New Zealand’s Production Structure: An International Comparison

The purpose of this paper is to compare New Zealand’s production structure in the mid-1990s to that in other OECD countries using input output analysis. Comparable inter industry transactions tables to the New Zealand data are available for Australia, Belgium, Denmark, Finland, Germany, Norway and the United Kingdom. The composition of total supply and value added is examined across countries. Backward and forward linkages, indices of industry interconnectedness, a value added production multiplier, a cumulated primary input coefficient for compensation of employees and a measure of import content of final demand output are calculated, taking into account direct and indirect transactions. New Zealand’s industrial structure is broadly similar to that in other OECD countries. Some differences arise as certain industries are more important in some countries. New Zealand’s exports appear to be more diversified and have a large value added content. Moreover, the return to capital, as measured by the share of gross operating surplus in value added, is high.Input output models; industry importance; production structure; inter industry dependencies; country comparisons

An analysis of the Supramolecular NanoStamping technology for its market potential based upon a review of DNA microarray intellectual property

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2006.Includes bibliographical references (leaf 38).Supramolecular NanoStamping is a novel printing method for exploiting the supramolecular interactions between organic and biological molecules. This technology is advantageous because of the ability to transfer a massive amount of chemical and spatial information, its high resolution, the growth of masters used multiple times and the versatility of initial master fabrication. The technology may be used to make DNA microarrays which are an essential tool to genomic research assisting in gene expression and genotyping. This paper explores the potential of bring Supramolecular NanoStamping technology to the microarray market. An in depth analysis of the current patent landscape of DNA microarrays is conducted to recognize the various competitors and the coverage of their patents. In addition, a better understanding of the landscape was achieved by assessing the major litigation that has occurred in the field. By engaging in a thorough intellectual property analysis, the commercialization potential of Supramolecular NanoStamping technology was realized through a licensing model.by Kathy H. Li.M.Eng

Mosquito detection with low-cost smartphones: data acquisition for malaria research

Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year. Not only is the prevention of mosquito bites of paramount importance to the reduction of malaria transmission cases, but understanding in more forensic detail the interplay between malaria, mosquito vectors, vegetation, standing water and human populations is crucial to the deployment of more effective interventions. Typically the presence and detection of malaria-vectoring mosquitoes is only quantified by hand-operated insect traps or signified by the diagnosis of malaria. If we are to gather timely, large-scale data to improve this situation, we need to automate the process of mosquito detection and classification as much as possible. In this paper, we present a candidate mobile sensing system that acts as both a portable early warning device and an automatic acoustic data acquisition pipeline to help fuel scientific inquiry and policy. The machine learning algorithm that powers the mobile system achieves excellent off-line multi-species detection performance while remaining computationally efficient. Further, we have conducted preliminary live mosquito detection tests using low-cost mobile phones and achieved promising results. The deployment of this system for field usage in Southeast Asia and Africa is planned in the near future. In order to accelerate processing of field recordings and labelling of collected data, we employ a citizen science platform in conjunction with automated methods, the former implemented using the Zooniverse platform, allowing crowdsourcing on a grand scale.Comment: Presented at NIPS 2017 Workshop on Machine Learning for the Developing Worl

Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data

The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual tracking mobile apps become more widely adopted, they provide an increasingly large, content-rich source of menstrual health experiences and behaviors over time. By exploring a database of user-tracked observations from the Clue app by BioWink of over 378,000 users and 4.9 million natural cycles, we show that self-reported menstrual tracker data can reveal statistically significant relationships between per-person cycle length variability and self-reported qualitative symptoms. A concern for self-tracked data is that they reflect not only physiological behaviors, but also the engagement dynamics of app users. To mitigate such potential artifacts, we develop a procedure to exclude cycles lacking user engagement, thereby allowing us to better distinguish true menstrual patterns from tracking anomalies. We uncover that women located at different ends of the menstrual variability spectrum, based on the consistency of their cycle length statistics, exhibit statistically significant differences in their cycle characteristics and symptom tracking patterns. We also find that cycle and period length statistics are stationary over the app usage timeline across the variability spectrum. The symptoms that we identify as showing statistically significant association with timing data can be useful to clinicians and users for predicting cycle variability from symptoms or as potential health indicators for conditions like endometriosis. Our findings showcase the potential of longitudinal, high-resolution self-tracked data to improve understanding of menstruation and women's health as a whole.Comment: The Supplementary Information for this work, as well as the code required for data pre-processing and producing results is available in https://github.com/iurteaga/menstrual_cycle_analysi

CURVE SPRINTING KINEMATICS EXHIBITED BY ATHLETES USING A SINGLE, TRANS-TIBIAL PROSTHESIS

The purpose of our study was to determine whether kinematics exhibited during the curve section of a 200 m sprint are influenced by ‘limb type’ (prosthetic vs nonprosthetic limb) or ‘prosthetic limb side’ (‘inside’ compared to the ‘outside’ of the curve). Two video cameras (60 Hz) were used to capture 13 male athletes using a single, trans-tibial prosthesis during an international, 200 m T-44 competition. From mixed-model ANOVA (p < .05), prosthetic and nonprosthetic limb kinematics were different, but differences were dependent on the prosthetic limb side. The inside versus outside prosthetic limb may be affected more due to the rotational influences that affect the inside and outside foot differently. Therefore, athletes whose prosthetic limb was on the inside may be at a disadvantage compared to those with an outside prosthetic limb