Search Results (7)

The original EEG data collected are the 1D sequence, which ignores spatial topology information; Feature Pyramid Networks (FPN) is better at small dimension target detection and insufficient feature extraction in the scale transformation than CNN. We propose a method of FPN and Long Short-Term Memory (FPN-LSTM) for EEG feature map-based emotion recognition. According to the spatial arrangement of brain electrodes, the Azimuth Equidistant Projection (AEP) is employed to generate the 2D EEG map, which preserves the spatial topology information; then, the average power, variance power, and standard deviation power of three frequency bands ($\alpha$, $\beta$, and $\gamma$) are extracted as the feature data for the EEG feature map. BiCubic interpolation is employed to interpolate the blank pixel among the electrodes; the three frequency bands EEG feature maps are used as the G, R, and B channels to generate EEG feature maps. Then, we put forward the idea of distributing the weight proportion for channels, assign large weight to strong emotion correlation channels (AF3, F3, F7, FC5, and T7), and assign small weight to the others; the proposed FPN-LSTM is used on EEG feature maps for emotion recognition. The experiment results show that the proposed method can achieve Value and Arousal recognition rates of 90.05% and 90.84%, respectively. Full article

Phosphorous (P) fixation in saline soils is a concern worldwide. To investigate optimization strategies for P fertilizer application that improve P use efficiency (PUE) and crop yield in saline soil, in terms of P sources and rates, we conducted a two year field experiment in the coastal saline area of China to investigate the effects of P rates and sources, including superphosphate (SSP), monoammonium phosphate (MAP) and ammonium polyphosphate (APP) on yield, aboveground P uptake, agronomy efficiency (AE_P), and soil available P of winter wheat (Triticum aestivum L.). Wheat yield, under the three P sources, increased with P rates and reached a plateau under 20 kg P ha⁻¹ SSP,18 kg P ha⁻¹ MAP, and 17 kg P ha⁻¹ MAP, respectively. The application of SSP increased the wheat yield by 9–11% compared to MAP and APP. The aboveground P uptake of winter wheat under SSP was 14% and 13% higher than MAP and APP, respectively, under the optimal P application rate. The AE_P under SSP was higher than the other two P sources under the same P rate. SSP increased the soil Ca²⁺ concentration by 20–42%, but decreased the Na⁺ concentration by 14–18% at the P rate of 26 kg P ha⁻¹ in all soil layers, including 0–20, 20–40, 40–60 cm, compared to CK (0 kg P ha⁻¹). The soil Olsen-P concentration under APP was higher than the other P sources. This study suggests that optimizing P sources and rates can improve wheat yield, PUE, and soil quality in the coastal saline soil. Full article

Sea-level rise will cause erosion of land, deeper and increasingly frequent flooding and will eventually permanently inundate low-elevation land, forcing the adaptation of seaside communities to avoid or reduce risk. To inform adaptation planning, we quantified the effects of incremental relative sea-level rise (RSLR) on exposed land area, number and replacement value of buildings within Tauranga Harbour, New Zealand. The assessment compared three coastal hazards: flooding, permanent inundation and erosion. Increasingly frequent coastal flooding will be the dominant trigger for adaptation in Tauranga. In the absence of adaptation, coastal flooding, recurring at least once every 5 years on average, will overtake erosion as the dominant coastal hazard after about 0.15–0.2 m RSLR, which is likely to occur between the years 2038–2062 in New Zealand and will rapidly escalate in frequency and consequence thereafter. Coastal erosion will remain the dominant hazard for the relatively-few properties on high-elevation coastal cliffs. It will take 0.8 m more RSLR for permanent inundation to reach similar impact thresholds to coastal flooding, in terms of the number and value of buildings exposed. For buildings currently within the mapped 1% annual exceedance probability (AEP) zone, the flooding frequency will transition to 20% AEP within 2–3 decades depending on the RSLR rate, requiring prior adaptive action. We also compared the performance of simple static-planar versus complex dynamic models for assessing coastal flooding exposure. Use of the static-planar model could result in sea level thresholds being reached 15–45 years earlier than planned for in this case. This is compelling evidence to use dynamic models to support adaptation planning. Full article

Diversifying the energy mix of Bangladesh is becoming indispensable not only to improve its energy security, but also for a more sustainable economic development. This study focused on mapping the wind potential of southern coastal areas of Bangladesh to estimate the wind energy potential, along with the reduction in carbon emissions due to wind energy. Analysis of the carbon footprint was based on the annual energy production (AEP) from the selected low-wind turbine generators (WTGs). The time series-measured and -predicted wind data were incorporated with the high-resolution mesoscale and microscale wind re-source mapping technique at 60, 80, and 100 m above ground level (AGL). Coupling mesoscale and microscale modeling provided reliable mapping results for the commercially exploitable wind resource and was verified by ground-based wind measurement. The results revealed that, among the selected areas, two sites named Charfashion and Monpura have a promising annual mean wind speed of 7.3 m/s at 100 m AGL for energy generation. Different WTGs with ranges of 1–3.3 MW were used to estimate the wind energy generation capacity at different sites in the study area. A WTG with a 1 MW wind energy generation capacity installed at 60 m AGL in the selected site has the potential to produce 2.79 GWh/year of clean energy, reducing 1781.689 tons of CO₂ per year, whereas a 3.3 MW WTG at 80 m AGL can produce 18.99 GWh/year of energy, reducing 12,098.54 tons of CO₂ per year, and a 1.6 MW WTG at 100 m AGL produces 11.04 GWh/year of energy, cutting 7035.028 tons of CO₂ per year. With its reliable scientific and time-tested wind energy estimation method, this research is very important for the development of wind energy in the southern coastal areas of Bangladesh to meet the increasing energy demands through initiating the development of renewable energy to improve the energy security and reduce the carbon emissions of the country. Full article

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates. Full article

Hot compression tests over the temperature range from 350 °C to 500 °C and strain rates range from 0.001 s⁻¹ to 1 s⁻¹ for homogenized Al–6.32Zn–2.10Mg alloy were carried out on a Gleeble-3800 thermal simulation machine to characterize its hot deformation behavior. At the same time, a modified Arrhenius constitutive equation was established to describe the flow behavior of the alloy, whose average absolute error is 2.89%, which proved to have an excellent predictive effect on the flow stress of the alloy. The hot processing map of the alloy was established, and the stability processing parameters were 460–500 °C and 0.01–0.08 s⁻¹. Then, the Z parameter processing map and activation energy processing (AEP) maps were established for further optimization. Eventually, the optimal processing parameters of the alloy was 460–500 °C (0.03–0.08 s⁻¹). Then, the microstructure of specimens was observed using electron backscatter diffraction. Based on the findings the reasonability of the AEP map and Z parameter map was verified. Finally, electron backscatter diffraction (EBSD) techniques were used to analyze the evolution of the grain structure during the deformation process. It was found that dynamic recovery (DRV) was the main softening mechanism of Al–6.32Zn–2.10Mg. Continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) operated together with the increase of strain, but CDRX was confirmed as the dominant DRX mechanism. Full article

Although the size of the wind turbine has become larger to improve the economic feasibility of wind power generation, whether increases in rotor diameter and hub height always lead to the optimization of energy cost remains to be seen. This paper proposes an algorithm that calculates the optimized hub height to minimize the cost of energy (COE) using the regional wind profile database. The optimized hub height was determined by identifying the minimum COE after calculating the annual energy production (AEP) and cost increase, according to hub height increase, by using the wind profiles of the wind resource map in South Korea and drawing the COE curve. The optimized hub altitude was calculated as 75~80 m in the inland plain but as 60~70 m in onshore or mountain sites, where the wind profile at the lower layer from the hub height showed relatively strong wind speed than that in inland plain. The AEP loss due to the decrease in hub height was compensated for by increasing the rotor diameter, in which case COE also decreased in the entire region of South Korea. The proposed algorithm of identifying the optimized hub height is expected to serve as a good guideline when determining the hub height according to different geographic regions. Full article