Punctuated Equilibrium in Software Evolution

The approach based on paradigm of self-organized criticality proposed for experimental investigation and theoretical modelling of software evolution. The dynamics of modifications studied for three free, open source programs Mozilla, Free-BSD and Emacs using the data from version control systems. Scaling laws typical for the self-organization criticality found. The model of software evolution presenting the natural selection principle is proposed. The results of numerical and analytical investigation of the model are presented. They are in a good agreement with the data collected for the real-world software.Comment: 4 pages, LaTeX, 2 Postscript figure

YouTube Video Project: A Cool Way to Learn Communication Ethics

The millennial generation embraces new technologies as a natural way of accessing and exchanging information, staying connected, and having fun. YouTube, a video-sharing site that allows users to upload, view, and share video clips, is among the latest “cool” technologies for enjoying quick laughs, employing a wide variety of corporate activities, and also communicating relevant, engaging instructional content for today’s students. This article describes a YouTube video class project that is a natural fit with today’s students because it involves cutting-edge social media while addressing a critical component of professional development—communication ethics. This project encourages critical thinking, creativity, and applied learning in a team environment using a “cool” new media tool

Empirical Studies of Evolving Systems

This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analysed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together

Face recognition system using fringe projection and moiré: characterization with fractal parameters

We show a new method for face recognition which combines the projection of structures with different characteristics (fringes, bars or grids, dots or speckle) over the face. These projections will then allow the creation of a computer-generated moiré pattern over which different kinds of fractal and complex geometry parameters are then measured. Such parameters will then be used as inputs for a neuro-symbolic hybrid system. Here, we analyze the incidence of some parameters on the efficience for the face recognition method

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible

Human phosphodiesterase 4D7 (PDE4D7) expression is increased in TMPRSS2-ERG positive primary prostate cancer and independently adds to a reduced risk of post-surgical disease progression

background: There is an acute need to uncover biomarkers that reflect the molecular pathologies, underpinning prostate cancer progression and poor patient outcome. We have previously demonstrated that in prostate cancer cell lines PDE4D7 is downregulated in advanced cases of the disease. To investigate further the prognostic power of PDE4D7 expression during prostate cancer progression and assess how downregulation of this PDE isoform may affect disease outcome, we have examined PDE4D7 expression in physiologically relevant primary human samples. methods: About 1405 patient samples across 8 publically available qPCR, Affymetrix Exon 1.0 ST arrays and RNA sequencing data sets were screened for PDE4D7 expression. The TMPRSS2-ERG gene rearrangement status of patient samples was determined by transformation of the exon array and RNA seq expression data to robust z-scores followed by the application of a threshold >3 to define a positive TMPRSS2-ERG gene fusion event in a tumour sample. results: We demonstrate that PDE4D7 expression positively correlates with primary tumour development. We also show a positive association with the highly prostate cancer-specific gene rearrangement between TMPRSS2 and the ETS transcription factor family member ERG. In addition, we find that in primary TMPRSS2-ERG-positive tumours PDE4D7 expression is significantly positively correlated with low-grade disease and a reduced likelihood of progression after primary treatment. Conversely, PDE4D7 transcript levels become significantly decreased in castration resistant prostate cancer (CRPC). conclusions: We further characterise and add physiological relevance to PDE4D7 as a novel marker that is associated with the development and progression of prostate tumours. We propose that the assessment of PDE4D7 levels may provide a novel, independent predictor of post-surgical disease progression

Novelty Search in Competitive Coevolution

One of the main motivations for the use of competitive coevolution systems is their ability to capitalise on arms races between competing species to evolve increasingly sophisticated solutions. Such arms races can, however, be hard to sustain, and it has been shown that the competing species often converge prematurely to certain classes of behaviours. In this paper, we investigate if and how novelty search, an evolutionary technique driven by behavioural novelty, can overcome convergence in coevolution. We propose three methods for applying novelty search to coevolutionary systems with two species: (i) score both populations according to behavioural novelty; (ii) score one population according to novelty, and the other according to fitness; and (iii) score both populations with a combination of novelty and fitness. We evaluate the methods in a predator-prey pursuit task. Our results show that novelty-based approaches can evolve a significantly more diverse set of solutions, when compared to traditional fitness-based coevolution.Comment: To appear in 13th International Conference on Parallel Problem Solving from Nature (PPSN 2014

A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms

The Wild Turkey in South Dakota

This bulletin provides an extensive look at the wild turkey in South Dakota