Miracle-dz/UniFAR-FTUs huggingface dataset:
Adult equine bone-marrow stromal cells produce a cartilage-like ECM superior to animal-matched adult chondrocytes

Our objective was to evaluate the age-dependent mechanical phenotype of bone marrow stromal cell(BMSC-) and chondrocyte-produced cartilage-like neotissue and to elucidate the matrix-associated mechanisms which generate this phenotype. Cells from both immature (2-4 month-old foals) and skeletally-mature (2-5 year-old adults) mixed-breed horses were isolated from animal-matched bone marrow and cartilage tissue, encapsulated in self-assembling-peptide hydrogels, and cultured with and without TGF-β1 supplementation. BMSCs and chondrocytes from both donor ages were encapsulated with high viability. BMSCs from both ages produced neo-tissue with higher mechanical stiffness than that produced by either young or adult chondrocytes. Young, but not adult, chondrocytes proliferated in response to TGF-β1 while BMSCs from both age groups proliferated with TGF-β1. Young chondrocytes stimulated by TGF-β1 accumulated ECM with 10-fold higher sulfated-glycosaminoglycan content than adult chondrocytes and 2-3-fold higher than BMSCs of either age. The opposite trend was observed for hydroxyproline content, with BMSCs accumulating 2-3-fold more than chondrocytes, independent of age. Size-exclusion chromatography of extracted proteoglycans showed that an aggrecan-like peak was the predominant sulfated proteoglycan for all cell types. Direct measurement of aggrecan core protein length and chondroitin sulfate chain length by single molecule atomic force microscopy imaging revealed that, independent of age, BMSCs produced longer core protein and longer chondroitin sulfate chains, and fewer short core protein molecules than chondrocytes, suggesting that the BMSC-produced aggrecan has a phenotype more © 2009 Elsevier B.V. All rights reserved. Corresponding author: Alan J. Grodzinsky Department of Biological Engineering and MIT Center for Biomedical Engineering Massachusetts Institute of Technology 77 Massachusetts Ave, Rm. NE47-377 Cambridge, MA 02139 phone: 617-253-4969 fax: 617-258-5239 alg@mit.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author Manuscript Matrix Biol. Author manuscript; available in PMC 2011 June 1. Published in final edited form as: Matrix Biol. 2010 June ; 29(5): 427–438. doi:10.1016/j.matbio. 2010.02. 003. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript characteristic of young tissue than chondrocyte-produced aggrecan. Aggrecan ultrastructure, ECM composition, and cellular proliferation combine to suggest a mechanism by which BMSCs produce a superior cartilage-like neotissue than either young or adult chondrocytes.
Peer-to-Peer in Metric Space and Semantic Space

This paper first proposes three improved gossip mechanisms by mapping links into metric space and dynamically adapting the number of selected neighbors to disseminate messages. Experiments and comparisons show that these mechanisms can improve the performance of gossip in peer-to-peer (P2P) networks. This is the effect of mapping a network into a metric space that differentiates nodes and links according to linking characteristics and controlling local information flow with knowing such differences. A further study about query routing on P2P semantic link network shows that mapping a network into a semantic space can also improve the performance. An intrinsic rule is found by experimental comparisons and analysis: the performance of a P2P network can be improved by designing an appropriate mapping from the network into metric space or semantic space. A general framework for networking with metric space and semantic space is suggested
GOPred: GO Molecular Function Prediction by Combined Classifiers

Functional protein annotation is an important matter for in vivo and in silico biology. Several computational methods have been proposed that make use of a wide range of features such as motifs, domains, homology, structure and physicochemical properties. There is no single method that performs best in all functional classification problems because information obtained using any of these features depends on the function to be assigned to the protein. In this study, we portray a novel approach that combines different methods to better represent protein function. First, we formulated the function annotation problem as a classification problem defined on 300 different Gene Ontology (GO) terms from molecular function aspect. We presented a method to form positive and negative training examples while taking into account the directed acyclic graph (DAG) structure and evidence codes of GO. We applied three different methods and their combinations. Results show that combining different methods improves prediction accuracy in most cases. The proposed method, GOPred, is available as an online computational annotation tool (http://kinaz.fen.bilkent.edu.tr/gopred).
Recovering Camera Pose from Omni-directional Images

Omni-directional images are widely used in image-based walkthrough applications, in which camera pose recovery is one of the initial and important processes. Existing methods may recover camera pose of omnidirectional images from lines. However, it may not work well when there is insufficient scene structure in the images. In addition, existing methods involve non-linear optimization and iterative algorithms, which may lead to the convergence problem and high computational cost. In this paper, we propose an automatic camera pose recovery method for a network of omni-directional images. Our method only requires 2D point correspondences as input. We divide the problem into the orientation and position components, and determine them separately. The relative rotations between adjacent views are aggregated to estimate the global orientations. An algorithm is developed to adjust the rotations for avoiding global inconsistency and error accumulation. For position recovery, we have derived a linear global formulation for establishing correspondences and positions among multiple views. Globally optimized positions can be obtained simply by solving the formulation. We demonstrate the performance of our method with some experiments.
Communication Theory Analysis of the effects of Nyquist pulse-shaping on the performance of OFDM systems with carrier frequency offset

An exact method for calculating the bit error rate (BER) of an uncoded orthogonal frequency-division multiplexing (OFDM) system with transmitter Nyquist pulse-shaping over AWGN channels in the presence of frequency offset is derived. This method represents a unified way to calculate the BER of this system with different one- and two-dimensional subcarrier modulation formats. The precise BER expressions are obtained using a characteristic function method. The effects of several widely referenced Nyquist pulse-shapings, including the Franks pulse, the raised-cosine pulse, the ‘better than’ raised-cosine (BTRC) pulse, the second-order continuous window (SOCW), the double-jump pulse and the polynomial pulse on intercarrier interference (ICI) reduction and BER improvement of the system with carrier frequency offset are examined in the AWGN channel. The dependence of the BER on the roll-off factor of the pulse employed for a specific system in the presence of frequency offset is investigated. Analysis and numerical results show that the Franks pulse exhibits the best performance among the Nyquist pulses considered in most cases. Copyright © 2008 John Wiley & Sons, Ltd.
Genetic Algorithms for Optimization in Electromagnetics I. Fundamentals

Niching methods extend genetic algorithms and permit the investigation of multiple optimal solutions in the search space. In this paper, we review and discuss various strategies of niching for optimization in electromagnetics. Traditional mathematical problems and an electromagnetic benchmark are solved using niching genetic algorithms to show their interest in real world optimization. Index terms-Genetic algorithms, niching methods, sharing, crowding, clearing, shape optimization, magnetizer.
Network-aware placement of virtual machine ensembles using effective bandwidth estimation

Modern datacenters rely heavily on virtualization technologies to offer customized computing and network resources on demand to a large number of tenant applications. However, efficiency in resource utilization delivered by virtualization technologies that exploit statistical multiplexing of resources across applications means that predictability in performance remains a challenge. Allocation of network bandwidth is particularly difficult, given the variability of traffic flows between the components of multi-tier applications. Static bandwidth allocation based on peak traffic rates ensures SLA compliance at the cost of significant overprovisioning, while allocation based on mean traffic rates ensures efficient usage of bandwidth at the cost of QoS violations. We describe MAPLE, a network-aware VM ensemble placement scheme that uses empirical estimations of the effective bandwidth required between servers to ensure that QoS violations are within targets specified in the SLA for the tenant application. Experimental results obtained using traffic traces collected from an emulated datacenter show that, in contrast to the Oktopus network-aware VM placement system, MAPLE is able to allocate computing and network resources in a manner that balances efficiency of resource utilization with performance predictability.
Preparing Preservice Elementary Teachers to Teach Science through Computer Models.

The purpose of this study was to examine the extent to which preservice elementary teachers were able to construct viable scientific models with a computer-modeling tool, namely Model-It, and design a science lesson with models. The results of the study showed that (a) Model-It, through its scaffolds (i.e., Plan, Build, and Test modes), enabled the majority of preservice teachers to build models that were structurally correct, (b) participants’ models were structurally correct but simplistic, and (c) 65% of the participants preferred to teach science using the explorative modeling method, 27% the expressive method, and only 8% both the explorative and the expressive methods. In essence, Model-It effectively scaffolded preservice teachers’ first modeling experiences and enabled them to quickly build and test their models. It is, however, recognized that systematic efforts need to be undertaken in teacher education departments to adequately prepare prospective teachers to teach science through computer models.
The nite connectivity of linguistic structure

While there is no interesting limitation on the degree of right-embedding in acceptable sentences, center-embedding is quite severely restricted. Similarly, while there is no interesting bound on the number of nouns that can occur in acceptable noun compounds, there is a very low bound on the number of causative morphemes that can occur in the verb compounds of agglutinative languages. Turning to the clausenal verb clusters of West Germanic languages, we nd another similar bound. A cluster including verbs from one embedded clause may be acceptable, but clusters formed from the verbs of two or three or even more deeply embedded clauses are much more awkward (regardless of whether the subject-verb dependencies are crossing or nested). And in languages that allow multiple wh-extractions from a single clause, extractions of more than one element with a given case quickly become unacceptable. More careful experimental study of the nature of these limitations is needed, in a range of languages, but here a preliminary attempt is made to subsume them all under a single generalization, a version of the familar idea that the human parsing mechanism is limited in its ability to keep track of many grammatical relations of the same kind. To make this idea more precise, we assume in the rst place,
Reinforcement and inference in cross-situational word learning

Cross-situational word learning is based on the notion that a learner can determine the referent of a word by finding something in common across many observed uses of that word. Here we propose an adaptive learning algorithm that contains a parameter that controls the strength of the reinforcement applied to associations between concurrent words and referents, and a parameter that regulates inference, which includes built-in biases, such as mutual exclusivity, and information of past learning events. By adjusting these parameters so that the model predictions agree with data from representative experiments on cross-situational word learning, we were able to explain the learning strategies adopted by the participants of those experiments in terms of a trade-off between reinforcement and inference. These strategies can vary wildly depending on the conditions of the experiments. For instance, for fast mapping experiments (i.e., the correct referent could, in principle, be inferred in a single observation) inference is prevalent, whereas for segregated contextual diversity experiments (i.e., the referents are separated in groups and are exhibited with members of their groups only) reinforcement is predominant. Other experiments are explained with more balanced doses of reinforcement and inference.
Performance Improvement of Iterative Multiuser Detection for Large Sparsely Spread CDMA Systems by Spatial Coupling

Kudekar et al. proved that the belief-propagation (BP) performance for low-density parity check codes can be boosted up to the maximum a posteriori (MAP) performance by spatial coupling. In this paper, spatial coupling is applied to sparsely spread code-division multiple-access systems to improve the performance of iterative multiuser detection based on BP. Two iterative receivers based on BP are considered: 1) one receiver is based on exact BP and 2) the other on an approximate BP with Gaussian approximation. The performance of the two BP receivers is evaluated via density evolution (DE) in the dense limit after taking the large-system limit, in which the number of users and the spreading factor tend to infinity while their ratio is kept constant. The two BP receivers are shown to achieve the same performance as each other in these limits. Furthermore, taking a continuum limit for the obtained DE equations implies that the performance of the two BP receivers can be improved up to the performance achieved by the symbol-wise MAP detection, called individually optimal detection, via spatial coupling. Numerical simulations show that spatial coupling can provide a significant improvement in bit-error rate for finite-sized systems especially in the region of high system loads.
Knowledge-Based Question Answering

This paper describes the Webclopedia Question Answering system, in which methods to automatically learn patterns and parameterizations are combined with hand-crafted rules and concept ontologies. The source for answers is a collection of 1 million newspaper texts, distributed by NIST. In general, two kinds of knowledge are used by Webclopedia to answer questions: knowledge about language and knowledge about the world. The former is embodied both in the Information Retrieval engine that identifies likely answer sentences and the CONTEX parser that analyses the input question and candidate answers. The latter is embodied in a QA typology of some 140 nodes, a concept ontology of some 10,000 concepts, and the IR engine’s ranking algorithm that takes typical document structure into account.
Okapi at TREC{7: automatic ad hoc, ltering, VLC and interactive track

Three runs were submitted: medium (title and description), short (title only) and a run which was a combination of a long run (title, description and narrative) with the medium and short runs. The average precision of the last mentioned run was higher by several percent than any other submitted run, but another participant recently noticed an impossibly high score for one topic in the short run. This led to the discovery that due to a mistake in the indexing procedures part of the SUBJECT eld of the LA Times documents had been indexed. Use of this eld was explicitly forbidden in the guidelines [1] for the ad hoc track. The o cial runs were repeated against a corrected index, and the corrected results are reported below, average precisions being reduced by about 2{4%.
Noise Level Estimation for Natural Images Based on Scale-Invariant Kurtosis and Piecewise Stationarity

Noise level estimation is crucial in many image processing applications, such as blind image denoising. In this paper, we propose a novel noise level estimation approach for natural images by jointly exploiting the piecewise stationarity and a regular property of the kurtosis in bandpass domains. We design a $K$ -means-based algorithm to adaptively partition an image into a series of non-overlapping regions, each of whose clean versions is assumed to be associated with a constant, but unknown kurtosis throughout scales. The noise level estimation is then cast into a problem to optimally fit this new kurtosis model. In addition, we develop a rectification scheme to further reduce the estimation bias through noise injection mechanism. Extensive experimental results show that our method can reliably estimate the noise level for a variety of noise types, and outperforms some state-of-the-art techniques, especially for non-Gaussian noises.
Experimental simulation of model platelet adhesion to a semi-permeable wall exposed to flow disturbance

A sudden tubular expansion with a semi-permeable wall was constructed from a tubular dialysis membrane to investigate the effects of filtration flow and flow disturbance on particle deposition. The expansion was perfused with a dilute, neutrally buoyant suspension of 1.10 ώm diameter polystyrene latex spheres (as models of platelets) in Tris buffer solution containing 10% Dextran T70 and 2% bovine serum albumin. The results showed that adhesion of particles correlated positively with the filtration rate and inversely with the wall shear rate. In the vortex flow region distal to the expansion, particle adhesion was significantly elevated with a maximum at the reattachment point where the wall shear rate was the lowest and particles were constantly carried toward the vessel wall along the curved streamlines. In conclusion, filtration flow has a profound impact on the interaction of blood cells such as platelets with blood vessel walls, and the disturbed flow with a low wall shear rate can enhance the deposits of platelet thrombi to the vessel wall.
User Assistance for Effective Data Mining

Today, several tools are available for solving data mining problems, both in open source and commercial category. For solving classification problems these tools provide variety of strategies such as decision tree, neural networks, lazy classifiers etc. For each strategy, the tools allow the user to select specific values for large number parameters [1] for e.g. in case of a neural network classifier, user needs to provide values for parameters such as epochs, learning rate, momentum etc . Although default setting for such parameters is provided by tools, it is often found that the classifier performance (accuracy) may be enhanced by making series of experiments with different values for these parameters. Thus, for a novice user it is difficult to guess proper values for these parameters and the only option is to try with series of experiments which is time consuming. This paper aims at developing a database to record the nature of data such as number and type of attributes, presence or absence of missing values etc along with various values for building classifier models and the accuracy of the classifier. Such a data is then can be made available to novice users to build a model based on past experience. The work also aims at developing required forms reports
Particle filters for positioning, navigation, and tracking

A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is developed. It consists of a class of motion models and a general nonlinear measurement equation in position. A general algorithm is presented, which is parsimonious with the particle dimension. It is based on marginalization, enabling a Kalman filter to estimate all position derivatives, and the particle filter becomes low dimensional. This is of utmost importance for high-performance real-time applications. Automotive and airborne applications illustrate numerically the advantage over classical Kalman filter-based algorithms. Here, the use of nonlinear models and non-Gaussian noise is the main explanation for the improvement in accuracy. More specifically, we describe how the technique of map matching is used to match an aircraft's elevation profile to a digital elevation map and a car's horizontal driven path to a street map. In both cases, real-time implementations are available, and tests have shown that the accuracy in both cases is comparable with satellite navigation (as GPS) but with higher integrity. Based on simulations, we also argue how the particle filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne hunting and collision avoidance systems in cars.
A comprehensive strategy for contention management in software transactional memory

In Software Transactional Memory (STM), contention management refers to the mechanisms used to ensure forward progress--to avoid livelock and starvation, and to promote throughput and fairness. Unfortunately, most past approaches to contention management were designed for obstruction-free STM frameworks, and impose significant constant-time overheads. Priority-based approaches in particular typically require that reads be visible to all transactions, an expensive property that is not easy to support in most STM systems. In this paper we present a comprehensive strategy for contention management via fair resolution of conflicts in an STM with invisible reads. Our strategy depends on (1) lazy acquisition of ownership, (2) extendable timestamps, and (3) an efficient way to capture both priority and conflicts. We introduce two mechanisms--one using Bloom filters, the other using visible read bits--that implement point (3). These mechanisms unify the notions of conflict resolution, inevitability, and transaction retry. They are orthogonal to the rest of the contention management strategy, and could be used in a wide variety of hardware and software TM systems. Experimental evaluation demonstrates that the overhead of the mechanisms is low, particularly when conflicts are rare, and that our strategy as a whole provides good throughput and fairness, including livelock and starvation freedom, even for challenging workloads.