Miracle-dz/UniFAR-FTUs huggingface dataset:
Change detection in Migrating Parallel Web Crawler: A Neural Network Based Approach

Search engines are the tools for Web site navigation and search. Search engines maintain indices for web documents and provide search facilities by continuously downloading Web pages for processing. This process of downloading web pages is known as web crawling. In this paper we propose A neural network based change detection method in migrating parallel web crawler. This method for Effective Migrating Parallel Web Crawling approach will detect changes in the content and structure using neural network. This crawling strategy makes web crawling system more effective and efficient. The major advantages of migrating parallel web crawler are that the analysis portion of the crawling process is done locally at the residence of data rather than inside the Web search engine repository. This significantly reduces network load and traffic which in turn improves the performance, effectiveness and efficiency of the crawling process. The another advantage of migrating parallel crawler is that as the size of the Web grows, it becomes necessary to parallelize a crawling process, in order to finish downloading web pages in a comparatively shorter time. Neural network based change detection method in migrating parallel web crawler will yield high quality pages and detect for changes will always download fresh pages.
Nature-Like Computation and a Measure of Programmability 1

I will propose an alternative behavioural definition of computation based on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programma- bility. This will be done by using a phase transition coefficient previously defined in an attempt to characterise the evolution of cellular automata and other systems. This transition coefficient measures the sensitivity of a system to external stimuli and will be used to define the susceptibility of a system to being (efficiently) programmed in the context of a nature-like definition of computation.
Dimensionality reduction and motion coordination in learning trajectories with Dynamic Movement Primitives

Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning trajectories, because of their linearity in the parameters, rescaling robustness and continuity. However, when learning a movement with a robot using DMP, many parameters may need to be tuned, requiring a prohibitive number of experiments/simulations to converge to a solution with a locally or globally optimal reward.
Readability of Informed Consent Documents at University Counseling Centers

ABSTRACT The extent to which clients understand the nature and anticipated course of therapy is referred to as informed consent. Counseling psychologists often provide informed consent documents to enhance the education of services and for liability purposes. Professionals in numerous health care settings have evaluated the readability of their informed consent documents, but no such peer-reviewed research exists for university counseling centers. This study evaluated the informed consent documents for psychotherapy from university counseling centers using three readability formulas (Flesch-Kincaid Grade Level, Flesch Reading Ease Score, and Simple Measure of Gobbledygook [SMOG] Grading). The findings support the authors’ exploratory hypotheses that informed consent documents in university counseling centers are rated as challenging to read for college students. Recommendations and implications for practice are discussed.
On finding multi-constrained paths

New emerging distributed multimedia applications provide guaranteed end-to-end quality of service (QoS) and have stringent constraints on delay, delay-jitter, cost, etc. The task of QoS routing is to find a route in the network which has sufficient resources to satisfy the constraints. The delay-cost-constrained routing problem is NP-complete. We propose a heuristic algorithm for this problem. The idea is to first reduce the NP-complete problem to a simpler one which can be solved in polynomial time, and then solve the new problem by either an extended Dijkstra's algorithm or an extended Bellman-Ford algorithm. We prove the correctness of our algorithm by showing that a solution for the simpler problem must also be a solution for the original problem. The performance of the algorithm is studied by both theoretical analysis and simulation.
Thing May Be Bad Visual Environment , Attention Allocation , and Learning in Young Children : When Too Much of a Good

A large body of evidence supports the importance of focused attention for encoding and task performance. Yet young children with immature regulation of focused attention are often placed in elementary-school classrooms containing many displays that are not relevant to ongoing instruction. We investigated whether such displays can affect children’s ability to maintain focused attention during instruction and to learn the lesson content. We placed kindergarten children in a laboratory classroom for six introductory science lessons, and we experimentally manipulated the visual environment in the classroom. Children were more distracted by the visual environment, spent more time off task, and demonstrated smaller learning gains when the walls were highly decorated than when the decorations were removed.
MAP MULTIUSER DETECTION WITH SOFT INTERFERENCE CANCELLATION FOR UMTS TD-CDMA RECEIVERS

A new multiuser detector (MUD) exploiting the MAP algorithm is proposed for channels affected by severe multipath and is then suitable for TDCDMA receivers. After coherent combining the received multipaths, a multidimensional MAP nonlinearity is employed to compute step-by-step the A Posteriori Probabilities (APPs) of the transmitted data for each user separately and then their expected values conditional to the available observations. These are then employed for soft ISI and MAI removal from the received sequences so that the APPs can be more reliably re-computed. The procedure is iterated in a multistage structure until that final decisions are taken. From the comparison with other existing techniques (interference cancellation, zero-forcing) the proposed reduced MAP-MUD receiver exhibits better performance and equal or minor complexity.
The Compositional Security Checker: A Tool for the Verification of Information Flow Security Properties

The Compositional Security Checker (CoSeC for short) is a semantic-based tool for the automatic verification of some compositional information flow properties. The specifications given as inputs to CoSeC are terms of the Security Process Algebra, a language suited for the specification of concurrent systems where actions belong to two different levels of confidentiality. The information flow security properties which can be verified by CoSeC are some of those classified in (Focardi and Gorrieri, 1994). They are derived from some classic notions, e.g., noninterference. The tool is based on the same architecture as the Concurrency Workbench, from which some modules have been imported unchanged. The usefulness of the tool is tested with the significant case-study of an access-monitor, presented in several versions in order to illustrate the relative merits of the various information flow properties that CoSeC can check. Finally, we present an application in the area of network security: we show that the theory (and the tool) can be reasonably applied also for singling out security flaws in a simple, yet paradigmatic, communication protocol.
Antiserum from a patient with cerebellar degeneration identifies a novel protein in Purkinje cells, cortical neurons, and neuroectodermal tumors

The serum and cerebrospinal fluid of a patient (NB) with subacute cerebellar degeneration were found to contain a novel antineuronal autoantibody (anti-Nb). Using this antibody, we have identified and characterized antigens present in a subset of neurons in the CNS and in some neuroectodermal tumor lines. Anti-Nb antibody bound to antigens of Mr 150, 120, and 65 kDa in Western blots using extracts of human cerebellar Purkinje cells or human cerebral cortical neurons. Immunohistochemistry demonstrated relatively specific binding of anti- Nb IgG to Purkinje cells in sections of human cerebellum and to some neocortical neurons, especially those in layer VI. Because of the association of cerebellar degeneration with occult malignancies, we screened a number of tumor cell lines for immunoreactivity to anti-Nb antibody; only tumor lines of neuroectodermal origin (melanoma, small- cell lung cancer, and neuroblastoma) expressed the Nb antigen. Anti-Nb antibody thus identifies neuronal and tumor cell antigens that appear to be unique in size and distribution of expression.
Granulocyte colony-stimulating factor expression from transduced vascular smooth muscle cells provides sustained neutrophil increases in rats.

Granulocyte colony-stimulating factor (G-CSF) regulates granulocyte precursor cell proliferation, neutrophil survival, and activation. Cyclic hematopoiesis, a disease that occurs both in humans and grey collie dogs is characterized by cyclical variations in blood neutrophils. Although the underlying molecular defect is not known, long-term daily administration of recombinant G-CSF eliminates the severe recurrent neutropenia, indicating that expression of G-CSF by gene therapy would be beneficial. As a prelude to preclinical studies in affected collie dogs, we monitored hematopoiesis in rats receiving vascular smooth muscle cells transduced to express G-CSF. Cells transduced with LrGSN, a retrovirus expressing rat G-CSF, were implanted in the carotid artery and control animals received cells transduced with LASN, a retrovirus expressing human adenosine deaminase (ADA). Test animals showed significant increases in neutrophil counts for at least 7 weeks, with mean values of 3,670 +/- 740 cells/microliter in comparison to 1,870 +/- 460 cells/microliter in controls (p < 0.001). Thus, in rats G-CSF gene transfer targeted at vascular smooth muscle cells initiated sustained production of 1,800 neutrophils/microliter, a cell number that would provide clinical benefit to patients. Lymphocytes, red cells and platelets were not different between control and test animals (p > 0.05). These studies indicate that retrovirally transduced vascular smooth muscle cells can provide sustained clinically useful levels of neutrophils in vivo.
A User Study on Multivariate Edge Visualizations for Graph-Based Visual Analysis Tasks

Providing insight in complex networks or graphs with multivariate data is one of the main challenges for visual analysis today. Much work has been done for visualizing information on nodes, but the space in between has mostly not been used yet. We developed a user study based on two techniques called Partially filled Bars and Bars of Varying Height and asked subjects to perform different tasks. We briefly present both techniques and our design of a large user study. Our goal is to understand the advantages and disadvantages of both approaches compared to each other. After describing our evaluation setup and our initial hypothesis, the results are analyzed, discussed and the most accepted configuration is presented. Finally we briefly discuss the outcome of the user study and our next steps for further investigations.
Living on the Edge : Safe Search with Unsafe Heuristics

Considering heuristic search for satisficing and cost-optimal planning, we introduce the notion of global safeness of a heuristic, a property weaker than the standard safeness, which we claim is better for heuristic search. We describe one concrete approach for creating globally safe and optimality preserving heuristics by exploiting information in the history of the search via a new form of inference related to existential landmarks. We evaluate our approach on some state-of-theart heuristic search tools for cost-optimal planning, and discuss the outcomes of this evaluation.
Audible Image Description as an Accommodation in Statewide Assessments for Students with Visual and Print Disabilities

Introduction Although image description has been identified as an accommodation for presentations conducted in the classroom, only a few U.S. states have approved it for use in high-stakes assessments. This study examined the use of audible image description as an assessment accommodation for students with visual and print disabilities by investigating student comprehension under multiple conditions. Methods Students in three western states in grades three through eight who had visual (n = 117) or print (n = 178) disabilities participated in an abbreviated test constructed of retired assessment questions in English language arts, mathematics, and science, that were aligned with each state's instructional standards, under conditions with and without standardized description of graphic images. The study used a within-subjects block design to collect and compare comprehension data under conditions where audible image description was both used and not used in an abbreviated test. Results Results indicated that students who read braille were more likely to respond correctly under the audible image description condition, and students with visual and print disabilities who used print were equally likely to respond correctly regardless of condition. Discussion Braille readers were more likely to obtain a correct answer when audible image description accompanied the question. Audible image description did not affect the likelihood of a correct response from students with print disabilities or students with visual disabilities who read print. Implications for practitioners Audible image description is an accommodation that may help braille readers perform better on tests. Although the Partnership for Assessment of Readiness for College and Careers (PARCC) and Smarter Balanced consortia are taking steps to include image (or picture) descriptions in their assessment accommodations, teachers may want to develop a standard method for describing images and familiarize their braille readers to the strategy by including it in instruction and in classroom tests. Readers are referred to the National Center on Accessible Media's online guidelines for image description.
Influence of Sci-Fi films on artificial intelligence and vice-versa

Sci-fi technological movie domain is an important part of human culture. The paper focus on comparison study of selected robotics sci-fi movie domain from a technological point of view. It is necessary to accomplish technological analysis of studied sci-fi movies and able to distinguish about possible current technology and future direction of the artificial intelligence in the domain of Robot intelligence. The review of existing movies which are in fact influencing thinking of humans is essential since it can influence a future research direction in AI. This information is interesting for inspiration of students and research associates in theory and applications. In conclusion, we envision potential problems of social networks and impact of Internet of things facts which is becoming a reality with IPv6 protocol. The goal of the paper is also to underline the importance of such cultural phenomena as sci-fi movies for the future of humanity.
Mining Web data to create online navigation recommendations

A system to provide online navigation recommendation for Web visitors is introduced. We call visitor the anonymous user, i.e., when only data about her/his browsing behavior (Web logs) are available. We first apply clustering techniques over a large sample of Web data. Next, from the significant patterns that are discovered, a set of rules about how to use them is created. Finally, comparing the current Web visitor session with the patterns, online navigation recommendations are proposed using the mentioned rules. The system was tested using data from a real Web site, showing its effectiveness.
Behavior-Based Segmentation of Demonstrated Tasks

Robot learning from demonstration presents several challenges. Given a task demonstration, the robot must sense, understand, and learn appropriate task attributes.We propose a method for automatic segmentation of a complex demonstration into an ordered set of simpler behaviors. The se behaviors present a significantly less complex domain for learning. Our method is based on empirically derived attributes of tasks and simple mathematical transformations that results in a fast and intuitive mechanism for automatic task segmentation. The method is validated on a simulated Pioneer 2 DX platform across four demonstrations that vary in environmental complexity, task complexity, and task strategy.
Effects of Stress on Economic Decision-Making: Evidence from Laboratory Experiments

The ways in which preferences respond to the varying stress of economic environments is a key question for behavioral economics and public policy. We conducted a laboratory experiment to investigate the effects of stress on financial decision making among individuals aged 50 and older. Using the cold pressor task as a physiological stressor, and a series of intelligence tests as cognitive stressors, we find that stress increases subjective discounting rates, has no effect on the degree of risk-aversion, and substantially lowers the effort individuals make to learn about financial decisions.
Connections between sparse estimation and robust statistical learning

Recent literature on robust statistical inference suggests that promising outlier rejection schemes can be based on accounting explicitly for sparse gross errors in the modeling, and then relying on compressed sensing ideas to perform the outlier detection. In this paper, we consider two models for recovering a sparse signal from noisy measurements, possibly also contaminated with outliers. The models considered here are a linear regression model, and its natural one-bit counterpart where measurements are additionally quantized to a single bit. Our contributions can be summarized as follows: We start by providing conditions for identification and the Cramér-Rao Lower Bounds (CRLBs) for these two models. Then, focusing on the one-bit model, we derive conditions for consistency of the associated Maximum Likelihood estimator, and show the performance of relevant ℓ1-based relaxation strategies by comparing against the theoretical CRLB.
Sub-Sampled Newton Methods I: Globally Convergent Algorithms

Large scale optimization problems are ubiquitous in machine learning and data analysis and there is a plethora of algorithms for solving such problems. Many of these algorithms employ sub-sampling, as a way to either speed up the computations and/or to implicitly implement a form of statistical regularization. In this paper, we consider second-order iterative optimization algorithms and we provide bounds on the convergence of the variants of Newton's method that incorporate uniform sub-sampling as a means to estimate the gradient and/or Hessian. Our bounds are non-asymptotic and quantitative. Our algorithms are global and are guaranteed to converge from any initial iterate. Using random matrix concentration inequalities, one can sub-sample the Hessian to preserve the curvature information. Our first algorithm incorporates Hessian sub-sampling while using the full gradient. We also give additional convergence results for when the sub-sampled Hessian is regularized by modifying its spectrum or ridge-type regularization. Next, in addition to Hessian sub-sampling, we also consider sub-sampling the gradient as a way to further reduce the computational complexity per iteration. We use approximate matrix multiplication results from randomized numerical linear algebra to obtain the proper sampling strategy. In all these algorithms, computing the update boils down to solving a large scale linear system, which can be computationally expensive. As a remedy, for all of our algorithms, we also give global convergence results for the case of inexact updates where such linear system is solved only approximately. This paper has a more advanced companion paper, [42], in which we demonstrate that, by doing a finer-grained analysis, we can get problem-independent bounds for local convergence of these algorithms and explore trade-offs to improve upon the basic results of the present paper.
differentiation progenitor cells and is required for epo regulation of erythroid cell AKT induces erythroid cell maturation of JAK2-deficient fetal liver

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Financial Systems, Economic Growth, and Globalization

This paper brings together two strands of the economic literature -- that on the finance-growth nexus and that on capital market integration -- and explores key issues surrounding each strand through both institutional/country histories and formal quantitative analysis. We begin with studies of the Dutch Republic, England, the U.S., France, Germany and Japan that span three centuries, detailing how in each case the emergence of a financial system jump-started economic growth. Using a cross-country panel of seventeen countries covering the 1850-1997 period, we then uncover a robust correlation between financial factors and economic growth that is consistent with a leading role for finance, and show that these effects were strongest over the 80 years preceding the Great Depression. Next, we show that countries with more sophisticated financial systems engage in more trade and appear to be better integrated with other economies by identifying roles for both finance and trade in the convergence of interest rates that occurred among the Atlantic economies prior to 1914. Our results suggest that the growth and increasing globalization of these economies might indeed have been 'finance-led. '
Endothelial Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 Is Critical for Lymphatic Vascular Development and Function

ABSTRACT The molecular mechanisms underlying lymphatic vascular development and function are not well understood. Recent studies have suggested a role for endothelial cell (EC) mitogen-activated protein kinase kinase kinase kinase 4 (Map4k4) in developmental angiogenesis and atherosclerosis. Here, we show that constitutive loss of EC Map4k4 in mice causes postnatal lethality due to chylothorax, suggesting that Map4k4 is required for normal lymphatic vascular function. Mice constitutively lacking EC Map4k4 displayed dilated lymphatic capillaries, insufficient lymphatic valves, and impaired lymphatic flow; furthermore, primary ECs derived from these animals displayed enhanced proliferation compared with controls. Yeast 2-hybrid analyses identified the Ras GTPase-activating protein Rasa1, a known regulator of lymphatic development and lymphatic endothelial cell fate, as a direct interacting partner for Map4k4. Map4k4 silencing in ECs enhanced basal Ras and extracellular signal-regulated kinase (Erk) activities, and primary ECs lacking Map4k4 displayed enhanced lymphatic EC marker expression. Taken together, these results reveal that EC Map4k4 is critical for lymphatic vascular development by regulating EC quiescence and lymphatic EC fate.