Miracle-dz/UniFAR-FTUs huggingface dataset:
Normobaric Hypoxia as a Cognitive Stress Test for Mild Traumatic Brain Injury: Oculometrics, Pulse Oximetry, and the Self Report of Symptom Severity

Abstract : The present report describes research assessing the effects mild hypoxia has on individuals with a medical history of mild traumatic brain injury (mTBI). The research tests the hypothesis that individuals who have a history of mTBI but who are asymptomatic may have latent deficits that become apparent in the presence of relatively minor physiological stressors routinely encountered by military personnel or by civilians during normal daily activities. The research used a minor, altitude-referenced hypoxic challenge as a prototypical physiological stressor. The present report describes the methodology used to generate the hypoxic challenge as well as the experimental design and procedures. Two groups of 36 subjects were studied; one group with a history of mTBI and one group with no such history. The report describes the characteristics of the study volunteers who were matched on the basis of such variables as age, gender, body mass index, and smoking behavior. The response parameters included oculometric, pulse rate, pulse oximetry, a self-report inventory of subjective symptoms, and neurocognitive assessments. The present report provides an extensive tabulation of the oculometric, pulse rate, pulse oximetry and inventory of subjective symptoms data as well as statistical summaries of these data and initial analyses. These initial analyses suggest that the oculometric instrumentation used in this study was insufficiently sensitive to expected differences whereas the pulse rate, pulse oximetry, and symptom severity data warrant further detailed analysis. A separate report addresses the neurocognitive assessments.
UvA-DARE ( Digital Academic Repository ) Effects of hypertext writing and observational learning on content knowledge acquisition , self-efficacy , and text quality : Two experimental studies exploring aptitude treatment interactions

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CS 224 N Final Project : Unsupervised Clustering of People , Places , and Organizations in Wikileaks Cables with NLP Cues

Our goal is to extract the names of key entities from written U.S. diplomatic communications and then to apply natural-languageand sentiment-based clustering to these entities using contextual features extracted from the data. We extract entities using an off-the-shelf statistical NLP package, and then seek to generate meaningful clusters of entities in an unsupervised fashion. To do so, we experiment with different models, feature sets, and clustering algorithms. For the purposes of this project, we define key entities to be people, nations, and organizations that occur at least k times in the dataset. We determined k through empirical evaluation of the entities extracted from the data, and also the need of different scenarios.
Analysis, design and control of a planar micro-robot driven by two centripetal-force actuators

This paper presents the motion analysis, design and position control of a novel, low cost, sliding micro-robot, which is actuated by centripetal forces generated by robot mounted vibration micro-motors. A new, two-micromotor design of the platform is presented, that improves system energy efficiency, and further does not necessitate for synchronous actuator operation and robot symmetry. The motion behavior of the micro-robot, for asynchronous actuation operation, is expressed analytically and simulation results are presented. A control strategy for microrobot x,thetasz, position control that employs two motor speed controllers, and a platform position controller is designed. The control system performance is evaluated through the simulation of a successful trajectory tracking task. A prototype of the micro-robot has been constructed and is presented
Interactive Solid Texturing using Point-based Multiresolution Representations

This paper presents an interactive environment for texturing surfaces of arbitrary 3D objects. By uniquely using solid textures and applying them to the surface, we do not require an explicit parameterisation in texture space. Various solid textures can be combined by building a constructive texturing tree of space partitions to define the photometric attributes at each location of the object. Though solid texturing using constructive textures is very powerful, mainly because of its generality, it is quite difficult to use in practice as it is not well suited to interactive tools. To overcome this limitation, we use a multiresolution point-based representation ensuring that texture evaluation and rendering maintains a given frame rate. Our tool is realized as a plugin for the Pointshop3D system. The main advantage of our texturing approach compared to Pointshop3D is that point-based rendering is only used during the interactive texturing step. We always keep a feedback to the initial geometric representation of the object (polygonal mesh, parametric or implicit surface, voxel arrays, or whatever) which means that the final textured object can be easily exported to standard graphics software that cannot directly handle discrete surface points (e.g. CAD systems, photorealistic rendering engines).
Altered serum creatine kinase level and cardiac function in ischemia-reperfusion injury during percutaneous coronary intervention

Summary Background Myocardial ischemia-reperfusion injury (MIRI) resulting from primary percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI) is considered harmful to the patient, but its clinical significance remains unclear. This study explored the relationship of cardiac function examined by echocardiography and serum creatine kinase (CK) and CK-MB levels with MIRI in a cohort of Chinese AMI patients. Material/Methods We retrospectively analysed the clinical and angiographic data in 228 AMI patients in whom the infarct-related artery (IRA) was successfully recanalized by primary PCI. Cardiac function was evaluated by use of echocardiography before discharge from hospital. Results The in-hospital mortality rate in the MIRI group was 13.4% (16/119), which was significantly higher than the 4.6% (5/109) mortality rate in the non-MIRI group (P=0.021). The median of peak serum CK level was remarkably lower in the suppression-type MIRI group than in the non-MIRI group. There were no significant differences in the peak serum CK or CK-MB levels between the irritation-type MIRI group and the non-MIRI group. The peak CK and CK-MB levels were significantly higher in the no-reflow-type MIRI group than in the non-MIRI group. Left ventricular ejection fraction in the no-reflow-type MIRI group was significantly lower than in the non-MIRI group; left ventricular end-diastolic volume was significantly higher than in the irritation-type MIRI subgroup; and left ventricular end-systolic volume was greater than that in non-MIRI group and suppression-type MIRI group. Conclusions MIRI (especially the no-reflow type) may lead to acute hemodynamic disorders and increase the mortality rate. However, suppression- and irritation-type MIRI may imply the existence of surviving myocardium.
Optimal Parallel Hardware K-Sorter and Top K-Sorter, with FPGA Implementations

This paper presents a FIFO-based parallel merge sorter optimized for the latest FPGA. More specifically, we show a sorter that sorts K keys in latency K+log2 K-1 using log2 K comparators. It uses K/M +log2 K +log2 M-1 memory blocks with capacity M to implement FIFOs. It receives K keys one by one in every clock cycle and outputs the sorted sequence of them from K + log2 K - 1 clock cycles after. Since K clock cycles are necessary to input all K keys, our sorter is almost optimal in terms of the latency. Also, since the total FIFO capacity is only K +M log2 K +M log2 M -M and at least K keys must be stored in the sorter, our sorter is also almost optimal in terms of the total FIFO capacity if M is small. This paper also presents top K-sorter, which outputs top K keys in N input keys for any large N. Our top K-sorter runs in latency N + log2 K using log2 K + 1 comparators. It uses memory blocks of size M and the total FIFO capacity is only 2K+M log2 K +M log2 M - 2M. Quite surprisingly, the total FIFO capacity is independent of N. Also, since the latency must be at least N, that of our top Ksorter is almost optimal in terms of the latency. Finally, we have implemented our K-sorter and top K-sorter in a Xilinx Virtex-7 FPGA using built-in Distributed RAMs and Block RAMs. The implementation results show that our K-sorter reduces the used memory resources by half, and both K-sorter and top K-sorter are practical and efficient.
The mCRL 2 toolset

We describe the toolset for the behavioural specification language mCRL2. The purpose of the toolset is to analyse abstract models that describe the communication behaviour of software based systems. With the help of the toolset we want to efficiently detect and prevent problems in software, preferably before it is built. The tools allow to transform specifications, generate and visualise state spaces, verify modal properties, and much more. In order to facilitate reuse of the code most of the functionality is included in libraries. This makes the toolset suitable as a platform for third party tool development and for other specification languages as well. The toolset is distributed under the Boost license, which permits such use.
Segmentation of Aerial Surveillance Video Using a Mixture of Experts

In recent years, aerial video surveillance has proved to be an effective way to collect information for a variety of applications including military operations, law-enforcement activities, disaster management and commercial applications. In order to keep pace with the growing demand for aerial surveillance, a vast amount of aerial video needs to be processed automatically. In particular, objects and regions in aerial videos need to be segmented and labeled to enable other automated video processing, such as event detection, summarization, indexing and high level aerial video understanding. In this paper, we propose a video segmentation algorithm for aerial surveillance video. The algorithm uses a Mixture of Experts (MoE) consisting of a supervised image segmentation algorithm named the Trainable Sequential MAP (TSMAP) segmentation algorithm; the unsupervised mean shift image segmentation algorithm and a moving object detection algorithm. Using domain knowledge from aerial video surveillance, the outputs of the three experts are judiciously combined to generate the final segmentation results. One advantage of our MoE based segmentation algorithm is that it exploits the benefits of each of the experts: the unsupervised segmentation algorithm provides accurate region boundaries; the supervised segmentation algorithm provides semantic labeling for each region using texture information; and the moving object detection algorithm provides a reliable object segmentation using the motion information. We illustrate the efficacy of our approach with aerial surveillance videos containing vehicles, roads, buildings, trees, fields, and shadows.
Social Cognitive Determinants of Dietary Behavior Change in University Employes

Many adults have poor dietary habits and few studies have focused on mechanisms underlying these behaviors. This study examined psychosocial determinants of dietary behavior change in university employes across a 5-month period. Participants completed measures of fruit and vegetable consumption (FVC) and low fat food consumption (LFC) and social cognitive constructs. Multiple regression analyses accounted for a unique proportion of variation in dietary change. Outcome expectations significantly predicted FVC and LFC. Self-efficacy significantly predicted LFC. Goals were not associated with dietary behaviors. Further research into implementation strategies may provide insight into how goals work to bring about change.
Cosy Cognitive Systems for Cognitive Assistants Wp 3.1 Software for Self-insertion Executive Summary Role of Spatial Insertion in Cosy Cosy Fp6-004250 Contents I Software for Self-insertion 4

Sensory data to be dealt with by embodied agents such as considered in CoSy are complex and high dimensional. Navigation, planning and communication systems on the other hand require tractable information as input, since their efficiency often crucially depends on the number of possible situations they have to consider. This imposes as a result to implement modules interfacing low level data acquisition and higher cognitive processing. These modules rely on solutions specifically engineered for the agent's sensory devices and the data format used by defined cognitive functions. But while device dependent solutions ensure a level of efficiency and robustness, they also constrain the possibility of evolution at the perceptual level as the task requirements and sensorimotor competences change, or as the agent's body suffers modifications, changes in environmental conditions or damage. For these reasons the current workpackage investigates the question of an unsupervised and multimodal approach to sensory data analysis, based on the hypothesis that the structure of sensorimotor interactions provides means for such an analysis. This would ultimately lay the ground for a developmental approach to self insertion in space in a way converging to the flexible exploitation of the sensorimotor devices available to the agent. The first 12 months were devoted to the development of software implementing basic requirements for interfacing between sensory data and cognitive functions: dimension reduction, and to the investigation of using similar ideas in a robotic system in a realistic environment. The first part of this report is devoted to the description of the rationale and implementation of the software. We extend the classical framework of dimension reduction to the case where sensory data are acquired through an embodied agent, by grounding the metric at the basis of the reduction in the sensorimotor abilities of the agent. The objective of the workpackage is then to build on this to provide the demonstration of some basic unsupervised learning of interactions with space and objects. The second part of this report describe the current status of the work done in that direction. The software provides several functionalities for the local analysis of sensory data: it can estimate a code independent distance between sensory data, suggest actions to be taken so as to link neighbouring sensory configurations, and decompose possible sensory variations into sets of variations with structurally different properties. Additionally, it can provide a local flattening of the sensory manifold and therefore it can be used …
The effects of maternal deprivation on problem behavior in post-institutionalized children [electronic resource] /

THE EFFECTS OF MATERNAL DEPRIVATION ON PROBLEM BEHAVIOR IN POST-INSTITUTIONALIZED CHILDREN by Jacquelyn Sue Pennings, M.S., 2005 Department of Psychology Texas Christian University Thesis Advisor: David Cross, Professor of Psychology Children adopted from institutions may experience serious behavior problems once placed with their adoptive families. The current research seeks to illuminate this process by addressing two questions: 1) Do attachment and sensory integration mediate the impact of maternal deprivation on child behavior problems? and 2) Do attachment and sensory integration make independent contributions to the prediction of behavior problems in post-institutionalized children? Data were collected as part of a therapeutic summer camp for children (N = 49) adopted from institutions in other countries. Results indicate that attachment did weakly mediate the impact of maternal deprivation on child behavior problems. Further, we found attachment and sensory integration problems independently predicted child behavior problems. Mechanisms, limitations and ideas for future research are discussed.
On Plumbed L-spaces

L-spaces were introduced by Ozsvath and Szabo using the Heegaard Floer Homology. In the quest for L-spaces we consider links of isolated complete intersection surface singularities. We show that if such a manifold is an L-space, then it is a link of a rational singularity. We also prove that if it is not an L-space then it admits a symplectic filling with $b_2^+>0$. Based on these results we pin down all integral homology sphere L-spaces in this realm.
The lifted wavelet transform for encephalic signal compression

The compression of Electroencephalographic (EEG) signal is of great interest to many in the biomedical community. The motivation for this is the large amount of data involved in collecting EEG information which requires more memory for storage and high bandwidth for transmission. This work shows the contribution of biomedical signal processing by lifted wavelet transform LWT, in the field of encephalic signal compression. Our results show a high performance compression for normal and pathological EEG. A statistical study on a set of 200 signals healthy and epileptic, confirms these results. The choice of wavelet rbior 5.5 is best suited to the shape of the EEG signal, it allows to increasing the compression ratio and to ensuring a safe recovery. The increase, in the level decomposition and the threshold, allows to increasing the compression ratio while keeping a good performance of reconstitution. Our study allows us to choose the LWT rbio5.5 as tool for encephalic signal compression with a compression ratio of 83.16% and a recovery rate of 99.95%.
Optimal Cognitive Beamforming for Target Tracking in MIMO Radar/Sonar

In this paper, a cognitive beamforming method for target tracking by multiple-input multiple-output (MIMO) radar or sonar is proposed. In this method, at each step, the transmit beampattern is sequentially determined based on history observations. The conditional Bayesian Cramér-Rao bound (BCRB) for one-step prediction of the state-vector in target tracking problem was used as the optimization criterion for beampattern design. The proposed method is applied to the problem of target tracking in a shallow underwater environment in the presence of environmental uncertainties. It is shown that the method is able to automatically focus the transmit beampattern toward the target direction within a few steps at very low signal-to-noise ratios (SNRs). The method exhibits much better performance in terms of localization estimation error compared to other methods, such as orthogonal (omnidirectional) transmission.
Cooperation for transmission scheduling in wireless networks

We study the use of node cooperation as a way to improve performance in multiple-source, single-destination wireless networks that use scheduled access as the channel-access method. Unlike many other studies of scheduled access, which are based on the use of a collision channel, we use a physical channel model that incorporates other-user interference, fading, and background noise. The characteristics of such channels are exploited to enable the successful reception of multiple packets simultaneously. Our primary performance measure is throughput, which is the average number of packets that are successfully received by the destination per time slot. First, we study the performance of transmission schedules, which depends on channel fading, receiver noise, and interference. We then show that a cooperative strategy, based on the introduction of a relay to assist unsuccessful source nodes, can improve the throughput.
Application of Computer Modelling in Predicting Endocrine Disrupting Chemicals Functions

Crystal structures of proteins are necessary in controlling the mechanism between Endocrine Disrupting Chemicals and protein receptors. However there lacks the researches protein structures delay. The strategy of computing including homology modelling and docking method can be used to fill up the gap. Up to now, homology modelling is the best way to obtain useful structures. Meanwhile docking is used in protein ligand researches. The corresponding computational tools are helpful to carry on the research on the endocrine disrupting mechanism which is triggered by receptor ligand interaction.
Accommodating Workload Diversity in Chip Multiprocessors via Adaptive Core Fusion

This paper presents core fusion, a reconfigurable chip multiprocessor (CMP) architecture where groups of fundamentally independent cores can dynamically morph into a large execution engine, or they can be used as distinct processing elements, as needed at run time by applications. Core fusion gracefully accommodates workload diversity and incremental parallelization in CMPs. It requires no additional programming effort or specialized compiler support, maintains ISA compatibility, and keeps both hardware and software complexity manageable. Our evaluation pits core fusion against more traditional homogeneous and asymmetric CMP architectures and shows that, when confronted with workload diversity, core fusion is the only architecture evaluated in the paper that is consistently at or near the top performance level, whereas every other architecture lags significantly behind in at least one scenario.
Reduced Dimensionality Extended Kalman Filter for SLAM

Computational complexity of the Kalman filter grows at least quadratically with the number of dimensions in the filter. This is a particular problem for applications like monocular simultaneous localization and mapping (SLAM) where it is not possible to run a single filter on a large map with many thousands of landmarks. The filtering approach for SLAM, maintains only the current camera pose with all landmarks of interest as the state [2]. This paper presents a method for reducing the computational complexity of the Kalman filters by reducing the dimensionality as information is acquired. The method reduces the dimensionality of the extended Kalman filter (EKF) for SLAM by identifying dominant modes of the filter. This can be used in general to reduce the dimensionality of the EKF irrespectively of its application, without being limited to SLAM. For a filter with zero process noise, the mean of this distribution can be represented as a point in a nD space with its uncertainty as a hyper ellipse. Further information will reduce this uncertainty along some directions. After some time uncertainty along many directions becomes comparatively small, making further information redundant. So the covariance matrix can be decompose into certain and uncertain dimensions.
Developmental origin of wiring specificity in the olfactory system of Drosophila

In both insects and mammals, olfactory receptor neurons (ORNs) expressing specific olfactory receptors converge their axons onto specific glomeruli, creating a spatial map in the brain. We have previously shown that second order projection neurons (PNs) in Drosophila are prespecified by lineage and birth order to send their dendrites to one of ∼50 glomeruli in the antennal lobe. How can a given class of ORN axons match up with a given class of PN dendrites? Here, we examine the cellular and developmental events that lead to this wiring specificity. We find that, before ORN axon arrival, PN dendrites have already created a prototypic map that resembles the adult glomerular map, by virtue of their selective dendritic localization. Positional cues that create this prototypic dendritic map do not appear to be either from the residual larval olfactory system or from glial processes within the antennal lobe. We propose instead that this prototypic map might originate from both patterning information external to the developing antennal lobe and interactions among PN dendrites.