Miracle-dz/UniFAR-FTUs huggingface dataset:
Strain-specific parallel evolution drives short-term diversification during Pseudomonas aeruginosa biofilm formation

Significance Within-population genetic diversity is an essential evolutionary prerequisite for processes ranging from antibiotic resistance to niche adaptation, but its generation is poorly understood, with most studies focusing on fixed substitutions at the end point of long-term evolution. Using deep sequencing, we analyzed short-term, within-population genetic diversification occurring during biofilm formation of the model bacterium Pseudomonas aeruginosa. We discovered extensive parallel evolution between biological replicates at the level of pathways, genes, and even individual nucleotides. Short-term diversification featured positive selection of relatively few nonsynonymous mutations, with the majority of the genome being conserved by negative selection. This result is broadly consistent with observations of long-term evolution and suggests diversifying selection may underlie genetic diversification of Pseudomonas aeruginosa biofilms. Generation of genetic diversity is a prerequisite for bacterial evolution and adaptation. Short-term diversification and selection within populations is, however, largely uncharacterised, as existing studies typically focus on fixed substitutions. Here, we use whole-genome deep-sequencing to capture the spectrum of mutations arising during biofilm development for two Pseudomonas aeruginosa strains. This approach identified single nucleotide variants with frequencies from 0.5% to 98.0% and showed that the clinical strain 18A exhibits greater genetic diversification than the type strain PA01, despite its lower per base mutation rate. Mutations were found to be strain specific: the mucoid strain 18A experienced mutations in alginate production genes and a c-di-GMP regulator gene; while PA01 acquired mutations in PilT and PilY1, possibly in response to a rapid expansion of a lytic Pf4 bacteriophage, which may use type IV pili for infection. The Pf4 population diversified with an evolutionary rate of 2.43 × 10−3 substitutions per site per day, which is comparable to single-stranded RNA viruses. Extensive within-strain parallel evolution, often involving identical nucleotides, was also observed indicating that mutation supply is not limiting, which was contrasted by an almost complete lack of noncoding and synonymous mutations. Taken together, these results suggest that the majority of the P. aeruginosa genome is constrained by negative selection, with strong positive selection acting on an accessory subset of genes that facilitate adaptation to the biofilm lifecycle. Long-term bacterial evolution is known to proceed via few, nonsynonymous, positively selected mutations, and here we show that similar dynamics govern short-term, within-population bacterial diversification.
Line Matching in Wide-Baseline Stereo: A Top-Down Approach

This paper introduces a new algorithm for matching lines across images that exploit the epipolar geometry and the coplanarity constraints between pairs of lines. In contrast to common treatment in matching of interest points, we use the epipolar geometry to constrain coplanarity conditions between line-pairs. This treatment eliminates the potential matching problems due to the incomplete line observations with nonmatching endpoints. This observation is used to detect a set of candidate line-pair correspondences. These matching pairs are then verified via local homography transforms derived from the neighboring interest point correspondences. This step results in a line affinity matrix, which is processed to obtain matching lines. During this process, we do not use appearance models and show that the proposed treatment performs better than the state-of-the-art appearance and geometry-based methods, especially for images with wide-baseline.
PGE1 stimulation of HEK293 cells generates multiple contiguous domains with different [cAMP]: role of compartmentalized phosphodiesterases

There is a growing appreciation that the cyclic adenosine monophosphate (cAMP)–protein kinase A (PKA) signaling pathway is organized to form transduction units that function to deliver specific messages. Such organization results in the local activation of PKA subsets through the generation of confined intracellular gradients of cAMP, but the mechanisms responsible for limiting the diffusion of cAMP largely remain to be clarified. In this study, by performing real-time imaging of cAMP, we show that prostaglandin 1 stimulation generates multiple contiguous, intracellular domains with different cAMP concentration in human embryonic kidney 293 cells. By using pharmacological and genetic manipulation of phosphodiesterases (PDEs), we demonstrate that compartmentalized PDE4B and PDE4D are responsible for selectively modulating the concentration of cAMP in individual subcellular compartments. We propose a model whereby compartmentalized PDEs, rather than representing an enzymatic barrier to cAMP diffusion, act as a sink to drain the second messenger from discrete locations, resulting in multiple and simultaneous domains with different cAMP concentrations irrespective of their distance from the site of cAMP synthesis.
An evolutionary tuned driving system for virtual car racing games: The AUTOPIA driver

This work presents a driving system designed for virtual racing situations. It is based on a complete modular architecture capable of automatically driving a car along a track with or without opponents. The architecture is composed of intuitive modules, with each one being responsible for a basic aspect of car driving. Moreover, this modularity of the architecture will allow us to replace or add modules in the future as a way to enhance particular features of particular situations. In the present work, some of the modules are implemented by means of hand‐designed driving heuristics, whereas modules responsible for adapting the speed and direction of the vehicle to the track's shape, both critical aspects of driving a vehicle, are optimized by means of a genetic algorithm that evaluates the performance of the controller in four different tracks to obtain the best controller in a large number of situations; the algorithm also penalizes controllers that go out of the track, lose control, or get damaged. The evaluation of the performance is done in two ways. First, in runs with and without adversaries over several tracks. And second, the architecture was submitted as a participant to the 2010 Simulated Car Racing Competition, which in end won laurels. © 2012 Wiley Periodicals, Inc.
Variation-Aware Custom IC Design

Variation has become a critical concern in modern process geometries; managing it properly is key in designing custom circuits with competitive performance, power, and area. This paper describes how a flow using design-specific corners manages variation issues in a unified fashion. To enable corner-based design, the key ingredients are corner extraction and design verification tools. This paper describes such tools for PVT, 3-sigma Monte Carlo, and highsigma design; and how appropriate technology can make these tools fast, accurate, and scalable. Finally, as an example, this paper focuses on high-sigma problems, showcasing High-Sigma Monte Carlo (HSMC) which analyzes billions of Monte Carlo samples in minutes, with SPICE accuracy.
Automatic Dem Generation And 3D Change Detection From Satellite Imagery

In this paper we present a method for fully automatic generation of digital surface models (DSM) from very high resolution (VHR) satellite imagery and the consecutively automatic change detection from the derived 3D information. Common change detection methods are normally only based on spectral change detection. These methods will fail for e.g. comparing summer and winter scenes with the latter covered with snow. Introducing the digital elevation model into the change detection process will allow for a more detailled object modeling and also for the possibility to detect more sophisticated changes like volume estimation of mining activities. Here we present the involved methods for the generation of the high resolution surface models, the fusion and classification and finally the automatic 3D change detection. The methods are applied to some VHR stereo test data sets and the results are evaluated for quality and usefulness for automatic information derivation from large data sets.
The role of surprising events in a math game on proportional reasoning

Reviews regarding serious games show that the effect on learning can be qualified as moderately positive. Despite the active involvement of players it seems that they sometimes refrain from relevant cognitive processes during game play. This study addresses a technique involving the generation of manageable cognitive conflicts to stimulate these cognitive processes. Surprise comprises events that undermine an expectation which trigger players to evaluate the new situation more extensively. Participants (N = 94) played a game in which they practiced proportional reasoning skills. The pretestposttest design involved two factors: Surprise (surprise vs. no surprise) and Expectancy (strong vs. weak). Surprise was implemented as an appearing game character that modified some parameters of a problem while the player was solving that problem. We expected that this would prompt players to evaluate their solution strategy and decide whether another strategy was more appropriate. Expectancy pertains to the type of problems that players expect. In the strong expectancy version players received a series of problems with the same structure as before. In the weak expectancy version problems with different structures are randomly presented to the players and each problem may involve a different solution strategy. We hypothesized an interaction between Surprise and Expectancy, next to a main effect of Surprise. The results show that participants learned from the game. We also did find a weak positive effect of Surprise, but no effect of Expectancy nor interaction effect on learning. The facilitating effect of Surprise was stronger when existing proportional reasoning skill was included as factor. These results indicate that surprise as implemented in the game has effect on learning regardless whether expectancy was weak or strong. We discuss some suggestions for finding stronger effects of surprise such as the fact that the repetitive nature may have weakened the 'surprisingness' of the surprises and the observation that our sample may not have possessed a sufficient level of metacognitive skills to interpret the changes caused by the surprises.
Indirect evolutionary rescue: prey adapts, predator avoids extinction

Recent studies have increasingly recognized evolutionary rescue (adaptive evolution that prevents extinction following environmental change) as an important process in evolutionary biology and conservation science. Researchers have concentrated on single species living in isolation, but populations in nature exist within communities of interacting species, so evolutionary rescue should also be investigated in a multispecies context. We argue that the persistence or extinction of a focal species can be determined solely by evolutionary change in an interacting species. We demonstrate that prey adaptive evolution can prevent predator extinction in two‐species predator–prey models, and we derive the conditions under which this indirect evolutionary interaction is essential to prevent extinction following environmental change. A nonevolving predator can be rescued from extinction by adaptive evolution of its prey due to a trade‐off for the prey between defense against predation and population growth rate. As prey typically have larger populations and shorter generations than their predators, prey evolution can be rapid and have profound effects on predator population dynamics. We suggest that this process, which we term ‘indirect evolutionary rescue’, has the potential to be critically important to the ecological and evolutionary responses of populations and communities to dramatic environmental change.
Effect of Accommodation on Corneal Topography

Purpose: To investigate the effect of accommodation on corneal topography in healthy subjects. Methods: Using a Nidek OPD-Scan ARK-10000, corneal topographic images, images of the iris, and the refraction of 18 eyes of 10 normal subjects with a mean age of 26.3 ± 7.1 years (median, 24 years; range, 19–41 years) were simultaneously obtained before and during fixation of a near target in the Department of Ophthalmology, Istanbul Medeniyet University Medical Faculty, Istanbul, Turkey. At baseline, iris landmarks, such as nevi and crypts, were identified on each iris image that were on opposite sides of the pupil and 180 degrees apart. A line was drawn on the iris images between these 2 landmarks. The same landmarks were identified on the iris images obtained when the eye was fixating at the near target. A line was drawn between the landmarks. The angular rotation of the lines relative to the vertical meridian was measured to assess cyclotorsion of the eyes during accommodation. Results: At baseline, the mean spherical equivalent refraction of the eyes was −0.78 ± 0.38 diopters (D) (range, −0.25 to −1.67 D) with <0.5 D of astigmatism. During a mean accommodative amplitude of −4.55 ± 2.04 (median, −4.25 D; range, −1.75 D to −8.12 D), there was no apparent difference in corneal topography and no statistical difference in mean keratometry (P = 0.26) or cyclotorsion (P = 0.74). Conclusions: During accommodation, the cornea does not change curvature and the eye does not appear to significantly cyclotort.
African Indigenous Cattle: Unique Genetic Resources in a Rapidly Changing World

At least 150 indigenous African cattle breeds have been named, but the majority of African cattle populations remain largely uncharacterized. As cattle breeds and populations in Africa adapted to various local environmental conditions, they acquired unique features. We know now that the history of African cattle was particularly complex and while several of its episodes remain debated, there is no doubt that African cattle population evolved dramatically over time. Today, we find a mosaic of genetically diverse population from the purest Bos taurus to the nearly pure Bos indicus. African cattle are now found all across the continent, with the exception of the Sahara and the river Congo basin. They are found on the rift valley highlands as well as below sea level in the Afar depression. These unique livestock genetic resources are in danger to disappear rapidly following uncontrolled crossbreeding and breed replacements with exotic breeds. Breeding improvement programs of African indigenous livestock remain too few while paradoxically the demand of livestock products is continually increasing. Many African indigenous breeds are endangered now, and their unique adaptive traits may be lost forever. This paper reviews the unique known characteristics of indigenous African cattle populations while describing the opportunities, the necessity and urgency to understand and utilize these resources to respond to the needs of the people of the continent and to the benefit of African farmers.
More on Wire Routing with ASP

Wire routing is an important component in the design of very large scale integrated circuits (VLSI). In a recent work Erdem et al. argued that routing problems can be solved by general-purpose answer-set programming solvers. They proposed to view routing as a planning problem in which multiple robots have to determine their paths between matching pins. As in other planning problems, the representation refers to time moments (or a counter of the number of steps taken). We propose a different approach which eliminates the need to represent time. In adition, we develop techniques to limit the search space by eliminating from consideration grid points that are far from the terminal points. We have experimented with our approach using both smodels and our program dcs. Both programs ran faster on representations proposed here than on the original ones.
A study of feature subset evaluators and feature subset searching methods for phishing classification

Phishing is a semantic attack that aims to take advantage of the naivety of users of electronic services (e.g. e-banking). A number of solutions have been proposed to minimize the impact of phishing attacks. The most accurate email phishing classifiers, that are publicly known, use machine learning techniques. Previous work in phishing email classification via machine learning have primarily focused on enhancing the classification accuracy by studying the addition of novel features, ensembles, or classification algorithms. This study follows a different path by taking advantage of previously proposed features. The primary focus of this paper is to enhance the classification accuracy of phishing email classifiers by finding an effective feature subset out of a number of previously proposed features, by evaluating various feature selection methods. The selected feature subset in this study resulted in a classification model with an f1 score of 99.396% for 21 heuristic features and a single classifier.
Two-Layer Multiple Kernel Learning

Multiple Kernel Learning (MKL) aims to learn kernel machines for solving a real machine learning problem (e.g. classification) by exploring the combinations of multiple kernels. The traditional MKL approach is in general “shallow” in the sense that the target kernel is simply a linear (or convex) combination of some base kernels. In this paper, we investigate a framework of Multi-Layer Multiple Kernel Learning (MLMKL) that aims to learn “deep” kernel machines by exploring the combinations of multiple kernels in a multi-layer structure, which goes beyond the conventional MKL approach. Through a multiple layer mapping, the proposed MLMKL framework offers higher flexibility than the regular MKL for finding the optimal kernel for applications. As the first attempt to this new MKL framework, we present a Two-Layer Multiple Kernel Learning (2LMKL) method together with two efficient algorithms for classification tasks. We analyze their generalization performances and have conducted an extensive set of experiments over 16 benchmark datasets, in which encouraging results showed that our method performed better than the conventional MKL methods.
Fabricating Monsters is Hard Towards the Automation of Conceptual Blending

The theory of conceptual blending has been applied very successfully in cognitive science to explain the process of concept generation. In previous work, we have shown a formalisation and implementation of conceptual blending that is borrowing techniques from logic, ontological engineering, and algebraic specification. However, so far our attempts (and similar approaches in the literature) have been reconstructive; that is they show how a particular concept (e.g., houseboat) can be ‘discovered’ by computationally blending two carefully selected input spaces (e.g, a house and a boat) and a suitable base. This paper describes an attempt to take the next step and automate the concept generation based on a database of input spaces. Particularly, we attempt to create monsters from a library of animals formalised as OWL ontologies.
In quest of the science in statistical fault localization

Many researchers employ various statistical methods to locate faults in faulty programs. Like other researchers, we sometimes have made mistakes in the quest of making statistical fault localization both practical and scientific. In this experience report, we reflect on our work conducted on this topic, organize our isolated experiences in the format of models and errors, and cast them in the context of statistics. Copyright © 2011 John Wiley & Sons, Ltd.
Earnings Management and Tunneling Through Related Party Transactions: Evidence from Chinese Corporate Groups

From the U.S. accounting scandals to the emerging markets crisis of 1997-1998, there have been numerous examples of managers or large shareholders using related party transactions to manipulate earnings or divert resources away from their companies. This paper attempts to provide large sample evidence of these transactions in China where the corporate structure, economic institutions and weak legal system are conducive to the related party dealings. Using a sample of 131 Chinese listed firms in the basic materials industries such as mining, lumber, chemicals and building materials, we have found that firms that are controlled by a corporate group engage in more related party transactions than firms that are not. Among the group-controlled listed firms, the results show that they report abnormally high levels of related party sales, mainly to their controlling shareholders and other member firms in the group, when they have incentives to inflate earnings to avoid being delisted or prior to issuing new equity. Once the group-controlled listed firms have generated more free cash flows, they divert resources back to the group through providing other member firms generous trade credits. Our stock return results also confirm the conjectures that at least part of the related party transactions is perceived by the market as opportunistic. Investors view the reported sales figures to be less credible when they are generated from related party dealings than through arm's length transactions. Related party lending is negatively correlated with firm value, as measured by Tobin's Q and market-to-book equity.
Principles for Improving Interaction in Telephone-Based Interfaces

BACKGROUND AND CONTEXT Telephone-based interfaces (TBIs) are an increasingly important method for interacting with computer systems. The telephone is a ubiquitous device and is many people’s primary method of entry into the information infrastructure. Access to an increasing number of services is being offered over the telephone (such as electronic banking and Web pages). The provision of these extra services may be rendered useless if usability issues are not considered [23]. The rapidly increasing use of mobile phones means that people access services at many different times and places. This is a huge growth area – there are approximately 25 million mobile phone subscribers in the UK and this is expected to rise to 45 million over the next five years [18]. Mobile telephones themselves now incorporate greater functionality (such as diaries, address books and WAP services). We therefore concentrated our research on the interfaces to mobile telephones. The Government’s Foresight panel recognised mobile devices and their interfaces are a key area of focus in UK science and engineering [16]. The telephone itself allows only a limited form of interaction [27]. In TBIs (both for dial-up services and interfaces to mobile phones) the user interacts by navigating through a series of menus. A common problem is that users get lost in the menu hierarchy [26, 30, 31] of the device or service. One reason for this is that the interfaces are very limited – input is via a small number of keys and output via speech or a small screen.
Seed and Grow: Augmenting Statistically Generated Summary Sentences using Schematic Word Patterns

We examine the problem of content selection in statistical novel sentence generation. Our approach models the processes performed by professional editors when incorporating material from additional sentences to support some initially chosen key summary sentence, a process we refer to as Sentence Augmentation. We propose and evaluate a method called "Seed and Grow" for selecting such auxiliary information. Additionally, we argue that this can be performed using schemata, as represented by word-pair co-occurrences, and demonstrate its use in statistical summary sentence generation. Evaluation results are supportive, indicating that a schemata model significantly improves over the baseline.