Miracle-dz/UniFAR-FTUs huggingface dataset:
Jointly Compatible Pair Linking for Visual Tracking with Probabilistic Priors

Video sequences of real-world situations are often difficult to track with machine vision. Scenes frequently contain visual clutter, repetitive textures and occlusions that make online visual feature tracking difficult. If the camera is allowed to shake or moving objects are present, the exponential search-space of potential feature matches rapidly becomes intractable for real-time applications. In this paper we introduce "Jointly Compatible Pair Linking" (JCPL), an algorithm that efficiently and deterministically identifies the most globally consensual set of feature-measurement matches in tracking problems with probabilistic priors. We demonstrate JCPL as part of a two-stage visual tracking algorithm, showing it correctly resolving significant matching ambiguities in sequences with highly dynamic camera motion while robustly ignoring moving scene objects. In these experiments we show JCPL and the two-stage tracker evaluating a fixed number of tests in an exponential search-space. In one experiment JCPL tested less than 1/200th of the total search space and executed 4.6 times faster than the current gold-standard algorithm "Joint Compatibility Branch and Bound" (JCBB). Given highly ambiguous sequences we show JCPL tracking successfully while standard JCBB chooses incorrect matches and fails. Throughout our experiments the number of costly image matching operations are minimised, where in a typical sequence only 20.4% of the full image matching operations are required.
A Generative Spatial Clustering Model for Random Data through Spanning Trees

When performing analysis of spatial data, there is often the need to aggregate geographical areas into larger regions, a process called regionalization or spatially constrained clustering. These algorithms assume that the items to be clustered are non-stochastic, an assumption not held in many applications. In this work, we present a new probabilistic regionalization algorithm that allows spatially varying random variables as features. Hence, an area highly different from its neighbors can still be considered a member of their cluster if it has a large variance. Our proposal is based on a Bayesian generative spatial product partition model. We build an effective Markov Chain Monte Carlo algorithm to carry out a random walk on the space of all trees and their induced spatial partitions by edges' deletion. We evaluate our algorithm using synthetic data and with one problem of municipalities regionalization based on cancer incidence rates. We are able to better accommodate the natural variation of the data and to diminish the effect of outliers, producing better results than state-of-art approaches.
Associating Terms with Text Categories

Discriminating between text articles and automatically classifying documents is an essential task for many applications. With the prevalence of digital documents and the wide use of e-mail and web documents, text categorization is regaining interest and is becoming a central problem in digital text collections. There have been many approaches to solve this problem, mainly from the machine learning community. This paper proposes a new fast method for building a text classifier using association rule mining by discovering associations between terms and topical categories of documents.
Decisive Heuristics to Differentiate Legitimate from Phishing Sites

Phishing attacks are a major concern for preserving Internet users privacy, especially when most of them lead to financial data theft by combining both social engineering and spoofing techniques. As blacklists are not the most effective in detecting phishing sites because of their short lifetime, heuristics appears as a privileged way at time 0. Several previous studies discussed the different types of phishing characteristics that can help defining heuristics tests, as well as comparing them to blacklists. In our paper, we studied heuristics using a different approach. Based on the characteristics of phishing URLs and webpages, we defined 20 heuristics tests and implemented them in our own active anti-phishing toolbar (Phishark). Then, we tested the heuristics effectiveness and determined which heuristics are decisive to differentiate legitimate from phishing sites.
Reusability Evaluation Model for Procedure Based Software Systems

— Software professionals have found reuse as a powerful means to potentially overcome the situation of software crisis. Anything that is produced from a software development effort can potentially be reused and reduces the software development cost. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this research work, structural attributes of function oriented software components are explored using software metrics and reusability of the software is evaluated by experimenting five different Neural Network based approaches, taking the metric values as input. The calculated reusability value enables to identify a good quality code automatically. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) and are convincing enough to propose the system for the identification of reusable software components. So, the proposed model can be used to improve the productivity and quality of software development.
A Timescale for Evolution, Population Expansion, and Spatial Spread of an Emerging Clone of Methicillin-Resistant Staphylococcus aureus

Due to the lack of fossil evidence, the timescales of bacterial evolution are largely unknown. The speed with which genetic change accumulates in populations of pathogenic bacteria, however, is a key parameter that is crucial for understanding the emergence of traits such as increased virulence or antibiotic resistance, together with the forces driving pathogen spread. Methicillin-resistant Staphylococcus aureus (MRSA) is a common cause of hospital-acquired infections. We have investigated an MRSA strain (ST225) that is highly prevalent in hospitals in Central Europe. By using mutation discovery at 269 genetic loci (118,804 basepairs) within an international isolate collection, we ascertained extremely low diversity among European ST225 isolates, indicating that a recent population bottleneck had preceded the expansion of this clone. In contrast, US isolates were more divergent, suggesting they represent the ancestral population. While diversity was low, however, our results demonstrate that the short-term evolutionary rate in this natural population of MRSA resulted in the accumulation of measurable DNA sequence variation within two decades, which we could exploit to reconstruct its recent demographic history and the spatiotemporal dynamics of spread. By applying Bayesian coalescent methods on DNA sequences serially sampled through time, we estimated that ST225 had diverged since approximately 1990 (1987 to 1994), and that expansion of the European clade began in 1995 (1991 to 1999), several years before the new clone was recognized. Demographic analysis based on DNA sequence variation indicated a sharp increase of bacterial population size from 2001 to 2004, which is concordant with the reported prevalence of this strain in several European countries. A detailed ancestry-based reconstruction of the spatiotemporal dispersal dynamics suggested a pattern of frequent transmission of the ST225 clone among hospitals within Central Europe. In addition, comparative genomics indicated complex bacteriophage dynamics.
Monetary policy in a changing economic environment

My remarks focus on the challenges facing monetary policy in a rapidly changing world. I start by examining the nature of economic change confronting monetary policy in its daily execution. In the absence of an unambiguous mandate to maintain price stability and of a clear strategy to sustain it, the ongoing task of identifying the latest economic shocks may easily distract the central bank from the need to maintain a firm sense of direction in the longer run. Next, I advance an interpretation of why the transition to European monetary union involving, by all standards, a state of acute uncertaintycould be accomplished in the smooth manner in which it proceeded. In this context, I highlight the role of two complementary policy perspectives. These two principles of good policy are conducive to flexible and timely responses to unfolding events and, at the same time, ensure policy against myopia and short-termism and keep it solidly anchored to its medium-term objective.
A Simplified Structure for FIR Filters with an Adjustable Fractional Delay

This paper introduces an efficient filter structure for implementing finite-impulse response (FIR) filters with an adjustable fractional delay. In this structure the first two subfilters are the same as in the modified Farrow structure, whereas the remaining ones are generated by properly combining these two subfilters with some additional very short filters, pure delay terms, adders, and multipliers. For significantly reducing the number of multipliers, the three-step synthesis scheme proposed by Yli-Kaakinen and Saramaki in the case of the modified Farrow structure is followed. First, the number of subfilters and their orders are determined such that the given criteria are sufficiently exceeded. Second, an initial filter is determined using a simple design scheme. This filter serves as a start-up solution for further optimization being performed using a constrained nonlinear optimization algorithm. Third, those coefficient values of the subfilters having a negligible effect on the overall system performance are fixed to be zero-valued. Both the performance and complexity of the proposed adjustable digital filters are compared with those of some existing adjustable FIR filters proposed in the literature. This comparison shows that, in the case of stringent amplitude and phase delay specifications, the number of multipliers for the proposed filters is less than 80 percent when compared with the corresponding optimized modified Farrow structure.
Commodity price uncertainty and shocks: implications for economic growth

It has long been believed that commodity price variability causes problems for primary-producing developing countries, but there is less agreement about which particular manifestations of commodity price movements matter to developing countries. This paper tests the effects of ex post shocks and ex ante price uncertainty on economic growth using the Burnside and Dollar (1997) data set. The shock and uncertainty variables are constructed using a new data set of unique aggregate commodity price indices for 113 developing countries over the period 1957Q1-1997Q4. The analysis shows that per capita growth rates are significantly reduced by large discrete negative commodity price shocks. The magnitude of the effect of negative shocks on growth is very substantial, and appears to work independently of investment, which suggests that adjustment is achieved through severe reductions in capacity utilization. Negative shocks remain highly significant after controlling for government economic policy and institutional quality, which indicates that the result is not attributable exclusively to inappropriate policy responses on the part of governments. The paper also shows that positive shocks have no lasting impact on growth, which is consistent with the findings of both Deaton and Miller (1995) and Collier and Gunning (1999a), but overturns an earlier result which suggested that the long run effects of positive temporary shocks are negative. The third key result is that ex ante uncertainty does not affect growth, which holds for nine different definitions of uncertainty. Hence, what reduces growth is not the prospect of volatile world prices, but the actual realizations of negative shocks. The results are robust to changes in sample composition, changing the time series dimensions of the data, instrumenting for endogenous regressors, and across different estimation methods.
An optimized molecular inclusion complex of diferuloylmethane: enhanced physical properties and biological activity

Objective The purpose of this study was to explore and evaluate the enhanced physical properties and biological activity of a molecular inclusion complex (MICDH) comprising diferuloylmethane (DFM) and hydroxypropyl-β-cyclodextrin. Methods The preparation conditions of MICDH were optimized using an orthogonal experimental design. The solubility, in vitro release and model fitting, microscopic morphology, molecular structure simulation, anti-lung cancer activity, and action mechanism of MICDH were evaluated. Results The solubility of DFM was improved 4400-fold upon complexation with hydroxypropyl-β-cyclodextrin. The release rate of DFM was significantly higher from MICDH than from free DFM. MICDH exhibited higher antitumor activity against human lung adenocarcinoma A549 cells than free DFM. More cells were arrested in the S/G2 phase of the cell cycle or were induced to undergo apoptosis when treated with MICDH than when treated with free DFM. Furthermore, increased reactive oxygen species and intracellular calcium ion levels and decreased mitochondrial membrane potential were observed in cells treated with MICDH. Conclusion MICDH markedly improved the physical properties and antitumor activity of DFM. MICDH may prove to be a preferred alternative to free DFM as a formulation for DFM delivery in lung cancer treatment.
FX Arbitrage and Market Liquidity: Statistical Significance and Economic Value

This paper studies covered interest parity arbitrage violations in foreign exchange markets and their relationship with market liquidity using a novel and unique dataset of tick-by-tick firm quotes for all financial instruments involved in the arbitrage strategy. The statistical analysis reveals that arbitrage opportunities are larger in size and slower to dissipate when market liquidity is poorer. Furthermore, their economic value is sizable but arbitrage profits only accrue to traders who are able to obtain low trading costs. These findings are consistent with a competitive equilibrium with real frictions when some traders have a comparative advantage in arbitrage trading.
MicroRNAs: New Players in Cardiac Injury and Protection

MicroRNAs (miRNAs) have emerged as a novel class of endogenous, small, noncoding RNAs that negatively regulate gene expression via degradation or translational inhibition of their target mRNAs. Over 700 miRNAs have been identified and sequenced in humans, and the number of miRNA genes is estimated at more than 1000. Individual miRNA is functionally important as a transcription factor because it has the ability to regulate the expression of multiple genes through binding to its target with imperfect or perfect complement. In the heart, miRNAs have been involved in several clinical scenarios, such as ischemia/reperfusion (I/R) injury and heart failure suggesting that regulation of their function could be used as a novel cardioprotective strategy. In particular, miRNA-1, miRNA-21, miRNA-24, miRNA-29, miRNA-92a, miRNA-126, miRNA-133, miRNA-320, miRNA-199a, miRNA-208, and miRNA-195 have been shown to be regulated after I/R injury. Because tissue miRNAs can be released into circulating blood, they also offer exciting new opportunities for developing sensitive biomarkers, including miRNA-1, miRNA-126, miR-208, and miRNA-499, for acute myocardial infarction and other cardiac diseases.
EEG-based Estimation of Cognitive Fatigue

We measured multichannel EEG spectra during a continuous mental arithmetic task and created statistical learning models of cognitive fatigue for single subjects. Sixteen subjects (4 F, 18-38 y) viewed 4-digit problems on a computer, solved the problems, and pressed keys to respond (inter-trial interval = 1 s). Subjects performed until either they felt exhausted or three hours had elapsed. Preand post-task measures of mood (Activation Deactivation Adjective Checklist, Visual Analogue Mood Scale) confirmed that fatigue increased and energy decreased over time. We examined response times (RT); amplitudes of ERP components N1, P2, and P300, readiness potentials; and power of frontal theta and parietal alpha rhythms for change as a function of time. Mean RT rose from 6.7 s to 7.9 s over time. After controlling for or rejecting sources of artifact such as EOG, EMG, motion, bad electrodes, and electrical interference, we found that frontal theta power rose by 29% and alpha power rose by 44% over the course of the task. We used 30-channel EEG frequency spectra to model the effects of time in single subjects using a kernel partial least squares (KPLS) classifier. We classified 13-s long EEG segments as being from the first or last 15 minutes of the task, using random sub-samples of each class. Test set accuracies ranged from 91% to 100% correct. We conclude that a KPLS classifier of multichannel spectral measures provides a highly accurate model of EEG-fatigue relationships and is suitable for on-line applications to neurological monitoring.
Effect of three-dimensional cloud inhomogeneity on shortwave radiative transfer

The three-dimensional LES model with explicit microphysics and a 3D Monte Carlo radiation transfer model were used to study the influence of vertical variability of extinction coefficient on the mean, variance, and two-dimensional fields of upward, downward, and horizontal radiative fluxes of overcast stratocumulus clouds. Within the cloud layer, the vertical stratification of extinction coefficient has considerable effect on the means and variances of the fluxes. At the cloud boundaries, the spatial distributions of the fluxes depend strongly on the vertical inhomogeneity of extinction coefficient.
Photogrammetric calibration and accuracy evaluation of a cross-pattern stripe projector

Presently there is a growing demand for fast and precise 3D computer vision systems for a wide variety of industrial applications like reverse engineering, quality control and industrial gauging. One important aspect of any vision system is the data acquisition. If the principle of triangulation is used the correspondence problem is to be solved. The coded light approach offers a fast way to overcome this problem and to provide dense range data. In order to get high accuracy range images the system needs to be calibrated. In this paper, we compare two calibration techniques: polynomial depth calibration and photogrammetric calibration. We have carried out both methods independently. To obtain results about the accuracy in object space, we measured the surface of a plane- table.
Nucleolin Inhibits G4 Oligonucleotide Unwinding by Werner Helicase

Background The Werner protein (WRNp), a member of the RecQ helicase family, is strongly associated with the nucleolus, as is nucleolin (NCL), an important nucleolar constituent protein. Both WRNp and NCL respond to the effects of DNA damaging agents. Therefore, we have investigated if these nuclear proteins interact and if this interaction has a possible functional significance in DNA damage repair. Methodology/Principal Findings Here we report that WRNp interacts with the RNA-binding protein, NCL, based on immunoprecipitation, immunofluorescent co-localization in live and fixed cells, and direct binding of purified WRNp to nucleolin. We also map the binding region to the C-terminal domains of both proteins. Furthermore, treatment of U2OS cells with 15 µM of the Topoisomerase I inhibitor, camptothecin, causes the dissociation of the nucleolin-Werner complex in the nucleolus, followed by partial re-association in the nucleoplasm. Other DNA damaging agents, such as hydroxyurea, Mitomycin C, and aphidicolin do not have these effects. Nucleolin or its C-terminal fragment affected the helicase, but not the exonuclease activity of WRNp, by inhibiting WRN unwinding of G4 tetraplex DNA structures, as seen in activity assays and electrophoretic mobility shift assays (EMSA). Conclusions/Significance These data suggest that nucleolin may regulate G4 DNA unwinding by WRNp, possibly in response to certain DNA damaging agents. We postulate that the NCL-WRNp complex may contain an inactive form of WRNp, which is released from the nucleolus upon DNA damage. Then, when required, WRNp is released from inhibition and can participate in the DNA repair processes.
Predictors and Moderators of Internet- and Group-Based Cognitive Behaviour Therapy for Panic Disorder

Internet-based cognitive behaviour therapy (ICBT) can be equally effective as traditional face-to-face cognitive behaviour therapy (CBT) for treating panic disorder (PD). However, little is known about the predictors and moderators of outcome of ICBT when delivered in psychiatric outpatient settings. This study investigated a selection of outcome predictors and moderators of ICBT for panic disorder based on data from a randomised controlled trial where therapist-guided ICBT was compared with group CBT (GCBT) for panic disorder. Participants (N = 104) received 10 weeks of ICBT or GCBT and were assessed before and after treatment, and after six months. Multiple regression analyses were used to test for significant predictors of treatment outcome. Predictors of positive treatment response for both modalities were having low levels of symptom severity and work impairment. In addition, anxiety sensitivity was found to have a small negative relationship with treatment outcome, suggesting that anxiety sensitivity may slightly enhance treatment response. Treatment modality had a moderating effect on the relationship between domestic impairment and outcome and on the relationship between initial age of onset of panic symptoms and treatment outcome, favouring ICBT for patients having had an early onset of PD symptoms and for patients having a high domestic functional impairment. These results suggest that both ICBT and GCBT are effective treatment modalities for PD and that it is possible to predict a significant proportion of the long-term outcome variance based on clinical variables.
Subcutaneous veins detection and backprojection method using Frangi vesselness filter

Blood vessels detection is a common task performed in numerous medical procedures. During regular medical treatments venipuncture procedures are performed for invasive medication and blood sampling. Near infrared imaging technology can be used to visualize the subcutaneous veins in cases of difficult venous access. In this paper the methods for veins centerline detection and back projection is presented. In order to highlight the suitable veins for venipuncture, the centerline of larger veins are detected and back projected to the original image. The method is applied on the near infrared images of subjects selected from four different classes of skin tone. This can be helpful to medical staff to select suitable vein for venipuncture procedures. The method is based on Frangi vesselness filter for 2D images. The artifacts like hair and small vessel-like structures are removed with morphological operations. The presented method shows consistent performance in terms of vascular structure detection for all skin tone classes.