927 resultados para asymptotically almost periodic functions


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Alle bisher untersuchten Lebewesen besitzen (circadiane) innere Uhren, die eine endogene Perioden-länge von ungefähr 24 Stunden generieren. Eine innere Uhr kann über Zeitgeber mit der Umwelt synchronisiert werden und ermöglicht dem Organismus, rhythmische Umweltveränderungen vorweg zu nehmen. Neben einem zentralen Schrittmacher, der Physiologie und Verhalten des Organismus steuert, gibt es in unterschiedlichen Organen auch periphere Uhren, die die zeitlichen Abläufe in der spezifischen Funktion dieser Organe steuern. In dieser Arbeit sollten zentrale und periphere Schrittmacherneurone von Insekten physiologisch untersucht und verglichen werden. Die Neurone der akzessorischen Medulla (AME) von Rhyparobia maderae dienten als Modellsystem für zentrale Schrittmacher, während olfaktorische Rezeptorneurone (ORNs) von Manduca sexta als Modellsystem für periphere Schrittmacher dienten. Die zentralen Schrittmacherneurone wurden in extrazellulären Ableitungen an der isolierten AME (Netzwerkebene) und in Patch-Clamp Experimenten an primären AME Zellkulturen (Einzelzellebene) untersucht. Auf Netzwerkebene zeigten sich zwei charakteristische Aktivitätsmuster: regelmäßige Aktivität und Wechsel zwischen hoher und niedriger Aktivität (Oszillationen). Es wurde gezeigt, dass Glutamat ein Neurotransmitter der weitverbreiteten inhibitorischen Synapsen der AME ist, und dass in geringem Maße auch exzitatorische Synapsen vorkommen. Das Neuropeptid pigment-dispersing factor (PDF), das von nur wenigen AME Neuronen exprimiert wird und ein wichtiger Kopplungsfaktor im circadianen System ist, führte zu Hemmungen, Aktivierungen oder Oszillationen. Die Effekte waren transient oder langanhaltend und wurden wahrscheinlich durch den sekundären Botenstoff cAMP vermittelt. Ein Zielmolekül von cAMP war vermutlich exchange protein directly activated by cAMP (EPAC). Auf Einzelzellebene wurde gezeigt, dass die meisten AME Neurone depolarisiert waren und deshalb nicht feuerten. Die Analyse von Strom-Spannungs-Kennlinien und pharmakologische Experimente ergaben, dass unterschiedliche Ionenkanäle vorhanden waren (Ca2+, Cl-, K+, Na+ Kanäle sowie nicht-spezifische Kationenkanäle). Starke, bei hohen Spannungen aktivierende Ca2+ Ströme (ICa) könnten eine wichtige Rolle bei Ca2+-abhängiger Neurotransmitter-Ausschüttung, Oszillationen, und Aktionspotentialen spielen. PDF hemmte unterschiedliche Ströme (ICa, IK und INa) und aktivierte nicht-spezifische Kationenströme (Ih). Es wurde angenommen, dass simultane PDF-abhängige Hyper- und Depolarisationen rhythmische Membranpotential-Oszillationen verursachen. Dieser Mechanismus könnte eine Rolle bei PDF-abhängigen Synchronisationen spielen. Die Analyse peripherer Schrittmacherneurone konzentrierte sich auf die Charakterisierung des olfaktorischen Corezeptors von M. sexta (MsexORCO). In anderen Insekten ist ORCO für die Membran-Insertion von olfaktorischen Rezeptoren (ORs) erforderlich. ORCO bildet Komplexe mit den ORs, die in heterologen Expressionssystemen als Ionenkanäle fungieren und Duft-Antworten vermitteln. Es wurde die Hypothese aufgestellt, dass MsexORCO in pheromonsensitiven ORNs in vivo nicht als Teil eines ionotropen Rezeptors sondern als Schrittmacherkanal fungiert, der unterschwellige Membranpotential-Oszillationen generiert. MsexORCO wurde mit vermeintlichen Pheromonrezeptoren in human embryonic kidney (HEK 293) Zellen coexprimiert. Immuncytochemie und Ca2+ Imaging Experimente zeigten sehr schwache Expressionsraten. Trotzdem war es möglich zu zeigen, dass MsexORCO wahrscheinlich ein spontan-aktiver, Ca2+-permeabler Ionenkanal ist, der durch den ORCO-Agonisten VUAA1 und cyclische Nucleotide aktiviert wird. Außerdem wiesen die Experimente darauf hin, dass MsexOR-1 offensichtlich der Bombykal-Rezeptor ist. Eine weitere Charakterisierung von MsexORCO in primären M. sexta ORN Zellkulturen konnte nicht vollendet werden, weil die ORNs nicht signifikant auf ORCO-Agonisten oder -Antagonisten reagierten.

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Worldwide water managers are increasingly challenged to allocate sufficient and affordable water supplies to different water use sectors without further degrading river ecosystems and their valuable services to mankind. Since 1950 human population almost tripled, water abstractions increased by a factor of four, and the number of large dam constructions is about eight times higher today. From a hydrological perspective, the alteration of river flows (temporally and spatially) is one of the main consequences of global change and further impairments can be expected given growing population pressure and projected climate change. Implications have been addressed in numerous hydrological studies, but with a clear focus on human water demands. Ecological water requirements have often been neglected or addressed in a very simplistic manner, particularly from the large-scale perspective. With his PhD thesis, Christof Schneider took up the challenge to assess direct (dam operation and water abstraction) and indirect (climate change) impacts of human activities on river flow regimes and evaluate the consequences for river ecosystems by using a modeling approach. The global hydrology model WaterGAP3 (developed at CESR) was applied and further developed within this thesis to carry out several model experiments and assess anthropogenic river flow regime modifications and their effects on river ecosystems. To address the complexity of ecological water requirements the assessment is based on three main ideas: (i) the natural flow paradigm, (ii) the perception that different flows have different ecological functions, and (iii) the flood pulse concept. The thesis shows that WaterGAP3 performs well in representing ecologically relevant flow characteristics on a daily time step, and therefore justifies its application within this research field. For the first time a methodology was established to estimate bankfull flow on a 5 by 5 arc minute grid cell raster globally, which is a key parameter in eFlow assessments as it marks the point where rivers hydraulically connect to adjacent floodplains. Management of dams and water consumption pose a risk to floodplains and riparian wetlands as flood volumes are significantly reduced. The thesis highlights that almost one-third of 93 selected Ramsar sites are seriously affected by modified inundation patterns today, and in the future, inundation patterns are very likely to be further impaired as a result of new major dam initiatives and climate change. Global warming has been identified as a major threat to river flow regimes as rising temperatures, declining snow cover, changing precipitation patterns and increasing climate variability are expected to seriously modify river flow regimes in the future. Flow regimes in all climate zones will be affected, in particular the polar zone (Northern Scandinavia) with higher river flows during the year and higher flood peaks in spring. On the other side, river flows in the Mediterranean are likely to be even more intermittent in the future because of strong reductions in mean summer precipitation as well as a decrease in winter precipitation, leading to an increasing number of zero flow events creating isolated pools along the river and transitions from lotic to lentic waters. As a result, strong impacts on river ecosystem integrity can be expected. Already today, large amounts of water are withdrawn in this region for agricultural irrigation and climate change is likely to exacerbate the current situation of water shortages.

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The dynamic power requirement of CMOS circuits is rapidly becoming a major concern in the design of personal information systems and large computers. In this work we present a number of new CMOS logic families, Charge Recovery Logic (CRL) as well as the much improved Split-Level Charge Recovery Logic (SCRL), within which the transfer of charge between the nodes occurs quasistatically. Operating quasistatically, these logic families have an energy dissipation that drops linearly with operating frequency, i.e., their power consumption drops quadratically with operating frequency as opposed to the linear drop of conventional CMOS. The circuit techniques in these new families rely on constructing an explicitly reversible pipelined logic gate, where the information necessary to recover the energy used to compute a value is provided by computing its logical inverse. Information necessary to uncompute the inverse is available from the subsequent inverse logic stage. We demonstrate the low energy operation of SCRL by presenting the results from the testing of the first fully quasistatic 8 x 8 multiplier chip (SCRL-1) employing SCRL circuit techniques.

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We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models, Breiman's hinge functions and some forms of Projection Pursuit Regression. In the probabilistic interpretation of regularization, the different classes of basis functions correspond to different classes of prior probabilities on the approximating function spaces, and therefore to different types of smoothness assumptions. In the final part of the paper, we also show a relation between activation functions of the Gaussian and sigmoidal type.

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The periodic silane burst technique was employed during metalorganic chemical vapor deposition of epitaxial GaN on AlN buffer layers grown on Si (111). Periodic silicon delta doping during growth of both the AlN and GaN layers led to growth of GaN films with decreased tensile stresses and decreased threading dislocation densities, as well as films with improved quality as indicated by x-ray diffraction, micro-Raman spectroscopy, atomic force microscopy, and transmission electron microscopy. The possible mechanism of the reduction of tensile stress and the dislocation density is discussed in the paper.

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We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy.

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We analyze an infinite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are identically distributed random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to maximize expected discounted, or expected average profit over the infinite planning horizon. We show that a stationary (s,S,p) policy is optimal for both the discounted and average profit models with general demand functions. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period.

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Compositional data analysis motivated the introduction of a complete Euclidean structure in the simplex of D parts. This was based on the early work of J. Aitchison (1986) and completed recently when Aitchinson distance in the simplex was associated with an inner product and orthonormal bases were identified (Aitchison and others, 2002; Egozcue and others, 2003). A partition of the support of a random variable generates a composition by assigning the probability of each interval to a part of the composition. One can imagine that the partition can be refined and the probability density would represent a kind of continuous composition of probabilities in a simplex of infinitely many parts. This intuitive idea would lead to a Hilbert-space of probability densities by generalizing the Aitchison geometry for compositions in the simplex into the set probability densities

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Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total cost over a planning horizon. In this paper, we propose a framework for incorporating risk aversion in multi-period inventory models as well as multi-period models that coordinate inventory and pricing strategies. In each case, we characterize the optimal policy for various measures of risk that have been commonly used in the finance literature. In particular, we show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk-neutral inventory (and pricing) policies. Computational results demonstrate the importance of this approach not only to risk-averse decision makers, but also to risk-neutral decision makers with limited information on the demand distribution.

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Functional Data Analysis (FDA) deals with samples where a whole function is observed for each individual. A particular case of FDA is when the observed functions are density functions, that are also an example of infinite dimensional compositional data. In this work we compare several methods for dimensionality reduction for this particular type of data: functional principal components analysis (PCA) with or without a previous data transformation and multidimensional scaling (MDS) for diferent inter-densities distances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (households income distributions)

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An essential tool for chemistry students. Presentation of the table in which elements are assigned a symbol and shows the atomic number of each element.

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Exam questions and solutions in LaTex

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Exam questions and solutions in PDF

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Exam questions and solutions in PDF

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Exam questions and solutions in LaTex. Diagrams for the questions are all together in the support.zip file, as .eps files