Learning Rich Feature Representation and State Change Monitoring for Accurate Animal Target Tracking.

Animal tracking is crucial for understanding migration, habitat selection, and behavior patterns. However, challenges in video data acquisition and the unpredictability of animal movements have hindered progress in this field. To address these challenges, we present a novel animal tracking method based on correlation filters. Our approach integrates hand-crafted features, deep features, and temporal context information to learn a rich feature representation of the target animal, enabling effective monitoring and updating of its state. Specifically, we extract hand-crafted histogram of oriented gradient features and deep features from different layers of the animal, creating tailored fusion features that encapsulate both appearance and motion characteristics. By analyzing the response map, we select optimal fusion features based on the oscillation degree. When the target animal's state changes significantly, we adaptively update the target model using temporal context information and robust feature data from the current frame. This updated model is then used for re-tracking, leading to improved results compared to recent mainstream algorithms, as demonstrated in extensive experiments conducted on our self-constructed animal datasets. By addressing specific challenges in animal tracking, our method offers a promising approach for more effective and accurate animal behavior research.

Person re-identification based on multi-branch visual transformer and self-distillation.

Person re-identification technology has made significant progress in recent years with the development of deep learning. However, the recognition rate of models in this field is still lower than that of face recognition, which is challenging to implement in practical application scenarios. Therefore, improving the recognition rate of the pedestrian re-identification model is still a critical task. This paper mainly focuses on three aspects of this problem. The first is to use the characteristics of the multi-branch network structure of person re-identification to dig out the most effective online self-distillation scheme between branches without increasing additional resource requirements, making full use of the information contained in each branch. Secondly, this paper analyzes and verifies the pros and cons of knowledge distillation based on mean squared error (MSE) loss function and Kullback-Leibler (KL) divergence from theoretical and experimental perspectives. Finally, we verified through experiments that adding a specific value of noise perturbation to the model weights can further improve the recognition rate of the model. After several improvements in these areas, we obtained the current state-of-the-art performance on four public datasets for person re-identification.

Heterobimetallic rare earth metal-zinc catalysts for reactions of epoxides and CO2 under ambient conditions.

Four homodinuclear rare earth metal (RE) complexes 1-4 bearing a multidentate diglycolamine-bridged bis(phenolate) ligand were synthesized. In addition, seven heterobimetallic RE-Zn complexes 5-11 were prepared through a one-pot strategy. In these heterobimetallic complexes, two RE centers are bridged by either Zn(OAc)2 or Zn(OBn)2 moieties. All complexes were characterized by single crystal X-ray diffraction, elemental analysis, IR spectroscopy, and multinuclear NMR spectroscopy (in the case of diamagnetic complexes 1, 4, 7 and 11). Moreover, the multi-nuclear structures of complexes 4 and 11 in solution were also studied by 1H DOSY spectroscopy. These complexes were applied in catalyzing the coupling reaction of carbon dioxide (CO2) with epoxides. Zn(OAc)2- and Zn(OBn)2-bridged heterobimetallic complexes showed comparable catalytic activities under ambient conditions and were more active than monometallic RE complexes. Significant synergistic effect in heterobimetallic complexes is observed. Mono-substituted epoxides were converted into cyclic carbonates under 1 atm CO2 at 25 °C in 88-96% yields, whereas di-substituted epoxides reacted under 1 atm CO2 at higher temperatures in 40-80% yields.

Publisher Correction: Methionine is a metabolic dependency of tumor-initiating cells.

In the version of this article originally published, there is an error in Fig. 5a. Originally, 'MAT2A' appeared between 'Methionine' and 'Homocysteine'. 'MAT2A' should have been 'MTR'. The error has been corrected in the PDF and HTML versions of this article.

Methionine is a metabolic dependency of tumor-initiating cells.

Understanding cellular metabolism holds immense potential for developing new classes of therapeutics that target metabolic pathways in cancer. Metabolic pathways are altered in bulk neoplastic cells in comparison to normal tissues. However, carcinoma cells within tumors are heterogeneous, and tumor-initiating cells (TICs) are important therapeutic targets that have remained metabolically uncharacterized. To understand their metabolic alterations, we performed metabolomics and metabolite tracing analyses, which revealed that TICs have highly elevated methionine cycle activity and transmethylation rates that are driven by MAT2A. High methionine cycle activity causes methionine consumption to far outstrip its regeneration, leading to addiction to exogenous methionine. Pharmacological inhibition of the methionine cycle, even transiently, is sufficient to cripple the tumor-initiating capability of these cells. Methionine cycle flux specifically influences the epigenetic state of cancer cells and drives tumor initiation. Methionine cycle enzymes are also enriched in other tumor types, and MAT2A expression impinges upon the sensitivity of certain cancer cells to therapeutic inhibition.

Copper Sulfide-Based Plasmonic Photothermal Membrane for High-Efficiency Solar Vapor Generation.

Solar vapor generation has attracted tremendous attention as one of the most efficient ways of utilizing solar energy. It is highly desirable to develop low-cost, eco-friendly, and high-efficiency solar absorbers for practical applications of solar vapor generation. Herein, a three-dimensional plasmonic covellite CuS hierarchical nanostructure has been synthesized as the light-absorbing material via a facile one-pot hydrothermal method for structurally integrated solar absorbers with microporous poly(vinylidene fluoride) membrane (PVDFM) as the supporting material. A broadband and highly efficient light absorption has been achieved in the wavelength of 300-2500 nm, along with high water evaporation efficiencies of 90.4 ± 1.1 and 93.3 ± 2.0% under 1 and 4 sun irradiation, respectively. Meanwhile, stable performance has been demonstrated for over 20 consecutive runs without much performance degradation. To the best of our knowledge, this is the highest performance among the copper sulfide-based solar absorbers. With the additional features of low-cost and convenient fabrication, this plasmonic solar absorber exhibits a tremendous potential for practical solar vapor generation.

Reprogramming mouse fibroblasts into engraftable myeloerythroid and lymphoid progenitors.

Recent efforts have attempted to convert non-blood cells into hematopoietic stem cells (HSCs) with the goal of generating blood lineages de novo. Here we show that hematopoietic transcription factors Scl, Lmo2, Runx1 and Bmi1 can convert a developmentally distant lineage (fibroblasts) into 'induced hematopoietic progenitors' (iHPs). Functionally, iHPs generate acetylcholinesterase+ megakaryocytes and phagocytic myeloid cells in vitro and can also engraft immunodeficient mice, generating myeloerythoid and B-lymphoid cells for up to 4 months in vivo. Molecularly, iHPs transcriptionally resemble native Kit+ hematopoietic progenitors. Mechanistically, reprogramming factor Lmo2 implements a hematopoietic programme in fibroblasts by rapidly binding to and upregulating the Hhex and Gfi1 genes within days. Moreover the reprogramming transcription factors also require extracellular BMP and MEK signalling to cooperatively effectuate reprogramming. Thus, the transcription factors that orchestrate embryonic hematopoiesis can artificially reconstitute this programme in developmentally distant fibroblasts, converting them into engraftable blood progenitors.

Cyclin A2 regulates erythrocyte morphology and numbers.

Cyclin A2 is an essential gene for development and in haematopoietic stem cells and therefore its functions in definitive erythropoiesis have not been investigated. We have ablated cyclin A2 in committed erythroid progenitors in vivo using erythropoietin receptor promoter-driven Cre, which revealed its critical role in regulating erythrocyte morphology and numbers. Erythroid-specific cyclin A2 knockout mice are viable but displayed increased mean erythrocyte volume and reduced erythrocyte counts, as well as increased frequency of erythrocytes containing Howell-Jolly bodies. Erythroblasts lacking cyclin A2 displayed defective enucleation, resulting in reduced production of enucleated erythrocytes and increased frequencies of erythrocytes containing nuclear remnants. Deletion of the Cdk inhibitor p27Kip1 but not Cdk2, ameliorated the erythroid defects resulting from deficiency of cyclin A2, confirming the critical role of cyclin A2/Cdk activity in erythroid development. Loss of cyclin A2 in bone marrow cells in semisolid culture prevented the formation of BFU-E but not CFU-E colonies, uncovering its essential role in BFU-E function. Our data unveils the critical functions of cyclin A2 in regulating mammalian erythropoiesis.