Miracle-dz/UniFAR-FTUs huggingface dataset:
Varieties with few subalgebras of powers

The Constraint Satisfaction Problem Dichotomy Conjecture of Feder and Vardi (1999) has in the last 10 years been profitably reformulated as a conjecture about the set SP fin (A) of subalgebras of finite Cartesian powers of a finite universal algebra A. One particular strategy, advanced by Dalmau in his doctoral thesis (2000), has confirmed the conjecture for a certain class of finite algebras A which, among other things, have the property that the number of subalgebras of A n is bounded by an exponential polynomial. In this paper we characterize the finite algebras A with this property, which we call having few subpowers, and develop a representation theory for the subpowers of algebras having few subpowers. Our characterization shows that algebras having few subpowers are the finite members of a newly discovered and surprisingly robust Maltsev class defined by the existence of a special term we call an edge term. We also prove some tight connections between the asymptotic behavior of the number of subalgebras of A n and some related functions on the one hand, and some standard algebraic properties of A on the other hand. The theory developed here was applied to the Constraint Satisfaction Problem Dichotomy Conjecture, completing Dalmau's strategy.
Resource allocation for data-parallel computing in networks with data locality

This paper studies resource allocation for data-parallel applications in a networked computing system with data locality. Data-parallel computing tasks have two components: data and computation. To support efficient data-processing in the system, the resource allocation algorithm should jointly consider load-balancing, data transmissions and processing scheduling. In this paper, we consider a general model of a computing system where the computing system is a network represented by a graph, with nodes being computing devices or switches and edges being communication links. The data chunks stored at the nodes can be processed locally or be transmitted to other computing nodes in the network to be processed. The throughput of such a system for processing data-parallel applications is determined jointly by the computing capacity of the nodes and the communication capacity of the network, and the resource allocation algorithm should strike a right balance between computing and communication. In this paper, we propose a throughput-optimal resource allocation algorithm, which is also able to control the tradeoff between the expected amount of data transmitted and the expected number of backlogged tasks in steady state through a parameter qth. We show that the gap between the expected data transmission rate under our algorithm and the optimal value is O(1/qth), while the expected number of total backlogged tasks is upper bounded by O(qth).
An efficient scheduling algorithm for downlink multi-antenna CDMA systems

We design efficient scheduling algorithms for multiantenna CDMA downlink systems using zero forcing beamforming. Our proposition maximizes the system sum rate and keeps the computational complexity low. We make use of a graph theoretical approach to represent the system as an undirected weighted graph. As a second step, we formulate the scheduling problem as the maximum weight k-colorable subgraph problem. We propose two heuristic solutions to find the users to serve in each time slot in an acceptable polynomial time. Finally we evaluate the efficiency of the proposed schemes by mean of simulations and the results shows the near-optimal performance of the proposed schedulers with very low computational complexity compared to the optimal exhaustive search over all the possible users combinations. Assuming the use of non-orthogonal spreading codes, our proposed algorithms are shown to still have near-optimal performance even in the case of high values of the orthogonality factor.
Methods for comparing and constraining models of dendritic spines

Physiological evidence using Infrared Video Microscopy during the uncaging of glutamate has proven the existence of excitable calcium ion channels in spine heads, highlighting the need for reliable models of spines. In this study we compare the three main methods of simulating excitable spines: Baer & Rinzel's Continuum (B&R) model, Coombes' Spike-Diffuse-Spike (SDS) model and paired cable and ion channel equations (Cable model). Tests are done to determine how well the models approximate each other in terms of speed and heights of travelling waves. Significant quantitative differences are found between the models: travelling waves in the SDS model in particular are found to travel at much lower speeds and sometimes much higher voltages than in the Cable or B&R models. Meanwhile qualitative differences are found between the B&R and SDS models over realistic parameter ranges. The cause of these differences is investigated and potential solutions proposed.
Interleukin 4, but not interleukin 5 or eosinophils, is required in a murine model of acute airway hyperreactivity [published erratum appears in J Exp Med 1997 May 5;185(9):1715]

Reversible airway hyperreactivity underlies the pathophysiology of asthma, yet the precise mediators of the response remain unclear. Human studies have correlated aberrant activation of T helper (Th) 2-like effector systems in the airways with disease. A murine model of airway hyperreactivity in response to acetylcholine was established using mice immunized with ovalbumin and challenged with aerosolized antigen. No airway hyperractivity occurred in severe combined immunodeficient mice. Identically immunized BALB/c mice developed an influx of cells, with a predominance of eosinophils and CD4+ T cells, into the lungs and bronchoalveolar lavage fluid at the time that substantial changes in airway pressure and resistance were quantitated. Challenged animals developed marked increases in Th2 cytokine production, eosinophil influx, and serum immunoglobulin E levels. Neutralization of interleukin (IL) 4 using monoclonal antibodies administered during the period of systemic immunization abrogated airway hyperractivity but had little effect on the influx of eosinophils. Administration of anti-IL-4 only during the period of the aerosol challenge did not affect the subsequent response to acetylcholine. Finally, administration of anti- IL-5 antibodies at levels that suppressed eosinophils to < 1% of recruited cells had no effect on the subsequent airway responses. BALB/c mice had significantly greater airway responses than C57BL/6 mice, consistent with enhanced IL-4 responses to antigen in BALB/c mice. Taken together, these data implicate IL-4 generated during the period of lymphocyte priming with antigen in establishing the cascade of responses required to generate airway hyperractivity to inhaled antigen. No role for IL-5 or eosinophils could be demonstrated.
Sparse Group Restricted Boltzmann Machines

Since learning in Boltzmann machines is typically quite slow, there is a need to restrict connections within hidden layers. However, theresulting states of hidden units exhibit statistical dependencies. Based on this observation, we propose using l1/l2 regularization upon the activation probabilities of hidden units in restricted Boltzmann machines to capture the local dependencies among hidden units. This regularization not only encourages hidden units of many groups to be inactive given observed data but also makes hidden units within a group compete with each other for modeling observed data. Thus, the l1/l2 regularization on RBMs yields sparsity at both the group and the hidden unit levels. We call RBMs trained with the regularizer sparse group RBMs (SGRBMs). The proposed SGRBMs are appliedto model patches of natural images, handwritten digits and OCR English letters. Then to emphasize that SGRBMs can learn more discriminative features we applied SGRBMs to pretrain deep networks for classification tasks. Furthermore, we illustrate the regularizer can also be applied to deep Boltzmann machines, which lead to sparse group deep Boltzmann machines. When adapted to the MNIST data set, a two-layer sparse group Boltzmann machine achieves an error rate of 0.84%, which is, to our knowledge, the best published result on the permutation-invariant version of the MNIST task.
Deterministic initialization of metric state estimation filters for loosely-coupled monocular vision-inertial systems

In this work, we present a novel, deterministic closed-form solution for computing the scale factor and the gravity direction of a moving, loosely-coupled, and monocular vision-inertial system. The methodology is based on analysing delta-velocities. On one hand, they are obtained from a differentiation of the up-to-scale camera pose computation by a visual odometry or visual SLAM algorithm. On the other hand, they can also be retrieved from the gravity-affected short-term integration of acceleration signals. We derive a method for separating the gravity contribution and recovering the metric scale factor of the vision algorithm. The method thus also recovers the offset in roll and pitch angles of the vision reference frame with respect to the direction of the gravity vector. It uses only a single inertial integration period, and no absolute orientation information is required. For optimal sensor-fusion and metric scale-estimation filters in the loosely-coupled case, it has been shown that the convergence of the fusion of an up-to-scale pose information with inertial measurements largely depends on the availability of a good initial value for the scale factor. We show how this problem can be tackled by applying the method presented in this paper. Finally, we present results in simulation and on real data, demonstrating the suitability of the method in real scenarios.
Value Directed Exploration in Multi-Armed Bandits with Structured Priors

Multi-armed bandits are a quintessential machine learning problem requiring the balancing of exploration and exploitation. While there has been progress in developing algorithms with strong theoretical guarantees, there has been less focus on practical near-optimal finite-time performance. In this paper, we propose an algorithm for Bayesian multi-armed bandits that utilizes value-function-driven online planning techniques. Building on previous work on UCB and Gittins index, we introduce linearly-separable value functions that take both the expected return and the benefit of exploration into consideration to perform n-step lookahead. The algorithm enjoys a sub-linear performance guarantee and we present simulation results that confirm its strength in problems with structured priors. The simplicity and generality of our approach makes it a strong candidate for analyzing more complex multi-armed bandit problems.
A more efficient classification scheme for ID3

Analyzed the principles and implementation steps of ID3 and the existing two improved ID3 algorithms proposed in [4] and [5]. ID3 has the shortcoming of inclining to choose attributes which have many values. Although the current two improved classification algorithms have solved the shortcoming of ID3, their classification time is not enough short, and their classification accuracy is not enough high. We proposed a new scheme. Our scheme solved the shortcoming of ID3 and improved the existing two algorithms effectively. Finally we use experiment to prove that the new scheme has shorter classification time and higher classification accuracy than ID3 and the existing two classification algorithms.
Improving the precision of automatically constructed human-oriented translation dictionaries

In this paper we address the problem of automatic acquisition of a human-oriented translation dictionary from a large-scale parallel corpus. The initial translation equivalents can be extracted with the help of the techniques and tools developed for the phrase-table construction in statistical machine translation. The acquired translation equivalents usually provide good lexicon coverage, but they also contain a large amount of noise. We propose a supervised learning algorithm for the detection of noisy translations, which takes into account the context and syntax features, averaged over the sentences in which a given phrase pair occurred. Across nine European language pairs the number of serious translation errors is reduced by 43.2%, compared to a baseline which uses only phrase-level statistics.
The Benefits and Costs of Managerial Earnings Forecasts in Mergers and Acquisitions

In this study we provide evidence on the benefits and costs of voluntary earnings forecasts by bidding firms during acquisitions, shedding light on the motives and capital market consequences of these voluntary disclosures. Specifically, we find a higher propensity of forecast disclosure when the acquisition is made with stock and the bidder's stock is highly valued. We document that merger forecasts are significantly positively biased (inflated) and that these forecasts are associated with a higher likelihood of deal completion, expedited deal closing, and with a lower acquisition premium. Forecast disclosure also attenuates the generally negative investor reaction to acquisition announcements with stock. The evidence suggests that the benefits of forecast disclosure only accrue to bidders that have built a good forecasting reputation prior to the acquisition. Explaining why not all bidders forecast, we provide evidence on high forecasting costs, particularly higher likelihood of post-merger litigation and CEO turnover for forecasting firms.
Efficacy and safety of non-pharmacological and non-biological pharmacological treatment: a systematic literature review informing the 2016 update of the ASAS/EULAR recommendations for the management of axial spondyloarthritis

To assess the efficacy and safety of non-biological therapies in patients with axial spondyloarthritis (axSpA) to inform the update of the Assessment of SpondyloArthritis international Society (ASAS)/European League Against Rheumatism (EULAR) recommendations for the management of axSpA. A systematic literature review (2009–2016) of all non-pharmacological treatments, non-biological drugs (except targeted synthetic disease-modifying antirheumatic drugs (DMARDs)) and surgical therapies was performed. Randomised controlled trials (RCTs) and clinical controlled trials were assessed for efficacy and safety, while observational studies with a comparator were assessed for safety. All relevant efficacy and safety outcomes were included. Study heterogeneity precluded data pooling. If possible, Cohen's effect size was calculated for non-pharmacological treatments. In total, 45 papers and 2 abstracts were included. Studies on non-pharmacological treatments were very heterogeneous but overall confirmed a benefit for regular exercises, with small improvements in disease activity, function and spinal mobility. New studies on non-steroidal anti-inflammatory drugs (NSAIDs) confirmed their efficacy and new safety signals were not found. NSAIDs used continuously compared with on-demand did not reduce the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) mean change over 2 years in patients with ankylosing spondylitis with normal C reactive protein (CRP; ≤5 mg/L) (1 ‘negative’ RCT (0.9 vs 0.8; p=0.62)), while for patients with high CRP, conflicting results were found (1 ‘positive’ RCT (0.2 vs 1.7; p=0.003), 1 ‘negative’ RCT (1.68 vs 0.96; p=0.28)). No new trials were found for conventional synthetic DMARDs (csDMARDs). Short-term high-dose systemic glucocorticoids showed limited efficacy. Regular exercises may improve several outcomes. Efficacy and safety of NSAIDs in axSpA are confirmed. Glucocorticoids are not proven to be effective in axSpA and new data on csDMARDs are lacking.
An Effective Batching Scheme Combining Static Multicasting with Dynamic Multicasting for Mobile IPTV

Recently, the demand on IPTV services has been greatly increasing. For effectively supporting IPTV services via wireless network of limited resource, various techniques have been developed. In this paper, in order to efficiently provide the VoD(Video on Demand) service to a large number of users of wireless IPTV, we propose a scheme improving the existing batching scheme. The proposed scheme properly utilizes the relationship between the transmission time, decoding time, and playing time of the video segments. It applies dynamic multicasting during the interval of successive transmissions of the segments, and needs to store only a small number of segments in the mobile node for continuous playback. As a result, the proposed approach improves the channel utilization and decreases the number of segments transmitted. Simulation shows that the proposed approach allows seamless service with a smaller number of channels and buffer size than the existing batching scheme.
Simple distributed fiber sensor based on Brillouin gain spectrum analysis.

A novel configuration of a distributed fiber sensor by Brillouin gain analysis has been developed for temperature and strain monitoring. It uses a single laser source, and the required light signals are all generated with an electro-optic modulator, resulting in high stability and excellent reliability of the measuring setup. Measurement of the induced strain in a wound fiber is presented as a demonstration of the system performance.
WWOF: An Energy Efficient Offloading Framework for Mobile Webpage

Currently, the smart-phone has become a significant part for many people. As the major role in providing excellent surfing experiences for users, web browser can not only serve web sites visiting, but also support mobile web applications in smart-phones. In the meantime, in order to attract users, mobile web applications provide more and more diverse choices, which, however, results in the increase of CPU usage, time and energy consumption. Hence, how to improve efficiency of these applications without affecting user experiences has became a significant project. One of the solutions is to migrate the heavy computing tasks of mobile web applications from browser to cloud, which is called Offloading. This paper presents the design and implementation of a generic framework to realize the offloading from local browsers to cloud--Web Worker Offloading Framework (WWOF). The designed framework is easy to apply and is fully compatible with HTML5 API. On client side, the native Web Worker API is replaced by a library to offload seamlessly. On cloud side, corresponding interfaces are implemented to run workers on the server. To prove the effect of WWOF, evaluation of several benchmarks has been made, which shows 85% energy saving and 2-4 times execution speed-up on average for some mobile web applications.
Alternative exon usage creates novel transcript variants of tumor suppressor SHREW-1 gene with differential tissue expression profile

ABSTRACT Shrew-1, also called AJAP1, is a transmembrane protein associated with E-cadherin-mediated adherence junctions and a putative tumor suppressor. Apart from its interaction with β-catenin and involvement in E-cadherin internalization, little structure or function information exists. Here we explored shrew-1 expression during postnatal differentiation of mammary gland as a model system. Immunohistological analyses with antibodies against either the extracellular or the cytoplasmic domains of shrew-1 consistently revealed the expression of full-length shrew-1 in myoepithelial cells, but only part of it in luminal cells. While shrew-1 localization remained unaltered in myoepithelial cells, nuclear localization occurred in luminal cells during lactation. Based on these observations, we identified two unknown shrew-1 transcript variants encoding N-terminally truncated proteins. The smallest shrew-1 protein lacks the extracellular domain and is most likely the only variant present in luminal cells. RNA analyses of human tissues confirmed that the novel transcript variants of shrew-1 exist in vivo and exhibit a differential tissue expression profile. We conclude that our findings are essential for the understanding and interpretation of future functional and interactome analyses of shrew-1 variants. Summary: Transcripts of the tumor suppressor gene SHREW-1 exist in various splice variants in human and mouse encoding proteins with a differential expression and intracellular localization profile.
BioMart Central Portal—unified access to biological data

BioMart Central Portal (www.biomart.org) offers a one-stop shop solution to access a wide array of biological databases. These include major biomolecular sequence, pathway and annotation databases such as Ensembl, Uniprot, Reactome, HGNC, Wormbase and PRIDE; for a complete list, visit, http://www.biomart. org/biomart/martview. Moreover, the web server features seamless data federation making cross querying of these data sources in a user friendly and unified way. The web server not only provides access through a web interface (MartView), it also supports programmatic access through a Perl API as well as RESTful and SOAP oriented web services. The website is free and open to all users and there is no login requirement.
Multiscale approach to contour fitting for MR images

We present a new multiscale contour fitting process which combines information about the image and the contour of the object at different levels of scale. The algorithm is based on energy minimizing deformable models but avoids some of the problems associated with these models. The segmentation algorithm starts by constructing a linear scale-space of an image through convolution of the original image with a Gaussian kernel at different levels of scale, where the scale corresponds to the standard deviation of the Gaussian kernel. At high levels of scale large scale features of the objects are preserved while small scale features, like object details as well as noise, are suppressed. In order to maximize the accuracy of the segmentation, the contour of the object of interest is then tracked in scale-space from coarse to fine scales. We propose a hybrid multi-temperature simulated annealing optimization to minimize the energy of the deformable model. At high levels of scale the SA optimization is started at high temperatures, enabling the SA optimization to find a global optimal solution. At lower levels of scale the SA optimization is started at lower temperatures (at the lowest level the temperature is close to 0). This enforces a more deterministic behavior of the SA optimization at lower scales and leads to an increasingly local optimization as high energy barriers cannot be crossed. The performance and robustness of the algorithm have been tested on spin-echo MR images of the cardiovascular system. The task was to segment the ascending and descending aorta in 15 datasets of different individuals in order to measure regional aortic compliance. The results show that the algorithm is able to provide more accurate segmentation results than the classic contour fitting process and is at the same time very robust to noise and initialization.