Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximal aerobic and anaerobic exercise responses in children with cerebral palsy.

PURPOSE The objective of this study is to compare the maximal aerobic and anaerobic exercise responses of children with cerebral palsy (CP) by level of motor impairment and in comparison with those of typically developing children (TD). METHODS Seventy children with CP, with varying levels of motor impairment (Gross Motor Function Classification System (GMFCS) I-III), and 31 TD performed an incremental continuous maximal aerobic exercise test and a 20-s anaerobic Wingate test on a cycle ergometer. Peak oxygen uptake (V˙O2peak), anaerobic threshold (AT), peak ventilation (V˙Epeak), peak oxygen pulse (peak O2 pulse), peak ventilatory equivalent of oxygen (peak V˙E/V˙O2) and carbon dioxide (peak V˙E/V˙CO2), peak aerobic power output (POpeak), and mean anaerobic power (P20mean) were measured. Isometric leg muscle strength was determined as a secondary outcome. RESULTS Analysis revealed a lower V˙O2peak for CP (I: 35.5 ± 1.2 (SE); II: 33.9 ± 1.6; III: 29.3 ± 2.5 mL·kg-1·min-1) compared with TD (41.0 ± 1.3, P < 0.001) and a similar effect for AT (I: 19.4 ± 0.9; II: 19.2 ± 1.2; III: 15.5 ± 1.9; TD: 24.1 ± 1.0 mL·kg-1·min-1, P < 0.001). V˙Epeak and peak O2 pulse were also lower, whereas peak V˙E/V˙CO2 was higher in CP compared with TD (P < 0.05) and peak V˙E/V˙O2 similar between groups. All these variables showed no differences for different motor impairment levels. POpeak was lower for CP (I: 2.4 ± 0.1; II: 1.8 ± 0.1; III: 1.4 ± 0.2 W·kg-1) versus TD (3.0 ± 0.1, P < 0.001), together with a lower P20mean in CP (I: 4.6 ± 0.2; II: 3.3 ± 0.2; III: 2.5 ± 0.4 W·kg-1) versus TD (6.4 ± 0.2, P < 0.001), and both decreased significantly with increasing motor impairment. CONCLUSION Children with CP have decreased aerobic and anaerobic exercise responses, but decreases in respiratory and aerobic exercise responses were not as severe as predicted by motor impairment. Future research should reveal the role of inactivity on the exercise responses of children with CP and possibilities for improvement through training interventions.
Role of Rac1 GTPase in NADPH Oxidase Activation and Cognitive Impairment Following Cerebral Ischemia in the Rat

Background Recent work by our laboratory and others has implicated NADPH oxidase as having an important role in reactive oxygen species (ROS) generation and neuronal damage following cerebral ischemia, although the mechanisms controlling NADPH oxidase in the brain remain poorly understood. The purpose of the current study was to examine the regulatory and functional role of the Rho GTPase, Rac1 in NADPH oxidase activation, ROS generation and neuronal cell death/cognitive dysfunction following global cerebral ischemia in the male rat. Methodology/Principal Findings Our studies revealed that NADPH oxidase activity and superoxide (O2 −) production in the hippocampal CA1 region increased rapidly after cerebral ischemia to reach a peak at 3 h post-reperfusion, followed by a fall in levels by 24 h post-reperfusion. Administration of a Rac GTPase inhibitor (NSC23766) 15 min before cerebral ischemia significantly attenuated NADPH oxidase activation and O2 − production at 3 h after stroke as compared to vehicle-treated controls. NSC23766 also attenuated “in situ” O2 − production in the hippocampus after ischemia/reperfusion, as determined by fluorescent oxidized hydroethidine staining. Oxidative stress damage in the hippocampal CA1 after ischemia/reperfusion was also significantly attenuated by NSC23766 treatment, as evidenced by a marked attenuation of immunostaining for the oxidative stress damage markers, 4-HNE, 8-OHdG and H2AX at 24 h in the hippocampal CA1 region following cerebral ischemia. In addition, Morris Water maze testing revealed that Rac GTPase inhibition after ischemic injury significantly improved hippocampal-dependent memory and cognitive spatial abilities at 7–9 d post reperfusion as compared to vehicle-treated animals. Conclusions/Significance The results of the study suggest that Rac1 GTPase has a critical role in mediating ischemia/reperfusion injury-induced NADPH oxidase activation, ROS generation and oxidative stress in the hippocampal CA1 region of the rat, and thus contributes significantly to neuronal degeneration and cognitive dysfunction following cerebral ischemia.
Reuse In Modelling Instructional Design

Instructional Design (ID) is a difficult task. Even when formal design methods may help in this task, most critical design decisions or knowledge remain undocumented making reuse a difficult task. Case-based scenarios, which contain captured data and knowledge during each ID instance, simulate real-life and provide a basis for reuse of best inherent knowledge in these scenarios to scaffold designers or instructors to reach better ID decisions and consequently to create learning materials, which meet diverse students' needs.
Improving Channel Estimation in Power Line Communications by using Linear Interpolation Revitalized

The power line channel can be considered, from a physical point of view, as a multipath channel due to the numerous reflections created by the impedance mismatches. The channel is stationary piecewise with sudden variations. Pilot symbol assisted modulation (PSAM), combined with interpolation techniques, is used for channel estimation. In this paper, we use a new linear interpolation method that improves the performances of the standard linear interpolation.
A Novel Convolution Kernel Model for Chinese Relation Extraction Based on Semantic Feature and Instances Partition

Relation extraction is an important part of the information extraction. Nowadays, researches focus on tree kernels based solutions that employ different tree structures and kernel functions. since those solutions fail to employ semantic feature effectively and have a low Recall, this paper proposes a novel convolution kernel model based on semantic feature and instances partition. This model involves synonym information as a node in a parse tree, varies partial trees as instances partition and uses the convolution tree kernel function for similarity calculation which outputs data for SVM classifier. the experimental results show that the uses of synonyms and instances partition improve the performance of relation extraction.
Damped Lyα Absorber at High Redshift: Large Disks or Galactic Building Blocks?

We investigate the nature of the physical structures giving rise to damped Lyα absorption systems (DLAS) at high redshift. In particular, we examine the suggestion that rapidly rotating large disks are the only viable explanation for the characteristic observed asymmetric profiles of low-ionization absorption lines. Using hydrodynamic simulations of galaxy formation in a cosmological context, we demonstrate that irregular protogalactic clumps can reproduce the observed velocity width distribution and asymmetries of the absorption profiles equally well. The velocity broadening in the simulated clumps is the result of a mixture of rotation, random motions, infall, and merging. The observed velocity width correlates with the virial velocity of the dark matter halo of the forming protogalactic clump (Δv ≈ 0.6vvir for the median values, with a large scatter, on the order of a factor of 2, between different lines of sight). The typical virial velocity of the halos required to give rise to the DLAS population is about 100 km s-1, and most standard hierarchical structure formation scenarios can easily account for even the largest observed velocity widths. We conclude that the evidence that DLAS at high redshift are related to large, rapidly rotating disks with vcirc ≳ 200 km s-1 is not compelling.
The redshift distribution of Swift gamma‐ray bursts: evidence for evolution

We predict the redshift distribution of long gamma-ray bursts (GRBs) with Monte Carlo simulations. Our improved analysis constrains free parameters with three kinds of observation: (i) the log N - log P diagram of Burst and Transient Source Experiment (BATSE) bursts; (ii) the peak energy distribution of bright BATSE bursts and (iii) the High Energy Transient Explorer (HETE2) fraction of X-ray rich GRBs and X-ray flashes. The statistical analysis of the Monte Carlo simulation results allows us to carefully study the impact of the uncertainties in the GRB intrinsic properties on the redshift distribution. The comparison with Swift data then leads to the following conclusions. The Amati relation should be intrinsic, if observationally confirmed by Swift. The progenitor and/or the GRB properties have to evolve to reproduce the high mean redshift of Swift bursts. Our results favour an evolution of the efficiency of GRB production by massive stars, that would be nearly six to seven times higher at z ∼ 7 than at z ∼ 2. We finally predict around 10 GRBs detected by Swift at redshift z > 6 for a 3-yr mission. These may be sufficient to open a new observational window over the high redshift Universe.
Final analysis of ELAIS 15-μm observations: method, reduction and catalogue

We present the final analysis of the European Large Area Infrared Space Observatory (ISO) Survey (ELAIS) 15-mum observations, carried out with the ISO Camera (ISOCAM) instrument on board the ISO. The data-reduction method, known as the Lari Method, is based on a mathematical model of the behaviour of the detector and was specifically designed for the detection of faint sources in ISOCAM/ISO Photopolarimeter (ISOPHOT) data. The method is fully interactive and leads to very reliable and complete source lists. The resulting catalogue includes 1923 sources detected with signal-to-noise ratio of >5 in the 0.5-100mJy flux range and over an area of 10.85deg2 split into four fields, making it the largest non-serendipitous extragalactic source catalogue obtained to date from the ISO data. This paper presents the concepts underlying the data-reduction method together with its latest enhancements. The data-reduction process, the production and basic properties of the resulting catalogue are discussed. The catalogue quality is assessed by means of detailed simulations, optical identifications and comparison with previous analyses.
Fast and Accurate Timing Characterization Using Functional Information

In deep submicrometer integrated circuit design, there is a growing need to quickly and accurately characterize the timing of large circuit blocks. Accurate timing characterization requires making available as much timing information as possible at each step of the design process. Conventional fast characterization methods typically employ topological analysis, which can be inaccurate because of its inability to eliminate false paths. To address this problem, a new method for creating accurate timing models of circuit blocks by making efficient use of their functionality is introduced. The proposed mode-dependent characterization (ModeChar) method is based on calculating a distinct timing model for each mode of circuit operation and reflects the way practical circuits function. ModeChar produces a mode-dependent timing model that contains delay information for a given set of circuit modes. It is shown that circuit delays are never underestimated by the mode-dependent models. The concept of mode dependency is taken further by extending it to sequential circuits. Given a sequential circuit, a compact set of constraints is derived for each circuit mode that captures all the timing constraints that must be satisfied for correct operation of the circuit. Experimental results are presented that demonstrate the effectiveness of ModeChar in eliminating many false paths that would otherwise result in performance penalties. In addition, our experiments indicate that delays can vary considerably among circuit modes, making conventional topological analysis overly pessimistic. To make the mode-dependent models more compact, an efficient algorithm for coalescing delay information is also introduced.
Modeling of distortion for arbitrary packet loss patterns in video transmission

This paper proposes an accurate model for predicting the total distortion produced by arbitrary packet loss patterns. The proposed model takes into account the effects of multiple packet losses, and operates with low complexity. It is designed as a general model for different coding characteristics and various packet loss rates. We test the proposed model using H.264/AVC coded video at different loss rates. The experimental results demonstrate that the proposed model achieves higher estimation accuracy compared to the existing additive model.
ECARMI: An Ensemble Based Approach for Medical Images Based Disease  Classification and ROIs Recognition

In this paper, we proposed a novel medical images based computer aided diagnosis method named ECARMI. It combines the cost-sensitive learning with selective ensemble techniques to improve the medical images based diagnosis performance. At first, selective cost-sensitive SVM ensemble is utilized to perform the classification of medical images. Then, the Regions of Interest (ROIs) in positively identified image are identified by using a selective ensemble of cost-sensitive Fuzzy C-Means models. The real dataset based experiments show that, the ECARMI approach not only improved generalization ability but also achieved a satisfactory result in both the accuracy of classification and correctly labeling the ROIs.
Directivity improvement of patch antenna using metamaterial

In this paper, author achieved a very important directivity improvement for a circularly polarized microstrip patch antenna using a new metamaterial structure. To this end, a homogenization procedure of the LHM is carried out in order to design the patch antenna at a suitable frequency where the losses of the LHM are low. From the results, it is noted that in the presence of the LHM, the antenna is more directive and has a higher gain. The metamaterial structure is a combination of hexagonal split ring and pentagonal shapes to form a design which modifies the patch antenna results to require extent i.e. improved directivity. All the designing and simulation work was done in the CST-MWS.
TickTockRay: smartwatch-based 3D pointing for smartphone-based virtual reality

TickTockRay is a smartwatch-based raycasting technique designed for smartphone-based head mounted displays. It demonstrates that smartwatch-based raycasting can be reliably implemented on an off-the-shelf smartphone and may provide a feasible alternative for specialized input devices. We release TickTockRay to the research community as an open-source plugin for Unity along with an example application, a Minecraft VR game clone, that shows the utility of the technique for placement and destruction of Minecraft blocks.
Cognitive rehabilitation in patients with gliomas: a randomized, controlled trial.

PURPOSE Patients with gliomas often experience cognitive deficits, including problems with attention and memory. This randomized, controlled trial evaluated the effects of a multifaceted cognitive rehabilitation program (CRP) on cognitive functioning and selected quality-of-life domains in patients with gliomas. PATIENTS AND METHODS One hundred forty adult patients with low-grade and anaplastic gliomas, favorable prognostic factors, and both subjective cognitive symptoms and objective cognitive deficits were recruited from 11 hospitals in the Netherlands. Patients were randomly assigned to an intervention group or to a waiting-list control group. The intervention incorporated both computer-based attention retraining and compensatory skills training of attention, memory, and executive functioning. Participants completed a battery of neuropsychological (NP) tests and self-report questionnaires on cognitive functioning, fatigue, mental health-related quality of life, and community integration at baseline, after completion of the CRP, and at 6-month follow-up. RESULTS At the immediate post-treatment evaluation, statistically significant intervention effects were observed for measures of subjective cognitive functioning and its perceived burden but not for the objective NP outcomes or for any of the other self-report measures. At the 6-month follow-up, the CRP group performed significantly better than the control group on NP tests of attention and verbal memory and reported less mental fatigue. Group differences in other subjective outcomes were not significant at 6 months. CONCLUSION The CRP has a salutary effect on short-term cognitive complaints and on longer-term cognitive performance and mental fatigue. Additional research is needed to identify which elements of the intervention are most effective.
An Extension for the Univariate Exponentially Weighted Moving Average Control Chart

The univariate Exponentially Weighted Moving Average (EWMA) control chart, which will be called the EWMA chart hereafter is a good alternative to the Shewhart control chart when one is interested in detecting small shifts quickly. The performance of the EWMA control chart is comparable to that of the cumulative sum (CUSUM) control chart but the former is easier to set up and operate. In this paper, an approach by means of transformation of using the EWMA chart in a multivariate process monitoring will be discussed. Keywords: EWMA; CUSUM; MEWMA; Hotelling; noncentrality parameter; mean vector; covariance matrix; average run length; in-control; out-of-control
Adeno-associated virus-mediated delivery of glial cell line-derived neurotrophic factor protects motor neuron-like cells from apoptosis

Motor neuron disorders including amyotrophic lateral sclerosis may benefit from the induction of neurotrophic factors such as glial cell line-derived neurotrophic factor (GDNF) that are known to be trophic and protective for motor neurons. However, the application of such factors is limited by an inability to successfully target their expression in the nervous system. In this study we investigate the potential of using adeno-associated virus (AAV) as a vector for gene delivery into motor neuron-like cells. In initial experiments on the motor neuron cell line NSC-19 using a recombinant AAV vector expressing the reporter gene β-galactosidase (AAV-LacZ), we successfully demonstrate the utility of AAV for gene transfer. In addition, a recombinant AAV vector expressing GDNF was shown to express and secrete high levels of the neurotrophic factor into the surrounding media of NSC-19 infected cells. Finally, the AAV-GDNF vector is demonstrated to act in a neuroprotective fashion. Withdrawal of trophic support from NSC-19 cells through serum deprivation results in a subsequent increase in the number of cells entering apoptosis. However, the percentage of apoptotic cells are significantly reduced in cells infected with the AAV-GDNF vector, as compared to AAV-LacZ or uninfected controls. This work demonstrates the potential of using AAV as a vector in motor neuron-like cells and should prove important in devising future gene therapy strategies for the treatment of in vivo motor neuron disorders.
Revisiting Heterogeneous Storage Optimization in the Vector-Sum Model

Large-scale data centers often adopt more than one type of storage device, each with different storage capacity, I/O capability, and cost. Optimizing the performance-to-cost efficiency of such heterogeneous storage systems is of great practical importance (CapEx), and it is a classic problem in computer system design. The Vector-Sum Model (VSM) is a mental model widely-used by system administrators for this task, due to its conceptual simplicity. The model encompasses various commonly-used rules-of-thumb, such as the five-minute rule or various Knapsack-based heuristics. In this paper we revisit the vector-sum model and study heterogeneous storage using a new form of optimization diagrams. These diagrams give raise to a near-optimal solution to the problem, which subsumes the existing rules-of-thumb used in practice. Our solution also explains that these heuristics are indeed optimal under their respective assumptions, while they become sub-optimal in more general cases. Specifically, our analysis implies that the recent adoption of SSD in data centers may challenge the quality of these commonly-used heuristics, and that our new optimization approach can sustain data center-scale workloads at lower total purchasing cost. Finally, we show that, although the commonly-used I/O metrics of storage are non-additive, we can use regression techniques to transform the metric into an additive form. Experiments using web search production workloads show that the Vector-Sum Model becomes more accurate after the metric transformation.
Deep neural network based voice conversion with a large synthesized parallel corpus

We propose a voice conversion framework to map the speech features of a source speaker to a target speaker based on deep neural networks (DNNs). Due to a limited availability of the parallel data needed for a pair of source and target speakers, speech synthesis and dynamic time warping are utilized to construct a large parallel corpus for DNN training. With a small corpus to train DNNs, a lower log spectral distortion can still be seen over the conventional Gaussian mixture model (GMM) approach, trained with the same data. With the synthesized parallel corpus, a speech naturalness preference score of about 54.5% vs. 32.8% and a speech similarity preference score of about 52.5% vs. 23.6% are observed for the DNN-converted speech from the large parallel corpus when compared with the DNN-converted speech from the small parallel corpus.
Enabling Ad{Hoc Collaboration Through Schedule Learning and Prediction

The transferal of the desktop interface to the world at large is not the goal of ubiquitous computing. Rather, ubiquitous computing strives to increase the responsiveness of the world at large to the individual. A large part of this responsiveness is improved communication with other individuals. In this paper we describe a system that can enable ad–hoc collaboration between several people by creating a model of the daily schedules of individuals and by performing predictions based on this model. Using GPS data we learn to distinguish locations and track the times that these locations are visited. In addition, we use Markov models to predict which locations might be visited next based on the user’s previous behavior.
Molecular genetics of the extracellular lipase of PAOl Pseudomonas

The structural gene (&A) coding for the extracellular lipase of Pseudomonus aeruginusa PAOl has been cloned on plasmid pSW118. Nucleotide sequence analysis revealed a gene of 936 bp. 1ipA codes for a proenzyme of 311 amino acids including a leader sequence of 26 amino acids. The mature protein was predicted to have a M, of 30134, an isoelectric point of 5.6, and a consensus sequence (IGHSHGG) typical of lipases. Furthermore it is highly homologous ( > 60%) to other lipases from various pseudomonads. The 1ipA gene failed to hybridize detectably with genomic DNA from other Pseudomonus species except P. ulcaligenes, even under relaxed stringency. Located 220 bp downstream of the lipA gene, is an open reading frame (ORF2, lipH) which encodes a hydrophilic protein (283 amino acids; M, 33587) that shows some homology to the IimA gene product of P. cepwia, In complementation tests of lipase-defective mutants, lipH was shown to be necessary for expression of active extracellular lipase in P. aeruginosa PAO1.