Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Support Vector Clustering Algorithm to Network Intrusion Detection

The support vector clustering (SVC) algorithm is inspired from support vector machines (SVM). It takes the form of quadratic programming and can yield a global optimum, and gives a sparse representation of the data set by way of only a few number of support vectors. Aiming at its defection of slowly training of large-scale sets, and considering the characteristic of network intrusion detection, an improved algorithm of SVC is proposed in this paper. The proposed method uses similarity measurement instead of Euclidian distance, and makes small clusters substituted by their reference points, then compensates the information distortion caused by the references. The training of the SVC is enhanced on large-scale data set as well as unevenly distributed data set
Parasitoids, predators and PCR: the use of diagnostic molecular markers in biological control of Arthropods

Abstract: The polymerase chain reaction (PCR) revolutionized the field of diagnostics, and today it has routine applications in medical, veterinary, forensic and botanical sciences. The fields of biological control and insect pest management have generally been slow to adopt PCR‐based diagnostics in comparison with other fields of science. However, there has been increasing interest in the use of molecular diagnostic tools in arthropod biological control. In applied entomology, molecular techniques have generally been used for insect identification and systematics; however, PCR‐based techniques are increasingly becoming recognized as valuable tools in ecological studies. Here, we review research that has used PCR‐based techniques for parasitoid and predator/prey identification and detection, and place these studies in the context of their contributions to biological control of arthropods. The status and future directions of diagnostic molecular markers in applied entomology and insect pest management are also discussed.
An Econometric Analysis of Pine Pulpwood Market in the Southern US

This paper examines the determinants of pine pulpwood supply and demand in the southern US using annual data from 1950 to 2002. A structural simultaneous system of equations (SSE) model is used to estimate short-run price elasticities with three-stage least squares (3SLS) regression techniques. The results show that price elasticities of supply of and demand for pine pulpwood are relatively small, but similar to those reported for the US South. The results also show that the cross elasticity with pine sawtimber is significantly positive at the 5% level, but very small in magnitude at 0.11, which is consistent with the previous finding. The significant substitution between pulpwood stumpage and energy use was found with elasticity of -0.35.
Instruction set customization of application specific processors for network processing: a case study

The growth of the Internet in the last decade has made current networking applications immensely complex. Systems running such applications need special architectural support to meet the tight constraints of power and performance. This paper presents a case study of architecture exploration and optimization of an application specific instruction set processor (ASIP) for networking applications. The case study particularly focuses on the effects of instruction set customization for applications from different layers of the protocol stack. Using a state-of-the-art VLIW processor as the starting template, and architecture description language (ADL) based architecture exploration tools, this case study suggests possible instruction set and architectural modifications that can speed-up some networking applications up to 6.8 times. Moreover, this paper also shows that there exist very few similarities between diverse networking applications. Our results suggest that, it is extremely difficult to have a common set of architectural features for efficient network protocol processing and, ASIPs with specialized instruction sets can become viable solutions for such an application domain.
Can Vector Space Bases Model Context ?

Current Information Retrieval models do not directly incorporate context, which is instead managed by means of techniques juxtaposed to indexing or retrieval. In this paper, direct modeling of context is addressed by proposing the full recover of the notion of vector space base, whose role has been understated in the formulation and investigation of the Vector Space Model. A base of a vector space models document or query content descriptors. Moreover the semantics of content descriptors depends on context. Therefore a baseof a vector space is the construct to model context . Also, change of context can be modeled by linear transformations from one base to another. Matrix algebra can thus by employed to process context, its evolution and application. In particular, Relevance Feedback is shown to be an example of context change.
CMOS Wide-Bandwidth Magnetic Sensors for Contactless Current Measurements

This Ph.D. dissertation describes the theory and realization of wide-bandwidth magnetic sensors for current measurements which breach the conventional offset and noise constraints in CMOS processes. These are achieved by several circuit-level and system-level innovations, including the use of three orthogonal ripple reduction loops (RRLs) in spinning-current Hall sensors, a multipath architecture with double Hall sensors, and a hybrid magnetic sensor system combining Hall sensors and pick-up coils. The prototypes with these techniques have advanced the bandwidth of state-of-the-art CMOS magnetic sensors by more than two orders of magnitude.
New polarimetric SAR processors based on signal and interference subspace models

We develop in this paper new polarimetric SAR processors based on signal and interference subspaces model. These processors aim at using models with physical and polarimetric scattering properties not exploited by the isotropic point model. Our goal is to increase the response of the target and decrease the response of the interferences. These processors are implemented by computing the corresponding target and interference subspaces. Results on FOPEN simulated data with realistic target show the interest and the limits of these new processors.
Adamts18 deficiency promotes colon carcinogenesis by enhancing β-catenin and p38MAPK/ERK1/2 signaling in the mouse model of AOM/DSS-induced colitis-associated colorectal cancer

ADAMTS18 is a novel tumor suppressor and is critical to the pathology of human colorectal cancer. However, the underlying mechanism is not clear. Here we generated an Adamts18-deficient mouse strain as an in vivo model to investigate the role of ADAMTS18 in the pathogenesis of colorectal cancer. In AOM/DSS–induced colitis-associated colorectal cancer, the deficiency of Adamts18 in mice resulted in enhanced tumorigenesis and colon inflammation that could be attributed in part to enhanced nuclear translocation of β-catenin and elevated expression of its downstream target genes, cyclin D1 and c-myc. Moreover, increased p38MAPK and ERK1/2 activities were detected in colon cancer cells from Adamts18-deficient mice. Further studies revealed that ADAMTS18 deficiency reduced intestinal E-cadherin levels in mice, which ultimately led to intestinal barrier dysfunction. These data indicate that Adamts18 deficiency enhances tumorigenesis and intestinal inflammation through elevated Wnt/β-catenin and p38MAPK/ERK1/2 signaling and promotes colon cancer in this mouse model.
Semi-supervised Collaborative Clustering with Partial Background Knowledge

In this paper we present a new algorithm for semisupervised clustering. We assume to have a small set of labeled samples and we use it in a clustering algorithm to discover relevant patterns. We study how our algorithm works against two other semisupervised algorithms when the data are multimodal. Then, we study the case where the user is able to produce few samples for some classes but not for each class of the dataset. Indeed, in complex problems, the user is not always able to produce samples for each class present in the dataset. The challenging task is consequently to use the set of labeled samples to discover other members of these classes, but also to keep a degree of freedom to discover unknown clusters, for which samples are not available. We address this problem through a series of experimentations on synthetic datasets, to show the relevance of the proposed method.
Contemporaneous and longitudinal prediction of children's social functioning from regulation and emotionality.

Relations of regulation and emotionality to social functioning were examined for 77 children followed from early to middle school age. Parents and teachers reported on children's social behavior, emotionality, and regulation, and children engaged in analogue peer conflict situations (i.e., with puppets). High-quality social functioning was predicted by high regulation and low levels of nonconstructive coping, negative emotionality, and general emotional intensity. Prediction often was obtained across reporters and time, although prediction was strongest within context (home versus school). Moreover, measures of regulation and emotionality frequently contributed unique variance to the prediction of social functioning. Contemporaneous correlations at age 8-10 were similar to those obtained at age 6-8, and prediction of later social functioning from emotionality and regulation at age 4-6 was similar at ages 6-8 and 8-10.
The Internet Topology Zoo

The study of network topology has attracted a great deal of attention in the last decade, but has been hampered by a lack of accurate data. Existing methods for measuring topology have flaws, and arguments about the importance of these have overshadowed the more interesting questions about network structure. The Internet Topology Zoo is a store of network data created from the information that network operators make public. As such it is the most accurate large-scale collection of network topologies available, and includes meta-data that couldn't have been measured. With this data we can answer questions about network structure with more certainty than ever before - we illustrate its power through a preliminary analysis of the PoP-level topology of over 140 networks. We find a wide range of network designs not conforming as a whole to any obvious model.
Toward Precision Tests of General Relativity with Black Hole X-Ray Reflection Spectroscopy

Astrophysical black hole systems are the ideal laboratories for testing Einstein’s theory of gravity in the strong field regime. We have recently developed a framework that uses the reflection spectrum of black hole systems to perform precision tests of general relativity by testing the Kerr black hole hypothesis. In this paper, we analyze XMM-Newton and NuSTAR observations of the supermassive black hole in the Seyfert 1 galaxy MCG–06–30–15 with our disk reflection model. We consider the Johannsen metric with the deformation parameters α13 and α22, which quantify deviations from the Kerr metric. For α22 = 0, we obtain the black hole spin and . For α13 = 0, we obtain and . The Kerr solution is recovered for α13 = α22 = 0. Thus, our results include the Kerr solution within statistical uncertainties. Systematic uncertainties are difficult to account for, and we discuss some issues in this regard.
Improving image registration by correspondence interpolation

This paper presents how using a correspondence-based interpolation scheme for 3D image registration improves the registration accuracy. The interpolator takes into account correspondences across slices, which is an advantage, particularly when the volume has thick slices, and where anatomies lie non-parallel to the slice direction. We use our previously presented approach for correspondence-based interpolation and demonstrate results on two different datasets, brain and cardiac MRI. The results are evaluated (i) qualitatively by examination of gradient images and cardiac pig atlases and (ii) quantitatively by registering downsampled brain data using two different interpolators and subsequently applying the deformation fields to the original data. The results show that the interpolator provides better gradient images and a more sharp cardiac atlas. Moreover, it provides better deformation fields on downsampled data, increasing the registration accuracy of original data to 5.8% on average with respect to a standard interpolator.
Deploying PaaS for Accelerating Cloud Uptake in the Guifi Community Network

Community networks is an emerging model in which communities of citizens build and own open shared networks. But currently, cloud computing infrastructures, common in today's Internet, hardy exist in community networks. We present in this paper our approach for bringing clouds into community networks. The main element of our strategy for achieving cloud uptake is the deployment of the Guifi-Community-Distribution (GCODIS) on all cloud nodes, a distribution containing common services and applications. We argue in the paper the reasons why this approach is appropriate for the scenario of community networks, where the user acceptance needs to be gained. We show the steps and the on-going process with which we actually implement our approach in the Guifi community network. With these key elements in place, we conclude that we are closer to the vision that the users of community networks ultimately will not need to consume cloud applications from the Internet, but find them within the community network. An interesting open issue is to what extend our approach can be applied to the more generic volunteer computing scenario.
Interactive terrain modeling using hydraulic erosion

We present a step toward interactive physics-based modeling of terrains. A terrain, composed of layers of materials, is edited with interactive modeling tools built upon different physics-based erosion and deposition algorithms. First, two hydraulic erosion algorithms for running water are coupled. Areas where the motion is slow become more eroded by the dissolution erosion, whereas in the areas with faster motion, the force-based erosion prevails. Second, when the water under-erodes certain areas, slippage takes effect and the river banks fall into the water. A variety of local and global editing operation is provided. The user has a great level of control over the process and receives immediate feedback since the GPU-based erosion simulation runs at least at 20 fps on off-the-shelf computers for scenes with grid resolution of 2048 x 1024 and four layers of material. We also present a divide and conquer approach to handle large terrain erosion, where the terrain is tiled, and each tile calculated independently on the GPU. We show a wide variety of erosion-based modeling features such as forming rivers, drying flooded areas, rain, interactive manipulation with rivers, spring, adding obstacles into the water, etc.
Control-Plane based Failure Detection for Highly Available Software-Defined Network

To ensure high availability, redundancies such as active/standby controllers have been adopted on production SDN networks. However, the complex functionalities embodied by a SDN network make it difficult to ascertain the presence of failures. Not all failures will exhibit as component crashes to be captured by heartbeat-based failure detectors. We propose a novel failure detector for SDN network based on transparent monitoring of control-plane messages and real-time modeling of network state. By detecting deviation of the model, the proposed failure detector is capable of detecting a wide range of failures. The detector does not depend on specific SDN applications or controllers. We implemented a prototype for OpenFlow-based [3] SDN network and provide the preliminary results confirming the feasibility of a control-plane based failure detector.
Network-on-Chip multicasting with low latency path setup

A low-latency path setup approach with multiple setup packets for parallel set is presented. It reduces the header overhead compared to multiaddress encoding. Further, we propose four variants of deadlock-free multicast routing algorithms using different subpath generation methods, different destination partitioning, and channel sharing strategies. Experimental results show that the quatuor partitions path-like tree outperforms other algorithms.
Molecular characterization of turkey enteric reovirus S3 gene

The molecular diversity in S3 gene sequences of turkey reovirus (TRV) was determined in poult enteritis syndrome (PES)-affected and apparently healthy turkey poults. Twenty-nine TRV-positive samples (15 from PES-affected flocks and 14 from apparently healthy flocks) were tested using self-designed primers for the S3 gene. Phylogenetic analysis revealed that the TRV S3 sequences of this study clustered in clade III and formed two different groups in this clade. The avian reoviruses from duck and goose formed clade I and those from chickens formed clade II. The clade III TRV sequences had a nucleotide percent identity of 88.9 to 100% among themselves but only of 59.5 to 63.5% and 69.2 to 72.6% with clades I and II, respectively. More amino acid substitutions were present in TRVs from PES-affected flocks than in those from apparently healthy flocks using ATCC VR-818 (AY444912) as a benchmark. All TRVs of this study showed substitutions at positions 244 and 285. The impact of these changes on the virulence of the virus, if any, needs to be studied.
Segmentation of Review Texts by using Thesaurus and Corpus-based Word Similarity

Recently, we can refer to user reviews in the shopping or hotel reservation sites. However, with the exponential growth of information of the Internet, it is becoming increasingly difficult for a user to read and understand all the materials from a large-scale reviews that is potentially of interest. In this paper, we propose a method for review texts segmentation by guest’s criteria, such as service, location and facilities. Our system firstly extracts words which represent criteria from hotel review texts. We focused on topic markers such as “ha” in Japanese to extract guest’s criteria. The extracted words are classified into classes with similar words. The classification is proceeded by using Japanese WordNet. Then, for each hotel, each text with all of the guest reviews is segmented into word sequence by using criteria classes. Review text segmentation is difficult because of short text. We thus used Japanese WordNet, extracted similar word pairs, and indexes of Wikipedia. We performed text segmentation of hotel review. The results showed the effectiveness of our method and indicated that it can be used for review summarization by guest’s criteria.
Expression and Functional Characterization of Membrane-Integrated Mammalian Corticotropin Releasing Factor Receptors 1 and 2 in Escherichia coli

Corticotropin-Releasing Factor Receptors (CRFRs) are class B1 G-protein-coupled receptors, which bind peptides of the corticotropin releasing factor family and are key mediators in the stress response. In order to dissect the receptors' binding specificity and enable structural studies, full-length human CRFR1α and mouse CRFR2β as well as fragments lacking the N-terminal extracellular domain, were overproduced in E. coli. The characteristics of different CRFR2β -PhoA gene fusion products expressed in bacteria were found to be in agreement with the predicted ones in the hepta-helical membrane topology model. Recombinant histidine-tagged CRFR1α and CRFR2β expression levels and bacterial subcellular localization were evaluated by cell fractionation and Western blot analysis. Protein expression parameters were assessed, including the influence of E. coli bacterial hosts, culture media and the impact of either PelB or DsbA signal peptide. In general, the large majority of receptor proteins became inserted in the bacterial membrane. Across all experimental conditions significantly more CRFR2β product was obtained in comparison to CRFR1α. Following a detergent screen analysis, bacterial membranes containing CRFR1α and CRFR2β were best solubilized with the zwitterionic detergent FC-14. Binding of different peptide ligands to CRFR1α and CRFR2β membrane fractions were similar, in part, to the complex pharmacology observed in eukaryotic cells. We suggest that our E. coli expression system producing functional CRFRs will be useful for large-scale expression of these receptors for structural studies.
Measurements of the neutron dose equivalent for various radiation qualities, treatment machines and delivery techniques in radiation therapy

In radiation therapy, high energy photon and proton beams cause the production of secondary neutrons. This leads to an unwanted dose contribution, which can be considerable for tissues outside of the target volume regarding the long term health of cancer patients. Due to the high biological effectiveness of neutrons in regards to cancer induction, small neutron doses can be important. This study quantified the neutron doses for different radiation therapy modalities. Most of the reports in the literature used neutron dose measurements free in air or on the surface of phantoms to estimate the amount of neutron dose to the patient. In this study, dose measurements were performed in terms of neutron dose equivalent inside an anthropomorphic phantom. The neutron dose equivalent was determined using track etch detectors as a function of the distance to the isocenter, as well as for radiation sensitive organs. The dose distributions were compared with respect to treatment techniques (3D-conformal, volumetric modulated arc therapy and intensity-modulated radiation therapy for photons; spot scanning and passive scattering for protons), therapy machines (Varian, Elekta and Siemens linear accelerators) and radiation quality (photons and protons). The neutron dose equivalent varied between 0.002 and 3 mSv per treatment gray over all measurements. Only small differences were found when comparing treatment techniques, but substantial differences were observed between the linear accelerator models. The neutron dose equivalent for proton therapy was higher than for photons in general and in particular for double-scattered protons. The overall neutron dose equivalent measured in this study was an order of magnitude lower than the stray dose of a treatment using 6 MV photons, suggesting that the contribution of the secondary neutron dose equivalent to the integral dose of a radiotherapy patient is small.
Taxonomy and genetic divergence of Paranoplocephala kalelai (Tenora, Haukisalmi et Henttonen, 1985) (Cestoda, Anoplocephalidae) in the grey-sided vole Myodes rufocanus in northern Fennoscandia

Paranoplocephala kalelai (Tenora, Haukisalmi et Henttonen, 1985) is an anoplocephalid cestode that primarily parasitizes the grey-sided vole Myodes rufocanus (syn. Clethrionomys rufocanus) in northern Fennoscandia. In a preliminary molecular phylogenetic analysis, the cytochrome oxidase I (mtDNA) sequences of P. kalelai formed two divergent sublineages originating from two different localities in northern Finland and northern Norway. The present data confirm the existence of two strongly supported clades and show that their geographic distributions are overlapping in northernmost Finland. Relatively deep genetic divergence and coexistence of the two main clades at one of the localities suggest that the material may include two biological species. However, because the specimens representing the two mtDNA clades of P. kalelai are not morphometrically sufficiently differentiated and because the mtDNA clade of the specimens from the type locality is unknown, they are not assigned to different species. Comparison with the existing phylogeographic data of M. rufocanus suggests that the genetic structure of this host-specific cestode reflects the glacial and post-glacial history of its primary host. A redescription is presented for P. kalelai.