Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-Agent System using Semantic Metadata for the Cooperation among Multiple Information Sources

We propose an agent architecture that enables actual cooperation among a set of autonomous and heterogeneous information sources. An object oriented descriptive layer is defined to insure an homogeneous view of the local accessible data. To preserve local autonomy and the architecture scalability, the descriptive layer is composed of two metadata object types : Data Descriptive Objects (DDO) represent the structural (data model) and terminological dimensions of local data whereas Semantic Links Objects implement various semantic relations among the DDO. Thus, a global object oriented semantic knowledge base is obtained and distributed to Agents involved in a cooperation protocol dedicated to global queries treatment. Conflict resolution and completeness of the answer are processed during a negotiation phase in the multi-agent protocol.
PARSEC3.0: A Multicore Benchmark Suite with Network Stacks and SPLASH-2X

Benchmarks play a very important role in accelerating the development and research of CMP. As one of them, the PARSEC suite continues to be updated and revised over and over again so that it can offer better support for researchers. The former versions of PARSEC have enough workloads to evaluate the property of CMP about CPU, cache and memory, but it lacks of applications based on network stack to assess the performance of CMPs in respect of network. In this work, we introduce PARSEC3.0, a new version of PARSEC suite that implements a user-level network stack and generates three network workloads with this stack to cover network domain. We explore the input sets of splash-2 and expand them to multiple scales, a.k. a, splash-2x. We integrate splash-2 and splash-2x into PARSEC framework so that researchers use these benchmark suite conveniently. Finally, we evaluate the u-TCP/IP stack and new network workloads, and analyze the characterizes of splash-2 and splash-2x
Physical-Layer Network Coding Aided Two-Way Relay for Transmitted-Reference UWB Networks

A physical-layer network coding (PNC) aided twoway relay scheme is proposed for Transmitted-Reference (TR) UWB networks. In particular, a novel noncoherent UWB-PNC detector is investigated for the TR UWB networks. Inheriting the simplicity of the TR-UWB receiver, the proposed PNC detector is based on the autocorrelation receiver (AcR) with simple structure, which effectively suppresses the multi-user interference and harvests the multipath energy. Equipped with the proposed TR UWB-PNC detector, the relay node first detects the bitwise XORed symbol directly from the overlapped information bearing waveforms transmitted from the source nodes, then broadcasts the estimate of the XORed symbol to achieve efficient two-way relay. Simulation results show that, compared with the non-relay, one-way relay and two-way relay with time division multiple access (TDMA) and network coded broadcasting (NCBC), the proposed PNC aided two-way scheme significantly improves both the energy and spectral efficiencies of the TR-UWB networks.
A numerical study of the effect of operating parameters on drop formation in a squeeze mode inkjet device

This study aims to investigate the ink droplet formation process of a squeeze mode piezoelectric printhead after an electrical pulse is applied by numerical analysis. The ink flow channel is modelled as a straight circular pipe ending in a convergent nozzle. The three-dimensional simulation system is based on the solution algorithm scheme for the solution of the governing equations of the flow field, and a volume-of-fluid method to predict the fluid interfaces is presented. The surface tension is modelled using a continuum surface force concept and thus computed as a function of the interfacial curvature. The pressure at the nozzle inlet, which is related to the applied voltage imposed on the simulation system, is determined by the propagation theory of acoustic waves. The effects of a pressure wave and cavity length on the droplet ejection process are presented.
Signaling Pathways Underlying Muscarinic Receptor-induced [Ca2+] i Oscillations in HEK293 Cells*

We have investigated the signaling pathways underlying muscarinic receptor-induced calcium oscillations in human embryonic kidney (HEK293) cells. Activation of muscarinic receptors with a maximal concentration of carbachol (100 μm) induced a biphasic rise in cytoplasmic calcium ([Ca2+] i ) comprised of release of Ca2+ from intracellular stores and influx of Ca2+ from the extracellular space. A lower concentration of carbachol (5 μm) induced repetitive [Ca2+] i spikes or oscillations, the continuation of which was dependent on extracellular Ca2+. The entry of Ca2+ with 100 μm carbachol and with the sarcoplasmic-endoplasmic reticulum calcium ATPase inhibitor, thapsigargin, was completely blocked by 1 μmGd3+, as well as 30–100 μm concentrations of the membrane-permeant inositol 1,4,5-trisphosphate receptor inhibitor, 2-aminoethyoxydiphenyl borane (2-APB). Sensitivity to these inhibitors is indicative of capacitative calcium entry. Arachidonic acid, a candidate signal for Ca2+ entry associated with [Ca2+] i oscillations in HEK293 cells, induced entry that was inhibited only by much higher concentrations of Gd3+ and was unaffected by 100 μm 2-APB. Like arachidonic acid-induced entry, the entry associated with [Ca2+] i oscillations was insensitive to inhibition by Gd3+ but was completely blocked by 100 μm 2-APB. These findings indicate that the signaling pathway responsible for the Ca2+ entry driving [Ca2+] i oscillations in HEK293 cells is more complex than originally thought, and may involve neither capacitative calcium entry nor a role for PLA2 and arachidonic acid.
Effect of CYP2C19*2 and *3 Loss-of-Function Alleles on Platelet Reactivity and Adverse Clinical Events in East Asian Acute Myocardial Infarction Survivors Treated With Clopidogrel and Aspirin

Background— As compared with whites, East Asians more often carry the cytochrome P450 (CYP) 2C19 loss-of-function (LOF) allele with the CYP2C19*3 variant. The influence of the CYP2C19 LOF alleles (*2 and *3) on clopidogrel response and clinical outcomes in East Asians with acute myocardial infarction (AMI) has not been reported. We sought to evaluate the effect of the CYP2C19 variants on clopidogrel pharmacodynamics and long-term prognosis in these patients. Methods and Results— Patients who survived an AMI (n=266) were enrolled in a single-center registry. Predischarge platelet reactivity was assessed with light transmittance aggregometry and the VerifyNow P2Y12 assay; the CYP2C19*2, *3, *17 and ABCB1 3435C>T variants were determined. The primary clinical end point was the composite of cardiovascular death, nonfatal MI, and ischemic stroke. The median exposure to clopidogrel was 21 months (interquartile range, 13–29). The ABCB1 3435C>T was not related to clopidogrel response or cardiovascular events. Carriage of the CYP2C19 LOF variant allele was relatively high (60.9%, n=162; *2/*17=2, *3/*17=1, *1/*2=96, *1/*3=29, *2/*2=20, and *2/*3=14). Platelet reactivity increased proportionally according to the number of the CYP2C19 LOF alleles. In a multivariate regression analysis, the risk of high on-treatment platelet reactivity (HPR) increased depending on the number of CYP2C19 LOF allele [1 LOF allele; odds ratio (OR), 1.8; 95% confidence interval (CI), 0.8 to 4.2, P=0.152; and 2 LOF alleles; OR, 2.8; 95% CI, 1.2 to 6.5; P=0.016]; platelet reactivity and the rate of HPR did not differ between the CYP2C19*2 versus *3 allele carriage. In addition, cardiovascular event occurrence increased according to the number of the CYP2C19 LOF allele; compared with noncarriers, carriers of 1 [hazard ratio (HR), 3.1; 95% CI, 0.8 to 11.6; P=0.089] and 2 CYP2C19 LOF allele(s) (HR, 10.1; 95% CI, 1.8–58.8; P=0.008) were associated with clinical end point. The clinical impact of the CYP2C19*2 versus *3 allele carriage also did not differ. Conclusions— Among East Asian patients who survived an AMI, the CYP2C19 LOF allele carriage appears to affect clopidogrel pharmacodynamics and cardiovascular events according to the number of the CYP2C19 LOF allele; the influence of the CYP2C19*2 and *3 alleles on clopidogrel response and long-term outcomes does not differ.
Joint Classifier and Feature Optimization for Comprehensive Cancer Diagnosis Using Gene Expression Data

Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression profile of a tissue of unknown cancer status to a database of stored expression profiles from tissues of known cancer status. This paper introduces the JCFO, a novel algorithm that uses a sparse Bayesian approach to jointly identify both the optimal nonlinear classifier for diagnosis and the optimal set of genes on which to base that diagnosis. We show that the diagnostic classification accuracy of the proposed algorithm is superior to a number of current state-of-the-art methods in a full leave-one-out cross-validation study of five widely used benchmark datasets. In addition to its superior classification accuracy, the algorithm is designed to automatically identify a small subset of genes (typically around twenty in our experiments) that are capable of providing complete discriminatory information for diagnosis. Focusing attention on a small subset of genes is useful not only because it produces a classifier with good generalization capacity, but also because this set of genes may provide insights into the mechanisms responsible for the disease itself. A number of the genes identified by the JCFO in our experiments are already in use as clinical markers for cancer diagnosis; some of the remaining genes may be excellent candidates for further clinical investigation. If it is possible to identify a small set of genes that is indeed capable of providing complete discrimination, inexpensive diagnostic assays might be widely deployable in clinical settings.
Flexible Electronics: Fast Fabrication of Flexible Functional Circuits Based on Liquid Metal Dual-Trans Printing (Adv. Mater. 44/2015).

A dual-trans method to print a functional liquid-metal circuit on poly(vinyl chloride) (PVC) film and then transfer it to a poly(dimethylsiloxane) PDMS substrate, which can be conformably molded to any irregular shape, is illustrated by J. Liu and co-workers on page 7109. As examples, a programmable soft electronic band and a wearable temperature-sensing module that can wirelessly communicate with a mobile phone are demonstrated.
Reliability demonstration testing method for embedded operating systems

The reliability target is becoming higher and higher for modern embedded operating systems with their being extensively used in safety-critical situations. In order to solve the problem that the fixed duration testing method, which was based on the classical statistics, can't satisfy the requirements of reliability demonstration testing for modern embedded operating systems due to the long testing duration, a new method based on the empirical Bayesian inference is presented. Firstly, the prior distribution of the embedded operating system failure intensity is derived on the basis of analyzing the testing records of reliability growth testing phase. Then, the reliability demonstration testing duration can be calculated by the prior distribution. Finally, the prior knowledge dynamic integrating approach taking both the specific testing information and the prior knowledge into account is developed. Experiment shows that the method introduced above can reduce the testing duration effectively without decreasing the confidence level in the testing results.
Dictyostelium Differentiation-inducing Factor-3 Activates Glycogen Synthase Kinase-3β and Degrades Cyclin D1 in Mammalian Cells*

In search of chemical substances applicable for the treatment of cancer and other proliferative disorders, we studied the signal transduction of Dictyosteliumdifferentiation-inducing factors (DIFs) in mammalian cells mainly using HeLa cells. Although DIF-1 and DIF-3 both strongly inhibited cell proliferation by inducing G0/G1 arrest, DIF-3 was more effective than DIF-1. DIF-3 suppressed cyclin D1 expression at both mRNA and protein levels, whereas the overexpression of cyclin D1 overrode DIF-3-induced cell cycle arrest. The DIF-3-induced decrease in the amount of cyclin D1 protein preceded the reduction in the level of cyclin D1 mRNA. The decrease in cyclin D1 protein seemed to be caused by accelerated proteolysis, since it was abrogated byN-acetyl-Leu-Leu-norleucinal, a proteasome inhibitor. DIF-3-induced degradation of cyclin D1 was also prevented by treatment with lithium chloride, an inhibitor of glycogen synthase kinase-3β (GSK-3β), suggesting that DIF-3 induced cyclin D1 proteolysis through the activation of GSK-3β. Indeed, DIF-3 dephosphorylated Ser9 and phosphorylated tyrosine on GSK-3β, and it stimulated GSK-3β activity in an in vitro kinase assay. Moreover, DIF-3 was revealed to induce the nuclear translocation of GSK-3β by immunofluorescent microscopy and immunoblotting of subcellular protein fractions. These results suggested that DIF-3 activates GSK-3β to accelerate the proteolysis of cyclin D1 and that this mechanism is involved in the DIF-3-induced G0/G1 arrest in mammalian cells.
Adapting the hybrid data dissemination protocol to density by dynamically controlling the broadcast zone radius

Environment densities change both frequently and rapidly in VANETs. In this paper, we enhance our protocol to become adaptable to density such that as a car moves from one environment density to another, the protocol dynamically sets the broadcast zone radius to adjust to the new density. We study the effect of network density against a range of broadcast zone radius values and obtain a weighted performance metric for each combination. Using this data, we identify the optimal broadcast zone radius per density. We plot these optimal values against the densities values (lambda) known to each of the nodes in the network to obtain the formula we use to determine the broadcast zone radius.
The virtual speech community: social network and language variation on IRC

Many scholars anticipate that online interaction will have a long-term effect on the evolution of language, but little linguistic research yet addresses this question directly. In sociolinguistics, social network relations are recognized as the principal vehicle of language change. In this paper, I develop a social network approach to online language variation and change through qualitative and quantitative analysis of log files of Internet Relay Chat (IRC) interaction. The analysis reveals a highly structured relationship between participants' social positions on a channel and the linguistic variants they use. The emerging sociolinguistic relationship is more complex than what is predicted by current sociolinguistic theory for offline interaction, suggesting that sociolinguistic investigation of online interaction, where more detailed and fine-grained information about social contacts can be obtained, may offer unique contributions to the study of language variation and change.
Homology Modeling of Nitrogenase Iron Protein of Nitrogen Fixing Actinomycete Arthrobacter sp

Nitrogenase is an important enzyme associated with nitrogen fixation. Nitrogenase iron protein (Nif H) is one of the vital genes contributing to the nitrogen fixation. Arthrobacter sp. is one of the actinomycetes fixing atmospheric nitrogen. Nitrogenase iron protein of Arthrobacter sp. was retrieved from NCBI in FASTA format and a good template was selected by Basic Local Alignment Search tool and it was found to be Azotobacter vinelandii. The modeling of 3D structure of the protein was performed by Swiss model, GENO3D and ModWeb. The modeled 3D structure was evaluated by ProSA, VERIFY3D, PROCHECK, PROVE and ERRAT. The nitrogenase iron protein 3D structure modeled by ModWeb was found to be the best reliable model based on the above mentioned evaluation. The structural dynamics were performed by WEBnm@ and elNemo.3D structure of the nitrogenase iron protein was visualized by Rasmol.
Right parietal cortex mediates recognition memory for melodies

Functional brain imaging studies have highlighted the significance of right‐lateralized temporal, frontal and parietal brain areas for memory for melodies. The present study investigated the involvement of bilateral posterior parietal cortices (PPCs) for the recognition memory of melodies using transcranial direct current stimulation (tDCS). Participants performed a recognition task before and after tDCS. The task included an encoding phase (12 melodies), a retention period, as well as a recognition phase (24 melodies). Experiment 1 revealed that anodal tDCS over the right PPC led to a deterioration of overall memory performance compared with sham. Experiment 2 confirmed the results of Experiment 1 and further showed that anodal tDCS over the left PPC did not show a modulatory effect on memory task performance, indicating a right lateralization for musical memory. Furthermore, both experiments revealed that the decline in memory for melodies can be traced back to an interference of anodal stimulation on the recollection process (remember judgements) rather than to familiarity judgements. Taken together, this study revealed a causal involvement of the right PPC for memory for melodies and demonstrated a key role for this brain region in the recollection process of the memory task.
Using Existing Reconfigurable Logic in 3D Die Stacks for Test

We propose an architecture for an FPGA-based tester for a 3D stacked IC. Our design exploits the underlying structure of the FPGA, allowing it to be used to efficiently store and apply predefined test patterns at a high bandwidth, reducing the FPGA resources required and often reducing scan shift toggling. The proposed approach and its advantages can generally also be applied to 2.5D multi-die circuits containing FPGAs.
Control of Non-Solid Diffusers by Electrostatic Charging

The form factors of displays using fog or water surface are limited by our ability to control the non-solid substances used as the diffuser. We propose a charging technique for polar aerosols (e.g., mist or fog) that allows control of the shape and trajectory of such non-solid diffusers using electric fields. We report experiments that allowed us to design a charging mechanism that produces charged fog aerosols with homogeneous electrical mobility. We illustrate our idea by demonstrating how electric fields can be used to control the shape of a fog display and the trajectory of a bubble display.
Propylene polymerization in a circulating slugging fluidized bed reactor

The work presented in this thesis is concerned with research on the riser of a circulating fluidized bed system for olefin polymerization. In the riser section, fluidization takes place in the transporting slugging mode and polymer particles are produced in the riser in a non-isothermal way. Properties of the polymerization reaction and of the hydrodynamics were studied and their behavior with respect to conditions in the reactor were described. A reactor model was constructed that accurately describes the polymerization process in the circulating slugging fluidized bed. Elements in the reactor model are fluidization, heat transfer and kinetics of the used catalyst system. For heat transfer relations from the open literature are taken. Sorption of monomer into the polypropylene is not considered in the reactor model.
A HYBRID GA/PSO TO EVOLVE ARTIFICIAL RECURRENT NEURAL NETWORKS

In this paper we propose a novel hybrid algorithm (GA/PSO) combining the strengths of particle swarm optimization with genetic algorithms to evolve the weights of recurrent neural networks. Particle swarm optimization and genetic algorithms are two optimization techniques that have proven to be successful in solving difficult problems, in particular both can successfully evolve recurrent neural networks. The hybrid algorithm combines the standard velocity and update rules of PSOs with the ideas of selection and crossover from GAs. We compare the hybrid algorithm to both the standard GA and PSO models, when evolving weights to two recurrent neural network problems. This paper presents results using the new hybrid algorithm and describes the hybrids benefits. INTRODUCTION Genetic algorithms (GA) and particles swarm optimization (PSO) are both population based algorithms that have proven to be successful in solving very difficult problems, including recurrent artificial neural networks (RANN). However, both models have strengths and weaknesses. Comparisons between GA and PSOs have been performed by both Eberhart (1998) and Angeline (1998) and both conclude that a hybrid of the standard GA and PSO models could lead to further advances. In this paper we present a novel hybrid algorithm, combining the strengths of GAs with those of PSO. The hybrid algorithm is compared to the standard GA and PSO models in evolving the weights of two RANN problems. Traditional neural network (NN) training algorithms, such as back propagation, are based on gradient descent. They systematically and incrementally reduce the output error. Although gradient descent approaches are very effective for a wide range of problems, they suffer from two significant drawbacks. First, they are generally restricted to finding local minimum. Second, they may get stuck in flat regions of a search space. In such cases the typical recourse is to restart the algorithm from a new random location. In contrast, population based searches are not restricted to a local search and can easily move across flat regions. However, they tend to be slower than gradient 1 This work is supported by NSF EPSCoR EPS-0132626. The experiments were performed on a Beowulf cluster built with funds from NSF grant EPS-80935 and a generous hardware donation form Micron Technologies.
Long‐memory dynamic Tobit models

We introduce a long-memory dynamic Tobit model, defining it as a censored version of a fractionally integrated Gaussian ARMA model, which may include seasonal components and|or additional regression variables. Parameter estimation for such a model using standard techniques is typically infeasible, since the model is not Markovian, cannot be expressed in a finite-dimensional state-space form, and includes censored observations. Furthermore, the long-memory property renders a standard Gibbs sampling scheme impractical. Therefore we introduce a new Markov chain Monte Carlo sampling scheme, which is orders of magnitude more efficient than the standard Gibbs sampler. The method is inherently capable of handling missing observations. In case studies, the model is fit to two time series: one consisting of volumes of requests to a hard disk over time, and the other consisting of hourly rainfall measurements in Edinburgh over a 2-year period. The resulting posterior distributions for the fractional differencing parameter demonstrate, for these two time series, the importance of the long-memory structure in the models. Copyright © 2006 John Wiley & Sons, Ltd.
Computer prediction of location of heat centres in castings

AbstractComputer software, to aid the feeding of metal castings by identifying relative rates of solidification, has been developed. The algorithms within the software are based on the traditional modulus concept but have been refined so that detailed information on relative cooling rates in any chosen section within a cast shape may be obtained. The software has been validated by referring its output to well known cases and to aluminium castings of three different shapes. The major shrinkage cavities in the castings were found to be in the positions predicted using the software.MST/1791