Simpson University

Although there is a growing evidence base for systemic working with people with a learning disability, this primarily has been presented through case studies. This article will focus on the reflections gathered from a reflecting team to consider how systemic provision in a community learning disability service could be improved. Key findings from a 6-phase reflexive thematic analysis proposed that two-three reflectors in a reflecting team, alongside pre and post debrief sessions with easy-read leaflets to support these was helpful. Considerations were also given to whether the reflecting team online or in person encourages a full systemic experience, and how best to conduct systemic supervision is also discussed. The findings from this evaluation may be transferable to systemic provision more broadly. Easy to read summary ■ People with a learning disability often have a system around them. This system can include lots of different people such as their family, friends, partners, professionals or staff team. ■ Working with the system can help everyone to understand each other and work together to make things better. ■ Staff from a psychology team have shared their thoughts about how to make their work with systems better. ■ Providing support before, during and after this work with systems can be helpful for all involved. Also holding sessions face-to-face can be more effective than online.

The most prevalent form of malignant tumors that originate in the brain are known as gliomas. In order to diagnose, treat, and identify risk factors, it is crucial to have precise and resilient segmentation of the tumors, along with an estimation of the patients’ overall survival rate. Therefore, we have introduced a deep learning approach that employs a combination of MRI scans to accurately segment brain tumors and predict survival in patients with gliomas. To ensure strong and reliable tumor segmentation, we employ 2D volumetric convolution neural network architectures that utilize a majority rule. This method helps to significantly decrease model bias and improve performance. Additionally, in order to predict survival rates, we extract radiomic features from the tumor regions that have been segmented, and then use a Deep Learning Inspired 3D replicator neural network to identify the most effective features. The model presented in this study was successful in segmenting brain tumors and predicting the outcome of enhancing tumor and real enhancing tumor. The model was evaluated using the BRATS2020 benchmarks dataset, and the obtained results are quite satisfactory and promising.

Perinatal nurses in the United States who care for patients during labor, birth, and postpartum have witnessed the increase in rates of induction of labor (Figure) over the last decade (Centers for Disease Control and Prevention & National Center for Health Statistics, 2024; Hamilton et al., 2015; Martin et al., 2015; Martin et al., 2017), in part due to publication of the ARRIVE trial (Grobman et al., 2018; Wood et al., 2023). Compared to expectant management for low-risk nulliparous women, induction of labor at 39 weeks when conducted under the conditions described in the trial was found to be safe and offered a lower risk of cesarean birth and development of hypertensive disorders of pregnancy, although there was no significant difference in the primary outcome of a composite of perinatal death or severe neonatal complications (Grobman et al., 2018). These benefits have not been found in all studies (Grobman, 2024). Cost of overall care may be lower due to fewer prenatal visits, fewer obstetric triage visits, and lower rates of cesarean and hypertensive disorders of pregnancy; however, the costs of a longer labor and staffing requirements for 1 nurse to 1 patient receiving oxytocin are shifted to inpatient maternity units (Grobman, 2024). Women having induction of labor need adequate information about the process including pros and cons so they can be full partners in their care and decision-making (Runyon, 2023). Safe care during labor induction requires nurse staffing as per the nurse staffing standards from the Association of Women's Health, Obstetric and Neonatal Nurses (2022).Figure:: Induction of Labor in the United States 2013 to 2022

The purpose of this study is to investigate how the level of controls testing coordination with the external auditor affects internal auditors' effort. The internal auditor's planned substantive testing audit hours are the measure of effort in this study. Regulators and stakeholder organizations have encouraged more collaboration between external and internal auditors to improve audit efficiency. The effect of external auditor coordination on internal auditors' planned audit hours has important implications for audit efficiency and effectiveness. An experiment is conducted with 112 internal auditors to examine the hypothesized effect. The study uses a 2 × 2 between-subjects design and manipulates fraud risk and external auditor coordination. Consistent with my prediction, I find that coordination moderates the relationship between fraud risk and planned audit hours. The results illustrate that although high external auditor controls testing coordination decreases internal auditors' planned substantive testing audit hours, internal auditors are more sensitive to responding to fraud risk when external auditor controls testing coordination is high.

The development of the world of education now continues to strive to improve the quality of the implementation of the learning process to produce graduates who can compete in the world of work, and have creativity and critical thinking skills. The government also plays a role in improving the quality of school management through decentralization of education in the form of school-based management and the provision of an independent learning curriculum. The aim of independent learning is the development of superior quality human resources. Therefore, this article aims to answer the question of how to optimize school-based management in the era of independent learning. The purpose of this study is to describe the optimization of school-based management in the era of independent learning. The research method used is a literature study by exploring various data sources and the results of research that has been carried out on school-based management and the independent learning curriculum. The results showed that school-based management supports the process of implementing learning in improving the quality of education in Indonesia. By taking into account the current educational curriculum, freedom of learning, becomes a guideline for managers of educational institutions to produce graduates of superior quality. Two important aspects of school-based management in improving the quality of education are managerial aspects and learning aspects.

Two methods were developed to estimate updated mean seismic hazard for existing probabilistic seismic hazard analyses (PSHAs) due to a change in the ground motion model (GMM). Both methods were used to estimate updated hazard at nuclear power plant (NPP) sites in the Central and Eastern United States (CEUS) for a change from the Electric Power Research Institute (EPRI) 2013 GMM to the Next Generation Attenuation (NGA)‐East GMM. These methods present efficient tools to inform decisions on whether to perform a full PSHA revision or other detailed evaluations, especially when a large number of sites must be analyzed. A Simplified Hazard (SiHaz) method was developed to estimate mean hazard explicitly using a reduced PSHA logic tree that incorporates the updated GMM and potential changes in the site response model. An alternative scaling method was independently developed to be applied directly to current CEUS NPP hazard. Both methods were validated using updated PSHA results at several sites. Estimates at 46 NPP sites using both methods showed good agreement for mean annual frequencies of exceedance between 1E‐4 and 1E‐5/yr.

Soft microfluidic systems that capture, store, and perform biomarker analysis of microliter volumes of sweat, in situ, as it emerges from the surface of the skin, represent an emerging class of wearable technology with powerful capabilities that complement those of traditional biophysical sensing devices. Recent work establishes applications in the real-time characterization of sweat dynamics and sweat chemistry in the context of sports performance and healthcare diagnostics. This paper presents a collection of advances in biochemical sensors and microfluidic designs that support multimodal operation in the monitoring of physiological signatures directly correlated to physical and mental stresses. These wireless, battery-free, skin-interfaced devices combine lateral flow immunoassays for cortisol, fluorometric assays for glucose and ascorbic acid (vitamin C), and digital tracking of skin galvanic responses. Systematic benchtop evaluations and field studies on human subjects highlight the key features of this platform for the continuous, noninvasive monitoring of biochemical and biophysical correlates of the stress state.

Abstract

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