Miracle-dz/UniFAR-FTUs huggingface dataset:
Addendum to the paper “ Codon usage domains over bacterial chromosomes

An issue left unexplained in the paper [1] is the striking quantitative difference between E. coli and B. subtilis. This is clearly visible in Fig. 6 of [1], where it is shown the probability that two genes at distance l belong to the same cluster of codon usage. Clusters are characterized by a similar codon bias and were identified using a novel information-based clustering method. While both curves decay on distances sizably longer than what could be accounted by operons, B. subtilis curve manifestly features much longer correlations. It is hard to develop a biologically well-founded explanation for such a striking difference between the two organisms. This observation and discussions with Dr. Morten Kloster (Princeton Univ.) spurred us to reconsider the issue and further pursue our analysis of the clusters. The purpose of this addendum is to describe this analysis, which allows us to point out an incorrect statement made in the paper [1], and provide an explanation for the aforementioned difference between the two organisms. The conclusion is that clusters of B. subtilis and E. coli not biased in GC content display now the same behaviour, with correlations of codons usage of the same order, roughly three times the length of the average operon. Contrary to what was previously stated, the GC content of the various clusters is not quite homogeneous and the correct values are reported in Table A1.
UWA-CSSE-2010-001 March 2010 Learning Classi er Systems for Fraud Detection

Fraud is a serious problem that costs the worldwide economy trillions of dollars annually. However, fraud detection is di cult as perpetrators actively attempt to masquerade their actions, among typically overwhelming large volumes of, legitimate activity. In this paper, we investigate the fraud detection problem and examine how learning classi er systems can be applied to it. We describe the common properties of fraud, introducing an abstract problem which can be tuned to exhibit those characteristics. We report experiments on this abstract problem with a popular real-time learning classi er system algorithm; results from our experiments demonstrating that this approach can overcome the di culties inherent to the fraud detection problem. Finally we apply the algorithm to a real-world problem (KDD Cup 1999 network intrusion detection) and show that it can achieve very good performance in this domain.
Towards a Design-Theoretic Characterisation of Software Development Process Models

Context: Effective assessment, comparison, selection and adaptation of software development processes remain an acute problem in Software Engineering practice. The quest for a unified theory which might serve this purpose is ongoing. Objective: To take a first step towards such a theory, with focus on characterising and comparing features of software development process models. Method: We consider a theory of design as problem solving and investigate how it can be applied to characterise and explicate specific process features in well known process models from the literature. The intention is to characterise emerging trade-offs between resource expenditure and risk mitigation, which result from the interplay between process efforts into problem and solution exploration vs. stakeholder validation. The analysis, at this point performed, is purely qualitative, and the treatment of resource expenditure and risk quite abstract. Results: We provide an initial characterisation and comparison of features found in a wide range of process models from the literature, within a design theoretic framework using a single building block -- the Problem Oriented Engineering (POE) Process Pattern -- that allows the characterisation of information flow, the relationship between actors, resource usage and developmental risk. Conclusions: The initial characterisation identifies repeated structure in diverse processes, which allows basic process comparison across models. The interpretations are modular, allowing the possibility of relationships between different process models to be explored. As such, the theory allows for a unified means to characterise and compare systematically key features of different process models. In being of an exploratory nature, the work has a number of limitations, which should be addressed by further research.
SS-IDS: Statistical Signature Based IDS

Security of web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based Intrusion Detection Systems (IDS). SS-IDS derives automatically the parameter profiles from the analyzed data thereby generating the Statistical Signatures. Statistical Signatures are based on modeling of normal requests and their distribution value without explicit intervention. Several attributes are used to calculate the behavior of the legitimate request on the web server. SS-IDS is best suited for the newly installed web servers which doesn’t have large number of requests in the data set to train the IDS and can be used on top of currently used signature based IDS like SNORT. Experiments conducted on real data sets have shown high accuracy up to 99.98% for predicting valid request as valid and false positive rate ranges from 3.82-7.84%.
On the use of sequential patterns mining as temporal features for music genre classification

Music can be viewed as a sequence of sound events. However, most of current approaches to genre classification either ignore temporal information or only capture local structures within the music under analysis. In this paper, we propose the use of a song tokenization method (which transforms the music into a sequence of units) in conjunction with a data mining technique for investigating the long-term structures (also known as sequential patterns) for music genre classification. Experimental results show that the introduction of sequential patterns can effectively outperform previous approach that considers local temporal features only for music genre classification.
Dissection of the genetics of Parkinson's disease identifies an additional association 5′ of SNCA and multiple associated haplotypes at 17q21

We performed a genome-wide association study (GWAS) in 1705 Parkinson's disease (PD) UK patients and 5175 UK controls, the largest sample size so far for a PD GWAS. Replication was attempted in an additional cohort of 1039 French PD cases and 1984 controls for the 27 regions showing the strongest evidence of association (P< 10−4). We replicated published associations in the 4q22/SNCA and 17q21/MAPT chromosome regions (P< 10−10) and found evidence for an additional independent association in 4q22/SNCA. A detailed analysis of the haplotype structure at 17q21 showed that there are three separate risk groups within this region. We found weak but consistent evidence of association for common variants located in three previously published associated regions (4p15/BST1, 4p16/GAK and 1q32/PARK16). We found no support for the previously reported SNP association in 12q12/LRRK2. We also found an association of the two SNPs in 4q22/SNCA with the age of onset of the disease.
Unsupervised Temporal Segmentation of Human Activities in Video

Temporal segmentation of human actions in video is central to understand and build computational models of human motion. Several issues contribute to the challenge of temporal segmentation of human motion from video. These include the large variability in the temporal scale and periodicity of human actions, the complexity of representing articulated motion, and the exponential nature of all possible movement combinations. We formulate the temporal segmentation problem as an unsupervised learning problem, and propose Aligned Cluster Analysis (ACA), an extension of standard kernel k-means clustering to cluster time series. ACA extends standard kernel k-means clustering in two ways: (1) allows the cluster means contain a variable number of features and (2) introduces a generalized dynamic time warping (DTW) kernel as temporal metric between sequences. Experimental results reported on the Weizmann and KTH action datasets demonstrate the effectiveness of ACA for factorizing human actions in video.
Localized epigenetic silencing of a damage-activated WNT enhancer limits regeneration in mature Drosophila imaginal discs

Many organisms lose the capacity to regenerate damaged tissues as they mature. Damaged Drosophila imaginal discs regenerate efficiently early in the third larval instar (L3) but progressively lose this ability. This correlates with reduced damage-responsive expression of multiple genes, including the WNT genes wingless (wg) and Wnt6. We demonstrate that damage-responsive expression of both genes requires a bipartite enhancer whose activity declines during L3. Within this enhancer, a damage-responsive module stays active throughout L3, while an adjacent silencing element nucleates increasing levels of epigenetic silencing restricted to this enhancer. Cas9-mediated deletion of the silencing element alleviates WNT repression, but is, in itself, insufficient to promote regeneration. However, directing Myc expression to the blastema overcomes repression of multiple genes, including wg, and restores cellular responses necessary for regeneration. Localized epigenetic silencing of damage-responsive enhancers can therefore restrict regenerative capacity in maturing organisms without compromising gene functions regulated by developmental signals. DOI: http://dx.doi. org/10.7554/eLife.11588. 001
Big data analytics for the virtual network topology reconfiguration use case

ABNO's OAM Handler is extended with big data analytics capabilities to anticipate traffic changes in volume and direction. Predicted traffic is used to trigger virtual network topology re-optimization. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. A heuristic algorithm to adapt current virtual topology to meet both actual demands and expected traffic matrix is proposed. Experimental assessment is carried out on UPC's SYNERGY testbed.
IQ Imbalance Compensation in OFDMA based WiMAX Digital Receivers

WiMAX is one of the most promising technologies for broadcast wireless communication and based on the IEEE 802.16 standards. The WiMAX networks support high speed transmission. But some hardware design, such as the IQ (inphase quadrature) imbalance due to direct conversion in RF front-end, limits their throughput. This problem is especially serious in high-order modulation. Most current papers of this field focus on OFDM based systems, such as wireless local area networks (WLAN). Little attention has been paid to OFDMA based WiMAX systems. So we propose some time-domain compensation strategies to work on this problem according to the preamble symbol. In order to test the performance of compensation, we carry out simulation experiments in AWGN and multi-path fading conditions respectively. Simulation results show that the proposed strategies offer good effect.
Ab initio random structure searching

It is essential to know the arrangement of the atoms in a material in order to compute and understand its properties. Searching for stable structures of materials using first-principles electronic structure methods, such as density-functional-theory (DFT), is a rapidly growing field. Here we describe our simple, elegant and powerful approach to searching for structures with DFT, which we call ab initio random structure searching (AIRSS). Applications to discovering the structures of solids, point defects, surfaces, and clusters are reviewed. New results for iron clusters on graphene, silicon clusters, polymeric nitrogen, hydrogen-rich lithium hydrides, and boron are presented.
Happily ever after? ‘Successful ageing’ and the heterosexual imaginary

‘Successful ageing’ has been a controversial concept in cultural gerontology, prompting critiques of its inherent individualism, neglect of structural inequalities and promotion of neoliberal strategies of self-care. This article aims at developing the critique of its heteronormative underpinnings. Drawing on cultural gerontology, feminist theory and queer theory, a critique of the rhetoric and visual representation of ‘successful ageing’ is developed that demonstrates the extent to which ‘success’ is equated with enactments of normative, gendered heterosexuality. The intent is not to simply map the exclusion or marginalization of queer representations but to make visible the ways in which assumptions of heterosexuality organize the visual field of ‘successful ageing’. Using examples from ‘lifestyle’ magazines and health promotion materials aimed at mid-to-later life adults, I demonstrate how the promise of ‘heterohappiness’ shapes visions of anticipatory ageing. This article forms part of ‘Media and the Ageing Body’ Special Issue.
Individual differences in attention during category learning

A central idea in many successful models of category learning—including the Generalized Context Model (GCM)—is that people selectively attend to those dimensions of stimuli that are relevant for dividing them into categories. We use the GCM to re-examine some previously analyzed category learning data, but extend the modeling to allow for individual differences. Our modeling suggests a very different psychological interpretation of the data from the standard account. Rather than concluding that people attend to both dimensions, because they are both relevant to the category structure, we conclude that it is possible there are two groups of people, both of whom attend to only one of the dimensions. We discuss the need to allow for individual differences in models of category learning, and argue for hierarchical mixture models as a way of achieving this flexibility in accounting for people’s cognition.
Memorisation methods in science education: tactics to improve the teaching and learning practice

ABSTRACT How can science teachers support students in developing an appropriate declarative knowledge base for solving problems? This article focuses on the question whether the development of students’ memory of scientific propositions is better served by writing propositions down on paper or by making drawings of propositions either by silent or muttering rehearsal. By means of a memorisation experiment with eighth- and ninth-grade students, we answer this question. In this experiment, students received instruction to memorise nine science propositions and to reproduce them afterwards. To support memorisation students were randomly assigned either to a group that received instruction to write each proposition on paper or to a group that received instruction to make a drawing about the content of the proposition. In addition, half of the students in both groups received instruction to mutter and the other half of them received instruction to write or draw in silence. The main conclusion from the experiment is that after four weeks students who had made a drawing remembered significantly more propositions than those who had memorised the propositions by writing them down. Our research further revealed that it did not matter whether students muttered or memorised silently.
Regulation and promotion of an addictive product : Spanish tobacco business in the spread of cigarette consumption (1880s to 1930s)

Tobacco is an addictive product, a big business and an important source of fiscal revenues. From 1880s to 1930s tobacco consumption spread in Western World mainly in the form of cigarettes. Supply changes such as mass production techniques, mass distribution and brand advertising and demand changes such as growing GNP or urbanization levels, interacted explaining changes and convergence in international consumption patterns. However, some differences have to be found regarding the national regulation framework. Tobacco industry was organized either under a fiscal monopoly or under a highly taxed industry mainly within an oligopoly. This paper analyses in depth and on a comparative basis, the Spanish case, paying special attention on the difference made by the regulatory framework and the lack of development of modern business tools such as brand advertising on consumption patterns and business activity. Spanish consumers were behaving as expected in the economic literature on addiction (rational addiction model) without brand advertising. That has to be related with the addictive character of tobacco consumption and more specifically with industrial organization of Spanish tobacco market. This is consistent with what is found in economic literature about addiction and market structure: for oligopoly or monopoly, if marginal cost is increasing, supply of an addictive good may be as high or higher than for perfect competition. This paper concludes that brand advertising is essential for market share mechanisms but its relation with the expansion of tobacco market is not as clear as it could be found on policies banning tobacco advertising or in Business and economic history literature. The lack of branding development in the Spanish case is just a consequence of the fact that tobacco industry was organized in Spain under a fiscal monopoly, and it was the lack of competence of the monopoly that make the Spanish products non-competitive, and as a matter of fact, the opportunities for a traditional tobacco producer of exporting or becoming a foreign direct investor were lost in Spain.
Sampling-based Planning for Sensor Scheduling in Constrained Environments

This paper considers the optimal estimation of the state of a dynamic observable using a mobile sensor. The main goal is to compute a sensor trajectory which minimizes the estimation error over a given time horizon taking into account the uncertainty in the observable dynamics and its sensing and respecting the constraints of the workspace. The main contribution is a methodology for handling arbitrary dynamics, noise models and environment constraints in a global optimization framework. It is based on sequential Monte Carlo methods and sampling-based motion planning. Three variance reduction techniques–utility sampling, shuffling, and pruning–based on importance sampling, are proposed to speed-up convergence. The developed framework is applied to two typical scenarios: a simple vehicle operating in a planar polygonal obstacle environment; a simulated helicopter searching for a moving target in a 3-D terrain. Note: the paper is a condensed version of the journal article [1].
Color Gradients and Surface Brightness Profiles of Galaxies in the Hubble Deep Field-North

We fit elliptical isophotes to the Hubble Deep Field North WFPC-2 and NICMOS data to study the rest-frame (UV218-U300)0 color profiles and rest-frame B surface brightness profiles of 33 intermediate-redshift galaxies (0.5 ≤ z ≤ 1.2) with I814 < 25 and 50 high-redshift galaxies (2.0 ≤ z ≤ 3.5) with H160 < 27. From the weighted least-squares fit to the color profiles we find that at intermediate redshifts the galaxies possess negative color gradients [⟨Δ(UV218-U300)0/Δ log r⟩ = -0.091 ± 0.007 mag dex-1], indicating a reddening toward the center of the profile similar to local samples, whereas at high redshifts the galaxies possess positive color gradients [⟨Δ(UV218-U300)0/Δ log r⟩ = 0.272 ± 0.007 mag dex-1], indicating that star formation is more centrally concentrated. Although the presence of dust can cause some reddening to occur toward the centers of the profiles seen at intermediate redshifts, it cannot explain the strong central blueing of light seen at high redshifts. Thus, we are witnessing a population of galaxies with strong positive color gradients at high redshifts that do not seem to exist in large numbers at lower redshifts. This indicates that star formation is more centrally concentrated in the distant galaxy sample, which differs from the prevalent mode of extended disk star formation that we observe in the local universe. Additionally, we find that it is critical to correct for point-spread function (PSF) effects when evaluating the surface brightness profiles since at small scale lengths and faint magnitudes, an r1/4 profile can be smoothed out substantially to become consistent with an exponential profile. After correcting for PSF effects, we find that at higher look-back time, the fraction of galaxies possessing exponential profiles have slightly decreased while the fraction of galaxies possessing r1/4 profiles have slightly increased. Our results also suggest a statistically insignificant increase in the fraction of peculiar or irregular galaxies. We compare our results with recent semianalytical models that treat galaxy formation and evolution following the cold dark matter hierarchical framework.
Practical Person-Fit Assessment with the Linear FA Model: New Developments and a Comparative Study

Linear factor analysis (FA) is, possibly, the most widely used model in psychometric applications based on graded-response or more continuous items. However, in these applications consistency at the individual level (person fit) is virtually never assessed. The aim of the present study is to propose a simple and workable approach to routinely assess person fit in FA-based studies. To do so, we first consider five potentially appropriate indices, of which one is a new proposal and the other is a modification of an existing index. Next, the effectiveness of these indices is assessed by using (a) a thorough simulation study that attempts to mimic realistic conditions, and (b) an illustrative example based on real data. Results suggest that the mean-squared lico index and the personal correlation work well in conjunction and can function effectively for detecting different types of inconsistency. Finally future directions and lines of research are discussed.
An empirical investigation into the nature of test smells

Test smells have been defined as poorly designed tests and, as reported by recent empirical studies, their presence may negatively affect comprehension and maintenance of test suites. Despite this, there are no available automated tools to support identification and repair of test smells. In this paper, we firstly investigate developers' perception of test smells in a study with 19 participants. The results show that developers generally do not recognize (potentially harmful) test smells, highlighting that automated tools for identifying such smells are much needed. However, to build effective tools, deeper insights into the test smells phenomenon are required. To this aim, we conducted a large-scale empirical investigation aimed at analyzing (i) when test smells occur in source code, (ii) what their survivability is, and (iii) whether their presence is associated with the presence of design problems in production code (code smells). The results indicate that test smells are usually introduced when the corresponding test code is committed in the repository for the first time, and they tend to remain in a system for a long time. Moreover, we found various unexpected relationships between test and code smells. Finally, we show how the results of this study can be used to build effective automated tools for test smell detection and refactoring.