Oxygen isotope ratios (18O/16O) of hemicellulose-derived sugar biomarkers in plants, soils and sediments as paleoclimate proxy II: insight from a climate transect study

The oxygen isotopic composition of precipitation (δ18Oprec) is well known to be a valuable (paleo-)climate proxy. Paleosols and sediments and hemicelluloses therein have the potential to serve as archives recording the isotopic composition of paleoprecipitation. In a companion paper (Zech et al., 2014) we investigated δ18Ohemicellulose values of plants grown under different climatic conditions in a climate chamber experiment. Here we present results of compound-specific δ18O analyses of arabinose, fucose and xylose extracted from modern topsoils (n = 56) along a large humid-arid climate transect in Argentina in order to answer the question whether hemicellulose biomarkers in soils reflect δ18Oprec. The results from the field replications indicate that the homogeneity of topsoils with regard to δ18Ohemicellulose is very high for most of the 20 sampling sites. Standard deviations for the field replications are 1.5‰, 2.2‰ and 1.7‰, for arabinose, fucose and xylose, respectively. Furthermore, all three hemicellulose biomarkers reveal systematic and similar trends along the climate gradient. However, the δ18Ohemicellulose values (mean of the three sugars) do not correlate positively with δ18Oprec (r = −0.54, p < 0.014, n = 20). By using a Péclet-modified Craig-Gordon (PMCG) model it can be shown that the δ18Ohemicellulose values correlate highly significantly with modeled δ18Oleaf water values (r = 0.81, p < 0.001, n = 20). This finding suggests that hemicellulose biomarkers in (paleo-)soils do not simply reflect δ18Oprec but rather δ18Oprec altered by evaporative 18O enrichment of leaf water due to evapotranspiration. According to the modeling results, evaporative 18O enrichment of leaf water is relatively low (∼10‰) in the humid northern part of the Argentinian transect and much higher (up to 19‰) in the arid middle and southern part of the transect. Model sensitivity tests corroborate that changes in relative air humidity exert a dominant control on evaporative 18O enrichment of leaf water and thus δ18Ohemicellulose, whereas the effect of temperature changes is of minor importance. While oxygen exchange and degradation effects seem to be negligible, further factors needing consideration when interpreting δ18Ohemicellulose values obtained from (paleo-)soils are evaporative 18O enrichment of soil water, seasonality effects, wind effects and in case of abundant stem/root-derived organic matter input a partial loss of the evaporative 18O enrichment of leaf water. Overall, our results prove that compound-specific δ18O analyses of hemicellulose biomarkers in soils and sediments are a promising tool for paleoclimate research. However, disentangling the two major factors influencing δ18Ohemicellulose, namely δ18Oprec and relative air humidity controlled evaporative 18O enrichment of leaf water, is challenging based on δ18O analyses alone.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

Trends in Human-Centric Multimedia Networking Scenarios

The evolution of wireless access technologies and mobile devices, together with the constant demand for video services, has created new Human-Centric Multimedia Networking (HCMN) scenarios. However, HCMN poses several challenges for content creators and network providers to deliver multimedia data with an acceptable quality level based on the user experience. Moreover, human experience and context, as well as network information play an important role in adapting and optimizing video dissemination. In this paper, we discuss trends to provide video dissemination with Quality of Experience (QoE) support by integrating HCMN with cloud computing approaches. We identified five trends coming from such integration, namely Participatory Sensor Networks, Mobile Cloud Computing formation, QoE assessment, QoE management, and video or network adaptation.

Age model for ODP Leg 175 sites

Upwelling along the western coast of Africa south of the equator may be partitioned into three major areas, each having its own dynamics and history: (1) the eastern equatorial region, comprising the Congo Fan and the area of Mid-Angola; (2) the Namibia upwelling system, extending from the Walvis Ridge to Lüderitz; and (3) the Cape Province region, where upwelling is subdued. The highest nutrient contents in thermocline waters are in the northern region, the lowest in the southern one. Wind effects are at a maximum near the southern end of the Namibia upwelling system, and maximum productivity occurs near Walvis Bay, where the product between upwelling rate and nutrient content of upwelled waters is at a maximum. In the Congo/Angola region, opal tends to follow organic carbon quite closely in the Quaternary record. However, organic carbon has a strong precessional component, while opal does not. Despite relatively low opal content, sediments off Angola show the same patterns as those off the Congo; thus, they are part of the same regime. The spectrum shows nonlinear interference patterns between high- and low-latitude forcing, presumably tied to thermocline fertility and wind. On Walvis Ridge, as in the Congo-Angola region, the organic matter record behaves normally; that is, supply is high during glacial periods. In contrast, interglacial periods are favorable for opal deposition. The pattern suggests reduction in silicate content of the thermocline during glacial periods. The reversed phase (opal abundant during interglacials) persists during the entire Pleistocene and can be demonstrated deep into the Pliocene, not just on Walvis Ridge but all the way to the Oranje River and off the Cape Province. From comparison with other regions, it appears that silicate is diminished in the global thermocline, on average, whenever winds become strong enough to substantially shorten the residence time of silicate in upper waters (Walvis Hypothesis, solving the Walvis Paradox of reversed phase in opal deposition). The central discovery during Leg 175 was the documentation of a late Pliocene opal maximum for the entire Namibia upwelling system (early Matuyama Diatom Maximum [MDM]). The maximum is centered on the period between the end of the Gauss Chron and the beginning of the Olduvai Chron. A rather sharp increase in both organic matter deposition and opal deposition occurs near 3 Ma in the middle of the Gauss Chron, in association with a series of major cooling steps. As concerns organic matter, high production persists at least to 1 Ma, when there are large changes in variability, heralding subsequent pulsed production periods. From 3 to 2 Ma, organic matter and opal deposition run more or less parallel, but after 2 Ma opal goes out of phase with organic matter. Apparently, this is the point when silicate becomes limiting to opal production. Thus, the MDM conundrum is solved by linking planetary cooling to increased mixing and upwelling (ramping up to the MDM) and a general removal of silicate from the upper ocean through excess precipitation over global supply (ramping down from the MDM). The hypothesis concerning the origin of the Namibia opal acme or MDM is fundamentally the same as the Walvis Hypothesis, stating that glacial conditions result in removal of silicate from the thermocline (and quite likely from the ocean as a whole, given enough time). The Namibia opal acme, and other opal maxima in the latest Neogene in other regions of the ocean, marks the interval when a cooling ocean selectively removes the abundant silicate inherited from a warm ocean. When the excess silicate is removed, the process ceases. According to the data gathered during Leg 175, major upwelling started in the late part of the late Miocene. Presumably, this process contributed to the drawing down of carbon dioxide from the atmosphere, helping to prepare the way for Northern Hemisphere glaciation.

Age model, raw data and interpolated raw data from proxy records of sediment cores GeoB6007-1 and GeoB6007-2

Here we present a 1200 yr long benthic foraminiferal Mg/Ca based temperature and oxygen isotope record from a ~900 m deep sediment core off northwest Africa to show that atmosphere-ocean interactions in the eastern subpolar gyre are transferred at central water depth into the eastern boundary of the subtropical gyre. Further we link the variability of the NAO (over the past 165 yrs) and solar irradiance (Late Holocene) and their control on subpolar mode water formation to the multidecadal variability observed at mid-depth in the eastern subtropical gyre. Our results show that eastern North Atlantic central waters cooled by up to ~0.8± 0.7 °C and densities decreased by Sigma theta=0.3±0.2 during positive NAO years and during minima in solar irradiance during the Late Holocene. The presented records demonstrate the sensitivity of central water formation to enhanced atmospheric forcing and ice/freshwater fluxes into the eastern subpolar gyre and the importance of central water circulation for cross-gyre climate signal propagation during the Late Holocene.

Nonparametric Message Passing Methods for Cooperative Localization and Tracking

The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

Low-resource synchronous coincidence processor for positron emission tomography

We developed a new FPGA-based method for coincidence detection in positronemissiontomography. The method requires low device resources and no specific peripherals in order to resolve coincident digital pulses within a time window of a few nanoseconds. This method has been validated with a low-end Xilinx Spartan-3E and provided coincidence resolutions lower than 6 ns. This resolution depends directly on the signal propagation properties of the target device and the maximum available clock frequency, therefore it is expected to improve considerably on higher-end FPGAs.