The Abdus Salam International Centre for Theoretical Physics (ICTP)

This data article presents an image dataset compiled for the purpose of machine learning-based identification and prediction of adulteration levels in Teff (Eragrostis tef (Zucc.) Trotter) flour. The dataset includes images of pure white, mixed, and red Teff flour varieties, as well as these flours adulterated with wood flour (sawdust) and gypsum (calcium sulfate) powder. Adulteration levels range from 10% to 40% in 5% increments. The data collection process involved preparing Teff flour from naturally dried and milled Teff grains. Samples of 100 grams of each Teff flour variety were then mixed with the adulterants at the specified concentrations. A total of 5,000 raw images were captured using an 18-megapixel Canon EOS 7D camera under controlled studio lighting (300 W incandescent lamps), with the samples placed 30 cm from the camera lens in a 10 cm x 10 cm plastic box. To enhance the dataset's diversity and quantity, 25,000 augmented images were generated by shuffling image pixels' locations with various block sizes (1 × 1, 2 × 2, 4 × 4, 8 × 8, and 16 × 16). This dataset is a valuable resource for researchers and students in Teff adulteration using image processing and feature extraction. It also holds potential for use by Food and Drug Administration Authorities and law enforcement to develop automated methods for detecting Teff flour adulteration, offering an alternative to time-consuming physio-chemical laboratory tests. The dataset's structure and augmentation methods are detailed to ensure reproducibility and encourage further research into robust machine learning models for food quality control.

Within the payloads of JUICE and Europa Clipper, there are instruments suitable for the search of specific biosignatures that can diagnose life tracks in two ways. The payloads include mass spectrometers capable of measuring isotopic abundances for identifying life, and chromatography instruments testing whether ocean worlds harbor amphiphile mixtures, which would lead to a lipid-first origin of life. In this paper we describe how the two missions may begin to test whether there may be large detectable excursions of stable isotopes of chemical elements on the icy surfaces of the Jovian icy moons that are substantially shifted from their expected isotopic distributions. The detection of an unambiguous signal would suggest a biogenic origin, provided care is taken to exclude abiotic thermal isotopic fractionation. Our suggested tests should be confirmed independently with other techniques. Stable isotope geochemistry on the icy Jovian moons has not yet been thoroughly discussed in the literature. In addition, we enquire whether insights into life's origin could be retrieved from Europa's ocean and surface, including the question of the first steps in the evolution of life. Special emphasis has been put on an approach to seek on the surface of ocean worlds chemical phenomena that are rather primitive, such as reproducing lipid micelles as roots of protocells, but nevertheless can predict a path towards life with published models.

Abstract We review and elaborate on the issue of three-dimensional (3D) world-volume supersymmetry that appears as a residual part of global target space supersymmetry in the Bergshoeff–Sezgin–Townsend (BST) supermembrane action. While there is no direct ‘spinning membrane’ analogue of the world-volume supersymmetric spinning string action that could be obtained by coupling D copies of 3D scalar multiplet to 3D supergravity, we discuss how one may construct an N=1 3D supersymmetric analogue of the derivative expansion of the bosonic membrane action in static gauge. We compare the resulting N=1 supersymmetric action for eight 3D scalar multiplets to the N=8 3D supersymmetric action describing the D=11 supermembrane in the static gauge. The two actions are not equivalent which is related to the fact that the full N=8 supersymmetry of the static-gauge D=11 supermembrane action can be realized only if the fermions are described by an SO(8) spinor rather than vector. The two actions are still directly related in special dimensions D=4 and 5. We also compute the one-loop world-volume scattering amplitudes for the two theories finding that they indeed agree for D=4,5 but disagree for D=11.

Understanding the spatial distribution and intensity of climate-related hazards is essential for effective risk assessment and adaptation planning. This study presents a comprehensive analysis of climate hazard indices applied across all IPCC reference regions, using all the available CMIP5-driven regional climate model (RCM) simulations at 25 km resolution over the CORDEX domains, together with Euro-CORDEX simulations at 12 km resolution. The objective is to identify climate hazard hot spots through the formulation of a composite hazard index. A subset of hazard indicators representing key climate extremes is selected. Temperature- and heat-stress–related hazards are characterized using TX90p (extreme maximum temperature), TN90p (extreme minimum temperature), and the NOAA Extended Heat Index (HI). Heavy precipitation and drought-related hazards are represented by RX1DAY (maximum 1-day precipitation), P99 (99th percentile of precipitation), and CDD (consecutive dry days).The composite index integrates both the frequency and intensity of extremes and is computed at both regional and grid-point levels. A normalization approach is used to ensure comparability across regions with diverse climatic characteristics. Results reveal pronounced spatial heterogeneity in hazard intensity, highlighting regions where multiple hazards converge and amplify overall risk. This framework enables systematic identification of global and regional climate hot spots, offering insights into areas that may face heightened climate stress under current and projected conditions. By providing a consistent, region-wide assessment of hazard exposure, this study aims to support comparative climate risk analyses and inform policy-relevant decision-making for climate adaptation and resilience strategies at multiple scales.

Europe suffers great financial loss and loss of life every year due to extreme events, particularly heat waves, flooding, droughts, and wildfires. The impacts of these events are increasing with both the increasing exposure of society and the increasing intensity and frequency of the events themselves under a warming climate. Accurate projections of the future changes in extreme events are vital for those stakeholders responsible for preparing the European cities to withstand future extreme events. They are also highly valuable to many industries which are heavily exposed to the impacts of extreme events, including insurance, construction, agriculture, health and energy. However, any adaptation requires information that is tailored to the needs and workflow of the decision makers.In the EU-Impetus4Change project (I4C), we worked with stakeholders from four cities across Europe to select hazard indicators that are relevant to their ongoing adaptation work. The cities of Paris, Prague, Barcelona, and Bergen, were selected because they represent a wide range of climates across Europe and because they provide a sample of the different types of hazardous events faced by most European cities. The selected indicators focus primarily on extreme temperatures and precipitation hazards, though some relate to other sectors including energy and human health. The indicators have been calculated in 67 Euro-CORDEX simulations covering 120 years from 1980 to 2100 at a horizontal resolution of 0.11°. They have also been calculated in various convection permitting simulations of 10-year time slices in the current, mid-century and end of century, with a horizontal resolution of 3 km. This talk will present highlights from the analysis of this unique dataset, show the projected changes in these stakeholder-relevant indicators across different Global Warming Levels (GWLs), explore the biases compared to reanalysis, and examine the improvements of the convection permitting simulations compared to the lower resolution Euro-CORDEX simulations. The full dataset of these indices is planned to be made openly available through an online, user-friendly toolkit as part of the ongoing I4C project.

Abstract Climate change is intensifying the frequency and severity of environmental hazards, with distinct impacts in urban and rural areas. Cities can experience amplified risks due to the urban heat island effect and increased exposure to extremes. We analyze climate extreme indices using Euro-CORDEX regional climate models that include urban representations, focusing on 40 cities and their surrounding rural areas. Our findings highlight that city-scale hazards intensify with warming across the domain, while precipitation responses are strongly regional. Mediterranean cities exhibit robust drying and longer dry spells, whereas central and northern European cities experience the strongest and most widespread increases in heavy-precipitation extremes. Urban–rural contrasts strengthen several hazard metrics, particularly minimum-temperature extremes, with the strongest signals found in inland cities, underscoring the need for targeted adaptation measures. Understanding how global warming impacts these hazard indices is crucial for developing climate-resilient policies and strategies tailored to both urban and rural settings.