Saint Peter's University

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with non-tensor-product or poorly shaped tensor-product elements. To overcome this, we introduce ApSEM (AES-FEM post-processed Spectral Element Method) to recover the accuracy near the curved boundaries when solving elliptic PDEs. The combination of curvature-based geometric refinement (Jones et al. in Eng Comput 40:1877–1892, 2024) and accurate post-processing offers an effective alternative to methods that rely on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 3D and show up to two orders of magnitude improvement in solution accuracy, even when the elements are poorly shaped near curved boundaries. We also show the efficiency of ApSEM as it can recover superconvergence in nodal solutions without significantly increasing computational cost.

Choosing which features to retain from a high-dimensional dataset is one of the more practically consequential decisions in building a machine learning pipeline, yet it is rarely treated as anything other than a preprocessing afterthought. In this paper we ask whether quantum computation can play a meaningful role in that decision. We present Variational Quantum Feature Selection (VQFS), a method that assigns trainable scalar weights to input features and folds those weights directly into the rotation angles of a parameterized quantum circuit. An Ll penalty on the weight vector encourages many weights to collapse toward zero during training, leaving a compact subset of features that the circuit has learned to rely on. Because the weights are differentiable, the whole system-feature selector and quantum classifier together-is trained end-to-end with gradient descent rather than through the combinatorial search that makes classical wrapper methods expensive. We built VQFS on top of the PennyLane simulator so that it runs on an ordinary laptop without access to quantum hardware. Testing on the Breast Cancer Wisconsin, Wine, and Iris benchmarks, we found that VQFS matched or beat five classical baselines (Lasso, PCA, Random Forest importance, Mutual Information, and RFE) on accuracy while cutting the feature count by 25-60%. Five-fold cross-validation showed the gains were consistent rather than the result of a lucky split. We see this work as a small but concrete step toward integrating quantum methods into the full machine learning workflow, not just the classification stage.

This article examines labor-market barriers relevant to refugee integration in the United States and translates those patterns into practical recommendations for community-based enrichment programs. Because consistent annual refugee-only national time series are limited, the empirical section uses annual U.S. foreign-born indicators for 2012-2022 as a contextual proxy. The analysis combines trend review, descriptive statistics, correlation matrices, and exploratory ordinary least squares models linking unemployment to citizenship status, sex composition, marital status, home-language patterns, and region-of-birth shares. The descriptive trends show declining unemployment through 2019, a pandemic-era increase in 2020-2021, and partial recovery in 2022. Across the exploratory models, marital status is positively associated with unemployment in the Asia and Latin America specifications, Latin America is positively associated with unemployment, and Africa and Asia are negatively associated with unemployment. Language other than English at home is negatively associated with unemployment in the Latin America model after controls. The paper argues that these findings should be interpreted cautiously but the results point to clear programmatic priorities: flexible English instruction, digital-skills training, childcare support, credential navigation, financial literacy, and employer-facing job-readiness services.

According to the October 2024 briefing UK Disability Statistics: Prevalence and Life Experiences, an estimated 11% of children in the UK have a disability consistent with definitions in the Equality Act 2010. Of those, mobility is cited as the most frequently reported, accounting for 48% of the reports. These estimates are based on self-reported data and as such are subject to statistical uncertainty, and reporting is not compulsory, so results must be interpreted as estimates, not definitive, but they are high enough to raise concerns about the need to improve success among students in secondary schools and higher education, particularly in STEM fields that involve laboratory work. These students will need a wide variety of adjustments and may also be accompanied by an assistance dog, with its own need for safe practices in the laboratory.

The usage of cyclophosphamide (CYP) in cancer treatment is associated with organ toxicity, cellular degeneration, and myelosuppression, which result in treatment discontinuation. Its debilitating impact has increased the quest to search for novel substances or measures that will alleviate the adverse effects, while its therapeutic efficiency remains intact. This study evaluated the effects of Magnesium glycinate on cyclophosphamide-induced neurotoxicity in Wistar rats. Forty-eight Wistar rats (eight weeks old) were allocated into four experimental groups (n = 8), as the normal control (A), oral Magnesium glycinate at 22.8 mg/kg (B) and 32.8mg/kg (C), 150mg/kg of CYP (D), CYP/oral magnesium glycinate at 22.8 mg/kg (E) and CYP/oral magnesium glycinate 32.8mg/kg (F). The animal’s body weight was measured weekly. Following the spatial working memory evaluation using the Y-maze. Animals were sacrificed by cervical dislocation, brain tissues excised, followed by the homogenization of the right hemisphere. The supernatant of the homogenates was used to assess the neurotransmitter activities and the levels of brain-derived neurotrophic factor, interleukin 1beta, interleukin 10, and Tumour Necrosis Factor alpha. Furthermore, the left hemisphere was processed for histological evaluation (H&E and Cresyl fast violet stain) and synaptophysin immunoreactivity. Cyclophosphamide induces weight loss, dysregulation of neurotransmitter and modulator activities, and inflammatory marker levels, as well as neurodegeneration and decreased hippocampal synaptophysin immunoreactivity. However, Magnesium glycinate, particularly at 32.8mg, reversed the stated adverse effects. Mg. Glycinate possesses potential therapeutic properties as a supplement in the management of cancer, particularly in alleviating the adverse effects of Cyclophosphamide.