Forecasting with vector autoregressive models of data vintages: US output growth and inflation

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.

Evidence that nematodes may vector the soft rot-causing enterobacterial phytopathogens

Bacterial soft rot is a globally significant plant disease that causes major losses in the production of many popular crops, such as potato. Little is known about the dispersal and ecology of soft-rot enterobacteria, and few animals have been identified as vectors for these pathogens. This study investigates whether soil-living and bacterial-feeding nematodes could act as vectors for the dispersal of soft-rot enterobacteria to plants. Soft-rot enterobacteria associated with nematodes were quantified and visualized through bacterial enumeration, GFP-tagging, and confocal and electron scanning microscopy. Soft-rot enterobacteria were able to withstand nematode grazing, colonize the gut of Caenorhabditis elegans and subsequently disperse to plant material while remaining virulent. Two nematode species were also isolated from a rotten potato sample obtained from a potato storage facility in Finland. Furthermore, one of these isolates (Pristionchus sp. FIN-1) was shown to be able to disperse soft-rot enterobacteria to plant material. The interaction of nematodes and soft-rot enterobacteria seems to be more mutualistic rather than pathogenic, but more research is needed to explain how soft-rot enterobacteria remain viable inside nematodes.

The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

Gender, race, and heterogeneous effects of epidemic malaria on human capital and income

This article investigates the impact of exposure to a serious, unusual, and unforeseen malaria epidemic in northeast Brazil in 1938–40 on subsequent human capital attainment and income. Arguing the event was exogenous, the article exploits cohort and regional heterogeneity in exposure to identify effects. Results are consistent with differential mortality rates according to gender and socioeconomic status, such that heterogeneous selection and scarring effects are observed. Analyzing by gender alone, positive (selection) effects are found for men, and mixed (positive and negative) effects for women. Allowing for heterogeneity by race, selection effects persist for men. In contrast, positive (selection) effects are observed for nonwhite women, and negative (scarring) effects for white women. Results contribute to evidence suggesting that exposure to negative environmental shocks affects human capital attainment, while also suggesting it heterogeneously affects cohort composition.

Quinine, mosquitoes and empire: reassembling malaria in British India, 1890-1910

The drug quinine figured as an object of enforced consumption in British India between the late 1890s and the 1910s, when the corresponding diagnostic category malaria itself was redefined as a mosquito-borne fever disease. This article details an overlapping milieu in which quinine, mosquitoes and malaria emerged as intrinsic components of shared and symbiotic histories. It combines insights from new imperial histories, constructivism in the histories of medicine and literature about non-humans in science studies to examine the ways in which histories of insects, drugs, disease and empire interacted and shaped one another. Firstly, it locates the production of historical intimacies between quinine, malaria and mosquitoes within the exigencies and apparatuses of imperial rule. In so doing, it explores the intersections between the worlds of colonial governance, medical knowledge, vernacular markets and pharmaceutical business. Secondly, it outlines ways to narrate characteristics and enabling properties of non-humans (such as quinines and mosquitoes) while retaining a constructivist critique of scientism and empire. Thirdly, it shows how empire itself was reshaped and reinforced while occasioning the proliferation of categories and entities like malaria, quinine and mosquitoes.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.