The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently utilized technologies, providing an overview of emerging technologies, addressing material challenges, exploring novel computing concepts, and finally examining the maturity level of emerging technologies while determining the next essential steps for their advancement.

Improved molecular strong-field approximation theory is used to calculate the ionisation probability for the high-order above-threshold ionisation process induced by a few-cycle pulse with two carrier frequencies and one envelope. The asymmetry in the photoelectron momentum distribution is due to the ultrashort nature of the driving pulse and due to the relative orientation of the molecule with respect to the laser field. We introduce the generalised asymmetry parameter, which can be used to quantitatively measure the asymmetry between the photoelectron spectra along arbitrarily many selected directions. We investigate the difference between the asymmetry parameters calculated for atomic and molecular targets and show that the contributions to the asymmetry strongly depend on the type of the employed driving pulse. For the driving pulse with components that are linearly polarised with mutually orthogonal polarisations, we find that the main source of the asymmetry, especially in the high-energy part of the spectrum, is the ultrashort nature of the pulse. The relative orientation of the molecule with respect to the laser pulse only affects the low- and medium-energy parts of the spectrum. On the other hand, for the driving pulse with circularly polarised counterrotating components, the asymmetry introduced by molecular orientation is more pronounced. We also analyse the influence of the characteristics of molecular orbitals on the asymmetries using the examples of N2 and O2 molecules.

The eternal 1-secure set, strategically protects graphical structures against attacks by placing sentinels within dominating sets. This study adapts this concept to real-world scenarios, like emergency response systems, by addressing challenges such as roadblocks and traffic congestion. We introduce the secure set and the eternal 1-secure set for fuzzy graphs based on edge membership levels J. Our analysis examines the relationship between the security number of a fuzzy graph G at level J and the domination number of its spanning subgraph at level J, demonstrating the potential of the eternal 1-secure set to enhance security measures in dynamic environments.

We present single-stage optimization of islands in finite-β stellarator equilibria. Stellarator optimization is traditionally performed as a two-stage process; in the first stage, an optimal equilibrium is calculated that balances a set of competing constraints, and in the second stage, a set of coils is found that supports the said equilibrium. Stage one is generally performed using a representation for the equilibrium that assumes nestedness of flux surfaces, even though this is not warranted and occasionally undesired. The second stage optimization of coils is never perfect, and the mismatch leads to worse performing equilibria and further deteriorates if additional constraints, such as force minimization, coil torsion, or port access, are included. The higher fidelity of single-stage optimization is especially important for the optimization of islands as these are incredibly sensitive to changes in the field. In this paper, we demonstrate an optimization scheme capable of optimizing islands in finite β stellarator equilibria directly from coils. We furthermore develop and demonstrate a method to reduce the dimensionality of the single-stage optimization problem to that of the first stage in the two-stage approach.

Introduction. The development of the coronavirus disease 2019 (COVID-19) vaccine marked the beginning of the end of the pandemic and the understanding of the disease as something that is part of clinical practice. The aim of this study was to investigate, assess, and demonstrate the signifi cance of vaccination on the outcome of severely ill patients treated in intensive care units. Methods. A retrospective study was conducted on a sample of patients hospitalized at the Clinic for Infectious Diseases of the Clinical Center of the University of Sarajevo during 2022. Results. Participants who were vaccinated against COVID-19 had a lower mortality rate and a higher chance of survival compared to unvaccinated participants. Additionally, disease outcomes were signifi cantly infl uenced by oxygen saturation and platelet count at admission. Conclusion. COVID-19 vaccination signifi cantly reduced the mortality rate, with vaccinated par-ticipants having a higher chance of survival compared to unvaccinated participants.

Case summary A 1-year-old domestic shorthair queen with five neonates was referred for umbilical cord entwinement in three kittens 24 h after parturition. The owner noticed the kittens were stuck to each other 3 h before admission. Despite a conservative treatment approach, prolonged ischaemia led to dry gangrenous changes in one of the kitten’s metatarsi. Relevance and novel information This and other neonatal complications in cats are rarely reported. Primiparity is a known factor contributing to postpartum complications. Furthermore, inexperienced owners require more assistance in mitigating these challenges. Therefore, further research and collaboration among breeders, owners and veterinary professionals are imperative in order to accurately determine the prevalence of this condition in kittens and develop effective strategies to address it.

BACKGROUND The proliferation of sexting among adolescents around the world today has woven a complex tapestry of sexual expression and exploration. However, its implications extend beyond consensual engagement, occasionally manifesting as a form of cyberviolence. Varied prevalence rates further complicate our understanding of the extent of youth sexting worldwide. Therefore, this study aims to provide a tool to measure sexting in young people from different countries by validating the Sexting Behaviours and Motives Questionnaire (SBM-Q), a comprehensive instrument that captures the diversity of consensual and non-consensual sexting behaviors and motives in different countries. METHOD A total of 4739 students, aged 15 to 25, participated. They were from Spain (1563), Croatia (1598), and Bosnia and Herzegovina (1578). Confirmatory factor analyses and multigroup analyses were conducted. RESULTS The validity of the instrument was confirmed, endorsing its six-factor structure, which includes the dimensions of sending, reasons for sending, victimization by non-consensual forwarding, receiving, forwarding, and reasons for forwarding. Internal consistency across the three countries further underscores the robustness of the SBM-Q. CONCLUSIONS This validated questionnaire provides a reliable measure for understanding sexting behaviors and motives in different countries. Cultural nuances are discussed.

Robots and other autonomous agents are well-positioned in the research discourse to support the care of people with challenges such as physical and/or cognitive disabilities. However, designing these robots can be complex as it involves considering a wide range of factors (e.g., individual needs, physical environment, technology capabilities, digital literacy), stakeholders (e.g., care recipients, formal and informal caregivers, technology developers), and contexts (e.g., hospitals, nursing homes, outpatient care facilities, private homes). The challenges are in gaining design insights for this unique use case and translating this knowledge into actionable, generalizable guidelines for other designers. This one-day workshop seeks to bring together researchers with diverse expertise and experience across academia, healthcare, and industry, spanning perspectives from multiple disciplines, including design, robotics, and human-computer interaction, with the primary goal being a consensus on best practices for generating and operationalizing design knowledge for robotic systems for care settings.

We report a case of a 34-year-old woman diagnosed with HER2-positive breast cancer at 12 weeks of pregnancy. The oncology team opted for neoadjuvant chemotherapy while continuing the pregnancy. To exclude metastatic liver disease, CT was not feasible due to radiation risks, and liver MRI was avoided due to concerns about gadolinium deposition in the fetal basal ganglia.

Thermal insulation materials play a vital role in minimising energy loss in building operation and also affect the amount of greenhouse gas emissions associated with heating and cooling. In this context, it is becoming an increasingly important milestone to find suitable thermal insulation materials that not only meet the technical requirements but also minimise their environmental impact. The trend towards the use of eco-friendly materials for thermal insulation reflects the construction industry’s desire to contribute to environmental protection and the transition to more sustainable models of building construction and renovation. For more than 20 years, a number of research teams have been investigating the possibility of replacing synthetically produced materials such as mineral wool and polystyrene foam with natural fibre-based insulation materials. These alternatives include wood as a traditional, easily renewable raw material. This, together with the low energy intensity of processing and manufacturing wood materials, contributes to its low carbon footprint. Compared to traditional synthetic insulation materials, which are often energy intensive to produce, wood is a more environmentally friendly choice. However, with many European countries now facing a potential shortage of higher quality wood, it is necessary to look for alternative sources of wood, including in the field of thermal insulation materials, materials with a lower carbon footprint that can be produced from lower quality wood or from wood waste that would otherwise only have an energy use. The paper is devoted to the study and use of suitable wood waste and secondary raw materials from spruce wood (coarse wood chips, sawdust and wood flour) for the development of modern thermal insulations with the aim of an environmentally friendly and less energy-intensive production process compared to conventional insulants.

Abstract Red mud, a voluminous industrial waste produced during the Bayer process in the alumina industry, has numerous application possibilities across various fields. Its potential uses are diverse, ranging from the construction industry and metallurgy to environmental protection and agriculture. There are three main aspects of red mud utilization. First, it can be analyzed from the point of view of resource utilization, where it could be applied as raw material mostly in the construction industry. Second, it could be a useful source of valuable components, such as rare earths and metals, especially iron. Third, red mud could have different environmental applications, in wastewater treatment, soil remediation, etc.The paper summarizes current data on red mud utilization methods and aims to emphasize the potential for red mud utilization in various fields.

The paper explores the evolving role of Artificial Intelligence (AI) in perinatal medicine and hu-man reproduction, highlighting its potential to transform clinical practices. AI technologies are being utilized to improve diagnostic accuracy, personalize treatment, and enhance patient care, particularly in areas like perinatal ultrasound, fetal heart rate monitoring, and fetal neurology. The Kurjak Antenatal Neurodevelopmental Test (KANET) exemplifies how AI can aid early detection of neurodevelopmental disorders. However, the integration of AI presents challenges such as data quality concerns, algorithmic bias, ethical concerns, and the need for robust regulatory frameworks. The authors argue that while AI offers significant opportunities, its implementation must be carefully managed to avoid over-reliance on technology and ensure equitable healthcare access. The paper concludes that the current state of AI in this field marks not an endpoint but a critical phase of growth and development, necessitating a balanced approach that combines innovation with ethical and practical considerations.

Accurate differentiation between Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) is essential in the field of cardiology. Recent advancements in deep learning have facilitated automated arrhythmia recognition, surpassing traditional electrocardiogram (ECG) methods that depend on manual feature extraction. Building on our previous work, which emphasized the importance of identifying patterns of regularity, we have developed a model that merges Graph Convolutional Networks (GCN) with Long Short-Term Memory (LSTM) networks. This GCN-LSTM model employs a trainable weighted ϵ-neighborhood graph to capture the similarity among time series within ECG segments. This approach has demonstrated substantial improvement in the classification of VT, VF, and non-ventricular rhythms.

The targeted compounds in this research, resveratrol analogs 1–14, were synthesized as mixtures of isomers by the Wittig reaction using heterocyclic triphenylphosphonium salts and various benzaldehydes. The planned compounds were those possessing the trans-configuration as the biologically active trans-resveratrol. The pure isomers were obtained by repeated column chromatography in various isolated yields depending on the heteroaromatic ring. It was found that butyrylcholinesterase (BChE) was more sensitive to the heteroaromatic resveratrol analogs than acetylcholinesterase (AChE), except for 6, the methylated thiophene derivative with chlorine, which showed equal inhibition toward both enzymes. Compounds 5 and 8 achieved the highest BChE inhibition with IC50 values of 22.9 and 24.8 μM, respectively. The same as with AChE and BChE, methylated thiophene subunits of resveratrol analogs showed better enzyme inhibition than unmethylated ones. Two antioxidant spectrophotometric methods, DPPH and CUPRAC, were applied to determine the antioxidant potential of new heteroaromatic resveratrol analogs. The molecular docking of these compounds was conducted to visualize the ligand-active site complexes’ structure and identify the non-covalent interactions responsible for the complex’s stability, which influence the inhibitory potential. As ADME properties are crucial in developing drug product formulations, they have also been addressed in this work. The potential genotoxicity is evaluated by in silico studies for all compounds synthesized.