Transgenerational Effects of Sublethal Glyphosate Exposure on the Predatory Spider Pardosa pseudoannulata in Rice Fields: From Individual to Population-Level Impacts.

Glyphosate, the most widely used herbicide globally, may inadvertently affect non-target arthropods, including beneficial predators such as spiders. Here, we evaluated the lethal and sublethal effects of glyphosate on spiders (G0) and explored transgenerational impacts on their offspring (G1). Short-term exposure to LC and LC concentrations significantly altered mating behavior and reproductive output in G0 individuals.

Metabolic enhancement contributed by horizontal gene transfer is essential for dietary specialization in leaf beetles.

Horizontal gene transfer (HGT) from bacteria to insects is widely reported and often associated with the adaptation and diversification of insects. However, compelling evidence demonstrating how HGT-conferred metabolic adjustments enable species to adapt to surrounding environment remains scarce. Dietary specialization is an important ecological strategy adopted by animals to reduce inter- and intraspecific competition for limited resources.

Enhanced toxicity of entomopathogenic fungi Beauveria bassiana with bacteria expressing immune suppressive dsRNA in a leaf beetle.

The entomopathogenic fungus is recognized as an ideal alternative to chemical pesticides, nonetheless, its efficacy is often limited by insect's innate immune system. The suppression of the host immunity may overcome the obstacle and promote the toxicity of the fungi. Here, by using an entomopathogenic fungus Beauveria bassiana and immune genes dsRNA-expressing bacteria, we explored the potentially synergistic toxicity of the two agents on a leaf beetle Plagiodera versicolora (Coleoptera: Chrysomelidae).

Learned Image Compression With Gaussian-Laplacian-Logistic Mixture Model and Concatenated Residual Modules.

Recently deep learning-based image compression methods have achieved significant achievements and gradually outperformed traditional approaches including the latest standard Versatile Video Coding (VVC) in both PSNR and MS-SSIM metrics. Two key components of learned image compression are the entropy model of the latent representations and the encoding/decoding network architectures. Various models have been proposed, such as autoregressive, softmax, logistic mixture, Gaussian mixture, and Laplacian.

Comparative Analysis of Jakovlev (Hemiptera: Miridae) Immune Responses to Fungal and Bacterial Pathogens.

The wide-spread culture of transgenic Bt cotton resisting the infamous cotton bollworms has reduced the adoption of broad-spectrum insecticides to a large extent. Consequently, the non-targeted insect Jakovlev has become a major cotton pest in China. Entomopathogenic microbes show promising results for controlling this pest in the future, but innate immune responses to these pathogens are poorly understood.

Metabolic and immunological effects of gut microbiota in leaf beetles at the local and systemic levels.

Insects' intestinal microbes have profound effects on the host's physiological traits, which can impact their physiology at both the local (gut) and systemic (body) levels. Nevertheless, the molecular mechanisms underlying host-microbiota interactions, especially in non-model insects, remain elusive. Recently, tissue-specific transcriptomic analysis has been highlighted as a robust tool in studying host-microbe interactions.

Multiple description coding with prediction compensation.

A new multiple description coding paradigm is proposed by combining the time-domain lapped transform, block level source splitting, linear prediction, and prediction residual encoding. The method provides effective redundancy control and fully utilizes the source correlation. The joint optimization of all system components and the asymptotic performance analysis are presented.

Context-based entropy coding of block transform coefficients for image compression.

It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. Wavelet-based JPEG2000 is emerging as the new high-performance international standard for still image compression. An often asked question is: how much of the coding improvement is due to the transform and how much is due to the encoding strategy? Current block transform coders such as JPEG suffer from poor context modeling and fail to take full advantage of correlation in both space and frequency sense.

Wiener filter-based error resilient time-domain lapped transform.

In this paper, the design of the error resilient time-domain lapped transform is formulated as a linear minimal mean-squared error problem. The optimal Wiener solution and several simplifications with different tradeoffs between complexity and performance are developed. We also prove the persymmetric structure of these Wiener filters.

Undersampled boundary pre-/postfilters for low bit-rate DCT-based block coders.

It has been well established that critically sampled boundary pre-/postfiltering operators can improve the coding efficiency and mitigate blocking artifacts in traditional discrete cosine transform-based block coders at low bit rates. In these systems, both the prefilter and the postfilter are square matrices. This paper proposes to use undersampled boundary pre- and postfiltering modules, where the pre-/postfilters are rectangular matrices.

Error resilient pre/post-filtering for DCT-based block coding systems.

Block coding based on the discrete cosine transform (DCT) is very popular in image and video compression. Pre/post-filtering can be attached to a DCT-based block coding system to improve coding efficiency as well as to mitigate blocking artifacts. Previously designed pre/post-filters are optimized to maximize coding efficiency solely.

Optimal block boundary pre/postfiltering for wavelet-based image and video compression.

This paper presents a pre/postfiltering framework to reduce the reconstruction errors near block boundaries in wavelet-based image and video compression. Two algorithms are developed to obtain the optimal filter, based on boundary filter bank and polyphase structure, respectively. A low-complexity structure is employed to approximate the optimal solution.