Miracle-dz/UniFAR-FTUs huggingface dataset:
MDP based dynamic base station management for power conservation in self-organizing networks

This paper proposes a Markov decision process (MDP) based base station management scheme that dynamically and collectively manages activation of a group of base stations depending on the time-varying traffic demand for power conservation in self-organization networks. Our MDP model is unique in a sense that it accurately captures the dynamics of handover traffic among neighboring cells, and it formulates infeasible actions as constraints in a constrained optimization problem. Simulation results confirm that the proposed scheme can significantly reduce power consumption: 55% of daily power savings, upto 73% of power savings during low traffic periods, and the minimum 23% of power savings even during high traffic periods. Our MDP algorithms find desired optimal policies to deactivate unnecessary base stations without sacrificing network performances.
On Sets of Distances of N Points in Euclidean Space

Let [Pg)] he the clans of all subsets Pjlc, of the Ic dimensional space consisting of TZ distinct points and having diameter 1. Denote by g,Jn, T) the maximum number of times a given distance r can occur among n points of a set Pik). Put G,(n) = max gkh 4, g,(n) = g,(n, 1) r (i. P. g,(n) denotes the maximum number of times the diameter can occur as a distance among 'n points of k dimensional space and G,(n) denotes the maximum number of times the same distance can occur between ' ~2 suitably chosen points in X: dimensional space). It is well known [l] that g,(n) = n and I [a] prored that (1) 111 +c/loglwn < G2(n) < n3:3 .
vBattle: A new framework to simulate medium-scale battles in individual-per-individual basis

Strategy games such as Warcraft<sup>™</sup>or UFO<sup>™</sup>franchises or RPG games like Never Winter Nights<sup>™</sup>or Baldur Gate<sup>™</sup>are successful blockbusters in video game industry. These games are based on battles simulated individual per individual. These type of games is a very interesting scenario to develop multilevel strategies or emergent behavior in multiagent systems.
Design aspects of carry lookahead adders with vertically-stacked nanowire transistors

This paper discusses the newly introduced vertically-stacked silicon nanowire gate-all-around field-effect-transistor technology and its advantages for higher density layout design. The vertical nanowire stacking technology allows very-high density arrangement of nanowire transistors with near-ideal characteristics, and opens the possibility for design optimization by adjusting the number of nanowire stacks without affecting the footprint area of the device. Several libraries for combinational logic synthesis have been designed and implemented for the synthesis of carry-lookahead adders, using the vertically-stacked nanowire technology. The reduction in silicon active area occupancy of vertically-stacked gates are envisaged of great significance for regular cell mapping, in disruptive future applications based on nanowire transistor arrays.
Maximal generalization of Baum-Katz theorem and optimality of sequential tests

Baum-Katz theorem asserts that the Cesaro means of i.i. d. increments distributed like X r-converge if and only if |X|^{r+1} is integrable. We generalize this, and we unify other results, by proving that the following equivalence holds, if and only if G is moderate: the Cesaro means G-converge if and only if G(L(a)) is integrable for every a if and only if |X|. G(|X|) is integrable. Here, L(a) is the last time when the deviation of the Cesaro mean from its limit exceeds a, and G-convergence is the analogue of r-convergence. This solves a question about the asymptotic optimality of Wald's sequential tests.
Sparse Frequency Diverse MIMO Radar Imaging for Off-Grid Target Based on Adaptive Iterative MAP

The frequency diverse multiple-input-multiple-output (FD-MIMO) radar synthesizes a wideband waveform by transmitting and receiving multiple frequency signals simultaneously. For FD-MIMO radar imaging, conventional imaging methods based on Matched Filter (MF) cannot enjoy good imaging performance owing to the few and incomplete wavenumber-domain coverage. Higher resolution and better imaging performance can be obtained by exploiting the sparsity of the target. However, good sparse recovery performance is based on the assumption that the scatterers of the target are positioned at the pre-discretized grid locations; otherwise, the performance would significantly degrade. Here, we propose a novel approach of sparse adaptive calibration recovery via iterative maximum a posteriori (SACR-iMAP) for the general off-grid FD-MIMO radar imaging. SACR-iMAP contains three loop stages: sparse recovery, off-grid errors calibration and parameter update. The convergence and the initialization of the method are also discussed. Numerical simulations are carried out to verify the effectiveness of the proposed method.
Effects of Electric Arc on The Dielectric Properties of Liquid Dielectrics

In high voltage equipment, insulation is an important part. There are solid, liquid, gaseous insulations and combination between them used in various equipments in a power system. Liquid dielectric is widely used in transformer, circuit breaker, capacitor and oil-filled cable. During the operation of the equipment, electric arc may take place in the liquid insulation. The arc contains high energy in the form of thermal energy and photonic energy radiated by the arc. Electric arc appearance in a liquid insulation may degrade the performance of the insulation and may lead to the failure of the insulation. This paper reports the results of investigation on the influence of electric arc on the dielectric properties of liquid insulation. Several transformer oils were used as samples. The samples were subjected to an electric arc generated by applying AC voltage to steel needle electrodes in a needle-plane electrode system. The distance between needle and plane electrode was varied from 1 to 3 mm corresponding to applied voltage varied from 12 to 24 kV in order to obtain several sizes of electric arc. After applying electric arc to the samples, dielectric measurements were done. Dielectric properties measured were breakdown voltage (Vbd), dissipation factor (tan delta) and relative permittivity (epsivr). The influences of electric arc size and the duration of arc application were investigated. Chemical change of the oil samples was investigated using Fourier Transform Infra Red (FTIR). The results showed that electric arc reduced significantly the breakdown voltage and increased the losses factor. The application of arc slightly reduced the relative permittivity of the samples. FTIR analysis indicated that C=O bonding was generated during arcing in the oil samples
Toward Understanding the Role of Aryl Hydrocarbon Receptor in the Immune System: Current Progress and Future Trends

The immune system is regulated by distinct signaling pathways that control the development and function of the immune cells. Accumulating evidence suggest that ligation of aryl hydrocarbon receptor (Ahr), an environmentally responsive transcription factor, results in multiple cross talks that are capable of modulating these pathways and their downstream responsive genes. Most of the immune cells respond to such modulation, and many inflammatory response-related genes contain multiple xenobiotic-responsive elements (XREs) boxes upstream. Active research efforts have investigated the physiological role of Ahr in inflammation and autoimmunity using different animal models. Recently formed paradigm has shown that activation of Ahr by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) or 3,3′-diindolylmethane (DIM) prompts the differentiation of CD4+Foxp3+ regulatory T cells (Tregs) and inhibits T helper (Th)-17 suggesting that Ahr is an innovative therapeutic strategy for autoimmune inflammation. These promising findings generate a basis for future clinical practices in humans. This review addresses the current knowledge on the role of Ahr in different immune cell compartments, with a particular focus on inflammation and autoimmunity.
360° panoramic overviews for location-based services

We investigate 360° panoramas as overviews to support users in the task of locating objects in the surrounding environment. Panoramas are typically visualized as rectangular photographs, but this does not provide clear cues for physical directions in the environment. In this paper, we conduct a series of studies with three different shapes: Frontal, Top-Down and Bird's Eye; the last two shapes are chosen because they provide a clearer representation of the spatial mapping between panorama and environment. Our results show that good readability of the panorama is most important and that a clear representation of the spatial mapping plays a secondary role. This paper is the first to provide understanding on how users exploit 360° panoramic over-views to locate objects in the surrounding environment and how different design factors can affect user performance.
2 Time in Connectionist Models Version : second draft [ 2 . 2 ] 1

There exist two different kinds of knowledge representation in Artificial Inte lligence: explicit, that can be represented by symbolicexpressions, and implicit (i.e. non-symbolic ), which can for instance be modelled by connectionist networks. Time is a characteristic that can affect both types of knowledge representa tion. This chapter covers the second kind of temporal problems, which are worthwhile handled by connectionist networks. The prototypical use of “classical” connectionist models (including the multilayer perceptron, the Hopfield network and the Kohonen self-organizing map) is in static data processing. These classical models are not well suited to working with data varying over time. In response to this, temporal connectionist model s have appeared and constitute a continuously growing research field. The purpose of this chapter is to present the main aspects of this research area and to r eview the key connectionist architectures that have been designed for solving temporal problems. It is not the purpose of this chapter however to provide an introduction to standard connectionist models. For such an introduction, we refer the interest ed reader to some good introductory material, e.g. (Lippmann 1987) or (Hertz et al. 1991). The following section presents the fundamentals of temporal processing with neural networks. Several temporal connectionist models are then detailed in s ction 3. As a matter of illustration, most important applications of this domain are reviewed in the third section. The chapter concludes with the presentation of a promising future issue: the extension of temporal processing to more complex structures data.
Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU

The estimation of the position of a person in a building is a must for creating Intelligent Spaces. State-of-the-art Local Positioning Systems (LPS) require a complex sensornetwork infrastructure to locate with enough accuracy and coverage. Alternatively, Inertial Measuring Units (IMU) can be used to estimate the movement of a person; a methodology that is called Pedestrian Dead-Reckoning (PDR). In this paper, we describe and implement a Kalman-based framework, called INS-EKF-ZUPT (IEZ), to estimate the position and attitude of a person while walking. IEZ makes use of an Extended Kalman filter (EKF), an INS mechanization algorithm, a Zero Velocity Update (ZUPT) methodology, as well as, a stance detection algorithm. As the IEZ methodology is not able to estimate the heading and its drift (non-observable variables), then several methods are used for heading drift reduction: ZARU, HDR and Compass. The main contribution of the paper is the integration of the heading drift reduction algorithms into a Kalman-based IEZ platform, which represents an extended PDR methodology (IEZ+) valid for operation in indoor spaces with local magnetic disturbances. The IEZ+ PDR methodology was tested in several simulated and real indoor scenarios with a low-performance IMU mounted on the foot. The positioning errors were about 1% of the total travelled distance, which are good figures if compared with other works using IMUs of higher performance.
Multivariate methods for identifying differentially expressed genes

Motivation: Univariate testing procedures remain the most common way to identify differentially expressed genes (DEGs). Univariate techniques suffer from the multiple comparison problem and reduced power, because they fail to account for gene interaction. Motivated by these issues, we adopt a multivariate procedure. Namely, we utilize the sup-norm test, which was specifically developed for high dimensional, low sample size problems. We propose an algorithm which repeatedly applies the sup-norm test to screen for DEGs. Results: We evaluate our methodology with both simulated and experimental data. Our simulation studies establish the validity of the sup-norm statistic in terms of Type I error and power. With simulated data sets, the screening algorithm retains the majority of DEGs under a variety of experimental conditions. We also used our methodology to analyze the publicly available ApoAI knockout data set. Our algorithm identified the biologically significant genes, as discussed by other authors (Callow et al., 2000; Smyth, 2004). Availability: A set of Matlab functions used to implement the proposed methodology is available at Bioinformatics online. Contact: bmh35@cornell.edu
Unified entity search in social media community

The search for entities is the most common search behavior on the Web, especially in social media communities where entities (such as images, videos, people, locations, and tags) are highly heterogeneous and correlated. While previous research usually deals with these social media entities separately, we are investigating in this paper a unified, multi-level, and correlative entity graph to represent the unstructured social media data, through which various applications (e.g., friend suggestion, personalized image search, image tagging, etc.) can be realized more effectively in one single framework. We regard the social media objects equally as "entities" and all of these applications as "entity search" problem which searches for entities with different types. We first construct a multi-level graph which organizes the heterogeneous entities into multiple levels, with one type of entities as vertices in each level. The edges between graphs pairwisely connect the entities weighted by intra-relations in the same level and inter-links across two different levels distilled from the social behaviors (e.g., tagging, commenting, and joining communities). To infer the strength of intra-relations, we propose a circular propagation scheme, which reinforces the mutual exchange of information across different entity types in a cyclic manner. Based on the constructed unified graph, we explicitly formulate entity search as a global optimization problem in a unified Bayesian framework, in which various applications are efficiently realized. Empirically, we validate the effectiveness of our unified entity graph for various social media applications on million-scale real-world dataset.
IP3-dependent, post-tetanic calcium transients induced by electrostimulation of adult skeletal muscle fibers

Tetanic electrical stimulation induces two separate calcium signals in rat skeletal myotubes, a fast one, dependent on Cav 1.1 or dihydropyridine receptors (DHPRs) and ryanodine receptors and related to contraction, and a slow signal, dependent on DHPR and inositol trisphosphate receptors (IP3Rs) and related to transcriptional events. We searched for slow calcium signals in adult muscle fibers using isolated adult flexor digitorum brevis fibers from 5–7-wk-old mice, loaded with fluo-3. When stimulated with trains of 0.3-ms pulses at various frequencies, cells responded with a fast calcium signal associated with muscle contraction, followed by a slower signal similar to one previously described in cultured myotubes. Nifedipine inhibited the slow signal more effectively than the fast one, suggesting a role for DHPR in its onset. The IP3R inhibitors Xestospongin B or C (5 µM) also inhibited it. The amplitude of post-tetanic calcium transients depends on both tetanus frequency and duration, having a maximum at 10–20 Hz. At this stimulation frequency, an increase of the slow isoform of troponin I mRNA was detected, while the fast isoform of this gene was inhibited. All three IP3R isoforms were present in adult muscle. IP3R-1 was differentially expressed in different types of muscle fibers, being higher in a subset of fast-type fibers. Interestingly, isolated fibers from the slow soleus muscle did not reveal the slow calcium signal induced by electrical stimulus. These results support the idea that IP3R-dependent slow calcium signals may be characteristic of distinct types of muscle fibers and may participate in the activation of specific transcriptional programs of slow and fast phenotype.
The Tolman Surface Brightness Test for the Reality of the Expansion. III. Hubble Space Telescope Profile and Surface Brightness Data for Early-Type Galaxies in Three High-Redshift Clusters

Photometric data for 34 early-type galaxies in the three high-redshift clusters Cl 1324+3011 (z = 0.76), Cl 1604+4304 (z = 0.90), and Cl 1604+4321 (z = 0.92), observed with the Hubble Space Telescope (HST) and with the Keck 10 m telescopes by Oke, Postman, & Lubin, are analyzed to obtain the photometric parameters of mean surface brightness, magnitudes for the growth curves, and angular radii at various Petrosian η radii. The angular radii at η = 1.3 mag for the program galaxies are all larger than 0. ″24. All the galaxies are well resolved at this angular size using HST, whose point-spread function is 0. ″05, half-width at half-maximum. The data for each of the program galaxies are listed at η = 1.0, 1.3, 1.5, 1.7, and 2.0 mag. They are corrected by color equations and K-terms for the effects of redshift to the rest-frame Cape/Cousins I for Cl 1324+3011 and Cl 1604+4304 and R for Cl 1604+4321. The K-corrections are calculated from synthetic spectral energy distributions derived from evolving stellar population models of Bruzual & Charlot, that have been fitted to the observed broadband (BVRI) AB magnitudes of each program galaxy. The listed photometric data are independent of all cosmological parameters. They are the source data for the Tolman surface brightness test made in Paper IV.
Relation between Agreement Measures on Human Labeling and Machine Learning Performance : Results from an Art History Image Indexing Domain

The domain of digital images and texts we focus on parallels the ARTstor Art HistorySurvey Collection (AHSC), a Mellon funded collection of 4,000 images. The AHSC is based on thirteen standard art history survey texts, thus there is a strong correlation between the images and these texts. The AHSC images all have tombstone metadata (e.g., the name of the work, the artist, date, the location of the work), but few have subject matter metadata. We are currently using two of the texts from the AHSC concordance that we scanned and encoded in TEI-Lite (http://www.teic.org/Lite/teiu5 split en.html).
The 5′-AT-rich half-site of Maf recognition element: a functional target for bZIP transcription factor Maf

The Maf family of proteins are a subgroup of basic region-leucine zipper (bZIP) transcription factors, which recognize a long palindromic DNA sequence [TGCTGAC(G)TCAGCA] known as the Maf recognition element (MARE). Interestingly, the functional target enhancer sequences present in the αA-crystallin gene contain a well-conserved half-site of MARE rather than the entire palindromic sequence. To resolve how Maf proteins bind to target sequences containing only MARE half-sites, we examined their binding activities using electrophoretic gel mobility shift assays as well as in vitro and in vivo reporter assays. Our results indicate that the 5′-flanking region of the MARE half-site is required for Maf proteins to bind both in vitro and in vivo. The critical 5′-flanking sequences for c-Maf were determined by a selection and amplification binding assay and show a preference for AT-rich nucleotides. Furthermore, sequence analysis of the regulatory regions of several target genes also suggests that AT-rich sequences are important. We conclude that Maf can bind to at least two types of target sequences, the classical MARE (palindrome type) and a 5′-AT-rich MARE half-site (half-site type). Our results provide important new insights into the DNA binding and site selection by bZIP transcription factors.
Guiding Dynamic Symbolic Execution toward Unverified Program Executions

Most techniques to detect program errors, such as testing, code reviews, and static program analysis, do not fully verify all possible executions of a program. They leave executions unverified when they do not check certain properties, fail to verify properties, or check properties under certain unsound assumptions such as the absence of arithmetic overflow. In this paper, we present a technique to complement partial verification results by automatic test case generation. In contrast to existing work, our technique supports the common case that the verification results are based on unsound assumptions. We annotate programs to reflect which executions have been verified, and under which assumptions. These annotations are then used to guide dynamic symbolic execution toward unverified program executions. Our main technical contribution is a code instrumentation that causes dynamic symbolic execution to abort tests that lead to verified executions, to prune parts of the search space, and to prioritize tests that cover more properties that are not fully verified. We have implemented our technique for the . NET static analyzer Clousot and the dynamic symbolic execution tool Pex. It produces smaller test suites (by up to 19.2%), covers more unverified executions (by up to 7.1%), and reduces testing time (by up to 52.4%) compared to combining Clousot and Pex without our technique.
A Novel Clustering Algorithm on Large-Scale Graph Data

Large scale Social Network Service (SNS) applications use graph as the default data organization model. To discover hidden useful information, data clustering techniques are widely adopted in data analysis tasks. State-of-the-art clustering algorithms are based on distributed programming paradigms such as MapReduce and Bulk Synchronization Parallel (BSP) models. These solutions suffer from heavy data transmission cost as well as excessive storage overhead problems. Thus, they can hardly achieve the optimal performance. In this paper, we propose a novel clustering algorithm based on pagerank to relieve these issues. Compare to current systems, our algorithm can achieve similar clustering results on large-scale graph data with much lower network and storage overhead. It consists of three steps. First, it calculates the pagerank values for each vertex based on the underlying data set. Then, we select multiple vertexes from the list as clustering centers. Third, our algorithm expands the range of the cluster by adding more neighboring vertexes iteratively. We compare our algorithm with other popular clustering algorithms using real world data sets and the results show that it achieves better performance than any other distributed solutions. For example, on a web graph data set with hundreds of thousands of vertexes and millions of edges, the time and memory consumption can be reduced by more than 95% and 70%, respectively.