Forecasting camping tourism demand in America’s national parks using a machine learning approach

Camping has emerged as a growing sector of tourism. Within the context of the United States, where national parks are designated with the goal of preserving the natural ecosystem, this growing demand is met with a fixed supply of campsites. It is therefore important for agency managers to be able to understand and model future demand for their finite accommodations so that they might better allocate resources and disseminate projected demand trends to park visitors planning their national park journeys. This presentation describes the state of affairs concerning camping tourism within US national parks and presents an analysis using six forecasting methods to project future campsite demand. This includes a discussion of how the unique nature of camping tourism and the behavior of automobile campers present unexplored challenges for forecasting

Harnessing nuclear spin polarization fluctuations in a semiconductor nanowire

Soon after the first measurements of nuclear magnetic resonance (NMR) in a condensed matter system, Bloch predicted the presence of statistical fluctuations proportional to $1/\sqrt{N}$ in the polarization of an ensemble of $N$ spins. First observed by Sleator et al., so-called "spin noise" has recently emerged as a critical ingredient in nanometer-scale magnetic resonance imaging (nanoMRI). This prominence is a direct result of MRI resolution improving to better than 100 nm^3, a size-scale in which statistical spin fluctuations begin to dominate the polarization dynamics. We demonstrate a technique that creates spin order in nanometer-scale ensembles of nuclear spins by harnessing these fluctuations to produce polarizations both larger and narrower than the natural thermal distribution. We focus on ensembles containing ~10^6 phosphorus and hydrogen spins associated with single InP and GaP nanowires (NWs) and their hydrogen-containing adsorbate layers. We monitor, control, and capture fluctuations in the ensemble's spin polarization in real-time and store them for extended periods. This selective capture of large polarization fluctuations may provide a route for enhancing the weak magnetic signals produced by nanometer-scale volumes of nuclear spins. The scheme may also prove useful for initializing the nuclear hyperfine field of electron spin qubits in the solid-state.Comment: 18 pages, 5 figure

The First Korean Case of Beare-Stevenson Syndrome with a Tyr375Cys Mutation in the Fibroblast Growth Factor Receptor 2 Gene

Here we report the first case of a Korean infant with a cloverleaf-shaped craniosynostosis, in which the diagnosis of Beare-Stevenson syndrome was suspected upon observation of the typical morphological features. This infant exhibited craniofacial anomalies, ocular proptosis, cutis gyrata, acanthosis nigricans, prominent umbilical stump, furrowed palms and soles, hypospadia, and sacral skin tag coupled with dermal sinus tract. Brain magnetic resonance imaging revealed that the patient also had non-communicating hydrocephalus with Chiari malformation. This is the 8th report of Beare-Stevenson syndrome in the literature, which was confirmed by the detection of a Tyr375Cys mutation in the fibroblast growth factor receptor 2 (FGFR2) gene

Chemical modification studies on the [alpha]--galactopyranosyl binding lectin from the seeds of Bandeiraea simplicifolia

The role of amino, carboxyl and sulfhydryl groups in the binding of carbohydrate ligands to the [alpha]--galactopyranosyl binding lectin from Bandeiraea simplicifolia has been evaluated using specific chemical modification techniques. The results indicate that carboxyl groups participate in the carbohydrate binding phenomenon, whereas free amino and sulfhydryl groups do not appear to be directly involved.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/21717/1/0000109.pd

Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community

Parameter Estimation Error Dependency on the Acquisition Protocol in Diffusion Kurtosis Imaging

Mono-exponential kurtosis model is routinely fitted on diffusion weighted, magnetic resonance imaging data to describe non-Gaussian diffusion. Here, the purpose was to optimize acquisitions for this model to minimize the errors in estimating diffusion coefficient and kurtosis. Similar to a previous study, covariance matrix calculations were used, and coefficients of variation in estimating each parameter of this model were calculated. The acquisition parameter, b values, varied in discrete grids to find the optimum ones that minimize the coefficient of variation in estimating the two non-Gaussian parameters. Also, the effect of variation of the target values on the optimized values was investigated. Additionally, the results were benchmarked with Monte Carlo noise simulations. Simple correlations were found between the optimized b values and target values of diffusion and kurtosis. For small target values of the two parameters, there is higher chance of having significant errors; this is caused by maximum b value limits imposed by the scanner than the mathematical bounds. The results here, cover a wide range of parameters D and K so that they could be used in many directionally averaged diffusion weighted cases such as head and neck, prostate, etc

Deep analysis of perception through dynamic structures that emerge in cortical activity from self-regulated noise

The statistical properties of the spontaneous background electrocorticogram (ECoG) were modeled, starting with random numbers, constraining the distributions, and identifying characteristic deviations from randomness in ECoG from subjects at rest and during intentional behaviors. The ECoG had been recorded through 8 × 8 arrays of 64 electrodes, from the surfaces of auditory, visual, or somatic cortices of 9 rabbits, and from the inferotemporal cortex of a human subject. Power spectral densities (PSD) in coordinates of log10 power versus log10 frequency of ECoG from subjects at rest usually conformed to noise in power-law distributions in a continuum. PSD of ECoG from active subjects usually deviated from noise in having peaks in log10 power above the power-law line in various frequency bands. The analytic signals from the Hilbert transform after band pass filtering in the beta and gamma ranges revealed beats from interference among distributed frequencies in band pass filtered noise called Rayleigh noise. The beats were displayed as repetitive down spikes in log10 analytic power. Repetition rates were proportional to filter bandwidths for all center frequencies. Resting ECoG often gave histograms of the magnitudes and intervals of down spikes that conformed to noise. Histograms from active ECoG often deviated from noise in Rayleigh distributions of down spike intervals by giving what are called Rice (Mathematical analysis of random noise—and appendixes—technical publications monograph B-1589. Bell Telephone Labs Inc., New York, 1950) distributions. Adding power to noise as signals at single frequencies simulated those deviations. The beats in dynamic theory are deemed essential for perception, by gating beta and gamma bursts at theta rates through enhancement of the cortical signal-to-noise ratio in exceptionally deep down spikes called null spikes

Intrinsic optical biomarkers associated with the invasive potential of tumor cells in engineered tissue models

This report assesses the ability of intrinsic two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging to characterize features associated with the motility and invasive potential of epithelial tumor cells engineered in tissues. Distinct patterns of organization are found both within the cells and the matrix that depend on the adhesive properties of the cells as well as factors attributed to adjacent fibroblasts. TPEF images are analyzed using automated algorithms that reveal unique features in subcellular organization and cell spacing that correlate with the invasive potential. We expect that such features have significant diagnostic potential for basic in vitro studies that aim to improve our understanding of cancer development or response to treatments, and, ultimately can be applied in prognostic evaluation

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36