Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous 15-Year Decrease in Incidence and Mortality of Stroke in Finland: The FINSTROKE Study

Background and Purpose— The purpose of this study was to analyze the incidence and mortality trends in stroke events among persons 25 to 74 years of age in Finland during 1983 to 1997. Methods— The population-based FINSTROKE register recorded 5650 new strokes among persons 25 to 74 years of age in 2 geographical areas of Finland: 2770 in the Kuopio area (east central Finland) and 2880 in Turku (southwestern Finland). Of these, 3065 were men and 2585 were women. Results— The rates of acute stroke events fell during the whole study period in both men and women. In both FINSTROKE areas combined, the average annual decline in the age-standardized incidence of first stroke events was 2.0% (95% confidence interval [CI], −2.8 to −1.2; P <0.001) among men and 1.7% (95% CI, −2.6 to −0.8; P <0.001) among women. The decline in the incidence of ischemic stroke was even steeper, 2.9%/y (95% CI, −4.9 to −1.1; P <0.001) among men and 3.1%/y (95% CI, −5.0 to −1.1; P <0.001) among women, whereas the incidence of intracerebral hemorrhage and subarachnoid hemorrhage did not change. Mortality from all stroke events declined in the FINSTROKE areas by 3.7%/y (95% CI, −5.3 to −2.0; P <0.001) among men and by 4.1%/y (95% CI, −5.9 to −2.4; P <0.001) among women. The 28-day case fatality of all stroke events also tended to decline, but the decline was of borderline statistical significance only (P =0.07 among men, P =0.05 among women). Conclusions— Incidence and mortality of stroke events declined significantly in these 2 register areas in Finland during the 15-year period of 1983 to 1997.
Information Processing by Simple Molecular Motifs and Susceptibility to Noise

Biological organisms rely on their ability to sense and respond appropriately to their environment. The molecular mechanisms that facilitate these essential processes are however subject to a range of random effects and stochastic processes, which jointly affect the reliability of information transmission between receptors and e.g. the physiological downstream response. Information is mathematically defined in terms of the entropy; and the extent of information flowing across an information channel or signalling system is typically measured by the “mutual information”, or the reduction in the uncertainty about the output once the input signal is known. Here we quantify how extrinsic and intrinsic noise affect the transmission of simple signals along simple motifs of molecular interaction networks. Even for very simple systems the effects of the different sources of variability alone and in combination can give rise to bewildering complexity. In particular extrinsic variability is apt to generate “apparent” information that can in extreme cases mask the actual information that for a single system would flow between the different molecular components making up cellular signalling pathways. We show how this artificial inflation in apparent information arises and how the effects of different types of noise alone and in combination can be understood.
Global Hough localization for mobile robots in polygonal environments

Knowing the position of a mobile robot in the environment in which it operates is an important element for effectively accomplishing complex tasks requiring autonomous navigation. Among several existing techniques for robot self-localization, a new approach called Hough localization was proposed for map matching in the Hough domain, that turned out to be reliable and efficient for position tracking in polygonal environments. In this paper we present an extension of Hough localization which is able to deal with the global localization problem, in which the robot does not know its initial position in the environment.
Current Controlled Charging Scheme for off Board Electric vehicle Batteries from Solar PV Array

In this paper, we are proposing current-controlled hill-climbing strategy used in Maximum power point tracking (MPPT) of the solar photovoltaic array to Charge OFF Board Electric vehicle lithium-ion batteries within the safety limits and supported rating of batteries so that EV battery does not get damaged and can also increase the life of the battery. Here, a current sensor and potential difference sensor-based electric vehicle off-board battery charging by hill-climbing strategy is tested on MATLAB simulation. The satisfactory steady-state battery is charging within the rated charging limit, under variable solar irradiance.
Learning in Planning with Temporally Extended Goals and Uncontrollable Events

Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution plan. This paper introduces a planning model that combines temporally extended goals and uncontrollable events. The planning task is to reach a state such that all event sequences generated from that state satisfy the problem's temporally extended goal. A real-life application that motivates this work is to use planning to configure a system in such a way that its subsequent, non-deterministic internal evolution (nominal behavior) is guaranteed to satisfy a condition expressed in temporal logic. A solving architecture is presented that combines planning, model checking and learning. An online learning process incrementally discovers information about the problem instance at hand. The learned information is useful both to guide the search in planning and to safely avoid unnecessary calls to the model checking module. A detailed experimental analysis of the approach presented in this paper is included. The new method for online learning is shown to greatly improve the system performance.
Exploring the Positive Impact of Peers on Adolescent Substance Misuse

ABSTRACT Background: Previous research has consistently shown the negative impact that peers can have on adolescent substance use patterns. Few studies have examined the positive influence adolescents can have on their peers. This study aimed to examine the relationship of positive peer influence with indices of substance use and also to compare abstinent adolescents and substance-using adolescents on positive peer influence. Method: One hundred fifty-four adolescents (age range 12–20 years) completed a questionnaire on positive peer influence and other correlates of adolescent substance use including mental health, family functioning, and social support. Results: Positive peer influence was a significant predictor of lower substance use behaviors in adolescents, with positive influence from close friends being the strongest predictor. Substance-using adolescents' scores were significantly different from abstinent adolescents' scores for positive peer support, mental health functioning, impulsivity, and social support. Conclusions: These results indicate that positive influence from adolescents' peers may act as a protective factor in substance use. This influence should be utilized to aid the design of prevention and intervention initiatives in adolescent substance use.
Aerosol-cloud interaction inferred from MODIS satellite data and global aerosol models

We have used the MODIS satellite data and two global aerosol models to investigate the relationships be- tween aerosol optical depth (AOD) and cloud parameters that may be affected by the aerosol concentration. The relation- ships that are studied are mainly between AOD, on the one hand, and cloud cover, cloud liquid water path, and water vapour, on the other. Additionally, cloud droplet effective radius, cloud optical depth, cloud top pressure and aerosol ˚ Angstrexponent, have been analysed in a few cases. In the MODIS data we found, as in earlier studies, an enhance- ment in the cloud cover with increasing AOD. We find it likely that most of the strong increase in cloud cover with AOD, at least for AOD 0.2 can be explained by larger water uptake close to the clouds since relative humidity is higher in regions with higher cloud cover. The efficiency of the hy- groscopic growth depends on aerosol type, the hygroscopic nature of the aerosol, the relative humidity, and to some ex- tent the cloud screening. By analysing the ˚ Angstr¨ om expo- nent we find that the hygroscopic growth of the aerosol is not likely to be a main contributor to the cloud cover increase with AOD. Since the largest increase in cloud cover with
Robust breast tumor detection via shrinkage covariance matrix estimation

Microwave imaging (MWI) is a promising imaging modality for breast tumor detection. One challenge faced by the ultra-wideband (UWB) radar-based breast cancer detection is the estimation of clutter-plus-noise covariance matrix. To render a more accurate covariance matrix estimate when the number of samples is not large, this paper presents a new covariance matrix estimate using the shrinkage method. The parameters of the proposed shrinkage-based covariance matrix are cast as a modified semi-definite programming (SDP) problem based on the minimum mean-squared error (MMSE) criterion. Moreover, to reduce the computational overhead, we also incorporate the compressive sensing (CS) technique with the above scheme for UWB breast tumor detection. The performance of the Capon beamformer based on the new reconstructed covariance matrix is tested under multistatic scenario by a 2-D numerical breast analysis model. Simulations show that the proposed approach possesses a better target identification capability and improves the signal-to-clutter-noise ratio (SCNR) than the existing counterparts.
SERIMI results for OAEI 2011

This paper presents the results of SERIMI in the Ontology Alignment Evaluation Initiative (OAEI) 2011. We participate in the track [email protected] (IMEI) of the campaign. We first describe the basic interlinking process and interlinking strategies in SERIMI, and then we present specific techniques used in this track. We conclude with a discussion of our results, and possible directions to improve SERIMI in future work.
Symbolic Model Checking forSequential Circuit Veri cationJ

The temporal logic model checking algorithm of Clarke, Emerson, and Sistla [17] is modi ed to represent state graphs using binary decision diagrams (BDDs) [7] and partitioned transition relations [10, 11]. Because this representation captures some of the regularity in the state space of circuits with data path logic, we are able to verify circuits with an extremely large number of states. We demonstrate this new technique on a synchronous pipelined design with approximately 5 10120 states. Our model checking algorithm handles full CTL with fairness constraints. Consequently, we are able to express a number of important liveness and fairness properties, which would otherwise not be expressible in CTL. We give empirical results on the performance of the algorithm applied to both synchronous and asynchronous circuits with data path logic. 3
Exploiting phase transitions for the efficient sampling of the fixed degree sequence model

Real-world network data is often very noisy and contains erroneous or missing edges. These superfluous and missing edges can be identified statistically by assessing the number of common neighbors of the two incident nodes. To evaluate whether this number of common neighbors, the so called co-occurrence, is statistically significant, a comparison with the expected co-occurrence in a suitable random graph model is required. For networks with a skewed degree distribution, including most real-world networks, it is known that the fixed degree sequence model, which maintains the degrees of nodes, is favourable over using simplified graph models that are based on an independence assumption. However, the use of a fixed degree sequence model requires sampling from the space of all graphs with the given degree sequence and measuring the co-occurrence of each pair of nodes in each of the samples, since there is no known closed formula for this statistic. While there exist log-linear approaches such as Markov chain Monte Carlo sampling, the computational complexity still depends on the length of the Markov chain and the number of samples, which is significant in large-scale networks. In this article, we show based on ground truth data that there are various phase transition-like tipping points that enable us to choose a comparatively low number of samples and to reduce the length of the Markov chains without reducing the quality of the significance test. As a result, the computational effort can be reduced by an order of magnitudes.
An Intricate Mechanism of Action of Avonex in Relapsing Remitting Multiple Sclerosis Patients: Variation of Serum Titre of Interleukin-17A, Interleukin-10 and Transforming Growth Factor-β.

INTRODUCTION The immunopathogenesis of multiple sclerosis (MS) is a main field of research, together with the mechanism of action of most immune therapies in this disease, such as interferon beta. Interleukin (IL)-17 is considered to play a central part in the initial immune cascade in MS, though there are numerous interactions between other cytokines that might explain the heterogeneity of disease evolution and treatment response. MATERIAL AND METHODS We tested the serum levels of IL-17A, IL-10 and transforming growth factor (TGF-β) using the enzyme-linked immunosorbent assay method in three small groups of relapsing-remitting MS patients: 10 being naïve without treatment, 10 patients receiving Avonex treatment early in the MS evolution (≤ one year from the MS onset) and 12 MS patients who received Avonex later in the disease evolution. The values were compared with those obtained from 32 healthy subjects using statistical analysis. RESULTS In the naive multiple sclerosis group: IL-17A values were statistically higher than among healthy subjects; IL- 17A inversely correlated with MS duration; serum IL-17A negatively correlated with TGF-β. A direct correlation was found between the serum titre of IL-17A and IL-10 in the early treated multiple sclerosis group; the titre of IL-17A was significantly reduced compared with that from the late treated multiple sclerosis group. CONCLUSION The role in MS pathology of IL-17A, IL-10 and TGF-β is only partially elucidated. IL-17 plays an important role in the inflammatory phase of relapsing-remitting MS and is diminished by Avonex mainly if this disease modifying treatment is administered early in the evolution of MS.
SIGMA - A Tool for Coarse-grained Plan Matching in Automated program Understanding

Plan-based program understanders recognize concepts in the code by comparing the target code chunk against a library of programming plans. For a large plan library, an exhaustive search for a matching plan during concept recognition is not effective. This paper describes a prototype system, SIGMA (the Signature Matching Agent), which supports the comprehension process in the BUG-DOCTOR fault localization tool. SIGMA is a coarse-grained plan matching component. It uses a set of code features called a signature, as an index to retrieve a reduced set of plans from a plan library for matching with the target code chunk. Preliminary experiments with SIGMA show promising results in filtering irrelevant plans from the library. It appears that SIGMA may be an effective pre-processing tool for use prior to attempting the computational intense concept recognition process. We believe that the successful application of the techniques used by SIGMA to plan retrieval could facilitate scaling up automated plan-based understanders for use on large legacy systems.
Face detection and recognition using neural network and hidden Markov models

This paper proposes an integrated system for face recognition in cluttered images. An extension of the system is able to recognize faces by directly working with JPEG compressed image data without decompressing. The system consists of face detection using a polynomial neural network (PNN) and face recognition using pseudo-2D hidden Markov models (P2D HMM or pseudo-2D HMM). Firstly, images from a database or a Website are rescaled and preprocessed to form a standard size and file format. Secondly, face regions in image are located and extracted by PNN. Finally through face recognition the detected faces are labeled as one person of the database or rejected as "new subject". Our experiments show that the face detector has a higher detection rate and low false positive rate. At the same time, the face recognition achieves higher performance with lower complexity and less computation time compared with other systems.
Bifurcation in Blood Oscillatory Rhythms for Patients with Ischemic Stroke: A Small Scale Clinical Trial using Laser Doppler Flowmetry and Computational Modeling of Vasomotion

We describe application of spectral analysis of laser Doppler flowmetry (LDF) signals to investigation of cerebrovascular haemodynamics in patients with post-acute ischemic stroke (AIS) and cerebrovascular insufficiency. LDF was performed from 3 to 7 days after the onset of AIS on forehead in the right and left supraorbital regions in patients. Analysis of LDF signals showed that perfusion in the microvasculature in AIS patients was lower than that in patients with cerebrovascular insufficiency. As a result of wavelet analysis of the LDF signals we obtained activation of the vasomotion in the frequency range of myogenic oscillation of 0.1 Hz and predominantly nutritive regime microcirculation after systemic thrombolytic therapy of the AIS patients. In case of significant stroke size, myogenic activity, and nutritive pattern microhaemodynamics were reduced, in some cases non-nutritive pattern and/or venular stasis was revealed. Wavelet analysis of the LDF signals also showed asymmetry in wavelet spectra of the LDF signals obtained in stroke-affected and unaffected hemispheres in the AIS patients. A mechanism underlying the observed asymmetry was analyzed by computational modeling of vasomotion developed in Arciero and Secomb (2012). We applied this model to describe relaxation oscillation of arteriole diameter which is forced by myogenic oscillation induced by synchronous calcium oscillation in vascular smooth muscle cells. Calculation showed that vasomotion frequency spectrum at the low-frequency range (0.01 Hz) is reciprocally modulated by myogenic oscillation (0.1 Hz) that correlates with experimental observation of inter-hemispheric variation in the LDF spectrum.
Predictors of survival in patients with spinal ependymoma

Abstract Objectives: We aimed to examine the impact of demographic and treatment factors on overall survival among spinal ependymoma patients. Methods: Using data from Surveillance, Epidemiology, and End Results (SEER) from 1990–2008, we evaluated subjects with histologically confirmed spinal cord ependymoma. Results: We identified 1,353 patients with spinal ependymoma (mean age 43.5 years). Among these, 26 had anaplastic ependymoma (AE), 374 had myxopapillary ependymoma (MPE), and 953 had other low-grade ependymoma (non-MPE). Median follow-up was 61 months. Overall survival at 5 years was 97% for MPE, 92% for low-grade non-MPE, and 73% for AE. Gross total resection (GTR) was achieved in 58% of subjects with MPE, 51% with low-grade non-MPE, and 50% with AE. Radiation occurred more often after subtotal resection (STR) than after GTR, and more often among those with anaplastic histology. Histology and extent of surgical resection were significant prognostic factors in multivariate analyses. Compared to MPE, subjects with low-grade non-MPE had a higher risk of mortality at 5 years (HR 2.35, P = 0.03), as did subjects with AE (HR 8.63, P < 0.01). Compared to GTR, STR was associated with an increased risk of mortality at 5 years (HR 2.2, P = 0.01), as was biopsy only (HR 2.05, P = 0.03) and no surgery (HR 4.97, P < 0.01). Among patients with either STR or GTR, adjuvant radiotherapy did not confer a survival benefit at 5 years (STR: HR 2.29, P = 0.07, and GTR: HR 2.2, P = 0.12). Discussion: We found that lower grade histology and higher extent of surgical resection were significant prognostic factors for more favourable survival outcomes for spinal ependymoma patients.
24.4 A 680nA fully integrated implantable ECG-acquisition IC with analog feature extraction

Ultra-low power consumption and miniature size are by far the most important design requirements for implantable pacemakers. In order to guarantee a long life span of the device, saving power in the sensing IC is a primary concern as cardiac rhythm disorders must be continuously monitored [1]. Shifting the functionality of QRS-band power parameter extraction to the analog domain can reduce system-level power consumption of heartbeat detection significantly through minimizing computational complexity of the DSP [2,3]. In addition, current biomedical ICs still require further improvement of power efficiency as their analog back ends consume significant power [2-4]. For low-power means, the presented analog signal processor (ASP) introduces a power-efficient analog feature extraction, a current-multiplexed ADC driver and a flexible ADC. This advances the state of the art by reducing the power consumption of the ASP below 1μW without compromising other specs, such as input SNR >70dB, CMRR >90dB, PSRR >80dB, and enables low-power heartbeat detection for implantable pacemakers.
The Role of the Hostile-World Scenario in Predicting Physical and Mental Health Outcomes in Older Adults

Objective: The hostile-world scenario (HWS) denotes a personal belief system regarding threats to one’s physical and mental integrity. We examined whether the HWS predicted health among older adults. Method: The Israeli branch of the Survey of Health, Ageing and Retirement in Europe (SHARE-Israel) provided data on 1,286 participants, aged 50+, interviewed in two waves 4 years apart. A special measure assembled items pertinent to the HWS throughout the SHARE survey. Nine outcomes indicated physical health (e.g., activities of daily living, medical conditions) and mental health (e.g., depressive symptoms, satisfaction with life). Results: The HWS at Wave 1 predicted all physical and mental outcomes at Wave 2, except cognitive functioning, beyond effects of sociodemographics and the respective outcome’s baseline at Wave 1. This predictive effect was stronger among older participants. Discussion: The results support the conception of the HWS as a psychological monitor that senses approaching functional declines in later life.
Boosted Linear Projections for Discriminant Analysis

In this paper we explain a new linear Discriminant technique to project high dimensional data into a low dimensional subspace where the accuracy of the nearest neighbor classifier is maximized. Our algorithm combines a set of one-dimensional projections, using the Adaboost algorithm, to form the final discriminant projection matrix. We also introduce the way to establish an order to rank the features extracted, and select the best directions given a fixed low dimensional subspace. Due to nature of the algorithm, we do not restrict the projection vectors to be orthogonal, and no global assumptions on the data distribution are performed, the projection matrix is constructed into the boosting scheme minimizing the classification error at each iteration. Two different experiments using our technique are also presented, a gender recognition problem using face images, and the classification of manuscript digits.