Solitary Dust--Acoustic Waves in a Plasma with Two-Temperature Ions and Distributed Grain Size

The propagation of weakly nonlinear dust--acoustic waves in a dusty plasma containing two ion species with different temperatures is explored. The nonlinear equations describing both the quadratic and cubic plasma nonlinearities are derived. It is shown that the properties of dust--acoustic waves depend substantially on the grain size distribution. In particular, for solitary dust--acoustic waves with a positive potential to exist in a plasma with distributed grain size, it is necessary that the difference between the temperatures of two ion species be large that that in the case of unusized grains.Comment: 16 pages, 6 figure

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

In Xenopus ependymal cilia drive embryonic CSF circulation and brain development independently of cardiac pulsatile forces.

BACKGROUND: Hydrocephalus, the pathological expansion of the cerebrospinal fluid (CSF)-filled cerebral ventricles, is a common, deadly disease. In the adult, cardiac and respiratory forces are the main drivers of CSF flow within the brain ventricular system to remove waste and deliver nutrients. In contrast, the mechanics and functions of CSF circulation in the embryonic brain are poorly understood. This is primarily due to the lack of model systems and imaging technology to study these early time points. Here, we studied embryos of the vertebrate Xenopus with optical coherence tomography (OCT) imaging to investigate in vivo ventricular and neural development during the onset of CSF circulation. METHODS: Optical coherence tomography (OCT), a cross-sectional imaging modality, was used to study developing Xenopus tadpole brains and to dynamically detect in vivo ventricular morphology and CSF circulation in real-time, at micrometer resolution. The effects of immobilizing cilia and cardiac ablation were investigated. RESULTS: In Xenopus, using OCT imaging, we demonstrated that ventriculogenesis can be tracked throughout development until the beginning of metamorphosis. We found that during Xenopus embryogenesis, initially, CSF fills the primitive ventricular space and remains static, followed by the initiation of the cilia driven CSF circulation where ependymal cilia create a polarized CSF flow. No pulsatile flow was detected throughout these tailbud and early tadpole stages. As development progressed, despite the emergence of the choroid plexus in Xenopus, cardiac forces did not contribute to the CSF circulation, and ciliary flow remained the driver of the intercompartmental bidirectional flow as well as the near-wall flow. We finally showed that cilia driven flow is crucial for proper rostral development and regulated the spatial neural cell organization. CONCLUSIONS: Our data support a paradigm in which Xenopus embryonic ventriculogenesis and rostral brain development are critically dependent on ependymal cilia-driven CSF flow currents that are generated independently of cardiac pulsatile forces. Our work suggests that the Xenopus ventricular system forms a complex cilia-driven CSF flow network which regulates neural cell organization. This work will redirect efforts to understand the molecular regulators of embryonic CSF flow by focusing attention on motile cilia rather than other forces relevant only to the adult

Suggestions for a better tertiary physical education experience: insights from students at a rural state university

This study explored the concerns and suggestions of generation Z students in rural communities to improve the newly implemented tertiary physical education (PE) program in the Philippines - physical activity towards health and fitness (PATHFit). Employing a qualitative-ethnographic approach, data were gathered from 20 generation Z students who were selected and participated in purposive interviews using open-ended questions validated by experts. The findings highlighted several themes following the data analysis using the Colaizzi method: PE should be engaging and fun, moving beyond traditional books and materials; a more flexible curriculum is needed, one that does not feel like a rigid prescription; student-centered activities should be prioritized to promote active involvement; lectures should be limited, with a greater focus on interactive, hands-on experiences; access to sports equipment through a borrowing system is crucial for student participation; and high-quality teaching, characterized by clear communication and practical demonstrations, is essential for a more meaningful learning experience. The study concludes and implies that generation Z students in rural communities desire a more engaging, flexible, and interactive PATHFit program that aligns with their interests and needs. Their insights provide valuable direction for enhancing the curriculum, promoting active student involvement, and ensuring that teaching is clear, practical, and engaging

In the zone or out of bounds? How sports and physical activity anxiety affects life satisfaction among students

This study aims to explore the relationship between sports and physical anxiety and life satisfaction among college students in a leading Philippine state university. Employing a quantitative research design, specifically descriptive correlation, data were collected from 2,043 respondents using simple random sampling. The research utilized the physical activity and sport anxiety scale and the life satisfaction index to measure the respective constructs, with analyses conducted using Spearman’s rho correlation coefficient to assess relationships between variables. Results indicated a significant relationship between sports and physical anxiety and life satisfaction, revealing that higher levels of anxiety corresponded to lower life satisfaction. These findings highlight the importance of addressing sports and physical anxiety to improve overall well-being. Implications suggest that institutions should implement mental health and wellness initiatives aimed at reducing anxiety and promoting supportive environments in physical education settings. By fostering a culture that prioritizes psychological well-being alongside physical engagement, institutions can enhance students’ life satisfaction and overall quality of life

Prototypes for Content-Based Image Retrieval in Clinical Practice

Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice