<p dir="ltr">This thesis involves three topics related to forensic analysis of media data. The first topic is the analysis of images and documents that have been created with a scanner. The goal is to detect and identify scanner model from the scanned images/documents. We propose a deep learning system that can automatically learn the inherent features of the scanned images. This system will produce a scanner model identification and a reliability map for a scanned image. The proposed system has shown promising results in the forensic analysis of scanned images. The second topic is related to forensic integrity of scientific papers. The project is divided into multiple tasks, data collection, image extraction, and manipulation detection. We have constructed a dataset of retracted scientific papers that have been verified to have issues with integrity. We design and maintain a web-based Scientific Integrity System for forensic analysis of the images within scientific publications. The third topic is related to media document analysis. Our goal is to identify the publication style for media document, aiding in the potential document manipulation. We are mainly focusing on image-text consistency check, and synthetic tweets analysis. For image-text inconsistency check, we describe a system that can examine an image in document and the corresponding text caption (or other associated text with the image) to check the image/text consistency. For synthetic tweets analysis, we propose a system to detect and identify the text generation models and paraphrase attack models.</p>

<p dir="ltr">In the realm of autonomous vehicle technology, the Multimodal Vehicle Detection Network (MVDNet) represents a significant leap forward, particularly in the challenging context of weather conditions. This paper focuses on the enhancement of MVDNet through the integration of a multi-head attention layer, aimed at refining its performance. The integrated multi-head attention layer in the MVDNet model is a pivotal modification, advancing the network's ability to process and fuse multimodal sensor information more efficiently. The paper validates the improved performance of MVDNet with multi-head attention through comprehensive testing, which includes a training dataset derived from the Oxford Radar Robotcar. The results clearly demonstrate that the Multi-Head MVDNet outperforms the other related conventional models, particularly in the Average Precision (AP) estimation, under challenging environmental conditions. The proposed Multi-Head MVDNet not only contributes significantly to the field of autonomous vehicle detection but also underscores the potential of sophisticated sensor fusion techniques in overcoming environmental limitations.</p>

This thesis deals with specific learning disabilities on the first level of primary education. The theoretical part is devoted to the definition of the basic concepts, to the etiology of the occurrence of specific learning disabilities and to the classification of their manifestation. It draws up the possibilities of the diagnostics and of the follow-up re-education. It describes the possibilities of educating students with disabilities at basic schools or individually. The practical part of this thesis focuses on exploring the issue of specific learning disabilities on the first level of primary education, namely, in the third and fourth grade. Three case reports whose results most visibly pointed to a problem are also present here.

Aquesta tesi doctoral versa sobre el processament digital de la veu cantada, més concretament, sobre l'anàlisi, transformació i síntesi d'aquets tipus de veu en el domini espectral, amb especial èmfasi en aquelles tècniques rellevants per al desenvolupament d'aplicacions musicals.La tesi presenta nous procediments i formulacions per a la descripció i transformació d'aquells atributs específicament vocals de la veu cantada. La tesis inclou, entre d'altres, algorismes per l'anàlisi i la generació de desordres vocals como ara rugositat, ronquera, o veu aspirada, detecció i modificació de la freqüència fonamental de la veu, detecció de nasalitat, conversió de veu cantada a melodia, detecció de cops de veu, mutació de veu cantada, i transformació de veu a instrument; exemplificant alguns d'aquests algorismes en aplicacions concretes. / Esta tesis doctoral versa sobre el procesado digital de la voz cantada, más concretamente, sobre el análisis, transformación y síntesis de este tipo de voz basándose e dominio espectral, con especial énfasis en aquellas técnicas relevantes para el desarrollo de aplicaciones musicales.La tesis presenta nuevos procedimientos y formulaciones para la descripción y transformación de aquellos atributos específicamente vocales de la voz cantada. La tesis incluye, entre otros, algoritmos para el análisis y la generación de desórdenes vocales como rugosidad, ronquera, o voz aspirada, detección y modificación de la frecuencia fundamental de la voz, detección de nasalidad, conversión de voz cantada a melodía, detección de los golpes de voz, mutación de voz cantada, y transformación de voz a instrumento; ejemplificando algunos de éstos en aplicaciones concretas. / This dissertation is centered on the digital processing of the singing voice, more concretely on the analysis, transformation and synthesis of this type of voice in the spectral domain, with special emphasis on those techniques relevant for music applications. The thesis presents new formulations and procedures for both describing and transforming those attributes of the singing voice that can be regarded as voice specific. The thesis includes, among others, algorithms for rough and growl analysis and transformation, breathiness estimation and emulation, pitch detection and modification, nasality identification, voice to melody conversion, voice beat onset detection, singing voice morphing, and voice to instrument transformation; being some of them exemplified with concrete applications.

This theses aims to find ways how to expand cultural and historical awareness of the young generation. It is inspired by a longterm program of the National Heritage Institute, Regional Center in České Budějovice, which is called "Let's play and study with sights." The theses follows the main ideas of this project and an educational proposal is created, which is supposed to introduce religious monuments in the city as well as try to point out the fact that these sites have been more or less transformed in the interior and some of them have undergone a change in its original purpose over decades or centuries. The theses also introduces the former holy of holies where an educational process was taking place in the 19th century. Descriptive research is developed into an educational program where presentation and comparison with other sacred objects is offered. An attempt to discover a tangible symbol of transcendence, and take photos of it, was chosen to be the activation element. Regarding the complexity of issues, this theses is meant for the final grades of primary schools and at the same level for the grades of grammar schools, it can also be used for lower grades of fouryear grammar schools and secondary schools. Its content should extend the lessons of history, art, aesthetics, and is also applicable as an extracurricular activity. It represents an educational proposal using the objectbased learning along with a continuous dialogue.

Trace component analysis in gasification processes are important part of elemental component balances in order to understand the fate of these participating compounds in the feedstock. Residual traces in the raw synthesis gas after quench could bring about the poisoning of catalysts and corrosion effects on plant facilities. The objective of this work is to investigate the effects of quenching operation on the trace components during test campaigns of the autothermal non-catalytic reforming of natural gas (Gas-POX) mode in the HP POX (high pressure partial oxidation) test plant. In order to achieve this, Aspen Plus simulation model of the quench chamber of the HP POX test plant was developed to re-calculate the quench chamber input amount of different trace compounds from their output amount measured during test points of the Gas-POX campaigns. Variation in quench water temperatures from 130 °C to 220 °C and pH value of quench water as well as the resulting variation in Henry´s and Dissociation constant of the traces (CO2, H2S, NH3 and HCN) changed the distribution of traces calculated in the quench water. The formation of traces of organic acid (formic acid and acetic acid) and traces of BTEX, PAHs and soot in the quench water effluent were discussed. The discrepancies between equilibrium constant and reaction quotient (non-equilibrium or real) for the formation of NH3 and HCN at the exit of the gasifier were discussed. The assessment of the results in this work should lead to the improvement in the understanding of trace components and concepts that could be employed to influence their formation and reduction.:List of Figures vii List of Tables xii List of Abbreviations and Symbols xiii 1 Introduction 1 1.1 Background 1 1.2 Objective of the Work 4 1.3 Overview of the Work 5 2 Process and test conditions 6 2.1 HP POX test plant 6 2.2 Test campaign procedure 8 2.2.1 Gas-POX operating parameter range 8 2.2.2 Gas-POX experiments 9 2.2.3 Net reactions of partial oxidation 9 2.3 Gaseous feedstock characterization 11 2.3.1 Natural gas feedstock composition 11 2.4 Analytical methods for gaseous products 12 2.4.1 Hot gas sampling 12 2.4.2 Raw synthesis gas analysis after quench 13 2.5 Aqueous phase product analysis 14 2.5.1 Molecularly dissolved trace compounds and their ions trace analysis 14 2.5.2 Other trace analysis 15 2.6 Limit of accuracy in measurement systems 15 2.7 Summary 17 3 Simulation and methods 18 3.1 Test points calculation of the HP POX test campaign 18 3.1.1 Aspen Plus model for HP POX quench water system 19 3.2 Gas-POX 201 VP1 quench water system model simulation by Aspen Plus 23 3.2.1 Measured and calculated input parameters 23 3.2.2 Calculated sensitivity studies of species and their distribution for test point (VP1) 24 3.3 Used calculation tools related to the work 25 3.3.1 VBA in Excel 25 3.3.2 Python as interface between Aspen Plus and Microsoft Excel 26 3.3.3 Aspen Simulation Workbook 27 3.4 Summary 29 4 Trace components in quench water system 30 4.1 Physico-chemical parameters of quench water 31 4.1.1 Quench water pH adjustment 32 4.1.2 Henry constant 34 4.1.3 Dissociation constant 35 4.1.4 Organic acids in quench water 38 4.2 Carbon dioxide (CO2) 39 4.2.1 Results of sensitivity study: quench water temperature variation effects on CO2 41 4.2.2 Results of sensitivity study: quench water pH variation influence on CO2 42 4.3 Nitrogen compounds 43 4.3.1 Ammonia (NH3) 44 4.3.2 Results of sensitivity study: quench water temperature variation effects on NH3 46 4.3.3 Results of sensitivity study: quench water pH variation influence on NH3 47 4.3.4 Hydrogen Cyanide (HCN) 48 4.3.5 Results of sensitivity study: quench water temperature variation effects on HCN 50 4.3.6 Results of sensitivity study: quench water pH variation influence on HCN 50 4.4 Sulphur compounds: H2S 51 4.4.1 Results of sensitivity study: quench water temperature variation effects on H2S 53 4.4.2 Results of sensitivity study: quench water pH variation influence on H2S 54 4.5 Summary 55 5 Organic acids trace studies in quench water 57 5.1 Organic acids interaction with ammonia compounds in the quench water 57 5.2 Formic acid 62 5.2.1 Trace of formic acid in quench water 64 5.3 Acetic acid 67 5.3.1 Trace of acetic acid in quench water 69 5.4 Summary 72 6 Temperature approach studies for NH3 and HCN formation in gasifier 74 6.1 Nitrogen compounds: NH3 and HCN 74 6.2 Ammonia (NH3) formation in the gasifer 77 6.3 Hydrogen cyanide (HCN) formation in the gasifier 79 6.4 Discrepancies between back-calculated reaction quotients and equilibrium constants of the NH3 formation 81 6.4.1 Case 1: calculated equilibrium distribution between N2, NH3 and HCN 81 6.4.2 Case 2: calculated equilibrium distribution between NH3 and HCN 83 6.5 Summary 84 7 Traces of BTEX, PAHs and soot in quench water 86 7.1 Quench water behaviour 87 7.2 BTEX compounds 88 7.2.1 BTEX in quench water effluent 90 7.3 PAH compounds 93 7.3.1 PAHs in quench water effluent 95 7.4 Soot formation 99 7.4.1 Soots in quench water effluent 101 7.5 Summary 102 8 Summary and outlook 103 Bibliography 106 9 Appendix 135 List of Figures Figure 2.1: HP POX test plant main facility components and material flow courtesy of [Lurgi GmbH, 2008] 6 Figure 2.2: Simplified scheme of HP POX plant (including quench system) [Lurgi GmbH, 2008] 7 Figure 2.3: Overview of reactions of methane 10 Figure 3.1: Simplified scheme for HP POX quench water system 18 Figure 3.2: Aspen Plus flow diagrams of simulated HP POX quench water system 19 Figure 3.3: Integration of information and functions in VBA via Microsoft Excel to Aspen Plus model 25 Figure 3.4: Integration of information and functions in Python via Microsoft Excel to Aspen Plus model 26 Figure 3.5: ASW enables Excel users to rapidly run scenarios using the underlying rigorous models to analyze plant data, monitor performance, and make better decisions. 27 Figure 4.1: Vapour-liquid equilibria system of CO2, H2S, NH3, HCN and organic acids in the quench water and extended mechanisms according to [Kamps et al., 2001], [Alvaro et al., 2000], [Kuranov et al., 1996], [Xia et al., 1999] and [Edwards et al., 1978]. 30 Figure 4.2: HP POX quench water system with pH regulator for sensitivity studies 34 Figure 4.3: Henry´s constant for CO2, H2S, NH3 and HCN derived from [Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN 35 Figure 4.4: Dissociation constants for CO2, H2S, NH3, HCN and H2O derived from [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] 37 Figure 4.5: The flow of CO2 in the quench water cycle (test point VP1). 40 Figure 4.6: Calculated quench water temperature variation and effects on CO2 distribution 42 Figure 4.7: Calculated influence of pH regulation and effects on CO2 distribution 43 Figure 4.8: The flow of NH3 in the quench water cycle (test point VP1). 46 Figure 4.9: Calculated quench water temperature variation and effects on NH3 distribution 47 Figure 4.10: Calculated influence of pH regulation and effects on NH3 distribution 48 Figure 4.11: The flow of HCN in the quench water cycle (test point VP1). 49 Figure 4.12: Calculated quench water temperature variation and effects on HCN distribution 50 Figure 4.13: Calculated influence of pH regulation and effects on HCN distribution 51 Figure 4.14: The flow of H2S in the quench water cycle (test point VP1) 53 Figure 4.15: Calculated quench water temperature variation and effects on H2S distribution 54 Figure 4.16: Calculated influence of pH regulation and effects on H2S distribution 55 Figure 5.1: Aspen Plus back-calculated (real) formic acid concentration, quench water temperature and the calculated equilibrium formic acid concentration against back-calculated (real) ammonia concentration for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 59 Figure 5.2: Aspen plus back-calculated (real) formic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium formic acid concentration against quench water temperature for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 60 Figure 5.3: Aspen plus back-calculated (real) acetic acid concentration, quench water temperature and the calculated equilibrium acetic acid concentration against back-calculated (real) ammonia concentration for the 47 test points. 61 Figure 5.4: Aspen plus back-calculated (real) acetic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium acetic acid concentration against quench water temperature for the 47 test points. 62 Figure 5.5: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) formation in the quench and quench water temperature for the 47 test points. 64 Figure 5.6: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.2). 65 Figure 5.7: Comparison between formic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 66 Figure 5.8: Comparison between formic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 67 Figure 5.9: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench and quench water temperature for the 47 test points. 69 Figure 5.10: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.4). 70 Figure 5.11: Comparison between acetic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 71 Figure 5.12: Comparison between acetic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 72 Figure 6.1: Mole fraction of gas compoents in the hot gas outlet out of gasifier against hot gas temperature for the 47 test points 76 Figure 6.2: Calculated reaction quotient (Q) and equlibrium constant (Keq) for NH3 against hot gas temperature for the 47 test points (see Fig. 9.10 in Appendix) 77 Figure 6.3: NH3 temperature approach against hot gas temperature for the 47 test points (see Fig. 9.11 in Appendix) 78 Figure 6.4: Calculated reaction quotient (Q) and equlibrium constant (Keq) for HCN against hot gas temperature for the 47 test points (see Fig. 9.13 in Appendix) 79 Figure 6.5: HCN temperature approach against hot gas temperature for the 47 test points (see Fig. 9.14 in Appendix) 80 Figure 6.6: Comparison between calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions against their respective hot gas temperature (case 1). 82 Figure 6.7: Relations between back-calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions (for chemical equilibrium according to equations (6.1) and (6.4)) against their respective hot gas temperature (see Case 1, Section 6.4.1, and Fig. 6.6) 82 Figure 6.8: Comparison between calculated real and equilibrium hot gas HCN mol fraction against their respective hot gas temperature (case 2). 83 Figure 6.9: Relations between back-calculated real and equilibrium hot gas HCN mol fractions, and change in NH3 mol fractions (for chemical equilibrium according to equation (6.4)), against their respective hot gas temperature (see. Case 2, Section 6.4.2 and Fig. 6.7) 84 Figure 6.10 Comparison between NH3 and HCN formation (mole fraction) calculated equilibrium constant (Keq) and calculated reaction quotient (Q), N2 consumption and hot gas temperatures for the 47 test points (case 1 and case 2). 85 Figure 7.1: HP POX test plant quench water system 88 Figure 7.2: Traces of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 91 Figure 7.3: Individual component of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 92 Figure 7.4: (a) Alkyl radical decomposition and (b) C1 and C2 hydrocarbons oxidation mechanism [Warnatz et al., 2000] 93 Figure 7.5: Recombination of C3H3 to form benzene 94 Figure 7.6: The Diels - Alder reaction for the formation of PAHs 95 Figure 7.7: Amount of PAHs that were detected in Gas-POX 203 – 207 test points quench water effluent samples. 97 Figure 7.8: Distribution of PAH compounds in Gas-POX 203 – 207 quench water effluent samples. 98 Figure 7.9: Some steps in soot formation [McEnally et al., 2006]. 99 Figure 7.10: Illustration of soot formation path in homogenous mixture [Bockhorn et al., 1994] 100 Figure 9.1: Aspen flow sheet set up for HP POX quench system GasPOX 201 VP1 (simplified and extension of Fig. 3.2, organic acids not taken into account). Tabulated values are given in Table 9.11. 135 Figure 9.2: Comparison between the Henry´s constant profiles: Aspen Plus (markers) and Literatures (solid lines) ([Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137 Figure 9.3: Henry´s constant profiles derived from literatures ([Edwards et al., 1978] for CO2, [Alvaro Pérez-Salado et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137 Figure 9.4: Comparison between the dissociation constant profiles: Aspen Plus (markers) and Literatures (solid or dashed lines) [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138 Figure 9.5: Dissociation constant profiles derived from literatures [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138 Figure 9.6: Calculated pH values, temperature range and species 139 Figure 9.7: Aspen Plus flow sheet setup for organic acid compounds calculations (GasPOX 201 VP1, see also Table 9.12) 142 Figure 9.8: Aspen Plus flow sheet setup for nitrogen compounds calculations (GasPOX 201 VP1, see also Table 9.12, organic acids are taken into account in the aqueous streams of the quench system) 145 Figure 9.9: Yield of ammonia in gasifier (calculated real) and hot gas temperature against the 47 test points 146 Figure 9.10: Kreal or reaction quotient for ammonia formation in the gasifier against the 47 test points. 146 Figure 9.11: Temperature approach studies for ammonia and the 47 test points 147 Figure 9.12: Yield of HCN from the gasifier (calculated real and equilibrium) and hot gas temperature and the 47 test points 147 Figure 9.13: Comparison between equilibrium constant and reaction quotient for HCN and 47 test points 148 Figure 9.14: Temperature approach studies for HCN and the 47 test points 148 Figure 9.15: Comparison among equilibrium constants of reactions against temperature, T [°C] 149 Figure 9.16: Comparison among equilibrium constants of reactions against temperature, 1/T [1/K] 150 List of Tables Table 2.1: Outline of Gas-POX mode operating parameter range 8 Table 2.2: Outline of test runs operating mode and parameters of chosen test campaigns 9 Table 2.3: Natural gas feedstock compositions 12 Table 2.4: Product synthesis gas analysis method (hot gas before quench) [Brüggemann, 2010] 12 Table 2.5: Analysis methods for raw synthesis gas [Brüggemann, 2010] 13 Table 2.6: Analysis methods for aqueous phase products [Brüggemann, 2010] 14 Table 2.7: Relative accuracy for the measured value for temperature, pressure and flow of each feed and product stream [Meyer, 2007] and [Brüggemann, 2010] 17 Table 3.1: Description of blocks used in Aspen Plus simulation. 20 Table 3.2: HP POX test plant quench water cycle parameters Gas-POX 201 VP1* 23 Table 3.3: pH regulator parameters 24 Table 4.1: Organic acids distribution in streams for VP1 based on calculation from Aspen Plus. 38 Table 4.2: The distribution of CO2 and its ions in all the streams 40 Table 4.3: The distribution of NH3 and its ions in all the streams 45 Table 4.4: The distribution of HCN and its ions in all the streams 49 Table 4.5: The distribution of H2S and its ions in all the streams 52 Table 7.1: Relative sooting tendency [Tesner et al., 2010] 101 Table 9.1: Natural gas feed analysis method [Brüggemann, 2010] 135 Table 9.2: pH scale with examples of solution [NALCO 2008] 136 Table 9.3: Gas-POX test campaigns and with designated serial numbers 140 Table 9.4: Summary of correlation coefficient (r) from Figures in Chapter 5 144 Table 9.5: Comparison among reactions temperatures and heat of reactions 149 Table 9.6: Content of BTEX compounds in Gas-POX quench water samples 151 Table 9.7: BTEX in quench water effluent samples results 152 Table 9.8: Content of PAH compounds in Gas-POX quench water samples 157 Table 9.9: PAHs in quench water effluent samples results 160 Table 9.10: Soot in quench water effluent samples results 169 Table 9.11: Aspen Plus flow sheet setup stream details (GasPOX 201 VP1, according to Fig.3.2 and Fig.9.1, organic acids not taken into account) 170 Table 9.12: Aspen Plus flow sheet setup for organic acid and nitrogen compounds calculations for GasPOX 201 VP1 (according to Figures 9.7 and 9.8, organic acids are taken into account) 174

The diploma thesis deals with problems of depression in older people. Mainly the work is focused on identifying and analyzing the role of nurses in screening for depression in older people in primary care, acute care, long-term care and home care. This thesis was focused on theoretical direction and was used the method of design and demonstration. In this thesis was set one main goals with five research questions. The main goal was to identify and analyze the role of nurses in screening for depression in the elderly. RQ 1: What is the role of the nurse in screening for depression in the elderly? RQ 2: What is the role of the nurse in the primary care in screening for depression in the elderly? RQ 3: What is the role of the nurse in screening for depression in hospitalized patients in acute care? RQ 4: What is the role of the nurse in screening for depression in seniors in long-term and home care? RQ 5: What rating scales and methods are used in screening for depression in the elderly? The thesis introduce the concept of depression. The following are specified the causes of and the important factors that affect depression in the elderly. It also deals the differences in the clinical symptomatology of depression in old age. It explains possibilities and various barriers in the diagnosis of depression. Another chapter introduces complete geriatric examination, diagnostic classification systems, possible screening methods and scales for detection of depression in the elderly population. It also deals methods of pharmacological and non-pharmacological treatment and its possible complications associated with older age. By reason of increased suicide rate caused by depressive disorder the issue of suicidal behavior in the elderly is introduced. The next chapter deals with the nursing process, which is used by nurses in practice. It consists of the evaluation of the patient's health condition, making nursing diagnosis, creating nursing plan and subsequent implementation and evaluation. The nursing process is also needy for providing quality care. The nursing process in the stage of nursing diagnosis, introduces possible nursing diagnosis for a patient suffering from depression, which are based on the latest classification. Finally is described the role of nurses in screening for depression in the elderly in different health facilities and their contribution to the timely evaluation of depression in the elderly. This chapter introduces the role of nurses, nursing screening and collaboration with a physician. The role of nurses in screening for depression in different medical facilities is based on the first phase of the nursing process of assessment. On the basis of objective and subjective information, the nurse will assess the overall health and mental condition of the patient. Primarily, it was investigated what is the role of the nurse in screening for depression. On the basis of content analysis and synthesis it was necessary to used and processed domestic and foreign literature. A number of relevant sources are the results of various studies and Meta-analyzes, mostly from abroad, but also from the Czech Republic. The thesis can serve as a basis for nurses. The result of this thesis is to create e-learning material available for students in the Faculty of Health and Social Sciences of South Bohemia in Ceske Budejovice in the tutorial called Moodle.