Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy set...Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.展开更多
Surface 03 production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O3-NOx-VOC-sensitivity regimes complicates the control- decision making. In this paper, the indi...Surface 03 production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O3-NOx-VOC-sensitivity regimes complicates the control- decision making. In this paper, the indicator method was used to establish the relationship between 03 sensitivity and assessment indicators. Six popular ratios indicating ozone-precursor sensitivity, HCHO/NOy, H2O2/ HNO3, O3/NOy, O3/NOz, O3/HNO3, and H2O2/NOz, were evaluated based on the distribution of NOx- and VOC-sensitive regimes. WRF-Chem was used to study a serious ozone episode in fall over the Pearl River Delta （PRD）. It was found that the south-west of the PRD is characterized by a VOCsensitive regime, while its north-east is NO y-sensitive, with a sharp transition area between the two regimes. All indicators produced good representations of the elevated ozone hours in the episode on 6 November 2009, with H202/HNO3 being the best indicator. The threshold sensitivity levels for HCHO/NOy, H2O2/HNO3, O3/NOy, O3/NOz, O3/HNO3, and H2O2/NOz were estimated to be 0.41, 0.55, 10.2, 14.0, 19.1, and 0.38, respectively. Threshold intervals for the indicators H2O2/HNO3, O3/ NOy, O3/NOz, O3/HNO3, and H202/NOz were able to identify more than 95% of VOC- and NOx-sensitive grids. The ozone episode on 16 November 16 2008 was used to independently verify the results, and it was found that only H2O2/HNO3 and H2O2/NOz were able to differentiate the ozone sensitivity regime well. Hence, these two ratios are suggested as the most appropriate indicators for identifying fall ozone sensitivity in the PRD. Since the species used for indicators have seasonal variation, the utility of those indicators for other seasons should be investigated in the future work.展开更多
GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some...GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some cases.To solve this problem,this paper proposes a self-adaptive GM(1,1)model,termed as SAGM(1,1)model,which aims to solve the defects of the existing GM(1,1)model family by deleting their modeling hypothesis.Moreover,a novel multi-parameter simultaneous optimization scheme based on firefly algorithm is proposed,the proposed multi-parameter optimization scheme adopts machine learning ideas,takes all adjustable parameters of SAGM(1,1)model as input variables,and trains it with firefly algorithm.And Sobol’sensitivity indices are applied to study global sensitivity of SAGM(1,1)model parameters,which provides an important reference for model parameter calibration.Finally,forecasting capability of SAGM(1,1)model is illustrated by Anhui electricity consumption dataset.Results show that prediction accuracy of SAGM(1,1)model is significantly better than other models,and it is shown that the proposed approach enhances the prediction performance of GM(1,1)model significantly.展开更多
文摘Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.
基金Acknowledgements Financial supports from the Special Fund for Meteorological-scientific Research in the Public Interest of China （No. GYHY201406031）, National Science Foundation for Distinguished Young Scholars （No. 41425020）, National Key Technology Research and Development Program of the Ministry of Science and Technology of China （Grant No. 2014BAC21B02）, Foshan Environmental Protection Bureau Project （GDJAFS 2015046G） are gratefully acknowledged by the authors. We acknowledge Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund （the second phase） and National Supercomputing Center in Guangzhou （NSCC-GZ）. At the same time, we are grateful for Guangzhou Meteorological Service for the Meteorological data, and Guangzhou Environmental Monitoring for air quality observational data.
文摘Surface 03 production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O3-NOx-VOC-sensitivity regimes complicates the control- decision making. In this paper, the indicator method was used to establish the relationship between 03 sensitivity and assessment indicators. Six popular ratios indicating ozone-precursor sensitivity, HCHO/NOy, H2O2/ HNO3, O3/NOy, O3/NOz, O3/HNO3, and H2O2/NOz, were evaluated based on the distribution of NOx- and VOC-sensitive regimes. WRF-Chem was used to study a serious ozone episode in fall over the Pearl River Delta （PRD）. It was found that the south-west of the PRD is characterized by a VOCsensitive regime, while its north-east is NO y-sensitive, with a sharp transition area between the two regimes. All indicators produced good representations of the elevated ozone hours in the episode on 6 November 2009, with H202/HNO3 being the best indicator. The threshold sensitivity levels for HCHO/NOy, H2O2/HNO3, O3/NOy, O3/NOz, O3/HNO3, and H2O2/NOz were estimated to be 0.41, 0.55, 10.2, 14.0, 19.1, and 0.38, respectively. Threshold intervals for the indicators H2O2/HNO3, O3/ NOy, O3/NOz, O3/HNO3, and H202/NOz were able to identify more than 95% of VOC- and NOx-sensitive grids. The ozone episode on 16 November 16 2008 was used to independently verify the results, and it was found that only H2O2/HNO3 and H2O2/NOz were able to differentiate the ozone sensitivity regime well. Hence, these two ratios are suggested as the most appropriate indicators for identifying fall ozone sensitivity in the PRD. Since the species used for indicators have seasonal variation, the utility of those indicators for other seasons should be investigated in the future work.
基金supported by the National Natural Science Foundation of China(72171116,71671090)the Fundamental Research Funds for the Central Universities(NP2020022)+1 种基金the Key Research Projects of Humanities and Social Sciences in Anhui Education Department(SK2021A1018)Qinglan Project for Excellent Youth or Middlea ged Academic Leaders in Jiangsu Province,China.
文摘GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some cases.To solve this problem,this paper proposes a self-adaptive GM(1,1)model,termed as SAGM(1,1)model,which aims to solve the defects of the existing GM(1,1)model family by deleting their modeling hypothesis.Moreover,a novel multi-parameter simultaneous optimization scheme based on firefly algorithm is proposed,the proposed multi-parameter optimization scheme adopts machine learning ideas,takes all adjustable parameters of SAGM(1,1)model as input variables,and trains it with firefly algorithm.And Sobol’sensitivity indices are applied to study global sensitivity of SAGM(1,1)model parameters,which provides an important reference for model parameter calibration.Finally,forecasting capability of SAGM(1,1)model is illustrated by Anhui electricity consumption dataset.Results show that prediction accuracy of SAGM(1,1)model is significantly better than other models,and it is shown that the proposed approach enhances the prediction performance of GM(1,1)model significantly.
