Miracle-dz/UniFAR-FTUs huggingface dataset:
Insights into the Structures of DNA Damaged by Hydroxyl Radical: Crystal Structures of DNA Duplexes Containing 5-Formyluracil

Hydroxyl radicals are potent mutagens that attack DNA to form various base and ribose derivatives. One of the major damaged thymine derivatives is 5-formyluracil (fU), which induces pyrimidine transition during replication. In order to establish the structural basis for such mutagenesis, the crystal structures of two kinds of DNA d(CGCGRATfUCGCG) with R = A/G have been determined by X-ray crystallography. The fU residues form a Watson-Crick-type pair with A and two types of pairs (wobble and reversed wobble) with G, the latter being a new type of base pair between ionized thymine base and guanine base. In silico structural modeling suggests that the DNA polymerase can accept the reversed wobble pair with G, as well as the Watson-Crick pair with A.
Prevalence and Factors Associated With Circadian Blood Pressure Patterns in Hypertensive Patients

Ambulatory blood pressure (BP) monitoring has become useful in the diagnosis and management of hypertensive individuals. In addition to 24-hour values, the circadian variation of BP adds prognostic significance in predicting cardiovascular outcome. However, the magnitude of circadian BP patterns in large studies has hardly been noticed. Our aims were to determine the prevalence of circadian BP patterns and to assess clinical conditions associated with the nondipping status in groups of both treated and untreated hypertensive subjects, studied separately. Clinical data and 24-hour ambulatory BP monitoring were obtained from 42 947 hypertensive patients included in the Spanish Society of Hypertension Ambulatory Blood Pressure Monitoring Registry. They were 8384 previously untreated and 34 563 treated hypertensives. Twenty-four-hour ambulatory BP monitoring was performed with an oscillometric device (SpaceLabs 90207). A nondipping pattern was defined when nocturnal systolic BP dip was <10% of daytime systolic BP. The prevalence of nondipping was 41% in the untreated group and 53% in treated patients. In both groups, advanced age, obesity, diabetes mellitus, and overt cardiovascular or renal disease were associated with a blunted nocturnal BP decline (P<0.001). In treated patients, nondipping was associated with the use of a higher number of antihypertensive drugs but not with the time of the day at which antihypertensive drugs were administered. In conclusion, a blunted nocturnal BP dip (the nondipping pattern) is common in hypertensive patients. A clinical pattern of high cardiovascular risk is associated with nondipping, suggesting that the blunted nocturnal BP dip may be merely a marker of high cardiovascular risk.
The effect of group size on people's attitudes and cooperative behaviors toward robots in interactive gameplay

This paper contributes to the study of interaction between groups of people and groups of robots by examining the effect of group size on people's attitudes and behaviors toward robots as interaction partners. Our work is motivated by psychological research on human intergroup dynamics, particularly the interindividual-intergroup discontinuity effect, which suggest that interactions among groups are more competitive than interactions among individuals. To test the discontinuity effect in the context of human-robot interaction, we conducted a between-subjects experiment with four conditions, derived by differentiating the ratio of humans to robots in the interaction (one or two humans interacting with one or two robots). Participants played a game with robots in which they were given a chance to exhibit competitive and cooperative behaviors, which we tracked. We also measured changes in participants' attitudes toward robots following gameplay. Our results show that people playing in groups behave more competitively towards the robots than individual human players. However, participants' attitudes toward robots did not change after the short-term interaction.
Evidence for actin filament-microtubule interaction mediated by microtubule-associated proteins

We have used low shear viscometry and electron microscopy to study the interaction between pure actin filaments and microtubules. Mixtures of microtubules having microtubule-associated proteins (MAPs) with actin filament have very high viscosities compared with the viscosities of the separate components. MAPs themselves also cause a large increase in the viscosity of actin filaments. In contrast, mixtures of actin filaments with tubulin polymers lacking MAPs have low viscosities, close to the sum of the viscosities of the separate components. Our interpretation of these observations is that there is an interaction between actin filaments and microtubules which requires MAPs. This interaction is inhibited by ATP and some related compounds. Electron micrographs of thin sections through mixtures of actin and microtubules show numerous close associations between the two polymers which may be responsible for their high viscosity.
An agent-supported simulation architecture for manufacturing systems

The manufacturing field is an area where the application of simulation is an essential tool to validate methods and architectures before applying them on the factory floor. Despite the great number of simulation tools that are available, most of them do not take into account the specific requirements for the "new manufacturing era". However, Multiagent System technology has demonstrated its utility in manufacturing system modeling and implementation. Agenthood features such as proactivity, reactivity, and sociability may also be useful to associate them with the specific simulation needs of the new manufacturing requirements. In this paper, we present an Agent-Based approach to define a Simulation Architecture in order to build an Agent-Supported Simulation Tool for Manufacturing Systems. The different roles that will be played by agents are defined taking into account the specific manufacturing simulation requirements. The interaction scenarios are specified to facilitate manufacturing simulation in an appropriate and flexible way.
Evaluation of Intelligent Intrusion Detection Models

This paper discusses an evaluation methodology that can be used to assess the performance of intelligent techniques at detecting, as well as predicting, unauthorised activities in networks. The effectiveness and the performance of any developed intrusion detection model will be determined by means of evaluation and validation. The evaluation and the learning prediction performance for this task will be discussed, together with a description of validation procedures. The performance of developed detection models that incorporate intelligent elements can be evaluated using well known standard methods, such as matrix confusion, ROC curves and Lift charts. In this paper these methods, as well as other useful evaluation approaches, are discussed.
Object edge contour localisation based on HexBinary feature matching

This paper addresses the issue of localising object edge contours in cluttered backgrounds to support robotics tasks such as grasping and manipulation and also to improve the potential perceptual capabilities of robot vision systems. Our approach is based on coarse-to-fine matching of a new recursively constructed hierarchical, dense, edge-localised descriptor, the HexBinary, based on the HexHog descriptor structure first proposed in [1]. Since Binary String image descriptors [2]-[5] require much lower computational resources, but provide similar or even better matching performance than Histogram of Orientated Gradient (HoG) descriptors, we have replaced the HoG base descriptor fields used in HexHog with Binary Strings generated from first and second order polar derivative approximations. The ALOI [6] dataset is used to evaluate the HexBinary descriptors which we demonstrate to achieve a superior performance to that of HexHoG [1] for pose refinement. The validation of our object contour localisation system shows promising results with correctly labelling ~ 86% of edgel positions and mis-labelling ~ 3%.
Parametrization and computations in shape spaces with area and boundary invariants

—Shape spaces play an important role in several applications in robotics, most notably by providing a manifold structure on which to perform motion planning, control, behavior discovery and related algorithmic operations. Many classical approaches to deﬁning shape spaces are not well suited to the needs of robotics. In this abstract, we outline an approach to deﬁning shape spaces that address the needs of such problems, which often involve constraints on area/volume, perimeter/boundary, etc. Using the simple example of the space of constant-area and constant-perimeter triangles, which are represented as Riemannian manifolds, we demonstrate efﬁcient solutions to problems involving continuous shape evolution, optimal sampling, etc.
Tripartite Modular Multiplication using Toom-Cook Multiplication

Modular multiplication is the fundamental operation in most public-key cryptosystem. Therefore, the efficiency of modular multiplication directly affects the efficiency of whole crypto-system. This paper presents an efficient modular multiplication algorithm for large integer. The proposed algorithm integrates with three existing algorithm, Barrett Algorithm and Montgomery algorithm for modular multiplication, Toom-Cook algorithm for multiplication. This algorithm execution done in parallel way so that enhance the performance. These algorithms Analysis with respect to their performance and compare to other modular multiplication algorithms.
Forest Height Estimation Using P- Band Pol-InSAR Data

A P-band Pol-InSAR dataset acquired over a maritime pine forest is evaluated for forest height estimation. First, a time-frequency inversion methodology is presented. Good r esults have been obtained (2 m RMS error over 27 stands). However, since the method is adapted to airborne SAR data, we further investigate methods that could be used to invert spaceborne SAR data. Possible adaptations of the RVoG model to P band are studied through two key effects: the effect of ground decorr elation and the effect of vertically variable extinction within the canopy. The results show that the ground decorrelation may be neglig ible if the decorrelation is small, whereas the effect of the vert ical distribution of the extinction is important and needs to be taken into account.
Rack-scale disaggregated cloud data centers: The dReDBox project vision

For quite some time now, computing systems servers, whether low-power or high-end ones designs are created around a common design principle: the main-board and its hardware components form a baseline, monolithic building block that the rest of the hardware/software stack design builds upon. This proportionality of compute/memory/network/storage resources is fixed during design time and remains static throughout machine lifetime, with known ramifications in terms of low system resource utilization, costly upgrade cycles and degraded energy proportionality. dReDBox takes on the challenge of revolutionizing the low-power computing market by breaking server boundaries through materialization of the concept of disaggregation. Besides proposing a highly modular software-defined architecture for the next generation datacentre, dRedBox will specify, design and prototype a novel hardware architecture where SoC-based microservers, memory modules and accelerators, will be placed in separated modular server trays interconnected via a high-speed, low-latency opto-electronic system fabric, and be allocated in arbitrary sets, as driven by fit-for-purpose resource/power management software. These blocks will employ state-of-the-art low-power components and be amenable to deployment in various integration form factors and target scenarios. dRedBox aims to deliver a full-fledged, vertically integrated datacentre-in-a-box prototype to showcase the superiority of disaggregation in terms of scalability, efficiency, reliability, performance and energy reduction which will be demonstrated in three pilot use-cases.
Novel domain combinations in proteins encoded by chimeric transcripts

Motivation: Chimeric RNA transcripts are generated by different mechanisms including pre-mRNA trans-splicing, chromosomal translocations and/or gene fusions. It was shown recently that at least some of chimeric transcripts can be translated into functional chimeric proteins. Results: To gain a better understanding of the design principles underlying chimeric proteins, we have analyzed 7,424 chimeric RNAs from humans. We focused on the specific domains present in these proteins, comparing their permutations with those of known human proteins. Our method uses genomic alignments of the chimeras, identification of the gene–gene junction sites and prediction of the protein domains. We found that chimeras contain complete protein domains significantly more often than in random data sets. Specifically, we show that eight different types of domains are over-represented among all chimeras as well as in those chimeras confirmed by RNA-seq experiments. Moreover, we discovered that some chimeras potentially encode proteins with novel and unique domain combinations. Given the observed prevalence of entire protein domains in chimeras, we predict that certain putative chimeras that lack activation domains may actively compete with their parental proteins, thereby exerting dominant negative effects. More generally, the production of chimeric transcripts enables a combinatorial increase in the number of protein products available, which may disturb the function of parental genes and influence their protein–protein interaction network. Availability: our scripts are available upon request. Contact: avalencia@cnio.es Supplementary information: Supplementary data are available at Bioinformatics online.
Simulating hci for all

Computers offer valuable assistance to people with physical disabilities. However designing human-computer interfaces for these users is complicated. The range of abilities is more diverse than for able-bodied users, which makes analytical modelling harder. Practical user trials are also difficult and time consuming. I am developing a simulator to help with the evaluation of assistive interfaces. It can predict the likely interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different disabilities and for different levels of skills.
Classification of Copper Alloys Microstructure using Image Processing and Neural Network

: The most important aspect of any engineering material is its structure. The methods used to accurately determine the material microstructures is a very time-consuming process, causes operator fatigue, and it is prone to human errors and inconsistency. There are two computational approaches, a feature features and a neural network algorithm, are used separately for classifying and detection of surface textures in the field of remote sensing, science, medicine, journalism, advertising, design, education and entertainment. In this paper, a combination of the two approaches has been utilized to classify and to detect copper and copper alloys microstructure using image process, texture features and neural network. The overall average discrimination rate results from the combined approaches are about 97.6%. This paper offers a reliable basis for the classification and characterization of microscopic images by image processing and neural network.
Improved adaptive demosaicking using directional weighting

Color filter array (CFA) interpolation is the integral part of image processing for single sensor digital cameras. In this paper, we present a novel algorithm based on directional weighting and adaptive edge detection. We evaluate the edges by using improved edge detection method and estimate the missing color values in different directions. By calculating differences of directional gradients, the threshold will be determined when we calculate the pixel values according to weighting coefficients. Experimental results show that the proposed method yields visually pleasant results and outperforms existing demosaicking methods in composite peak signal-to-noise ratio (CPSNR). In addition, the computational complexity of the proposed method is comparable to the existing methods.
Statistical Cryptography using a Fisher-Schrodinger Model

A principled procedure to infer a hierarchy of statistical distributions possessing ill-conditioned eigenstructures, from incomplete constraints, is presented. The inference process of the pdfs employs the Fisher information as the measure of uncertainty, and, utilizes a semi-supervised learning paradigm based on a measurement-response model. The principle underlying the learning paradigm involves providing a quantum mechanical connotation to statistical processes. The inferred pdfs constitute a statistical host that facilitates the encryption/decryption of covert information (code). A systematic strategy to encrypt/decrypt code via unitary projections into the null spaces of the ill-conditioned eigenstructures, is presented. Numerical simulations exemplify the efficacy of the model
Dynamic stator-flux-oriented induction machine control for electric vehicle application

Induction machines are affordable and robust, presenting a valid option for electric vehicles. Many control schemes for such machines are known and have been published. With regard to fast torque dynamics and robustness against parameter variation, stator-flux-oriented control is a very favorable option. This paper presents a stator-flux oriented control which bases on a comprehensive model of the induction machine. A sophisticated compensation of non-ideal converter behavior further enhances the results obtained. These results are documented by measurements and verify excellent performance: Fast response without current overshoot uses the rating of the converter optimally. Dynamic field weakening keeps excellent torque response in the field-weakening range without any voltage margin, too. Fast torque dynamics are not required for fulfilling the commands issued by the driver but for efficient disturbance rejection and additional features like slip-slide control and maximum-traction-point detection. For such features, the underlying torque control defines the performance - consequently, fast and precise reaction is requested.
The coalitional switch-off game of service providers

This paper studies a significant problem in green networking called switching off base stations in case of cooperating service providers by means of stochastic geometric and coalitional game tools. The coalitional game herein considered is played by service providers who cooperate in switching off base stations. When they cooperate, any mobile is associated to the nearest BS of any service provider. Given a Poisson point process deployment model of nodes over an area and switching off base stations with some probability, it is proved that the distribution of signal to interference plus noise ratio remains unchanged while the transmission power is increased up to preserving the quality of service. The coalitional game behavior of a typical player is called to be hedonic if the gain of any player depends solely on the members of the coalition to which the player belongs, thus, the coalitions form as a result of the preferences of the players over their possible coalitions' set. We utilize the Nash-stable core for determining the coalitions of service providers.
Index structures and top-k join algorithms for native keyword search databases

For supporting keyword search on structured data, current solutions require large indexes to be built that redundantly store subgraphs called neighborhoods. Further, for exploring keyword search results, large graphs have to be loaded into memory. We propose a solution, which employs much more compact index structures for neighborhood lookups. Using these indexes, we reduce keyword search result exploration to the traditional database problem of top-k join processing, enabling results to be computed efficiently. In particular, this computation can be performed on data streams successively loaded from disk (i.e., does not require the entire input to be loaded at once into memory). For supporting this, we propose a top-k procedure based on the rank join operator, which not only computes the k-best results, but also selects query plans in a top-k fashion during the process. In experiments using large real-world datasets, our solution reduced storage requirements and also outperformed the state-of-the-art in terms of performance and scalability.
A Feature Level Fusion in Similarity Matching to Content-Based Image Retrieval

This paper presents a fusion-based similarity matching framework for content-based image retrieval on a combination of global, semi-global and local region specific features at different levels of abstraction. In this framework, an image is represented by global color and edge histogram descriptors, semi-global color and texture descriptors from grid based overlapping sub-images and local color features from a clustering-based segmented regions. As a result, image similarities are obtained through a weighted combination of overall similarity fusing global, semi-global and local region-based image level similarities. This fusing approach decreases the impact of inaccurate segmentation and increases retrieval effectiveness as constituent features are of a complementary nature. The experimental results on a general-purpose image database indicate that the aggregation or fusion-based technique provides an effective and flexible tool for similarity calculation based on a combination of descriptors from different levels of image representation
Cooperative resource allocation in OFDM-based multicell cognitive radio systems

In this paper, we investigate the resource allocation problem for an orthogonal frequency division multiplexing (OFDM) based multicell cognitive radio (CR) system. Secondary users (SUs) served by the CR system distribute randomly in multiple cells and share radio spectrum with primary users (PUs) in a licensed system, where the interference introduced to the PUs must be kept below their tolerable thresholds. In our system model, SUs in different CR cells can transmit signals with the same OFDM subchannel, so cochannel interference among the SUs should also be considered. We propose an efficient algorithm, named as multi-level waterfilling (MLWF), to allocate power among OFDM subchannels for all CR cells by jointly considering transmission power and interference constraints. The MLWF always allocates much power to a subchannel which generates less interference to the PUs. Simulation results show that our proposed algorithm provides better performance than other existing ones. Moreover, the complexity of the MLWF is much lower than other representative algorithms.