Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Carbon Nanotube Bundle Interconnect for Future FPGA Architectures

Field programmable gate arrays (FPGAs) are important hardware platforms in various applications due to increasing design complexity and mask costs. However, as CMOS process technology continues to scale, standard copper interconnect becomes a major bottleneck for FPGA performance. This paper proposed utilizing bundles of single-walled carbon nanotubes (SWCNT) as wires in the FPGA interconnect fabric and compare their performance to standard copper interconnect in future process technologies. To leverage the performance advantages of nanotube-based interconnect, several important aspects of the FPGA routing architecture were explored including the segmentation distribution and the internal population of the wires. The results demonstrate that FPGAs utilizing SWCNT bundle interconnect can achieve a 19% improvement in average area delay product over the best performing architecture for standard copper interconnect in 22 nm process technology
Exact pairwise error probability analysis of space-time codes in spatially correlated fading channels

In this paper, we derive an analytical expression for the exact pairwise error probability (PEP) of a space-time coded system operating over a spatially correlated slow fading channel using a moment-generating function-based approach. This analytical PEP expression is more realistic than previously published exact-PEP expressions as it fully accounts for antenna spacing, antenna geometries (uniform linear array, uniform grid array, uniform circular array, etc.) and scattering models (uniform, Gaussian, Laplacian, Von-Mises, etc.). Inclusion of spatial information provides valuable insights into the physical factors determining the performance of a spacetime code. We demonstrate the strength of our new analytical PEP expression by evaluating the performance of two spacetime trellis codes proposed in the literature for different spatial scenarios. Keywords— Gaussian Q-function, modal correlation, momentgenerating function, MIMO system, non-isotropic scattering, space-time coding.
Termination of the respiratory burst in human neutrophils.

Recent evidence has suggested that a particulate O(2) (-)-forming system is responsible for the respiratory burst in activated neutrophils. The respiratory burst is normally a transient event, lasting only 30-60 min. To investigate the mechanism by which the burst is terminated, we examined the O(2) (-)-forming activity of neutrophil particles as a function of time in the presence and absence of agents known to affect the function of intact cells. Measurements of the O(2) (-)-forming capacity of the particles against time of exposure of neutrophils to opsonized zymosan, a potent stimulating agent, revealed a rapid fall in activity when exposure was continued beyond 3 min. Exposure to zymosan under conditions in which the myeloperoxidase system was inactive (i.e., in the presence of myeloperoxidase inhibitors, or in the absence of oxygen) resulted in a substantial increase in the initial O(2) (-)-forming activity of particles from the zymosan-treated cells, but did not prevent the sharp fall in activity seen when zymosan exposure exceeded 10 min. The fall in activity was, however, prevented when activation took place in the presence of cytochalasin B (1.5 mug/ml), an agent thought to act largely by paralyzing the neutrophil through an interaction with its microfilament network.We conclude from these findings that the termination of the respiratory burst results at least in part from the inactivation of the particulate O(2) (-)-forming system. This inactivation involves at least two processes which probably act simultaneously. One is the destruction of the system through the action of myeloperoxidase. The other appears to require active cell motility and is independent of oxygen. The current view holds that the O(2) (-)-forming system of the neutrophil is located in the plasma membrane. It may be that the second process involves the internalization and degradation of this membrane-bound system.
Fluorescent Bacterial Magnetic Nanoparticles as Bimodal Contrast Agents

Objectives:The purpose of this study was to assess whether fluorochrome-coupled bacterial magnetic nanoparticles can be used as bimodal contrast agent for both magnetic resonance imaging (MRI) and near-infrared fluorescence optical (NIRF) imaging of cultured macrophages. Materials and Methods:Bacterial magnetic nanoparticles (magnetosomes, particle diameter: 42 nm) were harvested from Magnetospirillum gryphiswaldense and characterized by using MRI. After covalent coupling to the fluorescent dye DY-676 (λabs./λem.= 676 nm/701 nm, Dyomics, Jena, Germany), the fluorescent magnetosomes were analyzed by fluorescence-activated cell sorting. Subsequently, murine macrophages J774 were incubated with the bimodal contrast agent (3 hours) and examined by a whole-body near infrared small animal imaging system as well as by using a 1.5 T clinical MR system. Moreover, labeled cells were characterized using confocal laser scanning microscopy (CLSM) and ultrathin section transmission electron microscopy. Results:Characterization of the nanoparticles by MRI revealed R1 and R2 relaxivities of 3.2 mM−1s−1 and 526 mM−1s−1, respectively. Fluorochrome-coupled magnetosomes exhibited increased fluorescence intensities at wavelengths >670 nm. Macrophages that were incubated with the contrast agent showed a significant fluorescence emission in the near infrared range as imaged with a whole body NIR imaging system, FACS analysis and CLSM. Moreover, CLSM data showed the greatest fluorescence intensities within intracellular compartments and colocalized with the magnetosomes. With MRI, both T1 and T2 relaxation times were substantially shortened at concentrations greater than 600 cells/&mgr;L. Discussion and Conclusion:Macrophages could be labeled with fluorescent magnetosomes, and they were successfully imaged using both a 1.5 T MR scanner as well as with NIRF optical methods. The use of this bimodal contrast agent for diagnostic purposes may benefit from the excellent spatial resolution of the MRI and the high sensitivity of the fluorescence imaging.
Power Management Extensions for Tagus-SensorNet

A flexible Wireless Sensor Network platform for easier implementation of diverse applications has been developed and deployed at one of the Instituto Superior Tecnico - Technical University of Lisbon (IST-TUL) campus. Since its initial deployment in 2007, this test-bed has grown steadily, supporting new nodes, applications and experiments. However, some initial problems, which were solved on an ad hoc basis, are becoming more serious as the network spans throughout the campus. Major issues, like global power management, have to be tackled not only with traditional protocol level approaches but also from a system’s viewpoint, providing solutions that are capable of guaranteeing a consistent operational test-bed. We discuss the main issues related with the development of power management solutions, at different levels, presenting our architecture, design choices and implementation. We also address the lessons learnt from its integration in the platform. Results of the experimental evaluation of our solution have shown considerable energy savings (extending the network lifetime up to 9 times) even in the presence of demanding applications.
Forward Correction and Fountain Codes in Delay-Tolerant Networks

Delay-tolerant ad hoc networks leverage the mobility of relay nodes to compensate for lack of permanent connectivity and thus enable communication between nodes that are out of range of each other. To decrease delivery delay, the information to be delivered is replicated in the network. Our objective in this paper is to study a class of replication mechanisms that include coding in order to improve the probability of successful delivery within a given time limit. We propose an analytical approach that allows to quantify tradeoffs between resources and performance measures (energy and delay). We study the effect of coding on the performance of the network while optimizing parameters that govern routing. Our results, based on fluid approximations, are compared to simulations that validate the model.
Identifying malicious Android apps using permissions and system events

With the popularity of the Android platform, more and more hackers take the Android platform as the profitable target. Android provides a risk communication defence mechanism against malicious applications, which has been demonstrated to be ineffective. It is common to quickly identify malicious applications by permission-based analysis methods. Recently, those permission-based methods are becoming useless when more and more applications request dangerous permissions. The proposed approaches are based on the key insight that the difference in the components trigger model in malware applications and benign applications. The malwares are interested in monitoring system broadcast to activate malicious components and request more permissions. The benign applications are preferable to receive self-define broadcast to activate their components and ask fewer permissions. Existing permission-based Android malware check methods can identify nearly 81% malware samples, but they also identify many normal applications as malware. In this paper, we extend the permission-based approach and employ machine learning approaches to identify the malicious applications. We use the datasets of the Market 2011, Market 2012, Market 2013 and Malware to evaluate the proposed methods. The experimental results illustrate the effectiveness of our proposal.
Renal function in rheumatoid arthritis patients treated with methotrexate and infliximab.

OBJECTIVE This study was aimed at monitoring the early and late effects of infliximab on renal proximal function in RA patients treated with methotrexate. N-acetyl-3-D-glucosaminidase (NAG) activity in urine served as an indicator of proximal tubular damage METHODS NAG activity was estimated in 21 patients during the course of treatment with infliximab and methotrexate. In every patient NAG-enzymuria was estimated directly before and 60 min after infliximab infusions and 62 weeks after starting the therapy. RESULTS The total of mean NAG activities observed before each infusion of infliximab was significantly lower (p < 0.02) than NAG-enzymuria before the start of infliximab treatment (7.4 UI/g vs 11.8 UI/g). The proportion of patients in whom NAG activity rose by more than 50% during treatment ranged from 5.3% to 25%. Administration of infliximab did not significantly change the mean serum creatinine levels or creatinine clearance. No significant differences were observed in the mean values of NAG values before and 60 min after infliximab infusion. Patients who demonstrated elevated NAG activities during the course of the whole treatment demonstrated significantly more pronounced NAG enzymuria before treatment and one hour after the first infusion (p < 0.0005), as well as higher RA activity (p < 0.05). There was no observed influence of NSAIDs or prednisone on the frequency of elevated NAG activities. Raised creatinine concentrations (> 1.3 mg/dL) were noted before and during the course of infliximab treatment in 3 patients. In 16 patients abdominal fat aspiration biopsy was performed and in 3 the presence of amyloid deposits was demonstrated. In these patients NAG activity exceeded twice the upper normal limit. CONCLUSION The introduction of infliximab during methotrexate therapy demonstrated no early or delayed nephrotoxicity of the drug in patients with rheumatoid arthritis.
A log NH I = 22.6 Damped Lyα Absorber in a Dark Gamma-Ray Burst: The Environment of GRB 050401

The optical afterglow spectrum of GRB 050401 (at z = 2.8992 ± 0.0004) shows the presence of a damped Lyα absorber (DLA), with log N = 22.6 ± 0.3. This is the highest column density ever observed in a DLA and is about 5 times larger than the strongest DLA detected so far in any QSO spectrum. From the optical spectrum, we also find a very large Zn column density, implying an abundance of [Zn/H] = -1.0 ± 0.4. These large columns are supported by the early X-ray spectrum from Swift XRT, which shows a column density (in excess of Galactic) of log NH = 22.21 assuming solar abundances (at z = 2.9). The comparison of this X-ray column density, which is dominated by absorption due to α-chain elements, and the H I column density derived from the Lyα absorption line allows us to derive a metallicity for the absorbing matter of [α/H] = -0.4 ± 0.3. The optical spectrum is reddened and can be well reproduced with a power law with SMC extinction, where AV = 0.62 ± 0.06. But the total optical extinction can also be constrained independent of the shape of the extinction curve: from the optical to X-ray spectral energy distribution, we find 0.5 ≲ AV ≲ 4.5. However, even this upper limit, independent of the shape of the extinction curve, is still well below the dust column that is inferred from the X-ray column density, i.e., AV = 9.1. This discrepancy might be explained by a small dust content with high metallicity (low dust-to-metals ratio). "Gray" extinction cannot explain the discrepancy, since we are comparing the metallicity to a measurement of the total extinction (without reference to the reddening). Little dust with high metallicity may be produced by sublimation of dust grains or may naturally exist in systems younger than a few hundred megayears.
An Efficient Feature Extraction Method for Classification of Image Spam Using Artificial Neural Networks

The widespread use of the internet has lead to enormous benefits to the internet users. However the use of one type of these facilities, the email system, has been highly damaged by the uncontrolled flooding of unwanted commercial messages, so called spam. Image spamming is a new kind of method of email spamming in which the text is embedded in image or picture files. Identifying and preventing spam is one of the top challenges in the internet world. The back propagation neural network is an effective classification method for solving feature extraction problems. In this paper we present an experimental system for the classification of image spam by considering single image feature, color histogram. The experimental result shows the performance of the proposed system and it achieves best results with minimum false positive.
Thermoplastics and Thermoplastic Composites: Technical Information for Plastics Users

1. Plastics compared to conventional materials 2. The Plastics Industry: Economic Overview 3. Basic Criteria for the Selection of Thermoplastics 4. Detailed Accounts of Thermoplastic Resins 5. Thermoplastic Processing 6. Thermoplastic Composites 7. Future Prospects for Thermoplastics and their Composites
Using Simple Recurrent Networks to Learn Fixed-Length Representations of Variable-Length Strings

Four connectionist models are reported that learn static representations of variable-length strings using a novel autosequencer architecture. These representations were learned as plans for a simple recurrent network to regenerate a given input sequence. Results showed that the autosequencer can be used to address the dispersion problem because the positions and identities of letters in a string were integrated over learning into the plan representations. Results also revealed a moderate degree of componentiality in the plan representations. Linguistic structures vary in length. Paragraphs contain varying numbers of sentences, sentences contain varyi ng numbers of words, and words contain varying numbers of letters and sounds. By contrast, standard connectionist mechanisms are designed to compute fixed-length vectors. In connectionist models of human language processing, variable-length structures have been most commonly processed using simple recurrent networks (Elman, 1990; Jordan, 1986) Perhaps the most well-known usage of SRNs is to learn the transitional probabilities in a grammar (Christia nsen et al., 1998; Cleeremans et al., 1989). The SRN is given a sequence of inputs, and it is trained to predict the next input on the basis of the current and previous inputs. Given this task, the fixed-length hidden representations learn to hold just enough information about the variable length sequence of past inputs in order to best predict the next input. However, the hidden representations are not pressured to hold enough information such that they could be used to reproduce the past N inputs in order. Two other common usages of SRNs are 1) to map static, fixed-length inputs onto variable-length outputs, or 2) to map variable-length inputs onto static, fixed-length outputs. As an example of the former, Dell and his colleagues (Dell et al., 1993) built an SRN model of phonological encoding in which a fixed-length representation of a word lemma or word form served as a “plan” representation to generate a variable-length sequence phonological features. As an example of the latter, Plaut and Kello (1999) built a model of phonological development in which variable-length sequences of phonetic features were mapped onto fixedlength semantic representations. In both of these exam ples (and all such previous work), the static representations were engineered by the modelers.
Single tracking location acoustic radiation force impulse viscoelasticity estimation (STL-VE): A method for measuring tissue viscoelastic parameters

Single tracking location (STL) shear wave elasticity imaging (SWEI) is a method for detecting elastic differences between tissues. It has the advantage of intrinsic speckle bias suppression compared with multiple tracking location variants of SWEI. However, the assumption of a linear model leads to an overestimation of the shear modulus in viscoelastic media. A new reconstruction technique denoted single tracking location viscosity estimation (STL-VE) is introduced to correct for this overestimation. This technique utilizes the same raw data generated in STL-SWEI imaging. Here, the STL-VE technique is developed by way of a maximum likelihood estimation for general viscoelastic materials. The method is then implemented for the particular case of the Kelvin-Voigt Model. Using simulation data, the STL-VE technique is demonstrated and the performance of the estimator is characterized. Finally, the STL-VE method is used to estimate the viscoelastic parameters of ex vivo bovine liver. We find good agreement between the STL-VE results and the simulation parameters as well as between the liver shear wave data and the modeled data fit.
Doppler spread estimation for mobile OFDM systems in Rayleigh fading channels

In this paper, a technique based on the autocorrelation function is proposed to estimate the Doppler spread in Rayleigh fading channels for mobile OFDM systems. It is simply implemented with the cyclic structure of OFDM symbols, and any other additive data and pilots need not to be inserted into the common OFDM symbols. This algorithm can be applied directly to the OFDM system with transmit diversity (TD) and to MIMO OFDM systems. Computer simulation results are included to support our developments in the terms of mean estimation value and mean square error.
A broadband resonant cavity antenna using a metamaterial based on double-side identical arrays

This paper presents the design of a broadband resonant cavity antenna (RCA) over the X-band region. A broad radiation bandwidth is obtained with a novel low-profile superstrate using a two-layer metamaterial. The proposed metamaterial superstrate configuration consists of cladding identical patch arrays on a double-side FR4 slab. The metamatereial effect is associated with the transmission resonance. The superstrate interacts with the wideband patch based feed source. The characteristics of the radiation and impedance are focused in order to enhance the antenna performance. The responses as the design parameters of the cavity configuration are studied. The simulation shows good results of antenna radiation with enhanced directivity with a wide band and a flat ripple. The 1-dB radiation bandwidth is 50% and the maximum directivity is 13.5 dBi at the middle frequency of 10 GHz. Also, the impedance bandwidth is as large as 50%.
Southern analysis reveals a large deletion at the hypoxanthine phosphoribosyltransferase locus in a patient with Lesch‐Nyhan syndrome

Whole genomic hprt clones were used in Southern analysis to screen the integrity of the hprt gene in a family that includes a patient with HPRT enzyme deficiency causal to Lesch‐Nyhan syndrome. A 5 kb DNA sequence deletion was found to have its endpoints in the first and third introns. The probes identified the carrier status of female family members, aided by an RFLP carried by the mother's normal X‐chromosome.
Surviving the Bottleneck: Transmission Mutants and the Evolution of Microbial Populations

The ability of microbial populations to increase fitness through fixation of mutants with an increased growth rate has been well described. In experimental studies, this is often the only way fitness can be increased. In natural settings, however, fitness can also be improved by increasing the ability of the microbe to transmit from one host to the next. For many pathogens, transmission includes a phase outside the host during which they need to survive before the chance of reinfecting a new host occurs. In such a situation, a reduced death rate during this phase will lead to improved fitness. Here, we compute the fixation probability of mutants that better survive the transmission bottleneck during the evolution of microbial populations. We derive analytical results that show that transmission mutants are often likely to occur and that their importance relative to growth mutants increases as the population decline during the transmission phase increases. We confirm our theoretical results with numerical simulations and suggest specific experiments that can be done to test our predictions.
A New Bigram-PLSA Language Model for Speech Recognition

A novel method for combining bigram model and Probabilistic Latent Semantic Analysis (PLSA) is introduced for language modeling. The motivation behind this idea is the relaxation of the "bag of words" assumption fundamentally present in latent topic models including the PLSA model. An EM-based parameter estimation technique for the proposed model is presented in this paper. Previous attempts to incorporate word order in the PLSA model are surveyed and compared with our new proposed model both in theory and by experimental evaluation. Perplexity measure is employed to compare the effectiveness of recently introduced models with the new proposed model. Furthermore, experiments are designed and carried out on continuous speech recognition (CSR) tasks using word error rate (WER) as the evaluation criterion. The superiority of the new bigram-PLSA model over Nie et al.'s bigram-PLSA and simple PLSA models is demonstrated in the results of our experiments. Experiments on BLLIP WSJ corpus show about 12% reduction in perplexity and 2.8% WER improvement compared to Nie et al.'s bigram-PLSA model.