Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical implications of the new definition of myocardial infarction

Myocardial infarction (MI) can be considered from several perspectives: clinical, electrocardiographic, biochemical, pathological, epidemiological, and imaging. The diagnosis of MI has psychological, social, and legal implications. MI is often used as a major end point in clinical trials. Historically, there has been tacit agreement as to the meaning of the term “myocardial infarction”. The World Health Organization definition, which has been widely used, requires the presence of two of the following three features: symptoms of myocardial ischaemia, elevation of cardiac marker (enzyme) concentrations in the blood, and a typical electrocardiographic pattern involving the development of Q waves or persistent T wave changes.w1 Using specific and highly sensitive immunoassays for myocardial proteins, such as cardiac troponins T and/or I, it is now possible to identify patients with small areas of myocardial necrosis. The emphasis on cardiac protein markers in the new American College of Cardiology/European Society of Cardiology (ACC/ESC) definition of MI, published in September 2000, has simplified the classification of MI.1 The new diagnostic criteria include a characteristic rise and fall in blood concentrations of cardiac troponins and/or creatine kinase (CK)-MB in the context of spontaneous ischaemic symptoms or coronary intervention (table 1). 1 View this table: Table 1 The new ACC/ESC definition of myocardial infarction (MI)1 If it is accepted that any myocardial necrosis caused by ischaemia constitutes MI, many patients who were formerly diagnosed as having unstable angina pectoris will be now diagnosed as having had a small MI. For example, in a review of data from the Hennepin County Medical Centre (Minnesota, USA), the incidence of MI increased by 37% when the new definition of MI was applied.w2 However, the specificity of the new tests will reduce the number of false positive diagnoses of MI. Under the WHO classification, which was expanded for the monitoring trends and determinants …
Introducing FOBOS : Flexible Open-source BOard for Side-channel analysis

Side-channel analysis attacks pose a growing threat to implementations of cryptographic algorithms implemented in software as well as in hardware. Current standard side-channel evaluation boards with Field Programmable Gate Arrays (FPGAs), that allow for exploring the vulnerability of cryptographic implementations on FPGAs, are expensive and available only for a few FPGA devices. Furthermore, a complete open source software package that includes drivers that run test cases on the board, control the measurement equipment, and contain several side-channel analysis techniques is not readily available. Each user has to assemble their own setup based on software packages from multiple sources, written in multiple languages and write parts themselves. While educating students on side-channel analysis is important, hands-on laboratory exercises are not feasible do to cost and complexity. In this paper, we introduce am open-source environment, called FOBOS for conducting side-channel attacks on FPGAs. FOBOS supports multiple FPGA devices and includes all necessary software to run differential power analysis attacks, which are the most prominent kind of side-channel attacks. The components of FOBOS are build in a modular fashion so that it can easily be adapted for new FPGA boards, oscilloscopes, and attack techniques.
Regional Variation in the Prevalence of Asthma Symptoms among Omani School Children: Comparisons from Two Nationwide Cross-sectional Surveys Six Years Apart.

OBJECTIVES The International Study of Asthma and Allergies in Children (ISAAC) highlighted the presence of wide variations in asthma prevalence between and within countries. The aim of this study was to determine the changes in the prevalence of asthma and its symptoms across the different regions of Oman. METHODS Two cross-sectional surveys were conducted as part of ISAAC phases I (1995) and III (2001) in two age groups (6-7 and 13-14 years) from nation-wide samples of Omani school children, with 7,067 participants in 1995 (3,893 young and 3,174 older group) and 7,879 participants in 2001 (4,126 young and 3,753 older group). RESULTS Over the period of six years, the Sharqiya (Eastern) region continued to have the highest prevalence of self-reported asthma diagnosis and all asthma symptoms in both age groups, with a significant increase in the prevalence of wheeze in the past 12 months (from 8.7% to 13.8%; p=0.002) and asthma diagnosis (from 13.8% to 17.8 %; p=0.046) in the young group, and a significant increase in night cough (from 21.6% to 27.8%; p=0.039) in the older group. All other regions had lower prevalence rates in 1995 in both age groups, and showed either no significant change or a decline in one or two of the self-reported asthma symptoms. The prevalence of asthma diagnosis among wheezy children remained unchanged across all regions. In addition, asthma under-diagnosis remains a problem with only 60% of children with severe wheeze reporting asthma diagnosis in both surveys. CONCLUSION The geographic variation in the prevalence of self-reported of asthma symptoms among Omani school children persists with further increase in the Sharqiya region. The findings also suggest under-diagnosis and/or poor recognition of asthma which had not improved over time.
Reasoning about infinite computation paths

We investigate extensions of temporal logic by finite automata on infinite words. There are three different types of acceptance conditions (finite, looping and repeating) that one can give for these finite automata. This gives rise to three different logics. It turns out, however. that these logics have the same expressive power but differ in the complexity of their decision problem. We also investigate the addition of alternation and show that it does not increase the complexity of the decision problem.
Accelerating Synchronous Sequential Circuits Using an Adaptive Clock

In this paper we propose a scheme for enhancing the timing performance of a pre-designed synchronous sequential circuit. In the proposed scheme, a circuit is driven by two clocks. One of them is the conventional clock while the other one, having a shorter period, is applied when the circuit stabilizes well before the critical delay. We use a symbolic algorithm to analyze the timing behavior of the synchronous sequential circuit and provide add-on circuitry to select the appropriate clock based on the current state of the circuit. We demonstrate an appreciable gain (67% in average) in timing performance on several benchmark circuits.
Formal verification of automatic circuit transformations for fault-tolerance

We present a language-based approach to certify fault-tolerance techniques for digital circuits. Circuits are expressed in a gate-level Hardware Description Language (HDL), fault-tolerance techniques are described as automatic circuit transformations in that language, and fault-models are specified as particular semantics of the HDL. These elements are formalized in the Coq proof assistant and the properties, ensuring that for all circuits their transformed version masks all faults of the considered fault-model, can be expressed and proved. In this article, we consider Single-Event Transients (SETs) and faultmodels of the form "at most 1 SET within k clock cycles". The primary motivation of this work was to certify the Double-Time Redundant Transformation (DTR), a new technique proposed recently [1]. The DTR transformation combines double-time redundancy, micro-checkpointing, rollback, several execution modes and input/output buffers. That intricacy requested a formal proof to make sure that no single-point of failure existed. The correctness of DTR as well as two other transformations for fault-tolerance (TMR & TTR) have been proved in Coq.
Probabilistic Interactive Installations

We present a description of two small audio/visual immersive installations. The main framework is an interactive structure that enables multiple participants to generate jazz improvisations, loosely speaking. The first uses a Bayesian Network to respond to sung or played pitches with machine pitches, in a kind of constrained harmonic way. The second uses Bayesian Networks and Hidden Markov Models to track human motion, play reactive chords, and to respond to pitches both aurally and visually.
Real Text-CS - Corpus Based Domain Independent Content Selection Model

Content selection is a highly domain dependent task responsible for retrieving relevant information from a knowledge source using a given communicative goal. This paper presents a domain independent content selection model using keywords as communicative goal. We employ DBpedia triple store as our knowledge source and triples are selected based on weights assigned to each triple. The calculation of the weights is carried out through log likelihood distance between a domain corpus and a general reference corpus. The method was evaluated using keywords extracted from QALD dataset and the performance was compared with cross entropy based statistical content selection. The evaluation results showed that the proposed method can perform 32% better than cross entropy based statistical content selection.
Elevated activation of CaMKIIα in the CPEB3-knockout hippocampus impairs a specific form of NMDAR-dependent synaptic depotentiation

Cytoplasmic polyadenylation element binding protein 3 (CPEB3) is a sequence-specific RNA-binding protein that confines the strength of glutamatergic synapses by translationally downregulating the expression of multiple plasticity-related proteins (PRPs), including the N-methyl-D-aspartate receptor (NMDAR) and the postsynaptic density protein 95 (PSD95). CPEB3 knockout (KO) mice exhibit hippocampus-dependent abnormalities related not only to long-term spatial memory but also to the short-term acquisition and extinction of contextual fear memory. In this study, we identified a specific form of NMDAR-dependent synaptic depotentiation (DPT) that is impaired in the adult CPEB3 KO hippocampus. In parallel, cultured KO neurons also exhibited delayed morphological and biochemical responses under NMDA-induced chemical long-term depression (c-LTD). The c-LTD defects in the KO neurons include elevated activation of calcium/calmodulin-dependent protein kinase II alpha subunit (CaMKIIα), increased Ser831 phosphorylation of GluA1 and slow degradation of PSD95 and GluA1. Because transient pharmacological suppression of CaMKIIα activity during the DPT-initiating phase successfully reversed the LTP in the KO hippocampus, DPT and c-LTD in the two different systems shared common molecular defects due to the absence of CPEB3. Together, our results suggest that CPEB3 deficiency imbalances NMDAR-activated CaMKIIα signaling, which consequently fails to depress synaptic strength under certain stimulation conditions.
Funbrella: recording and replaying vibrations through an umbrella axis

We propose an umbrella-like device called Funbrella that entertains people with many types of rain by focusing on an umbrella as a user interface that connects humans and rain. Generally, people experience rain with sound, sight, or sometimes smell; however, in our proposed system, we focus on the vibration perceived through an umbrella's handle so that people can feel the rain. We implemented a vibration-giving mechanism with an extremely simple structure based on a dynamic microphone and a dynamic speaker whose structures are almost identical. With this structure, Funbrella records the vibrations caused by raindrops and plays them. We implemented three applications: Crazy Rain, Tele-rain, and Minibrella. A questionnaire study about Crazy Rain application reveals that Funbrella is amusing enough for people regardless of age or gender because Funbrella accurately reproduces rain.
Business Cycles: Cyclical Comovement Within the European Union in the Period 1960-1999. A Frequency Domain Approach

This paper provides a descriptive analysis of the business cycles of the European Union countries and of the two main industrialised countries outside the Union, the United States and Japan. We use the spectral analysis to identify three main features of the business cycles: 1- The duration of the business cycle. 2- The degree of correlation, in the frequency domain, of the business cycles. 3- The identification of leading and lagging countries with respect to the business cycles of a reference series. We conclude that the United States, Italy and Greece have the shortest cycles, with an average duration around eight years. Japan, Spain and Austria have the longest cycles, lasting more than ten years. All the other countries lie in between with an average duration ranging from eight to nine years. By comparing the business cycles of the various countries with the Euro Area business cycle we conclude that Sweden, Finland, Great Britain and the United States lead the Euro Area by more than one year. The Netherlands, Italy, Japan and Spain are also leading countries but with a lead of no more than one year. There is evidence of counter-cyclical behaviour for Denmark in a sub-period of the sample and no reliable conclusions can be stated for Greece and Ireland. The remaining countries exhibit a high degree of correlation with the Euro Area business cycles and with a lag of no more than three-quarters, with the exception of Austria.
Texture and shape in fluorescence pattern identification for auto-immune disease diagnosis

Automation of HEp-2 cell pattern classification would drastically improve the accuracy and throughput of diagnostic services for many auto-immune diseases, but it has proven difficult to reach a sufficient level of precision. Correct diagnosis relies on a subtle assessment of texture type in microscopic images of indirect immunofluorescence (IIF), which so far has eluded reliable replication through automated measurements. We introduce a combination of spectral analysis and multi-scale digital filtering to extract the most discriminative variables from the cell images. We also apply multistage classification techniques to make optimal use of the limited labelled data set. Overall error rate of 1.6% is achieved in recognition of 6 different cell patterns, which drops to 0.5% if only positive samples are considered.
Human-Seeded Attacks and Exploiting Hot-Spots in Graphical Passwords

Although motivated by both usability and security concerns, the existing literature on click-based graphical password schemes using a single background image (e.g., PassPoints) has focused largely on usability. We examine the security of such schemes, including the impact of different background images, and strategies for guessing user passwords. We report on both short- and long-term user studies: one lab-controlled, involving 43 users and 17 diverse images, and the other a field test of 223 user accounts. We provide empirical evidence that popular points (hot-spots) do exist for many images, and explore two different types of attack to exploit this hot-spotting: (1) a "human-seeded" attack based on harvesting click-points from a small set of users, and (2) an entirely automated attack based on image processing techniques. Our most effective attacks are generated by harvesting password data from a small set of users to attack other targets. These attacks can guess 36% of user passwords within 231 guesses (or 12% within 216 guesses) in one instance, and 20% within 233 guesses (or 10% within 218 guesses) in a second instance. We perform an image-processing attack by implementing and adapting a bottom-up model of visual attention, resulting in a purely automated tool that can guess up to 30% of user passwords in 235 guesses for some instances, but under 3% on others. Our results suggest that these graphical password schemes appear to be at least as susceptible to offline attack as the traditional text passwords they were proposed to replace.
Growing a bag of systems tree for fast and accurate classification

The bag-of-systems (BoS) representation is a descriptor of motion in a video, where dynamic texture (DT) codewords represent the typical motion patterns in spatio-temporal patches extracted from the video. The efficacy of the BoS descriptor depends on the richness of the codebook, which directly depends on the number of codewords in the codebook. However, for even modest sized codebooks, mapping videos onto the codebook results in a heavy computational load. In this paper we propose the BoS Tree, which constructs a bottom-up hierarchy of codewords that enables efficient mapping of videos to the BoS codebook. By leveraging the tree structure to efficiently index the codewords, the BoS Tree allows for fast look-ups in the codebook and enables the practical use of larger, richer codebooks. We demonstrate the effectiveness of BoS Trees on classification of three video datasets, as well as on annotation of a music dataset.
Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation

In this paper, a new method is presented for spatial resolution enhancement of hyperspectral images (HSI) using spectral unmixing and a Bayesian sparse representation. The proposed method combines the high spectral resolution from the HSI with the high spatial resolution from a multispectral image (MSI) of the same scene and high resolution images from unrelated scenes. The fusion method is based on a spectral unmixing procedure for which the endmember matrix and the abundance fractions are estimated from the HSI and MSI, respectively. A Bayesian formulation of this method leads to an ill-posed fusion problem. A sparse representation regularization term is added to convert it into a well-posed inverse problem. In the sparse representation, dictionaries are constructed from the MSI, high optical resolution images, synthetic aperture radar (SAR) or combinations of them. The proposed algorithm is applied to real datasets and compared with state-of-the-art fusion algorithms based on spectral unmixing and sparse representation, respectively. The proposed method significantly increases the spatial resolution and decreases the spectral distortion efficiently.
An Improved Recovery Algorithm Based on ISD for Multiband Signals

Multiband signal is an important signal in radar and communication systems, which is generally sparse and with a wide spectrum. Due to the wide spectral range of multiband signals, traditional ADC sampling at Nyquist rate may be too difficult to achieve. Modulated wideband converter (MWC), which is based on compressed sensing (CS), is a subtle scheme to solve wide spectrum sampling problem. In addition, reconstruction algorithm is the key of MWC which can decide the performance of the architecture. In this paper, we propose an improved reconstruction method, which expands iterative support detection (ISD), an iterative recovery algorithm for one- dimensional signal, to continue to finite (CTF) system. Our algorithm uses ISD to compute the solutions which satisfy that every column's reconstructions is l1 minimization. Then, utilizing the resulting matrix and support detection rule, we can find the support set and obtain the recovered signal. Our algorithm does not require the number of support set as prior knowledge. And the property of our method is close to orthogonal matching pursuit multiple measurement vectors (OMPMMV), and better than Sparsity adaptive matching pursuit multiple measurement vectors (SAMPMMV). Simulation results confirm the conclusion.
On Subnormal Floating Point and Abnormal Timing

We identify a timing channel in the floating point instructions of modern x86 processors: the running time of floating point addition and multiplication instructions can vary by two orders of magnitude depending on their operands. We develop a benchmark measuring the timing variability of floating point operations and report on its results. We use floating point data timing variability to demonstrate practical attacks on the security of the Fire fox browser (versions 23 through 27) and the Fuzz differentially private database. Finally, we initiate the study of mitigations to floating point data timing channels with libfixedtimefixedpoint, a new fixed-point, constant-time math library. Modern floating point standards and implementations are sophisticated, complex, and subtle, a fact that has not been sufficiently recognized by the security community. More work is needed to assess the implications of the use of floating point instructions in security-relevant software.
betawrap: Successful prediction of parallel β-helices from primary sequence reveals an association with many microbial pathogens

The amino acid sequence rules that specify β-sheet structure in proteins remain obscure. A subclass of β-sheet proteins, parallel β-helices, represent a processive folding of the chain into an elongated topologically simpler fold than globular β-sheets. In this paper, we present a computational approach that predicts the right-handed parallel β-helix supersecondary structural motif in primary amino acid sequences by using β-strand interactions learned from non-β-helix structures. A program called BETAWRAP (http://theory.lcs.mit.edu/betawrap) implements this method and recognizes each of the seven known parallel β-helix families, when trained on the known parallel β-helices from outside that family. BETAWRAP identifies 2,448 sequences among 595,890 screened from the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/) nonredundant protein database as likely parallel β-helices. It identifies surprisingly many bacterial and fungal protein sequences that play a role in human infectious disease; these include toxins, virulence factors, adhesins, and surface proteins of Chlamydia, Helicobacteria, Bordetella, Leishmania, Borrelia, Rickettsia, Neisseria, and Bacillus anthracis. Also unexpected was the rarity of the parallel β-helix fold and its predicted sequences among higher eukaryotes. The computational method introduced here can be called a three-dimensional dynamic profile method because it generates interstrand pairwise correlations from a processive sequence wrap. Such methods may be applicable to recognizing other beta structures for which strand topology and profiles of residue accessibility are well conserved.
NOVEL METHOD TO ANALYZE AND DESIGN ONE- DIMENSIONAL RECIPROCAL PERIODIC STRUCTURES WITH SYMMETRICAL CELLS

The dispersion relation is derived for the most general con- flguration of a passive and reciprocal periodically loaded transmission line in a unique and simple form by introducing two novel parameters. Based on this relation, the phase and group velocities are determined and a simple condition for phase reversal propagation is obtained. The two above mentioned parameters help us to develop a polar diagram to model the behavior of any two-port network as a function of fre- quency. By this diagram, we can determine the direction of the phase velocity and also the value of the propagation constant. Then, sym- metrical cells and thereof the periodic structures composed of them are analyzed. For such structures, it will be shown that the dispersion re- lation can be rewritten in a form similar to the Lorentz transformation. We design and analyze a bandstop fllter to verify the method.