Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Microencapsulation of Ketoprofen in Blends of Acrylic Resins by Spray Drying

Microparticles of ketoprofen entrapped in blends of acrylic resins (Eudragit RL 30D and RS 30D) were successfully produced by spray drying. The effects of the proportion ketoprofen : polymer (1: 1 and 1: 3) and of spray-drying parameters (drying gas inlet temperatures of 80 and 100 degrees C; microencapsulating composition feed flow rates of 4 and 6 g/min) on the microparticles properties (drug content, encapsulation efficiency, mean particle size, moisture content, and dissolution behavior) were evaluated. Differential scanning calorimetry (DSC) thermograms and X-ray diffractograms of the spray-dried product, the free drug, and the physical mixture between the free drug and spray-dried composition (blank) were carried out. Microparticles obtained at inlet temperature of 80 degrees C, feed flow rate of 4 g/min, and ketoprofen : acrylic resin ratio of 1: 3 presented an encapsulation efficiency of 88.1%, moisture content of 5.8%, production yield around 50%, and a higher reduction in dissolution rate of the entrapped ketoprofen. Sigmoidal shape dissolution profiles were presented by the spray-dried microparticles. The dissolution profiles were relatively well described by the Weibull model, a showing high coefficient of determination, R-2, and a mean absolute error between experimental and estimated values of between 4.6 and 10.1%.

Performance of Down syndrome subjects during a coincident timing task

Abstract Background The time synchronization is a very important ability for the acquisition and performance of motor skills that generate the need to adapt the actions of body segments to external events of the environment that are changing their position in space. Down Syndrome (DS) individuals may present some deficits to perform tasks with synchronization demand. We aimed to investigate the performance of individuals with DS in a simple Coincident Timing task. Method 32 individuals were divided into 2 groups: the Down syndrome group (DSG) comprised of 16 individuals with average age of 20 (+/− 5 years old), and a control group (CG) comprised of 16 individuals of the same age. All individuals performed the Simple Timing (ST) task and their performance was measured in milliseconds. The study was conducted in a single phase with the execution of 20 consecutive trials for each participant. Results There was a significant difference in the intergroup analysis for the accuracy adjustment - Absolute Error (Z = 3.656, p = 0.001); and for the performance consistence - Variable Error (Z = 2.939, p = 0.003). Conclusion DS individuals have more difficulty in integrating the motor action to an external stimulus and they also present more inconsistence in performance. Both groups presented the same tendency to delay their motor responses.

Hochgenaue Berechnungen von Energien und molekularen Eigenschaften mit Hilfe der Coupled-Cluster-Theorie

Coupled-Cluster-Theorie (CC) ist in der heutigen Quantenchemie eine der erfolgreichsten Methoden zur genauen Beschreibung von Molekülen. Die in dieser Arbeit vorgestellten Ergebnisse zeigen, daß neben den Berechnungen von Energien eine Reihe von Eigenschaften wie Strukturparameter, Schwingungsfrequenzen und Rotations-Schwingungs-Parameter kleiner und mittelgrofler Moleküle zuverlässig und präzise vorhergesagt werden können. Im ersten Teil der Arbeit wird mit dem Spin-adaptierten Coupled-Cluster-Ansatz (SA-CC) ein neuer Weg zur Verbesserung der Beschreibung von offenschaligen Systemen vorgestellt. Dabei werden zur Bestimmung der unbekannten Wellenfunktionsparameter zusätzlich die CC-Spingleichungen gelöst. Durch dieses Vorgehen wird gewährleistet, daß die erhaltene Wellenfunktion eine Spineigenfunktion ist. Die durchgeführte Implementierung des Spin-adaptierten CC-Ansatzes unter Berücksichtigung von Einfach- und Zweifachanregungen (CCSD) für high-spin Triplett-Systeme wird ausführlich erläutert. Im zweiten Teil werden CC-Additionsschemata vorgestellt, die auf der Annahme der Additivität von Elektronenkorrelations- und Basissatzeffekten basieren. Die etablierte Vorgehensweise, verschiedene Beiträge zur Energie mit an den Rechenaufwand angepassten Basissätzen separat zu berechnen und aufzusummieren, wird hier auf Gradienten und Kraftkonstanten übertragen. Für eine Beschreibung von Bindungslängen und harmonischen Schwingungsfrequenzen mit experimenteller Genauigkeit ist die Berücksichtigung von Innerschalenkorrelationseffekten sowie Dreifach- und Vierfachanregungen im Clusteroperator der Wellenfunktion nötig. Die Basissatzkonvergenz wird dabei zusätzlich mit Extrapolationsmethoden beschleunigt. Die quantitative Vorhersage der Bindungslängen von 17 kleinen Molekülen, aufgebaut aus Atomen der ersten Langperiode, ist so mit einer Genauigkeit von wenigen Hundertstel Pikometern möglich. Für die Schwingungsfrequenzen dieser Moleküle weist das CC-Additionsschema basierend auf den berechneten Kraftkonstanten im Vergleich zu experimentellen Ergebnissen einen mittleren absoluten Fehler von 3.5 cm-1 und eine Standardabweichung von 2.2 cm-1 auf. Darüber hinaus werden zur Unterstützung von experimentellen Untersuchungen berechnete spektroskopische Daten einiger größerer Moleküle vorgelegt. Die in dieser Arbeit vorgestellten Untersuchungen zur Isomerisierung von Dihalogensulfanen XSSX (X= F, Cl) oder die Berechnung von Struktur- und Rotations-Schwingungs-Parametern für die Moleküle CHCl2F und CHClF2 zeigen, daß bereits störungstheoretische CCSD(T)-Näherungsmethoden qualitativ gute Vorhersagen experimenteller Resultate liefern. Desweiteren werden Diskrepanzen von experimentellen und berechneten Bindungsabständen bei den Molekülen Borhydrid- und Carbenylium durch die Berücksichtigung des elektronischen Beitrages zum Trägheitsmoment beseitigt.

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

Estimating Annual CO2 Flux for Lutjewad Station Using Three Different Gap-Filling Techniques

Long-term measurements of CO2 flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO2 flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set. The performances of gap-filling techniques were analysed by calculating statistical criteria: coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), maximum absolute error (MaxAE), and mean square bias (MSB). The gap-fill accuracy is seasonally dependent, with better results in cold seasons. The highest accuracy is obtained using ANN technique which is also less sensitive to environmental/seasonal conditions. We argue that filling gaps directly on measured CO2 fluxes is more advantageous than the common method of filling gaps on calculated net ecosystem change, because ANN is an empirical method and smaller scatter is expected when gap filling is applied directly to measurements.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Geochemical and physical sediment properties of sediment cores from the Portuguese shelf

Marine sediments from the Portuguese shelf are influenced by environmental changes in the surrounding continental and marine environment. These are largely controlled by the North Atlantic Oscillation, but additional impacts may arise from episodic tsunamis. In order to investigate these influences, a high resolution multi-proxy study has been carried out on a 5.4 m long gravity core and five box cores from the Tagus prodelta on the western Portuguese margin, incorporating geochemical (Corg/Ntotal ratios, d13Corg, d15N, d18O, Corg and CaCO3 content) and physical sediment properties (magnetic susceptibility, grain-size). Subsurface data of the five box cores indicate no major effect of early postdepositional alteration. Surface data show a higher fraction of terrigenous organic material close to the river mouth and in the southern prodelta. Gravity core GeoB 8903 covers the last 3.2 kyrs with a temporal resolution of at least 0.1 cm/yr. Very high sedimentation rates between 69 and 140 cm core depth indicate a possible disturbance of the record by the AD1755 tsunami, although no evidence for a disturbance is observed in the data. Sea surface temperature and salinity on the prodelta, the local budget of marine NO3- as well as the provenance of organic matter remained virtually constant during the past 3.2 kyrs. A positive correlation between magnetic susceptibility (MS) and North Atlantic Oscillation (NAO) is evident for the past 250 years, coinciding with a negative correlation between mean grain-size and NAO. This is assigned to a constant riverine supply of fine material with high MS, which is diluted by the riverine input of a coarser, low-MS component during NAO negative, high-precipitation phases. End-member modelling of the lithic grain-size spectrum supports this, revealing a third, coarse lithic component. The high abundance of this coarse end-member prior to 2 kyr BP is interpreted as the result of stronger bottom currents, concentrating the coarse sediment fraction by winnowing. As continental climate was more arid prior to 2 kyr BP (Subboreal), the coarse end-member may also consist of dust from local sources. A decrease in grain-size and CaCO3 content after 2 kyr BP is interpreted as a result of decreasing wind strength. The onset of a fining trend and a further decrease in CaCO3 around AD900 occurs simultaneous to climatic variations, reconstructed from eastern North Atlantic records. A strong increase in MS between AD1400 and AD1500 indicates higher lithic terrigenous input, caused by deforestation in the hinterland.

Mid-Pliocene palynomorph record of the North Atlantic

The mid-Pliocene was an episode of prolonged global warmth and strong North Atlantic thermohaline circulation, interrupted briefly at circa 3.30 Ma by a global cooling event corresponding to marine isotope stage (MIS) M2. Paleoceanographic changes in the eastern North Atlantic have been reconstructed between circa 3.35 and 3.24 Ma at Deep Sea Drilling Project Site 610 and Integrated Ocean Drilling Program Site 1308. Mg/Ca ratios and d18O from Globigerina bulloides are used to reconstruct the temperature and relative salinity of surface waters, and dinoflagellate cyst assemblages are used to assess variability in the North Atlantic Current (NAC). Our sea surface temperature data indicate warm waters at both sites before and after MIS M2 but a cooling of ~2-3°C during MIS M2. A dinoflagellate cyst assemblage overturn marked by a decline in Operculodinium centrocarpum reflects a southward shift or slowdown of the NAC between circa 3.330 and 3.283 Ma, reducing northward heat transport 23-35 ka before the global ice volume maximum of MIS M2. This will have established conditions that ultimately allowed the Greenland ice sheet to expand, leading to the global cooling event at MIS M2. Comparison with an ice-rafted debris record excludes fresh water input via icebergs in the northeast Atlantic as a cause of NAC decline. The mechanism causing the temporary disruption of the NAC may be related to a brief reopening of the Panamanian Gateway at about this time.

A comparison between multi-proxy and historical data of drift-ice conditions on the East Greenland shelf

The reduction in sea ice along the SE Greenland coast during the last century has severely impacted ice-rafting to this area. In order to reconstruct ice-rafting and oceanographic conditions in the area of Denmark Strait during the last ~150 years, we conducted a multiproxy study on three short (20 cm) sediment cores from outer Kangerdlugssuaq Trough (~300 m water depth). The proxy-based data obtained have been compared with historical and instrumental data to gain a better understanding of the ice sheet-ocean interactions in the area. A robust chronology has been developed based on 210Pb and 137Cs measurements on core PO175GKC#9 (~66.2°N, 32°W) and expanded to the two adjacent cores based on correlations between calcite weight percent records. Our proxy records include sea-ice and phytoplankton biomarkers, and a variety of mineralogical determinations based on the <2 mm sediment fraction, including identification with quantitative x-ray diffraction, ice-rafted debris counts on the 63-150 µm sand fraction, and source identifications based on the composition of Fe oxides in the 45-250 µm fraction. A multivariate statistical analysis indicated significant correlations between our proxy records and historical data, especially with the mean annual temperature data from Stykkishólmur (Iceland) and the storis index (historical observations of sea-ice export via the East Greenland Current). In particular, the biological proxies (calcite weight percent, IP25, and total organic carbon %) showed significant linkage with the storis index. Our records show two distinct intervals in the recent history of the SE Greenland coast. The first of these (ad 1850-1910) shows predominantly perennial sea-ice conditions in the area, while the second (ad 1910-1990) shows more seasonally open water conditions.

Particulate and phytoplankton absorption during POLARSTERN cruises ANT-XXVI/3 and ANT-XXVIII/3

The euphotic depth (Zeu) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Zeu products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Zeu from satellite and to evaluate how different Zeu products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). They were compared with in situ measurements of Zeu from different regions of the SO. Both approaches and sensors are robust to retrieve Zeu, although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Zeu-Chla and Zeu-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Zeu-Chla was 8% higher than PP based on Zeu-IOP, but it was up to 30% higher south of 60°S. Satellite phytoplankton absorption coefficients (aph) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS aph are generally more robust than SeaWiFS. Thus, MODIS aph should be preferred in PP models based on aph in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data.

Age determination and grwoth rates of stalagmites and stalactites from the Okshola cave, Fauske, northern Norway

The sensitivity of terrestrial environments to past changes in heat transport is expected to be manifested in Holocene climate proxy records on millennial to seasonal timescales. Stalagmite formation in the Okshola cave near Fauske (northern Norway) began at about 10.4 ka, soon after the valley was deglaciated. Past monitoring of the cave and surface has revealed stable modern conditions with uniform drip rates, relative humidity and temperature. Stable isotope records from two stalagmites provide time-series spanning from c. 10380 yr to AD 1997; a banded, multi-coloured stalagmite (Oks82) was formed between 10380 yr and 5050 yr, whereas a pristine, white stalagmite (FM3) covers the period from ~7500 yr to the present. The stable oxygen isotope (delta18Oc), stable carbon isotope (delta13Cc), and growth rate records are interpreted as showing i) a negative correlation between cave/surface temperature and delta18Oc, ii) a positive correlation between wetness and delta13Cc, and iii) a positive correlation between temperature and growth rate. Following this, the data from Okshola show that the Holocene was characterised by high-variability climate in the early part, low-variability climate in the middle part, and high-variability climate and shifts between two distinct modes in the late part. A total of nine Scandinavian stalagmite delta18Oc records of comparable dating precision are now available for parts or most of the Holocene. None of them show a clear Holocene thermal optimum, suggesting that they are influenced by annual mean temperature (cave temperature) rather than seasonal temperature. For the last 1000 years, delta18Oc values display a depletion-enrichment-depletion pattern commonly interpreted as reflecting the conventional view on climate development for the last millennium. Although the delta18Oc records show similar patterns and amplitudes of change, the main challenges for utilising high-latitude stalagmites as palaeoclimate archives are i) the accuracy of the age models, ii) the ambiguity of the proxy signals, and iii) calibration with monitoring data.

Planktonic foraminiferal oxygen isotopes of ODP Site 143-865 samples

Cool tropical sea surface temperatures (SSTs) are reported for warm Paleogene greenhouse climates based on the d18O of planktonic foraminiferal tests. These results are difficult to reconcile with models of greenhouse gas-forced climate. It has been suggested that this "cool tropics paradox" arises from postdepositional alteration of foraminiferal calcite, yielding erroneously high d18O values. Recrystallization of foraminiferal tests is cryptic and difficult to quantify, and the compilation of robust d18O records from moderately altered material remains challenging. Scanning electron microscopy of planktonic foraminiferal chamber-wall cross sections reveals that the basal area of muricae, pustular outgrowths on the chamber walls of species belonging to the genus Morozovella, contain no mural pores and may be less susceptible to postdepositional alteration. We analyzed the d18O in muricae bases of morozovellids from the central Pacific (Ocean Drilling Program Site 865) by ion microprobe using 10 ?m pits with an analytical reproducibility of ±0.34 per mil (2 standard deviations). In situ measurements of d18O in these domains yield consistently lower values than those published for conventional multispecimen analyses. Assuming that the original d18O is largely preserved in the basal areas of muricae, this new d18O record indicates Early Paleogene (~49-56 Ma) tropical SSTs in the central Pacific were 4°-8°C higher than inferred from the previously published d18O record and that SSTs reached at least ~33°C during the Paleocene-Eocene thermal maximum. This study demonstrates the utility of ion microprobe analysis for generating more reliable paleoclimate records from moderately altered foraminiferal tests preserved in deep-sea sediments.