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Soil respiration (Rs) represents the greatest carbon dioxide flux from terrestrial ecosystems to the atmosphere. However, its environmental drivers are not fully understood, and there are still significant uncertainties in soil respiration model estimates. This study aimed to estimate the spatial distribution pattern and driving mechanism of global soil respiration by constructing a machine learning model method based on ecological big data. First, we constructed ecological big data containing five categories of 27-dimensional environmental factors. We then used four typical machine learning methods to develop the performance of machine learning models under four training strategies and explored the relationship between soil respiration and environmental factors. Finally, we used the RF machine learning algorithm to estimate the global Rs spatial distribution pattern in 2021, driven by multiple dimensions of environmental factors, and derived the annual soil respiration values. The results showed that RF performed better under the four training strategies, with a coefficient of determination R 2  = 0.78216, root mean squared error (RMSE) = 285.8964 gCm −2 y −1 , and mean absolute error (MAE) = 180.4186 gCm −2 y −1 , which was more suitable for the estimation of large-scale soil respiration. In terms of the importance of environmental factors, unlike previous studies, we found that the influence of geographical location was greater than that of MAP. Another new finding was that enhanced vegetation index 2 (EVI2) had a higher contribution to soil respiration estimates than the enhanced vegetation index (EVI) and normalized vegetation index (NDVI). Our results confirm the potential of utilizing ecological big data for spatially large-scale Rs estimations. Ecological big data and machine learning algorithms can be considered to improve the spatial distribution patterns and driver analysis of Rs.

The silicon photomultiplier (SiPM)-based optical detection method, which provides strong resistance to electromagnetic interference and high sensitivity, is attracting increasing attention. However, most studies have been conducted on laboratory simulation platforms, and few studies have systematically investigated SiPM-based partial discharge (PD) detection in actual gas insulated switchgear (GIS) equipment. In addition, the photon detection efficiency (PDE) of SiPMs varies with photon wavelength, and current studies lack a theoretical basis for the selection of SiPMs. To address this issue, an experimental platform for GIS gas discharge analysis was established in this study to systematically investigate the emission spectral characteristics of SF 6 gas discharge at different discharge intensities, pressures, and temperatures. On this basis, a SiPM-based optical sensing system adapted for GIS applications was developed. Ultimately, a PD detection experiment was conducted on an actual 110 kV GIS platform. The experimental results indicate that the detection signal-to-noise ratio of the developed SiPM-based optical detection system is approximately 5.8 dB higher than that of the high-frequency current transformer and that the minimum detectable discharge quantity is below 18 pC. These results highlight the potential of SiPM-based optical detection technology for GIS PD detection.

Incorporating rare-earth elements into wurtzite nitride semiconductors, such as scandium-alloyed aluminum nitride (ScAlN), significantly enhances the piezoelectric response, which is vital for a broad range of acoustic, electronic, photonic, and quantum applications. To date, however, the measured piezoelectric response of nitride semiconductors is far below what theory has predicted. Herein, we demonstrate a simple, scalable, post-growth thermal annealing process that can dramatically boost the piezoelectric response of ScAlN. We achieve a 3.5-fold increase in the piezoelectric modulus, d 33 for ScAlN, from 12.3 pC/N in the as-grown state to 45.5 pC/N, which is eight times larger than that of AlN commercially used in 5 G cellphones. The observed enhancement is unambiguously confirmed by three separate measurement techniques. Detailed material characterization techniques reveal that optimized annealing conditions significantly improve the macroscopic structural quality, achieving a more homogeneous and ordered domain orientation, and reduces the lattice parameter ratio (c/a) in the wurtzite crystal structure. The dramatic enhancement of d 33 in ScAlN thin films promises extreme frequency scaling opportunities for bulk acoustic wave resonators for beyond-5 G applications. The authors present a process that boosts the piezoelectric properties of ScAlN thin films by 3.5 times, enhancing their performance for use in acoustic devices. The technique is scalable, cost effective, and could enable advanced sensors, clocks, and communication technologies.

The strategies adopted by viruses to reprogram the translation and protein quality control machinery and promote infection are poorly understood. Here, we report that the viral ubiquitin deconjugase (vDUB)—encoded in the large tegument protein of Epstein-Barr virus (EBV BPLF1)—regulates the ribosomal quality control (RQC) and integrated stress responses (ISR). The vDUB participates in protein complexes that include the RQC ubiquitin ligases ZNF598 and LTN1. Upon ribosomal stalling, the vDUB counteracts the ubiquitination of the 40 S particle and inhibits the degradation of translation-stalled polypeptides by the proteasome. Impairment of the RQC correlates with the readthrough of stall-inducing mRNAs and with activation of a GCN2-dependent ISR that redirects translation towards upstream open reading frames (uORFs)- and internal ribosome entry sites (IRES)-containing transcripts. Physiological levels of active BPLF1 promote the translation of the EBV Nuclear Antigen (EBNA)1 mRNA in productively infected cells and enhance the release of progeny virus, pointing to a pivotal role of the vDUB in the translation reprogramming that enables efficient virus production. Here, the authors show how the vDUB from the large tegument protein from the human herpes virus can reprogram translation in host cells by modulating the activity of the ribosome quality machinery and activating the integrated stress response.

Due to its potential impact on business efficiency, automated customer complaint labeling and classification are of great importance for management decision making and business applications. The majority of the current research on automated labeling uses large and well-balanced datasets. However, customer complaint labels are hierarchical in structure, with many labels at the lowest hierarchy level. Relying on lower-level labels leads to small and imbalanced samples, thus rendering the current automatic labeling practices inapplicable to customer complaints. This article proposes an automatic labeling model incorporating the BERT and word2vec methods. The model is validated on electric utility customer complaint data. Within the model, the BERT method serves to obtain shallow text tags. Furthermore, text enhancement is used to mitigate the problem of imbalanced samples that emerge when the number of labels is large. Finally, the word2vec model is utilized for deep text analysis. Experiments demonstrate the proposed model's efficiency in automating customer complaint labeling. Consequently, the proposed model supports enterprises in improving their service quality while simultaneously reducing labor costs.

The magnetic abrasive finishing process using the magnetic machining tool was proposed to finish the internal surface of the thick tube (the thickness of the tube is 5~30 mm). It has been proved that this process can improve the roundness while improving the roughness. In this paper, we mainly study the machining mechanism of roundness improvement. Firstly, the influence of finishing characteristics on the roundness improvement was discussed, including the rotational speed of the magnetic machining tool and the rotational speed of the tube. It was concluded that the roundness improvement increases with the increase in the rotational speed through the analysis of finishing force and finishing times. Furthermore, the influence on roundness improvement of different distributions of magnetic particles were experimentally compared. After finishing, due to the magnetic force generated by the magnetic machining tool and the magnetic pole unit exerting pressure on the magnetic particles, a fixed magnetic brush is formed. The experimental results show that the circumferential length of the fixed magnetic brush is different due to the different distribution areas of magnetic particles. It was concluded that the roundness improvement increases with the circumferential length of the fixed magnetic brush increases by discussing the relationship between the circumferential length of the fixed magnetic brush and the wavelength of the roundness curve. When the circumferential length of the fixed magnetic brush is 76 mm, the roundness was improved from 379 μm to 236 μm after 60 min of finishing.

Micro or submicron scale light-emitting diodes (µLEDs) have been extensively studied recently as the next-generation display technology. It is desired that µLEDs exhibit high stability and efficiency, submicron pixel size, and potential monolithic integration with Si-based complementary metal-oxide-semiconductor (CMOS) electronics. Achieving such µLEDs, however, has remained a daunting challenge. The polar nature of III-nitrides causes severe wavelength/color instability with varying carrier concentrations in the active region. The etching-induced surface damages and poor material quality of high indium composition InGaN quantum wells (QWs) severely deteriorate the performance of µLEDs, particularly those emitting in the green/red wavelength. Here we report, for the first time, µLEDs grown directly on Si with submicron lateral dimensions. The µLEDs feature ultra-stable, bright green emission with negligible quantum-confined Stark effect (QCSE). Detailed elemental mapping and numerical calculations show that the QCSE is screened by introducing polarization doping in the active region, which consists of InGaN/AlGaN QWs surrounded by an AlGaN/GaN shell with a negative Al composition gradient along the c-axis. In comparison with conventional GaN barriers, AlGaN barriers are shown to effectively compensate for the tensile strain within the active region, which significantly reduces the strain distribution and results in enhanced indium incorporation without compromising the material quality. This study provides new insights and a viable path for the design, fabrication, and integration of high-performance µLEDs on Si for a broad range of applications in on-chip optical communication and emerging augmented reality/mixed reality devices, and so on.Micro-light-emitting diodes (µLED) with bright, ultra-stable green emissions are monolithically achieved on Si substrate. The quantum-confined Stark effect is screened by introducing polarization doping in the shell.

Background Neutrophil extracellular traps (NETs) are composed of DNA chains from neutrophils and associated proteolytic enzymes, which play an important role in cancer metastasis. However, the molecular mechanism of NET-mediated lung metastasis in triple-negative breast cancer (TNBC) remains unclear. Methods The expression levels of NETs in breast cancer specimens and serum were analyzed and compared with normal samples. Single-cell sequencing bioinformatics analysis was conducted to identify differentially expressed genes and functional enrichment related to NET formation in patients with breast cancer. The effects of c-FOS on neutrophil recruitment and NET formation in TNBC were investigated. The upstream and downstream regulatory mechanisms mediated by c-FOS were explored through in vitro and in vivo experiments. Therapeutic approaches targeting c-FOS for treating TNBC were further studied. Results Inhibition of c-FOS can suppress tumor growth and lung metastasis in TNBC. Mechanistically, c-FOS promotes transcription by binding to the PAD4 promoter region, facilitating the formation of NETs. Additionally, the activation of the ROS-p38 pathway further enhances c-FOS expression. High expression of c-FOS also promotes the expression of inflammatory factors, facilitating neutrophil recruitment. Both in vitro and in vivo experiments demonstrated that the application of T5224 effectively inhibits the formation of NETs, suppressing lung metastasis and tumor growth. Conclusion In summary, this study demonstrates that the ROS-p38-cFOS-PAD4 axis can increase NET formation in TNBC and promote the expression of inflammatory factors, facilitating neutrophil recruitment. Therefore, targeting this pathway may help inform new therapeutic strategies and provide new insights for immunotherapy in TNBC.

An internal magnetic abrasive finishing process using a magnetic machining tool was proposed for finishing the internal surface of the thick tubes. It has been proved that this process is effective for finishing thick tubes, and it can improve the roundness while improving the roughness. However, the mechanism of improving the roundness is not clear, so it is necessary to study it theoretically. In this research, firstly, the roundness curve expression was derived using the principle of roundness measurement by the assumed center method, and the expression of roundness curve expanded by Fourier series was obtained. The influencing factors of roundness improvement were then analyzed. Secondly, the experiments were carried out on SUS304 stainless steel tubes. By confirming the mechanism analysis results and the experimental results, it was concluded that the internal magnetic abrasive finishing process using the magnetic machining tool was effective for improving the roundness of the thick tubes whose thickness is from 10 mm to 30 mm. As the thickness of the tube increased, the improvement in roundness decreased.

Predation events are an important key factor determining the survival and reproduction of prey species. To cope, prey species have evolved various anti‐predator strategies, including mechanisms for accurate predator identification and distinguishing predator types and risk levels. Birds rely on visual, auditory, and olfactory cues to perceive and categorize predators. However, previous studies have focused on single sensory modalities and have largely been conducted during breeding seasons. Thus, analyses of the accuracy and differences in predator recognition cues, especially during non‐breeding periods, are needed. In this study, predator recognition in Azure‐winged Magpies (Cyanopica cyanus) was evaluated during the non‐breeding season. We examined responses to two predators, Common Kestrel (Falco tinnunculus) and Domestic Cat (Felis catus), and two non‐predators, Oriental Magpie (Pica serica) and Oriental Turtle Dove (Streptopelia orientalis). Using specimens and playback experiment, the ability of Azure‐winged magpies to identify threats through both visual and auditory cues was evaluated. The results showed that Azure‐winged Magpies can identify predator types through both visual and auditory cues, accurately distinguish threat levels, and adjust their foraging behavior accordingly. Notably, they exhibited the strongest anti‐predator response to Domestic Cats (frequently encountered under natural conditions), as evidenced by longer observation times, shorter foraging duration, and quicker flight responses. The results indicate that Azure‐winged Magpies can correctly identify predator types and threat levels through both visual and auditory cues and exhibit stronger anti‐predator behaviors with increasing apparent threat levels. In this study, we demonstrated that Azure‐winged Magpies (Cyanopica cyanus) uses both visual and auditory cues to detect different predator types and to assess the risk level during the non‐breeding season. In particular, a stronger anti‐predator response was observed to Domestic Cats than to the less frequently encountered Common Kestrel and two non‐predator species, Oriental Magpie and Oriental Turtle Dove. These findings demonstrate the complex mechanisms by which magpies adjust foraging behavior in response to specific predators.