Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformers

Biological systems in nature have evolved for millions of years to adapt and survive the environment. Many features they developed can be inspirational and beneficial for solving technical problems in modern industries. This leads to a specific form of design-by-analogy called bio-inspired design (BID). Although BID as a design method has been proven beneficial, the gap between biology and engineering continuously hinders designers from effectively applying the method. Therefore, we explore the recent advance of artificial intelligence (AI) for a data-driven approach to bridge the gap. This paper proposes a generative design approach based on the generative pre-trained language model (PLM) to automatically retrieve and map biological analogy and generate BID in the form of natural language. The latest generative pre-trained transformer, namely GPT-3, is used as the base PLM. Three types of design concept generators are identified and fine-tuned from the PLM according to the looseness of the problem space representation. Machine evaluators are also fine-tuned to assess the mapping relevancy between the domains within the generated BID concepts. The approach is evaluated and then employed in a real-world project of designing light-weighted flying cars during its conceptual design phase The results show our approach can generate BID concepts with good performance.Comment: Accepted by J. Mech. Des. arXiv admin note: substantial text overlap with arXiv:2204.0971

Reconstructing Sparse Illicit Supply Networks: A Case Study of Multiplex Drug Trafficking Networks

The network structure provides critical information for law enforcement agencies to develop effective strategies to interdict illicit supply networks. However, the complete structure of covert networks is often unavailable, thus it is crucially important to develop approaches to infer a more complete structure of covert networks. In this paper, we work on real-world multiplex drug trafficking networks extracted from an investigation report. A statistical approach built on the EM algorithm (DegEM) as well as other methods based on structural similarity are applied to reconstruct the multiplex drug trafficking network given different fractions of observed nodes and links. It is found that DegEM approach achieves the best predictive performance in terms of several accuracy metrics. Meanwhile, structural similarity-based methods perform poorly in reconstructing the drug trafficking networks due to the sparsity of links between nodes in the network. The inferred multiplex networks can be leveraged to (i) inform the decision-making on monitoring covert networks as well as allocating limited resources for collecting additional information to improve the reconstruction accuracy and (ii) develop more effective interdiction strategies

Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model

To predict regional-scale winter wheat yield, we developed a crop model and data assimilation framework that assimilated leaf area index (LAI) derived from Landsat TM and MODIS data into the WOFOST crop growth model. We measured LAI during seven phenological phases in two agricultural cities in China’s Hebei Province. To reduce cloud contamination, we applied Savitzky–Golay (S–G) filtering to the MODIS LAI products to obtain a filtered LAI. We then regressed field-measured LAI on Landsat TM vegetation indices to derive multi-temporal TM LAIs. We developed a nonlinear method to adjust LAI by accounting for the scale mismatch between the remotely sensed data and the model’s state variables. The TM LAI and scale-adjusted LAI datasets were assimilated into the WOFOST model to allow evaluation of the yield estimation accuracy. We constructed a four-dimensional variational data assimilation (4DVar) cost function to account for the observations and model errors during key phenological stages. We used the shuffled complex evolution–University of Arizona algorithm to minimize the 4DVar cost function between the remotely sensed and modeled LAI and to optimize two important WOFOST parameters. Finally, we simulated winter wheat yield in a 1-km grid for cells with at least 50% of their area occupied by winter wheat using the optimized WOFOST, and aggregated the results at a regional scale. The scale adjustment substantially improved the accuracy of regional wheat yield predictions (R2 = 0.48; RMSE= 151.92 kg ha−1) compared with the unassimilated results (R2 = 0.23;RMSE= 373.6 kg ha−1) and the TM LAI results (R2 = 0.27; RMSE= 191.6 kg ha−1). Thus, the assimilation performance depends strongly on the LAI retrieval accuracy and the scaling correction. Our research provides a scheme to employ remotely sensed data, ground-measured data, and a crop growth model to improve regional crop yield estimates

Joint retrieval of growing season corn canopy LAI and leaf chlorophyll content by fusing Sentinel-2 and MODIS images

Continuous and accurate estimates of crop canopy leaf area index (LAI) and chlorophyll content are of great importance for crop growth monitoring. These estimates can be useful for precision agricultural management and agricultural planning. Our objectives were to investigate the joint retrieval of corn canopy LAI and chlorophyll content using filtered reflectances from Sentinel-2 and MODIS data acquired during the corn growing season, which, being generally hot and rainy, results in few cloud-free Sentinel-2 images. In addition, the retrieved time series of LAI and chlorophyll content results were used to monitor the corn growth behavior in the study area. Our results showed that: (1) the joint retrieval of LAI and chlorophyll content using the proposed joint probability distribution method improved the estimation accuracy of both corn canopy LAI and chlorophyll content. Corn canopy LAI and chlorophyll content were retrieved jointly and accurately using the PROSAIL model with fused Kalman filtered (KF) reflectance images. The relation between retrieved and field measured LAI and chlorophyll content of four corn-growing stages had a coefficient of determination (R2) of about 0.6, and root mean square errors (RMSEs) ranges of mainly 0.1-0.2 and 0.0-0.3, respectively. (2) Kalman filtering is a good way to produce continuous high-resolution reflectance images by synthesizing Sentinel-2 and MODIS reflectances. The correlation between fused KF and Sentinel-2 reflectances had an R2 value of 0.98 and RMSE of 0.0133, and the correlation between KF and field-measured reflectances had an R2 value of 0.8598 and RMSE of 0.0404. (3) The derived continuous KF reflectances captured the crop behavior well. Our analysis showed that the LAI increased from day of year (DOY) 181 (trefoil stage) to DOY 236 (filling stage), and then increased continuously until harvest, while the chlorophyll content first also increased from DOY 181 to DOY 236, and then remained stable until harvest. These results revealed that the jointly retrieved continuous LAI and chlorophyll content could be used to monitor corn growth conditions

Synergistic adsorption of Cd(II) with sulfate/phosphate on ferrihydrite: An in situ ATR-FTIR/2D-COS study

Elucidation of the co-adsorption characteristics of heavy metal cations and oxyanions on (oxyhydr)oxides can help to better understand their distribution and transformation in many geological settings. In this work, batch adsorption experiments in combination with in situ attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) were applied to explore the interaction mechanisms of Cd(II) with sulfate or phosphate at the ferrihydrite (Fh)–water interface, and the two-dimensional correlation spectroscopic analysis (2D–COS) was used to enhance the resolution of ATR-FTIR bands and the accuracy of analysis. The batch adsorption experiments showed enhanced adsorption of both sulfate (S) and phosphate (P) on Fh when co-adsorbed with Cd(II); additionally, the desorbed percentages of Cd(II) were much lower in the P + Cd adsorption systems than those in the S + Cd adsorption systems. The spectroscopic results suggested that in the single adsorption systems, sulfate primarily adsorbed as outer-sphere complexes with a small amount of bidentate inner-sphere complexes, while the dominant adsorbed species of phosphate were largely the bidentate nonprotonated inner-sphere complexes, although there was significant pH-dependence. In the co-adsorption systems, the synergistic adsorption of Cd(II) and sulfate was dominantly attributed to the electrostatic interaction, as well as the formation of Fe–Cd–S (i.e., Cd-bridged) ternary complexes. In contrast, Fe–P–Cd (i.e., phosphate-bridged) ternary complexes were found in all of the co-adsorption systems of phosphate and Cd(II); furthermore, electrostatic interaction should also contribute to the co-adsorption process. Our results show that in situ ATR-FTIR in combination with 2D–COS can be an efficient tool in analyzing the co-adsorption mechanisms of anions and heavy metal cations on iron (oxyhydr)oxides in ternary adsorption systems. The co-existence of Cd(II) with sulfate or phosphate can be beneficial for their accumulations on Fh, and phosphate is more efficient than sulfate for the long-term immobilization of Cd(II)

Impact of in-cloud aqueous processes on the chemical compositions and morphology of individual atmospheric aerosols

The composition, morphology, and mixing structure of individual cloud residues (RES) and interstitial particles (INT) at a mountaintop site were investigated. Eight types of particles were identified, including sulfate-rich (S-rich), S-organic matter (OM), aged soot, aged mineral dust, aged fly ash, aged metal, refractory, and aged refractory mixture. A shift of dominant particle types from S-rich (29 %) and aged soot (27 %) in the INT to aged refractory mixture (23 %) and S-OM (22 %) in the RES is observed. In particular, particles with organic shells are enriched in the RES (27 %) relative to the INT (12 %). Our results highlight that the formation of more oxidized organic matter in the cloud contributes to the existence of organic shells after cloud processing. The fractal dimension (D$_{f}$), a morphologic parameter to represent the branching degree of particles, for soot particles in the RES (1.82 ± 0.12) is lower than that in the INT (2.11 ± 0.09), which indicates that in-cloud processes may result in less compact soot. This research emphasizes the role of in-cloud processes in the chemistry and microphysical properties of individual particles. Given that organic coatings may determine the particle hygroscopicity, activation ability, and heterogeneous chemical reactivity, the increase of OM-shelled particles upon in-cloud processes should have considerable implications