Improving location prediction services for new users with probabilistic latent semantic analysis

Location prediction systems that attempt to determine the mobility patterns of individuals in their daily lives have become increasingly common in recent years. Approaches to this prediction task include eigenvalue decomposition [5], non-linear time series analysis of arrival times [10], and variable order Markov models [1]. However, these approachesall assume sufficient sets of training data. For new users, by definition, this data is typically not available, leading to poor predictive performance. Given that mobility is a highly personal behaviour, this represents a significant barrier to entry. Against this background, we present a novel framework to enhance prediction using information about the mobility habits of existing users. At the core of the framework is a hierarchical Bayesian model, a type of probabilistic semantic analysis [7], representing the intuition that the temporal features of the new user’s location habits are likely to be similar to those of an existing user in the system. We evaluate this framework on the real life location habits of 38 users in the Nokia Lausanne dataset, showing that accuracy is improved by 16%, relative to the state of the art, when predicting the next location of new users

Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries

In many developing countries, half the population lives in rural locations, where access to essentials such as school materials, mosquito nets, and medical supplies is restricted. We propose an alternative method of distribution (to standard road delivery) in which the existing mobility habits of a local population are leveraged to deliver aid, which raises two technical challenges in the areas optimisation and learning. For optimisation, a standard Markov decision process applied to this problem is intractable, so we provide an exact formulation that takes advantage of the periodicities in human location behaviour. To learn such behaviour models from sparse data (i.e., cell tower observations), we develop a Bayesian model of human mobility. Using real cell tower data of the mobility behaviour of 50,000 individuals in Ivory Coast, we find that our model outperforms the state of the art approaches in mobility prediction by at least 25% (in held-out data likelihood). Furthermore, when incorporating mobility prediction with our MDP approach, we find a 81.3% reduction in total delivery time versus routine planning that minimises just the number of participants in the solution path.Comment: Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013

Copy number analysis of the low-copy repeats at the primate NPHP1 locus by array comparative genomic hybridization

AbstractArray comparative genomic hybridization (aCGH) has been widely used to detect copy number variants (CNVs) in both research and clinical settings. A customizable aCGH platform may greatly facilitate copy number analyses in genomic regions with higher-order complexity, such as low-copy repeats (LCRs). Here we present the aCGH analyses focusing on the 45kb LCRs [1] at the NPHP1 region with diverse copy numbers in humans. Also, the interspecies aCGH analysis comparing human and nonhuman primates revealed dynamic copy number transitions of the human 45kb LCR orthologues during primate evolution and therefore shed light on the origin of complexity at this locus. The original aCGH data are available at GEO under GSE73962

Noradrenaline neuron degeneration contributes to motor impairments and development of L-DOPA-induced dyskinesia in a rat model of Parkinson's disease.

Parkinson's disease (PD) is characterized by progressive loss of dopaminergic (DA) neurons in the substantia nigra. However, studies of post-mortem PD brains have shown that not only DA neurons but also the noradrenergic (NA) neurons in the locus coeruleus degenerate, and that the NA neurodegeneration may be as profound, and also precede degeneration of the midbrain DA neurons. Previous studies in animal models of PD have suggested that loss of forebrain NA will add to the development of motor symptoms in animals with lesions of the nigrostriatal DA neurons, but the results obtained in rodents have been inconclusive due to the shortcomings of the toxin, DSP-4, used to lesion the NA projections. Here, we have developed an alternative double-lesion paradigm using injections of 6-OHDA into striatum in combination with intraventricular injections of a powerful NA immunotoxin, anti-DBH-Saporin, to eliminate the NA neurons in the locus coeruleus, and associated pontine nuclei. Animals with combined DA and NA lesions were more prone to develop L-DOPA-induced dyskinesia, even at low L-DOPA doses, and they performed significantly worse in tests of reflexive and skilled paw use, the stepping and staircase tests, compared to DA-only lesioned rats. Post-mortem analysis revealed that NA depletion did not affect the degree of DA depletion, or the loss of tyrosine hydroxylase-positive innervation in the striatum. Cell loss in the substantia nigra was similar in both single and double lesioned animals, showing that the worsening effect was not due to increased loss of nigral DA neurons. The results show that damage to brainstem NA neurons, contributes to the development of motor impairments and the appearance of L-DOPA-induced dyskinesia in 6-OHDA lesioned rats, and provide support for the view that the development of motor symptoms and dyskinetic side effects in PD patients reflects the combined loss of midbrain DA neurons and NA neurons

Quaking Aspen in the Residential-Wildland Interface: Elk Herbivory Hinders Forest Conservation

Quaking aspen (Populus tremuloides Michx.) forests are experiencing numerous impediments across North America. In the West, recent drought, fire suppression, insects, diseases, climate trends, inappropriate management, and ungulate herbivory are impacting these high biodiversity forests. Additionally, ecological tension zones are sometimes created where the above factors intermingle with jurisdictional boundaries. The public-private land interface may result in stress to natural areas where game species find refuge and plentiful forage at the expense of ecosystem function. We examined putative herbivore impacts to aspen forests at Wolf Creek Ranch (WCR), a large residential landscape in northern Utah. Forty-three ha-1 monitoring plots were established to measure a range of attributes summarizing location description, tree and vegetation condition, and herbivore presence. Additionally, we tested the ability of a stand-level visual rating system to represent more detailed field measures. Elk (Cervus elaphus L.) herbivory is currently having a strong effect on aspen in the study area, reducing many locations to single-layer aspen forests dominated by aging canopy trees. Regeneration (\u3c 2 m stems) is experiencing moderate-to-high browse and recruitment (2 - 6 m stems) are below replacement levels on approximately half of WCR\u27s aspen forests. The condition rating system represented significant trends in forest cover, canopy height, stand aspect, regeneration, recruitment, and tree mortality. Ordination of all plot and forest data found a strong negative relationship between elk presence and recruitment success. We make recommendations for addressing difficult herbivore-aspen interactions where publicly managed wildlife a present barriers to conservation of privately owned forest reserves

Motorized Beam Alignment of a Commercial X-ray Diffractometer

X-ray diffraction (XRD) is a powerful analysis method that allows researchers to noninvasively probe the crystalline structure of a material. This includes the ability to determine the crystalline phases present, quantify surface residual stresses, and measure the distribution of crystallographic orientations. The Structures and Materials Division at the NASA Glenn Research Center (GRC) heavily uses the on-site XRD lab to characterize advanced metal alloys, ceramics, and polymers. One of the x-ray diffractometers in the XRD lab (Bruker D8 Discover) uses three different x-ray tubes (Cu, Cr, and Mn) for optimal performance over numerous material types and various experimental techniques. This requires that the tubes be switched out and aligned between experiments. This alignment maximizes the x-ray tube s output through an iterative process involving four set screws. However, the output of the x-ray tube cannot be monitored during the adjustment process due to standard radiation safety engineering controls that prevent exposure to the x-ray beam when the diffractometer doors are open. Therefore, the adjustment process is a very tedious series of blind adjustments, each followed by measurement of the output beam using a PIN diode after the enclosure doors are shut. This process can take up to 4 hr to perform. This technical memorandum documents an in-house project to motorize this alignment process. Unlike a human, motors are not harmed by x-ray radiation of the energy range used in this instrument. Therefore, using motors to adjust the set screws will allow the researcher to monitor the x-ray tube s output while making interactive adjustments from outside the diffractometer. The motorized alignment system consists of four motors, a motor controller, and a hand-held user interface module. Our goal was to reduce the alignment time to less than 30 min. The time available was the 10-week span of the Lewis' Educational and Research Collaborative Internship Project (LERCIP) summer internship program and the budget goal was $1200. In this report, we will describe our motorization design and discuss the results of its implementation