Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas

Molecular and clinical heterogeneity critically hinders better treatment outcome for glioblastomas (GBMs); integrative analysis of genomic and epigenomic data may provide useful information for improving personalized medicine. By applying training-validation approach, we identified a novel hypomethylation signature comprising of three CpGs at non-CpG island (CGI) open sea regions for GBMs. The hypomethylation signature consistently predicted poor prognosis of GBMs in a series of discovery and validation datasets. It was demonstrated as an independent prognostic indicator, and showed interrelationships with known molecular marks such as MGMT promoter methylation status, and glioma CpG island methylator phenotype (G-CIMP) or IDH1 mutations. Bioinformatic analysis found that the hypomethylation signature was closely associated with the transcriptional status of an EGFR/VEGFA/ANXA1-centered gene network. The integrative molecular analysis finally revealed that the gene network defined two distinct clinically relevant molecular subtypes reminiscent of different immature neuroglial lineages in GBMs. The novel hypomethylation signature and relevant gene network may provide new insights into prognostic classification, molecular characterization, and treatment development for GBMs.
All SBR/image approach to indoor radio propagation modeling

Detailed understanding the radio propagation characteristics in a room will help the design of personal communication services (PCS) systems. There are two methods that have been applied to analyze this problem. The first, is the image theory, which is efficient, but can handle simple environments only. The second is the ray tracing technique, which is powerful for complex environments, but a reception sphere has to be introduced to determine the rays that reach the receivers, and the computed results are sensitive to the radius of the reception sphere. A deterministic model using a modified shooting and bouncing ray (SBR) technique is used to model the indoor radio propagation channels. This method can deal with complex environments, and the reception sphere is not needed. Conceptually we use the SBR method to trace ray tubes bouncing in the indoor environments. If the receiver is within a ray tube, the corresponding equivalent source (image) and its contribution to the received field at the receiver (Rx), can be determined. By summing all contributions, we can obtain the total received field at Rx.
Investigation of text-independent speaker indentification over telephone channels

In this paper, we examine several methods for text-independent speaker identification of telephone speech with limited duration data, The issue addressed is the assessment of channel characteristics, especially linear aspects, and methods for improving speaker identification performance when the speaker to be identified is on a different telephone channel than that data used for training. We show experimental evidence illustrating the cross-channel problem and also show that the direct approach, of using simple channel-invariant features, can discard much speaker dependent information. The methods we have found to be most effective rely on the training process to incorporate channel variability.
Sliding Mode Control with Disturbance Observer for Antilock Braking Systems

� Abstract— A sliding mode controller (SMC) with a disturbance observer (DOB) is developed for control of the anti-lock brake system (ABS) for passenger vehicles. Hydraulic brake dynamics as well as vehicle model parameter variation are considered in the developed control method. A SMC is designed to attain a desired wheel slip ratio without consideration of the hydraulic brake dynamics. A DOB is inserted into the SMC to reduce effects of un-modeled dynamics of the hydraulic brake system and the model parameter variation. The proposed ABS control shows good results of simulations on ABS brake dynamics, model parameter variation, and external disturbances.
Pipelining in query execution

It is shown that the use of an adjusted algorithm can improve the performance of a nested query execution containing join operations. Apart from the equijoin, the union, Cartesian product, Theta -join, and intersection operations can be implemented in a pipelining way. The difference, however, cannot be implemented in this way. The proposed algorithms are implemented in PRISMA/DB. <<ETX>>
A new approach to structural failure detection based on adaptive lattice filtering

A new approach to structural failure detection and localization previously introduced by the authors (1993) based on acoustic reflections is reviewed. It is shown that the cross-sectional areas of structural elements can be computed directly in terms of the reflection coefficients of an optimal finite impulse response filter realized in lattice form. This leads to an elegant method to detect and localize structural failures using recursive online estimation methods. In addition, for the present paper, the reflectivity method theory is investigated for noisy measurements. Also, it is shown how the theory may be applied to compound bars of varying materials and cross sectional areas. A simulation example of a compound bar is given which demonstrates the method. <<ETX>>
Quantum Computing and Grover's Algorithm

Quantum computers are at the forefront of modern computer research. They have the potential to completely redefine what computers are capable of. If peo- ple become able to efficiently construct effective quantum computers the new found computing technology would have vast implications in the fields of cryptography, artificial intelligence, physical simulations and likely many more areas which no one has yet conceived of. This talk will introduce the basics of how quantum computers work and what makes them so much more powerful than classical computers. It will explain in detail the process of one of the most famous quantum algorithms, Grover's algorithm, which is an algorithm that can find an element in a list that exploits the principles of quantum superposition and quantum entanglement to, in general, arrive at the solution faster than any classical computer could.
Bandwidth efficient QAM schemes for Rayleigh fading channels

Techniques to improve the BER performance of 16-level QAM transmission over Rayleigh fading channels for PCM systems are presented, simulations were carried out with a carrier frequency of 1.9GHz, data rate of 64 kbit/s and mobile speed of 30mph. The residual BER was reduced by over an order of magnitutde, by introducing circular constellation coupled differential amplitude and phase encoding, compared with a square QAM constellation. When an oversampling and interpolation technique was combined with circular constellation with differential encoding another order of magnitude reduction in residual BER was obtained. By expanding the number of QAM levels to 64, and on using the two extra bits gained for block coding, the BER was reduced 10-6 for channel SNRs in excess of 35 dB. Decreasing the data throughput to 48 kbit/s using 3/4 rate RS(60, 44, 12) code, 16 level QAM, interleaved over 40ms, transmitted over a Rayleigh fading channel yielded a BER of 10-6 for channel SNRs above 25 dB.
Multilayer Matching SLAM for Large-Scale and Spacious Environments

In large-scale and spacious environments, keeping a reliable data association and reducing computational complexity are challenges for the implementation of Simultaneous Localization and Mapping (SLAM). Focused on these problems, a multilayer-matching-based incremental SLAM algorithm is proposed in this article. In this algorithm, SLAM is simplified as a problem composed of a least-square-based optimization problem and data association. Then, it is solved in two steps. Firstly, a multilayer matching method is applied to deal with the data-association problem. Both matching between observation and local map and matching between different local maps are carried out. The uncertainty of the results-matching is described by the Fisher information matrix. Secondly, the robot pose is optimized through an incremental QR decomposition method. This algorithm effectively avoids the local minima caused by the limited observation information, and can build a consistent map of the environment. Meanwhile, the characters (hierarchical and incremental) of the proposed algorithm ensure low computational complexity. Experiments on simulation environments and two kinds of real environments with different sparse features verify that the algorithm is applicable for real-time application in large-scale and spacious environments.
An Improved MyProxy System in Grid by Using Hardware Security Devices

Globus, the most popular toolkit of grid, has been used to develop grid system conveniently. It comprises several security subsystems and MyProxy is an important one of them. As an online credential repository of GSI, MyProxy prevents the users from copying his credentials and private keys between computers. We provide a modified MyProxy by integrating hardware devices into it and construct a system to provide services of key management, crypto operations, etc. By using cryptography and network technologies, the security of the improved MyProxy is enhanced largely.
Parallel algorithms and systolic array designs for RSA cryptosystem

Two algorithms for computing very large integer modular exponentiation are proposed. One is based on a recording technique that significantly reduces the total number of modular multiplications. The second is parallel algorithm that can be implemented by two parallel processors and achieves optimal performance. Two corresponding systolic array designs are developed. The main advantage of these systolic architectures is to provide a potentially higher throughput for a large number of computations, namely, encryptions and decryptions in an RSA cryptosystem. <<ETX>>
AN OBJECT-ORIENTED METHODOLOGY FOR MANAGING THE COMPLEXITY OF ATM SYSTEMS

In this paper we emphasize how a computer science technology, namely the Object-Oriented (OO) approach, is able to help modeling and (in)validating large and complex systems such as ATM systems, airport ATC… Such models are the right basis for a deep analysis of properties that current or future systems should have. Systems can be modeled from two points of view: static and dynamic. We will focus our presentation on the methodological aspects. First of all we have a glance on our methodology, and the used notations. We then will exhibit a small example extracted from a current large project conducted at ONERA. Finally we will show how our models are a firm basis from which fast prototypes can be easily derived. These prototypes are the first development steps for Decision Support Systems (DSS) that can be developed and implemented according to some strong requirements. 1 An OO methodology for mastering the complexity of large and complex systems
Octopull: Integrating Static Analysis with Code Reviews

Teams using modern day software engineering practices often incorporate code reviews as a quality assurance step in their development. These code reviews are intended to uncover software quality defects before code changes are incorporated into the project. Certain classes of these software quality defects can be detected by so-called static analysis tools. These tools have seen increasing uptake and are found to be effective at finding relevant quality defects in these classes. Several tools to integrate the static analysis results into code review have been created, such as SCRUB and Review Bot. However, these tools were created specifically for internally used platforms and their source is not made available. In this thesis, we propose and implement a tool called Octopull, which is an open-source implementation that incorporates static analysis results in the user-interface of the GitHub platform. We evaluate the tool by performing a user-study on undergraduate students. Our study shows no significant effect of using the tool on the effectiveness of their code review sessions.
Intracellular and Intraorgan Concentrations of Small Molecule Drugs: Theory, Uncertainties in Infectious Diseases and Oncology, and Promise

The distribution of a drug within the body should be considered as involving movement of unbound drug between the various aqueous spaces of the body. At true steady state, even for a compound of restricted lipoidal permeability, unbound concentrations in all aqueous compartments (blood, extracellular, and intracellular) are considered identical, unless a compartment has a clearance/transport process. In contrast, total drug concentrations may differ greatly, reflecting binding or partitioning into constituents of each compartment. For most highly lipid permeable drugs, this uniform unbound concentration is expected to apply. However, many compounds have restricted lipoidal permeability and are subjected to transport/clearance processes causing a gradient between intracellular and extracellular unbound concentrations even at steady state. Additional concerns arise where the drug target resides in a site of limited vascularity. Many misleading assumptions about drug concentrations and access to drug targets are based on total drug. Correction, if made, is usually by measuring tissue binding, but this is limited by the lack of homogenicity of the organ or compartment. Rather than looking for technology to measure the unbound concentration it may be better to focus on designing high lipoidal permeable molecules with a high chance of achieving a uniform unbound drug concentration. It is hoped this paper will stimulate greater understanding of the path from circulation to cell interior, and thereby in part avoid or minimize the need to provide the experimentally very determining, and sometimes still questionable, answer to this problem.
CACHE REPLACEMENT FOR MULTI-THREADED APPLICATIONS USING CONTEXT BASED DATA PATTERN EXPLOITATION TECHNIQUE

The impact of various cache replacement policies act as the main deciding factor of system performance and efficiency in Chip Multi-Core Processors (CMP). Many existing cache replacement polices such as the Least Recently Used (LRU), Most Recently Used (MRU), Not Recently Used (NRU) etc. have proved to work well in the shared L2 cache for most of the data set patterns generated by current applications. But when it comes to parallel multi-threaded applications which generate differing patterns of workload at different intervals, the above specified schemes might prove sub-optimal as they generally do not abide by the spatial and temporal locality theories. This paper proposes a novel cache replacement policy that is targeted towards such applications. Context Based Data Pattern Exploitation Technique (CB-DPET) assigns a counter for every block of the L2 cache. It then closely monitors the data access patterns of various threads and modifies the counter values appropriately to maximize the overall hit percentage. Experimental results obtained by using the PARSEC benchmarks have shown an average improvement of 8% to 9% in overall hits at L2 cache level when compared to the conventional LRU algorithm.
Imperfect Data Analysis

Trial planning should prevent errors, but imperfections are unavoidable. Transparency is necessary (listing and description of imperfections as well as rules to deal with imperfect data should be given in the trial report). Between purism and laxism, realistic rules are often acceptable. Decisions on data should be independent of the results: written rules, and independent and blind decisions are necessary. Intent-to-treat analysis avoids biased post hoc exclusions, but a few exceptions are acceptable in extreme cases. Sensitivity analysis enables testing the robustness of results to some decisions on data. Rules are proposed for the most frequent situations: missing data, outliers, cases of protocol violations, treatment discontinuations, poor compliance, and losses to follow-up.
LINEAR AND NONLINEAR MIXED-EFFECTS MODELS

Douglas M. Bates Department of Statistics University of Wisconsin Madison Jose C. Pinheiro Bell Laboratories Lucent Technologies 1 Recent developments in computational methods for maximum likelihood (ML) or restricted maximum likelihood (REML) estimation of parameters in general linear mixed-effects models have made the analysis of data in typical agricultural settings much easier. With software such as SAS PROC MIXED we are able to handle da~ from random-effects one-way classifications, from blocked designs including incomplete blocked designs, from hierarchical designs such as splitplot designs, and other types of data that may be described as repeated measures or longitudinal data or growth-curve data. It is especially helpful that the new computational methods do not depend on balance in the data so we are able to deal more easily with observational studies or with randomly missing data in a designed experiment. We describe some of the new computational approaches and how they are implemented in the nlme3.0 library for the S-PLUS language. One of the most powerful features of this language is the graphics capabilities, especially the trellis graphics facilities developed by Bill Cleveland and his coworkers at Bell Labs. Although most participants in this conference may be more familiar with SAS, and most of the models described here can be fit with PROC MIXED or the NLiNMIX macro or new P ROC N LM IXED in SAS version 7, some exposure to the combination of graphical display and model-fitting approaches from S-PLUS may be informative. 1 Annual Conference on Applied Statistics in Agriculture Kansas State University New Prairie Press http://newprairiepress.org/agstatconference/1998/proceedings/2 2 Kansas State University We show how data exploration with trellis graphics, followed by fitting and comparing mixedeffects models, followed by graphical assessment of the fitted model can be used in a variety of situations. On some occasions, such as modeling growth curves, a linear trend or polynomial trend or other types of linear statistical models for the within-subject time dependence are just not going to do an adequate job of representing the data. In those cases, a nonlinear model is more appropriate. We show how the concept of a random coefficient model can be extended to nonlinear models so as to fit nonlinear mixed-effects models.
Separability oriented fusion of LBP and CS-LDP for infrared face recognition

Due to low resolutions of infrared face image, the local texture features are more appreciated for infrared face feature extraction. To extract rich facial texture features, infrared face recognition based on local binary pattern (LBP) and center-symmetric local derivative pattern (CS-LDP) is proposed. Firstly, LBP is utilized to extract the first order texture from the original infrared face image; Secondly, the second order features are extracted CS-LDP. Finally, an adaptive weighted fusion algorithm based separability discriminant criterion is proposed to get final recognition features. Experimental results on our infrared faces databases demonstrate that separability oriented fusion of LBP and CS-LDP contributes complementary discriminant ability, which can improve the performance for infrared face recognition
(Spine title: Computational Complexity of Numerical Solutions of IVP for DAE)

Computational Complexity of Numerical Solution of Initial Value Problems for Differential Algebraic Equations Silvana Ilie Doctor of Philosophy Graduate Department of Applied Mathematics The University of Western Ontario 2005 We investigate the cost of solving initial value problems for differential algebraic equations depending on the number of digits of accuracy requested. A recent result showed that the cost of solving initial value problems (IVP) for ordinary differential equations (ODE) is polynomial in the number of digits of accuracy. This improves on the classical result of information-based complexity, which predicts exponential cost. The new theory is based on more realistic assumptions. The algorithm analysed in this thesis is based on a previously published Taylor series method for solving a general class of differential algebraic equations. We consider DAE of constant index to which the method applies. The DAE is allowed to be of arbitrary index, fully implicit and have derivatives of order higher than one. Similarly, by considering a realistic model, we show that the cost of computing the solution of IVP for DAE with the algorithm adopted and by using automatic
Assessing the Usefulness of Object-based Programming Education Using Arduino

The purpose of this study is to use Squeak etoys and Arduino to design education activities so that middle school students can learn the object-oriented paradigm, and assess how usable the education activities are at the level of middle school students. As for education activities, learning methods, such as imitating, modifying and creating, were introduced. Usefulness assessment was divided into a cognitive domain and a definitional domain before the assessment tools were developed. An object-based programming class for 11 middle school students was then conducted and the results analysed. Positive results were confirmed in both the cognitive domain and the definitional domain. The results of this study are meaningful in that the possibility of object-oriented education was discovered for middle school students as well. Also, considering the sequence of object-oriented education, it was found that it is necessary to develop object-oriented programming education at the level of both elementary and high schools.
Brief review of non-invasive motion trajectory prediction based brain-compurer interfaces

This paper presents a brief overview of non-invasive motion trajectory prediction (MTP) for brain-computer interface (BCI). This method is an ideal solution for controlling an artificial limb or robot arm because the applied signal processing algorithm reconstruct the track of the imagined movement. Regularly used neurosensory technique for an online outside of the lab application is electroencephalography (EEG). To date only a limited number of motion trajectory prediction studies have been reported using non-invasive techniques. This review provides a brief summary of the state of the art in this area.
Programming With CLASS: Keeping Your Options Open

SAS ® procedures utilize classification variables when they are processing the data. These variables control how the procedure forms groupings, summarizations, and analysis elements. For statistics procedures they are often used in the formation of the statistical model that is being analyzed. Classification variables may be explicitly specified with a CLASS statement, or they may be specified implicitly from their usage in the procedure. Because classification variables have such a heavy influence on the outcome of so many procedures, it is essential that the analyst have a good understanding of how classification variables are applied. Certainly there are a number of options (system and procedural) that affect how classification variables behave. While you may be aware of some of these options, a great many are new, and some of these new options and techniques are especially powerful. You really need to be open to learning how to program with CLASS.