Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum BER FIR receiver filters for DS-CDMA systems

The problem of multi-user receiver design in direct sequence single antenna-code division multiple access (DS-CDMA) uplink networks is studied over multipath channels. An exact expression for the bit error rate (BER) is derived and an algorithm is proposed for finding the finite impulse response (FIR) receiver filters such that the exact BER of the active users is minimized. The algorithm performance is found for scenarios with different channel qualities, receiver filter lengths, near-far effects, and channel mismatch. The proposed FIR receiver structure has significant better BER with respect to Eb/N0 and near-far resistance than the corresponding minimum mean square error (MSE) filters
On the Impact of Environmental Metrics on CVSS Scores

CVSS is a framework which provides a method for rating the severity level of IT vulnerabilities. It takes into account not only the intrinsic characteristics of the vulnerability, but also its evolution over time and the user environment in which it is detected. A severity, or CVSS, score, is evaluated using several metrics : base / temporal / environmental. Base metrics assessments are achieved through organizations which maintain IT dictionaries ( CVE for example). These ratings can be found in public IT vulnerability databases such as NVD, OSVDB, … This paper studies the impact of applying environmental metrics to CVSS scores stored in NVD database, focuses on the variation of CVSS score distribution and identifies specific problems in modified CVSS score formulae.
Quantum stabilizer codes from difference sets

In this work we have developed a new method to construct general quantum stabilizer codes of variable block size by adopting the notion of a difference set. The proposed method comprises an efficient way to obtain the difference set, and from that set the construction of a quantum stabilizer code, which we refer to as a DSS (Difference Set Stabilizer) code. Our efficient method to generate the difference set requires no computer search, instead only a single parameter is required to generate the set.
Arsenic in Groundwater in Eastern New England : Occurrence , Controls , and Human Health Implications

In eastern New England, high concentrations (greater than 10 μg/L) of arsenic occur in groundwater. Privately supplied drinking water from bedrock aquifers often has arsenic concentrations at levels of concern to human health, whereas drinking water from unconsolidated aquifers is least affected by arsenic contamination. Water from wells in metasedimentary bedrock units, primarily in Maine and New Hampshire, has the highest arsenic concentrationss nearly 30% of wells in these aquifers produce water with arsenic concentrations greater than 10 μg/L. Arsenic was also found at concentrations of 3-40 mg/kg in whole rock samples in these formations, suggesting a possible geologic source. Arsenic is most common in groundwater with high pH. High pH is related to groundwater age and possibly the presence of calcite in bedrock. Ion exchange in areas formerly inundated by seawater also may increase pH. Wells sampled twice during periods of 1-10 months have similar arsenic concentrations (slope ) 0.89; r-squared ) 0.97). On the basis of wateruse information for the aquifers studied, about 103 000 people with private wells could have water supplies with arsenic at levels of concern (greater than 10 μg/L) for human health.
CAN A ONE-DIMENSIONAL STRAINED FLAME MODEL COMBUSTION IN FLAME-VORTEX INTERACTIONS ?

We present a study of the flame-embedding concept, introduced in [1] as an efficient approach for large-eddy simulation of turbulent combustion at high Reynolds and Damköhler numbers. In flame embedding, the combustion zone is modeled as an unsteady flame modified by the local tangential strain rate, with the latter extracted every time step from the flow field simulations. The flame structure is approximated locally as being one-dimensional, evolving in the flow field generated by a stagnation-point flow whose characteristic parameter is the applied flow strain. Two-dimensional flame-vortex interaction simulations are used as the benchmark for this study. The time-dependent strain rate at the flame front is extracted from the two-dimensional simulations and used in the one-dimensional, unsteady strained flame structure calculations. We present results for a matrix of parameters that define the impact of the flow on the flame in a flame-vortex interaction—the vortex pair size, separation and circulation—and use the instantaneous burning rate to determine the accuracy of the model. We show that the onedimensional unsteady flame calculation can capture the impact of the applied flow strain on the burning rate if the former is taken as the corresponding “non-reacting” flow strain rate at the flame reaction zone, and not the applied flow strain at the flame leading edge. The distinction is important in cases where the flame front thickness approaches that of the flow field, a situation that is likely to be encountered when small vortices interact with lean flames.
A Probabilistic OWL Reasoner for Intelligent Environments

OWL ontologies have gained great popularity as a context modelling tool for intelligent environments due to their expressivity. However, they present some disadvantages when it is necessary to deal with uncertainty, which is common in our daily life and affects the decisions that we take. To overcome this drawback, we have developed a novel framework to compute fact probabilities from the axioms in an OWL ontology. This proposal comprises the definition and description of our probabilistic ontology. Our probabilistic ontology extends OWL 2 DL with a new layer to model uncertainty. With this work we aim to overcome OWL limitations to reason with uncertainty, developing a novel framework that can be used in intelligent environments.
Expression and clinical significance of erb-B receptor family in hepatocellular carcinoma

In order to elucidate the clinical significance of the erbB family, epidermal growth factor receptor (EGF-R), c-erbB-2, c-erbB-3 and c-erbB-4 in hepatocellular carcinoma (HCC), we investigated the expression of these proteins by means of immunohistochemistry for HCC as well as adjacent noncancerous lesions. EGF-R was expressed in 68% of the HCC examined and showed correlation with the proliferating activity, stage, intrahepatic metastasis and carcinoma differentiation. c-erbB-2 was expressed in only 21% of the cases and showed no relationships with the clinicopathological parameters. c-erbB-3 protein was observed in 84% of the HCC and 38.1% of the noncancerous lesions. Its expression in HCC was equal to or greater than noncancerous lesions in 90.5% of the cases, and was related to the stage, portal invasion, cell proliferating activity, tumour size, intrahepatic metastasis and carcinoma differentiation. c-erbB-4 protein was expressed in 61.0% of HCC and in as much as 86.1% of the noncancerous lesions. Unlike the expression of c-erbB-3, that of c-erbB-4 in HCC was less than that of the adjacent noncancerous lesions in 51.2% of the cases. No statistical significance could be established between this protein expression in HCC and clinicopathological features. EGF-R and c-erbB-3 affected disease-free survival, but were not recognized as independent prognostic factors by multivariate analysis. The present study suggests that, of the four receptors, EGF-R and c-erbB-3 play important roles in the progression of HCC. © 2001 Cancer Research Campaign
Illumination Invariant Colour Recognition

The article describes a colour based recognition system with three novel features. Firstly, the proposed system can operate in environments where spectral characteristics of illumination change in both space and time. Secondly, benefits in terms of speed and quality of output are gained by focusing processing to areas of salient colour. Finally, an automatic model acquisition procedure allows rapid creation of the model database.
A Thermal Improvement Technique for the Phase Windings of Electrical Machines

In electrical machines, a higher torque/force density can usually be achieved by increasing the current density in the windings. However, the resulting increase in copper losses leads to higher temperatures in the coils, particularly in the center of the slots where the thermal resistance to the ambient/cooling surfaces is highest. In this paper, a novel, simple technique is presented in which a higher thermal conductivity path between the center of the slot and the cooling arrangement is created, thus increasing the heat flow away from the slot center. A lumped-parameter thermal model is presented and used along with finite-element analysis to investigate the effectiveness of the proposed technique. The lumped-parameter model is also used for optimizing the high conductivity path for maximum air-gap shear stress and to obtain a compromise between the reduced slot area and the improved temperature distribution. Experimental validation is then presented to compare the predicted results with the measured results on a purposely built instrumented setup.
Sparse Representation Based Discriminative Canonical Correlation Analysis for Face Recognition

Canonical correlation analysis (CCA) has been widely used in pattern recognition and machine learning. However, both CCA and its extensions sometimes cannot give satisfactory results. In this paper, we propose a new CCA-type method termed sparse representation based discriminative CCA (SPDCCA) by incorporating sparse representation and discriminative information simultaneously into traditional CCA. In particular, SPDCCA not only preserves the sparse reconstruction relationship within data based on sparse representation, but also preserves the maximum-margin based discriminative information, and thus it further enhances the classification performance. Experimental results on Yale, Extended Yale B, and ORL datasets show that SPDCCA outperforms both CCA and its extensions including KCCA, LPCCA and LDCCA in face recognition.
A DDS-compliant infrastructure for fault-tolerant and scalable data dissemination

Recent trends in data-centric systems have motivated significant standardization efforts, such as the Data Distribution Service (DDS) to enable data dissemination with guaranteed Quality of Service (QoS). However, clear design guidelines and techniques for the support of reliable and scalable DDS-based deployments, especially for (mobile) data intensive services, such as Internet-wide information dissemination for breaking news or financial analysis services, are still missing. After an analysis of main DDS fault-tolerance and scalability deployment issues, this paper proposes a novel solution with two core original contributions: i) DDS-compliant routing substrate to facilitate reliable data dissemination between mobile devices; ii) relay-based DDS support infrastructure with limited overhead to enable scalable Internet-wide data dissemination. Our solution, especially tailored for mobile computing scenarios, is lightweight and requires neither persistency nor heavy operations at mobile device side. Reported experimental results confirm that our proposal can guarantee desired scalability requirements with a limited network, CPU, and memory resource overhead.
A Novel Technique for the Restoration of AFM Images EnablinganEstimated Impulse Response forthe AFM to be Calculated Using Square Pillar and Cylindrical Pillar Samples

All atomic force microscope (AFM) images suffer from distortions, which are principally produced by the interaction between the measured sample and the AFM tip. The atomic force microscope (AFM) is a very important instrument for use in nanotechnology and biology since it can be used to measure a wide variety of objects, such as nano-particles and cells, either in air or liquid. However, the images that are measured using AFM are distorted because of both the influence of the tip geometry and the dynamic response of the instrument. This influence means that the images do not accurately represent the real shape of the measured particles or cells. Therefore, it is necessary to reconstruct the AFM tip shape. This paper proposes a new approach (impulse response technique) to reconstruct the AFM tip shape from either a square or cylindrical pillar sample that is measured using AFM. Once the tip shape is known, a deconvolution process is carried out between the estimated tip shape and typical AFM ‘distorted’ images in order to reduce the distortion effects. The experimental results and the computer simulations validate the performance of the proposed approach, in which it is shownthat the AFM image accuracy has been significantly improved. The suitability of this novel approach for restoring AFM images has been confirmed using both computer simulation and also with real experimental AFM images. The blind tip estimation approach is anindustrial and research standard algorithm for the restoration of AFM images. We therefore also compare the proposed algorithms with the blind tip estimation algorithm, via the use of both computer simulations and real AFM images, and our algorithm is shown to give enhanced results when compared with the blind tip estimation approach.
The Arabidopsis GRAS Protein SCL14 Interacts with Class II TGA Transcription Factors and Is Essential for the Activation of Stress-Inducible Promoters[C][W]

The plant signaling molecule salicylic acid (SA) and/or xenobiotic chemicals like the auxin mimic 2,4-D induce transcriptional activation of defense- and stress-related genes that contain activation sequence-1 (as-1)–like cis-elements in their promoters. as-1–like sequences are recognized by basic/leucine zipper transcription factors of the TGA family. Expression of genes related to the SA-dependent defense program systemic acquired resistance requires the TGA-interacting protein NPR1. However, a number of as-1–containing promoters can be activated independently from NPR1. Here, we report the identification of Arabidopsis thaliana SCARECROW-like 14 (SCL14), a member of the GRAS family of regulatory proteins, as a TGA-interacting protein that is required for the activation of TGA-dependent but NPR1-independent SA- and 2,4-D–inducible promoters. Chromatin immunoprecipitation experiments revealed that class II TGA factors TGA2, TGA5, and/or TGA6 are needed to recruit SCL14 to promoters of selected SCL14 target genes identified by whole-genome transcript profiling experiments. The coding regions and the expression profiles of the SCL14-dependent genes imply that they might be involved in the detoxification of xenobiotics and possibly endogenous harmful metabolites. Consistently, plants ectopically expressing SCL14 showed increased tolerance to toxic doses of the chemicals isonicotinic acid and 2,4,6-triiodobenzoic acid, whereas the scl14 and the tga2 tga5 tga6 mutants were more susceptible. Hence, the TGA/SCL14 complex seems to be involved in the activation of a general broad-spectrum detoxification network upon challenge of plants with xenobiotics.
Towards a Cognitively Realistic Representation of Word Associations

The ability to associate words is an important cognitive skill. In this study we investigate different methods for representing word associations in the brain, using the Remote Associates Test (RAT) as a task. We explore representations derived from free association norms and statistical n-gram data. Although n-gram representations yield better performance on the test, a closer match with the human performance is obtained with representations derived from free associations. We propose that word association strengths derived from free associations play an important role in the process of RAT solving. Furthermore, we show that this model can be implemented in spiking neurons, and estimate the number of biologically realistic neurons that would suffice for an accurate representation.
Adaptive discontinuous Galerkin approximation of optimal control problems governed by transient convection-diffusion equations

In this paper, we investigate a posteriori error estimates of a control-constrained optimal control problem governed by a time-dependent convection diffusion equation. The control constraints are handled by using the primal-dual active set algorithm as a semi-smooth Newton method and by adding a Moreau-Yosida-type penalty function to the cost functional. Residual-based error estimators are proposed for both approaches. The derived error estimators are used as error indicators to guide the mesh refinements. A symmetric interior penalty Galerkin method in space and a backward Euler method in time are applied in order to discretize the optimization problem. Numerical results are presented, which illustrate the performance of the proposed error estimators.
LMI approach to H2 reduction model of switched systems

This paper presents the H2 model reduction problem for discrete-time switched systems using average dwell-time approach. First, by constructing multiple Lyapunov functions, the exponential stability criterion of switched systems under average dwell-time taualpha is established. Then, a reduced-order model for the underlying system is constructed, which guarantees these two models are close in H2 norm sense. Finally, an example is given to illustrate our results. All the results in this paper are expressed in terms of linear matrix inequalities (LMIs), which can be easily tested with efficient LMI algorithms.
The Use of a Liposomal Formulation Incorporating an Antimicrobial Peptide from Tilapia as a New Adjuvant to Epirubicin in Human Squamous Cell Carcinoma and Pluripotent Testicular Embryonic Carcinoma Cells

This study aims to explore the effects and mechanisms of hepcidin, a potential antimicrobial peptide from Tilapia, and epirubicin (Epi), an antineoplastic agent, on the generation of reactive oxygen species (ROS) and link the ROS levels to the reversal mechanisms of multidrug resistance (MDR) by epirubicin and hepcidin in human squamous cell carcinoma SCC15 and human embryonal carcinoma NT2D1 cells. The cells, pretreated with hepcidin, epirubicin, or a combination of these compounds in PEGylated liposomes, were used to validate the molecular mechanisms involved in inhibiting efflux transporters and inducing apoptosis as evaluated by cytotoxicity, intracellular accumulation, mRNA levels, cell cycle distribution, and caspase activity of this combination. We found that hepcidin significantly enhanced the cytotoxicity of epirubicin in liposomes. The co-incubation of epirubicin with hepcidin in liposomes intensified the ROS production, including hydrogen peroxide and superoxide free radicals. Hepcidin significantly increased epirubicin intracellular uptake into NT2D1 and SCC15 cells, as supported by the diminished mRNA expressions of MDR1, MDR-associated protein (MRP) 1, and MRP2. Hepcidin and/or epirubicin in liposomes triggered apoptosis, as verified by the reduced mitochondrial membrane potential, increased sub-G1 phase of cell cycle, incremental populations of apoptosis using annexin V/PI assay, and chromatin condensation. As far as we know, this is the first example showing that PEGylated liposomal TH1-5 and epirubicin gives rise to cell death in human squamous carcinoma and testicular embryonic carcinoma cells through the reduced epirubicin efflux via ROS-mediated suppression of P-gp and MRPs and concomitant initiation of mitochondrial apoptosis pathway. Hence, hepcidin in PEGylated liposomes may function as an adjuvant to anticancer drugs, thus demonstrating a novel strategy for reversing MDR.
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping

Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a psychological and computational theory about analogy making, to find mappings between the source and target tasks and thus construct the transfer functional automatically. Our structure mapping algorithm is a specialized and optimized version of the structure mapping engine and uses heuristic search to find the best maximal mapping. The algorithm takes as input the source and target task specifications represented as qualitative dynamic Bayes networks, which do not need probability information. We apply this method to the Keepaway task from RoboCup simulated soccer and compare the result from automated transfer to that from handcoded transfer.
Epigenetic activation of mu opioid receptor ( MOR ) gene via increased expression and function of mitogen-and stress-activated protein kinase 1 ( MSK 1 )

55455 This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. ABSTRACT Since the discovery of mu opioid receptor (MOR) gene two decades ago, various regulatory factors have been shown to interact with the MOR promoter and modulate transcript levels. However, the majority of early transcriptional studies on MOR gene have not addressed how intracellular signaling pathways mediate extracellular modulators. In this study, we demonstrate that MOR epigenetic regulation requires multiple coordinated signals converged at the MOR promoter, involving mitogen-activated protein kinase (MAPK) activation and mitogen-and stress-activated protein kinase (MSK1)-similar ranges of intracellular signaling pathways that are activated by opioid agonists. Inhibiting p38 MAPK or ERK 1/2 MAPK (upstream activators of MSK1) reduced MOR expression levels, and accordingly, the functional role of MSK1, but not MSK2, was demonstrated using genetic approaches. However, for maximal MSK1 effect, an open chromatin configuration was required, because in-vitro CpG methylation of the MOR promoter abolished MSK1 activity. Finally, endogenous MSK1 levels concomitantly increased to regulate MOR gene expression during neuronal differentiation of P19 cells, suggesting a conserved role of this kinase in the epigenic activation of MOR in neurons. Taken together, our findings indicate that the expression of MOR gene requires the activity of intracellular signaling pathways that have been implicated in the behavioral outcomes of opioid drugs, which suggests that an auto-regulatory mechanism may function in opioid systems.