Miracle-dz/UniFAR-FTUs huggingface dataset:
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Causal knowledge is frequently pursued by researchers in many fields, such as medicine, economics, and social science, yet very little research in knowledge discovery focuses on discovering causal knowledge. Those researchers rely on a set of methods, called experimental and quasiexperimental designs, that exploit the ontological structure of the world to limit the set of possible statistical models that can produce observed correlations among variables. As a result, designs are powerful techniques for drawing conclusions about cause-and-effect relationships. However, designs are almost never used explicitly by knowledge discovery algorithms. In this work, we provide explicit evidence that designs have the potential to be highly useful as part of algorithms to discover causal knowledge. We first formalize the basic elements of experimental and quasiexperimental designs to characterize a design search space. We then quantify the range and diversity of designs that can be applied to examine the central questions associated with a large and complex domain (Wikipedia). Finally, we show that explicit consideration of designs can substantially improve the accuracy of causal inference and increase the statistical power of algorithms for learning the structure of graphical models.
Clumps and triggered star formation in ionized molecular clouds

Infrared shells and bubbles are ubiquitous in the Galaxy and can generally be associated with Hii regions formed around young, massive stars. In this paper, we use high-resolution 3D SPH simulations to explore the effect of a single O7 star emitting photons at 10 49 s −1 and located at the centre of a molecular cloud with mass 10 4 M ⊙ and radius 6.4 pc; the internal structure of the cloud is characterised by its fractal dimension,D (with 2.06D6 2.8), and the variance of its (log-normal) density distribution, σ 2 (with 0.366σ 2 6 1.42). Our study focuses on the morphology of the swept-up cold gas and the distribution and statistics of the resulting star formation. If the fractal dimension is low, the border o f the Hii region is dominated by extended shell-like structures, and these break up into a small number of massive high-density clumps which then spawn star clusters; star formation occurs relatively quickly, and delivers somewhat higher stellar masses. Conversely, if the fractal dimension is high, the border of the Hii region is dominated by a large number of pillars and cometary globules, which contain compact dense clumps and tend to spawn single stars or individual multiple systems; star formation occurs later, the stellar masses are somewhat lower, and the stars are more widely distributed.
Classification of Cancer Stage from Free-text Histology Reports

This article investigates the classification of a patient's lung cancer stage based on analysis of their free-text medical reports. The system uses natural language processing to transform the report text, including identification of UMLS terms and detection of negated findings. The transformed report is then classified using statistical machine learning techniques. A support vector machine is trained for each stage category based on word occurrences in a corpus of histology reports for pathologically staged patients. New reports can be classified according to the most likely stage, allowing the collection of population stage data for analysis of outcomes. While the system could in principle be applied to stage different cancer types, the current work focuses on lung cancer due to data availability. The article presents initial experiments quantifying system performance for T and N staging on a corpus of histology reports from more than 700 lung cancer patients
Advanced off-line simulation framework with deformation compensation for high speed machining with robot manipulators

In this paper, we present a complete off-line modelling and simulation framework with deformation compensation for accurate robot milling of workpieces. We consider two previously published methods for deformation modelling into our framework: A method containing a model for predicting the milling forces acting on the robot based on the net energy consumption of the milling device. The other method computes robot deflections due to these external forces using joint stiffness models. We illustrate how the methods are incorporated into our framework and we provide resulting accuracies obtained from experimental studies. For these studies we use a KUKA KR120 QUANTEC pro robot with a high speed milling tool working in aluminum 3003. We experimentally calibrate the unknown parameters in the joint stiffness model and the milling force prediction model. We then show experiments that verify that we by compensating for deviations, we can improve the accuracy to reach a value similar to the theoretical lower limit given by the precision specified by the robot manufacturer.
Relationship between anthropometric parameters and speed performance: A kinanthropometric research

The purpose in this study; determined of relationship between anthropometric parameters and speed performance. In this purpose; 118 sedentary university students age 21.2 ± 2.1 year, body weight 62.2 ± 10.7 kg and height 168.2 ± 8.1 cm participated in this study voluntarily. 30 m speed performance with stature (shoulder, chest, trunk, waist, hip, thigh, knee, calf and ankle) and (height, fathoms, upper arm, fore arm, all arms, trunk, thigh, leg and all leg) girths was measured. Statistical analysis was made in SPSS 22.0 packed program for Windows. Data from the measured of arithmetic means, standard deviation, lowest and highest values was found. Relationship between anthropometric parameters and speed performance was tested by Pearson's Correlation. According to Data from the measured; there were significant relationship in between speed values of workgroups and body weight, shoulder girths, chest girths, trunk girths, waist girths (p<0.01), leg girths (p<0.05) and there were significant relationship in between speed values of workgroup and height, fathoms length, fore arm length, all arm length, trunk length, leg length (p<0.01), thigh length (p<0.05). It can be said increases in speed values, if girths and length values increase.
Spiral Waves and Euclidean Symmetries

Spiral waves can be found in various chemical systems, for example in the Belousov–Zhabotinsky-reaction and in the catalysis on platinum surfaces. Such systems can be modelled by reaction-diffusion equations on the plane and have the symmetry of the Euclidean group of the plane. We present a center-manifold reduction ("slaving principle") near spiral waves which enables us to reduce the spiral wave dynamics to a small system of ordinary differential equations. Then we discuss the structure of the ordinary differential equations in detail. Our approach holds for any symmetry group G. As applications of our result we discuss the meandering transition of rotating spiral waves, periodic forcing of meandering spiral waves in the plane and dynamics of twisted scroll rings and helices in three-space.
Variability in fMRI: An Examination of Intersession Differences

The results from a single functional magnetic resonance imaging session are typically reported as indicative of the subject's functional neuroanatomy. Underlying this interpretation is the implicit assumption that there are no responses specific to that particular session, i.e., that the potential variability of response between sessions is negligible. The present study sought to examine this assumption empirically. A total of 99 sessions, comprising 33 repeats of simple motor, visual, and cognitive paradigms, were collected over a period of 2 months on a single male subject. For each paradigm, the inclusion of session-by-condition interactions explained a significant amount of error variance (P < 0.05 corrected for multiple comparisons) over a model assuming a common activation magnitude across all sessions. However, many of those voxels displaying significant session-by-condition interactions were not seen in a multisession fixed-effects analysis of the same data set; i.e., they were not activated on average across all sessions. Most voxels that were both significantly variable and activated on average across all sessions did not survive a random-effects analysis (modeling between-session variance). We interpret our results as demonstrating that correct inference about subject responses to activation tasks can be derived through the use of a statistical model which accounts for both within- and between-session variance, combined with an appropriately large session sample size. If researchers have access to only a single session from a single subject, erroneous conclusions are a possibility, in that responses specific to this single session may be claimed to be typical responses for this subject.
Joint power allocation and subcarrier pairing for cooperative OFDM transmission

This paper considers the joint power allocation and subcarrier pairing problem in decode-and-forward (DF) relaying orthogonal-frequency-division multiplexing (OFDM) system, and proposes a strategy, called MW-RA, to maximize the weighted sum rate with total power constraint. MW-RA is formulated as a mixed integer programming problem and then transformed to a convex optimization problem by continuous relaxation, and solved in the Lagrangian dual domain. Simulation results show that MW-RA can maximize the weighted sum rate under total power constraint and outperform equal power allocation (EPA).
AMPA–Kainate Subtypes of Glutamate Receptor in Rat Cerebral Microglia

Microglial cells were isolated from rat cerebral cortex, and kainate (KA)-induced inward current was measured at a holding potential of −40 or −60 mV. 6-Cyano-7-nitroquinoxaline-2, 3-dione-sensitive KA-induced currents increased with increasing KA concentration. The half-activation concentration and Hill coefficient were 3.3 × 10−4m and 1.4, respectively. Although glutamate (Glu) and AMPA-induced currents were much smaller than that induced by KA, all KA-, Glu-, and AMPA-induced currents were greatly and consistently enhanced in the presence of cyclothiazide (CTZ). On the other hand, KA-induced currents were much less sensitive to potentiation by concanavain A, suggesting that the KA-induced response in rat microglia is predominantly mediated by AMPA-preferring receptors (subunits GluR1–GluR4). The current–voltage relationships of KA- and AMPA–CTZ-induced currents were almost linear or slightly outward rectifying. The reversal potential of KA-induced current shifted to negative potentials (from +4 to −40 mV) on switching from high Na+ to high Ca2+ external solution, indicating the low Ca2+ permeability through the AMPA–KA receptor channel complexes. AMPA–KA receptor expression was studied with immunohistochemistry and reverse transcription-PCR, from which GluR2, GluR3, GluR4, and GluR5 were identified. Lower levels of mRNAs for GluR7 and KA-1–KA-2 were also indicated. Finally, activation of these receptors with KA or Glu significantly enhanced the production of tumor necrosis factor-α. These results suggest that primary cultured rat microglia possesses functional Glu receptor, which may mediate neuron to microglia communication in the physiological and pathological states.
Observing Deformations of 20 Nanometer with a Low Numerical Aperture Light Microscope

In the presented paper we show that { using appropriate image post processing { measurements with an accuracy and resolution far beyond the theoretical resolution limit of an optical sensor can be made. We demonstrate this based on the observation of tensile tests which are performed on m-sized samples under a low numerical aperture microscope. Although the microscope resolves only about 4 m, deformations of 20 nm can be observed. The measurement accuracy is in the same range. The algorithm achieving these results is an image matching technique combined with a diagnostic tool that automatically detects measurement errors and reenes the parameter estimates applying a rigorous statistical testing framework. The paper focuses on the mathematical and physical aspects of this image processing algorithm. The use of image data from tensile experiments is motivated by the fact that we can nd a ground truth { namely the linearity in the stress-strain relation in the elastic domain { even on the nanometer scale. Thus, we can test the algorithm on its performance. However, the matching technique has also the capability to estimate rigid body motion with the same accuracy and resolution. In addition, the algorithm is formulated independently of the microscope type. Therefore it is a straight forward task to transfer the procedure to other microscope types, i.e. Scanning Electron Microscopes.
Vision labs: seeing UCD as a relational practice

Relational aspects in user-centered design, UCD, are largely overlooked in the literature. We use criticism of UCD to facilitate a discussion of how discourse, activities, and materials give shape to user involvement in design activities. Drawing on experiments with the workshop format for devising innovations and creative solutions with users, we introduce some criteria and points of interest in the development of a workshop format we call Vision Labs.
Electron mobility in extremely thin single-gate silicon-on-insulator inversion layers

Inversion-layer mobility has been investigated in extremely thin silicon-on-insulator metal–oxide–semiconductor field-effect transistors with a silicon film thickness as low as 5 nm. The Poisson and Schrœdinger equations have been self-consistently solved to take into account inversion layer quantization. To evaluate the electron mobility, the Boltzmann transport equation has been solved by the Monte Carlo method, simultaneously taking into account phonon, surface-roughness, and Coulomb scattering. We show that the reduction of the silicon layer has several effects on the electron mobility: (i) a greater confinement of the electrons in the thin silicon film, which implies an increase in the phonon-scattering rate and therefore a mobility decrease; (ii) a reduction in the conduction effective mass and the intervalley-scattering rate due to the redistribution of carriers in the two subband ladders as a consequence of size quantization resulting in a mobility increase; and (iii) an increase in Coulomb scatte.
Longest Common Subsequences in Sets of Permutations

The sequence a_1,. ,a_m is a common subsequence in the set of permutations S = {p_1,. ,p_k} on [n] if it is a subsequence of p_i(1),. ,p_i(n) and p_j(1),. ,p_j(n) for some distinct p_i, p_j in S. Recently, Beame and Huynh-Ngoc (2008) showed that when k>=3, every set of k permutations on [n] has a common subsequence of length at least n^{1/3}. We show that, surprisingly, this lower bound is asymptotically optimal for all constant values of k. Specifically, we show that for any k>=3 and n>=k^2 there exists a set of k permutations on [n] in which the longest common subsequence has length at most 32(kn)^{1/3}. The proof of the upper bound is constructive, and uses elementary algebraic techniques.
Face image-based gender recognition using complex-valued neural network

Automatic gender recognition is an emerging problem in computer visions. An accurate gender recognition system can be used to reduce the search space in face recognition system for about half. However, since there is no definitive features of sexual dimorphism on human face that can be applied to all kind of face shapes from any race and age, it needs more studies to optimize the recognition system. Thus, this research investigates the implementation of complex-valued neural network as a classifier to recognize human gender which is based on face image. The experiment is also aimed to study the comparison between complex-valued and real-valued neural network. The methods proposed in this paper include image processing, feature extraction, and classification. After the face image processed by using local binary pattern to accentuate face texture and gradient filter to define face outline, the features of the face image is extracted by using histogram of oriented gradient. Then, the dimension of the resulted vectors is reduced by using principal component analysis. The final feature vectors is then used in neural network training and neural network testing processes. This paper shows investigation results in implementing the methods for some measurement parameters. The accuracy level of real-valued neural network system is a bit lower than the average accuracy level of complex-valued one, with 78.2% and 80.2% average accuracy rate, respectively. The results also show that complex-valued neural network system can achieve convergency rate four times faster than the real-valued neural network, which implies on the training process time.
On the Design of Future Wireless Ad Hoc Networks

In this paper, we study the design of future wireless ad hoc networks. Particularly, we consider that the future wireless ad hoc networks shall be able to efficiently provide connectivity and support a variety of quality of service requirements, such as bandwidth and delay requirements. To address these issues, we propose a novel framework for the design of future wireless ad hoc networks. The key idea of this framework is to establish an overlay hypernetwork, which consists of multiple hyperchannels, each of which can provide connectivity for multiple nodes in the hyperchannel. By comparison, a typical tunnel in existing overlay network schemes can only provide connectivity for two end nodes. Within the framework, we also develop advanced network coding design that can further improve the performance of the network in terms of throughput and delay.
Per-Sample Kernel Adaptation for Visual Recognition and Grouping

Object, action, or scene representations that are corrupted by noise significantly impair the performance of visual recognition. Typically, partial occlusion, clutter, or excessive articulation affects only a subset of all feature dimensions and, most importantly, different dimensions are corrupted in different samples. Nevertheless, the common approach to this problem in feature selection and kernel methods is to down-weight or eliminate entire training samples or the same dimensions of all samples. Thus, valuable signal is lost, resulting in suboptimal classification. Our goal is, therefore, to adjust the contribution of individual feature dimensions when comparing any two samples and computing their similarity. Consequently, per-sample selection of informative dimensions is directly integrated into kernel computation. The interrelated problems of learning the parameters of a kernel classifier and determining the informative components of each sample are then addressed in a joint objective function. The approach can be integrated into the learning stage of any kernel-based visual recognition problem and it does not affect the computational performance in the retrieval phase. Experiments on diverse challenges of action recognition in videos and indoor scene classification show the general applicability of the approach and its ability to improve learning of visual representations.
Implementation and Simulation of Half-Bridge Series Resonant Inverter in Zero Voltage Switching

In switch mode power inverters, small sized inverters can be obtained by increasing the switching frequency. Switching frequency increment causes high driver losses. Also, high dt di and dt dv produced by the switching action creates high Electromagnetic Interference (EMI) and Radio Frequency Interference (RFI). In this paper, a series half bridge series resonant inverter circuit is simulated and evaluated practically to demonstrate the turn-on and turn-off conditions during zero or close to zero voltage switching. Also, the reverse recovery current effects of the body diode of the MOSFETs were investigated by operating above and below resonant frequency. Keywords—Driver losses, Half Bridge series resonant inverter, Zero Voltage Switching
Coalgebras and Modal Logic

1 These lecture notes were written mainly during my stay as an ERCIM fellow at the Masaryk University, Brno, Czech Republic. I owe special thanks to Lubo s Brim, Ji r Rosick y, and the Faculty for Informatics. Preface These course notes present universal coalgebra as a general theory of systems. By`system' we understand some entity running in and communicating with an environment. We also assume that a system has a xed interface and that the environment can perform only those observations/experiments/communications on the system allowed by the interface. By`general theory' we understand a theory which allows to investigate in a uniform way as many diierent types of systems as possible. Of course, here is a trade oo: the more diverse the types of systems we admit for study, the less results we can expect to obtain in a uniform way. It is one of the aims of this course to show that the notion of coalgebra is general enough to cover many types of systems and is speciic enough to allow for quite a number of interesting results. The termùniversal' coalgebra not only refers to the generality of the theory but also reeects that universal coalgebra dualises (to some extent) the well-established area of universal algebra. To explore this duality is another of the main topics of this course. In particular we will see what can be said about the duality of logics for algebras and coalgebras. Concerning prerequisites, Chapters 1 and 3 should be easily accessible. Chapter 2 requires a bit of category theory which was introduced in the course in more detail than in the text. The Appendix recalls the necessary deenitions but cannot replace an introduction to category theory. Section 2.5 contains additional material illustrating the techniques presented in Chapter 2. Chapter 4 needs Chapters 2.1 and 3, Chapter 5 builds on Chapter 2 (excluding Section 2.5). The exercises in the text are essential and are not meant to be skipped. They should be easy to solve, often even obvious, but the solution needs ideas which are important in the following. The exercises in the separate sections contain additional material which did not t in a one week's course. They may be more diicult. I gave courses based on earlier versions of these notes at the Faculty of Informatics of the Masaryk University in Brno, Czech Republic, and at ESSLLI 2001 in Helsinki, Finland. I would …