Miracle-dz/UniFAR-FTUs huggingface dataset:
Domestication and the Mitochondrial Genome: Comparing Patterns and Rates of Molecular Evolution in Domesticated Mammals and Birds and Their Wild Relatives

Studies of domesticated animals have led to the suggestion that domestication could have significant effects on patterns of molecular evolution. In particular, analyses of mitochondrial genome sequences from domestic dogs and yaks have yielded higher ratios of non-synonymous to synonymous substitutions in the domesticated lineages than in their wild relatives. These results are important because they imply that changes to selection or population size operating over a short timescale can cause significant changes to the patterns of mitochondrial molecular evolution. In this study, our aim is to test whether the impact on mitochondrial genome evolution is a general feature of domestication or whether it is specific to particular examples. We test whether domesticated mammals and birds have consistently different patterns of molecular evolution than their wild relatives for 16 phylogenetically independent comparisons of mitochondrial genome sequences. We find no consistent difference in branch lengths or dN/dS between domesticated and wild lineages. We also find no evidence that our failure to detect a consistent pattern is due to the short timescales involved or low genetic distance between domesticated lineages and their wild relatives. However, removing comparisons where the wild relative may also have undergone a bottleneck does reveal a pattern consistent with reduced effective population size in domesticated lineages. Our results suggest that, although some domesticated lineages may have undergone changes to selective regime or effective population size that could have affected mitochondrial evolution, it is not possible to generalize these patterns over all domesticated mammals and birds.
Illumination Invariant Texture Retrieval

Two fast illumination invariant image retrieval methods for scenes comprising textured objects with variable illumination are introduced. Both methods are based on texture gradient modeled by efficient set of random field models. We developed the illumination insensitive measures for textured images representation and compared them favorably with steerable pyramid and Gabor features in the illumination invariant BTF texture recognition
A behavioral study of learning in standard SOM and in S-SOM

In this paper we establish the completion of a previously published work, in part by the same authors, in which we proposed a novel learning algorithm involving Self Organizing Map's (SOM) internal structure in the learning process. We present a statistical and a behavioral study of our proposed solution, and confirm its results on a breast cancer classification application. After establishing the mathematical foundations of the passage of input vectors, we show how to conclude better initial conditions leading to the generation of a unique feature map in standard SOM.
Virtual deployment of pipeline flow diverters in cerebral vessels with aneurysms to understand thrombosis

We present a prototype software to virtually deploy pipeline fl ow diverting stents in intracranial vessels with aneurysms. The fi nal objective is to understand the biological and biomechanical mechanisms underlying the stent-induced clot formation within the aneurysm. The weaving pattern of the selected pipeline stent is described w.r. t. cylindrical coordinates. Patient-speci fic 3D vascular geometry is extracted by a level-set image segmentation algorithm. A deformable cylindrical simplex mesh model is used to simulate the virtual stent positioning. A continuous Right Generalized Cylinder model is then used to obtain the mapping of the stent geometry onto the deformed cylindrical surface. Meshes representing the vessel/aneurysm surface and the fi laments of the stent are used as input to simulate the fl uid dynamics without and with the virtual stent. Lattice Boltzmann method is used to solve the equations. We show preliminary visual results on a first patient.
Heat transfer model for capacitor banks

The life expectancy of aluminum electrolytic capacitors used for DC bus filtering in motor drives depends upon their operating temperature. This paper discusses convection and radiation heat transfer from capacitor banks and presents a heat transfer model for banks of capacitors that can be used to estimate temperature rise. The model is verified with experimental data and is further extended by using computational fluid dynamics and radiation theory. Bank design options are explored for their impact on bank cooling efficiency.
A Survey on Opportunistic Scheduling in Wireless Communications

Wireless technology advancements made opportunistic scheduling a popular topic in recent times. However, opportunistic schedulers for wireless systems have been studied since nearly twenty years, but not implemented in real systems due to their high complexity and hardly achievable requirements. In contrast, today's popularity of opportunistic schedulers extends to implementation proposals for next generation cellular technologies. Motivated by such a novel interest towards opportunistic scheduling, we provide a taxonomy for opportunistic schedulers, which is based on scheduling design's objectives; accordingly, we provide an extensive review of opportunistic scheduling proposals which have appeared in the literature during nearly two decades. The huge number of papers available in the literature propose different techniques to perform opportunistic scheduling, ranging from simple heuristic algorithms to complex mathematical models. Some proposals are only designed to increase the total network capacity, while others enhance QoS objectives such as throughput and fairness. Interestingly, our survey helps to unveil two major issues: (i) the research in opportunistic is mature enough to jump from pure theory to implementation, and (ii) there are still under-explored and interesting research areas in opportunistic scheduling, e.g., opportunistic offloading of cellular traffic to 802.11-like networks, or cooperative/distributed opportunistic scheduling.
A Perspective Analysis of Hidden Community Mining Methods in Large Scale Social Networks

Research in social network analysis has increased in recent years. Because of the popularity of the social networking sites, many researchers concentrate on this area for research. In this, community mining plays an important role. Hidden communities affect the social networks in different ways. But not all hidden communities are dangerous or illegal. Most of the hidden communities are having potential knowledge. Communities are represented as a graph format. People are represented as nodes, and the relationship between the nodes are represented as edges. Several mining techniques do not considered the disconnected edges in the graph. Those hidden or disconnected edges may useful to the others in the network. Our approach on social network is fully based on the community mining on heterogeneous network. Here we analysis the various community mining techniques which is already available. Such as MinCut algorithm, Regression based algorithm, Max-Min modularity measure, LM algorithm and SECI model. Our results show that, there are some limitations in the hidden community mining technique in large scale networks. So we planned to do research in this area for better improvement.
Channel sharing techniques in hybrid optical networks for data centers

This paper presents performance evaluations and comparisons of different sharing approaches applied to the available optical bandwidth in data center networks. The recently proposed hybrid optical network concept, which combines multi-wavelength optical packet switching (OPS) and optical circuit switching (OCS) in WDM networks, is compared with a service-specific sharing model. Simulation results show that a careful design of dedicated channel allocation gives similar performance to a complete channel sharing with prioritized scheduling, which is however more flexible.
An experimental comparison of modern methods of segmentation

This paper deals with experimental comparison of classical method of Graph cut segmentation with segmentation using Active contours. From methods of Active contours are chosen to comparison two methods. First method is based on classic Active contour method and second method is based on Active contours independent on gradient of the edges. Application of Graph cut segmentation allows finding the optimal global segmentation with the best balance between regional and boundary conditions among all possible segmentations at met condition limitations. Active contour segments the image by iterative deformation contour till this contour divided the image on the regions. Active contours are often implemented with level set methods for their universality and performance, but disadvantage is their computational complexity. The second method of the active contour allows to detect objects whose boundaries are not necessarily defined by gradient. The end rule in this case does not depend on gradient of the image, as in classical model of active contour, but instead refer to a particular segmentation of the image.
Modification of flower architecture during early stages in the evolution of self-fertilization.

BACKGROUND AND AIMS The evolution of selfing from outcrossing is characterized by a series of morphological changes to flowers culminating in the selfing syndrome. However, which morphological traits initiate increased self-pollination and which are accumulated after self-fertilization establishes is poorly understood. Because the expression of floral traits may depend on the conditions experienced by an individual during flower development, investigation of changes in mating system should also account for environmental and developmental factors. Here, early stages in the evolution of self-pollination are investigated by comparing floral traits among Brazilian populations of Eichhornia paniculata (Pontederiaceae), an annual aquatic that displays variation in selfing rates associated with the breakdown of tristyly to semi-homostyly. METHODS Thirty-one Brazilian populations under uniform glasshouse conditions were compared to investigate genetic and environmental influences on flower size and stigma-anther separation (herkogamy), two traits that commonly vary in association with transitions to selfing. Within-plant variation in herkogamy was also examined and plants grown under contrasting environmental conditions were compared to examine to what extent this trait exhibits phenotypic plasticity. KEY RESULTS In E. paniculata a reduction in herkogamy is the principal modification initiating the evolution of selfing. Significantly, reduced herkogamy was restricted to the mid-styled morph and occurred independently of flower size. Significant genetic variation for herkogamy was detected among populations and families, including genotypes exhibiting developmental instability of stamen position with bimodal distributions of herkogamy values. Cloned genets exposed to contrasting growth conditions demonstrated environmental control of herkogamy and genotypic differences in plasticity of this trait. CONCLUSIONS The ability to modify herkogamy independently of other floral traits, genetic variation in the environmental sensitivity of herkogamy, and the production of modified and unmodified flowers within some individuals, reveal the potential for dynamic control of the mating system in a species that commonly confronts heterogeneous aquatic environments.
Low latency and high throughput dedicated loop of transforms and quantization focusing in the H.264/AVC Intra Prediction

This paper presents an efficient architectural design for a dedicated transforms and quantization loop. This design targeted the Intra Prediction of the H.264/AVC standard. The architecture was designed intending to achieve the best possible relation between throughput, latency and hardware resources consumption. The latency and throughput of this loop are extremely important to define the Intra Prediction performance. The use of hardware was reduced through the reuse of the same datapath for different calculations. The architecture was synthesized to Altera Stratix III FPGA and to the TSMC 0. 18µm standard-cells technology. The architecture, when mapped to standard-cells, reaches a processing rate of 114 HDTV frames per second, attending the Intra Prediction restrictions.
Well-Tempered Spelling: A Key Invariant Pitch Spelling Algorithm

In this paper is described a data-driven algorithm for the functionally correct spelling of MIDI pitch values in terms of Western musical notation. Input is in the form of MIDI files containing accurate pitch and rhythmic information with corresponding ground-truth spelling information for training and evaluation. The algorithm recovers harmonic information from the MIDI data and spells pitches according to their relation to the local tonic. The algorithm achieved 94.98% accuracy on the pitches that required accidentals in the local key and 99.686% overall. Voice-leading resolution was found to be the best feature of those used to infer the correct spelling. Also, this paper outlines great potential for improvement under this model.
"Ethical Tourism" or Self-Preservation? An Empirical Analysis of the Effect of Political Violence on Tourism in Egypt in the 1990s

This paper uses a new database of political violence in Egypt to study the effects of political violence on the monthly arrival of tourists from the EU and the US in Egypt in the 1990s. We use time series analysis to study the impact of different aspects of political violence and counter-violence. We find that both US and EU tourists respond negatively to attacks on tourists, but do not appear to be influenced by casualties arising in confrontations between domestic groups. However, European tourists are sensitive to the counter-violence measures implemented by the Egyptian government. There is also evidence of tourism in Egypt being affected by the Israeli / Palestinian conflict, with arrivals of US tourists into Egypt rising when fatalities in Israel increase, while European tourists reduce their demand for Egyptian holidays.
Checkpointing as a Service in Heterogeneous Cloud Environments

A non-invasive, cloud-agnostic approach is demonstrated for extending existing cloud platforms to include checkpoint-restart capability. Most cloud platforms currently rely on each application to provide its own fault tolerance. A uniform mechanism within the cloud itself serves two purposes: (a) direct support for long-running jobs, which would otherwise require a custom fault-tolerant mechanism for each application, and (b) the administrative capability to manage an over-subscribed cloud by temporarily swapping out jobs when higher priority jobs arrive. An advantage of this uniform approach is that it also supports parallel and distributed computations, over both TCP and InfiniBand, thus allowing traditional HPC applications to take advantage of an existing cloud infrastructure. Additionally, an integrated health-monitoring mechanism detects when long-running jobs either fail or incur exceptionally low performance, perhaps due to resource starvation, and proactively suspends the job. The cloud-agnostic feature is demonstrated by applying the implementation to two very different cloud platforms: Snooze and Open Stack. The use of a cloud-agnostic architecture also enables, for the first time, migration of applications from one cloud platform to another.
Black Carbon as an Additional Indicator of the Adverse Health Effects of Airborne Particles Compared with PM10 and PM2.5

Background: Current air quality standards for particulate matter (PM) use the PM mass concentration [PM with aerodynamic diameters ≤ 10 μm (PM10) or ≤ 2.5 μm (PM2.5)] as a metric. It has been suggested that particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration. Objectives: We evaluated the value of black carbon particles (BCP) as an additional indicator in air quality management. Methods: We performed a systematic review and meta-analysis of health effects of BCP compared with PM mass based on data from time-series studies and cohort studies that measured both exposures. We compared the potential health benefits of a hypothetical traffic abatement measure, using near-roadway concentration increments of BCP and PM2.5 based on data from prior studies. Results: Estimated health effects of a 1-μg/m3 increase in exposure were greater for BCP than for PM10 or PM2.5, but estimated effects of an interquartile range increase were similar. Two-pollutant models in time-series studies suggested that the effect of BCP was more robust than the effect of PM mass. The estimated increase in life expectancy associated with a hypothetical traffic abatement measure was four to nine times higher when expressed in BCP compared with an equivalent change in PM2.5 mass. Conclusion: BCP is a valuable additional air quality indicator to evaluate the health risks of air quality dominated by primary combustion particles.
The Informational Requirement on Financial Systems at Different Stages of Economic Development: The Case of South Korea

In this paper, I review the evolution and characteristics of South Korea’s financial system since the early 1960s. The South Korean experiences are then used to argue that the distribution of the knowledge about valuable businesses varies with the stage of economic development. This has implications for the design of financial system. In the early development stage when low labor cost is the main competitive advantage, it is easy for everyone to see what businesses will create value. A centralized financial system is not likely to significantly misallocate resources. Government-directed credit allocation can be justified in some cases. In the more advanced development stage when the labor cost advantage disappears and the knowledge about the technologically advanced products becomes widely dispersed, a financial system that promotes security trading is more likely to guide efficient resource allocation.
A Gene Prediction Method Based on Statistics and Signal Processing

Bioinformatics, as an emerging and rapidly developing interdisciplinary, has become a promising and popular research field in 21st century. Extracting and explaining useful biological information from huge amount of genetic data is an urgent issue in post-genome era. In eukaryotic DNA sequences, gene consists of exons and introns. To predict the location of exons which carry most genetic information accurately has become one of the most essential issues in bioinformatics. Here, we have used biological characteristics of introns to find the candidate initial and final exon sections. Then we select candidate exon sections by using Support Vector Machine (SVM). Next, we predict exon sections accurately based on Discrete Fourier Transform (DFT) and using three-base periodicity of DNA sequence signals. This paper provides a gene prediction method based on statistics and signal processing and also, the improvement and prospect for this method in the future are discussed.
Supporting Computational Algorithmic Thinking (SCAT): Understanding the Development of Computational Algorithmic Thinking Capabilities in African-American Middle-School Girls Through Game Design

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that it solves the problem, and evaluating the solution based on some set of criteria. This paper not only introduces and describes CAT as explored through the Supporting Computational Algorithmic Thinking (SCAT) project, but it also presents insights from preliminary analysis of the data. SCAT is an on-going longitudinal between-subjects research project and enrichment program that guides African-American middle school girls through the iterative game design cycle resulting in a set of complex games with themes focused on social change.
A Domain-Specific Language for the Generation of Optimized SIMD-Parallel Assembly Code

We present a domain-specific language embedded into Haskell that allows mathematicians to formulate novel high-performance SIMD-parallel algorithms for the evaluation of special functions. Developing such functions involves explorations both of mathematical properties of the functions which lead to effective (rational) polynomial approximations, and of specific properties of the binary representation of floating point numbers. Our framework includes support for estimating the effectiveness of different approximation schemes in Maple. Once a scheme is chosen, the Maple-generated component is integrated into the code generation setup. Numerical experimentation can then be performed interactively, with support functions for running standard tests and tabulating results. Once a satisfactory formulation is achieved, a codegraph representation of the algorithm can be passed to other components which produce C function bodies, or to a state-of-the-art scheduler which produces optimal or near-optimal schedules, currently targetting the “Cell Broadband Engine” processor. Encapsulating a considerable amount of knowledge about specific “tricks” in DSL constructs allows us produce algorithm specifications that are precise, readable, and compile to optimal-quality assembly code, while formulations of the equivalent algorithms in C would be almost impossible to understand and maintain. General Terms Domain-specific languages, Synthesis from specifications, Industrial applications
A Highly Functional Synthetic Phage Display Library Containing over 40 Billion Human Antibody Clones

Several synthetic antibody phage display libraries have been created and used for the isolation of human monoclonal antibodies. The performance of antibody libraries, which is usually measured in terms of their ability to yield high-affinity binding specificities against target proteins of interest, depends both on technical aspects (such as library size and quality of cloning) and on design features (which influence the percentage of functional clones in the library and their ability to be used for practical applications). Here, we describe the design, construction and characterization of a combinatorial phage display library, comprising over 40 billion human antibody clones in single-chain fragment variable (scFv) format. The library was designed with the aim to obtain highly stable antibody clones, which can be affinity-purified on protein A supports, even when used in scFv format. The library was found to be highly functional, as >90% of randomly selected clones expressed the corresponding antibody. When selected against more than 15 antigens from various sources, the library always yielded specific and potent binders, at a higher frequency compared to previous antibody libraries. To demonstrate library performance in practical biomedical research projects, we isolated the human antibody G5, which reacts both against human and murine forms of the alternatively spliced BCD segment of tenascin-C, an extracellular matrix component frequently over-expressed in cancer and in chronic inflammation. The new library represents a useful source of binding specificities, both for academic research and for the development of antibody-based therapeutics.