3,134 research outputs found

    Predicting pharmaceutical particle size distributions using kernel mean embedding

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    In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGmaTM-25 continuous powder-to-tablet system (GEA Pharma systems, Collette, Wommelgem, Belgium), the product under study presents itself as a collection of particles that differ in shape and size. The measurement of this collection results in a particle size distribution. However, the theoretical basis to describe the physical phenomena leading to changes in this particle size distribution is lacking. It is essential to understand how the particle size distribution changes as a function of the unit operation's process settings, as it has a profound effect on the behavior of the fluid bed dryer. Therefore, we suggest a data-driven modeling framework that links the machine settings of the wet granulation unit operation and the output distribution of granules. We do this without making any assumptions on the nature of the distributions under study. A simulation of the granule size distribution could act as a soft sensor when in-line measurements are challenging to perform. The method of this work is a two-step procedure: first, the measured distributions are transformed into a high-dimensional feature space, where the relation between the machine settings and the distributions can be learnt. Second, the inverse transformation is performed, allowing an interpretation of the results in the original measurement space. Further, a comparison is made with previous work, which employs a more mechanistic framework for describing the granules. A reliable prediction of the granule size is vital in the assurance of quality in the production line, and is needed in the assessment of upstream (feeding) and downstream (drying, milling, and tableting) issues. Now that a validated data-driven framework for predicting pharmaceutical particle size distributions is available, it can be applied in settings such as model-based experimental design and, due to its fast computation, there is potential in real-time model predictive control

    Development and computer implementation of design/analysis techniques for multilayered composite structures. Probabilistic fiber composite micromechanics

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    Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. The variables in which uncertainties are accounted for include constituent and void volume ratios, constituent elastic properties and strengths, and fiber misalignment. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material property variations induced by random changes expected at the material micro level. Regression results are presented to show the relative correlation between predictor and response variables in the study. These computational procedures make possible a formal description of anticipated random processes at the intraply level, and the related effects of these on composite properties

    Probabilistic Fiber Composite Micromechanics

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    Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. The variables in which uncertainties are accounted for include constituent and void volume ratios, constituent elastic properties and strengths, and fiber misalignment. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material property variations induced by random changes expected at the material micro level. Regression results are presented to show the relative correlation between predictor and response variables in the study. These computational procedures make possible a formal description of anticipated random processes at the intra-ply level, and the related effects of these on composite properties

    Economies of Size for Conventional Tillage and No-till Wheat Production

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    Production costs and economies of size for both conventional tillage and no-till wheat production were determined. The reduction in the price of glyphosate after the patent expired improved the relative economics of no-till for continuous monoculture winter wheat. Production costs differ across farm size and by production system.Crop Production/Industries,

    The status of Bogidiella Balearica Dancau, 1973, a stygobiont amphipod from Mallorca

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    [spa] Se presenta la redescripción de Bogidiella balearica Dancau, 1973, un anfípodo estigobionte de las cuevas anquihalinas de Mallorca. Queda demostrado que se trata de una buena especie, clasificable dentro del subgénero Bogidiella s. str., y que se puede diferenciar fåcilmente de Bogidiella chappuisi Ruffo, 1952 (con la cual se intentó sinonimizar con anterioridad), perteneciente a otro subgénero, Medigidiella.[eng] Redescription of Bogidiella balearica Dancau, 1973, a stygobiont amphipod from anchihaline caves in Mallorca. It proves to be a good species, to be classified with the subgenus Bogidiella s. str., and it is well-distinguished from Bogidiella chappuisi Ruffo, 1952 (with which it was tentatively synonyrnized in the past), belonging to a different suhgenus, Medigidiella

    Global oceanic emission of ammonia: constraints from seawater and atmospheric observations

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    Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia (NHx(sw)), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here we compare [NHx(sw)] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [NHx(sw)] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NHx within observed ranges. The resulting global ocean emissions is 2.5 TgN a−1, much lower than current literature values (7–23 TgN a−1), including the widely used Global Emissions InitiAtive (GEIA) inventory (8 TgN a−1). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NHx over most of the ocean in the Northern Hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a−1, comparable in magnitude to other natural sources from open fires and soils
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