Imipenem resistance in clinical Escherichia coli from Qom, Iran

OBJECTIVE: The emergence of metallo-\u3b2-lactamase-producing Enterobacteriaceae is a worldwide health concern. In this study, the first evaluation of MBL genes, bla IMP and bla VIM , in Escherichia coli resistant to imipenem isolated from urine and blood specimens in Qom, Iran is described. Three hundred urine and blood specimens were analysed to detect the presence of E. coli. Resistance to imipenem and other antimicrobials was determined by disk diffusion and MIC. MBL production was screened using CDDT. PCR was also carried out to determine the presence of bla IMP and bla VIM genes in imipenem-resistant isolates. RESULTS: In total, 160 E. coli isolates were collected from March to May 2016. According to disk diffusion, high-level of resistance (20%) to cefotaxime was observed, whereas the lowest (1%) was detected for tetracycline. In addition, five isolates showed resistance to imipenem with a MIC\u2009 65\u20094 \ub5g/mL. CDDT test confirmed that five isolates were MBL-producing strains, but no bla IMP and bla VIM genes were detected. Results of this study show a very low level of resistance to imipenem in our geographical area

A nearly zero-energy microgrid testbed laboratory: Centralized control strategy based on SCADA system

Currently, despite the use of renewable energy sources (RESs), distribution networks are facing problems, such as complexity and low productivity. Emerging microgrids (MGs) with RESs based on supervisory control and data acquisition (SCADA) are an effective solution to control, manage, and finally deal with these challenges. The development and success of MGs is highly dependent on the use of power electronic interfaces. The use of these interfaces is directly related to the progress of SCADA systems and communication infrastructures. The use of SCADA systems for the control and operation of MGs and active distribution networks promotes productivity and efficiency. This paper presents a real MG case study called the LAMBDA MG testbed laboratory, which has been implemented in the electrical department of the Sapienza University of Rome with a centralized energy management system (CEMS). The real-time results of the SCADA system show that a CEMS can create proper energy balance in a LAMBDA MG testbed and, consequently, minimize the exchange power of the LAMBDA MG and main grid

Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

Antioxidant Effects of Bioactive Glasses (BGs) and Their Significance in Tissue Engineering Strategies

Elevated levels of oxidative stress are usually observed following injuries, leading to impaired tissue repair due to oxidation-related chronic inflammation. Several attempts have been made to manage this unfavorable situation, and the use of biomaterials with antioxidant activity is showing great promise in tissue engineering and regenerative medicine approaches. Bioactive glasses (BGs) are a versatile group of inorganic substances that exhibit an outstanding regenerative capacity for both hard and soft damaged tissues. The chemical composition of BGs provides a great opportunity for imparting specific biological activities to them. On this point, BGs may easily become antioxidant substances through simple physicochemical modifications. For example, particular antioxidant elements (mostly cerium (Ce)) can be added to the basic composition of the glasses. On the other hand, grafting natural antioxidant substances (e.g., polyphenols) on the BG surface is feasible for making antioxidant substitutes with promising results in vitro. Mesoporous BGs (MBGs) were demonstrated to have unique merits compared with melt-derived BGs since they make it possible to load antioxidants and deliver them to the desired locations. However, there are actually limited in vivo experimental studies on the capability of modified BGs for scavenging free radicals (e.g., reactive oxygen species (ROS)). Therefore, more research is required to determine the actual potential of BGs in decreasing oxidative stress and subsequently improving tissue repair and regeneration. The present work aims to highlight the potential of different types of BGs in modulating oxidative stress and subsequently improving tissue healing

Hydroxyapatite Nanoparticles for Improved Cancer Theranostics

Beyond their well-known applications in bone tissue engineering, hydroxyapatite nanoparticles (HAp NPs) have also been showing great promise for improved cancer therapy. The chemical structure of HAp NPs offers excellent possibilities for loading and delivering a broad range of anticancer drugs in a sustained, prolonged, and targeted manner and thus eliciting lower complications than conventional chemotherapeutic strategies. The incorporation of specific therapeutic elements into the basic composition of HAp NPs is another approach, alone or synergistically with drug release, to provide advanced anticancer effects such as the capability to inhibit the growth and metastasis of cancer cells through activating specific cell signaling pathways. HAp NPs can be easily converted to smart anticancer agents by applying different surface modification treatments to facilitate the targeting and killing of cancer cells without significant adverse effects on normal healthy cells. The applications in cancer diagnosis for magnetic and nuclear in vivo imaging are also promising as the detection of solid tumor cells is now achievable by utilizing superparamagnetic HAp NPs. The ongoing research emphasizes the use of HAp NPs in fabricating three-dimensional scaffolds for the treatment of cancerous tissues or organs, promoting the regeneration of healthy tissue after cancer detection and removal. This review provides a summary of HAp NP applications in cancer theranostics, highlighting the current limitations and the challenges ahead for this field to open new avenues for research

Strontium-and cobalt-doped multicomponent mesoporous bioactive glasses (MBGS) for potential use in bone tissue engineering applications

Mesoporous bioactive glasses (MBGs) offer suitable platforms for drug/ion delivery in tissue engineering strategies. The main goal of this study was to prepare strontium (Sr)-and cobalt (Co)-doped MBGs; strontium is currently used in the treatment of osteoporosis, and cobalt is known to exhibit pro-angiogenic effects. Sr-and Co-doped mesoporous glasses were synthesized for the first time in a multicomponent silicate system via the sol-gel method by using P123 as a structure-directing agent. The glassy state of the Sr-and Co-doped materials was confirmed by XRD before immersion in SBF, while an apatite-like layer was detected onto the surface of samples post-immersion. The textural characteristics of MBGs were confirmed by nitrogen adsorption/desorption measurements. In vitro experiments including MTT assay, Alizarin red staining, and cell attachment and migration showed the cytocompatibility of all the samples as well as their positive effects on osteoblast-like cell line MG-63. Early experiments with human umbilical vein endothelial cells also suggested the potential of these MBGs in the context of angiogenesis. In conclusion, the prepared materials were bioactive, showed the ability to improve osteoblast cell function in vitro and could be considered as valuable delivery vehicles for therapeutics, like Co2+ and Sr2+ ions

Modeling of carbon dioxide solubility in ionic liquids based on group method of data handling

Due to industrial development, the volume of carbon dioxide (CO2) is rapidly increasing.. Several techniques have been used to eliminate CO2 from the output gas mixtures. One of these methods is CO2 capturing by ionic liquids (ILs). Computational models for estimating the CO2 solubility in ILS is of utmost importance. In this research, a white box model in the form of a mathematical correlation using the largest data bank in literature is presented by the group method of data handling (GMDH). This research investigates the application of GMDH intelligent method as a powerful computational approach for predicting CO2 solubility in different ionic liquids with temperature lower and upper than 324 K. In this regard, 4726 data points including the solubility of CO2 in 60 ILs were used for model development Moreover, seven different ionic liquids were selected to perform the external test. To evaluate the validity and efficiency of the suggested model, regression analysis was implemented on the actual and estimated target values. As a result, a proper fit between the experimental and predicted data was obtained and presented by various figures and statistical parameters. It is also worth noting that the predicted negative values in the proposed models are considered zero. Also, the results of the established correlation were compared to other proposed models exist in the literature of ionic liquids. The terminal form of the models suggested by GMDH approach and obtained based on temperature are two simple mathematical correlations by exerting input parameters of temperature (T), pressure (P), critical temperature (Tc ), critical pressure (Pc ) and, acentric factor (ω) which does not suffer from the black box property of other neural network algorithms. The model suggested in this work, would be a promising one which can act as an efficient predictor for CO2 solubility estimation in ILs and is capable of being used in different industries

Joint Energy and Reserve Scheduling of a Wind Power Producer in a Peer-to-Peer Mechanism

This paper proposes a risk constrained decision making problem for wind power producers (WPPs) in a competitive environment. In this problem, the WPP copts to maximize its likely profit whereas aggregators want to minimize their payments. So, this bi-level problem is converted to a single level one. Then, the WPP offers proper prices to the aggregators to attract them to supply their demand. Also, these aggregators can procure reserve for the WPP to compensate its uncertainties. Therefore, through a peer-to- peer (P2P) trading mechanism, the WPP requests the aggregators to allocate reserve to cover the uncertainties of the wind generation. Also, due to the presence of uncertain resources of the problem, a risk measurement tool is applied to the problem to control the uncertainties. The effectiveness of the model is assessed on realistic data from the Nordpool market and the results show that as the loads become responsive, more loads are allowed to choose their WPP to supply their load. Also, the reserve that is provided by these responsive loads to the WPP increases.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs

This paper addresses the optimal bidding strategy problem of a virtual power plant (VPP) participating in the dayahead (DA), real-time (RT) and spinning reserve (SR) markets (SRMs). The VPP comprises a number of dispatchable energy resources (DERs), renewable energy resources (RESs), energy storage systems (ESSs) and a number of customers with flexible demand. A two-stage risk-constrained stochastic problem is formulated for the VPP scheduling, where the uncertainty lies in the energy and reserve prices, RESs production, load consumption, as well as calls for reserve services. Based on this model, the VPP bidding/offering strategy in the DA market (DAM), RT market (RTM) and SRM is decided aiming to maximize the VPP profit considering both supply and demandsides (DS) capability for providing reserve services. On the other hand, customers participate in demand response (DR) programs by using load curtailment (LC) and load shifting (LS) options as well as by providing reserve service to minimize their consumption costs. The proposed model is implemented on a test VPP and the optimal decisions are investigated in detail through a numerical study. Numerical simulations demonstrate the effectiveness of the proposed scheduling strategy and its operational advantages and the computational effectiveness.© Institute of Electrical and Electronics Engineers.fi=vertaisarvioitu|en=peerReviewed

The reaction pi N to pi pi N in a meson-exchange approach

A resonance model for two-pion production in the pion-nucleon reaction is developed that includes information obtained in the analysis of pion-nucleon scattering in a meson-exchange model. The baryonic resonances Delta(1232), N*(1440), N*(1520), N*(1535), and N*(1650) are included. The model reproduces the total cross sections up to kinetic energies of the incident pion of 350 MeV and obtains the shapes of the differential cross sections in reasonable agreement with the data.Comment: 7 pages, 7 figures, 2 table