Agro-voltaic (AV) systems enable the simultaneous use of land for both agriculture and solar energy generation, offering a promising solution to land-use conflicts. However, the shadows cast by solar panels present a significant challenge: while they can protect crops from excessive heat and reduce water loss, they may also limit sunlight exposure, reducing crop yield. This paper presents a method for controlling shadow placement on farmland by dynamically adjusting the azimuth and elevation angles of dual-axis solar panels. A geometric formulation is introduced to model the shadow of a rectangular panel on the ground, followed by an optimization framework that restricts the shadow to a predefined zone while ensuring minimum solar radiation within that zone over the course of a day. The proposed approach balances the goals of maximizing solar energy capture and achieving precise shadow control, using an iterative refinement method. The system is evaluated using real-world solar data from a clear day in Bari, Italy. The results demonstrate the system’s practical potential for effectively managing shading in real-world AV applications, thus enabling sustainable integration of energy generation and farming activities.

Eye movements routinely induce motion streaks as they shift visual projections across the retina at high speeds. To investigate the visual consequences of intra-saccadic motion streaks, we co-registered eye tracking and EEG while gaze-contingently shifting target objects during saccades, presenting either continuous, 'streaky' or apparent, step-like motion in four directions. We found significant reductions of secondary saccade latency, as well as improved decoding of the post-saccadic target location from the EEG signal when motion streaks were available. These signals arose as early as 50 ms after saccade offset and had a clear occipital topography. Using a physiologically plausible visual processing model, we provide evidence that the target's motion trajectory is coded in orientation-selective channels and that speed of gaze correction was linked to the visual dynamics arising from the combination of saccadic and target motion, providing a parsimonious explanation of the behavioral benefits of intra-saccadic motion streaks.

In this paper, we formulate a notion of diagnosability for labeled weighted automata over a class of dioids which admit both positive and negative numbers as well as vectors. The weights can represent diverse physical meanings such as time elapsing and position deviations. We also develop an original tool called concurrent composition to verify diagnosability for such automata. These results are fundamentally new compared with the existing ones in the literature. In a little more detail, diagnosability is characterized for a labeled weighted automaton A D p over a special dioid D p called progressive , which can represent diverse physical meanings such as time elapsing and position deviations. In a progressive dioid, the canonical order is total, there is at least one eventually dominant element, there is no zero divisor, and the cancellative law is satisfied, where the functionality of an eventually dominant element t is to make every nonzero element a arbitrarily large by multiplying a by t for sufficiently many times. A notion of diagnosability is formulated for A D p . By developing a notion of concurrent composition , a necessary and sufficient condition is given for diagnosability of automaton A D p . It is proven that the problem of computing the concurrent composition for an automaton A Q _ is NP -complete, then the problem of verifying diagnosability of A Q _ is proven to be coNP -complete, where the NP -hardness and coNP -hardness results even hold for deterministic, deadlock-free, and divergence-free automaton A N _ , where Q _ and N _ are the max-plus dioids having elements in Q ∪ { − ∞ } and N ∪ { − ∞ } , respectively. Several extensions of the main results have also been obtained.

In this paper the application of Nonlinear Model Predictive Control (NMPC) to a chemical reactor, namely the Open Plate Reactor(OPR), is considered. A control strategy which allows a safe start-up operation of the reactor and provides an easy handling of system restrictions and nonlinearities, is proposed. An efficient open-loop parameterization of the control signals is used to further reduce the size of the optimization variables. It is shown that the NMPC algorithm developed gives satisfactory operation and the reduced open loop parameterization results in a sufficiently rich closed loop behavior.