Antiretroviral drug resistance mutations in naïve and experienced patients in Shiraz, Iran, 2014

Resistance to antiretroviral agents is a significant concern in the clinical management of HIV-infected individuals, particularly in areas of the world where treatment options are limited. In this study, we aimed to identify HIV drug-resistance-associated mutations in 40 drug-naïve patients and 62 patients under antiretroviral therapy (ART) referred to the Shiraz HIV/AIDS Research Center – the first such data available for the south of Iran. HIV reverse transcriptase and protease genes were amplified and sequenced to determine subtypes and antiretroviral- resistance-associated mutations (RAMs). Subtype CRF35-AD recombinant was the most prevalent in all patients (98 of 102, 96 % ), followed by subtype A1, and subtype B (one each, 2 % ). Among the 40 ART-naïve patients, two mutations associated with nucleoside reverse transcriptase inhibitor (NRTI) resistance (two with Y115F and T215I) and three associated with non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance (two with G190S and Y181C, four with V179T) were found. Among ART-experienced patients, four mutations associated with resistance to NRTI, four with NNRTI, and five with protease inhibitors (PI) were found. Twenty patients with high levels of resistance were already on second-line therapy. We document for the first time in this region of Iran high levels of ART resistance to multiple drugs. Our findings call for more vigilant systematic ART resistance surveillance, increased resistance testing, careful management of patients with existing regimens, and strong advocacy for expansion of available drugs in Iran. © 2016, Springer-Verlag Wien

Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages

Due to the harmful effects and depletion of non-renewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively

Temperature dependent thermal conductivity of magnetocaloric materials: impact assessment on the performance of active magnetic regenerative refrigerators

Due to the dynamic nature of the active magnetic regenerative mechanism in magnetocaloric refrigeration, the thermal conductivity of the refrigerant is a critical parameter. Experimental studies have shown how the thermal conductivity of high-performance magnetic refrigerants can drastically change around their Curie temperatures (TC). However, this fact has been largely ignored in the numerical simulation of devices, raising the need to assess the impact of this approximation, particularly when the simulations are aimed at optimizing or dimensioning a particular device geometry. In this paper we show how, by employing a unidimensional numerical model of a magnetic refrigerator with parallel plates, two different temperature dependent thermal conductivity scenarios of the refrigerant affect the resulting temperature span and cooling power. By considering a gadolinium-like material as the refrigerant with thermal conductivities varying 50% near its TC, a change of the resulting device temperature span of  ∼15% is reached. The cooling power is also affected, changing also  ∼15% when the considered systems are at half their respective maximum temperature span. Our results are also discussed in terms of other geometries where the impact of these effects can be even larger, namely in cases where the axial thermal conduction in the AMR element is not negligible, or the time-scale of longitudinal thermal processes has a larger impact on the optimum operating frequency.publishe

Differentiation between Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissue for Treatment Response Assessment using Multi-Scale Texture Analysis of CT Images

Background: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreas cancer with a high mortality rate and its staging is highly dependent on the extent of involvement between the tumor and surrounding vessels, facilitating treatment response assessment in PDAC. Objective: This study aims at detecting and visualizing the tumor region and the surrounding vessels in PDAC CT scan since, despite the tumors in other abdominal organs, clear detection of PDAC is highly difficult. Material and Methods: This retrospective study consists of three stages: 1) a patch-based algorithm for differentiation between tumor region and healthy tissue using multi-scale texture analysis along with L1-SVM (Support Vector Machine) classifier, 2) a voting-based approach, developed on a standard logistic function, to mitigate false detections, and 3) 3D visualization of the tumor and the surrounding vessels using ITK-SNAP software. Results: The results demonstrate that multi-scale texture analysis strikes a balance between recall and precision in tumor and healthy tissue differentiation with an overall accuracy of 0.78±0.12 and a sensitivity of 0.90±0.09 in PDAC. Conclusion: Multi-scale texture analysis using statistical and wavelet-based features along with L1-SVM can be employed to differentiate between healthy and pancreatic tissues. Besides, 3D visualization of the tumor region and surrounding vessels can facilitate the assessment of treatment response in PDAC. However, the 3D visualization software must be further developed for integrating with clinical applications

Climate System Ontology: A Formal Specification of the Complex Climate System

Modeling the climate system requires a formal representation of the characteristics of the system elements and the processes that change them. The Climate System Ontology (CSO) represents the semantics of the processes that continuously cause change at component and system levels. The CSO domain ontology logically represents various links that relate the nodes in this complex network. It models changes in the radiative balance caused by human activities and other forcings as solar energy flows through the system. CSO formally expresses various processes, including non-linear feedbacks and cycles, that change the compositional, structural, and behavioral characteristics of system components. By reusing the foundational logic of a set of top- and mid-level ontologies, we have modeled complex concepts such as hydrological cycle, forcing, greenhouse effect, feedback, and climate change in the ontology. This coherent, publicly available ontology can be queried to reveal the input and output of processes that directly impact the system elements and causal chains that bring change to the whole system. Our description of best practices in ontology development and explanation of the logics that underlie the extended upper-level ontologies help climate scientists to design interoperable domain and application ontologies, and share and reuse semantically rich climate data

Enhancement of physical and reaction to fire properties of crude glycerol polyurethane foams filled with expanded graphite

The reation to fire of polyurethane foams (PUFs) has been a subject of increasing relevance, so in this study the reaction to fire performance of PUFs derived from crude glycerol (CG) has been improved using expanded graphite (EG). The influence of different loadings of EG on the physical–mechanical properties of composite foams has been assessed and the results obtained show that it has significant positive impact. Moreover, the reaction to fire of the PUF and EG/PUF composites has been investigated and the results obtained showed that the fire behavior of composite foams containing as little as 5 wt% of EG are significantly improved. Indeed a dramatic reduction of the rate of heat release, mass loss rate, effective heat of combustion and specific extinction area, has been observed even for a relative low amount of EG. Likewise, the use of Infrared Thermography as a function of time has proven that, when EG is used, the combustion stops suddenly and the temperature drops sharply compared with the behavior of the unfilled PUF sample, which suggests that EG acts like a flame extinguisher. The results obtained have proven the suitability of CG for the production of PUFs and that the addition of EG considerably improves the reaction to fire of composite foams.publishe

Investigation the integration of heliostat solar receiver to gas and combined cycles by energy, exergy, and economic point of views

Due to the high amount of natural gas resources in Iran, the gas cycle as one of the main important power production system is used to produce electricity. The gas cycle has some disadvantages such as power consumption of air compressors, which is a major part of gas turbine electrical production and a considerable reduction in electrical power production by increasing the environment temperature due to a reduction in air density and constant volumetric airflow through a gas cycle. To overcome these weaknesses, several methods are applied such as cooling the inlet air of the system by different methods and integration heat recovery steam generator (HRSG) with the gas cycle. In this paper, using a heliostat solar receiver (HSR) in gas and combined cycles are investigated by energy, exergy, and economic analyses in Tehran city. The heliostat solar receiver is used to heat the pressurized exhaust air from the air compressor in gas and combined cycles. The key parameter of the three mentioned analyses was calculated and compared by writing computer code in MATLAB software. Results showed the use of HSR in gas and combined cycles increase the annual average energy efficiency from 28.4% and 48.5% to 44% and 76.5%, respectively. Additionally, for exergy efficiency, these increases are from 29.2% and 49.8% to 45.2% and 78.5%, respectively. However, from an economic point of view, adding the HRSG increases the payback period (PP) and it decreases the net present value (NPV) and internal rate of return (IRR)