The tabular and visual dataset focuses on South African basic education and provides insights into the distribution of schools and basic population statistics across the country. This tabular and visual data are stratified across different quintiles for each provincial and district boundary. The quintile system is used by the South African government to classify schools based on their level of socio-economic disadvantage, with quintile 1 being the most disadvantaged and quintile 5 being the least disadvantaged. The data was joined by extracting information from the debarment of basic education with StatsSA population census data. Thereafter, all tabular data and geo located data were transformed to maps using GIS software and the Python integrated development environment. The dataset includes information on the number of schools and students in each quintile, as well as the population density in each area. The data is displayed through a combination of charts, maps and tables, allowing for easy analysis and interpretation of the information.
<p> </p> <p>The tabular and visual dataset focuses on South African basic education and provides insights into the distribution of schools and basic population statistics across the country. This tabular and visual data are stratified across different quintiles for each provincial and district boundary. The quintile system is used by the South African government to classify schools based on their level of socio-economic disadvantage, with quintile 1 being the most disadvantaged and quintile 5 being the least disadvantaged. The data was joined by extracting information from the debarment of basic education with StatsSA population census data. Thereafter, all tabular data and geo located data were transformed to maps using GIS software and the Python integrated development environment. The dataset includes information on the number of schools and students in each quintile, as well as the population density in each area. The data is displayed through a combination of charts, maps and tables, allowing for easy analysis and interpretation of the information.</p>
A 3-day-old alpaca cria presented for progressive weakness and dyspnea since birth. Complete bloodwork, thoracic radiographs, and endoscopic examination of the nasal passages and distal trachea revealed no significant findings. Echocardiogram and contrast study revealed a single artery overriding a large ventricular septal defect (VSD). A small atrial septal defect or patent foramen ovale was also noted. Color flow Doppler and an agitated saline contrast study revealed bidirectional but primarily right to left flow through the VSD and bidirectional shunting through the atrial defect. Differential diagnosis based on echocardiographic findings included common arterial trunk, Tetralogy of Fallot, and pulmonary atresia with a VSD. Postmortem examination revealed a large common arterial trunk with a quadricuspid valve overriding a VSD. Additionally, defect in the atrial septum was determined to be a patent foramen ovale. A single pulmonary trunk arose from the common arterial trunk and bifurcated to the left and right pulmonary artery, consistent with a Collet and Edwards' type I common arterial trunk with aortic predominance. Although uncommon, congenital cardiac defects should be considered in animals presenting with clinical signs of hypoxemia, dyspnea, or failure to thrive.
Recognizing that psychoanalysis needs to change to meet the challenges described by the Holmes Report on American Psychoanalysis, the authors describe their journey to include socio-cultural perspectives in their teaching activities. To widen the lens of course content, they include topics of race, racial trauma, and inequality by bringing additional voices into their Self Psychology course materials including Beverly Stoute and Franz Fanon. Further, they discuss these authors' contributions in relation to Heinz Kohut's foundational ideas about development and clinical practice. They describe the features of an anti-racist pedagogical approach to teaching which supports encouraging and appreciating the contributions of all participants in the learning process. They provide several vignettes from their teaching experiences and argue that self psychologically-informed clinicians are particularly well-suited to meet the challenge of expanding psychoanalytic thinking to incorporate socio-cultural perspectives.
Anthropogenic Litter (AL) is ubiquitous in distribution and diverse in type and impact. Citizen science AL clean-ups engage citizens with the environment and have the potential to generate data that can inform policy. Here we present a detailed citizen science survey of AL across freshwater, terrestrial, and coastal environments of the United Kingdom (UK), coordinated by the not-for-profit Planet Patrol throughout 2020. Key materials, industries, brands, and parent companies associated with AL are identified. Plastic dominated AL (63%), followed by metal (14%), and composite materials (12%). The majority of AL (56%) had been used as beverage containers and non-beverage packaging, and 38.8% of AL was branded. Of the branded AL, 26% was associated with The Coca-Cola Company, Anheuser-Busch InBev, and PepsiCo. These three companies were associated with significantly more branded litter than any other. We place these data in the context of upcoming UK legislation and the Environmental Social Governance (ESG) statements of the companies associated with the majority of the recorded litter. Knowledge gaps and recommendations for AL surveying are made, and the focus of corporate and government actions are discussed.
<p> </p> <p>The tabular and visual dataset focuses on South African basic education and provides insights into the distribution of schools and basic population statistics across the country. This tabular and visual data are stratified across different quintiles for each provincial and district boundary. The quintile system is used by the South African government to classify schools based on their level of socio-economic disadvantage, with quintile 1 being the most disadvantaged and quintile 5 being the least disadvantaged. The data was joined by extracting information from the debarment of basic education with StatsSA population census data. Thereafter, all tabular data and geo located data were transformed to maps using GIS software and the Python integrated development environment. The dataset includes information on the number of schools and students in each quintile, as well as the population density in each area. The data is displayed through a combination of charts, maps and tables, allowing for easy analysis and interpretation of the information.</p>
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