902 resultados para Simulation with multiple Consumers Profiles


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BACKGROUND: Patients with BM rarely survive .6 months and are commonly excluded from clinical trials. We aimed at improving outcome by exploring 2 combined modality regimens with at the time novel agents for which single-agent activity had been shown. METHODS: NSCLC patients with multiple BM were randomized to WBRT (10 × 3 Gy) and either GFT 250 mg p.o. daily or TMZ 75 mg/m2 p.o. daily ×21/28 days, starting on Day 1 of RT and to be continued until PD. Primary endpoint was overall survival, a Simon's optimal 2-stage design was based on assumptions for the 3-month survival rate. Cognitive functioning and quality of life were also evaluated. RESULTS: Fifty-nine patients (36 M, 23 F; 9 after prior chemo) were included. Median age was 61 years (range 46-82), WHO PS was 0 in 18 patients, 1 in 31 patients, and 2 in 10 patients. All but 1 patients had extracranial disease; 33 of 43 (TMZ) and 15 of 16 (GFT) had adenocarcinoma histology. GFT arm was closed early after stage 1 analysis when the prespecified 3-mo survival rate threshold (66%) was not reached, causes of death were not GFT related. Main causes of death were PD in the CNS 24%, systemic 41%, both 8%, and toxicity 10% [intestinal perforation (2 patients), pneumonia (2), pulmonary emboli (1), pneumonitis NOS (1), seizure (1)]. We summarize here other patients' characteristics for the 2 trial arms: TMZ (n ¼ 43)/GFT (n ¼ 16); median treatment duration: 1.6 /1.8 mo; Grade 3-4 toxicity: lymphopenia 5 patients (12%)/0; fatigue 8 patients (19%)/2 patients (13%). Survival data for TMZ/GFT arms: 3-month survival rate: 58.1% (95% CI 42.1-73)/62.5% (95% CI 35- 85); median OS: 4.9 months (95% CI 2.5-5.6)/6.3 months (95% CI 2.2- 14.6); median PFS: 1.8 months (95% CI 1.5-1.8)/1.8 (95% CI 1.1-3.9); median time to neurol. progr.: 8.0 months (95% CI 2.2-X)/4.8 (95% CI 3.9-10.5). In a model to predict survival time including the variables' age, PS, number of BM, global QL, total MMSE score, and subjective cognitive function, none of the variables accounted for a significant improvement in survival time. CONCLUSIONS: The combinations of WBRT with GFT or TMZ were feasible. However, in this unselected patient population, survival remains poor and a high rate of complication was observed. Four patients died as a result of high-dose corticosteroids. Preliminary evaluation of cognitive function andQL failed to show significant improvement. Indications and patient selection for palliative treatment should be revisited and careful monitoring and supportive care is required. Research and progress for this frequent clinical situation is urgently needed. Trial partly supported by AstraZeneca (Switzerland), Essex Chemie (Switzerland) and Swiss Federal Government.

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This work describes a simulation tool being developed at UPC to predict the microwave nonlinear behavior of planar superconducting structures with very few restrictions on the geometry of the planar layout. The software is intended to be applicable to most structures used in planar HTS circuits, including line, patch, and quasi-lumped microstrip resonators. The tool combines Method of Moments (MoM) algorithms for general electromagnetic simulation with Harmonic Balance algorithms to take into account the nonlinearities in the HTS material. The Method of Moments code is based on discretization of the Electric Field Integral Equation in Rao, Wilton and Glisson Basis Functions. The multilayer dyadic Green's function is used with Sommerfeld integral formulation. The Harmonic Balance algorithm has been adapted to this application where the nonlinearity is distributed and where compatibility with the MoM algorithm is required. Tests of the algorithm in TM010 disk resonators agree with closed-form equations for both the fundamental and third-order intermodulation currents. Simulations of hairpin resonators show good qualitative agreement with previously published results, but it is found that a finer meshing would be necessary to get correct quantitative results. Possible improvements are suggested.

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Reproductive division of labor and the coexistence of distinct castes are hallmarks of insect societies. In social insect species with multiple queens per colony, the fitness of nestmate queens directly depends on the process of caste allocation (i.e., the relative investment in queen, sterile worker and male production). The aim of this study is to investigate the genetic components to the process of caste allocation in a multiple-queen ant species. We conducted controlled crosses in the Argentine ant Linepithema humile and established single-queen colonies to identify maternal and paternal family effects on the relative production of new queens, workers, and males. There were significant effects of parental genetic backgrounds on various aspects of caste allocation: the paternal lineage affected the proportion of queens and workers produced whereas the proportions of queens and males, and females and males were influenced by the interaction between parental lineages. In addition to revealing nonadditive genetic effects on female caste determination in a multiple-queen ant species, this study reveals strong genetic compatibility effects between parental genomes on caste allocation components.

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INTRODUCTION: Deficits in decision making (DM) are commonly associated with prefrontal cortical damage, but may occur with multiple sclerosis (MS). There are no data concerning the impact of MS on tasks evaluating DM under explicit risk, where different emotional and cognitive components can be distinguished. METHODS: We assessed 72 relapsing-remitting MS (RRMS) patients with mild to moderate disease and 38 healthy controls in two DM tasks involving risk with explicit rules: (1) The Wheel of Fortune (WOF), which probes the anticipated affects of decisions outcomes on future choices; and (2) The Cambridge Gamble Task (CGT) which measures risk taking. Participants also underwent a neuropsychological and emotional assessment, and skin conductance responses (SCRs) were recorded. RESULTS: In the WOF, RRMS patients showed deficits in integrating positive counterfactual information (p<0.005) and greater risk aversion (p<0.001). They reported less negative affect than controls (disappointment: p = 0.007; regret: p = 0.01), although their implicit emotional reactions as measured by post-choice SCRs did not differ. In the CGT, RRMS patients differed from controls in quality of DM (p = 0.01) and deliberation time (p = 0.0002), the latter difference being correlated with attention scores. Such changes did not result in overall decreases in performance (total gains). CONCLUSIONS: The quality of DM under risk was modified by MS in both tasks. The reduction in the expression of disappointment coexisted with an increased risk aversion in the WOF and alexithymia features. These concomitant emotional alterations may have implications for better understanding the components of explicit DM and for the clinical support of MS patients.

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Background: The main goal of the present study was to analyse the genetic architecture of mRNA expression in muscle, a tissue with an outmost economic importance for pig breeders. Previous studies have used F2 crosses to detect porcine expression QTL (eQTL), so they contributed with data that mostly represents the between-breed component of eQTL variation. Herewith, we have analysed eQTL segregation in an outbred Duroc population using two groups of animals with divergent fatness profiles. This approach is particularly suitable to analyse the within-breed component of eQTL variation, with a special emphasis on loci involved in lipid metabolism. Methodology/Principal Findings: GeneChip Porcine Genome arrays (Affymetrix) were used to determine the mRNA expression levels of gluteus medius samples from 105 Duroc barrows. A whole-genome eQTL scan was carried out with a panel of 116 microsatellites. Results allowed us to detect 613 genome-wide significant eQTL unevenly distributed across the pig genome. A clear predominance of trans- over cis-eQTL, was observed. Moreover, 11 trans-regulatory hotspots affecting the expression levels of four to 16 genes were identified. A Gene Ontology study showed that regulatory polymorphisms affected the expression of muscle development and lipid metabolism genes. A number of positional concordances between eQTL and lipid trait QTL were also found, whereas limited evidence of a linear relationship between muscle fat deposition and mRNA levels of eQTL regulated genes was obtained. Conclusions/Significance: Our data provide substantial evidence that there is a remarkable amount of within-breed genetic variation affecting muscle mRNA expression. Most of this variation acts in trans and influences biological processes related with muscle development, lipid deposition and energy balance. The identification of the underlying causal mutations and the ascertainment of their effects on phenotypes would allow gaining a fundamental perspective about how complex traits are built at the molecular level.

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BACKGROUND: Increasing evidences link T helper 17 (Th17) cells with multiple sclerosis (MS). In this context, interleukin-22 (IL-22), a Th17-linked cytokine, has been implicated in blood brain barrier breakdown and lymphocyte infiltration. Furthermore, polymorphism between MS patients and controls has been recently described in the gene coding for IL-22 binding protein (IL-22BP). Here, we aimed to better characterize IL-22 in the context of MS. METHODS: IL-22 and IL-22BP expressions were assessed by ELISA and qPCR in the following compartments of MS patients and control subjects: (1) the serum, (2) the cerebrospinal fluid, and (3) immune cells of peripheral blood. Identification of the IL-22 receptor subunit, IL-22R1, was performed by immunohistochemistry and immunofluorescence in human brain tissues and human primary astrocytes. The role of IL-22 on human primary astrocytes was evaluated using 7-AAD and annexin V, markers of cell viability and apoptosis, respectively. RESULTS: In a cohort of 141 MS patients and healthy control (HC) subjects, we found that serum levels of IL-22 were significantly higher in relapsing MS patients than in HC but also remitting and progressive MS patients. Monocytes and monocyte-derived dendritic cells contained an enhanced expression of mRNA coding for IL-22BP as compared to HC. Using immunohistochemistry and confocal microscopy, we found that IL-22 and its receptor were detected on astrocytes of brain tissues from both control subjects and MS patients, although in the latter, the expression was higher around blood vessels and in MS plaques. Cytometry-based functional assays revealed that addition of IL-22 improved the survival of human primary astrocytes. Furthermore, tumor necrosis factor α-treated astrocytes had a better long-term survival capacity upon IL-22 co-treatment. This protective effect of IL-22 seemed to be conferred, at least partially, by a decreased apoptosis. CONCLUSIONS: We show that (1) there is a dysregulation in the expression of IL-22 and its antagonist, IL-22BP, in MS patients, (2) IL-22 targets specifically astrocytes in the human brain, and (3) this cytokine confers an increased survival of the latter cells.

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Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.

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The optimal number of mate partners for females rarely coincides with that for males, leading to a potential sexual conflict over multiple-partner mating. This suggests that the population sex ratio may affect multiple-partner mating and thus multiple paternity. We investigate the relationship between multiple paternity and the population sex ratio in the polygynandrous common lizard (Lacerta vivipara). In six populations the adult sex ratio was biased toward males, and in another six populations the adult sex ratio was biased toward females, the latter corresponding to the average adult sex ratio encountered in natural populations. In males the frequency and the degree of polygyny were lower in male-biased populations, as expected if competition among males determines polygyny. In females the frequency of polyandry was not different between treatments, and polyandrous females produced larger clutches, suggesting that polyandry might be adaptive. However, in male-biased populations females suffered from reduced reproductive success compared to female-biased populations, and the number of mate partners increased with female body size in polyandrous females. Polyandrous females of male-biased populations showed disproportionately more mating scars, indicating that polyandrous females of male-biased populations had more interactions with males and suggesting that the degree of multiple paternity is controlled by male sexual harassment. Our results thus imply that polyandry may be hierarchically controlled, with females controlling when to mate with multiple partners and male sexual harassment being a proximate determinant of the degree of multiple paternity. The results are also consistent with a sexual conflict in which male behaviors are harmful to females.

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An LC-MS/MS method has been developed for the determination of efavirenz (EFZ) in human plasma using hydrochlorothiazide as internal standard (I.S.). An ESI negative mode with multiple reaction-monitoring was used monitoring the transitions m/z 313.88→69.24 (EFZ) and 296.02→204.76 (I.S.). Samples were extracted using liquid-liquid extraction. The total run time was 2.0 min. The separation was achieved with HPLC-RP using a monolithic column. The assay was linear in the concentration range of 100 - 5000 ng mL-1. The mean recovery was 83%. Intra- and inter-day precision were < 9.5% and < 8.9%, respectively and accuracy was in the range ± 8.33%. The method was successfully applied to a bioequivalence study.

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The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

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Our understanding of the pathogenesis of organ‐specific autoinflammation has been restricted by limited access to the target organs. Peripheral blood, however, as a preferred transportation route for immune cells, provides a window to assess the entire immune system throughout the body. Transcriptional profiling with RNA stabilizing blood collection tubes reflects in vivo expression profiles at the time the blood is drawn, allowing detection of the disease activity in different samples or within the same sample over time. The main objective of this Ph.D. study was to apply gene‐expression microarrays in the characterization of peripheral blood transcriptional profiles in patients with autoimmune diseases. To achieve this goal a custom cDNA microarray targeted for gene‐expression profiling of human immune system was designed and produced. Sample collection and preparation was then optimized to allow gene‐expression profiling from whole‐blood samples. To overcome challenges resulting from minute amounts of sample material, RNA amplification was successfully applied to study pregnancy related immunosuppression in patients with multiple sclerosis (MS). Furthermore, similar sample preparation was applied to characterize longitudinal genome‐wide expression profiles in children with type 1 diabetes (T1D) associated autoantibodies and eventually clinical T1D. Blood transcriptome analyses, using both the ImmunoChip cDNA microarray with targeted probe selection and genome‐wide Affymetrix U133 Plus 2.0 oligonucleotide array, enabled monitoring of autoimmune activity. Novel disease related genes and general autoimmune signatures were identified. Notably, down‐regulation of the HLA class Ib molecules in peripheral blood was associated with disease activity in both MS and T1D. Taken together, these studies demonstrate the potential of peripheral blood transcriptional profiling in biomedical research and diagnostics. Imbalances in peripheral blood transcriptional activity may reveal dynamic changes that are relevant for the disease but might be completely missed in conventional cross‐sectional studies.

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The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

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Objective: To analyze the characteristics of trauma patients with renal lesions treated at a university hospital in Curitiba. Methods: We conducted a retrospective, cross-sectional study guided by review of medical records of trauma victims who underwent surgical treatment. The variables analyzed were age, gender, mechanism of injury, degree of kidney damage, conduct individualized according to the degree of renal injury, associated injuries, complications and deaths. We classified lesions according to the American Association of Trauma Surgery (TSAA). Results: We analyzed 794 records and found renal lesions in 33 patients, with mean age 29.8 years, most (87.8%) being male. Penetrating trauma accounted for 84.8% of cases. The most common renal injuries were grade II (33.3%), followed by grade I (18.1%), III, IV and V. Nephrectomy treated 45.4% of injuries, 73.3% being total nephrectomy, and 45.4% by nephrorraphy. In 9% treatment was non-surgical. Only 12.1% of patients had isolated renal lesions. Complications ensued in 15.1% and mortality was 6.06%. Conclusion: The surgical approach was preferred due to penetrating trauma mechanism. We achieved low rates of complications and deaths, and neither case could be directly related to kidney damage, and there were patients with multiple lesions. In this sample, we could not observe a direct relationship between kidney damage and complications, deaths or the type of conduct employed.

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The objective of this work is to describe the design and the implementation of an experiment to study the dynamics and the active control of a slewing multi-link flexible structure. The experimental apparatus was designed to be representative of a flexible space structure such as a satellite with multiple flexible appendages. In this study we describe the design procedures, the analog and digital instrumentation, the analytical modeling together with model validation studies carried out through experimental modal testing and parametric system identification studies in the frequency domain. Preliminary results of a simple positional control where the sensor and the actuator are positioned physically at the same point is also described.

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In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.