Miracle-dz/UniFAR-FTUs huggingface dataset:
Coherent and Differential Space-Time Shift Keying: A Dispersion Matrix Approach

Motivated by the recent concept of Spatial Modulation (SM), we propose a novel Space-Time Shift Keying (STSK) modulation scheme for Multiple-Input Multiple-Output (MIMO) communication systems, where the concept of SM is extended to include both the space and time dimensions, in order to provide a general shift-keying framework. More specifically, in the proposed STSK scheme one out of Q dispersion matrices is activated during each transmitted block, which enables us to strike a flexible diversity and multiplexing tradeoff. This is achieved by optimizing both the space-time block duration as well as the number of the dispersion matrices in addition to the number of transmit and receive antennas. We will demonstrate that the resultant equivalent system model does not impose any Inter-Channel Interference (ICI), and hence the employment of single-stream Maximum Likelihood (ML) detection becomes realistic at a low-complexity. Furthermore, we propose a Differential STSK (DSTSK) scheme, assisted by the Cayley unitary transform, which does not require any Channel State Information (CSI) at the receiver. Here, the usual error-doubling, caused by the differential decoding, gives rise to 3-dB performance penalty in comparison to Coherent STSK (CSTSK). Additionally, we introduce an enhanced CSTSK scheme, which avoids the requirement of Inter-Antenna Synchronization (IAS) between the RF chains associated with the transmit Antenna Elements (AEs) by imposing a certain constraint on the dispersion matrix design, where each column of the dispersion matrices includes only a single non-zero component. Moreover, according to the turbo-coding principle, the proposed CSTSK and DSTSK schemes are combined with multiple serially concatenated codes and an iterative bit-to-symbol soft-demapper. More specifically, the associated STSK parameters are optimized with the aid of Extrinsic Information Transfer (EXIT) charts, for the sake of achieving a near-capacity performance.
Impact of Discrete Corrections in a Modular Approach for Trajectory Generation in Quadruped Robots

Online generation of trajectories in robots is a very complex task that involves the combination of different types of movements, i.e., distinct motor primitives. The later are used to model complex behaviors in robots, such as locomotion in irregular terrain and obstacle avoidance. In this paper, we consider two motor primitives: rhythmic and discrete. We study the effect on the robots’ gaits of superimposing the two motor primitives, considering two distinct types of coupling. Additionally, we simulate two scenarios, where the discrete primitive is inserted in all of the four limbs, or is inserted in ipsilateral pairs of limbs. Numerical results show that amplitude and frequency of the periodic solutions, corresponding to the gaits trot and pace, are almost constant for diffusive and synaptic couplings.
Potential Drop Based Model to Analyze Electrode Passivation by Fouling from Phenolic Compounds

Dielectric interface would be formed on the electrode surface during the analysis or disposal of many phenolic compounds due to electro-polymerization. This could cause electrode passivation, also called electrode fouling, which is indicated by the continuously decaying current signal. This paper proposed a model based on the potential drop across the fouling layer, which is helpful for deep understanding of the electrode passivation/fouling process. This model successfully fitted the experimental results.
A Mutation within the Leucine-Rich Repeat Domain of the Arabidopsis Disease Resistance Gene RPS5 Partially Suppresses Multiple Bacterial and Downy Mildew Resistance Genes

Recognition of pathogens by plants is mediated by several distinct families of functionally variable but structurally related disease resistance (R) genes. The largest family is defined by the presence of a putative nucleotide binding domain and 12 to 21 leucine-rich repeats (LRRs). The function of these LRRs has not been defined, but they are speculated to bind pathogen-derived ligands. We have isolated a mutation in the Arabidopsis RPS5 gene that indicates that the LRR region may interact with other plant proteins. The rps5-1 mutation causes a glutamate-to-lysine substitution in the third LRR and partially compromises the function of several R genes that confer bacterial and downy mildew resistance. The third LRR is relatively well conserved, and we speculate that it may interact with a signal transduction component shared by multiple R gene pathways.
Sentiment Polarity Detection in Reviews for Identifying the Best Feature Combination

Today E-commerce popularity has made web an excellent source of gathering customer reviews/opinions about a product that they have purchased. The number of customer reviews that a product receives is growing at a very fast rate. Opinion mining from product reviews, forum posts and blogs is an important research topic today with many applications. Customers use the reviews for deciding quality of product to buy. So, opinion mining may be a Decision making process. It means reviews are given to promote or to demote the product. There is need to find how many reviews are positive and how many are negative. So, to find out it features for which classification is going to be performed should be best or optimal. This Paper presents various approaches of classification for sentiment analysis and proposed work is selecting best feature set such as pos tags from reviews which we can easily classify the review of customer. Only features which are giving best decision for analysis have been selected in pre-processing task and Combination of best feature set will be used to classify reviews.
Electrophysiologic and molecular characteristics of cardiomyocytes after heavy ion irradiation in the frame of the ESA IBER-10 program

Since essentially no information is available on the effects of high linear energy transfer (LET) radiation on the heart, an assessment of possible late effects on the cardiovascular system is important with respect to the planning of manned long-term space missions [ 1, 2]. In order to examine if and to what extent heart muscle cells are affected by an exposure to heavy ions, primary avian cardiomyocytes were isolated, cultured in vitro and exposed at GSI (Darmstadt) to different ion species (carbon, titanium and nickel). Investigation of electrophysiologic radiation effects was performed on cells grown on a microelectrode array (MEA) allowing the monitoring of beat rate, spike shape, field action potential duration and signal conduction pathways across the electrode array. Data were analysed using the DrCell software [ 3]. In parallel, immunohistological stainings were conducted to examine cell cycle progression, DNA-damage repair and apoptosis. Our preliminary data indicate that primary cardiac cells possess a high robustness toward ionizing radiation as cultures receiving doses of up to 7 Gy still show unaltered electrophysiologic activity. This is exemplarily shown in Fig. 1, where the beat rate of cells irradiated with 2 and 7 Gy carbon ions has been plotted. Figure 1 also illustrates that within each treatment group, inter-sample variations are quite large and thus do not allow detection of subtle changes in cellular electrophysiology, probably due to the embryonic character of the cells. Interestingly, in terms of the formation of double-strand breaks (DSBs) and cell cycle progression delay, the cultures showed a dose-dependent reduction in proliferation and DSB accumulation. Taken together, our electrophysiologic studies indicate that the large variations within the same treatment group of avian embryonic cardiomyocytes obscure the detection of radiation effects. To account for this problem, we will use in further studies human cardiomyocytes differentiated from iPS cells, as these cells resemble more closely the condition of an adult human heart and do not undergo developmental changes as embryonic cell cultures do. Fig. 1. Normalized beat rates measured in samples before and after exposure to carbon ions. (spread-out Bragg peak, LET: 75 keV/µm). Average beat rates range from 22 to 53 beats/min.
Jointly Modeling Review Content and Aspect Ratings for Review Rating Prediction

Review rating prediction is of much importance for sentiment analysis and business intelligence. Existing methods work well when aspect-opinion pairs can be accurately extracted from review texts and aspect ratings are complete. The challenges of improving prediction accuracy are how to capture the semantics of review content and how to fill in the missing values of aspect ratings. In this paper, we propose a novel review rating prediction method, which improves the prediction accuracy by capturing deep semantics of review content and alleviating data missing problem of aspect ratings. The method firstly learns the latent vector representation of review content using skip-thought vectors, a state-of-the-art deep learning method, then, the missing values of aspect ratings are filled in based on users? history reviewing behaviors, finally, a novel optimization framework is proposed to predict the review rating. Experimental results on two real-world datasets demonstrate the efficacy of the proposed method.
Evaluation of Automatic Speech Recognition and Speech Language Translation within TC-STAR:Results from the first evaluation campaign

This paper reports on the evaluation activities conducted in the first year of the TC-STAR project. The TC-STAR project, financed by the European Commission within the Sixth Framework Program, is envisaged as a long-term effort to advance research in the core technologies of Speech-to-Speech Translation (SST). SST technology is a combination of Automatic Speech Recognition (ASR), Spoken Language Translation (SLT) and Text To Speech (TTS).
Estimating the Spectral Reflectance of Natural Imagery Using Color Image Features

Relative spectral reflectance is an illumination invariant image feature that is related to many ecological phenomena that are difficult to measure, such as plant CO2 uptake. We describe a procedure to estimate the relative spectral reflectance of known subject using color image features. Through application, we show that this procedure produces accurate estimates in the presence of changing field conditions. Using this procedure, we can use imagers as sensors to measure natural phenomena that cannot be easily measured using any other available sensing modality.
Yield Curve as a Predictor of Recessions: Evidence from Panel Data

In this study, we test empirically whether the slope of the yield curve—yield spread—is a good predictor of recessions. Although the convention in the literature is to use time series, we adopt an unbalanced panel data framework for thirty-two countries in the Organization for Economic Cooperation and Development from 1990 to 2011. This modification allows us to apply this model for countries with short time series. Furthermore, we include four-quarter lagged gross domestic product (GDP) in the model to assure that yield spread is a good predictor of recessions, even when controlling for GDP changes. The results show that with a type I error of 25 percent, the models deliver a power of roughly 63 percent and can be used as an effective instrument to predict recessions one year ahead.
A VNS-based hierarchical clustering method

Traditional hierarchical clustering methods adopt a greedy strategy to merge objects progressively and construct a clustering dendrogram. However, their clustering quality might not be reliable because only local optimal information is referred during a dendrogram construction. To conquer the problem, this paper proposes a global optimal strategy to guide the dendrogram construction. The strategy aims to find an optimal circular traveling order that minimizes the total traveling distances for visiting all objects along the branches of the dendrogram, which is viewed as a traveling salesman problem (TSP). The TSP problem is solved using the variable neighborhood search (VNS) method because of its parameter-free advantage. Then, the clustering dendrogram is constructed based on the information provided by the order. Through our experiments, the clustering quality of our proposed method is superior to traditional hierarchical clustering methods.
Meteorological path planning using dynamic programming for a solar-powered UAV

Solar-powered Unmanned Aerial Vehicles (SUAV) designed for Low-Altitude Long-Endurance (LALE) applications provide potential multi-day continuous flight capability, but are generally prone to local meteorological impediments such as rain, strong winds or reduced solar irradiance. This paper therefore presents METPASS, the Meteorology-aware Trajectory Planning and Analysis Software for Solar-powered UAVs. METPASS optimizes large-scale solar-powered UAV missions using a detailed consideration of meteorological effects: An optimal trajectory is found on a 3-D grid for given departure and arrival points by applying a Dynamic Programming approach and a cost function that considers environmental hazards, winds, solar radiation, aircraft parameters and flight time. The cost function is evaluated based on a kinematic and energetic UAV system model and forecast data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The trajectory-planning environment is applied to an envisioned fully autonomous and solar-powered crossing of the North Atlantic Ocean by AtlantikSolar, a 5.6m-wingspan SUAV developed at ETH Zurich. Results based on historical ECMWF weather data from 2012 and 2013 show that properly pre-optimized routes allow the Atlantic crossing even in case of significant global cloud coverage and that optimal routes can reduce the required flight time by up to 50% (from 106h to 52h) by exploiting wind conditions.
The determination of flare launching programs to use against pulse width modulating guided missile seekers via hidden Markov models

The infrared (IR) guided missiles (G/M) which is equipped with pulse width modulated (PWM) seeker are present in inventory of various countries. Especially air platforms use flares to protect itself from such kind of G/M's. But the efficiency of the flare launching program is dependent on the type of the flares and their launching times. In this paper the process of determination of the flare type and flare launching time parameters in flare launching program via hidden Markov models (HMM) will be investigated.
Three-Dimensional Ideal Gas Reference State based Energy Function

This Thesis is protected by copyright and/or related rights. It has been brought to you by ScholarWorks@UNO with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rightsholder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself.
RESIDUAL GAS MOTIONS IN THE INTRACLUSTER MEDIUM AND BIAS IN HYDROSTATIC MEASUREMENTS OF MASS PROFILES OF CLUSTERS

We present analysis of bulk and random gas motions in the intracluster medium using high-resolution Eulerian cosmological simulations of 16 simulated clusters, including both very relaxed and unrelaxed systems and spanning a virial mass range of 5 × 1013–. We investigate effects of the residual subsonic gas motions on the hydrostatic estimates of mass profiles and concentrations of galaxy clusters. In agreement with previous studies, we find that the gas motions contribute up to ≈5%–15% of the total pressure support in relaxed clusters with contribution increasing with the cluster-centric radius. The fractional pressure support is higher in unrelaxed systems. This contribution would not be accounted for in hydrostatic estimates of the total mass profile and would lead to systematic underestimate of mass. We demonstrate that total mass can be recovered accurately if pressure due to gas motions measured in simulations is explicitly taken into account in the equation of hydrostatic equilibrium. Given that the underestimate of mass is increasing at larger radii, where gas is less relaxed and contribution of gas motions to pressure is larger, the total density profile derived from hydrostatic analysis is more concentrated than the true profile. This may at least partially explain some high values of concentrations of clusters estimated from hydrostatic analysis of X-ray data.
Challenges for Transitioning Conventional Farming in the Sudan to Organic

United States Department of Agriculture (USDA), defines organic agriculture as a production system which voids or largely excludes the use of synthetically compounded fertilizers, pesticides, growth regulators and livestock feed additives. To the maximum extent feasible, organic farming systems rely upon crop rotation, crop residues, animal manure, legumes, green manure, off-farm organic wastes, mechanical cultivation, mineral supply bearing rocks and aspects of biological pest control to maintain soil productivity and tilth, to supply plant nutrients and to control insects, weeds and other pests. Therefore, organic agriculture combines tradition, innovation and science to benefit the shared environment and to sustain and optimize the health and productivity of interdependent communities of organic agriculture, in the modern sense of the term, is a highly regulated form of ecological agriculture. The legalities of organic agriculture are codified in a number of formal standards that define the regimes that producers or processors need to work within in order to claim organic status. These organic standards besides stipulating the prohibition of use of certain inputs also demand strict adherence to a range of practices by the farm. This paper reviews the process of conversion from a conventional to an organic system which requires complete deterrence from application of chemical inputs, significant changes at the farm level particularly within soil and major changes in the attitudes of the farmers, besides other costs and obstacles that affect transition process. On the other hand, it highlights the chances and prospects in favor of organic farming in the Sudan.
Nonlinear Aggregate Investment Dynamics: Theory and Evidence

In this paper we derive a model of aggregate investment that builds from the lumpy microeconomic behavior of firms facing stochastic fixed adjustment costs. Instead of the standard sharp (S,s) bands, firms' adjustment policies take the form of a probability of adjustment (adjustment hazard) that responds smoothly to changes in firms' capacity gap. The model has appealing aggregation properties, and yields nonlinear aggregate time series processes. The passivity of normal times is, occasionally, more than offset by the brisk response to large accumulated shocks. Using within and out-of-sample criteria, we find that the model performs substantially better than the standard linear models of investment for postwar sectoral U.S. manufacturing equipment and structures investment data.
Robust Image and Video Communication for Mobile Multimedia

What characterizes mobile multimedia is multiple signal sources, a multitude of applications, and transmission over channels with limited bandwidth and power, plus varying noise and attenuation. To cope with these variabilities new and improved communication systems should be developed. Joint source-channel coding may be one contribution towards this end. This article suggests an efficient communication principle where the sampled analog signal is first decomposed and thereafter mapped to the channel space using dimension-reducing nonlinear mappings. The article discusses the optimality of such an approach for artificial sources, but also shows simulation results for practical still image and video sources. Graceful degradation as a function of channel deterioration is shown to result from the proposed method.
Morphology of the anterior cingulate gyrus in patients with schizophrenia: relationship to typical neuroleptic exposure.

OBJECTIVE The anterior cingulate gyrus is a pivotal component of brain networks directing affective and cognitive functions, and abnormalities of the anterior cingulate gyrus may be involved in the pathophysiology of schizophrenia. However, magnetic resonance imaging studies of the morphology of this region have been few and the results inconsistent. Many of the studies have not accounted for confounding factors such as gender, handedness, or clinical variables such as neuroleptic exposure. METHOD The morphology and clinical correlates of the anterior cingulate gyrus were evaluated in a group of 30 right-handed male subjects with schizophrenia and a comparison group matched for age, sex, and handedness. The patient group was specifically designed to provide measures of multiple phenomenological differences such as severity of illness, duration of illness, and exposure to typical neuroleptics. RESULTS The patient group had a significantly larger left anterior cingulate gyrus volume relative to comparison subjects, whereas right anterior cingulate gyrus volume did not differ between groups. Depth of the left anterior cingulate gyrus was significantly correlated with neuroleptic exposure, indicating that greater exposure to neuroleptics was associated with greater cortical depth of this region. There was no significant relationship between anterior cingulate gyrus morphology and duration of illness or severity of symptoms. CONCLUSIONS Anterior cingulate gyrus depth in subjects with schizophrenia is directly related to typical medication exposure (the greater the exposure, the thicker the anterior cingulate gyrus) but not to other clinical variables such as length of illness or symptom severity. Future research is needed to determine the functional consequences of these changes and relationship to atypical neuroleptic use.
Varying probability of the development of acute nonlymphoblastic leukemia in refractory anemia patients with an excess of blasts.

The cumulative leukemia-free survival rate of refractory anemia with excess of blasts was fitted to three parametric failure time models, i.e., the usual exponential and Weibull, and exponential mixture models. Among the three, the best fit model was the exponential mixture model, which was 119 times more likely to assume that samples came from the exponential mixture distribution than to assume that those were from the usual Weibull distribution. This strongly suggests that refractory anemia with excess of blasts consists of subgroups with very high and very low probability to develop acute nonlymphoblastic leukemia. The estimated proportion of the very low probability group was about 30%. Analysis by the exponential mixture model with covariates revealed that the probability of a patient to develop acute nonlymphoblastic leukemia could be estimated by three covariates, i.e., bone marrow blast percentage; abnormal granules of granulocytes; and mononuclear large megakaryocytes. The estimated probabilities ranged from 17 to 99%, according to the model.
Identifying shopping center attractiveness using taxi trajectory data

Intensive research has demonstrated that shopping center attractiveness analysis, such as identifying catchment area, attracted trips, and attractiveness factors, can benefit not only market analysis, but also traffic management and urban planning. Conventionally, socioeconomic and survey data are needed to conduct the analysis, which is both labor-intensive and time-consuming. This study takes advantage of increasingly available taxi trajectory data to identify shopping center attractiveness using the case of Wuhan, a large city in China. The empirical results are consistent with previous studies. This demonstrates the feasibility of using trajectory data to generate choice-based sample and benefit market and related studies.