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Studies on estimating cumulative fire intensity from spreading wildland fires based on fire radiative energy density (FRED) have primarily been conducted through controlled experiments. The objective of this study was to assess the potential for estimating FRED for freely-burning wildfires at landscape scales. Airborne thermal infrared image sequences collected 8 and 9 December 2017 during the Thomas Fire were used for surface temperature derivation and FRED estimation. Sensitivity of varying ambient temperatures, and a newly developed method that adjusts for ash radiances on fire radiative flux density (FRFD) and FRED estimates were tested. Pixel-level image classification was run to identify FRFD time sequences that were complete or incomplete because of cloud obscuration and provided the basis for an obscuration gap filling technique. Variations in estimated ambient temperature used to estimate FRFD had little impact on FRED estimates, while our ash adjustment led to notable differences. An exponential decay model characterized FRFD time sequences well, providing a basis for gap filling irregular sequences caused by atmospheric obscuration. FRED estimates were regressed on rate of spread (ROS) magnitudes and found to be positively and significantly correlated. FRED magnitudes were higher on 9 December when the Thomas Fire burned under higher wind speeds and lower relative humidity levels (Santa Ana weather conditions) than on 8 December.

Demand response (DR) has been studied widely in the smart grid literature, however, there is still a significant gap in approaches that address security, privacy, and robustness of settlement processes simultaneously. The need for security and robustness emerges as a vital property, as Internet of Things (IoT) devices become part of the smart grid; in the form of smart meters, home energy management systems (HEMSs), intelligent transformers, and so on. In this paper, we use energy blockchain to secure energy transactions among customers and the utility. In addition, we formulate a mixed-strategy stochastic game model to address uncertainties in DR contributions of agents and achieve optimal demand response decisions. This model utilizes the processing hardware of customers for block mining, stores customer DR agreements as distributed ledgers, and offers a smart contract and consensus algorithm for energy transaction validation. We use a real dataset of residential demand profiles and photovoltaic (PV) generation to validate the performance of the proposed scheme. The results show the impact of electric vehicle (EV) discharging and customer demand reduction on increasing the probability of successful block mining and improving customer profits. Moreover, the results demonstrate the security and robustness of our consensus algorithm for detecting malicious activities.

The Energy-efficiency of demand management technologies and customer’s experience have emerged as important issues as consumers began to heavily adopt these technologies. In this context, where the electrical load imposed on the smart grid by residential users needs to be optimized, it can be better managed when customer’s comfort parameters are used, such as thermal comfort and preferred appliance usage time interval. In this paper a multi-layer architecture is proposed that uses a multi-objective optimization model at the energy consumption level to take consumer comfort and experience into consideration. The paper shows how our proposed Clustered Sequential Management (CSM) approach could improve consumer comfort via appliance use scheduling. To quantify thermal comfort, we use thermodynamic solutions for a Heating Ventilation and Air Conditioner (HVAC) system and then apply our scheduling model to find the best time slot for such thermal loads, linking consumer experience to power consumption. In addition to thermal loads, we also include non-thermal loads in the cost minimization and the enhanced consumer experience. In this hierarchal algorithm, we classified appliances by their load profile including degrees of freedom for consumer appliance prioritization. Finally, we scheduled consumption within a Time of Use (ToU) pricing model. In this model, we used Mixed Integer Linear Programming (MILP) and Linear Programming (LP) optimization for different categories with different constraints for various loads. We eliminate the customer’s inconvenience on thermal load considering ASHRAE standard, increase the satisfaction on EV optimal chagrining constrained by minimum cost and achieve the preferred usage time for the non-interruptible deferrable loads. The results show that our model is typically able to achieve cost minimization almost equal to 13% and Peak-to-Average Ratios (PAR) reduction with almost 45%.

1. Bats are important components of agricultural ecosystems. However, little is known about the extent to which bats use linear features when foraging and commuting in agricultural settings, when compared to the interior of fields. 2. As part of a large-scale citizen science project, bat detectors were placed in the centre of agricultural fields (arable and pasture) and along linear features (intensively managed hedgerows, sympathetically managed hedgerows and treelines). 3. Our results show that all 10 of the bat species groups identified were found both along linear features and in the middle of agricultural fields. Of the five species groups analysed further, all had significantly more bat activity along linear features compared to the middle of fields, except for Nyctalus noctula. However, our results showed that 29% of calls from Rhinolophus ferrumequinum were recorded in the middle of agricultural fields, compared to only 10% for Pipistrellus pipistrellus. Bat activity was more likely to be associated with treelines compared to other linear feature types. 4. Our results highlight the importance of linear feature management to bat conservation, but also the need to consider field centres during survey design and Environmental Impact Assessments.

The time-efficient and accurate implementation of physics-based fluidic damping effects is still one of the biggest challenges in the simulation of complex MEMS devices. Two modelling approaches utilizing the CRAIG/BAMPTON component mode synthesis method are discussed and compared in context of a highly automated model generation procedure. The first approach uses a modal projection technique with pressure profiles obtained from REYNOLDS flow simulations using the thermal-fluidic analogy. The second approach is based on the representation of the fluidic domain in form of a generalized KIRCHHOFFian lumped flow resistance network model. Both methods are generally suited for the simulation of structures like gyroscopes or accelerometers, but show different behaviors in terms of scaling and complexity during the model generation step and in the final ROM. The methods are demonstrated on examples and are compared to optical measurements of an out-of-plane teeter-totter type accelerometer.

Barranquilla is known as a dynamically growing city in the Colombian Caribbean. Urbanisation induces land use and land cover (LULC) changes in the city and its hinterland affecting the region’s climate and biodiversity. This paper aims to identify the trends of land use and land cover changes in the hinterland of Barranquilla corresponding to 13 municipalities in the north of the Department Atlántico. Landsat TM/ETM/OLI imagery from 1985 to 2017 was used to map and analyse the spatio-temporal development of land use and land cover changes. During the investigation period, the settlement areas grew by approximately 50% (from 103.3 to 153.6 km2), while areas with woody vegetation cover experienced dynamic changes and increased in size since 2001. Peri-urban and rural areas were characterized by highly dynamic changes, particularly regarding clearing and recovery of vegetated areas. Regression analyses were performed to identify the impact factors of detected vegetation cover changes. Computed logistic regression models included 20 independent variables, such as relief, climate, soil, proximity characteristics and socio-economic data. The results of this study may act as a basis to enable researchers and decision-makers to focus on the most important signals of systematic landscape transformations and on the conservation of ecosystems and the services they provide.

(1) Background: Maximum isokinetic force loads show strongly increased post-load lactate concentrations and an increase in the maximum blood lactate concentration rate ( V ˙ Lamax), depending on load duration. The reproducibility of V ˙ Lamax must be known to be able to better assess training-related adjustments of anaerobic performance using isokinetic force tests. (2) Methods: 32 subjects were assigned to two groups and completed two unilateral isokinetic force tests (210° s−1, Range of Motion 90°) within seven days. Group 1 (n = 16; age 24.0 ± 2.8 years, BMI 23.5 ± 2.6 kg m−2, training duration: 4.5 ± 2.4 h week−1) completed eight repetitions and group 2 (n = 16; age 23.7 ± 1.9 years, BMI 24.6 ± 2.4 kg m−2, training duration: 5.5 ± 2.1 h week−1) completed 16 repetitions. To determine V ˙ Lamax, capillary blood (20 µL) was taken before and immediately after loading, and up to the 9th minute post-load. Reproducibility and variability was determined using Pearson and Spearman correlation analyses, and variability were determined using within-subject standard deviation (Sw) and Limits of Agreement (LoA) using Bland Altman plots. (3) Results: The correlation of V ˙ Lamax in group 1 was r = 0.721, and in group 2 r = 0.677. The Sw of V ˙ Lamax was 0.04 mmol L−1 s−1 in both groups. In group 1, V ˙ Lamax showed a systematic bias due to measurement repetition of 0.02 mmol L−1 s−1 in an interval (LoA) of ±0.11 mmol L−1 s−1. In group 2, a systematic bias of −0.008 mmol L−1 s−1 at an interval (LoA) of ±0.11 mmol L−1 s−1 was observed for repeated measurements of V ˙ Lamax. (4) Conclusions: Based on the existing variability, a reliable calculation of V ˙ Lamax seems to be possible with both short and longer isokinetic force loads. Changes in V ˙ Lamax above 0.11 mmol L−1 s−1 due to training can be described as a non-random increase or decrease in V ˙ Lamax.