Miracle-dz/UniFAR-FTUs huggingface dataset:
Brown Dwarf : Distributing the Power of OLAP to Unstructured P 2 P Overlays

In this paper we present the Brown Dwarf, a distributed system designed to efficiently store, query and update multidimensional data over a Peer-to-Peer overlay. The Brown Dwarf manages to distribute a highly effective centralized structure among peers on-the-fly. Both point and aggregate queries are then naturally answered online through cooperating nodes that hold parts of a fully or partially materialized data cube. Updates are also performed on-line, eliminating the usually costly over-night process. To tackle dynamic shifts in skew as well as network and node failures, our system employs an adaptive replication scheme, by creating copies of various units of the distributed data structure according to the load as well as the churn rate of the network. This process, called mirroring, ensures balanced load distribution, guarantees resilience and allows for smooth query resolution even in the most dynamic environments. Extensive experiments with the current implementation prove that our system achieves fair storage and load distribution with minimum overhead under variable data and query sets. It manages to quickly adapt even after sudden bursts in load and remains unaffected with up to 10% node failures. These measurements clearly identify Brown Dwarf as a robust and efficient system for distributing a data cube.
Lyman Limit Imaging of High Redshift Galaxies. III. New Observations of 4 QSO Fields

We present the results of deep Lyman limit imaging in four new fields as part of a continuing search for galaxies at $3.0 \le z \le 3.5$. The technique uses a custom broad--band filter set ($U_n G {\cal R}$) designed to isolate objects having Lyman continuum breaks superposed on otherwise flat--spectrum ultraviolet continua. The observations are specifically aimed at detecting known galaxies producing optically thick QSO metal line absorption systems, but are equally sensitive to more generally distributed objects at the redshifts of interest. Together with previously published results of the survey, we have now detected in two out of six cases objects with the expected properties of star--forming galaxies at $z \simgt 3$ within 3~arcsec of the QSO sight lines; the two candidate absorbers have similar luminosities, $M_B \simeq -22$ ($q_0=0.5$, $H_0=50$ \kms Mpc$^{-1}$), and impact parameters, $R \sim 10~h^{-1}$~kpc. The average surface density of robust Lyman break objects is $\sim 0.5$ galaxies per square arcminute to a magnitude limit ${\cal R} = 25.0$. A simple, ``no evolution'' model based on the properties of normal galaxies at $z \simlt 1$ predicts a density of Lyman break objects only a few times larger than observed. We conclude that there is a substantial population of star--forming galaxies, of relatively normal luminosity, already in place at $z = 3 - 3.5$.
Bayesian Computation and Model Selection Without Likelihoods

Until recently, the use of Bayesian inference was limited to a few cases because for many realistic probability models the likelihood function cannot be calculated analytically. The situation changed with the advent of likelihood-free inference algorithms, often subsumed under the term approximate Bayesian computation (ABC). A key innovation was the use of a postsampling regression adjustment, allowing larger tolerance values and as such shifting computation time to realistic orders of magnitude. Here we propose a reformulation of the regression adjustment in terms of a general linear model (GLM). This allows the integration into the sound theoretical framework of Bayesian statistics and the use of its methods, including model selection via Bayes factors. We then apply the proposed methodology to the question of population subdivision among western chimpanzees, Pan troglodytes verus.
Galaxy And Mass Assembly (GAMA): The unimodal nature of the dwarf galaxy population

In this paper we aim to (i) test the number of statistically di stinct classes required to classify the local galaxy population, and, (ii) identify the differe nces in the physical and star formation properties of visually-distinct galaxies. To accomplish t his, we analyse the structural parame- ters (effective radius (Reff ), effective surface brightness within Reff (hµie), central surface brightness (µ0), and Sersic index (n)), obtained by fitting the light profile of 432 galaxies (0.002 < z 6 0.02; Viking Z-band), and their spectral energy distribution using multi -band photometry in 18 broadbands to obtain the stellar mass (M � ), the star formation rate (SFR), the specific SFR (sSFR) and the dust mass (Mdust), respectively. We show that visually distinct, star-forming dwarf galaxies (irregulars, blue spheroids and low surface brightness galaxies) form a unimodal population in a parameter space mapped by hµie, µ0, n, Reff , SFR, sSFR, M � , Mdust and (g − i). The SFR and sSFR distribution of passively evolving (dwarf) ellipticals on the other hand, s tatistically distinguish them from other galaxies with similar luminosity, while the giant gal axies clearly segregate into star- forming spirals and passive lenticulars. We therefore suggest that the morphology classifica- tion scheme(s) used in literature for dwarf galaxies only re flect the observational differences based on luminosity and surface brightness among the apparent distinct classes, rather than any physical differences between them.
Generalized Predictive Control of Depth of Anesthesia by Using a Pharmocokinetic-Pharmacodynamic Model of the Patient

Monitoring and controlling the depth of anesthesia during a surgery is really important since over dosing and under dosing can be dangerous for the patients. The model which is used for describing the relationship between input anesthetic agents and output patient endpoint variables is pharmacokinetic- pharmacodynamic model which included the most significant covariates such as age and weight. Bispectral index (BIS) is one of the best criteria for evaluating the depth of Anesthesia. In this research we used BIS as a patient endpoint and Propofol as an anesthetic agent. As there is a large variety between the patients, we need a controller which should be robust against the disturbances and because the anesthesia process is nonlinear and contains a time delay, model predictive controllers (MPCs) seems act very well for it. In this paper we tried to use a constrained generalized predictive control (GPC) method for controlling the depth of Anesthesia. For comparison a PID controller has been designed. The results showed that the performance of GPC with or without presence of the noise and disturbance was much better than PID controller and also it was more robust.
Evaluation of the Socio Emotional Learning (SEL) Activities on Self-Regulation Skills Among Primary School Children

I seek the experience of the primary school children who participated in the SEL Activities instructing self-regulation skill. I designed the SEL Activities and conducted them with the participant students’ classroom teacher. I used phenomenological methods (Moustakas, 1994) to collect data through semi-structured interviews with primary school children who are 10-years-old and analysed the data by identifying significant statements and then clustering the significant statements into themes, writing textural and structural descriptions, before finally arriving at a composite description. Findings demonstrate that through the SEL Activities, the participant children became more competent in realizing the influence of emotions on their behaviours and in using practical and strategic knowledge on self-regulation skills.
CinC challenge 2002 undertaken by non-stationary and fractal techniques

By using a local recursive least squares approach, named the /spl alpha//spl beta/ filter, to improve Detrended Fluctuation Analysis, we addressed the identification of real and synthetic Heart Rate Variability (HRV) data proposed as part of the Computers in Cardiology Challenge 2002. This approach provided power-law patterns that were used to correctly classify the majority (46/50) of the Challenge dataset. In addition, we show that this approach revealed patterns in real HRV data that do not necessarily follow a uniform power-law. Consequently, this paper promotes familiarisation with scaling information that has not been reported previously for healthy HRV data.
Answering queries in categorical databases

A compatible categorical data base can be viewed as a single (contingency) table by taking the maximum-entropy extension of the component tables. Such a view, here called universal table model, is needed to answer a user who wishes “cross-classified” categorical data, that is, categorical data resulting from the combination of the information contents of two or more base tables. In order to implement a universal table interface we make use of a query-optimization procedure, which is able to generate an appropriate answer both in the case that the asked data are present in the data base and in the case that they are not and, then, have to be estimated
Title Cooperative sensing and compression in vehicular sensornetworks for urban monitoring

A Vehicular Sensor Network (VSN) may be used for urban environment surveillance utilizing vehicle-based sensors to provide an affordable yet good coverage for the urban area. The sensors in VSN enjoy the vehicle’s steady power supply and strong computational capacity not available in traditional Wireless Sensor Network (WSN). However, the mobility of the vehicles results in highly dynamic and unpredictable network topology, leading to packet losses and distorted surveillance results. To resolve these problems, we propose a cooperative data sensing and compression approach with zero inter-sensor collaboration overhead based on sparse random projections. The algorithm provides excellent reconstruction accuracy for the sensed field, and by taking advantage of the spatial correlation of the data, enjoys much smaller communication traffic load compared to traditional sampling algorithms in wireless sensor networks. Real urban environment data sets are used in the experiments to test the reconstruction accuracy and energy efficiency under different vehicular mobility models. The results show that our approach is superior to the conventional sampling and interpolation strategy which propagates data in an uncompressed form, with 4-5dB gain in reconstruction quality and 21-55% savings in communication cost for the same sampling times.
Studies of a wideband stereophonic acoustic echo canceler

In this paper a wideband stereophonic acoustic echo canceler is presented. The fundamental difficulty of stereophonic acoustic echo cancellation (SAEC) is described and an echo canceler based on a fast recursive least squares algorithm in a subband structure is proposed. This structure have been used in a real-time implementation, on which experiments have been performed. In the paper, simulation results of this implementation on real life recordings, with 8 kHz bandwidth, are studied. The results clearly verify that the theoretic fundamental problem of SAEC also applies in real-life situations. They also show that more sophisticated adaptive algorithms are needed in the lower frequency regions than in the higher regions.
The rank of random matrices over finite fields

We determine the rank of a random matrix A over a finite field with prescribed numbers of non-zero entries in each row and column. As an application we obtain a formula for the rate of low-density parity check codes. This formula verifies a conjecture of Lelarge [Proc. IEEE Information Theory Workshop 2013]. The proofs are based on coupling arguments and the interpolation method from mathematical physics.
Molecules in the Circumstellar Disk Orbiting BP Piscium

Context. BP Psc is a puzzling late-type, emission-line field star with large infrared excess. The star is encircled and enshrouded by a nearly edge-on, dusty circumstellar disk, and displays an extensive jet system similar to those associated with pre-main sequence (pre-MS) stars. However, the photospheric absorption features of the star itself appear more consistent with post-main sequence status. Aims. We seek to characterize the molecular gas component of the BP Psc disk, so as to compare the properties of its molecular disk with those of well-studied pre-main sequence stars. Methods. We conducted a mm-wave molecular line survey of BP Psc with the 30 m telescope of the Institut de Radio Astronomie Millimetrique (IRAM). We use these data to investigate the kinematics, gas mass, and chemical constituents of the BP Psc disk. Results. We detected lines of 12 CO and 13 CO and, possibly, very weak emission from HCO + and CN; HCN, H 2 CO, and SiO are not detected. The CO line profiles of BP Psc are well fit by a model invoking a disk in Keplerian rotation. The mimumum disk gas mass, inferred from the 12 CO line intensity and 13 CO/ 12 CO line ratio, is ∼0.1 Jupiter masses. Conclusions. The weakness of HCO + and CN (relative to 13 CO) stands in sharp contrast to the strong HCO+ and CN emission that characterizes most low-mass, pre-main sequence stars that have been the subjects of molecular emission-line surveys, and is suggestive of a very low level of X-ray-induced molecular ionization within the BP Psc disk. These results lend some support to the notion that BP Psc is an evolved star whose circumstellar disk has its origins in a catastrophic interaction with a close companion.
An algorithm to compute similarity between danger objects based on ontology for danger-aware systems

Context awareness is one of the most important aspects in the current ubiquitous computing research field. Danger-aware system is a kind of context awareness system, which detects the dangerous situations and provides services responsive to the dangerous situation. However, there is a shortcoming in the current danger/context awareness systems that the reasoning mechanisms are not flexible. Without enough predefined contexts, the system cannot work well, e.g., if a detected context is similar to a predefined context, but not exactly same as the predefined one, the system cannot recognize it.
Electronic Communications of the EASST Volume 39 ( 2011 ) Graph Computation Models Selected Revised Papers from the Third International Workshop on Graph Computation Models ( GCM 2010 ) Construction of Pushout Complements in the Category of Hypergraphs

We describe a concrete construction of all pushout complements for two given morphisms f : A→ B, m : B→ D in the category of hypergraphs, valid also for the case where f ,m are non-injective. It is based on the generation of suitable equivalence relations. We also give a combinatorial interpretation and show how well-known coefficients from combinatorics, such as the Bell numbers, can be recovered. Furthermore we present a formula that can be used to compute the number of pushout complements for two given morphisms.1
Quality Assessment of Colonoscopy Reporting: Results from a Statewide Cancer Screening Program

This paper aimed to assess quality of colonoscopy reports and determine if physicians in practice were already documenting recommended quality indicators, prior to the publication of a standardized Colonoscopy Reporting and Data System (CO-RADS) in 2007. We examined 110 colonoscopy reports from 2005-2006 through Maryland Colorectal Cancer Screening Program. We evaluated 25 key data elements recommended by CO-RADS, including procedure indications, risk/comorbidity assessments, procedure technical descriptions, colonoscopy findings, specimen retrieval/pathology. Among 110 reports, 73% documented the bowel preparation quality and 82% documented specific cecal landmarks. For the 177 individual polyps identified, information on size and morphology was documented for 87% and 53%, respectively. Colonoscopy reporting varied considerately in the pre-CO-RADS period. The absence of key data elements may impact the ability to make recommendations for recall intervals. This paper provides baseline data to assess if CO-RADS has an impact on reporting and how best to improve the quality of reporting.
Ranking features of wavelet-decomposed EEG based on significance in epileptic seizure prediction

A method for ranking features of wavelet-decomposed EEG in order of importance in prediction of epileptic seizures is introduced. Using this method, the four most important features (extracted from each level of wavelet decomposition) are selected from ten features. The proposed set of features is then used to recognize “pre-seizure” signal, thus predicting a seizure. Our feature set outperforms previously used sets by achieving higher class separability index and correct classification rate.
Mining association rules in learning management systems

Learning management systems collect huge amounts of data that can later be analysed. The University of Rijeka uses MudRi e-learning system, which is based on the Moodle open source software. This paper focuses on the Programming course, for which data over several years are available. The data can be interpreted and valuable knowledge can be obtained and used for improving the quality of lectures, as well as making the lectures more suitable for students based on the actions and material deemed the most popular. Since the MudRi database contains many facts that might affect each other (e.g. homework might affect the final grade), association rule mining, which discovers regularities in data, is the most suitable data mining method. Apriori algorithm for the discovery of association rules is used for finding connections between various actions and final grades. Many interesting rules and information are discovered, which lead to conclusions on actions that seem to be in relation with the course success.
STEPS: An EPSS Tool for Instructional Planning.

Support for Teachers Enhancing Performance in Schools (STEPS) is a World Wide Web and CD-ROM electronic performance support system (EPSS) designed for preK-12 and preservice educators to assist in designing and developing lessons, units, or curricula; this tool was developed around school reform and accountability initiatives in Florida. To achieve the four areas of accountability (i.e., integrated curriculum, integrating technology, alternative assessment, and diverse learning environments) and to maintain that all teachers would be able to use STEPS for instructional planning and ongoing support, the following variables were established as development guiding principles: easy access; user interface; teacher planning model; scaffolding for guidance; teacher developed and tested materials; and plan for continuous evaluation and revision. Six components were established within STEPS: (1) Lesson Architect, a guide through the instructional planning process; (2) Tutorial Library, 40 instructional tutorials centered around the four areas of accountability; (3) Model Units, designed for teachers to use as models for planning their own units; (4) Related Web Links, over 400 annotated links to relevant, reliable Web sites; (5) Best Practices Database, accessible by Sunshine State Standard and subject area or keyword; and (6) Coach, scaffolded help. A diagram of STEPS is included. (Contains 13 references.) (DLS) ******************************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ******************************************************************************** U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) O This document has been reproduced as received from the person or organization originating it. O Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. STEPS: An EPSS Tool for Instructional Planning Pamela Taylor Northrup Janet K. Pilcher University of West Florida "PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY
Genetic Divergence among Regions Containing the Vulnerable Great Desert Skink (Liopholis kintorei) in the Australian Arid Zone

Knowledge of genetic structure and patterns of connectivity is valuable for implementation of effective conservation management. The arid zone of Australia contains a rich biodiversity, however this has come under threat due to activities such as altered fire regimes, grazing and the introduction of feral herbivores and predators. Suitable habitats for many species can be separated by vast distances, and despite an apparent lack of current geographical barriers to dispersal, habitat specialisation, which is exhibited by many desert species, may limit connectivity throughout this expansive region. We characterised the genetic structure and differentiation of the great desert skink (Liopholis kintorei), which has a patchy, but widespread distribution in the western region of the Australian arid zone. As a species of cultural importance to local Aboriginal groups and nationally listed as Vulnerable, it is a conservation priority for numerous land managers in central Australia. Analysis of mitochondrial ND4 sequence data and ten nuclear microsatellite loci across six sampling localities through the distribution of L. kintorei revealed considerable differentiation among sites, with mitochondrial FST and microsatellite F′ST ranging from 0.047-0.938 and 0.257-0.440, respectively. The extent of differentiation suggests three main regions that should be managed separately, in particular the southeastern locality of Uluru. Current genetic delineation of these regions should be maintained if future intervention such as translocation or captive breeding is to be undertaken.
Deductive Formation of Recursive Workflows

We present an action theory with the power to represent recursive plans and the capability to reason about and synthesize recursive workflow control structures. In contrast with the software verification setting, reasoning does not take place solely over predefined data structures, and neither is there a process specification available in recursive form. Rather, specification takes the form of goals, and domain structure takes the form of a physical application setting containing objects. For this reason, well-founded induction is employed for its suitability for practical action domains where recursive structures must be described or inferred. Under this method, termination of the synthesized recursive workflow is a property that follows automatically. We show how a general workflow recursive construct is added to an action language that is then augmented with induction. This formalism is then transformed in a way amenable to automated reasoning. We demonstrate the method with a particular example specified in the theory, and then extracted from a proof constructed by the SNARK first-order theorem prover.