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In response to the deficiencies in visible-near infrared spectral identification of coal gangue under different working conditions, this paper employs multiple algorithms to construct local and global recognition models and conducts analysis. Simulating five different working conditions in the laboratory, including different detection angles, illumination angles, detection distances, coal powder content, and moisture content. Each working condition is further divided into four levels. Collecting spectral data of coal and gangue samples. Constructing global and local datasets, which are respectively derived from all levels and single levels under certain working conditions. Training local and global models to identify samples based on machine learning algorithms such as Lightgbm and 1DCNN. The results of the experiment indicate that there are variations in the sample spectra and recognition accuracy based on different working conditions. Furthermore, the local model exhibits lower recognition accuracy and inadequate robustness for other level samples under the same working condition. The global model is more robust and practical, as it achieves higher or equal recognition accuracy for local data compared to the local model. Among the global models, Lightgbm has the best overall performance, with an average F1-score of 99.34% and 97.9% for local and global datasets, respectively. It also has fast training time of 0.75s and recognition time of 1 ms. The Lightgbm global model can accurately identify coal and gangue in various working conditions, making it a reliable solution. [ABSTRACT FROM AUTHOR]

This work presents a numerical analysis by zero-dimensional global model of the influence of electron temperature and concentration on production of OH and NO for helium plasma jet propagating in the atmosphere of humid air. The calculations are done for the constant electron temperatures (1–4 eV) and concentrations (1010 cm−3 to 1014 cm−3). The mole fractions of air and water vapor vary from 100 to 10,000 ppm. The presented analysis reveals that at low electron temperature and H2O contents, the dissociative electron attachment to O2 dominates over attachment to H2O in production of OH. At higher amount, H2O modifies the high-energy tail of electron distribution function and increases rate coefficients for electron impact processes. Dissociative electron attachment to H2O dominates in the production of OH at 1 eV and remains important at higher energies when processes with O(1D), O(1S), O2(1∆) produce OH. Impact dissociation of H2O dominates over the dissociative attachment at 3 and 4 eV. NO comes mainly from air effluent in the plasma and O + NO2 at 100 ppm of H2O. Above 2 eV, the conversion process between OH and NO dominates in NO production at higher amount of H2O. Regarding dependencies on electron concentration, at low electron temperatures, electron distribution function is affected only at 1014 cm−3. But in the case of higher temperature, electron concentration and water vapor have negligible influence. The best agreement with measured data is obtained for electron concentration 1010 cm−3 and at temperature of 2 eV for OH and 1012 cm−3 and 3 eV for NO.

GRIST (Global-Regional Integrated forecast SysTem), the kilometer-scale variable-resolution (VR) model, combines the virtues of both global and regional models. It can provide medium-term forecast products without lateral conditions while it is expected to reach a forecast level similar to that of high-precision regional models. To evaluate GRIST' s ability to simulate extreme weather events, this study uses the VR version of GRIST to conduct a hindcast experiment on the extremely heavy rainfall event that occurred in North China from July 29 to August 2, 2023. The simulation results are evaluated against satellite-gauge merged precipitation analysis (China Merged Precipitation Analysis, CMPA) and global reanalysis (the fifth generation of the European Center for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate, ERA5) data, and are also compared with five other operational numerical models (including global models, ECMWF and CMA-GFS, as well as regional models, CMA-MESO, CMA-SH, and CMA-BJ). Results indicate that both GRIST and five operational models can reproduce the occurrence of this heavy rainfall event at various degrees. From 08 BT 30 July to 08 BT 1 August, the period with the strongest precipitation during the event, the simulation performance of GRIST is optimal. The spatial correlation coefficient between GRIST and CMPA can reach up to 0.85, and the TS scores of precipitation at various intensities are at the levels of regional model forecasts. GRIST accurately simulated the large-scale circulation characteristics during this process, encompassing the location and extent of the Western Pacific Subtropical High, northward water vapor transport. Furthermore, it demonstrated a commendable capability in simulating the distribution and intensity of storm-relative helicity, a key indicator of the local circulation. The precise representation of circulation conditions at various scales by GRIST contributes significantly to its ability to characterize precipitation areas and the evolution of precipitation.

Based on recent interest and on the importance of the ongoing climate change catastrophe, this article provides the basics of global carbon cycle modelling as required for the assessment of the degree of carbon neutrality of biomass energy, and its underlying dynamics. It is aimed at clarifying the question "Are biomass fuels carbon neutral?". The "Combined Energy and Biosphere Model" (CEBM) computes annual carbon flows including growth and decay of plants on 2.5 × 2.5° grid elements of the continents' surface and offers detailed results on the changes of after implementation of large-scale biomass energy strategies worldwide. The main (and possibly unexpected) effect is the long-term depletion of the soil organic compartment after extraction of biomass fuels. When comparing CEBM model runs using (i) biomass energy sources and (ii) carbon-free energy sources (such as solar or wind), it becomes quantitatively clear already on the theoretical level (i.e., even without taking into account efficiency losses) that biomass is only "half as carbon neutral" as ideally assumed, to express a rule of thumb—mainly because of soil carbon depletion. Still, biomass energy will play an important role when fighting global warming, even if efforts to lower energy demand are preferable as a fundamental strategy. [ABSTRACT FROM AUTHOR]

Electron cyclotron resonance ion source (ECRIS) as the front-end for the neutral beam injection (NBI) system has production potential of hydrogen ion beam in tokamaks. In this article, two methods are hired to evaluate the plasma ion fractions: H + , H 2 + and H 3 + with respect to the ECRIS operating parameters. The methods are matured by utilizing 28 important volume and surface collisions processes. We encrypted a global 0D numerical model (GM) based on solving the nonlinear equations of plasma species as the first method. Next, a 3D plasma simulation (PS) is applied through the finite element method (FEM) by COMSOL Multiphysics. Then, the results are compared to the experimental data. • Two methods have been compared for calculating plasma characteristics. • 0D global model is based on solving the nonlinear population balance equations. • 3D plasma simulation by applying COMSOL Multiphysics is based on fluid model. • Output results of the methods are in a good agreement with the experimental data. [ABSTRACT FROM AUTHOR]

We investigate the representation of individual supercells and intriguing tornado‐like vortices in a simplified, locally refined global atmosphere model. The model, featuring grid stretching, can locally enhance the model resolution and reach cloud‐resolving scales with modest computational resources. Given a conditionally unstable sheared environment, the model can simulate supercells realistically, with a near‐ground vortex and funnel cloud at the center of a rotating updraft reminiscent of a tornado. An analysis of the Eulerian vertical vorticity budget suggests that the updraft core of the supercell tilts horizontal vorticity into the tornado‐like vortex, which is then amplified through vertical stretching by the updraft. Results suggest that the simulated vortex is dynamically similar to observed tornadoes, as well as those simulated in modeling studies at much higher horizontal resolution. Lastly, we discuss the prospects for the study of cross‐scale interactions involving supercells. Plain Language Summary: We use a simplified global model to study individual supercells and intriguing cloudy rotating winds that behave like tornadoes. This model uses grid‐stretching techniques, making it a computationally efficient tool to study supercells on a real‐size Earth. Unlike most numerical models of tornadoes which simulate scales of a few tens of meters, our model can realistically simulate supercells and cloudy tornado‐like rotating winds even at kilometer scales, which appears unprecedented in the literature. We find that the physics behind the rotating winds is consistent with previous studies, including observations of tornado formation and simulations at much higher resolution. The findings of this study open the door to a better understanding of complex interaction between supercells, tornadoes, and their environment. Key Points: The FV3 dynamical core with simple microphysics can simulate individual supercells and cloudy tornado‐like vortices at kilometer scalesA stretched cubed‐sphere grid is used to economically reach cloud‐resolving scales locally on a real‐size EarthThe dynamics of the simulated tornado‐like vortices is consistent with previous studies on tornadogenesis [ABSTRACT FROM AUTHOR]

The potential scope of superparameterization (SP) was extended to higher resolutions of the global climate model (GCM) component by devising a technique called blockwise coupling. In this method, a horizontal average of multiple GCM columns, instead of one, is coupled to a cloud‐resolving model (CRM) domain. This enables SP‐GCMs to reduce the computational cost drastically, enabling higher‐resolution GCMs to be superparameterized. A blockwise‐coupled SP‐GCM called SP‐MIROC was implemented by coupling the climate model MIROC6 to the CRM SCALE‐RM. The 4 × 4‐bundled SP‐MIROC successfully reproduced horizontal patterns and frequency distributions of precipitation and realistic amplitudes of equatorial Kelvin waves (EKWs), which were underestimated in the standard MIROC6. As discussed in Yamazaki and Miura (2024b, https://doi.org/10.1029/2023MS003837) of this study, the amplitude boost of EKWs was enabled by a top‐heavy heating in SP‐MIROC. Comparison of power spectra between the 4 × 4‐bundled SP‐MIROC and nonbundled SP‐MIROC indicated that the effective resolution of dynamic variables was not degraded by the blockwise technique. Rather, spectra in the 4 × 4‐bundled SP‐MIROC were more realistic than those in the nonbundled SP‐MIROC. Although the 4 × 4‐bundling limits convective coupling in the smallest GCM scale, it could offer the best match of resolutions between the GCM‐handled dynamics and SP‐derived physics because the effective resolution of the dynamics is lower than the nominal grid spacing. Plain Language Summary: Superparameterization is a technique to explicitly simulate subgrid clouds in low‐resolution global climate models (GCMs) by coupling small domains of a high‐resolution cloud‐resolving model (CRM). This study expands the superparameterization technique by proposing and verifying blockwise coupling, in which a CRM domain is coupled to an average of multiple GCM columns; in contrast, the existing superparameterized (SP) models employ one‐to‐one coupling between a CRM and a GCM column. We implemented a SP‐GCM by coupling the climate model MIROC6 and the SCALE‐RM CRM with 4 × 4‐to‐one blockwise coupling. Multiple benefits in existing SP‐GCMs are reproduced in the simulation results of the blockwise‐coupled SP‐MIROC. Furthermore, 4 × 4‐bundled SP‐MIROC outperformed the one‐to‐one SP‐MIROC in terms of reproducing realistic zonal spectra. Blockwise coupling will drastically reduce computational costs, making superparameterization in higher‐resolution GCMs affordable. Key Points: A superparameterized version of the climate model MIROC6 named superparameterized (SP)‐MIROC was developedComputational cost is reduced by coupling a cloud‐resolving model domain to a block of multiple global climate model columns, instead of oneBlockwise‐coupled SP‐MIROC reproduced most benefits of SP without losing the effective resolution of dynamic variables [ABSTRACT FROM AUTHOR]

Abstract High-resolution regional model simulation of CO2 may be more beneficial to reduce the uncertainty in estimation of CO2 source and sink via inverse modeling. However, the study of atmospheric CO2 transport with regional models is rare over India. Here, weather research and forecasting chemistry model adjusted for CO2 (WRF-CO2) is used for simulating vertical profile of CO2 and its assessment is performed over Delhi, India (27.4–28.6° N and 77–96° E) by comparing aircraft observations (CONTRAIL) and a global model (ACTM) data. During August and September, the positive vertical gradient (~ 13.4 ppm) within ~ 2.5 km height is observed due to strong CO2 uptake by newly growing vegetation. A similar pattern (~ 4 ppm) is noticed in February due to photosynthesis by newly growing winter crops. The WRF-CO2 does not show such steep increasing slope (capture up to 5%) during August and September but same for February is estimated ~ 1.7 ppm. Generally, CO2 is quite well mixed between ~ 2.5 and ~ 8 km height above ground which is well simulated by the WRF-CO2 model. During stubble burning period of 2010, the highest gradient within 2.5 km height above ground was recorded in October (− 9.3 ppm), followed by November (− 7.6 ppm). The WRF-CO2 and ACTM models partially capture these gradients (October − 3.3 and − 2.7 ppm and November − 3.8 and − 4.3 ppm respectively). A study of the seasonal variability of CO2 indicates seasonal amplitudes decrease with increasing height (amplitude is ~ 21 ppm at the near ground and ~ 6 ppm at 6–8 km altitude bin). Correlation coefficients (CC) between the WRF-CO2 model and observation are noted to be greater than 0.59 for all the altitude bins. In contrast to simulated fossil CO2, the biospheric CO2 is in phase with observed seasonality, having about 80% at the lowest level and gradually declines with height due to mixing processes, reaching around 60% at the highest level. The model simulation reveals that meteorology plays a significant role of the horizontal and vertical gradient of CO2 over the region.

Abstract Background Fertility preservation treatment is increasingly essential for patients with apical endometrial hyperplasia (AEH) and early endometrial cancer (EEC) worldwide. Complete regression (CR) is the main endpoint of this treatment. Accurately predicting CR and implementing appropriate interventions during treatment are crucial for these patients. Methods We conducted a retrospective study involving 193 patients diagnosed with atypical AEH or EEC, enrolled from January 2012 to March 2022 at our center. We evaluated 24 clinical parameters as candidate predictors and employed LASSO regression to develop a prediction model for CR. Subsequently, a nomogram was constructed to predict CR after the treatment. We evaluated the performance of the nomogram using receiver operator characteristic (ROC) curve and decision curve analysis (DCA) to assess its predictive accuracy. Additionally, we employed cumulative curves to determine the CR rate among patients. Results Out of the 193 patients, 173 achieved CR after undergoing fertility preservation treatment. We categorized features with similar properties and provided a list of formulas based on their coefficients. The final model, named GLOBAL (including basic information, characteristics, blood pressure, glucose metabolism, lipid metabolism, immunohistochemistry, histological type, and medication), comprised eight variables identified using LASSO regression. A nomogram incorporating these eight risk factors was developed to predict CR. The GLOBAL model exhibited an AUC of 0.907 (95% CI 0.828–0.969). Calibration plots demonstrated a favorable agreement between the predicted probability by the GLOBAL model and actual observations in the cohort. The cumulative curve analysis revealed varying cumulative CR rates among patients in the eight subgroups. Categorized analysis demonstrated significant diversity in the effects of the GLOBAL model on CR among patients with different total points (p

High-resolution regional model simulation of CO2 may be more beneficial to reduce the uncertainty in estimation of CO2 source and sink via inverse modeling. However, the study of atmospheric CO2 transport with regional models is rare over India. Here, weather research and forecasting chemistry model adjusted for CO2 (WRF-CO2) is used for simulating vertical profile of CO2 and its assessment is performed over Delhi, India (27.4–28.6° N and 77–96° E) by comparing aircraft observations (CONTRAIL) and a global model (ACTM) data. During August and September, the positive vertical gradient (~ 13.4 ppm) within ~ 2.5 km height is observed due to strong CO2 uptake by newly growing vegetation. A similar pattern (~ 4 ppm) is noticed in February due to photosynthesis by newly growing winter crops. The WRF-CO2 does not show such steep increasing slope (capture up to 5%) during August and September but same for February is estimated ~ 1.7 ppm. Generally, CO2 is quite well mixed between ~ 2.5 and ~ 8 km height above ground which is well simulated by the WRF-CO2 model. During stubble burning period of 2010, the highest gradient within 2.5 km height above ground was recorded in October (− 9.3 ppm), followed by November (− 7.6 ppm). The WRF-CO2 and ACTM models partially capture these gradients (October − 3.3 and − 2.7 ppm and November − 3.8 and − 4.3 ppm respectively). A study of the seasonal variability of CO2 indicates seasonal amplitudes decrease with increasing height (amplitude is ~ 21 ppm at the near ground and ~ 6 ppm at 6–8 km altitude bin). Correlation coefficients (CC) between the WRF-CO2 model and observation are noted to be greater than 0.59 for all the altitude bins. In contrast to simulated fossil CO2, the biospheric CO2 is in phase with observed seasonality, having about 80% at the lowest level and gradually declines with height due to mixing processes, reaching around 60% at the highest level. The model simulation reveals that meteorology plays a significant role of the horizontal and vertical gradient of CO2 over the region. [ABSTRACT FROM AUTHOR]

Background: Fertility preservation treatment is increasingly essential for patients with apical endometrial hyperplasia (AEH) and early endometrial cancer (EEC) worldwide. Complete regression (CR) is the main endpoint of this treatment. Accurately predicting CR and implementing appropriate interventions during treatment are crucial for these patients. Methods: We conducted a retrospective study involving 193 patients diagnosed with atypical AEH or EEC, enrolled from January 2012 to March 2022 at our center. We evaluated 24 clinical parameters as candidate predictors and employed LASSO regression to develop a prediction model for CR. Subsequently, a nomogram was constructed to predict CR after the treatment. We evaluated the performance of the nomogram using receiver operator characteristic (ROC) curve and decision curve analysis (DCA) to assess its predictive accuracy. Additionally, we employed cumulative curves to determine the CR rate among patients. Results: Out of the 193 patients, 173 achieved CR after undergoing fertility preservation treatment. We categorized features with similar properties and provided a list of formulas based on their coefficients. The final model, named GLOBAL (including basic information, characteristics, blood pressure, glucose metabolism, lipid metabolism, immunohistochemistry, histological type, and medication), comprised eight variables identified using LASSO regression. A nomogram incorporating these eight risk factors was developed to predict CR. The GLOBAL model exhibited an AUC of 0.907 (95% CI 0.828–0.969). Calibration plots demonstrated a favorable agreement between the predicted probability by the GLOBAL model and actual observations in the cohort. The cumulative curve analysis revealed varying cumulative CR rates among patients in the eight subgroups. Categorized analysis demonstrated significant diversity in the effects of the GLOBAL model on CR among patients with different total points (p < 0.05). Conclusion: We have developed and validated a model that significantly enhances the predictive accuracy of CR in AEH and EEC patients seeking fertility preservation treatment. [ABSTRACT FROM AUTHOR]

Abstract We investigate the representation of individual supercells and intriguing tornado‐like vortices in a simplified, locally refined global atmosphere model. The model, featuring grid stretching, can locally enhance the model resolution and reach cloud‐resolving scales with modest computational resources. Given a conditionally unstable sheared environment, the model can simulate supercells realistically, with a near‐ground vortex and funnel cloud at the center of a rotating updraft reminiscent of a tornado. An analysis of the Eulerian vertical vorticity budget suggests that the updraft core of the supercell tilts horizontal vorticity into the tornado‐like vortex, which is then amplified through vertical stretching by the updraft. Results suggest that the simulated vortex is dynamically similar to observed tornadoes, as well as those simulated in modeling studies at much higher horizontal resolution. Lastly, we discuss the prospects for the study of cross‐scale interactions involving supercells.

Abstract The potential scope of superparameterization (SP) was extended to higher resolutions of the global climate model (GCM) component by devising a technique called blockwise coupling. In this method, a horizontal average of multiple GCM columns, instead of one, is coupled to a cloud‐resolving model (CRM) domain. This enables SP‐GCMs to reduce the computational cost drastically, enabling higher‐resolution GCMs to be superparameterized. A blockwise‐coupled SP‐GCM called SP‐MIROC was implemented by coupling the climate model MIROC6 to the CRM SCALE‐RM. The 4 × 4‐bundled SP‐MIROC successfully reproduced horizontal patterns and frequency distributions of precipitation and realistic amplitudes of equatorial Kelvin waves (EKWs), which were underestimated in the standard MIROC6. As discussed in Yamazaki and Miura (2024b, https://doi.org/10.1029/2023MS003837) of this study, the amplitude boost of EKWs was enabled by a top‐heavy heating in SP‐MIROC. Comparison of power spectra between the 4 × 4‐bundled SP‐MIROC and nonbundled SP‐MIROC indicated that the effective resolution of dynamic variables was not degraded by the blockwise technique. Rather, spectra in the 4 × 4‐bundled SP‐MIROC were more realistic than those in the nonbundled SP‐MIROC. Although the 4 × 4‐bundling limits convective coupling in the smallest GCM scale, it could offer the best match of resolutions between the GCM‐handled dynamics and SP‐derived physics because the effective resolution of the dynamics is lower than the nominal grid spacing.

Within large and growing human communities where interactions occur, trust is a key factor to consider. Computational trust models have then been widely studied since the 2000s targeting items ratings (e.g. in e-commerce) or M2M (e.g. in IoT network). Among these models, EigenTrust is today one of the most popular and studied ones. It provides a global reputation calculation and is efficient in distributed networks, but not fully satisfactory for human interactions. On the opposite, the Bi-lattice model is well suited for human networks interactions such as solidarity networks and/or human services exchange networks but is limited to local trust results. In this paper, we propose a new aggregator that extends the Bi-lattice model to enable a global reputation calculation. This new aggregator discovers the trust links from the member whose score is to be evaluated to every other members he is connected to on the trust network. It then computes the global reputation of this member based on these trust links. Furthermore, it enables a lightweight approach, as it is able to compute a global reputation based only on a partial knowledge of the trust network. Throughout the paper, the proposed aggregator is presented, evaluated and compared to Eigentrust to show its effectiveness.

An improved method for noise reduction from a time series obtained from a chaotic system is presented. This improved method is based on a noise reduction technique presented by Schreiber and Grassberger that has good performance and less complexity compared to other noise reduction methods from chaotic data. Here a global model created using a neural network has been used as a prediction model for chaotic time series. This global prediction model performs better compared to the local prediction model used in the original method. The improved method also takes advantage of the singular spectrum analysis reconstruction technique. Both of these improvements led to a more accurate noise reduction method while preserving the unique properties of the original. The improved method is applied to a time series obtained from the chaotic state of Lorenz equations that is polluted with Gaussian noise. The final results show a 33 percent reduction in mean absolute error values compared to the original method. Also, the error of calculating the correlation dimension from the data has been reduced to 2 percent after applying the improved method. [ABSTRACT FROM AUTHOR]

Abstract In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the number of monitored clients will increase with the ongoing smart meter rollout, the amount of data per client will always be limited. We evaluate whether a Transformer load forecasting model benefits from a transfer learning strategy, where a global univariate model is trained on the load time series from multiple clients. In experiments with two datasets containing load time series from several hundred clients, we find that the global training strategy is superior to the multivariate and local training strategies used in related work. On average, the global training strategy results in 21.8% and 12.8% lower forecasting errors than the two other strategies, measured across forecasting horizons from one day to one month into the future. A comparison to linear models, multi-layer perceptrons and LSTMs shows that Transformers are effective for load forecasting when they are trained with the global training strategy.

Based on recent interest and on the importance of the ongoing climate change catastrophe, this article provides the basics of global carbon cycle modelling as required for the assessment of the degree of carbon neutrality of biomass energy, and its underlying dynamics. It is aimed at clarifying the question “Are biomass fuels carbon neutral?”. The “Combined Energy and Biosphere Model” (CEBM) computes annual carbon flows including growth and decay of plants on 2.5 × 2.5° grid elements of the continents’ surface and offers detailed results on the changes of after implementation of large-scale biomass energy strategies worldwide. The main (and possibly unexpected) effect is the long-term depletion of the soil organic compartment after extraction of biomass fuels. When comparing CEBM model runs using (i) biomass energy sources and (ii) carbon-free energy sources (such as solar or wind), it becomes quantitatively clear already on the theoretical level (i.e., even without taking into account efficiency losses) that biomass is only “half as carbon neutral” as ideally assumed, to express a rule of thumb—mainly because of soil carbon depletion. Still, biomass energy will play an important role when fighting global warming, even if efforts to lower energy demand are preferable as a fundamental strategy.

In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the number of monitored clients will increase with the ongoing smart meter rollout, the amount of data per client will always be limited. We evaluate whether a Transformer load forecasting model benefits from a transfer learning strategy, where a global univariate model is trained on the load time series from multiple clients. In experiments with two datasets containing load time series from several hundred clients, we find that the global training strategy is superior to the multivariate and local training strategies used in related work. On average, the global training strategy results in 21.8% and 12.8% lower forecasting errors than the two other strategies, measured across forecasting horizons from one day to one month into the future. A comparison to linear models, multi-layer perceptrons and LSTMs shows that Transformers are effective for load forecasting when they are trained with the global training strategy. [ABSTRACT FROM AUTHOR]

Using Magnetospheric Multiscale mission (MMS) orbits in the Earth's magnetotail from 2017 to 2020, plasma conditions and the 3D spatial structure of inner‐magnetotail plasma environments (with a focus on the plasma sheet (PS)) are studied with different approaches. Threshold conditions for distinguishing the PS, PS boundary layers, and lobes are derived from the statistical properties of background plasma parameters. Our results support previous studies that employed similar methods using Cluster data. However, stronger currents are observed in both the lobes and PS, likely due to the smaller spacecraft separation (≲70 km) that can resolve thin electron‐scale currents. Threshold conditions are used together with magnetic field and electric field measurements to image the spatial structure of the PS. Results are in good agreement with a global neutral sheet model based on solar wind conditions and magnetospheric configurations. Furthermore, the Earth's dipole tilts toward the Sun around June solstice, which warps the magnetotail as much as ∼2–4 RE in Z geocentric solar magnetospheric. This warping effect is relaxed toward September equinox. Consequently, as MMS travels through the magnetotail from dawn to dusk during this period, there is an apparent dawn‐dusk asymmetry in plasma conditions between June and September. Kink‐like flapping waves and interplanetary magnetic field twisting are other mesoscale processes attributed with a few RE of flaring near the flanks. These findings reveal important insights into the mesoscale structure and dynamics of the magnetotail. Plain Language Summary: Data from 4 years of observations by NASA's MMS mission are used to statistically identify distinctive regions within the Earth's magnetospheric tail. This study reveals insights into the spatial structure of this "magnetotail" and seasonal variations attributed with changes in the Earth's magnetic field configurations, particularly those of the orientation of the Earth's dipole. Our results agree with reported findings from ESA's Cluster mission. However, certain aspects unique to MMS lead to some improved measurements and features relating to MMS orbital design. The presented results are highly beneficial to future large statistical studies with MMS data. Key Points: Inner‐magnetotail environments are statistically identified with background plasma conditions and their global 3D structure is studiedWarping effects attributed to changes in the Earth's dipole tilt angle leads to an apparent dawn‐dusk asymmetry during the summer monthsWe utilize a large volume of Magnetospheric Multiscale mission data with partial plasma moments calculated from low‐energy plasma and energetic particle instruments [ABSTRACT FROM AUTHOR]

Plasma processes enhance the high-quality, semiconductor fabrication employed in large-scale industries. A crucial element in this process are the many gases that generate different reactive species at low temperatures. Capacitive plasma discharge radio frequency CCPs play a major role in semiconductor scale fabrication. The analysis of nonlinear dynamics in CCPs are complicated even under simple approaches. Therefore, we study self consistent collision fluid model, particle in cell simulation PIC, step approximation and finally the global model to find the accurate solution of merging plasma sheath -bulk region. For this purpose we study the self consistent collisional fluid model to find the accurate charge–voltage distribution V(Q) which controls the nonlinear dynamics of CCPs. The results against the PIC simulations and the more elaborate model step approximation is accomplished with higher accuracy. Consequently, the cubic polynomial formula V(Q) are applied in the global model. Accurate analytical global sheath-bulk calculations of the higher harmonic effect-exhibiting average power distributions, bulk potentials, and currents are obtained. This study provides an effective solution of collision regime for any arbitrary plasma reactor designs, including single-frequency and double frequency CCPs. Moreover, we used the argon gas as a good example in our study for a good ion etching. Finally, we can assist in achieving effective results that are consistent with experimental data and in large-scale applications in the semiconductor sector.

In recent years, the increasing demand for simple and low-cost propulsion for small satellites has given rise to a growing interest in low-power cathode-less plasma thrusters. Plasma is produced within a source tube using radiofrequency (RF) ionisation, enhanced by a magnetic field which also accelerates the discharge via the magnetic nozzle effect. A key advantage of cathode-less thrusters is that they can operate on a wider range of propellants, more easily stored, and often inexpensive (e.g., iodine) compared to traditional xenon. Despite simple hardware, plasma dynamics in this kind of device are highly complex. This work presents a numerical suite developed for cathode-less plasma thruster design and analysis. First, a 0D Global Source Model provides the plasma production in the source. A fully kinetic Particle-in-Cell model (2D and 3D) then handles plasma expansion in the magnetic nozzle. The capabilities of the suite are presented by-way-of investigation into the behaviour of alternative propellants iodine and krypton within the 50 and 150 W class REGULUS thrusters. The performance of each propellant is assessed in terms of plasma source and magnetic nozzle efficiencies. The results are then benchmarked against experimental measurements, obtaining agreement of < 30%. At absorbed powers < 20 W, iodine exhibits comparable performance to xenon but produces about 50% less thrust as the power is increased above 40 W. This occurs because of the molecular reaction processes seen by iodine, and associated inelastic energy thresholds which result in higher collisional energy losses. The high ionisation energy of krypton results in a low source efficiency. Instead, in the magnetic nozzle, krypton was found to perform best, facilitating the most thermal-to-kinetic conversion. But, the final thrust is < 20% of xenon; instead iodine performs within 43% of the thrust provided by xenon. Finally, iodine contamination of spacecraft surfaces is found to be comparable to estimates found in other electric propulsion devices. • Multiscale numerical model for cathode-less plasma thruster design and characterisation. • 0D Global Source Model for inductive RF plasma production. • Fully kinetic Particle-in-Cell model for the magnetic nozzle and expansion cone. • Iodine performs within 43% of the thrust provided by xenon. • Experimental agreement to REGULUS-50 and REGULUS-150 thrusters within 30%. [ABSTRACT FROM AUTHOR]

While climate models are an invaluable tool for increasing our understanding and therefore, the predictability of the Earth's system for decades, their increase in complexity and resolution has put a considerable, growing strain on the computational resources of research centers and institutions worldwide. The statistics community has a long history of developing stochastic models as a means to save computational time, but the emergence of storage as an additional cost for climate investigations has prompted a reformulation of the aim of statistical models in model-based environmental science. Can stochastic approximations be useful as a mechanism for saving both computational time and storage? We focus on a collection of simulations from a climate model and propose several statistical models of increasing complexity. By analyzing and discussing the associated costs for each model, we demonstrate how computation and storage are closely intertwined, and how a statistical model of increasing complexity is justified only to the extent that information at a fine spatial and/or temporal scale is sought to be preserved.Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

The ionization of sputtered species in high power impulse magnetron sputtering of titanium, chromium, and aluminum targets is analyzed using Abel-inverted spectroscopic imaging to locate the position of ionization. From the spatial emission of neutrals, it is deduced that most of the sputtered titanium particles become ionized within 0.5 mm distance from the target, whereas sputtered aluminum or chromium can travel much further through the discharge before ionization occurs. Probe measurements reveal the reason for this difference to be the unusually high electron temperature of around 4.5 eV for titanium compared to 2.6 eV and 1.5 eV for aluminum and chromium as the target material, respectively. These probe measurements are then compared to a global model derived from the ionization region model. Excellent agreement between model and measurements can be reached, but only if the transport physics for the confinement of the species is adjusted. Using the model, the difference between the three discharges can be traced back to be mostly caused by the sputter yield. Thus, we propose that ionization in discharges with low-yield materials should generally be expected to occur closer to the target surface, leading the ions to be affected more strongly by the electric field across the magnetic trap region, resulting in a more severe deposition rate loss compared to high-yield materials. [ABSTRACT FROM AUTHOR]

This study investigates the preliminary propulsive performances of a cathode-less plasma thruster with air as its propellant. The analysis is carried out through a global model and simulates a thruster over a power range of 0 to 50 W. The developed code considers a set of 177 chemical reactions involving 8 different species and includes empirical equations to account for electronegative effects. The analysis presents the steady-state values of species densities at 10 W, 30 W, and 50 W to gain insights into the key characteristics of plasma dynamics. Moreover, the study estimates the thrust and specific impulse and compares the results to data from models that employ xenon and iodine, aiming to understand the performances of air in low-power thrusters. Lastly, the study examines the effects of varying air inflow concentration on the chemistry, analyzing three different orbit altitudes (i.e., 200, 300, and 400 km). [ABSTRACT FROM AUTHOR]

Hungarian A cikk a kormányzás történelmileg változó intézményrendszerének evolúcióját elemezi. Megmutatja, hogy a kicsiny, egalitárius törzsek mindenki számára nyitott döntéshozatala – a közösség méreteinek, az egyenlőtlenségnek és a szervezet komplexitásának növekedésével– szükségszerűen átalakul az államok hierarchikus struktúrába szervezett centralizált kormányzásává. A szuverén államok alkotta nemzetközi rendszer az elmúlt évtizedekben alapvető változáson ment keresztül. Fokozatosan komplex és szorosan csatolt rendszerré vált. Ennek következtében a nemzetközi viszonyok és kapcsolatok rendezésére szolgáló intézmények egyre kevésbé voltak képesek a zavarokat enyhítésére. Ez a globális rendszer súlyosbodó válságaighoz vezetett. A problémák forrása a világ állapotából fakadó kihívásokhoz képest a rendelkezésre álló kormányzási eszközök elégtelenek. A cikk felrajzolja a világunkra ma jellemző un. policentrikus döntési rendszer eredetét. Megállapítja, hogy a globális kormányzás megalapozható, a világ hosszútávú fejlődését felrajzoló globális modellel. Egy ilyen modell alkalmas lehet, hogy iránymutatásával rávezesse és rávegye az országokat, a globális vállalatokat és a globális közlegelők döntéshozóit az egész emberiség érdekeinek követésére. English The article analyses the evolution of the historically changing institutional system of governance. It shows how the open-for-all decision-making of small egalitarian tribes necessarily transforms into centralised governance of states, organised in hierarchical structures as community size, inequality and organisational complexity increase. The international system of sovereign states has undergone fundamental changes in the recent decades. It gradually became a complex and tightly coupled system. As a consequence, the institutions for managing international relations and connections have been less and less able to mitigate the disturbances. This has led to worsening crises in the global system. The source of these problems: the available tools of governance are inadequate to the challenges posed by the state of the world. The article traces the origins of the so-called polycentric decision-making system that characterises our world today. It concludes that global governance can be based upon a global model that maps the long-term development of the world. Such a model can be used to guide and persuade countries, global corporations and global public decision-makers to pursue the interests of all humanity.

The dynamics of COVID-19 virus were investigated in the literature via mathematical models. These models take into account the action of the suspected-exposed-infected-recovered people (SEIR). Also, among them, those which account for quarantined, social distancing functions or health isolation, were presented. In the absence of effective vaccines or therapies, prevention and treatment strategies for COVID-19 infections can not issue to non-epidemic state. Over the world, vaccination against the virus is set on. This motivated us to develop a model for inspecting if this treatment will issue to non endemic state. To this end, a global continuum model for the dynamics of this virus in the presence of vaccine and stimulated immunity is constructed. The present model deals with EIR - deceased individuals (EIRD) together with action of the health isolation and travelers (HIT). Which is described by nonlinear dynamical system (NLDS). Our aim here is to reduce the problem of solving this system to the case of solving LDS. This is carried by introducing the unified method (UM) via an approach present by the authors. By the UM, the solutions of a NLDS are recast to solutions of LDS via auxiliary equations. Numerical results of the exact solutions are evaluated, with initial data for the EIRD together with the number of vaccinated people. Real data are taken from Egypt (can be from elsewhere) at the end of the first wave, and they are considered as the initial conditions. These results are compared with a previous work by the authors in the absence of vaccination. The results of exposed, infected, recovered and deceased people are computed. It is found that the number of infected people decays to zero asymptotically, while, the number of infected people decays to an asymptotic value. This is in contrast to the results found previously in the case of absence of vaccination, where, these numbers grow monotonically. This is completely new. It is shown that locking-down has a remarkable effect in diminishing the number of infected people. The region of initial conditions for I-E people, that guarantee non-epidemic, non-endemic states, is determined via initial states control analysis. A software tool, based on this model, for simplifying the utilization of various data of different countries is developed. It is worth to mention that, the exact solutions of nonlinear dynamical equations, found here, are novel.

Plasma processes enhance the high-quality, semiconductor fabrication employed in large-scale industries. A crucial element in this process are the many gases that generate different reactive species at low temperatures. Capacitive plasma discharge radio frequency CCPs play a major role in semiconductor scale fabrication. The analysis of nonlinear dynamics in CCPs are complicated even under simple approaches. Therefore, we study self consistent collision fluid model, particle in cell simulation PIC, step approximation and finally the global model to find the accurate solution of merging plasma sheath -bulk region. For this purpose we study the self consistent collisional fluid model to find the accurate charge–voltage distribution V(Q) which controls the nonlinear dynamics of CCPs. The results against the PIC simulations and the more elaborate model step approximation is accomplished with higher accuracy. Consequently, the cubic polynomial formula V(Q) are applied in the global model. Accurate analytical global sheath-bulk calculations of the higher harmonic effect-exhibiting average power distributions, bulk potentials, and currents are obtained. This study provides an effective solution of collision regime for any arbitrary plasma reactor designs, including single-frequency and double frequency CCPs. Moreover, we used the argon gas as a good example in our study for a good ion etching. Finally, we can assist in achieving effective results that are consistent with experimental data and in large-scale applications in the semiconductor sector. [ABSTRACT FROM AUTHOR]

The track forecasts of tropical cyclones (TC) in the western North Pacific (WNP) basin during 2021 typhoon season with five global models and four regional models are evaluated here. The results show that the average direct position errors (DPEs) of the global and regional models are approximately 80, 150, 200, 300, and 400 km at 24 h, 48 h, 72 h, 96 h, and 120 h lead-times, respectively. The European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) achieved the best track forecast performance at each lead among the five global models. Among the four regional models, The China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) attained the smallest DPEs within a 72 h lead, while The Hurricane Weather Research and Forecasting (HWRF) achieved the best track forecast performance at 96 h and 120 h leads. Most of the models produced an obvious westward systematic bias on track forecast from a 24 h to a 120 h lead. Further correlation and cluster analyses indicate that initial TC intensity and size and environmental steering flow can be regarded as good predictors for TC DPEs. TCs with a stronger initial intensity, a bigger initial size, and a larger environmental steering flow in general attain a smaller DPE, and the improvements may go up to 36% at short lead-time. [ABSTRACT FROM AUTHOR]

This study investigates the effects of the assumption on the types of air-mass conservation prescribed in numerical models. First, predictions of the July 2021 ("21.7") Henan extreme rainfall event from the Integrated Forecast System (IFS) at ECMWF were compared with those from the Yin-He Global Spectral Model (YHGSM), which is a global spectral model with total air-mass conservation (TMC) and dry air-mass conservation (DMC) options. Then, a sensitivity test between simulations from the YHGSM adopting TMC and DMC was conducted. The results show that both the IFS and YHGSM predicted relatively well the 24-h rainfall amount less than 100 mm day−1 on 20 and 21 July 2021 at lead times of 84, 60, and 36 h. For heavy precipitation exceeding 100 mm day−1, however, both models obviously underestimated the daily rainfall amount on 20 July 2021, but the YHGSM produced more precise and stable precipitation forecasts on these two days than the IFS, especially the maximum 24-h precipitation amount, with better consistency at lead times of 84, 60, and 36 h. These differences are further examined in the sensitivity test. Predictions from the YHGSM with DMC show rainfall distributions and daily rainfall amounts closer to the observations at longer lead times. It is inferred that considering sources or sinks of total water in dynamical cores with DMC may have positive feedback for the precise prediction of condensates. For extreme rainfall events, the high local loss of total water may have caused a loss of the atmospheric mass, leading to an additional decrease in surface pressure. Subsequently, the unbalanced pressure gradient force enhances the cyclonic rotation of surface wind and strengthens convergence in the lower troposphere, which in turn further strengthens the vertical velocity, circularly contributing to the enhanced precipitation if the water vapor condition is favorable. [ABSTRACT FROM AUTHOR]

A global model (GM) assumes ion energy ( $\varepsilon $ ) on the electrode equals the time-averaged sheath voltage ( ${\left\langle {V}_{{\rm{sh}}}\left(t\right)\right\rangle }_{t}$ ). However, using particle-in-cell simulation, we found that $\varepsilon $ differs from ${\left\langle {V}_{{\rm{sh}}}\left(t\right)\right\rangle }_{t}.$ We propose a unified global model (UGM) that calculates $\varepsilon $ and collisional energy losses of ions by employing plasma circuit and sheath models, accompanied by a voltage and current sensor. We compared the results of the UGM with the experimental measurements and the results revealed that UGM is closer to the experiment than GM. UGM shows a linear relationship with the experiment, indicating that the UGM is applicable for plasma monitoring.

This work reports on the (zero-dimensional) global model study of argon plasma chemistry for a cylindrical thruster based on inductively coupled plasma (ICP) whose output has a system of two grids polarized with each other with direct current potential. The global model developed is based on particle and energy balance equations, where the latter considers both charged and neutral species. Thus, the model allows the determination of the neutral gas temperature. Finally, this study also investigated the role of excited species in plasma chemistry especially in the ions production and its implications for propulsion parameters, such as thrust. For this, the study was carried out in two different scenarios: (1) one taking into account the metastable species Arr and Arp (multi-step ionization), and (2) the other without these species (single-step ionization). Results indicates a distinct behavior of electron temperature with radiofrequency (RF) power for the investigated cases. On the other hand, the gas temperature is almost the same for investigated power range of up to 900 W. Concern propulsion analysis, a thrust of 40 mN at 450 W was verified for case (1), which represents a remarkable thrust value for electric thrusters.

The subject of the article is a variant of an efficient algorithm for synthesizing a dual discrete model and controller for tracking a given trajectory of a dynamic nonlinear, nonstationary black box object, using standard procedures for diagonalizing the state matrix, which makes it possible to simplify obtaining control values in numerical form and reduce the number of calculations. The current article presents one the possible solutions to the problem of regulator synthesis to ensure stable development of a given trajectory of motion of a nonlinear, non-stationary object of "black box" type using the concept of dual control. The task was set to simplify the previously proposed synthesis algorithm for the adaptive control of dynamic nonlinear, non-stationary objects using the example of first-order object of the "black box" type, using standard procedures for the diagonalization of the state matrix. An extended state matrix is the basis for obtaining a control model and predicting the behavior of a nonlinear non-stationary object, which in turn makes it possible to effectively use the concept of dual control. Methods used in the work are based on concept of dual control, nonlinear dynamic models, matrix theory, difference equations. Obtained results of this work consist of the development of a version of a dual nonparametric controller of nonstationary nonlinear processes, which has adaptive properties, does not require knowledge of the physics of functioning of the control object, is presented in the form of a simple algebraic formula that does not contain coefficients that require adjustment. Conclusion. Scientific novelty lies in the application of each interval matrix operator control for the diagonalization of the state submatrix. This operator is used for subsequent calculation of the control action. This approach enables the use of a standard diagonalization procedure using mathematical applications. The results are presented in the form of a final formula that does not require use of matrix operations during control, which makes it possible to simplify the synthesis of the controller using standard mathematical procedures.

In this work, we report the ongoing implementation of online-coupled aerosol–cloud microphysical–radiation interactions in the Brazilian global atmospheric model (BAM) and evaluate the initial results, using remote-sensing data for JFM 2014 and JAS 2019. Rather than developing a new aerosol model, which incurs significant overheads in terms of fundamental research and workforce, a simplified aerosol module from a preexisting global aerosol–chemistry–climate model is adopted. The aerosol module is based on a modal representation and comprises a suite of aerosol microphysical processes. Mass and number mixing ratios, along with dry and wet radii, are predicted for black carbon, particulate organic matter, secondary organic aerosols, sulfate, dust, and sea salt aerosols. The module is extended further to include physically based parameterization for aerosol activation, vertical mixing, ice nucleation, and radiative optical properties computations. The simulated spatial patterns of surface mass and number concentrations are similar to those of other studies. The global means of simulated shortwave and longwave cloud radiative forcing are comparable with observations with normalized mean biases ≤11% and ≤30%, respectively. Large positive bias in BAM control simulation is enhanced with the inclusion of aerosols, resulting in strong overprediction of cloud optical properties. Simulated aerosol optical depths over biomass burning regions are moderately comparable. A case study simulating an intense biomass burning episode in the Amazon is able to reproduce the transport of smoke plumes towards the southeast, thus showing a potential for improved forecasts subject to using near-real-time remote-sensing fire products and a fire emission model. Here, we rely completely on remote-sensing data for the present evaluation and restrain from comparing our results with previous results until a complete representation of the aerosol lifecycle is implemented. A further step is to incorporate dry deposition, in-cloud and below-cloud scavenging, sedimentation, the sulfur cycle, and the treatment of fires. [ABSTRACT FROM AUTHOR]

Accurate modeling of zenith tropospheric delay (ZTD) is beneficial for high-precision navigation and positioning. Many models with good performance have been developed for calibrating ZTD, such as the GPT3 model, which is recognized as an excellent global model and is widely used. However, certain limitations still remain in current models, such as the adoption of only single gridded data for modeling, and the model parameters need to be further optimized. In our previous research, a new approach based on the sliding window algorithm was proposed and applied to develop the GZTD-H model to address some of these limitations. However, this model is only suitable for the vertical adjustment of ZTD, not for estimating ZTD directly. In this study, an improved global grid ZTD model considering height scale factor (GGZTD-H) is derived from the initial GZTD-H model for estimating ZTD. The RMSs of the GGZTD-H model are 4.11 cm and 3.29 cm as validated by radiosonde data and IGS data, respectively. Compared with the UNB3m model and the canonical GPT3 model, the new model exhibits better performance. Moreover, three resolutions of the GGZTD-H model have been developed to reduce the quantity of gridded data delivered to users and optimize the ZTD computation process. Compared with the GPT3 model, the GGZTD-H model shows better performance with lower resolution and requires fewer model parameters for ZTD estimation, greatly optimizing ZTD computation. Users may select the best model that meets their needs in terms of the balance between resolution and accuracy. The high-precision GGZTD-H model could be used as a ZTD vertical stratification model for the vertical adjustment of atmospheric data and as an empirical model for ZTD estimation, which has potential applications in GNSS precise positioning, such as for the establishment and maintenance of the global terrestrial reference frame. [ABSTRACT FROM AUTHOR]

In order to realistically fulfil global and national climate protection targets, all potential measures have to be made use of to a maximum extent. Because it is readily available, biomass energy has been playing a key practical role for decades, supported by the traditional assumption of its carbon neutrality: under sustainable conditions, carbon dioxide emitted during combustion is held to be equal to its absorption during plant growth. In order to clarify conditions of carbon (C) neutrality, it is therefore necessary to model the annual natural C cycle on the entire planet and to include changes caused by a variety of growth strategies for biomass fuels. The "Combined Energy and Biosphere Model" CEBM calculates the cycle of plant growth, decay, biomass fuel production and its combustion on 2433 grid elements worldwide. CEBM results suggest that over many decades, the C pools of litter and especially soil organic carbon (i.e., humus layer) deplete considerably as a consequence of the interrupted natural carbon cycle. Overall, based on this finding, the earlier assumption of "carbon-neutral biomass fuels" is disapproved of in a long-term evaluation and—as a coarse rule of thumb—might be reduced to "half as carbon neutral as previously assumed" (when compared to a current fuel mix). On top of this principal effect, it is well known that life-cycle emissions, indirect or secondary emissions such as energy input related to production, transport and conversion into fuels will still add to this already principally highly incomplete carbon neutrality of biomass. [ABSTRACT FROM AUTHOR]

It is difficult to determine the accurate pose of non-cooperative space targets in on-orbit servicing (OOS). The visual camera is easily affected by the extreme light environment in space, and the scanning lidar will have motion distortion when the target moves at high speed. Therefore, we proposed a non-cooperative target pose-estimation system combining a registration and a mapping algorithm using a TOF camera. We first introduce the projection model of the TOF camera and proposed a new calibration method. Then, we introduce the three modules of the proposed method: the TOF data preprocessing module, the registration module and the model mapping module. We assembled the experimental platform to conduct semi-physical experiments; the results showed that the proposed method has the smallest translation error 8 mm and Euler angle error 1° compared with other classical methods. The total time consumption is about 100 ms, and the pose tracking frequency can reach 10 Hz. We can conclude that the proposed pose-estimation scheme can achieve the high-precision pose estimation of non-cooperative targets and meet the requirements necessary for aerospace applications. [ABSTRACT FROM AUTHOR]

Cash management optimization is one of the most essential tasks for any bank, because it helps save a significant amount of money by reducing the cost of ATMs funding and encashment. This paper focuses on forecasting customer cash demand, which is one of the key components of the optimization system. Furthermore, for the first time, our research touches on the problem of nonstationarity, which is typical for real-world ATM data, and proposes a data preprocessing pipeline to tackle it. We proposed new forecasting methods in the paradigms of local and global models, proved their superiority over classical approaches to forecasting time series and approaches used specifically for the cash demand forecasting problem. [ABSTRACT FROM AUTHOR]

Identifying the source of seafood is critical for combatting seafood fraud, but current tools are predominantly developed and applied on a species‐specific basis. This study investigates how multiple marine taxa could be geolocated at global scales by exploiting stable oxygen isotope compositions in carbonate biominerals (δ18Obiomin), where we expect to see universally expressed and predictable spatial variation in δ18Obiomin values across taxa. We constructed global ocean isoscapes of predicted δ18Obiomin values specific to fish (otoliths), cephalopod (statoliths) and shellfish (shells), and a fourth combined "universal" isoscape, and evaluated their capacity to derive δ18Obiomin values among known‐origin samples. High correspondence between isoscape‐predicted δ18Obiomin values and a compiled database of measured, georeferenced values (3954 datapoints encompassing 68 species) indicated that this δ18Obiomin approach works effectively, particularly in regions with highly resolved projections of seawater δ18O composition. When compared to taxon‐specific isoscapes, the universal isoscape demonstrated similar accuracy, indicating exciting potential for universal provenance applications. We tested the universal framework via a case study, using machine‐learning models to identify sample origins amongst regions of divergent (Tropical Asia vs Temperate Australasia) and similar (Temperate Asia vs Temperate Australasia) climates and latitudes. Classification accuracy averaged 75.3% between divergent regions, and 66% between similar regions. When endothermic tuna species were excluded from the analysis, the accuracy between divergent regions increased up to 90% between divergent regions. This study presents the first empirical step towards developing universal chemical markers, which have the potential to support a more inclusive and global approach of validating provenance of seafood. [ABSTRACT FROM AUTHOR]

The dynamics of COVID-19 virus were investigated in the literature via mathematical models. These models take into account the action of the suspected-exposed-infected-recovered people (SEIR). Also, among them, those which account for quarantined, social distancing functions or health isolation, were presented. In the absence of effective vaccines or therapies, prevention and treatment strategies for COVID-19 infections can not issue to non-epidemic state. Over the world, vaccination against the virus is set on. This motivated us to develop a model for inspecting if this treatment will issue to non endemic state. To this end, a global continuum model for the dynamics of this virus in the presence of vaccine and stimulated immunity is constructed. The present model deals with EIR - deceased individuals (EIRD) together with action of the health isolation and travelers (HIT). Which is described by nonlinear dynamical system (NLDS). Our aim here is to reduce the problem of solving this system to the case of solving LDS. This is carried by introducing the unified method (UM) via an approach present by the authors. By the UM, the solutions of a NLDS are recast to solutions of LDS via auxiliary equations. Numerical results of the exact solutions are evaluated, with initial data for the EIRD together with the number of vaccinated people. Real data are taken from Egypt (can be from elsewhere) at the end of the first wave, and they are considered as the initial conditions. These results are compared with a previous work by the authors in the absence of vaccination. The results of exposed, infected, recovered and deceased people are computed. It is found that the number of infected people decays to zero asymptotically, while, the number of infected people decays to an asymptotic value. This is in contrast to the results found previously in the case of absence of vaccination, where, these numbers grow monotonically. This is completely new. It is shown that locking-down has a remarkable effect in diminishing the number of infected people. The region of initial conditions for I-E people, that guarantee non-epidemic, non-endemic states, is determined via initial states control analysis. A software tool, based on this model, for simplifying the utilization of various data of different countries is developed. It is worth to mention that, the exact solutions of nonlinear dynamical equations, found here, are novel. [ABSTRACT FROM AUTHOR]