Miracle-dz/UniFAR-FTUs huggingface dataset:
Timing analysis of combinational circuits using ADDs

This paper presents a symbolic algorithm to perform timing analysis of combinational circuits which takes advantage of the high compactness of representation of the Algebraic Decision Diagrams (ADDs). The procedure we propose, implemented as on extension of the SIS synthesis system, is able to provide more accurate timing information than any other method presented so far; in particular, it is able to compute and store the true delay of the gate-level representation of the circuit for all possible input vectors, as opposed to the traditional methods which consider only the worst-case primary inputs combination. Furthermore, the approach does not require any explicit false path elimination. The information calculated by the timing analyzer has several practical applications such as determining the sets of critical input vectors, critical gates, and critical paths of the circuit, which may be efficiently used in the process of resynthesizing the network for low-power consumption. <<ETX>>
Parathyroid Hormone-dependent Degradation of Type II Na+/Pi Cotransporters*

Parathyroid hormone (PTH) inhibits proximal tubular brush border membrane Na+/Picotransport activity; this decrease in the transport activity was found to be associated with a decrease in type II Na+/Pi cotransporter protein content in rat brush border membranes. In the present study we investigated the PTH-dependent regulation of the type II Na+/Pi cotransporter in opossum kidney cells, a previously established model to study cellular mechanisms involved in the regulation of proximal tubular Na+/Picotransport. We transfected opossum kidney cells with a cDNA coding for NaPi-2 (rat renal type II Na+/Pi cotransporter). This allowed the study of PTH-dependent regulation of the transfected NaPi-2 and of the corresponding intrinsic cotransporter (NaPi-4). The results show (i) that the intrinsic and the transfected cotransporters are functionally (transport) and morphologically (immunofluorescence) localized at the apical membrane, (ii) that the intrinsic as well as the transfected Na+/Pi cotransport activities are inhibited by PTH, (iii) that PTH leads to a retrieval of both cotransporters from the apical membrane, (iv) that both cotransporters are rapidly degraded in response to PTH, and (v) that the reappearance/recovery of type II Na+/Pi cotransporter protein and function from PTH inhibition requires de novo protein synthesis. These results document that PTH leads to a removal of type II Na+/Pi cotransporters from the apical membrane and to their subsequent degradation.
Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.
Dilute – Sulfuric Acid Pretreatment of Corn Stover in Pilot-Scale Reactor Investigation of Yields , Kinetics , and Enzymatic Digestibilities of Solids

Corn stover is a domestic feedstock that has potential to produce significant quantities of fuel ethanol and other bioenergy and biobased products. However, comprehensive yield and carbon mass balance information and validated kinetic models for dilute–sulfuric acid (H2SO4) pretreatment of corn stover have not been available. This has hindered the estimation of process economics and also limited the ability to perform technoeconomic modeling to guide research. To better characterize pretreatment and assess its kinetics, we pretreated corn stover in a continuous 1 t/d reactor. Corn stover was pretreated at 20% (w/w) solids concentration over a range of conditions encompassing residence times of 3–12 min, temperatures of 165– 195°C, and H2SO4 concentrations of 0.5–1.4% (w/w). Xylan conversion yield and carbon mass balance data were collected at each run condition. Performance results were used to estimate kinetic model parameters assuming biphasic hemicellulose hydrolysis and a hydrolysis mechanism incorporating formation of intermediate xylo-oligomers. In addition, some of the pretreated solids were tested in a simultaneous saccharification and fermentation (SSF) process to measure the reactivity of their cellulose component to enzymatic digestion by cellulase enzymes. Monomeric xylose yields of 69–71% and total xylose yields (monomers and oligomers) of 70–77% were achieved with performance level depending on pretreatment severity. Cellulose conversion yields in SSF of 80–87% were obtained for some of the most digestible pretreated solids. Index Entries: Pretreatment; dilute–sulfuric acid; enzymatic conversion; corn stover; xylan conversion; kinetics; pilot scale.
Providing Secure Integrity in Peer-to-Peer Oriented Mobile Environments

Providing confidentiality, integrity, and availability is indispensable for secure systems. In particular, almost every commerce application requires that integrity be provided in a secure manner, such that the integrity of data is retained even if the owner of the data is malicious. However, providing secure integrity in mobile environments, where participating nodes and their communication channels are unstable, is not a simple task. This is mainly because of the difficulty of solving the agreement problem securely in these environments due to the unreliability of channels, and the passivity of smartcards that complicates the implementation of distributed protocols among them. In this paper, we propose an optimistic approach to address these problems. This approach introduces an optimistic non-blocking atomic commitment (NBAC) protocol for smartcards to secure reliable agreements, and implements the protocol on a distributed framework for inter-smartcard communication to relax the implementation complexity. Our implementation results show the feasibility of this approach: current smartcards can conduct the protocol in no more than about a half second, which should be enough performance to support commerce transactions, the application most likely to need secure integrity.
A feedback-based adaptive broadcast coding scheme for reducing in-order delivery delay

We propose a new feedback-based adaptive coding scheme for a packet erasure broadcast channel. The main performance metric of interest is the delay. We consider two types of delay - decoding delay and delivery delay. Decoding delay is the time difference between the instant when the packet is decoded at an arbitrary receiver and the instant when it arrived at the sender. Delivery delay also includes the period when a decoded packet waits in a resequencing buffer at the receiver until all previous packets have also been decoded. This notion of delay is motivated by applications that accept packets only in order. Our coding scheme has the innovation guarantee property and is hence throughput optimal. It also allows efficient queue management. It uses the simple strategy of mixing only the oldest undecoded packet of each receiver, and therefore extends to any number of receivers. We conjecture that this scheme achieves the asymptotically optimal delivery (and hence decoding) delay. The asymptotic behavior is studied in the limit as the load factor of the system approaches capacity. This conjecture is verified through simulations.
How Local are Labor Markets? Evidence from a Spatial Job Search Model

This paper uses data on very small UK geographies to investigate the effective size of local labor markets. Our approach treats geographic space as continuous, as opposed to a collection of non-overlapping administrative units, thus avoiding problems of mismeasurement of local labor markets encountered in previous work. We develop a theory of job search across space that allows us to estimate a matching process with a very large number of areas. Estimates of this model show that the cost of distance is relatively high - the utility of being offered a job decays at exponential rate around 0.3 with distance (in km) to the job - so that labor markets are indeed quite `local'. Also, workers are discouraged from applying to jobs in areas where they expect relatively strong competition from other jobseekers. The estimated model replicates fairly accurately actual commuting patterns across neighbourhoods, although it tends to underpredict the proportion of individuals who live and work in the same ward. Finally, we find that, despite the fact that labor markets are relatively `local', local development policies are fairly ineffective in raising the local unemployment outflow, because labor markets overlap, and the associated ripple effects in applications largely dilute the impact of local stimulus across space.
Bee)Dancing on the Boundary Between PIM and GIM

In the life sciences, 40,000 new articles are published each month, adding a large number of findings to an already immense area of knowledge [15]. Literature review is difficult, increasing the chance of duplicated effort. It is also timeconsuming, reducing the amount of resources scientists have to pursue new discoveries. One approach to this problem would be to fund a talented team of researchers to curate all published knowledge in a structured database. However, it is our position that the information gathering activity of individual investigators provides both an effective means of self-curation of published knowledge and an effective vehicle for communicating this information to researchers who will need it. Stated more concretely, our position is that researchers need an information system that enables them to:
Reducing abstraction level when learning computability theory concepts

The paper illustrates how theories from mathematics education can be applied for explaining student conception of computing science ideas. It does this by demonstrating how the theme of reducing abstraction [5] can be used for analyzing students' mental processes when the students are in the process of solving problems in Computability Theory. The topic of Computability Theory in presented here as an example for demonstrating how research in Computing Science education can use learning theories, "borrowed" from mathematics education research, for explaining learning processes.
Absorbing boundary conditions for the wave equation and parallel computing

Absorbing boundary conditions have been developed for truncating unbounded computational domains to bounded ones. The authors investigate the use of absorbing boundary conditions in domain decomposition algorithms for the wave equation. Moreover, they optimize the absorbing boundary conditions in order to obtain a good performance of the Schwarz waveform relaxation algorithm. The analysis given is confirmed by numerical experiments.
Blind Estimation of Channel Length for OFDM Systems

In orthogonal frequency division multiplexing (OFDM) systems, multipath fading channels introduce interference between adjacent symbols. Although the interference degrades the system performance considerably, it also provides the information of channel impulse response (CIR) length to us. Therefore, based on the estimation of interference in the cyclic prefix (CP) interval, we can use the minimum description length (MDL) criterion to detect the channel length blindly.
Fusion of Multimodal Information in Music Content Analysis

Music is often processed through its acoustic realization. This is restrictive in the sense that music is clearly a highly multimodal concept where various types of heterogeneous information can be associated to a given piece of music (a musical score, musicians' gestures, lyrics, user-generated metadata, etc.). This has recently led researchers to apprehend music through its various facets, giving rise to "multimodal music analysis" studies. This article gives a synthetic overview of methods that have been successfully employed in multimodal signal analysis. In particular, their use in music content processing is discussed in more details through five case studies that highlight different multimodal integration techniques. The case studies include an example of cross-modal correlation for music video analysis, an audiovisual drum transcription system, a description of the concept of informed source separation, a discussion of multimodal dance-scene analysis, and an example of user-interactive music analysis. In the light of these case studies, some perspectives of multimodality in music processing are finally suggested.
Simulation of a population of isolated neutron stars evolving through the emission of gravitational waves

We study, via a Monte Carlo simulation, a population of isolated asymmetric neutron stars where the magnitude of the magnetic field is low enough so that the dynamical evolution is dominated by the emission of gravitational waves. A starting population, with age uniformly distributed back to 100 Myr (or 500 Myr) and endowed with a birth kick velocity, is evolved in the Galactic gravitational potential to the present time. In describing the initial spatial distribution, the Gould belt, with an enhanced neutron star formation rate, is taken into account. Different models for the initial period distribution are considered. The star ellipticity, measuring the amount of deformation, is drawn from an exponential distribution. We estimate the detectability of the emitted gravitational signals by the first and planned second generation of interferometric detectors. Results are parametrized by the fraction of the whole galactic neutron star population made up of these kinds of sources. Some possible mechanisms, which would make possible the existence of such a population, are discussed. A comparison of the gravitational spin-down with the braking due to a possible interaction of the neutron star with the interstellar medium is also presented.
High-Speed Tactile Sensing for Array-Type Tactile Sensor and Object Manipulation Based on Tactile Information

We have developed a universal robot hand with tactile and other sensors. An array-type tactile sensor is crucial for dexterous manipulation of objects using a robotic hand, since this sensor can measure the pressure distribution on finger pads. The sensor has a very high resolution, and the shape of a grasped object can be classified by using this sensor. The more the number of measurement points provided, the higher the accuracy of the classification, but with a corresponding lengthening of the measurement cycle. In this paper, the problem of slow response time is resolved by using software for an array-type tactile sensor with high resolution that emulates the human sensor system. The validity of the proposed method is demonstrated through experiments.
A new method for the identification of proactive information security management system metrics

Information security is topic of everyday interest, with mainstream media reports revealing information security incidents in many different areas. These reports demonstrate the importance to any organization of having an information security management system (ISMS). Foreseeing potential security risks is usually key to successful risk management. Available information security standards such as the ISO 27000 set of standards give a formal framework for successful information security management in any size of organisation or company. In this paper we draw on experience gained during a project leading to successful ISO 27001 certification at the Central Bank of Bosnia and Herzegovina in 2009. We review recent work on proactive damage prevention, and we propose methodology based on the GQM (Goal, Question, Metrics) paradigm for determining proactive steps for detection and resolution of different information security control violations. For creating proactive measurement metrics we use the well recognised standards ISO 27004:2009, and NIST 800-55. We present several examples of proactive metrics.
Nonlinear estimation framework in target tracking

The goal of the article is to describe a software framework designed for nonlinear state estimation of discrete-time dynamic systems. The framework was designed with the aim to facilitate implementation, testing and use of various nonlinear state estimation methods. The main strength of the framework is its versatility due to the possibility of either structural or probabilistic model description. Besides the well-known basic nonlinear estimation methods such as the extended Kalman filter, the divided difference filters and the unscented Kalman filter, the framework implements the particle filter with advanced features. As the framework is designed on the object oriented basis, further extension by user-specified nonlinear estimation algorithms is extremely easy. The paper describes the individual components of the framework, their key features and use. The paper demonstrates easy and natural application of the framework in target tracking which is illustrated in two examples - tracking a ship with unknown control and tracking three targets based on raw data.
Thermal noise modeling of nano-scale MOSFETs for mixed-signal and RF applications

This paper presents the thermal noise in nano-scale MOSFETs - from measurement, characterization, modeling, and potential technology enhancement for future low power, mixed-signal, and radio-frequency (RF) applications. Experimental data from five CMOS technology nodes, namely 180 nm, 130 nm, 90 nm, 65 nm, and 40 nm nodes are presented and discussed.
Elastic wavefield modelling in 3 D by fourth-order staggered-grid finite difference technique

Modern computational power makes possible realistic simulations of elastic wavefields at frequencies of interest. The most general numerical methods for modelling are grid-based techniques that track the wavefield on a dense 3D grid of points, e.g. the finite-difference, finite-element and pseudospectral methods. The study of wavefield propagation with 3D finite-difference methods has contributed to a better understanding of wave-path effects and the response of complex structures. The approach using a staggered grid in finite-difference methods has the advantage of accuracy with less computational effort because it allows a larger grid size.
Visual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration

Visual and inertial sensors, in combination, are able to provide accurate motion estimates and are well suited for use in many robot navigation tasks. However, correct data fusion, and hence overall performance, depends on careful calibration of the rigid body transform between the sensors. Obtaining this calibration information is typically difficult and time-consuming, and normally requires additional equipment. In this paper we describe an algorithm, based on the unscented Kalman filter, for self-calibration of the transform between a camera and an inertial measurement unit (IMU). Our formulation rests on a differential geometric analysis of the observability of the camera—IMU system; this analysis shows that the sensor-to-sensor transform, the IMU gyroscope and accelerometer biases, the local gravity vector, and the metric scene structure can be recovered from camera and IMU measurements alone. While calibrating the transform we simultaneously localize the IMU and build a map of the surroundings, all without additional hardware or prior knowledge about the environment in which a robot is operating. We present results from simulation studies and from experiments with a monocular camera and a low-cost IMU, which demonstrate accurate estimation of both the calibration parameters and the local scene structure.
Bagged ensembles of Support Vector Machines for gene expression data analysis

Extracting information from gene expression data is a difficult task, as these data are characterized by very high dimensional, small sized, samples and large degree of biological variability. However, a possible way of dealing with the curse of dimensionality is offered by feature selection algorithms, while variance problems arising from small samples and biological variability can be addressed through ensemble methods based on resampling techniques. These two approaches have been combined to improve the accuracy of Support Vector Machines (SVM) in the classification of malignant tissues from DNA microarray data. To assess the accuracy and the confidence of the predictions performed proper measures have been introduced. Presented results show that bagged ensembles of SVM are more reliable and achieve equal or better classification accuracy with respect to single SVM, whereas feature selection methods can further enhance classification accuracy.
Old technology meets new technology: complementarities, similarities, and alliance formation

Alliance formation is commonplace in many high-technology industries experiencing radical technological change, where established firms use alliances with new entrants to adapt to technological change, while new entrants benefit from the ability of established players to commercialize the new technology. Despite the prevalence of these alliances, we know little about how these firms choose to ally with specific firms given the range of possible partners they may choose from. This study explores factors that lead to alliance formation between pharmaceutical and biotechnology companies. We focus on the alliance tie as the unit of analysis and argue that dyadic complementarities and similarities directly influence alliance formation. We then introduce a contingency model in which the positive effect of complementarities and similarities on alliance formation is moderated by the age of the new technology firm. We draw theoretical attention to the intersection between levels of analysis, in particular, the intersection between dyadic and firm-level constructs. We find that a pharmaceutical and a biotechnology firm are more likely to enter an alliance based on complementarities when the biotechnology firm is younger. Another noteworthy contribution is the finding that proxies for broad capabilities appear to be at least as, if not more, effective in predicting alliance formation compared to fine-grained science and technology-related indicators, like patent cross citations or patent common citations. We conclude by suggesting that future studies on alliance formation need to take into account interactions across levels; for example, how dyadic capabilities interact with firm-level factors, and the advantages and disadvantages of more or less fine-grained measures of organizational capabilities.