Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Scan-Based BIST Scheme for Low Power Testing of VLSI Chips

It is seen that power dissipation during test mode is quite high compared to that during the functional mode of operation of a digital circuit. This may lead to damage of certain chips only because they are tested, leading to unnecessary loss of yield. This paper presents a simple yet efficient low power scheme for scan-based BIST. It reduces test length and switching-activity in CUTs reducing power dissipation during test mode without compromising fault coverage. Experiments conducted on ISCAS89 benchmark circuits demonstrate that proposed scheme gives better fault coverage with a large reduction in transitions reducing power dissipation during testing
Composite Learning From Adaptive Dynamic Surface Control

In the conventional adaptive control, a stringent condition named persistent excitation (PE) must be satisfied to guarantee parameter convergence. This technical note focuses on adaptive dynamic surface control for a class of strict-feedback nonlinear systems with parametric uncertainties, where a novel technique coined composite learning is developed to guarantee parameter convergence without the PE condition. In the composite learning, online recorded data together with instantaneous data are applied to generate prediction errors, and both tracking errors and prediction errors are utilized to update parametric estimates. The proposed approach is also extended to an output-feedback case by using a nonlinear separation principle. The distinctive feature of the composite learning is that parameter convergence can be guaranteed by an interval-excitation condition which is much weaker than the PE condition such that the control performance can be improved from practical asymptotic stability to practical exponential stability. An illustrative example is used for verifying effectiveness of the proposed approach.
Junta distributions and the average-case complexity of manipulating elections

Encouraging voters to truthfully reveal their preferences in an election has long been an important issue. Previous studies have shown that some voting protocols are hard to manipulate, but predictably used NP-hardness as the complexity measure. Such a worst-case analysis may be an insufficient guarantee of resistance to manipulation.Indeed, we demonstrate that NP-hard manipulations may be tractable in the average-case. For this purpose, we augment the existing theory of average-case complexity with new concepts; we consider elections distributed with respect to junta distributions, which concentrate on hard instances, and introduce a notion of heuristic polynomial time. We use our techniques to prove that a family of important voting protocols is susceptible to manipulation by coalitions, when the number of candidates is constant.
Large neotheropods from the Upper Triassic of North America and the early evolution of large theropod body sizes

Abstract Large body sizes among nonavian theropod dinosaurs is a major feature in the evolution of this clade, with theropods reaching greater sizes than any other terrestrial carnivores. However, the early evolution of large body sizes among theropods is obscured by an incomplete fossil record, with the largest Triassic theropods represented by only a few individuals of uncertain ontogenetic stage. Here I describe two neotheropod specimens from the Upper Triassic Bull Canyon Formation of New Mexico and place them in a broader comparative context of early theropod anatomy. These specimens possess morphologies indicative of ontogenetic immaturity (e.g., absence of femoral bone scars, lack of co-ossification between the astragalus and calcaneum), and phylogenetic analyses recover these specimens as early-diverging neotheropods in a polytomy with other early neotheropods at the base of the clade. Ancestral state reconstruction for body size suggests that the ancestral theropod condition was small (~240 mm femur length), but the ancestral neotheropod was larger (~300–340 mm femur length), with coelophysoids experiencing secondary body size reduction, although this is highly dependent on the phylogenetic position of a few key taxa. Theropods evolved large body sizes before the Triassic–Jurassic extinction, as hypothesized in most other ancestral state reconstructions of theropod body sizes, but remained rare relative to smaller theropods until the Jurassic.
Absolute dimensions of detached eclipsing binaries – I. The metallic‐lined system WW Aurigae

WWAurigae is a detached eclipsing binary composed of two metallic-lined A-type stars orbiting each other every 2.5 days. We have determined the masses and radii of both components to accuracies of 0.4% and 0.6%, respectively. From a cross-correlation analysis of high-resolution spectra we find masses of 1.964±0.007M⊙ for the primary star and 1.814±0.007M⊙ for the secondary star. From an analysis of photoelectric uvby and UBV light curves we find the radii of the stars to be 1.927±0.011R⊙ and 1.841± 0.011R⊙, where the uncertainties have been calculated using a Monte Carlo algorithm. Fundamental effective temperatures of the two stars have been derived, using the Hipparcos parallax of WWAur and published ultraviolet, optical and infrared fluxes, and are 7960±420 and 7670±410K. The masses, radii and effective temperatures of WWAur are only matched by theoretical evolutionary models for a fractional initial metal abundance, Z, of approximately 0.06 and an age of roughly 90Myr. This seems to be the highest metal abundance inferred for a well-studied detached eclipsing binary, but we find no evidence that it is related to the metallic-lined nature of the stars. The circular orbit of WWAur is in conflict with the circularization timescales of both the Tassoul and the Zahn tidal theories and we suggest that this is due to pre-mainsequence evolution or the presence of a circular orbit when the stars were formed.
VARIATION IN THE GROUP-SPECIFIC CARBOHYDRATE OF GROUP A STREPTOCOCCI

The phenomenon of apparent loss of group-specific carbohydrate in the course of mouse passage of group A streptococci has been subjected to further study, and several additional variants showing this property have been described. The loss of group reactivity is shown to be due to an alteration in the chemical structure and serological specificity of the cell wall carbohydrate. This alteration appears to be essentially the same in each of the variants available for study. The carbohydrate of the variant strains (V) contains the same two monosaccharide components as the group A carbohydrate (A), but they are present in different proportions. Precipitating sera reactive with V carbohydrate have been prepared, and the A and V carbohydrates have been compared by qualitative and quantitative precipitin analysis. A second type of variation has been encountered during mouse passage. This variation is characterized by the occurrence of a cell wall carbohydrate (I) intermediate in chemical and serological properties between the A and V carbohydrates. The I carbohydrate reacts with both A and V antisera and does not appear to be a simple mixture of A and V carbohydrate. Similarly, antisera against the intermediate strain contain antibodies reactive with both A and V carbohydrates, and evidence is presented indicating that in part this represents antibody with double specificity.
Survey and Classiﬁcation of Head-Up Display Presentation Principles

With increasing size of Head-Up Displays and sensor technology Augmented Reality gains the potential to be used in automotive environments. Head-Up Displays provide a third dimension for information presentation. The increased dimensionality and the fact that the display space contains the outside environment which is essential for safe driving generates new opportunities for information presentation but also new issues. This paper collects the common principles for information presentation in the Head-Up Display and classiﬁes these in according dimensions. Pair-wise combinations of the classes are used to illustrate examples for presentation concepts. Awareness about the di ﬀ erent concepts and their underlying principles enables avoiding potential cross-relationships between multiple dimensions and thus enables unique attributing of e ﬀ ects in user studies.
A new metric on the manifold of kernel matrices with application to matrix geometric means

Symmetric positive definite (spd) matrices pervade numerous scientific disciplines, including machine learning and optimization. We consider the key task of measuring distances between two spd matrices; a task that is often nontrivial whenever the distance function must respect the non-Euclidean geometry of spd matrices. Typical non-Euclidean distance measures such as the Riemannian metric δR(X, Y) = ||log(Y-1/2XY-1/2)||F, are computationally demanding and also complicated to use. To allay some of these difficulties, we introduce a new metric on spd matrices, which not only respects non-Euclidean geometry but also offers faster computation than δR while being less complicated to use. We support our claims theoretically by listing a set of theorems that relate our metric to δR(X, Y), and experimentally by studying the nonconvex problem of computing matrix geometric means based on squared distances.
Adaptive state space representations enabling reliable and robust decision-making in asynchronous drives for mechatronic applications

In contemporary mechatronic applications decision-making is often based on information about the underlying model governing the dynamical evolution, in order to ensure optimal operation with respect to a prioritized objective. Modeling errors stemming from parameter uncertainty or varying operational conditions result in inevitable deviations from the theoretical estimate and consequently in suboptimal operation. Intelligent systems need to be equipped with inherent means to compensate for these a priori unknown discrepancies, hereby guaranteeing a robust operation in uncertain environments. In this manuscript, advanced filtering techniques are applied to assess both an optimal model representation and state estimates. An appropriate interconnection between both model and state estimation is determined. The proposed methodology is demonstrated for an electric drive, embodying a DC-source, a voltage source inverter (VSI) and an asynchronous machine, as the presence of discrete switching sequences and physical constraints introduces additional challenges. Results prove that the error on the state estimates can be improved by 92.7–97.2%, outperforming the classical estimation techniques, while the relative model mismatch is scaled down to 0.03%, even in highly demanding scenarios. The introduced strategy thus enables high-fidelity virtual sensing and reliable decision-making procedures for advanced asynchronous drives when modeling errors can be anticipated.
Self-Guided Supramolecular Cargo-Loaded Nanomotors with Chemotactic Behavior towards Cells

Delivery vehicles that are able to actively seek and precisely locate targeted tissues using concentration gradients of signaling molecules have hardly been explored. The directed movement toward specific cell types of cargo-loaded polymeric nanomotors along a hydrogen peroxide concentration gradient (chemotaxis) is reported. Through self-assembly, bowl-shaped poly(ethylene glycol)-b-polystyrene nanomotors, or stomatocytes, were formed with platinum nanoparticles entrapped in the cavity while a model drug was encapsulated in the inner compartment. Directional movement of the stomatocytes in the presence of a fuel gradient (chemotaxis) was first demonstrated in both static and dynamic systems using glass channels and a microfluidic flow. The highly efficient response of these motors was subsequently shown by their directional and autonomous movement towards hydrogen peroxide secreting neutrophil cells.
DPiSAX: Massively Distributed Partitioned iSAX

Indexing is crucial for many data mining tasks that rely on efficient and effective similarity query processing. Consequently, indexing large volumes of time series, along with high performance similarity query processing, have became topics of high interest. For many applications across diverse domains though, the amount of data to be processed might be intractable for a single machine, making existing centralized indexing solutions inefficient. We propose a parallel indexing solution that gracefully scales to billions of time series, and a parallel query processing strategy that, given a batch of queries, efficiently exploits the index. Our experiments, on both synthetic and real world data, illustrate that our index creation algorithm works on 1 billion time series in less than 2 hours, while the state of the art centralized algorithms need more than 5 days. Also, our distributed querying algorithm is able to efficiently process millions of queries over collections of billions of time series, thanks to an effective load balancing mechanism.
A specialist’s audit of aggregated occurrence records: An ‘aggregator’s’ perspective

Abstract A recent ZooKeys’ paper (Mesibov, 2013: http://www.pensoft.net/journal_home_page.php? journal_id=1&page=article&SESID=df7bcb35b02603283dcb83ee0e0af0c9&type=show&article_id=5111) has highlighted data quality issues in aggregated data sets, but did not provide a realistic way to address these issues. This paper provides an aggregator’s perspective including ways that the whole community can help to address data quality issues. The establishment of GBIF and national nodes (national aggregators) such as the Atlas of Living Australia (ALA) have integrated and exposed a huge diversity of biological observations along with many associated issues. Much of the admirable work by Mesibov (2013) was enabled by having the data exposed. Data quality, one of the highest priorities for GBIF, the national nodes and other aggregators, depends on both automatic methods and community experts to detect and correct data issues. Not all issues can however be automatically detected or corrected, so community assistance is needed to help improve the quality of exposed biological data. We do need to improve the infrastructure and associated processes to more easily identify data issues and document all changes to ensure a full record is permanently and publicly available.
Apoptosis Signaling Pathway Bid Cleavage and Activation of Mitochondria TRAIL-Mediated Apoptosis by Enhancing Hepatitis C Virus Core Protein Modulates

Hepatitis C virus (HCV) is a major human pathogen causing chronic liver disease, which leads to cirrhosis of liver and hepatocellular carcinoma. The HCV core protein, a viral nucleocapsid, has been shown to affect various intracellular events, including cell proliferation and apoptosis. However, the precise mechanisms of the effects are not fully understood. In this study, we show that HCV core protein sensitizes human hepatocellular carcinoma cell line, Huh7, conferred sensitivity to TRAIL-, but not Fas ligand-mediated apoptosis. Huh7 cells are resistant to TRAIL, despite the induction of caspase-8 after TRAIL engagement. However, HCV core protein induces TRAIL apoptosis signaling via sequential induction of caspase-8, Bid cleavage, activation of mitochondrial pathway, and effector caspase-3. HCV core protein also induces activation of caspase-9 after TRAIL engagement, and the induction of TRAIL sensitivity by HCV core protein could be reversed by caspase-9 inhibitor. Therefore, the HCV core protein-induced TRAIL-mediated apoptosis is dependent upon activation of caspase-8 downstream pathway to convey the death signal to mitochondria, leading to activation of mitochondrial signaling pathway and breaking the apoptosis resistance. These results combined indicate that the HCV core protein enhances TRAIL-, but not Fas ligand-mediated apoptotic cell death in Huh7 cells via a mechanism dependent on the activation of mitochondria apoptosis signaling pathway. These results suggest that HCV core protein may have a role in immune-mediated liver cell injury by modulation of TRAIL-induced apoptosis. The Journal of Immunology, 2005, 174: 2160–2166. superfamily member strong homology FasL, capable of inducing apoptosis in a variety of transformed cell lines in vitro but usually not in normal primary cells. It was shown recently that T cells can kill target cells via TRAIL/TRAIL receptor interaction suggesting that TRAIL might serve as a cytotoxic effector molecule in activated T cells in vivo. In addition to its role in inducing apoptosis by binding to DRs, TRAIL itself can stimulate T cell after TCR engagement and augment IFN- (cid:4) secretion These ﬁnd-ings led us to hypothesize that TRAIL/TRAIL receptor interaction is involved in the interaction between inﬁltrating T cells and hepatocytes during HCV infection. In this study, we report that overexpression of HCV core protein sensitizes human HCC cell line, Huh7, conferred sensitivity to TRAIL-, but not FasL-mediated apoptosis. These results indicate that the HCV core protein enhances TRAIL-mediated apoptotic cell death in Huh7 cell via a mechanism dependent on the activation of mitochondrial apoptosis signaling pathway. The results suggest that HCV core protein may have a role in immune-mediated liver cell injury.
Governance and Educational Expectations in the U.S. States

This article analyzes the relationship between U.S. state governance and policies designed to enhance educational expectations. It examines three policy areas: state participation in voluntary National Assessment of Educational Progress testing, state testing requirements for new teachers, and state high school graduation requirements in math and science. In general, it identifies associations between state institutional and political characteristics and the state policies under study. In particular, state policies that impose higher demands on local school districts are more likely to be present in states with more centralized control of their K–12 systems. Furthermore, state partisanship appears to suggest that Republicans favor policies that push power to lower levels of the U.S. intergovernmental system.
MobiVMM: a virtual machine monitor for mobile phones

Mobile phones have evolved into complex systems as they have more and more new applications built-in. As a result, they are less reliable and less secure than before. Virtual Machine Monitors (VMM) or hypervisors have been introduced to help the reliability and security of mobile phones but the existing research does not completely address three issues critical to mobile phones: real-time support, resource limitation, and power efficiency. In this paper we propose building a new VMM called MobiVMM for mobile phones to deal with these issues. MobiVMM enables real-time support using priority based scheduling and a pseudo-polling mechanism. Resource and power efficiency is achieved through light-weight design and implementation, highly customized guest operating systems, and a virtual hardware abstraction layer. We present our design considerations and report some preliminary experimental results based on the OMAP 2430 development platform.
Choosing to Co-Finance - an Analysis of Project Specific Alliances in the Film Industry

We use a movie industry project-by-project data set to consider the choice of internal project financing versus financing via through alliances that span the legal boundaries of several business entities. We find that project risk is positively correlated with alliance formation. Studios, which produce a variety of films, tend to develop the safest projects internally. Our findings are consistent with internal-capital-market explanations, in particular, with the theory offered by Robinson (2005). We find mixed evidence regarding "resource pooling," i.e., sharing the cost of large projects. Finally, we find that the ex-post performance of projects developed internally is similar to the performance of projects developed via through alliances.
Biogeochemical cycles (C, N, S, P and Fe) of modern and ancient microbialites (Western Australia)

iii Stromatolites are “accretionary sedimentary structures, commonly thinly layered, megascopic and calcareous, produced by the activities of mat-building communities of mucilage-secreting microorganisms, mainly photoautotrophic prokaryotes”. They represent the earliest traces of life, with macro-fossil specimens reported in the rock record back to 3430 Ma. Stromatolites were dominant structures in the rock record until 600 Ma reflecting a crucial role in Earth’s evolution, particularly in oceans and the oxidation of the atmosphere. Yet, the general lack of microfossils or molecular fossils during this period of life’s early evolution makes the study of microbial assemblages highly challenging and prone to scrutiny. In addition, little is known about the sources – i.e., at a microbial species level biogeochemical processes and preservation pathways of these ancient microbial macrostructures. Modern microbial mats, including laminated lithifying smooth mats reported in the World Heritage listed Shark Bay, Western Australia are considered modern analogues of earlyformed stromatolites. Consequently, the study of these specimens provides an opportunity to gain a better understanding of the evolution of early life and conduct a molecular comparison with ancient microbial structures with the hope of correlating molecular microfossils (i.e., biomarkers). Studies of modern microbial mats and diagenetic pathways supporting their biomarker preservation are critically important for discerning early microbial assemblages, complex and dynamic elemental cycles and the true nature of macroscopic biosignatures (e.g. organic petrography). The analysis of biomarkers and their stable isotopic composition bears a great potential for the investigation of recent and ancient stromatolites. These data can be used to characterise microbial assemblages, identify organic sources and to reconstruct environmental settings. This PhD study explored this potential and identified the advantages biomarker and stable isotope analyses bring to the microbial characterisation of mat communities. Complimentary methods including 16s rRNA analysis, diffusive equilibration in thin films (DET) and diffusive gradients in thin films (DGT) samplers were also applied to contribute to a more holistic characterisation of microbial communities.
Genre-based decomposition of email class noise

Corruption of data by class-label noise is an important practical concern impacting many classification problems. Studies of data cleaning techniques often assume a uniform label noise model, however, which is seldom realized in practice. Relatively little is understood, as to how the natural label noise distribution can be measured or simulated. Using email spam-filtering data, we demonstrate that class noise can have substantial content specific bias. We also demonstrate that noise detection techniques based on classifier confidence tend to identify instances that human assessors are likely to label in error. We show that genre modeling can be very informative in identifying potential areas of mislabeling. Moreover, we are able to show that genre decomposition can also be used to substantially improve spam filtering accuracy, with our results outperforming the best published figures for the trec05-p1 and ceas-2008 benchmark collections.
Finding Bias in Political News and Blog Websites

News and blog websites often have political bias (such as Republican, Democratic) in their articles. Automatic detection of the bias will improve personalized feed and categorization of news and blog articles. Our project aims to predict Republican vs. Democratic bias of news websites and political blogs using the phrases (a.k.a. memes) they quote in their text. We form a bipartite graph of websites and memes quoted by the websites. The algorithm starts with labels of a few websites and labels the rest of nodes in the bipartite graph using a simple label propagation algorithm. Our algorithm predicts labels better than supervised classification approach and other baselines.