Miracle-dz/UniFAR-FTUs huggingface dataset:
All pairs shortest paths in undirected graphs with integer weights

We show that the all pairs shortest paths (APSP) problem for undirected graphs with integer edge weights taken from the range {1, 2, . , M} can be solved using only a logarithmic number of distance products of matrices with elements in the range (1, 2, ., M). As a result, we get an algorithm for the APSP problem in such graphs that runs in O~(Mn/sup /spl omega//) time, where n is the number of vertices in the input graph, M is the largest edge weight in the graph, and /spl omega/<2.376 is the exponent of matrix multiplication. This improves, and also simplifies, an O~(M/sup (/spl omega/+1)/2/n/sup /spl omega//) time algorithm of Galil and Margalit (1997).
EVIDENCE FROM THYMIDINE-3H-LABELED MERISTEMS OF VICIA FABA OF TWO CELL POPULATIONS

Treatments with tritiated thymidine (TdR-3H) have revealed the existence of two populations of mitotically active cells in meristems of lateral roots of Vicia faba. A rapidly dividing population, with a cycle time of 14 hr, constitutes about half the cells in the meristem. A second population of cells, with a cycle time in excess of 30 hr, is also present. Estimates of the relative size of this slowly dividing population are more difficult to make, but we calculate that this population includes 27–43% of meristem cells. The remaining fraction of the meristem is made up of cells that divide rarely or not at all. Since, at all times, both populations contribute to the mitotic index, the curve of the percentage of labeled mitoses that can be determined after a pulse label with TdR-3H differs from the curve expected of an ideal population in an important way: the peak value of the curve of the percentage of labeled mitoses is always less than 100%, usually between 75 and 80%. This heterogeneity within a meristem must be borne in mind in terms of the response of meristems to disruptive treatments, the mechanisms controlling mitotic cycle duration, and the spatial organization of a heterogeneous population in an organ that shows polarized growth.
PTK6 Regulates IGF-1-Induced Anchorage-Independent Survival

Background Proteins that are required for anchorage-independent survival of tumor cells represent attractive targets for therapeutic intervention since this property is believed to be critical for survival of tumor cells displaced from their natural niches. Anchorage-independent survival is induced by growth factor receptor hyperactivation in many cell types. We aimed to identify molecules that critically regulate IGF-1-induced anchorage-independent survival. Methods and Results We conducted a high-throughput siRNA screen and identified PTK6 as a critical component of IGF-1 receptor (IGF-1R)-induced anchorage-independent survival of mammary epithelial cells. PTK6 downregulation induces apoptosis of breast and ovarian cancer cells deprived of matrix attachment, whereas its overexpression enhances survival. Reverse-phase protein arrays and subsequent analyses revealed that PTK6 forms a complex with IGF-1R and the adaptor protein IRS-1, and modulates anchorage-independent survival by regulating IGF-1R expression and phosphorylation. PTK6 is highly expressed not only in the previously reported Her2+ breast cancer subtype, but also in high grade ER+, Luminal B tumors and high expression is associated with adverse outcomes. Conclusions These findings highlight PTK6 as a critical regulator of anchorage-independent survival of breast and ovarian tumor cells via modulation of IGF-1 receptor signaling, thus supporting PTK6 as a potential therapeutic target for multiple tumor types. The combined genomic and proteomic approaches in this report provide an effective strategy for identifying oncogenes and their mechanism of action.
Neural Basis of Self and Other Representation in Autism: An fMRI Study of Self-Face Recognition

Background Autism is a developmental disorder characterized by decreased interest and engagement in social interactions and by enhanced self-focus. While previous theoretical approaches to understanding autism have emphasized social impairments and altered interpersonal interactions, there is a recent shift towards understanding the nature of the representation of the self in individuals with autism spectrum disorders (ASD). Still, the neural mechanisms subserving self-representations in ASD are relatively unexplored. Methodology/Principal Findings We used event-related fMRI to investigate brain responsiveness to images of the subjects' own face and to faces of others. Children with ASD and typically developing (TD) children viewed randomly presented digital morphs between their own face and a gender-matched other face, and made “self/other” judgments. Both groups of children activated a right premotor/prefrontal system when identifying images containing a greater percentage of the self face. However, while TD children showed activation of this system during both self- and other-processing, children with ASD only recruited this system while viewing images containing mostly their own face. Conclusions/Significance This functional dissociation between the representation of self versus others points to a potential neural substrate for the characteristic self-focus and decreased social understanding exhibited by these individuals, and suggests that individuals with ASD lack the shared neural representations for self and others that TD children and adults possess and may use to understand others.
Dementia=(MC)2: A 4-item Screening Test for Mild Cognitive Impairment and Dementia

To develop a practical informant-based screening tool that reliably identifies patients with mild cognitive impairment (MCI) and dementia, we analyzed data from a sample of patients and normal controls seen in a memory clinic. All patients were evaluated with the Clinical Dementia Rating scale. Individual Clinical Dementia Rating responses were dichotomized and entered into a forward stepwise multivariable logistic regression model. Four independent predictors of MCI and dementia thus identified were combined into a prediction rule that was validated in a separate cohort drawn from the same clinic. Using a cut point of 2 or more positive responses to the 4 questions, the final prediction rule had sensitivity of 95% (95% confidence interval (CI): 92-97%) for MCI or dementia, and a specificity of 91% (95% CI: 86-95%). When applied to the validation cohort, the sensitivity for MCI or dementia was 96% (95% CI: 94-98%), and the specificity was 96% (95% CI: 92-98%). Using both cohorts, the positive likelihood ratio for MCI or dementia was 15.6 (95% CI: 14.0-17.3) and the negative likelihood ratio was 0.05 (95% CI: 0.04-0.07). This tool has the potential to identify patients who warrant further cognitive evaluation in busy outpatient or emergency department settings.
Hybrid wavelength routed and optical packet switched ring networks for the metropolitan area network

Increased data traffic in the metropolitan area network calls for new network architectures. This paper evaluates optical ring architectures based on optical packet switching, wavelength routing, and hybrid combinations of the two concepts. The evaluation includes overall throughput and fairness aspects in both uniform and unbalanced traffic scenarios, for both Poisson and bursty input traffic. Simulations show a trade-off between performance and complexity. Whilst the static wavelength routed optical network is a good solutions for uniform traffic, the proposed hybrid architectures are more attractive when traffic is unbalanced.
Subplate in a rat model of preterm hypoxia–ischemia

Hypoxia–ischemia (HI) in preterm infants primarily leads to injuries in the cerebral white matter. However, there is growing evidence that perinatal injury in preterms can also involve other zones including the cortical gray matter. In a neonatal rat model of HI, selective vulnerability of subplate has been suggested using BrdU birth‐dating methods. In this study, we aimed to investigate the neuropathological changes of the subplate and deep layers of the cortex following cerebral HI in neonatal rats with specific cell markers.
ℌ∞ Filtering of Lipschitz nonlinear systems with network-induced uncertain delays

In this paper, a filter design scheme is proposed for Lipschitz nonlinear systems with delays. It is assumed that the measurements are transmitted through a communication network and therefore reach the filter with an uncertain delay. The design methodology is formulated as an optimization problem with LMI constraints, which are derived using a less conservative Lyapunov-Krasovskii function and establish an ℌ∞ attenuation level on the effects of the unwanted exogenous inputs on the estimation error. Simulation results are given to illustrate the effectiveness of the proposed filter.
Children, Adolescents, Obesity, and the Media

Obesity has become a worldwide public health problem. Considerable research has shown that the media contribute to the development of child and adolescent obesity, although the exact mechanism remains unclear. Screen time may displace more active pursuits, advertising of junk food and fast food increases children's requests for those particular foods and products, snacking increases while watching TV or movies, and late-night screen time may interfere with getting adequate amounts of sleep, which is a known risk factor for obesity. Sufficient evidence exists to warrant a ban on junk-food or fast-food advertising in children's TV programming. Pediatricians need to ask 2 questions about media use at every well-child or well-adolescent visit: (1) How much screen time is being spent per day? and (2) Is there a TV set or Internet connection in the child's bedroom?
Differential Angular Imaging for Material Recognition

Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation in the wild. Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based representations based on internet-mined images of materials captured in the scene. We propose to take a middle-ground approach for material recognition that takes advantage of both rich radiometric cues and flexible image capture. We realize this by developing a framework for differential angular imaging, where small angular variations in image capture provide an enhanced appearance representation and significant recognition improvement. We build a large-scale material database, Ground Terrain in Outdoor Scenes (GTOS) database, geared towards real use for autonomous agents. The database consists of over 30,000 images covering 40 classes of outdoor ground terrain under varying weather and lighting conditions. We develop a novel approach for material recognition called a Differential Angular Imaging Network (DAIN) to fully leverage this large dataset. With this novel network architecture, we extract characteristics of materials encoded in the angular and spatial gradients of their appearance. Our results show that DAIN achieves recognition performance that surpasses single view or coarsely quantized multiview images. These results demonstrate the effectiveness of differential angular imaging as a means for flexible, in-place material recognition.
Dual-waveband infrared focal plane arrays using MCT grown by MOVPE on silicon substrates (Invited Paper)

Dual-waveband, Focal Plane Arrays (FPAs) based on Hg1-xCdxTe multi-layer structures have previously been produced by the Molecular Beam Epitaxy (MBE) growth technique. It is shown that the multi-layer structures required for dual-waveband devices can also be grown by Metal Organic Vapor Phase Epitaxy (MOVPE). The MOVPE growth process allows excellent control of both the composition and doping profiles and has the advantage of allowing growth on a range of substrates including silicon. Previous research on back-to-back diodes for dual-waveband has concentrated on npn structures. The design of the alternative pnp structures is discussed and a model is developed which gives a good fit to the measured spectra. We report on the design and characterization of dual-waveband detectors including current-voltage and spectral cross talk for the case of two close sub-bands within the 3-5 μm mid-wave infrared (MWIR) spectral range. The mechanisms for spectral cross talk are discussed including incomplete absorption, transistor action and radiative coupling. A custom readout circuit (ROIC) has been designed. This allows the capture of data from the two bands which is spatially aligned but sequential in time.
A Markov model for the evaluation of cache insertion on peer-to-peer performance

Peer-to-peer file sharing applications generate huge volumes of the Internet traffic, thus leading to increased congestion and costs for the ISPs, particularly due to inter-domain traffic. Thus, analysis of peer-to-peer applications and related optimization approaches (such as locality awareness or caching techniques) has been the subject of extensive recent research. In this paper we introduce and analyze a probabilistic model that employs a Markov chain, aiming to approximate the transient evolution of a swarm with a fixed number of peers. This model estimates the distribution of the number of chunks already downloaded by a certain peer at any time. We also show how this model can serve as a tool to analyze certain properties of peer-to-peer applications, such as monotonicity of performance, and primarily to evaluate the effectiveness of cache insertion in a network serving peer-to-peer. For tractability reasons, the model employs certain simplifications of the original BitTorrent protocol, the impact of which is limited as validated experimentally.
Building apps with open data in india: an experience

Open data is a well-established paradigm to make data available freely to everyone. The general belief is that open data leads to rapid pace in problem discovery, empowerment of citizens and greater collaborations. Opening up government data for free public access is a global trend, which India too followed in 2012. Though India is one of the early adopters, it has been ranked low in the last year's Open Data Index. We participated in an open data app contest conducted by Government of India to come up with societal applications based on the datasets provided in data.gov. in portal. We would like to share our experiences and challenges during this contest and compare them with a similar internal contest that we participated in, where datasets were from U.S.
Simple Pedestrian Localization Algorithms Based on Distributed Wireless Sensor Networks

This paper addresses simple algorithms for pedestrian localization based on the measurements from distributed wireless sensor networks (WSNs). It appears to be quite difficult to install a set of hardware sensors onto a human body; thus, traditional navigation sensors such as the inertial measurement unit cannot be employed for human tracking in a practical point of view. Recently, to minimize hardware installation onto the human body, WSNs have been actively investigated. However, there is a critical problem in WSNs associated with the measurement noises and signal disturbances. In this paper, we establish very simple localization algorithms that can reduce the noise effects as well as disturbances without a priori knowledge of them. Through actual experimental tests, the validity of the proposed methods is demonstrated.
R  U  M T Ami  Amida P

The AMI and AMIDA projects are concerned with the recognition and interpretation of multiparty meetings. Within these projects we have: developed an infrastructure for recording meetings using multiple microphones and cameras; released a 100 hour annotated corpus of meetings; developed techniques for the recognition and interpretation of meetings based primarily on speech recognition and computer vision; and developed an evaluation framework at both component and system levels. In this paper we present an overview of these projects, with an emphasis on speech recognition and content extraction.
Structured online interactions: improving the decision-making of small discussion groups

A quantitative research experiment was used to examine whether a group's computer-mediated decision-making could be improved by providing a scripted structure to the groups text chat discussion. The study compared a regular chat discussion to a scripted chat discussion using Lead Line, a program that allows people to add a layer of pre-authored structure to regular text chat. We found that groups were more likely to come to consensus in structured chat discussions. In addition, groups applied the structure they learned to subsequent regular chat sessions.
Information retrieval in big data using evolutionary computation: A survey

The basic aim of this paper is to present a broad picture of Big Data and to show how information can be retrieved using different methodologies and especially using evolutionary computation techniques that help in the information retrieval process in a better way compared to traditional retrieval techniques. Big data is considered as a collection of large data which are heterogeneous in nature and cannot be handled by traditional computing techniques and require more advanced statistical procedures to extract relevant information from a voluminous pool of data. This paper also covers some of the basic information retrieval models which are used and present a basic outline of evolutionary computation techniques.
Interactive visual analysis of large simulation ensembles

Recent advancements in simulation and computing make it possible to compute large simulation ensembles. A simulation ensemble consists of multiple simulation runs of the same model with different values of control parameters. In order to cope with ensemble data, a modern analysis methodology is necessary. In this paper, we present our experience with simulation ensemble exploration and steering by means of interactive visual analysis. We describe our long-term collaboration with fuel injection experts from the automotive industry. We present how interactive visual analysis can be used to gain a deep understanding in the ensemble data, and how it can be used, in a combination with automatic methods, to steer the ensemble creation, even for very complex systems. Very positive feedback from domain experts motivated us, a team of visualization and simulation experts, to present this research to the simulation community.
Techniques and modifications for TMJ arthrocentesis: A literature review

Abstract Objectives: To discuss advantages and disadvantages of TMJ arthrocentesis techniques, identifying modifications as reported in the literature. Methods: A PubMed web-based search was carried out, using the terms TMJ and arthrocentesis, to determine the scope of coverage in well-documented articles in English. Results: Among 237 articles, 12 distinct techniques were described for TMJ arthrocentesis in 12 articles. Among 12 techniques, 5 were classified as double puncture arthrocentesis (DPA) and 7 as single puncture arthrocentesis (SPA). In total, 17 well documented articles about SPA were found in literature. Discussion: Arthrocentesis of the temporomandibular joint (TMJ) was first described in 1991. To make the traditional procedure even less invasive, many arthrocentesis methods have been described. However, in 2015, TMJ arthrocentesis techniques were divided into two groups to limit the complexities surrounding the concepts related to TMJ arthrocentesis techniques.
Estimating the Orientation and Recovery of Text Planes in a Single Image

A method for the fronto-parallel recovery of paragraphs of text under full perspective transformation is presented. The horizontal vanishing point of the text plane is found using an extension of 2D projection profiles. This allows the accurate segmentation of the lines of text. Analysis of the lines will then reveal the style of justification of the paragraph, and provide an estimate of the vertical vanishing point of the plane. The text is finally recovered to a fronto-parallel view suitable for OCR or other higher-level recognition.
Reliability of pharmacokinetic parameters: Small vs. medium‐sized contrast agents

Current clinical applications of dynamic contrast‐enhanced MRI (DCE‐MRI) are based on the extravasation of relatively small contrast agents (SCAs). SCAs are considered disadvantageous, as they require high image sampling rates. Medium‐sized contrast agents (MCAs) leak more slowly into tissue and allow longer dynamic acquisition times, enabling improved image quality. The influence of molecular size on the reliability of pharmacokinetic parameters, including the transfer constant Ktrans, was investigated. Computer simulations were performed, with in vivo measured arterial input functions (AIFs), to determine the bias and variance of pharmacokinetic parameters as a function of contrast agent size, sampling frequency, noise level, and acquisition time. Better reliability of all parameters was obtained for the MCA compared to the SCA. To obtain similar variance (10%) in Ktrans, the sampling frequency for the SCA (28 min−1) had to be 20 times faster than for the MCA (1.3 min−1). Optimal reliability in parameter estimation required longer acquisition times for MCAs (13 min for the fraction of the extravascular extracellular space into which the contrast agent distributes (ve) and 5 min for Ktrans) than for SCAs (1.7 min for Ktrans and ve). Reliable estimation of the fractional blood plasma volume (vp) was only achieved with MCAs. In conclusion, MCAs provided superior reliability for pharmacokinetic parameter estimation compared to SCAs. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Modeling Stereopsis via Markov Random Field

Markov random field (MRF) and belief propagation have given birth to stereo vision algorithms with top performance. This article explores their biological plausibility. First, an MRF model guided by physiological and psychophysical facts was designed. Typically an MRF-based stereo vision algorithm employs a likelihood function that reflects the local similarity of two regions and a potential function that models the continuity constraint. In our model, the likelihood function is constructed on the basis of the disparity energy model because complex cells are considered as front-end disparity encoders in the visual pathway. Our likelihood function is also relevant to several psychological findings. The potential function in our model is constrained by the psychological finding that the strength of the cooperative interaction minimizing relative disparity decreases as the separation between stimuli increases. Our model is tested on three kinds of stereo images. In simulations on images with repetitive patterns, we demonstrate that our model could account for the human depth percepts that were previously explained by the second-order mechanism. In simulations on random dot stereograms and natural scene images, we demonstrate that false matches introduced by the disparity energy model can be reliably removed using our model. A comparison with the coarse-to-fine model shows that our model is able to compute the absolute disparity of small objects with larger relative disparity. We also relate our model to several physiological findings. The hypothesized neurons of the model are selective for absolute disparity and have facilitative extra receptive field. There are plenty of such neurons in the visual cortex. In conclusion, we think that stereopsis can be implemented by neural networks resembling MRF.