Random Lens Imaging

We call a random lens one for which the function relating the input light ray to the output sensor location is pseudo-random. Imaging systems with random lensescan expand the space of possible camera designs, allowing new trade-offs in optical design and potentially adding new imaging capabilities. Machine learningmethods are critical for both camera calibration and image reconstruction from the sensor data. We develop the theory and compare two different methods for calibration and reconstruction: an MAP approach, and basis pursuit from compressive sensing. We show proof-of-concept experimental results from a random lens made from a multi-faceted mirror, showing successful calibration and image reconstruction. We illustrate the potential for super-resolution and 3D imaging

Tiny images

The human visual system is remarkably tolerant to degradations in image resolution: in a scene recognition task, human performance is similar whether $32 \times 32$ color images or multi-mega pixel images are used. With small images, even object recognition and segmentation is performed robustly by the visual system, despite the object being unrecognizable in isolation. Motivated by these observations, we explore the space of 32x32 images using a database of 10^8 32x32 color images gathered from the Internet using image search engines. Each image is loosely labeled with one of the 70,399 non-abstract nouns in English, as listed in the Wordnet lexical database. Hence the image database represents a dense sampling of all object categories and scenes. With this dataset, we use nearest neighbor methods to perform objectrecognition across the 10^8 images

Molecular antimicrobial resistance surveillance for neisseria gonorrhoeae, Northern Territory, Australia

Neisseria gonorrhoeae antimicrobial resistance (AMR) is a globally recognized health threat; new strategies are needed to enhance AMR surveillance. The Northern Territory of Australia is unique in that 2 different first-line therapies, based primarily on geographic location, are used for gonorrhea treatment. We tested 1,629 N. gonorrhoeae nucleic acid amplification test–positive clinical samples, collected from regions where ceftriaxone plus azithromycin or amoxicillin plus azithromycin are recommended first-line treatments, by using 8 N. gonorrhoeae AMR PCR assays. We compared results with those from routine culture-based surveillance data. PCR data confirmed an absence of ceftriaxone resistance and a low level of azithromycin resistance (0.2%), and that penicillin resistance was \u3c5% in amoxicillin plus azithromycin regions. Rates of ciprofloxacin resistance and penicillinase-producing N. gonorrhoeae were lower when molecular methods were used. Molecular methods to detect N. gonorrhoeae AMR can increase the evidence base for treatment guidelines, particularly in settings where culture-based surveillance is limited

Improving technology transfer through national systems of innovation: climate relevant innovation-system builders (CRIBs)

The Technology Executive Committee (TEC) of the United Nations Framework Convention on Climate Change (UNFCCC) recently convened a workshop seeking to understand how strengthening national systems of innovation (NSIs) might help to foster the transfer of climate technologies to developing countries. This article reviews insights from the literatures on Innovation Studies and Socio-Technical Transitions to demonstrate why this focus on fostering innovation systems has potential to be more transformative as an international policy mechanism for climate technology transfer than anything the UNFCCC has considered to date. Based on insights from empirical research, the article also articulates how the existing architecture of the UNFCCC Technology Mechanism could be usefully extended by supporting the establishment of CRIBs (climate relevant innovation-system builders) in developing countries – key institutions focused on nurturing the climate-relevant innovation systems and building technological capabilities that form the bedrock of transformative, climate-compatible technological change and development

The K2-HERMES Survey: Age and Metallicity of the Thick Disc

Asteroseismology is a promising tool to study Galactic structure and evolution because it can probe the ages of stars. Earlier attempts comparing seismic data from the {\it Kepler} satellite with predictions from Galaxy models found that the models predicted more low-mass stars compared to the observed distribution of masses. It was unclear if the mismatch was due to inaccuracies in the Galactic models, or the unknown aspects of the selection function of the stars. Using new data from the K2 mission, which has a well-defined selection function, we find that an old metal-poor thick disc, as used in previous Galactic models, is incompatible with the asteroseismic information. We show that spectroscopic measurements of [Fe/H] and [$\alpha$/Fe] elemental abundances from the GALAH survey indicate a mean metallicity of $\log (Z/Z_{\odot})=-0.16$ for the thick disc. Here $Z$ is the effective solar-scaled metallicity, which is a function of [Fe/H] and [$\alpha$/Fe]. With the revised disc metallicities, for the first time, the theoretically predicted distribution of seismic masses show excellent agreement with the observed distribution of masses. This provides an indirect verification of the asteroseismic mass scaling relation is good to within five percent. Using an importance-sampling framework that takes the selection function into account, we fit a population synthesis model of the Galaxy to the observed seismic and spectroscopic data. Assuming the asteroseismic scaling relations are correct, we estimate the mean age of the thick disc to be about 10 Gyr, in agreement with the traditional idea of an old $\alpha$-enhanced thick disc.Comment: 21 pages, submitted to MNRA

Cumulant Methods and Short Time Propagators

The present paper clarifies a number of issues concerning the general problem of constructing improved short time quantum mechanical propagators. Cumulant methods are shown to be a particularly convenient tool for this task. Numerical results comparing methods based on partial averaging and on gradient approaches are presented for simple model problems and for many particle quantum fluids

Science granting councils in Sub-Saharan Africa: trends and tensions

This article documents recent trends in science funding support in Sub-Saharan Africa (SSA). We analyse these trends at the SSA regional level alongside a summary of four case studies of science funding in four Science Granting Councils (SGCs) in East Africa. Our findings support the literature on science funding in SSA regarding low levels of funding, cross-country engagement, and the need for capacity building. However, we also find there are tensions among funding and policy actors around the perceived ways in which investment in science will benefit society. We argue that the narratives and logics of science funders and their roots in ‘Republic of Science’ vs. ‘Embedded Autonomy’ rationales for SGC activity must be more transparent to enable critical engagement with the ideas being used to justify spending

Partial Averaging Approach to Fourier Coefficient Path Integration

The recently introduced method of partial averaging is developed in a general formalism for computing simple Cartesian path integrals. Examples of its application to both harmonic and anharmonic systems are given. For harmonic systems, where analytical results can be derived, both imaginary and complex time evolution is discussed. For two representative anharmonic systems, Monte Carlo path integral simulations of the imaginary time propagator (statistical density matrix) are presented. Connections with other Cartesian path integral techniques are stressed