Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time PCR Data Processing Shown by the Analysis of Colorectal Specific Candidate Genes , ERCC 1 , RRM 1 and TS in Relation to β 2 M as Endogenous Control

Currently, quantitative real-time PCR (Q-PCR) of archival formalin-fixed, paraffin embedded (FFPE) tissue is a critical tool for research and is not well established in routine diagnostics. Therefore, continuous improvement in mathematics and statistics associated with interpreting final accurate and reproducible results are fundamental. This project describes and discusses specificity and sensitivity with respect to intraand inter-assay variances by use of a commercial Human Reference RNA and individual RNA derived from colorectal cancer patients (n = 25). All patients were treated with 5-fluoruracil (5-FU) and a concomitant pelvic radiotherapy (50.4 Gy). Quality assessment of target tissue samples was evaluated by clinicopathological findings and optical density (OD) measurements. We analyzed the steady state messenger RNA (mRNA) expression level of a small panel of cancer relevant genes, excision repair cross-complementing group 1 (ERCC1), ribonucleoside-diphosphate reductase subunit M1 (RRM1), thymidylate synthase (TYMS) and ß-2microglobulin (ß-2M) as endogenous control. The mRNA of a Human Reference RNA, tumor and non-neoplastic material was reverse transcribed into its complementary DNA (cDNA). cDNA was amplified based on dual-labeled TaqMan real-time fluorescence measurements. The real-time efficiency and therefore the output OPEN ACCESS Appl. Sci. 2012, 2 140 data can be influenced through the kind of calibrator used, the amount and quality of used RNA and by the degree of individual assay variability. Each sample presents an individual amplification curve. Thus, confirmation of primer specificity, one or more invariant endogenous controls, RNA and cDNA quality, as well as real-time PCR amplification efficiencies and linearity calculations from individual slopes or R-values must be included in each study.
Porting and Adapting Predicate frames from Hindi and Arabic PropBanks

This paper describes our efforts for the development of a Proposition Bank for Urdu, an Indo-Aryan language. Our primary goal is the labeling of syntactic nodes in the existing Urdu dependency Treebank with specific argument labels. In essence, it involves annotation of predicate argument structures of both simple and complex predicates in the Treebank corpus. In this paper, we describe the overall process of building the PropBank of Urdu. We discuss various statistics pertaining to the Urdu PropBank and the issues which the annotators encountered while developing the PropBank. We also discuss how these challenges were addressed to successfully expand the PropBank corpus. While reporting the Inter-annotator agreement between the two annotators, we show that the annotators share similar understanding of the annotation guidelines and of the linguistic phenomena present in the language.
Flow Direction Prediction of Ball Movement for Humanoid Robot Soccer Goalkeeper

In Robocup, The most important sensor on humanoid robot soccer is a camera. The camera serves as the eyes of the robot as well as in humans. This camera is used by the robot to detect the ball. The task of Humanoid Robot Soccer as a Goalkeeper is to keep the goal and must be able to block a ball that came directly to the goal from many directions so the ball is not got into the goal. As already been known, the results of the camera image captured is always later than the pictures that has been taken, moreover if the shooting process is added with image processing such as adjusting contrast, brightness, etc. then the delay in image capture will be even greater. This causes late in reaction to the Humanoid Robot Soccer Goalkeeper when it’s blocking the ball that coming from any direction. Therefore we need a computer vision technique to estimate the direction of movement of the ball so there is no delay in reaction to the robot in blocking the ball. In this paper is discussed the flow direction prediction of the ball movement for Humanoid Robot Soccer Goalkeeper. The processing of ball movement prediction is obtained by comparing the previous ball data detection and the latest data detection to get the direction of the ball movement. This robot is a second generation of humanoid robot called EFuRIO soccer (Fusball EEPIS Robot IO).
Hybrid Primary and Secondary Biometric Fusion

Face and Fingerprint identifications are one of the basic forms of person&apos;s identification and they are well known for universality. They remain efficient and acceptable biometric trait in the society and hybrid fusion of these traits will increase a performance of one&apos;s system and also accuracy therefore ,this paper gives an idea about fusion of primary and secondary biometric information providing two levels of security which can be used in the field of criminal identification and prison security based application the most simple and yet strong fusion rules
On Harnessing the Electroencephalogram for the Musical Braincap

The braincap, as described in 3001: The Final Odyssey, the concluding edition of Arthur C. Clarke’s science fiction classic, is the ultimate humancomputer interface: it connects the brain to a system that is able to read thoughts and upload new information. The wearer can in minutes acquire new skills that would otherwise take years to master. Currently, however, a system that uploads information into the brain cannot exist outside the realm of science fiction, although machines that can read signals from the brain are becoming present-day reality. Furthermore, we should soon be able to control all sorts of devices by our thoughts alone. In 1998, a paper presented at the 9th European Congress of Clinical Neurophysiology already reported impressive advances in research on an electroencephalogram-based system to control a prosthetic hand (Guger and Pfurtscheller 1998). More recently, scientists at Brown University reported the development of a brain-computer interface for a system whereby a monkey controlled a cursor on a computer screen (Turner 2002). At first, the monkey used a joystick to move the cursor. After a while, the joystick was disconnected, and the monkey, who had not realized this, continued moving the cursor by means of tiny electrical signals emanating from an electrode implanted on the monkey’s motor cortex (the main brain area for motor control). We are interested in developing thoughtcontrolled musical devices, and to this end we are currently working on the design of a musical braincap. We are developing technology to interface the brain with music systems and compositional techniques suitable for thought control. This article focuses on extracting and harnessing tiny electrical brain signals from electroencephalograms (EEGs) that can be captured with electrodes on the scalp. We present three experiments whose results provide the basis for building systems to automatically detect information in the electroencephalogram associated with musical mental activities. Then, we describe how these results are currently being embedded in the design of the musical braincap. Before we present the experiments, we briefly introduce the growing field of BrainComputer Interfaces (BCI), followed by an introduction to the EEG and the signal processing techniques we employed to harness it. Before we continue, it is necessary to clarify the meaning of the expression ‘‘thought control. ’’ In Eduardo Reck Miranda,* Ken Sharman,† Kerry Kilborn,‡ and Alexander Duncan§ *Computer Music Research—Neuroscience of Music Group, School of Computing, Communications, and Electronics, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, United Kingdom eduardo.miranda@plymouth.ac.uk † Instituto Tecnologico de Informatica Universidad Politecnica de Valencia, Camino de Vera s/n, 46071 Valencia, Spain ken@iti.upv. es ‡ Department of Psychology University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, United Kingdom k.kilborn@psy.gla. ac.uk § The Sun Centre Prades, 48160 St. Martin de Boubaux, France alex@thesuncentre.net On Harnessing the Electroencephalogram for the Musical Braincap
HaG: Hash graph based key predistribution scheme for multiphase wireless sensor networks

Wireless Sensor Networks (WSN) consist of small sensor nodes which operate until their energy reserve is depleted. These nodes are generally deployed to the environments where network lifespan is much longer than the lifetime of a node. Therefore, WSN are typically operated in a multiphase fashion, as in [1-3, 9-10], which use different key pools for nodes deployed at different generations. In multiphase WSN, new nodes are periodically deployed to the environment to ensure constant local and global network connectivity. Also, key ring of these newly deployed nodes is selected from their deployment generation key pool to improve the resiliency of WSN. In this paper, we propose a key predistribution scheme for multiphase WSN which is resilient against permanent and temporary node capture attacks. In our Hash Graph based (HaG) scheme, every generation has its own key pool which is generated using the key pool of the previous generation. This allows nodes deployed at different generations to have the ability to establish secure channels. Likewise, a captured node can only be used to obtain keys for a limited amount of successive generations. We compare the connectivity and resiliency performance of our scheme with other multiphase key predistribution schemes and show that our scheme performs better when the attack rate is low. When the attack rate is high, our scheme still has better resiliency performance inasmuch as using less key ring size compared to the existing multiphase schemes.
Mobility-Assisted Position Estimation in Wireless Sensor Networks

Wireless sensor networks (WSNs) have been proposed for a multitude of location-dependent applications. To stamp the collected data and facilitate communication protocols, it is necessary to identify the location of each sensor. In this paper, we discuss the performance of a novel received signal strength indicator (RSSI) positioning scheme, which uses a generalized geometrical location algorithm to achieve an accurate estimation based on mean received signal strength measurements. In order to improve the network performance and address limitations of static WSNs position estimation, mobile sensors are utilized effectively and an attractive movement strategy with mobile elements is designed. The effectiveness of our approach is validated and compared with the traditional RSSI method by extensive simulations.
The effect of a holistic self-management plan on asthma control

ABSTRACT The holistic self-management plan includes lifelong actions that enable patients to cope with their disease. The present study was designed to evaluate the effect of a holistic self-management plan on asthma control. A 12-month controlled study was conducted. Adult patients with mild-to-moderate asthma (n = 24) who attended the emergency asthma department were randomized to two groups: One group followed four educational sessions and three personal home sessions (n = 12), while a second group received a short manual with asthma information (n = 12). The main measure was the asthma control test (ACT), while secondary outcomes were self-efficacy (general self-efficacy scale, GSE), end-tidal carbon dioxide (ETCO2), respiratory rate (RR), breathing hold time (BHT), the Nijmegen Questionnaire (NQ), and spirometry (FEV1% predicted (forced expiratory volume in 1 second % predicted)) scores. The 2 × 4 ANOVA showed a significant interaction effect between intervention and time in ACT (p = 0.001), GSE (p < 0.001), ETCO2 (p < 0.001), RR (p < 0.001), BHT (p < 0.001), NQ (p = 0.05), and FEV1% predicted (p < 0.001). Predictors of asthma control were self-efficacy and ETCO2. In conclusion, this exploratory study provided support for the effectiveness of holistic self-management in asthma control. Behavioral changes, as indicated by the development of self-efficacy and the reduction of hyperventilation, contributed to the effectiveness of the intervention.
Reusing Code by Reasoning About its Purpose

When programmers face unfamiliar or challenging tasks, code written by others could give them inspiration or reusable pieces. But how can they find code appropriate for their goals? This thesis describes a programming interface, called Zones, that connects code with descriptions of purpose, encouraging annotation, sharing, and reuse of code. The backend, called ProcedureSpace, reasons jointly over both the words that people used to describe code fragments and syntactic features derived from static analysis of that code to enable searching for code given purpose descriptions or vice versa. It uses a technique called Bridge Blending to do joint inference across data of many types, including using domain-specific and commonsense background knowledge to help understand different ways of describing goals. Since Zones uses the same interface for searching as for annotating, users can leave searches around as annotations, even if the search fails, which helps the system learn from user interaction. This thesis describes the design, implementation, and evaluation of the Zones and ProcedureSpace system, showing that reasoning jointly over natural language and programming language helps programmers reuse code. Thesis Supervisor: Henry Lieberman Title: Research Scientist
Gender and Cultural Patterns of Mothers' and Fathers' Attachment and Links with Children's Self-Competence, Depression and Loneliness in Middle and Late Childhood.

This study examined: (1) the independence of children’s attachments to mother and father; (2) the relationships between father and mother quality of attachment and children’s social and cognitive self‐competence, depression and loneliness; and (3) differences in those relationships by gender. Spanish translations of standardised and self‐report measures of mother and father attachment quality, scholastic and social competence, depression and loneliness were administered to 860 middle‐class children, aged 8–12 in Buenos Aires, Argentina. Children’s attachment security with mothers was only moderately related to their attachment security with fathers, suggesting that these two constructs were somewhat independent. In addition, mother security and father security were uniquely predictive of children’s social–emotional outcomes. Availability of and reliance on father most strongly predicted lowered depression scores for children. There were differences in father and mother attachment dimensions and child outc.
Multi-Criteria Code Refactoring Using Search-Based Software Engineering

One of the most widely used techniques to improve the quality of existing software systems is refactoring—the process of improving the design of existing code by changing its internal structure without altering its external behavior. While it is important to suggest refactorings that improve the quality and structure of the system, many other criteria are also important to consider, such as reducing the number of code changes, preserving the semantics of the software design and not only its behavior, and maintaining consistency with the previously applied refactorings. In this article, we propose a multi-objective search-based approach for automating the recommendation of refactorings. The process aims at finding the optimal sequence of refactorings that (i) improves the quality by minimizing the number of design defects, (ii) minimizes code changes required to fix those defects, (iii) preserves design semantics, and (iv) maximizes the consistency with the previously code changes. We evaluated the efficiency of our approach using a benchmark of six open-source systems, 11 different types of refactorings (move method, move field, pull up method, pull up field, push down method, push down field, inline class, move class, extract class, extract method, and extract interface) and six commonly occurring design defect types (blob, spaghetti code, functional decomposition, data class, shotgun surgery, and feature envy) through an empirical study conducted with experts. In addition, we performed an industrial validation of our technique, with 10 software engineers, on a large project provided by our industrial partner. We found that the proposed refactorings succeed in preserving the design coherence of the code, with an acceptable level of code change score while reusing knowledge from recorded refactorings applied in the past to similar contexts.
KINETIC AND THERMODYNAMIC PARAMETERS OF THE THERMOSTABLE XYLANASE PRODUCTION Rhizomucor pusillus

A thermostable extracellular xylanase from Rhizomucor pusillus was produced using a 120 h solid-state culture and exhibited maximal enzyme activity at pH 6.0 and 70 °C. Thermal inactivation of the pure enzyme followed first-order kinetics. The activation and inactivation energies were 14.73 and 356.95 kJ/mol, respectively. Thermodynamic parameters (entropy and enthalpy) suggested that the xylanase was highly thermostable. This is the first report on the thermodynamic parameters of xylanase produced by Rh. pusillus.
A QoS Supported Multi-Channel MAC for Vehicular Ad Hoc Networks

The emerging wireless vehicular communication technology is intended to improve safety and comfort of transportation systems. Different types of traffic information could be delivered through vehicle-to-vehicle and vehicle-to- infrastructure communications. This paper proposes a Quality-of-Service (QoS) supported multi-channel MAC scheme for Vehicular Ad Hoc Networks (VANETs), which can adaptively tune the contention window for different services at each node, and dynamically adjust the intervals of the Control Channel (CCH) and the Service Channels (SCHs) working in multi-rate. Theoretical model is proposed to obtain the contention window and optimize the intervals based on traffic conditions. Analysis and simulation results show that the proposed MAC is able to help IEEE 1690.4 MAC support QoS services, while ensuring the high saturation throughput and the prioritized transmission of critical safety information.
Chapter 19 Entanglement and Differentiable Information Gain Maximization

Decision forests can be thought of as a flexible optimization toolbox with many avenues to alter or recombine the underlying architectural components and improve recognition accuracy and efficiency. In this chapter, we present two fundamental approaches for re-architecting decision forests that yield higher prediction accuracy and shortened decision time. The first is entanglement, i.e. using the learned tree structure and intermediate probabilities computed in nodes closer to the root to affect the training of other nodes deeper in the trees. Unlike more conventional classifiers which assume that all data points (even those neighboring in space or time) are IID, the entanglement approach learns semantic correlation in non IID data. To demonstrate, we build an entangled decision forest (EDF) that exploits spatial correlation in human anatomy by simultaneously labeling voxels in computed tomography (CT) scans into 12 anatomical structures. The second contribution is the formulation of information gain as a function that is differentiable with respect to the parameters of the split node weak learner. This provides increased confidence and accuracy of maximum margin boundary localization and reduces classification time by using a few, shallow trees. We further extend the method to incorporate training label confidence, when available, into the information gain maximization. Due to bagging and random feature subset selection, we can retain decision forest virtues such as resiliency to overfitting. To demon-
Toll-Like Receptor-4 Inhibitor TAK-242 Attenuates Motor Dysfunction and Spinal Cord Pathology in an Amyotrophic Lateral Sclerosis Mouse Model

Neuroinflammation contributes to amyotrophic lateral sclerosis (ALS) progression. TLR4, a transmembrane protein that plays a central role in activation of the innate immune system, has been shown to induce microglial activation in ALS models. TLR4 is up-regulated in the spinal cords of hSOD1G93A mice. We aimed to examine the effects of specific TLR4 inhibition on disease progression and survival in the hSOD1G93A mouse model of ALS. Immunologic effect of TLR4 inhibition in vitro was measured by the effect of TAK-242 treatment on LPS-induced splenocytes proliferation. hSOD1G93A transgenic mice were treated with TAK-242, a selective TLR4 inhibitor, or vehicle. Survival, body weight, and motor behavior were monitored. To evaluate in vivo immunologic modifications associated with TAK-242 treatment, we measured serum IL-1β in the plasma, as well as IL-1β and TNF-α mRNAs in the spinal cord in wild-type mice and in TAK-242-treated and vehicle-treated early symptomatic hSOD1G93A mice. Immunohistochemical analysis of motor neurons, astrocytes, and microglial reactivity in the spinal cords were performed on symptomatic (100 days old) TAK-242-treated and vehicle-treated hSOD1G93A mice. In vitro, splenocytes taken from 100 days old hSOD1G93A mice showed significantly increased proliferation when exposed to LPS (p = 0.0002), a phenomenon that was reduced by TAK-242 (p = 0.0179). TAK-242 treatment did not attenuate body weight loss or significantly affect survival. However, TAK-242-treated hSOD1G93A mice showed temporary clinical delay in disease progression evident in the ladder test and hindlimb reflex measurements. Plasma IL-1β levels were significantly reduced in TAK-242-treated compared to vehicle-treated hSOD1G93A mice (p = 0.0023). TAK-242 treatment reduced spinal cord astrogliosis and microglial activation and significantly attenuated spinal cord motor neuron loss at early disease stage (p = 0.0259). Compared to wild-type animals, both IL-1β and TNF-α mRNAs were significantly upregulated in the spinal cords of hSOD1G93A mice. Spinal cord analysis in TAK-242-treated hSOD1G93A mice revealed significant attenuation of TNF-α mRNA (p = 0.0431), but no change in IL-1β mRNA. TLR4 inhibition delayed disease progression, attenuated spinal cord astroglial and microglial reaction, and reduced spinal motor neuron loss in the ALS hSOD1G93A mouse model. However, this effect did not result in increased survival. To our knowledge, this is the first report on TAK-242 treatment in a neurodegenerative disease model. Further studies are warranted to assess TLR4 as a therapeutic target in ALS.
Transient striatal &ggr; local field potentials signal movement initiation in rats

Transient coherent neural oscillations, as indicated by local field potentials, are thought to underlie key perceptual and cognitive events. We report a transient, state-dependent 50 Hz oscillation recorded from electrodes placed in the striatum of awake, behaving rats. These coherent oscillations, which we term &ggr;50, occurred in brief (150 ms) events co-incident with the initiation of movement. On navigation tasks, the animal's speed increased dramatically at the precise moment of the &ggr;50 event. This synchronous oscillation may provide a key to understanding striatal function, as well as basal ganglia pathology, which often impairs the control of voluntary movements.