Miracle-dz/UniFAR-FTUs huggingface dataset:
Implicit comparison of accuracy of heart rate variability spectral measures estimated via heart rate and heart period signals

In this article an overview of existing signals for evaluation of HRV spectral domain measures is made. Functional dependency between heart rate and heart period signals has been analyzed. Artificial data series have been used to extract features of spectra estimated via heart rate and heart period signals. Criteria for choosing between mentioned signals has been introduced and discussed. Implicit comparison of distortions of spectral measures estimation has been tested on ldquoFantasiardquo database (Physionet.org). Statistical analysis of differences between calculated spectral HRV measures obtained using heart rate and heart period signals has been presented.
Expression of Neuronal Connexin36 in AII Amacrine Cells of the Mammalian Retina

We have studied the expression pattern of neuronal connexin36 (Cx36) in the mouse and rat retina. In vertical sections of both retinas, a polyclonal antibody directed against Cx36 produced punctate labeling in the inner plexiform layer (IPL). Intense immunoreactivity was localized to the entire OFF sublamina of the IPL, and much weaker staining could be observed in the ON sublamina. Double-labeling experiments in the rat retina with antibodies directed against parvalbumin indicate that Cx36 is expressed on dendrites of AII amacrine cells. Cx36-like immunoreactivity in sublamina a of the IPL did not overlap with lobular appendages or cell bodies of AII amacrine cells. In a mouse retinal slice preparation, AII amacrine and ON cone bipolar cells were intracellularly injected with Neurobiotin and counterstained with antibody against Cx36. Punctate labeling appeared to be in register with dendritic arborization of AII amacrines and cone bipolar cells in the ON sublamina of the IPL. Whereas AII amacrine cells isolated from the rat retina clearly displayed Cx36-like immunoreactivity, isolated ON cone bipolar cells were negative for Cx36. Axon terminals of rod bipolar cells were decorated with Cx36-positive contacts but did not express Cx36 themselves. These results indicate that Cx36 is expressed by AII amacrine cells in homologous and heterologous gap junctions made with AII amacrines and cone bipolar cells, respectively. The heterologous gap junctions appear to be heterotypic, because ON cone bipolar cells do not express Cx36.
An Algorithm of Mean-Shift Template Update Based On Mixture Gaussian Model

To improve the limitation of Mean-Shift lack of the template update, an algorithm based on mixture Gaussian model is proposed. It treats the target region as ldquobackgroundrdquo, and three Gaussian functions are used to evaluate each pixel value in the target region. After using Mean-Shift algorithm to track the target region in the current frame, we update the Mixture Gaussian Model with the new target region in the current frame, so that the current target template can update automatically with the changing surveillance of selected target. Experiment results show that this algorithm can successful track the changing target surveillance under the condition of change illumination and surface.
The control of a double-pendulum system

In this paper, the control of a double mass and spring system as a physical model of a flexible arm robot is considered. The main goal of design is to use an appropriate control method that produces suitable external torques such that the whole system can be completely stabilized and controlled. For this purpose, mathematical model of the system is required which is achieved by Lagrange's equations in the first part of the paper. Since the controller design in this paper is based on state space description, these dynamical equations are re-written in the form of state-space equations and are linearized about an operating state. After examining the controllability of the system, a state feedback controller and also a Linear Quadratic Regulator (LQR) are designed. Moreover, since in these controllers the states of the system are required, a suitable full-order state estimator is developed as well. Finally, simulation results are provided to show the effectiveness of the proposed controllers.
Fair Division Procedures : Why use Mathematics ?

2 From Solutions to Procedures 14 3 Why do we (have to) use Mathematics? 18 4 Concluding Remarks 19 Good sense is, of all things among men, the most equally distributed; for everyone thinks himself so abundantly provided with it, that those even who are the most difficult to satisfy in everything else, do not usually desire a larger measure of the quality than they already possess.
Toll-Like Receptor 9 Deficiency Protects Mice against Pseudomonas aeruginosa Lung Infection

Pseudomonas aeruginosa is an opportunistic pathogen involved in nosocomial infections. While a number of studies have demonstrated the roles of TLR2, TLR4 and TLR5 in host defense againt P. aeruginosa infection, the implication of TLR9 in this process has been overlooked. Here, we show that P. aeruginosa DNA stimulates the inflammatory response through TLR9 pathway in both a cell line and primary alveolar macrophages (AMs). This activation requires asparagine endopeptidase- and endosomal acidification. Interestingly, TLR9-/- mice resisted to lethal lung infection by P. aeruginosa, compared to WT C57BL/6 mice. The resistance of TLR9-/- mice to P. aeruginosa infection was associated with: (i) a higher ability of TLR9-/- AMs to kill P. aeruginosa; (ii) a rapid increase in the pro-inflammatory cytokines such as TNFα, IL-1β and IL-6 production; and (iii) an increase in nitric oxide (NO) production and inductible NO synthase expression in AMs. In addition, inhibition of both IL-1β and NO production resulted in a significant decrease of P. aeruginosa clearance by AMs. Altogether these results indicate that TLR9 plays a detrimental role in pulmonary host defense toward P. aeruginosa by reducing the AMs clearance activity and production of IL-1β and NO necessary for bacteria killing.
Investigation of reflection area on strategic reflectarray resonant elements

Selection of strategic resonant elements plays an effective role in enhancing the reflectivity performance of reflectarrays. This paper presents a systematic analysis of various potential reflectarray resonant elements for operation at X-band (8-12GHz) frequency range. The considerations mainly focus on the exploitation of reflection area for an accurate characterization of reflection loss and reflection phase performance. Furthermore, two patch unit cells have been fabricated for each configuration by mounting on the top of the Rogers RT/Duroid 5870 dielectric substrate. The scattering parameter measurements of the fabricated unit cells have also been carried out using vector network analyzer based on waveguide simulator technique. Measured results demonstrated that reduction in reflection area of resonant elements from 105.74mm2 to 7.33mm2 tends to increase the reflection loss values from 2.63dB to 20.25dB. Moreover the reduction in phase errors offering an increased measured static phase range of 290° is also shown by employing triangular loop element.
Gesture-based interaction with virtual 3D objects on large display: what makes it fun?

In this paper, we describe a virtual game where game play is afforded by the user's silhouette interacting with on-screen 3D gaming objects, e.g. a soccer ball or a "chapteh" (Shuttlecock Kicking) -- a game played traditionally in villages, i.e. "kampongs", in Asia. The virtual game system projects a life-size image of the location where the game is often played, e.g. soccer field when soccer is played or village playground in the case of "chapteh". The player's silhouette is super-imposed on the screen as the user interacts with the on-screen virtual 3D object using his body movement, e.g. bounce or lift. We compare the game play when different design variables were changed, e.g. replacing the soccer field image or removing the silhouette outline, to evaluate which design variable affects a user's experience during game play.
Distributed Approximation in a Constant Number of Rounds

We present a novel efficient distributed approximation algorithm for covering and packing linear programs (LP). We show that on general graphs, for this class of LPs, a non-trivial approximation ratio can be achieved. Namely, for k ∈ O(log(ρ∆)), our (deterministic) algorithm achieves a (ρ∆)approximation in O(k) rounds, using only messages of size O(log(ρ∆)). Increasing k, we get an (1 + ε)-approximation in time O(log(ρ∆)/ε) and therefore only log rounds are needed in order to get a constant approximation ratio. Additionally, we show that by combining our LP algorithm with randomized rounding techniques, we obtain efficient distributed approximation algorithms for a number of combinatorial problems.
From liberation to salvation: Revolutionary critical pedagogy meets liberation theology

This conversation between Peter McLaren and Petar Jandrić brings about some of the most recent and deepest of McLaren’s insights into the relationship between revolutionary critical pedagogy and liberation theology, and outlines the main directions of development of McLaren’s thought during and after Pedagogy of Insurrection. In the conversation, McLaren reveals his personal and theoretical path to liberation theology. He argues for the relevance of liberation theology for contemporary social struggles, links it with social sciences, and addresses some recent critiques of Pedagogy of Insurrection. McLaren identifies the idolatry of money as the central point of convergence between liberation theology and Marxism. Developing this thought further, he asserts that Jesus was a communist. McLaren analyses the revolutionary praxis of liberation theology in Latin America, and concludes that the struggle needs to avoid violence and endure without losing tenderness. He analyzes the international politics of liberation theology and shows that liberation theology was demonized by the US administration because it works for the poor. McLaren then expands experiences from Latin America towards a global ethics of solidarity, criticizes Church positions on various matters, and insists on a critical approach to Church dogmas. He explores theoretical and practical dissonances between Marxism and Christianity, and expands them towards a more general dichotomy between the material and the spiritual. He explores the Christian eschaton – the arrival of the Kingdom of God – and links it to Marx’s prophecy of the future socialist society. Finally, he explores ecumenical opportunities of liberation theology and firmly links it with the arrival of the socialist society.
Practical Scoring System for the Identification of Patients with Intracerebral Hemorrhage at Highest Risk of Harboring an Underlying Vascular Etiology: The Secondary Intracerebral Hemorrhage Score

BACKGROUND AND PURPOSE: An ICH patient's risk of harboring an underlying vascular etiology varies according to baseline clinical and NCCT characteristics. Our aim was to develop a practical scoring system to stratify patients with ICH according to their risk of harboring a vascular etiology. MATERIALS AND METHODS: Using a data base of 623 patients with ICH evaluated with MDCTA during a 9-year period, we developed a scoring system based on baseline clinical characteristics (age group [0–2 points], sex [0–1 point], neither known HTN nor impaired coagulation [0–1 point]), and NCCT categorization (0–2 points) to predict the risk of harboring a vascular lesion as the ICH etiology (SICH score). We subsequently applied the SICH score to a prospective cohort of 222 patients with ICH who presented to our emergency department during a 13-month period. Using ROC analysis, we calculated the AUC and MOP for the SICH score in both the retrospective and prospective patient cohorts separately and the entire patient population. Patients with SAH in the basal cisterns were excluded. RESULTS: A vascular etiology was found in 120 of 845 patients with ICH evaluated with MDCTA (14.2%), most commonly AVMs (45.8%), aneurysms with purely intraparenchymal rupture (21.7%), and DVSTs (16.7%). The MOP was reached at a SICH score of >2, with the highest incidence of vascular ICH etiologies in patients with SICH scores of 3 (18.5%), 4 (39%), 5 (84.2%), and 6 (100%). There was no significant difference in the AUC between both patient cohorts (0.86–0.87). CONCLUSIONS: The SICH score successfully predicts a given ICH patient's risk of harboring an underlying vascular etiology and could be used as a guide to select patients with ICH for neurovascular evaluation to exclude the presence of a vascular abnormality.
Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA). This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX). This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.
Adapting noisy speech models — Extended uncertainty decoding

Most conventional techniques for noise adaptation assume a clean initial speech model which is adapted to a specific noise condition using adaptation data accumulated from the condition. In this paper, a different problem is considered, i.e. adapting a noisy speech model to a specific noise condition. For example, the initial noisy model may be a multi-condition model which is used to provide more accurate transcripts for the adaptation data than could be provided by a clean model, thereby obtaining a more accurate adaptation. We develop the formulation for this new problem by combining and extending maximum likelihood linear regression (MLLR), constrained MLLR (CMLLR) and uncertainty decoding techniques. We also present an implementation which has been tested on the Aurora 4 database, assuming an initial multi-condition model trained using white noise corrupted data. Significant word error rate (WER) reductions are achieved in comparison with other approaches.
A Flexible and Powerful Bayesian Hierarchical Model for ChIP–Chip Experiments

Summary Chromatin‐immunoprecipitation microarrays (ChIP–chip) that enable researchers to identify regions of a given genome that are bound by specific DNA‐binding proteins present new challenges for statistical analysis due to the large number of probes, the high noise‐to‐signal ratio, and the spatial dependence between probes. We propose a method called BAC (Bayesian analysis of ChIP–chip) to detect transcription factor bound regions, which incorporate the dependence between probes while making little assumptions about the bound regions (e.g., length). BAC is robust to probe outliers with an exchangeable prior for the variances, which allows different variances for the probes but still shrink extreme empirical variances. Parameter estimation is carried out using Markov chain Monte Carlo and inference is based on the joint distribution of the parameters. Bound regions are detected using posterior probabilities computed from the joint posterior distribution of neighboring probes. We show that these posterior probabilities are well calibrated and can be used to obtain an estimate of the false discovery rate. The method is illustrated using two publicly available ChIP–chip data sets containing 18 experimentally validated regions. We compare our method to four other baseline and commonly used techniques, namely, the Wilcoxon's rank sum test, TileMap, HGMM, and MAT. We found BAC and HGMM to perform best at detecting validated regions. However, HGMM appears to be very sensitive to probe outliers compared to BAC. In addition, we present a simulation study, which shows that BAC is more powerful than the other four techniques under various simulation scenarios while being robust to model misspecification.
PLOrk: The Princeton Laptop Orchestra, Year 1

In this paper we report on the current state of the newly established Princeton Laptop Orchestra (PLOrk), a collection of 15 meta-instruments each consisting of a laptop computer, interfacing equipment, and a hemispherical speaker. Founded in the fall of 2005, PLOrk represents the first laptop ensemble of its size and kind, and brings together many of our research and aesthetic interests as musicians, composers, and computer scientists. Here we chronicle the first steps of the ensemble, including details about the technology, the music, compositional challenges, and what we have learned in the process.
A Survey on Super-Resolution Methods for Image Reconstruction

Today, in many applications of Machine vision, image SuperResolution is preferred. Super-Resolution is estimation of a high-resolution image from an image or several low resolution images. Popular techniques in the field of enhancing images can be used to remove noise or blurring. In this paper, an overview of super resolution methods has been presented. Types of resolution methods have been used so far can be divided into three groups as frequency-domain methods, spatial domain methods and techniques can be classified as the wavelet domain. Super-resolution methods in different domains have different characteristics and comparison between these methods is usually done using a special index in one domain. In this paper, we will introduce these indexes and review best techniques used in all three domains.
3D model capture system

3D model capture system will overcome the limitation of current 3D model software such as required more than 2D standstill image as inputs and with poor or no measurement features. This research is to develop a quick measurement of simple symmetrical geometrical object by input three 2D standstill images of the object for 3D development. These three images are the top view, front view, and side view of the object which capture by the low resolution webcam. The input image will undergo several stages of image processing to generate the data required for 3D model construction of the original object such as Red Green Blue (RGB) to Hue Saturation Value (HSV) color map conversion, HSV to Otsu thresholding and mesh methods. It shows that, the 3D model constructed able to achieved 95% accuracy. In addition, the 3D model also able to provide object measurements such as height, width and volume.
A nonlinear programming approach for estimation of transmission parameters in childhood infectious disease using a continuous time model

Mathematical models can enhance our understanding of childhood infectious disease dynamics, but these models depend on appropriate parameter values that are often unknown and must be estimated from disease case data. In this paper, we develop a framework for efficient estimation of childhood infectious disease models with seasonal transmission parameters using continuous differential equations containing model and measurement noise. The problem is formulated using the simultaneous approach where all state variables are discretized, and the discretized differential equations are included as constraints, giving a large-scale algebraic nonlinear programming problem that is solved using a nonlinear primal–dual interior-point solver. The technique is demonstrated using measles case data from three different locations having different school holiday schedules, and our estimates of the seasonality of the transmission parameter show strong correlation to school term holidays. Our approach gives dramatic efficiency gains, showing a 40–400-fold reduction in solution time over other published methods. While our approach has an increased susceptibility to bias over techniques that integrate over the entire unknown state-space, a detailed simulation study shows no evidence of bias. Furthermore, the computational efficiency of our approach allows for investigation of a large model space compared with more computationally intensive approaches.
Evidence of systematic Expressed Sequence Tag ( EST ) I . M . A . G . E . clone cross-hybridization on cDNA microarrays

We present evidence of a potentially serious source of error intrinsic to all spotted cDNA microarrays that use I.M.A.G. E. clones of expressed sequence tags (ESTs). We found that a high proportion of these EST sequences contain 5’ end poly(dT) sequences that are remnants from the oligo (dT)-primed reverse transcription of polyadenylated mRNA templates used to generate EST cDNA for sequence clone libraries. Analysis of expression data from two singledye cDNA microarray experiments showed that ESTs whose sequences contain repeats of consecutive 5’-end dT residues appeared to be strongly co-expressed, while expression data of all other sequences exhibited no such pattern. Our analysis suggests that expression data from sequences containing 5’ poly(dT) tracts is more likely to be due to systematic crosshybridization of these poly(dT) tracts than true mRNA co-expression. This indicates that existing data generated by cDNA microarrays containing I.M.A.G. E clone ESTs should be filtered to remove expression data containing significant 5’ poly(dT) tracts.
Correlation Structure of International Equity Markets During Extremely Volatile Periods

Recent studies in international finance have shown that correlation of international equity returns increases during volatile periods. However, correlation should be used with great care. For example, assuming a multivariate normal distribution with constant correlation, conditional correlation during volatile periods (large absolute returns) is higher than conditional correlation during tranquil periods (small absolute returns) even though the correlation of all returns remains constant over time. In order to test whether correlation increases during volatile periods, the distribution of the conditional correlation under the null hypothesis must then be clearly specified. In this paper we focus on the correlation conditional on large returns and study the dependence structure of international equity markets during extremely volatile bear and bull periods. We use "extreme value theory" to model the multivariate distribution of large returns. This theory allows one to specify the distribution of correlation conditional on large negative or positive returns under the null hypothesis of multivariate normality with constant correlation. Empirically, using monthly data from January 1959 to December 1996 for the five largest stock markets, we find that the correlation of large positive returns is not inconsistent with multivariate normality, while the correlation of large negative returns is much greater than expected.
Characterizing a varactor contribution to the residual distortion of load-modulated PAs

In this paper, a technique for extracting the Taylor series expansion coefficients of a varactor reactive nonlinearity is presented. A single diode and a dual-device antiseries (back-to-back cathode) combination have been characterized, aimed to accurately control their contribution to the residual intermodulation distortion (IMD) appearing in load-modulated power amplifiers (PAs). A test set-up for dynamically measuring the harmonic content has been implemented, able to be extended to the evaluation of load-based envelope tracking transmitters.