Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotically good ramp secret sharing schemes

We coin the term of asymptotically good sequences of ramp secret sharing schemes. These are sequences such that when the number of participants goes to infinity, the information rate approaches some fixed positive number while the worst case information leakage of a fixed fraction of information, relative to the number of participants, attains another fixed number. A third fixed positive number describes the ratio of participants that are guaranteed to be able to recover all – or almost all – of the secret. By a non-constructive proof we demonstrate the existence of asymptotically good sequences of schemes with parameters arbitrarily close to the optimal ones. Moreover, we demonstrate how to concretely construct asymptotically good sequences of schemes from sequences of algebraic geometric codes related to a tower of function fields. Our study involves a detailed treatment of the relative generalized Hamming weights of the involved codes.
Evolution in the black hole mass–bulge mass relation: a theoretical perspective

We explore the growth of supermassive black holes and host galaxy bulges in the galaxy population using the Millennium Run A cold dark matter (ACDM) simulation coupled with a model of galaxy formation. We find that, if galaxy mergers are the primary drivers for both bulge and black hole growth, then in the simplest picture one should expect the m BH -m bulge relation to evolve with redshift, with a larger black hole mass associated with a given bulge mass at earlier times relative to the present day. This result is independent of an evolving cold gas fraction in the galaxy population. The evolution arises from the disruption of galactic discs during mergers that make a larger fractional mass contribution to bulges at low redshift than at earlier epochs. There is no comparable growth mode for the black hole population. Thus, this effect produces evolution in the m BH -m bulge relation that is driven by bulge mass growth and not by black holes.
Social Barriers to Cooperation: Experiments on the Extent and Nature of Discrimination in Peru

We present a series of experiments to understand the nature and extent of discrimination in urban Lima, Peru. The experiments exploit varying degrees of information on performance and personal characteristics as people sort into groups to test for statistical versus taste-based discrimination. This allows us to examine the nature of discrimination. Our sample is similar to the racial and socio-economic diversity of young adults in urban Lima. This allows us to look at the extent of discrimination. We use a unique method to measure race, along four racial dimensions common in Peru, and find that race is clearly observable. This gives us confidence that we can examine discrimination based on race. While behavior is not correlated with personal, socio-economic or racial characteristics, people do use personal characteristics to sort themselves into groups. Beauty is a robust predictor of being a desirable group member as is being a woman. Being unattractive or looking indigenous makes one less desirable and looking white increases oneA¢? s desirability. Interestingly, indigenous subjects are three times more likely to be classified as unattractive, suggesting that beauty might mask discrimination. We find that once information on performance is provided, almost all evidence of discrimination is eliminated, except in the most-preferred group. The evidence in these cases is consistent with taste-based, rather than statistical, discrimination.
Timing, Bursting, and Cycling as Corollaries of Multiplex Regulation of Eukaryotic Transcription

Eukaryotic transcription depends on dozens of regulatory proteins. It is unclear how transcription is controlled in a robust and flexible manner. We show that equilibrium-binding mechanisms for gene regulation become ineffective if many regulatory signals are integrated. A cyclic ratchet mechanism does not suffer from these limitations. It involves the sequential assembly of small protein-complexes. After each assembly, covalent histone-modifications mark the current phase and sensitizes the chromatin for the assembly of the next complex. Even though the individual assembly steps are highly stochastic in duration, a sequence of them gives rise to remarkable precision of transcription-cycle durations. This mechanism explains how transcription cycles, lasting for tens of minutes, derive from regulatory proteins residing on chromatin for only tens of seconds. Transcription bursting is an inherent emergent feature of the transcription cycle. Bursty transcription by single cells can stay transiently in synchrony, which explains transcription cycling as observed experimentally.
The O II Luminosity Density of the Universe

Equivalent widths of [O II] 3727 Å lines are measured in 375 faint galaxy spectra taken as part of the Caltech Faint Galaxy Redshift Survey centered on the Hubble Deep Field. The sensitivity of the survey spectra to the [O II] line is computed as a function of magnitude, color, and redshift. The luminosity function of galaxies in the [O II] line, and the integrated luminosity density of the universe in the [O II] line, are computed as a function of redshift. It is found that the luminosity density in the [O II] line was a factor of ~10 higher at redshifts z ~ 1 than it is at the present day. The simplest interpretation is that the star formation rate density of the universe has declined dramatically since z ~ 1.
Social sensing in the field: challenges in detecting social interactions in construction sites

Construction industry is a sector that is renowned for the slow uptake of new technologies. This is usually due to the conservative nature of this sector that relies heavily on tried and tested and successful old business practices. However, there is an eagerness in this industry to adopt Building Information Modelling (BIM) technologies to capture and record accurate information about a building project. But vast amounts of information and knowledge about the construction process is typically hidden within informal social interactions that take place in the work environment. In this paper we present a vision where smartphones and tablet devices carried by construction workers are used to capture the interaction and communication between workers in the field. Informal chats about decisions taken in the field, impromptu formation of teams, identification of key persons for certain tasks, and tracking the flow of information across the project community, are some pieces of information that could be captured by employing social sensing in the field. This information can not only be used during the construction to improve the site processes but it can also be exploited by the end user during maintenance of the building. We highlight the challenges that need to be overcome for this mobile and social sensing system to become a reality.
Visceral fat is associated with cardiovascular risk in women with polycystic ovary syndrome.

BACKGROUND Women with polycystic ovary syndrome (PCOS) have been reported to have subclinical cardiovascular disease (CVD) and increased abdominal fat. The aim of this study was to evaluate the relationship between visceral fat (VF) and early markers of CVD in PCOS women. METHODS Two hundred overweight PCOS women [(mean +/- SD) age 24.6 +/- 3.2 years, body mass index (BMI) 28.5 +/- 2.8 kg/m2] and 100 healthy age- and BMI-matched volunteer controls entered this cross-sectional study. In all subjects, the amount of VF was measured by ultrasonography. Anthropometric measurements [BMI and waist circumference (WC)], complete hormonal and metabolic pattern, carotid intima-media thickness (IMT), brachial arterial flow-mediated dilation (FMD) and inflammatory biomarkers [C-reactive protein (CRP), fibrinogen, white blood cells count and plasminogen activated inhibitor-1] were also obtained from all subjects. A stepwise linear regression model was used in PCOS patients to verify if IMT or FMD as dependent variables are affected by other independent variables. RESULTS VF amount was significantly (P < 0.001) higher in PCOS subjects than in healthy controls [31.4 +/- 7.3 versus 28.0 +/- 6.1 (mean+/-SD) mm, respectively] and directly related to insulin resistance: HOMA (r = 0.918, P < 0.001) and AUC(INS) (r = 0.879, P < 0.001), and to WC (r = 0.658; P < 0.001). In PCOS, the two linear regression analyses showed that IMT is positively affected by VF and CRP, whereas FMD is positively affected by IMT and negatively by VF and CRP. CONCLUSIONS VF amount is associated with subclinical CVD in PCOS patients.
Working Together in Harmony - An Implementation of the CORBA Object Query Service and Its Evaluation

The CORBA standard, together with its service specifications, has gained considerable attention in recent years. The CORBA Object Query Service allows for declarative access to heterogeneous storage systems. We have come up with an implementation of this service called Harmony. The objective of the article is to provide a detailed description and quantitative assessment of Harmony. Its main technical characteristics are data-flow evaluation, bulk transfer and intra-query parallelism. To carry out the evaluation, we have classified data exchange between components of applications in several dimensions: one is to distinguish between point-, context- and bulk data access. We have compared Harmony with: (1) data access through application-specific CORBA objects, and (2) conventional client/server communication, i.e., Embedded SQL. Our results show that Harmony performs much better than Alternative 1 for bulk data access. Besides that, due to the features mentioned above, Harmony, performs approximately as well as conventional client/server communication mechanisms.
Associative Reinforcement Learning using Linear Probabilistic Concepts

We consider the problem of maximizing the total number of successes while learning about a probability function determining the likelihood of a success. In particular, we consider the case in which the probability function is represented by a linear function of the attribute vector associated with each action/choice. In the scenario we consider, learning proceeds in trials and in each trial, the algorithm is given a number of alternatives to choose from, each having an attribute vector associated with it, and for the alternative it selects it gets either a success or a failure with probability determined by applying a xed but unknown linear success probability function to the attribute vector. Our algorithms consist of a learning method like the Widrow-Ho rule and a probabilistic selection strategy which work together to resolve the so-called exploration-exploitation tradeo . We analyze the performance of these methods by proving bounds on the worst-case regret, or how many less successes they expect to get as compared to the ideal (but unrealistic) strategy that knows the target probability function. Our analysis shows that the worst-case (expected) regret for our methods is almost optimal: the upper bounds grow with the number m of trials and the number n of alternatives like O(m 3=4 n 1=2 ) and O(m 4=5 n 2=5 ), and the lower bound is
The Impact of Sensor Node Distribution on Routing Protocols Performance: A Comparitive Study

The contemporary routing algorithms were built and tested under the assumption of uniformly distributed sensor nodes. However, this assumption is not always true. In some industrial applications and due to the scope of the ongoing monitoring process, sensors are installed and condensed in some area, while they are sparse in other areas. In this work, we investigate the impact of sensor node deployment distributions on the performance of different flavors of LEACH routing algorithm. Further, we study the impact of base station location, and different data loads. A comparison between LEACH and LEACH-C is conducted. The results show that different sensor distributions leads to significant differences in network performance. Furthermore, it shows that LEACH-C out performs LEACH almost in all distributions variations and base station locations.
Mapping the business model canvas to ArchiMate

Many IT projects fail to succeed in the market, as they start purely from technology. Much effort is therefore wasted, while the potential benefits are not realized. We argue that the design process should start with creating a business model, which is then translated to an architecture to ensure fitness for market of the future system. Therefore, we propose a mapping from Osterwalder's business modeling canvas and ontology to the enterprise architecture modeling standard ArchiMate, which makes the above translation possible and represents a formal basis for business modeling in ArchiMate. A case study illustrates the mapping between the two languages.
Survey Of Currency Recognition System Using Image Processing

Image processing based currency recognition technique consists of few basic steps like image acquisition, its pre-processing and finally recognition of the currency. Normally camera or scanner is used for image acquisition. Then these images are processed by using various techniques of image processing and various features are extracted from the images which are the key concept behind currency classification. Application area of currency recognition includes foreign exchange, automatic selling of things and in banks. Recognition ability depends on the currency note characteristics of particular country and extraction of features.
Ischaemic cardiac outcomes in patients with atrial fibrillation treated with vitamin K antagonism or factor Xa inhibition: results from the ROCKET AF trial.

AIMS We investigated the prevalence of prior myocardial infarction (MI) and incidence of ischaemic cardiovascular (CV) events among atrial fibrillation (AF) patients. METHODS AND RESULTS In ROCKET AF, 14 264 patients with nonvalvular AF were randomized to rivaroxaban or warfarin. The key efficacy outcome for these analyses was CV death, MI, and unstable angina (UA). This pre-specified analysis was performed on patients while on treatment. Rates are per 100 patient-years. Overall, 2468 (17%) patients had prior MI at enrollment. Compared with patients without prior MI, these patients were more likely to be male (75 vs. 57%), on aspirin at baseline (47 vs. 34%), have prior congestive heart failure (78 vs. 59%), diabetes (47 vs. 39%), hypertension (94 vs. 90%), higher mean CHADS2 score (3.64 vs. 3.43), and fewer prior strokes or transient ischaemic attacks (46 vs. 54%). CV death, MI, or UA rates tended to be lower in patients assigned rivaroxaban compared with warfarin [2.70 vs. 3.15; hazard ratio (HR) 0.86, 95% confidence interval (CI) 0.73-1.00; P = 0.0509]. CV death, MI, or UA rates were higher in those with prior MI compared with no prior MI (6.68 vs. 2.19; HR 3.04, 95% CI 2.59-3.56) with consistent results for CV death, MI, or UA for rivaroxaban compared with warfarin in prior MI compared with no prior MI (P interaction = 0.10). CONCLUSION Prior MI was common and associated with substantial risk for subsequent cardiac events. Patients with prior MI assigned rivaroxaban compared with warfarin had a non-significant 14% reduction of ischaemic cardiac events.
Pose estimation using local structure-specific shape and appearance context

We address the problem of estimating the alignment pose between two models using structure-specific local descriptors. Our descriptors are generated using a combination of 2D image data and 3D contextual shape data, resulting in a set of semi-local descriptors containing rich appearance and shape information for both edge and texture structures. This is achieved by defining feature space relations which describe the neighborhood of a descriptor. By quantitative evaluations, we show that our descriptors provide high discriminative power compared to state of the art approaches. In addition, we show how to utilize this for the estimation of the alignment pose between two point sets. We present experiments both in controlled and real-life scenarios to validate our approach.
Multilevel Coding over Two-Hop Single-User Networks

In this paper, a two-hop network in which information is transmitted from a source via a relay to a destination is considered. It is assumed that the channels are static fading with additive white Gaussian noise. All nodes are equipped with a single antenna and the Channel State Information (CSI) of each hop is not available at the corresponding transmitter. The relay is assumed to be simple, i.e., not capable of data buffering over multiple coding blocks, water-filling over time, or rescheduling. A commonly used design criterion in such configurations is the maximization of the average received rate at the destination. We show that using a continuum of multilevel codes at both the source and the relay, in conjunction with decode and forward strategy at the relay, performs optimum in this setup. In addition, we present a scheme to optimally allocate the available source and relay powers to different levels of their corresponding codes. The performance of this scheme is evaluated assuming Rayleigh fading and compared with the previously known strategies.
On the consistency of EKF-SLAM: Focusing on the observation models

In this paper a new strategy for handling the observation information of a bearing-range sensor throughout the filtering process of EKF-SLAM is proposed. This new strategy is advised based on a thorough consistency analysis and aims to improve the process consistency while reducing the computational cost. At first, three different possible observation models are introduced for the EKF-SLAM solution for a robot equipped with a bearing-range sensor. General form of the covariance matrix and the level of inconsistency in the robot orientation estimate is then calculated for these variants, and based on the numerical comparison of the estimation results, it is proposed to use the bearing and range information of a feature in the initialization step of EKF-SLAM. However, it is recommended to use only the bearing information to perform other iteration steps. The simulation observations verify that the new strategy yields to more consistent estimates both for the robot and the features. Moreover, through the proposed consistency analysis, it is shown that since the source of consistency improvement is independent from the choice of the motion model, it gives us an advantage over other existing methods that assume a specific motion models for consistency improvement.
Stochastic models for chemically reacting systems using polynomial stochastic hybrid systems

A stochastic model for chemical reactions is presented, which represents the population of various species involved in a chemical reaction as the continuous state of a polynomial stochastic hybrid system (pSHS). pSHSs correspond to stochastic hybrid systems with polynomial continuous vector fields, reset maps, and transition intensities. We show that for pSHSs, the dynamics of the statistical moments of its continuous states, evolves according to infinite‐dimensional linear ordinary differential equations (ODEs), which can be approximated by finite‐dimensional nonlinear ODEs with arbitrary precision. Based on this result, a procedure to build this types of approximation is provided.
CONVOLUITIONAL NEURAL NETWORKS FOR MS LESION SEGMENTATION , METHOD DESCRIPTION OF DIAG TEAM

Recently deep neural networks have shown many successful applications in different domains. For this lesion segmentation task, we utilize a deep convolutional neural network with 5 layers in a sliding window fashion to create a voxel-based classifier. We evaluate our system with Dice similarity, misclassification rate and area under the ROC curve. Based on experimental results our proposed CAD system reaches average Dice similarity, misclassification rate and area under the ROC curve of 0.976, 0.565, 0.073 respectively.
Biophysical Properties of Cultivated Pastures in the Brazilian Savanna Biome: An Analysis in the Spatial-Temporal Domains Based on Ground and Satellite Data

Abstract: Brazil has the largest commercial beef cattle herd in the world, with cattle ranching being particularly prominent in the 200-million ha, Brazilian neotropical moist savanna biome, known as Cerrado, one of the world’s hotspots for biodiversity conservation. As decreasing productivity is a major concern affecting the Cerrado pasturelands, evaluation of pasture conditions through the determination of biophysical parameters is instrumental for more effective management practices and herd occupation strategies. Within this context, the primary goal of this study was the regional assessment of pasture biophysical properties, through the scaling of wet- and dry-season ground truth data (total biomass, green biomass, and % green cover) via the combined use of high (Landsat-TM) and moderate (MODIS) spatial resolution vegetation index images. Based on the high correlation found between NDVI (normalized difference vegetation index) and % green cover (r = 0.95), monthly MODIS-based % green cover images were derived for the 2009–2010 hydrological cycle, which were able to capture major regional patterns and differences in pasture biophysical responses, including the increasing greenness values towards the southern portions of the biome, due to both local conditions (e.g., more fertile
Analysis of a Two-Scale, Locally Conservative Subgrid Upscaling for Elliptic Problems

We present a two-scale theoretical framework for approximating the solution of a second order elliptic problem. The elliptic coefficient is assumed to vary on a scale that can be resolved on a fine numerical grid, but limits on computational power require that computations be performed on a coarse grid. We consider the elliptic problem in mixed variational form over $W \times {\bf V} \subset L^2 \times H({\rm div})$. We base our scale expansion on local mass conservation over the coarse grid. It is used to define a direct sum decomposition of $W \times {\bf V}$ into coarse and "subgrid" subspaces $W_c \times {\bf V}_c$ and $\delta W \times \delta{\bf V}$ such that (1) $\nabla \cdot {\bf V}_c=W_c$ and $\nabla \cdot \delta{\bf V} = \delta W$, and (2) the space $\delta{\bf V}$ is locally supported over the coarse mesh. We then explicitly decompose the variational problem into coarse and subgrid scale problems. The subgrid problem gives a well-defined operator taking $W_c \times {\bf V}_c$ to $\delta W \times \delta{\bf V}$, which is localized in space, and it is used to upscale, that is, to remove the subgrid from the coarse-scale problem. Using standard mixed finite element spaces, two-scale mixed spaces are defined. A mixed approximation is defined, which can be viewed as a type of variational multiscale method or a residual-free bubble technique. A numerical Green's function approach is used to make the approximation to the subgrid operator efficient to compute. A mixed method $\pi$-operator is defined for the two-scale approximation spaces and used to show optimal order error estimates.