Miracle-dz/UniFAR-FTUs huggingface dataset:
Body Size, Performance and Fitness in Galapagos Marine Iguanas1

Abstract Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This ‘performance paradigm’ allows predictions about adaptive evolution in natural populations.
Evidence for a Population of Beamed Radio-intermediate Quasars

Whether radio-intermediate quasars possess relativistic jets as radio-loud quasars do is an important issue in the understanding of the origin of radio emission in quasars. In this paper, using the two-epoch radio data obtained during the Faint Images of the Radio Sky at Twenty cm (FIRST) and NRAO VLA Sky Survey (NVSS), we identified 89 radio-variable sources in the Sloan Digital Sky Survey (SDSS). Among them, more than half are radio-intermediate quasars (RL = f20 cm/f2500 Å < 250). For all objects with available multiple-band radio observations, the radio spectra are either flat or inverted. The brightness temperature inferred from the variability is larger than the synchrotron self-Compton limit for a stationary source in 87 objects, indicating relativistic beaming. Considering the sample selection and the viewing angle effect, we conclude that relativistic jets probably exist in a substantial fraction of radio-intermediate quasars.
Generalizing XPath for directed graphs Table of Contents

XPath is a very natural and powerful way to specify locations in XML documents. This paper examines possible generalizations of XPath to allow both locations and paths through generalized labeled directed graphs to be specified. The need for such a path language is driven by work in querying Linguistic Annotations which are in general more complex in structure than XML documents. The result of this exercise is a powerful path language which reduces to XPath as a special case and which could potentially be useful in a range of query applications. Generalizing XPath for directed graphs Table of
A Faster-converging Algorithm for Image Segmentation with a Modified Chan-Vese Model

We propose an algorithm for segmentation of grayscale images. Our algorithm computes a solution to the convex, unconstrained minimization problem proposed by T. Chan, S. Esedoḡlu, and M. Nikolova in [1], which is closely related to the Chan-Vese level set algorithm for the Mumford-Shah segmentation model. Up to now this problem has been solved with a gradient descent method. Our approach is a quasi-Newton method based on the lagged diffusivity algorithm [2] for minimizing the total-variation functional for image denoising [3]. Our results show that our algorithm requires a much smaller number of iterations and less time to converge than gradient descent, and is able to segment noisy images correctly. Keywords—image segmentation, Mumford-Shah segmentation, Chan-Vese model, quasi-Newton method
Science, governance, and public participation: An analysis of decision making on genetic modification in Aotearoa/New Zealand

The acceptance of public participation in science and technology governance in liberal democratic contexts is evident in the institutionalization of a variety of mechanisms for participation in recent decades. Yet questions remain about the extent to which institutions have actually transformed their policy practice to embrace democratic governance of techno-scientific decision making. A critical discourse analysis of the response to public participation by the Environmental Risk Management Authority (ERMA), the key decision-making body on genetic modification in Aotearoa/New Zealand, in a specific case demonstrates that ERMA systematically marginalized concerns raised by the public about risk management, ethics, and ecological, economic, and cultural issues in order to give primacy to a positivist, technological worldview. Such delegitimization of public perspectives pre-empts the possibility of the democratic governance of science.
Generalized Correlation of Binary Interaction Parameters in Cubic Equations of State for Hydrocarbon/co2, Hydrocarbon/h2s and Co2/h2s Systems

In the present work, we develop a predictive corresponding-states correlation for the binary interaction parameters of systems composed of hydrocarbons (HC), up to C10, with CO2 and H2S. Experimental data were collected from the literature for 12 HC/CO2 systems (1017 data points for 90 isotherms), 7 HC/H2S systems (293 data points for 27 isotherms), and the CO2/H2S systems (61 data points for 19 isotherms). Optimal kij were computed using the isofugacity method of Paunovic et al. Computations were made for the van der Waals, Redlich-Kwong and Peng-Robinson equations of state, with the cohesion functions of Soave, Gibbons and Laughton, Stryjek and Vera, Twu et al., and our own group. Analysis of the results showed that kij are essentially the same for each binary pair and equation of state, regardless of the cohesion function used, thus making them true system properties. Average deviations obtained with the present correlation range from 2.5% to 4.5% for compositions, and from 1.5% to 4.0% for pressures, depending on the equation of state and type of binary pair. The correlation has also been used successfully in predicting vapor-liquid equilibria of ternary and higher mixtures involving these same components.
A low complexity block matching algorithm for fast motion estimation in High Efficiency Video Coding

This paper proposes a search mechanism, namely accelerated internal stop search (AISS), to reduce the complexity of the block matching process used for motion estimation in High Efficiency Video Coding (HEVC). The proposed mechanism reduces the number of operations required to find the best matching reference block. Moreover, it uses the correlation with the previous reference frames to further reduce the complexity of motion estimation for the current reference frame. Results demonstrate that the proposed mechanism is able to reduce the complexity of motion estimation in the fast search mode of the HM-14.0 reference software for HEVC, i.e., the TZ Search motion estimation. The AISS mechanism outperforms the dynamic internal stop search algorithm (DISS) proposed by Ismail et al. in the year 2012 in terms of motion estimation time saving. Moreover, when AISS is integrated with the dynamic model based fast motion estimation proposed by Ismail et al. [1], the complexity of motion estimation is further reduced.
The Largest Black Holes and the Most Luminous Galaxies

The empirical relationship between the broad-line region size and the source luminosity in active galactic nuclei (AGNs) is used to obtain black hole (BH) masses for a large number of quasars in three samples. The largest black hole masses exceed 1010 M☉ and are found to occur in the objects with the highest luminosities. Such BH masses, when converted to galaxy bulge mass and luminosity, indicate masses in excess of 1013 M☉ and σ* in excess of 700 km s-1. Such massive galaxies have never been observed. The largest BHs reside, almost exclusively, in high-redshift quasars. All this is inconsistent with several suggested scenarios of BH and galaxy formation. Possible ways out are that either the observed size-luminosity relationship in low-luminosity AGNs does not extend to very high luminosity or else the MBH-Mbulge-σ* correlations observed in the local universe do not reflect the relation between those quantities at the epoch of galaxy formation.
Optimization of phase-locked loop circuits via geometric programming

We describe the global optimization of phase-locked loop (PLL) circuits using geometric programming (GP). Equations for the jitter, frequency range, and power of the PLL are presented in GP form. An array of PLL circuits was automatically generated using this technique in a 0.18 /spl mu/m, 1.8 V CMOS process. Silicon measurements show good agreement with the model. The results include a 1.9 GHz PLL with a period jitter of 2.2 ps RMS and an accumulated jitter of 6.2 ps RMS, consuming 10.8 mW.
Numerical Normal Forms for Codim 2 Bifurcations of Fixed Points with at Most Two Critical Eigenvalues

In this paper we derive explicit formulas for the normal form coefficients to verify the nondegeneracy of eight codimension two bifurcations of fixed points with one or two critical eigenvalues. These include all strong resonances, as well as the degenerate flip and Neimark--Sacker bifurcations. Applying our results to n-dimensional maps, one avoids the computation of the center manifold, but one can directly evaluate the critical normal form coefficients in the original basis. The formulas remain valid also for n=2 and allow one to avoid the transformation of the linear part of the map into Jordan form. The developed techniques are tested on two examples: (1) a three-dimensional map appearing in adaptive control; (2) a periodically forced epidemic model. We compute numerically the critical normal form coefficients for several codim 2 bifurcations occurring in these models. To compute the required derivatives of the Poincare map for the epidemic model, the automatic differentiation package ADOL-C is used.
The Case for Programmable Object Storage Systems

As applications scale to new levels and migrate into cloud environments, there has been a significant departure from the exclusive reliance on the POSIX file I/O interface. However in doing so, application often discover a lack of services, forcing them to use bolt-on features or take on the responsibility of critical data management tasks. This often results in duplication of complex software with extreme correctness requirements. Instead, wouldn’t it be nice if an application could just convey what it wanted out of a storage system, and have the storage system understand? The central question we address in this paper is whether or not the design delta between two storage systems can be expressed in a form such that one system becomes little more than a configuration of the other. Storage systems should expose their useful services in a way that separates performance from correctness, allowing for their safe reuse. After all, hardened code in storage systems protects countless value, and its correctness is only as good as the stress we place on it. We demonstrate these concepts by synthesizing the CORFU high-performance shared-log abstraction in Ceph through minor modifications of existing sub-systems that are orthogonal to correctness.
3D pose estimation for robotic applications based on a multi-camera hybrid visual system

An algorithm for the estimation of the position and orientation of a moving object using a hybrid eye-in-hand/eye-to-hand multi-camera system is presented. Based on the extended Kalman filter, this approach exploits the data provided by all the cameras without "a priori" discrimination, allowing real-time estimation. The proposed formulation can be used with different kinds of image features and different representations of the object orientation. A simulation case study is reported to test the feasibility and the effectiveness of the proposed technique
Emergeables: Deformable Displays for Continuous Eyes-Free Mobile Interaction

In this paper we present the concept of Emergeables -- mobile surfaces that can deform or 'morph' to provide fully-actuated, tangible controls. Our goal in this work is to provide the flexibility of graphical touchscreens, coupled with the affordance and tactile benefits offered by physical widgets. In contrast to previous research in the area of deformable displays, our work focuses on continuous controls (e.g., dials or sliders), and strives for fully-dynamic positioning, providing versatile widgets that can change shape and location depending on the user's needs. We describe the design and implementation of two prototype emergeables built to demonstrate the concept, and present an in-depth evaluation that compares both with a touchscreen alternative. The results show the strong potential of emergeables for on-demand, eyes-free control of continuous parameters, particularly when comparing the accuracy and usability of a high-resolution emergeable to a standard GUI approach. We conclude with a discussion of the level of resolution that is necessary for future emergeables, and suggest how high-resolution versions might be achieved.
The Swedish CArdioPulmonary BioImage Study: objectives and design

Cardiopulmonary diseases are major causes of death worldwide, but currently recommended strategies for diagnosis and prevention may be outdated because of recent changes in risk factor patterns. The Swedish CArdioPulmonarybioImage Study (SCAPIS) combines the use of new imaging technologies, advances in large‐scale ‘omics’ and epidemiological analyses to extensively characterize a Swedish cohort of 30 000 men and women aged between 50 and 64 years. The information obtained will be used to improve risk prediction of cardiopulmonary diseases and optimize the ability to study disease mechanisms. A comprehensive pilot study in 1111 individuals, which was completed in 2012, demonstrated the feasibility and financial and ethical consequences of SCAPIS. Recruitment to the national, multicentre study has recently started.
Sentiment Classification of Crisis Related Tweets using Segmentation

Social media data has served as a quick and accessible means of communication which may convey many important event-related information. Social media such as Twitter gives users the ability to tweet any current situation to other people and in emergencies such as disaster-related events, it is important to know the sentiments of the people and their concerns from the tweets posted by users. It can be helpful in facilitating the needs of those affected by the disaster. The tweets in the original form include many grammatical errors and slang words because of the informal nature of tweets. Many sentiment classifications have been performed on the tweets using techniques like bag-of-words and using word sequences. A sentence-level sentiment classification can be conducted on the tweets using segmentation in addition to the features extracted using word sequences. Segmentation model produces segments that are generated using a tree structure from a phrase dictionary that further is classified using a classification model for predicting the sentiment polarity. We assess the polarity predicted by the classifier for each segmentation result of a particular tweet and using a majority rule approach we predict a new sentiment class. The primary goal is to help in improving the sentiment classification for crisis-related events.
Discovering Database Replication Techniques in RDBMS

Data replication is a key factor to achieve scalability and fault tolerance in databases as it maintains several clones of data objects. A change made in data automatically triggers carrying out similar changes in each of the replica. A number of data replication techniques have been proposed in the contemporary literature due to its large scale application in the real world like astronomy, high energy physics and biology. In this study we provide a critical analysis of these techniques.
Integrating Extreme Programming and User-Centered Design

The success of a software development project is associated not only with tools and technologies, but it also depends on how much the development process helps to be user-centered and developer-oriented. Involving customers in the process and being people-oriented, Extreme Programming (XP)– One of the popular agile methods – can be a choice for developing a usable system. The project under study is a multimedia streaming application for mobile phones that allows to make content-based search for audio and video content in large databases and play it on a mobile phone virtually anywhere, at any time. Our approach to application development focuses on the adoption of XP and User-Centered Design (UCD), emphasizing iterative user-interface development involving usability engineers and end-users. The paper describes the process of integrating XP with user-centered design and shows how an agile development technique facilitates to be user-oriented and at the same time preserves the social values of the development team.
Establishment of a Conditional Transgenic System Using the 2A Peptide in the Female Mouse Germline

Transgenic mice are essential research tools in developmental biology studies. The 2A peptide allows multiple genes to be expressed simultaneously at comparable levels in somatic cells, but there are no reports of it being used successfully in germ cells. We constructed a Cre/loxP-based conditional vector containing the 2A peptide to significantly enhance the expression of a reporter and target gene from a constitutive promoter in oocytes. Mice with a transgene insertion containing the chicken β-actin promoter, floxed EGFP-polyA cassette, mCherry reporter, 2A peptide and target gene DNA methyltransferase 3A2 (Dnmt3a2) were crossed with TNAP- or Vasa-Cre mice to produce offspring, in which mCherry and DNMT3A2 proteins were highly expressed in oocytes upon Cre-mediated removal of EGFP-polyA. This novel transgenic mouse line based on the 2A expression system can serve as a useful tool for examining gene function during oogenesis.
Pas Ywe Xilt?gation

2 rntthod IF prcpctc-d for dctc~rniuing the motion of a b ~ d y rclativc to a fixcd rn.tirr:nrnt.nt using thr rhangmg image seen by a camcra attached to thrd Imly. The cq~ttcz! flo-c. in t h e Image plane is t h e input, while the instants~;eous rotation and transIatlon of t h e body are t h e ~ i i t p i t t . if oj)tlcnl -flow could be ctclertn~tted p ~ e c i w l y , ~t w.voutd only h;v~ to be h o v n a t a few places to compute t l ~ r parameters of the n$otion. In practice, hwvever, the ~neasured optical flow will be somec% hat inaccural e. It is therei,jre advautageous t o c-omider methods sb ich use as much of the avallablt. information as postiblc. IVo cmpluy a Icast-squarcs approach which minirnizcs soxnc rncasurc of the disrrcpancy between t h c mcasured How and that predlctrd from thc comput~ )d motion parametex. Several diFerent error norms are investigated. In general, our algorithm lead. : to a s y s t ~ m of nonlinear equation? from xhictl t h e m o t ~ o n parameters may be ::)ml! uteci ~~rlrnerically. flowever, in t h e special c a m uheie f l i t 1 motion of the camera 1s purely t ra~i~iat lonwl or purely rotat lonnl , u i e c,f t h e ttppropr~,ztz ! lorn, leads t o ;t FJ stem ol equallous f r o ~ r ~ ;zhich these parar~wters call be determmtd iu closed form.
Safe Exploration for Optimization with Gaussian Processes

We consider sequential decision problems under uncertainty, where we seek to optimize an unknown function from noisy samples. This requires balancing exploration (learning about the objective) and exploitation (localizing the maximum), a problem well-studied in the multiarmed bandit literature. In many applications, however, we require that the sampled function values exceed some prespecified "safety" threshold, a requirement that existing algorithms fail to meet. Examples include medical applications where patient comfort must be guaranteed, recommender systems aiming to avoid user dissatisfaction, and robotic control, where one seeks to avoid controls causing physical harm to the platform. We tackle this novel, yet rich, set of problems under the assumption that the unknown function satisfies regularity conditions expressed via a Gaussian process prior. We develop an efficient algorithm called SAFEOPT, and theoretically guarantee its convergence to a natural notion of optimum reachable under safety constraints. We evaluate SAFEOPT on synthetic data, as well as two real applications: movie recommendation, and therapeutic spinal cord stimulation.
A Mesochronous Network-on-Chip for an FPGA

Networks-on-Chip (NoCs) are a new paradigm for the design of integrated systems. NoCs address design complexity and physical issues in ASIC and FPGA designs. In this paper, we present a scalable, mesochronous NoC architecture for an FPGA. A special hybrid switching scheme has been developed for globally asynchronous locally synchronous (GALS) operation of the whole NoC-based system. The NoC was designed with respect to simplicity and a small hardware footprint.
Customization of UWB 3D-RTLS Based on the New Uncertainty Model of the AoA Ranging Technique

The increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical uncertainty model of Angle of Arrival (AoA) localization in a 3D indoor space, which is the foundation of the customization concept, is established in a working environment. Additionally, a suitable angular-based 3D localization algorithm is introduced. The paper investigates the following issues: the influence of the proposed correction vector on the localization accuracy; the impact of the system’s configuration and LS’s relative deployment on the localization precision distribution map. The advantages of the method are verified by comparing them with a reference commercial RTLS localization engine. The results of simulations and physical experiments prove the value of the proposed customization method. The research confirms that the analytical uncertainty model is the valid representation of RTLS’ localization uncertainty in terms of accuracy and precision and can be useful for its performance improvement. The research shows, that the Angle of Arrival localization in a 3D indoor space applying the simple angular-based localization algorithm and correction vector improves of localization accuracy and precision in a way that the system challenges the reference hardware advanced localization engine. Moreover, the research guides the deployment of location sensors to enhance the localization precision.
Improvement in both sensitivity and specificity of readers with next generation of mammography CAD

Poster: "ECR 2013 / B-0206 / Improvement in both sensitivity and specificity of readers with next generation of mammography CAD" by: "V. Nikitin, I. Lossev, A. Filatov, N. Bagotskaya, I. Kil; Longmont, CO/US"