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Abstract The framework of this study is to weight 8 selected determinants and rank energy alternatives for hydrogen investments. For this purpose, different criteria that are based on two dimensions are identified with supported literature and interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) with alpha cuts is considered to measure the significant criteria. Additionally, renewable and non-renewable energy alternatives are ranked regarding the appropriateness for hydrogen energy investments with the help of IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and IT2 fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) with alpha cuts. It is concluded that the weights of the criteria are quite similar for different alpha cuts. Also, ranking results of different energy alternatives are almost the same for both IT2 fuzzy TOPSIS and IT2 fuzzy VIKOR. Thus, it can be concluded that the analysis results are reliable and coherent. The principal results indicate that cost-efficiency and reserve adequacy play a key role in hydrogen investments since they have the highest weight (0.129). Moreover, it is also found that technological capacity also plays a critical role in this regard with the weight of 0.127. However, legal regulation has the lowest importance weight (0.121) in comparison with other factors. Additionally, the weights of personnel competency (criterion 3) and storage (criterion 4) are also low (0.122). The major conclusion show that renewable energy alternatives are more suitable to generate hydrogen energy in comparison with non-renewable ones. Within this context, it is identified that solar and geothermal energies are more appropriate alternatives for hydrogen production whereas coal and nuclear are on the last rank. Hence, the main strategy should be lowering the costs by following up-to-date technological developments. Another important issue is that it becomes more logical to produce hydrogen in renewable energy sources that will not be consumed forever so that sustainable production of the hydrogen can be provided.

Non-orthogonal multiple access (NOMA) deployment in future wireless networks has been recently considered a promising radio access technology to enhance spectral efficiency (SE). However, gain in SE comes always with the cost of energy efficiency (EE). In this paper, we investigate the SE and EE tradeoff in downlink NOMA with the consideration of quality of service (QoS) requirements based on three population-based multi-objective evolutionary algorithms (MOEAs): multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm-II (NSGA-II) and strength Pareto evolutionary algorithm-2 (SPEA2). The tradeoff is optimized and Pareto optimal solutions are obtained through MOEAs. The effectiveness of the algorithms is evaluated based on the hypervolume metric and the capability of solving multi-objective optimization problems. Simulation results reveal that SPEA2 outperforms NSGA-II and MOPSO. Furthermore, NSGA-II is the loser among all algorithms in terms of finding Pareto optimal results.

This paper proposes a technique for the probabilistic wind power forecasting (WPF) of a newly built wind farm (NWF) using a limited amount of historical data. First, the state-of-the-art Transformer network is employed to capture the power generation pattern of different wind farms (WFs) based on abundant historical training samples. Then, the Bayesian averaging regression method is applied to transfer the learned power generation pattern to the NWF by assigning proper weights to the WPF results of different WFs. This enables the proposed method to yield accurate NWF power predictions utilizing a limited amount of historical data. The Bayesian characteristics further enable the quantification of multiple uncertainties in forecasting results that may be essential for the NWF operator when the input is uncertain. Comprehensive tests were also performed by employing other deterministic and probabilistic WPF methods using field data. By comparing the results, the proposed method is demonstrated to produce accurate forecasting results with sparse historical data. Moreover, the uncertainties of outcomes are quantified, and acceptable performance is achieved.

[EN] Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real-world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi-physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle¿s Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time-resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively. This research is part of the project TED2021-131463B-I00 (DI-VERGENT) funded by MCIN/AEI/10.13039/501100011033 and the European Union "NextGenerationEU"/PRTR. It has also been partially funded by the Spanish Ministry of Science, Innovation, and University through the University Faculty Training (FPU) program (FPU19/00550) . Toby Rockstroh and Ram Vijayagopal acknowledge support through the US DOE Vehicle Technologies Program. Argonne National Laboratory is operated by UChicago Argonne, LLC under Contract no. DE-AC02-06CH11357. The US Government retains for itself, and others acting on its behalf, a paid-up non-exclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly, by or on behalf of the Government. The authors would like to express their gratitude to Kevin Stutenberg from Argonne National Laboratory for the informative discussions surrounding the experimental test campaign.

ABSTRACTIntraguild interactions among carnivores have long held the fascination of ecologists. Ranging from competition to facilitation and coexistence, these interactions and their complex interplay influence everything from species persistence to ecosystem functioning. Yet, the patterns and pathways of such interactions are far from understood in tropical forest systems, particularly across countries in the Global South. Here, we examined the determinants and consequences of competitive interactions between dholes Cuon alpinus and the two large felids (leopards Panthera pardus and tigers Panthera tigris) with which they most commonly co‐occur across Asia. Using a combination of traditional and novel data sources (N = 118), we integrate information from spatial, temporal, and dietary niche dimensions. These three species have faced catastrophic declines in their extent of co‐occurrence over the past century; most of their source populations are now confined to Protected Areas. Analysis of dyadic interactions between species pairs showed a clear social hierarchy. Tigers were dominant over dholes, although pack strength in dholes helped ameliorate some of these effects; leopards were subordinate to dholes. Population‐level spatio‐temporal interactions assessed at 25 locations across Asia did not show a clear pattern of overlap or avoidance between species pairs. Diet‐profile assessments indicated that wild ungulate biomass consumption by tigers was highest, while leopards consumed more primate and livestock prey as compared to their co‐predators. In terms of prey offtake (ratio of wild prey biomass consumed to biomass available), the three species together harvested 0.4–30.2% of available prey, with the highest offtake recorded from the location where the carnivores reach very high densities. When re‐examined in the context of prey availability and offtake, locations with low wild prey availability showed spatial avoidance and temporal overlap among the carnivore pairs, and locations with high wild prey availability showed spatial overlap and temporal segregation. Based on these observations, we make predictions for 40 Protected Areas in India where temporally synchronous estimates of predator and prey densities are available. We expect that low prey availability will lead to higher competition, and in extreme cases, to the complete exclusion of one or more species. In Protected Areas with high prey availability, we expect intraguild coexistence and conspecific competition among carnivores, with spill‐over to forest‐edge habitats and subsequent prey‐switching to livestock. We stress that dhole–leopard–tiger co‐occurrence across their range is facilitated through an intricate yet fragile balance between prey availability, and intraguild and conspecific competition. Data gaps and limitations notwithstanding, our study shows how insights from fundamental ecology can be of immense utility for applied aspects like large predator conservation and management of human–carnivore interactions. Our findings also highlight potential avenues for future research on tropical carnivores that can broaden current understanding of intraguild competition in forest systems of Asia and beyond.

Regional estimates of economic damages across the UK by sector, for sectors driven by local climate.

The development of environmentally friendly techniques to obtain mesoporous solids allows the construction of new and better materials, making potential use of natural resources. In this study, mesoporous silica with high specific surface area and controlled porosity is synthesized by a novel and facile method, which employs potato or corn starches as directing structure agent. Using SEM microscopy, the ellipsoidal morphology of potato starch and the irregular and polygonal shape of corn starch were determined. Pattern A and B were identified by XRD, corresponding to samples of cereals and tubers, respectively. The stages of gelatinization and retrogradation of the starches were studied, obtaining mesoporous silicas with type IV adsorption/desorption isotherms and specific surface areas of 708.6 m2 g−1 with potato starch and 1018.1 m2 g−1 with corn starch for short gelatinization times (4 h, 353 K) and long retrogradation (14 h, 298 K). In addition, the use of HCl solution promoted the hydrolysis of starch in its monomeric unit (glucose) and the consequent bimolecular nucleophilic substitution with silica. The materials obtained presented a random mesoporous order and a CO2 adsorption capacity at 373 K in the range between 150.2 and 131.4 mg CO2 g−1. Fil: Aspromonte, Soledad Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera". Universidad Nacional del Litoral. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera"; Argentina Fil: Tavella, María Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera". Universidad Nacional del Litoral. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera"; Argentina Fil: Boix, Alicia Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera". Universidad Nacional del Litoral. Instituto de Investigaciones en Catálisis y Petroquímica "Ing. José Miguel Parera"; Argentina Fil: Albarracín, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología de los Alimentos; Argentina

This archive includes a minimal dataset needed to reproduce the analysis as well as a table (CSV) and spatial polygons (ESRI shapefile) of the resulting output from the publication: Hoecker, T.J., S. A. Parks, M. Krosby & S. Z. Dobrowski. 2023. Widespread exposure to altered fire regimes under 2°C warming is projected to transform conifer forests of the Western United States. Communications Earth and Environment. Publication abstract: Changes in wildfire frequency and severity are altering conifer forests and pose threats to biodiversity and natural climate solutions. Where and when feedbacks between vegetation and fire could mediate forest transformation are unresolved. Here, for the western U.S., we used climate analogs to measure exposure to fire-regime change; quantified the direction and spatial distribution of changes in burn severity; and intersected exposure with fire-resistance trait data. We measured exposure as multivariate dissimilarities between contemporary distributions of fire frequency, burn severity, and vegetation productivity and distributions supported by a 2 °C-warmer climate. We project exposure to fire-regime change across 65% of western US conifer forests and mean burn severity to ultimately decline across 63% because of feedbacks with forest productivity and fire frequency. We find that forests occupying disparate portions of climate space are vulnerable to projected fire-regime changes. Forests may adapt to future disturbance regimes, but trajectories remain uncertain.