Concentration-dependent effects of lithium on Daphnia magna: Life-history profiles and integrated biomarker response implementation.

The growing use of lithium (Li) in industrial and energy applications and increasing demand worldwide has inevitably resulted in its wide dispersal, representing a significant threat to aquatic systems. Unfortunately, as a ubiquitous emerging contaminant, the comprehensive toxicological information regarding Li at multifarious levels is limited. To diminish this gap, this work was focused to explore Li-induced cascading effects on Daphnia magna as a key species in freshwater ecosystems. Specifically, the organisms were chronically exposed to gradient Li concentrations with emphasis on characterizing life-history traits from individual to population scale, primarily as observed by a markedly concentration-dependent decrease along exposure gradients. In parallel, a robust set of biomarkers relating to energy reserves, antioxidant and biotransformation enzymes, cellular damage, ionoregulation and neurotoxicity were assayed for further understanding potential underlying mechanisms. As a result, biomarker alterations were characterized by significant decreases in energy storage and enzymatic profiles of antioxidant and biotransformation systems, not only triggering an imbalance between reactive oxygen species (ROS) generation and elimination under Li exposure, but compromising the fecundity fitness of phenotypical costs. In contrast, malondialdehyde (MDA) levels were remarkably enhanced as a consequence of inefficient antioxidant and biotransformation capacity leading to lipid peroxidation (LPO). Additionally, Li exerted a dose-dependent biphasic effect on the activities of superoxide dismutase (SOD), Na+,K+-ATPase and acetylcholinesterase (AChE) by interfering with inherent balance. In terms of responsive patterns and dose-effect trends, the integrated biomarker response indices (IBRv2) and star plots were consistent with the differences in biomarker profiles, not only presenting comprehensively biological effects in a visualized form, but signaling the importance of progressive induced changes in an integrative way. Overall, these findings highlighted the need for elucidating Li-produced impacts from a comprehensive perspective, providing valuable insights into better understanding the toxicity of Li in relation to aquatic ecosystem functioning and ecological relevance.

Pose Guided Person Image Generation via Dual-task Correlation and Affinity Learning.

Pose Guided Person Image Generation (PGPIG) is the task of transforming a person's image from the source pose to a target pose. Existing PGPIG methods often tend to learn an end-to-end transformation between the source image and the target image, but do not seriously consider two issues: 1) the PGPIG is an ill-posed problem, and 2) the texture mapping requires effective supervision. In order to alleviate these two challenges, we propose a novel method by incorporating Dual-task Pose Transformer Network and Texture Affinity learning mechanism (DPTN-TA). To assist the ill-posed source-to-target task learning, DPTN-TA introduces an auxiliary task, i.e., source-to-source task, by a Siamese structure and further explores the dual-task correlation. Specifically, the correlation is built by the proposed Pose Transformer Module (PTM), which can adaptively capture the fine-grained mapping between sources and targets and can promote the source texture transmission to enhance the details of the generated images. Moreover, we propose a novel texture affinity loss to better supervise the learning of texture mapping. In this way, the network is able to learn complex spatial transformations effectively. Extensive experiments show that our DPTN-TA can produce perceptually realistic person images under significant pose changes. Furthermore, our DPTN-TA is not limited to processing human bodies but can be flexibly extended to view synthesis of other objects, i.e., faces and chairs, outperforming the state-of-the-arts in terms of both LPIPS and FID. Our code is available at: https://github.com/PangzeCheung/Dual-task-Pose-Transformer-Network.

Outstanding catalytic performance in the semi-hydrogenation of acetylene in a front-end process by establishing a "hydrogen deficient" phase.

Pd-[Bmim][Cl] phase was immobilized onto Al2O3 to neutralize the excessive hydrogen in the gas phase to prevent the over-hydrogenation of acetylene, thereby achieving a high selectivity for ethylene.