bluuebunny/crossref_metadata_2025 huggingface dataset:
Versatile surface tension and adhesion for SPH fluids
Authors: Akinci Nadir , Akinci Gizem , Teschner Matthias
Published: November 2013

Realistic handling of fluid-air and fluid-solid interfaces in SPH is a challenging problem. The main reason is that some important physical phenomena such as surface tension and adhesion emerge as a result of inter-molecular forces in a microscopic scale. This is different from scalar fields such as fluid pressure, which can be plausibly evaluated on a macroscopic scale using particles. Although there exist techniques to address this problem for some specific simulation scenarios, there does not yet exist a general approach to reproduce the variety of effects that emerge in reality from fluid-air and fluid-solid interactions. In order to address this problem, we present a new surface tension force and a new adhesion force. Different from the existing work, our surface tension force can handle large surface tensions in a realistic way. This property lets our approach handle challenging real scenarios, such as water crown formation, various types of fluid-solid interactions, and even droplet simulations. Furthermore, it prevents particle clustering at the free surface where inter-particle pressure forces are incorrect. Our adhesion force allows plausible two-way attraction of fluids and solids and can be used to model different wetting conditions. By using our forces, modeling surface tension and adhesion effects do not require involved techniques such as generating a ghost air phase or surface tracking. The forces are applied to the neighboring fluid-fluid and fluid-boundary particle pairs in a symmetric way, which satisfies momentum conservation. We demonstrate that combining both forces allows simulating a variety of interesting effects in a plausible way.
Inverse dynamic hair modeling with frictional contact
Authors: Derouet-Jourdan Alexandre , Bertails-Descoubes Florence , Daviet Gilles , Thollot Joëlle
Published: November 2013

In the latest years, considerable progress has been achieved for accurately acquiring the geometry of human hair, thus largely improving the realism of virtual characters. In parallel, rich physics-based simulators have been successfully designed to capture the intricate dynamics of hair due to contact and friction. However, at the moment there exists no consistent pipeline for converting a given hair geometry into a realistic physics-based hair model. Current approaches simply initialize the hair simulator with the input geometry in the absence of external forces. This results in an undesired sagging effect when the dynamic simulation is started, which basically ruins all the efforts put into the accurate design and/or capture of the input hairstyle. In this paper we propose the first method which consistently and robustly accounts for surrounding forces---gravity and frictional contacts, including hair self-contacts---when converting a geometric hairstyle into a physics-based hair model. Taking an arbitrary hair geometry as input together with a corresponding body mesh, we interpret the hair shape as a static equilibrium configuration of a hair simulator, in the presence of gravity as well as hair-body and hair-hair frictional contacts. Assuming that hair parameters are homogeneous and lie in a plausible range of physical values, we show that this large underdetermined inverse problem can be formulated as a well-posed constrained optimization problem, which can be solved robustly and efficiently by leveraging the frictional contact solver of the direct hair simulator. Our method was successfully applied to the animation of various hair geometries, ranging from synthetic hairstyles manually designed by an artist to the most recent human hair data automatically reconstructed from capture.
Spatio-temporal extrapolation for fluid animation
Authors: Zhang Yubo , Ma Kwan-Liu
Published: November 2013

We introduce a novel spatio-temporal extrapolation technique for fluid simulation designed to improve the results without using higher resolution simulation grids. In general, there are rigid demands associated with pushing fluid animations to higher resolutions given limited computational capabilities. This results in tradeoffs between implementing high-order numerical methods and increasing the resolution of the simulation in space and time. For 3D problems, such challenges rapidly become cost-ineffective. The extrapolation method we present improves the flow features without using higher resolution simulation grids. In this paper, we show that simulation results from our extrapolation are comparable to those from higher resolution simulations. In addition, our method differs from high-order numerical methods because it does not depend on the equation or specific solver. We demonstrate that it is easy to implement and can significantly improve the fluid animation results.
Patch-based high dynamic range video
Authors: Kalantari Nima Khademi , Shechtman Eli , Barnes Connelly , Darabi Soheil , Goldman Dan B. , Sen Pradeep
Published: November 2013

Despite significant progress in high dynamic range (HDR) imaging over the years, it is still difficult to capture high-quality HDR video with a conventional, off-the-shelf camera. The most practical way to do this is to capture alternating exposures for every LDR frame and then use an alignment method based on optical flow to register the exposures together. However, this results in objectionable artifacts whenever there is complex motion and optical flow fails. To address this problem, we propose a new approach for HDR reconstruction from alternating exposure video sequences that combines the advantages of optical flow and recently introduced patch-based synthesis for HDR images. We use patch-based synthesis to enforce similarity between adjacent frames, increasing temporal continuity. To synthesize visually plausible solutions, we enforce constraints from motion estimation coupled with a search window map that guides the patch-based synthesis. This results in a novel reconstruction algorithm that can produce high-quality HDR videos with a standard camera. Furthermore, our method is able to synthesize plausible texture and motion in fast-moving regions, where either patch-based synthesis or optical flow alone would exhibit artifacts. We present results of our reconstructed HDR video sequences that are superior to those produced by current approaches.
Augmenting physical avatars using projector-based illumination
Authors: Bermano Amit , Brüschweiler Philipp , Grundhöfer Anselm , Iwai Daisuke , Bickel Bernd , Gross Markus
Published: November 2013

Animated animatronic figures are a unique way to give physical presence to a character. However, their movement and expressions are often limited due to mechanical constraints. In this paper, we propose a complete process for augmenting physical avatars using projector-based illumination, significantly increasing their expressiveness. Given an input animation, the system decomposes the motion into low-frequency motion that can be physically reproduced by the animatronic head and high-frequency details that are added using projected shading. At the core is a spatio-temporal optimization process that compresses the motion in gradient space, ensuring faithful motion replay while respecting the physical limitations of the system. We also propose a complete multi-camera and projection system, including a novel defocused projection and subsurface scattering compensation scheme. The result of our system is a highly expressive physical avatar that features facial details and motion otherwise unattainable due to physical constraints.
Sparse localized deformation components
Authors: Neumann Thomas , Varanasi Kiran , Wenger Stephan , Wacker Markus , Magnor Marcus , Theobalt Christian
Published: November 2013

We propose a method that extracts sparse and spatially localized deformation modes from an animated mesh sequence. To this end, we propose a new way to extend the theory of sparse matrix decompositions to 3D mesh sequence processing, and further contribute with an automatic way to ensure spatial locality of the decomposition in a new optimization framework. The extracted dimensions often have an intuitive and clear interpretable meaning. Our method optionally accepts user-constraints to guide the process of discovering the underlying latent deformation space. The capabilities of our efficient, versatile, and easy-to-implement method are extensively demonstrated on a variety of data sets and application contexts. We demonstrate its power for user friendly intuitive editing of captured mesh animations, such as faces, full body motion, cloth animations, and muscle deformations. We further show its benefit for statistical geometry processing and biomechanically meaningful animation editing. It is further shown qualitatively and quantitatively that our method outperforms other unsupervised decomposition methods and other animation parameterization approaches in the above use cases.
On-set performance capture of multiple actors with a stereo camera
Authors: Wu Chenglei , Stoll Carsten , Valgaerts Levi , Theobalt Christian
Published: November 2013

State-of-the-art marker-less performance capture algorithms reconstruct detailed human skeletal motion and space-time coherent surface geometry. Despite being a big improvement over marker-based motion capture methods, they are still rarely applied in practical VFX productions as they require ten or more cameras and a studio with controlled lighting or a green screen background. If one was able to capture performances directly on a general set using only the primary stereo camera used for principal photography, many possibilities would open up in virtual production and previsualization, the creation of virtual actors, and video editing during post-production. We describe a new algorithm which works towards this goal. It is able to track skeletal motion and detailed surface geometry of one or more actors from footage recorded with a stereo rig that is allowed to move. It succeeds in general sets with uncontrolled background and uncontrolled illumination, and scenes in which actors strike non-frontal poses. It is one of the first performance capture methods to exploit detailed BRDF information and scene illumination for accurate pose tracking and surface refinement in general scenes. It also relies on a new foreground segmentation approach that combines appearance, stereo, and pose tracking results to segment out actors from the background. Appearance, segmentation, and motion cues are combined in a new pose optimization framework that is robust under uncontrolled lighting, uncontrolled background and very sparse camera views.
A general and efficient method for finding cycles in 3D curve networks
Authors: Zhuang Yixin , Zou Ming , Carr Nathan , Ju Tao
Published: November 2013

Generating surfaces from 3D curve networks has been a longstanding problem in computer graphics. Recent attention to this area has resurfaced as a result of new sketch based modeling systems. In this work we present a new algorithm for finding cycles that bound surface patches. Unlike prior art in this area, the output of our technique is unrestricted, generating both manifold and non-manifold geometry with arbitrary genus. The novel insight behind our method is to formulate our problem as finding local mappings at the vertices and curves of our network, where each mapping describes how incident curves are grouped into cycles. This approach lends us the efficiency necessary to present our system in an interactive design modeler, whereby the user can adjust patch constraints and change the manifold properties of curves while the system automatically re-optimizes the solution.
Coded time of flight cameras
Authors: Kadambi Achuta , Whyte Refael , Bhandari Ayush , Streeter Lee , Barsi Christopher , Dorrington Adrian , Raskar Ramesh
Published: November 2013

Time of flight cameras produce real-time range maps at a relatively low cost using continuous wave amplitude modulation and demodulation. However, they are geared to measure range (or phase) for a single reflected bounce of light and suffer from systematic errors due to multipath interference.

We re-purpose the conventional time of flight device for a new goal: to recover per-pixel sparse time profiles expressed as a sequence of impulses. With this modification, we show that we can not only address multipath interference but also enable new applications such as recovering depth of near-transparent surfaces, looking through diffusers and creating time-profile movies of sweeping light.

Our key idea is to formulate the forward amplitude modulated light propagation as a convolution with custom codes, record samples by introducing a simple sequence of electronic time delays, and perform sparse deconvolution to recover sequences of Diracs that correspond to multipath returns. Applications to computer vision include ranging of near-transparent objects and subsurface imaging through diffusers. Our low cost prototype may lead to new insights regarding forward and inverse problems in light transport.
Robust detection of semi-structured web records using a DOM structure-knowledge-driven model
Authors: Bing Lidong , Lam Wai , Wong Tak-Lam
Published: November 2013

Web data record extraction aims at extracting a set of similar object records from a single webpage. These records have similar attributes or fields and are presented with a regular format in a coherent region of the page. To tackle this problem, most existing works analyze the DOM tree of an input page. One major limitation of these methods is that the lack of a global view in detecting data records from an input page results in a myopic decision. Their brute-force searching manner in detecting various types of records degrades the flexibility and robustness. We propose a Structure-Knowledge-Oriented Global Analysis (Skoga) framework which can perform robust detection of different-kinds of data records and record regions. The major component of the Skoga framework is a DOM structure-knowledge-driven detection model which can conduct a global analysis on the DOM structure to achieve effective detection. The DOM structure knowledge consists of background knowledge as well as statistical knowledge capturing different characteristics of data records and record regions, as exhibited in the DOM structure. The background knowledge encodes the semantics of labels indicating general constituents of data records and regions. The statistical knowledge is represented by some carefully designed features that capture different characteristics of a single node or a node group in the DOM. The feature weights are determined using a development dataset via a parameter estimation algorithm based on a structured output support vector machine. An optimization method based on the divide-and-conquer principle is developed making use of the DOM structure knowledge to quantitatively infer and recognize appropriate records and regions for a page. Extensive experiments have been conducted on four datasets. The experimental results demonstrate that our framework achieves higher accuracy compared with state-of-the-art methods.
The first killer app
Authors: Zynda Melissa Rodriguez
Published: November 2013

Timelines provides perspectives on HCI history, glancing back at a road that sometimes took unexpected branches and turns. History is not a dry list of events; it is about points of view and differing interpretations.
---Jonathan Grudin, Editor
Empowerment through community crime-prevention technologies
Authors: Erete Sheena Lewis
Published: November 2013

Community + Culture features practitioner perspectives on designing technologies for and with communities. We highlight compelling projects and provocative points of view that speak to both community technology practice and the interaction design field as a whole.

Christopher A. Le Dantec
A survey on service quality description
Authors: Kritikos Kyriakos , Pernici Barbara , Plebani Pierluigi , Cappiello Cinzia , Comuzzi Marco , Benrernou Salima , Brandic Ivona , Kertész Attila , Parkin Michael , Carro Manuel
Published: November 2013

Quality of service (QoS) can be a critical element for achieving the business goals of a service provider, for the acceptance of a service by the user, or for guaranteeing service characteristics in a composition of services, where a service is defined as either a software or a software-support (i.e., infrastructural) service which is available on any type of network or electronic channel. The goal of this article is to compare the approaches to QoS description in the literature, where several models and metamodels are included. consider a large spectrum of models and metamodels to describe service quality, ranging from ontological approaches to define quality measures, metrics, and dimensions, to metamodels enabling the specification of quality-based service requirements and capabilities as well as of SLAs (Service-Level Agreements) and SLA templates for service provisioning. Our survey is performed by inspecting the characteristics of the available approaches to reveal which are the consolidated ones and which are the ones specific to given aspects and to analyze where the need for further research and investigation lies. The approaches here illustrated have been selected based on a systematic review of conference proceedings and journals spanning various research areas in computer science and engineering, including: distributed, information, and telecommunication systems, networks and security, and service-oriented and grid computing.
Slice embedding solutions for distributed service architectures
Authors: Esposito Flavio , Matta Ibrahim , Ishakian Vatche
Published: November 2013

Network virtualization provides a novel approach to running multiple concurrent virtual networks over a common physical network infrastructure. From a research perspective, this enables the networking community to concurrently experiment with new Internet architectures and protocols. From a market perspective, on the other hand, this paradigm is appealing as it enables infrastructure service providers to experiment with new business models that range from leasing virtual slices of their infrastructure to hosting multiple concurrent network services.

In this article, we present the slice embedding problem and recent developments in the area. A slice is a set of virtual instances spanning a set of physical resources. The embedding problem consists of three main tasks: (1) resource discovery, which involves monitoring the state of the physical resources, (2) virtual network mapping, which involves matching users' requests with the available resources, and (3) allocation, which involves assigning the resources that match the users' requests.

We also outline how these three tasks are tightly coupled, and how there exists a wide spectrum of solutions that either solve a particular task or jointly solve multiple tasks along with the interactions among them. To dissect the space of solutions, we introduce three main classification criteria, namely: (1) the type of constraints imposed by the user, (2) the type of dynamics considered in the embedding process, and (3) the allocation strategy adopted. Finally, we conclude with a few interesting research directions.
Methods for fault tolerance in networks-on-chip
Authors: Radetzki Martin , Feng Chaochao , Zhao Xueqian , Jantsch Axel
Published: November 2013

Networks-on-Chip constitute the interconnection architecture of future, massively parallel multiprocessors that assemble hundreds to thousands of processing cores on a single chip. Their integration is enabled by ongoing miniaturization of chip manufacturing technologies following Moore's Law. It comes with the downside of the circuit elements' increased susceptibility to failure. Research on fault-tolerant Networks-on-Chip tries to mitigate partial failure and its effect on network performance and reliability by exploiting various forms of redundancy at the suitable network layers. The article at hand reviews the failure mechanisms, fault models, diagnosis techniques, and fault-tolerance methods in on-chip networks, and surveys and summarizes the research of the last ten years. It is structured along three communication layers: the data link, the network, and the transport layers. The most important results are summarized and open research problems and challenges are highlighted to guide future research on this topic.
Peer-to-peer architectures for massively multiplayer online games
Authors: Yahyavi Amir , Kemme Bettina
Published: November 2013

Scalability, fast response time, and low cost are of utmost importance in designing a successful massively multiplayer online game. The underlying architecture plays an important role in meeting these conditions. Peer-to-peer architectures, due to their distributed and collaborative nature, have low infrastructure costs and can achieve high scalability. They can also achieve fast response times by creating direct connections between players. However, these architectures face many challenges. Distributing a game among peers makes maintaining control over the game more complex. Peer-to-peer architectures also tend to be vulnerable to churn and cheating. Moreover, different genres of games have different requirements that should be met by the underlying architecture, rendering the task of designing a general-purpose architecture harder. Many peer-to-peer gaming solutions have been proposed that utilize a range of techniques while using somewhat different and confusing terminologies. This article presents a comprehensive overview of current peer-to-peer solutions for massively multiplayer games using a uniform terminology.
Data stream clustering
Authors: Silva Jonathan A. , Faria Elaine R. , Barros Rodrigo C. , Hruschka Eduardo R. , Carvalho André C. P. L. F. de , Gama João
Published: November 2013

Data stream mining is an active research area that has recently emerged to discover knowledge from large amounts of continuously generated data. In this context, several data stream clustering algorithms have been proposed to perform unsupervised learning. Nevertheless, data stream clustering imposes several challenges to be addressed, such as dealing with nonstationary, unbounded data that arrive in an online fashion. The intrinsic nature of stream data requires the development of algorithms capable of performing fast and incremental processing of data objects, suitably addressing time and memory limitations. In this article, we present a survey of data stream clustering algorithms, providing a thorough discussion of the main design components of state-of-the-art algorithms. In addition, this work addresses the temporal aspects involved in data stream clustering, and presents an overview of the usually employed experimental methodologies. A number of references are provided that describe applications of data stream clustering in different domains, such as network intrusion detection, sensor networks, and stock market analysis. Information regarding software packages and data repositories are also available for helping researchers and practitioners. Finally, some important issues and open questions that can be subject of future research are discussed.
LiveAction
Authors: Amershi Saleema , Mahmud Jalal , Nichols Jeffrey , Lau Tessa , Ruiz German Attanasio
Published: November 2013

Task automation systems promise to increase human productivity by assisting us with our mundane and difficult tasks. These systems often rely on people to (1)
identify the tasks
they want automated and (2)
specify the procedural steps
necessary to accomplish those tasks (i.e., to create task models). However, our interviews with users of a Web task automation system reveal that people find it difficult to identify tasks to automate and most do not even believe they perform repetitive tasks worthy of automation. Furthermore, even when automatable tasks are identified, the well-recognized difficulties of specifying task steps often prevent people from taking advantage of these automation systems.

In this research, we analyze real Web usage data and find that people do in fact repeat behaviors on the Web and that automating these behaviors, regardless of their complexity, would reduce the overall number of actions people need to perform when completing their tasks, potentially saving time. Motivated by these findings, we developed LiveAction, a fully-automated approach to generating task models from Web usage data. LiveAction models can be used to populate the task model repositories required by many automation systems, helping us take advantage of automation in our everyday lives.
Characterizing and Predicting the Multifaceted Nature of Quality in Educational Web Resources
Authors: Wetzler Philipp , Bethard Steven , Leary Heather , Butcher Kirsten , Bahreini Soheil Danesh , Zhao Jin , Martin James H. , Sumner Tamara
Published: November 2013

Efficient learning from Web resources can depend on accurately assessing the quality of each resource. We present a methodology for developing computational models of quality that can assist users in assessing Web resources. The methodology consists of four steps: 1) a meta-analysis of previous studies to decompose quality into high-level dimensions and low-level indicators, 2) an expert study to identify the key low-level indicators of quality in the target domain, 3) human annotation to provide a collection of example resources where the presence or absence of quality indicators has been tagged, and 4) training of a machine learning model to predict quality indicators based on content and link features of Web resources. We find that quality is a multifaceted construct, with different aspects that may be important to different users at different times. We show that machine learning models can predict this multifaceted nature of quality, both in the context of aiding curators as they evaluate resources submitted to digital libraries, and in the context of aiding teachers as they develop online educational resources. Finally, we demonstrate how computational models of quality can be provided as a service, and embedded into applications such as Web search.
Too Big to Fail: Causes, Consequences, and Policy Responses
Authors: Strahan Philip E.
Published: November 2013

Governments cannot credibly commit to eschew bailouts of creditors when large financial institutions become distressed. This too-big-to-fail (TBTF) problem distorts how markets price securities issued by TBTF firms, thus encouraging them to borrow too much and take too much risk. TBTF also encourages financial firms to grow, leading to competitive inequity and potential misallocation of credit. This review discusses evidence that such distortions are empirically relevant and also discusses the policy efforts to limit them. In the wake of the Financial Crisis of 2007–2008, it seems increased concentration in the financial industry has worsened the TBTF problem. Nevertheless, markets price the risks of large financial firms more now than before the Financial Crisis.
Persistence and Nonpersistence of a Food Chain Model with Stochastic Perturbation
Authors: Li Haihong , Cong Fuzhong , Jiang Daqing , Hua Hongtu
Published: November 2013

We analyze a three species predator-prey chain model with stochastic perturbation. First, we show that this system has a unique positive solution and itspth moment is bounded. Then, we deduce conditions that the system is persistent in time average. After that, conditions for the system going to be extinction in probability are established. At last, numerical simulations are carried out to support our results.
Grape Seed Proanthocyanidin Rescues Rats from Steatosis: A Comparative and Combination Study with Metformin
Authors: Yogalakshmi Baskaran , Sreeja S , Geetha Rajagopalan , Radika Mutlur Krishnamoorthy , Anuradha Carani Venkatraman
Published: November 2013

Nonalcoholic fatty liver disease (NAFLD), a premorbid condition, lacks proper management owing to multitude of abnormalities. In this study, we compared the effects of a potent antioxidant, grape seed proanthocyanidins (GSP), and an insulin sensitizer, metformin (MET), in high-fat-fructose-diet- (HFFD-) induced albino Wistar rat model of NAFLD. Either GSP (100 mg/Kg b.w) or MET (50 mg/Kg b.w) or both were administered as therapeutic options. HFFD-fed rats showed abnormal plasma lipid profile, inflammation, and steatosis of the liver when examined by biochemical and histology techniques. Increased lipid storage, lipogenesis, and reduced lipolysis were evident from mRNA expression studies of hepatic lipid droplets (LD) proteins, sterol regulatory element binding 1c (SREBP 1c), and peroxisome proliferator activated receptor-α(PPAR-α). GSP administration to HFFD-fed rats caused 69% reduction in hepatic TG levels, whereas MET caused only 23%. The combination treatment reduced TG levels by 63%. GSP reduced the mRNA expression of SREBP1c and LD proteins and increased that of PPAR-αmore effectively compared to MET in HFFD-induced hyperlipidemic rats. Combination of MET and GSP improved the metabolism of lipids effectively, but the effect was not additive in restoring lipid levels.
Alkyne‐Azide Cycloaddition Catalyzed by Silver Chloride and “Abnormal” Silver N‐Heterocyclic Carbene Complex
Authors: Ortega-Arizmendi Aldo I. , Aldeco-Pérez Eugenia , Cuevas-Yañez Erick
Published: November 2013

A library of 1,2,3‐triazoles was synthesized from diverse alkynes and azides using catalytic amounts of silver chloride instead of copper compounds. In addition, a novel “abnormal” silver N‐heterocyclic carbene complex was tested as catalyst in this process. The results suggest that the reaction requires only 0.5% of silver complex, affording 1,2,3‐triazoles in good yields.
A New Approach for Wage Management System Using Fuzzy Brackets in Industry
Authors: Eraslan Ergün , Atalay Kumru Didem
Published: November 2013

Job evaluation is used to determine the relative importance of each job in a company in order to structure an accurate wage management system. Job evaluation can be also defined as a multicriteria decision-making problem. However, according to the diversity of managers’ assessment, the evaluation processes are often resulting in pay inequity. This outcome can be circumvented by utilizing a fuzzy job evaluation system. In this study, one of the more robust multicriteria decision-making methods, Fuzzy Analytic Hierarchy Process (FAHP), is performed in job evaluation system in order to rank predetermined 13 criteria. The fuzzy wage brackets are developed and inserted into the process which is obtained from the results of mathematical model to designate the bounds for predefined 86 jobs. Eventually an accurate payment system is proposed for a company in steel industry by using Fuzzy Regression Analysis (FRA).
Intravenous Paracetamol Reduces Postoperative Opioid Consumption after Orthopedic Surgery: A Systematic Review of Clinical Trials
Authors: Jebaraj Bright , Maitra Souvik , Baidya Dalim Kumar , Khanna Puneet
Published: November 2013

Postoperative pain management is one of the most challenging jobs in orthopedic surgical population as it comprises of patients from extremes of ages and with multiple comorbidities. Though effective, opioids may contribute to serious adverse effects particularly in old age patients. Intravenous paracetamol is widely used in the postoperative period with the hope that it may reduce opioid consumption and produce better pain relief. A brief review of human clinical trials where intravenous paracetamol was compared with placebo or no treatment in postoperative period in orthopedic surgical population has been done here. We found that four clinical trials reported that there is a significant reduction in postoperative opioid consumption. When patients received an IV injection of 2 g propacetamol, reduction of morphine consumption up to 46% has been reported. However, one study did not find any reduction of opioid requirement after spinal surgery in children and adolescent. Four clinical trials reported better pain scores when paracetamol has been used, but other three trials denied. We conclude that postoperative intravenous paracetamol is a safe and effective adjunct to opioid after orthopedic surgery, but at present there is no data to decide whether paracetamol reduces opioid related adverse effects or not.
Liver Transplant Tolerance and Its Application to the Clinic: Can We Exploit the High Dose Effect?
Authors: Cunningham Eithne C. , Sharland Alexandra F. , Bishop G. Alex
Published: November 2013

The tolerogenic properties of the liver have long been recognised, especially in regard to transplantation. Spontaneous acceptance of liver grafts occurs in a number of experimental models and also in a proportion of clinical transplant recipients. Liver graft acceptance results from donor antigen-specific tolerance, demonstrated by the extension of tolerance to other grafts of donor origin. A number of factors have been proposed to be involved in liver transplant tolerance induction, including the release of soluble major histocompatibility (MHC) molecules from the liver, its complement of immunosuppressive donor leucocytes, and the ability of hepatocytes to directly interact with and destroy antigen-specific T cells. The large tissue mass of the liver has also been suggested to act as a cytokine sink, with the potential to exhaust the immune response. In this review, we outline the growing body of evidence, from experimental models and clinical transplantation, which supports a role for large tissue mass and high antigen dose in the induction of tolerance. We also discuss a novel gene therapy approach to exploit this dose effect and induce antigen-specific tolerance robust enough to overcome a primed T cell memory response.
The Reaction of Cyclopentanone with Cyanomethylene Reagents: Novel Synthesis of Pyrazole, Thiophene, and Pyridazine Derivatives
Authors: Wardakhan Wagnat W. , Samir Eman M.
Published: November 2013

The reaction of cyclopentanone with either malononitrile or ethyl cyanoacetate gave the corresponding condensated products. The latter underwent some heterocyclic reactions to give new pyrazole, thiophene, and pyridazine derivatives. The antitumor evaluation of the newly synthesized products against the three cancer cells, namely, breast adenocarcinoma (MCF‐7), nonsmall cell lung cancer (NCI‐H460), and CNS cancer (SF‐268) showed that some of them have high inhibitory effect towards three cell lines which is higher than the standard.
Analysis of Weighted Multifrequency MUSIC-Type Algorithm for Imaging of Arc-Like, Perfectly Conducting Cracks
Authors: Joh Young-Deuk
Published: November 2013

The main purpose of this paper is to investigate the structure of the weighted multifrequency multiple signal classification (MUSIC) type imaging function in order to improve the traditional MUSIC-type imaging. For this purpose, we devise a weighted multifrequency MUSIC-type imaging function and examine a relationship between weighted multifrequency MUSIC-type function and Bessel functions of integer order of the first kind. Some numerical results are demonstrated to support the survey.
Stability Analysis of Numerical Methods for a 1.5-Layer Shallow-Water Ocean Model
Authors: Zou Guang-an , Wang Bo , Mu Mu
Published: November 2013

A 1.5-layer reduced-gravity shallow-water ocean model in spherical coordinates is described and discretized in a staggered grid (standard Arakawa C-grid) with the forward-time central-space (FTCS) method and the Leap-frog finite difference scheme. The discrete Fourier analysis method combined with the Gershgorin circle theorem is used to study the stability of these two finite difference numerical models. A series of necessary conditions of selection criteria for the time-space step sizes and model parameters are obtained. It is showed that these stability conditions are more accurate than the Courant-Friedrichs-Lewy (CFL) condition and other two criterions (Blumberg and Mellor, 1987; Casulli, 1990, 1992). Numerical experiments are proposed to test our stability results, and numerical model that is designed is also used to simulate the ocean current.
Recycle HPLC: A Powerful Tool for the Purification of Natural Products
Authors: Sidana Jasmeen , Joshi Lokesh Kumar
Published: November 2013

Natural compounds occur as various isomeric or closely related structures in biological matrices. These compounds are difficult to separate from the complex mixtures, and hence, the need for effective and innovative separation techniques arises. Recycle HPLC allows the recycling of sample, in part or full, and increases the separation efficiency of the process while keeping the peak dispersion to a minimum. Recycling in an HPLC system has been used in the isolation and purification of different types of natural products including enantiomers, diastereomers, epimers, positional isomers, and structurally related or unrelated compounds having similar retention characteristics. The present paper overviews the development of instrumentation and setup of recycle HPLC and its applications in the separation of natural products.
Mayor Erythropoietic Response after Deferasirox Treatment in a Transfusion-Dependent Anemic Patient with Primary Myelofibrosis
Authors: Lisette Del Corso , Enrico Balleari , Eleonora Arboscello , Riccardo Ghio , Manlio Mencoboni , Omar Racchi
Published: November 2013

Primary myelofibrosis (PMF) is a myeloproliferative neoplasm frequently complicated by transfusion dependent anemia. Both anemia and transfusion-dependence are associated with a poor outcome, at least in part because of toxic effects of iron overload (IOL). Iron-chelating therapy (ICT) is increasingly used in order to prevent IOL in this setting. Here, we describe the case of a 73-year-old man affected by PMF and severe transfusion-dependent anemia who experienced a dramatic erythroid response after being treated with deferasirox to prevent IOL.
An Adaptive UKF Based SLAM Method for Unmanned Underwater Vehicle
Authors: Wang Hongjian , Fu Guixia , Li Juan , Yan Zheping , Bian Xinqian
Published: November 2013

This work proposes an improved unscented Kalman filter (UKF)-based simultaneous localization and mapping (SLAM) algorithm based on an adaptive unscented Kalman filter (AUKF) with a noise statistic estimator. The algorithm solves the issue that conventional UKF-SLAM algorithms have declining accuracy, with divergence occurring when the prior noise statistic is unknown and time-varying. The new SLAM algorithm performs an online estimation of the statistical parameters of unknown system noise by introducing a modified Sage-Husa noise statistic estimator. The algorithm also judges whether the filter is divergent and restrains potential filtering divergence using a covariance matching method. This approach reduces state estimation error, effectively improving navigation accuracy of the SLAM system. A line feature extraction is implemented through a Hough transform based on the ranging sonar model. Test results based on unmanned underwater vehicle (UUV) sea trial data indicate that the proposed AUKF-SLAM algorithm is valid and feasible and provides better accuracy than the standard UKF-SLAM system.
A GPU-Based Parallel Procedure for Nonlinear Analysis of Complex Structures Using a Coupled FEM/DEM Approach
Authors: Wang Lixiang , Li Shihai , Zhang Guoxin , Ma Zhaosong , Zhang Lei
Published: November 2013

This study reports the GPU parallelization of complex three-dimensional software for nonlinear analysis of concrete structures. It focuses on coupled thermomechanical analysis of complex structures. A coupled FEM/DEM approach (CDEM) is given from a fundamental theoretical viewpoint. As the modeling of a large structure by means of FEM/DEM may lead to prohibitive computation times, a parallelization strategy is required. With the substantial development of computer science, a GPU-based parallel procedure is implemented. A comparative study between the GPU and CPU computation results is presented, and the runtimes and speedups are analyzed. The results show that dramatic performance improvements are gained from GPU parallelization.
Strongly Almost Lacunary -Convergent Sequences
Authors: Kılıçman Adem , Borgohain Stuti
Published: November 2013

We study some new strongly almost lacunary -convergent generalized difference sequence spaces defined by an Orlicz function. We give also some inclusion relations related to these sequence spaces.
Adnexal Masses Treated Using a Combination of the SILS Port and Noncurved Straight Laparoscopic Instruments: Turkish Experience and Review of the Literature
Authors: Dursun Polat , Tezcaner Tugan , Zeyneloglu Hulusi B. , Alyazıcı Irem , Haberal Ali , Ayhan Ali
Published: November 2013

Objective. To report our experience treating adnexal masses using a combination of the SILS port and straight nonroticulating laparoscopic instruments.Study Design. This prospective feasibility study included 14 women with symptomatic and persistent adnexal masses. Removal of adnexal masses via single-incision laparoscopic surgery using a combination of the SILS port and straight nonroticulating laparoscopic instruments was performed.Results. All of the patients had symptomatic complex adnexal masses. Mean age of the patients was 38.4 years (range: 21–61 years) and mean duration of surgery was 71 min (range: 45–130 min). All surgeries were performed using nonroticulating straight laparoscopic instruments. Mean tumor diameter was 6 cm (range: 5–12 cm). All patient pathology reports were benign. None of the patients converted to laparotomy. All the patients were discharged on postoperative d1. Postoperatively, all the patients were satisfied with their incision and cosmetic results.Conclusion. All 14 patients were successfully treated using standard, straight nonroticulating laparoscopic instruments via the SILS port. This procedure can reduce the cost of treatment, which may eventually lead to more widespread use of the SILS port approach. Furthermore, concomitant surgical procedures are possible using this approach. However, properly designed comparative studies with single port and classic laparoscopic surgery are urgently needed.
Modeling and Backstepping Control of the Electronic Throttle System
Authors: Bai Rui , Tong Shaocheng , Karimi Hamid Reza
Published: November 2013

Electronic throttle is widely used in modern automotive engines. An electronic throttle system regulates the throttle plate angle by using a DC servo motor to adjust the inlet airflow rate of an internal combustion engine. Its application leads to improvements in vehicle drivability, fuel economy, and emissions. In this paper, by taking into account the dynamical behavior of the electronic throttle, the mechanism model is first built, and then the mechanism model is transformed into the state-space model. Based on the state-space model and using the backstepping design technique, a new backstepping controller is developed for the electronic throttle. The proposed controller can make the actual angle of the electronic throttle track its set point with the satisfactory performance. Finally, a computer simulation is performed, and simulation results verify that the proposed control system can achieve favorable tracking performance.
Identifying Vulnerable Nodes of Complex Networks in Cascading Failures Induced by Node-Based Attacks
Authors: Li Shudong , Li Lixiang , Jia Yan , Liu Xinran , Yang Yixian
Published: November 2013

In the research on network security, distinguishing the vulnerable components of networks is very important for protecting infrastructures systems. Here, we probe how to identify the vulnerable nodes of complex networks in cascading failures, which was ignored before. Concerned with random attack (RA) and highest load attack (HL) on nodes, we model cascading dynamics of complex networks. Then, we introduce four kinds of weighting methods to characterize the nodes of networks including Barabási-Albert scale-free networks (SF), Watts-Strogatz small-world networks (WS), Erdos-Renyi random networks (ER), and two real-world networks. The simulations show that, for SF networks under HL attack, the nodes with small value of the fourth kind of weight are the most vulnerable and the ones with small value of the third weight are also vulnerable. Also, the real-world autonomous system with power-law distribution verifies these findings. Moreover, for WS and ER networks under both RA and HL attack, when the nodes have low tolerant ability, the ones with small value of the fourth kind of weight are more vulnerable and also the ones with high degree are easier to break down. The results give us important theoretical basis for digging the potential safety loophole and making protection strategy.
Pd(II) and Zn(II) Based Complexes with Schiff Base Ligands: Synthesis, Characterization, Luminescence, and Antibacterial and Catalytic Activities
Authors: Feng Zhi-Qiang , Yang Xiao-Li , Ye Yuan-Feng
Published: November 2013

Two new metal complexes involving Schiff base ligands, namely, [Pd(L1)2] (1) and [Zn(L2)2] (2), [HL1: 2,4‐dibromo‐6‐((E)‐(mesitylimino)methyl)phenol and HL2: 2‐((E)‐(2,6‐diisopropylphenylimino)methyl)‐4,6‐dibromophenol], have been solvothermally synthesized and characterized by elemental analysis, IR‐spectroscopy, thermogravimetric analysis, powder X‐ray diffraction, and single‐crystal X‐ray diffraction. Both 1 and 2 are mononuclear cyclometalated complexes with square planar and tetrahedral coordination geometry, respectively. 1 and 2 display photoluminescence in the solid state at 298 K (fluorescence lifetimes τ = 5.521 μs at 508 nm for 1; τ = 3.697 μs at 506 nm for 2). These Schiff base ligands and their metal complexes have been screened for antibacterial activity against several bacteria strains, and the results are compared with the activity of penicillin. Moreover, the Suzuki reaction of 4‐bromoanisole with phenylboronic acid by 1 has also been studied.
A Novel Nonadditive Collaborative-Filtering Approach Using Multicriteria Ratings
Authors: Hu Yi-Chung
Published: November 2013

Although single-criterion recommender systems have been successfully used in several applications, multicriteria rating systems which allow users to specify ratings for various content attributes of individual items are gaining importance in recommendation context. An overall rating of an unrated item is often obtained by the weighted average method (WAM) when criterion weights are available. However, the assumption of additivity for the WAM is not always reasonable. For this reason, this paper presents a new collaborative-filtering approach using multicriteria ratings, in which a nonadditive technique in Multicriteria decision making (MCDM), namely, the Choquet integral, is used to aggregate multicriteria ratings for unrated items. Subsequently, the system can recommend items with higher overall ratings for each user. The degrees of importance of the respective criteria are determined by a genetic algorithm. In contrast to the additive weighted average aggregation, the Choquet integral does not ignore the interaction among criteria. The applicability of the proposed approach to the recommendation of the initiators on a group-buying website is examined. Experimental results demonstrate that the generalization ability of the proposed approach performs well compared with other similarity-based collaborative-filtering approaches using multicriteria ratings.