Miracle-dz/UniFAR-FTUs huggingface dataset:
Level set-based histology image segmentation with region-based comparison

Automated histological grading of tissue biopsies for clinical cancer care is a challenging problem that requires sophisticated algorithms for image segmentation, tissue architecture characterization, global texture feature extraction, and high-dimensional clustering and classification algorithms. Currently there are no automatic image-based grading systems for establishing the pathology of cancer tissues. A primary step in computational histology is accurate image segmentation to detect significant regions such as nuclei, lumen and epithelial cytoplasm which together make up a gland structure. We describe a new approach for tissue segmentation using fuzzy spatial clustering and level set active contours. The proposed technique shows improvement in segmentation accuracy and outperform the classical clustering and level set methods, when compared to ground truth segmentation.
THE CELL TRANSMISSION MODEL WITH CAPACITY DROP Dipl

Dynamic Traffic Management (DTA) is a growing field in transportation applications. A traffic control center, for example, needs to react quickly to incidents on a highway. It uses a traffic flow model with forecasting features, to predict the traffic state and the travel time over one hour. One of these traffic flow models is the macroscopic first-order Cell Transmission Model. In this paper, the Cell Transmission Model is expanded to reproduce the traffic phenomena of the capacity drop and of the boomerang effect by a applying a fundamental diagram in the shape of an inverted lambda.
Tardis 2.0: Optimized time traveling coherence for relaxed consistency models

Cache coherence scalability is a big challenge in shared memory systems. Traditional protocols do not scale due to the storage and traffic overhead of cache invalidation. Tardis, a recently proposed coherence protocol, removes cache invalidation using logical timestamps and achieves excellent scalability. The original Tardis protocol, however, only supports the Sequential Consistency (SC) memory model, limiting its applicability. Tardis also incurs extra network traffic on some benchmarks due to renew messages, and has suboptimal performance when the program uses spinning to communicate between threads. In this paper, we address these downsides of Tardis protocol and make it significantly more practical. Specifically, we discuss the architectural, memory system and protocol changes required in order to implement the TSO consistency model on Tardis, and prove that the modified protocol satisfies TSO. We also describe modifications for Partial Store Order (PSO) and Release Consistency (RC). Finally, we propose optimizations for better leasing policies and to handle program spinning. On a set of benchmarks, optimized Tardis improves on a full-map directory protocol in the metrics of performance, storage and network traffic, while being simpler to implement.
Statistical Applications in Genetics and Molecular Biology Two-Stage Model-Based Clustering for Liquid Chromatography Mass Spectrometry Data Analysis

Proteomic mass spectrometry is gaining an increasing role in diagnostics and in studies on protein complexes and biological systems. This experimental technology is producing highthroughput data which is inherently noisy and may contain various errors. Mathematical processing can help in removing them. In this paper we focus on the peak alignment problem in LC-MS spectra. As an alternative to heuristic approaches to the problem, we propose a mathematically sound method which exploits a model-based clustering. In this framework experiment errors are modeled as deviations from real values and mass spectra are regarded as finite Gaussian mixtures. The advantage of such an approach is that it provides convenient techniques for adjusting parameters and selecting solutions of best quality. The method can be parameterized by assuming various constraints. In this paper we investigate and compare different classes of models. We analyze the results in terms of statistically significant biomarkers that can be identified after the alignment of spectra. The study was conducted on a dataset of plasma samples of colorectal cancer patients and healthy donors.
The Impact of Structural Breaks on the Integration of the Asean-5 Stock Markets

This paper examines the ASEAN-5 countries and explores the impact of structural breaks on the level of financial integration in that region. An extended cointegration procedure allowing for three types of structural break, is employed and compared with the standard Johansen procedure, for daily and weekly returns. The empirical results suggest a higher level of integration within the ASEAN-5 markets than previously found, suggesting that financial risk reduction benefits from diversifying investments across the region are less than previously thought. Further, Singapore and Thailand are the main long-term drivers in the region; Malaysia and Indonesia are more short-term drivers. Structural breaks are found to correspond with the Asian financial crisis in 1997/98 and a possible Y2K effect in late 1999. Results are verified using another structural break model and method, where break dates are treated as known.
Leveraging multi-faceted tagging to improve search in folksonomy systems

In this paper we present ranking algorithms for folksonomy systems that exploit additional contextual information attached to tag assignments available. We evaluate the algorithms in the TagMe! system, a tagging front-end for Flickr, and show that our algorithms, which exploit categories, spatial information, and URIs describing the semantics of tag assignments, perform significantly better than the FolkRank that does not consider such contextual information.
Improved implementation and experimental evaluation of the max-error optimized wavelet synopses

This paper provides an improved implementation of an algorithm for building wavelet synopses for max-error metrics, recently introduced by Garofalakis and Kumar (GK) [4]. Given a storage space of size M, the GK algorithm flnds a wavelet synopsis of size M, which minimizes the max (absolute or relative) error, measured over the data values, with respect to any other wavelet synopsis of size M. The running time of the GK algorithm is O i N 2 M logM ¢ and its space complexity is O i N 2 M ¢ . In this paper we improve the time and space complexities by a factor of M, reducing the running time to O i N 2 logM ¢ and the space requirement to O i N 2 ¢ . As in [4] no experimental results were shown, we present experimental comparison between the accuracy of the GK synopsis with other wavelet synopses, as well as experimental comparison between the running-time of the original GK algorithm with our improved implementation. We also apply the GK synopsis for rangequeries, built on the raw data as well as over the preflx-sums of the data, and compare it experimentally with other wavelet synopses, demonstrating an interesting similarity to another synopsis that can be computed in linear time.
Representing and Computing Temporally Scoped Beliefs

Planning effective courses of action requires making predictions about what the world may be like at the time the actions are to be performed. Making these predictions requires a temporal representation, and—assuming a world that is not entirely predictable and an agent that is not omniscient—a representation of the uncertainty that will characterize its incomplete knowledge of the world. We provide in this paper a representation and calculus for computing an agent's strength of belief in a proposition at a point in time, based on (possibly imperfect) observations about that proposition and information about the tendency of the proposition to persist over time.
Collusion-resistant repeated double auctions for cooperative communications

Deployment of relay nodes to existing wireless net-works recently has received much attention since the channel capacity from sources to destinations through the cooperation of relay nodes is greatly enhanced. However, choosing appropriate relay nodes is critical to maximize the overall network performance. In this paper, we consider the assignment problem of relay nodes in a cooperative wireless network, where physical relay infrastructures and relay supporting services (relay assignment) are independently operated by different selfish entities with each being driven by its own benefit. We first formulate the problem as a repeated double auction by taking into account the benefits of all entities. Specifically, we consider a system that consists of a set of source-to-destination pairs, where the source nodes are grouped into groups and each of them is represented by a group agent. We assume that both the source nodes and the group agents seek opportunities to maximize their own benefits through various means including untruthful bidding and collusion with each other, and so on. To maximize the social benefit of the system that include the benefits of the source nodes, the relay nodes and the auctioneer, we devise an auction which we refer it to as the repeated multi-heterogeneous-item double auction with collusion resistance. We also analytically show that this auction is not only truthful but also collusion resistant. The experimental results indicate that the proposed auction is effective in collusion-resistance.
Network Analysis and Experimental Validation of the Five Shu Points Model of Traditional Oriental Medicine

In this paper, we propose an extended network model to detect relationships among disease states based on the Five Shu Points model commonly used in traditional oriental medicine. We expand the network model to encompass relationships between disease state and protein expression by using Korean traditional disease codes as a classifier. On the basis of the proposed model, we show that interactions between the Five Shu points can be validated with experimental observations.
SAFERPHP: finding semantic vulnerabilities in PHP applications

Web applications are vulnerable to semantic attacks such as denial of service due to infinite loops caused by malicious inputs and unauthorized database operations due to missing security checks. Unlike "conventional" threats such as SQL injection and cross-site scripting, these attacks exploit bugs in the logic of the vulnerable application and cannot be discovered using data-flow analysis alone. We give the first characterization of these types of vulnerabilities in PHP applications, develop novel inter-procedural algorithms for discovering them in PHP source code, and implement these algorithms as part of SaferPHP, a framework for static security analysis of PHP applications. SaferPHP uncovered multiple, previously unreported vulnerabilities in several popular Web applications.
Typing of Chlamydia psittaci to monitor epidemiology of psittacosis and aid disease control in the Netherlands, 2008 to 2013.

A simple genotyping method was developed and validated for all known Chlamydia psittaci reference genotypes. C. psittaci is currently divided into nine genotypes (A-F, E/B, M-5(6) and WC), all more or less associated with the preferred avian host. This method targeting variable domain 4 of the ompA gene has a lowest detection limit of 1 to 10 copies per PCR and was applied to 69 human samples collected in nine hospitals in the Netherlands from September 2008 until the end of October 2013. Genotype A was the most prevalent genotype. In addition, genotypes B, C, a new genotype, and C. abortus were found. A C. caviae infection was detected as a result of extension of this surveillance study to the national level. The sensitivity of this method compared with our real-time diagnostic PCR was 0.98 (66/67 typable samples). Specificity was 1.0 based on 33 commonly encountered bacterial and yeast species and 20 human respiratory samples. This typing method could help monitor C. psittaci infections in humans and provides insight into the relationships between notified human 'psittacosis' cases and the probable avian and other animal sources. When needed, a result can be obtained within 24 hours.
A behavioural approach to obstacle avoidance for mobile manipulators based on distributed sensing

A reactive obstacle avoidance method for mobile manipulators is presented. The objectives of the developed algorithm are twofold. The first one is to find a trajectory in the configuration space of a mobile manipulator so as to follow a given trajectory in the task space. The second objective consists in locally adjusting the trajectory in the configuration space in order to avoid collisions with potentially moving obstacles and self-collisions in unstructured and dynamic environments. The perception is exclusively based on a set of proximity sensors distributed on the robot mechanical structure and visual information are not required. Thanks to the adoption of this kind of proximity distributed perception, the approach does not require a 3D model of the robot and allows the real-time collision avoidance without the need of a sensorized environment. To achieve the features cited above, a behaviour-based technique known as Null-Space-Based (NSB) approach has been adopted with some modifications.On one hand, the concept of a total pseudo-energy based on the information from the distributed sensors has been introduced. On the other hand, a method to combine different tasks has been proposed to guarantee the smoothness of the realtime trajectory adjustments. Another significant feature of the method is the strict coordination between the base and the arm exploiting the redundant degrees of freedom, that is a relevant topic in mobile manipulation.
Understanding Plug-in Test Suites from an Extensibility Perspective

Plug-in architectures enable developers to build extensible software products. Such products are assembled from plug-ins, and their functionality can be enriched by adding or configuring plug-ins. The plug-ins themselves consist also of multiple plug-ins, and offer dedicated points through which their functionality can be influenced. A well-known example of such an architecture is Eclipse, best known for its use to create a series of extensible IDEs. In order to test systems built from plug-ins developers use extensive automated test suites. Unfortunately, current testing tools offer little insight in which of the many possible combinations of plug-ins and plug-in configurations are actually tested. To remedy this problem, we propose three architectural views that provide an extensibility perspective on plug-in-based systems and their test suites. The views combine static and dynamic information on plug-in dependencies, extension initialization, and extension usage. The views are implemented in ETSE, the Eclipse Plug-in Test Suite Exploration tool. We evaluate the proposed views by analyzing eGit and Mylyn, two open source Eclipse plug-ins.
Culture in social neuroscience: A review

The aim of this review is to highlight an emerging field: the neuroscience of culture. This new field links cross-cultural psychology with cognitive neuroscience across fundamental domains of cognitive and social psychology. We present a summary of studies on emotion, perspective-taking, memory, object perception, attention, language, and the self, showing cultural differences in behavior as well as in neural activation. Although it is still nascent, the broad impact of merging the study of culture with cognitive neuroscience holds mutual distributed benefits for multiple related fields. Thus, cultural neuroscience may be uniquely poised to provide insights and breakthroughs for longstanding questions and problems in the study of behavior and thought, and its capacity for integration across multiple levels of analysis is especially high. These findings attest to the plasticity of the brain and its adaptation to cultural contexts.
A successive decoding strategy for channels with memory

This paper presents both an information lossless coding scheme and a method to evaluate constrained capacity for channels with memory and unknown state. The fundamental idea is to decompose the original channel into a bank of memoryless sub-channels with partially known states, then successively decode these sub-channels. The receiver of each sub-channel consists of an optimal estimator followed by a memoryless channel decoder. The coding scheme translates the codes and decoders designed for memoryless channels with near capacity performance to channels with memory. The results are applied to both finite state Markov channels and correlated flat fading channels
Improving test collection pools with machine learning

IR experiments typically use test collections for evaluation. Such test collections are formed by judging a pool of documents retrieved by a combination of automatic and manual runs for each topic. The proportion of relevant documents found for each topic depends on the diversity across each of the runs submitted and the depth to which runs are assessed (pool depth). Manual runs are commonly believed to reduce bias in test collections when evaluating new IR systems. In this work, we explore alternative approaches to improving test collection reliability. Using fully automated approaches, we are able to recognise a large portion of relevant documents that would normally only be found through manual runs. Our approach combines simple fusion methods with machine learning. The approach demonstrates the potential to find many more relevant documents than are found using traditional pooling approaches. Our initial results are promising and can be extended in future studies to help test collection curators ensure proper judgment coverage is maintained across the entire document collection.
The incidence and control of livestock diseases in Darfur, Anglo-Egyptian Sudan, during the period of the condominium, 1916-1956.

Darfur is the westernmost province of the Republic of the Sudan. It encompasses almost one-half million square kilometers in area, bounded on the south by the Bahr el 'Arab at about 9? north latitude and in the north by the twentieth parallel; and extending from approximately 22? 30'E in the west to 27? E in the east. Much of the northern area is desert, either totally unused or only occasionally occupied by livestock. In all, about 250,000 square kilometers are suitable for continuous livestock use, including the whole of the 160,000 square kilometers which now constitute the province of Southern Darfur.1 Darfur, and particularly the southern part of the province, has long been the principal source from which livestock have been drawn, especially cattle for export and for slaughter in Khartoum. An analysis of veterinary department records for the twelve years prior to the outbreak of the Second World War shows that of the total cattle exported from the Sudan during this period, 69.3 percent came from southern Darfur and neighbouring southern Kordofan, varying in individual years from 44 percent to 94 percent. After the war it was estimated that about 80 percent of export animals came from these areas.2 The location of this important area in the Sudan's livestock economy in relation to northeast Africa as a whole, and the approximate areas occupied by the principal cattle-owning tribes, known collectively in the Sudan as Baqqara, is illustrated in the accompanying map.
Hands Free Interaction with Virtual Information in a Real Environment: Eye Gaze as an Interaction Tool in an Augmented Reality System

Eye contact in human conversations is a natural source of information about the visual attention of people talking, and also indicates who is speaking to whom. Eye gaze can be used as an interaction method, but gaze tracking can also be used to monitor a user’s eye movements and visual interest. This paper describes how gaze-based interaction can be used and implemented in an Augmented Reality (AR) system. The results of the preliminary tests of the gaze-controlled AR system show that the system does work, but that it needs considerable development and further user studies before it can be a realistic option in real end user settings.
Visual observation and numerical studies of polymer foaming behavior of polypropylene/carbon dioxide system in a core-back injection molding process

Thermoplastic foaming within a mold cavity was visualized as it was conducted in an 85-ton core-back injection-molding machine. The core-back molding process moved a section of the mold just after injecting a molten polymer into the cavity, quickly reducing the pressure to enhance the bubble nucleation. The foaming behavior during core-back was observed directly through the glass windows of the mold. In the experiments, impact copolymer polypropylene was foamed with carbon dioxide. The effects of the gas concentration and the core-back rate on bubble nucleation and growth were investigated. It was experimentally confirmed that the bubbles disappeared when the cavity was fully packed and that bubble nucleation occurred when the mold plate was moved and the cavity pressure dropped. Faster core-back rates and higher gas concentrations increased the number of bubbles while decreasing their size. To analyze the experimental results, a bubble nucleation and growth model was employed that was based on batch foaming. The numerical results were a reasonable representation of the experiments, and this study demonstrated the applicability of the conventional free foaming model to the industrial core-back molding process. Many aspects of the foaming in the core-back molding aresimilar to the behaviors observed by batch foaming. POLYM. ENG. SCI., 2011. © 2011 Society of Plastics Engineers
Sackcloth or silk?: the impact of appearance vs dynamics on the perception of animated cloth

Physical simulation and rendering of cloth is widely used in 3D graphics applications to create realistic and compelling scenes. However, cloth animation can be slow to compute and difficult to specify. In this paper, we present a set of experiments in which we explore some factors that contribute to the perception of cloth, to determine how efficiency could be improved without sacrificing realism. Using real video footage of several fabrics covering a wide range of visual appearances and dynamic behaviors, and their simulated counterparts, we explore the interplay of visual appearance and dynamics in cloth animation.
PGC-1&bgr; Deficiency Accelerates the Transition to Heart Failure in Pressure Overload Hypertrophy

Rationale: Pressure overload cardiac hypertrophy, a risk factor for heart failure, is associated with reduced mitochondrial fatty acid oxidation (FAO) and oxidative phosphorylation (OXPHOS) proteins that correlate in rodents with reduced PGC-1&agr; expression. Objective: To determine the role of PGC-1&bgr; in maintaining mitochondrial energy metabolism and contractile function in pressure overload hypertrophy. Methods and Results: PGC-1&bgr; deficient (KO) mice and wildtype (WT) controls were subjected to transverse aortic constriction (TAC). Although LV function was modestly reduced in young KO hearts, there was no further decline with age so that LV function was similar between KO and WT when TAC was performed. WT-TAC mice developed relatively compensated LVH, despite reduced mitochondrial function and repression of OXPHOS and FAO genes. In nonstressed KO hearts, OXPHOS gene expression and palmitoyl-carnitine-supported mitochondrial function were reduced to the same extent as banded WT, but FAO gene expression was normal. Following TAC, KO mice progressed more rapidly to heart failure and developed more severe mitochondrial dysfunction, despite a similar overall pattern of repression of OXPHOS and FAO genes as WT-TAC. However, in relation to WT-TAC, PGC-1&bgr; deficient mice exhibited greater degrees of oxidative stress, decreased cardiac efficiency, lower rates of glucose metabolism, and repression of hexokinase II protein. Conclusions: PGC-1&bgr; plays an important role in maintaining baseline mitochondrial function and cardiac contractile function following pressure overload hypertrophy by preserving glucose metabolism and preventing oxidative stress.