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Background: Estimating changes in fine fuel loads (FFL) is essential for carbon monitoring and fire management. Field measurements of post-fire fuel response are challenging, leading to reliance on generalised fuel types in operational models. Aims: This study presents a proof-of-concept for estimating fine fuel consumption and accumulation by integrating forest inventory and fire records, aiming to refine fuel dynamics estimates and enhance current practices. Methods: We estimated FFL changes across vertical strata in southeast Australian eucalypt forests, considering burn severity, fire type and forest cover. Fuel consumption was estimated by correlating pre-fire observations with combustion factors defined by burn severity. Fuel accumulation was predicted using modified Olson models with dynamic input parameters. Key results: Wildfires typically occurred in forests with higher FFL and consumed more fuels than prescribed burns. Closed forests experienced greater fuel loss compared with open and woodland forests. Increasing fire severity led to lower decomposition rates and a longer time to reach pre-fire FFL, with denser forests showing higher accumulation rates. Conclusions: Integrating forest inventory and fire history data offers valuable insights into fuel dynamics, potentially enhancing existing fuel hazard models. Implications: The approach is applicable in regions with mature forest inventories and advanced fire severity mapping. This study presents a proof-of-concept for estimating fine fuel consumption and accumulation by integrating forest inventory and fire records, aiming to refine fuel dynamics estimates and enhance current practices. We estimated FFL changes across different vertical strata in southeast Australian eucalypt forests, considering burn severity, fire type and forest cover. [ABSTRACT FROM AUTHOR]

Context: Pasture dieback has emerged as a significant threat to the health and productivity of sown pastures in eastern Queensland and northern New South Wales, Australia. Aims: We aimed to address knowledge gaps on spatial spread patterns, recovery trajectories and floristic changes using remote sensing and ground surveys. Methods: We used a time series of high-resolution (12–25 cm) aerial imagery to quantify and compare pasture dieback spread over 7 years in three land-use areas: ungrazed pasture, grazed pasture and rehabilitation following mining. The green leaf index was applied using supervised random forest algorithms to classify areas affected between 2015 and 2021. Flora surveys were conducted to compare impacted and unimpacted areas for the three land uses and validate classifications. Key results: The first emergence of pasture dieback was in ungrazed pasture, and these areas recorded the highest rate of dieback spread at 1.88 ha month−1, compared with 0.54 and 0.19 ha month−1 in rehabilitated and grazed pastures respectively. Field validation showed that dieback-impacted pastures shifted from buffel grass (Cenchrus ciliaris L.), to forb-dominated communities with significantly different species mix, biomass and cover conditions. An analysis of local climate data showed that winter night-time temperatures and rainfall were notably higher than long-term means in the year preceding the first detection of pasture dieback. Conclusions: High resolution aerial imagery and ground surveys can be used to monitor pasture health by employing vegetation indices and random forest classifiers. Implications: Ungrazed pastures and roadside areas should be managed to protect the region from further outbreaks. Pasture dieback has been affecting the health and productivity of pastures in eastern Queensland and northern NSW. We used aerial imagery to map and compare pasture dieback spread patterns in three land use areas: grazed pasture, ungrazed pasture and rehabilitated pasture following coal mining. The fastest rate of spread was recorded in ungrazed pasture followed by rehabilitation and grazed pastures. Flora surveys showed that dieback-impacted sites shifted from buffel grass to forb dominated pastures. [ABSTRACT FROM AUTHOR]

Background: Determining the clinical and subclinical characteristics related to the recurrence status in patients with a thyroid carcinoma has great significance for prognosis, prediction of recurrence and monitoring of treatment outcomes. This study aimed to determine the association between recurrence rate and some characteristics in patients with thyroid carcinoma. Patients and Methods: The study was conducted by descriptive method with longitudinal follow-up on 102 thyroid carcinoma patients at 103 Military Hospital, Hanoi, Vietnam, from July 2013 to December 2016. Results: Univariate analysis showed that there was a relationship between the recurrence characteristics in the studied patients and the characteristics of lymph node metastasis (P = 0.026; OR = 15; 95% CI = 1.4-163.2) and BRAF V600E mutation status (P = 0.01; OR = 3.41; 95% CI = 1.31-8.88). When analysing the multivariable Logistic regression model, there was a positive correlation between the occurrence of BRAF V600E gene mutation (P = 0.032; OR = 17.649; 95% CI = 1.290-241.523) and male sex (P = 0.036; OR = 12.788; 95% CI = 1.185-137.961) and the occurrence of recurrence in study patients. The mean time to relapse was earlier in male patients than in female patients (P = 0.02). The mean time to relapse in patients with the BRAF V600E mutation (31.81 ± 1.14 months) was shorter than the mean time to relapse in the group without the mutation (57.82 ± 2.08 months) (P = 0.01). The group of patients with mutations in the BRAF V600E gene increased the risk of recurrence compared with the group without the mutation (HR = 9.14, P = 0.04). Conclusion: There is a positive correlation between recurrence and masculinity, lymph node metastasis and the occurrence of BRAF V600E mutations in thyroid carcinoma patients. [ABSTRACT FROM AUTHOR]

An empirical scale-up model of the pan-coating process for controlled-release urea fertilizer (CRUF) was novel performed via a pan-coating process using the biodegradable polymer solution. The similarities in the geometry, kinetics, dynamics, and thermodynamics during the scaling-up of the pan-coating process were analyzed. The dimensionless numbers and a dimensionless number equation were determined and derived, respectively. The thickness of the formed coating related almost to the air velocity and the pan speed. This model showed the significant applications in the design and optimization of industrial particle-coating systems. [ABSTRACT FROM AUTHOR]

In 2016, extreme drought and saline intrusion led to widespread damage and livelihood disruption for many people in the coastal region of the Vietnamese Mekong Delta. Through an integrated multi-step approach of literature and stakeholder analysis, focus group discussions and interviews with local governments and farmers, an understanding of the local water governance systems and their functioning is gained, providing insight into the power, interest and responsibility of multiple agencies. Development of more responsive and inclusive water governance systems, with improved early warnings and information flows during extreme events, is needed to improve the resilience and adaptation of the region. [ABSTRACT FROM AUTHOR]

The spray coating process is an important process of the coating particle technology for the production of controlled-release fertilisers (CRFs). Its modelling would be helpful in the production process such as increase material usage efficiency, save production costs, and reduce dispersal waste produced that will cause environmental pollution. This article presents the results of an experimental study to establish an empirical model of the spray coating process with a biodegradable polymer solution. The shape and size of the spray area, droplet size distribution (DSD) and Sauter mean diameter (SMD) were determined by using high-speed camera 1000 frames per second (fps), laser transmitter and the image processing toolbox of MATLAB software. The results showed that the spray area had a cone shape, its mean width, corresponding to a spray distance of 300 mm, was 451 mm at a pressure of 0.18 MPa, viscosity of 50 mPa.s, spray flow of 1.5 mL/min and the droplet size distributions were noted 0.153 to 1.449 mm and droplet SMD was 0.876 mm. The model also showed that droplet SMD was calculated by four dimensionless numbers, will be applied to calculate, optimize and simulate coating particle technology. [ABSTRACT FROM AUTHOR]

Satellite earth observation is being increasingly used to monitor forests across the world. Freely available Landsat data stretching back four decades, coupled with advances in computer processing capabilities, has enabled new time-series techniques for analyzing forest change. Typically, these methods track individual pixel values over time, through the use of various spectral indices. This study examines the utility of eight spectral indices for characterizing fire disturbance and recovery in sclerophyll forests, in order to determine their relative merits in the context of Landsat time-series. Although existing research into Landsat indices is comprehensive, this study presents a new approach, by comparing the distributions of pre and post-fire pixels using Glass's delta, for evaluating indices without the need of detailed field information. Our results show that in the sclerophyll forests of southeast Australia, common indices, such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), both accurately capture wildfire disturbance in a pixel-based time-series approach, especially if images from soon after the disturbance are available. However, for tracking forest regrowth and recovery, indices, such as NDVI, which typically capture chlorophyll concentration or canopy 'greenness', are not as reliable, with values returning to pre-fire levels in 3-5 years. In comparison, indices that are more sensitive to forest moisture and structure, such as NBR, indicate much longer (8-10 years) recovery timeframes. This finding is consistent with studies that were conducted in other forest types. We also demonstrate that additional information regarding forest condition, particularly in relation to recovery, can be extracted from less well known indices, such as NBR2, as well as textural indices incorporating spatial variance. With Landsat time-series gaining in popularity in recent years, it is critical to understand the advantages and limitations of the various indices that these methods rely on. [ABSTRACT FROM AUTHOR]