Miracle-dz/UniFAR-FTUs huggingface dataset:
Random frames from binary linear block codes

Let C be an [n, k, d] binary linear block code of length n, dimension k and minimum Hamming distance d over GF(2<sup>n</sup>). Let d<sup>⊥</sup> denote the minimum Hamming distance of the dual code of C over GF(2<sup>n</sup>). Let ɛ : GF(2<sup>n</sup>) → {−1, 1}n be the component-wise mapping ɛ(v<inf>i</inf>) := (−1)<sup>vi</sup> , for v =(v<inf>1</inf>, v<inf>2</inf>, … , v<inf>n</inf>) ∈ GF(2<sup>n</sup>). Finally, for p ≪ n, let φ<inf>C</inf> be a p × n random matrix whose rows are obtained by mapping a uniformly drawn set of size p of the codewords of C under e. Recently, the authors have established that [3] for d<sup>⊥</sup> large enough and y := p/n ∈ (0, 1) fixed, as n → ∞ the empirical eigen-distribution of the Gram matrix of 1 over √n times φ<inf>C</inf> resembles that of a random i.i. d. Rademacher matrix (i.e., the Marchenko-Pastur distribution). In this paper, we overview this result and discuss its implications on the design of frames for compressed sensing applications.
Static output feedback stabilization: necessary conditions for multiple delay controllers

This note focuses on the static output feedback stabilization problem for a class of single-input-single-output systems when the control law includes multiple (distinct) delays. We are interested in giving necessary conditions for the existence of such stabilizing controllers. Illustrative examples (second-order system, chain of integrators, or chain of oscillators) are presented, and discussed.
The elephant in the room: ambiguity and temporary closure in a design process

In this paper we challenge the Participatory Design practice of integrating lay perspectives and involving users in the design process. We do this by questioning the ways in which "asking", "participation", or "involvement" is practically staged. With the aim of exploring how ideas and concepts come to be or come to be rejected, and what is the role of materials in this process we report on an experimental workshop wherein student design teams work on a case. The study shows how design ideas and concepts are managed through the phase of idea generation and conceptualization. Design decisions are really oscillations between ambiguity and temporary closures or stabilizations. They are not forking paths of decisions that lead to possibilities that lead to rhetorical situations and so on. The paper shows the potential centripetal (i.e. centering and attention grabbing) force of materials in a design workshop.
Relay based cooperative spectrum sensing in distributed cognitive radio networks

In cognitive radio (CR), spectrum sensing plays a fundamental and critical role. This paper deals with the issue of spectrum sensing in a distributed CR network, and proposes a novel relay based cooperative spectrum sensing method, which makes one secondary user (SU) with higher signal-to-noise ratio spend part of its sensing time acting as the relay node. Different from conventional relay based methods, this method does not require idle SUs, and thereby is able to work well even when all SUs in the network sense and access the licensed spectrum band simultaneously. Moreover, via maximizing the agility of the entire CR network, its relay policy is optimized. Simulation results are provided to verify the optimal relay policy as well as its agility again.
SS-ADC: Scatter search with adaptive diversity control

Basic Scatter Search is a meta-heuristic approach based evolutionary method which yields promising outcomes for solving some of the combinatorial and nonlinear optimization problems. But due to the loss of population diversity, Standard Scatter Search techniques are often reported to have converged too early producing suboptimal solutions. Addressing this problem we propose a variant of Scatter Search which controls the diversity dynamically through the generations and reduces the possibility of premature convergence. We denote this variant as Scatter Search with Adaptive Diversity Control (SS-ADC). This method performs better than Basic Scatter Search on ten and similar on twelve functions from a total of twenty three benchmark functions.
Robustness in Highly Dynamic Networks

We investigate a special case of hereditary property that we refer to as {\em robustness}. A property is {\em robust} in a given graph if it is inherited by all connected spanning subgraphs of this graph. We motivate this definition in different contexts, showing that it plays a central role in highly dynamic networks, although the problem is defined in terms of classical (static) graph theory. In this paper, we focus on the robustness of {\em maximal independent sets} (MIS). Following the above definition, a MIS is said to be {\em robust} (RMIS) if it remains a valid MIS in all connected spanning subgraphs of the original graph. We characterize the class of graphs in which {\em all} possible MISs are robust. We show that, in these particular graphs, the problem of finding a robust MIS is {\em local}; that is, we present an RMIS algorithm using only a sublogarithmic number of rounds (in the number of nodes $n$) in the ${\cal LOCAL}$ model. On the negative side, we show that, in general graphs, the problem is not local. Precisely, we prove a $\Omega(n)$ lower bound on the number of rounds required for the nodes to decide consistently in some graphs. This result implies a separation between the RMIS problem and the MIS problem in general graphs. It also implies that any strategy in this case is asymptotically (in order) as bad as collecting all the network information at one node and solving the problem in a centralized manner. Motivated by this observation, we present a centralized algorithm that computes a robust MIS in a given graph, if one exists, and rejects otherwise. Significantly, this algorithm requires only a polynomial amount of local computation time, despite the fact that exponentially many MISs and exponentially many connected spanning subgraphs may exist.
Achieving Coverage through Distributed Reinforcement Learning in Wireless Sensor Networks

With the extensive implementations of wireless sensor networks in many areas, it is imperative to have better management of the coverage and energy consumption of such networks. These networks consist of large number of sensor nodes and therefore a multi-agent system approach needs to be taken in order for a more accurate model. Three coordination algorithms are being put to the test in this paper: (i) fully distributed Q-learning which we refer to as independent learner (IL), (ii) distributed value function (DVF) and (iii) an algorithm we developed which is a variation of the IL, coordinated algorithm (COORD). The results show that the IL and DVF algorithm performed for higher sensor node densities but at low sensor node densities, the three algorithms have similar performance.
Average levels and power spectra of ambient sound in the habitat of southern resident orcas

We used a pair of hydrophones to monitor sound pressure levels (SPL, dB re 1 μPa) and frequency spectra of ambient sounds in Haro Strait during 18 months (April 2004 November 2005). Half-hour average SPL in the broad frequency band 0.1-15 kHz ranges from minimum (background) levels of 95 dB to maximum levels of 130 dB. The average SPL over 17 months is 115 dB. The broadband sound field is dominated by noise from large vessels (commercial ships). They increase two-second average SPL ~20-25 dB for 10-30 minute periods about 20 times per day, thereby elevating the 17-month average SPL ~20 dB above background levels. Smaller vessels (motor boats) raise two-second SPL about as much as ships (15-20 dB) but do so for shorter periods and at higher frequencies (10-20 kHz). Their prevalence during summer afternoons explains why the average SPL during summer days (118 dB) is 3 dB higher than during summer nights, winter days, or winter nights.
Recognizing patterns in high-dimensional data: automated histogram filtering for protein structure elucidation

Advanced automated clustering algorithms are essential to meet the challenge of understanding high-dimensional data that arise in protein structure elucidation. In this paper, we first describe a powerful new approach to cluster analysis, automated histogram filtering (AHF). We follow this by a review of applications of AHF-clustering of Monte Carlo and molecular dynamics simulation data for off-lattice and all-atom model protein systems. Next, we present the results of a time-complexity analysis performed on a computer cluster suggesting how the computational effort scales with the size of the protein and the number of processors. And finally, we conclude with a summary of our findings.
The Rapidly Expanding Family of Human Polyomaviruses: Recent Developments in Understanding Their Life Cycle and Role in Human Pathology

Since their discovery in 1971, the polyomaviruses JC (JCPyV) and BK (BKPyV), isolated from patients with progressive multifocal leukoencephalopathy and polyomavirus-associated nephropathy, respectively, remained for decades as the only known members of the Polyomaviridae family of viruses of human origin. Over the past five years, the application of new genomic amplification technologies has facilitated the discovery of several novel human polyomaviruses (HPyVs), bringing the present number to 10. These HPyVs share many fundamental features in common such as genome size and organization. Infection by all HPyVs is widespread in the human population, but they show important differences in their tissue tropism and association with disease. Much remains unknown about these new viruses. In this review, we discuss the problems associated with studying HPyVs, such as the lack of culture systems for the new viruses and the gaps in our basic understanding of their biology. We summarize what is known so far about their distribution, life cycle, tissue tropism, their associated pathologies (if any), and future research directions in the field.
A Summary of the Vocabulary Research With Students Who Are Deaf or Hard of Hearing

Vocabulary is essential for communicating, reading, thinking, and learning. In comparison to typical hearing peers, students who are deaf or hard of hearing demonstrate vocabulary knowledge that is quantitatively reduced. The authors review and summarize research studies published in peer-reviewed journals between 1967 and 2008 focusing on vocabulary and students who are deaf or hard of hearing. Forty-one studies are examined. A summary of each study is presented in a table, and potential educational implications are described. The authors note the paucity of research to guide instruction and provide suggestions for future research.
The Smart-TSH-Finder: Crawling and Analyzing Tempo-Spatial Hotspots in Second Life

In this paper we introduce the Smart Tempo-Spatial Hotspots Finder (Smart-TSH-Finder) for smart data crawling in the Second Life (SL) virtual world. Classical methods of crawling data from SL lead to irrelevant data content because of the dynamic nature of avatars and objects in SL. In order to build artificially intelligent expert avatar agents that are able to provide intelligent services for other typical avatars in virtual world we attempt to enhance the quality of extracted data from SL. Based on experimental observation, avatars tend to gather in some places for different amounts of time, which forms temporal and spatial hotspots. Utilizing the Tempo-Spatial characteristics of the avatars behavior in virtual worlds could improve the quality of the extracted data. Smart-TSHFinder implements a Tempo-Spatial Hotspots finding mechanism to crawl dynamic contents such as chat conversations from Second Life. The system introduces two mechanisms: the Tempo-Spatial Hotspots Detection, and the Tempo-Spatial Hotspots Prediction. Our smart chat conversations that have been crawled showed good enhancement in content quality of the crawled chat conversation which will enrich the future textual analysis work. Additionally, we found that extracting avatars interactions and behavior in the Tempo-Spatial Hotspots in addition to chat conversations can help in generation a more coherent social network model for SL.
NTRP: Novel approach for DUT testing based on nonintrusive timing randomization probes using SystemC verification library

To meet the rapidly transforming computing requirement of System on Chip (SoC), On-Chip Interconnect BUS specifications is been evolved continuously from single-channel one-way, serial, in-order, shared BUS communication system to complex multi-channel, burst based, out-of-order, separate read/ write/ address BUS communication system. This resulted in development of several industry standard verification methodologies using Hardware Description Languages particularly System Verilog like Universal Verification Methodology (UVM) facilitating constrained randomization based stimulus generation and functional coverage. Adopting such methodologies involves its know-how to get accustomed, recurring licensing charges and simulation overhead. In this work, for stress testing of Design Under Test (DUT), a novel approach is proposed based on Bus Cycle Accurate Nonintrusive Timing Randomization Probes (NTRP) using SystemC Verification (SCV) Library. Based on empirical results, it is argued that the annotations proposed in the work using NTRP causes little overhead, however provides convenient approach for adding timing delays to the interface of DUT including other advantages particularly — transactions reordering for better BUS utilization, selective constrained randomization on interface signal timing, score boarding for self-checking, little simulation overheads and no licensing terms, being based on Open Source SCV, makes it convenient to adopt for DUT testing.
New Entry Threats, Firm Governance, and Innovation in the U.S. IT Industry

We examine how firms in the U.S.-based IT industry adjust their innovation strategy based on two factors that have been under-studied in the literature: the potential new entry threats the firm faces in its product market, and the firm’s governance structure. We argue that: 1) turbulence in the product markets caused by threat from entrepreneurial startups affects the focal firm’s investments in long-term risky activities such as innovation, and 2) this relationship is moderated by the extent to which management of the firm is protected through corporate governance. While extant research has discussed the potential disruptions that incumbent firms may experience from start-ups and their technologies, the absence of acceptable measures of industry classification for startups as well as the inability to accurately gauge when they represent a credible threat has limited empirical research into this question. We contribute a new measure to identify these threats through text analyses based on product descriptions provided by incumbent firm 10-K filings and product blurbs provided by start-ups. This new measure differs significantly from approaches that use static industry classifications, which are backward-looking and do not fully account for industry evolution over time, thereby not capturing the threat of new entry. We measure the degree to which managers are protected through corporate governance using the G-Index (Gompers et al. 2003). Our analyses, performed on a sample of IT firms during the period 1997-2007, show that incumbent firms react to new entry threats by systematically reducing innovation. Moreover, more governance provisions protecting managers amplify this effect: protected managers reduce innovation to a greater extent when the firm faces intensive new entry threats. We discuss the implications for research and practice.
An MMIC receiver front-end design for 2.4GHz frequency band applications in 0.2μm GaAs pseudomorphic HEMT process

A 2.4-GHz radio receiver front-end for ISM-band applications incorporating the superheterodyne architecture is designed and simulated in 0. 2μm GaAs pseudomorphic HEMT technology. It features an ultra low-noise cascode-topology highly-integrated amplifier followed by an external image-rejection band-pass filter and an active half-Gilbert-cell down-conversion mixer with an IF frequency of 340 MHz. The receiver chain showed a gain, noise figure and input-referred third-order intercept-point equal to 17.9 dB, 1.8 dB and −18 dBm, respectively. Operating in 3-volt DC supply, it draws a 33-mA current. Finally, the characteristics of this front-end are compared in brief with those of a front-end of the same topology, but in a different process.
Depth-Based View-Invariant Blind 3D Image Watermarking

With the huge advance in Internet technology as well as the availability of low-cost 3D display devices, 3D image transmission has become popular in recent times. Since watermarking has become regarded as a potential Digital Rights Management (DRM) tools in the past decade, 3D image watermarking is an emerging research topic. With the introduction of the Depth Image-Based Rendering (DIBR) technique, 3D image watermarking is a more challenging task, especially for synthetic view generation. In this article, synthetic view generation is regarded as a potential attack, and a blind watermarking scheme is proposed that can resist it. In the proposed scheme, the watermark is embedded into the low-pass filtered dependent view region of 3D images. Block Discrete Cosine Transformation (DCT) is used for spatial-filtration of the dependent view region to find the DC coefficient with horizontally shifted coherent regions from the left and right view to make the scheme robust against synthesis view attack. A comprehensive set of experiments have been carried out to justify the robustness of the proposed scheme over related existing schemes with respect to Stereo JPEG compression and different noise addition attacks.
Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers

The RANSAC [2] algorithm (RANdom SAmple Consensus) is a robust method to estimate parameters of a model tting the data, in presence of outliers among the data. Its random nature is due only to complexity considerations. It iteratively extracts a random sample out of all data, of minimal size sucient to estimate the parameters. At each such trial, the number
HLA DR-DQ Haplotypes and Genotypes and Type 1 Diabetes Risk

OBJECTIVE—The Type 1 Diabetes Genetics Consortium has collected type 1 diabetic families worldwide for genetic analysis. The major genetic determinants of type 1 diabetes are alleles at the HLA-DRB1 and DQB1 loci, with both susceptible and protective DR-DQ haplotypes present in all human populations. The aim of this study is to estimate the risk conferred by specific DR-DQ haplotypes and genotypes. RESEARCH DESIGN AND METHODS:—Six hundred and seven Caucasian families and 38 Asian families were typed at high resolution for the DRB1, DQA1, and DQB1 loci. The association analysis was performed by comparing the frequency of DR-DQ haplotypes among the chromosomes transmitted to an affected child with the frequency of chromosomes not transmitted to any affected child. RESULTS—A number of susceptible, neutral, and protective DR-DQ haplotypes have been identified, and a statistically significant hierarchy of type 1 diabetes risk has been established. The most susceptible haplotypes are the DRB1*0301-DQA1*0501-DQB1*0201 (odds ratio [OR] 3.64) and the DRB1*0405-DQA1*0301-DQB1*0302, DRB1*0401-DQA1*0301-DQB*0302, and DRB1*0402-DQA1*0301-DQB1*0302 haplotypes (ORs 11.37, 8.39, and 3.63), followed by the DRB1*0404-DQA1*0301-DQB1*0302 (OR 1.59) and the DRB1*0801-DQB1*0401-DQB1*0402 (OR 1.25) haplotypes. The most protective haplotypes are DRB1*1501-DQA1*0102-DQB1*0602 (OR 0.03), DRB1*1401-DQA1*0101-DQB1*0503 (OR 0.02), and DRB1*0701-DQA1*0201-DQB1*0303 (OR 0.02). CONCLUSIONS—Specific combinations of alleles at the DRB1, DQA1, and DQB1 loci determine the extent of haplotypic risk. The comparison of closely related DR-DQ haplotype pairs with different type 1 diabetes risks allowed identification of specific amino acid positions critical in determining disease susceptibility. These data also indicate that the risk associated with specific HLA haplotypes can be influenced by the genotype context and that the trans-complementing heterodimer encoded by DQA1*0501 and DQB1*0302 confers very high risk.
OpenABLE: An open-source toolbox for application in life-long visual localization of autonomous vehicles

Visual information is a valuable asset in any perception scheme designed for an intelligent transportation system. In this regard, the camera-based recognition of locations provides a higher situational awareness of the environment, which is very useful for varied localization solutions typically needed in long-term autonomous navigation, such as loop closure detection and visual odometry or SLAM correction. In this paper we present OpenABLE, an open-source toolbox contributed to the community with the aim of helping researchers in the application of these kinds of life-long localization algorithms. The implementation follows the philosophy of the topological place recognition method named ABLE, including several new features and improvements. These functionalities allow to match locations using different global image description methods and several configuration options, which enable the users to control varied parameters in order to improve the performance of place recognition depending on their specific problem requisites. The applicability of our toolbox in visual localization purposes for intelligent vehicles is validated in the presented results, jointly with comparisons to the main state-of-the-art methods.
Filter Importance Sampling

High quality ray tracing requires pixel sampling and filtering for antialiasing, as well as illumination sampling for complex lighting effects. Both problems are well understood and sophisticated sampling techniques are available for each of them. However, it turns out that weighted pixel sampling spoils the benefits of clever illumination sampling, even with the best filter functions. We propose to circumvent this problem by using pixel sampling and filtering based on importance sampling. Although this technique disallows sharing of samples between neighboring pixels, it results in significant noise reduction and improvement of image quality. The method is easy to implement and well suited for parallel, tile based rendering
Secreted Phospholipases A2 of Snake Venoms: Effects on the Peripheral Neuromuscular System with Comments on the Role of Phospholipases A2 in Disorders of the CNS and Their Uses in Industry

Neuro- and myotoxicological signs and symptoms are significant clinical features of envenoming snakebites in many parts of the world. The toxins primarily responsible for the neuro and myotoxicity fall into one of two categories—those that bind to and block the post-synaptic acetylcholine receptors (AChR) at the neuromuscular junction and neurotoxic phospholipases A2 (PLAs) that bind to and hydrolyse membrane phospholipids of the motor nerve terminal (and, in most cases, the plasma membrane of skeletal muscle) to cause degeneration of the nerve terminal and skeletal muscle. This review provides an introduction to the biochemical properties of secreted sPLA2s in the venoms of many dangerous snakes and a detailed discussion of their role in the initiation of the neurologically important consequences of snakebite. The rationale behind the experimental studies on the pharmacology and toxicology of the venoms and isolated PLAs in the venoms is discussed, with particular reference to the way these studies allow one to understand the biological basis of the clinical syndrome. The review also introduces the involvement of PLAs in inflammatory and degenerative disorders of the central nervous system (CNS) and their commercial use in the food industry. It concludes with an introduction to the problems associated with the use of antivenoms in the treatment of neuro-myotoxic snakebite and the search for alternative treatments.