Gait recognition is a biometric technology that recognizes the identity of humans through their walking patterns. Compared with other biometric technologies, gait recognition is more difficult to disguise and can be applied to the condition of long-distance without the cooperation of subjects. Thus, it has unique potential and wide application for crime prevention and social security. At present, most gait recognition methods directly extract features from the video frames to establish representations. However, these architectures learn representations from different features equally but do not pay enough attention to dynamic features, which refers to a representation of dynamic parts of silhouettes over time (e.g. legs). Since dynamic parts of the human body are more informative than other parts (e.g. bags) during walking, in this paper, we propose a novel and high-performance framework named DyGait. This is the first framework on gait recognition that is designed to focus on the extraction of dynamic features. Specifically, to take full advantage of the dynamic information, we propose a Dynamic Augmentation Module (DAM), which can automatically establish spatial-temporal feature representations of the dynamic parts of the human body. The experimental results show that our DyGait network outperforms other state-of-the-art gait recognition methods. It achieves an average Rank-1 accuracy of 71.4% on the GREW dataset, 66.3% on the Gait3D dataset, 98.4% on the CAS1A-B dataset and 98.3% on the OU-MVLP dataset.

Microplastics (MPs) pose a profound environmental challenge, impacting ecosystems and human health through mechanisms such as bioaccumulation and ecosystem contamination. While traditional water treatment methods can partially remove microplastics, their limitations highlight the need for innovative green approaches like photodegradation to ensure more effective and sustainable removal. This review explores the potential of nanomaterial-enhanced photocatalysts in addressing this issue. Utilizing their unique properties like large surface area and tunable bandgap, nanomaterials significantly improve degradation efficiency. Different strategies for photocatalyst modification to improve photocatalytic performance are thoroughly summarized, with a particular emphasis on element doping and heterojunction construction. Furthermore, this review thoroughly summarizes the possible fundamental mechanisms driving the photodegradation of microplastics facilitated by nanomaterials, with a focus on processes like free radical formation and singlet oxygen oxidation. This review not only synthesizes critical findings from existing studies but also identifies gaps in the current research landscape, suggesting that further development of these photocatalytic techniques could lead to substantial advancements in environmental remediation practices. By delineating these novel approaches and their mechanisms, this work underscores the significant environmental implications and contributes to the ongoing development of sustainable solutions to mitigate microplastic pollution.

This study investigates the genetic determinants of seed coat color and pattern variations in cowpea (Vigna unguiculata), employing a genome-wide association approach. Analyzing a mapping panel of 296 cowpea varieties with 110,000 single nucleotide polymorphisms (SNPs), we focused on eight unique coat patterns: (1) Red and (2) Cream seed; (3) White and (4) Brown/Tan seed coat; (5) Pink, (6) Black, (7) Browneye and (8) Red/Brown Holstein. Across six GWAS models (GLM, SRM, MLM, MLMM, FarmCPU from GAPIT3, and TASSEL5), 13 significant SNP markers were identified and led to the discovery of 23 candidate genes. Among these, four specific genes may play a direct role in determining seed coat pigment. These findings lay a foundational basis for future breeding programs aimed at creating cowpea varieties aligned with consumer preferences and market requirements.

Microplastics (MPs) are a critical environmental issue, with impacts ranging from ecosystem contamination to health risks through bioaccumulation. This review addresses the inefficacy of traditional water treatments in removing MPs and proposes photodegradation, particularly via nanomaterial-enhanced photocatalysts, as a solution. Utilizing their unique properties like large surface area and tunable bandgap, nanomaterials significantly improve degradation efficiency. Different strategies for photocatalysts modification to improve photocatalytic performance are thoroughly summarized, with the particular emphasis on element doping and heterojunction construction. Furthermore, this review thoroughly summarizes the possible fundamental mechanisms driving photodegradation of microplastics facilitated by nanomaterials, with a focus on processes like free radical formation and singlet oxygen oxidation. By clearly elucidating these strategies and mechanisms, this review aims to provide valuable insights and inspire further progress in microplastic photodegradation.

Water pollution, which is intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and can potentially result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona dielectric-barrier discharge for wastewater treatment. Using the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) was achieved within 10 min by optimizing parameters such as pH and voltage. Furthermore, the mechanisms underlying the generation of reactive oxygen species through this device were discussed in detail and the degradation pathways of MB were elucidated. Moreover, this device is very energy-efficient, exhibiting a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.