Evaluation of the wind conditions for the acquisition of energy from renewable sources on the base of Sosnowiec city

Inherent in the continuous development of civilization is a constant increase in demand for electricity. The result of this situation could be a threat to cover domestic demand for electricity generated from domestic sources. It is significant therefore, to increase the energy security of the country, as well as to generate a positive impact on the development and dynamics of social and economic processes which is carried by the development of renewable energy sources. A crucial argument for the need to implement new sustainable solutions is growing environmental degradation and pollution resulting from the acquisition and use of non-renewable energy resources. Renewable energy resource for interest of this analysis is the wind. A crucial feature of the wind is its high volatility. Wind speed is characterized by diurnal, seasonal and long-term variation. The study area is Sosnowiec city. The analysis covers the data from the period 2002 - 2011 obtained using a meteorological station located in the Department of Earth Sciences, University of Silesia in Sosnowiec. Analyzed data are observations of wind speed measured at the height of 10m above the ground - average values of 10 minutes. The mean and maximum daily, monthly and annual values of wind speed have been calculated, and on their basis, a relevant analysis have been made. Average wind speed value for the analyzed area of the analyzed period (2002 - 2011) is 1,70m/s, while the maximum wind speed value is 3,78m/s. Sosnowiec is located in zone IV - unfavorable for the use of wind energy

Evaluation of the solar conditions for the acquisitions of energy from renewable sources on the base of Sosnowiec city (Poland)

Inherent in the continuous development of civilization is a constant increase in demand for electricity. The result of this situation could be a threat to cover domestic demand for electricity generated from domestic sources. It is significant therefore, to increase the energy security of the country, as well as to generate a positive impact on the development and dynamics of social and economic processes which is carried by the development of renewable energy sources. A crucial argument for the need to implement new sustainable solutions is growing environmental degradation and pollution resulting from the acquisition and use of non-renewable energy resources. Renewable energy resource for interest of this analysis is the wind. A crucial feature of the wind is its high volatility. Wind speed is characterized by diurnal, seasonal and long-term variation. The study area is Sosnowiec city. The analysis covers the data from the period 2002 - 2011 obtained using a meteorological station located in the Department of Earth Sciences, University of Silesia in Sosnowiec. Analyzed data are observations of wind speed measured at the height of 10m above the ground - average values of 10 minutes. The mean and maximum daily, monthly and annual values of wind speed have been calculated, and on their basis, a relevant analysis have been made. Average wind speed value for the analyzed area of the analyzed period (2002 - 2011) is 1,70m/s, while the maximum wind speed value is 3,78m/s. Sosnowiec is located in zone IV - unfavorable for the use of wind energy

A Comparison and Catalog of Intrinsic Tumor Growth Models

Determining the dynamics and parameter values that drive tumor growth is of great interest to mathematical modelers, experimentalists and practitioners alike. We provide a basis on which to estimate the growth dynamics of ten different tumors by fitting growth parameters to at least five sets of published experimental data per type of tumor. These timescale tumor growth data are also used to determine which of the most common tumor growth models (exponential, power law, logistic, Gompertz, or von Bertalanffy) provides the best fit for each type of tumor. In order to compute the best-fit parameters, we implemented a hybrid local-global least squares minimization algorithm based on a combination of Nelder-Mead simplex direct search and Monte Carlo Markov Chain methods

CVD of pure copper films from amidinate precursor

Copper(I) amidinate [Cu(i-Pr-Me-AMD)]2 was investigated to produce copper films in conventional low pressure chemical vapor deposition (CVD) using hydrogen as reducing gas-reagent. Copper films were deposited on steel, silicon, and SiO2/Si substrates in the temperature range 200–350°C at a total pressure of 1333 Pa. The growth rate on steel follows the surface reaction between atomic hydrogen and the entire precursor molecule up to 240°C. A significant increase of the growth rate at temperatures higher than 300°C was attributed to thermal decomposition of the precursor molecule. It is shown that [Cu(i-Pr-Me-AMD)]2 meets the specifications for the metal organic chemical vapor deposition of Cu-based alloy coatings containing oxophilic elements such as aluminum

The influence of retention intervals and warning signals on prospective memory.

Prospective memory, memory for future events, is used for remembering duties and obligations that all people must complete. Past research has contributed to our understanding of the bases of prospective memory tasks (time versus event) and the kinds of situations requiring prospective memory (appointments, chores, deadlines, and medications). However, research has yet to examine how prospective remembering unfolds over time. For example, very little is known about how such remembering is affected by the time from when the task is encoded to the time that a task must be conducted (the retention interval), the length of the time in which a response can be counted as correct (the response window), and the time from a warning signal, if given, to the time that the prospective task must be completed (the anticipatory lag). This research explored the accuracy and temporal precision to remember to complete a prospective memory task. An accurate prospective remembering involves responding within a response window. The precision of a prospective response refers to how close in time a response is to the ideal time expected of a response. Participants completed prospective memory tasks with three retention intervals ( 45 second, 60 second, and 7 5 second) and attempted to respond within a response window often seconds. Warning signals were either not presented or presented at five and fifteen seconds prior to the expected reaction time. The results indicated that a warning signal affected both the accuracy and precision of prospective remebering such that shorter anticipatory lags created greater accuracy and lower failure rates.Michael Andrew SarapataHermann,DouglasNot ListedMaster of ScienceDepartment of PsychologyCunningham Memorial library, Terre Haute,Indiana State UniversityILL-ETD-037MastersTitle from document title page. Document formatted into pages: contains 56 p.: ill. Includes abstract and appendix

DNA microarray integromics analysis platform

Background: The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray Integromics Analysis Platform, a unique web application that focuses on computational integration and analysis of "multi-omics" data. Our tool supports a range of complex analyses, including - among others - low- and high-level analyses of DNA microarray data, integrated analysis of transcriptomics and lipidomics data and the ability to infer miRNA-mRNA interactions. Results: We demonstrate the characteristics and benefits of the DNA Microarray Integromics Analysis Platform using two different test cases. The first test case involves the analysis of the nutrimouse dataset, which contains measurements of the expression of genes involved in nutritional problems and the concentrations of hepatic fatty acids. The second test case involves the analysis of miRNA-mRNA interactions in polysaccharide-stimulated human dermal fibroblasts infected with porcine endogenous retroviruses. Conclusions: The DNA Microarray Integromics Analysis Platform is a web-based graphical user interface for "multi-omics" data management and analysis. Its intuitive nature and wide range of available workflows make it an effective tool for molecular biology research. The platform is hosted at https://lifescience.plgrid.pl

Mathematical Modeling of the Regulatory T Cell Effects on Renal Cell Carcinoma Treatment

We present a mathematical model to study the effects of the regulatory T cells (Treg) on Renal Cell Carcinoma (RCC) treatment with sunitinib. The drug sunitinib inhibits the natural self-regulation of the immune system, allowing the effector components of the immune system to function for longer periods of time. This mathematical model builds upon our non-linear ODE model by de Pillis et al. (2009) [13] to incorporate sunitinib treatment, regulatory T cell dynamics, and RCC-specific parameters. The model also elucidates the roles of certain RCC-specific parameters in determining key differences between in silico patients whose immune profiles allowed them to respond well to sunitinib treatment, and those whose profiles did not. Simulations from our model are able to produce results that reflect clinical outcomes to sunitinib treatment such as: (1) sunitinib treatments following standard protocols led to improved tumor control (over no treatment) in about 40% of patients; (2) sunitinib treatments at double the standard dose led to a greater response rate in about 15% the patient population; (3) simulations of patient response indicated improved responses to sunitinib treatment when the patient\u27s immune strength scaling and the immune system strength coefficients parameters were low, allowing for a slightly stronger natural immune response

Chemical vapor deposition of iron, iron carbides, and iron nitride films from amidinate precursors

Iron bis(N,N-diisopropylacetamidinate) [Fe2(µ-iPr-MeAMD)2(2-iPr-MeAMD)2] and iron bis(N,N-di-tert-butylacetamidinate) [Fe(tBu-MeAMD)2] were used as precursors for the metallorganic chemical vapor deposition (MOCVD) of iron-containing compounds including pure iron, iron carbides, Fe3C and Fe4C, and iron nitrides Fe4C. Their decomposition mechanism involves hydrogen migration followed by dissociation of the Fe–N bond and the release of free hydrogenated ligand (HL) and radicals. Surface intermediates are either released or decomposed on the surface providing Fe–N or Fe–C bonds. MOCVD experiments were run at 10 Torr, in the temperature ranges of 350–450°C with Fe2(µ−iPr-MeAMD)2(2-iPr-MeAMD)2 and 280–350°C with Fe(tBu-MeAMD)2. Films prepared from Fe2(µ−iPr-MeAMD)2(2-iPr-MeAMD)2 contain Fe, Fe3C, and Fe4C. Those prepared from Fe(tBu-MeAMD)2 contain Fe, Fe3C, and also Fe4C or Fe4N, depending on the temperature and hydrogen to precursor ratio (H/P) in the input gas. The room-temperature coercive field of films processed from Fe(tBu-MeAMD)2 is 3 times higher than that of the high temperature processed Fe4N films

Video-Based Activity Recognition for Automated Motor Assessment of Parkinson's Disease

Over the last decade, video-enabled mobile devices have become ubiquitous, while advances in markerless pose estimation allow an individual's body position to be tracked accurately and efficiently across the frames of a video. Previous work by this and other groups has shown that pose-extracted kinematic features can be used to reliably measure motor impairment in Parkinson's disease (PD). This presents the prospect of developing an asynchronous and scalable, video-based assessment of motor dysfunction. Crucial to this endeavour is the ability to automatically recognise the class of an action being performed, without which manual labelling is required. Representing the evolution of body joint locations as a spatio-temporal graph, we implement a deep-learning model for video and frame-level classification of activities performed according to part 3 of the Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS). We train and validate this system using a dataset of n = 7310 video clips, recorded at 5 independent sites. This approach reaches human-level performance in detecting and classifying periods of activity within monocular video clips. Our framework could support clinical workflows and patient care at scale through applications such as quality monitoring of clinical data collection, automated labelling of video streams, or a module within a remote self-assessment system

Iron amidinates as precursors for the MOCVD of iron-containing thin films

Iron amidinates as precursors for the MOCVD of iron-containing thin film