Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Histopathological Characterization of Tumorgraft Models of Pancreatic Ductal Adenocarcinoma

Pancreatic cancer is the one of the deadliest of all malignancies. The five year survival rate for patients with this disease is 3-5%. Thus, there is a compelling need for novel therapeutic strategies to improve the clinical outcome for patients with pancreatic cancer. Several groups have demonstrated for other types of solid tumors that early passage human tumor xenograft models can be used to define some genetic and molecular characteristics of specific human tumors. Published studies also suggest that murine tumorgraft models (early passage xenografts derived from direct implantation of primary tumor specimens) may be useful in identifying compounds with efficacy against specific tumor types. Because pancreatic cancer is a fatal disease and few well-characterized model systems are available for translational research, we developed and characterized a panel of pancreatic tumorgraft models for biological evaluation and therapeutic drug testing. Of the 41 primary tumor specimens implanted subcutaneously into mice, 35 produced viable tumorgraft models. We document the fidelity of histological and morphological characteristics and of KRAS mutation status among primary (F0), F1, and F2 tumors for the twenty models that have progressed to the F3 generation. Importantly, our procedures produced a take rate of 85%, higher than any reported in the literature. Primary tumor specimens that failed to produce tumorgrafts were those that either contained <10% tumor cells or that were obtained from significantly smaller primary tumors. In view of the fidelity of characteristics of primary tumor specimens through at least the F2 generation in mice, we propose that these tumorgraft models represent a useful tool for identifying critical characteristics of pancreatic tumors and for evaluating potential therapies.
Synthetic Feature Transformation with RBF Neural Network to Improve the Intrusion Detection System Accuracy and Decrease Computational Costs

With the rapidly growing and wide spread use of computer networks, the number of new attacks and malicious has grown widely. Intrusion Detection System can identify the attacks and protect the systems successfully. However, performance of IDS related to feature extraction and selection phases. In this paper, we proposed new feature transformation to overcome this weakness. For this aim, we combined LDA and PCA as feature transformation and RBF Neural Network as classifier. RBF Neural Net (RBF-NN) has a high speed in classification and low computational costs. Hence, the proposed method can be use in real time systems. Our results on KDDCUP99 shows our proposed method have better performance related to other feature transformation methods such as LDA, PCA, Kernel Discriminant Analysis (KDA) and Local Linear Embedding (LLE).
Face, Ear and Fingerprint: Designing Multibiometric Architectures

The number of biometrics as well as the number of publications about biometrics have noticeably grown in the last ten years. However, it was not possible yet to identify a bodily or behavioral feature able by itself to satisfy the acceptability and reliability constraints imposed by real applications. In this work we analyze the combination of the three different biometries face, ear and fingerprint using both a new multimodal schema, namely the N-Cross Testing Protocol, and a fast hierarchical architecture. Experimental results in the final part of our work provide a positive feedback.
Using Oxidized Low-Density Lipoprotein Autoantibodies to Predict Restenosis after Balloon Angioplasty in Patients with Acute Myocardial Infarction

Objectives Oxidized low-density lipoproteins (oxLDL) and oxidized low-density lipoprotein autoantibodies (OLAB) have been detected in human plasma and atherosclerotic lesions. OLAB appear to play a role in the clearance of oxLDL from circulation. Higher levels of OLAB appear to be associated with a reduced risk of a wide range of cardiovascular diseases. We investigated the prognostic value of plasma oxLDL and OLAB in patients undergoing primary coronary balloon angioplasty for acute ST-elevation myocardial infarction (STEMI). Methods Plasma oxLDL and OLAB concentrations were measured in 56 patients with acute STEMI before primary angioplasty, and then 3 days, 7 days and 1 month after the acute event. Follow-up angiography was repeated 6 months later to detect the presence of restensosis (defined as >50% luminal diameter stenosis). The thrombolysis in myocardial infarction (TIMI) risk score was calculated to determine the relationship between OLAB/oxLDL ratio and TIMI risk scores. Results Of the 56 patients, 18 (31%) had angiographic evidence of restenosis. Plasma OLAB concentrations were significantly lower in the restenosis group before angioplasty (181±114 vs. 335±257 U/L, p = 0.003), and at day 3 (155±92 vs. 277±185 U/L, p<0.001) and day 7 (177±110 vs. 352±279 U/L, p<0.001) after the acute event. There was no difference in oxLDL concentration between the two groups. The ratio of OLAB/oxLDL positively correlated with TIMI risk scores before angioplasty (p for trend analysis, p = 0.004), at day 3 (p = 0.008) and day 7 (p<0.001) after STEMI. Significance A relative deficit of OLAB, and hence likely impaired clearance of oxLDL, is associated with the risk of arterial restenosis after primary angioplasty for acute STEMI.
Performance Impact of Batching Web-Application Requests Using Hot-Spot Processing on GPUs

Web applications are a good fit for many-core servers because of their inherent high-degree of request-level parallelism. Yet, processing-intensive web-server requests can lead to low quality-of-service due to hot-spots, which calls for methods that can improve single-thread performance. This paper explores how to use off-chip GPUs to speed up web application hot-spots written in productivity-friendly environments (e.g. C#). First, we apply a number of straightforward optimizations through refactoring of a commercial-strength, web application code. This yields a speedup of 7.6 in a CPU multi-threaded, and multi-core test. Second, we then gather similar requests from different threads of the optimized code, by applying a technique called batching, to exploit SIMD parallelism provided by GPUs. Surprisingly, there is ample parallelism to be exploited from the already optimized code yielding a speedup of a factor between 2x to 3x compared to the best optimized CPU version.
Exploiting Readily Available Information to Support Everyday Creativity on the Move

The advent of smartphones has enormously expanded utilitarian capabilities of mobile computing and has provided many advanced capabilities to their users. We take advantage of the advanced interaction capabilities of smartphones to enable their user perform exploratory search with the goal of fostering inspiration. Our search application combines diversification of content and sources with a user interface design that utilises cues from the social chatter to perform query expansion and let users interactively explore the available information space.
Aggressive dynamic voltage scaling for energy-aware video playback based on decoding time estimation

An effective way for reducing CPU power consumption is to reduce its operating frequency. But this slows down program execution, which may violate the real-time requirements of video playback. What is worse, it is difficult to predict future decoding times, and unduly conservative policies may miss viable opportunities to reduce the CPU frequency. The effectiveness of such power-saving techniques is thus dependent on an ability to estimate future demands on the CPU. We present the design, implementation and evaluation of a dynamic voltage scaling (DVS) scheme for portable media players. We measured decoding times on real videos and extracted a precise relationship between frame size and decoding time using logarithmic regression. Based on this model, we propose a frequency selection algorithm which accepts some deadline misses, and selects the frequencies required to achieve a specified deadline miss ratio. We implemented this scheme in MPlayer running on the Linux 2.6. Experimental results show that its system-wide energy consumption is up to 17% less than conventional DVS schemes and up to 24% less than non-DVS schemes.
Measuring and policing blocking times in real-time systems

In real-time systems, the execution-time overrun of a thread may lead to a deadline being missed by the thread or even others threads in the system. From a fault tolerance perspective, both execution time overruns and deadline misses can be considered timing errors that could potentially cause a failure in the system's ability to deliver its services in a timely manner. In this context, the ideal is to detect the error in the system as soon as possible, so that the propagation of the error can be limited and error recovery strategies can take place with more accurate information. The run-time support mechanism usually deployed for monitoring the timing requirements of real-time systems is based on deadline monitoring, that is, the system calls specific application code whenever a deadline is violated. Recognizing that deadline monitoring may not be enough for providing an adequate level of fault tolerance for timing errors, major real-time programming standards, like Ada, POSIX and the Real-Time Specification for Java (RTSJ), have proposed different mechanisms for monitoring the execution time of threads. Nevertheless, in order to provide a complete fault tolerance approach for timing errors, the potential blocking time of threads also has to be monitored. In this article, we propose mechanisms for measuring and policing the blocking time of threads in the context of both basic priority inheritance and priority ceiling protocols. The notion of blocking-time clocks and timers for the POSIX standard is proposed, implemented and evaluated in the open-source real-time operating system MaRTE OS. Also, a blocking time monitoring model for measuring and policing blocking times in the RTSJ framework is specified. This model is implemented and evaluated in the (RTSJ-compliant) open-source middleware jRate, running on top of MaRTE OS.
GLYCAM06: A generalizable biomolecular force field. Carbohydrates

A new derivation of the GLYCAM06 force field, which removes its previous specificity for carbohydrates, and its dependency on the AMBER force field and parameters, is presented. All pertinent force field terms have been explicitly specified and so no default or generic parameters are employed. The new GLYCAM is no longer limited to any particular class of biomolecules, but is extendible to all molecular classes in the spirit of a small‐molecule force field. The torsion terms in the present work were all derived from quantum mechanical data from a collection of minimal molecular fragments and related small molecules. For carbohydrates, there is now a single parameter set applicable to both α‐ and β‐anomers and to all monosaccharide ring sizes and conformations. We demonstrate that deriving dihedral parameters by fitting to QM data for internal rotational energy curves for representative small molecules generally leads to correct rotamer populations in molecular dynamics simulations, and that this approach removes the need for phase corrections in the dihedral terms. However, we note that there are cases where this approach is inadequate. Reported here are the basic components of the new force field as well as an illustration of its extension to carbohydrates. In addition to reproducing the gas‐phase properties of an array of small test molecules, condensed‐phase simulations employing GLYCAM06 are shown to reproduce rotamer populations for key small molecules and representative biopolymer building blocks in explicit water, as well as crystalline lattice properties, such as unit cell dimensions, and vibrational frequencies. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008
Zero-Delay Source-Channel Coding with a One-Bit ADC Front End and Correlated Side Information at the Receiver

Zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel is considered with a one-bit analog-to-digital converter (ADC) front end and a correlated side information at the receiver. The design of the optimal encoder and decoder is studied for two performance criteria, namely, the mean squared error (MSE) distortion and the distortion outage probability (DOP), under an average power constraint on the channel input. For both criteria, necessary optimality conditions for the encoder and the decoder are derived. Using these conditions, it is observed that the numerically optimized encoder (NOE) under the MSE distortion criterion is periodic, and its period increases with the correlation between the source and the receiver side information. For the DOP, it is instead seen that the NOE mappings periodically acquire positive and negative values, which decay to zero with increasing source magnitude, and the interval over which the mapping takes non-zero values, becomes wider with the correlation between the source and the side information.
Density-Dependent Feedback Inhibition of Oligodendrocyte Precursor Expansion

The myelin sheath in the vertebrate CNS is formed by oligodendrocytes. The number of oligodendrocytes in a mature axon tract must be sufficient to myelinate all appropriate axons. How the number of oligodendrocytes is matched to axonal requirements and whether such matching involves axon–oligodendrocyte signaling or intrinsic oligodendrocyte self-regulation are not clear. Using a combination of in vitro analyses, we demonstrate that oligodendrocyte precursors closely regulate their numbers through interactions between adjacent precursors. In low-density rat spinal cord cultures, the number of oligodendrocyte lineage cells increases rapidly. The addition of large numbers of oligodendrocyte precursors substantially reduces precursor expansion and results in a normalization of oligodendrocyte lineage cell numbers in the cultures over time. Thus, the number of oligodendrocyte lineage cells that develop appears dependent on the density of oligodendrocyte lineage cells. This normalization of cell number is reflected in assays of clonal potential and proliferation. For example, precursors gave rise to fewer progeny and proliferated less at high density. Reduced precursor expansion at high density was not attributable to the depletion of growth factors. Cocultures of high and low densities did not inhibit precursor expansion in low-density cultures, suggesting the requirement for local cell–cell interactions. The inhibition of precursor expansion was cell-type-specific and dependent on the presence of oligodendrocyte lineage cells. We propose that this density-dependent feedback inhibition of oligodendrocyte precursor expansion may play a primary role in regulating the number of oligodendrocytes in the developing spinal cord.
Recovery of motion patterns and dominant paths in videos of crowded scenes

Assessing crowd behaviors from videos is a difficult task while of interest in many applications. We have defined a novel approach which identifies from two successive frames only, crowd behaviors expressed by simple image motion patterns. It relies on the estimation of a collection of sub-affine motion models in the image, a local motion classification based on a penalized likelihood criterion, and a regularization stage involving inhibition and reinforcement factors. We have also developed an original and simple method for recovering the dominant paths followed by people in the observed scene. It involves the introduction of local paths determined from the space-time average of the parametric motion subfields selected in each image block. Experiments on synthetic and real scenes have demonstrated the performance of our method.
A novel reduced-complexity widely linear QLMS algorithm

The widely linear quaternion least mean square (WL-QLMS) algorithm is used to capture complete second order statistics in quaternion valued mean-square estimation (MSE). However, quaternion operations during the signal processing have high computational cost, since each operation involves the calculation of one real part and three different imaginary elements. We propose a reduced-complexity WL-QLMS (RC-WL-QLMS) algorithm, and we show that using a real data vector, the RC-WL-QLMS achieves the same MSE of the WL-QLMS, with lower computational cost. The new algorithm also presents faster convergence when compared to the WL-QLMS, which is shown analytically and through simulations.
A Phase and intensity preserved image denoising technique

This paper explores the issues of denoising methodology by non-orthogonal, complex valued, log-Gabor wavelets, rather than the more usual orthogonal or bi-orthogonal wavelets. Thresholding of wavelet responses in the complex domain allows one to ensure that perceptually important phase information in the image is not corrupted. And to preserve the intensity information, the preprocessed image is given into the process of image registration with the same object of its atlas image. This method used the locally affine but globally smooth warping techniques.
Solution Scattering Suggests Cross-linking Function of Telethonin in the Complex with Titin*

Telethonin interacts specifically with the two Z-disk IG-like domains (Z1Z2) at the N terminus of titin, the largest presently known protein. Analytical ultracentrifugation and synchrotron radiation x-ray scattering were employed to study the solution structures of Z1Z2 and its complexes with telethonin, and low resolution models were constructed ab initio from the scattering data. A seven residues-long polyhistidine tag was localized at the tip of the Z1 domain by comparison of independent models of native and His-tagged versions of Z1Z2. The stoichiometry and shape of the complex between the telethonin construct lacking the C terminus and Z1Z2 indicate antiparallel association of two Z1Z2 molecules with telethonin acting as a central linker. The complex of full-length telethonin with Z1Z2 appears to also have a 1:2 stoichiometry at concentrations below 1 mg/ml but dimerizes at higher concentrations. These results suggest a possible role of telethonin in linking titin filaments at the Z-disk periphery.
Resource and Application Models for Advanced Grid Schedulers

As Grid computing is becoming an inevitable future, managing, scheduling and monitoring dynamic, heterogeneous resources will present new challenges. Solutions will have to be agile and adaptive, support self-organization and autonomous management, while maintaining optimal resource utilisation. Presented in this paper are basic principles and architectural concepts for efficient resource allocation in heterogeneous Grid environment.
Providing views and closure for the ODMG object model.

The ODMG Object Model uses a standard for object-oriented database designers, while attempting to address some issues of interoperability. This research is focused on the viability of using the ODMG data model as a canonical data model in a multidatabase environment, and where weaknesses are identified we have proposed amendments to enable the model to suit the specific needs of this type of distributed database system. This paper describes our eorts to extend its relational style alge-bra, and to provide query closure and a viewing mechanism for OQL to construct multidatabase schemas.
Semantically driven inversion transduction grammar induction for early stage training of spoken language translation

We propose an approach in which we inject a crosslingual semantic frame based objective function directly into inversion transduction grammar (ITG) induction in order to semantically train spoken language translation systems. This approach represents a follow-up of our recent work on improving machine translation quality by tuning loglinear mixture weights using a semantic frame based objective function in the late, final stage of statistical machine translation training. In contrast, our new approach injects a semantic frame based objective function back into earlier stages of the training pipeline, during the actual learning of the translation model, biasing learning toward semantically more accurate alignments. Our work is motivated by the fact that ITG alignments have empirically been shown to fully cover crosslingual semantic frame alternations. We show that injecting a crosslingual semantic based objective function for driving ITG induction further sharpens the ITG constraints, leading to better performance than either the conventional ITG or the traditional GIZA++ based approaches.
Stochastic Spectral Descent for Restricted Boltzmann Machines

Restricted Boltzmann Machines (RBMs) are widely used as building blocks for deep learning models. Learning typically proceeds by using stochastic gradient descent, and the gradients are estimated with sampling methods. However, the gradient estimation is a computational bottleneck, so better use of the gradients will speed up the descent algorithm. To this end, we rst derive upper bounds on the RBM cost function, then show that descent methods can have natural advantages by operating in the‘1 and Shatten1 norm. We introduce a new method called \Stochastic Spectral Descent" that updates parameters in the normed space. Empirical results show dramatic improvements over stochastic gradient descent, and have only have a fractional increase on the per-iteration cost.
Modelling to Simulate Botnet Command and Control Protocols for the Evaluation of Network Intrusion Detection Systems

The purpose of this paper is the modelization and simulation of zombie machines for the evaluation of Network Intrusion Detection Systems (NIDS), used to detect botnets. We propose an automatic method to infer zombies behaviours through the analysis of messages exchanged with their masters. Once computed, a model provides a way to generate realistic and manageable traffic, which is mandatory for an NIDS evaluation. We propose to use a Stochastic Mealy Machine to model zombies behaviours, and an active inference algorithm to learn it. With our approach, it is possible to generate a realistic traffic corresponding to the communications of botnets while ensuring its controllability in the context of an NIDS evaluation.
Radicals as Ontologies : Concept Derivation and Knowledge Representation of Four-Hoofed Mammals as Semantic Symbols

Research on linguistic ontology can shed light on how human beings conceptualize as well as provide powerful tools for knowledge engineering. We show in this paper that the linguistic ontology of Chinese is conventionalized by the radical/semantic symbol of its writing system and a study of this conventionalized system leads to many interesting theoretical discoveries. The Shuowen Jiezi (Xu Shen 121), the oldest preserved dictionary of Chinese, is organized according to the radical forms as semantic symbols. Our hypothesis is that for characters sharing the same radical, their meanings must be related to the basic concept of the semantic symbol in a systemic way. In this current research, we focus on the small semantic field of four-hoofed mammals: 羊 ‘caprid’, 鹿 ‘cervid’, 牛 ‘bovine’ and 馬 ‘equine’. We describe the relations between the derived characters and each basic concept to construct a conventionalized ontology, headed by basic concepts expressed by the semantic symbols. Our analysis of the semantic symbol ontologies for these four-hoofed mammals shows that they have similar conceptual structures, which are strongly motivated by their functions in human society. In particular, we show that the conceptual dependencies between the basic concept of a radical and the meanings of the derived characters can be explained by an enriched version of the generative lexicon.