ARDENT - An Augmented Reality Framework for Education

Virtual Reality (VR) in education and medicine has been a widely researched area. Increase in motivation and learning gain is demonstrated to be directly related to introduction of VR applications. However, the necessity for expensive and bulky hardware limits the usability of VR. This problem can be partially solved by using Augmented Reality (AR), which is readily available in most modern smart devices. In later years the same kind of research has been increasing for AR, but to a lesser extent. This increase might be attributed to improved affordability and the rapid technological advances of smart devices. ARDENT is a framework for the standard development of an AR application and its swift deployment across diverse smart device platforms. The framework seeks to make it as effortless as possible for a user to deploy their models before a multitude of other users can see these models through their smart devices. Finally, this framework is showcased in a one-to-many teacher-student relationship for a seamless in-class AR experience

ARDENT - An Augmented Reality Framework for Education

Virtual Reality (VR) in education and medicine has been a widely researched area. Increase in motivation and learning gain is demonstrated to be directly related to introduction of VR applications. However, the necessity for expensive and bulky hardware limits the usability of VR. This problem can be partially solved by using Augmented Reality (AR), which is readily available in most modern smart devices. In later years the same kind of research has been increasing for AR, but to a lesser extent. This increase might be attributed to improved affordability and the rapid technological advances of smart devices. ARDENT is a framework for the standard development of an AR application and its swift deployment across diverse smart device platforms. The framework seeks to make it as effortless as possible for a user to deploy their models before a multitude of other users can see these models through their smart devices. Finally, this framework is showcased in a one-to-many teacher-student relationship for a seamless in-class AR experience

Creatinine-based renal function estimates and dosage of postoperative pain management for elderly acute hip fracture patients

Many analgesics and their metabolites are renally excreted. The widely used Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)-estimated glomerular filtration rate (eGFR) equations are not developed for use in the elderly, while the recent Berlin Initiative Study (BIS), Full Age Spectrum (FAS), and Lund-Malmö revised (LMR) equations are. This observational study investigated differences between creatinine-based eGFR equations and how the choice of equation influences dosage of analgesics in elderly (≥70 years) patients admitted with acute hip fracture. eGFR was calculated by the CKD-EPI, BIS, Cockcroft-Gault (CG), FAS, LMR, and Modification of Diet in Renal Disease (MDRD) equations. Standard daily dose for postoperative pain medications ibuprofen, morphine and gabapentin was simulated for each equation according to dosage recommendations in Renbase®. For 118 patients, mean eGFR from the CKD-EPI, BIS, CG, FAS, LMR, and MDRD equations was 67.3 mL/min/1.73 m2, 59.1 mL/min/1.73 m2, 56.9 mL/min/1.73 m2, 60.3 mL/min/1.73 m2, 58.9 mL/min/1.73 m2, and 79.1 mL/min/1.73 m2, respectively (p < 0.0001). Mean difference to CKD-EPI was −10.4 mL/min/1.73 m2 to 11.8 mL/min/1.73 m2. Choice of eGFR equation significantly influenced the recommended dose (p < 0.0001). Shifting to BIS, FAS, or LMR equations led to a lower recommended dose in 20% to 31% of patients. Choice of eGFR equation significantly influenced dosing of ibuprofen, morphine, and gabapentin

ARDENT - An Augmented Reality Framework for Education

Virtual Reality (VR) in education and medicine has been a widely researched area. Increase in motivation and learning gain is demonstrated to be directly related to introduction of VR applications. However, the necessity for expensive and bulky hardware limits the usability of VR. This problem can be partially solved by using Augmented Reality (AR), which is readily available in most modern smart devices. In later years the same kind of research has been increasing for AR, but to a lesser extent. This increase might be attributed to improved affordability and the rapid technological advances of smart devices. ARDENT is a framework for the standard development of an AR application and its swift deployment across diverse smart device platforms. The framework seeks to make it as effortless as possible for a user to deploy their models before a multitude of other users can see these models through their smart devices. Finally, this framework is showcased in a one-to-many teacher-student relationship for a seamless in-class AR experience

The Dalton quantum chemistry program system

Dalton is a powerful general-purpose program system for the study of molecular electronic structure at the Hartree–Fock, Kohn–Sham, multiconfigurational self-consistent-field, Møller–Plesset, configuration-interaction, and coupled-cluster levels of theory. Apart from the total energy, a wide variety of molecular properties may be calculated using these electronic-structure models. Molecular gradients and Hessians are available for geometry optimizations, molecular dynamics, and vibrational studies, whereas magnetic resonance and optical activity can be studied in a gauge-origin-invariant manner. Frequency-dependent molecular properties can be calculated using linear, quadratic, and cubic response theory. A large number of singlet and triplet perturbation operators are available for the study of one-, two-, and three-photon processes. Environmental effects may be included using various dielectric-medium and quantum-mechanics/molecular-mechanics models. Large molecules may be studied using linear-scaling and massively parallel algorithms. Dalton is distributed at no cost from http://www.daltonprogram.org for a number of UNIX platforms