Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion transforms for video coding

Video coding standards use motion compensated prediction to reduce temporal redundancies. In general this is performed by computing motion vectors for predefined regions in the image (rectangular blocks), and transmitting these vectors as side-information. The motion transform (MT) provides a new motion compensation technique that does not require the transmission of motion vectors and yet, performs as well as forward motion estimation for many image sequences. In the MT, motion information is obtained in a bottom-up hierarchical fashion using a two-dimensional nonlinear filter bank. In this paper we elaborate on MT implementation details and discuss a new variation of the MT. Results obtained using MTs on typical image sequences are compared to results for the full search block matching algorithm (BMA).
Pupil-occluding organized hyphema anterior to the intraocular lens treated by neodymium: yttrium-aluminum-garnet laser: a case report

We report, to our best knowledge, the first case of treatment of pupil-occluding postoperative organized hyphema anterior to the intraocular lens (IOL) using neodymium: yttrium-aluminum-garnet (Nd:YAG) laser. A 78-year-old Asian female underwent uneventful cataract operation. She had been taking aspirin, which she discontinued 1 week before surgery. Iris prolapse occurred at the end of the surgery, which led to intracameral bleeding. Two weeks later, her best-corrected visual acuity was hand motion. Although hyphema had decreased, pupil-occluding organized hematoma had formed anterior to the IOL. The blood clot anterior to the IOL was removed using Nd:YAG laser. One week later, although the hematoma anterior to the IOL resolved, endocapsular hematoma was observed, which was dispersed with Nd:YAG laser posterior capsulotomy. Two weeks later, her best-corrected visual acuity improved to 20/60. There was no complication associated with Nd:YAG laser. In conclusion, pupil-occluding organized hyphema anterior to the IOL can occur as a complication of cataract surgery, in which Nd:YAG laser can be a useful treatment option.
Accelerating Sequence Event Detection through Condensed Composition

Composite event processing systems are useful in various application domains such as stock data stream monitoring, RFID data management, web access pattern monitoring, etc. The tree-based method is a typical method for implementing composite event processing system. In this paper, we introduce an optimization method called "condensed composition" for the tree-based composite event processing. "Condensed composition" divides the events in groups to participate the composition. We analyze the reason why the performance is improved and utilizes the statistics of the "condensation degree" to dynamically decide using condensed composition or not for different data characteristics. In the experiments, the "condensed composition" method significantly improved the performance on the real stock data.
‘I Want to Persuade You!’ – Investigating the effectiveness of explicit persuasion concerning attributes of the communicator and the marketing campaign

Abstract In explicit persuasion, the communicator states explicitly a desire to persuade the consumer. By referring to an attributional approach, social engagement was simultaneously explored as a beneficial communicator attribute, while cause-related marketing (CRM) was addressed as a boundary condition. In an experiment, we varied the persuasion strategy (explicit vs. implicit), the communicator’s prior experience with social engagement (yes vs. no), and the specific marketing strategy (CRM vs. non-charity marketing). As expected, in the non-charity marketing condition, explicit (vs. implicit) persuasion was more effective when the communicator had prior experience in social engagement. In the CRM condition, explicit (vs. implicit) persuasion was less effective when the communicator had prior experience in social engagement; when no prior experience was reported, persuasiveness increased.
Improved bounds for routing and sorting on multi-dimensional meshes

We show improved bounds for 1–1 routing and sorting on multi-dimensional meshes and tori. In particular, we give a fairly simple deterministic algorithm for sorting on the <italic>d</italic>-dimensional mesh of side length <italic>n</italic> that achieves a running time of <italic>3dn</italic>/2+<italic>o</italic>(<italic>n</italic>) for the <italic>d</italic>-dimensional mesh and torus, respectively, that make one copy of each element. We also show lower bounds for sorting with respect to a large class of indexing schemes, under a model of the mesh where each processor can hold an arbitrary number of packets. Finally, we describe algorithms for permutation routing whose running times come very close to the diameter lower bound.
Design for microstrip leaky wave antenna based on SRR structure

Left-handed materials are artificial structures which received substantial attention in scientific and engineering communities in recent years. The designs of left-handed materials are developed rapidly. While applying the left-handed materials to the design of microstrip leaky wave antennas, the performance of antennas can be improved. These materials are composed of periodically assigned unit cells, which have electromagnetic responses in specified frequency bands. Based on the SRR structure, a microstrip leaky wave antenna is designed using the composite right/left-handed (CRLH) transmission line theory, then its radiation characteristics is discussed. The results of the simulations demonstrate that the antenna is capable of continuous scanning from backward to forward angles, moreover, the loss analysis is first proposed and it confirms that different loss characteristics of the structures have different effects on the performance.
Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review

Objective To conduct a systematic review of studies reporting on the validity of International Classification of Diseases (ICD) codes for identifying stroke in administrative data. Methods MEDLINE and EMBASE were searched (inception to February 2015) for studies: (a) Using administrative data to identify stroke; or (b) Evaluating the validity of stroke codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), or Kappa scores) for stroke, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2015) of original papers. Studies solely evaluating codes for transient ischaemic attack were excluded. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Results Seventy-seven studies published from 1976–2015 were included. The sensitivity of ICD-9 430-438/ICD-10 I60-I69 for any cerebrovascular disease was ≥ 82% in most [≥ 50%] studies, and specificity and NPV were both ≥ 95%. The PPV of these codes for any cerebrovascular disease was ≥ 81% in most studies, while the PPV specifically for acute stroke was ≤ 68%. In at least 50% of studies, PPVs were ≥ 93% for subarachnoid haemorrhage (ICD-9 430/ICD-10 I60), 89% for intracerebral haemorrhage (ICD-9 431/ICD-10 I61), and 82% for ischaemic stroke (ICD-9 434/ICD-10 I63 or ICD-9 434&436). For in-hospital deaths, sensitivity was 55%. For cerebrovascular disease or acute stroke as a cause-of-death on death certificates, sensitivity was ≤ 71% in most studies while PPV was ≥ 87%. Conclusions While most cases of prevalent cerebrovascular disease can be detected using 430-438/I60-I69 collectively, acute stroke must be defined using more specific codes. Most in-hospital deaths and death certificates with stroke as a cause-of-death correspond to true stroke deaths. Linking vital statistics and hospitalization data may improve the ascertainment of fatal stroke.
Effects of the Chemokine Receptor 5 (CCR5)-Delta32 Mutation on Hepatitis C Virus-Specific Immune Responses and Liver Tissue Pathology in HCV Infected Patients

Background: The specific antiviral T cells provide CC chemokine receptor 5 (CCR5) for the immune response during the hepatitis C virus (HCV) infection. Heterogenous and/or homozygous 32 base pair deletion in CCR5 gene (CCR5Δ32 bpdel) leads to reduced protein expression. Objectives: In the current case control study, we aimed to compare the histopathological findings of liver to the CCR5Δ32 bpdel mutation profiles, expression and some other clinical findings in patients with chronic HCV infection. Materials and Methods: Multiple Strip Assay reverse hybridisation and Real Time PCR techniques were used to determine the germline CCR5 mutations and immunohistochemical technique was used to evaluate the gene expression in targer tissue biopsies. Results: Target CCR5 WT/WT, WT/Δ32, and Δ32/Δ32 genotypes were observed in 91.4%, 8.6% and 0.0% for HCV positive patients and 98.3%, 1.7% and 0.0% for control group respectively. The histologic activity index (HAI) was significantly lower (4.0 ± 1.0) in the mutated group than the non-mutated group (5.7 ± 1.0). Decreased fibrosis levels were detected in HCV positive mutated group. Conclusions: Results showed that CCR5 polymorphism was more frequent in HCV positive patients than in healthy population in Turkish population. Current results also showed that mutated CCR5 signalling pathway due to CCR5-Delta32 may potentially result in subtle reduction of HCV specifity to the drug responses due to the positive impact on liver inflammation, fibrosis levels and liver destruction in HCV infection.
Clustering in Weight Space of Feedforward

We study symmetries of feedforward networks in terms of their corresponding groups and nd that these groups naturally act on and partition weight space. We specify an algorithm to generate representative weight vectors in a speciic fundamental domain. The analysis of the metric structure of the fundamental domain enables us to use the location information of weight vector estimates, e. g. for cluster analysis. This can be implemented eeciently even for large networks.
Evolutionary Many-Objective Optimization Based on Adversarial Decomposition

The decomposition-based evolutionary algorithm has become an increasingly popular choice for posterior multiobjective optimization. Facing the challenges of an increasing number of objectives, many techniques have been developed which help to balance the convergence and diversity. Nevertheless, according to a recent study by Ishibuchi et al., due to the predefined search directions toward the ideal point, their performance strongly depends on the Pareto front (PF) shapes, especially the orientation of the PFs. To balance the convergence and diversity for decomposition-based methods and to alleviate their performance dependence on the orientation of the PFs, this paper develops an adversarial decomposition method for many-objective optimization, which leverages the complementary characteristics of different subproblem formulations within a single paradigm. More specifically, two populations are co-evolved by two subproblem formulations with different contours and adversarial search directions. To avoid allocating redundant computational resources to the same region of the PF, the two populations are matched into one-to-one solution pairs according to their working regions upon the PF. Each solution pair can at most contribute one principal mating parent during the mating selection process. When comparing nine state-of-the-art many-objective optimizers, we have witnessed the competitive performance of our proposed algorithm on 130 many-objective test problems with various characteristics, including regular and inverted PFs.
Supervised manifold learning for image and video classification

This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize the distance preserving, we propose a novel algorithm called maximum distance embedding (MDE), which aims to maximize the distances between some particular pairs of data points, with the intention of flattening the local nonlinearity and keeping the discriminant information simultaneously in the embedded feature space. Moreover, MDE measures the dissimilarity between data points using L1-norm distance, which is more robust to outliers than widely used Frobenius norm distance. To adapt the nature tensor structure of image and video data, we further propose the multilinear MDE (M2DE). Experiments on various datasets demonstrate that both MDE and M2DE achieve impressive embedding results of image and video data for classification tasks.
User Demographics for Embodiment Customization

Attempts at interface agent personalization are usually aimed at helping the user perform a task or service. For example,scheduling of appointments, inspection of messages, discovering items of interest and different forms of negotiation. While this is very noble undertaking, it makes assumptions about the level of trust and credibility a user may place in such an agent in a realworld setting. If Microsoft's experiments in social user interfaces teach us anything, it is that a ''one size fits all'' solution does not truly engage the user and encourage reuse. This ''relationship management'' between the user and the character begins when the two first meet. As with human-human relationships, first impressions are essential. Instead of looking at the functional aspects of the relationship, we believe the characters embodiment is the best place to start the personalization process. We describe a study in which participants from several different age ranges,genders and ethnic groups were asked their preference of anthropomorphic character, based on a cooperative computer task. We found that participants generally selected characters from the same ethic group as themselves and that almost all participants selected a young character (instead of a middle aged or elderly character). No significant preference was foundmore » for character gender. « less
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The Evolution of Climate Sensitivity and Climate Feedbacks in the Community Atmosphere Model

AbstractThe major evolution of the National Center for Atmospheric Research Community Atmosphere Model (CAM) is used to diagnose climate feedbacks, understand how climate feedbacks change with different physical parameterizations, and identify the processes and regions that determine climate sensitivity. In the evolution of CAM from version 4 to version 5, the water vapor, temperature, surface albedo, and lapse rate feedbacks are remarkably stable across changes to the physical parameterization suite. However, the climate sensitivity increases from 3.2 K in CAM4 to 4.0 K in CAM5. The difference is mostly due to (i) more positive cloud feedbacks and (ii) higher CO2 radiative forcing in CAM5. The intermodel differences in cloud feedbacks are largest in the tropical trade cumulus regime and in the midlatitude storm tracks. The subtropical stratocumulus regions do not contribute strongly to climate feedbacks owing to their small area coverage. A “modified Cess” configuration for atmosphere-only model experime.
Two-loop amplitudes of gluons and octa-cuts in Script N = 4 super Yang-Mills

After reduction techniques, two-loop amplitudes in = 4 super Yang-Mills theory can be written in a basis of integrals containing scalar double-box integrals with rational coefficients, though the complete basis is unknown. Generically, at two loops, the leading singular behavior of a scalar double box integral with seven propagators is captured by a hepta-cut. However, it turns out that a certain class of such integrals has an additional propagator-like singularity. One can then formally cut the new propagator to obtain an octa-cut which localizes the cut integral just as a quadruple cut does at one-loop. This immediately gives the coefficient of the scalar double box integral as a product of six tree-level amplitudes. We compute, as examples, several coefficients of the five- and six-gluon non-MHV two-loop amplitudes. We also discuss possible generalizations to higher loops.
Inhibition of mutant EGFR in lung cancer cells triggers SOX2-FOXO6-dependent survival pathways

Treatment of EGFR-mutant lung cancer with erlotinib results in dramatic tumor regression but it is invariably followed by drug resistance. In characterizing early transcriptional changes following drug treatment of mutant EGFR-addicted cells, we identified the stem cell transcriptional regulator SOX2 as being rapidly and specifically induced, both in vitro and in vivo. Suppression of SOX2 sensitizes cells to erlotinib-mediated apoptosis, ultimately decreasing the emergence of acquired resistance, whereas its ectopic expression reduces drug-induced cell death. We show that erlotinib relieves EGFR-dependent suppression of FOXO6, leading to its induction of SOX2, which in turn represses the pro-apoptotic BH3-only genes BIM and BMF. Together, these observations point to a physiological feedback mechanism that attenuates oncogene addiction-mediated cell death associated with the withdrawal of growth factor signaling and may therefore contribute to the development of resistance. DOI: http://dx.doi. org/10.7554/eLife.06132. 001
Monomer dynamics in double- and single-stranded DNA polymers.

We present the first measurements of the kinetics of random motion of individual monomers within large polymer coils. We use double- and single-stranded DNA (dsDNA and ssDNA) as models of semiflexible and flexible polymers, respectively. Fluorescence fluctuations of DNA fragments labeled specifically at a single position reveal the time dependence of the DNA monomer's mean-square displacement . The monomer motions within dsDNA and ssDNA coils are characterized by two qualitatively different kinetic regimes: close to proportional to t(2/3) for ssDNA and proportional to sqrt[t] for dsDNA. While the kinetic behavior of ssDNA is consistent with the generally accepted Zimm theory of polymer dynamics, the kinetic behavior of dsDNA monomers is in good agreement with the Rouse model.
T2-Weighted Cardiac Magnetic Resonance Imaging of Edema in Myocardial Diseases

The purpose of this paper is to describe imaging techniques and findings of T2-weighted magnetic resonance imaging (MRI) of edema in myocardial diseases. T2-weighted cardiac MRI is acquired by combining acceleration techniques with motion and signal suppression techniques. The MRI findings should be interpreted based on coronary artery supply, intramural distribution, and comparison with delayed-enhancement MRI. In acute myocardial diseases, such as acute myocardial infarction and myocarditis, the edema is larger than myocardial scarring, whereas the edema can be smaller than the scarring in some types of nonischemic cardiomyopathy, including hypertrophic cardiomyopathy. T2-weighted MRI of edema identifies myocardial edema associated with ischemia, inflammation, vasculitis, or intervention in the myocardium and provides information complementary to delayed-enhancement MRI.
Face Recognition Using an Enhanced Independent Component Analysis Approach

This paper is concerned with an enhanced independent component analysis (ICA) and its application to face recognition. Typically, face representations obtained by ICA involve unsupervised learning and high-order statistics. In this paper, we develop an enhancement of the generic ICA by augmenting this method by the Fisher linear discriminant analysis (LDA); hence, its abbreviation, FICA. The FICA is systematically developed and presented along with its underlying architecture. A comparative analysis explores four distance metrics, as well as classification with support vector machines (SVMs). We demonstrate that the FICA approach leads to the formation of well-separated classes in low-dimension subspace and is endowed with a great deal of insensitivity to large variation in illumination and facial expression. The comprehensive experiments are completed for the facial-recognition technology (FERET) face database; a comparative analysis demonstrates that FICA comes with improved classification rates when compared with some other conventional approaches such as eigenface, fisherface, and the ICA itself
Alcohol-Related Context Modulates Performance of Social Drinkers in a Visual Go/No-Go Task: A Preliminary Assessment of Event-Related Potentials

Background Increased alcohol cue-reactivity and altered inhibitory processing have been reported in heavy social drinkers and alcohol-dependent patients, and are associated with relapse. In social drinkers, these two processes have been usually studied separately by recording event-related potentials (ERPs) during rapid picture presentation. The aim of our study was to confront social drinkers to a task triggering high alcohol cue-reactivity, to verify whether it specifically altered inhibitory performance, by using long-lasting background picture presentation. Methods ERP were recorded during visual Go/No-Go tasks performed by social drinkers, in which a frequent Go signal (letter “M”), and a rare No-Go signal (letter “W”) were superimposed on three different types of background pictures: neutral (black background), alcohol-related and non alcohol-related. Results Our data suggested that heavy social drinkers made more commission errors than light drinkers, but only in the alcohol-related context. Neurophysiologically, this was reflected by a delayed No-Go P3 component. Conclusions Elevated alcohol cue-reactivity may lead to poorer inhibitory performance in heavy social drinkers, and may be considered as an important vulnerability factor in developing alcohol misuse. Prevention programs should be designed to decrease the high arousal of alcohol stimuli and strengthen cognitive control in young, at-risk individuals.
Power Harvester Design for Passive UHF RFID Tag Using a Voltage Boosting Technique

This paper presents a guideline to design and optimize a power harvester circuit for an RF identification transponder. A power harvester has been designed and fabricated in a CMOS 0.18- process that operates at the UHF band of 920 MHz. The circuit employs an impedance transformation circuit to boost the input RF signal that leads to the improvement of the circuit performance. The power harvester has been optimized to achieve maximum sensitivity by characterizing both the impedance transformation network and the rectifier circuit and choosing the optimum values for the circuit parameters. The measurement results show sensitivity of 14.1 dBm for dc output voltage of 1 V and the output current of 2 mum that corresponds to the output power of 2 muW.