Model Resolution Research Articles

A dual branch attention network based on practical degradation model for face super resolution

A dual branch attention network based on practical degradation model for face super resolution

Sensitivity of the future evolution of the Wilkes Subglacial Basin ice sheet to grounding-line melt parameterizations

Abstract. Projections of Antarctic Ice Sheet mass loss and therefore global sea level rise are hugely uncertain, partly due to how mass loss of the ice sheet occurs at the grounding line. The Wilkes Subglacial Basin (WSB), a vast region of the East Antarctic Ice Sheet, is thought to be particularly vulnerable to deglaciation under future climate warming scenarios. However, future projections of ice loss, driven by grounding-line migration, are known to be sensitive to the parameterization of ocean-induced basal melt of the floating ice shelves and, specifically, to the adjacent grounding line – termed grounding-line melt parameterizations (GLMPs). This study investigates future ice sheet dynamics in the WSB with respect to four GLMPs under both the upper and lower bounds of climate warming scenarios from the present to 2500, with different model resolutions, ice shelf melt parameterizations (ISMPs) and choices of sliding relationships. The variation in these GLMPs determines the distribution and the amount of melt applied in the finite-element assembly procedure on partially grounded elements (i.e. elements containing the grounding line). Our findings indicate that the GLMPs significantly affect both the trigger timings of tipping points and the overall magnitude of ice mass loss. We conclude that applying full melting to the partially grounded elements, which causes melting on the grounded side of the grounding line, should be avoided under all circumstances due to its poor numerical convergence and substantial overestimation of ice mass loss. We recommend preferring options that depend on the specific model context, by either (1) not applying any melt immediately adjacent to the grounding line or (2) employing a sub-element parameterization.

Planning and Evaluation of Water-Dropping Strategy for Fixed-Wing Fire Extinguisher Based on Multi-Resolution Modeling

The deployment of fixed-wing aircraft in fire-extinguishing operations represents a significant advancement in the domain of aviation emergency rescue. Addressing the challenge of enhancing firefighting efficacy, this study delves into the water-dropping strategies of fixed-wing extinguishers and provides a methodological framework for the strategic planning and assessment of water-dropping tactics, employing multi-resolution modeling. The formulation of the planning algorithm and the structure of the effectiveness evaluation index system are explained accordingly. The corresponding prototype system was designed, comprising four subsystems that utilized distinct resolution models: fire environment simulation, water-dropping point scheme planning, approaching path planning, and mission evaluation simulation. Case studies validate the system’s capability to forecast fire and smoke propagation, plan a water-dropping trajectory based on the fire line, optimize flight paths based on the trajectory, and simulate as well as evaluate the whole firefighting mission process. The above research comprehensively constructs the model, finishes the iterative optimization, and evaluates the water-dropping strategy by simulation. The technical path and methodological framework of studying water-dropping strategies are established. The outcomes of this study provide invaluable support for the parameter inversion design of the fixed-wing extinguisher, offering decision-making assistance to commanders and supplying training scenarios for new aviation crews.

Use of spectral transmittance model to improve the detection accuracy of chromium in soil

As a new quantitative analysis method for heavy-metal elements in soil, the main function of the polarization resolution model is to filter out the disturbance of other elements on the spectral signal of target plasma. In order to quantify the mechanism of improving detection performance, the spectral transmittance of plasma intensity in the polarization-resolved optical path has been derived, and the relationship between the intensity of polarization-resolved laser-induced breakdown spectroscopy (PRLIBS) and the characteristic peak wavelength has been defined. Using the spectral data in the wavelength range of 424.50–429.24 nm as the characteristic signal, a quantitative analysis method for detection of the Cr element in soil has been developed. The improvement of spectral intensity stability at the characteristic peak of Cr I 425.7 was analyzed, and the mechanism of enhancing the detection accuracy was elucidated. Research has shown that, based on the polarization characteristics of Cr element plasma, PRLIBS is not affected by the matrix effects of soil and characterizes the amplitude conversion from the reference concentration of Cr element to the plasma spectral intensity. The spectral transmittance of plasma spectra depends not only on the characteristic peak wavelength and complex refractive index of heavy-metal elements but also on the measurement conditions such as spatial geometric angles and reflectivity of the transmission medium.

Effect of skin thickness on electromagnetic dosimetry analysis of a human body model up to 100 GHz

Abstract The accuracy of electromagnetic (EM) exposure assessments depends mainly on the resolution of a voxel human body model. The resolution of the conventional human body model is limited to a few millimeters. In the millimeter wave (mmWave) frequency range, EM waves are absorbed by the superficial tissues in the human body. Therefore, resolution and skin thickness of the human body model are important for accuracy of the EM wave exposure metrics recommended by international human safety guidelines. Realistic thickness modeling of the skin tissue on the human body may provide greater accuracy in the EM exposure assessment, especially at mmWave frequency range. In this paper, effects of the skin thickness on the EM exposure metrics in one-dimensional multi-layered models obtained from different regions of the body model are investigated using the dispersive algorithm based on the finite-difference time-domain method over the frequency range from 1 to 100 GHz. Furthermore, effects of eyelid tissue in a human eye on the EM exposure metrics are studied over the frequency range. The EM exposure metrics such as absorbed power density, heating factor, and power transmission coefficient are calculated up to 100 GHz to evaluate the limits of EM wave exposure.

Disentangling regional climate change: Assessing the contribution of global– and regional–scale anthropogenic factors to observed regional warming

Abstract While the influence of uniformly-distributed well-mixed greenhouse gas emissions on global warming is well-documented and robustly attributed through multiple lines of evidence, regional attribution remains more challenging and dependent on the performance and resolution of climate models. This study investigates the extent to which observed regional temperature trends are attributable to global-scale anthropogenic factors, mainly the direct effects of CO2, aiming to differentiate the portion of the change attributable to regional-scale drivers and local feedback mechanisms. To quantify the contribution of global– and regional–scale climate drivers to observed temperature change, we conducted regression analyses using the observed temperature change in HadCRUT4 and the Global Warming Index (GWI) derived from global radiative forcing series. Results indicate that in certain regions — specifically West Asia, East N. America, and West Africa — 62±4%, 61±12%, and 58±3% of the warming observed over 1991-2020 can be attributed to global anthropogenic warming, primarily the direct effects of CO2. The remaining portion, which represents 22±5%, 21±13%, and 27±3% of the observed warming, is attributable to regional drivers. The Mediterranean showcases high sensitivity, with regional drivers contributing 31±8% of the observed 1.2°C warming, amplifying the warming attributed to global anthropogenic drivers, estimated at 55±7% of the warming. The Arctic Ocean along with the Russian-Arctic region exhibits a substantial contribution from regional drivers and local feedback mechanisms to the observed warming amplification, quantified at 43±10% of the 3°C warming over 1991-2020. Regional cooling drivers, however, are significant in East Asia and the Tibetan Plateau, with the latter experiencing a cooling contribution of -42±11%. By breaking down the contributions of climate drivers into global and regional-scale components, we gain valuable insights into the local climate mechanisms responsible for the observed regional warming, which is a crucial factor that affects agriculture, ecosystems and societies.

Restorative Justice and Agrarian Reform Conflict Resolution

Abstract: The government emasculates agrarian reform. The government no longer interprets agrarian reform as a restructuring of land ownership. Furthermore, the interpretation of agrarian reform now primarily focuses on asset legalization, land redistribution, and social forestry. The issue lies in the emasculation of agrarian reform. Various structural agrarian conflicts remain unresolved after the government's implementation of agrarian reform. Differences in interpretation of agrarian reform trigger the conflict. The government's interpretation is different from the community's interpretation, which considers agrarian reform to be a systematic effort to provide the community with access to land. The author recommends the concept of restorative justice as an effort to resolve this problem. The government should use restorative justice instead of the militaristic approach to resolve the problem. This article employs an empirical legal research method, combining a sociological perspective and a case study approach. This article contains several important findings, one of which is that asset legalization is not an agrarian reform. Asset legalization fails to address the issue of land ownership inequality. The government's implementation of land redistribution fails to address the issue of land ownership inequality. The government's version of land redistribution not only fails to resolve the issue of land ownership inequality, but also seizes land from marginalized communities. The same goes for social forestry. Social forestry leaves behind unresolved agrarian and environmental conflicts. Differences in interpreting agrarian reform actually cause all these problems. Therefore, we can use restorative justice as an alternative to solving the problem. As a problem-solving model involving victims and suspects, this resolution model seeks peace between the two parties. The hope is that there will be no more bloody agrarian conflicts, especially related to agrarian reform in Indonesia. Keywords: Agrarian Conflict, Agrarian Reform, Restorative Justice

Submesoscales are a significant turbulence source in global ocean surface boundary layer

The turbulent ocean surface boundary layer is a key part of the climate system affecting both the energy and carbon cycles. Accurately simulating the boundary layer is critical in improving climate model performance, which deeply relies on our understanding of the turbulence in the boundary layer. Turbulent energy sources in the boundary layer are traditionally believed to be dominated by waves, winds and convection. Recently, submesoscale phenomena with spatial scales of 0.1~10 km at ocean fronts have been shown to also make a contribution. Here, by applying a non-dimensional turbulent kinetic energy budget equation, we show that the submesoscale geostrophic shear production at fronts is a significant turbulent energy source within the ocean boundary layer away from the sea surface. The contribution reaches 34% of the total dissipation in winter and 17% in summer at the mid-depth of the boundary layer, despite its intermittency in space and time. This work indicates fundamental deficiencies in previous conceptions of ocean boundary layer turbulence, and invites a reappraisal of the sampling scale in observations, model resolution and parameterizations, and other consequences of the global energy budget.

HVASR: Enhancing 360-degree video delivery with viewport-aware super resolution

In recent years, 360-degree videos have gained significant traction due to their capacity to provide immersive experiences. However, the adoption of 360-degree videos substantially escalates bandwidth demands, necessitating approximately four to ten times more bandwidth than traditional video formats do. This presents a considerable challenge in maintaining high-quality videos in environments characterized by limited bandwidth or unstable networks. A trend has emerged where client-side computational power and deep neural networks are employed to enhance video quality while mitigating bandwidth requirements within contemporary video delivery systems. These approaches segment a video into discrete chunks and apply super resolution (SR) models to each segment, streaming low-resolution (LR) chunks alongside their corresponding SR models to the client. Although these methods enhance both video quality and transmission efficiency for conventional videos, they impose greater computational resource demands when applied to 360-degree content, thereby constraining widespread implementation. This paper introduces an innovative method called HVASR for 360-degree videos that leverages viewport information for more precise segmentation and minimizes model training costs as well as bandwidth requirements. Additionally, HVASR incorporates a viewport-aware training strategy that is aimed at further enhancing performance while reducing computational expenses. The experimental results demonstrate that HVASR achieves an average utility increase ranging from 12.46% to 40.89% across various scenes.

GAN-Based Dual Image Super Resolution for Satellite Imagery Decreasing Radiometric Uncertainty

Abstract. Super resolution for satellite imagery possesses specific challenges due to its unique feature geometry compared to classic computer vision. Specifically, satellite images contain a high amount of relatively small, distributed high-frequency features that are hard to preserve when sampling up to a higher resolution. General adversarial networks (GANs) are suitable for super resolution tasks but need special attention concerning the geometric and radiometric accuracy of the results. We propose a network for versatile satellite imagery super resolution (VSISR) that focuses on high-frequency detail preservation and radiometric consistency. As a novelty, it is able to utilize a reference high resolution image during inference to lower hallucinations without altering the source image’s radiometric characteristics.A GAN that is already handling well high frequencies in standard computer vision cases is adapted for satellite imagery and supplemented with a mixed pixel approach for data augmentation. Training on a diverse RGB dataset from four satellite missions results in a versatile super resolution model that is optimized to preserve radiometric features and minimize hallucinations. Compared to other neural networks for satellite image super resolution in their respective datasets, VSISR performs in the middle regarding mean PSNR (25.30 dB) and SSIM (0.8098). Nevertheless, it is the first time that, using mixed pixel training on a comparably small dataset, this versatility concerning the satellite data source is achieved while maintaining their unique radiometric traits.

Community Conflict Resolution Model in Climate Central Sulawesi Investment

This study is based on the view that Central Sulawesi is a region with increasingly rapid development of the Investment Climate. Not only positive impacts that always occur but also negative impacts. The presence of the state to provide security and comfort to investors is one thing that is needed, on the other hand the state must also be present to provide justice to citizens related to the condition of the region that is always explored by certain parties. The state that is present as a manifestation of the mediator between investors and citizens must present a balance. However, the balancing tool used is of course the law, which is manifested in the form of policy. policies often create inequality between investors and citizens, therefore the law of harmony is present in an innovative form as a manifestation that the law is not arbitrary and not a tool of power, and by the Law of Harmony considers that the Law is the Resultant of an agreement on the goals to be achieved. The desired legal study will be poured into the form of a policy pattern. The pattern born in this study is the antithesis of comparative studies.

Association of ambient ozone exposure with early cardiovascular damage among general urban adults: A repeated-measures cohort study in China

Longitudinal evidence of long-term ozone exposure on heart rate variability (HRV, an early indicator of cardiovascular damage) is lacking and the potential mechanism remains largely unclear. Our objectives were to evaluate the cross-sectional and longitudinal associations of ozone exposure with HRV alteration, and the potential roles of protein carbonyl (PC, biomarker of oxidative protein damage) and transforming growth factor (TGF)-β1 in this association. This repeated-measures prospective study included 4138 participants with 6617 observations from the Wuhan-Zhuhai cohort. Ozone concentrations were estimated using a high temporospatial resolution model for each participant. HRV indices, PC, and TGF-β1 were also repeatedly measured. Cross-sectional and longitudinal relationships of ozone exposure with HRV alteration were evaluated by linear mixed model. Cross-sectionally, the strongest lag effect of each 10 ppb increment in short-term ozone exposure showed a 12.40 %, 8.47 %, 4.31 %, 8.03 %, 3.69 %, and 2.41 % decrement on very low frequency (VLF, lag 3 weeks), LF (lag 2 weeks), high frequency (HF, lag 0–7 days), total power (TP, lag 2 weeks), standard deviation of all normal-to-normal intervals (SDNN, lag 3 weeks), and square root of the mean squared difference between adjacent normal-to-normal intervals (lag 2 weeks), respectively. Longitudinally, each 10 ppb increment of annual average ozone was related with an annual change rate of −0.024 ms2/year in VLF, −0.009 ms2/year in LF, −0.013 ms2/year in HF, −0.014 ms2/year in TP, and −0.004 ms/year in SDNN. Mediation analyses indicated that PC mediated 20.77 % and 12.18 % of ozone-associated VLF and TP decline, respectively; TGF-β1 mediated 16.87 % and 27.78 % of ozone-associated VLF and SDNN reduction, respectively. Our study demonstrated that ozone exposure was cross-sectionally and longitudinally related with HRV decline in general Chinese urban adults, and oxidative protein damage and increased TGF-β1 partly mediated ozone exposure-related HRV reduction.

Influence of Model Resolution on Wind Energy Simulations over Tibetan Plateau Using CMIP6 HighResMIP

The assessment of wind energy resources is critical for the transition from fossil fuel to renewable energy sources. Using the outputs from high-resolution global climate models (GCMs), such as the High Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6), has become one of the most important tools in wind energy research. This study evaluated the reliability of the 22 GCMs available in the HighResMIP-PRIMAVERA project by simulating the wind energy climatology and variability over the Tibetan Plateau (TP) with reference to observations and investigated the differences in performance of the GCMs between high-resolution (HR) and low-resolution (LR) simulations. The results show that most models performed relatively well in simulating the probability distribution of the observed wind speed over the TP, but nearly half of the models generally underestimated the wind speed, whereas the others tended to overestimated the wind speed. Compared with the wind speed, the GCMs showed larger biases in reproducing the wind power density (WPD) and other wind energy resources, whereas the biases in multi-model ensembles were relatively smaller than those in most individual models. With respect to interannual variability, both the HR and LR models failed to capture interannual variations in WPD over the TP. Furthermore, more than half of the HR GCMs had a reduced bias relative to the corresponding LR GCMs, indicating the good performance of most HR models in simulating wind energy resources over the TP in terms of spatial pattern and temporal variability. However, the overall performance of HR GCMs varied among models, which suggests that solely improving the horizontal resolution is not sufficient to completely solve the uncertainties and deficiencies in the simulation of wind energy over complex terrain.

Matrix representation of the graph model for conflict resolution based on intuitionistic preferences with applications to trans-regional water resource conflicts in the Lancang–Mekong River Basin

With the continual growth in global demand for water resources, the governance of trans-regional water resources has become an important field of cooperation between countries, and conflicts caused by competition for water resources have become a focal issue in international relations. The root causes of trans-regional water resource conflicts include unclear ownership of water resources and the limited rationality of the parties involved. The water rights trading model has proven to play a stabilizing role in resolving trans-regional water resource conflicts versus the traditional negotiation model. To demonstrate the rationality and theoretical strength of the water rights trading model in allocating trans-regional water resources in uncertain environments, this paper proposes a novel matrix representation of intuitionistic stability definitions through a graph model for conflict resolution (GMCR). First, decision-makers’ (DMs’) intuitionistic preferences, unilateral movements, and intuitionistic unilateral improvements in a GMCR with two DMs are represented in a matrix. The joint unilateral movements and joint intuitionistic unilateral improvements for a coalition in a GMCR with multiple DMs are also represented. Next, according to the logical forms of intuitionistic stability definitions, four stability definitions in a GMCR with intuitionistic preferences were redefined to enable matrix representations of graph models with either two DMs or multiple DMs. Finally, we analyzed the state transitions and strategies of all stakeholders in trans-regional water resource conflicts in the Lancang-Mekong River Basin within the intuitionistic graph model. The contributions of this paper are twofold. First, in terms of theoretical research, this article enriches and develops the GMCR and proposes a set of definitions of matrix intuitionistic stability. Second, in terms of practical application, the intuitionistic stability analysis results can provide a reference for water rights trading to solve trans-regional water resource conflicts in uncertain environments and transform trans-regional water resource governance systems.

Graph Model for Conflict Resolution for Mixed-Stability Combinatorial Foresight Based on the Combination of Regret Theory and VIKOR Method

Graph Model for Conflict Resolution for Mixed-Stability Combinatorial Foresight Based on the Combination of Regret Theory and VIKOR Method

3-D full-field reconstruction of chemically reacting flow towards high-dimension conditions through machine learning

Monitoring chemically reacting flow is crucial for optimizing and controlling the conversion processes in various chemical engineering scenarios. These processes are often influenced by multiple factors, creating a high-dimensional condition space that imposes intensive computational cost to computational fluid dynamics (CFD) methods. We present a machine learning (ML) framework to reconstruct the 3-D scalar field preserving the accuracy and resolution of CFD modeling. We demonstrate the framework’s effectiveness through a case study on biomass combustion in an industrial-scale grate furnace, which exemplifies the challenges of modeling chemically reacting flow in complex geometric domains influenced non-linearly by multiple parameters. The framework implements three core principles: (1) a Reactor-Structure-Resembled Network (RSRNet) reflecting the operational logics of the reactor, (2) an incremental learning strategy based on random Latin Hypercube Sampling, and (3) the incorporation of self-extracted high-level features from data as soft constraints in the loss function. Ground truth data were calculated through a CFD model, with all cases sampled from a 11-variable condition space. Using only 240 randomly sampled cases (around 1 % total cases in the discretized condition space), RSRNet precisely replicated 1-D and 2-D scalar distributions through incremental training. Further reconstruction of 3-D temperature field only used 40 3-D CFD cases, resulting in the training and testing errors decreased to 7.94 × 10-4 and 1.55 × 10-3, respectively, approaching the level of the 2-D reconstruction, with the average error in temperature field predictions not exceeding 50 K. The generalization ability was validated using a separate test dataset with continuously changing excess air ratio and capacity ratio in wide ranges, including some extreme values, and the model successfully captured complex phenomena under unseen conditions.

Wind stress modification by offshore wind turbines: A numerical study of wave blocking impacts

Offshore wind energy, as a clean and renewable resource, offers numerous advantages over onshore wind energy due to higher wind speeds and greater turbine capacity. However, the inadequate representation of wave-atmosphere interaction within the marine-atmospheric boundary layer may constrain wind resource assessments and, consequently, the design and layout of offshore wind turbines. By using the third-generation spectral wave model WAVEWATCH III, high-resolution numerical experiments which are capable of resolving the wind turbine foundation have been conducted to explore the blocking impact of wind turbine foundation on downstream wind stress. The findings provided significant insights into the factors influencing this effect, including foundation diameter, sea state, water depth, and wave directional spreading. Specifically, higher model resolution enables a more detailed characterization of wind stress distribution behind wind turbines. Increasing the foundation diameter resulted in a reduction of downstream wind stress. Notably, changes in wind stress exhibit a strong dependence on the sea state. The use of double periodic boundary conditions for the simulation domain enables an approximate representation of the entire wind farm by using a single turbine. Model results indicate that after waves pass through 20 turbines, domain-averaged wind stress decreases by approximately 3%, a figure that increases to 6% after passing through 50 turbines. The findings suggest the need to explore to what extent the changes in wind stress can alter wind profiles and how to parameterize the blocking impact of turbine foundations in wave models. This could have significant implications for wind farm site selection and layout design.

Impact of Horizontal Model Resolution on Mixing and Dispersion in the Northeastern Gulf of Mexico

AbstractIn this paper, the importance of model horizontal resolution in mixing and dispersion is investigated by comparing two data‐assimilative high‐resolution simulations (4 and 1 km), one of which is submesoscale‐permitting. By employing both Eulerian and Lagrangian metrics, upper‐ocean differences between the mesoscale‐resolving and submesoscale‐permitting simulations are examined in the northeastern Gulf of Mexico, a region of high mesoscale and submesoscale activity. Mixing in both simulations is explored by conducting Lagrangian experiments to track the generation of Lagrangian coherent structures (LCSs) and their associated transport barriers. Finite‐time Lyapunov exponent (FTLE) fields show higher separation rates of fluid particles in the submesoscale‐permitting case, which indicate more vigorous mixing with differences being more pronounced in the shelf regions (depths ≤ 500 m). The extent of the mixing homogeneity is examined using probability density functions (PDFs) of FTLEs with results suggesting that mixing is heterogeneous in both simulations, but some homogeneity is exhibited in the submesoscale‐permitting case. The FTLE fields also indicate that chaotic advection dominates turbulent mixing in both simulations regardless of the horizontal resolution. In the submesoscale‐permitting experiment, however, smaller scale LCSs emerge as noise‐like filaments that suggest a larger turbulent mixing component than in the mesoscale‐resolving experiment. The impact of resolution is then explored by investigating the spread of oil particles at the location of the Deepwater Horizon oil spill.

Stability and reliability of regional cumulative impact mapping: A Canadian Pacific case study

Cumulative impact mapping is a commonly applied spatial representation of the impacts of human activities on the ocean. This spatial model has been applied at varying scales around the world, in part due to its ability to visually communicate complicated information in a simple way. The application of the model to decision-making processes requires an understanding of the reliability and stability of its outputs. This paper represents both an updated regional application in Pacific Canada and an evaluation of the tool over two iterations, 2015 and 2023. The regional application utilised higher model resolution and new and improved data inputs including 38 habitats and 46 activities across five sectors. High impact hotspots were found around major population centres and ports, as well as in fishing and shipping areas along the continental shelf. Commercial fishing, shipping, and climate change (sea surface temperature change) remained the major drivers of cumulative impacts in the region, and cumulative impacts per unit area continued to be highest in kelp and seagrass. Results suggest evidence of decreased impacts where improved protection for sponge reefs were implemented but show an overall increase in cumulative impacts for the region. Results showed consistency and reliability in the location of cumulative impact hotspots. Refinements in data quality and resolution of spatial data inputs contributed towards increasing the spatial precision of hot spot areas identified. Confidence in the cumulative impact mapping outputs and applications for marine spatial planning, marine protected area designation and management, research, and decision support are discussed.

Route-based Train Conflict Resolution Model Extended from Alternative Graph

Route-based Train Conflict Resolution Model Extended from Alternative Graph