Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding the most prominent group in complex networks

In many applications we are required to locate the most prominent group of vertices in a complex network. Group Betweenness Centrality can be used to evaluate the prominence of a group of vertices. Evaluating the Betweenness of every possible group in order to find the most prominent is not computationally feasible for large networks. In this paper we present two algorithms for finding the most prominent group. The first algorithm is based on heuristic search and the second is based on iterative greedy choice of vertices. The algorithms were evaluated on random and scale-free networks. Empirical evaluation suggests that the greedy algorithm results were negligibly below the optimal result. In addition, both algorithms performed better on scale-free networks: heuristic search was faster and the greedy algorithm produced more accurate results. The greedy algorithm was applied for optimizing deployment of intrusion detection devices on network service provider infrastructure.
Recommendations for developing common standards for the study of VCI : summary of the 2006 NINDS / CSN workshop

Until recently, the study of cognitive impairment as a manifestation of cerebrovascular disease (CVD) has been hampered by the lack of common standards for assessment. The term vascular cognitive impairment (VCI) encompasses all levels of cognitive decline associated with CVD from mild deficits in one or more cognitive domains to crude dementia syndrome. VCI incorporates the complex interactions among classic vascular risk factors (i.e. arterial hypertension, high cholesterol, and diabetes), CVD subtypes, and Alzheimer’s Disease (AD) pathology. VCI may be the earliest, commonest, and subtlest manifestation of CVD and can be regarded as a highly prevalent and preventable syndrome. However, cognition is not a standardized outcome measure in clinical trials assessing functional ability after stroke. Furthermore, with the exception of anti-hypertensive medications, the impact of either preventive or acute stroke treatments on cognitive outcome is not known. Although clinical, epidemiological, neuroimaging, and experimental data support the VCI concept, there is a lack of integrated knowledge on the role played by the most relevant pathophysiological mechanisms involved in several neurological conditions including stroke and cognitive impairment such as excitotoxicity, apoptosis, mitochondrial DNA damage, oxidative stress, disturbed neurotransmitter release, and inflammation. For this reason, in 2006 the National Institute of Neurological Disorders and Stroke (NINDS) and the Canadian Stroke Network (CSN) defined a set of data elements to be collected in future studies aimed at defining VCI etiology, clinical manifestations, predictive factors, and treatment. These recommendations represent the first step toward developing diagnostic criteria for VCI based on sound knowledge rather than on hypotheses. The second step will be to integrate all studies using the agreed methodologies. This is likely to accelerate the search for answers.
Neurohumoral mechanisms associated with orthostasis: reaffirmation of the significant contribution of the heart rate response

The inability to compensate for acute central hypovolemia underlies the clinical development of orthostatic hypotension and instability (e.g., syncope). Although neuro-humoral control of both cardiac output and peripheral vascular resistance contributes to hemodynamic stability during orthostasis, a notion has been proposed that the failure of adequate peripheral vascular constriction rather than cardiac responses represents the primary mechanism underlying the development of orthostatic intolerance. This review article provides an opportunity to present compelling evidence captured over the past 30 years in our laboratory to support the concept that neural-mediated tachycardia during orthostasis in healthy individuals represents a critical response to tolerating acute reduction in central blood volume in addition to, and independent of, peripheral vascular constriction. In this review paper, data are presented from experiments using graded lower body negative pressure (LBNP) as a method to induce orthostatic intolerance in two experimental human models: (1) comparison of heart rate and autonomic responses in individuals with relatively high and low tolerance to LBNP; and (2) vagal and sympathetic blockade of cardiac neural control. These experiments revealed that: (1) greater elevations in heart rate are associated with higher orthostatic (LBNP) tolerance; (2) higher orthostatic heart rate is associated with greater sympathetic nerve activity and withdrawal of vagally-mediated cardiac baroreflex response; and (3) non-specific sympathetic blockade causes a pronounced reduction in heart rate and LBNP tolerance. Cardiac parasympathetic withdrawal contributes to protection against development of hypotension during the initial seconds of transition to an orthostatic challenge, while the primary mechanism by which tachycardia defends orthostatic stability in healthy subjects for extended durations is mediated predominantly through sympathetic adrenergic control.
Joint Source-Channel Decoding of Variable-Length Encoded Markov Multiple Sources

Joint source-channel decoding (JSCD) has been shown to be effective for multimedia transmission over time varying channels. In this paper, we present a method for joint source-channel soft decision decoding of variable-length encoded multiple sources. Compared with the single source decoding scheme addressed by Marion Jeanne, the proposed technique is more practical in wideband wireless communications. Simulation results show our new method obtains substantial improvements with a minor increasing of complexity. For two sources, the gain in SNR is around 1.5dB when symbol-error rate (SER) reaches 10-2 and around 1.3dB when SER=10-3.
Serotonergic projections and serotonin receptor expression in the reticular nucleus of the thalamus in the rat

The reticular nucleus (RT) of the thalamus, a thin sheet of GABAergic neurons located between the external medullary lamina and the internal capsule of the thalamus, has functionally distinct afferent and efferent connections with thalamic nuclei, the neocortex, the basal forebrain and the brainstem. RT is critically positioned to rhythmically pace thalamocortical networks leading to the generation of spindle activity during the early phases of sleep and during absence (spike‐wave) seizures. Serotonin, acting on 5‐HT1A receptors on parvalbumin‐containing cells of RT, has been implicated in this rhythmicity. However, the precise source(s) of 5‐HT afferents to the RT remains to be determined. In the present study, we injected the retrograde tracer, Fluorogold, into dorsal and ventral regions of RT to determine the origins of raphe input to RT. We further characterized the distribution of 5‐HT fibers to RT by using immunohistochemistry for 5‐HT and for the 5HT transporter (SERT) detection. Finally, we described the presence of the two major postsynaptic 5‐HT receptors in RT, 5‐HT1A and 5‐HT2A receptors. Our results show that the dorsal raphe nucleus and the supralemniscal nucleus (B9) of the midbrain are the principal sources of raphe projections to RT. In addition, serotonergic fibers (5‐HT and SERT positive) were richly distributed throughout RT, and 5‐HT1A and 5‐HT2A receptors were highly expressed on RT neurons and dendrites. These findings suggest a significant 5‐HT modulatory influence on GABAergic neurons of RT in the control of rhythmical (or spindle) activity in thalamocortical systems directly associated with sleep and possibly with absence seizures. Synapse, 2011. © 2011 Wiley‐Liss, Inc.
Large scale spatial temporal data visualization based on spark and 3D volume rendering

In this paper, we presented a spark based analysis framework for large scale spatial temporal data such as trajectories, LBS, Noise distribution and so on. With spark, spatial temporal data can be processed, mined and the results can be saved in parallel. Then these results will be imported into spatial-indexed databases for further applications. Finally, we studied the volume rendering methods to improve the visualization for the spatial temporal analysis results. We tested our algorithm on a spark cluster. The experimental results indicate that the proposed method is efficient to process and illustrate the spatial temporal big data.
Prioritization of pharmaceuticals in urban rivers: the case of oral contraceptives in the Belém River basin, Curitiba / PR, Brazil

Efforts to prioritize pharmaceutical products in urban rivers are still rare in Brazil. However, European and U.S. management experiences of pharmaceuticals in urban waters show that this has been one of the first steps necessary to reduce and control this type of pollution. The main objective of this research was to evaluate the presence of oral contraceptives in the catchment area of the Belém River in Curitiba based on the different criteria normally applied to prioritization. For this, in addition to a literature review, historical data on the concentrations of contraceptive hormones in the Belém River, data on pharmaceutical consumption in the basin (collected through interviews by random sampling in pharmacies and from the database of medicines provided by the City of Curitiba Health Units), and data from interviews conducted using intentional sampling with regional stakeholders. The results show that a consistent set of criteria supporting prioritization of ethinylestradiol and estradiol already exists, while the periodic monitoring of these two hormones has proved feasible and necessary in the waters of the region.
Optimizing the cloud platform performance for supporting large-scale cognitive radio networks

In this paper, we optimize the performance of a cloud platform to effectively support cooperative spectrum sensing in a cognitive radio (CR) cloud network. This cloud uses the Apache Hadoop platform to run a cooperative spectrum sensing algorithm in parallel over multiple servers in the cloud. A cooperative spectrum sensing algorithm needs to process a very large number of spectrum sensing reports per second to quickly update its database that stores the current activities of all primary users of the CR network. Because the updates of the database must be finished as soon as possible to make the CR approach effective, the cloud platform must be able to run the algorithm in real time with as little overhead as possible. In this work, we first measured the execution time of such an algorithm over our own cloud and the Amazon EC2 public cloud, using the original Hadoop platform design and implementation. We found that the original Hadoop platform has too much fixed overhead and incurs too much delay to the cooperative spectrum sensing algorithm, which makes it unable to update the primary user database in just a few seconds. Therefore, we studied the source code and the design and implementation of the Hadoop platform to improve its performance. Our experimental results show that our improvement of the Hadoop platform can significantly reduce the required time of the cooperative spectrum sensing algorithm and make it more suitable for large-scale CR networks.
The Evolutionary Impact of Functional RNA Secondary Structures within Protein-Coding Regions in Yeast

In recent years, the importance of functional RNAs in biological processes has been repeatedly demonstrated. Furthermore, a number of studies have indicated that the number and biological significance of functional RNAs has been underestimated. Here we focus on the impact of functional RNAs on the evolutionary rate of protein-coding genes. We used computational methods to predict a set of novel functional RNA secondary structures in the yeast genome. We found that the presence of predicted functional RNAs within coding regions causes a decrease in both synonymous and nonsynonymous evolutionary rates of the corresponding protein. We studied yeast genomes because abundant functional data is available for Saccharomyces cerevisiae, a common model genetic organism. Furthermore, the set of yeast duplicate genes produced by an ancient whole genome duplication provides a useful model for studying the evolution of gene function in yeast, and results from duplicate gene analysis also demonstrate that the duplicate gene with a greater number of coding functional RNAs also tends to have a relatively slower rate of protein evolution. Moreover, we discovered that genes with a significant portion of functional RNAs within their coding regions tend to be associated with either protein biosynthesis or transport.
Complimentary Phylogenetic Signals for Morphological Characters and Quantitative 3D Shape Data within genus Homo

Estimating the phylogeny of the genus Homo is entering a new phase of vastly improved data and methodology. There is increasing evidence of 6 to 10 competing species/lineages at any point in the last half million years, making the elucidation of the relationships of individual specimens particularly important. Recent estimates of the phylogeny of key specimens include Waddell (2013, 2014, 2015, 2016), and Mounier et al. (2016). These are made with quite different data (3D skull shapes and discrete morphological characters, respectively) and methods of analysis (unweighted least squares fitting of distances, OLS+, and reweighted maximum parsimony, respectively). Initial inspection of the trees in these articles might leave the impression of a great deal of disagreement and confused results. Here it is shown this need not be the case, and that these two types of data and analysis may be indicating a very similar tree, one that is in good agreement also with subjective current wisdom/expert opinions on particular parts of the phylogeny. The precise location of the African LH18 specimen arises as key to a better understanding of the likely form of the last common ancestors of H. sapiens and Neanderthals. A diverse approach seems to bring forth much more agreement of trees than otherwise perceived, and argues against being dogmatic about methods of phylogenetic analysis particularly when working with difficult problems.
On marine reserves: rents, resilience and ‘Rules of thumb’

Using a bioeconomic model with two separate forms of uncertainty (a diffusion process and a jump process) a perturbation method is used to determine optimal reserve size for a harvested population with density-dependent growth. The results show that the benefits of reserves are understated in deterministic models and that, even with optimal harvesting, risk neutrality, a persistent population and without initial overexploitation, reserves have a positive economic value. Concavity of the value function with respect to optimal reserve size under uncertainty implies that, for many harvested populations, a positive economic return will arise from initially establishing small reserves, even when harvesting is optimal. The results also lead to general ‘rules of thumb’ when establishing reserves. Namely, that optimal reserve size rises with (1) the greater the rate of transfer from the reserve, (2) the greater the magn itude or the likelihood of negative shocks, (3) the more the actual harvest exceeds the optimal harvest, (4) the lower the intrinsic growth rate, (5) an increase in price or demand provided the population is between zero and its maximum yield, (6) an increase in marginal harvesting costs provided the population is between its maximum yield and carrying capacity and (7) the lower the discount rate.
Three-dimensionally designed protein-responsive RNA devices for cell signaling regulation

The three-dimensional (3D) structures of many biomacromolecules have been solved to reveal the functions of these molecules. However, these 3D structures have rarely been applied to constructing efficient molecular devices that function in living cells. Here, we demonstrate a 3D structure-based molecular design principle for constructing short hairpin RNA (shRNA)-mediated genetic information converters; these converters respond to specific proteins and trigger the desired gene expression by modulating the function of the RNA-processing enzyme Dicer. The inhibitory effect on Dicer cleavage against the shRNA designed to specifically bind to U1A spliceosomal protein was correlated with the degree of steric hindrance between Dicer and the shRNA-protein complex in vitro: The level of the hindrance was predicted based on the models. Moreover, the regulation of gene expression was achieved by using the shRNA converters designed to bind to the target U1A or nuclear factor-κB (NF-κB) p50 proteins expressed in human cells. The 3D molecular design approach is widely applicable for developing new devices in synthetic biology.
A theoretical bound for noise-robust speech recognition

Model compensation techniques for noise-robust speech recognition approximate the corrupted speech distribution. is work introduces a sampling method that, given speech and noise distributions and a mismatch function, in the limit calculates the corrupted speech likelihood exactly. For this, it transforms the integral in the likelihood expression, and then applies sequential importance resampling. ough it is too slow to compensate a speech recognition system, it enables a more ne-grained assessment of compensation techniques, based on the kl divergences to the ideal compensation for individual components. e kl divergence appears to predict the word error rate well. is technique alsomakes it possible to evaluate the impact of approximations that compensation schemes make. For example, this work examines the inuence of the assumption that the corrupted speech distribution is Gaussian and diagonalising that Gaussian’s covariance. It also assesses the impact of a common approximation to the mismatch function for vts compensation, namely setting the phase factor to a xed value.
Motion-guided attention promotes adaptive communications during social navigation

Animals are capable of enhanced decision making through cooperation, whereby accurate decisions can occur quickly through decentralized consensus. These interactions often depend upon reliable social cues, which can result in highly coordinated activities in uncertain environments. Yet information within a crowd may be lost in translation, generating confusion and enhancing individual risk. As quantitative data detailing animal social interactions accumulate, the mechanisms enabling individuals to rapidly and accurately process competing social cues remain unresolved. Here, we model how motion-guided attention influences the exchange of visual information during social navigation. We also compare the performance of this mechanism to the hypothesis that robust social coordination requires individuals to numerically limit their attention to a set of n-nearest neighbours. While we find that such numerically limited attention does not generate robust social navigation across ecological contexts, several notable qualities arise from selective attention to motion cues. First, individuals can instantly become a local information hub when startled into action, without requiring changes in neighbour attention level. Second, individuals can circumvent speed–accuracy trade-offs by tuning their motion thresholds. In turn, these properties enable groups to collectively dampen or amplify social information. Lastly, the minority required to sway a group's short-term directional decisions can change substantially with social context. Our findings suggest that motion-guided attention is a fundamental and efficient mechanism underlying collaborative decision making during social navigation.
Modeling TCP Throughput and Delay ( results only )

This writeup describes the models from two papers [ 1] and [2]. The model in [1] uses the throughput model of [2] for the congestion avoidanc e phase. There are three phases: connection establishment, Slow Start, Congestion avoidance. Th is is a model of the congestion control procedures implemented in the Reno version. Only results are provided in this paper. For a detailed derivation, see http://www.ece. virginia.edu/mv/edu/715 /lectures/TCP/tcp-model.pdf.
A constrained maximum-likelihood approach for efficient multipath mitigation in GNSS receivers

In this paper, we develop a new method for mitigating multipath effects in GNSS receivers, based on a constrained maximum-likelihood (CML) estimates of the multipath parameters. First, we apply a nonlinear transformation on the signal parameters to reduce the search space. Then, we define a new criterion for constraining the relative amplitude of the received secondary signal, and use the Lagrange multiplier method to solve the CML optimization problem. The resulting likelihood cost function has a unique minimum and yields to closed-form parameters estimates. The proposed method does not suffer from the correlation multi-peak problem, as for the standard discriminators, thus it can be used for any type of GNSS signal to mitigate both code and carrier phase multipath errors, including the new BOC signals. Numerical examples show that the CML approach gives a significant refinement to reach the optimal positioning solution.
OBJECT-BASED ANALYSIS OF REMOTE SENSING DATA FOR LANDSCAPE MONITORING: RECENT DEVELOPMENTS

Environmental remote sensing is dominated by land use and land cover classifications. Different land cover features reflect electromagnetic radiation in different ways and remotely sensed images provide a basic and synoptic representation of land cover variation on the Earth's surface. The pixel based analysis has been 'the holy grail' for many years. Land-based features may be categorized according to land cover classes (e.g., grass, concrete, water, etc.) but not likely according to land use classes (urban park, golf course, etc.). Only contextual information allows to encountering spatial relationships, object shapes or neighbourhood information. Even where land cover information is not the ultimate goal of remote sensing studies, it is often a useful aid for further analysis. This Progress Report will focus on one recent development in land cover research, namely the advent of object-based image processing. We report on the rapid diffusion of this approach and critically discuss the possibilities and methodological shortcomings. We discuss that tangible objects are desirable in many applications and conclude that many environmental management applications necessitate the control and use of object-based land cover distributions - in the opposite to pixel-based pattern - to exploit land resources while safeguarding environmental concerns.