Higher rates of prebreeding condition gain positively impacts clutch size: A mechanistic test of the condition-dependent individual optimization model

A combination of timing of and body condition (i.e., mass) at arrival on the breeding grounds interact to influence the optimal combination of the timing of reproduction and clutch size in migratory species. This relationship has been formalized by Rowe et al. in a condition-dependent individual optimization model (American Naturalist, 1994, 143, 689-722), which has been empirically tested and validated in avian species with a capital-based breeding strategy. This model makes a key, but currently untested prediction; that variation in the rate of body condition gain will shift the optimal combination of laying date and clutch size. This prediction is essential because it implies that individuals can compensate for the challenges associated with late timing of arrival or poor body condition at arrival on the breeding grounds through adjustment of their life history investment decisions, in an attempt to maximize fitness. Using an 11-year data set in arctic-nesting common eiders (Somateria mollissima), quantification of fattening rates using plasma triglycerides (an energetic metabolite), and a path analysis approach, we test this prediction of this optimization model; controlling for arrival date and body condition, females that fatten more quickly will adjust the optimal combination of lay date and clutch size, in favour of a larger clutch size. As predicted, females fattening at higher rates initiated clutches earlier and produced larger clutch sizes, indicating that fattening rate is an important factor in addition to arrival date and body condition in predicting individual variation in reproductive investment. However, there was no direct effect of fattening rate on clutch size (i.e., birds laying on the same date had similar clutch sizes, independent of their fattening rate). Instead, fattening rate indirectly affected clutch size via earlier lay dates, thus not supporting the original predictions of the optimization model. Our results demonstrate that variation in the rate of condition gain allows individuals to shift flexibly along the seasonal decline in clutch size to presumably optimize the combination of laying date and clutch size. A plain language summary is available for this article

Higher rates of prebreeding condition gain positively impacts clutch size: A mechanistic test of the condition-dependent individual optimization model

A combination of timing of and body condition (i.e., mass) at arrival on the breeding grounds interact to influence the optimal combination of the timing of reproduction and clutch size in migratory species. This relationship has been formalized by Rowe et al. in a condition-dependent individual optimization model (American Naturalist, 1994, 143, 689-722), which has been empirically tested and validated in avian species with a capital-based breeding strategy. This model makes a key, but currently untested prediction; that variation in the rate of body condition gain will shift the optimal combination of laying date and clutch size. This prediction is essential because it implies that individuals can compensate for the challenges associated with late timing of arrival or poor body condition at arrival on the breeding grounds through adjustment of their life history investment decisions, in an attempt to maximize fitness. Using an 11-year data set in arctic-nesting common eiders (Somateria mollissima), quantification of fattening rates using plasma triglycerides (an energetic metabolite), and a path analysis approach, we test this prediction of this optimization model; controlling for arrival date and body condition, females that fatten more quickly will adjust the optimal combination of lay date and clutch size, in favour of a larger clutch size. As predicted, females fattening at higher rates initiated clutches earlier and produced larger clutch sizes, indicating that fattening rate is an important factor in addition to arrival date and body condition in predicting individual variation in reproductive investment. However, there was no direct effect of fattening rate on clutch size (i.e., birds laying on the same date had similar clutch sizes, independent of their fattening rate). Instead, fattening rate indirectly affected clutch size via earlier lay dates, thus not supporting the original predictions of the optimization model. Our results demonstrate that variation in the rate of condition gain allows individuals to shift flexibly along the seasonal decline in clutch size to presumably optimize the combination of laying date and clutch size. A plain language summary is available for this article

Designing and Solving Location-Routing-Allocation Problems in a Sustainable Blood Supply Chain Network of Blood Transport in Uncertainty Conditions

Purpose: In this paper, a location-routing-allocation problem in a multi-objective blood supply chain network was designed to reduce the total cost of the supply chain network, the maximum unmet demand from distribution of goods, and decline greenhouse gas emissions due to the transport of goods among different levels of the network. The network levels considered for modeling include blood donation clusters, permanent and temporary blood transfusion centers, major laboratory centers and blood supply points. Other objectives included determining the optimal number and location of potential facilities, optimal allocation of the flow of goods between the selected facilities and determining the most suitable transport route to distribute the goods to customer areas in uncertainty conditions. Methodology: Given that the model was NP-hard, the NSGA II and MOPSO algorithms were used to solve the model with a priority-based solution. Findings: The results of the design of the experiments showed the high efficiency of the NSGA II algorithm in comparison with the MOPSO algorithm in finding efficient solutions. Originality/Value: This study addresses the issue of blood perishability from blood sampling to distribution to customer demand areas

Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable Hands-free Dynamic Walking

This manuscript presents control of a high-DOF fully actuated lower-limb exoskeleton for paraplegic individuals. The key novelty is the ability for the user to walk without the use of crutches or other external means of stabilization. We harness the power of modern optimization techniques and supervised machine learning to develop a smooth feedback control policy that provides robust velocity regulation and perturbation rejection. Preliminary evaluation of the stability and robustness of the proposed approach is demonstrated through the Gazebo simulation environment. In addition, preliminary experimental results with (complete) paraplegic individuals are included for the previous version of the controller.Comment: Submitted to IEEE Control System Magazine. This version addresses reviewers' concerns about the robustness of the algorithm and the motivation for using such exoskeleton

Optimization of two-photon excited fluorescence for volumetric imaging

Two-photon microscopy is often used in biological imaging due to its optical sectioning and depth penetration capabilities. These characteristics have made two-photon microscopy especially useful for neurobiological studies where imaging a volume at single cell resolution is typically required. This dissertation focuses on the optimization of two-photon excited fluorescence for volumetric imaging of biological samples, with special attention to imaging the mouse brain. Chapter 2 studies wavefront manipulation as a way of optimizing two-photon excited fluorescence. We show, through numerical simulations and experiments, that the magnitude of the two-photon fluorescence signal originating from cell-sized objects can be used as a metric of beam quality. We also show that the cranial window used in mouse experiment is a major source of aberrations, which can readily be represented in the Zernike basis. Finally, we implement a modal wavefront optimization scheme that optimizes the wavefront based entirely on the magnitude of the fluorescence. Along with this scheme, Zernike functions are found to be a useful basis for correcting aberrations encountered in mouse brain imaging while the Hadamard basis is found to be useful for scattering compensation. Corrections performed in mouse brain using Zernike functions are found to be valid over hundreds of microns, allowing a single correction to be applied to a whole volume. Finally, we show that the wavefront correction system can double as a wavefront encoding system for experiments that require custom point-spread-functions. Chapter 3 aims to significantly improve the volume imaging rate of two-photon microscopy. The imaging speed is improved by combining two-photon excitation with scanning confocally-aligned planar excitation microscopy (SCAPE). Numerical simulations, analytical arguments, and experiments reveal that the standard method of combining nano-joule pulses with 80 MHz repetition rates is inadequate for two-photon light-sheet excitation. We use numerical simulations and experiments to explore the possibility of achieving fast volumetric imaging using line and sheet excitation and find that the sheet excitation scheme is more promising. Given that two-photon excitation requires high photon-flux-densities near the focus, achieving high enough fluorescence has to be balanced with restrictions placed by saturation, photodamage, photobleaching and sample heating effects. Finally, we experimentally study light sheet excitation at various pulse repetition rates with femtosecond pulses and find that repetition rates near 100 kHz allow imaging of nonbiological samples of ~200x300x300 μm^3 volume at 20 volumes per second while balancing the above constraints. This work paves the way for achieving fast, volumetric two-photon imaging of the mouse brain

Optimal allocation of blood products

The high cost of collection and the short shelf life of apheresis platelets demand efficient inventory management to reduce outdates and shortages. Apheresis platelets are licensed for seven days, and blood centers are keen on knowing the consequences of various product collection and distribution strategies. To reduce outdates, inventory managers typically distribute the older units first, thereby following first-in first-out (FIFO) policy; however, hospital blood banks would prefer that the blood center issues out the freshest units first, equivalent to a last-in first-out (LIFO) policy. This study addresses the optimal distribution policy to achieve a desired outdate, shortage and average age of apheresis platelets. A comprehensive literature review was conducted on previous models studied to efficiently distribute blood products. However, most of the research on blood inventory management has been restricted to the hospital blood bank level in terms of ordering policies and inventory levels. This study takes the approach from the perspective of the inventory manager at the regional blood center. The inventory manager needs a reliable forecast of the quantity and timing of future blood supply (collection from donors) and blood demand from hospital blood banks to make an effective decision on blood inventory control. A forecasting method is used in this study to predict collection and demand for Single Donor Platelets (SDPs), and solves the blood inventory problem using a heuristic method and a Linear Programming (LP) with a rolling horizon method to find the near optimal issuing policy, the expected average age, outdate rate, and shortage rate of a blood product from the perspective of the blood center. It is concluded that regional blood centers can distribute with a ‘mixed’ FIFO/LIFO strategy and not significantly affect outdates or ability to cover shortages. For the LP model with a rolling horizon schedule, the inventory manager at the blood center would have to use forecast windows of five to achieve good issuing policies. A simulation study comparing the heuristic method and an LP-based with a rolling horizon method indicated that LP models with forecast windows of five and heuristics methods with a ‘mixed’ FIFO/LIFO strategy can be used to optimize this inventory problem

Using isotopic niche dynamics to predict resiliency to climate change in an Arctic seabird

Resource limitation drives fitness-related decisions and constrains the ability of organisms to invest in energetically demanding life history stages. Environmental factors (e.g., temperature) play an important role in affecting resource availability and quality which can downstream effect the ability of individuals to invest in energetically demanding life history stages, including reproduction. Human-induced climate change is generating increasingly variable environmental conditions, impacting the abundance and distribution of prey items and therefore the ability of individuals to successfully reproduce, and these effects are especially pronounced in the Arctic. However, it is currently unknown whether Arctic organisms possess the ability to adjust foraging decisions and prey selection to overcome newly emerging environmental constraints. Quantifying stable isotopes in the tissues of consumers provides a minimally invasive method of inferring foraging niche; however, has yet to be validated as a method of predicting population-level resiliency to climate change. Seabirds are a useful system to test these linkages in because they are wide-ranging, predominantly oceanic-based group, reliant on marine-based resources and they are often widely distributed across polar regions. Using common eiders (Somateria mollissima), an Arctic diving seabird, as a model organism, this thesis examines the linkages between environmental variation, isotopic variation in foraging niche, and breeding parameters, as a means of predicting the resiliency of Arctic seabirds to the effects of climate change. Using a long term data set from a focal breeding colony, I found significant inter-annual and inter-breeding stage variation in isotopes and isotopic niche. Although environmental cues only weakly predicted variation in isotopic niche, variation in isotopic niche was a key predictor of breeding probability. Given that variation in isotopic niche has fitness-related impacts, I then took a species-wide approach to assess inter-colony variation in isotopic niche by sampling 8 breeding colonies across the distribution of eiders. While common eiders are a generalist species overall, individual colonies had significantly different foraging strategies and levels of generalization. Taken together, these results suggest that common eiders are likely to be resilient in the face of climate change, but some colonies may be more at risk from the ongoing effects of climate change. This thesis provides the first steps towards developing a minimally invasive method for foraging flexibility as a means of assessing the resiliency of Arctic seabirds to climate change