Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA Sequence Contribution to Nucleosome Distribution

DNA in eukaryotes is efficiently and compactly organized into chromatin, the fundamental subunit of which is the nucleosome: approximately 150 bp of DNA spooled 1.65 times around a histone octamer. The location and density of nucleosomes play a role in regulating nuclear processes including transcription, replication, recombination, and repair. Mechanisms acting in trans, like adenosine triphosphate (ATP)-dependent remodellers and cellular memory complexes, as well as in cis features intrinsic to the DNA sequence itself regulate the location and density of nucleosomes. Here, we review the three cis acting DNA sequence features that affect the distribution of nucleosomes: (1) two frameworks defining the relationship between the histone octamer and the underlying DNA sequence (nucleosome occupancy and nucleosome position, then statistical positioning and a nucleosome positioning code), (2) the organization of DNA into the nucleosome core particle, and (3) specific DNA sequence features and DNA templates that promote or inhibit the formation of nucleosomes. We close by describing three computational algorithms trained on DNA sequence that have been used to predict nucleosome position and density. In summary, we hope to draw attention to multiple aspects of DNA sequence that specify organization of sequence into nucleosomes and influence the distribution of nucleosomes in eukaryotic genomes. Introduction In eukaryotic genomes, DNA is spooled around histone octamers to form nucleosomes, the distributions of which affect DNA-templated processes including transcription, replication, recombination, and repair. Mechanisms acting in trans and in cis play a role in the distribution of nucleosomes. Adenosine triphosphate (ATP)-dependent remodellers, complexes that covalently modify histones, and cellular memory complexes act in trans to alter the relationship between the DNA and the histone octamer. Features intrinsic to the DNA sequence itself are in cis determinants of nucleosome distribution. The first observations that features inherent in the DNA sequence favour nucleosome formation appeared more than three decades ago (Lohr et al., 1977; Trifonov, 1980; Trifonov and Sussman, 1980; Mengeritsky and Trifonov, 1983; Hsieh and Griffith, 1988; Wang et al., 1996; Wang and Griffith, 1996). The degree to which DNA sequence plays a role in regulating and organizing nucleosomal arrays remains one of the fundamental unanswered questions in eukaryotic biology. Here we describe the features of DNA sequence that specify organization of that sequence into nucleosomes. Defining the language for the distribution of nucleosomes with respect to the underlying
Project proposal for FRITEK , 2007 : ReqSec : Requirements for Secure Information Systems

The project will develop and evaluate methodology and tool support for security requirements engineering, integrated with mainstream software development methods. The main features of the contribution will be as follows: • The methodology shall be lightweight, meant to be used primarily by mainstream software developers rather than by security experts • The methodology shall be integrated with popular methodologies for software development in general, so that security requirements can be considered in the normal run of development activities rather than as a separate activity on the side • Tools delivered in the project will not be developed from scratch but rather as add-ons to existing modelling and requirements management tools. This makes it more realistic to achieve industry-strength functionality and usability within a limited budget, and also ensures that tools will be applicable in a larger development context • Thorough evaluations (e.g., experiments, case studies) shall ensure that the methodology provides empirically founded advice on when and how to apply various techniques and tools.
Complex objects ranking: a relational data mining approach

A key task in data mining and information retrieval is learning preference relations. Most of methods reported in the literature learn preference relations between objects which are represented by attribute-value pairs or feature vectors (propositional representation). The growing interest in data mining techniques which are able to directly deal with more sophisticated representations of complex objects, motivates the investigation of relational learning methods for learning preference relations. In this paper, we present a probabilistic relational data mining method which permits to model preference relations between complex objects. Preference relations are then used to rank objects. Experiments on two ranking problems for scientific literature mining prove the effectiveness of the proposed method.
Good study design and analysis plans as features of ethical research with humans.

T his article highlights for investigators and institutional review board (IRB) members the importance of a methodological-ly well-designed study and statistically valid analysis plan for the ethical conduct of research with humans. We describe features of good study designs and statistical plans and explain their relevance to ethical research. Another author has considered this general area for a statistical audience. 1 We emphasize that our goal here is not to compare the ethical merits of competing statistical approaches; that is also material for a statistical audience. We focus our attention on three categories of research methodology: study design; data analysis/statistical methods; and sample size considerations. For full details about study design and statistical methodology, we suggest texts on introductory bio-statistics, 2 clinical trial design and methods, 3 and epidemiological methods. 4 Throughout, we use protocol examples based on our experiences working with our respective IRBs; we have changed some details to protect the confidentiality of the material. n Does the general study design enable the investigator to address the aims and hypotheses? Investigators must choose a study design that allows them to address the hypotheses. For example, consider an educational intervention to reduce the distress caused by a false positive mammogram. The best study design would be a randomized trial that assigned patients to either receive the intervention or not. This would ensure that any changes seen over time are due to the educational intervention rather than some other factor. A deviation from this ideal design might be contemplated if practical considerations required, but the implications of this should be discussed and evaluated. If an inappropriate design is chosen, there is little chance that the study merits the risks to subjects because the study cannot answer the questions and hypotheses developed to meet its aims. Consider a recently proposed pilot study designed to determine the safety of a new surgical technique. The investigators proposed random-izing subjects to receive the new surgical technique or the standard technique. Since this is a pilot safety study, randomization is probably not an appropriate design, in that ran-domization more commonly is used for efficacy comparisons. In this case, efficacy comparisons were specifically planned for a future study. n Are outcomes clearly defined? The investigator must put forward and defend a primary outcome measure by which the study's hypothesis is to be addressed. Returning to the example of an intervention to reduce the distress caused by …
A Research of MapReduce with GPU Acceleration

MapReduce is an efficient distributed computing model on large data sets. The data processing is fully distributed on huge amount of nodes, and a MapReduce cluster is of highly scalable. However, single-node performance is gradually to be a bottleneck in computeintensive jobs, which makes it difficult to extend the MapReduce model to wider application fields such as largescale image processing and image mining. As an attempt, this paper presents an approach of GPU-accelerated MapReduce, which is implemented by Hadoop and OpenCL. Being a distinctive feature, it aims at general and inexpensive hardware platform, and it is seamlessly integrated with Apache Hadoop, the most widely used MapReduce framework. As a heterogeneous multi-machine and many-core architecture, it targets at both dataand compute-intensive applications. An almost 2 times performance improvement has been validated, without any special optimization.
LOUD : An Immersive Music Exploration System

We propose a system, called LOUD, for immersive, multidimensional music exploration based on music similarity algorithms. LOUD permits non-linear browsing, searching, and navigation of songs, genres, and musical properties using a physical interface. The system follows a navigation metaphor relating the physical controls to a map of musical styles.
Assessing and Implementing Automated News Classification

Newsfeed websites sort articles by subject to make it easier for readers to search for articles in their preferred category. When uploading a new article, authors are usually tasked with selecting the most pertinent category so the new addition can then be grouped with similar articles. We are interested in further developing the framework to automatize the classification of news articles using machine learning and Natural Language Processing (NLP) techniques. We explore three classification methods: Support Vector Machine (SVM), Naïve Bayes, and Softmax Regression, and evaluate each classifier’s ability to select the appropriate category given an article’s title and a brief article description. Our results show Softmax Regression to be the best classifier among the three we evaluated.
Middle school science classroom practices in Crow and Northern Cheyenne schools

This study first identifies the teaching and learning practices that have shown to be effective in producing achievement gains with K-12 Native American students. In order to identify effective practices, policy guidelines and research studies focusing on achievement gains among Native American students were reviewed. This information was then mapped to the National Science Education Standards and aligned with a widely used mathematics and science observation instrument. The instrument was used by the author to gather data from 13 teachers by observing 68 lessons in 11 middle schools on the Crow and Northern Cheyenne Reservations in Southeast Montana. Interviewing and surveying the observed teachers generated further data. To complete the study, administrators and community members, including tribal elders, were interviewed. The literature reveals that Native American students achieve more when student centered teaching methods are used. These methods include the use of visual teaching aids, cooperative learning, and practical applications all interwoven in culturally relevant lessons. The literature supports building community support, including involvement from tribal elders. Data gathered by the researcher revealed that the teachers on and near the two reservations have more teaching experience, more science credits, and attain higher ratings for observed lessons than a national sample of teachers. A factor analysis indicated that Crow and Northern Cheyenne region teachers scored especially high in student / teacher relationships, classroom management, and content knowledge. Even though 43 percent of class time was spent in hands-on paired activities, teachers scored lower on indicators pertaining to creating classroom environments that engaged students in rigorous, meaningful learning experiences. Teachers reported on not feeling prepared to include cultural applications and meanings during instruction. Teachers attaining lower scores during classroom observations tended to cite low student motivation as their major barrier, while teachers receiving higher ratings cited external factors like the size of their classroom. The teachers described colleagues and professional development opportunities as particularly beneficial. Recommendations for further studies include additional research on effective classroom practices that produce achievement gains with Native American students, and stronger professional development focused on specific advanced teaching skills, including methods of embedding culture and community in the science curriculum.
Multiphysics modeling of metal ceramic compact for microwave processing

A multiphysics model of metal powder embedded ceramic matrix is developed in order to explore their usage for the microwave processing and sintering application. The development of the required model is facilitated by introducing the concept of the effective permittivity and permeability of the mixture of the metal powder and the base matrix. The effective dielectric and magnetic properties of the mixture are estimated by Lichtenecker's mixture formula using the complex permittivity and permeability of the iron metal powder and nano alumina powder. The simulation is carried out using COMSOL multiphysics software, where a spherical sample of the mixture is placed inside a cavity and the microwave energy is incident from the rectangular waveguide into the cavity. In the first step, the electromagnetic field distribution inside the sample is studied by varying its position inside the cavity. The electromagnetic model data is then fed to the thermal model of the COMSOL, and the simulation is carried out for 600 seconds with the microwave power of 500 watt. It is observed that the optimum heating pattern is obtained for a mixture of 5% iron metal powder and 95% Alumina. It is also noticed that the maximum temperature rise is obtained when the sample is placed at the position of maximum electric field, which is due to the fact that the iron powder has quite high value of dielectric loss factor as compared to the magnetic loss.
Advanced enterprise process modelling utilizing ontology semantics

Ontologies present a state-of-the-art technology for the provision of machine-readable semantics. Its utilization for the annotation of end-to-end enterprise/industrial processes characterizing advanced collaborative business models, largely contributes to enterprise interoperability, flexibility and component reusability. Our work in this paper emphasizes on the use of ontologies in combination with workflows for business process modeling and presents an associated methodology and architecture
Multiple query-dependent RankSVM aggregation for document retrieval

This paper is concerned with supervised rank aggregation, which aims to improve the ranking performance by combining the outputs from multiple rankers. However, there are two main shortcomings in previous rank aggregation approaches. Firstly, the learned weights for base rankers do not distinguish the differences among queries. This is suboptimal since queries vary significantly in terms of ranking. Besides, most current aggregation functions are unsupervised. A supervised aggregation function could further improve the ranking performance. In this paper, the significant difference existing among queries is taken into consideration, and a supervised rank aggregation approach is proposed. As a case study, we employ RankSVM model to aggregate the base rankers, referred to as Q.D. RSVM, and prove that Q.D. RSVM can set up query-dependent weights for different base rankers. Experimental results based on benchmark datasets show our approach outperforms conventional ranking approaches.
Power to the Parties: Cohesion and Competition in the European Parliament, 1979–2001

How cohesive are political parties in the European Parliament? What coalitions form and why? The answers to these questions are central for understanding the impact of the European Parliament on European Union policies. These questions are also central in the study of legislative behaviour in general. We collected the total population of roll-call votes in the European Parliament, from the first elections in 1979 to the end of 2001 (over 11,500 votes). The data show growing party cohesion despite growing internal national and ideological diversity within the European party groups. We also find that the distance between parties on the left-right dimension is the strongest predictor of coalition patterns. We conclude that increased power of the European Parliament has meant increased power for the transnational parties, via increased internal party cohesion and inter-party competition.
Improving precision in the quantification of cognition using the Montreal Cognitive Assessment and the Mini-Mental State Examination

ABSTRACT Background: The Montreal Cognitive Assessment (MoCA) can be used to quantify cognitive ability in older persons undergoing screening for cognitive impairment. Although highly sensitive in detecting mild cognitive impairment, its measurement precision is weakest among persons with milder forms of impairment. We sought to overcome this limitation by integrating information from the Mini-Mental State Examination (MMSE) into the calculation of cognitive ability. Methods: Data from 185 geriatric outpatients screened for cognitive impairment with the MoCA and the MMSE were Rasch analyzed to evaluate the extent to which the MMSE items improved measurement precision in the upper ability ranges of the population. Results: Adding information from the MMSE resulted in a 13.8% (13.3–14.3%) reduction in measurement error, with significant improvements in all quartiles of patient ability. The addition of three-word repetition and recall, copy pentagons, repeat sentence, and write sentence improved measurement of cognition in the upper levels of ability. Conclusions: The algorithm presented here maximizes the yield of available clinical data while improving measurement of cognitive ability, which is particularly important for tracking changes over time in patients with milder levels of impairment.
Extrema selection: accelerated evolution on neutral networks

A new modification to the genetic algorithm is presented which is specifically designed to increase the rate of evolution on fitness functions with high degrees of neutrality (mutations that do not change the individual's fitness). Instead of allowing random genetic drift to occur when most of the population has reached the same fitness, the "reproduction fitness" of individuals is set to their distance from the population centroid. This has the theoretical effect of spreading the population quickly across the neutral network, and thus finding regions of higher fitness more quickly than it mould otherwise. A series of experiments is described which shows a significant improvement in using this method on the NKp family of fitness functions, and show that this improvement is correlated with the degree of neutrality.
Image-Based Control of Two Mobile Robots for Object Pushing

This paper shows how to push an unknown object in the plane from an initial pose to a target pose with two cooperating mobile robots. On the object motion, we deliberately impose non-holonomic velocity constraint with pushing mobile robots. This yields smooth and efficient trajectories. Pushing manipulation is performed, for the first time, with a new uncalibrated image-based control scheme. This is achieved by transforming the image information to a scaled Euclidean space without using any metric information or calibration. Stability of the control law is also demonstrated.
A uniform path-loss model by power balance theory (PBT) and its application on tunnels

This paper presents a uniform path-loss prediction model with the ratio of the total effective area of the cabin to the corresponding mean cross sections by power balance theory (PBT). Furthermore, its applications on the tunnel path-loss predictions are deduced and discussed under the line-of-sight (LOS) and non-line-of-sight (NLOS) circumstances theoretically. Finally, the path-loss numerical simulations and the exponent estimation are studied and compared on a mine tunnel and a high-speed railway tunnel according to the ideal anechoic and reverberation chamber with the interest frequencies of WLAN 802/b/g/a and GSM900/TD-SCDMA services, respectively.
ANALYSING THE OVERHEAD IN MOBILE AD-HOC NETWORK WITH A HIERARCHICAL ROUTING STRUCTURE

Hierarchical routing is a common practice in actual Internet networks. This kind of routing allows nodes and routers to get small routing tables and small routing overhead. On the opposite side, routing in MANETs is flat; therefore, nodes have to learn how to reach each node in the network. It means large routing tables, impact in the look up algorithm and large routing overhead. In this paper we analyze the advantages of using hierarchical routing in MANETs under specific scenarios, showing the reduction of routing overhead from a factor of N to N/k (being N the number of nodes and k the number of subnets).
Effect of Y on microstructure of laser clad coatings reinforced by in situ synthesized TiB and TiC

Titanium-based composite coatings reinforced by in situ synthesized TiB and TiC particles were fabricated on Ti6Al4V by laser cladding. The effect of rare earth Y addition on microstructure of the coatings was investigated by means of X-ray Diffraction (XRD), Optical Microscope (OM), Scanning Electron Microscopy (SEM) and Electron Probe Micro-Analysis (EPMA). The results show that the coatings with Y mainly consist of a great amount of α-Ti cellular dendrites and few coarse/fine needle-shaped TiB, equiaxial TiC and spherical Y2O3 particles. A small amount of Y (1–3 wt.%) added to the coatings can refine the microstructure, improve the microstructural uniformity and increase the volume fraction of eutectics, which will endow the coatings with more excellent mechanical properties, such as higher strength, microhardness and toughness. When the addition content of Y varies from 2 wt. % to 3 wt. %, the microstructure of the coatings presents no significant difference except that the volume fraction of eutectics is increased gradually.
Preemption Games with Private Information

Preemption games are widely used to model economic problems such as patent races. We introduce private information into these games and allow for this information to stochastically change over time. This reflects, e.g. how R&D competitors improve their innovations over time and keep these innovations secret before patenting them. The analysis initially appears intractable because of the complexity of the equilibrium updating of beliefs on opponents' information. However, we demonstrate the existence of a class of equilibria and calculate these equilibria in closed form. We find that the expected durations in these equilibria are longer than when players' information is public but, in some cases, shorter than in the collusive outcome. Hence, R&D secrecy slows down innovation disclosure. Copyright 2011, Oxford University Press. (This abstract was borrowed from another version of this item.)
DC-Bus Signaling: A Distributed Control Strategy for a Hybrid Renewable Nanogrid

A dc nanogrid is a hybrid renewable system since renewable sources supply the average load demand, while storage and nonrenewable generation maintain the power balance in the presence of the stochastic renewable sources. The system is power electronic based, with converters being used to interface both the sources and loads to the system. The nanogrid is controlled using dc-bus signaling (DBS), a distributed control strategy in which the control nodes, the source/storage interface converters, induce voltage-level changes to communicate with the other control nodes. This paper explains the control structure required for the converters to permit the use of DBS, and explains a procedure for implementing a system-wide control law through independent control of the source/storage interface converters. Experimental results are presented to demonstrate the operation of this novel control strategy