Erratum for "Tropical superelliptic curves"

We correct two errors in our paper Tropical superelliptic curves published in Advances in Geometry 20 (2020), 527–551. These corrections do not change the main results of the paper

Spatiotemporal modeling of schistosomiasis in Ghana: linking remote sensing data to infectious disease

More than 90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. The use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. The transmission of schistosomiasis, a disease acquired from contact with contaminated surface water, requires specific environmental conditions to sustain freshwater snails. If a connection between schistosomiasis and remotely sensed environmental variables can be established, then cost effective and current disease risk predictions can be made available. Schistosomiasis transmission has unknown seasonality, and the disease is difficult to study due to a long lag between infection and clinical symptoms. To overcome these challenges, we employed a comprehensive 15-year time-series built from remote sensing feeds, which is the longest environmental dataset to be used in the application of remote sensing to schistosomiasis. The following environmental variables will be used in the model: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique. This technique, improves upon the conventional Köppen-Geiger method, which has been the primary climate classification system in use the past 100 years. These predictor variables will be regressed against 8 years of national health data in Ghana, the largest health dataset of its kind to be used in this context, and acquired from freely available satellite imagery data. A benefit of remote sensing processing is that it only requires training and time in terms of resources. The results of a fixed effects model can be used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.Published versio

Rapid Systematic Review of Occupational Therapy-Adaptable Interventions to Improve Social Engagement in Children and Adolescents with Autism Spectrum Disorder

Indiana University Purdue University IndianapolisIn this rapid systematic review, we describe how evidence-based interventions aiming to improve social engagement in children and adolescents with Autism Spectrum Disorder (ASD) can be potentially adapted to be included within the scope of occupational therapy. Children and adolescents with ASD often experience difficulty with social engagement, impacting overall social participation and other aspects of daily life. It is important to address this issue within this population to ensure engagement in the occupation of social participation, which is vital to optimal health and well-being. We discovered several themes including communication, joint attention, peer engagement, social skills, and play as outcomes addressed within the interventions included in this review. There is limited research available regarding social engagement interventions for children and adolescents with ASD directly including an occupational therapist within the intervention. This review demonstrates that there is a large variety of social engagement interventions that could be implemented by occupational therapists; however, therapists must be mindful of choosing an intervention that is specific to the client's condition. There is strong evidence to suggest that interventions targeting social engagement in children and adolescents with ASD result in increased social abilities. Further research should be conducted assessing the implementation of these interventions by occupational therapists to ensure generalizability.Occupational Therap

The use of remotely sensed environmental parameters for spatial and temporal schistosomiasis prediction across climate zones in Ghana

Schistosomiasis control in sub-Saharan Africa is enacted primarily through preventive chemotherapy. Predictive models can play an important role in filling knowledge gaps in the distribution of the disease and help guide the allocation of limited resources. Previous modeling approaches have used localized cross-sectional survey data and environmental data typically collected at a discrete point in time. In this analysis, 8 years (2008-2015) of monthly schistosomiasis cases reported into Ghana's national surveillance system were used to assess temporal and spatial relationships between disease rates and three remotely sensed environmental variables: land surface temperature (LST), normalized difference vegetation index (NDVI), and accumulated precipitation (AP). Furthermore, the analysis was stratified by three major and nine minor climate zones, defined using a new climate classification method. Results showed a downward trend in reported disease rates (~ 1% per month) for all climate zones. Seasonality was present in the north with two peaks (March and September), and in the middle of the country with a single peak (July). Lowest disease rates were observed in December/January across climate zones. Seasonal patterns in the environmental variables and their associations with reported schistosomiasis infection rates varied across climate zones. Precipitation consistently demonstrated a positive association with disease outcome, with a 1-cm increase in rainfall contributing a 0.3-1.6% increase in monthly reported schistosomiasis infection rates. Generally, surveillance of neglected tropical diseases (NTDs) in low-income countries continues to suffer from data quality issues. However, with systematic improvements, our approach demonstrates a way for health departments to use routine surveillance data in combination with publicly available remote sensing data to analyze disease patterns with wide geographic coverage and varying levels of spatial and temporal aggregation.Accepted manuscrip

Discovery of seven volcanic outbursts on Io from an IRTF observation campaign 2016 to 2022

This study analyzes near-infrared measurements of Io, Jupiter's moon, observed over 170 nights from 2016 to early 2022 using the NASA Infrared Telescope Facility (IRTF). During this period, seven new volcanic outbursts, the most energetic volcanic events on Io, were discovered and characterized, increasing the total number of observed outburst events from 18 to 25. We also present simplified criteria for the thermal detection of an outburst, requiring it to be both confined to a specific location of Io and above a threshold intensity in the Lp-band (3.8 micron). Our measurements use 2 to 5 micron photometry in eclipse, Jupiter occultation, and reflected sunlight. In addition to extending the observational dataset of Io's dynamic activity, these data provide insights into the temporal and spatial distribution of outbursts on Io. Notably, all seven outbursts were detected in Io's trailing hemisphere. These include Pillan Patera and a newly discovered repeating outburst location at Acala Fluctus. We add these events to the rare category of recurring outbursts, before which Tvashtar was the only known example. We observed that another outburst at UP 254W decreased in Lp-band intensity by a factor of two in 4.5 hours. In August 2021, Io exhibited high volcanic activity when two powerful outbursts rapidly appeared, propagating East. Our findings underscore IRTF's ongoing contributions to the study of Io

Continual trials spontaneous recognition tasks in mice: reducing animal numbers and improving our understanding of the mechanisms underlying memory

Spontaneous recognition tasks are widely used as a laboratory measure of memory in animals but give rise to high levels of behavioural noise leading to a lack of reliability. Previous work has shown that a modification of the procedure to allow continual trials testing (in which many trials are run concurrently in a single session) decreases behavioural noise and thus significantly reduces the numbers of rats required to retain statistical power. Here we demonstrate for the first time that this improved method of testing extends to mice, increasing the overall power of the approach. Moreover, our results show that the new continual trials approach provides the additional benefits of heightened sensitivity and thus provides greater insight into the mechanisms at play. Standard (c57) and transgenic Alzheimer model (TASTPM) mice were tested both at 7 and 10 months of age in both object recognition (OR) and object location (OL) spontaneous recognition tasks using the continual trials methodology. Both c57 and TASTPM mice showed age-dependent changes in performance in OR. While c57 mice also showed age-related changes in performance of OL, TASTPM mice were unable to perform OL at either age. Significantly, we demonstrate that differences in OL performance in c57s and TASTPM animals is a result of proactive interference rather than an absolute inability to recognise object-location combinations. We argue that these continual trials approaches provide overall improved reliability and better interpretation of the memory ability of mice, as well as providing a significant reduction in overall animal use