Bufferless Compression of Asynchronously Sampled ECG Signals in Cubic Hermitian Vector Space.

Asynchronous level crossing sampling analog-to-digital converters (ADCs) are known to be more energy efficient and produce fewer samples than their equidistantly sampling counterparts. However, as the required threshold voltage is lowered, the number of samples and, in turn, the data rate and the energy consumed by the overall system increases. In this paper, we present a cubic Hermitian vector-based technique for online compression of asynchronously sampled electrocardiogram signals. The proposed method is computationally efficient data compression. The algorithm has complexity O(n), thus well suited for asynchronous ADCs. Our algorithm requires no data buffering, maintaining the energy advantage of asynchronous ADCs. The proposed method of compression has a compression ratio of up to 90% with achievable percentage root-mean-square difference ratios as a low as 0.97. The algorithm preserves the superior feature-to-feature timing accuracy of asynchronously sampled signals. These advantages are achieved in a computationally efficient manner since algorithm boundary parameters for the signals are extracted a priori.

CHOLINERGIC MODULATION OF THALAMIC INPUT INTO THE CINGULATE CORTEX

This research demonstrates cholinergic modulation of thalamic input into the limbic cortex. A projection from the mediodorsal thalamus (MD) to the anterior cingulate cortex was defined anatomically and physiologically. Injections of horse-radish peroxidase into the anterior cingulate cortex labels neurons in the lateral, parvocellular, region of MD. Electrical Stimulation of this area produces a complex field potential in the anterior cingulate cortex which was further characterized by current density analysis and single cell recordings.^ The monsynaptic component of the response was identified as a large negative field which is maximal in layer IV of the anterior cingulate cortex. This response shows remarkable tetanic potentiation of frequencies near 7 Hz. During a train of 50 or more stimuli, the response would grow quickly and remain at a fairly stable potentiated level throughout the train.^ Cholinergic modulation of this thalamic response was demonstrated by iontophoretic application of the cholinergic agonist carbachol decreased the effectiveness of the thalamic imput by rapidly attenuation the response during a train of stimuli. The effect was apparently mediated by muscarinic receptors since the effect of carbachol was blocked by atropine but not by hexamethonium.^ To determine the source of the cingulate cortex cholinergic innervation, lesions were made in the anterior and medial thalamus and in the nucleus of the diagonal band of Broca. The effects of these lesions on choline acetyltranferase activity in the cingulate cortex were determined by a micro-radio-enzymatical assay. Only the lesions of the nucleus of the diagonal band significantly decreased the choline acetyltransferase activity in the cingulate cortex regions. Therefore, the diagonal band appears to be a major source of sensory cholinergic innervation and may be involved in gating of sensory information from the thalamus into the limbic cortex. Attempts to modulate the cingulate response to MD stimulation with electrical stimulation of the diagonal band, however were not successful.^

Measuring Scale Efficiency from the Translog Multi-Input, Multi-Output Distance Function

Ray (1998) developed measures of input- and output-oriented scale efficiency that can be directly computed from an estimated Translog frontier production function. This note extends the earlier results from Ray (1998) to the multiple-output multiple input case.

Comparing Input- and Output-Oriented Measures of Technical Efficiency to Determine Local Returns to Scale in DEA Models

This paper shows how one can infer the nature of local returns to scale at the input- or output-oriented efficient projection of a technically inefficient input-output bundle, when the input- and output-oriented measures of efficiency differ.

Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing

A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

Responding to Price Signals in Communal Agriculture: Shaker Hog Production, 1788-1850

Isolated Shaker communal farms stressed self-sufficiency as an ideal but carefully chose which goods to buy and sell in external markets and which to produce and consume themselves. We use records of hog slaughter weights to investigate the extent to which the Shakers incorporated market-based price information in determining production levels of a consumption good which they did not sell in external markets: pork. Granger causality tests indicate that Shaker pork production decisions were influenced as hypothesized, strongly by corn prices and weakly by pork prices. We infer that attention to opportunity costs of goods that they produced and consumed themselves was a likely factor aiding the longevity of Shaker communal societies.

Input Price Variation Across Locations and a Generalized Measure of Cost Efficiency

We propose a nonparametric model for global cost minimization as a framework for optimal allocation of a firm's output target across multiple locations, taking account of differences in input prices and technologies across locations. This should be useful for firms planning production sites within a country and for foreign direct investment decisions by multi-national firms. Two illustrative examples are included. The first example considers the production location decision of a manufacturing firm across a number of adjacent states of the US. In the other example, we consider the optimal allocation of US and Canadian automobile manufacturers across the two countries.

Diversity of neuronal connexins in the mammalian retina

Many neurons in the mammalian retina are electrically coupled by intercellular channels or gap junctions, which are assembled from a family of proteins called connexins. Numerous studies indicate that gap junctions differ in properties such as conductance and tracer permeability. For example, A-type horizontal cell gap junctions are permeable to Lucifer Yellow, but B-type horizontal cell gap junctions are not. This suggests the two cell types express different connexins. My hypothesis is that multiple neuronal connexins are expressed in the mammalian retina in a cell type specific manner. Immunohistochemical techniques and confocal microscopy were used to localize certain connexins within well-defined neuronal circuits. The results of this study can be summarized as follows: AII amacrine cells, which receive direct input from rod bipolar cells, are well-coupled to neighboring AIIs. In addition, AII amacrine cells also form gap junctions with ON cone bipolar cells. This is a complex heterocellular network. In both rabbit and primate retina, connexin36 occurs at dendritic crossings in the AII matrix as well as between AIIs and ON cone bipolar cells. Coupling in the AII network is thought to reduce noise in the rod pathway while AII/bipolar gap junctions are required for the transmission of rod signals to ON ganglion cells. In the outer plexiform layer, connexin36 forms gap junctions between cones and between rods and cones via cone telodendria. Cone to cone coupling is thought to reduce noise and is partly color selective. Rod to cone coupling forms an alternative rod pathway thought to operate at intermediate light intensity. A-type horizontal cells in the rabbit retina are strongly coupled via massive low resistance gap junctions composed from Cx50. Coupling dramatically extends the receptive field of horizontal cells and the modulation of coupling is thought to change the strength of the feedback signal from horizontal cells to cones. Finally, there are other coupled networks, such as B-type horizontal cells and S1/S2 amacrine cells, which do not use either connexin36 or Cx50. These results confirm the hypothesis that multiple neuronal connexins are expressed in the mammalian retina and these connexins are localized to particular retinal circuits. ^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Regulation of myogenesis by growth signals -growth factors, oncogenes and protein kinases

Establishment of a myogenic phenotype involves antagonism between cell proliferation and differentiation. The recent identification of the MyoD family of muscle-specific transcription factors provides opportunities to dissect at the molecular level the mechanisms through which defined cell type-specific transcription factors respond to environmental cues and regulate differentiation programs. This project is aimed at elucidation of the molecular mechanism whereby growth factors repress myogenesis. Initial studies demonstrated that nuclear oncogenes such as c-fos, junB and c-jun are immediate early genes that respond to serum and TGF-$\beta$. Using the muscle creatine kinase (MCK) enhancer linked to the reporter gene CAT as a marker for differentiation, we showed that transcriptional function of myogenin can be disrupted in the presence of c-Fos, JunB and cjun. In contrast, JunD, which shares DNA-binding specificity with JunB and c-Jun but is expressed constitutively in muscle cells, failed to show the inhibition. The repression by Fos and Jun is targeted at KE-2 motif, the same sequence that mediates myogenin-dependent activation and muscle-specific transactivation. Deletion analysis indicated that the transactivation domain of c-Jun at the N-terminus is responsible for the repression. Considering that myogenin is a phosphoprotein and cAMP and TPA are able to regulate myogenesis, we examined whether constitutively active protein kinase C (PKC) and protein kinase A (PKA) could substitute for exogenous growth factors and prevent transcription activation by myogenin. Indeed, the basic region of myogenin is phosphorylated by PKC at a threonine that is conserved in all members of the MyoD family. Phosphorylation at this site attenuates DNA binding activity of myogenin. Protein kinase A can also phosphorylate myogenin in a region adjacent to the DNA binding domain. However, phosphorylation at this site is insufficient to abrogate myogenin's DNA binding capacity, suggesting that PKA and PKC may affect myogenin transcriptional activity through different mechanisms. These findings provide insight into the mechanisms through which growth factor signals negatively regulate the muscle differentiation program and contribute to an understanding of signal transducing pathways between the cell membrane and nucleus. ^

Diatoms, total organic carbon, and total nitrogen of sediment core Dethlingen, Germany

To provide insights into the long-term evolution of aquatic ecosystems without human interference, we here evaluate a decadal- to centennial-scale-resolution diatom record spanning about 12 ka of the Holsteinian interglacial (Marine Isotope Stage 11c). Using a partially varved sediment core from the Dethlingen palaeolake (northern Germany), which has previously been studied for palynological and microfacies signals, we document the co-evolution of the aquatic and surrounding terrestrial environment. The diatom record is dominated by the genera Stephanodiscus, Aulacoseira, Ulnaria and Fragilaria. Based on the diatom assemblages and physical sediment properties, the evolution of the Dethlingen palaeolake can be subdivided into three major phases. During the oldest phase (lasting ~1900 varve years), the lake was ~10-15 m deep and characterized by anoxic bottom-water conditions and a high nutrient content. The following ~5600 years exhibited water depths >20 m, maximum diatom and Pediastrum productivity, and a peak in allochtonous nutrient input. During this phase, water-column mixing became more vigorous, resulting in a breakdown of anoxia. The youngest lake phase (~4000-5000 years) was characterized by decreasing water depth, turbulent water conditions and decreased nutrient loading. Based on our palaeolimnological data, we conclude that the evolution of the Dethlingen palaeolake during the Holsteinian interglacial responded closely to (i) changes within the catchment area (as documented by vegetation and sedimentation) related to the transition from closed forests growing on nutrient-rich soils (mesocratic forest phase) to open forests developing on poor soils (oligocratic forest phase), and (ii) short-term climate variability as reflected in centennial-scale climate perturbations.

Sedimentology on 19 cores from the South China Sea

Based on the study of 10 sediment cores and 40 core-top samples from the South China Sea (SCS) we obtained proxy records of past changes in East Asian monsoon climate on millennial to bidecadal time scales over the last 220,000 years. Climate proxies such as global sea level, estimates of paleotemperature, salinity, and nutrients in surface water, ventilation of deep water, paleowind strength, freshwater lids, fluvial and/or eolian sediment supply, and sediment winnowing on the sea floor were derived from planktonic and benthic stable-isotope records, the distribution of siliciclastic grain sizes, planktonic foraminifera species, and the UK37 biomarker index. Four cores were AMS-14C-dated. Two different regimes of monsoon circulation dominated the SCS over the last two glacial cycles, being linked to the minima and maxima of Northern Hemisphere solar insolation. (1) Glacial stages led to a stable estuarine circulation and a strong O2-minimum layer via a closure of the Borneo sea strait. Strong northeast monsoon and cool surface water occurred during winter, in part fed by an inflow from the north tip of Luzon. In contrast, summer temperatures were as high as during interglacials, hence the seasonality was strong. Low wetness in subtropical South China was opposed to large river input from the emerged Sunda shelf, serving as glacial refuge for tropical forest. (2) Interglacials were marked by a strong inflow of warm water via the Borneo sea strait, intense upwelling southeast of Vietnam and continental wetness in China during summer, weaker northeast monsoon and high sea-surface temperatures during winter, i.e. low seasonality. On top of the long-term variations we found millennial- to centennial-scale cold and dry, warm and humid spells during the Holocene, glacial Terminations I and II, and Stage 3. The spells were coeval with published variations in the Indian monsoon and probably, with the cold Heinrich and warm Dansgaard-Oeschger events recorded in Greenland ice cores, thus suggesting global climatic teleconnections. Holocene oscillations in the runoff from South China centered around periodicities of 775 years, ascribed to subharmonics of the 1500-year cycle in oceanic thermohaline circulation. 102/84-year cycles are tentatively assigned to the Gleissberg period of solar activity. Phase relationships among various monsoon proxies near the onset of Termination IA suggest that summer-monsoon rains and fluvial runoff from South China had already intensified right after the last glacial maximum (LGM) insolation minimum, coeval with the start of Antarctic ice melt, prior to the d18O signals of global sea-level rise. Vice versa, the strength of winter-monsoon winds decreased in short centennial steps only 3000-4000 years later, along with the melt of glacial ice sheets in the Northern Hemisphere.

Minimum water input event for seedling emergence of three native perennial grasses of the Central Monte desert (Argentina) influenced by the effect of shade and the season of the year

In deserts, seedling emergence occurs only after precipitation threshold has been exceeded, however, the presence of trees modifies microenvironmental conditions that might affect the effectiveness of a water pulse. In the Monte desert, Prosopis flexuosa trees generate different micro-environmental conditions that might influence grass seedlings establishment. The objective of this work was: a) to know the effective minimum water input event that triggers the emergence of native perennial grass seedlings; b) to relate this fact with the effect of the shade of P. flexuosa canopy and the seasonal temperatures. Three important forage species of the Monte were studied: Pappophorum caespitosum and Trichloris crinita, with C4, and Jarava ichu, with C3 metabolism. Each season, seeds of these species were sown in pots placed at two light conditions: shade (similar to P. flexuosa cover) and open area, and with seven irrigation treatments (0, 10, 20, 30, 40, 2*10 and 3*10 mm). J. ichu did not emerge in any of the treatments. Significant seedling emergence was registered for P. caespitosum and T. crinita in shade conditions with 40 mm irrigation treatment in summer. Since 40 mm precipitation events are infrequent in the Monte, seedling emergence for these species would be restricted to exceptional rainy years. The facilitating effect of P. flexuosa shade would be important during the hot season.

Aerosols over the Arabian Sea

This paper provides an overview of dust transport pathways and concentrations over the Arabian Sea during 1995. Results indicate that the transport and input of dust to the region is complex, being affected by both temporally and spatially important processes. Highest values of dust were found off the Omani coast and in the entrance to the Gulf of Oman. Dust levels were generally lower in summer than the other seasons, although still relatively high compared to other oceanic regions. The Findlater jet, rather than acting as a source of dust from Africa, appears to block the direct transport of dust to the open Arabian Sea from desert dust source regions in the Middle East and Iran/Pakistan. Dust transport aloft, above the jet, rather than at the surface, may be more important during summer. In an opposite pattern to dust, sea salt levels were exceedingly high during the summer monsoon, presumably due to the sustained strong surface winds. The high sea salt aerosols during the summer months may be impacting on the strong aerosol reflectance and absorbance signals over the Arabian Sea that are detected by satellite each year.

Gravity potential spherical harmonic series

Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth's surface or by geophysical processes in the Earth's interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US/German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking successor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on ''Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites''. The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the different domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earthquake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth's global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested.