Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary Intakes of Urban Adolescents of Sialkot, Pakistan Do Not Meet the Standards of Adequacy

There is paucity of national data on dietary intakes of adolescents in Pakistan presently. Therefore, this study was conducted to investigate the dietary intake and nutritional status of urban adolescents in a cross-sectional descriptive survey. A convenience sample of 328 high school students (46.67% female and 53.33% male; mean age, 14.3 years) in Sialkot, Pakistan was analyzed by a demographic questionnaire with lifestyle and health-related questions and kept a 3-day food record for evaluation of dietary intake. Anthropometric measurements, including body composition, were performed. Female adolescents had significantly lower total energy intake than male adolescents (P<0.001); however, percentage of killocalorie distribution of protein (12.5%), carbohydrate (51.5%) and fat (36.3%) was similar between male and female adolescents. Male participants had significantly higher micronutrient intakes than female adolescents while female consumed more caffeine than male participants. Both male and female did not meet the estimated average requirements and/or adequate intakes for vitamins A, C, D and E, calcium, potassium and magnesium, whereas more than 70% of female adolescents did not meet the recommendations for vitamin A, D, E, folic acid, phosphorus, zinc and approximately 44% of them did not meet the estimated average requirements for vitamin C, sodium, potassium, iron and manganese. Dietary intake among Pakistani high schools student population intakes in many macroand micro-minerals, especially in female adolescents, do not meet the standards of adequacy and it reflects the inadequate dietary intake and eating patterns compared with adolescents in other countries.
Beta-band intermuscular coherence: a novel biomarker of upper motor neuron dysfunction in motor neuron disease

In motor neuron disease, the focus of therapy is to prevent or slow neuronal degeneration with neuroprotective pharmacological agents; early diagnosis and treatment are thus essential. Incorporation of needle electromyographic evidence of lower motor neuron degeneration into diagnostic criteria has undoubtedly advanced diagnosis, but even earlier diagnosis might be possible by including tests of subclinical upper motor neuron disease. We hypothesized that beta-band (15–30 Hz) intermuscular coherence could be used as an electrophysiological marker of upper motor neuron integrity in such patients. We measured intermuscular coherence in eight patients who conformed to established diagnostic criteria for primary lateral sclerosis and six patients with progressive muscular atrophy, together with 16 age-matched controls. In the primary lateral sclerosis variant of motor neuron disease, there is selective destruction of motor cortical layer V pyramidal neurons and degeneration of the corticospinal tract, without involvement of anterior horn cells. In progressive muscular atrophy, there is selective degeneration of anterior horn cells but a normal corticospinal tract. All patients with primary lateral sclerosis had abnormal motor-evoked potentials as assessed using transcranial magnetic stimulation, whereas these were similar to controls in progressive muscular atrophy. Upper and lower limb intermuscular coherence was measured during a precision grip and an ankle dorsiflexion task, respectively. Significant beta-band coherence was observed in all control subjects and all patients with progressive muscular atrophy tested, but not in the patients with primary lateral sclerosis. We conclude that intermuscular coherence in the 15–30 Hz range is dependent on an intact corticospinal tract but persists in the face of selective anterior horn cell destruction. Based on the distributions of coherence values measured from patients with primary lateral sclerosis and control subjects, we estimated the likelihood that a given measurement reflects corticospinal tract degeneration. Therefore, intermuscular coherence has potential as a quantitative test of subclinical upper motor neuron involvement in motor neuron disease.
Towards an analytical framework of organizational innovation in the service industry

This paper discusses the analytical typology of organizational innovation in service industry. After outlining empirical approaches, this paper offers a new measurement model for empirical and theoretical researches. With the construction of the organizational innovation model, the empirical study concludes that the weights of important dimensions in measuring organizational innovation measurement are: technical innovation (0.416), administrative innovation (0.584), external relational innovation (0.318), internal organizational innovation (0.266), product/service innovation (0.262), and process innovation (0.154). This paper proposes a typology and tests for the validity of a multidimensional measure of organizational innovation. Key words: Service industry, innovation, organizational innovation (OI), analytical framework, analytic hierarchy process (AHP).
High resolution virtual reality

I define the lower layers of Virtual Reality to be: the highly-accurate, real-time simulation by computer of the interaction of the physical world with human senses. My focus is on the visual system, the talk will desceribe the techniques used to perform this simulation in several running systems at Sun microsystems. These include: correct perspective viewing equations, correcting for the optics of both human includes details of the Virtual Portal, a 1K x 2K walk-in virtual display device.
Distribution of the Object Oriented Databases. A Viewpoint of the MVDB Model's Methodology and Architecture

In databases, much work has been done towards extending models with advanced tools such as view technology, schema evolution support, multiple classification, role modeling and viewpoints. Over the past years, most of the research dealing with the object multiple representation and evolution has proposed to enrich the monolithic vision of the classical object approach in which an object belongs to one hierarchy class. In particular, the integration of the viewpoint mechanism to the conventional object-oriented data model gives it flexibility and allows one to improve the modeling power of objects. The viewpoint paradigm refers to the multiple descriptions, the distribution, and the evolution of object. Also, it can be an undeniable contribution for a distributed design of complex databases. The motivation of this paper is to define an object data model integrating viewpoints in databases and to present a federated database architecture integrating multiple viewpoint sources following a local-as-extended-view data integration approach.
DOREMUS: Doing Reusable Musical Data

This paper introduces DOREMUS—a semantic web project aiming to provide common knowledge models and shared multilingual vocabularies to cultural institutions, publishers, distributors and users in the musical domain. The project develops methods to describe, publish, connect and contextualize music catalogs on the web of data. Our focus is on the description of classical and traditional musical works as well as their interpretations (events).
YtxR, a Conserved LysR-Like Regulator That Induces Expression of Genes Encoding a Putative ADP-Ribosyltransferase Toxin Homologue in Yersinia enterocolitica

ABSTRACT Yersinia enterocolitica causes human gastroenteritis, and many isolates have been classified as either “American” or “non-American” strains based on their geographic prevalence and virulence properties. In this study we describe identification of a transcriptional regulator that controls expression of the Y. enterocolitica ytxAB genes. The ytxAB genes have the potential to encode an ADP-ribosylating toxin with similarity to pertussis toxin. However, a ytxAB null mutation did not affect virulence in mice. Nevertheless, the ytxAB genes are conserved in many Y. enterocolitica strains. Interestingly, American and non-American strains have different ytxAB alleles encoding proteins that are only 50 to 60% identical. To obtain further insight into the ytxAB locus, we investigated whether it is regulated as part of a known or novel regulon. Transposon mutagenesis identified a LysR-like regulator, which we designated YtxR. Expression of ytxR from a nonnative promoter increased Φ(ytxA-lacZ) operon fusion expression up to 35-fold. YtxR also activated expression of its own promoter. DNase I footprinting showed that a His6-YtxR fusion protein directly interacted with the ytxA and ytxR control regions at similar distances upstream of their probable transcription initiation sites, identified by primer extension. Deletion analysis demonstrated that removal of the regions protected by His6-YtxR in vitro eliminated YtxR-dependent induction in vivo. The ytxAB locus is not present in most Yersinia species. In contrast, ytxR is conserved in multiple Yersinia species, as well as in the closely related organisms Photorhabdus luminescens and Photorhabdus asymbiotica. These observations suggest that YtxR may play a conserved role involving regulation of other genes besides ytxAB.
Risk-Neutral Pricing and Hedging of In-Play Football Bets

ABSTRACT A risk-neutral valuation framework is developed for pricing and hedging in-play football bets based on modelling scores by independent Poisson processes with constant intensities. The Fundamental Theorems of Asset Pricing are applied to this set-up which enables us to derive novel arbitrage-free valuation formulæ for contracts currently traded in the market. We also describe how to calibrate the model to the market and how trades can be replicated and hedged.
A simple expert system

Expert systems are one field of artificial intelligence (AI) that has received considerable recent attention. These systems generally are written in Lisp or Prolog -- languages that are interpretive, have flexible data accessing mechanisms, and use powerful string manipulation tools. This raises two questions: what are expert systems, and can they be implemented using MUMPS? Some answers are presented in this paper.
On modeling product advertisement in social networks

Advertising via social networks is receiving more attention these days. Given a fixed investment (e.g., free samples), a company needs to find out the final probability that users will purchase the product. In this paper we characterize and model various influence mechanisms that govern the word-of-mouth spread of advertisements in large social networks. We use the local mean field (LMF) technique to analyze large scale networks wherein states of nodes can be changed by various influence mechanisms. Extensive simulations are carried out to validate the accuracy of our model, and the results also provide insights on designing advertising strategies.
Optimal Design of Uniform Planar Antenna Arrays for Strong Line-of-Sight MIMO Channels

We investigate the optimal design of uniform planar antenna arrays employed in multiple-input multiple-output communications where a strong line-of-sight (LOS) component is present. A new general geometrical model is introduced to model the LOS channel, which allows for any orientation of the two arrays. Based on this model, we derive the optimal design equations with respect to maximizing Shannon capacity, which turn out to be solvable for several interesting cases. The solutions reveal that the proposed principle is best suited for fixed applications, as e.g. fixed wireless access. The LOS channel matrix is used in a Ricean channel model to evaluate performance under different channel conditions. Results show that even with some deviation from the optimal design, we get good performance compared to the case of uncorrelated Rayleigh subchannels
Parameterization of the Atmospheric Boundary Layer

tion models, in spite of some advances, the boundary layer is still not represented realistically. Figure 1 illustrates an aspect of this problem by showing the opposing response of boundary layer (low) clouds to perturbation experiments (e.g., double CO2) in current climate models. The general problem of parameterization in fluids dates back to the first modern studies of turbulence during the nineteenth and early twentieth centuries. By then, it was already clear that for turbulent flows such as the atmosphere, it was not feasible (or even relevant) to try and follow every parcel of f luid in its turbulent trajectories. Instead, research should concentrate on trying to understand the statistical properties of turbulent f lows. With the advent of computers came the possibility of developing numerical models for weather and climate prediction. Numerical discretizations imply a limit for the temporal/spatial scales below which the flow cannot O ne of the main components of the climate system is the atmospheric boundary layer, which mediates the interactions between the ocean/land surface and the free atmosphere. Several boundary Parameterization of the Atmospheric Boundary Layer A View from Just Above the Inversion
Multiprocessor Scheduling of Dependent Tasks to Minimize Makespan and Reliability Cost Using NSGA-II

Algorithms developed for scheduling applications on heterogeneous multiprocessor system focus on asingle objective such as execution time, cost or total data transmission time. However, if more than oneobjective (e.g. execution cost and time, which may be in conflict) are considered, then the problem becomes more challenging. This project is proposed to develop a multiobjective scheduling algorithm using Evolutionary techniques for scheduling a set of dependent tasks on available resources in a multiprocessor environment which will minimize the makespan and reliability cost. A Non-dominated sorting Genetic Algorithm-II procedure has been developed to get the pareto- optimal solutions. NSGA-II is a Elitist Evolutionary algorithm, and it takes the initial parental solution without any changes, in all iteration to eliminate the problem of loss of some pareto-optimal solutions.NSGA-II uses crowding distance concept to create a diversity of the solutions.
LT code design for inactivation decoding

We present a simple model of inactivation decoding for LT codes which can be used to estimate the decoding complexity as a function of the LT code degree distribution. The model is shown to be accurate in variety of settings of practical importance. The proposed method allows to perform a numerical optimization on the degree distribution of a LT code aiming at minimizing the number of inactivations required for decoding.
An Experimental Parser

Uppsala Chart Processor is a linguistic processor for phonological, morphological, and syntactic analysis. It incorporates the basic mechanisms of the General Syntactic Processor. Linguistic rules as well as dictionary articles are presented to the processor in a procedural formalism, the UCP-formalism. The control of the processing rests upon the grammar and the dictionaries. Special attention has been devoted to problems concerning the interplay between different kinds of linguistic processes.
Galois groups of prime degree polynomials with nonreal roots

In the process of computing the Galois group of a prime degree polynomial $f(x)$ over $\mathbb Q$ we suggest a preliminary checking for the existence of non-real roots. If $f(x)$ has non-real roots, then combining a 1871 result of Jordan and the classification of transitive groups of prime degree which follows from CFSG we get that the Galois group of $f(x)$ contains $A_p$ or is one of a short list. Let $f(x)\in \mathbb Q [x] $ be an irreducible polynomial of prime degree $p \geq 5$ and $r=2s$ be the number of non-real roots of $f(x)$. We show that if $s$ satisfies $s (s \log s + 2 \log s + 3) \leq p $ then $Gal (f)= A_p, S_p$.
A Comprehensive Dynamic Bayesian Model Combination Approach to Forecasting Equity Premia

We introduce a novel dynamic Bayesian model combination approach for predicting aggregate stock returns. Our method involves combining predictive densities in a data-adaptive fashion and simultaneously features (i) uncertainty about relevant predictor variables, (ii) parameter instability, (iii) time-varying volatility, (iv) time-varying model weights and (v) multivariate information. We analyze the predictability of monthly S&P 500 returns and disentangle which components of prediction models pay off in terms of statistical accuracy and economic utility. As a key feature of our approach, we formally address the (possibly) diminishing relevance of past information over time. The flexibility embedded in our approach enhances density forecasting accuracy and provides sizeable economic utility gains. We find predictability to be strongly tied to business cycle fluctuations and document disagreement between statistical and economic metrics of forecast performance.
ScreenX: Public Immersive Theatres with Uniform Movie Viewing Experiences

This paper introduces ScreenX, which is a novel movie viewing platform that enables ordinary movie theatres to become multi-projection movie theatres. This enables the general public to enjoy immersive viewing experiences. The left and right side walls are used to form surrounding screens. This surrounding display environment delivers a strong sense of immersion in general movie viewing. However, naïve display of the content on the side walls results in the appearance of distorted images according to the location of the viewer. In addition, the different dimensions in width, height, and depth among theatres may lead to different viewing experiences. Therefore, for successful deployment of this novel platform, an approach to providing similar movie viewing experiences across target theatres is presented. The proposed image representation model ensures minimum average distortion of the images displayed on the side walls when viewed from different locations. Furthermore, the proposed model assists with determining the appropriate variation of the content according to the diverse viewing environments of different theatres. The theatre suitability estimation method excludes outlier theatres that have extraordinary dimensions. In addition, the content production guidelines indicate appropriate regions to place scene elements for the side wall, depending on their importance. The experiments demonstrate that the proposed method improves the movie viewing experiences in ScreenX theatres. Finally, ScreenX and the proposed techniques are discussed with regard to various aspects and the research issues that are relevant to this movie viewing platform are summarized.
Extending Relevance Model for Relevance Feedback

Abstract : Relevance feedback is the retrieval task where the system is given not only an information need, but also some relevance judgement information, usually from users' feedback for an initial result list by the system. With different amount of feedback information available, the optimal feedback strategy might be very different. In TREC Relevance Feedback task, the system is given different sets of feedback information from 1 relevant document to over 40 judgements with at least 3 relevant. Thus, in this work, we try to develop a feedback algorithm that works well on all levels of feedback by extending the relevance model for pseudo relevance feedback to include judged relevant documents when scoring feedback terms. Within these different levels of feedback, it is more difficult for the feedback algorithm to perform well when given minimal amount of feedback. Experiments show that our algorithm performs robustly in those difficult cases.
DFS-Perf : A Scalable and Unified Benchmarking Framework for Distributed File Systems

A distributed file system (DFS) is a key component of virtually any cluster computing system. The performance of such system depends heavily on the underlying DFS design and deployment. As a result, it is critical to characterize the performance and design trade-offs of DFSes with respect to cluster configurations and real-world workloads. To this end, we present DFS-Perf, a scalable, extensible, and low-overhead benchmarking framework to evaluate the properties and the performance of various DFS implementations. DFS-Perf uses a highly parallel architecture to cover a large variety of workloads at different scales, and provides an extensible interface to incorporate user-defined workloads and integrate with various DFSes. As a proof of concept, our current DFS-Perf implementation includes several built-in benchmarks and workloads, including machine learning and SQL applications. We present performance comparisons of four stateof-the-art DFS designs, namely Alluxio, CephFS, GlusterFS, and HDFS, on a cluster with 40 nodes (960 cores). We demonstrate that DFS-Perf can provide guidance on existing DFS designs and implementations, while adding 5.7% overhead.
Detection of shilling attacks in collaborative filtering recommender systems

Collaborative filtering recommender systems are essentially information systems which are capable of combining the judgment of a large group of people to make personalized recommendations and thereby alleviate the so-called information overload problem. However,collaborative filtering recommender systems are generally vulnerable to shilling attacks. Attackers can inject carefully chosen profiles into recommender systems in order to bias the recommendation results to their benefits. This may lead to a significant negative impact on the robustness of the systems. The main contribution of this paper is to build a probabilistic model for attack detection in the framework of probabilistic generative model. Experimental results show that this model can effectively detect shilling attacks of typical types.
Effects of plasma flow velocity on melt-layer splashing and erosion during plasma instabilities

It is recognized both experimentally and computationally that the main damage of divertor in fusion devices such as ITER could be due to melting of metallic plasma facing components such as tungsten developed during plasma instabilities. Macroscopic melt motion and splashing with ejection of molten droplets into plasma are major concern. The computational modelling of uncoupled/coupled plasma–melt flows is carried out using the developed VoF-MHD model. The goal of this research is to study the effect of viscous plasma flowing with a velocity of 0–5 km s−1 on the melt stability. Development of running waves with large wavelengths is observed on the melt surface in the absence of plasma impact. The magnetic field of 5 T that is parallel to the direction of melt motion completely damps these surface waves. When the magnetic field is perpendicular to the direction of melt motion, the small-amplitude standing waves are formed. The viscous plasma streaming with ∼0.1–5 km s−1 over the melt surface develops waves that are not damped by the magnetic field which is either parallel or normal to the direction of melt motion. It is observed that the surface waves are generated much faster at higher plasma speeds and their wavelength decreases accordingly. The high-speed viscous plasma flowing with ∼5 km s−1 produces small melt ripples that break up into droplets carried away by the plasma wind. This is a major concern for magnetic fusion as a reliable source of energy production.