An Eye for AI: A Multimodal Bottleneck Transformer Approach for Predicting Individual Eye Movements : Towards Foundation Models for Human Factors & Neuroscience

Human perception has been a subject of study for centuries. Various eye tracking methods in many study designs have shed light on individual differences in perception and visual navigation. However, accurately identifying individuals based on gaze behaviour remains a challenge. Artificial intelligence (AI) based methods have led to large successes in domains such as vision and language; they are also making their introduction in human factors & neuroscience (HFN). Leveraging AI for HFN requires quantities of data several orders of magnitude larger than the field is used to organising; there exists a clear discrepancy in the standardisation of data publication. In this work, we work towards foundation models (FM) for HFN by highlighting important data insights from AI. A multimodal bottleneck transformer is proposed, a model architecture that can effectively and efficiently represent and work with the varying modalities encountered in HFN. Results indicate that classification of individuals and prediction of gaze is possible, given more training data

Does the geographical footprint of Ethiopia’s flagship social protection programme align with climatic and conflict risks?

Ethiopia’s flagship ‘Productive Safety Net Programme’ (PSNP) entered its fifth phase of implementation in 2021. After more than fifteen years, the Government reoriented the programme’s targeting of woredas (districts) with a history of food insecurity, to prioritising those experiencing ‘extreme poverty through shocks’ – particularly drought. In doing so, it has rebranded the PSNP as an ‘adaptive’ safety net. The focus of the ‘adaptive social protection’ policy agenda, however, extends beyond responding to biophysical risks associated with climate variability and change; it also seeks to address non-climatic, contextual factors underpinning relational vulnerability to climate change. This study asks whether the PSNP’s system of geographic targeting at the start of its fifth phase aligns with this more comprehensive framing of ‘adaptive social protection’. Using binary logit regression analysis, it assesses whether the PSNP-covered woredas are those most exposed to three major risks in the country: drought, flooding, and political conflict. We find that, controlling for poverty headcount rate and population density, PSNP coverage is positively associated with districts experiencing higher year-to-year drought conditions, yet woredas with higher multi-year drought variability are less likely to be covered. We find no relationship between PSNP coverage and exposure to flood risk, which is unevenly distributed across the country. Whilst the programme is currently well-targeted toward districts facing disproportionately high levels of political insecurity, this association disappears if the recent escalation of conflict beginning in 2020 is disregarded. As such, this study points to risks that PSNP administrators need to be more attentive to as they consider expanding the programme’s geographical footprint to become more ‘adaptive’. Doing so could better support the strengthening of PSNP participants’ long-term resilience to climate change

Benchmarking Nursing Practice for Clients with Extended Spectrum Beta-Lactamases Bacteria

The prevalence of multi-resistant ESBL-producing bacteria in nursing homes is a problem not only in Finland but worldwide. It presents a major challenge for nurses and healthcare workers in providing quality care to residents. The ESBL-producing bacteria might reside in a carrier without any infection but it severely limits the treatment choices if the carrier becomes ill. In a nursing home, where most residents stay for long periods, nurses have an important role in preventing the spread of ESBL from carriers to other residents and staff. The aim of this study is to provide nurses with evidence-based guidelines to care for ESBL carriers residing in nursing homes. Furthermore, the current situation of evidence-based practices regarding care of ESBL carriers in nursing homes and the situation of ESBL in Finland is investigated. The study is conducted through a review of literature. Nineteen topic-relevant articles have been selected using different academic search databases. The Health Promotion Model by Nola Pender provides the theoretical frame-work. This study found that the lack of implementation of infection prevention measures was associated with the spread of ESBL in nursing homes. Despite having knowledge, nurses did not implement the proper procedures in practice due to lack of time, resources and proper guidelines. Additionally, inappropriate use of antibiotics was one of the main risk factor in ESBL carriers. In conclusion, healthcare workers must have proper knowledge and implement proper infection control practices in order to restrict the spread of ESBL. Continued education for nurses in the form of training and educational programs could affect the spread of this disease along with proper use of antibiotics. Further study about isolation precaution in nursing homes could shed light on the sources of cross-transmission so that good nursing practice could be developed, impacting the safety of clients and staff

Study of Various Waste to Energy Production Techniques and its Potential in India

With the ever-rapid pace of urbanization comes the problem of waste. As we tend be more materialistic, we tend to generate more garbage. The western world has already adopted this technique successfully and we in India have with our population the potential of being one of the largest producers of Energy from Waste. This paper tends to highlight the various Waste to Energy (WTE) techniques prevalent in the world at presen