Indirect punishment traditionally sustains cooperation in social systems through reputation or norms, often by reducing defectors' payoffs indirectly. In this study, we redefine indirect punishment for structured populations as a spatially explicit mechanism, where individuals on a square lattice target second-order defectors-those harming their neighbors-rather than their own immediate defectors, guided by the principle: "I help you by punishing those who defect against you". Using evolutionary simulations, we compare this adapted indirect punishment to direct punishment, where individuals punish immediate defectors. Results show that within a narrow range of low punishment costs and fines, adapted indirect punishment outperforms direct punishment in promoting cooperation. However, outside this cost-fine region, outcomes vary: direct punishment may excel, both may be equally effective, or neither improves cooperation, depending on the parameter values. These findings hold even when network reciprocity alone does not support cooperation. Notably, when adapted indirect punishment outperforms direct punishment in promoting cooperation, defectors face stricter penalties without appreciably increasing punishers' costs, making it more efficient than direct punishment. Overall, our findings provide insights into the role of indirect punishment in structured populations and highlight its importance in understanding the evolution of cooperation.

The advancement of modern clock tree synthesis (CTS) encounters a bottleneck, primarily due to the difficulty in achieving multiobjective co-optimization among complex design processes. To concurrently optimize skew, latency, and load capacitance, we propose an iterative and hierarchical CTS framework, which is composed of clustering, topology generation and routing, buffering, and optimization. First, we introduce a capacitance-based metric to achieve adaptive balanced clustering and optimize the cluster results through simulated annealing. Second, to construct a clock tree with lower latency, load capacitance, and skew, we introduce the skew-latency-load tree (SLLT), which combines the advantages of bound skew tree and Steiner shallow-light tree, and we propose an effective SLLT construction algorithm. Third, to further optimize CTS result by buffering, we introduce the critical wirelength evaluation (CWE) to evaluate the capability of each buffer, and propose the insertion delay estimation (IDE) to reduce the evaluation bias during buffering, then design the iterative skew convergence algorithm (ISCA) to achieve complete convergence of skew. We validate our solution using 28 nm process technology. Compared to our method, the commercial tool increases skew, latency, and clock capacitance by 39.5%, 13.0%, and 18.5%, respectively, while the OpenROAD by 101.6%, 50.7%, and 25.5%, respectively.

Time series anomaly detection is one of the critical tasks in time series analysis. There are many existing works using autoencoders for time series anomaly detection; however, autoencoders can not only reconstruct normal sequences but also reconstruct anomalous sequences sometimes, which leads to the poor effect of anomaly detection based on reconstruction error. At the same time, the real-world time series have the characteristic of temporal coupling, and the existing methods often cannot take into account the multiple modes of the time series, which leads to the low accuracy of time series anomaly detection. Aiming at the above problems, we propose a Time Series Anomaly Detection method incorporating Wavelet Decomposition and Temporal Decoupled Autoencoder (WDAE). Specifically, WDAE first reshapes the original 1D time series into 2D data harboring different temporal patterns based on frequency components and independently extracts the different temporal features of the time series data. Then, the original data are reconstructed in the time domain by the autoencoder to obtain the reconstructed time-domain sequence, and in the frequency domain, the 2D data are subjected to the discrete wavelet transform and the inverse wavelet transform after weight adjustment to obtain the reconstructed frequency domain sequence, and the captured normal sequence pattern in the frequency domain restricts the latent feature space in the time domain so that the autoencoder can rebuild the normal sequence to avoid reconstructing the anomalous sequence well. Experiments on five publicly available data show that WDAE significantly improves the F1 value over related state-of-the-art baseline methods.

The context of the Internet of Vehicles (IoV) and the growing vehicular deployment of sensors and smart devices have demanded alternative wireless communication technologies. Despite the prevalent works on radio-frequency (RF)-based vehicular communication technologies, visible-light communication (VLC) is envisaged to be a promising candidate due to its unlicensed spectrum and high transmission rates. However, the long-distance and high-speed transmission performance of vehicular VLC needs more investigation considering the massive data transmission needs for automotive applications. In this article, a vehicular multiple-input–multiple-output (MIMO) VLC system based on two commercial headlights and a self-designed PIN array is experimentally demonstrated as a proof of concept for the IoV. Considering the relative movement of vehicles, different communication areas are divided based on the position-dependent receiver receiving states. The boundary condition of each area is derived. For the first time, the selection of the strategy that best suits the MIMO demultiplexing scheme is discussed by analyzing the rank and type of the channel matrix. A modified pilot-aided phase recovery method based on polynomial curve fitting (PCF) is proposed to compensate for the phase noise caused by the sampling frequency offset (SFO). The proposed method maintains good robustness even when the VLC system suffers from the strong nonlinearity and bandwidth limitation of the headlights. Based on the proposed MIMO VLC system, we achieve a record-breaking data rate of 3.08 Gb/s at a 2-m indoor transmission link. We further extend the transmission distance to 100 m, and successfully achieve overall data rates of 336 and 362 Mb/s during the daytime and nighttime, respectively. To the best of our knowledge, these are the highest transmission data rates ever reported for a 100-m vehicular VLC system. Our experimental demonstration clearly verifies the feasibility of VLC in the application of IoV.