995 resultados para Structural parameter
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The recent wave of upheavals and revolts in Northern Africa and the Middle East goes back to an old question often raised by theories of collective action: does repression act as a negative or positive incentive for further mobilization? Through a review of the vast literature devoted to this question, this article aims to go beyond theoretical and methodological dead-ends. The article moves on to non-Western settings in order to better understand, via a macro-sociological and dynamic approach, the causal effects between mobilizations and repression. It pleads for a meso- and micro-level approach to this issue: an approach that puts analytical emphasis both on protest organizations and on individual activists' careers.
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Background: One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer.Results: We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes. Conclusion: We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.
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The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.
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BACKGROUND: Structural mutations (SMs) play a major role in cancer development. In some cancers, such as breast and ovarian, DNA double-strand breaks (DSBs) occur more frequently in transcribed regions, while in other cancer types such as prostate, there is a consistent depletion of breakpoints in transcribed regions. Despite such regularity, little is understood about the mechanisms driving these effects. A few works have suggested that protein binding may be relevant, e.g. in studies of androgen receptor binding and active chromatin in specific cell types. We hypothesized that this behavior might be general, i.e. that correlation between protein-DNA binding (and open chromatin) and breakpoint locations is common across divergent cancers. RESULTS: We investigated this hypothesis by comprehensively analyzing the relationship among 457 ENCODE protein binding ChIP-seq experiments, 125 DnaseI and 24 FAIRE experiments, and 14,600 SMs from 8 diverse cancer datasets covering 147 samples. In most cancers, including breast and ovarian, we found enrichment of protein binding and open chromatin in the vicinity of SM breakpoints at distances up to 200 kb. Furthermore, for all cancer types we observed an enhanced enrichment in regions distant from genes when compared to regions proximal to genes, suggesting that the SM-induction mechanism is independent from the bias of DSBs to occur near transcribed regions. We also observed a stronger effect for sites with more than one protein bound. CONCLUSIONS: Protein binding and open chromatin state are associated with nearby SM breakpoints in many cancer datasets. These observations suggest a consistent mechanism underlying SM locations across different cancers.
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Papez circuit is one of the major pathways of the limbic system, and it is involved in the control of memory and emotion. Structural and functional alterations have been reported in psychiatric, neurodegenerative, and epileptic diseases. Despite the clinical interest, however, in-vivo imaging of the entire circuit remains a technological challenge. We used magnetic resonance diffusion spectrum imaging to comprehensively picture the Papez circuit in healthy humans: (i) the hippocampus-mammillary body pathway, (ii) the connections between the lateral subiculum and the cingulate cortex, and (iii) the mammillo-thalamic tract. The diagnostic and therapeutic implications of these results are discussed in the context of recent findings reporting the involvement of the Papez circuit in neurological and psychiatric diseases.
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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.
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From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.
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Background and aim of the study: Bicuspid aortic valve is the most common congenital heart malformation, and a high percentage of patients with this condition will develop complications over time. It is rare that pilots undergo aortic valve surgery, and the confirmation of flight-licensing requirements after aortic valve replacement (AVR) is a challenge for the patient's cardiac surgeon and, particularly, for the Aeromedical Examiner (AME). Only AMEs are able to determine the flight status of pilots. Furthermore, in military and in civil aviation (e.g., Red Bull Air Race), the high G-load environment experienced by pilots is an exceptional physiological parameter, which must be considered postoperatively. Methods: A review was conducted of the aeronautical, surgical and medical literature, and of European pilot-licensing regulations. Case studies are also reported for two Swiss Air Force pilots. Results: According to European legislation, pilots can return to flight duty from the sixth postoperative month, with the following limitations: that an aortic bioprosthesis presents no restrictions in cardiac function, requires no cardioactive medications, yet requires a flight operation with co-pilot, the avoidance of accelerations over +3 Gz and, in military aviation, restricts the pilot to non-ejection-seat aircraft. The patient follow up must include both echocardiographic and rhythm assessments every six months. Mechanical prostheses cannot be certified because the required anticoagulation therapy is a disqualifying condition for pilot licensing. Conclusion: Pilot licensing after aortic valve surgery is possible, but with restrictions. The +Gz exposition is of concern in both military and civilian aviation (aerobatics). The choice of bioprosthesis type and size is determinant. Pericardial and stentless valves seem to show better flow characteristics under high-output conditions. Repetitive cardiological controls are mandatory for the early assessment of structural valve disease and rhythm disturbances. A pre-emptive timing is recommended when reoperation is indicated, without waiting for clinical manifestations of structural valve disease.
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BACKGROUND: Pneumocystis jirovecii dihydropteroate synthase (DHPS) mutations are associated with failure of prophylaxis with sulfa drugs. This retrospective study sought to better understand the geographical variation in the prevalence of these mutations. METHODS: DHPS polymorphisms in 394 clinical specimens from immunosuppressed patients who received a diagnosis of P. jirovecii pneumonia and who were hospitalized in 3 European cities were examined using polymerase chain reaction (PCR) single-strand conformation polymorphism. Demographic and clinical characteristics were obtained from patients' medical charts. RESULTS: Of the 394 patients, 79 (20%) were infected with a P. jirovecii strain harboring one or both of the previously reported DHPS mutations. The prevalence of DHPS mutations was significantly higher in Lyon than in Switzerland (33.0% vs 7.5%; P < .001). The proportion of patients with no evidence of sulfa exposure who harbored a mutant P. jirovecii DHPS genotype was significantly higher in Lyon than in Switzerland (29.7% vs 3.0%; P < .001). During the study period in Lyon, in contrast to the Swiss hospitals, measures to prevent dissemination of P. jirovecii from patients with P. jirovecii pneumonia were generally not implemented, and most patients received suboptimal prophylaxis, the failure of which was strictly associated with mutated P. jirovecii. Thus, nosocomial interhuman transmission of mutated strains directly or indirectly from other individuals in whom selection of mutants occurred may explain the high proportion of mutations without sulfa exposure in Lyon. CONCLUSIONS: Interhuman transmission of P. jirovecii, rather than selection pressure by sulfa prophylaxis, may play a predominant role in the geographical variation in the prevalence in the P. jirovecii DHPS mutations.
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This paper investigates the relationship between time variations in output and inflation dynamics and monetary policy in the US. There are changes in the structural coefficients and in the variance of the structural shocks. The policy rules in the 1970s and 1990s are similar as is the transmission of policy disturbances. Inflation persistence is only partly a monetary phenomena. Variations in the systematic component of policy have limited effects on the dynamics of output and inflation. Results are robust to alterations in the auxiliary assumptions.
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The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.
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We performed whole genome sequencing in 16 unrelated patients with autosomal recessive retinitis pigmentosa (ARRP), a disease characterized by progressive retinal degeneration and caused by mutations in over 50 genes, in search of pathogenic DNA variants. Eight patients were from North America, whereas eight were Japanese, a population for which ARRP seems to have different genetic drivers. Using a specific workflow, we assessed both the coding and noncoding regions of the human genome, including the evaluation of highly polymorphic SNPs, structural and copy number variations, as well as 69 control genomes sequenced by the same procedures. We detected homozygous or compound heterozygous mutations in 7 genes associated with ARRP (USH2A, RDH12, CNGB1, EYS, PDE6B, DFNB31, and CERKL) in eight patients, three Japanese and five Americans. Fourteen of the 16 mutant alleles identified were previously unknown. Among these, there was a 2.3-kb deletion in USH2A and an inverted duplication of ∼446 kb in EYS, which would have likely escaped conventional screening techniques or exome sequencing. Moreover, in another Japanese patient, we identified a homozygous frameshift (p.L206fs), absent in more than 2,500 chromosomes from ethnically matched controls, in the ciliary gene NEK2, encoding a serine/threonine-protein kinase. Inactivation of this gene in zebrafish induced retinal photoreceptor defects that were rescued by human NEK2 mRNA. In addition to identifying a previously undescribed ARRP gene, our study highlights the importance of rare structural DNA variations in Mendelian diseases and advocates the need for screening approaches that transcend the analysis of the coding sequences of the human genome.
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Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.