Miracle-dz/UniFAR-FTUs huggingface dataset:
GriCoL: A Language for Scientific Grids

The development of the Grid has opened new possibilities for scientists and engineers to execute large-scale modeling experiments. This has stimulated the generation and development of tools for the creation and management of complex computing experiments in the Grid. Among these, tools for the automation of the programming of experiments play a significant role. In this paper we present GriCoL, which we propose as a simple and efficient language for the description of complex Grid experiments. We also describe the environment within which GriCoL works, namely the Science Experimental Grid Laboratory (SEGL) system for designing and executing complex experiments. As an illustration, the paper includes the description of a biochemical experiment using Molecular Dynamics simulations.
MIMO Channel Model and Correlation between Channel Matrix Elements in Multipath Channel

To clarify MIMO channel complex correlation for various cell types, we studied the correlation analytically and by computer simulation. We prepared a MIMO channel model consisting of base and mobile antenna configurations and a delay profile with arriving and incident wave angles (ξ<sub>n</sub>, ζ<sub>n</sub>) in line-of-sight (LOS) and non-line-of-sight (NLOS) paths. Then, the general correlation formula ρ<sub>i-j,i'-j'</sub>(bm) was derived for the model. It shows that ρ<sub>i-j,i'-j'</sub>(bm) depends on two factors: antenna configuration at mobile and base sites (z<sub>i-i'</sub>, z<sub>j-j'</sub>, Ψ<sub>i-i'</sub> , Ψ<sub>j-j'</sub>) and angle distribution (ξ<sub>c</sub>, Δξ<sub>n</sub>, ζ<sub>c</sub>, σ). It also shows that ρ<sub>i-j,i'-j'</sub>(bm) is expressed as the addition of a directive wave term kexp(jdθ<sub>0</sub>) to the product of mobile site correlation ρ<sub>i-i'</sub>(m) and base site correlation ρ<sub>j-j'</sub>(b) without LOS, which are calculated independently of each other. So, the formulas for ρ<sub>i-i'</sub>(m) and ρ<sub>j-j'</sub>(b) were derived for uniform and Gaussian angular distributions. Furthermore, a computer simulation was performed and the simulated and theoretical values agreed well. Therefore, we can apply the ρ<sub>i-j,i'-j'</sub>(bm) to various cell types indoors and outdoors by combining them, so it is possible to calculate the correlation between MIMO channel matrix elements for a given cell and environment.
Robust 3D scan segmentation for teleoperation tasks in areas contaminated by radiation

3D data collected by a laser scanner has great potential for robotic applications. Exact geometrical models of the environment surrounding the robot can be created from these point clouds. But, before creating any model, the 3D point cloud has to be segmented and depending on the size and quality of the point cloud, this can be a very challenging task. This article describes a robust 3D scan segmentation technique, which is capable of segmenting a 3D point cloud in a short amount of time. The results of the segmentation are used to assist a teleoperator to manoeuvre a robot through an unknown environment. Our segmentation approach copes with indoor and outdoor environments, using only a minimum of assumptions, which makes it very robust. A 3D visualisation illustrates the segmentation results in a clear and user-friendly way.
Self‐assembly of amphiphilic β‐sheet peptide tapes based on aliphatic side chains

Amphiphilic β‐sheet nanotapes based on the self‐assembly of 9mer and 7mer de novo designed β‐strand peptides were studied in the dilute regime. The hydrophobic face of the tapes consisted predominantly of aliphatic (leucine) side chains, while the hydrophilic tape face contained polar side chains (glutamine, arginine and glutamic acid). Both peptides underwent a transition from a monomeric random coil to a self‐assembled β‐sheet tape upon increase of peptide concentration in aqueous solutions. P9‐6 exhibited lower critical concentration (c*) for self‐assembly and thus higher propensity for self‐assembly in water, compared to the shorter P7‐6. At neutral pH where there was little net charge per peptide, self‐assembly was favoured compared to low pH in which there was a net + 1 charge per peptide; the net charge decreased overall intermolecular attraction, manifested as an increase in c* for self‐assembly in low compared to neutral pH aqueous solutions. Propensity for self‐assembly and β‐sheet formation was found to be greatly enhanced in a polar organic solvent (methanol) compared to water. These studies combined with future more extensive comparative studies between amphiphilic tapes based on aliphatic amino acid residues and amphiphilic tapes based on aromatic residues will throw more light on the relative importance of hydrophobic versus aromatic interactions for the stabilisation of peptide assemblies. Systematic studies of this kind may also allow us to throw light on the fundamental principles that drive peptide self‐assembly and β‐sheet formation; they may also lead to a set of refined criteria for the effective design of peptides with prescribed combination of properties appropriate for specific applications. Copyright © 2010 European Peptide Society and John Wiley & Sons, Ltd.
Marine Biodiversity in Juan Fernández and Desventuradas Islands, Chile: Global Endemism Hotspots

The Juan Fernández and Desventuradas islands are among the few oceanic islands belonging to Chile. They possess a unique mix of tropical, subtropical, and temperate marine species, and although close to continental South America, elements of the biota have greater affinities with the central and south Pacific owing to the Humboldt Current, which creates a strong biogeographic barrier between these islands and the continent. The Juan Fernández Archipelago has ~700 people, with the major industry being the fishery for the endemic lobster, Jasus frontalis. The Desventuradas Islands are uninhabited except for a small Chilean military garrison on San Félix Island. We compared the marine biodiversity of these islands across multiple taxonomic groups. At San Ambrosio Island (SA), in Desventuradas, the laminarian kelp (Eisenia cokeri), which is limited to Desventuradas in Chile, accounted for >50% of the benthic cover at wave exposed areas, while more sheltered sites were dominated by sea urchin barrens. The benthos at Robinson Crusoe Island (RC), in the Juan Fernández Archipelago, comprised a diverse mix of macroalgae and invertebrates, a number of which are endemic to the region. The biomass of commercially targeted fishes was >2 times higher in remote sites around RC compared to sheltered locations closest to port, and overall biomass was 35% higher around SA compared to RC, likely reflecting fishing effects around RC. The number of endemic fish species was extremely high at both islands, with 87.5% of the species surveyed at RC and 72% at SA consisting of regional endemics. Remarkably, endemics accounted for 99% of the numerical abundance of fishes surveyed at RC and 96% at SA, which is the highest assemblage-level endemism known for any individual marine ecosystem on earth. Our results highlight the uniqueness and global significance of these biodiversity hotspots exposed to very different fishing pressures.
Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.
Hereditary cancer syndromes with high risk of endometrial and ovarian cancer: Surgical options for personalized care

Cancer genomics has increased our recognition of specific hereditary cancer mutations. Hereditary breast and ovarian cancer (HBOC) syndrome and Lynch syndrome are two such entities in which women carrying specific mutations may be at high risk for developing breast, ovarian, and/or endometrial cancers. Risk reducing surgery such as prophylactic mastectomy, oophorectomy, and/or hysterectomy may allow women to decrease these risks after completing childbearing. Background, indications, and consequences of these procedures are reviewed. J. Surg. Oncol. 2015 111:118–124. © 2014 Wiley Periodicals, Inc.
Please Scroll down for Article International Journal of General Systems Fuzzy Sets and Systems* Fuzzy Sets and Systems*

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the "class of bald men," or the "class of numbers which are much greater than 10," or the "class of adaptive systems," etc. A basic concept which makes it possible to treat fuzziness in a quantitative manner is that of a fuzzy set, that is, a class in which there may be grades of membership intermediate between full membership and non-membership. Thus, a fuzzy set is characterized by a membership function which assigns to each object its grade of membership (a number lying between °and 1) in the fuzzy set. After a review of some of the relevant properties of fuzzy sets, the notions of a fuzzy system and a fuzzy class of systems are introduced and briefly analyzed. The paper closes with a section dealing with optimization under fuzzy constraints in which an approach to problems of this type is briefly sketched.
SimGate : Full-System , Cycle-Accurate Simulation of the Stargate Intermediate Node for Sensor Networks ∗

We present an accuracy and performance analysis of SimGate – a full-system simulation of the Stargate intermediate-level, resource-constrained, sensor network device. We also examine ensemble simulations using SimGate and either one or two simulated Mica2 Motes using the same criteria. We find that accurate functional behavior and cycle counts (at the full device level) are achievable using SimGate alone, and in conjunction with simulated Motes. Also, the slowdown compared to real-time for these simulations is modest with respect to previously published work.
An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.
Secure code distribution in dynamically programmable wireless sensor networks

Remote reprogramming of in situ wireless sensor networks (WSNs) via the wireless link is an important capability. Securing the process of reprogramming allows each sensor node to authenticate each received code image. Due to the resource constraints of WSNs, public key schemes must be used sparingly. This paper introduces a mechanism for secure and efficient code distribution that employs public key cryptography only to sign the root of a combined structure consisting of both hash chains and hash trees. The chain based scheme works best when packets are received in the order they are sent with very few losses. Our hash tree based scheme allows nodes to authenticate packets and verify their integrity quickly, even when the packets may arrive out of order, but can result in too many public key operations. Integrating hash chains and hash trees produces a mechanism that is both resilient to losses and lightweight in terms of reducing memory consumption and the number of public key operations that a node has to perform. Simulation shows that the proposed secure reprogramming schemes add only a modest amount of overhead to a conventional non-secure reprogramming scheme, namely Deluge, and are therefore feasible and practical in a wireless sensor network
Spatio-temporal models for estimating click-through rate

We propose novel spatio-temporal models to estimate click-through rates in the context of content recommendation. We track article CTR at a fixed location over time through a dynamic Gamma-Poisson model and combine information from correlated locations through dynamic linear regressions, significantly improving on per-location model. Our models adjust for user fatigue through an exponential tilt to the first-view CTR (probability of click on first article exposure) that is based only on user-specific repeat-exposure features. We illustrate our approach on data obtained from a module (Today Module) published regularly on Yahoo! Front Page and demonstrate significant improvement over commonly used baseline methods. Large scale simulation experiments to study the performance of our models under different scenarios provide encouraging results. Throughout, all modeling assumptions are validated via rigorous exploratory data analysis.
Functional Specialization and Flexibility in Human Association Cortex.

B. T. Thomas Yeo1,4,2,3,5, Fenna M. Krienen5,7, Simon B. Eickhoff8,9, Siti N. Yaakub4, Peter T. Fox10,11,12, Randy L. Buckner5,7,6, Christopher L. Asplund4,2,13 and Michael W.L. Chee4 Department of Electrical and Computer Engineering, Singapore Institute of Neurotechnology and Clinical Imaging Research Centre, National University of Singapore, Singapore, Center for Cognitive Neuroscience, Duke-NUS Graduate Medical School, Singapore, Athinoula A. Martinos Center for Biomedical Imaging and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA, Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany, Institute for Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany, Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA, South Texas Veterans Health Care System, San Antonio, TX, USA, State Key Laboratory for Brain and Cognitive Sciences, University of Hong Kong, Pokfulam, Hong Kong and Division of Social Sciences, Yale-NUS College, Singapore
Antenna design for UHF RFID tags: a review and a practical application

In this paper, an overview of antenna design for passive radio frequency identification (RFID) tags is presented. We discuss various requirements of such designs, outline a generic design process including range measurement techniques and concentrate on one practical application: RFID tag for box tracking in warehouses. A loaded meander antenna design for this application is described and its various practical aspects such as sensitivity to fabrication process and box content are analyzed. Modeling and simulation results are also presented which are in good agreement with measurement data.
Hyperanalytic Denoising

A new threshold rule for the estimation of a deterministic image immersed in noise is proposed. The full estimation procedure is based on a separable wavelet decomposition of the observed image, and the estimation is improved by introducing the new threshold to estimate the decomposition coefficients. The observed wavelet coefficients are thresholded, using the magnitudes of wavelet transforms of a small number of "replicates" of the image. The "replicates" are calculated by extending the image into a vector-valued hyperanalytic signal. More than one hyperanalytic signal may be chosen, and either the hypercomplex or Riesz transforms are used, to calculate this object. The deterministic and stochastic properties of the observed wavelet coefficients of the hyperanalytic signal, at a fixed scale and position index, are determined. A "universal" threshold is calculated for the proposed procedure. An expression for the risk of an individual coefficient is derived. The risk is calculated explicitly when the "universal" threshold is used and is shown to be less than the risk of "universal" hard thresholding, under certain conditions. The proposed method is implemented and the derived theoretical risk reductions substantiated
Recent Results in Computational Origami

Computational origami is a recent branch of computer science studying e–cient algorithms for solving paper-folding problems. This ﬂeld essentially began with Robert Lang’s work on algorithmic origami design [25], starting around 1993. Since then, the ﬂeld of computational origami has grown signiﬂcantly. The purpose of this paper is to survey the work in the ﬂeld, with a focus on recent results, and to present several open problems that remain. The survey cannot hope to be complete, but we attempt to cover most areas of interest.
Exploring Tradable and NonTradable Inflation in Consumer Prices

Statistics New Zealand (Statistics NZ) will shortly introduce tradable and nontradable inflation component series of the Consumer Price Index. These series are indicative of goods and services whose prices are primarily determined on world markets, and those whose prices are primarily determined on the domestic market. This paper will outline the intended approach by Statistics NZ. The practical aspects, methodology, and problems of categorising items as tradable and non-tradable are also addressed. JEL Classification: C43 & E31 (Index Numbers and Aggregation, and Price Level; Inflation and Deflation)
Analysis of Map Reduce Performance using Prefetching Mechanism

In this massive technological atmosphere the number of information generated is increasing at an awfully high rate. Distributed storage system will be used for storing this immense quantity of information. Massive information will be handled by victimization hadoop and map reduces. The multiple node clusters will discover victimization the hadoop framework. Hadoop comes with default distributed file system that is hadoop distributed file system. The mapped is enforced by map technique and that we can see the performance of map reduce task on the bases of bytes written. The amount of bytes written by map task doesn't increase with the amount of files increasing. The explanation is that once the reduce function perform reduces the map output it simply combines the output of the map function. Thus so as to enhance the performance of map reduce task we are going to setup the cluster of nodes in heterogeneous atmosphere and analyze the behavior of map reduce task victimization the perfecting mechanism.
A Notification Management Architecture for Service Co-evolution in the Internet of Things

IoT applications are essentially characterized by their highly dynamic nature, in which the configurations of both network and software systems may change. In the context of IoT software services, modifications can occur during application lifespan due to updates and amendments. Hence, third-party applications and services depending on the changed services need to take appropriate coordination and adaptation actions. Existing solutions do not focus on coordinated coevolution within resource constrained environments. Addressing this issue in a resource-efficient manner is the objective of our proposed notification management mechanism. It detects and informs dependent third-party applications automatically about service changes and categorizes them into crucial and minor changes. Furthermore, it maintains a list of possibly affected clients without consuming further resources on the IoT device the service is running on. Special attention is also paid to the usability and integrability of our mechanism for clients as well as for providers.
Surface structure of the COPII-coated vesicle

The spatial arrangement of COPII coat protein subunits was analyzed by crosslinking to an artificial membrane surface and by electron microscopy of coat proteins and coated vesicle surfaces. The efficiency of COPII subunit crosslinking to phospholipids declined in order of protein recruitment to the coat: Sar1p > Sec23/24p ≫ Sec13/31p. Deep-etch rotary shadowing and electron microscopy were used to explore the COPII subunit structure with isolated proteins and coated vesicles. Sec23/24 resembles a bow tie, and Sec13/31p contains terminal bilobed globular structures bordering a central rod. The surface structure of COPII vesicles revealed a coat built with polygonal units. The length of the side of the hexagonal/pentagonal units is close to the dimension of the central rod-like segment of Sec13/31. Partially uncoated profiles revealed strands of Sec13/31p stripped from the vesicle surface. We conclude that the coat subunits form layers displaced from the membrane surface in reverse order of addition to the coat.
ESync: an energy synchronized charging protocol for rechargeable wireless sensor networks

Different from energy harvesting which generates dynamic energy supplies, the mobile charger is able to provide stable and reliable energy supply for sensor nodes, and thus enables sustainable system operations. While previous mobile charging protocols either focus on the charger travel distance or the charging delay of sensor nodes, in this work we propose a novel Energy Synchronized Charging (ESync) protocol, which simultaneously reduces both of them. Observing the limitation of the Traveling Salesman Problem (TSP)-based solutions when nodes energy consumptions are diverse, we construct a set of nested TSP tours based on their energy consumptions, and only nodes with low remaining energy are involved in each charging round. Furthermore, we propose the concept of energy synchronization to synchronize the charging re- quests sequence of nodes with their sequence on the TSP tours. Experiment and simulation demonstrate ESync can reduce charger travel distance and nodes charging delay by about 30% and 40% respectively.