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.

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. ^

Assemblages and isotopic signals of modern ostracodes and host waters from Patagonia, Argentine

Ostracode species assemblages and stable oxygen and carbon isotope ratios of living and recent ostracodes, together with delta18O and delta13C_DIC values of host water samples, provide a first data set that characterizes a wide range of modern aquatic environments in the Laguna Cari-Laufquen (41°S, 68 - 69°W) and the Lago Cardiel area (48 - 49°S, 70 - 71°W) in Patagonia, Argentina. This data set will ultimately be used to interpret and calibrate data acquired from lake sediment cores with the goal of reconstructing past climate. Species assemblages and isotope values can be assigned to three groups; (1) springs, seeps and streams, (2) permanent ponds and lakes, and (3) ephemeral ponds and lakes. Springs, seeps and streams are characterized by Darwinula sp., Heterocypris incongruens, Eucypris fontana, Amphicypris nobilis and Ilyocypris ramirezi. Ostracode and water isotope values range between -13 and -5 per mil for oxygen, and between -15 and -3 per mil for carbon. They are the most negative of the entire sample set, reflecting ground water input with little or no evaporative enrichment. Limnocythere patagonica, Eucypris labyrinthica, Limnocythere sp. and Eucypris aff. fontana are typical species of permanent ponds and lakes. Isotope values indicate high degree of evaporation of lake waters relative to feeder springs and streams and range between -7 and +5 per mil for oxygen, and -5 and +4 per mil for carbon. Limnocythere rionegroensis is the dominant species in ephemeral ponds and lakes. These systems display the most enriched isotope values in both ostracodes and host waters, extending from -5 to +7 per mil for oxygen, and from -5 to +6 per mil for carbon. Living ostracodes show a positive offset from equilibrium values of up to 2 per mil for oxygen. Carbon-isotope values are up to 6? more negative than equilibrium values in highly productive pools. Comparison of ostracode and host water isotope signals permits assessment of the life span of the aquatic environments. Valves from dead ostracodes collected from ephemeral ponds and lakes show a wide scatter with each sample providing a snapshot of the seasonal history of the host water. The presence of the stream species Ilyocypris ramirezi and a wide range of ostracode isotope values suggest that ephemeral ponds and lakes are fed by streams during spring run-off and seasonally dry. A temporary character is also indicated by Heterocypris incongruens, a drought-resistant species that occupies most springs and seeps. In addition, Limnocythere rionegroensis has adjusted its reproduction strategies to its environment. Whereas only females were collected in fresh host waters, males were found in ephemeral ponds and lakes with higher solute content. Sexual reproduction seems to be the more successful reproduction strategy in high and variable salinities and seasonal droughts. The temporary character of the aquatic environments shows that the availability of meteoric water controls the life span of host waters and underlines the sensitivity of the area to changes in precipitation.

Surface sediment samples from several fore-arc basins west and southwest of the Indonesian Archipelago, analyzed by planktonic foraminifera, stable oxygen and carbon isotopic signals and opal and CaCO3 contents in bulk sediment

A total of 69 surface sediment samples from several fore-arc basins located west and southwest of the Indonesian Archipelago was analyzed with respect to the faunal composition of planktonic foraminifera, the stable oxygen and carbon isotopic signal of a surface-dwelling (Globigerinoides ruber) and a thermocline-dwelling (Neogloboquadrina dutertrei) species, and the opal and CaCO3 contents in bulk sediment. Our results show that the distribution pattern of opal in surface sediments corresponds well to the upwelling-induced chlorophyll concentration in the upper water column and thus, represents a reliable proxy for marine productivity in the coastal upwelling area off S and SW Indonesia. Present-day oceanography and marine productivity are also reflected in the tropical to subtropical and upwelling assemblages of planktonic foraminifera in the surface sediments, which in part differ from previous studies in this region probably due to different coring methods and dissolution effects. The average stable oxygen isotopic values (d18O) of G. ruber in surface sediments vary between 2.9 per mill and 3.2 per mill from basin to basin and correspond to the oceanographic settings during the SE monsoon (July-October) off west Sumatra, whereas off southern Indonesia, they reflect the NW monsoon (December-March) or annual average conditions. The d18O values of N. dutertrei show a stronger interbasinal variation between 1.6 per mill and 2.2 per mill and correspond to the upper thermocline hydrology in July-October. In addition, the difference between the shell carbon isotopic values (d13C) of G. ruber and N. dutertrei (Delta d13C) appears to be an appropriate productivity recorder only in the non-upwelling areas off west Sumatra. Consequently, joint interpretation of the isotopic values of these species is distinctive for different fore-arc basins W and SW of Indonesia and should be considered in paleoceanographic studies.

Isotopic composition of water in fog, rain, throughfall and stemflow in the Monte Verde, Costa Rica

Fog deposition, precipitation, throughfall and stemflow were measured in a windward tropical montane cloud forest near Monteverde, Costa Rica, for a 65-day period during the dry season of 2003. Net fog deposition was measured directly using the eddy covariance (EC) method and it amounted to 1.2 ± 0.1 mm/day (mean ± standard error). Fog water deposition was 5-9% of incident rainfall for the entire period, which is at the low end of previously reported values. Stable isotope concentrations (d18O and d2H) were determined in a large number of samples of each water component. Mass balance-based estimates of fog deposition were 1.0 ± 0.3 and 5.0 ± 2.7 mm/day (mean ± SE) when d18O and d2H were used as tracer, respectively. Comparisons between direct fog deposition measurements and the results of the mass balance model using d18O as a tracer indicated that the latter might be a good tool to estimate fog deposition in the absence of direct measurement under many (but not all) conditions. At 506 mm, measured water inputs over the 65 days (fog plus rain) fell short by 46 mm compared to the canopy output of 552 mm (throughfall, stemflow and interception evaporation). This discrepancy is attributed to the underestimation of rainfall during conditions of high wind.

Signals of resilience to ocean change: high thermal tolerance of early stage Antarctic sea urchins (Sterechinus neumayeri) reared under present-day and future pCO2 and temperature

We tested the hypothesis that development of the Antarctic urchin Sterechinus neumayeri under future ocean conditions of warming and acidification would incur physiological costs, reducing the tolerance of a secondary stressor. The aim of this study is twofold: (1) quantify current austral spring temperature and pH near sea urchin habitat at Cape Evans in McMurdo Sound, Antarctica and (2) spawn S. neumayeri in the laboratory and raise early developmental stages (EDSs) under ambient (-0.7 °C; 400 µatm pCO2) and future (+2.6 °C; 650 and 1,000 µatm pCO2) ocean conditions and expose four EDSs (blastula, gastrula, prism, and 4-arm echinopluteus) to a one hour acute heat stress and assess survivorship. Results of field data from 2011 to 2012 show extremely stable inter-annual pH conditions ranging from 7.99 to 8.08, suggesting that future ocean acidification will drastically alter the pH-seascape for S. neumayeri. In the laboratory, S. neumayeri EDSs appear to be tolerant of temperatures and pCO2 levels above their current habitat conditions. EDSs survived acute heat exposures >20 °C above habitat temperatures of -1.9 °C. No pCO2 effect was observed for EDSs reared at -0.7 °C. When reared at +2.6 °C, small but significant pCO2 effects were observed at the blastula and prism stage, suggesting that multiple stressors are more detrimental than single stressors. While surprisingly tolerant overall, blastulae were the most sensitive stage to ocean warming and acidification. We conclude that S. neumayeri may be unexpectedly physiologically tolerant of future ocean conditions.

Abundance patterns and isotopic signals of morphotypes of Globigerinoides ruber

The chemical composition of shells of the planktonic foraminifer Globigerinoides ruber (white) is frequently used to determine past sea surface conditions. Recently, it has been shown that arbitrarily defined morphotypes within this species exhibit different chemical and isotopic signatures. Here, we investigate the occurrence through time and in space of morphological types of G. ruber (white) in late Quaternary and Holocene sediments of the central and the eastern Mediterranean Sea. In 115 samples representing two distinct time intervals (MIS 1-2 and MIS 9-12) at ODP Site 964 and the piston core GeoTü-SL96, we have defined three morphological types within this species and determined their relative abundances and stable isotopic composition. A quantitative analysis of morphological variation within G. ruber (white) in four samples revealed that the subjectively defined morphotypes occupy separate segments of a continuous and homogenous morphospace. We further show that the abundance of the morphotypes changes significantly between glacials and interglacials and that the three morphotypes of G. ruber show significant offsets in their stable isotopic composition. These offsets are consistent within glacial and interglacial stages but their sign is systematically reversed between the two Sites. Since the isotopic shifts among the three G. ruber morphotypes are systematic and often exceed 1per mil, their understanding is essential for the interpretation of all G. ruber-based proxy records for the paleoceanographic development of the Mediterranean during the late Quaternary.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The electroencephalograph (EEG) signal is one of the most widely used signals in the biomedicine field due to its rich information about human tasks. This research study describes a new approach based on i) build reference models from a set of time series, based on the analysis of the events that they contain, is suitable for domains where the relevant information is concentrated in specific regions of the time series, known as events. In order to deal with events, each event is characterized by a set of attributes. ii) Discrete wavelet transform to the EEG data in order to extract temporal information in the form of changes in the frequency domain over time- that is they are able to extract non-stationary signals embedded in the noisy background of the human brain. The performance of the model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The focus of this chapter is to study feature extraction and pattern classification methods from two medical areas, Stabilometry and Electroencephalography (EEG). Stabilometry is the branch of medicine responsible for examining balance in human beings. Balance and dizziness disorders are probably two of the most common illnesses that physicians have to deal with. In Stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods are known as events. In this chapter, two feature extraction schemes have been developed to identify and characterise the events in Stabilometry and EEG signals. Based on these extracted features, an Adaptive Fuzzy Inference Neural network has been applied for classification of Stabilometry and EEG signals.

A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.

Quantitative evaluation of artifact removal in real magnetoencephalogram signals with blind source separation

The magnetoencephalogram (MEG) is contaminated with undesired signals, which are called artifacts. Some of the most important ones are the cardiac and the ocular artifacts (CA and OA, respectively), and the power line noise (PLN). Blind source separation (BSS) has been used to reduce the influence of the artifacts in the data. There is a plethora of BSS-based artifact removal approaches, but few comparative analyses. In this study, MEG background activity from 26 subjects was processed with five widespread BSS (AMUSE, SOBI, JADE, extended Infomax, and FastICA) and one constrained BSS (cBSS) techniques. Then, the ability of several combinations of BSS algorithm, epoch length, and artifact detection metric to automatically reduce the CA, OA, and PLN were quantified with objective criteria. The results pinpointed to cBSS as a very suitable approach to remove the CA. Additionally, a combination of AMUSE or SOBI and artifact detection metrics based on entropy or power criteria decreased the OA. Finally, the PLN was reduced by means of a spectral metric. These findings confirm the utility of BSS to help in the artifact removal for MEG background activity.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

Analysis and design of multirate synchronous sampling schemes for sparse multiband signals

We consider the problem of developing efficient sampling schemes for multiband sparse signals. Previous results on multicoset sampling implementations that lead to universal sampling patterns (which guarantee perfect reconstruction), are based on a set of appropriate interleaved analog to digital converters, all of them operating at the same sampling frequency. In this paper we propose an alternative multirate synchronous implementation of multicoset codes, that is, all the analog to digital converters in the sampling scheme operate at different sampling frequencies, without need of introducing any delay. The interleaving is achieved through the usage of different rates, whose sum is significantly lower than the Nyquist rate of the multiband signal. To obtain universal patterns the sampling matrix is formulated and analyzed. Appropriate choices of the parameters, that is the block length and the sampling rates, are also proposed.