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"Lu, Feiyu"
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لقاء في القرية العالمية = An encounter in the global village : قصص مختارة من المؤتمر الدولي الرابع عشر للقصة القصيرة
هذا الكتاب يحتوي على قصص مختارة من المؤتمر الدولي الرابع عشر للقصة القصيرة وهذا اللقاء الذي نظم من قبل جمعية دراسة القصص القصيرة الإنجليزية (أس أس أس أس إي) وهي جمعية عالمية أنشئت في الولايات المتحدة عام 1992 وينعقد كل عامين ويعتبر اللقاء العالمي الوحيد الذي يركز بشكل خاص على دراسات القصة القصيرة أما القصص المشاركة في اللقاء فهي مكتوبة من قبل 29 كاتبا ينتمون إلى عشرة دول هي الصين وتايوان والهند والولايات المتحدة وكندا ونيوزلندا وفرنسا وإيرلندا والنمسا وسنغافورا وجامايكا.
BOOK
Assessing Extratropical Influence on Observed El Niño–Southern Oscillation Events Using Regional Coupled Data Assimilation
The extratropical influence on the observed events of El Niño–Southern Oscillation (ENSO) variability from 1948 to 2015 is assessed by constraining the extratropical atmospheric variability in a coupled general circulation model (CGCM) using the regional coupled data assimilation (RCDA) method. The ensemble-mean ENSO response to extratropical atmospheric forcing, which is systematically and quantitatively studied through a series of RCDA experiments, indicates robust extratropical influence on some observed ENSO events. Furthermore, an event-by-event quantitative analysis shows significant differences of the extratropical influence among the observed ENSO events, both in its own strength and in its relation to tropical precursors such as the equatorial Pacific heat content anomaly. This study provides the first dynamic quantitative assessment of the extratropical influence on observed ENSO variability on an event-by-event basis.
Journal Article
Coupled data assimilation and parameter estimation in coupled ocean–atmosphere models: a review
Recent studies have started to explore coupled data assimilation (CDA) in coupled ocean–atmosphere models because of the great potential of CDA to improve climate analysis and seamless weather–climate prediction on weekly-to-decadal time scales in advanced high-resolution coupled models. In this review article, we briefly introduce the concept of CDA before outlining its potential for producing balanced and coherent weather–climate reanalysis and minimizing initial coupling shocks. We then describe approaches to the implementation of CDA and review progress in the development of various CDA methods, notably weakly and strongly coupled data assimilation. We introduce the method of coupled model parameter estimation (PE) within the CDA framework and summarize recent progress. After summarizing the current status of the research and applications of CDA-PE, we discuss the challenges and opportunities in high-resolution CDA-PE and nonlinear CDA-PE methods. Finally, potential solutions are laid out.
Journal Article
A CNN-Transformer Hybrid Framework for Multi-Label Predator–Prey Detection in Agricultural Fields
Accurate identification of predator–pest relationships is essential for implementing effective and sustainable biological control in agriculture. However, existing image-based methods struggle to recognize insect co-occurrence under complex field conditions, limiting their ecological applicability. To address this challenge, we propose a hybrid deep learning framework that integrates convolutional neural networks (CNNs) and Transformer architectures for multi-label recognition of predator–pest combinations. The model leverages a novel co-occurrence attention mechanism to capture semantic relationships between insect categories and employs a pairwise label matching loss to enhance ecological pairing accuracy. Evaluated on a field-constructed dataset of 5,037 images across eight categories, the model achieved an F1-score of 86.5%, mAP50 of 85.1%, and demonstrated strong generalization to unseen predator–pest pairs with an average F1-score of 79.6%. These results outperform several strong baselines, including ResNet-50, YOLOv8, and Vision Transformer. This work contributes a robust, interpretable approach for multi-object ecological detection and offers practical potential for deployment in smart farming systems, UAV-based monitoring, and precision pest management.
Journal Article
FABP5 regulates lipid metabolism to facilitate pancreatic neuroendocrine neoplasms progression via FASN mediated Wnt/β‐catenin pathway
Pancreatic neuroendocrine neoplasms (pNENs) are among the most frequently occurring neuroendocrine neoplasms (NENs) and require targeted therapy. High levels of fatty acid binding protein 5 (FABP5) are involved in tumor progression, but its role in pNENs remains unclear. We investigated the mRNA and protein levels of FABP5 in pNEN tissues and cell lines and found them to be upregulated. We evaluated changes in cell proliferation using CCK‐8, colony formation, and 5‐ethynyl‐2′‐deoxyuridine assays and examined the effects on cell migration and invasion using transwell assays. We found that knockdown of FABP5 suppressed the proliferation, migration, and invasion of pNEN cell lines, while overexpression of FABP5 had the opposite effect. Co‐immunoprecipitation experiments were performed to clarify the interaction between FABP5 and fatty acid synthase (FASN). We further showed that FABP5 regulates the expression of FASN via the ubiquitin proteasome pathway and both proteins facilitate the progression of pNENs. Our study demonstrated that FABP5 acts as an oncogene by promoting lipid droplet deposition and activating the WNT/β‐catenin signaling pathway. Moreover, the carcinogenic effects of FABP5 can be reversed by orlistat, providing a novel therapeutic intervention option. This study showed that FABP5 might play a role of oncogene through playing an auxo‐action for the deposition of lipid droplets and FABP5 is involved in activating the WNT/β‐catenin pathway. Moreover, those carcinogenic effects of FABP5 can be reversed by orlistat, providing novel choice for therapeutic intervention.
Journal Article
A Marine Object Detection Algorithm Based on SSD and Feature Enhancement
Autonomous detection and fishing by underwater robots will be the main way to obtain aquatic products in the future; sea urchins are the main research object of aquatic product detection. When the classical Single-Shot MultiBox Detector (SSD) algorithm is applied to the detection of sea urchins, it also has disadvantages of being inaccurate to small targets and insensitive to the direction of the sea urchin. Based on the classic SSD algorithm, this paper proposes a feature-enhanced sea urchin detection algorithm. Firstly, according to the spiny-edge characteristics of a sea urchin, a multidirectional edge detection algorithm is proposed to enhance the feature, which is taken as the 4th channel of image and the original 3 channels of underwater image together as the input for the further deep learning. Then, in order to improve the shortcomings of SSD algorithm’s poor ability to detect small targets, resnet 50 is used as the basic framework of the network, and the idea of feature cross-level fusion is adopted to improve the feature expression ability and strengthen semantic information. The open data set provided by the National Natural Science Foundation of China underwater Robot Competition will be used as the test set and training set. Under the same training and test conditions, the AP value of the algorithm in this paper reaches 81.0%, 7.6% higher than the classic SSD algorithm, and the confidence of small target analysis is also improved. Experimental results show that the algorithm in this paper can effectively improve the accuracy of sea urchin detection.
Journal Article
Hypoxia upregulating ACSS2 enhances lipid metabolism reprogramming through HMGCS1 mediated PI3K/AKT/mTOR pathway to promote the progression of pancreatic neuroendocrine neoplasms
Background
Pancreatic neuroendocrine neoplasms (pNENs) are relatively rare. Hypoxia and lipid metabolism-related gene acetyl-CoA synthetase 2 (ACSS2) is involved in tumor progression, but its role in pNENs is not revealed. This study showed that hypoxia can upregulate ACSS2, which plays an important role in the occurrence and development of pNENs through lipid metabolism reprogramming. However, the precise role and mechanisms of ACSS2 in pNENs remain unknown.
Methods
mRNA and protein levels of ACSS2 and 3-hydroxy-3-methylglutaryl-CoA synthase1 (HMGCS1) were detected using quantitative real-time PCR (qRT-PCR) and Western blotting (WB). The effects of ACSS2 and HMGCS1 on cell proliferation were examined using CCK-8, colony formation assay and EdU assay, and their effects on cell migration and invasion were examined using transwell assay. The interaction between ACSS2 and HMGCS1 was verified by Co-immunoprecipitation (Co-IP) experiments, and the functions of ACSS2 and HMGCS1 in vivo were determined by nude mouse xenografts.
Results
We demonstrated that hypoxia can upregulate ACSS2 while hypoxia also promoted the progression of pNENs. ACSS2 was significantly upregulated in pNENs, and overexpression of ACSS2 promoted the progression of pNENs and knockdown of ACSS2 and ACSS2 inhibitor (ACSS2i) treatment inhibited the progression of pNENs. ACSS2 regulated lipid reprogramming and the PI3K/AKT/mTOR pathway in pNENs, and ACSS2 regulated lipid metabolism reprogramming through the PI3K/AKT/mTOR pathway. Co-IP experiments indicated that HMGCS1 interacted with ACSS2 in pNENs. Overexpression of HMGCS1 can reverse the enhanced lipid metabolism reprogramming and tumor-promoting effects of knockdown of ACSS2. Moreover, overexpression of HMGCS1 reversed the inhibitory effect of knockdown of ACSS2 on the PI3K/AKT/mTOR pathway.
Conclusion
Our study revealed that hypoxia can upregulate the lipid metabolism-related gene ACSS2, which plays a tumorigenic effect by regulating lipid metabolism through activating the PI3K/AKT/mTOR pathway. In addition, HMGCS1 can reverse the oncogenic effects of ACSS2, providing a new option for therapeutic strategy.
Journal Article
A New De-Noising Method Based on Enhanced Time-Frequency Manifold and Kurtosis-Wavelet Dictionary for Rolling Bearing Fault Vibration Signal
The transient pulses caused by local faults of rolling bearings are an important measurement information for fault diagnosis. However, extracting transient pulses from complex nonstationary vibration signals with a large amount of background noise is challenging, especially in the early stage. To improve the anti-noise ability and detect incipient faults, a novel signal de-noising method based on enhanced time-frequency manifold (ETFM) and kurtosis-wavelet dictionary is proposed. First, to mine the high-dimensional features, the C-C method and Cao’s method are combined to determine the embedding dimension and delay time of phase space reconstruction. Second, the input parameters of the liner local tangent space arrangement (LLTSA) algorithm are determined by the grid search method based on Renyi entropy, and the dimension is reduced by manifold learning to obtain the ETFM with the highest time-frequency aggregation. Finally, a kurtosis-wavelet dictionary is constructed for selecting the best atom and eliminating the noise and reconstruct the defective signal. Actual simulations showed that the proposed method is more effective in noise suppression than traditional algorithms and that it can accurately reproduce the amplitude and phase information of the raw signal.
Journal Article
Deep Reconstruction Transfer Convolutional Neural Network for Rolling Bearing Fault Diagnosis
Deep transfer learning has been widely used to improve the versatility of models. In the problem of cross-domain fault diagnosis in rolling bearings, most models require that the given data have a similar distribution, which limits the diagnostic effect and generalization of the model. This paper proposes a deep reconstruction transfer convolutional neural network (DRTCNN), which satisfies the domain adaptability of the model under cross-domain conditions. Firstly, the model uses a deep reconstruction convolutional automatic encoder for feature extraction and data reconstruction. Through sharing parameters and unsupervised training, the structural information of target domain samples is effectively used to extract domain-invariant features. Secondly, a new subdomain alignment loss function is introduced to align the subdomain distribution of the source domain and the target domain, which can improve the classification accuracy by reducing the intra-class distance and increasing the inter-class distance. In addition, a label smoothing algorithm considering the credibility of the sample is introduced to train the model classifier to avoid the impact of wrong labels on the training process. Three datasets are used to verify the versatility of the model, and the results show that the model has a high accuracy and stability.
Journal Article
A decoy oligodeoxynucleotide favors the differentiation of CpG ODN-induced B cells into IL-10-producing Breg-like cells over plasma cells by restoring IRF4/IRF8 imbalance
The imbalanced expression of interferon regulatory factor (IRF) 4 and IRF8 in activated B cells significantly influences their differentiation and promotes the development of immune-related diseases. Restoring abnormal B cells to appropriate responses may treat these diseases. In this study, an oligodeoxynucleotide (ODN) S2, designed according to the consensus sequence recognized by IRFs in interferon-stimulated response elements, was used as an immunomodulator to investigate its effects on mouse splenic B cells stimulated with the TLR9 agonist CpG ODN, either alone or in combination with antigen, and to explore its underlying mechanisms. The results showed that S2 had a significant negative regulatory effect on CpG ODN induced B cell activation. It also significantly downregulated the production of IL-6 and the percentage of IL-6
+
B cells in splenocytes stimulated by CpG ODN, but significantly upregulated the percentage of IL-10
+
B cells. Interestingly, S2 impaired antibody production both in vitro and in vivo, but rescued mice from lethal inflammatory responses. Further studies showed that S2 could bind IRF4 and IRF8 with high affinity, slightly upregulate phosphorylated IRF4, reduce the expression and nuclear translocation of IRF8, and alter the proportion of IRF4
+
, IRF8
+
or double-positive B cells in spleen cells induced by CpG ODN. These results suggest that S2 acts as a decoy directing some B cells to differentiate into IL-10-producing Breg-like cells rather than plasma cells by restoring the TLR9 signal-induced IRF4 and IRF8 ratio imbalance. This indicates its potential as an immunomodulator for the treatment of diseases associated with B-cell abnormalities.
Graphical Abstract
Journal Article