IMPROVING IRRIGATION WATER ALLOCATION EFFICIENCY USING ALTERNATIVE POLICY OPTIONS IN EGYPT

This study provides an empirical perspective on alternative irrigation policies for allocating limited water to agricultural production in Egypt. Positive mathematical programming is used for model calibration. Three policy options for Egypt are tested: water pricing, water complementary input factor taxes, and output taxes. The results of the research show that: 1) water pricing needs to be much higher than the recovery cost in order to be effective in limiting irrigation water use; 2) at a higher tax rate, fertilizer and energy taxes are effective in reducing the irrigation water demand while maintaining adequate welfare levels; 3) a pesticide tax is less effective than fertilizer or energy taxes; and 4) an output tax on sugar cane and rice would decrease irrigation water demand substantially while allocating land to other crops which are less water intensive and have higher market values.Resource /Energy Economics and Policy,

Strategic Policy Options to Improve Irrigation Water Allocation Efficiency: Analysis on Egypt and Morocco

For a number of reasons government the world over have been unwilling to use water pricing to achieve water use efficiency. This research addresses questions of what policy alternatives to water pricing might improve irrigation water allocation efficiency. An empirical framework is provided to compare irrigation policies for allocating scarce water to agricultural production in Egypt and Morocco. Partial equilibrium agricultural sector models specific to Egypt and Morocco were employed for policy tests. Positive Mathematical Programming (PMP) was used to calibrate the models. Water pricing policy, water complementary input factor tax policy, and output tax policy are tested. Results suggest that effective policy depends on the social, economic, and environmental contexts of specific regions. The results for both countries demonstrate that some of the alternative irrigation policies can work towards directing cropping decisions to less water intensive crops and also generating revenues for governments in situations where governments choose not to price water.Resource /Energy Economics and Policy,

Some investigations into non passive listening

Our knowledge of the function of the auditory nervous system is based upon a wealth of data obtained, for the most part, in anaesthetised animals. More recently, it has been generally acknowledged that factors such as attention profoundly modulate the activity of sensory systems and this can take place at many levels of processing. Imaging studies, in particular, have revealed the greater activation of auditory areas and areas outside of sensory processing areas when attending to a stimulus. We present here a brief review of the consequences of such non-passive listening and go on to describe some of the experiments we are conducting to investigate them. In imaging studies, using fMRI, we can demonstrate the activation of attention networks that are non-specific to the sensory modality as well as greater and different activation of the areas of the supra-temporal plane that includes primary and secondary auditory areas. The profuse descending connections of the auditory system seem likely to be part of the mechanisms subserving attention to sound. These are generally thought to be largely inactivated by anaesthesia. However, we have been able to demonstrate that even in an anaesthetised preparation, removing the descending control from the cortex leads to quite profound changes in the temporal patterns of activation by sounds in thalamus and inferior colliculus. Some of these effects seem to be specific to the ear of stimulation and affect interaural processing. To bridge these observations we are developing an awake behaving preparation involving freely moving animals in which it will be possible to investigate the effects of consciousness (by contrasting awake and anaesthetized), passive and active listening

Conducting Polymers and Corrosion III. A Scanning Vibrating Electrode Study of Poly(3-octyl pyrrole) on Steel and Aluminum

Electroactive conducting polymers (ECPs) continue to be of considerable interest as components of corrosion-resistant coating systems. ECPs, in addition to being conductive, are redox active materials, typically with potentials that are positive of iron and aluminum. Thus, as with chromate, interesting and potentially beneficial interactions of ECPs with active metal alloys such as steel and aluminum are anticipated. In this work, the scanning vibrating electrode technique (SVET), also known as the current density probe, was used to probe such interactions between a poly(3-octyl pyrrole) coating (POP) and cold-rolled steel and aluminum (Al 2024-T3) substrates. The POP coatings were scribed to simulate a defect through the coating to the metal substrate surface. The SVET was used to map the current flowing in and around the defect while the sample was immersed in either 3% NaCl (steel) or in dilute Harrison solution (aluminum), an aqueous solution consisting of 0.35% (NH4)2SO4, 0.05% NaCl. Although there were significant differences in the behavior of the POP-coated steel and POP-coated aluminum substrates, both exhibited a significant delay before the onset of any observable current compared to uncoated or epoxy-coated samples. Current density maps for the steel clearly indicate that the reduction reaction occurred on the conducting polymer surface, with oxidation confined to the defect. Current density maps for the aluminum alloy never displayed significant oxidation at the defect. Rather, reduction (after a significant delay) occurred at the defect as well as across the polymer surface, with concomitant localized undercoating oxidation of the aluminum substrate

In situ growth of SnO2 on graphene nanosheets as advanced anode materials for rechargeable lithium batteries

Graphene with a single layer of carbon atoms densely packed in a honeycomb crystal lattice is one of attractive materials for the intercalation of lithium ion, but it has low volumetric capacity owing to low tap density. We report a method for in situ growth of SnO2 on graphene nanosheets (SGN) as anode materials for rechargeable lithium batteries. The results indicated that the SnO2 nanoparticles with size in the range of 5-10 nm and a polycrystalline structure are homogeneously supported on graphene nanosheets. The charge and discharge capacities of SGN attained to 1559.7 and 779.7 mAh/g in the first cycle at a current density of 300 mA/g. The specific discharge capacities remained at 620 mAh⋅g-1 in the 200th cycle. The SGN exhibits a superior Listorage performance with good cycle life and high capacity

Control of Lipid Metabolism by Adipocyte FGFR1-mediated Adipohepatic Communication During Hepatic Stress

Background: Endocrine FGF19 and FGF21 exert their effects on metabolic homeostasis through fibroblast growth factor receptor (FGFR) and co-factor betaKlotho (KLB). Ileal FGF19 regulates bile acid metabolism through specifically FGFR4-KLB in hepatocytes where FGFR1 is not significant. Both FGF19 and FGF21 activate FGFR1-KLB whose function predominates in adipocytes. Recent studies using administration of FGF19 and FGF21 and genetic ablation of KLB or adipocyte FGFR1 indicate that FGFR1-KLB mediates the response of adipocytes to both FGF21 and FGF19. Here we show that adipose FGFR1 regulates lipid metabolism through direct effect on adipose tissue and indirect effects on liver under starvation conditions that cause hepatic stress. Methods: We employed adipocyte-specific ablations of FGFR1 and FGFR2 genes in mice, and analyzed metabolic consequences in adipose tissue, liver and systemic parameters under normal, fasting and starvation conditions. Results: Under normal conditions, the ablation of adipose FGFR1 had little effect on adipocytes, but caused shifts in expression of hepatic genes involved in lipid metabolism. Starvation conditions precipitated a concurrent elevation of serum triglycerides and non-esterified fatty acids, and increased hepatic steatosis and adipose lipolysis in the FGFR1-deficient mice. Little effect on glucose or ketone bodies due to the FGFR1 deficiency was observed. Conclusions: Our results suggest an adipocyte-hepatocyte communication network mediated by adipocyte FGFR1 that concurrently dampens hepatic lipogenesis and adipocyte lipolysis. We propose that this serves overall to mete out and extend lipid reserves for neural fuels (glucose and ketone bodies), while at the same time governing extent of hepatosteatosis during metabolic extremes and other conditions causing hepatic stress

Effectiveness and Safety of COPD Maintenance Therapy with Tiotropium/Olodaterol versus LABA/ICS in a US Claims Database

Malaltia pulmonar obstructiva crònica; Corticosteroides; OlodaterolEnfermedad pulmonar obstructiva crónica; Corticosteroides; OlodaterolChronic obstructive pulmonary disease; Corticosteroids; OlodaterolIntroduction In patients with chronic obstructive pulmonary disease (COPD), treatment with long-acting muscarinic antagonist (LAMA)/long-acting β2-agonist (LABA) combination therapy significantly improves lung function versus LABA/inhaled corticosteroid (ICS). To investigate whether LAMA/LABA could provide better clinical outcomes than LABA/ICS, this non-interventional database study assessed the risk of COPD exacerbations, pneumonia, and escalation to triple therapy in patients with COPD initiating maintenance therapy with tiotropium/olodaterol versus any LABA/ICS combination. Methods Administrative healthcare claims and laboratory results data from the US HealthCore Integrated Research DatabaseSM were evaluated for patients with COPD initiating tiotropium/olodaterol versus LABA/ICS treatment (January 2013–March 2019). Patients were aged at least 40 years with a diagnosis of COPD (but not asthma) at cohort entry. A Cox proportional hazard regression model was used (as-treated analysis) to assess risk of COPD exacerbation, community-acquired pneumonia, and escalation to triple therapy, both individually and as a combined risk of any one of these events. Potential imbalance of confounding factors between cohorts was handled using fine stratification, reweighting, and trimming by exposure propensity score (high-dimensional); subgroup analyses were conducted on the basis of blood eosinophil levels and exacerbation history. Results The total population consisted of 61,985 patients (tiotropium/olodaterol n = 2684; LABA/ICS n = 59,301); after reweighting, the total was 42,953 patients (tiotropium/olodaterol n = 2600; LABA/ICS n = 40,353; mean age 65 years; female 54.5%). Patients treated with tiotropium/olodaterol versus LABA/ICS experienced a reduction in the risk of COPD exacerbations (adjusted hazard ratio 0.76 [95% confidence interval 0.68, 0.85]), pneumonia (0.74 [0.57, 0.97]), escalation to triple therapy (0.22 [0.19, 0.26]), and any one of these events (0.45 [0.41, 0.49]); the combined risk was similar irrespective of baseline eosinophils and exacerbation history. Conclusions In patients with COPD, tiotropium/olodaterol was associated with a lower risk of COPD exacerbations, pneumonia, and escalation to triple therapy versus LABA/ICS, both individually and in combination; the combined risk was reduced irrespective of baseline eosinophils or exacerbation history.Support for this project and the journal’s Open Access Fee were funded by Boehringer Ingelheim International GmbH. No Rapid Service Fee was received by the journal for the publication of this article

Leveraging ChatGPT in pharmacovigilance event extraction : an empirical study

With the advent of large language models (LLMs), there has been growing interest in exploring their potential for medical applications. This research aims to investigate the ability of LLMs, specifically ChatGPT, in the context of pharmacovigilance event extraction, of which the main goal is to identify and extract adverse events or potential therapeutic events from textual medical sources. We conduct extensive experiments to assess the performance of ChatGPT in the pharmacovigilance event extraction task, employing various prompts and demonstration selection strategies. The findings demonstrate that while ChatGPT demonstrates reasonable performance with appropriate demonstration selection strategies, it still falls short compared to fully fine-tuned small models. Additionally, we explore the potential of leveraging ChatGPT for data augmentation. However, our investigation reveals that the inclusion of synthesized data into fine-tuning may lead to a decrease in performance, possibly attributed to noise in the ChatGPT-generated labels. To mitigate this, we explore different filtering strategies and find that, with the proper approach, more stable performance can be achieved, although constant improvement remains elusive