DECORAS: detection and characterization of radio-astronomical sources using deep learning

We present DECORAS, a deep learning based approach to detect both point and extended sources from Very Long Baseline Interferometry (VLBI) observations. Our approach is based on an encoder-decoder neural network architecture that uses a low number of convolutional layers to provide a scalable solution for source detection. In addition, DECORAS performs source characterization in terms of the position, effective radius and peak brightness of the detected sources. We have trained and tested the network with images that are based on realistic Very Long Baseline Array (VLBA) observations at 20 cm. Also, these images have not gone through any prior de-convolution step and are directly related to the visibility data via a Fourier transform. We find that the source catalog generated by DECORAS has a better overall completeness and purity, when compared to a traditional source detection algorithm. DECORAS is complete at the 7.5$\sigma$ level, and has an almost factor of two improvement in reliability at 5.5$\sigma$. We find that DECORAS can recover the position of the detected sources to within 0.61 $\pm$ 0.69 mas, and the effective radius and peak surface brightness are recovered to within 20 per cent for 98 and 94 per cent of the sources, respectively. Overall, we find that DECORAS provides a reliable source detection and characterization solution for future wide-field VLBI surveys.Comment: submitted to MNRA

Optimizing the best play in basketball using deep learning

In a close game of basketball, victory or defeat can depend on a single shot. Being able to identify the best player and play scenario for a given opponent’s defense can increase the likelihood of victory. Progress in technology has resulted in an increase in the popularity of sports analytics over the last two decades, where data can be used by teams and individuals to their advantage. A popular data analytic technique in sports is deep learning. Deep learning is a branch of machine learning that finds patterns within big data and can predict future decisions. The process relies on a raw dataset for training purposes. It can be utilized in sports by using deep learning to read the data and provide a better understanding of where players can be the most successful. In this study the data used were on division I women’s basketball games of a private university in a conference featuring top 25 teams. Deep learning was applied to optimize the best offensive play in a game scenario for a given set of features. The system is used to predict the play that would lead to the highest probability of a made shot

Cerebral activations during viewing of food stimuli in adult patients with acquired structural hypothalamic damage: A functional neuroimaging study

BACKGROUND/OBJECTIVES: Obesity is common following hypothalamic damage due to tumours. Homeostatic and non-homeostatic brain centres control appetite and energy balance but their interaction in the presence of hypothalamic damage remains unknown. We hypothesized that abnormal appetite in obese patients with hypothalamic damage results from aberrant brain processing of food stimuli. We sought to establish differences in activation of brain food motivation and reward neurocircuitry in patients with hypothalamic obesity (HO) compared with patients with hypothalamic damage whose weight had remained stable. SUBJECTS/METHODS: In a cross-sectional study at a University Clinical Research Centre, we studied 9 patients with HO, 10 age-matched obese controls, 7 patients who remained weight-stable following hypothalamic insult (HWS) and 10 non-obese controls. Functional magnetic resonance imaging was performed in the fasted state, 1 h and 3 h after a test meal, while subjects were presented with images of high-calorie foods, low-calorie foods and non-food objects. Insulin, glucagon-like peptide-1, Peptide YY and ghrelin were measured throughout the experiment, and appetite ratings were recorded. RESULTS: Mean neural activation in the posterior insula and lingual gyrus (brain areas linked to food motivation and reward value of food) in HWS were significantly lower than in the other three groups (P=0.001). A significant negative correlation was found between insulin levels and posterior insula activation (P=0.002). CONCLUSIONS: Neural pathways associated with food motivation and reward-related behaviour, and the influence of insulin on their activation may be involved in the pathophysiology of HO.International Journal of Obesity advance online publicatio

Template-Based Synthesis of Nanoporous Hydroxyapatite

Hydroxyapatite (HAp) particles, a potential starting material for bone substitutes, with nanopores were synthesized in the presence of cetyltrimethylammonium bromide (CTAB) and P123 as cationic and nonionic surfactants as the structuring units. Effect of nonionic surfactant concentration on surface areas is also investigated. Based on N2 adsorption-desorption isotherms investigation, surface area increased up to 50 m2/g by using P123 and 147 m2/g by using CTAB as porosity agent. Pore structure remained even after the removal of surfactant and calcinations at 400°C.</jats:p

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Myocardial energy depletion and dynamic systolic dysfunction in hypertrophic cardiomyopathy

Evidence indicates that anatomical and physiological phenotypes of hypertrophic cardiomyopathy (HCM) stem from genetically mediated, inefficient cardiomyocyte energy utilization, and subsequent cellular energy depletion. However, HCM often presents clinically with normal left ventricular (LV) systolic function or hyperkinesia. If energy inefficiency is a feature of HCM, why is it not manifest as resting LV systolic dysfunction? In this Perspectives article, we focus on an idiosyncratic form of reversible systolic dysfunction provoked by LV obstruction that we have previously termed the 'lobster claw abnormality' — a mid-systolic drop in LV Doppler ejection velocities. In obstructive HCM, this drop explains the mid-systolic closure of the aortic valve, the bifid aortic pressure trace, and why patients cannot increase stroke volume with exercise. This phenomenon is characteristic of a broader phenomenon in HCM that we have termed dynamic systolic dysfunction. It underlies the development of apical aneurysms, and rare occurrence of cardiogenic shock after obstruction. We posit that dynamic systolic dysfunction is a manifestation of inefficient cardiomyocyte energy utilization. Systolic dysfunction is clinically inapparent at rest; however, it becomes overt through the mechanism of afterload mismatch when LV outflow obstruction is imposed. Energetic insufficiency is also present in nonobstructive HCM. This paradigm might suggest novel therapies. Other pathways that might be central to HCM, such as myofilament Ca2+ hypersensitivity, and enhanced late Na+ current, are discussed

The ROAM/EORTC-1308 trial: Radiation versus Observation following surgical resection of Atypical Meningioma: study protocol for a randomised controlled trial

BACKGROUND Atypical meningiomas are an intermediate grade brain tumour with a recurrence rate of 39-58 %. It is not known whether early adjuvant radiotherapy reduces the risk of tumour recurrence and whether the potential side-effects are justified. An alternative management strategy is to perform active monitoring with magnetic resonance imaging (MRI) and to treat at recurrence. There are no randomised controlled trials comparing these two approaches. METHODS/DESIGN A total of 190 patients will be recruited from neurosurgical/neuro-oncology centres across the United Kingdom, Ireland and mainland Europe. Adult patients undergoing gross total resection of intracranial atypical meningioma are eligible. Patients with multiple meningioma, optic nerve sheath meningioma, previous intracranial tumour, previous cranial radiotherapy and neurofibromatosis will be excluded. Informed consent will be obtained from patients. This is a two-stage trial (both stages will run in parallel): Stage 1 (qualitative study) is designed to maximise patient and clinician acceptability, thereby optimising recruitment and retention. Patients wishing to continue will proceed to randomisation. Stage 2 (randomisation) patients will be randomised to receive either early adjuvant radiotherapy for 6 weeks (60 Gy in 30 fractions) or active monitoring. The primary outcome measure is time to MRI evidence of tumour recurrence (progression-free survival (PFS)). Secondary outcome measures include assessing the toxicity of the radiotherapy, the quality of life, neurocognitive function, time to second line treatment, time to death (overall survival (OS)) and incremental cost per quality-adjusted life year (QALY) gained. DISCUSSION ROAM/EORTC-1308 is the first multi-centre randomised controlled trial designed to determine whether early adjuvant radiotherapy reduces the risk of tumour recurrence following complete surgical resection of atypical meningioma. The results of this study will be used to inform current neurosurgery and neuro-oncology practice worldwide. TRIAL REGISTRATION ISRCTN71502099 on 19 May 2014

Apple's Knowledge Navigator: Why Doesn't that Conversational Agent Exist Yet?

Apple's 1987 Knowledge Navigator video contains a vision of a sophisticated digital personal assistant, but the natural human-agent conversational dialog shown does not currently exist. To investigate why, the authors analyzed the video using three theoretical frameworks: the DiCoT framework, the HAT Game Analysis framework, and the Flows of Power framework. These were used to codify the human-agent interactions and classify the agent's capabilities. While some barriers to creating such agents are technological, other barriers arise from privacy, social and situational factors, trust, and the financial business case. The social roles and asymmetric interactions of the human and agent are discussed in the broader context of HAT research, along with the need for a new term for these agents that does not rely on a human social relationship metaphor. This research offers designers of conversational agents a research roadmap to build more highly capable and trusted non-human teammates.This proceeding is published as Newendorp, Amanda K., Mohammadamin Sanaei, Arthur J. Perron, Hila Sabouni, Nikoo Javadpour, Maddie Sells, Katherine Nelson, Michael Dorneich, and Stephen B. Gilbert. "Apple's Knowledge Navigator: Why Doesn't that Conversational Agent Exist Yet?." In Proceedings of the CHI Conference on Human Factors in Computing Systems, pp. 1-14. 2024. doi: https://doi.org/10.1145/3613904.3642739. Copyright 2024, The Authors. This work is licensed under a Creative Commons Attribution-Share Alike International 4.0 License

Pituitary society expert Delphi consensus: operative workflow in endoscopic transsphenoidal pituitary adenoma resection.

Funder: Wellcome TrustPurposeSurgical workflow analysis seeks to systematically break down operations into hierarchal components. It facilitates education, training, and understanding of surgical variations. There are known educational demands and variations in surgical practice in endoscopic transsphenoidal approaches to pituitary adenomas. Through an iterative consensus process, we generated a surgical workflow reflective of contemporary surgical practice.MethodsA mixed-methods consensus process composed of a literature review and iterative Delphi surveys was carried out within the Pituitary Society. Each round of the survey was repeated until data saturation and > 90% consensus was reached.ResultsThere was a 100% response rate and no attrition across both Delphi rounds. Eighteen international expert panel members participated. An extensive workflow of 4 phases (nasal, sphenoid, sellar and closure) and 40 steps, with associated technical errors and adverse events, were agreed upon by 100% of panel members across rounds. Both core and case-specific or surgeon-specific variations in operative steps were captured.ConclusionsThrough an international expert panel consensus, a workflow for the performance of endoscopic transsphenoidal pituitary adenoma resection has been generated. This workflow captures a wide range of contemporary operative practice. The agreed "core" steps will serve as a foundation for education, training, assessment and technological development (e.g. models and simulators). The "optional" steps highlight areas of heterogeneity of practice that will benefit from further research (e.g. methods of skull base repair). Further adjustments could be made to increase applicability around the world