Search

The safety and efficiency of drilling engineering are greatly impeded by destructive vibrations of drill string in air drilling, such as stick-slip, bit-bounce and their coupled vibrations. To avoid or suppress these vibrations improving the stability of drilling operations, revealing the occurrence mechanisms of abovementioned harmful vibrations are indispensable by investigating dynamics characteristics of drill string system. In this paper, an axial-torsional coupled dynamics model that can capture the motion behaviors of bottom hole assembly (BHA) is established adopting the lumped parameter method. Subsequently, a rate of penetration (ROP) model appropriating for air drilling is obtained firstly by linear fitting means. Meanwhile, a novel discontinuous support model is established to describe the bit-formation interactions. Then, BHA dynamics are discussed using numerical simulations under different vibration scenarios: normal operation; stick-slip; bit-bounce; bit-bounce and stick-slip combination. Subsequently, in two drilling modes: the continuous and intermittent drilling, the vibration mitigation strategies and dynamics sensibility study of BHA are carried out based on the parametric analysis. The results show that increasing torsional stiffness of drill-pipes, appropriately adjusting rotation speed of top driven system and dynamic weight on bit (WOB) are deemed as an effective strategy suppressing or eliminating stick-slip and bit-bounce vibrations of BHA. Suggest that the rotation speed of top driven system and dynamic WOB are 5 rad/s and 3.5 kN, respectively. Finally, the constructed probability maps allow to driller to choose reasonable mechanical parameters, thereby realizing smooth drilling operation in the air drilling.

The release source term of radioactivity becomes a critical foundation for emergency response and accident consequence assessment after a nuclear accident Rapidly and accurately inverting the source term remains an urgent scientific challenge. Today source term inversion based on meteorological data and gamma dose rate measurements is a common method. But gamma dose rate actually includes all nuclides information, and the composition of radioactive nuclides is generally uncertain. This paper introduces a novel nuclear accident source term inversion model, which is Improve Snow Ablation Optimizer-Sensitivity Analysis Pruning Extreme Learning Machine (ISAO-SAELM) model. The model inverts the release rates of 11 radioactive nuclides (I-131, Xe-133, Cs-137, Kr-88, Sr-91, Te-132, Mo-99, Ba-140, La-140, Ce-144, Sb-129). It does not require the use of the physical field of the reactor to obtain prior information and establish a dispersion model. And the robustness is validated through noise analysis test. The mean absolute errors of the release rates of 11 nuclides are 15.52 %, 15.28 %, 15.70 %, 14.99 %, 14.85 %, 15.61 %, 15.96 %, 15.42 %, 15.84 %, 15.13 %, 17.72 %, which show the significant superiority of ISAO-SAELM. ISAO-SAELM model not only achieves notable advancements in accuracy but also receives validation in terms of practicality and feasibility.

Abstract The Atlantic Multidecadal Oscillation (AMO) has garnered attention for its important role in shaping surface air temperature (SAT) patterns over Eurasia. While Eurasian winter SAT was traditionally attributed to changes in large-scale atmospheric circulations associated with the AMO, a careful examination of the latest unforced CMIP6 simulations in this study unveils a significant contribution of the AMO’s thermodynamic effects. Specifically, the heat released from the North Atlantic Ocean and transported to northern Eurasia through westerlies takes precedence over the effect of dynamic Rossby waves, resulting in warm (cold) phases during positive (negative) AMO cycles, along with increased (decreased) warm extremes and reduced (enhanced) cold extremes. This study contributes to an improved understanding of the dominating mechanism of the AMO’s impact on Eurasian SAT.

Advanced manufacturing equipment heavily relies on gearboxes for optimal performance, especially in heavy-duty applications like industrial robot joints and advanced machine tools where precision and stiffness are paramount. While harmonic and cycloid gearboxes are common for their low backlash characteristic, conventional 3 K planetary gears excel in efficiency, torque density and stiffness but they are rarely utilized in high precision scenario due to backlash issue. In this study, a deformable planet carrier system (DPCS) is proposed for backlash restrain by center distance compensation. The DPCS incorporates a self-lock design, preserving low backlash feature while upholding load capacity and stiffness, meeting the demands of precision industrial equipment. To illustrate its principles, statics models demonstrate its force analysis, and FEM simulations reveal its self-lock feature. Backlash compensation model theoretically analyzes its anti-backlash effect from kinematics and geometry aspects. To validate its feasibility, the first prototype is manufactured and designated as H3K-40K-104. Experiment result prove that prototype achieves significant low backlash characteristic, with the maximum dynamic transmission error (DTE) of 20.5 arcsec and backlash of 6.561 arcsec. Stiffness hysteresis curve indicates a minimal lost motion of 20.01 arcsec. This paper provides an effective method to greatly refine precision performance in 3 K gear trains.

Abstract Surface defects on steel, arising from factors like steel composition and manufacturing techniques, pose significant challenges to industrial production. Efficient and precise detection of these defects is crucial for enhancing production efficiency and product quality. In accordance with these requisites, this paper elects to undertake the detection task predicated on the you only look once (YOLO) algorithm. In this study, we propose a novel approach for surface flaw identification based on the YOLOv5 algorithm, called YOLOv5-KBS. This method integrates attention mechanism and weighted Bidirectional Feature Pyramid Network (BiFPN) into YOLOv5 architecture. Our method addresses issues of background interference and defect size variability in images. Experimental results show that the YOLOv5-KBS model achieves a notable 4.2% increase in mean Average Precision (mAP) and reaches a detection speed of 70 Frames Per Second (FPS), outperforming the baseline model. These findings underscore the effectiveness and potential applications of our proposed method in industrial settings.

Abstract The vigorous development of the construction industry has also brought unprecedented safety risks. The wearing of safety helmets at the construction site can effectively reduce casualties. As a result, this paper suggests employing a deep learning-based approach for the real-time detection of safety helmet usage among construction workers. Based on the selected YOLOv5s network through experiments, this paper analyzes its training results. Considering its poor detection effect on small objects and occluded objects. Therefore, multiple attention mechanisms are used to improve the YOLOv5s network, the feature pyramid network is improved into a BiFPN bidirectional feature pyramid network, and the post-processing method NMS is improved into Soft-NMS. Based on the above-improved method, the loss function is improved to enhance the convergence speed of the model and improve the detection speed. We propose a network model called BiFEL-YOLOv5s, which combines the BiFPN network and Focal-EIoU Loss to improve YOLOv5s. The average precision of the model is increased by 0.9% the recall rate is increased by 2.8%, and the detection speed of the model does not decrease too much. It is better suited for real-time safety helmet object detection, addressing the requirements of helmet detection across various work scenarios.

Drying soil has been conducive to a high frequency of extreme high-temperature events over many regions worldwide in recent decades. However, changes in the intraseasonal variability of soil moisture can also influence the likelihood of extremely high temperatures. Although previous investigators have examined the association between extremely high temperatures and large-scale atmospheric circulation variability, the role of land–atmosphere coupling dominated by soil moisture variability in extremely high temperatures, particularly over the Eurasian continent, is not well understood. In this study, on the basis of the Land Surface, Snow, and Soil Moisture Model Intercomparison Project, we found that land–atmosphere feedback amplified the variability of soil moisture in most regions of Eurasia during summer from 1980 to 2014. This amplification of soil moisture variability is closely correlated with more intensive intraseasonal variability of surface air temperature and more frequent occurrences of extreme high-temperature events, particularly in Europe, Siberia, Northeast Asia, and the Indochina Peninsula. This correlation implies that increasing the intraseasonal variability of soil moisture results in a high likelihood of heat extremes during summer in most parts of Eurasia except Asian desert areas. On the intraseasonal timescale, the land–atmosphere coupling increases the variability of surface sensible heat flux and net long-wave radiation heating the atmosphere by intensifying the soil moisture variability, thus amplifying the variability of surface air temperature and enhancing the extreme high-temperature days. This finding demonstrates the importance of changes in intraseasonal soil moisture variability for the increasing likelihood of heat extremes in summer.

Abstract Background In recent years, the development of adjunctive therapeutic hyperthermia for cancer therapy has received considerable attention. However, the mechanisms underlying hyperthermia resistance are still poorly understood. In this study, we investigated the roles of cold‑inducible RNA binding protein (Cirbp) in regulating hyperthermia resistance and underlying mechanisms in nasopharyngeal carcinoma (NPC). Methods CCK-8 assay, colony formation assay, tumor sphere formation assay, qRT-PCR, Western blot were employed to examine the effects of hyperthermia (HT), HT + oridonin(Ori) or HT + radiotherapy (RT) on the proliferation and stemness of NPC cells. RNA sequencing was applied to gain differentially expressed genes upon hyperthermia. Gain-of-function and loss-of-function experiments were used to evaluate the effects of RNAi-mediated Cirbp silencing or Cirbp overexpression on the sensitivity or resistance of NPC cells and cancer stem-like cells to hyperthermia by CCK-8 assay, colony formation assay, tumorsphere formation assay and apoptosis assay, and in subcutaneous xenograft animal model. miRNA transient transfection and luciferase reporter assay were used to demonstrate that Cirbp is a direct target of miR-377-3p. The phosphorylation levels of key members in ATM-Chk2 and ATR-Chk1 pathways were detected by Western blot. Results Our results firstly revealed that hyperthermia significantly attenuated the stemness of NPC cells, while combination treatment of hyperthermia and oridonin dramatically increased the killing effect on NPC cells and cancer stem cell (CSC)‑like population. Moreover, hyperthermia substantially improved the sensitivity of radiation‑resistant NPC cells and CSC‑like cells to radiotherapy. Hyperthermia noticeably suppressed Cirbp expression in NPC cells and xenograft tumor tissues. Furthermore, Cirbp inhibition remarkably boosted anti‑tumor‑killing activity of hyperthermia against NPC cells and CSC‑like cells, whereas ectopic expression of Cirbp compromised tumor‑killing effect of hyperthermia on these cells, indicating that Cirbp overexpression induces hyperthermia resistance. ThermomiR-377-3p improved the sensitivity of NPC cells and CSC‑like cells to hyperthermia in vitro by directly suppressing Cirbp expression. More importantly, our results displayed the significantly boosted sensitization of tumor xenografts to hyperthermia by Cirbp silencing in vivo, but ectopic expression of Cirbp almost completely counteracted hyperthermia-mediated tumor cell-killing effect against tumor xenografts in vivo. Mechanistically, Cirbp silencing-induced inhibition of DNA damage repair by inactivating ATM-Chk2 and ATR-Chk1 pathways, decrease in stemness and increase in cell death contributed to hyperthermic sensitization; conversely, Cirbp overexpression-induced promotion of DNA damage repair, increase in stemness and decrease in cell apoptosis contributed to hyperthermia resistance. Conclusion Taken together, these findings reveal a previously unrecognized role for Cirbp in positively regulating hyperthermia resistance and suggest that thermomiR-377-3p and its target gene Cirbp represent promising targets for therapeutic hyperthermia.

Abstract Few research discuss whether the body measurement indexs of obesity in general populations is applicable to patients with type 2 diabetes. We explore the optimal cutoffs of visceral fat area (VFA) and subcutaneous fat area (SFA) in the diagnosis of central obesity and the cutoffs of corresponding waist circumference (WC) and body mass index (BMI) in patients with Type 2 Diabetes (T2D). Cross-sectional cohort study. 1057 patients with T2D (550 males and 507 females) aged 18 or above that satisfied the criteria were included. The definition and diagnostic criteria of Metabolic syndrome (Mets) were analyzed according to the 2020 Chinese Diabetes Society (CDS) Guideline. The VFA and SFA were measured by bioelectrical impedance analysis (BIA). The optimal VFA and SFA cutoffs and corresponding WC and BMI when two or more nonadipose components of MetS (without central obesity) were met were analyzed by ROC curve. Among all of the T2D patients, the optimal VFA cutoff for identifying two or more nonadipose components of MetS was 73.30 cm2 for females and 69.20 cm2 for males, while the optimal SFA cutoff was 186.70 cm2 for females and 123.30 cm2 for males. The ROC area under curve (AUC) of VFA for identifying two or more nonadipose components of MetS was higher than that of SFA (Female: 0.65 vs. 0.58, P = 0.01). The VFA cutoff of newly diagnosed T2D patients (females = 86.10 cm2, males = 69.00 cm2) was higher than that of non-newly diagnosed T2D patients (females = 73.30 cm2, males = 65.40 cm2). A stratification analysis of gender and whether newly diagnosed with T2D or not showed that the WCs corresponding to VFA were 85.00 cm and BMI was about 24.00 kg/m2. VFA measured by BIA can be a non-invasive method to detect central obesity in patients with T2D, the corresponding WC were 85.00 cm and BMI was 24.00 kg/m2.

Plant extracts from natural sources are an excellent choice for food additives and natural antioxidants. In this study, the active components of Tulipa edulis were extracted and analysed, and their antioxidant capacity was measured. Then, the crude extract mixture was separated and purified using a Sephadex LH-20 gel, and the antioxidant activity of the purified products was determined. Human umbilical vein endothelial human umbilical vein endothelial cells (HUVEC) cells were treated with 35 mmol/L glucose to construct a model of oxidative stress. Then, the cells were treated with the active component to observe whether the products of T. edulis could have a good protective effect on HUVEC cells induced by glucose. Transcriptome analysis was also performed on HUVEC cells after same treatment to explore the possible mechanism of the component F2 protecting HUVEC cells from oxidative stress induced by high glucose. The results showed that component F2 obtained from T. edulis has strong antioxidant activity. Moreover, F2 can play a strong antioxidant protective role in HUVEC cells. Meanwhile, the gene expression of heme oxygenase 1 (HO-1), γ-glutamyl cysteine ligase catalytic subunit (GCLC) and NAD(P)H quinone oxidoreductase-1 (NQO1) in HUVEC cells was up-regulated after treated with F2. This study provides reference value for the further development and application of T. edulis and the development of functional food.

Abstract Despite the ability of 3D convolutional methods to extract spatio-temporal information simultaneously, they also increase parameter redundancy and computational and storage costs. Previous work that has utilized the 2D convolution method has approached the problem in one of two ways: either using the entire body sequence as input to extract global features or dividing the body sequence into several parts to extract local features. However, global information tends to overlook detailed information specific to each body part, while local information fails to capture relationships between local regions. Therefore, this study proposes a new framework for constructing spatio-temporal representations, which involves extracting and fusing features in a novel manner. To achieve this, we introduce the multi-feature extraction-fusion (MFEF) module, which includes two branches: each branch extracts global features or local features individually, after which they are fused using multiple strategies. Additionally, as gait is a periodic action and different body parts contribute unequally to recognition during each cycle, we propose the periodic temporal feature modeling (PTFM) module, which extracts temporal features from adjacent frame parts during the complete gait cycle, based on the fused features. Furthermore, to capture fine-grained information specific to each body part, our framework utilizes multiple parallel PTFMs to correspond with each body part. We conducted a comprehensive experimental study on the widely used public dataset CASIA-B. Results indicate that the proposed approach achieved an average rank-1 accuracy of 97.2% in normal walking conditions, 92.3% while carrying a bag during walking, and 80.5% while wearing a jacket during walking.

An enhanced algorithm, YOLOv5s-FCW, is put forward in this study to tackle the problems that exist in the current helmet detection (HD) methods. These issues include having too many parameters, a complex network, and large computation requirements, making it unsuitable for deployment on embedded and other devices. Additionally, existing algorithms struggle with detecting small targets and do not achieve high enough recognition accuracy. Firstly, the YOLOv5s backbone network is replaced by FasterNet for feature extraction (FE), which reduces the number of parameters and computational effort in the network. Secondly, a convolutional block attention module (CBAM) is added to the YOLOv5 model to improve the detection model’s ability to detect small objects such as helmets by increasing its attention to them. Finally, to enhance model convergence, the WIoU_Loss loss function is adopted instead of the GIoU_Loss loss function. As reported by the experimental results, the YOLOv5s-FCW algorithm proposed in this study has improved accuracy by 4.6% compared to the baseline algorithm. The proposed approach not only enhances detection concerning small and obscured targets but also reduces computation for the YOLOv5s model by 20%, thereby decreasing the hardware cost while maintaining a higher average accuracy regarding detection.

The extraction of shale gas via horizontal drilling presents considerable challenges, primarily due to the accumulation of cuttings within the annular space, resulting in increased friction, torque, and potential drilling complications. To address this issue, the study proposes an experimental setup aimed at simulating cuttings transport under various operational conditions, with a particular emphasis on gas wells. The methodology encompasses the modulation of the drilling fluid flow rate and the drill’s rotational speed to examine the transport velocity of cuttings. Furthermore, the study analyzes the impact of annular eccentricity on return volume, transport time, and cuttings bed height. Critical initiation velocities for cuttings across different motion modes were also determined, and theoretical calculations were compared with empirical data. The findings indicate that an increased flow rate of drilling fluid and higher rotation speed substantially improve the transport of cuttings, thereby minimizing bed formation, whereas increased eccentricity hinders this process. The results revealed that the theoretical model showed a greater overestimation of the start-up velocity for spherical particles, with average errors ranging from 15.50% to 17.56%. In contrast, the model exhibited better accuracy for non-spherical (flaky) particles, with errors between 8.63% and 9.61%. Under non-rotating conditions, the average error of the model was approximately 8.32%, while the introduction of drill tool rotation increased the average error to 11.94%. These results have the potential to optimize operational parameters in shale gas well drilling and may contribute to the development of specialized borehole purification tools.

Autonomous aerial refueling technology can significantly extend the operational endurance of unmanned aerial vehicles (UAVs), enhancing their ability to perform long-duration missions efficiently. In this paper, we address the identification of refueling drogues in the close docking phase of autonomous aerial refueling. We propose a high-precision real-time drogue recognition network called DREP-Net. The backbone of this network employs the DGST module for efficient feature extraction and improved representation of multi-scale information. For occlusion and complex background problems, we designed the RGConv module, which combines the re-parameterization module with the GhostNet idea to improve the detection of an occluded drogue. Meanwhile, we introduced the efficient local attention mechanism into the neck network to enhance the overall attention to the target region. Then, we designed Phead, a lightweight detection head that combines the advantages of decoupling and coupling heads to improve the detection speed. Finally, we compared our network with mainstream algorithms on a real drogue dataset, and the results show that DREP-Net has 2.7% higher mean average precision (mAP) compared to the YOLOv8n model, and the detection speed is improved by 31.4 frames per second.

Abstract Gossypol is a polyphenol from the cotton plant with anti‐inflammatory and anti‐oxidation activities and can also function as a histone deacetylase (HDAC) inhibitor. Sepsis is an inflammatory disease with high mortality. Inflammation, oxidative stress, and epigenetic factors are involved in sepsis and its complications. The biological activities of gossypol strongly suggest the potential effects of gossypol on sepsis. In the present study, the beneficial effects of gossypol on sepsis were evaluated. We established a cecal ligation and puncture (CLP) mouse model of sepsis and treated CLP mice with gossypol. The survival rate, serum level of myocardial injury markers, and myocardial level of oxidation markers were measured. We also administered gossypol to lipopolysaccharide (LPS)‐treated primary cardiomyocytes. The production of pro‐inflammatory cytokines, activation of protein kinase B (AKT) and IκB kinase (IKK), acetylation of histone, and expression of HDACs were measured. Gossypol prevented the death of CLP mice and ameliorated myocardial damage in CLP mice. Moreover, gossypol decreased oxidative factors, while promoting antioxidant production in CLP mice. Gossypol prevented LPS and cytosine‐phosphate‐guanosine‐induced expression of pro‐inflammatory cytokines, suppressed LPS‐induced activation of AKT and IKK, inhibited histone acetylation, and decreased the expression of HDACs. In conclusion, gossypol ameliorates myocardial dysfunction in mice with sepsis.

Abstract Pueraria lobata is a typical medicinal and edible plant with great market value and demand, thus exploring the relationship between soil environmental factors and the yield and quality of Pueraria lobata is of great significance for its high-value cultivation. In this study, using the Guige 1 variety (Pueraria montana var. Thomsonii) selected by our research group as the material to compare the effects of five soil types, endophytes in three parts of Pueraria lobata and two fertilizers on its yield and quality. The results showed that the comprehensive evaluation effect of five soil types on the yield and quality of Guige 1 was as follow: red-yellow mixed soil (RYMS) > black loam soil (BLS) > sandy loam soil (SLS) > sandy loam soil waterlogging (SLSW) > yellow soil compaction soil (YSCS); the descending order of endophyte types and quantities is in BLS > RYMS > SLS > YSC > SLSW; applying General Compound Fertilizers (GCF) in RYMS is more suitable for the rapid expansion of Guige 1 than Organic-Slow-Release-Fertilizers (OSRF). The high potassium content in RYMS and high effective phosphorus content in BLS are positively correlated with the content of starch and isoflavone in Pueraria lobata. The conclusion is that the high potassium and available phosphorus content in RYMS and BLS, as well as the rich types and quantities of endophytic bacteria, are positively correlated with the yield and quality of Pueraria lobata. The research results have important guiding significance for the high-value cultivation of Pueraria lobata.

Abstract This paper presents an improved Fast-Segmentation Convolutional Neural Network (Fast-SCNN) and U-Net networks based on the channel attention mechanism. While ensuring the speed of network detection, the accuracy of image segmentation is also considered. The experimental results show that the accuracy rate of improved Fast-SCNN based on the channel attention mechanism is greatly improved compared with the original Fast-SCNN, reaching 88.056%, and the mean intersection over union is also improved to a certain extent, reaching 81.087%, and the detection speed is better than the original Fast-SCNN network. The accuracy of improved U-Net network based on the channel attention mechanism is 0.91805, which is better than the original U-Net network. In terms of detection speed, the improved U-Net network based on channel attention mechanism has greatly improved compared with the original U-Net network, reaching 24.02 frames per second. In addition, a method of preventing clogging of ore conveyor belts based on static image detection is proposed in this paper. By judging and predicting the blockage of the ore conveyor belt. When the conveyor belt is about to be blocked or has been blocked, the fuzzy algorithm is used to control the ore conveyor belt to slow down and stop, to improve the safety and efficiency of the conveyor belt.

Extremophile strain Monascus pilosus YX-1125 was isolated from the baijiu-making environment. It was found that this strain could use sorghum as substrate and could tolerate multiple extreme environmental stress. Based on this, Monascus and Sorghum Fermentation Filtrate (MSFF) derived from this strain was developed, and its composition, safety, and bioactivity were studied. Research findings revealed that MSFF was abundant in various bioactive substances, including short-chain fatty acids such as propionic acid, butyric acid, and acetic acid, phenolic compounds (greater than 7.0 mg/mL) and 17 amino acids (greater than 7.5 mg/mL), and had strong antioxidant potentials (80% concentration of MSFF with DPPH scavenging 67.3%, copper chelation 59.71%, iron chelation 42.62%, hydroxyl scavenging 83.31%, superoxide scavenging 55.8%, and ferric ion reducing antioxidant power 1.24 mmoL eq FeSO4/mL). The results of in vitro experiments revealed that 1% (v/v) MSFF could inhibit inflammation and reduce its damage by reducing 81.4% cell apoptosis, removing 35.8% intracellular reactive oxygen species, inhibiting the release of proinflammatory cytokines (interleukins-6 and -8) up to 83.2% and down-regulating the expression of matrix metalloproteinases (MMP-1 and MMP-9) up to 42.5%. The safety test confirmed that MSFF had high cytocompatibility. In conclusion, MSFF was a safe and highly effective antioxidant and anti-inflammatory ingredient, which had great potential applications in the fields of health food and skincare.

In the realm of urban planning and environmental evaluation, the delineation and categorization of land types are pivotal. This study introduces a convolutional neural network-based image semantic segmentation approach to delineate parcel data in remote sensing imagery. The initial phase involved a comparative analysis of various CNN architectures. ResNet and VGG serve as the foundational networks for training, followed by a comparative assessment of the experimental outcomes. Subsequently, the VGG+U-Net model, which demonstrated superior efficacy, was chosen as the primary network. Enhancements to this model were made by integrating attention mechanisms. Specifically, three distinct attention mechanisms—spatial, SE, and channel—were incorporated into the VGG+U-Net framework, and various loss functions were evaluated and selected. The impact of these attention mechanisms, in conjunction with different loss functions, was scrutinized. This study proposes a novel network model, designated VGG+U-Net+Channel, that leverages the VGG architecture as the backbone network in conjunction with the U-Net structure and augments it with the channel attention mechanism to refine the model’s performance. This refinement resulted in a 1.14% enhancement in the network’s overall precision and marked improvements in MPA and MioU. A comparative analysis of the detection capabilities between the enhanced and original models was conducted, including a pixel count for each category to ascertain the extent of various semantic information. The experimental validation confirms the viability and efficacy of the proposed methodology.

Flowering is critical to the success of plant propagation. The MYB family transcription factor CIRCADIAN CLOCK-ASSOCIATED1 (CCA1) is an essential component of the core loop of the circadian clock and plays a crucial role in regulating plant flowering time. In this study, we found that photoperiod affects the expression pattern and expression level of BcCCA1, which is delayed flowering time under short-day conditions in Pak-choi [Brassica campestris (syn. Brassica rapa) ssp. chinensis]. We detected overexpression and silencing of BcCCA1 in Pak-choi, resulting in delayed and promoted flowering time, respectively. Furthermore, we also discovered that FLOWERING LOCUS C (BcFLC) and SUPPRESSOR OF CONSTANS1 (BcSOC1) were expressed significantly differently in BcCCA1 overexpression and silencing plants compared with control plants. Therefore, we further investigated the interaction relationship between BcCCA1, BcFLC, and BcSOC1, and the results showed that BcCCA1 and BcFLC as a complex interacted with each other. Moreover, both BcCCA1 and BcFLC can directly bind to the promoter of BcSOC1 and repress its transcription, and BcCCA1 can form a complex with BcFLC to enhance the transcriptional inhibition of BcSOC1 by BcFLC. This study reveals a new mechanism by which the circadian clock regulates flowering time.

Abstract Soil moisture–atmosphere coupling (SA) amplifies greenhouse gas-driven global warming via changes in surface heat balance. The Scenario Model Intercomparison Project projects an acceleration in SA-driven warming due to the ‘warmer climate – drier soil’ feedback, which continuously warms the globe and thereby exerts an acceleration effect on global warming. The projection shows that SA-driven warming exceeds 0.5 °C over extratropical landmasses by the end of the 21st Century. The likelihood of extreme high temperatures will additionally increase by about 10% over the entire globe (excluding Antarctica) and more than 30% over large parts of North America and Europe under the high-emission scenario. This demonstrates the high sensitivity of SA to climate change, in which SA can exceed the natural range of climate variability and play a non-linear warming component role on the globe.

Abstract Aims Sepsis is an inflammatory disease with high mortality and morbidity. Inflammation plays an essential role in sepsis, and suppressing inflammation has been shown to ameliorate sepsis. Rnf144b is an ubiquitin E3 ligation with anti‐inflammation activities. Its precise roles in sepsis remain unknown. Here, we explored the function of Rnf144b in sepsis. Methods and results We generated conditional knockout mice with Rnf144b deficiency in the myeloid cells. We monitored the Rnf144b expression in peripheral blood mononuclear cells from healthy donor and patients with sepsis, and in lipopolysaccharides (LPS)‐treated bone marrow‐derived macrophages (BMDMs). The cytokine expression between wild‐type BMDMs and Rnf144b‐deficient BMDMs after LPS and CpG treatments was compared. The survival rate and cardiac function were monitored. The activation of TANK binding kinase 1 and nuclear factor kappa‐B was examined by Western blot and real‐time PCR. Up‐regulated expression of Rnf144b was observed in peripheral blood mononuclear cells from patients with sepsis. LPS induced the expression of Rnf144b in BMDMs. Rnf144b‐deficient BMDMs produced more inflammatory cytokines after LPS or CpG stimulation. Septic mice with Rnf144b deficiency in myeloid cells had higher mortality and exacerbated cardiac dysfunction. Rnf144b interacted with TANK binding kinase 1 and Rnf144b deficiency resulted in impaired activation of TBK1 but enhanced activation of nuclear factor kappa‐B. Conclusions Rnf144b prevents inflammatory responses and cardiac dysfunction in sepsis.

Extractive electrospray ionization (EESI) technology has the advantages of directly ionizing the target molecules in the samples without complex sample pretreatments, and it is widely used for analysis of complex matrix samples, especially for aerosol samples. However, the current EESI device with open structure is easily affected by the surrounding environmental factors, especially susceptible to the airflow disturbance and exogenous aerosols. To solve this problem, an enclosed-structure EESI device was developed in this work. Three standard solutions of histidine, reserpine and MRFA were used to test the performances of the enclosed and open EESI-MS under laboratory conditions, respectively. The results showed that intra-day precision and sensitivity of enclosed EESI device are slightly better than that of open EESI device. Then, the performances of the two EESI-MS devices were tested with reserpine solution under different external air flow rates. As the external air flow rate increased, the intra-day precision of the open EESI device gradually decreased (RSD increased from 3.4% to 5.6%), and the intra-day precision of the enclosed EESI device remained good (RSD increased from 2.4% to 3.6%), indicating that the enclosed EESI device has a strong ability to resist airflow disturbance. The glucose aerosols of different concentrations were used to test the enclosed EESI-MS for 5 consecutive days. The results showed that intra-day precision (RSD

The pollen receptor-like protein kinase (PRK) family, an LRR receptor-like protein kinase, not only plays a role in pollen development and fertilization, but also plays a role in stress response. Based on the analysis of transcriptome data that generated in our previous study, we found that AhPRK4 was an aluminum-responsive gene. To explore the role of AhPRK4 in response to aluminum stress, we analyzed the expression of AhPRK4 by qRT-PCR in ‘ZH2’ (Al-sensitive) and ‘99-1507’ (Al-tolerant), clarified the protein structure and genetic relationship of AhPRK4 by sequence analysis, phylogenetic tree construction and other genetic analysis, constructed the recombinant plasmid by homologous recombination, obtained the intracellular domain recombinant protein of AhPRK4 by prokaryotic expression technology and determined the activity of the recombinant protein by incubation with phosphorylated antibodys. The results were as follows: (1) The transcription level of AhPRK4 was up-regulated after different aluminum treatments time and different aluminum concentrations, indicating that AhPRK4 was an aluminum inducible gene. (2) The AhPRK4 protein had 673 amino acids with transmembrane domain, signal peptide and phosphorylation active sites, belonging to the LRR-III protein kinase family. (3) The GST-AhPRK4-CD recombinant protein was induced in vitro and verified by Western Blot. And the recombinant protein had phosphorylated on both serine/threonine and tyrosine residues, but had no significant auto-phosphorylation activity. In conclusion, AhPRK4 is an aluminum responsive gene, which participates in the regulation of short-term aluminum stress and is phosphorylated in vitro.

Abstract In the process of mining belt transportation, various foreign objects may appear, which will have a great impact on the crusher and belt, thus affecting production progress and causing serious safety accidents. Therefore, it is important to detect foreign objects in the early stages of intrusion in mining belt conveyor systems. To solve this problem, the YOLOv4_GECA method is proposed in this paper. Firstly, the GECA attention module is added to establish the YOLOv4_GECA foreign object detection model in the mineral belt to enhance the foreign object feature extraction capability. Secondly, based on this model, the learning rate decay of restart cosine annealing is used to improve the foreign object image detection performance of the model. Finally, we collected belt transport image information from the Pai Shan Lou gold mine site in Shenyang and established a belt foreign body detection dataset. The experimental results show that the average detection accuracy of the YOLOv4_GECA method proposed in this paper is 90.1%, the recall rate is 90.7%, and the average detection time is 30 ms, which meets the requirements for detection accuracy and real-time performance at the mine belt transportation site.

In this paper, the computer experiment cloud platform is built using big data technology, and various functions are implemented based on optimizing the platform parameters based on distributed estimation algorithms. The functional and non-functional requirements of the platform are determined, and the overall architecture design and system database design of the platform are carried out. The distributed estimation algorithm and the UDMA algorithm are used to identify the motor model, and the PID controller uses a particle swarm-based algorithm for parameter optimization. The platform system’s requirements are evaluated from environmental and performance perspectives to ensure that it meets the requirements proposed by the requirements analysis. The value of W(Si) is small, and the actual performance load of the platform remains. The performance of the platform function is good and can withstand a large amount of concurrency, and the average value of 90% response time is maintained at 5.8698s, showing an increasing trend.

Abstract Power system operation and control are based on power flow calculations. In order to solve the uncertainty of the increasing penetration of renewable energy, the voltage fluctuation at the load point increases in the distribution network, and the inaccuracy of the power flow calculation due to the insufficient power flow data collection capability of the traditional power system. In this paper, a data‐driven power flow analysis model is proposed, a back propagation neural network combined with genetic algorithm (GA) and adaptive moment estimation (ADAM) optimization algorithm model is constructed to analyze the power flow calculation method of distribution networks under stochasticity. Firstly, the power flow initial value information, topology characteristics, and power factor index are introduced to construct a training set, and the mapping relationship between bus voltage and power is fully explored by training the regression model. Second, the GA‐ADAM algorithm is used to optimize the initial values and weight parameters of the model. Finally, it is verified based on IEEE‐33 bus distribution model, and the model is used for power flow calculation, and compared with other methods through each relevant error evaluation indicators. The results show that the model constructed in this paper has small error indicators and high accuracy, which improves the efficiency and accuracy of power flow calculation.

Vegetation restoration is an important indicator of ecosystem health in a mining area. Understanding the impact of vegetation restoration on the characteristics and assembly process of soil microbial community is very important to explore the resilience and self-sustaining mechanism of the restored ecosystem in a mining area. Therefore, this study uses MiSeq high-throughput sequencing and zero model to detect the composition of soil microbial communities, the characteristics of molecular ecological network, the key flora and its assembly mechanism in the shrubs (BL), coniferous forests (CF), broad-leaved forests (BF), mixed forests (MF), that have been reclaimed for 18 years in Antaibao open-pit mining dump, and the control plots (CK, undisturbed surrounding poplar forests that have continued to grow for more than 30 years) in Pingshuo, Loess Plateau. The results show that: ① The effects of different vegetation restoration types on the bacterial community α-diversity are significant (P < 0.05). Compared with CK, the Sobs and Shannon index of MF and CF have increased by 35.29%, 3.50% and 25.18%, 1.05%, respectively, whereas there is no significant difference in the α-diversity of fungal community among different vegetation restoration types. ② Actinobacteria, Chloroflexi, Proteobacteria and Acidobacteria dominate in the bacterial community, and the first two dominant phylum are significantly higher than CK, while the latter two are opposite (P < 0.05). Ascomycota and Basidiomycota are the dominant fungi in the fungal community. The former is significantly higher than CK, while the latter is opposite (P < 0.05). ③ The stochastic process dominates the construction process of the soil bacterial community. In addition to the MF soil fungal community dominated by deterministic process, other fungal communities are also dominated by a stochastic process. However, no matter which type of vegetation is restored, the dominant role of the randomness process on the assembly of the bacterial community is much higher than that of the fungal community. Moreover, Proteobacteria and Acidobacteria are key taxa of the bacterial network, while Mortierellales, Thelebolales, Chaetothyriales, and Hypocreales are the key taxa of the fungal network. Vegetation restoration affects microbial community diversity, BL, CF, and MF increase the stability of the bacterial network, and MF makes fungal network more complex. The soil bacterial assembly process is dominated by stochastic processes, except for MF, and the fungal assembly process is also dominated by stochastic processes.

Rice bran is an important byproduct of the rice polishing process, rich in nutrients, but it is underutilized and often used as feed or discarded, resulting in a huge amount of waste. In this study, rice bran was fermented by Lactobacillus fermentum MF423 to obtain a product with high antioxidant activity. First, a reliable and efficient method for assessing the antioxidant capacity of the fermentation products was established using high-performance liquid chromatography (HPLC), which ensured the consistency of the batch fermentation. The fermented rice bran product (FLRB) exhibited significant antioxidant activity in cells, C. elegans, and hyperlipidemic mice. Transcriptome analysis of mouse livers showed that the expression of plin5 was upregulated in diabetic mice administered FLRB, thereby preventing the excessive production of free fatty acids (FFAs) and the subsequent generation of large amounts of reactive oxygen species (ROS). These studies lay the foundation for the application of rice bran fermentation products.

With the continuous advancement of drone technology, drones are demonstrating a trend toward autonomy and clustering. The detection of airborne objects from the perspective of drones is critical for addressing threats posed by aerial targets and ensuring the safety of drones in the flight process. Despite the rapid advancements in general object detection technology in recent years, the task of object detection from the unique perspective of drones remains a formidable challenge. In order to tackle this issue, our research presents a novel and efficient mechanism for adjacent frame fusion to enhance the performance of visual object detection in airborne scenarios. The proposed mechanism primarily consists of two modules: a feature alignment fusion module and a background subtraction module. The feature alignment fusion module aims to fuse features from aligned adjacent frames and key frames based on their similarity weights. The background subtraction module is designed to compute the difference between the foreground features extracted from the key frame and the background features obtained from the adjacent frames. This process enables a more effective enhancement of the target features. Given that this method can significantly enhance performance without a substantial increase in parameters and computational complexity, by effectively leveraging the feature information from adjacent frames, we refer to it as an efficient adjacent frame fusion mechanism. Experiments conducted on two challenging datasets demonstrate that the proposed method achieves superior performance compared to existing algorithms.

Sucrosic dolomite, an important hydrocarbon reservoir, has long been the focus of carbonate sedimentological and reservoir geological studies. This study investigated a kind of heterogeneous sucrosic dolomite in the Lower Permian Qixia Formation of NW Sichuan Basin, which has recently been the location of giant natural gas discoveries. The heterogeneous sucrosic dolomite is characterized by coexistence of porous euhedral dolomite and tight anhedral dolomite, and it is mainly distributed in the platform-marginal shoal facies with a quasi-layered structure. Further geochemical analysis, including C, O, and Sr isotopes as well as rare earth elements, reveals that the euhedral dolomite and anhedral dolomite have similar geochemical properties to the matrix limestone representing coeval seawater, and they were mainly generated from dolomitization by the closed marine-related fluid (left-leaning REE and δPr

In order to explore the differences in the molecular mechanism of the Pueraria cultivars between isoflavone metabolic enzyme gene PtCHI, and to preliminarily reveal the difference content causes of the isoflavones. The materials of the study were Pueraria montana var. lobata and P. montana var. thomsonii. Puerarin and total flavonoids of P. montana var. lobata and P. montana var. thomsonii were extracted by ethanol, and their contents were measured by high-performance liquid chromatography. Based on the reported CHI gene of Pueraria montana var. lobata, the PtCHI gene from P. montana var. thomsonii was isolated by homologous cloning method, and the protein was expressed in vitro. At the same time, the location of the PtCHI gene was studied in Arabidopsis thaliana protoplasts. The results were as follows: (1)The content of puerarin in P. montana var. lobata was significantly higher than the P. montana var. thomsonii, and the content of total flavonoids was also higher but not significant.（2) The gene PtCHI was successfully isolated from P. montana var. thomsonii. The gene was 742 bp in length, containing a complete ORF frame of 672 bp, encoding 223 amino acids, and had up to 99% homology with P. montana var. lobata. (3)This study found that the expression of CHI gene in P. montana var. thomsonii was stem>root>leaf, P. montana var. lobata was root>stem>leaf. The expression of CHI gene from P. montana var. lobata was significantly higher than P. montana var. thomsonii besides in leaves. (4) Through the online tool prediction analysis, PtCHI was found to be stable hydrophilic protein and the size was 27.8 kD. The secondary and tertiary structures were based on α-helix, with 25 phosphorylation sites, closely relating P. montana var. lobata, Glycine max and Glycyrrhiza uralensis, and were more likely to interact with F3H2, F3H, 4CL4, DFR2 and CHS. (5)At the same time, the protein of PtCHI was successfully induced and isolated in vitro, with a single protein of 27.8 kD. (6) Through the Arabidopsis thaliana protoplasts revealed that PtCHI was mainly located in the chloroplasts. This study further analyzed the difference in flavonoids in P. montana var. lobata and P. montana var. thomsonii, as well as provides the reference for the functional verification of P. montana var. thomsonii PtCHI and the research on the mechanism of isoflavone metabolism.

Abstract Widespread observed and projected increases in warm extremes, along with decreases in cold extremes, have been confirmed as being consistent with global and regional warming. Here we disclosed that the decadal variation in the frequency of the surface air temperature (SAT) extremes over Siberia in winter was primarily dominated by the Atlantic Meridional Overturning Circulation (AMOC) rather than anthropogenic forcing. The stronger AMOC induced more warm and cold extremes through increasing the variance of winter SAT over Siberia while the direct effect of external forcings, especially anthropogenic greenhouse gases, had little impact on the summation of warm and cold extremes due to equivalent effects on the increases in warm extremes and decreases in cold extremes. The possible mechanism can be deduced that the stronger AMOC stimulated the propagation of the wave train originated in the North Atlantic Ocean, across mid- to high latitudes, thereby increasing the variabilities in the circulations over the Ural blocking region and Siberia, which are critical to the SAT extremes there.

The role of eiptranscriptomic modifications in autophagy is unclear. Here, the authors show that the m6A reader YTHDF3 functions as a nutrient responder to recognize upregulated m6A modification, promoting FOXO3 translation to subsequently initiate autophagy.

Objective: The purpose of this study is to improve the extraction rate of total flavonoids from the leaves of Moringa oleifera Lam. and evaluate their in vitro antibacterial and antioxidant capacity. Methods: The extraction of total flavonoids from the leaves of M. oleifera Lam. from Baoshan city was optimized by Box-Behnken response surface methodology, and its antibacterial and antioxidant activities were evaluated. Results: The optimal conditions for microwave-assisted extraction of total flavonoids from leaves of M. oleifera Lam. were solid-liquid ratio 1∶29 (g/mL), microwave power 567 W, microwave time 3.6 min and ethanol fraction 50%, and the highest extraction rate of total flavonoids was (7.414±0.027)%. The total flavonoids from leaves of M. oleifera Lam. showed strong DPPH·, ABTS+· and hydroxyl radical scavenging activities, with IC50 value of 0.024 mg/mL, 0.014 mg/mL and 0.051 mg/mL, which were 3.43, 14.00, 1.09 times of ascorbic acid, respectively. Conclusion: The total flavonoids from leaves of M. oleifera Lam. have different degrees of antibacterial effect on B. subtilis and E. coli and have no inhibition on S. aureus.

Ethylene-acrylate rubber (AEM)/polyvinylidene fluoride (PVDF) thermoplastic vulcanizate (TPV) was prepared by dynamic vulcanization, and the effects of rotor shear rate during dynamic vulcanization on the microphase structure and properties of TPV were investigated. The results showed that the higher the shear rate of the rotor during the dynamic vulcanization process, the more likely the phase inversion of AEM and PVDF occured, and the microscopic phase structure was more refined, forming a TPV with a “sea-island” structure. With the increase of shear rate of rotor, the tensile strength and elongation at break of TPV increased first and then decreased. When the share rate was 75 r/min, AEM/PVDF TPV had better mechanical properties, the tensile strength reached 14.84 MPa, and the elongation at break was 246%. TPV had better hot oil and hot air resistance.

Abstract Pseudorabies virus (PRV) variant infections have caused a substantial economic impact on swine production in the absence of new powerful candidate vaccines. In this study, we developed and evaluated a gene-deleted variant pseudorabies virus (PRV)-attenuated vaccine, PRV GX-ΔTK/IES, in which the genes TK, gI, gE, US9 and US2 were deleted. During a study of innocuousness, all mice inoculated with PRV GX-ΔTK/IES survived, neither clinical signs nor pathological changes were observed, and viral genomes could not be detected in the blood and tissues. All piglets inoculated with high titres of PRV GX-ΔTK/IES remained clinically healthy, and neither fever nor clinical signs were observed. Viral detection results were negative in nasal swab samples, blood and tissue samples. Moreover, none of the cohabitated piglets seroconverted during a trial on horizontal transmission. The immunogenicity was assessed through a vaccination and challenge experiment in piglets. Piglets vaccinated with PRV GX-ΔTK/IES and the commercial vaccine were completely protected from subsequent PRV infection, and the level of immunity and protection induced by PRV GX-ΔTK/IES was better than that provided by the live commercial vaccine. Thus, PRV GX-ΔTK/IES is completely safe for both nontarget and target animals and can be regarded as a novel live gene-deleted PRV vaccine candidate.

Abstract Background Tuberous root formation and development is a complex process in sweet potato, which is regulated by multiple genes and environmental factors. However, the regulatory mechanism of tuberous root development is unclear. Results In this study, the transcriptome of fibrous roots (R0) and tuberous roots in three developmental stages (Rl, R2, R3) were analyzed in two sweet potato varieties, GJS-8 and XGH. A total of 22,914 and 24,446 differentially expressed genes (DEGs) were identified in GJS-8 and XGH respectively, 15,920 differential genes were shared by GJS-8 and XGH. KEGG pathway enrichment analysis showed that the DEGs shared by GJS-8 and XGH were mainly involved in “plant hormone signal transduction” “starch and sucrose metabolism” and “MAPK signal transduction”. Trihelix transcription factor (Tai6.25300) was found to be closely related to tuberous root enlargement by the comprehensive analysis of these DEGs and weighted gene co-expression network analysis (WGCNA). Conclusion A hypothetical model of genetic regulatory network for tuberous root development of sweet potato is proposed, which emphasizes that some specific signal transduction pathways like “plant hormone signal transduction” “Ca2+signal” “MAPK signal transduction” and metabolic processes including “starch and sucrose metabolism” and “cell cycle and cell wall metabolism” are related to tuberous root development in sweet potato. These results provide new insights into the molecular mechanism of tuberous root development in sweet potato.

Abstract Background Total knee arthroplasty is the leading way to treat hemophilia arthritis. At present, there is a lack of research on the influencing factors of blood loss in total knee arthroplasty for hemophilia arthritis. This study comprehensively explores the definite factors affecting the hidden blood loss in total knee arthroplasty for hemophilia patients. Materials and methods Ninety-two hemophilia A patients who underwent total knee arthroplasty in our center were included. Demographics, laboratory data, surgical data, and complications were collected. The Gross equation and Sehat equation were used to calculate the estimated value of hidden blood loss. Multivariate linear regression analysis was used to determine the influencing factors of hidden blood loss. Result The hidden blood loss of hemophilia A patients undergoing total knee arthroplasty was 1069.51 ± 341.99 mL, and the age was positively correlated with the hidden blood loss (P

IntroductionThe research investigates the mechanism, diagnosis, treatment, and subsequent endocrine therapy of severe pancreatitis induced by tamoxifen treatment in patients who have undergone breast cancer surgery.Case presentationWe studied two cases of breast cancer in whom severe acute pancreatitis developed after taking tamoxifen for endocrine therapy in our hospital. A brief literature review was provided to analyze the causes, clinical manifestations, treatment process, and prognosis of severe acute pancreatitis. Both cases involved patients with severe hyperlipidemic pancreatitis. After conservative treatment, none of them died. Pancreatitis did not recur after changing endocrine therapy drugs.Discussion/conclusionEndocrine therapy with tamoxifen in breast cancer patients can induce hyperlipidemia, which can subsequently cause severe pancreatitis. The treatment of severe pancreatitis should strengthen the regulation of blood lipids. The application of low-molecular-weight heparin combined with insulin therapy can rapidly lower blood lipids. Involved treatments, including acid suppression, enzyme suppression, and peritoneal dialysis, can accelerate the recovery of pancreatitis and reduce the occurrence of serious complications. Patients with severe pancreatitis should not continue to use tamoxifen for endocrine therapy. To complete follow-up endocrine therapy, switching to a steroidal aromatase inhibitor is better if the situation allows it.

Abstract Background Late embryogenesis abundant (LEA) proteins are a group of highly hydrophilic glycine-rich proteins, which accumulate in the late stage of seed maturation and are associated with many abiotic stresses. However, few peanut LEA genes had been reported, and the research on the number, location, structure, molecular phylogeny and expression of AhLEAs was very limited. Results In this study, 126 LEA genes were identified in the peanut genome through genome-wide analysis and were further divided into eight groups. Sequence analysis showed that most of the AhLEAs (85.7%) had no or only one intron. LEA genes were randomly distributed on 20 chromosomes. Compared with tandem duplication, segmental duplication played a more critical role in AhLEAs amplication, and 93 segmental duplication AhLEAs and 5 pairs of tandem duplication genes were identified. Synteny analysis showed that some AhLEAs genes come from a common ancestor, and genome rearrangement and translocation occurred among these genomes. Almost all promoters of LEAs contain ABRE, MYB recognition sites, MYC recognition sites, and ERE cis-acting elements, suggesting that the LEA genes were involved in stress response. Gene transcription analyses revealed that most of the LEAs were expressed in the late stages of peanut embryonic development. LEA3 (AH16G06810.1, AH06G03960.1), and Dehydrin (AH07G18700.1, AH17G19710.1) were highly expressed in roots, stems, leaves and flowers. Moreover, 100 AhLEAs were involved in response to drought, low-temperature, or Al stresses. Some LEAs that were regulated by different abiotic stresses were also regulated by hormones including ABA, brassinolide, ethylene and salicylic acid. Interestingly, AhLEAs that were up-regulated by ethylene and salicylic acid showed obvious subfamily preferences. Furthermore, three AhLEA genes, AhLEA1, AhLEA3-1, and AhLEA3-3, which were up-regulated by drought, low-temperature, or Al stresses was proved to enhance cold and Al tolerance in yeast, and AhLEA3-1 enhanced the drought tolerance in yeast. Conclusions AhLEAs are involved in abiotic stress response, and segmental duplication plays an important role in the evolution and amplification of AhLEAs. The genome-wide identification, classification, evolutionary and transcription analyses of the AhLEA gene family provide a foundation for further exploring the LEA genes’ function in response to abiotic stress in peanuts.

The seasonal prediction of sea-ice concentration (SIC), especially sudden loss events, is always challenging. Weddell Sea SIC experienced two unprecedented decline events, falling from 2.21% in the austral winter of 2015 to 0.02% in the austral summer of 2016 and then falling to −2.32% in the austral spring of 2017. This study proposes several statistical prediction models for Weddell Sea SIC and performs them for a period that includes the sudden decline events. We identified six potential oceanic and atmospheric factors at different leading times that relate to the variability of the Weddell Sea SIC, including the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Niño12 sea surface temperature (SST), Southeastern Indian Ocean (SEIO) SST, Antarctic sea level pressure (SLP), and Weddell Sea surface air temperature (SAT). Multiple linear regression models were employed to establish equations to simulate the variation of Weddell Sea SIC under three groups of climate factors for 1979–2012. These models could effectively reproduce the low-frequency variation of SIC in the Weddell Sea during the simulation period and the high-frequency values through two kinds of error-correction methods developed in this study. After applying these error correction methods, the correlation coefficients (absolute errors) of these models were enhanced (decreased) during the simulation period. In the prediction period of 2013–2018, the corrected models generally predicted well the sudden losses of Weddell Sea SIC. The possible primary factors influencing these sudden losses were the PDO, Niño12 SST, Southern Annular Mode (SAM), and SAT during 2015–2016 and the AMO, PDO, Niño12 SST, SAM, and SAT during 2016–2017.

This study revealed a new regime shift in the North Pacific annual mean sea surface temperature (SST) in 2013/14, robust in multiple SST data sets. This regime shift shows a horseshoe pattern with warming SST along the North American western coast and toward the Central Pacific. It suggests a phase reversal of the Victoria Mode (VM) and it seems unrelated to the shift in the Pacific Decadal Oscillation (PDO) and Interdecadal Pacific Oscillation (IPO). Associated with this regime shift, the annual surface air temperature significantly enhanced over the high-latitude landmass after 2014, whereas it declined over northeastern Canada and southwestern Greenland. The annual precipitation generally increased (decreased) in the Northern (Southern) Hemisphere landmass monsoon regions. There are no regime shifts in Equatorial Central-East Pacific SST and the intensity and locations of the Aleutian Low around 2013/14. These facts suggest the regime shift of North Pacific SST in 2013/14 may not originate from the decadal variations of the midlatitude atmosphere and tropical ocean. The extensive influence of this regime shift in 2013/14 on the atmospheric, oceanic and ecological systems warrants further investigation.

MicroRNA-155 (miR155) is overexpressed in various inflammatory diseases and cancer, in which bone resorption and osteolysis are frequently observed. However, the role of miR155 on osteogenesis and bone mass phenotype is still unknown. Here, we report a low bone mass phenotype in the long bone of Mir155-Tg mice compared with wild-type mice. In contrast, Mir155-KO mice showed a high bone mass phenotype and protective effect against inflammation-induced bone loss. Mir155-KO mice showed robust bone regeneration in the ectopic and orthotopic model, but Mir155-Tg mice showed compromised bone regeneration compared with the wild-type mice. Similarly, the osteogenic differentiation potential of bone marrow stromal stem cells (BMSCs) from Mir155-KO mice was robust and Mir155-Tg was compromised compared with that of wild-type mice. Moreover, Mir155 knockdown in BMSCs from wild-type mice showed higher osteogenic differentiation potential, supporting the results from Mir155-KO mice. TargetScan analysis predicted sphingosine 1-phosphate receptor-1 (S1pr1) as a target gene of Mir155, which was further confirmed by luciferase assay and Mir155 knockdown. S1pr1 overexpression in BMSCs robustly promoted osteogenic differentiation without affecting cell viability and proliferation. Furthermore, osteoclastogenic differentiation of Mir155-Tg bone marrow-derived macrophages was inhibited compared with that of wild-type mice. Thus, Mir155 showed a catabolic effect on osteogenesis and bone mass phenotype via interaction with the S1pr1 gene, suggesting inhibition of Mir155 as a potential strategy for bone regeneration and bone defect healing.

During the drilling of shale gas wells, the shape of shale cuttings cut by polycrystalline diamond compact bits has an obvious flaky structure. The accumulation of such flaky cuttings is one of the main reasons for high drilling torque and drag and serious back pressure, which affect the drilling speed of the horizontal section of shale gas wells. Therefore, predicting the thickness of the flaky cuttings bed and restraining it are essential for ensuring safe and efficient drilling of the horizontal section of shale gas wells. However, most of the previous research on migration laws for cuttings were based on spherical particles, which affected the accuracy of cuttings bed thickness prediction. In this study, through visualization experiments combined with computational fluid dynamics numerical simulation, the hole cleaning laws of shale gas wells in the long horizontal section were studied, and a set of cuttings bed thickness prediction models and cuttings bed removal process parameter optimization methods were established. Field application was conducted in the Changning 209H24-1 well in the southern Sichuan Basin, China. The results revealed the following: (1) There are significant differences in the migration laws of flaky cuttings and spherical cuttings in the horizontal section. (2) The fitting accuracy of the established long horizontal fragmentation layer distribution model considering multiple factors and the experimental data is as high as 0.973. (3) Based on this model, the drilling parameters of the Changning 209H24-1 well were optimized, which played a good role in wellbore cleaning and ensured the safe and smooth implementation of the later casing operation.

ObjectiveEnteral feeding after intestinal atresia has always been a concern for clinicians. But the present studies mainly focused on single factors. This research aimed to comprehensively analyze the multiple factors on complete enteral nutrition after primary anastomosis, and establish the convenient prediction model.MethodsWe retrospectively collected reliable information in neonates with intestinal atresia form January 2010 to June 2022. The cox regression analysis was performed to select independent risk factors and develop nomogram. Subsequently, ROC curve, calibration curve and decision curve were drawn to thoroughly evaluate the accuracy and applicability of the model.ResultsThe predictors finally included in the model were gestational age, meconium peritonitis, distance from the anastomosis to the ileocecal region, diameter ratio of proximal to distal bowels, and time of initial feeding. The nomogram of predicting the probability of week 2, week 3 and week 4 was drawn and their area under the curve were 0.765, 0.785 and 0.747, respectively. Similarly, calibration and decision curve indicated that the prediction model had a great prediction performance.ConclusionThe clinical value of predictive models can be recognized. The hope is that the predictive model can help pediatricians reduce hospital costs and parental anxiety.