Miracle-dz/UniFAR-FTUs huggingface dataset:
The importance of tides for the Local Group dwarf spheroidals

There are two main tidal effects that can act on the Local Group dwarf spheroidals (dSphs): tidal stripping and tidal shocking. Using N-body simulations, we show that tidal stripping always leads to flat or rising projected velocity dispersions beyond a critical radius; it is ∼5 times more likely, when averaging over all possible projection angles, that the cylindrically averaged projected dispersion will rise, rather than be flat. In contrast, the Local Group dSphs, as a class, show flat or falling projected velocity dispersions interior to ∼1 kpc. This argues for tidal stripping being unimportant interior to ∼1 kpc for most of the Local Group dSphs observed so far. We show that tidal shocking may still be important, however, even when tidal stripping is not. This could explain the observed correlation for the Local Group dSphs between central surface brightness and distance from the nearest large galaxy. These results have important implications for the formation of the dSphs and for cosmology. As a result of the existence of cold stars at large radii in several dSphs, a tidal origin for the formation of these Local Group dSphs (in which they contain no dark matter) is strongly disfavoured. In the cosmological context, a naive solution to the missing satellites problem is to allow only the most massive substructure dark matter haloes around the Milky Way to form stars. It is possible for dSphs to reside within these haloes (∼10 10 M� ) and have their velocity dispersions lowered through the action of tidal shocks, but only if they have a central density core in their dark matter, rather than a cusp. A central density cusp persists even after unrealistically extreme tidal shocking and leads to central velocity dispersions which are too high to be consistent with data from the Local Group dSphs. dSphs can reside within cuspy dark matter haloes if their haloes are less massive (∼10 9 M� ) and therefore have smaller
Spinocerebellar Ataxia Type 2 Is Associated with the Extracellular Loss of Superoxide Dismutase but Not Catalase Activity

Background Spinocerebellar ataxia type 2 (SCA2) is an inherited and still incurable neurodegenerative disorder. Evidence suggests that pro-oxidant agents as well as factors involved in antioxidant cellular defenses are part of SCA2 physiopathology. Aim To assess the influence of superoxide dismutase (SOD3) and catalase (CAT) enzymatic activities on the SCA2 syndrome. Method Clinical, molecular, and electrophysiological variables, as well as SOD3 and CAT enzymatic activities were evaluated in 97 SCA2 patients and in 64 age- and sex-matched control individuals. Results Spinocerebellar ataxia type 2 patients had significantly lower SOD3 enzymatic activity than the control group. However, there were no differences between patients and controls for CAT enzymatic activity. The effect size for the loss of patients’ SOD3 enzymatic activity was 0.342, corresponding to a moderate effect. SOD3 and CAT enzymatic activities were not associated with the CAG repeat number at the ATXN2 gene. SOD3 and CAT enzymatic activities did not show significant associations with the age at onset, severity score, or the studied electrophysiological markers. Conclusion There is a reduced SOD3 enzymatic activity in SCA2 patients with no repercussion on the clinical phenotype.
Studies on Properties and Estimation Problems for Modified Extension of Exponential Distribution

The present paper considers modified extension of the exponential distribution with three parameters. We study the main properties of this new distribution, with special emphasis on its median, mode and moments function and some characteristics related to reliability studies. For Modified- extension exponential distribution (MEXED) we have obtained the Bayes Estimators of scale and shape parameters using Lindley's approximation (L-approximation) under squared error loss function. But, through this approximation technique it is not possible to compute the interval estimates of the parameters. Therefore, we also propose Gibbs sampling method to generate sample from the posterior distribution. On the basis of generated posterior sample we computed the Bayes estimates of the unknown parameters and constructed 95 % highest posterior density credible intervals. A Monte Carlo simulation study is carried out to compare the performance of Bayes estimators with the corresponding classical estimators in terms of their simulated risk. A real data set has been considered for illustrative purpose of the study.
Enhance the Efficiency Routing between Mobile Nodes in MANET Networks

paper evaluates the performance of the OLSR pro-active protocol with and without backup routes under varying node densities and with different speed movements in the network. Additionally, this paper assists in ascertaining the effect of varying node densities on the connectivity's life between mobile nodes in the network. Hence, it showed the affect of a local recovery mechanism resulted in achieving a significant improvement in network performance by seeking a long life backup path between source and destination for low/high density nodes. Real time applications are required to be supported by mobile ad hoc networks. This is because of the free movement for the mobile nodes from one area to another without any notification via frequent paths. The real time applications traffics are considered a sensitive application, and it is the most affected by failure through the occurrence of delay and loss of packets. It is, therefore, not suitable for use by players. In mobile ad hoc networks, routing protocol functions are based on many factors, such as, node mobility and density and broken paths
Parallel mining frequent patterns over big transactional data in extended mapreduce

In big data era, data size has raised from TB-level to PB-level. Traditional algorithm can not satisfy the needs of big data computing. This paper design a parallel algorithm for mining frequent pattern over big transactional data based on an extended MapReduce Frame. In which, the mass data file is firstly split into many data subfiles, the patterns in each subfile can be quickly located based on bitmap computation by scanning the data only once. And the computing results of all subfiles are merged for mining the frequent patterns in the whole big data. In order to improve the performance of the proposed method, the insignificant patterns are pruned by a statistic analysis method when the data subfiles are processed. The experimental results show that the method is efficient, strong in scalability, and can be used to efficiently mine frequent patterns in big data.
Focused Exploration for Cooperative Robotic Watercraft

Environmental monitoring is one of the main societal challenge of the last century. This is particularly important when considering the increasing population growth and the industrialization of developing countries. Information and Communication Technology (ICT) and robotics can play a significant role in this perspective as they offer invaluable tools to continuously gather relevant information over wide, possibly dangerous areas. In particular autonomous boats hold great promises for monitoring water bodies (lakes, rivers, fishfarms) or providing first aid in floods. However, a key feature for such systems to have a practical impact on society is to provide accurate measures over large areas while being cost effective. In this work, we focus on a water monitoring system, based on Cooperative Robotic Watercrafts (CRW), commercialised by Platypus LLC . The CRW approach is based on the use of low cost, small, robotics platforms, which are able to interact with each other and make use of various artificial intelligence methods to ensure a significant level of autonomy for navigation and information gathering tasks. Figure 1(a) shows a differential drive propeller versions. In addition to a battery based propulsion mechanism, each boat is equipped with an Android OS smartphone, custom electronics board, and sensor payload. The Android smartphone provides communication, GPS, compass, and multi-core processor. The Arduino Mega based electronics board receives commands from the Android phone and interfaces with the propulsion mechanism and sensor payload, as shown in Figure 1(b). The electronics board supports a wide variety of devices including acoustic doppler current profilers and sensors that measure temperature, Dissolved Oxygen (DO), and pH level. A crucial aspect for the CRW is the high level of autonomy of the platforms, which can be controlled by few human operators that provide high level instructions to the system. In particular, Figure 1(c) shows the Graphical User Interface that the human operators can use to control the robotic platforms. Boats behaviors are expressed in the form of high level plan encoded as Colored Petri Nets [1]. In this example, the human operator activated an explore area plan providing the shape of the area that must be explored. The platforms will then automatically divide the area in different sections and execute a pre-specified strategy to monitor the area. Figure 1(d) shows an example of the standard lawnmower strategy employed by the boats. Notice that such strategy is decided off-line, i.e., before the system acquires any readings, and as such it does not depend on the data that the platforms are collecting.
Fast tracking via context depth model learning

Visual tracking is one of the challenging tasks in computer vision. In this paper, we propose a fast and robust visual tracking algorithm which is directly extended from STC [1]. By exploring RGB-D data, we construct a context depth model to record spatial correlation between the low-level features from the target and its surrounding regions. According to the continuity and stability of target in depth image, we adopt region growing method and a model updating schema for scaling and occlusion detection. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed tracker performs favorably against several state-of-the-art algorithms.
Experiences from the pilot operation and commissioning phase of a SCM process improvement program

Piloting of new practices and taking them into successful large-scale use within an organisation are challenging tasks in software process improvement programs. This paper describes an approach to piloting Software Configuration Management (SCM) practices within an industrial organisation. In this case, the SCM improvement program based on Pr/sup 2/imer, Practical Process Improvement for Embedded Real-time Software, which is a framework for software process improvement developed by VTT Electronics. The aim of this paper is to describe the experiences from the pilot operation and commissioning phase of Pr/sup 2/imer, including collection of SCM metrics, planning and arranging of feedback sessions, as well as analysis of the improvement.
Solute flux approach to transport through spatially nonstationary flow in porous media

A theoretical framework for solute flux through spatially nonstationary flows in porous media is presented. The flow nonstationarity may stem from medium nonstationarity (e.g., the presence of distinct geological layers, zones, or facies), finite domain boundaries, and/or fluid pumping and injecting. This work provides an approach for studying solute transport in multiscale media, where random heterogeneities exist at some small scale while deterministic geological structures and patterns can be prescribed at some larger scale. In such a flow field the solute flux depends on solute travel time and transverse displacement at a fixed control plane. The solute flux statistics (mean and variance) are derived using the Lagrangian framework and are expressed in terms of the probability density functions (PDFs) of the particle travel time and transverse displacement. These PDFs are given with the statistical moments derived based on nonstationary Eulerian velocity moments. The general approach is illustrated with some examples of conservative and reactive solute transport in stationary and nonstationary flow fields. It is found based on these examples that medium nonstationarities (or multiscale structures and heterogeneities) have a strong impact on predicting solute flux across a control plane and on the corresponding prediction uncertainty. In particular, the behavior of solute flux moments strongly depends on the configuration of nonstationary medium features and the source dimension and location. The developed nonstationary approach may result in non‐Gaussian (multiple modal) yet realistic behaviors for solute flux moments in the presence of flow nonstationarities, while these non‐Gaussian behaviors may not be reproduced with a traditional stationary approach.
Detecting the Age of a Person through Web Browsing Patterns

As more and more people are using the internet, the demographics of these people such as their age, their gender, their location etc. are highly valued by several business enterprises. We are cognizant about the fact that each user has his/her preferences when it comes to browsing over the internet. This paper designed a system that predicts the age of the user based on his/her web browsing patterns using the A- priori algorithm.
EVALUATION OF SPEECH ENHANCEMENT IN NOISY CONDITIONS USING A SPECTRAL SUBTRACTION AND LINEAR PREDICTION COMBINATION

Improving quality and intelligibility of speech signals in mobile devices has been studied with great interest in the past. Speech information in communication channels is usually corrupted by additive acoustic noise, reverberation or channel noise. This paper explores into the possibilities of enhancing corrupted speech using the Spectral Subtraction (SS) and Linear Prediction Coding (LPC) system for mobile applications only in acoustically noisy conditions. A Spectral Subtraction block is cascaded in series with a LPC system. For a pth order LPC system, a Levinson-Durbin based algorithm computes the LPC coefficients. Typically LPC is used as a data reduction system in speech communication but in this work, we try to find an optimum pth order LPC system that could enhance speech quality. We focus on improving speech quality and not speech intelligibility in this paper. The algorithm output will be evaluated objectively with a combined Perceptual Evaluation of Speech Quality (PESQ) and Itakura-Saito (IS) system and will be compared against Mean Opinion Scores (MOS) of various other Speech Enhancement algorithms.
Assisting Instructional Assessment of Undergraduate Collaborative Wiki and SVN Activities.

In this paper we examine the collaborative performance of undergraduate engineering students who used shared project documents (Wikis, Google documents) and a software version control system (SVN) to support project collaboration. We present an initial implementation of TeamAnalytics, an instructional tool that facilitates the analyses of the student collaboration process by creating dynamic summaries of team member contributions over time in. Document content is processed using machine learning techniques. We validated the summary’s effectiveness using a questionnaire given to instructors and team managers. Team managers indicated that summaries of student contribution to coding activities influenced their evaluation and coordination of team projects.
An interactive multiple model approach for robust GNSS carrier phase tracking under scintillation conditions

This contribution deals with robust carrier phase tracking in Global Navigation Satellite Systems, where the ultimate goal is to obtain accurate and robust phase estimates under non-nominal conditions, such as high dynamics, strong fading and ionospheric scintillation. Within this framework, an Interacting Multiple Model approach, using a bank of parallel Kalman-based filters with different dynamic state models, is proposed to cope with signals corrupted by severe ionospheric scintillation. In the proposed formulation, the time-varying and correlated scintillation phase is introduced into the dynamic system using an AR(1) model. Simulation results are provided to show the enhanced robustness and improved accuracy of the proposed approach, with respect to state-of-the-art carrier phase tracking techniques.
An International Case-Control Study of Interleukin-4Rα, Interleukin-13, and Cyclooxygenase-2 Polymorphisms and Glioblastoma Risk

Previous studies found that allergies are inversely related to risk of glioma. In an earlier publication, using data from a Swedish case-control study, Schwartzbaum et al. report an inverse relation between risk of glioblastoma and four single nucleotide polymorphisms (SNP) on two genes [interleukin (IL)-4Rα, IL-13] that are associated with allergies. In addition, recent studies suggest that IL-4 and IL-13 induce cyclooxygenase-2 (COX-2) to resolve brain inflammation. To see whether previous Swedish results (110 cases, 430 controls) would be replicated, we estimated the association between glioblastoma and two IL-4Rα (rs1805015, rs1801275) and two IL-13 (rs20541, rs1800925) SNPs and their haplotypes and one COX-2 SNP (−765GC) using additional English, Danish, and Finnish data (217 cases, 1,171 controls). Among general population controls, we evaluated associations between these haplotypes, the COX-2 SNP, and self-reported allergies. Our data did not support our original observations relating individual IL-4Rα, IL-13, or COX-2 SNPs to glioblastoma risk. However, the T-G IL-4Rα haplotype was associated with glioblastoma risk (odds ratio, 2.26; 95% confidence interval, 1.13-4.52) and there was a suggestion of an inverse relation between this haplotype and hayfever prevalence among controls (odds ratio, 0.38; 95% confidence interval, 0.14-1.03). The lack of support for a link between four IL-4Rα and IL-13 SNPs and glioblastoma may reflect the absence of associations or may result from uncontrolled confounding by haplotypes related both to those that we examined and glioblastoma. Nonetheless, the association between the T-G IL-4Rα haplotype and glioblastoma risk may indicate a role of immune factors in glioblastoma development. (Cancer Epidemiol Biomarkers Prev 2007;16(11):2448–54)
Dynamic partial-order reduction for model checking software

We present a new approach to partial-order reduction for model checking software. This approach is based on initially exploring an arbitrary interleaving of the various concurrent processes/threads, and dynamically tracking interactions between these to identify backtracking points where alternative paths in the state space need to be explored. We present examples of multi-threaded programs where our new dynamic partial-order reduction technique significantly reduces the search space, even though traditional partial-order algorithms are helpless.
Effects of Leptin Replacement Therapy on Pancreatic β-Cell Function in Patients With Lipodystrophy

OBJECTIVE Leptin administration is known to directly modulate pancreatic β-cell function in leptin-deficient rodent models. However, human studies examining the effects of leptin administration on β-cell function are lacking. In this study, we examined the effects (16–20 weeks) of leptin replacement on β-cell function in patients with lipodystrophy. RESEARCH DESIGN AND METHODS In a prospective, open-label, currently ongoing study, we studied the effects of leptin replacement on β-cell function in 13 patients with congenital or acquired lipodystrophy. Insulin secretory rate (ISR) was calculated by C-peptide deconvolution from plasma glucose and C-peptide levels measured during oral glucose tolerance tests (OGTTs) performed at baseline and after 16–20 weeks of leptin replacement. β-Cell glucose sensitivity and rate sensitivity were assessed by mathematical modeling of OGTT. RESULTS There was a significant decrease in triglycerides, free fatty acids, and glycosylated hemoglobin levels (A1C) after leptin therapy. Patients with lipodystrophy have high fasting and glucose-stimulated ISR. However, leptin therapy had no significant effect on fasting ISR, total insulin secretion during OGTT, β-cell glucose sensitivity, rate sensitivity, or insulin clearance. CONCLUSIONS In contrast to the suppressive effects of leptin on β-cell function in rodents, 16–20-week treatment with leptin in lipodystrophy patients did not significantly affect insulin secretion or β-cell function in leptin-deficient individuals with lipodystrophy.
Representative agents and the contract negotiation cold start problem

Principal Agent Theory (PAT) seeks to identify the incentives and sanctions that a consumer should apply when entering into a contract with a provider in order to maximise their own utility. However, identifying suitable contracts-maximising utility while minimising regret-is difficult, particularly when little information is available about provider competencies. In this paper we show that a global contract can be used to govern such interactions, derived from the properties of a representative agent. After describing how such a contract can be obtained, we analyse the contract utility space and its properties. Then, we show how this contract can be used to address the cold start problem and that it significantly outperforms other approaches. Finally, we discuss how our work can be integrated with existing research into multi-agent systems.
Soil-cement for high-velocity spillway flow applications

The use of soil-cement for slope protection on dams first began in the United States with an experimental test section constructed in 1951 by the United States Bureau of Reclamation (USBR) at Bonny Dam located in eastern Colorado (NTIS, 1984) at a site that experienced “maximum destructive exposure. ” The facing was inspected frequently and after 10 years of evaluation, soil-cement was added to the USBR specifications as an alternative to riprap for upstream slope protection (Holtz and Walker, 1962). The first three dams to use soil-cement for upstream slope protection were Ute Dam in New Mexico (built in 1962), Merritt Dam in Nebraska (built in 1963), and Cheney Dam in Kansas (built in 1964). The first documented use of soil-cement in spillways in the United States was at Broad Canyon Dam in Radium Springs, NM in 1969. Significant data is available related to the performance of soil-cement for upstream slope protection; however, there is limited research and documented performance data available regarding the performance of soil-cement lining subject to high velocity flows in spillway channels. Four publications that investigated soil-cement for channel lining applications are described in this paper. The soil-cement type presented in this study is categorized as “cement-treated base” as defined by the Portland Cement Association (PCA). Based on a review of these publications, it is the authors’ opinion that the current literature verifies that soil-cement for channel lining applications will perform effectively for maximum flow velocities on the order of 25 feet per second (fps) and that the performance of soil-cement for channel lining applications for these high velocity flows is a function of strength and aggregate size. The purpose of this paper is to supplement the existing base of research regarding the suitability of soil-cement for channel lining applications for high velocity flow based on a special application to an emergency spillway for a large, High Hazard dam located in Colorado.