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Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a 'poor man's crop', finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

During the process of cloud-to-ground lightning connection, the propagation of downward leader to the near-ground area can elevate the electric field at one or several points on the surface of ground tip object to the breakdown threshold of surrounding air, initiating one or more upward leaders, which are known as multiple upward leaders. The emergence of tall buildings has led to an increase in the number of observations of upward lightning strikes on different buildings or the same building. The presence of multiple upward leaders means that multiple parts of the building may be struck. Conducting simulation experiments to study the mechanism of the multiple upward leader phenomenon is of great significance for developing lightning protection. The relative velocity ratio of the downward and upward leaders may be one of the key factors in the lightning connection process. The relative speed ratio of leader propagation in random lightning connection mode cannot accurately describe the relative distance ratio of downward and upward leader propagation. Taking into account the optical observation facts and the electric field environment during thunderstorms, the background electric field module setting is improved on the basis of the existing three-dimensional random mode for multiple upward leaders. It also incorporates a relative propagation speed module for the downward negative and upward positive leaders, establishing the relative propagation speed of leaders according to their propagation distance. Applying the new model to simulate multiple upward leader phenomena triggered by a flat-roofed single building, compared with the previous version, parameters of the new model, such as flash distance and upward leader length, show better consistency with natural lightning. On this basis, the lightning connection process on the high-rise buildings in the Pearl River New Town is simulated, and the improved model can more accurately replicate the lightning occurrence patterns of complex buildings. Characteristic parameters of lightning strikes on urban building clusters are mainly determined by factors such as the shape characteristics, relative position, and relative height of each building. The distance at which lightning strikes buildings is positively correlated with their height. The probability of lightning strikes, the distance of lightning strikes, and other parameters of buildings with similar shapes in the same building group are relatively consistent during ground lightning activities. However, there are still special events that occur when a branch of the downward leader is in close spatial proximity to the building, causing the upward leader to initiate at the top of the building and connect to it.

Tall buildings distort the electric field of the surrounding environment, resulting in a relatively strong electric field at top corners, which affects the lightning strike process, and the protection effect that short buildings receive from tall buildings varies with the distance between them. A three-dimensional fine-resolution lightning attachment model with multiple upward leaders (LAMM) is used to simulate protection effect of a tall building and a short building with different height and distance, with an isolated building set as a control group. Experimental results show that when there is a tall building with a short building in the space and two buildings are close to each other, the distortion range of the tall building almost completely contains the distortion range of the short building, the development of downward leader is completely affected by the tall building, and the shielding effect of the tall building on the short building is significant. With the increase of the building distance, the shielding effect of the tall building on the short building decreases exponentially. When tall building is 250 m high and the short building is 150 m high, probabilities of lightning strikes on short building with distance from 50 m to 600 m with interval of 50 m are 8.3%, 15.0%, 26.5%, 36.7%, 39.5%, 47.5%, 58.9%, 57.0%, 56.0%, 57.2%, 61.0%, and 62.5%. When there is a cut-off point where the increasing trend of the probability of lightning strikes on short buildings appears to slow down significantly, the probability of lightning strikes on short building differs from its probability of lightning strikes in isolation by only 3.6%. Comparing the lightning strike results for different building distance and isolated building, the difference in lightning strike results caused by the presence of tall building decreases from 44.5% to 22.7% when the horizontal distance between tall and short buildings is increased from 400 m to 600 m. Given the height of tall building, the probability of lightning strikes on short building with different heights follows a similar trend from a large increase to a flat increase with an inflection point. Corresponding to short building height from 50 m to 200 m, the horizontal distances reaching cut-off point are 300, 450, 550 m and 600 m, respectively. When two buildings are far separated, the effect of tall building on the probability of lightning strikes on short building is weaker, and it can be assumed that there is a state when tall building have no effect on the lightning attachment process.

The scraper conveyor chain transmission system is prone to frequent faults due to its complex load bearing capacity. However, traditional fault diagnosis requires a large amount of prior knowledge and subjective intervention, which requires high technical personnel. In order to achieve the autonomy, accuracy, and efficiency of fault warning for the scraper conveyor chain transmission system, a fault warning method for the scraper conveyor chain transmission system based on LSTM-Adam is proposed using the powerful data mining capability of deep learning. Firstly, a monitoring system for the working conditions of the scraper conveyor is built based on configuration technology. The system collects real-time operating data of the scraper conveyor, such as the torque and speed of the output shaft of the reducer, the pressure of the middle groove plate, the vibration acceleration in the vertical direction of the scraper, and the strain in the running direction of the scraper chain. The data is cleaned and normalized in min-max to provide data support for fault warning. Secondly, a prediction model is built based on LSTM and trained and optimized using the Adam optimization algorithm to obtain the optimal LSTM Adam prediction model. Finally, the real-time operating data of the scraper conveyor is imported into the LSTM-Adam prediction model to obtain the predicted values of the scraper conveyor operating parameters. The sliding weighted average method is used to calculate the residual between the predicted value and the true value. The maximum residual of the same type of data under normal operating conditions is used as the warning threshold. When the residual exceeds the warning threshold, an early warning is given. The experimental results show that the LSTM-Adam prediction model can accurately predict the trend of strain data of the scraper chain and provide accurate warnings for stuck chain and broken chain faults.