Miracle-dz/UniFAR-FTUs huggingface dataset:
Chandra Observation of V426 Ophiuchi: Weighing the Evidence for a Magnetic White Dwarf

We report the results of a 45 ks Chandra observation of the cataclysmic variable (CV) V426 Ophiuchus. The high-resolution spectrum from the high-energy transmission grating spectrometer is most consistent with a cooling flow model, placing V426 Oph among the group of CVs including U Gem and EX Hya. An uninterrupted light curve was also constructed, in which we detect a significant 4.2 hr modulation together with its first harmonic at 2.1 hr. Reanalysis of archival Ginga and ROSAT X-ray light curves also reveals modulations at periods consistent with 4.2 and/or 2.1 hr. Furthermore, optical photometry in V, simultaneous with the Chandra observation, indicates a modulation anticorrelated with the X-ray, and later more extensive R-band photometry finds a signal at ~2.1 hr. The earlier reported X-ray periods at ~0.5 and 1 hr appear to be only transient and quasi-periodic in nature. In contrast, the 4.2 hr period or its harmonic is stable and persistent in X-ray/optical data from 1988 to 2003. This periodicity is clearly distinct from the 6.85 hr orbit and could be due to the spin of the white dwarf. If this is the case, V426 Oph would be the first long-period intermediate polar with a ratio Pspin/Porb of 0.6. However, this interpretation requires unreasonable values of magnetic field strength and mass accretion rate.
Cache investment: integrating query optimization and distributed data placement

Emerging distributed query-processing systems support flexible execution strategies in which each query can be run using a combination of data shipping and query shipping. As in any distributed environment, these systems can obtain tremendous performance and availability benefits by employing dynamic data caching. When flexible execution and dynamic caching are combined, however, a circular dependency arises: Caching occurs as a by-product of query operator placement, but query operator placement decisions are based on (cached) data location. The practical impact of this dependency is that query optimization decisions that appear valid on a per-query basis can actually cause suboptimal performance for all queries in the long run. To address this problem, we developed Cache Investment - a novel approach for integrating query optimization and data placement that looks beyond the performance of a single query. Cache Investment sometimes intentionally generates a “suboptimal” plan for a particular query in the interest of effecting a better data placement for subsequent queries. Cache Investment can be integrated into a distributed database system without changing the internals of the query optimizer. In this paper, we propose Cache Investment mechanisms and policies and analyze their performance. The analysis uses results from both an implementation on the SHORE storage manager and a detailed simulation model. Our results show that Cache Investment can significantly improve the overall performance of a system and demonstrate the trade-offs among various alternative policies.
Scalable program analysis through proof caching (doctoral symposium)

Despite the remarkable advances attained by the SMT community in the last decade, solving complex formulas still represents the main bottleneck to the scalability of program analysis techniques. Recent research work has shown that formulas generated during program analysis recur, and such redundancy can be captured and exploited by means of caching frameworks to avoid repeating complex queries to solvers. Although current approaches show that reusing formulas syntactically can indeed reduce the impact of SMT solvers on program analysis, they still suffer from being logic-dependent, and performing poorly on huge sets of heterogenous formulas. The core idea of our approach is to go beyond merely syntactical caching frameworks by designing a caching framework that is able to reuse proofs instead of formulas. In fact, even formulas that are syntactically different can share solutions. We aim to study the recurrence of proofs across heterogeneous formulas, and to define a technique to efficiently retrieve such proofs. We plan to exploit a suitable distance function that measures the amount of proofs shared by two formulas to allow the efficient retrieval of candidate proofs within a potentially large space of proofs. In this paper, we present the problem, draft the core idea, discuss the early results and present our research plans.
Differences between the QBO in the first and in the second half of the ERA-40 reanalysis

The representation of the quasi-biennial oscilla- tion (QBO) is investigated in the ERA-40 reanalysis. In the lower stratosphere, where there are a reasonable number of observations, the representation of the QBO is equally good throughout the record. However, strong differences between the first and the second half of the zonal wind data set are found in the upper stratosphere, with a typical offset of - 10 m/s in the equatorial zonal wind in the earlier part versus the later part of the ERA-40 record. At the same time, the strength of the QBO is similar. The 7-year running means of zonal wind, wind shear and temperature reveal interest- ing structures with major changes occuring in the beginning and the middle of the 1980s. Possible explanations are dis- cussed. The identified change of the reanalysed wind profiles over time in ERA-40 demands for a careful use of equatorial upper stratospheric winds from the reanalysis e.g. for model validation purposes.
Segmental Pattern Discovery in Music

In this paper we describe a new method for discovering recurrent patterns in a corpus of segmented melodies. Elements of patterns in this scheme do not represent individual notes but rather represent melodic segments that are sequences of notes. A new knowledge representation for segmental patterns is designed, and a pattern discovery algorithm based on suffix trees is used to discover segmental patterns in large corpora. The method is applied to a large collection of melodies, including Nova Scotia folk songs, Bach chorale melodies, and sections from the Essen folk song database. Patterns are ranked using a statistical significance method that integrates pattern self-overlap, length, and frequency in a corpus into a single measure. A musical interpretation of some of the statistically significant discovered patterns is presented.
The Role of Oxygen Free Radicals in Acute Renal Failure Complicating Obstructive Jaundice: An Experimental Study

Oxydant injury is considered to be an important mechanism in the pathophysiology of acute renal failure. It has been thought that decrease in extracellular and intracellular fluid and endotoxemia seen in obstructive jaundice may cause an increase in production of oxygen free radicals and impairment in antioxydant defense mechanism. This study is designed to investigate the possible role of oxydant injury in renal failure seen in jaundiced patients. In this study, 28 rats were divided into four groups: Control(C) (N=7); Renal ischemia (RI) (N=7); Obstructive jaundice+renal ischemia (OJ+RI) (N=7); Obstructive jaundice (OJ) (N=7). All groups were compared with each other according to renal failure findings and enzyme activities, such as Xanthine oxidase (XOD), Superoxide Dismutase (SOD) and Catalase in renal cortex and Glutathione Peroxidase (GSH-Px), in blood at 3rd day after ischemia and reperfusion. Renal failure findings monitored by blood urea and creatinine levels, seemed more evident in OJ+RI than RI group (p <0.05). When compared with RI, in OJ+RI group, increase in XOD activity at 3rd day was statistically significant [0.259 ±0.01 U/g (tissue) and 0.362±0.03 U/g (tissue) respectively] (p <0.05). SOD and GSH-Px activities of each ischemic group at 3rd day were decreased compared to non-ischemic groups. This fall was significant (p <0.05). But there was no statistical difference between jaundiced and non-jaundiced groups. Alterations in catalase activities also had no statistical significance. These findings may suggest that the injury induced by oxygen free radicals at re-oxygenation of tissue after ischemia may also play a role in the pathogenesis of acute renal failure developed in obstructive jaundice.
Fast speaker adaptive training for speech recognition

In this paper we describe various fast and convenient implementations of Speaker Adaptive Training (SAT) for use in training when Maximum Likelihood Linear Regression (MLLR) is to be used in test time to adapt Gaussian means. The memory and disk requirements for most of these are similar to those for normal ML training; the computation in all cases is dominated by the need to compute the MLLR transforms. Commonly MLLR is combined with Constrained MLLR (CMLLR) which can be viewed as a feature space afﬁne transform and has its own form of SAT (we will call this CMLLR-SAT); we experiment with combining the two forms of SAT. We ﬁnd that even on top of CMLLR-SAT, MLLR-SAT gives improvements.
Multi-projectors and implicit interaction in persuasive public displays

Recent advances in computer video projection open up new possibilities for real-time interactive, persuasive displays. Now a display can continuously adapt to a viewer so as to maximize its effectiveness. However, by the very nature of persuasion, these displays must be both immersive and subtle. We have been working on technologies that support this application including multi-projector and implicit interaction techniques. These technologies have been used to create a series of interactive persuasive displays that are described.
Outcomes of antiretroviral treatment programmes in rural Lesotho: health centres and hospitals compared

Lesotho was among the first countries to adopt decentralization of care from hospitals to nurse‐led health centres (HCs) to scale up the provision of antiretroviral therapy (ART). We compared outcomes between patients who started ART at HCs and hospitals in two rural catchment areas in Lesotho.
Active wheel - An autonomous modular robot

In this paper, a novel robotic platform is introduced, which is able to support other modular robots during the locomotion or self-repair process to increase efficiency of locomotion, payload and runtime. The robot is able to operate autonomous as a stand-alone robot in a swarm or aggregate into robot organisms. We outline the developmental phases of the final robot generation, including mechanics, electronics and software design.
Investigation of multiorientation and multiresolution features for microcalcifications classification in mammograms

Breast cancer is one of the most common cancers among women. One of the early signs of the disease is the appearance of microcalcifications clusters, which often show up as bright spots in mammograms. It is important to be able to distinguish between the shapes of these clusters to increase the reliability and accuracy of the diagnosis. In this paper, a new method to extract features to classify the microcalcification clusters using steerable pyramid decomposition is presented. The method is motivated by the fact that microcalcification clusters can be of arbitrary sizes and orientations. Thus, it is important to extract the features in all possible orientations to capture most of the distinguishing information for classification. The proposed method shows a clear improvement in the classification performance when compared to the wavelet transform; the most commonly used multiscale analysis technique at present.
ODK tables: building easily customizable information applications on Android devices

ODK Tables is an Android app that allows users to enter and curate tabular data. Users can explore the data through a variety of built-in views or build custom views using HTML/JavaScript. It also supports the linking of multiple data tables. Data values can be updated in a variety of ways, including using mobile data collection tools such as ODK Collect, that support rich data types including multi-media, or by communicating with low-cost phones over SMS. Additionally, ODK Tables supports a simple synchronization scheme appropriate for a distributed workforce and backed up on cloud servers. The goal of ODK Tables is to lower barriers to developing customized information applications by making it easy to customize data views using standard web technologieś that do not require recompilation. Our experience in working with many organizations in the developing world led us to make feature choices based on their input (through an on-line survey) with particular consideration to the potential pool of developers available. In this paper, we report on our implementation of ODK Tables and some of its performance parameters. We have designed it to be a flexible solution for a variety of use cases, including logistics management, public health, and environment monitoring where previously collected data is often revisited and updated.
Broadcast Capacity Region of Two-Phase Bidirectional Relaying

In a three-node network bidirectional communication between two nodes can be enabled by a half-duplex relay node with a decode-and-forward protocol. In the first phase, the messages of two nodes are transmitted to the relay node. In the second phase a re-encoded composition is broadcasted by the relay node. In this work the capacity region of the broadcast phase in terms of the maximal probability of error is determined. It is characterized by the mutual informations of the separate channels coupled by the common input.
Climate Change Forces New Ecological States in Tropical Andean Lakes

Air temperatures in the tropical Andes have risen at an accelerated rate relative to the global average over recent decades. However, the effects of climate change on Andean lakes, which are vital to sustaining regional biodiversity and serve as an important water resource to local populations, remain largely unknown. Here, we show that recent climate changes have forced alpine lakes of the equatorial Andes towards new ecological and physical states, in close synchrony to the rapid shrinkage of glaciers regionally. Using dated sediment cores from three lakes in the southern Sierra of Ecuador, we record abrupt increases in the planktonic thalassiosiroid diatom Discostella stelligera from trace abundances to dominance within the phytoplankton. This unprecedented shift occurs against the backdrop of rising temperatures, changing atmospheric pressure fields, and declining wind speeds. Ecological restructuring in these lakes is linked to warming and/or enhanced water column stratification. In contrast to seasonally ice-covered Arctic and temperate alpine counterparts, aquatic production has not increased universally with warming, and has even declined in some lakes, possibly because enhanced thermal stability impedes the re-circulation of hypolimnetic nutrients to surface waters. Our results demonstrate that these lakes have already passed important ecological thresholds, with potentially far-reaching consequences for Andean water resources.
Toxic Combustion Product Yields as a Function of Equivalence Ratio and Flame Retardants in Under-Ventilated Fires: Bench-Large-Scale Comparisons

In large-scale compartment fires; combustion product yields vary with combustion conditions mainly in relation to the fuel:air equivalence ratio (Φ) and the effects of gas-phase flame retardants. Yields of products of inefficient combustion; including the major toxic products CO; HCN and organic irritants; increase considerably as combustion changes from well-ventilated (Φ < 1) to under-ventilated (Φ = 1–3). It is therefore essential that bench-scale toxicity tests reproduce this behaviour across the Φ range. Yield data from repeat compartment fire tests for any specific fuel show some variation on either side of a best-fit curve for CO yield as a function of Φ. In order to quantify the extent to which data from the steady state tube furnace (SSTF [1]; ISO TS19700 [2]) represents compartment fire yields; the range and average deviations of SSTF data for CO yields from the compartment fire best-fit curve were compared to those for direct compartment fire measurements for six different polymeric fuels with textile and non-textile applications and for generic post-flashover fire CO yield data. The average yields; range and standard deviations of the SSTF data around the best-fit compartment fire curves were found to be close to those for the compartment fire data. It is concluded that SSTF data are as good a predictor of compartment fire yields as are repeat compartment fire test data.
PROSPECT features and their application to missing data techniques for vocal tract length normalization

Speaker normalization by (piecewise) linear warping of the frequency axis is a popular method because of its simplicity and effectiveness. However, when this so-called vocal tract length normalization is applied to map test speakers with a shorter vocal tract onto acoustic models trained on speakers with a longer vocal tract, there is important information missing in the frequency bins at the high end of the spectrum. Usually, this missing information is reconstructed by ad hoc rules or through extrapolation of the spectrum. In this paper, we present a new method to estimate the content of those bins. The proposed so-lution is derived from Missing Data Techniques, that are used for noise robust speech recognizers. To alleviate the accuracy loss associated with Missing Data Techniques that are usually expressed in the spectral domain, we apply the PROSPECT feature representation introduced about a year ago. We demonstrate the superiority of our approach on the TIDigits database.
Hierarchical Discovery of Patterns of Infections in Chest Radiographs Using Non-Negative Matrix Factorization

Chest radiography is a screening tool for the detection and the primary assessment of abnormalities consistent with the infections of the lower respiratory tract. Most commonly, the radiographic manifestations of bacterial infection are areas of consolidation with a segmental or lobar distribution which appear as areas of increased pulmonary opacity. This paper addresses the problem of the discovery of consolidation patterns in chest radiographs, by a methodology for automatic segregation of lung consolidations from normal lung parenchyma. The proposed methodology is based on non-negative matrix factorization (NMF) of pulmonary radiographic patterns represented by intensity histograms and Gabor textural features. NMF is considered as a soft clustering algorithm which is iteratively applied according to an hierarchical cluster-merging scheme. This scheme reckons with the resulting NMF bases so as to overcome the limitations associated with the geometry of the clusters. The experimentation results validate the effectiveness of the proposed methodology and demonstrate its comparative advantage over the conventional hierarchical and NMF partitional clustering algorithms.
Applying Intelligent System Concepts to Automatic Beamline Alignment

Increasingly, automatic systems are required to have high dynamical performance and robust behaviour, yet they are expected to cope with more complex processes which are under development and highly non-linear dynamic. A very promising approach in dealing with this scenario is through Intelligent Systems (IS). IS incorporate the creative, abstract and adaptive attributes of a human while minimising the undesirable aspects such as unpredictability, inconsistency, fatigue, subjectivity and temporal instability. Even if the Autonomous Systems area has always provided the demonstration platform of IS, the methodologies are applicable to a wider range of complex problems. Synchrotron Radiation facilities or Free Electron Lasers with their complex data acquisition, data analysis, diagnostic and control problems provide a challenging application area for Intelligent Systems. The paper describes a framework for the conceptual development of IS for Experimental Physics. The proposed framework, based on emerging technologies such as Soft Computing (i.e. Fuzzy Logic, Neural Networks, Genetic Algorithms ), Distributed Objects, Component Software, Java and WWW, has been tested on a pilot project: the automatic beamline alignment.
Phases and geometry of the Script N = 1 A2 quiver gauge theory and matrix models

We study the phases and geometry of the = 1 A2 quiver gauge theory using matrix models and a generalized Konishi anomaly. We consider the theory both in the Coulomb and Higgs phases. Solving the anomaly equations, we find that a meromorphic one-form σ(z)dz is naturally defined on the curve Σ associated to the theory. Using the Dijkgraaf-Vafa conjecture, we evaluate the effective low-energy superpotential and demonstrate that its equations of motion can be translated into a geometric property of Σ:σ(z)dz has integer periods around all compact cycles. This ensures that there exists on Σ a meromorphic function whose logarithm σ(z)dz is the differential. We argue that the surface determined by this function is the = 2 Seiberg-Witten curve of the theory.
On isomorphisms of intersection types

The study of type isomorphisms for different λ-calculi started over twenty years ago, and a very wide body of knowledge has been established, both in terms of results and in terms of techniques. A notable missing piece of the puzzle was the characterization of type isomorphisms in the presence of intersection types. While, at first thought, this may seem to be a simple exercise, it turns out that not only finding the right characterization is not simple, but that the very notion of isomorphism in intersection types is an unexpectedly original element in the previously known landscape, breaking most of the known properties of isomorphisms of the typed λ-calculus. In particular, isomorphism is not a congruence and types that are equal in the standard models of intersection types may be nonisomorphic.
Ceiling camera based environment objects recognition of intelligent space

An efficient objects identification method of intelligent space based on ceiling camera is proposed. First, the environment segmentation method is introduced, and we can get several labeled connected components. Then, a color-based Gaussian mixture model (GMM) method is used for recognizing the components as the objects accordingly. At last, the experiment shows the feasibility and efficiency of the method.
Performance comparison of CPU and GPU on a discrete heterogeneous architecture

Today Graphics Processing Units (GPUs) in scientific computing have led the computing system to achieve tera-scale computing power to the laptops and peta-scale computing power to the clusters by combining multicore Central Processing Units (CPUs) and many core GPUs which can be called a heterogeneous computer architecture. This paper describes briefly an evolutionary journey of GPUs. For performance comparison, parameters considered are latency and throughput. So based on the execution time of a GPU and CPU for a given task, written with Compute Unified Device Architecture (CUDA) C language, the two parameters are measured with increasing size of workload. When the task size is increased GPU is found to be approximately 51% faster than the multithreaded CPU when GPU achieves 100% occupancy. Throughput of GPU is found to be 2.1 times higher than that of CPU for large task size. The GPU used is NVIDIA's GeForce GT630M with CPU of Intel's i-5 3210M 3rd generation processor.