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Watson-Crick base-pairing of DNA allows the nanoscale fabrication of biocompatible synthetic nanostructures for diagnostic and therapeutic biomedical purposes. DNA nanostructure design elicits exquisite control of shape and conformation compared to other nanoparticles. Furthermore, nucleic acid aptamers can be coupled to DNA nanostructures to allow interaction and response to a plethora of biomolecules beyond nucleic acids. When compared to the better-known approach of using protein antibodies for molecular recognition, nucleic acid aptamers are bespoke with the underlying DNA nanostructure backbone and have various other stability, synthesis, and cost advantages. Here, we provide detailed methodologies to synthesize and characterize aptamer-enabled DNA nanostructures. The methods described can be generally applied to various designs of aptamer-enabled DNA nanostructures with a wide range of applications both within and beyond biomedical nanotechnology. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a business-as-usual (BAU) assumption. Therefore, WNMs are used to assess the impact of many events on urban pollution. Recently, different approaches have been implemented to develop WNMs and quantify the lockdown effects of COVID-19 on air quality, including Machine Learning (ML). However, more advanced methods, such as Deep Learning (DL), have never been applied for developing WNMs. In this study, we proposed WNMs based on DL algorithms, aiming to test five DL architectures and compare their performances to a recent ML approach, namely Gradient Boosting Machine (GBM). The concentrations of five air pollutants (CO, NO2, PM2.5, SO2, and O3) are studied in the city of Quito, Ecuador. The results show that Long-Short Term Memory (LSTM) and Bidirectional Recurrent Neural Network (BiRNN) outperform the other algorithms and, consequently, are recommended as appropriate WNMs to quantify the effects of the lockdowns on air pollution. Furthermore, examining the variable importance in the LSTM and BiRNN models, we identify that the most relevant temporal and meteorological features for predicting air quality are Hours (time of day), Index (1 is the first collected data and increases by one after each instance), Julian Day (day of the year), Relative Humidity, Wind Speed, and Solar Radiation. During the full lockdown, the concentration of most pollutants has decreased drastically: −48.75%, for CO, −45.76%, for SO2, −42.17%, for PM2.5, and −63.98%, for NO2. The reduction of this latter gas has induced an increase of O3 by +26.54%.

Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a business-as-usual (BAU) assumption. Therefore, WNMs are used to assess the impact of many events on urban pollution. Recently, different approaches have been implemented to develop WNMs and quantify the lockdown effects of COVID-19 on air quality, including Machine Learning (ML). However, more advanced methods, such as Deep Learning (DL), have never been applied for developing WNMs. In this study, we proposed WNMs based on DL algorithms, aiming to test five DL architectures and compare their performances to a recent ML approach, namely Gradient Boosting Machine (GBM). The concentrations of five air pollutants (CO, NO2, PM2.5, SO2, and O3) are studied in the city of Quito, Ecuador. The results show that Long-Short Term Memory (LSTM) and Bidirectional Recurrent Neural Network (BiRNN) outperform the other algorithms and, consequently, are recommended as appropriate WNMs to quantify the effects of the lockdowns on air pollution. Furthermore, examining the variable importance in the LSTM and BiRNN models, we identify that the most relevant temporal and meteorological features for predicting air quality are Hours (time of day), Index (1 is the first collected data and increases by one after each instance), Julian Day (day of the year), Relative Humidity, Wind Speed, and Solar Radiation. During the full lockdown, the concentration of most pollutants has decreased drastically: −48.75%, for CO, −45.76%, for SO2, −42.17%, for PM2.5, and −63.98%, for NO2. The reduction of this latter gas has induced an increase of O3 by +26.54%.

The concentration peaks of atmospheric pollutants are the most challenging and important phenomena in air quality forecasting. The fact that these elevated levels of pollution do not seem to follow any specific pattern explains why current models still struggle to provide an accurate prediction of these harmful events for human health. The present study tackles this issue by testing several supervised learning methods to discriminate between peak and no peak of concentrations of five contaminants: NO2, CO, SO2, PM2.5, and O3. The classification performance of ensemble decision tree (gradient boosting machine (GBM)) models and ensemble deep learning (EDL) models are compared. The results reveal that the EDL outperforms the GBM model. An analysis of the variable importance (SHapley additive exPlanations (SHAP)) shows that both temporal and meteorological features have an impact on the proposed models. In particular, time of day and wind speed are the most important features to explain the performance of the ensemble DL models.

Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a business-as-usual (BAU) assumption. Therefore, WNMs are used to assess the impact of many events on urban pollution. Recently, different approaches have been implemented to develop WNMs and quantify the lockdown effects of COVID-19 on air quality, including Machine Learning (ML). However, more advanced methods, such as Deep Learning (DL), have never been applied for developing WNMs. In this study, we proposed WNMs based on DL algorithms, aiming to test five DL architectures and compare their performances to a recent ML approach, namely Gradient Boosting Machine (GBM). The concentrations of five air pollutants (CO, NO2, PM2.5, SO2, and O3) are studied in the city of Quito, Ecuador. The results show that Long-Short Term Memory (LSTM) and Bidirectional Recurrent Neural Network (BiRNN) outperform the other algorithms and, consequently, are recommended as appropriate WNMs to quantify the effects of the lockdowns on air pollution. Furthermore, examining the variable importance in the LSTM and BiRNN models, we identify that the most relevant temporal and meteorological features for predicting air quality are Hours (time of day), Index (1 is the first collected data and increases by one after each instance), Julian Day (day of the year), Relative Humidity, Wind Speed, and Solar Radiation. During the full lockdown, the concentration of most pollutants has decreased drastically: −48.75%, for CO, −45.76%, for SO2, −42.17%, for PM2.5, and −63.98%, for NO2. The reduction of this latter gas has induced an increase of O3 by +26.54%.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall - 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall - 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall - 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns.

Killing more than one million people each year, tuberculosis remains the leading cause of death from a single infectious agent. The growing threat of multidrug-resistant strains of Mycobacterium tuberculosis stresses the need for alternative therapies. EthR, a mycobacterial transcriptional regulator, is involved in the control of the bioactivation of the second-line drug ethionamide. We have previously reported the discovery of in vitro nanomolar boosters of ethionamide through fragment-based approaches. In this study, we have further explored the structure-activity and structure-property relationships in this chemical family. By combining structure-based drug design and in vitro evaluation of the compounds, we identified a new oxadiazole compound as the first fragment-based ethionamide booster which proved to be active in vivo, in an acute model of tuberculosis infection., SCOPUS: ar.j, info:eu-repo/semantics/published

This paper investigates current analysis arouse by IASB and Management Commentary Consultative Group (MCCG) affects standard setters and other regulatory bodies on the improvement of management commentary before coming to the Exposure Draft in 2020. Also, the implementing of management commentary is considered whether compulsory or voluntary instruments in different jurisdictions across the border. Since management commentary project is modified and supplemented until half quarter of 2020, the study only takes into account the remarkable discussions related to the revise of management commentary.

This paper investigates current analysis arouse by IASB and Management Commentary Consultative Group (MCCG) affects standard setters and other regulatory bodies on the improvement of management commentary before coming to the Exposure Draft in 2020. Also, the implementing of management commentary is considered whether compulsory or voluntary instruments in different jurisdictions across the border. Since management commentary project is modified and supplemented until half quarter of 2020, the study only takes into account the remarkable discussions related to the revise of management commentary.

The relationship between the properties of fly ash generated during waste incineration and the thermal formation of persistent organic pollutants (POPs), such as polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs), was investigated on two artificial wastes using a laboratory incinerator. Fly ash particles were sampled in the post-combustion zone at approximately 300 degrees C and were characterized with the following complementary techniques: X-ray diffraction (XRD), scanning electron microscopy energy-dispersive X-ray (SEM-EDX), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared (FTIR) spectroscopy. Flue gas samples were collected at the same location and analyzed for Mo-OCDDs, Mo-OCDFs, Tri-DCBs, and Di-OCNs. A strong correlation between fly ash characteristics and waste composition exists for several of the elements considered in this work. For instance, the waste containing the highest levels of Al produced more abundant Al-bearing minerals and elemental Al in the resulting fly ashes. Copper, an especially important POP formation catalyst, was not detected in the top 10 nm surface of fly ash particles but rather occurred within the top 2 pm, indicating that surface copper of catalytic importance for POP formation reactions was not available. Important contributions of ferric iron present in the abundant fly ash-building hematite phase could have also played an important role, especially given its documented contributions in chlorination pathways. Orthogonal projections to latent structures (OPLS) modeling resolved the relationship between fly ash properties and the post-combustion POP formation. These efforts showed that low levels of ash-forming elements (i.e., Na, Mg, Fe, Ti, etc.) were associated with an increase in flue gas S levels, which, in turn, poison the Cl-2 production via the Deacon process. Wastes with depleted levels of fly-ash-building elements should therefore be favored

The thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) is a major problem in waste incineration. Ideally, rather than relying on air cleaning systems and treatment techniques, their formation should be minimized or, if possible eliminated. The work presented in this thesis was conducted to obtain a deeper understanding of the thermal formation of PCDDs, PCDFs, PCBs, and PCNs during incineration using a 5 kW laboratory scale incinerator and two artificial wastes that were designed to reflect regional differences in waste composition. The first part of the thesis focuses on the validation of a recently-developed flue-gas sampling probe with enhanced cooling capabilities. Artifact formation of PCDDs and PCDFs can occur during the sampling of hot flue gases if the cooling is insufficient. The new probe was successfully used to collect samples at 700 °C without biasing the measured POP levels. The thermal formation of PCDDs, PCDFs, PCBs, and PCNs in the post-combustion zone of the incinerator was then studied by collecting flue gas samples at 400 °C, 300 °C, and 200 °C during the incineration of the two artificial wastes. Highly chlorinated POPs were formed in larger quantities when burning the waste with the higher content of metals and chlorine, which suggests that high metal levels in the waste favor the chlorination of less chlorinated POPs or otherwise facilitate the formation of highly chlorinated polyaromatics, possibly via the condensation of highly chlorinated phenols. The concentrations of these pollutants and the abundance of highly chlorinated homologues increased as the flue gas cooled. Fly ash particles play an important role in thermal POP formation by providing essential elements (carbon, chlorine, etc.) and catalytic sites. The chemical and mineralogical properties of fly ash samples were studied by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron M

Two artificial wastes (A and B) whose contents reflect regional differences in municipal solid waste composition, were used to investigate the thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) during incineration. Flue gas samples were simultaneously collected at three ports in the post-combustion zone corresponding to flue gas temperatures of 400, 300, and 200 °C. The combustion of Waste B, which had a higher chlorine and metal content than Waste A, produced greater levels of highly-chlorinated homologues, as demonstrated by a higher degree of chlorination. The total concentrations of PCDDs, PCDFs, PCBs, and PCNs formed in the combustion of both wastes increased as temperature decreased along the convector. There were no significant differences in total concentrations between Waste A and Waste B combustion at specific temperatures, with exception of PCDFs at 400 °C. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) modeling, used to evaluate the data for all compound groups, suggest that during flue gas quenching at temperatures of 400 °C low-chlorinated homologues are preferentially formed in the presence of copper, which is known to be a very active catalyst for this process. At 300 and 200 °C, the formation of highly-chlorinated homologues is favored.

The thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) is a major problem in waste incineration. Ideally, rather than relying on air cleaning systems and treatment techniques, their formation should be minimized or, if possible eliminated. The work presented in this thesis was conducted to obtain a deeper understanding of the thermal formation of PCDDs, PCDFs, PCBs, and PCNs during incineration using a 5 kW laboratory scale incinerator and two artificial wastes that were designed to reflect regional differences in waste composition. The first part of the thesis focuses on the validation of a recently-developed flue-gas sampling probe with enhanced cooling capabilities. Artifact formation of PCDDs and PCDFs can occur during the sampling of hot flue gases if the cooling is insufficient. The new probe was successfully used to collect samples at 700 °C without biasing the measured POP levels. The thermal formation of PCDDs, PCDFs, PCBs, and PCNs in the post-combustion zone of the incinerator was then studied by collecting flue gas samples at 400 °C, 300 °C, and 200 °C during the incineration of the two artificial wastes. Highly chlorinated POPs were formed in larger quantities when burning the waste with the higher content of metals and chlorine, which suggests that high metal levels in the waste favor the chlorination of less chlorinated POPs or otherwise facilitate the formation of highly chlorinated polyaromatics, possibly via the condensation of highly chlorinated phenols. The concentrations of these pollutants and the abundance of highly chlorinated homologues increased as the flue gas cooled. Fly ash particles play an important role in thermal POP formation by providing essential elements (carbon, chlorine, etc.) and catalytic sites. The chemical and mineralogical properties of fly ash samples were studied by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron M

The temporal variation of nematode communities in eight mouth stations of the Mekong River system was investigated in order to compare the change between the dry and the wet season. The nematode data was analysed by multivariate techniques such as SIMPROF, MDS, ANOSIM and SIMPER in the software PRIMER v.6 – PERMANOVA. Our results showed that average dissimi-larity between seasons of the nematode communities in each station was high. Seasonal factor did not affect strongly their distribution pattern. Dominant genera Desmodora and Oncholaimellus usually occurred in the sand stations and Parodontophora and Halalaimus were characteristic for the silty group in both seasons. The spatial variations in this estuarine area have an influence that is larger than seasonal factors., Sự phân bố theo thời gian của quần xã tuyến trùng sống tự do vùng cửa sông Mekong được nghiên cứu nhằm đánh giá sự khác biệt của chúng trong mùa mưa và mùa khô. Dữ liệu của tuyến trùng được xử lý và phân tích đa biến như SIMPROF, MDS, ANOSIM và SIMPER bằng phần mềm PRIMER v.6 – PERMANOVA. Kết quả nghiên cứu cho thấy sự khác biệt theo mùa trong quần xã tuyến trùng tại mỗi điểm là khá lớn nhưng yếu tố mùa không ảnh hưởng gì tới mô hình phân bố của chúng. Một số giống ưu thế trong nền đáy cát như Desmodora and Oncholaimellus trong khi đó Parodontophora và Halalaimus thích nghi nền bùn sét phù sa vẫn hiễn diện trong cả 2 mùa. Kết quả nghiên cứu cũng cho thấy sự biến động trong không gian ở đây lớn hơn sự biến động về mùa vụ.

The temporal variation of nematode communities in eight mouth stations of the Mekong River system was investigated in order to compare the change between the dry and the wet season. The nematode data was analysed by multivariate techniques such as SIMPROF, MDS, ANOSIM and SIMPER in the software PRIMER v.6 – PERMANOVA. Our results showed that average dissimi-larity between seasons of the nematode communities in each station was high. Seasonal factor did not affect strongly their distribution pattern. Dominant genera Desmodora and Oncholaimellus usually occurred in the sand stations and Parodontophora and Halalaimus were characteristic for the silty group in both seasons. The spatial variations in this estuarine area have an influence that is larger than seasonal factors., Sự phân bố theo thời gian của quần xã tuyến trùng sống tự do vùng cửa sông Mekong được nghiên cứu nhằm đánh giá sự khác biệt của chúng trong mùa mưa và mùa khô. Dữ liệu của tuyến trùng được xử lý và phân tích đa biến như SIMPROF, MDS, ANOSIM và SIMPER bằng phần mềm PRIMER v.6 – PERMANOVA. Kết quả nghiên cứu cho thấy sự khác biệt theo mùa trong quần xã tuyến trùng tại mỗi điểm là khá lớn nhưng yếu tố mùa không ảnh hưởng gì tới mô hình phân bố của chúng. Một số giống ưu thế trong nền đáy cát như Desmodora and Oncholaimellus trong khi đó Parodontophora và Halalaimus thích nghi nền bùn sét phù sa vẫn hiễn diện trong cả 2 mùa. Kết quả nghiên cứu cũng cho thấy sự biến động trong không gian ở đây lớn hơn sự biến động về mùa vụ.

The thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) is a major problem in waste incineration. Ideally, rather than relying on air cleaning systems and treatment techniques, their formation should be minimized or, if possible eliminated. The work presented in this thesis was conducted to obtain a deeper understanding of the thermal formation of PCDDs, PCDFs, PCBs, and PCNs during incineration using a 5 kW laboratory scale incinerator and two artificial wastes that were designed to reflect regional differences in waste composition. The first part of the thesis focuses on the validation of a recently-developed flue-gas sampling probe with enhanced cooling capabilities. Artifact formation of PCDDs and PCDFs can occur during the sampling of hot flue gases if the cooling is insufficient. The new probe was successfully used to collect samples at 700 °C without biasing the measured POP levels. The thermal formation of PCDDs, PCDFs, PCBs, and PCNs in the post-combustion zone of the incinerator was then studied by collecting flue gas samples at 400 °C, 300 °C, and 200 °C during the incineration of the two artificial wastes. Highly chlorinated POPs were formed in larger quantities when burning the waste with the higher content of metals and chlorine, which suggests that high metal levels in the waste favor the chlorination of less chlorinated POPs or otherwise facilitate the formation of highly chlorinated polyaromatics, possibly via the condensation of highly chlorinated phenols. The concentrations of these pollutants and the abundance of highly chlorinated homologues increased as the flue gas cooled. Fly ash particles play an important role in thermal POP formation by providing essential elements (carbon, chlorine, etc.) and catalytic sites. The chemical and mineralogical properties of fly ash samples were studied by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron M

The thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) is a major problem in waste incineration. Ideally, rather than relying on air cleaning systems and treatment techniques, their formation should be minimized or, if possible eliminated. The work presented in this thesis was conducted to obtain a deeper understanding of the thermal formation of PCDDs, PCDFs, PCBs, and PCNs during incineration using a 5 kW laboratory scale incinerator and two artificial wastes that were designed to reflect regional differences in waste composition. The first part of the thesis focuses on the validation of a recently-developed flue-gas sampling probe with enhanced cooling capabilities. Artifact formation of PCDDs and PCDFs can occur during the sampling of hot flue gases if the cooling is insufficient. The new probe was successfully used to collect samples at 700 °C without biasing the measured POP levels. The thermal formation of PCDDs, PCDFs, PCBs, and PCNs in the post-combustion zone of the incinerator was then studied by collecting flue gas samples at 400 °C, 300 °C, and 200 °C during the incineration of the two artificial wastes. Highly chlorinated POPs were formed in larger quantities when burning the waste with the higher content of metals and chlorine, which suggests that high metal levels in the waste favor the chlorination of less chlorinated POPs or otherwise facilitate the formation of highly chlorinated polyaromatics, possibly via the condensation of highly chlorinated phenols. The concentrations of these pollutants and the abundance of highly chlorinated homologues increased as the flue gas cooled. Fly ash particles play an important role in thermal POP formation by providing essential elements (carbon, chlorine, etc.) and catalytic sites. The chemical and mineralogical properties of fly ash samples were studied by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron M

The thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) is a major problem in waste incineration. Ideally, rather than relying on air cleaning systems and treatment techniques, their formation should be minimized or, if possible eliminated. The work presented in this thesis was conducted to obtain a deeper understanding of the thermal formation of PCDDs, PCDFs, PCBs, and PCNs during incineration using a 5 kW laboratory scale incinerator and two artificial wastes that were designed to reflect regional differences in waste composition. The first part of the thesis focuses on the validation of a recently-developed flue-gas sampling probe with enhanced cooling capabilities. Artifact formation of PCDDs and PCDFs can occur during the sampling of hot flue gases if the cooling is insufficient. The new probe was successfully used to collect samples at 700 °C without biasing the measured POP levels. The thermal formation of PCDDs, PCDFs, PCBs, and PCNs in the post-combustion zone of the incinerator was then studied by collecting flue gas samples at 400 °C, 300 °C, and 200 °C during the incineration of the two artificial wastes. Highly chlorinated POPs were formed in larger quantities when burning the waste with the higher content of metals and chlorine, which suggests that high metal levels in the waste favor the chlorination of less chlorinated POPs or otherwise facilitate the formation of highly chlorinated polyaromatics, possibly via the condensation of highly chlorinated phenols. The concentrations of these pollutants and the abundance of highly chlorinated homologues increased as the flue gas cooled. Fly ash particles play an important role in thermal POP formation by providing essential elements (carbon, chlorine, etc.) and catalytic sites. The chemical and mineralogical properties of fly ash samples were studied by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron M

In a laboratory-scale combustion reactor, flue-gas samples were collected at two temperatures in the post-combustion zone, 700 °C and 400 °C, using two different water-cooled sampling probes. The probes were the cooled probe described in the European Standard method EN-1948:1, referred to as the original probe, and a modified probe that contained a salt/ice mixture to assist the cooling, referred to as the sub-zero probe. To determine the efficiency of the cooling probes, internal temperature measurements were recorded at 5 cm intervals inside the probes. Flue-gas samples were analyzed for polychlorinated dibenzo-p-dioxin and dibenzofurans (PCDD/Fs). Samples collected at 700 °C using the original cooling probe showed higher concentrations of PCDD/Fs compared to samples collected using the sub-zero probe. No significant differences were observed between samples collected at 400 °C. The results indicated that artifact formation of PCDD/Fs readily occurs during flue-gas sampling at high temperatures if the cooling within the probe is insufficient, as found for the original probe at 700 °C. It was also shown that this problem could be alleviated by using probes with an enhanced cooling capacity, such as the sub-zero probe. Although this may not affect samples collected for regulatory purposes in exit gases, it is of great importance for research conducted in the high-temperature region of the post-combustion zone., Available online 28 April 2012

Fly ashes generated from two artificial wastes were investigated with regard to physicochemical properties of importance for thermal formation of persistent organic pollutants (POPs). The ash samples were collected in the post-combustion zone at approximately 300 °C and were characterized using complementary techniques: X-ray diffraction (XRD), scanning electron microscopy/energy dispersive X-ray (SEM/EDX), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared (FTIR) spectroscopy. The results showed a strong correlation between ash chemistry and waste composition. The waste containing higher levels of Al resulted in more abundant Al-bearing minerals, as well as the element Al, in the fly ash. In the case of Fe, no such correlation was found. Copper, an especially important reaction catalyst, was not detected by in the top 10-nm layer of ash but rather occurred within the top 2-µm, indicating that POPs formation reactions may have depleted the available surface Cu. The possibly inaccessible buried forms of Cu may also be a limiting factor in the production of POPs. Furthermore, organic forms of carbon were present at fly ash surfaces, although not significantly in their chlorinated forms. Taken collectively, these results contribute to understanding the correlations between fly ash chemistry and the thermal formation of POPs.

The relationship between the properties of fly ash generated during waste incineration and the thermal formation of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), biphenyls (PCBs), and naphthalenes (PCNs) was investigated using a laboratory incinerator and two artificial wastes that were designed to reflect regional differences in municipal solid waste composition. Flue gas and fly ash samples were collected isokinetically via a sampling port in the post-combustion zone at a flue gas temperature of 300 °C. The mineralogical properties, morphology and sub-surface composition, surface composition and elemental oxidation states of the fly ash samples were determined. The flue gas samples were analyzed for Mo-OCDDs, Mo-OCDFs, Tri-DCBs, and Di-OCNs. Orthogonal Projections to Latent Structures (OPLS) modeling was used to study the relationship between the properties of the fly ash and the post-combustion formation of polychlorinated aromatics. The presence of high levels of ash-forming elements (i.e. Na, Mg, Fe, Ti, etc…) in the waste reduced the S content of the flue gas and thereby promoted the production of Cl2 via the Deacon process. Because this process is vital for the formation of polyaromatic species, wastes with depleted levels of fly ash-building elements should be favored to minimize the release of toxic PCDDs, PCDFs, PCBs, and PCNs during incineration.

Bakalářská práce se zabývá analýzou nákladů v podniku a návrhem na její zlepšení pomocí bodu zvratu. První část této práce je zaměřena na definici bodu zvratu a jeho vyčíslení. Druhá část práce je zaměřena na realizaci Break even point analýzy v podniku. Výsledky této analýzy pak slouží jako podklad pro nalezení doporučení v oblasti snižování nákladů., Bachelor thesis analyzes the company's costs and its proposals for improvement using a breaking even point. First part of this thesis is focused on BEP definition and its enumeration. Second part is focused on realization of break even point analysis of company. Results of this analysis are used as a basis for finding recommendations for reducing costs.

Bakalářská práce se zabývá analýzou nákladů v podniku a návrhem na její zlepšení pomocí bodu zvratu. První část této práce je zaměřena na definici bodu zvratu a jeho vyčíslení. Druhá část práce je zaměřena na realizaci Break even point analýzy v podniku. Výsledky této analýzy pak slouží jako podklad pro nalezení doporučení v oblasti snižování nákladů., Bachelor thesis analyzes the company's costs and its proposals for improvement using a breaking even point. First part of this thesis is focused on BEP definition and its enumeration. Second part is focused on realization of break even point analysis of company. Results of this analysis are used as a basis for finding recommendations for reducing costs.