Polarity Information Coded Flip-OFDM for Intensity Modulated Systems

A polarity-information-coded flip orthogonal frequency division multiplexing (PIC-flip-OFDM) is proposed for intensity modulation/direct detection (IM/DD) optical communications in this letter. In the proposed scheme, the modulated signals in the frequency domain are not constrained to have Hermitian symmetry. The real and imaginary parts of the timedomain complex signals are separated, and the polarities of the real and imaginary parts are jointly encoded and modulated. The transmit strategy and the receive algorithm of the proposed scheme are analyzed in detail. The major advantage of the proposed scheme is that its spectral and optical power efficiencies are higher than existing schemes, which is validated in simulation

Receiver Algorithms for Single-Carrier OSM Based High-Rate Indoor Visible Light Communications

In intensity-modulation and direct-detection (IM/DD) multiple-input and multiple-output (MIMO) visible light communication (VLC) systems, spatial subchannels are usually correlated, and spatial modulation is a good choice to achieve the advantages of MIMO technology. Peak-to-average power ratio (PAPR) is a key issue in VLCs due to the limited linear dynamic range of light emitting diodes (LEDs). Single-carrier communication systems have a lower PAPR than orthogonal frequency division multiplexing (OFDM) communication systems. However, it is challenging to design a single-carrier spatial modulation for high-rate transmissions because of the time domain intersymbol interference. This paper develops an optical spatial modulation (OSM) scheme based on bipolar pulse amplitude modulation (PAM) and spatial elements for high-rate indoor VLC systems. Multiple data streams can be transmitted simultaneously in the proposed scheme. Based on the transmit strategy, we develop a low-complexity receiver algorithm that achieves better bit-error rate performance than reference schemes, and the proposed OSM scheme has a much lower PAPR than OFDM based OSM schemes. When the spatial subchannels are highly correlated, a spatial area division strategy is applied, and the receiver algorithm is investigated. The symbol-error rate expression of the proposed OSM scheme is derived, and the computational complexity is analyzed

Low-crystallinity to highly amorphous copolyesters with high glass transition temperatures based on rigid carbohydrate-derived building blocks

The current trend of developing novel biobased polymeric materials is focused more on utilizing the unique structural/physical properties of renewable building blocks towards niche market applications. In this work, with the aim of developing low-crystallinity to amorphous polyesters with enhanced thermal properties, a series of copolyesters based on rigid and structurally asymmetric carbohydrate-derived building blocks, namely furan-2,5-dicarboxylic acid and isosorbide, and 1,4-butanediol were successfully synthesized using melt polycondensation. The copolyesters were obtained with varied chemical compositions and rather high molecular weights (Mn = 24 000–31 000 g mol−1) and intrinsic viscosities ([η] = 0.56–0.72 dL g−1). Incorporation of both building blocks significantly enhances the glass transition temperatures (Tg = 38–107 °C) of polyesters, and also efficiently inhibits the crystallization of the copolyesters. A low content of isosorbide (ca 10 mol%) leads to complete transition of the homopolyester to nearly fully amorphous materials. Detailed characterizations of the chemical structures and thermal properties of the synthesized copolyesters were conducted using various analytical techniques. In addition, hydrolytic and enzymatic degradations of the copolymers in the presence of porcine pancreatic lipase and cutinase were also investigated

EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language Models

Vision-language models (VLMs) have recently shown promising results in traditional downstream tasks. Evaluation studies have emerged to assess their abilities, with the majority focusing on the third-person perspective, and only a few addressing specific tasks from the first-person perspective. However, the capability of VLMs to "think" from a first-person perspective, a crucial attribute for advancing autonomous agents and robotics, remains largely unexplored. To bridge this research gap, we introduce EgoThink, a novel visual question-answering benchmark that encompasses six core capabilities with twelve detailed dimensions. The benchmark is constructed using selected clips from egocentric videos, with manually annotated question-answer pairs containing first-person information. To comprehensively assess VLMs, we evaluate eighteen popular VLMs on EgoThink. Moreover, given the open-ended format of the answers, we use GPT-4 as the automatic judge to compute single-answer grading. Experimental results indicate that although GPT-4V leads in numerous dimensions, all evaluated VLMs still possess considerable potential for improvement in first-person perspective tasks. Meanwhile, enlarging the number of trainable parameters has the most significant impact on model performance on EgoThink. In conclusion, EgoThink serves as a valuable addition to existing evaluation benchmarks for VLMs, providing an indispensable resource for future research in the realm of embodied artificial intelligence and robotics

A dynamic homogenization model for long-wavelength wave propagation in corrugated sandwich plates

In the present work, a new dynamic homogenization model is developed to investigate the long-wavelength wave propagation in a corrugated sandwich plate. With the harmonic motion assumption and using a shifting operator, the governing equations of the plate are firstly represented in a state-space form. Then, a dynamic homogenization model is developed via the two-scale homogenization method. Based on this model and considering the propagation of sinusoidal waves, the dispersion relations and corresponding wave modes can be easily obtained. In order to validate the developed homogenization model, the obtained dispersion relations are compared with those predicted by the spectral element method. It is found that the present method gives accurate results in low frequency range. Furthermore, the effects of some geometric and material parameters on the dispersion relations for the corrugated sandwich plate are also discussed. The developed homogenization model is expected to be helpful in the prediction and control of dynamic responses of corrugated or even lattice sandwich structures

Rethinking Causal Relationships Learning in Graph Neural Networks

Graph Neural Networks (GNNs) demonstrate their significance by effectively modeling complex interrelationships within graph-structured data. To enhance the credibility and robustness of GNNs, it becomes exceptionally crucial to bolster their ability to capture causal relationships. However, despite recent advancements that have indeed strengthened GNNs from a causal learning perspective, conducting an in-depth analysis specifically targeting the causal modeling prowess of GNNs remains an unresolved issue. In order to comprehensively analyze various GNN models from a causal learning perspective, we constructed an artificially synthesized dataset with known and controllable causal relationships between data and labels. The rationality of the generated data is further ensured through theoretical foundations. Drawing insights from analyses conducted using our dataset, we introduce a lightweight and highly adaptable GNN module designed to strengthen GNNs' causal learning capabilities across a diverse range of tasks. Through a series of experiments conducted on both synthetic datasets and other real-world datasets, we empirically validate the effectiveness of the proposed module

Channel Estimation for Multicell Multiuser Massive MIMO Uplink Over Rician Fading Channels

Pilot contamination (PC) is a major problem in massive multiple-input multiple-output (MIMO) systems. This paper proposes a novel channel estimation scheme for such a system in Rician fading channels. First, the possible angle of arrivals (AOAs) of users served by a base station (BS) are derived by exploiting the channel statistical information, assuming a traditional pilot structure, where the pilots for the same-cell users are orthogonal but are identical for the same-indexed users from different cells. Although with this pilot structure the channel state information (CSI) derived contains CSI from other-cell users caused by PC, the line-of-sight (LOS) component of the desired user is PC-free when the number of antennas equipped at the BS is large. Then, based on the AOAs and the contaminated CSI, the LOS component of each user served by a BS is estimated, and data are detected by using the derived LOS components. Finally, the decoded data are used to update the CSI estimate via an iterative process. The achievable spectral efficiency of the proposed scheme is analyzed in detail, and simulation results are presented to compare the performance of the proposed scheme with that of three existing schemes