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We study two-stage short-term staffing adjustments for the upcoming nursing shift. Our proposed adjustments are first used at the beginning of each 4-hour nursing shift, shift t, for the upcoming shift, shift t + 1. Then, after observing actual patient demand for nursing at the start of shift t + 1, we make our final staffing adjustments to meet the patient demand. We model six different adjustment options for the two-stage stochastic programming model, five options available as first-stage decisions and one option available as the second-stage decision. We develop a two-stage stochastic integer programming model, which minimizes total nurse staffing costs and the cost of adjustments to the original schedules, while ensuring the coverage of nursing demand. Our experimental results, using the data from an urban Children's Hospital, indicate that the developed stochastic nurse schedule adjustment model can deliver cost savings up to 18% for the medical units, compared to alternative no short-term adjustment scheduling models. The proposed stochastic adjustments model successfully keeps average understaffing percentages under 2% throughout the staffing horizon. [ABSTRACT FROM AUTHOR]

Floods remain a wicked-problem and are becoming more destructive with widespread ecological, social and economic impacts. The problem is particularly acute in modified formerly pristine, mountainous river-catchments where plausible assumptions of risk-behaviour relevant to flood exposure and vulnerability are crucial for robust early warning system development. In particular more focused conversation with the community-at-risks is required. In such context, we advocate the use of a SMART -approach to facilitate bottom-up initiatives to facilitate development of inclusive and purposeful early warning systems that benefit the community-at-risk by engaging them every step of the way along with including other stakeholders at multiple-scales of operations. [ABSTRACT FROM AUTHOR]

This work examines medium-term integrated nurse staffing policy options for hospital Intensive Care Units (ICU) Our aim is to reduce nurse staffing costs while balancing the under/ over-staffing risks. Medium-term nurse schedules are highly uncertain as they are generated long before actual patient demand is realised. Optimisation models presented in this study allow us to examine fixed versus dynamic nurse staffing policy options for the medical units. In the dynamic nurse staffing, we utilise historical patient data to fit estimates of non-stationary patient demand. We compare the performance of both policy options with the optimal staffing scheme reached by the actual patient data. We generate feasible schedules for nurse sub-groups to avoid complete enumeration. We evaluate the performance of models with the pediatric ICU of a large urban children's hospital. Experiments with the dynamic policy resulted in more than 3% higher average cost savings compared to the fixed staffing policies. [ABSTRACT FROM AUTHOR]

This study models counseling research as a social action process while highlighting multicultural counselor identity. Seven co-researchers/participants possessing a shared counselor identity engaged in a community-based reflexive contemplative practice group which aimed at dismantling the power imbalance that normally exists between researchers and participants while remaining cognizant of the insidious influence of white supremacy in the research process. The data collected represents the content and process reflections on participating in this group which invited contemplation about identity on many different levels. Several themes emerged from the data as did implications for counseling research and practice. [ABSTRACT FROM AUTHOR]

The obesity pandemic currently affects more than 70 million Americans and more than 650 million individuals worldwide. In addition to increasing susceptibility to pathogenic infections (eg, SARS-CoV-2), obesity promotes the development of many cancer subtypes and increases mortality rates in most cases. We and others have demonstrated that, in the context of B-cell acute lymphoblastic leukemia (B-ALL), adipocytes promote multidrug chemoresistance. Furthermore, others have demonstrated that B-ALL cells exposed to the adipocyte secretome alter their metabolic states to circumvent chemotherapy-mediated cytotoxicity. To better understand how adipocytes impact the function of human B-ALL cells, we used a multi-omic RNA-sequencing (single-cell and bulk transcriptomic) and mass spectroscopy (metabolomic and proteomic) approaches to define adipocyte-induced changes in normal and malignant B cells. These analyses revealed that the adipocyte secretome directly modulates programs in human B-ALL cells associated with metabolism, protection from oxidative stress, increased survival, B-cell development, and drivers of chemoresistance. Single-cell RNA sequencing analysis of mice on low- and high-fat diets revealed that obesity suppresses an immunologically active B-cell subpopulation and that the loss of this transcriptomic signature in patients with B-ALL is associated with poor survival outcomes. Analyses of sera and plasma samples from healthy donors and those with B-ALL revealed that obesity is associated with higher circulating levels of immunoglobulin-associated proteins, which support observations in obese mice of altered immunological homeostasis. In all, our multi-omics approach increases our understanding of pathways that may promote chemoresistance in human B-ALL and highlight a novel B-cell-specific signature in patients associated with survival outcomes., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)