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关键词： Computer science   Engineering   Energy systems  

摘要： Global warming concerns have led to emission regulations and various incentives for low-carbon technologies. Energy system models, which are used to examine how investments affect our ability to meet energy demand, are typically based on two assumptions: key parameters are assumed to be known deterministically and a multi-period energy transition plan is determined at one point in time. We argue that for a systematic generation and analysis of energy transition pathways, these assumptions should be relaxed and, accordingly, we propose methods to achieve that. First, we use stochastic programming (SP) to account for uncertainty in key parameters. Second, we pair SP with a sequential decision-making approach that represents how decisions can be updated as uncertainties unfold. Third, we use simulation-based methods to evaluate the quality of energy transitions. Importantly, we find that accounting for uncertainty, proactively and through feedback, yields pathways with diverse technology portfolios that are resilient to uncertainty.

关键词： Applied sciences   Computer science   Engineering  

摘要： Advancements in noninvasive surface and internal imaging techniques, along with computational methods, have revolutionized 3D visualization of organismal morphology-enhancing research, medical anatomical analysis, and facilitating the preservation and digital archiving of scientific specimens. We introduce the SmARTR pipeline (Small Animal Realistic Three-dimensional Rendering), a comprehensive workflow integrating wet lab procedures, 3D data acquisition, and processing to produce photorealistic scientific data through 3D cinematic rendering. This versatile pipeline supports multiscale visualizations-from tissue-level to whole-organism details across diverse living organisms-and is adaptable to various imaging sources. Its modular design and customizable rendering scenarios, enabled by the global illumination modeling and programming modules available in the free MeVisLab software and seamlessly integrated into detailed SmARTR networks, make it a powerful tool for 3D data analysis. Accessible to a broad audience, the SmARTR pipeline serves as a valuable resource across multiple life science research fields and for education, diagnosis, outreach, and artistic endeavors.

关键词： Computer science   Computational mathematics   Artificial intelligence  

摘要： Neighborhood rough set (NRS) have been successfully applied to attribute reduction (AR). However, most current methods of AR based on NRS are supervised or semi-supervised. This limits their ability to process data without decision information. When granulating data samples, NRS considers only the number of samples within the neighborhood radius. It does not consider distribution information between samples, which can result in the loss of original data information. To address the aforementioned issue, we propose an unsupervised attribute reduction (UAR) strategy based on variable precision weighted neighborhood dependency (VPWND) (UAR_VPWND). We compare algorithm UAR_VPWND to existing classical UAR algorithms using public datasets. The experimental results show that algorithm UAR_VPWND can select fewer attributes to maintain or improve the performance of clustering learning algorithms.

关键词： Computer science   Engineering   Environmental science  

摘要： In an emerging trajectory-based operation (TBO) environment within the advanced autonomous airspace, traffic operation along reference trajectories can function as trajectory-following mechanisms. However, 5G-based following dynamics still remain underexplored, limiting further utilization of lower-latency 5G technology other than data links. This limitation affects air traffic stability when encountering disturbance, preventing autonomous airspeed adjustment, and safe separation without air traffic controller interventions. Thus, this paper addresses these gaps by proposing a generalized 5G-based trajectory-following model to explore microscopic behaviors and traffic stability in a typically connected environment. Three key variables are identified based on the classical optimal velocity model: bi-directional attention distribution, airto-air communication performance, and communication latency. Finally, the stability criterion is derived by the adopted perturbation method. Typical numerical simulations have verified the air traffic stability under various connectivity degrees. These findings can precisely identify the optimal connectivity, rational attention distribution, and their balance for enhancing stability.

关键词： Highlights   scenarios   Computer science   Artificial intelligence  

摘要： With the increasing popularity of location-based services (LBSs), safeguarding location privacy has become critically important. Traditional methods often struggle to balance the intensity of privacy protection with service quality. To address this challenge, this research proposes the comprehensive location privacy enhanced model (CLPEM), which enhances personalized privacy protection by integrating dynamic weight allocation at the policy layer, incorporating a user feedback mechanism, and designing tailored privacy strategies for various scenarios. Additionally, the model employs data fusion and optimization techniques to enhance the usability of location data while ensuring effective privacy protection. Our experimental results demonstrate that CLPEM outperforms existing technologies in terms of privacy strength, data availability, and user satisfaction, providing a robust technical framework for location privacy and paving the way for future research and applications.

关键词： Computer science   Machine learning   Philosophy  

摘要： Researchers call on technology companies to test their systems for consciousness and create AI welfare policies.

关键词： Arctic   COI   Insect   Overwintering   Pemphigus groenlandicus   Taxonomy  

摘要： Species identification within the aphid genus Pemphigus Hartig, 1839 poses challenges due to morphological similarities and host-plant associations. Aphids of this genus generally exhibit complex life cycles involving primary hosts (poplars) and secondary (mostly unrelated herbaceous) host-plants, with some species relying solely on root-feeding generation. An example is a representative of the genus Pemphigus, trophically associated with grass roots, found in the High Arctic Svalbard archipelago. Historical records tentatively identify it as Pemphigus groenlandicus (R & uuml;bsaamen, 1898), although its formal classification remains elusive, due to limited material of freshly collected samples. Recent collections from 2007 to 2024 across various Svalbard sites, revealed its presence under stones in sheltered microhabitats, providing valuable specimens for comparative studies. Our molecular analyses indicate that the Svalbard specimens are not a separate species commonly identified as P. groenlandicus, nor an anholocyclic generation of Pemphigus bursarius (Linnaeus, 1758) or P. borealis Tullgren, 1909, but represent a secondary generation of Pemphigus populiglobuli Fitch, 1859, the Nearctic poplar bullet gall aphid. This suggests that they may have lost their primary host associations and adapted to living on grass roots year-round. Our specimens did not host any known facultative symbionts;however, we detected a strain of Pseudomonas Migula, 1894, closely related to a cold-tolerant bacterium abundant in polar regions. The present study also investigates the taxonomic relationships and morphometric characteristics of grass-feeding Pemphigus populations across the Arctic and an isolated locations on the European continent. Specimens from Svalbard were compared with samples from Greenland and Iceland, but identified no substantial morphometric differences among these geographically separated populations. Similarly, analyses of samples of Pemphigus groenlandicus crassi

关键词： Gelatin hydrogel nanoparticles   Gastric cancer treatment   BPA sensing   Nursing applications   Computer Science  

摘要： This study presents a dual application approach for the environmentally friendly synthesis of gelatin hydrogel nanoparticles with potential applications in gastric cancer treatment, bisphenol A (BPA) sensing, and nursing. Gelatin hydrogel nanoparticles were synthesized using a green and freeze-drying method, avoiding the use of toxic chemicals and solvents. The nanoparticles showed excellent biocompatibility and promising potential for drug delivery system (DDS) in gastric cancer treatment. The controlled release of anticancer drugs from the gelatin nanoparticles was showed, highlighting their potential in targeted therapy. Additionally, the gelatin hydrogel nanoparticles were explored for BPA sensing. BPA is a widely used chemical known for its adverse effects on human health. The gelatin nanoparticles showed high selectivity and sensitivity towards BPA detection, making them suitable for environmental monitoring and health applications using scanning electron microscope (SEM). Also, in this study, an artificial neural network (ANN) was used to estimate the release of docetaxel (%) at 72 h, the release of paclitaxel (%) at 72 h, tensile strength with sample (wt%), and porosity (%) in broader ranges than the experimental samples. The environmentally friendly synthesis of gelatin hydrogel nanoparticles presented in this study offers a versatile platform with dual applications in gastric cancer treatment and sensing of harmful chemicals. The obtained results show the potential of these nanoparticles for innovative therapeutic and diagnostic strategies in healthcare and environmental monitoring. The study showed the development of sustainable and multifunctional nanomaterials for various biomedical applications. The modeling of the neural network predictions shows that increasing the sample (wt%) and porosity (%) leads to an increase in the release of docetaxel (%) at 72 h, the release of paclitaxel (%) at 72 h, and tensile strength. As porosity decreases, the release

关键词： Computer science   Scientific community   Machine learning  

摘要： How many researchers are using the AI tool?Naturegathers data and talks to members of the academic community.

关键词： Computer science   Machine learning   Mathematics and computing   Technology   Society  

摘要： AI companies want to give machines human-level intelligence. The safest and best results will come when academic and industry scientists oversee it together.