875 resultados para Continuous Variable Systems


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Utilisation of sorting systems’ maximum performance demands continuous conveying of goods by infeed lines to sorters. This is the case especially for sorters with one single infeed line, because the sorters’ performance is limited by the performance of the infeed line. Within this paper different infeed line constructions at the Rotary Sorter with diverse performances will be presented. The focus lies on a specific conveying system to synchronise the goods with the sorter by a performance of 6000 pieces per hour with one dynamic infeed line. By this means there is no extensive adjustment control of serial conveyors in the infeed line any longer.

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Fifty-six acres of central Iowa corn land were seeded to bromegrass and divided with high-tensile wire into eight seven-acre plots. This bromegrass was fertilized with 70 pounds of nitrogen each spring and fall, 1987-1990. In 1991 – 1995, the nitrogen was increased to 80 pounds both spring and fall. The plots were stocked with 1.3 cow/calf pairs per acre in 1987-1991 and 1993–1995, but in 1992 the plots were stocked with 1.55 cow/calf pairs per acre. The pairs were rotated using two distinct schemes among four cells for about 150 days. The plots averaged 607 pounds of net calf weight per acre per year over nine years. Rainfall was quite variable during the grazing seasons and was reflected in calf performance as well as summer feed costs. This intensive rotational grazing system has greatly reduced both weed population and the need for mechanical clipping.

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Economic comparisons of income on highly erodible land (HEL) in Adams County were made utilizing five years of grazing data collected from a 13- paddock intensive-rotational grazing system and a four-paddock rotational-grazing system and four years of data collected from an 18-paddock intensive-rotational grazing system, all at the Adams County CRP Research and Demonstration Farm near Corning. Net income from the average grazing weight-gain of Angus-sired calves nursing crossbred cows was compared to the net income from grazing yearling steers, to the net income of eight NRCS-recommended crop rotations, and to the Conservation Reserve Program (CRP) option. Results of these comparisons show the 13-paddock intensive rotational grazing system with cow-calf pairs to be the most profitable alternative, with a net return of $19.86 per acre per year. The second most profitable alternative is the CRP option, with a net return of $13.09 per acre, and the third most profitable option is the fourpaddock rotation with cows and calves with a net return of $12.53 per acre. An 18-paddock system returned a net income of $2.47 per acre per year with cows and calves in 1993, but lost an average of $107.69 per acre each year in 1994 and 1995 with yearling steers. Each year, the steers were purchased high and sold low, contributing to the large loss per acre. The following recommended crop rotations all show net losses on these 9-14 % slope, Adair-Shelby Complex soils (ApD3): continuous corn; corn-soybean rotation; corn-soybean rotation with a farm program deficiency payment; corn-corn-corn-oats-meadow-meadow rotation with grass headlands; continuous corn to “T” with grass headlands and buffer strips; continuous corn to “T” with grass headlands, buffer strips, and a deficiency payment; corn-corn-oats-meadow rotation to “T”; and corn-soybeans-oats-meadow-meadow-meadow-meadow rotation to “T”. Per-acre yield assumptions of 90 bushels for corn, 30 bushels for soybeans, 45 bushels for oats, and four tons for alfalfa were used, with per-bushel prices of $2.40 on corn, $5.50 on soybeans, and $1.50 on oats. Alfalfa hay was priced at $40.00 per ton and grass hay at $33.33 per ton. The calf weight-gain in the cow/ calf systems was valued at $.90 per pound. All crop expenses except land costs were calculated from ISU publication Fm 1712, “Estimated Costs of Crop Production in Iowa - 1995.” Land costs were determined by using an opportunity cost and actual property tax figures for the land at the grazing site. In preparation for the end of the CRP beginning in 1996, further economic comparisons will be made after additional grazing seasons and data collection. This project is an interagency cooperative effort sponsored by the Southern Iowa Forage and Livestock Committee which has special permission from the USDA Farm Service Agency (FSA) to use CRP land for research and demonstration.

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Recent outstanding clinical advances with new mechanical circulatory systems have led to additional strategies in the treatment of end-stage heart failure. Heart transplantation can be postponed and for certain patients even replaced by smaller implantable left ventricular assist devices (LVADs). Mechanical support of the failing left ventricle enables appropriate haemodynamic stabilization and recovery of secondary organ failure, often seen in these severely ill patients. These new devices may be of great help to bridge patients until a suitable cardiac allograft is available but are also discussed as definitive treatment for patients who do not qualify for transplantation. Main indications for LVAD implantation are bridge to recovery, bridge to transplantation or destination therapy. An LVAD may be an important tool for patients with an expected prolonged period on the waiting list, for instance those with blood group O or B, with high or low body weight and those with potentially reversible secondary organ failure and pulmonary artery hypertension. However, LVAD implantation means an additional heart operation with inherent perioperative risks and complications during the waiting period. Finally, cardiac transplantation in patients with prior implantation of an LVAD represents a surgical challenge. The care of patients after the implantation of miniaturized LVADs, such as the HeartWare® system, seems to be easier than following pulsatile devices. The explantation of such devices at the time of transplantation is technically more comfortable than after HeartMate II implantation.

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BACKGROUND Epidemiological studies show that elevated levels of particulate matter in ambient air are highly correlated with respiratory and cardiovascular diseases. Atmospheric particles originate from a large number of sources and have a highly complex and variable composition. An assessment of their potential health risks and the identification of the most toxic particle sources would require a large number of investigations. Due to ethical and economic reasons, it is desirable to reduce the number of in vivo studies and to develop suitable in vitro systems for the investigation of cell-particle interactions. METHODS We present the design of a new particle deposition chamber in which aerosol particles are deposited onto cell cultures out of a continuous air flow. The chamber allows for a simultaneous exposure of 12 cell cultures. RESULTS Physiological conditions within the deposition chamber can be sustained constantly at 36-37°C and 90-95% relative humidity. Particle deposition within the chamber and especially on the cell cultures was determined in detail, showing that during a deposition time of 2 hr 8.4% (24% relative standard deviation) of particles with a mean diameter of 50 nm [mass median diameter of 100 nm (geometric standard deviation 1.7)] are deposited on the cell cultures, which is equal to 24-34% of all charged particles. The average well-to-well variability of particles deposited simultaneously in the 12 cell cultures during an experiment is 15.6% (24.7% relative standard deviation). CONCLUSIONS This particle deposition chamber is a new in vitro system to investigate realistic cell-particle interactions at physiological conditions, minimizing stress on the cell cultures other than from deposited particles. A detailed knowledge of particle deposition characteristics on the cell cultures allows evaluating reliable dose-response relationships. The compact and portable design of the deposition chamber allows for measurements at any particle sources of interest.

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With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

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When drilling ice cores deeper than ∼100 m, drill liquid is required to maintain ice-core quality and to limit borehole closure. Due to high-pressure air bubbles in the ice, the ice core can crack during drilling and core retrieval, typically at 600–1200 m depth in Greenland. Ice from this 'brittle zone' can be contaminated by drill liquid as it seeps through cracks into the core. Continuous flow analysis (CFA) systems are routinely used to analyse ice for chemical impurities, so the detection of drill liquid is important for validating accurate measurements and avoiding potential instrument damage. An optical detector was constructed to identify drill liquid in CFA tubing by ultraviolet absorption spectroscopy at a wavelength of 290 nm. The set-up was successfully field-tested in the frame of the NEEM ice-core drilling project in Greenland. A total of 27 cases of drill liquid contamination were identified during the analysis of 175 m of brittle zone ice. The analyses most strongly affected by drill liquid contamination include insoluble dust particles, electrolytic conductivity, ammonium, hydrogen peroxide and sulphate. This method may also be applied to other types of drill liquid used at other drill sites.

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Both theoretically and empirically there is a continuous interest in understanding the specific relation between cognitive and motor development in childhood. In the present longitudinal study including three measurement points, this relation was targeted. At the beginning of the study, the participating children were 5-6-year-olds. By assessing participants' fine motor skills, their executive functioning, and their non-verbal intelligence, their cross-sectional and cross-lagged interrelations were examined. Additionally, performance in these three areas was used to predict early school achievement (in terms of mathematics, reading, and spelling) at the end of participants' first grade. Correlational analyses and structural equation modeling revealed that fine motor skills, non-verbal intelligence and executive functioning were significantly interrelated. Both fine motor skills and intelligence had significant links to later school achievement. However, when executive functioning was additionally included into the prediction of early academic achievement, fine motor skills and non-verbal intelligence were no longer significantly associated with later school performance suggesting that executive functioning plays an important role for the motor-cognitive performance link.

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We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

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The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

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Demonstration of survival and outcome of progressive multifocal leukoencephalopathy (PML) in a 56-year-old patient with common variable immunodeficiency, consisting of severe hypogammaglobulinemia and CD4+ T lymphocytopenia, during continuous treatment with mirtazapine (30 mg/day) and mefloquine (250 mg/week) over 23 months. Regular clinical examinations including Rankin scale and Barthel index, nine-hole peg and box and block tests, Berg balance, 10-m walking tests, and Montreal Cognitive Assessment (MoCA) were done. Laboratory diagnostics included complete blood count and JC virus (JCV) concentration in cerebrospinal fluid (CSF). The noncoding control region (NCCR) of JCV, important for neurotropism and neurovirulence, was sequenced. Repetitive MRI investigated the course of brain lesions. JCV was detected in increasing concentrations (peak 2568 copies/ml CSF), and its NCCR was genetically rearranged. Under treatment, the rearrangement changed toward the archetype sequence, and later JCV DNA became undetectable. Total brain lesion volume decreased (8.54 to 3.97 cm(3)) and atrophy increased. Barthel (60 to 100 to 80 points) and Rankin (4 to 2 to 3) scores, gait stability, and box and block (7, 35, 25 pieces) and nine-hole peg (300, 50, 300 s) test performances first improved but subsequently worsened. Cognition and walking speed remained stable. Despite initial rapid deterioration, the patient survived under continuous treatment with mirtazapine and mefloquine even though he belongs to a PML subgroup that is usually fatal within a few months. This course was paralleled by JCV clones with presumably lower replication capability before JCV became undetectable. Neurological deficits were due to PML lesions and progressive brain atrophy.

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A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

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When genetic constraints restrict phenotypic evolution, diversification can be predicted to evolve along so-called lines of least resistance. To address the importance of such constraints and their resolution, studies of parallel phenotypic divergence that differ in their age are valuable. Here, we investigate the parapatric evolution of six lake and stream threespine stickleback systems from Iceland and Switzerland, ranging in age from a few decades to several millennia. Using phenotypic data, we test for parallelism in ecotypic divergence between parapatric lake and stream populations and compare the observed patterns to an ancestral-like marine population. We find strong and consistent phenotypic divergence, both among lake and stream populations and between our freshwater populations and the marine population. Interestingly, ecotypic divergence in low-dimensional phenotype space (i.e. single traits) is rapid and seems to be often completed within 100 years. Yet, the dimensionality of ecotypic divergence was highest in our oldest systems and only there parallel evolution of unrelated ecotypes was strong enough to overwrite phylogenetic contingency. Moreover, the dimensionality of divergence in different systems varies between trait complexes, suggesting different constraints and evolutionary pathways to their resolution among freshwater systems.

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Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

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Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^