Despite extensive vaccination, the quantity of patients infected with the SARS-CoV-2 virus and its variants continues to grow worldwide. Treating patients with a severe course of COVID-19 is a difficult challenge. One of the generally accepted and specific therapy methods is the use of plasma rich in anti-SARS-CoV-2 antibodies. On the other hand, assessing the antibodies level depending on the time after infection allows for vaccine-decision. The study marked the level of anti-SARS-CoV-2 IgG antibodies in 351 COVID-19 convalescent residents of one geographical region in Poland. The study group included blood donors. The studies were crosssectional and extended to a questionnaire to determine infection severity. These data were compiled statistically. The study considered epidemiological factors, the time from the end of the infection, and infection severity. The fastest increase of the antibodies level was observed up to 59 days after COVID-19, and it was statistically significantly higher among men. Higher levels of antibodies were found among people above the average age in both men and women. There was an increase in the level of antibodies since the onset of the disease in men, while in women, it decreased. The antibodies level was also found to depend on the severity of the course of COVID-19 infection. The optimal group of plasma donors in the studied geographical region is men and women above 39 years old. after a more severe infection. The titer of antibodies increases with time from the disease.
The production of silica in thermal petroleum recovery projects is a well-known phenomenon, and considerable efforts for its control are a common feature of facilities engineering in such projects. In solutions of high pH, such as boiler feedwater and blowdown, however, the silicates of iron, calcium, magnesium and sodium are of greater interest than the silica itself. Scaling by such silicates is usually predictable by means of computer programs that rely on free energy minimizations. Where instabilities for scaling are predicted in this way, often a large range of potential mineral deposits are identified as potential scale deposits. The reality is, however, that only one or two such minerals are ever found in the analysis of pigging solids. A simple method, that permits the prediction by non-chemists of both type and quantity of preferential scales, is derived and its use in SAGD water management and recycling schemes is illustrated. The effect of the presence of chelants in boiler feedwater may not prevent silicate scales, but merely shift the preferred scale. Sample recovery and handling, on the other hand, may cause a shift in scale preference under laboratory conditions, as opposed to facility conditions. Introduction The observation of scaling by metal silicates, rather than amorphous silica, is a phenomenon in SAGD operations that has been recognized relatively recently. A variety of alkaline earth silicates and mixed silicates have been observed(1,2) in various unit operations of SAGD plants, including boiler tubes, production headers and separation facilities. Analyses of fluid interactions in disposal wells also often predict formation damage due to precipitation of such silicates. The prediction or thermodynamic confirmation of the scales found analytically is usually accomplished by water chemistry software that is based on free energy minimization. The program used in this work is the well-known SOLMINEQ program developed by the Alberta Research Council. Silicate Scales in SAGD A number of scales have been observed by various authors in the past few years. Table 1 provides a summary of silicate scale type and references. The most commonly encountered scales appear to be Talc, a magnesium silicate and Tremolite, which is a more complex calcium magnesium silicate of the asbestos variety. From time to time, isomorphic substitutions are reported. Among them is Richterite, where one of the calcium atoms in Tremolite is replaced by sodium atoms. In general, it is found that the predictive programs, when run with a given analysis, tend to predict a range of metal silicates. Given that waters in SAGD operations are generally quite soft, only one or two of the scales predicted will be found in practice, however. The purpose of this paper is to provide a simple method of predicting which of the predicted scales will be the preferred one. The importance of this work is the prediction of scale quantity. The predictive programs are able to predict a scaling index, which is not necessarily related to quantity.
Hydrogen as a raw material finds its main use and application on the Polish market in the chemical industry. Its potential applications for the production of energy in fuel cell systems or as a fuel for automobiles are widely analyzed and commented upon ever more frequently. At present, hydrogen is produced worldwide mainly from natural gas, using the SMR technology or via the electrolysis of water. Countries with high levels of coal resources are exceptional in that respect, as there the production of hydrogen is increasingly based on gasification processes. China is such an example. There some 68% of hydrogen is generated from coal. The paper discusses the economic efficiency of hydrogen production technologies employing lignite gasification, comparing it with steam reforming of natural gas technology (SMR). In present Polish conditions, this technology seems to be the most probable alternative for natural gas substitution. For the purpose of evaluating the economic efficiency, a model has been developed, in which a sensitivity analysis has been carried out. An example of the technological process of energy-chemical processing of lignite has been presented, based on the gasification process rooted in disperse systems, characteristics of the fuel has been discussed, as well as carbon dioxide emission issues. Subsequently, the assumed methodology of economic assessment has been described in detail, together with its key assumptions. Successively, based on the method of discounted cash flows, the unit of hydrogen generation has been determined, which was followed by a detailed sensitivity analysis, taking the main risk factors connected with lignite/coal and natural gas price relations, as well as the price of carbon credits (allowances for emission of CO 2) into account.
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