Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association between RAD23B Ala249Val Polymorphism and Cancer Susceptibility: Evidence from a Meta-Analysis

Background A number of studies have investigated associations of genetic variation in RAD23B Ala249Val (rs1805329 C>T) with cancer susceptibility; however, the findings are inconsistent. We performed a meta-analysis to acquire a more precise estimation of the relationship. Method We searched literatures from PubMed, Embase and Web of Science. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the association between Ala249Val polymorphism and cancer risk. Results A total of 23 studies consisting of 10837 cases and 13971 controls were included in this meta-analysis. Overall, no significant associations were found between RAD23B Ala249Val polymorphism and cancer risk (Val/Val vs. Ala/Ala: OR = 0.97, 95% CI = 0.75–1.25; Ala/Val vs. Ala/Ala: OR = 1.08, 95% CI = 0.96–1.22; recessive model: OR = 0.93, 95% CI = 0.76–1.14 and dominant model: OR = 1.07, 95% CI = 0.94–1.20). We did not find any significant associations in the further stratification analyses by cancer type, ethnicity and source of control. Conclusions Despite some limitations, this meta-analysis indicates that it is unlikely that the RAD23B 249Val/Val polymorphism may contribute to the individual susceptibility to cancer risk. However, further advanced designed studies with larger sample size and different ethnicities should be conducted to confirm our results.
A comparison of algorithms for a complete backtranslation of oligopeptides

In the context of new metabolic pathways discovery, a full backtranslation of oligopeptides can be a promising approach. When studying complex environments where the composing microorganisms are unknown it is also preferable to have all the complete nucleic sequences corresponding to an enzyme of interest. In this paper, we revisit the existing bioinformatics applications, which bring partial reverse translation solutions, and we compare two algorithms based on oligopeptide degeneracy able to efficiently compute a complete backtranslation of oligopeptides. Such algorithms are precious for the discovery of new organisms and we show their performances on simulated and real biological data sets.
Earth Observation Applications Approach to Data and Metadata Deployment on the European DataGrid Testbed

The European DataGrid (EDG) experience represents an important challenge for the current state-of-the-art in developing and deploying extended, large scale, Grid testbeds. The Earth Observation (EO) community has taken the EDG opportunity to examine the correspondence between EO application needs and actual and potential functionalities offered by Grids today. The application chosen for deployment is a typical one in the EO domain. It consists of elaborating low-level (e.g. raw) satellite data into higher-level products and validating them against similar products obtained from instruments using other platforms, such as groundbased instruments, balloon and other airborne observations, observations from ships, etc.
Multi-view image-based rendering and modeling

While both work with images, Computer Graphics and Computer Vision are different fields. Computer graphics starts with the creation of geometric models and produces linage sequences. Computer vision starts with images or image sequences and produces interpretations including geometric models. Lately, there has been a meeting in the middle, the goal being to create photorealistic images with the help of accurate models recovered from projections of real objects. This convergence has produced a new subfield called Image-Based Rendering and Modeling (IBRM). In this research, the geometric aspects of IBRM are studied. The case of two views is studied first. New algorithms are developed that automatically align the input images, match them and reconstruct 3-D surfaces in Euclidean space. The matching algorithm is designed to cope with complex shapes such as human faces. The reconstruction algorithms are then generalized to the multi-view case, based on a stratified framework. At the root of the stratification is a novel projective reconstruction algorithm that produces a non-metric structure of the scene. An image-based rendering system is implemented, that directly uses this non-metric structure to synthesize images from novel viewpoints. On top of that, a novel algorithm is developed to upgrade the non-metric structures into metric ones. Intrinsic and extrinsic camera parameters are obtained at the same time. One potential application, showcased in this thesis, is to blend computer graphics objects into real images with correct perspective and occlusion. The proposed theory and the associated algorithms lay down the groundwork for future development in multi-view image based rendering and modeling.
The International Mobility of Technical Talent: Trends and Development Implications

This paper charts the complex dynamics of the movement of technical talent in the world economy and assesses broadly the impact of such mobility on both sending and receiving countries. Based on secondary data and primary information from the Indian and Japanese IT industry, the study presents a global view of the movement of talent and its development and policy implications. By synthesizing disparate data and the multifaceted processes and outcomes of international mobility, the paper examines some of the distributional issues of gains and losses in both sending and receiving countries.
The blood vessel recognition of ocular fundus

Today, iris recognition, fingerprint recognition, face recognition, voice recognition and other biometric technology are experiencing rapid development. This paper addresses a new biometric technology - skeleton recognition for blood vessel of optic fundus. The green grayscale ocular fundus image is utilized. The skeleton feature of blood vessel of optic fundus is extracted at first. After filtering treatment and extracting feature, vector curve of blood vessels is obtained. Shape curve matching is later carried out by means of reference point matching. The recognition for blood vessel optic fundus has been demonstrated in this paper to possess high recognition rate, low recognition rejection rate as well as good universality, exclusiveness and stability. With more and more progress made in extracting technology, the optic fundus blood vessel recognition is to become an effective biometric technology.
Frequency-specific network topologies in the resting human brain

A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both “communities” and “hubs” exist simultaneously in the brain's functional connectivity network (FCN), as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signal changes (0.01–0.10 Hz). This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01–0.03 Hz (very low frequency [VLF] band) and 0.07–0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations.
Performance of an OLTP application on Symmetry multiprocessor system

Sequent's Symmetry series is a bus-based shared-memory multiprocessor. System performance in an OLTP (online transaction processing) relational database application was investigated using the TP1 benchmark. System performance was tested with fully cached benchmarks and with scaled benchmarks. In fully-cached tests, the entire database fits inside main memory. In scaled tests, the database is larger than available memory. In the fully-cached benchmark, performance was initially limited by bus saturation. The cause was the transfer of process context from processor to processor. This was eliminated by assigning each process to a processor. Processor affinity was combined with reductions in message passing within the database. Throughput was dramatically improved. The scaled tests were I/O bound. This bottleneck can be eliminated by connecting more disk drives or by increasing the main memory size. <<ETX>>
Do Individual Investors Treat Trading as a Fun and Exciting Gambling Activity? Evidence from Repeated Natural Experiments

We hypothesize that individual investors treat trading as a fun and exciting gambling activity, implying substitution between this activity and alternative gambling opportunities. To examine this hypothesis, we study the lottery jackpots and the trading of individual investors in Taiwan. When the jackpots exceed 500 million Taiwan dollars, the trading volume decreases between 5.2% and 9.1% among stocks preferred by individual investors and between 6.8% and 8.6% among lottery-like stocks. The decline in individual buy volume is statistically indistinct from the decline in sell volume. Large jackpots are associated with less trading in options with high sensitivity to volatility.
Physical embodied communication between robots and children: An approach for relationship building by holding hands

The influence of holding hands on the relationship building process between children and robots is investigated in this study. In particular, at the first meeting, it is difficult for a child to be open if he/she starts to rebuff the robot partner. This significantly degrades the possibility of the child forming a friendship relationship with the robot. Thus, the initial approach of the robot to the child in the early stage of the relationship building process should be appropriate. We hypothesize that physical embodied communication, such as walking hand in hand, improves the relationship between children and robots. A holding hands system was implemented in a real robot, and an experiment was conducted at a kindergarten to validate our hypothesis. The results strongly support our hypothesis.
Topology control and routing in ad hoc networks: a survey

An ad hoc wireless network, or simply an ad hoc network, consists of a collection of geographically distributed nodes that communicate with one other over a wireless medium. An ad hoc network differs from cellular networks in that there is no wired infrastructure and the communication capabilities of the network are limited by the battery power of the network nodes. One of the original motivations for ad hoc networks is found in military applications. A classic example of ad hoc networking is network of war fighters and their mobile platforms in battlefields. Indeed, a wealth of early research in the area involved the development of packet-radio networks (PRNs) and survivable radio networks [16]. While military applications still dominate the research needs in ad hoc networking, the recent rapid advent of mobile telephony and plethora of personal digital assistants has brought to the fore a number of potential commercial applications of ad hoc networks. Examples are disaster relief, conferencing, home networking, sensor networks, personal area networks, and embedded computing applications [37]. The lack of a fixed infrastructure in ad hoc networks implies that any computation on the network needs to be carried out in a decentralized manner. Thus, many of the important problems in ad hoc networking can be formulated as problems in distributed computing. However, there are certain characteristics of ad hoc networks that makes this study somewhat different than traditional work in distributed computing. In this article, we review some of the characteristic features of ad hoc networks, formulate problems and survey research work done in the area. We focus on two basic problem domains: topology control, the problem of computing and maintaining a connected topology among the network nodes, and routing. This article is not intended to be a comprehensive survey on ad hoc networking. The choice of the problems discussed in this article are somewhat biased by the research interests of the author.The remainder of this article is organized as follows. In Section 2, we describe various aspects relevant to modeling ad hoc networks. In Section 3, we discuss topology control. Since the nodes of an ad hoc network are often associated with points in 2-dimensional space, topology control is closely tied to computational geometry; we will briefly review this relationship and extant work in the area. In Section 4, we discuss routing protocols for ad hoc networks. After a brief overview of the many protocols that have been proposed, we discuss alternative approaches based on the adversarial network model.
Augmenting Grid-Based Contours to Improve Thin-Plate DEM Generation

We present two new pre-processing techniques that improve thin plate Digital Elevation Model (DEM) approximations from grid-based contour data. One method computes gradients from an initial interpolated or approximated surface. The aspects are used to create gradient paths that are interpolated using Catmull-Rom splines. The computed elevations are added to the initial contour data set. Thin plate methods are applied to all of the data. The splines allow information to flow across contours, improving the final surface. The second method successively computes new, intermediate contours in between existing isolines, which provide additional data for subsequent thin plate processing. Both methods alleviate artifacts visible in previous thin plate methods. The surfaces are tested with published methods to show qualitative and quantitative improvements over previous methods.
A Formal Framework for the Specification, Verification and Synthesis of Diagnosers

In this work we present a formal approach to the design of Fault Detection and Identification (FDI) components. We define a comprehensive language for the specification of FDI, and discuss how to check whether a given FDI component fulfills its specification. Then, we propose an automatic procedure to synthesize an FDI component that satisfies a given specification. The approach has been implemented and tested in realistic case studies from the aerospace domain.
Self-calibration of a biologically-inspired cable-driven robotic arm

Identification of errors in the geometric model parameters of a robotic arm is critical for path planning and motion control. This paper presents the self-calibration of a novel biologically-inspired cable-driven robotic arm. A self-calibration model is formulated based on the differential change in the cable end-point distances. A computationally efficient algorithm using iterative least-squares is employed to identify the errors in the geometric model parameters. It does not require any external measurement devices because it utilizes the cable length data obtained from the redundant actuation scheme of the cable-driven arm. Both computer simulations and experimental studies were carried out to verify the robustness and effectiveness of the proposed self-calibration algorithm. From the experimental studies, errors in the geometric model parameters were precisely identified after a minimum of 35 pose measurements.
Locating Zigbee Devices in a Cluster-Tree Wireless Sensor Network: an ESD-based Integrated Solution

Recent advances in the technology of wireless electronic devices have made possible to build ad-hoc Wireless Sensor Networks (WSNs) using inexpensive nodes consisting of low power processors, a modest amount of memory and simple wireless transceivers. Over the last years, many novel applications have been envisaged for distributed WSNs in the area of monitoring, communication and control. One of the key enabling and indispensable services in WSNs is localization (i.e., positioning), given that the availability of nodes' location may represent the fundamental support for various protocols (e.g., routing) and applications (e.g., habitat monitoring). Furthermore, WSNs are now being increasingly used for real-time applications having stringent Quality-of-Service (QoS) requirements, such as timeliness and reliability. Towards this end, Zigbee/IEEE 802.15. 4 and the Cluster-Tree model are considered among the most promising candidates. Building from (i) our proposed Enhanced Steepest Descent (ESD) algorithm to solve positioning of nodes in a fully distributed fashion, (ii) the mechanism to evaluate at run-time the site-specific parameters for the correct operation of the ESD (i.e., RSSI-based ranging) and (iii) the recent availability of Zigbee/IEEE 802.15. 4 implementations over TinyOS, the main output of this paper is to outline how a positioning service can be fully integrated into a communication protocol stack.
Evolutionary model-based pose estimation for variable configuration objects

The work presented in this paper concerns visual-based relative navigation of autonomous vehicles for satellite service. An evolutionary-based algorithm for the problem of pose estimation of 3D objects using 2D images is presented. The procedure consists on looking for six position parameters, three for rotation and three for translation, such that the projection of a model best fits a set of points (vertices) extracted from a 2D image. Distinguishing feature of the proposed algorithm is that the best matching model is also looked for. This feature is used for visual inspection in order to detect macro defects. A population of candidate solutions is used, whose goodness is measured in terms of distance between model and image points. Key features of the algorithm are also speed and robustness with respect to noise on the input data. Experimental results conducted both on synthetic and real images demonstrate the effectiveness of the proposed approach.
French listeners counting syllables in read French and Russian: implications for the cognitive realty of syllable

This paper examines the question of cognitive status of syllable as a linguistic unit. The experiment was conceived in the objective to test, in a metalinguistic task of counting the syllables, put to French speaking subjects, whether the syllable is a mere methodological concept adopted in linguistic descriptions or whether there is a cognitive reality behind it. Working with filtered stimuli permits to concentrate the attention on the role of the syllable in the prosodic organisation of the utterance.
Software Framework for Agent-Based Games and Simulations

This paper introduces a multi-agent framework for distributed multiplayer game development and simulations. The framework allows the incorporation and experimentation with different strategies of the Players, possibly including intelligent behaviors. The framework consists of a set of generic agent types that must be specialized and configured for a specific game. The framework uses a generic agent that enforces the rules of the game, as well as generic bot-agents that represent the game Players. To support our claims of flexibility and generality we present three simple games implemented on top of our framework: football, battle and labyrinth. Game configuration details are presented as rules imposed on agent actions. We also present simple agents and their strategies to demonstrate how to use the framework in a practical setting.
Remarks on Denominal Verbs Paul Kiparsky 1 Plato ’ s problem in lexical semantics

Word meaning confronts us, as acutely as anything in syntax, with what Chomsky has called Plato’s problem. We know far more about the meaning of almost any word than we could have learned just from our exposure to uses of it. Communication would be unbearably laborious if we did not share with other speakers the ability to generalize the meanings of words in the right ways. As Fodor (1981) notes in arguing for the innateness of lexical semantics, the most we might plausibly have learned about meaning of the verb paint is that it means something like “to cover with paint”. Even if we have only seen this done with a brush, we have no hesitation in applying the verb correctly to novel techniques of painting, such as rolling, spraying, or dipping. But when a vat of paint explodes in a paint factory, covering everyone with paint, or when Velázquez dips his brush in a pot of burnt sienna, we know that the sentences in [1] would not be legitimate reports of what happened.
Queue Length and Mobility aware Routing Protocol for Mobile Ad hoc Network

A mobile ad-hoc network (MANET) is different from other wireless networks in many ways. One of the key differences is that a MANET is a multihop wireless network,i.e., a routing path is composed of intermediate mobile nodes and wireless links connecting them. In this paper, heterogeneous Mobile Ad-hoc Networks (H-MANETs) are considered. H-MANETs are composed of nodes with different transmission range. We propose an improvement of AODV protocol called AMAODV (Adaptative Mobility aware AODV). This protocol is based on new metric combine more routing metrics (distance, relative velocity, queue length and hop count) between each node and one hop neighbor. Which permits to avoid losing route. Through the simulation, it is confirmed that this improvement has higher packet delivery ratio and less average end-to-end delay than basic AODV protocol.
How Could Veins Speed Up The Process Of Discourse Parsing

In this paper we propose a method of reducing the search space of a discourse parsing process, while keeping unaffected its capacity to generate cohesive and coherent tree structures. The parsing method uses Veins Theory (VT), by developing incrementally a forest of parallel discourse trees, evaluating them on cohesion and coherence criteria and keeping only the most promising structures to go on with at each step. The incremental development is constrained by two general principles, well known in discourse parsing: sequentiality of the terminal nodes and attachment restricted to the right frontier. A set of formulas rooted on VT helps to guess the most promising nodes of the right frontier where an attachment can be made, thus avoiding an exhaustive generation of the whole search space and in the same time maximizing the coherence of the discourse structures. We report good results of applying this approach, representing a significant improvement in discourse parsing process.
Using Multi-Stage Features in Fast R-CNN for Pedestrian Detection

Pedestrian detection and tracking remains popular issue in computer vision, with many applications in robotics, surveillance, security and telecare systems, especially when connected with Smart Cities and Smart Destinations. As a particular case of object detection, pedestrian detection in general is a difficult task due to a large variability of features due to different scales, views and occlusion. Typically, smaller and occluded pedestrians are hard to detect due to fewer discriminative features if compared to large-size, visible pedestrians. In order to overcome this, we use convolutional features from different stages in a deep Convolutional Neural Network (CNN), with the idea of combining more global features with finer details. In this paper we present an object detection framework based on multi-stage convolutional features for pedestrian detection. This framework extends the Fast R-CNN framework for the combination of several convolutional features from different stages of the used CNN to improve the network's detection accuracy. The Caltech Pedestrian dataset was used to train and evaluate the proposed method.