Adaptive dynamic programming for containment control with robustness analysis to iterative error: A global Nash equilibrium solution.

Global Nash equilibrium is an optimal solution for each player in a graphical game. This paper proposes an iterative adaptive dynamic programming-based algorithm to solve the global Nash equilibrium solution for optimal containment control problem with robustness analysis to the iterative error. The containment control problem is transferred into the graphical game formulation. Sufficient conditions are given to decouple the Hamilton-Jacobi equations, which guarantee the solvability of the global Nash equilibrium solution. The iterative algorithm is designed to obtain the solution without any knowledge of system dynamics. Conditions of iterative error for global stability are given with rigorous proof. Compared with existing works, the design procedures of control gain and coupling strength are separated, which avoids trivial cases in the design procedure. The robustness analysis exactly quantifies the effect of the iterative error caused by various sources in engineering practice. The theoretical results are validated by two numerical examples with marginally stable and unstable dynamics of the leader.

Enhancing rice ecological production: synergistic effects of wheat-straw decomposition and microbial agents on soil health and yield.

Aims: This study evaluated the impact of wheat straw return and microbial agent application on rice field environments. Methods: Using Rice variety Chuankangyou 2115 and a microbial mix of Bacillus subtilis and Trichoderma harzianum. Five treatments were tested: T1 (no straw return), T2 (straw return), T3, T4, and T5 (straw return with varying ratios of Bacillus subtilis and Trichoderma harzianum). Results: Results indicated significant improvements in rice root length, surface area, dry weight, soil nutrients, and enzyme activity across T2-T5 compared to T1, enhancing yield by 3.81-26.63%. T3 (50:50 microbial ratio) was optimal, further increasing root dry weight, soil enzyme activity, effective panicle and spikelet numbers, and yield. Dominant bacteria in T3 included MBNT15, Defluviicoccus, Rokubacteriales, and Latescibacterota. Higher Trichoderma harzianum proportions (75% in T5) increased straw decomposition but slightly inhibited root growth. Correlation analysis revealed a significant positive relationship between yield and soil microorganisms like Gemmatimonadota and Firmicutes at the heading stage. Factors like dry root weight, straw decomposition rate post-jointing stage, and elevated soil enzyme activity and nutrient content from tiller to jointing stage contributed to increased panicle and spikelet numbers, boosting yield. Conclusion: The optimal Bacillus subtilis and Trichoderma harzianum ratio for straw return was 50:50, effectively improving soil health and synergizing high rice yield with efficient straw utilization.

Optimal synchronization with L2-gain performance: An adaptive dynamic programming approach.

This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton-Jacobi-Isaacs equation is derived by the performance index function and system dynamics, which serves as an equivalent formulation. Distributed policy iteration adaptive dynamic programming is developed to obtain the numerical solution to the Hamilton-Jacobi-Isaacs equation. Three theoretical results are given about the proposed algorithm. First, the iterative variables is proved to converge to the solution to Hamilton-Jacobi-Isaacs equation. Second, the L2-gain performance of the closed loop system is achieved. As a special case, the origin of the nominal system is asymptotically stable. Third, the obtained control protocol constitutes an Nash equilibrium solution. Neural network-based implementation is designed following the main results. Finally, two numerical examples are provided to verify the effectiveness of the proposed method.

ACcoding: A graph-based dataset for online judge programming.

A well-designed educational programming dataset is a valuable asset for students and educators. Such a dataset enables students to improve their programming performances continuously, provides researchers with significant data sources to identify students' learning behaviours and enhance the quality of programming education. Several existing datasets for programming education are either limited by a small number of participating students or a short span of learning records, bringing great challenges to investigate students' learning patterns in programming. We present a graph-based large-scale dataset specialized in programming learning on Online Judge (OJ) platform. The dataset, named ACcoding, was built by a university teaching group. As of the submission date of the initial manuscript of this paper (May 6, 2022), the dataset contains 4,046,652 task-solving records submitted by 27,444 students on 4,559 programming tasks over a span of 6 years. The large size of the dataset, combined with rich functional features, empowers educators to trace students' programming progress and choose appropriate programming tasks for specific training purposes. We also presents examples of applications used by the dataset.

Effects of postponing nitrogen topdressing on starch structural properties of superior and inferior grains in hybrid indica rice cultivars with different taste values.

Introduction: Nitrogen (N) fertilizer management, especially postponing N topdressing can affect rice eating quality by regulating starch quality of superior and inferior grains, but the details are unclear. This study aimed to evaluate the effects of N topdressing on starch structure and properties of superior and inferior grains in hybrid indica rice with different tastes and to clarify the relationship between starch structure, properties, and taste quality. Methods: Two hybrid indica rice varieties, namely the low-taste Fyou 498 and high-taste Shuangyou 573, were used as experimental materials. Based on 150 kg·N hm-2, three N fertilizer treatments were established: zero N (N0), local farmer practice (basal fertilizer: tillering fertilizer: panicle fertilizer=7:3:0) (N1), postponing N topdressing (basal fertilizer: tillering fertilizer: panicle fertilizer=3:1:6) (N2). Results: The starch granules of superior grains were more complete, and the decrease in small granules content and the stability of starch crystals were a certain extent less than those of inferior grains. Compared with N1, under N2, low-taste and high-taste varieties large starch granules content were significantly reduced by 6.89%, 0.74% in superior grains and 4.26%, 2.71% in inferior grains, the (B2 + B3) chains was significantly reduced by 1.61%, 0.98% in superior grains, and 1.18%, 0.97% in inferior grains, both reduced the relative crystallinity and 1045/1022 cm-1, thereby decreasing the stability of the starch crystalline region and the orderliness of starch granules. N2 treatment reduced the ΔHgel of two varieties. These changes ultimately contributed to the enhancement of the taste values in superior and inferior grains in both varieties, especially the inferior grains. Correlation analysis showed that the average starch volume diameter (D[4,3]) and relative crystallinity were significantly positively correlated with the taste value of superior and inferior sgrains, suggesting their potential use as an evaluation index for the simultaneous enhancement of the taste value of rice with superior and inferior grains. Discussion: Based on 150 kg·N hm-2, postponing N topdressing (basal fertilizer: tillering fertilizer: panicle fertilizer=3:1:6) promotes the enhancement of the overall taste value and provides theoretical information for the production of rice with high quality.

ZIP Genes Are Involved in the Retransfer of Zinc Ions during the Senescence of Zinc-Deficient Rice Leaves.

Rice lacks sufficient amounts of zinc despite its vitality for human health. Leaf senescence enables redistribution of nutrients to other organs, yet Zn retransfer during deficiency is often overlooked. In this hydroponic experiment, we studied the effect of Zn deficiency on rice seedlings, focusing on the fourth leaf under control and deficient conditions. Growth phenotype analysis showed that the growth of rice nodal roots was inhibited in Zn deficiency, and the fourth leaf exhibited accelerated senescence and increased Zn ion transfer. Analyzing differentially expressed genes showed that Zn deficiency regulates more ZIP family genes involved in Zn ion retransfer. OsZIP3 upregulation under Zn-deficient conditions may not be induced by Zn deficiency, whereas OsZIP4 is only induced during Zn deficiency. Gene ontology enrichment analysis showed that Zn-deficient leaves mobilized more biological pathways (BPs) during aging, and the enrichment function differed from that of normal aging leaves. The most apparent "zinc ion transport" BP was stronger than that of normal senescence, possibly due to Zn-deficient leaves mobilizing large amounts of BP related to lipid metabolism during senescence. These results provide a basis for further functional analyses of genes and the study of trace element transfer during rice leaf senescence.

Improving the yield and nitrogen use efficiency of hybrid rice through rational use of controlled-release nitrogen fertilizer and urea topdressing.

Introduction: Controlled-release fertilizers effectively improve crop yield and nitrogen use efficiency (NUE). However, their use increases the cost of crop production. Optimal management modes involving urea replacement with controlled-release N fertilizers to increase rice yield through enhanced NUE are not widely explored. Methods: Field experiments were conducted from 2017 to 2018 to determine the effects of different controlled-release N fertilizers combined with urea [urea-N (180 kg ha-1, N1)]. We used controlled-release N (150 kg ha-1, N2) as the base, and four controlled-release N and urea-N ratio treatments [(80%:0% (N3), 60%:20% (N4), 40%:40% (N5), or 20%:60% (N6) as the base with 20% urea-N as topdressing at the panicle initiation stage under 150 kg ha-1] to study their impact on the grain yield and NUE of machine-transplanted rice. Results and discussion: Grain yield and NUE were positively correlated with increases in photosynthetic production, flag leaf net photosynthetic rate (Pn), root activity, N transport, and grain-filling characteristics. The photosynthetic potential and population growth rate from the jointing to the full-heading stage, highly effective leaf area index (LAI) rate and Pn at the full-heading stage, root activity at 15 d after the full-heading stage, and N transport in the leaves from the full-heading to mature stage were significantly increased by the N4 treatment, thereby increasing both grain yield and NUE. Furthermore, compared with the other N treatments, the N4 treatment promoted the mean filling rate of inferior grains, which is closely related to increased filled grains per spikelet and filled grains rate. These effects ultimately improved the grain yield (5.03-25.75%), N agronomic efficiency (NAE, 3.96-17.58%), and N partial factor productivity (NPP, 3.98-27.13%) under the N4 treatment. Thus, the N4 treatment with controlled-release N (60%) and urea-N (20%) as a base and urea-N (20%) as topdressing at the panicle-initiation stage proved effective in improving the grain yield and NUE of machine-transplanted hybrid indica rice. These findings offer a theoretical and practical basis for enhancing rice grain yield, NUE, and saving the cost of fertilizer.

Finite-time consensus control for multi-agent systems with full-state constraints and actuator failures.

Aiming at a class of uncertain nonlinear multi-agent systems (MASs) with full-state constraints and actuator failures, a finite-time consensus control method is developed. Full-state constraints and actuator failures are ubiquitous in practical engineering applications. Violation of constraints would drastically affect the performance of MASs, even arise security problems. It is challenging to guarantee the performance of the MASs when undergoing actuator failures. To tackle these problems, an adaptive consensus control method is established by applying the Backstepping technique and Barrier Lyapunov functions (BLFs) to ensure the performance of the MASs with full-state constraints no matter actuator failures occur. Simultaneously, for the uncertain nonlinear MASs, a finite-time neural network (NN) consensus control scheme is established to ensure system's signals are synchronized in finite time. Moreover, an event-triggered control strategy is constructed to relieve the communication pressure of each agent. Finally, numerical and practical examples are employed to verify the effectiveness of the proposed control strategy.

Comparison of Four Electrical Interfacing Circuits in Frequency Up-Conversion Piezoelectric Energy Harvesting.

Efficiently scavenging piezoelectric vibration energy is attracting a lot of interest. One important type is the frequency up-conversion (FUC) energy harvester, in which a low-frequency beam (LFB) impacts a high-frequency beam (HFB). In this paper, four interface circuits, standard energy harvesting (SEH), self-powered synchronous electric charge extraction (SP-SECE), self-powered synchronized switch harvesting on inductor (SP-SSHI) and self-powered optimized SECE (SP-OSECE), are compared while rectifying the generated piezoelectric voltage. The efficiencies of the four circuits are firstly tested at constant displacement and further analyzed. Furthermore, the harvested power under FUC is tested for different electromechanical couplings and different load values. The results show that SP-OSECE performs best in the case of a weak coupling or low-load resistance, for which the maximum power can be 43% higher than that of SEH. As the coupling level increases, SP-SSHI becomes the most efficient circuit with a 31% higher maximum power compared to that of SEH. The reasons for the variations in each circuit with different coupling coefficients are also analyzed.

Event-triggered H∞ consensus for uncertain nonlinear systems using integral sliding mode based adaptive dynamic programming.

This paper studies a robust optimal consensus problem for uncertain nonlinear multi-agent systems, where the uncertainties include both input and external disturbances. Adaptive distributed observer, integral sliding mode control and H∞ adaptive dynamic programming are integrated to obtain a sub-optimal control protocol for each follower. Firstly, an adaptive distributed observer is designed for state estimation of the leader, which serves as the reference of the ADP algorithm. Then, an H∞ ADP algorithm is presented to make each follower track the reference in real-time. An integral sliding manifold-based discontinuous control is designed to eliminate the matched uncertainty, and continuous control is obtained by solving the Hamilton-Jacobi-Isaac equation under the H∞ tracking framework. Two event-triggered rules are developed to relieve the communication pressure. For simplicity, a critic-only structure is used to numerically implement the proposed algorithm, and a concurrent learning technique is employed to update weights of neural networks. All signals in the closed-loop system are proven to be uniformly ultimately bounded. Finally, a simulation is conducted to demonstrate demonstrates the effectiveness of the method.

Glandular Odontogenic Cyst Associated with Odontoma: A Rare Case Report.

Background: Glandular odontogenic cyst (GOC) is an extremely rare developmental jawbone cyst, tending to recurrence owing to its aggressive behavior. There has been no reported case of presence of GOC simultaneous with odontoma. We presented a case of GOC associated with odontoma with special reference to the diagnostic imaging and the histopathological features. Case Presentation: A 42-year-old Chinese man presented with swelling and pain in the anterior mandible for the past 3 months. Panoramic scan showed a large multiocular well-circumscribed radiolucency accompanied by toothlike morphological abnormality. Histological findings confirmed a GOC associated with odontoma. Conclusion: This case demonstrates GOC with multiple clinical spectrum, and its association with odontoma might enhance the existing knowledge of this rare jawbone cyst.

Prescribed performance adaptive event-triggered consensus control for multiagent systems with input saturation.

In this paper, a prescribed performance adaptive event-triggered consensus control method is developed for a class of multiagent systems with the consideration of input dead zone and saturation. In practical engineering applications, systems are inevitably suffered from input saturation. In addition, input dead zone is widely existing. As the larger signal is limited and the smaller signal is difficult to effectively operate, system efficacious input encounters unknown magnitude limitations, which seriously impact system control performance and even lead to system instability. Furthermore, when constrained multiagent systems are required to converge quickly, the followers would achieve it with drastic and quick variation of states, which may violate the constraints and even cause security problems. To address those problems, an adaptive event-triggered consensus control is proposed. By constructing the transform function and the barrier Lyapunov function, while state constrained is guaranteed, multiagent systems quickly converge with prescribed performance. Finally, some examples are adopted to confirm the effectiveness of the proposed control method.