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Poverty remains a significant global challenge, despite ongoing efforts throughout history to address it. China’s fight against poverty, as part of global poverty governance efforts, has yielded valuable insights and examples for anti-poverty strategies, propelling changes within the global poverty governance system. This paper conducts a review of post-1978 anti-poverty research covering China’s ethnic minority regions, roughly dividing the research history into three distinct phases: 1978–2012, 2013–2020, and post-2020. The research findings at each stage are summarized in terms of research topics, perspectives, and paradigms. Based on these findings, the paper provides a forward-looking outlook on future research into anti-poverty efforts in China’s ethnic minority regions.

Demodulation is a key technology for the enhanced Loran (eLoran) system to achieve positioning and timing, and it affects the final performance of the system. Based on the traditional matched correlation algorithm, this paper proposes a new matched correlation demodulation method with notch processing. Furthermore, by combining it with the pattern modulation of the eLoran system, the matched correlation integrate notch demodulation method is further modified to improve demodulation performance. Firstly, the data link of the eLoran system is introduced in detail, including the encoding and modulation processes, the influencing factors of received signals, and the evaluation methods in the demodulation process. Secondly, on the basis of the principle of the matched correlation (MC) demodulation algorithm, a matched correlation demodulation algorithm integrating notch processing (MC-NF) and a demodulation correlation algorithm combined with modulation patterns (PMC-NF) are proposed. And, an analysis of the key factors affecting demodulation performance is given. Next, the demodulation performance of the mentioned algorithms under the conditions of random noise, skywave, and in-band continuous wave interference is calculated in detail. A large number of experimental results show that notch processing performs excellently in suppressing random noise and in-band continuous wave interference, and it can greatly improve the demodulation performance of the traditional matched correlation algorithm. Moreover, PMC-NF is superior to MC-NF; approximately 2.8 dB at decoding the critical point.

Research has widely validated three-band spectral index as a simple, valid, and highly accurate method of estimating the copper content of soil. However, selecting the best band combination from hundreds of thousands, even millions of candidate combinations in hyperspectral data, is a very complicated problem. To address this issue, this study collected a total of 170 soil samples from the Aktas copper-gold mining area in Fuyun County, Xinjiang, China. Then, two algorithms including Competitive Weighted Resampling (CARS) and Stepwise Regression Analysis (STE) were applied to pick the bands from the original and first-order derivative spectra, respectively. A three-band index model was developed using the selected feature bands to estimate soil copper content. Results showed the first-order derivative spectrum transforms the spectral curve into a sharper one, with more peaks and valleys, which is beneficial for increasing the correlation between bands and copper content compared with the original spectrum. Moreover, integrating first-order derivative spectroscopy with CARS makes it possible to precisely identify key spectral bands and outperforms the dimensionality-reduction capabilities compared with the integration of STE. This strategy drastically reduces the time spent screening and is proven to have similar model accuracy, as compared to the individual group lifting method. Specifically, it reduces the duration of an 8 h task down to a mere 2 s. An intelligent screening of three-band indices is proposed in this study as a method of rapidly estimating copper content in soil.

The core of eLoran ground-based timing navigation systems is the accurate measurement of groundwave propagation delay. However, meteorological changes will disturb the conductive characteristic factors along the groundwave propagation path, especially for a complex terrestrial propagation environment, and may even lead to microsecond-level propagation delay fluctuation, seriously affecting the timing accuracy of the system. Aiming at this problem, this paper proposes a propagation delay prediction model based on a Back-Propagation neural network (BPNN) for a complex meteorological environment, which realizes the function of directly mapping propagation delay fluctuation through meteorological factors. First, the theoretical influence of meteorological factors on each component of propagation delay is analyzed based on calculation parameters. Then, through the correlation analysis of the measured data, the complex relationship between the seven main meteorological factors and the propagation delay, as well as their regional differences, are demonstrated. Finally, a BPNN prediction model considering regional changes of multiple meteorological factors is proposed, and the validity of the model is verified by long-term collected data. Experimental results show that the proposed model can effectively predict the propagation delay fluctuation in the next few days, and its overall performance is significantly improved compared with that of the existing linear model and simple neural network model.

Background Studies have assessed the impact of Invisalign on maxillary molar distalization; however, varying results were reported. Methods By using the iTero intraoral laser scanner to obtain three-dimensional (3D) digital models and using the palatal area for the registration of models, the position and angulations of the maxillary first molar (U6) and second molar (U7) were determined before treatment (T0), after U7 distalization (T1) and after U6 distalization (T2). In addition, the rotation angle and vertical changes of U6 and U7, and the sagittal and torque changes of the maxillary central incisor (U1) were determined from T0 to T2. Results The U6 was moved distally from T0 to T1, T1 to T2, and T0 to T2, by 0.91 ± 0.80 mm, 0.80 ± 0.49 mm, and 1.71 ± 0.89 mm, respectively. Similarly, the U7 was moved by 2.25 ± 1.30 mm, -0.21 ± 0.78 mm, and 2.04 ± 1.16 mm, respectively. From T0 to T2, the U6 and U7 molars were distally tipped by angles of -5.20 ± 2.62° and − 5.35 ± 4.19°, respectively. Molar intrusion and loss of anterior anchorage were also observed. Conclusions Invisalign can achieve maxillary molar distalization primarily through tipping movement, often accompanied by decreased angulation control and anterior anchorage loss, which requires additional auxiliaries to strengthen anchorage.

The timing accuracy of eLoran systems is susceptible to meteorological fluctuations, with medium-to-long-range propagation delay variations reaching hundreds of nanoseconds to microseconds. While conventional models have been widely adopted for short-range delay prediction, they fail to accurately characterize the coupled effects of multiple factors in long-range scenarios. This study theoretically examines the influence mechanisms of temperature, humidity, and atmospheric pressure on signal propagation delays, proposing a hybrid prediction model integrating meteorological data with a back-propagation neural network (BPNN) through path-weighted Pearson correlation coefficient analysis. Long-term observational data from multiple differential reference stations and meteorological stations reveal that short-term delay fluctuations strongly correlate with localized instantaneous humidity variations, whereas long-term trends are governed by cumulative temperature–humidity effects in regional environments. A multi-tier neural network architecture was developed, incorporating spatial analysis of propagation distance impacts on model accuracy. Experimental results demonstrate enhanced prediction stability in long-range scenarios. The proposed model provides an innovative tool for eLoran system delay correction, while establishing an interdisciplinary framework that bridges meteorological parameters with signal propagation characteristics. This methodology offers new perspectives for reliable timing solutions in global navigation satellite system (GNSS)-denied environments and advances our understanding of meteorological–electromagnetic wave interactions.

Few studies have considered nutrients as a mixture and their impact on Mild Cognitive Impairment (MCI). The generalized linear regression (GLM), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models are fitted to estimate the association between intake of a mixture of nutrients and MCI. Comparing the results from these three models, vitamin E and vitamin B6 were identified as the most important factors associated with the risk of MCI. Considering the characteristics of BKMR, it may be more advantageous to use BKMR to estimate the combined the joint effects of nutrients mixture. In the future, studies need to move from a “one nutrient at a time” approach to simultaneous analyses of multiple nutrients intakes in order to understand and quantify the joint effect of nutrients mixture on health.

The RAD51 recombinase is evolutionarily conserved critical for homologous recombination (HR)‐mediated repair of DNA double‐strand breaks. It binds to single strand DNA to form protein‐DNA filaments for homology searching and pairing during HR repair. RFWD3 is an E3 ubiquitin ligase shown to remove RAD51 at the completion of HR repair through ubiquitination and degradation of RAD51. However, it remains elusive what prevents RFWD3 from attacking RAD51 in the absence of DNA damage and early on during the repair process. Here, we show that it is UHRF1 that protects RAD51, and it does so by acting as an E3 ubiquitin ligase of RFWD3 is demonstrated. Interestingly, RAD51 also protects RFWD3 from UHRF1, thereby establishing a negative feedback circuit that regulates the protein levels of RFWD3 and RAD51. Furthermore, it is shown that the ubiquitination of RFWD3 is regulated by phosphorylation status of UHRF1, and that phosphatase PP4 is important for modulating UHRF1 activity. Altogether, these regulatory mechanisms ensure that the recombinase RAD51 is maintained at appropriate levels for HR repair. We demonstrate here that the recombinase RAD51 is protected by UHRF1 through ubiquitinating RFWD3, an E3 for RAD51, and this very process is inhibited by RAD51, leading to a triple negative feedback circuit that ensures appropriate levels of RFWD3 and RAD51 for DNA damage response.

Background High rates of health inequalities and chronic non-communicable diseases exist amongst the prison population. This places people in and/or released from prison at heightened risk of multimorbidity, premature mortality, and reduced quality of life. Ensuring appropriate healthcare for people in prison to improve their health outcomes is an important aspect of social justice. This review examines the global literature on healthcare interventions to detect, monitor and manage chronic non-communicable diseases amongst the prison population and people recently released from prison. Methods Systematic searches of EMBASE, MEDLINE, CINAHL, Web of Science, Scopus, and the Cochrane Library were conducted and supplemented by citation searching and review of the grey literature. The literature searches attempted to identify all articles describing any healthcare intervention for adults in prison, or released from prison in the past 1 year, to detect, monitor, or manage any chronic non-communicable illness. 19,061 articles were identified, of which 1058 articles were screened by abstract and 203 articles were reviewed by full text. Results Sixty-five studies were included in the review, involving 18,311 participants from multiple countries. Most studies were quasi-experimental and/or low to moderate in quality. Numerous healthcare interventions were described in the literature including chronic disease screening, telemedicine, health education, integrated care systems, implementing specialist equipment and staff roles to manage chronic diseases in prisons, and providing enhanced primary care contact and/or support from community health workers for people recently released from prison. These interventions were associated with improvement in various measures of clinical and cost effectiveness, although comparison between different care models was not possible due to high levels of clinical heterogeneity. Conclusions It is currently unclear which interventions are most effective at monitoring and managing chronic non-communicable diseases in prison. More research is needed to determine the most effective interventions for improving chronic disease management in prisons and how these should be implemented to ensure optimal success. Future research should examine interventions for addressing multimorbidity within prisons, since most studies tested interventions for a singular non-communicable disease.

Xinjiang is an important hub connecting China and Eurasia and has a vital strategic position in economy, energy, and ecological security. However, owing to the fragile ecological environment in Xinjiang, substantial challenges exist in coordinating the relationship between social and economic development and ecological environment construction. To elucidate the relationship between land use changes induced by human activities and the valuation of ecosystem services, this study utilized the value equivalent method to evaluate the ecosystem service value in Xinjiang from 2000 to 2020 while analyzing its spatiotemporal response characteristics related to land use. Results showed that from 2000 to 2020, the value of ecosystem services in Xinjiang showed an upward trend, reaching 25.77 USD hm −2 in 2020, and the total value of the whole region was 42.80 billion USD. The value of ecological services in Xinjiang was mainly low grade (about 50%), and high grade only accounted for 1.03%–2.19%. A significant increase in land use in forested areas and water body was noted, whereas the conversion trend from effective grassland to other land types was relatively limited—specifically, 4.47% of bare land and 3.76% of meadows were transformed into water body. Additionally, 2.69% of grassland experienced conversion into woodland. The land use intensity was generally low (more than 85% of the low-grade states), and 83.71% of the land use intensity increased during the study period. The water body was the main controlling factor of the service value of the state system, with a contribution rate of 78.83%, followed by grassland (11.29%) and woodlands (9.30%), and 54.39% of the land use changes increased the value of ecosystem services.