Miracle-dz/UniFAR-FTUs huggingface dataset:
Cluster-based logic blocks for FPGAs: area-efficiency vs. input sharing and size

While modern FPGAs often contain clusters of 4-input lookup tables and flip flops, little is known about good choices for two key architectural parameters: the number of these basic logic elements (BLEs) in each cluster, and the total number of distinct inputs that the programmable routing can provide to each cluster. In this paper we explore the effect of these parameters on FPGA area-efficiency. We show that a cluster containing N BLEs needs only 2N+2 distinct inputs (vs. the 4N maximum) to achieve complete logic utilization. Secondly, we find that a cluster size of 4 is most area-efficient, and leads to an FPGA that is 5-10% more area-efficient than an FPGA based on a single BLE logic block.
Computing the Field in Proteins and Channels

This is an early but comprehensive review of the PNP Poisson Nernst Planck theory of ion channels. Extensive reference is made to the earlier literature. The starting place for this theory of open channels is a theory of electrodiffusion rather like that used previously to describe membranes. The theory uses Poisson's equation to describe how charge on ions and the channel protein creates electrical potential; it uses the Nernst-Planck equations to describe migration and diffusion of ions in gradients of concentration and electrical potential. Combined, these are also the "drift-diffusion equations" of solid state physics, which are widely, if not universally used to describe the flow of current and the behavior of semiconductors.
On the Stability of a N-class Aloha Network

Necessary and sufficient conditions are established for the stability of a high-mobility N-class Aloha network, where the position of the sources follows a Poisson point process, each source has an infinity capacity buffer, packets arrive according to a Bernoulli distribution and the link distance between source and destination follows a Rayleigh distribution. It is also derived simple formulas for the stationary packet success probability and mean delay.
Seasonal confounding in air pollution and health time‐series studies: effect on air pollution effect estimates

A major statistical challenge in air pollution and health time‐series studies is to adequately control for confounding effects of time‐varying covariates. Daily health outcome counts are most commonly analysed by Poisson regression models, adjusted for overdispersion, with air pollution levels included as a linear predictor and smooth functions for calendar time and weather variables to adjust for time‐varying confounders. Various smoothers have been used so far, but the optimal strategy for choosing smoothers and their degree of smoothing remains controversial. In this work, we evaluate the performance of various smoothers with different criteria for choosing the degree of smoothing in terms of bias and efficiency of the air pollution effect estimate in a simulation study. The evaluated approaches were also applied to real mortality data from 22 European cities. The simulation study imitated a multi‐city study. Data were generated from a fully parametric model. Model selection methods which optimize prediction may lead to increased biases in the air pollution effect estimate. Minimization of the absolute value of the sum of the partial autocorrelation function of the model's residuals (PACF), as a criterion to choose the degree of smoothness, gave the smallest biases. The penalized splines (PS) method with a large number of effective dfs (e.g. 8–12 per year) could be used as the basic, relatively conservative, analysis whereas the PS and natural splines in combination with PACF could be applied to provide a reasonable range of the effect estimate. Copyright © 2006 John Wiley & Sons, Ltd.
Green synthesis of silver nanoparticles using Prosopis juliflora bark extract: reaction optimization, antimicrobial and catalytic activities

Abstract In the present study, silver nanoparticles (PJB-AgNPs) have been biosynthesized employing Prosopis juliflora bark extract. The biosynthesis of silver nanoparticles was monitored on UV-vis spectrophotometer. The size, charge and polydispersity index (PDI) of PJB-AgNPs were determined using dynamic light scattering (DLS). Different parameters dictating the size of PJB-AgNPs were explored. Nanoparticles biosynthesis optimization studies suggested efficient synthesis of highly dispersed PJB-AgNPs at 25 °C when 9.5 ml of 1 mM AgNO3 was reduced with 0.5 ml of bark extract for 40 min. Characterization of PJB-AgNPs by SEM showed spherical-shaped nanoparticles with a size range ∼10–50 nm along with a hydrodynamic diameter of ∼55 nm as evaluated by DLS. Further, characterizations were done by FTIR and EDS to evaluate the functional groups and purity of PJB-AgNPs. The antibacterial potential of PJB-AgNPs was tested against E. coli and P. aeruginosa. The PJB-AgNPs remarkably exhibited anticancer activity against A549 cell line as evidenced by Alamar blue assay. The dye degradation activity was also evaluated against 4-nitrophenol that has carcinogenic effect. The results thus obtained suggest application of PJB-AgNPs as antimicrobial, anticancer and catalytic agents.
JEP-TALN 2004 - session on Arabic Language Processing A Review of Arabic Corpus Analysis Tools Un Examen d'Outils pour l'Analyse de Corpus Arabes

Dans ce papier nous presentons une vue d'ensemble critique d'outils disponibles pour l'analyse de corpus arabes, en nous concentrant sur la concordance (Monoconc : Barlow 2003), l’analyse morphologique et le marquage des categories grammaticales (Shaalan 1989, Ahmed 2000, Khoja 2001, Freeman 2001, Beesley 2001, Berri Zidoum et Atif 2001, Buckwalter 2002, Maamouri et Cieri 2002, Sakhr 2003, Darwish 2003), sur les dictionnaires sous forme exploitable par un ordinateur (Ajeeb 2003) et les outils de visualisation de corpus (Abu Shawar 2004). Nous suggerons qu'une etape essentielle pour les membres de la communaute de recherche d'analyse morphologique arabe devraient se mettre d’accord sur un objectif: choisir un corpus comme echantillon representatif de textes arabes et se mettre d’accord sur quelles annotations constituent un etalon-or, une sortie correcte decidee que des systemes devraient viser a repeter. En consequence, des systemes individuels peuvent etre evalues objectivement en mesurant leurs sorties contre un etalon-or. Le Coran est une norme possible, etant facile a trouver sous la forme de scriptes qui comprennent des signes diacritiques, que des linguistes peuvent enrichir en analyses.
Generic object recognition with local features: From bags to subspaces

We propose an alternative approach to the widely-used Bag-of-Features (BoF) for representing objects in terms of a collection of local features extracted from their images. In this new framework, called Subspaces-of-Features (SoF), first the sets of local features extracted from the images of the objects are represented as low-dimensional linear subspaces. Then the subspaces corresponding to different categories are orthogonalized, and the similarity between subspaces corresponding to different categories is calculated using the Grassmannian distances defined through the principal angles between the subspaces. The performance of SoF is illustrated on a standard generic object recognition benchmark.
Neuropsychological impairment and its neurological correlates in adult offspring with heightened risk for schizophrenia and affective psychosis.

OBJECTIVE Schizophrenia is generally considered to be a neurodevelopmental disorder reflected in findings of neuropsychological impairments and neurological abnormality in patients and their relatives. The authors investigated whether neuropsychological impairments are related to neurological abnormality and whether such deficits also characterize risk for affective psychosis. METHOD In a longitudinal study with a 93% rate of effective follow-up, the authors investigated neuropsychological impairment and its relation to neurological abnormality at a mean age of 22.3 years in 74 offspring of mothers with a history of psychotic disorders (38 offspring with heightened risk for schizophrenia and 36 with risk for affective psychosis) and 88 normal-risk offspring born to mothers with no history of psychosis. RESULTS Offspring with genetically heightened risk for schizophrenia showed significantly impaired verbal memory, selective attention, and grammatical reasoning, compared with normal-risk offspring. Having impaired verbal memory, attention, and grammatical reasoning functions identified a significantly larger subgroup (16%) among offspring with heightened risk for schizophrenia than among offspring with heightened risk for affective psychosis (0%) and among normal-risk offspring (3%). Multiple neuropsychological functions were significantly related to neurological abnormality in offspring with heightened risk for schizophrenia and in normal-risk offspring but not among offspring with heightened risk for affective psychosis. The extension of schizophrenia and affective psychosis risk groups to include additional offspring of mothers with psychosis-spectrum disorders yielded results similar to those for the core risk groups. CONCLUSIONS The neurocognitive dysfunction attending heightened risk for schizophrenia is likely based on genetically mediated neurodevelopmental factors, with schizophrenia and affective psychosis belonging to different biological spheres.
Imaging studies on the role of dopamine in cocaine reinforcement and addiction in humans

We summarize our studies with positron emission tomography investigating the role of dopamine (DA) in the reinforcing effects of cocaine and methylphenidate in humans and its involvement in cocaine addiction. These studies have shown that the rate at which cocaine and methylphenidate enter the brain and block the dopamine transporters (DAT) is the variable associated with the `high', rather than the presence per se of the drug in the brain. Our studies also show that, while the level of DAT blockade is important in predicting the intensity of the `high' induced by these drugs (DAT blockade 450% is required for these drugs to induce a `high'), the rate at which DAT are blocked determines whether the `high' is perceived or not. Thus, oral methylphenidate, which leads to slow DAT blockade, does not induce a `high', even at doses which block DAT more than 60%. In cocaine abusers, we have shown significant reductions in DA D2 receptors that are associated with decreased metabolism in cingulate gyrus and in orbitofrontal cortex. We suggest that this is one of the mechanisms by which DA disruption leads to compulsive drug administration in cocaine addiction. Cocaine abusers also show significant decreases in DA release, which coupled with the reduction in D2 receptors may result in decreased activation of reward circuits by physiological reinforcers and may perpetuate cocaine use as a means to compensate for this deficit. Thus, strategies to enhance DA brain function in ways that mimic physiological DA activity may be of help in overcoming cocaine addiction.
Database high availability using SHADOW systems

Hot standby techniques are widely used to implement highly available database systems. These techniques make use of two separate copies of the database, an active copy and a backup that is managed by the standby. The two database copies are stored independently and synchronized by the database systems that manage them. However, database systems deployed in computing clouds often have access to reliable persistent storage that can be shared by multiple servers. In this paper we consider how hot standby techniques can be improved in such settings. We present SHADOW systems, a novel approach to hot standby high availability. Like other database systems that use shared storage, SHADOW systems push the task of managing database replication out of the database system and into the underlying storage service, simplifying the database system. Unlike other systems, SHADOW systems also provide write offloading, which frees the active database system from the need to update the persistent database. Instead, that responsibility is placed on the standby system. We present the results of a performance evaluation using a SHADOW prototype on Amazon's cloud, showing that write offloading enables SHADOW to outperform traditional hot standby replication and even a standalone DBMS that does not provide high availability.
The hunt for origins of DNA replication in multicellular eukaryotes

Origins of DNA replication (ORIs) occur at defined regions in the genome. Although DNA sequence defines the position of ORIs in budding yeast, the factors for ORI specification remain elusive in metazoa. Several methods have been used recently to map ORIs in metazoan genomes with the hope that features for ORI specification might emerge. These methods are reviewed here with analysis of their advantages and shortcomings. The various factors that may influence ORI selection for initiation of DNA replication are discussed.
Achievable performance of Bayesian compressive sensing based spectrum sensing

In wideband spectrum sensing, compressive sensing approaches have been used at the receiver side to decrease the sampling rate, if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately, it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore, these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues, we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly, we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE), compression ratio and signal-to-noise ratio (SNR), and compare it with the conventionally used basis pursuit approach, (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error, and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing.
The pattern of early lung parenchymal and air space injury following acute blood loss.

UNLABELLED Acute lung injury is a frequent clinical occurrence following blood loss and trauma. The nature of this injury remains poorly understood. OBJECTIVE To examine the relative parenchymal and intra-alveolar distribution of inflammation in a rat model of hemorrhage and resuscitation. METHODS Rats were anesthetized and subjected to hemorrhage followed by resuscitation with shed blood and saline. Myeloperoxidase activity of lung homogenates and cytology of bronchoalveolar lavage fluid were used to measure total lung and intra-alveolar neutrophil invasion. Extravasation of i.v. -administered [125I]-albumin was used to determine total lung and alveolar permeability. Permeability results were analyzed using their base-10 logarithmic transformations. RESULTS 86 animals were studied. Whole-lung myeloperoxidase activity was increased (control = 0.34 +/- 0.16 units, injured = 0.84 +/- 0.43 units, p < 0.01), while there was no difference in intra-alveolar leukocyte counts (injured = 1.85 +/- 1.30 x 10(5)/mL, control = 2.44 +/- 1.75 x 10(5)/mL, p = 0.40), suggesting that the cellular component of the injury was more severe in the intravascular and interstitial spaces. There was a strong trend toward increased permeability in the interstitial compartment, and a significant increase in permeability in the intra-alveolar compartment (whole-lung permeability: control = -0.27 +/- 0.19 units, injured = 0.10 +/- 0.55 units, p = 0.06; alveolar permeability: control = -2.00 +/- 0.47 units, injured = -1.32 +/- 0.49 units, p < 0.01), suggesting that the loss of integrity to macromolecules was not limited to the interstitium. CONCLUSION Hemorrhage and resuscitation resulted in an acute lung injury characterized by extravasation of intravascular protein into both the interstitium and the intra-alveolar space. Neutrophil invasion of the lung was demonstrable only in the interstitial compartment.
Long short-term memory recurrent neural network architectures for large scale acoustic modeling

Long Short-Term Memory (LSTM) is a specific recurrent neural network (RNN) architecture that was designed to model temporal sequences and their long-range dependencies more accurately than conventional RNNs. In this paper, we explore LSTM RNN architectures for large scale acoustic modeling in speech recognition. We recently showed that LSTM RNNs are more effective than DNNs and conventional RNNs for acoustic modeling, considering moderately-sized models trained on a single machine. Here, we introduce the first distributed training of LSTM RNNs using asynchronous stochastic gradient descent optimization on a large cluster of machines. We show that a two-layer deep LSTM RNN where each LSTM layer has a linear recurrent projection layer can exceed state-of-the-art speech recognition performance. This architecture makes more effective use of model parameters than the others considered, converges quickly, and outperforms a deep feed forward neural network having an order of magnitude more parameters. Index Terms: Long Short-Term Memory, LSTM, recurrent neural network, RNN, speech recognition, acoustic modeling.
Design of Low power & Reliable Networks on Chip through joint crosstalk avoidance and forward error correction coding

With the ever-increasing degrees of integration, design of communication architectures for big systems on chip (SoCs) is a challenge. The communication requirements of these large multi processor SoCs (MP-SoCs) are convened by the emerging network-on-a-chip (NoC) paradigm. To become a viable alternative IC design methodology, the NoC paradigm must address system-level reliability issues, which are among the dominant concerns for SoC design. The basic operations of NoCs are governed by on-chip packet switched networks. On the other hand, incorporation of different coding schemes in SoC design is being investigated as a means to increase system reliability. As NoCs are built on packet-switching, it is very natural to modify the data packets by adding extra bits of coded information to protect against any transient malfunction. By incorporating joint crosstalk avoidance coding (CAC) and forward error correction (FEC) schemes in the NoC data stream we are able to enhance the system reliability and at the same time reduce communication energy
An effective approach for accurate estimation of trust of distant information sources in the semantic Web

To assess the trustworthiness of the information published in the World Wide Web referrals are often employed. This is due to the fact that most information sources are visited only occasionally by the same client, and thus, direct own experience rarely suffices. The accuracy of trust inference for unknown information sources may considerably deteriorate due to "noise" or to the intervention of malicious nodes producing and propagating untrustworthy referrals. In this paper, we describe an innovative approach for trust inference in the semantic Web and in trust networks in general, referred to as FACiLE (faith assessment combining last edges). Unlike all other approaches, FACilE infers a trust value for an information source from a proper combination of only the direct trust values of its neighbours. We evaluate the efficiency of our approach by means of a series of simulation experiments run for a wide variety of mixes of sources of untrustworthy information. FACiLE outperforms other trust-inference approach in the most interesting cases of population mixes
Non redundant data cache

Current microprocessors spend a huge percentage of the die area to implement the memory hierarchy. Moreover, cache memory is responsible for a significant percentage of the total energy consumption. This paper presents a novel data cache design to reduce its die area, power dissipation and latency. The new scheme, called Non Redundant Cache (NRC), exploits the immense amount of value replication observed in traditional data caches. The NRC cache significantly reduces the storage requirements by avoiding the replication of values. Results show that the NRC cache reduces the die area in a 32%, the power dissipation by 14% and the latency by 25%, while maintaining the miss ratio of a conventional cache.
Multiple Time Scale Analysis of a Model Belousov-Zhabotinskii Reaction

This paper discusses the dynamics of a seven dimensional model of the Belousov--Zhabotinskii (BZ) reaction. The model was proposed by Gyorgyi and Field as a system of rate equations with mass-action kinetics that reproduce the complex dynamics displayed by the BZ reaction in a stirred tank reactor. We investigate the geometric mechanisms that shape the behavior of this model and the bifurcations which occur as the flow rate of the reactor is varied. Our perspective is that of geometric singular perturbation theory, and we use recent results from this theory as a foundation for mathematical analysis of the model. In particular, we examine qualitative differences in the two families of mixed-mode oscillations observed in the model.
Middle East respiratory syndrome coronavirus: epidemic potential or a storm in a teacup?

The Middle East respiratory syndrome (MERS) is a new killer respiratory disease caused by the MERS coronavirus (CoV) first reported from the Kingdom of Saudi Arabia (KSA) in September 2012, after identification of a novel betacoronavirus from a Saudi Arabian patient who died from a severe respiratory illness [1, 2]. Retrospective study of stored samples later showed that, earlier in April 2012, a cluster of severe respiratory illness occurred in a public health hospital in Zarqa, Jordan, where eight healthcare workers (HCWs) were among the 11 people affected, with two deaths attributed to MERS-CoV [3]. The appearance of any new fatal infectious disease, and uncertainty about its origin and mode of transmission, invariably threatens global health security and its detection in western countries rapidly focuses political and scientific attention. Unfortunately, at the same time, it evokes unnecessary and unwarranted fierce scientific competition and discourse, as was illustrated by the HIV, severe acute respiratory syndrome (SARS) and avian influenza epidemics [4–8]. Disappointingly, the events surrounding the MERS-CoV have been no different [6]. MERS-CoV was first isolated, sequenced and patented by Erasmus Medical Centre (EMC) researchers in Rotterdam, the Netherlands, and initially it was named after their centre as HCoV-EMC [2]. Subsequently, international consensus led to renaming it as MERS-CoV [9]. Since the first KSA case report in September 2012, the KSA Ministry of Health (MoH) has recommended mandatory testing for MERS-CoV in all cases of respiratory illness requiring intensive care admission. 6 months after MERS-CoV was discovered, at the end of March 2013, there were only 17 MERS-CoV cases reported globally, nine of which were from KSA [10], four of these from one family case cluster [11]. This small number of MERS-CoV …