Abstract Purpose: The treatment of locally advanced rectal cancer includes chemoradiation (CRT) followed by surgical resection. The response of rectal cancers to the CRT is variable. The finding that up to 25% of tumor seem to be totally eradicated by the CRT has raised the question as to whether surgery can be avoided in these patients. Findings predictors or response or resistance to CRT could potentially change the treatment paradigm of rectal cancer patients. In this study we explored DNA copy number alterations as predictors of rectal cancer response to preoperative CRT. Patients and Methods: High-density oligonucleotide-based comparative genomic hybridization (human 244k aCGH kit, Agilent Cor.) was employed to identify the DNA copy number alterations in 89 pretreatment tumor biopsy specimens and paired normal surgical specimens collected from stage II and III rectal cancer patients treated in a prospective multi-institutional study. Data analysis was performed using Nexus Copy Number and Ingenuity Pathway Analysis. A pathologic complete response (pCR), defined as absence of cancer cells in the surgical specimen, was used as clinical end-point. Results: A total of 25 (28%) patients had a pCR. The pCR rate was higher among tumors with low fractional genomic alterations (FGA, ≤21%) (12/26 or 46.1%) compared to tumors with high FGA (>21%) (13/63 or 20.6%) (p<0.02). Gain or losses of individual chromosome segments containing individual candidate genes and miRNAs in tumors with or without pCR are presented in table 1.Chrom. LocationCandidate GeneChangepCRNon- pCRp-valuechr18q21.2SMAD4loss52%82.8%0.0059chr.8p12EIF4EBP1loss8%35.9%0.0085chr.17q12ERBB2gain4%29.7%0.0098chr.16p12.1PRKCBgain4%29.7%0.0098chr.7p15.2hsa-mir-148again32%58.7%0.0352 Conclusion: This study shows that DNA copy number aberrations, measured as a FGA and individual chromosome regions gain and loses, may be predictors of rectal cancer resistance to CRT. This information could be used to select patients that may not benefit from a non-surgical treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2694.
With the increasingly prominent environmental and energy issues, emission regulations are becoming more stringent. Ammonia diesel dual fuel (ADDF) engine is one of the effective ways to reduce carbon emissions. This study investigated the effect of multiple injection strategy on the combustion and emission characteristics of liquid ammonia/diesel dual direct injection (DI) engines through numerical simulation. The results showed that under the condition of maintaining the same pre injection diesel fuel and high ammonia energy ratio (80%), with the introduction of multiple injection, the peak cylinder pressure decreased and the peak phase advanced, the combustion start angle (CA10) advanced, the heat release showed a multi-stage pattern. The times of injection (TSOI) has a significant effect on combustion and emissions. As TSOI increased, ignition delay decreased, the combustion duration is shortened, and the combustion is accelerated. Notably, overall emissions of NOx and N2O have decreased, but the emissions of unburned NH3 have increased. Optimized the state of ammonia injection (SOAI) timing and ammonia injection pressure (AIP), showed that advancing SOAI timing and increasing AIP improved combustion. Advanced the SOAI timing to −8 °CA ATDC, resulted in a significant NOx emissions decrease with an increase in TSOI, reaching over 50%. Although increasing injection pressure can improve combustion, it also results in higher N2O emissions.
Prompt learning was proposed to solve the problem of inconsistency between the upstream and downstream tasks and has achieved State-Of-The-Art (SOTA) results in various Natural Language Processing (NLP) tasks. However, Relation Extraction (RE) is more complex than other text classification tasks, which makes it more difficult to design a suitable prompt template for each dataset manually. To solve this issue, we propose a Adaptive Prompt Construction method (APC) for relation extraction. Our method entails obtaining context-aware prompt tokens by extracting and generating trigger words associated with the entities. Furthermore, to alleviate the issue of instability in the prompt-tuning framework during training, we introduce a novel joint contrastive loss to optimize our model. Our method not only effectively reduces the human effort used for prompt template construction, but also achieves better performance in RE. We conduct the experiment on four public RE datasets, which demonstrate the proposed method outperforms the existing SOTA results in both datasets and experimental settings.
The lithium-ion batteries of an electric vehicle belong to a high-voltage direct-current system. The high-voltage insulation performance of electric vehicles is very important for their safe operation. To solve the problems of slow response and the poor estimation accuracy of the insulation resistance under complex vehicle working conditions, a real-time insulation resistance detection method based on the variable forgetting factor least squares algorithm is proposed in this paper. Based on the low-frequency signal injection method and considering the influence of the Y capacitor, the corresponding circuit model and the mathematical model of the reflected wave voltage are established, and the mathematical model is linearized by a first-order Taylor expansion. By analyzing the influence of the forgetting factor on model parameter identification and setting appropriate shutdown criteria, the least squares algorithm with a variable forgetting factor is designed to quickly and accurately estimate the insulation resistance and Y capacitance. The experimental test results show that the proposed method can quickly track the changes in the insulation resistance and Y capacitance under the condition of noise interference and that the root mean square error of the estimation resistor is within 0.012.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
