Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

A reconstruction of radiocarbon production and total solar irradiance from the Holocene ¹⁴C and CO₂ records: implications of data and model uncertainties

Radiocarbon production, solar activity, total solar irradiance (TSI) and solar-induced climate change are reconstructed for the Holocene (10 to 0 kyr BP), and TSI is predicted for the next centuries. The IntCal09/SHCal04 radiocarbon and ice core CO2 records, reconstructions of the geomagnetic dipole, and instrumental data of solar activity are applied in the Bern3D-LPJ, a fully featured Earth system model of intermediate complexity including a 3-D dynamic ocean, ocean sediments, and a dynamic vegetation model, and in formulations linking radiocarbon production, the solar modulation potential, and TSI. Uncertainties are assessed using Monte Carlo simulations and bounding scenarios. Transient climate simulations span the past 21 thousand years, thereby considering the time lags and uncertainties associated with the last glacial termination. Our carbon-cycle-based modern estimate of radiocarbon production of 1.7 atoms cm−2 s−1 is lower than previously reported for the cosmogenic nuclide production model by Masarik and Beer (2009) and is more in-line with Kovaltsov et al. (2012). In contrast to earlier studies, periods of high solar activity were quite common not only in recent millennia, but throughout the Holocene. Notable deviations compared to earlier reconstructions are also found on decadal to centennial timescales. We show that earlier Holocene reconstructions, not accounting for the interhemispheric gradients in radiocarbon, are biased low. Solar activity is during 28% of the time higher than the modern average (650 MeV), but the absolute values remain weakly constrained due to uncertainties in the normalisation of the solar modulation to instrumental data. A recently published solar activity–TSI relationship yields small changes in Holocene TSI of the order of 1 W m−2 with a Maunder Minimum irradiance reduction of 0.85 ± 0.16 W m−2. Related solar-induced variations in global mean surface air temperature are simulated to be within 0.1 K. Autoregressive modelling suggests a declining trend of solar activity in the 21st century towards average Holocene conditions.

Age and oxygen isotope data for bulk carbonate from DSDP Sites 41-366 and 72-516 and ODP Sites 111-677A and 130-807

A numerical model which describes oxygen isotope exchange during burial and recrystallization of deep-sea carbonate is used to obtain information on how sea surface temperatures have varied in the past by correcting measured d18O values of bulk carbonate for diagenetic overprinting. Comparison of bulk carbonate and planktonic foraminiferal d18O records from ODP site 677A indicates that the oxygen isotopic composition of bulk carbonate does reflect changes in sea surface temperature and d18O. At ODP Site 690, we calculate that diagenetic effects are small, and that both bulk carbonate and planktonic foraminiferal d18O records accurately reflect Paleogene warming of high latitude surface oceans, biased from diagenesis by no more than 1°C. The same is likely to be true for other high latitude sites where sedimentation rates are low. At DSDP sites 516 and 525, the effects of diagenesis are more significant. Measured d18O values of Eocene bulk carbonates are more than 2? lower at deeply buried site 516 than at site 525, consistent with the model prediction that the effects of diagenesis should be proportional to sedimentation rate. Model-corrections reconcile the differences in the data between the two sites; the resulting paleotemperature reconstruction indicates a 4°C cooling of mid-latitude surface oceans since the Eocene. At low latitudes, the contrast in temperature between the ocean surface and bottom makes the carbonate d180 values particularly sensitive to diagenetic effects; most of the observed variations in measured d18O values are accounted for by diagenetic effects rather than by sea surface temperature variations. We show that the data are consistent with constant equatorial sea surface temperatures through most of the Cenozoic, with the possible exception of the early Eocene, when slightly higher temperatures are indicated. We suggest that the lower equatorial sea surface temperatures for the Eocene and Oligocene reported in other oxygen isotope studies are artifacts of diagenetic recrystallization, and that it is impossible to reconstruct accurately equatorial sea surface temperatures without explicitly accounting for diagenetic overprinting.

Consumption-based accounting of U.S. CO2 emissions from 1990 to 2010

To tackle global climate change, it is desirable to reduce CO2 emissions associated with household consumption in particular in developed countries, which tend to have much higher per capita household carbon footprints than less developed countries. Our results show that carbon intensity of different consumption categories in the U.S. varies significantly. The carbon footprint tends to increase with increasing income but at a decreasing rate due to additional income being spent on less carbon intensive consumption items. This general tendency is frequently compensated by higher frequency of international trips and higher housing related carbon emissions (larger houses and more space for consumption items). Our results also show that more than 30% of CO2 emissions associated with household consumption in the U.S. occur outside of the U.S. Given these facts, the design of carbon mitigation policies should take changing household consumption patterns and international trade into account.

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Influence of Agricultural Support on Sale Prices of French Farmland: A comparison of different subsidies, accounting for the role of environmental and land regulations. Factor Markets Working Document No. 51, June 2013

This paper investigates the determinants of agricultural land price in several regions in France over the period 1994-2011, using individual plot transaction data, with a particular emphasis on agricultural subsidies and nitrate zoning regulations. It found a positive but relatively small capitalisation effect of the total subsidies per hectare. The data revealed that agricultural subsidies capitalised, at least to some extent, but the magnitude of such a capitalisation depends on the region considered, on the type of subsidy considered, and on the location of the plot in a nitrate surplus zone or not. Only land set-aside premiums significantly capitalise into land price, while single farm payments have a significant positive capitalisation impact only for plots located in a nitrate-surplus zone.

Consumers need more reliable automobile fuel economy data.

Mode of access: Internet.

Review of automatic data processing developments in the Federal Government.

Mode of access: Internet.

Historical financial data--domestic automobile manufacturers. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Outer continental shelf sale 40--inadequate data used to select and evaluate lands to lease, Department of the Interior : report to the Congress /

"B-118678."

Environmental data : major effort is needed to improve NOAA's data management and archiving : report to the Chairman, Committee on Commerce, Science and Transportation, U.S. Senate /

"B-241021"--P. l.

Highway user fees: updated data needed to determine whether all users pay their fair share.

Mode of access: Internet.

Head Start : better data and processes needed to monitor underenrollment : report to congressional requesters /

"GAO-04-17."

Automated data systems manual, Nonappropriated Funds Information Standard System (FAFISS) : budget, users manual.

"1 January 1985."