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The combined effects of warming and increased nitrogen (N) deposition in various ecosystems have become global issues. We used high‐throughput sequencing in an 8‐year field experiment to evaluate the impacts of the interactions between warming and nitrogen addition on soil nematode communities in a desert steppe. The soil nematode community presented with a certain degree of tolerance to warming. Warming mainly altered soil nematode diversity and community stability in deep soils whereas nitrogen addition primarily affected the nematode community in surface soils. Moreover, warming interacted with nitrogen addition exacerbated its negative effects on nematode richness and diversity. A Mantel analysis showed that soil pH was significantly negatively correlated with soil NH4+ and NO3− content. All three soil physicochemical (pH, NH4+ and NO3−) parameters were significantly correlated with desert steppe soil nematode community structure. Based on network and relative abundance analyses, we determined that Paratylenchus, Cervidellus, and Acrobeloides were the major hub soil nematode genera responding to soil warming and nitrogen addition in a desert steppe. The present study comprehensively analyzed the responses of desert steppe soil nematode communities to warming and nitrogen addition and provided an exemplar for studying the impact of environmental factors on soil nematodes communities worldwide. [ABSTRACT FROM AUTHOR]

Myocardial infarction (MI) is the leading cause of death worldwide and can lead to the loss of cardiac function and heart failure. Reactive oxygen species (ROS) play a key role in the pathological progression of MI. The levels and effects of ROS are significantly different in three unique pathological stages of MI, and most antioxidants cannot make corresponding adjustments to eliminate ROS, which leads to a great compromise to treat MI with antioxidants. Herein, an innovative self‐sustaining antioxidant strategy is developed to treat MI with self‐sustaining selenium‐embedded nanoparticles (SSSe NPs). SSSe NPs possess unique self‐sustaining antioxidant effects at different pathological stages of MI. This strategy of on‐demand ROS elimination during different pathological stages demonstrated excellent MI treatment efficacy and effectively reversed heart failure to normal heart function. The therapeutic mechanism of SSSe NPs is intensively investigated through a series of experiments and mainly involved five critical aspects of myocardial repair: protecting mitochondria, reducing cardiomyocyte apoptosis and ferroptosis, reducing inflammation and fibrosis, and promoting angiogenesis. This strategy not only provides a promising treatment option for MI but also offers inspiration for other ischemic diseases. [ABSTRACT FROM AUTHOR]

The White-eared Night Heron (Gorsachius magnificus) is a poorly known species. Little ecological research has been conducted on this species, and its migration route in particular is poorly understood. Clarification of the migratory routes of this species can enhance our understanding of its distribution and aid its conservation. Here, we identified the wintering and summering sites and characterized the migration route of one White-eared Night Heron by GPS/GSM tracking. Our results indicated that the Nanting River on the China–Myanmar border is the wintering site for this individual, and the Shizhuang River in Nanzhang, Hubei Province, China is the summering site. The heron migrated along the mountains and rested near rivers and reservoirs. This study is the first to reveal the migration route of the White-eared Night Heron. Our findings suggest that this species in Yunnan, Hubei, and Guizhou Provinces is not a resident bird. Generally, these data will aid the conservation of this species, including the development of action plans and the establishment of local nature reserves along its migration route and at wintering, summering, and stopover sites. [ABSTRACT FROM AUTHOR]

Summary: Four of China's six wintering populations of "grey" geese Anser spp. declined during the last decade. In contrast, the Bar-headed Goose A. indicus wintering population in China's Tibet Autonomous Region more than doubled. During six surveys in Tibet over a 27-year period (1991/92 to 2017/18 winters) we documented an annual growth rate of 6.8% in the Bar-headed Goose population – an increase from approximately 10,100 to 68,100 birds. We propose that in addition to the cessation of hunting, the population growth of Bar-headed Goose is being driven by changes in agricultural land use patterns in Tibet, the establishment of protected areas on the wintering and breeding grounds, and the impacts of climate change across the Tibetan Plateau. Consistent with this hypothesis, the sown area of winter wheat in Tibet has increased and geese have shifted from primarily feeding in crop stubble to planted winter wheat fields. We also found that the most rapid population growth coincided with a 1998 climate regime shift across the Tibetan Plateau resulting in warmer temperatures, an increase in net precipitation, the appearance of new lakes and changes in the water levels and surface area of historical lakes. We suggest that warmer temperatures and high-quality forage on the south-central Tibet wintering grounds may be enhancing over-winter survival, while on the breeding grounds the expansion of lakes and wet meadows is augmenting breeding and brood-rearing habitat. [ABSTRACT FROM AUTHOR]

• This paper chooses consecutive dissolved gases data (CDGD) as indexer for transformer diagnosis, which encapsulates more plentiful characteristics reflecting the real condition of transformer. • A novel structure called multichannel consecutive data cross-extraction (MCDC) is proposed, which aims to comprehensively harness the intrinsic characteristics of CDGD by successionally exploit the hidden token-wised emphasis and coherence in various dimensions of CDGD clued by information carried on other dimensions. • A 1-dimensional convolution neural network attention (1DCNN-attention) mechanism is introduced and integrated into MCDC to enhance the applicability in transformer diagnosis scenarios. • This paper verifies the superior generalization ability of deep learning methods. This sort of ability is of great significance when there are needs for transfer diagnostics across voltage levels. MCDC achieves the best generalization performance. Power transformer plays a critical role in grid infrastructure, and its diagnosis is paramount for maintaining stable operation. However, the current methods for transformer diagnosis focus on discrete dissolved gas analysis, neglecting deep feature extraction of multichannel consecutive data. The unutilized sequential data contains the significant temporal information reflecting the transformer condition. In light of this, the structure of multichannel consecutive data cross-extraction (MCDC) is proposed in this article in order to comprehensively exploit the intrinsic characteristic and evaluate the states of transformer. Moreover, for the better accommodation in scenario of transformer diagnosis, one dimensional convolution neural network attention (1DCNN-attention) mechanism is introduced and offers a more efficient solution given the simplified spatial complexity. Finally, the effectiveness of MCDC and the superior generalization ability, compared with other algorithms, are validated in experiments conducted on a dataset collected from real operation cases of power transformer. Additionally, the better stability of 1DCNN-attention has also been certified. [ABSTRACT FROM AUTHOR]