Three Shades of Embeddedness, State Capitalism as the Informal Economy, Emic Notions of the Anti-Market, and Counterfeit Garments in the Mauritian Export Processing Zone

Purpose This paper furthers the analysis of patterns regulating capitalist accumulation based on a historical anthropology of economic activities revolving around and within the Mauritian Export Processing Zone (EPZ). Design/methodology/approach This paper uses fieldwork in Mauritius to interrogate and critique two important concepts in contemporary social theory – “embeddedness” and “the informal economy.” These are viewed in the wider frame of social anthropology’s engagement with (neoliberal) capitalism. Findings A process-oriented revision of Polanyi’s work on embeddedness and the “double movement” is proposed to help us situate EPZs within ongoing power struggles found throughout the history of capitalism. This helps us to challenge the notion of economic informality as supplied by Hart and others. Social implications Scholars and policymakers have tended to see economic informality as a force from below, able to disrupt the legal-rational nature of capitalism as practiced from on high. Similarly, there is a view that a precapitalist embeddedness, a “human economy,” has many good things to offer. However, this paper shows that the practices of the state and multinational capitalism, in EPZs and elsewhere, exactly match the practices that are envisioned as the cure to the pitfalls of capitalism. Value of the paper Setting aside the formal-informal distinction in favor of a process-oriented analysis of embeddedness allows us better to understand the shifting struggles among the state, capital, and labor.

Characterization and differentiation of body fluids, putrefaction fluid, and blood using Hounsfield unit in postmortem CT

The purpose of the present study was to evaluate the ranges of Hounsfield unit (HU) found in body fluids, putrefaction fluids, and blood on postmortem CT and how these ranges are affected by postmortem interval, temperatures, and CT beam energy. Body fluids, putrefaction fluids, and blood from a total of 53 corpses were analyzed to determine the ranges of HU values from postmortem CT images that were taken prior to autopsy. The fluids measured in CT images were obtained at autopsy and examined in terms of macroscopic and microscopic appearances. Body fluids and blood were also collected in plastic bottles, which were subjected to CT scans at different beam energies (80-130 kV) and at various fluid temperatures (4 to 40 °C). At a postmortem interval of 1 to 4 days, the ranges of HU values of the serous fluids (13-38 HU) and the nonsedimented blood (40-88 HU) did not overlap. In the sedimented blood, the upper serum layer exhibited HU value ranges that overlapped with those of the serous fluids. The putrefaction fluids exhibited a range of HU values between 80 and -130 HU. Elevated HU values were observed in fluids with accretive cell impurities. HU values decreased slightly with increasing temperature and CT beam energy. We concluded that serous fluids and blood in fresh corpses can be characterized and differentiated from each other based on HU value ranges. In contrast, body fluids in decomposed corpses cannot be differentiated by their HU value ranges. Different beam energies and corpse temperatures had only minor influences on HU value ranges and therefore should not be obstacles to the differentiation and characterization of body fluids and blood.

Added value of dual-energy computed tomography versus single-energy computed tomography in assessing ferromagnetic properties of ballistic projectiles: implications for magnetic resonance imaging of gunshot victims.

OBJECTIVE The objective of this study was to assess the discriminative power of dual-energy computed tomography (DECT) versus single-energy CT (SECT) to distinguish between ferromagnetic and non-ferromagnetic ballistic projectiles to improve safety regarding magnetic resonance (MR) imaging studies in patients with retained projectiles. MATERIALS AND METHODS Twenty-seven ballistic projectiles including 25 bullets (diameter, 3-15 mm) and 2 shotgun pellets (2 mm each) were examined in an anthropomorphic chest phantom using 128-section dual-source CT. Data acquisition was performed with tube voltages set at 80, 100, 120, and 140 kV(p). Two readers independently assessed CT numbers of the projectile's core on images reconstructed with an extended CT scale. Dual-energy indices (DEIs) were calculated from both 80-/140-kV(p) and 100-/140-kV(p) pairs; receiver operating characteristics curves were fitted to assess ferromagnetic properties by means of CT numbers and DEI. RESULTS Nine (33%) of the projectiles were ferromagnetic; 18 were nonferromagnetic (67%). Interreader and intrareader correlations of CT number measurements were excellent (intraclass correlation coefficients, >0.906; P<0.001). The DEI calculated from both 80/140 and 100/140 kV(p) were significantly (P<0.05) different between the ferromagnetic and non-ferromagnetic projectiles. The area under the curve (AUC) was 0.75 and 0.8 for the tube voltage pairs of 80/140 and 100/140 kV(p) (P<0.05; 95% confidence interval, 0.57-0.94 and 0.62-0.97, respectively) to differentiate between the ferromagnetic and non-ferromagnetic ballistic projectiles; which increased to 0.83 and 0.85 when shotgun pellets were excluded from the analysis. The AUC for SECT was 0.69 and 0.73 (80 and 100 kV[p], respectively). CONCLUSIONS Measurements of DECT combined with an extended CT scale allow for the discrimination of projectiles with non-ferromagnetic from those with ferromagnetic properties in an anthropomorphic chest phantom with a higher AUC compared with SECT. This study indicates that DECT may have the potential to contribute to MR safety and allow for MR imaging of patients with retained projectiles. However, further studies are necessary before this concept may be used to triage clinical patients before MR.

Diagnostic Performance and Additional Value of Elastosonography in Focal Breast Lesions: Statistical Correlation between Size-Dependant Strain Index Measurements, Multimodality-BI-RADS Score, and Histopathology in a Clinical Routine Setting

Objective. To evaluate the diagnostic benefit of real-time elastography (RTE) in clinical routine. Strain indices (SI) for benign and malignant tumors were assessed. Methods. 100 patients with 110 focal breast lesions were retrieved. Patients had mammography (MG), ultrasound (US), and, if necessary, MRI. RTE was conducted after ultrasound. Lesions were assessed with BI-RADS for mammography and ultrasound. Diagnosis was established with histology or follow-up. Results. SI for BI-RADS 2 was 1.71 ± 0.86. Higher SI (2.21 ± 1.96) was observed for BI-RADS 3 lesions. SI of BI-RADS 4 and 5 lesions were significantly higher (16.92 ± 20.89) and (19.54 ± 10.41). 31 malignant tumors exhibited an average SI of 16.13 ± 14.67; SI of benign lesions was 5.29 ± 11.87 (P value <0.0001). ROC analysis threshold was >3.8 for malignant disease. Sensitivity of sonography was 90.3% (specificity 78.5%). RTE showed a sensitivity of 87.1% (specificity 79.7%). Accuracy of all modalities combined was 96.8%. In BI-RADS 3 lesions RTE was able to detect all malignant lesions (sensitivity 100%, specificity 92.9%, and accuracy 93.9%). Conclusions. RTE increased sensitivity and specificity for breast cancer detection when used in combination with ultrasound.

Amino Acid Export in Developing Arabidopsis Seeds Depends on UmamiT Facilitators

Essential amino acids cannot be synthesized by humans and animals. They often are limiting in plant-derived foods and determine the nutritional value of a given diet [1]. Seeds and fruits often represent the harvestable portion of plants. In order to improve the amino acid composition of these tissues, it is indispensable to understand how these substrates are transported within the plant. Amino acids result from nitrogen assimilation, which often occurs in leaves, the source tissue. They are transported via the vasculature, the xylem, and the phloem into the seeds, the so-called sink tissue, where they are stored or consumed. In seeds, several tissues are symplasmically isolated [2, 3], i.e., not connected by plasmodesmata, channels in the cell walls that enable a cytoplasmic continuum in plants [4]. Consequently, amino acids must be exported from cells into the apoplast and re-imported many times to support seed development. Several amino acid importers are known, but exporters remained elusive [5, 6]. Here, we characterize four members of the plant-specific UmamiT transporter family from Arabidopsis, related to the amino acid facilitator SIAR1 and the vacuolar auxin transporter WAT1 [7, 8]. We show that the proteins transport amino acids along their (electro)chemical potential across the plasma membrane. In seeds, they are found in tissues from which amino acids are exported. Loss-of-function mutants accumulate high levels of free amino acids in fruits and produce smaller seeds. Our results strongly suggest a crucial role for the UmamiTs in amino acid export and possibly a means to improve yield quality.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

Impact of a communication strategy on family satisfaction in the intensive care unit.

BACKGROUND Family satisfaction of critically ill patients has gained increased interest as important indicator to evaluate the quality of care in the intensive care unit (ICU). The family satisfaction in the ICU questionnaire (FS-ICU 24) is a well-established tool to assess satisfaction in such settings. We tested the hypothesis that an intervention, aiming at improved communication between health professionals and patients' next of kin in the ICU improves family satisfaction, as assessed by FS-ICU 24. METHODS Using a multicenter before-and-after study design, we evaluated medium-term effectiveness of VALUE, a recently proposed strategy aiming at improved communication. Satisfaction was assessed using the FS-ICU 24 questionnaire. Performance-importance plots were generated in order to identify items highly correlated with overall satisfaction but with low individual score. RESULTS A total of 163 completed family questionnaires in the pre-intervention and 118 in the post-intervention period were analyzed. Following the intervention, we observed: (1) a non-significant increase in family satisfaction summary score and sub-scores; (2) no decline in any individual family satisfaction item, and (3) improvement in items with high overall impact on satisfaction but quoted with low degree of satisfaction. CONCLUSION No significant improvement in family satisfaction of critically ill adult patients could be found after implementing the VALUE strategy. Whether these results are due to insufficient training of the new strategy or a missing effect of the strategy in our socio-economic environment remains to be shown.

The Export Insurance System and Export Supply of Britain

This paper examines whether or not the export insurance subsidy provided by the British government has promoted Britain.s export supply. Unlike previous studies on the effectiveness of export subsidy in export supply, the current study examines the stationarity nature of the concerned variables. The unit root tests show that all concerned variables are integrated of order one. According to Johansen cointegration test, the concerned variables are not cointegrated. The empirical evidences using the first differenced data show that the export subsidy in terms of provision of export insurances by the government is not statistically significant in increasing export supply.

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.

A time-slice study in Heinrich Stadial 1 and Mid Holocene sediment cores off northern Senegal

Sediment dynamics in limnic, fluvial and marine environments can be assessed by granulometric and rock-magnetic methodologies. While classical grain-size analysis by sieving or settling mainly bears information on composition and transport, the magnetic mineral assemblages reflect to a larger extent the petrology and weathering conditions in the sediment source areas. Here, we combine both methods to investigate Late Quaternary marine sediments from five cores along a transect across the continental slope off Senegal. This region near the modern summer Intertropical Convergence Zone is particularly sensitive to climate change and receives sediments from several aeolian, fluvial and marine sources. From each of the investigated five GeoB sediment cores (494-2956 m water depth) two time slices were processed which represent contrasting climatic conditions: the arid Heinrich Stadial 1 (~ 15 kyr BP) and the humid Mid Holocene (~ 6 kyr BP). Each sediment sample was split into 16 grain-size fractions ranging from 1.6 to 500 µm. Concentration and grain-size indicative magnetic parameters (susceptibility, SIRM, HIRM, ARM and ARM/IRM) were determined at room temperature for each of these fractions. The joint consideration of whole sediment and magnetic mineral grain-size distributions allows to address several important issues: (i) distinction of two aeolian sediment fractions, one carried by the north-easterly trade winds (40-63 µm) and the other by the overlying easterly Harmattan wind (10-20 µm) as well as a fluvial fraction assigned to the Senegal River (< 10 µm); (ii) identification of three terrigenous sediment source areas: southern Sahara and Sahel dust (low fine-grained magnetite amounts and a comparatively high haematite content), dust from Senegalese coastal dunes (intermediate fine-grained magnetite and haematite contents) and soils from the upper reaches of the Senegal River (high fine-grained magnetite content); (iii) detection of partial diagenetic dissolution of fine magnetite particles as a function of organic input and shore distance; (iv) analysis of magnetic properties of marine carbonates dominating the grain-size fractions 63-500 µm.

Low-molecular-weight hydrocarbon concentrations, organic carbon contents, and Rock-Eval pyrolysis hydrogen indices at DSDP Holes 75-530A and 75-532

A series of C2-C8 hydrocarbons (including saturated, aromatic, and olefinic compounds) from deep-frozen core samples taken during DSDP Leg 75 (Holes 530A and 532) were analyzed by a combined hydrogen-stripping/thermovaporization method. Concentrations representing both hydrocarbons dissolved in the pore water and adsorbed on the mineral surfaces vary in Hole 530A from about 10 to 15,000 ng/g of dry sediment weight depending on the lithology (organic-carbon-lean calcareous oozes versus "black shales"). Likewise, the organic-carbon-normalized C2-C8 hydrocarbon concentrations vary from 3,500 to 93,100 ng/g Corg, reflecting drastic differences in the hydrogen contents and hence the hydrocarbon potential of the kerogens. The highest concentrations measured of nearly 10**5 ng/g Corg are about two orders of magnitude below those usually encountered in Type-II kerogen-bearing source beds in the main phase of petroleum generation. Therefore, it was concluded that Hole 530A sediments, even at 1100 m depth, are in an early stage of evolution. The corresponding data from Hole 532 indicated lower amounts (3,000-9,000 ng/g Corg), which is in accordance with the shallow burial depth and immaturity of these Pliocene/late Miocene sediments. Significant changes in the light hydrocarbon composition with depth were attributed either to changes in kerogen type or to maturity related effects. Redistribution pheonomena, possibly the result of diffusion, were recognized only sporadically in Hole 530A, where several organic-carbon lean samples were enriched by migrated gaseous hydrocarbons. The core samples from Hole 530A were found to be severely contaminated by large quantities of acetone, which is routinely used as a solvent during sampling procedures on board Glomar Challenger.

Carbon, hydrocarbon and alkenone composition and indices of ODP Hole 167-1016C sediments

Total organic carbon (TOC) and calcium carbonate (CaCO3) concentrations were determined for 304 samples, and biomarkers were analyzed for 101 samples from Core 167-1016C-1H. TOC varies between 1% and 2%, and CaCO3 is typically 1%-4%, with peaks reaching 14%. Paleotemperature estimated from Uk'37 varies from 8.5° to 17.5°C. The Uk'37 variation implies that Core 167-1016C-1H covers oxygen isotope Stages 1-6. Peaks of diatom-derived C25:1 HBI alkene concentrations occur during warming intervals, suggesting intensified upwelling during deglaciation. The concentrations of haptophyte-derived alkenones and diatom-derived C25:1 HBI alkene vary out of phase, which presumably resulted from the changes in the mode of nutrient supply to surface mixed layer. Maximal CaCO3 contents (>10%) were observed in both warming and cooling intervals. The peak in cooling interval relates to an alkenone maximum, whereas the peaks in warming intervals do not. This implies that carbonate production is not the only factor controlling carbonate compensation depth at this site, and it suggests considering the changes in North Pacific deep-water chemistry. Petroleum-type compounds are present in Site 1016 sediments. Their concentrations are maximized in the warming intervals that correspond to the timing of destruction of a huge tar mound off Point Conception. The tarry material was presumably transported by the Arguello Fan system to Site 1016.