Miracle-dz/UniFAR-FTUs huggingface dataset:
Brown Dwarfs as Ejected Stellar Embryos: Observational Perspectives

We discuss a scenario in which brown dwarfs are formed like stars, except that their full collapse phases are interrupted through dynamical interactions in small multiple systems, leading to the ejection of the lightest member. This disintegration is a stochastic process, often resulting in the expulsion of newborn low mass stars, but when it occurs early enough the ejected stellar embryo will be a substellar object. This process may be so common at early ages that a large fraction of the ubiquitous brown dwarfs could have formed in this manner. Detailed gas dynamical simulations are required in order to better understand the details of the decay of small newborn multiple systems. We discuss the observational consequences of the ejection hypothesis, noting especially the importance of binaries with brown dwarf components as an observational test. Finally, we note that brown dwarfs that have recently been ejected may be so disturbed, by infall from the collapsing core and also by heavy accretion from perturbed circumstellar disks, that traditional spectral and luminosity criteria may fail to identify their substellar nature.
Antimutagenic and some other effects of conjugated linoleic acid

Conjugated linoleic acid (CLA) is a collective term for positional and geometric isomers of octadecadienoic acid in which the double bonds are conjugated, i.e. contiguous. CLA was identified as a component of milk and dairy products over 20 years ago. It is formed as an intermediate in the course of the conversion of linoleic acid to oleic acid in the rumen. The predominant naturally occurring isomer is the cis-9, trans-11 modification. Treatment of linoleic acid-rich oils such as safflower oil, soyabean oil, or maize oil with base and heat will result in the formation of CLA. Two isomers predominate in the synthetic preparation, c9,t11 and t10,c12. CLA has been shown to inhibit chemically-induced skin, stomach, mammary or colon tumours in mice and rats. The inhibition of mammary tumours in rats is effective regardless of type of carcinogen or type or amount of dietary fat. CLA has also been shown to inhibit cholesterol-induced atherosclerosis in rabbits. When young animals (mice, pigs) are placed on CLA-containing diets after weaning they accumulate more body protein and less fat. Since CLA is derived from the milk of ruminant animals and is found primarily in their meat and in products derived from their milk there is a concerted world-wide effort to increase CLA content of milk by dietary means. Its effect on growth (less fat, more protein) is also a subject of active research. The mechanisms underlying the effects of CLA are still moot.
Optimal approach to quantum communication using dynamic programming

Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished by noisy channels (such as optical fibers) that generally result in exponential attenuation of quantum signals at large distances. A special class of quantum error correction protocols, quantum repeater protocols, can be used to overcome such losses. In this work, we introduce a method for systematically optimizing existing protocols and developing more efficient protocols. Our approach makes use of a dynamic programming-based searching algorithm, the complexity of which scales only polynomially with the communication distance, letting us efficiently determine near-optimal solutions. We find significant improvements in both the speed and the final-state fidelity for preparing long-distance entangled states.
A developmental model of neural computation using cartesian genetic programming

The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the genetic basis of neural functions. In this paper we describe a radically different approach. We have devised a compartmental model of a neuron as a collection of seven chromosomes encoding distinct computational functions representing aspects of real neurons. This model allows neurons, dendrites, and axon branches to grow, die and change while solving a computational problem. This also causes the synaptic morphology to change and affect the information processing. Since the appropriate computational equivalent functions of neural computation are unknown, we have used a form of genetic programming known as Cartesian Genetic Programming (CGP) to obtain these functions. We have evaluated the learning potential of this system in the context of solving a well known agent based learning scenario, known as wumpus world and obtained promising results.
Parallel AES Encryption Engine for Many Core Processor Arrays Using Masked S-Box

With the ever increasing growth of data communication, hardware encryption technology will become an irreplaceable safety technology. In this paper, I present a method of AES encryption and decryption algorithm with 128 bit key on an FPGA. In order to protect “data-at-rest” in memory from differential power analysis attacks with high-throughput advanced encryption standard (AES) engine with masked S-Box is proposed. By exploring different granularities of data-level and task-level parallelism, we map 2 implementations of an Advanced Encryption Standard (AES) cipher with online key expansion on a fine-grained many-core system.
Discovering the full spectrum of cardiovascular disease: Minority Health Summit 2003: report of the Obesity, Metabolic Syndrome, and Hypertension Writing Group.

This article provides an overview of our current understanding of the epidemiology of obesity, the metabolic syndrome, and hypertension among racial/ethnic groups. Three presentations made at the conference by the present writing group are summarized and updated with other information on ethnic groups, and recommendations developed by the writing group for programs, public policy, and research are put forward.
Educational Activity Finder for Children with Pervasive Developmental Disorder through a Semantic Search System

Children with pervasive developmental disorders have special needs so they should be supported with special education programs. These programs are planned according to the type and degree of the disorder, age, characteristics, and needs of the children. Families prefer Internet to search resources about related educational methods (and associated activity/game) and materials. However, syntactic search in today's Internet is insufficient because of its static base and the search results are not sufficient enough to offer desired relevant results corresponding to a child's needs. With the help of Semantic Web-based agents an intelligent system able to identify the suitable educational methods and material, will contribute to the development of children with disorders, and support education specialists in this process. In addition it will be extremely useful for the families of these children in need of assisting and monitoring their child's development. In this article, an Educational Activity Finder (EAF) is being proposed. The architecture of EAF is structured after semantic Web technology so that it can find and propose semantically relevant suitable educational methods (i.e., activities to carry out) and material for use by children with disorders. The knowledge base of EAF keeps educational methods using the OWL language. All related concepts, attributes, and relations between these concepts and features about pervasive developmental disorders are defined through ontology. EAF is structured to recognize a pervasive developmental disorder, sort out symptoms and anomalies, suggest activities, compile performance scores, and decide on new activity based on user preferences by utilizing the semantic descriptions of available methods and activities. Strength of EAF is demonstrated through sample scenarios. EAF may be used by parents, pre-school educators, primary schools, special educational institutions and experts working for these institutions, university students studying in related fields, and individuals interested in pervasive developmental disorders.
Robust trajectory tracking controller for 5 degree of freedom robotic manipulator

Kinematic and Dynamic models of Robotic manipulators are nonlinear in nature. Hence trajectory planning tracking and control has been a challenging issue in almost all obstacle avoidance problems. In trajectory planning and tracking, the designed trajectory needs to be followed for avoiding obstacles, damage of robots and end-effector tools. This paper proposes a robust controller for designed trajectory tracking of 5 Degree of freedom (DOF) phantom X pincher robotic manipulator with high nonlinearity and coupled dynamics. This paper also presents kinematic and dynamic modeling of robotic manipulator, trajectory planning and tracking using Proportional Integral Derivative (PID) and Sliding Mode Controller (SMC). The performance of the designed controllers are analyzed and compared through MATLAB Simulations.
Searching 4 FUN Workshop of the 34 rd European Conference on Information Retrieval

The mobile search space has witnessed phenomenal growth in recent years. As a result there has been a growing body of research aimed at understanding why and how mobile users search the Web via their handsets and how their mobile search experiences could be improved. However, much of this work has focused on addressing the many challenges of the mobile space. In this short position paper argue the need for more casual, shared, social mobile search experiences. We outline a number of open and challenging research questions related to shared, social mobile search. Finally, we present our ideas through a proof-ofconcept mobile paper prototype designed to support causal mobile search and information sharing with co-located groups of friends.
Grain Retention and Formation of Planetesimals near the Snow Line in MRI-driven Turbulent Protoplanetary Disks

The first challenge in the formation of both terrestrial planets and the cores of gas giants is the retention of grains in protoplanetary disks. In most regions of these disks, gas attains sub-Keplerian speeds as a consequence of a negative pressure gradient. Hydrodynamic drag leads to orbital decay and depletion of the solid material in the disk, with characteristic timescales as short as only a few hundred years for meter-sized objects at 1 AU. In this Letter, we suggest a particle retention mechanism that promotes the accumulation of grains and the formation of planetesimals near the water sublimation front or "snow line. " This model is based on the assumption that, in the regions most interesting for planet formation, the viscous evolution of the disk is due to turbulence driven by the magnetorotational instability (MRI) in the surface layers of the disk. The depth to which MRI effectively generates turbulence is a strong function of grain size and abundance. A sharp increase in the grain-to-gas density ratio across the snow line reduces the column depth of the active layer. As the disk evolves toward a quasi-steady state, this change in the active layer creates a local maximum in radial distribution of the gas surface density and pressure, causing the gas to rotate at super-Keplerian speed and halting the inward migration of grains. This scenario presents a robust process for grain retention that may aid in the formation of proto-gas giant cores preferentially near the snow line.
ect of cue-enhancement on the intelligibility of nonsense word and sentence materials presented in noise 1

Two sets of experiments were performed to test the perceptual bene®ts of enhancing consonantal regions which contain a high density of acoustic cues to phonemic contrasts. In the ®rst set, hand-annotated consonantal regions of natural vowel±consonant±vowel (VCV) stimuli were ampli®ed to increase their salience, and ®ltered to stylise the cues they contained. In the second set, corresponding regions in natural semantically-unpredictable sentence (SUS) material were annotated and enhanced in the same way. Both sets of stimuli were combined with speech-shaped noise and presented to normally-hearing listeners. The VCV experiments showed statistically signi®cant improvements in intelligibility as a result of enhancement; signi®cant improvements were also obtained for sentence material after some adjustments in enhancement strategies and levels. These results demonstrate the bene®ts gained from enhancement techniques which use knowledge of acoustic cues to phonetic contrasts to improve the intelligibility of speech in the presence of background noise. Ó 1998 Elsevier Science B.V. All rights reserved.
Arterial baroreflex function in humans anaesthetized with sevoflurane.

Volatile anaesthetic agents attenuate arterial baroreflex function, while noxious stimuli may modify baroreflex-induced circulatory responses during anaesthesia. We have examined baroreflex control of heart rate during the entire course of sevoflurane anaesthesia in adult patients undergoing surgical procedures. Baroreflex sensitivity was assessed in nine healthy patients undergoing general anaesthesia with sevoflurane. After an 8-10-h fast and no premedication, measurements of R-R intervals were made at conscious baseline (awake), during 2% end-tidal sevoflurane and 67% nitrous oxide before incision (anaesthesia), during surgery at 2% end-tidal sevoflurane and 67% nitrous oxide (surgery) and 20 min after extubation (recovery). Baroreflex responses were triggered by bolus i.v. injections of phenylephrine 50-100 micrograms and nitroprusside 100-200 micrograms to increase and decrease systolic arterial pressure by 20-30 mm Hg, respectively. Baroreflex sensitivities to both pressor and depressor tests were significantly depressed during anaesthesia, surgery and the recovery periods compared with awake values. Pressor test sensitivity during recovery increased significantly from that during surgery (mean 6.16 (SD 2.95) vs 4.42 (3.19) ms mm Hg-1; P < 0.05), but was still significantly less than the awake value (22.50 (17.02) ms mm Hg-1). No improvement in the depressor test sensitivity was seen during the recovery period.
Distributed Wireless Links Repair for Maximizing Reliability and Utilization in Multicast MANET

For achieving multicast routing in self-organizing wireless on demand networks, the multicast ad hoc on-demand distance vector (MAODV) routing protocol is proposed. In MAODV, a multicast tree is created when a sender wants to send packets to several receivers in mobile ad hoc networks (MANETs). In such ad hoc networks, wireless links may be lost occasionally due to mobile nodes on the multicast tree that are unreachable, which causes broken branches, low network reliability, and low packet delivery rate. For overcoming the problem MAODV provides a simple local repair mechanism that tries to find an alternative route to a tree by broadcasting the RREQ message from the downstream nodes of the broken link, but results in extensive control messages and obvious low successful repair rate. Therefore, in this paper we propose a unicast-type multihop local repair protocol in multicasting MANET to recover lost links efficiently while increasing network reliability, minimizing the number of control messages, and reducing repair delay. Meanwhile, the optimal number of hops of neighbor table is also analyzed. Numerical results demonstrate that the proposed multihop local repair approach outperforms other repair approaches in successful repair rate and control message overhead.
CRIB: Cyber crime investigation, data archival and analysis using big data tool

In today's world Cyber Crimes are happening at a very rapid rate, the tools and techniques required to handle bulky and complex cyber crimes and attacks, are making organisations to remain coherent with evolving threats. Big data analytics provides a better and focussed way to overcome these threats and shorten their time to remediate with the help of tools like MongoDB. While the crime complete impairment are still unexplored there is need to control this damage by analysing the fast investigation using Big Data tools. This paper puts forth the ideas and strategies of using the cyber crime investigation tool to analyse the data and generate a report and deploying this data in MongoDB in order to manage large data and extracting structured data sets that it could help us to better understand and analyzed how to ensure threats from recurring.
Cohort profile: LifeLines DEEP, a prospective, general population cohort study in the northern Netherlands: study design and baseline characteristics

Purpose There is a critical need for population-based prospective cohort studies because they follow individuals before the onset of disease, allowing for studies that can identify biomarkers and disease-modifying effects, and thereby contributing to systems epidemiology. Participants This paper describes the design and baseline characteristics of an intensively examined subpopulation of the LifeLines cohort in the Netherlands. In this unique subcohort, LifeLines DEEP, we included 1539 participants aged 18 years and older. Findings to date We collected additional blood (n=1387), exhaled air (n=1425) and faecal samples (n=1248), and elicited responses to gastrointestinal health questionnaires (n=1176) for analysis of the genome, epigenome, transcriptome, microbiome, metabolome and other biological levels. Here, we provide an overview of the different data layers in LifeLines DEEP and present baseline characteristics of the study population including food intake and quality of life. We also describe how the LifeLines DEEP cohort allows for the detailed investigation of genetic, genomic and metabolic variation for a wide range of phenotypic outcomes. Finally, we examine the determinants of gastrointestinal health, an area of particular interest to us that can be addressed by LifeLines DEEP. Future plans We have established a cohort of which multiple data levels allow for the integrative analysis of populations for translation of this information into biomarkers for disease, and which will offer new insights into disease mechanisms and prevention.
Essays in Macroeconomics of Development

This thesis consists of three chapters on macroeconomics of development. The first chapter discusses the impact of educational corruption on economic development. Its main contribution lies in quantifying two channels of educational corruption: a direct channel, whereby incompetent workers affect production due to a misallocation of talent, and a dynamic indirect channel, which can be referred to as a teacher’s effect on the availability of competent agents for production. The results suggest that, for the countries with the highest levels of educational corruption, the losses in output per capita induced by the indirect channel are ten times as large as the ones induced by the direct channel. The removal of educational corruption would increase the output per capita of these countries by more than 20%. The second chapter examines corruption as a social norm and allows civil society to play a role in the fight against it. The theory shows that a more engaged civil society leads to lower levels of corruption but has an ambiguous effect on social capital (captured by the notion of honesty). Wage policies are proven to be ineffective in the proposed economic environment. The analysis of survey data from African countries indicates that the predictions of the model find empirical support and that the causality goes from civic engagement to corruption. The third chapter investigates the factors shaping inter-ethnic relations through the links between one’s trust in one’s own ethnic group (intra-ethnic trust)
Mitochondrial DNA induces inflammation and increases TLR9/NF-κB expression in lung tissue

Mitochondrial DNA (mtDNA) contains unmethylated CpG motifs that exhibit immune stimulatory capacities. The aim of this study was to investigate whether mtDNA activates the Toll-like receptor 9 (TLR9)/nuclear factor-κB (NF-κB) pathway, thereby contributing to post-traumatic systemic inflammatory response syndrome (SIRS) and lung injury in rats. The effects of mtDNA on macrophage culture were examined in order to elucidate the putative cellular mechanisms. Rats and macrophage cultures were treated with phosphate-buffered saline, nuclear DNA, or mtDNA for 2, 4, 8 and 24 h. Histological analysis of lung tissue was undertaken following hematoxylin and eosin staining, and cytokine levels were assessed by ELISA. NF-κB and IκB-α phosphorylation levels, as well as TLR9 protein expression were determined by western blot analysis; NF-κB, IκB-α and TLR9 mRNA levels were analyzed by RT-PCR. A greater degree of inflammation and lung injury was observed in response to mtDNA. In addition, mtDNA increased serum tumor necrosis factor-α, interleukin (IL)-6 and IL-10 levels in vivo and increased their secretion by cultured macrophages (p<0.05). In lung tissue, mtDNA increased NF-κB, IκB-α and TLR9 mRNA levels (p<0.05); it also increased phosphorylated NF-κB p65 and TLR9 protein levels in the macrophage cultures. Thus, mtDNA may be part of the danger-associated molecular patterns, contributing to the initiation of sterile SIRS through the activation of the TLR9/NF-κB pathway and the induction of pro-inflammatory cytokine production.
K Means of Cloud Computing: MapReduce, DVM, and Windows Azure

Cloud-based systems and the datacenter computing environment present a series of challenges to system design ers for supporting massively concurrent computation on clusters with commodity hardware. The platform software should abstractthe unreliable but highly provisioned hardware to provide a highperformance platform for a diversity of concurrent program s processing potentially very large data sets. Toward this goal, a number of solutions are designed or proposed. Among these produ cts and systems, we elect three technologies, MapReduce/Hadoo p, DVM, and Windows Azure, as representatives of three different approaches to constructing the infrastructure and instructing the programming in the cloud. We empirically study these technologies using a well-known and widely used applicatio n, k-means, and analyze their performance data in relation wit h the abstraction layers they establish. The implementation s of kmeans on the three platforms are presented with sufficient de tails to show the design patterns with these technologies. We anal yze the evaluation results in the context of the design goals and constraints of the technologies, and show that the instruct ionlevel abstraction can provide flexible programming capabil ity as well as high performance. Keywords—Cloud computing; k-means; parallel programming; MapReduce; DISA; big data processing
Identity leakage mitigation on asymmetric secure sketch

We consider secure sketch construction in an asymmetric setting, that is, multiple samples are acquired during enrollment, but only a single sample is obtained during verification. Known protection methods apply secure sketch constructions on the average of the samples, while publishing the auxiliary information extracted from the set of samples, such as variances or weights of the features, in clear. Since the auxiliary information is revealed, an adversary can potentially use it to determine the relationship among multiple sketches, and gather information on the identity of the sketches. In this paper, we give a formal formulation of secure sketch under the asymmetric setting, and propose two schemes that mix the identity-dependent auxiliary information within the sketch. Our analysis shows that while our schemes maintain similar bounds of information loss compared to schemes that reveal the auxiliary information, they offer better privacy protection by limiting the linkages among sketches.