Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithmes de fourmis artificielles : applications à la classification et à l'optimisation. (Artificial ant based algorithms applied to clustering and optimization problems)

Dans ce travail de these, nous presentons les travaux s'inspirant des fourmis reelles pour la resolution de problemes en informatique. Nous proposons deux approches supplementaires de ces nouvelles inspirations biomimetiques. La premiere reprend certains travaux en classification non supervisee et etend ces principes dans plusieurs directions. L'algorithme AntClass developpe a cette occasion, est hybride dans le sens ou la recherche du nombre de classes est effectue par des fourmis artificielles et qu'un algorithme classique en classification, les centres mobiles, est utilise pour gommer les erreurs de classification inherentes a une methode stochastique telle que les fourmis artificielles. Apres avoir souligne les ressemblances et differences entre les approches evolutionnaires et celles a base de population de fourmis et propose un modele commun, nous nous inspirons de la strategie de recherche de nourriture d'une espece de fourmis (Pachycondyla apicalis) pour resoudre des problemes d'optimisation globale. L'apport de cette adaptation reside principalement dans sa simplicite. Nous appliquons l'algorithme qui en decoule, appele API, a des problemes varies tels que l'optimisation de fonctions numeriques, l'apprentissage de chaines de Markov cachees ou des poids d'un reseau de neurones artificiels, ou encore a un probleme d'optimisation combinatoire classique : le probleme du voyageur de commerce.
Learning Inverse Statics Models Efficiently With Symmetry-Based Exploration

Learning (inverse) kinematics and dynamics models of dexterous robots for the entire action or observation space is challenging and costly. Sampling the entire space is usually intractable in terms of time, tear, and wear. We propose an efficient approach to learn inverse statics models—primarily for gravity compensation—by exploring only a small part of the configuration space and exploiting the symmetry properties of the inverse statics mapping. In particular, there exist symmetric configurations that require the same absolute motor torques to be maintained. We show that those symmetric configurations can be discovered, the functional relations between them can be successfully learned and exploited to generate multiple training samples from one sampled configuration-torque pair. This strategy drastically reduces the number of samples required for learning inverse statics models. Moreover, we demonstrate that exploiting symmetries for learning inverse statics models is a generally applicable strategy for online and offline learning algorithms. We exemplify this by two different learning approaches. First, we modify the Direction Sampling approach for learning inverse statics models online, in a plain exploratory fashion, from scratch and without using a closed-loop controller. Second, we show that inverse statics mappings can be efficiently learned offline utilizing lattice sampling. Results for a 2R planar robot and a 3R simplified human arm demonstrate that their inverse statics mappings can be learned successfully for the entire configuration space. Furthermore, we demonstrate that the number of samples required for learning inverse statics mappings for 2R and 3R manipulators can be reduced at least by factors of approximately 8 and 16, respectively–depending on the number of discovered symmetries.
A Study of the Effect of Prefetching in Shared-Memory Resource Contention

Managing contention for shared resources in chip multiprocessors has become very challenging as the number of cores and execution contexts scale up. Contention for the memory hierarchy resources, especially the shared caches, can severely degrade an application’s performance and system throughput [2]. One of the important resources related to caching is hardware prefetcher whose effect on the shared-memory resource contention has not been fully explored. Hardware prefetchers can have potential impact on an application’s performance depending on its data access pattern. If the application has sequential or strided data access pattern, the prefetchers can bring data in the caches in advance, reducing cache misses and improving performance. On the other hand, if the application’s data access pattern does not follow any pattern, the prefetched data can pollute the cache, resulting in more cache misses and worse performance. In this research, we study and measure the prefetching usefulness on multi-threaded applications’ performances while the applications contend for different shared-memory resources. Such a study provides insights in understanding applications’ behaviors and helps to further improve an application’s performance by dynamically adjusting and utilizing prefetching along with the contention mitigating techniques. We use the multi-threaded PARSEC benchmarks to measure the prefetching effect on several resources in the memory hierarchy, including L1-cache, L2-cache and Front Side Bus (FSB). To determine the effect of prefetching on shared-resource contention in the memory hierarchy, we need a methodology for comparing the application’s performance when the prefetcher is enabled and disabled, at the same time when there is contention for the targeted resource. In general, to measure contention for a particular shared resource, applications are run in two resource configurations. In the baseline configuration, application threads are mapped onto cores such that the threads do not share the targeted resource and run using dedicated resources. In the contention configuration, the application threads are mapped onto the cores such that the threads execute sharing the targeted resource. Because a multi-threaded application has multiple threads, there is possibility of contention when these threads share a resource.
Australian Economic Booms in Historical Perspective

The current economic boom in Australia is part of a historical pattern. Australian development has occurred in several phases of capital accumulation: an era of primary capitalist accumulation - from 1788 until the economic crash of the early 1840s; the first long boom - from the colonial gold rushes of the 1850s until the Depression of the early 1890s; the era of early national development - from Federation until the Depression decade of the 1930s; the second long boom - from 1945 until the global crisis of the 1970s; and the era of neoliberal globalism from the early 1990s to the present. Each previous boom featured a burst of innovation and growth followed by economic collapse. Each collapse was characterised by intensive capital, labour and state restructuring during which there occurred significant changes in the role of the state, shifts in economic policy, and fundamental realignments of class forces. These phases of restructuring have been periods of creative destruction through which the problems increasingly inherent in the previous boom were at least partly resolved and the conditions for a new phase of accumulation forged.
The Effect of Family Environment, Personality, and Self-Efficacy on Career Indecision of College Students

The present study was to investigate the utility of Lent, Brown, and Hackett’s (1994) social cognitive theory. By means of a structural equation model using LISREL 8, a causal model regarding specific direct and indirect influences among family environment, personality, self-efficacy, and career indecision constructs was investigated for college students. The sample included 268 university student participants who declare major undecided. Data were collected from major undecided students residing in the Midwest university. Gender differences were found with women reported no significant effect of family environment on career indecision directly and indirectly through self-efficacy. They reported a significant effect of personality on career indecision directly and indirectly through self-efficacy. Yet, Men reported a significant effect of family environment and personality on career indecision directly and indirectly through self-efficacy. Aesthetic self-efficacy was considered as an important cognitive factor mediating the women’s educational and occupational choice behaviors. Technical-scientific self-efficacy was and important cognitive factor mediating the educational and occupational choice behaviors of men.
Health in climate change research from 1990 to 2014: positive trend, but still underperforming

Background Climate change has been recognized as both one of the biggest threats and the biggest opportunities for global health in the 21st century. This trend review seeks to assess and characterize the amount and type of scientific literature on the link between climate change and human health. Design We tracked the use of climate-related terms and their co-occurrence with health terms during the 25 years since the first Intergovernmental Panel on Climate Change (IPCC) report, from 1990 to 2014, in two scientific databases and in the IPCC reports. We investigated the trends in the number of publications about health and climate change through time, by nature of the health impact under study, and by geographic area. We compared the scientific production in the health field with that of other sectors on which climate change has an impact. Results The number of publications was extremely low in both databases from 1990 (325 and 1,004, respectively) until around 2006 (1,332 and 4,319, respectively), which has since then increased exponentially in recent years (6,079 and 17,395, respectively, in 2014). However, the number of climate change papers regarding health is still about half that of other sectors. Certain health impacts, particularly malnutrition and non-communicable diseases (NCDs), remain substantially understudied. Approximately two-thirds of all published studies were carried out in OECD countries (Organization for Economic Cooperation and Development), predominantly in Europe and North America. Conclusions There is a clear need for further research on the links between climate change and health. This pertains particularly to research in and by those countries in which health will be mostly affected and capacity to adapt is least. Specific undertreated topics such as NCDs, malnutrition, and mental health should gain the priority they deserve. Funding agencies are invited to take note of and establish calls for proposals accordingly. Raising the interest in this research area in young scientists remains a challenge and should lead to innovative courses for large audiences, such as Massive Open Online Courses.
Second generation endometrial ablation techniques for heavy menstrual bleeding: network meta-analysis

Objective To determine the relative effectiveness of second generation ablation techniques in the treatment of heavy menstrual bleeding. Design Network meta-analysis on the primary outcome measures of amenorrhoea, heavy bleeding, and patients’ dissatisfaction with treatment. Data sources Nineteen randomised controlled trials (involving 3287 women) were identified through electronic searches of the Cochrane Library, Medline, Embase and PsycINFO databases from inception to April 2011. The reference lists of known relevant articles were searched for further articles. Two reviewers independently selected articles without language restrictions. Eligibility criteria for selecting studies Randomised controlled trials involving second generation endometrial destruction techniques for women with heavy menstrual bleeding unresponsive to medical treatment. Results Of the three most commonly used techniques, network meta-analysis showed that bipolar radiofrequency and microwave ablation resulted in higher rates of amenorrhoea than thermal balloon ablation at around 12 months (odds ratio 2.51, 95% confidence interval 1.53 to 4.12, P<0.001; and 1.66, 1.01 to 2.71, P=0.05, respectively), but there was no evidence of a convincing difference between the three techniques in the number of women dissatisfied with treatment or still experiencing heavy bleeding. Compared with bipolar radio frequency and microwave devices, an increased number of women still experienced heavy bleeding after free fluid ablation (2.19, 1.07 to 4.50, P=0.03; and 2.91, 1.23 to 6.88, P=0.02, respectively). Compared with radio frequency ablation, free fluid ablation was associated with reduced rates of amenorrhoea (0.36, 0.19 to 0.67, P=0.004) and increased rates of dissatisfaction (4.79, 1.07 to 21.5, P=0.04). Of the less commonly used devices, endometrial laser intrauterine thermotherapy was associated with increased rates of amenorrhoea compared with all the other devices, while cryoablation led to a reduced rate compared with bipolar radio frequency and microwave. Conclusions Bipolar radio frequency and microwave ablative devices are more effective than thermal balloon and free fluid ablation in the treatment of heavy menstrual bleeding with second generation endometrial ablation devices.
Quadratic Higher Order Criteria for Iterative Blind Separation of a MIMO Convolutive Mixture of Sources

This paper deals with the problem of source separation in the case when the observations result from a multiple-input multiple-output convolutive mixing system. In a blind framework, higher order contrast functions have been proved to be efficient for extracting sources. Inspired by a semiblind approach, we propose new contrast functions for blind signal separation that make use of reference signals. The main advantage of this approach consists in the quadratic form of these criteria: the extraction of one source hence reduces to a simple optimization task for which fast and efficient algorithms are available. The separation of the other sources from the mixture is then carried out by an iterative deflation method. Furthermore, these contrasts are shown to be valid for both independent identically distributed (i.i.d.) and non-i.i. d. source signals. The performance offered by these criteria is investigated through simulations: they appear as very appealing tools compared with some classical contrast functions
The role of B cells in systemic sclerosis

Systemic sclerosis (SSc) is a connective disease characterized by features of autoimmunity, vasculopathy, inflammation, and fibrosis. The disease typically starts with Raynaud’s phenomenon, followed by skin thickening in the extremities due to inflammation and fibrosis. Fibrosis results from excessive collagen production by fibroblasts, which constitutes the final common pathway of complex cellular interactions including B cells. Several studies have indicated that B cells may play a role in SSc. Lesional skin infiltrates from SSc patients consist of a variety of cells, including eosinophils, neutrophils, lymphocytes, plasma cells, and macrophages. Autoantibodies of several specificities are present in the serum of SSc patients of which antitopoisomerase 1 is the most common, and evidence has been gathered for a potential pathogenic role of some autoantibodies, eg, anti-PDGF antibodies. The blood of SSc patients contains an increased proportion of naïve B cells but a decreased proportion of memory B cells. Furthermore, serum levels of interleukin-6, an important pro-inflammatory cytokine, have been shown to correlate with skin fibrosis. Animal models of SSc have provided more in-depth information on the role of B lymphocytes, eg, through disruption of B cell function. In this review we will discuss the evidence that B cells are involved in the pathogenesis of SSc.
Technology Adoption from Hybrid Corn to Beta Blockers

In his classic 1957 study of hybrid corn, Griliches emphasized the importance of economic incentives and profitability in the adoption of new technology, and this focus has been continued in the economics literature. But there is a distinct literature with roots in sociology emphasizing the structure of organizations, informal networks, and "change agents. " We return to a forty-year-old debate between Griliches and the sociologists by considering state-level factors associated with the adoption of a variety of technological innovations: hybrid corn and tractors in the first half of the 20th century, computers in the 1990s, and the treatment of heart attacks during the last decade. First, we find that some states consistently adopted new effective technology, whether hybrid corn, tractors, or effective treatments for heart attacks such as Beta Blockers. Second, the adoption of these new highly effective technologies was closely associated with social capital and state-level 1928 high school graduation rates, but not per capita income, density, or (in the case of Beta Blockers) expenditures on heart attack patients. Economic models are useful in identifying why some regions are more likely to adopt early, but sociological barriers -- perhaps related to a lack of social capital or informational networks -- can potentially explain why other regions lag far behind.
Bad Versus Good, What Matters More on the Treatment Floor? Relationships of Positive and Negative Events With Nurses' Burnout and Engagement.

Many investigators have reported the stressful aspects of nursing; fewer have focused on nurses' positive work experiences. For this study, we developed a 2 × 2 typology of positive and negative events related to the tasks of nursing work and the social and organizational context of that work: successes, supports, constraints, and conflicts. We hypothesized that positive events would predict engagement, negative events would predict burnout, and negative events would be more strongly related to both burnout and engagement. In secondary analyses of data from 310 acute care nurses who completed survey measures of workplace events at one time point and burnout and engagement measures approximately eight months later, regression results indicated that both positive and negative work events contributed to engagement, whereas only negative events were related to burnout. The results of dominance analyses established that constraints and conflicts more strongly predicted burnout than did supports and successes. Additionally, consistent with a "bad is stronger than good" perspective, the strongest predictor of engagement was lower constraints, although successes, supports, and conflicts also predicted engagement.
Retrievability: an evaluation measure for higher order information access tasks

Evaluation in Information Retrieval (IR) has long focused on effectiveness and efficiency. However, new and emerging access tasks now demand alternative evaluation measures which go beyond this traditional view. A retrieval system provides a means of gaining access to documents, therefore intuitively, our view of the collection is shaped by the retrieval system. In this paper, we outline some emerging information access related scenarios that require knowledge about how the retrieval system affects the users' ability to access information. This provides the motivation for the proposed evaluation measures and methodology where the focus is on capturing the behavior of the system, in terms of how retrievable it makes individual documents within the collection. To demonstrate the utility of the proposed methods, we perform an extensive analysis on two TREC collections showing how the measures can be applied to evaluate different information access questions. For higher order information access tasks that are inherently dependent on retrievability, our novel evaluation methodology emphasizes that effectiveness is an insufficient characterization of a retrieval system. This paper provides the foundations for the evaluation of higher order access related tasks.
Mitral cells in the olfactory bulb of adult zebrafish (Danio rerio): Morphology and distribution

The mitral cell is the primary output neuron and central relay in the olfactory bulb of vertebrates. The morphology of these cells has been studied extensively in mammalian systems and to a lesser degree in teleosts. This study uses retrograde tract tracing and other techniques to characterize the morphology and distribution of mitral cells in the olfactory bulb of adult zebrafish, Danio rerio. These output neurons, located primarily in the glomerular layer and superficial internal cell layer, had variable‐shaped somata that ranged in size from 4–18 μm in diameter and 31–96 μm2 in cross‐sectional area. The mitral cells exhibited two main types of morphologies with regard to their dendrites: the unidendritic morphology was a single primary dendrite with one or more tufts, but multidendritic cells with several dendritic projections also were seen. The axons of these cells projected to either the medial or the lateral olfactory tract and, in general, the location of the cell on the medial or lateral side of the bulb was indicative of the tract to which it would project. Further, this study shows that the majority of zebrafish mitral cells likely innervate a single glomerulus rather than multiple glomeruli. This information is contrary to the multiple innervation pattern suggested for all teleost mitral cells. Our findings suggest that mitral cells in zebrafish may be more similar to mammalian mitral cells than previously believed, despite variation in size and structure. This information provides a revised anatomical framework for olfactory processing studies in this key model system. J. Comp. Neurol. 499:218–230, 2006. © 2006 Wiley‐Liss, Inc.
Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines

Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic data staging area for extreme-scale machines. Such a staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
Spatial Domain No Reference Image Quality Assessment of JPEG Compressed Images

Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available. This paper aims to develop NR quality measurement algorithm for JPEG compressed images. For this purpose, standard LIVE image database is used. We try to show that Peak Signal to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality. Therefore, tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics. Furthermore, we tries to develop a computational and memory efficient NR quality assessment models for JPEG compressed images. Subjective test results are used to train the model, which achieves good quality prediction performance.