Killer Whales and Marine Mammal Trends in The North Pacific—A Re-Examination of Evidence for Sequential Megafauna Collapse and the Prey-Switching Hypothesis

Springer et al. (2003) contend that sequential declines occurred in North Pacific populations of harbor and fur seals, Steller sea lions, and sea otters. They hypothesize that these were due to increased predation by killer whales, when industrial whaling’s removal of large whales as a supposed primary food source precipitated a prey switch. Using a regional approach, we reexamined whale catch data, killer whale predation observations, and the current biomass and trends of potential prey, and found little support for the prey-switching hypothesis. Large whale biomass in the Bering Sea did not decline as much as suggested by Springer et al., and much of the reduction occurred 50–100 yr ago, well before the declines of pinnipeds and sea otters began; thus, the need to switch prey starting in the 1970s is doubtful. With the sole exception that the sea otter decline followed the decline of pinnipeds, the reported declines were not in fact sequential. Given this, it is unlikely that a sequential megafaunal collapse from whales to sea otters occurred. The spatial and temporal patterns of pinniped and sea otter population trends are more complex than Springer et al. suggest, and are often inconsistent with their hypothesis. Populations remained stable or increased in many areas, despite extensive historical whaling and high killer whale abundance. Furthermore, observed killer whale predation has largely involved pinnipeds and small cetaceans; there is little evidence that large whales were ever a major prey item in high latitudes. Small cetaceans (ignored by Springer et al.) were likely abundant throughout the period. Overall, we suggest that the Springer et al. hypothesis represents a misleading and simplistic view of events and trophic relationships within this complex marine ecosystem.

A Novel Fiber Delay Line Buffering Architecture for Optical Packet Switching

Due to the lack of optical random access memory, optical fiber delay line (FDL) is currently the only way to implement optical buffering. Feed-forward and feedback are two kinds of FDL structures in optical buffering. Both have advantages and disadvantages. In this paper, we propose a more effective hybrid FDL architecture that combines the merits of both schemes. The core of this switch is the arrayed waveguide grating (AWG) and the tunable wavelength converter (TWC). It requires smaller optical device sizes and fewer wavelengths and has less noise than feedback architecture. At the same time, it can facilitate preemptive priority routing which feed-forward architecture cannot support. Our numerical results show that the new switch architecture significantly reduces packet loss probability.

Selection of Switching Sites in All-Optical Nework Topology Design

In this paper, we consider the problem of topology design for optical networks. We investigate the problem of selecting switching sites to minimize total cost of the optical network. The cost of an optical network can be expressed as a sum of three main factors: the site cost, the link cost, and the switch cost. To the best of our knowledge, this problem has not been studied in its general form as investigated in this paper. We present a mixed integer quadratic programming (MIQP) formulation of the problem to find the optimal value of the total network cost. We also present an efficient heuristic to approximate the solution in polynomial time. The experimental results show good performance of the heuristic. The value of the total network cost computed by the heuristic varies within 2% to 21% of its optimal value in the experiments with 10 nodes. The total network cost computed by the heuristic for 51% of the experiments with 10 node network topologies varies within 8% of its optimal value. We also discuss the insight gained from our experiments.

Inward-Inclined Implant Platform for the Amplified Platform-Switching Concept: 18-Month Follow-up Report of a Prospective Randomized Matched-Pair Controlled Trial

Purpose: This prospective randomized matched-pair controlled trial aimed to evaluate marginal bone levels and soft tissue alterations at implants restored according to the platform-switching concept with a new inward-inclined platform and compare them with external-hexagon implants. Materials and Methods: Traditional external-hexagon (control group) implants and inward-inclined platform implants (test group), all with the same implant body geometry and 13 mm in length, were inserted in a standardized manner in the posterior maxillae of 40 patients. Radiographic bone levels were measured by two independent examiners after 6, 12, and 18 months of prosthetic loading. Buccal soft tissue height was measured at the time of abutment connection and 18 months later. Results: After 18 months of loading, all 80 implants were clinically osseointegrated in the 40 participating patients. Radiographic evaluation showed mean bone losses of 0.5 +/- 0.1 mm (range, 0.3 to 0.7 mm) and 1.6 +/- 0.3 mm (range, 1.1 to 2.2 mm) for test and control implants, respectively. Soft tissue height showed a significant mean decrease of 2.4 mm in the control group, compared to 0.6 mm around the test implants. Conclusions: After 18 months, significantly greater bone loss was observed at implants restored according to the conventional external-hexagon protocol compared to the platform-switching concept. In addition, decreased soft tissue height was associated with the external-hexagon implants versus the platform-switched implants. INT J ORAL MAXILLOFAC IMPLANTS 2012;27:927-934.

A New Method of Current Switching for Linear Wide-Range Measurement Systems

This new and general method here called overflow current switching allows a fast, continuous, and smooth transition between scales in wide-range current measurement systems, like electrometers. This is achieved, using a hydraulic analogy, by diverting only the overflow current, such that no slow element is forced to change its state during the switching. As a result, this approach practically eliminates the long dead time in low-current (picoamperes) switching. Similar to a logarithmic scale, a composition of n adjacent linear scales, like a segmented ruler, measures the current. The use of a linear wide-range system based on this technique assures fast and continuous measurement in the entire range, without blind regions during transitions and still holding suitable accuracy for many applications. A full mathematical development of the method is given. Several computer realistic simulations demonstrated the viability of the technique.

Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e. g., fractional Brownian motion, Levy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation sigma t which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

Switching the mode of sucrose utilization by Saccharomyces cerevisiae

Abstract Background Overflow metabolism is an undesirable characteristic of aerobic cultures of Saccharomyces cerevisiae during biomass-directed processes. It results from elevated sugar consumption rates that cause a high substrate conversion to ethanol and other bi-products, severely affecting cell physiology, bioprocess performance, and biomass yields. Fed-batch culture, where sucrose consumption rates are controlled by the external addition of sugar aiming at its low concentrations in the fermentor, is the classical bioprocessing alternative to prevent sugar fermentation by yeasts. However, fed-batch fermentations present drawbacks that could be overcome by simpler batch cultures at relatively high (e.g. 20 g/L) initial sugar concentrations. In this study, a S. cerevisiae strain lacking invertase activity was engineered to transport sucrose into the cells through a low-affinity and low-capacity sucrose-H+ symport activity, and the growth kinetics and biomass yields on sucrose analyzed using simple batch cultures. Results We have deleted from the genome of a S. cerevisiae strain lacking invertase the high-affinity sucrose-H+ symporter encoded by the AGT1 gene. This strain could still grow efficiently on sucrose due to a low-affinity and low-capacity sucrose-H+ symport activity mediated by the MALx1 maltose permeases, and its further intracellular hydrolysis by cytoplasmic maltases. Although sucrose consumption by this engineered yeast strain was slower than with the parental yeast strain, the cells grew efficiently on sucrose due to an increased respiration of the carbon source. Consequently, this engineered yeast strain produced less ethanol and 1.5 to 2 times more biomass when cultivated in simple batch mode using 20 g/L sucrose as the carbon source. Conclusion Higher cell densities during batch cultures on 20 g/L sucrose were achieved by using a S. cerevisiae strain engineered in the sucrose uptake system. Such result was accomplished by effectively reducing sucrose uptake by the yeast cells, avoiding overflow metabolism, with the concomitant reduction in ethanol production. The use of this modified yeast strain in simpler batch culture mode can be a viable option to more complicated traditional sucrose-limited fed-batch cultures for biomass-directed processes of S. cerevisiae.

Amplificatori Switching (ad alto rendimento)

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Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

High-performance switching architectures for optical networks

The need for high bandwidth, due to the explosion of new multi\-media-oriented IP-based services, as well as increasing broadband access requirements is leading to the need of flexible and highly reconfigurable optical networks. While transmission bandwidth does not represent a limit due to the huge bandwidth provided by optical fibers and Dense Wavelength Division Multiplexing (DWDM) technology, the electronic switching nodes in the core of the network represent the bottleneck in terms of speed and capacity for the overall network. For this reason DWDM technology must be exploited not only for data transport but also for switching operations. In this Ph.D. thesis solutions for photonic packet switches, a flexible alternative with respect to circuit-switched optical networks are proposed. In particular solutions based on devices and components that are expected to mature in the near future are proposed, with the aim to limit the employment of complex components. The work presented here is the result of part of the research activities performed by the Networks Research Group at the Department of Electronics, Computer Science and Systems (DEIS) of the University of Bologna, Italy. In particular, the work on optical packet switching has been carried on within three relevant research projects: the e-Photon/ONe and e-Photon/ONe+ projects, funded by the European Union in the Sixth Framework Programme, and the national project OSATE funded by the Italian Ministry of Education, University and Scientific Research. The rest of the work is organized as follows. Chapter 1 gives a brief introduction to network context and contention resolution in photonic packet switches. Chapter 2 presents different strategies for contention resolution in wavelength domain. Chapter 3 illustrates a possible implementation of one of the schemes proposed in chapter 2. Then, chapter 4 presents multi-fiber switches, which employ jointly wavelength and space domains to solve contention. Chapter 5 shows buffered switches, to solve contention in time domain besides wavelength domain. Finally chapter 6 presents a cost model to compare different switch architectures in terms of cost.

Internal Model Principle: extension to the switching case and applications

This thesis deals with a novel control approach based on the extension of the well-known Internal Model Principle to the case of periodic switched linear exosystems. This extension, inspired by power electronics applications, aims to provide an effective design method to robustly achieve the asymptotic tracking of periodic references with an infinite number of harmonics. In the first part of the thesis the basic components of the novel control scheme are described and preliminary results on stabilization are provided. In the second part, advanced control methods for two applications coming from the world high energy physics are presented.

Un algoritmo di visione artificiale per l'individuazione dello switching point nel processo di etichettatura markerless

La tesi descrive il progetto e il funzionamento di un algoritmo basato su un sistema di visione, studiato allo scopo di eliminare i marker, che vengono utilizzati dai sensori di contrasto nel processo di taglio delle singole etichette a partire dalle bobine che scorrono sul rullo.

Designed functional defects in colloidal photonic crystals: switching, biomonitoring and modified photoluminescence

Es werden zwei komplementäre "bottom-up" Methoden präsentiert, die den kontrollierten Einbau von "intelligenten" planaren Defekten in selbstorganisierte kolloidale photonische Kristalle (KPKs) ermöglichen. Die Defektschicht basiert auf einem funktionellen, nanometer-skalierten dünnen Film, der entweder durch schichtweise ("layer-by-layer") Selbstorganisation und Mikrokontakttransferübertragung oder durch Aufschleudern und einer KPK-Opferfüllung hergestellt wird. Die entwickelten Techniken gestatten die Integration von maßgeschneiderten dünnen Defektfilmen bestehend aus einer enorm großen Vielfalt an Materialien; sie sind kostengünstig und können im größeren Maßstab angewendet werden. Optische Untersuchungen zeigen einen engen, durch den Defekt hervorgerufenen Transmissionszustand in der photonischen Bandlücke. Die Defektwellenlänge hängt von der optischen Dicke der Defektschicht ab. Aktives Schalten der Defektwellenlänge wird erreicht, indem Defektschichten aus Makromolekülen hergestellt werden, die über externe Erreger wie Licht, Temperatur, Redoxzyklen und mechanischen Druck adressiert werden können. Die Ergebnisse der Untersuchungen sind im Einklang mit separat durchgeführten Ellipsometrie-Messungen und theoretischen "scalar wave approximation"-Berechnungen. Darüber hinaus werden KPKs mit funktionellen biomolekularen Defekten vorgestellt. Über Verschiebungen der Defektmode können DNA-Konformationsänderungen, die enantioselektive Einlagerung eines chiralen Antitumormedikaments sowie Enzymaktivitäten optisch beobachtet werden. Die Einlagerung von fluoreszierenden Farbstoffen und Quantenpunkten in Defekt-KPKs führt zu einer eindeutigen, durch die photonische Bandlücke und den Defektzustand hervorgerufenen Modifizierung der Photolumineszenz (PL)-Spektren. Schaltbare PL-Modifizierungen werden detektiert, wenn adressierbare Defekt-KPKs verwendet werden.