Adenosine negatively regulates duodenal motility in mice: role of A1 and A2a receptors .

BACKGROUND AND PURPOSE: Adenosine is considered to be an important modulator of intestinal motility. This study was undertaken to investigate the role of adenosine in the modulation of contractility in the mouse duodenum and to characterize the adenosine receptor subtypes involved. EXPERIMENTAL APPROACH: RT-PCR was used to investigate the expression of mRNA encoding for A(1), A(2A), A(2B) and A(3) receptors. Contractile activity was examined in vitro as changes in isometric tension. KEY RESULTS: In mouse duodenum, all four classes of adenosine receptors were expressed, with the A(2B) receptor subtype being confined to the mucosal layer. Adenosine caused relaxation of mouse longitudinal duodenal muscle; this was antagonized by the A(1) receptor antagonist and mimicked by N(6)-cyclopentyladenosine (CPA), selective A(1) agonist. The relaxation induced by A(1) receptor activation was insensitive to tetrodotoxin (TTX) or N(ω)-nitro-l-arginine methyl ester (l-NAME). Adenosine also inhibited cholinergic contractions evoked by neural stimulation, effect reversed by the A(1) receptor antagonist, but not myogenic contractions induced by carbachol. CPA and 2-p-(2-carboxyethyl) phenethylamino-5′-N-ethylcarboxamidoadenosine hydrochloride hydrate (CGS-21680), A(2A) receptor agonist, both inhibited the nerve-evoked cholinergic contractions. l-NAME prevented only the CGS-21680-induced effects. S-(4-Nitrobenzyl)-6-thioinosine, a nucleoside uptake inhibitor, reduced the amplitude of nerve-evoked cholinergic contractions, an effect reversed by an A(2A) receptor antagonist or l-NAME. CONCLUSIONS AND IMPLICATIONS: Adenosine can negatively regulate mouse duodenal motility either by activating A(1) inhibitory receptors located post-junctionally or controlling neurotransmitter release via A(1) or A(2A) receptors. Both receptors are available for pharmacological recruitment, even if only A(2A) receptors appear to be preferentially stimulated by endogenous adenosine. LINKED ARTICLE: This article is commented on by Antonioli et al., pp. 1577–1579 of this issue. To view this commentary visit http://dx.doi.org/10.1111/j.1476-5381.2011.01529.

Inattentive Consumers in Markets for Services

In an experiment on markets for services, we find that consumers are likely to stick to default tariffs and achieve suboptimal outcomes. We find that inattention to the task of choosing a better tariff is likely to be a substantial problem in addition to any task and tariff complexity effect. The institutional setup on which we primarily model our experiment is the UK electricity and gas markets, and our conclusion is that the new measures by the UK regulator Ofgem to improve consumer outcomes are likely to be of limited impact

Aggregation and remuneration in Demand-Response with a blockchain-based framework

This paper describes the possibility to use the blockchain technology for load and generation aggregation in a new distributed Demand Response (DR) service and customers remuneration system. The blockchain technology and the use of smart contracts for DR allow the creation of a distributed system in which customers can communicate directly, in a transparent, secure and traceable way, with the grid operator to provide their flexibility. In this paper, the DR problem formulation takes into account several aspects, which are periodically executed. First, the blockchain records customers’ energy consumption or production, then, the smart contract starts calculating the baseline and the potential support provided by each customer to fulfil the requested load adaptation. Customers’ availability for generation and load profile modulation is also taken into account, as well as their privacy and an updated definition of the roles of grid and market operators in a new Demand-Response scenario supported by the blockchain technology. The blockchain used is Hyperledger Fabric, since it turned to be flexible for smart contracts implementation while supporting multi-tenancy. Results show the possibility to successfully apply the blockchain technology to this particular topic, even considering privacy-preserving issues

An Energy Blockchain, a Use Case on Tendermint

The recent advances in distributed energy systems require new models for exchanging energy among prosumers in microgrids. The blockchain technology promises to solve the digital issues related to distributed systems without a trusted authority and to allow quick and secure energy transactions, which are verified and cryptographically protected. Transactions are approved and subsequently recorded on all the machines participating in the blockchain. This work demonstrates how users, which are nodes of the energy and digital networks, exchange energy supported by a customized blockchain based on Tendermint. We focus on the procedures for generating blocks and defining data structures for storing energy transactions

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primarily focused on a single operating condition, they are unable to effectively determine the health condition of turbines, which results in unwanted downtimes. New and reliable strategies for data analysis were incorporated into this research, given the large amount and variety of data. The development of a new model of the temperature of the DFIG bearing versus wind speed to identify false alarms is the key innovation of this work. This research aims to analyze the parameters for condition monitoring of DFIG bearings using SCADA data for k-means clustering training. The variables of k are obtained by the elbow method that revealed three classes of k (k = 0, 1, and 2). Box plot visualization is used to quantify data points. The average rotation speed and average temperature measurement of the DFIG bearings are found to be primary indicators to characterize normal or irregular operating conditions. In order to evaluate the performance of the clustering model, an analysis of the assessment indices is also executed. The ultimate goal of the study is to be able to use SCADA-recorded data to provide advance warning of failures or performance issues

Systematic pathologic findings report of callosciurus finlaysonii (Horsfield, 1823) (rodentia, sciuridae) squirrels from maratea area (south italy) to investigate species-specific pathologies, reliability of co2 euthanasia method, and possible use as environmental sentinels

The aim of the present study was to macroscopically and microscopically describe the main pathological findings occurring in this invasive species, in order to better understand the real risks for naïve animals and humans. The present study was conducted on Callosciurusfinlaysonii squirrels (n = 165), captured in the Maratea area and euthanatized with CO2 according to a population control of invasive species of the Italian Agriculture Ministry project (ex CIPE project) and conferred to the Department of Veterinary Medicine of Bari (Italy). Macroscopic analysis demonstrated heart, lung, and liver congestion, probably due to the euthanasia method, and variable lesions of bowel, liver, and kidney. The microscopically examination showed the presence of lymphocytic infiltration in the lower layers of the bowel, suggesting enteritis. To the best of our knowledge, this is the first systemic report of gross and microscopical anatomopathological lesions in C.finlaysonii, in South Italy. The results could be useful to fill a gap of knowledge of this species in Italy

Performance Improvement of Grid-Integrated Doubly Fed Induction Generator under Asymmetrical and Symmetrical Faults

The doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) suffers from voltage and frequency fluctuations due to the stochastic nature of wind speed as well as nonlinear loads. Moreover, the high penetration of wind energy into the power grid is a challenge for its smooth operation. Hence, symmetrical faults are most intense, inflicting the stator winding to low voltage, disturbing the low-voltage ride-through (LVRT) functionality of a DFIG. The vector control strategy with proportional–integral (PI) controllers was used to control rotor-side converter (RSC) and grid-side converter (GSC) parameters. During a symmetrical fault, however, a series grid-side converter (SGSC) with a shunt injection transformer on the stator side was used to keep the rotor current at an acceptable level in accordance with grid code requirements (GCRs). For the validation of results, the proposed scheme of PI + SGSC is compared with PI and a combination of PI with Dynamic Impedance Fault Current Limiter (DIFCL). The MATLAB simulation results demonstrate that the proposed scheme provides superior performance by providing 77.6% and 20.61% improved performance in rotor current compared to that of PI and PI + DIFCL control schemes for improving the LVRT performance of DFIG

On reminder effects, drop-outs and dominance: evidence from an online experiment on charitable giving

We present the results of an experiment that (a) shows the usefulness of screening out drop-outs and (b) tests whether different methods of payment and reminder intervals affect charitable giving. Following a lab session, participants could make online donations to charity for a total duration of three months. Our procedure justifying the exclusion of drop-outs consists in requiring participants to collect payments in person flexibly and as known in advance and as highlighted to them later. Our interpretation is that participants who failed to collect their positive payments under these circumstances are likely not to satisfy dominance. If we restrict the sample to subjects who did not drop out, but not otherwise, reminders significantly increase the overall amount of charitable giving. We also find that weekly reminders are no more effective than monthly reminders in increasing charitable giving, and that, in our three months duration experiment, standing orders do not increase giving relative to one-off donations