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New selective therapeutics are needed for the treatment of hepatocellular carcinoma (HCC), the 7th most common cancer. In this study, we compared the cytotoxic effect induced by the release of pH-dependent iron nanoparticles from nitrogen-doped graphene-coated mixed iron oxide nanoparticles (FexOy/N-GN) with the cytotoxic effect of nitrogen-doped graphene (N-GN) and commercial graphene nanoflakes (GN) in Hepatoma G2 (HepG2) cells and healthy cells. The cytotoxic effect of nanocomposites (2.5–100 ug/ml) on HepG2 and healthy fibroblast (BJ) cells (12–48 h) was measured by Cell Viability assay, and the half maximal inhibitory concentration (IC50) was calculated. After the shortest (12 h) and longest incubation (48 h) incubation periods in HepG2 cells, IC50 values of FexOy/N-GN were calculated as 21.95 to 2.11 µg.mL−1, IC50 values of N-GN were calculated as 39.64 to 26.47 µg.mL−1 and IC50 values of GN were calculated as 49.94 to 29.94, respectively. After 48 h, FexOy/N-GN showed a selectivity index (SI) of 10.80 for HepG2/BJ cells, exceeding the SI of N-GN (1.27) by about 8.5-fold. The high cytotoxicity of FexOy/N-GN was caused by the fact that liver cancer cells have many transferrin receptors and time-dependent pH changes in their microenvironment increase iron release. This indicates the potential of FexOy/N-GN as a new selective therapeutic. [ABSTRACT FROM AUTHOR]

Determination of proximate characteristics can be achieved using conventional analyses methods that require a certain amount of time. In cement factories, refuse-derived fuel (RDF) is continuously fed to a kiln by a conveyor belt, so even if an inappropriate proximate characteristic is determined, it would be too late to prevent the feeding of RDF to the kiln. To overcome this problem, there is a need for instant measurement of the proximate characteristics (moisture, volatile matter, ash) that enables the feeding to be stopped. In such cases, the deep learning (DL) is a useful method based on the prediction of proximate characteristics. Therefore, in this study, the aim is to estimate the mentioned parameters developed by near-infrared spectroscopy (NIR) combined with deep learning models. For this purpose, the spectrographic measurements taken from RDF samples with an NIR spectrometer, and the results of proximate analysis in a laboratory, were used together as a dataset. A fully convolutional neural network (FCNN) and ResNet were used as a network, and they were trained using images of RDF samples and proximate analysis values. The FCNN model was more successful in prediction studies. According to the FCNN model, the results show that the models in the study can predict the moisture, ash, and volatile matter content of RDF with satisfactory R2 values between 0.979, 0.983, and 0.952. [ABSTRACT FROM AUTHOR]

In this study, pyrolysis of low-density polyethylene (LDPE) and LDPE with aluminum (C/LDPE) wastes was carried out with different heating rates (5, 10, 20 °C/min) at different temperatures (400, 600, 800 °C). Product yields of LDPE and C/LDPE wastes were compared, and optimum liquid products were analyzed to utilize as commercial waxes for future use. The properties of pyrolyzed wastes was investigated with proximate, elemental analysis, and TGA. The as-produced liquid from pyrolysis of wastes was characterized by different characteristic tools, such as elemental analyses, GC-MS analyses, 1H-NMR tests, FT-IR spectra, the density, melting point, and carbon residue to compare commercial waxes. As a result of pyrolysis, the highest liquid product yield was achieved at 800 °C with 5 °C/min heating rate (85.87%) and at 600 °C with 5 °C/min heating rate (71.3%) for LDPE and C/LDPE, respectively. The results indicated that the derived liquid products are similar to commercial heavy wax. [ABSTRACT FROM AUTHOR]

An energy audit was realized for a building group located on a university campus to measure the environmental sustainability and efficient usage of natural resources. As a result of energy audit, exterior insulation and double-glazing application were came to the front for energy-saving options. Although energy audit provides energy-saving options as output, it is not enough to provide information about how environmental impacts will change if the defined options are used. To determine the improvements in terms of environmental indicators, these options were assessed with life cycle assessment (LCA). LCA was realized for 50 years life span for 1 m3 of the building. CML-IA method was used to conduct LCA analyses. Ecovalue08 was applied as a monetary weighting method since the used CML-IA method has no weighting function. Results show that there are significant improvements (> 5%) on ADPff (11–12.5%) and GWP100 (8.5–9.7%) impacts provided by both of the energy-saving options. Additionally, double glazing would provide a 10.5% improvement on ODP. On the other hand, the exterior insulation application would increase the ODP value of EB by 34%. The impact category of GWP100 is found as the most dominant impact according to Ecovalue08. The ranking of the other impact categories from higher to lower value is HTP, ADPff, and AP. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) landfill leachate is a highly contaminated liquid effluent. Leachate has a complex nature that needs to be appropriately treated before being discharged into the environment. There are various options for leachate treatment. Deciding which option should be applied is a complex process, since it depends on many factors that need to provide a balance between the technical, economic, and environmental aspects of sustainability. Multi-criteria decision-making (MCDM) methods are useful techniques to solve complex problems that cannot be easily solved. In this study, MCDM techniques are used for an evaluation of four different leachate treatment options: recirculation of leachate to a landfill site (A1), combined treatment with municipal wastewater (A2), anaerobic and aerobic sequential treatment (A3), and advanced leachate treatment based on membrane processes (A4). The selection of the most appropriate one, based on the criteria, analytic network process (ANP), and preference ranking organization method for enrichment evaluations (PROMETHEE) methods, was applied as MCDM techniques using the Super Decisions software and D-Sight software, respectively. Both the ANP and the PROMETHEE analysis results demonstrate that option A2 is the most appropriate for all of the decision-makers. [ABSTRACT FROM AUTHOR]

The aim of this study was to remediate lead (Pb), cadmium (Cd) and zinc (Zn) from contaminated soil and stabilize to pyrolysis solid product. To accomplish this, phytoremediation of soil contaminated with Pb, Cd and Zn by different plants (sunflower, corn and rape) was performed with and without ethylenediaminetetraacetic acid (EDTA). According to phytoremediation results, rape was the most effective plant with 72 %, 76 % and 77 % removal efficiency for Pb, Cd and Zn, respectively. Also, EDTA addition had no significant effect on translocation of the metals from roots to stems. According to pyrolysis results, Pb, Cd and Zn in the contaminated plants were stabilized in the ash/char fraction. In addition, the solid product can be safely landfilled as inert waste since its toxicity leaching value is lower than the limit values given in the Turkish Regulation on Landfilling of Wastes. [ABSTRACT FROM AUTHOR]

The main focus of this study was quality improvement of solid product obtained from tire-derived fuel (TDF) pyrolysis to use it as a substitute for commercial carbon blacks. First of all, TDF samples were analyzed by means of proximate and ultimate analysis, heating value, X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. They were then pyrolyzed at a 400 °C pyrolysis temperature with 5 °C/min heating rate. After that, a two-stage improvement was performed on solid product to reduce its sulfur and ash content to that of commercial carbon black. As a result of this improvement process, the sulfur and ash content of the solid product was reduced to 0.22 and 0.27 % from 1.71 and 12.14 %, respectively. In addition, the XRD, SEM, atomic force microscopy, Brunauer-Emmett-Teller surface area, oil adsorption number and ICP-MS/MS analyses were performed for all products. The results were compared with different commercial carbon blacks. It was determined that the properties of the improved products were similar to those of commercial carbon blacks. These results suggest that improved pyrolytic product of TDF can be used as a raw material by industries such as tire, plastic and paint manufacturing. [ABSTRACT FROM AUTHOR]

We have aimed at characterizing top soil samples taken in-situ from five different locations of the unregulated dumping site in Eskişehir/Turkey for a period of six months. The study is the first attempt in the city and in Turkey, regarding particularly the SPME (Solid Phase Microextraction Technique) analysis method utilized. A comprehensive research has been conducted to produce critical soil data to be used for indicating current risks as well as the urgency of rehabilitating the site and establishing a sanitary landfill in the site. Conventional physicochemical analytical methods and SPME technique were used to analyze the samples. Physicochemical analyses were performed for determining the pH, total dried matter, volatile matter, total nitrogen, phosphorus, macro elements and heavy metals. Meteorological data were also recorded for the same period. SPSS.10.0 statistical program was used to determine the correlation between meteorological data and physicochemical analysis results. Mean values were used in the correlation analyses. These data indicated that the air temperature and precipitation have significant effects on soil characteristics. SPME, coupled with GC/MS, was used to identify eighty six volatile and semi-volatile organic compounds contained in soil samples. The samples were extracted by headspace SPME with heating (δHS-SPME). SPME analyses were conducted using a commercially available polydimethylsiloxane/divinylbenzene (PDMS/DVB) fiber having a film thickness of 65 μm (Supelco) as a capture medium. The experimentally optimized headspace sampling conditions were arranged (15 min. at 50˚C) before a 30 min. sampling period. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate extensively the characterization and identification of major pollutant parameters by paying attention to the organic chemical pollution for unregulated dumping site leachate in Eskişehir/Turkey. The study that is first and only one research has been very important data related with before new sanitary landfill site in Eskişehir city. For this purpose, in this study leachate samples were collected in-situ at monthly interval for a period of 8 months. Firstly, thirty three physicochemical parameters were monitored. Secondly, SPME technique was used for identification of organic pollutants. Meteorological data were also recorded for the same sampling period to correlate meteorological data and physicochemical parameters. Mean values are used in the correlation analysis. Correlation is shown only for the relationship between air temperature and NO3 −. No correlation has been found between rain and leachate quality parameters since the amount of rain was very low during the sampling period. However, analysis results were generally decreased in winter season when each parameter and each sampling point are examined separately. According to correlation between every parameter, especially solid content and dissolved oxygen concentration of leachate is affecting to other parameters. Also, sodium and potassium are changing proportionally with same parameters (suspended solids, fixed solids, dissolved oxygen) and high correlation between chloride and heavy metal concentration is showing. The results were statistically evaluated by use of SPSS 10.0 program. Second part of the study, the leachate was extracted by Solid Phase Microextraction (SPME) technique and then analyzed. Of the methodologies tested in this study, the best one selected was based on 100 μ m polydimethylsiloxane coated fiber (PDMS), headspace with heating (Δ HS) sampling mode and an extraction time of 15 min. at a temperature of 50 o C. Thirty three organic compounds in leachate were identified by GC/MS. [ABSTRACT FROM AUTHOR]