Miracle-dz/UniFAR-FTUs huggingface dataset:
Contour-Shape Recognition and Retrieval Based on Chain Code

The direction chain code has been widely used in image coding and recognition for its simplicity and low storage requirement. However, the researches on how to use chain code for shape retrieval are few. The traditional retrieval methods, chain code histogram (CCH) and Minimize Sum Statistical Direction Code (MSSDC) did not take the distribution feature into consideration. In our previous work, three novel descriptors, chain code distribution vector (CCDV), chain code relativity entropy (CCRE), chain code spatial distribution entropy (CCSDE) are discussed which take full advantage of the statistical feature and the distribution, spatial and relativity feature. In this paper, we compared the five algorithms on a large set of shape database. The experimental results denote the efficiency of each method.
Microarray analysis of corneal fibroblast gene expression after interleukin-1 treatment.

PURPOSE To identify changes in gene expression in human corneal fibroblasts after exposure to interleukin-1alpha. METHODS RNA was isolated from cultured human corneal fibroblasts after treatment with interleukin-1alpha and subjected to DNA microarray analysis. Changes in gene expression were determined by comparison with untreated cells in three independent experiments after a Bayesian statistical analysis of variance. RESULTS Changes in gene expression were reproducibly observed in 165 genes representing previously identified and novel chemokines, matrix molecules, membrane receptors, angiogenic mediators, and transcription factors that correlated with pathophysiological responses to inflammation. Dramatic increases in gene expression were observed with exodus-1 (CCL20), MMP-12, and RhoA. CONCLUSIONS DNA microarray analysis of the corneal fibroblast response to interleukin-1alpha provides important insight into modeling changes in gene expression and suggests novel therapeutic targets for the control of corneal inflammation.
Tuning the Magnetic Properties of Nanoparticles

The tremendous interest in magnetic nanoparticles (MNPs) is reflected in published research that ranges from novel methods of synthesis of unique nanoparticle shapes and composite structures to a large number of MNP characterization techniques, and finally to their use in many biomedical and nanotechnology-based applications. The knowledge gained from this vast body of research can be made more useful if we organize the associated results to correlate key magnetic properties with the parameters that influence them. Tuning these properties of MNPs will allow us to tailor nanoparticles for specific applications, thus increasing their effectiveness. The complex magnetic behavior exhibited by MNPs is governed by many factors; these factors can either improve or adversely affect the desired magnetic properties. In this report, we have outlined a matrix of parameters that can be varied to tune the magnetic properties of nanoparticles. For practical utility, this review focuses on the effect of size, shape, composition, and shell-core structure on saturation magnetization, coercivity, blocking temperature, and relaxation time.
A Multi-agent Based Load Balancing Framework in Cloud Environment

Cloud computing is a commercial application of distributed system. With the rapid development of cloud computing, resource management problem has been widely studied and discussed. Most of the existing researches concern resource allocation by launching virtual machines, however, instant monitoring of the hosts, load balancing of the cloud platform is much more important for cloud providers. In this paper, a multi-Agent based distributed load balancing framework is proposed for cloud platform, it uses workload prediction technology and threshold buffering strategies to reduce the migration of VMs. Experiments show that our method can significantly reduce the workload data transmission and solve the frequent migration problem, which can effectively achieve load balancing, promote the utilization of the entire data center resources.
Experimental analysis of dynamic all pairs shortest path algorithms

We present the results of an extensive computational study on dynamic algorithms for all pairs shortest path problems. We describe our implementations of the recent dynamic algorithms of King [18] and of Demetrescu and Italiano [7], and compare them to the dynamic algorithm of Ramalingam and Reps [25] and to static algorithms on random, real-world and hard instances. Our experimental data suggest that some of the dynamic algorithms and their algorithmic techniques can be really of practical value in many situations.
The mechanics of collaboration: developing low cost usability evaluation methods for shared workspaces

We introduce a conceptual framework that articulates the mechanics of collaboration for shared-workspace groupware: the low level actions and interactions that must be carried out to complete a task in a shared manner. These include communication, coordination, planning, monitoring, assistance, and protection. The framework also includes three general measures of these mechanics: effectiveness, efficiency, and satisfaction. The underlying idea of the framework is that some usability problems in groupware systems are not inherently tied to the social context in which the system is used but rather are a result of poor support for the basic activities of collaborative work in shared spaces. We believe that existing low-cost evaluation methods-heuristic evaluation, walkthroughs, user observations and questionnaires-can be modified to include this framework in a way that helps a groupware evaluator uncover these usability problems.
FIASCO: game interface for location-based play

In this paper we describe FIASCO, a location based street game that is played both on a website and on the city streets. In the current technology landscape, data is readily accessed via an array of devices and across a variety of locations. There are many resulting design opportunities, but location based computing poses challenges. With FIASCO, the authors propose game design as a research tool to explore new approaches to computing in public space. Engaging with place, promoting self expression through physical action, and reinterpreting mapping conventions are the driving goals towards an understanding of 'situated computing. ' In using a pervasive gaming model FIASCO creates a support mechanism for these exploratory activities, while bringing the challenges inherent to designing for online/offline experience to the forefront.
Role of growth factors and cytokines in hepatic regeneration

During liver regeneration quiescent hepatocytes undergo one or two rounds of replication and then return to a nonproliferative state. Growth factors regulate this process by providing both stimulatory and inhibitory signals for cell proliferation. EGF, TGFα, and HGF stimidate DNA synthesis in hepatocytes in vivo and in culture but the sensitivity of cidtured hepatocytes to the mitogenic effects of these factors is much higher than that of quiescent hepatocytes in intact livers. We have proposed that after partial hepatectomy, hepatocytes enter a state of replicative competence (“priming”) before they can fully respond to growth factors. The priming step is an initiating event in liver regeneration that involves the activation and DNA binding of NF‐κB and other transcription factors, which could be induced by TNF or other cytokines. EGF, TGFα, and HGF have major effects on liver growth. TGFα expression correlates with hepatocyte DNA synthesis during liver development and growth and the constitutive expression of the factor confers proliferative activity to adult hepatocytes in vivo and in culture. The data indicate that the activity of stimulatory and inhibitory growth factors such as TGFβl and activin is low in normal livers but that the expression of both types of factors increase during liver regeneration. —Fausto, N. , Laird, A. D. , Webber, E. M. Role of growth factors and cytokines in hepatic regeneration. FASEB J. 9, 1527‐1536 (1995)
A model of process documentation to determine provenance in mash-ups

Through technologies such as RSS (Really Simple Syndication), Web Services, and AJAX (Asynchronous JavaScript and XML), the Internet has facilitated the emergence of applications that are composed from a variety of services and data sources. Through tools such as Yahoo Pipes, these “mash-ups” can be composed in a dynamic, just-in-time manner from components provided by multiple institutions (i.e., Google, Amazon, your neighbor). However, when using these applications, it is not apparent where data comes from or how it is processed. Thus, to inspire trust and confidence in mash-ups, it is critical to be able to analyze their processes after the fact. These trailing analyses, in particular the determination of the provenance of a result (i.e., the process that led to it), are enabled by process documentation, which is documentation of an application's past process created by the components of that application at execution time. In this article, we define a generic conceptual data model that supports the autonomous creation of attributable, factual process documentation for dynamic multi-institutional applications. The data model is instantiated using two Internet formats, OWL and XML, and is evaluated with respect to questions about the provenance of results generated by a complex bioinformatics mash-up.
An unsupervised approach to automatic object extraction from a maritime video scene

In this paper, an efficient unsupervised approach for extracting objects from maritime background using solely still video images is proposed. Its main idea is that maritime background (sea) has the main particularity of absorbing only hot light frequencies (red and green), while an object has not this property. Therefore if a timely vector of class features is considered, then two distinct statistical classes can be easily obtained in one maritime image, using an appropriate unsupervised two-class classification algorithm, and thus one can efficiently extract object from background. This is achieved by firstly partitioning a maritime image into equally-sized blocks, and constructing a 13-dimensional block-wise feature vector (regardless of block size) based on some observed statistics of light absorption in a block. The latter capture at the same time the characteristics (higher-order geometric moments) of the Fourier spectrum of RGB intensities in an image block, and its Shannon entropies. Both types of RGB information allow together generally to characterize well background versus object regions. Furthermore, a mere statistical test makes it possible to detect situations where there is no object in a maritime video scene but only sea. We have tested the proposed approach using several maritime scene videos and it has shown good performances in terms of detection accuracy, robustness and computational time.
Please Scroll down for Article Applied Economics Letters Analysing the C-minus-age Strategy for Life-cycle Investing

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Energy Efficient Hierarchical Routing Protocol (EEHRP) for Wireless Sensor Network

Wireless sensor network consisting of various tiny wireless sensor nodes that are equipped with transmission devices that require some amount of energy to transmit the data to other node(s). Most often the battery of sensor nodes cannot be charged or changed during transmission. To preserve the longetivity of the network it is very challenging task to build a sensor node that require very little amount of energy for data transmission. Lifetime of wireless sensor network is directly proportional to the energy source of wireless sensor node. It is proved that 70% of energy consumption is caused during data transmission process [1]. In order to maximize the network lifetime we need to optimize data transmission process. An energy efficient routing algorithm may result in better network lifetime. This is the reason why routing techniques in wireless sensor network focus mainly on the accomplishment of power conservation. Most of the recent researches have shown various algorithms mainly designed to minimize energy consumption in sensor networks. Each routing mechanism has its advantages and disadvantages over energy efficiency. There is no single, best routing protocol that is suitable for all applications. Routing mechanism might differ depending on the application, network architecture and topologies. Routing algorithms/techniques have been classified in a number of ways by various researchers. There is no general classification is available till today. Some researchers [2, 3, 4, and 5] have classified routing algorithms into three broad categories Datacentric Routing Protocols, Hierarchical Routing Protocols and Location-based Routing Protocols. In this Paper an energy efficient hierarchical routing algorithm is being proposed. Using simulation a basic idea is also given in this paper that shows how hierarchical routing mechanism is better than non hierarchical mechanism.
A Systematic Literature Review of the Factors of Influence on the Environmental Impact of ICT

Context: Many publications have described, measured, tracked or assessed Information and Communication Technology (ICT) activities that impact the environment. A complete conceptual view of the environmental impact of ICT can be described in three orders of effect: Direct, indirect and systemic. Objective: The goal of this study is to find out how the existing literature contributes towards our understanding of the environmental impact of ICT. We approach this question by identifying factors that can be of influence on the environmental impact and map these factors onto a conceptual framework of Green ICT. Method: We used a systematic literature review to collect factors of influence regarding the environmental impact of ICT. Results: From the data we collected and the analyses made, we created a taxonomy, and report on the frequencies of the factors of influence in the primary studies as well as gaps and additions compared to the conceptual framework. We found five main classes of influence that can form a continuous cycle, but noted that the research field is strongly focused on the direct impact of ICT. Conclusion: Our study contributes towards a better understanding of the environmental impact of ICT by framing factors of influence in a conceptual framework. The taxonomy we create and the analysis of the studies could be helpful in defining a research agenda, to further enable the full potential of Green ICT. In addition, the taxonomy can be used as a starting point for a practical tool, for organizations that wish to apply Green ICT to its full extent.
Characterizing verification of bug fixes in two open source IDEs

Data from bug repositories have been used to enable inquiries about software product and process quality. Unfortunately, such repositories often contain inaccurate, inconsistent, or missing data, which can originate misleading results. In this paper, we investigate how well data from bug repositories support the discovery of details about the software verification process in two open source projects, Eclipse and NetBeans. We have been able do identify quality assurance teams in NetBeans and to detect a well-defined verification phase in Eclipse. A major challenge, however, was to identify the verification techniques used in the projects. Moreover, we found cases in which a large batch of bug fixes is simultaneously reported to be verified, although no software verification was actually done. Such mass verifications, if not acknowledged, threatens analyses that rely on information about software verification reported on bug repositories. Therefore, we recommend that the exploratory analyses presented in this paper precede inferences based on reported verifications.
MET as a potential therapeutic target for the treatment of upper gastrointestinal cancers: characterization of novel c-Met inhibitors for therapeutic intervention

The receptor tyrosine kinase mesenchymal-epithelial transition factor (c-Met) plays a pivotal role in regulation of cell proliferation and migration. Abnormal expression of c-Met has been associated with poor prognosis in several cancer types, including upper gastrointestinal malignancies. Moreover, c-Met interaction with multiple signalling pathways involved in tumor growth and invasive/metastatic phenotype has gained substantial attention in the last few years, suggesting the therapeutic potential of this target. This has led to the development and evaluation of a number of c-Met inhibitors. Here we describe the critical role of the HGF/c-Met pathway in cancer, as well as the preclinical and clinical investigations on c-Met inhibitors in solid tumors, with particular emphasis on recent findings with small-molecule inhibitors in gastrointestinal cancers. Clinical trials with several of these novel inhibitors have been encouraging and one of them, crizotinib (dual c-Met/ALK inhibitor), has recently been approved for lung cancers with ALKrearrangement. There are accumulating evidences on the therapeutic potential of this and other c-Met inhibitors for the treatment of other malignancies, such as gastric and pancreatic cancers. These inhibitors might be used in combination with chemotherapy as well as with other biological agents, in order to overcome different resistance mechanisms. However, further studies are needed to identify determinants of the activity of c-Met inhibitors, through the analysis of genetic and environmental alterations affecting c-Met and parallel pro-cancer pathways. These studies will be critical to improve the efficacy and selectivity of current and future anticancer strategies targeting c-Met.
A distance for elastic matching in object recognition

We define distances between geometric curves by the square root of the minimal energy required to transform one curve into the other. The energy is formally defined from a left invariant Riemannian distance on an infinite dimensional group acting on the curves, which can be explicitly computed. The obtained distance boils down to a variational problem for which an optimal matching between the curves has be computed. An analysis of the distance when the curves are polygonal leads to a numerical procedure for the solution of the variational problem, which can efficiently be implemented, as illustrated by experiments.
Improved Clinical Outcomes of High Risk β Thalassemia Major Patients Undergoing a HLA Matched Related Allogeneic Stem Cell Transplant with a Treosulfan Based Conditioning Regimen and Peripheral Blood Stem Cell Grafts

Improving clinical outcomes among high risk Class III β thalassemia major patients (Class IIIHR) receiving an allogeneic SCT remains a challenge. From October, 2009 a treosulfan based regimen (TreoFluT) was used for all consecutive Class III patients (n = 50). The clinical outcomes were compared with the historical conventional busulfan (BuCy) based regimen (n = 139). Use of TreoFluT was associated with a significantly reduced incidence of sinusoidal obstruction syndrome (SOS) among Class IIIHR cases (78% to 30%; P = 0.000) and early TRM (46% to 13%; p = 0.005). There was also a trend towards better engraftment in the Class IIIHR subset (P = 0.055). However, the use of bone marrow (BM) as source of stem cells along with the TreoFluT regimen was associated with 50% early mixed chimerism which reduced to 8.5% with the use of a peripheral blood stem cell graft (PBSC). Use of a PBSC graft was not associated with a significant increase in the incidence of acute or chronic graft versus host disease (GVHD). The overall and event free survival was significantly better among the Class IIIHR subset with the use of TreoFluT Vs. BuCy (86.6±7.3 Vs. 39.4±6.8%; P = 0.002 and 77.8±8.8 Vs. 32.4±6.5%; P = 0.003 respectively). A TreoFluT conditioning regimen with a PBSC graft can significantly improve clinical outcomes of Class IIIHR patients.
A personalized recommendation method using item domain features to estimate the vacancies of user-item rating matrix

Collaborative filtering (CF) is a widely used personalized recommendation method. However, its performance is often limited by sparsity problem. Some researchers capitalize dimensionality reduction to alleviate this problem, but dimensionality reduction might lose potentially useful information. Although some others fill the vacant ratings by specific technologies to alleviate the sparsity, they never exploit potentially useful information between items to fill the vacancies. In this paper, we introduce a method that utilizes item domain features to estimate the vacant ratings of user-item rating matrix rather than specific technologies, and combines CF to make personalized recommendation. This method not only alleviates the sparsity of CF, but also integrates domain characteristics with a personalized recommendation system. We compare the proposed method with existing methods and find our method gets better performance than other methods.
Polymorphonuclear neutrophils deliver activation signals and antigenic molecules to dendritic cells: a new link between leukocytes upstream of T lymphocytes

Polymorphonuclear neutrophils (PMNs) are rapidly recruited to tissues upon injury or infection. There, they can encounter local and/or recruited immature dendritic cells (iDCs), a colocalization that could promote at least transient interactions and mutually influence the two leukocyte populations. Using human live blood PMNs and monocyte‐derived iDCs, we examined if these leukocytes actually interacted and whether this influenced DC function. Indeed, coculture with live but not apoptotic PMNs led to up‐regulation of membrane CD40, CD86, and human leukocyte antigen (HLA)‐DR on DCs. Whereas CD40 up‐regulation was dependent on soluble factors released by PMNs, as determined in cultures conducted in different chambers, cell contact was necessary for CD86 and HLA‐DR up‐regulation, a process that was inhibited by anti‐CD18 antibodies, indicating that CD18 ligation was required. We also found that via a cell contact‐dependent mechanism, DCs acquired Candida albicans‐derived antigens from live as well as from apoptotic PMNs and could thus elicit antigen‐specific T lymphocyte responses. Altogether, our data demonstrate the occurrence of cross‐talk between human PMNs and DCs and provide new insights into the immune processes occurring upstream of the interactions between DCs and T lymphocytes.
MULTIVARIABLE LQG VIBRATION CONTROL USING CHARGE-DRIVEN PIEZOELECTRIC ACTUATORS

Abstract Piezoelectric actuators are known to exhibit hysteresis when driven at relatively large voltages. In most situations this phenomenon is detrimental. Electric charge is known to naturally reduce the effects of hysteresis. The interaction of charge driven piezoceramics with flexible structures is analyzed and reveals that the dynamics of the system are different from the voltage driven case. A procedure for obtaining a charge driven plant model is documented, which can be used with standard control design tools. A multivariable LQG charge controller is designed to reject disturbance vibrations acting on a cantilever beam. Experimental results demonstrating the effectiveness of this method are included.