Formation of Hϵ{\epsilon} in the solar atmosphere

Aims. We aim to understand how Hepsilon is formed in the quiet Sun. In particular, we consider the particular physical mechanism that sets its source function and extinction, how it is formed in different solar structures, and why it is sometimes observed in emission. Methods. We used a 3D radiative magnetohydrodynamic (MHD) simulation that accounts for non-equilibrium hydrogen ionization, run with the Bifrost code. To synthesize Hepsilon and Ca II H spectra, we made use of the RH code, which was modified to take into account the non-equilibrium hydrogen ionization. To determine the dominant terms in the H${\epsilon}$ source function, we adopted a multi-level description of the source function. Using synthetic spectra and simulation, we studied the contribution function to the relative line absorption or emission and compared it with atmospheric quantities at different locations. Results. Our multi-level source function description suggests that the H${\epsilon}$ source function is dominated by interlocking, with the dominant interlocking transition being through the ground level, populating the upper level of H${\epsilon}$ via the Lyman series. This makes the H${\epsilon}$ source function partly sensitive to temperature. The H${\epsilon}$ extinction is set by Lyman-${\alpha}$. In some cases, this temperature dependence gives rise to H${\epsilon}$ emission, indicating heating. High-resolution observations reveal that H${\epsilon}$ is not just a weak absorption line. Regions with H${\epsilon}$ in emission are especially interesting to detect small-scale heating events in the lower solar atmosphere, such as Ellerman bombs. Thus, H${\epsilon}$ can be an important new diagnostic tool for studies of heating in the solar atmosphere, augmenting the diagnostic potential of Ca II H when observed simultaneousl

Trust in Dutch intensive care networks:the results of a survey

Introduction: Dutch ICUs have been enrolled in network organisations since the Quality Standard of 2016. In networks, intensivists have to cooperate to provide a high quality of care for all patients in their network. Trust is essential to cooperate effectively in a network. It is unknown what the degree of trust is in Dutch ICU networks. Methods: A survey was composed using the questionnaire by Cummings, measuring the experience of trust, and the questionnaire by Currall, measuring the willingness to show behaviour that is consistent with trust. Two overall questions concerning the feeling of being part of the network and the overall level of trust were added. All questions were answered on a 7-point Likert scale. Network managers passed the questionnaire to intensivists in the network. Results: The overall level of trust showed a mean of 5.5 (SD 1.2), similar to the mean of the Cummings questionnaire (5.3; SD 0.9). Academic intensivists had a significantly higher level of trust than intensivists from other hospitals (5.9 vs 5.0 and 5.3; p=0.009). The questions covering `surveillance', which measures the need for control, scored lowest with 3.8 (SD 1.3). Intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. Conclusion: Intensivists experience a reasonable level of trust within their network. However, intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. This suggests that the actual trust is conditional. Academic intensivists showed the highest level of trust

Trust in Dutch intensive care networks:the results of a survey

Introduction: Dutch ICUs have been enrolled in network organisations since the Quality Standard of 2016. In networks, intensivists have to cooperate to provide a high quality of care for all patients in their network. Trust is essential to cooperate effectively in a network. It is unknown what the degree of trust is in Dutch ICU networks. Methods: A survey was composed using the questionnaire by Cummings, measuring the experience of trust, and the questionnaire by Currall, measuring the willingness to show behaviour that is consistent with trust. Two overall questions concerning the feeling of being part of the network and the overall level of trust were added. All questions were answered on a 7-point Likert scale. Network managers passed the questionnaire to intensivists in the network. Results: The overall level of trust showed a mean of 5.5 (SD 1.2), similar to the mean of the Cummings questionnaire (5.3; SD 0.9). Academic intensivists had a significantly higher level of trust than intensivists from other hospitals (5.9 vs 5.0 and 5.3; p=0.009). The questions covering `surveillance', which measures the need for control, scored lowest with 3.8 (SD 1.3). Intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. Conclusion: Intensivists experience a reasonable level of trust within their network. However, intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. This suggests that the actual trust is conditional. Academic intensivists showed the highest level of trust

3-Dimensional Imaging of Biological Structures by High Resolution Confocal Scanning Laser Microscopy

Imaging in confocal microscopy is characterized by the ability to make a selective image of just one plane inside a specimen, virtually unaffected -within certain limits-by the out-of-focus regions above and below it. This property, called optical sectioning, is accompanied by improved imaging transverse to the optical axis. We have coupled a confocal microscope to a computer system, making the combination of both an excellent instrument for mapping the 3-dimensional structure of extended specimens into a computer memory/data array. We measured that the volume element contributing to each data point has, under typical fluorescence conditions, a size of 0.2 x 0.2 x 0.72 μm. The data can be analysed and represented in various ways, i.e., stereoscopical views from any desired angle. After a description of the experimental arrangement, we show various examples of biological and food-structural studies. The microscope can be operated either in reflection or in fluorescence. In the latter mode a spectral element allows selection of the wavelength band of fluorescence light contributing to the image. In this way, we can distinguish various structures inside the cell and study their 3-dimensional relationships. Various applications in biology and the study of food structure are presented

Network governance of Dutch intensive care units:state of affairs after implementation of the Quality Standard

Objective: To study the current state of affairs concerning Dutch intensive care network governance in relation to known effective governance structures of network organisations. Methods: Six characteristics of intensive care networks were defined to determine the four contingency factors from the Provan & Kenis network governance models. The contingency factors were determined for all Dutch intensive care networks. An overview of the networks and characteristics was created by triangulation, using information from two national intensive care network meetings (November 2017 and June 2018) and semi-structured interviews by telephone with 10 network intensivists and / or network managers. Results: Based on the chosen characteristics, none of the Dutch intensive care networks has a governance structure according to one of the Provan & Kenis successful forms of governance. Each of the present networks has a governance structure with elements from two or three different types. Characteristics of the network administrative organisation and shared governance form overlap in 10 out of 15 networks. All networks have a form of governance in which at least one intensivist is represented. Conclusion: After implementation of the Quality Standard, the presence of networks of intensive care units covering the Netherlands is a fact. The network governance that has developed varies but none of the networks has a governance structure that matches with a proven effective governance structure. Based on theory, the network administrative organisation seems to be the most effective for larger networks, and shared governance for smaller networks

Network governance of Dutch intensive care units:state of affairs after implementation of the Quality Standard

Objective: To study the current state of affairs concerning Dutch intensive care network governance in relation to known effective governance structures of network organisations. Methods: Six characteristics of intensive care networks were defined to determine the four contingency factors from the Provan & Kenis network governance models. The contingency factors were determined for all Dutch intensive care networks. An overview of the networks and characteristics was created by triangulation, using information from two national intensive care network meetings (November 2017 and June 2018) and semi-structured interviews by telephone with 10 network intensivists and / or network managers. Results: Based on the chosen characteristics, none of the Dutch intensive care networks has a governance structure according to one of the Provan & Kenis successful forms of governance. Each of the present networks has a governance structure with elements from two or three different types. Characteristics of the network administrative organisation and shared governance form overlap in 10 out of 15 networks. All networks have a form of governance in which at least one intensivist is represented. Conclusion: After implementation of the Quality Standard, the presence of networks of intensive care units covering the Netherlands is a fact. The network governance that has developed varies but none of the networks has a governance structure that matches with a proven effective governance structure. Based on theory, the network administrative organisation seems to be the most effective for larger networks, and shared governance for smaller networks