Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of immunological markers and continuous‐time Markov models to estimate progression of HIV infection in homosexual men

Objectives We used continuous-time Markov models based on CD4 cell counts and anti-CD3 reactivity (i.e., measure for T-cell quality) to study the progression of HIV infection in a cohort study of homosexual men in Amsterdam. We also compared the effectiveness of anti-CD3 reactivity as a marker for disease progression with that of CD4 cell counts. Methods We used data from 467 men (6905 visits) with visits at 3-month intervals between October 1984 and March 1993. To account for measurement error and short time-scale variability, the immunological stage at each visit was determined using a kernel smoother on log-transformed data from each individual. The Markov model had six marker-defined stages and a seventh stage for clinical AIDS. The initial stage-occupation probabilities for seroconverters were used to estimate the incubation time from infection to AIDS. Confidence intervals were calculated using the bootstrap method to account for the effect of smoothing on the variability of our estimates. Results The CD4 staging scheme estimated the median time from seroconversion to AIDS at 8.3 years [95% confidence interval (Cl), 8.1–8.6], and a similar estimate was obtained with the anti-CD3 staging model. The CD4 model predicts that 10.2% (95% Cl, 9.9–13.1) will remain AIDS-free 15 years after seroconversion. The mean number of stages visited before AIDS is lower with the CD4 model (7.4; 95% Cl, 7.2–7.7) than with theanti-CD3 model (11.3; 95%CI, 10.8–12.0), implying that anti-CD3 predicts progression less well than CD4 cell count. Conclusions CD4 lymphocyte counts and anti-CD3 reactivity are each associated with an increased hazard for progression to AIDS. Therefore, men in different CD4-stages (anti-CD3 stages) follow different incubation period distributions to AIDS. However, anti-CD3 predicts progression less well than CD4 cell count. Staged time-continuous Markov models are useful to study immunological markers for HIV disease progression.
Dynamic Hedging with Stochastic Differential Utility

In this paper we study the dynamic hedging problem using three different utility specifications: stochastic differential utility, terminal wealth utility, and we propose a particular utility transformation connecting both previous approaches. In all cases, we assume Markovian prices. Stochastic differential utility, SDU, impacts the pure hedging demand ambiguously, but decreases the pure speculative demand, because risk aversion increases. We also show that consumption decision is, in some sense, independent of hedging decision. With terminal wealth utility, we derive a general and compact hedging formula, which nests as special all cases studied in Duffie and Jackson (1990). We then show how to obtain their formulas. With the third approach we find a compact formula for hedging, which makes the second-type utility framework a particular case, and show that the pure hedging demand is not impacted by this specification. In addition, with CRRA- and CARA-type utilities, the risk aversion increases and, consequently the pure speculative demand decreases. If futures prices are martingales, then the transformation plays no role in determining the hedging allocation. We also derive the relevant Bellman equation for each case, using semigroup techniques.
A novel technique of privacy preserving association rule mining

Privacy Preserving Association Rule Mining (PPAM) becomes an important issue in recent years. Since data mining alone is not enough to share data between companies without privacy preserving. In this paper, a new technique has been proposed to maintain the confidentiality of the data by fabricating of association rule using a stochastic standard map without returning to mining sensitive data again. The system simulation using Matlab and tested that shows the successful difference between the original data and fabricated. And also been achieved high speed and fewer memory requirements.
Accepted for Publication in Ieee Transactions on Visualization and Computer Graphics 1 Streamline Embedding for 3d Vector Field Exploration

—We propose a new technique for visual exploration of streamlines in 3D vector fields. We construct a map from the space of all streamlines to points in IR n based on the preservation of the Hausdorff metric in streamline space. The image of a vector field under this map is a set of 2-manifolds in IR n with characteristic geometry and topology. Then standard clustering methods applied to the point sets in IR n yield a segmentation of the original vector field. Our approach provides a global analysis of 3D vector fields which incorporates the topological segmentation but yields additional information. In addition to a pure segmentation, the established map provides a natural " parametrization " visualized by the manifolds. We test our approach on a number of synthetic and real-world data sets.
Automatic target detection using binary template matching

This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.
Bridging Common Sense Knowledge Bases with Analogy by Graph Similarity

Present-day programs are brittle as computers are notoriously lacking in common sense. While significant progress has been made in building large common sense knowledge bases, they are intrinsically incomplete and inconsistent. This paper presents a novel approach to bridging the gaps between multiple knowledge bases, making it possible to answer queries based on knowledge collected from multiple sources without a common ontology. New assertions are found by computing graph similarity with principle component analysis to draw analogies across multiple knowledge bases. Experiments are designed to find new assertions for a Chinese commonsense knowledge base using the OMCS ConceptNet and similarly for WordNet. The assertions are voted by online users to verify that 75.77% / 77.59% for Chinese ConceptNet / WordNet respectively are good, despite the low overlap in coverage among the knowledge bases.
Community Event Prediction in Dynamic Social Networks

Communities are fundamental units of every social network, their structure and evolution are essential to understanding the structure and functionality of large networks. Also, community evolution prediction is an important task with various real-life applications in social network analysis. In this paper, we present a framework for modeling community evolution prediction in social networks. Each community is characterized by a wide range of structural features to describe community characteristics and a series of evolutionary events. A community matching algorithm is also proposed to efficiently identify and track similar communities over time. Experiments on different data sets prove that a high rate of community evolution prediction has been achieved.
On infostation density of vehicular networks

Vehicle-to-Vehicle and Vehicle-to-Roadside communications are going to become an indispensable part of the modern day automotive experience. For people on the move, vehicular networks can provide critical network connectivity and access to real-time information. Infestations play a vital role in these networks by acting as gateways to the Internet and by extending network connectivity. In this context, an important question is "What is the minimum number of infestations that need to be deployed in an area in order to support vehicular applications? " Optimizing infostation density is vital to understanding and reducing the cost of deployment and management. In this paper, we examine the required infostation density in a highway scenario using different data dissemination models. We start from a simple analysis that captures the required density under idealized assumptions. We then run detailed QualNet simulations on both controlled and realistic vehicular traces to observe the information density trends in practical environments, and consequently propose techniques to improve dissemination performance and reduce the required infostation density.
The RNA Chaperone Hfq Is Involved in Stress Response and Virulence in Neisseria meningitidis and Is a Pleiotropic Regulator of Protein Expression

ABSTRACT The well-conserved protein Hfq has emerged as the key modulator of riboregulation in bacteria. This protein is thought to function as an RNA chaperone and to facilitate base pairing between small regulatory RNA (sRNA) and mRNA targets, and many sRNAs are dependent on the Hfq protein for their regulatory functions. To address the possible role of Hfq in riboregulated circuits in Neisseria meningitidis, we generated an Hfq mutant of the MC58 strain, and the knockout mutant has pleiotropic phenotypes; it has a general growth phenotype in vitro in culture media, and it is sensitive to a wide range of stresses, including those that it may encounter in the host. Furthermore, the expression profile of a vast number of proteins is clearly altered in the mutant, and we have identified 27 proteins by proteomics. All of the phenotypes tested to date are also restored by complementation of Hfq expression in the mutant strain. Importantly, in ex vivo and in vivo models of infection the Hfq mutant is attenuated. These data indicate that Hfq plays a key role in stress response and virulence, and we propose a major role for Hfq in regulation of gene expression. Moreover, this study suggests that in meningococcus there is a large Hfq-mediated sRNA network which so far is largely unexplored.
Ankle injuries in basketball: injury rate and risk factors

Objectives—To determine the rate of ankle injury and examine risk factors of ankle injuries in mainly recreational basketball players. Methods—Injury observers sat courtside to determine the occurrence of ankle injuries in basketball. Ankle injured players and a group of non-injured basketball players completed a questionnaire. Results—A total of 10 393 basketball participations were observed and 40 ankle injuries documented. A group of non-injured players formed the control group (n = 360). The rate of ankle injury was 3.85 per 1000 participations, with almost half (45.9%) missing one week or more of competition and the most common mechanism being landing (45%). Over half (56.8%) of the ankle injured basketball players did not seek professional treatment. Three risk factors for ankle injury were identified: (1) players with a history of ankle injury were almost five times more likely to sustain an ankle injury (odds ratio (OR) 4.94, 95% confidence interval (CI) 1.95 to 12.48); (2) players wearing shoes with air cells in the heel were 4.3 times more likely to injure an ankle than those wearing shoes without air cells (OR 4.34, 95% CI 1.51 to 12.40); (3) players who did not stretch before the game were 2.6 times more likely to injure an ankle than players who did (OR 2.62, 95% CI 1.01 to 6.34). There was also a trend toward ankle tape decreasing the risk of ankle injury in players with a history of ankle injury (p = 0.06). Conclusions—Ankle injuries occurred at a rate of 3.85 per 1000 participations. The three identified risk factors, and landing, should all be considered when preventive strategies for ankle injuries in basketball are being formulated.
Measurement of residual stresses in vvelded steel joints using hole drilling method

AbstractAn experimental investigation of the residual stresses in three types of welded structural steel joint is presented. A total of twelve specimens was tested. In this investigation, the blind hole-drilling method of ASTM E837 was used–adapted and improvedfor determination of residual stresses.To accountfor the effect of local plasticity due to stress concentration near the drilled hole, new calibration coefficients were obtained by carrying out a series of calibration tests. Then, the residual stresses in the welded joints were determined using the new coefficients. The improved hole drilling method presented in this paper was found to be much less time consuming than the conventional sectioning (saw cutting) method for residual stress measurement. The final results obtained in this study showed good agreement with the residual stresses obtained by previous researchers using the sectioning method.MST/1486
Stackelberg Strategies for Network Design Games

We consider the network-design game introduced by Anshelevich et al. in which n source–destination pairs must be connected by n respective players equally sharing the cost of the used links. It is well known that the price of anarchy for this class of games may be as large as n. One approach for reducing this bound is that of resorting to the Stackelberg model, in which for a subset of at most ⌊αn⌋ coordinated players, with 0⩽α⩽1, communication paths inducing better equilibria are fixed. In this paper we show the effectiveness of Stackelberg strategies by providing optimal and nearly optimal bounds on the performance achievable by such Stackelberg strategies. In particular, in contrast to previous works, we are also able to provide Stackelberg strategies computable in polynomial time and lowering the price of anarchy from n to . Most of the results are extended to the case in which each player aims at connecting k>2 nodes of the network.
Codon Characterization Based on Electrical Response

circuit modeling of biological system is a significant research topic in recent years. Codon is an important element in DNA sequence which is responsible for formation of protein in genes. 64 codons of genes are modeled using MOSFET from elementary level and characterized them based on purine and pyrimidine property. The model is realized in Spice domain and a new genetic code classification table is described based on simulated transient voltage and current responses of purine and pyrimidine bases.The effect of base position is investigated using frequency domain analysis of voltage and phase characteristics of codon electrical circuit. KeywordsDNA, nucleotides electrical model, MOSFET.
Online geometric reconstruction

We investigate a new class of geometric problems based on the idea of online error correction. Suppose one is given access to a large geometric dataset though a query mechanism; for example, the dataset could be a terrain and a query might ask for the coordinates of a particular vertex or for the edges incident to it. Suppose, in addition, that the dataset satisfies some known structural property P (eg, monotonicity or convexity) but that, because of errors and noise, the queries occasionally provide answers that violate P. Can one design a filter that modifies the query's answers so that (i) the output satisfies P; (ii) the amount of data modification is minimized? We provide upper and lower bounds on the complexity of online reconstruction for convexity in 2D and 3D.
Regulatory mechanisms of hepatic microcirculation.

Hepatic microvasculature receives blood from two types of afferent vessels: the terminal portal venule (TPVn) and the terminal hepatic arteriole (THAo). The TPVns directly connect with the capillary bed in the liver parenchyma, which is referred to as sinusoids. Hepatic arterial blood pours into the hepatic sinusoids not only indirectly via the anastomosis between the THAo and the portal venule (PVn), but also directly through the THAo or the capillaries derived from the arterial capillary network around the bile duct. From a regulatory point of view, the hepatic arterial system is considered to be supplementary, but hepatic arterial flow is essential for supplying oxygen to sinusoidal blood flow as well as to the bile ducts, portal venules and nerves in the portal tract. The main regulators of hepatic sinusoidal blood flow are present in the portal venous system. By intravital and scanning electron microscopy, it is evident that a potent vasoconstrictor endothelin (ET)-1 causes a contraction of the SEF via the ET_B receptors, as well as a significant contraction of the PVn and TPVn, resulting in an increase in sinusoidal and pre-sinusoidal microvascular resistance. This phenomenon implies that the TPVn, particularly the transitional part to the sinusoid, would provide an essential regulatory site for hepatic sinusoidal blood flow as an inlet sphincter-like function. The endothelial cell linings along the hepatic sinusoids are characterized by the presence of a large number of sieve plate-like pores, 100 nm in diameter, i.e. the sinusoidal endothelial fenestrae (SEF). The SEF are dynamic structures, forming the racemose invaginations of the endothelial plasma membrane across the endothelium, and regulating not only the permeability of hepatic sinusoids, but also the sinusoidal blood flow by the Ca++ -actomyosin-mediated contraction and dilatation of the SEF. Our recent immunoelectron microscopic and Western blot studies have revealed that caveolin-1, i.e. the principal structural protein of caveolae, and endothelial nitric oxide synthase (eNOS) co-exist in the plasma membrane of the SEF, implying that the SEF may correspond to a permanent (stationary) type of fused and interconnected caveolae, thus contributing to the local control of hepatic sinusoidal blood flow by the regulation of NO synthesis.
Genotypic Drug Resistance and Long-Term Mortality in Patients with Triple-Class Antiretroviral Drug Failure

Objective To examine the prevalence of drug-resistance-associated mutations in HIV patients with triple-drug class virological failure (TCF) and their association with long-term mortality. Design Population-based study from the Danish HIV Cohort Study (DHCS). Methods We included all patients in the DHCS who experienced TCF between January 1995 and November 2004, and we performed genotypic resistance tests for International AIDS Society (IAS)-USA primary mutations on virus from plasma samples taken around the date of TCF. We computed time to all-cause death from date of TCF. The relative risk of death according to the number of mutations and individual mutations was estimated by Cox regression analysis and adjusted for potential confounders. Results Resistance tests were done for 133 of the 179 patients who experienced TCF. The median number of resistance mutations was eight (interquartile range 2–10), and 81 (61%) patients had mutations conferring resistance towards all three major drug classes. In a regression model adjusted for CD4+ T-cell count, HIV RNA, year of TCF, age, gender and previous inferior antiretroviral therapy, harbouring ≥9 versus ≤8 mutations was associated with increased mortality (mortality rate ratio [MRR] 2.3 [95% confidence interval (CI) 1.1–4.8]), as were the individual mutations T215Y (MRR 3.4 [95% CI 1.6–7.0]), G190A/S (MRR 3.2 [95% CI 1.6–6.6]) and V82F/A/T/S (MRR 2.5 [95% CI 1.2–5.3]). Conclusions In HIV patients with TCF, the total number of genotypic resistance mutations and specific single mutations predicted mortality.
A nanometer-resolution displacement measurement system based on laser feedback interferometry

Based on laser feedback interferometry (LFI) combined with phase-freezing technology (PFT), a novel displacement measurement system is demonstrated, which improves the measurement resolution to nanometer scale. The phase modulator is added to modulate the external cavity phase, and the PFT is used for sampling and demodulation. The displacement information of the external target is reconstructed. The signal modulation, sampling, reconstruction technology is researched and the simulation results show the feasibility of the method. Error analysis is made for searching the influence of modulation frequency, sampling frequency and reflector vibration frequency. Verification experiment is made to check the accuracy of the system with appropriate parameters. It provides a displacement and vibration measurement method for MEMS elements.
Regulation of Hepatic Stellate Cell Differentiation by the Neurotrophin Receptor p75NTR

Differentiation of hepatic stellate cells (HSCs) to extracellular matrix– and growth factor–producing cells supports liver regeneration through promotion of hepatocyte proliferation. We show that the neurotrophin receptor p75NTR, a tumor necrosis factor receptor superfamily member expressed in HSCs after fibrotic and cirrhotic liver injury in humans, is a regulator of liver repair. In mice, depletion of p75NTR exacerbated liver pathology and inhibited hepatocyte proliferation in vivo. p75NTR–/– HSCs failed to differentiate to myofibroblasts and did not support hepatocyte proliferation. Moreover, inhibition of p75NTR signaling to the small guanosine triphosphatase Rho resulted in impaired HSC differentiation. Our results identify signaling from p75NTR to Rho as a mechanism for the regulation of HSC differentiation to regeneration-promoting cells that support hepatocyte proliferation in the diseased liver.
The Mecanex system for Multimedia Content Annotation

A system for efficient multimedia content analysis and automatic annotation is presented in this paper. The system is able to identify objects in videos and annotate them with metadata. It includes three modules: the first provides detection and recognition of faces; the second provides generic object detection, based on a deep convolutional neural network; the third provides automated location estimation and landmark recognition based on the state-of-the-art technologies of Bag-of-Words and RANSAC. The system has been developed and successfully tested in the framework of the EC Horizon 2020 Mecanex project, targeting advertising and campaign production markets.
Farmland Scene Classification Based on Convolutional Neural Network

This paper proposed a farmland scene classification method based on CNN (Convolutional neural network). The farmland image datasets are divided into 4 types, namely, Crops_field, House_field, Not_farming_field and Woods_field. There are 100 pictures in each type, 80 images in each type are used as training sets, and the remaining 20 images are processed as test sets. Design a CNN with 2 convolution layers and 2 sub sample layers.In the training process, input images are restricted to 64*64, and the convolutional kernel is 5*5. Use the opensource toolkit of deep learning namely Tensorflow as the realization platform. After 700 times trainings, we validated the effects on the dataset, The corresponding correct rates of the four scenes are 79%,82%,76% and 75%. The result show that this method can achieve satisfactory effect. Keywords—deep neural network;deep learning;CNN;feature extraction