Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust estimation of value-at-risk through correlated frequency and severity model

In this article we develop a novel method for accurately estimating the Value-at-Risk (VaR) in the context of modern Operational Risk Management (ORM). We develop a method called Data Partition of Frequency and Severity (DPFS) which more accurately computes the VaR in a modern ORM context. The DPFS involves using clustering analysis to partition the frequency and severity components of the loss data. Since the fundamental theory of modern ORM implicitly assumes a “correlation” between frequency and severity of losses, we argue that this approach should follow naturally. To test this idea, we perform simulation based studies which show that in a theoretical situation, the new DPFS method will perform better than and in worst case as well as the current VaR best practices (which we call “classical” method). In addition, we implement our methodology on two publicly available datasets: (1) Financial Index data of S&P 500; (2) Chemical Loss spills as tracked by the US National Coast Guard. We observe that the “classical” VaR calculation inaccurately estimates the data in both the simulation and real-world data studies while DPFS attains much more accurate VaR estimates.
Correlation between tumor engraftment in patient-derived xenograft models and clinical outcomes in colorectal cancer patients

Despite numerous studies involving patient-derived xenograft (PDX) models, few studies have investigated the relationship between the ability of the tumor to engraft (tumorigenicity) and the clinical features of colorectal cancer (CRC). The aim of this study was to determine whether tumorigenicity correlates with clinical outcomes of CRC patients. We included 241 CRC patients who underwent radical surgery from 2010 to 2013. PDX models were established by implanting tumor fragments obtained from these patients into the subcutaneous layer of immunodeficient mice. Xenografts were successfully established from 62.2%. Successful engraftment was associated with advanced stage (p < 0.001) and moderate/poor differentiation (p = 0.029). Three-year disease-free survival (DFS) rates were lower for patients with tumorigenicity (p = 0.011). In stage III patients, tumorigenicity was an independent predictor of poor DFS (p = 0.034). In addition, mutation of TP53 was most frequently detected in stage III patients with tumorigenicity. Two models of stage IV disease without KRAS mutations showed high sensitivity to EGFR-targeted agents, while none of the models with KRAS mutations showed high sensitivity. In conclusion, PDX models may provide an effective preclinical tool for predicting cancer progression and could be used to further genomic and pharmacologic research on personalized treatments.
Regulation of Gene Expression in Protozoa Parasites

Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp. , Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.
Graphical user interface testing using evolutionary algorithms

In software applications industry, the most important challenge is to ensure the maximum quality for software products. The demand for Graphical user interface (GUI) testing has very much increased in the last years. An important progress in this field has been achieved, from GUI manual testing to complete automate GUI testing. In this paper, optimization theory and evolutionary algorithms (EA) concepts were applied for GUI testing. In our approach, the GUI is completely separated from the code itself. The aim of the proposed methodology is to find the test case sequence(s) which produce(s) the maximum amount of changes inside the GUI while preserving all other constraints. The method starts by randomly generating the initial set of test cases, which is then improved through measuring and evaluating specific fitness functions. By using optimization theory, very good results were obtained for accelerating the automatic test of large interfaces.
Transcriptomic Analysis of the Ion Channelome of Human Platelets and Megakaryocytic Cell Lines

Summary Ion channels have crucial roles in all cell types and represent important therapeutic targets. Approximately 20 ion channels have been reported in human platelets; however, no systematic study has been undertaken to define the platelet channelome. These membrane proteins need only be expressed at low copy number to influence function and may not be detected using proteomic or transcriptomic microarray approaches. In our recent work, quantitative real-time PCR (qPCR) provided key evidence that Kv1.3 is responsible for the voltage-dependent K+ conductance of platelets and megakaryocytes. The present study has expanded this approach to assess relative expression of 402 ion channels and channel regulatory genes in human platelets and three megakaryoblastic/erythroleukaemic cell lines. mRNA levels in platelets are low compared to other blood cells, therefore an improved method of isolating platelets was developed. This used a cocktail of inhibitors to prevent formation of leukocyte-platelet aggregates, and a combination of positive and negative immunomagnetic cell separation, followed by rapid extraction of mRNA. Expression of 34 channel-related transcripts was quantified in platelets, including 24 with unknown roles in platelet function, but that were detected at levels comparable to ion channels with established roles in haemostasis or thrombosis. Trace expression of a further 50 ion channel genes was also detected. More extensive channelomes were detected in MEG-01, CHRF-288–11 and HEL cells (195, 185 and 197 transcripts, respectively), but lacked several channels observed in the platelet. These “channelome” datasets provide an important resource for further studies of ion channel function in the platelet and megakaryocyte. Supplementary Material to this article is available online at www.thrombosis-online.com.
An SDN Based Intra-Domain Routing and Resource Management Model

Software Defined Networking (SDN) has become a promising network architecture that simplifies the network control, management and deployment of differentiated services. SDN architecture decouples control and data planes. Control functions are moved to a logically centralized entity called controller. The underlying infrastructure solely performs forwarding. Most of the previous studies focus on using SDN in data centers. In this paper, we propose scalable routing and resource management model for SDN based intra-domain networks. To virtualize the underlying network, we use pre-established multi-paths (PMP) between each ingress-egress switch. SDN-Controller performs admission control, routing, load balancing and path resizing functions based on these paths. The experimental results show that the proposed model significantly improves routing and signaling scalability, network resource utilization and decreases admission control time.
Optimized Unit Testing for Antipattern Detection

Antipatterns are poor design choices that are conjectured to make object oriented systems harder to maintain. We investigate the impact of antipatterns on classes in object-oriented systems by studying the relation between the presence of antipatterns and the change- and fault-proneness of the classes. Due to increased complexities in the software development, there is huge need of testing process to be carried on in better way. Also as the computer systems are significant to our society in everyday life and are performing an increasing number of critical tasks, so more work in software testing and analysis has become of great importance. Anti pattern testing is type of testing which is used to cut off the directly price associated with testing of different modules. This paper discusses various anti pattern detection techniques and proposes a new testing technique based on GUI for detection of anti patterns during software development.
Public health in the Calais refugee camp: environment, health and exclusion

Abstract The ongoing emergency for refugees is having profound and hidden health consequences for thousands of displaced persons who live in informal ‘makeshift’ camps across Europe. This interdisciplinary paper reports the results of the first environmental health assessment in such a location, in what was Europe’s largest informal refugee camp in 2016, in Calais, northern France. We detail the lack of facilities for sanitation, safe provision of food, water and shelter, demonstrating how conditions fall short of agreed international standards for formal refugee camps. Rather than the notion of migrants being the cause of health problems, this paper critically reveals the hidden materiality of bodily injury caused by poor health conditions, where the camp itself produces harm. Drawing upon theories of biopolitical exclusion, the paper concludes by (i) emphasising the empirical and conceptual themes that tie refugee politics and biologies together and (ii) makes a call for increased attention to makeshift camps as key sites of health exclusion in Europe and beyond.
International Workshop on Global Software Development Workshop Organization Organizing Committee Program Committee Supporting Global Software Development with Event Notification Servers ……. Preliminary Evaluation of Tool-based Support for Distributed Inspection ……... Process Support for Distributed 

Distributed software development typically uses a centralized architecture, which has some drawbacks such as, the participants may experience lengthy delays if they are located far from the central server, and the organization that runs the server must deal with the security and privacy issues that come with being in charge of a central repository of information. We are investigating whether this centralized control can be relaxed by using peer-topeer (P2P) technology. Adopting a P2P architecture includes some of the following benefits for software development: (1) the peer (or group) is able to have complete control of its information, (2) groups can share and duplicate information to help users with slow network connections, and (3) users can easily contribute their own resources to the project, such as hard drive space. The P2P architecture also has potential drawbacks, including the need for complex search and retrieval algorithms, and having to coordinate the synchronization of duplicated stores of data. The objectives of our research are threefold: (1) to examine the design issues related to the development of a P2P software development application, (2) to alter an existing virtual software development application (MILOS) from a client-server to a P2P application using the Sun JXTA framework, and (3) to present empirical evidence on the value of the P2P implementation based on data gathered during the development process, and during application use (i.e., delays when searching and retrieving information).
Random walks on lattices

For complex electrical networks, we can take advantage of this result to simply our network. When we raise the resistance of edges, the effective resistance in our modified graph is an upper bound on the effective resistance of – and a lower bound on the effective conductance of – the original graph. When we lower the resistance of edges, the effective resistance in our modified graph is a lower bound on the effective resistance of – and an upper bound of the effective conductance of – the original graph.
School Counselors and Multicultural Education: Applying the Five Dimensions.

Multicultural education is an educational approach designed to ensure equal educational opportunities for all students, including those in marginalized groups. This approach has historically been directed towards teachers, but school counselors have the appropriate training and skills to lead multicultural education efforts, as well. In this article, the five dimensions of multicultural education are described and examples are provided that suggest how school counselors can use each dimension in order to create a context in which all students succeed.
An Improved Corpus Comparison Approach to Domain Specific Term Recognition

Domain specific terms are words carrying special conceptual meanings in a sub- ject field. Automatic term recognition plays an important role in many natural language processing and knowledge engineering applications such as information retrieval and knowledge mining. This paper explores a novel approach to automatic term extraction based on the basic ideas of corpus comparison and emerging pattern with significant elabo- ration. It measures the termhood of a term candidate in terms of its peculiarity to a given domain via comparison to several background domains. Our experiments confirm its out- performance against other approaches, achieving an average precision of 83% on the top 10% candidates in terms of their termhood.
Finding Curvilinear Features in Spatial Point Patterns: Principal Curve Clustering with Noise

Clustering about principal curves combines parametric modeling of noise with nonparametric modeling of feature shape. This is useful for detecting curvilinear features in spatial point patterns, with or without background noise. Applications include the detection of curvilinear minefields from reconnaissance images, some of the points in which represent false detections, and the detection of seismic faults from earthquake catalogs. Our algorithm for principal curve clustering is in two steps: The first is hierarchical and agglomerative (HPCC) and the second consists of iterative relocation based on the classification EM algorithm (CEM-PCC). HPCC is used to combine potential feature clusters, while CEM-PCC refines the results and deals with background noise. It is important to have a good starting point for the algorithm: This can be found manually or automatically using, for example, nearest neighbor clutter removal or model-based clustering. We choose the number of features and the amount of smoothing simultaneously, using approximate Bayes factors.
Time-evolving graph processing at scale

Time-evolving graph-structured big data arises naturally in many application domains such as social networks and communication networks. However, existing graph processing systems lack support for efficient computations on dynamic graphs. In this paper, we represent most computations on time evolving graphs into (1) a stream of consistent and resilient graph snapshots, and (2) a small set of operators that manipulate such streams of snapshots. We then introduce GraphTau, a time-evolving graph processing framework built on top of Apache Spark, a widely used distributed dataflow system. GraphTau quickly builds fault-tolerant graph snapshots as each small batch of new data arrives. GraphTau achieves high performance and fault tolerant graph stream processing via a number of optimizations. GraphTau also unifies data streaming and graph streaming processing. Our preliminary evaluations on two representative datasets show promising results. Besides performance benefit, GraphTau API relieves programmers from handling graph snapshot generation, windowing operators and sophisticated differential computation mechanisms.
Re-identification of Persons in Videos and Images

Problem definition, performance metrics, and datasets Person re-identification (re-id) is defined as the problem of recognizing an individual captured in different times and/or locations over several non-overlapping camera views, considering a large set of candidates. This is a very difficult problem as most of the time people are captured by diverse low resolution cameras, under occlusions conditions, badly (and different from view to view) illuminated, and in varying poses. In this context, a robust modeling of the entire body appearance of a person is mandatory, especially when other classical biometric cues (face, gait) are not available or difficult to catch, due to the sensors’ scarce resolution or low frame-rate. Re-id algorithms are typically tested considering ad hoc datasets composed by a fixed number of individuals, each one represented by several (minimum two) image windows containing or bounding boxes surrounding a person, typically in different poses (e.g., frontal, back, profile, etc.). The actual re-identification is performed by considering one instance of an individual, the so-called “probe”, which is compared and matched against all the other instances of all subjects in the dataset, the so-called “gallery” set. Hence, given a set of probes, an re-id method provides a ranking of a certain number of subjects in the gallery set, typically ranging from 1 to 25, 50 or 100, depending on the used dataset. Algorithms’ performance is commonly calculated by the recognition rate estimated by the Cumulative Matching Characteristic (CMC) curve, and the normalized Area Under Curve (nAUC) score for the CMC curve. The CMC curve is a plot of the recognition performance vs. the ranking score and represents the expectation of finding the correct match in the top n matches; nAUC gives an overall score of how well a re-identification method performs overall. The most used image datasets are VIPER, iLIDS, ETHZ, and CAVIAR4REID, which differs for a number of characteristics: number of subjects considered (in the order of hundreds), number of instances per subject (from 2 to 10), pose and lighting variations, severity of the occlusions, number of viewpoints (cameras), window resolution (from 17×39 up to 72×144, 48×128, 64×128, etc.). Furthermore, 3D datasets are now becoming available for re-id research. All the following developed methods proved to perform better than state of the art at the moment of the publication.
The performance of PC solid-state disks (SSDs) as a function of bandwidth, concurrency, device architecture, and system organization

As their prices decline, their storage capacities increase, and their endurance improves, NAND Flash Solid State Disks (SSD) provide an increasingly attractive alternative to Hard Disk Drives (HDD) for portable computing systems and PCs. This paper presents a study of NAND Flash SSD architectures and their management techniques, quantifying SSD performance under user-driven/PC applications in a multi-tasked environment; user activity represents typical PC workloads and includes browsing files and folders, emailing, text editing and document creation, surfing the web, listening to music and playing movies, editing large pictures, and running office applications. We find the following: (a) the real limitation to NAND Flash memory performance is not its low per-device bandwidth but its internal core interface; (b) NAND Flash memory media transfer rates do not need to scale up to those of HDDs for good performance; (c) SSD organizations that exploit concurrency at both the system and device level (e.g. RAID-like organizations and Micron-style (superblocks) improve performance significantly; and (d) these system- and device-level concurrency mechanisms are, to a significant degree, orthogonal: that is, the performance increase due to one does not come at the expense of the other, as each exploits a different facet of concurrency exhibited within the PC workload.
Progress toward scalable tomography of quantum maps using twirling-based methods and information hierarchies

We present in a unified manner the existing methods for scalable partial quantum process tomography. We focus on two main approaches: the one presented in Bendersky et al. [Phys. Rev. Lett. 100, 190403 (2008)] and the ones described, respectively, in Emerson et al. [Science 317, 1893 (2007)] and Lopez et al. [Phys. Rev. A 79, 042328 (2009)], which can be combined together. The methods share an essential feature: They are based on the idea that the tomography of a quantum map can be efficiently performed by studying certain properties of a twirling of such a map. From this perspective, in this paper we present extensions, improvements, and comparative analyses of the scalable methods for partial quantum process tomography. We also clarify the significance of the extracted information, and we introduce interesting and useful properties of the {chi}-matrix representation of quantum maps that can be used to establish a clearer path toward achieving full tomography of quantum processes in a scalable way.
The Golgi-localization of yeast Emp47p depends on its di-lysine motif but is not affected by the ret1-1 mutation in alpha-COP

The Saccharomyces cerevisiae EMP47 gene encodes a nonessential type-I transmembrane protein with sequence homology to a class of intracellular lectins defined by ERGIC-53 and VIP36. The 12-amino acid COOH-terminal cytoplasmic tail of Emp47p ends in the sequence KTKLL, which conforms with the consensus for di-lysine-based ER-localization signals. Despite the presence of this motif, Emp47p was shown to be a Golgi protein at steady-state. The di-lysine motif of Emp47p was functional when transplanted onto Ste2p, a plasma membrane protein, conferring ER localization. Nevertheless, the di-lysine motif was required for Golgi-localization of Emp47p and showed the same charge- independent, position-dependent characteristics of other di-lysine motifs. Alpha-COP has been shown to be required for ER localization of di-lysine-tagged proteins. Consistent with this finding, the Ste2p- Emp47p hybrid protein was mislocalized to the cell surface in the alpha- COP mutant, ret1-1. Surprisingly, the Golgi-localization of Emp47p was unaffected by the ret1-1 mutation. To investigate whether Emp47p undergoes retrograde transport from the Golgi to the ER like other di- lysine-tagged proteins we developed an assay to measure this step after block of forward transport in a sec12 mutant. Under these conditions retrograde transport led to a specific redistribution of Emp47p from the Golgi to the ER. This recycling occurred from a Golgi subcompartment containing alpha 1,3 mannose-modified oligosaccharides suggesting that it originated from a medial-or later Golgi compartment. Thus Emp47p cycles between the Golgi apparatus and the ER and requires a di-lysine motif for its alpha-COP-independent, steady state localization in the Golgi.
Parallelization of the Scale-Invariant Keypoint Detection Algorithm for Cell Broadband Engine Architecture

This paper describes design and implementation of a parallel algorithm that detects scale-invariant keypoints from digital images. Keypoint detection is one of the most important operations in image processing since efficient image matching is possible with it. Image matching is used in many intelligent image processing service, including object/scene recognition, stereo correspondence, motion tracking, and panorama imaging. In this paper, we design a new parallel algorithm of keypoint detection that is suitable for Cell Broadband Engine architecture by converting each subprocess of keypoint detection algorithm into parallel version. The experimental results show that performance of our algorithm increases in proportion to the number of processors utilized, that is, it achieves linear scalability.