Evaluating search and matching models using experimental data

This paper introduces an innovative test of search and matching models using the exogenous variation available in experimental data. We take an off-the-shelf Pissarides matching model and calibrate it to data on the control group from a randomized social experiment. We then simulate a program group from a randomized experiment within the model. As a measure of the performance of the model, we compare the outcomes of the program groups from the model and from the randomized experiment. We illustrate our methodology using the Canadian Self-Sufficiency Project (SSP), a social experiment providing a time limited earnings supplement for Income Assistance recipients who obtain full time employment within a 12 month period. We find two features of the model are consistent with the experimental results: endogenous search intensity and exogenous job destruction. We find mixed evidence in support of the assumption of fixed hours of labor supply. Finally, we find a constant job destruction rate is not consistent with the experimental data in this context

Attributes and action recognition based on convolutional neural networks and spatial pyramid VLAD encoding

© Springer International Publishing AG 2017.Determination of human attributes and recognition of actions in still images are two related and challenging tasks in computer vision, which often appear in fine-grained domains where the distinctions between the different categories are very small. Deep Convolutional Neural Network (CNN) models have demonstrated their remarkable representational learning capability through various examples. However, the successes are very limited for attributes and action recognition as the potential of CNNs to acquire both of the global and local information of an image remains largely unexplored. This paper proposes to tackle the problem with an encoding of a spatial pyramid Vector of Locally Aggregated Descriptors (VLAD) on top of CNN features. With region proposals generated by Edgeboxes, a compact and efficient representation of an image is thus produced for subsequent prediction of attributes and classification of actions. The proposed scheme is validated with competitive results on two benchmark datasets: 90.4% mean Average Precision (mAP) on the Berkeley Attributes of People dataset and 88.5% mAP on the Stanford 40 action dataset

Wearable EEG: what is it, why is it needed and what does it entail?

Published versio

Decreased dopamine activity predicts relapse in methamphetamine abusers.

Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [(11)C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes

Connected OFCity Challenge: Addressing the Digital Divide in the Developing World

Over the past 50 years, the development of information and communications technology has provided unprecedented support to the steady economic growth of developed countries. In recent years, some of the largest growth has been reported in emerging economies, which, however, often lack adequate telecommunications infrastructure to further sustain their development. Although a number of service providers and system vendors have started to address the issue, the challenges they encounter are substantially different from those in the developed world, including an unreliable electricity grid, poor fiber infrastructure, low revenue expectations, and often a harsh climate environment. This paper reports use cases and solutions pertinent to the development of the networking infrastructure in emerging economies, provided by organizations directly involved in such activities. After providing some background information on the current state of network infrastructure and the main challenges for Africa and rural China, the paper provides details on two proposed solutions. The first focuses on the provisioning of services and network infrastructure through the development of low-cost data centers, whereas the second proposes cost-effective adaptation of both fiber and hybrid copper-fiber technology to rural areas. The article is concluded with a brief discussion on the complementarity of the two approaches

The James Clerk Maxwell telescope dense gas survey of the Perseus molecular cloud

This is the final version of the article. Available from the publisher via the DOI in this record.We present the results of a large-scale survey of the very dense (n > 106 cm-3) gas in the Perseus molecular cloud using HCO+ and HCN (J = 4 → 3) transitions. We have used this emission to trace the structure and kinematics of gas found in pre- and protostellar cores, as well as in outflows. We compare the HCO+/HCN data, highlighting regions where there is a marked discrepancy in the spectra of the two emission lines. We use the HCO+ to identify positively protostellar outflows and their driving sources, and present a statistical analysis of the outflow properties that we derive from this tracer. We find that the relations we calculate between the HCO+ outflow driving force and the Menv and Lbol of the driving source are comparable to those obtained from similar outflow analyses using 12CO, indicating that the two molecules give reliable estimates of outflow properties. We also compare the HCO+ and the HCN in the outflows, and find that the HCN traces only the most energetic outflows, the majority of which are driven by young Class 0 sources. We analyse the abundances of HCN and HCO+ in the particular case of the IRAS 2A outflows, and find that the HCN is much more enhanced than the HCO+ in the outflow lobes. We suggest that this is indicative of shock enhancement of HCN along the length of the outflow; this process is not so evident for HCO+, which is largely confined to the outflow base. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.SLW-S and JH are funded by the Science and Technology Facilities Council of the UK. The James Clerk Maxwell Telescope is operated by the Joint Astronomy Centre on behalf of the Science and Technology Facilities Council of the United Kingdom, the National Research Council of Canada and (until 2013 March 31) the Netherlands Organisation for Scientific Researc

Eta Carinae and the Luminous Blue Variables

We evaluate the place of Eta Carinae amongst the class of luminous blue variables (LBVs) and show that the LBV phenomenon is not restricted to extremely luminous objects like Eta Car, but extends luminosities as low as log(L/Lsun) = 5.4 - corresponding to initial masses ~25 Msun, and final masses as low as ~10-15 Msun. We present a census of S Doradus variability, and discuss basic LBV properties, their mass-loss behaviour, and whether at maximum light they form pseudo-photospheres. We argue that those objects that exhibit giant Eta Car-type eruptions are most likely related to the more common type of S Doradus variability. Alternative atmospheric models as well as sub-photospheric models for the instability are presented, but the true nature of the LBV phenomenon remains as yet elusive. We end with a discussion on the evolutionary status of LBVs - highlighting recent indications that some LBVs may be in a direct pre-supernova state, in contradiction to the standard paradigm for massive star evolution.Comment: 27 pages, 6 figures, Review Chapter in "Eta Carinae and the supernova imposters" (eds R. Humphreys and K. Davidson) new version submitted to Springe

Importance of food-demand management for climate mitigation

Recent studies show that current trends in yield improvement will not be sufficient to meet projected global food demand in 2050, and suggest that a further expansion of agricultural area will be required. However, agriculture is the main driver of losses of biodiversity and a major contributor to climate change and pollution, and so further expansion is undesirable. The usual proposed alternative - intensification with increased resource use - also has negative effects. It is therefore imperative to find ways to achieve global food security without expanding crop or pastureland and without increasing greenhouse gas emissions. Some authors have emphasised a role for sustainable intensification in closing global 'yield gaps' between the currently realised and potentially achievable yields. However, in this paper we use a transparent, data-driven model, to show that even if yield gaps are closed, the projected demand will drive further agricultural expansion. There are, however, options for reduction on the demand side that are rarely considered. In the second part of this paper we quantify the potential for demand-side mitigation options, and show that improved diets and decreases in food waste are essential to deliver emissions reductions, and to provide global food security in 2050.This work was funded by a grant to the University of Cambridge from BP as part of their Energy Sustainability Challenge.This is the accepted manuscript version. The final version is available from Nature Climate Change at http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2353.html