Miracle-dz/UniFAR-FTUs huggingface dataset:
The Variable Warm Absorber in Circinus X-1

We observed Circinus X-1 twice during a newly reached low-flux phase near zero orbital phase using the High-Energy Transmission Grating Spectrometer (HETGS) onboard Chandra. In both observations the source did not show the P Cygni lines we observed during the high-flux phases of the source in 2000 and 2001. During the prezero phase the source did not exhibit significant variability but did exhibit an emission-line spectrum rich in H- and He-like lines from high-Z elements such as Si, S, Ar, and Ca. The light curve in the postdip observation showed quiescent and flaring episodes. Only in these flaring episodes was the source luminosity significantly higher than observed during the prezero phase. We analyzed all high-resolution X-ray spectra by fitting photoionization and absorption models from the most recent version of the XSTAR code. The prezero-phase spectrum could be fully modeled with a very hot photoionized plasma with an ionization parameter of log ξ = 3.0, down from log ξ = 4.0 in the high-flux state. The ionization balances we measure from the spectra during the postzero-phase episodes are significantly different. Both episodes feature absorbers with variable high columns, ionization parameters, and luminosity. While cold absorption remains at levels quite similar to that observed in previous years, the new observations show unprecedented levels of variable warm absorption. The line emissivities also indicate that the observed low source luminosity is inconsistent with a static hot accretion disk corona (ADC), an effect that seems common to other near-edge-on ADC sources as well. We conclude that unless there exists some means of coronal heating other than X-rays, the true source luminosity is likely much higher, and we observe obscuration in analogy to the extragalactic Seyfert 2 sources. We discuss possible consequences and relate cold, lukewarm, warm, and hot absorbers to dynamic accretion scenarios.
Shape Matching Using Curvature Processes

Shape matching is a fundamental problem of vision in general atrd interpretation of deforming shapes in particular. The objective of marching in this instance is to recover the deformation and therefore generalizes the notion of correlation, which aims to only produce a numerical me:rsure of the similarity between two shapes. To address shape matching, we introduce a new representation of a closed 2D shape as a cyclic sequence of the extended circular images of the convex and concave segments of its contour. This representation is then used to establish correspondences between segments of the two contours using dynamic programming. Finally, we compute a recrvery of the differences between two similar contours in terms of the action of curvature process. Computation of convex and concave segments of the contours, given in piecewise linear form, is accomplished using the analytic representation of a local B-spline fit. We show the result of our deformation recovery scheme appliedto dynamis cloud silhouette analysis using hand-traced input from real satellite images. o lese Academic Prcss, Inc.
ES detection range model of circular scan radars

The signal power received at an ES(Electronic warfare Support) system varies over the time due to the scan characteristics of radar, which results in the ES detection range. This paper analyzes the ES detection range for the circular scan and proposes a model to evaluate it quantitatively. Experimental results using real radars demonstrate that the proposed model is suitable for the evaluation of the ES detection range related with the circular scan of radars.
Table 4: Experimental Results Using Retrieval Algorithm Optdocretrv 7 Conclusion

report discussed how to estimate the database usefulness used deened in this paper for the high-correlation and disjoint scenarios. Such discussion did not appear in 6]. ) ranked order of the databases. Table 4 shows the results according to the two measures ciDb and ciDoc for n = 5, 10, 20 and 30. It is shown that the algorithm identiies 85% to 91% of the desired databases and 88% to 95% of the desired documents. As the number of the most similar documents to be retrieved increases, the percentages of desired databases and desired documents also increase. In this paper, we developed an algorithm to retrieve the n most similar documents with respect to a given query from a collection of databases. A suucient condition for our algorithm to retrieve all the desired documents is that those databases containing the desired documents are ranked higher than other databases. The rank of a database is based on the similarity of the most similar document in the database with respect to the query. Our algorithm does not require us to have an accurate estimate of the number of most similar documents in each database. The experimental results show that the combined-term method when used in conjunction with the proposed retrieval strategy is promising. When the number of desired documents was 5, we retrieved on the average about 88% of them. For all other cases, we retrieved on the average more than 90% of the desired documents. However, the experimental results are limited in scope. We will perform many more experiments with much larger collections and many more queries in the near future. 19 of these two estimation methods will use their top M databases to retrieve the n most similar documents. Clearly, the choices of databases by the two methods may diier. For each method and each database chosen by it, it will retrieve c est number documents from the database, where est number is the number of documents in the database which are estimated to be among the n most similar documents and c is a parameter which varies from 1.5 to 4. If the estimated number of documents is very precise, then it is suucient to retrieve from each chosen database exactly est number documents, as the sum of these estimated numbers over the chosen databases should be n or slightly above it. Since the estimated number may not be that …
Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures

The adjusted measure of realized volatility suggested in [20] is applied to high- frequency orderbook and transaction data of DAX and BUND futures from EU- REX in order to identify the drivers of intraday volatility. Four components are identified to have predictive power: an auto-regressive pattern, a seasonal pattern, long-term memory and scheduled data releases. These components are analyzed in detail. Some evidence for two additional components, market microstrucuture events and unscheduled news, is given. Depending on the sampling frequency we estimate that between one and two thirds of the variation in realized volatility can be predicted by a simple linear model based on the components identified. It is shown how the predictive power of the different components depends on sampling frequencies.
Drowsiness estimation under driving environment by heart rate variability and/or breathing rate variability with logistic regression analysis

It is widely known that many traffic accidents occur every year, not only in Japan but also in the world. Drowsiness or sleepiness, which is the cause of dozing at the wheel, happens regardless of the physical condition of the driver after having meals or during midnight. This means that to avoid driver's drowsiness or sleepiness by oneself is hard. Therefore, various systems have been proposed to prevent traffic accidents caused by dozing at the wheel. In this study, we examined the relationship between psychological drowsiness during driving, which was evaluated by the Japanese version of the Karolinska sleepiness scale (KSS-J) and physiological parameters extracted from electrocardiogram and respiration signals. Then we tried to estimate the existence of drowsiness using logistic regression analysis on that parameters. In this study, since KSS-J score 7 indicates sleepy, we determined KSS-J score 7 and more as drowsiness state. The logistic regression method was performed using the half of the data for each subject and used the remaining data as the testing data. As a result, we got 71% of accuracy with heart rate variability (HRV), 72% of accuracy with breathing rate variability (BRV), 81% of accuracy with both signals in the whole subjects using logistic regression. Therefore, it is suggested that HRV and BRV parameters are relevant to drowsiness.
A Scalable Three-Step Approach for Demand Side Management of Plug-in Hybrid Vehicles

In this paper, we present a scalable approach for DSM (demand side management) of PHEVs (plug-in hybrid electric vehicles). Essentially, our approach consists of three steps: aggregation, optimization, and control. In the aggregation step, individual PHEV charging constraints are aggregated upwards in a tree structure. In the optimization step, the aggregated constraints are used for scalable computation of a collective charging plan, which minimizes costs for electricity supply. In the real-time control step, this charging plan is used to create an incentive signal for all PHEVs, determined by a market-based priority scheme. These three steps are executed iteratively to cope with uncertainty and dynamism. In simulation experiments, the proposed three-step approach is benchmarked against classic, fully centralized approaches. Results show that our approach is able to charge PHEVs with comparable quality to optimal, centrally computed charging plans, while significantly improving scalability.
Hydroxyl radicals in the tropical troposphere over the Suriname rainforest: comparison of measurements with the box model MECCA

Abstract. As a major source region of the hydroxyl radical OH, the Tropics largely control the oxidation capacity of the atmosphere on a global scale. However, emissions of hydrocarbons from the tropical rainforest that react rapidly with OH can potentially deplete the amount of OH and thereby reduce the oxidation capacity. The airborne GABRIEL field campaign in equatorial South America (Suriname) in October 2005 investigated the influence of the tropical rainforest on the HOx budget (HOx = OH + HO2). The first observations of OH and HO2 over a tropical rainforest are compared to steady state concentrations calculated with the atmospheric chemistry box model MECCA. The important precursors and sinks for HOx chemistry, measured during the campaign, are used as constraining parameters for the simulation of OH and HO2. Significant underestimations of HOx are found by the model over land during the afternoon, with mean ratios of observation to model of 12.2 ± 3.5 and 4.1 ± 1.4 for OH and HO2, respectively. The discrepancy between measurements and simulation results is correlated to the abundance of isoprene. While for low isoprene mixing ratios (above ocean or at altitudes >3 km), observation and simulation agree fairly well, for mixing ratios >200 pptV ( Box model simulations have been performed with the condensed chemical mechanism of MECCA and with the detailed isoprene reaction scheme of MCM, resulting in similar results for HOx concentrations. Simulations with constrained HO2 concentrations show that the conversion from HO2 to OH in the model is too low. However, by neglecting the isoprene chemistry in the model, observations and simulations agree much better. An OH source similar to the strength of the OH sink via isoprene chemistry is needed in the model to resolve the discrepancy. A possible explanation is that the oxidation of isoprene by OH not only dominates the removal of OH but also produces it in a similar amount. Several additional reactions which directly produce OH have been implemented into the box model, suggesting that upper limits in producing OH are still not able to reproduce the observations (improvement by factors of ≈2.4 and ≈2 for OH and HO2, respectively). We determine that OH has to be recycled to 94% instead of the simulated 38% to match the observations, which is most likely to happen in the isoprene degradation process, otherwise additional sources are required.
The decrease of b -synuclein in cortical brain areas deﬁnes a molecular subgroup of dementia with Lewy bodies

Lewy body diseases include dementia with Lewy bodies and Parkinson’s disease. Whereas dementia with Lewy bodies and Parkinson’s disease can be distinguished as separate clinical entities, the pathological picture is very often identical. a -synuclein aggregation is a key event in the pathogenesis of Lewy body diseases and b -synuclein inhibits a -synuclein aggregation in vitro and in vivo. Recently, b -synuclein has been shown to interact directly with a -synuclein, regulating its functionality and pre-venting its oligomerization. In this study, we analysed the expression of two b -synuclein transcript variants and the main a -synuclein transcript SNCA140, in frozen samples of three areas from brains of patients with (i) pure diffuse Lewy body pathology; (ii) pure Alzheimer’s disease pathology; (iii) diffuse Lewy body pathology and concomitant Alzheimer’s disease pathology and (iv) controls. Relative messenger RNA expression was determined by real-time polymerase chain reaction, expression changes were evaluated by the (cid:2)(cid:2) C t method and messenger RNA expression data were conﬁrmed at the protein level. A drastic diminution of b -synuclein expression was observed in cortical areas of all samples that presented neuropathological features corresponding to pure diffuse Lewy body pathology and the clinical phenotype of dementia with Lewy bodies, but not in those with neuropathological features corresponding to diffuse Lewy body pathology and concomitant Alzheimer’s disease pathology or the clinical phenotype of Parkinson’s disease with dementia. The correlation of expression data with the clinical phenotype and neuropathological diagnosis of the patients suggested the existence of a speciﬁc molecular subtype of dementia with Lewy bodies, characterized by a strong decrease of b -synuclein in the frontal and temporal cortices. Furthermore, our ﬁndings provide new insights into the pathogenesis of Lewy body diseases that may be important for the understanding of molecular mechanisms involved in these complex diseases.
A Structured Construction of Optimal Measurement Matrix for Noiseless Compressed Sensing via Analog Polarization

In this paper, we propose a method of structured construction of the optimal measurement matrix for noiseless compressed sensing (CS), which achieves the minimum number of measurements which only needs to be as large as the sparsity of the signal itself to be recovered to guarantee almost error-free recovery, for sufficiently large dimension. To arrive at the results, we employ a duality between noiseless CS and analog coding across sparse additive noisy channel (SANC). Extending Renyi Information Dimension to Mutual Information Dimension (MID), we show the operational meaning of MID to be the fundamental limit of asymptotically error-free analog transmission across SANC under linear analog encoding constraint. We prove that MID polarizes after analog polar transformation and obeys the same recursive relationship as BEC. We further prove that analog polar encoding can achieve the fundamental limit of achievable dimension rate with vanishing Pe across SANC. From the duality, a structured construction scheme is proposed for the linear measurement matrix which achieves the minimum measurement requirement for noiseless CS.
A Perisynaptic Ménage à Trois between Dlg, DLin-7, and Metro Controls Proper Organization of Drosophila Synaptic Junctions

Structural plasticity of synaptic junctions is a prerequisite to achieve and modulate connectivity within nervous systems, e.g., during learning and memory formation. It demands adequate backup systems that allow remodeling while retaining sufficient stability to prevent unwanted synaptic disintegration. The strength of submembranous scaffold complexes, which are fundamental to the architecture of synaptic junctions, likely constitutes a crucial determinant of synaptic stability. Postsynaptic density protein-95 (PSD-95)/ Discs-large (Dlg)-like membrane-associated guanylate kinases (DLG-MAGUKs) are principal scaffold proteins at both vertebrate and invertebrate synapses. At Drosophila larval glutamatergic neuromuscular junctions (NMJs) DlgA and DlgS97 exert pleiotropic functions, probably reflecting a few known and a number of yet-unknown binding partners. In this study we have identified Metro, a novel p55/MPP-like Drosophila MAGUK as a major binding partner of perisynaptic DlgS97 at larval NMJs. Based on homotypic LIN-2,-7 (L27) domain interactions, Metro stabilizes junctional DlgS97 in a complex with the highly conserved adaptor protein DLin-7. In a remarkably interdependent manner, Metro and DLin-7 act downstream of DlgS97 to control NMJ expansion and proper establishment of synaptic boutons. Using quantitative 3D-imaging we further demonstrate that the complex controls the size of postsynaptic glutamate receptor fields. Our findings accentuate the importance of perisynaptic scaffold complexes for synaptic stabilization and organization.
Research on Small Unmanned Four-rotor Control Based on AIC

Taking the small unmanned four-rotor as a research object, the dynamic model of the small four-rotor was built according to Newton-Euler formaLism. Adaptive Inverse Control (AIC) Theory was used in the control of the small unmanned four-rotor for the first time and the attitude stabiLization control of the small unmanned four-rotor was reaLized on the experimental platform. The simulation results and platform control experiment indicate that AIC is robust in the attitude control of the small unmanned four-rotor.
Operating region modeling of deep-submicron CMOS buffers driving global scope inductive interconnects

The actual operation of a complementary metal-oxide- semiconductor (CMOS) gate driving long resistance-inductance-capacitance (RLC) interconnects is investigated in this paper. Using the alpha-law model, inductance effects of long on-chip interconnects on the operating region of submicron CMOS line-driver transistors is analyzed. A computationally efficient closed form expression for the time the MOS transistors of a line driver actually operate in the saturation region is also presented. The accuracy of the novel expression, particularly suitable for CAD tools implementation, is within 15% as compared to SPICE simulations for a wide range of line parameters.
Co-Evolution based Feature Selection for Pedestrian Detection

In a pedestrian detection system, the most critical requirement is to quickly and reliably determine whether a candidate region contains a pedestrian. The detection ability of whole system determines directly upon quality of chosen features. However, due to the large number and various types of available features, it is difficult to find an optimal feature subset and acquire the proper feature proportion at the same time for most traditional methods including AdaBoost Algorithm. This paper presents a co-evolutionary method with sub-population size adjusting strategy for the feature selection problem in pedestrian detection system. Our method is able to find an optimal feature subset and adjust feature proportion to a proper state in the mean time. Experiments show that our method performs better than AdaBoost Algorithm.
Optimal biped walking with a complete dynamical model

We solve the problem of generating symmetric, periodic minimum energy gaits for a 5-link biped robot moving in the sagittal plane of forward motion. We seek to approximate natural walking motion through the minimization of actuation energy. The model we use has considerably more structure than those previously studied. We deal with a fully nonlinear minimum energy path planning problem on a 14-dimensional state space. Also, a large number of constraints must be considered, including contact and collision effects. Our solution required development of various symbolic, dynamical algorithms relating to multibody systems and use of powerful numerical optimal control software. Solving the minimum energy walking problem including saturation and algebraic constraints amounts to solving a Hamilton-Jacobi-Bellman type equation along the optimal path. We use the path planning software DIRCOL which provides a substantial decrease in computing time required for generating solutions. We discuss numerical optimization and other modeling issues.
Rule Extraction from A Trained Conditional Random Field Model

Conditional Random Field (CRF) has proven to be highly successful for sequence labeling problems like part of speech tagging, segmentation etc. However, the model acts like a black box, providing no insight into what is learned. We propose a system for rule extraction from CRF to assist comprehensibility of the model. Experiments on POS tagging and chunking problem in English are performed as case studies. We test the quality of the extracted rule base by implementing a majority voting rule based tagger, which shows maximum precision of 93.9% for POS tagging and 77% for chunking. The obtained rules conform to our linguistic knowledge of English. We also give quantitative comparison of our approach with PART decision list and C4.5 decision tree learner. Comprehensibility of statistical models is our guiding principle.
The Ring — Issue XXXIII — May 2013

We present 3D Constrained Local Model (CLM-Z) for robust facial feature tracking under varying pose. Our approach integrates both depth and intensity information in a common framework. We show the benefit of our CLMZ method in both accuracy and convergence rates over regular CLM formulation through experiments on publicly available datasets. Additionally, we demonstrate a way to combine a rigid head pose tracker with CLM-Z that benefits rigid head tracking. We show better performance than the current state-of-the-art approaches in head pose tracking with our extension of the generalised adaptive view-based appearance model (GAVAM).
The Powers of the Union: Delegation in the EU

Book description: The Powers of the Union develops and tests a new theory of centralization and bureaucratization in the European Union. Using original data spanning five decades and a multi-method approach, Franchino argues that most EU laws rely extensively on national administrations for policy implementation and provide for ample national discretionary authority, while limiting tightly the involvement of the European Commission. However, when Council ministers do not share the same policy objectives, some have the incentive to limit national executive discretion and to rely more on the Commission. Majority voting facilitates this outcome, but the limited policy expertise of supranational bureaucrats and their biased views impede extensive supranational delegation. Finally, the European Parliament systematically attempts to limit national discretion, especially when its views differ from ministerial opinions, and tries to increase the Commission's policy autonomy. The book contributes towards understanding political-bureaucratic relations and evaluates the implications for EU democracy and subsidiarity.