Miracle-dz/UniFAR-FTUs huggingface dataset:
Brane inflation and the WMAP data: a Bayesian analysis

The Wilkinson Microwave Anisotropy Probe (WMAP) constraints on string inspired ‘brane inflation’ are investigated. Here, the inflaton field is interpreted as the distance between two branes placed in a flux-enriched background geometry and has a Dirac–Born–Infeld (DBI) kinetic term. Our method relies on an exact numerical integration of the inflationary power spectra coupled to a Markov chain Monte Carlo exploration of the parameter space. This analysis is valid for any perturbative value of the string coupling constant and of the string length, and includes a phenomenological modelling of the reheating era to describe the post-inflationary evolution. It is found that the data favour a scenario where inflation stops by violation of the slow-roll conditions well before brane annihilation, rather than by tachyonic instability. As regards the background geometry, it is established that logv>−10 at 95% confidence level (CL), where v is the dimensionless ratio of the five-dimensional sub-manifold at the base of the six-dimensional warped conifold geometry to the volume of the unit 5-sphere. The reheating energy scale remains poorly constrained, Treh>20 GeV at 95% CL, for an extreme equation of state () only. Assuming that the string length is known, the favoured values of the string coupling and of the Ramond–Ramond total background charge appear to be correlated. Finally, the stochastic regime (without and with volume effects) is studied using a perturbative treatment of the Langevin equation. The validity of such an approximate scheme is discussed and shown to be too limited for a full characterization of the quantum effects.
Distributed wake-up scheduling for data collection in tree-based wireless sensor networks

In a multi-hop wireless network, a conventional way of defining interference neighbors is to prohibit a node from using the same slot/code as those of its 1-hop and 2-hop neighbors. However, for data collection in a wireless sensor network, since the set of communication nodes is limited and the transmission directions are toward the sink, we show that a less strict set of interference neighbors can be defined. Based on this observation, we develop an efficient distributed wake-up scheduling scheme for data collection in a sensor network that achieves both energy conservation and low reporting latency.
Design of Cpw-fed Patch Antenna with Triangular Slots for Wireless Communication Applications

— This paper presents a microstrip antenna using CPW-fed heptagonal shaped antenna embedded with triangular shaped slots for WLAN/WIMAX applications. The proposed antenna provides an impedance bandwidth of 3.08 GHz. The antenna exhibits dual frequency bands 3.4 GHz to 6.48 GHz, covering WLAN and WiMAX bands. The parametric study is performed to understand the characteristics of the proposed antenna, various antenna parameters like S-parameters, current distribution and radiation pattern comes under this section.
GENETIC ANALYSES OF HESSIAN FLY RESISTANCE IN KS 94 U 275

The need for enhanced genetic diversity in wheat (Triticum aestivum L.) for resistance against the Hessian fly (HF) [Mayetiola destructor Say] is a continuous one, as the HF remains a seriously damaging pest throughout the wheat producing regions of the United States and the world over. Breeding for resistance has been the most practical and economical method for effecting HF control as new genes for resistance are needed because of the evolution of virulence in HF populations. Thus far, twenty nine major genes conferring resistance to HF have been identified and described (H1 to H29), and these continue to be used in cultivar improvement programs. KS 94U275 is an experimental line developed by the Wheat Genetics Research Center (WGRC) at Kansas State University, which is suspected to have derived HF resistance from its Aegilops tauschii lineage. The objectives of this study were to (i) determine the number of resistant genes in KS 94U275 to Hessian fly biotype L, and (ii) determine the mode of inheritance of this resistance. On the basis of segregation ratios (1:1 resistant/susceptible in BC1F1 populations; 3:1 resistant/susceptible in F2 populations), it was determined that resistance in KS 94U275 is conditioned by a single dominant gene. This finding holds great promise in the campaign for novel HF resistant genes that can be incorporated into superior cultivars to aid in withstanding assault from the HF.
Determining noise temperatures in beam waveguide systems

A new 34-m research and development antenna was fabricated and tested as a precursor to introducing beam waveguide (BWG) antennas and Ka-band (32 GHz) frequencies into the NASA/JPL Deep Space Network. For deep space use, system noise temperature is a critical parameter. There are thought to be two major contributors to noise temperature in a BWG system: the spillover past the mirrors, and the conductivity loss in the walls. However, to date, there are no generally accepted methods for computing noise temperatures in a beam waveguide system. An extensive measurement program was undertaken to determine noise temperatures in such a system along with a correspondent effort in analytic prediction. Utilizing a very sensitive radiometer, noise temperature measurements were made at the Cassegrain focus, an intermediate focal point, and the focal point in the basement pedestal room. Several different horn diameters were used to simulate different amounts of spillover past the mirrors. Two analytic procedures were developed for computing noise temperature, one utilizing circular waveguide modes and the other a semiempirical approach. The results of both prediction methods are compared to the experimental data.
Context-based media adaptation in pervasive computing

In pervasive computing applications, computer embedded devices are used to perform control tasks and access the Internet or other information sources. However, most content of current information sources was designed with desktop computers and high-speed network connections in mind. They contain rich media data, which are not suitable for those pervasive devices with limited capabilities. Moreover, for different user preference and application scenarios, not all of the data are relevant and critical to the application. Context-based media adaptation is mainly concerned with selecting different qualities of single media types or selecting different media types, and then delivering information to different context. Some related issues for building a general context-based media adaptation framework are discussed. These issues include context description and exchange schemes, adaptable model for managing and manipulating multimedia content, adaptation techniques and architectural issues.
Event intensity tracking in weblog collections

Event tracking is the task of discovering temporal patterns of events from text streams. Existing approaches for event tracking have two limitations: scalability and their inability to rule out non-relevant portions within texts in the stream ‘relevant’ to the event of interest. In this study, we propose a novel approach to tackle these limitations. To demonstrate our approach, we track news events across a collection of weblogs spanning a two-month time period. In particular we track variations in the intensity of discussion on a given event over time. We demonstrate that our model is capable of tracking both events and sub-events at a finer granularity. We also present in this paper our analysis of the blog dataset distributed by the conference organizers.
Challenges and Supports for African American STEM Student Persistence: A Case Study at a Racially Diverse Four-Year Institution

Abstract:This qualitative case study examined the experiences of twenty-five African American students in STEM majors, at different junctures in their program of study. The students were interviewed in focus groups guided by a semi-structured interview protocol. Several themes emerged to describe the dynamic factors that both weakened and strengthened student perseverance and on-time degree completion. Themes describing barriers to degree completion include: ambivalence toward the teaching and learning environment; weak, formal, relationships with faculty, inadequate preparation for challenging classes; large classes and infrequent class offerings; and frustration with academic advising. Themes describing the militating factors include: peer support, student organizations, and mentoring. Particularly, the findings illuminate the importance of academically meaningful social activities for African American students enrolled in STEM majors.
A New Class of Balanced Near-Perfect Nonlinear Mappings and Its Application to Sequence Design

A mapping from ZN to ZM can be directly applied for the design of a sequence of period N with alphabet size M, where ZN denotes the ring of integers modulo N. The nonlinearity of such a mapping is closely related to the autocorrelation of the corresponding sequence. When M is a divisor of N, the sequence corresponding to a perfect nonlinear mapping has perfect autocorrelation, but it is not balanced. In this paper, we study balanced near-perfect nonlinear (NPN) mappings applicable for the design of sequence sets with low correlation. We first construct a new class of balanced NPN mappings from Z(p2-p) to Zp for an odd prime p. We then present a general method to construct a frequency-hopping sequence (FHS) set from a nonlinear mapping. By applying it to the new class, we obtain a new optimal FHS set of period p2-p with respect to the Peng-Fan bound, whose FHSs are balanced and optimal with respect to the Lempel-Greenberger bound. Moreover, we construct a low-correlation sequence set with size p, period p2-p, and maximum correlation magnitude p from the new class of balanced NPN mappings, which is asymptotically optimal with respect to the Welch bound.
Nonlinear predictive control for real time applications

The design of nonlinear predictive controllers based on linear time-varying prediction models is discussed. The linear time-varying models can be obtained by applying a local linearization along the nominal input and state trajectory or by describing the nonlinear state equations by state dependent state space equations. A graphical predictive control framework that provides practical methods for nonlinear control design is introduced using LabVIEW. The effectiveness of the algorithms and the easy applicability of the developed framework are illustrated in a simulation example
Real-time Automatic Deceit Detection from Involuntary Facial Expressions

Being the most broadly used tool for deceit measurement, the polygraph is a limited method as it suffers from human operator subjectivity and the fact that target subjects are aware of the measurement, which invites the opportunity to alter their behavior or plan counter-measures in advance. The approach presented in this paper attempts to circumvent these problems by unobtrusively and automatically measuring several prior identified deceit indicators (DIs) based upon involuntary, so-called reliable facial expressions through computer vision analysis of image sequences in real time. Reliable expressions are expressions said by the psychology community to be impossible for a significant percentage of the population to convincingly simulate, without feeling a true inner felt emotion. The strategy is to detect the difference between those expressions which arise from internal emotion, implying verity, and those expressions which are simulated, implying deceit. First, a group of facial action units (AUs) related to the reliable expressions are detected based on distance and texture based features. The DIs then can be measured and finally a decision of deceit or verity will be made accordingly. The performance of this proposed approach is evaluated by its real time implementation for deceit detection.
Dealing with Receiver Misbehavior in Multicast Congestion Control

In multicast congestion control, receivers can misbehave by maliciously causing congestion to steal network bandwidth from well behaved flows. In source driven congestion control protocols (SDCC), receivers misbehave by sending a wrong feedback to the source. In receiver-driven congestion control protocols(RDCC), receivers misbehave by inflating their subscriptions. In this report, we present techniques to deal with these misbehaviours. Firstly, we show that when network tomography tools such as MINC are used in conjunction with SDCC protocols, they can aid in misbehavior detection. But in order to use MINC for misbehaviour detection, MINC itself must be made immune to misbehaviour. we analyze the effect of misbehavior within MINC and propose two techniques to detect and prevent misbehavior in MINC. For RDCC protocols, a misbehaviour prevention mechanism based on in-band distribution of keys was recently proposed for FLID-DL protocol. In this report, we show how we can design keys which can prevent misbehaviour in most RDCC protocols.
Research Advances for Fall 2012 Mimetic Methods Toolkit : An object-oriented API implementing Mimetic Discretization Methods

In this work, we introduce the Mimetic Methods Toolkit (MTK), an object-oriented Application Programming Interface for the implementation of Mimetic Discretization Methods in developing computer applications of a scientific nature, where the numerical solution of Partial Differential Equations may be required. The MTK was designed based on the Castillo–Grone Method for the construction of discrete differential operators that mimic important properties of their continuous counterparts. The MTK is built as a collection of abstract and concrete classes, thus allowing for an extensible framework, which fosters code reutilization, while intuitively educating the user about the important theoretical aspects of the Mimetic Discretization Methods. In this work, we present an introduction to Mimetic Discretization Methods, and we discuss the computational modeling of the related concepts; in this way, we explain how does the MTK implement these methods. By means of examples, we illustrate the MTK’s usage philosophy and, finally, by means of comparing the attained result against previously studied reference solutions, we conclude the correctitude of the implementation efforts in the MTK. ∗Computational Science Research Center, 5500 Campanile Dr, San Diego State University, College of Sciences, San Diego, California, USA, 92182-1245. †Computational Science Research Center, 5500 Campanile Dr, San Diego State University, College of Sciences, San Diego, California, USA, 92182-1245. ‡Computational Science Research Center, 5500 Campanile Dr, San Diego State University, College of Sciences, San Diego, California, USA, 92182-1245.
FDU at TREC 2007: Opinion Retrieval of Blog Track

paper describes our participation in the opinion retrieval task at Blog Track 07. The system consisted of the preprocess part, the topic retrieval part and sentiment analysis part. In the topic retrieval part, we adopted pseudo-relevance feedback and a novel approach to form a modified query. In the sentiment analysis part, each blog post was given an opinion score based on the sentences contained in this post. The subjectivity of each sentence was predicted by a CME classifier. Then the blog posts were reranked based on the similarity given by the topic retrieval and the opinion score given by the sentiment analysis.
The evolutionary history of methicillin-resistant Staphylococcus aureus (MRSA)

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of hospital-acquired infections that are becoming increasingly difficult to combat because of emerging resistance to all current antibiotic classes. The evolutionary origins of MRSA are poorly understood, no rational nomenclature exists, and there is no consensus on the number of major MRSA clones or the relatedness of clones described from different countries. We resolve all of these issues and provide a more thorough and precise analysis of the evolution of MRSA clones than has previously been possible. Using multilocus sequence typing and an algorithm, burst, we analyzed an international collection of 912 MRSA and methicillin-susceptible S. aureus (MSSA) isolates. We identified 11 major MRSA clones within five groups of related genotypes. The putative ancestral genotype of each group and the most parsimonious patterns of descent of isolates from each ancestor were inferred by using burst, which, together with analysis of the methicillin resistance genes, established the likely evolutionary origins of each major MRSA clone, the genotype of the original MRSA clone and its MSSA progenitor, and the extent of acquisition and horizontal movement of the methicillin resistance genes. Major MRSA clones have arisen repeatedly from successful epidemic MSSA strains, and isolates with decreased susceptibility to vancomycin, the antibiotic of last resort, are arising from some of these major MRSA clones, highlighting a depressing progression of increasing drug resistance within a small number of ecologically successful S. aureus genotypes.
Sustaining Availability of Web Services under Distributed Denial of Service Attacks

The recent tide of Distributed Denial of Service (DDoS) attacks against high-profile web sites demonstrate how devastating DDoS attacks are and how defenseless the Internet is under such attacks. We design a practical DDoS defense system that can protect the availability of web services during severe DDoS attacks. The basic idea behind our system is to isolate and protect legitimate traffic from a huge volume of DDoS traffic when an attack occurs. Traffic that needs to be protected can be recognized and protected using efficient cryptographic techniques. Therefore, by provisioning adequate resource (e.g., bandwidth) to legitimate traffic separated by this process, we are able to provide adequate service to a large percentage of clients during DDoS attacks. The worst-case performance (effectiveness) of the system is evaluated based on a novel game theoretical framework, which characterizes the natural adversarial relationship between a DDoS adversary and the proposed system. We also conduct a simulation study to verify a key assumption used in the game-theoretical analysis and to demonstrate the system dynamics during an attack.
Characterization of outpatients with systolic dysfunction in a Japanese community by total enumeration.

BACKGROUND The prevalence of congestive heart failure (CHF) is increasing with the aging of the community. Management of patients with systolic dysfunction (SD) is important for prevention of CHF, but there is little information regarding the burden of SD on Japanese communities. METHODS AND RESULTS In order to delineate the epidemiological and clinical characteristics of SD patients, the medical records of patients from Sado Island were collected and summarized in 2003. From the 5 years prior to 2003, data for 497 patients were extracted. The mortality rate was significantly higher compared with the general population; and the total number of survivors had decreased to 410 by 2003. The proportion of SD patients in the general population increased sharply after the age of 65 years in males and 70 years in females, reaching 3.3% and 1.7% for men and women, respectively, in their 80 s. In 49% of the patients, the Charlson comorbidity index was > or = 2, whereas 24% of females led a solitary life. CONCLUSIONS The total count of outpatients with SD is progressively increasing with age. These patients have multiple comorbidities, making the outcome of SD a poor one. The gender difference in disease characteristics and living conditions should be taken into consideration when establishing preventive strategies for CHF in Japanese communities.
Real-Time Volume Shadow Using Stencil Buffer

Two of the best methods to recognize silhouette to create real-time volume shadow in virtual environment are described in this paper. Volume shadow algorithm is implemented for virtual environment with moveable illuminated light source. Triangular method and the Visible-non visible method are introduced. The recent traditional silhouette detection and implementation techniques used in volume shadow algorithm are improved. With introduce flowchart of both algorithms, the last volume shadow algorithm using stencil buffer is rewritten. A very simple pseudo code to create volume shadow is proposed. These techniques are poised to bring realism into commercial games. It may be use in virtual reality applications.
Multiple Alignment of RNAs by Maximizing the Sum of the Matching Probability of Stem Fragments

1 Department of Computational Biology, Graduate School of Frontier Science, University of Tokyo, CB04 Kiban-tou 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan 2 Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology 3 Graduate School of Information Sciences, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
Knowledge Discovery from Trouble Ticketing Reports in a Large Telecommunication Company

This paper describes the work developed by Telefonica I+D about an application of advanced data mining, text mining and machine learning techniques for the study of the network elements failures managed by the trouble ticketing system of a large telecommunication company, in order to be able to analyze, prioritize and, in some cases, solve without human intervention the huge amount of trouble reports to be managed. Furthermore, this paper will present the techniques used for its achievement, as well as the results obtained so far, showing how these techniques may help important companies to save plenty of time and resources in fault management, improving the service quality.
Modeling the Connectome of a Simple Spinal Cord

In this paper we develop a computational model of the anatomy of a spinal cord. We address a long-standing ambition of neuroscience to understand the structure–function problem by modeling the complete spinal cord connectome map in the 2-day old hatchling Xenopus tadpole. Our approach to modeling neuronal connectivity is based on developmental processes of axon growth. A simple mathematical model of axon growth allows us to reconstruct a biologically realistic connectome of the tadpole spinal cord based on neurobiological data. In our model we distribute neuron cell bodies and dendrites on both sides of the body based on experimental measurements. If growing axons cross the dendrite of another neuron, they make a synaptic contact with a defined probability. The total neuronal network contains ∼1,500 neurons of six cell-types with a total of ∼120,000 connections. The anatomical model contains random components so each repetition of the connectome reconstruction procedure generates a different neuronal network, though all share consistent features such as distributions of cell bodies, dendrites, and axon lengths. Our study reveals a complex structure for the connectome with many interesting specific features including contrasting distributions of connection length distributions. The connectome also shows some similarities to connectivity graphs for other animals such as the global neuronal network of C. elegans. In addition to the interesting intrinsic properties of the connectome, we expect the ability to grow and analyze a biologically realistic spinal cord connectome will provide valuable insights into the properties of the real neuronal networks underlying simple behavior.