Miracle-dz/UniFAR-FTUs huggingface dataset:
SUDS : Primitive Mechanismsfor MemoryDependenceSpeculation

As VLSI chip sizesanddensitiesincrease,it becomespossibleto putmany processingelementsonasinglechipandconnecthemtogetherwith alow latency communicationnetwork. In thispaperwe proposea softwaresystem,SUDS (SoftwareUn-Do System),that leveragestheseresourcesusingspeculationto exploit parallelism in integerprogramswith many datadependences. We demonstrate thatin orderto achieveparallelspeedupsaspeculationsystemmust deliver memoryrequestlatencieslower thanabout30 cycles. We give a costbreakdown for our currentworking implementationof SUDSthathasamemoryrequestlatency thatis nearlyableto meet this goal. In addition,we identify the threeprimitive runtimeoperations that are necessaryto efficiently parallelizetheseprograms. The subsystemsinclude(1) a fastcommunicationpathfor truedependenceswithin the program,(2) a methodfor renamingvariables that have anti andoutputdependences and (3) a memorydependencespeculationmechanismto guaranteethatparallelaccesses to global datastructuresdon’t violatesequentialprogramsemantics. Wefind thatthesethreesubsystems donot interact,sothatthey can beimplementedseparately . Eachsubsystemis thensimpleenough that it canbe built in softwareusingonly minimal hardwaresupport. In this paperwe focuson thememorydependencesubsystem anddemonstratethat it canbe implementedusinga simplebut effective low-costprotocol.
Support vector machine classification of woody patches in New Zealand from synthetic aperture radar and optical data, with LiDAR training

Abstract. A light detection and ranging canopy height model (CHM) was used as training data for a segment-based classification of woody patches. The classifier is accurate (∼92%) and suitable for use at the national scale. Height thresholds and percentage cover of vegetation from the CHM were used to produce larger quantities of reliable training data compared to other, mostly point or plot-based, ground-truthing approaches. It was found that the regional-scale differentiation between woody and nonwoody vegetation might be achieved by a combination of L-band dual-polarized Phased Array type L-band synthetic aperture radar data (HV) with multispectral optical data that include a short-wave infrared band. The application of a support vector machine algorithm to these data proved successful. The versatility of these algorithms regarding the discrimination function and their ability to solve classification problems with multiple output classes were critical factors for success. The identified and classified woody patches constitute a valuable addition and enhancement of the national land cover database.
Biosynthesis of Stable Antioxidant ZnO Nanoparticles by Pseudomonas aeruginosa Rhamnolipids

During the last several years, various chemical methods have been used for synthesis of a variety of metal nanoparticles. Most of these methods pose severe environmental problems and biological risks; therefore the present study reports a biological route for synthesis of zinc oxide nanoparticles using Pseudomonas aeruginosa rhamnolipids (RLs) (denoted as RL@ZnO) and their antioxidant property. Formation of stable RL@ZnO nanoparticles gave mostly spherical particles with a particle size ranging from 35 to 80 nm. The RL@ZnO nanoparticles were characterized by UV-visible (UV–vis) spectroscopy, scanning electron microscopy, transmission electron microscopy, dynamic light scattering, Fourier transform infrared spectroscopy, X-ray diffraction (XRD), and thermal gravimetric analysis. The UV–vis spectra presented a characteristic absorbance peak at ∼360 nm for synthesized RL@ZnO nanoparticles. The XRD spectrum showed that RL@ZnO nanoparticles are crystalline in nature and have typical wurtzite type polycrystals. Antioxidant potential of RL@ZnO nanoparticles was assessed through 2,2–diphenyl-1-picrylhydrazyl (DPPH), hydroxyl, and superoxide anion free radicals with varying concentration and time of the storage up to 15 months, while it was found to decline in bare ZnO nanoparticles. Similarly, the inhibitory effects on β-carotene oxidation and lipid peroxidation were also observed. These results elucidate the significance of P. aeruginosa RL as effective stabilizing agents to develop surface protective ZnO nanoparticles, which can be used as promising antioxidants in biological system.
On-line storage management with distributed decision making for content-centric networks

Content traffic proliferation in Internet makes more dire than ever the development of radical new network architectures, where information will be addressed by semantic attributes rather than the origin and destination identities. In this direction, content-centric networking appears as a flexible communication model that meets the requirements of the content distribution trends of the future Internet. In such networks, information will reside at various locations/nodes (the Content Delivery Network surrogate servers) and the requests of the users for some piece of information will be directed to the closest replica. Since the location of the users and the popularity of the content varies over time, the problem of finding the optimal replication pattern for the available content, given the storage constraints, comes into the foreground. In this paper, we propose two on-line storage management algorithms of gradient descent type, designed specifically for content-centric networks. The proposed algorithms are of polynomial complexity and thus adapt easily to any environmental changes. Each node re-assigns its information items with the aim to minimize the overall traffic cost of the content delivery as the popularity and locality of users' requests change. While both the proposed algorithms operate in a distributed way, differ in the amount of information required for the decision making. Thus, we identify the inherent information — performance tradeoff and compare them in terms of network traffic, convergence speed and amount of circulated information.
Mobile Application to Detect Induction Motor Faults

An Android-based application has been developed which can convert any mobile phone with inbuilt accelerometer into a squirrel cage induction motor (SCIM) fault diagnosis tool. To detect the faults, the mobile phone needs to be attached to the motor, and the application will record the motor vibration signal using the inbuilt accelerometer. After the recording, the faults are detected by locating the fault frequencies in the motor vibration spectrum. The developed application can also detect the motor faults from any previously recorded files of vibration data. The application has been tested on a 22 kW SCIM using Moto G4 Plus and Moto G5 Plus Android phones. Unlike the other SCIM fault diagnosis systems, the proposed method does not require any dedicated sensors, processing platforms, and power supply arrangements.
Identification of variants in NFKBIA and association analysis with hepatocellular carcinoma risk among chronic HBV patients

Human nuclear factor of kappa light chain gene enhancer in B cells inhibitor, alpha (NFKBIA) inhibits the action of NF‐κB by forming a heterodimer with NF‐κB, and preventing its translocation to the nucleus. We have sequenced a human NFKBIA full gene including −1000bp promoter region to identify its gene polymorphisms as a potential candidate gene for host genetic study of Hepatocellular Carcinoma (HCC). Nine novel single nucleotide polymorphisms (SNPs) and one GAA deletion were identified; two in promoter region (c.−673A>T, c.−642C>T), two in exon 1 (c.78G>A (Leu26Leu), c.81C>T (Asp27Asp)), three in introns (c.284T>A, c.1952A>G and c.2444C>T) and three in 3'UTR (c.2710‐2712delGAA, c.2758G>A and c.3053G>A). Among ten identified variants, six were selected for larger scale genotyping (n=1,750) for association study based on frequencies and location. Haplotypes, their frequencies and linkage disequilibrium coefficients (∣D′∣) between SNP pairs were estimated. Allele frequencies of each SNPs and haplotypes were compared between patients with HCC and patients without HCC among HbsAg positives by logistic regression. As a conclusion, we could not find any significant association of NFKBIA variants with development of HCC among chronic hepatitis B patients. © 2003 Wiley‐Liss, Inc.
Two‐dimensional fractal growth properties of the filamentous fungus Cryphonectria parasitica: the effects of hypovirus infection

Whole‐colony two‐dimensional fractal growth patterns produced by hypovirus‐infected Cryphonectria parasitica (EP155/CHV1‐EP713) were measured and compared with those produced by the isogenic virus‐free strain (EP155) on solid medium. We have quantified statistically significant differences in the rates of expansion and spatial dynamics of colony growth between the two strains and concluded that fractal dimension is affected by the presence of the hypovirus. Therefore, fractal dimension measurement is an effective quantitative tool for testing the effects of mycovirus infection on fungal growth parameters. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Power capping of CPU-GPU heterogeneous systems through coordinating DVFS and task mapping

Future computer systems are built under much stringent power budget due to the limitation of power delivery and cooling systems. To this end, sophisticated power management techniques are required. Power capping is a technique to limit the power consumption of a system to the predetermined level, and has been extensively studied in homogeneous systems. However, few studies about the power capping of CPU-GPU heterogeneous systems have been done yet. In this paper, we propose an efficient power capping technique through coordinating DVFS and task mapping in a single computing node equipped with GPUs. In CPU-GPU heterogeneous systems, settings of the device frequencies have to be considered with task mapping between the CPUs and the GPUs because the frequency scaling can incurs load imbalance between them. To guide the settings of DVFS and task mapping for avoiding power violation and the load imbalance, we develop new empirical models of the performance and the maximum power consumption of a CPU-GPU heterogeneous system. The models enable us to set near-optimal settings of the device frequencies and the task mapping in advance of the application execution. We evaluate the proposed technique with five data-parallel applications on a machine equipped with a single CPU and a single GPU. The experimental result shows that the performance achieved by the proposed power capping technique is comparable to the ideal one.
An LSTM-CTC based verification system for proxy-word based OOV keyword search

Proxy-word based out of vocabulary (OOV) keyword search has been proven to be quite effective in keyword search. In proxy-word based OOV keyword search, each OOV keyword is assigned several proxies and detections of the proxies are regarded as detections of the OOV keywords. However, the confidence scores of these detections are still those of the proxies from lattices. To obtain a better confidence measure, we employ an LSTM-CTC verification method in this work and the confidence scores are regenerated. OOV keyword search results on the evalpart1 dataset of the OpenKWS16 Evaluation have shown consistent improvement and the maximum relative improvement can reach 21.06% for the MWTW metric.
Cell surface engineering of renal cell carcinoma with glycosylphosphatidylinositol-anchored TIMP-1 blocks TGF-β1 activation and reduces regulatory ID gene expression

Abstract Tissue inhibitor of metalloproteinase 1 (TIMP-1) controls matrix metalloproteinase activity through 1:1 stoichiometric binding. Human TIMP-1 fused to a glycosylphosphatidylinositol (GPI) anchor (TIMP-1–GPI) shifts the activity of TIMP-1 from the extracellular matrix to the cell surface. TIMP-1–GPI treated renal cell carcinoma cells show increased apoptosis and reduced proliferation. Transcriptomic profiling and regulatory pathway mapping were used to identify the potential mechanisms driving these effects. Significant changes in the DNA binding inhibitors, TGF-β1/SMAD and BMP pathways resulted from TIMP-1–GPI treatment. These events were linked to reduced TGF-β1 signaling mediated by inhibition of proteolytic processing of latent TGF-β1 by TIMP-1–GPI.
Variationally diagonalized multichannel state-space frequency-domain adaptive filtering for acoustic echo cancellation

In this contribution, we present a novel low-complexity state-space algorithm for multichannel acoustic echo cancellation. The reduction in complexity is brought about by means of top-down imposition of mutual independence on the respective acoustic echo paths within a variational Bayesian framework. This results in a fully diagonalized multichannel echo-path state estimator with a complexity that varies linearly with the channel order. The state estimator is augmented with learning rules for the model parameters that are optimal in the maximum-likelihood sense. We substantiate the efficacy of our formulation by means of simulation results in the presence of changes in the echo paths and continuous double-talk.
An integrated prognostic based hybrid genetic-immune algorithm for scheduling jobs and predictive maintenance

Recently, Prognostics and Health Management (PHM) reveals to be a key feature for industrials as it should improve manufacturing system availability and allow avoiding downtime as well as inopportune maintenance spending. In this context, we investigate the problem of scheduling several jobs on a single machine subjected to predictive maintenance based on PHM. We propose a new hybrid genetic immune algorithm, called IPro-HGIA, which incorporates an emulation of GA with artificial immune system, to create an integrated prognostic based scheduling for planning both production and predictive maintenance interventions under the total interventions cost minimization criterion. Furthermore, we use the principals of vaccination and receptor editing in order to strengthen search ability. Computational results show the efficiency of our hybrid scheme.
Evaluation of Disambiguation Mechanisms of Object-Based Selection in Virtual Environment: Which Performances and Features to Support "Pick Out"?

A 3D object selection technique is an essential building part of interactive virtual environment system. This ability to choose which object is the target for subsequent actions precedes any further behavior. Selection mechanism as part of manipulation process in a virtual environment is performed using different techniques. Furthermore, many problems make selection a difficult task and contribute to target ambiguity that leads users to select wrong objects by mistake. Therefore, disambiguation mechanisms have been proposed in the literature to solve target ambiguity. In this paper, we present an evaluation study of selection techniques that support disambiguation mechanisms. We performed a comparative study of 4 selection techniques including disambiguation mechanisms: Ray-Casting, Depth Ray, SQUAD and Shadow Cone. We developed an automated test environment where we varied scene density and measured the performance of each selection technique. Our goal was to measure the velocity of each technique, its sensitivity to occlusion, how much navigation it required and how far it could select targets. We found that discrete progressive refinement used in SQUAD was the fastest solution when user acts in a scene containing few objects to select. We also found that techniques that augment the pointing metaphor by using a 3D cursor, such as Depth Ray and SQUAD, performed better than ray casting itself or cone casting.
Functional Identification of Arabidopsis Stress Regulatory Genes Using the Controlled cDNA Overexpression System1[W][OA]

Responses to environmental stresses in higher plants are controlled by a complex web of abscisic acid (ABA)-dependent and independent signaling pathways. To perform genetic screens for identification of novel Arabidopsis (Arabidopsis thaliana) loci involved in the control of abiotic stress responses, a complementary DNA (cDNA) expression library was created in a Gateway version of estradiol-inducible XVE binary vector (controlled cDNA overexpression system [COS]). The COS system was tested in three genetic screens by selecting for ABA insensitivity, salt tolerance, and activation of a stress-responsive ADH1-LUC (alcohol dehydrogenase-luciferase) reporter gene. Twenty-seven cDNAs conferring dominant, estradiol-dependent stress tolerance phenotype, were identified by polymerase chain reaction amplification and sequence analysis. Several cDNAs were recloned into the XVE vector and transformed recurrently into Arabidopsis, to confirm that the observed conditional phenotypes were due to their estradiol-dependent expression. Characterization of a cDNA conferring insensitivity to ABA in germination assays has identified the coding region of heat shock protein HSP17.6A suggesting its implication in ABA signal transduction. Screening for enhanced salt tolerance in germination and seedling growth assays revealed that estradiol-controlled overexpression of a 2-alkenal reductase cDNA confers considerable level of salt insensitivity. Screening for transcriptional activation of stress- and ABA-inducible ADH1-LUC reporter gene has identified the ERF/AP2-type transcription factor RAP2.12, which sustained high-level ADH1-LUC bioluminescence, enhanced ADH1 transcription rate, and increased ADH enzyme activity in the presence of estradiol. These data illustrate that application of the COS cDNA expression library provides an efficient strategy for genetic identification and characterization of novel regulators of abiotic stress responses.
COCAST: Multicast mobile ad hoc networks using cognitive radio

Many multicast protocols have been proposed for ad hoc networks. ODMRP is one of the most popular protocols due to its robustness in highly mobile wireless networks. However, ODMRP is unscalable in terms of the number of sources. We improve the scalability of ODMRP using cognitive radio technology, which diversifies channel usage for multicast members with multiple cognitive channels. We design a channel allocation and distribution scheme to build a multicast tree for each group. In addition, we implement cooperative sensing by multicast members using Join Query and Join Reply messages. In simulation experiments, our protocol, CoCast, demonstrates a superior delivery ratio and throughput performance to conventional ODMRP.
Deletion of Syk in Neutrophils Prevents Immune Complex Arthritis

The K/BxN serum transfer model of arthritis is critically dependent on FcγR signaling events mediated by spleen tyrosine kinase (Syk). However, the specific cell types in which this signaling is required are not known. We report that deletion of Syk in neutrophils, achieved using sykf/f MRP8-cre+ mice, blocks disease development in serum transfer arthritis. The sykf/f MRP8-cre+ mice display absent joint disease and reduced deposition of pathogenic anti–glucose-6-phosphate isomerase Abs in the joint (with a reciprocal accumulation of these Abs in the peripheral circulation). Additionally, sykf/f MRP8-cre+ mice manifest poor edema formation within 3 h after formation of cutaneous immune complexes (Arthus reaction). Together, this suggests that neutrophil-dependent recognition of immune complexes contributes significantly to changes in vascular permeability during the early phases of immune complex disease. Using mixed chimeric mice, containing both wild-type and sykf/f MRP8-cre+ neutrophils, we find no impairment in recruitment of Syk-deficient neutrophils to the inflamed joint, but they fail to become primed, demonstrating lower cytokine production after removal from the joint. They also display an increased apoptotic rate compared with wild-type cells in the same joint. Mast cell-deficient c-kitsh/sh mice developed robust arthritis after serum transfer whereas c-kitW/Wv mice did not, suggesting that previous conclusions concerning the central role of mast cells in this model may need to be revised. Basophil-deficient mice also responded normally to K/BxN serum transfer. These results demonstrate that Syk-dependent signaling in neutrophils alone is critically required for arthritis development in the serum transfer model.
M-PAES: a memetic algorithm for multiobjective optimization

A memetic algorithm for tackling multiobjective optimization problems is presented. The algorithm employs the proven local search strategy used in the Pareto archived evolution strategy (PAES) and combines it with the use of a population and recombination. Verification of the new M-PAES (memetic PAES) algorithm is carried out by testing it on a set of multiobjective 0/1 knapsack problems. On each problem instance, a comparison is made between the new memetic algorithm, the (1+1)-PAES local searcher, and the strength Pareto evolutionary algorithm (SPEA) of E. Zitzler and L. Thiele (1998, 1999).
A new high speed, low power adder; using hybrid analog-digital circuits

In this paper a new high speed and low power adder is presented. The circuit uses a hybrid concept of analog and digital circuit design to propagate the carry and so achieve a Full Adder with 78<sup>ps</sup> delay and 7.26<sup>μ</sup><sup>w</sup> of power consumption. SPICE Simulations performed on the 0.18<sup>μm</sup> TSMC Technology demonstrates the average improvement of 159%, 184% and 516%, respectively for Delay, Power Consumption and PDP.
Active online learning of trusts in social networks

This paper considers an online optimization algorithm for actively learning trusts on social networks. We first introduce a DeGroot model for opinion dynamics under the influence of stubborn agents and demonstrate how an observer with estimates of the individuals opinions can actively learn the relative trusts among different agents, by fitting the opinions to the steady state equations of the social system equations. The main contribution of this article is an online algorithm for extracting the trust parameters from streaming data of randomly sampled, noisy opinion estimates. The algorithm is based on the stochastic proximal gradient method and it is proven to converge almost surely. Finally, numerical results are presented to corroborate our findings.
Individual Differences and Differential Psychology

Differential psychology has been a central concern to philosophers and psychologists, both applied and theoretical, for the past several millennia. It remains so today. The proper study of individual differences integrates methodology, affective and cognitive science, genetics and biology. It is a field with a long history and an exciting future. We review some of the major questions that have been addressed and make suggestions as to future directions.
Long Time Asymptotics of Solutions to the Anharmonic Oscillator Model from Nonlinear Optics

The anharmonic oscillator model describing the propagation of electromagnetic waves in an exterior domain containing a nonlinear dielectric medium is investigated. The system under consideration consists of a generally nonlinear second order differential equation for the dielectrical polarization coupled with Maxwell's equations for the electromagnetic field. Local decay of the electromagnetic field for $t\rightarrow\infty$ in the charge free case is shown for a large class of potentials.