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Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, machine learning can be used to find improved relationships between nonlinear variables in complex systems. Initially, the standardized precipitation

The escalating levels of heavy metals in soil, attributed to diverse sources, pose a pressing concern for human and animal health through their entry into the food chain. This study aimed to evaluate the uptake behavior of Cu, Zn, and Pb in carrots grown in different levels of contaminated soil (control, 30, 60, 90, 120 ppm) and to assess the associated health risks to mitigate the enrichment of h

(1) Background: Water scarcity is a pressing global issue, impacting food security, health, and economic stability in many regions. In Yemen, the challenges related to water resources are particularly acute, exacerbated by climate change, overuse, and a lack of sustainable management strategies. (2) Objective: this paper assesses water resources and demands under two shared socioeconomic pathways,

The Sustainable Development Goals (SDGs) build on the Millennium Development Goals (MDGs) and aim to promote sustainable global development by addressing poverty, inequality, and environmental sustainability. Among the key objectives of the SDGs, Goal 6 targets universal access to safely managed drinking water and sanitation by 2030, recognizing the critical link between water, sanitation, hygiene

Experimental results from student and other non-representative convenience samples often suggest that men, on average, are more risk taking and competitive than women. We explore whether these gender preference gaps also exist in incentivized tasks in a simple random sample of the Swedish adult population. Our design comprises four different conditions to systematically explore how the experimenta

Semiconductor double quantum dots (DQD) coupled to superconducting microwave resonators offer a promising platform for the detection of single microwave photons. In previous works, the photodetection was studied for a monochromatic source of microwave photons. Here, we theoretically analyze the photodetection of single microwave pulses. The photodetection in this case can be seen as a nonlinear fi

The emergency department is a stressful environment, in which physicians are required to make fast and accurate diagnostic assessments amidst an ever increasing flood of clinical information, including a growing body of medical knowledge. Meanwhile, the digitization of medical health records in combination with recent breakthroughs in Artificial Intelligence is ushering in a new era of precision m

Random indexing (RI) is a lightweight dimension reduction method, which is used, for example, to approximate vector semantic relationships in online natural language processing systems. Here we generalise RI to multidimensional arrays and therefore enable approximation of higher-order statistical relationships in data. The generalised method is a sparse implementation of random projections, which

The rapid integration of physical systems with cyberspace infrastructure, the so-called Internet of Things, is likely to have a significant effect on how people interact with the physical environment and design information and communication systems. Internet-connected systems are expected to vastly outnumber people on the planet in the near future, leading to grand challenges in software engineeri

The traditional way of teaching may no longer be sufficient to cope with current requirements specifically in the Internet of Things (IoT) domain. The case for this paper is related to an introductory programming course on JavaScript for the period of 2016-2018. In this study a multi-method approach for data collection is utilized. Project-Based Learning (PBL), Scrum and rapid prototyping are util

The pyISC is a Python API and extension to the C++ based Incremental Stream Clustering (ISC) anomaly detection and classification framework. The framework is based on parametric Bayesian statistical inference using the Bayesian Principal Anomaly (BPA), which enables to combine the output from several probability distributions. pyISC is designed to be easy to use and integrated with other Python li

IntroductionImmigrant children are often challenged at school. School performance is an important predictor of future socioeconomic position and mental and physical health. While studies have investigated parental mental disorders as a potential factor for poor school performance, no studies have investigated this among children with foreign-born parents, i.e., second-generation immigrant children