Miracle-dz/UniFAR-FTUs huggingface dataset:
Obesity: An epidemiological perspective from Asia and its relationship to gastrointestinal and liver cancers

Obesity is major health problem in the Asia‐Pacific region. The proportion of people who are overweight and obese in the region has increased dramatically and is closely linked to the increasing affluence in the region. While the body mass index has been used as a yardstick in many published studies, it has been noted that Asian patients have a greater percentage body fat for a given body mass index and especially abdominal or visceral obesity.
A Comparison of Radiolocation Methods for Mobile Terminals by Distance Measurements

Popular methods to locate wireless terminals use measurements of Received Signal Strength (RSS), Time of Arrival (ToA), and Time Difference of Arrival (TDoA). RSS has low cost and experiments for small scale networks show that it provides good accuracy. With large scale networks, experiments show that ToA/TDoA has better accuracy than RSS. This paper derives Cramer-Rao bounds for the RSS, ToA, and TDoA estimators and calculates limits on accuracy. These limits are used to demonstrate analytically the reason for the results at different size scales and can be used to identify when the cheaper RSS location method can be utilized.
eview ractionating theory of mind : A meta-analysis of functional brain maging studies

We meta-analyzed imaging studies on theory of mind and formed individual task groups based on stimuli and instructions. Overlap in brain activation between all task groups was found in the mPFC and in the bilateral posterior TPJ. This supports the idea of a core network for theory of mind that is activated whenever we are reasoning about mental states, irrespective of the taskand stimulus-formats (Mar, 2011). In addition, we found a number of task-related activation differences surrounding this core-network. ROI based analyses show that areas in the TPJ, the mPFC, the precuneus, the temporal lobes and the inferior frontal gyri have distinct profiles of task-related activation. Functional accounts of these areas are eta-analysis ask groups edial prefrontal cortex recuneus emporo-parietal junction reviewed and discussed with respect to our findings. © 2014 Published by Elsevier Ltd. nterior temporal lobe nferior frontal gyrus
Isolated third nerve palsy complicating rickettsial infection : A rare neurological complication

Corresponding Author N S Premathilake < nspremathilake@gmail.com>, E-mail: https://orcid.org/0000-0003-4256-9396 Submitted: July 2018, Accepted: August 2018, Published December 2018 Competing Interests: Authors have declared that no competing interests exist © Authors. This is an open-access article distributed under a Creative Commons Attribution-Share Alike 4.0 International License (CC BY-SA 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are attributed and materials are shared under the same license.
MODELING OF TASK SCHEDULING IN DESKTOP GRID SYSTEMS AT THE INITIAL STAGE OF DEVELOPMENT

The paper presents an overview of modern methods for task scheduling in desktop grid systems, estimates of the quality of methods, including: the time of execution of all tasks, the level of resource utilization. Heuristic approach to task scheduling is considered, which allows ensuring high performance and reliability of such systems at the early stages of development. A comparative analysis of the results of computational experiments performed with the help of the GridSim high performance computing simulation tool for various desktop grid system configurations is carried out.
Analysis of Different Cloud-RAN Implementation Strategies in Small Cells Scenarios

The main objective of this work was to analyse different strategies for the implementation of Cloud Radio Access Networks (C-RAN) in an existing LTE-A network, by taking advantage of the functional split of a base station into Remote Radio Head and Baseband Unit, with the centralisation of the processing power in standard data centres. Four different strategies are compared: Minimise Delay, Load Balancing, Maximise Multiplexing Gain, and Minimise Number of Pools. The location of existing base station and possible data centres is taken as input. The metrics taken for the analysis are fronthaul latency, pool capacity of hourly traffic, processing power capacity, and multiplexing gain. The total cost of ownership model is also presented, to estimate possible cost savings. The model was implemented in a tool that enables the study of any scenario. The results obtained for the city of Oporto prove that a C-RAN implementation with 19 pools is possible without introducing latency problems; the operator can combine different traffic profiles, and achieve a multiplexing gain up to 1.31 that can be translated into capacity savings, and cost reductions of 63 % in capital investment and 31 % in operational expenditure can be achieved.
Modeling the spread of active worms

Active worms spread in an automated fashion and can flood the Internet in a very short time. Modeling the spread of active worms can help us understand how active worms spread, and how we can monitor and defend against the propagation of worms effectively. In this paper, we present a mathematical model, referred to as the Analytical Active Worm Propagation (AAWP) model, which characterizes the propagation of worms that employ random scanning. We compare our model with the Epidemiological model and Weaver's simulator. Our results show that our model can characterize the spread of worms effectively. Taking the Code Red v2 worm as an example, we give a quantitative analysis for monitoring, detecting and defending against worms. Furthermore, we extend our AAWP model to understand the spread of worms that employ local subnet scanning. To the best of our knowledge, there is no model for the spread of a worm that employs the localized scanning strategy and we believe that this is the first attempt on understanding local subnet scanning quantitatively.
Association of Single Nucleotide Polymorphism in Chromosome 11 with Autism Spectrum Disorder

Abstract Several genetic loci in chromosomes 11 and 15 have recently been associated with non-syndromic autism spectrum disorder (ASD) in populations from North America and Europe. The aim of the present study was to investigate whether such an association exists in a Latvian population. Ninety-five patients with ASD in the age range 3–20 years (mean age 8 years, SD 3.18) participated in the study. The control group consisted of 161 healthy, non-related individuals without ASD randomly selected from the Latvian Genome Database. Four single nucleotide polymorphisms (SNPs) — rs11212733, SNP rs1394119, rs2421826, rs1454985 — were genotyped by the TaqMan method. Allele frequency differences between ASD patients and control subjects were compared for each SNP using a standard chi-square test with Bonferroni correction. The level of statistical significance was set at 0.05 for nominal association. Only the genetic marker rs11212733, localised on the long arm of chromosome 11 in locus 22.3, was found to be strongly associated with the ASD patient group (χ2 6.982, Padjusted 0.033, odds ratio 1.625). Our data demonstrating a significant relationship between the SNP rs11212733 and the development of ASD in a Latvian population suggest that it is not a population-specific relationship. Thus, future studies focusing on the DDX10 gene and related genetic loci are needed.
่Ecotourism Mix, Good Practice, and Green Marketing: An Approach Towards the Quality Tourism Business

During the past decades, the literature on tourism marketing contributes the knowledge to large businesses in the tourism industry (e.g. hotels, airlines, restaurants). However, the knowledge on green marketing given to a small business like the tour operators in reducing tourism impacts is limited. In addition, the global trend concerns more on the environmental issues. In particular, there are needs for promoting responsible tourism businesses, ethical conducts and green marketing. This article, therefore, has the objectives to 1) introduce the ecotourism mix contributing to the identification of ecotourism good practice for the tour operators and 2) provide green marketing implications that care the environment. Responsible tour operators and ecotourism tour operators may implement the suggested green marketing to develop or improve their tour conducts in order to be the quality tourism business and the alternatives for travelers.
Towards Multi-Person Pose Tracking : Bottom-up and Top-down Methods

In this paper, we focus on the challenging problem of multi-person pose tracking in the wild. Recent multi-person articulated tracking methods can be categorized into the top-down and bottom-up approaches. We investigate the advantages and disadvantages of both bottom-up and topdown methods on various datasets. We propose a novel bottom-up joint detector, termed as MSPAF to extract multiscale features and implement a human detector based on recent development of object detection. Incorporating the global context, we use a human detector to rule out bottomup false alarms which significantly improves the tracking results. Following the commonly used graph partitioning formulation, we construct a spatio-temporal graph and solve a minimum cost multicut problem for human pose tracking. Our proposed method achieves the state-of-the-art performance on both ”Multi-Person PoseTrack” dataset and ”ICCV 2017 PoseTrack Challenge” dataset.
2016 Ieee International Conference on Big Data (big Data) Leveraging Cloud Computing to Convert the Non- Intrusive Load Monitor into a Powerful Framework for Grid-responsive Buildings

— This paper describes how the non-intrusive load monitoring technique can be applied to develop a powerful framework for grid-responsive buildings, particularly in the small commercial and residential sector. Specifically, recent advances have made it cost-effective to monitor a number of electrical circuits in a building using low-cost embedded platforms that can send their data to cloud-computing and data-storage services. This approach significantly reduces the effort required to deploy and commission monitoring solutions, specifically because the cloud allows one to create a large library of load patterns and it provides a powerful platform for computation. This approach thus solves one of the major challenges in power monitoring and energy management, which has been the development of robust unsupervised learning algorithms that eliminate the need for costly human involvement. The cloud also provides an opportunity to learn fault patterns and to predict the performance of individual building systems. This paper describes the unsupervised training that can be performed in the cloud using intuition about the underlying physics of major load devices. It also describes how load on-off patterns can be used for fault detection as well as load prediction and control and the deployment of powerful algorithms for a large data set obtained across a large portfolio is discussed.
Building Detection Using LIDAR Data and Multispectral Images

A method the automatic detection of buildings from LIDAR data and multispectral images is presented. A classification technique using various cues derived from these data is applied in a hierarchic way to overcome the problems encountered in areas of heterogeneous appearance of buildings. Both first and last pulse data and the normalised difference vegetation index are used in that process. We describe the algorithms involved, giving examples for a test site in Fairfield (Victoria).
UEBER DIE VERSCHIEDENEN METHODEN DES UEBERSEZENS

[. ] Ueberall, wo die Rede nicht ganz durch vor Augen liegende Gegenstände oder äußere Thatsachen gebunden ist, welche sie nur aussprechen soll, wo also der redende mehr oder minder selbstthätig denkt, also sich aussprechen will, steht der redende in einem zwiefachen Verhältniß zur Sprache, und seine Rede wird schon nur richtig verstanden, in wiefern dieses Verhältnis richtig aufgefaßt wird. Jeder Mensch ist auf der einen Seite in der Gewalt der Sprache, die er redet; er und sein ganzes Denken ist ein Erzeugniß derselben. Er kann nichts mit völliger Bestimmtheit denken, was außerhalb der Grenzen derselben läge; die Gestalt seiner Begriffe, die Art und die Grenzen ihrer Verknüpfbarkeit ist ihm vorgezeichnet durch die Sprache, in der er geboren und erzogen ist, Verstand und Fantasie sind durch sie gebunden. Auf der andern Seite aber bildet jeder freidenkende geistig selbstthätige Mensch auch seinerseits die Sprache. Denn wie anders als durch diese Einwirkungen wäre sie geworden und gewachsen von ihrem ersten rohen Zustande zu der vollkommneren Ausbildung in Wissenschaft und Kunst? In diesem Sinne also ist es die lebendige Kraft des einzelnen, welche in dem bildsamen Stoff der Sprache neue Formen hervorbringt, ursprünglich nur für den augenblikklichen Zwekk ein vorübergehendes Bewußtsein mitzutheilen, von denen aber bald mehr bald minder in der Sprache zurükkbleibt und von andern aufgenommen weiter bildend um sich greift. Ja man kann sagen, nur in dem Maaß einer so auf die Sprache wirkt, verdient er weiter als in seinem jedesmaligen unmittelbaren Bereich vernommen zu werden. Jede Rede verhallt nothwendig bald, welche durch tausend Organe immer wieder eben so kann hervorgebracht werden; nur die kann und darf länger bleiben, welche einen neuen Moment im Leben der Sprache selbst bildet. Daher nun will jede freie und höhere
Mitigating Cotton Revenue Risk Through Irrigation, Insurance, and Hedging

This study focuses on managing cotton production and marketing risks using combinations of irrigation levels, put options (as price insurance), and crop insurance. Stochastic cotton yields and prices are used to simulate a whole-farm financial statement for a 1,000 acre furrow-irrigated cotton farm in the Texas Lower Rio Grande Valley under 16 combinations of risk management strategies. Analyses for risk-averse decision makers indicate that multiple irrigations are preferred. The benefits to purchasing put options increase with yields, as they are more beneficial when higher yields are expected from applying more irrigation applications. Crop insurance is strongly preferred at lower irrigation levels.
Guest Editorial: Wavelets in Medical Imaging - Medical Imaging, IEEE Transactions on

WAVELETS are the result of collective efforts that recognized common threads between ideas and concepts that had been independently developed and investigated by distinct research communities. They provide a unifying framework for decomposing images, volumes, and time-series data into their elementary constituents across scale. Although a relatively recent construct, wavelets have become a tool of choice for engineers, physicists, and mathematicians, leading to efficient solutions in time and space frequency analysis problems, as well as a multitude of other applications. One of the consequences is that wavelet methods of analysis and representation are presently having a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Because of a powerful underlying mathematical theory, they offer exciting opportunities for the design of new multiresolution image processing algorithms, and novel acquisition methods such as wavelet-encoded magnetic resonance imaging (MRI). This special issue of the IEEE TRANSACTIONS ON MEDICAL IMAGING focuses on these recent developments and highlights progress that has been accomplished in the areas related to medical imaging.
A REVIEW OF INFORMATION SYSTEM SUCCESS MODELS

Measuring Information systems success has been the most arguable and important issue. Evaluation of success is not an easy task. Many models have been given by researchers in the past for the same purpose. The main objective of this paper is to study and review four main models of IS success –TAM, DeLone and McLean model, Updated DeLone and McLean model and Gable et. al model. Here we have compared these four models and discussed their relevance to the IS field.
Estimation of the Hurst Exponent for the Burdekin River using the Hurst-Mandelbrot Rescaled Range Statistic

The issue of the impact of agricultural run-off in north Queensland on nutrient accumulation in the Great Barrier Reef lagoon has recently been the subject of increased scientific, media and policy debate. Models of river flow and of nutrient plumes at the mouth of Queensland rivers are an essential prerequisite for studying the impact of agriculture on the Great Barrier Reef ecosystem. Hurst found long-term dependency in fluctuations at the mouth of the Nile River the theoretical basis of which was later found by Mandelbrot to involve fractional Brownian motion. Approximately one quarter of the inflow into the Barrier Reef lagoon comes from the Burdekin and Fitzroy region. Using a data set collected by Isdale et al. that covers the period 1644-1980, that is based on reconstructing river flow data for the Burdekin river by analysing luminescence lines in coral reefs at the river mouth, we have estimated the Hurst exponent of the Burdekin river for the purpose of developing a river flow simulation model based on fractional Brownian motion.
Neural Networks and Support Vector Machine based Approach for Classifying Tweets by Information Types at TREC 2018 Incident Streams Task

: Microblog, especially twitter, is treated as an important source to serve the situational information needs during a disaster period. Monitoring and producing the curated tweets based on di ﬀ erent information types from massive twitter posts provide enormous opportunities to di ﬀ erent public safety personnel or used for post-incident analysis. In this paper, we present our approach to addressing the problem deﬁned in the TREC 2018 incident streams (TREC-IS) task. The task is to classify the tweets in each event / incident’s stream into di ﬀ erent high-level information types within the incident ontology. In our approach, we employ di ﬀ erent deep neural network (DNN) classiﬁers in combination with a multi-class support vector machine (SVM) classiﬁer and a rule-based classiﬁer. We consider a rich set of hand-crafted features to train our multi-class SVM classiﬁer, whereas a pre-trained word2vec model is used for the DNN based classiﬁers. Moreover, we introduce a set of rules based on the language of tweets, exploiting indicator terms, and WH-orientation of tweets for our rule-based classiﬁer. Experimental results showed that our proposed KDEIS4 DM method obtained the second position among the participants in TREC-IS task and outperforms the participant median by more than 8% and 5% in terms of F1 Score and accuracy, respectively.
Programming Embedded Manycore : Refinement and Optimizing Compilation of a Parallel Action Language for Hierarchical State Machines. (Programmation de systèmes embarqués many-core : Raffinement et compilation optimisante d'un langage d'action parallèle pour machines à états hiérarchiques)

Modeling languages propose convenient abstractions and transformations to handle the complexity of today's embedded systems. Based on the formalism of \acrlong{hsm}, they enable the expression of hierarchical control parallelism. However, they face two importants challenges when it comes to model data-intensive applications: no unified approach that also accounts for data-parallel actions; and no effective code optimization and generation flows. In this thesis, we propose a modeling language extended with parallel action semantics and hierarchical indexed-state machines suitable for computationally intensive applications. Together with its formal semantics, we present an optimizing model compiler aiming for the generation of efficient data-parallel implementations.
A Peroxisomal Lon Protease and Peroxisome Degradation by Autophagy Play Key Roles in Vitality of Hansenula polymorpha Cells

In eukaryote cells various mechanisms exist that are responsible for the removal of non-functional proteins. Here we show that in the yeast Hansenula polymorpha a peroxisomal Lon protease, Pln, plays a role in degradation of unfolded and non-assembled peroxisomal matrix proteins. In addition, we demonstrate that whole peroxisomes are constitutively degraded by autophagy during normal vegetative growth of WT cells. Deletion of both H. polymorpha PLN and ATG1, required for autophagy, resulted in a significant increase in peroxisome numbers, paralleled by a decrease in cell viability relative to WT cells. Also, in these cells and in cells of PLN and ATG1 single deletion strains, the intracellular levels of reactive oxygen species had increased relative to WT controls. The enhanced generation of reactive oxygen species may be related to an uneven distribution of peroxisomal catalase activities in the mutant cells, as demonstrated by cytochemistry. We speculate that in the absence of HpPln or autophagy unfolded and non-assembled peroxisomal matrix proteins accumulate, which can form aggregates and lead to an imbalance in hydrogen peroxide production and degradation in some of the organelles.
Ecosystem Responses to Partial Harvesting in Eastern Boreal Mixedwood Stands

Partial harvesting has been proposed as a key aspect to implementing ecosystem management in the Canadian boreal forest. We report on a replicated experiment located in boreal mixedwoods of Northwestern Quebec. In the winter of 2000-2001, two partial harvesting treatments, one using a dispersed pattern, and a second, which created a (400 m 2 ) gap pattern, were applied to a 90-year-old aspen-dominated mixed stand. The design also included a clear cut and a control. Over the course of the following eight years, live tree, coarse woody debris, regeneration and ground beetles were inventoried at variable intervals. Our results indicate that all harvesting treatments created conditions
Survey and benchmark of lightweight block ciphers for MSP430 16-bit microcontroller

For security applications in wireless sensor networks WSNs, choosing best algorithms in terms of energy-efficiency and of small memory requirements is a real challenge because the sensor networks are composed of low-power entities. In some previous works, 12 block-ciphers have been benchmarked on an ATMEL AVR ATtiny45 8-bit microcontroller and the best candidates to use in the context of small embedded platforms have been deduced. This article proposes to study on the TI 16-bit microcontroller MSP430 most of the recent lightweight block cipher proposals as well as some conventional block ciphers. First, we describe the design of the chosen block ciphers with a security and an implementation summary and we then present some implementation tests performed on our dedicated platform. Copyright © 2015 John Wiley & Sons, Ltd.