learning organizations

The path of tokamak fusion and International thermonuclear experimental reactor (ITER) is maintaining high-performance plasma to produce sufficient fusion power. This effort is hindered by the transient energy burst arising from the instabilities at the boundary of plasmas. Conventional 3D magnetic perturbations used to suppress these instabilities often degrade fusion performance and increase the risk of other instabilities. This study presents an innovative 3D field optimization approach that leverages machine learning and real-time adaptability to overcome these challenges...

This review article explores the challenges associated with landfill leachate resulting from the increasing disposal of municipal solid waste in landfills and open areas. The composition of landfill leachate includes antibiotics (0.001 to 100 μg), heavy metals (0.001 to 1.4 g/L), dissolved organic and inorganic components, and xenobiotics including polyaromatic hydrocarbons (10-25 μg/L). Conventional treatment methods, such as biological (microbial and phytoremediation) and physicochemical (electrochemical and membrane-based) techniques, are available but face limitations in terms of cost, accuracy, and environmental risks...

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area...

AIM: The purpose of the study was to describe social and healthcare educators' evidence-based healthcare competence and explore the associated factors. DESIGN: A descriptive, cross-sectional study was carried out. METHODS: The research spanned 5 universities, 19 universities of applied sciences, and 10 vocational colleges in Finland from September to December 2022. Social and healthcare educators (n = 256), of which 21 worked at universities, 176 worked at universities of applied sciences, and 49 worked at vocational colleges...

AIM: To explore the experiences, expectations and needs of mothers from low-socioeconomic status at 1 month postpartum. DESIGN: Descriptive qualitative. METHODS: Mothers from low-socioeconomic status and irrespective of their parity were invited to participate in one-to-one interviews at 1 month postpartum. Semi-structured interviews were conducted until data saturation. Interviews were audio recorded, transcribed verbatim and analysed thematically...

Underwater visual detection technology is crucial for marine exploration and monitoring. Given the growing demand for accurate underwater target recognition, this study introduces an innovative architecture, YOLOv8-MU, which significantly enhances the detection accuracy. This model incorporates the large kernel block (LarK block) from UniRepLKNet to optimize the backbone network, achieving a broader receptive field without increasing the model's depth. Additionally, the integration of C2fSTR, which combines the Swin transformer with the C2f module, and the SPPFCSPC_EMA module, which blends Cross-Stage Partial Fast Spatial Pyramid Pooling (SPPFCSPC) with attention mechanisms, notably improves the detection accuracy and robustness for various biological targets...

With the development of biometric identification technology, finger vein identification has received more and more widespread attention for its security, efficiency, and stability. However, because of the performance of the current standard finger vein image acquisition device and the complex internal organization of the finger, the acquired images are often heavily degraded and have lost their texture characteristics. This makes the topology of the finger veins inconspicuous or even difficult to distinguish, greatly affecting the identification accuracy...

Given the high relevance and impact of ransomware in companies, organizations, and individuals around the world, coupled with the widespread adoption of mobile and IoT-related devices for both personal and professional use, the development of effective and efficient ransomware mitigation schemes is a necessity nowadays. Although a number of proposals are available in the literature in this line, most of them rely on machine-learning schemes that usually involve high computational cost and resource consumption...

Studying cell settlement in the three-dimensional structure of synthetic biomaterials over time is of great interest in research and clinical translation for the development of artificial tissues and organs. Tracking cells as physical objects improves our understanding of the processes of migration, homing, and cell division during colonisation of the artificial environment. In this study, the 3D environment had a direct effect on the behaviour of biological objects. Recently, deep learning-based algorithms have shown significant benefits for cell segmentation tasks and, furthermore, for biomaterial design optimisation...

Post-traumatic stress disorder (PTSD) is a debilitating psychological condition that may develop in certain individuals following exposure to life-threatening or traumatic events. Distressing symptoms, including flashbacks, are characterized by disrupted stress responses, fear, anxiety, avoidance tendencies, and disturbances in sleep patterns. The enduring effects of PTSD can profoundly impact personal and familial relationships, as well as social, medical, and financial stability. The prevalence of PTSD varies among different populations and is influenced by the nature of the traumatic event...

With the rapid increase in computer processing capacity over the past two decades, machine learning techniques have been applied in many sectors of daily life. Machine learning in therapeutic settings is also gaining popularity. We analysed current studies on machine learning in robotic urologic surgery. We searched PubMed/Medline and Google Scholar up to December 2023. Search terms included "urologic surgery", "artificial intelligence", "machine learning", "neural network", "automation", and "robotic surgery"...

Advancements in reliable information transfer across biotic-abiotic interfaces have enabled the restoration of lost human function. For example, communication between neuronal cells and electrical devices restores the ability to walk to a tetraplegic patient and vision to patients blinded by retinal disease. These impactful medical achievements are aided by tailored biotic-abiotic interfaces that maximize information transfer fidelity by considering the physical properties of the underlying biological and synthetic components...

BACKGROUND: Structured reporting (SR) replaced narrative (free text) reporting and utilizes templated headings and subheadings with findings typically based on the anatomy included in the examination. Its use has been widely advocated by radiology and non-radiology organizations as the new reporting standard. There are, however, shortcomings to SR, such as templated text not addressing a specific clinical indication. Contextual reporting (CR) fills this gap. CR is a type of SR which is tailored to a narrow clinical indication by including pertinent positive and negative findings for that specific clinical entity...

Fuzhuan brick tea (FBT) fungal fermentation is a key factor in achieving its unique dark color, aroma, and taste. Therefore, it is essential to develop a rapid and reliable method that could assess its quality during FBT fermentation process. This study focused on using electronic nose (e-nose) and spectroscopy combination with sensory evaluations and physicochemical measurements for building machine learning (ML) models of FBT. The results showed that the fused data achieved 100 % accuracy in classifying the FBT fermentation process...

The diversity of vertebrate body plans is dizzying, yet stunning for the many things they have in common. Vertebrates have inhabited virtually every part of the earth from its coldest to warmest climates. They locomote by swimming, flying, walking, slithering, or climbing, or combinations of these behaviors. And they exist in many different sizes, from the smallest of frogs, fish and lizards to giraffes, elephants, and blue whales. Despite these differences, vertebrates follow a remarkably similar blueprint for the establishment of their body plan...

OBJECTIVE: To define competency-based education (CBE) for pharmacy education and describe how strengths and barriers of CBE can support or hinder implementation. METHODS: A narrative synthesis was performed via search of English-language articles related to CBE within health professions education from 2015-2021. Articles were included if they described CBE or the strengths or barriers of its use. Articles could be of any type. Full text review and data extraction occurred independently by each author for a subset of included articles...

OBJECTIVE: Variability in prostate MRI quality is an increasingly recognized problem that negatively affects patient care. This report aims to describe the results and key learnings of the first cohort of the ACR Learning Network Prostate MR Image Quality Improvement Collaborative. METHODS: Teams from five organizations in the U.S. were trained on a structured improvement method. After reaching a consensus on image quality and auditing their images using the Prostate Imaging Quality (PI-QUAL) system, teams conducted a current state analysis to identify barriers to obtaining high-quality images...

Self-supervised pre-training and fully supervised fine-tuning paradigms have received much attention to solve the data annotation problem in deep learning fields. Compared with traditional pre-training on large natural image datasets, medical self-supervised learning methods learn rich representations derived from unlabeled data itself thus avoiding the distribution shift between different image domains. However, nowadays state-of-the-art medical pre-training methods were specifically designed for downstream tasks making them less flexible and difficult to apply to new tasks...

Anaerobic digestion (AD) has become a popular technique for organic waste management while offering economic and environmental advantages. As AD becomes increasingly prevalent worldwide, research efforts are primarily focused on optimizing its processes. During the operation of AD systems, the occurrence of unstable events is inevitable. So far, numerous conclusions have been drawn from full and lab-scale studies regarding the driving factors of start-up perturbations. However, the lack of standardized practices reported in start-up studies raises concerns about the comparability and reliability of obtained data...

PROBLEM: There is a need to increase the number of physician-scientists from underrepresented in medicine (URiM) groups. To engage URiM medical students, a committee of pediatric departmental leaders at the Children's Hospital of Philadelphia created the Summer Underrepresented in Medicine Medical Student Research program. This 8-week, onsite research and clinical experience takes place during the summer between students' first and second years of medical school. APPROACH: Applications were solicited between 2019-2023 through nationwide outreach to medical school deans and members of URiM student organizations...