Purdue University Global

The integration of simulation into nursing education is essential for providing safe, structured, and effective clinical learning experiences. This paper presents findings from the 2024 review of simulation regulations in nursing education across the United States and Canada. The authors conducted a descriptive study of simulation regulations in the United States and Canada and compared findings to the results of previous simulation regulation reviews to identify changes in regulations that occurred since 2022. This study noted simulation regulations in 90% of U.S. states and 15% of Canadian provinces. Clinical replacement ratios ranged from 1:1 to 2:1, with limits from 25 to 100% in both countries. Canadian regulations did not elaborate on the use of virtual simulation, simulation best practice, or accreditation standards. Regulations in the United States mentioned virtual simulation in 12 states. Regulations referenced best practice standards in 26% of states; accreditation in 10%. Regulation rose from 35% in 2014 to 68.3% in 2022; and is now at 90% in the United States. This review provides updated information on the evolving, yet inconsistent regulations for simulation education across the United States and Canada. These findings demonstrate an increase in formalized simulation use with continued variability in some key regulatory areas.

We examine how organizational structure affected internal liquidity mobilization during the Global Financial Crisis using quarterly data on U.S. bank holding companies (BHCs) from 2006 to 2010. The analysis addresses endogeneity using instrumental variables and pre-crisis measurement of organizational structure. Nonbank subsidiaries became an important liquidity source during the crisis, but this effect weakened among the largest BHCs unless they had high organizational complexity. High-complexity BHCs maintained effectiveness at large scale, with advantages concentrated when rapid response is most valuable (early crisis) and when managing many subsidiaries. These timing and subsidiary-count patterns distinguish coordination capacity from alternative mechanisms such as information advantages or regulatory optimization. The findings suggest supervisors should assess organizational coordination capacity alongside size-based metrics when evaluating crisis preparedness.

This study presents a reproducible evaluation framework for hybrid quantum-classical neural networks (HQCNNs) in healthcare classification, rather than a new architecture. We assess a four-qubit HQCNN combining a compact classical encoder, a two-layer parameterized quantum circuit (PQC), and a classical readout (441 trainable parameters) against carefully tuned classical baselines on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset under identical five-fold cross-validation. The work is framed as a single-dataset proof-of-concept: the contribution is a documented, shared-fold evaluation protocol with a parameter-matched classical control and a quantified epistemic-informativeness analysis, not a demonstration of general quantum advantage. The HQCNN reached 96.49±1.96% accuracy and 99.44±0.60% ROC-AUC. A parameter-matched classical multilayer perceptron (441 parameters) reached 95.08±1.81% accuracy; the HQCNN’s +1.41 percentage-point edge at equal capacity was not statistically significant (paired t, p=0.056). Across five shared folds, no HQCNN-versus-classical accuracy difference survived Holm–Bonferroni correction (all adjusted p≥0.625), so we report the HQCNN as competitive with, not superior to, strong tuned classical baselines. A multi-split depth ablation showed that circuit depth L∈{1,2,3} had no statistically detectable effect on accuracy (L=2 vs. L=3: Wilcoxon p=1.00); we therefore adopt two variational layers as a practical default rather than an optimum. Under a low-noise simulator (depolarising and amplitude-damping channels, p=0.01), accuracy was 96.49%, indicating robustness only at modest uniform error rates; realistic hardware noise is higher. We additionally apply Bayesian surprise as an epistemic-informativeness heuristic—not a formal generative model—to rank which findings are most worth building on. The framework offers a reproducible, documented evaluation procedure that can support cumulative comparison of hybrid quantum-classical models in healthcare.

The multifaceted nature and the quantity of digital assaults has been expanding constantly which induces that the security frameworks that are being used today have restricted accomplishment in keeping these advanced assaults. By incorporating Responsible AI, we can predict the possible threat patterns to get guardrails applied. Advanced Persistent Threats like Stuxnet, hacking group RCS, Red October, Wild Neutron and all the more as of late Carbanak have further lessened the trust in present security frameworks. In this paper, we have performed the specialized investigation of these Advanced Persistent Threats which highlights their individual salient features and identify common patterns among them. This analysis will assist us to think of a skeletal structure for all the APT’s which in turn assists in concocting a cautious defensive mechanism to identify similar threats in future. This paper sheds light on methodologies as well as research covered on the mentioned in depth.

Creating an equity-minded classroom in the online environment that supports the belonging, success, and graduation rates of lesbian, gay, bisexual, transgender, queer, intersex, asexual, two-spirit, and other non-heteronormative identifying college students is challenging. Previous research indicates that these students are at risk both academically and psychologically because of political and social threats to their identities and the trauma they may bring to their college experience. This study found that instructor attitudes towards these online students has a profound impact on whether instructors recognize the relevance of gender identity and sexual orientation to the learning process and whether they take the steps necessary to create an equity-minded classroom that supports particular historically minoritized student populations. The online classroom may contribute to whether instructors respect and support these students' identities, positively impact their sense of belonging, and respond to the microaggressions and homo/queer/transphobia they may encounter at college.