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We analyzed the role of primary and postoperative low linear energy transfer radiotherapy in 538 patients treated for salivary gland cancer in centers of the Dutch Head and Neck Oncology Cooperative Group, in search for prognostic factors and dose response.The tumor was located in the parotid gland in 59%, submandibular gland in 14%, oral cavity in 23%, and elsewhere in 5%. In 386 of 498 patients surgery was combined with radiotherapy, with a median dose of 62 Gy. Median delay between surgery and radiotherapy was 6 weeks. In the postoperative radiotherapy group, adverse prognostic factors prevailed. Elective radiotherapy to the neck was given in 40%, with a median dose of 50 Gy. Primary radiotherapy (n = 40) was given for unresectable disease or M(1), with a dose range of 28-74 Gy.Postoperative radiotherapy improved 10-year local control significantly compared with surgery alone in T(3-4) tumors (84% vs. 18%), in patients with close (95% vs. 55%) and incomplete resection (82% vs. 44%), in bone invasion (86% vs. 54%), and perineural invasion (88% vs. 60%). Local control was not correlated with interval between surgery and radiotherapy. No dose-response relationship was shown. Postoperative radiotherapy significantly improved regional control in the pN(+) neck (86% vs. 62% for surgery alone). A rating scale for different sites, T stage, and histologic type may be applied to calculate the risk of disease in the neck at presentation, and so indicate the need for elective neck treatment. A marginal dose-response was seen, in favor of a dose > or =46 Gy. A clear dose-response relationship was shown for patients treated with primary radiotherapy. Five-year local control was 50% with a dose of 66-70 Gy.Postoperative radiotherapy with a dose of at least 60 Gy is indicated for patients with T(3-4) tumors, incomplete or close resection, bone invasion, perineural invasion, and pN(+). In unresectable tumors, a dose of at least 66 Gy is advisable.

Gas-based power plants have attracted more attention in providing electrical energy worldwide because of their lower costs and air pollution. In addition, the use of multi-carrier energy systems has several advantages, such as sustainability benefits and improving performance in supplying the energy demand. This study aims to optimize the total operation cost of multi-carrier energy systems considering the uncertain parameters. The storage technology and consumption side assist the operator in achieving lower costs based on conceptions of demand response programs. Therefore, this study presents a comprehensive mathematical model for the coordinated operation of integrated multi-carrier energy systems while the operational constraints of both gas and power networks are considered. Furthermore, this paper utilizes a new uncertainty modeling method based on Hong's two-point estimate method for addressing the uncertainties of load consumption and wind generation. The proposed model is applied to a gas and power multi-carrier energy system through four case studies. The results affirm the high performance of the presented method and investigate the influence of demand response programs in both sides of energy carriers.

Accurate wind power forecasting is one of the most important operations within the economic dispatch problem to increase the performance of power and energy systems. Accordingly, this study proposes a cyber-resilient hybrid approach based on the Federated Learning and Convolutional Neural Network (CNN) procedure for short-term wind power generation forecasting in different regions of Iran. Generalizability, data independence, forecasting for regions where no training data is available, and preserving the security and privacy of data are prominent features of the proposed method. The federated network was designed with an architecture of 9 clients to perform the training process and extract the salient features from the data associated with each region in each client via the CNN technique. Then, the generalized global supermodel is produced based on the extracted features in each client to forecast the wind power in new and unknown regions such as Mahshahr, Bojnord, and Lootak that had no training data available and had no effect on global supermodel generation. Various scenarios were developed to test the robustness of the suggested methodology. In the first scenario, wind power forecasting is performed based on the suggested technique. In this scenario, the accuracy of the generalized supermodel to forecast wind power generation in each of the Mahshahr, Bojnord, and Lootak regions is 84%, 85%, and 74%, respectively. The second scenario models the scaling attack by changing the wind speed parameters to evaluate the performance of forecasting models against the data integrity attack. In this scenario, an evaluation of the forecast results based on various performance metrics is conducted highlighting the accuracy reduction of the forecast model, due to the damage caused by cyber-attacks on the input data. In the third scenario, the detection of cyber-attack is done based on the image processing-based technique. The presented results emphasize the accurate performance and high generalizability of the cyber-resilient global supermodel in forecasting wind power in various regions of Iran.

Humic-like substances (HULIS) account for a major redox-active fraction of biomass burning organic aerosols (BBOA). During atmospheric transport, fresh acidic BB-HULIS in droplets and humid aerosols are subject to neutralization and pH-modified aging process. In this study, solutions containing HULIS isolated from wood smoldering emissions were first adjusted with NaOH and NH3 to pH values in the range of 3.6-9.0 and then aged under oxic dark conditions. Evolution of HULIS oxidative potential (OP) and total peroxide content (equivalent H2O2 concentration, H2O2eq) were measured together with the changes in solution absorbance and chemical composition. Notable immediate responses such as peroxide generation, HULIS autoxidation, and an increase in OP and light absorption were observed under alkaline conditions. Initial H2O2eq, OP, and absorption increased exponentially with pH, regardless of the alkaline species added. Dark aging further oxidized the HULIS and led to pH-dependent toxic and chemical changes, exhibiting an alkaline-facilitated initial increase followed by a decrease of OP and H2O2eq. Although highly correlated with HULIS OP, the contributions of H2O2eq to OP are minor but increased both with solution pH and dark aging time. Alkalinity-assisted autoxidation of phenolic compounds and quinoids with concomitant formation of H2O2 and other alkalinity-favored peroxide oxidation reactions are proposed here for explaining the observed HULIS OP and chemical changes in the dark. Our findings suggest that alkaline neutralization of fresh BB-HULIS represents a previously overlooked peroxide source and pathway for modifying aerosol redox-activity and composition. Additionally, these findings imply that the lung fluid neutral environment can modify the OP and peroxide content of inhaled BB-HULIS. The results also suggest that common separation protocols of HULIS using base extraction methods should be treated with caution when evaluating and comparing their composition, absorption, and relative toxicity.

Anaerobic nitrogen removal technologies offer advantages in terms of energy and cost savings over conventional nitrification-denitrification systems. A mathematical model was constructed to evaluate the influence of process operation on the coexistence of nitrite dependent anaerobic methane oxidizing bacteria (n-damo) and anaerobic ammonium oxidizing bacteria (anammox) in a single granule. The nitrite and methane affinity constants of n-damo bacteria were measured experimentally. The biomass yield of n-damo bacteria was derived from experimental data and a thermodynamic state analysis. Through simulations, it was found that the possible survival of n-damo besides anammox bacteria was sensitive to the nitrite/ammonium influent ratio. If ammonium was supplied in excess, n-damo bacteria were outcompeted. At low biomass concentration, n-damo bacteria lost the competition against anammox bacteria. When the biomass loading closely matched the biomass concentration needed for full nutrient removal, strong substrate competition occurred resulting in oscillating removal rates. The simulation results further reveal that smaller granules enabled higher simultaneous ammonium and methane removal efficiencies. The implementation of simultaneous anaerobic methane and ammonium removal will decrease greenhouse gas emissions, but an economic analysis showed that adding anaerobic methane removal to a partial nitritation/anammox process may increase the aeration costs with over 20%. Finally, some considerations were given regarding the practical implementation of the process.

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.