Miracle-dz/UniFAR-FTUs huggingface dataset:
Circuit-level delay modeling considering both TDDB and NBTI

With aggressive scaling down of the technology node, the time-dependent dielectric breakdown (TDDB) and negative biased temperature instability (NBTI) are becoming key challenges for circuit designers. Both TDDB and NBTI significantly degrade the electrical characteristic of the CMOS devices. A delay model considering TDDB and NBTI is proposed in this paper. The output degradation of the breakdown gate is considered in circuit-level delay analysis. Traditionally, it is considered the TDDB degradation always degrades the circuit delay. However, this paper shows the TDDB effect may boost up the circuit speed. The spatial correlation of TDDB effect is also demonstrated in this paper and shows the difference of 40% in circuit delay depending on the location of the breakdown gate in the signal path.
The Asymptotic Bit Error Probability of LDPC Codes for the Binary Erasure Channel with Finite Iteration Number

We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is well known that a difference between the bit error probability at finite iteration number for finite block length $n$ and for infinite block length is asymptotically $\alpha/n$, where $\alpha$ is a specific constant depending on the degree distribution, the iteration number and the erasure probability. Our main result is to derive an efficient algorithm for calculating $\alpha$ for regular ensembles. The approximation using $\alpha$ is accurate for $(2,r)$-regular ensembles even in small block length.
Finding good optimization sequences covering program space

The compiler optimizations we enable and the order in which we apply them on a program have a substantial impact on the program execution time. Compilers provide default optimization sequences which can give good program speedup. As the default sequences have to optimize programs with different characteristics, they embed in them multiple subsequences which can optimize different classes of programs. These multiple subsequences may falsely interact with each other and affect the potential program speedup achievable. Instead of searching for a single universally optimal sequence, we can construct a small set of good sequences such that for every program class there exists a near-optimal optimization sequence in the good sequences set. If we can construct such a good sequences set which covers all the program classes in the program space, then we can choose the best sequence for a program by trying all the sequences in the good sequences set. This approach completely circumvents the need to solve the program classification problem. Using a sequence set size of around 10 we got an average speedup up to 14% on PolyBench programs and up to 12% on MiBench programs. Our approach is quite different from either the iterative compilation or machine-learning-based prediction modeling techniques proposed in the literature so far. We use different training and test datasets for cross-validation as against the Leave-One-Out cross-validation technique.
A Gradient‐Based Comparison Measure for Visual analysis of Multifield Data

We introduce a multifield comparison measure for scalar fields that helps in studying relations between them. The comparison measure is insensitive to noise in the scalar fields and to noise in their gradients. Further, it can be computed robustly and efficiently. Results from the visual analysis of various data sets from climate science and combustion applications demonstrate the effective use of the measure.
A Theory of C-Style Memory Allocation ?

This paper introduces the theory TH for reasoning about the correctness of memory access operations in the context of a C-style heap memory. The proposed approach makes a clear distinction between reasoning about the values stored in memory and checking whether access to a specific memory location is allowed. The theory provides support for malloc and free and is presented in the form of axioms that can be converted into conditional rewrite rules. It is also shown how TH can be used in a bounded model checker for C programs.
Atrial extrasystoles after exercise predict atrial fibrillation in patients with left ventricular hypertrophy

Prediction of atrial fibrillation (AF) is usually based on anatomical and functional characterisation of the atrial substrate, such as left atrial diameter, ejection fraction, and P wave duration.1 In this respect, triggers such as atrial extrasystoles are often neglected.2 Atrial extrasystoles may occur during or shortly after exercise as a result of acute atrial stretch, especially in patients with left ventricular hypertrophy (LVH) and diastolic dysfunction. As LVH may induce the atrial substrate and atrial extrasystoles are the trigger for AF, we reasoned that these exercise induced atrial extrasystoles may predict AF in patients with LVH. Patients with LVH (interventricular septal diameter ⩾ 11 mm) and ejection fraction ⩾ 55% who underwent an exercise test between 1994 and 2004 were studied. Patients with prior AF or flutter or pacemaker rhythm, patients without at least one follow up ECG, and those with an incomplete exercise test were excluded. Of 864 screened patients 258 were selected. The exercise tests (Case Exercise Testing System; GE Medical Systems, Milwaukee, USA) were performed according to standard protocols.3 Each test was manually reviewed for atrial extrasystoles and supraventricular tachycardia (SVT; three or more consecutive supraventricular extrasystoles). Follow up ECG data were retrieved from an electronic storage system containing all ECGs recorded in our institution since 1994. The follow up period lasted from the date of the exercise test …
Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large‐scale analysis of 14 published GWAS datasets in the DRIVE study

A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta‐analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis‐driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta‐analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM‐ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03–1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89–0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03–1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90–0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08–1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM‐ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10−22, respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.
Strong authentication using dynamic hashing and steganography

Now a day's online services became part of our life which performs communication digitally. This digital communication needs confidentiality and data integrity to protect from unauthorized use. Security can be provided by using two popular methods cryptography and steganography. Cryptography scrambles the message so that it cannot be understood, where as the steganography hides the message in another medium which cannot be detected by normal human eye. This paper introduces a technique which provides high security to the digital communication by using dynamic hashing for integrity and also embedding the data in image file using steganography to misguide attacker. There by providing high security for the communication between two parties.
Routing for concurrent video sessions in ad hoc networks

In this paper, we consider the problem of how to optimally support multiple concurrent video sessions in an ad hoc network. Specifically, we present a framework on modeling the end-to-end video distortion as a function of routing layer behavior. Our formulation seamlessly integrates the interactions of competing video flows and network layer performance metrics, thus allowing optimal utilization of network resource. We describe a detailed solution procedure based on genetic algorithms (GAs), which allows joint determination of near-optimal routes and rates for the video sessions. We also present a greedy heuristic algorithm that can produce near-optimal solutions and speed up the GA computation. Through simulation results, we demonstrate the superior performance of the GA-based approach.
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures

Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on the expectation-maximization algorithm, the maximum likelihood estimates of the model parameters can be iteratively computed in an elegant way. Unfortunately, in some cases the algorithm is not converging properly because of numerical difficulties. They are of two kinds: they can be associated to outliers or to repeated data samples. In this paper, we trace and discuss their origin while providing some theoretical evidence. As a matter of fact, both can be explained by the concept of isolation, which is leading to the width of the collapsing mixture component to become zero.
Edinburgh Research Explorer Attacking Group Multicast Key Management Protocol using CORAL

This paper describes the modelling of a two multicast group key management protocols in a ﬁrst-order inductive model, and the discovery of previously unknown attacks on them by the automated inductive counterexample ﬁnder C ORAL . These kinds of protocols had not been analysed in a scenario with an active intruder before. C ORAL proved to be a suitable tool for a job because, unlike most automated tools for discovering attacks, it deals directly with an open-ended model where the number of agents and the roles they play are unbounded. Additionally, C ORAL ’s model allows us to reason explicitly about lists of terms in a message, which proved to be essential for modelling the second protocol. In the course of the case studies, we also discuss other issues surrounding multicast protocol analysis, including identifying the goals of the protocol with respect to the intended trust model, modelling of the control conditions, which are considerably more complex than for standard two and three party protocols, and effective searching of the state space generated by the model, which has a much larger branching rate than for standard protocols.
Comparison of Transmission Performances for CO-SCFDE and CO-OFDM Systems

Single-carrier (SC) and multicarrier (MC) transmissions have emerged as two competitive technologies for long-haul coherent optical fiber transmission systems. In this letter, we compare chromatic dispersion (CD) and nonlinearity tolerances for coherent optical SC frequency-domain-equalization and SC orthogonal frequency-division-multiplexing systems. We establish the simulation systems employing the same structures of transmitter and receiver, the same structure of frame, and almost the same frequency-domain equalization method except the inverse fast Fourier transform processing. Both CD tolerance and nonlinear transmission performance in single-channel and wavelength-division-multiplexing scenarios are investigated. The comparison can reveal the difference of SC and MC transmissions.
An autonomous sensor-based path-planner for planetary microrovers

With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. This paper reviews issues which are critical for successful autonomous navigation of planetary rovers. We report on the "Wedgebug" algorithm for planetary rover navigation. This algorithm is complete, correct, requires minimal memory for storage of its world model, and uses only on-board sensors, which are guided by the algorithm to efficiently sense only the data needed for motion planning. The implementation of a version of Wedgebug on the Rocky7 Mars rover prototype at the Jet Propulsion Laboratory is described, and experimental results from operation in simulated martian terrain are presented.
Taking advantage of design patterns in GIS domain (poster session)

Geographic Information Systems (GIS) are used to collect, store, analyze and present information describing physical and logical aspects of real world entities. They deal with several areas, such as georeferencing, topology, visualization, representation of continuous information and so on. Most of GIS applications are hardly adapted to new requirements, like changing of the reference system, integrating vector and raster models, or handling continuous information, among others. This work presents an pattern driven architecture for building GIS applications. The result is a framework that is focused on flexibility and adaptability features.
Improved Integer Programming Models and Heuristic Search for AI Planning

Motivated by the requirements of many real-life applications, recent research in AI planning has shown a growing interest in tackling problems that involve numeric constraints and complex optimization objectives. Applying Integer Programming (IP) to such domains seems to have a significant potential, since it can naturally accommodate their representational requirements. In this paper we explore the area of applying IP to AI planning in two different directions. First, we improve the domain-independent IP formulation of Vossen et al., by an extended exploitation of mutual exclusion relations between the operators, and other information derivable by state of the art domain analysis tools. This information may reduce the number of variables of an IP model and tighten its constraints. Second, we link IP methods to recent work in heuristic search for planning, by introducing a variant of {\tt FF}'s enforced hill-climbing algorithm that uses IP models as its underlying representation. In addition to extending the delete lists heuristic to parallel planning and the more expressive language of IP, we also introduce a new heuristic based on the linear relaxation.
Analysing performance of SLEUTH model calibration using brute force and genetic algorithm–based methods

Abstract Present study is aimed to compare the performance of SLEUTH model from two different calibration methods, that is, brute force and GA in term of computational efficiency of calibration processes, capturing urban growth, a form of growth or growth pattern and its spatial distribution. SLEUTH has been parameterized for Ajmer city (India) and its performance has been compared in term of eight parameters/methods, that is, computational efficiency, model fitness that is, OSM, urban shape index, best fit coefficient values, hit-miss-false alarm method, kappa statistics, accuracy percentage and visual analysis. GA-based calibration has been found to be computationally more efficient and relatively better in capturing urban growth and form of growth as compared to brute force. Brute force calibration seems to be slightly better considering urban hits as compared to GA, however, GA is better with respect to lesser false alarms.
Investigating Mitochondrial Redox Potential with Redox-sensitive Green Fluorescent Protein Indicators*

Current methods for determining ambient redox potential in cells are labor-intensive and generally require destruction of tissue. This precludes single cell or real time studies of changes in redox poise that result from metabolic processes or environmental influences. By substitution of surface-exposed residues on the Aequorea victoria green fluorescent protein (GFP) with cysteines in appropriate positions to form disulfide bonds, reduction-oxidation-sensitive GFPs (roGFPs) have been created. roGFPs have two fluorescence excitation maxima at about 400 and 490 nm and display rapid and reversible ratiometric changes in fluorescence in response to changes in ambient redox potential in vitro and in vivo. Crystal structure analyses of reduced and oxidized crystals of roGFP2 at 2.0- and 1.9-Å resolution, respectively, reveal in the oxidized state a highly strained disulfide and localized main chain structural changes that presumably account for the state-dependent spectral changes. roGFP1 has been targeted to the mitochondria in HeLa cells. Fluorometric measurements on these cells using a fluorescence microscope or in cell suspension using a fluorometer reveal that the roGFP1 probe is in dynamic equilibrium with the mitochondrial redox status and responds to membrane-permeable reductants and oxidants. The roGFP1 probe reports that the matrix space in HeLa cell mitochondria is highly reducing, with a midpoint potential near -360 mV (assuming mitochondrial pH ∼8.0 at 37 °C). In other work (C. T. Dooley, T. M. Dore, G. Hanson, W. C. Jackson, S. J. Remington, and R. Y. Tsien, submitted for publication), it is shown that the cytosol of HeLa cells is also unusually reducing but somewhat less so than the mitochondrial matrix.
Cooperative Selection Diversity with CSI-Based Amplify-and-Forward Relaying in Nakagami-m Fading Channels

We derive new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with amplify-and-forward (AF) transmission using channel-state-information (CSI)-based gain relaying. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n. d. Rayleigh fading as a special case. We highlight the impact of the m fading parameter on the SER performance in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.
Ethylene Role in Plant Growth, Development and Senescence: Interaction with Other Phytohormones

The complex juvenile/maturity transition during a plant’s life cycle includes growth, reproduction, and senescence of its fundamental organs: leaves, flowers, and fruits. Growth and senescence of leaves, flowers, and fruits involve several genetic networks where the phytohormone ethylene plays a key role, together with other hormones, integrating different signals and allowing the onset of conditions favorable for stage progression, reproductive success and organ longevity. Changes in ethylene level, its perception, and the hormonal crosstalk directly or indirectly regulate the lifespan of plants. The present review focused on ethylene’s role in the development and senescence processes in leaves, flowers and fruits, paying special attention to the complex networks of ethylene crosstalk with other hormones. Moreover, aspects with limited information have been highlighted for future research, extending our understanding on the importance of ethylene during growth and senescence and boosting future research with the aim to improve the qualitative and quantitative traits of crops.
Detection of underwater objects based on machine learning

Side-scan and forward-looking sonars are some of the most widely used imaging systems for obtaining large scale images of the seafloor, and their use continues to expand rapidly with their increased deployment on autonomous underwater vehicles. However, it is difficult to extract quantitative information from the images generated from these processes, particularly for the detection and extraction of information on the objects within these images. We propose in this paper an algorithm for automatic detection of underwater objects in side-scan images based on machine learning employing adaptive boosting. Experimental results show that the method produces consistent maps of the seafloor.
Multiplex Structures: Patterns of Complexity in Real-World Networks

Complex network theory aims to model and analyze complex systems that consist of multiple and interdependent components. Among all studies on complex networks, topological structure analysis is of the most fundamental importance, as it represents a natural route to understand the dynamics, as well as to synthesize or optimize the functions, of networks. A broad spectrum of network structural patterns have been respectively reported in the past decade, such as communities, multipartites, hubs, authorities, outliers, bow ties, and others. Here, we show that most individual real-world networks demonstrate multiplex structures. That is, a multitude of known or even unknown (hidden) patterns can simultaneously situate in the same network, and moreover they may be overlapped and nested with each other to collaboratively form a heterogeneous, nested or hierarchical organization, in which different connective phenomena can be observed at different granular levels. In addition, we show that the multiplex structures hidden in exploratory networks can be well defined as well as effectively recognized within an unified framework consisting of a set of proposed concepts, models, and algorithms. Our findings provide a strong evidence that most real-world complex systems are driven by a combination of heterogeneous mechanisms that may collaboratively shape their ubiquitous multiplex structures as we observe currently. This work also contributes a mathematical tool for analyzing different sources of networks from a new perspective of unveiling multiplex structures, which will be beneficial to multiple disciplines including sociology, economics and computer science.
Case Study in Hebrew Character Searching

Searching for a letter or a word in historical documents is a practical challenge due to the various degradations present in such documents and the wide variance of handwriting. Searching in historical Hebrew documents is somewhat harder because of high similarities among Hebrew characters. In order to determine the features and their combinations appropriate for recognizing Hebrew script, we study a range of known features using a Dynamic Time Warping algorithm. In addition we describe a novel meth od for feature-based searching, which uses a number of models for the same character. This method is based on our original DTW algorithm that can match fragments of several models of the same character to match a query character. Consequently, we are not limited to any particular model of the character set. Application of this method leads to a significant improvement, even when using a small set of models.