Miracle-dz/UniFAR-FTUs huggingface dataset:
A competitive mechanism for self-organized learning of sensorimotor mappings

How can a robot learn sensorimotor knowledge in a developmental way based on its own experiences solely? An important step is the acquisition of a body-schema—learning about the physical behavior of its own body, and how incoming sensory stimuli can be put in relation to the own body. In this work, we study how a competitive learning mechanism, which is related to the EM algorithm, can help to simplify the learning problem. We demonstrate how a robot can learn the way visual stimuli move as a consequence of the robots own actions of moving its camera or moving its end-effector in front of its camera. We show how the robot can discriminate stimuli originating from these two kinds of actions and learn the position of the end-effector in its visual input. Previous approaches have relied on a preprocessing step to “self-detect”, which we find is not necessary. The robot acquires a set of sensorimotor estimates, which could later be used, e.g. in visually guided reaching.
A Comparison of Questionnaires for Assessing Website Usability

Five questionnaires for assessing the usability of a website were compared in a study with 123 participants. The questionnaires studied were SUS, QUIS, CSUQ, a variant of Microsoft’s Product Reaction Cards, and one that we have used in our Usability Lab for several years. Each participant performed two tasks on each of two websites: finance.yahoo. com and kiplinger.com. All five questionnaires revealed that one site was significantly preferred over the other. The data were analyzed to determine what the results would have been at different sample sizes from 6 to 14. At a sample size of 6, only 30-40% of the samples would have identified that one of the sites was significantly preferred. Most of the data reach an apparent asymptote at a sample size of 12, where two of the questionnaires (SUS and CSUQ) yielded the same conclusion as the full dataset at least 90% of the time.
PPIXpress: construction of condition-specific protein interaction networks based on transcript expression

UNLABELLED Protein-protein interaction networks are an important component of modern systems biology. Yet, comparatively few efforts have been made to tailor their topology to the actual cellular condition being studied. Here, we present a network construction method that exploits expression data at the transcript-level and thus reveals alterations in protein connectivity not only caused by differential gene expression but also by alternative splicing. We achieved this by establishing a direct correspondence between individual protein interactions and underlying domain interactions in a complete but condition-unspecific protein interaction network. This knowledge was then used to infer the condition-specific presence of interactions from the dominant protein isoforms. When we compared contextualized interaction networks of matched normal and tumor samples in breast cancer, our transcript-based construction identified more significant alterations that affected proteins associated with cancerogenesis than a method that only uses gene expression data. The approach is provided as the user-friendly tool PPIXpress. AVAILABILITY AND IMPLEMENTATION PPIXpress is available at https://sourceforge.net/projects/ppixpress/.
A general optical flow based terrain-following strategy for a VTOL UAV using multiple views

This paper presents a general approach for terrain following (including obstacle avoidance) of a vertical take-off and landing vehicle (VTOL) using multiple observation points. The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera, IMU and barometric altimeter), manoeuvering over a textured rough terrain made of a concatenation of planar surfaces. Assuming that the forward velocity is separately regulated to a desired non-zero value, the proposed control approach ensures terrain following and guarantees the vehicle does not collide with obstacles during the task. The proposed control acquires an optical flow from multiple spatially separate observation points, typically obtained via multiple cameras or non collinear directions in a unique camera. The proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor UAV to demonstrate the performance of the closed loop system.
Arabidopsis Nitric Oxide Synthase1 Is Targeted to Mitochondria and Protects against Oxidative Damage and Dark-Induced Senescence

The Arabidopsis thaliana protein nitric oxide synthase1 (NOS1) is needed for nitric oxide (NO) synthesis and signaling during defense responses, hormonal signaling, and flowering. The cellular localization of NOS1 was examined because it is predicted to be a mitochondrial protein. NOS1–green fluorescent protein fusions were localized by confocal microscopy to mitochondria in roots. Isolated mitochondria from leaves of wild-type plants supported Arg-stimulated NO synthesis that could be inhibited by NOS inhibitors and quenched by a NO scavenger; this NOS activity is absent in mitochondria isolated from nos1 mutant plants. Because mitochondria are a source of reactive oxygen species (ROS), which participate in senescence and programmed cell death, these parameters were examined in the nos1 mutant. Dark-induced senescence of detached leaves and intact plants progressed more rapidly in the mutant compared with the wild type. Hydrogen peroxide, superoxide anion, oxidized lipid, and oxidized protein levels were all higher in the mutant. These results demonstrate that NOS1 is a mitochondrial NOS that reduces ROS levels, mitigates oxidative damage, and acts as an antisenescence agent.
3-D magnetostatic field calculation for a magnetic circuit with no (a arrow) air gap

Noting that 3-D magnetostatic field calculations for gapless magnetic circuits are strongly affected by the discretization, the author analyzes this effect for an iron torus using a boundary integral equation based on the surface magnetization current method. The main cause of computational error is the imperfect cancellation of the permeability-free terms in the boundary integral equation due to the improper size of the analytical integration region containing a singular point. A method of reducing the computational error is presented and verified to be valid. >
Uncovering Measurements of Social and Demographic Behavior From Smartphone Location Data

Human behavior, and in particular location behavior, is highly routine based. Modern mobile phones, through global position system (GPS) technology and cell tower and WiFi location identification, enable us to trace human location behavior at scales that were previously unattainable. The goal of this paper is to examine human location behavior, through mobile phone data, and investigate if links can be made between location behavior patterns and particular demographic and social characteristics about an individual. We hypothesize that an individual's daily predictability can be key to linking their behavior to certain characteristics, and we propose predictability and geographic areas of interest models to analyze this hypothesis. Experiments reveal that measurements, which are based on our proposed location predictability models, can correctly infer 17 different characteristics about an individual with an average accuracy of 85.5%.
An Advanced Vehicle Collision Warning Algorithm over the DSRC Communication Environment: An Advanced Vehicle Collision Warning Algorithm

Although many kinds of collision pre-warning algorithms and systems for vehicles were proposed in order to prevent accidents in past years, two problems have to be resolve in order to enhance the accuracy of collision detection. First, a vehicle does not always keep the same velocity when it is moving. Second, the curve road condition should be considered. In this paper, we proposed an Advanced Cooperative Collision Warning algorithm named ACCW to deal with these two problems. Basically, ACCW uses the acceleration parameter to correct some errors that are caused by velocity and direction changing. The simulation results show that that the proposed ACCW algorithm has high accuracy's warning rates in both intersection and curve situations.
Test Development: Statistical Aspects

FOR THE PERIOD REVIEWED the large number of publications, either directly or indirectly related to the statistical aspects of test development, made it imperative that severe restrictions be imposed on the scope of the following discussion. Correlation, analysis of variance, and other techniques were not reviewed unless they happened to relate to tests. It may be observed that although the greatest frequency of publications was found under factor analysis, the studies apparently showing the keenest insight in terms of analysis of basic concepts appeared under reliability.
Twitter sentiment analysis using various classification algorithms

Twitter is a web application built to find out what is happening at any instance through its micro blogging feature, anywhere in the world. Twitter posts are generally short and generated constantly by public and very well-suited for opinion mining. These messages can be classified as containing either positive or a negative sentiment on the basis of certain aspects with respect to a term based query. The past studies of sentiment classification are not very conclusive about which features and supervised classification algorithms are good for designing accurate and efficient sentiment classification system. We propose to combine many feature extraction techniques like emoticons, exclamation and question mark symbol, word gazetteer, unigrams to design more accurate sentiment classification system. This paper presents empirical comparison of six supervised classification algorithms.
Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading

We demonstrate the use of shape-from-shading (SfS) to improve both the quality and the robustness of 3D reconstruction of dynamic objects captured by a single camera. Unlike previous approaches that made use of SfS as a post-processing step, we offer a principled integrated approach that solves dynamic object tracking and reconstruction and SfS as a single unified cost function. Moving beyond Lambertian S f S , we propose a general approach that models both specularities and shading while simultaneously tracking and reconstructing general dynamic objects. Solving these problems jointly prevents the kinds of tracking failures which can not be recovered from by pipeline approaches. We show state-of-the-art results both qualitatively and quantitatively.
Neural Mechanisms in Dyslexia

Within the last two decades, evidence from many laboratories has converged to indicate the cognitive basis for dyslexia: Dyslexia is a disorder within the language system and, more specifically, within a particular subcomponent of that system, phonological processing. Converging evidence from a number of laboratories using functional brain imaging indicates that there is a disruption of left-hemisphere posterior neural systems in child and adult dyslexic readers when they perform reading tasks. The discovery of a disruption in the neural systems serving reading has significant implications for the acceptance of dyslexia as a valid disorder—a necessary condition for its identification and treatment. Brain-imaging findings provide, for the first time, convincing, irrefutable evidence that what has been considered a hidden disability is “real,” and these findings have practical implications for the provision of accommodations, a critical component of management for older children and young adults attending postsecondary and graduate programs. The utilization of advances in neuroscience to inform educational policy and practices provides an exciting example of translational science being used for the public good.
The effectiveness of a computerized self-help stress coping program with adult males

The purpose of this study was to determine if a computerized self-help stress coping program, based upon cognitive learning theory, is effective in reducing stress in adult males. Thirty adult male juvenile counselors were randomly assigned to an experimental or non-participating control group. A computerized self-help stress coping was used over a five week period by those in the experimental group. As hypothesized, no differences were found between the groups on the variables of occupational stress and trait anxiety. However, decreases in personal strain and state anxiety were found along with increases in personal resources. The factor of social support was found to account for the greatest amount of variance in all dependent variables. It was concluded that stress coping computer programs can provide some relief for situational types of stress.
Soy protein for infant feeding: what do we know?

Purpose of reviewThis review discusses the safety, nutritional adequacy and recommendations for use of soy protein formulae, based mainly on the most relevant reports published during 2005 and 2006. Recent findingsConcerns have recently been raised regarding potential risks with soy protein formulae, in particular regarding their high phytoestrogenic isoflavone content. Recent data are insufficient to draw definitive conclusions on safety, but authorities and paediatric societies from several countries recently advised health professionals to use soy protein formulae only in certain cases. Indications for use of soy protein formulae, mainly for prevention and management of food allergy, have also been better defined. SummarySoy protein formulae ensure normal growth and development in healthy term infants but they have no nutritional advantages over cow's milk protein formulae. Main indications include severe lactose intolerance, galactosaemia and need to avoid foods of animal origin. Soy protein formulae have no role in preventing allergy or in management of nonspecific gastrointestinal symptoms (e.g. infantile colic and regurgitation). They should not be used in preterm infants or infants with food allergy before age 6 months. After 6 months, soy protein formulae may be considered if tolerance to soy protein is established.
A Study of the Frequency and Social Determinants of Exposure to Cancer-Related Direct-to-Consumer Advertising Among Breast, Prostate, and Colorectal Cancer Patients

Cancer-related direct-to-consumer advertising (DTCA) is controversial because cancer treatment is complex and entails more risks and costs than typical treatments that are advertised for other conditions. Drawing from the Structural Influence Model of Communication, this study explores communication inequalities in DTCA exposure across social determinants among a population-based sample of 2013 patients diagnosed with breast, prostate, or colorectal cancers. Three survey items assessed patients’ frequency of encountering ads concerning treatment alternatives for cancer, dealing with side effects of treatment, and doctors or hospitals offering services for cancer following their diagnosis. The analysis showed that overall exposure to DTCA in this study population was modest (median was once per week). Breast cancer patients reported significantly higher exposure to all three ad categories and overall DTCA exposure than prostate and colorectal cancer patients. Older patients consistently reported lower overall exposure to DTCA across the three cancer types. Other significant correlates included ethnicity (higher exposures among African American prostate cancer patients vs. White; lower exposures in Hispanic colorectal cancer patients vs. White) and cancer stage (higher exposures in Stage IV prostate cancer patients vs. Stages 0–II). Education level did not predict patients’ DTCA exposure. The implications of these observed inequalities in DTCA exposure on cancer outcomes are discussed.
A geometric approach for early power grid verification using current constraints

The verification of power grids in modern integrated circuits must start, at design time, where circuit information is unknown but could be specified or inferred from design or architectural considerations. This work builds on previously proposed techniques to deal with circuit uncertainty in the framework of linear current constraints, but proposes a cost-controlled solution, by following a geometric approach, and transforming a problem that requires as many linear programs as there are power grid nodes, to another involving a user-limited number of solutions of one linear system.
Data-driven Multilingual Coreference Resolution using Resolver Stacking

This paper describes our contribution to the CoNLL 2012 Shared Task. We present a novel decoding algorithm for coreference resolution which is combined with a standard pair-wise coreference resolver in a stacking approach. The stacked decoders are evaluated on the three languages of the Shared Task. We obtain an official overall score of 58.25 which is the second highest in the Shared Task.
A Data Warehouse for Multidimensional Gene Expression Analysis

We introduce the GeWare data warehouse approach for microarray-based gene expression analysis. GeWare centrally stores raw and preprocessed expression data together with a variety of annotations to support different analysis forms. The flexibility of GeWare is made possible by a multi-dimensional data model where expression data is stored in several fact tables which are associated with multiple hierarchical dimensions holding describing metadata on genes, samples, experiments, and processing methods. Annotations are uniformly managed in a generic way thus supporting the high variability of annotations and easy extensibility. Gene annotations are imported from several public sources and integrated with each other based on commonly used accession numbers, e.g. Uni-Gene clusters.
Public Verifiability in Cloud Computing Using Signcryption Based on Elliptic Curves

Cloud computing is a computing paradigm that involves outsourcing of computing resources with the capabilities of expendable resource scalability, on-demand provisioning with little or no up-front IT infrastructure investment costs. It has recently emerged as a promising hosting platform that performs an intelligent usage of a collection of services, applications, information and infrastructure comprised of pools of computer, network, information and storage resources. However along with these advantages, storing a large amount of data including critical information on the cloud motivates highly skilled hackers thus creating a need for the security to be considered as one of the top issues while considering Cloud Computing. In the cloud storage model, data is stored on multiple virtualized servers. Physically the resources will span multiple servers and can even span storage sites. We have proposed an effective scheme to ensure the correctness of user's data on cloud data storage and public verifiability without demanding user's time, feasibility or resources. Whenever data corruption is detected during the storage correctness verification, this scheme can almost guarantee the simultaneous localization of data errors and the identification of the misbehaving server(s). Keywords - Elliptic Curves, Homomorphic, Signcryption, Unsigncryption.
Depot‐ and ethnic‐specific differences in the relationship between adipose tissue inflammation and insulin sensitivity

Objective It is unclear whether there are differences in inflammatory gene expression between abdominal and gluteal subcutaneous adipose tissue (SAT), and between black and white women. We therefore tested the hypotheses that SAT inflammatory gene expression is greater in the abdominal compared to the gluteal depot, and SAT inflammatory gene expression is associated with differential insulin sensitivity (SI) in black and white women.
Who is Politically Active: The Athlete, the Scout Member or the Environmental Activist?

Most research finds that voluntary engagement leads to more political participation. However, it is not entirely clear which type of organization encourages political participation and what skills are required. There is also some discussion about whether multiple memberships promote political participation. In this article, I use the Belgian Youth Survey (n = 6,330) in investigating the effect that type of organization, the time spent in organizations, the number of memberships and skills-related activities has on political participation. My findings suggest that voluntary organizations are powerful political socialization agents leading to young people engaging in politics. Young people who are members of several organizations are more active in politics, while spending a greater amount of time in one organization does not increase level of political participation. Cultural, deliberative and help organizations are more successful than expressive, religious—ethnic and youth groups in fostering political engagement. Finally, organizations that allow young people to take up a leadership role, or to organize activities, encourage participation in political activities.
Immunosuppressant FK506 enhances phosphorylation of nitric oxide synthase and protects against glutamate neurotoxicity.

Immunosuppressants FK506 and cyclosporin A inhibit neurotoxicity of N-methyl-D-aspartate in primary cortical cultures, while having no effect on quisqualate- and kainate-mediated neurotoxicity. Rapamycin completely reverses the neuroprotective effect of FK506. Both FK506 and cyclosporin A inhibit NMDA-elicited/nitric oxide-mediated increases in cGMP levels in cortical cultures. FK506 has no effect on sodium nitroprusside-induced increases in cGMP. In a stably transfected human kidney 293 cell line overexpressing the gene encoding nitric oxide synthase [L-arginine, NADPH:oxygen oxidoreductase (nitric oxide-forming), EC 1.14. 13.39], FK506 inhibits the calcium ionophore A23187, stimulated increases in nitrite (a breakdown product of nitric oxide), and potentiates phorbol ester-mediated inhibition of nitrite formation. FK506-mediated inhibition of nitric oxide formation is completely reversed by rapamycin. Calcineurin dephosphorylates protein kinase C-mediated phosphorylation of nitric oxide synthase. FK506 prevents the calcineurin-mediated dephosphorylation of nitric oxide synthase and thereby diminishes the enzyme's catalytic activity. These data establish nitric oxide synthase as a calcineurin substrate. Nitric oxide synthase catalytic activity is regulated by the phosphorylation state of the enzyme. Enhanced phosphorylation of nitric oxide synthase diminishes catalytic activity, and dephosphorylation (through activation of calcineurin) enhances catalytic activity. The neuroprotective effect of FK506 and cyclosporin A presumably involves the inhibition of calcineurin, preventing the dephosphorylation of nitric oxide synthase and its subsequent activation.
Using probabilistic latent semantic analysis for Web page grouping

The locality of Web pages within a Web site is initially determined by the designer's expectation. Web usage mining can discover the patterns in the navigational behaviour of Web visitors, in turn, improve Web site functionality and service designing by considering users' actual opinion. Conventional Web page clustering technique is often utilized to reveal the functional similarity of Web pages. However, high-dimensional computation problem will be incurred due to taking user transaction as dimension. In this paper, we propose a new Web page grouping approach based on a probabilistic latent semantic analysis (PLSA) model. An iterative algorithm based on maximum likelihood principle is employed to overcome the aforementioned computational shortcoming. The Web pages are classified into various groups according to user access patterns. Meanwhile, the semantic latent factors or tasks are characterized by extracting the content of "dominant" pages related to the factors. We demonstrate the effectiveness of our approach by conducting experiments on real world data sets.