10,832 results on '"Ling-Chen"'
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2. A visceral organ function-focused therapeutic strategy using a 6-hour time window for patients with acute type a aortic dissection complicated by mesenteric malperfusion
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Ling-chen Huang, Shuang-kun Chen, Hua Peng, and Xi-jie Wu
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Acute type a aortic dissection ,Mesenteric malperfusion ,Treatment strategy ,6-hour time window ,Visceral organ function ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Background Acute type A aortic dissection (ATAAD) complicated by mesenteric malperfusion is a critical and complicated condition. The optimal treatment strategy remains controversial, debate exists as to whether aortic dissection or mesenteric malperfusion should be addressed first, and the exact time window for mesenteric ischemia intervention is still unclear. To solve this problem, we developed a new concept based on the pathophysiological mechanism of mesenteric ischemia, using a 6-hour time window to divide newly admitted patients by the time from onset to admission, applying different treatment protocols to improve the clinical outcomes of patients with ATAAD complicated by mesenteric malperfusion. Methods This was a retrospective study that covered a five-year period. From July 2018 to December 2020(phase I), all patients underwent emergency open surgery. From January 2021 to June 2023(phase II), patients with an onset within 6 h all underwent open surgical repair, followed by immediately postoperative examination if the malperfusion is suspected, while the restoration of mesenteric perfusion and visceral organ function was performed first, followed by open repair, in patients with an onset beyond 6 h. Results There were no significant differences in baseline and surgical data. In phase I, eleven patients with mesenteric malperfusion underwent open surgery, while in phase II, our novel strategy was applied, with sixteen patients with an onset greater than 6 h and eleven patients with an onset less than 6 h. During the waiting period, none died of aortic rupture, but four patients died of organ failure, twelve patients had organ function improvement and underwent surgery successfully survived. The overall mortality rate decreased with the use of this novel strategy (54.55% vs. 18.52%, p = 0.047). Furthermore, the surgical mortality rate between the two periods showed even stronger statistical significance (54.55% vs. 4.35%, p = 0.022). Moreover, the proportions of patients with sepsis and multiorgan failure also showed differences. Conclusions Our novel strategy for patients with ATAAD complicated by mesenteric malperfusion not only improves the surgical success rate but also reduces the overall mortality rate.
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- 2024
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3. The top 100 most cited articles on axon regeneration from 2003 to 2023: a bibliometric analysis
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Saijilafu, Ling-Chen Ye, Jing-Yu Zhang, and Ren-Jie Xu
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axon regeneration ,bibliometric analysis ,Web of Science Core Collection ,VOSviewer ,CiteSpace ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
ObjectiveIn this study, we used a bibliometric and visual analysis to evaluate the characteristics of the 100 most cited articles on axon regeneration.MethodsThe 100 most cited papers on axon regeneration published between 2003 and 2023 were identified by searching the Web of Science Core Collection database. The extracted data included the title, author, keywords, journal, publication year, country, and institution. A bibliometric analysis was subsequently undertaken.ResultsThe examined set of 100 papers collectively accumulated a total of 39,548 citations. The number of citations for each of the top 100 articles ranged from 215 to 1,604, with a median value of 326. The author with the most contributions to this collection was He, Zhigang, having authored eight papers. Most articles originated in the United States (n = 72), while Harvard University was the institution with the most cited manuscripts (n = 19). Keyword analysis unveiled several research hotspots, such as chondroitin sulfate proteoglycan, alternative activation, exosome, Schwann cells, axonal protein synthesis, electrical stimulation, therapeutic factors, and remyelination. Examination of keywords in the articles indicated that the most recent prominent keyword was “local delivery.”ConclusionThis study offers bibliometric insights into axon regeneration, underscoring that the United States is a prominent leader in this field. Our analysis highlights the growing relevance of local delivery systems in axon regeneration. Although these systems have shown promise in preclinical models, challenges associated with long-term optimization, agent selection, and clinical translation remain. Nevertheless, the continued development of local delivery technologies represents a promising pathway for achieving axon regeneration; however, additional research is essential to fully realize their potential and thereby enhance patient outcomes.
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- 2024
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4. Prolonged efficacy of cefazolin in intraosseous regional prophylaxis for total knee arthroplasty: a rabbit model study
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Jing-Yu Zhang, Ling-Chen Ye, Yu-bo Liu, Xiao Yu, Xiang-Xin Zhang, Guang-Xiang Chen, and Ren-Jie Xu
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Blood concentration ,Cefazolin ,Intraosseous regional administration ,Periprosthetic joint infection ,Total knee arthroplasty ,Diseases of the musculoskeletal system ,RC925-935 - Abstract
Abstract Background A novel approach known as intraosseous regional administration (IORA) has emerged as a technique for delivering prophylactic antibiotics, and it results in higher tissue concentrations around the knee. It is hypothesized that IORA of cefazolin for antibiotic prophylaxis during total knee arthroplasty will result in sustained effective levels for a longer duration. The aim of the current study was to investigate temporal changes in peri-knee cefazolin blood concentrations after IORA of cefazolin. Methods Twelve rabbits were randomly divided into two groups, with six rabbits in each group. In control group a single intravenous bolus injection of cefazolin (10 mL, 100 mg) was administered into the marginal ear vein. In experimental groupexperimental group the same dose of cefazolin was injected into the left tibial marrow cavity after tourniquet inflation at the base of the left thigh. Blood samples were collected periodically at different timepoints, and cefazolin concentrations were determined. Results The intraosseous treatment resulted in significant differences in plasma cefazolin concentrations at all timepoints. Experimental group exhibited higher plasma cefazolin concentrations than control group. Conclusions Cefazolin in intraosseous regional prophylaxis exhibits effectiveness in intraoperative antibiotic prophylaxis by maintaining concentrations above the minimum inhibitory concentration for extended durations, rather than relying solely on high concentrations.
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- 2024
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5. Correlation of preclinical and clinical biomarkers with efficacy and toxicity of cancer immunotherapy
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Lin-Peng Zheng, Jing Yang, Xie-Wan Chen, Ling-Chen Li, and Jian-Guo Sun
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival after ICIs treatment, and many patients may experience other undesirable clinical features. Therefore, biomarkers are critical for patients to choose exact optimum therapy. Here, we reviewed existing preclinical and clinical biomarkers of immunotherapeutic efficacy and immune-related adverse events (irAEs). Based on efficacy prediction, pseudoprogression, hyperprogressive disease, or irAEs, these biomarkers were divided into cancer cell-derived biomarkers, tumor microenvironment-derived biomarkers, host-derived biomarkers, peripheral blood biomarkers, and multi-modal model and artificial intelligence assessment-based biomarkers. Furthermore, we describe the relation between ICIs efficacy and irAEs. This review provides the overall perspective of biomarkers of immunotherapeutic outcome and irAEs prediction during ICIs treatment.
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- 2023
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6. Isoaaptamine increases ROS levels causing autophagy and mitochondria-mediated apoptosis in glioblastoma multiforme cells
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Zhi-Hong Wen, Hsiao-Mei Kuo, Po-Chang Shih, Ling-Chen Hsu, Jimmy Ming-Jung Chuang, Nan-Fu Chen, Hsi-Wen Sun, Hsin-Tzu Liu, Chun-Sung Sung, and Wu-Fu Chen
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Natural product ,Mitochondria ,Apoptosis ,Autophagy ,Isoaaptamine ,Reactive oxygen species ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Glioblastoma multiforme (GBM) is a common central nervous system disease with a poor prognosis; its five-year survival rate is
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- 2023
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7. YAP1 as a Novel Negative Biomarker of Immune Checkpoint Inhibitors for EGFR-Mutant Non-Small-Cell Lung Cancer
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Ling-Chen Li, Xie-Wan Chen, Ling Fang, Chun-Li Jian, Yong-Xin Yu, Xing-Yun Liao, and Jian-Guo Sun
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Diseases of the respiratory system ,RC705-779 - Abstract
Background. Immune checkpoint inhibitors (ICIs) have become a standard care in non-small-cell lung cancer (NSCLC). However, its application to epidermal growth factor receptor (EGFR)-mutant NSCLC patients is confronted with drug resistance. This study aimed to clarify the potential role of Yes1-associated transcriptional regulator (YAP1) in ICIs treatment for EGFR-mutant NSCLC population. Methods. All the clinical data of NSCLC were downloaded from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) for GSE11969 and GSE72094. Based on YAP1 expression, all the NSCLC patients including the EGFR-mutant and EGFR-wildtype (WT) patients were divided into two groups, YAP1_High and YAP1_Low. Using cBioPortal, genetic alterations were analyzed for identification of immunogenicity in EGFR-mutant NSCLC. MR analysis was used to analyze the hub gene of EGFR. The infiltration of immune cells and the expression of the identified tumor-associated antigens were identified with TIMER. By graph learning-based dimensionality reduction analysis, the immune landscape was visualized. Moreover, survival analysis was performed to verify the predictive value of YAP1 in ICIs treatment for EGFR-mutant NSCLC population using Ren’s research data (NCT03513666). Results. YAP1 was a poor prognostic factor of EGFR-mutant NSCLC population rather than lung adenocarcinoma (LUAD) patients. MR analysis revealed that the EGFR gene regulated YAP1 expression. YAP1 was identified as a hub gene closely associated with immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population in TCGA LUAD. Tumors with YAP1_High showed an immune-“cold” and immunosuppressive phenotype, whereas those with YAP1_Low demonstrated an immune-“hot” and immunoactive phenotype. More importantly, it was verified that YAP1_High subpopulation had a significantly shorter progression-free survival (PFS) and overall survival (OS) after ICIs treatment in EGFR-mutant NSCLC patients in the clinical trial. Conclusions. YAP1 mediates immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population. YAP1 is a novel negative biomarker of ICIs treatment in EGFR-mutant NSCLC population. Clinical Trials. This trial is registered with NCT03513666.
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- 2023
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8. HiReview: Hierarchical Taxonomy-Driven Automatic Literature Review Generation
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Hu, Yuntong, Li, Zhuofeng, Zhang, Zheng, Ling, Chen, Kanjiani, Raasikh, Zhao, Boxin, and Zhao, Liang
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Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
In this work, we present HiReview, a novel framework for hierarchical taxonomy-driven automatic literature review generation. With the exponential growth of academic documents, manual literature reviews have become increasingly labor-intensive and time-consuming, while traditional summarization models struggle to generate comprehensive document reviews effectively. Large language models (LLMs), with their powerful text processing capabilities, offer a potential solution; however, research on incorporating LLMs for automatic document generation remains limited. To address key challenges in large-scale automatic literature review generation (LRG), we propose a two-stage taxonomy-then-generation approach that combines graph-based hierarchical clustering with retrieval-augmented LLMs. First, we retrieve the most relevant sub-community within the citation network, then generate a hierarchical taxonomy tree by clustering papers based on both textual content and citation relationships. In the second stage, an LLM generates coherent and contextually accurate summaries for clusters or topics at each hierarchical level, ensuring comprehensive coverage and logical organization of the literature. Extensive experiments demonstrate that HiReview significantly outperforms state-of-the-art methods, achieving superior hierarchical organization, content relevance, and factual accuracy in automatic literature review generation tasks.
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- 2024
9. An Inertial Bregman Proximal DC Algorithm for Generalized DC Programming with Application to Data Completion
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Pan, Chenjian, Zhou, Yingxin, He, Hongjin, and Ling, Chen
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Mathematics - Optimization and Control - Abstract
In this paper, we consider a class of generalized difference-of-convex functions (DC) programming, whose objective is the difference of two convex (not necessarily smooth) functions plus a decomposable (possibly nonconvex) function with Lipschitz gradient. By employing the Fenchel-Young inequality and Moreau decomposition theorem, we introduce an inertial Bregman proximal DC algorithm to solve the problem under consideration. Our algorithmic framework is able to fully exploit the decomposable structure of the generalized DC programming such that each subproblem of the algorithm is enough easy in many cases. Theoretically, we show that the sequence generated by the proposed algorithm globally converges to a critical point under the Kurdyka-{\L}ojasiewicz condition. A series of numerical results demonstrate that our algorithm runs efficiently on matrix and tensor completion problems., Comment: This paper has been accepted by Communications in Optimization Theory
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- 2024
10. Correction: Stable atrogin-1 (Fbxo32) and MuRF1 (Trim63) gene expression is involved in the protective mechanism in soleus muscle of hibernating Daurian ground squirrels (Spermophilus dauricus)
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Kai Dang, Ya-Zhao Li, Ling-Chen Gong, Wei Xue, Hui-Ping Wang, Nandu Goswami, and Yun-Fang Gao
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Science ,Biology (General) ,QH301-705.5 - Published
- 2022
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11. Design, synthesis and biological activity against estrogen receptor-dependent breast cancer of furo[1]benzofuran derivatives
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Li-Ping Jin, Chao Zhang, Qian Xie, Jing Xu, Lin Wang, Ling-Chen Yang, Er-Fang Huang, David Chi-Cheong Wan, and Chun Hu
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Estrogen receptor ,Breast cancer ,Inhibitors ,Synthesis ,Heterocycles ,Docking ,Chemistry ,QD1-999 - Abstract
The docking study on a series of furo[1]benzofuran derivatives with ERα has been demonstrated. The synthesis and characterization of a series of furo[1]benzofuran derivatives were described. All the target compounds were conducted to in vitro for the inhibitory activities against human breast cancer strains T-47D, MCF-7 and toxicity against human liver normal cell strains HL7702 via MTT assay. Most of the target compounds possessed anti-estrogen receptor-dependent breast cancer activities with weak toxicity to healthy cell strains. The preliminary structure–activity relationships were discussed.
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- 2022
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12. Investigating Pre-Service Teachers' Satisfaction of Integrating Drama-Based Activities into Practical Science Teaching
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Chiu-Hsia Huang, Ya-Ling Chen, and Holger Haas
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This study explored the views of 63 Taiwanese pre-service teachers who had participated in a workshop about the value of integrating drama-based approaches in their practical science learning. It was primarily designed to investigate the pedagogical approach of Heathcote and other founders of process drama. In addition, it examined specific claims that it immerses learners in an enjoyable and social learning environment (Poston-Anderson, 2008; Lin, 2017) and that learners can practice core scientific skills such as making predictions, observing, and then validating their predictions (Weisberg et al., 2016). Following the workshop, participants completed an anonymized online questionnaire. Descriptive data analysis indicated that most participants (75%) strongly agreed that integrating drama-based approaches into practical science teaching was satisfying. Of the remainder, 20.7% agreed, 2.1% neither agreed nor disagreed, 2.2% disagreed, and none strongly disagreed with this statement. Moreover, 34.9% of the participants lacked opportunities to experience improvisation and integration of drama-based teaching in practical science. The study indicated that a drama-based approach can be a highly effective strategy for enhancing practical science teaching among pre-service teachers. Furthermore, the findings provide valuable insights into the factors influencing drama-based teaching in practical science. They suggest it could be an excellent strategy to stimulate learners' interest in science and interdisciplinary science-related subjects and improve their science skills. Teachers could thus provide young children with similar drama-based teaching in practical science activities to promote their learning of science. Finally, the study offers a set of important recommendations for future pedagogical policymaking and further research by drama-based practitioners.
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- 2024
13. Endovascular surgery for thoracic aortic pathologies involving the aortic arch
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Heng Lu, Ling-chen Huang, and Liang-wan Chen
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aortic arch pathology ,endovascular surgery ,TEVAR ,in situ fenestration ,aortic arch reconstruction ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
BackgroundAortic arch pathologies are serious clinical conditions associated with a very dismal prognosis. Traditional open surgery has a high mortality and is not suitable for critically ill patients. Recently years, endovascular treatment of thoracic aorta has made rapid progress and has been gradually applied to the treatment of aortic arch pathologies. However, maintaining cerebral blood flow during endovascular treatment of aortic arch lesions remains a challenge at this time. This study aims to evaluate the feasibility, efficacy, and safety of endovascular treatment of thoracic aortic pathologies involving the aortic arch, and to present initial experience with this technique.MethodsFrom October 2016 to December 2020, patients who met the inclusion criteria were enrolled. All patients underwent thoracic endovascular aortic repair with the proximal landing zone of the stent-graft in the aortic arch at Ishimaru zones 0–1, in which cerebral flow needs to be maintained during surgery, and the supra-aortic branches were reconstruction with either in situ fenestration or the chimney technique.ResultsA total of 62 cases with lesions involving the arch were treated with endovascular surgery. Total supra-aortic branches reconstruction was successfully performed in 51 cases, the left carotid artery (LCA) and the innominate artery reconstruction were performed in eight cases, the left subclavian artery (LSA) and the LCA were reconstructed in three patients. Among them, the in situ fenestration or chimney repair technique for the LSA was successful performed in 42 and 12 cases. However, in 20 patients, attempts to reconstruction the LSA using the fenestration technique were unsuccessful due to tortuous and angulated vessels. Early mortality was 6.45%. No neurological complications related to surgery occurred. Computer tomography images at post-operative follow-up (mean 3.51 months) confirmed patency of all branch stents without any signs of endoleaks, migration, conversion to retrograde dissection or receive open-heart surgery.ConclusionThe endovascular technique is an effective, feasible, safe and repeatable method to reconstruct the aortic arch, which allows for the reconstruction of the supra-aortic branches.
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- 2022
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14. Totally endoscopic mitral valve surgery: early experience in 188 patients
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Yi Chen, Ling-chen Huang, Dao-zhong Chen, Liang-wan Chen, Zi-he Zheng, and Xiao-fu Dai
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Minimally invasive ,Totally endoscopic ,Mitral valve surgery ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Introduction Totally endoscopic technique has been widely used in cardiac surgery, and minimally invasive totally endoscopic mitral valve surgery has been developed as an alternative to median sternotomy for many patients with mitral valve disease. In this study, we describe our experience about a modified minimally invasive totally endoscopic mitral valve surgery and reported the preliminary results of totally endoscopic mitral valve surgery. The aim of this retrospective study is to evaluate the results of totally endoscopic technique in mitral valve surgery. Material and methods We retrospectively reviewed the profiles of 188 patients who were treated for mitral valve disease by modified totally endoscopic mitral valve surgery at our institution between January 2019 and December 2020. The procedure was performed under endoscopic right minithoracotomy and with femoro-femoral cannulation using the single two-stage venous cannula. Results A total of 188 patients underwent total endoscopic mitral valve surgery. Fifty-six patients had concomitant tricuspid valvuloplasty, 11 patients underwent concomitant ablation of atrial fibrillation and atrial septal defect repair was performed in three patients. Only one patient postoperatively died of multi-organ failure. Two patients were converted to median sternotomy. Except for one patient underwent operation to stop the bleeding from the incision site, no other serious complications nor reintervention occurred during the follow-up period. Conclusions The modified totally endoscopic mitral valve surgery performed at our institution is technically feasible and safe with the same efficacy as reported studies.
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- 2021
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15. Peripheral vascular complications following totally endoscopic cardiac surgery
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Ling-chen Huang, Qi-chen Xu, Dao-zhong Chen, Xiao-fu Dai, and Liang-wan Chen
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Totally endoscopic ,Cardiac surgery ,Vascular complication ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Background Clinical application of minimally invasive cardiac surgery has increased annually. Cardiopulmonary bypass is established by peripheral cannulation during minimally invasive cardiac surgery. The methodology of peripheral cannulation has unique characteristics, which have associated risks and complications. Few studies have been conducted on this topic. In this study, we focused on complications of peripheral cannulation in totally endoscopic cardiac surgery. Methods Patients who underwent totally endoscopic cardiac surgery with cardiopulmonary bypass established by peripheral cannulation at our institution between January 2019 and June 2020 were reviewed. Specific cannulation strategies and related cannulation complications were noted. Results One hundred forty-eight patients underwent totally endoscopic cardiac surgery. One hundred forty-eight cannulations were performed in the femoral artery and vein, and eleven were performed in the internal jugular vein (combined with the femoral vein). The median size of the femoral artery cannula was 22Fr, and that of the venous canula was 24Fr. One patient died of retroperitoneal haematoma due to femoral artery injury. Three patients had postoperative lower limb oedema. One patient had a postoperative diagnosis of femoral vein thrombosis. Conclusions Different from cannulation in patients with aortic dissection and aneurysms, femoral artery cannulation is safe in totally endoscopic cardiac surgery. Venous cannulation is characterized by a large-bore venous cannula and a short period of use. There are few reports about complications of venous cannulation. The main complication in this study was mechanical injury, and the key to preventing this injury is meticulous manipulation during surgery.
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- 2021
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16. PIXELMOD: Improving Soft Moderation of Visual Misleading Information on Twitter
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Paudel, Pujan, Ling, Chen, Blackburn, Jeremy, and Stringhini, Gianluca
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computers and Society - Abstract
Images are a powerful and immediate vehicle to carry misleading or outright false messages, yet identifying image-based misinformation at scale poses unique challenges. In this paper, we present PIXELMOD, a system that leverages perceptual hashes, vector databases, and optical character recognition (OCR) to efficiently identify images that are candidates to receive soft moderation labels on Twitter. We show that PIXELMOD outperforms existing image similarity approaches when applied to soft moderation, with negligible performance overhead. We then test PIXELMOD on a dataset of tweets surrounding the 2020 US Presidential Election, and find that it is able to identify visually misleading images that are candidates for soft moderation with 0.99% false detection and 2.06% false negatives.
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- 2024
17. TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs
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Li, Zhuofeng, Gou, Zixing, Zhang, Xiangnan, Liu, Zhongyuan, Li, Sirui, Hu, Yuntong, Ling, Chen, Zhang, Zheng, and Zhao, Liang
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Text-Attributed Graphs (TAGs) augment graph structures with natural language descriptions, facilitating detailed depictions of data and their interconnections across various real-world settings. However, existing TAG datasets predominantly feature textual information only at the nodes, with edges typically represented by mere binary or categorical attributes. This lack of rich textual edge annotations significantly limits the exploration of contextual relationships between entities, hindering deeper insights into graph-structured data. To address this gap, we introduce Textual-Edge Graphs Datasets and Benchmark (TEG-DB), a comprehensive and diverse collection of benchmark textual-edge datasets featuring rich textual descriptions on nodes and edges. The TEG-DB datasets are large-scale and encompass a wide range of domains, from citation networks to social networks. In addition, we conduct extensive benchmark experiments on TEG-DB to assess the extent to which current techniques, including pre-trained language models, graph neural networks, and their combinations, can utilize textual node and edge information. Our goal is to elicit advancements in textual-edge graph research, specifically in developing methodologies that exploit rich textual node and edge descriptions to enhance graph analysis and provide deeper insights into complex real-world networks. The entire TEG-DB project is publicly accessible as an open-source repository on Github, accessible at https://github.com/Zhuofeng-Li/TEG-Benchmark.
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- 2024
18. Combined femoral and axillary perfusion strategy for Stanford type a aortic dissection repair
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Ling-chen Huang, Qi-chen Xu, Dao-zhong Chen, Xiao-fu Dai, and Liang-wan Chen
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Aortic dissection ,Artery cannulation ,Malperfusion ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Background The optimal cannulation strategy in surgery for Stanford type A aortic dissection is critical to patient survival but remains controversial. Different cannulation strategies have their own advantages and drawbacks during cardiopulmonary bypass. Our centre used a combined femoral and axillary perfusion strategy for the surgical treatment of type A aortic dissection. The purpose of this study was to review and clarify the clinical outcome of femoral artery cannulation combined with axillary artery cannulation for the treatment of Stanford type A aortic dissection. Methods We performed a retrospective study that included 327 patients who were surgically treated for type A aortic dissection in our institution from January 2017 to June 2019. Femoral and axillary artery cannulation was used to establish cardiopulmonary bypass in patients with type A aortic dissection. The demographic data, surgical data, and clinical results of the patients were calculated. Results Femoral artery combined with axillary artery cannulation was technically successful in 327 patients. The cardiopulmonary bypass time was 141.60 ± 34.89 min, and the selective antegrade cerebral perfusion time was 14.94 ± 2.76 min. The early mortality rate was 3.06%. The incidence of permanent neurologic dysfunction was 0.92%. Sixteen patients had postoperative renal insufficiency, and five patients had liver failure. Conclusion Femoral artery combined with axillary artery cannulation for type A aortic dissection can significantly improve the prognosis of patients, especially in terms of cerebral protection, and can reduce the occurrence of adverse malperfusion syndrome and neurological complications.
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- 2020
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19. The use of the Scar Cosmesis Assessment and rating scale to evaluate the cosmetic outcomes of totally thoracoscopic cardiac surgery
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Ling-chen Huang, Dao-zhong Chen, Liang-wan Chen, Qi-chen Xu, Zi-he Zheng, and Xiao-fu Dai
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Median Sternotomy ,Totally thoracoscopic ,Cardiac surgery ,Cosmetic outcomes ,Scar assessment ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Background Conventional median sternotomy is widely used in cardiac surgery, while thoracoscopic cardiac surgery, which is considered to have aesthetic advantages, is being performed increasingly more often in China because patients’ requests for minimally invasive procedures yielding aesthetically pleasing results have significantly increased. Few studies have been conducted to assess surgical scars after cardiac surgery. Compared to the median sternotomy approach, multiple-incision totally thoracoscopic cardiac surgery requires smaller but numerous and scattered incisions. In addition to two working ports on the upper and lower margins of the right breast, an inguinal incision and an axillary incision are made. Therefore, does totally thoracoscopic cardiac surgery truly have aesthetic advantages? This study has the following objectives: (a) to compare median sternotomy cardiac surgery and total thoracoscopic cardiac surgery in terms of the long-term cosmetic outcomes of post-operative scars and (b) to evaluate the effectiveness of the Scar Cosmesis Assessment and Rating scale in combination with the numeric rating scale in the assessment of surgical scars after cardiac surgery. Methods Consecutive patients who visited our institution from January 2019 to May 2019 for cardiac surgery via median sternotomy or the totally thoracoscopic approach and followed up for at least one year were included. Inter-rater reliability, internal consistency and convergent validity were evaluated for the Scar Cosmesis Assessment and Rating scale and the numeric rating scale. Clinical characteristics and the scores of the two scales were compared between the two groups using Student’s t test or the Mann-Whitney U test. Results Thirty-one patients underwent cardiac surgery via the totally thoracoscopic approach, and 42 patients underwent cardiac surgery via the median sternotomy approach. No significant differences were found in the demographic or clinical data between the two groups. The validity and reliability of the two scales were satisfactory. For the Scar Cosmesis Assessment and Rating scale, the median sternotomy group scored statistically significantly higher than did the totally thoracoscopic group on the “overall impression” and “patient question” subscales (P
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- 2020
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20. Health-related quality of life following minimally invasive totally endoscopic mitral valve surgery
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Ling-chen Huang, Dao-zhong Chen, Liang-wan Chen, Qi-chen Xu, Zi-he Zheng, and Xiao-fu Dai
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Minimally invasive ,Quality of life ,Mitral valve surgery ,SF-36 ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Background To compare the impact of two different types of mitral valve surgery on health-related quality of life, we conducted a retrospective study comparing modified totally endoscopic mitral valve surgery with median sternotomy mitral valve surgery. Methods A total of 163 patients who underwent mitral valve surgery at our institution between January 1, 2019 and December 31, 2019 were enrolled. For these 163 patients, mitral valve surgery was performed using either a modified totally endoscopic approach or median sternotomy approach. We used the numerical rating scale and the Scar Cosmesis Assessment and Rating Scale to measure pain intensity and the aesthetic appearance of the surgical incision and used the MOS 36-item Short-Form Health Survey to assess health-related quality of life. Results Seventy-eight patients underwent the modified totally endoscopic mitral valve surgery, and eighty-five patients underwent the median sternotomy mitral valve surgery. The two groups of patients were similar in terms of demographics and echocardiography findings. The number of bioprosthetic valve replacements performed was significantly higher in the totally endoscopic group than in the median sternotomy group (p = 0.04), whereas the subvalvular apparatus was less preserved in only 33 cases in the totally endoscopic group (p = 0.01). The rate of postoperative adverse events was similar between the two groups. The pain was mild and aesthetic appearance was significantly better in the totally endoscopic approach group than in the sternotomy approach group. Significant differences in the scores for the bodily pain and mental health subscales of the MOS 36-item Short-Form Health Survey were found between the two groups. Conclusions Compared with median sternotomy mitral valve surgery, totally endoscopic mitral valve surgery has an equally good treatment effect, improving patient’s health-related quality of life with a better cosmetic appearance and a lower pain intensity. Our study suggested that the totally endoscopic approach is superior to the median sternotomy approach in terms of pain intensity, aesthetic appearance and health-related quality of life.
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- 2020
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21. Generating geologically realistic 3D reservoir facies models using deep learning of sedimentary architecture with generative adversarial networks
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Tuan-Feng Zhang, Peter Tilke, Emilien Dupont, Ling-Chen Zhu, Lin Liang, and William Bailey
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Geological facies ,Geomodeling ,Data conditioning ,Generative adversarial networks ,Science ,Petrology ,QE420-499 - Abstract
Abstract This paper proposes a novel approach for generating 3-dimensional complex geological facies models based on deep generative models. It can reproduce a wide range of conceptual geological models while possessing the flexibility necessary to honor constraints such as well data. Compared with existing geostatistics-based modeling methods, our approach produces realistic subsurface facies architecture in 3D using a state-of-the-art deep learning method called generative adversarial networks (GANs). GANs couple a generator with a discriminator, and each uses a deep convolutional neural network. The networks are trained in an adversarial manner until the generator can create “fake” images that the discriminator cannot distinguish from “real” images. We extend the original GAN approach to 3D geological modeling at the reservoir scale. The GANs are trained using a library of 3D facies models. Once the GANs have been trained, they can generate a variety of geologically realistic facies models constrained by well data interpretations. This geomodelling approach using GANs has been tested on models of both complex fluvial depositional systems and carbonate reservoirs that exhibit progradational and aggradational trends. The results demonstrate that this deep learning-driven modeling approach can capture more realistic facies architectures and associations than existing geostatistical modeling methods, which often fail to reproduce heterogeneous nonstationary sedimentary facies with apparent depositional trend.
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- 2019
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22. TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
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Zhang, Zheng, Hu, Yuntong, Pan, Bo, Ling, Chen, and Zhao, Liang
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum of real-world scenarios. Despite the potential for deeper insights, existing TAG representation learning primarily relies on supervised methods, necessitating extensive labeled data and limiting applicability across diverse contexts. This paper introduces a new self-supervised learning framework, Text-And-Graph Multi-View Alignment (TAGA), which overcomes these constraints by integrating TAGs' structural and semantic dimensions. TAGA constructs two complementary views: Text-of-Graph view, which organizes node texts into structured documents based on graph topology, and the Graph-of-Text view, which converts textual nodes and connections into graph data. By aligning representations from both views, TAGA captures joint textual and structural information. In addition, a novel structure-preserving random walk algorithm is proposed for efficient training on large-sized TAGs. Our framework demonstrates strong performance in zero-shot and few-shot scenarios across eight real-world datasets.
- Published
- 2024
23. Link Prediction on Textual Edge Graphs
- Author
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Ling, Chen, Li, Zhuofeng, Hu, Yuntong, Zhang, Zheng, Liu, Zhongyuan, Zheng, Shuang, and Zhao, Liang
- Subjects
Computer Science - Social and Information Networks - Abstract
Textual-edge Graphs (TEGs), characterized by rich text annotations on edges, are increasingly significant in network science due to their ability to capture rich contextual information among entities. Existing works have proposed various edge-aware graph neural networks (GNNs) or let language models directly make predictions. However, they often fall short of fully capturing the contextualized semantics on edges and graph topology, respectively. This inadequacy is particularly evident in link prediction tasks that require a comprehensive understanding of graph topology and semantics between nodes. In this paper, we present a novel framework - Link2Doc, designed especially for link prediction on textual-edge graphs. Specifically, we propose to summarize neighborhood information between node pairs as a human-written document to preserve both semantic and topology information. A self-supervised learning model is then utilized to enhance GNN's text-understanding ability from language models. Empirical evaluations, including link prediction, edge classification, parameter analysis, runtime comparison, and ablation studies, on four real-world datasets demonstrate that Link2Doc achieves generally better performance against existing edge-aware GNNs and pre-trained language models in predicting links on TEGs.
- Published
- 2024
24. GRAG: Graph Retrieval-Augmented Generation
- Author
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Hu, Yuntong, Lei, Zhihan, Zhang, Zheng, Pan, Bo, Ling, Chen, and Zhao, Liang
- Subjects
Computer Science - Machine Learning - Abstract
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation graphs, social media, and knowledge graphs. To overcome this limitation, we introduce Graph Retrieval-Augmented Generation (GRAG), which tackles the fundamental challenges in retrieving textual subgraphs and integrating the joint textual and topological information into Large Language Models (LLMs) to enhance its generation. To enable efficient textual subgraph retrieval, we propose a novel divide-and-conquer strategy that retrieves the optimal subgraph structure in linear time. To achieve graph context-aware generation, incorporate textual graphs into LLMs through two complementary views-the text view and the graph view-enabling LLMs to more effectively comprehend and utilize the graph context. Extensive experiments on graph reasoning benchmarks demonstrate that in scenarios requiring multi-hop reasoning on textual graphs, our GRAG approach significantly outperforms current state-of-the-art RAG methods., Comment: 13 pages, 5 figures
- Published
- 2024
25. Simulating optically-active spin defects with a quantum computer
- Author
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Baker, Jack S., Casares, Pablo A. M., Zini, Modjtaba Shokrian, Thik, Jaydeep, Banerjee, Debasish, Ling, Chen, Delgado, Alain, and Arrazola, Juan Miguel
- Subjects
Quantum Physics ,Condensed Matter - Materials Science - Abstract
There is a pressing need for more accurate computational simulations of the opto-electronic properties of defects in materials to aid in the development of quantum sensing platforms. In this work, we explore how quantum computers could be effectively utilized for this purpose. Specifically, we develop fault-tolerant quantum algorithms to simulate optically active defect states and their radiative emission rates. We employ quantum defect embedding theory to translate the Hamiltonian of a defect-containing supercell into a smaller, effective Hamiltonian that accounts for dielectric screening effects. Our approach integrates block-encoding of the dipole operator with quantum phase estimation to selectively sample the optically active excited states that exhibit the largest dipole transition amplitudes. We also provide estimates of the quantum resources required to simulate a negatively-charged boron vacancy in a hexagonal boron nitride cluster. We conclude by offering a forward-looking perspective on the potential of quantum computers to enhance quantum sensor capabilities and identify specific scenarios where quantum computing can resolve problems traditionally challenging for classical computers., Comment: 18 pages, 4 figures, 2 tables
- Published
- 2024
26. Quasi-determinant and right eigenvalues of dual quaternion matrices
- Author
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Ling, Chen and Qi, Liqun
- Subjects
Mathematics - Rings and Algebras - Abstract
Dual quaternion/complex matrices have important applications in brain science and multi-agent formation control. In this paper, we first study some basic properties of determinants of dual complex matrices, including Sturm theorem and Bloomfield-Watson inequality for dual complex matrices. Then, we show that every eigenvalue of a dual complex matrix must be the root of the characteristic polynomial of this matrix. With the help of the determinants of dual complex matrices, we introduce the concept of quasi-determinants of dual quaternion matrices, and show that every right eigenvalue of a dual quaternion matrix must be the root of the quasi-characteristic polynomial of this matrix, as well as the quasi-determinant of a dual quaternion Hermitian matrix is equivalent to the product of the square of the magnitudes of all eigenvalues. Our results are helpful for the further study of dual quaternion matrix theory, and their applications.
- Published
- 2024
27. Source Localization for Cross Network Information Diffusion
- Author
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Ling, Chen, Chowdhury, Tanmoy, Ji, Jie, Li, Sirui, Züfle, Andreas, and Zhao, Liang
- Subjects
Computer Science - Social and Information Networks - Abstract
Source localization aims to locate information diffusion sources only given the diffusion observation, which has attracted extensive attention in the past few years. Existing methods are mostly tailored for single networks and may not be generalized to handle more complex networks like cross-networks. Cross-network is defined as two interconnected networks, where one network's functionality depends on the other. Source localization on cross-networks entails locating diffusion sources on the source network by only giving the diffused observation in the target network. The task is challenging due to challenges including: 1) diffusion sources distribution modeling; 2) jointly considering both static and dynamic node features; and 3) heterogeneous diffusion patterns learning. In this work, we propose a novel method, namely CNSL, to handle the three primary challenges. Specifically, we propose to learn the distribution of diffusion sources through Bayesian inference and leverage disentangled encoders to separately learn static and dynamic node features. The learning objective is coupled with the cross-network information propagation estimation model to make the inference of diffusion sources considering the overall diffusion process. Additionally, we also provide two novel cross-network datasets collected by ourselves. Extensive experiments are conducted on both datasets to demonstrate the effectiveness of \textit{CNSL} in handling the source localization on cross-networks., Comment: Code and data are available at: https://github.com/tanmoysr/CNSL/
- Published
- 2024
28. Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma
- Author
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Ren, He, Wang, Qiubo, Xiao, Zhengguang, Mo, Runwei, Guo, Jiachen, Hide, Gareth Richard, Tu, Mengting, Zeng, Yanan, Ling, Chen, and Li, Ping
- Published
- 2024
- Full Text
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29. Solvent-free flexible epoxy intumescent fire-retardant coatings
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Ling, Chen, Zhou, Rudong, Xiang, Yanli, Fang, Jianbo, Meng, Xu, Ren, Qiang, and Wang, Chenyi
- Published
- 2024
- Full Text
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30. Depression Risk Factors for Knowledge Workers in the Post-Capitalist Society of Taiwan
- Author
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Hui-Li Lin, Fang-Suey Lin, Ling-Chen Liu, and Wen-Hsin Liu
- Subjects
post-capitalist society ,knowledge worker ,depression risk factor ,individual characteristic ,Medicine - Abstract
This study aimed to examine the depression risk factors for knowledge workers aged 20–64 in the post-capitalist society of Taiwan. Interview data from 2014 and 2019 were adopted for quantitative analysis of the depression risk by demographic and individual characteristics. The results showed that the depression risks of knowledge workers were not affected by demographic variables in a single period. From 2014 to 2019, the prevalence of high depression risk in knowledge workers aged 20–64 years increased over time. The more attention is paid to gender equality in society, the less the change in the gender depression index gap may be seen. Positive psychological state and family relationships are both depression risk factors and depression protective factors. Being male, married, religious, and aged 45–49 years old were found to be critical risk factors. Variables of individual characteristics could effectively predict depression risk.
- Published
- 2022
- Full Text
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31. SparseLLM: Towards Global Pruning for Pre-trained Language Models
- Author
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Bai, Guangji, Li, Yijiang, Ling, Chen, Kim, Kibaek, and Zhao, Liang
- Subjects
Computer Science - Computation and Language - Abstract
The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands. Pruning has emerged as a pivotal compression strategy, introducing sparsity to enhance both memory and computational efficiency. Yet, traditional global pruning is impractical for LLMs due to scalability issues, while local pruning, despite its efficiency, leads to suboptimal solutions. Addressing these challenges, we propose SparseLLM, a novel framework that redefines the global pruning process into manageable, coordinated subproblems, allowing for resource-efficient optimization with global optimality. SparseLLM's approach, which conceptualizes LLMs as a chain of modular functions and leverages auxiliary variables for problem decomposition, not only facilitates a pragmatic application on LLMs but also demonstrates significant performance improvements, particularly in high-sparsity regimes where it surpasses current state-of-the-art methods., Comment: NeurIPS 2024
- Published
- 2024
32. MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization
- Author
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Do, Nguyen, Chowdhury, Tanmoy, Ling, Chen, Zhao, Liang, and Thai, My T.
- Subjects
Computer Science - Social and Information Networks ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,Mathematics - Probability ,Statistics - Machine Learning - Abstract
Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network. MIM has been one of central research topics, especially in nowadays social networking landscape where users participate in multiple online social networks (OSNs) and their influences can propagate among several OSNs simultaneously. Although there exist a couple combinatorial algorithms to MIM, learning-based solutions have been desired due to its generalization ability to heterogeneous networks and their diversified propagation characteristics. In this paper, we introduce MIM-Reasoner, coupling reinforcement learning with probabilistic graphical model, which effectively captures the complex propagation process within and between layers of a given multiplex network, thereby tackling the most challenging problem in MIM. We establish a theoretical guarantee for MIM-Reasoner as well as conduct extensive analyses on both synthetic and real-world datasets to validate our MIM-Reasoner's performance.
- Published
- 2024
33. ELAD: Explanation-Guided Large Language Models Active Distillation
- Author
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Zhang, Yifei, Pan, Bo, Ling, Chen, Hu, Yuntong, and Zhao, Liang
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences. Traditional distillation methods, which transfer the capabilities of LLMs to smaller models, often fail to determine whether the knowledge has been sufficiently transferred, potentially resulting in high costs or incomplete distillation. In this paper, we propose an Explanation-Guided LLMs Active Distillation (ELAD) framework that employs an active learning strategy to optimize the balance between annotation costs and model performance. To improve efficient sample selection, we introduce an explanation-guided sample selection method that identifies samples challenging its reasoning by exploiting uncertainties in explanation steps. Additionally, we present a customized LLM-annotated explanation revision technique where the teacher model detects and corrects flaws in the student model's reasoning. Our experiments across various reasoning datasets demonstrate that our framework significantly enhances the efficiency of LLM knowledge distillation.
- Published
- 2024
34. A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models
- Author
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Li, Mingchen, Ling, Chen, Zhang, Rui, and Zhao, Liang
- Subjects
Computer Science - Computation and Language - Abstract
Zero-shot link prediction (ZSLP) on knowledge graphs aims at automatically identifying relations between given entities. Existing methods primarily employ auxiliary information to predict tail entity given head entity and its relation, yet face challenges due to the occasional unavailability of such detailed information and the inherent simplicity of predicting tail entities based on semantic similarities. Even though Large Language Models (LLMs) offer a promising solution to predict unobserved relations between the head and tail entity in a zero-shot manner, their performance is still restricted due to the inability to leverage all the (exponentially many) paths' information between two entities, which are critical in collectively indicating their relation types. To address this, in this work, we introduce a Condensed Transition Graph Framework for Zero-Shot Link Prediction (CTLP), which encodes all the paths' information in linear time complexity to predict unseen relations between entities, attaining both efficiency and information preservation. Specifically, we design a condensed transition graph encoder with theoretical guarantees on its coverage, expressiveness, and efficiency. It is learned by a transition graph contrastive learning strategy. Subsequently, we design a soft instruction tuning to learn and map the all-path embedding to the input of LLMs. Experimental results show that our proposed CTLP method achieves state-of-the-art performance on three standard ZSLP datasets
- Published
- 2024
35. Uncertainty Quantification for In-Context Learning of Large Language Models
- Author
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Ling, Chen, Zhao, Xujiang, Zhang, Xuchao, Cheng, Wei, Liu, Yanchi, Sun, Yiyou, Oishi, Mika, Osaki, Takao, Matsuda, Katsushi, Ji, Jie, Bai, Guangji, Zhao, Liang, and Chen, Haifeng
- Subjects
Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
In-context learning has emerged as a groundbreaking ability of Large Language Models (LLMs) and revolutionized various fields by providing a few task-relevant demonstrations in the prompt. However, trustworthy issues with LLM's response, such as hallucination, have also been actively discussed. Existing works have been devoted to quantifying the uncertainty in LLM's response, but they often overlook the complex nature of LLMs and the uniqueness of in-context learning. In this work, we delve into the predictive uncertainty of LLMs associated with in-context learning, highlighting that such uncertainties may stem from both the provided demonstrations (aleatoric uncertainty) and ambiguities tied to the model's configurations (epistemic uncertainty). We propose a novel formulation and corresponding estimation method to quantify both types of uncertainties. The proposed method offers an unsupervised way to understand the prediction of in-context learning in a plug-and-play fashion. Extensive experiments are conducted to demonstrate the effectiveness of the decomposition. The code and data are available at: https://github.com/lingchen0331/UQ_ICL., Comment: Accepted to the main conference of NAACL 2024
- Published
- 2024
36. Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models
- Author
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Bai, Guangji, Chai, Zheng, Ling, Chen, Wang, Shiyu, Lu, Jiaying, Zhang, Nan, Shi, Tingwei, Yu, Ziyang, Zhu, Mengdan, Zhang, Yifei, Yang, Carl, Cheng, Yue, and Zhao, Liang
- Subjects
Computer Science - Machine Learning - Abstract
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in the high consumption of computational, memory, energy, and financial resources, especially in environments with limited resource capabilities. This survey aims to systematically address these challenges by reviewing a broad spectrum of techniques designed to enhance the resource efficiency of LLMs. We categorize methods based on their optimization focus: computational, memory, energy, financial, and network resources and their applicability across various stages of an LLM's lifecycle, including architecture design, pretraining, finetuning, and system design. Additionally, the survey introduces a nuanced categorization of resource efficiency techniques by their specific resource types, which uncovers the intricate relationships and mappings between various resources and corresponding optimization techniques. A standardized set of evaluation metrics and datasets is also presented to facilitate consistent and fair comparisons across different models and techniques. By offering a comprehensive overview of the current sota and identifying open research avenues, this survey serves as a foundational reference for researchers and practitioners, aiding them in developing more sustainable and efficient LLMs in a rapidly evolving landscape., Comment: GitHub repo: https://github.com/tiingweii-shii/Awesome-Resource-Efficient-LLM-Papers
- Published
- 2023
37. New instability model leading the wrinkling at the positive-curvature arc part during the tube hydro-forging process
- Author
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Lin, Caiyuan, Chu, Guannan, Liu, Xiehan, Wang, Qingfeng, Ling, Chen, and Sun, Lei
- Published
- 2024
- Full Text
- View/download PDF
38. A tensor train approach for internet traffic data completion
- Author
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Zhang, Zhiyuan, Ling, Chen, He, Hongjin, and Qi, Liqun
- Published
- 2024
- Full Text
- View/download PDF
39. Open-ended Commonsense Reasoning with Unrestricted Answer Scope
- Author
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Ling, Chen, Zhang, Xuchao, Zhao, Xujiang, Liu, Yanchi, Cheng, Wei, Oishi, Mika, Osaki, Takao, Matsuda, Katsushi, Chen, Haifeng, and Zhao, Liang
- Subjects
Computer Science - Computation and Language - Abstract
Open-ended Commonsense Reasoning is defined as solving a commonsense question without providing 1) a short list of answer candidates and 2) a pre-defined answer scope. Conventional ways of formulating the commonsense question into a question-answering form or utilizing external knowledge to learn retrieval-based methods are less applicable in the open-ended setting due to an inherent challenge. Without pre-defining an answer scope or a few candidates, open-ended commonsense reasoning entails predicting answers by searching over an extremely large searching space. Moreover, most questions require implicit multi-hop reasoning, which presents even more challenges to our problem. In this work, we leverage pre-trained language models to iteratively retrieve reasoning paths on the external knowledge base, which does not require task-specific supervision. The reasoning paths can help to identify the most precise answer to the commonsense question. We conduct experiments on two commonsense benchmark datasets. Compared to other approaches, our proposed method achieves better performance both quantitatively and qualitatively., Comment: Findings of EMNLP 2023
- Published
- 2023
40. Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty
- Author
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Ling, Chen, Zhao, Xujiang, Zhang, Xuchao, Liu, Yanchi, Cheng, Wei, Wang, Haoyu, Chen, Zhengzhang, Osaki, Takao, Matsuda, Katsushi, Chen, Haifeng, and Zhao, Liang
- Subjects
Computer Science - Computation and Language - Abstract
Open Information Extraction (OIE) task aims at extracting structured facts from unstructured text, typically in the form of (subject, relation, object) triples. Despite the potential of large language models (LLMs) like ChatGPT as a general task solver, they lag behind state-of-the-art (supervised) methods in OIE tasks due to two key issues. First, LLMs struggle to distinguish irrelevant context from relevant relations and generate structured output due to the restrictions on fine-tuning the model. Second, LLMs generates responses autoregressively based on probability, which makes the predicted relations lack confidence. In this paper, we assess the capabilities of LLMs in improving the OIE task. Particularly, we propose various in-context learning strategies to enhance LLM's instruction-following ability and a demonstration uncertainty quantification module to enhance the confidence of the generated relations. Our experiments on three OIE benchmark datasets show that our approach holds its own against established supervised methods, both quantitatively and qualitatively.
- Published
- 2023
41. Helper Recommendation with seniority control in Online Health Community
- Author
-
Gao, Junruo, Ling, Chen, Yang, Carl, and Zhao, Liang
- Subjects
Computer Science - Social and Information Networks ,Computer Science - Information Retrieval - Abstract
Online health communities (OHCs) are forums where patients with similar conditions communicate their experiences and provide moral support. Social support in OHCs plays a crucial role in easing and rehabilitating patients. However, many time-sensitive questions from patients often remain unanswered due to the multitude of threads and the random nature of patient visits in OHCs. To address this issue, it is imperative to propose a recommender system that assists solution seekers in finding appropriate problem helpers. Nevertheless, developing a recommendation algorithm to enhance social support in OHCs remains an under-explored area. Traditional recommender systems cannot be directly adapted due to the following obstacles. First, unlike user-item links in traditional recommender systems, it is hard to model the social support behind helper-seeker links in OHCs since they are formed based on various heterogeneous reasons. Second, it is difficult to distinguish the impact of historical activities in characterizing patients. Third, it is significantly challenging to ensure that the recommended helpers possess sufficient expertise to assist the seekers. To tackle the aforementioned challenges, we develop a Monotonically regularIzed diseNTangled Variational Autoencoders (MINT) model to strengthen social support in OHCs.
- Published
- 2023
42. Stable atrogin-1 (Fbxo32) and MuRF1 (Trim63) gene expression is involved in the protective mechanism in soleus muscle of hibernating Daurian ground squirrels (Spermophilus dauricus)
- Author
-
Kai Dang, Ya-Zhao Li, Ling-Chen Gong, Wei Xue, Hui-Ping Wang, Nandu Goswami, and Yun-Fang Gao
- Subjects
Disuse muscle atrophy ,Hibernation ,Hindlimb-unloading ,Seasons ,Science ,Biology (General) ,QH301-705.5 - Abstract
Understanding the mechanisms that protect against or limit muscle atrophy in hibernators during prolonged inactivity has important implications for its treatment. We examined whether external factors influence the pathways regulating protein synthesis and degradation, leading to muscle atrophy prevention in Daurian ground squirrels (Spermophilus dauricus). We investigated the effects of 14-day hindlimb-unloading (HU) in different seasons and two-month hibernation on the soleus (SOL) muscle wet mass, muscle-to-body mass ratio, fiber cross sectional area (CSA), fiber distribution and muscle ultrastructure. We also measured changes in the protein expression and activation states of Akt, mTOR and FoxO1 and the mRNA expression of atrogin-1 and MuRF1. Compared with the control groups, autumn and winter HU significantly lowered SOL muscle wet mass and muscle-to-body mass ratio, decreased type I and II fiber CSA and induced ultrastructural anomalies. However, these measured indices were unchanged between Pre-hibernation and Hibernation groups. Furthermore, phosphorylation levels of Akt and mTOR significantly decreased, while the phosphorylation level of FoxO1 and mRNA expression of atrogin-1 and MuRF1 increased after HU. During hibernation, the phosphorylation levels of Akt and mTOR significantly decreased, but the phosphorylation level of FoxO1 and mRNA expression of atrogin-1 and MuRF1 remained unchanged. Overall, our findings suggest that disuse and seasonality may not be sufficient to initiate the innate protective mechanism that prevents SOL atrophy during prolonged periods of hibernation inactivity. The stable expression of atrogin-1 and MuRF1 may facilitate to prevent SOL atrophy via controlling ubiquitination of muscle proteins during hibernation.
- Published
- 2016
- Full Text
- View/download PDF
43. A breathable waterborne poly-(urethane/urea) coating containing PO-EO-PO triblock copolymer
- Author
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Shu-Yi Chen, Chin-Wen Chen, Ling-Chen Cheng, Fu-Sheng Chuang, and Syang-Peng Rwei
- Subjects
waterborne polyurethane ,textile coating ,breathable coating ,water vapor permeability ,water pressure resistance ,Materials of engineering and construction. Mechanics of materials ,TA401-492 ,Chemical technology ,TP1-1185 - Abstract
A breathable waterborne poly-(urethane/urea) (WPU) coating for textiles was synthesized by a pre-polymer method with 4,4′-Diisocyanate dicyclohexylmethane (H _12 MDI), Poly(propylene oxide)- b -poly(ethylene oxide)- b -poly(propylene oxide) triblock diols (PO-EO-PO diols), and Polyteramethylene glycol (PTMG). The PO-EO-PO diols were incorporated into the WPU to improve the swelling issue of frequently observed in the polyethylene glycol (PEO) segments. The stability, mechanical property, thermal properties, and breathability of PO-EO-PO, including WPUs were investigated by varying PTMG/PO-EO-PO diol ratios. The PO-EO-PO incorporated WPUs showed excellent mechanical properties: 250% of tensile elongation and breaking stress of 15–27 MPa. The breathability reached 620–15 000 mm of water pressure resistance H _2 O and 2717–63 822 g H _2 O 24 h m ^−2 of vapor permeability. The highly breathable, WPU coating contained with different PO/EO fraction of PO-EO-PO diols will play an essential role in the garment-textile industry to convert to a greener process.
- Published
- 2020
- Full Text
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44. Generic stability of linear algebraic groups over $\mathbb{C}[[t]]$
- Author
-
Ling, Chen and Yao, Ningyuan
- Subjects
Mathematics - Logic ,20G30 03C98 12L12 - Abstract
Let $K$ be a henselian valued field with ${\cal O}_K$ its valuation ring, $\Gamma$ its value group, and $\boldsymbol{k}$ its residue field. We study the definable subsets of ${\cal O}_K$ and algebraic groups definable over ${\cal O}_K$ in the case where $\boldsymbol{k}$ is algebraically closed and $\Gamma$ is a $\mathbb Z$-group. We first describe the definable subsets of ${\cal O}_K$, showing that every definable subset of ${\cal O}_K$ is either res-finite or res-cofinite (see Definition \ref{def-res-finite-cofinite}). Applying this result, we show that $\mathrm{GL}(n,{\cal O}_K)$ (the invertible $n$ by $n$ matrices over ${\cal O}_K$) are generically stable for each $n$, generalizing Y. Halevi's result, where $K$ is an algebraically closed valued field \cite{Y.Halevi}.
- Published
- 2023
45. A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises
- Author
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Yang, Carl, Cui, Hejie, Lu, Jiaying, Wang, Shiyu, Xu, Ran, Ma, Wenjing, Yu, Yue, Yu, Shaojun, Kan, Xuan, Ling, Chen, Fu, Tianfan, Zhao, Liang, Ho, Joyce, and Wang, Fei
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Machine Learning ,Computer Science - Social and Information Networks - Abstract
Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts and their relationships with interpretable structures. The recent advent of large language models (LLMs) has paved the way for building more comprehensive and accurate HKGs. This, in turn, can improve the reliability of generated content and enable better evaluation of LLMs. However, the challenges of HKGs such as regarding data heterogeneity and limited coverage are not fully understood, highlighting the need for detailed reviews. This work provides the first comprehensive review of HKGs. It summarizes the pipeline and key techniques for HKG construction, as well as the common utilization approaches, i.e., model-free and model-based. The existing HKG resources are also organized based on the data types they capture and application domains they cover, along with relevant statistical information (Resource available at https://github.com/lujiaying/Awesome-HealthCare-KnowledgeBase). At the application level, we delve into the successful integration of HKGs across various health domains, ranging from fine-grained basic science research to high-level clinical decision support and public health. Lastly, the paper highlights the opportunities for HKGs in the era of LLMs. This work aims to serve as a valuable resource for understanding the potential and opportunities of HKG in health research., Comment: 21 pages, preprint submitted to ACM
- Published
- 2023
46. Uncommon presentation of acute type A aortic dissection: sleeve-severed and everted proximal right coronary artery intima without myocardial ischaemia
- Author
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Huang, Ling-chen, Feng, Zeng-bin, and Guo, Hong-wei
- Published
- 2024
- Full Text
- View/download PDF
47. Correlation and risk factors of peripheral and cervicocephalic arterial atherosclerosis in patients with ischemic cerebrovascular disease
- Author
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Li, Lu-guang, Ma, Xin, Zhao, Xiaoxi, Du, Xiangying, and Ling, Chen
- Published
- 2024
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- View/download PDF
48. A visceral organ function-focused therapeutic strategy using a 6-hour time window for patients with acute type a aortic dissection complicated by mesenteric malperfusion
- Author
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Huang, Ling-chen, Chen, Shuang-kun, Peng, Hua, and Wu, Xi-jie
- Published
- 2024
- Full Text
- View/download PDF
49. An integrated framework for prognosis prediction and drug response modeling in colorectal liver metastasis drug discovery
- Author
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Zhou, Xiuman, Qian, Yuzhen, Ling, Chen, He, Zhuoying, Shi, Peishang, Gao, Yanfeng, and Sui, Xinghua
- Published
- 2024
- Full Text
- View/download PDF
50. Prolonged efficacy of cefazolin in intraosseous regional prophylaxis for total knee arthroplasty: a rabbit model study
- Author
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Zhang, Jing-Yu, Ye, Ling-Chen, Liu, Yu-bo, Yu, Xiao, Zhang, Xiang-Xin, Chen, Guang-Xiang, and Xu, Ren-Jie
- Published
- 2024
- Full Text
- View/download PDF
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