Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of virtual optical bus networks: A heuristic approach

We study the design of virtual optical bus (VOB) network, which has been recently proposed as a packet-oriented all-optical solution for transport networks. Design of a VOB network consists of grouping all edge-to-edge flows in the network into clusters called VOBs and that has to be done with the objective of minimizing packet collision rate in the optical network. We present an efficient heuristic algorithm, which can be utilized in networks with both ring and arbitrary meshed topology to find near optimal solutions to the VOB network design problem. Several design examples are presented and the results are compared to those obtained by applying a linear-programming-based design method. The comparisons show that the algorithm can find comparable solutions-in terms of network performance-in a much less amount of time.
Effects of well-boat transportation on the muscle pH and onset of rigor mortis in Atlantic salmon

During the transport of salmon (Salmo salar), in a well-boat, 10 fish were sampled at each of six stages: in cages after crowding at the farm (stage 1), in the well-boat after loading (stage 2), in the well-boat after eight hours transport and before unloading (stage 3), in the resting cages immediately after finishing unloading (stage 4), after 24 hours resting in cages, (stage 5) and in the processing plant after pumping from the resting cages (stage 6). The water in the well-boat was at ambient temperature with recirculation to the sea. At each stage the fish were stunned percussively and bled by gill cutting. Immediately after death, and then every three hours for 18 hours, the muscle pH and rigor index of the fish were measured. At successive stages the initial muscle pH of the fish decreased, except for a slight gain in stage 5, after they had been rested for 24 hours. The lowest initial muscle pH was observed at stage 6. The fishes' rigor index showed that rigor developed more quickly at each successive stage, except for a slight decrease in rate at stage 5, attributable to the recovery of muscle reserves.
A Physical Measurement-Based Sybil Nodes Detection Mechanism in VANETs

In traffic safety applications of Vehicular Ad-hoc Networks (VANETs), security is a very important issue. Sybil attack is a particular attack where the attacker illegitimately claims multiple identities. In the past, several approaches have been proposed to solve this problem. They are categorized into PKI-based, infrastructure-based, observer-based, and resourcetesting-based schemes. In this paper, existing protocols are analyzed, and a novel scheme for detecting the Sybil nodes in VANETs is presented, reducing the effect of a Sybil attack. The proposed Sybil nodes-detection scheme, Physical MeasurementBased Sybil Nodes Detection Mechanism in VANETs (PMSD), takes advantage of physical measurements of the beacon message instead of key-based materials, which not only solves the Sybil attack problem, but also reduces the overhead of detection. The proposed scheme has no fixed infrastructure, which makes it easier to implement. The simulation results show a 95% detection rate of Sybil nodes, with only about a 4% error rate. Keywords—VANETs, Sybil Attack, Physical Measurement,
Process noise identification based particle filter: An efficient method to track highly maneuvering target

In this paper, a novel method, process noise identification based particle filter is proposed for tracking highly maneuvering target. In the proposed method, the equivalent-noise approach is adopted, which converts the problem of maneuvering target tracking to that of state estimation in the presence of non-stationary process noise with unknown statistics. A novel method for identifying the non-stationary process noise is proposed in the particle filter framework. Compared with the multiple model approaches for maneuvering target tracking, the proposed method needs to know neither the possible multiple models nor the transition probability matrices. One simple dynamic model is adopted during the whole tracking process. The proposed method is especially suitable for tracking highly maneuvering target due to its capability of dealing with sample impoverishment, which is a common problem in particle filter and becomes serious when tracking large uncertain dynamics.
Collaborative Deep Reinforcement Learning for Joint Object Search

We examine the problem of joint top-down active search of multiple objects under interaction, e.g., person riding a bicycle, cups held by the table, etc. Such objects under interaction often can provide contextual cues to each other to facilitate more efficient search. By treating each detector as an agent, we present the first collaborative multi-agent deep reinforcement learning algorithm to learn the optimal policy for joint active object localization, which effectively exploits such beneficial contextual information. We learn inter-agent communication through cross connections with gates between the Q-networks, which is facilitated by a novel multi-agent deep Q-learning algorithm with joint exploitation sampling. We verify our proposed method on multiple object detection benchmarks. Not only does our model help to improve the performance of state-of-the-art active localization models, it also reveals interesting co-detection patterns that are intuitively interpretable.
Curcumin and EGCG Suppress Apurinic/Apyrimidinic Endonuclease 1 and Induce Complete Remission in B-cell Non-Hodgkin's lymphoma Patients

Background: Follicular lymphoma (FL) is the most common subtype of indolent lymphoma. FL is still considered to be an incurable disease and palliation of symptoms is an acceptable approach to the expected pattern of repeated relapses due to developing resistance to chemotherapy agents. Apurinic/apyrimidinic endonuclease/redox factor-1 (APE1/Ref-1) is a multifunctional protein involved in DNA base excision repair (BER) of oxidative DNA damage and in redox regulation of a number of transcription factors. It was observed that cytoplasmic APE1 induced COX-2 expression through NF-κB activation. It has been shown that chemopreventive agents potentiate the efficacy of chemotherapy through the regulation of multiple signaling pathways, including NF-κB, c-Myc, cyclooxygenase-2, apoptosis, and others, suggesting a multitargeted nature of chemopreventive agents. We hypothesized that curcumin, a polyphenolic antioxidant derived from the spice turmeric, and epigallocatechin gallate (EGCG) from green tea would potentiate the effect of chemotherapy in B-cell lymphoma. Objective: We examined the role of human apurinic/apyrimidinic endonuclease 1 (APE1) in resistance and prognosis in patients with FL. Our major objective was to update the safety and efficacy results of the antitumor effect of combination of curcumin and EGCG therapy in relapsed or resistant indolent or transformed non-Hodgkin follicular lymphoma patients and their peripheral blood mononuclear cells (PBMCs) compared with healthy donors’ controls.
Dynactin Function in Mitotic Spindle Positioning

Dynactin is a multisubunit protein complex necessary for dynein function. Here, we investigated the function of dynactin in budding yeast. Loss of dynactin impaired movement and positioning of the mitotic spindle, similar to loss of dynein. Dynactin subunits required for function included p150Glued, dynamitin, actin‐related protein (Arp) 1 and p24. Arp10 and capping protein were dispensable, even in combination. All dynactin subunits tested localized to dynamic plus ends of cytoplasmic microtubules, to stationary foci on the cell cortex and to spindle pole bodies. The number of molecules of dynactin in those locations was small, less than five. In the absence of dynactin, dynein accumulated at plus ends and did not appear at the cell cortex, consistent with a role for dynactin in offloading dynein from the plus end to the cortex. Dynein at the plus end was necessary for dynactin plus‐end targeting. p150Glued was the only dynactin subunit sufficient for plus‐end targeting. Interactions among the subunits support a molecular model that resembles the current model for brain dynactin in many respects; however, three subunits at the pointed end of brain dynactin appear to be absent from yeast.
Stability and plasticity in self-organized networks

– Despite some research on self-management and self-organization, the control and the coordination of an organization without hierarchy remains a mysterious phenomenon. However, the dissemination of the responsibilities and the decentralized decisions in a business network require improving our knowledge in this field. From this theoretical point of view, our article aims to explore the modes of development and regulation of the networks not supervised. After having underlined the difficulties of empirical observation at the origin of the modeling attempts, we put forward the idea according to which a network without pilot is pulled about two tensions: stability and plasticity. Indeed, to mitigate the problems of internal coherence, it is led to evolve towards a more stable form and thus more hierarchical. But, in the absence of central coordination unit, it is also directed towards a more unstable form, based on the flexibility of the embedded connections. Classification Codes: M10.
A prediction model for progressive disease in systemic sclerosis

Objective To develop a model that assesses the risk for progressive disease in patients with systemic sclerosis (SSc) over the short term, in order to guide clinical management. Methods Baseline characteristics and 1 year follow-up results of 163 patients with SSc referred to a multidisciplinary healthcare programme were evaluated. Progressive disease was defined as: death, ≥10% decrease in forced vital capacity, ≥15% decrease in diffusing capacity for carbon monoxide, ≥10% decrease in body weight, ≥30% decrease in estimated-glomerular filtration rate, ≥30% increase in modified Rodnan Skin Score (with Δ≥5) or ≥0.25 increase in Scleroderma Health Assessment Questionnaire. The number of patients with progressive disease was determined. Univariable and multivariable logistic regression analyses were used to assess the probability of progressive disease for each individual patient. Performance of the prediction model was evaluated using a calibration plot and area under the receiver operating characteristic curve. Results 63 patients had progressive disease, including 8 patients who died ≤18 months after first evaluation. Multivariable analysis showed that friction rubs, proximal muscular weakness and decreased maximum oxygen uptake as % predicted, adjusted for age, gender and use of immunosuppressive therapy at baseline, were significantly associated with progressive disease. Using the prediction model, the predicted chance for progressive disease increased from a pretest chance of 37% to 67–89%. Conclusions Using the prediction model, the chance for progressive disease for individual patients could be doubled. Friction rubs, proximal muscular weakness and maximum oxygen uptake as % predicted were identified as relevant parameters.
A Wavelet Based Method to Modeling Realistic Flexible Robots

Abstract In this paper a modular, computationally efficient, and numerically stable method is presented, which allows to obtain the dynamic model of a robot constituted by flexible links having variable cross-section and subjected to generic ending forces and torques and to the gravity actions. This method is based on the use of admissible deformation functions of wavelet type, obtained by using the Instantaneity Principle of the deflection of an element, and it is based on the Euler-Bernoulli beam theory if the link is slender or, otherwise, on the Timoshenko one. Moreover, it is easy to extend the presented methodology to deal also with the case of large link deformations. The proposed modeling methodology guarantees no static error independently of the number of wavelet functions per link, both in the presence of generic forces and torques at both ends, for generic cross-section profiles, and in the presence of gravity actions, for several cross-section ones; moreover, it guarantees good dynamic performance in a frequency range which increases when the number of wavelet functions increases. It is shown that the presented methodology is also more efficient and numerically stable than other modeling methods known in literature. In this paper some significant examples are presented which illustrate the properties of the proposed methodology; they also show that the proposed modeling methodology is an advisable choice when it is necessary to obtain high precisions, in particular at low frequencies, and/or not prohibitive calculus time, and/or when other modeling methods result inapplicable because of numerical divergence problems.
A solution model for Service-oriented architecture

SOA (service-oriented architecture) solution model involves SOA associated reference architecture, e-commerce patterns, methodologies and best practices ranging from the beginning to the end of a complete SOA project. A new solution model is presented. Service is the kernel and process is the breakthrough point of business innovation in this model. A series of widely acceptable standards, such as SDO (service data object), SCA (service component architecture) and BPEL (business process execution language), are adopted in this model. Analysis, design, implementation and management methodologies and best practices are covered in this model. By analyzing the characteristic, mechanism and function of the model, we give a real-world example to illustrate how this solution model can be used in practice.
Best Linear Unbiased Allele‐Frequency Estimation in Complex Pedigrees

Summary. Many types of genetic analyses depend on estimates of allele frequencies. We consider the problem of allele‐frequency estimation based on data from related individuals. The motivation for this work is data collected on the Hutterites, an isolated founder population, so we focus particularly on the case in which the relationships among the sampled individuals are specified by a large, complex pedigree for which maximum likelihood estimation is impractical. For this case, we propose to use the best linear unbiased estimator (BLUE) of allele frequency. We derive this estimator, which is equivalent to the quasi‐likelihood estimator for this problem, and we describe an efficient algorithm for computing the estimate and its variance. We show that our estimator has certain desirable small‐sample properties in common with the maximum likelihood estimator (MLE) for this problem. We treat both the case when parental origin of each allele is known and when it is unknown. The results are extended to prediction of allele frequency in some set of individuals S based on genotype data collected on a set of individuals R. We compare the mean‐squared error of the BLUE, the commonly used naive estimator (sample frequency) and the MLE when the latter is feasible to calculate. The results indicate that although the MLE performs the best of the three, the BLUE is close in performance to the MLE and is substantially easier to calculate, making it particularly useful for large complex pedigrees in which MLE calculation is impractical or infeasible. We apply our method to allele‐frequency estimation in a Hutterite data set.
The Two Micron All Sky Survey (2MASS)

Between 1997 June and 2001 February the Two Micron All Sky Survey (2MASS) collected 25.4 Tbytes of raw imaging data covering 99.998% of the celestial sphere in the near-infrared J (1.25 μm), H (1.65 μm), and Ks (2.16 μm) bandpasses. Observations were conducted from two dedicated 1.3 m diameter telescopes located at Mount Hopkins, Arizona, and Cerro Tololo, Chile. The 7.8 s of integration time accumulated for each point on the sky and strict quality control yielded a 10 σ point-source detection level of better than 15.8, 15.1, and 14.3 mag at the J, H, and Ks bands, respectively, for virtually the entire sky. Bright source extractions have 1 σ photometric uncertainty of <0.03 mag and astrometric accuracy of order 100 mas. Calibration offsets between any two points in the sky are <0.02 mag. The 2MASS All-Sky Data Release includes 4.1 million compressed FITS images covering the entire sky, 471 million source extractions in a Point Source Catalog, and 1.6 million objects identified as extended in an Extended Source Catalog.
Bluetooth -model analysis and simulation using NS2

Bluetooth-based devices become very popular nowadays with boom in mobile phone market. This paper investigates ad-hoc communication network architecture where a set of Bluetooth devices are connected to each others, and allowing possible location based services. An implementation using master-slave configuration and OpenLAPI open source has been achieved. Besides, in order to test the network parameters, a simulation using NS-2 framework has been successfully implemented.
Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data

This paper presents a comparison of three different speaker recognition methods deployed in a broadcast news processing system. We focus on how the generative and discriminative nature of these methods affects the speaker recognition framework and we also deal with intersession variability compensation techniques in more detail, which are of great interest in broadcast processing domain. Performed experiments are specific particularly for the very limited amount of data used for both speaker enrollment (typically ranging from 30 to 60 seconds) and recognition (typically ranging from 5 to 15 seconds). Our results show that the system based on Gaussian Mixture Models (GMMs) outperforms both systems based on Support Vector Machines (SVMs) but its drawback is higher computational cost.
An Ultra-Wideband Twin-Patch Monopole Antenna with Band-Rejection Characteristic

To suppress electromagnetic interference at 5.5-GHz WLAN (5.15-5.825 GHz) band operation, a novel ultra-wideband (UWB) design of a slotted twin-patch monopole antenna with a band-rejection characteristic is presented. The proposed antenna with a simple structure has a large impedance bandwidth, defined by 10-dB return loss, covering the range from 2.95 to 10.85 GHz, and a tunable cutoff band from 5.18 to 6 GHz for band-operation suppression. Measured monopole-like radiation pattern and in-band average gain of about 2.3 dBi have also been obtained, simultaneously, with good agreement to the simulated results.
Monetary Policy in Retrospective: A Taylor Rule Inspired Exercise

A time varying backward-looking Taylor rule, that is, a Taylor rule in which the coefficients change over time is estimated over the period 1954-2003 using historically revised data and the years 1965-1998 using real time (unrevised) data. The findings seem to show that during the 1970s a first attempt was made in order to respond to inflation, but later policymakers seemed to stop trying. The change to a higher response to inflation was a gradual one and reached its peak in 1982. After that, the response was consistent and along the lines of the Taylor principle. Also, estimation of an alternative specification in which the chairman and election years' effects are explicitly taken care of provides evidence in favor of time variation in the inflation coefficient regardless of the type of data used. The latter indicates that instability in the monetary policy reaction function is explained by reasons that go beyond the type of data used, who the Chairman of the FOMC is, and election years.
Serum Biomarkers in Patients with Relapsing Eosinophilic Granulomatosis with Polyangiitis (Churg-Strauss)

Introduction Previous studies suggest a role for eotaxin-3, TARC/CCL17 and IgG4 in newly- diagnosed patients with eosinophilic granulomatosis with polyangiitis (EGPA, Churg-Strauss) with highly active disease. The role of these biomarkers in relapsing disease is unclear. Methods Serum levels of TARC/CCL17, eotaxin-3, IgG4, and IgG4/IgG ratio were determined in serum samples from a longitudinal cohort of patients with EGPA (105 visits of 25 patients). Epidemiological, clinical and laboratory data were available for all visits. Results At the first visit, 80% of patients were using glucocorticoids and 68% additional immunosuppressive drugs. Disease flares were seen at 18 visits. The median BVAS and BVAS/WG scores at time of relapse were 4 and 2, respectively. None of the biomarkers tested were useful to discriminate between active disease and remission. Patients treated with prednisone had lower eotaxin-3 and eosinophil levels compared to patients not taking glucocorticoids irrespective of disease activity. Use of immunosuppressive agents was not associated with biomarker levels. Conclusions Serum levels of TARC/CCL17, eotaxin-3, IgG4, and IgG4/IgG ratio do not clearly differentiate active and inactive disease in established EGPA. Defining biomarkers in EGPA remains a challenge especially during times of glucocorticoid use.
Sum rate capacity for orthogonal random beamforming in multi-cell MIMO scenarios

In multiple-antenna broadcast channels, orthogonal random beamforming (ORB) constitutes an effective mean to exploit multi-user diversity (MUD) for its inherent opportunistic attribute. However, most of recent papers just consider the single-cell hypothesis in which case multi-cell interference is completely neglected. In order to conform to the wireless environment in reality, a multi-cell model employing ORB scheme is proposed in this paper. Based on the nonquantized signal to interference plus noise ratio (SINR) feedback model, a closed-form expression of theory limit for sum rate capacity is proposed. The theory limit of single-cell model is proved to be a special case of our proposed model. Furthermore, the fairness of our model in interference limited system can be improved distinctly than that of single-cell model, at the decreasing cost of sum rate capacity. Simulation results show that the proposed model has more rationality and generality compared with single-cell model.
Structure-from-motion : factorization method

Last lecture we looked at a structure from motion method that used two adjacent frames in a video. It was assumed that the instantaneous motion vectors could be computed reliably at many points, especially points near depth discontinuities. It was also assumed that the field of view was large so that the camera rotation field was not parallel i.e. second order terms were significant. Finally, it was also assumed that perspective effects were significant, namely there were large variations in depths; specifically, large differences in inverse depths at depth discontinuities which gave parallax information. The above conditions are met in many situations, but certainly not all situations. Today we will look at a scenario that is quite different, and that needs a very different approach-now called Tomasi-Kanade factorization 1. Here is what we assume: • F image frames (not just 2). Normally one collects many frames using a video camera. • N corresponding points (x ki , y ki), i = 1, /dots, N that are visible in each frame k. Typically, these points are detected and tracked from frame to frame. We have not discussed the problem of tracking a point – but we have discussed how to find interest points (Harris corners) and how to register two images. So you can imagine that we could find the motion of an interest point from one frame to the next. That is basically the tracking problem.