Miracle-dz/UniFAR-FTUs huggingface dataset:
European Flint Landraces Grown In Situ Reveal Adaptive Introgression from Modern Maize

We have investigated the role of selection in the determination of the detected levels of introgression from modern maize hybrid varieties into maize landraces still cultivated in situ in Italy. We exploited the availability of a historical collection of landraces undertaken before the introduction and widespread use of modern maize, to analyse genomic changes that have occurred in these maize landraces over 50 years of co-existence with hybrid varieties. We have combined a previously published SSR dataset (n=21) with an AFLP loci dataset (n=168) to provide higher resolution power and to obtain a more detailed picture. We show that selection pressures for adaptation have favoured new alleles introduced by migration from hybrids. This shows the potential for analysis of historical introgression even over this short period of 50 years, for an understanding of the evolution of the genome and for the identification of its functionally important regions. Moreover, this demonstrates that landraces grown in situ represent almost unique populations for use for such studies when the focus is on the domesticated plant. This is due to their adaptation, which has arisen from their dynamic evolution under a continuously changing agro-ecological environment, and their capture of new alleles from hybridisation. We have also identified loci for which selection has inhibited introgression from modern germplasm and has enhanced the distinction between landraces and modern maize. These loci indicate that selection acted in the past, during the formation of the flint and dent gene pools. In particular, the locus showing the strongest signals of selection is a Misfit transposable element. Finally, molecular characterisation of the same samples with two different molecular markers has allowed us to compare their performances. Although the genetic-diversity and population-structure analyses provide the same global qualitative pattern, which thus provides the same inferences, there are differences related to their natures and characteristics.
Notice of RetractionApplying PRG model to typical optimization algorithm development in logistics

The problem reduction graph (PRG) is a model for formally describing the reduction processes of combinatorial optimization problems and systematically deriving efficient algorithms for the problems. The paper applies the model for several optimization problems including vehicle loading, vehicle routing, and warehouse location, which are typical problems in the domain of logistics. We work out their problem-solving algorithms by specification transformation and derivation, and show that the model is capable of developing algorithms covering classic design tactics including branch-and-bound, greedy, and dynamic programming.
Common sense in philosophical and scientific perspective

Purpose – The purpose of this paper is to deepen our understanding of the philosophical and scientific pedigree of the concept of “common sense”, and explore the implications for managerial decision‐makers.Design/methodology/approach – After examining the management literature on this topic, a brief history of the notion and philosophy of common sense is followed by a review of recent findings in cognitive science and other fields and a discussion of implications for managerial decision‐making.Findings – The notion of common sense has a stable perceptual basis in the makeup of the human mind, as has been shown by philosophers and scientists. Common sense intuitions serve as the basis for making sense of the world: visual perception, scientific reasoning, language, psychology, mathematics, and moral judgments are all rooted in “mental hardware” of common sense. While it is a necessary element of human cognition, common sense can nevertheless lead us astray if we are unaware of its contours and limitations,.
Object detection and features extraction in video frames using direct thresholding

This paper. presents a method for objects detection and features extraction in static video imagery that operates on color/gray-scale frames grabbed by common digital cameras or readily available images from external sources. Segmenting objects is achieved by a technique proposed here and named as direct thresholding (DTh) with background extracted through applying morphological background estimation scheme (MBES). The accommodating hardware is represented by a dedicated P4 PC-based image processing environment, whereas the intrinsic software has been simulated and validated using MATLAB7.3 platform. Human visual perceptual inspection plus histogramming showed an appreciable level of performance through a specific experimentation of multiple-phases. The envisaged diverse fields of application of this method may involve: traffic flow measurement of vehicles and pedestrians; athletic and dancing performance evaluation; public, private, and military security, and so on.
Self-configuring network traffic generation

The ability to generate repeatable, realistic network traffic is critical in both simulation and testbed environments. Traffic generation capabilities to date have been limited to either simple sequenced packet streams typically aimed at throughput testing, or to application-specific tools focused on, for example, recreating representative HTTP requests. In this paper we describe Harpoon, a new application-independent tool for generating representative packet traffic at the <i>IP flow level</i>. Harpoon generates TCP and UDP packet flows that have the same byte, packet, temporal and spatial characteristics as measured at routers in live environments. Harpoon is distinguished from other tools that generate statistically representative traffic in that it can <i>self-configure</i> by automatically extracting parameters from standard Netflow logs or packet traces. We provide details on Harpoon's architecture and implementation, and validate its capabilities in controlled laboratory experiments using configurations derived from flow and packet traces gathered in live environments. We then demonstrate Harpoon's capabilities in a router benchmarking experiment that compares Harpoon with commonly used throughput test methods. Our results show that the router subsystem load generated by Harpoon is significantly different, suggesting that this kind of test can provide important insights into how routers might behave under actual operating conditions.
A construction of auditor independence in the Czech Republic: local insights

A notion of auditor independence, envisaged as crucial to the credibility of the audit function, resides in professional Codes of Ethics in much of the western world. Since the beginning of the 1990s, the auditor independence construct has been imported eastwards and incorporated into legislation and Code of Practices amongst central and eastern European economies (CEE), together with other requirements, as the countries prepare for their accession to the European Union. This study is aimed at ascertaining the meanings conveyed by the auditor independence construct and its state of realisation in one of the transition economies of the CEE region, the Czech Republic. Also, the study seeks to understand how local culture impacts upon a particular understanding of auditor independence. In order to examine the auditor independence in this part of the world, a framework for analysis incorporating structural conditions, local traditions and culture is proposed. The analysis is conducted first de jure, and is based upon a review of the Czech law and professional regulation. This is complemented with a de facto analysis based upon interviews with audit practitioners, regulators and financial statement users in the Czech Republic and on a review of Czech media coverage. What emerges from the study is a particular local understanding of the auditor independence construct, perceived primarily as an economic concept in the context of market instability and the immature legal framework. It appears that there is a tendency to follow the form of audit procedures without substantial rationalisation. We conclude that socio‐economic and cultural pressures appear to far outweigh any formal safeguards implemented to maintain professional integrity and competence in the CEE region.
Cross-Document Coreference Resolution Using Latent Features

Over the last years, entity detection approaches which combine named entity recognition and entity linking have been used to detect mentions of RDF resources from a given reference knowledge base in unstructured data. In this paper, we address the problem of assigning a single URI to named entities which stand for the same real-object across documents but are not yet available in the reference knowledge base. This task is known as cross-document co-reference resolution and has been addressed by manifold approaches in the past. We present a preliminary study of a novel take on the task based on the use of latent features derived from matrix factorizations combined with parameter-free graph clustering. We study the influence of different parameters (window size, rank, hardening) on our approach by comparing the F-measures we achieve on the N3 benchmark. Our results suggest that using latent features leads to higher F-measures with an increase of up to 20.5% on datasets of the N3 collection.
LDADEEP+: Latent aspect discovery with deep representations

Nowadays, with the success and fast growth of social media communities and mobile devices, people are encouraged to share their multimedia data online. Analyzing and summarizing data into useful information thus becomes increasingly important. For online photo sharing services like Flickr, when users are uploading a batch of daily photos at a time, the tags users provided tend to be rather vague, containing only a small amount of information. For better photo application and understanding, we attempt to automatically discover semantic-rich (hidden) aspects of photos merely by looking at image contents. In this paper, we propose an effective model, which is a combination of LDA model and deep learning representations, to realize the idea of automatic aspect discovery. We then discuss the properties of this aspect discovery model through experiments on event summarization task. In those experiments, we show the high diversity and high quality of aspects discovered by our proposed method. Meanwhile, we conduct an user study to evaluate the quality of the summarized results. Moreover, the proposed method can be further extended to human attribute discovery for a given event. We automatically discover different aspects on our Olympic Games data (e.g. football, ice skating).
Inside 6th gen Intel® Core™: New microarchitecture code named skylake

•Skylake delivers record levels of performance and battery life in many personal computing use cases and form factors •Intel® Speed Shift Technology provides higher performance, responsiveness and efficiency at power constrained form factors •Skylake Processor Graphics delivers scalable performance, >1TFLOPS compute, enhanced low power media engines, flexible power management, and end-to-end 4K experience •Skylake family of products allows developers to: •Choose from wide range of platform capabilities •Innovate with products for wide range of thermal envelopes and I/O solutions •Optimize the system performance using the advanced PMU capabilities •Skylake introduces Intel® SGX: a revolutionary game changer to trusted application security in the main stream SW environment
Gaussian Mixture Model Based Approach to Color Image Retrieval

Recently, with the explosive growth of the World Wide Web resources of digital color images, much research effort has been devoted to the development of efficient content based image retrieval systems. In this contribution we propose a color indexing method based on the Gaussian Mixture Model of a histogram. The model parameters serve as signatures enabling fast and efficient color image retrieval. We present the results of performed experiments which show that proposed approach is robust to color image distortions introduced by compression artifacts. Therefore, the proposed method is well suited for indexing and retrieval of Internet based collections of color images stored in lossy formats.
Genes in the Dopaminergic System and Delinquent Behaviors Across the Life Course

This article examines the interaction between social control and social risk mechanisms, and genes within the dopaminergic system (DAT1 and DRD2) as related to serious and violent forms of delinquent behavior among adolescents and young adults. We use nine waves of data from the National Youth Survey Family Study (NYSFS) to examine the relevance of protective or risky social factors at four social levels, including school, neighborhood, friends, and family within the gene–environment interaction framework. We extend previous work in this area by providing a testable typology of gene–environment interactions derived from current theories in this area. We find consistent evidence that the associations between putatively risky genotypes and delinquent behavior are suppressed within protective social environments. We also provide some evidence that supports the differential susceptibility hypothesis for these outcomes. Our findings largely confirm the conclusions of previous work and continue to highlight the critical role of the social environment within candidate gene studies of complex behaviors.
Playing by the rules: researching, teaching and learning sexual ethics with young men in the Australian National Rugby League

In 2004, the Australian National Rugby League (NRL) commissioned the Playing By The Rules research project in response to allegations of sexual assault by members of a professional rugby league team. This article offers an overview of the theoretical and methodological approaches adopted by the team, and the subsequent workplace education programmes designed to promote ethical sexual behaviour and attitudes within NRL culture. The researchers reflect on contemporary thinking in the relatively new field of violence prevention education aimed at young men, and consider new critical approaches to the intersection of masculinities and sexual learning.
De novo transcriptome assembly with ABySS

MOTIVATION Whole transcriptome shotgun sequencing data from non-normalized samples offer unique opportunities to study the metabolic states of organisms. One can deduce gene expression levels using sequence coverage as a surrogate, identify coding changes or discover novel isoforms or transcripts. Especially for discovery of novel events, de novo assembly of transcriptomes is desirable. RESULTS Transcriptome from tumor tissue of a patient with follicular lymphoma was sequenced with 36 base pair (bp) single- and paired-end reads on the Illumina Genome Analyzer II platform. We assembled approximately 194 million reads using ABySS into 66 921 contigs 100 bp or longer, with a maximum contig length of 10 951 bp, representing over 30 million base pairs of unique transcriptome sequence, or roughly 1% of the genome. AVAILABILITY AND IMPLEMENTATION Source code and binaries of ABySS are freely available for download at http://www.bcgsc.ca/platform/bioinfo/software/abyss. Assembler tool is implemented in C++. The parallel version uses Open MPI. ABySS-Explorer tool is implemented in Java using the Java universal network/graph framework. CONTACT ibirol@bcgsc.ca.
Internet suspend/resume

We identify a new capability for mobile computing that mimics the opening and closing of a laptop, but avoids physical transport of hardware. Through rapid and easy personalization and depersonalization of anonymous hardware, a user is able to suspend work at one machine and to resume it at another. Our key insight is that this capability can be achieved by layering virtual machine technology on a distributed file system. We report on an initial implementation and describe our plans for improving efficiency, portability, and security.
Religion and Military Conscription

The military benefits from fostering an “us-feeling” among its members. On what basis is this formed? Rooted in the discipline of religion, the following article explores how religion feeds into the selective conscription practices of the Israel Defense Forces (IDF). Combining legal documents with data gathered through interviews with thirty-four soldiers in a combat battalion, it is argued that the IDF’s conscription practices are sensitive to the contents of religion. The IDF applies a multifarious concept of religion with significant impact on the IDF’s ability to foster a sense of “us. ” The IDF recruits draftees on the basis of a twofold definition of Judaism, either as an ethnic group or as a theological concept. Both definitions help determine whether one is drafted. Interviews with soldiers expand on this definition, drawing attention to the integrative as well as disintegrative consequences of this notion of religion within the IDF.
A Spatiotemporal Framework for MEG/EEG Evoked Response Amplitude and Latency Variability Estimation

This paper presents a spatiotemporal framework for estimating single-trial response latencies and amplitudes from evoked response magnetoencephalographic/electroencephalographic data. Spatial and temporal bases are employed to capture the aspects of the evoked response that are consistent across trials. Trial amplitudes are assumed independent but have the same underlying normal distribution with unknown mean and variance. The trial latency is assumed to be deterministic but unknown. We assume that the noise is spatially correlated with unknown covariance matrix. We introduce a generalized expectation-maximization algorithm called Trial Variability in Amplitude and Latency (TriViAL) that computes the maximum likelihood (ML) estimates of the amplitudes, latencies, basis coefficients, and noise covariance matrix. The proposed approach also performs ML source localization by scanning the TriViAL algorithm over spatial bases corresponding to different locations on the cortical surface. Source locations are identified as the locations corresponding to large likelihood values. The effectiveness of the TriViAL algorithm is demonstrated using simulated data and human evoked response experiments. The localization performance is validated using tactile stimulation of the finger. The efficacy of the algorithm in estimating latency variability is shown using the known dependence of the M100 auditory response latency to stimulus tone frequency. We also demonstrate that estimation of response amplitude is improved when latency is included in the signal model.
SiCoGrid : A Complete Grid Simulator for Scheduling and Algorithmical Research , with Emergent Artificial Intelligence data algorithms

Grids are become popular paradigms for parallel and distributed computing. Dynamically aggregation of resources on heterogeneous infrastructures allow to solve large scale problems in science, engineering, and ecommerce. The numerous parameters that have to be taken in account, becomes difficult to use analytical models. In this paper we propose a completed Grid simulator, called SiCoGrid (from the Spanish Simulator Completo Grid), where every Grid entity is modelled. We focus on event driven low level Grid simulation, regard the less of the Grid application running on the top level, and the upper architecture abstractions. The aim is to provide an easy scaling tool for Grid researches, where implementing different core algorithms and policies, integrating new approaches on the existing SiCoGrid code, and thus analyse performances in terms of response rate and resources use. Actually SiCoGrid have implemented canonical data algorithms and job schedulers, and also an economic data algorithm, and two Emergent Artificial Intelligence algorithms proposed by authors on previous works: the Grid flavours of Particle Swarm Optimization(PSO) and Ant Colony Optimization(ACO).
PSO AND TABU SEARCH APPROACHES FOR THE CAR ALLOCATION PROBLEM IN MULTI-CAR ELEVATOR SYSTEMS

Heavy vertical traffic conditions appear in high-rise buildings especially during the rush-hour period. So, offered service provided by multi-car elevator systems for such buildings during that period is expected to work fast, efficiently and without long waiting times for users. The approach of our work focuses on reducing the passengers travel and waiting times. To do so Particle Swarm Optimization (PSO) and Tabu Search (TS) algorithms are applied to multi-car elevator control systems that are usually implemented in such buildings. In this paper, PSO and TS algorithms are proposed to optimize the controller of such elevator control systems and successful simulation results are provided for an illustrative example.
Distributed Approximation Algorithms via LP-Duality and Randomization

The spread of computer networks, from sensor networks to the Internet, creates an ever-growing need for efficient distributed algorithms. In such scenarios, familiar combinatorial structures such as spanning trees and dominating sets are often useful for a variety of tasks. Others, like maximal independent sets, turn out to be a very useful primitive for computing other structures. In a distributed setting, where transmission of messages can be orders of magnitude slower than local computation, the expensive resource is communication. Therefore, the running time of an algorithm is given by the number of communication rounds that are needed by the algorithm. This will be made precise below.
Pro-inflammatory cytokines and leukocyte oxidative burst in chronic kidney disease: culprits or innocent bystanders?

BACKGROUND Pro-inflammatory cytokines are elevated in chronic kidney disease (CKD), a condition characterized by microinflammation with oxidative stress as key feature. However, their role in the inflammatory response at uraemic concentrations has not yet been defined. In this study, the contribution of cytokines on induction of leukocyte oxidative stress was investigated. METHODS Whole blood from healthy donors was incubated with 20-1400 pg/mL TNFα, 5-102.8 pg/mL IL-6, 20-400 pg/mL IL-1β and 75-1200 pg/mL IL-18 separately or in combination. Oxidative burst was measured, at baseline and after stimulation with fMLP (Phagoburst™). The effect of the TNFα blocker, adalimumab (Ada), was evaluated on TNFα-induced ROS production. Finally, the association between TNFα and the composite end point all-cause mortality or first cardiovascular event was analysed in a CKD population stage 4-5 (n = 121). RESULTS While interleukin (IL)-6, IL-1β and IL-18 alone induced no ROS activation of normal leukocytes, irrespective of concentrations, TNFα induced ROS activation at baseline (P < 0.01) and after fMLP stimulation (P < 0.05), but only at uraemic concentrations in the high range (400 and 1400 pg/mL). A similar pattern was observed with all cytokines in combination, but already at intermediate uraemic concentrations (all P < 0.05, except for monocytes after fMLP stimulation: n.s.), suggesting synergism between cytokines. ROS production induced by TNFα (400 pg/mL) and the cytokine combination was blocked with Ada. Uraemia-related oxidative stress in leukocytes of haemodialysis patients was however not blocked by Ada. In patients, TNFα was not associated to adverse events (HR: 1.52, 95% CI 0.81-2.85, P = 0.13). CONCLUSION Among several pro-inflammatory cytokines, TNFα alone was pro-oxidative but only at high-range uraemic concentrations. Adding a TNFα blocker, Ada, blocked this ROS production, but not the oxidative stress in blood samples from haemodialysis patients, suggesting that other uraemic toxins than TNFα are more crucial in this process. However, the lack of association between TNFα and mortality suggests that the role of TNFα-linked oxidative stress is limited.