Continual Learning for Abdominal Multi-Organ and Tumor Segmentation

The ability to dynamically extend a model to new data and classes is critical for multiple organ and tumor segmentation. However, due to privacy regulations, accessing previous data and annotations can be problematic in the medical domain. This poses a significant barrier to preserving the high segmentation accuracy of the old classes when learning from new classes because of the catastrophic forgetting problem. In this paper, we first empirically demonstrate that simply using high-quality pseudo labels can fairly mitigate this problem in the setting of organ segmentation. Furthermore, we put forward an innovative architecture designed specifically for continuous organ and tumor segmentation, which incurs minimal computational overhead. Our proposed design involves replacing the conventional output layer with a suite of lightweight, class-specific heads, thereby offering the flexibility to accommodate newly emerging classes. These heads enable independent predictions for newly introduced and previously learned classes, effectively minimizing the impact of new classes on old ones during the course of continual learning. We further propose incorporating Contrastive Language-Image Pretraining (CLIP) embeddings into the organ-specific heads. These embeddings encapsulate the semantic information of each class, informed by extensive image-text co-training. The proposed method is evaluated on both in-house and public abdominal CT datasets under organ and tumor segmentation tasks. Empirical results suggest that the proposed design improves the segmentation performance of a baseline neural network on newly-introduced and previously-learned classes along the learning trajectory.Comment: MICCAI-202

Balance between poverty alleviation and air pollutant reduction in China

Key targets of the sustainable development goals might be in contradiction to each other. For example, poverty alleviation may exacerbate air pollution by increasing production and associated emissions. This paper investigates the potential impacts of achieving different poverty eradication goals on typical air pollutants in China by capturing household consumption patterns for different income groups and locations, and linking it to China’s multi-regional input-output table and various scenarios. We find that ending extreme poverty, i.e. lifting people above the poverty line of USD 1.90 a day in 2011 purchasing power parity (PPP), increases China’s household emissions by only less than 0.6%. The contribution increases to 2.4%–4.4% when adopting the USD 3.20 PPP poverty line for lower-middle-income countries. Technical improvements in economic sectors can easily offset poverty-alleviation-induced emissions in both scenarios. Nevertheless, when moving all impoverished residents below the USD 5.50 PPP poverty line for upper-middle-income countries, household emissions in China would increase significantly by 18.5%–22.3%. Counteracting these additional emissions would require national emission intensity in production to decrease by 23.7% for SO2, 13.6% for NOx, 82.1% for PM2.5, and 58.0% for PM10. Required synergies between poverty alleviation and emission reduction call for changes in household lifestyles and production

MD simulation study on defect evolution and doping efficiency of p-type doping of 3C-SiC by Al ion implantation with subsequent annealing

We use molecular dynamics (MD) simulation with numerical characterisation and statistical analysis to study the mechanisms of damage evolution and p-type doping efficiency by aluminum (Al) ion implantation into 3C silicon carbide (SiC) with subsequent annealing. By incorporating the electronic stopping power for implantation, a more accurate description of the atomic-scale mechanisms of damage evolution and distribution in SiC can be obtained. The simulation results show a novel observation that the recrystallization process occurs in the region below the subsurface layer, and develops from amorphous-crystalline interface to the damage center region, which is a new insight into previously published studies. During surface recrystallization, significant compressive stress concentration occurs, and more structural phase transition atoms and dislocations formed at the damage-rich-crystalline interface. Another point of interest is that for low-dose implantation, more implantation-induced defects hamper the doping efficiency. Correspondingly, the correlation between lattice damage and doping efficiency becomes weaker as the implant dose increases under the same annealing conditions. Our simulation also predicts that annealing after high temperature (HT) implantation is more likely to lead to the formation of carbon vacancies (V-C).Peer reviewe

Quantization and diagnosis of Shanghuo (Heatiness) in Chinese medicine using a diagnostic scoring scheme and salivary biochemical parameters

Background: This study aims to establish a diagnostic scoring scheme for Shanghuo (Heatiness) and to evaluate whether Shanghuo is associated with biochemical parameters of salivary lysozyme (LYZ), salivary secreted immunoglobulin (S-IgA), salivary amylase (AMS), and saliva flow rate (SFR). Methods: We collected 121 Shanghuo patients at the Affiliated Hospitals of Guangzhou University of Traditional Chinese Medicine in Guangdong Province, 60 cases as a Shanghuo recovered group, and 60 healthy cases as a healthy control group. The diagnostic scoring scheme was established by probability theory and maximum likelihood discriminatory analysis on the basis of epidemiology with the design of self-controlled clinical trial. Subsequently, we used the same methods to collect 120 Shanghuo patients, 60 Shanghuo recovered cases, and 60 healthy cases in both Hunan Province and Henan Province. The levels of LYZ, S-IgA, AMS, and SFR were tested when the patients suffered from Shanghuo or recovered, respectively. Results: The diagnostic score table for Shanghuo syndrome was established first. In the retrospective tests, the sensitivity, specificity, accuracy, and positive likelihood ratio of the diagnostic score table were 98.9%, 93.5%, 97.5%, and 14.34%, respectively. In the prospective tests, the corresponding values were 94.9%, 85.7%, 91.7%, and 6.64%, respectively. Shanghuo was classified into three degrees based on the diagnostic scores, common Shanghuo: 63–120; serious Shanghuo: 121–150; very serious Shanghuo: >150. A negative correlation was found between Shanghuo and S-IgA (R = -0.428; P = 0.000). The level of S-IgA was also affected by seasonal and regional factors. No significant correlations were found between Shanghuo and the levels of LYZ, AMS, and SFR. Conclusions: In this study, Shanghuo could be diagnosed by the combination of the diagnostic score table and S-lgA level

Molecular dynamics simulation of helium ion implantation into silicon and its migration

In this paper, a model of helium ion implanted monocrystalline Si was constructed by using molecular dynamics (MD) simulation method to study the interaction mechanism of helium ion with monocrystalline Si and helium ion migration. In order to study the damage effect of helium ion implantation on monocrystalline Si, identify diamond structure (IDS), radial distribution function, temperature analysis were calculated and analyzed. The effects of ion doses, beam currents and energies on the damage were studied. Helium ion implanted Si with ion doses of 1 x 10(14)/cm(2) was subsequently heated to 300 K. MD simulation results indicated that IDS damage induced by ion implantation was positively correlated with ion doses as the ion implantation increased to 1 x 10(14)/cm(2). The mean-square displacement of helium atoms was calculated during the temperature rising to 300 K. It was found that the high permeability of helium atoms in Si and the acceleration of atomic thermal motion owing to elevated temperature as well as the existence of larger stress would be helpful to the migration of implant helium atoms.Peer reviewe

Thickened Perirenal Fat Predicts Poor Renal Outcome in Patients with Immunoglobulin A Nephropathy: A Population-Based Retrospective Cohort Study

Introduction: Perirenal fat is a pad that fills the retroperitoneal space outside the kidney, which affects kidney function in various ways. However, the association between perirenal fat and IgA nephropathy (IgAN) has not yet been elucidated. This study aimed to investigate the role of perirenal fat in predicting IgAN progression. Methods: A total of 473 patients with biopsy-proven IgAN and follow-up information were recruited, and perirenal fat thickness (PFT) was measured using color Doppler ultrasonography at renal biopsy. Patients were divided into two groups according to the median PFT: the low-PFT group (PFT ≤1.34 cm, n = 239) and the high PFT group (PFT >1.35 cm, n = 234). A total of 473 healthy participants were included in the control group. Basic clinical characteristics were assessed at the time of renal biopsy, and the relationship between PFT and combined endpoints was analyzed. The renal composite endpoints were defined as a two-fold increase in blood creatinine level, end-stage renal disease (dialysis over 3 months). Kaplan-Meier survival analysis was used to explore the role of PFT in the progression of IgAN. Three clinicopathological models of multivariate Cox regression analysis were established to evaluate the association between PFT and renal prognosis in patients with IgAN. Results: Compared to healthy subjects, patients with IgAN showed significantly higher PFT. After a median follow-up of 50 months, 75 of 473 patients (15.9%) with IgAN reached renal composite endpoints. Among those, 13 of 239 patients (5.4%) were in the low PFT group, and 62 of 234 patients (26.5%) were in the high PFT group (p < 0.001). The results of three Cox regression models (including demographics, pathological and clinical indicators, and PFT) demonstrated that a higher PFT was significantly associated with a higher risk of reaching renal composite endpoints in patients with IgAN. Conclusion: This study indicated a positive relationship between PFT at renal biopsy and renal progression in patients with IgAN, suggesting that perirenal fat might act as a marker of poor prognosis in patients with IgAN

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem of each dataset, as well as a limited investigation of diverse types of tumors, the resulting models are often limited to segmenting specific organs/tumors and ignore the semantics of anatomical structures, nor can they be extended to novel domains. To address these issues, we propose the CLIP-Driven Universal Model, which incorporates text embedding learned from Contrastive Language-Image Pre-training (CLIP) to segmentation models. This CLIP-based label encoding captures anatomical relationships, enabling the model to learn a structured feature embedding and segment 25 organs and 6 types of tumors. The proposed model is developed from an assembly of 14 datasets, using a total of 3,410 CT scans for training and then evaluated on 6,162 external CT scans from 3 additional datasets. We rank first on the Medical Segmentation Decathlon (MSD) public leaderboard and achieve state-of-the-art results on Beyond The Cranial Vault (BTCV). Additionally, the Universal Model is computationally more efficient (6x faster) compared with dataset-specific models, generalized better to CT scans from varying sites, and shows stronger transfer learning performance on novel tasks.Comment: Rank first in Medical Segmentation Decathlon (MSD) Competitio

Nanocutting mechanism of 6H-SiC investigated by scanning electron microscope online observation and stress-assisted and ion implant-assisted approaches

Nanocutting mechanism of single crystal 6H-SiC is investigated through a novel scanning electron microscope setup in this paper. Various undeformed chip thicknesses on (0001) orientation are adopted in the nanocutting experiments. Phase transformation and dislocation activities involved in the 6H-SiC nanocutting process are also characterized and analyzed. Two methods of stress-assisted and ion implant-assisted nanocutting are studied to improve 6H-SiC ductile machining ability. Results show that stress-assisted method can effectively decrease the hydrostatic stress and help to activate dislocation motion and ductile machining; ion implant-induced damages are helpful to improve the ductile machining ability from MD simulation and continuous nanocutting experiments under the online observation platform.Peer reviewe

Large Virtual Transboundary Hazardous Waste Flows: The Case of China

The Basel Convention and prior studies mainly focused on the physical transboundary movements of hazardous waste (transporting waste from one region to another for cheaper disposal). Here, we take China, the world's largest waste producer, as an example and reveal the virtual hazardous waste flows in trade (outsourcing waste by importing waste-intensive products) by developing a multiregional input-output model. Our model characterizes the impact of international trade between China and 140 economies and China's interprovincial trade on hazardous waste generated by 161,599 Chinese enterprises. We find that, in 2015, virtual hazardous waste flows in China's trade reached 26.6 million tons (67% of the national total), of which 31% were generated during the production of goods that were ultimately consumed abroad. Trade-related production is much dirtier than locally consumed production, generating 26% more hazardous waste per unit of GDP. Under the impact of virtual flows, 40% of the waste-intensive production and relevant disposal duty is unequally concentrated in three Chinese provinces (including two least-developed ones, Qinghai and Xinjiang). Our findings imply the importance of expanding the scope of transboundary waste regulations and provide a quantitative basis for introducing consumer responsibilities. This may help relieve waste management burdens in less-developed "waste havens"