Miracle-dz/UniFAR-FTUs huggingface dataset:
Accuracy and power of the likelihood ratio test in detecting adaptive molecular evolution.

The selective pressure at the protein level is usually measured by the nonsynonymous/synonymous rate ratio (omega = dN/dS), with omega < 1, omega = 1, and omega > 1 indicating purifying (or negative) selection, neutral evolution, and diversifying (or positive) selection, respectively. The omega ratio is commonly calculated as an average over sites. As every functional protein has some amino acid sites under selective constraints, averaging rates across sites leads to low power to detect positive selection. Recently developed models of codon substitution allow the omega ratio to vary among sites and appear to be powerful in detecting positive selection in empirical data analysis. In this study, we used computer simulation to investigate the accuracy and power of the likelihood ratio test (LRT) in detecting positive selection at amino acid sites. The test compares two nested models: one that allows for sites under positive selection (with omega > 1), and another that does not, with the chi2 distribution used for significance testing. We found that use of the chi(2) distribution makes the test conservative, especially when the data contain very short and highly similar sequences. Nevertheless, the LRT is powerful. Although the power can be low with only 5 or 6 sequences in the data, it was nearly 100% in data sets of 17 sequences. Sequence length, sequence divergence, and the strength of positive selection also were found to affect the power of the LRT. The exact distribution assumed for the omega ratio over sites was found not to affect the effectiveness of the LRT.
INTEGRATION FRAMEWORK FOR USING PATTERNS IN MODEL DRIVEN DEVELOPMENT

Awareness of software's importance in today's environment each day is growing. As new types of applications appears, need for modern, high quality methodological ways of their development is rising. Last few years researches in software industry move in different directions. This doctoral dissertation is based on currently most skeptical software development paradigm called Model Driven Development (MDD). The idea is examine the possibilities of using patterns in context of MDD paradigm. Because in the methodological approach of software development is necessary to use some kind of development process, intention is discover applicability of existing development process for MDD paradigm. Then, in the context of patterns it is necessary to define what kind of patterns is possible to use, and in what kind of form patterns has to be defined to use them for MDD. Furthermore, when this criteria's are satisfied, using patterns in context of MDD paradigm to provide automated SW development –what that paradigm promote, it is necessary to define framework for using patterns in MDD paradigm and then integrated its with modern software development methodology suitable for model driven development. AN OVERVIEW OF SOFTWARE ENGINEERING In software development during 90's two paradigms were dominated. In the early 90's it was popular the concept of Computer Aided Software Engineering based on CASE tools and 4GL while in the second half of the decade strong influence in software industry take object oriented (OO) paradigm. Although it wasn’t fulfilled all expectation, OO paradigm preserve to nowadays and during this years becomes a foundation for: component based development (CBD), OO languages, modeling notation today known as UML and philosophy called round trip engineering. Today's situation in software industry pointing that scenario repeats. Although use of OO development solves many problems in today's SW industry, evolution in all segments of society causes new challenges. Requirements of new and/or existing systems are growing, systems are complex and it is hard to build them on time and on budget. As an answer to these challenges, a wide spectrum of new approaches occurred, varying from buzzwords to comprehensive methodologies. The most important are: Service Oriented Architecture (SOA), Model Driven Development (MDD), Agile Development, Software Product Lines (SPL), Model Driven Architecture (MDA) and Software Factories (SF).
A comparison of software assurance methods

Several methods are currently employed by software developers to improve software quality. This paper explores the application of three of these methods: quality assurance, acceptance testing, and independent verification and validation. At first glance these methods appear to overlap, but a closer evaluation reveals that each has a distinct objective and an established set of procedures. The purpose of this paper is to clarify the role of each of these methods by examining their scope, organization, and implementation in the software development process.
Properties of bootstrap tests for N‐of‐1 studies

N‐of‐1 study designs involve the collection and analysis of repeated measures data from an individual not using an intervention and using an intervention. This study explores the use of semi‐parametric and parametric bootstrap tests in the analysis of N‐of‐1 studies under a single time series framework in the presence of autocorrelation. When the Type I error rates of bootstrap tests are compared to Wald tests, our results show that the bootstrap tests have more desirable properties. We compare the results for normally distributed errors with those for contaminated normally distributed errors and find that, except when there is relatively large autocorrelation, there is little difference between the power of the parametric and semi‐parametric bootstrap tests. We also experiment with two intervention designs: ABAB and AB, and show the ABAB design has more power. The results provide guidelines for designing N‐of‐1 studies, in the sense of how many observations and how many intervention changes are needed to achieve a certain level of power and which test should be performed.
Color-based watershed segmentation of low-altitude aerial images

In this paper we introduce the color-based catchment basin merging algorithm, an area-based segmentation approach that is specifically designed to segment low-altitude aerial images, as a preprocessing step to 3D reconstruction. This approach extends the watershed-based catchment basin merging algorithm, which is purely geometric, by introducing color similarity as an additional criterion to decide on the merging of evolving regions. Experiments performed with real aerial images of varied nature demonstrate that this modification eliminates over-segmentation problems of the existing algorithm, allowing large-scale urban scenes to be segmented in an accurate, reliable and fully automatic way.
Do music and art influence one another? Measuring cross-modal similarities in music and art

The visual arts and music interact with one another on both an individual scale (e.g., music-inspired synesthetes and artist-musician duos) and on a grand scale (e.g., the art movement Baroque, wherein abstract qualities such as “ornamentation” permeate both media). We develop a means to measure one of the many cross-modal similarities between music and visual art to both reveal any direct influences between the media, and to apply them to determine whether these connections became stronger or weaker throughout time. We examined the cross-modally linked continuums of lightness of color and height of pitch within comparable paintings and music of a time-determined art movement. The model of comparison extracted, measured, and contrasted the attributes of lightness of color in art and height of pitch in music in works from Russia and France created between 1870 and 1920. Although Russian visual art was measurably darker in value than French visual art of the same time, no significant differences were found between Russian and French music. While our results do not suggest direct influences manifesting differently in each medium, they demonstrate the use of the lightness-pitch model, applicable to other eras to measure potential cross-modal convergence and divergence through time.
Robust NL-Means Filter With Optimal Pixel-Wise Smoothing Parameter for Statistical Image Denoising

Most denoising methods require that some smoothing parameters be set manually to optimize their performance. Among these methods, a new filter based on nonlocal weighting (NL-means filter) has been shown to have a very attractive denoising capacity. In this paper, we propose fixing the smoothing parameter of this filter automatically. The smoothing parameter corresponds to the bandwidth h of a local constant regression. We use the Cp statistic embedded in Newton's method to optimize h in a point-wise fashion. This statistic also has the advantage of being a reliable measure of the quality of the denoising process for each pixel. In addition, we introduce a robust regression in the NL-means filter designed to greatly reduce the blur yielded by the weighting. Finally, we show how the automatic denoising model can be extended to images degraded by multiplicative noise. Experiments conducted on images with additive and multiplicative noise demonstrate a high denoising power with a degree of detail preservation.
A Fovea Localization Scheme Using Vessel Origin-Based Parabolic Model

At the center of the macula, fovea plays an important role in computer-aided diagnosis. To locate the fovea, this paper proposes a vessel origin (VO)-based parabolic model, which takes the VO as the vertex of the parabola-like vasculature. Image processing steps are applied to accurately locate the fovea on retinal images. Firstly, morphological gradient and the circular Hough transform are used to find the optic disc. The structure of the vessel is then segmented with the line detector. Based on the characteristics of the VO, four features of VO are extracted, following the Bayesian classification procedure. Once the VO is identified, the VO-based parabolic model will locate the fovea. To find the fittest parabola and the symmetry axis of the retinal vessel, an Shift and Rotation (SR)-Hough transform that combines the Hough transform with the shift and rotation of coordinates is presented. Two public databases of retinal images, DRIVE and STARE, are used to evaluate the proposed method. The experiment results show that the average Euclidean distances between the located fovea and the fovea marked by experts in two databases are 9.8 pixels and 30.7 pixels, respectively. The results are stronger than other methods and thus provide a better macular detection for further disease discovery.
The impact of space division multiplexing on resource allocation: a unified approach

Recent advances in the area of wireless communications have revealed the emerging need for efficient wireless access in personal, local and wide area networks. Space division multiple access (SDMA) with smart antennas at the base station is recognized as a promising means of increasing system capacity and supporting rate-demanding services. However, the existence of SDMA at the physical layer raises significant issues at higher layers. In this paper, we attempt to capture the impact of SDMA on channel allocation at the media access control (MAC) layer. This impact obtains different forms in TDMA, CDMA and OFDMA access schemes, due to the different cochannel and interchannel interference instances, as well as the different effect of corresponding channels (time slots, codes or subcarrier frequencies) on user channel characteristics. We follow a unified approach for these multiple access schemes and propose heuristic algorithms to allocate channels to users and adjust down-link beamforming vectors and transmission powers, with the objective to increase achievable system rate and provide QoS to users in the form of minimum rate guarantees. We consider the class of greedy algorithms, based on criteria such as minimum induced or received interference and minimum signal-to-interference ratio (SIR), as well as the class of SIR balancing algorithms. Our results indicate that this cross-layer approach yields significant performance benefits and that SIR balancing algorithms achieves the best performance.
Optimizing features by correlating for concept labeling in text classification

Unstructured form of text documents has seen a huge growth. Feature selection methods are important for the preprocessing of such text documents for dynamic text classification. Appropriate and useful features are focused during feature selection. This can decrease the cost involved while huge amount of data is dispensed out and will also amplify the next textual classifying work. This paper devised a novel geometric optimization method labeling for textual classification. An experimental study on the said geometric feature optimization method is conducted using divergent sizes of text data sets. Experimentally it is shown that how effective this method and how it is better than the tradition methods.
Nonequilibrium, multiple‐timescale simulations of ligand‐receptor interactions in structured protein systems

Predicting the long‐time, nonequilibrium dynamics of receptor‐ligand interactions for structured proteins in a host fluid is a formidable task, but of great importance to predicting and analyzing cell‐signaling processes and small molecule drug efficacies. Such processes take place on timescales on the order of milliseconds to seconds, so “brute‐force” real‐time, molecular or atomic simulations to determine absolute ligand‐binding rates to receptor targets and over a statistical ensemble of systems are not currently feasible. In the current study, we implement on real protein systems a previously developed 3–5 hybrid molecular dynamics/Brownian dynamics algorithm, which takes advantage of the underlying, disparate timescales involved and overcomes the limitations of brute‐force approaches. The algorithm is based on a multiple timescale analysis of the total system Hamiltonian, including all atomic and molecular structure information for the system: water, ligand, and receptor. In general, the method can account for the complex hydrodynamic, translational‐orientational diffusion aspects of ligand‐docking dynamics as well as predict the actual or absolute rates of ligand binding. To test some of the underlying features of the method, simulations were conducted here for an artificially constructed spherical protein “made” from the real protein insulin. Excellent comparisons of simulation calculations of the so‐called grand particle friction tensor to analytical values were obtained for this system when protein charge effects were neglected. When protein charges were included, we found anomalous results caused by the alteration of the spatial, microscopic structure of water proximal to the protein surface. Protein charge effects were found to be highly significant and consistent with the recent hypothesis of Hoppert and Mayer (Am Sci 1999;87:518–525) for charged macromolecules in water, which involves the formation of a “water dense region” proximal to the charged protein surface followed by a “dilute water region. ” We further studied the algorithm on a D‐peptide/HIV capside protein system and demonstrated the algorithms utility to study the nonequilibrium docking dynamics in this contemporary problem. In general, protein charge effects, which alter water structural properties in an anomalous fashion proximal to the protein surface, were found to be much more important than the so‐called hydrodynamic interaction effects between ligand and receptor. The diminished role of hydrodynamic interactions in protein systems allows for a much simpler overall dynamic algorithm for the nonequilibrium protein‐docking process. Further studies are now underway to critically examine this simpler overall algorithm in analyzing the nonequilibrium protein‐docking problem. Proteins 2003;52:339–348. © 2003 Wiley‐Liss, Inc.
Leveling the Playing Field: Supporting Neurodiversity Via Virtual Realities

Neurodiversity is a term that encapsulates the diverse expression of human neurology. By thinking in broad terms about neurological development, we can become focused on delivering a diverse set of design features to meet the needs of the human condition. In this work, we move toward developing virtual environments that support variations in sensory processing. If we understand that people have differences in sensory perception that result in their own unique sensory traits, many of which are clustered by diagnostic labels such as Autism Spectrum Disorder (ASD), Sensory Processing Disorder, Attention-Deficit/Hyperactivity Disorder, Rett syndrome, dyslexia, and so on, then we can leverage that knowledge to create new input modalities for accessible and assistive technologies. In an effort to translate differences in sensory perception into new variations of input modalities, we focus this work on ASD. ASD has been characterized by a complex sensory signature that can impact social, cognitive, and communication skills. By providing assistance for these diverse sensory perceptual abilities, we create an opportunity to improve the interactions people have with technology and the world. In this paper, we describe, through a variety of examples, the ways to address sensory differences to support neurologically diverse individuals by leveraging advances in virtual reality.
Autonomous Hard Real-time Response in Safety-Critical Systems

Autonomy introduces computational complexity, particularly when multiple behaviors are required to handle events that compromise safety. A real-time control plan specifies actions plus a resource schedule to guarantee real-time constraints will be met during plan execution. The Cooperative Real-time Control Architecture (CIRCA) was designed to automatically create and execute real-time control plans. We describe CIRCA, its application to UCAV automation, and ongoing efforts to apply this approach to autonomous spacecraft operations and satellite inspection missions.
The psychometric properties of the Big Five inventory-10 (BFI-10) including correlations with subjective and psychological well-being

The article sums up the results of a psychometric study carried out on a sample of Romanian students (N = 496; 193 females) in order to assess the psychometric qualities of Big Five Inventory-10 (BFI-10). The questionnaire measures the 5 factors of personality from the Five Factors model. The convergent validity is demonstrated by the fact that BFI-10 correlates with the measures for: subjective well-being like happiness, life satisfaction, positive and negative affect and psychological well-being and its dimensions. Internal consistency is acceptable given that we evaluated an extra-short scale with two items per factor, although much reduced in comparison with the instruments with a large number of items. The confirmatory factorial analysis revealed a five-factor structure similar to the original structure with the modification of the factors Extraversion, Agreeableness, and Neuroticism. We consider that the application of BFI-10 must be accompanied and correlated with other instruments when it comes to assessing personality. It is necessary that the instrument BFI-10 should be perfected by redefining the items it contains.
Serotonin Depletion and Barrel Cortex Development : Impact of Growth Impairment vs . Serotonin Effects on Thalamocortical Endings

amine; 5-HT) in barrel cortex development. Systemic administration of 5-HT-depleting drugs reduces cross-sectional whisker barrel areas in the somatosensory cortex (SSC) of neonatal rats. Here we assess the relative impact on barrel pattern formation of (i) 5-HT depletion and (ii) decreased brain growth, which is often associated with pharmacological 5-HT depletion, by comparing the effects of 5-HT-depleting drugs with those of reduced protein intake. Left hemisphere 5-HT levels in the SSC and right hemisphere whisker barrel areas were assessed at postnatal day 6 (P6) in the same animal following injection of p-chloroamphetamine (PCA) or p-chlorophenylalanine (PCPA) at P0. Both drugs significantly reduced cortical 5-HT content and mean barrel areas at P6, but also body and brain growth. Differences in brain weight accounted for 84.4% of the variance in barrel size, with negligible contributions by cortical 5-HT content. PCPA-treated animals sacrificed at P14 yielded similar trends, albeit less pronounced. Finally, reduced protein intake resulted in lower body weight and cortical 5-HT levels at P6, but yielded no change in brain weight or mean barrel area. Barrel formation therefore appears markedly less sensitive to 5-HT depletionper se than to drug-induced growth impairment.
Ranking Linked-Entities in a Sentiment Graph

Reputation analysis is naturally associated to a sentiment analysis task of the targeted named-entities. This analysis leverages on a sentiment lexicon that includes general sentiment words that characterize the general sentiment towards the targeted named-entity. However, in most cases, target entities are themselves part of the sentiment lexicon, creating a loop from which it is difficult to infer an entity reputation. Sometimes, the entity became a reference in the domain and is vastly cited as an example of a highly reputable entity. For example, in the movies domain it is not uncommon to see reviews citing Batman or Anthony Hopkins as esteemed references. In this paper we describe a three-step procedure to perform reputation analysis of linked entities. First, our method jointly extracts named entities reputation and a domain specific sentiment lexicon. Second, an entities graph is created by analyzing cross-citations in subjective sentences. Third, the entities reputation are updated through an iterative optimization that exploits the graph of the linked-entities. The proposed approach closely models real-world domains, where domain specific jargon is common and entities are so popular that they become widely used as sentiment references. The evaluation on a graph with 12,687 vertices, of which 3,177 are linked entities and 9,510 are sentiment words, shows that our approach can improve the correct detection of an entity's reputation.
A Modeling Environment for the Simulation and Design of Charge Redistribution DACs Used in SAR ADCs

The optimal design of successive approximation register (SAR) analog-to-digital converters (ADCs) requires the accurate estimate of nonlinearity and parasitic capacitance effects in the feedback charge-redistribution digital-to-analog converters (DACs). Since the effects of both mismatch and stray capacitances depend on the specific array topology, complex calculations, custom modeling and heavy simulations in common circuit design environments are often required. This paper presents a novel MATLAB-based numerical tool to assist the design of classic, split and with attenuation capacitor binary weighted capacitive array topologies with an even number of bits from 6 to 14. The tool allows to perform both parametric and statistical simulations taking into account capacitive mismatch and parasitic capacitances in order to compute both differential- (DNL) and integral nonlinearity (INL). Signal-to-noise plus distortion ratio (SNDR) and Effective Number of Bits (ENoB) degradation due to static non-linear effects is also estimated. An excellent agreement with the results obtained by the available circuit simulators (e.g. Cadence Spectre) is shown but featuring up to 10^4-times shorter simulation time.
Extremality Properties for the Basic Polarization Transformations

We study the extremality of the BEC and the BSC for Gallager's reliability function $E_0$ evaluated under the uniform input distribution for binary input DMCs from the aspect of channel polarization. In particular, we show that amongst all B-DMCs of a given $E_0(\rho)$ value, for a fixed $\rho \geq 0$, the BEC and BSC are extremal in the evolution of $E_0$ under the one-step polarization transformations.