Miracle-dz/UniFAR-FTUs huggingface dataset:
SEPSen: semantic event processing at the sensor nodes for energy efficient wireless sensor networks

Traditionally in WSNs, the sensor nodes are used only for capturing data that is then later analyzed in the more powerful gateway nodes. This requires a continuous communication that wastes energy at the sensor nodes and greatly reduces the overall network lifetime. We propose a semantic-based in-network data processing that reduces energy consumption and improves the scalability of heterogeneous sensor networks. Ontology fragments in each sensor node help identify the data routed through the sensor network. We have adapted a matching algorithm to process a changing knowledge base. Simulation results show that the networks' energy consumption is considerably reduced.
Cortical patch basis model for spatially extended neural activity

A new source model for representing spatially distributed neural activity is presented. The signal of interest is modeled as originating from a patch of cortex and is represented using a set of basis functions. Each cortical patch has its own set of bases, which allows representation of arbitrary source activity within the patch. This is in contrast to previously proposed cortical patch models which assume a specific distribution of activity within the patch. We present a procedure for designing bases that minimize the normalized mean squared representation error, averaged over different activity distributions within the patch. Extension of existing algorithms to the basis function framework is straightforward and is illustrated using linearly constrained minimum variance (LCMV) spatial filtering and maximum-likelihood signal estimation/generalized likelihood ratio test (ML/GLRT). The number of bases chosen for each patch determines a tradeoff between representation accuracy and the ability to differentiate between distinct patches. We propose choosing the minimum number of bases that satisfy a constraint on the normalized mean squared representation accuracy. A mismatch analysis for LCMV and ML/GLRT is presented to show that this is an appropriate strategy for choosing the number of bases. The effectiveness of the patch basis model is demonstrated using real and simulated evoked response data. We show that significant changes in performance occur as the number of basis functions varies, and that very good results are obtained by allowing modest representation error
Safe Overclocking of Tightly Coupled CGRAs and Processor Arrays using Razor

Overclocking a CPU is a common practice among home-built PC enthusiasts where the CPU is operated at a higher frequency than its speed rating. This practice is unsafe because timing errors cannot be detected by modern CPUs and they can be practically undetectable by the end user. Using a timing speculation technique such as Razor, it is possible to detect timing errors in CPUs. To date, Razor has been shown to correct only unidirectional, feed-forward processor pipelines. In this paper, we safely overclock 2D arrays by extending Razor correction to cover bidirectional communication in a tightly coupled or lockstep fashion. To recover from an error, stall wavefronts are produced which propagate across the device. Multiple errors may arise in close proximity in time and space; if the corresponding stall wavefronts collide, they merge to produce a single unified wavefront, allowing recovery from multiple errors with one stall cycle. We demonstrate the correctness and viability of our approach by constructing a proof-of-concept prototype which runs on a traditional Altera FPGA. Our approach can be applied to custom computing arrays, systolic arrays, CGRAs, and also time-multiplexed FPGAs such as those produced by Tabula. As a result, these devices can be overclocked and safely tolerate dynamic, data-dependent timing errors. Alternatively, instead of overclocking, this same technique can be used to `undervolt' the power supply and save energy.
Molecular Basis of Bacterial Outer Membrane Permeability Revisited

SUMMARY Gram-negative bacteria characteristically are surrounded by an additional membrane layer, the outer membrane. Although outer membrane components often play important roles in the interaction of symbiotic or pathogenic bacteria with their host organisms, the major role of this membrane must usually be to serve as a permeability barrier to prevent the entry of noxious compounds and at the same time to allow the influx of nutrient molecules. This review summarizes the development in the field since our previous review (H. Nikaido and M. Vaara, Microbiol. Rev. 49:1-32, 1985) was published. With the discovery of protein channels, structural knowledge enables us to understand in molecular detail how porins, specific channels, TonB-linked receptors, and other proteins function. We are now beginning to see how the export of large proteins occurs across the outer membrane. With our knowledge of the lipopolysaccharide-phospholipid asymmetric bilayer of the outer membrane, we are finally beginning to understand how this bilayer can retard the entry of lipophilic compounds, owing to our increasing knowledge about the chemistry of lipopolysaccharide from diverse organisms and the way in which lipopolysaccharide structure is modified by environmental conditions.
A Markov chain model to evaluate patient transitions in small community hospitals

A patient journey in the hospital may include many departments or units. Making safe and smooth transitions within the hospital is of significant importance. This paper introduces a Markov chain model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward. An iteration method is presented to evaluate the performance of transition process. It is shown that such a method has a high accuracy of estimation and can be used to study patient transitions in small community hospitals.
Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient

Image registration is the process by which we determine a transformation that provides the most accurate match between two images. The search for the matching transformation can be automated with the use of a suitable metric, but it can be very time-consuming and tedious. We introduce a registration algorithm that combines a simple yet powerful search strategy based on a stochastic gradient with two similarity measures, correlation and mutual information, together with a wavelet-based multiresolution pyramid. We limit our study to pairs of images, which are misaligned by rotation and/or translation, and present two main results. First, we demonstrate that, in our application, mutual information may be better suited for sub-pixel registration as it produces consistently sharper optimum peaks than correlation. Then, we show that the stochastic gradient search combined with either measure produces accurate results when applied to synthetic data, as well as to multitemporal or multisensor collections of satellite data. Mutual information is generally found to optimize with one-third the number of iterations required by correlation. Results also show that a multiresolution implementation of the algorithm yields significant improvements in terms of both speed and robustness over a single-resolution implementation.
Causality relation map: A novel methodology for the identification of hierarchical fibrillatory processes

Cardiac fibrillation is a complex arrhythmia whose mechanisms of onset, maintenance and interruption are not completely understood. Fibrillatory processes have usually been considered as random phenomena without any apparent coordinated pattern. However, recently developed experimental and human studies have demonstrated that a hierarchical activation may govern some fibrillatory processes. In this study a novel methodology for the identification of hierarchical activation patterns is presented. Specifically, causal relations between neighboring electrodes are used to identify predominant propagation directions. The presented methodology may be of useful to identify regions of the myocardium that may sustain a fibrillatory process and consequently are targets for arrhythmia termination.
Link Discovery in the Wikipedia

In this paper we describe our approaches taken in the Link-the-Wiki track. We submitted runs for all three Link-the-Wiki tasks: Link-the-Wiki, Link-Te-Ara, and Link-Te-Ara-to-the-Wiki. To generate outgoing links for each task, our link discovery system employs the top ranking algorithms from previous LTW tracks and a hybrid method derived from them. For incoming links, we used traditional information retrieval strategy on the Wikipedia XML collection. The official results for the INEX 2009 Link-the-Wiki track show encouraging performance of our system.
Reverse Reverse-Engineering

Reverse engineering a program constructs a high-level representation suitable for various software development purposes such as documentation or reengineering. Unfortunately however, there are no established guidelines to assess the adequacy of such a representation. We propose two such criteria, completeness and accuracy, and show how they can be determined during the course of reversing the representation. A representation is successfully reversed when it is given as input to a suitable code generator, and a program equivalent to the original is produced. To explore this idea, we reverse engineer a small but complex numerical application, represent our understanding using algebraic specifications, and then use a code generator to produce code from the specification. We discuss the strengths and weaknesses of the approach as well as alternative approaches to reverse engineering adequacy.
Microalgae Tolerance to High Concentrations of Carbon Dioxide: A Review

The increasing concentration of carbon dioxide (CO2) in the atmosphere is considered to be one of the main causes of the global warming problem. Moreover, there is an international movement to reduce the emission of CO2 by imposing different measures such as carbon tax. Biological CO2 fixation has been extensively investigated as part of efforts to solve the global warming problem. Microalgae are fast growing systems that can consume high quantities of CO2 to produce different types of biomass. The efficiency of microalgae is highly related to the concentration of CO2 in the growth atmosphere and the higher the concentration of CO2 the better is the growth and hence productivity. The present review aimed at shedding some light upon microalgal capability to sustain their viability and propagate under high CO2 concentration.
Authoring Simulation-Centered Tutors with RIDES

RIDES is an application for authoring and delivering interactive graphical simulations and tutorials in the context of those simulations. Some types of instruction can be generated automatically by exploiting structured simulation data. RIDES technology plays an important part in a number of related research and development projects. RIDES introduces innovations in the human-computer interface (HCI) of simulation-centered tutorial authoring systems, including support for constraint and event authoring, enforcing the primacy of reference, and permitting the authoring of procedure tutorials by interactive demonstration. RIDES simulations provide low level automatic support for detecting student operations and observations and are well-suited for teaching procedures. Authoring use has revealed a number of additional design considerations that should be taken into account in the development of future tutor authoring systems. Foremost among these is the need for an open architecture that supports collaboration among tutor components, including collaboration with types of tutor components that have not yet been developed.
Enhancing Human Aspect of Software Engineering using Bayesian Classifier

IT industries in current scenario have to struggle effectively in terms of cost, quality, service or innovation for their subsistence in the global market. Due to the swift transformation of technology, software industries owe to manage a large set of data having precious information hidden. Data mining technique enables one to effectively cope with this hidden information where it can be applied to code optimization, fault prediction and other domains which modulates the success nature of software projects. Additionally, the efficiency of the product developed further depends upon the quality of the project personnel. The position of the paper therefore is to explore potentials of project personnel in terms of their competency and skill set and its influence on quality of project. The above mentioned objective is accomplished using a Bayesian classifier in order to capture the pattern of human performance. By this means, the hidden and valuable knowledge discovered in the related databases will be summarized in the statistical structure. This mode of predictive study enables the project managers to reduce the failure ratio to a significant level and improve the performance of the project using the right choice of project personnel.
Persuasive Effects of Presence in Immersive Virtual Environments

In general, current research suggests that virtual environments, compared to classical advertising media, provide users with a higher level of presence, more perceptual and psychological immersion. This paper reviews empirical findings from an ongoing research program studying information processing consequences of presence in virtual environments. Based on theoretical models and preliminary findings from recent empirical studies summarized in this chapter, a two-step theoretical model of persuasion-related effects is proposed: more presence will, probably, lead to more arousal and affect, which will have a subsequent impact on depth of processing, making the user more likely to process information affectively, more implicitly and heuristically. This, in turn, will have the effect of making him/her less aware of an embedded persuasive message, which will thus have a moderating effect on various advertising-related outcomes: less ad recall, but more positive brand attitudes and favorable purchase intentions. The paper proposes that due to their specific characteristics, immersive virtual environments could be more effective persuasion channels, than classical advertising media. This could be a very useful finding for applications in entertainment VR, e-marketing, advertising, public or health communication.
Impact of Neurodevelopmental Genes on the Trajectory of ADHD Severity: A Pilot Study

Impact of Neurodevelopmental Genes on the Trajectory of ADHD severity: A Pilot Study by Agnieszka Mlodnicka Advisor: Dr. Jeffrey Halperin Attention-deficit/Hyperactivity Disorder (ADHD) is a chronic neurodevelopmental disorder characterized by symptoms of inattention and hyperactivity, and is associated with delays in neural development. To assess the association of genes involved in neurodevelopment with symptoms and trajectory of ADHD, saliva was collected and genotyped from 145 participants from a longitudinal study of preschoolers who were followed annually for 7 years. We examined four single nucleotide polymorphisms (SNPs) in genes associated with neurodevelopment: neuregulin-1 (NRG-1; SNP rs3924999), neurotropin-3 (NT-3; SNP rs6489630), brain-derived neurotrophic factor (BDNF; rs6265), and regulator of G protein signaling 4 (RGS4; rs951439). Hierarchical linear modeling revealed that neuregulin-1 and neurotropin-3 were associated with symptoms of inattention and hyperactivity at age 3-4 and throughout early childhood; however, these genes did not impact the trajectory of the inattentive and hyperactive symptoms over development. Early environmental factors such as maternal diabetes, maternal substance use (tobacco, alcohol, illicit drug) were also analyzed along with each of the genetic factors. Maternal gestational diabetes and NRG-1 risk allele, maternal gestational diabetes and BDNF, alcohol and NRG-1, and illicit drug use and NT-3 were all associated with greater inattentive and hyperactive symptoms. Although the sample size is small for a genetics study, these findings can inform future investigations in understanding the neurodevelopment and heritability of ADHD. NEURODEVELOPMENTAL GENES ADHD v
An Optimization Based Approach for Quality of Service Routing in High-Bandwidth Networks

Abstract In this paper, we propose an optimization based approach for Quality of Service routing in high-bandwidth networks. We view a network that employs QoS routing as an entity that distributively optimizes some global utility function. By solving the optimization problem, the network is driven to an efficient operating point. In earlier work, it has been shown that when the capacity of the network is large, this optimization takes on a simple form, and once the solution to this optimization problem is found, simple proportional QoS routing schemes will suffice. However, this optimization problem requires global information. We develop a distributed and adaptive algorithm that can efficiently solve the optimization online. Compared with existing QoS routing schemes, the proposed optimization based approach has the following advantages: (1) The computation and communication overhead can be greatly reduced without sacrificing performance; (2) The operating characteristics of the network can be analytically studied; and (3) The desired operating point can be tuned by choosing appropriate utility functions. This work has been partially supported by the NSF grant ANI-0099137 and the Indiana 21st Century Fund 651-1285-074.
Genome-Wide Transcriptional and Post-transcriptional Regulation of Innate Immune and Defense Responses of Bovine Mammary Gland to Staphylococcus aureus

Staphylococcus aureus (S. aureus) is problematic for lactating mammals and public health. Understanding of mechanisms by which the hosts respond to severe invasion of S. aureus remains elusive. In this study, the genome-wide expression of mRNAs and miRNAs in bovine mammary gland cells were interrogated at 24 h after intra-mammary infection (IMI) with high or low concentrations of S. aureus. Compared to the negative control quarters, 194 highly-confident responsive genes were identified in the quarters with high concentration (109 cfu/mL) of S. aureus, which were predominantly implicated in pathways and biological processes pertaining to innate immune system, such as cytokine-cytokine receptor interaction and inflammatory response. In contrast, only 21 highly-confident genes were significantly differentially expressed in face of low concentration (106 cfu/mL) of S. aureus, which slightly perturbed the cell signaling and invoked corresponding responses like vasoconstriction, indicating limited perturbations and immunological evading. Additionally, the significant up-regulations of bta-mir-223 and bta-mir-21-3p were observed in the quarters infected by high concentration of S. aureus. Network analysis suggested that the two miRNAs' pivotal roles in defending hosts against bacterial infection probably through inhibiting CXCL14 and KIT. The significant down-regulation of CXCL14 was also observed in bovine mammary epithelial cells at 24 h post-infection of S. aureus (108 cfu/mL) in vitro. Integrated analysis with QTL database further suggested 28 genes (e.g., CXCL14, KIT, and SLC4A11) as candidates of bovine mastitis. This study first systematically revealed transcriptional and post-transcriptional responses of bovine mammary gland cells to invading S. aureus in a dosage-dependent pattern, and highlighted a complicated responsive mechanism in a network of miRNA-gene-pathway interplay.
A segmentation progressive mesh compression method

The progressive mesh compression algorithm on the blocks of model based on edge-collapse mesh simplification is proposed to solve some practical problems. At first, we adopt K-means to cluster the mesh triangles. Secondly, we compress each model block. The detail information of different groups obtained by compressing each of blocks are independent of each other. If some details are lost in transmission, other details can also decode independently. We only need to request server to resend the lost part of the groups data. At the same time, it can be decoded regional details depend on our viewpoint when we need to load the complex models. Because our vision can only focus on part region of model, and the area in which we isn't interested can be instead by coarse model.
Steganography using JPEG-compressed images

In this paper, a novel steganographic method based on JPEG is proposed. We take advantage of the quantization error resulting from processing the JPEG-compressed image with two different scaling factors. One of the scaling factors is used to control the bit rate of the stego-image while the other is used to guarantee the quality of the stego-image. Our experimental results show that the proposed steganographic method can provide a high information hiding capacity and successfully control the compression ratio and distortion of the stego-image.
Challenges in development of the American Sign Language Lexicon Video Dataset (ASLLVD) corpus

The American Sign Language Lexicon Video Dataset (ASLLVD) consists of videos of >3,300 ASL signs in citation form, each produced by 1-6 native ASL signers, for a total of almost 9,800 tokens. This dataset, including multiple synchronized videos showing the signing from different angles, will be shared publicly once the linguistic annotations and verifications are complete. Linguistic annotations include gloss labels, sign start and end time codes, start and end handshape labels for both hands, morphological and articulatory classifications of sign type. For compound signs, the dataset includes annotations for each morpheme. To facilitate computer vision-based sign language recognition, the dataset also includes numeric ID labels for sign variants, video sequences in uncompressed-raw format, camera calibration sequences, and software for skin region extraction. We discuss here some of the challenges involved in the linguistic annotations and categorizations. We also report an example computer vision application that leverages the ASLLVD: the formulation employs a HandShapes Bayesian Network (HSBN), which models the transition probabilities between start and end handshapes in monomorphemic lexical signs. Further details and statistics for the ASLLVD dataset, as well as information about annotation conventions, are available from http://www.bu. edu/asllrp/lexicon.
SPATIOTEMPORAL CONTROL OF WAVE INSTABILITIES IN CARDIAC TISSUE

Electrical waves circulating around an obstacle in cardiac tissue are subject to a generic oscillatory instability. In a one-dimensional ring geometry this instability can produce both quasiperiodic and spatiotemporally chaotic oscillations while in a two-dimensional sheet of cardiac tissue it can lead to spiral wave breakup. We present a control scheme to prevent this instability in these two geometries which is based on applying a feedback current at a discrete set of control points during the repolarizing phase of the action potential. The feasibility of this scheme is demonstrated via simulations of a two-variable model of excitable media with restitution and of the Beeler-Reuter model of ventricular action potential.