Spatially encoded light for Large-alphabet Quantum Key Distribution

Most Quantum Key Distribution protocols use a two-dimensional basis such as HV polarization as first proposed by Bennett and Brassard in 1984. These protocols are consequently limited to a key generation density of 1 bit per photon. We increase this key density by encoding information in the transverse spatial displacement of the used photons. Employing this higher-dimensional Hilbert space together with modern single-photon-detecting cameras, we demonstrate a proof-of-principle large-alphabet Quantum Key Distribution experiment with 1024 symbols and a shared information between sender and receiver of 7 bit per photon.Comment: 9 pages, 6 figures, Added references, Updated Fig. 1 in the main text, Updated Fig.1 in supplementary material, Added section Trojan-horse attacks in supplementary material, title changed, Added paragraphs about final key rate and overfilling the detector to result sectio

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

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