Miracle-dz/UniFAR-FTUs huggingface dataset:
Formal Veriication of Combinational Circuits

With the increase in the complexity of present day systems, proving the correctness of a design has become a major concern. Simulation based methodologies are generally inadequate to validate the correctness of a design with a reasonable conndence. More and more designers are moving towards formal methods to guarantee the correctness of their designs. In this paper we survey some state-of-the-art techniques used to perform automatic veriication of combinational circuits. We classify the current approaches for combinational ver-iication into two categories: functional and structural. The functional methods consist of representing a circuit as a canon-ical decision diagram. Two circuits are equivalent if and only if their decision diagrams are equal. The structural methods consist of identifying related nodes in the circuit and using them to simplify the problem of veriication. We brieey describe some of the methods in both the categories and discuss their merits and drawbacks.
Polynomial Trajectory Planning for Quadrotor Flight

We explore the challenges of planning trajectories through complex environments for quadrotors. We use the RRT* algorithm to generate an initial route through a 3D environment and then construct a trajectory consisting of a sequence of polynomial spline segments to follow that route. We present a method of jointly optimizing polynomial path segments that is numerically stable for high-order polynomials and large numbers of segments, and is easily formulated for efficient sparse computation. Using a differentially flat representation of the quadrotor, these polynomial trajectories encode the complete dynamics of the vehicle and allow calculation of feed-forward control commands in closed form, eliminating the need to sample in a high-dimensional state space or carry out expensive dynamics simulations during planning. Our approach generates high-quality trajectories much faster than purely sampling-based kinodynamic planning methods, but sacrifices convergence to the global optimum. We demonstrate the performance of our algorithm by efficiently generating a trajectories through challenging indoor spaces and successfully traversing them at speeds up to 8m/s.
Context-aware intrusion alerts verification approach

Intrusion detection systems (IDSs) produce a massive number of intrusion alerts. A huge number of these alerts are false positives. Investigating false positive alerts is an expensive and time consuming process, and as such represents a significant problem for intrusion analysts. This shows the needs for automated approaches to eliminate false positive alerts. In this paper, we propose a novel alert verification and false positives reduction approach. The proposed approach uses context-aware and semantic similarity to filter IDS alerts and eliminate false positives. Evaluation of the approach with an IDS dataset that contains massive number of IDS alerts yields strong performance in detecting false positive alerts.
ArticleRank: a PageRank-based alternative to numbers of citations for analysing citation networks

Purpose – The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations.Design/methodology/approach – ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets – a citation network based on an early paper on webometrics, and a self‐citation network based on the 19 most cited papers in the Journal of Documentation – using citation data taken from the Web of Knowledge database.Findings – ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited .
Study on Iterative Regularization Method in Ultrasonic Imaging Reconstruction for Concrete's Testing

Demands for the non-destructive techniques (NDT) developing for concrete structures has greatly increased with the growing concern about the deteriorating condition of the World’s infrastructure. But traditional image reconstruction algorithms or other inspecting methods can only reconstruct qualitative images. In this paper, the modified landweber iterative regularization method was applied to reconstruct the imaging on ultrasonic traveling speed as to the concrete’s internal estimating. Experimental results show that this modified algorithm has stable reconstruction performance with high accuracy and anti-disturbance ability.
DELLY: structural variant discovery by integrated paired-end and split-read analysis

Motivation: The discovery of genomic structural variants (SVs) at high sensitivity and specificity is an essential requirement for characterizing naturally occurring variation and for understanding pathological somatic rearrangements in personal genome sequencing data. Of particular interest are integrated methods that accurately identify simple and complex rearrangements in heterogeneous sequencing datasets at single-nucleotide resolution, as an optimal basis for investigating the formation mechanisms and functional consequences of SVs. Results: We have developed an SV discovery method, called DELLY, that integrates short insert paired-ends, long-range mate-pairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution. DELLY is suitable for detecting copy-number variable deletion and tandem duplication events as well as balanced rearrangements such as inversions or reciprocal translocations. DELLY, thus, enables to ascertain the full spectrum of genomic rearrangements, including complex events. On simulated data, DELLY compares favorably to other SV prediction methods across a wide range of sequencing parameters. On real data, DELLY reliably uncovers SVs from the 1000 Genomes Project and cancer genomes, and validation experiments of randomly selected deletion loci show a high specificity. Availability: DELLY is available at www.korbel. embl.de/software.html Contact: tobias.rausch@embl.de
Design and Implementation of the POWER5 TM Microprocessor

offers significantly increased performance over previous POWER designs by incorporating simultaneous multithreading, an enhanced memory subsystem, and extensive RAS and power management support. The 276M transistor processor is implemented in 130nm silicon-on-insulator technology with 8-level of Cu metallization and operates at >1.5 GHz.
Decentralized multi-agent exploration with online-learning of Gaussian processes

Exploration is a crucial problem in safety of life applications, such as search and rescue missions. Gaussian processes constitute an interesting underlying data model that leverages the spatial correlations of the process to be explored to reduce the required sampling of data. Furthermore, multi-agent approaches offer well known advantages for exploration. Previous decentralized multi-agent exploration algorithms that use Gaussian processes as underlying data model, have only been validated through simulations. However, the implementation of an exploration algorithm brings difficulties that were not tackle yet. In this work, we propose an exploration algorithm that deals with the following challenges: (i) which information to transmit to achieve multi-agent coordination; (ii) how to implement a light-weight collision avoidance; (iii) how to learn the data's model without prior information. We validate our algorithm with two experiments employing real robots. First, we explore the magnetic field intensity with a ground-based robot. Second, two quadcopters equipped with an ultrasound sensor explore a terrain profile. We show that our algorithm outperforms a meander and a random trajectory, as well as we are able to learn the data's model online while exploring.
Tumor dormancy and oncogene addiction  

Cancer is caused by genetic changes that activate oncogenes or inactivate tumor suppressor genes. The repair or inactivation of mutant genes may be effective in the treatment of cancer. Indeed, drugs that target oncogenes can be effective in the treatment of cancer. However, it is still unclear why the inactivation of a single cancer‐associated gene would ever result in the elimination of tumor cells. In experimental transgenic mouse models the consequences of oncogene inactivation depend upon the genetic and cellular context. In some cases, oncogene inactivation results in the elimination of all or almost all tumor cells through apoptosis by the phenomenon described as oncogene addiction. In other cases, oncogene inactivation predominantly results in the terminal differentiation or cellular senescence of tumor cells. In yet others, oncogene inactivation results in the apparent loss of the neoplastic properties of tumor cells, which now appear and behave like normal cells; however, upon oncogene reactivation at least some of these cells rapidly recover their neoplastic phenotype. Thus, oncogene inactivation can result in a state of tumor dormancy. Hence, understanding when and how oncogene inactivation induces apoptosis, differentiation, and senescence within a tumor will be important when developing effective strategies for the treatment of cancer.
Lead User's theory adapted to services: Towards Service User's Toolkit

It makes no doubt that the development of innovative products benefits from being considered under the perspective of networks and communities. Lead User's theory (LUT) focused mainly on the process by which user innovation may be transformed into commercial product. However, when LUT methodology was proven successful for products such as scientific instrument, sports equipment or even medical instruments, very few experiences were reported for services. Thus, the specific contribution of the paper is to adapt lead user's theory and practice to the specific case of the intangible processes and services such as Banks, Call centers, etc., in the purpose of improving efficiency of innovative efforts. In a first theoretical part, the paper reviews service characteristics which prevent adoption of LUT methods. Four main factors are identified and investigated in details: intangibility, inseparability, process based aspects of services and investment cycle in services. Based on these analyses, the paper suggests a specific framework for applying LUT methodologies in the case of services. It details first recommendation on the way to select potential lead users. Then, it recommends the way lead users should be associated and involved so that potential innovation may be proposed. The concept of communities applied to services is proposed and discussed from managerial point of view. Perspective of further research is then detailed.
Liver pathology

This unique book provides detailed insight into a wealth of expert experience in liver pathology, with an in-depth review of the expertís analysis and diagnostic process supported by high-quality color photomicrographs and discussion of the diagnostic principles involved in evaluating these lesions. The diagnostic problems and cases selected show the wide range of specimens seen in liver pathology and address the difficult issues in diagnosis encountered in these lesions. Chapters and cases are authored by many of the leading experts and educators in liver pathology today.
Development of example-tracing tutors for teaching control systems performance fundamentals

Control systems performance is one the major subtopics taught in Automatic Control Systems introductory courses. Example-tracing tutors, a novel type of intelligent tutoring system (ITS), have been created in order to support the learning experience of mechatronics engineering students. A scoring system based on very well supported ITS design guidelines have led to the selection and successful prioritization of a relevant and general set of top ranked problems taken from a large initial problem space that was created by an exhaustive revision on imparted material in previous classes. Experiences on the advanced usage of the authoring tool and discussion about development issues are provided.
Trading-off Incrementality and Dynamic Restart of Multiple Solvers in IC3

This paper 1 addresses the problem of SAT solver performance in IC3, one of the major recent breakthroughs in Model Checking algorithms. Unlike other Bounded and Unbounded Model Checking algorithms, IC3 is characterized by numerous SAT solver queries on small sets of problem clauses. Besides algorithmic issues, the above scenario poses serious performance challenges for SAT solver configuratio n and tuning. As well known in other application fields, finding a good compromise between learning and overhead is key to performance. We address solver cleanup and restart heuristics, as well as clause database minimality, based on on-demand clause loading: transition relation clauses are loaded in solver b ased on structural dependency and phase analysis. We also compare different solutions for multiple specialized solvers, and we provide an experimental evaluation on benchmarks from the HWMCC suite. Though not finding a clear winner, the work outlines se veral potential improvements for a portfolio-based verification tool with multiple engines and tunings.
Audio Segmentation Using Di erent Time-Frequency Representations

A blind audio source separation technique for mono mixtures, composed of two noise-free instantaneously mixed audio sources, is presented. The separation is done by image segmentation of di erent time-frequency representa- tions. Therefore a mixture is transformed by the Short-Time Fourier Transform into time-frequency domain. The result- ing spectrogram image is used in log-amplitude or normal amplitude form and then segmented into significant areas. This areas are separately retransformed into time domain, and then grouped to segregate the source signals. The out- put results are rated by the improvement of SNR compared to the mixture.
Mining Frequent Induced Subtrees by Prefix-Tree-Projected Pattern Growth

Frequent subtree pattern mining is an important data mining problem with broad applications. Most existing algorithms, such as Apriori-like algorithms, are based on candidate-generation-and-test framework, except for Chopper and XSpanner [8]. Unfortunately, candidate pattern generation and test used in Apriori-like algorithms are always time and space consuming, and this is especially true when candidate patterns are numerous and large. To solve this problem, the technique of pattern growth was proposed by Han et al [6]. And the famous PrefixSpan algorithm was proposed for sequential pattern mining by Pei et al. in [7]. Along this line, in this paper, we propose a novel induced subtree mining algorithm, called PrefixTreeISpan (i.e. Prefix-Tree-projected Induced-Subtree pattern), which finds induced subtree patterns by growing the frequent prefix-trees. Thus, using divide and conquer, mining local length-1 frequent subtree patterns in Prefix- Tree-Projected database recursively will lead to the complete set of frequent patterns. Different from Chopper and XSpanner, PrefixTreeISpan is for mining induced subtree patterns and it does not need a checking process. Our performance study shows that PrefixTreeISpan has achieved good performance in both different large synthetic datasets and real datasets.
The Head of the Table: Marking the “Front” of An Object Is Tightly Linked with Selection

Objects in the world do not have a surface that can be objectively labeled the “front. ” We impose this designation on one surface of an object according to several cues, including which surface is associated with the most task-relevant information or the direction of motion of an object. However, when these cues are competing, weak, or absent, we can also flexibly assign one surface as the front. One possibility is that this assignment is guided by the location of the “spotlight” of selection, where the selected region becomes the front. Here we used an electrophysiological correlate to show a direct temporal link between object structure assignments and the spatial locus of selection. We found that when human participants viewed a shape whose front and back surfaces were ambiguous, seeing a given surface as front was associated with selectively attending to that location. In Experiment 1, this pattern occurred during directed rapid (every 1 s) switches in structural percepts. In Experiment 2, this pattern occurred during spontaneous reversals, from 900 ms before to 600 ms after the reported percept. These results suggest that the distribution of selective attention might guide the organization of object structure.
UV radiation induced DNA damage in marine viruses along a latitudinal gradient in the southeastern Pacific Ocean

UV radiation induced DNA damage (inferred from cyclobutane pyrimidine dimers, CPDs) in native marine virus communities was examined at 12 locations along a latitudinal transect from 41° S to 3° N in the southeastern Pacific Ocean. Surface waters were collected prior to sunrise each day and placed in UV transparent incubators kept at in situ seawater temperatures. A replicate treatment was prefiltered through a 0.2 µm filter to remove microbial host cells. Both treatments were exposed to ambient solar radiation until approximately 1 h before sunset. At the end of the day, the virus fraction was collected from each sample by filtration and concentration. DNA damage was determined in each fraction and compared to DNA damage in pre-dawn samples as well as DNA dosimeters exposed to an entire solar day's influence. CPDs in dosimeters and integrated solar irra- diance were very highly correlated, as was DNA damage in the pre-sunrise virus community and latitude. A reduction in host cell abundance resulted in no consistent pattern or change in the CPD induction of virus particles, suggesting minimal host mediated repair in this natural virus community. The low daily induction of damage in virus incubations combined with the high residual damage suggests that the sunrise damage levels were the result of DNA damage accumulation over numer- ous days, indicating a long residence time for virus particles in surface waters in this region.
Copy Number Variations in Alternative Splicing Gene Networks Impact Lifespan

Longevity has a strong genetic component evidenced by family-based studies. Lipoprotein metabolism, FOXO proteins, and insulin/IGF-1 signaling pathways in model systems have shown polygenic variations predisposing to shorter lifespan. To test the hypothesis that rare variants could influence lifespan, we compared the rates of CNVs in healthy children (0–18 years of age) with individuals 67 years or older. CNVs at a significantly higher frequency in the pediatric cohort were considered risk variants impacting lifespan, while those enriched in the geriatric cohort were considered longevity protective variants. We performed a whole-genome CNV analysis on 7,313 children and 2,701 adults of European ancestry genotyped with 302,108 SNP probes. Positive findings were evaluated in an independent cohort of 2,079 pediatric and 4,692 geriatric subjects. We detected 8 deletions and 10 duplications that were enriched in the pediatric group (P = 3.33×10−8–1.6×10−2 unadjusted), while only one duplication was enriched in the geriatric cohort (P = 6.3×10−4). Population stratification correction resulted in 5 deletions and 3 duplications remaining significant (P = 5.16×10−5–4.26×10−2) in the replication cohort. Three deletions and four duplications were significant combined (combined P = 3.7×10−4−3.9×10−2). All associated loci were experimentally validated using qPCR. Evaluation of these genes for pathway enrichment demonstrated ∼50% are involved in alternative splicing (P = 0.0077 Benjamini and Hochberg corrected). We conclude that genetic variations disrupting RNA splicing could have long-term biological effects impacting lifespan.
Loneliness and Solitude in Education: How to Value Individuality and Create an Enstatic School

Analysing loneliness and solitude in schools and exploring how to deal with them is a vital task. In recent research for the author’s Spirit of the School project, a number of pupils, teachers and headteachers described times when they felt lonely and times when they felt the need for healthy solitude. The causes of loneliness are numerous and its consequences have a significant unrecognised impact on education. How do schools deal with people when they are lonely, and how can they overcome loneliness? How can they create opportunities for healthy solitude, a welcome alternative to loneliness? Schools can sometimes try to include people by being intensely social, but end up making them feel even more excluded. A school that teaches solitude well and helps individuals deal with loneliness can be called an ‘enstatic’ school: a school in which people are comfortable within themselves. The objective of this book – the first comprehensive study of the subject – is to help us all understand loneliness and solitude and thereby to reinvigorate debates on personal, character and values education.
Can the Color Red Improve Men's Perceived Mate Value? Examining the Interactive Effects of Facial Masculinity and Color on Female Evaluation of Potential Mates

We manipulated facial masculinity (masculine-morph/feminine-morph) and color (red/white) through two independent studies—one in-lab at the University of Dayton and one online using Amazon’s MTurk—to examine its effect on social status and attractiveness for men when rated by women. We specifically aimed to see if the color red could serve a compensatory effect for feminine-faced men, who were least likely to be found attractive by women at peak fertility. When paired with red, women rated the masculine and feminine faces higher in social status. Through this increase in social status, the color red was also able to indirectly increase the physical attractiveness of the men. Additionally, the sensitivity to the color red was predicted by conception risk, such that women closer to peak fertility were most attentive of the color red. Acknowledgements An enormous debt of gratitude is owed to the University of Dayton Honors Program, as well as the University of Dayton Psychology department, for the generous funding provided for this project’s research and presentation at the Society of Personality and Social Psychology annual conference. In addition, this project’s completion would not have been possible without the guidance, patience, and continuous mentorship of Dr. Erin O’Mara.
HPF Analysis and Code Generation using Integer Sets

The core of the Rice dHPF compiler for High Performance Fortran is a practical, executable, equa-tional framework for data parallel program analysis and optimization. This framework, based on abstract operations on sets of integers, greatly simpliies the implementation of many key analysis, optimization and code generation tasks (even with a general computation partitioning model), and yet enhances their generality and exibility. This paper describes the equational framework, tradeoos in its implementation, the formulation and implementation of important analyses and optimizations within the framework, and a hierarchical code generation strategy to support the framework.