Epidemiology and biology of cutaneous human papillomavirus

Cutaneous human papillomaviruses (HPVs) include b- and g-HPVs, in addition to a small fraction of a-HPVs. b-HPVs were first isolated from patients with the rare genetic disorder Epidermodysplasia verruciformis, and they are associated with the development of nonmelanoma skin cancer at sun-exposed skin sites in these individuals. Organ transplant recipients also have greater susceptibility to b-HPV infection of the skin and an increased risk of developing nonmelanoma skin cancer. In both immunosuppressed and immunocompromised individuals, cutaneous HPVs are ubiquitously disseminated throughout healthy skin and may be an intrinsic part of the commensal flora. Functional analysis of E6 and E7 proteins of specific cutaneous HPVs has provided a mechanistic comprehension of how these viruses may induce carcinogenesis. Nevertheless, additional research is crucial to better understand the pathological implications of the broad distribution of these HPVs

Characterization of crater morphometry on the Moon and Mercury from altimetry observations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 51-55).Recently acquired altimetry data from laser altimeters are used to assess the morphometry of impact craters. Data acquired by the Mercury Laser Altimeter on the MESSENGER spacecraft are used to measure the depths and diameters of 537 craters at the high northern latitudes on Mercury, including 42 polar-deposit-hosting craters (PDCs) which host material that is bright to earth-based radar observations. A comparative analysis suggests that the radar-bright material forms a thin (< 20 m) layer emplaced preferentially in comparatively young craters, contradicting an earlier morphometric study that indicated that PDCs contained a thick layer of water ice and dust. Topographic datasets from the lunar surface, collected by the Lunar Orbiter Laser Altimeter onboard the LRO spacecraft, are also used to evaluate the morphometry of 1,356 lunar craters. We study the morphologic change between the simple and complex crater regime, a manifestation of the transition between gravity-dominated and strength-dominated impact-forming processes, on the Moon and Mercury. The Moons transition diameter is near 16 km, in line with previous studies, while Mercurys is near 8 km, 2 km smaller than previously determined. The onset of gravity-dominated mechanisms scales inversely with gravity, which explains why Mercurys transition diameter is approximately half of the Moons.by Matthieu Jean Talpe.S.M

Wisconsin Libraries Say Cheese Again! Using Pictures to Tell the Library Story

The Campaign for Wisconsin Libraries, a program of the WLA Foundation, is once again sponsoring the very successful Wisconsin Libraries Say Cheese! This panel wants to show the world the business - and the busy-ness - of libraries. By enlisting the Wisconsin library community to post snapshots online, the Campaign will showcase the rich and varied services offered in libraries of all types across the state. Attend this program and learn how to include your library’s story – in pictures! The presenters will also give an update on other campaign activities

Developing a Complex Independent Component Analysis (CICA) technique to extract non-stationary patterns from geophysical time series

In recent decades, decomposition techniques have enabled increasingly more applications for dimension reduction, as well as extraction of additional information from geophysical time series. Traditionally, the principal component analysis (PCA)/empirical orthogonal function (EOF) method and more recently the independent component analysis (ICA) have been applied to extract, statistical orthogonal (uncorrelated), and independent modes that represent the maximum variance of time series, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the autocovariance matrix and diagonalizing higher (than two) order statistical tensors from centered time series, respectively. However, the stationarity assumption in these techniques is not justified for many geophysical and climate variables even after removing cyclic components, e.g., the commonly removed dominant seasonal cycles. In this paper, we present a novel decomposition method, the complex independent component analysis (CICA), which can be applied to extract non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA, where (a) we first define a new complex dataset that contains the observed time series in its real part, and their Hilbert transformed series as its imaginary part, (b) an ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex dataset in (a), and finally, (c) the dominant independent complex modes are extracted and used to represent the dominant space and time amplitudes and associated phase propagation patterns. The performance of CICA is examined by analyzing synthetic data constructed from multiple physically meaningful modes in a simulation framework, with known truth. Next, global terrestrial water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) gravimetry mission (2003–2016), and satellite radiometric sea surface temperature (SST) data (1982–2016) over the Atlantic and Pacific Oceans are used with the aim of demonstrating signal separations of the North Atlantic Oscillation (NAO) from the Atlantic Multi-decadal Oscillation (AMO), and the El Niño Southern Oscillation (ENSO) from the Pacific Decadal Oscillation (PDO). CICA results indicate that ENSO-related patterns can be extracted from the Gravity Recovery And Climate Experiment Terrestrial Water Storage (GRACE TWS) with an accuracy of 0.5–1 cm in terms of equivalent water height (EWH). The magnitude of errors in extracting NAO or AMO from SST data using the complex EOF (CEOF) approach reaches up to ~50% of the signal itself, while it is reduced to ~16% when applying CICA. Larger errors with magnitudes of ~100% and ~30% of the signal itself are found while separating ENSO from PDO using CEOF and CICA, respectively. We thus conclude that the CICA is more effective than CEOF in separating non-stationary patterns

Ice mass change in Greenland and Antarctica between 1993 and 2013 from satellite gravity measurements

We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a Principal Component Analysis to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite track-ing data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low and high degree potential coe�cients re ected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily in uenced by interannual variations

Initial Orbit Determination Results from the University of Luxembourg using Spire GNSS Tracking Data

CubeSats constellations using commercial off-the-shelf components have been studied for different applications, such as GNSS Radio Occultation (GNSS-RO). Furthermore, precise orbit determination of Low Earth Orbit (LEO) CubeSats based on multiple GNSS constellations would open new opportunities for scientific applications such as Earth’s gravity field measurements. In GNSS kinematic orbit determination, which is the common method used for small sats, the derived orbits are affected by noise, data gaps, outliers, measurement errors as well as poor geometry of the observations. Our work seeks to mitigate these issues and we present two areas of research: 1) GNSS network processing of GPS and Galileo constellations and 2) kinematic orbit determination of a set of Spire CubeSats that host a GNSS-RO payload. An initial architecture of kinematic orbit processing for the Spire GNSS-RO CubeSats constellation is obtained and the details on validations and limitations are discussed in more details. In addition, we showcase the agreement between the GNSS orbit products produced at the University of Luxembourg (UL) with those of the Center for Orbit Determination in Europe (CODE). Finally, the Spire kinematic orbits based on the raw observation approach are derived and compared to the L1B Spire orbit products

All-electronic frequency stabilization of a DFB laser diode

A laser diode’s junction voltage is a sensitive measure of its temperature and can be used in a thermal control feedback loop. To compensate for the temperature dependence of the laser’s internal resistance, we have measured the dynamic resistance, ∂V/∂I, by modulating the injection current and measuring the demodulated voltage. The junction voltage was thus controlled while operating at fixed DC injection current. Over an external temperature range of 15°C to 35°C, this stabilised the centre frequency (wavelength) of a 1651 nm DFB laser diode with a residual mean frequency shift of 60 MHz (0.5pm), less than the uncertainty on the centre frequency of 80 MHz (0.7 pm). Under the same conditions, conventional thermistor control gave a systematic wavelength shift of −8.4 GHz (−76 pm), and control of the uncompensated forward voltage gave a shift of 9.9 GHz (90 pm)

An iterative ICA-based reconstruction method to produce consistent time-variable total water storage fields using GRACE and swarm satellite data

Observing global terrestrial water storage changes (TWSCs) from (inter-)seasonal to (multi-)decade time-scales is very important to understand the Earth as a system under natural and anthropogenic climate change. The primary goal of the Gravity Recovery And Climate Experiment (GRACE) satellite mission (2002–2017) and its follow-on mission (GRACE-FO, 2018–onward) is to provide time-variable gravity fields, which can be converted to TWSCs with ∼300 km spatial resolution; however, the one year data gap between GRACE and GRACE-FO represents a critical discontinuity, which cannot be replaced by alternative data or model with the same quality. To fill this gap, we applied time-variable gravity fields (2013–onward) from the Swarm Earth explorer mission with low spatial resolution of ∼1500 km. A novel iterative reconstruction approach was formulated based on the independent component analysis (ICA) that combines the GRACE and Swarm fields. The reconstructed TWSC fields of 2003–2018 were compared with a commonly applied reconstruction technique and GRACE-FO TWSC fields, whose results indicate a considerable noise reduction and long-term consistency improvement of the iterative ICA reconstruction technique. They were applied to evaluate trends and seasonal mass changes (of 2003–2018) within the world’s 33 largest river basin