Data-driven Optimization for Drone Delivery Service Planning with Online Demand

In this study, we develop an innovative data-driven optimization approach to solve the drone delivery service planning problem with online demand. Drone-based logistics are expected to improve operations by enhancing flexibility and reducing congestion effects induced by last-mile deliveries. With rising digitalization and urbanization, however, logistics service providers are constantly grappling with the challenge of uncertain real-time demand. This study investigates the problem of planning drone delivery service through an urban air traffic network to fulfil online and stochastic demand. Customer requests, if accepted, generate profit and are serviced by individual drone flights as per request origins, destinations and time windows. We cast this stochastic optimization problem as a Markov decision process. We present a novel data-driven optimization approach which generates predictive prescriptions of parameters of a surrogate optimization formulation. Our solution method consists of synthesizing training data via lookahead simulations to train a supervised machine learning model for predicting relative link priority based on the state of the network. This knowledge is then leveraged to selectively create weighted reserve capacity in the network and via a surrogate objective function that controls the trade-off between reserve capacity and profit maximization to maximize the cumulative profit earned. Using numerical experiments based on benchmarking transportation networks, the resulting data-driven optimization policy is shown to outperform a myopic policy. Sensitivity analyses on learning parameters reveal insights into the design of efficient policies for drone delivery service planning with online demand

Assessing the number of users who are excluded by domestic heating controls

This is the pre-print version of the Article. This Article is also referred to as: "Assessing the 'Design Exclusion' of Heating Controls at a Low-Cost, Low-Carbon Housing Development". - Copyright @ 2011 Taylor & FrancisSpace heating accounts for almost 60% of the energy delivered to housing which in turn accounts for nearly 27% of the total UK's carbon emissions. This study was conducted to investigate the influence of heating control design on the degree of ‘user exclusion’. This was calculated using the Design Exclusion Calculator, developed by the Engineering Design Centre at the University of Cambridge. To elucidate the capability requirements of the system, a detailed hierarchical task analysis was produced, due to the complexity of the overall task. The Exclusion Calculation found that the current design placed excessive demands upon the capabilities of at least 9.5% of the UK population over 16 years old, particularly in terms of ‘vision’, ‘thinking’ and ‘dexterity’ requirements. This increased to 20.7% for users over 60 years old. The method does not account for the level of numeracy and literacy and so the true exclusion may be higher. Usability testing was conducted to help validate the results which indicated that 66% of users at a low-carbon housing development could not programme their controls as desired. Therefore, more detailed analysis of the cognitive demands placed upon the users is required to understand where problems within the programming process occur. Further research focusing on this cognitive interaction will work towards a solution that may allow users to behave easily in a more sustainable manner

A Predictive Spatial Model to Quantify the Risk of Air-Travel-Associated Dengue Importation into the United States and Europe

The number of travel-acquired dengue infections has been on a constant rise in the United States and Europe over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue contributes to the increasing number of dengue cases. This paper reports results from a network-based regression model which uses international passenger travel volumes, travel distances, predictive species distribution models (for the vector species), and infection data to quantify the relative risk of importing travel-acquired dengue infections into the US and Europe from dengue-endemic regions. Given the necessary data, this model can be used to identify optimal locations (origin cities, destination airports, etc.) for dengue surveillance. The model can be extended to other geographical regions and vector-borne diseases, as well as other network-based processes

Dive, food and exercise effects on blood microparticles in Steller sea lions (Eumetopias jubatus) : exploring a biomarker for decompression sickness

Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of American Physiological Society for personal use, not for redistribution. The definitive version was published in American Journal of Physiology - Regulatory, Integrative and Comparative Physiology 310 (2016): R596-R601, doi:10.1152/ajpregu.00512.2015.Recent studies of stranded marine mammals indicate that exposure to underwater military sonar may induce pathophysiological responses consistent with decompression sickness (DCS). However, DCS has been difficult to diagnose in marine mammals. We investigated whether blood microparticles (MPs, measured as number/μl plasma), which increase in response to decompression stress in terrestrial mammals, are a suitable biomarker for DCS in marine mammals. We obtained blood samples from trained Steller sea lions (Eumetopias jubatus, 4 adult females) wearing time-depth recorders that dove to predetermined depths (either 5 or 50 m). We hypothesized that MPs would be positively related to decompression stress (depth and duration underwater). We also tested the effect of feeding and exercise in isolation on MPs using the same blood sampling protocol. We found that feeding and exercise had no effect on blood MP levels, but that diving caused MPs to increase. However, blood MP levels did not correlate with diving depth, relative time underwater, and presumably decompression stress―possibly indicating acclimation following repeated exposure to depth.Funding for this project was provided by the Office of Naval Research to MM (ONR Award # N00014-12-10388) and SRT (ONR Award # N00014-13-10614). Additional support was provided by the National Oceanic and Atmospheric Administration through the North Pacific Marine Science Foundation and the North Pacific Universities Marine Mammal Research Consortium.2017-02-0

Toward an Understanding of the Role of the Environment in the Development of Early Callous Behavior

Key to understanding the long‐term impact of social inequalities is identifying early behaviors that may signal higher risk for later poor psychosocial outcomes, such as psychopathology. A set of early‐emerging characteristics that may signal risk for later externalizing psychopathology is callous‐unemotional (CU) behavior. CU behavior predicts severe and chronic trajectories of externalizing behaviors in youth. However, much research on CU behavior has focused on late childhood and adolescence, with little attention paid to early childhood when preventative interventions may be most effective. In this article, we summarize our recent work showing that (a) CU behavior can be identified in early childhood using items from common behavior checklists, (b) CU behavior predicts worse outcomes across early childhood, (c) CU behavior exhibits a nomological network distinct from other early externalizing behaviors, and (d) malleable environmental factors, particularly parenting, may play a role in the development of early CU behaviors. We discuss the challenges of studying contextual contributors to the development of CU behavior in terms of gene–environment correlations and present initial results from work examining CU behavior in an adoption study in which gene–environment correlations are examined in early childhood. We find that parenting is a predictor of early CU behavior even in a sample in which parents are not genetically related to the children.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/136006/1/jopy12221_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136006/2/jopy12221.pd

Striking a Chord: Dementia and Song

We have co-written this piece to relay what can be achieved with song and music in familial and non-familial settings when caring for a person with dementia. This article started as a conversation we had in the Wellcome Collection cafe in London to catch up with each other while Prabhjot was en route from Canada to India, to meet her father. We shared how dementia was becoming a part of our parents’ lives. This article is dedicated to the chords Prabhjot Parmar has struck with her father, Major Harbhajan Singh (25 Dec 1925 – 16 April 2018) and Nirmal Puwar has had the pleasure of sharing with her mother, Kartar Kaur. Both of us have been drawn to understanding how our own performance of song with our respective parent enabled them and us to maintain a register of connection. Song became a means of trying to keep striking a parental and musical chord. We aimed to connect by engendering ‘therapeutic atmospheres’ (Sonntag 2016) through song. We use song and music interchangeably, operating with performance as an umbrella term that includes gesture, utterance, dance, singing and playing musical instruments, for example. Two autoethnographic relational contributions provide a substantive basis to our article, each written by a researcher-carer-daughter, seeking to sustain contact with what remains in her parent living with dementia