-lapse cameras was used to carry out a continuous observation of snow processes and snow cover properties throughout three mid-latitude medium elevation mountain catchments in hourly intervals. A simple technical modification was conducted to enable the deployment of the standard digital cameras in any location. Image analysis software was applied to extract information about snow depth, surface albedo, and canopy interception from the digital images. Furthermore, the distributed design of the camera network made it possible to identify the elevation of the snow rain interface for any precipitation event for the interpretation of winter flooding events resulting from snow melt. Study results prove that the application of digital time-lapse photography is an appropriate technique to observe the spatial distribution and temporal evolution of seasonal snow covers in a mountainous environment.
Evaluation of areal precipitation estimates based on downscaled reanalysis and station data by hydrological modelling
Authors: Duethmann D. , Zimmer J. , Gafurov A. , Güntner A. , Merz B. , Vorogushyn S.
Published: September 2012

Abstract. In data sparse regions, as in many mountainous catchments, it is a challenge to generate suitable precipitation input fields for hydrological modelling, as station data do not provide enough information to derive areal precipitation estimates. This study presents a method using the spatial variation of precipitation from downscaled reanalysis data for the interpolation of gauge observations. The second aim of this study is the evaluation of different precipitation estimates by hydrological modelling. Study area is the Karadarya catchment in Central Asia (11 700 km2). ERA-40 reanalysis data are downscaled with the regional climate model Weather Research and Forecasting Model (WRF). Precipitation data from gauge observations are interpolated (i) using monthly accumulated WRF precipitation data, (ii) using monthly fields from multiple linear regression against topographical variables and (iii) with the inverse distance approach. These precipitation data sets are also compared to (iv) the direct use of the precipitation output from the WRF downscaled ERA-40 data and (v) precipitation from the APHRODITE data set. Our study suggests that using monthly fields from downscaled reanalysis data can be a good approach for the interpolation of station data in data sparse mountainous regions. Compared to mean annual precipitation from continental and global scale gridded data sets our precipitation estimates for the study area are considerably higher. The introduction of a calibrated precipitation bias factor for the comparison of different precipitation estimates by hydrological modelling allows for a more informed differentiation with regard to the temporal dynamics, on the one hand, and the overall bias, on the other hand. Uncertainty and sensitivity analyses suggest that our results are robust against uncertainties in the calibration parameters, other model parameters and inputs, and the selected calibration period.
The HUPO Human Proteome Project (HPP), a Global Health Research Collaboration
Authors: Omenn Gilbert S.
Published: September 2012

The global Human Proteome Project (HPP) was announced by the Human Proteome Organization (HUPO) at the 2010 World Congress of Proteomics in Sydney, Australia, and launched at the 2011 World Congress of Proteomics in Geneva, Switzerland, with analogies to the highly successful Human Genome Project. Extensive progress was reported at the September 2012 World Congress in Boston, USA. The HPP is designed to map the entire human proteome using available and emerging technologies.The HPP aims to create a molecular and biological foundation for improving health globally through better understanding of disease processes, more accurate diagnoses, and targets for more effective therapies and preventive interventions against many diseases. There are opportunities for individual investigators everywhere to access advanced datasets and to join HPP research teams.
Enhancing English Vocabularies through Language Play in Children Movies
Authors: Sujatna Eva Tuckyta Sari , Sujatna Meita Lukitawati
Published: September 2012

Everybody either a child or an adult, likes playing. Playing is a fun activity. For children, watching movies is one of the fun activities. Learning languages can also be a fun activity by using language play. Language play can help the children in enhancing their ability in improving their vocabularies.  In children movies, we usually found language play. The language play forms in children movies can be found both phonologically and morphologically forms. This article tries to explore the language play forms through children movies to support the children ability in enhancing their English vocabularies.
Performance Evaluation of an Induction Machine with Auxiliary Winding for Wind Turbine Power
Authors: Habash Riadh W. Y. , Tang Qianjun , Guillemette Pierre , Irfan Nazish
Published: September 2012

The purpose of this paper is to reinforce with theoretical and experimental evaluation the effectiveness of employing an induction generator to enhance the performance of a small wind energy converter (SWEC). With this generator, the SWEC works more efficiently and therefore can produce more energy in a unit turbine area. To verify the SWEC performance, a model has been proposed, simulated, built, and experimentally tested over a range of operating conditions. The results demonstrate a significant increase in output power with an induction generator that employs an auxiliary winding, which is only magnetically coupled to the stator main winding. It is also shown that the operating performance of the induction machine with the novel proposed technique is significantly enhanced in terms of suppressed signal distortion and harmonics, severity of resistive losses and overheating, power factor, and preventing high inrush current at starting.
Uniform Asymptotics for the Finite-Time Ruin Probability of a Time-Dependent Risk Model with Pairwise Quasiasymptotically Independent Claims
Authors: Gao Qingwu
Published: September 2012

We consider a generalized time-dependent risk model with constant interest force, where the claim sizes are of pairwise quasiasymptotical independence structure, and the claim size and its interclaim time satisfy a dependence structure defined by a conditional tail probability of the claim size given the interclaim time before the claim occurs. As the claim-size distribution belongs to the dominated variation class, we establish some weakly asymptotic formulae for the tail probability of discounted aggregate claims and the finite-time ruin probability, which hold uniformly for all times in a relevant infinite interval.