Miracle-dz/UniFAR-FTUs huggingface dataset:
Assembly and Use of New Task Rules in Fronto-parietal Cortex

Severe capacity limits, closely associated with fluid intelligence, arise in learning and use of new task rules. We used fMRI to investigate these limits in a series of multirule tasks involving different stimuli, rules, and response keys. Data were analyzed both during presentation of instructions and during later task execution. Between tasks, we manipulated the number of rules specified in task instructions, and within tasks, we manipulated the number of rules operative in each trial block. Replicating previous results, rule failures were strongly predicted by fluid intelligence and increased with the number of operative rules. In fMRI data, analyses of the instruction period showed that the bilateral inferior frontal sulcus, intraparietal sulcus, and presupplementary motor area were phasically active with presentation of each new rule. In a broader range of frontal and parietal regions, baseline activity gradually increased as successive rules were instructed. During task performance, we observed contrasting fronto-parietal patterns of sustained (block-related) and transient (trial-related) activity. Block, but not trial, activity showed effects of task complexity. We suggest that, as a new task is learned, a fronto-parietal representation of relevant rules and facts is assembled for future control of behavior. Capacity limits in learning and executing new rules, and their association with fluid intelligence, may be mediated by this load-sensitive fronto-parietal network.
Teaching for understanding and school sport: a study in an intercultural context and situation of social risk / Enseñanza para la comprensión y deporte escolar: un estudio en contexto intercultural y situación de riesgo social

Abstract This study analyses the integration of Mapuche-Huilliche students who participate in a school sport programme based on the teaching for understanding model in a situation of social risk. In this context, 41 students (aged nine to 12) participate, 24 of whom are from the aforementioned ethnic group. To collect data, participant observation was conducted for eight months and group and individual interviews were held. The results show that the Mapuche-Huilliche students recognize themselves as members of the same collective when participating in games associated with their ethnic group. Their main motives for participating in school sport are the teaching approach and the acquisition of social capital. Cooperative learning activities are shown to foster positive interactions with non-Mapuche students.
IPMC actuator-based an underwater microrobot with 8 legs

Biomimetic microrobot and micro biped robot with multi DOF that can swim smoothly in water or aqueous medium has urgently been demanded in the medical field and industry application. The IPMC (Ionic Polymer Metal Composite) has a good response and soft characteristic. Also it can generate large bending motions under a low driving voltage (about 1 V). In order to resolve the problems of asymmetry in former microrobot, we have developed a new underwater microrobot with 8 IPMC actuators as legs. In addition, we have proposed a concept of biomimetic microrobot consisted of a body and a base. The base has 8 legs, which can walk forward and back. Also it can rotate to change its walking direction. The body is made of rubber material shaped as a hemisphere. SMA actuators are used in the body. It has a movement process as the jellyfish does when it is floating and sinking. The process of floating and sinking can be controlled. Characteristic of the base and the body is measured respectively. The simulation of walking and rotating process of the base is also done in the following. Some improvement has been done for higher efficiency.
Thesis for the Degree of Doctor of Philosophy Understanding Attention Selection in Driving from Limited Capacity to Adaptive Behaviour Understanding Attention Selection in Driving: from Limited Capacity to Adaptive Behaviour Understanding Attention Selection in Driving: from Limited Capacity to Adap

Accident analysis studies have consistently identified attention-related failures as key factors behind road crashes. However, less is known about how such failures lead to accidents. Traditionally, one reason for this knowledge gap has been a lack of sufficiently detailed data from the pre-crash phase, although this situation is currently changing with the advent of naturalistic driving studies. However, a remaining issue is the lack of an adequate conceptual model of attention selection applicable in natural driving situations. Existing attention models applied in the driving domain are generally based on the notion of attention as a resource with limited capacity, subject to overload in demanding conditions. Such models have mainly focused on dual task interference in experimental situations and but have put less emphasis on aspects central to attention selection in everyday driving such as expectancy and anticipatory attention allocation. The general objective of the present thesis was to obtain a better understanding of the relation between attention, performance and crash risk in real driving situations. To this end, a general conceptual framework for understanding attention selection in natural driving was developed, based on the view of attention selection as a form of adaptive behaviour rather than a consequence of limited information processing capacity. This also involved the development of a specific model of attention selection mechanisms and a series of empirical studies to support the model development. The main objective of these studies was to better understand the effects of working memory (or cognitive-) load on driving performance and the key mechanisms behind expectancy and proactive attention scheduling in driving. A key finding was that working memory load appears to selectively affect aspects of driving performance that can be characterised as controlled, while leaving reflexive and habitual, automatic, behaviours largely unaffected, an idea that resolves several inconsistent findings in the existing literature. Based on the proposed model, precise definitions of attention, expectancy, driver inattention and driver distraction were proposed. The thesis also suggests a general conceptualisation of the relation between attention selection and crashes. Finally, practical applications of the present findings in the areas of accident and incident analysis, countermeasure development and evaluation methods are discussed. Contribution: The experimental design and planning was worked out jointly with other partners in the HASTE project. Engström conducted the statistical analysis of the driving performance and eye movement data from the fixed-base simulator study and wrote the paper. Contribution: The study was designed …
Maternal Cocaine Administration in Mice Alters DNA Methylation and Gene Expression in Hippocampal Neurons of Neonatal and Prepubertal Offspring

Previous studies documented significant behavioral changes in the offspring of cocaine-exposed mothers. We now explore the hypothesis that maternal cocaine exposure could alter the fetal epigenetic machinery sufficiently to cause lasting neurochemical and functional changes in the offspring. Pregnant CD1 mice were administered either saline or 20 mg/kg cocaine twice daily on gestational days 8–19. Male pups from each of ten litters of the cocaine and control groups were analyzed at 3 (P3) or 30 (P30) days postnatum. Global DNA methylation, methylated DNA immunoprecipitation followed by CGI2 microarray profiling and bisulfite sequencing, as well as quantitative real-time RT-PCR gene expression analysis, were evaluated in hippocampal pyramidal neurons excised by laser capture microdissection. Following maternal cocaine exposure, global DNA methylation was significantly decreased at P3 and increased at P30. Among the 492 CGIs whose methylation was significantly altered by cocaine at P3, 34% were hypermethylated while 66% were hypomethylated. Several of these CGIs contained promoter regions for genes implicated in crucial cellular functions. Endogenous expression of selected genes linked to the abnormally methylated CGIs was correspondingly decreased or increased by as much as 4–19-fold. By P30, some of the cocaine-associated effects at P3 endured, reversed to opposite directions, or disappeared. Further, additional sets of abnormally methylated targets emerged at P30 that were not observed at P3. Taken together, these observations indicate that maternal cocaine exposure during the second and third trimesters of gestation could produce potentially profound structural and functional modifications in the epigenomic programs of neonatal and prepubertal mice.
Adaptive Hybrid Semantic Selection of SAWSDL Services with SAWSDL-MX2

In this paper, the authors present an adaptive, hybrid semantic matchmaker for SAWSDL services, called SAWSDL-MX2. It determines three types of semantic matching of an advertised service with a requested one, which are described in standard SAWSDL: logic-based, text-similarity-based and XML-tree edit-based structural similarity. Before selection, SAWSDL-MX2 learns the optimal aggregation of these different matching degrees off-line over a random subset of a given SAWSDL service retrieval test collection by exploiting a binary support vector machine-based classifier with ranking. The authors present a comparative evaluation of the retrieval performance of SAWSDL-MX2.
Face Recognition Based on an Alternative Formulation of Orthogonal LPP

In this paper, an alternative formulation of orthogonal locality preserving projections (OLPP) is proposed. Schur-OLPP introduces Schur decomposition in locality preserving projections (LPP) to get the orthogonal vectors and extracts discriminant features. The proposed method was tested and evaluated using the Yale and AR face databases. Recognition rates were compared with Eigenface, Fisherface and Laplacianface. Experimental results indicated the promising performance of the proposed method.
A case study of the task-based parallel wavefront pattern

This paper analyzes the applicability of the task-programming model to the parallelization of the wavefront pattern. Computations for this type of problem are characterized by a data dependency pattern across a data space. This pattern can produce a variable number of independent tasks through traversing this space. Different implementations of this pattern are studied based on the current state-of-theart threading frameworks that support tasks. For each implementation, the specific issues are discussed from a programmer’s point of view, highlighting any advantageous features in each case. In addition, several experiments are carried out, and the factors that can limit performance in each implementation are identified. Moreover, some optimizations that the programmer can exploit to reduce overheads (task recycling, prioritization of tasks based on locality hints and tiling) are proposed and
Enhancing Fault / Intrusion Tolerance through Design and Configuration Diversity

Fault/intrusion tolerance is usually the only viable way of improving the system dependability and security in the presence of continuously evolving threats. Many of the solutions in the literature concern a specific snapshot in the production or deployment of a fault-tolerant system and no immediate considerations are made about how the system should evolve to deal with novel threats. In this paper we outline and evaluate a set of operating systems’ and applications’ reconfiguration rules which can be used to modify the state of a system replica prior to deployment or in between recoveries, and hence increase the replicas chance of a longer intrusion-free operation.
ExecScent: Mining for New C&C Domains in Live Networks with Adaptive Control Protocol Templates

In this paper, we present ExecScent, a novel system that aims to mine new, previously unknown C&C domain names from live enterprise network traffic. ExecScent automatically learns control protocol templates (CPTs) from examples of known C&C communications. These CPTs are then adapted to the "background traffic" of the network where the templates are to be deployed. The goal is to generate hybrid templates that can self-tune to each specific deployment scenario, thus yielding a better trade-off between true and false positives for a given network environment. To the best of our knowledge, ExecScent is the first system to use this type of adaptive C&C traffic models. We implemented a prototype version of ExecScent, and deployed it in three different large networks for a period of two weeks. During the deployment, we discovered many new, previously unknown C&C domains and hundreds of new infected machines, compared to using a large up-to-date commercial C&C domain blacklist. Furthermore, we deployed the new C&C domains mined by ExecScent to six large ISP networks, discovering more than 25,000 new infected machines.
Bridging DBpedia Categories and DL-Concept Definitions Using Formal Concept Analysis

The popularization and quick growth of Linked Open Data (LOD) has led to challenging aspects regarding quality assessment and data exploration of the RDF triples that shape the LOD cloud. Particularly, we are interested in the completeness of data and its potential to provide concept definitions in terms of necessary and sufficient conditions. In this work we propose a novel technique based on Formal Concept Analysis which organizes RDF data into a concept lattice. This allows the discovery of implications, which are used to automatically detect missing information and then to complete RDF data.
The Oncoprotein SS18-SSX1 Promotes p53 Ubiquitination and Degradation by Enhancing HDM2 Stability

Mutations of the p53 gene are uncommon in synovial sarcoma, a high-grade tumor genetically characterized by the chromosomal translocation t:(X;18), which results in the fusion of SS18 with members of SSX gene family. Although implicated in tumorigenesis, the mechanisms by which SS18-SSX promotes tumor growth and cell survival are poorly defined. Here, we show that SS18-SSX1 negatively regulates the stability of the tumor suppressor p53 under basal conditions. Overexpression of SS18-SSX1 enhanced p53 ubiquitination and degradation in a manner dependent on the ubiquitin ligase activity of HDM2. The negative effect of SS18-SSX1 expression on p53 was mediated by its ability to promote HDM2 stabilization through inhibition of HDM2 autoubiquitination. Furthermore, SS18-SSX1 expression altered the induction of p53-regulated genes in response to cellular stress by abrogating the transactivation of HDM2, PUMA, and NOXA but not p21. Our data uncover a novel mechanism whereby SS18-SSX1 can negatively regulate p53 tumor-suppressive function by increasing the stability of its negative regulator HDM2 and suggest that chemical compounds that target the p53-HDM2 regulatory axis may be of therapeutic benefit for the treatment of synovial sarcoma. (Mol Cancer Res 2008;6(1):127–38)
Real-time UML-based performance engineering to aid manager's decisions in multi-project planning

We investigate the usage of software performance engineering to aid the project manager in making sound, reliable predictions in software development, and in optimizing the utilization of resources (typically the people). We assimilate the project teams to the processing elements of a performance model, and their activities to the tasks to be accomplished within established time intervals. The proposed methodology uses as the manager's interface a subset of Real-Time UML, the recently adopted OMG standard specialized profile for addressing schedulability, performance and timeliness. To illustrate the approach, we model the case of a manager that must decide a release date for a product undergoing the testing phase. We show how, by means of basic performance analyses, different workflow assumptions can be explored and their consequent outcomes automatically derived: by looking at the analysis results, the manager can thus take an informed, more responsible decision.
USING LINKED OPEN DATA FOR NOVEL ARTIST RECOMMENDATIONS

As part of the Linking Open Data initiative many (community) platforms have made their data freely available in recent years. In these systems valuable information from the music domain can be found. We use this data for contentbased music recommendations thus not requiring expensive metadata annotations from domain experts. In this demo paper we present a system that uses data from the Freebase platform to describe music artists. The artists are represented using metadata profiles that characterize different aspects of their works such as genres and instrumentations but also collaborations with other artists. The system uses a Lucene index for content-based artist recommendations aiming at Web-scalability.
Functional analysis of desmoplakin domains: specification of the interaction with keratin versus vimentin intermediate filament networks

We previously demonstrated that truncated desmoplakin I (DP I) molecules containing the carboxyl terminus specifically coalign with and disrupt both keratin and vimentin intermediate filament (IF) networks when overexpressed in tissue culture cells (Stappenbeck, T. S., and K. J. Green. J. Cell Biol. 116:1197-1209). These experiments suggested that the DP carboxyl-terminal domain is involved either directly or indirectly in linking IF with the desmosome. Using a similar approach, we have now investigated the behavior of ectopically expressed full-length DP I in cultured cells. In addition, we have further dissected the functional sequences in the carboxyl terminus of DP I that facilitate the interaction with IF networks. Transient transfection of a clone encoding full-length DP I into COS-7 cells produced protein that appeared in some cells to associate with desmosomes and in others to coalign with and disrupt IF. Deletion of the carboxyl terminus from this clone resulted in protein that still appeared capable of associating with desmosomes but not interacting with IF networks. As the amino terminus appeared to be dispensable for IF interaction, we made finer deletions in the carboxyl terminus of DP based on blocks of sequence similarity with the related molecules bullous pemphigoid antigen and plectin. We found a sequence at the very carboxyl terminus of DP that was necessary for coalignment with and disruption of keratin IF but not vimentin IF. Furthermore, the coalignment of specific DP proteins along keratin IF but not vimentin IF was correlated with resistance to extraction by Triton. The striking uncoupling resulting from the deletion of specific DP sequences suggests that the carboxyl terminus of DP interacts differentially with keratin and vimentin IF networks.
Admission control and routing in ATM networks using inferences from measured buffer occupancy

Addresses the issue of call acceptance and routing in ATM networks. The goal is to design an algorithm that guarantees bounds on the fraction of cells lost by a call. The method proposed for call acceptance and routing does not require models describing the traffic. Each switch estimates the additional fraction of cells that would be lost if new calls were routed through the switch. The routing algorithm uses these estimates. The estimates are obtained by monitoring the switch operations and extrapolating to the situation where more calls are routed through the switch. The extrapolation is justified by a scaling property. To reduce the variance of the estimates, the switches calculate the cell loss that would occur with virtual buffers. A way to choose the sizes of the virtual buffers in order to minimize the variance is discussed. Thus, the switches constantly estimate their spare capacity. Simulations were performed using Markov fluid sources to test the validity of the approach. >
Inverse Kinematics Kicking in the Humanoid RoboCup Simulation League

This paper describes the inverse kinematics kicking system used in UT Austin Villa’s submission to the humanoid RoboCup simulation league competition. It describes the infrastructure we designed and how machine learning is used to optimize a set of kicks with the hope of developing a versatile and omnidirectional kick. As of now, the ability to kick has not substantially affected the outcome of the 3D simulation competition as walk speed and dribbling have been the main focus and the strongest factors in a team’s ability to do well competitively. The underlying goal is to create a set of kicks that can be optimized using machine learning to be faster to align but that can achieve similar distance and accuracy to fix keyframe based skills. To evaluate this goal we look to test the kick over many iterations against varied opponents and situations. We hypothesize that it is possible to create an abstracted representation of skills such as kicking through the use of inverse kinematics based curves that while simultaneously achieving the performance goals we pose and allowing a much simpler human interaction with the system.
Sparse Representations and Invariant Sequence-feature Extraction for Event Detection

We address the problem of detecting unusual actions performed by a human in a video. Broadly speaking, we achieve our goal by matching the observed action to a set of a-priori known actions. If the observed action can not be matched to any of the known actions (representing the normal case), we conclude that an event has taken place. In this contribution we will show how sparse representations of actions can be used for event detection. Our input data are video sequences showing different actions. Special care is taken to extract features from these sequences. The features are chosen such that the sparse-representations paradigm can be applied and they exhibit a set of invariance properties needed for detecting unusual human actions. We test our methods on sequences showing different people performing various actions such as walking or running.