Hybrid Scenario Research Articles

The physics basis to integrate an MHD stable, high-power hybrid scenario to a cool divertor for steady-state reactor operation

Coupling a high-performance core to a low heat flux divertor is a crucial step for ITER and a Fusion Pilot Plant or DEMO. Experiments in DIII-D recently expanded the steady-state hybrid scenario to high density and divertor impurity injection to study the feasibility of a radiating mantle solution. This work presents the physics basis for trade-offs between density, current drive and stability to tearing modes (TMs) at high β. EC power is crucial to tailor the plasma profiles into a passively stable state, and to eject impurities from the core. Off-axis EC depositions decrease the heating efficiency, but calculated electron heat transport coefficients show that this effect is partially mitigated by improved confinement inside the EC deposition. Additionally, the reduction in pressure is recovered by increasing the density. This favourable scaling of confinement with density was observed in high power plasmas for years, and this work provides a comprehensive explanation. ELITE predictions indicate that a path in peeling-ballooning stability opens up for certain conditions of density, power, q 95 and shaping, allowing the edge pressure to continue increasing without encountering a limit. In the core, calculated anomalous fast-ion diffusion coefficients are consistent with density fluctuation measurements in the toroidicity-induced Alfvén eigenmode range, showing that smaller fast-ion losses contribute to the enhanced confinement at high density. The edge integration study shows that divertor heat loads can be reduced with Ne and Ar injection, but this eventually triggers a cascade of n = 1, 2, 3 core TMs. We can now show that impurity radiation in the core is small and it is not the cause for the drop in confinement at high Ar and Ne injection rates. The overlap between the core TMs is consistent with the loss of pressure as estimated by the Belt model for the coupled rational surfaces. Optimization of these trade-offs has achieved plasmas with sustained H 98y2 = 1.7, f GW = 0.7 and ∼85% mantle radiation. The scenario and its variations at higher density and on- vs off-axis EC heating has been studied as a candidate for an integrated solution for several reactor designs, such as ITER, ARC, and the ARIES-ACT1 case, showing promising results in terms of fusion power and gain.

Bell inequalities for nonlocality depth

When three or more particles are considered, quantum correlations can be stronger than the correlations generated by so-called hybrid local hidden variable models, where some of the particles are considered as a single block inside which communication and signaling is allowed. We provide an exhaustive classification of Bell inequalities to characterize various hybrid scenarios in four- and five-particle systems. In quantum mechanics, these inequalities provide device-independent witnesses for the entanglement depth. In addition, we construct a family of inequalities to detect a nonlocality depth of $(n\ensuremath{-}1)$ in $n$-particle systems. Moreover, we present two generalizations of the original Svetlichny inequality, which was the first Bell inequality designed for hybrid models. Our results are based on the cone-projection technique, which can be used to completely characterize Bell inequalities under affine constraints; even for many parties, measurements, and outcomes.

Integrated simulation analysis of the HL-2M high-parameter hybrid scenario

On the basis of the OMFIT integrated simulation platform and the parameters of the HL-2M device, a hybrid scenario with a typical safety factor q profile is simulated using the joint injection method of neutral beam and electron cyclotron wave with a normalized toroidal beta (β N) of 2.39. At the same time, by analyzing the effect of impurity concentration (Z eff) and pedestal density (n e,ped) on confinement, a higher parameters hybrid scenario is obtained, with β N reaching 3.118. The research results indicate that the turbulent stabilization effect caused by Z eff gradually decreases from strong to weak with the increase of Z eff, whereas the radiation power loss increases linearly as Z eff increases. Consequently, there exists an optimal Z eff value for optimal confinement. In addition, it is found that the optimal Z eff value decreases with the increase of n e,ped. The research results are crucial for the HL-2M device to accomplish the 1 MA advanced scenario discharge target, and they serve as a reference for future impurity seeding experiments.

Development of an Immersive VR Experience Using Integrated Survey Technologies and Hybrid Scenarios

The paper was aimed to promoting and improving the knowledge of the Naples city’s monuments through an immersive visit experience, according to the paradigms of new digital languages. Thanks to the use of integrated technologies, some monuments of the city are presented in virtual way, with unusual viewpoints, that reveal previously unseen details, many of them not directly visible to tourists. A journey created by the use of integrated technologies, to discover historical facades and museums to be explored in total freedom, without physical constraints, without cognitive barriers. The technological basis supporting the visit consists of integrated solutions including digital photogrammetry, 3D modelling, virtual restoration and persuasive storytelling, all organised to provide a product for the general public, to be enjoyed with VR headsets. The available contents are organised on different reading levels, in according to three paths that include: a visit to the MANN (National Archaeological Museum of Naples), a visit within the virtual room dedicated to the most important museums of the city and a virtual walk through the decumani, the heart of historical centre. The virtual enjoyment of contexts no longer visible in original state or not accessible by tourists is resolved by the virtual reconstruction and re-location of artefacts in a virtual space, here called Virtual Room.

EWST: an extreme weather scene text detector with dehazing and localization refinement

In real life, the emergence of haze brings great inconvenience and does harm to traffic and pedestrian safety, whereas previous studies paid less attention to text detection in haze scenes. In this experiment, we found that the candidates obtained by the general non-maximum suppression (NMS) method or the soft-NMS method are difficult to precisely match the ground truth, and the incomplete feature extraction will affect the final performance. In this work, a haze scene text detection framework is skillfully designed. An optimized NMS and an optimized long short-term memory for spatial feature extraction and temporal feature extraction are proposed to improve the text detection performance. In addition, a hazing scene text dataset (named HSText-1000) and a hybrid scenario text dataset (named MHSText-4600) have been built in our work for evaluating the performance conveniently, which have been released and can be downloaded from https://github.com/lyy0117/lyy. Experimental results illustrate that our method is superior to some state-of-the-art methods in the hazing scene and the hybrid scene. Meanwhile, we achieved competitive results in nonhaze’s public dataset (ICDAR 2013), which means that our method has satisfactory adaptability. We will release code to facilitate community research.

Improving the resilience of maritime supply chains: The integration of ports and inland transporters in duopoly markets

The adverse impact of the outbreak of COVID-19 has reduced ports’ operational efficiency. In addition, ports and inland logistics providers are generally independent of each other and difficult to work together, which leads to time loss. Thus, as the core player, ports can integrate with inland logistics providers to improve the efficiency and resilience of maritime supply chains. This study examines the strategic options of two competing maritime supply chains consisting of ports and inland logistics providers. We investigate the impact of cooperation between ports and inland logistics providers and government regulation on the maritime supply chain by comparing members’ optimal pricing and overall social welfare under centralized, decentralized, and hybrid scenarios. Results indicate that the hybrid scenario is an equilibrium strategy for maritime supply chain, although this strategy is not optimal for governments seeking to improve supply chain resilience and maximize social welfare. Furthermore, observations show that through government economic intervention, both seaborne supplies can be incentivized to adopt an integrated strategy, and business and society can achieve a win–win situation.

Lightning Initiation as a Consequence of Natural Thundercloud Evolution. Part 1. The Role of Detachment in Reducing the Critical Air Breakdown Field

Direct measurements show that the maximum values of electric fields measured in thunderclouds are approximately an order of magnitude lower than the air breakdown (ionization threshold) field. At first glance, this means the impossibility of electron avalanches to form and, as a consequence, the impossibility of a lightning discharge to occur. This circumstance puts the question about the lightning origin physical mechanism on a par with the most amazing mysteries of the nature. For more than half a century of research, several mechanisms have been proposed to solve this problem, among which two main lines can be distinguished. The first group of approaches focuses on the possibility of a streamer or a system of streamers to initiate from the surface of one or several hydrometeors, while the second one interprets lightning initiation as a consequence of the runaway electrons breakdown emerging from the interaction between high-energy cosmic rays and the atmosphere. There are also hybrid scenarios that combine both the ideas. However, in view of certain limitations, none of the proposed approaches has been recognized as the final solution to the problem. The article describes a fundamentally new lightning initiation mechanism that develops sequentially on several spatiotemporal scales. The scenario proposed shows how a series of corona discharges occurring during collisions of hydrometeors seeds the cloud with decimeter-scale elevated ionic conductivity regions, the electric field at the poles of which increases to the level necessary for positive streamers to appear. At the next stage, multiple streamer discharges oriented by the direction of a large-scale electric field are combined into a single plasma network, within which a hot leader channel is formed. The mechanism discussed effectively utilizes small-scale and mesoscale electric field fluctuations arising in a thundercloud and can be implemented if the spatiotemporal frequency of corona discharges, accompanying collisions and near collisions of hydrometeors, and the potential difference between the strong intracloud field zone boundaries exceed 0.1 m-3s-1 and 3 MV, respectively. In contrast to alternative approaches, the proposed lightning initiation scenario can be implemented under the conditions of a typical thundercloud without the need to involve any external auxiliary factors. The study results are presented in three parts. This article gives an introductory part, which sets the general context of the narrative and determines the study aims, and describes the role the detachment of electrons from negative ions plays in the air breakdown field reduction. The authors' lightning initiation scenario based on the results described in the present paper is given in two subsequent publications.

Towards 100% renewable energy systems: The role of hydrogen and batteries

New challenges arise for the accurate modelling of energy systems with a high share of renewable energy. In this context, energy storage technologies become key elements to manage fluctuations in renewable energy sources and electricity demand. The aim of this work is to investigate the role of batteries and hydrogen storage in achieving a 100% renewable energy system. First, the impact of time series clustering on the multi-year planning of energy systems that rely heavily on energy storage is assessed. The results show good accuracy, even for a small number of representative days, which is necessary to limit the computational burden of the optimisation problem. Then, different configurations of carbon-free energy systems are considered by varying the energy storage solution: only-battery, only‑hydrogen, and hybrid scenarios. An island energy system based on photovoltaics and floating offshore wind turbines is used as a demonstrative case study. It is shown that the cost of the only-battery configuration is 155% higher than the cost of the hydrogen-based scenarios. The reason is that the long-term hydrogen-based storage, despite its low round-trip efficiency, avoids costly oversizing of batteries and wind turbines throughout the analysed period. In the selected case study, hydrogen storage reduces the total rated power of the wind farm by about 5 times compared to the only-battery system. Hydrogen-based solutions are therefore crucial in 100% renewable energy systems to achieve energy self-sufficiency in a cost-effective way.

Discovery of a Filamentary Synchrotron Structure Connected to the Coherent Magnetic Field in the Outer Galaxy

Using data from the Galactic Arecibo L-band Feed Array Continuum Transit Survey, we report the discovery of two previously unidentified, very compressed, thin, and straight polarized filaments approximately centered at Galactic coordinates, (l, b) = (182.°5, − 4.°0), which we call G182.5–4.0. Using data from the Isaac Newton Telescope Galactic Plane Survey, we also find straight, long, and extremely thin Hα filaments coincident with the radio emission. These filaments are positioned in projection at the edge of the Orion-Eridanus superbubble and we find evidence indicating that the filaments align with the coherent magnetic field of the outer Galaxy. We find a lower limit on the total radio flux at 1.4 GHz to be 0.7 ± 0.3 Jy with an average linearly polarized fraction of . We consider various scenarios that could explain the origin of these filaments, including a shell-type supernova remnant (SNR), a bow shock nebula associated with a pulsar, or relic fragments from one or more supernova explosions in the adjacent superbubble, with a hybrid scenario being most likely. This may represent an example of a new class of objects that is neither an SNR nor a bow shock. The highly compressed nature of these filaments and their alignment with the Galactic plane suggests a scenario where this object formed in a magnetic field that was compressed by the expanding Orion-Eridanus superbubble, suggesting that the object is related to this superbubble and implying a distance of ∼400 pc.

A comprehensive study of the vector leptoquark with U(1)B3-L2 on the B-meson and muon g − 2 anomalies

Abstract Recently reported anomalies in various B-meson decays and also in the anomalous magnetic moment of muon (g − 2)μ motivate us to consider a particular extension of the standard model incorporating new interactions in the lepton and quark sectors simultaneously. Our minimal choice would be the leptoquark. In particular, we take the vector leptoquark (U1) and comprehensively study all related observables including ${(g-2)_{\mu }},\ R_{K^{(*)}},\ R_{D^{(*)}}$, B → (K)ℓℓ′, where ℓℓ′ are various combinations of μ and τ, and also lepton flavor violation in the τ decays. We find that a hybrid scenario with an additional $U(1)_{B_3-L_2}$ gauge boson provides a common explanation for all these anomalies.

Assessment of outdoor shading strategies to improve outdoor thermal comfort in school courtyards in hot and arid climates

• To encourage students to perform different activities and interact in open spaces of school • to improve OTC for students in school courtyards located in a hot, arid climate. • Significant reduction in the PET for courtyard temperatures based on the ENVI-met model reached 18.5°C • To integrate hybrid scenarios of staggered shading and trees whether in the current schools or in the early design stages Schools in hot arid climate depend on courtyard to encourage students’ for social activity. In order to improve Outdoor Thermal Comfort (OTC), applying passive mitigation strategies in the courtyard is critical issue. This paper aims to improve students’ thermal comfort in school courtyards throughout the study of a public school with an E-shaped style in New Assiut City. Hence, different shading strategies (shading with different heights, vegetation, and hybrid) are simulated by using ENVI-met model v 5.0.0 to improve OTC for students in school courtyards. Firstly, monitoring was conducted inside outer courtyards. Then nine scenarios of passive strategies were implemented inside two courtyards with a ratio H/W = 0.4 and 0.7. After that, Physiological Equivalent Temperature (PET) was used to compare different scenarios. The results found, by applying hybrid orthogonal and diagonal staggered shading with trees in wide canyons, significant reductions of PET values reached 18.5°C and 18.6°C respectively. In addition, the shading at height= 4 m hybrid with trees achieves the best OTC improvement in the school courtyards. Thus, PET values were located in comfortable and slightly warm ranges for wide courtyard with H/W ratio = 0.4, and this result is more sufficient than in deep canyon with H/W = 0.7. Hence, the study provides information for architects and planners to integrate hybrid scenarios of staggered shading and trees whether in the current schools or in the early design stages for them to reduce heat stress and improve students’ thermal comfort.

Task assignment for hybrid scenarios in spatial crowdsourcing: A Q-Learning-based approach

With the increasing popularity of smart devices and spatio-temporal crowdsourcing, a new data gathering and perception approach combined with edge computing have made exceptional development in solving crowdsourcing problems. As a basic component of the spatio-temporal crowdsourcing system, task assignment seeks to arrange suitable workers for tasks. Existing research is mostly concerned with dynamic and static circumstances. On the other hand, dynamic scenarios cannot meet the advanced understanding of workers who arrive dynamically, and static scenarios cannot match the dynamic requirements of real situations. This paper provides a framework for Latency Time Based Task Assignment with Online and Offline (LTB-TAOO). This framework dynamically receives workers and tasks from the perspective of full assignment process. The static assignment method is utilized throughout the job assignment algorithm. A Q-Learning Based Task Algorithm for LTC (QL-LTC) algorithm is proposed to address the problem of latency time compute (LTC) in the LTB-TAOO framework. In order to improve the efficiency and accuracy of the LTB-TAOO framework, a new state transition Q-Learning based task assignment for LTC (NSQL-LTC) algorithm is applied after optimizing the state transition matrix and reward mechanism. Finally, the proposed methods’ effectiveness and efficiency are evaluated by conducting extensive experiments based on real datasets.

Performance analysis of the centroid method predictor implemented in the JET real time network

Recently, a linear disruption predictor (Vega et al 2020 Nucl. Fusion 60 026001) was installed in the JET real-time network for disruption mitigation purposes. From a mathematical point of view, the predictor is based on computing centroids of disruptive examples and non-disruptive examples in a two-dimensional space. This is the reason for calling it centroid method (CM). It uses a single signal: the mode lock normalized to the plasma current. The predictor is not based on thresholds to trigger alarms but on the differences of amplitudes between consecutive samples. The article analyses its results for the range of discharges 94 152–97 137 (June 2019–March 2020), including discharges of both baseline scenario and hybrid scenario. The article presents a comparison between the CM predictor and several different disruption detection systems operational in the JET real-time event detection platform named PETRA (Plasma Events Triggering for Alarms). The CM predictor outperforms all the other classifiers implemented in PETRA, according to all the main statistical indicators normally used to qualify these tools.

Assessing K-12 school reopenings under different COVID-19 Spread scenarios – United States, school year 2020/21: A retrospective modeling study

IntroductionSchool-age children play a key role in the spread of airborne viruses like influenza due to the prolonged and close contacts they have in school settings. As a result, school closures and other non-pharmaceutical interventions were recommended as the first line of defense in response to the novel coronavirus pandemic (COVID-19). MethodsWe used an agent-based model that simulates communities across the United States including daycares, primary, and secondary schools to quantify the relative health outcomes of reopening schools for the period of August 15, 2020 to April 11, 2021. Our simulation was carried out in early September 2020 and was based on the latest (at the time) Centers for Disease Control and Prevention (CDC)’s Pandemic Planning Scenarios released in May 2020. We explored different reopening scenarios including virtual learning, in-person school, and several hybrid options that stratify the student population into cohorts in order to reduce exposure and pathogen spread. ResultsScenarios where cohorts of students return to school in non-overlapping formats, which we refer to as hybrid scenarios, resulted in significant decreases in the percentage of symptomatic individuals with COVID-19, by as much as 75%. These hybrid scenarios have only slightly more negative health impacts of COVID-19 compared to implementing a 100% virtual learning scenario. Hybrid scenarios can significantly avert the number of COVID-19 cases at the national scale–approximately between 28 M and 60 M depending on the scenario–over the simulated eight-month period. We found the results of our simulations to be highly dependent on the number of workplaces assumed to be open for in-person business, as well as the initial level of COVID-19 incidence within the simulated community. ConclusionIn an evolving pandemic, while a large proportion of people remain susceptible, reducing the number of students attending school leads to better health outcomes; part-time in-classroom education substantially reduces health risks.

ν = 0 quantum Hall state in a cadmium arsenide thin film

Graphene and topological insulators can feature a unique quantum Hall state with a filling factor of ν = 0 that supplies a wealth of information about the nature of the underlying electronic states. Here, we report on the observation of a ν = 0 Hall state in magnetotransport experiments on a 20-nm-thin, (001)-oriented cadmium arsenide film that is tuned by a gate voltage. While cadmium arsenide is a topological semimetal as a bulk material, thin films can host topological insulator phases. At high magnetic fields, we observe a highly resistive ν = 0 Hall state that we attribute to a widening gap between two zeroth Landau levels as the magnetic field is increased. We discuss possible scenarios that could give rise to the lifting of the degeneracy of zeroth Landau levels. Our results are most consistent with a scenario of hybridization of the topological surface states induced by quantum confinement.

Discussion on “Providing renewable cooling in an office building with a Ground–Source heat pump system hybridized with natural ventilation & personal comfort systems”, energy and buildings 261 (2022), 111,982

Climate change will increase the magnitude and frequency of high temperatures, resulting in higher cooling demands in buildings and a possible diminished efficacy of the passive solutions that could be used to limit that increased demand. However, building energy simulations are often performed with past weather data files, ignoring the effect of the changing climate.Portuguese building certification regulations use standard TMY (typical meteorological year) weather files that were updated with RCP4.5 predictions. These updated weather files were used to reassess the impact of climate change on a hybridized ground–source heat pump (GSHP) system with piles, natural ventilation (NV) and personal comfort systems (PCS). Cooling loads increased the most in Porto and the least in Faro, varying from 3 to 163%, with the exception of the GSHP–NV–PCS hybrid scenario in Lisbon, where the cooling load decreased 27%. This increased unbalance of the thermal loads resulted in a higher build–up of heat in the ground, decreasing the fraction of load that could be covered by the GSHP, especially in Porto. Despite the increase in final energy needs for heating and cooling, the GSHP–NV–PCS approach is a resilient solution to supply heating and cooling in a warming climate, as it can still reduce final energy consumption by more than 90%, relative to a non–hybrid approach.

Deadline-Aware Dynamic Task Scheduling in Edge–Cloud Collaborative Computing

In recent years, modern industry has been exploring the transition to cyber physical system (CPS)-based smart factories. As intelligent industrial detection and control technology grows in popularity, massive amounts of time-sensitive applications are generated. A cutting-edge computing paradigm called edge-cloud collaborative computing was developed to satisfy the need of time-sensitive tasks such as smart vehicles and automatic mechanical remote control, which require substantially low latency. In edge-cloud collaborative computing, it is extremely challenging to improve task scheduling while taking into account both the dynamic changes of user requirements and the limited available resources. The current task scheduling system applies a round-robin policy to cyclically select the next server from the list of available servers, but it may not choose the best-suited server for the task. To satisfy the real-time task flow of industrial production in terms of task scheduling based on deadline and time sensitivity, we propose a hierarchical architecture for edge-cloud collaborative environments in the Industrial Internet of Things (IoT) and then simplify and mathematically formulate the time consumption of edge-cloud collaborative computing to reduce latency. Based on the above hierarchical model, we present a dynamic time-sensitive scheduling algorithm (DSOTS). After the optimization of DSOTS, the dynamic time-sensitive scheduling algorithm with greedy strategy (TSGS) that ranks server capability and job size in a hybrid and hierarchical scenario is proposed. What cannot be ignored is that we propose to employ comprehensive execution capability (CEC) to measure the performance of a server for the first time and perform effective server load balancing while satisfying the user’s requirement for tasks. In this paper, we simulate an edge-cloud collaborative computing environment to evaluate the performance of our algorithm in terms of processing time, SLA violation rate, and cost by extending the CloudSimPlus toolkit, and the experimental results are very promising. Aiming to choose a more suitable server to handle dynamically incoming tasks, our algorithm decreases the average processing time and cost by 30% and 45%, respectively, as well as the average SLA violation by 25%, when compared to existing state-of-the-art solutions.

Heterogeneous Transfer Learning for Wi-Fi Indoor Positioning Based Hybrid Feature Selection.

This paper presents the application of heterogeneous transfer learning (HetTL) methods which consider hybrid feature selection to reduce the training calibration effort and the noise generated by fingerprint duplicates obtained from multiple Wi-Fi access points. The Cramer–Rao Lower Bound analysis (CRLB) was also applied to evaluate and estimate a lower limit for the variance of a parameter estimator used to analyze positioning performance. We developed two novel algorithms for feature selection in fingerprint-based indoor positioning problems (IPP) to enhance positioning performance in the target domain with the HetTL. The algorithms comprised two scenarios: (i) a principal component analysis-based approach (PCA-based) and (ii) a hybrid approach that takes both PCA and correlation effect analysis into account (hybrid scenario). Accordingly, a new feature vector was constructed by retaining only the most significant predictors, and the most efficient feature dimensions were also determined by using a hybrid-based approach. Experimental results showed that the hybrid-based proposed algorithm has the minimum mean absolute error. The CRLB analysis also showed that the number of Wi-Fi access points could affect the lower bound location estimation error; however, identifying the most significant predictors is an effective approach to improve positioning performance.

Simulations of energetic alpha particle loss in the presence of toroidal field ripple in the CFETR tokamak

Energetic alpha particle losses with the toroidal field ripple and the Coulomb collision in the CFETR tokamak have been simulated by using the orbit-following code GYCAVA for the steady-state and hybrid scenarios. The effects of the outer boundary and the ripple amplitude on alpha particle losses have been investigated. The loss fractions and heat loads of alpha particles in the hybrid scenario are much smaller than those in the steady-state scenario for a significant ripple amplitude. Some alpha particles in the plasma core are lost due to the ripple stochastic transport for a large ripple amplitude parameter. The heat loads with the last closed flux surface boundary are different from those with the wall boundary for the CFETR tokamak, which can be explained by typical alpha particle orbits. Discrete heat load spots have been observed in alpha particle loss simulations, which is due to the ripple well loss. The transition of the lost alpha particle behavior from the ripple stochastic diffusion to the ripple well trapping has been identified in our CFETR simulations. The Coulomb collision effect is responsible for this transition.

Simulation as an Alternative to Women's Health Clinical Rotations for Ultra-Orthodox Men: A Pilot Study of Cultural Adjustment

BackgroundDue to the cultural needs of male Jewish Ultra-Orthodox nursing students, the entire women's health clinical rotation in our nursing program was replaced with simulation training. This study sought to determine student and teacher satisfaction and student knowledge and skill acquisition during a pilot of an alternative method of instruction. MethodsParticipants, a total of 96 Ultra-Orthodox male students from four student cohorts. Six clinical settings were created, with 32 hybrid scenarios, covering 47 clinical situations. The program's evaluation was based on student and instructor feedback and pre-post knowledge exams. ResultsStudents and instructors reported that the training improved students' skills and readiness to practice. Students significantly improved their post-course knowledge score and were comfortable taking care of female standardized patients in common women's health clinical settings. ConclusionsSimulation was found to be an effective and feasible way to meet curriculum requirements while also addressing the cultural needs of male Ultra-Orthodox nursing students.