Miracle-dz/UniFAR-FTUs huggingface dataset:
A 4mW wide bandwidth ring-based fractional-n DPLL with 1.9psrms integrated-jitter

In this paper, a ring oscillator based fractional-N DPLL that achieves low jitter by extending bandwidth using noise cancellation techniques is presented. A dual-path digital loop filter architecture is employed to resolve the ΔΣ DAC quantization noise challenge. Fabricated in 65nm CMOS process, the proposed PLL operates over a wide frequency range of 4GHz-5.5GHz and achieves 1.9psrms jitter while consuming only 4mW. The measured in-band phase noise is better than -96 dBc/Hz at 1MHz offset. The proposed FNDPLL achieves wide bandwidth up to 6MHz using a 50 MHz reference. The FoM is -228.5dB, which is at least 20dB better than all reported ring-based FNDPLLs.
Firm size diversity, functional richness, and resilience

This paper applies recent advances in ecology to our understanding of firm development, sustainability, and economic development. The ecological literature indicates that the greater the functional richness of species in a system, the greater its resilience – that is, its ability to persist in the face of substantial changes in the environment. This paper focuses on the effects of functional richness across firm size on the ability of industries to survive in the face of economic change. Our results indicate that industries with a richness of industrial functions are more resilient to employment volatility.
SER-Based Web Graph Decontamination

The creation of a web bubble, or link farm, is a technique used by web spammers to increase the visibility of a target page T. Specialized mobile agents, called Web Marshals, are employed to detect and dismantle link farms. As the number of Web Marshals, as well as the number of hops needed to disassemble a link farm, need to be minimized, this kind of process can be seen as a graph decontamination problem. This paper presents an asynchronous distributed decontamination algorithm which can be embedded into the web marshals’ behavior. Although the novel algorithm is topology independent, compared to recent related works, having circulant graphs as targets, it presents equal or better performance and a smaller number of deployed web marshals when applied to the same circulant graph topologies.
An Algorithm for Assigning Tasks in Parallel Computing

As the parallel distributed architectures are increasing used to solve the large-scale scientific problems, the scheduling algorithm which can heavily affect the communication overhead and the execution time is becoming more and more important for the optimization of parallel programs in real distribute system or in the performance prediction to make more precise, so it requires appropriate techniques to identify the factors which influence the application execution time and also the way they interact. Generally, parallel applications characterized as a collection of tasks and their interrelations. As the number of the processes increasing, the overhead of the communication among these processes can be very impressive, different tasks assignment algorithm can affect the performance of the parallel application. This paper introduces a scheduling algorithm TMDC (Task Mapping based on Dependence and Communication) for assigning tasks to the processors and minimizes the communications volume to optimize the total execution time. It’s based on the DAGs can helps to understand the details of the application and to increase the accuracy of the prediction models.
Disfluency Detection Using a Bidirectional LSTM

We introduce a new approach for disfluency detection using a Bidirectional Long-Short Term Memory neural network (BLSTM). In addition to the word sequence, the model takes as input pattern match features that were developed to reduce sensitivity to vocabulary size in training, which lead to improved performance over the word sequence alone. The BLSTM takes advantage of explicit repair states in addition to the standard reparandum states. The final output leverages integer linear programming to incorporate constraints of disfluency structure. In experiments on the Switchboard corpus, the model achieves state-of-the-art performance for both the standard disfluency detection task and the correction detection task. Analysis shows that the model has better detection of non-repetition disfluencies, which tend to be much harder to detect.
More on the scalar-tensor BF theory

This work is based on an earlier proposal [H. Singh, Phys. Lett. B 673, 68 (2009)] that the membrane BF theory consists of matter fields along with Chern-Simons fields as well as the auxiliary pairs of scalar and tensor fields. In particular, we discuss the supersymmetry aspects of such a membrane theory. It is concluded that the theory possesses maximal supersymmetry, and it is related to the L-BLG theory via a field map. We obtain fuzzy-sphere solution, and corresponding tensor field configuration is given.
Heavy Metal Tolerance and Accumulation in Indian Mustard (Brassica Juncea L.) Expressing Bacterial γ-Glutamylcysteine Synthetase or Glutathione Synthetase

The overexpression of either γ-glutamylcysteine synthetase (γ-ECS) or glutathione synthetase (GS) in Brassica juncea transgenics was shown previously to result in higher accumulation of glutathione (GSH) and phytochelatins (PCs), as well as enhanced Cd tolerance and accumulation. The present study was aimed at analyzing the effects of γ-ECS or GS overexpression on tolerance to and accumulation of other metal/loids supplied individually in agar medium (seedlings) or in hydroponics (mature plants). Also, as pollution in nature generally consists of mixtures of metals, glutamylcysteine synthetase (ECS) and GS seedlings were tested on combinations of metals. Compared to wild-type plants, ECS and GS transgenics exhibited a significantly higher capacity to tolerate and accumulate a variety of metal/loids (particularly As, Cd, and Cr) as well as mixed-metal combinations (As, Cd, Zn/As, Pb, and Zn). This enhanced metal tolerance and accumulation of the ECS and GS transgenics may be attributable to enhanced production of PCs, sustained by a greater availability of GSH as substrate, as suggested by their higher concentrations of GSH, PC2, PC3, and PC4 as compared to wild-type plants. Overexpression of GS and γ-ECS may represent a promising strategy for the development of plants with an enhanced phytoremediation capacity for mixtures of metals.
Adaptive neural control of pure-feedback stochastic nonlinear systems with multiple unknown time-varying delays

By the combination of the adaptive backstepping design with the dynamic surface control technique, an novel adaptive neural control approach is investigated for a class of pure-feedback stochastic nonlinear systems with multiple unknown time-varying delays. To overcome the design difficulty arising from the non-affine structure of pure-feedback stochastic systems, the mean value theorem is exploited. The design difficulties due to multiple unknown time-varying delay functions are overcome by using the function separation technique, the appropriate Lyapunov-Krasovskii functionals and the desirable property of hyperbolic tangent functions. The radial-basis-function (RBF) neural networks are utilized to approximate the unknown nonlinear functions. It is shown that the proposed control approach can guarantee that all signals of the closed-loop system are bounded in probability, and the tracking errors can be made arbitrarily small in probability by choosing suitable design parameters. Finally, simulation example is provided to demonstrate the effectiveness of the proposed control scheme.
Combining micro-blogging and IDE interactions to support developers in their quests

Software engineers spend a considerable amount of time on program comprehension. Although vendors of Integrated Development Environments (IDEs) and analysis tools address this challenge, current support for reusing and sharing program comprehension knowledge is limited. As a consequence, developers have to go through the time-consuming program understanding phase multiple times, instead of recalling knowledge from their past or other's program comprehension activities. In this paper, we present an approach to making the knowledge gained during the program comprehension process accessible, by combining micro-blog messages with interaction data automatically collected from the IDE. We implemented the approach in an Eclipse plugin called James and performed a first evaluation of the underlying approach effectiveness, assessing the nature and usefulness of the collected messages, as well as the added benefit of combining them with interaction data.
Nanoparticle assembly by confinement in wrinkles: experiment and simulations

We created hierarchically ordered structures of nanoparticles on smooth planar hydrophilic substrates by drying colloidal dispersions in confinement under macroscopic stamps with microscopically wrinkled surfaces. Experiments were carried out with model nanoparticle suspensions that possess high colloidal stability and monodispersity. The structures ranged from single parallel lines of particles to arrays of dense prismatic ridges. The type of observed structure could be controlled by the particle concentration in the initial dispersion. Confinement between two crossed stamps led to interconnected meshes of particles. The precise morphology could be predicted in all cases by Monte Carlo computer simulations of confined hard spheres. Our findings open up possibilities for versatile nanoparticle assembly on surfaces.
Inner Garden: an Augmented Sandbox Designed for Self-Reflection

We present a prototype of an augmented sandbox where the sand is used to create a miniature living world, designed as an ambient display for contemplation and self-reflection. The landscape can be reshaped at any time. Once the sand is left still for a moment, the world starts evolving -- vegetation grows, water flows and creatures move around -- according to the user's internal state. We use a consumer-grade EEG and breathing sensors to reflect on frustration and meditative states of users, which they can monitor by looking at the sandbox.
Cuckoo directory: A scalable directory for many-core systems

Growing core counts have highlighted the need for scalable on-chip coherence mechanisms. The increase in the number of on-chip cores exposes the energy and area costs of scaling the directories. Duplicate-tag-based directories require highly associative structures that grow with core count, precluding scalability due to prohibitive power consumption. Sparse directories overcome the power barrier by reducing directory associativity, but require storage area over-provisioning to avoid high invalidation rates. We propose the Cuckoo directory, a power- and area-efficient scalable distributed directory. The cuckoo directory scales to high core counts without the energy costs of wide associative lookup and without gross capacity over-provisioning. Simulation of a 16-core CMP with commercial server and scientific workloads shows that the Cuckoo directory eliminates invalidations while being up to four times more power-efficient than the Duplicate-tag directory and 24% more power-efficient and up to seven times more area-efficient than the Sparse directory organization. Analytical projections indicate that the Cuckoo directory retains its energy and area benefits with increasing core count, efficiently scaling to at least 1024 cores.
Towards an Ultra Lightweight Crypto Processor

In this paper, a lightweight processor suitable for lightweight cryptographic applications is presented. The processor instruction set is based on the stack-based ZPU architecture. In addition, a simple generic plug-in interface is implemented in order to allow integration of application specific coprocessors to the main processor core. In the current version of the processor, a simple direct memory access engine and a serialized Klein cipher coprocessor are implemented and connected to the processor core. Through these engines, it is possible to implement various lightweight security and authentication schemes in a code and area effective way. A simple assembler code is written and tested on the processor in order to verify the functionality of the processor core and coprocessors. The code implements a Davies-Meyer coding scheme and uses the Klein block cipher as a hash function. The GCC toolset originally written for the 32-bit ZPU is being adapted to work with the 8-bit processor core. The designed processor is synthesized using VeriSilicon GSMC 0.13um low-power process high-density standard cell library for a target operating frequency of 100 KHz, and the resultant gate count is 4.5K GE.
Manipulation Robustness of Collaborative Filtering

A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions and hence have become targets of manipulation by unscrupulous vendors. We demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust.
REMOVING OCCLUSION IN IMAGES USING SPARSE PROCESSING AND TEXTURE SYNTHESIS

We provide a solution to problem of occlusi on in images by removing the occluding region and filling in the gap left behind. Inpainting algorithms fail in filling occlusions when the occluding region is large since there is loss of both structure and texture. We decompose the image into structure a nd texture images using a decomposition method based on sparseness of the image. The sparse reconstruction of the decomposed images result in an inpainted image with all the structures made intact. A texture synthesis is performed on the texture only image. Finally the structure and texture images are combined to get an image where the occlusion is filled. The performance of our algorithm in terms of visual effectiveness is compared with other algorithms used for inpainting .
A Vision for a Semantic Infrastructure Supporting Model-based Tool Integration

With the rise of model-driven software development, more and more development tasks are being performed on models. Seamless exchange of models among different modeling tools increasingly becomes a crucial prerequisite for effective software development processes. Due to lack of interoperability, however, it is often difficult to use tools in combination, thus the potential of model-driven software development cannot be fully utilized. To tackle this problem, our main contribution is ModelCVS, a sketch of a system aiming at model-based tool integration. ModelCVS enables transparent transformation of models between different tools’ languages and exchange formats, as well as versioning exploiting the rich syntax and semantics of models, thus going beyond existing low-level model transformation approaches. For this, ModelCVS utilizes semantic technologies and integration patterns, allowing integration at the metamodel level. To foster reuse, a tool integration knowledge base captures essential knowledge about modeling languages and tools in terms of ontologies.
Extraction of Preference of Recipe Providers and Users on Recipe-Sharing Websites

The growth of the Internet provides us with an easy access to information and methods are proposed for market analysis. This paper focuses on a method using KeyGraph for extraction and visualization of preference from information of a recipe sharing website, which enables us to grasp the user's preferences and find business opportunities. Furthermore, several analyses are conducted to evaluate the proposed method. The results show that the presented method is promising in preference extraction.
Comparative Accuracy of Apical Biplane Cross‐sectional Echocardiography and Gated Equilibrium Radionuclide Angiography for Estimating Left Ventricular Size and Performance

To compare measurements of left ventricular size and performance obtained by apical biplane cross-sectional echocardiography (CSE) and gated equilibrium radionuclide angiography (RNA), we studied 70 patients, all of whom had single-plane and 30 of whom had biplane left ventricular cineangiography. Wideangle, phased-array CSE images were obtained from two orthogonal apical views and left ventricular volumes were calculated using a microprocessor-controlled, video light-pen system programmed for a Simpson's rule algorithm. The average CSE end-diastolic volume (EDV) for all 70 patients of 158 ± 56 ml (± SD) was less than the single-plane angiographic value of 176 ± 68 ml (p < 0.001, r = 0.80). The average CSE end-systolic volume (ESV) of 78 ± 57 ml was not different from the angiographic value of 84 ± 70 ml (r = 0.88). The average CSE and single-plane angiographic ejection fraction (EF) values of 55 ± 16% and 57 ± 19% were not different (r = 0.90). In the 30 patients who underwent biplane angiography, the average CSE EDV of 166 ± 62 ml was less than the biplane angiographic EDV of 217 ± 87 ml (p < 0.001, r = 0.81), and the average CSE ESV of 89 ± 69 ml was also less than the angiographic value of 114 ± 89 ml (p < 0.001, r = 0.92). The average CSE LV EF of 52 ± 19% was not different from the biplane angiographic value of 52 ± 17% (r = 0.87). In the 25 patients who underwent CSE, RNA and biplane angiography, the average LVEF values were 51 ± 20%, 46 ± 18% and 50 ± 17%, respectively, and the CSE and RNA values correlated with the biplane angiographic value (r = 0.90 and 0.93, respectively). Therefore, apical biplane CSE estimates of left ventricular volume correlate linearly with single-plane and biplane cineangiographic determinations, and this CSE technique compares favorably with gated equilibrium RNA for assessing left ventricular performance.
Phase II Efficacy and Pharmacogenomic Study of Selumetinib (AZD6244; ARRY-142886) in Iodine-131 Refractory Papillary Thyroid Carcinoma with or without Follicular Elements

Purpose: A multicenter, open-label, phase II trial was conducted to evaluate the efficacy, safety, and tolerability of selumetinib in iodine-refractory papillary thyroid cancer (IRPTC). Experimental Design: Patients with advanced IRPTC with or without follicular elements and documented disease progression within the preceding 12 months were eligible to receive selumetinib at a dose of 100 mg twice daily. The primary endpoint was objective response rate using Response Evaluation Criteria in Solid Tumors. Secondary endpoints were safety, overall survival, and progression-free survival (PFS). Tumor genotype including mutations in BRAF, NRAS, and HRAS was assessed. Results: Best responses in 32 evaluable patients out of 39 enrolled were 1 partial response (3%), 21 stable disease (54%), and 11 progressive disease (28%). Disease stability maintenance occurred for 16 weeks in 49%, 24 weeks in 36%. Median PFS was 32 weeks. BRAF V600E mutants (12 of 26 evaluated, 46%) had a longer median PFS compared with patients with BRAF wild-type (WT) tumors (33 versus 11 weeks, respectively, HR = 0.6, not significant, P = 0.3). The most common adverse events and grades 3 to 4 toxicities included rash, fatigue, diarrhea, and peripheral edema. Two pulmonary deaths occurred in the study and were judged unlikely to be related to the study drug. Conclusions: Selumetinib was well tolerated but the study was negative with regard to the primary outcome. Secondary analyses suggest that future studies of selumetinib and other mitogen-activated protein (MAP)/extracellular signal-regulated kinase (ERK; MEK) inhibitors in IRPTC should consider BRAF V600E mutation status in the trial design based on differential trends in outcome. Clin Cancer Res; 18(7); 2056–65. ©2012 AACR.
On the Convergence Error in Loopy Propagation

Reasoning with a Bayesian network amounts to computing probability distributions for the network’s variables. Pearl’s propagation algorithm provides for efficient reasoning with singly connected networks. When applied to a multiply connected network, the algorithm no longer yields exact probabilities, yet has been reported to result in good approximations. In this paper we provide some theoretical background to the algorithm’s performance on multiply connected networks. We indicate the two types of error that can arise in the probabilities computed by the algorithm and analyse the different factors that govern one of these errors.
Ca 2 1 Sparks Triggered by Patch Depolarization in Rat Heart Cells

The goal of this study was to examine the relationship between Ca entry through L-type Ca channels and local [Ca]i transients (Ca 21 sparks) in single rat cardiac ventricular cells. L-type Ca channels were activated by depolarization of cell-attached membrane patches, and [Ca]i was measured simultaneously as fluo 3 fluorescence using laser scanning confocal microscopy. Patch depolarization with Ca as the charge carrier (10 or 110 mmol z L) significantly increased the probability of the occurrence of Ca sparks (Ca spark rate) only in the volume of cytoplasm located immediately beneath the membrane patch (basal Ca spark rate, 119 Ca sparks z cell z s; patch depolarization Ca spark rate, 610 Ca sparks z cell z s; P,.005). With Ba in the pipette solution (10 mmol z L), patch depolarization was not associated with an increased Ca spark rate at the position of the pipette or at any other sites distant from the pipette. Therefore, Ca entry and not voltage per se was a necessary event for the occurrence of Ca sparks. Under identical experimental conditions, patch depolarization experiments opened single L-type Ca channels with a single-channel conductance of 19 pS with Ba as the charge carrier. Although single-channel openings could not be resolved when Ca was the charge carrier, ensemble averages yielded an inward current of up to 0.75 pA. The results suggest that voltage-activated Ca entry through one or a small number of L type Ca channels triggers the release of Ca only from the sarcoplasmic reticulum in direct proximity to those L-type Ca channels. The relatively low probability of triggering Ca sparks may have resulted from some alteration of excitation-contraction coupling associated with the technique of the cell-attached patch clamp. (Circ Res. 1998;82:424-429.)
Tuning protocols to improve the energy efficiency of sensornets

Energy efficiency is of critical importance in sensornets where the working life of wireless motes, and consequently the entire network, is limited by the finite energy capacity of batteries. Radio network activity typically dominates the energy consumption profile of motes running distributed applications, and hence represents the obvious target when attempting to use energy more frugally. Significant savings can be obtained by carefully tuning existing energy-ignorant protocols. Current practice in choosing parameters is generally based on experience, intuition, and trial and error. This approach rarely leads to the best choice. In this paper a novel method is presented through which the complex relationships between protocol parameters, network structure, application workload and observed network behaviour are understood and tuned.
A NEW GENETIC REPRESENTATION FOR QUADRATIC ASSIGNMENT PROBLEM

In this paper, we propose a new genetic encoding for well known Quadratic Assignment Problem (QAP). The new encoding schemes are implemented with appropriate objective function and modified genetic operators. The numerical experiments were carried out on the standard QAPLIB data sets known from the literature. The presented results show that in all cases proposed genetic algorithm reached known optimal solutions in reasonable time.