FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer

Federated Learning (FL) has been widely concerned for it enables decentralized learning while ensuring data privacy. However, most existing methods unrealistically assume that the classes encountered by local clients are fixed over time. After learning new classes, this assumption will make the model's catastrophic forgetting of old classes significantly severe. Moreover, due to the limitation of communication cost, it is challenging to use large-scale models in FL, which will affect the prediction accuracy. To address these challenges, we propose a novel framework, Federated Enhanced Transformer (FedET), which simultaneously achieves high accuracy and low communication cost. Specifically, FedET uses Enhancer, a tiny module, to absorb and communicate new knowledge, and applies pre-trained Transformers combined with different Enhancers to ensure high precision on various tasks. To address local forgetting caused by new classes of new tasks and global forgetting brought by non-i.i.d (non-independent and identically distributed) class imbalance across different local clients, we proposed an Enhancer distillation method to modify the imbalance between old and new knowledge and repair the non-i.i.d. problem. Experimental results demonstrate that FedET's average accuracy on representative benchmark datasets is 14.1% higher than the state-of-the-art method, while FedET saves 90% of the communication cost compared to the previous method.Comment: Accepted by 2023 International Joint Conference on Artificial Intelligence (IJCAI2023

Enhancing Low-Resource Relation Representations through Multi-View Decoupling

Recently, prompt-tuning with pre-trained language models (PLMs) has demonstrated the significantly enhancing ability of relation extraction (RE) tasks. However, in low-resource scenarios, where the available training data is scarce, previous prompt-based methods may still perform poorly for prompt-based representation learning due to a superficial understanding of the relation. To this end, we highlight the importance of learning high-quality relation representation in low-resource scenarios for RE, and propose a novel prompt-based relation representation method, named MVRE (\underline{M}ulti-\underline{V}iew \underline{R}elation \underline{E}xtraction), to better leverage the capacity of PLMs to improve the performance of RE within the low-resource prompt-tuning paradigm. Specifically, MVRE decouples each relation into different perspectives to encompass multi-view relation representations for maximizing the likelihood during relation inference. Furthermore, we also design a Global-Local loss and a Dynamic-Initialization method for better alignment of the multi-view relation-representing virtual words, containing the semantics of relation labels during the optimization learning process and initialization. Extensive experiments on three benchmark datasets show that our method can achieve state-of-the-art in low-resource settings.Comment: Accepted to AAAI 202

Comparison of the perioperative outcomes between robotic-assisted thoracic surgery and video-assisted thoracic surgery in non-small cell lung cancer patients with different body mass index ranges

Background: Non-small cell lung cancer (NSCLC) is the most common malignancy and one of the most common causes of cancer-related death worldwide. Robotic-assisted thoracic surgery (RATS) has gradually become a prevalent surgical method for patients with NSCLC. Previous studies have found that body mass index (BMI) is associated with postoperative outcomes. This study aimed to investigate the effectiveness of RATS compared to video-assisted thoracic surgery (VATS) in the treatment of NSCLC with different BMI, in terms of perioperative outcomes.Methods: The baseline and perioperative data, including BMI, of 849 NSCLC patients who underwent minimally invasive anatomic lung resections from August 2020 to April 2021 were retrospectively collected and analyzed. Propensity score matching analysis was applied to minimize potential bias between the two groups (VATS and RATS), and the perioperative outcomes were compared. Subgroup analysis was subsequently performed.Results: Compared to VATS, RATS had more lymph nodes dissected 19 [inter-quartile range (11QR), 6-12] vs. 7 (IQR, 6-10), P<0.001), a lower estimated bleeding volume [40 (IQR, 30-50) vs. 50 (IQR, 40-60) mL, P<0.001], and other better postoperative outcomes, but a higher cost of hospitalization [(sic)83,626 (IQR, 77,211-92,686) vs. (sic)75,804 (IQR, 66,184-83,693), P<0.001]. Multivariable logistic regression analysis indicated that RATS (P=0.027) and increasing BMI (P=0.030) were associated with a statistically significant reduction in the risk of postoperative complications. Subgroup analysis indicated that the advantages of RATS may be more obvious in patients with a BMI of 24-28 kg/m(2), in which the RATS group had more lymph nodes dissected [9 (IQR, 6-12) vs. 7 (IQR, 5-10), P<0.001] and a decreased risk of total postoperative complications [odds ratio (OR), 0.443; 95% confidence interval (CI), 0.212-0.924; P=0.030] compared to the VATS group.Conclusions: Both, RATS and VATS can be safely applied for patients with NSCLC. Perioperative outcome parameters indicate advantages for RATS, however at a higher cost of hospitalization. The advantages of RATS might be more obvious in patients with a BMI of 24-28 kg/m(2)

Distinguishing EGFR mutant subtypes in stage IA non-small cell lung cancer using the presence status of ground glass opacity and final histologic classification: a systematic review and meta-analysis

BackgroundThe progression of early stage non-small cell lung cancer (NSCLC) is closely related to epidermal growth factor receptor (EGFR) mutation status. The purpose of this study was to systematically investigate the relationship between EGFR mutation status and demographic, imaging, and ultimately pathologic features in patients with NSCLC.MethodsA complete literature search was conducted using the PubMed, Web of Science, EMBASE, and Cochrane Library databases to discover articles published by May 15, 2023 that were eligible. The relationship between EGFR mutation status and specific demographic, imaging, and ultimately pathologic features in patients with NSCLC was evaluated using pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The standardized mean difference (SMD) with 95% CIs was the appropriate statistic to summarize standard deviations (SDs) means for continuous variables.ResultsA total of 9 studies with 1789 patients were included in this analysis. The final findings suggested that patients with a greater age, female gender, and non-smoking status would have a relatively higher incidence of EGFR mutations. Additionally, the risk of EGFR mutations increased with larger tumor diameter, tumor imaging presentation of mixed ground glass opacity (mGGO), and tumor pathological findings of minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IAC). Significantly, malignancies presenting as MIA are more likely to contain L858R point mutations (OR = 1.80; 95% CI: 1.04–3.13; p = 0.04) rather than exon 19 deletions (OR = 1.81; 95% CI: 0.95–3.44; p = 0.07).ConclusionThis meta-analysis showed that imaging parameters and histological classifications of pulmonary nodules may be able to predict stage IA NSCLC genetic changes

A nomogram combining thoracic CT and tumor markers to predict the malignant grade of pulmonary nodules ≤3 cm in diameter

BackgroundWith the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging.MethodsA retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors.ResultsA total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful.ConclusionThe nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Effects of Neoadjuvant Radiotherapy on Survival in Patients with Stage IIIA-N2 Non-Small-Cell Lung Cancer Following Pneumonectomy

Background: Pneumonectomy is a drastic but sometimes inevitable treatment option for patients with non-small-cell lung cancer (NSCLC) to improve their chances for long-term survival. However, the optimal adjuvant radiotherapy used for patients with N2 NSCLC following pneumonectomy remains unclear in the literature. Methods: T1-4N0-2M0 NSCLC patients registered in the Surveillance, Epidemiology, and End Results database were retrospectively analyzed. Propensity score matching was applied to balance the assignment of patients. Cox proportional hazards models and Kaplan–Meier analyses were used to identify the factors related to overall survival rates. Restricted cubic splines were used to detect the possible nonlinear dependency of the relationship between the risk of survival and age. Results: A total of 4308 NSCLC patients were enrolled in this study. In N2 patients, the long-term outcome of the chemotherapy and postoperative radiotherapy groups was the worst (p = 0.014). Subgroup analyses showed that the influence of age on survival outcome was confined to patients who received chemotherapy and neoadjuvant radiotherapy (p = 0.004). Meanwhile, patients >65 years of age who received chemotherapy and neoadjuvant radiotherapy had significantly worse prognoses than those in the chemotherapy group (p = 0.005). Conclusions: Our results show that neoadjuvant radiotherapy may have potential benefits in patients aged ≤ 65 years who are scheduled for pneumonectomy, but not in elderly patients

The Progress of Investigation on Neutrino Properties

Abstract Generally, particle physics plays an important role in the whole modern physics system. Thereinto, neutrino, as an elementary particle found from beta decay, is of great importance to discover its properties and mechanics. With the help of information retrieve and literature review, this paper aims at helping recollecting sorts of knowledge, e.g., the developing history of the principle, different kinds of matrix expressions, field theories etc. Additionally, some possible future developing directions have been proposed. Moreover, plenty of analytical models and experimental approaches for generating massive neutrinos are demonstrated, e.g., Lagrangian and beta decay. More experiments need to be carried out for the sake of verifying the theoretical predictions. Overall, these results offer a guideline for completing the Standard Model and hopefully the Grand Unified Theory, such as Majorana mass term.</jats:p

Brief Study on Application of New Indoor Lawn in Northern Areas of China

At present, the development and function research of lawn has become diversified, and the application of lawn has been extended from outdoor to indoor environment. The indoor lawn has functions of absorbing toxic and harmful gases, releasing oxygen, increasing air humidity and regulating temperature. It can effectively improve the indoor air quality of northern areas, purify and beautify the home environment. This paper elaborated the purpose and significance of the application of new indoor lawn, the establishment methods of the indoor lawn, and the application design of the indoor lawn landscape