Miracle-dz/UniFAR-FTUs huggingface dataset:
Reflex‐Hemodynamic Adjustments and Baroreflex Sensitivity During Converting Enzyme Inhibition with MK‐421 in Normal Humans

Invasive hemodynamic measurements and determination of baroreflex sensitivity were carried out in 12 mildly sodium-depleted normotensive volunteers in a randomized double-blind crossover study with a single dose of converting enzyme inhibitor, MK-421, and placebo. In supine humans at rest, MK-421 caused a reduction in blood pressure through a fall in total peripheral resistance and an increase in arterial compliance. Thus, MK-421 appears to dilate both resistance vessels and larger arteries. Cardiac output increased, but contrary to the effects of other vasodilators, the increase was due to a higher stroke volume with an unchanged heart rate. The lack of heart rate response may well reflect enhanced central parasympathetic cardiac inhibition. Head-up tilt on MK-421 caused an additional decrease in blood pressure in 65° of the subjects. The major determinant for the blood pressure fall during tilt and converting enzyme inhibition was a decrease in cardiac performance, while the reflex increase of arteriolar and venous tone was largely unimpaired. The decreased stroke volume may be secondary to elimination of a positive inotropic effect of angiotensin II (All). It is also conceivable that in the absence of AH the inotropic response to sympathetic activation is inadequate during tilt in these sodium-depleted normotensive individuals. Baroreflex sensitivity to blood pressure increase (i.v. phenylephrine) was enhanced after MK 421. Arterial compliance was increased, and this may explain the altered baroreceptor sensitivity. However, a possible central nervous enhancement of baroreceptor sensitivity after MK-421 could not be ruled out in this study.
A Neural Network Based Hybrid Mixture Model to Extract Information from Non-linear Mixed Pixels

Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember’s (pure pixel’s) distribution. This communication discusses inferring class fraction through a novel hybrid mixture model (HMM). HMM is a three-step process, where the endmembers are first derived from the images themselves using the N-FINDR algorithm. These endmembers are used by the linear mixture model (LMM) in the second step that provides an abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual ground proportions are fed into neural network based multi-layer perceptron (MLP) architecture as input to train the neurons. The neural output further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. HMM is first implemented and validated on simulated hyper spectral data of 200 bands and subsequently on real time MODIS data with a spatial resolution of 250 m. The results on computer simulated data show that the method gives acceptable results for unmixing pixels with an overall RMSE of 0.0089 ± 0.0022 with LMM and 0.0030 ± 0.0001 with the HMM when compared to actual class proportions. The unmixed MODIS images showed overall RMSE with HMM as 0.0191 ± 0.022 as compared to the LMM output considered alone that had an overall RMSE of 0.2005 ± 0.41, indicating that individual class abundances obtained from HMM are very close to the real observations.
Trening uwagi u dzieci z ADHD – przegląd badań

Monika Deja © Medical Communications Sp. z o.o. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND). Reproduction is permitted for personal, educational, non-commercial use, provided that the original article is in whole, unmodified, and properly cited. Received: 29.09. 2016 Accepted: 05.12. 2016 Published: 31.03. 2017 © Psychiatr Psychol Klin 2017, 17 (1), p. 63–71 DOI: 10.15557/PiPK.2017. 0007
Optimal Spline Trajectories by Modelling Kinematic Constraints in Robot Soccer

We integrate learning and motion planning for soccer playing differential drive robots using Bayesian optimisation. Trajectories generated using end-slope cubic Bezier splines are first optimised globally through Bayesian optimisation for a set of candidate points with obstacles. The optimised trajectories along with robot and obstacle positions and velocities are stored in a database. The closest planning situation is identified from the database using k-Nearest Neighbour approach. It is further optimised online through reuse of prior information from previously optimised trajectory. Our approach reduces computation time of trajectory optimisation considerably. Velocity profiling generates velocities consistent with robot kinodynamoic constraints, and avoids collision and slipping. Extensive testing is done on developed simulator, as well as on physical differential drive robots. Our method shows marked improvements in mitigating tracking error, and reducing traversal and computational time over competing techniques under the constraints of performing tasks in real time.
CHARACTERIZATION OF THE NPMPLE OF THE DISEASE ONSET DISTRIBUTION FUNCTION FOR A SURVIVAL-SACRIFICE MODEL

In carcinogenicity experiments with animals where the tumor is not palpable it is common to observe only the time of death of the animal, the cause of death (the tumor or another independent cause, as sacrifice) and whether the tumor was present at the time of death. These last two indicator variables are evaluated after an autopsy. Defining the non-negative variables T1 (time of tumor onset), T2 (time of death from the tumor) and C (time of death from an unrelated cause), we observe (Y,∆1,∆2), where Y = min {T2, C}, ∆1 = 1{T1≤C}, and ∆2 = 1{T2≤C}, T1 and T2 have a joint distribution function F such that P (T1 ≤ T2) = 1, and are independent of C. Some authors call this model a “survival-sacrifice model”. The interest here is to estimate the marginal distribution functions F1 and F2 of T1 and T2, respectively (since F is not identifiable). One possible way of doing that is by using a consistent estimator F̂2 for F2 (Kaplan-Meier, for example) and then plugging it in the loglikelihood to obtain F̂1, the nonparametric maximum pseudo likelihood estimator (NPMPLE) of F1. A characterization theorem of F̂1 is stated here and an algorithm for its calculation is presented.
A Mid-level Melody-based Representation for Calculating Audio Similarity

We propose a mid-level melody-based representation that incorporates melodic, rhythmic and structural aspects of a music signal and is useful for calculating audio similarity measures. Most current approaches to music similarity use either low-level signal features, such as MFCCs that mostly capture timbral characteristics of music and contain little semantic information, or require symbolic representations, which are difficult to obtain from audio signals. The proposed mid-level representation is our attempt to bridge the gap between audio and symbolic domains by providing an integrated melodic, rhythmic and structural representation of music signals. The representation is based on a set of melodic fragments extracted from prominent melodic lines, it is beat-synchronous, which makes it independent of tempo variations and contains information on repetitions of short melodic phrases within the analyzed piece. We show how it can be calculated automatically from polyphonic audio signals and demonstrate its use for discovering melodic similarities between songs. We present results obtained by using the representation for finding different interpretations of songs in a music collection.
Reconstruction of specular surfaces using polarization imaging

Traditional intensity imaging does not offer a general approach for the perception of textureless and specular reflecting surfaces. Intensity based methods for shape reconstruction of specular surfaces rely on virtual (i.e. mirrored) features moving over the surface under viewer motion. We present a novel method based on polarization imaging for shape recovery of specular surfaces. This method overcomes the limitations of the intensity based approach because no virtual features are required. It recovers whole surface patches and not only single curves on the surface. The presented solution is general as it is independent of the illumination. The polarization image encodes the projection of the surface normals onto the image and therefore provides constraints on the surface geometry. Taking polarization images from multiple views produces enough constraints to infer the complete surface shape. The reconstruction problem is solved by an optimization scheme where the surface geometry is modelled by a set of hierarchical basis functions. The optimization algorithm proves to be well converging, accurate and noise resistant. The work is substantiated by experiments on synthetic and real data.
The Beacon Movement Detection Problem in Wireless Sensor Networks for Localization Applications

Localization is a critical issue in wireless sensor networks. In most localization systems, beacons are being placed as references to determine the positions of objects or events appearing in the sensing field. The underlying assumption is that beacons are always reliable. In this work, we define a new beacon movement detection (BMD) problem. Assuming that there are unnoticed changes of locations of some beacons in the system, this problem concerns how to automatically monitor such situations and identify such unreliable beacons based on the mutual observations among beacons only. Existence of such unreliable beacons may affect the localization accuracy. After identifying such beacons, we can remove them from the localization engine. Four BMD schemes are proposed to solve the BMD problem. Then, we evaluate how these solutions can improve the accuracy of localization systems in case there are unnoticed movements of some beacons. Simulation results show that our solutions can capture most of the unnoticed beacon movement events and thus can significantly alleviate the degradation of such events.
Novel and Viable Acetylcholinesterase Target Site for Developing Effective and Environmentally Safe Insecticides

Insect pests are responsible for human suffering and financial losses worldwide. New and environmentally safe insecticides are urgently needed to cope with these serious problems. Resistance to current insecticides has resulted in a resurgence of insect pests, and growing concerns about insecticide toxicity to humans discourage the use of insecticides for pest control. The small market for insecticides has hampered insecticide development; however, advances in genomics and structural genomics offer new opportunities to develop insecticides that are less dependent on the insecticide market. This review summarizes the literature data that support the hypothesis that an insect-specific cysteine residue located at the opening of the acetylcholinesterase active site is a promising target site for developing new insecticides with reduced off-target toxicity and low propensity for insect resistance. These data are used to discuss the differences between targeting the insect-specific cysteine residue and targeting the ubiquitous catalytic serine residue of acetylcholinesterase from the perspective of reducing off-target toxicity and insect resistance. Also discussed is the prospect of developing cysteine-targeting anticholinesterases as effective and environmentally safe insecticides for control of disease vectors, crop damage, and residential insect pests within the financial confines of the present insecticide market.
The Effect of Dust Storm on the Microbial Quality of Ambient Air in Sanandaj: A City Located in the West of Iran

Background and Aims: The presence of pathogenic microorganisms in the dust storm can cause diseases such as Asthma, Pneumonia, and respiratory infections. The aim of this study was to determine the relationship between air-borne particles with airborne microorganisms in normal and dusty days in Sanandaj, a city located in the west of Iran. Materials and Methods: Air sampling was conducted during the normal and dusty days through Andersen single-stage impactor (28.3 L/min) for 2.5 min. Air particles concentration (PM10) was measured daily and microbial sampling was also conducted on every six days and on the dusty days. Finally, the data was analyzed by SPSS-16 (ANOVA and paired T-tests). Results: The concentration of airborne microorganisms (bacteria and fungi) was increased by an increase of the airborne particles. Particles concentration in May, June and July (twice per month) was more than of the standard value. The predominant species of bacteria and fungi during the occurrence of Dust storm was Bacillus spp. (56.2% of total bacteria) and Mycosporium spp. (28.6% of total fungi), respectively. Discussion and Conclusion: The results showed that the number of airborne microorganisms (bacteria and fungi) increased during the dust storm. Therefore, the microorganisms in the dust storm can cause biological harmful effects on human health.
Predicting Sensitive Relationships from Email Corpus

in this paper, we focus on the problem of predicting sensitive relationships from Email corpus. We refer to the problem of predicting sensitive relationships from a social network as link re-identification. We propose a predicting sensitive relationships method which has two steps. First step is counting mutual privacy communication. Second step is evaluation cluster factor. Experimental results on Enron email corpus are presented to support our analysis.
An Efficient and Robust Overlay Routing Scheme for VoIP

Even though voice over Internet protocol (VoIP) provides good call quality in most cases, there are occasions in which the delay, jitter and loss rate in the Internet exceeds the values tolerable for voice traffic. This leads to a degradation in voice quality or may cause a VoIP call to fail entirely. Overlay networks provide a solution to increase the quality of service (QoS) in the Internet. However, application-agnostic overlay networks cannot fully exploit the characteristics of VoIP traffic. In this paper, we propose a new overlay routing scheme for VoIP. By utilizing the signaling phase that precedes a VoIP call and passively monitoring VoIP flows, our VoIP overlay routing scheme can effectively select a route that meets a given quality of service criteria. It is robust in that it quickly reroutes traffic around network failures and efficient by creating only a minimal overhead through the tight integration with VoIP protocols
Statistical fusion of continuous labels: identification of cardiac landmarks

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.
Bil: A tool-chain for bitstream reverse-engineering

This paper performs an investigation into the security of Xilinx FPGA bitstreams, introducing a tool-chain for reversing bitstreams back to their device-specific netlists. Bitstream reversal is performed by querying a database containing the mapping of bitstream bits to their related configurable FPGA resources and a secondary database describing the FPGA structure. The mapping database is created by applying an algorithm that correlates binary bitstream data with data extracted from a corresponding netlist. The resource database is derived from a textual device description which can be obtained from the Xilinx design flow. The method can successfully reverse certain sections of the bitstream, although complete bitstream reversal remains infeasible for the time being. The presented tool-chain, the Bitfile Interpretation Library (BIL), improves on previous attempts at bitstream reverse engineering. It is made available as open source for further development.
Slip segmentation and slow rupture to the trench during the 2015, Mw8.3 Illapel, Chile earthquake

The 2015 Mw8.3 Illapel, Chile earthquake is the latest megathrust event on the central segment of that subduction zone. It generated strong ground motions and a large (up to 11 m runup) tsunami which prompted the evacuation of more than 1 million people in the first hours following the event. Observations during recent earthquakes suggest that these phenomena can be associated with rupture on different parts of the megathrust. The deep portion generates strong shaking while slow, large slip on the shallow fault is responsible for the tsunami. It is unclear whether all megathrusts can have shallow slip during coseismic rupture and what physical properties regulate this. Here we show that the Illapel event ruptured both deep and shallow segments with substantial slip. We resolve a kinematic slip model using regional geophysical observations and analyze it jointly with teleseismic backprojection. We find that the shallow and deep portions of the megathrust are segmented and have fundamentally different behavior. We forward calculate local tsunami propagation from the resolved slip and find good agreement with field measurements, independently validating the slip model. These results show that the central portion of the Chilean subduction zone has accumulated a significant shallow slip deficit and indicates that, given enough time, shallow slip might be possible everywhere along the subduction zone.
Detectable Subclinical Myocardial Necrosis Is Associated With Cardiovascular Risk in Stable Patients With Diabetes

OBJECTIVE To investigate the relationship between different degrees of subclinical myocardial necrosis, glycemic control, and long-term adverse clinical outcomes within a stable patient population with diabetes mellitus. RESEARCH DESIGN AND METHODS We examined 1,275 stable patients with diabetes mellitus undergoing elective diagnostic coronary angiography with cardiac troponin I (cTnI) levels below the diagnostic cut-off for defining myocardial infarction (MI) (<0.03 ng/mL). The relationship of subclinical myocardial necrosis (cTnI 0.009–0.029 ng/mL) with incident major adverse cardiovascular events (MACE; defined as any death, MI, or stroke) over 3 years of follow-up was examined. RESULTS Subclinical myocardial necrosis was observed in 22% of patients. A strong association was observed between the magnitude of subclinical myocardial necrosis and risk of 3-year incident MACE (hazard ratio, 1.98; 95% confidence interval, 1.48–2.65; P < 0.001) and remained statistically significant even after adjustment for traditional risk factors, high-sensitivity C-reactive protein, and creatinine clearance. Only a weak correlation was observed between the presence of subclinical myocardial necrosis and either glycemic control (r = 0.06; P = 0.044 for hemoglobin A1c versus cTnI) or insulin resistance (r = 0.04; P = 0.094 for glucose-to-insulin ratio versus cTnI). CONCLUSIONS The presence of detectable subclinical myocardial necrosis in stable patients with diabetes mellitus is associated with heightened long-term risk for MACE, independent of traditional risk factors and glycemic control.
Exploiting Coarse-Grain Parallelism in the MPEG-2 Algorithm

As the demand for multimedia applications increases, the performance of algorithms such as MPEG-2 video compression on general-purpose microprocessors is becoming more important. In this paper, we propose a number of coarse-grained parallel implementations of MPEG-2 decoding and encoding. We evaluate the performance of these implementations on a single-chip multiprocessor, and compare the performance against a baseline wide issue superscalar processor. On both MPEG-2 decoding and encoding, the single-chip multiprocessor achieves signi cantly better performance than a wide issue superscalar processor. We also nd that the coarse-grained parallelism in MPEG-2 is orthogonal to the ne-grained parallelism which can be exploited by multimedia extensions to the instruction set architecture such as Intel MMX. keywords: MPEG-2 decoding, MPEG-2 encoding, coarse-grained parallelism, single-chip multiprocessor, multimedia extensions
Development of raphe serotonin neurons from specification to guidance

The main features of the development of the serotonin (5‐HT) raphe neurons have been known for many years but more recent molecular studies, using mouse genetics, have since unveiled several intriguing aspects of the specification of the raphe serotonergic system. These studies indicated that, although all 5‐HT neurons in the raphe follow the same general program for their specification, there are also clear regional differences in the way that these neurons are specified and are guided towards different brain targets. Here we overview recent progress made in the understanding of the developmental programming of serotonergic neurons in the mouse raphe, emphasizing data showing how heterogeneous subsets of 5‐HT neurons may be generated. Serotonergic progenitors are produced in the brainstem in different rhombomeres under the influence of a set of secreted factors, sonic hedgehog and fibroblast growth factors, which determine their position in the neural tube. Two main transcriptional gene networks are involved in the specification of 5‐HT identity, with Lmx1b and Pet1 transcription factors as main players. A differential requirement for Pet1 was, however, revealed, which underlies an anatomical and functional diversity. Transcriptional programs controlling 5‐HT identity could also impact axon guidance mechanisms directing 5‐HT neurons to their targets. Although no direct links have yet been established, a large set of molecular determinants have already been shown to be involved in the growth, axon guidance and targeting of 5‐HT raphe neurons, particularly within the forebrain. Alterations in the molecular mechanisms involved in 5‐HT development are likely to have significant roles in mood disease predisposition.