Search Results (27)

Evapotranspiration (ET) is a crucial parameter for agricultural management and the hydrologic cycle, and instantaneous satellite images are the primary data source for regional ET. The constant evaporative fraction method (EFO) is a common approach for converting short-time ET (ET_st) to daily ET (ET_day). However, EFO has some limitations due to simple assumptions, including the following: the short-time evaporative fraction (EF_st) equals the daily evaporative fraction (EF_day). This study proposed an improved evaporative fraction method (EFI) through theoretical derivation and data analysis without additional data requirements, enabling the accurate upscaling of ET_st to ET_day. The vapor pressure deficit and available energy were considered in EFI to describe the main effect factor and estimate the deviation between EF_st and EF_day, defining the deviation coefficient and potential deviation between EF_st and EF_day. EFI was tested through four aspects: different agricultural systems, various sites, two growth stages, and different sources of EF_st, comparing estimated ET_day from EFI and measured ET_day. EFI reduced the mean absolute percentage error (MAPE) of ET_day estimation from 23% to 16% when EF_st is derived from measured data compared to EFO. Similarly, the MAPE of ET_day estimation reduced from 38% to 31% when EF_st is derived from a remote sensing model (Surface Energy Balance Algorithm for Land, SEBAL). EFI performs better during the growing period than the fallow season, providing critical information for irrigation practices. Crop type is not a main control factor for the relationship between η (ratio between VPD and R_n-G) and EF_st, and EFI is adaptable to various agricultural systems. The encouraging results of EFI in different scenarios demonstrate its accuracy and robustness. Therefore, EFI is anticipated to upscale EF_st to EF_day, generating a more accurate ET on a regional scale through remote sensing technology. Full article

Stainless steel wires exhibit excellent mechanical properties and are widely used in engineering applications. This study fabricates 15 μm stainless steel wires for potential integration into wire bonding technology for electronic packaging. The research explores the microstructural characteristics, electrical conduction mechanisms, and ball formation behavior of ultra-fine stainless-steel wires to assess their feasibility for wire bonding applications. Results indicate that both 15 μm and 30 μm stainless steel wires exhibit elongated grains with outstanding tensile strength and hardness. Compared to the 30 μm wires, the 15 μm wires undergo more pronounced work hardening, leading to higher tensile strength and resistance. This study investigates the differences between vacuum and electrified annealing processes to address the work hardening and ductility issues in stainless steel wires. Results confirm that the hardness of the original wire significantly decreases after vacuum annealing at 780 °C for 15 min. Furthermore, using the derived equation, $T={\displaystyle \frac{IV}{2.3085\times {10}^{-3}}}+25$, the annealing temperature of 780 °C is converted into an equivalent current, and electrify annealing is conducted under a condition of 0.08 A for 15 min. The annealed wires exhibit a softening effect and enhance ductility. Furthermore, due to stored deformation energy and recrystallization effects, the electrical fatigue life of 15 μm stainless steel wires is approximately 300 cycles. After electrifying annealing, the base microstructure becomes more homogeneous due to thermal effects, reducing fatigue life to around 150 cycles. However, due to the softening effect, the annealed wires make the EFO process easier and minimize solidification segregation in the free air ball (FAB) microstructure, demonstrating their potential for electronic packaging applications. Full article

The Electric Fish Optimization (EFO) algorithm is inspired by the predation behavior and communication of weak electric fish. It is a novel meta-heuristic algorithm that attracts researchers because it has few tunable parameters, high robustness, and strong global search capabilities. Nevertheless, when operating in complex environments, the EFO algorithm encounters several challenges including premature convergence, susceptibility to local optima, and issues related to passive electric field localization stagnation. To address these challenges, this study introduces Adaptive Electric Fish Optimization Algorithm Based on Standstill Label and Level Flight (SLLF-EFO). This hybrid approach incorporates the Golden Sine Algorithm and good point set theory to augment the EFO algorithm’s capabilities, employs a variable-step-size Levy flight strategy to efficiently address passive electric field localization stagnation problems, and utilizes a standstill label strategy to mitigate the algorithm’s tendency to fall into local optima during the iterative process. By leveraging multiple solutions to optimize the EFO algorithm, this framework enhances its adaptability in complex environments. Experimental results from benchmark functions reveal that the proposed SLLF-EFO algorithm exhibits improved performance in complex settings, demonstrating enhanced search speed and optimization accuracy. This comprehensive optimization not only enhances the robustness and reliability of the EFO algorithm but also provides valuable insights for its future applications. Full article

An information-theoretic data mining method is employed to analyze categorical spatiotemporal Geographic Information System land use data. Reconstructability Analysis (RA) is a maximum-entropy-based data modeling methodology that works exclusively with discrete data such as those in the National Land Cover Database (NLCD). The NLCD is organized into a spatial (raster) grid and data are available in a consistent format for every five years from 2001 to 2021. An NLCD tool reports how much change occurred for each category of land use; for the study area examined, the most dynamic class is Evergreen Forest (EFO), so the presence or absence of EFO in 2021 was chosen as the dependent variable that our data modeling attempts to predict. RA predicts the outcome with approximately 80% accuracy using a sparse set of cells from a spacetime data cube consisting of neighboring lagged-time cells. When the predicting cells are all Shrubs and Grasses, there is a high probability for a 2021 state of EFO, while when the predicting cells are all EFO, there is a high probability that the 2021 state will not be EFO. These findings are interpreted as detecting forest clear-cut cycles that show up in the data and explain why this class is so dynamic. This study introduces a new approach to analyzing GIS categorical data and expands the range of applications that this entropy-based methodology can successfully model. Full article

This paper presents an optimal tuning of a proportional integral differential (PID) controller used to maintain glucose concentration at a desired set point. The PID controller synthesizes an appropriate feed rate profile for an E. coli fed-batch cultivation process. Mathematical models are developed based on dynamic mass balance equations for biomass, substrate, and product concentration of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation for bacterial phytase extracellular production. For model parameter identification and PID tuning, a hybrid metaheuristic technique—chaotic electromagnetic field optimization (CEFO)—is proposed. In the hybridization, a chaotic map is used for the generation of a new electromagnetic particle instead of the electromagnetic field optimization (EFO) search strategy. The CEFO combines the exploitation capability of the EFO algorithm and the exploration power of ten different chaotic maps. The comparison of the results with classical EFO shows the superior behaviour of the designed CEFO. An improvement of 30% of the objective function is achieved by applying CEFO. Based on the obtained mathematical models, 10 PID controllers are tuned. The simulation experiments show that the designed controllers are robust, resulting in a good control system performance. The closed-loop transient responses for the corresponding controllers are similar to the estimated models. The settling time of the control system based on the third PID controller for all estimated models is approximately 9 min and the overshoot is approximately 15%. The proposed CEFO algorithm can be considered an effective methodology for mathematical modelling and achievement of high quality and better performance of the designed closed-loop system for cultivation processes. Full article

Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction. In detail, the docking simulations submitted to the MEDIATE initiative are utilized to predict the viral targets involved in the hits retrieved by a recently published cytopathic screening. Multiple docking results are combined by the EFO approach to develop target-specific consensus models. The combination of multiple docking simulations enhances the performances of the developed consensus models (average increases in EF1% value of 40% and 25% when combining three and two docking runs, respectively). These models are able to propose reliable targets for about half of the retrieved hits (31 out of 59). Thus, the study emphasizes that docking simulations might be effective in target identification and provide a convincing validation for the collaborative strategies that inspire the MEDIATE initiative. Disappointingly, cross-target and cross-program correlations suggest that common scoring functions are not specific enough for the simulated target. Full article

Bond properties were performed on Ag-2.35Au-0.7Pd-0.2Pt-0.1Cu alloy wire with a diameter of 25 µm under different process parameters. The effects of electrical flaming off (EFO) current and EFO time on the deformability of the free air ball (FAB) were investigated using scanning electron microscopy (SEM), as well as the effects of ultrasonic power and bonding force on the bond characteristic. The experimental results show that FAB grows from a preheated tip to a small ball, a regular ball, and finally to a golf ball with increasing either the EFO current or the EFO time, and the FAB presents an optimal shape at 25 mA and 650 μs. Moreover, a nonlinear relationship between FAB diameter and EFO time is obtained at an EFO current of 25 mA, which could be expressed by a cubic equation. Further, at a constant bonding force, as the ultrasonic power increased, the mashed ball diameter grew larger and larger, the capillary hole imprint became more and more obvious, and the tail width also increased, and vice versa. The optimal ultrasonic power and bonding force are 70 mW and 45 gf for ball bonding and 90 mW and 75 gf for wedge bonding, respectively. Finally, for all the bonded wire samples prepared under optimal process parameters, no ball and wedge bond lifts happened after the destructive pull test, and full intermetallic compound coverage with perfect morphology occurred on the bond pad after the ball shear test, which meant that the bonded wire samples had high bond strength and hence improved the reliability of microelectronic products. It provided technical support for the reliability research of Pt-containing Ag-based bonding alloy wires. Full article

Concrete compressive strength (CCS) is among the most important mechanical characteristics of this widely used material. This study develops a novel integrative method for efficient prediction of CCS. The suggested method is an artificial neural network (ANN) favorably tuned by electromagnetic field optimization (EFO). The EFO simulates a physics-based strategy, which in this work is employed to find the best contribution of the concrete parameters (i.e., cement (C), blast furnace slag ($S_{BF}$), fly ash (${FA}_1$), water (W), superplasticizer (SP), coarse aggregate ($A_C$), fine aggregate (${FA}_2$), and the age of testing ($A_T$)) to the CCS. The same effort is carried out by three benchmark optimizers, namely the water cycle algorithm (WCA), sine cosine algorithm (SCA), and cuttlefish optimization algorithm (CFOA) to be compared with the EFO. The results show that hybridizing the ANN using the mentioned algorithms led to reliable approaches for predicting the CCS. However, comparative analysis indicates that there are appreciable distinctions between the prediction capacity of the ANNs created by the EFO and WCA vs. the SCA and CFOA. For example, the mean absolute error calculated for the testing phase of the ANN-WCA, ANN-SCA, ANN-CFOA, and ANN-EFO was 5.8363, 7.8248, 7.6538, and 5.6236, respectively. Moreover, the EFO was considerably faster than the other strategies. In short, the ANN-EFO is a highly efficient hybrid model, and can be recommended for the early prediction of the CCS. A user-friendly explainable and explicit predictive formula is also derived for the convenient estimation of the CCS. Full article

A microwave hot pressing machine (MHPM) was used to heat the colander to produce fixed oils from each of castor, sunflower, rapeseed, and moringa seed and compared them to those obtained using an ordinary electric hot pressing machine (EHPM). The physical properties, namely the moisture content of seed (MCs), the seed content of fixed oil (S_cfo), the yield of the main fixed oil (Y_mfo), the yield of recovered fixed oil (Y_rfo), extraction loss (EL), six Efficiency of fixed oil extraction (E_foe), specific gravity (SG_fo), refractive index (RI) as well as chemical properties, namely iodine number (IN), saponification value (SV), acid value (AV), and the yield of fatty acid (Y_fa) of the four oils extracted by the MHPM and EHPM were determined. Chemical constituents of the resultant oil were identified using GC/MS after saponification and methylation processes. The Ymfo and SV obtained using the MHPM were higher than those for the EHPM for all four fixed oils studied. On the other hand, each of the SG_fo, RI, IN, AV, and pH of the fixed oils did not alter statistically due to changing the heating tool from electric band heaters into a microwave beam. The qualities of the four fixed oils extracted by the MHPM were very encouraging as a pivot of the industrial fixed oil projects compared to the EHPM. The prominent fatty acid of the castor fixed oil was found to be ricinoleic acid, making up 76.41% and 71.99% contents of oils extracted using the MHPM and EHPM, respectively. In addition, the oleic acid was the prominent fatty acid in each of the fixed oils of sunflower, rapeseed, and moringa species, and its yield by using the MHPM was higher than that for the EHPM. The role of microwave irradiation in facilitating fixed oil extrusion from the biopolymeric structured organelles (lipid bodies) was protruded. Since it was confirmed by the present study that using microwave irradiation is simple, facile, more eco-friendly, cost-effective, retains parent quality of oils, and allows for the warming of bigger machines and spaces, we think it will make an industrial revolution in oil extraction field. Full article

Cloud-fog computing is a wide range of service environments created to provide quick, flexible services to customers, and the phenomenal growth of the Internet of Things (IoT) has produced an immense amount of data on a daily basis. To complete tasks and meet service-level agreement (SLA) commitments, the provider assigns appropriate resources and employs scheduling techniques to efficiently manage the execution of received IoT tasks in fog or cloud systems. The effectiveness of cloud services is directly impacted by some other important criteria, such as energy usage and cost, which are not taken into account by many of the existing methodologies. To resolve the aforementioned problems, an effective scheduling algorithm is required to schedule the heterogeneous workload and enhance the quality of service (QoS). Therefore, a nature-inspired multi-objective task scheduling algorithm called the electric earthworm optimization algorithm (EEOA) is proposed in this paper for IoT requests in a cloud-fog framework. This method was created using the combination of the earthworm optimization algorithm (EOA) and the electric fish optimization algorithm (EFO) to improve EFO’s potential to be exploited while looking for the best solution to the problem at hand. Concerning execution time, cost, makespan, and energy consumption, the suggested scheduling technique’s performance was assessed using significant instances of real-world workloads such as CEA-CURIE and HPC2N. Based on simulation results, our proposed approach improves efficiency by 89%, energy consumption by 94%, and total cost by 87% over existing algorithms for the scenarios considered using different benchmarks. Detailed simulations demonstrate that the suggested approach provides a superior scheduling scheme with better results than the existing scheduling techniques. Full article

Background: Excessive foot pronation may be attributed to an increasing burden on leg muscles during running, which might be a factor in medial tibial stress syndrome. We developed an elastic foot orthosis (EFO) that can decrease foot pronation and aimed to identify whether this orthosis could limit the increase in lower leg muscle hardness after running. Methods: Twenty-one healthy volunteers participated in this randomized crossover trial with an elastic or sham foot orthosis (SFO). All volunteers ran on a treadmill for 60 min while wearing either orthosis. Muscle hardness of the posterior lower leg was assessed using shear wave elastography before and after running. The Wilcoxon signed rank test was used to compare muscle hardness between the two orthotic conditions. Results: No significant differences were observed between the two orthotic conditions before running (p > 0.05). After running, the flexor digitorum longus (FDL) hardness in the EFO group was significantly lower than that in the SFO group (p < 0.01). No significant changes were observed in the other muscles. Conclusion: The results suggest that the EFO can restrict the increase in FDL hardness with running. The EFO may be an effective orthotic treatment for medial tibial stress syndrome. Full article

In recent years, with the continuous development of information technology, the amount of data generated and hosted by cloud service platforms in urban environments is unprecedented. Mobile edge computing (MEC) is combined with UAV networks to better realize the ability to provide nearby services to a large number of terminal devices in cities. Unmanned aerial vehicles (UAVs) are highly maneuverable and inexpensive and are good carriers for carrying MEC platforms. In UAV edge networks, we usually face the problem of fine-grained task offloading based on relevant features of urban environments. We need to address high energy consumption and task processing delays to help achieve urban sustainability goals. Therefore, we combine the software definition network (SDN) technology and, on this basis, we propose two task offloading strategies based on an improved EFO intelligent algorithm for different user scales. At the same time, we run the proposed offloading system in the UAV sensor. The experiment shows that, compared with the traditional strategy, the unloading efficiency of the proposed method can be improved by about 10%. Full article

Multilevel inverters (MLIs), both symmetrical and asymmetrical, have shown to be useful in a number of applications. Continuous improvements in output voltage waveform control and converter size reduction have made this practicable. The output voltage is managed using a low frequency modulation technique called selective harmonic elimination. This paper investigates an unique selective harmonic elimination (SHE) control that uses electromagnetic field optimization (EFO). The major features of the EFO guarantee that the targeted harmonics are removed via computation of the ideal angles, such as its easier compilation procedure and capacity for single-stage local and global searches. Additionally, a comparison with well-known algorithms namely Genetic Algorithm and Differential Evolution in accessing performance based on Total Harmonic Distortion demonstrates the EFO’s competence. The suggested algorithm’s performance has been tested using a symmetric cascaded H-Bridge MLI structure. In the MATLAB/Simulink environment, simulation analysis is performed, validating the viability of the created system. To further show the effectiveness of the suggested approach, experimental testing using low switching frequency control methods has been carried out in a dynamic setting. Full article

This study aims to investigate the effects of fish oil supplementation on the muscle adaptive response to resistance exercise training, physical performance and serum levels of inflammatory cytokines in sarcopenic older women. A randomised, double-blind, placebo-controlled trial is performed with thirty-four sarcopenic women (2010 European Consensus of Sarcopenia), aged ≥ 65 years. The participants are allocated into the following two groups: Exercise and Fish Oil (EFO) and Exercise and Placebo (EP). Both groups undertook a resistance exercise programme over 14 weeks. All participants are instructed to ingest 4 g/day of food supplements; the EP group received sunflower oil capsules, and the EFO group, fish oil capsules. The cross-sectional area (CSA) of the quadriceps muscle is calculated using magnetic resonance imaging (MRI). The strength of the lower limbs is measured using isokinetic dynamometry. Both groups show improvements in CSA and strength after the intervention. Changes in EFO are significantly greater compared with EP for muscle strength (peak torque, 19.46 Nm and 5.74 Nm, respectively, p < 0.001). CSA increased after the intervention in both groups (EFO; 6.11% and EP; 2.91%), although there is no significant difference between the groups (p = 0.23). There are no significant intra-group, inter-group or time differences in any of the cytokines measured. The use of fish oil supplementation potentiates the neuromuscular response to the anabolic stimulus from training, increasing muscle strength and physical performance in sarcopenic older women. Full article

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations. Full article