A clean-label graph backdoor attack method in node classification task

Backdoor attacks in the traditional graph neural networks (GNNs) field are easily detectable due to the dilemma of confusing labels. To explore the backdoor vulnerability of GNNs and create a more stealthy backdoor attack method, a clean-label graph backdoor attack method(CGBA) in the node classification task is proposed in this paper. Differently from existing backdoor attack methods, CGBA requires neither modification of node labels nor graph structure. Specifically, to solve the problem of inconsistency between the contents and labels of the samples, CGBA selects poisoning samples in a specific target class and uses the label of sample as the target label (i.e., clean-label) after injecting triggers into the target samples. To guarantee the similarity of neighboring nodes, the raw features of the nodes are elaborately picked as triggers to further improve the concealment of the triggers. Extensive experiments results show the effectiveness of our method. When the poisoning rate is 0.04, CGBA can achieve an average attack success rate of 87.8%, 98.9%, 89.1%, and 98.5%, respectively.Comment: 14page

Development and performance evaluation of bioenzyme-responsive temporary plugging materials

Ocean gas hydrate is a potentially efficient and clean oil and gas alternative energy resource. Wells with complex structure, such as horizontal wells, can improve the extraction efficiency; however, drilling operations face challenges such as wellbore instability and reservoir damage due to the complex interaction between drilling fluids and hydrate reservoirs. This work presents a ceramsite temporary plugging microcapsule that uses ceramsite modified by 3-aminopropyltriethoxysilane as the core material and chitosan and sodium alginate as shell materials. It exhibits high strength during drilling and excellent plugging effects. After the action of bioenzymes, it can easily be dissolved, leading to high permeability post-drilling. The analysis and performance evaluation of ceramsite microcapsules show that their particle size is generally 40 μm, which can match the pore size of the hydrate reservoir depending on the number of encapsulation layers. Bioenzyme optimization at 15 ◦C yields the best permeability recovery of 74.5% for the low-temperature composite enzyme. As the temperature rises, the permeability recovery rate of ceramic microcapsules gradually increases and the difference in permeability recovery rate between 5 and 25 ◦C becomes more significant. With a longer degradation time, the permeability recovery rate of ceramsite microcapsules gradually enhances and the difference in permeability recovery rate becomes smaller after 12 h. The microcapsules exhibit a specific inhibitory effect on the decomposition of hydrates. Utilizing bioenzyme- responsive ceramsite microcapsules as temporary plugging materials can establish an “isolation barrier” around the wellbore, effectively sealing off the interaction between the wellbore and the gas hydrate reservoir during the drilling process. Re-opening the flow path around the well by bio-enzymatic unblocking at the end of drilling proves to be effective in solving the problem of balancing the stability of the well wall and protecting the reservoir.Document Type: Original articleCited as: Sun, J., Li, Y., Liao, B., Bai, Y., Li, W., Wang, J. Development and performance evaluation of bioenzyme-responsive temporary plugging materials. Advances in Geo-Energy Research, 2024, 11(1): 20-28. https://doi.org/10.46690/ager.2024.01.0

TextNAS: A Neural Architecture Search Space tailored for Text Representation

Learning text representation is crucial for text classification and other language related tasks. There are a diverse set of text representation networks in the literature, and how to find the optimal one is a non-trivial problem. Recently, the emerging Neural Architecture Search (NAS) techniques have demonstrated good potential to solve the problem. Nevertheless, most of the existing works of NAS focus on the search algorithms and pay little attention to the search space. In this paper, we argue that the search space is also an important human prior to the success of NAS in different applications. Thus, we propose a novel search space tailored for text representation. Through automatic search, the discovered network architecture outperforms state-of-the-art models on various public datasets on text classification and natural language inference tasks. Furthermore, some of the design principles found in the automatic network agree well with human intuition

Clinicopathological characteristics of gastric cancer patients with dermatomyositis and analysis of perioperative management: a case series study

BackgroundThis study aimed to investigate the clinical characteristics of gastric cancer (GC) patients with dermatomyositis (DM) and summarize the perioperative outcomes.MethodsThe clinical and pathological data of five patients diagnosed with co-occurring DM and GC (DM-GC group) were retrospectively analyzed, who were admitted to the Department of Gastrointestinal Surgery at Ren ji Hospital, Shanghai Jiao Tong University, between January 2012 and April 2023. Their data were compared with 618 GC patients (GC-1 group) from September 2016 to August 2017 and 35 GC patients who were meticulously screened from 14,580 GC cases from January 2012 and April 2023. The matching criteria included identical gender, age, tumor location, TNM stage, and surgical procedure (7 GC patients were matched for each DM-GC patient).ResultsAnalysis indicated that the DM-GC group comprised four female and one male patient. The female proportion was significantly higher (P = 0.032) than that of GC-1 group. In DM-GC group, four DM patients were diagnosed as GC within 12 months. One DM patients was diagnosed as GC within 15 months. Among them, four patients presented with varying degrees of skin rashes, muscle weakness while one patient had elevated CK levels as the typical symptom. Similarly, the preoperative tumor markers (CA-199 and CA-125) in the DM-GC group were significantly higher than normal levels (CA-199: 100 vs. 28.6%, P = 0.002; CA-125: 40 vs. 2.9%, P = 0.003) compared to GC-2 group. Moreover, postoperative complication incidence and the length of hospital stay were significantly higher in the DM-GC than GC-2 group [complication rate: 40 vs. 8.6%, P = 0.047; hospital stay: 15 days (range: 9–28) vs. 9 days (range: 8–10), P = 0.021].ConclusionGC Patients with dermatomyositis are more prone to experience postoperative complications and longer hospital stay

A novel DSPP mutation causes dentinogenesis imperfecta type II in a large Mongolian family

<p>Abstract</p> <p>Background</p> <p>Several studies have shown that the clinical phenotypes of dentinogenesis imperfecta type II (DGI-II) may be caused by mutations in <it>dentin sialophosphoprotein </it>(<it>DSPP</it>). However, no previous studies have documented the clinical phenotype and genetic basis of DGI-II in a Mongolian family from China.</p> <p>Methods</p> <p>We identified a large five-generation Mongolian family from China with DGI-II, comprising 64 living family members of whom 22 were affected. Linkage analysis of five polymorphic markers flanking <it>DSPP </it>gene was used to genotype the families and to construct the haplotypes of these families. All five DSPP exons including the intron-exon boundaries were PCR-amplified and sequenced in 48 members of this large family.</p> <p>Results</p> <p>All affected individuals showed discoloration and severe attrition of their teeth, with obliterated pulp chambers and without progressive high frequency hearing loss or skeletal abnormalities. No recombination was found at five polymorphic markers flanking DSPP in the family. Direct DNA sequencing identified a novel A→G transition mutation adjacent to the donor splicing site within intron 3 in all affected individuals but not in the unaffected family members and 50 unrelated Mongolian individuals.</p> <p>Conclusion</p> <p>This study identified a novel mutation (IVS3+3A→G) in <it>DSPP</it>, which caused DGI-II in a large Mongolian family. This expands the spectrum of mutations leading to DGI-II.</p