2,345 research outputs found
Potential Iimpacts of a Turkish EU-membership on Agri-food Markets
This paper examines possible impacts of a Turkish accession to the EU on the agricultural markets in Turkey and the EU. AGMEMOD, an econometric, dynamic, multi-market, partial equilibrium economic model for EU agriculture at Member State level, has been extended with a model for the Turkish agricultural sector and afterwards applied to gain quantitative insights into Turkish accession effects.
To establish a model for Turkey, the implementation of the model equations required parameter estimates, or the specification of synthetic model parameters. A database with time series on Turkish agricultural production, market balances and prices, macroeconomic variables and policy variables was developed in order to estimate such model parameters and to build an operational Turkish agriculture sector model.
Most results show that the dominant impact of the Turkish accession on Turkish agriculture is a reduction of domestic producer prices, which induces further market effects. The ¿ mostly decoupled ¿ CAP support payments will induce smaller incentives to increase production than those which Turkish farmers receive prior to the EU accession. In Turkey effects of accession to the EU will be mostly negative for crop producers (except for tobacco), whereas the consumers are expected to gain from lower market prices. In contrast, producers of sheep meat, broiler and dairy milk could gain from an accession due to lower feed costs.JRC.J.4-Agriculture and Life Sciences in the Econom
Regression discontinuity designs in health: a systematic review
Background:
Regression discontinuity designs are non-randomized study designs that permit strong causal inference with relatively weak assumptions. Interest in these designs is growing but there is limited knowledge of the extent of their application in health. We aimed to conduct a comprehensive systematic review of the use of regression discontinuity designs in health research.
Methods:
We included studies that used regression discontinuity designs to investigate the physical or mental health outcomes of any interventions or exposures in any populations. We searched 32 health, social science, and grey literature databases (1 January 1960-1 January 2019). We critically appraised studies using eight criteria adapted from the What Works Clearinghouse Standards for regression discontinuity designs. We conducted a narrative synthesis, analyzing the forcing variables and threshold rules used in each study.
Results:
The literature search retrieved 7658 records, producing 325 studies that met the inclusion criteria. A broad range of health topics were represented. The forcing variables used to implement the design were age; socioeconomic measures; date or time of exposure or implementation; environmental measures such as air quality; geographic location; and clinical measures that act as a threshold for treatment. Twelve percent of the studies fully met the eight quality appraisal criteria. Fifteen percent of studies reported a pre-specified primary outcome or study protocol.
Conclusions:
This systematic review demonstrates that regression discontinuity designs have been widely applied in health research and could be used more widely still. Shortcomings in study quality and reporting suggest that the potential benefits of this method have not yet been fully realized
Intergroup helping in response to separatism
Despite its prevalence and widespread media coverage, separatism as a phenomenon is barely covered in psychological investigations, and the majority's response to separatism has been completely ignored. We present two studies in which we investigated the notion that separatist movements threaten the continuation of the national identity, as well as the nation's economic position. Moreover, we hypothesized and found that members of the majority group respond to continuation threat by supporting government measures to help the separatist group. Javanese students who were induced to believe that existing separatist movements in West Papua (Study 1, N = 322) or Aceh (Study 2, N = 180) were currently increasing their efforts to gain independence were more willing to support these groups than participants who believed these movements were dormant. Moreover, this effect was mediated by continuation threat but not economic threat. These results demonstrate the possibility of a peaceful response to separatism threat. © 2013 by the Society for Personality and Social Psychology, Inc
Preservation of renal endothelial integrity and reduction of renal edema by aprotinin does not preserve renal perfusion and function following experimental cardiopulmonary bypass.
Gut bacterial deamination of residual levodopa medication for Parkinson's disease
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by both motor and non-motor symptoms. Gastrointestinal tract dysfunction is one of the non-motor features, where constipation is reported as the most common gastrointestinal symptom. Aromatic bacterial metabolites are attracting considerable attention due to their impact on gut homeostasis and host's physiology. In particular, Clostridium sporogenes is a key contributor to the production of these bioactive metabolites in the human gut. RESULTS: Here, we show that C. sporogenes deaminates levodopa, the main treatment in Parkinson's disease, and identify the aromatic aminotransferase responsible for the initiation of the deamination pathway. The deaminated metabolite from levodopa, 3-(3,4-dihydroxyphenyl)propionic acid, elicits an inhibitory effect on ileal motility in an ex vivo model. We detected 3-(3,4-dihydroxyphenyl)propionic acid in fecal samples of Parkinson's disease patients on levodopa medication and found that this metabolite is actively produced by the gut microbiota in those stool samples. CONCLUSIONS: Levodopa is deaminated by the gut bacterium C. sporogenes producing a metabolite that inhibits ileal motility ex vivo. Overall, this study underpins the importance of the metabolic pathways of the gut microbiome involved in drug metabolism not only to preserve drug effectiveness, but also to avoid potential side effects of bacterial breakdown products of the unabsorbed residue of medication
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
We present a novel approach to transcranial ultrasound computed tomography that utilizes normalizing flows to improve the speed of imaging and provide Bayesian uncertainty quantification. Our method combines physics-informed methods and data-driven methods to accelerate the reconstruction of the final image. We make use of a physics-informed summary statistic to incorporate the known ultrasound physics with the goal of compressing large incoming observations. This compression enables efficient training of the normalizing flow and standardizes the size of the data regardless of imaging configurations. The combinations of these methods results in fast uncertainty-aware image reconstruction that generalizes to a variety of transducer configurations. We evaluate our approach with in silico experiments and demonstrate that it can significantly improve the imaging speed while quantifying uncertainty. We validate the quality of our image reconstructions by comparing against the traditional physics-only method and also verify that our provided uncertainty is calibrated with the error
The hepatoadrenal syndrome: A common yet unrecognized clinical condition
Objective: Adrenal failure is common in critically ill patients, particularly those with sepsis. As liver failure and sepsis are both associated with increased circulating levels of endotoxin and proinflammatory mediators and reduced levels of apoprotein-1/ high-density lipoprotein, we postulated that adrenal failure may be common in patients with liver disease. Design: Clinical study. Setting: Liver transplant intensive care unit. Patients: The study cohort included 340 patients with liver disease. Interventions: Based on preliminary observational data, all patients admitted to our 28-bed liver transplant intensive care unit (LTICU) undergo adrenal function testing. An honest broker system was used to extract clinical, hemodynamic, medication, and laboratory data on patients admitted to the LTICU from March 2002 to March 2004. A random (stress) cortisol level <20 μg/dL in a highly stressed patient (respiratory failure, hypotension) was used to diagnose adrenal insufficiency. In all other patients, a random cortisol level <15 μg/dL or a 30-min level <20 μg/dL post-low-dose (1 μg) cosyntropin was considered diagnostic of adrenal insufficiency. Patients were grouped as follows: a) chronic liver failure; b) fulminant hepatic failure; c) patients immediately status post-orthotopic liver transplantation receiving a steroid-free protocol of immunosuppression; and d) patients status post-remote liver transplant (≥6 months). The decision to treat patients with stress doses of hydrocortisone was at the discretion of the treating intensivist and transplant surgeon. Measurements and Main Results: Two-hundred and forty-five (72%) patients met our criteria for adrenal insufficiency (the hepatoadrenal syndrome). Eight (33%) patients with fulminant hepatic failure, 97 (66%) patients with chronic liver disease, 31(61%) patients with a remote history of liver transplantation, and 109 (92%) patients who had undergone liver transplantation under steroid-free immunosuppression were diagnosed with adrenal insufficiency. The high-density lipoprotein level at the time of adrenal testing was the only variable predictive of adrenal insufficiency (p < .0001). In vasopressor-dependent patients with adrenal insufficiency, treatment with hydrocortisone was associated with a significant reduction (p = .02) in the dose of norepinephrine at 24 hrs, whereas the dose of norepinephrine was significantly higher (p = .04) in those patients with adrenal failure not treated with hydrocortisone. In vasopressor-dependent patients without adrenal insufficiency, treatment with hydrocortisone did not affect vasopressor dose at 24 hrs. One hundred and forty-one patients (26.4%) died during their hospitalization. The baseline serum cortisol was 18.8 ± 16.2 μg/dL in the nonsurvivors compared with 13.0 ± 11.8 μg/dL in the survivors (p < .001). Of those patients with adrenal failure who were treated with glucocorticoids, the mortality rate was 26% compared with 46% (p = .002) in those who were not treated. In those patients receiving vasopressor agents at the time of adrenal testing, the baseline cortisol was 10.0 ± 4.8 μg/dL in those with adrenal insufficiency compared with 35.6 ± 21.2 μg/dL in those with normal adrenal function. Vasopressor-dependent patients who did not have adrenal failure had a mortality rate of 75%. Conclusions: Patients with liver failure and patients post-liver transplantation have an exceedingly high incidence of adrenal failure, which may be pathophysiologically related to low levels of high-density lipoprotein. Treatment of patients with adrenal failure may improve outcome. High baseline serum cortisol levels may be a maker of disease severity and portend a poor prognosis. Copyright © 2005 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins
Voices of girls with disabilities in rural Iran
This paper investigates the interaction of gender, disability and education in rural Iran, which is a relatively unexplored field of research. The responses of 10 female students with disabilities from Isfahan indicated that the obstacles they faced included marginalization, difficulties in getting from home to school, difficulties within the school building itself, and discrimination by teachers, classmates and school authorities. The data collected for the study contain a wide range of conservative gendered discourses, and show how traditional gender beliefs interact with disability to aggravate the problems faced in education by young women with disabilities. It is hoped that the findings will raise awareness among policy-makers of the many formidable obstacles that make it difficult for young women with disabilities to achieve their full potential in education
Gendered Representations of Male and Female Social Actors in Iranian Educational Materials
This research investigates the representations of gendered social actors within the subversionary discourse of equal educational opportunities for males and females in Iranian English as a Foreign Language (EFL) books. Using critical discourse analysis (CDA) as the theoretical framework, the authors blend van Leeuwen’s (Texts and practices: Readings in critical discourse analysis, Routledge, London, 2003) ‘Social Actor Network Model’ and Sunderland’s (Gendered discourses, Palgrave Macmillan, Hampshire, 2004) ‘Gendered Discourses Model’ in order to examine the depictions of male and female social actors within this gendered discourse. The gendered discourse of equal opportunities was buttressed by such representations within a tight perspective in proportion to gender ideologies prevailing in Iran. Resorting to CDA, we can claim that resistance against such gendered discourse in Iranian EFL textbooks militates against such gender norms. These representations of male and female social actors in school books are indicative of an all-encompassing education, reinforcing that the discourse of equal opportunities is yet to be realized in the education system of Iran
Photoacoustic imaging with conditional priors from normalizing flows
For many ill-posed inverse problems, such as photoacoustic imaging, the uncer- tainty of the solution is highly affected by measurement noise and data incompleteness (due, for example, to limited aperture). For these problems, the choice of prior information is a crucial aspect of a computationally effective solution scheme. We propose a regularization scheme for photoacoustic imaging that leverages prior information learned by a generative network. We train conditional normalizing flows on pairs of photoacoustic sources (the unknowns of the problem) and the associated data in order to exploit the posterior distribution of the solution. The learned prior is combined with physics-based optimization (enforced by partial differential equations), according to the deep prior framework, in order to achieve robustness with respect to out-of-distribution data. Numerical evidence suggests the superiority of this approach with respect to non-conditional deep priors, and the ability to retrieve features of the unknowns that are typically challenging for limited-view photoacoustics
- …