Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Algorithms and Performance Bounds for Sum Rate Maximization in Wireless Networks

In this paper, we consider a wireless network where interference is treated as noise, and we study the nonconvex problem of sum rate maximization by power control. We focus on finding approximately optimal solutions that can be efficiently computed to this NP-hard problem by studying the solutions to two related problems, the sum rate maximization using a signal-to-interference-plus-noise ratio (SINR ) approximation and the max-min weighted SINR optimization. We show that these two problems are intimately connected, can be solved efficiently by algorithms with fast convergence and minimal parameter configuration, and can yield high-quality approximately optimal solutions to sum rate maximization in the low interference regime. As an application of these results, we analyze the connection-level stability of cross-layer utility maximization in the wireless network, where users arrive and depart randomly and are subject to congestion control, and the queue service rates at all the links are determined by the sum rate maximization problem. In particular, we determine the stability region when all the links solve the max-min weighted SINR problem, using instantaneous queue sizes as weights.
Residual-Consensus Driven Linear Matching

Linear matching (LM) is a simple and effective method for solving image matching problems. In many cases, image matching problems are nonlinear due to involvement of the geometric transformations; therefore, an essential step for utilizing linear models for image matching is to linearize the geometric transformation matrices that introduce nonlinear terms into image matching problems. Existing LM methods usually use low-order transformations to artificially initialize a linear model. In this paper, we propose a residual-consensus driven LM algorithm that generalizes existing LM methods by allowing higher order transformations to automatically initialize a linear model. Based on the observation that transformation models generated from inlier subsets exhibit correlated behaviors (termed residual consensus hereafter), we develop a residual-consensus robust estimation algorithm to project the nontrivial linear transformation problem into a much smaller subspace, and thus enable efficient optimizations through linear programming. The experimental results on synthetic and real databases demonstrate the effectiveness and robustness of the proposed algorithm.
Market Competition and Metropolitan-Area Grocery Prices

This paper examines the relationship of 1987 retail grocery prices to supermarket sales concentration across 95 U.S. metropolitan areas. The regression model incorporates a large number of population, retail-cost, and retail competition factors and separate prices by type of grocery item. We find that the concentration-price relationship is sensitive to item type: Positive for packaged, branded, dry groceries and unrelated for produce, meat and dairy product prices. As for market rivalry, we find that small grocery stores provide no grocery price competition for supermarkets. However, branded grocery prices are driven down by fast-food places and by rapid price churning, whereas for unbranded foods the presence of warehouse stores places downward pressure on supermarket prices while fast-food presence does not. For the branded-groceries component, we also find prices higher in large, fast-growing, low-income, Eastern cities. We also find that cities where rents, wages and electricity costs are high tend to have high dry grocery prices. However, for the unbranded-products component retail costs are unrelated to prices, and cities in the South have the highest prices.
Neural Mechanisms of Person-Specific Theory of Mind

Author(s): Welborn, Benjamin Locke | Advisor(s): Lieberman, Matthew D | Abstract: Human beings are uniquely equipped with the capacity to reason in sophisticated ways about others’ thoughts and feelings, an ability often referred to as a ‘theory of mind’ (Premack a Woodruff, 1978; Gopnik a Wellman, 1994; Leslie et al., 2004). Recent literature on theory of mind has expanded considerably, and contemporary theoretical work has sought to differentiate ways in which different component psychological processes may contribute to mental state reasoning (Schaafsma et al., 2015; Van Overwalle a Vandekerckhove, 2013). Several prominent accounts have sought to explain an empirical dissociation between mentalizing-related activity in the dorsal medial prefrontal cortex (DMPFC) and the ventral medial prefrontal cortex (VMPFC): the former region is characteristically implicated in reasoning about unknown others while the latter is consistently evoked with participants reason about the self and close others (see meta-analysis by Van Overwalle a Baetens, 2009). A ‘similarity’ account sees the activity of ventral MPFC as related to its role in simulating the minds of others by reference to our own thoughts and feelings (Mitchell, Banaji, a Macrae, 2005; Mitchell, Macrae, a Banaji, 2006). According to this viewpoint, we can employ the same neuro-cognitive resources and mechanisms when thinking about others as when introspecting about our own mental states, provided that others are seen to be sufficiently similar to the self. A second theoretical view contends that VMPFC is responsible for encoding and reasoning about the minds of close others, who are members of our family, tribe, or another meaningful social group (Krienen, Tu, a Buckner, 2010). In the present dissertation work a third alternative is proposed, according to which person-specific knowledge of others’ unique personal characteristics allows for nuanced and individuated inferences about their transient mental states and enduring dispositional traits. We theorize that rich experiential knowledge of particular individuals can be leveraged into person-specific theories of mind, instantiated in the MPFC, which facilitate mental state reasoning that is tailored to the minds of those persons we know especially well. In Study 1, we provide neuroimaging (fMRI) results in favor of this ‘person-specific theory-of-mind hypothesis’, showing that ventral VMPFC is more responsive to well-known targets than to poorly-known targets, regardless of perceived similarity and affective closeness. Moreover, activity in medial prefrontal cortex is associated with trial-by-trial variation in the availability of person-specific knowledge, and with participants’ willingness to attribute idiosyncratic traits to social targets. In a second fMRI study (Study 2), we explore the formation of person-specific theories of mind regarding initially unfamiliar targets, revealing a comparable pattern of hemodynamic activity.
Data Science Technologies for Vibrant Cities

Smart Cities forced IT technologies make a significant step in their development. A new generation of agile knowledge based software applications and systems have been successfully designed and implemented. Wide capabilities of the agile applications were sufficient to meet the complete set of requirements of smart cities. Fast transformation of modern cities from smart cities to vibrant cities throws new even more complicated challenges to information technologies. While smart cities assumed wide usage of agile means and tools for solving applied tasks, applications for vibrant cities must provide agile environment for exploring and managing of all types of data, information and knowledge. Agile environment must be flexible enough to support iterative data processing and analyses procedures that can be easily reorganized or changed depending on context. The aim of agile environment creation and support is to extend a set of used mathematical, technological and program solutions. In the paper it is proposed to build applications for vibrant cities using agile data science methodologies and toolsets within the commonly used approaches for developing agile information systems.
Obstacle avoidance in multi-vehicle coordinated motion via stabilization of time-varying sets

In this paper, we review the recent results on stability and control for time-varying sets of nonlinear time-varying dynamical systems and utilize them for the problem of multi-vehicle coordinated motion in the context of obstacle avoidance where obstacles are approximated and enclosed by elliptic shapes. Specifically, we design distributed controllers for individual vehicles moving in a specified formation in the presence of such obstacles. The obstacle avoidance algorithm that we propose is based on transitional trajectories which are denned by a set of ordinary differential equations that exhibit a stable elliptical limit cycle. The control framework is implemented on the system of double integrators and is shown to globally exponentially stabilize moving formation of the agents in pursuit of a leader while ensuring obstacle avoidance.
A Breaker-Oriented, Three-Phase IEEE 24-Substation Test System

Accurate bus-oriented, three-phase modeling of power systems is desirable for advanced applications and has become practical due to increased computational capability. To assist research activities in this area, this paper presents a benchmark three-phase test system. The proposed system is based on the 24-bus IEEE Reliability Test System that has been converted into a 24-substation, breaker-oriented, three-phase model. The model is available in electronic form at the site: http://pscal.ece. gatech.edu/testsys/. The proposed model is intended for use in research for three-phase power flow analysis, reliability analysis, fault analysis, transient stability, evaluation of fault currents through specific breakers, risk assessment of breaker failures, and other applications.
On some Bayesian choices of regularization parameter in image restoration

Recently there has been considerable interest in the problem of estimating 'optimal' degrees of smoothing within the context of Bayesian solutions to ill-posed inverse problems (e.g. Gull (1989) and Thompson and co-workers (1990)). In this paper we examine the hyperparametric method of selecting the regularization parameter described in Gull. We show how Gull's results may be generalised to situations where the log-prior may be approximated by a positive semi-definite quadratic form. We also show by means of some illustrative examples that hyperparametric approach can lead to undersmoothed reconstructions of the underlying image.
Standardized Mortality Ratio and Confidence Interval

This module tests for statistical significance and calculates various confidence intervals for SMR, based on a number of different methods. First, the user is prompted to enter observed and expected number of deaths in the respective data entry cells. Please note that the observed number of cases must be an integer as they are assumed to be Poisson variates (random variables with a Poisson distribution). The user can change the confidence interval settings as seen in the data entry dialog box (or) at ‘Options/Setting’ at the main menu screen.
Effect of morphology on the large-amplitude flapping dynamics of an inverted flag in a uniform flow

The stability of a cantilevered elastic sheet in a uniform flow has been studied extensively due to its importance in engineering and its prevalence in natural structures. Varying the flow speed can give rise to a range of dynamics including limit cycle behaviour and chaotic motion of the cantilevered sheet. Recently, the ‘inverted flag’ configuration – a cantilevered elastic sheet aligned with the flow impinging on its free edge – has been observed to produce large-amplitude flapping over a finite band of flow speeds. This flapping phenomenon has been found to be a vortex-induced vibration, and only occurs at sufficiently large Reynolds numbers. In all cases studied, the inverted flag has been formed from a cantilevered sheet of rectangular morphology, i.e. the planform of its elastic sheet is a rectangle. Here, we investigate the effect of the inverted flag’s morphology on its resulting stability and dynamics. We choose a trapezoidal planform which is explored using experiment and an analytical theory for the divergence instability of an inverted flag of arbitrary morphology. Strikingly, for this planform we observe that the flow speed range over which flapping occurs scales approximately with the flow speed at which the divergence instability occurs. This provides a means by which to predict and control flapping. In a biological setting, leaves in a wind can also align themselves in an inverted flag configuration. Motivated by this natural occurrence we also study the effect of adding an artificial ‘petiole’ (a thin elastic stalk that connects the sheet to the clamp) on the inverted flag’s dynamics. We find that the petiole serves to partially decouple fluid forces from elastic forces, for which an analytical theory is also derived, in addition to increasing the freedom by which the flapping dynamics can be tuned. These results highlight the intricacies of the flapping instability and account for some of the varied dynamics of leaves in nature.
Effective Implementation of Edge-Preserving Filtering on CPU Microarchitectures

In this paper, we propose acceleration methods for edge-preserving filtering. The filters natively include denormalized numbers, which are defined in IEEE Standard 754. The processing of the denormalized numbers has a higher computational cost than normal numbers; thus, the computational performance of edge-preserving filtering is severely diminished. We propose approaches to prevent the occurrence of the denormalized numbers for acceleration. Moreover, we verify an effective vectorization of the edge-preserving filtering based on changes in microarchitectures of central processing units by carefully treating kernel weights. The experimental results show that the proposed methods are up to five-times faster than the straightforward implementation of bilateral filtering and non-local means filtering, while the filters maintain the high accuracy. In addition, we showed effective vectorization for each central processing unit microarchitecture. The implementation of the bilateral filter is up to 14-times faster than that of OpenCV. The proposed methods and the vectorization are practical for real-time tasks such as image editing.
Panel Threshold Regression Models with Endogenous Threshold Variables

This paper extends the panel threshold regression of Hansen (1999) and Kourtellos, Stengos and Tan (2007) to allow for endogeneity of the threshold variable. We consider the static linear panels with fixed effect. The modified concentrated two-stage least square methods that are based on inverse Mills ratio bias correction terms are proposed to estimate threshold parameters. Our estimators are consistent even though individual effects have any correlation with regressors. Monte Carlo simulations are performed to investigate the finite sample properties of the proposed estimators. JEL Classifications : C13, C33, C51
Asymmetric Interaction between Stock Price Index and Exchange Rates: Empirical Evidence for Romania

This paper examines the interaction between the stock market and the foreign exchange market of Romania. This relationship has important implications from the viewpoint of the two economic theories - the traditional theory and the portfolio balance theory - and especially in the light of the increasing openness of the economy to international trade and investment. The data set, from March 2000 to March 2014, covers different market phases and stock market crashes, such as the recent global financial crisis and the Euro Area debt crisis. Due to the nonlinear nature of the relation between the variables, the study employs a threshold error-correction model based on two distinct regimes extended to incorporate asymmetries related to short-term good or bad news from the two markets. Within this framework, the empirical evidence shows that there is a long-run equilibrium between the two variables during the time period investigated. There are also short-run non-linear relationships sensitive to short-term good or bad news in the regime with fewer observations, called ‘extreme regime’.
Trade in Commodities and Business Cycle Volatility

This paper studies the role of differences in the patterns of production and international trade on the business cycle volatility of emerging and developed economies. We study a multisector small open economy in which firms produce and trade commodities and manufactures. We estimate the model to match key cross-sectional and time-series differences across countries. Emerging economies run trade surpluses in commodities and trade deficits in manufactures, while sectoral trade flows are balanced in developed economies. We find that these differences amplify the response of emerging economies to commodity price fluctuations. We show evidence consistent with this mechanism using cross-country data. (JEL E23, E32, F14, F41, F44)
Relationship between hypocentral distributions and Vp/Vs ratio structures inferred from dense seismic array data: a case study of the 1984 western Nagano Prefecture earthquake, central Japan

We conducted a three-dimensional traveltime tomographic reconstruction in and around the source region of the 1984 western Nagano Prefecture earthquake to investigate the generation process for the main shock and associated swarm activity. Up to 220 000 high-resolution trav-eltime records (2 ms error) were compiled from a dense seismic network. From these records, we performed accurate, high-resolution calculations to estimate hypocentre distributions and three-dimensional velocity structure. Most hypocentres aligned along the same path or within the same plane, rather than in three-dimensional clusters. Hypocentres in the swarm region are located in regions with low Vp / Vs ratios, while few earthquakes occurred in regions with high or normal Vp / Vs ratios. We suggest that differences in the number of small fractures and ﬂuid content between these two regions inﬂuenced the seismic activity. Rupture propagation associated with the main shock appears to be conﬁned by relatively higher Vp / Vs surroundings, and a low-velocity region which limits its vertical extent
Ab initio calculation of resonant x-ray scattering in manganites

We study the origin of the resonant x-ray signal in manganites and generalize the resonant cross section to the band-structure framework. With ab initio LSDA and $\mathrm{LSDA}+U$ calculations we determine the resonant x-ray spectrum of ${\mathrm{LaMnO}}_{3}. $ The calculated spectrum and azimuthal angle dependence at the Mn K edge reproduce the measured data without adjustable parameters. The intensity of this signal is directly related to the orthorhombicity of the lattice. We also predict a resonant x-ray signal at the La L edge, caused by the tilting of the ${\mathrm{MnO}}_{6}$ octahedra. This shows that the resonant x-ray signal in the hard x-ray regime can be understood in terms of the band structure of a material and is sensitive to the fine details of crystal structure.
Stereo Vision based Traffic Analysis System

Provided intelligent vechile concept analyzes status of current traffic. Traffic analyze system based on stero vision technology, wich extracts 3D informaion from observed image. Priciples of typical stero vision system and main problems are described. Possible main functions, which can be used for a intelligent cars to help driver to avoid dangerous situations and incidents are reviewed. Sterovision system features are compared to other types of environmental sensor, which combination can increase system flexibility.
The Excursion set approach: Stratonovich approximation and Cholesky decomposition

The excursion set approach is a framework for estimating how the number density of nonlinear structures in the cosmic web depends on the expansion history of the universe and the nature of gravity. A key part of the approach is the estimation of the first crossing distribution of a suitably chosen barrier by random walks having correlated steps: The shape of the barrier is determined by the physics of nonlinear collapse, and the correlations between steps by the nature of the initial density fluctuation field. We describe analytic and numerical methods for calculating such first up-crossing distributions. While the exact solution can be written formally as an infinite series, we show how to approximate it efficiently using the Stratonovich approximation. We demonstrate its accuracy using Monte-Carlo realizations of the walks, which we generate using a novel Cholesky-decomposition based algorithm, which is significantly faster than the algorithm that is currently in the literature.
Chemical Treatment to Recover Molybdenum and Vanadium from Spent Heavy Gasoil Hydrodesulfurization Catalyst

Large quantities of spent hydrodesulfurization (HDS) catalysts are available from petrochemical industry. Disposal of spent catalyst is a problem as it falls under the category of hazardous industrial waste due to its vanadium concentration. Most of these catalysts are usually supported on alumina containing a variable percentage of elements such as nickel or molybdenum. Hence these catalysts contain environmentally critical, and economically valuable metals such as molyb denum, vanadium, and, nickel. In this paper, a spent HDS catalyst was treated with caustic soda solution. Parameters such as temperature, time, and NaOH solution concentration have been studied thoroughly, in order to settle the appropriate conditions for the maximum recovery of molybdenum and vanadium. Under the best leaching conditions (20 %w NaOH, room temperature, 2 h) about 95% recovery of Mo and V was achieved, and the recovery of nickel obtained was of 99% in the form of NiAlO4.
Disorder-specific and shared neurophysiological impairments of attention and inhibition in women with ADHD and women with bipolar disorder

Abstract: Background: In adults, attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) have certain overlapping symptoms, which can lead to uncertainty regarding the boundaries of the two disorders. Despite evidence of cognitive impairments in both disorders separately, such as in attentional and inhibitory processes, data on direct comparisons across ADHD and BD on cognitiveneurophysiological measures are as yet limited. Methods: We directly compared cognitive performance and event-related potential (ERP) measures from a Cued Continuous Performance Test (CPT-OX) in 20 women with ADHD, 20 women with BD (currently euthymic) and 20 control women. Results: The NoGo-N2 was attenuated in women with BD, reflecting reduced conflict monitoring, compared to women with ADHD and controls (both p<0.05). Both ADHD and BD groups showed a reduced NoGo-P3, reflecting inhibitory control, compared to controls (both p<0.05). In addition, the CNV was significantly reduced in the ADHD group (p=0.05), with a trend in the BD group (p=0.07), compared to controls. Conclusions: These findings indicate potential disorder-specific (conflict monitoring) and overlapping (inhibitory control, and potentially response preparation) neurophysiological impairments in women with ADHD and women with BD. The identified neurophysiological parameters further our understanding of neurophysiological impairments in women with ADHD and BD, and are candidate biomarkers that may aid in the identification of the diagnostic boundaries of the two disorders.